The Large Sample Behaviour of the Generalized Method of Moments Estimator in Misspecified Models

Alastair Hall and Atsushi Inoue

Econometrics from University Library of Munich, Germany

Abstract: This paper presents the limiting distribution theory for the GMM estimator when the estimation is based on a population moment condition which is subject to non--local (or fixed) misspecification. It is shown that if the parameter vector is overidentified then the weighting matrix plays a far more fundamental role than it does in the corresponding analysis for correctly specified models. Specifically, the rate of convergence of the estimator depends on the rate of convergence of the weighting matrix to its probability limit. The analysis is presented for four particular choices of weighting matrix which are commonly used in practice. In each case the limiting distribution theory is different, and also different from the limiting distribution in a correctly specified model. Statistics are proposed which allow the researcher to test hypotheses about the parameters in misspecified models.

Keywords: Misspecification; Generalized Method of Moments; Asymptotic Distribution Theory (search for similar items in EconPapers)
JEL-codes: C10 C32 (search for similar items in EconPapers)
Date: 2005-05-10
New Economics Papers: this item is included in nep-ecm and nep-ets
Note: Type of Document - pdf
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0505/0505002.pdf (application/pdf)

Related works:
Journal Article: The large sample behaviour of the generalized method of moments estimator in misspecified models (2003)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0505002

Access Statistics for this paper

More papers in Econometrics from University Library of Munich, Germany
Bibliographic data for series maintained by EconWPA ( this e-mail address is bad, please contact ).