Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/97367
Authors: 
Wilhelm, Daniel
Year of Publication: 
2014
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP15/14
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 meansquared 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 significantly different. 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.
Subjects: 
GMM
higher-order expansion
optimal bandwidth
mean-squared error
long-run variance
JEL: 
C12
C13
C14
C22
C51
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
419.35 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.