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Optimal bandwidth selection for robust generalized method of moments estimation

Authors: Daniel Wilhelm
Date: 24 March 2014
Type: cemmap Working Paper, CWP15/14
DOI: 10.1920/wp.cem.2014.1514

Abstract

A two-step generalized method of moments estimation procedure can be made robust to heteroskedasticity and autocorrelation in the data by using a nonparametric estimator of the optimal weighting matrix. This paper addresses the issue of choosing the corresponding smoothing parameter (or bandwidth) so that the resulting point estimate is optimal in a certain sense. We derive an asymptotically optimal bandwidth that minimizes a higher-order approximation to the asymptotic mean-squared error of the estimator of interest. We show that the optimal bandwidth is of the same order as the one minimizing the mean-squared error of the nonparametric plugin estimator, but the constants of proportionality are signifi cantly di fferent. Finally, we develop a data-driven bandwidth selection rule and show, in a simulation experiment, that it may substantially reduce the estimator's mean-squared error relative to existing bandwidth choices, especially when the number of moment conditions is large.

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Now published:
Daniel Wilhelm October 2015, Optimal bandwidth selection for robust generalized method of moments estimation, Journal Article, Cambridge University Press

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