Other Resources

Extra resources for applied statistics, causal inference, econometrics etc.

Disclaimer: Resources in this page are listed by the past teaching assistants of QSS at UTokyo (cohort 2021 and 2022) for the sole purpose of broadly introducing students to a wide array of study materials. Prof. Kosuke Imai does not personally endorse (or dis-endorse) any of the materials listed (or unlisted) in this page.

Causal Inference & Econometrics

Introductory

• Causal Inference: The Mixtape - Scott Cunningham
• Mastering ’Metrics - Josh Angrist and Steve Pischke
• Introductory Econometrics - A Modern Approach - Jeffrey M. Wooldridge
• Introduction to econometrics with R - Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer
• Using R for Introductory Econometrics - Florian Heiss

Intermediate & Advanced

• Angrist, Joshua D. and Jörn-Steffen Pischke. 2008. Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton University Press.
• Imbens, Guido W., and Donald B. Rubin. 2015. Causal Inference for Statistics, Social, and Biomedical Sciences. Cambridge University Press.
• Hayashi, Fumio. 2000. Econometrics. Princeton University Press
• Econometrics - Bruce Hansen
• Hernán, Miguel A. and James M. Robins. 2012. Causal Inference. Forthcoming, Cambridge University Press.
• Wooldridge, Jeffrey M. 2010. Econometric Analysis of Cross Section and Panel Data, Second Edition. MIT Press.
• Morgan, Stephen L, and Christopher Winship. 2015. Counterfactuals and Causal Inference, Second Edition. Cambridge University Press.
• Rosenbaum, Paul R. 2009. Design of Observational Studies. Springer Series in Statistics.
• Rosenbaum, Paul R. 2002. Observational Studies. Springer-Verlag. 2nd edition.
• Pearl, Judea. 2000. Causality: Models, Reasoning, and Inference. New York: Cambridge University Press.
• Manski, Charles F. 1995.* Identification Problems in the Social Sciences*. Cambridge: Harvard University Press.
• Rubin, Donald. 2006. Matched Sampling for Causal Effects. Cambridge University Press.
• Econometric Analysis - William H. Greene

Bayesian Data Analysis

• Bayesian Data Analysis, 3rd ed. - Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin
• Statistical Rethinking - Richard McElreath

Machine Learning

• Pattern Recognition and Machine Learning - Christopher M. Bishop

Maths (probability theory; linear algebra; calculus; statistics)

• Foundations of Agonostic Statistics - Peter M. Aronow et al. 
• PROBABILITY AND STATISTICS FOR ECONOMISTS - Bruce Hansen
• Notes for Mathematics for Political Science - Kosuke Imai

Others

• How to write an empirical social science paper? - Kosuke Imai
• Data Analysis in International Relations/国際関係論におけるデータ分析 - Shohei Doi
• Data Analysis and Politics - Matthew Blackwell

Resources in Japanese

Causal Inference

• 松林哲也. (2021).『政治学と因果推論：比較から見える政治と社会』, 岩波書店

• 高橋将宜. (2022).『統計的因果推論の理論と実装:潜在的結果変数と欠測データ』, 共立出版

• 久米郁男. (2013).『原因を推論する：政治分析方法論のすゝめ』, 有斐閣

Political Methodology

• Rで計量政治学入門 - Shohei Doi

• 浅野正彦・矢内勇生.（2018）.『Rによる計量政治学』, オーム社

• 加藤淳子・境家史郎・山本健太郎. (2014).『政治学の方法』, 有斐閣