Bayesian Analysis of Long Memory and Persistence using ARFIMA Models

Gary Koop

Working Papers from University of Toronto, Department of Economics

Abstract: This paper provides a Bayesian analysis of Autoregressive Fractionally Integrated Moving Average (ARFIMA) models. We discuss in detail inference on impulse responses, and show how Bayesian methods can be used to (i) test ARFIMA models against ARIMA alternatives, and (ii) take model uncertainty into account when making inferences on quantities of interest. Our methods are then used to investigate the persistence properties of real U.S. GNP.

Keywords: Fractionally Integrated Models; Impulse Responses; Time Series; Trend Stationarity; Unit Root (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Pages: 25 pages
Date: 1995-05-24
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Bayesian analysis of long memory and persistence using ARFIMA models (1997)
Working Paper: Bayesian analysis of long memory and persistence using ARFIMA models (1997)
Working Paper: Bayesian Analysis of Long Memory and Persistence using ARFIMA Models (1995)
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Persistent link: https://EconPapers.repec.org/RePEc:tor:tecipa:gkoop-95-01

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