Econ Resources

Based on the rapidly development of computer and internet, we could discover various learning material in the internet. But it also need to judge the quality and fitness of them when we are flooded with plenty of materials.

• last updated: Dec. 2023

• I cut off some unrelated resources with econ/fin. Comments are welcome. jianqihuang2002 [at] gmail [dot] com

1 Causal Inference and Econometrics

• Causal Inference: written by Scott.

• The Effect: An Introduction to Research Design and Causality: R code Stata code and Python code.

• Introduction to Econometrics with R

• Mixed Models with R

• Applied Empirical Methods https://github.com/paulgp/applied-methods-phd: designed for graduate students learning econometric methods using empirical research.

• STAT 286/GOV 203

• Introduction to Computational Finance and Financial Econometrics with R

• Statistical Tools for Causal Inference other useful resource given by writter is here

2 Math and Statistics

• Statistical Inference via Data Science https://moderndive.com/

• Doing Bayesian Data Analysis https://bookdown.org/content/3686/

• STAT545:Data wrangling, exploration, and analysis with R

• https://www.statlearning.com/ The classic book: An Introduction to Statistical Learning.

• Statistics Inference: Data Analyst Handbook

• Statistical Inference via Data Science https://moderndive.com/ using R and tidyverse to do statistical inference.

• Bayesian Stats: using Julia to apply Bayesian Statistics.

• Lecture Notes for STAT 709: Mathematical Statistics

• Applied Nonparametric and Modern Statistics

• 应用随机过程：介绍随机过程的基本概念及鞅和在金融中的应用。

3 Computer Science

• Foundations of Machine Learning

• Statistical-Rethinking https://xcelab.net/rm/statistical-rethinking/ A Bayesian Course with R and Stan. It has the equipped video on Youtube, It also appears on Bilibili

• Very Statisticious https://aosmith.rbind.io/

• Deep Learning https://d2l.ai/chapter_preface/index.html

• 神经网络与深度学习 https://nndl.github.io/：复旦大学邱锡鹏

• Deep Learning DIY collecting resources to learn DL.

• https://lost-stats.github.io/ Library of Statistical Techniques (LOST)!

• Advanced Machine Learning

• 数据科学和机器学习

• pytorch tutorial stared in github more than 26k times.

• tf2

• Convex Optimization

• DeepLearning Some derivations in DP

• Advanced Machine Learning

• Neural Network Class Video https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH

• cs231https://cs231n.github.io/

3.1 Data Science

• Julia Data Science

• Using Spatial Data with R: a quick introduction to spatial data with R.

• Spatial Data Science: Getting a deeper learning in Spatial Data Science.

• Computational and Inferential Thinking it is full of statistic methods to do data science.

• Python for Data Science

• Methods for Network Analysis

• Geocomputation with R

• Data Science for Economics and Finance

• https://socviz.co/index.html#preface Data Visualization

• https://tellingstorieswithdata.com/ Telling stories with data.

• DataScience at the Command Line

• Data Visualization with R

• Data Science for Economists: using R.

• Data Science for Economists and Other Animals introducing the core R usuage in Econ.

• Tidy Finance

• R as GIS for Economists

• Computational Economics for PhDs: using Julia in the field of economics is getting more and more popular. written by Florian Oswald.

• Introduction to Python for Econometrics, Statistics and Numerical Analysis

• Forcecasting

• Introduction to Computational Finance and Financial Econometrics with R written by Eric Zivot

• 金融时间序列讲义

• Openair A Guide to the Analysis of Air Pollution Data.

• Economic Networks THEORY AND COMPUTATION written by John Stachurski and Thomas J.Sargent.

4 Lectures

• Abhijit Banerjee and Esther Duflo’s online course at PSE https://www.parisschoolofeconomics.eu/en/news/from-may-24-to-june-4-watch-abhijit-banerjee-and-esther-duflo-s-online-course/#partie1

• Search and Matching in Macro and Finance Virtual Seminar Series https://sammf.com/

• NBER https://www.nber.org/ working paper, online lecture and conferences.

• Useful ML tools for empirical researchers https://www.nber.org/lecture/summer-institute-2018-meet-randomistas-useful-ml-tools-empirical-researchers Development Economics Masters Lecture by Esther Dulfo

• Xiamen University has some lecture on Bilibili, like The Advanced Econometric, Introduction to Nonparametric Analysis in Time Series Econometrics.

5 Macro

• ECON 7300 Tools for Applied Macro I(Cornell, Sp2017)

• Advanced Macroeconomics I taught by Professor Gertler

• Notes on Macroeconomic Theory(pdf)

• Macaro Theory

• Advanced Macroeconomics: Models with Heterogeneous Agents: taught by José Víctor Ríos Rull and Wei Cui

• Advanced macroeconomic analysis taught by JENNIFER LA’O(Columbia Business School)

• PhD Computational Methods Course Fatih Guvenen(UMN)

6 Econometrics and Time Series

• https://web.sas.upenn.edu/schorf/classes/ VAR estimation

• Forecasting: Principles and Practice: the classic book in time-series analysis.

• SVAR

• Graduate Macro Theory II taught by Eric Sims(University of Notre Dame)

• The Econometrics of Unobservables(pdf)

7 Trade and IO

• Advanced Topics in Trade taught by ​Heiwai Tang

• Quantitative Dynamic Model taught by Daniel XU.

• Graduate Trade

• QUANTITATIVE INTERNATIONAL TRADE(pdf)

• Empirical Methods for Industrial Organization taught by Matthew Shum(Caltech).

• Organizational Economics II taught by Daniel Barron(Northwestern).

8 Other Fields

• Urban Economics
• Information Economics
• Environmental Economics
• Political Economy of Development: it is a online book built by bookdown, has some great material in development field.

9 Datas

• Harvard database https://dataverse.harvard.edu/

• Data Sharing for demographic Research https://www.icpsr.umich.edu/web/pages/DSDR/index.html

• Peking Open Research Data https://opendata.pku.edu.cn/

• Kaggle Datasets https://www.kaggle.com/datasets/ The datas are usually uploaded by individuals. So the accuracy couldn’t be permitted. But the datasets are various.

• https://ejd.econ.mathematik.uni-ulm.de/: the newest economic articles data

• UCI machine learning dataset https://archive.ics.uci.edu/ml/datasets.php

• Openicpsr https://www.openicpsr.org/openicpsr/search/studies

• Prof.Yuhua Huang personal Data :https://scholar.harvard.edu/yuhuawang/data includes Corruption Data, Chinese Listed Firms Personnel Database and some replication data from politics paper. By the way Prof.Yuhua Huang has great enthusiasm to help Chinese Social Science student to apply PhD especially in Politics.

• 中国历代人物传记数据库 https://projects.iq.harvard.edu/chinesecbdb

• 中国历史地图 https://chgis.fas.harvard.edu/

• Chinese Country Map with 2000-2010 population Census Data https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/VKGEBX

• Mobility Index based on High-speed Railway Data in China https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/JUBLGB

• China Multi-Generational Panel Dataset, Liaoning. https://www.icpsr.umich.edu/web/DSDR/studies/27063

• China micro survey data: like CFPS CHARLS, CFPS, CGSS, CLDS, CHNS etc. The more detailed information could be found in this or this

• 经济金融实证顶刊数据代码共享网站汇总

• How to access standard data sources

• Nighttime Lights it’s a guest lecuture.

9.1 Replication

• ReplicationWiki

• Find Econ Articles with Data

10 Research

• Guidelines: Research Design & term paper draft

• Guidelines: Term paper

• FINDING ECONOMIC ARTICLES WITH DATA UND STATA REPRODUCTIONS https://skranz.github.io/

• https://gregmankiw.blogspot.com/search?q=advice: the research suggestions from Greg Mankiw.

• https://blogs.ubc.ca/khead/research/research-advice: collected research advice by Keith Head.

• https://sites.google.com/site/mounirkaradja/resources: Tips and resources for research

• https://sites.google.com/view/kleintob/ph-d-students: Academic writing, communicating and many other thing.

11 Programming

• QuantEcon https://quantecon.org/: mainly include some Lectures and projects like Quantitative Economics with Julia etc.

• Coding for Economists https://aeturrell.github.io/coding-for-economists

• The Missing Semester of Your CS Education（中文版）https://missing-semester-cn.github.io/: 强烈推荐，无论是任何专业的都需要学习了解一下。

• https://randrescastaneda.rbind.io/post/notepadpp/ Notepad++ as a Stata editor.

• 东海岸的雨:编程建议集合，包含Stata、R、Python和LaTeX网上资源。

• The Vim Tutorial https://www.truth.sk/vim/vimbook-OPL.pdf

• Happy Git and GitHub for the useR it is a great guidance to access Git and Github in R.

11.1 LaTeX

• getting start with LaTeX https://www.maths.tcd.ie/~dwilkins/LaTeXPrimer/

• Useful LaTeX snippets https://flowus.cn/latex/share/66110e84-b24a-4cd5-b8a7-2ba2afb35a30

• Basic LaTex by kochiyu(HKU)

• A LaTeX Template for Economics Papers https://github.com/cheinchi/Template-for-Overleaf

11.2 Stata

• https://randrescastaneda.rbind.io/post/profile-do/:Stata profile.do: nice tips.

• https://randrescastaneda.rbind.io/post/data-shape-to-export-results/:export rescult to Tableau or Excel.

• Anders Sundell(https://www.stathelp.se/index_en.html ): Stata tips and helps.

• https://julianreif.com/guide/ Stata coding guide.

11.3 R

The online resources of R is vast because of the support of bookdown and the popularity of R.

• https://swirlstats.com/ Interactively learning R in RStudio.

• Local tips for R http://egret.psychol.cam.ac.uk/statistics/R/index.html It is a little outdate but useful.

• Big Book of R https://www.bigbookofr.com/ The Resources collection of R.

• API for Social Scientists https://bookdown.org/paul/apis_for_social_scientists/introduction.html

• The Advanced Rhttps://adv-r.hadley.nz/ This book helps learners master and understand R better and how it works.

• https://r-graphics.org/ R Graphics Cookbook

11.4 Julia

• Dongfeng Li(PKU) https://www.math.pku.edu.cn/teachers/lidf/docs/Julia/html/_book/index.html

• Data-parallel Programming in Julia https://juliafolds.github.io/data-parallelism/#data-parallel_programming_in_julia

• Juliaplots

11.5 Python

• FinTech Toolbox https://www.bilibili.com/video/BV1DE411y7nz/?spm_id_from=333.999.0.0

12 Personal Website

• Yan Liu(Wuhan U)http://www.liuyanecon.com/misc/

• Alvin Roth http://web.stanford.edu/~alroth/alroth.html

• 周其仁

• Jichun Si

• Leilei(SWUFE) dataset https://sites.google.com/view/leileitilburg/resources/data-in-china

• Yiqing Xu(Stanford)https://yiqingxu.org/

• https://sites.google.com/site/mkudamatsu/home: Prof.Masayuki Kudamatsu, the stata collection and Devecondata.

• Daniel L. Millimet(SMU) https://people.smu.edu/dmillimet/：containing the Econmetrics II, Microeconometrics at Graduate level and the code and Blog about econometric.

• Zhengtao Shi(CUHK) http://zhentaoshi.github.io/ There are many econometric and data science learning material in his github page.

• Xu Liu(SHUFE) https://xliusufe.github.io/: R and Python.

• Shujia Wang(Shenzhen U) https://andrewwang.rbind.io/

• Garrick Aden-Buie https://www.garrickadenbuie.com/about/ The Data Science Educator and R developer.

• Ariel Rubinsteinhttps://arielrubinstein.tau.ac.il/

• https://www.alexanderkzentefis.com/

• Menghan Xuhttp://xumhandy.com/wp/: Assistant professor at Xiamen University, including the micro theory course.

• https://cms27.github.io/ assitant professor at bocconi university, he teach some useful course.

• Zhaopeng Qu(NanJing U) https://byelenin.github.io/zh/index.html Applied Microeconometrics

• Weiping Li(USTC) http://staff.ustc.edu.cn/~zwp/ 概率论与数理统计、贝叶斯统计等统计课程，包括统计计算R软件的一些应用。

• Florain Oswald(Science Po) https://floswald.github.io/ having some econometric material

• Kevin Sheppard(Oxford University) https://www.kevinsheppard.com/ having a large volume of teching resources, including Financial Economics and introduction to both python and MATLAB.

• https://www.garrickadenbuie.com/blog/

• Eric Sims(University of Notre Dame)https://www3.nd.edu/~esims1/ there is a intermediate macroeconomics on his webisite.

12.1 Blogs

• https://critical-inference.com/

• Andrew Gelman https://statmodeling.stat.columbia.edu/

• https://xianblog.wordpress.com/

• Economics and R https://skranz.github.io/ the replication with Economic Top journal.

• https://deliasguidetoeconomics.blogspot.com/

13 Resouces Set

• https://www.albrightalex.com/public-goods

• Advice on and resources for doing research: collected by David Angenendt(TUM)

• https://jblevins.org/notes/: jblevins’s note

• https://weisi.website/resources/: 上海科技大学助理教授司唯的资源集合

• http://www.ryanbedwards.com/resources: the resources is mostly for students.

• https://sites.google.com/site/mkudamatsu/tips4economists: Tips 4 Economists

• Resources for PhD Students http://li.dyson.cornell.edu/phdRes.php

• http://jenniferdoleac.com/resources/, Jennifer Doleac