Nonparametric instrumental-variable estimation
Denis Chetverikov
Department of Economics
University of California, Los Angeles
Los Angeles, CA
[email protected]
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Dongwoo Kim
Department of Economics
University College London
London, UK
[email protected]
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Daniel Wilhelm
Department of Economics
University College London
London, UK
[email protected]
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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
commands can impose the constraint that the resulting estimated function is
monotone. 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 unconstrained 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 estimator. We provide a
small Monte Carlo experiment to study the estimators' finite-sample properties
and an application to the estimation of gasoline demand functions.
View all articles by these authors:
Denis Chetverikov, Dongwoo Kim, Daniel Wilhelm
View all articles with these keywords:
npiv, npivcv, nonparametric instrumental-variable estimation, shape restrictions, monotonicity, endogeneity, regression
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