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GENERAL SPECIFICATION TESTING WITH LOCALLY MISSPECIFIED MODELS

Published online by Cambridge University Press:  22 March 2010

Anil K. Bera ,
Gabriel Montes-Rojas  and
Walter Sosa-Escudero
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Abstract

A well known result is that many of the tests used in econometrics, such as the Rao score (RS) test, may not be robust to misspecified alternatives, that is, when the alternative model does not correspond to the underlying data generating process. Under this scenario, these tests spuriously reject the null hypothesis too often. We generalize this result to generalized method of moments–based (GMM-based) tests. We also extend the method proposed in Bera and Yoon (1993, Econometric Theory 9, 649–658) for constructing RS tests that are robust to local misspecification to GMM-based tests. Finally, a further generalization for general estimating and testing functions is developed. This framework encompasses both likelihood and GMM-based results.

Type
Brief Report
Information
Econometric Theory , Volume 26 , Issue 6 , December 2010 , pp. 1838 - 1845
Copyright
Copyright © Cambridge University Press 2010

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Footnotes

We are grateful to the coeditor Jinyong Hahn and two anonymous referees for many pertinent comments and suggestions. However, we retain the responsibility for any remaining shortcomings.

References

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