index.md

title	Econometrics Free Library Project
layout	default

The Econometrics Free Library Project aims to distribute free and open access econometrics texts suitable for graduate education. Although the original plan was to produce these texts ourselves, time constraints have made that impractical, so we’ll focus on curation. (“We” is one tenure-track professor.)

• Page contents
  • Resources for the PhD core classes
  • Microeconometrics electives
  • Macroeconometrics and financial econometrics
  • Machine Learning topics
  • Undergraduate
  • Computing
  • Website details

The README page has more information. You can get updates by Twitter, email (archived on Gmane), or our blog (RSS).

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Resources for the PhD core classes

• Textbooks:
  • 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)
• MIT OpenCourseWare:
  • 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)

Microeconometrics electives

• Textbooks:
  • 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).
• Lecture notes:
  • Imbens and Wooldridge, What’s new in Econometrics (2007 NBER Summer Institute) — single pdf file of notes to accompany their recorded lectures (see below)
• Recorded lectures:
  • 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)

Macroeconometrics and financial econometrics

• Textbooks:
  • John Cochrane’s Time Series for Macroeconomics and Finance: pdf, free of cost for noncommercial use, but no explicit license
• MIT OpenCourseWare:
  • Anna Mikusheva’s Time Series Analysis: homepage, local copy (Creative Commons BY-NC-SA)
• Recorded lectures:
  • 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)
• Software:
  • Dynare, version 4.4.3, released July 31, 2014; (source code)

Machine Learning topics

• Textbooks:
  • 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
• Recorded lectures:
  • 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)

Undergraduate

• Textbooks:
  • 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.)

Computing

• 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
• Python:
  • SciPy (scientific computing tools for Python)
  • Thomas J. Sargent and John Stachurski’s Quantitative Economics
  • Kevin Sheppard’s Python for Econometrics
• Matlab/Octave:
  • Dynare (also listed under Macroeconometrics)
• Julia:
  • Project homepage
  • Thomas J. Sargent and John Stachurski’s Quantitative Economics
  • JuliaStats (statistical computing resources)
• Scientific computing, general 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.

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Website details

This website is hosted on GitHub Pages and maintained by Gray Calhoun (email: gcalhoun@iastate.edu, twitter: @grayclhn).