A Bayesian approach to testing for Markov-switching in univariate and dynamic factor models

Chang-Jin Kim, Charles R. Nelson

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Though Hamilton's (1989) Markov-switching model has been widely estimated in various contexts, formal testing for Markov-switching is not straight-forward. 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.

Original languageEnglish
Pages (from-to)989-1013
Number of pages25
JournalInternational Economic Review
Volume42
Issue number4
Publication statusPublished - 2001 Nov 1

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Markov switching
Dynamic factor model
Bayesian approach
Testing
Markov switching model
Business cycle asymmetry
Posterior probability

ASJC Scopus subject areas

  • Economics and Econometrics

Cite this

A Bayesian approach to testing for Markov-switching in univariate and dynamic factor models. / Kim, Chang-Jin; Nelson, Charles R.

In: International Economic Review, Vol. 42, No. 4, 01.11.2001, p. 989-1013.

Research output: Contribution to journalArticle

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