| title | Free and open access econometrics textbooks |
|---|---|
| layout | default |
The Econometrics Free Library Project aims to distribute free and open access econometrics texts suitable for graduate education.
- Resources for the PhD core classes
- Microeconometrics electives
- Macroeconometrics and financial econometrics
- Machine Learning topics
- Undergraduate
- Computing
The README page has more information. You can get updates by Twitter, email (archived on Gmane), or our blog (RSS).
- Dan McFadden’s Statistical Tools for Economists, 2001: homepage, local copy and data sets (may be printed and reproduced for individual use, but not for commercial purposes)
- Bruce Hansen’s Econometrics, revised Jan. 16th, 2015: homepage, local copy (may be printed and reproduced for individual or instructional use, but not for commercial purposes)
- Anna Mikusheva’s Statistical Methods in Economics (Part I): homepage, local copy (Creative Commons BY-NC-SA)
- Victor Chernozhukov’s Statistical Methods in Economics (Part II): Homepage, local copy (Creative Commons BY-NC-SA)
- Kenneth Train’s Discrete Choice Methods with Simulation, second edition, 2009 Homepage — the electronic version is “made available for use by individuals for their personal research and study,” so we’re unable to provide a local copy (published by Cambridge University Press).
- Imbens and Wooldridge, What’s new in Econometrics (2007 NBER Summer Institute) — single pdf file of notes to accompany their recorded lectures (see below)
- Imbens and Wooldridge, What’s new in Econometrics (2007 NBER Summer Institute) (pdf of course notes)
- List and Kremer, Using field experiments in economics (2009 NBER Summer Institute)
- Pakes and Nevo’s, Econometric methods for demand estimation (2012 NBER Summer Institute)
- Acemoglu and Jackson’s Theory and Application of Network Models (2014 NBER Summer Institute)
- John Cochrane’s Time Series for Macroeconomics and Finance: pdf, free of cost for noncommercial use, but no explicit license
- Anna Mikusheva’s Time Series Analysis: homepage, local copy (Creative Commons BY-NC-SA)
- Stock and Watson, What’s new in econometrics — time series (2008 NBER Summer Institute)
- Ludvigson, Ait-Sahalia, Brandt, and Lo’s Financial econometrics (2010 NBER Summer Institute)
- Christiano and Fernandez-Villaverde’s Computational tools and macro applications (2011 NBER Summer Institute)
- Dynare, version 4.4.3, released July 31, 2014; (source code)
- Hastie, Tibshirani, and Friedman’s The elements of statistical learning (2nd edition, last corrected in Jan 2013): homepage, pdf
- James, Witten, Hastie, and Tibshirani’s An Introduction to Statistical Learning (corrected 4th printing): homepage, [pdf][e5] This book is aimed at advanced undergraduates and masters students
- Chernozhukov, Gentzkow, Hansen, Shapiro, and Taddy’s Econometric methods for high-dimensional data (2013 NBER Summer Institute)
[e5]: (http://www-bcf.usc.edu/~gareth/ISL/ISLR Fourth Printing.pdf)
- Frank Diebold’s Econometrics: homepage, pdf, and local copy (February 17th, 2015 edition) Creative Commons BY-NC-ND 4.0)
- Frank Diebold’s Forecasting: homepage, pdf, and local copy (December 21st, 2014 edition) Creative Commons BY-NC-ND 4.0)
- James, Witten, Hastie, and Tibshirani’s An Introduction to Statistical Learning: homepage, [pdf][e5] (corrected 4th printing.) (Repeated from above.)
R:
- Project homepage
- CRAN’s Econometrics Task View (maintained by Achim Zeileis)
- CRAN’s Finance Task View (maintained by Dirk Eddelbuettel)
- CRAN’s Statistics for the Social Sciences Task View (maintained by John Fox)
- Hadley Wickham’s Advanced R
- SciPy (scientific computing tools for Python)
- Thomas J. Sargent and John Stachurski’s Quantitative Economics
- Kevin Sheppard’s Python for Econometrics
- Dynare (also listed under Macroeconometrics)
- Project homepage
- Thomas J. Sargent and John Stachurski’s Quantitative Economics
- JuliaStats (statistical computing resources)
- Gentzkow and Shapiro’s Code and Data for the Social Sciences: A Practitioner’s Guide (March, 2014)
- Software Carpentry, part of Mozilla’s Science Lab.