Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments
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Post-Selection and Post-Regularization.pdf
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482.46 KB
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Author(s)
Hansen, Christian
Spindler, Martin
Chernozhukov, Victor V
Date Issued
May 2015
Journal
American Economic Review
Publisher
American Economic Association
Citation
Chernozhukov, Victor, Christian Hansen, and Martin Spindler. “ Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments .” American Economic Review 105, no. 5 (May 2015): 486–490. © 2017 American Economic Association.
Version
Final published version
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.
MIT Department
Massachusetts Institute of Technology. Department of Economics
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1257/aer.p20151022
