Arbeitspapier

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

In this paper, we make use of state space models toinvestigate the presence of stochastic trends in economic time series. Amodel is specified where such a trend can enter either in the autoregressiverepresentation or in a separate state equation. Tests based on the formerare analogous to Dickey-Fuller tests of unit roots, while the latter areanalogous to KPSS tests of trend-stationarity. We use Bayesian methods tosurvey the properties of the likelihood function in such models and tocalculate posterior odds ratios comparing models with and without stochastictrends. We extend these ideas to the problem of testing for integration atseasonal frequencies and show how our techniques can be used to carry outBayesian variants of either the HEGY or Canova-Hansen test. Stochasticintegration rules, based on Markov Chain Monte Carlo, as well asdeterministic integration rules are used. Strengths and weaknesses of eachapproach are indicated.

Sprache
Englisch

Erschienen in
Series: Tinbergen Institute Discussion Paper ; No. 99-072/4

Klassifikation
Wirtschaft
Thema
State space models
Bayes Factor
Gibbs sampler
unit root
seasonality
Zeitreihenanalyse
Schätztheorie
Theorie
Saisonbereinigung

Ereignis
Geistige Schöpfung
(wer)
Koop, Gary
van Dijk, Herman K.
Ereignis
Veröffentlichung
(wer)
Tinbergen Institute
(wo)
Amsterdam and Rotterdam
(wann)
1999

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Koop, Gary
  • van Dijk, Herman K.
  • Tinbergen Institute

Entstanden

  • 1999

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