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

Chang Jin Kim, Charles R. Nelson

Research output: Contribution to journalArticlepeer-review

13 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
DOIs
Publication statusPublished - 2001 Nov

ASJC Scopus subject areas

  • Economics and Econometrics

Fingerprint

Dive into the research topics of 'A Bayesian approach to testing for Markov-switching in univariate and dynamic factor models'. Together they form a unique fingerprint.

Cite this