Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments
Victor Chernozhukov, Christian Hansen, Martin Spindler
American Economic Review · 2015 · Volume 105 · Issue 5
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.
Keywords
Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation, Multiple or Simultaneous Equation Models: Instrumental Variables (IV) Estimation, Consumer Economics: Empirical Analysis
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