Ридинг лист по конкретным методам находится тут (пока это очень черновая неразобранная версия).
- Literature on Recent Advances in Applied Micro Methods (Christine Cai, 2022)
- Collection of lecture notes, videos, papers, workshops, etc. (Asjad Naqvi )
- Введение в прикладную статистику и эконометрику (Архангельский, 2016)
- Topics in Causal Inference (Архангельский, 2018)
- Intro into Panel Data Methods (Архангельский, 2020)
- Intro to Experimental Analysis (Архангельский, 2021)
- Causal Inference: The Mixtape (Scott Cunningham, 2021)
- The Effect: An Introduction to Research Design and Causality (Nick Huntington-Klein, 2022)
- Causal Inference: What If (Miguel Hernan, Jamie Robins, 2020)
- Mostly Harmess Econometrics (Joshua D. Angrist, Jörn-Steffen Pischke)
- Mastering ‘Metrics (Joshua D. Angrist, Jörn-Steffen Pischke)
- Causal Inference for The Brave and True (Matheus Facure)
- Statistical Tools for Causal Inference (Sylvain Chabé-Ferret, 2022)
- Introduction to Causal Inference (Brady Neal, 2020)
- Counterfactuals and Causal Inference. Methods and Principles for Social Research (Stephen L. Morgan, Christopher Winship, 2007)
- The Theory and Practice of Field Experiments: An Introduction from the EGAP Learning Days
- Using R for introductory econometrics (Heiss, 2016)
- Causality (Judea Pearl, 2009)
- Causal inference in statistics (Judea Pearl, Madelyn Glymour, Nicholas P. Jewell, 2016)
- The book of why: the new science of cause and effect (Judea Pearl, Dana Mackenzie, 2018)
- A Guide on Data Analysis
- Marketing Research
- Introduction to Causal Inference from a Machine Learning Perspective (Brady Neal, 2020)
- Research Design in the Social Sciences (Declaration, Diagnosis, Redesign)
- The Effect. Econometrics, Causality, and Coding with Dr. HK (Nick Huntington-Klein)
- Econometrics, Causality, and Coding with Dr. HK (Nick Huntington-Klein)
- Causal Inference -- Online Lectures (M.Sc/PhD Level) (Ben Elsner)
- Visualization, Identification, and Estimation in the Linear Panel Event-Study Design (Jesse Shapiro, Christian Hansen)
- Applied Methods PhD Course (Paul Goldsmith-Pinkham, 2021)
- DiD Reading Group (Taylor Wright) и Other DiD Seminars
- Introduction to Econometrics (Ivan A. Canay, 2021)
- Topics in Econometric Theory (Ivan A. Canay, 2021)
- Mastering Mostly Harmless Econometrics (Alberto Abadie, Joshua Angrist, and Christopher Walters, 2020)
- Cross-Section Econometrics (Alberto Abadie, Joshua Angrist, Christopher Walters, 2017)
- Time Series Econometrics (James H. Stock and Mark W. Watson, 2015)
- Сross-Section Econometrics (Alberto Abadie and Joshua Angrist, 2014)
- Time Series Econometrics (Giorgio Primiceri and Frank Schorfheide, 2013)
- Cross-section Econometrics (Guido Imbens and Jeffrey Wooldridge, 2012)
- Time-Series Econometrics (James H. Stock and Mark W. Watson, 2010)
- Cross-Section Econometrics (Jeffrey Wooldridge and Guido Imbens, 2009)
- Mixtape-Sessions (Scott Cunningham)
- Introduction to Causal Inference (Brady Neal, 2020)
- Causal Inference for the Social Sciences (Jasjeet S. Sekhon, 2015)
- Program Evaluation for Public Service (Andrew Heiss, 2020)
- Class material in Statistics and Econometrics (Paolo Zacchia)
- Introduction to Statistics with Computer Applications (Kyle F Butts)
- Applied Empirical Methods (Paul Goldsmith-Pinkham)
- Applied Econometrics at NYU Stern (Chris Conlon)
- Data Science for Business Applications (Magdalena Bennett)
- Probability and Statistics / Econometric Theory / Microeconometrics (Paolo Zacchia)
- Graduate econometrics (Ivan A. Canay)
- Topics in Econometrics (Ivan A. Canay)
- Causal Inference (Stefan Wager)
- Econometrics (Undergraduate)(Daniele Girardi)
- Introduction to Probability and Statistics (Kyle Butts)
- Causal AI Blog (Brady Neal)
- Causal Analysis in Theory and Practice
- Nick Huntington-Klein
- Christine Cai
- Andrew Baker
- Paul Goldsmith-Pinkham
- David Schönholzer
- Разведывательный анализ данных с помощью языка R (Пензар Д, Жарикова А., Валяева А.)
- Основы программирования на R (Антонов А.)
- Анализ данных в R (Иванчей И., Карпов А.)
- Анализ данных в R. Часть 2 (Карпов А., Грозин В., Антонов А.)
- An Introduction to R. Notes on R: A Programming Environment for Data Analysis and Graphics (W. N. Venables, D. M. Smith, 2022)
- Using R for Introductory Econometrics (Florian Heiss)
- Guide to R For SCU Economics Students (William A. Sundstrom, Michael J. Kevane)
- Introduction to Econometrics with R (Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer)
- R for Data Science (Hadley Wickham, Garrett Grolemund)
- Hands-On Programming with R (Garrett Grolemund)
- Data Science: A First Introduction (Tiffany Timbers, Trevor Campbell, and Melissa Lee)
- YaRrr! The Pirate’s Guide to R (Nathaniel D. Phillips)
- Advanced R (Hadley Wickham)