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

• 成果类型: Article
• 署名作者: Kim, CJ; Nelson, CR
• 署名单位: Korea University; University of Washington; University of Washington Seattle
• 刊物名称: INTERNATIONAL ECONOMIC REVIEW
• ISSN/ISSBN: 0020-6598
• DOI: 10.1111/1468-2354.00143
• 发表日期: 2001
• 页码: 989-1013
• 关键词: time-series subject; BUSINESS; likelihood; inference

摘要

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.