From 0fb1da835176d7108502be1c2ce50f8b8d9c50f1 Mon Sep 17 00:00:00 2001
From: Quarto GHA Workflow Runner <quarto-github-actions-publish@example.com>
Date: Wed, 6 Mar 2024 02:59:31 +0000
Subject: [PATCH] Built site for gh-pages

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diff --git a/.nojekyll b/.nojekyll
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@@ -1,71 +0,0 @@
-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">2020: A year in review</h1><p class="page-description">Highlights from the Policy Simulation Library in 2020.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2020-12-23T00:00:00-06:00" itemprop="datePublished">
-        Dec 23, 2020
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      2 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#psl">psl</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#psl-foundation">psl-foundation</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul><p><img src="https://pslmodels.org/imgs/PSL.svg" alt=""></p>
-
-<hr>
-
-<p>This year has been one to forget!
-But 2020 did have its bright spots, especially in the PSL community.
-This post reviews some of the highlights from the year.</p>
-
-<p>The Library was able to welcome two new models to the catalog in 2020: <a href="https://github.com/PSLmodels/microdf">microdf</a> and <a href="https://github.com/PSLmodels/openfisca-uk">OpenFisca-UK</a>.
-microdf provides a number of useful tools for use with economic survey data.
-OpenFisca-UK builds off the <a href="https://openfisca.org/en/">OpenFisca</a> platform, offering a microsimulation model for tax and benefit programs in the UK.</p>
-
-<p>In addition, four new models were added to the Library as incubating projects.  The <a href="https://github.com/PSLmodels/ui_calculator">ui-calculator</a> model has received a lot of attention this year in the U.S., as it provides the capability to calculate unemployment insurance benefits across U.S. states, a major mode of delivering financial relief to individuals during the COVID crisis. 
-<a href="https://github.com/PSLmodels/PCI-Outbreak">PCI-Outbreak</a> directly relates to the COVID crisis, using machine learning and natural language processing to estimate the true extent of the COVID pandemic in China.
-The model finds that actual COVID cases are significantly higher than what official statistics claim.
-The <a href="https://github.com/PSLmodels/COVID-MCS">COVID-MCS</a> model considers COVID case counts and test positivity rates to measure whether or not U.S. communities are meeting certain benchmarks in controlling the spread of the disease.
-On a lighter note, the <a href="https://github.com/PSLmodels/Git-Tutorial">Git-Tutorial</a> project provides instruction and resources for learning to use Git and GitHub, with an emphasis on the workflow used by many projects in the PSL community.</p>
-
-<p>The organization surrounding the Policy Simulation Library has been bolstered in two ways.
-First, we have formed a relationship with the <a href="https://opencollective.com/psl">Open Collective Foundation</a>, who is now our fiscal host.
-This allows PSL to accept tax deductible contributions that will support the efforts of the community.  Second, we’ve formed the PSL Foundation, with an initial board that includes <a href="https://associates.bloomberg.org/team/linda-gibbs/">Linda Gibbs</a>, <a href="https://glennhubbard.net">Glenn Hubbard</a>, and <a href="http://jasondebacker.com">Jason DeBacker</a>.</p>
-
-<p>Our outreach efforts have grown in 2020 to include the regular PSL Demo Day series and this PSL Blog.
-Community members have also presented work with PSL models at the <a href="https://glennhubbard.net">PyData Global Conference</a>, the Tax Economists Forum, <a href="https://www.youtube.com/watch?time_continue=7&amp;v=mRCcJ-pD7R0&amp;feature=emb_logo">AEI</a>, the <a href="https://coiled.io/live-stream/scaling-open-source-policy-models-biden-plan-science-thursdays/">Coiled Podcast</a>, and the <a href="https://www.virtualglobalvillage.com/blog/meet-jason-debacker">Virtual Global Village Podcast</a>.
-New users will also find a better experience learning how to use and contribute to PSL models as many PSL models have improved their documentation through the use of <a href="https://jupyterbook.org/intro.html">Jupyter Book</a> (e.g., see the <a href="https://pslmodels.github.io/Tax-Calculator/">Tax-Calculator documentation</a>).</p>
-
-<p>We love seeing the community around open source policymaking expand and are proud that PSL models have been used for important policy analysis in 2020, including analyzing <a href="https://medium.com/@ernietedeschi/updated-distribution-of-household-rebate-ideas-so-far-f46360034f9d">economic policy responses to the pandemic</a> and the <a href="https://www.aei.org/research-products/report/an-analysis-of-joe-bidens-tax-proposals/">platforms of presidential candidates</a>.
-We look forward to more progress in 2021 and welcome you to join the effort as a contributor, <a href="https://opencollective.com/psl">financially</a> or <a href="https://pslmodels.org/Community/contribute.html">as an open source developer</a>.</p>
-
-<p>Best wishes from PSL for a happy and healthy new year!</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://twitter.com/PSLmodels">PSL Twitter Feed</a></li>
-  <li><a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">PSL YouTube</a></li>
-  <li><a href="https://opencollective.com/psl">PSL on Open Collective</a></li>
-</ul>
-
-  </div><a class="u-url" href="/2020-year-in-review" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">2021: A year in review</h1><p class="page-description">Highlights from the Policy Simulation Library in 2021.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-12-28T00:00:00-06:00" itemprop="datePublished">
-        Dec 28, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      2 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#psl">psl</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#psl-foundation">psl-foundation</a>
-        
-      
-      </p>
-    
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-    </header>
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-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul><p><img src="https://pslmodels.org/imgs/PSL.svg" alt=""></p>
-
-<hr>
-
-<p>As 2021 winds down, I wanted to take a few minutes to reflect on the Policy Simulation Library’s efforts over the past year.
-With an amazing community of contributors, supporters, and users, PSL has been able to make a real impact in 2021.</p>
-
-<p>The library saw two new projects achieve “cataloged” status: Tax Foundation’s <a href="https://github.com/TaxFoundation/capital-cost-recovery">Capital Cost Recovery model</a> and the Federal Reserve Bank of New York’s <a href="https://github.com/FRBNY-DSGE/DSGE.jl">DSGE.jl model</a>.
-Both models satisfy all the the <a href="http://pslmodels.org/Catalog/library_criteria.html">PSL criteria</a> for transparency and reproducibility.
-Both are also written entirely in open source software: the Capital Cost Recovery model is in R and the DSGE model in Julia.</p>
-
-<p>An exciting new project to join the Library this year is <a href="https://policyengine.org/uk/policy">PolicyEngine</a>.
-PolicyEngine is building open source tax and benefit mircosimulation models and very user-friendly interfaces to these models.
-The goal of this project is to take policy analysis to the masses through intuitive web and mobile interfaces for policy models.
-The UK version of the PolicyEngine app has already seen use from politicians interested in reforming the tax and benefit system in the UK.</p>
-
-<p>Another excellent new addition to the library is the <a href="https://github.com/PSLmodels/Federal-State-Tax">Federal-State Tax Project</a>.
-This project provides data imputation tools to allow for state tax data that are representative of each state as well as federal totals.
-These datasets can then be used in microsimulation models, such as <a href="https://taxcalc.pslmodels.org">Tax-Calculator</a> to study the impact of federal tax laws across the states.
-Matt Jensen and Don Boyd have published several pieces with these tools, including in <a href="https://www.taxnotes.com/special-reports/tax-cuts-and-jobs-act/repealing-salt-cap-state-state-impacts/2021/10/21/7bbv3"><em>State Tax Notes</em></a></p>
-
-<p><a href="https://psl-foundation.org">PSL Foundation</a> became an official business entity in 2021.
-While still awaiting a letter of determination for 501(c)(3) status from the IRS, PSL Foundation was able to raise more than $25,000 in the last few months of 2021 to support open source policy analysis!</p>
-
-<p>PSL community members continued to interact several times each week in our public calls.
-The <a href="https://pslmodels.org/shop#!/">PSL Shop</a> was launched in 2021 so that anyone can get themselves some PSL swag (with some of each purchase going back to the PSL Foundation to support the Library).
-In addition, PSL hosted 20 <a href="http://blog.pslmodels.org/categories/#demo-days">Demo Day presentations</a> from 11 different presenters!
-These short talks covered everything from new projects to interesting applications of some of the first projects to join the Library, as well as general open source tools.</p>
-
-<p>As in past years, PSL cataloged and incubating models were found to be of great use in current policy debates.
-Whether it was the <a href="https://www.openrg.com/reports/QN_ARPA_Distribution.pdf">ARPA</a>, <a href="https://www.jainfamilyinstitute.org/assets/full-refundability-of-child-tax-credit-without-expansion.pdf">Biden administration proposals to expand the CTC</a>, or <a href="https://blog.ubicenter.org/20210403/california-ab65-calubi.html">California’s Basic Income Bill</a>, the accessibility and ability to reproduce results from these open source projects has made them a boon to policy analysts.</p>
-
-<p>We are looking forward to a great 2022!
-We expect the Library to continue to grow, foresee many interesting and helpful Demo Days, and are planning a DC PSL Workshop for March 2022.
-We hope to see you around these or other events!</p>
-
-<p>Best wishes from PSL for a happy and healthy New Year!</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://psl-foundation.org">PSL Foundation</a></li>
-  <li><a href="https://twitter.com/PSLmodels">PSL Twitter Feed</a></li>
-  <li><a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">PSL YouTube channel</a></li>
-  <li><a href="https://opencollective.com/psl">PSL on Open Collective</a></li>
-</ul>
-
-  </div><a class="u-url" href="/2021-year-in-review" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">2022: A year in review</h1><p class="page-description">Highlights from the Policy Simulation Library in 2022.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2022-12-31T00:00:00-06:00" itemprop="datePublished">
-        Dec 31, 2022
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      2 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#psl">psl</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#psl-foundation">psl-foundation</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul><p><img src="https://pslmodels.org/imgs/PSL.svg" alt=""></p>
-
-<hr>
-
-<p>This has been another successful year for the Policy Simulation Library, whose great community of contributors continue to make innovative advances in open source policy analysis, and for the PSL Foundation, which supports the Library and its community.
-We are so thankful for all those who have made financial or technical contributions to the PSL this year!
-In this blog post, I want to take this time at the end of the year to reflect on a few of the highlights from 2022.</p>
-
-<p><a href="https://policyengine.org">PolicyEngine</a>, a PSL Foundation fiscally-sponsored project, launched <a href="https://policyengine.org/us/policy">PolicyEngine US</a> in April and has since seen many use cases of the model (check out the PolicyEngine year-in-review <a href="https://blog.policyengine.org/policyengine-2022-year-in-review-35984ec3917c">here</a>).
-PolicyEngine had begun by leveraging the <a href="https://openfisca.org/en/">OpenFisca</a> platform, but has transitioned to their own-maintained <a href="https://policyengine.github.io/policyengine-core/intro.html">PolicyEngine Core</a>.
-PolicyEngine Core and their related projects (such as <a href="https://policyengine.org/us/policy">PolicyEngine US</a> and <a href="https://policyengine.org/uk">PolicyEngine UK</a>) already meet all the <a href="http://pslmodels.org/Catalog/library_criteria.html">criteria</a> set forth by the Policy Simulation Library.
-Keep an eye out for lots more excellent tax and benefit policy analysis tools from PolicyEngine in 2023 and beyond!</p>
-
-<p>PSL Foundation has partnered with <a href="https://quantecon.org">QuantEcon</a>, acting as a fiscal sponsor for their projects that provide training and training materials for economic modeling and econometrics using open source tools.
-QuantEcon ran a massive open online class in India that had more than 1000 registrants in summer of 2022.
-They also ran an online course for over 100 students from universities in Africa in 2022.
-Further, with the funding received through their partnership with PSL Foundation, QuantEcon will continue these efforts in 2023 with a planned, in-person course in India.</p>
-
-<p>PSL hosted its first in-person workshop in March.
-The workshop focused on open source tools for tax policy analysis including <a href="https://github.com/PSLmodels/Tax-Calculator/">Tax-Calculator</a>, <a href="https://github.com/PSLmodels/Cost-of-Capital-Calculator/">Cost-of-Capital-Calculator</a>, <a href="https://github.com/PSLmodels/OG-USA">OG-USA</a>, and <a href="https://policyengine.org/us/policy">PolicyEngine US</a>.
-The PSL event was, appropriately enough, hosted at the MLK Memorial Library in DC.
-We filled the space with 30 attendees from think tanks, consultancies, and government agencies.
-The workshop was a great success and we look forward to hosting more in-person workshops in the future.</p>
-
-<p>PSL’s bi-weekly Demo Day series continued throughout 2022, with 13 Demo Days this year.
-In these, we saw a wide array of presenters from institutions such as the Federal Reserve Bank of Atlanta, PolicyEngine, Tax Foundation, National Center for Children in Poverty, IZA Institute of Labor Economics, Channels, the University of South Carolina, the Center for Growth and Opportunity, and the American Enterprise Institute.
-You can go back and rewatch any of these presentations on <a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">YouTube</a>.</p>
-
-<p>It’s been a fantastic year and we expect even more from the community and PSL Foundation in 2023.
-PSL community members continue to interact several times each week on our public calls.
-Check out the <a href="http://pslmodels.org/events">events page</a> and join us in the New Year!</p>
-
-<p>From all of us at the PSL, best wishes for a happy and healthy New Year!</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://psl-foundation.org">PSL Foundation</a></li>
-  <li><a href="https://twitter.com/PSLmodels">PSL Twitter Feed</a></li>
-  <li><a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">PSL YouTube channel</a></li>
-  <li><a href="https://opencollective.com/psl">PSL on Open Collective</a></li>
-  <li>
-<a href="https://pslmodels.org/shop#!/">PSL Shop</a> for PSL branded merchandise</li>
-</ul>
-
-  </div><a class="u-url" href="/2022-year-in-review" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">2023: A year in review</h1>
-<p class="page-description">Highlights from the Policy Simulation Library in 2023.</p>
-<p class="post-meta post-meta-title"><time class="dt-published" datetime="2023-12-28T00:00:00-06:00" itemprop="datePublished">
-        Dec 28, 2023
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      3 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i> 
-      
-        <a class="category-tags-link" href="/categories/#psl">psl</a>
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-</ul>
-<p><img src="https://pslmodels.org/imgs/PSL.svg" alt=""></p>
-
-<hr>
-
-<p>While there haven’t been any blog posts in 2023 <img class="emoji" title=":wink:" alt=":wink:" src="https://github.githubassets.com/images/icons/emoji/unicode/1f609.png" height="20" width="20">, it has been a productive year for the Policy Simulation Library (PSL) community and PSL Foundation!</p>
-
-<p>We’ve continued to serve our mission through education and outreach efforts.
-We hosted 13 Demo Days in 2023, including presentations from individuals at the Congressional Budget Office, Allegheny County, NOAA, Johns Hopkins, QuantEcon, the City of New York, and other institutions.
-Archived videos of the Demo Days are available on our <a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">YouTube Channel</a>.</p>
-
-<p>In addition, we hosted an in person workshop at the National Tax Association’s annual conference in November.
-This event featured the <a href="https://policyengine.org">PolicyEngine-US</a> project and was lead by Max Ghenis and Nikhil Woodruff, co-founders of PolicyEngine.
-Attendees included individuals from the local area (Denver) and conference attendees, who represented academia, government, and think tanks.
-Max and Nikhil provided an overview of PolicyEngine and then walked attendees through a hands-on exercise using the PolicyEngine US tool, having them write code to generate custom plots in a Google Colab notebook.
-It was a lot of fun – and the pizza was decent too!</p>
-
-<p>Speaking of <a href="https://policyengine.org">PolicyEngine</a>, this fiscally-sponsored project of PSL Foundation had a banner year in terms of fundraising and development.
-The group received several grants in 2023 and closed out the year with a large grant from Arnold Ventures.
-They also wrote an NSF grant proposal which they are waiting to hear back from.
-The group added an experienced nonprofit executive, <a href="https://www.linkedin.com/in/leigh-gibson-2a260a8/">Leigh Gibson</a>, to their team.
-Leigh provides support with fundraising and operations, and she’s been instrumental in these efforts.
-In terms of software development, the PolicyEngine team has been able to greatly leverage volunteers (more than 60!) with <a href="https://www.linkedin.com/in/pavel-makarchuk-170989203/">Pavel Makarchuk</a> coming on as Policy Modeling Manager to help coordinate these efforts.
-With their community, PolicyEngine has codified numerous US state tax and benefit policies and has developed a robust method to create synthetic data for use in policy analysis.
-Be on the lookout for a lot more from them in 2024.</p>
-
-<p><a href="https://quantecon.org">QuantEcon</a>, another fiscally sponsored project, has also made tremendous contributions to open source economics in 2023.
-Most importantly, they ran a very successful summer school in West Africa.
-In addition, they have continued make key contributions to software tools useful for teaching and training economics tools.
-These include Jupyteach, which <a href="https://youtu.be/mJWeY94uKUI?si=-mvv8sbKMbPSwMwH">Spencer Lyon shared in our Demo Day series</a>.
-With their online materials, textbooks, and workshops around the world, QuantEcon is shaping how researchers and policy analysts employ economic tools to solve real-world problems.</p>
-
-<p>PSL Foundation added a third fiscally sponsored project, <a href="https://youtu.be/mJWeY94uKUI?si=-mvv8sbKMbPSwMwH">Policy Change Index</a> (PCI) in 2023.
-PCI was founded by <a href="https://www.weifengzhong.com">Weifeng Zhong</a>, a Senior Research Fellow at the Mercatus Center at George Mason University, and uses natural language processing and machine learning to predict changes in policy among autocratic regimes.
-PCI has had a very successful start with <a href="https://policychangeindex.org/overview-PCI-China.html">PCI-China</a>, predicting policy changes in China, and <a href="https://policychangeindex.org/overview-PCI-Outbreak.html">PCI-Outbreak</a>, predicting the extent of true COVID-19 case counts in China during the pandemic.
-Currently, they are extending their work to include predictive indices for Russia, North Korea, and Iran.
-PSL-F is excited for the opportunity to help support this important work.</p>
-
-<p>Other cataloged projects have continued to be widely used in 2023.
-To note a few of these use cases, the United Nations has partnered with Richard Evans and Jason DeBacker, maintainers of <a href="https://pslmodels.github.io/OG-Core/content/intro/intro.html">OG-Core</a>, to help bring the modeling platform to developing countries they are assisting.
-Tax Foundation’s <a href="https://github.com/TaxFoundation/capital-cost-recovery">Capital Cost Recovery</a> model has been updated to 2023 and used in their widely cited <a href="https://taxfoundation.org/research/all/global/2023-international-tax-competitiveness-index/#:~:text=The%20International%20Tax%20Competitiveness%20Index%20(ITCI)%20seeks%20to%20measure%20the,world%2C%20capital%20is%20highly%20mobile.">2023 Tax Competitiveness Index</a>.
-And the <a href="taxcalc.pslmodels.org">Tax-Calculator</a> and <a href="https://github.com/PSLmodels/taxdata">TaxData</a> projects both continue to used by think tanks and researchers.</p>
-
-<p>As 2023 comes to a close, we look forward to 2024.
-We’ll be launching a new <a href="https://pslmodels.org">PSLmodels.org</a> website soon.
-And there’ll be many more <a href="http://pslmodels.org/events">events</a> – we hope you join in.</p>
-
-<p>From all of us at the PSL, best wishes for a happy and healthy New Year!</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://pslmodels.org">PSL Models</a></li>
-  <li><a href="https://psl-foundation.org">PSL Foundation</a></li>
-  <li><a href="https://twitter.com/PSLmodels">PSL Twitter Feed</a></li>
-  <li><a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">PSL YouTube channel</a></li>
-  <li><a href="https://opencollective.com/psl">PSL on Open Collective</a></li>
-  <li>
-<a href="https://pslmodels.org/shop#!/">PSL Shop</a> for PSL branded merchandise</li>
-</ul>
-
-  </div>
-<a class="u-url" href="/2023-year-in-review" hidden></a>
-</article>
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-    <h1 class="post-title p-name" itemprop="name headline">Policy Simulation Library DC Workshop: Open source tools for analyzing tax policy</h1><p class="page-description">Washington, DC open-source modeling workshop, March 25, 2022, 8:30am-1:00pm, Martin Luther King, Jr. Memorial Library.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2022-03-03T00:00:00-06:00" itemprop="datePublished">
-        Mar 3, 2022
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#PSL">PSL</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#PSL-Foundation">PSL-Foundation</a>
-        &nbsp;
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-        <a class="category-tags-link" href="/categories/#Workshop">Workshop</a>
-        
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-    
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-  <div class="post-content e-content" itemprop="articleBody">
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-<hr>
-
-<p>The <a href="https://pslmodels.org/">Policy Simulation Library</a> is hosting a workshop in Washington, DC on March 25 on open source tools for the analysis of tax policy. Participants will learn how to use open source models from the Library for revenue estimation, distributional analysis, and to simulate economic impacts of tax policy. The workshop is intended to be a hands-on experience and participants can expect to leave with the required software, documentation, and knowledge to continue using these tools. All models in the workshop are written in the Python programming language–familiarity with the language is helpful, but not required.</p>
-
-<p><strong>Workshop Schedule:</strong></p>
-<ul>
-  <li>
-<strong>8:15-8:45a:</strong> Breakfast</li>
-  <li>
-<strong>8:45-9:00a:</strong> Introduction</li>
-  <li>
-<strong>9:00-9:50a:</strong> Using <a href="https://taxcalc.pslmodels.org/"><strong>Tax-Calculator</strong></a> for revenue estimation and distributional analysis (<a href="https://www.aei.org/profile/matthew-h-jensen/">Matt Jensen</a>)</li>
-  <li>
-<strong>10:00-10:50a:</strong> Estimating effective tax rates on investment with <a href="https://ccc.pslmodels.org/"><strong>Cost-of-Capital-Calculator</strong></a> (<a href="https://jasondebacker.com/">Jason DeBacker</a>)</li>
-  <li>
-<strong>11:00-11:50a:</strong> Macroeconomic modeling of fiscal policy with <a href="https://pslmodels.github.io/OG-Core/"><strong>OG-Core</strong></a> and <a href="https://pslmodels.github.io/OG-USA/"><strong>OG-USA</strong></a> (<a href="https://sites.google.com/site/rickecon">Richard W. Evans</a>)</li>
-  <li>
-<strong>noon-1:00p:</strong> Lunch and demonstration of <a href="https://policyengine.org/"><strong>PolicyEngine</strong></a> (<a href="https://www.ubicenter.org/author/max/">Max Ghenis</a>)</li>
-</ul>
-
-<p>The workshop will be held at the Martin Luther King Jr. Memorial Library in Washington, DC. Participants are expected to arrive by 8:30am and the program will conclude at 1:00pm. Breakfast and lunch will be provided. <a href="https://psl-foundation.org/">PSL Foundation</a> is sponsoring the event and there is no cost to attend. Attendance is limited to 30 in order to make this a dynamic and interactive workshop.</p>
-
-<p>To register, please use <a href="https://docs.google.com/forms/d/e/1FAIpQLSewWIdF7r7BIEPRDjq_AWE6yJMx9fHwIxCwyg58D52lNMFqiA/viewform">this Google Form</a>. Registration will close March 11. Participants will be expected to bring a laptop to the workshop where they can interact with the software in real time with the instructors. Registered participants will receive an email before the event with a list of software to install before the workshop.</p>
-
-<p>Please feel free to share this invitation with your colleagues.</p>
-
-<p>Questions about the workshop can be directed to Jason DeBacker at <a href="mailto:jason.debacker@gmail.com">jason.debacker@gmail.com</a>.</p>
-
-  </div><a class="u-url" href="/DC-workshop" hidden></a>
-</article>
\ No newline at end of file
diff --git a/LICENSE b/LICENSE
deleted file mode 100755
index 5c1d0d4..0000000
--- a/LICENSE
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@@ -1,201 +0,0 @@
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diff --git a/PSL/PSL-Foundation/Workshop/2022/03/03/DC-workshop/index.html b/PSL/PSL-Foundation/Workshop/2022/03/03/DC-workshop/index.html
new file mode 100644
index 0000000..2ccdd0e
--- /dev/null
+++ b/PSL/PSL-Foundation/Workshop/2022/03/03/DC-workshop/index.html
@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../posts/2022-03-03-DC-workshop.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/README.md b/README.md
deleted file mode 100755
index c51bef5..0000000
--- a/README.md
+++ /dev/null
@@ -1,58 +0,0 @@
-[//]: # (This template replaces README.md when someone creates a new repo with the fastpages template.)
-
-![](https://github.com/PSLmodels/blog/workflows/CI/badge.svg) 
-![](https://github.com/PSLmodels/blog/workflows/GH-Pages%20Status/badge.svg) 
-[![](https://img.shields.io/static/v1?label=fastai&message=fastpages&color=57aeac&labelColor=black&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABkAAAAjCAYAAABhCKGoAAAGMklEQVR42q1Xa0xTVxyfKExlui9blszoB12yDzPGzJhtyT5s+zBxUxELBQSHm2ZzU5epBF/LclXae29pCxR5VEGgLQUuIOKDuClhm8oUK7S9ve19tLTl/fA5p9MNc/Y/hRYEzGLxJL/87zk9Ob/zf5++NGHMALzYgdDYmWh0Qly3Lybtwi6lXdpN2cWN5A0+hrQKe5R2PoN2uD+OKcn/UF5ZsVduMmyXVRi+jzebdmI5/juhwrgj3mTI2GA0vvsUIcMwM7GkOD42t7Mf6bqHkFry2yk7X5PXcxMVDN5DGtFf9NkJfe6W5iaUyFShjfV1KPlk7VPAa0k11WjzL+eRvMJ4IKQO0dw8SydJL+Op0u5cn+3tQTn+fqTivTbQpiavF0iG7iGt6NevKjpKpTbUo3hj+QO47XB8hfHfIGAelA+T6mqQzFi+e0oTKm3iexQnXaU56ZrK5SlVsq70LMF7TuX0XNTyvi1rThzLST3TgOCgxwD0DPwDGoE07QkcSl/m5ynbHWmZVm6b0sp9o2DZN8aTZtqk9w9b2G2HLbbvsjlx+fry0vwU0OS5SH68Ylmilny3c3x9SOvpRuQN7hO8vqulZQ6WJMuXFAzcRfkDd5BG8B1bpc+nU0+fQtgkYLIngOEJwGt/J9UxCIJg1whJ05Ul4IMejbsLqUUfOjJKQnCDr4ySHMeO1/UMIa3UmR9TUpj7ZdMFJK8yo6RaZjLAF/JqM/rifCO+yP4AycGmlgUaT9cZ0OYP2um5prjBLhtvLhy68Fs7RFqbRvSlf15ybGdyLcPJmcpfIcIuT4nqqt+Sa2vaZaby1FB+JGi1c9INhuiv9fpIysItIh3CVgVAzXfEE1evzse/bwr8bolcAXs+zcqKXksQc5+FD2D/svT06I8IYtaUeZLZzsVm+3oRDmON1Ok/2NKyIJSs0xnj84RknXG6zgGEE1It+rsPtrYuDOxBKAJLrO1qnW7+OpqeNxF4HWv6v4Rql3uFRvL/DATnc/29x4lmy2t4fXVjY+ASGwylm8DBvkSm2gpgx1Bpg4hyyysqVoUuFRw0z8+jXe40yiFsp1lpC9navlJpE9JIh7RVwfJywmKZO4Hkh02NZ1FilfkJLi1B4GhLPduAZGazHO9LGDX/WAj7+npzwUQqvuOBoo1Va91dj3Tdgyinc0Dae+HyIrxvc2npbCxlxrJvcW3CeSKDMhKCoexRYnUlSqg0xU0iIS5dXwzm6c/x9iKKEx8q2lkV5RARJCcm9We2sgsZhGZmgMYjJOU7UhpOIqhRwwlmEwrBZHgCBRKkKX4ySVvbmzQnXoSDHWCyS6SV20Ha+VaSFTiSE8/ttVheDe4NarLxVB1kdE0fYAgjGaOWGYD1vxKrqmInkSBchRkmiuC4KILhonAo4+9gWVHYnElQMEsAxbRDSHtp7dq5CRWly2VlZe/EFRcvDcBQvBTPZeXly1JMpvlThzBBRASBoDsSBIpgOBQV6C+sUJzffwflQX8BTevCTZMZeoslUo9QJJZYTZDw3RuIKtIhlhXdfhDoJ7TTXY/XdBBpgUshwFMSRYTVwim7FJvt6aFyOnoVKqc7MZQDzzNwsmnd3UegCudl8R2qzHZ7bJbQoYGyn692+zMULCfXenoOacTOTBUnJYRFsq+5+a3sjp5BXM6hEz7ObHNoVEIHyocekiX6WIiykwWDd1HhzT8RzY2YqxnK0HNQBJtW500ddiwrDgdIeCABZ4MPnKQdk9xDhUP3wfHSqbBI9v/e9jo0Iy30cCOgAMyVgMMVCMwql/cQxfKp2R1dWWrRm0PzUkrIXC9ykDY+hnJ5DqkE709guriwSRgGzWTQCPABWJZ6vbNHQlgo099+CCEMPnF6xnwynYETEWd8ls0WPUpSWnTrfuAhAWacPslUiQRNLBGXFSA7TrL8V3gNhesTnLFY0jb+bYWVp0i7SClY184jVtcayi7so2yuA0r4npbjsV8CJHZhPQ7no323cJ5w8FqpLwR/YJNRnHs0hNGs6ZFw/Lpsb+9oj/dZSbuL0XUNojx4d9Gch5mOT0ImINsdKyHzT9Muz1lcXhRWbo9a8J3B72H8Lg6+bKb1hyWMPeERBXMGRxEBCM7Ddfh/1jDuWhb5+QkAAAAASUVORK5CYII=)](https://github.com/fastai/fastpages)
-
-
-# [PSL blog](https://blog.pslmodels.org)
-
-
-_powered by [fastpages](https://github.com/fastai/fastpages)_
-
-
-## How to contribute
-
-The `PSL blog` accepts posts as Jupyter notebooks or Markdown documents:
-
-* To submit a Jupyter post, create a PR with your `YYYY-MM-DD-post-title.ipynb` file in the `_notebooks` folder.
-* To submit a Markdown post, create a PR with your `YYYY-MM-DD-post-title.md` file in the `_posts` folder.
-
-In both cases, please take the following steps:
-1. Follow the Fastpages guides on writing blogs with [Jupyter](https://github.com/fastai/fastpages#writing-blog-posts-with-jupyter) and [Markdown](https://github.com/fastai/fastpages#writing-blog-posts-with-markdown), and include the required "front matter" with metadata.
-2. [Preview the blog locally](_fastpages_docs/DEVELOPMENT.md) using the `make server` command from the root directory after drafting your post.
-You'll need [Docker](https://docs.docker.com/get-docker/) installed on your machine to run the command.
-3. Include a screenshot of the blog post in your PR.
-
-Please use the [nbdev & blogging channel](https://forums.fast.ai/c/fastai-users/nbdev/48) in the fastai forums for any questions or feature requests.
-
-## Technical guide
-
-* Make URLs concise but descriptive of the post.
-* Use lowercase and dashes for all tags.
-* Make each new sentence its own line (for easier code review).
-
-## Post formats
-
-Please follow the below guidance for each post type.
-
-### Demo Days recaps
-
-* Tag the post as `demo-days`.
-* Title the post `Demo Day: {title}`.
-* Show the video at the top of the post.
-* Describe the motivation for the demo and what you demonstrated.
-* Link materials shown in the demo, including code and/or Compute Studio simulations.
-
-See [PR #10](https://github.com/PSLmodels/blog/pull/10) as an example.
-
-## Style guide
-
-* Focus on PSL software and models; reserve policy analysis for think tank and op-ed reports.
-* Write with a neutral tone.
-* Favor active over passive voice.
-* Capitalize post titles.
-* Favor `Mmm DD`, `Mmm DD, YYYY`, or `YYYY-MM-DD` date formats over `MM/DD` and `MM/DD/YYYY`, which can be misinterpreted outside the US.
-* Avoid "click here" links; for better [accessibility](https://webaccess.berkeley.edu/resources/tips/web-accessibility#accessible-links) and [SEO](https://www.lamar.edu/web-communication/resources/avoid-using-click-here.html), provide descriptive links.
-
-*Questions? Contact Max Ghenis (mghenis@gmail.com).*
diff --git a/about.html b/about.html
new file mode 100644
index 0000000..a91c295
--- /dev/null
+++ b/about.html
@@ -0,0 +1,555 @@
+<!DOCTYPE html>
+<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"><head>
+
+<meta charset="utf-8">
+<meta name="generator" content="quarto-1.4.551">
+
+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
+
+
+<title>Policy Simulation Library Blog - PSL Blog</title>
+<style>
+code{white-space: pre-wrap;}
+span.smallcaps{font-variant: small-caps;}
+div.columns{display: flex; gap: min(4vw, 1.5em);}
+div.column{flex: auto; overflow-x: auto;}
+div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
+ul.task-list{list-style: none;}
+ul.task-list li input[type="checkbox"] {
+  width: 0.8em;
+  margin: 0 0.8em 0.2em -1em; /* quarto-specific, see https://github.com/quarto-dev/quarto-cli/issues/4556 */ 
+  vertical-align: middle;
+}
+</style>
+
+
+<script src="site_libs/quarto-nav/quarto-nav.js"></script>
+<script src="site_libs/quarto-nav/headroom.min.js"></script>
+<script src="site_libs/clipboard/clipboard.min.js"></script>
+<script src="site_libs/quarto-search/autocomplete.umd.js"></script>
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+<meta name="quarto:offset" content="./">
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+<script src="site_libs/quarto-html/popper.min.js"></script>
+<script src="site_libs/quarto-html/tippy.umd.min.js"></script>
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+<link href="site_libs/bootstrap/bootstrap-icons.css" rel="stylesheet">
+<link href="site_libs/bootstrap/bootstrap.min.css" rel="stylesheet" id="quarto-bootstrap" data-mode="light">
+<script id="quarto-search-options" type="application/json">{
+  "location": "navbar",
+  "copy-button": false,
+  "collapse-after": 3,
+  "panel-placement": "end",
+  "type": "overlay",
+  "limit": 50,
+  "keyboard-shortcut": [
+    "f",
+    "/",
+    "s"
+  ],
+  "show-item-context": false,
+  "language": {
+    "search-no-results-text": "No results",
+    "search-matching-documents-text": "matching documents",
+    "search-copy-link-title": "Copy link to search",
+    "search-hide-matches-text": "Hide additional matches",
+    "search-more-match-text": "more match in this document",
+    "search-more-matches-text": "more matches in this document",
+    "search-clear-button-title": "Clear",
+    "search-text-placeholder": "",
+    "search-detached-cancel-button-title": "Cancel",
+    "search-submit-button-title": "Submit",
+    "search-label": "Search"
+  }
+}</script>
+
+
+<link rel="stylesheet" href="styles.css">
+</head>
+
+<body class="nav-fixed fullcontent">
+
+<div id="quarto-search-results"></div>
+  <header id="quarto-header" class="headroom fixed-top">
+    <nav class="navbar navbar-expand-lg " data-bs-theme="dark">
+      <div class="navbar-container container-fluid">
+      <div class="navbar-brand-container mx-auto">
+    <a class="navbar-brand" href="./index.html">
+    <span class="navbar-title">Policy Simulation Library Blog</span>
+    </a>
+  </div>
+            <div id="quarto-search" class="" title="Search"></div>
+          <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarCollapse" aria-controls="navbarCollapse" aria-expanded="false" aria-label="Toggle navigation" onclick="if (window.quartoToggleHeadroom) { window.quartoToggleHeadroom(); }">
+  <span class="navbar-toggler-icon"></span>
+</button>
+          <div class="collapse navbar-collapse" id="navbarCollapse">
+            <ul class="navbar-nav navbar-nav-scroll ms-auto">
+  <li class="nav-item">
+    <a class="nav-link active" href="./about.html" aria-current="page"> 
+<span class="menu-text">PSL Blog</span></a>
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+  <li class="nav-item compact">
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-@media screen and (max-width: 1000px) { table { display: block; overflow-x: auto; -webkit-overflow-scrolling: touch; -ms-overflow-style: -ms-autohiding-scrollbar; } }
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-/** Site header */
-.site-header { border-top: 5px solid #424242; border-bottom: 1px solid #e8e8e8; min-height: 55.95px; line-height: 54px; position: relative; }
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-.site-nav input:checked ~ .trigger { display: block; padding-bottom: 5px; }
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-.site-nav .page-link { color: #111111; line-height: 1.5; display: block; padding: 5px 10px; margin-left: 20px; }
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-@media screen and (min-width: 1000px) { .site-nav { position: static; float: right; border: none; background-color: inherit; } .site-nav label[for="nav-trigger"] { display: none; } .site-nav .menu-icon { display: none; } .site-nav input ~ .trigger { display: block; } .site-nav .page-link { display: inline; padding: 0; margin-left: auto; } .site-nav .page-link:not(:last-child) { margin-right: 20px; } }
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-.site-footer { border-top: 1px solid #e8e8e8; padding: 30px 0; }
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-.footer-heading { font-size: 1.125rem; margin-bottom: 15px; }
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-.feed-subscribe .svg-icon { padding: 5px 5px 2px 0; }
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-.contact-list, .social-media-list, .pagination { list-style: none; margin-left: 0; }
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-.footer-col-wrapper, .social-links { font-size: 0.9375rem; color: #828282; }
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-.footer-col { margin-bottom: 15px; }
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-.footer-col-1, .footer-col-2 { width: calc(50% - (30px / 2)); }
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-.footer-col-3 { width: calc(100% - (30px / 2)); }
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-@media screen and (min-width: 1200px) { .footer-col-1 { width: calc(35% - (30px / 2)); } .footer-col-2 { width: calc(20% - (30px / 2)); } .footer-col-3 { width: calc(45% - (30px / 2)); } }
-
-@media screen and (min-width: 1000px) { .footer-col-wrapper { display: flex; } .footer-col { width: calc(100% - (30px / 2)); padding: 0 15px; } .footer-col:first-child { padding-right: 15px; padding-left: 0; } .footer-col:last-child { padding-right: 0; padding-left: 15px; } }
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-/** Page content */
-.page-content { padding: 30px 0; flex: 1 0 auto; }
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-.page-heading { font-size: 2rem; }
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-.post-list-heading { font-size: 1.75rem; }
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-.post-list { margin-left: 0; list-style: none; }
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-.post-list > li { margin-bottom: 30px; }
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-.post-meta { font-size: 14px; color: #828282; }
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-.post-link { display: block; font-size: 1.5rem; }
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-/** Posts */
-.post-header { margin-bottom: 30px; }
-
-.post-title, .post-content h1 { font-size: 2.625rem; letter-spacing: -1px; line-height: 1.15; }
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-@media screen and (min-width: 1200px) { .post-title, .post-content h1 { font-size: 2.625rem; } }
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-.post-content { margin-bottom: 30px; }
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-.post-content h1, .post-content h2, .post-content h3, .post-content h4, .post-content h5, .post-content h6 { margin-top: 30px; }
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-.post-content h2 { font-size: 1.75rem; }
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-.post-content h3 { font-size: 1.375rem; }
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-.social-media-list, .pagination { display: table; margin: 0 auto; }
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-.social-media-list li, .pagination li { float: left; margin: 5px 10px 5px 0; }
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-.social-media-list li:last-of-type, .pagination li:last-of-type { margin-right: 0; }
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-.social-media-list li a, .pagination li a { display: block; padding: 10px 12px; border: 1px solid #e8e8e8; }
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-.social-media-list li a:hover, .pagination li a:hover { border-color: #dbdbdb; }
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-/** Pagination navbar */
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-.pagination li a, .pagination li div { min-width: 41px; text-align: center; box-sizing: border-box; }
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-.pagination li div { display: block; padding: 7.5px; border: 1px solid transparent; }
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-.pagination li div.pager-edge { color: #e8e8e8; border: 1px dashed; }
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-/** Grid helpers */
-@media screen and (min-width: 1200px) { .one-half { width: calc(50% - (30px / 2)); } }
-
-/*-----------------------------------*/
-/*--- IMPORT STYLES FOR FASTPAGES ---*/
-.post img { display: block; vertical-align: top; margin-left: auto; margin-right: auto; }
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-img.emoji { display: inline !important; vertical-align: baseline !important; }
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-.post figcaption { text-align: center; font-size: .8rem; font-style: italic; color: light-grey; }
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-.page-content { -webkit-font-smoothing: antialiased !important; text-rendering: optimizeLegibility !important; font-family: "Segoe UI", SegoeUI, Roboto, "Segoe WP", "Helvetica Neue", "Helvetica", "Tahoma", "Arial", sans-serif !important; }
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-.post-content p, .post-content li { font-size: 20px; color: #515151; }
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-.post-link { font-weight: normal; }
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-h1 { margin-top: 2.5rem !important; }
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-h2 { margin-top: 2rem !important; }
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-h3, h4 { margin-top: 1.5rem !important; }
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-p { margin-top: 1rem !important; margin-bottom: 1rem !important; }
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-h1, h2, h3, h4 { font-weight: normal !important; margin-bottom: 0.5rem !important; }
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-h1 code, h2 code, h3 code, h4 code { font-size: 100%; }
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-pre { margin-bottom: 1.5rem !important; }
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-.post-title { margin-top: .5rem !important; }
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-li h3, li h4 { margin-top: .05rem !important; margin-bottom: .05rem !important; }
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-li .post-meta-description { color: #585858; font-size: 15px; margin-top: .05rem !important; margin-bottom: .05rem !important; }
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-details.description[open] summary::after { content: attr(data-open); }
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-.notebook-badge-image { border: 0 !important; }
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-.footnotes { font-size: 12px !important; }
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-.social-media-list .svg-icon, .pagination .svg-icon { width: 25px !important; height: 23px !important; }
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-.anchor-link { opacity: 0; padding-left: 0.375em; \-webkit-text-stroke: 1.75px white; \-webkit-transition: opacity 0.2s ease-in-out 0.1s; \-moz-transition: opacity 0.2s ease-in-out 0.1s; \-ms-transition: opacity 0.2s ease-in-out 0.1s; }
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-.category-tags { margin-top: .25rem !important; margin-bottom: .25rem !important; font-size: 105%; }
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-.post-meta-title, .post-meta { margin-top: .25em !important; margin-bottom: .25em !important; font-size: 105%; }
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-.page-description { margin-top: .5rem !important; margin-bottom: .5rem !important; color: #585858; font-size: 115%; }
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-.category-tags-icon { font-size: 75% !important; padding-left: 0.375em; opacity: 35%; }
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-.category-tags-link { color: #bb8181 !important; font-size: 13px !important; }
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-.js-search-results { padding-top: 0.2rem; }
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-.search-results-list-item { padding-bottom: 1rem; }
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-.search-result-rel-url { color: silver; }
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-.search-result-rel-date { color: #6d788a; font-size: 14px; }
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-.search-result-preview { color: #777; font-size: 16px; margin-top: .02rem !important; margin-bottom: .02rem !important; }
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-.search-result-highlight { color: #2e0137; font-weight: bold; }
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-table { white-space: normal; max-width: 100%; font-size: 100%; border: none; }
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-table th { text-align: center !important; }
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-::-webkit-scrollbar { width: 14px; height: 18px; }
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-::-webkit-scrollbar-thumb { height: 6px; border: 4px solid rgba(0, 0, 0, 0); background-clip: padding-box; -webkit-border-radius: 7px; background-color: #9D9D9D; -webkit-box-shadow: inset -1px -1px 0px rgba(0, 0, 0, 0.05), inset 1px 1px 0px rgba(0, 0, 0, 0.05); }
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-.output_text.output_execute_result pre { white-space: pre-wrap; }
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-.svg-icon.orange { width: 30px; height: 23px; }
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-/*-----------------------------------*/
-/*----- ADD YOUR STYLES BELOW -------*/
-.language-python + .language-plaintext { border-left: 1px solid grey; margin-left: 1rem !important; }
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-.input_area pre, .input_area div { margin-bottom: 1.0rem !important; margin-top: 1.5rem !important; padding-bottom: 0 !important; padding-top: 0 !important; background: #323443 !important; -webkit-font-smoothing: antialiased; text-rendering: optimizeLegibility; font-family: Menlo, Monaco, Consolas, "Lucida Console", Roboto, Ubuntu, monospace; border-radius: 5px; font-size: 105%; }
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-.output_area pre, .output_area div { margin-bottom: 1rem !important; margin-top: 0rem !important; padding-bottom: 0 !important; padding-top: 0 !important; }
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-.input_area pre { border-left: 1px solid lightcoral; }
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-.code_cell table { width: auto; }
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-/* Dracula Theme v1.2.5 https://github.com/zenorocha/dracula-theme Copyright 2016, All rights reserved Code licensed under the MIT license */
-.highlight { background: #323443 !important; color: #f8f8f2 !important; }
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-.highlight pre, .highlight code { background: #323443; color: #f8f8f2; font-size: 110%; }
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-.highlight .go { color: #44475a; }
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-.highlight .ge { text-decoration: underline; }
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-/*# sourceMappingURL=style.css.map */
\ No newline at end of file
diff --git a/assets/css/style.css.map b/assets/css/style.css.map
deleted file mode 100755
index 5a76d7b..0000000
--- a/assets/css/style.css.map
+++ /dev/null
@@ -1,30 +0,0 @@
-{
-	"version": 3,
-	"file": "style.css",
-	"sources": [
-		"style.scss",
-		"../../tmp/jekyll-remote-theme-20231229-1-7f1xdb/_sass/minima/skins/classic.scss",
-		"../../tmp/jekyll-remote-theme-20231229-1-7f1xdb/_sass/minima/skins/auto.scss",
-		"../../tmp/jekyll-remote-theme-20231229-1-7f1xdb/_sass/minima/initialize.scss",
-		"_sass/minima/custom-variables.scss",
-		"../../tmp/jekyll-remote-theme-20231229-1-7f1xdb/_sass/minima/_base.scss",
-		"../../tmp/jekyll-remote-theme-20231229-1-7f1xdb/_sass/minima/_layout.scss",
-		"_sass/minima/custom-styles.scss",
-		"_sass/minima/fastpages-styles.scss",
-		"_sass/minima/fastpages-dracula-highlight.scss"
-	],
-	"sourcesContent": [
-		"@import\n  \"minima/skins/classic\",\n  \"minima/initialize\";\n",
-		"@charset \"utf-8\";\n\n$color-scheme-auto: false;\n$color-scheme-dark: false;\n@import \"minima/skins/auto\";\n",
-		"@charset \"utf-8\";\n\n// Default color scheme settings\n// These are overridden in classic.css and dark.scss\n\n$color-scheme-auto: true !default;\n$color-scheme-dark: false !default;\n\n\n// Light mode\n// ----------\n\n$lm-brand-color:           #828282 !default;\n$lm-brand-color-light:     lighten($lm-brand-color, 40%) !default;\n$lm-brand-color-dark:      darken($lm-brand-color, 25%) !default;\n\n$lm-site-title-color:      $lm-brand-color-dark !default;\n\n$lm-text-color:            #111111 !default;\n$lm-background-color:      #fdfdfd !default;\n$lm-code-background-color: #eeeeff !default;\n\n$lm-link-base-color:       #2a7ae2 !default;\n$lm-link-visited-color:    darken($lm-link-base-color, 15%) !default;\n$lm-link-hover-color:      $lm-text-color !default;\n\n$lm-border-color-01:       $lm-brand-color-light !default;\n$lm-border-color-02:       lighten($lm-brand-color, 35%) !default;\n$lm-border-color-03:       $lm-brand-color-dark !default;\n\n$lm-table-text-color:      lighten($lm-text-color, 18%) !default;\n$lm-table-zebra-color:     lighten($lm-brand-color, 46%) !default;\n$lm-table-header-bg-color: lighten($lm-brand-color, 43%) !default;\n$lm-table-header-border:   lighten($lm-brand-color, 37%) !default;\n$lm-table-border-color:    $lm-border-color-01 !default;\n\n\n// Syntax highlighting styles should be adjusted appropriately for every \"skin\"\n// ----------------------------------------------------------------------------\n\n@mixin lm-highlight {\n  .highlight {\n    .c     { color: #998; font-style: italic } // Comment\n    .err   { color: #a61717; background-color: #e3d2d2 } // Error\n    .k     { font-weight: bold } // Keyword\n    .o     { font-weight: bold } // Operator\n    .cm    { color: #998; font-style: italic } // Comment.Multiline\n    .cp    { color: #999; font-weight: bold } // Comment.Preproc\n    .c1    { color: #998; font-style: italic } // Comment.Single\n    .cs    { color: #999; font-weight: bold; font-style: italic } // Comment.Special\n    .gd    { color: #000; background-color: #fdd } // Generic.Deleted\n    .gd .x { color: #000; background-color: #faa } // Generic.Deleted.Specific\n    .ge    { font-style: italic } // Generic.Emph\n    .gr    { color: #a00 } // Generic.Error\n    .gh    { color: #999 } // Generic.Heading\n    .gi    { color: #000; background-color: #dfd } // Generic.Inserted\n    .gi .x { color: #000; background-color: #afa } // Generic.Inserted.Specific\n    .go    { color: #888 } // Generic.Output\n    .gp    { color: #555 } // Generic.Prompt\n    .gs    { font-weight: bold } // Generic.Strong\n    .gu    { color: #aaa } // Generic.Subheading\n    .gt    { color: #a00 } // Generic.Traceback\n    .kc    { font-weight: bold } // Keyword.Constant\n    .kd    { font-weight: bold } // Keyword.Declaration\n    .kp    { font-weight: bold } // Keyword.Pseudo\n    .kr    { font-weight: bold } // Keyword.Reserved\n    .kt    { color: #458; font-weight: bold } // Keyword.Type\n    .m     { color: #099 } // Literal.Number\n    .s     { color: #d14 } // Literal.String\n    .na    { color: #008080 } // Name.Attribute\n    .nb    { color: #0086B3 } // Name.Builtin\n    .nc    { color: #458; font-weight: bold } // Name.Class\n    .no    { color: #008080 } // Name.Constant\n    .ni    { color: #800080 } // Name.Entity\n    .ne    { color: #900; font-weight: bold } // Name.Exception\n    .nf    { color: #900; font-weight: bold } // Name.Function\n    .nn    { color: #555 } // Name.Namespace\n    .nt    { color: #000080 } // Name.Tag\n    .nv    { color: #008080 } // Name.Variable\n    .ow    { font-weight: bold } // Operator.Word\n    .w     { color: #bbb } // Text.Whitespace\n    .mf    { color: #099 } // Literal.Number.Float\n    .mh    { color: #099 } // Literal.Number.Hex\n    .mi    { color: #099 } // Literal.Number.Integer\n    .mo    { color: #099 } // Literal.Number.Oct\n    .sb    { color: #d14 } // Literal.String.Backtick\n    .sc    { color: #d14 } // Literal.String.Char\n    .sd    { color: #d14 } // Literal.String.Doc\n    .s2    { color: #d14 } // Literal.String.Double\n    .se    { color: #d14 } // Literal.String.Escape\n    .sh    { color: #d14 } // Literal.String.Heredoc\n    .si    { color: #d14 } // Literal.String.Interpol\n    .sx    { color: #d14 } // Literal.String.Other\n    .sr    { color: #009926 } // Literal.String.Regex\n    .s1    { color: #d14 } // Literal.String.Single\n    .ss    { color: #990073 } // Literal.String.Symbol\n    .bp    { color: #999 } // Name.Builtin.Pseudo\n    .vc    { color: #008080 } // Name.Variable.Class\n    .vg    { color: #008080 } // Name.Variable.Global\n    .vi    { color: #008080 } // Name.Variable.Instance\n    .il    { color: #099 } // Literal.Number.Integer.Long\n  }\n}\n\n\n// Dark mode\n// ---------\n\n$dm-brand-color:           #999999 !default;\n$dm-brand-color-light:     lighten($dm-brand-color, 5%) !default;\n$dm-brand-color-dark:      darken($dm-brand-color, 35%) !default;\n\n$dm-site-title-color:      $dm-brand-color-light !default;\n\n$dm-text-color:            #bbbbbb !default;\n$dm-background-color:      #181818 !default;\n$dm-code-background-color: #212121 !default;\n\n$dm-link-base-color:       #79b8ff !default;\n$dm-link-visited-color:    $dm-link-base-color !default;\n$dm-link-hover-color:      $dm-text-color !default;\n\n$dm-border-color-01:       $dm-brand-color-dark !default;\n$dm-border-color-02:       $dm-brand-color-light !default;\n$dm-border-color-03:       $dm-brand-color !default;\n\n$dm-table-text-color:      $dm-text-color !default;\n$dm-table-zebra-color:     lighten($dm-background-color, 4%) !default;\n$dm-table-header-bg-color: lighten($dm-background-color, 10%) !default;\n$dm-table-header-border:   lighten($dm-background-color, 21%) !default;\n$dm-table-border-color:    $dm-border-color-01 !default;\n\n\n// Syntax highlighting styles should be adjusted appropriately for every \"skin\"\n// List of tokens: https://github.com/rouge-ruby/rouge/wiki/List-of-tokens\n// Some colors come from Material Theme Darker:\n// https://github.com/material-theme/vsc-material-theme/blob/master/scripts/generator/settings/specific/darker-hc.ts\n// https://github.com/material-theme/vsc-material-theme/blob/master/scripts/generator/color-set.ts\n// ----------------------------------------------------------------------------\n\n@mixin dm-highlight {\n  .highlight {\n    .c     { color: #545454; font-style: italic } // Comment\n    .err   { color: #f07178; background-color: #e3d2d2 } // Error\n    .k     { color: #89DDFF; font-weight: bold } // Keyword\n    .o     { font-weight: bold } // Operator\n    .cm    { color: #545454; font-style: italic } // Comment.Multiline\n    .cp    { color: #545454; font-weight: bold } // Comment.Preproc\n    .c1    { color: #545454; font-style: italic } // Comment.Single\n    .cs    { color: #545454; font-weight: bold; font-style: italic } // Comment.Special\n    .gd    { color: #000; background-color: #fdd } // Generic.Deleted\n    .gd .x { color: #000; background-color: #faa } // Generic.Deleted.Specific\n    .ge    { font-style: italic } // Generic.Emph\n    .gr    { color: #f07178 } // Generic.Error\n    .gh    { color: #999 } // Generic.Heading\n    .gi    { color: #000; background-color: #dfd } // Generic.Inserted\n    .gi .x { color: #000; background-color: #afa } // Generic.Inserted.Specific\n    .go    { color: #888 } // Generic.Output\n    .gp    { color: #555 } // Generic.Prompt\n    .gs    { font-weight: bold } // Generic.Strong\n    .gu    { color: #aaa } // Generic.Subheading\n    .gt    { color: #f07178 } // Generic.Traceback\n    .kc    { font-weight: bold } // Keyword.Constant\n    .kd    { font-weight: bold } // Keyword.Declaration\n    .kp    { font-weight: bold } // Keyword.Pseudo\n    .kr    { font-weight: bold } // Keyword.Reserved\n    .kt    { color: #FFCB6B; font-weight: bold } // Keyword.Type\n    .m     { color: #F78C6C } // Literal.Number\n    .s     { color: #C3E88D } // Literal.String\n    .na    { color: #008080 } // Name.Attribute\n    .nb    { color: #EEFFFF } // Name.Builtin\n    .nc    { color: #FFCB6B; font-weight: bold } // Name.Class\n    .no    { color: #008080 } // Name.Constant\n    .ni    { color: #800080 } // Name.Entity\n    .ne    { color: #900; font-weight: bold } // Name.Exception\n    .nf    { color: #82AAFF; font-weight: bold } // Name.Function\n    .nn    { color: #555 } // Name.Namespace\n    .nt    { color: #FFCB6B } // Name.Tag\n    .nv    { color: #EEFFFF } // Name.Variable\n    .ow    { font-weight: bold } // Operator.Word\n    .w     { color: #EEFFFF } // Text.Whitespace\n    .mf    { color: #F78C6C } // Literal.Number.Float\n    .mh    { color: #F78C6C } // Literal.Number.Hex\n    .mi    { color: #F78C6C } // Literal.Number.Integer\n    .mo    { color: #F78C6C } // Literal.Number.Oct\n    .sb    { color: #C3E88D } // Literal.String.Backtick\n    .sc    { color: #C3E88D } // Literal.String.Char\n    .sd    { color: #C3E88D } // Literal.String.Doc\n    .s2    { color: #C3E88D } // Literal.String.Double\n    .se    { color: #EEFFFF } // Literal.String.Escape\n    .sh    { color: #C3E88D } // Literal.String.Heredoc\n    .si    { color: #C3E88D } // Literal.String.Interpol\n    .sx    { color: #C3E88D } // Literal.String.Other\n    .sr    { color: #C3E88D } // Literal.String.Regex\n    .s1    { color: #C3E88D } // Literal.String.Single\n    .ss    { color: #C3E88D } // Literal.String.Symbol\n    .bp    { color: #999 } // Name.Builtin.Pseudo\n    .vc    { color: #FFCB6B } // Name.Variable.Class\n    .vg    { color: #EEFFFF } // Name.Variable.Global\n    .vi    { color: #EEFFFF } // Name.Variable.Instance\n    .il    { color: #F78C6C } // Literal.Number.Integer.Long\n  }\n}\n\n\n// Mode selection\n// --------------\n\n\n// Classic skin (always light mode)\n// Assign outside of the if construct to establish global variable scope\n\n$brand-color: $lm-brand-color;\n$brand-color-light: $lm-brand-color-light;\n$brand-color-dark: $lm-brand-color-dark;\n\n$site-title-color: $lm-site-title-color;\n\n$text-color: $lm-text-color;\n$background-color: $lm-background-color;\n$code-background-color: $lm-code-background-color;\n\n$link-base-color: $lm-link-base-color;\n$link-visited-color: $lm-link-visited-color;\n$link-hover-color: $lm-link-hover-color;\n\n$border-color-01: $lm-border-color-01;\n$border-color-02: $lm-border-color-02;\n$border-color-03: $lm-border-color-03;\n\n$table-text-color: $lm-table-text-color;\n$table-zebra-color: $lm-table-zebra-color;\n$table-header-bg-color: $lm-table-header-bg-color;\n$table-header-border: $lm-table-header-border;\n$table-border-color: $lm-table-border-color;\n\n\n@if $color-scheme-auto {\n\n  // Auto mode\n\n  :root {\n    --minima-brand-color: #{$lm-brand-color};\n    --minima-brand-color-light: #{$lm-brand-color-light};\n    --minima-brand-color-dark: #{$lm-brand-color-dark};\n\n    --minima-site-title-color: #{$lm-site-title-color};\n\n    --minima-text-color: #{$lm-text-color};\n    --minima-background-color: #{$lm-background-color};\n    --minima-code-background-color: #{$lm-code-background-color};\n\n    --minima-link-base-color: #{$lm-link-base-color};\n    --minima-link-visited-color: #{$lm-link-visited-color};\n    --minima-link-hover-color: #{$lm-link-hover-color};\n\n    --minima-border-color-01: #{$lm-border-color-01};\n    --minima-border-color-02: #{$lm-border-color-02};\n    --minima-border-color-03: #{$lm-border-color-03};\n\n    --minima-table-text-color: #{$lm-table-text-color};\n    --minima-table-zebra-color: #{$lm-table-zebra-color};\n    --minima-table-header-bg-color: #{$lm-table-header-bg-color};\n    --minima-table-header-border: #{$lm-table-header-border};\n    --minima-table-border-color: #{$lm-table-border-color};\n  }\n\n  @include lm-highlight;\n\n  @media (prefers-color-scheme: dark) {\n    :root {\n      --minima-brand-color: #{$dm-brand-color};\n      --minima-brand-color-light: #{$dm-brand-color-light};\n      --minima-brand-color-dark: #{$dm-brand-color-dark};\n\n      --minima-site-title-color: #{$dm-site-title-color};\n\n      --minima-text-color: #{$dm-text-color};\n      --minima-background-color: #{$dm-background-color};\n      --minima-code-background-color: #{$dm-code-background-color};\n\n      --minima-link-base-color: #{$dm-link-base-color};\n      --minima-link-visited-color: #{$dm-link-visited-color};\n      --minima-link-hover-color: #{$dm-link-hover-color};\n\n      --minima-border-color-01: #{$dm-border-color-01};\n      --minima-border-color-02: #{$dm-border-color-02};\n      --minima-border-color-03: #{$dm-border-color-03};\n\n      --minima-table-text-color: #{$dm-table-text-color};\n      --minima-table-zebra-color: #{$dm-table-zebra-color};\n      --minima-table-header-bg-color: #{$dm-table-header-bg-color};\n      --minima-table-header-border: #{$dm-table-header-border};\n      --minima-table-border-color: #{$dm-table-border-color};\n    }\n\n    @include dm-highlight;\n  }\n\n  $brand-color: var(--minima-brand-color);\n  $brand-color-light: var(--minima-brand-color-light);\n  $brand-color-dark: var(--minima-brand-color-dark);\n\n  $site-title-color: var(--minima-site-title-color);\n\n  $text-color: var(--minima-text-color);\n  $background-color: var(--minima-background-color);\n  $code-background-color: var(--minima-code-background-color);\n\n  $link-base-color: var(--minima-link-base-color);\n  $link-visited-color: var(--minima-link-visited-color);\n  $link-hover-color: var(--minima-link-hover-color);\n\n  $border-color-01: var(--minima-border-color-01);\n  $border-color-02: var(--minima-border-color-02);\n  $border-color-03: var(--minima-border-color-03);\n\n  $table-text-color: var(--minima-table-text-color);\n  $table-zebra-color: var(--minima-table-zebra-color);\n  $table-header-bg-color: var(--minima-table-header-bg-color);\n  $table-header-border: var(--minima-table-header-border);\n  $table-border-color: var(--minima-table-border-color);\n\n\n} @else if $color-scheme-dark {\n\n  // Dark skin (always dark mode)\n\n  $brand-color: $dm-brand-color;\n  $brand-color-light: $dm-brand-color-light;\n  $brand-color-dark: $dm-brand-color-dark;\n\n  $site-title-color: $dm-site-title-color;\n\n  $text-color: $dm-text-color;\n  $background-color: $dm-background-color;\n  $code-background-color: $dm-code-background-color;\n\n  $link-base-color: $dm-link-base-color;\n  $link-visited-color: $dm-link-visited-color;\n  $link-hover-color: $dm-link-hover-color;\n\n  $border-color-01: $dm-border-color-01;\n  $border-color-02: $dm-border-color-02;\n  $border-color-03: $dm-border-color-03;\n\n  $table-text-color: $dm-table-text-color;\n  $table-zebra-color: $dm-table-zebra-color;\n  $table-header-bg-color: $dm-table-header-bg-color;\n  $table-header-border: $dm-table-header-border;\n  $table-border-color: $dm-table-border-color;\n\n  @include dm-highlight;\n\n\n} @else {\n\n  // Classic skin syntax highlighting\n  @include lm-highlight;\n\n}\n",
-		"@charset \"utf-8\";\n\n// Define defaults for each variable.\n\n$base-font-family: -apple-system, system-ui, BlinkMacSystemFont, \"Segoe UI\", \"Segoe UI Emoji\", \"Segoe UI Symbol\", \"Apple Color Emoji\", Roboto, Helvetica, Arial, sans-serif !default;\n$code-font-family: \"Menlo\", \"Inconsolata\", \"Consolas\", \"Roboto Mono\", \"Ubuntu Mono\", \"Liberation Mono\", \"Courier New\", monospace;\n$base-font-size:   16px !default;\n$base-font-weight: 400 !default;\n$small-font-size:  $base-font-size * 0.875 !default;\n$base-line-height: 1.5 !default;\n\n$spacing-unit:     30px !default;\n\n$table-text-align: left !default;\n\n// Width of the content area\n$content-width:    800px !default;\n\n$on-palm:          600px !default;\n$on-laptop:        800px !default;\n\n$on-medium:        $on-palm !default;\n$on-large:         $on-laptop !default;\n\n// Use media queries like this:\n// @include media-query($on-palm) {\n//   .wrapper {\n//     padding-right: $spacing-unit / 2;\n//     padding-left: $spacing-unit / 2;\n//   }\n// }\n// Notice the following mixin uses max-width, in a deprecated, desktop-first\n// approach, whereas media queries used elsewhere now use min-width.\n@mixin media-query($device) {\n  @media screen and (max-width: $device) {\n    @content;\n  }\n}\n\n@mixin relative-font-size($ratio) {\n  font-size: #{$ratio}rem;\n}\n\n// Import pre-styling-overrides hook and style-partials.\n@import\n  \"minima/custom-variables\", // Hook to override predefined variables.\n  \"minima/base\",             // Defines element resets.\n  \"minima/layout\",           // Defines structure and style based on CSS selectors.\n  \"minima/custom-styles\"     // Hook to override existing styles.\n;\n",
-		"// override defalt minima variables \n\n// width of the content area\n// can be set as \"px\" or \"%\"\n$content-width:    1000px;\n$on-palm:          800px;\n$on-laptop:        1000px;\n$on-medium:        1000px;\n$on-large:         1200px;\n",
-		"html {\n  font-size: $base-font-size;\n}\n\n/**\n * Reset some basic elements\n */\nbody, h1, h2, h3, h4, h5, h6,\np, blockquote, pre, hr,\ndl, dd, ol, ul, figure {\n  margin: 0;\n  padding: 0;\n\n}\n\n\n\n/**\n * Basic styling\n */\nbody {\n  font: $base-font-weight #{$base-font-size}/#{$base-line-height} $base-font-family;\n  color: $text-color;\n  background-color: $background-color;\n  -webkit-text-size-adjust: 100%;\n  -webkit-font-feature-settings: \"kern\" 1;\n     -moz-font-feature-settings: \"kern\" 1;\n       -o-font-feature-settings: \"kern\" 1;\n          font-feature-settings: \"kern\" 1;\n  font-kerning: normal;\n  display: flex;\n  min-height: 100vh;\n  flex-direction: column;\n  overflow-wrap: break-word;\n}\n\n\n\n/**\n * Set `margin-bottom` to maintain vertical rhythm\n */\nh1, h2, h3, h4, h5, h6,\np, blockquote, pre,\nul, ol, dl, figure,\n%vertical-rhythm {\n  margin-bottom: $spacing-unit * .5;\n}\n\nhr {\n  margin-top: $spacing-unit;\n  margin-bottom: $spacing-unit;\n}\n\n/**\n * `main` element\n */\nmain {\n  display: block; /* Default value of `display` of `main` element is 'inline' in IE 11. */\n}\n\n\n\n/**\n * Images\n */\nimg {\n  max-width: 100%;\n  vertical-align: middle;\n}\n\n\n\n/**\n * Figures\n */\nfigure > img {\n  display: block;\n}\n\nfigcaption {\n  font-size: $small-font-size;\n}\n\n\n\n/**\n * Lists\n */\nul, ol {\n  margin-left: $spacing-unit;\n}\n\nli {\n  > ul,\n  > ol {\n    margin-bottom: 0;\n  }\n}\n\n\n\n/**\n * Headings\n */\nh1, h2, h3, h4, h5, h6 {\n  font-weight: $base-font-weight;\n}\n\n\n\n/**\n * Links\n */\na {\n  color: $link-base-color;\n  text-decoration: none;\n\n  &:visited {\n    color: $link-visited-color;\n  }\n\n  &:hover {\n    color: $link-hover-color;\n    text-decoration: underline;\n  }\n\n  .social-media-list &:hover {\n    text-decoration: none;\n\n    .username {\n      text-decoration: underline;\n    }\n  }\n}\n\n\n/**\n * Blockquotes\n */\nblockquote {\n  color: $brand-color;\n  border-left: 4px solid $border-color-01;\n  padding-left: $spacing-unit * .5;\n  @include relative-font-size(1.125);\n  font-style: italic;\n\n  > :last-child {\n    margin-bottom: 0;\n  }\n\n  i, em {\n    font-style: normal;\n  }\n}\n\n\n\n/**\n * Code formatting\n */\npre,\ncode {\n  font-family: $code-font-family;\n  font-size: 0.9375em;\n  border: 1px solid $border-color-01;\n  border-radius: 3px;\n  background-color: $code-background-color;\n}\n\ncode {\n  padding: 1px 5px;\n}\n\npre {\n  padding: 8px 12px;\n  overflow-x: auto;\n\n  > code {\n    border: 0;\n    padding-right: 0;\n    padding-left: 0;\n  }\n}\n\n.highlight {\n  border-radius: 3px;\n  background: $code-background-color;\n  @extend %vertical-rhythm;\n\n  .highlighter-rouge & {\n    background: $code-background-color;\n  }\n}\n\n\n\n/**\n * Wrapper\n */\n.wrapper {\n  max-width: calc(#{$content-width} - (#{$spacing-unit}));\n  margin-right: auto;\n  margin-left: auto;\n  padding-right: $spacing-unit * .5;\n  padding-left: $spacing-unit * .5;\n  @extend %clearfix;\n\n  @media screen and (min-width: $on-large) {\n    max-width: calc(#{$content-width} - (#{$spacing-unit} * 2));\n    padding-right: $spacing-unit;\n    padding-left: $spacing-unit;\n  }\n}\n\n\n\n/**\n * Clearfix\n */\n%clearfix:after {\n  content: \"\";\n  display: table;\n  clear: both;\n}\n\n\n\n/**\n * Icons\n */\n\n.orange {\n  color: #f66a0a;\n}\n\n.grey {\n  color: #828282;\n}\n\n.svg-icon {\n  width: 1.25em;\n  height: 1.25em;\n  display: inline-block;\n  fill: currentColor;\n  vertical-align: text-bottom;\n}\n\n\n/**\n * Tables\n */\ntable {\n  margin-bottom: $spacing-unit;\n  width: 100%;\n  text-align: $table-text-align;\n  color: $table-text-color;\n  border-collapse: collapse;\n  border: 1px solid $table-border-color;\n  tr {\n    &:nth-child(even) {\n      background-color: $table-zebra-color;\n    }\n  }\n  th, td {\n    padding: ($spacing-unit * 33.3333333333 * .01) ($spacing-unit * .5);\n  }\n  th {\n    background-color: $table-header-bg-color;\n    border: 1px solid $table-header-border;\n  }\n  td {\n    border: 1px solid $table-border-color;\n  }\n\n  @include media-query($on-laptop) {\n    display: block;\n    overflow-x: auto;\n    -webkit-overflow-scrolling: touch;\n            -ms-overflow-style: -ms-autohiding-scrollbar;\n  }\n}\n",
-		"/**\n * Site header\n */\n.site-header {\n  border-top: 5px solid $border-color-03;\n  border-bottom: 1px solid $border-color-01;\n  min-height: $spacing-unit * 1.865;\n  line-height: $base-line-height * $base-font-size * 2.25;\n\n  // Positioning context for the mobile navigation icon\n  position: relative;\n}\n\n.site-title {\n  @include relative-font-size(1.625);\n  font-weight: 300;\n  letter-spacing: -1px;\n  margin-bottom: 0;\n  float: left;\n\n  @include media-query($on-palm) {\n    padding-right: 45px;\n  }\n\n  &,\n  &:visited {\n    color: $site-title-color;\n  }\n}\n\n.site-nav {\n  position: absolute;\n  top: 9px;\n  right: $spacing-unit * .5;\n  background-color: $background-color;\n  border: 1px solid $border-color-01;\n  border-radius: 5px;\n  text-align: right;\n\n  .nav-trigger {\n    display: none;\n  }\n\n  .menu-icon {\n    float: right;\n    width: 36px;\n    height: 26px;\n    line-height: 0;\n    padding-top: 10px;\n    text-align: center;\n\n    > svg path {\n      fill: $border-color-03;\n    }\n  }\n\n  label[for=\"nav-trigger\"] {\n    display: block;\n    float: right;\n    width: 36px;\n    height: 36px;\n    z-index: 2;\n    cursor: pointer;\n  }\n\n  input ~ .trigger {\n    clear: both;\n    display: none;\n  }\n\n  input:checked ~ .trigger {\n    display: block;\n    padding-bottom: 5px;\n  }\n\n  .page-link {\n    color: $text-color;\n    line-height: $base-line-height;\n    display: block;\n    padding: 5px 10px;\n\n    // Gaps between nav items, but not on the last one\n    &:not(:last-child) {\n      margin-right: 0;\n    }\n    margin-left: 20px;\n  }\n\n  @media screen and (min-width: $on-medium) {\n    position: static;\n    float: right;\n    border: none;\n    background-color: inherit;\n\n    label[for=\"nav-trigger\"] {\n      display: none;\n    }\n\n    .menu-icon {\n      display: none;\n    }\n\n    input ~ .trigger {\n      display: block;\n    }\n\n    .page-link {\n      display: inline;\n      padding: 0;\n\n      &:not(:last-child) {\n        margin-right: 20px;\n      }\n      margin-left: auto;\n    }\n  }\n}\n\n\n\n/**\n * Site footer\n */\n.site-footer {\n  border-top: 1px solid $border-color-01;\n  padding: $spacing-unit 0;\n}\n\n.footer-heading {\n  @include relative-font-size(1.125);\n  margin-bottom: $spacing-unit * .5;\n}\n\n.feed-subscribe .svg-icon {\n  padding: 5px 5px 2px 0\n}\n\n.contact-list,\n.social-media-list {\n  list-style: none;\n  margin-left: 0;\n}\n\n.footer-col-wrapper,\n.social-links {\n  @include relative-font-size(0.9375);\n  color: $brand-color;\n}\n\n.footer-col {\n  margin-bottom: $spacing-unit * .5;\n}\n\n.footer-col-1,\n.footer-col-2 {\n  width: calc(50% - (#{$spacing-unit} / 2));\n}\n\n.footer-col-3 {\n  width: calc(100% - (#{$spacing-unit} / 2));\n}\n\n@media screen and (min-width: $on-large) {\n  .footer-col-1 {\n    width: calc(35% - (#{$spacing-unit} / 2));\n  }\n\n  .footer-col-2 {\n    width: calc(20% - (#{$spacing-unit} / 2));\n  }\n\n  .footer-col-3 {\n    width: calc(45% - (#{$spacing-unit} / 2));\n  }\n}\n\n@media screen and (min-width: $on-medium) {\n  .footer-col-wrapper {\n    display: flex\n  }\n\n  .footer-col {\n    width: calc(100% - (#{$spacing-unit} / 2));\n    padding: 0 ($spacing-unit * .5);\n\n    &:first-child {\n      padding-right: $spacing-unit * .5;\n      padding-left: 0;\n    }\n\n    &:last-child {\n      padding-right: 0;\n      padding-left: $spacing-unit * .5;\n    }\n  }\n}\n\n\n\n/**\n * Page content\n */\n.page-content {\n  padding: $spacing-unit 0;\n  flex: 1 0 auto;\n}\n\n.page-heading {\n  @include relative-font-size(2);\n}\n\n.post-list-heading {\n  @include relative-font-size(1.75);\n}\n\n.post-list {\n  margin-left: 0;\n  list-style: none;\n\n  > li {\n    margin-bottom: $spacing-unit;\n  }\n}\n\n.post-meta {\n  font-size: $small-font-size;\n  color: $brand-color;\n}\n\n.post-link {\n  display: block;\n  @include relative-font-size(1.5);\n}\n\n\n\n/**\n * Posts\n */\n.post-header {\n  margin-bottom: $spacing-unit;\n}\n\n.post-title,\n.post-content h1 {\n  @include relative-font-size(2.625);\n  letter-spacing: -1px;\n  line-height: 1.15;\n\n  @media screen and (min-width: $on-large) {\n    @include relative-font-size(2.625);\n  }\n}\n\n.post-content {\n  margin-bottom: $spacing-unit;\n\n  h1, h2, h3, h4, h5, h6 { margin-top: $spacing-unit }\n\n  h2 {\n    @include relative-font-size(1.75);\n\n    @media screen and (min-width: $on-large) {\n      @include relative-font-size(2);\n    }\n  }\n\n  h3 {\n    @include relative-font-size(1.375);\n\n    @media screen and (min-width: $on-large) {\n      @include relative-font-size(1.625);\n    }\n  }\n\n  h4 {\n    @include relative-font-size(1.25);\n  }\n\n  h5 {\n    @include relative-font-size(1.125);\n  }\n  h6 {\n    @include relative-font-size(1.0625);\n  }\n}\n\n\n.social-media-list {\n  display: table;\n  margin: 0 auto;\n  li {\n    float: left;\n    margin: 5px 10px 5px 0;\n    &:last-of-type { margin-right: 0 }\n    a {\n      display: block;\n      padding: 10px 12px;\n      border: 1px solid $border-color-01;\n      &:hover { border-color: $border-color-02 }\n    }\n  }\n}\n\n\n\n/**\n * Pagination navbar\n */\n.pagination {\n  margin-bottom: $spacing-unit;\n  @extend .social-media-list;\n  li {\n    a, div {\n      min-width: 41px;\n      text-align: center;\n      box-sizing: border-box;\n    }\n    div {\n      display: block;\n      padding: $spacing-unit * .25;\n      border: 1px solid transparent;\n\n      &.pager-edge {\n        color: $border-color-01;\n        border: 1px dashed;\n      }\n    }\n  }\n}\n\n\n\n/**\n * Grid helpers\n */\n@media screen and (min-width: $on-large) {\n  .one-half {\n    width: calc(50% - (#{$spacing-unit} / 2));\n  }\n}\n",
-		"/*-----------------------------------*/\n/*--- IMPORT STYLES FOR FASTPAGES ---*/\n@import \"minima/fastpages-styles\";   \n\n\n\n/*-----------------------------------*/\n/*----- ADD YOUR STYLES BELOW -------*/\n\n// If you want to turn off dark background for syntax highlighting, comment or delete the below line.\n@import \"minima/fastpages-dracula-highlight\"; \n",
-		"//Default Overrides For Styles In Minima \n// If you wish to override any of this CSS, do so in _sass/minima/custom-styles.css\n\n.post img {\n        display: block;\n        // border:1px solid #021a40;\n        vertical-align: top;\n        margin-left: auto;\n        margin-right: auto;\n}\n\nimg.emoji{\n      display: inline !important;\n      vertical-align: baseline !important;\n}\n\n.post figcaption {\n  text-align: center;\n  font-size: .8rem;\n  font-style: italic;\n  color: light-grey;\n}\n\n.page-content {\n        -webkit-font-smoothing: antialiased !important;\n        text-rendering: optimizeLegibility !important;\n        font-family: \"Segoe UI\", SegoeUI, Roboto, \"Segoe WP\", \"Helvetica Neue\", \"Helvetica\", \"Tahoma\", \"Arial\", sans-serif !important;\n}\n\n// make non-headings slightly lighter\n.post-content p, .post-content li {\n   font-size: 20px;\n   color: #515151;\n}\n\n.post-link{\n    font-weight: normal;\n}\n\n// change padding of headings\nh1 {\n    margin-top:2.5rem !important;\n}\n\nh2 {\n    margin-top:2rem !important;      \n}\n\nh3, h4 {\n    margin-top:1.5rem !important;      \n}\n\np {\n    margin-top:1rem !important; \n    margin-bottom:1rem !important;   \n}\n\nh1, h2, h3, h4 {\n    font-weight: normal !important;\n    margin-bottom:0.5rem !important;  \n    code {\n      font-size: 100%;\n    }\n}\n\npre {\n    margin-bottom:1.5rem !important; \n}\n\n// make sure the post title doesn't have too much spacing\n.post-title { margin-top: .5rem !important; }\n\nli {\n  h3, h4 {\n  margin-top:.05rem !important;\n  margin-bottom:.05rem !important;\n  }\n  .post-meta-description {\n    color: rgb(88, 88, 88);\n    font-size: 15px;\n    margin-top:.05rem !important;\n    margin-bottom:.05rem !important;\n  }\n}\n\n\n\n//  Code Folding\n details.description[open] summary::after {\n  content: attr(data-open);\n}\n\ndetails.description:not([open]) summary::after {\n  content: attr(data-close);\n}\n\n// Notebook badges\n.notebook-badge-image {\n  border:0 !important;\n}\n\n// Adjust font size for footnotes.\n.footnotes {\n  font-size: 12px !important;\n  p, li{\n    font-size: 12px !important;\n } \n}\n\n// Adjust with of social media icons were getting cut off\n.social-media-list{\n  .svg-icon {\n    width: 25px !important;\n    height: 23px !important;\n  }\n}\n\n// Make Anchor Links Appear Only on Hover\n\n.anchor-link {\n  opacity: 0;\n  padding-left: 0.375em;\n  \\-webkit-text-stroke: 1.75px white;\n  \\-webkit-transition: opacity 0.2s ease-in-out 0.1s;\n  \\-moz-transition: opacity 0.2s ease-in-out 0.1s;\n  \\-ms-transition: opacity 0.2s ease-in-out 0.1s;\n}\n\nh1:hover .anchor-link,\nh2:hover .anchor-link,\nh3:hover .anchor-link,\nh4:hover .anchor-link,\nh5:hover .anchor-link,\nh6:hover .anchor-link {\n  opacity: 1;\n}\n\n\n// category tags\n.category-tags {\n  margin-top: .25rem !important;\n  margin-bottom: .25rem !important;\n  font-size: 105%;\n}\n\n// Custom styling for homepage post previews\n.post-meta-title, .post-meta{\n  margin-top: .25em !important;\n  margin-bottom: .25em !important;\n  font-size: 105%;\n}\n\n.page-description {\n  margin-top: .5rem !important;\n  margin-bottom: .5rem !important;\n  color: #585858;\n  font-size: 115%;\n}\n\n// Custom styling for category tags\n.category-tags-icon {\n  font-size: 75% !important;\n  padding-left: 0.375em;\n  opacity: 35%;\n}\n.category-tags-link {\n  color:rgb(187, 129, 129) !important;\n  font-size: 13px !important;\n}\n\n// Search Page Styles\n.js-search-results {padding-top: 0.2rem;}\n.search-results-list-item {padding-bottom: 1rem;}\n.search-results-list-item .search-result-title {\n  font-size: 16px;\n  color: #d9230f;\n}\n.search-result-rel-url {color: silver;}\n.search-results-list-item a {display: block; color: #777;}\n.search-results-list-item a:hover, .search-results-list-item a:focus {text-decoration: none;}\n.search-results-list-item a:hover .search-result-title {text-decoration: underline;}\n\n.search-result-rel-date {\n  color: rgb(109, 120, 138);\n  font-size: 14px;\n}\n\n.search-result-preview {\n  color: #777;\n  font-size: 16px;\n  margin-top:.02rem !important;\n  margin-bottom:.02rem !important;\n}\n.search-result-highlight {\n  color: #2e0137;\n  font-weight:bold;\n}\n\ntable {\n  white-space: normal;\n  max-width: 100%;\n  font-size: 100%;\n  border:none;\n  th{\n    text-align: center! important;\n  }\n}\n\n// customize scrollbars\n::-webkit-scrollbar {\n  width: 14px;\n  height: 18px;\n}\n::-webkit-scrollbar-thumb {\n  height: 6px;\n  border: 4px solid rgba(0, 0, 0, 0);\n  background-clip: padding-box;\n  -webkit-border-radius: 7px;\n  background-color: #9D9D9D;\n  -webkit-box-shadow: inset -1px -1px 0px rgba(0, 0, 0, 0.05), inset 1px 1px 0px rgba(0, 0, 0, 0.05);\n}\n::-webkit-scrollbar-button {\n  width: 0;\n  height: 0;\n  display: none;\n}\n::-webkit-scrollbar-corner {\n  background-color: transparent;\n}\n\n// Wrap text outputs instead of horizontal scroll\n.output_text.output_execute_result {\n  pre{\n    white-space: pre-wrap;\n  }\n}\n\n\n// Handling large charts on mobile devices\n// @media only screen and (max-width: 1200px) {\n//   /* for mobile phone and tablet devices */\n//   .output_wrapper{\n//     overflow: scroll;\n//   }\n// }\n\n.svg-icon.orange{\n  width: 30px;\n  height: 23px;\n}\n\n.code_cell {\n  margin: 1.5rem 0px !important;\n}\n\npre code {\n  font-size: 15px !important;\n}\n",
-		"// Override Syntax Highlighting In Minima With the Dracula Theme: https://draculatheme.com/\n// If you wish to override any of this CSS, do so in _sass/minima/custom-styles.css\n \n$dt-gray-dark: #282a36;  // Background\n$dt-code-cell-background: #323443;\n$dt-gray: #44475a;       // Current Line & Selection\n$dt-gray-light: #f8f8f2; // Foreground\n$dt-blue: #6272a4;       // Comment\n$dt-cyan: #8be9fd;\n$dt-green: #50fa7b;\n$dt-orange: #ffb86c;\n$dt-pink: #ff79c6;\n$dt-purple: #bd93f9;\n$dt-red: #ff5555;\n$dt-yellow: #f1fa8c;\n$dt-green-light: rgb(172, 229, 145);\n\n.language-python + .language-plaintext {\n    border-left: 1px solid grey;\n    margin-left: 1rem !important;\n}\n\n// ensure dark background for code in markdown\n[class^=\"language-\"]:not(.language-plaintext) pre,\n[class^=\"language-\"]:not(.language-plaintext) code {\n    background-color: $dt-code-cell-background !important;\n    color: $dt-gray-light;\n}\n\n.language-python + .language-plaintext code { background-color: white !important; }\n.language-python + .language-plaintext pre  { background-color: white !important; }\n\n// for Jupyter Notebook HTML Code Cells modified from https://www.fast.ai/public/css/hyde.css\n\n.input_area pre, .input_area div {\n    margin-bottom:1.0rem !important;\n    margin-top:1.5rem !important;\n    padding-bottom:0 !important;\n    padding-top:0 !important;\n    background: #323443 !important;\n    -webkit-font-smoothing: antialiased;\n    text-rendering: optimizeLegibility;\n    font-family: Menlo, Monaco, Consolas, \"Lucida Console\", Roboto, Ubuntu, monospace;\n    border-radius: 5px;\n    font-size: 105%;\n}\n.output_area pre, .output_area div {\n    margin-bottom:1rem !important;\n    margin-top:0rem !important;\n    padding-bottom:0 !important;\n    padding-top:0 !important;\n}\n.input_area pre {\n    border-left: 1px solid lightcoral;\n}\n.output_area pre {\n    border-left: 1px solid grey;\n    margin-left: 1rem !important;\n    font-size: 16px;\n}\n\n.code_cell table { width: auto; }\n\n/* Dracula Theme v1.2.5\n *\n * https://github.com/zenorocha/dracula-theme\n *\n * Copyright 2016, All rights reserved\n *\n * Code licensed under the MIT license\n *\n */\n\n.highlight {\n    background: $dt-code-cell-background !important;\n    color: $dt-gray-light !important;\n    pre, code {\n     background: $dt-code-cell-background;\n     color: $dt-gray-light;\n     font-size: 110%;\n    }\n   \n    .hll,\n    .s,\n    .sa,\n    .sb,\n    .sc,\n    .dl,\n    .sd,\n    .s2,\n    .se,\n    .sh,\n    .si,\n    .sx,\n    .sr,\n    .s1,\n    .ss {\n         color:rgb(231, 153, 122);\n    }\n  \n    .go {\n      color: $dt-gray;\n    }\n  \n    .err,\n    .g,\n    .l,\n    .n,\n    .x,\n    .ge,\n    .gr,\n    .gh,\n    .gi,\n    .gp,\n    .gs,\n    .gu,\n    .gt,\n    .ld,\n    .no,\n    .nd,\n    .pi,\n    .ni,\n    .ne,\n    .nn,\n    .nx,\n    .py,\n    .w,\n    .bp {\n      color: $dt-gray-light;\n      background-color: $dt-code-cell-background !important;\n    }\n \n    .p {\n         font-weight: bold;\n         color: rgb(102, 217, 239);\n }\n  \n    .ge {\n      text-decoration: underline;\n    }\n  \n    .bp {\n      font-style: italic;\n    }\n  \n    .c,\n    .ch,\n    .cm,\n    .cpf,\n    .cs {\n      color: $dt-blue;\n    }\n\n    .c1 {\n      color: gray;\n    }\n  \n    .kd,\n    .kt,\n    .nb,\n    .nl,\n    .nv,\n    .vc,\n    .vg,\n    .vi,\n    .vm {\n      color: $dt-cyan;\n    }\n  \n    .kd,\n    .nb,\n    .nl,\n    .nv,\n    .vc,\n    .vg,\n    .vi,\n    .vm {\n      font-style: italic;\n    }\n  \n    .fm,\n    .na,\n    .nc,\n    .nf\n     {\n      color: $dt-green-light;\n    }\n  \n    .k,\n    .o,\n    .cp,\n    .kc,\n    .kn,\n    .kp,\n    .kr,\n    .nt,\n    .ow {\n      color: $dt-pink;\n    }\n \n    .kc {\n         color: $dt-green-light;   \n    }\n  \n    .m,\n    .mb,\n    .mf,\n    .mh,\n    .mi,\n    .mo,\n    .il {\n      color: $dt-purple;\n    }\n  \n    .gd {\n      color: $dt-red;\n    }\n}\n\np code{\n  font-size: 19px;\n}\n"
-	],
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-{
-  
-    
-        "post0": {
-            "title": "2023: A year in review",
-            "content": ". . While there haven’t been any blog posts in 2023 :wink:, it has been a productive year for the Policy Simulation Library (PSL) community and PSL Foundation! . We’ve continued to serve our mission through education and outreach efforts. We hosted 13 Demo Days in 2023, including presentations from individuals at the Congressional Budget Office, Allegheny County, NOAA, Johns Hopkins, QuantEcon, the City of New York, and other institutions. Archived videos of the Demo Days are available on our YouTube Channel. . In addition, we hosted an in person workshop at the National Tax Association’s annual conference in November. This event featured the PolicyEngine-US project and was lead by Max Ghenis and Nikhil Woodruff, co-founders of PolicyEngine. Attendees included individuals from the local area (Denver) and conference attendees, who represented academia, government, and think tanks. Max and Nikhil provided an overview of PolicyEngine and then walked attendees through a hands-on exercise using the PolicyEngine US tool, having them write code to generate custom plots in a Google Colab notebook. It was a lot of fun – and the pizza was decent too! . Speaking of PolicyEngine, this fiscally-sponsored project of PSL Foundation had a banner year in terms of fundraising and development. The group received several grants in 2023 and closed out the year with a large grant from Arnold Ventures. They also wrote an NSF grant proposal which they are waiting to hear back from. The group added an experienced nonprofit executive, Leigh Gibson, to their team. Leigh provides support with fundraising and operations, and she’s been instrumental in these efforts. In terms of software development, the PolicyEngine team has been able to greatly leverage volunteers (more than 60!) with Pavel Makarchuk coming on as Policy Modeling Manager to help coordinate these efforts. With their community, PolicyEngine has codified numerous US state tax and benefit policies and has developed a robust method to create synthetic data for use in policy analysis. Be on the lookout for a lot more from them in 2024. . QuantEcon, another fiscally sponsored project, has also made tremendous contributions to open source economics in 2023. Most importantly, they ran a very successful summer school in West Africa. In addition, they have continued make key contributions to software tools useful for teaching and training economics tools. These include Jupyteach, which Spencer Lyon shared in our Demo Day series. With their online materials, textbooks, and workshops around the world, QuantEcon is shaping how researchers and policy analysts employ economic tools to solve real-world problems. . PSL Foundation added a third fiscally sponsored project, Policy Change Index (PCI) in 2023. PCI was founded by Weifeng Zhong, a Senior Research Fellow at the Mercatus Center at George Mason University, and uses natural language processing and machine learning to predict changes in policy among autocratic regimes. PCI has had a very successful start with PCI-China, predicting policy changes in China, and PCI-Outbreak, predicting the extent of true COVID-19 case counts in China during the pandemic. Currently, they are extending their work to include predictive indices for Russia, North Korea, and Iran. PSL-F is excited for the opportunity to help support this important work. . Other cataloged projects have continued to be widely used in 2023. To note a few of these use cases, the United Nations has partnered with Richard Evans and Jason DeBacker, maintainers of OG-Core, to help bring the modeling platform to developing countries they are assisting. Tax Foundation’s Capital Cost Recovery model has been updated to 2023 and used in their widely cited 2023 Tax Competitiveness Index. And the Tax-Calculator and TaxData projects both continue to used by think tanks and researchers. . As 2023 comes to a close, we look forward to 2024. We’ll be launching a new PSLmodels.org website soon. And there’ll be many more events – we hope you join in. . From all of us at the PSL, best wishes for a happy and healthy New Year! . Resources: . PSL Models | PSL Foundation | PSL Twitter Feed | PSL YouTube channel | PSL on Open Collective | PSL Shop for PSL branded merchandise | .",
-            "url": "https://blog.pslmodels.org/2023-year-in-review",
-            "relUrl": "/2023-year-in-review",
-            "date": " • Dec 28, 2023"
-        }
-        
-    
-  
-    
-        ,"post1": {
-            "title": "2022: A year in review",
-            "content": ". . This has been another successful year for the Policy Simulation Library, whose great community of contributors continue to make innovative advances in open source policy analysis, and for the PSL Foundation, which supports the Library and its community. We are so thankful for all those who have made financial or technical contributions to the PSL this year! In this blog post, I want to take this time at the end of the year to reflect on a few of the highlights from 2022. . PolicyEngine, a PSL Foundation fiscally-sponsored project, launched PolicyEngine US in April and has since seen many use cases of the model (check out the PolicyEngine year-in-review here). PolicyEngine had begun by leveraging the OpenFisca platform, but has transitioned to their own-maintained PolicyEngine Core. PolicyEngine Core and their related projects (such as PolicyEngine US and PolicyEngine UK) already meet all the criteria set forth by the Policy Simulation Library. Keep an eye out for lots more excellent tax and benefit policy analysis tools from PolicyEngine in 2023 and beyond! . PSL Foundation has partnered with QuantEcon, acting as a fiscal sponsor for their projects that provide training and training materials for economic modeling and econometrics using open source tools. QuantEcon ran a massive open online class in India that had more than 1000 registrants in summer of 2022. They also ran an online course for over 100 students from universities in Africa in 2022. Further, with the funding received through their partnership with PSL Foundation, QuantEcon will continue these efforts in 2023 with a planned, in-person course in India. . PSL hosted its first in-person workshop in March. The workshop focused on open source tools for tax policy analysis including Tax-Calculator, Cost-of-Capital-Calculator, OG-USA, and PolicyEngine US. The PSL event was, appropriately enough, hosted at the MLK Memorial Library in DC. We filled the space with 30 attendees from think tanks, consultancies, and government agencies. The workshop was a great success and we look forward to hosting more in-person workshops in the future. . PSL’s bi-weekly Demo Day series continued throughout 2022, with 13 Demo Days this year. In these, we saw a wide array of presenters from institutions such as the Federal Reserve Bank of Atlanta, PolicyEngine, Tax Foundation, National Center for Children in Poverty, IZA Institute of Labor Economics, Channels, the University of South Carolina, the Center for Growth and Opportunity, and the American Enterprise Institute. You can go back and rewatch any of these presentations on YouTube. . It’s been a fantastic year and we expect even more from the community and PSL Foundation in 2023. PSL community members continue to interact several times each week on our public calls. Check out the events page and join us in the New Year! . From all of us at the PSL, best wishes for a happy and healthy New Year! . Resources: . PSL Foundation | PSL Twitter Feed | PSL YouTube channel | PSL on Open Collective | PSL Shop for PSL branded merchandise | .",
-            "url": "https://blog.pslmodels.org/2022-year-in-review",
-            "relUrl": "/2022-year-in-review",
-            "date": " • Dec 31, 2022"
-        }
-        
-    
-  
-    
-        ,"post2": {
-            "title": "Demo Day: How does targeted cash assistance affect incentives to work?",
-            "content": ". In this week’s Demo Day, I shared my paper published at the Center for Growth and Opportunity in June. “How does targeted cash assistance affect incentives to work?” analyzed a program Mayor Sumbul Siddiqui proposed in Cambridge, Massachusetts to provide $500 per month for 18 months to all families with dependents and income below 200% of the poverty line. . Targeted programs like these are common in guaranteed income pilots, and in some enacted policies, and I find that it would cost-effectively reduce poverty: if expanded to Massachusetts, it would cost $1.2 billion per year and cut child poverty 42%. . However, that targeting comes at a cost. Using the OpenFisca US microsimulation model (supported by the Center for Growth and Opportunity and cataloged by the Policy Simulation Library), I find that the program would deepen an existing welfare cliff at 200% of the poverty line. For example, a family of four would lose over $19,000 total—$9,000 from the cash assistance and $10,000 from other benefits—once they earn a dollar above 200% of the poverty line (about $55,000). To recover those lost benefits, they would have to earn an additional $26,000, a range I call the “earnings dead zone”. . My presentation reviews these trends in both slides and the PolicyEngine US app for computing the impacts of tax and benefit policy. For example, I show how repealing the SNAP emergency allotment would smooth out welfare cliffs, while reducing resources available to low-income families, and how a universal child allowance avoids work disincentives while less cost-effectively reducing poverty. . Policymakers face trade-offs between equity and efficiency, and typically labor supply responses consider marginal tax rates. With their infinite marginal tax rates, welfare cliffs are a less explored area, even though they surface in several parts of the tax and benefit system. This paper makes a start, but more research is yet to be done. .",
-            "url": "https://blog.pslmodels.org/demo-day-cambridge-cash-assistance",
-            "relUrl": "/demo-day-cambridge-cash-assistance",
-            "date": " • Jul 14, 2022"
-        }
-        
-    
-  
-    
-        ,"post3": {
-            "title": "Demo Day: Getting Started with GitHub",
-            "content": ". Git and GitHub often present themselves as barriers to entry to would-be contributors to PSL projects, even for those who are otherwise experienced with policy modeling. But these tools are critical to collaboration on open source projects. In the Demo Day video linked above, I cover some of the basics to get set up and begin contributing to an open source project. . There are four steps I outline: . Create a “fork” of the repository you are interested in. A fork is a copy of the source code that resides on GitHub (i.e., in the cloud). A fork gives you control over a copy of the source code. You will be able to merge in changes to the code on this fork, even if you don’t have permissions to do so with the original repository. | “Clone” the fork. Cloning will download a copy of the source code from your fork onto your local machine. But cloning is more than just downloading the source code. It will include the version history of the code and automatically create a link between the local files and the remote files on your fork. | Configure your local files to talk to both your fork (which has a default name of origin) and the original repository you forked from (which typically has the default name of upstream). Do this by using your command prompt or terminal to navigate to the directory you just cloned. From there, run: git remote add upstream URL_to_original_repo.git . And check that this worked by giving the command: . git remote -v . | If things worked, you should see URLs to your fork and the upstream repository with “(fetch)” and “(push)” by them More info on this is in the Git docs. . Now that you have copies of the source code on your fork and on your local machine, you are ready to begin contributing. As you make changes to the source code, you’ll want to work on development branches. Branches are copies of the code. Ideally, you keep your “main” (or “master”) branch clean (i.e., your best version of the code) and develop the code on branches. When you’ve completed the development work (e.g., adding a new feature) you will them merge this into the “main” branch. | I hope this helps you get started contributing to open source projects. Git and GitHub are valuable tools and there is lots more to learn, but these basics will get you going. For more information, see the links below. If you want to get started working with a project in the Library, feel free to reach out to me through the relevant repo (@jdebacker on GitHub) or drop into a PSL Community Call (dates on the PSL Calendar). . Resources: . PSL Git Tutorial | Git Basics | .",
-            "url": "https://blog.pslmodels.org/demo-day-github",
-            "relUrl": "/demo-day-github",
-            "date": " • Jun 28, 2022"
-        }
-        
-    
-  
-    
-        ,"post4": {
-            "title": "Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator",
-            "content": ". In the Demo Day video shared here, I show how to use open source tools to analyze international corporate tax competitiveness. The two main tools illustrated are the Cost-of-Capital-Calculator (CCC), a model to compute measures of the tax burden on new investments, and Tax Foundation’s International Tax Competitiveness Index (ITCI). . Tax Foundation has made many helpful resources available online. Their measures of international business tax policy are a great example of this. The ICTI outputs and inputs are all well documented, with source code to reproduce results available on GitHub. . I plug Tax Foundation’s country-by-country data into CCC functions using it’s Python API. Because CCC is designed to flexibly take array or scalar data, operating on rows of tabular data, such as that in the ITCI, is relatively straight-forward. The Google Colab notebook I walk through in this Demo Day, can be a helpful example to follow if you’d like to do something similar to this with the Tax Foundation data - or your own data source. From the basic building blocks there (reading in data, calling CCC functions), you can extend the analysis in a number of ways. For example adding additional years of data (Tax Foundation posts their data back to 2014), modifying economic assumptions, or creating counter-factual policy experiments across sets of countries. . If you find this example useful, or have questions or suggestions about this type of analysis, please feel free to reach out to me. . Resources: . Colab Notebook | Tax Foundation International Tax Competitiveness Index 2021 | GitHub repo for Tax Foundation ITCI data | Cost-of-Capital-Calculator documentation | .",
-            "url": "https://blog.pslmodels.org/demo-day-ccc-international",
-            "relUrl": "/demo-day-ccc-international",
-            "date": " • Apr 18, 2022"
-        }
-        
-    
-  
-    
-        ,"post5": {
-            "title": "Demo Day: Modeling taxes and benefits with the PolicyEngine US web app",
-            "content": ". PolicyEngine is a nonprofit that builds free, open-source software to compute the impact of public policy. After launching our UK app in October 2021, we’ve just launched our US app, which calculates households’ federal taxes and several benefit programs, both under current law and under customizable policy reforms. . In this Demo Day, I provide background on PolicyEngine and demonstrate how to use PolicyEngine US (a Policy Simulation Library cataloged model) to answer a novel policy question: . How would doubling both (a) the Child Tax Credit and (b) the Supplemental Nutrition Assistance Program (SNAP) net income limit affect a single parent in California with $1,000 monthly rent and $50 monthly broadband costs? . By bringing together tax and benefit models into a web interface, we can answer this question quickly without programming experience, as well as an unlimited array of questions like it. The result is a table breaking down the household’s net income by program, as well as graphs of net income and marginal tax rates as the household’s earnings vary. . I close with a quick demo of PolicyEngine UK, which adds society-wide results like the impact of reforms on the budget, poverty, and inequality, as well as contributed policy parameters. We’re planning to bring those features to PolicyEngine US, along with state tax and benefit programs in all 50 states, over the next two years (if not sooner). . Feel free to explore the app and reach out with any questions at max@policyengine.org. . Resources: . PolicyEngine US | Presentation slides | PolicyEngine blog post on launching PolicyEngine US | .",
-            "url": "https://blog.pslmodels.org/demo-day-policyengine-us",
-            "relUrl": "/demo-day-policyengine-us",
-            "date": " • Apr 12, 2022"
-        }
-        
-    
-  
-    
-        ,"post6": {
-            "title": "Policy Simulation Library DC Workshop: Open source tools for analyzing tax policy",
-            "content": ". . The Policy Simulation Library is hosting a workshop in Washington, DC on March 25 on open source tools for the analysis of tax policy. Participants will learn how to use open source models from the Library for revenue estimation, distributional analysis, and to simulate economic impacts of tax policy. The workshop is intended to be a hands-on experience and participants can expect to leave with the required software, documentation, and knowledge to continue using these tools. All models in the workshop are written in the Python programming language–familiarity with the language is helpful, but not required. . Workshop Schedule: . 8:15-8:45a: Breakfast | 8:45-9:00a: Introduction | 9:00-9:50a: Using Tax-Calculator for revenue estimation and distributional analysis (Matt Jensen) | 10:00-10:50a: Estimating effective tax rates on investment with Cost-of-Capital-Calculator (Jason DeBacker) | 11:00-11:50a: Macroeconomic modeling of fiscal policy with OG-Core and OG-USA (Richard W. Evans) | noon-1:00p: Lunch and demonstration of PolicyEngine (Max Ghenis) | . The workshop will be held at the Martin Luther King Jr. Memorial Library in Washington, DC. Participants are expected to arrive by 8:30am and the program will conclude at 1:00pm. Breakfast and lunch will be provided. PSL Foundation is sponsoring the event and there is no cost to attend. Attendance is limited to 30 in order to make this a dynamic and interactive workshop. . To register, please use this Google Form. Registration will close March 11. Participants will be expected to bring a laptop to the workshop where they can interact with the software in real time with the instructors. Registered participants will receive an email before the event with a list of software to install before the workshop. . Please feel free to share this invitation with your colleagues. . Questions about the workshop can be directed to Jason DeBacker at jason.debacker@gmail.com. .",
-            "url": "https://blog.pslmodels.org/DC-workshop",
-            "relUrl": "/DC-workshop",
-            "date": " • Mar 3, 2022"
-        }
-        
-    
-  
-    
-        ,"post7": {
-            "title": "2021: A year in review",
-            "content": ". . As 2021 winds down, I wanted to take a few minutes to reflect on the Policy Simulation Library’s efforts over the past year. With an amazing community of contributors, supporters, and users, PSL has been able to make a real impact in 2021. . The library saw two new projects achieve “cataloged” status: Tax Foundation’s Capital Cost Recovery model and the Federal Reserve Bank of New York’s DSGE.jl model. Both models satisfy all the the PSL criteria for transparency and reproducibility. Both are also written entirely in open source software: the Capital Cost Recovery model is in R and the DSGE model in Julia. . An exciting new project to join the Library this year is PolicyEngine. PolicyEngine is building open source tax and benefit mircosimulation models and very user-friendly interfaces to these models. The goal of this project is to take policy analysis to the masses through intuitive web and mobile interfaces for policy models. The UK version of the PolicyEngine app has already seen use from politicians interested in reforming the tax and benefit system in the UK. . Another excellent new addition to the library is the Federal-State Tax Project. This project provides data imputation tools to allow for state tax data that are representative of each state as well as federal totals. These datasets can then be used in microsimulation models, such as Tax-Calculator to study the impact of federal tax laws across the states. Matt Jensen and Don Boyd have published several pieces with these tools, including in State Tax Notes . PSL Foundation became an official business entity in 2021. While still awaiting a letter of determination for 501(c)(3) status from the IRS, PSL Foundation was able to raise more than $25,000 in the last few months of 2021 to support open source policy analysis! . PSL community members continued to interact several times each week in our public calls. The PSL Shop was launched in 2021 so that anyone can get themselves some PSL swag (with some of each purchase going back to the PSL Foundation to support the Library). In addition, PSL hosted 20 Demo Day presentations from 11 different presenters! These short talks covered everything from new projects to interesting applications of some of the first projects to join the Library, as well as general open source tools. . As in past years, PSL cataloged and incubating models were found to be of great use in current policy debates. Whether it was the ARPA, Biden administration proposals to expand the CTC, or California’s Basic Income Bill, the accessibility and ability to reproduce results from these open source projects has made them a boon to policy analysts. . We are looking forward to a great 2022! We expect the Library to continue to grow, foresee many interesting and helpful Demo Days, and are planning a DC PSL Workshop for March 2022. We hope to see you around these or other events! . Best wishes from PSL for a happy and healthy New Year! . Resources: . PSL Foundation | PSL Twitter Feed | PSL YouTube channel | PSL on Open Collective | .",
-            "url": "https://blog.pslmodels.org/2021-year-in-review",
-            "relUrl": "/2021-year-in-review",
-            "date": " • Dec 28, 2021"
-        }
-        
-    
-  
-    
-        ,"post8": {
-            "title": "Demo Day: Using synthimpute for data fusion",
-            "content": ". Suppose a policy analyst sought to estimate the impact of a policy that changed income tax rates and benefit rules while also adding a progressive wealth tax. The standard approach is to use a microsimulation model, where the rules are programmed as code, and then to run that program over a representative sample of households. Unfortunately, no single US government survey captures all the households characteristics needed to analyze this policy; in particular, the reliable tax and benefit information lies in surveys like the Current Population Survey (CPS), while wealth lies in the Survey of Consumer Finances (SCF). . Assuming the analyst wanted to start with the CPS, they have several options to estimate wealth for households to levy the progressive wealth tax. Two typical approaches include: . Linear regression, predicting wealth from other household characteristics common to the CPS and SCF. | Matching, in which each CPS household is matched with the most similar household in the SCF. | Neither of these approaches, however, aim to estimate the distribution of wealth conditional on other characteristics. Linear regression explicitly estimates the mean prediction, but that could miss the tails of wealth from whom most of the wealth tax revenue will be collected. . Instead, the analyst could apply quantile regression to estimate the distribution of wealth conditional on other characteristics, and then measure the effectiveness of the estimation using quantile loss. . In this Demo Day, I present the concepts of microsimulation, imputation, and quantile loss to motivate the synthimpute Python package I’ve developed with my PolicyEngine colleague Nikhil Woodruff. In an experiment predicting wealth on a holdout set from the SCF, my former colleague Deepak Singh and I found that random forests significantly outperform OLS and matching for quantile regression, and this is the approach applied in synthimpute for both data fusion and data synthesis. The synthimpute API will be familiar to users of scikit-learn and statsmodels , with the difference being that synthimpute ‘s rf_impute function returns a random value from the predicted distribution; it can also skew the predictions to meet a target total. . We’ve used synthimpute to fuse data for research reports at the UBI Center and to enhance the PolicyEngine web app for UK tax and benefit simulation, and we welcome new users and contributors. Feel free to explore the repository or contact me with questions at max@policyengine.org. . Resources: . synthimpute package on GitHub | Presentation slides | UBI Center report on land value taxation in the UK, using synthimpute to impute land value from the UK Wealth and Assets Survey to the Family Resources Survey | PolicyEngine UK carbon tax example, using synthimpute to impute carbon emissions from the Living Costs and Food Survey to the Family Resources Survey | Notebook comparing random forests to matching and other techniques using a holdout set from the US Survey of Consumer Finances | My blog post on quantile regression for Towards Data Science, which laid the groundwork for synthimpute | .",
-            "url": "https://blog.pslmodels.org/demo-day-synthimpute",
-            "relUrl": "/demo-day-synthimpute",
-            "date": " • Dec 8, 2021"
-        }
-        
-    
-  
-    
-        ,"post9": {
-            "title": "Demo Day: The OG-Core platform",
-            "content": ". The OG-Core model is a general equilibrium, overlapping generations (OG) model suitable for evaluating fiscal policy. Since the work of Alan Auerbach and Laurence Kotlikoff in the 1980s, this class of model has become a standard in the macroeconomic analysis of tax and spending policy. This is for good reason. OG models are able to capture the impacts of taxes and spending in the short and long run, examine incidence of policy across generations of people (not just short run or steady state analysis of a cross-section of the economy), and capture important economic dynamics (e.g., crowding out effects of deficit-financed policy). . In the PSL Demo Day presentation linked above, I cover the basics of OG-Core: its history, its API, and how country-specific models can use OG-Core as a dependency. In brief, OG-Core provides a general overlapping generations framework, from which parameters can be calibrated to represent particular economies. Think of it this way: an economic model is just a set of parameters plus a system of equations. OG-Core spells out all of the equations to represent an economy with heterogeneous agents, production and government sectors, open economy options, and detailed policy rules. OG-Core also includes default values for all parameters, along with parameter metadata and parameter validation rules. A country specific application is then just a particular parameterization of the general OG-Core model. . As an example of a country-specific application, one can look at the OG-USA model. This model provides a calibration of OG-Core to the United States. The source code in that project allows one to go from raw data sources to the estimation and calibration procedures used to determine parameter values representing the United States, to parameter values in formats suitable for use in OG-Core. Country-specific models like OG-USA include (where available) links to microsimulation models of tax and spending programs to allow detailed microdata of actual and counterfactual policies to inform the net tax-transfer functions used in the OG-Core model. For those interested in building their own country-specific model, the OG-USA project provides a good example to work from. . We encourage you to take a look at OG-Core and related projects. New contributions and applications are always welcome. If you have questions or comments, reach out through the relevant repositories on Github to me, @jdebacker, or Rick Evans, @rickecon. . Resources: . OG-Core documentation | OG-USA documentation package for unit testing in Python | Tax-Calculator documentation | OG-UK repository | OpenFisca-UK repository | Slides from the Demo Day presentation | .",
-            "url": "https://blog.pslmodels.org/demo-day-og-core",
-            "relUrl": "/demo-day-og-core",
-            "date": " • Nov 1, 2021"
-        }
-        
-    
-  
-    
-        ,"post10": {
-            "title": "Demo Day: Deploying apps on Compute Studio",
-            "content": ". . Compute Studio (C/S) is a platform for publishing and sharing computational models and data visualizations. In this demo day, I show how to publish your own project on C/S using the new automated deployments feature. You can find an in depth guide to publishing on C/S in the developer docs. . C/S supports two types of projects: models and data visualizations. Models are fed some inputs and return a result. Data visualizations are web servers backed by popular open-source libraries like Bokeh, Dash, or Streamlit. Models are good for long-running processes and producing archivable results that can be shared and returned to easily. Data visualizations are good for highly interactive and custom user experiences. . Now that you’ve checked out the developer docs and set up your model or data-viz, you can head over to the C/S publishing page https://compute.studio/new/ to publish your project. Note that this page is still very much under construction and may look different in a few weeks. . . Next, you will be sent to the second stage in the publish flow where you will provide more details on how to connect your project on C/S: . . Clicking “Connect App” will take you to the project home page: . . Go to the “Settings” button in the top-right corner and this will take you to the project dashboard where you can modify everything from the social preview of your project to the amount of compute resources it needs: . . The “Builds” link in the sidebar will take you to the builds dashboard where you can create your first build: . . It’s time to create the first build. You can do so by clicking “New Build”. This will take you to the build status page. While the build is being scheduled, the page will look like this: . . You can click the “Build History” link and it will show that the build has been started: . . The build status page should be updated at this point and will look something like this: . . C/S automated deployments are built on top of Github Actions. Unfortunately, the logs in Github Actions are not available through the Github API until after the workflow is completely finished. The build status dashboard will update as the build progresses and once it’s done, you will have full access to the logs from the build. These will contain outputs from installing your project and the outputs from your project’s tests. . In this case, the build failed. We can inspect the logs to see that an import error caused the failure: . . . I pushed an update to my fork of Tax-Cruncher on Github and restarted the build by clicking “Failure. Start new Build”. The next build succeeded and we can click “Release” to publish the project: . . The builds dashboard now shows the two builds: . . Finally, let’s go run our new model: . . It may take a few seconds for the page to load. This is because the model code and all of its dependencies are being loaded onto the C/S servers for the first time: . . The steps for publishing a data visualization are very similar. The main idea is that you tell C/S what Python file your app lives in and C/S will know how to run it given your data visualization technology choice. .",
-            "url": "https://blog.pslmodels.org/demo-day-cs-auto-deploy",
-            "relUrl": "/demo-day-cs-auto-deploy",
-            "date": " • Sep 20, 2021"
-        }
-        
-    
-  
-    
-        ,"post11": {
-            "title": "Demo Day: Unit testing for open source projects",
-            "content": ". Unit testing is the testing of individual units or functions of a software application. This differs from regression testing that focuses on the verification of final outputs. Instead, unit testing tests each smallest testable component of your code. This helps to more easily identify and trace errors in the code. . Writing unit tests is good practice, though not one that’s always followed. The biggest barrier to writing unit tests is that doing so takes time. You might wonder “why am I testing code that runs?” But there are a number benefits to writing unit tests: . It ensures that the code does what you expect it to do | You’ll better understand what your code is doing | You will reduce time tracking down bugs in your code | . Often, writing unit tests will save you time in the longer run because it reduces debugging time and because it forces you to think more about what your code does, which often leads to the development of more efficient code. And for open source projects, or projects with many contributors, writing unit tests is important in reducing the likelihood that errors are introduced into your code. This is why the PSL catalog criteria requires projects to provide at least some level of unit testing. . In the PSL Demo Day video linked above, I illustrate how to implement unit tests in R using the testthat package. There are essentially three steps to this process: . Create a directory to put your testing script in, e.g., a folder called tests | Create one or more scripts that define your tests. Each test is represented as a call of the test_that function and contain an statement that will evaluate as true or false (e.g., you may use the expect_equal function to verify that a function returns expected values given certain inputs). | You will want to use test in the name of these tests scripts as well as something descriptive of what is tested. | . | Create a script that will run your tests. Here you’ll need to import the testthat package and you’ll need to call the script(s) you are testing to load their functions. | Then you’ll use the test_dir function to pass the directory in which the script(s) you created in Step 2 reside. | . | Check out the video to see examples of how each of these steps is executed. I’ve also found this blog post on unit tests with testthat to be helpful. . Unit testing in Python seems to be more developed and straightforward with the excellent pytest package. While pytest offers many options for parameterizing tests, running tests in parallel, and more, the basic steps remain the same as those outlined above: . Create a directory for your test modules (call this folder tests as pytest will look for that name). | Create test modules that define each test Tests are defined much like any other function in Python, the but will involve some assertion statement is triggered upon test failure. | You will want to use test in the name of these tests modules as well as something descriptive of what is tested. | . | You won’t need to create a script to run your tests as with testthat, but you may create a pytest.ini file to customize your tests options. | That’s about it to get started writing unit tests for your code. PSL cataloged projects provide many excellent examples of a variety of unit tests, so search them for examples to build from. In a future Demo Day and blog post, we’ll talk about continuous integration testing to help get even more out of you unit tests. . Resources: . testthat package for unit testing in R | pytest package for unit testing in Python | PSL catalog criteria | Unit tests for the capital-cost-recovery model | .",
-            "url": "https://blog.pslmodels.org/demo-day-unit-testing",
-            "relUrl": "/demo-day-unit-testing",
-            "date": " • Aug 9, 2021"
-        }
-        
-    
-  
-    
-        ,"post12": {
-            "title": "Demo Day: Constructing tax data for the 50 states",
-            "content": ". Federal income tax reform impacts can vary dramatically across states. The cap on state and local tax deductions (SALT) is a well-known example, but other policies also have differential effects because important tax-relevant features vary across states such as the income distribution, relative importance of wage, business, and retirement income, and family size and structure. Analyzing how policy impacts vary across states requires data that faithfully represent the characteristics of the 50 states. . This Demo Day described a method and software for constructing state weights for microdata files that (1) come as close as possible to targets for individual states, while (2) ensuring that the state weights for each tax record sum to its national weight. The latter objective ensures that the sum of state impacts for a tax reform equals the national impact. . This project developed state weights for a data file with more than 200,000 microdata records. The weighted data file comes within 0.01% of desired values for more than 95% of approximately 10,000 targets. . The goal of the slides and video was to enable a motivated Python-skilled user of the PSL TaxData and Tax-Calculator projects to reproduce project results: 50-state weights for TaxData’s primary output, the puf.csv microdata file (based primarily on an IRS Public Use File), using early-stage open-source software developed in the project. Thus, the demo is technical and focused on nuts and bolts. . The methods and software can also be used to: . Create geographic-area weights for other microdata files | Apportion state weights to Congressional Districts or counties, if suitable targets can be developed | Create state-specific microdata files suitable for modeling state income taxes | . The main topics covered in the slides and video are: . Creating national and state targets from IRS summary data | Preparing a national microdata file for state weighting | Approaches to constructing geographic weights | Running software that implements the Poisson-modeling approach used in the project | Measures of quality of the results | .",
-            "url": "https://blog.pslmodels.org/demo-day-constructing-tax-data-for-the-50-states",
-            "relUrl": "/demo-day-constructing-tax-data-for-the-50-states",
-            "date": " • Jul 16, 2021"
-        }
-        
-    
-  
-    
-        ,"post13": {
-            "title": "Demo Day: Using the TaxBrain Python API",
-            "content": ". . The TaxBrain project was primarily created to serve as the backend of the Tax-Brain web-application. But at its core, TaxBrain is a Python package that greatly simplifies tax policy analysis. For this PSL Demo-Day, I demonstrated TaxBrain’s capabilities as a standalone package, and how to use it to produce high-level summaries of the revenue impacts of proposed tax policies. The Jupyter Notebook from the presentation can be found here. . TaxBrain’s Python API allows you to run a full analysis of income tax policies in just three lines of code: . from taxbrain import TaxBrain tb = TaxBrain(START_YEAR, END_YEAR, use_cps=True, reform=REFORM_POLICY) tb.run() . Where START_YEAR and END_YEAR are the first and last years, respectively, of the analysis; use_cps is a boolean indicator that you want to use the CPS-based microdata file prepared for use with Tax-Calculator; and REFORM_POLICY is either a JSON file or Python dictionary that specifies a reform suitable for Tax-Calculator. The forthcoming release of TaxBrain will also include a feature that allows you to perform a stacked revenue analysis as well. The inspiration for this feature was presented by Jason DeBacker in a previous demo-day. . Once TaxBrain has been run, there are a number of methods and functions included in the package to create tables and plots to summarize the results. I used the Biden 2020 campaign proposal in the demo and the resulting figures are below. The first is a “volcano plot” that makes it easy to see the magnitude of the change in tax liability individuals across the income distribution face. Each dot represents a tax unit, and the x and y variables can be customized based on the user’s needs. . . The second gives a higher-level look at how taxes change in each income bin. It breaks down what percentage of each income bin faces a tax increase or decrease, and the size of that change. . . The final plot shown in the demo simply shows tax liabilities by year over the budget window. . . The last feature I showed was TaxBrain’s automated reports. TaxBrain uses saved results and an included report template to write a report summarizing the findings of your simulation. The reports include tables and figures similar to what you may find in similar write ups by the Joint Committee on Taxation or Tax Policy Center including a summary of significant changes caused by the reform, and all you need is one line of code: . report(tb, name=&#39;Biden Proposal&#39;, outdir=&#39;biden&#39;, author=&#39;Anderson Frailey&#39;) . The above code will save a PDF copy of the report in a directory called biden along with PNG files for each of the graphs created and the raw Markdown text used for the report, which you can then edit as needed if you would like to add content to the report that is not already included. Screenshots of the default report are included below. . . There are of course downsides to using TaxBrain instead of Tax-Calculator directly. Specifically, it’s more difficult, and sometimes impossible, to perform custom tasks like modeling a feature of the tax code that hasn’t been added to Tax-Calculator yet or advanced work with marginal tax rates. But for day-to-day tax modeling, the TaxBrain Python package can significantly simply any workflow. . Resources: . Tax-Brain GitHub repo | Tax-Brain Documentation | .",
-            "url": "https://blog.pslmodels.org/demo-day-tax-brain-python-api",
-            "relUrl": "/demo-day-tax-brain-python-api",
-            "date": " • Jun 14, 2021"
-        }
-        
-    
-  
-    
-        ,"post14": {
-            "title": "Demo Day: Updating Jupyter Book documentation with GitHub Actions",
-            "content": ". Open source projects must maintain clear and up-to-date documentation in order to attract users and contributors. Because of this, PSL sets minimum standards for documentation among cataloged projects in its model criteria. A recent innovation in executable books, Jupyter Book, has provided an excellent format for model documentation and has been widely adopted by PSL projects (see for example OG-USA, Tax-Brain, Tax-Calculator). . Jupyter Book allows one to write documents with executable code and text together, as in Jupyter notebooks. But Jupyter Book pushes this further by allowing documents with multiple sections, better integration of TeX for symbols and equations, BibTex style references and citations, links between sections, and Sphinx integration (for auto-built documentation of model APIs from source code). Importantly for sharing documentation, Jupyter Books can easily be compiled to HTML, PDF, or other formats. Portions of a Jupyter Book that contain executable code can be downloaded as Jupyter Notebooks or opened in Google Colab or binder . The Jupyter Book documentation is excellent and will help you get started creating your “book” (tip: pay close attention to formatting details, including proper whitespace). What I do here is outline how you can easily deploy your documentation to the web and keep it up-to-date with your project. . I start from the assumption that you have the source files to build your Jupyter Book checked into the main branch of your project (these maybe yml , md , rst , ipynb or other files). For version control purposes and to keep your repo trim, you generally don’t want to check the built documentation files to this branch (tip: consider adding the folder these files will go to (e.g., /_build to your .gitignore ). When these files are in place and you can successfully build your book locally, it’s time for the first step. . Step 1: Add two GH Actions to your project’s workflow: . An action to check that your documentation files build without an error. I like to run this on each push to a PR. The action won’t hang on warnings, but will fail if your Jupyter Book doesn’t build at all. An example of this action from the OG-USA repo is here: | name: Check that docs build on: [push, pull_request] jobs: build: runs-on: ubuntu-latest steps: - name: Checkout uses: actions/checkout@v2 # If you&#39;re using actions/checkout@v2 you must set persist-credentials to false in most cases for the deployment to work correctly. with: persist-credentials: false - name: Setup Miniconda uses: conda-incubator/setup-miniconda@v2 with: activate-environment: ogusa-dev environment-file: environment.yml python-version: 3.7 auto-activate-base: false - name: Build # Build Jupyter Book shell: bash -l {0} run: | pip install jupyter-book pip install sphinxcontrib-bibtex==1.0.0 pip install -e . cd docs jb build ./book . To use this in your repo, you’ll just need to change a few settings such as the name of the environment and perhaps the Python version and path to the book source files. Note that in the above yml file sphinxcontrib-bibtex is pinned. You maybe able to unpin this, but OG-USA needed this pin for documentation to compile property due to changes in the jupyter-book and sphinxcontrib-bibtex packages. . An action that builds and deploys the Jupyter Book to GH Pages. The OG-USA project uses the deploy action from James Ives in this action. This is something that you will want to run when PRs are merged into your main branch so that the documentation is kept up-to-date with the project. To modify this action for your repo, you’ll need to change the repo name, the environment name, and potentially the Python version, branch name, and path to the book source files. | Step 2: Once the action in (2) above is run, your compiled Jupyter Book docs will be pushed to a gh-pages branch in your repository (the action will create this branch for you if it doesn’t already exist). At this point, you should be able to see your docs at the url https://GH_org_name.github.io/Repo_name . But it probably won’t look very good until you complete this next step. To have your Jupyter Book render on the web as you see it on your machine, you will want to push and merge an empty file with the name .nojekyll into your repo’s gh-pages branch. . That’s it! With these actions, you’ll be sure that your book continues to compile and a new version will be published to the web with with each merge to your main branch, ensuring that your documentation stays up-to-date. . Some additional tips: . Use Sphinx to document your projects API. By doing so you’ll automate an important part of your project’s documentation – as long as the docstrings are updated when the source code is, the Jupyter Book you are publishing to the web will be kept in sync with no additional work needed. | You can have your gh-pages-hosted documentation point to a custom URL. | Project maintainers should ensure that docs are updated with PRs that are relevant (e.g., if the PR changes an the source code affecting a user interface, then documentation showing example usage should be updated) and help contributors make the necessary changes to the documentation source files. | .",
-            "url": "https://blog.pslmodels.org/demo-day-jupyter-book-deploy",
-            "relUrl": "/demo-day-jupyter-book-deploy",
-            "date": " • May 17, 2021"
-        }
-        
-    
-  
-    
-        ,"post15": {
-            "title": "Demo Day: Producing stacked revenue estimates with the Tax-Calculator Python API",
-            "content": ". It’s often useful to be able to identify the effects of specific provisions individually and not just the overall impact of a proposal with many provisions. Indeed, when revenue estimates of tax law changes are reported (such as this JCT analysis of the American Rescue Plan Act of 2021), they are typically reported on a provision-by-provision basis. Finding the provision-by-provision revenue estimates is cumbersome with the Tax-Brain web application both because it’s hard to iterate over many provisions and because the order matters when stacking estimates, so that one needs to keep this order in mind as parameter values are updated for each additional provision in a full proposal. . In the PSL Demo Day on April 5, 2021, I show how to use the Python API of Tax-Calculator to efficiently produce stacked revenue estimates. In fact, after some initial setup, this can be done with just 12 lines of code (plus a few more to make the output look nice). The Google Colab notebook that illustrates this approach can be found at this link, but here I’ll walk through the four steps that are involved: . Divide up the full proposal into strings of JSON text that contain each provision you want to analyze. My example breaks up the Biden 2020 campaign proposal into seven provisions, but this is illustrative and you can make more or less provisions depending on the detail you would like to see. | Create a dictionary that contains, as its values, the JSON strings. A couple notes on this. First, the dictionary keys should be descriptive of the provisions as they will become the labels for each provision in the final table of revenue estimates we produce. Second, order matters here. You’ll want to be sure the current law baseline is first (the value for this will be an empty dictionary). Then you specify the provisions. The order you specify will likely affect your revenue estimates from a given provision (for instance, expanding/restricting a deduction has a larger revenue effect when rates are higher), but there are not hard and fast rules on the “right” order. Traditionally, rate changes are stacked first and tax expenditures later in the order. | Iterate over this dictionary. With a dictionary of provisions in hand, we can write a “for loop” to iterate over the provision, simulating the Tax-Calculator model at each step. Note that when the Policy class object in Tax-Calculator is modified, it only needs to be told the changes in tax law parameters relative to its current state. In other words, when we are stacking provisions, estimating the incremental effect of each, you can think of the Policy object having a baseline policy that is represented by the current law baseline plus all provisions that have been analyzed before the provision at the current iteration. The Policy class was created in this way so that one can easily represent policy changes, requiring the user to only input the set of parameters that are modified, not every single parameter’s value under the hypothetical policy. But this also makes it parsimonious to stack provisions as we are doing here. Notice that the JSON strings for each provision (created in Step 1) can be specified independent of the stacking order. We only needed to slice the full set of proposals into discrete chunks, we didn’t need to worry about creating specifications of cumulative policy changes. | Format output for presentation. After we’ve run a Tax-Calculator simulation for the current law baseline plus each provision (and each year in the budget window), we’ve got all the output we need. With this output, we can quickly create a table that will nicely present our stacked revenue estimate. One good check to do here is to create totals across all provisions and compare this to the simulated revenue effects of running the full set of proposals in one go. This check helps to ensure that you didn’t make an error in specifying your JSON strings. For example, it’s easy to leave out one or more provisions, especially if there are many. | I hope this provides a helpful template for your own analysis. Note that one can modify this code in several useful ways. For example, within the for-loops, the Behavioral-Responses can be called to produce revenue estimates that take into account behavioral feedback. Or one could store the individual income tax and payroll tax revenue impacts separately (rather than return the combined values as in the example notebook). Additional outputs (even the full set of microdata after each provision is applied) can be stored for even more analysis. . In the future, look for Tax-Brain to add stacked revenue estimates to its capabilities. It’ll still be important for users to carve up their full list of policy changes into sets of provisions as we did in Steps 1 and 2 above, but Tax-Brain will then take care of the rest behind the scenes. . Resources: . Colab Notebook with example | Biden campaign reform file in PSL Examples | .",
-            "url": "https://blog.pslmodels.org/demo-day-stacked-revenue-estimates",
-            "relUrl": "/demo-day-stacked-revenue-estimates",
-            "date": " • Apr 5, 2021"
-        }
-        
-    
-  
-    
-        ,"post16": {
-            "title": "Demo Day: Stitching together apps on Compute Studio",
-            "content": ". In Demo Day 8, I talked about connecting multiple apps on Compute Studio with PSL Stitch. The source code for PSL stitch can be found in this repository. . Stitch is composed of three components: . A python package that can be run like a normal Python package. | A RESTful API built with FastAPI that is called remotely to create simulations on Compute Studio. | A GUI built with ReactJS that makes calls to the REST API to create and monitor simulations. | . One of the cool things about this app is that it uses ParamTools to read the JSON files under the hood. This means that it can read links to data in other Compute Studio runs, files on GitHub, or just plain JSON. Here are some example parameters: . policy parameters: cs://PSLmodels:Tax-Brain@49779/inputs/adjustment/policy | tax-cruncher parameters: {&quot;sage&quot;: [{&quot;value&quot;: 25}]} | business tax parameters: {&quot;CIT_rate&quot;: [{&quot;value&quot;: 0.25, &quot;year&quot;: 2021}]} | . After clicking run, three simulations will be created on Compute Studio and the app will update as soon as the simulations have finished: . . . Once they are done, the simulations are best viewed and interacted with on Compute Studio, but you can still inspect the JSON response from the Compute Studio API: . . I created this app to show that it’s possible to build apps on top of the Compute Studio API. I think PSL Stitch is a neat example of how to do this, but I am even more excited to see what others build next. . Also, this is an open source project and has lots of room for improvement. If you are interested in learning web technologies related to REST APIs and frontend development with JavaScript, then this project could be a good place to start! . Resources: . PSL Stitch | Source code | Compute Studio API Docs | .",
-            "url": "https://blog.pslmodels.org/demo-day-cs-api-stitch",
-            "relUrl": "/demo-day-cs-api-stitch",
-            "date": " • Mar 8, 2021"
-        }
-        
-    
-  
-    
-        ,"post17": {
-            "title": "Demo Day: Moving policy reform files from Tax-Brain to Tax-Cruncher",
-            "content": "Check out the video: . . Show notes: . I demonstrate how to move a policy reform file from Tax-Brain to Tax-Cruncher using the Compute.Studio API. See the Demo C/S simulation linked below for text instructions that accompany the video. . Resources: . Demo C/S simulation with instructions | .",
-            "url": "https://blog.pslmodels.org/demo-day-taxbrain-to-taxcruncher",
-            "relUrl": "/demo-day-taxbrain-to-taxcruncher",
-            "date": " • Mar 2, 2021"
-        }
-        
-    
-  
-    
-        ,"post18": {
-            "title": "Demo Day: Contributing to PSL projects",
-            "content": ". In the most recent PSL Demo Day, I illustrate how to contribute to PSL projects. The open source nature of projects in the PSL catalog allows anyone to contribute. The modularity of the code, coupled with robust testing, means that one can bite off small pieces that help improve the models and remain confident those changes work as expected. . To begin the process of finding where to contribute to PSL projects, I advise looking through the PSL GitHub Organization to see what projects interest you. Once a project of interest is identified, looking over the open “Issues” can provide a sense of where model maintainers and users are looking for help (see especially the “Help Wanted” tags). It is also completely appropriate to create a new Issue to express interest in helping and ask for direction on where that might best be done given your experience and preferences. . When you are ready to begin to contribute to a project, you’ll want to fork and clone the GitHub repository to help you get the files on your local machine and ready for you to work with. Many PSL projects outline the detailed steps to get you up and running. For example, see the Tax-Calculator Contributor Guide, which outlines the step-by-step process for doing this and confirming that everything works as expected on your computer. . After you are set up and ready to begin modifying source code for the PSL project(s) you’re interested in contributing to, you can reference the PSL-incubating Git-Tutorial project that provides more details on the Git workflow followed by most PSL projects. . As you contribute, you may want to get more involved in the community. A couple ways to do this are to join any of the PSL community events, all of which are open to the public, and to post to the PSL Discourse Forums. These are great places to meet community members and ask questions about how and where to best contribute. . I hope this helps you get started as a PSL contributor – we look forward to getting you involved in making policy analysis better and more transparent! . Resources: . PSL Git-Tutorial | PSL community events | PSL Discourse Forums | Tax-Calculator Contributor Guide | PSL GitHub Organization | .",
-            "url": "https://blog.pslmodels.org/demo-day-contributing-psl",
-            "relUrl": "/demo-day-contributing-psl",
-            "date": " • Mar 2, 2021"
-        }
-        
-    
-  
-    
-        ,"post19": {
-            "title": "Demo Day: Running the scf and microdf Python packages in Google Colab",
-            "content": ". For Monday’s PSL Demo Day, I showed how to use the scf and microdf PSL Python packages from the Google Colab web-based Jupyter notebook interface. . The scf package extracts data from the Federal Reserve’s Survey of Consumer Finances, the canonical source of US wealth microdata. scf has a single function: load(years, columns) , which then returns a pandas DataFrame with the specified column(s), each record’s survey weight, and the year (when multiple years are requested). . The microdf package analyzes survey microdata, such as that returned by the scf.load function. It offers a consistent paradigm for calculating statistics like means, medians, sums, and inequality statistics like the Gini index. Most functions are structured as follows: f(df, col, w, groupby) where df is a pandas DataFrame of survey microdata, col is a column(s) name to be summarized, w is the weight column, and groupby is the column(s) to group records in before summarizing. . Using Google Colab, I showed how to use these packages to quickly calculate mean, median, and total wealth from the SCF data, without having to install any software or leave the browser. I also demonstrated how to use the groupby argument of microdf functions to show how different measures of wealth inequality have changed over time. Finally, I previewed some of what’s to come with scf and microdf : imputations, extrapolations, inflation, visualization, and documentation, to name a few priorities. . Resources: . Slides | Demo notebook in Google Colab | Simulation from the demonstration | scf GitHub repo | microdf GitHub repo | microdf documentation | .",
-            "url": "https://blog.pslmodels.org/demo-day-scf-microdf",
-            "relUrl": "/demo-day-scf-microdf",
-            "date": " • Jan 29, 2021"
-        }
-        
-    
-  
-    
-        ,"post20": {
-            "title": "Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy",
-            "content": ". . . In this PSL Demo Day, I demonstrate how to use the open source OG-USA macroeconomic model of U.S. fiscal policy. Jason DeBacker and I (Richard Evans) have been the core maintainers of this project and repository for the last six years. This demo is organized into the following sections. The YouTube webinar linked above took place on January 11, 2021. . A brief note about value of the PSL community | Description of the OG-USA model | Using OG-USA on Compute Studio | . Brief note about the value of the PSL community . The Policy Simulation Library is a decentralized organization of open source policy models. The Policy Simulation Library GitHub organization houses many open source repositories, each of which represents a curated policy project by a diverse group of maintainers. The projects that have met the highest standards of best practices and documentation are designated as psl-cataloged , while newer projects that are in earlier stages are designated as psl-incubating . The philosophy and goal of the PSL environment is to make policy modeling open and transparent. It also allows more collaboration and cross-project contributions and interactions. . The Policy Simulation Library group has been holding these PSL Demo Day webinars since the end of 2020. The video of each webinar is available on the Policy Simulation Library YouTube channel. These videos are a great resource for learning the different models available in the PSL community, how the models interact, how to contribute to them, and what is on the horizon in their development. Also excellent in many of the PSL Demo Day webinars is a demonstration of how to use the models on the Compute Studio web application platform. . I have been a participant in and contributor to the PSL community since its inception. I love economic policy modeling. And I learned how sophisticated and complicated economic policy models can be. And any simulation can have hundreds of underlying assumptions, some of which may not be explicitly transparent. I think models that are used for public policy analysis have a philosophical imperative to be open source. This allows others to verify results and test sensitivity to assumptions. . Another strong benefit of open source modeling is that it is fundamentally apolitical. With proprietary closed-source policy models, an outside observer might criticize the results of the model based on the perceived political biases of the modeler or the sponsoring organization. With open-source models, a critic can be redirected to the underlying assumptions, structure, and content of the model. This is constructive criticism and debate that moves the science foreward. In the current polarized political environment in the U.S., open-source modeling can provide a constructive route for bipartisan cooperation and the democratization of computational modeling. Furthermore, open-source modeling and workflow encourages the widest forms of collaboration and contributions. . Description of OG-USA model . OG-USA is an open-source overlapping generations, dynamic general equilibrium, heterogeneous agent, macroeconomic model of U.S. fiscal policy. The GitHub repository for the OG-USA source code is github.com/PSLmodels/OG-USA. This repository contains all the source code and instructions for loading and running OG-USA and all of its dependencies on your local machine. We will probably do another PSL Demo Day on how to run OG-USA locally. This Demo Day webinar is about running OG-USA on the Compute Studio web application. See Section “Using OG-USA on Compute.Studio” below. . As a heterogeneous agent macroeconomic model, OG-USA allows for distributional analyses at the individual and firm level. That is, you can simulate the model and answer questions like, “How will an increase in the top three personal income tax rates affect people of different ages and income levels?” Microsimulation models can answer these types of distributional analysis questions as well. However, the difference between a macroeconomic model and a microsimulation model is that the macroeconomic models can simulate how each of those individuals and firms will respond to a policy change (e.g., lower labor supply or increased investment demand) and how those behavioral responses will add up and feed back into the macroeconomy (e.g., the effect on GDP, government revenue, government debt, interest rates, and wages). . OG-USA is a large-scale model and comprises tens of thousands of lines of code. The status of all of this code being publicly available on the internet with all collaboration and updates also public makes this an open source project. However, it is not enough to simply post one’s code. We have gone to great lengths to make in-line comments or “docstring” in the code to clarify the purpose of each function and line of code. For example, look in the OG-USA/ogusa/household.py module. The first function on line 18 is the marg_ut_cons() function. As is described in its docstring, its purpose is to “Compute the marginal utility of consumption.” . These in-code docstrings are not enough. We have also created textbook style OG-USA documentation at pslmodels.github.io/OG-USA/ using the Jupyter Book medium. This form of documentation has the advantage of being in book form and available online. It allows us to update the documentation in the open-source repository so changes and versions can be tracked. It describes the OG-USA API, OG-USA theory, and `OG-USA calibration. As with the model, this documentation is always a work in progress. But being open-source allows outside contributors to help with its updated and error checking. . One particular strength of the OG-USA model I want to highlight is its interaction with microsimulation models to incorporate information about tax incentives faced by the heterogeneous households in the model. We have interfaced OG-USA with microsimulation models in India and in the European Commission. OG-USA ‘s default for modeling the United States is to use the open-source Tax-Calculator microsimulation model, which was described by Anderson Frailey in the last Demo Day of 2020. However, DeBacker and I currently have a project in which we use OG-USA to simulate policies using the Tax Policy Center’s microsimulation model. The way OG-USA interfaces with microsimulation models to incorporate rich tax data is described in the documentation in the calibration chapter entitled, “Tax Functions”. . Using OG-USA on Compute Studio . In the demonstration, I focus on how to run experiments and simulations with OG-USA using the Compute Studio web application platform rather than installing running the model on your local machine. To use OG-USA on this web application, you will need a Compute Studio account. Once you have an account, you can start running any model available through the site. For some models, you will have to pay for the compute time, although the cost of running these models is very modest. However, all Compute Studio simulations of the OG-USA model are currently sponsored by the Open Source Economics Laboratory. This subsidy will probably run out in the next year. But we are always looking for funding for these models. . Once you are signed up and logged in to your Compute Studio account, you can go to the OG-USA model on Compute Studio at compute.studio/PSLmodels/OG-USA. The experiment that we simulated in the demonstration is available at compute.studio/PSLmodels/OG-USA/206. The description at the top of the simulation page describes the changes we made. You can look through the input page by clicking on the “Inputs” tab. We ran the model by clicking the green “Run” button at the lower left of the page. The model took about 5 hours to run, so I pre-computed the results that we discussed in the demo. The outputs of the experiment are available in the “Outputs” tab on the page. I also demonstrated how one can click the “Download Results” button at the bottom of the “Outputs” tab to download more results from the simulation. However, the full set of results is only available by installing and running the OG-USA model simulation on your local machine. . The benefits of the Compute Studio web application are that running the OG-USA model is much easier for the non-expert, and the multiple-hour computation time can be completed on a remote machine in the cloud. . Resources . PSL Demo Day YouTube webinar: “How to use OG-USA” | OG-USA on Compute Studio | Simulation from the demonstration | OG-USA GitHub repo | OG-USA documentation | Tax-Calculator GitHub repo | .",
-            "url": "https://blog.pslmodels.org/demo-day-how-to-use-og-usa",
-            "relUrl": "/demo-day-how-to-use-og-usa",
-            "date": " • Jan 28, 2021"
-        }
-        
-    
-  
-    
-        ,"post21": {
-            "title": "Demo Day: Tax-Brain",
-            "content": ". For this PSL demo-day I showed how to use the Tax-Brain web-application, hosted on Compute Studio, to analyze proposed individual income tax policies. Tax-Brain integrates the Tax-Calculator and Behavioral-Responses models to make running both static and dynamic analyses of the US federal income and payroll taxes simple. The web interface for the model makes it possible for anyone to run their own analyses without writing a single line of code. . We started the demo by simply walking through the interface and features of the web-app before creating our own sample reform to model. This reform, which to my knowledge does not reflect any proposals currently up for debate, included changes to the income and payroll tax rates, bringing back personal exemptions, modifying the standard deduction, and implementing a universal basic income. . While the model ran, I explained how Tax-Brain validated all of the user inputs, the data behind the model, and how the final tax liability projections are determined. We concluded by looking through the variety of tables and graphs Tax-Brain produces and how they can easily be shared with others. . Resources: . Simulation from the demonstration | Tax-Brain GitHub repo | Tax-Calculator documentation | Behavioral-Responses documentation | .",
-            "url": "https://blog.pslmodels.org/demo-day-tax-brain",
-            "relUrl": "/demo-day-tax-brain",
-            "date": " • Dec 23, 2020"
-        }
-        
-    
-  
-    
-        ,"post22": {
-            "title": "2020: A year in review",
-            "content": ". . This year has been one to forget! But 2020 did have its bright spots, especially in the PSL community. This post reviews some of the highlights from the year. . The Library was able to welcome two new models to the catalog in 2020: microdf and OpenFisca-UK. microdf provides a number of useful tools for use with economic survey data. OpenFisca-UK builds off the OpenFisca platform, offering a microsimulation model for tax and benefit programs in the UK. . In addition, four new models were added to the Library as incubating projects. The ui-calculator model has received a lot of attention this year in the U.S., as it provides the capability to calculate unemployment insurance benefits across U.S. states, a major mode of delivering financial relief to individuals during the COVID crisis. PCI-Outbreak directly relates to the COVID crisis, using machine learning and natural language processing to estimate the true extent of the COVID pandemic in China. The model finds that actual COVID cases are significantly higher than what official statistics claim. The COVID-MCS model considers COVID case counts and test positivity rates to measure whether or not U.S. communities are meeting certain benchmarks in controlling the spread of the disease. On a lighter note, the Git-Tutorial project provides instruction and resources for learning to use Git and GitHub, with an emphasis on the workflow used by many projects in the PSL community. . The organization surrounding the Policy Simulation Library has been bolstered in two ways. First, we have formed a relationship with the Open Collective Foundation, who is now our fiscal host. This allows PSL to accept tax deductible contributions that will support the efforts of the community. Second, we’ve formed the PSL Foundation, with an initial board that includes Linda Gibbs, Glenn Hubbard, and Jason DeBacker. . Our outreach efforts have grown in 2020 to include the regular PSL Demo Day series and this PSL Blog. Community members have also presented work with PSL models at the PyData Global Conference, the Tax Economists Forum, AEI, the Coiled Podcast, and the Virtual Global Village Podcast. New users will also find a better experience learning how to use and contribute to PSL models as many PSL models have improved their documentation through the use of Jupyter Book (e.g., see the Tax-Calculator documentation). . We love seeing the community around open source policymaking expand and are proud that PSL models have been used for important policy analysis in 2020, including analyzing economic policy responses to the pandemic and the platforms of presidential candidates. We look forward to more progress in 2021 and welcome you to join the effort as a contributor, financially or as an open source developer. . Best wishes from PSL for a happy and healthy new year! . Resources: . PSL Twitter Feed | PSL YouTube | PSL on Open Collective | .",
-            "url": "https://blog.pslmodels.org/2020-year-in-review",
-            "relUrl": "/2020-year-in-review",
-            "date": " • Dec 23, 2020"
-        }
-        
-    
-  
-    
-        ,"post23": {
-            "title": "Demo Day: Cost-of-Capital-Calculator Web Application",
-            "content": ". In the PSL Demo Day video linked above, I demonstrate how to use the Cost-of-Capital-Calculator (CCC) web application on Compute-Studio. CCC computes various measures of the impact of the tax system on business investment. These include the Hall-Jorgenson cost of capital, marginal effective tax rates, and effective average tax rates (following the methodology of Devereux and Griffith (1999)). . I begin by illustrating the various parameters available for the user to manipulate. These include parameters of the business and individual income tax systems, as well as parameters representing economic assumptions (e.g., inflation rates and nominal interest rates) and parameters dictating financial and accounting policy (e.g., the fraction of financing using debt). Note that all default values for tax policy parameters represent the “baseline policy”, which is defined as the current law policy in the year being analyzed (which itself is a parameter the user can change). Other parameters are estimated using historical data following the methodology of CBO (2014). . Next, I change a few parameters and run the model. In this example, I move the corporate income tax rate up to 28% and lower bonus depreciation for assets with depreciable lives of 20 years or less to 50%. . Finally, I discuss how to interpret output. The web app returns a table and three figures summarizing marginal effective total tax rates on new investments. This selection of output helps give one a sense of the the overall changes, as well as effects across asset types, industries, and type of financing. For the full model output, one can click on “Download Results”. Doing so will download four CSV files contain several measures of the impact of the tax system on investment for very fine asset and industry categories. Users can take these files and create tables and visualizations relevant to their own use case. . Please take the model for a spin and simulate your own reform. If you have questions, comments, or suggestions, please let me know on the PSL Discourse (non-technical questions) or by opening an issue in the CCC GitHub repository (technical questions). . Resources: . Compute Studio simulation used in the demonstration | Cost-of-Capital-Calculator web app | Cost-of-Capital-Calculator documentation | Cost-of-Capital-Calculator GitHub repository | .",
-            "url": "https://blog.pslmodels.org/demo-day-cost-of-capital-calculator",
-            "relUrl": "/demo-day-cost-of-capital-calculator",
-            "date": " • Dec 3, 2020"
-        }
-        
-    
-  
-    
-        ,"post24": {
-            "title": "Demo Day: Tax-Cruncher",
-            "content": ". For the Demo Day on November 16, I showed how to calculate a taxpayer’s liabilities under current law and under a policy reform with Tax-Cruncher. The Tax-Cruncher web application takes two sets of inputs: a taxpayer’s demographic and financial information and the provisions of a tax reform. . For the first Demo Day example (3:50), we looked at how eliminating the state and local tax (SALT) deduction cap and applying payroll tax to earnings above $400,000 would affect a high earner. In particular, our hypothetical filer had $500,000 in wages, $100,000 in capital gains, and $100,000 in itemizable expenses. You can see the results at Compute Studio simulation #634. . For the second example (17:50), we looked at how expanding the Earned Income Tax Credit (EITC) and Child Tax Credit would impact a family with $45,000 in wages and two young children. You can see the results at Compute Studio simulation #636. . Resources: . Tax-Cruncher | Tax-Cruncher-Biden | .",
-            "url": "https://blog.pslmodels.org/demo-day-tax-cruncher",
-            "relUrl": "/demo-day-tax-cruncher",
-            "date": " • Nov 23, 2020"
-        }
-        
-    
-  
-    
-        ,"post25": {
-            "title": "Demo Day: Building policy reform files",
-            "content": "Check out the video: . We will host Demo Days every two weeks until the end of the year. You can see our schedule on our events page. . . Show notes: . I demonstrate how to build policy reform files using the Tax-Brain webapp on Compute Studio. (Useful links below.) This is an introductory lesson that ends with a cliffhanger. We don’t run the model. But we do generate an individual income and payroll tax reform file that is compatible with a range of policy simulation models and analytic tools, some designed for policy decision makers, others for taxpayers and benefits recipients interested in assessing their own circumstances. . Beyond individual and payroll tax analysis, the reform file can be used with models that assess pass-through and corporate taxation of businesses, as well as a variety of income benefit programs. A wide range of use cases will occupy future events. . Resources: . Demo C/S simulation | IRS Form 1040 | PSL Catalog | PSL Events | .",
-            "url": "https://blog.pslmodels.org/demo-day-creating-reform-files",
-            "relUrl": "/demo-day-creating-reform-files",
-            "date": " • Nov 18, 2020"
-        }
-        
-    
-  
-    
-        ,"post26": {
-            "title": "Introducing the PSL Blog",
-            "content": "Our mission at the Policy Simulation Library is to improve public policy by opening up models and data preparation routines for policy analysis. To support and showcase our diverse community of users and developers, we engage across several mediums: a monthly newsletter, a Q&amp;A forum, (now-virtual) meetups, our Twitter feed, our YouTube channel, documentation for models in our catalog, and of course, issues and pull requests on GitHub. . Today, we’re adding a new medium: the PSL Blog. We’ll use this space to share major updates on our catalog, provide tutorials, and summarize events or papers that involve our models. . If you’d like to share your work on our blog, or to suggest content, drop me a line. To follow along, add the PSL blog’s RSS feed or subscribe to our newsletter. . Happy reading, . Max Ghenis . Editor, PSL Blog .",
-            "url": "https://blog.pslmodels.org/introducing-psl-blog",
-            "relUrl": "/introducing-psl-blog",
-            "date": " • Nov 6, 2020"
-        }
-        
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-      ,"page1": {
-          "title": "About",
-          "content": "The Policy Simulation Library (PSL) is a collection of models and other software for public-policy decisionmaking. PSL is developed by independent projects that meet standards for transparency and accessibility. The PSL community encourages collaborative contribution and makes the tools it develops accessible to a diverse group of users.1 . This website is powered by fastpages, a blogging platform that natively supports Jupyter notebooks in addition to other formats. &#8617; . |",
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-  if (el.attachEvent) el.attachEvent('on'+type, handler); else el.addEventListener(type, handler);
-}
-jtd.removeEvent = function(el, type, handler) {
-  if (el.detachEvent) el.detachEvent('on'+type, handler); else el.removeEventListener(type, handler);
-}
-jtd.onReady = function(ready) {
-  // in case the document is already rendered
-  if (document.readyState!='loading') ready();
-  // modern browsers
-  else if (document.addEventListener) document.addEventListener('DOMContentLoaded', ready);
-  // IE <= 8
-  else document.attachEvent('onreadystatechange', function(){
-      if (document.readyState=='complete') ready();
-  });
-}
-
-// Show/hide mobile menu
-
-// function initNav() {
-//     const mainNav = document.querySelector('.js-main-nav');
-//     const pageHeader = document.querySelector('.js-page-header');
-//     const navTrigger = document.querySelector('.js-main-nav-trigger');
-  
-//     jtd.addEvent(navTrigger, 'click', function(e){
-//       e.preventDefault();
-//       var text = navTrigger.innerText;
-//       var textToggle = navTrigger.getAttribute('data-text-toggle');
-  
-//       mainNav.classList.toggle('nav-open');
-//       pageHeader.classList.toggle('nav-open');
-//       navTrigger.classList.toggle('nav-open');
-//       navTrigger.innerText = textToggle;
-//       navTrigger.setAttribute('data-text-toggle', text);
-//       textToggle = text;
-//     })
-//   }
-
-
-// Site search
-
-function initSearch() {
-    var request = new XMLHttpRequest();
-    request.open('GET', '/assets/js/search-data.json', true);
-  
-    request.onload = function(){
-      if (request.status >= 200 && request.status < 400) {
-        // Success!
-        var data = JSON.parse(request.responseText);
-        
-        
-        lunr.tokenizer.separator = /[\s\-/]+/
-        
-        
-        var index = lunr(function () {
-          this.ref('id');
-          this.field('title', { boost: 200 });
-          this.field('content', { boost: 2 });
-          this.field('url');
-          this.metadataWhitelist = ['position']
-  
-          for (var i in data) {
-            this.add({
-              id: i,
-              title: data[i].title,
-              content: data[i].content,
-              url: data[i].url
-            });
-          }
-        });
-  
-        searchResults(index, data);
-      } else {
-        // We reached our target server, but it returned an error
-        console.log('Error loading ajax request. Request status:' + request.status);
-      }
-    };
-  
-    request.onerror = function(){
-      // There was a connection error of some sort
-      console.log('There was a connection error');
-    };
-  
-    request.send();
-  
-    function searchResults(index, data) {
-      var index = index;
-      var docs = data;
-      var searchInput = document.querySelector('.js-search-input');
-      var searchResults = document.querySelector('.js-search-results');
-  
-      function hideResults() {
-        searchResults.innerHTML = '';
-        searchResults.classList.remove('active');
-      }
-  
-      jtd.addEvent(searchInput, 'keydown', function(e){
-        switch (e.keyCode) {
-          case 38: // arrow up
-            e.preventDefault();
-            var active = document.querySelector('.search-result.active');
-            if (active) {
-              active.classList.remove('active');
-              if (active.parentElement.previousSibling) {
-                var previous = active.parentElement.previousSibling.querySelector('.search-result');
-                previous.classList.add('active');
-              }
-            }
-            return;
-          case 40: // arrow down
-            e.preventDefault();
-            var active = document.querySelector('.search-result.active');
-            if (active) {
-              if (active.parentElement.nextSibling) {
-                var next = active.parentElement.nextSibling.querySelector('.search-result');
-                active.classList.remove('active');
-                next.classList.add('active');
-              }
-            } else {
-              var next = document.querySelector('.search-result');
-              if (next) {
-                next.classList.add('active');
-              }
-            }
-            return;
-          case 13: // enter
-            e.preventDefault();
-            var active = document.querySelector('.search-result.active');
-            if (active) {
-              active.click();
-            } else {
-              var first = document.querySelector('.search-result');
-              if (first) {
-                first.click();
-              }
-            }
-            return;
-        }
-      });
-  
-      jtd.addEvent(searchInput, 'keyup', function(e){
-        switch (e.keyCode) {
-          case 27: // When esc key is pressed, hide the results and clear the field
-            hideResults();
-            searchInput.value = '';
-            return;
-          case 38: // arrow up
-          case 40: // arrow down
-          case 13: // enter
-            e.preventDefault();
-            return;
-        }
-  
-        hideResults();
-  
-        var input = this.value;
-        if (input === '') {
-          return;
-        }
-  
-        var results = index.query(function (query) {
-          var tokens = lunr.tokenizer(input)
-          query.term(tokens, {
-            boost: 10
-          });
-          query.term(tokens, {
-            wildcard: lunr.Query.wildcard.TRAILING
-          });
-        });
-  
-        if (results.length > 0) {
-          searchResults.classList.add('active');
-          var resultsList = document.createElement('ul');
-          resultsList.classList.add('search-results-list');
-          searchResults.appendChild(resultsList);
-  
-          for (var i in results) {
-            var result = results[i];
-            var doc = docs[result.ref];
-  
-            var resultsListItem = document.createElement('li');
-            resultsListItem.classList.add('search-results-list-item');
-            resultsList.appendChild(resultsListItem);
-  
-            var resultLink = document.createElement('a');
-            resultLink.classList.add('search-result');
-            resultLink.setAttribute('href', doc.url);
-            resultsListItem.appendChild(resultLink);
-  
-            var resultTitle = document.createElement('div');
-            resultTitle.classList.add('search-result-title');
-            resultTitle.innerText = doc.title;
-            resultLink.appendChild(resultTitle);
-  
-            var resultRelUrl = document.createElement('span');
-            resultRelUrl.classList.add('search-result-rel-date');
-            resultRelUrl.innerText = doc.date;
-            resultTitle.appendChild(resultRelUrl);
-  
-            var metadata = result.matchData.metadata;
-            var contentFound = false;
-            for (var j in metadata) {
-              if (metadata[j].title) {
-                var position = metadata[j].title.position[0];
-                var start = position[0];
-                var end = position[0] + position[1];
-                resultTitle.innerHTML = doc.title.substring(0, start) + '<span class="search-result-highlight">' + doc.title.substring(start, end) + '</span>' + doc.title.substring(end, doc.title.length)+'<span class="search-result-rel-date">'+doc.date+'</span>';
-  
-              } else if (metadata[j].content && !contentFound) {
-                contentFound = true;
-  
-                var position = metadata[j].content.position[0];
-                var start = position[0];
-                var end = position[0] + position[1];
-                var previewStart = start;
-                var previewEnd = end;
-                var ellipsesBefore = true;
-                var ellipsesAfter = true;
-                for (var k = 0; k < 3; k++) {
-                  var nextSpace = doc.content.lastIndexOf(' ', previewStart - 2);
-                  var nextDot = doc.content.lastIndexOf('.', previewStart - 2);
-                  if ((nextDot > 0) && (nextDot > nextSpace)) {
-                    previewStart = nextDot + 1;
-                    ellipsesBefore = false;
-                    break;
-                  }
-                  if (nextSpace < 0) {
-                    previewStart = 0;
-                    ellipsesBefore = false;
-                    break;
-                  }
-                  previewStart = nextSpace + 1;
-                }
-                for (var k = 0; k < 10; k++) {
-                  var nextSpace = doc.content.indexOf(' ', previewEnd + 1);
-                  var nextDot = doc.content.indexOf('.', previewEnd + 1);
-                  if ((nextDot > 0) && (nextDot < nextSpace)) {
-                    previewEnd = nextDot;
-                    ellipsesAfter = false;
-                    break;
-                  }
-                  if (nextSpace < 0) {
-                    previewEnd = doc.content.length;
-                    ellipsesAfter = false;
-                    break;
-                  }
-                  previewEnd = nextSpace;
-                }
-                var preview = doc.content.substring(previewStart, start);
-                if (ellipsesBefore) {
-                  preview = '... ' + preview;
-                }
-                preview += '<span class="search-result-highlight">' + doc.content.substring(start, end) + '</span>';
-                preview += doc.content.substring(end, previewEnd);
-                if (ellipsesAfter) {
-                  preview += ' ...';
-                }
-  
-                var resultPreview = document.createElement('div');
-                resultPreview.classList.add('search-result-preview');
-                resultPreview.innerHTML = preview;
-                resultLink.appendChild(resultPreview);
-              }
-            }
-          }
-        }
-      });
-  
-      // jtd.addEvent(searchInput, 'blur', function(){
-      //   setTimeout(function(){ hideResults() }, 300);
-      // });
-    }
-  }
-  
-//   function pageFocus() {
-//     var mainContent = document.querySelector('.js-main-content');
-//     mainContent.focus();
-//   }
-  
-  // Document ready
-  
-  jtd.onReady(function(){
-    // initNav();
-    // pageFocus();
-    if (typeof lunr !== 'undefined') {
-      initSearch();
-    }
-  });
-  
-  })(window.jtd = window.jtd || {});
\ No newline at end of file
diff --git a/assets/js/vendor/lunr.min.js b/assets/js/vendor/lunr.min.js
deleted file mode 100755
index 34b279d..0000000
--- a/assets/js/vendor/lunr.min.js
+++ /dev/null
@@ -1,6 +0,0 @@
-/**
- * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.6
- * Copyright (C) 2019 Oliver Nightingale
- * @license MIT
- */
-!function(){var e=function(t){var r=new e.Builder;return r.pipeline.add(e.trimmer,e.stopWordFilter,e.stemmer),r.searchPipeline.add(e.stemmer),t.call(r,r),r.build()};e.version="2.3.6",e.utils={},e.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),e.utils.asString=function(e){return void 0===e||null===e?"":e.toString()},e.utils.clone=function(e){if(null===e||void 0===e)return e;for(var t=Object.create(null),r=Object.keys(e),i=0;i<r.length;i++){var n=r[i],s=e[n];if(Array.isArray(s))t[n]=s.slice();else{if("string"!=typeof s&&"number"!=typeof s&&"boolean"!=typeof s)throw new TypeError("clone is not deep and does not support nested objects");t[n]=s}}return t},e.FieldRef=function(e,t,r){this.docRef=e,this.fieldName=t,this._stringValue=r},e.FieldRef.joiner="/",e.FieldRef.fromString=function(t){var r=t.indexOf(e.FieldRef.joiner);if(r===-1)throw"malformed field ref string";var i=t.slice(0,r),n=t.slice(r+1);return new e.FieldRef(n,i,t)},e.FieldRef.prototype.toString=function(){return void 0==this._stringValue&&(this._stringValue=this.fieldName+e.FieldRef.joiner+this.docRef),this._stringValue},e.Set=function(e){if(this.elements=Object.create(null),e){this.length=e.length;for(var t=0;t<this.length;t++)this.elements[e[t]]=!0}else this.length=0},e.Set.complete={intersect:function(e){return e},union:function(e){return e},contains:function(){return!0}},e.Set.empty={intersect:function(){return this},union:function(e){return e},contains:function(){return!1}},e.Set.prototype.contains=function(e){return!!this.elements[e]},e.Set.prototype.intersect=function(t){var r,i,n,s=[];if(t===e.Set.complete)return this;if(t===e.Set.empty)return t;this.length<t.length?(r=this,i=t):(r=t,i=this),n=Object.keys(r.elements);for(var o=0;o<n.length;o++){var a=n[o];a in i.elements&&s.push(a)}return new e.Set(s)},e.Set.prototype.union=function(t){return t===e.Set.complete?e.Set.complete:t===e.Set.empty?this:new e.Set(Object.keys(this.elements).concat(Object.keys(t.elements)))},e.idf=function(e,t){var r=0;for(var i in e)"_index"!=i&&(r+=Object.keys(e[i]).length);var n=(t-r+.5)/(r+.5);return Math.log(1+Math.abs(n))},e.Token=function(e,t){this.str=e||"",this.metadata=t||{}},e.Token.prototype.toString=function(){return this.str},e.Token.prototype.update=function(e){return this.str=e(this.str,this.metadata),this},e.Token.prototype.clone=function(t){return t=t||function(e){return e},new e.Token(t(this.str,this.metadata),this.metadata)},e.tokenizer=function(t,r){if(null==t||void 0==t)return[];if(Array.isArray(t))return t.map(function(t){return new e.Token(e.utils.asString(t).toLowerCase(),e.utils.clone(r))});for(var i=t.toString().trim().toLowerCase(),n=i.length,s=[],o=0,a=0;o<=n;o++){var u=i.charAt(o),l=o-a;if(u.match(e.tokenizer.separator)||o==n){if(l>0){var c=e.utils.clone(r)||{};c.position=[a,l],c.index=s.length,s.push(new e.Token(i.slice(a,o),c))}a=o+1}}return s},e.tokenizer.separator=/[\s\-]+/,e.Pipeline=function(){this._stack=[]},e.Pipeline.registeredFunctions=Object.create(null),e.Pipeline.registerFunction=function(t,r){r in this.registeredFunctions&&e.utils.warn("Overwriting existing registered function: "+r),t.label=r,e.Pipeline.registeredFunctions[t.label]=t},e.Pipeline.warnIfFunctionNotRegistered=function(t){var r=t.label&&t.label in this.registeredFunctions;r||e.utils.warn("Function is not registered with pipeline. This may cause problems when serialising the index.\n",t)},e.Pipeline.load=function(t){var r=new e.Pipeline;return t.forEach(function(t){var i=e.Pipeline.registeredFunctions[t];if(!i)throw new Error("Cannot load unregistered function: "+t);r.add(i)}),r},e.Pipeline.prototype.add=function(){var t=Array.prototype.slice.call(arguments);t.forEach(function(t){e.Pipeline.warnIfFunctionNotRegistered(t),this._stack.push(t)},this)},e.Pipeline.prototype.after=function(t,r){e.Pipeline.warnIfFunctionNotRegistered(r);var i=this._stack.indexOf(t);if(i==-1)throw new Error("Cannot find existingFn");i+=1,this._stack.splice(i,0,r)},e.Pipeline.prototype.before=function(t,r){e.Pipeline.warnIfFunctionNotRegistered(r);var i=this._stack.indexOf(t);if(i==-1)throw new Error("Cannot find existingFn");this._stack.splice(i,0,r)},e.Pipeline.prototype.remove=function(e){var t=this._stack.indexOf(e);t!=-1&&this._stack.splice(t,1)},e.Pipeline.prototype.run=function(e){for(var t=this._stack.length,r=0;r<t;r++){for(var i=this._stack[r],n=[],s=0;s<e.length;s++){var o=i(e[s],s,e);if(void 0!==o&&""!==o)if(Array.isArray(o))for(var a=0;a<o.length;a++)n.push(o[a]);else n.push(o)}e=n}return e},e.Pipeline.prototype.runString=function(t,r){var i=new e.Token(t,r);return this.run([i]).map(function(e){return e.toString()})},e.Pipeline.prototype.reset=function(){this._stack=[]},e.Pipeline.prototype.toJSON=function(){return this._stack.map(function(t){return e.Pipeline.warnIfFunctionNotRegistered(t),t.label})},e.Vector=function(e){this._magnitude=0,this.elements=e||[]},e.Vector.prototype.positionForIndex=function(e){if(0==this.elements.length)return 0;for(var t=0,r=this.elements.length/2,i=r-t,n=Math.floor(i/2),s=this.elements[2*n];i>1&&(s<e&&(t=n),s>e&&(r=n),s!=e);)i=r-t,n=t+Math.floor(i/2),s=this.elements[2*n];return s==e?2*n:s>e?2*n:s<e?2*(n+1):void 0},e.Vector.prototype.insert=function(e,t){this.upsert(e,t,function(){throw"duplicate index"})},e.Vector.prototype.upsert=function(e,t,r){this._magnitude=0;var i=this.positionForIndex(e);this.elements[i]==e?this.elements[i+1]=r(this.elements[i+1],t):this.elements.splice(i,0,e,t)},e.Vector.prototype.magnitude=function(){if(this._magnitude)return this._magnitude;for(var e=0,t=this.elements.length,r=1;r<t;r+=2){var i=this.elements[r];e+=i*i}return this._magnitude=Math.sqrt(e)},e.Vector.prototype.dot=function(e){for(var t=0,r=this.elements,i=e.elements,n=r.length,s=i.length,o=0,a=0,u=0,l=0;u<n&&l<s;)o=r[u],a=i[l],o<a?u+=2:o>a?l+=2:o==a&&(t+=r[u+1]*i[l+1],u+=2,l+=2);return t},e.Vector.prototype.similarity=function(e){return this.dot(e)/this.magnitude()||0},e.Vector.prototype.toArray=function(){for(var e=new Array(this.elements.length/2),t=1,r=0;t<this.elements.length;t+=2,r++)e[r]=this.elements[t];return e},e.Vector.prototype.toJSON=function(){return this.elements},e.stemmer=function(){var e={ational:"ate",tional:"tion",enci:"ence",anci:"ance",izer:"ize",bli:"ble",alli:"al",entli:"ent",eli:"e",ousli:"ous",ization:"ize",ation:"ate",ator:"ate",alism:"al",iveness:"ive",fulness:"ful",ousness:"ous",aliti:"al",iviti:"ive",biliti:"ble",logi:"log"},t={icate:"ic",ative:"",alize:"al",iciti:"ic",ical:"ic",ful:"",ness:""},r="[^aeiou]",i="[aeiouy]",n=r+"[^aeiouy]*",s=i+"[aeiou]*",o="^("+n+")?"+s+n,a="^("+n+")?"+s+n+"("+s+")?$",u="^("+n+")?"+s+n+s+n,l="^("+n+")?"+i,c=new RegExp(o),h=new RegExp(u),d=new RegExp(a),f=new RegExp(l),p=/^(.+?)(ss|i)es$/,y=/^(.+?)([^s])s$/,m=/^(.+?)eed$/,v=/^(.+?)(ed|ing)$/,g=/.$/,x=/(at|bl|iz)$/,w=new RegExp("([^aeiouylsz])\\1$"),Q=new RegExp("^"+n+i+"[^aeiouwxy]$"),k=/^(.+?[^aeiou])y$/,S=/^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/,E=/^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/,L=/^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/,b=/^(.+?)(s|t)(ion)$/,P=/^(.+?)e$/,T=/ll$/,O=new RegExp("^"+n+i+"[^aeiouwxy]$"),I=function(r){var i,n,s,o,a,u,l;if(r.length<3)return r;if(s=r.substr(0,1),"y"==s&&(r=s.toUpperCase()+r.substr(1)),o=p,a=y,o.test(r)?r=r.replace(o,"$1$2"):a.test(r)&&(r=r.replace(a,"$1$2")),o=m,a=v,o.test(r)){var I=o.exec(r);o=c,o.test(I[1])&&(o=g,r=r.replace(o,""))}else if(a.test(r)){var I=a.exec(r);i=I[1],a=f,a.test(i)&&(r=i,a=x,u=w,l=Q,a.test(r)?r+="e":u.test(r)?(o=g,r=r.replace(o,"")):l.test(r)&&(r+="e"))}if(o=k,o.test(r)){var I=o.exec(r);i=I[1],r=i+"i"}if(o=S,o.test(r)){var I=o.exec(r);i=I[1],n=I[2],o=c,o.test(i)&&(r=i+e[n])}if(o=E,o.test(r)){var I=o.exec(r);i=I[1],n=I[2],o=c,o.test(i)&&(r=i+t[n])}if(o=L,a=b,o.test(r)){var I=o.exec(r);i=I[1],o=h,o.test(i)&&(r=i)}else if(a.test(r)){var I=a.exec(r);i=I[1]+I[2],a=h,a.test(i)&&(r=i)}if(o=P,o.test(r)){var I=o.exec(r);i=I[1],o=h,a=d,u=O,(o.test(i)||a.test(i)&&!u.test(i))&&(r=i)}return o=T,a=h,o.test(r)&&a.test(r)&&(o=g,r=r.replace(o,"")),"y"==s&&(r=s.toLowerCase()+r.substr(1)),r};return function(e){return e.update(I)}}(),e.Pipeline.registerFunction(e.stemmer,"stemmer"),e.generateStopWordFilter=function(e){var t=e.reduce(function(e,t){return e[t]=t,e},{});return function(e){if(e&&t[e.toString()]!==e.toString())return e}},e.stopWordFilter=e.generateStopWordFilter(["a","able","about","across","after","all","almost","also","am","among","an","and","any","are","as","at","be","because","been","but","by","can","cannot","could","dear","did","do","does","either","else","ever","every","for","from","get","got","had","has","have","he","her","hers","him","his","how","however","i","if","in","into","is","it","its","just","least","let","like","likely","may","me","might","most","must","my","neither","no","nor","not","of","off","often","on","only","or","other","our","own","rather","said","say","says","she","should","since","so","some","than","that","the","their","them","then","there","these","they","this","tis","to","too","twas","us","wants","was","we","were","what","when","where","which","while","who","whom","why","will","with","would","yet","you","your"]),e.Pipeline.registerFunction(e.stopWordFilter,"stopWordFilter"),e.trimmer=function(e){return e.update(function(e){return e.replace(/^\W+/,"").replace(/\W+$/,"")})},e.Pipeline.registerFunction(e.trimmer,"trimmer"),e.TokenSet=function(){this["final"]=!1,this.edges={},this.id=e.TokenSet._nextId,e.TokenSet._nextId+=1},e.TokenSet._nextId=1,e.TokenSet.fromArray=function(t){for(var r=new e.TokenSet.Builder,i=0,n=t.length;i<n;i++)r.insert(t[i]);return r.finish(),r.root},e.TokenSet.fromClause=function(t){return"editDistance"in t?e.TokenSet.fromFuzzyString(t.term,t.editDistance):e.TokenSet.fromString(t.term)},e.TokenSet.fromFuzzyString=function(t,r){for(var i=new e.TokenSet,n=[{node:i,editsRemaining:r,str:t}];n.length;){var s=n.pop();if(s.str.length>0){var o,a=s.str.charAt(0);a in s.node.edges?o=s.node.edges[a]:(o=new e.TokenSet,s.node.edges[a]=o),1==s.str.length&&(o["final"]=!0),n.push({node:o,editsRemaining:s.editsRemaining,str:s.str.slice(1)})}if(0!=s.editsRemaining){if("*"in s.node.edges)var u=s.node.edges["*"];else{var u=new e.TokenSet;s.node.edges["*"]=u}if(0==s.str.length&&(u["final"]=!0),n.push({node:u,editsRemaining:s.editsRemaining-1,str:s.str}),s.str.length>1&&n.push({node:s.node,editsRemaining:s.editsRemaining-1,str:s.str.slice(1)}),1==s.str.length&&(s.node["final"]=!0),s.str.length>=1){if("*"in s.node.edges)var l=s.node.edges["*"];else{var l=new e.TokenSet;s.node.edges["*"]=l}1==s.str.length&&(l["final"]=!0),n.push({node:l,editsRemaining:s.editsRemaining-1,str:s.str.slice(1)})}if(s.str.length>1){var c,h=s.str.charAt(0),d=s.str.charAt(1);d in s.node.edges?c=s.node.edges[d]:(c=new e.TokenSet,s.node.edges[d]=c),1==s.str.length&&(c["final"]=!0),n.push({node:c,editsRemaining:s.editsRemaining-1,str:h+s.str.slice(2)})}}}return i},e.TokenSet.fromString=function(t){for(var r=new e.TokenSet,i=r,n=0,s=t.length;n<s;n++){var o=t[n],a=n==s-1;if("*"==o)r.edges[o]=r,r["final"]=a;else{var u=new e.TokenSet;u["final"]=a,r.edges[o]=u,r=u}}return i},e.TokenSet.prototype.toArray=function(){for(var e=[],t=[{prefix:"",node:this}];t.length;){var r=t.pop(),i=Object.keys(r.node.edges),n=i.length;r.node["final"]&&(r.prefix.charAt(0),e.push(r.prefix));for(var s=0;s<n;s++){var o=i[s];t.push({prefix:r.prefix.concat(o),node:r.node.edges[o]})}}return e},e.TokenSet.prototype.toString=function(){if(this._str)return this._str;for(var e=this["final"]?"1":"0",t=Object.keys(this.edges).sort(),r=t.length,i=0;i<r;i++){var n=t[i],s=this.edges[n];e=e+n+s.id}return e},e.TokenSet.prototype.intersect=function(t){for(var r=new e.TokenSet,i=void 0,n=[{qNode:t,output:r,node:this}];n.length;){i=n.pop();for(var s=Object.keys(i.qNode.edges),o=s.length,a=Object.keys(i.node.edges),u=a.length,l=0;l<o;l++)for(var c=s[l],h=0;h<u;h++){var d=a[h];if(d==c||"*"==c){var f=i.node.edges[d],p=i.qNode.edges[c],y=f["final"]&&p["final"],m=void 0;d in i.output.edges?(m=i.output.edges[d],m["final"]=m["final"]||y):(m=new e.TokenSet,m["final"]=y,i.output.edges[d]=m),n.push({qNode:p,output:m,node:f})}}}return r},e.TokenSet.Builder=function(){this.previousWord="",this.root=new e.TokenSet,this.uncheckedNodes=[],this.minimizedNodes={}},e.TokenSet.Builder.prototype.insert=function(t){var r,i=0;if(t<this.previousWord)throw new Error("Out of order word insertion");for(var n=0;n<t.length&&n<this.previousWord.length&&t[n]==this.previousWord[n];n++)i++;this.minimize(i),r=0==this.uncheckedNodes.length?this.root:this.uncheckedNodes[this.uncheckedNodes.length-1].child;for(var n=i;n<t.length;n++){var s=new e.TokenSet,o=t[n];r.edges[o]=s,this.uncheckedNodes.push({parent:r,"char":o,child:s}),r=s}r["final"]=!0,this.previousWord=t},e.TokenSet.Builder.prototype.finish=function(){this.minimize(0)},e.TokenSet.Builder.prototype.minimize=function(e){for(var t=this.uncheckedNodes.length-1;t>=e;t--){var r=this.uncheckedNodes[t],i=r.child.toString();i in this.minimizedNodes?r.parent.edges[r["char"]]=this.minimizedNodes[i]:(r.child._str=i,this.minimizedNodes[i]=r.child),this.uncheckedNodes.pop()}},e.Index=function(e){this.invertedIndex=e.invertedIndex,this.fieldVectors=e.fieldVectors,this.tokenSet=e.tokenSet,this.fields=e.fields,this.pipeline=e.pipeline},e.Index.prototype.search=function(t){return this.query(function(r){var i=new e.QueryParser(t,r);i.parse()})},e.Index.prototype.query=function(t){for(var r=new e.Query(this.fields),i=Object.create(null),n=Object.create(null),s=Object.create(null),o=Object.create(null),a=Object.create(null),u=0;u<this.fields.length;u++)n[this.fields[u]]=new e.Vector;t.call(r,r);for(var u=0;u<r.clauses.length;u++){var l=r.clauses[u],c=null,h=e.Set.complete;c=l.usePipeline?this.pipeline.runString(l.term,{fields:l.fields}):[l.term];for(var d=0;d<c.length;d++){var f=c[d];l.term=f;var p=e.TokenSet.fromClause(l),y=this.tokenSet.intersect(p).toArray();if(0===y.length&&l.presence===e.Query.presence.REQUIRED){for(var m=0;m<l.fields.length;m++){var v=l.fields[m];o[v]=e.Set.empty}break}for(var g=0;g<y.length;g++)for(var x=y[g],w=this.invertedIndex[x],Q=w._index,m=0;m<l.fields.length;m++){var v=l.fields[m],k=w[v],S=Object.keys(k),E=x+"/"+v,L=new e.Set(S);if(l.presence==e.Query.presence.REQUIRED&&(h=h.union(L),void 0===o[v]&&(o[v]=e.Set.complete)),l.presence!=e.Query.presence.PROHIBITED){if(n[v].upsert(Q,l.boost,function(e,t){return e+t}),!s[E]){for(var b=0;b<S.length;b++){var P,T=S[b],O=new e.FieldRef(T,v),I=k[T];void 0===(P=i[O])?i[O]=new e.MatchData(x,v,I):P.add(x,v,I)}s[E]=!0}}else void 0===a[v]&&(a[v]=e.Set.empty),a[v]=a[v].union(L)}}if(l.presence===e.Query.presence.REQUIRED)for(var m=0;m<l.fields.length;m++){var v=l.fields[m];o[v]=o[v].intersect(h)}}for(var R=e.Set.complete,F=e.Set.empty,u=0;u<this.fields.length;u++){var v=this.fields[u];o[v]&&(R=R.intersect(o[v])),a[v]&&(F=F.union(a[v]))}var C=Object.keys(i),N=[],_=Object.create(null);if(r.isNegated()){C=Object.keys(this.fieldVectors);for(var u=0;u<C.length;u++){var O=C[u],j=e.FieldRef.fromString(O);i[O]=new e.MatchData}}for(var u=0;u<C.length;u++){var j=e.FieldRef.fromString(C[u]),D=j.docRef;if(R.contains(D)&&!F.contains(D)){var A,B=this.fieldVectors[j],V=n[j.fieldName].similarity(B);if(void 0!==(A=_[D]))A.score+=V,A.matchData.combine(i[j]);else{var z={ref:D,score:V,matchData:i[j]};_[D]=z,N.push(z)}}}return N.sort(function(e,t){return t.score-e.score})},e.Index.prototype.toJSON=function(){var t=Object.keys(this.invertedIndex).sort().map(function(e){return[e,this.invertedIndex[e]]},this),r=Object.keys(this.fieldVectors).map(function(e){return[e,this.fieldVectors[e].toJSON()]},this);return{version:e.version,fields:this.fields,fieldVectors:r,invertedIndex:t,pipeline:this.pipeline.toJSON()}},e.Index.load=function(t){var r={},i={},n=t.fieldVectors,s=Object.create(null),o=t.invertedIndex,a=new e.TokenSet.Builder,u=e.Pipeline.load(t.pipeline);t.version!=e.version&&e.utils.warn("Version mismatch when loading serialised index. Current version of lunr '"+e.version+"' does not match serialized index '"+t.version+"'");for(var l=0;l<n.length;l++){var c=n[l],h=c[0],d=c[1];i[h]=new e.Vector(d)}for(var l=0;l<o.length;l++){var c=o[l],f=c[0],p=c[1];a.insert(f),s[f]=p}return a.finish(),r.fields=t.fields,r.fieldVectors=i,r.invertedIndex=s,r.tokenSet=a.root,r.pipeline=u,new e.Index(r)},e.Builder=function(){this._ref="id",this._fields=Object.create(null),this._documents=Object.create(null),this.invertedIndex=Object.create(null),this.fieldTermFrequencies={},this.fieldLengths={},this.tokenizer=e.tokenizer,this.pipeline=new e.Pipeline,this.searchPipeline=new e.Pipeline,this.documentCount=0,this._b=.75,this._k1=1.2,this.termIndex=0,this.metadataWhitelist=[]},e.Builder.prototype.ref=function(e){this._ref=e},e.Builder.prototype.field=function(e,t){if(/\//.test(e))throw new RangeError("Field '"+e+"' contains illegal character '/'");this._fields[e]=t||{}},e.Builder.prototype.b=function(e){e<0?this._b=0:e>1?this._b=1:this._b=e},e.Builder.prototype.k1=function(e){this._k1=e},e.Builder.prototype.add=function(t,r){var i=t[this._ref],n=Object.keys(this._fields);this._documents[i]=r||{},this.documentCount+=1;for(var s=0;s<n.length;s++){var o=n[s],a=this._fields[o].extractor,u=a?a(t):t[o],l=this.tokenizer(u,{fields:[o]}),c=this.pipeline.run(l),h=new e.FieldRef(i,o),d=Object.create(null);this.fieldTermFrequencies[h]=d,this.fieldLengths[h]=0,this.fieldLengths[h]+=c.length;for(var f=0;f<c.length;f++){var p=c[f];if(void 0==d[p]&&(d[p]=0),d[p]+=1,void 0==this.invertedIndex[p]){var y=Object.create(null);y._index=this.termIndex,this.termIndex+=1;for(var m=0;m<n.length;m++)y[n[m]]=Object.create(null);this.invertedIndex[p]=y}void 0==this.invertedIndex[p][o][i]&&(this.invertedIndex[p][o][i]=Object.create(null));for(var v=0;v<this.metadataWhitelist.length;v++){var g=this.metadataWhitelist[v],x=p.metadata[g];void 0==this.invertedIndex[p][o][i][g]&&(this.invertedIndex[p][o][i][g]=[]),this.invertedIndex[p][o][i][g].push(x)}}}},e.Builder.prototype.calculateAverageFieldLengths=function(){for(var t=Object.keys(this.fieldLengths),r=t.length,i={},n={},s=0;s<r;s++){var o=e.FieldRef.fromString(t[s]),a=o.fieldName;n[a]||(n[a]=0),n[a]+=1,i[a]||(i[a]=0),i[a]+=this.fieldLengths[o]}for(var u=Object.keys(this._fields),s=0;s<u.length;s++){var l=u[s];i[l]=i[l]/n[l]}this.averageFieldLength=i},e.Builder.prototype.createFieldVectors=function(){for(var t={},r=Object.keys(this.fieldTermFrequencies),i=r.length,n=Object.create(null),s=0;s<i;s++){for(var o=e.FieldRef.fromString(r[s]),a=o.fieldName,u=this.fieldLengths[o],l=new e.Vector,c=this.fieldTermFrequencies[o],h=Object.keys(c),d=h.length,f=this._fields[a].boost||1,p=this._documents[o.docRef].boost||1,y=0;y<d;y++){var m,v,g,x=h[y],w=c[x],Q=this.invertedIndex[x]._index;void 0===n[x]?(m=e.idf(this.invertedIndex[x],this.documentCount),n[x]=m):m=n[x],v=m*((this._k1+1)*w)/(this._k1*(1-this._b+this._b*(u/this.averageFieldLength[a]))+w),v*=f,v*=p,g=Math.round(1e3*v)/1e3,l.insert(Q,g)}t[o]=l}this.fieldVectors=t},e.Builder.prototype.createTokenSet=function(){this.tokenSet=e.TokenSet.fromArray(Object.keys(this.invertedIndex).sort())},e.Builder.prototype.build=function(){return this.calculateAverageFieldLengths(),this.createFieldVectors(),this.createTokenSet(),new e.Index({invertedIndex:this.invertedIndex,fieldVectors:this.fieldVectors,tokenSet:this.tokenSet,fields:Object.keys(this._fields),pipeline:this.searchPipeline})},e.Builder.prototype.use=function(e){var t=Array.prototype.slice.call(arguments,1);t.unshift(this),e.apply(this,t)},e.MatchData=function(e,t,r){for(var i=Object.create(null),n=Object.keys(r||{}),s=0;s<n.length;s++){var o=n[s];i[o]=r[o].slice()}this.metadata=Object.create(null),void 0!==e&&(this.metadata[e]=Object.create(null),this.metadata[e][t]=i)},e.MatchData.prototype.combine=function(e){for(var t=Object.keys(e.metadata),r=0;r<t.length;r++){var i=t[r],n=Object.keys(e.metadata[i]);void 0==this.metadata[i]&&(this.metadata[i]=Object.create(null));for(var s=0;s<n.length;s++){var o=n[s],a=Object.keys(e.metadata[i][o]);void 0==this.metadata[i][o]&&(this.metadata[i][o]=Object.create(null));for(var u=0;u<a.length;u++){var l=a[u];void 0==this.metadata[i][o][l]?this.metadata[i][o][l]=e.metadata[i][o][l]:this.metadata[i][o][l]=this.metadata[i][o][l].concat(e.metadata[i][o][l])}}}},e.MatchData.prototype.add=function(e,t,r){if(!(e in this.metadata))return this.metadata[e]=Object.create(null),void(this.metadata[e][t]=r);if(!(t in this.metadata[e]))return void(this.metadata[e][t]=r);for(var i=Object.keys(r),n=0;n<i.length;n++){var s=i[n];s in this.metadata[e][t]?this.metadata[e][t][s]=this.metadata[e][t][s].concat(r[s]):this.metadata[e][t][s]=r[s]}},e.Query=function(e){this.clauses=[],this.allFields=e},e.Query.wildcard=new String("*"),e.Query.wildcard.NONE=0,e.Query.wildcard.LEADING=1,e.Query.wildcard.TRAILING=2,e.Query.presence={OPTIONAL:1,REQUIRED:2,PROHIBITED:3},e.Query.prototype.clause=function(t){return"fields"in t||(t.fields=this.allFields),"boost"in t||(t.boost=1),"usePipeline"in t||(t.usePipeline=!0),"wildcard"in t||(t.wildcard=e.Query.wildcard.NONE),t.wildcard&e.Query.wildcard.LEADING&&t.term.charAt(0)!=e.Query.wildcard&&(t.term="*"+t.term),t.wildcard&e.Query.wildcard.TRAILING&&t.term.slice(-1)!=e.Query.wildcard&&(t.term=""+t.term+"*"),"presence"in t||(t.presence=e.Query.presence.OPTIONAL),this.clauses.push(t),this},e.Query.prototype.isNegated=function(){for(var t=0;t<this.clauses.length;t++)if(this.clauses[t].presence!=e.Query.presence.PROHIBITED)return!1;return!0},e.Query.prototype.term=function(t,r){if(Array.isArray(t))return t.forEach(function(t){this.term(t,e.utils.clone(r))},this),this;var i=r||{};return i.term=t.toString(),this.clause(i),this},e.QueryParseError=function(e,t,r){this.name="QueryParseError",this.message=e,this.start=t,this.end=r},e.QueryParseError.prototype=new Error,e.QueryLexer=function(e){this.lexemes=[],this.str=e,this.length=e.length,this.pos=0,this.start=0,this.escapeCharPositions=[]},e.QueryLexer.prototype.run=function(){for(var t=e.QueryLexer.lexText;t;)t=t(this)},e.QueryLexer.prototype.sliceString=function(){for(var e=[],t=this.start,r=this.pos,i=0;i<this.escapeCharPositions.length;i++)r=this.escapeCharPositions[i],e.push(this.str.slice(t,r)),t=r+1;return e.push(this.str.slice(t,this.pos)),this.escapeCharPositions.length=0,e.join("")},e.QueryLexer.prototype.emit=function(e){this.lexemes.push({type:e,str:this.sliceString(),start:this.start,end:this.pos}),this.start=this.pos},e.QueryLexer.prototype.escapeCharacter=function(){this.escapeCharPositions.push(this.pos-1),this.pos+=1},e.QueryLexer.prototype.next=function(){if(this.pos>=this.length)return e.QueryLexer.EOS;var t=this.str.charAt(this.pos);return this.pos+=1,t},e.QueryLexer.prototype.width=function(){return this.pos-this.start},e.QueryLexer.prototype.ignore=function(){this.start==this.pos&&(this.pos+=1),this.start=this.pos},e.QueryLexer.prototype.backup=function(){this.pos-=1},e.QueryLexer.prototype.acceptDigitRun=function(){var t,r;do t=this.next(),r=t.charCodeAt(0);while(r>47&&r<58);t!=e.QueryLexer.EOS&&this.backup()},e.QueryLexer.prototype.more=function(){return this.pos<this.length},e.QueryLexer.EOS="EOS",e.QueryLexer.FIELD="FIELD",e.QueryLexer.TERM="TERM",e.QueryLexer.EDIT_DISTANCE="EDIT_DISTANCE",e.QueryLexer.BOOST="BOOST",e.QueryLexer.PRESENCE="PRESENCE",e.QueryLexer.lexField=function(t){return t.backup(),t.emit(e.QueryLexer.FIELD),t.ignore(),e.QueryLexer.lexText},e.QueryLexer.lexTerm=function(t){if(t.width()>1&&(t.backup(),t.emit(e.QueryLexer.TERM)),t.ignore(),t.more())return e.QueryLexer.lexText},e.QueryLexer.lexEditDistance=function(t){return t.ignore(),t.acceptDigitRun(),t.emit(e.QueryLexer.EDIT_DISTANCE),e.QueryLexer.lexText},e.QueryLexer.lexBoost=function(t){return t.ignore(),t.acceptDigitRun(),t.emit(e.QueryLexer.BOOST),e.QueryLexer.lexText},e.QueryLexer.lexEOS=function(t){t.width()>0&&t.emit(e.QueryLexer.TERM)},e.QueryLexer.termSeparator=e.tokenizer.separator,e.QueryLexer.lexText=function(t){for(;;){var r=t.next();if(r==e.QueryLexer.EOS)return e.QueryLexer.lexEOS;if(92!=r.charCodeAt(0)){if(":"==r)return e.QueryLexer.lexField;if("~"==r)return t.backup(),t.width()>0&&t.emit(e.QueryLexer.TERM),e.QueryLexer.lexEditDistance;if("^"==r)return t.backup(),t.width()>0&&t.emit(e.QueryLexer.TERM),e.QueryLexer.lexBoost;if("+"==r&&1===t.width())return t.emit(e.QueryLexer.PRESENCE),e.QueryLexer.lexText;if("-"==r&&1===t.width())return t.emit(e.QueryLexer.PRESENCE),e.QueryLexer.lexText;if(r.match(e.QueryLexer.termSeparator))return e.QueryLexer.lexTerm}else t.escapeCharacter()}},e.QueryParser=function(t,r){this.lexer=new e.QueryLexer(t),this.query=r,this.currentClause={},this.lexemeIdx=0},e.QueryParser.prototype.parse=function(){this.lexer.run(),this.lexemes=this.lexer.lexemes;for(var t=e.QueryParser.parseClause;t;)t=t(this);return this.query},e.QueryParser.prototype.peekLexeme=function(){return this.lexemes[this.lexemeIdx]},e.QueryParser.prototype.consumeLexeme=function(){var e=this.peekLexeme();return this.lexemeIdx+=1,e},e.QueryParser.prototype.nextClause=function(){var e=this.currentClause;this.query.clause(e),this.currentClause={}},e.QueryParser.parseClause=function(t){var r=t.peekLexeme();if(void 0!=r)switch(r.type){case e.QueryLexer.PRESENCE:return e.QueryParser.parsePresence;case e.QueryLexer.FIELD:return e.QueryParser.parseField;case e.QueryLexer.TERM:return e.QueryParser.parseTerm;default:var i="expected either a field or a term, found "+r.type;throw r.str.length>=1&&(i+=" with value '"+r.str+"'"),new e.QueryParseError(i,r.start,r.end)}},e.QueryParser.parsePresence=function(t){var r=t.consumeLexeme();if(void 0!=r){switch(r.str){case"-":t.currentClause.presence=e.Query.presence.PROHIBITED;break;case"+":t.currentClause.presence=e.Query.presence.REQUIRED;break;default:var i="unrecognised presence operator'"+r.str+"'";throw new e.QueryParseError(i,r.start,r.end)}var n=t.peekLexeme();if(void 0==n){var i="expecting term or field, found nothing";throw new e.QueryParseError(i,r.start,r.end)}switch(n.type){case e.QueryLexer.FIELD:return e.QueryParser.parseField;case e.QueryLexer.TERM:return e.QueryParser.parseTerm;default:var i="expecting term or field, found '"+n.type+"'";throw new e.QueryParseError(i,n.start,n.end)}}},e.QueryParser.parseField=function(t){var r=t.consumeLexeme();if(void 0!=r){if(t.query.allFields.indexOf(r.str)==-1){var i=t.query.allFields.map(function(e){return"'"+e+"'"}).join(", "),n="unrecognised field '"+r.str+"', possible fields: "+i;throw new e.QueryParseError(n,r.start,r.end)}t.currentClause.fields=[r.str];var s=t.peekLexeme();if(void 0==s){var n="expecting term, found nothing";throw new e.QueryParseError(n,r.start,r.end)}switch(s.type){case e.QueryLexer.TERM:return e.QueryParser.parseTerm;default:var n="expecting term, found '"+s.type+"'";throw new e.QueryParseError(n,s.start,s.end)}}},e.QueryParser.parseTerm=function(t){var r=t.consumeLexeme();if(void 0!=r){t.currentClause.term=r.str.toLowerCase(),r.str.indexOf("*")!=-1&&(t.currentClause.usePipeline=!1);var i=t.peekLexeme();if(void 0==i)return void t.nextClause();switch(i.type){case e.QueryLexer.TERM:return t.nextClause(),e.QueryParser.parseTerm;case e.QueryLexer.FIELD:return t.nextClause(),e.QueryParser.parseField;case e.QueryLexer.EDIT_DISTANCE:return e.QueryParser.parseEditDistance;case e.QueryLexer.BOOST:return e.QueryParser.parseBoost;case e.QueryLexer.PRESENCE:return t.nextClause(),e.QueryParser.parsePresence;default:var n="Unexpected lexeme type '"+i.type+"'";throw new e.QueryParseError(n,i.start,i.end)}}},e.QueryParser.parseEditDistance=function(t){var r=t.consumeLexeme();if(void 0!=r){var i=parseInt(r.str,10);if(isNaN(i)){var n="edit distance must be numeric";throw new e.QueryParseError(n,r.start,r.end)}t.currentClause.editDistance=i;var s=t.peekLexeme();if(void 0==s)return void t.nextClause();switch(s.type){case e.QueryLexer.TERM:return t.nextClause(),e.QueryParser.parseTerm;case e.QueryLexer.FIELD:return t.nextClause(),e.QueryParser.parseField;case e.QueryLexer.EDIT_DISTANCE:return e.QueryParser.parseEditDistance;case e.QueryLexer.BOOST:return e.QueryParser.parseBoost;case e.QueryLexer.PRESENCE:return t.nextClause(),e.QueryParser.parsePresence;default:var n="Unexpected lexeme type '"+s.type+"'";throw new e.QueryParseError(n,s.start,s.end)}}},e.QueryParser.parseBoost=function(t){var r=t.consumeLexeme();if(void 0!=r){var i=parseInt(r.str,10);if(isNaN(i)){var n="boost must be numeric";throw new e.QueryParseError(n,r.start,r.end)}t.currentClause.boost=i;var s=t.peekLexeme();if(void 0==s)return void t.nextClause();switch(s.type){case e.QueryLexer.TERM:return t.nextClause(),e.QueryParser.parseTerm;case e.QueryLexer.FIELD:return t.nextClause(),e.QueryParser.parseField;case e.QueryLexer.EDIT_DISTANCE:return e.QueryParser.parseEditDistance;case e.QueryLexer.BOOST:return e.QueryParser.parseBoost;case e.QueryLexer.PRESENCE:return t.nextClause(),e.QueryParser.parsePresence;default:var n="Unexpected lexeme type '"+s.type+"'";throw new e.QueryParseError(n,s.start,s.end)}}},function(e,t){"function"==typeof define&&define.amd?define(t):"object"==typeof exports?module.exports=t():e.lunr=t()}(this,function(){return e})}();
diff --git a/assets/minima-social-icons.svg b/assets/minima-social-icons.svg
deleted file mode 100755
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diff --git a/categories/index.html b/categories/index.html
deleted file mode 100755
index 336c7a1..0000000
--- a/categories/index.html
+++ /dev/null
@@ -1,721 +0,0 @@
-<div class="home">
-
-
-<h2>Contents</h2>
-
-  
-  
-  
-
-  <ul>
-  
-    <li><a href="#announcements">announcements</a></li>
-  
-    <li><a href="#apps">apps</a></li>
-  
-    <li><a href="#benefits">benefits</a></li>
-  
-    <li><a href="#business-taxation">business-taxation</a></li>
-  
-    <li><a href="#compute-studio">compute-studio</a></li>
-  
-    <li><a href="#corporate-income-tax">corporate-income-tax</a></li>
-  
-    <li><a href="#cost-of-capital-calculator">cost-of-capital-calculator</a></li>
-  
-    <li><a href="#data">data</a></li>
-  
-    <li><a href="#data-fusion">data-fusion</a></li>
-  
-    <li><a href="#demo-days">demo-days</a></li>
-  
-    <li><a href="#documentation">documentation</a></li>
-  
-    <li><a href="#getting-started">getting-started</a></li>
-  
-    <li><a href="#GH-actions">GH-actions</a></li>
-  
-    <li><a href="#git">git</a></li>
-  
-    <li><a href="#github">github</a></li>
-  
-    <li><a href="#individual-income-tax">individual-income-tax</a></li>
-  
-    <li><a href="#jupyter-book">jupyter-book</a></li>
-  
-    <li><a href="#macroeconomics">macroeconomics</a></li>
-  
-    <li><a href="#microdf">microdf</a></li>
-  
-    <li><a href="#OG-USA">OG-USA</a></li>
-  
-    <li><a href="#open-source">open-source</a></li>
-  
-    <li><a href="#overlapping-generations">overlapping-generations</a></li>
-  
-    <li><a href="#policy-simulation-library">policy-simulation-library</a></li>
-  
-    <li><a href="#PSL">PSL</a></li>
-  
-    <li><a href="#psl">psl</a></li>
-  
-    <li><a href="#PSL-Foundation">PSL-Foundation</a></li>
-  
-    <li><a href="#psl-foundation">psl-foundation</a></li>
-  
-    <li><a href="#python">python</a></li>
-  
-    <li><a href="#Python">Python</a></li>
-  
-    <li><a href="#R">R</a></li>
-  
-    <li><a href="#scf">scf</a></li>
-  
-    <li><a href="#synthimpute">synthimpute</a></li>
-  
-    <li><a href="#tax">tax</a></li>
-  
-    <li><a href="#tax-brain">tax-brain</a></li>
-  
-    <li><a href="#Tax-Calculator">Tax-Calculator</a></li>
-  
-    <li><a href="#tax-calculator">tax-calculator</a></li>
-  
-    <li><a href="#tax-cruncher">tax-cruncher</a></li>
-  
-    <li><a href="#taxes">taxes</a></li>
-  
-    <li><a href="#unit-testing">unit-testing</a></li>
-  
-    <li><a href="#us">us</a></li>
-  
-    <li><a href="#workflow">workflow</a></li>
-  
-    <li><a href="#Workshop">Workshop</a></li>
-  
-  </ul>
-
-  
-      <h3 id ="announcements"><i class="fas fa-tags category-tags-icon"></i></i> announcements</h3>
-      <a name="announcements"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/introducing-psl-blog">Introducing the PSL Blog</a>  • Nov 6, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="apps"><i class="fas fa-tags category-tags-icon"></i></i> apps</h3>
-      <a name="apps"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-policyengine-us">Demo Day: Modeling taxes and benefits with the PolicyEngine US web app</a>  • Apr 12, 2022</p>
-        </article>
-        
-      
-  
-      <h3 id ="benefits"><i class="fas fa-tags category-tags-icon"></i></i> benefits</h3>
-      <a name="benefits"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cambridge-cash-assistance">Demo Day: How does targeted cash assistance affect incentives to work?</a>  • Jul 14, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-policyengine-us">Demo Day: Modeling taxes and benefits with the PolicyEngine US web app</a>  • Apr 12, 2022</p>
-        </article>
-        
-      
-  
-      <h3 id ="business-taxation"><i class="fas fa-tags category-tags-icon"></i></i> business-taxation</h3>
-      <a name="business-taxation"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-ccc-international">Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator</a>  • Apr 18, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cost-of-capital-calculator">Demo Day: Cost-of-Capital-Calculator Web Application</a>  • Dec 3, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="compute-studio"><i class="fas fa-tags category-tags-icon"></i></i> compute-studio</h3>
-      <a name="compute-studio"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cs-auto-deploy">Demo Day: Deploying apps on Compute Studio</a>  • Sep 20, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-how-to-use-og-usa">Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy</a>  • Jan 28, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="corporate-income-tax"><i class="fas fa-tags category-tags-icon"></i></i> corporate-income-tax</h3>
-      <a name="corporate-income-tax"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-ccc-international">Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator</a>  • Apr 18, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cost-of-capital-calculator">Demo Day: Cost-of-Capital-Calculator Web Application</a>  • Dec 3, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="cost-of-capital-calculator"><i class="fas fa-tags category-tags-icon"></i></i> cost-of-capital-calculator</h3>
-      <a name="cost-of-capital-calculator"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-ccc-international">Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator</a>  • Apr 18, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cost-of-capital-calculator">Demo Day: Cost-of-Capital-Calculator Web Application</a>  • Dec 3, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="data"><i class="fas fa-tags category-tags-icon"></i></i> data</h3>
-      <a name="data"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-constructing-tax-data-for-the-50-states">Demo Day: Constructing tax data for the 50 states</a>  • Jul 16, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="data-fusion"><i class="fas fa-tags category-tags-icon"></i></i> data-fusion</h3>
-      <a name="data-fusion"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-synthimpute">Demo Day: Using synthimpute for data fusion</a>  • Dec 8, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="demo-days"><i class="fas fa-tags category-tags-icon"></i></i> demo-days</h3>
-      <a name="demo-days"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cambridge-cash-assistance">Demo Day: How does targeted cash assistance affect incentives to work?</a>  • Jul 14, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-github">Demo Day: Getting Started with GitHub</a>  • Jun 28, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-ccc-international">Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator</a>  • Apr 18, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-policyengine-us">Demo Day: Modeling taxes and benefits with the PolicyEngine US web app</a>  • Apr 12, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-synthimpute">Demo Day: Using synthimpute for data fusion</a>  • Dec 8, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-og-core">Demo Day: The OG-Core platform</a>  • Nov 1, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cs-auto-deploy">Demo Day: Deploying apps on Compute Studio</a>  • Sep 20, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-unit-testing">Demo Day: Unit testing for open source projects</a>  • Aug 9, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-constructing-tax-data-for-the-50-states">Demo Day: Constructing tax data for the 50 states</a>  • Jul 16, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-brain-python-api">Demo Day: Using the TaxBrain Python API</a>  • Jun 14, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-jupyter-book-deploy">Demo Day: Updating Jupyter Book documentation with GitHub Actions</a>  • May 17, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-stacked-revenue-estimates">Demo Day: Producing stacked revenue estimates with the Tax-Calculator Python API</a>  • Apr 5, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cs-api-stitch">Demo Day: Stitching together apps on Compute Studio</a>  • Mar 8, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-taxbrain-to-taxcruncher">Demo Day: Moving policy reform files from Tax-Brain to Tax-Cruncher</a>  • Mar 2, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-contributing-psl">Demo Day: Contributing to PSL projects</a>  • Mar 2, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-scf-microdf">Demo Day: Running the scf and microdf Python packages in Google Colab</a>  • Jan 29, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-how-to-use-og-usa">Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy</a>  • Jan 28, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-brain">Demo Day: Tax-Brain</a>  • Dec 23, 2020</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cost-of-capital-calculator">Demo Day: Cost-of-Capital-Calculator Web Application</a>  • Dec 3, 2020</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-cruncher">Demo Day: Tax-Cruncher</a>  • Nov 23, 2020</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-creating-reform-files">Demo Day: Building policy reform files</a>  • Nov 18, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="documentation"><i class="fas fa-tags category-tags-icon"></i></i> documentation</h3>
-      <a name="documentation"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-jupyter-book-deploy">Demo Day: Updating Jupyter Book documentation with GitHub Actions</a>  • May 17, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="getting-started"><i class="fas fa-tags category-tags-icon"></i></i> getting-started</h3>
-      <a name="getting-started"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-github">Demo Day: Getting Started with GitHub</a>  • Jun 28, 2022</p>
-        </article>
-        
-      
-  
-      <h3 id ="GH-actions"><i class="fas fa-tags category-tags-icon"></i></i> GH-actions</h3>
-      <a name="GH-actions"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-jupyter-book-deploy">Demo Day: Updating Jupyter Book documentation with GitHub Actions</a>  • May 17, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="git"><i class="fas fa-tags category-tags-icon"></i></i> git</h3>
-      <a name="git"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-github">Demo Day: Getting Started with GitHub</a>  • Jun 28, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-contributing-psl">Demo Day: Contributing to PSL projects</a>  • Mar 2, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="github"><i class="fas fa-tags category-tags-icon"></i></i> github</h3>
-      <a name="github"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-github">Demo Day: Getting Started with GitHub</a>  • Jun 28, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-contributing-psl">Demo Day: Contributing to PSL projects</a>  • Mar 2, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="individual-income-tax"><i class="fas fa-tags category-tags-icon"></i></i> individual-income-tax</h3>
-      <a name="individual-income-tax"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-brain-python-api">Demo Day: Using the TaxBrain Python API</a>  • Jun 14, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-stacked-revenue-estimates">Demo Day: Producing stacked revenue estimates with the Tax-Calculator Python API</a>  • Apr 5, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-brain">Demo Day: Tax-Brain</a>  • Dec 23, 2020</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-cruncher">Demo Day: Tax-Cruncher</a>  • Nov 23, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="jupyter-book"><i class="fas fa-tags category-tags-icon"></i></i> jupyter-book</h3>
-      <a name="jupyter-book"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-jupyter-book-deploy">Demo Day: Updating Jupyter Book documentation with GitHub Actions</a>  • May 17, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="macroeconomics"><i class="fas fa-tags category-tags-icon"></i></i> macroeconomics</h3>
-      <a name="macroeconomics"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-og-core">Demo Day: The OG-Core platform</a>  • Nov 1, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="microdf"><i class="fas fa-tags category-tags-icon"></i></i> microdf</h3>
-      <a name="microdf"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-scf-microdf">Demo Day: Running the scf and microdf Python packages in Google Colab</a>  • Jan 29, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="OG-USA"><i class="fas fa-tags category-tags-icon"></i></i> OG-USA</h3>
-      <a name="OG-USA"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-how-to-use-og-usa">Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy</a>  • Jan 28, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="open-source"><i class="fas fa-tags category-tags-icon"></i></i> open-source</h3>
-      <a name="open-source"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-how-to-use-og-usa">Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy</a>  • Jan 28, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="overlapping-generations"><i class="fas fa-tags category-tags-icon"></i></i> overlapping-generations</h3>
-      <a name="overlapping-generations"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-og-core">Demo Day: The OG-Core platform</a>  • Nov 1, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="policy-simulation-library"><i class="fas fa-tags category-tags-icon"></i></i> policy-simulation-library</h3>
-      <a name="policy-simulation-library"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cs-auto-deploy">Demo Day: Deploying apps on Compute Studio</a>  • Sep 20, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-how-to-use-og-usa">Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy</a>  • Jan 28, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="PSL"><i class="fas fa-tags category-tags-icon"></i></i> PSL</h3>
-      <a name="PSL"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/DC-workshop">Policy Simulation Library DC Workshop: Open source tools for analyzing tax policy</a>  • Mar 3, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cs-api-stitch">Demo Day: Stitching together apps on Compute Studio</a>  • Mar 8, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-contributing-psl">Demo Day: Contributing to PSL projects</a>  • Mar 2, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="psl"><i class="fas fa-tags category-tags-icon"></i></i> psl</h3>
-      <a name="psl"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/2023-year-in-review">2023: A year in review</a>  • Dec 28, 2023</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/2022-year-in-review">2022: A year in review</a>  • Dec 31, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/2021-year-in-review">2021: A year in review</a>  • Dec 28, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/2020-year-in-review">2020: A year in review</a>  • Dec 23, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="PSL-Foundation"><i class="fas fa-tags category-tags-icon"></i></i> PSL-Foundation</h3>
-      <a name="PSL-Foundation"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/DC-workshop">Policy Simulation Library DC Workshop: Open source tools for analyzing tax policy</a>  • Mar 3, 2022</p>
-        </article>
-        
-      
-  
-      <h3 id ="psl-foundation"><i class="fas fa-tags category-tags-icon"></i></i> psl-foundation</h3>
-      <a name="psl-foundation"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/2023-year-in-review">2023: A year in review</a>  • Dec 28, 2023</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/2022-year-in-review">2022: A year in review</a>  • Dec 31, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/2021-year-in-review">2021: A year in review</a>  • Dec 28, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/2020-year-in-review">2020: A year in review</a>  • Dec 23, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="python"><i class="fas fa-tags category-tags-icon"></i></i> python</h3>
-      <a name="python"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-synthimpute">Demo Day: Using synthimpute for data fusion</a>  • Dec 8, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-og-core">Demo Day: The OG-Core platform</a>  • Nov 1, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="Python"><i class="fas fa-tags category-tags-icon"></i></i> Python</h3>
-      <a name="Python"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-unit-testing">Demo Day: Unit testing for open source projects</a>  • Aug 9, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="R"><i class="fas fa-tags category-tags-icon"></i></i> R</h3>
-      <a name="R"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-unit-testing">Demo Day: Unit testing for open source projects</a>  • Aug 9, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="scf"><i class="fas fa-tags category-tags-icon"></i></i> scf</h3>
-      <a name="scf"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-scf-microdf">Demo Day: Running the scf and microdf Python packages in Google Colab</a>  • Jan 29, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="synthimpute"><i class="fas fa-tags category-tags-icon"></i></i> synthimpute</h3>
-      <a name="synthimpute"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-synthimpute">Demo Day: Using synthimpute for data fusion</a>  • Dec 8, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="tax"><i class="fas fa-tags category-tags-icon"></i></i> tax</h3>
-      <a name="tax"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-constructing-tax-data-for-the-50-states">Demo Day: Constructing tax data for the 50 states</a>  • Jul 16, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="tax-brain"><i class="fas fa-tags category-tags-icon"></i></i> tax-brain</h3>
-      <a name="tax-brain"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-brain-python-api">Demo Day: Using the TaxBrain Python API</a>  • Jun 14, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-stacked-revenue-estimates">Demo Day: Producing stacked revenue estimates with the Tax-Calculator Python API</a>  • Apr 5, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-brain">Demo Day: Tax-Brain</a>  • Dec 23, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="Tax-Calculator"><i class="fas fa-tags category-tags-icon"></i></i> Tax-Calculator</h3>
-      <a name="Tax-Calculator"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-how-to-use-og-usa">Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy</a>  • Jan 28, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="tax-calculator"><i class="fas fa-tags category-tags-icon"></i></i> tax-calculator</h3>
-      <a name="tax-calculator"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-brain-python-api">Demo Day: Using the TaxBrain Python API</a>  • Jun 14, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-stacked-revenue-estimates">Demo Day: Producing stacked revenue estimates with the Tax-Calculator Python API</a>  • Apr 5, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="tax-cruncher"><i class="fas fa-tags category-tags-icon"></i></i> tax-cruncher</h3>
-      <a name="tax-cruncher"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-cruncher">Demo Day: Tax-Cruncher</a>  • Nov 23, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="taxes"><i class="fas fa-tags category-tags-icon"></i></i> taxes</h3>
-      <a name="taxes"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-ccc-international">Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator</a>  • Apr 18, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-policyengine-us">Demo Day: Modeling taxes and benefits with the PolicyEngine US web app</a>  • Apr 12, 2022</p>
-        </article>
-        
-      
-  
-      <h3 id ="unit-testing"><i class="fas fa-tags category-tags-icon"></i></i> unit-testing</h3>
-      <a name="unit-testing"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-unit-testing">Demo Day: Unit testing for open source projects</a>  • Aug 9, 2021</p>
-        </article>
-        
-      
-  
-      <h3 id ="us"><i class="fas fa-tags category-tags-icon"></i></i> us</h3>
-      <a name="us"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-cambridge-cash-assistance">Demo Day: How does targeted cash assistance affect incentives to work?</a>  • Jul 14, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-policyengine-us">Demo Day: Modeling taxes and benefits with the PolicyEngine US web app</a>  • Apr 12, 2022</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-constructing-tax-data-for-the-50-states">Demo Day: Constructing tax data for the 50 states</a>  • Jul 16, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-how-to-use-og-usa">Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy</a>  • Jan 28, 2021</p>
-        </article>
-        
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-tax-brain">Demo Day: Tax-Brain</a>  • Dec 23, 2020</p>
-        </article>
-        
-      
-  
-      <h3 id ="workflow"><i class="fas fa-tags category-tags-icon"></i></i> workflow</h3>
-      <a name="workflow"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/demo-day-github">Demo Day: Getting Started with GitHub</a>  • Jun 28, 2022</p>
-        </article>
-        
-      
-  
-      <h3 id ="Workshop"><i class="fas fa-tags category-tags-icon"></i></i> Workshop</h3>
-      <a name="Workshop"></a>
-      
-        <article class="archive-item">
-          <p class="post-meta post-meta-title"><a class="page-meta" href="/DC-workshop">Policy Simulation Library DC Workshop: Open source tools for analyzing tax policy</a>  • Mar 3, 2022</p>
-        </article>
-        
-      
-  
-
-
-
-
-</div>
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diff --git a/demo-day-cambridge-cash-assistance.html b/demo-day-cambridge-cash-assistance.html
deleted file mode 100755
index 3f575e6..0000000
--- a/demo-day-cambridge-cash-assistance.html
+++ /dev/null
@@ -1,60 +0,0 @@
-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: How does targeted cash assistance affect incentives to work?</h1><p class="page-description">How a proposed program in Cambridge, Massachusetts would affect poverty and incentives.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2022-07-14T00:00:00-05:00" itemprop="datePublished">
-        Jul 14, 2022
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Max Ghenis</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#benefits">benefits</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#us">us</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/IPcjZnwNPdY" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>In this week’s Demo Day, I shared my paper published at the <a href="https://thecgo.org">Center for Growth and Opportunity</a> in June.
-<a href="https://www.thecgo.org/research/how-does-targeted-cash-assistance-affect-incentives-to-work/">“How does targeted cash assistance affect incentives to work?”</a> analyzed a program Mayor Sumbul Siddiqui proposed in Cambridge, Massachusetts to provide $500 per month for 18 months to all families with dependents and income below 200% of the poverty line.</p>
-
-<p>Targeted programs like these are common in guaranteed income pilots, and in some enacted policies, and I find that it would cost-effectively reduce poverty: if expanded to Massachusetts, it would cost $1.2 billion per year and cut child poverty 42%.</p>
-
-<p>However, that targeting comes at a cost.
-Using the <a href="https://openfisca.us">OpenFisca US</a> microsimulation model (supported by the Center for Growth and Opportunity and cataloged by the Policy Simulation Library), I find that the program would deepen an existing welfare cliff at 200% of the poverty line.
-For example, a family of four would lose over $19,000 total—$9,000 from the cash assistance and $10,000 from other benefits—once they earn a dollar above 200% of the poverty line (about $55,000).
-To recover those lost benefits, they would have to earn an additional $26,000, a range I call the “earnings dead zone”.</p>
-
-<p>My presentation reviews these trends in both <a href="https://docs.google.com/presentation/d/1sWJ1VrSKFLdj1nw6IuRF65XoI1sTBDk7QgF3UHMcF34">slides</a> and the <a href="https://policyengine.org/us">PolicyEngine US</a> app for computing the impacts of tax and benefit policy.
-For example, I show how <a href="https://policyengine.org/us/household?abolish_snap_ea=1">repealing the SNAP emergency allotment</a> would smooth out welfare cliffs, while reducing resources available to low-income families, and how a universal child allowance avoids work disincentives while less cost-effectively reducing poverty.</p>
-
-<p>Policymakers face trade-offs between equity and efficiency, and typically labor supply responses consider marginal tax rates.
-With their infinite marginal tax rates, welfare cliffs are a less explored area, even though they surface in several parts of the tax and benefit system.
-This paper makes a start, but more research is yet to be done.</p>
-
-  </div><a class="u-url" href="/demo-day-cambridge-cash-assistance" hidden></a>
-</article>
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diff --git a/demo-day-ccc-international.html b/demo-day-ccc-international.html
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator</h1><p class="page-description">Using Cost-of-Capital-Calculator with data on international business tax policies.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2022-04-18T00:00:00-05:00" itemprop="datePublished">
-        Apr 18, 2022
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#cost-of-capital-calculator">cost-of-capital-calculator</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#business-taxation">business-taxation</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#corporate-income-tax">corporate-income-tax</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#taxes">taxes</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/JbVXRSbb2Dk" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>In the Demo Day video shared here, I show how to use open source tools to analyze international corporate tax competitiveness.
-The two main tools illustrated are the <a href="https://ccc.pslmodels.org/content/intro.html">Cost-of-Capital-Calculator</a> (CCC), a model to compute measures of the tax burden on new investments, and <a href="https://taxfoundation.org/publications/international-tax-competitiveness-index/">Tax Foundation’s International Tax Competitiveness Index</a> (ITCI).</p>
-
-<p>Tax Foundation has made many helpful resources available online.
-Their measures of international business tax policy are a great example of this.
-The ICTI outputs and inputs are all well documented, with source code to reproduce results <a href="https://github.com/TaxFoundation/international-tax-competitiveness-index/">available on GitHub</a>.</p>
-
-<p>I plug Tax Foundation’s country-by-country data into CCC functions using it’s Python API.
-Because CCC is designed to flexibly take array or scalar data, operating on rows of tabular data, such as that in the ITCI, is relatively straight-forward.
-The Google <a href="https://colab.research.google.com/drive/1t_NDNqP5-Aq_vsOkGO9SE1Qj4oEVCqCN?usp=sharing">Colab notebook</a> I walk through in this Demo Day, can be a helpful example to follow if you’d like to do something similar to this with the Tax Foundation data - or your own data source.
-From the basic building blocks there (reading in data, calling CCC functions), you can extend the analysis in a number of ways.
-For example adding additional years of data (Tax Foundation posts their data back to 2014), modifying economic assumptions, or creating counter-factual policy experiments across sets of countries.</p>
-
-<p>If you find this example useful, or have questions or suggestions about this type of analysis, please feel free to <a href="mailto:jason.debacker@gmail.com">reach out to me</a>.</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://colab.research.google.com/drive/1t_NDNqP5-Aq_vsOkGO9SE1Qj4oEVCqCN?usp=sharing">Colab Notebook</a></li>
-  <li><a href="https://taxfoundation.org/publications/international-tax-competitiveness-index/">Tax Foundation International Tax Competitiveness Index 2021</a></li>
-  <li><a href="https://github.com/TaxFoundation/international-tax-competitiveness-index/tree/master/final_data">GitHub repo for Tax Foundation ITCI data</a></li>
-  <li><a href="https://ccc.pslmodels.org/content/intro.html">Cost-of-Capital-Calculator documentation</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-ccc-international" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Constructing tax data for the 50 states</h1><p class="page-description">A new dataset to facilitate state-level analysis of federal tax reforms.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-07-16T00:00:00-05:00" itemprop="datePublished">
-        Jul 16, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Don Boyd</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#tax">tax</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#data">data</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#us">us</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/gnYKHtdSqbY" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>Federal income tax reform impacts can vary dramatically across states. 
-The cap on state and local tax deductions (SALT) is a well-known example, but other policies also have differential effects because important tax-relevant features vary across states such as the income distribution, relative importance of wage, business, and retirement income, and family size and structure.
-Analyzing how policy impacts vary across states requires data that faithfully represent the characteristics of the 50 states.</p>
-
-<p>This Demo Day described a method and software for constructing state weights for microdata files that (1) come as close as possible to targets for individual states, while (2) ensuring that the state weights for each tax record sum to its national weight.
-The latter objective ensures that the sum of state impacts for a tax reform equals the national impact.</p>
-
-<p>This project developed state weights for a data file with more than 200,000 microdata records.
-The weighted data file comes within 0.01% of desired values for more than 95% of approximately 10,000 targets.</p>
-
-<p>The goal of the <a href="https://github.com/donboyd5/slides/blob/master/2021-07-12_Boyd_PSL_Demo_Constructing_State_Tax_Weights_For_PUF.pdf">slides</a> and <a href="https://youtu.be/gnYKHtdSqbY">video</a> was to enable a motivated Python-skilled user of the PSL <a href="https://github.com/PSLmodels/taxdata">TaxData</a> and <a href="https://taxcalc.pslmodels.org">Tax-Calculator</a> projects to reproduce project results: 50-state weights for TaxData’s primary output, the puf.csv microdata file (based primarily on an IRS Public Use File), using early-stage open-source software developed in the project.
-Thus, the demo is technical and focused on nuts and bolts.</p>
-
-<p>The methods and software can also be used to:</p>
-<ul>
-  <li>Create geographic-area weights for other microdata files</li>
-  <li>Apportion state weights to Congressional Districts or counties, if suitable targets can be developed</li>
-  <li>Create state-specific microdata files suitable for modeling state income taxes</li>
-</ul>
-
-<p>The main topics covered in the slides and video are:</p>
-<ul>
-  <li>Creating national and state targets from IRS summary data</li>
-  <li>Preparing a national microdata file for state weighting</li>
-  <li>Approaches to constructing geographic weights</li>
-  <li>Running software that implements the Poisson-modeling approach used in the project</li>
-  <li>Measures of quality of the results</li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-constructing-tax-data-for-the-50-states" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Contributing to PSL projects</h1><p class="page-description">How to help software projects in the Policy Simulation Library.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-03-02T00:00:00-06:00" itemprop="datePublished">
-        Mar 2, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      2 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#PSL">PSL</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#git">git</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#github">github</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/LZUPYJ0RwJM" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>In the most recent PSL Demo Day, I illustrate how to contribute to PSL projects.
- The open source nature of projects in the PSL catalog allows anyone to contribute.
- The modularity of the code, coupled with robust testing, means that one can bite off small pieces that help improve the models and remain confident those changes work as expected.</p>
-
-<p>To begin the process of finding where to contribute to PSL projects, I advise looking through the <a href="https://github.com/PSLmodels">PSL GitHub Organization</a> to see what projects interest you.
-Once a project of interest is identified, looking over the open “Issues” can provide a sense of where model maintainers and users are looking for help (see especially the “Help Wanted” tags).
-It is also completely appropriate to create a new Issue to express interest in helping and ask for direction on where that might best be done given your experience and preferences.</p>
-
-<p>When you are ready to begin to contribute to a project, you’ll want to fork and clone the GitHub repository to help you get the files on your local machine and ready for you to work with.
-Many PSL projects outline the detailed steps to get you up and running.
-For example, see the <a href="https://pslmodels.github.io/Tax-Calculator/contributing/contributor_guide.html">Tax-Calculator Contributor Guide</a>, which outlines the step-by-step process for doing this and confirming that everything works as expected on your computer.</p>
-
-<p>After you are set up and ready to begin modifying source code for the PSL project(s) you’re interested in contributing to, you can reference the PSL-incubating <a href="https://pslmodels.github.io/Git-Tutorial/content/intro.html">Git-Tutorial project</a> that provides more details on the Git workflow followed by most PSL projects.</p>
-
-<p>As you contribute, you may want to get more involved in the community.
-A couple ways to do this are to join any of the <a href="https://pslmodels.org/events.html">PSL community events</a>, all of which are open to the public, and to post to the <a href="http://discourse.pslmodels.org">PSL Discourse Forums</a>.
-These are great places to meet community members and ask questions about how and where to best contribute.</p>
-
-<p>I hope this helps you get started as a PSL contributor – we look forward to getting you involved in making policy analysis better and more transparent!</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://pslmodels.github.io/Git-Tutorial/content/intro.html">PSL Git-Tutorial</a></li>
-  <li><a href="https://pslmodels.org/events.html">PSL community events</a></li>
-  <li><a href="http://discourse.pslmodels.org">PSL Discourse Forums</a></li>
-  <li><a href="https://pslmodels.github.io/Tax-Calculator/contributing/contributor_guide.html">Tax-Calculator Contributor Guide</a></li>
-  <li><a href="https://github.com/PSLmodels">PSL GitHub Organization</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-contributing-psl" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Cost-of-Capital-Calculator Web Application</h1><p class="page-description">Computing the impact of taxes on business investment incentives under alternative policy scenarios.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2020-12-03T00:00:00-06:00" itemprop="datePublished">
-        Dec 3, 2020
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#cost-of-capital-calculator">cost-of-capital-calculator</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#business-taxation">business-taxation</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#corporate-income-tax">corporate-income-tax</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/KLIuFbYPpNA" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>In the PSL Demo Day video linked above, I demonstrate how to use the Cost-of-Capital-Calculator (CCC) web application on <a href="https://compute.studio">Compute-Studio</a>.
-CCC computes various measures of the impact of the tax system on business investment.
-These include the <a href="http://piketty.pse.ens.fr/files/HallJorgenson67.pdf">Hall-Jorgenson cost of capital</a>, <a href="http://webarchive.urban.org/UploadedPDF/1000538.pdf">marginal effective tax rates</a>, and effective average tax rates (following the methodology of <a href="https://www.ifs.org.uk/wps/wp9816.pdf">Devereux and Griffith (1999)</a>).</p>
-
-<p>I begin by illustrating the various parameters available for the user to manipulate.
-These include parameters of the business and individual income tax systems, as well as parameters representing economic assumptions (e.g., inflation rates and nominal interest rates) and parameters dictating financial and accounting policy (e.g., the fraction of financing using debt).
-Note that all default values for tax policy parameters represent the “baseline policy”, which is defined as the current law policy in the year being analyzed (which itself is a parameter the user can change).
-Other parameters are estimated using historical data following the methodology of <a href="https://www.cbo.gov/sites/default/files/113th-congress-2013-2014/reports/49817-taxingcapitalincome0.pdf">CBO (2014)</a>.</p>
-
-<p>Next, I change a few parameters and run the model.
-In this example, I move the corporate income tax rate up to 28% and lower bonus depreciation for assets with depreciable lives of 20 years or less to 50%.</p>
-
-<p>Finally, I discuss how to interpret output.
-The web app returns a table and three figures summarizing marginal effective total tax rates on new investments.
-This selection of output helps give one a sense of the the overall changes, as well as effects across asset types, industries, and type of financing.
-For the full model output, one can click on “Download Results”.
-Doing so will download four CSV files contain several measures of the impact of the tax system on investment for very fine asset and industry categories.
-Users can take these files and create tables and visualizations relevant to their own use case.</p>
-
-<p>Please take the model for a spin and simulate your own reform.
-If you have questions, comments, or suggestions, please let me know on the <a href="http://discourse.pslmodels.org">PSL Discourse</a> (non-technical questions) or by opening an issue in the <a href="https://github.com/PSLmodels/Cost-of-Capital-Calculator/issues">CCC GitHub repository</a> (technical questions).</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://compute.studio/PSLmodels/Cost-of-Capital-Calculator/104/">Compute Studio simulation used in the demonstration</a></li>
-  <li><a href="https://compute.studio/PSLmodels/Cost-of-Capital-Calculator/">Cost-of-Capital-Calculator web app</a></li>
-  <li><a href="https://pslmodels.github.io/Cost-of-Capital-Calculator/content/intro.html">Cost-of-Capital-Calculator documentation</a></li>
-  <li><a href="https://github.com/PSLmodels/Cost-of-Capital-Calculator/">Cost-of-Capital-Calculator GitHub repository</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-cost-of-capital-calculator" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Building policy reform files</h1><p class="page-description">The first in Policy Simulation Library's new live demo series describes specifying tax reforms.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2020-11-18T00:00:00-06:00" itemprop="datePublished">
-        Nov 18, 2020
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Matt Jensen</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul><p>Check out the video:</p>
-
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/AFJq4ZrwEqA" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<p>We will host Demo Days every two weeks until the end of the year.
-You can see our schedule on <a href="https://www.pslmodels.org/events.html">our events page</a>.</p>
-
-<hr>
-
-<p>Show notes:</p>
-
-<p>I demonstrate how to build policy reform files using the Tax-Brain webapp on Compute Studio.
-(Useful links below.)
-This is an introductory lesson that ends with a cliffhanger.
-We don’t run the model.
-But we do generate an individual income and payroll tax reform file that is compatible with a range of policy simulation models and analytic tools, some designed for policy decision makers, others for taxpayers and benefits recipients interested in assessing their own circumstances.</p>
-
-<p>Beyond individual and payroll tax analysis, the reform file can be used with models that assess pass-through and corporate taxation of businesses, as well as a variety of income benefit programs.
-A wide range of use cases will occupy future events.</p>
-
-<p>Resources:</p>
-
-<ul>
-  <li><a href="https://https://compute.studio/PSLmodels/Tax-Brain/48422/">Demo C/S simulation</a></li>
-  <li><a href="https://https://www.irs.gov/pub/irs-pdf/f1040.pdf">IRS Form 1040</a></li>
-  <li><a href="https://https://www.pslmodels.org/Catalog/index.html">PSL Catalog</a></li>
-  <li><a href="https://https://www.pslmodels.org/events.html">PSL Events</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-creating-reform-files" hidden></a>
-</article>
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diff --git a/demo-day-cs-api-stitch.html b/demo-day-cs-api-stitch.html
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Stitching together apps on Compute Studio</h1><p class="page-description">Creating an app with the Compute Studio API.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-03-08T00:00:00-06:00" itemprop="datePublished">
-        Mar 8, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Hank Doupe</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#PSL">PSL</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/5I59dyB_2ws" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>In Demo Day 8, I talked about connecting multiple apps on <a href="https://compute.studio">Compute Studio</a> with <a href="https://stitch.hankdoupe.com">PSL Stitch</a>. The source code for PSL stitch can be found in this <a href="https://github.com/hdoupe/psl-stitch">repository</a>.</p>
-
-<p>Stitch is composed of three components:</p>
-
-<ul>
-  <li>A <a href="https://github.com/hdoupe/psl-stitch/tree/main/psl_stitch">python package</a> that can be run like a normal Python package.</li>
-  <li>A <a href="https://github.com/hdoupe/psl-stitch/tree/main/api">RESTful API</a> built with <a href="https://fastapi.tiangolo.com">FastAPI</a> that is called remotely to create simulations on Compute Studio.</li>
-  <li>A <a href="https://github.com/hdoupe/psl-stitch/tree/main/psl-stitch-app">GUI</a> built with <a href="https://reactjs.org/">ReactJS</a> that makes calls to the REST API to create and monitor simulations.</li>
-</ul>
-
-<p>One of the cool things about this app is that it uses <a href="https://paramtools.dev">ParamTools</a> to read the JSON files under the hood. This means that it can read links to data in other Compute Studio runs, files on GitHub, or just plain JSON. Here are some example parameters:</p>
-
-<ul>
-  <li>policy parameters: <code class="language-plaintext highlighter-rouge">cs://PSLmodels:Tax-Brain@49779/inputs/adjustment/policy</code>
-</li>
-  <li>tax-cruncher parameters: <code class="language-plaintext highlighter-rouge">{"sage": [{"value": 25}]}</code>
-</li>
-  <li>business tax parameters: <code class="language-plaintext highlighter-rouge">{"CIT_rate": [{"value": 0.25, "year": 2021}]}</code>
-</li>
-</ul>
-
-<p>After clicking run, three simulations will be created on Compute Studio and the app will update as soon as the simulations have finished:</p>
-
-<p><img src="https://user-images.githubusercontent.com/9206065/112211937-ca75db00-8bf2-11eb-856f-41c46e7e8ec5.png" alt="Getting started"></p>
-
-<p><img src="https://user-images.githubusercontent.com/9206065/112211931-c9dd4480-8bf2-11eb-83d8-678fd6d80dd9.png" alt="CS Simulations"></p>
-
-<p>Once they are done, the simulations are best viewed and interacted with on Compute Studio, but you can still inspect the JSON response from the Compute Studio API:</p>
-
-<p><img src="https://user-images.githubusercontent.com/9206065/112211930-c944ae00-8bf2-11eb-87dc-949ff3007229.png" alt="Simulation Complete"></p>
-
-<p>I created this app to show that it’s possible to build apps on top of the Compute Studio API. I think PSL Stitch is a neat example of how to do this, but I am even more excited to see what others build next.</p>
-
-<p>Also, this is an open source project and has lots of room for improvement. If you are interested in learning web technologies related to REST APIs and frontend development with JavaScript, then this project could be a good place to start!</p>
-
-<p>Resources:</p>
-
-<ul>
-  <li><a href="https://stitch.hankdoupe.com">PSL Stitch</a></li>
-  <li><a href="https://github.com/hdoupe/psl-stitch">Source code</a></li>
-  <li><a href="https://docs.compute.studio/api/guide.html">Compute Studio API Docs</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-cs-api-stitch" hidden></a>
-</article>
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+++ /dev/null
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Deploying apps on Compute Studio</h1><p class="page-description">How to deploy apps on Compute Studio using the new automated deployments feature.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-09-20T00:00:00-05:00" itemprop="datePublished">
-        Sep 20, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Hank Doupe</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      2 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#policy-simulation-library">policy-simulation-library</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#compute-studio">compute-studio</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <hr />
-
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/P1mzhZkwRt0" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr />
-
-<p>Compute Studio (C/S) is a platform for publishing and sharing computational models and data visualizations. In this demo day, I show how to publish your own project on C/S using the new automated deployments feature. You can find an in depth guide to publishing on C/S
-in the <a href="https://docs.compute.studio/publish/guide.html">developer docs</a>.</p>
-
-<p>C/S supports two types of projects: models and data visualizations. Models are fed some inputs and return a result. Data visualizations are web servers  backed by popular open-source libraries like Bokeh, Dash, or Streamlit. Models are good for long-running processes and producing archivable results that can be shared and returned to easily. Data visualizations are good for highly interactive and custom user experiences.</p>
-
-<p>Now that you’ve checked out the <a href="https://docs.compute.studio/publish/guide.html">developer docs</a> and set up your model or data-viz, you can head over to the C/S publishing page <a href="https://compute.studio/new/">https://compute.studio/new/</a> to publish your project. Note that this page is still very much under construction and may look different in a few weeks.</p>
-
-<p><img src="../images/cs-auto-deploy/publish_page.png" alt="Publish page" /></p>
-
-<p>Next, you will be sent to the second stage in the publish flow where you will provide more details on how to connect your project on C/S:</p>
-
-<p><img src="../images/cs-auto-deploy/connect_project_page.png" alt="Connect Project page" /></p>
-
-<p>Clicking “Connect App” will take you to the project home page:</p>
-
-<p><img src="../images/cs-auto-deploy/project_home_page.png" alt="Project home page" /></p>
-
-<p>Go to the “Settings” button in the top-right corner and this will take you to the project dashboard where you can modify everything from the social preview of your project to the amount of compute resources it needs:</p>
-
-<p><img src="../images/cs-auto-deploy/project_dashboard.png" alt="Project dashboard" /></p>
-
-<p>The “Builds” link in the sidebar will take you to the builds dashboard where you can create your first build:</p>
-
-<p><img src="../images/cs-auto-deploy/build_history_dashboard.png" alt="Build history dashboard" /></p>
-
-<p>It’s time to create the first build. You can do so by clicking “New Build”. This will take you to the build status page. While the build is being scheduled, the page will look like this:</p>
-
-<p><img src="../images/cs-auto-deploy/build_scheduled_page.png" alt="Build scheduled page" /></p>
-
-<p>You can click the “Build History” link and it will show that the build has been started:</p>
-
-<p><img src="../images/cs-auto-deploy/build_history_dashboard_progress.png" alt="Build history dashboard" /></p>
-
-<p>The build status page should be updated at this point and will look something like this:</p>
-
-<p><img src="../images/cs-auto-deploy/build_status_page_progress.png" alt="Build status page" /></p>
-
-<p>C/S automated deployments are built on top of <a href="https://github.com/features/actions">Github Actions</a>. Unfortunately, the logs in Github Actions are not available through the Github API until after the workflow is completely finished. The build status dashboard will update as the build progresses and once it’s done, you will have full access to the logs from the build. These will contain outputs from installing your project and the outputs from your project’s tests.</p>
-
-<p>In this case, the build failed. We can inspect the logs to see that an import error caused the failure:</p>
-
-<p><img src="../images/cs-auto-deploy/build_status_failed.png" alt="Build failed status page" /></p>
-
-<p><img src="../images/cs-auto-deploy/build_status_failed_logs.png" alt="Build failed status page with logs" /></p>
-
-<p>I pushed an update to my fork of Tax-Cruncher on Github and restarted the build by clicking “Failure. Start new Build”. The next build succeeded and we can click “Release” to publish the project:</p>
-
-<p><img src="../images/cs-auto-deploy/build_status_page_success.png" alt="Build status page success" /></p>
-
-<p>The builds dashboard now shows the two builds:</p>
-
-<p><img src="../images/cs-auto-deploy/updated_build_history_page.png" alt="Updated build history page" /></p>
-
-<p>Finally, let’s go run our new model:</p>
-
-<p><img src="../images/cs-auto-deploy/run_project_page_loading.png" alt="Run project page" /></p>
-
-<p>It may take a few seconds for the page to load. This is because the model code and all of its dependencies are being loaded onto the C/S servers for the first time:</p>
-
-<p><img src="../images/cs-auto-deploy/run_project_page_success.png" alt="Run project page with inputs form" /></p>
-
-<p>The steps for publishing a data visualization are very similar. The main idea is that you tell C/S what Python file your app lives in and C/S will know how to run it given your data visualization technology choice.</p>
-
-  </div><a class="u-url" href="/demo-day-cs-auto-deploy" hidden></a>
-</article>
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diff --git a/demo-day-github.html b/demo-day-github.html
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@@ -1,96 +0,0 @@
-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Getting Started with GitHub</h1><p class="page-description">The basics of forking and cloning repositories and working on branches.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2022-06-28T00:00:00-05:00" itemprop="datePublished">
-        Jun 28, 2022
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      2 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#github">github</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#git">git</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#workflow">workflow</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#getting-started">getting-started</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/ENl3AkZZgRQ" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>Git and GitHub often present themselves as barriers to entry to would-be contributors to PSL projects, even for those who are otherwise experienced with policy modeling.
-But these tools are critical to collaboration on open source projects.
-In the Demo Day video linked above, I cover some of the basics to get set up and begin contributing to an open source project.</p>
-
-<p>There are four steps I outline:</p>
-<ol>
-  <li>Create a “<a href="https://docs.github.com/en/get-started/quickstart/fork-a-repo">fork</a>” of the repository you are interested in.
-A fork is a copy of the source code that resides on GitHub (i.e., in the cloud).
-A fork gives you control over a copy of the source code.  You will be able to merge in changes to the code on this fork, even if you don’t have permissions to do so with the original repository.</li>
-  <li>“<a href="https://git-scm.com/book/en/v2/Git-Basics-Getting-a-Git-Repository">Clone</a>” the fork.
-Cloning will download a copy of the source code from your fork onto your local machine.
-But cloning is more than just downloading the source code.
-It will include the version history of the code and automatically create a link between the local files and the remote files on your fork.</li>
-  <li>Configure your local files to talk to both your fork (which has a default name of <code class="language-plaintext highlighter-rouge">origin</code>) and the original repository you forked from (which typically has the default name of <code class="language-plaintext highlighter-rouge">upstream</code>).
-Do this by using your command prompt or terminal to navigate to the directory you just cloned.
-From there, run:
-    <div class="language-plaintext highlighter-rouge">
-<div class="highlight"><pre class="highlight"><code>git remote add upstream URL_to_original_repo.git
-</code></pre></div>    </div>
-    <p>And check that this worked by giving the command:</p>
-    <div class="language-plaintext highlighter-rouge">
-<div class="highlight"><pre class="highlight"><code>git remote -v
-</code></pre></div>    </div>
-  </li>
-</ol>
-
-<p>If things worked, you should see URLs to your fork and the upstream repository with “(fetch)” and “(push)” by them
-More info on this is in the <a href="https://git-scm.com/book/en/v2/Git-Basics-Working-with-Remotes">Git docs</a>.</p>
-
-<ol>
-  <li>Now that you have copies of the source code on your fork and on your local machine, you are ready to begin contributing.
-As you make changes to the source code, you’ll want to work on <a href="https://git-scm.com/book/en/v2/Git-Branching-Basic-Branching-and-Merging">development branches</a>.
-Branches are copies of the code. Ideally, you keep your “main” (or “master”) branch clean (i.e., your best version of the code) and develop the code on branches.
-When you’ve completed the development work (e.g., adding a new feature) you will them merge this into the “main” branch.</li>
-</ol>
-
-<p>I hope this helps you get started contributing to open source projects.
-Git and GitHub are valuable tools and there is lots more to learn, but these basics will get you going.
-For more information, see the links below.
-If you want to get started working with a project in the Library, feel free to reach out to me through the relevant repo (<a href="https://github.com/jdebacker/">@jdebacker on GitHub</a>) or drop into a PSL Community Call (dates on the <a href="http://pslmodels.org/events.html">PSL Calendar</a>).</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://pslmodels.github.io/Git-Tutorial/content/intro.html">PSL Git Tutorial</a></li>
-  <li><a href="https://git-scm.com/book/en/v2/Git-Basics-Getting-a-Git-Repository">Git Basics</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-github" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy</h1><p class="page-description">How to model the macroeconomic effects of tax reform with a web app.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-01-28T00:00:00-06:00" itemprop="datePublished">
-        Jan 28, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Richard W. Evans</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      7 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#OG-USA">OG-USA</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#Tax-Calculator">Tax-Calculator</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#open-source">open-source</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#policy-simulation-library">policy-simulation-library</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#compute-studio">compute-studio</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#us">us</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <p><img src="../images/OG-USA_logo_long.png" alt="" /></p>
-
-<hr />
-
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/EUS6QG6UjZY" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr />
-
-<p>In this PSL Demo Day, I demonstrate how to use the open source <a href="https://github.com/PSLmodels/OG-USA"> <code class="language-plaintext highlighter-rouge">OG-USA</code> </a> macroeconomic model of U.S. fiscal policy. <a href="https://www.jasondebacker.com/">Jason DeBacker</a> and I (<a href="https://sites.google.com/site/rickecon/">Richard Evans</a>) have been the core maintainers of this project and repository for the last six years. This demo is organized into the following sections. The <a href="https://youtu.be/EUS6QG6UjZY">YouTube webinar</a> linked above took place on January 11, 2021.</p>
-
-<ul>
-  <li><a href="#brief-note-about-the-value-of-the-PSL-community">A brief note about value of the PSL community</a></li>
-  <li><a href="#description-of-og-usa-model">Description of the OG-USA model</a></li>
-  <li><a href="#using-og-usa-on-compute-studio">Using OG-USA on Compute Studio</a></li>
-</ul>
-
-<h2 id="brief-note-about-the-value-of-the-psl-community">Brief note about the value of the PSL community</h2>
-
-<p>The Policy Simulation Library is a decentralized organization of open source policy models. The <a href="https://github.com/PSLmodels">Policy Simulation Library GitHub organization</a> houses many open source repositories, each of which represents a curated policy project by a diverse group of maintainers. The projects that have met the highest standards of best practices and documentation are designated as <code class="language-plaintext highlighter-rouge">psl-cataloged</code> , while newer projects that are in earlier stages are designated as <code class="language-plaintext highlighter-rouge">psl-incubating</code> . The philosophy and goal of the PSL environment is to make policy modeling open and transparent. It also allows more collaboration and cross-project contributions and interactions.</p>
-
-<p>The Policy Simulation Library group has been holding these PSL Demo Day webinars since the end of 2020. The video of each webinar is available on the <a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">Policy Simulation Library YouTube channel</a>. These videos are a great resource for learning the different models available in the PSL community, how the models interact, how to contribute to them, and what is on the horizon in their development. Also excellent in many of the PSL Demo Day webinars is a demonstration of how to use the models on the <a href="https://about.compute.studio/">Compute Studio</a> web application platform.</p>
-
-<p>I have been a participant in and contributor to the PSL community since its inception. I love economic policy modeling. And I learned how sophisticated and complicated economic policy models can be. And any simulation can have hundreds of underlying assumptions, some of which may not be explicitly transparent. I think models that are used for public policy analysis have a philosophical imperative to be open source. This allows others to verify results and test sensitivity to assumptions.</p>
-
-<p>Another strong benefit of open source modeling is that it is fundamentally apolitical. With proprietary closed-source policy models, an outside observer might criticize the results of the model based on the perceived political biases of the modeler or the sponsoring organization. With open-source models, a critic can be redirected to the underlying assumptions, structure, and content of the model. This is constructive criticism and debate that moves the science foreward. In the current polarized political environment in the U.S., open-source modeling can provide a constructive route for bipartisan cooperation and the democratization of computational modeling. Furthermore, open-source modeling and workflow encourages the widest forms of collaboration and contributions.</p>
-
-<h2 id="description-of-og-usa-model">Description of OG-USA model</h2>
-
-<p><a href="https://github.com/PSLmodels/OG-USA"> <code class="language-plaintext highlighter-rouge">OG-USA</code> </a> is an open-source overlapping generations, dynamic general equilibrium, heterogeneous agent, macroeconomic model of U.S. fiscal policy. The GitHub repository for the <code class="language-plaintext highlighter-rouge">OG-USA</code> source code is <a href="https://github.com/PSLmodels/OG-USA">github.com/PSLmodels/OG-USA</a>. This repository contains all the source code and instructions for loading and running <code class="language-plaintext highlighter-rouge">OG-USA</code> and all of its dependencies on your local machine. We will probably do another PSL Demo Day on how to run <code class="language-plaintext highlighter-rouge">OG-USA</code> locally. This Demo Day webinar is about running <code class="language-plaintext highlighter-rouge">OG-USA</code> on the <a href="https://compute.studio/PSLmodels/OG-USA/">Compute Studio web application</a>. See Section “<a href="#using-og-usa-on-compute-studio">Using OG-USA on Compute.Studio</a>” below.</p>
-
-<p>As a heterogeneous agent macroeconomic model, <code class="language-plaintext highlighter-rouge">OG-USA</code> allows for distributional analyses at the individual and firm level. That is, you can simulate the model and answer questions like, “How will an increase in the top three personal income tax rates affect people of different ages and income levels?” Microsimulation models can answer these types of distributional analysis questions as well. However, the difference between a macroeconomic model and a microsimulation model is that the macroeconomic models can simulate how each of those individuals and firms will respond to a policy change (e.g., lower labor supply or increased investment demand) and how those behavioral responses will add up and feed back into the macroeconomy (e.g., the effect on GDP, government revenue, government debt, interest rates, and wages).</p>
-
-<p><code class="language-plaintext highlighter-rouge">OG-USA</code> is a large-scale model and comprises tens of thousands of lines of code. The status of all of this code being publicly available on the internet with all collaboration and updates also public makes this an open source project. However, it is not enough to simply post one’s code. We have gone to great lengths to make in-line comments or “docstring” in the code to clarify the purpose of each function and line of code. For example, look in the <a href="https://github.com/PSLmodels/OG-USA/blob/master/ogusa/household.py"> <code class="language-plaintext highlighter-rouge">OG-USA/ogusa/household.py</code> </a> module. The first function on <a href="https://github.com/PSLmodels/OG-USA/blob/master/ogusa/household.py#L18">line 18</a> is the <code class="language-plaintext highlighter-rouge">marg_ut_cons()</code> function. As is described in its docstring, its purpose is to “Compute the marginal utility of consumption.”</p>
-
-<p>These in-code docstrings are not enough. We have also created textbook style OG-USA documentation at <a href="https://pslmodels.github.io/OG-USA/">pslmodels.github.io/OG-USA/</a> using the <a href="https://jupyterbook.org/">Jupyter Book</a> medium. This form of documentation has the advantage of being in book form and available online. It allows us to update the documentation in the open-source repository so changes and versions can be tracked. It describes the <a href="https://pslmodels.github.io/OG-USA/content/api/public_api.html"> <code class="language-plaintext highlighter-rouge">OG-USA</code> API</a>, <a href="https://pslmodels.github.io/OG-USA/content/theory/intro.html"> <code class="language-plaintext highlighter-rouge">OG-USA</code> theory</a>, and <a href="https://pslmodels.github.io/OG-USA/content/calibration/exogenous_parameters.html">`OG-USA calibration</a>. As with the model, this documentation is always a work in progress. But being open-source allows outside contributors to help with its updated and error checking.</p>
-
-<p>One particular strength of the <code class="language-plaintext highlighter-rouge">OG-USA</code> model I want to highlight is its interaction with microsimulation models to incorporate information about tax incentives faced by the heterogeneous households in the model. We have interfaced <code class="language-plaintext highlighter-rouge">OG-USA</code> with microsimulation models in India and in the European Commission. <code class="language-plaintext highlighter-rouge">OG-USA</code> ‘s default for modeling the United States is to use the open-source <code class="language-plaintext highlighter-rouge">Tax-Calculator</code> microsimulation model, which was described by Anderson Frailey in the <a href="http://blog.pslmodels.org/demo-day-4-taxbrain">last Demo Day of 2020</a>. However, DeBacker and I currently have a project in which we use <code class="language-plaintext highlighter-rouge">OG-USA</code> to simulate policies using the Tax Policy Center’s microsimulation model. The way <code class="language-plaintext highlighter-rouge">OG-USA</code> interfaces with microsimulation models to incorporate rich tax data is described in the documentation in the calibration chapter entitled, “<a href="https://pslmodels.github.io/OG-USA/content/calibration/tax_functions.html">Tax Functions</a>”.</p>
-
-<h2 id="using-og-usa-on-compute-studio">Using OG-USA on Compute Studio</h2>
-
-<p>In the demonstration, I focus on how to run experiments and simulations with <code class="language-plaintext highlighter-rouge">OG-USA</code> using the <a href="https://compute.studio/PSLmodels/OG-USA/">Compute Studio</a> web application platform rather than installing running the model on your local machine. To use <code class="language-plaintext highlighter-rouge">OG-USA</code> on this web application, you will need a <a href="https://compute.studio/users/signup/">Compute Studio account</a>. Once you have an account, you can start running any model available through the site. For some models, you will have to pay for the compute time, although the cost of running these models is very modest. However, all Compute Studio simulations of the <code class="language-plaintext highlighter-rouge">OG-USA</code> model are currently sponsored by the <a href="https://www.oselab.org/">Open Source Economics Laboratory</a>. This subsidy will probably run out in the next year. But we are always looking for funding for these models.</p>
-
-<p>Once you are signed up and logged in to your Compute Studio account, you can go to the <code class="language-plaintext highlighter-rouge">OG-USA</code> model on Compute Studio at <a href="https://compute.studio/PSLmodels/OG-USA/">compute.studio/PSLmodels/OG-USA</a>. The experiment that we simulated in the demonstration is available at <a href="https://compute.studio/PSLmodels/OG-USA/206/">compute.studio/PSLmodels/OG-USA/206</a>. The description at the top of the simulation page describes the changes we made. You can look through the input page by clicking on the “Inputs” tab. We ran the model by clicking the green “Run” button at the lower left of the page. The model took about 5 hours to run, so I pre-computed the results that we discussed in the demo. The outputs of the experiment are available in the “Outputs” tab on the page. I also demonstrated how one can click the “Download Results” button at the bottom of the “Outputs” tab to download more results from the simulation. However, the full set of results is only available by installing and running the <code class="language-plaintext highlighter-rouge">OG-USA</code> model simulation on your local machine.</p>
-
-<p>The benefits of the Compute Studio web application are that running the <code class="language-plaintext highlighter-rouge">OG-USA</code> model is much easier for the non-expert, and the multiple-hour computation time can be completed on a remote machine in the cloud.</p>
-
-<h2 id="resources">Resources</h2>
-
-<ul>
-  <li><a href="https://youtu.be/EUS6QG6UjZY">PSL Demo Day YouTube webinar: “How to use <code class="language-plaintext highlighter-rouge">OG-USA</code>”</a></li>
-  <li><a href="https://compute.studio/PSLmodels/OG-USA/"><code class="language-plaintext highlighter-rouge">OG-USA</code> on Compute Studio</a></li>
-  <li><a href="https://compute.studio/PSLmodels/OG-USA/206/">Simulation from the demonstration</a></li>
-  <li><a href="https://github.com/PSLmodels/OG-USA"><code class="language-plaintext highlighter-rouge">OG-USA</code> GitHub repo</a></li>
-  <li><a href="https://pslmodels.github.io/OG-USA/"><code class="language-plaintext highlighter-rouge">OG-USA</code> documentation</a></li>
-  <li><a href="https://github.com/PSLmodels/Tax-Calculator"><code class="language-plaintext highlighter-rouge">Tax-Calculator</code> GitHub repo</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-how-to-use-og-usa" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Updating Jupyter Book documentation with GitHub Actions</h1><p class="page-description">How to keep interactive programmatic notebook-based documentation up-to-date in your pull request workflow.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-05-17T00:00:00-05:00" itemprop="datePublished">
-        May 17, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      4 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#jupyter-book">jupyter-book</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#GH-actions">GH-actions</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#documentation">documentation</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/rEG5vGMkDsg" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>Open source projects must maintain clear and up-to-date documentation in order to attract users and contributors.
-Because of this, PSL sets minimum standards for documentation among cataloged projects in its <a href="https://pslmodels.org/Catalog/library_criteria.html">model criteria</a>.
-A recent innovation in executable books, <a href="https://jupyterbook.org/intro.html">Jupyter Book</a>, has provided an excellent format for model documentation and has been widely adopted by PSL projects (see for example <a href="https://pslmodels.github.io/OG-USA/content/intro/intro.html">OG-USA</a>, <a href="http://taxbrain.pslmodels.org/content/intro.html">Tax-Brain</a>, <a href="https://taxcalc.pslmodels.org">Tax-Calculator</a>).</p>
-
-<p>Jupyter Book allows one to write documents with executable code and text together, as in Jupyter notebooks.
-But Jupyter Book pushes this further by allowing documents with multiple sections, better integration of TeX for symbols and equations, BibTex style references and citations, links between sections, and <a href="https://www.sphinx-doc.org/en/master/">Sphinx</a> integration (for auto-built documentation of model APIs from source code).
-Importantly for sharing documentation, Jupyter Books can easily be compiled to HTML, PDF, or other formats.
-Portions of a Jupyter Book that contain executable code can be downloaded as Jupyter Notebooks or opened in <a href="https://research.google.com/colaboratory/">Google Colab</a> or <a href="https://mybinder.org">binder</a></p>
-
-<p>The <a href="https://jupyterbook.org/intro.html">Jupyter Book</a> documentation is excellent and will help you get started creating your “book” (tip: pay close attention to formatting details, including proper whitespace).
-What I do here is outline how you can easily deploy your documentation to the web and keep it up-to-date with your project.</p>
-
-<p>I start from the assumption that you have the source files to build your Jupyter Book checked into the main branch of your project (these maybe <code class="language-plaintext highlighter-rouge">yml</code> , <code class="language-plaintext highlighter-rouge">md</code> , <code class="language-plaintext highlighter-rouge">rst</code> , <code class="language-plaintext highlighter-rouge">ipynb</code> or other files).
-For version control purposes and to keep your repo trim, you generally don’t want to check the built documentation files to this branch (tip: consider adding the folder these files will go to (e.g., <code class="language-plaintext highlighter-rouge">/_build</code> to your <code class="language-plaintext highlighter-rouge">.gitignore</code> ).
-When these files are in place and you can successfully build your book locally, it’s time for the first step.</p>
-
-<p><em>Step 1</em>: Add two GH Actions to your project’s workflow:</p>
-<ol>
-  <li>An action to check that your documentation files build without an error.
-I like to run this on each push to a PR.
-The action won’t hang on warnings, but will fail if your Jupyter Book doesn’t build at all.
-An example of this action from the OG-USA repo is <a href="https://github.com/PSLmodels/OG-USA/blob/master/.github/workflows/docs_check.yml">here</a>:</li>
-</ol>
-
-<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>
-name: Check that docs build
-on: [push, pull_request]
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v2 # If you're using actions/checkout@v2 you must set persist-credentials to false in most cases for the deployment to work correctly.
-        with:
-          persist-credentials: false
-
-      - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v2
-        with:
-          activate-environment: ogusa-dev
-          environment-file: environment.yml
-          python-version: 3.7
-          auto-activate-base: false
-
-      - name: Build # Build Jupyter Book
-        shell: bash -l {0}
-        run: |
-          pip install jupyter-book
-          pip install sphinxcontrib-bibtex==1.0.0
-          pip install -e .
-          cd docs
-          jb build ./book
-</code></pre></div></div>
-
-<p>To use this in your repo, you’ll just need to change a few settings such as the name of the environment and perhaps the Python version and path to the book source files.
-Note that in the above <code class="language-plaintext highlighter-rouge">yml</code> file <code class="language-plaintext highlighter-rouge">sphinxcontrib-bibtex</code> is pinned.
-You maybe able to unpin this, but OG-USA needed this pin for documentation to compile property due to changes in the <code class="language-plaintext highlighter-rouge">jupyter-book</code> and <code class="language-plaintext highlighter-rouge">sphinxcontrib-bibtex</code> packages.</p>
-
-<ol>
-  <li>An action that builds and deploys the Jupyter Book to <a href="https://pages.github.com">GH Pages</a>.
-The OG-USA project uses the <a href="https://github.com/JamesIves/github-pages-deploy-action">deploy action from James Ives</a> in <a href="https://github.com/PSLmodels/OG-USA/blob/master/.github/workflows/deploy_docs.yml">this action</a>.
-This is something that you will want to run when PRs are merged into your main branch so that the documentation is kept up-to-date with the project.
-To modify this action for your repo, you’ll need to change the repo name, the environment name, and potentially the Python version, branch name, and path to the book source files.</li>
-</ol>
-
-<p><em>Step 2</em>: Once the action in (2) above is run, your compiled Jupyter Book docs will be pushed to a <code class="language-plaintext highlighter-rouge">gh-pages</code> branch in your repository (the action will create this branch for you if it doesn’t already exist).
-At this point, you should be able to see your docs at the url <code class="language-plaintext highlighter-rouge">https://GH_org_name.github.io/Repo_name</code> .
-But it probably won’t look very good until you complete this next step.
-To have your Jupyter Book render on the web as you see it on your machine, you will want to push and merge an empty file with the name <code class="language-plaintext highlighter-rouge">.nojekyll</code> into your repo’s <code class="language-plaintext highlighter-rouge">gh-pages</code> branch.</p>
-
-<p>That’s it!
-With these actions, you’ll be sure that your book continues to compile and a new version will be published to the web with with each merge to your main branch, ensuring that your documentation stays up-to-date.</p>
-
-<p>Some additional tips:</p>
-<ul>
-  <li>Use <a href="https://www.sphinx-doc.org/en/master/">Sphinx</a> to document your projects API.
-By doing so you’ll automate an important part of your project’s documentation – as long as the docstrings are updated when the source code is, the Jupyter Book you are publishing to the web will be kept in sync with no additional work needed.</li>
-  <li>You can have your <code class="language-plaintext highlighter-rouge">gh-pages</code>-hosted documentation point to a custom URL.</li>
-  <li>Project maintainers should ensure that docs are updated with PRs that are relevant (e.g., if the PR changes an the source code affecting a user interface, then documentation showing example usage should be updated) and help contributors make the necessary changes to the documentation source files.</li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-jupyter-book-deploy" hidden></a>
-</article>
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diff --git a/demo-day-og-core.html b/demo-day-og-core.html
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: The OG-Core platform</h1><p class="page-description">A Python platform for building country-specific overlapping generations general equilibrium models.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-11-01T00:00:00-05:00" itemprop="datePublished">
-        Nov 1, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      2 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#python">python</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#macroeconomics">macroeconomics</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#overlapping-generations">overlapping-generations</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/y1vSgmEtgxs" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>The <a href="https://pslmodels.github.io/OG-Core/">OG-Core</a> model is a general equilibrium, overlapping generations (OG) model suitable for evaluating fiscal policy.
-Since the work of Alan Auerbach and Laurence Kotlikoff in the 1980s, this class of model has become a standard in the macroeconomic analysis of tax and spending policy.
-This is for good reason.
-OG models are able to capture the impacts of taxes and spending in the short and long run, examine incidence of policy across generations of people (not just short run or steady state analysis of a cross-section of the economy), and capture important economic dynamics (e.g., crowding out effects of deficit-financed policy).</p>
-
-<p>In the PSL Demo Day presentation linked above, I cover the basics of OG-Core: its history, its API, and how country-specific models can use OG-Core as a dependency.
-In brief, OG-Core provides a general overlapping generations framework, from which parameters can be calibrated to represent particular economies.
-Think of it this way: an economic model is just a set of parameters plus a system of equations.
-OG-Core spells out all of the equations to represent an economy with heterogeneous agents, production and government sectors, open economy options, and detailed policy rules.
-OG-Core also includes default values for all parameters, along with parameter metadata and parameter validation rules.
-A country specific application is then just a particular parameterization of the general OG-Core model.</p>
-
-<p>As an example of a country-specific application, one can look at the <a href="https://pslmodels.github.io/OG-USA">OG-USA model</a>.
-This model provides a calibration of OG-Core to the United States.
-The source code in that project allows one to go from raw data sources to the estimation and calibration procedures used to determine parameter values representing the United States, to parameter values in formats suitable for use in OG-Core.
-Country-specific models like OG-USA include (where available) links to microsimulation models of tax and spending programs to allow detailed microdata of actual and counterfactual policies to inform the net tax-transfer functions used in the OG-Core model.
-For those interested in building their own country-specific model, the OG-USA project provides a good example to work from.</p>
-
-<p>We encourage you to take a look at OG-Core and related projects.
-New contributions and applications are always welcome.
-If you have questions or comments, reach out through the relevant repositories on Github to me, <a href="https://github.com/jdebacker/">@jdebacker</a>, or Rick Evans, <a href="https://github.com/rickecon">@rickecon</a>.</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://pslmodels.github.io/OG-Core/content/intro/intro.html">OG-Core documentation</a></li>
-  <li>
-<a href="https://pslmodels.github.io/OG-USA">OG-USA documentation</a> package for unit testing in Python</li>
-  <li><a href="http://taxcalc.pslmodels.org">Tax-Calculator documentation</a></li>
-  <li><a href="https://github.com/PSLmodels/OG-UK">OG-UK repository</a></li>
-  <li><a href="https://github.com/PolicyEngine/openfisca-uk">OpenFisca-UK repository</a></li>
-  <li><a href="https://docs.google.com/presentation/d/1AT3SYNJ6JieAB1HrPT6HPSBC6-2A1QNtIdBDO-3PSCI/edit?usp=sharing">Slides from the Demo Day presentation</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-og-core" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Modeling taxes and benefits with the PolicyEngine US web app</h1><p class="page-description">PolicyEngine US is a new web app for computing the impact of US tax and benefit policy.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2022-04-12T00:00:00-05:00" itemprop="datePublished">
-        Apr 12, 2022
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Max Ghenis</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#apps">apps</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#taxes">taxes</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#benefits">benefits</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#us">us</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/b9d18Lk-zu8" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p><a href="https://policyengine.org">PolicyEngine</a> is a nonprofit that builds free, open-source software to compute the impact of public policy.
-After launching our <a href="https://policyengine.org/uk">UK app</a> in October 2021, we’ve just launched our <a href="https://policyengine.org/us">US app</a>, which calculates households’ federal taxes and several benefit programs, both under current law and under customizable policy reforms.</p>
-
-<p>In this Demo Day, I provide background on PolicyEngine and demonstrate how to use PolicyEngine US (a Policy Simulation Library cataloged model) to answer a novel policy question:</p>
-
-<blockquote>
-  <p>How would doubling both (a) the Child Tax Credit and (b) the Supplemental Nutrition Assistance Program (SNAP) net income limit affect a single parent in California with $1,000 monthly rent and $50 monthly broadband costs?</p>
-</blockquote>
-
-<p>By bringing together tax and benefit models into a web interface, we can answer this question quickly without programming experience, as well as an unlimited array of questions like it.
-The result is a table breaking down the household’s net income by program, as well as graphs of net income and marginal tax rates as the household’s earnings vary.</p>
-
-<p>I close with a quick demo of <a href="https://policyengine.org/uk">PolicyEngine UK</a>, which adds society-wide results like the impact of reforms on the budget, poverty, and inequality, as well as contributed policy parameters.
-We’re planning to bring those features to PolicyEngine US, along with state tax and benefit programs in all 50 states, over the next two years (if not sooner).</p>
-
-<p>Feel free to explore the app and reach out with any questions at <a href="mailto:max@policyengine.org">max@policyengine.org</a>.</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://policyengine.org/us">PolicyEngine US</a></li>
-  <li><a href="https://docs.google.com/presentation/d/1ckaxNiPrUZeD1IGhqeqAjLPjjCx1zswhZiIqO0ps72w">Presentation slides</a></li>
-  <li><a href="https://blog.policyengine.org/policyengine-comes-stateside-cef88b122e48">PolicyEngine blog post on launching PolicyEngine US</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-policyengine-us" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Running the scf and microdf Python packages in Google Colab</h1><p class="page-description">Analyzing US wealth data in a web-based Python notebook.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-01-29T00:00:00-06:00" itemprop="datePublished">
-        Jan 29, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Max Ghenis</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#microdf">microdf</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#scf">scf</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/Zlws_gC9HeY" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>For Monday’s PSL Demo Day, I showed how to use the <code class="language-plaintext highlighter-rouge">scf</code> and <code class="language-plaintext highlighter-rouge">microdf</code> PSL Python packages from the <a href="http://colab.research.google.com">Google Colab</a> web-based Jupyter notebook interface.</p>
-
-<p>The <code class="language-plaintext highlighter-rouge">scf</code> package extracts data from the Federal Reserve’s Survey of Consumer Finances, the canonical source of US wealth microdata.
-<code class="language-plaintext highlighter-rouge">scf</code> has a single function: <code class="language-plaintext highlighter-rouge">load(years, columns)</code> , which then returns a <code class="language-plaintext highlighter-rouge">pandas</code>  <code class="language-plaintext highlighter-rouge">DataFrame</code> with the specified column(s), each record’s survey weight, and the year (when multiple years are requested).</p>
-
-<p>The <code class="language-plaintext highlighter-rouge">microdf</code> package analyzes survey microdata, such as that returned by the <code class="language-plaintext highlighter-rouge">scf.load</code> function.
- It offers a consistent paradigm for calculating statistics like means, medians, sums, and inequality statistics like the Gini index.
- Most functions are structured as follows: <code class="language-plaintext highlighter-rouge">f(df, col, w, groupby)</code> where <code class="language-plaintext highlighter-rouge">df</code> is a <code class="language-plaintext highlighter-rouge">pandas</code>  <code class="language-plaintext highlighter-rouge">DataFrame</code> of survey microdata, <code class="language-plaintext highlighter-rouge">col</code> is a column(s) name to be summarized, <code class="language-plaintext highlighter-rouge">w</code> is the weight column, and <code class="language-plaintext highlighter-rouge">groupby</code> is the column(s) to group records in before summarizing.</p>
-
-<p>Using Google Colab, I showed how to use these packages to quickly calculate mean, median, and total wealth from the SCF data, without having to install any software or leave the browser.
- I also demonstrated how to use the <code class="language-plaintext highlighter-rouge">groupby</code> argument of <code class="language-plaintext highlighter-rouge">microdf</code> functions to show how different measures of wealth inequality have changed over time.
- Finally, I previewed some of what’s to come with <code class="language-plaintext highlighter-rouge">scf</code> and <code class="language-plaintext highlighter-rouge">microdf</code> : imputations, extrapolations, inflation, visualization, and documentation, to name a few priorities.</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://docs.google.com/presentation/d/1bXWD_8wjbvG4J-Tq8PvlP7xK7Kz2X0oVpsOnjFZ_6zY">Slides</a></li>
-  <li><a href="https://colab.research.google.com/drive/1WLOYxAtC347g2tIyO_iJJQUAZmwL4raB?usp=sharing">Demo notebook in Google Colab</a></li>
-  <li><a href="https://compute.studio/PSLmodels/Tax-Brain/48969/">Simulation from the demonstration</a></li>
-  <li><a href="https://github.com/PSLmodels/scf"><code class="language-plaintext highlighter-rouge">scf</code> GitHub repo</a></li>
-  <li><a href="https://github.com/PSLmodels/microdf"><code class="language-plaintext highlighter-rouge">microdf</code> GitHub repo</a></li>
-  <li><a href="https://pslmodels.github.io/microdf"><code class="language-plaintext highlighter-rouge">microdf</code> documentation</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-scf-microdf" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Producing stacked revenue estimates with the Tax-Calculator Python API</h1><p class="page-description">How to evaluate the cumulative effects of a multi-part tax reform.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-04-05T00:00:00-05:00" itemprop="datePublished">
-        Apr 5, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      4 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#individual-income-tax">individual-income-tax</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#tax-brain">tax-brain</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#tax-calculator">tax-calculator</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/O79H2Z8CeGc" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>It’s often useful to be able to identify the effects of specific provisions individually and not just the overall impact of a proposal with many provisions.
-Indeed, when revenue estimates of tax law changes are reported (such as <a href="https://www.jct.gov/publications/2021/jcx-14-21/">this JCT analysis</a> of the American Rescue Plan Act of 2021), they are typically reported on a provision-by-provision basis.
-Finding the provision-by-provision revenue estimates is cumbersome with the <a href="https://compute.studio/PSLmodels/Tax-Brain/">Tax-Brain web application</a> both because it’s hard to iterate over many provisions and because the order matters when stacking estimates, so that one needs to keep this order in mind as parameter values are updated for each additional provision in a full proposal.</p>
-
-<p>In the PSL Demo Day on April 5, 2021, I show how to use the Python API of Tax-Calculator to efficiently produce stacked revenue estimates.
-In fact, after some initial setup, this can be done with just 12 lines of code (plus a few more to make the output look nice).
-The Google Colab notebook that illustrates this approach can be found <a href="https://colab.research.google.com/drive/1P-m61lWbPpb_ih42vQKrD2zi9Bpe16BM?usp=sharing">at this link</a>, but here I’ll walk through the four steps that are involved:</p>
-
-<ol>
-  <li>
-<em>Divide up the full proposal into strings of JSON text that contain each provision you want to analyze</em>.
-My example breaks up the <a href="https://github.com/PSLmodels/examples/blob/main/psl_examples/taxcalc/Biden2020.json">Biden 2020 campaign proposal</a> into seven provisions, but this is illustrative and you can make more or less provisions depending on the detail you would like to see.</li>
-  <li>
-<em>Create a dictionary that contains, as its values, the JSON strings</em>.
-A couple notes on this.
-First, the dictionary keys should be descriptive of the provisions as they will become the labels for each provision in the final table of revenue estimates we produce.
-Second, order matters here.
-You’ll want to be sure the current law baseline is first (the value for this will be an empty dictionary).
-Then you specify the provisions.
-The order you specify will likely affect your revenue estimates from a given provision (for instance, expanding/restricting a deduction has a larger revenue effect when rates are higher), but there are not hard and fast rules on the “right” order.
-Traditionally, rate changes are stacked first and tax expenditures later in the order.</li>
-  <li>
-<em>Iterate over this dictionary</em>.
-With a dictionary of provisions in hand, we can write a “for loop” to iterate over the provision, simulating the Tax-Calculator model at each step.
-Note that when the <code class="language-plaintext highlighter-rouge">Policy</code> class object in Tax-Calculator is modified, it only needs to be told the changes in tax law parameters relative to its current state.
-In other words, when we are stacking provisions, estimating the incremental effect of each, you can think of the <code class="language-plaintext highlighter-rouge">Policy</code> object having a baseline policy that is represented by the current law baseline plus all provisions that have been analyzed before the provision at the current iteration.
-The <code class="language-plaintext highlighter-rouge">Policy</code> class was created in this way so that one can easily represent policy changes, requiring the user to only input the set of parameters that are modified, not every single parameter’s value under the hypothetical policy.
-But this also makes it parsimonious to stack provisions as we are doing here.
-Notice that the JSON strings for each provision (created in Step 1) can be specified independent of the stacking order.
-We only needed to slice the full set of proposals into discrete chunks, we didn’t need to worry about creating specifications of cumulative policy changes.</li>
-  <li>
-<em>Format output for presentation</em>.
-After we’ve run a Tax-Calculator simulation for the current law baseline plus each provision (and each year in the budget window), we’ve got all the output we need.
-With this output, we can quickly create a table that will nicely present our stacked revenue estimate.
-One good check to do here is to create totals across all provisions and compare this to the simulated revenue effects of running the full set of proposals in one go.
-This check helps to ensure that you didn’t make an error in specifying your JSON strings.
-For example, it’s easy to leave out one or more provisions, especially if there are many.</li>
-</ol>
-
-<p>I hope this provides a helpful template for your own analysis.
-Note that one can modify this code in several useful ways.
-For example, within the for-loops, the <a href="https://github.com/PSLmodels/Behavioral-Responses">Behavioral-Responses</a> can be called to produce revenue estimates that take into account behavioral feedback.
-Or one could store the individual income tax and payroll tax revenue impacts separately (rather than return the combined values as in the example notebook).
-Additional outputs (even the full set of microdata after each provision is applied) can be stored for even more analysis.</p>
-
-<p>In the future, look for <a href="https://github.com/PSLmodels/Tax-Brain">Tax-Brain</a> to add stacked revenue estimates to its capabilities.
-It’ll still be important for users to carve up their full list of policy changes into sets of provisions as we did in Steps 1 and 2 above, but Tax-Brain will then take care of the rest behind the scenes.</p>
-
-<p>Resources:</p>
-
-<ul>
-  <li><a href="https://colab.research.google.com/drive/1P-m61lWbPpb_ih42vQKrD2zi9Bpe16BM?usp=sharing">Colab Notebook with example</a></li>
-  <li><a href="https://github.com/PSLmodels/examples/blob/main/psl_examples/taxcalc/Biden2020.json">Biden campaign reform file in PSL Examples</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-stacked-revenue-estimates" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Using synthimpute for data fusion</h1><p class="page-description">The synthimpute Python package fuses and synthesizes economic datasets with machine learning.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-12-08T00:00:00-06:00" itemprop="datePublished">
-        Dec 8, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Max Ghenis</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      2 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#python">python</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#data-fusion">data-fusion</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#synthimpute">synthimpute</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/e_sk-_yWamY" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>Suppose a policy analyst sought to estimate the impact of a policy that changed income tax rates and benefit rules while also adding a progressive wealth tax.
-The standard approach is to use a <em>microsimulation</em> model, where the rules are programmed as code, and then to run that program over a representative sample of households.
-Unfortunately, no single US government survey captures all the households characteristics needed to analyze this policy; in particular, the reliable tax and benefit information lies in surveys like the Current Population Survey (CPS), while wealth lies in the Survey of Consumer Finances (SCF).</p>
-
-<p>Assuming the analyst wanted to start with the CPS, they have several options to estimate wealth for households to levy the progressive wealth tax.
-Two typical approaches include:</p>
-<ol>
-  <li>Linear regression, predicting wealth from other household characteristics common to the CPS and SCF.</li>
-  <li>Matching, in which each CPS household is matched with the most similar household in the SCF.</li>
-</ol>
-
-<p>Neither of these approaches, however, aim to estimate the <em>distribution</em> of wealth conditional on other characteristics.
-Linear regression explicitly estimates the mean prediction, but that could miss the tails of wealth from whom most of the wealth tax revenue will be collected.</p>
-
-<p>Instead, the analyst could apply <em>quantile regression</em> to estimate the distribution of wealth conditional on other characteristics, and then measure the effectiveness of the estimation using <em>quantile loss</em>.</p>
-
-<p>In this Demo Day, I present the concepts of microsimulation, imputation, and quantile loss to motivate the <code class="language-plaintext highlighter-rouge">synthimpute</code> Python package I’ve developed with my PolicyEngine colleague Nikhil Woodruff.
-In an experiment predicting wealth on a holdout set from the SCF, my former colleague Deepak Singh and I found that random forests significantly outperform OLS and matching for quantile regression, and this is the approach applied in <code class="language-plaintext highlighter-rouge">synthimpute</code> for both data fusion and data synthesis.
-The <code class="language-plaintext highlighter-rouge">synthimpute</code> API will be familiar to users of <code class="language-plaintext highlighter-rouge">scikit-learn</code> and <code class="language-plaintext highlighter-rouge">statsmodels</code> , with the difference being that <code class="language-plaintext highlighter-rouge">synthimpute</code> ‘s <code class="language-plaintext highlighter-rouge">rf_impute</code> function returns a random value from the predicted distribution; it can also skew the predictions to meet a target total.</p>
-
-<p>We’ve used <code class="language-plaintext highlighter-rouge">synthimpute</code> to fuse data for research reports at the <a href="https://ubicenter.org">UBI Center</a> and to enhance the <a href="https://policyengine.org">PolicyEngine</a> web app for UK tax and benefit simulation, and we welcome new users and contributors.
-Feel free to explore the repository or contact me with questions at <a href="mailto:max@policyengine.org">max@policyengine.org</a>.</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://github.com/PolicyEngine/synthimpute"><code class="language-plaintext highlighter-rouge">synthimpute</code> package on GitHub</a></li>
-  <li><a href="https://docs.google.com/presentation/d/1Hw0zIkbnXZluW8ntjbw_NXryRvjVcg6DDp-btkXXV_o">Presentation slides</a></li>
-  <li>
-<a href="https://www.ubicenter.org/uk-lvt">UBI Center report on land value taxation in the UK</a>, using <code class="language-plaintext highlighter-rouge">synthimpute</code> to impute land value from the UK Wealth and Assets Survey to the Family Resources Survey</li>
-  <li>
-<a href="http://policyengine.org/uk/population-impact?carbon_tax=100">PolicyEngine UK carbon tax example</a>, using <code class="language-plaintext highlighter-rouge">synthimpute</code> to impute carbon emissions from the Living Costs and Food Survey to the Family Resources Survey</li>
-  <li>
-<a href="https://colab.research.google.com/drive/1E8F7S1Uvfw_3PmpS226Sl1LWV5NBi0CE">Notebook comparing random forests to matching and other techniques</a> using a holdout set from the US Survey of Consumer Finances</li>
-  <li>
-<a href="https://towardsdatascience.com/quantile-regression-from-linear-models-to-trees-to-deep-learning-af3738b527c3">My blog post on quantile regression for Towards Data Science</a>, which laid the groundwork for <code class="language-plaintext highlighter-rouge">synthimpute</code>
-</li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-synthimpute" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Using the TaxBrain Python API</h1><p class="page-description">A programmatic interface to compute the impact of tax reform.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-06-14T00:00:00-05:00" itemprop="datePublished">
-        Jun 14, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Anderson Frailey</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      2 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#individual-income-tax">individual-income-tax</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#tax-brain">tax-brain</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#tax-calculator">tax-calculator</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul><hr>
-
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/HXN2TrOvXn0" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>The TaxBrain project was primarily created to serve as the backend of the <a href="https://www.compute.studio/PSLmodels/Tax-Brain/">Tax-Brain web-application</a>.
-But at its core, TaxBrain is a Python package that greatly simplifies tax policy analysis.
-For this PSL Demo-Day, I demonstrated TaxBrain’s capabilities as a standalone package, and how to use it to produce high-level summaries of the revenue impacts of proposed tax policies.
-The Jupyter Notebook from the presentation can be found <a href="https://gist.github.com/andersonfrailey/bb8ac6db609bf0146ef23d1d35d32334">here</a>.</p>
-
-<p>TaxBrain’s Python API allows you to run a full analysis of income tax policies in just three lines of code:</p>
-
-<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">from</span> <span class="nn">taxbrain</span> <span class="kn">import</span> <span class="n">TaxBrain</span>
-
-<span class="n">tb</span> <span class="o">=</span> <span class="n">TaxBrain</span><span class="p">(</span><span class="n">START_YEAR</span><span class="p">,</span> <span class="n">END_YEAR</span><span class="p">,</span> <span class="n">use_cps</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span> <span class="n">reform</span><span class="o">=</span><span class="n">REFORM_POLICY</span><span class="p">)</span>
-<span class="n">tb</span><span class="p">.</span><span class="n">run</span><span class="p">()</span>
-</code></pre></div></div>
-
-<p>Where <code class="language-plaintext highlighter-rouge">START_YEAR</code> and <code class="language-plaintext highlighter-rouge">END_YEAR</code> are the first and last years, respectively, of the analysis; <code class="language-plaintext highlighter-rouge">use_cps</code> is a boolean indicator that you want to use the CPS-based microdata file prepared for use with Tax-Calculator; and <code class="language-plaintext highlighter-rouge">REFORM_POLICY</code> is either a JSON file or Python dictionary that specifies a reform suitable for Tax-Calculator.
-The forthcoming release of TaxBrain will also include a feature that allows you to perform a stacked revenue analysis as well.
-The inspiration for this feature was presented by Jason DeBacker in a <a href="http://blog.pslmodels.org/demo-day-11-stacked-revenue-estimates">previous demo-day</a>.</p>
-
-<p>Once TaxBrain has been run, there are a number of methods and functions included in the package to create tables and plots to summarize the results.
-I used the <a href="https://github.com/PSLmodels/examples/blob/main/psl_examples/taxcalc/Biden2020.json">Biden 2020 campaign proposal</a> in the demo and the resulting figures are below.
-The first is a “volcano plot” that makes it easy to see the magnitude of the change in tax liability individuals across the income distribution face.
-Each dot represents a tax unit, and the x and y variables can be customized based on the user’s needs.</p>
-
-<p><img src="../images/biden_volcano.png" alt=""></p>
-
-<p>The second gives a higher-level look at how taxes change in each income bin.
-It breaks down what percentage of each income bin faces a tax increase or decrease, and the size of that change.</p>
-
-<p><img src="../images/biden_dist_fig.png" alt=""></p>
-
-<p>The final plot shown in the demo simply shows tax liabilities by year over the budget window.</p>
-
-<p><img src="../images/biden_revenue.png" alt=""></p>
-
-<p>The last feature I showed was TaxBrain’s automated reports. 
-TaxBrain uses saved results and an included report template to write a report summarizing the findings of your simulation.
-The reports include tables and figures similar to what you may find in similar write ups by the Joint Committee on Taxation or Tax Policy Center including a summary of significant changes caused by the reform, and all you need is one line of code:</p>
-
-<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">report</span><span class="p">(</span><span class="n">tb</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s">'Biden Proposal'</span><span class="p">,</span> <span class="n">outdir</span><span class="o">=</span><span class="s">'biden'</span><span class="p">,</span> <span class="n">author</span><span class="o">=</span><span class="s">'Anderson Frailey'</span><span class="p">)</span>
-</code></pre></div></div>
-
-<p>The above code will save a PDF copy of the report in a directory called <code class="language-plaintext highlighter-rouge">biden</code> along with PNG files for each of the graphs created and the raw Markdown text used for the report, which you can then edit as needed if you would like to add content to the report that is not already included.
-Screenshots of the default report are included below.</p>
-
-<p><img src="../images/tb_report1.png" alt="">
-<img src="../images/tb_report2.png" alt="">
-<img src="../images/tb_report3.png" alt="">
-<img src="../images/tb_report4.png" alt="">
-<img src="../images/tb_report5.png" alt=""></p>
-
-<p>There are of course downsides to using TaxBrain instead of Tax-Calculator directly.
-Specifically, it’s more difficult, and sometimes impossible, to perform custom  tasks like modeling a feature of the tax code that hasn’t been added to Tax-Calculator yet or advanced work with marginal tax rates.
-But for day-to-day tax modeling, the TaxBrain Python package can significantly simply any workflow.</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://github.com/PSLmodels/Tax-Brain">Tax-Brain GitHub repo</a></li>
-  <li><a href="http://taxbrain.pslmodels.org/content/intro.html">Tax-Brain Documentation</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-tax-brain-python-api" hidden></a>
-</article>
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-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Tax-Brain</h1><p class="page-description">Computing the impact of US tax reform with the Tax-Brain web-app.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2020-12-23T00:00:00-06:00" itemprop="datePublished">
-        Dec 23, 2020
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Anderson Frailey</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#individual-income-tax">individual-income-tax</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#tax-brain">tax-brain</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#us">us</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/Zc_XEErfO5E" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>For this PSL demo-day I showed how to use the <a href="https://www.compute.studio/PSLmodels/Tax-Brain/">Tax-Brain web-application</a>,
- hosted on <a href="http://compute.studio">Compute Studio</a>, to analyze proposed individual income tax policies.
-Tax-Brain integrates the <a href="https://pslmodels.github.io/Tax-Calculator/">Tax-Calculator</a>
-and <a href="https://github.com/PSLmodels/Behavioral-Responses#readme">Behavioral-Responses</a>
-models to make running both static and dynamic analyses of the US federal income
-and payroll taxes simple. The web interface for the model makes it possible for
-anyone to run their own analyses without writing a single line of code.</p>
-
-<p>We started the demo by simply walking through the interface and features of the
-web-app before creating our own sample reform to model. This reform, which to
-my knowledge does not reflect any proposals currently up for debate, included
-changes to the income and payroll tax rates, bringing back personal exemptions,
-modifying the standard deduction, and implementing a universal basic income.</p>
-
-<p>While the model ran, I explained how Tax-Brain validated all of the user inputs,
-the data behind the model, and how the final tax liability projections are
-determined. We concluded by looking through the variety of tables and graphs
-Tax-Brain produces and how they can easily be shared with others.</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://compute.studio/PSLmodels/Tax-Brain/48969/">Simulation from the demonstration</a></li>
-  <li><a href="https://github.com/PSLmodels/Tax-Brain">Tax-Brain GitHub repo</a></li>
-  <li><a href="https://pslmodels.github.io/Tax-Calculator/#">Tax-Calculator documentation</a></li>
-  <li><a href="https://pslmodels.github.io/Behavioral-Responses/index.html">Behavioral-Responses documentation</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-tax-brain" hidden></a>
-</article>
\ No newline at end of file
diff --git a/demo-day-tax-cruncher.html b/demo-day-tax-cruncher.html
deleted file mode 100755
index 0c27c29..0000000
--- a/demo-day-tax-cruncher.html
+++ /dev/null
@@ -1,59 +0,0 @@
-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Tax-Cruncher</h1><p class="page-description">How to calculate a taxpayer's liabilities under current law and under a policy reform.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2020-11-23T00:00:00-06:00" itemprop="datePublished">
-        Nov 23, 2020
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Peter Metz</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#individual-income-tax">individual-income-tax</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#tax-cruncher">tax-cruncher</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/d4T-DOxm2QQ" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>For the Demo Day on November 16, I showed how to calculate a taxpayer’s liabilities under current law and under a policy reform with Tax-Cruncher.
-The Tax-Cruncher web application takes two sets of inputs: a taxpayer’s demographic and financial information and the provisions of a tax reform.</p>
-
-<p>For the first Demo Day example (<a href="https://youtu.be/d4T-DOxm2QQ?t=230">3:50</a>), we looked at how eliminating the state and local tax (SALT) deduction cap and applying payroll tax to earnings above $400,000 would affect a high earner.
-In particular, our hypothetical filer had $500,000 in wages, $100,000 in capital gains, and $100,000 in itemizable expenses.
-You can see the results at <a href="https://compute.studio/PSLmodels/Tax-Cruncher/634/">Compute Studio simulation #634</a>.</p>
-
-<p>For the second example (<a href="https://youtu.be/d4T-DOxm2QQ?t=1070">17:50</a>), we looked at how expanding the Earned Income Tax Credit (EITC) and Child Tax Credit would impact a family with $45,000 in wages and two young children.
-You can see the results at <a href="https://compute.studio/PSLmodels/Tax-Cruncher/636/">Compute Studio simulation #636</a>.</p>
-
-<p>Resources:</p>
-<ul>
-  <li><a href="https://compute.studio/PSLmodels/Tax-Cruncher/">Tax-Cruncher</a></li>
-  <li><a href="https://compute.studio/AEIEconomics/Tax-Cruncher-Biden/">Tax-Cruncher-Biden</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-tax-cruncher" hidden></a>
-</article>
\ No newline at end of file
diff --git a/demo-day-taxbrain-to-taxcruncher.html b/demo-day-taxbrain-to-taxcruncher.html
deleted file mode 100755
index 75ddada..0000000
--- a/demo-day-taxbrain-to-taxcruncher.html
+++ /dev/null
@@ -1,49 +0,0 @@
-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Moving policy reform files from Tax-Brain to Tax-Cruncher</h1><p class="page-description">How to move reforms between a tax-unit-level and society-wide model with the Compute.Studio API.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-03-02T00:00:00-06:00" itemprop="datePublished">
-        Mar 2, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Matt Jensen</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul><p>Check out the video:</p>
-
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/0E_GawHQres" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>Show notes:</p>
-
-<p>I demonstrate how to move a policy reform file from Tax-Brain to Tax-Cruncher using the Compute.Studio API. 
-See the Demo C/S simulation linked below for text instructions that accompany the video.</p>
-
-<p>Resources:</p>
-
-<ul>
-  <li><a href="https://compute.studio/PSLmodels/Tax-Brain/49779/">Demo C/S simulation with instructions</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-taxbrain-to-taxcruncher" hidden></a>
-</article>
\ No newline at end of file
diff --git a/demo-day-unit-testing.html b/demo-day-unit-testing.html
deleted file mode 100755
index 1920a79..0000000
--- a/demo-day-unit-testing.html
+++ /dev/null
@@ -1,112 +0,0 @@
-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Demo Day: Unit testing for open source projects</h1><p class="page-description">How to ensure that individual functions do what you expect.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2021-08-09T00:00:00-05:00" itemprop="datePublished">
-        Aug 9, 2021
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Jason DeBacker</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      3 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#demo-days">demo-days</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#R">R</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#Python">Python</a>
-        &nbsp;
-      
-        <a class="category-tags-link" href="/categories/#unit-testing">unit-testing</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul>
-<center>
-    <iframe width="560" height="315" src="https://www.youtube.com/embed/LkNEfbKHM5E" frameborder="0" allowfullscreen=""></iframe>
-</center>
-
-<hr>
-
-<p>Unit testing is the testing of individual units or functions of a software application.
-This differs from regression testing that focuses on the verification of final outputs.
-Instead, unit testing tests each smallest testable component of your code.
-This helps to more easily identify and trace errors in the code.</p>
-
-<p>Writing unit tests is good practice, though not one that’s always followed.
-The biggest barrier to writing unit tests is that doing so takes time.
-You might wonder “why am I testing code that runs?”
-But there are a number benefits to writing unit tests:</p>
-<ul>
-  <li>It ensures that the code does what you expect it to do</li>
-  <li>You’ll better understand what your code is doing</li>
-  <li>You will reduce time tracking down bugs in your code</li>
-</ul>
-
-<p>Often, writing unit tests will save you time in the longer run because it reduces debugging time and because it forces you to think more about what your code does, which often leads to the development of more efficient code.
-And for open source projects, or projects with many contributors, writing unit tests is important in reducing the likelihood that errors are introduced into your code.
-This is why the <a href="https://pslmodels.org/Catalog/library_criteria.html">PSL catalog criteria</a> requires projects to provide at least some level of unit testing.</p>
-
-<p>In the PSL Demo Day video linked above, I illustrate how to implement unit tests in R using the <a href="https://testthat.r-lib.org"> <code class="language-plaintext highlighter-rouge">testthat</code> </a> package.  There are essentially three steps to this process:</p>
-<ol>
-  <li>Create a directory to put your testing script in, e.g., a folder called <code class="language-plaintext highlighter-rouge">tests</code>
-</li>
-  <li>Create one or more scripts that define your tests.
-    <ul>
-      <li>Each test is represented as a call of the <code class="language-plaintext highlighter-rouge">test_that</code> function and contain an statement that will evaluate as true or false (e.g., you may use the <code class="language-plaintext highlighter-rouge">expect_equal</code> function to verify that a function returns expected values given certain inputs).</li>
-      <li>You will want to use <code class="language-plaintext highlighter-rouge">test</code> in the name of these tests scripts as well as something descriptive of what is tested.</li>
-    </ul>
-  </li>
-  <li>Create a script that will run your tests.
-    <ul>
-      <li>Here you’ll need to import the <code class="language-plaintext highlighter-rouge">testthat</code> package and you’ll need to call the script(s) you are testing to load their functions.</li>
-      <li>Then you’ll use the <code class="language-plaintext highlighter-rouge">test_dir</code> function to pass the directory in which the script(s) you created in Step 2 reside.</li>
-    </ul>
-  </li>
-</ol>
-
-<p>Check out the video to see examples of how each of these steps is executed.
-I’ve also found <a href="https://towardsdatascience.com/unit-testing-in-r-68ab9cc8d211">this blog post</a> on unit tests with <code class="language-plaintext highlighter-rouge">testthat</code> to be helpful.</p>
-
-<p>Unit testing in Python seems to be more developed and straightforward with the excellent <a href="https://docs.pytest.org/en/6.2.x/"> <code class="language-plaintext highlighter-rouge">pytest</code> </a> package.
-While <code class="language-plaintext highlighter-rouge">pytest</code> offers many options for parameterizing tests, running tests in parallel, and more, the basic steps remain the same as those outlined above:</p>
-<ol>
-  <li>Create a directory for your test modules (call this folder <code class="language-plaintext highlighter-rouge">tests</code> as <code class="language-plaintext highlighter-rouge">pytest</code> will look for that name).</li>
-  <li>Create test modules that define each test
-    <ul>
-      <li>Tests are defined much like any other function in Python, the but will involve some assertion statement is triggered upon test failure.</li>
-      <li>You will want to use <code class="language-plaintext highlighter-rouge">test</code> in the name of these tests modules as well as something descriptive of what is tested.</li>
-    </ul>
-  </li>
-  <li>You won’t need to create a script to run your tests as with <code class="language-plaintext highlighter-rouge">testthat</code>, but you may create a <a href="https://docs.pytest.org/en/6.2.x/customize.html"><code class="language-plaintext highlighter-rouge">pytest.ini</code></a> file to customize your tests options.</li>
-</ol>
-
-<p>That’s about it to get started writing unit tests for your code.  PSL cataloged projects provide many excellent examples of a variety of unit tests, so search them for examples to build from.
-In a future Demo Day and blog post, we’ll talk about continuous integration testing to help get even more out of you unit tests.</p>
-
-<p>Resources:</p>
-<ul>
-  <li>
-<a href="https://testthat.r-lib.org"><code class="language-plaintext highlighter-rouge">testthat</code></a> package for unit testing in R</li>
-  <li>
-<a href="https://docs.pytest.org/en/6.2.x/"><code class="language-plaintext highlighter-rouge">pytest</code></a> package for unit testing in Python</li>
-  <li><a href="https://pslmodels.org/Catalog/library_criteria.html">PSL catalog criteria</a></li>
-  <li><a href="https://github.com/TaxFoundation/capital-cost-recovery/tree/master/tests">Unit tests for the <code class="language-plaintext highlighter-rouge">capital-cost-recovery</code> model</a></li>
-</ul>
-
-  </div><a class="u-url" href="/demo-day-unit-testing" hidden></a>
-</article>
\ No newline at end of file
diff --git a/demo-days/2020/11/18/demo-day-creating-reform-files/index.html b/demo-days/2020/11/18/demo-day-creating-reform-files/index.html
new file mode 100644
index 0000000..db6e8c6
--- /dev/null
+++ b/demo-days/2020/11/18/demo-day-creating-reform-files/index.html
@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../posts/2020-11-18-demo-day-creating-reform-files.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/2021/03/02/demo-day-taxbrain-to-taxcruncher/index.html b/demo-days/2021/03/02/demo-day-taxbrain-to-taxcruncher/index.html
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--- /dev/null
+++ b/demo-days/2021/03/02/demo-day-taxbrain-to-taxcruncher/index.html
@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../posts/2021-03-02-demo-day-taxbrain-to-taxcruncher.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/OG-USA/Tax-Calculator/open-source/policy-simulation-library/compute-studio/us/2021/01/28/demo-day-how-to-use-og-usa/index.html b/demo-days/OG-USA/Tax-Calculator/open-source/policy-simulation-library/compute-studio/us/2021/01/28/demo-day-how-to-use-og-usa/index.html
new file mode 100644
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--- /dev/null
+++ b/demo-days/OG-USA/Tax-Calculator/open-source/policy-simulation-library/compute-studio/us/2021/01/28/demo-day-how-to-use-og-usa/index.html
@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../../../../../posts/2021-01-28-demo-day-how-to-use-og-usa.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/PSL/2021/03/08/demo-day-cs-api-stitch/index.html b/demo-days/PSL/2021/03/08/demo-day-cs-api-stitch/index.html
new file mode 100644
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--- /dev/null
+++ b/demo-days/PSL/2021/03/08/demo-day-cs-api-stitch/index.html
@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../posts/2021-03-08-demo-day-cs-api-stitch.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/PSL/git/github/2021/03/02/demo-day-contributing-psl/index.html b/demo-days/PSL/git/github/2021/03/02/demo-day-contributing-psl/index.html
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--- /dev/null
+++ b/demo-days/PSL/git/github/2021/03/02/demo-day-contributing-psl/index.html
@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../../posts/2021-03-02-demo-day-contributing-psl.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/R/Python/unit-testing/2021/08/09/demo-day-unit-testing/index.html b/demo-days/R/Python/unit-testing/2021/08/09/demo-day-unit-testing/index.html
new file mode 100644
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--- /dev/null
+++ b/demo-days/R/Python/unit-testing/2021/08/09/demo-day-unit-testing/index.html
@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../../posts/2021-08-09-demo-day-unit-testing.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/apps/taxes/benefits/us/2022/04/12/demo-day-policyengine-us/index.html b/demo-days/apps/taxes/benefits/us/2022/04/12/demo-day-policyengine-us/index.html
new file mode 100644
index 0000000..109c37d
--- /dev/null
+++ b/demo-days/apps/taxes/benefits/us/2022/04/12/demo-day-policyengine-us/index.html
@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../../../posts/2022-04-12-demo-day-policyengine-us.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/benefits/us/2022/07/14/demo-day-cambridge-cash-assistance/index.html b/demo-days/benefits/us/2022/07/14/demo-day-cambridge-cash-assistance/index.html
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--- /dev/null
+++ b/demo-days/benefits/us/2022/07/14/demo-day-cambridge-cash-assistance/index.html
@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../posts/2022-07-14-demo-day-cambridge-cash-assistance.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/cost-of-capital-calculator/business-taxation/corporate-income-tax/2020/12/03/demo-day-cost-of-capital-calculator/index.html b/demo-days/cost-of-capital-calculator/business-taxation/corporate-income-tax/2020/12/03/demo-day-cost-of-capital-calculator/index.html
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index 0000000..c833833
--- /dev/null
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+<body>
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+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
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+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
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+<head>
+  <title>Redirect</title>
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+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
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+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
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diff --git a/demo-days/individual-income-tax/tax-brain/tax-calculator/2021/04/05/demo-day-stacked-revenue-estimates/index.html b/demo-days/individual-income-tax/tax-brain/tax-calculator/2021/04/05/demo-day-stacked-revenue-estimates/index.html
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+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../../posts/2021-04-05-demo-day-stacked-revenue-estimates.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
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+  </script>
+</head>
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+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
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+    var redirects = {"":"../../../../../../../../posts/2021-06-14-demo-day-tax-brain-python-api.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
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+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../../posts/2020-12-23-demo-day-tax-brain.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
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+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
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+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../posts/2020-11-23-demo-day-tax-cruncher.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
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+  <title>Redirect</title>
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+    var redirects = {"":"../../../../../../../../posts/2021-05-17-demo-day-jupyter-book-deploy.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/microdf/scf/2021/01/29/demo-day-scf-microdf/index.html b/demo-days/microdf/scf/2021/01/29/demo-day-scf-microdf/index.html
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+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
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+    var redirects = {"":"../../../../../../../posts/2021-01-29-demo-day-scf-microdf.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
+    window.document.title = 'Redirect to  ' +  redirect;
+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/policy-simulation-library/compute-studio/2021/09/20/demo-day-cs-auto-deploy/index.html b/demo-days/policy-simulation-library/compute-studio/2021/09/20/demo-day-cs-auto-deploy/index.html
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@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../posts/2021-09-20-demo-day-cs-auto-deploy.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
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+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
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diff --git a/demo-days/python/data-fusion/synthimpute/2021/12/08/demo-day-synthimpute/index.html b/demo-days/python/data-fusion/synthimpute/2021/12/08/demo-day-synthimpute/index.html
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@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../../posts/2021-12-08-demo-day-synthimpute.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
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+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
+</html>
diff --git a/demo-days/python/macroeconomics/overlapping-generations/2021/11/01/demo-day-og-core/index.html b/demo-days/python/macroeconomics/overlapping-generations/2021/11/01/demo-day-og-core/index.html
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@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../../posts/2021-11-01-demo-day-og-core.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
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+    window.location.replace(redirect);
+  </script>
+</head>
+<body>
+</body>
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diff --git a/demo-days/tax/data/us/2021/07/16/demo-day-constructing-tax-data-for-the-50-states/index.html b/demo-days/tax/data/us/2021/07/16/demo-day-constructing-tax-data-for-the-50-states/index.html
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@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
+    var redirects = {"":"../../../../../../../../posts/2021-07-16-demo-day-constructing-tax-data-for-the-50-states.html"};
+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
+    var redirect = redirects[hash] || redirects[""] || "/";
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diff --git a/images/copied_from_nb/README.md b/images/copied_from_nb/README.md
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index 37c795c..0000000
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+++ /dev/null
@@ -1,3 +0,0 @@
-<center><h1>Warning</h1></center>
-
-Do not manually save images into this folder. This is used by GitHub Actions to automatically copy images.  Any images you save into this folder could be deleted at build time.
\ No newline at end of file
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-   <!-- Assemble final sorted posts array -->
-  
-  <ul class="post-list"><li><h3>
-    <a class="post-link" href="/2023-year-in-review">
-    2023: A year in review
-    </a>
-</h3><p class="post-meta-description">Highlights from the Policy Simulation Library in 2023.</p><p class="post-meta">Dec 28, 2023</p>
-</li><li><h3>
-    <a class="post-link" href="/2022-year-in-review">
-    2022: A year in review
-    </a>
-</h3><p class="post-meta-description">Highlights from the Policy Simulation Library in 2022.</p><p class="post-meta">Dec 31, 2022</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-cambridge-cash-assistance">
-    Demo Day: How does targeted cash assistance affect incentives to work?
-    </a>
-</h3><p class="post-meta-description">How a proposed program in Cambridge, Massachusetts would affect poverty and incentives.</p><p class="post-meta">Jul 14, 2022</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-github">
-    Demo Day: Getting Started with GitHub
-    </a>
-</h3><p class="post-meta-description">The basics of forking and cloning repositories and working on branches.</p><p class="post-meta">Jun 28, 2022</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-ccc-international">
-    Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator
-    </a>
-</h3><p class="post-meta-description">Using Cost-of-Capital-Calculator with data on international business tax policies.</p><p class="post-meta">Apr 18, 2022</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-policyengine-us">
-    Demo Day: Modeling taxes and benefits with the PolicyEngine US web app
-    </a>
-</h3><p class="post-meta-description">PolicyEngine US is a new web app for computing the impact of US tax and benefit policy.</p><p class="post-meta">Apr 12, 2022</p>
-</li><li><h3>
-    <a class="post-link" href="/DC-workshop">
-    Policy Simulation Library DC Workshop: Open source tools for analyzing tax policy
-    </a>
-</h3><p class="post-meta-description">Washington, DC open-source modeling workshop, March 25, 2022, 8:30am-1:00pm, Martin Luther King, Jr. Memorial Library.</p><p class="post-meta">Mar 3, 2022</p>
-</li><li><h3>
-    <a class="post-link" href="/2021-year-in-review">
-    2021: A year in review
-    </a>
-</h3><p class="post-meta-description">Highlights from the Policy Simulation Library in 2021.</p><p class="post-meta">Dec 28, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-synthimpute">
-    Demo Day: Using synthimpute for data fusion
-    </a>
-</h3><p class="post-meta-description">The synthimpute Python package fuses and synthesizes economic datasets with machine learning.</p><p class="post-meta">Dec 8, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-og-core">
-    Demo Day: The OG-Core platform
-    </a>
-</h3><p class="post-meta-description">A Python platform for building country-specific overlapping generations general equilibrium models.</p><p class="post-meta">Nov 1, 2021</p>
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-    <a class="post-link" href="/demo-day-cs-auto-deploy">
-    Demo Day: Deploying apps on Compute Studio
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-</h3><p class="post-meta-description">How to deploy apps on Compute Studio using the new automated deployments feature.</p><p class="post-meta">Sep 20, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-unit-testing">
-    Demo Day: Unit testing for open source projects
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-</h3><p class="post-meta-description">How to ensure that individual functions do what you expect.</p><p class="post-meta">Aug 9, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-constructing-tax-data-for-the-50-states">
-    Demo Day: Constructing tax data for the 50 states
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-</h3><p class="post-meta-description">A new dataset to facilitate state-level analysis of federal tax reforms.</p><p class="post-meta">Jul 16, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-tax-brain-python-api">
-    Demo Day: Using the TaxBrain Python API
-    </a>
-</h3><p class="post-meta-description">A programmatic interface to compute the impact of tax reform.</p><p class="post-meta">Jun 14, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-jupyter-book-deploy">
-    Demo Day: Updating Jupyter Book documentation with GitHub Actions
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+</div>
+<div class="listing-category" onclick="window.quartoListingCategory('us'); return false;">
+us
+</div>
+</div>
+<div class="listing-description">
+<a href="./posts/2020-12-23-demo-day-tax-brain.html" class="no-external">Computing the impact of US tax reform with the Tax-Brain web-app.</a>
+</div>
+</div>
+<div class="metadata">
+<a href="./posts/2020-12-23-demo-day-tax-brain.html" class="no-external">
+<div class="listing-date">
+Dec 23, 2020
+</div>
+<div class="listing-author">
+Anderson Frailey
+</div>
+</a>
+</div>
+</div>
+<div class="quarto-post image-right" data-index="22" data-categories="psl,psl-foundation" data-listing-date-sort="1608681600000" data-listing-file-modified-sort="1709693948225" data-listing-date-modified-sort="NaN" data-listing-reading-time-sort="3" data-listing-word-count-sort="447">
+<div class="thumbnail">
+<p><a href="./posts/2020-12-23-2020-year-in-review.html" class="no-external"></a></p><a href="./posts/2020-12-23-2020-year-in-review.html" class="no-external">
+<p><img src="https://pslmodels.org/imgs/PSL.svg" class="thumbnail-image"></p>
+</a><p><a href="./posts/2020-12-23-2020-year-in-review.html" class="no-external"></a></p>
+</div>
+<div class="body">
+<h3 class="no-anchor listing-title">
+<a href="./posts/2020-12-23-2020-year-in-review.html" class="no-external">2020: A year in review</a>
+</h3>
+<div class="listing-subtitle">
+<a href="./posts/2020-12-23-2020-year-in-review.html" class="no-external"></a>
+</div>
+<div class="listing-categories">
+<div class="listing-category" onclick="window.quartoListingCategory('psl'); return false;">
+psl
+</div>
+<div class="listing-category" onclick="window.quartoListingCategory('psl-foundation'); return false;">
+psl-foundation
+</div>
+</div>
+<div class="listing-description">
+<a href="./posts/2020-12-23-2020-year-in-review.html" class="no-external">Highlights from the Policy Simulation Library in 2020.</a>
+</div>
+</div>
+<div class="metadata">
+<a href="./posts/2020-12-23-2020-year-in-review.html" class="no-external">
+<div class="listing-date">
+Dec 23, 2020
+</div>
+<div class="listing-author">
+Jason DeBacker
+</div>
+</a>
+</div>
+</div>
+<div class="quarto-post image-right" data-index="23" data-categories="demo-days,cost-of-capital-calculator,business-taxation,corporate-income-tax" data-listing-date-sort="1606953600000" data-listing-file-modified-sort="1709693948225" data-listing-date-modified-sort="NaN" data-listing-reading-time-sort="2" data-listing-word-count-sort="345">
+<div class="thumbnail">
+<p><a href="./posts/2020-12-03-demo-day-cost-of-capital-calculator.html" class="no-external"></a></p><a href="./posts/2020-12-03-demo-day-cost-of-capital-calculator.html" class="no-external">
+<div class="listing-item-img-placeholder card-img-top" >&nbsp;</div>
+</a><p><a href="./posts/2020-12-03-demo-day-cost-of-capital-calculator.html" class="no-external"></a></p>
+</div>
+<div class="body">
+<h3 class="no-anchor listing-title">
+<a href="./posts/2020-12-03-demo-day-cost-of-capital-calculator.html" class="no-external">Demo Day: Cost-of-Capital-Calculator Web Application</a>
+</h3>
+<div class="listing-subtitle">
+<a href="./posts/2020-12-03-demo-day-cost-of-capital-calculator.html" class="no-external"></a>
+</div>
+<div class="listing-categories">
+<div class="listing-category" onclick="window.quartoListingCategory('demo-days'); return false;">
+demo-days
+</div>
+<div class="listing-category" onclick="window.quartoListingCategory('cost-of-capital-calculator'); return false;">
+cost-of-capital-calculator
+</div>
+<div class="listing-category" onclick="window.quartoListingCategory('business-taxation'); return false;">
+business-taxation
+</div>
+<div class="listing-category" onclick="window.quartoListingCategory('corporate-income-tax'); return false;">
+corporate-income-tax
+</div>
+</div>
+<div class="listing-description">
+<a href="./posts/2020-12-03-demo-day-cost-of-capital-calculator.html" class="no-external">Computing the impact of taxes on business investment incentives under alternative policy scenarios.</a>
+</div>
+</div>
+<div class="metadata">
+<a href="./posts/2020-12-03-demo-day-cost-of-capital-calculator.html" class="no-external">
+<div class="listing-date">
+Dec 3, 2020
+</div>
+<div class="listing-author">
+Jason DeBacker
+</div>
+</a>
+</div>
+</div>
+<div class="quarto-post image-right" data-index="24" data-categories="demo-days,individual-income-tax,tax-cruncher" data-listing-date-sort="1606089600000" data-listing-file-modified-sort="1709693948225" data-listing-date-modified-sort="NaN" data-listing-reading-time-sort="1" data-listing-word-count-sort="149">
+<div class="thumbnail">
+<p><a href="./posts/2020-11-23-demo-day-tax-cruncher.html" class="no-external"></a></p><a href="./posts/2020-11-23-demo-day-tax-cruncher.html" class="no-external">
+<div class="listing-item-img-placeholder card-img-top" >&nbsp;</div>
+</a><p><a href="./posts/2020-11-23-demo-day-tax-cruncher.html" class="no-external"></a></p>
+</div>
+<div class="body">
+<h3 class="no-anchor listing-title">
+<a href="./posts/2020-11-23-demo-day-tax-cruncher.html" class="no-external">Demo Day: Tax-Cruncher</a>
+</h3>
+<div class="listing-subtitle">
+<a href="./posts/2020-11-23-demo-day-tax-cruncher.html" class="no-external"></a>
+</div>
+<div class="listing-categories">
+<div class="listing-category" onclick="window.quartoListingCategory('demo-days'); return false;">
+demo-days
+</div>
+<div class="listing-category" onclick="window.quartoListingCategory('individual-income-tax'); return false;">
+individual-income-tax
+</div>
+<div class="listing-category" onclick="window.quartoListingCategory('tax-cruncher'); return false;">
+tax-cruncher
+</div>
+</div>
+<div class="listing-description">
+<a href="./posts/2020-11-23-demo-day-tax-cruncher.html" class="no-external">How to calculate a taxpayer’s liabilities under current law and under a policy reform.</a>
+</div>
+</div>
+<div class="metadata">
+<a href="./posts/2020-11-23-demo-day-tax-cruncher.html" class="no-external">
+<div class="listing-date">
+Nov 23, 2020
+</div>
+<div class="listing-author">
+Peter Metz
+</div>
+</a>
+</div>
+</div>
+<div class="quarto-post image-right" data-index="25" data-categories="demo-days" data-listing-date-sort="1605657600000" data-listing-file-modified-sort="1709693948225" data-listing-date-modified-sort="NaN" data-listing-reading-time-sort="1" data-listing-word-count-sort="149">
+<div class="thumbnail">
+<p><a href="./posts/2020-11-18-demo-day-creating-reform-files.html" class="no-external"></a></p><a href="./posts/2020-11-18-demo-day-creating-reform-files.html" class="no-external">
+<div class="listing-item-img-placeholder card-img-top" >&nbsp;</div>
+</a><p><a href="./posts/2020-11-18-demo-day-creating-reform-files.html" class="no-external"></a></p>
+</div>
+<div class="body">
+<h3 class="no-anchor listing-title">
+<a href="./posts/2020-11-18-demo-day-creating-reform-files.html" class="no-external">Demo Day: Building policy reform files</a>
+</h3>
+<div class="listing-subtitle">
+<a href="./posts/2020-11-18-demo-day-creating-reform-files.html" class="no-external"></a>
+</div>
+<div class="listing-categories">
+<div class="listing-category" onclick="window.quartoListingCategory('demo-days'); return false;">
+demo-days
+</div>
+</div>
+<div class="listing-description">
+<a href="./posts/2020-11-18-demo-day-creating-reform-files.html" class="no-external">The first in Policy Simulation Library’s new live demo series describes specifying tax reforms.</a>
+</div>
+</div>
+<div class="metadata">
+<a href="./posts/2020-11-18-demo-day-creating-reform-files.html" class="no-external">
+<div class="listing-date">
+Nov 18, 2020
+</div>
+<div class="listing-author">
+Matt Jensen
+</div>
+</a>
+</div>
+</div>
+<div class="quarto-post image-right" data-index="26" data-categories="announcements" data-listing-date-sort="1604620800000" data-listing-file-modified-sort="1709693948225" data-listing-date-modified-sort="NaN" data-listing-reading-time-sort="1" data-listing-word-count-sort="130">
+<div class="thumbnail">
+<p><a href="./posts/2020-11-06-introducing-psl-blog.html" class="no-external"></a></p><a href="./posts/2020-11-06-introducing-psl-blog.html" class="no-external">
+<div class="listing-item-img-placeholder card-img-top" >&nbsp;</div>
+</a><p><a href="./posts/2020-11-06-introducing-psl-blog.html" class="no-external"></a></p>
+</div>
+<div class="body">
+<h3 class="no-anchor listing-title">
+<a href="./posts/2020-11-06-introducing-psl-blog.html" class="no-external">Introducing the PSL Blog</a>
+</h3>
+<div class="listing-subtitle">
+<a href="./posts/2020-11-06-introducing-psl-blog.html" class="no-external"></a>
+</div>
+<div class="listing-categories">
+<div class="listing-category" onclick="window.quartoListingCategory('announcements'); return false;">
+announcements
+</div>
+</div>
+<div class="listing-description">
+<a href="./posts/2020-11-06-introducing-psl-blog.html" class="no-external">A new way to follow models in the Policy Simulation Library catalog.</a>
+</div>
+</div>
+<div class="metadata">
+<a href="./posts/2020-11-06-introducing-psl-blog.html" class="no-external">
+<div class="listing-date">
+Nov 6, 2020
+</div>
+<div class="listing-author">
+Max Ghenis
+</div>
+</a>
+</div>
+</div>
+</div>
+<div class="listing-no-matching d-none">
+No matching items
+</div>
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diff --git a/introducing-psl-blog.html b/introducing-psl-blog.html
deleted file mode 100755
index 9b04ece..0000000
--- a/introducing-psl-blog.html
+++ /dev/null
@@ -1,45 +0,0 @@
-<article class="post h-entry" itemscope itemtype="http://schema.org/BlogPosting">
-
-  <header class="post-header">
-    <h1 class="post-title p-name" itemprop="name headline">Introducing the PSL Blog</h1><p class="page-description">A new way to follow models in the Policy Simulation Library catalog.</p><p class="post-meta post-meta-title"><time class="dt-published" datetime="2020-11-06T00:00:00-06:00" itemprop="datePublished">
-        Nov 6, 2020
-      </time>• 
-          <span itemprop="author" itemscope itemtype="http://schema.org/Person">
-            <span class="p-author h-card" itemprop="name">Max Ghenis</span></span>
-       • <span class="read-time" title="Estimated read time">
-    
-    
-      1 min read
-    
-</span></p>
-
-    
-      <p class="category-tags"><i class="fas fa-tags category-tags-icon"></i></i> 
-      
-        <a class="category-tags-link" href="/categories/#announcements">announcements</a>
-        
-      
-      </p>
-    
-
-    </header>
-
-  <div class="post-content e-content" itemprop="articleBody">
-    <ul class="section-nav">
-</ul><p>Our mission at the Policy Simulation Library is to improve public policy by opening up models and data preparation routines for policy analysis.
-To support and showcase our diverse community of users and developers, we engage across several mediums: a monthly <a href="https://www.pslmodels.org/Newsletter/archive.html">newsletter</a>, a Q&amp;A <a href="http://discourse.pslmodels.org/">forum</a>, (now-virtual) <a href="https://www.meetup.com/dc-psl-meetup/">meetups</a>, our Twitter <a href="https://twitter.com/pslmodels">feed</a>, our YouTube <a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">channel</a>, <a href="https://www.pslmodels.org/Catalog/index.html">documentation</a> for models in our catalog, and of course, issues and pull requests on <a href="http://github.com/pslmodels">GitHub</a>.</p>
-
-<p>Today, we’re adding a new medium: the PSL Blog.
-We’ll use this space to share major updates on our catalog, provide tutorials, and summarize events or papers that involve our models.</p>
-
-<p>If you’d like to share your work on our blog, or to suggest content, <a href="mailto:mghenis@gmail.com">drop me a line</a>.
-To follow along, add the PSL blog’s RSS feed or subscribe to our <a href="https://www.pslmodels.org/Newsletter/archive.html">newsletter</a>.</p>
-
-<p>Happy reading,</p>
-
-<p>Max Ghenis</p>
-
-<p>Editor, PSL Blog</p>
-
-  </div><a class="u-url" href="/introducing-psl-blog" hidden></a>
-</article>
\ No newline at end of file
diff --git a/listings.json b/listings.json
new file mode 100644
index 0000000..fad6afe
--- /dev/null
+++ b/listings.json
@@ -0,0 +1,34 @@
+[
+  {
+    "listing": "/index.html",
+    "items": [
+      "/posts/2023-12-28-2023-year-in-review.html",
+      "/posts/2022-12-31-2022-year-in-review.html",
+      "/posts/2022-07-14-demo-day-cambridge-cash-assistance.html",
+      "/posts/2022-06-28-demo-day-github.html",
+      "/posts/2022-04-18-demo-day-ccc-international.html",
+      "/posts/2022-04-12-demo-day-policyengine-us.html",
+      "/posts/2022-03-03-DC-workshop.html",
+      "/posts/2021-12-28-2021-year-in-review.html",
+      "/posts/2021-12-08-demo-day-synthimpute.html",
+      "/posts/2021-11-01-demo-day-og-core.html",
+      "/posts/2021-09-20-demo-day-cs-auto-deploy.html",
+      "/posts/2021-08-09-demo-day-unit-testing.html",
+      "/posts/2021-07-16-demo-day-constructing-tax-data-for-the-50-states.html",
+      "/posts/2021-06-14-demo-day-tax-brain-python-api.html",
+      "/posts/2021-05-17-demo-day-jupyter-book-deploy.html",
+      "/posts/2021-04-05-demo-day-stacked-revenue-estimates.html",
+      "/posts/2021-03-08-demo-day-cs-api-stitch.html",
+      "/posts/2021-03-02-demo-day-taxbrain-to-taxcruncher.html",
+      "/posts/2021-03-02-demo-day-contributing-psl.html",
+      "/posts/2021-01-29-demo-day-scf-microdf.html",
+      "/posts/2021-01-28-demo-day-how-to-use-og-usa.html",
+      "/posts/2020-12-23-demo-day-tax-brain.html",
+      "/posts/2020-12-23-2020-year-in-review.html",
+      "/posts/2020-12-03-demo-day-cost-of-capital-calculator.html",
+      "/posts/2020-11-23-demo-day-tax-cruncher.html",
+      "/posts/2020-11-18-demo-day-creating-reform-files.html",
+      "/posts/2020-11-06-introducing-psl-blog.html"
+    ]
+  }
+]
\ No newline at end of file
diff --git a/images/logo.png b/logo.png
similarity index 100%
rename from images/logo.png
rename to logo.png
diff --git a/page2/index.html b/page2/index.html
deleted file mode 100755
index 0ed058b..0000000
--- a/page2/index.html
+++ /dev/null
@@ -1,90 +0,0 @@
-<div class="home"><h1 id="posts">Posts</h1>
-
-
-
-  
-
-  <!-- Hide posts if front matter flag hide:true -->
-  
-  
-
-  <!-- Sort posts by rank, then date -->
-  
-  
-  
-
- 
-  
-
-   <!-- Assemble final sorted posts array -->
-  
-  <ul class="post-list"><li><h3>
-    <a class="post-link" href="/demo-day-stacked-revenue-estimates">
-    Demo Day: Producing stacked revenue estimates with the Tax-Calculator Python API
-    </a>
-</h3><p class="post-meta-description">How to evaluate the cumulative effects of a multi-part tax reform.</p><p class="post-meta">Apr 5, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-cs-api-stitch">
-    Demo Day: Stitching together apps on Compute Studio
-    </a>
-</h3><p class="post-meta-description">Creating an app with the Compute Studio API.</p><p class="post-meta">Mar 8, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-taxbrain-to-taxcruncher">
-    Demo Day: Moving policy reform files from Tax-Brain to Tax-Cruncher
-    </a>
-</h3><p class="post-meta-description">How to move reforms between a tax-unit-level and society-wide model with the Compute.Studio API.</p><p class="post-meta">Mar 2, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-contributing-psl">
-    Demo Day: Contributing to PSL projects
-    </a>
-</h3><p class="post-meta-description">How to help software projects in the Policy Simulation Library.</p><p class="post-meta">Mar 2, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-scf-microdf">
-    Demo Day: Running the scf and microdf Python packages in Google Colab
-    </a>
-</h3><p class="post-meta-description">Analyzing US wealth data in a web-based Python notebook.</p><p class="post-meta">Jan 29, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-how-to-use-og-usa">
-    Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy
-    </a>
-</h3><p class="post-meta-description">How to model the macroeconomic effects of tax reform with a web app.</p><p class="post-meta">Jan 28, 2021</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-tax-brain">
-    Demo Day: Tax-Brain
-    </a>
-</h3><p class="post-meta-description">Computing the impact of US tax reform with the Tax-Brain web-app.</p><p class="post-meta">Dec 23, 2020</p>
-</li><li><h3>
-    <a class="post-link" href="/2020-year-in-review">
-    2020: A year in review
-    </a>
-</h3><p class="post-meta-description">Highlights from the Policy Simulation Library in 2020.</p><p class="post-meta">Dec 23, 2020</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-cost-of-capital-calculator">
-    Demo Day: Cost-of-Capital-Calculator Web Application
-    </a>
-</h3><p class="post-meta-description">Computing the impact of taxes on business investment incentives under alternative policy scenarios.</p><p class="post-meta">Dec 3, 2020</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-tax-cruncher">
-    Demo Day: Tax-Cruncher
-    </a>
-</h3><p class="post-meta-description">How to calculate a taxpayer's liabilities under current law and under a policy reform.</p><p class="post-meta">Nov 23, 2020</p>
-</li><li><h3>
-    <a class="post-link" href="/demo-day-creating-reform-files">
-    Demo Day: Building policy reform files
-    </a>
-</h3><p class="post-meta-description">The first in Policy Simulation Library's new live demo series describes specifying tax reforms.</p><p class="post-meta">Nov 18, 2020</p>
-</li><li><h3>
-    <a class="post-link" href="/introducing-psl-blog">
-    Introducing the PSL Blog
-    </a>
-</h3><p class="post-meta-description">A new way to follow models in the Policy Simulation Library catalog.</p><p class="post-meta">Nov 6, 2020</p>
-</li></ul>
-
-    
-      <div class="pager">
-        <ul class="pagination">
-          <li><a href="/" class="previous-page">1</a></li>
-          <li><div class="current-page">2</div></li>
-          <li><div class="pager-edge">•</div></li>
-        </ul>
-      </div></div>
\ No newline at end of file
diff --git a/posts/2020-11-06-introducing-psl-blog.html b/posts/2020-11-06-introducing-psl-blog.html
new file mode 100644
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+<meta name="dcterms.date" content="2020-11-06">
+<meta name="description" content="A new way to follow models in the Policy Simulation Library catalog.">
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+    <span class="navbar-title">Policy Simulation Library Blog</span>
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+    <a class="nav-link" href="https://github.com/PSLmodels"> <i class="bi bi-github" role="img">
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+</i> 
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+      <h1 class="title">Introducing the PSL Blog</h1>
+                  <div>
+        <div class="description">
+          A new way to follow models in the Policy Simulation Library catalog.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">announcements</div>
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+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Max Ghenis </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">November 6, 2020</p>
+      </div>
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+
+
+
+
+
+<p>Our mission at the Policy Simulation Library is to improve public policy by opening up models and data preparation routines for policy analysis. To support and showcase our diverse community of users and developers, we engage across several mediums: a monthly <a href="https://www.pslmodels.org/Newsletter/archive.html">newsletter</a>, a Q&amp;A <a href="http://discourse.pslmodels.org/">forum</a>, (now-virtual) <a href="https://www.meetup.com/dc-psl-meetup/">meetups</a>, our Twitter <a href="https://twitter.com/pslmodels">feed</a>, our YouTube <a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">channel</a>, <a href="https://www.pslmodels.org/Catalog/index.html">documentation</a> for models in our catalog, and of course, issues and pull requests on <a href="http://github.com/pslmodels">GitHub</a>.</p>
+<p>Today, we’re adding a new medium: the PSL Blog. We’ll use this space to share major updates on our catalog, provide tutorials, and summarize events or papers that involve our models.</p>
+<p>If you’d like to share your work on our blog, or to suggest content, <a href="mailto:mghenis@gmail.com">drop me a line</a>. To follow along, add the PSL blog’s RSS feed or subscribe to our <a href="https://www.pslmodels.org/Newsletter/archive.html">newsletter</a>.</p>
+<p>Happy reading,</p>
+<p>Max Ghenis</p>
+<p>Editor, PSL Blog</p>
+
+
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+
+
+
+
+</body></html>
\ No newline at end of file
diff --git a/posts/2020-11-18-demo-day-creating-reform-files.html b/posts/2020-11-18-demo-day-creating-reform-files.html
new file mode 100644
index 0000000..8aa13ed
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+++ b/posts/2020-11-18-demo-day-creating-reform-files.html
@@ -0,0 +1,597 @@
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+
+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
+
+<meta name="author" content="Matt Jensen">
+<meta name="dcterms.date" content="2020-11-18">
+<meta name="description" content="The first in Policy Simulation Library’s new live demo series describes specifying tax reforms.">
+
+<title>Policy Simulation Library Blog - Demo Day: Building policy reform files</title>
+<style>
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+div.columns{display: flex; gap: min(4vw, 1.5em);}
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+      <div class="navbar-container container-fluid">
+      <div class="navbar-brand-container mx-auto">
+    <a class="navbar-brand" href="../index.html">
+    <span class="navbar-title">Policy Simulation Library Blog</span>
+    </a>
+  </div>
+            <div id="quarto-search" class="" title="Search"></div>
+          <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarCollapse" aria-controls="navbarCollapse" aria-expanded="false" aria-label="Toggle navigation" onclick="if (window.quartoToggleHeadroom) { window.quartoToggleHeadroom(); }">
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+            <ul class="navbar-nav navbar-nav-scroll ms-auto">
+  <li class="nav-item">
+    <a class="nav-link" href="../about.html"> 
+<span class="menu-text">PSL Blog</span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://github.com/PSLmodels"> <i class="bi bi-github" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://twitter.com/PSLmodels"> <i class="bi bi-twitter" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+</ul>
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+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Building policy reform files</h1>
+                  <div>
+        <div class="description">
+          The first in Policy Simulation Library’s new live demo series describes specifying tax reforms.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Matt Jensen </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">November 18, 2020</p>
+      </div>
+    </div>
+    
+      
+    </div>
+    
+  
+  </header><div id="quarto-content" class="quarto-container page-columns page-rows-contents page-layout-article page-navbar">
+<!-- sidebar -->
+<!-- margin-sidebar -->
+    <div id="quarto-margin-sidebar" class="sidebar margin-sidebar">
+        
+    </div>
+<!-- main -->
+<main class="content quarto-banner-title-block" id="quarto-document-content">
+
+
+
+
+
+<p>Check out the video:</p>
+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/AFJq4ZrwEqA" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<p>We will host Demo Days every two weeks until the end of the year. You can see our schedule on <a href="https://www.pslmodels.org/events.html">our events page</a>.</p>
+<hr>
+<p>Show notes:</p>
+<p>I demonstrate how to build policy reform files using the Tax-Brain webapp on Compute Studio. (Useful links below.) This is an introductory lesson that ends with a cliffhanger. We don’t run the model. But we do generate an individual income and payroll tax reform file that is compatible with a range of policy simulation models and analytic tools, some designed for policy decision makers, others for taxpayers and benefits recipients interested in assessing their own circumstances.</p>
+<p>Beyond individual and payroll tax analysis, the reform file can be used with models that assess pass-through and corporate taxation of businesses, as well as a variety of income benefit programs. A wide range of use cases will occupy future events.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://https://compute.studio/PSLmodels/Tax-Brain/48422/">Demo C/S simulation</a></li>
+<li><a href="https://https://www.irs.gov/pub/irs-pdf/f1040.pdf">IRS Form 1040</a></li>
+<li><a href="https://https://www.pslmodels.org/Catalog/index.html">PSL Catalog</a></li>
+<li><a href="https://https://www.pslmodels.org/events.html">PSL Events</a></li>
+</ul>
+
+
+
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+</body></html>
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diff --git a/posts/2020-11-23-demo-day-tax-cruncher.html b/posts/2020-11-23-demo-day-tax-cruncher.html
new file mode 100644
index 0000000..53630ce
--- /dev/null
+++ b/posts/2020-11-23-demo-day-tax-cruncher.html
@@ -0,0 +1,595 @@
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+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
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+<meta name="author" content="Peter Metz">
+<meta name="dcterms.date" content="2020-11-23">
+<meta name="description" content="How to calculate a taxpayer’s liabilities under current law and under a policy reform.">
+
+<title>Policy Simulation Library Blog - Demo Day: Tax-Cruncher</title>
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+<span class="menu-text">PSL Blog</span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://github.com/PSLmodels"> <i class="bi bi-github" role="img">
+</i> 
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+      <h1 class="title">Demo Day: Tax-Cruncher</h1>
+                  <div>
+        <div class="description">
+          How to calculate a taxpayer’s liabilities under current law and under a policy reform.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">individual-income-tax</div>
+                <div class="quarto-category">tax-cruncher</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Peter Metz </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">November 23, 2020</p>
+      </div>
+    </div>
+    
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+<hr>
+<p>For the Demo Day on November 16, I showed how to calculate a taxpayer’s liabilities under current law and under a policy reform with Tax-Cruncher. The Tax-Cruncher web application takes two sets of inputs: a taxpayer’s demographic and financial information and the provisions of a tax reform.</p>
+<p>For the first Demo Day example (<a href="https://youtu.be/d4T-DOxm2QQ?t=230">3:50</a>), we looked at how eliminating the state and local tax (SALT) deduction cap and applying payroll tax to earnings above $400,000 would affect a high earner. In particular, our hypothetical filer had $500,000 in wages, $100,000 in capital gains, and $100,000 in itemizable expenses. You can see the results at <a href="https://compute.studio/PSLmodels/Tax-Cruncher/634/">Compute Studio simulation #634</a>.</p>
+<p>For the second example (<a href="https://youtu.be/d4T-DOxm2QQ?t=1070">17:50</a>), we looked at how expanding the Earned Income Tax Credit (EITC) and Child Tax Credit would impact a family with $45,000 in wages and two young children. You can see the results at <a href="https://compute.studio/PSLmodels/Tax-Cruncher/636/">Compute Studio simulation #636</a>.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://compute.studio/PSLmodels/Tax-Cruncher/">Tax-Cruncher</a></li>
+<li><a href="https://compute.studio/AEIEconomics/Tax-Cruncher-Biden/">Tax-Cruncher-Biden</a></li>
+</ul>
+
+
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diff --git a/posts/2020-12-03-demo-day-cost-of-capital-calculator.html b/posts/2020-12-03-demo-day-cost-of-capital-calculator.html
new file mode 100644
index 0000000..80672ca
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+<meta name="author" content="Jason DeBacker">
+<meta name="dcterms.date" content="2020-12-03">
+<meta name="description" content="Computing the impact of taxes on business investment incentives under alternative policy scenarios.">
+
+<title>Policy Simulation Library Blog - Demo Day: Cost-of-Capital-Calculator Web Application</title>
+<style>
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+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Cost-of-Capital-Calculator Web Application</h1>
+                  <div>
+        <div class="description">
+          Computing the impact of taxes on business investment incentives under alternative policy scenarios.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">cost-of-capital-calculator</div>
+                <div class="quarto-category">business-taxation</div>
+                <div class="quarto-category">corporate-income-tax</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">December 3, 2020</p>
+      </div>
+    </div>
+    
+      
+    </div>
+    
+  
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+        
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+<!-- main -->
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+
+
+
+
+
+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/KLIuFbYPpNA" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<hr>
+<p>In the PSL Demo Day video linked above, I demonstrate how to use the Cost-of-Capital-Calculator (CCC) web application on <a href="https://compute.studio">Compute-Studio</a>. CCC computes various measures of the impact of the tax system on business investment. These include the <a href="http://piketty.pse.ens.fr/files/HallJorgenson67.pdf">Hall-Jorgenson cost of capital</a>, <a href="http://webarchive.urban.org/UploadedPDF/1000538.pdf">marginal effective tax rates</a>, and effective average tax rates (following the methodology of <a href="https://www.ifs.org.uk/wps/wp9816.pdf">Devereux and Griffith (1999)</a>).</p>
+<p>I begin by illustrating the various parameters available for the user to manipulate. These include parameters of the business and individual income tax systems, as well as parameters representing economic assumptions (e.g., inflation rates and nominal interest rates) and parameters dictating financial and accounting policy (e.g., the fraction of financing using debt). Note that all default values for tax policy parameters represent the “baseline policy”, which is defined as the current law policy in the year being analyzed (which itself is a parameter the user can change). Other parameters are estimated using historical data following the methodology of <a href="https://www.cbo.gov/sites/default/files/113th-congress-2013-2014/reports/49817-taxingcapitalincome0.pdf">CBO (2014)</a>.</p>
+<p>Next, I change a few parameters and run the model. In this example, I move the corporate income tax rate up to 28% and lower bonus depreciation for assets with depreciable lives of 20 years or less to 50%.</p>
+<p>Finally, I discuss how to interpret output. The web app returns a table and three figures summarizing marginal effective total tax rates on new investments. This selection of output helps give one a sense of the the overall changes, as well as effects across asset types, industries, and type of financing. For the full model output, one can click on “Download Results”. Doing so will download four CSV files contain several measures of the impact of the tax system on investment for very fine asset and industry categories. Users can take these files and create tables and visualizations relevant to their own use case.</p>
+<p>Please take the model for a spin and simulate your own reform. If you have questions, comments, or suggestions, please let me know on the <a href="http://discourse.pslmodels.org">PSL Discourse</a> (non-technical questions) or by opening an issue in the <a href="https://github.com/PSLmodels/Cost-of-Capital-Calculator/issues">CCC GitHub repository</a> (technical questions).</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://compute.studio/PSLmodels/Cost-of-Capital-Calculator/104/">Compute Studio simulation used in the demonstration</a></li>
+<li><a href="https://compute.studio/PSLmodels/Cost-of-Capital-Calculator/">Cost-of-Capital-Calculator web app</a></li>
+<li><a href="https://pslmodels.github.io/Cost-of-Capital-Calculator/content/intro.html">Cost-of-Capital-Calculator documentation</a></li>
+<li><a href="https://github.com/PSLmodels/Cost-of-Capital-Calculator/">Cost-of-Capital-Calculator GitHub repository</a></li>
+</ul>
+
+
+
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diff --git a/posts/2020-12-23-2020-year-in-review.html b/posts/2020-12-23-2020-year-in-review.html
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+<meta name="dcterms.date" content="2020-12-23">
+<meta name="description" content="Highlights from the Policy Simulation Library in 2020.">
+
+<title>Policy Simulation Library Blog - 2020: A year in review</title>
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+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">2020: A year in review</h1>
+                  <div>
+        <div class="description">
+          Highlights from the Policy Simulation Library in 2020.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">psl</div>
+                <div class="quarto-category">psl-foundation</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">December 23, 2020</p>
+      </div>
+    </div>
+    
+      
+    </div>
+    
+  
+  </header><div id="quarto-content" class="quarto-container page-columns page-rows-contents page-layout-article page-navbar">
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+
+
+
+<p><img src="https://pslmodels.org/imgs/PSL.svg" class="img-fluid"></p>
+<hr>
+<p>This year has been one to forget! But 2020 did have its bright spots, especially in the PSL community. This post reviews some of the highlights from the year.</p>
+<p>The Library was able to welcome two new models to the catalog in 2020: <a href="https://github.com/PSLmodels/microdf">microdf</a> and <a href="https://github.com/PSLmodels/openfisca-uk">OpenFisca-UK</a>. microdf provides a number of useful tools for use with economic survey data. OpenFisca-UK builds off the <a href="https://openfisca.org/en/">OpenFisca</a> platform, offering a microsimulation model for tax and benefit programs in the UK.</p>
+<p>In addition, four new models were added to the Library as incubating projects. The <a href="https://github.com/PSLmodels/ui_calculator">ui-calculator</a> model has received a lot of attention this year in the U.S., as it provides the capability to calculate unemployment insurance benefits across U.S. states, a major mode of delivering financial relief to individuals during the COVID crisis. <a href="https://github.com/PSLmodels/PCI-Outbreak">PCI-Outbreak</a> directly relates to the COVID crisis, using machine learning and natural language processing to estimate the true extent of the COVID pandemic in China. The model finds that actual COVID cases are significantly higher than what official statistics claim. The <a href="https://github.com/PSLmodels/COVID-MCS">COVID-MCS</a> model considers COVID case counts and test positivity rates to measure whether or not U.S. communities are meeting certain benchmarks in controlling the spread of the disease. On a lighter note, the <a href="https://github.com/PSLmodels/Git-Tutorial">Git-Tutorial</a> project provides instruction and resources for learning to use Git and GitHub, with an emphasis on the workflow used by many projects in the PSL community.</p>
+<p>The organization surrounding the Policy Simulation Library has been bolstered in two ways. First, we have formed a relationship with the <a href="https://opencollective.com/psl">Open Collective Foundation</a>, who is now our fiscal host. This allows PSL to accept tax deductible contributions that will support the efforts of the community. Second, we’ve formed the PSL Foundation, with an initial board that includes <a href="https://associates.bloomberg.org/team/linda-gibbs/">Linda Gibbs</a>, <a href="https://glennhubbard.net">Glenn Hubbard</a>, and <a href="http://jasondebacker.com">Jason DeBacker</a>.</p>
+<p>Our outreach efforts have grown in 2020 to include the regular PSL Demo Day series and this PSL Blog. Community members have also presented work with PSL models at the <a href="https://glennhubbard.net">PyData Global Conference</a>, the Tax Economists Forum, <a href="https://www.youtube.com/watch?time_continue=7&amp;v=mRCcJ-pD7R0&amp;feature=emb_logo">AEI</a>, the <a href="https://coiled.io/live-stream/scaling-open-source-policy-models-biden-plan-science-thursdays/">Coiled Podcast</a>, and the <a href="https://www.virtualglobalvillage.com/blog/meet-jason-debacker">Virtual Global Village Podcast</a>. New users will also find a better experience learning how to use and contribute to PSL models as many PSL models have improved their documentation through the use of <a href="https://jupyterbook.org/intro.html">Jupyter Book</a> (e.g., see the <a href="https://pslmodels.github.io/Tax-Calculator/">Tax-Calculator documentation</a>).</p>
+<p>We love seeing the community around open source policymaking expand and are proud that PSL models have been used for important policy analysis in 2020, including analyzing <a href="https://medium.com/@ernietedeschi/updated-distribution-of-household-rebate-ideas-so-far-f46360034f9d">economic policy responses to the pandemic</a> and the <a href="https://www.aei.org/research-products/report/an-analysis-of-joe-bidens-tax-proposals/">platforms of presidential candidates</a>. We look forward to more progress in 2021 and welcome you to join the effort as a contributor, <a href="https://opencollective.com/psl">financially</a> or <a href="https://pslmodels.org/Community/contribute.html">as an open source developer</a>.</p>
+<p>Best wishes from PSL for a happy and healthy new year!</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://twitter.com/PSLmodels">PSL Twitter Feed</a></li>
+<li><a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">PSL YouTube</a></li>
+<li><a href="https://opencollective.com/psl">PSL on Open Collective</a></li>
+</ul>
+
+
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+</body></html>
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diff --git a/posts/2020-12-23-demo-day-tax-brain.html b/posts/2020-12-23-demo-day-tax-brain.html
new file mode 100644
index 0000000..76b2c26
--- /dev/null
+++ b/posts/2020-12-23-demo-day-tax-brain.html
@@ -0,0 +1,598 @@
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+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
+
+<meta name="author" content="Anderson Frailey">
+<meta name="dcterms.date" content="2020-12-23">
+<meta name="description" content="Computing the impact of US tax reform with the Tax-Brain web-app.">
+
+<title>Policy Simulation Library Blog - Demo Day: Tax-Brain</title>
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+      <div class="navbar-container container-fluid">
+      <div class="navbar-brand-container mx-auto">
+    <a class="navbar-brand" href="../index.html">
+    <span class="navbar-title">Policy Simulation Library Blog</span>
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+            <div id="quarto-search" class="" title="Search"></div>
+          <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarCollapse" aria-controls="navbarCollapse" aria-expanded="false" aria-label="Toggle navigation" onclick="if (window.quartoToggleHeadroom) { window.quartoToggleHeadroom(); }">
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+          <div class="collapse navbar-collapse" id="navbarCollapse">
+            <ul class="navbar-nav navbar-nav-scroll ms-auto">
+  <li class="nav-item">
+    <a class="nav-link" href="../about.html"> 
+<span class="menu-text">PSL Blog</span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://github.com/PSLmodels"> <i class="bi bi-github" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://twitter.com/PSLmodels"> <i class="bi bi-twitter" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+</ul>
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+<header id="title-block-header" class="quarto-title-block default page-columns page-full">
+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Tax-Brain</h1>
+                  <div>
+        <div class="description">
+          Computing the impact of US tax reform with the Tax-Brain web-app.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">individual-income-tax</div>
+                <div class="quarto-category">tax-brain</div>
+                <div class="quarto-category">us</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Anderson Frailey </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">December 23, 2020</p>
+      </div>
+    </div>
+    
+      
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+<hr>
+<p>For this PSL demo-day I showed how to use the <a href="https://www.compute.studio/PSLmodels/Tax-Brain/">Tax-Brain web-application</a>, hosted on <a href="http://compute.studio">Compute Studio</a>, to analyze proposed individual income tax policies. Tax-Brain integrates the <a href="https://pslmodels.github.io/Tax-Calculator/">Tax-Calculator</a> and <a href="https://github.com/PSLmodels/Behavioral-Responses#readme">Behavioral-Responses</a> models to make running both static and dynamic analyses of the US federal income and payroll taxes simple. The web interface for the model makes it possible for anyone to run their own analyses without writing a single line of code.</p>
+<p>We started the demo by simply walking through the interface and features of the web-app before creating our own sample reform to model. This reform, which to my knowledge does not reflect any proposals currently up for debate, included changes to the income and payroll tax rates, bringing back personal exemptions, modifying the standard deduction, and implementing a universal basic income.</p>
+<p>While the model ran, I explained how Tax-Brain validated all of the user inputs, the data behind the model, and how the final tax liability projections are determined. We concluded by looking through the variety of tables and graphs Tax-Brain produces and how they can easily be shared with others.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://compute.studio/PSLmodels/Tax-Brain/48969/">Simulation from the demonstration</a></li>
+<li><a href="https://github.com/PSLmodels/Tax-Brain">Tax-Brain GitHub repo</a></li>
+<li><a href="https://pslmodels.github.io/Tax-Calculator/#">Tax-Calculator documentation</a></li>
+<li><a href="https://pslmodels.github.io/Behavioral-Responses/index.html">Behavioral-Responses documentation</a></li>
+</ul>
+
+
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diff --git a/posts/2021-01-28-demo-day-how-to-use-og-usa.html b/posts/2021-01-28-demo-day-how-to-use-og-usa.html
new file mode 100644
index 0000000..88da324
--- /dev/null
+++ b/posts/2021-01-28-demo-day-how-to-use-og-usa.html
@@ -0,0 +1,630 @@
+<!DOCTYPE html>
+<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"><head>
+
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+
+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
+
+<meta name="author" content="Richard W. Evans">
+<meta name="dcterms.date" content="2021-01-28">
+<meta name="description" content="How to model the macroeconomic effects of tax reform with a web app.">
+
+<title>Policy Simulation Library Blog - Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy</title>
+<style>
+code{white-space: pre-wrap;}
+span.smallcaps{font-variant: small-caps;}
+div.columns{display: flex; gap: min(4vw, 1.5em);}
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+
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+      <div class="navbar-container container-fluid">
+      <div class="navbar-brand-container mx-auto">
+    <a class="navbar-brand" href="../index.html">
+    <span class="navbar-title">Policy Simulation Library Blog</span>
+    </a>
+  </div>
+            <div id="quarto-search" class="" title="Search"></div>
+          <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarCollapse" aria-controls="navbarCollapse" aria-expanded="false" aria-label="Toggle navigation" onclick="if (window.quartoToggleHeadroom) { window.quartoToggleHeadroom(); }">
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+</button>
+          <div class="collapse navbar-collapse" id="navbarCollapse">
+            <ul class="navbar-nav navbar-nav-scroll ms-auto">
+  <li class="nav-item">
+    <a class="nav-link" href="../about.html"> 
+<span class="menu-text">PSL Blog</span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://github.com/PSLmodels"> <i class="bi bi-github" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://twitter.com/PSLmodels"> <i class="bi bi-twitter" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+</ul>
+          </div> <!-- /navcollapse -->
+          <div class="quarto-navbar-tools">
+</div>
+      </div> <!-- /container-fluid -->
+    </nav>
+</header>
+<!-- content -->
+<header id="title-block-header" class="quarto-title-block default page-columns page-full">
+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy</h1>
+                  <div>
+        <div class="description">
+          How to model the macroeconomic effects of tax reform with a web app.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">OG-USA</div>
+                <div class="quarto-category">Tax-Calculator</div>
+                <div class="quarto-category">open-source</div>
+                <div class="quarto-category">policy-simulation-library</div>
+                <div class="quarto-category">compute-studio</div>
+                <div class="quarto-category">us</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Richard W. Evans </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">January 28, 2021</p>
+      </div>
+    </div>
+    
+      
+    </div>
+    
+  
+  </header><div id="quarto-content" class="quarto-container page-columns page-rows-contents page-layout-article page-navbar">
+<!-- sidebar -->
+<!-- margin-sidebar -->
+    
+<!-- main -->
+<main class="content quarto-banner-title-block" id="quarto-document-content">
+
+
+
+
+
+<p><img src="../images/OG-USA_logo_long.png" class="img-fluid"></p>
+<hr>
+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/EUS6QG6UjZY" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<hr>
+<p>In this PSL Demo Day, I demonstrate how to use the open source <a href="https://github.com/PSLmodels/OG-USA"><code>OG-USA</code></a> macroeconomic model of U.S. fiscal policy. <a href="https://www.jasondebacker.com/">Jason DeBacker</a> and I (<a href="https://sites.google.com/site/rickecon/">Richard Evans</a>) have been the core maintainers of this project and repository for the last six years. This demo is organized into the following sections. The <a href="https://youtu.be/EUS6QG6UjZY">YouTube webinar</a> linked above took place on January 11, 2021.</p>
+<ul>
+<li><a href="#brief-note-about-the-value-of-the-psl-community">Brief note about the value of the PSL community</a></li>
+<li><a href="#description-of-og-usa-model">Description of OG-USA model</a></li>
+<li><a href="#using-og-usa-on-compute-studio">Using OG-USA on Compute Studio</a></li>
+<li><a href="#resources">Resources</a></li>
+</ul>
+<section id="brief-note-about-the-value-of-the-psl-community" class="level2">
+<h2 class="anchored" data-anchor-id="brief-note-about-the-value-of-the-psl-community">Brief note about the value of the PSL community</h2>
+<p>The Policy Simulation Library is a decentralized organization of open source policy models. The <a href="https://github.com/PSLmodels">Policy Simulation Library GitHub organization</a> houses many open source repositories, each of which represents a curated policy project by a diverse group of maintainers. The projects that have met the highest standards of best practices and documentation are designated as <code>psl-cataloged</code> , while newer projects that are in earlier stages are designated as <code>psl-incubating</code> . The philosophy and goal of the PSL environment is to make policy modeling open and transparent. It also allows more collaboration and cross-project contributions and interactions.</p>
+<p>The Policy Simulation Library group has been holding these PSL Demo Day webinars since the end of 2020. The video of each webinar is available on the <a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">Policy Simulation Library YouTube channel</a>. These videos are a great resource for learning the different models available in the PSL community, how the models interact, how to contribute to them, and what is on the horizon in their development. Also excellent in many of the PSL Demo Day webinars is a demonstration of how to use the models on the <a href="https://about.compute.studio/">Compute Studio</a> web application platform.</p>
+<p>I have been a participant in and contributor to the PSL community since its inception. I love economic policy modeling. And I learned how sophisticated and complicated economic policy models can be. And any simulation can have hundreds of underlying assumptions, some of which may not be explicitly transparent. I think models that are used for public policy analysis have a philosophical imperative to be open source. This allows others to verify results and test sensitivity to assumptions.</p>
+<p>Another strong benefit of open source modeling is that it is fundamentally apolitical. With proprietary closed-source policy models, an outside observer might criticize the results of the model based on the perceived political biases of the modeler or the sponsoring organization. With open-source models, a critic can be redirected to the underlying assumptions, structure, and content of the model. This is constructive criticism and debate that moves the science foreward. In the current polarized political environment in the U.S., open-source modeling can provide a constructive route for bipartisan cooperation and the democratization of computational modeling. Furthermore, open-source modeling and workflow encourages the widest forms of collaboration and contributions.</p>
+</section>
+<section id="description-of-og-usa-model" class="level2">
+<h2 class="anchored" data-anchor-id="description-of-og-usa-model">Description of OG-USA model</h2>
+<p><a href="https://github.com/PSLmodels/OG-USA"><code>OG-USA</code></a> is an open-source overlapping generations, dynamic general equilibrium, heterogeneous agent, macroeconomic model of U.S. fiscal policy. The GitHub repository for the <code>OG-USA</code> source code is <a href="https://github.com/PSLmodels/OG-USA">github.com/PSLmodels/OG-USA</a>. This repository contains all the source code and instructions for loading and running <code>OG-USA</code> and all of its dependencies on your local machine. We will probably do another PSL Demo Day on how to run <code>OG-USA</code> locally. This Demo Day webinar is about running <code>OG-USA</code> on the <a href="https://compute.studio/PSLmodels/OG-USA/">Compute Studio web application</a>. See Section “<a href="#using-og-usa-on-compute-studio">Using OG-USA on Compute.Studio</a>” below.</p>
+<p>As a heterogeneous agent macroeconomic model, <code>OG-USA</code> allows for distributional analyses at the individual and firm level. That is, you can simulate the model and answer questions like, “How will an increase in the top three personal income tax rates affect people of different ages and income levels?” Microsimulation models can answer these types of distributional analysis questions as well. However, the difference between a macroeconomic model and a microsimulation model is that the macroeconomic models can simulate how each of those individuals and firms will respond to a policy change (e.g., lower labor supply or increased investment demand) and how those behavioral responses will add up and feed back into the macroeconomy (e.g., the effect on GDP, government revenue, government debt, interest rates, and wages).</p>
+<p><code>OG-USA</code> is a large-scale model and comprises tens of thousands of lines of code. The status of all of this code being publicly available on the internet with all collaboration and updates also public makes this an open source project. However, it is not enough to simply post one’s code. We have gone to great lengths to make in-line comments or “docstring” in the code to clarify the purpose of each function and line of code. For example, look in the <a href="https://github.com/PSLmodels/OG-USA/blob/master/ogusa/household.py"><code>OG-USA/ogusa/household.py</code></a> module. The first function on <a href="https://github.com/PSLmodels/OG-USA/blob/master/ogusa/household.py#L18">line 18</a> is the <code>marg_ut_cons()</code> function. As is described in its docstring, its purpose is to “Compute the marginal utility of consumption.”</p>
+<p>These in-code docstrings are not enough. We have also created textbook style OG-USA documentation at <a href="https://pslmodels.github.io/OG-USA/">pslmodels.github.io/OG-USA/</a> using the <a href="https://jupyterbook.org/">Jupyter Book</a> medium. This form of documentation has the advantage of being in book form and available online. It allows us to update the documentation in the open-source repository so changes and versions can be tracked. It describes the <a href="https://pslmodels.github.io/OG-USA/content/api/public_api.html"><code>OG-USA</code> API</a>, <a href="https://pslmodels.github.io/OG-USA/content/theory/intro.html"><code>OG-USA</code> theory</a>, and <a href="https://pslmodels.github.io/OG-USA/content/calibration/exogenous_parameters.html">`OG-USA calibration</a>. As with the model, this documentation is always a work in progress. But being open-source allows outside contributors to help with its updated and error checking.</p>
+<p>One particular strength of the <code>OG-USA</code> model I want to highlight is its interaction with microsimulation models to incorporate information about tax incentives faced by the heterogeneous households in the model. We have interfaced <code>OG-USA</code> with microsimulation models in India and in the European Commission. <code>OG-USA</code> ’s default for modeling the United States is to use the open-source <code>Tax-Calculator</code> microsimulation model, which was described by Anderson Frailey in the <a href="http://blog.pslmodels.org/demo-day-4-taxbrain">last Demo Day of 2020</a>. However, DeBacker and I currently have a project in which we use <code>OG-USA</code> to simulate policies using the Tax Policy Center’s microsimulation model. The way <code>OG-USA</code> interfaces with microsimulation models to incorporate rich tax data is described in the documentation in the calibration chapter entitled, “<a href="https://pslmodels.github.io/OG-USA/content/calibration/tax_functions.html">Tax Functions</a>”.</p>
+</section>
+<section id="using-og-usa-on-compute-studio" class="level2">
+<h2 class="anchored" data-anchor-id="using-og-usa-on-compute-studio">Using OG-USA on Compute Studio</h2>
+<p>In the demonstration, I focus on how to run experiments and simulations with <code>OG-USA</code> using the <a href="https://compute.studio/PSLmodels/OG-USA/">Compute Studio</a> web application platform rather than installing running the model on your local machine. To use <code>OG-USA</code> on this web application, you will need a <a href="https://compute.studio/users/signup/">Compute Studio account</a>. Once you have an account, you can start running any model available through the site. For some models, you will have to pay for the compute time, although the cost of running these models is very modest. However, all Compute Studio simulations of the <code>OG-USA</code> model are currently sponsored by the <a href="https://www.oselab.org/">Open Source Economics Laboratory</a>. This subsidy will probably run out in the next year. But we are always looking for funding for these models.</p>
+<p>Once you are signed up and logged in to your Compute Studio account, you can go to the <code>OG-USA</code> model on Compute Studio at <a href="https://compute.studio/PSLmodels/OG-USA/">compute.studio/PSLmodels/OG-USA</a>. The experiment that we simulated in the demonstration is available at <a href="https://compute.studio/PSLmodels/OG-USA/206/">compute.studio/PSLmodels/OG-USA/206</a>. The description at the top of the simulation page describes the changes we made. You can look through the input page by clicking on the “Inputs” tab. We ran the model by clicking the green “Run” button at the lower left of the page. The model took about 5 hours to run, so I pre-computed the results that we discussed in the demo. The outputs of the experiment are available in the “Outputs” tab on the page. I also demonstrated how one can click the “Download Results” button at the bottom of the “Outputs” tab to download more results from the simulation. However, the full set of results is only available by installing and running the <code>OG-USA</code> model simulation on your local machine.</p>
+<p>The benefits of the Compute Studio web application are that running the <code>OG-USA</code> model is much easier for the non-expert, and the multiple-hour computation time can be completed on a remote machine in the cloud.</p>
+</section>
+<section id="resources" class="level2">
+<h2 class="anchored" data-anchor-id="resources">Resources</h2>
+<ul>
+<li><a href="https://youtu.be/EUS6QG6UjZY">PSL Demo Day YouTube webinar: “How to use <code>OG-USA</code>”</a></li>
+<li><a href="https://compute.studio/PSLmodels/OG-USA/"><code>OG-USA</code> on Compute Studio</a></li>
+<li><a href="https://compute.studio/PSLmodels/OG-USA/206/">Simulation from the demonstration</a></li>
+<li><a href="https://github.com/PSLmodels/OG-USA"><code>OG-USA</code> GitHub repo</a></li>
+<li><a href="https://pslmodels.github.io/OG-USA/"><code>OG-USA</code> documentation</a></li>
+<li><a href="https://github.com/PSLmodels/Tax-Calculator"><code>Tax-Calculator</code> GitHub repo</a></li>
+</ul>
+
+
+</section>
+
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+<meta name="author" content="Max Ghenis">
+<meta name="dcterms.date" content="2021-01-29">
+<meta name="description" content="Analyzing US wealth data in a web-based Python notebook.">
+
+<title>Policy Simulation Library Blog - Demo Day: Running the scf and microdf Python packages in Google Colab</title>
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+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Running the scf and microdf Python packages in Google Colab</h1>
+                  <div>
+        <div class="description">
+          Analyzing US wealth data in a web-based Python notebook.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">microdf</div>
+                <div class="quarto-category">scf</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Max Ghenis </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">January 29, 2021</p>
+      </div>
+    </div>
+    
+      
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+<hr>
+<p>For Monday’s PSL Demo Day, I showed how to use the <code>scf</code> and <code>microdf</code> PSL Python packages from the <a href="http://colab.research.google.com">Google Colab</a> web-based Jupyter notebook interface.</p>
+<p>The <code>scf</code> package extracts data from the Federal Reserve’s Survey of Consumer Finances, the canonical source of US wealth microdata. <code>scf</code> has a single function: <code>load(years, columns)</code> , which then returns a <code>pandas</code> <code>DataFrame</code> with the specified column(s), each record’s survey weight, and the year (when multiple years are requested).</p>
+<p>The <code>microdf</code> package analyzes survey microdata, such as that returned by the <code>scf.load</code> function. It offers a consistent paradigm for calculating statistics like means, medians, sums, and inequality statistics like the Gini index. Most functions are structured as follows: <code>f(df, col, w, groupby)</code> where <code>df</code> is a <code>pandas</code> <code>DataFrame</code> of survey microdata, <code>col</code> is a column(s) name to be summarized, <code>w</code> is the weight column, and <code>groupby</code> is the column(s) to group records in before summarizing.</p>
+<p>Using Google Colab, I showed how to use these packages to quickly calculate mean, median, and total wealth from the SCF data, without having to install any software or leave the browser. I also demonstrated how to use the <code>groupby</code> argument of <code>microdf</code> functions to show how different measures of wealth inequality have changed over time. Finally, I previewed some of what’s to come with <code>scf</code> and <code>microdf</code> : imputations, extrapolations, inflation, visualization, and documentation, to name a few priorities.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://docs.google.com/presentation/d/1bXWD_8wjbvG4J-Tq8PvlP7xK7Kz2X0oVpsOnjFZ_6zY">Slides</a></li>
+<li><a href="https://colab.research.google.com/drive/1WLOYxAtC347g2tIyO_iJJQUAZmwL4raB?usp=sharing">Demo notebook in Google Colab</a></li>
+<li><a href="https://compute.studio/PSLmodels/Tax-Brain/48969/">Simulation from the demonstration</a></li>
+<li><a href="https://github.com/PSLmodels/scf"><code>scf</code> GitHub repo</a></li>
+<li><a href="https://github.com/PSLmodels/microdf"><code>microdf</code> GitHub repo</a></li>
+<li><a href="https://pslmodels.github.io/microdf"><code>microdf</code> documentation</a></li>
+</ul>
+
+
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diff --git a/posts/2021-03-02-demo-day-contributing-psl.html b/posts/2021-03-02-demo-day-contributing-psl.html
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+++ b/posts/2021-03-02-demo-day-contributing-psl.html
@@ -0,0 +1,602 @@
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+<meta name="dcterms.date" content="2021-03-02">
+<meta name="description" content="How to help software projects in the Policy Simulation Library.">
+
+<title>Policy Simulation Library Blog - Demo Day: Contributing to PSL projects</title>
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+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Contributing to PSL projects</h1>
+                  <div>
+        <div class="description">
+          How to help software projects in the Policy Simulation Library.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">PSL</div>
+                <div class="quarto-category">git</div>
+                <div class="quarto-category">github</div>
+              </div>
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+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">March 2, 2021</p>
+      </div>
+    </div>
+    
+      
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+<hr>
+<p>In the most recent PSL Demo Day, I illustrate how to contribute to PSL projects. The open source nature of projects in the PSL catalog allows anyone to contribute. The modularity of the code, coupled with robust testing, means that one can bite off small pieces that help improve the models and remain confident those changes work as expected.</p>
+<p>To begin the process of finding where to contribute to PSL projects, I advise looking through the <a href="https://github.com/PSLmodels">PSL GitHub Organization</a> to see what projects interest you. Once a project of interest is identified, looking over the open “Issues” can provide a sense of where model maintainers and users are looking for help (see especially the “Help Wanted” tags). It is also completely appropriate to create a new Issue to express interest in helping and ask for direction on where that might best be done given your experience and preferences.</p>
+<p>When you are ready to begin to contribute to a project, you’ll want to fork and clone the GitHub repository to help you get the files on your local machine and ready for you to work with. Many PSL projects outline the detailed steps to get you up and running. For example, see the <a href="https://pslmodels.github.io/Tax-Calculator/contributing/contributor_guide.html">Tax-Calculator Contributor Guide</a>, which outlines the step-by-step process for doing this and confirming that everything works as expected on your computer.</p>
+<p>After you are set up and ready to begin modifying source code for the PSL project(s) you’re interested in contributing to, you can reference the PSL-incubating <a href="https://pslmodels.github.io/Git-Tutorial/content/intro.html">Git-Tutorial project</a> that provides more details on the Git workflow followed by most PSL projects.</p>
+<p>As you contribute, you may want to get more involved in the community. A couple ways to do this are to join any of the <a href="https://pslmodels.org/events.html">PSL community events</a>, all of which are open to the public, and to post to the <a href="http://discourse.pslmodels.org">PSL Discourse Forums</a>. These are great places to meet community members and ask questions about how and where to best contribute.</p>
+<p>I hope this helps you get started as a PSL contributor – we look forward to getting you involved in making policy analysis better and more transparent!</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://pslmodels.github.io/Git-Tutorial/content/intro.html">PSL Git-Tutorial</a></li>
+<li><a href="https://pslmodels.org/events.html">PSL community events</a></li>
+<li><a href="http://discourse.pslmodels.org">PSL Discourse Forums</a></li>
+<li><a href="https://pslmodels.github.io/Tax-Calculator/contributing/contributor_guide.html">Tax-Calculator Contributor Guide</a></li>
+<li><a href="https://github.com/PSLmodels">PSL GitHub Organization</a></li>
+</ul>
+
+
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+</div> <!-- /content -->
+
+
+
+
+</body></html>
\ No newline at end of file
diff --git a/posts/2021-03-02-demo-day-taxbrain-to-taxcruncher.html b/posts/2021-03-02-demo-day-taxbrain-to-taxcruncher.html
new file mode 100644
index 0000000..ca2dd4f
--- /dev/null
+++ b/posts/2021-03-02-demo-day-taxbrain-to-taxcruncher.html
@@ -0,0 +1,592 @@
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+
+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
+
+<meta name="author" content="Matt Jensen">
+<meta name="dcterms.date" content="2021-03-02">
+<meta name="description" content="How to move reforms between a tax-unit-level and society-wide model with the Compute.Studio API.">
+
+<title>Policy Simulation Library Blog - Demo Day: Moving policy reform files from Tax-Brain to Tax-Cruncher</title>
+<style>
+code{white-space: pre-wrap;}
+span.smallcaps{font-variant: small-caps;}
+div.columns{display: flex; gap: min(4vw, 1.5em);}
+div.column{flex: auto; overflow-x: auto;}
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+<link href="../site_libs/bootstrap/bootstrap-icons.css" rel="stylesheet">
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+</head>
+
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+
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+  <header id="quarto-header" class="headroom fixed-top quarto-banner">
+    <nav class="navbar navbar-expand-lg " data-bs-theme="dark">
+      <div class="navbar-container container-fluid">
+      <div class="navbar-brand-container mx-auto">
+    <a class="navbar-brand" href="../index.html">
+    <span class="navbar-title">Policy Simulation Library Blog</span>
+    </a>
+  </div>
+            <div id="quarto-search" class="" title="Search"></div>
+          <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarCollapse" aria-controls="navbarCollapse" aria-expanded="false" aria-label="Toggle navigation" onclick="if (window.quartoToggleHeadroom) { window.quartoToggleHeadroom(); }">
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+</button>
+          <div class="collapse navbar-collapse" id="navbarCollapse">
+            <ul class="navbar-nav navbar-nav-scroll ms-auto">
+  <li class="nav-item">
+    <a class="nav-link" href="../about.html"> 
+<span class="menu-text">PSL Blog</span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://github.com/PSLmodels"> <i class="bi bi-github" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://twitter.com/PSLmodels"> <i class="bi bi-twitter" role="img">
+</i> 
+<span class="menu-text"></span></a>
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+</ul>
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+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Moving policy reform files from Tax-Brain to Tax-Cruncher</h1>
+                  <div>
+        <div class="description">
+          How to move reforms between a tax-unit-level and society-wide model with the Compute.Studio API.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Matt Jensen </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">March 2, 2021</p>
+      </div>
+    </div>
+    
+      
+    </div>
+    
+  
+  </header><div id="quarto-content" class="quarto-container page-columns page-rows-contents page-layout-article page-navbar">
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+        
+    </div>
+<!-- main -->
+<main class="content quarto-banner-title-block" id="quarto-document-content">
+
+
+
+
+
+<p>Check out the video:</p>
+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/0E_GawHQres" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<hr>
+<p>Show notes:</p>
+<p>I demonstrate how to move a policy reform file from Tax-Brain to Tax-Cruncher using the Compute.Studio API. See the Demo C/S simulation linked below for text instructions that accompany the video.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://compute.studio/PSLmodels/Tax-Brain/49779/">Demo C/S simulation with instructions</a></li>
+</ul>
+
+
+
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+</div> <!-- /content -->
+
+
+
+
+</body></html>
\ No newline at end of file
diff --git a/posts/2021-03-08-demo-day-cs-api-stitch.html b/posts/2021-03-08-demo-day-cs-api-stitch.html
new file mode 100644
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+<!DOCTYPE html>
+<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"><head>
+
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+<meta name="generator" content="quarto-1.4.551">
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+<meta name="author" content="Hank Doupe">
+<meta name="dcterms.date" content="2021-03-08">
+<meta name="description" content="Creating an app with the Compute Studio API.">
+
+<title>Policy Simulation Library Blog - Demo Day: Stitching together apps on Compute Studio</title>
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+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Stitching together apps on Compute Studio</h1>
+                  <div>
+        <div class="description">
+          Creating an app with the Compute Studio API.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">PSL</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Hank Doupe </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">March 8, 2021</p>
+      </div>
+    </div>
+    
+      
+    </div>
+    
+  
+  </header><div id="quarto-content" class="quarto-container page-columns page-rows-contents page-layout-article page-navbar">
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+
+
+
+
+
+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/5I59dyB_2ws" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<hr>
+<p>In Demo Day 8, I talked about connecting multiple apps on <a href="https://compute.studio">Compute Studio</a> with <a href="https://stitch.hankdoupe.com">PSL Stitch</a>. The source code for PSL stitch can be found in this <a href="https://github.com/hdoupe/psl-stitch">repository</a>.</p>
+<p>Stitch is composed of three components:</p>
+<ul>
+<li>A <a href="https://github.com/hdoupe/psl-stitch/tree/main/psl_stitch">python package</a> that can be run like a normal Python package.</li>
+<li>A <a href="https://github.com/hdoupe/psl-stitch/tree/main/api">RESTful API</a> built with <a href="https://fastapi.tiangolo.com">FastAPI</a> that is called remotely to create simulations on Compute Studio.</li>
+<li>A <a href="https://github.com/hdoupe/psl-stitch/tree/main/psl-stitch-app">GUI</a> built with <a href="https://reactjs.org/">ReactJS</a> that makes calls to the REST API to create and monitor simulations.</li>
+</ul>
+<p>One of the cool things about this app is that it uses <a href="https://paramtools.dev">ParamTools</a> to read the JSON files under the hood. This means that it can read links to data in other Compute Studio runs, files on GitHub, or just plain JSON. Here are some example parameters:</p>
+<ul>
+<li>policy parameters: <code>cs://PSLmodels:Tax-Brain@49779/inputs/adjustment/policy</code></li>
+<li>tax-cruncher parameters: <code>{"sage": [{"value": 25}]}</code></li>
+<li>business tax parameters: <code>{"CIT_rate": [{"value": 0.25, "year": 2021}]}</code></li>
+</ul>
+<p>After clicking run, three simulations will be created on Compute Studio and the app will update as soon as the simulations have finished:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="https://user-images.githubusercontent.com/9206065/112211937-ca75db00-8bf2-11eb-856f-41c46e7e8ec5.png" class="img-fluid figure-img"></p>
+<figcaption>Getting started</figcaption>
+</figure>
+</div>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="https://user-images.githubusercontent.com/9206065/112211931-c9dd4480-8bf2-11eb-83d8-678fd6d80dd9.png" class="img-fluid figure-img"></p>
+<figcaption>CS Simulations</figcaption>
+</figure>
+</div>
+<p>Once they are done, the simulations are best viewed and interacted with on Compute Studio, but you can still inspect the JSON response from the Compute Studio API:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="https://user-images.githubusercontent.com/9206065/112211930-c944ae00-8bf2-11eb-87dc-949ff3007229.png" class="img-fluid figure-img"></p>
+<figcaption>Simulation Complete</figcaption>
+</figure>
+</div>
+<p>I created this app to show that it’s possible to build apps on top of the Compute Studio API. I think PSL Stitch is a neat example of how to do this, but I am even more excited to see what others build next.</p>
+<p>Also, this is an open source project and has lots of room for improvement. If you are interested in learning web technologies related to REST APIs and frontend development with JavaScript, then this project could be a good place to start!</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://stitch.hankdoupe.com">PSL Stitch</a></li>
+<li><a href="https://github.com/hdoupe/psl-stitch">Source code</a></li>
+<li><a href="https://docs.compute.studio/api/guide.html">Compute Studio API Docs</a></li>
+</ul>
+
+
+
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+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Producing stacked revenue estimates with the Tax-Calculator Python API</h1>
+                  <div>
+        <div class="description">
+          How to evaluate the cumulative effects of a multi-part tax reform.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">individual-income-tax</div>
+                <div class="quarto-category">tax-brain</div>
+                <div class="quarto-category">tax-calculator</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">April 5, 2021</p>
+      </div>
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+<hr>
+<p>It’s often useful to be able to identify the effects of specific provisions individually and not just the overall impact of a proposal with many provisions. Indeed, when revenue estimates of tax law changes are reported (such as <a href="https://www.jct.gov/publications/2021/jcx-14-21/">this JCT analysis</a> of the American Rescue Plan Act of 2021), they are typically reported on a provision-by-provision basis. Finding the provision-by-provision revenue estimates is cumbersome with the <a href="https://compute.studio/PSLmodels/Tax-Brain/">Tax-Brain web application</a> both because it’s hard to iterate over many provisions and because the order matters when stacking estimates, so that one needs to keep this order in mind as parameter values are updated for each additional provision in a full proposal.</p>
+<p>In the PSL Demo Day on April 5, 2021, I show how to use the Python API of Tax-Calculator to efficiently produce stacked revenue estimates. In fact, after some initial setup, this can be done with just 12 lines of code (plus a few more to make the output look nice). The Google Colab notebook that illustrates this approach can be found <a href="https://colab.research.google.com/drive/1P-m61lWbPpb_ih42vQKrD2zi9Bpe16BM?usp=sharing">at this link</a>, but here I’ll walk through the four steps that are involved:</p>
+<ol type="1">
+<li><em>Divide up the full proposal into strings of JSON text that contain each provision you want to analyze</em>. My example breaks up the <a href="https://github.com/PSLmodels/examples/blob/main/psl_examples/taxcalc/Biden2020.json">Biden 2020 campaign proposal</a> into seven provisions, but this is illustrative and you can make more or less provisions depending on the detail you would like to see.</li>
+<li><em>Create a dictionary that contains, as its values, the JSON strings</em>. A couple notes on this. First, the dictionary keys should be descriptive of the provisions as they will become the labels for each provision in the final table of revenue estimates we produce. Second, order matters here. You’ll want to be sure the current law baseline is first (the value for this will be an empty dictionary). Then you specify the provisions. The order you specify will likely affect your revenue estimates from a given provision (for instance, expanding/restricting a deduction has a larger revenue effect when rates are higher), but there are not hard and fast rules on the “right” order. Traditionally, rate changes are stacked first and tax expenditures later in the order.</li>
+<li><em>Iterate over this dictionary</em>. With a dictionary of provisions in hand, we can write a “for loop” to iterate over the provision, simulating the Tax-Calculator model at each step. Note that when the <code>Policy</code> class object in Tax-Calculator is modified, it only needs to be told the changes in tax law parameters relative to its current state. In other words, when we are stacking provisions, estimating the incremental effect of each, you can think of the <code>Policy</code> object having a baseline policy that is represented by the current law baseline plus all provisions that have been analyzed before the provision at the current iteration. The <code>Policy</code> class was created in this way so that one can easily represent policy changes, requiring the user to only input the set of parameters that are modified, not every single parameter’s value under the hypothetical policy. But this also makes it parsimonious to stack provisions as we are doing here. Notice that the JSON strings for each provision (created in Step 1) can be specified independent of the stacking order. We only needed to slice the full set of proposals into discrete chunks, we didn’t need to worry about creating specifications of cumulative policy changes.</li>
+<li><em>Format output for presentation</em>. After we’ve run a Tax-Calculator simulation for the current law baseline plus each provision (and each year in the budget window), we’ve got all the output we need. With this output, we can quickly create a table that will nicely present our stacked revenue estimate. One good check to do here is to create totals across all provisions and compare this to the simulated revenue effects of running the full set of proposals in one go. This check helps to ensure that you didn’t make an error in specifying your JSON strings. For example, it’s easy to leave out one or more provisions, especially if there are many.</li>
+</ol>
+<p>I hope this provides a helpful template for your own analysis. Note that one can modify this code in several useful ways. For example, within the for-loops, the <a href="https://github.com/PSLmodels/Behavioral-Responses">Behavioral-Responses</a> can be called to produce revenue estimates that take into account behavioral feedback. Or one could store the individual income tax and payroll tax revenue impacts separately (rather than return the combined values as in the example notebook). Additional outputs (even the full set of microdata after each provision is applied) can be stored for even more analysis.</p>
+<p>In the future, look for <a href="https://github.com/PSLmodels/Tax-Brain">Tax-Brain</a> to add stacked revenue estimates to its capabilities. It’ll still be important for users to carve up their full list of policy changes into sets of provisions as we did in Steps 1 and 2 above, but Tax-Brain will then take care of the rest behind the scenes.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://colab.research.google.com/drive/1P-m61lWbPpb_ih42vQKrD2zi9Bpe16BM?usp=sharing">Colab Notebook with example</a></li>
+<li><a href="https://github.com/PSLmodels/examples/blob/main/psl_examples/taxcalc/Biden2020.json">Biden campaign reform file in PSL Examples</a></li>
+</ul>
+
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+</div> <!-- /content -->
+
+
+
+
+</body></html>
\ No newline at end of file
diff --git a/posts/2021-05-17-demo-day-jupyter-book-deploy.html b/posts/2021-05-17-demo-day-jupyter-book-deploy.html
new file mode 100644
index 0000000..a84f7c0
--- /dev/null
+++ b/posts/2021-05-17-demo-day-jupyter-book-deploy.html
@@ -0,0 +1,634 @@
+<!DOCTYPE html>
+<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"><head>
+
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+
+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
+
+<meta name="author" content="Jason DeBacker">
+<meta name="dcterms.date" content="2021-05-17">
+<meta name="description" content="How to keep interactive programmatic notebook-based documentation up-to-date in your pull request workflow.">
+
+<title>Policy Simulation Library Blog - Demo Day: Updating Jupyter Book documentation with GitHub Actions</title>
+<style>
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+<script id="quarto-search-options" type="application/json">{
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+    "search-detached-cancel-button-title": "Cancel",
+    "search-submit-button-title": "Submit",
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+}</script>
+
+
+<link rel="stylesheet" href="../styles.css">
+</head>
+
+<body class="nav-fixed">
+
+<div id="quarto-search-results"></div>
+  <header id="quarto-header" class="headroom fixed-top quarto-banner">
+    <nav class="navbar navbar-expand-lg " data-bs-theme="dark">
+      <div class="navbar-container container-fluid">
+      <div class="navbar-brand-container mx-auto">
+    <a class="navbar-brand" href="../index.html">
+    <span class="navbar-title">Policy Simulation Library Blog</span>
+    </a>
+  </div>
+            <div id="quarto-search" class="" title="Search"></div>
+          <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarCollapse" aria-controls="navbarCollapse" aria-expanded="false" aria-label="Toggle navigation" onclick="if (window.quartoToggleHeadroom) { window.quartoToggleHeadroom(); }">
+  <span class="navbar-toggler-icon"></span>
+</button>
+          <div class="collapse navbar-collapse" id="navbarCollapse">
+            <ul class="navbar-nav navbar-nav-scroll ms-auto">
+  <li class="nav-item">
+    <a class="nav-link" href="../about.html"> 
+<span class="menu-text">PSL Blog</span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://github.com/PSLmodels"> <i class="bi bi-github" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://twitter.com/PSLmodels"> <i class="bi bi-twitter" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+</ul>
+          </div> <!-- /navcollapse -->
+          <div class="quarto-navbar-tools">
+</div>
+      </div> <!-- /container-fluid -->
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+</header>
+<!-- content -->
+<header id="title-block-header" class="quarto-title-block default page-columns page-full">
+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Updating Jupyter Book documentation with GitHub Actions</h1>
+                  <div>
+        <div class="description">
+          How to keep interactive programmatic notebook-based documentation up-to-date in your pull request workflow.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">jupyter-book</div>
+                <div class="quarto-category">GH-actions</div>
+                <div class="quarto-category">documentation</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">May 17, 2021</p>
+      </div>
+    </div>
+    
+      
+    </div>
+    
+  
+  </header><div id="quarto-content" class="quarto-container page-columns page-rows-contents page-layout-article page-navbar">
+<!-- sidebar -->
+<!-- margin-sidebar -->
+    <div id="quarto-margin-sidebar" class="sidebar margin-sidebar">
+        
+    </div>
+<!-- main -->
+<main class="content quarto-banner-title-block" id="quarto-document-content">
+
+
+
+
+
+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/rEG5vGMkDsg" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<hr>
+<p>Open source projects must maintain clear and up-to-date documentation in order to attract users and contributors. Because of this, PSL sets minimum standards for documentation among cataloged projects in its <a href="https://pslmodels.org/Catalog/library_criteria.html">model criteria</a>. A recent innovation in executable books, <a href="https://jupyterbook.org/intro.html">Jupyter Book</a>, has provided an excellent format for model documentation and has been widely adopted by PSL projects (see for example <a href="https://pslmodels.github.io/OG-USA/content/intro/intro.html">OG-USA</a>, <a href="http://taxbrain.pslmodels.org/content/intro.html">Tax-Brain</a>, <a href="https://taxcalc.pslmodels.org">Tax-Calculator</a>).</p>
+<p>Jupyter Book allows one to write documents with executable code and text together, as in Jupyter notebooks. But Jupyter Book pushes this further by allowing documents with multiple sections, better integration of TeX for symbols and equations, BibTex style references and citations, links between sections, and <a href="https://www.sphinx-doc.org/en/master/">Sphinx</a> integration (for auto-built documentation of model APIs from source code). Importantly for sharing documentation, Jupyter Books can easily be compiled to HTML, PDF, or other formats. Portions of a Jupyter Book that contain executable code can be downloaded as Jupyter Notebooks or opened in <a href="https://research.google.com/colaboratory/">Google Colab</a> or <a href="https://mybinder.org">binder</a></p>
+<p>The <a href="https://jupyterbook.org/intro.html">Jupyter Book</a> documentation is excellent and will help you get started creating your “book” (tip: pay close attention to formatting details, including proper whitespace). What I do here is outline how you can easily deploy your documentation to the web and keep it up-to-date with your project.</p>
+<p>I start from the assumption that you have the source files to build your Jupyter Book checked into the main branch of your project (these maybe <code>yml</code> , <code>md</code> , <code>rst</code> , <code>ipynb</code> or other files). For version control purposes and to keep your repo trim, you generally don’t want to check the built documentation files to this branch (tip: consider adding the folder these files will go to (e.g., <code>/_build</code> to your <code>.gitignore</code> ). When these files are in place and you can successfully build your book locally, it’s time for the first step.</p>
+<p><em>Step 1</em>: Add two GH Actions to your project’s workflow: 1. An action to check that your documentation files build without an error. I like to run this on each push to a PR. The action won’t hang on warnings, but will fail if your Jupyter Book doesn’t build at all. An example of this action from the OG-USA repo is <a href="https://github.com/PSLmodels/OG-USA/blob/master/.github/workflows/docs_check.yml">here</a>:</p>
+<pre><code>
+name: Check that docs build
+on: [push, pull_request]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2 # If you're using actions/checkout@v2 you must set persist-credentials to false in most cases for the deployment to work correctly.
+        with:
+          persist-credentials: false
+
+      - name: Setup Miniconda
+        uses: conda-incubator/setup-miniconda@v2
+        with:
+          activate-environment: ogusa-dev
+          environment-file: environment.yml
+          python-version: 3.7
+          auto-activate-base: false
+
+      - name: Build # Build Jupyter Book
+        shell: bash -l {0}
+        run: |
+          pip install jupyter-book
+          pip install sphinxcontrib-bibtex==1.0.0
+          pip install -e .
+          cd docs
+          jb build ./book</code></pre>
+<p>To use this in your repo, you’ll just need to change a few settings such as the name of the environment and perhaps the Python version and path to the book source files. Note that in the above <code>yml</code> file <code>sphinxcontrib-bibtex</code> is pinned. You maybe able to unpin this, but OG-USA needed this pin for documentation to compile property due to changes in the <code>jupyter-book</code> and <code>sphinxcontrib-bibtex</code> packages.</p>
+<ol start="2" type="1">
+<li>An action that builds and deploys the Jupyter Book to <a href="https://pages.github.com">GH Pages</a>. The OG-USA project uses the <a href="https://github.com/JamesIves/github-pages-deploy-action">deploy action from James Ives</a> in <a href="https://github.com/PSLmodels/OG-USA/blob/master/.github/workflows/deploy_docs.yml">this action</a>. This is something that you will want to run when PRs are merged into your main branch so that the documentation is kept up-to-date with the project. To modify this action for your repo, you’ll need to change the repo name, the environment name, and potentially the Python version, branch name, and path to the book source files.</li>
+</ol>
+<p><em>Step 2</em>: Once the action in (2) above is run, your compiled Jupyter Book docs will be pushed to a <code>gh-pages</code> branch in your repository (the action will create this branch for you if it doesn’t already exist). At this point, you should be able to see your docs at the url <code>https://GH_org_name.github.io/Repo_name</code> . But it probably won’t look very good until you complete this next step. To have your Jupyter Book render on the web as you see it on your machine, you will want to push and merge an empty file with the name <code>.nojekyll</code> into your repo’s <code>gh-pages</code> branch.</p>
+<p>That’s it! With these actions, you’ll be sure that your book continues to compile and a new version will be published to the web with with each merge to your main branch, ensuring that your documentation stays up-to-date.</p>
+<p>Some additional tips:</p>
+<ul>
+<li>Use <a href="https://www.sphinx-doc.org/en/master/">Sphinx</a> to document your projects API. By doing so you’ll automate an important part of your project’s documentation – as long as the docstrings are updated when the source code is, the Jupyter Book you are publishing to the web will be kept in sync with no additional work needed.</li>
+<li>You can have your <code>gh-pages</code>-hosted documentation point to a custom URL.</li>
+<li>Project maintainers should ensure that docs are updated with PRs that are relevant (e.g., if the PR changes an the source code affecting a user interface, then documentation showing example usage should be updated) and help contributors make the necessary changes to the documentation source files.</li>
+</ul>
+
+
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diff --git a/posts/2021-06-14-demo-day-tax-brain-python-api.html b/posts/2021-06-14-demo-day-tax-brain-python-api.html
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+++ b/posts/2021-06-14-demo-day-tax-brain-python-api.html
@@ -0,0 +1,646 @@
+<!DOCTYPE html>
+<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"><head>
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+<meta name="dcterms.date" content="2021-06-14">
+<meta name="description" content="A programmatic interface to compute the impact of tax reform.">
+
+<title>Policy Simulation Library Blog - Demo Day: Using the TaxBrain Python API</title>
+<style>
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+<header id="title-block-header" class="quarto-title-block default page-columns page-full">
+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Using the TaxBrain Python API</h1>
+                  <div>
+        <div class="description">
+          A programmatic interface to compute the impact of tax reform.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">individual-income-tax</div>
+                <div class="quarto-category">tax-brain</div>
+                <div class="quarto-category">tax-calculator</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Anderson Frailey </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">June 14, 2021</p>
+      </div>
+    </div>
+    
+      
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+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/HXN2TrOvXn0" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<hr>
+<p>The TaxBrain project was primarily created to serve as the backend of the <a href="https://www.compute.studio/PSLmodels/Tax-Brain/">Tax-Brain web-application</a>. But at its core, TaxBrain is a Python package that greatly simplifies tax policy analysis. For this PSL Demo-Day, I demonstrated TaxBrain’s capabilities as a standalone package, and how to use it to produce high-level summaries of the revenue impacts of proposed tax policies. The Jupyter Notebook from the presentation can be found <a href="https://gist.github.com/andersonfrailey/bb8ac6db609bf0146ef23d1d35d32334">here</a>.</p>
+<p>TaxBrain’s Python API allows you to run a full analysis of income tax policies in just three lines of code:</p>
+<div class="sourceCode" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> taxbrain <span class="im">import</span> TaxBrain</span>
+<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a>tb <span class="op">=</span> TaxBrain(START_YEAR, END_YEAR, use_cps<span class="op">=</span><span class="va">True</span>, reform<span class="op">=</span>REFORM_POLICY)</span>
+<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a>tb.run()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>Where <code>START_YEAR</code> and <code>END_YEAR</code> are the first and last years, respectively, of the analysis; <code>use_cps</code> is a boolean indicator that you want to use the CPS-based microdata file prepared for use with Tax-Calculator; and <code>REFORM_POLICY</code> is either a JSON file or Python dictionary that specifies a reform suitable for Tax-Calculator. The forthcoming release of TaxBrain will also include a feature that allows you to perform a stacked revenue analysis as well. The inspiration for this feature was presented by Jason DeBacker in a <a href="http://blog.pslmodels.org/demo-day-11-stacked-revenue-estimates">previous demo-day</a>.</p>
+<p>Once TaxBrain has been run, there are a number of methods and functions included in the package to create tables and plots to summarize the results. I used the <a href="https://github.com/PSLmodels/examples/blob/main/psl_examples/taxcalc/Biden2020.json">Biden 2020 campaign proposal</a> in the demo and the resulting figures are below. The first is a “volcano plot” that makes it easy to see the magnitude of the change in tax liability individuals across the income distribution face. Each dot represents a tax unit, and the x and y variables can be customized based on the user’s needs.</p>
+<p><img src="../images/biden_volcano.png" class="img-fluid"></p>
+<p>The second gives a higher-level look at how taxes change in each income bin. It breaks down what percentage of each income bin faces a tax increase or decrease, and the size of that change.</p>
+<p><img src="../images/biden_dist_fig.png" class="img-fluid"></p>
+<p>The final plot shown in the demo simply shows tax liabilities by year over the budget window.</p>
+<p><img src="../images/biden_revenue.png" class="img-fluid"></p>
+<p>The last feature I showed was TaxBrain’s automated reports. TaxBrain uses saved results and an included report template to write a report summarizing the findings of your simulation. The reports include tables and figures similar to what you may find in similar write ups by the Joint Committee on Taxation or Tax Policy Center including a summary of significant changes caused by the reform, and all you need is one line of code:</p>
+<div class="sourceCode" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>report(tb, name<span class="op">=</span><span class="st">'Biden Proposal'</span>, outdir<span class="op">=</span><span class="st">'biden'</span>, author<span class="op">=</span><span class="st">'Anderson Frailey'</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>The above code will save a PDF copy of the report in a directory called <code>biden</code> along with PNG files for each of the graphs created and the raw Markdown text used for the report, which you can then edit as needed if you would like to add content to the report that is not already included. Screenshots of the default report are included below.</p>
+<p><img src="../images/tb_report1.png" class="img-fluid"> <img src="../images/tb_report2.png" class="img-fluid"> <img src="../images/tb_report3.png" class="img-fluid"> <img src="../images/tb_report4.png" class="img-fluid"> <img src="../images/tb_report5.png" class="img-fluid"></p>
+<p>There are of course downsides to using TaxBrain instead of Tax-Calculator directly. Specifically, it’s more difficult, and sometimes impossible, to perform custom tasks like modeling a feature of the tax code that hasn’t been added to Tax-Calculator yet or advanced work with marginal tax rates. But for day-to-day tax modeling, the TaxBrain Python package can significantly simply any workflow.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://github.com/PSLmodels/Tax-Brain">Tax-Brain GitHub repo</a></li>
+<li><a href="http://taxbrain.pslmodels.org/content/intro.html">Tax-Brain Documentation</a></li>
+</ul>
+
+
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diff --git a/posts/2021-07-16-demo-day-constructing-tax-data-for-the-50-states.html b/posts/2021-07-16-demo-day-constructing-tax-data-for-the-50-states.html
new file mode 100644
index 0000000..04746b4
--- /dev/null
+++ b/posts/2021-07-16-demo-day-constructing-tax-data-for-the-50-states.html
@@ -0,0 +1,606 @@
+<!DOCTYPE html>
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+
+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
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+<meta name="author" content="Don Boyd">
+<meta name="dcterms.date" content="2021-07-16">
+<meta name="description" content="A new dataset to facilitate state-level analysis of federal tax reforms.">
+
+<title>Policy Simulation Library Blog - Demo Day: Constructing tax data for the 50 states</title>
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+            <div id="quarto-search" class="" title="Search"></div>
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+<!-- content -->
+<header id="title-block-header" class="quarto-title-block default page-columns page-full">
+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Constructing tax data for the 50 states</h1>
+                  <div>
+        <div class="description">
+          A new dataset to facilitate state-level analysis of federal tax reforms.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">tax</div>
+                <div class="quarto-category">data</div>
+                <div class="quarto-category">us</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Don Boyd </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">July 16, 2021</p>
+      </div>
+    </div>
+    
+      
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+
+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/gnYKHtdSqbY" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<hr>
+<p>Federal income tax reform impacts can vary dramatically across states. The cap on state and local tax deductions (SALT) is a well-known example, but other policies also have differential effects because important tax-relevant features vary across states such as the income distribution, relative importance of wage, business, and retirement income, and family size and structure. Analyzing how policy impacts vary across states requires data that faithfully represent the characteristics of the 50 states.</p>
+<p>This Demo Day described a method and software for constructing state weights for microdata files that (1) come as close as possible to targets for individual states, while (2) ensuring that the state weights for each tax record sum to its national weight. The latter objective ensures that the sum of state impacts for a tax reform equals the national impact.</p>
+<p>This project developed state weights for a data file with more than 200,000 microdata records. The weighted data file comes within 0.01% of desired values for more than 95% of approximately 10,000 targets.</p>
+<p>The goal of the <a href="https://github.com/donboyd5/slides/blob/master/2021-07-12_Boyd_PSL_Demo_Constructing_State_Tax_Weights_For_PUF.pdf">slides</a> and <a href="https://youtu.be/gnYKHtdSqbY">video</a> was to enable a motivated Python-skilled user of the PSL <a href="https://github.com/PSLmodels/taxdata">TaxData</a> and <a href="https://taxcalc.pslmodels.org">Tax-Calculator</a> projects to reproduce project results: 50-state weights for TaxData’s primary output, the puf.csv microdata file (based primarily on an IRS Public Use File), using early-stage open-source software developed in the project. Thus, the demo is technical and focused on nuts and bolts.</p>
+<p>The methods and software can also be used to:</p>
+<ul>
+<li>Create geographic-area weights for other microdata files</li>
+<li>Apportion state weights to Congressional Districts or counties, if suitable targets can be developed</li>
+<li>Create state-specific microdata files suitable for modeling state income taxes</li>
+</ul>
+<p>The main topics covered in the slides and video are:</p>
+<ul>
+<li>Creating national and state targets from IRS summary data</li>
+<li>Preparing a national microdata file for state weighting</li>
+<li>Approaches to constructing geographic weights</li>
+<li>Running software that implements the Poisson-modeling approach used in the project</li>
+<li>Measures of quality of the results</li>
+</ul>
+
+
+
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+
+
+
+
+</body></html>
\ No newline at end of file
diff --git a/posts/2021-08-09-demo-day-unit-testing.html b/posts/2021-08-09-demo-day-unit-testing.html
new file mode 100644
index 0000000..576bdcc
--- /dev/null
+++ b/posts/2021-08-09-demo-day-unit-testing.html
@@ -0,0 +1,629 @@
+<!DOCTYPE html>
+<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"><head>
+
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+<meta name="generator" content="quarto-1.4.551">
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+
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+<meta name="dcterms.date" content="2021-08-09">
+<meta name="description" content="How to ensure that individual functions do what you expect.">
+
+<title>Policy Simulation Library Blog - Demo Day: Unit testing for open source projects</title>
+<style>
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+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Unit testing for open source projects</h1>
+                  <div>
+        <div class="description">
+          How to ensure that individual functions do what you expect.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">R</div>
+                <div class="quarto-category">Python</div>
+                <div class="quarto-category">unit-testing</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">August 9, 2021</p>
+      </div>
+    </div>
+    
+      
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+<hr>
+<p>Unit testing is the testing of individual units or functions of a software application. This differs from regression testing that focuses on the verification of final outputs. Instead, unit testing tests each smallest testable component of your code. This helps to more easily identify and trace errors in the code.</p>
+<p>Writing unit tests is good practice, though not one that’s always followed. The biggest barrier to writing unit tests is that doing so takes time. You might wonder “why am I testing code that runs?” But there are a number benefits to writing unit tests:</p>
+<ul>
+<li>It ensures that the code does what you expect it to do</li>
+<li>You’ll better understand what your code is doing</li>
+<li>You will reduce time tracking down bugs in your code</li>
+</ul>
+<p>Often, writing unit tests will save you time in the longer run because it reduces debugging time and because it forces you to think more about what your code does, which often leads to the development of more efficient code. And for open source projects, or projects with many contributors, writing unit tests is important in reducing the likelihood that errors are introduced into your code. This is why the <a href="https://pslmodels.org/Catalog/library_criteria.html">PSL catalog criteria</a> requires projects to provide at least some level of unit testing.</p>
+<p>In the PSL Demo Day video linked above, I illustrate how to implement unit tests in R using the <a href="https://testthat.r-lib.org"><code>testthat</code></a> package. There are essentially three steps to this process:</p>
+<ol type="1">
+<li>Create a directory to put your testing script in, e.g., a folder called <code>tests</code></li>
+<li>Create one or more scripts that define your tests.
+<ul>
+<li>Each test is represented as a call of the <code>test_that</code> function and contain an statement that will evaluate as true or false (e.g., you may use the <code>expect_equal</code> function to verify that a function returns expected values given certain inputs).</li>
+<li>You will want to use <code>test</code> in the name of these tests scripts as well as something descriptive of what is tested.</li>
+</ul></li>
+<li>Create a script that will run your tests.
+<ul>
+<li>Here you’ll need to import the <code>testthat</code> package and you’ll need to call the script(s) you are testing to load their functions.</li>
+<li>Then you’ll use the <code>test_dir</code> function to pass the directory in which the script(s) you created in Step 2 reside.</li>
+</ul></li>
+</ol>
+<p>Check out the video to see examples of how each of these steps is executed. I’ve also found <a href="https://towardsdatascience.com/unit-testing-in-r-68ab9cc8d211">this blog post</a> on unit tests with <code>testthat</code> to be helpful.</p>
+<p>Unit testing in Python seems to be more developed and straightforward with the excellent <a href="https://docs.pytest.org/en/6.2.x/"><code>pytest</code></a> package. While <code>pytest</code> offers many options for parameterizing tests, running tests in parallel, and more, the basic steps remain the same as those outlined above:</p>
+<ol type="1">
+<li>Create a directory for your test modules (call this folder <code>tests</code> as <code>pytest</code> will look for that name).</li>
+<li>Create test modules that define each test
+<ul>
+<li>Tests are defined much like any other function in Python, the but will involve some assertion statement is triggered upon test failure.</li>
+<li>You will want to use <code>test</code> in the name of these tests modules as well as something descriptive of what is tested.</li>
+</ul></li>
+<li>You won’t need to create a script to run your tests as with <code>testthat</code>, but you may create a <a href="https://docs.pytest.org/en/6.2.x/customize.html"><code>pytest.ini</code></a> file to customize your tests options.</li>
+</ol>
+<p>That’s about it to get started writing unit tests for your code. PSL cataloged projects provide many excellent examples of a variety of unit tests, so search them for examples to build from. In a future Demo Day and blog post, we’ll talk about continuous integration testing to help get even more out of you unit tests.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://testthat.r-lib.org"><code>testthat</code></a> package for unit testing in R</li>
+<li><a href="https://docs.pytest.org/en/6.2.x/"><code>pytest</code></a> package for unit testing in Python</li>
+<li><a href="https://pslmodels.org/Catalog/library_criteria.html">PSL catalog criteria</a></li>
+<li><a href="https://github.com/TaxFoundation/capital-cost-recovery/tree/master/tests">Unit tests for the <code>capital-cost-recovery</code> model</a></li>
+</ul>
+
+
+
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+
+
+
+</body></html>
\ No newline at end of file
diff --git a/posts/2021-09-20-demo-day-cs-auto-deploy.html b/posts/2021-09-20-demo-day-cs-auto-deploy.html
new file mode 100644
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+
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+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Deploying apps on Compute Studio</h1>
+                  <div>
+        <div class="description">
+          How to deploy apps on Compute Studio using the new automated deployments feature.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">policy-simulation-library</div>
+                <div class="quarto-category">compute-studio</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Hank Doupe </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">September 20, 2021</p>
+      </div>
+    </div>
+    
+      
+    </div>
+    
+  
+  </header><div id="quarto-content" class="quarto-container page-columns page-rows-contents page-layout-article page-navbar">
+<!-- sidebar -->
+<!-- margin-sidebar -->
+    
+<!-- main -->
+<main class="content quarto-banner-title-block" id="quarto-document-content">
+
+
+
+
+
+<hr>
+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/P1mzhZkwRt0" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<hr>
+<p>Compute Studio (C/S) is a platform for publishing and sharing computational models and data visualizations. In this demo day, I show how to publish your own project on C/S using the new automated deployments feature. You can find an in depth guide to publishing on C/S in the <a href="https://docs.compute.studio/publish/guide.html">developer docs</a>.</p>
+<p>C/S supports two types of projects: models and data visualizations. Models are fed some inputs and return a result. Data visualizations are web servers backed by popular open-source libraries like Bokeh, Dash, or Streamlit. Models are good for long-running processes and producing archivable results that can be shared and returned to easily. Data visualizations are good for highly interactive and custom user experiences.</p>
+<p>Now that you’ve checked out the <a href="https://docs.compute.studio/publish/guide.html">developer docs</a> and set up your model or data-viz, you can head over to the C/S publishing page <a href="https://compute.studio/new/">https://compute.studio/new/</a> to publish your project. Note that this page is still very much under construction and may look different in a few weeks.</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/publish_page.png" class="img-fluid figure-img"></p>
+<figcaption>Publish page</figcaption>
+</figure>
+</div>
+<p>Next, you will be sent to the second stage in the publish flow where you will provide more details on how to connect your project on C/S:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/connect_project_page.png" class="img-fluid figure-img"></p>
+<figcaption>Connect Project page</figcaption>
+</figure>
+</div>
+<p>Clicking “Connect App” will take you to the project home page:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/project_home_page.png" class="img-fluid figure-img"></p>
+<figcaption>Project home page</figcaption>
+</figure>
+</div>
+<p>Go to the “Settings” button in the top-right corner and this will take you to the project dashboard where you can modify everything from the social preview of your project to the amount of compute resources it needs:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/project_dashboard.png" class="img-fluid figure-img"></p>
+<figcaption>Project dashboard</figcaption>
+</figure>
+</div>
+<p>The “Builds” link in the sidebar will take you to the builds dashboard where you can create your first build:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/build_history_dashboard.png" class="img-fluid figure-img"></p>
+<figcaption>Build history dashboard</figcaption>
+</figure>
+</div>
+<p>It’s time to create the first build. You can do so by clicking “New Build”. This will take you to the build status page. While the build is being scheduled, the page will look like this:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/build_scheduled_page.png" class="img-fluid figure-img"></p>
+<figcaption>Build scheduled page</figcaption>
+</figure>
+</div>
+<p>You can click the “Build History” link and it will show that the build has been started:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/build_history_dashboard_progress.png" class="img-fluid figure-img"></p>
+<figcaption>Build history dashboard</figcaption>
+</figure>
+</div>
+<p>The build status page should be updated at this point and will look something like this:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/build_status_page_progress.png" class="img-fluid figure-img"></p>
+<figcaption>Build status page</figcaption>
+</figure>
+</div>
+<p>C/S automated deployments are built on top of <a href="https://github.com/features/actions">Github Actions</a>. Unfortunately, the logs in Github Actions are not available through the Github API until after the workflow is completely finished. The build status dashboard will update as the build progresses and once it’s done, you will have full access to the logs from the build. These will contain outputs from installing your project and the outputs from your project’s tests.</p>
+<p>In this case, the build failed. We can inspect the logs to see that an import error caused the failure:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/build_status_failed.png" class="img-fluid figure-img"></p>
+<figcaption>Build failed status page</figcaption>
+</figure>
+</div>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/build_status_failed_logs.png" class="img-fluid figure-img"></p>
+<figcaption>Build failed status page with logs</figcaption>
+</figure>
+</div>
+<p>I pushed an update to my fork of Tax-Cruncher on Github and restarted the build by clicking “Failure. Start new Build”. The next build succeeded and we can click “Release” to publish the project:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/build_status_page_success.png" class="img-fluid figure-img"></p>
+<figcaption>Build status page success</figcaption>
+</figure>
+</div>
+<p>The builds dashboard now shows the two builds:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/updated_build_history_page.png" class="img-fluid figure-img"></p>
+<figcaption>Updated build history page</figcaption>
+</figure>
+</div>
+<p>Finally, let’s go run our new model:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/run_project_page_loading.png" class="img-fluid figure-img"></p>
+<figcaption>Run project page</figcaption>
+</figure>
+</div>
+<p>It may take a few seconds for the page to load. This is because the model code and all of its dependencies are being loaded onto the C/S servers for the first time:</p>
+<div class="quarto-figure quarto-figure-center">
+<figure class="figure">
+<p><img src="../images/cs-auto-deploy/run_project_page_success.png" class="img-fluid figure-img"></p>
+<figcaption>Run project page with inputs form</figcaption>
+</figure>
+</div>
+<p>The steps for publishing a data visualization are very similar. The main idea is that you tell C/S what Python file your app lives in and C/S will know how to run it given your data visualization technology choice.</p>
+
+
+
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diff --git a/posts/2021-11-01-demo-day-og-core.html b/posts/2021-11-01-demo-day-og-core.html
new file mode 100644
index 0000000..15f8908
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+++ b/posts/2021-11-01-demo-day-og-core.html
@@ -0,0 +1,601 @@
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+<meta name="author" content="Jason DeBacker">
+<meta name="dcterms.date" content="2021-11-01">
+<meta name="description" content="A Python platform for building country-specific overlapping generations general equilibrium models.">
+
+<title>Policy Simulation Library Blog - Demo Day: The OG-Core platform</title>
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+<!-- content -->
+<header id="title-block-header" class="quarto-title-block default page-columns page-full">
+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: The OG-Core platform</h1>
+                  <div>
+        <div class="description">
+          A Python platform for building country-specific overlapping generations general equilibrium models.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">python</div>
+                <div class="quarto-category">macroeconomics</div>
+                <div class="quarto-category">overlapping-generations</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">November 1, 2021</p>
+      </div>
+    </div>
+    
+      
+    </div>
+    
+  
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+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/y1vSgmEtgxs" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<hr>
+<p>The <a href="https://pslmodels.github.io/OG-Core/">OG-Core</a> model is a general equilibrium, overlapping generations (OG) model suitable for evaluating fiscal policy. Since the work of Alan Auerbach and Laurence Kotlikoff in the 1980s, this class of model has become a standard in the macroeconomic analysis of tax and spending policy. This is for good reason. OG models are able to capture the impacts of taxes and spending in the short and long run, examine incidence of policy across generations of people (not just short run or steady state analysis of a cross-section of the economy), and capture important economic dynamics (e.g., crowding out effects of deficit-financed policy).</p>
+<p>In the PSL Demo Day presentation linked above, I cover the basics of OG-Core: its history, its API, and how country-specific models can use OG-Core as a dependency. In brief, OG-Core provides a general overlapping generations framework, from which parameters can be calibrated to represent particular economies. Think of it this way: an economic model is just a set of parameters plus a system of equations. OG-Core spells out all of the equations to represent an economy with heterogeneous agents, production and government sectors, open economy options, and detailed policy rules. OG-Core also includes default values for all parameters, along with parameter metadata and parameter validation rules. A country specific application is then just a particular parameterization of the general OG-Core model.</p>
+<p>As an example of a country-specific application, one can look at the <a href="https://pslmodels.github.io/OG-USA">OG-USA model</a>. This model provides a calibration of OG-Core to the United States. The source code in that project allows one to go from raw data sources to the estimation and calibration procedures used to determine parameter values representing the United States, to parameter values in formats suitable for use in OG-Core. Country-specific models like OG-USA include (where available) links to microsimulation models of tax and spending programs to allow detailed microdata of actual and counterfactual policies to inform the net tax-transfer functions used in the OG-Core model. For those interested in building their own country-specific model, the OG-USA project provides a good example to work from.</p>
+<p>We encourage you to take a look at OG-Core and related projects. New contributions and applications are always welcome. If you have questions or comments, reach out through the relevant repositories on Github to me, <a href="https://github.com/jdebacker/"><span class="citation" data-cites="jdebacker">@jdebacker</span></a>, or Rick Evans, <a href="https://github.com/rickecon"><span class="citation" data-cites="rickecon">@rickecon</span></a>.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://pslmodels.github.io/OG-Core/content/intro/intro.html">OG-Core documentation</a></li>
+<li><a href="https://pslmodels.github.io/OG-USA">OG-USA documentation</a> package for unit testing in Python</li>
+<li><a href="http://taxcalc.pslmodels.org">Tax-Calculator documentation</a></li>
+<li><a href="https://github.com/PSLmodels/OG-UK">OG-UK repository</a></li>
+<li><a href="https://github.com/PolicyEngine/openfisca-uk">OpenFisca-UK repository</a></li>
+<li><a href="https://docs.google.com/presentation/d/1AT3SYNJ6JieAB1HrPT6HPSBC6-2A1QNtIdBDO-3PSCI/edit?usp=sharing">Slides from the Demo Day presentation</a></li>
+</ul>
+
+
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+      <h1 class="title">Demo Day: Using synthimpute for data fusion</h1>
+                  <div>
+        <div class="description">
+          The synthimpute Python package fuses and synthesizes economic datasets with machine learning.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">python</div>
+                <div class="quarto-category">data-fusion</div>
+                <div class="quarto-category">synthimpute</div>
+              </div>
+                  </div>
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+    
+  
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+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Max Ghenis </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">December 8, 2021</p>
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+<hr>
+<p>Suppose a policy analyst sought to estimate the impact of a policy that changed income tax rates and benefit rules while also adding a progressive wealth tax. The standard approach is to use a <em>microsimulation</em> model, where the rules are programmed as code, and then to run that program over a representative sample of households. Unfortunately, no single US government survey captures all the households characteristics needed to analyze this policy; in particular, the reliable tax and benefit information lies in surveys like the Current Population Survey (CPS), while wealth lies in the Survey of Consumer Finances (SCF).</p>
+<p>Assuming the analyst wanted to start with the CPS, they have several options to estimate wealth for households to levy the progressive wealth tax. Two typical approaches include:</p>
+<ol type="1">
+<li>Linear regression, predicting wealth from other household characteristics common to the CPS and SCF.</li>
+<li>Matching, in which each CPS household is matched with the most similar household in the SCF.</li>
+</ol>
+<p>Neither of these approaches, however, aim to estimate the <em>distribution</em> of wealth conditional on other characteristics. Linear regression explicitly estimates the mean prediction, but that could miss the tails of wealth from whom most of the wealth tax revenue will be collected.</p>
+<p>Instead, the analyst could apply <em>quantile regression</em> to estimate the distribution of wealth conditional on other characteristics, and then measure the effectiveness of the estimation using <em>quantile loss</em>.</p>
+<p>In this Demo Day, I present the concepts of microsimulation, imputation, and quantile loss to motivate the <code>synthimpute</code> Python package I’ve developed with my PolicyEngine colleague Nikhil Woodruff. In an experiment predicting wealth on a holdout set from the SCF, my former colleague Deepak Singh and I found that random forests significantly outperform OLS and matching for quantile regression, and this is the approach applied in <code>synthimpute</code> for both data fusion and data synthesis. The <code>synthimpute</code> API will be familiar to users of <code>scikit-learn</code> and <code>statsmodels</code> , with the difference being that <code>synthimpute</code> ’s <code>rf_impute</code> function returns a random value from the predicted distribution; it can also skew the predictions to meet a target total.</p>
+<p>We’ve used <code>synthimpute</code> to fuse data for research reports at the <a href="https://ubicenter.org">UBI Center</a> and to enhance the <a href="https://policyengine.org">PolicyEngine</a> web app for UK tax and benefit simulation, and we welcome new users and contributors. Feel free to explore the repository or contact me with questions at <a href="mailto:max@policyengine.org">max@policyengine.org</a>.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://github.com/PolicyEngine/synthimpute"><code>synthimpute</code> package on GitHub</a></li>
+<li><a href="https://docs.google.com/presentation/d/1Hw0zIkbnXZluW8ntjbw_NXryRvjVcg6DDp-btkXXV_o">Presentation slides</a></li>
+<li><a href="https://www.ubicenter.org/uk-lvt">UBI Center report on land value taxation in the UK</a>, using <code>synthimpute</code> to impute land value from the UK Wealth and Assets Survey to the Family Resources Survey</li>
+<li><a href="http://policyengine.org/uk/population-impact?carbon_tax=100">PolicyEngine UK carbon tax example</a>, using <code>synthimpute</code> to impute carbon emissions from the Living Costs and Food Survey to the Family Resources Survey</li>
+<li><a href="https://colab.research.google.com/drive/1E8F7S1Uvfw_3PmpS226Sl1LWV5NBi0CE">Notebook comparing random forests to matching and other techniques</a> using a holdout set from the US Survey of Consumer Finances</li>
+<li><a href="https://towardsdatascience.com/quantile-regression-from-linear-models-to-trees-to-deep-learning-af3738b527c3">My blog post on quantile regression for Towards Data Science</a>, which laid the groundwork for <code>synthimpute</code></li>
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+<meta name="description" content="Highlights from the Policy Simulation Library in 2021.">
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+    <div class="quarto-title column-body">
+      <h1 class="title">2021: A year in review</h1>
+                  <div>
+        <div class="description">
+          Highlights from the Policy Simulation Library in 2021.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">psl</div>
+                <div class="quarto-category">psl-foundation</div>
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+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">December 28, 2021</p>
+      </div>
+    </div>
+    
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+
+
+
+<p><img src="https://pslmodels.org/imgs/PSL.svg" class="img-fluid"></p>
+<hr>
+<p>As 2021 winds down, I wanted to take a few minutes to reflect on the Policy Simulation Library’s efforts over the past year. With an amazing community of contributors, supporters, and users, PSL has been able to make a real impact in 2021.</p>
+<p>The library saw two new projects achieve “cataloged” status: Tax Foundation’s <a href="https://github.com/TaxFoundation/capital-cost-recovery">Capital Cost Recovery model</a> and the Federal Reserve Bank of New York’s <a href="https://github.com/FRBNY-DSGE/DSGE.jl">DSGE.jl model</a>. Both models satisfy all the the <a href="http://pslmodels.org/Catalog/library_criteria.html">PSL criteria</a> for transparency and reproducibility. Both are also written entirely in open source software: the Capital Cost Recovery model is in R and the DSGE model in Julia.</p>
+<p>An exciting new project to join the Library this year is <a href="https://policyengine.org/uk/policy">PolicyEngine</a>. PolicyEngine is building open source tax and benefit mircosimulation models and very user-friendly interfaces to these models. The goal of this project is to take policy analysis to the masses through intuitive web and mobile interfaces for policy models. The UK version of the PolicyEngine app has already seen use from politicians interested in reforming the tax and benefit system in the UK.</p>
+<p>Another excellent new addition to the library is the <a href="https://github.com/PSLmodels/Federal-State-Tax">Federal-State Tax Project</a>. This project provides data imputation tools to allow for state tax data that are representative of each state as well as federal totals. These datasets can then be used in microsimulation models, such as <a href="https://taxcalc.pslmodels.org">Tax-Calculator</a> to study the impact of federal tax laws across the states. Matt Jensen and Don Boyd have published several pieces with these tools, including in <a href="https://www.taxnotes.com/special-reports/tax-cuts-and-jobs-act/repealing-salt-cap-state-state-impacts/2021/10/21/7bbv3"><em>State Tax Notes</em></a></p>
+<p><a href="https://psl-foundation.org">PSL Foundation</a> became an official business entity in 2021. While still awaiting a letter of determination for 501(c)(3) status from the IRS, PSL Foundation was able to raise more than $25,000 in the last few months of 2021 to support open source policy analysis!</p>
+<p>PSL community members continued to interact several times each week in our public calls. The <a href="https://pslmodels.org/shop#!/">PSL Shop</a> was launched in 2021 so that anyone can get themselves some PSL swag (with some of each purchase going back to the PSL Foundation to support the Library). In addition, PSL hosted 20 <a href="http://blog.pslmodels.org/categories/#demo-days">Demo Day presentations</a> from 11 different presenters! These short talks covered everything from new projects to interesting applications of some of the first projects to join the Library, as well as general open source tools.</p>
+<p>As in past years, PSL cataloged and incubating models were found to be of great use in current policy debates. Whether it was the <a href="https://www.openrg.com/reports/QN_ARPA_Distribution.pdf">ARPA</a>, <a href="https://www.jainfamilyinstitute.org/assets/full-refundability-of-child-tax-credit-without-expansion.pdf">Biden administration proposals to expand the CTC</a>, or <a href="https://blog.ubicenter.org/20210403/california-ab65-calubi.html">California’s Basic Income Bill</a>, the accessibility and ability to reproduce results from these open source projects has made them a boon to policy analysts.</p>
+<p>We are looking forward to a great 2022! We expect the Library to continue to grow, foresee many interesting and helpful Demo Days, and are planning a DC PSL Workshop for March 2022. We hope to see you around these or other events!</p>
+<p>Best wishes from PSL for a happy and healthy New Year!</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://psl-foundation.org">PSL Foundation</a></li>
+<li><a href="https://twitter.com/PSLmodels">PSL Twitter Feed</a></li>
+<li><a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">PSL YouTube channel</a></li>
+<li><a href="https://opencollective.com/psl">PSL on Open Collective</a></li>
+</ul>
+
+
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diff --git a/posts/2022-03-03-DC-workshop.html b/posts/2022-03-03-DC-workshop.html
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+<meta name="description" content="Washington, DC open-source modeling workshop, March 25, 2022, 8:30am-1:00pm, Martin Luther King, Jr.&nbsp;Memorial Library.">
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+<title>Policy Simulation Library Blog - Policy Simulation Library DC Workshop: Open source tools for analyzing tax policy</title>
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+      <h1 class="title">Policy Simulation Library DC Workshop: Open source tools for analyzing tax policy</h1>
+                  <div>
+        <div class="description">
+          Washington, DC open-source modeling workshop, March 25, 2022, 8:30am-1:00pm, Martin Luther King, Jr.&nbsp;Memorial Library.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">PSL</div>
+                <div class="quarto-category">PSL-Foundation</div>
+                <div class="quarto-category">Workshop</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">March 3, 2022</p>
+      </div>
+    </div>
+    
+      
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+
+
+<p><img src="../images/MLK_Library_cut2.png" class="img-fluid"></p>
+<hr>
+<p>The <a href="https://pslmodels.org/">Policy Simulation Library</a> is hosting a workshop in Washington, DC on March 25 on open source tools for the analysis of tax policy. Participants will learn how to use open source models from the Library for revenue estimation, distributional analysis, and to simulate economic impacts of tax policy. The workshop is intended to be a hands-on experience and participants can expect to leave with the required software, documentation, and knowledge to continue using these tools. All models in the workshop are written in the Python programming language–familiarity with the language is helpful, but not required.</p>
+<p><strong>Workshop Schedule:</strong></p>
+<ul>
+<li><strong>8:15-8:45a:</strong> Breakfast</li>
+<li><strong>8:45-9:00a:</strong> Introduction</li>
+<li><strong>9:00-9:50a:</strong> Using <a href="https://taxcalc.pslmodels.org/"><strong>Tax-Calculator</strong></a> for revenue estimation and distributional analysis (<a href="https://www.aei.org/profile/matthew-h-jensen/">Matt Jensen</a>)</li>
+<li><strong>10:00-10:50a:</strong> Estimating effective tax rates on investment with <a href="https://ccc.pslmodels.org/"><strong>Cost-of-Capital-Calculator</strong></a> (<a href="https://jasondebacker.com/">Jason DeBacker</a>)</li>
+<li><strong>11:00-11:50a:</strong> Macroeconomic modeling of fiscal policy with <a href="https://pslmodels.github.io/OG-Core/"><strong>OG-Core</strong></a> and <a href="https://pslmodels.github.io/OG-USA/"><strong>OG-USA</strong></a> (<a href="https://sites.google.com/site/rickecon">Richard W. Evans</a>)</li>
+<li><strong>noon-1:00p:</strong> Lunch and demonstration of <a href="https://policyengine.org/"><strong>PolicyEngine</strong></a> (<a href="https://www.ubicenter.org/author/max/">Max Ghenis</a>)</li>
+</ul>
+<p>The workshop will be held at the Martin Luther King Jr.&nbsp;Memorial Library in Washington, DC. Participants are expected to arrive by 8:30am and the program will conclude at 1:00pm. Breakfast and lunch will be provided. <a href="https://psl-foundation.org/">PSL Foundation</a> is sponsoring the event and there is no cost to attend. Attendance is limited to 30 in order to make this a dynamic and interactive workshop.</p>
+<p>To register, please use <a href="https://docs.google.com/forms/d/e/1FAIpQLSewWIdF7r7BIEPRDjq_AWE6yJMx9fHwIxCwyg58D52lNMFqiA/viewform">this Google Form</a>. Registration will close March 11. Participants will be expected to bring a laptop to the workshop where they can interact with the software in real time with the instructors. Registered participants will receive an email before the event with a list of software to install before the workshop.</p>
+<p>Please feel free to share this invitation with your colleagues.</p>
+<p>Questions about the workshop can be directed to Jason DeBacker at <a href="mailto:jason.debacker@gmail.com">jason.debacker@gmail.com</a>.</p>
+
+
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diff --git a/posts/2022-04-12-demo-day-policyengine-us.html b/posts/2022-04-12-demo-day-policyengine-us.html
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+<meta name="dcterms.date" content="2022-04-12">
+<meta name="description" content="PolicyEngine US is a new web app for computing the impact of US tax and benefit policy.">
+
+<title>Policy Simulation Library Blog - Demo Day: Modeling taxes and benefits with the PolicyEngine US web app</title>
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+      <h1 class="title">Demo Day: Modeling taxes and benefits with the PolicyEngine US web app</h1>
+                  <div>
+        <div class="description">
+          PolicyEngine US is a new web app for computing the impact of US tax and benefit policy.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">apps</div>
+                <div class="quarto-category">taxes</div>
+                <div class="quarto-category">benefits</div>
+                <div class="quarto-category">us</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Max Ghenis </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">April 12, 2022</p>
+      </div>
+    </div>
+    
+      
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+<hr>
+<p><a href="https://policyengine.org">PolicyEngine</a> is a nonprofit that builds free, open-source software to compute the impact of public policy. After launching our <a href="https://policyengine.org/uk">UK app</a> in October 2021, we’ve just launched our <a href="https://policyengine.org/us">US app</a>, which calculates households’ federal taxes and several benefit programs, both under current law and under customizable policy reforms.</p>
+<p>In this Demo Day, I provide background on PolicyEngine and demonstrate how to use PolicyEngine US (a Policy Simulation Library cataloged model) to answer a novel policy question:</p>
+<blockquote class="blockquote">
+<p>How would doubling both (a) the Child Tax Credit and (b) the Supplemental Nutrition Assistance Program (SNAP) net income limit affect a single parent in California with $1,000 monthly rent and $50 monthly broadband costs?</p>
+</blockquote>
+<p>By bringing together tax and benefit models into a web interface, we can answer this question quickly without programming experience, as well as an unlimited array of questions like it. The result is a table breaking down the household’s net income by program, as well as graphs of net income and marginal tax rates as the household’s earnings vary.</p>
+<p>I close with a quick demo of <a href="https://policyengine.org/uk">PolicyEngine UK</a>, which adds society-wide results like the impact of reforms on the budget, poverty, and inequality, as well as contributed policy parameters. We’re planning to bring those features to PolicyEngine US, along with state tax and benefit programs in all 50 states, over the next two years (if not sooner).</p>
+<p>Feel free to explore the app and reach out with any questions at <a href="mailto:max@policyengine.org">max@policyengine.org</a>.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://policyengine.org/us">PolicyEngine US</a></li>
+<li><a href="https://docs.google.com/presentation/d/1ckaxNiPrUZeD1IGhqeqAjLPjjCx1zswhZiIqO0ps72w">Presentation slides</a></li>
+<li><a href="https://blog.policyengine.org/policyengine-comes-stateside-cef88b122e48">PolicyEngine blog post on launching PolicyEngine US</a></li>
+</ul>
+
+
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diff --git a/posts/2022-04-18-demo-day-ccc-international.html b/posts/2022-04-18-demo-day-ccc-international.html
new file mode 100644
index 0000000..1db13e5
--- /dev/null
+++ b/posts/2022-04-18-demo-day-ccc-international.html
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+<meta name="author" content="Jason DeBacker">
+<meta name="dcterms.date" content="2022-04-18">
+<meta name="description" content="Using Cost-of-Capital-Calculator with data on international business tax policies.">
+
+<title>Policy Simulation Library Blog - Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator</title>
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+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator</h1>
+                  <div>
+        <div class="description">
+          Using Cost-of-Capital-Calculator with data on international business tax policies.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">cost-of-capital-calculator</div>
+                <div class="quarto-category">business-taxation</div>
+                <div class="quarto-category">corporate-income-tax</div>
+                <div class="quarto-category">taxes</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">April 18, 2022</p>
+      </div>
+    </div>
+    
+      
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+
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+<hr>
+<p>In the Demo Day video shared here, I show how to use open source tools to analyze international corporate tax competitiveness. The two main tools illustrated are the <a href="https://ccc.pslmodels.org/content/intro.html">Cost-of-Capital-Calculator</a> (CCC), a model to compute measures of the tax burden on new investments, and <a href="https://taxfoundation.org/publications/international-tax-competitiveness-index/">Tax Foundation’s International Tax Competitiveness Index</a> (ITCI).</p>
+<p>Tax Foundation has made many helpful resources available online. Their measures of international business tax policy are a great example of this. The ICTI outputs and inputs are all well documented, with source code to reproduce results <a href="https://github.com/TaxFoundation/international-tax-competitiveness-index/">available on GitHub</a>.</p>
+<p>I plug Tax Foundation’s country-by-country data into CCC functions using it’s Python API. Because CCC is designed to flexibly take array or scalar data, operating on rows of tabular data, such as that in the ITCI, is relatively straight-forward. The Google <a href="https://colab.research.google.com/drive/1t_NDNqP5-Aq_vsOkGO9SE1Qj4oEVCqCN?usp=sharing">Colab notebook</a> I walk through in this Demo Day, can be a helpful example to follow if you’d like to do something similar to this with the Tax Foundation data - or your own data source. From the basic building blocks there (reading in data, calling CCC functions), you can extend the analysis in a number of ways. For example adding additional years of data (Tax Foundation posts their data back to 2014), modifying economic assumptions, or creating counter-factual policy experiments across sets of countries.</p>
+<p>If you find this example useful, or have questions or suggestions about this type of analysis, please feel free to <a href="mailto:jason.debacker@gmail.com">reach out to me</a>.</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://colab.research.google.com/drive/1t_NDNqP5-Aq_vsOkGO9SE1Qj4oEVCqCN?usp=sharing">Colab Notebook</a></li>
+<li><a href="https://taxfoundation.org/publications/international-tax-competitiveness-index/">Tax Foundation International Tax Competitiveness Index 2021</a></li>
+<li><a href="https://github.com/TaxFoundation/international-tax-competitiveness-index/tree/master/final_data">GitHub repo for Tax Foundation ITCI data</a></li>
+<li><a href="https://ccc.pslmodels.org/content/intro.html">Cost-of-Capital-Calculator documentation</a></li>
+</ul>
+
+
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+      }
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+  var bibliorefs = window.document.querySelectorAll('a[role="doc-biblioref"]');
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+</div> <!-- /content -->
+
+
+
+
+</body></html>
\ No newline at end of file
diff --git a/posts/2022-06-28-demo-day-github.html b/posts/2022-06-28-demo-day-github.html
new file mode 100644
index 0000000..a226a54
--- /dev/null
+++ b/posts/2022-06-28-demo-day-github.html
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+<meta charset="utf-8">
+<meta name="generator" content="quarto-1.4.551">
+
+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
+
+<meta name="author" content="Jason DeBacker">
+<meta name="dcterms.date" content="2022-06-28">
+<meta name="description" content="The basics of forking and cloning repositories and working on branches.">
+
+<title>Policy Simulation Library Blog - Demo Day: Getting Started with GitHub</title>
+<style>
+code{white-space: pre-wrap;}
+span.smallcaps{font-variant: small-caps;}
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+      <div class="navbar-container container-fluid">
+      <div class="navbar-brand-container mx-auto">
+    <a class="navbar-brand" href="../index.html">
+    <span class="navbar-title">Policy Simulation Library Blog</span>
+    </a>
+  </div>
+            <div id="quarto-search" class="" title="Search"></div>
+          <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarCollapse" aria-controls="navbarCollapse" aria-expanded="false" aria-label="Toggle navigation" onclick="if (window.quartoToggleHeadroom) { window.quartoToggleHeadroom(); }">
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+            <ul class="navbar-nav navbar-nav-scroll ms-auto">
+  <li class="nav-item">
+    <a class="nav-link" href="../about.html"> 
+<span class="menu-text">PSL Blog</span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://github.com/PSLmodels"> <i class="bi bi-github" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+  <li class="nav-item compact">
+    <a class="nav-link" href="https://twitter.com/PSLmodels"> <i class="bi bi-twitter" role="img">
+</i> 
+<span class="menu-text"></span></a>
+  </li>  
+</ul>
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+  <div class="quarto-title-banner page-columns page-full">
+    <div class="quarto-title column-body">
+      <h1 class="title">Demo Day: Getting Started with GitHub</h1>
+                  <div>
+        <div class="description">
+          The basics of forking and cloning repositories and working on branches.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">github</div>
+                <div class="quarto-category">git</div>
+                <div class="quarto-category">workflow</div>
+                <div class="quarto-category">getting-started</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">June 28, 2022</p>
+      </div>
+    </div>
+    
+      
+    </div>
+    
+  
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+<!-- sidebar -->
+<!-- margin-sidebar -->
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+        
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+<!-- main -->
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+
+
+
+
+
+<div class="quarto-video ratio ratio-16x9"><iframe data-external="1" src="https://www.youtube.com/embed/ENl3AkZZgRQ" title="" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen=""></iframe></div>
+<hr>
+<p>Git and GitHub often present themselves as barriers to entry to would-be contributors to PSL projects, even for those who are otherwise experienced with policy modeling. But these tools are critical to collaboration on open source projects. In the Demo Day video linked above, I cover some of the basics to get set up and begin contributing to an open source project.</p>
+<p>There are four steps I outline:</p>
+<ol type="1">
+<li>Create a “<a href="https://docs.github.com/en/get-started/quickstart/fork-a-repo">fork</a>” of the repository you are interested in. A fork is a copy of the source code that resides on GitHub (i.e., in the cloud). A fork gives you control over a copy of the source code. You will be able to merge in changes to the code on this fork, even if you don’t have permissions to do so with the original repository.</li>
+<li>“<a href="https://git-scm.com/book/en/v2/Git-Basics-Getting-a-Git-Repository">Clone</a>” the fork. Cloning will download a copy of the source code from your fork onto your local machine. But cloning is more than just downloading the source code. It will include the version history of the code and automatically create a link between the local files and the remote files on your fork.</li>
+<li>Configure your local files to talk to both your fork (which has a default name of <code>origin</code>) and the original repository you forked from (which typically has the default name of <code>upstream</code>). Do this by using your command prompt or terminal to navigate to the directory you just cloned. From there, run:</li>
+</ol>
+<pre><code>git remote add upstream URL_to_original_repo.git</code></pre>
+<p>And check that this worked by giving the command:</p>
+<pre><code>git remote -v</code></pre>
+<p>If things worked, you should see URLs to your fork and the upstream repository with “(fetch)” and “(push)” by them More info on this is in the <a href="https://git-scm.com/book/en/v2/Git-Basics-Working-with-Remotes">Git docs</a>.</p>
+<ol start="4" type="1">
+<li>Now that you have copies of the source code on your fork and on your local machine, you are ready to begin contributing. As you make changes to the source code, you’ll want to work on <a href="https://git-scm.com/book/en/v2/Git-Branching-Basic-Branching-and-Merging">development branches</a>. Branches are copies of the code. Ideally, you keep your “main” (or “master”) branch clean (i.e., your best version of the code) and develop the code on branches. When you’ve completed the development work (e.g., adding a new feature) you will them merge this into the “main” branch.</li>
+</ol>
+<p>I hope this helps you get started contributing to open source projects. Git and GitHub are valuable tools and there is lots more to learn, but these basics will get you going. For more information, see the links below. If you want to get started working with a project in the Library, feel free to reach out to me through the relevant repo (<a href="https://github.com/jdebacker/"><span class="citation" data-cites="jdebacker">@jdebacker</span> on GitHub</a>) or drop into a PSL Community Call (dates on the <a href="http://pslmodels.org/events.html">PSL Calendar</a>).</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://pslmodels.github.io/Git-Tutorial/content/intro.html">PSL Git Tutorial</a></li>
+<li><a href="https://git-scm.com/book/en/v2/Git-Basics-Getting-a-Git-Repository">Git Basics</a></li>
+</ul>
+
+
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+<title>Policy Simulation Library Blog - Demo Day: How does targeted cash assistance affect incentives to work?</title>
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+      <h1 class="title">Demo Day: How does targeted cash assistance affect incentives to work?</h1>
+                  <div>
+        <div class="description">
+          How a proposed program in Cambridge, Massachusetts would affect poverty and incentives.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">demo-days</div>
+                <div class="quarto-category">benefits</div>
+                <div class="quarto-category">us</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Max Ghenis </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">July 14, 2022</p>
+      </div>
+    </div>
+    
+      
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+<hr>
+<p>In this week’s Demo Day, I shared my paper published at the <a href="https://thecgo.org">Center for Growth and Opportunity</a> in June. <a href="https://www.thecgo.org/research/how-does-targeted-cash-assistance-affect-incentives-to-work/">“How does targeted cash assistance affect incentives to work?”</a> analyzed a program Mayor Sumbul Siddiqui proposed in Cambridge, Massachusetts to provide $500 per month for 18 months to all families with dependents and income below 200% of the poverty line.</p>
+<p>Targeted programs like these are common in guaranteed income pilots, and in some enacted policies, and I find that it would cost-effectively reduce poverty: if expanded to Massachusetts, it would cost $1.2 billion per year and cut child poverty 42%.</p>
+<p>However, that targeting comes at a cost. Using the <a href="https://openfisca.us">OpenFisca US</a> microsimulation model (supported by the Center for Growth and Opportunity and cataloged by the Policy Simulation Library), I find that the program would deepen an existing welfare cliff at 200% of the poverty line. For example, a family of four would lose over $19,000 total—$9,000 from the cash assistance and $10,000 from other benefits—once they earn a dollar above 200% of the poverty line (about $55,000). To recover those lost benefits, they would have to earn an additional $26,000, a range I call the “earnings dead zone”.</p>
+<p>My presentation reviews these trends in both <a href="https://docs.google.com/presentation/d/1sWJ1VrSKFLdj1nw6IuRF65XoI1sTBDk7QgF3UHMcF34">slides</a> and the <a href="https://policyengine.org/us">PolicyEngine US</a> app for computing the impacts of tax and benefit policy. For example, I show how <a href="https://policyengine.org/us/household?abolish_snap_ea=1">repealing the SNAP emergency allotment</a> would smooth out welfare cliffs, while reducing resources available to low-income families, and how a universal child allowance avoids work disincentives while less cost-effectively reducing poverty.</p>
+<p>Policymakers face trade-offs between equity and efficiency, and typically labor supply responses consider marginal tax rates. With their infinite marginal tax rates, welfare cliffs are a less explored area, even though they surface in several parts of the tax and benefit system. This paper makes a start, but more research is yet to be done.</p>
+
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+<meta name="dcterms.date" content="2022-12-31">
+<meta name="description" content="Highlights from the Policy Simulation Library in 2022.">
+
+<title>Policy Simulation Library Blog - 2022: A year in review</title>
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+    <div class="quarto-title column-body">
+      <h1 class="title">2022: A year in review</h1>
+                  <div>
+        <div class="description">
+          Highlights from the Policy Simulation Library in 2022.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">psl</div>
+                <div class="quarto-category">psl-foundation</div>
+              </div>
+                  </div>
+  </div>
+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">December 31, 2022</p>
+      </div>
+    </div>
+    
+      
+    </div>
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+
+
+
+
+
+<p><img src="https://pslmodels.org/imgs/PSL.svg" class="img-fluid"></p>
+<hr>
+<p>This has been another successful year for the Policy Simulation Library, whose great community of contributors continue to make innovative advances in open source policy analysis, and for the PSL Foundation, which supports the Library and its community. We are so thankful for all those who have made financial or technical contributions to the PSL this year! In this blog post, I want to take this time at the end of the year to reflect on a few of the highlights from 2022.</p>
+<p><a href="https://policyengine.org">PolicyEngine</a>, a PSL Foundation fiscally-sponsored project, launched <a href="https://policyengine.org/us/policy">PolicyEngine US</a> in April and has since seen many use cases of the model (check out the PolicyEngine year-in-review <a href="https://blog.policyengine.org/policyengine-2022-year-in-review-35984ec3917c">here</a>). PolicyEngine had begun by leveraging the <a href="https://openfisca.org/en/">OpenFisca</a> platform, but has transitioned to their own-maintained <a href="https://policyengine.github.io/policyengine-core/intro.html">PolicyEngine Core</a>. PolicyEngine Core and their related projects (such as <a href="https://policyengine.org/us/policy">PolicyEngine US</a> and <a href="https://policyengine.org/uk">PolicyEngine UK</a>) already meet all the <a href="http://pslmodels.org/Catalog/library_criteria.html">criteria</a> set forth by the Policy Simulation Library. Keep an eye out for lots more excellent tax and benefit policy analysis tools from PolicyEngine in 2023 and beyond!</p>
+<p>PSL Foundation has partnered with <a href="https://quantecon.org">QuantEcon</a>, acting as a fiscal sponsor for their projects that provide training and training materials for economic modeling and econometrics using open source tools. QuantEcon ran a massive open online class in India that had more than 1000 registrants in summer of 2022. They also ran an online course for over 100 students from universities in Africa in 2022. Further, with the funding received through their partnership with PSL Foundation, QuantEcon will continue these efforts in 2023 with a planned, in-person course in India.</p>
+<p>PSL hosted its first in-person workshop in March. The workshop focused on open source tools for tax policy analysis including <a href="https://github.com/PSLmodels/Tax-Calculator/">Tax-Calculator</a>, <a href="https://github.com/PSLmodels/Cost-of-Capital-Calculator/">Cost-of-Capital-Calculator</a>, <a href="https://github.com/PSLmodels/OG-USA">OG-USA</a>, and <a href="https://policyengine.org/us/policy">PolicyEngine US</a>. The PSL event was, appropriately enough, hosted at the MLK Memorial Library in DC. We filled the space with 30 attendees from think tanks, consultancies, and government agencies. The workshop was a great success and we look forward to hosting more in-person workshops in the future.</p>
+<p>PSL’s bi-weekly Demo Day series continued throughout 2022, with 13 Demo Days this year. In these, we saw a wide array of presenters from institutions such as the Federal Reserve Bank of Atlanta, PolicyEngine, Tax Foundation, National Center for Children in Poverty, IZA Institute of Labor Economics, Channels, the University of South Carolina, the Center for Growth and Opportunity, and the American Enterprise Institute. You can go back and rewatch any of these presentations on <a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">YouTube</a>.</p>
+<p>It’s been a fantastic year and we expect even more from the community and PSL Foundation in 2023. PSL community members continue to interact several times each week on our public calls. Check out the <a href="http://pslmodels.org/events">events page</a> and join us in the New Year!</p>
+<p>From all of us at the PSL, best wishes for a happy and healthy New Year!</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://psl-foundation.org">PSL Foundation</a></li>
+<li><a href="https://twitter.com/PSLmodels">PSL Twitter Feed</a></li>
+<li><a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">PSL YouTube channel</a></li>
+<li><a href="https://opencollective.com/psl">PSL on Open Collective</a></li>
+<li><a href="https://pslmodels.org/shop#!/">PSL Shop</a> for PSL branded merchandise</li>
+</ul>
+
+
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+<meta name="dcterms.date" content="2023-12-28">
+<meta name="description" content="Highlights from the Policy Simulation Library in 2023.">
+
+<title>Policy Simulation Library Blog - 2023: A year in review</title>
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+    <div class="quarto-title column-body">
+      <h1 class="title">2023: A year in review</h1>
+                  <div>
+        <div class="description">
+          Highlights from the Policy Simulation Library in 2023.
+        </div>
+      </div>
+                          <div class="quarto-categories">
+                <div class="quarto-category">psl</div>
+                <div class="quarto-category">psl-foundation</div>
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+    
+  
+  <div class="quarto-title-meta">
+
+      <div>
+      <div class="quarto-title-meta-heading">Author</div>
+      <div class="quarto-title-meta-contents">
+               <p>Jason DeBacker </p>
+            </div>
+    </div>
+      
+      <div>
+      <div class="quarto-title-meta-heading">Published</div>
+      <div class="quarto-title-meta-contents">
+        <p class="date">December 28, 2023</p>
+      </div>
+    </div>
+    
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+
+<p><img src="https://pslmodels.org/imgs/PSL.svg" class="img-fluid"></p>
+<hr>
+<p>While there haven’t been any blog posts in 2023 :wink:, it has been a productive year for the Policy Simulation Library (PSL) community and PSL Foundation!</p>
+<p>We’ve continued to serve our mission through education and outreach efforts. We hosted 13 Demo Days in 2023, including presentations from individuals at the Congressional Budget Office, Allegheny County, NOAA, Johns Hopkins, QuantEcon, the City of New York, and other institutions. Archived videos of the Demo Days are available on our <a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">YouTube Channel</a>.</p>
+<p>In addition, we hosted an in person workshop at the National Tax Association’s annual conference in November. This event featured the <a href="https://policyengine.org">PolicyEngine-US</a> project and was lead by Max Ghenis and Nikhil Woodruff, co-founders of PolicyEngine. Attendees included individuals from the local area (Denver) and conference attendees, who represented academia, government, and think tanks. Max and Nikhil provided an overview of PolicyEngine and then walked attendees through a hands-on exercise using the PolicyEngine US tool, having them write code to generate custom plots in a Google Colab notebook. It was a lot of fun – and the pizza was decent too!</p>
+<p>Speaking of <a href="https://policyengine.org">PolicyEngine</a>, this fiscally-sponsored project of PSL Foundation had a banner year in terms of fundraising and development. The group received several grants in 2023 and closed out the year with a large grant from Arnold Ventures. They also wrote an NSF grant proposal which they are waiting to hear back from. The group added an experienced nonprofit executive, <a href="https://www.linkedin.com/in/leigh-gibson-2a260a8/">Leigh Gibson</a>, to their team. Leigh provides support with fundraising and operations, and she’s been instrumental in these efforts. In terms of software development, the PolicyEngine team has been able to greatly leverage volunteers (more than 60!) with <a href="https://www.linkedin.com/in/pavel-makarchuk-170989203/">Pavel Makarchuk</a> coming on as Policy Modeling Manager to help coordinate these efforts. With their community, PolicyEngine has codified numerous US state tax and benefit policies and has developed a robust method to create synthetic data for use in policy analysis. Be on the lookout for a lot more from them in 2024.</p>
+<p><a href="https://quantecon.org">QuantEcon</a>, another fiscally sponsored project, has also made tremendous contributions to open source economics in 2023. Most importantly, they ran a very successful summer school in West Africa. In addition, they have continued make key contributions to software tools useful for teaching and training economics tools. These include Jupyteach, which <a href="https://youtu.be/mJWeY94uKUI?si=-mvv8sbKMbPSwMwH">Spencer Lyon shared in our Demo Day series</a>. With their online materials, textbooks, and workshops around the world, QuantEcon is shaping how researchers and policy analysts employ economic tools to solve real-world problems.</p>
+<p>PSL Foundation added a third fiscally sponsored project, <a href="https://youtu.be/mJWeY94uKUI?si=-mvv8sbKMbPSwMwH">Policy Change Index</a> (PCI) in 2023. PCI was founded by <a href="https://www.weifengzhong.com">Weifeng Zhong</a>, a Senior Research Fellow at the Mercatus Center at George Mason University, and uses natural language processing and machine learning to predict changes in policy among autocratic regimes. PCI has had a very successful start with <a href="https://policychangeindex.org/overview-PCI-China.html">PCI-China</a>, predicting policy changes in China, and <a href="https://policychangeindex.org/overview-PCI-Outbreak.html">PCI-Outbreak</a>, predicting the extent of true COVID-19 case counts in China during the pandemic. Currently, they are extending their work to include predictive indices for Russia, North Korea, and Iran. PSL-F is excited for the opportunity to help support this important work.</p>
+<p>Other cataloged projects have continued to be widely used in 2023. To note a few of these use cases, the United Nations has partnered with Richard Evans and Jason DeBacker, maintainers of <a href="https://pslmodels.github.io/OG-Core/content/intro/intro.html">OG-Core</a>, to help bring the modeling platform to developing countries they are assisting. Tax Foundation’s <a href="https://github.com/TaxFoundation/capital-cost-recovery">Capital Cost Recovery</a> model has been updated to 2023 and used in their widely cited <a href="https://taxfoundation.org/research/all/global/2023-international-tax-competitiveness-index/#:~:text=The%20International%20Tax%20Competitiveness%20Index%20(ITCI)%20seeks%20to%20measure%20the,world%2C%20capital%20is%20highly%20mobile.">2023 Tax Competitiveness Index</a>. And the <a href="taxcalc.pslmodels.org">Tax-Calculator</a> and <a href="https://github.com/PSLmodels/taxdata">TaxData</a> projects both continue to used by think tanks and researchers.</p>
+<p>As 2023 comes to a close, we look forward to 2024. We’ll be launching a new <a href="https://pslmodels.org">PSLmodels.org</a> website soon. And there’ll be many more <a href="http://pslmodels.org/events">events</a> – we hope you join in.</p>
+<p>From all of us at the PSL, best wishes for a happy and healthy New Year!</p>
+<p>Resources:</p>
+<ul>
+<li><a href="https://pslmodels.org">PSL Models</a></li>
+<li><a href="https://psl-foundation.org">PSL Foundation</a></li>
+<li><a href="https://twitter.com/PSLmodels">PSL Twitter Feed</a></li>
+<li><a href="https://www.youtube.com/channel/UCf7WWCuZHs_FFLjuBW4a4_Q">PSL YouTube channel</a></li>
+<li><a href="https://opencollective.com/psl">PSL on Open Collective</a></li>
+<li><a href="https://pslmodels.org/shop#!/">PSL Shop</a> for PSL branded merchandise</li>
+</ul>
+
+
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new file mode 100644
index 0000000..5e2bb32
--- /dev/null
+++ b/psl/psl-foundation/2020/12/23/2020-year-in-review/index.html
@@ -0,0 +1,14 @@
+<html xmlns="http://www.w3.org/1999/xhtml">
+<head>
+  <title>Redirect</title>
+  <script type="text/javascript">
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+    var hash = window.location.hash.startsWith('#') ? window.location.hash.slice(1) : window.location.hash;
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+<body>
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diff --git a/psl/psl-foundation/2021/12/28/2021-year-in-review/index.html b/psl/psl-foundation/2021/12/28/2021-year-in-review/index.html
new file mode 100644
index 0000000..bf1693c
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+++ b/psl/psl-foundation/2021/12/28/2021-year-in-review/index.html
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+<head>
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+<body>
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new file mode 100644
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+<body>
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diff --git a/robots.txt b/robots.txt
old mode 100755
new mode 100644
index 3d7106f..b2b4185
--- a/robots.txt
+++ b/robots.txt
@@ -1 +1 @@
-Sitemap: https://blog.pslmodels.org/sitemap.xml
+Sitemap: https://PSLmodels.github.io/blog/sitemap.xml
diff --git a/search.json b/search.json
new file mode 100644
index 0000000..4b2eeb3
--- /dev/null
+++ b/search.json
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+[
+  {
+    "objectID": "posts/2021-03-02-demo-day-contributing-psl.html",
+    "href": "posts/2021-03-02-demo-day-contributing-psl.html",
+    "title": "Demo Day: Contributing to PSL projects",
+    "section": "",
+    "text": "In the most recent PSL Demo Day, I illustrate how to contribute to PSL projects. The open source nature of projects in the PSL catalog allows anyone to contribute. The modularity of the code, coupled with robust testing, means that one can bite off small pieces that help improve the models and remain confident those changes work as expected.\nTo begin the process of finding where to contribute to PSL projects, I advise looking through the PSL GitHub Organization to see what projects interest you. Once a project of interest is identified, looking over the open “Issues” can provide a sense of where model maintainers and users are looking for help (see especially the “Help Wanted” tags). It is also completely appropriate to create a new Issue to express interest in helping and ask for direction on where that might best be done given your experience and preferences.\nWhen you are ready to begin to contribute to a project, you’ll want to fork and clone the GitHub repository to help you get the files on your local machine and ready for you to work with. Many PSL projects outline the detailed steps to get you up and running. For example, see the Tax-Calculator Contributor Guide, which outlines the step-by-step process for doing this and confirming that everything works as expected on your computer.\nAfter you are set up and ready to begin modifying source code for the PSL project(s) you’re interested in contributing to, you can reference the PSL-incubating Git-Tutorial project that provides more details on the Git workflow followed by most PSL projects.\nAs you contribute, you may want to get more involved in the community. A couple ways to do this are to join any of the PSL community events, all of which are open to the public, and to post to the PSL Discourse Forums. These are great places to meet community members and ask questions about how and where to best contribute.\nI hope this helps you get started as a PSL contributor – we look forward to getting you involved in making policy analysis better and more transparent!\nResources:\n\nPSL Git-Tutorial\nPSL community events\nPSL Discourse Forums\nTax-Calculator Contributor Guide\nPSL GitHub Organization"
+  },
+  {
+    "objectID": "posts/2021-09-20-demo-day-cs-auto-deploy.html",
+    "href": "posts/2021-09-20-demo-day-cs-auto-deploy.html",
+    "title": "Demo Day: Deploying apps on Compute Studio",
+    "section": "",
+    "text": "Compute Studio (C/S) is a platform for publishing and sharing computational models and data visualizations. In this demo day, I show how to publish your own project on C/S using the new automated deployments feature. You can find an in depth guide to publishing on C/S in the developer docs.\nC/S supports two types of projects: models and data visualizations. Models are fed some inputs and return a result. Data visualizations are web servers backed by popular open-source libraries like Bokeh, Dash, or Streamlit. Models are good for long-running processes and producing archivable results that can be shared and returned to easily. Data visualizations are good for highly interactive and custom user experiences.\nNow that you’ve checked out the developer docs and set up your model or data-viz, you can head over to the C/S publishing page https://compute.studio/new/ to publish your project. Note that this page is still very much under construction and may look different in a few weeks.\n\n\n\nPublish page\n\n\nNext, you will be sent to the second stage in the publish flow where you will provide more details on how to connect your project on C/S:\n\n\n\nConnect Project page\n\n\nClicking “Connect App” will take you to the project home page:\n\n\n\nProject home page\n\n\nGo to the “Settings” button in the top-right corner and this will take you to the project dashboard where you can modify everything from the social preview of your project to the amount of compute resources it needs:\n\n\n\nProject dashboard\n\n\nThe “Builds” link in the sidebar will take you to the builds dashboard where you can create your first build:\n\n\n\nBuild history dashboard\n\n\nIt’s time to create the first build. You can do so by clicking “New Build”. This will take you to the build status page. While the build is being scheduled, the page will look like this:\n\n\n\nBuild scheduled page\n\n\nYou can click the “Build History” link and it will show that the build has been started:\n\n\n\nBuild history dashboard\n\n\nThe build status page should be updated at this point and will look something like this:\n\n\n\nBuild status page\n\n\nC/S automated deployments are built on top of Github Actions. Unfortunately, the logs in Github Actions are not available through the Github API until after the workflow is completely finished. The build status dashboard will update as the build progresses and once it’s done, you will have full access to the logs from the build. These will contain outputs from installing your project and the outputs from your project’s tests.\nIn this case, the build failed. We can inspect the logs to see that an import error caused the failure:\n\n\n\nBuild failed status page\n\n\n\n\n\nBuild failed status page with logs\n\n\nI pushed an update to my fork of Tax-Cruncher on Github and restarted the build by clicking “Failure. Start new Build”. The next build succeeded and we can click “Release” to publish the project:\n\n\n\nBuild status page success\n\n\nThe builds dashboard now shows the two builds:\n\n\n\nUpdated build history page\n\n\nFinally, let’s go run our new model:\n\n\n\nRun project page\n\n\nIt may take a few seconds for the page to load. This is because the model code and all of its dependencies are being loaded onto the C/S servers for the first time:\n\n\n\nRun project page with inputs form\n\n\nThe steps for publishing a data visualization are very similar. The main idea is that you tell C/S what Python file your app lives in and C/S will know how to run it given your data visualization technology choice."
+  },
+  {
+    "objectID": "posts/2020-11-06-introducing-psl-blog.html",
+    "href": "posts/2020-11-06-introducing-psl-blog.html",
+    "title": "Introducing the PSL Blog",
+    "section": "",
+    "text": "Our mission at the Policy Simulation Library is to improve public policy by opening up models and data preparation routines for policy analysis. To support and showcase our diverse community of users and developers, we engage across several mediums: a monthly newsletter, a Q&A forum, (now-virtual) meetups, our Twitter feed, our YouTube channel, documentation for models in our catalog, and of course, issues and pull requests on GitHub.\nToday, we’re adding a new medium: the PSL Blog. We’ll use this space to share major updates on our catalog, provide tutorials, and summarize events or papers that involve our models.\nIf you’d like to share your work on our blog, or to suggest content, drop me a line. To follow along, add the PSL blog’s RSS feed or subscribe to our newsletter.\nHappy reading,\nMax Ghenis\nEditor, PSL Blog"
+  },
+  {
+    "objectID": "posts/2020-11-18-demo-day-creating-reform-files.html",
+    "href": "posts/2020-11-18-demo-day-creating-reform-files.html",
+    "title": "Demo Day: Building policy reform files",
+    "section": "",
+    "text": "Check out the video:\n\nWe will host Demo Days every two weeks until the end of the year. You can see our schedule on our events page.\n\nShow notes:\nI demonstrate how to build policy reform files using the Tax-Brain webapp on Compute Studio. (Useful links below.) This is an introductory lesson that ends with a cliffhanger. We don’t run the model. But we do generate an individual income and payroll tax reform file that is compatible with a range of policy simulation models and analytic tools, some designed for policy decision makers, others for taxpayers and benefits recipients interested in assessing their own circumstances.\nBeyond individual and payroll tax analysis, the reform file can be used with models that assess pass-through and corporate taxation of businesses, as well as a variety of income benefit programs. A wide range of use cases will occupy future events.\nResources:\n\nDemo C/S simulation\nIRS Form 1040\nPSL Catalog\nPSL Events"
+  },
+  {
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+    "title": "Demo Day: Stitching together apps on Compute Studio",
+    "section": "",
+    "text": "In Demo Day 8, I talked about connecting multiple apps on Compute Studio with PSL Stitch. The source code for PSL stitch can be found in this repository.\nStitch is composed of three components:\n\nA python package that can be run like a normal Python package.\nA RESTful API built with FastAPI that is called remotely to create simulations on Compute Studio.\nA GUI built with ReactJS that makes calls to the REST API to create and monitor simulations.\n\nOne of the cool things about this app is that it uses ParamTools to read the JSON files under the hood. This means that it can read links to data in other Compute Studio runs, files on GitHub, or just plain JSON. Here are some example parameters:\n\npolicy parameters: cs://PSLmodels:Tax-Brain@49779/inputs/adjustment/policy\ntax-cruncher parameters: {\"sage\": [{\"value\": 25}]}\nbusiness tax parameters: {\"CIT_rate\": [{\"value\": 0.25, \"year\": 2021}]}\n\nAfter clicking run, three simulations will be created on Compute Studio and the app will update as soon as the simulations have finished:\n\n\n\nGetting started\n\n\n\n\n\nCS Simulations\n\n\nOnce they are done, the simulations are best viewed and interacted with on Compute Studio, but you can still inspect the JSON response from the Compute Studio API:\n\n\n\nSimulation Complete\n\n\nI created this app to show that it’s possible to build apps on top of the Compute Studio API. I think PSL Stitch is a neat example of how to do this, but I am even more excited to see what others build next.\nAlso, this is an open source project and has lots of room for improvement. If you are interested in learning web technologies related to REST APIs and frontend development with JavaScript, then this project could be a good place to start!\nResources:\n\nPSL Stitch\nSource code\nCompute Studio API Docs"
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+    "text": "While there haven’t been any blog posts in 2023 :wink:, it has been a productive year for the Policy Simulation Library (PSL) community and PSL Foundation!\nWe’ve continued to serve our mission through education and outreach efforts. We hosted 13 Demo Days in 2023, including presentations from individuals at the Congressional Budget Office, Allegheny County, NOAA, Johns Hopkins, QuantEcon, the City of New York, and other institutions. Archived videos of the Demo Days are available on our YouTube Channel.\nIn addition, we hosted an in person workshop at the National Tax Association’s annual conference in November. This event featured the PolicyEngine-US project and was lead by Max Ghenis and Nikhil Woodruff, co-founders of PolicyEngine. Attendees included individuals from the local area (Denver) and conference attendees, who represented academia, government, and think tanks. Max and Nikhil provided an overview of PolicyEngine and then walked attendees through a hands-on exercise using the PolicyEngine US tool, having them write code to generate custom plots in a Google Colab notebook. It was a lot of fun – and the pizza was decent too!\nSpeaking of PolicyEngine, this fiscally-sponsored project of PSL Foundation had a banner year in terms of fundraising and development. The group received several grants in 2023 and closed out the year with a large grant from Arnold Ventures. They also wrote an NSF grant proposal which they are waiting to hear back from. The group added an experienced nonprofit executive, Leigh Gibson, to their team. Leigh provides support with fundraising and operations, and she’s been instrumental in these efforts. In terms of software development, the PolicyEngine team has been able to greatly leverage volunteers (more than 60!) with Pavel Makarchuk coming on as Policy Modeling Manager to help coordinate these efforts. With their community, PolicyEngine has codified numerous US state tax and benefit policies and has developed a robust method to create synthetic data for use in policy analysis. Be on the lookout for a lot more from them in 2024.\nQuantEcon, another fiscally sponsored project, has also made tremendous contributions to open source economics in 2023. Most importantly, they ran a very successful summer school in West Africa. In addition, they have continued make key contributions to software tools useful for teaching and training economics tools. These include Jupyteach, which Spencer Lyon shared in our Demo Day series. With their online materials, textbooks, and workshops around the world, QuantEcon is shaping how researchers and policy analysts employ economic tools to solve real-world problems.\nPSL Foundation added a third fiscally sponsored project, Policy Change Index (PCI) in 2023. PCI was founded by Weifeng Zhong, a Senior Research Fellow at the Mercatus Center at George Mason University, and uses natural language processing and machine learning to predict changes in policy among autocratic regimes. PCI has had a very successful start with PCI-China, predicting policy changes in China, and PCI-Outbreak, predicting the extent of true COVID-19 case counts in China during the pandemic. Currently, they are extending their work to include predictive indices for Russia, North Korea, and Iran. PSL-F is excited for the opportunity to help support this important work.\nOther cataloged projects have continued to be widely used in 2023. To note a few of these use cases, the United Nations has partnered with Richard Evans and Jason DeBacker, maintainers of OG-Core, to help bring the modeling platform to developing countries they are assisting. Tax Foundation’s Capital Cost Recovery model has been updated to 2023 and used in their widely cited 2023 Tax Competitiveness Index. And the Tax-Calculator and TaxData projects both continue to used by think tanks and researchers.\nAs 2023 comes to a close, we look forward to 2024. We’ll be launching a new PSLmodels.org website soon. And there’ll be many more events – we hope you join in.\nFrom all of us at the PSL, best wishes for a happy and healthy New Year!\nResources:\n\nPSL Models\nPSL Foundation\nPSL Twitter Feed\nPSL YouTube channel\nPSL on Open Collective\nPSL Shop for PSL branded merchandise"
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+    "title": "Demo Day: Modeling taxes and benefits with the PolicyEngine US web app",
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+    "text": "PolicyEngine is a nonprofit that builds free, open-source software to compute the impact of public policy. After launching our UK app in October 2021, we’ve just launched our US app, which calculates households’ federal taxes and several benefit programs, both under current law and under customizable policy reforms.\nIn this Demo Day, I provide background on PolicyEngine and demonstrate how to use PolicyEngine US (a Policy Simulation Library cataloged model) to answer a novel policy question:\n\nHow would doubling both (a) the Child Tax Credit and (b) the Supplemental Nutrition Assistance Program (SNAP) net income limit affect a single parent in California with $1,000 monthly rent and $50 monthly broadband costs?\n\nBy bringing together tax and benefit models into a web interface, we can answer this question quickly without programming experience, as well as an unlimited array of questions like it. The result is a table breaking down the household’s net income by program, as well as graphs of net income and marginal tax rates as the household’s earnings vary.\nI close with a quick demo of PolicyEngine UK, which adds society-wide results like the impact of reforms on the budget, poverty, and inequality, as well as contributed policy parameters. We’re planning to bring those features to PolicyEngine US, along with state tax and benefit programs in all 50 states, over the next two years (if not sooner).\nFeel free to explore the app and reach out with any questions at max@policyengine.org.\nResources:\n\nPolicyEngine US\nPresentation slides\nPolicyEngine blog post on launching PolicyEngine US"
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+    "title": "Demo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator",
+    "section": "",
+    "text": "In the Demo Day video shared here, I show how to use open source tools to analyze international corporate tax competitiveness. The two main tools illustrated are the Cost-of-Capital-Calculator (CCC), a model to compute measures of the tax burden on new investments, and Tax Foundation’s International Tax Competitiveness Index (ITCI).\nTax Foundation has made many helpful resources available online. Their measures of international business tax policy are a great example of this. The ICTI outputs and inputs are all well documented, with source code to reproduce results available on GitHub.\nI plug Tax Foundation’s country-by-country data into CCC functions using it’s Python API. Because CCC is designed to flexibly take array or scalar data, operating on rows of tabular data, such as that in the ITCI, is relatively straight-forward. The Google Colab notebook I walk through in this Demo Day, can be a helpful example to follow if you’d like to do something similar to this with the Tax Foundation data - or your own data source. From the basic building blocks there (reading in data, calling CCC functions), you can extend the analysis in a number of ways. For example adding additional years of data (Tax Foundation posts their data back to 2014), modifying economic assumptions, or creating counter-factual policy experiments across sets of countries.\nIf you find this example useful, or have questions or suggestions about this type of analysis, please feel free to reach out to me.\nResources:\n\nColab Notebook\nTax Foundation International Tax Competitiveness Index 2021\nGitHub repo for Tax Foundation ITCI data\nCost-of-Capital-Calculator documentation"
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+    "text": "The TaxBrain project was primarily created to serve as the backend of the Tax-Brain web-application. But at its core, TaxBrain is a Python package that greatly simplifies tax policy analysis. For this PSL Demo-Day, I demonstrated TaxBrain’s capabilities as a standalone package, and how to use it to produce high-level summaries of the revenue impacts of proposed tax policies. The Jupyter Notebook from the presentation can be found here.\nTaxBrain’s Python API allows you to run a full analysis of income tax policies in just three lines of code:\nfrom taxbrain import TaxBrain\n\ntb = TaxBrain(START_YEAR, END_YEAR, use_cps=True, reform=REFORM_POLICY)\ntb.run()\nWhere START_YEAR and END_YEAR are the first and last years, respectively, of the analysis; use_cps is a boolean indicator that you want to use the CPS-based microdata file prepared for use with Tax-Calculator; and REFORM_POLICY is either a JSON file or Python dictionary that specifies a reform suitable for Tax-Calculator. The forthcoming release of TaxBrain will also include a feature that allows you to perform a stacked revenue analysis as well. The inspiration for this feature was presented by Jason DeBacker in a previous demo-day.\nOnce TaxBrain has been run, there are a number of methods and functions included in the package to create tables and plots to summarize the results. I used the Biden 2020 campaign proposal in the demo and the resulting figures are below. The first is a “volcano plot” that makes it easy to see the magnitude of the change in tax liability individuals across the income distribution face. Each dot represents a tax unit, and the x and y variables can be customized based on the user’s needs.\n\nThe second gives a higher-level look at how taxes change in each income bin. It breaks down what percentage of each income bin faces a tax increase or decrease, and the size of that change.\n\nThe final plot shown in the demo simply shows tax liabilities by year over the budget window.\n\nThe last feature I showed was TaxBrain’s automated reports. TaxBrain uses saved results and an included report template to write a report summarizing the findings of your simulation. The reports include tables and figures similar to what you may find in similar write ups by the Joint Committee on Taxation or Tax Policy Center including a summary of significant changes caused by the reform, and all you need is one line of code:\nreport(tb, name='Biden Proposal', outdir='biden', author='Anderson Frailey')\nThe above code will save a PDF copy of the report in a directory called biden along with PNG files for each of the graphs created and the raw Markdown text used for the report, which you can then edit as needed if you would like to add content to the report that is not already included. Screenshots of the default report are included below.\n    \nThere are of course downsides to using TaxBrain instead of Tax-Calculator directly. Specifically, it’s more difficult, and sometimes impossible, to perform custom tasks like modeling a feature of the tax code that hasn’t been added to Tax-Calculator yet or advanced work with marginal tax rates. But for day-to-day tax modeling, the TaxBrain Python package can significantly simply any workflow.\nResources:\n\nTax-Brain GitHub repo\nTax-Brain Documentation"
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+    "title": "Demo Day: Moving policy reform files from Tax-Brain to Tax-Cruncher",
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+    "text": "Check out the video:\n\n\nShow notes:\nI demonstrate how to move a policy reform file from Tax-Brain to Tax-Cruncher using the Compute.Studio API. See the Demo C/S simulation linked below for text instructions that accompany the video.\nResources:\n\nDemo C/S simulation with instructions"
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+    "text": "As 2021 winds down, I wanted to take a few minutes to reflect on the Policy Simulation Library’s efforts over the past year. With an amazing community of contributors, supporters, and users, PSL has been able to make a real impact in 2021.\nThe library saw two new projects achieve “cataloged” status: Tax Foundation’s Capital Cost Recovery model and the Federal Reserve Bank of New York’s DSGE.jl model. Both models satisfy all the the PSL criteria for transparency and reproducibility. Both are also written entirely in open source software: the Capital Cost Recovery model is in R and the DSGE model in Julia.\nAn exciting new project to join the Library this year is PolicyEngine. PolicyEngine is building open source tax and benefit mircosimulation models and very user-friendly interfaces to these models. The goal of this project is to take policy analysis to the masses through intuitive web and mobile interfaces for policy models. The UK version of the PolicyEngine app has already seen use from politicians interested in reforming the tax and benefit system in the UK.\nAnother excellent new addition to the library is the Federal-State Tax Project. This project provides data imputation tools to allow for state tax data that are representative of each state as well as federal totals. These datasets can then be used in microsimulation models, such as Tax-Calculator to study the impact of federal tax laws across the states. Matt Jensen and Don Boyd have published several pieces with these tools, including in State Tax Notes\nPSL Foundation became an official business entity in 2021. While still awaiting a letter of determination for 501(c)(3) status from the IRS, PSL Foundation was able to raise more than $25,000 in the last few months of 2021 to support open source policy analysis!\nPSL community members continued to interact several times each week in our public calls. The PSL Shop was launched in 2021 so that anyone can get themselves some PSL swag (with some of each purchase going back to the PSL Foundation to support the Library). In addition, PSL hosted 20 Demo Day presentations from 11 different presenters! These short talks covered everything from new projects to interesting applications of some of the first projects to join the Library, as well as general open source tools.\nAs in past years, PSL cataloged and incubating models were found to be of great use in current policy debates. Whether it was the ARPA, Biden administration proposals to expand the CTC, or California’s Basic Income Bill, the accessibility and ability to reproduce results from these open source projects has made them a boon to policy analysts.\nWe are looking forward to a great 2022! We expect the Library to continue to grow, foresee many interesting and helpful Demo Days, and are planning a DC PSL Workshop for March 2022. We hope to see you around these or other events!\nBest wishes from PSL for a happy and healthy New Year!\nResources:\n\nPSL Foundation\nPSL Twitter Feed\nPSL YouTube channel\nPSL on Open Collective"
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+    "text": "Git and GitHub often present themselves as barriers to entry to would-be contributors to PSL projects, even for those who are otherwise experienced with policy modeling. But these tools are critical to collaboration on open source projects. In the Demo Day video linked above, I cover some of the basics to get set up and begin contributing to an open source project.\nThere are four steps I outline:\n\nCreate a “fork” of the repository you are interested in. A fork is a copy of the source code that resides on GitHub (i.e., in the cloud). A fork gives you control over a copy of the source code. You will be able to merge in changes to the code on this fork, even if you don’t have permissions to do so with the original repository.\n“Clone” the fork. Cloning will download a copy of the source code from your fork onto your local machine. But cloning is more than just downloading the source code. It will include the version history of the code and automatically create a link between the local files and the remote files on your fork.\nConfigure your local files to talk to both your fork (which has a default name of origin) and the original repository you forked from (which typically has the default name of upstream). Do this by using your command prompt or terminal to navigate to the directory you just cloned. From there, run:\n\ngit remote add upstream URL_to_original_repo.git\nAnd check that this worked by giving the command:\ngit remote -v\nIf things worked, you should see URLs to your fork and the upstream repository with “(fetch)” and “(push)” by them More info on this is in the Git docs.\n\nNow that you have copies of the source code on your fork and on your local machine, you are ready to begin contributing. As you make changes to the source code, you’ll want to work on development branches. Branches are copies of the code. Ideally, you keep your “main” (or “master”) branch clean (i.e., your best version of the code) and develop the code on branches. When you’ve completed the development work (e.g., adding a new feature) you will them merge this into the “main” branch.\n\nI hope this helps you get started contributing to open source projects. Git and GitHub are valuable tools and there is lots more to learn, but these basics will get you going. For more information, see the links below. If you want to get started working with a project in the Library, feel free to reach out to me through the relevant repo (@jdebacker on GitHub) or drop into a PSL Community Call (dates on the PSL Calendar).\nResources:\n\nPSL Git Tutorial\nGit Basics"
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+    "text": "In this week’s Demo Day, I shared my paper published at the Center for Growth and Opportunity in June. “How does targeted cash assistance affect incentives to work?” analyzed a program Mayor Sumbul Siddiqui proposed in Cambridge, Massachusetts to provide $500 per month for 18 months to all families with dependents and income below 200% of the poverty line.\nTargeted programs like these are common in guaranteed income pilots, and in some enacted policies, and I find that it would cost-effectively reduce poverty: if expanded to Massachusetts, it would cost $1.2 billion per year and cut child poverty 42%.\nHowever, that targeting comes at a cost. Using the OpenFisca US microsimulation model (supported by the Center for Growth and Opportunity and cataloged by the Policy Simulation Library), I find that the program would deepen an existing welfare cliff at 200% of the poverty line. For example, a family of four would lose over $19,000 total—$9,000 from the cash assistance and $10,000 from other benefits—once they earn a dollar above 200% of the poverty line (about $55,000). To recover those lost benefits, they would have to earn an additional $26,000, a range I call the “earnings dead zone”.\nMy presentation reviews these trends in both slides and the PolicyEngine US app for computing the impacts of tax and benefit policy. For example, I show how repealing the SNAP emergency allotment would smooth out welfare cliffs, while reducing resources available to low-income families, and how a universal child allowance avoids work disincentives while less cost-effectively reducing poverty.\nPolicymakers face trade-offs between equity and efficiency, and typically labor supply responses consider marginal tax rates. With their infinite marginal tax rates, welfare cliffs are a less explored area, even though they surface in several parts of the tax and benefit system. This paper makes a start, but more research is yet to be done."
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+    "text": "This has been another successful year for the Policy Simulation Library, whose great community of contributors continue to make innovative advances in open source policy analysis, and for the PSL Foundation, which supports the Library and its community. We are so thankful for all those who have made financial or technical contributions to the PSL this year! In this blog post, I want to take this time at the end of the year to reflect on a few of the highlights from 2022.\nPolicyEngine, a PSL Foundation fiscally-sponsored project, launched PolicyEngine US in April and has since seen many use cases of the model (check out the PolicyEngine year-in-review here). PolicyEngine had begun by leveraging the OpenFisca platform, but has transitioned to their own-maintained PolicyEngine Core. PolicyEngine Core and their related projects (such as PolicyEngine US and PolicyEngine UK) already meet all the criteria set forth by the Policy Simulation Library. Keep an eye out for lots more excellent tax and benefit policy analysis tools from PolicyEngine in 2023 and beyond!\nPSL Foundation has partnered with QuantEcon, acting as a fiscal sponsor for their projects that provide training and training materials for economic modeling and econometrics using open source tools. QuantEcon ran a massive open online class in India that had more than 1000 registrants in summer of 2022. They also ran an online course for over 100 students from universities in Africa in 2022. Further, with the funding received through their partnership with PSL Foundation, QuantEcon will continue these efforts in 2023 with a planned, in-person course in India.\nPSL hosted its first in-person workshop in March. The workshop focused on open source tools for tax policy analysis including Tax-Calculator, Cost-of-Capital-Calculator, OG-USA, and PolicyEngine US. The PSL event was, appropriately enough, hosted at the MLK Memorial Library in DC. We filled the space with 30 attendees from think tanks, consultancies, and government agencies. The workshop was a great success and we look forward to hosting more in-person workshops in the future.\nPSL’s bi-weekly Demo Day series continued throughout 2022, with 13 Demo Days this year. In these, we saw a wide array of presenters from institutions such as the Federal Reserve Bank of Atlanta, PolicyEngine, Tax Foundation, National Center for Children in Poverty, IZA Institute of Labor Economics, Channels, the University of South Carolina, the Center for Growth and Opportunity, and the American Enterprise Institute. You can go back and rewatch any of these presentations on YouTube.\nIt’s been a fantastic year and we expect even more from the community and PSL Foundation in 2023. PSL community members continue to interact several times each week on our public calls. Check out the events page and join us in the New Year!\nFrom all of us at the PSL, best wishes for a happy and healthy New Year!\nResources:\n\nPSL Foundation\nPSL Twitter Feed\nPSL YouTube channel\nPSL on Open Collective\nPSL Shop for PSL branded merchandise"
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+    "text": "Updates from the Policy Simulation Library."
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+    "text": "2023: A year in review\n\n\n\n\n\n\npsl\n\n\npsl-foundation\n\n\n\nHighlights from the Policy Simulation Library in 2023.\n\n\n\n\n\nDec 28, 2023\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\n2022: A year in review\n\n\n\n\n\n\npsl\n\n\npsl-foundation\n\n\n\nHighlights from the Policy Simulation Library in 2022.\n\n\n\n\n\nDec 31, 2022\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: How does targeted cash assistance affect incentives to work?\n\n\n\n\n\n\ndemo-days\n\n\nbenefits\n\n\nus\n\n\n\nHow a proposed program in Cambridge, Massachusetts would affect poverty and incentives.\n\n\n\n\n\nJul 14, 2022\n\n\nMax Ghenis\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Getting Started with GitHub\n\n\n\n\n\n\ndemo-days\n\n\ngithub\n\n\ngit\n\n\nworkflow\n\n\ngetting-started\n\n\n\nThe basics of forking and cloning repositories and working on branches.\n\n\n\n\n\nJun 28, 2022\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Analyzing tax competitiveness with Cost-of-Capital-Calculator\n\n\n\n\n\n\ndemo-days\n\n\ncost-of-capital-calculator\n\n\nbusiness-taxation\n\n\ncorporate-income-tax\n\n\ntaxes\n\n\n\nUsing Cost-of-Capital-Calculator with data on international business tax policies.\n\n\n\n\n\nApr 18, 2022\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Modeling taxes and benefits with the PolicyEngine US web app\n\n\n\n\n\n\ndemo-days\n\n\napps\n\n\ntaxes\n\n\nbenefits\n\n\nus\n\n\n\nPolicyEngine US is a new web app for computing the impact of US tax and benefit policy.\n\n\n\n\n\nApr 12, 2022\n\n\nMax Ghenis\n\n\n\n\n\n\n\n\n\n\n\n\nPolicy Simulation Library DC Workshop: Open source tools for analyzing tax policy\n\n\n\n\n\n\nPSL\n\n\nPSL-Foundation\n\n\nWorkshop\n\n\n\nWashington, DC open-source modeling workshop, March 25, 2022, 8:30am-1:00pm, Martin Luther King, Jr. Memorial Library.\n\n\n\n\n\nMar 3, 2022\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\n2021: A year in review\n\n\n\n\n\n\npsl\n\n\npsl-foundation\n\n\n\nHighlights from the Policy Simulation Library in 2021.\n\n\n\n\n\nDec 28, 2021\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Using synthimpute for data fusion\n\n\n\n\n\n\ndemo-days\n\n\npython\n\n\ndata-fusion\n\n\nsynthimpute\n\n\n\nThe synthimpute Python package fuses and synthesizes economic datasets with machine learning.\n\n\n\n\n\nDec 8, 2021\n\n\nMax Ghenis\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: The OG-Core platform\n\n\n\n\n\n\ndemo-days\n\n\npython\n\n\nmacroeconomics\n\n\noverlapping-generations\n\n\n\nA Python platform for building country-specific overlapping generations general equilibrium models.\n\n\n\n\n\nNov 1, 2021\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Deploying apps on Compute Studio\n\n\n\n\n\n\ndemo-days\n\n\npolicy-simulation-library\n\n\ncompute-studio\n\n\n\nHow to deploy apps on Compute Studio using the new automated deployments feature.\n\n\n\n\n\nSep 20, 2021\n\n\nHank Doupe\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Unit testing for open source projects\n\n\n\n\n\n\ndemo-days\n\n\nR\n\n\nPython\n\n\nunit-testing\n\n\n\nHow to ensure that individual functions do what you expect.\n\n\n\n\n\nAug 9, 2021\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Constructing tax data for the 50 states\n\n\n\n\n\n\ndemo-days\n\n\ntax\n\n\ndata\n\n\nus\n\n\n\nA new dataset to facilitate state-level analysis of federal tax reforms.\n\n\n\n\n\nJul 16, 2021\n\n\nDon Boyd\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Using the TaxBrain Python API\n\n\n\n\n\n\ndemo-days\n\n\nindividual-income-tax\n\n\ntax-brain\n\n\ntax-calculator\n\n\n\nA programmatic interface to compute the impact of tax reform.\n\n\n\n\n\nJun 14, 2021\n\n\nAnderson Frailey\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Updating Jupyter Book documentation with GitHub Actions\n\n\n\n\n\n\ndemo-days\n\n\njupyter-book\n\n\nGH-actions\n\n\ndocumentation\n\n\n\nHow to keep interactive programmatic notebook-based documentation up-to-date in your pull request workflow.\n\n\n\n\n\nMay 17, 2021\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Producing stacked revenue estimates with the Tax-Calculator Python API\n\n\n\n\n\n\ndemo-days\n\n\nindividual-income-tax\n\n\ntax-brain\n\n\ntax-calculator\n\n\n\nHow to evaluate the cumulative effects of a multi-part tax reform.\n\n\n\n\n\nApr 5, 2021\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Stitching together apps on Compute Studio\n\n\n\n\n\n\ndemo-days\n\n\nPSL\n\n\n\nCreating an app with the Compute Studio API.\n\n\n\n\n\nMar 8, 2021\n\n\nHank Doupe\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Moving policy reform files from Tax-Brain to Tax-Cruncher\n\n\n\n\n\n\ndemo-days\n\n\n\nHow to move reforms between a tax-unit-level and society-wide model with the Compute.Studio API.\n\n\n\n\n\nMar 2, 2021\n\n\nMatt Jensen\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Contributing to PSL projects\n\n\n\n\n\n\ndemo-days\n\n\nPSL\n\n\ngit\n\n\ngithub\n\n\n\nHow to help software projects in the Policy Simulation Library.\n\n\n\n\n\nMar 2, 2021\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Running the scf and microdf Python packages in Google Colab\n\n\n\n\n\n\ndemo-days\n\n\nmicrodf\n\n\nscf\n\n\n\nAnalyzing US wealth data in a web-based Python notebook.\n\n\n\n\n\nJan 29, 2021\n\n\nMax Ghenis\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: The OG-USA macroeconomic model of U.S. fiscal policy\n\n\n\n\n\n\ndemo-days\n\n\nOG-USA\n\n\nTax-Calculator\n\n\nopen-source\n\n\npolicy-simulation-library\n\n\ncompute-studio\n\n\nus\n\n\n\nHow to model the macroeconomic effects of tax reform with a web app.\n\n\n\n\n\nJan 28, 2021\n\n\nRichard W. Evans\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Tax-Brain\n\n\n\n\n\n\ndemo-days\n\n\nindividual-income-tax\n\n\ntax-brain\n\n\nus\n\n\n\nComputing the impact of US tax reform with the Tax-Brain web-app.\n\n\n\n\n\nDec 23, 2020\n\n\nAnderson Frailey\n\n\n\n\n\n\n\n\n\n\n\n\n2020: A year in review\n\n\n\n\n\n\npsl\n\n\npsl-foundation\n\n\n\nHighlights from the Policy Simulation Library in 2020.\n\n\n\n\n\nDec 23, 2020\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Cost-of-Capital-Calculator Web Application\n\n\n\n\n\n\ndemo-days\n\n\ncost-of-capital-calculator\n\n\nbusiness-taxation\n\n\ncorporate-income-tax\n\n\n\nComputing the impact of taxes on business investment incentives under alternative policy scenarios.\n\n\n\n\n\nDec 3, 2020\n\n\nJason DeBacker\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Tax-Cruncher\n\n\n\n\n\n\ndemo-days\n\n\nindividual-income-tax\n\n\ntax-cruncher\n\n\n\nHow to calculate a taxpayer’s liabilities under current law and under a policy reform.\n\n\n\n\n\nNov 23, 2020\n\n\nPeter Metz\n\n\n\n\n\n\n\n\n\n\n\n\nDemo Day: Building policy reform files\n\n\n\n\n\n\ndemo-days\n\n\n\nThe first in Policy Simulation Library’s new live demo series describes specifying tax reforms.\n\n\n\n\n\nNov 18, 2020\n\n\nMatt Jensen\n\n\n\n\n\n\n\n\n\n\n\n\nIntroducing the PSL Blog\n\n\n\n\n\n\nannouncements\n\n\n\nA new way to follow models in the Policy Simulation Library catalog.\n\n\n\n\n\nNov 6, 2020\n\n\nMax Ghenis\n\n\n\n\n\n\nNo matching items"
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+    "title": "Policy Simulation Library DC Workshop: Open source tools for analyzing tax policy",
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+    "text": "The Policy Simulation Library is hosting a workshop in Washington, DC on March 25 on open source tools for the analysis of tax policy. Participants will learn how to use open source models from the Library for revenue estimation, distributional analysis, and to simulate economic impacts of tax policy. The workshop is intended to be a hands-on experience and participants can expect to leave with the required software, documentation, and knowledge to continue using these tools. All models in the workshop are written in the Python programming language–familiarity with the language is helpful, but not required.\nWorkshop Schedule:\n\n8:15-8:45a: Breakfast\n8:45-9:00a: Introduction\n9:00-9:50a: Using Tax-Calculator for revenue estimation and distributional analysis (Matt Jensen)\n10:00-10:50a: Estimating effective tax rates on investment with Cost-of-Capital-Calculator (Jason DeBacker)\n11:00-11:50a: Macroeconomic modeling of fiscal policy with OG-Core and OG-USA (Richard W. Evans)\nnoon-1:00p: Lunch and demonstration of PolicyEngine (Max Ghenis)\n\nThe workshop will be held at the Martin Luther King Jr. Memorial Library in Washington, DC. Participants are expected to arrive by 8:30am and the program will conclude at 1:00pm. Breakfast and lunch will be provided. PSL Foundation is sponsoring the event and there is no cost to attend. Attendance is limited to 30 in order to make this a dynamic and interactive workshop.\nTo register, please use this Google Form. Registration will close March 11. Participants will be expected to bring a laptop to the workshop where they can interact with the software in real time with the instructors. Registered participants will receive an email before the event with a list of software to install before the workshop.\nPlease feel free to share this invitation with your colleagues.\nQuestions about the workshop can be directed to Jason DeBacker at jason.debacker@gmail.com."
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+    "title": "Demo Day: Tax-Brain",
+    "section": "",
+    "text": "For this PSL demo-day I showed how to use the Tax-Brain web-application, hosted on Compute Studio, to analyze proposed individual income tax policies. Tax-Brain integrates the Tax-Calculator and Behavioral-Responses models to make running both static and dynamic analyses of the US federal income and payroll taxes simple. The web interface for the model makes it possible for anyone to run their own analyses without writing a single line of code.\nWe started the demo by simply walking through the interface and features of the web-app before creating our own sample reform to model. This reform, which to my knowledge does not reflect any proposals currently up for debate, included changes to the income and payroll tax rates, bringing back personal exemptions, modifying the standard deduction, and implementing a universal basic income.\nWhile the model ran, I explained how Tax-Brain validated all of the user inputs, the data behind the model, and how the final tax liability projections are determined. We concluded by looking through the variety of tables and graphs Tax-Brain produces and how they can easily be shared with others.\nResources:\n\nSimulation from the demonstration\nTax-Brain GitHub repo\nTax-Calculator documentation\nBehavioral-Responses documentation"
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+    "title": "Demo Day: The OG-Core platform",
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+    "text": "The OG-Core model is a general equilibrium, overlapping generations (OG) model suitable for evaluating fiscal policy. Since the work of Alan Auerbach and Laurence Kotlikoff in the 1980s, this class of model has become a standard in the macroeconomic analysis of tax and spending policy. This is for good reason. OG models are able to capture the impacts of taxes and spending in the short and long run, examine incidence of policy across generations of people (not just short run or steady state analysis of a cross-section of the economy), and capture important economic dynamics (e.g., crowding out effects of deficit-financed policy).\nIn the PSL Demo Day presentation linked above, I cover the basics of OG-Core: its history, its API, and how country-specific models can use OG-Core as a dependency. In brief, OG-Core provides a general overlapping generations framework, from which parameters can be calibrated to represent particular economies. Think of it this way: an economic model is just a set of parameters plus a system of equations. OG-Core spells out all of the equations to represent an economy with heterogeneous agents, production and government sectors, open economy options, and detailed policy rules. OG-Core also includes default values for all parameters, along with parameter metadata and parameter validation rules. A country specific application is then just a particular parameterization of the general OG-Core model.\nAs an example of a country-specific application, one can look at the OG-USA model. This model provides a calibration of OG-Core to the United States. The source code in that project allows one to go from raw data sources to the estimation and calibration procedures used to determine parameter values representing the United States, to parameter values in formats suitable for use in OG-Core. Country-specific models like OG-USA include (where available) links to microsimulation models of tax and spending programs to allow detailed microdata of actual and counterfactual policies to inform the net tax-transfer functions used in the OG-Core model. For those interested in building their own country-specific model, the OG-USA project provides a good example to work from.\nWe encourage you to take a look at OG-Core and related projects. New contributions and applications are always welcome. If you have questions or comments, reach out through the relevant repositories on Github to me, @jdebacker, or Rick Evans, @rickecon.\nResources:\n\nOG-Core documentation\nOG-USA documentation package for unit testing in Python\nTax-Calculator documentation\nOG-UK repository\nOpenFisca-UK repository\nSlides from the Demo Day presentation"
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+    "title": "Demo Day: Cost-of-Capital-Calculator Web Application",
+    "section": "",
+    "text": "In the PSL Demo Day video linked above, I demonstrate how to use the Cost-of-Capital-Calculator (CCC) web application on Compute-Studio. CCC computes various measures of the impact of the tax system on business investment. These include the Hall-Jorgenson cost of capital, marginal effective tax rates, and effective average tax rates (following the methodology of Devereux and Griffith (1999)).\nI begin by illustrating the various parameters available for the user to manipulate. These include parameters of the business and individual income tax systems, as well as parameters representing economic assumptions (e.g., inflation rates and nominal interest rates) and parameters dictating financial and accounting policy (e.g., the fraction of financing using debt). Note that all default values for tax policy parameters represent the “baseline policy”, which is defined as the current law policy in the year being analyzed (which itself is a parameter the user can change). Other parameters are estimated using historical data following the methodology of CBO (2014).\nNext, I change a few parameters and run the model. In this example, I move the corporate income tax rate up to 28% and lower bonus depreciation for assets with depreciable lives of 20 years or less to 50%.\nFinally, I discuss how to interpret output. The web app returns a table and three figures summarizing marginal effective total tax rates on new investments. This selection of output helps give one a sense of the the overall changes, as well as effects across asset types, industries, and type of financing. For the full model output, one can click on “Download Results”. Doing so will download four CSV files contain several measures of the impact of the tax system on investment for very fine asset and industry categories. Users can take these files and create tables and visualizations relevant to their own use case.\nPlease take the model for a spin and simulate your own reform. If you have questions, comments, or suggestions, please let me know on the PSL Discourse (non-technical questions) or by opening an issue in the CCC GitHub repository (technical questions).\nResources:\n\nCompute Studio simulation used in the demonstration\nCost-of-Capital-Calculator web app\nCost-of-Capital-Calculator documentation\nCost-of-Capital-Calculator GitHub repository"
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+    "title": "Demo Day: Tax-Cruncher",
+    "section": "",
+    "text": "For the Demo Day on November 16, I showed how to calculate a taxpayer’s liabilities under current law and under a policy reform with Tax-Cruncher. The Tax-Cruncher web application takes two sets of inputs: a taxpayer’s demographic and financial information and the provisions of a tax reform.\nFor the first Demo Day example (3:50), we looked at how eliminating the state and local tax (SALT) deduction cap and applying payroll tax to earnings above $400,000 would affect a high earner. In particular, our hypothetical filer had $500,000 in wages, $100,000 in capital gains, and $100,000 in itemizable expenses. You can see the results at Compute Studio simulation #634.\nFor the second example (17:50), we looked at how expanding the Earned Income Tax Credit (EITC) and Child Tax Credit would impact a family with $45,000 in wages and two young children. You can see the results at Compute Studio simulation #636.\nResources:\n\nTax-Cruncher\nTax-Cruncher-Biden"
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+    "title": "Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy",
+    "section": "",
+    "text": "In this PSL Demo Day, I demonstrate how to use the open source OG-USA macroeconomic model of U.S. fiscal policy. Jason DeBacker and I (Richard Evans) have been the core maintainers of this project and repository for the last six years. This demo is organized into the following sections. The YouTube webinar linked above took place on January 11, 2021."
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+    "title": "Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy",
+    "section": "Brief note about the value of the PSL community",
+    "text": "Brief note about the value of the PSL community\nThe Policy Simulation Library is a decentralized organization of open source policy models. The Policy Simulation Library GitHub organization houses many open source repositories, each of which represents a curated policy project by a diverse group of maintainers. The projects that have met the highest standards of best practices and documentation are designated as psl-cataloged , while newer projects that are in earlier stages are designated as psl-incubating . The philosophy and goal of the PSL environment is to make policy modeling open and transparent. It also allows more collaboration and cross-project contributions and interactions.\nThe Policy Simulation Library group has been holding these PSL Demo Day webinars since the end of 2020. The video of each webinar is available on the Policy Simulation Library YouTube channel. These videos are a great resource for learning the different models available in the PSL community, how the models interact, how to contribute to them, and what is on the horizon in their development. Also excellent in many of the PSL Demo Day webinars is a demonstration of how to use the models on the Compute Studio web application platform.\nI have been a participant in and contributor to the PSL community since its inception. I love economic policy modeling. And I learned how sophisticated and complicated economic policy models can be. And any simulation can have hundreds of underlying assumptions, some of which may not be explicitly transparent. I think models that are used for public policy analysis have a philosophical imperative to be open source. This allows others to verify results and test sensitivity to assumptions.\nAnother strong benefit of open source modeling is that it is fundamentally apolitical. With proprietary closed-source policy models, an outside observer might criticize the results of the model based on the perceived political biases of the modeler or the sponsoring organization. With open-source models, a critic can be redirected to the underlying assumptions, structure, and content of the model. This is constructive criticism and debate that moves the science foreward. In the current polarized political environment in the U.S., open-source modeling can provide a constructive route for bipartisan cooperation and the democratization of computational modeling. Furthermore, open-source modeling and workflow encourages the widest forms of collaboration and contributions."
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+    "title": "Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy",
+    "section": "Description of OG-USA model",
+    "text": "Description of OG-USA model\nOG-USA is an open-source overlapping generations, dynamic general equilibrium, heterogeneous agent, macroeconomic model of U.S. fiscal policy. The GitHub repository for the OG-USA source code is github.com/PSLmodels/OG-USA. This repository contains all the source code and instructions for loading and running OG-USA and all of its dependencies on your local machine. We will probably do another PSL Demo Day on how to run OG-USA locally. This Demo Day webinar is about running OG-USA on the Compute Studio web application. See Section “Using OG-USA on Compute.Studio” below.\nAs a heterogeneous agent macroeconomic model, OG-USA allows for distributional analyses at the individual and firm level. That is, you can simulate the model and answer questions like, “How will an increase in the top three personal income tax rates affect people of different ages and income levels?” Microsimulation models can answer these types of distributional analysis questions as well. However, the difference between a macroeconomic model and a microsimulation model is that the macroeconomic models can simulate how each of those individuals and firms will respond to a policy change (e.g., lower labor supply or increased investment demand) and how those behavioral responses will add up and feed back into the macroeconomy (e.g., the effect on GDP, government revenue, government debt, interest rates, and wages).\nOG-USA is a large-scale model and comprises tens of thousands of lines of code. The status of all of this code being publicly available on the internet with all collaboration and updates also public makes this an open source project. However, it is not enough to simply post one’s code. We have gone to great lengths to make in-line comments or “docstring” in the code to clarify the purpose of each function and line of code. For example, look in the OG-USA/ogusa/household.py module. The first function on line 18 is the marg_ut_cons() function. As is described in its docstring, its purpose is to “Compute the marginal utility of consumption.”\nThese in-code docstrings are not enough. We have also created textbook style OG-USA documentation at pslmodels.github.io/OG-USA/ using the Jupyter Book medium. This form of documentation has the advantage of being in book form and available online. It allows us to update the documentation in the open-source repository so changes and versions can be tracked. It describes the OG-USA API, OG-USA theory, and `OG-USA calibration. As with the model, this documentation is always a work in progress. But being open-source allows outside contributors to help with its updated and error checking.\nOne particular strength of the OG-USA model I want to highlight is its interaction with microsimulation models to incorporate information about tax incentives faced by the heterogeneous households in the model. We have interfaced OG-USA with microsimulation models in India and in the European Commission. OG-USA ’s default for modeling the United States is to use the open-source Tax-Calculator microsimulation model, which was described by Anderson Frailey in the last Demo Day of 2020. However, DeBacker and I currently have a project in which we use OG-USA to simulate policies using the Tax Policy Center’s microsimulation model. The way OG-USA interfaces with microsimulation models to incorporate rich tax data is described in the documentation in the calibration chapter entitled, “Tax Functions”."
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+    "title": "Demo Day: The OG-USA macroeconomic model of U.S. fiscal policy",
+    "section": "Using OG-USA on Compute Studio",
+    "text": "Using OG-USA on Compute Studio\nIn the demonstration, I focus on how to run experiments and simulations with OG-USA using the Compute Studio web application platform rather than installing running the model on your local machine. To use OG-USA on this web application, you will need a Compute Studio account. Once you have an account, you can start running any model available through the site. For some models, you will have to pay for the compute time, although the cost of running these models is very modest. However, all Compute Studio simulations of the OG-USA model are currently sponsored by the Open Source Economics Laboratory. This subsidy will probably run out in the next year. But we are always looking for funding for these models.\nOnce you are signed up and logged in to your Compute Studio account, you can go to the OG-USA model on Compute Studio at compute.studio/PSLmodels/OG-USA. The experiment that we simulated in the demonstration is available at compute.studio/PSLmodels/OG-USA/206. The description at the top of the simulation page describes the changes we made. You can look through the input page by clicking on the “Inputs” tab. We ran the model by clicking the green “Run” button at the lower left of the page. The model took about 5 hours to run, so I pre-computed the results that we discussed in the demo. The outputs of the experiment are available in the “Outputs” tab on the page. I also demonstrated how one can click the “Download Results” button at the bottom of the “Outputs” tab to download more results from the simulation. However, the full set of results is only available by installing and running the OG-USA model simulation on your local machine.\nThe benefits of the Compute Studio web application are that running the OG-USA model is much easier for the non-expert, and the multiple-hour computation time can be completed on a remote machine in the cloud."
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+    "text": "Resources\n\nPSL Demo Day YouTube webinar: “How to use OG-USA”\nOG-USA on Compute Studio\nSimulation from the demonstration\nOG-USA GitHub repo\nOG-USA documentation\nTax-Calculator GitHub repo"
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+    "title": "Demo Day: Using synthimpute for data fusion",
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+    "text": "Suppose a policy analyst sought to estimate the impact of a policy that changed income tax rates and benefit rules while also adding a progressive wealth tax. The standard approach is to use a microsimulation model, where the rules are programmed as code, and then to run that program over a representative sample of households. Unfortunately, no single US government survey captures all the households characteristics needed to analyze this policy; in particular, the reliable tax and benefit information lies in surveys like the Current Population Survey (CPS), while wealth lies in the Survey of Consumer Finances (SCF).\nAssuming the analyst wanted to start with the CPS, they have several options to estimate wealth for households to levy the progressive wealth tax. Two typical approaches include:\n\nLinear regression, predicting wealth from other household characteristics common to the CPS and SCF.\nMatching, in which each CPS household is matched with the most similar household in the SCF.\n\nNeither of these approaches, however, aim to estimate the distribution of wealth conditional on other characteristics. Linear regression explicitly estimates the mean prediction, but that could miss the tails of wealth from whom most of the wealth tax revenue will be collected.\nInstead, the analyst could apply quantile regression to estimate the distribution of wealth conditional on other characteristics, and then measure the effectiveness of the estimation using quantile loss.\nIn this Demo Day, I present the concepts of microsimulation, imputation, and quantile loss to motivate the synthimpute Python package I’ve developed with my PolicyEngine colleague Nikhil Woodruff. In an experiment predicting wealth on a holdout set from the SCF, my former colleague Deepak Singh and I found that random forests significantly outperform OLS and matching for quantile regression, and this is the approach applied in synthimpute for both data fusion and data synthesis. The synthimpute API will be familiar to users of scikit-learn and statsmodels , with the difference being that synthimpute ’s rf_impute function returns a random value from the predicted distribution; it can also skew the predictions to meet a target total.\nWe’ve used synthimpute to fuse data for research reports at the UBI Center and to enhance the PolicyEngine web app for UK tax and benefit simulation, and we welcome new users and contributors. Feel free to explore the repository or contact me with questions at max@policyengine.org.\nResources:\n\nsynthimpute package on GitHub\nPresentation slides\nUBI Center report on land value taxation in the UK, using synthimpute to impute land value from the UK Wealth and Assets Survey to the Family Resources Survey\nPolicyEngine UK carbon tax example, using synthimpute to impute carbon emissions from the Living Costs and Food Survey to the Family Resources Survey\nNotebook comparing random forests to matching and other techniques using a holdout set from the US Survey of Consumer Finances\nMy blog post on quantile regression for Towards Data Science, which laid the groundwork for synthimpute"
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+    "title": "Demo Day: Producing stacked revenue estimates with the Tax-Calculator Python API",
+    "section": "",
+    "text": "It’s often useful to be able to identify the effects of specific provisions individually and not just the overall impact of a proposal with many provisions. Indeed, when revenue estimates of tax law changes are reported (such as this JCT analysis of the American Rescue Plan Act of 2021), they are typically reported on a provision-by-provision basis. Finding the provision-by-provision revenue estimates is cumbersome with the Tax-Brain web application both because it’s hard to iterate over many provisions and because the order matters when stacking estimates, so that one needs to keep this order in mind as parameter values are updated for each additional provision in a full proposal.\nIn the PSL Demo Day on April 5, 2021, I show how to use the Python API of Tax-Calculator to efficiently produce stacked revenue estimates. In fact, after some initial setup, this can be done with just 12 lines of code (plus a few more to make the output look nice). The Google Colab notebook that illustrates this approach can be found at this link, but here I’ll walk through the four steps that are involved:\n\nDivide up the full proposal into strings of JSON text that contain each provision you want to analyze. My example breaks up the Biden 2020 campaign proposal into seven provisions, but this is illustrative and you can make more or less provisions depending on the detail you would like to see.\nCreate a dictionary that contains, as its values, the JSON strings. A couple notes on this. First, the dictionary keys should be descriptive of the provisions as they will become the labels for each provision in the final table of revenue estimates we produce. Second, order matters here. You’ll want to be sure the current law baseline is first (the value for this will be an empty dictionary). Then you specify the provisions. The order you specify will likely affect your revenue estimates from a given provision (for instance, expanding/restricting a deduction has a larger revenue effect when rates are higher), but there are not hard and fast rules on the “right” order. Traditionally, rate changes are stacked first and tax expenditures later in the order.\nIterate over this dictionary. With a dictionary of provisions in hand, we can write a “for loop” to iterate over the provision, simulating the Tax-Calculator model at each step. Note that when the Policy class object in Tax-Calculator is modified, it only needs to be told the changes in tax law parameters relative to its current state. In other words, when we are stacking provisions, estimating the incremental effect of each, you can think of the Policy object having a baseline policy that is represented by the current law baseline plus all provisions that have been analyzed before the provision at the current iteration. The Policy class was created in this way so that one can easily represent policy changes, requiring the user to only input the set of parameters that are modified, not every single parameter’s value under the hypothetical policy. But this also makes it parsimonious to stack provisions as we are doing here. Notice that the JSON strings for each provision (created in Step 1) can be specified independent of the stacking order. We only needed to slice the full set of proposals into discrete chunks, we didn’t need to worry about creating specifications of cumulative policy changes.\nFormat output for presentation. After we’ve run a Tax-Calculator simulation for the current law baseline plus each provision (and each year in the budget window), we’ve got all the output we need. With this output, we can quickly create a table that will nicely present our stacked revenue estimate. One good check to do here is to create totals across all provisions and compare this to the simulated revenue effects of running the full set of proposals in one go. This check helps to ensure that you didn’t make an error in specifying your JSON strings. For example, it’s easy to leave out one or more provisions, especially if there are many.\n\nI hope this provides a helpful template for your own analysis. Note that one can modify this code in several useful ways. For example, within the for-loops, the Behavioral-Responses can be called to produce revenue estimates that take into account behavioral feedback. Or one could store the individual income tax and payroll tax revenue impacts separately (rather than return the combined values as in the example notebook). Additional outputs (even the full set of microdata after each provision is applied) can be stored for even more analysis.\nIn the future, look for Tax-Brain to add stacked revenue estimates to its capabilities. It’ll still be important for users to carve up their full list of policy changes into sets of provisions as we did in Steps 1 and 2 above, but Tax-Brain will then take care of the rest behind the scenes.\nResources:\n\nColab Notebook with example\nBiden campaign reform file in PSL Examples"
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+    "title": "2020: A year in review",
+    "section": "",
+    "text": "This year has been one to forget! But 2020 did have its bright spots, especially in the PSL community. This post reviews some of the highlights from the year.\nThe Library was able to welcome two new models to the catalog in 2020: microdf and OpenFisca-UK. microdf provides a number of useful tools for use with economic survey data. OpenFisca-UK builds off the OpenFisca platform, offering a microsimulation model for tax and benefit programs in the UK.\nIn addition, four new models were added to the Library as incubating projects. The ui-calculator model has received a lot of attention this year in the U.S., as it provides the capability to calculate unemployment insurance benefits across U.S. states, a major mode of delivering financial relief to individuals during the COVID crisis. PCI-Outbreak directly relates to the COVID crisis, using machine learning and natural language processing to estimate the true extent of the COVID pandemic in China. The model finds that actual COVID cases are significantly higher than what official statistics claim. The COVID-MCS model considers COVID case counts and test positivity rates to measure whether or not U.S. communities are meeting certain benchmarks in controlling the spread of the disease. On a lighter note, the Git-Tutorial project provides instruction and resources for learning to use Git and GitHub, with an emphasis on the workflow used by many projects in the PSL community.\nThe organization surrounding the Policy Simulation Library has been bolstered in two ways. First, we have formed a relationship with the Open Collective Foundation, who is now our fiscal host. This allows PSL to accept tax deductible contributions that will support the efforts of the community. Second, we’ve formed the PSL Foundation, with an initial board that includes Linda Gibbs, Glenn Hubbard, and Jason DeBacker.\nOur outreach efforts have grown in 2020 to include the regular PSL Demo Day series and this PSL Blog. Community members have also presented work with PSL models at the PyData Global Conference, the Tax Economists Forum, AEI, the Coiled Podcast, and the Virtual Global Village Podcast. New users will also find a better experience learning how to use and contribute to PSL models as many PSL models have improved their documentation through the use of Jupyter Book (e.g., see the Tax-Calculator documentation).\nWe love seeing the community around open source policymaking expand and are proud that PSL models have been used for important policy analysis in 2020, including analyzing economic policy responses to the pandemic and the platforms of presidential candidates. We look forward to more progress in 2021 and welcome you to join the effort as a contributor, financially or as an open source developer.\nBest wishes from PSL for a happy and healthy new year!\nResources:\n\nPSL Twitter Feed\nPSL YouTube\nPSL on Open Collective"
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+    "href": "posts/2021-05-17-demo-day-jupyter-book-deploy.html",
+    "title": "Demo Day: Updating Jupyter Book documentation with GitHub Actions",
+    "section": "",
+    "text": "Open source projects must maintain clear and up-to-date documentation in order to attract users and contributors. Because of this, PSL sets minimum standards for documentation among cataloged projects in its model criteria. A recent innovation in executable books, Jupyter Book, has provided an excellent format for model documentation and has been widely adopted by PSL projects (see for example OG-USA, Tax-Brain, Tax-Calculator).\nJupyter Book allows one to write documents with executable code and text together, as in Jupyter notebooks. But Jupyter Book pushes this further by allowing documents with multiple sections, better integration of TeX for symbols and equations, BibTex style references and citations, links between sections, and Sphinx integration (for auto-built documentation of model APIs from source code). Importantly for sharing documentation, Jupyter Books can easily be compiled to HTML, PDF, or other formats. Portions of a Jupyter Book that contain executable code can be downloaded as Jupyter Notebooks or opened in Google Colab or binder\nThe Jupyter Book documentation is excellent and will help you get started creating your “book” (tip: pay close attention to formatting details, including proper whitespace). What I do here is outline how you can easily deploy your documentation to the web and keep it up-to-date with your project.\nI start from the assumption that you have the source files to build your Jupyter Book checked into the main branch of your project (these maybe yml , md , rst , ipynb or other files). For version control purposes and to keep your repo trim, you generally don’t want to check the built documentation files to this branch (tip: consider adding the folder these files will go to (e.g., /_build to your .gitignore ). When these files are in place and you can successfully build your book locally, it’s time for the first step.\nStep 1: Add two GH Actions to your project’s workflow: 1. An action to check that your documentation files build without an error. I like to run this on each push to a PR. The action won’t hang on warnings, but will fail if your Jupyter Book doesn’t build at all. An example of this action from the OG-USA repo is here:\n\nname: Check that docs build\non: [push, pull_request]\n\njobs:\n  build:\n    runs-on: ubuntu-latest\n    steps:\n      - name: Checkout\n        uses: actions/checkout@v2 # If you're using actions/checkout@v2 you must set persist-credentials to false in most cases for the deployment to work correctly.\n        with:\n          persist-credentials: false\n\n      - name: Setup Miniconda\n        uses: conda-incubator/setup-miniconda@v2\n        with:\n          activate-environment: ogusa-dev\n          environment-file: environment.yml\n          python-version: 3.7\n          auto-activate-base: false\n\n      - name: Build # Build Jupyter Book\n        shell: bash -l {0}\n        run: |\n          pip install jupyter-book\n          pip install sphinxcontrib-bibtex==1.0.0\n          pip install -e .\n          cd docs\n          jb build ./book\nTo use this in your repo, you’ll just need to change a few settings such as the name of the environment and perhaps the Python version and path to the book source files. Note that in the above yml file sphinxcontrib-bibtex is pinned. You maybe able to unpin this, but OG-USA needed this pin for documentation to compile property due to changes in the jupyter-book and sphinxcontrib-bibtex packages.\n\nAn action that builds and deploys the Jupyter Book to GH Pages. The OG-USA project uses the deploy action from James Ives in this action. This is something that you will want to run when PRs are merged into your main branch so that the documentation is kept up-to-date with the project. To modify this action for your repo, you’ll need to change the repo name, the environment name, and potentially the Python version, branch name, and path to the book source files.\n\nStep 2: Once the action in (2) above is run, your compiled Jupyter Book docs will be pushed to a gh-pages branch in your repository (the action will create this branch for you if it doesn’t already exist). At this point, you should be able to see your docs at the url https://GH_org_name.github.io/Repo_name . But it probably won’t look very good until you complete this next step. To have your Jupyter Book render on the web as you see it on your machine, you will want to push and merge an empty file with the name .nojekyll into your repo’s gh-pages branch.\nThat’s it! With these actions, you’ll be sure that your book continues to compile and a new version will be published to the web with with each merge to your main branch, ensuring that your documentation stays up-to-date.\nSome additional tips:\n\nUse Sphinx to document your projects API. By doing so you’ll automate an important part of your project’s documentation – as long as the docstrings are updated when the source code is, the Jupyter Book you are publishing to the web will be kept in sync with no additional work needed.\nYou can have your gh-pages-hosted documentation point to a custom URL.\nProject maintainers should ensure that docs are updated with PRs that are relevant (e.g., if the PR changes an the source code affecting a user interface, then documentation showing example usage should be updated) and help contributors make the necessary changes to the documentation source files."
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+    "href": "posts/2021-07-16-demo-day-constructing-tax-data-for-the-50-states.html",
+    "title": "Demo Day: Constructing tax data for the 50 states",
+    "section": "",
+    "text": "Federal income tax reform impacts can vary dramatically across states. The cap on state and local tax deductions (SALT) is a well-known example, but other policies also have differential effects because important tax-relevant features vary across states such as the income distribution, relative importance of wage, business, and retirement income, and family size and structure. Analyzing how policy impacts vary across states requires data that faithfully represent the characteristics of the 50 states.\nThis Demo Day described a method and software for constructing state weights for microdata files that (1) come as close as possible to targets for individual states, while (2) ensuring that the state weights for each tax record sum to its national weight. The latter objective ensures that the sum of state impacts for a tax reform equals the national impact.\nThis project developed state weights for a data file with more than 200,000 microdata records. The weighted data file comes within 0.01% of desired values for more than 95% of approximately 10,000 targets.\nThe goal of the slides and video was to enable a motivated Python-skilled user of the PSL TaxData and Tax-Calculator projects to reproduce project results: 50-state weights for TaxData’s primary output, the puf.csv microdata file (based primarily on an IRS Public Use File), using early-stage open-source software developed in the project. Thus, the demo is technical and focused on nuts and bolts.\nThe methods and software can also be used to:\n\nCreate geographic-area weights for other microdata files\nApportion state weights to Congressional Districts or counties, if suitable targets can be developed\nCreate state-specific microdata files suitable for modeling state income taxes\n\nThe main topics covered in the slides and video are:\n\nCreating national and state targets from IRS summary data\nPreparing a national microdata file for state weighting\nApproaches to constructing geographic weights\nRunning software that implements the Poisson-modeling approach used in the project\nMeasures of quality of the results"
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+    "objectID": "posts/2021-01-29-demo-day-scf-microdf.html",
+    "href": "posts/2021-01-29-demo-day-scf-microdf.html",
+    "title": "Demo Day: Running the scf and microdf Python packages in Google Colab",
+    "section": "",
+    "text": "For Monday’s PSL Demo Day, I showed how to use the scf and microdf PSL Python packages from the Google Colab web-based Jupyter notebook interface.\nThe scf package extracts data from the Federal Reserve’s Survey of Consumer Finances, the canonical source of US wealth microdata. scf has a single function: load(years, columns) , which then returns a pandas DataFrame with the specified column(s), each record’s survey weight, and the year (when multiple years are requested).\nThe microdf package analyzes survey microdata, such as that returned by the scf.load function. It offers a consistent paradigm for calculating statistics like means, medians, sums, and inequality statistics like the Gini index. Most functions are structured as follows: f(df, col, w, groupby) where df is a pandas DataFrame of survey microdata, col is a column(s) name to be summarized, w is the weight column, and groupby is the column(s) to group records in before summarizing.\nUsing Google Colab, I showed how to use these packages to quickly calculate mean, median, and total wealth from the SCF data, without having to install any software or leave the browser. I also demonstrated how to use the groupby argument of microdf functions to show how different measures of wealth inequality have changed over time. Finally, I previewed some of what’s to come with scf and microdf : imputations, extrapolations, inflation, visualization, and documentation, to name a few priorities.\nResources:\n\nSlides\nDemo notebook in Google Colab\nSimulation from the demonstration\nscf GitHub repo\nmicrodf GitHub repo\nmicrodf documentation"
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+    "objectID": "posts/2021-08-09-demo-day-unit-testing.html",
+    "href": "posts/2021-08-09-demo-day-unit-testing.html",
+    "title": "Demo Day: Unit testing for open source projects",
+    "section": "",
+    "text": "Unit testing is the testing of individual units or functions of a software application. This differs from regression testing that focuses on the verification of final outputs. Instead, unit testing tests each smallest testable component of your code. This helps to more easily identify and trace errors in the code.\nWriting unit tests is good practice, though not one that’s always followed. The biggest barrier to writing unit tests is that doing so takes time. You might wonder “why am I testing code that runs?” But there are a number benefits to writing unit tests:\n\nIt ensures that the code does what you expect it to do\nYou’ll better understand what your code is doing\nYou will reduce time tracking down bugs in your code\n\nOften, writing unit tests will save you time in the longer run because it reduces debugging time and because it forces you to think more about what your code does, which often leads to the development of more efficient code. And for open source projects, or projects with many contributors, writing unit tests is important in reducing the likelihood that errors are introduced into your code. This is why the PSL catalog criteria requires projects to provide at least some level of unit testing.\nIn the PSL Demo Day video linked above, I illustrate how to implement unit tests in R using the testthat package. There are essentially three steps to this process:\n\nCreate a directory to put your testing script in, e.g., a folder called tests\nCreate one or more scripts that define your tests.\n\nEach test is represented as a call of the test_that function and contain an statement that will evaluate as true or false (e.g., you may use the expect_equal function to verify that a function returns expected values given certain inputs).\nYou will want to use test in the name of these tests scripts as well as something descriptive of what is tested.\n\nCreate a script that will run your tests.\n\nHere you’ll need to import the testthat package and you’ll need to call the script(s) you are testing to load their functions.\nThen you’ll use the test_dir function to pass the directory in which the script(s) you created in Step 2 reside.\n\n\nCheck out the video to see examples of how each of these steps is executed. I’ve also found this blog post on unit tests with testthat to be helpful.\nUnit testing in Python seems to be more developed and straightforward with the excellent pytest package. While pytest offers many options for parameterizing tests, running tests in parallel, and more, the basic steps remain the same as those outlined above:\n\nCreate a directory for your test modules (call this folder tests as pytest will look for that name).\nCreate test modules that define each test\n\nTests are defined much like any other function in Python, the but will involve some assertion statement is triggered upon test failure.\nYou will want to use test in the name of these tests modules as well as something descriptive of what is tested.\n\nYou won’t need to create a script to run your tests as with testthat, but you may create a pytest.ini file to customize your tests options.\n\nThat’s about it to get started writing unit tests for your code. PSL cataloged projects provide many excellent examples of a variety of unit tests, so search them for examples to build from. In a future Demo Day and blog post, we’ll talk about continuous integration testing to help get even more out of you unit tests.\nResources:\n\ntestthat package for unit testing in R\npytest package for unit testing in Python\nPSL catalog criteria\nUnit tests for the capital-cost-recovery model"
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diff --git a/site_libs/bootstrap/bootstrap.min.css b/site_libs/bootstrap/bootstrap.min.css
new file mode 100644
index 0000000..f77f69a
--- /dev/null
+++ b/site_libs/bootstrap/bootstrap.min.css
@@ -0,0 +1,12 @@
+/*!
+ * Bootstrap  v5.3.1 (https://getbootstrap.com/)
+ * Copyright 2011-2023 The Bootstrap Authors
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)
+ */@import"https://fonts.googleapis.com/css2?family=Source+Sans+Pro:wght@300;400;700&display=swap";:root,[data-bs-theme=light]{--bs-blue: #2780e3;--bs-indigo: #6610f2;--bs-purple: #613d7c;--bs-pink: #e83e8c;--bs-red: #ff0039;--bs-orange: #f0ad4e;--bs-yellow: #ff7518;--bs-green: #3fb618;--bs-teal: #20c997;--bs-cyan: #9954bb;--bs-black: #000;--bs-white: #fff;--bs-gray: #6c757d;--bs-gray-dark: #343a40;--bs-gray-100: #f8f9fa;--bs-gray-200: #e9ecef;--bs-gray-300: #dee2e6;--bs-gray-400: #ced4da;--bs-gray-500: #adb5bd;--bs-gray-600: #6c757d;--bs-gray-700: #495057;--bs-gray-800: #343a40;--bs-gray-900: #212529;--bs-default: #343a40;--bs-primary: #2780e3;--bs-secondary: #343a40;--bs-success: #3fb618;--bs-info: #9954bb;--bs-warning: #ff7518;--bs-danger: #ff0039;--bs-light: #f8f9fa;--bs-dark: #343a40;--bs-default-rgb: 52, 58, 64;--bs-primary-rgb: 39, 128, 227;--bs-secondary-rgb: 52, 58, 64;--bs-success-rgb: 63, 182, 24;--bs-info-rgb: 153, 84, 187;--bs-warning-rgb: 255, 117, 24;--bs-danger-rgb: 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none}.btn-outline-primary{--bs-btn-color: #2780e3;--bs-btn-border-color: #2780e3;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #2780e3;--bs-btn-hover-border-color: #2780e3;--bs-btn-focus-shadow-rgb: 39, 128, 227;--bs-btn-active-color: #fff;--bs-btn-active-bg: #2780e3;--bs-btn-active-border-color: #2780e3;--bs-btn-active-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);--bs-btn-disabled-color: #2780e3;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #2780e3;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-secondary{--bs-btn-color: #343a40;--bs-btn-border-color: #343a40;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #343a40;--bs-btn-hover-border-color: #343a40;--bs-btn-focus-shadow-rgb: 52, 58, 64;--bs-btn-active-color: #fff;--bs-btn-active-bg: #343a40;--bs-btn-active-border-color: #343a40;--bs-btn-active-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);--bs-btn-disabled-color: #343a40;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #343a40;--bs-btn-bg: 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#ff0039;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #ff0039;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-light{--bs-btn-color: #f8f9fa;--bs-btn-border-color: #f8f9fa;--bs-btn-hover-color: #000;--bs-btn-hover-bg: #f8f9fa;--bs-btn-hover-border-color: #f8f9fa;--bs-btn-focus-shadow-rgb: 248, 249, 250;--bs-btn-active-color: #000;--bs-btn-active-bg: #f8f9fa;--bs-btn-active-border-color: #f8f9fa;--bs-btn-active-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);--bs-btn-disabled-color: #f8f9fa;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #f8f9fa;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-dark{--bs-btn-color: #343a40;--bs-btn-border-color: #343a40;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #343a40;--bs-btn-hover-border-color: #343a40;--bs-btn-focus-shadow-rgb: 52, 58, 64;--bs-btn-active-color: #fff;--bs-btn-active-bg: #343a40;--bs-btn-active-border-color: #343a40;--bs-btn-active-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);--bs-btn-disabled-color: #343a40;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #343a40;--bs-btn-bg: transparent;--bs-gradient: none}.btn-link{--bs-btn-font-weight: 400;--bs-btn-color: #2761e3;--bs-btn-bg: transparent;--bs-btn-border-color: transparent;--bs-btn-hover-color: #1f4eb6;--bs-btn-hover-border-color: transparent;--bs-btn-active-color: #1f4eb6;--bs-btn-active-border-color: transparent;--bs-btn-disabled-color: #6c757d;--bs-btn-disabled-border-color: transparent;--bs-btn-box-shadow: 0 0 0 #000;--bs-btn-focus-shadow-rgb: 71, 121, 231;text-decoration:underline;-webkit-text-decoration:underline;-moz-text-decoration:underline;-ms-text-decoration:underline;-o-text-decoration:underline}.btn-link:focus-visible{color:var(--bs-btn-color)}.btn-link:hover{color:var(--bs-btn-hover-color)}.btn-lg,.btn-group-lg>.btn{--bs-btn-padding-y: 0.5rem;--bs-btn-padding-x: 1rem;--bs-btn-font-size:1.25rem;--bs-btn-border-radius: 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var(--bs-dropdown-item-padding-x);clear:both;font-weight:400;color:var(--bs-dropdown-link-color);text-align:inherit;text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;white-space:nowrap;background-color:rgba(0,0,0,0);border:0}.dropdown-item:hover,.dropdown-item:focus{color:var(--bs-dropdown-link-hover-color);background-color:var(--bs-dropdown-link-hover-bg)}.dropdown-item.active,.dropdown-item:active{color:var(--bs-dropdown-link-active-color);text-decoration:none;background-color:var(--bs-dropdown-link-active-bg)}.dropdown-item.disabled,.dropdown-item:disabled{color:var(--bs-dropdown-link-disabled-color);pointer-events:none;background-color:rgba(0,0,0,0)}.dropdown-menu.show{display:block}.dropdown-header{display:block;padding:var(--bs-dropdown-header-padding-y) 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auto}.btn-group>.btn-check:checked+.btn,.btn-group>.btn-check:focus+.btn,.btn-group>.btn:hover,.btn-group>.btn:focus,.btn-group>.btn:active,.btn-group>.btn.active,.btn-group-vertical>.btn-check:checked+.btn,.btn-group-vertical>.btn-check:focus+.btn,.btn-group-vertical>.btn:hover,.btn-group-vertical>.btn:focus,.btn-group-vertical>.btn:active,.btn-group-vertical>.btn.active{z-index:1}.btn-toolbar{display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;justify-content:flex-start;-webkit-justify-content:flex-start}.btn-toolbar .input-group{width:auto}.btn-group>:not(.btn-check:first-child)+.btn,.btn-group>.btn-group:not(:first-child){margin-left:calc(1px*-1)}.dropdown-toggle-split{padding-right:.5625rem;padding-left:.5625rem}.dropdown-toggle-split::after,.dropup .dropdown-toggle-split::after,.dropend .dropdown-toggle-split::after{margin-left:0}.dropstart .dropdown-toggle-split::before{margin-right:0}.btn-sm+.dropdown-toggle-split,.btn-group-sm>.btn+.dropdown-toggle-split{padding-right:.375rem;padding-left:.375rem}.btn-lg+.dropdown-toggle-split,.btn-group-lg>.btn+.dropdown-toggle-split{padding-right:.75rem;padding-left:.75rem}.btn-group-vertical{flex-direction:column;-webkit-flex-direction:column;align-items:flex-start;-webkit-align-items:flex-start;justify-content:center;-webkit-justify-content:center}.btn-group-vertical>.btn,.btn-group-vertical>.btn-group{width:100%}.btn-group-vertical>.btn:not(:first-child),.btn-group-vertical>.btn-group:not(:first-child){margin-top:calc(1px*-1)}.nav{--bs-nav-link-padding-x: 1rem;--bs-nav-link-padding-y: 0.5rem;--bs-nav-link-font-weight: ;--bs-nav-link-color: #2761e3;--bs-nav-link-hover-color: #1f4eb6;--bs-nav-link-disabled-color: rgba(52, 58, 64, 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var(--bs-navbar-hover-color);--bs-nav-link-disabled-color: var(--bs-navbar-disabled-color);display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;list-style:none}.navbar-nav .nav-link.active,.navbar-nav .nav-link.show{color:var(--bs-navbar-active-color)}.navbar-nav .dropdown-menu{position:static}.navbar-text{padding-top:.5rem;padding-bottom:.5rem;color:var(--bs-navbar-color)}.navbar-text a,.navbar-text a:hover,.navbar-text a:focus{color:var(--bs-navbar-active-color)}.navbar-collapse{flex-basis:100%;-webkit-flex-basis:100%;flex-grow:1;-webkit-flex-grow:1;align-items:center;-webkit-align-items:center}.navbar-toggler{padding:var(--bs-navbar-toggler-padding-y) var(--bs-navbar-toggler-padding-x);font-size:var(--bs-navbar-toggler-font-size);line-height:1;color:var(--bs-navbar-color);background-color:rgba(0,0,0,0);border:var(--bs-border-width) solid 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992px){.navbar-expand-lg{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-lg .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-lg .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-lg .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-lg .navbar-nav-scroll{overflow:visible}.navbar-expand-lg .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-lg .navbar-toggler{display:none}.navbar-expand-lg .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:rgba(0,0,0,0) !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-lg .offcanvas .offcanvas-header{display:none}.navbar-expand-lg .offcanvas 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.offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:rgba(0,0,0,0) !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-xxl .offcanvas .offcanvas-header{display:none}.navbar-expand-xxl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}.navbar-expand{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand .navbar-nav .dropdown-menu{position:absolute}.navbar-expand .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand .navbar-nav-scroll{overflow:visible}.navbar-expand .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand .navbar-toggler{display:none}.navbar-expand .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:rgba(0,0,0,0) !important;border:0 !important;transform:none !important;transition:none}.navbar-expand .offcanvas .offcanvas-header{display:none}.navbar-expand .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}.navbar-dark,.navbar[data-bs-theme=dark]{--bs-navbar-color: #545555;--bs-navbar-hover-color: rgba(31, 78, 182, 0.8);--bs-navbar-disabled-color: rgba(84, 85, 85, 0.75);--bs-navbar-active-color: #1f4eb6;--bs-navbar-brand-color: #545555;--bs-navbar-brand-hover-color: #1f4eb6;--bs-navbar-toggler-border-color: rgba(84, 85, 85, 0);--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 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0.75rem;position:relative;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;min-width:0;height:var(--bs-card-height);color:var(--bs-body-color);word-wrap:break-word;background-color:var(--bs-card-bg);background-clip:border-box;border:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card>hr{margin-right:0;margin-left:0}.card>.list-group{border-top:inherit;border-bottom:inherit}.card>.list-group:first-child{border-top-width:0}.card>.list-group:last-child{border-bottom-width:0}.card>.card-header+.list-group,.card>.list-group+.card-footer{border-top:0}.card-body{flex:1 1 auto;-webkit-flex:1 1 auto;padding:var(--bs-card-spacer-y) var(--bs-card-spacer-x);color:var(--bs-card-color)}.card-title{margin-bottom:var(--bs-card-title-spacer-y);color:var(--bs-card-title-color)}.card-subtitle{margin-top:calc(-0.5*var(--bs-card-title-spacer-y));margin-bottom:0;color:var(--bs-card-subtitle-color)}.card-text:last-child{margin-bottom:0}.card-link+.card-link{margin-left:var(--bs-card-spacer-x)}.card-header{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);margin-bottom:0;color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-bottom:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-footer{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-top:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-header-tabs{margin-right:calc(-0.5*var(--bs-card-cap-padding-x));margin-bottom:calc(-1*var(--bs-card-cap-padding-y));margin-left:calc(-0.5*var(--bs-card-cap-padding-x));border-bottom:0}.card-header-tabs .nav-link.active{background-color:var(--bs-card-bg);border-bottom-color:var(--bs-card-bg)}.card-header-pills{margin-right:calc(-0.5*var(--bs-card-cap-padding-x));margin-left:calc(-0.5*var(--bs-card-cap-padding-x))}.card-img-overlay{position:absolute;top:0;right:0;bottom:0;left:0;padding:var(--bs-card-img-overlay-padding)}.card-img,.card-img-top,.card-img-bottom{width:100%}.card-group>.card{margin-bottom:var(--bs-card-group-margin)}@media(min-width: 576px){.card-group{display:flex;display:-webkit-flex;flex-flow:row wrap;-webkit-flex-flow:row wrap}.card-group>.card{flex:1 0 0%;-webkit-flex:1 0 0%;margin-bottom:0}.card-group>.card+.card{margin-left:0;border-left:0}}.accordion{--bs-accordion-color: #343a40;--bs-accordion-bg: #fff;--bs-accordion-transition: color 0.15s ease-in-out, background-color 0.15s ease-in-out, border-color 0.15s ease-in-out, box-shadow 0.15s ease-in-out, border-radius 0.15s ease;--bs-accordion-border-color: #dee2e6;--bs-accordion-border-width: 1px;--bs-accordion-border-radius: 0.25rem;--bs-accordion-inner-border-radius: calc(0.25rem - 1px);--bs-accordion-btn-padding-x: 1.25rem;--bs-accordion-btn-padding-y: 1rem;--bs-accordion-btn-color: #343a40;--bs-accordion-btn-bg: #fff;--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23343a40'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-icon-width: 1.25rem;--bs-accordion-btn-icon-transform: rotate(-180deg);--bs-accordion-btn-icon-transition: transform 0.2s ease-in-out;--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%2310335b'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: #93c0f1;--bs-accordion-btn-focus-box-shadow: 0 0 0 0.25rem rgba(39, 128, 227, 0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: #10335b;--bs-accordion-active-bg: #d4e6f9}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media(prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1*var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media(prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:not(:first-of-type){border-top:0}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}[data-bs-theme=dark] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%237db3ee'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%237db3ee'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: rgba(52, 58, 64, 0.75);--bs-breadcrumb-item-padding-x: 0.5rem;--bs-breadcrumb-item-active-color: rgba(52, 58, 64, 0.75);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, ">") /* rtl: var(--bs-breadcrumb-divider, ">") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: 0.75rem;--bs-pagination-padding-y: 0.375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: #2761e3;--bs-pagination-bg: #fff;--bs-pagination-border-width: 1px;--bs-pagination-border-color: #dee2e6;--bs-pagination-border-radius: 0.25rem;--bs-pagination-hover-color: #1f4eb6;--bs-pagination-hover-bg: #f8f9fa;--bs-pagination-hover-border-color: #dee2e6;--bs-pagination-focus-color: #1f4eb6;--bs-pagination-focus-bg: #e9ecef;--bs-pagination-focus-box-shadow: 0 0 0 0.25rem rgba(39, 128, 227, 0.25);--bs-pagination-active-color: #fff;--bs-pagination-active-bg: #2780e3;--bs-pagination-active-border-color: #2780e3;--bs-pagination-disabled-color: rgba(52, 58, 64, 0.75);--bs-pagination-disabled-bg: #e9ecef;--bs-pagination-disabled-border-color: #dee2e6;display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color .15s ease-in-out,background-color .15s ease-in-out,border-color .15s ease-in-out,box-shadow .15s ease-in-out}@media(prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(1px*-1)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: 0.75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: 0.5rem}.pagination-sm{--bs-pagination-padding-x: 0.5rem;--bs-pagination-padding-y: 0.25rem;--bs-pagination-font-size:0.875rem;--bs-pagination-border-radius: 0.2em}.badge{--bs-badge-padding-x: 0.65em;--bs-badge-padding-y: 0.35em;--bs-badge-font-size:0.75em;--bs-badge-font-weight: 700;--bs-badge-color: #fff;--bs-badge-border-radius: 0.25rem;display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: 0 solid var(--bs-alert-border-color);--bs-alert-border-radius: 0.25rem;--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:.5rem}}.progress,.progress-stacked{--bs-progress-height: 0.5rem;--bs-progress-font-size:0.75rem;--bs-progress-bg: #e9ecef;--bs-progress-border-radius: 0.25rem;--bs-progress-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.075);--bs-progress-bar-color: #fff;--bs-progress-bar-bg: #2780e3;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media(prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media(prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: #343a40;--bs-list-group-bg: #fff;--bs-list-group-border-color: #dee2e6;--bs-list-group-border-width: 1px;--bs-list-group-border-radius: 0.25rem;--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: 0.5rem;--bs-list-group-action-color: rgba(52, 58, 64, 0.75);--bs-list-group-action-hover-color: #000;--bs-list-group-action-hover-bg: #f8f9fa;--bs-list-group-action-active-color: #343a40;--bs-list-group-action-active-bg: #e9ecef;--bs-list-group-disabled-color: rgba(52, 58, 64, 0.75);--bs-list-group-disabled-bg: #fff;--bs-list-group-active-color: #fff;--bs-list-group-active-bg: #2780e3;--bs-list-group-active-border-color: #2780e3;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") ". ";counter-increment:section}.list-group-item-action{width:100%;color:var(--bs-list-group-action-color);text-align:inherit}.list-group-item-action:hover,.list-group-item-action:focus{z-index:1;color:var(--bs-list-group-action-hover-color);text-decoration:none;background-color:var(--bs-list-group-action-hover-bg)}.list-group-item-action:active{color:var(--bs-list-group-action-active-color);background-color:var(--bs-list-group-action-active-bg)}.list-group-item{position:relative;display:block;padding:var(--bs-list-group-item-padding-y) var(--bs-list-group-item-padding-x);color:var(--bs-list-group-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-list-group-bg);border:var(--bs-list-group-border-width) solid var(--bs-list-group-border-color)}.list-group-item.disabled,.list-group-item:disabled{color:var(--bs-list-group-disabled-color);pointer-events:none;background-color:var(--bs-list-group-disabled-bg)}.list-group-item.active{z-index:2;color:var(--bs-list-group-active-color);background-color:var(--bs-list-group-active-bg);border-color:var(--bs-list-group-active-border-color)}.list-group-item+.list-group-item{border-top-width:0}.list-group-item+.list-group-item.active{margin-top:calc(-1*var(--bs-list-group-border-width));border-top-width:var(--bs-list-group-border-width)}.list-group-horizontal{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal>.list-group-item.active{margin-top:0}.list-group-horizontal>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}@media(min-width: 576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media(min-width: 1400px){.list-group-horizontal-xxl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xxl>.list-group-item.active{margin-top:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item.active{margin-left:calc(-1*var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000'%3e%3cpath d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/%3e%3c/svg%3e");--bs-btn-close-opacity: 0.5;--bs-btn-close-hover-opacity: 0.75;--bs-btn-close-focus-shadow: 0 0 0 0.25rem rgba(39, 128, 227, 0.25);--bs-btn-close-focus-opacity: 1;--bs-btn-close-disabled-opacity: 0.25;--bs-btn-close-white-filter: invert(1) grayscale(100%) brightness(200%);box-sizing:content-box;width:1em;height:1em;padding:.25em .25em;color:var(--bs-btn-close-color);background:rgba(0,0,0,0) var(--bs-btn-close-bg) center/1em auto no-repeat;border:0;opacity:var(--bs-btn-close-opacity)}.btn-close:hover{color:var(--bs-btn-close-color);text-decoration:none;opacity:var(--bs-btn-close-hover-opacity)}.btn-close:focus{outline:0;box-shadow:var(--bs-btn-close-focus-shadow);opacity:var(--bs-btn-close-focus-opacity)}.btn-close:disabled,.btn-close.disabled{pointer-events:none;user-select:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;-o-user-select:none;opacity:var(--bs-btn-close-disabled-opacity)}.btn-close-white{filter:var(--bs-btn-close-white-filter)}[data-bs-theme=dark] .btn-close{filter:var(--bs-btn-close-white-filter)}.toast{--bs-toast-zindex: 1090;--bs-toast-padding-x: 0.75rem;--bs-toast-padding-y: 0.5rem;--bs-toast-spacing: 1.5rem;--bs-toast-max-width: 350px;--bs-toast-font-size:0.875rem;--bs-toast-color: ;--bs-toast-bg: rgba(255, 255, 255, 0.85);--bs-toast-border-width: 1px;--bs-toast-border-color: rgba(0, 0, 0, 0.175);--bs-toast-border-radius: 0.25rem;--bs-toast-box-shadow: 0 0.5rem 1rem rgba(0, 0, 0, 0.15);--bs-toast-header-color: rgba(52, 58, 64, 0.75);--bs-toast-header-bg: rgba(255, 255, 255, 0.85);--bs-toast-header-border-color: rgba(0, 0, 0, 0.175);width:var(--bs-toast-max-width);max-width:100%;font-size:var(--bs-toast-font-size);color:var(--bs-toast-color);pointer-events:auto;background-color:var(--bs-toast-bg);background-clip:padding-box;border:var(--bs-toast-border-width) solid var(--bs-toast-border-color);box-shadow:var(--bs-toast-box-shadow)}.toast.showing{opacity:0}.toast:not(.show){display:none}.toast-container{--bs-toast-zindex: 1090;position:absolute;z-index:var(--bs-toast-zindex);width:max-content;width:-webkit-max-content;width:-moz-max-content;width:-ms-max-content;width:-o-max-content;max-width:100%;pointer-events:none}.toast-container>:not(:last-child){margin-bottom:var(--bs-toast-spacing)}.toast-header{display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;padding:var(--bs-toast-padding-y) var(--bs-toast-padding-x);color:var(--bs-toast-header-color);background-color:var(--bs-toast-header-bg);background-clip:padding-box;border-bottom:var(--bs-toast-border-width) solid var(--bs-toast-header-border-color)}.toast-header .btn-close{margin-right:calc(-0.5*var(--bs-toast-padding-x));margin-left:var(--bs-toast-padding-x)}.toast-body{padding:var(--bs-toast-padding-x);word-wrap:break-word}.modal{--bs-modal-zindex: 1055;--bs-modal-width: 500px;--bs-modal-padding: 1rem;--bs-modal-margin: 0.5rem;--bs-modal-color: ;--bs-modal-bg: #fff;--bs-modal-border-color: rgba(0, 0, 0, 0.175);--bs-modal-border-width: 1px;--bs-modal-border-radius: 0.5rem;--bs-modal-box-shadow: 0 0.125rem 0.25rem rgba(0, 0, 0, 0.075);--bs-modal-inner-border-radius: calc(0.5rem - 1px);--bs-modal-header-padding-x: 1rem;--bs-modal-header-padding-y: 1rem;--bs-modal-header-padding: 1rem 1rem;--bs-modal-header-border-color: #dee2e6;--bs-modal-header-border-width: 1px;--bs-modal-title-line-height: 1.5;--bs-modal-footer-gap: 0.5rem;--bs-modal-footer-bg: ;--bs-modal-footer-border-color: #dee2e6;--bs-modal-footer-border-width: 1px;position:fixed;top:0;left:0;z-index:var(--bs-modal-zindex);display:none;width:100%;height:100%;overflow-x:hidden;overflow-y:auto;outline:0}.modal-dialog{position:relative;width:auto;margin:var(--bs-modal-margin);pointer-events:none}.modal.fade .modal-dialog{transition:transform .3s ease-out;transform:translate(0, -50px)}@media(prefers-reduced-motion: reduce){.modal.fade .modal-dialog{transition:none}}.modal.show .modal-dialog{transform:none}.modal.modal-static .modal-dialog{transform:scale(1.02)}.modal-dialog-scrollable{height:calc(100% - var(--bs-modal-margin)*2)}.modal-dialog-scrollable .modal-content{max-height:100%;overflow:hidden}.modal-dialog-scrollable .modal-body{overflow-y:auto}.modal-dialog-centered{display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;min-height:calc(100% - var(--bs-modal-margin)*2)}.modal-content{position:relative;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;width:100%;color:var(--bs-modal-color);pointer-events:auto;background-color:var(--bs-modal-bg);background-clip:padding-box;border:var(--bs-modal-border-width) solid var(--bs-modal-border-color);outline:0}.modal-backdrop{--bs-backdrop-zindex: 1050;--bs-backdrop-bg: #000;--bs-backdrop-opacity: 0.5;position:fixed;top:0;left:0;z-index:var(--bs-backdrop-zindex);width:100vw;height:100vh;background-color:var(--bs-backdrop-bg)}.modal-backdrop.fade{opacity:0}.modal-backdrop.show{opacity:var(--bs-backdrop-opacity)}.modal-header{display:flex;display:-webkit-flex;flex-shrink:0;-webkit-flex-shrink:0;align-items:center;-webkit-align-items:center;justify-content:space-between;-webkit-justify-content:space-between;padding:var(--bs-modal-header-padding);border-bottom:var(--bs-modal-header-border-width) solid var(--bs-modal-header-border-color)}.modal-header .btn-close{padding:calc(var(--bs-modal-header-padding-y)*.5) calc(var(--bs-modal-header-padding-x)*.5);margin:calc(-0.5*var(--bs-modal-header-padding-y)) calc(-0.5*var(--bs-modal-header-padding-x)) calc(-0.5*var(--bs-modal-header-padding-y)) auto}.modal-title{margin-bottom:0;line-height:var(--bs-modal-title-line-height)}.modal-body{position:relative;flex:1 1 auto;-webkit-flex:1 1 auto;padding:var(--bs-modal-padding)}.modal-footer{display:flex;display:-webkit-flex;flex-shrink:0;-webkit-flex-shrink:0;flex-wrap:wrap;-webkit-flex-wrap:wrap;align-items:center;-webkit-align-items:center;justify-content:flex-end;-webkit-justify-content:flex-end;padding:calc(var(--bs-modal-padding) - var(--bs-modal-footer-gap)*.5);background-color:var(--bs-modal-footer-bg);border-top:var(--bs-modal-footer-border-width) solid var(--bs-modal-footer-border-color)}.modal-footer>*{margin:calc(var(--bs-modal-footer-gap)*.5)}@media(min-width: 576px){.modal{--bs-modal-margin: 1.75rem;--bs-modal-box-shadow: 0 0.5rem 1rem rgba(0, 0, 0, 0.15)}.modal-dialog{max-width:var(--bs-modal-width);margin-right:auto;margin-left:auto}.modal-sm{--bs-modal-width: 300px}}@media(min-width: 992px){.modal-lg,.modal-xl{--bs-modal-width: 800px}}@media(min-width: 1200px){.modal-xl{--bs-modal-width: 1140px}}.modal-fullscreen{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen .modal-content{height:100%;border:0}.modal-fullscreen .modal-body{overflow-y:auto}@media(max-width: 575.98px){.modal-fullscreen-sm-down{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen-sm-down .modal-content{height:100%;border:0}.modal-fullscreen-sm-down .modal-body{overflow-y:auto}}@media(max-width: 767.98px){.modal-fullscreen-md-down{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen-md-down .modal-content{height:100%;border:0}.modal-fullscreen-md-down .modal-body{overflow-y:auto}}@media(max-width: 991.98px){.modal-fullscreen-lg-down{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen-lg-down .modal-content{height:100%;border:0}.modal-fullscreen-lg-down .modal-body{overflow-y:auto}}@media(max-width: 1199.98px){.modal-fullscreen-xl-down{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen-xl-down .modal-content{height:100%;border:0}.modal-fullscreen-xl-down .modal-body{overflow-y:auto}}@media(max-width: 1399.98px){.modal-fullscreen-xxl-down{width:100vw;max-width:none;height:100%;margin:0}.modal-fullscreen-xxl-down .modal-content{height:100%;border:0}.modal-fullscreen-xxl-down .modal-body{overflow-y:auto}}.tooltip{--bs-tooltip-zindex: 1080;--bs-tooltip-max-width: 200px;--bs-tooltip-padding-x: 0.5rem;--bs-tooltip-padding-y: 0.25rem;--bs-tooltip-margin: ;--bs-tooltip-font-size:0.875rem;--bs-tooltip-color: #fff;--bs-tooltip-bg: #000;--bs-tooltip-border-radius: 0.25rem;--bs-tooltip-opacity: 0.9;--bs-tooltip-arrow-width: 0.8rem;--bs-tooltip-arrow-height: 0.4rem;z-index:var(--bs-tooltip-zindex);display:block;margin:var(--bs-tooltip-margin);font-family:"Source Sans Pro",-apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,"Helvetica Neue",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI 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#fff);--bslib-value-box-border-color-default: var(--bs-card-border-color, rgba(0, 0, 0, 0.175));color:var(--bslib-value-box-color);background-color:var(--bslib-value-box-bg, var(--bslib-value-box-bg-default));border-color:var(--bslib-value-box-border-color, var(--bslib-value-box-border-color-default))}.bslib-value-box .value-box-grid{display:grid;grid-template-areas:"left right";align-items:center;overflow:hidden}.bslib-value-box .value-box-showcase{height:100%;max-height:var(---bslib-value-box-showcase-max-h, 100%)}.bslib-value-box .value-box-showcase,.bslib-value-box .value-box-showcase>.html-fill-item{width:100%}.bslib-value-box[data-full-screen=true] .value-box-showcase{max-height:var(---bslib-value-box-showcase-max-h-fs, 100%)}@media screen and (min-width: 575.98px){@container bslib-value-box (max-width: 300px){.bslib-value-box:not(.showcase-bottom) .value-box-grid{grid-template-columns:1fr !important;grid-template-rows:auto auto;grid-template-areas:"top" 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m?m(Object.assign({},e.rects,{placement:e.placement})):m,O="number"==typeof C?{mainAxis:C,altAxis:C}:Object.assign({mainAxis:0,altAxis:0},C),x=e.modifiersData.offset?e.modifiersData.offset[e.placement]:null,k={x:0,y:0};if(A){if(o){var L,S="y"===y?zt:Vt,D="y"===y?Rt:qt,$="y"===y?"height":"width",I=A[y],N=I+g[S],P=I-g[D],M=f?-T[$]/2:0,j=b===Xt?E[$]:T[$],F=b===Xt?-T[$]:-E[$],H=e.elements.arrow,W=f&&H?Ce(H):{width:0,height:0},B=e.modifiersData["arrow#persistent"]?e.modifiersData["arrow#persistent"].padding:{top:0,right:0,bottom:0,left:0},z=B[S],R=B[D],q=Ne(0,E[$],W[$]),V=v?E[$]/2-M-q-z-O.mainAxis:j-q-z-O.mainAxis,K=v?-E[$]/2+M+q+R+O.mainAxis:F+q+R+O.mainAxis,Q=e.elements.arrow&&$e(e.elements.arrow),X=Q?"y"===y?Q.clientTop||0:Q.clientLeft||0:0,Y=null!=(L=null==x?void 0:x[y])?L:0,U=I+K-Y,G=Ne(f?ye(N,I+V-Y-X):N,I,f?ve(P,U):P);A[y]=G,k[y]=G-I}if(a){var J,Z="x"===y?zt:Vt,tt="x"===y?Rt:qt,et=A[w],it="y"===w?"height":"width",nt=et+g[Z],st=et-g[tt],ot=-1!==[zt,Vt].indexOf(_),rt=null!=(J=null==x?void 0:x[w])?J:0,at=ot?nt:et-E[it]-T[it]-rt+O.altAxis,lt=ot?et+E[it]+T[it]-rt-O.altAxis:st,ct=f&&ot?function(t,e,i){var n=Ne(t,e,i);return n>i?i:n}(at,et,lt):Ne(f?at:nt,et,f?lt:st);A[w]=ct,k[w]=ct-et}e.modifiersData[n]=k}},requiresIfExists:["offset"]};function di(t,e,i){void 0===i&&(i=!1);var n,s,o=me(e),r=me(e)&&function(t){var e=t.getBoundingClientRect(),i=we(e.width)/t.offsetWidth||1,n=we(e.height)/t.offsetHeight||1;return 1!==i||1!==n}(e),a=Le(e),l=Te(t,r,i),c={scrollLeft:0,scrollTop:0},h={x:0,y:0};return(o||!o&&!i)&&(("body"!==ue(e)||Ue(a))&&(c=(n=e)!==fe(n)&&me(n)?{scrollLeft:(s=n).scrollLeft,scrollTop:s.scrollTop}:Xe(n)),me(e)?((h=Te(e,!0)).x+=e.clientLeft,h.y+=e.clientTop):a&&(h.x=Ye(a))),{x:l.left+c.scrollLeft-h.x,y:l.top+c.scrollTop-h.y,width:l.width,height:l.height}}function ui(t){var e=new Map,i=new Set,n=[];function s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var fi={placement:"bottom",modifiers:[],strategy:"absolute"};function pi(){for(var t=arguments.length,e=new Array(t),i=0;i<t;i++)e[i]=arguments[i];return!e.some((function(t){return!(t&&"function"==typeof t.getBoundingClientRect)}))}function mi(t){void 0===t&&(t={});var e=t,i=e.defaultModifiers,n=void 0===i?[]:i,s=e.defaultOptions,o=void 0===s?fi:s;return function(t,e,i){void 0===i&&(i=o);var s,r,a={placement:"bottom",orderedModifiers:[],options:Object.assign({},fi,o),modifiersData:{},elements:{reference:t,popper:e},attributes:{},styles:{}},l=[],c=!1,h={state:a,setOptions:function(i){var s="function"==typeof i?i(a.options):i;d(),a.options=Object.assign({},o,a.options,s),a.scrollParents={reference:pe(t)?Je(t):t.contextElement?Je(t.contextElement):[],popper:Je(e)};var r,c,u=function(t){var e=ui(t);return de.reduce((function(t,i){return t.concat(e.filter((function(t){return t.phase===i})))}),[])}((r=[].concat(n,a.options.modifiers),c=r.reduce((function(t,e){var i=t[e.name];return t[e.name]=i?Object.assign({},i,e,{options:Object.assign({},i.options,e.options),data:Object.assign({},i.data,e.data)}):e,t}),{}),Object.keys(c).map((function(t){return c[t]}))));return a.orderedModifiers=u.filter((function(t){return t.enabled})),a.orderedModifiers.forEach((function(t){var e=t.name,i=t.options,n=void 0===i?{}:i,s=t.effect;if("function"==typeof s){var o=s({state:a,name:e,instance:h,options:n});l.push(o||function(){})}})),h.update()},forceUpdate:function(){if(!c){var t=a.elements,e=t.reference,i=t.popper;if(pi(e,i)){a.rects={reference:di(e,$e(i),"fixed"===a.options.strategy),popper:Ce(i)},a.reset=!1,a.placement=a.options.placement,a.orderedModifiers.forEach((function(t){return a.modifiersData[t.name]=Object.assign({},t.data)}));for(var n=0;n<a.orderedModifiers.length;n++)if(!0!==a.reset){var s=a.orderedModifiers[n],o=s.fn,r=s.options,l=void 0===r?{}:r,d=s.name;"function"==typeof o&&(a=o({state:a,options:l,name:d,instance:h})||a)}else a.reset=!1,n=-1}}},update:(s=function(){return new Promise((function(t){h.forceUpdate(),t(a)}))},function(){return r||(r=new Promise((function(t){Promise.resolve().then((function(){r=void 0,t(s())}))}))),r}),destroy:function(){d(),c=!0}};if(!pi(t,e))return h;function d(){l.forEach((function(t){return t()})),l=[]}return h.setOptions(i).then((function(t){!c&&i.onFirstUpdate&&i.onFirstUpdate(t)})),h}}var gi=mi(),_i=mi({defaultModifiers:[Re,ci,Be,_e]}),bi=mi({defaultModifiers:[Re,ci,Be,_e,li,si,hi,je,ai]});const vi=Object.freeze(Object.defineProperty({__proto__:null,afterMain:ae,afterRead:se,afterWrite:he,applyStyles:_e,arrow:je,auto:Kt,basePlacements:Qt,beforeMain:oe,beforeRead:ie,beforeWrite:le,bottom:Rt,clippingParents:Ut,computeStyles:Be,createPopper:bi,createPopperBase:gi,createPopperLite:_i,detectOverflow:ii,end:Yt,eventListeners:Re,flip:si,hide:ai,left:Vt,main:re,modifierPhases:de,offset:li,placements:ee,popper:Jt,popperGenerator:mi,popperOffsets:ci,preventOverflow:hi,read:ne,reference:Zt,right:qt,start:Xt,top:zt,variationPlacements:te,viewport:Gt,write:ce},Symbol.toStringTag,{value:"Module"})),yi="dropdown",wi=".bs.dropdown",Ai=".data-api",Ei="ArrowUp",Ti="ArrowDown",Ci=`hide${wi}`,Oi=`hidden${wi}`,xi=`show${wi}`,ki=`shown${wi}`,Li=`click${wi}${Ai}`,Si=`keydown${wi}${Ai}`,Di=`keyup${wi}${Ai}`,$i="show",Ii='[data-bs-toggle="dropdown"]:not(.disabled):not(:disabled)',Ni=`${Ii}.${$i}`,Pi=".dropdown-menu",Mi=p()?"top-end":"top-start",ji=p()?"top-start":"top-end",Fi=p()?"bottom-end":"bottom-start",Hi=p()?"bottom-start":"bottom-end",Wi=p()?"left-start":"right-start",Bi=p()?"right-start":"left-start",zi={autoClose:!0,boundary:"clippingParents",display:"dynamic",offset:[0,2],popperConfig:null,reference:"toggle"},Ri={autoClose:"(boolean|string)",boundary:"(string|element)",display:"string",offset:"(array|string|function)",popperConfig:"(null|object|function)",reference:"(string|element|object)"};class qi extends W{constructor(t,e){super(t,e),this._popper=null,this._parent=this._element.parentNode,this._menu=z.next(this._element,Pi)[0]||z.prev(this._element,Pi)[0]||z.findOne(Pi,this._parent),this._inNavbar=this._detectNavbar()}static get Default(){return zi}static get DefaultType(){return Ri}static get NAME(){return yi}toggle(){return this._isShown()?this.hide():this.show()}show(){if(l(this._element)||this._isShown())return;const t={relatedTarget:this._element};if(!N.trigger(this._element,xi,t).defaultPrevented){if(this._createPopper(),"ontouchstart"in document.documentElement&&!this._parent.closest(".navbar-nav"))for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add($i),this._element.classList.add($i),N.trigger(this._element,ki,t)}}hide(){if(l(this._element)||!this._isShown())return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){if(!N.trigger(this._element,Ci,t).defaultPrevented){if("ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.off(t,"mouseover",h);this._popper&&this._popper.destroy(),this._menu.classList.remove($i),this._element.classList.remove($i),this._element.setAttribute("aria-expanded","false"),F.removeDataAttribute(this._menu,"popper"),N.trigger(this._element,Oi,t)}}_getConfig(t){if("object"==typeof(t=super._getConfig(t)).reference&&!o(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${yi.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(){if(void 0===vi)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let t=this._element;"parent"===this._config.reference?t=this._parent:o(this._config.reference)?t=r(this._config.reference):"object"==typeof this._config.reference&&(t=this._config.reference);const e=this._getPopperConfig();this._popper=bi(t,this._menu,e)}_isShown(){return this._menu.classList.contains($i)}_getPlacement(){const t=this._parent;if(t.classList.contains("dropend"))return Wi;if(t.classList.contains("dropstart"))return Bi;if(t.classList.contains("dropup-center"))return"top";if(t.classList.contains("dropdown-center"))return"bottom";const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?ji:Mi:e?Hi:Fi}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(F.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...g(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=z.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter((t=>a(t)));i.length&&b(i,e,t===Ti,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=qi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(2===t.button||"keyup"===t.type&&"Tab"!==t.key)return;const e=z.find(Ni);for(const i of e){const e=qi.getInstance(i);if(!e||!1===e._config.autoClose)continue;const n=t.composedPath(),s=n.includes(e._menu);if(n.includes(e._element)||"inside"===e._config.autoClose&&!s||"outside"===e._config.autoClose&&s)continue;if(e._menu.contains(t.target)&&("keyup"===t.type&&"Tab"===t.key||/input|select|option|textarea|form/i.test(t.target.tagName)))continue;const o={relatedTarget:e._element};"click"===t.type&&(o.clickEvent=t),e._completeHide(o)}}static dataApiKeydownHandler(t){const e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ei,Ti].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ii)?this:z.prev(this,Ii)[0]||z.next(this,Ii)[0]||z.findOne(Ii,t.delegateTarget.parentNode),o=qi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}N.on(document,Si,Ii,qi.dataApiKeydownHandler),N.on(document,Si,Pi,qi.dataApiKeydownHandler),N.on(document,Li,qi.clearMenus),N.on(document,Di,qi.clearMenus),N.on(document,Li,Ii,(function(t){t.preventDefault(),qi.getOrCreateInstance(this).toggle()})),m(qi);const Vi="backdrop",Ki="show",Qi=`mousedown.bs.${Vi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Yi={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Ui extends H{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Yi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void g(t);this._append();const e=this._getElement();this._config.isAnimated&&d(e),e.classList.add(Ki),this._emulateAnimation((()=>{g(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),g(t)}))):g(t)}dispose(){this._isAppended&&(N.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=r(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=z.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&F.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=F.getDataAttribute(t,e);null!==i?(F.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(o(t))e(t);else for(const i of z.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||N.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(N.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){N.off(window,hn),N.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=On.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}N.on(document,yn,'[data-bs-toggle="modal"]',(function(t){const e=z.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),N.one(e,pn,(t=>{t.defaultPrevented||N.one(e,fn,(()=>{a(this)&&this.focus()}))}));const i=z.findOne(".modal.show");i&&On.getInstance(i).hide(),On.getOrCreateInstance(e).toggle(this)})),R(On),m(On);const xn=".bs.offcanvas",kn=".data-api",Ln=`load${xn}${kn}`,Sn="show",Dn="showing",$n="hiding",In=".offcanvas.show",Nn=`show${xn}`,Pn=`shown${xn}`,Mn=`hide${xn}`,jn=`hidePrevented${xn}`,Fn=`hidden${xn}`,Hn=`resize${xn}`,Wn=`click${xn}${kn}`,Bn=`keydown.dismiss${xn}`,zn={backdrop:!0,keyboard:!0,scroll:!1},Rn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class qn extends W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"<div></div>"},Un={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},Gn={entry:"(string|element|function|null)",selector:"(string|element)"};class Jn extends H{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Yn}static get DefaultType(){return Un}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return g(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:p()?"left":"right",BOTTOM:"bottom",LEFT:p()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'<div class="tooltip" role="tooltip"><div class="tooltip-arrow"></div><div class="tooltip-inner"></div></div>',title:"",trigger:"hover focus"},ls={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class cs extends W{constructor(t,e){if(void 0===vi)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,e),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return as}static get DefaultType(){return ls}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),N.off(this._element.closest(is),ns,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=N.trigger(this._element,this.constructor.eventName("show")),e=(c(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),N.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._queueCallback((()=>{N.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!N.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.off(t,"mouseover",h);this._activeTrigger.click=!1,this._activeTrigger[os]=!1,this._activeTrigger[ss]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),N.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ts,es),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ts),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Jn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ts)}_isShown(){return this.tip&&this.tip.classList.contains(es)}_createPopper(t){const e=g(this._config.placement,[this,t,this._element]),i=rs[e.toUpperCase()];return bi(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return g(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...g(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)N.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===ss?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===ss?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");N.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?os:ss]=!0,e._enter()})),N.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?os:ss]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},N.on(this._element.closest(is),ns,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=F.getDataAttributes(this._element);for(const t of Object.keys(e))Zn.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=cs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}m(cs);const hs={...cs.Default,content:"",offset:[0,8],placement:"right",template:'<div class="popover" role="tooltip"><div class="popover-arrow"></div><h3 class="popover-header"></h3><div class="popover-body"></div></div>',trigger:"click"},ds={...cs.DefaultType,content:"(null|string|element|function)"};class us extends cs{static get Default(){return hs}static get DefaultType(){return ds}static get NAME(){return"popover"}_isWithContent(){return this._getTitle()||this._getContent()}_getContentForTemplate(){return{".popover-header":this._getTitle(),".popover-body":this._getContent()}}_getContent(){return this._resolvePossibleFunction(this._config.content)}static jQueryInterface(t){return this.each((function(){const e=us.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}m(us);const fs=".bs.scrollspy",ps=`activate${fs}`,ms=`click${fs}`,gs=`load${fs}.data-api`,_s="active",bs="[href]",vs=".nav-link",ys=`${vs}, .nav-item > ${vs}, .list-group-item`,ws={offset:null,rootMargin:"0px 0px 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t){if(!o.isIntersecting){this._activeTarget=null,this._clearActiveClass(e(o));continue}const t=o.target.offsetTop>=this._previousScrollData.visibleEntryTop;if(s&&t){if(i(o),!n)return}else s||t||i(o)}}_initializeTargetsAndObservables(){this._targetLinks=new Map,this._observableSections=new Map;const t=z.find(bs,this._config.target);for(const e of t){if(!e.hash||l(e))continue;const t=z.findOne(decodeURI(e.hash),this._element);a(t)&&(this._targetLinks.set(decodeURI(e.hash),e),this._observableSections.set(e.hash,t))}}_process(t){this._activeTarget!==t&&(this._clearActiveClass(this._config.target),this._activeTarget=t,t.classList.add(_s),this._activateParents(t),N.trigger(this._element,ps,{relatedTarget:t}))}_activateParents(t){if(t.classList.contains("dropdown-item"))z.findOne(".dropdown-toggle",t.closest(".dropdown")).classList.add(_s);else for(const e of z.parents(t,".nav, .list-group"))for(const t of z.prev(e,ys))t.classList.add(_s)}_clearActiveClass(t){t.classList.remove(_s);const e=z.find(`${bs}.${_s}`,t);for(const t of e)t.classList.remove(_s)}static jQueryInterface(t){return this.each((function(){const e=Es.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}N.on(window,gs,(()=>{for(const t of z.find('[data-bs-spy="scroll"]'))Es.getOrCreateInstance(t)})),m(Es);const Ts=".bs.tab",Cs=`hide${Ts}`,Os=`hidden${Ts}`,xs=`show${Ts}`,ks=`shown${Ts}`,Ls=`click${Ts}`,Ss=`keydown${Ts}`,Ds=`load${Ts}`,$s="ArrowLeft",Is="ArrowRight",Ns="ArrowUp",Ps="ArrowDown",Ms="Home",js="End",Fs="active",Hs="fade",Ws="show",Bs=":not(.dropdown-toggle)",zs='[data-bs-toggle="tab"], [data-bs-toggle="pill"], [data-bs-toggle="list"]',Rs=`.nav-link${Bs}, .list-group-item${Bs}, [role="tab"]${Bs}, ${zs}`,qs=`.${Fs}[data-bs-toggle="tab"], .${Fs}[data-bs-toggle="pill"], .${Fs}[data-bs-toggle="list"]`;class Vs extends W{constructor(t){super(t),this._parent=this._element.closest('.list-group, .nav, [role="tablist"]'),this._parent&&(this._setInitialAttributes(this._parent,this._getChildren()),N.on(this._element,Ss,(t=>this._keydown(t))))}static get NAME(){return"tab"}show(){const t=this._element;if(this._elemIsActive(t))return;const e=this._getActiveElem(),i=e?N.trigger(e,Cs,{relatedTarget:t}):null;N.trigger(t,xs,{relatedTarget:e}).defaultPrevented||i&&i.defaultPrevented||(this._deactivate(e,t),this._activate(t,e))}_activate(t,e){t&&(t.classList.add(Fs),this._activate(z.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.removeAttribute("tabindex"),t.setAttribute("aria-selected",!0),this._toggleDropDown(t,!0),N.trigger(t,ks,{relatedTarget:e})):t.classList.add(Ws)}),t,t.classList.contains(Hs)))}_deactivate(t,e){t&&(t.classList.remove(Fs),t.blur(),this._deactivate(z.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.setAttribute("aria-selected",!1),t.setAttribute("tabindex","-1"),this._toggleDropDown(t,!1),N.trigger(t,Os,{relatedTarget:e})):t.classList.remove(Ws)}),t,t.classList.contains(Hs)))}_keydown(t){if(![$s,Is,Ns,Ps,Ms,js].includes(t.key))return;t.stopPropagation(),t.preventDefault();const e=this._getChildren().filter((t=>!l(t)));let i;if([Ms,js].includes(t.key))i=e[t.key===Ms?0:e.length-1];else{const n=[Is,Ps].includes(t.key);i=b(e,t.target,n,!0)}i&&(i.focus({preventScroll:!0}),Vs.getOrCreateInstance(i).show())}_getChildren(){return z.find(Rs,this._parent)}_getActiveElem(){return this._getChildren().find((t=>this._elemIsActive(t)))||null}_setInitialAttributes(t,e){this._setAttributeIfNotExists(t,"role","tablist");for(const t of e)this._setInitialAttributesOnChild(t)}_setInitialAttributesOnChild(t){t=this._getInnerElement(t);const e=this._elemIsActive(t),i=this._getOuterElement(t);t.setAttribute("aria-selected",e),i!==t&&this._setAttributeIfNotExists(i,"role","presentation"),e||t.setAttribute("tabindex","-1"),this._setAttributeIfNotExists(t,"role","tab"),this._setInitialAttributesOnTargetPanel(t)}_setInitialAttributesOnTargetPanel(t){const e=z.getElementFromSelector(t);e&&(this._setAttributeIfNotExists(e,"role","tabpanel"),t.id&&this._setAttributeIfNotExists(e,"aria-labelledby",`${t.id}`))}_toggleDropDown(t,e){const i=this._getOuterElement(t);if(!i.classList.contains("dropdown"))return;const n=(t,n)=>{const s=z.findOne(t,i);s&&s.classList.toggle(n,e)};n(".dropdown-toggle",Fs),n(".dropdown-menu",Ws),i.setAttribute("aria-expanded",e)}_setAttributeIfNotExists(t,e,i){t.hasAttribute(e)||t.setAttribute(e,i)}_elemIsActive(t){return t.classList.contains(Fs)}_getInnerElement(t){return t.matches(Rs)?t:z.findOne(Rs,t)}_getOuterElement(t){return t.closest(".nav-item, .list-group-item")||t}static jQueryInterface(t){return this.each((function(){const e=Vs.getOrCreateInstance(this);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named 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+//# sourceMappingURL=bootstrap.bundle.min.js.map
\ No newline at end of file
diff --git a/site_libs/clipboard/clipboard.min.js b/site_libs/clipboard/clipboard.min.js
new file mode 100644
index 0000000..1103f81
--- /dev/null
+++ b/site_libs/clipboard/clipboard.min.js
@@ -0,0 +1,7 @@
+/*!
+ * clipboard.js v2.0.11
+ * https://clipboardjs.com/
+ *
+ * Licensed MIT © Zeno Rocha
+ */
+!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return b}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),r=n.n(e);function c(t){try{return document.execCommand(t)}catch(t){return}}var a=function(t){t=r()(t);return c("cut"),t};function o(t,e){var n,o,t=(n=t,o="rtl"===document.documentElement.getAttribute("dir"),(t=document.createElement("textarea")).style.fontSize="12pt",t.style.border="0",t.style.padding="0",t.style.margin="0",t.style.position="absolute",t.style[o?"right":"left"]="-9999px",o=window.pageYOffset||document.documentElement.scrollTop,t.style.top="".concat(o,"px"),t.setAttribute("readonly",""),t.value=n,t);return e.container.appendChild(t),e=r()(t),c("copy"),t.remove(),e}var f=function(t){var e=1<arguments.length&&void 0!==arguments[1]?arguments[1]:{container:document.body},n="";return"string"==typeof t?n=o(t,e):t instanceof HTMLInputElement&&!["text","search","url","tel","password"].includes(null==t?void 0:t.type)?n=o(t.value,e):(n=r()(t),c("copy")),n};function l(t){return(l="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}var s=function(){var t=0<arguments.length&&void 0!==arguments[0]?arguments[0]:{},e=t.action,n=void 0===e?"copy":e,o=t.container,e=t.target,t=t.text;if("copy"!==n&&"cut"!==n)throw new Error('Invalid "action" value, use either "copy" or "cut"');if(void 0!==e){if(!e||"object"!==l(e)||1!==e.nodeType)throw new Error('Invalid "target" value, use a valid Element');if("copy"===n&&e.hasAttribute("disabled"))throw new Error('Invalid "target" attribute. 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\ No newline at end of file
diff --git a/site_libs/quarto-html/anchor.min.js b/site_libs/quarto-html/anchor.min.js
new file mode 100644
index 0000000..5ac814d
--- /dev/null
+++ b/site_libs/quarto-html/anchor.min.js
@@ -0,0 +1,9 @@
+// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt Expat
+//
+// AnchorJS - v5.0.0 - 2023-01-18
+// https://www.bryanbraun.com/anchorjs/
+// Copyright (c) 2023 Bryan Braun; Licensed MIT
+//
+// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt Expat
+!function(A,e){"use strict";"function"==typeof define&&define.amd?define([],e):"object"==typeof module&&module.exports?module.exports=e():(A.AnchorJS=e(),A.anchors=new A.AnchorJS)}(globalThis,function(){"use strict";return function(A){function u(A){A.icon=Object.prototype.hasOwnProperty.call(A,"icon")?A.icon:"",A.visible=Object.prototype.hasOwnProperty.call(A,"visible")?A.visible:"hover",A.placement=Object.prototype.hasOwnProperty.call(A,"placement")?A.placement:"right",A.ariaLabel=Object.prototype.hasOwnProperty.call(A,"ariaLabel")?A.ariaLabel:"Anchor",A.class=Object.prototype.hasOwnProperty.call(A,"class")?A.class:"",A.base=Object.prototype.hasOwnProperty.call(A,"base")?A.base:"",A.truncate=Object.prototype.hasOwnProperty.call(A,"truncate")?Math.floor(A.truncate):64,A.titleText=Object.prototype.hasOwnProperty.call(A,"titleText")?A.titleText:""}function d(A){var e;if("string"==typeof A||A instanceof String)e=[].slice.call(document.querySelectorAll(A));else{if(!(Array.isArray(A)||A instanceof NodeList))throw new TypeError("The selector provided to AnchorJS was invalid.");e=[].slice.call(A)}return e}this.options=A||{},this.elements=[],u(this.options),this.add=function(A){var e,t,o,i,n,s,a,r,l,c,h,p=[];if(u(this.options),0!==(e=d(A=A||"h2, h3, h4, h5, h6")).length){for(null===document.head.querySelector("style.anchorjs")&&((A=document.createElement("style")).className="anchorjs",A.appendChild(document.createTextNode("")),void 0===(h=document.head.querySelector('[rel="stylesheet"],style'))?document.head.appendChild(A):document.head.insertBefore(A,h),A.sheet.insertRule(".anchorjs-link{opacity:0;text-decoration:none;-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale}",A.sheet.cssRules.length),A.sheet.insertRule(":hover>.anchorjs-link,.anchorjs-link:focus{opacity:1}",A.sheet.cssRules.length),A.sheet.insertRule("[data-anchorjs-icon]::after{content:attr(data-anchorjs-icon)}",A.sheet.cssRules.length),A.sheet.insertRule('@font-face{font-family:anchorjs-icons;src:url(data:n/a;base64,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) format("truetype")}',A.sheet.cssRules.length)),h=document.querySelectorAll("[id]"),t=[].map.call(h,function(A){return A.id}),i=0;i<e.length;i++)if(this.hasAnchorJSLink(e[i]))p.push(i);else{if(e[i].hasAttribute("id"))o=e[i].getAttribute("id");else if(e[i].hasAttribute("data-anchor-id"))o=e[i].getAttribute("data-anchor-id");else{for(r=a=this.urlify(e[i].textContent),s=0;n=t.indexOf(r=void 0!==n?a+"-"+s:r),s+=1,-1!==n;);n=void 0,t.push(r),e[i].setAttribute("id",r),o=r}(l=document.createElement("a")).className="anchorjs-link "+this.options.class,l.setAttribute("aria-label",this.options.ariaLabel),l.setAttribute("data-anchorjs-icon",this.options.icon),this.options.titleText&&(l.title=this.options.titleText),c=document.querySelector("base")?window.location.pathname+window.location.search:"",c=this.options.base||c,l.href=c+"#"+o,"always"===this.options.visible&&(l.style.opacity="1"),""===this.options.icon&&(l.style.font="1em/1 anchorjs-icons","left"===this.options.placement)&&(l.style.lineHeight="inherit"),"left"===this.options.placement?(l.style.position="absolute",l.style.marginLeft="-1.25em",l.style.paddingRight=".25em",l.style.paddingLeft=".25em",e[i].insertBefore(l,e[i].firstChild)):(l.style.marginLeft=".1875em",l.style.paddingRight=".1875em",l.style.paddingLeft=".1875em",e[i].appendChild(l))}for(i=0;i<p.length;i++)e.splice(p[i]-i,1);this.elements=this.elements.concat(e)}return this},this.remove=function(A){for(var e,t,o=d(A),i=0;i<o.length;i++)(t=o[i].querySelector(".anchorjs-link"))&&(-1!==(e=this.elements.indexOf(o[i]))&&this.elements.splice(e,1),o[i].removeChild(t));return this},this.removeAll=function(){this.remove(this.elements)},this.urlify=function(A){var e=document.createElement("textarea");return e.innerHTML=A,A=e.value,this.options.truncate||u(this.options),A.trim().replace(/'/gi,"").replace(/[& +$,:;=?@"#{}|^~[`%!'<>\]./()*\\\n\t\b\v\u00A0]/g,"-").replace(/-{2,}/g,"-").substring(0,this.options.truncate).replace(/^-+|-+$/gm,"").toLowerCase()},this.hasAnchorJSLink=function(A){var e=A.firstChild&&-1<(" "+A.firstChild.className+" ").indexOf(" anchorjs-link "),A=A.lastChild&&-1<(" "+A.lastChild.className+" ").indexOf(" anchorjs-link ");return e||A||!1}}});
+// @license-end
\ No newline at end of file
diff --git a/site_libs/quarto-html/popper.min.js b/site_libs/quarto-html/popper.min.js
new file mode 100644
index 0000000..e3726d7
--- /dev/null
+++ b/site_libs/quarto-html/popper.min.js
@@ -0,0 +1,6 @@
+/**
+ * @popperjs/core v2.11.7 - MIT License
+ */
+
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+
diff --git a/site_libs/quarto-html/quarto-syntax-highlighting.css b/site_libs/quarto-html/quarto-syntax-highlighting.css
new file mode 100644
index 0000000..d9fd98f
--- /dev/null
+++ b/site_libs/quarto-html/quarto-syntax-highlighting.css
@@ -0,0 +1,203 @@
+/* quarto syntax highlight colors */
+:root {
+  --quarto-hl-ot-color: #003B4F;
+  --quarto-hl-at-color: #657422;
+  --quarto-hl-ss-color: #20794D;
+  --quarto-hl-an-color: #5E5E5E;
+  --quarto-hl-fu-color: #4758AB;
+  --quarto-hl-st-color: #20794D;
+  --quarto-hl-cf-color: #003B4F;
+  --quarto-hl-op-color: #5E5E5E;
+  --quarto-hl-er-color: #AD0000;
+  --quarto-hl-bn-color: #AD0000;
+  --quarto-hl-al-color: #AD0000;
+  --quarto-hl-va-color: #111111;
+  --quarto-hl-bu-color: inherit;
+  --quarto-hl-ex-color: inherit;
+  --quarto-hl-pp-color: #AD0000;
+  --quarto-hl-in-color: #5E5E5E;
+  --quarto-hl-vs-color: #20794D;
+  --quarto-hl-wa-color: #5E5E5E;
+  --quarto-hl-do-color: #5E5E5E;
+  --quarto-hl-im-color: #00769E;
+  --quarto-hl-ch-color: #20794D;
+  --quarto-hl-dt-color: #AD0000;
+  --quarto-hl-fl-color: #AD0000;
+  --quarto-hl-co-color: #5E5E5E;
+  --quarto-hl-cv-color: #5E5E5E;
+  --quarto-hl-cn-color: #8f5902;
+  --quarto-hl-sc-color: #5E5E5E;
+  --quarto-hl-dv-color: #AD0000;
+  --quarto-hl-kw-color: #003B4F;
+}
+
+/* other quarto variables */
+:root {
+  --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
+}
+
+pre > code.sourceCode > span {
+  color: #003B4F;
+}
+
+code span {
+  color: #003B4F;
+}
+
+code.sourceCode > span {
+  color: #003B4F;
+}
+
+div.sourceCode,
+div.sourceCode pre.sourceCode {
+  color: #003B4F;
+}
+
+code span.ot {
+  color: #003B4F;
+  font-style: inherit;
+}
+
+code span.at {
+  color: #657422;
+  font-style: inherit;
+}
+
+code span.ss {
+  color: #20794D;
+  font-style: inherit;
+}
+
+code span.an {
+  color: #5E5E5E;
+  font-style: inherit;
+}
+
+code span.fu {
+  color: #4758AB;
+  font-style: inherit;
+}
+
+code span.st {
+  color: #20794D;
+  font-style: inherit;
+}
+
+code span.cf {
+  color: #003B4F;
+  font-style: inherit;
+}
+
+code span.op {
+  color: #5E5E5E;
+  font-style: inherit;
+}
+
+code span.er {
+  color: #AD0000;
+  font-style: inherit;
+}
+
+code span.bn {
+  color: #AD0000;
+  font-style: inherit;
+}
+
+code span.al {
+  color: #AD0000;
+  font-style: inherit;
+}
+
+code span.va {
+  color: #111111;
+  font-style: inherit;
+}
+
+code span.bu {
+  font-style: inherit;
+}
+
+code span.ex {
+  font-style: inherit;
+}
+
+code span.pp {
+  color: #AD0000;
+  font-style: inherit;
+}
+
+code span.in {
+  color: #5E5E5E;
+  font-style: inherit;
+}
+
+code span.vs {
+  color: #20794D;
+  font-style: inherit;
+}
+
+code span.wa {
+  color: #5E5E5E;
+  font-style: italic;
+}
+
+code span.do {
+  color: #5E5E5E;
+  font-style: italic;
+}
+
+code span.im {
+  color: #00769E;
+  font-style: inherit;
+}
+
+code span.ch {
+  color: #20794D;
+  font-style: inherit;
+}
+
+code span.dt {
+  color: #AD0000;
+  font-style: inherit;
+}
+
+code span.fl {
+  color: #AD0000;
+  font-style: inherit;
+}
+
+code span.co {
+  color: #5E5E5E;
+  font-style: inherit;
+}
+
+code span.cv {
+  color: #5E5E5E;
+  font-style: italic;
+}
+
+code span.cn {
+  color: #8f5902;
+  font-style: inherit;
+}
+
+code span.sc {
+  color: #5E5E5E;
+  font-style: inherit;
+}
+
+code span.dv {
+  color: #AD0000;
+  font-style: inherit;
+}
+
+code span.kw {
+  color: #003B4F;
+  font-style: inherit;
+}
+
+.prevent-inlining {
+  content: "</";
+}
+
+/*# sourceMappingURL=debc5d5d77c3f9108843748ff7464032.css.map */
diff --git a/site_libs/quarto-html/quarto.js b/site_libs/quarto-html/quarto.js
new file mode 100644
index 0000000..3ebd49c
--- /dev/null
+++ b/site_libs/quarto-html/quarto.js
@@ -0,0 +1,899 @@
+const sectionChanged = new CustomEvent("quarto-sectionChanged", {
+  detail: {},
+  bubbles: true,
+  cancelable: false,
+  composed: false,
+});
+
+const layoutMarginEls = () => {
+  // Find any conflicting margin elements and add margins to the
+  // top to prevent overlap
+  const marginChildren = window.document.querySelectorAll(
+    ".column-margin.column-container > *, .margin-caption, .aside"
+  );
+
+  let lastBottom = 0;
+  for (const marginChild of marginChildren) {
+    if (marginChild.offsetParent !== null) {
+      // clear the top margin so we recompute it
+      marginChild.style.marginTop = null;
+      const top = marginChild.getBoundingClientRect().top + window.scrollY;
+      if (top < lastBottom) {
+        const marginChildStyle = window.getComputedStyle(marginChild);
+        const marginBottom = parseFloat(marginChildStyle["marginBottom"]);
+        const margin = lastBottom - top + marginBottom;
+        marginChild.style.marginTop = `${margin}px`;
+      }
+      const styles = window.getComputedStyle(marginChild);
+      const marginTop = parseFloat(styles["marginTop"]);
+      lastBottom = top + marginChild.getBoundingClientRect().height + marginTop;
+    }
+  }
+};
+
+window.document.addEventListener("DOMContentLoaded", function (_event) {
+  // Recompute the position of margin elements anytime the body size changes
+  if (window.ResizeObserver) {
+    const resizeObserver = new window.ResizeObserver(
+      throttle(() => {
+        layoutMarginEls();
+        if (
+          window.document.body.getBoundingClientRect().width < 990 &&
+          isReaderMode()
+        ) {
+          quartoToggleReader();
+        }
+      }, 50)
+    );
+    resizeObserver.observe(window.document.body);
+  }
+
+  const tocEl = window.document.querySelector('nav.toc-active[role="doc-toc"]');
+  const sidebarEl = window.document.getElementById("quarto-sidebar");
+  const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left");
+  const marginSidebarEl = window.document.getElementById(
+    "quarto-margin-sidebar"
+  );
+  // function to determine whether the element has a previous sibling that is active
+  const prevSiblingIsActiveLink = (el) => {
+    const sibling = el.previousElementSibling;
+    if (sibling && sibling.tagName === "A") {
+      return sibling.classList.contains("active");
+    } else {
+      return false;
+    }
+  };
+
+  // fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior)
+  function fireSlideEnter(e) {
+    const event = window.document.createEvent("Event");
+    event.initEvent("slideenter", true, true);
+    window.document.dispatchEvent(event);
+  }
+  const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]');
+  tabs.forEach((tab) => {
+    tab.addEventListener("shown.bs.tab", fireSlideEnter);
+  });
+
+  // fire slideEnter for tabby tab activations (for htmlwidget resize behavior)
+  document.addEventListener("tabby", fireSlideEnter, false);
+
+  // Track scrolling and mark TOC links as active
+  // get table of contents and sidebar (bail if we don't have at least one)
+  const tocLinks = tocEl
+    ? [...tocEl.querySelectorAll("a[data-scroll-target]")]
+    : [];
+  const makeActive = (link) => tocLinks[link].classList.add("active");
+  const removeActive = (link) => tocLinks[link].classList.remove("active");
+  const removeAllActive = () =>
+    [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link));
+
+  // activate the anchor for a section associated with this TOC entry
+  tocLinks.forEach((link) => {
+    link.addEventListener("click", () => {
+      if (link.href.indexOf("#") !== -1) {
+        const anchor = link.href.split("#")[1];
+        const heading = window.document.querySelector(
+          `[data-anchor-id=${anchor}]`
+        );
+        if (heading) {
+          // Add the class
+          heading.classList.add("reveal-anchorjs-link");
+
+          // function to show the anchor
+          const handleMouseout = () => {
+            heading.classList.remove("reveal-anchorjs-link");
+            heading.removeEventListener("mouseout", handleMouseout);
+          };
+
+          // add a function to clear the anchor when the user mouses out of it
+          heading.addEventListener("mouseout", handleMouseout);
+        }
+      }
+    });
+  });
+
+  const sections = tocLinks.map((link) => {
+    const target = link.getAttribute("data-scroll-target");
+    if (target.startsWith("#")) {
+      return window.document.getElementById(decodeURI(`${target.slice(1)}`));
+    } else {
+      return window.document.querySelector(decodeURI(`${target}`));
+    }
+  });
+
+  const sectionMargin = 200;
+  let currentActive = 0;
+  // track whether we've initialized state the first time
+  let init = false;
+
+  const updateActiveLink = () => {
+    // The index from bottom to top (e.g. reversed list)
+    let sectionIndex = -1;
+    if (
+      window.innerHeight + window.pageYOffset >=
+      window.document.body.offsetHeight
+    ) {
+      sectionIndex = 0;
+    } else {
+      sectionIndex = [...sections].reverse().findIndex((section) => {
+        if (section) {
+          return window.pageYOffset >= section.offsetTop - sectionMargin;
+        } else {
+          return false;
+        }
+      });
+    }
+    if (sectionIndex > -1) {
+      const current = sections.length - sectionIndex - 1;
+      if (current !== currentActive) {
+        removeAllActive();
+        currentActive = current;
+        makeActive(current);
+        if (init) {
+          window.dispatchEvent(sectionChanged);
+        }
+        init = true;
+      }
+    }
+  };
+
+  const inHiddenRegion = (top, bottom, hiddenRegions) => {
+    for (const region of hiddenRegions) {
+      if (top <= region.bottom && bottom >= region.top) {
+        return true;
+      }
+    }
+    return false;
+  };
+
+  const categorySelector = "header.quarto-title-block .quarto-category";
+  const activateCategories = (href) => {
+    // Find any categories
+    // Surround them with a link pointing back to:
+    // #category=Authoring
+    try {
+      const categoryEls = window.document.querySelectorAll(categorySelector);
+      for (const categoryEl of categoryEls) {
+        const categoryText = categoryEl.textContent;
+        if (categoryText) {
+          const link = `${href}#category=${encodeURIComponent(categoryText)}`;
+          const linkEl = window.document.createElement("a");
+          linkEl.setAttribute("href", link);
+          for (const child of categoryEl.childNodes) {
+            linkEl.append(child);
+          }
+          categoryEl.appendChild(linkEl);
+        }
+      }
+    } catch {
+      // Ignore errors
+    }
+  };
+  function hasTitleCategories() {
+    return window.document.querySelector(categorySelector) !== null;
+  }
+
+  function offsetRelativeUrl(url) {
+    const offset = getMeta("quarto:offset");
+    return offset ? offset + url : url;
+  }
+
+  function offsetAbsoluteUrl(url) {
+    const offset = getMeta("quarto:offset");
+    const baseUrl = new URL(offset, window.location);
+
+    const projRelativeUrl = url.replace(baseUrl, "");
+    if (projRelativeUrl.startsWith("/")) {
+      return projRelativeUrl;
+    } else {
+      return "/" + projRelativeUrl;
+    }
+  }
+
+  // read a meta tag value
+  function getMeta(metaName) {
+    const metas = window.document.getElementsByTagName("meta");
+    for (let i = 0; i < metas.length; i++) {
+      if (metas[i].getAttribute("name") === metaName) {
+        return metas[i].getAttribute("content");
+      }
+    }
+    return "";
+  }
+
+  async function findAndActivateCategories() {
+    const currentPagePath = offsetAbsoluteUrl(window.location.href);
+    const response = await fetch(offsetRelativeUrl("listings.json"));
+    if (response.status == 200) {
+      return response.json().then(function (listingPaths) {
+        const listingHrefs = [];
+        for (const listingPath of listingPaths) {
+          const pathWithoutLeadingSlash = listingPath.listing.substring(1);
+          for (const item of listingPath.items) {
+            if (
+              item === currentPagePath ||
+              item === currentPagePath + "index.html"
+            ) {
+              // Resolve this path against the offset to be sure
+              // we already are using the correct path to the listing
+              // (this adjusts the listing urls to be rooted against
+              // whatever root the page is actually running against)
+              const relative = offsetRelativeUrl(pathWithoutLeadingSlash);
+              const baseUrl = window.location;
+              const resolvedPath = new URL(relative, baseUrl);
+              listingHrefs.push(resolvedPath.pathname);
+              break;
+            }
+          }
+        }
+
+        // Look up the tree for a nearby linting and use that if we find one
+        const nearestListing = findNearestParentListing(
+          offsetAbsoluteUrl(window.location.pathname),
+          listingHrefs
+        );
+        if (nearestListing) {
+          activateCategories(nearestListing);
+        } else {
+          // See if the referrer is a listing page for this item
+          const referredRelativePath = offsetAbsoluteUrl(document.referrer);
+          const referrerListing = listingHrefs.find((listingHref) => {
+            const isListingReferrer =
+              listingHref === referredRelativePath ||
+              listingHref === referredRelativePath + "index.html";
+            return isListingReferrer;
+          });
+
+          if (referrerListing) {
+            // Try to use the referrer if possible
+            activateCategories(referrerListing);
+          } else if (listingHrefs.length > 0) {
+            // Otherwise, just fall back to the first listing
+            activateCategories(listingHrefs[0]);
+          }
+        }
+      });
+    }
+  }
+  if (hasTitleCategories()) {
+    findAndActivateCategories();
+  }
+
+  const findNearestParentListing = (href, listingHrefs) => {
+    if (!href || !listingHrefs) {
+      return undefined;
+    }
+    // Look up the tree for a nearby linting and use that if we find one
+    const relativeParts = href.substring(1).split("/");
+    while (relativeParts.length > 0) {
+      const path = relativeParts.join("/");
+      for (const listingHref of listingHrefs) {
+        if (listingHref.startsWith(path)) {
+          return listingHref;
+        }
+      }
+      relativeParts.pop();
+    }
+
+    return undefined;
+  };
+
+  const manageSidebarVisiblity = (el, placeholderDescriptor) => {
+    let isVisible = true;
+    let elRect;
+
+    return (hiddenRegions) => {
+      if (el === null) {
+        return;
+      }
+
+      // Find the last element of the TOC
+      const lastChildEl = el.lastElementChild;
+
+      if (lastChildEl) {
+        // Converts the sidebar to a menu
+        const convertToMenu = () => {
+          for (const child of el.children) {
+            child.style.opacity = 0;
+            child.style.overflow = "hidden";
+          }
+
+          nexttick(() => {
+            const toggleContainer = window.document.createElement("div");
+            toggleContainer.style.width = "100%";
+            toggleContainer.classList.add("zindex-over-content");
+            toggleContainer.classList.add("quarto-sidebar-toggle");
+            toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom
+            toggleContainer.id = placeholderDescriptor.id;
+            toggleContainer.style.position = "fixed";
+
+            const toggleIcon = window.document.createElement("i");
+            toggleIcon.classList.add("quarto-sidebar-toggle-icon");
+            toggleIcon.classList.add("bi");
+            toggleIcon.classList.add("bi-caret-down-fill");
+
+            const toggleTitle = window.document.createElement("div");
+            const titleEl = window.document.body.querySelector(
+              placeholderDescriptor.titleSelector
+            );
+            if (titleEl) {
+              toggleTitle.append(
+                titleEl.textContent || titleEl.innerText,
+                toggleIcon
+              );
+            }
+            toggleTitle.classList.add("zindex-over-content");
+            toggleTitle.classList.add("quarto-sidebar-toggle-title");
+            toggleContainer.append(toggleTitle);
+
+            const toggleContents = window.document.createElement("div");
+            toggleContents.classList = el.classList;
+            toggleContents.classList.add("zindex-over-content");
+            toggleContents.classList.add("quarto-sidebar-toggle-contents");
+            for (const child of el.children) {
+              if (child.id === "toc-title") {
+                continue;
+              }
+
+              const clone = child.cloneNode(true);
+              clone.style.opacity = 1;
+              clone.style.display = null;
+              toggleContents.append(clone);
+            }
+            toggleContents.style.height = "0px";
+            const positionToggle = () => {
+              // position the element (top left of parent, same width as parent)
+              if (!elRect) {
+                elRect = el.getBoundingClientRect();
+              }
+              toggleContainer.style.left = `${elRect.left}px`;
+              toggleContainer.style.top = `${elRect.top}px`;
+              toggleContainer.style.width = `${elRect.width}px`;
+            };
+            positionToggle();
+
+            toggleContainer.append(toggleContents);
+            el.parentElement.prepend(toggleContainer);
+
+            // Process clicks
+            let tocShowing = false;
+            // Allow the caller to control whether this is dismissed
+            // when it is clicked (e.g. sidebar navigation supports
+            // opening and closing the nav tree, so don't dismiss on click)
+            const clickEl = placeholderDescriptor.dismissOnClick
+              ? toggleContainer
+              : toggleTitle;
+
+            const closeToggle = () => {
+              if (tocShowing) {
+                toggleContainer.classList.remove("expanded");
+                toggleContents.style.height = "0px";
+                tocShowing = false;
+              }
+            };
+
+            // Get rid of any expanded toggle if the user scrolls
+            window.document.addEventListener(
+              "scroll",
+              throttle(() => {
+                closeToggle();
+              }, 50)
+            );
+
+            // Handle positioning of the toggle
+            window.addEventListener(
+              "resize",
+              throttle(() => {
+                elRect = undefined;
+                positionToggle();
+              }, 50)
+            );
+
+            window.addEventListener("quarto-hrChanged", () => {
+              elRect = undefined;
+            });
+
+            // Process the click
+            clickEl.onclick = () => {
+              if (!tocShowing) {
+                toggleContainer.classList.add("expanded");
+                toggleContents.style.height = null;
+                tocShowing = true;
+              } else {
+                closeToggle();
+              }
+            };
+          });
+        };
+
+        // Converts a sidebar from a menu back to a sidebar
+        const convertToSidebar = () => {
+          for (const child of el.children) {
+            child.style.opacity = 1;
+            child.style.overflow = null;
+          }
+
+          const placeholderEl = window.document.getElementById(
+            placeholderDescriptor.id
+          );
+          if (placeholderEl) {
+            placeholderEl.remove();
+          }
+
+          el.classList.remove("rollup");
+        };
+
+        if (isReaderMode()) {
+          convertToMenu();
+          isVisible = false;
+        } else {
+          // Find the top and bottom o the element that is being managed
+          const elTop = el.offsetTop;
+          const elBottom =
+            elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight;
+
+          if (!isVisible) {
+            // If the element is current not visible reveal if there are
+            // no conflicts with overlay regions
+            if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) {
+              convertToSidebar();
+              isVisible = true;
+            }
+          } else {
+            // If the element is visible, hide it if it conflicts with overlay regions
+            // and insert a placeholder toggle (or if we're in reader mode)
+            if (inHiddenRegion(elTop, elBottom, hiddenRegions)) {
+              convertToMenu();
+              isVisible = false;
+            }
+          }
+        }
+      }
+    };
+  };
+
+  const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]');
+  for (const tabEl of tabEls) {
+    const id = tabEl.getAttribute("data-bs-target");
+    if (id) {
+      const columnEl = document.querySelector(
+        `${id} .column-margin, .tabset-margin-content`
+      );
+      if (columnEl)
+        tabEl.addEventListener("shown.bs.tab", function (event) {
+          const el = event.srcElement;
+          if (el) {
+            const visibleCls = `${el.id}-margin-content`;
+            // walk up until we find a parent tabset
+            let panelTabsetEl = el.parentElement;
+            while (panelTabsetEl) {
+              if (panelTabsetEl.classList.contains("panel-tabset")) {
+                break;
+              }
+              panelTabsetEl = panelTabsetEl.parentElement;
+            }
+
+            if (panelTabsetEl) {
+              const prevSib = panelTabsetEl.previousElementSibling;
+              if (
+                prevSib &&
+                prevSib.classList.contains("tabset-margin-container")
+              ) {
+                const childNodes = prevSib.querySelectorAll(
+                  ".tabset-margin-content"
+                );
+                for (const childEl of childNodes) {
+                  if (childEl.classList.contains(visibleCls)) {
+                    childEl.classList.remove("collapse");
+                  } else {
+                    childEl.classList.add("collapse");
+                  }
+                }
+              }
+            }
+          }
+
+          layoutMarginEls();
+        });
+    }
+  }
+
+  // Manage the visibility of the toc and the sidebar
+  const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, {
+    id: "quarto-toc-toggle",
+    titleSelector: "#toc-title",
+    dismissOnClick: true,
+  });
+  const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, {
+    id: "quarto-sidebarnav-toggle",
+    titleSelector: ".title",
+    dismissOnClick: false,
+  });
+  let tocLeftScrollVisibility;
+  if (leftTocEl) {
+    tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, {
+      id: "quarto-lefttoc-toggle",
+      titleSelector: "#toc-title",
+      dismissOnClick: true,
+    });
+  }
+
+  // Find the first element that uses formatting in special columns
+  const conflictingEls = window.document.body.querySelectorAll(
+    '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]'
+  );
+
+  // Filter all the possibly conflicting elements into ones
+  // the do conflict on the left or ride side
+  const arrConflictingEls = Array.from(conflictingEls);
+  const leftSideConflictEls = arrConflictingEls.filter((el) => {
+    if (el.tagName === "ASIDE") {
+      return false;
+    }
+    return Array.from(el.classList).find((className) => {
+      return (
+        className !== "column-body" &&
+        className.startsWith("column-") &&
+        !className.endsWith("right") &&
+        !className.endsWith("container") &&
+        className !== "column-margin"
+      );
+    });
+  });
+  const rightSideConflictEls = arrConflictingEls.filter((el) => {
+    if (el.tagName === "ASIDE") {
+      return true;
+    }
+
+    const hasMarginCaption = Array.from(el.classList).find((className) => {
+      return className == "margin-caption";
+    });
+    if (hasMarginCaption) {
+      return true;
+    }
+
+    return Array.from(el.classList).find((className) => {
+      return (
+        className !== "column-body" &&
+        !className.endsWith("container") &&
+        className.startsWith("column-") &&
+        !className.endsWith("left")
+      );
+    });
+  });
+
+  const kOverlapPaddingSize = 10;
+  function toRegions(els) {
+    return els.map((el) => {
+      const boundRect = el.getBoundingClientRect();
+      const top =
+        boundRect.top +
+        document.documentElement.scrollTop -
+        kOverlapPaddingSize;
+      return {
+        top,
+        bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize,
+      };
+    });
+  }
+
+  let hasObserved = false;
+  const visibleItemObserver = (els) => {
+    let visibleElements = [...els];
+    const intersectionObserver = new IntersectionObserver(
+      (entries, _observer) => {
+        entries.forEach((entry) => {
+          if (entry.isIntersecting) {
+            if (visibleElements.indexOf(entry.target) === -1) {
+              visibleElements.push(entry.target);
+            }
+          } else {
+            visibleElements = visibleElements.filter((visibleEntry) => {
+              return visibleEntry !== entry;
+            });
+          }
+        });
+
+        if (!hasObserved) {
+          hideOverlappedSidebars();
+        }
+        hasObserved = true;
+      },
+      {}
+    );
+    els.forEach((el) => {
+      intersectionObserver.observe(el);
+    });
+
+    return {
+      getVisibleEntries: () => {
+        return visibleElements;
+      },
+    };
+  };
+
+  const rightElementObserver = visibleItemObserver(rightSideConflictEls);
+  const leftElementObserver = visibleItemObserver(leftSideConflictEls);
+
+  const hideOverlappedSidebars = () => {
+    marginScrollVisibility(toRegions(rightElementObserver.getVisibleEntries()));
+    sidebarScrollVisiblity(toRegions(leftElementObserver.getVisibleEntries()));
+    if (tocLeftScrollVisibility) {
+      tocLeftScrollVisibility(
+        toRegions(leftElementObserver.getVisibleEntries())
+      );
+    }
+  };
+
+  window.quartoToggleReader = () => {
+    // Applies a slow class (or removes it)
+    // to update the transition speed
+    const slowTransition = (slow) => {
+      const manageTransition = (id, slow) => {
+        const el = document.getElementById(id);
+        if (el) {
+          if (slow) {
+            el.classList.add("slow");
+          } else {
+            el.classList.remove("slow");
+          }
+        }
+      };
+
+      manageTransition("TOC", slow);
+      manageTransition("quarto-sidebar", slow);
+    };
+    const readerMode = !isReaderMode();
+    setReaderModeValue(readerMode);
+
+    // If we're entering reader mode, slow the transition
+    if (readerMode) {
+      slowTransition(readerMode);
+    }
+    highlightReaderToggle(readerMode);
+    hideOverlappedSidebars();
+
+    // If we're exiting reader mode, restore the non-slow transition
+    if (!readerMode) {
+      slowTransition(!readerMode);
+    }
+  };
+
+  const highlightReaderToggle = (readerMode) => {
+    const els = document.querySelectorAll(".quarto-reader-toggle");
+    if (els) {
+      els.forEach((el) => {
+        if (readerMode) {
+          el.classList.add("reader");
+        } else {
+          el.classList.remove("reader");
+        }
+      });
+    }
+  };
+
+  const setReaderModeValue = (val) => {
+    if (window.location.protocol !== "file:") {
+      window.localStorage.setItem("quarto-reader-mode", val);
+    } else {
+      localReaderMode = val;
+    }
+  };
+
+  const isReaderMode = () => {
+    if (window.location.protocol !== "file:") {
+      return window.localStorage.getItem("quarto-reader-mode") === "true";
+    } else {
+      return localReaderMode;
+    }
+  };
+  let localReaderMode = null;
+
+  const tocOpenDepthStr = tocEl?.getAttribute("data-toc-expanded");
+  const tocOpenDepth = tocOpenDepthStr ? Number(tocOpenDepthStr) : 1;
+
+  // Walk the TOC and collapse/expand nodes
+  // Nodes are expanded if:
+  // - they are top level
+  // - they have children that are 'active' links
+  // - they are directly below an link that is 'active'
+  const walk = (el, depth) => {
+    // Tick depth when we enter a UL
+    if (el.tagName === "UL") {
+      depth = depth + 1;
+    }
+
+    // It this is active link
+    let isActiveNode = false;
+    if (el.tagName === "A" && el.classList.contains("active")) {
+      isActiveNode = true;
+    }
+
+    // See if there is an active child to this element
+    let hasActiveChild = false;
+    for (child of el.children) {
+      hasActiveChild = walk(child, depth) || hasActiveChild;
+    }
+
+    // Process the collapse state if this is an UL
+    if (el.tagName === "UL") {
+      if (tocOpenDepth === -1 && depth > 1) {
+        el.classList.add("collapse");
+      } else if (
+        depth <= tocOpenDepth ||
+        hasActiveChild ||
+        prevSiblingIsActiveLink(el)
+      ) {
+        el.classList.remove("collapse");
+      } else {
+        el.classList.add("collapse");
+      }
+
+      // untick depth when we leave a UL
+      depth = depth - 1;
+    }
+    return hasActiveChild || isActiveNode;
+  };
+
+  // walk the TOC and expand / collapse any items that should be shown
+
+  if (tocEl) {
+    walk(tocEl, 0);
+    updateActiveLink();
+  }
+
+  // Throttle the scroll event and walk peridiocally
+  window.document.addEventListener(
+    "scroll",
+    throttle(() => {
+      if (tocEl) {
+        updateActiveLink();
+        walk(tocEl, 0);
+      }
+      if (!isReaderMode()) {
+        hideOverlappedSidebars();
+      }
+    }, 5)
+  );
+  window.addEventListener(
+    "resize",
+    throttle(() => {
+      if (!isReaderMode()) {
+        hideOverlappedSidebars();
+      }
+    }, 10)
+  );
+  hideOverlappedSidebars();
+  highlightReaderToggle(isReaderMode());
+});
+
+// grouped tabsets
+window.addEventListener("pageshow", (_event) => {
+  function getTabSettings() {
+    const data = localStorage.getItem("quarto-persistent-tabsets-data");
+    if (!data) {
+      localStorage.setItem("quarto-persistent-tabsets-data", "{}");
+      return {};
+    }
+    if (data) {
+      return JSON.parse(data);
+    }
+  }
+
+  function setTabSettings(data) {
+    localStorage.setItem(
+      "quarto-persistent-tabsets-data",
+      JSON.stringify(data)
+    );
+  }
+
+  function setTabState(groupName, groupValue) {
+    const data = getTabSettings();
+    data[groupName] = groupValue;
+    setTabSettings(data);
+  }
+
+  function toggleTab(tab, active) {
+    const tabPanelId = tab.getAttribute("aria-controls");
+    const tabPanel = document.getElementById(tabPanelId);
+    if (active) {
+      tab.classList.add("active");
+      tabPanel.classList.add("active");
+    } else {
+      tab.classList.remove("active");
+      tabPanel.classList.remove("active");
+    }
+  }
+
+  function toggleAll(selectedGroup, selectorsToSync) {
+    for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) {
+      const active = selectedGroup === thisGroup;
+      for (const tab of tabs) {
+        toggleTab(tab, active);
+      }
+    }
+  }
+
+  function findSelectorsToSyncByLanguage() {
+    const result = {};
+    const tabs = Array.from(
+      document.querySelectorAll(`div[data-group] a[id^='tabset-']`)
+    );
+    for (const item of tabs) {
+      const div = item.parentElement.parentElement.parentElement;
+      const group = div.getAttribute("data-group");
+      if (!result[group]) {
+        result[group] = {};
+      }
+      const selectorsToSync = result[group];
+      const value = item.innerHTML;
+      if (!selectorsToSync[value]) {
+        selectorsToSync[value] = [];
+      }
+      selectorsToSync[value].push(item);
+    }
+    return result;
+  }
+
+  function setupSelectorSync() {
+    const selectorsToSync = findSelectorsToSyncByLanguage();
+    Object.entries(selectorsToSync).forEach(([group, tabSetsByValue]) => {
+      Object.entries(tabSetsByValue).forEach(([value, items]) => {
+        items.forEach((item) => {
+          item.addEventListener("click", (_event) => {
+            setTabState(group, value);
+            toggleAll(value, selectorsToSync[group]);
+          });
+        });
+      });
+    });
+    return selectorsToSync;
+  }
+
+  const selectorsToSync = setupSelectorSync();
+  for (const [group, selectedName] of Object.entries(getTabSettings())) {
+    const selectors = selectorsToSync[group];
+    // it's possible that stale state gives us empty selections, so we explicitly check here.
+    if (selectors) {
+      toggleAll(selectedName, selectors);
+    }
+  }
+});
+
+function throttle(func, wait) {
+  let waiting = false;
+  return function () {
+    if (!waiting) {
+      func.apply(this, arguments);
+      waiting = true;
+      setTimeout(function () {
+        waiting = false;
+      }, wait);
+    }
+  };
+}
+
+function nexttick(func) {
+  return setTimeout(func, 0);
+}
diff --git a/site_libs/quarto-html/tippy.css b/site_libs/quarto-html/tippy.css
new file mode 100644
index 0000000..e6ae635
--- /dev/null
+++ b/site_libs/quarto-html/tippy.css
@@ -0,0 +1 @@
+.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 10px)}.tippy-box{position:relative;background-color:#333;color:#fff;border-radius:4px;font-size:14px;line-height:1.4;white-space:normal;outline:0;transition-property:transform,visibility,opacity}.tippy-box[data-placement^=top]>.tippy-arrow{bottom:0}.tippy-box[data-placement^=top]>.tippy-arrow:before{bottom:-7px;left:0;border-width:8px 8px 0;border-top-color:initial;transform-origin:center top}.tippy-box[data-placement^=bottom]>.tippy-arrow{top:0}.tippy-box[data-placement^=bottom]>.tippy-arrow:before{top:-7px;left:0;border-width:0 8px 8px;border-bottom-color:initial;transform-origin:center bottom}.tippy-box[data-placement^=left]>.tippy-arrow{right:0}.tippy-box[data-placement^=left]>.tippy-arrow:before{border-width:8px 0 8px 8px;border-left-color:initial;right:-7px;transform-origin:center left}.tippy-box[data-placement^=right]>.tippy-arrow{left:0}.tippy-box[data-placement^=right]>.tippy-arrow:before{left:-7px;border-width:8px 8px 8px 0;border-right-color:initial;transform-origin:center right}.tippy-box[data-inertia][data-state=visible]{transition-timing-function:cubic-bezier(.54,1.5,.38,1.11)}.tippy-arrow{width:16px;height:16px;color:#333}.tippy-arrow:before{content:"";position:absolute;border-color:transparent;border-style:solid}.tippy-content{position:relative;padding:5px 9px;z-index:1}
\ No newline at end of file
diff --git a/site_libs/quarto-html/tippy.umd.min.js b/site_libs/quarto-html/tippy.umd.min.js
new file mode 100644
index 0000000..ca292be
--- /dev/null
+++ b/site_libs/quarto-html/tippy.umd.min.js
@@ -0,0 +1,2 @@
+!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?module.exports=t(require("@popperjs/core")):"function"==typeof define&&define.amd?define(["@popperjs/core"],t):(e=e||self).tippy=t(e.Popper)}(this,(function(e){"use strict";var t={passive:!0,capture:!0},n=function(){return document.body};function r(e,t,n){if(Array.isArray(e)){var r=e[t];return null==r?Array.isArray(n)?n[t]:n:r}return e}function o(e,t){var n={}.toString.call(e);return 0===n.indexOf("[object")&&n.indexOf(t+"]")>-1}function i(e,t){return"function"==typeof e?e.apply(void 0,t):e}function a(e,t){return 0===t?e:function(r){clearTimeout(n),n=setTimeout((function(){e(r)}),t)};var n}function s(e,t){var n=Object.assign({},e);return t.forEach((function(e){delete n[e]})),n}function u(e){return[].concat(e)}function c(e,t){-1===e.indexOf(t)&&e.push(t)}function p(e){return e.split("-")[0]}function f(e){return[].slice.call(e)}function l(e){return Object.keys(e).reduce((function(t,n){return void 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diff --git a/site_libs/quarto-listing/list.min.js b/site_libs/quarto-listing/list.min.js
new file mode 100644
index 0000000..8131881
--- /dev/null
+++ b/site_libs/quarto-listing/list.min.js
@@ -0,0 +1,2 @@
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e,r,n,s={resetList:function(){t.i=1,t.templater.clear(),n=void 0},setOptions:function(t){2==t.length&&t[1]instanceof Array?e=t[1]:2==t.length&&"function"==typeof t[1]?(e=void 0,n=t[1]):3==t.length?(e=t[1],n=t[2]):e=void 0},setColumns:function(){0!==t.items.length&&void 0===e&&(e=void 0===t.searchColumns?s.toArray(t.items[0].values()):t.searchColumns)},setSearchString:function(e){e=(e=t.utils.toString(e).toLowerCase()).replace(/[-[\]{}()*+?.,\\^$|#]/g,"\\$&"),r=e},toArray:function(t){var e=[];for(var r in t)e.push(r);return e}},i=function(){for(var n,s=[],i=r;null!==(n=i.match(/"([^"]+)"/));)s.push(n[1]),i=i.substring(0,n.index)+i.substring(n.index+n[0].length);(i=i.trim()).length&&(s=s.concat(i.split(/\s+/)));for(var a=0,o=t.items.length;a<o;a++){var l=t.items[a];if(l.found=!1,s.length){for(var u=0,c=s.length;u<c;u++){for(var f=!1,h=0,d=e.length;h<d;h++){var v=l.values(),g=e[h];if(v.hasOwnProperty(g)&&void 0!==v[g]&&null!==v[g])if(-1!==("string"!=typeof 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r=0,n=e.els.length;r<n;r++)t.utils.classes(e.els[r]).remove("asc"),t.utils.classes(e.els[r]).remove("desc")},getOrder:function(e){var r=t.utils.getAttribute(e,"data-order");return"asc"==r||"desc"==r?r:t.utils.classes(e).has("desc")?"asc":t.utils.classes(e).has("asc")?"desc":"asc"},getInSensitive:function(e,r){var n=t.utils.getAttribute(e,"data-insensitive");r.insensitive="false"!==n},setOrder:function(r){for(var n=0,s=e.els.length;n<s;n++){var i=e.els[n];if(t.utils.getAttribute(i,"data-sort")===r.valueName){var a=t.utils.getAttribute(i,"data-order");"asc"==a||"desc"==a?a==r.order&&t.utils.classes(i).add(r.order):t.utils.classes(i).add(r.order)}}}},r=function(){t.trigger("sortStart");var r={},n=arguments[0].currentTarget||arguments[0].srcElement||void 0;n?(r.valueName=t.utils.getAttribute(n,"data-sort"),e.getInSensitive(n,r),r.order=e.getOrder(n)):((r=arguments[1]||r).valueName=arguments[0],r.order=r.order||"asc",r.insensitive=void 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o.attr&&o.name?(a=t.utils.getByClass(n,o.name,!0))&&a.setAttribute(o.attr,""):(a=t.utils.getByClass(n,o,!0))&&(a.innerHTML="")}return n},s=function(){for(var e=t.list.childNodes,r=0,n=e.length;r<n;r++)if(void 0===e[r].data)return e[r].cloneNode(!0)},i=function(t){if("string"==typeof t){if(/<tr[\s>]/g.exec(t)){var e=document.createElement("tbody");return e.innerHTML=t,e.firstElementChild}if(-1!==t.indexOf("<")){var r=document.createElement("div");return r.innerHTML=t,r.firstElementChild}}},a=function(e,r,n){var s=void 0,i=function(e){for(var r=0,n=t.valueNames.length;r<n;r++){var s=t.valueNames[r];if(s.data){for(var i=s.data,a=0,o=i.length;a<o;a++)if(i[a]===e)return{data:e}}else{if(s.attr&&s.name&&s.name==e)return s;if(s===e)return e}}}(r);i&&(i.data?e.elm.setAttribute("data-"+i.data,n):i.attr&&i.name?(s=t.utils.getByClass(e.elm,i.name,!0))&&s.setAttribute(i.attr,n):(s=t.utils.getByClass(e.elm,i,!0))&&(s.innerHTML=n))};this.get=function(e,n){r.create(e);for(var s={},i=0,a=n.length;i<a;i++){var o=void 0,l=n[i];if(l.data)for(var u=0,c=l.data.length;u<c;u++)s[l.data[u]]=t.utils.getAttribute(e.elm,"data-"+l.data[u]);else l.attr&&l.name?(o=t.utils.getByClass(e.elm,l.name,!0),s[l.name]=o?t.utils.getAttribute(o,l.attr):""):(o=t.utils.getByClass(e.elm,l,!0),s[l]=o?o.innerHTML:"")}return s},this.set=function(t,e){if(!r.create(t))for(var n in e)e.hasOwnProperty(n)&&a(t,n,e[n])},this.create=function(t){return void 0===t.elm&&(t.elm=e(t.values()),r.set(t,t.values()),!0)},this.remove=function(e){e.elm.parentNode===t.list&&t.list.removeChild(e.elm)},this.show=function(e){r.create(e),t.list.appendChild(e.elm)},this.hide=function(e){void 0!==e.elm&&e.elm.parentNode===t.list&&t.list.removeChild(e.elm)},this.clear=function(){if(t.list.hasChildNodes())for(;t.list.childNodes.length>=1;)t.list.removeChild(t.list.firstChild)},function(){var r;if("function"!=typeof t.item){if(!(r="string"==typeof t.item?-1===t.item.indexOf("<")?document.getElementById(t.item):i(t.item):s()))throw new Error("The list needs to have at least one item on init otherwise you'll have to add a template.");r=n(r,t.valueNames),e=function(){return r.cloneNode(!0)}}else e=function(e){var r=t.item(e);return i(r)}}()};t.exports=function(t){return new e(t)}},"./src/utils/classes.js":function(t,e,r){var n=r("./src/utils/index-of.js"),s=/\s+/;Object.prototype.toString;function i(t){if(!t||!t.nodeType)throw new Error("A DOM element reference is required");this.el=t,this.list=t.classList}t.exports=function(t){return new i(t)},i.prototype.add=function(t){if(this.list)return this.list.add(t),this;var e=this.array();return~n(e,t)||e.push(t),this.el.className=e.join(" "),this},i.prototype.remove=function(t){if(this.list)return this.list.remove(t),this;var e=this.array(),r=n(e,t);return~r&&e.splice(r,1),this.el.className=e.join(" "),this},i.prototype.toggle=function(t,e){return this.list?(void 0!==e?e!==this.list.toggle(t,e)&&this.list.toggle(t):this.list.toggle(t),this):(void 0!==e?e?this.add(t):this.remove(t):this.has(t)?this.remove(t):this.add(t),this)},i.prototype.array=function(){var t=(this.el.getAttribute("class")||"").replace(/^\s+|\s+$/g,"").split(s);return""===t[0]&&t.shift(),t},i.prototype.has=i.prototype.contains=function(t){return this.list?this.list.contains(t):!!~n(this.array(),t)}},"./src/utils/events.js":function(t,e,r){var n=window.addEventListener?"addEventListener":"attachEvent",s=window.removeEventListener?"removeEventListener":"detachEvent",i="addEventListener"!==n?"on":"",a=r("./src/utils/to-array.js");e.bind=function(t,e,r,s){for(var o=0,l=(t=a(t)).length;o<l;o++)t[o][n](i+e,r,s||!1)},e.unbind=function(t,e,r,n){for(var o=0,l=(t=a(t)).length;o<l;o++)t[o][s](i+e,r,n||!1)},e.debounce=function(t,e,r){var n;return e?function(){var s=this,i=arguments,a=function(){n=null,r||t.apply(s,i)},o=r&&!n;clearTimeout(n),n=setTimeout(a,e),o&&t.apply(s,i)}:t}},"./src/utils/extend.js":function(t){t.exports=function(t){for(var e,r=Array.prototype.slice.call(arguments,1),n=0;e=r[n];n++)if(e)for(var s in e)t[s]=e[s];return t}},"./src/utils/fuzzy.js":function(t){t.exports=function(t,e,r){var n=r.location||0,s=r.distance||100,i=r.threshold||.4;if(e===t)return!0;if(e.length>32)return!1;var a=n,o=function(){var t,r={};for(t=0;t<e.length;t++)r[e.charAt(t)]=0;for(t=0;t<e.length;t++)r[e.charAt(t)]|=1<<e.length-t-1;return r}();function l(t,r){var n=t/e.length,i=Math.abs(a-r);return s?n+i/s:i?1:n}var u=i,c=t.indexOf(e,a);-1!=c&&(u=Math.min(l(0,c),u),-1!=(c=t.lastIndexOf(e,a+e.length))&&(u=Math.min(l(0,c),u)));var f,h,d=1<<e.length-1;c=-1;for(var v,g=e.length+t.length,m=0;m<e.length;m++){for(f=0,h=g;f<h;)l(m,a+h)<=u?f=h:g=h,h=Math.floor((g-f)/2+f);g=h;var p=Math.max(1,a-h+1),y=Math.min(a+h,t.length)+e.length,C=Array(y+2);C[y+1]=(1<<m)-1;for(var b=y;b>=p;b--){var j=o[t.charAt(b-1)];if(C[b]=0===m?(C[b+1]<<1|1)&j:(C[b+1]<<1|1)&j|(v[b+1]|v[b])<<1|1|v[b+1],C[b]&d){var x=l(m,b-1);if(x<=u){if(u=x,!((c=b-1)>a))break;p=Math.max(1,2*a-c)}}}if(l(m+1,a)>u)break;v=C}return!(c<0)}},"./src/utils/get-attribute.js":function(t){t.exports=function(t,e){var r=t.getAttribute&&t.getAttribute(e)||null;if(!r)for(var n=t.attributes,s=n.length,i=0;i<s;i++)void 0!==n[i]&&n[i].nodeName===e&&(r=n[i].nodeValue);return r}},"./src/utils/get-by-class.js":function(t){t.exports=function(t,e,r,n){return(n=n||{}).test&&n.getElementsByClassName||!n.test&&document.getElementsByClassName?function(t,e,r){return r?t.getElementsByClassName(e)[0]:t.getElementsByClassName(e)}(t,e,r):n.test&&n.querySelector||!n.test&&document.querySelector?function(t,e,r){return e="."+e,r?t.querySelector(e):t.querySelectorAll(e)}(t,e,r):function(t,e,r){for(var n=[],s=t.getElementsByTagName("*"),i=s.length,a=new RegExp("(^|\\s)"+e+"(\\s|$)"),o=0,l=0;o<i;o++)if(a.test(s[o].className)){if(r)return s[o];n[l]=s[o],l++}return n}(t,e,r)}},"./src/utils/index-of.js":function(t){var e=[].indexOf;t.exports=function(t,r){if(e)return t.indexOf(r);for(var n=0,s=t.length;n<s;++n)if(t[n]===r)return n;return-1}},"./src/utils/to-array.js":function(t){t.exports=function(t){if(void 0===t)return[];if(null===t)return[null];if(t===window)return[window];if("string"==typeof t)return[t];if(function(t){return"[object Array]"===Object.prototype.toString.call(t)}(t))return t;if("number"!=typeof t.length)return[t];if("function"==typeof t&&t instanceof Function)return[t];for(var e=[],r=0,n=t.length;r<n;r++)(Object.prototype.hasOwnProperty.call(t,r)||r in t)&&e.push(t[r]);return e.length?e:[]}},"./src/utils/to-string.js":function(t){t.exports=function(t){return t=(t=null===(t=void 0===t?"":t)?"":t).toString()}},"./node_modules/string-natural-compare/natural-compare.js":function(t){"use strict";var e,r,n=0;function s(t){return t>=48&&t<=57}function i(t,e){for(var i=(t+="").length,a=(e+="").length,o=0,l=0;o<i&&l<a;){var u=t.charCodeAt(o),c=e.charCodeAt(l);if(s(u)){if(!s(c))return u-c;for(var f=o,h=l;48===u&&++f<i;)u=t.charCodeAt(f);for(;48===c&&++h<a;)c=e.charCodeAt(h);for(var d=f,v=h;d<i&&s(t.charCodeAt(d));)++d;for(;v<a&&s(e.charCodeAt(v));)++v;var g=d-f-v+h;if(g)return g;for(;f<d;)if(g=t.charCodeAt(f++)-e.charCodeAt(h++))return g;o=d,l=v}else{if(u!==c)return u<n&&c<n&&-1!==r[u]&&-1!==r[c]?r[u]-r[c]:u-c;++o,++l}}return o>=i&&l<a&&i>=a?-1:l>=a&&o<i&&a>=i?1:i-a}i.caseInsensitive=i.i=function(t,e){return i((""+t).toLowerCase(),(""+e).toLowerCase())},Object.defineProperties(i,{alphabet:{get:function(){return e},set:function(t){r=[];var s=0;if(e=t)for(;s<e.length;s++)r[e.charCodeAt(s)]=s;for(n=r.length,s=0;s<n;s++)void 0===r[s]&&(r[s]=-1)}}}),t.exports=i}},e={};return function r(n){if(e[n])return e[n].exports;var s=e[n]={exports:{}};return t[n](s,s.exports,r),s.exports}("./src/index.js")}();
+//# sourceMappingURL=list.min.js.map
\ No newline at end of file
diff --git a/site_libs/quarto-listing/quarto-listing.js b/site_libs/quarto-listing/quarto-listing.js
new file mode 100644
index 0000000..88d209a
--- /dev/null
+++ b/site_libs/quarto-listing/quarto-listing.js
@@ -0,0 +1,243 @@
+const kProgressiveAttr = "data-src";
+let categoriesLoaded = false;
+
+window.quartoListingCategory = (category) => {
+  if (categoriesLoaded) {
+    activateCategory(category);
+    setCategoryHash(category);
+  }
+};
+
+window["quarto-listing-loaded"] = () => {
+  // Process any existing hash
+  const hash = getHash();
+
+  if (hash) {
+    // If there is a category, switch to that
+    if (hash.category) {
+      activateCategory(hash.category);
+    }
+    // Paginate a specific listing
+    const listingIds = Object.keys(window["quarto-listings"]);
+    for (const listingId of listingIds) {
+      const page = hash[getListingPageKey(listingId)];
+      if (page) {
+        showPage(listingId, page);
+      }
+    }
+  }
+
+  const listingIds = Object.keys(window["quarto-listings"]);
+  for (const listingId of listingIds) {
+    // The actual list
+    const list = window["quarto-listings"][listingId];
+
+    // Update the handlers for pagination events
+    refreshPaginationHandlers(listingId);
+
+    // Render any visible items that need it
+    renderVisibleProgressiveImages(list);
+
+    // Whenever the list is updated, we also need to
+    // attach handlers to the new pagination elements
+    // and refresh any newly visible items.
+    list.on("updated", function () {
+      renderVisibleProgressiveImages(list);
+      setTimeout(() => refreshPaginationHandlers(listingId));
+
+      // Show or hide the no matching message
+      toggleNoMatchingMessage(list);
+    });
+  }
+};
+
+window.document.addEventListener("DOMContentLoaded", function (_event) {
+  // Attach click handlers to categories
+  const categoryEls = window.document.querySelectorAll(
+    ".quarto-listing-category .category"
+  );
+
+  for (const categoryEl of categoryEls) {
+    const category = categoryEl.getAttribute("data-category");
+    categoryEl.onclick = () => {
+      activateCategory(category);
+      setCategoryHash(category);
+    };
+  }
+
+  // Attach a click handler to the category title
+  // (there should be only one, but since it is a class name, handle N)
+  const categoryTitleEls = window.document.querySelectorAll(
+    ".quarto-listing-category-title"
+  );
+  for (const categoryTitleEl of categoryTitleEls) {
+    categoryTitleEl.onclick = () => {
+      activateCategory("");
+      setCategoryHash("");
+    };
+  }
+
+  categoriesLoaded = true;
+});
+
+function toggleNoMatchingMessage(list) {
+  const selector = `#${list.listContainer.id} .listing-no-matching`;
+  const noMatchingEl = window.document.querySelector(selector);
+  if (noMatchingEl) {
+    if (list.visibleItems.length === 0) {
+      noMatchingEl.classList.remove("d-none");
+    } else {
+      if (!noMatchingEl.classList.contains("d-none")) {
+        noMatchingEl.classList.add("d-none");
+      }
+    }
+  }
+}
+
+function setCategoryHash(category) {
+  setHash({ category });
+}
+
+function setPageHash(listingId, page) {
+  const currentHash = getHash() || {};
+  currentHash[getListingPageKey(listingId)] = page;
+  setHash(currentHash);
+}
+
+function getListingPageKey(listingId) {
+  return `${listingId}-page`;
+}
+
+function refreshPaginationHandlers(listingId) {
+  const listingEl = window.document.getElementById(listingId);
+  const paginationEls = listingEl.querySelectorAll(
+    ".pagination li.page-item:not(.disabled) .page.page-link"
+  );
+  for (const paginationEl of paginationEls) {
+    paginationEl.onclick = (sender) => {
+      setPageHash(listingId, sender.target.getAttribute("data-i"));
+      showPage(listingId, sender.target.getAttribute("data-i"));
+      return false;
+    };
+  }
+}
+
+function renderVisibleProgressiveImages(list) {
+  // Run through the visible items and render any progressive images
+  for (const item of list.visibleItems) {
+    const itemEl = item.elm;
+    if (itemEl) {
+      const progressiveImgs = itemEl.querySelectorAll(
+        `img[${kProgressiveAttr}]`
+      );
+      for (const progressiveImg of progressiveImgs) {
+        const srcValue = progressiveImg.getAttribute(kProgressiveAttr);
+        if (srcValue) {
+          progressiveImg.setAttribute("src", srcValue);
+        }
+        progressiveImg.removeAttribute(kProgressiveAttr);
+      }
+    }
+  }
+}
+
+function getHash() {
+  // Hashes are of the form
+  // #name:value|name1:value1|name2:value2
+  const currentUrl = new URL(window.location);
+  const hashRaw = currentUrl.hash ? currentUrl.hash.slice(1) : undefined;
+  return parseHash(hashRaw);
+}
+
+const kAnd = "&";
+const kEquals = "=";
+
+function parseHash(hash) {
+  if (!hash) {
+    return undefined;
+  }
+  const hasValuesStrs = hash.split(kAnd);
+  const hashValues = hasValuesStrs
+    .map((hashValueStr) => {
+      const vals = hashValueStr.split(kEquals);
+      if (vals.length === 2) {
+        return { name: vals[0], value: vals[1] };
+      } else {
+        return undefined;
+      }
+    })
+    .filter((value) => {
+      return value !== undefined;
+    });
+
+  const hashObj = {};
+  hashValues.forEach((hashValue) => {
+    hashObj[hashValue.name] = decodeURIComponent(hashValue.value);
+  });
+  return hashObj;
+}
+
+function makeHash(obj) {
+  return Object.keys(obj)
+    .map((key) => {
+      return `${key}${kEquals}${obj[key]}`;
+    })
+    .join(kAnd);
+}
+
+function setHash(obj) {
+  const hash = makeHash(obj);
+  window.history.pushState(null, null, `#${hash}`);
+}
+
+function showPage(listingId, page) {
+  const list = window["quarto-listings"][listingId];
+  if (list) {
+    list.show((page - 1) * list.page + 1, list.page);
+  }
+}
+
+function activateCategory(category) {
+  // Deactivate existing categories
+  const activeEls = window.document.querySelectorAll(
+    ".quarto-listing-category .category.active"
+  );
+  for (const activeEl of activeEls) {
+    activeEl.classList.remove("active");
+  }
+
+  // Activate this category
+  const categoryEl = window.document.querySelector(
+    `.quarto-listing-category .category[data-category='${category}'`
+  );
+  if (categoryEl) {
+    categoryEl.classList.add("active");
+  }
+
+  // Filter the listings to this category
+  filterListingCategory(category);
+}
+
+function filterListingCategory(category) {
+  const listingIds = Object.keys(window["quarto-listings"]);
+  for (const listingId of listingIds) {
+    const list = window["quarto-listings"][listingId];
+    if (list) {
+      if (category === "") {
+        // resets the filter
+        list.filter();
+      } else {
+        // filter to this category
+        list.filter(function (item) {
+          const itemValues = item.values();
+          if (itemValues.categories !== null) {
+            const categories = itemValues.categories.split(",");
+            return categories.includes(category);
+          } else {
+            return false;
+          }
+        });
+      }
+    }
+  }
+}
diff --git a/site_libs/quarto-nav/headroom.min.js b/site_libs/quarto-nav/headroom.min.js
new file mode 100644
index 0000000..b08f1df
--- /dev/null
+++ b/site_libs/quarto-nav/headroom.min.js
@@ -0,0 +1,7 @@
+/*!
+ * headroom.js v0.12.0 - Give your page some headroom. Hide your header until you need it
+ * Copyright (c) 2020 Nick Williams - http://wicky.nillia.ms/headroom.js
+ * License: MIT
+ */
+
+!function(t,n){"object"==typeof exports&&"undefined"!=typeof module?module.exports=n():"function"==typeof define&&define.amd?define(n):(t=t||self).Headroom=n()}(this,function(){"use strict";function t(){return"undefined"!=typeof window}function d(t){return function(t){return t&&t.document&&function(t){return 9===t.nodeType}(t.document)}(t)?function(t){var n=t.document,o=n.body,s=n.documentElement;return{scrollHeight:function(){return Math.max(o.scrollHeight,s.scrollHeight,o.offsetHeight,s.offsetHeight,o.clientHeight,s.clientHeight)},height:function(){return t.innerHeight||s.clientHeight||o.clientHeight},scrollY:function(){return void 0!==t.pageYOffset?t.pageYOffset:(s||o.parentNode||o).scrollTop}}}(t):function(t){return{scrollHeight:function(){return Math.max(t.scrollHeight,t.offsetHeight,t.clientHeight)},height:function(){return Math.max(t.offsetHeight,t.clientHeight)},scrollY:function(){return t.scrollTop}}}(t)}function n(t,s,e){var n,o=function(){var n=!1;try{var t={get passive(){n=!0}};window.addEventListener("test",t,t),window.removeEventListener("test",t,t)}catch(t){n=!1}return n}(),i=!1,r=d(t),l=r.scrollY(),a={};function c(){var t=Math.round(r.scrollY()),n=r.height(),o=r.scrollHeight();a.scrollY=t,a.lastScrollY=l,a.direction=l<t?"down":"up",a.distance=Math.abs(t-l),a.isOutOfBounds=t<0||o<t+n,a.top=t<=s.offset[a.direction],a.bottom=o<=t+n,a.toleranceExceeded=a.distance>s.tolerance[a.direction],e(a),l=t,i=!1}function h(){i||(i=!0,n=requestAnimationFrame(c))}var u=!!o&&{passive:!0,capture:!1};return t.addEventListener("scroll",h,u),c(),{destroy:function(){cancelAnimationFrame(n),t.removeEventListener("scroll",h,u)}}}function o(t){return t===Object(t)?t:{down:t,up:t}}function s(t,n){n=n||{},Object.assign(this,s.options,n),this.classes=Object.assign({},s.options.classes,n.classes),this.elem=t,this.tolerance=o(this.tolerance),this.offset=o(this.offset),this.initialised=!1,this.frozen=!1}return s.prototype={constructor:s,init:function(){return s.cutsTheMustard&&!this.initialised&&(this.addClass("initial"),this.initialised=!0,setTimeout(function(t){t.scrollTracker=n(t.scroller,{offset:t.offset,tolerance:t.tolerance},t.update.bind(t))},100,this)),this},destroy:function(){this.initialised=!1,Object.keys(this.classes).forEach(this.removeClass,this),this.scrollTracker.destroy()},unpin:function(){!this.hasClass("pinned")&&this.hasClass("unpinned")||(this.addClass("unpinned"),this.removeClass("pinned"),this.onUnpin&&this.onUnpin.call(this))},pin:function(){this.hasClass("unpinned")&&(this.addClass("pinned"),this.removeClass("unpinned"),this.onPin&&this.onPin.call(this))},freeze:function(){this.frozen=!0,this.addClass("frozen")},unfreeze:function(){this.frozen=!1,this.removeClass("frozen")},top:function(){this.hasClass("top")||(this.addClass("top"),this.removeClass("notTop"),this.onTop&&this.onTop.call(this))},notTop:function(){this.hasClass("notTop")||(this.addClass("notTop"),this.removeClass("top"),this.onNotTop&&this.onNotTop.call(this))},bottom:function(){this.hasClass("bottom")||(this.addClass("bottom"),this.removeClass("notBottom"),this.onBottom&&this.onBottom.call(this))},notBottom:function(){this.hasClass("notBottom")||(this.addClass("notBottom"),this.removeClass("bottom"),this.onNotBottom&&this.onNotBottom.call(this))},shouldUnpin:function(t){return"down"===t.direction&&!t.top&&t.toleranceExceeded},shouldPin:function(t){return"up"===t.direction&&t.toleranceExceeded||t.top},addClass:function(t){this.elem.classList.add.apply(this.elem.classList,this.classes[t].split(" "))},removeClass:function(t){this.elem.classList.remove.apply(this.elem.classList,this.classes[t].split(" "))},hasClass:function(t){return this.classes[t].split(" ").every(function(t){return this.classList.contains(t)},this.elem)},update:function(t){t.isOutOfBounds||!0!==this.frozen&&(t.top?this.top():this.notTop(),t.bottom?this.bottom():this.notBottom(),this.shouldUnpin(t)?this.unpin():this.shouldPin(t)&&this.pin())}},s.options={tolerance:{up:0,down:0},offset:0,scroller:t()?window:null,classes:{frozen:"headroom--frozen",pinned:"headroom--pinned",unpinned:"headroom--unpinned",top:"headroom--top",notTop:"headroom--not-top",bottom:"headroom--bottom",notBottom:"headroom--not-bottom",initial:"headroom"}},s.cutsTheMustard=!!(t()&&function(){}.bind&&"classList"in document.documentElement&&Object.assign&&Object.keys&&requestAnimationFrame),s});
diff --git a/site_libs/quarto-nav/quarto-nav.js b/site_libs/quarto-nav/quarto-nav.js
new file mode 100644
index 0000000..f6a53b1
--- /dev/null
+++ b/site_libs/quarto-nav/quarto-nav.js
@@ -0,0 +1,289 @@
+const headroomChanged = new CustomEvent("quarto-hrChanged", {
+  detail: {},
+  bubbles: true,
+  cancelable: false,
+  composed: false,
+});
+
+window.document.addEventListener("DOMContentLoaded", function () {
+  let init = false;
+
+  // Manage the back to top button, if one is present.
+  let lastScrollTop = window.pageYOffset || document.documentElement.scrollTop;
+  const scrollDownBuffer = 5;
+  const scrollUpBuffer = 35;
+  const btn = document.getElementById("quarto-back-to-top");
+  const hideBackToTop = () => {
+    btn.style.display = "none";
+  };
+  const showBackToTop = () => {
+    btn.style.display = "inline-block";
+  };
+  if (btn) {
+    window.document.addEventListener(
+      "scroll",
+      function () {
+        const currentScrollTop =
+          window.pageYOffset || document.documentElement.scrollTop;
+
+        // Shows and hides the button 'intelligently' as the user scrolls
+        if (currentScrollTop - scrollDownBuffer > lastScrollTop) {
+          hideBackToTop();
+          lastScrollTop = currentScrollTop <= 0 ? 0 : currentScrollTop;
+        } else if (currentScrollTop < lastScrollTop - scrollUpBuffer) {
+          showBackToTop();
+          lastScrollTop = currentScrollTop <= 0 ? 0 : currentScrollTop;
+        }
+
+        // Show the button at the bottom, hides it at the top
+        if (currentScrollTop <= 0) {
+          hideBackToTop();
+        } else if (
+          window.innerHeight + currentScrollTop >=
+          document.body.offsetHeight
+        ) {
+          showBackToTop();
+        }
+      },
+      false
+    );
+  }
+
+  function throttle(func, wait) {
+    var timeout;
+    return function () {
+      const context = this;
+      const args = arguments;
+      const later = function () {
+        clearTimeout(timeout);
+        timeout = null;
+        func.apply(context, args);
+      };
+
+      if (!timeout) {
+        timeout = setTimeout(later, wait);
+      }
+    };
+  }
+
+  function headerOffset() {
+    // Set an offset if there is are fixed top navbar
+    const headerEl = window.document.querySelector("header.fixed-top");
+    if (headerEl) {
+      return headerEl.clientHeight;
+    } else {
+      return 0;
+    }
+  }
+
+  function footerOffset() {
+    const footerEl = window.document.querySelector("footer.footer");
+    if (footerEl) {
+      return footerEl.clientHeight;
+    } else {
+      return 0;
+    }
+  }
+
+  function dashboardOffset() {
+    const dashboardNavEl = window.document.getElementById(
+      "quarto-dashboard-header"
+    );
+    if (dashboardNavEl !== null) {
+      return dashboardNavEl.clientHeight;
+    } else {
+      return 0;
+    }
+  }
+
+  function updateDocumentOffsetWithoutAnimation() {
+    updateDocumentOffset(false);
+  }
+
+  function updateDocumentOffset(animated) {
+    // set body offset
+    const topOffset = headerOffset();
+    const bodyOffset = topOffset + footerOffset() + dashboardOffset();
+    const bodyEl = window.document.body;
+    bodyEl.setAttribute("data-bs-offset", topOffset);
+    bodyEl.style.paddingTop = topOffset + "px";
+
+    // deal with sidebar offsets
+    const sidebars = window.document.querySelectorAll(
+      ".sidebar, .headroom-target"
+    );
+    sidebars.forEach((sidebar) => {
+      if (!animated) {
+        sidebar.classList.add("notransition");
+        // Remove the no transition class after the animation has time to complete
+        setTimeout(function () {
+          sidebar.classList.remove("notransition");
+        }, 201);
+      }
+
+      if (window.Headroom && sidebar.classList.contains("sidebar-unpinned")) {
+        sidebar.style.top = "0";
+        sidebar.style.maxHeight = "100vh";
+      } else {
+        sidebar.style.top = topOffset + "px";
+        sidebar.style.maxHeight = "calc(100vh - " + topOffset + "px)";
+      }
+    });
+
+    // allow space for footer
+    const mainContainer = window.document.querySelector(".quarto-container");
+    if (mainContainer) {
+      mainContainer.style.minHeight = "calc(100vh - " + bodyOffset + "px)";
+    }
+
+    // link offset
+    let linkStyle = window.document.querySelector("#quarto-target-style");
+    if (!linkStyle) {
+      linkStyle = window.document.createElement("style");
+      linkStyle.setAttribute("id", "quarto-target-style");
+      window.document.head.appendChild(linkStyle);
+    }
+    while (linkStyle.firstChild) {
+      linkStyle.removeChild(linkStyle.firstChild);
+    }
+    if (topOffset > 0) {
+      linkStyle.appendChild(
+        window.document.createTextNode(`
+      section:target::before {
+        content: "";
+        display: block;
+        height: ${topOffset}px;
+        margin: -${topOffset}px 0 0;
+      }`)
+      );
+    }
+    if (init) {
+      window.dispatchEvent(headroomChanged);
+    }
+    init = true;
+  }
+
+  // initialize headroom
+  var header = window.document.querySelector("#quarto-header");
+  if (header && window.Headroom) {
+    const headroom = new window.Headroom(header, {
+      tolerance: 5,
+      onPin: function () {
+        const sidebars = window.document.querySelectorAll(
+          ".sidebar, .headroom-target"
+        );
+        sidebars.forEach((sidebar) => {
+          sidebar.classList.remove("sidebar-unpinned");
+        });
+        updateDocumentOffset();
+      },
+      onUnpin: function () {
+        const sidebars = window.document.querySelectorAll(
+          ".sidebar, .headroom-target"
+        );
+        sidebars.forEach((sidebar) => {
+          sidebar.classList.add("sidebar-unpinned");
+        });
+        updateDocumentOffset();
+      },
+    });
+    headroom.init();
+
+    let frozen = false;
+    window.quartoToggleHeadroom = function () {
+      if (frozen) {
+        headroom.unfreeze();
+        frozen = false;
+      } else {
+        headroom.freeze();
+        frozen = true;
+      }
+    };
+  }
+
+  window.addEventListener(
+    "hashchange",
+    function (e) {
+      if (
+        getComputedStyle(document.documentElement).scrollBehavior !== "smooth"
+      ) {
+        window.scrollTo(0, window.pageYOffset - headerOffset());
+      }
+    },
+    false
+  );
+
+  // Observe size changed for the header
+  const headerEl = window.document.querySelector("header.fixed-top");
+  if (headerEl && window.ResizeObserver) {
+    const observer = new window.ResizeObserver(() => {
+      setTimeout(updateDocumentOffsetWithoutAnimation, 0);
+    });
+    observer.observe(headerEl, {
+      attributes: true,
+      childList: true,
+      characterData: true,
+    });
+  } else {
+    window.addEventListener(
+      "resize",
+      throttle(updateDocumentOffsetWithoutAnimation, 50)
+    );
+  }
+  setTimeout(updateDocumentOffsetWithoutAnimation, 250);
+
+  // fixup index.html links if we aren't on the filesystem
+  if (window.location.protocol !== "file:") {
+    const links = window.document.querySelectorAll("a");
+    for (let i = 0; i < links.length; i++) {
+      if (links[i].href) {
+        links[i].dataset.originalHref = links[i].href;
+        links[i].href = links[i].href.replace(/\/index\.html/, "/");
+      }
+    }
+
+    // Fixup any sharing links that require urls
+    // Append url to any sharing urls
+    const sharingLinks = window.document.querySelectorAll(
+      "a.sidebar-tools-main-item, a.quarto-navigation-tool, a.quarto-navbar-tools, a.quarto-navbar-tools-item"
+    );
+    for (let i = 0; i < sharingLinks.length; i++) {
+      const sharingLink = sharingLinks[i];
+      const href = sharingLink.getAttribute("href");
+      if (href) {
+        sharingLink.setAttribute(
+          "href",
+          href.replace("|url|", window.location.href)
+        );
+      }
+    }
+
+    // Scroll the active navigation item into view, if necessary
+    const navSidebar = window.document.querySelector("nav#quarto-sidebar");
+    if (navSidebar) {
+      // Find the active item
+      const activeItem = navSidebar.querySelector("li.sidebar-item a.active");
+      if (activeItem) {
+        // Wait for the scroll height and height to resolve by observing size changes on the
+        // nav element that is scrollable
+        const resizeObserver = new ResizeObserver((_entries) => {
+          // The bottom of the element
+          const elBottom = activeItem.offsetTop;
+          const viewBottom = navSidebar.scrollTop + navSidebar.clientHeight;
+
+          // The element height and scroll height are the same, then we are still loading
+          if (viewBottom !== navSidebar.scrollHeight) {
+            // Determine if the item isn't visible and scroll to it
+            if (elBottom >= viewBottom) {
+              navSidebar.scrollTop = elBottom;
+            }
+
+            // stop observing now since we've completed the scroll
+            resizeObserver.unobserve(navSidebar);
+          }
+        });
+        resizeObserver.observe(navSidebar);
+      }
+    }
+  }
+});
diff --git a/site_libs/quarto-search/autocomplete.umd.js b/site_libs/quarto-search/autocomplete.umd.js
new file mode 100644
index 0000000..ae0063a
--- /dev/null
+++ b/site_libs/quarto-search/autocomplete.umd.js
@@ -0,0 +1,3 @@
+/*! @algolia/autocomplete-js 1.11.1 | MIT License | © Algolia, Inc. and contributors | https://github.com/algolia/autocomplete */
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t(n(n({},e),{},{queries:r}))},e.getAlgoliaResults=Or,Object.defineProperty(e,"__esModule",{value:!0})}));
+
diff --git a/site_libs/quarto-search/fuse.min.js b/site_libs/quarto-search/fuse.min.js
new file mode 100644
index 0000000..adc2835
--- /dev/null
+++ b/site_libs/quarto-search/fuse.min.js
@@ -0,0 +1,9 @@
+/**
+ * Fuse.js v6.6.2 - Lightweight fuzzy-search (http://fusejs.io)
+ *
+ * Copyright (c) 2022 Kiro Risk (http://kiro.me)
+ * All Rights Reserved. Apache Software License 2.0
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ */
+var e,t;e=this,t=function(){"use strict";function e(e,t){var n=Object.keys(e);if(Object.getOwnPropertySymbols){var r=Object.getOwnPropertySymbols(e);t&&(r=r.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),n.push.apply(n,r)}return n}function t(t){for(var n=1;n<arguments.length;n++){var r=null!=arguments[n]?arguments[n]:{};n%2?e(Object(r),!0).forEach((function(e){c(t,e,r[e])})):Object.getOwnPropertyDescriptors?Object.defineProperties(t,Object.getOwnPropertyDescriptors(r)):e(Object(r)).forEach((function(e){Object.defineProperty(t,e,Object.getOwnPropertyDescriptor(r,e))}))}return t}function n(e){return n="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(e){return typeof e}:function(e){return e&&"function"==typeof Symbol&&e.constructor===Symbol&&e!==Symbol.prototype?"symbol":typeof e},n(e)}function r(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}function i(e,t){for(var n=0;n<t.length;n++){var 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\ No newline at end of file
diff --git a/site_libs/quarto-search/quarto-search.js b/site_libs/quarto-search/quarto-search.js
new file mode 100644
index 0000000..5f723d7
--- /dev/null
+++ b/site_libs/quarto-search/quarto-search.js
@@ -0,0 +1,1286 @@
+const kQueryArg = "q";
+const kResultsArg = "show-results";
+
+// If items don't provide a URL, then both the navigator and the onSelect
+// function aren't called (and therefore, the default implementation is used)
+//
+// We're using this sentinel URL to signal to those handlers that this
+// item is a more item (along with the type) and can be handled appropriately
+const kItemTypeMoreHref = "0767FDFD-0422-4E5A-BC8A-3BE11E5BBA05";
+
+window.document.addEventListener("DOMContentLoaded", function (_event) {
+  // Ensure that search is available on this page. If it isn't,
+  // should return early and not do anything
+  var searchEl = window.document.getElementById("quarto-search");
+  if (!searchEl) return;
+
+  const { autocomplete } = window["@algolia/autocomplete-js"];
+
+  let quartoSearchOptions = {};
+  let language = {};
+  const searchOptionEl = window.document.getElementById(
+    "quarto-search-options"
+  );
+  if (searchOptionEl) {
+    const jsonStr = searchOptionEl.textContent;
+    quartoSearchOptions = JSON.parse(jsonStr);
+    language = quartoSearchOptions.language;
+  }
+
+  // note the search mode
+  if (quartoSearchOptions.type === "overlay") {
+    searchEl.classList.add("type-overlay");
+  } else {
+    searchEl.classList.add("type-textbox");
+  }
+
+  // Used to determine highlighting behavior for this page
+  // A `q` query param is expected when the user follows a search
+  // to this page
+  const currentUrl = new URL(window.location);
+  const query = currentUrl.searchParams.get(kQueryArg);
+  const showSearchResults = currentUrl.searchParams.get(kResultsArg);
+  const mainEl = window.document.querySelector("main");
+
+  // highlight matches on the page
+  if (query && mainEl) {
+    // perform any highlighting
+    highlight(escapeRegExp(query), mainEl);
+
+    // fix up the URL to remove the q query param
+    const replacementUrl = new URL(window.location);
+    replacementUrl.searchParams.delete(kQueryArg);
+    window.history.replaceState({}, "", replacementUrl);
+  }
+
+  // function to clear highlighting on the page when the search query changes
+  // (e.g. if the user edits the query or clears it)
+  let highlighting = true;
+  const resetHighlighting = (searchTerm) => {
+    if (mainEl && highlighting && query && searchTerm !== query) {
+      clearHighlight(query, mainEl);
+      highlighting = false;
+    }
+  };
+
+  // Clear search highlighting when the user scrolls sufficiently
+  const resetFn = () => {
+    resetHighlighting("");
+    window.removeEventListener("quarto-hrChanged", resetFn);
+    window.removeEventListener("quarto-sectionChanged", resetFn);
+  };
+
+  // Register this event after the initial scrolling and settling of events
+  // on the page
+  window.addEventListener("quarto-hrChanged", resetFn);
+  window.addEventListener("quarto-sectionChanged", resetFn);
+
+  // Responsively switch to overlay mode if the search is present on the navbar
+  // Note that switching the sidebar to overlay mode requires more coordinate (not just
+  // the media query since we generate different HTML for sidebar overlays than we do
+  // for sidebar input UI)
+  const detachedMediaQuery =
+    quartoSearchOptions.type === "overlay" ? "all" : "(max-width: 991px)";
+
+  // If configured, include the analytics client to send insights
+  const plugins = configurePlugins(quartoSearchOptions);
+
+  let lastState = null;
+  const { setIsOpen, setQuery, setCollections } = autocomplete({
+    container: searchEl,
+    detachedMediaQuery: detachedMediaQuery,
+    defaultActiveItemId: 0,
+    panelContainer: "#quarto-search-results",
+    panelPlacement: quartoSearchOptions["panel-placement"],
+    debug: false,
+    openOnFocus: true,
+    plugins,
+    classNames: {
+      form: "d-flex",
+    },
+    placeholder: language["search-text-placeholder"],
+    translations: {
+      clearButtonTitle: language["search-clear-button-title"],
+      detachedCancelButtonText: language["search-detached-cancel-button-title"],
+      submitButtonTitle: language["search-submit-button-title"],
+    },
+    initialState: {
+      query,
+    },
+    getItemUrl({ item }) {
+      return item.href;
+    },
+    onStateChange({ state }) {
+      // If this is a file URL, note that
+
+      // Perhaps reset highlighting
+      resetHighlighting(state.query);
+
+      // If the panel just opened, ensure the panel is positioned properly
+      if (state.isOpen) {
+        if (lastState && !lastState.isOpen) {
+          setTimeout(() => {
+            positionPanel(quartoSearchOptions["panel-placement"]);
+          }, 150);
+        }
+      }
+
+      // Perhaps show the copy link
+      showCopyLink(state.query, quartoSearchOptions);
+
+      lastState = state;
+    },
+    reshape({ sources, state }) {
+      return sources.map((source) => {
+        try {
+          const items = source.getItems();
+
+          // Validate the items
+          validateItems(items);
+
+          // group the items by document
+          const groupedItems = new Map();
+          items.forEach((item) => {
+            const hrefParts = item.href.split("#");
+            const baseHref = hrefParts[0];
+            const isDocumentItem = hrefParts.length === 1;
+
+            const items = groupedItems.get(baseHref);
+            if (!items) {
+              groupedItems.set(baseHref, [item]);
+            } else {
+              // If the href for this item matches the document
+              // exactly, place this item first as it is the item that represents
+              // the document itself
+              if (isDocumentItem) {
+                items.unshift(item);
+              } else {
+                items.push(item);
+              }
+              groupedItems.set(baseHref, items);
+            }
+          });
+
+          const reshapedItems = [];
+          let count = 1;
+          for (const [_key, value] of groupedItems) {
+            const firstItem = value[0];
+            reshapedItems.push({
+              ...firstItem,
+              type: kItemTypeDoc,
+            });
+
+            const collapseMatches = quartoSearchOptions["collapse-after"];
+            const collapseCount =
+              typeof collapseMatches === "number" ? collapseMatches : 1;
+
+            if (value.length > 1) {
+              const target = `search-more-${count}`;
+              const isExpanded =
+                state.context.expanded &&
+                state.context.expanded.includes(target);
+
+              const remainingCount = value.length - collapseCount;
+
+              for (let i = 1; i < value.length; i++) {
+                if (collapseMatches && i === collapseCount) {
+                  reshapedItems.push({
+                    target,
+                    title: isExpanded
+                      ? language["search-hide-matches-text"]
+                      : remainingCount === 1
+                      ? `${remainingCount} ${language["search-more-match-text"]}`
+                      : `${remainingCount} ${language["search-more-matches-text"]}`,
+                    type: kItemTypeMore,
+                    href: kItemTypeMoreHref,
+                  });
+                }
+
+                if (isExpanded || !collapseMatches || i < collapseCount) {
+                  reshapedItems.push({
+                    ...value[i],
+                    type: kItemTypeItem,
+                    target,
+                  });
+                }
+              }
+            }
+            count += 1;
+          }
+
+          return {
+            ...source,
+            getItems() {
+              return reshapedItems;
+            },
+          };
+        } catch (error) {
+          // Some form of error occurred
+          return {
+            ...source,
+            getItems() {
+              return [
+                {
+                  title: error.name || "An Error Occurred While Searching",
+                  text:
+                    error.message ||
+                    "An unknown error occurred while attempting to perform the requested search.",
+                  type: kItemTypeError,
+                },
+              ];
+            },
+          };
+        }
+      });
+    },
+    navigator: {
+      navigate({ itemUrl }) {
+        if (itemUrl !== offsetURL(kItemTypeMoreHref)) {
+          window.location.assign(itemUrl);
+        }
+      },
+      navigateNewTab({ itemUrl }) {
+        if (itemUrl !== offsetURL(kItemTypeMoreHref)) {
+          const windowReference = window.open(itemUrl, "_blank", "noopener");
+          if (windowReference) {
+            windowReference.focus();
+          }
+        }
+      },
+      navigateNewWindow({ itemUrl }) {
+        if (itemUrl !== offsetURL(kItemTypeMoreHref)) {
+          window.open(itemUrl, "_blank", "noopener");
+        }
+      },
+    },
+    getSources({ state, setContext, setActiveItemId, refresh }) {
+      return [
+        {
+          sourceId: "documents",
+          getItemUrl({ item }) {
+            if (item.href) {
+              return offsetURL(item.href);
+            } else {
+              return undefined;
+            }
+          },
+          onSelect({
+            item,
+            state,
+            setContext,
+            setIsOpen,
+            setActiveItemId,
+            refresh,
+          }) {
+            if (item.type === kItemTypeMore) {
+              toggleExpanded(item, state, setContext, setActiveItemId, refresh);
+
+              // Toggle more
+              setIsOpen(true);
+            }
+          },
+          getItems({ query }) {
+            if (query === null || query === "") {
+              return [];
+            }
+
+            const limit = quartoSearchOptions.limit;
+            if (quartoSearchOptions.algolia) {
+              return algoliaSearch(query, limit, quartoSearchOptions.algolia);
+            } else {
+              // Fuse search options
+              const fuseSearchOptions = {
+                isCaseSensitive: false,
+                shouldSort: true,
+                minMatchCharLength: 2,
+                limit: limit,
+              };
+
+              return readSearchData().then(function (fuse) {
+                return fuseSearch(query, fuse, fuseSearchOptions);
+              });
+            }
+          },
+          templates: {
+            noResults({ createElement }) {
+              const hasQuery = lastState.query;
+
+              return createElement(
+                "div",
+                {
+                  class: `quarto-search-no-results${
+                    hasQuery ? "" : " no-query"
+                  }`,
+                },
+                language["search-no-results-text"]
+              );
+            },
+            header({ items, createElement }) {
+              // count the documents
+              const count = items.filter((item) => {
+                return item.type === kItemTypeDoc;
+              }).length;
+
+              if (count > 0) {
+                return createElement(
+                  "div",
+                  { class: "search-result-header" },
+                  `${count} ${language["search-matching-documents-text"]}`
+                );
+              } else {
+                return createElement(
+                  "div",
+                  { class: "search-result-header-no-results" },
+                  ``
+                );
+              }
+            },
+            footer({ _items, createElement }) {
+              if (
+                quartoSearchOptions.algolia &&
+                quartoSearchOptions.algolia["show-logo"]
+              ) {
+                const libDir = quartoSearchOptions.algolia["libDir"];
+                const logo = createElement("img", {
+                  src: offsetURL(
+                    `${libDir}/quarto-search/search-by-algolia.svg`
+                  ),
+                  class: "algolia-search-logo",
+                });
+                return createElement(
+                  "a",
+                  { href: "http://www.algolia.com/" },
+                  logo
+                );
+              }
+            },
+
+            item({ item, createElement }) {
+              return renderItem(
+                item,
+                createElement,
+                state,
+                setActiveItemId,
+                setContext,
+                refresh,
+                quartoSearchOptions
+              );
+            },
+          },
+        },
+      ];
+    },
+  });
+
+  window.quartoOpenSearch = () => {
+    setIsOpen(false);
+    setIsOpen(true);
+    focusSearchInput();
+  };
+
+  document.addEventListener("keyup", (event) => {
+    const { key } = event;
+    const kbds = quartoSearchOptions["keyboard-shortcut"];
+    const focusedEl = document.activeElement;
+
+    const isFormElFocused = [
+      "input",
+      "select",
+      "textarea",
+      "button",
+      "option",
+    ].find((tag) => {
+      return focusedEl.tagName.toLowerCase() === tag;
+    });
+
+    if (
+      kbds &&
+      kbds.includes(key) &&
+      !isFormElFocused &&
+      !document.activeElement.isContentEditable
+    ) {
+      event.preventDefault();
+      window.quartoOpenSearch();
+    }
+  });
+
+  // Remove the labeleledby attribute since it is pointing
+  // to a non-existent label
+  if (quartoSearchOptions.type === "overlay") {
+    const inputEl = window.document.querySelector(
+      "#quarto-search .aa-Autocomplete"
+    );
+    if (inputEl) {
+      inputEl.removeAttribute("aria-labelledby");
+    }
+  }
+
+  function throttle(func, wait) {
+    let waiting = false;
+    return function () {
+      if (!waiting) {
+        func.apply(this, arguments);
+        waiting = true;
+        setTimeout(function () {
+          waiting = false;
+        }, wait);
+      }
+    };
+  }
+
+  // If the main document scrolls dismiss the search results
+  // (otherwise, since they're floating in the document they can scroll with the document)
+  window.document.body.onscroll = throttle(() => {
+    // Only do this if we're not detached
+    // Bug #7117
+    // This will happen when the keyboard is shown on ios (resulting in a scroll)
+    // which then closed the search UI
+    if (!window.matchMedia(detachedMediaQuery).matches) {
+      setIsOpen(false);
+    }
+  }, 50);
+
+  if (showSearchResults) {
+    setIsOpen(true);
+    focusSearchInput();
+  }
+});
+
+function configurePlugins(quartoSearchOptions) {
+  const autocompletePlugins = [];
+  const algoliaOptions = quartoSearchOptions.algolia;
+  if (
+    algoliaOptions &&
+    algoliaOptions["analytics-events"] &&
+    algoliaOptions["search-only-api-key"] &&
+    algoliaOptions["application-id"]
+  ) {
+    const apiKey = algoliaOptions["search-only-api-key"];
+    const appId = algoliaOptions["application-id"];
+
+    // Aloglia insights may not be loaded because they require cookie consent
+    // Use deferred loading so events will start being recorded when/if consent
+    // is granted.
+    const algoliaInsightsDeferredPlugin = deferredLoadPlugin(() => {
+      if (
+        window.aa &&
+        window["@algolia/autocomplete-plugin-algolia-insights"]
+      ) {
+        window.aa("init", {
+          appId,
+          apiKey,
+          useCookie: true,
+        });
+
+        const { createAlgoliaInsightsPlugin } =
+          window["@algolia/autocomplete-plugin-algolia-insights"];
+        // Register the insights client
+        const algoliaInsightsPlugin = createAlgoliaInsightsPlugin({
+          insightsClient: window.aa,
+          onItemsChange({ insights, insightsEvents }) {
+            const events = insightsEvents.flatMap((event) => {
+              // This API limits the number of items per event to 20
+              const chunkSize = 20;
+              const itemChunks = [];
+              const eventItems = event.items;
+              for (let i = 0; i < eventItems.length; i += chunkSize) {
+                itemChunks.push(eventItems.slice(i, i + chunkSize));
+              }
+              // Split the items into multiple events that can be sent
+              const events = itemChunks.map((items) => {
+                return {
+                  ...event,
+                  items,
+                };
+              });
+              return events;
+            });
+
+            for (const event of events) {
+              insights.viewedObjectIDs(event);
+            }
+          },
+        });
+        return algoliaInsightsPlugin;
+      }
+    });
+
+    // Add the plugin
+    autocompletePlugins.push(algoliaInsightsDeferredPlugin);
+    return autocompletePlugins;
+  }
+}
+
+// For plugins that may not load immediately, create a wrapper
+// plugin and forward events and plugin data once the plugin
+// is initialized. This is useful for cases like cookie consent
+// which may prevent the analytics insights event plugin from initializing
+// immediately.
+function deferredLoadPlugin(createPlugin) {
+  let plugin = undefined;
+  let subscribeObj = undefined;
+  const wrappedPlugin = () => {
+    if (!plugin && subscribeObj) {
+      plugin = createPlugin();
+      if (plugin && plugin.subscribe) {
+        plugin.subscribe(subscribeObj);
+      }
+    }
+    return plugin;
+  };
+
+  return {
+    subscribe: (obj) => {
+      subscribeObj = obj;
+    },
+    onStateChange: (obj) => {
+      const plugin = wrappedPlugin();
+      if (plugin && plugin.onStateChange) {
+        plugin.onStateChange(obj);
+      }
+    },
+    onSubmit: (obj) => {
+      const plugin = wrappedPlugin();
+      if (plugin && plugin.onSubmit) {
+        plugin.onSubmit(obj);
+      }
+    },
+    onReset: (obj) => {
+      const plugin = wrappedPlugin();
+      if (plugin && plugin.onReset) {
+        plugin.onReset(obj);
+      }
+    },
+    getSources: (obj) => {
+      const plugin = wrappedPlugin();
+      if (plugin && plugin.getSources) {
+        return plugin.getSources(obj);
+      } else {
+        return Promise.resolve([]);
+      }
+    },
+    data: (obj) => {
+      const plugin = wrappedPlugin();
+      if (plugin && plugin.data) {
+        plugin.data(obj);
+      }
+    },
+  };
+}
+
+function validateItems(items) {
+  // Validate the first item
+  if (items.length > 0) {
+    const item = items[0];
+    const missingFields = [];
+    if (item.href == undefined) {
+      missingFields.push("href");
+    }
+    if (!item.title == undefined) {
+      missingFields.push("title");
+    }
+    if (!item.text == undefined) {
+      missingFields.push("text");
+    }
+
+    if (missingFields.length === 1) {
+      throw {
+        name: `Error: Search index is missing the <code>${missingFields[0]}</code> field.`,
+        message: `The items being returned for this search do not include all the required fields. Please ensure that your index items include the <code>${missingFields[0]}</code> field or use <code>index-fields</code> in your <code>_quarto.yml</code> file to specify the field names.`,
+      };
+    } else if (missingFields.length > 1) {
+      const missingFieldList = missingFields
+        .map((field) => {
+          return `<code>${field}</code>`;
+        })
+        .join(", ");
+
+      throw {
+        name: `Error: Search index is missing the following fields: ${missingFieldList}.`,
+        message: `The items being returned for this search do not include all the required fields. Please ensure that your index items includes the following fields: ${missingFieldList}, or use <code>index-fields</code> in your <code>_quarto.yml</code> file to specify the field names.`,
+      };
+    }
+  }
+}
+
+let lastQuery = null;
+function showCopyLink(query, options) {
+  const language = options.language;
+  lastQuery = query;
+  // Insert share icon
+  const inputSuffixEl = window.document.body.querySelector(
+    ".aa-Form .aa-InputWrapperSuffix"
+  );
+
+  if (inputSuffixEl) {
+    let copyButtonEl = window.document.body.querySelector(
+      ".aa-Form .aa-InputWrapperSuffix .aa-CopyButton"
+    );
+
+    if (copyButtonEl === null) {
+      copyButtonEl = window.document.createElement("button");
+      copyButtonEl.setAttribute("class", "aa-CopyButton");
+      copyButtonEl.setAttribute("type", "button");
+      copyButtonEl.setAttribute("title", language["search-copy-link-title"]);
+      copyButtonEl.onmousedown = (e) => {
+        e.preventDefault();
+        e.stopPropagation();
+      };
+
+      const linkIcon = "bi-clipboard";
+      const checkIcon = "bi-check2";
+
+      const shareIconEl = window.document.createElement("i");
+      shareIconEl.setAttribute("class", `bi ${linkIcon}`);
+      copyButtonEl.appendChild(shareIconEl);
+      inputSuffixEl.prepend(copyButtonEl);
+
+      const clipboard = new window.ClipboardJS(".aa-CopyButton", {
+        text: function (_trigger) {
+          const copyUrl = new URL(window.location);
+          copyUrl.searchParams.set(kQueryArg, lastQuery);
+          copyUrl.searchParams.set(kResultsArg, "1");
+          return copyUrl.toString();
+        },
+      });
+      clipboard.on("success", function (e) {
+        // Focus the input
+
+        // button target
+        const button = e.trigger;
+        const icon = button.querySelector("i.bi");
+
+        // flash "checked"
+        icon.classList.add(checkIcon);
+        icon.classList.remove(linkIcon);
+        setTimeout(function () {
+          icon.classList.remove(checkIcon);
+          icon.classList.add(linkIcon);
+        }, 1000);
+      });
+    }
+
+    // If there is a query, show the link icon
+    if (copyButtonEl) {
+      if (lastQuery && options["copy-button"]) {
+        copyButtonEl.style.display = "flex";
+      } else {
+        copyButtonEl.style.display = "none";
+      }
+    }
+  }
+}
+
+/* Search Index Handling */
+// create the index
+var fuseIndex = undefined;
+var shownWarning = false;
+
+// fuse index options
+const kFuseIndexOptions = {
+  keys: [
+    { name: "title", weight: 20 },
+    { name: "section", weight: 20 },
+    { name: "text", weight: 10 },
+  ],
+  ignoreLocation: true,
+  threshold: 0.1,
+};
+
+async function readSearchData() {
+  // Initialize the search index on demand
+  if (fuseIndex === undefined) {
+    if (window.location.protocol === "file:" && !shownWarning) {
+      window.alert(
+        "Search requires JavaScript features disabled when running in file://... URLs. In order to use search, please run this document in a web server."
+      );
+      shownWarning = true;
+      return;
+    }
+    const fuse = new window.Fuse([], kFuseIndexOptions);
+
+    // fetch the main search.json
+    const response = await fetch(offsetURL("search.json"));
+    if (response.status == 200) {
+      return response.json().then(function (searchDocs) {
+        searchDocs.forEach(function (searchDoc) {
+          fuse.add(searchDoc);
+        });
+        fuseIndex = fuse;
+        return fuseIndex;
+      });
+    } else {
+      return Promise.reject(
+        new Error(
+          "Unexpected status from search index request: " + response.status
+        )
+      );
+    }
+  }
+
+  return fuseIndex;
+}
+
+function inputElement() {
+  return window.document.body.querySelector(".aa-Form .aa-Input");
+}
+
+function focusSearchInput() {
+  setTimeout(() => {
+    const inputEl = inputElement();
+    if (inputEl) {
+      inputEl.focus();
+    }
+  }, 50);
+}
+
+/* Panels */
+const kItemTypeDoc = "document";
+const kItemTypeMore = "document-more";
+const kItemTypeItem = "document-item";
+const kItemTypeError = "error";
+
+function renderItem(
+  item,
+  createElement,
+  state,
+  setActiveItemId,
+  setContext,
+  refresh,
+  quartoSearchOptions
+) {
+  switch (item.type) {
+    case kItemTypeDoc:
+      return createDocumentCard(
+        createElement,
+        "file-richtext",
+        item.title,
+        item.section,
+        item.text,
+        item.href,
+        item.crumbs,
+        quartoSearchOptions
+      );
+    case kItemTypeMore:
+      return createMoreCard(
+        createElement,
+        item,
+        state,
+        setActiveItemId,
+        setContext,
+        refresh
+      );
+    case kItemTypeItem:
+      return createSectionCard(
+        createElement,
+        item.section,
+        item.text,
+        item.href
+      );
+    case kItemTypeError:
+      return createErrorCard(createElement, item.title, item.text);
+    default:
+      return undefined;
+  }
+}
+
+function createDocumentCard(
+  createElement,
+  icon,
+  title,
+  section,
+  text,
+  href,
+  crumbs,
+  quartoSearchOptions
+) {
+  const iconEl = createElement("i", {
+    class: `bi bi-${icon} search-result-icon`,
+  });
+  const titleEl = createElement("p", { class: "search-result-title" }, title);
+  const titleContents = [iconEl, titleEl];
+  const showParent = quartoSearchOptions["show-item-context"];
+  if (crumbs && showParent) {
+    let crumbsOut = undefined;
+    const crumbClz = ["search-result-crumbs"];
+    if (showParent === "root") {
+      crumbsOut = crumbs.length > 1 ? crumbs[0] : undefined;
+    } else if (showParent === "parent") {
+      crumbsOut = crumbs.length > 1 ? crumbs[crumbs.length - 2] : undefined;
+    } else {
+      crumbsOut = crumbs.length > 1 ? crumbs.join(" > ") : undefined;
+      crumbClz.push("search-result-crumbs-wrap");
+    }
+
+    const crumbEl = createElement(
+      "p",
+      { class: crumbClz.join(" ") },
+      crumbsOut
+    );
+    titleContents.push(crumbEl);
+  }
+
+  const titleContainerEl = createElement(
+    "div",
+    { class: "search-result-title-container" },
+    titleContents
+  );
+
+  const textEls = [];
+  if (section) {
+    const sectionEl = createElement(
+      "p",
+      { class: "search-result-section" },
+      section
+    );
+    textEls.push(sectionEl);
+  }
+  const descEl = createElement("p", {
+    class: "search-result-text",
+    dangerouslySetInnerHTML: {
+      __html: text,
+    },
+  });
+  textEls.push(descEl);
+
+  const textContainerEl = createElement(
+    "div",
+    { class: "search-result-text-container" },
+    textEls
+  );
+
+  const containerEl = createElement(
+    "div",
+    {
+      class: "search-result-container",
+    },
+    [titleContainerEl, textContainerEl]
+  );
+
+  const linkEl = createElement(
+    "a",
+    {
+      href: offsetURL(href),
+      class: "search-result-link",
+    },
+    containerEl
+  );
+
+  const classes = ["search-result-doc", "search-item"];
+  if (!section) {
+    classes.push("document-selectable");
+  }
+
+  return createElement(
+    "div",
+    {
+      class: classes.join(" "),
+    },
+    linkEl
+  );
+}
+
+function createMoreCard(
+  createElement,
+  item,
+  state,
+  setActiveItemId,
+  setContext,
+  refresh
+) {
+  const moreCardEl = createElement(
+    "div",
+    {
+      class: "search-result-more search-item",
+      onClick: (e) => {
+        // Handle expanding the sections by adding the expanded
+        // section to the list of expanded sections
+        toggleExpanded(item, state, setContext, setActiveItemId, refresh);
+        e.stopPropagation();
+      },
+    },
+    item.title
+  );
+
+  return moreCardEl;
+}
+
+function toggleExpanded(item, state, setContext, setActiveItemId, refresh) {
+  const expanded = state.context.expanded || [];
+  if (expanded.includes(item.target)) {
+    setContext({
+      expanded: expanded.filter((target) => target !== item.target),
+    });
+  } else {
+    setContext({ expanded: [...expanded, item.target] });
+  }
+
+  refresh();
+  setActiveItemId(item.__autocomplete_id);
+}
+
+function createSectionCard(createElement, section, text, href) {
+  const sectionEl = createSection(createElement, section, text, href);
+  return createElement(
+    "div",
+    {
+      class: "search-result-doc-section search-item",
+    },
+    sectionEl
+  );
+}
+
+function createSection(createElement, title, text, href) {
+  const descEl = createElement("p", {
+    class: "search-result-text",
+    dangerouslySetInnerHTML: {
+      __html: text,
+    },
+  });
+
+  const titleEl = createElement("p", { class: "search-result-section" }, title);
+  const linkEl = createElement(
+    "a",
+    {
+      href: offsetURL(href),
+      class: "search-result-link",
+    },
+    [titleEl, descEl]
+  );
+  return linkEl;
+}
+
+function createErrorCard(createElement, title, text) {
+  const descEl = createElement("p", {
+    class: "search-error-text",
+    dangerouslySetInnerHTML: {
+      __html: text,
+    },
+  });
+
+  const titleEl = createElement("p", {
+    class: "search-error-title",
+    dangerouslySetInnerHTML: {
+      __html: `<i class="bi bi-exclamation-circle search-error-icon"></i> ${title}`,
+    },
+  });
+  const errorEl = createElement("div", { class: "search-error" }, [
+    titleEl,
+    descEl,
+  ]);
+  return errorEl;
+}
+
+function positionPanel(pos) {
+  const panelEl = window.document.querySelector(
+    "#quarto-search-results .aa-Panel"
+  );
+  const inputEl = window.document.querySelector(
+    "#quarto-search .aa-Autocomplete"
+  );
+
+  if (panelEl && inputEl) {
+    panelEl.style.top = `${Math.round(panelEl.offsetTop)}px`;
+    if (pos === "start") {
+      panelEl.style.left = `${Math.round(inputEl.left)}px`;
+    } else {
+      panelEl.style.right = `${Math.round(inputEl.offsetRight)}px`;
+    }
+  }
+}
+
+/* Highlighting */
+// highlighting functions
+function highlightMatch(query, text) {
+  if (text) {
+    const start = text.toLowerCase().indexOf(query.toLowerCase());
+    if (start !== -1) {
+      const startMark = "<mark class='search-match'>";
+      const endMark = "</mark>";
+
+      const end = start + query.length;
+      text =
+        text.slice(0, start) +
+        startMark +
+        text.slice(start, end) +
+        endMark +
+        text.slice(end);
+      const startInfo = clipStart(text, start);
+      const endInfo = clipEnd(
+        text,
+        startInfo.position + startMark.length + endMark.length
+      );
+      text =
+        startInfo.prefix +
+        text.slice(startInfo.position, endInfo.position) +
+        endInfo.suffix;
+
+      return text;
+    } else {
+      return text;
+    }
+  } else {
+    return text;
+  }
+}
+
+function clipStart(text, pos) {
+  const clipStart = pos - 50;
+  if (clipStart < 0) {
+    // This will just return the start of the string
+    return {
+      position: 0,
+      prefix: "",
+    };
+  } else {
+    // We're clipping before the start of the string, walk backwards to the first space.
+    const spacePos = findSpace(text, pos, -1);
+    return {
+      position: spacePos.position,
+      prefix: "",
+    };
+  }
+}
+
+function clipEnd(text, pos) {
+  const clipEnd = pos + 200;
+  if (clipEnd > text.length) {
+    return {
+      position: text.length,
+      suffix: "",
+    };
+  } else {
+    const spacePos = findSpace(text, clipEnd, 1);
+    return {
+      position: spacePos.position,
+      suffix: spacePos.clipped ? "…" : "",
+    };
+  }
+}
+
+function findSpace(text, start, step) {
+  let stepPos = start;
+  while (stepPos > -1 && stepPos < text.length) {
+    const char = text[stepPos];
+    if (char === " " || char === "," || char === ":") {
+      return {
+        position: step === 1 ? stepPos : stepPos - step,
+        clipped: stepPos > 1 && stepPos < text.length,
+      };
+    }
+    stepPos = stepPos + step;
+  }
+
+  return {
+    position: stepPos - step,
+    clipped: false,
+  };
+}
+
+// removes highlighting as implemented by the mark tag
+function clearHighlight(searchterm, el) {
+  const childNodes = el.childNodes;
+  for (let i = childNodes.length - 1; i >= 0; i--) {
+    const node = childNodes[i];
+    if (node.nodeType === Node.ELEMENT_NODE) {
+      if (
+        node.tagName === "MARK" &&
+        node.innerText.toLowerCase() === searchterm.toLowerCase()
+      ) {
+        el.replaceChild(document.createTextNode(node.innerText), node);
+      } else {
+        clearHighlight(searchterm, node);
+      }
+    }
+  }
+}
+
+function escapeRegExp(string) {
+  return string.replace(/[.*+?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string
+}
+
+// highlight matches
+function highlight(term, el) {
+  const termRegex = new RegExp(term, "ig");
+  const childNodes = el.childNodes;
+
+  // walk back to front avoid mutating elements in front of us
+  for (let i = childNodes.length - 1; i >= 0; i--) {
+    const node = childNodes[i];
+
+    if (node.nodeType === Node.TEXT_NODE) {
+      // Search text nodes for text to highlight
+      const text = node.nodeValue;
+
+      let startIndex = 0;
+      let matchIndex = text.search(termRegex);
+      if (matchIndex > -1) {
+        const markFragment = document.createDocumentFragment();
+        while (matchIndex > -1) {
+          const prefix = text.slice(startIndex, matchIndex);
+          markFragment.appendChild(document.createTextNode(prefix));
+
+          const mark = document.createElement("mark");
+          mark.appendChild(
+            document.createTextNode(
+              text.slice(matchIndex, matchIndex + term.length)
+            )
+          );
+          markFragment.appendChild(mark);
+
+          startIndex = matchIndex + term.length;
+          matchIndex = text.slice(startIndex).search(new RegExp(term, "ig"));
+          if (matchIndex > -1) {
+            matchIndex = startIndex + matchIndex;
+          }
+        }
+        if (startIndex < text.length) {
+          markFragment.appendChild(
+            document.createTextNode(text.slice(startIndex, text.length))
+          );
+        }
+
+        el.replaceChild(markFragment, node);
+      }
+    } else if (node.nodeType === Node.ELEMENT_NODE) {
+      // recurse through elements
+      highlight(term, node);
+    }
+  }
+}
+
+/* Link Handling */
+// get the offset from this page for a given site root relative url
+function offsetURL(url) {
+  var offset = getMeta("quarto:offset");
+  return offset ? offset + url : url;
+}
+
+// read a meta tag value
+function getMeta(metaName) {
+  var metas = window.document.getElementsByTagName("meta");
+  for (let i = 0; i < metas.length; i++) {
+    if (metas[i].getAttribute("name") === metaName) {
+      return metas[i].getAttribute("content");
+    }
+  }
+  return "";
+}
+
+function algoliaSearch(query, limit, algoliaOptions) {
+  const { getAlgoliaResults } = window["@algolia/autocomplete-preset-algolia"];
+
+  const applicationId = algoliaOptions["application-id"];
+  const searchOnlyApiKey = algoliaOptions["search-only-api-key"];
+  const indexName = algoliaOptions["index-name"];
+  const indexFields = algoliaOptions["index-fields"];
+  const searchClient = window.algoliasearch(applicationId, searchOnlyApiKey);
+  const searchParams = algoliaOptions["params"];
+  const searchAnalytics = !!algoliaOptions["analytics-events"];
+
+  return getAlgoliaResults({
+    searchClient,
+    queries: [
+      {
+        indexName: indexName,
+        query,
+        params: {
+          hitsPerPage: limit,
+          clickAnalytics: searchAnalytics,
+          ...searchParams,
+        },
+      },
+    ],
+    transformResponse: (response) => {
+      if (!indexFields) {
+        return response.hits.map((hit) => {
+          return hit.map((item) => {
+            return {
+              ...item,
+              text: highlightMatch(query, item.text),
+            };
+          });
+        });
+      } else {
+        const remappedHits = response.hits.map((hit) => {
+          return hit.map((item) => {
+            const newItem = { ...item };
+            ["href", "section", "title", "text", "crumbs"].forEach(
+              (keyName) => {
+                const mappedName = indexFields[keyName];
+                if (
+                  mappedName &&
+                  item[mappedName] !== undefined &&
+                  mappedName !== keyName
+                ) {
+                  newItem[keyName] = item[mappedName];
+                  delete newItem[mappedName];
+                }
+              }
+            );
+            newItem.text = highlightMatch(query, newItem.text);
+            return newItem;
+          });
+        });
+        return remappedHits;
+      }
+    },
+  });
+}
+
+let subSearchTerm = undefined;
+let subSearchFuse = undefined;
+const kFuseMaxWait = 125;
+
+async function fuseSearch(query, fuse, fuseOptions) {
+  let index = fuse;
+  // Fuse.js using the Bitap algorithm for text matching which runs in
+  // O(nm) time (no matter the structure of the text). In our case this
+  // means that long search terms mixed with large index gets very slow
+  //
+  // This injects a subIndex that will be used once the terms get long enough
+  // Usually making this subindex is cheap since there will typically be
+  // a subset of results matching the existing query
+  if (subSearchFuse !== undefined && query.startsWith(subSearchTerm)) {
+    // Use the existing subSearchFuse
+    index = subSearchFuse;
+  } else if (subSearchFuse !== undefined) {
+    // The term changed, discard the existing fuse
+    subSearchFuse = undefined;
+    subSearchTerm = undefined;
+  }
+
+  // Search using the active fuse
+  const then = performance.now();
+  const resultsRaw = await index.search(query, fuseOptions);
+  const now = performance.now();
+
+  const results = resultsRaw.map((result) => {
+    const addParam = (url, name, value) => {
+      const anchorParts = url.split("#");
+      const baseUrl = anchorParts[0];
+      const sep = baseUrl.search("\\?") > 0 ? "&" : "?";
+      anchorParts[0] = baseUrl + sep + name + "=" + value;
+      return anchorParts.join("#");
+    };
+
+    return {
+      title: result.item.title,
+      section: result.item.section,
+      href: addParam(result.item.href, kQueryArg, query),
+      text: highlightMatch(query, result.item.text),
+      crumbs: result.item.crumbs,
+    };
+  });
+
+  // If we don't have a subfuse and the query is long enough, go ahead
+  // and create a subfuse to use for subsequent queries
+  if (now - then > kFuseMaxWait && subSearchFuse === undefined) {
+    subSearchTerm = query;
+    subSearchFuse = new window.Fuse([], kFuseIndexOptions);
+    resultsRaw.forEach((rr) => {
+      subSearchFuse.add(rr.item);
+    });
+  }
+  return results;
+}
diff --git a/sitemap.xml b/sitemap.xml
old mode 100755
new mode 100644
index da2c6fe..f8f48a4
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -1,126 +1,119 @@
 <?xml version="1.0" encoding="UTF-8"?>
-<urlset xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.sitemaps.org/schemas/sitemap/0.9 http://www.sitemaps.org/schemas/sitemap/0.9/sitemap.xsd" xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
-<url>
-<loc>https://blog.pslmodels.org/introducing-psl-blog</loc>
-<lastmod>2020-11-06T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-creating-reform-files</loc>
-<lastmod>2020-11-18T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-tax-cruncher</loc>
-<lastmod>2020-11-23T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-cost-of-capital-calculator</loc>
-<lastmod>2020-12-03T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/2020-year-in-review</loc>
-<lastmod>2020-12-23T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-tax-brain</loc>
-<lastmod>2020-12-23T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-how-to-use-og-usa</loc>
-<lastmod>2021-01-28T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-scf-microdf</loc>
-<lastmod>2021-01-29T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-contributing-psl</loc>
-<lastmod>2021-03-02T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-taxbrain-to-taxcruncher</loc>
-<lastmod>2021-03-02T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-cs-api-stitch</loc>
-<lastmod>2021-03-08T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-stacked-revenue-estimates</loc>
-<lastmod>2021-04-05T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-jupyter-book-deploy</loc>
-<lastmod>2021-05-17T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-tax-brain-python-api</loc>
-<lastmod>2021-06-14T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-constructing-tax-data-for-the-50-states</loc>
-<lastmod>2021-07-16T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-unit-testing</loc>
-<lastmod>2021-08-09T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-cs-auto-deploy</loc>
-<lastmod>2021-09-20T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-og-core</loc>
-<lastmod>2021-11-01T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-synthimpute</loc>
-<lastmod>2021-12-08T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/2021-year-in-review</loc>
-<lastmod>2021-12-28T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/DC-workshop</loc>
-<lastmod>2022-03-03T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-policyengine-us</loc>
-<lastmod>2022-04-12T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-ccc-international</loc>
-<lastmod>2022-04-18T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-github</loc>
-<lastmod>2022-06-28T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/demo-day-cambridge-cash-assistance</loc>
-<lastmod>2022-07-14T00:00:00-05:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/2022-year-in-review</loc>
-<lastmod>2022-12-31T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/2023-year-in-review</loc>
-<lastmod>2023-12-28T00:00:00-06:00</lastmod>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/about/</loc>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/</loc>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/search/</loc>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/categories/</loc>
-</url>
-<url>
-<loc>https://blog.pslmodels.org/page2/</loc>
-</url>
+<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-03-02-demo-day-contributing-psl.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-09-20-demo-day-cs-auto-deploy.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2020-11-06-introducing-psl-blog.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2020-11-18-demo-day-creating-reform-files.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-03-08-demo-day-cs-api-stitch.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2023-12-28-2023-year-in-review.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2022-04-12-demo-day-policyengine-us.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2022-04-18-demo-day-ccc-international.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-06-14-demo-day-tax-brain-python-api.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-03-02-demo-day-taxbrain-to-taxcruncher.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-12-28-2021-year-in-review.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2022-06-28-demo-day-github.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2022-07-14-demo-day-cambridge-cash-assistance.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2022-12-31-2022-year-in-review.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/about.html</loc>
+    <lastmod>2024-03-06T02:59:08.201Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/index.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2022-03-03-DC-workshop.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2020-12-23-demo-day-tax-brain.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-11-01-demo-day-og-core.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2020-12-03-demo-day-cost-of-capital-calculator.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2020-11-23-demo-day-tax-cruncher.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-01-28-demo-day-how-to-use-og-usa.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-12-08-demo-day-synthimpute.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-04-05-demo-day-stacked-revenue-estimates.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2020-12-23-2020-year-in-review.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-05-17-demo-day-jupyter-book-deploy.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-07-16-demo-day-constructing-tax-data-for-the-50-states.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-01-29-demo-day-scf-microdf.html</loc>
+    <lastmod>2024-03-06T02:59:08.225Z</lastmod>
+  </url>
+  <url>
+    <loc>https://PSLmodels.github.io/blog/posts/2021-08-09-demo-day-unit-testing.html</loc>
+    <lastmod>2024-03-06T02:59:08.229Z</lastmod>
+  </url>
 </urlset>
diff --git a/styles.css b/styles.css
new file mode 100644
index 0000000..2ddf50c
--- /dev/null
+++ b/styles.css
@@ -0,0 +1 @@
+/* css styles */