TOPICS IN ECONOMETRICS: CROSS-SECTION
ANALYSIS
(Econ/ARE 240F) Readings
Department of Economics
University of California - Davis
Spring 2016
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
STATISTICAL LEARNING FOR ECONOMETRICS
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
BAYESIAN ECONOMETRICS
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.
INFERENCE WITH CLUSTERED ERRORS
A. Colin Cameron and Douglas L. Miller, "A
Practitioner's Guide to Cluster-Robust Inference", Journal of Human
Resources, Spring
2015, Vol.50, No. 2, pp.317-373. http://cameron.econ.ucdavis.edu/research/Cameron_Miller_JHR_2015_February.pdf
FURTHER TOPICS
To come