MACHINE LEARNING or STATISTICAL LEARNING
Based on (Econ/ARE 240F)
Department of Economics, University of California -
Davis Spring 2016
TYPED LECTURE SLIDES
Based on the two books by Hastie, Tibsharani and coauthors
HAND-WRITTEN LECTURE SLIDES
Covers applications in econometrics with inference that
controls for data-mining
For statistical learning the main text used in 240F is an
undergraduate / masters 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
Supplementary material on statistical learning came from the
Ph.D. level book
A new book that will be good but I haven't used is
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
and a $25 hardcopy can e obtained via
Bradley Efron and Trevor Hastie (2016) Computer Age
Statistical Inference: Algorithms, Evidence and Data Science
LEADERS IN ECONOMETRICS
Bringing established machine learning methods into
econometrics is currently an active area. The literature focuses
on valid statistical inference controlling for fist-stage data
mining, and causal inference. Leading econometricians include
Guido Imbens https://www.gsb.stanford.edu/faculty-research/faculty/guido-w-imbens
Susan Athey https://www.gsb.stanford.edu/faculty-research/faculty/susan-athey
Coursera has many courses https://www.coursera.org/browse/data-science/machine-learning?languages=en
REFERENCES FOR 240F Spring 2016
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.
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