City Research Online

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 GMM based tests. We also extend the method proposed in Bera and Yoon (Econometric Theory 9, 1993) 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 the Bera-Yoon likelihood based results as well as its use in the GMM environment.

Publication Type:	Article
Additional Information:	Copyright Cambridge Journals, 2010. Content and layout follow Cambridge University Press’s submission requirements. This version may have been revised following peer review but may be subject to further editorial input by Cambridge University Press.
Publisher Keywords:	Specification testing; Rao's score test; Local misspecification; GMM based tests; General estimating and testing functions
Subjects:	H Social Sciences > HB Economic Theory
Departments:	School of Policy & Global Affairs > Economics
SWORD Depositor:	Symplectic Administrator

Export

Downloads