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Bayesian long-run prediction in time series models

Gary Koop, Jacek Osiewalski and Mark Steel

UC3M Working papers. Economics from Universidad Carlos III de Madrid. Departamento de Economía

Abstract: This paper considers Bayesian long-run prediction in time series models. We allow time series to exhibit stationary or non-stationary behavior and show how differences between prior structures which have little effect on posterior inferences can have a large effect in a prediction exercise. In particular, the Jeffreys' prior given in Phillips (1991) is seen to prevent the existence of one-period ahead predictive moments. A Bayesian counterpart is provided to Sampson (1991) who takes parameter uncertainty into account in a classical framework. An empirical example illustrates our results.

Keywords: Unit; root; Parameter; uncertainty; Forecasting; Predictive; moments (search for similar items in EconPapers)
Date: 1992-03
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Citations: View citations in EconPapers (1)

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Journal Article: Bayesian long-run prediction in time series models (1995) Downloads
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