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Nonparametric instrumental variable estimation

Daniel Wilhelm, Denis Chetverikov () and Dongwoo Kim ()
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Denis Chetverikov: Institute for Fiscal Studies and UCLA

No CWP47/17, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: This paper introduces Stata commands [R] npivreg and [R] npivregcv, which implement nonparametric instrumental variable (NPIV) estimation methods without and with a cross-validated choice of tuning parameters, respectively. Both commands are able to impose monotonicity of the estimated function. The use of such a shape restriction may signi cantly improve the performance of the NPIV estimator (Chetverikov and Wilhelm 2017). This is because the ill-posedness of the NPIV estimation problem leads to unconstrained estimators that suffer from particularly poor statistical properties such as very high variance. The constrained estimator that imposes the monotonicity, on the other hand, signi cantly reduces variance by removing oscillations of the estimator that is nonmonotone. 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: st0001; nonparametric instrumental variable estimation; shape restrictions; monotonicity; endogeneity; regression (search for similar items in EconPapers)
Date: 2017-10-30
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Journal Article: Nonparametric instrumental-variable estimation (2018) Downloads
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