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Bayesian Analysis of Long Memory and Persistence using ARFIMA Models

Gary Koop (), Eduardo Ley, Jacek Osiewalski and Mark Steel ()

Econometrics from University Library of Munich, Germany

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: C11 C22 (search for similar items in EconPapers)
Date: 1995-05-24, Revised 2004-06-22
Note: PDF replaced to display the graphics correctly. Published in The Journal of Econometrics, 76:1-2 (January), pages 149-170, 1997.
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Related works:
Journal Article: Bayesian analysis of long memory and persistence using ARFIMA models (1997) Downloads
Working Paper: Bayesian analysis of long memory and persistence using ARFIMA models (1997) Downloads
Working Paper: Bayesian Analysis of Long Memory and Persistence using ARFIMA Models (1995) Downloads
Working Paper: Bayesian Analysis of Long Memory and Persistence using ARFIMA Models (1995) Downloads
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