From 017dd90e4f1c58c581906770621968f20115d392 Mon Sep 17 00:00:00 2001 From: JustinMShea Date: Sun, 8 Apr 2018 23:06:13 -0500 Subject: [PATCH] Minor updates discovered during build checks --- .../Introductory-Econometrics-Examples.html | 14 +++++++------- docs/index.html | 7 +++---- 2 files changed, 10 insertions(+), 11 deletions(-) diff --git a/docs/articles/Introductory-Econometrics-Examples.html b/docs/articles/Introductory-Econometrics-Examples.html index 173c8eb..2e62173 100644 --- a/docs/articles/Introductory-Econometrics-Examples.html +++ b/docs/articles/Introductory-Econometrics-Examples.html @@ -87,8 +87,8 @@

Justin M Shea

Introduction

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This vignette contains examples from every chapter of Introductory Econometrics: A Modern Approach by Jeffrey M. Wooldridge. Each example illustrates how to load data, build econometric models, and compute estimates with R.

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Students new to both econometrics and R may find the introduction to both a bit challenging. In particular, the process of loading and preparing data prior to building one’s first econometric model can present challenges. The wooldridge data package aims to lighten this task. It contains 105 data sets from Introductory Econometrics: A Modern Approach, which can be loaded with a simple call to the data() function.

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This vignette contains examples from every chapter of Introductory Econometrics: A Modern Approach, 6e by Jeffrey M. Wooldridge. Each example illustrates how to load data, build econometric models, and compute estimates with R.

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Students new to both econometrics and R may find the introduction to both a bit challenging. In particular, the process of loading and preparing data prior to building one’s first econometric model can present challenges. The wooldridge data package aims to lighten this task. It contains 111 data sets from Introductory Econometrics: A Modern Approach, 6e, which can be loaded with a simple call to the data() function.

While the course companion site provides publicly available data sets for Eviews, Excel, MiniTab, and Stata commercial software, R is the open source option. Furthermore, using R while building a foundation in econometric modeling introduces one to software tools capable of scaling with the demands of modern methods in statistical computing.

In addition, the Appendix cites additional sources about using R for econometrics.

Now, install and load the wooldridge package and lets get started.

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Applied Econometrics with R

From the publisher’s website:

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This is the first book on applied econometrics using the R system for statistical computing and graphics. It presents hands-on examples for a wide range of econometric models, from classical linear regression models for cross-section, time series or panel data and the common non-linear models of microeconometrics such as logit, probit and tobit models, to recent semiparametric extensions. In addition, it provides a chapter on programming, including simulations, optimization, and an introduction to R tools enabling reproducible econometric research. An R package accompanying this book, AER, is available from the Comprehensive R Archive Network (CRAN) at http://CRAN.R-project.org/package=AER.

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This is the first book on applied econometrics using the R system for statistical computing and graphics. It presents hands-on examples for a wide range of econometric models, from classical linear regression models for cross-section, time series or panel data and the common non-linear models of microeconometrics such as logit, probit and tobit models, to recent semiparametric extensions. In addition, it provides a chapter on programming, including simulations, optimization, and an introduction to R tools enabling reproducible econometric research. An R package accompanying this book, AER, is available from the Comprehensive R Archive Network (CRAN) at https://CRAN.R-project.org/package=AER.

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Kleiber, Christian and Achim Zeileis. Applied Econometrics with R. ISBN 978-0-387-77316-2, Springer-Verlag, 2008, New York. http://www.springer.com/us/book/9780387773162

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Kleiber, Christian and Achim Zeileis. Applied Econometrics with R. ISBN 978-0-387-77316-2, Springer-Verlag, 2008, New York. https://www.springer.com/us/book/9780387773162

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Marek Hlavac (2015). stargazer: Well-Formatted Regression and Summary Statistics Tables. R package version 5.2. https://CRAN.R-project.org/package=stargazer

Christian Kleiber and Achim Zeileis (2008). Applied Econometrics with R. New York: Springer-Verlag. ISBN 978-0-387-77316-2. URL https://CRAN.R-project.org/package=AER

Franz Mohr (2015). prais: Prais-Winsten Estimation Procedure for AR(1) Serial Correlation. R package version 0.1.1. https://CRAN.R-project.org/package=prais

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R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

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R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Hadley Wickham and Winston Chang (2016). devtools: Tools to Make Developing R Packages Easier. R package version 1.12.0. https://CRAN.R-project.org/package=devtools

Hadley Wickham. testthat: Get Started with Testing. R package version 1.0.2. https://CRAN.R-project.org/package=testthat

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Jeffrey M. Wooldridge (2013). Introductory Econometrics: A Modern Approach. Mason, Ohio :South-Western Cengage Learning.

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Yihui Xie (2017). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.16. https://CRAN.R-project.org/package=knitr

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Jeffrey M. Wooldridge (2016). Introductory Econometrics: A Modern Approach. Mason, Ohio :South-Western Cengage Learning.

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Yihui Xie (2018). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.16. https://CRAN.R-project.org/package=knitr

diff --git a/docs/index.html b/docs/index.html index 5708d38..802113b 100644 --- a/docs/index.html +++ b/docs/index.html @@ -81,7 +81,7 @@

The wooldridge data package aims to lighten the task by easily loading any data set from the text. The package contains documentation for each set and all data has been compressed to a fraction its original size. Just install the package, load it, and call the data you wish to work with.

But wait…there’s more! A vignette, Introductory Econometrics Examples✨ illustrates solutions to examples from each chapter of the text, offering a relevant introduction to econometric modelling with R. The vignette also includes an Appendix of helpful resources, such as Using R for Introductory Econometrics by Florian Hess.

While the original course companion site provides publicly available data sets for Eviews, Excel, MiniTab, and Stata commercial software, R is the open source option. Furthermore, using R while building a foundation in econometric modeling introduces one to software tools capable of scaling with the demands of modern methods in statistical computing. And, working with R is fun.

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Note: All data sets are from the 6th edition (Wooldridge 2016, ISBN-13: 978-1-305-27010-7), which is compatible with most other editions.

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Note: All data sets are from the 6th edition (Wooldridge 2016, ISBN-13: 978-1-305-27010-7), which is backwards compatible with all other editions.

Installation

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Example

Load the wooldridge package and use the data() function to load the desired data set. Data set names match those in the text.

library(wooldridge)
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 data("jtrain")

If using RStudio, View the jtrain data set

View(jtrain)
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Developers

Dev status

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