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Bayes Estimates of Markov Trends in possibly Cointegrated Series: An Application to US Consumption and Income

Author

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  • Richard Paap

    (RIBES)

  • Herman K. van Dijk

    (Econometric Institute, Erasmus University Rotterdam)

Abstract

This discussion paper resulted in an article in the Journal of Business & Economic Statistics (2003). Volume 21, pages 547-563. Stylized 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.

Suggested Citation

  • Richard Paap & Herman K. van Dijk, 1999. "Bayes Estimates of Markov Trends in possibly Cointegrated Series: An Application to US Consumption and Income," Tinbergen Institute Discussion Papers 99-024/4, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:19990024
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    Keywords

    multivariate Markov trend; cointegration; MCMC; permanent income hypothesis;
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