
handle: 10419/189774
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.
npivcv, ddc:330, st0001, endogeneity, monotonicity, nonparametric instrumental variable estimation, shape restrictions, regression, nonparametric instrumental-variable estimation, npiv, st0547
npivcv, ddc:330, st0001, endogeneity, monotonicity, nonparametric instrumental variable estimation, shape restrictions, regression, nonparametric instrumental-variable estimation, npiv, st0547
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