Bayes Estimates of Markov Trends in Possibly Cointegrated Series: An Application to US Consumption and Income
AbstractStylized facts show that the average growth rates of US per capitaconsumption and income differ in recession and expansion periods.Since a linear combination of such series does not have to be a constant meanprocess, standard cointegration analysis between the variables, toexamine the permanent income hypothesis, may not be valid. To model thechanging growth rates in both series, we introduce a multivariate Markov trendmodel, which allows for different growth rates in consumption and incomeduring expansions and recessions. The deviations from the multivariateMarkov trend are modelled by a vector autoregressive model. Bayes estimates ofthis model are obtained using Markov chain Monte Carlo methods. The empiricalresults suggest that there exist a cointegration relation between US percapita disposable income and consumption, after correction for amultivariate Markov trend.
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Bibliographic InfoPaper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 99-024/4.
Date of creation: 31 Mar 1999
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multivariate Markov trend; cointegration; MCMC; permanent income hypothesis;
Other versions of this item:
- Paap, Richard & van Dijk, Herman K, 2003. "Bayes Estimates of Markov Trends in Possibly Cointegrated Series: An Application to U.S. Consumption and Income," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(4), pages 547-63, October.
- Paap, R. & Dijk, H.K. van, 2002. "Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income," Econometric Institute Report EI 2002-42, Erasmus University Rotterdam, Econometric Institute.
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