Partly Linear Instrumental Variables Regressions without Smoothing on the Instruments

TL;DR

This paper introduces a new estimation method for semiparametric partly linear models with instrumental variables that avoids smoothing on the instruments, extending regularization techniques and demonstrating favorable asymptotic properties.

Contribution

It develops a novel estimation approach that does not require smoothing on the instruments, extending Landweber-Fridman regularization to this context.

Findings

Estimator achieves asymptotic normality

Convergence rate for nonparametric component established

Simulation shows strong performance of the proposed method

Abstract

We consider a semiparametric partly linear model identified by instrumental variables. We propose an estimation method that does not smooth on the instruments and we extend the Landweber-Fridman regularization scheme to the estimation of this semiparametric model. We then show the asymptotic normality of the parametric estimator and obtain the convergence rate for the nonparametric estimator. Our estimator that does not smooth on the instruments coincides with a typical estimator that does smooth on the instruments but keeps the respective bandwidth fixed as the sample size increases. We propose a data driven method for the selection of the regularization parameter, and in a simulation study we show the attractive performance of our estimators.