Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models
AbstractMarkov switching (MS) models raise a problem known as testing hypotheses when a nuisance parameter is not identified under the null hypothesis. The author shows that the asymptotic distribution theory used for testing in presence of such a problem appears to work also for MS models, even though its validity can be questioned because of identically zero scores under the null estimates. Assuming the validity of this distribution theory, he derives the asymptotic null distribution of the likelihood ratio (LR) test for various MS models. Monte Carlo experiments show that the LR asymptotic distributions approximate the empirical distributions very well. Copyright 1998 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.
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Bibliographic InfoArticle provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.
Volume (Year): 39 (1998)
Issue (Month): 3 (August)
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Other versions of this item:
- René Garcia, 1995. "Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models," CIRANO Working Papers 95s-07, CIRANO.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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