 Bayes Estimates of Markov Trends in Possibly Cointegrated Series: An Application to U.S. Consumption and IncomeRichard Paap and Herman van Dijk Journal of Business & Economic Statistics, 2003, vol. 21, issue 4, 547-63 Abstract: Stylized facts show that average growth rates of U.S. per capita consumption and income differ in recession and expansion periods. Because a linear combination of such series does not have to be a constant mean process, standard cointegration analysis between the variables to examine the permanent income hypothesis may not be valid. To model the changing growth rates in both series, we introduce a multivariate Markov trend model that accounts for different growth rates in consumption and income during expansions and recessions and across variables within both regimes. The deviations from the multivariate Markov trend are modeled by a vector autoregression (VAR) model. Bayes estimates of this model are obtained using Markov chain Monte Carlo methods. The empirical results suggest the existence of a cointegration relation between U.S. per capita disposable income and consumption, after correction for a multivariate Markov trend. This result is also obtained when per capita investment is added to the VAR. Date: 2003 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:21:y:2003:i:4:p:547-63 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano More articles in Journal of Business & Economic Statistics from American Statistical Association |
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