Nonparametric instrumental-variable estimation

Denis Chetverikov (), Dongwoo Kim and Daniel Wilhelm
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Denis Chetverikov: University of California, Los Angeles

Stata Journal, 2018, vol. 18, issue 4, 937-950

Abstract: In this article, we introduce the commands npiv and npivcv, which implement nonparametric instrumental-variable (NPIV) estimation methods without and with a cross-validated choice of tuning parameters, respectively. Both com- mands can impose the constraint that the resulting estimated function is mono- tone. Using such a shape restriction may significantly improve the performance of the NPIV estimator (Chetverikov and Wilhelm, 2017, Econometrica 85: 1303– 1320) because the ill-posedness of the NPIV estimation problem leads to uncon- strained estimators that suffer from particularly poor statistical properties such as high variance. However, the constrained estimator that imposes the monotonicity significantly reduces variance by removing nonmonotone oscillations of the esti- mator. We provide a small Monte Carlo experiment to study the estimators’ finite-sample properties and an application to the estimation of gasoline demand functions.

Keywords: npiv; npivcv; nonparametric instrumental-variable estimation; shape restrictions; monotonicity; endogeneity; regression (search for similar items in EconPapers)
Date: 2018
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Related works:
Working Paper: Nonparametric instrumental variable estimation (2017)
Working Paper: Nonparametric instrumental variable estimation (2017)
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