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Posterior Analysis Of Possibly Integrated Time Series With An Application To Real Gnp

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  • Schotman, P.
  • van Dijk, H. K.

Abstract

We consider Bayesian statistical inference for univariate time series models where one of the autoregressive roots is close to or equals unity. Classical sampling theory for this type of models is hampered by the vast differences between asymptotic approximations in the stationary case and under the unit root hypothesis. Because of this dichotomy one has to decide early on in an empirical study whether a given time series is stationary or not. The present paper shows that a Bayesian approach allows for a smooth continuous transition between stationary and integrated time series models. Empirical results are presented for time series of annual real per capita GNP for 16 OECD countries.

Suggested Citation

  • Schotman, P. & van Dijk, H. K., 1990. "Posterior Analysis Of Possibly Integrated Time Series With An Application To Real Gnp," Econometric Institute Archives 272482, Erasmus University Rotterdam.
    • Handle: RePEc:ags:eureia:272482
    DOI: 10.22004/ag.econ.272482
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    References listed on IDEAS

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    Cited by:

    1. Geweke, John, 1994. "Priors for Macroeconomic Time Series and Their Application," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 609-632, August.
    2. Márcio Alves Diniz & C.A.B.Pereira & J.M.Stern, 2008. "FBST for Unit Root Problems," Working Papers 08_11, Universidade de São Paulo, Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto.
    3. Mattias Villani, 2009. "Steady-state priors for vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 630-650.

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