(Econ/ARE 240F) Readings

**STATISTICAL LEARNING**

For statistical learning the main text is an undergraduate level
book

**ISL: **Gareth James, Daniela Witten, Trevor Hastie and
Robert Tibsharani (2013), **An Introduction to Statistical
Learning: with Applications in R**, Springer.

A free legal pdf is at http://www-bcf.usc.edu/~gareth/ISL/
and a $25 hardcopy can be obtained via
http://www.springer.com/gp/products/books/mycopy

Supplementary material on statistical learning will come
from the graduate level book

**ESL: **Trevor Hastie, Robert Tibsharani and Jerome Friedman
(2009), The Elements of Statistical Learning: Data Mining,
Inference and Prediction, Springer.

A free legal pdf is at
http://statweb.stanford.edu/~tibs/ElemStatLearn/index.html
and a $25 hardcopy can e obtained via
http://www.springer.com/gp/products/books/mycopy

This is a very active area: All the papers below were published in 2012 or later.

Partial Survey focused on using LASSO: A. Belloni, V. Chernozhukov and C. Hansen: 54. "High-Dimensional Methods and Inference on Treatment and Structural Effects in Economics, " J. Economic Perspectives Spring 2014, pp.29-50 with Stata and Matlab programs here; and Stata replication code here

Lasso and IV: A. Belloni, V. Chernozhukov, D. Chen, and C. Hansen. "Sparse Models and Methods for Instrumental Regression, with an Application to Eminent Domain", Arxiv 2010, Econometrica 2012, pp.2369-2429.

Lasso and control function: A. Belloni, V. Chernozhukov and C. Hansen: "Inference on Treatment Effects After Selection Among High-Dimensional Controls," The Review of Economic Studies 2014, p.608-650.

Lasso and Propensity score weighting: M. Farrell, "Robust Inference on Average Treatment effects with possibly more Covariates than Observations," Journal of Econometrics, 2015, vol.189, pp.1-23.

H. Varian Big Data: New Tricks for Econometrics J. Economic Perspectives Spring 2014, pp. 3-28.

Dataset can be obtained from https://www.aeaweb.org/articles.php?doi=10.1257/jep.28.2

Other papers by Chernozhukov and coauthors on this topic are at http://www.mit.edu/~vchern/#veryhigh

G. Imbens and S. Athey "Machine Learning Methods for Estimating Heterogeneous Causal Effects"

Brief overview paper by S. Athey "Machine Learning and Causal Inference for Policy Evaluation" http://faculty-gsb.stanford.edu/athey/documents/AtheyKDDfinal.pdf

Other papers by Athey are at http://faculty-gsb.stanford.edu/athey/research.html#Econometric_Theory_%28Identification_and_E

See handouts on Smartsite

Cameron, A.C. and P.K. Trivedi (2005), Microeconometrics: Methods and Applications, 13.1-13.6; 13.8.

Koop, G. (2003), Bayesian Econometrics, New York, Wiley.

MULTIPLE IMPUTATION

Cameron, A.C. and P.K. Trivedi (2005), Microeconometrics: Methods and Applications, 13.7; 27.1-27.9.

Allison, P.D. (2002), Missing Data, Beverly Hills, CA , Sage Publications.

Rubin, D.B. (1996), "Multiple Imputation after 18+ Years," Journal of the American Statistical Association, 91, 473-489.

Stata Manual, [MI] Multiple Imputation, Stata Press.