ECON 211-001 (1094), 2021 Autumn Term (Seven Week – Second Session), Duke Kunshan University
Acknowledgments: the Autumn 2021 collection is partly supported by the Social Science Divisional Chair’s Discretionary Fund to encourage faculty engagement in undergraduate research and enhance student-faculty scholarly interactions outside of the classroom. The division chair is Prof. Keping Wu, Associate Professor of Anthropology at Duke Kunshan University. And the supported students include Administrative Teaching Assistants, Xinyu Tian and Tianyu Wu, and Teaching Assistants, Jingwei Li, Chenyu Wang, and Zesen Zhuang. We thank Jiaxin Wu and the team at DKU Center for Teaching and Learning for their assistants in implementing Gradescope for class assignments.
Instructor:
Dr. Luyao Zhang, Assistant Professor of Economics at Social Science Division and Senior Research Scientist at Data Science Research Center, Duke Kunshan University
Administrative Teaching Assistants：Xinyu Tian and Tianyu Wu
Xinyu Tian, Data Science, Class of 2023, Duke Kunshan University
Tianyu Wu, Applied Mathematics and Computational Science, Class of 2023, Duke Kunshan University
Teaching Assistants: Jingwei Li, Chenyu Wang, and Zesen Zhuang
Jingwei Li, Data Science, Class of 2023, Duke Kunshan University
Chenyu Wang, Applied Mathematics and Computational Science, Class of 2023, Duke Kunshan University
Zesen Zhuang, Data Science, Class of 2023, Duke Kunshan University
With the development of computer science, more and more tools are invented to help solve economic related problems. In this project, we will introduce five useful tools for Economics: Nashpy, QuanEcon, Game Theory Explorer (GTE), Gambit, and Mesa. Nashpy and QuantEcon are able to solve simple game theory problems, and both of them can be accessed by Python. Game Theory Explorer and Gambit are used for simulating and solving extensive games. Mesa is a Python framework for agent-based modeling. We hope this project would be helpful for those who want to solve economic problems with technical tools.
oTree is an open-source platform for making surveys and experiments. In this tutorial, we describe how to make a simple questionnaire application with oTree, covering the use of oTreeHub, modifying the oTree application on PyCharm, and how to run and release the oTree application on local and online platforms. ###Table of Content
Project 3: Software and Packages for Empirical Research: Statistic Tests, Econometrics, and Machine Learning
In this porject, we introduce 11 useful tools for Economics: Neural Network Playground, TensorFlow, PyTorch, Eli5, Scipy, Statsmodel, Pingouin, SKlearn (scikit-learn), Keras, FinTA, and Kaggle Kernel. Basic information is provided for every tool, including introduction, license, required citation for this tool. Also, we provide examples for three of the tools: TensorFlow, SKlearn and Kaggle Kernel. We hope this project would be helpful for those who want to conduct machine learning and statistical analysis in the field of economics.
For writing in emerging fields and interdisciplinary disciplines, writing skills are no longer the only need. The new era of research requires an increasing number of writing techniques to be mastered. This article introduces some of the software and platforms that are needed for writing, typesetting as well as content creating, and provides some relevant references.
We used Gradescope for both Essay and Code Assignments for two courses at Duke Kunshan University in Autumn 2021. In Econ 101 Economic Principles, we implement three essay assignments, and in Econ 211 Intelligent Economics: An Explainable AI Approach, we implement three essay assignments and one code assignment. In the user cases, we integrate Gradescope to Sakai, the Learning Management System (LMS) adopted at both Duke University and Duke Kunshan University. In this article, we summarize the Gradescope resources, user experience, and reflections for the future of gradings.