Dovonon, Prosper and Gonçalves, Sílvi (2017) Bootstrapping the GMM overidentification test under firstorder underidentification. Journal of Econometrics . ISSN 03044076 (In Press)

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Official URL: http://dx.doi.org/10.1016/j.jeconom.2017.06.021
Abstract
The main contribution of this paper is to study the applicability of the bootstrap to estimating the distribution of the standard test of overidentifying restrictions of Hansen (1982) when the model is globally identified but the rank condition fails to hold (lack of firstorder local identification). An important example for which these conditions are verified is the popular test of common conditionally heteroskedastic features proposed by Engle and Kozicki (1993). As Dovonon and Renault (2013b) show, the Jacobian matrix for this model is identically zero at the true parameter value, resulting in a highly nonstandard limiting distribution that complicates the computation of critical values.
We first show that the standard GMM bootstrap fails to consistently estimate the distribution of the overidentification restrictions test under lack of firstorder identification. We then propose a new bootstrap method that is asymptotically valid in this context. The modification consists of adding an additional term that recenters the bootstrap moment conditions in a way as to ensure that the bootstrap Jacobian matrix is zero when evaluated at the GMM estimate.
Divisions:  Concordia University > Faculty of Arts and Science > Economics 

Item Type:  Article 
Refereed:  Yes 
Authors:  Dovonon, Prosper and Gonçalves, Sílvi 
Journal or Publication:  Journal of Econometrics 
Date:  9 August 2017 
Funders: 

Digital Object Identifier (DOI):  10.1016/j.jeconom.2017.06.021 
ID Code:  982759 
Deposited By:  DANIELLE DENNIE 
Deposited On:  15 Aug 2017 13:25 
Last Modified:  01 Aug 2018 00:00 
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