Bayesian Analysis of Long Memory and Persistence using ARFIMA Models

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.

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Year of publication:	1995-05-24
Authors:	Koop, Gary ; Ley, Eduardo ; Osiewalski, Jacek ; Steel, Mark F.J.
Institutions:	EconWPA
Subject:	Fractionally Integrated Models \| Impulse Responses \| Time Series \| Trend Stationarity \| Unit Root

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Extent:	application/pdf
Series:	Econometrics.
Type of publication:	Book / Working Paper
Notes:	PDF replaced to display the graphics correctly. Published in The Journal of Econometrics, 76:1-2 (January), pages 149-170, 1997.
Classification:	C11 - Bayesian Analysis ; C22 - Time-Series Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005062558