Detecting Lack of Identification in GMM

34 Pages Posted: 22 Nov 2000

See all articles by Jonathan H. Wright

Jonathan H. Wright

Johns Hopkins University - Department of Economics

Date Written: July 2000

Abstract

In the standard linear instrumental variables regression model, it must be assumed that the instruments are correlated with the endogenous variables in order to ensure the consistency and asymptotic normality of the usual instrumental variables estimator. Indeed, if the instruments are only slightly correlated with the endogenous variables, the conventional Gaussian asymptotic theory may still provide a very poor approximation to the finite sample distribution of the usual instrumental variables estimator. Because of the crucial role of this identification condition, it is common to test for instrument relevance by a first-stage F-test. Identification issues also arise in the generalized method of moments model, of which the linear instrumental variables model is a special case. But I know of no means, in the existing literature, of testing for identification in this model. This paper proposes a test of the null of underidentification in the generalized method of moments model.

Keywords: Generalized Method of Moments, Identification, Asset Pricing, Instrumental Variables

JEL Classification: C10

Suggested Citation

Wright, Jonathan H., Detecting Lack of Identification in GMM (July 2000). Available at SSRN: https://ssrn.com/abstract=237284 or http://dx.doi.org/10.2139/ssrn.237284

Jonathan H. Wright (Contact Author)

Johns Hopkins University - Department of Economics ( email )

3400 Charles Street
Baltimore, MD 21218-2685
United States

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