A Bayesian Approach to Testing for Markov-Switching in Univariate and Dynamic Factor Models.
Though Hamilton's (1989) Markov-switching model has been widely estimated in various contexts, formal testing for Markov-switching is not straightforward. Univariate tests in the classical framework by Hansen (1992) and Garcia (1998) do not reject the linear model for GDP. We present Bayesian tests for Markov-switching in both univariate and multivariate settings based on sensitivity of the posterior probability to the prior. We find that evidence for Markov-switching, and thus the business cycle asymmetry, is stronger in a switching version of the dynamic factor model of Stock and Watson (1991) than it is for GDP by itself.
Year of publication: |
2001
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Authors: | Kim, Chang-Jin ; Nelson, Charles R |
Published in: |
International Economic Review. - Department of Economics. - Vol. 42.2001, 4, p. 989-1013
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Publisher: |
Department of Economics |
Saved in:
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