Specification Testing with Locally Misspecified Alternatives

It is well known that most of the standard specification tests are not robust when the alternative is misspecified. Using the asymptotic distributions of standard Lagrange multiplier (LM) test under local misspecification, we suggest a robust specification test. This test essentially adjusts the mea...

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Published in:Econometric theory 1993-12, Vol.9 (4), p.649-658
Main Authors: Bera, Anil K., Yoon, Mann J.
Format: Article
Language:English
Subjects:
Covariance matrices
Economic models
Economic statistics
Estimators
International economics
Lagrange multipliers
Maximum likelihood estimation
Probabilities
Statistical variance
Statistics
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description It is well known that most of the standard specification tests are not robust when the alternative is misspecified. Using the asymptotic distributions of standard Lagrange multiplier (LM) test under local misspecification, we suggest a robust specification test. This test essentially adjusts the mean and covariance matrix of the usual LM statistic. We show that for local misspecification the adjusted test is asymptotically equivalent to Neyman's C(α) test, and therefore, shares the optimality properties of the C(α) test. The main advantage of the new test is that, compared to the C(α) test, it is much simpler to compute. Our procedure does require full specification of the model and there might be some loss of asymptotic power relative to the unadjusted test if the model is indeed correctly specified.
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source International Bibliography of the Social Sciences (IBSS); JSTOR-E-Journals; KB+ Cambridge University Press: JISC Collections:Full Collection Digital Archives (STM and HSS)
subjects Covariance matrices
Economic models
Economic statistics
Estimators
International economics
Lagrange multipliers
Maximum likelihood estimation
Probabilities
Statistical variance
Statistics
title Specification Testing with Locally Misspecified Alternatives
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