← Search

American Economic Review Vol. 105 No. 5 2015

Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments

Victor Chernozhukov1; Christian Hansen2; Martin Spindler3

1 Massachusetts Institute of Technology, 50 Memorial Drive, E52-361B, Cambridge, MA 02142 (e-mail: ) · 2 Booth School of Business, University of Chicago, 5807 S. Woodlawn Ave., Chicago, IL 60637 (e-mail: ) · 3 Munich Center for the Economics of Aging, Amalienstr. 33, 80799 Munich, Germany (e-mail: )

open access

Abstract

We consider estimation of and inference about coefficients on endogenous variables in a linear instrumental variables model where the number of instruments and exogenous control variables are each allowed to be larger than the sample size. We work within an approximately sparse framework that maintains that the signal available in the instruments and control variables may be effectively captured by a small number of the available variables. We provide a LASSO-based method for this setting which provides uniformly valid inference about the coefficients on endogenous variables. We illustrate the method through an application to demand estimation.

DOI
10.1257/aer.p20151022
Volume
105
Issue
5
Pages
486-490
Language
en
Sources
bibtex:phds-export.bib openalex crossref

Cite