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Bootstrapping the GMM overidentification test under first-order underidentification


Bootstrapping the GMM overidentification test under first-order underidentification

Dovonon, Prosper and Gonçalves, Sílvi (2017) Bootstrapping the GMM overidentification test under first-order 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


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 first-order 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 first-order 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
Authors:Dovonon, Prosper and Gonçalves, Sílvi
Journal or Publication:Journal of Econometrics
Date:9 August 2017
  • FRQSC (Fonds de Recherche du Québec - Société et culture)
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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