Testing for Integration using Evolving Trend and Seasonals Models: A Bayesian Approach

Gary Koop, Herman van Dijk and Henk Hoek
Additional contact information
Henk Hoek: Erasmus University Rotterdam

No 97-078/4, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: This discussion paper resulted in a publication IN the 'Journal of Econometrics' , 2000, 97(2), 261-291.

In this paper, we make use of state space models to investigate the presence of stochastic trends in economic time series. A model is specified where such a trend can enter either in the autoregressive representation or in a separate state equation. Tests based on the former are analogous to Dickey-Fullertests of unit roots, while the latter are analogous to KPSS tests of trend-stationarity. We use Bayesian methods to survey the properties of the likelihood function in such models and to calculate posterior odds ratios comparing models with and without stochastic trends. In addition, we extend these ideas to the problem of testing for integration at seasonal frequencies and show how techniques can be used to carry out Bayesian variants of HEGY test or the Canova-Hansen test.

Keywords: State space models; Bayes Factor; Gibbs sampler; unit root; seasonality (search for similar items in EconPapers)
JEL-codes: C11 C12 C32 C52 (search for similar items in EconPapers)
Date: 1997-08-08
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Testing for integration using evolving trend and seasonals models: A Bayesian approach (2000)
Working Paper: Testing for integration using evolving trend and seasonal models: A Bayesian approach (1999)
Working Paper: Testing for Integration using Evolving Trend and Seasonals Models: A Bayesian Approach (1999)
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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:19970078

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