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Bayesian Analysis of Long Memory and Persistence using ARFIMA Models

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  • Gary Koop

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.

Suggested Citation

  • Gary Koop, 1995. "Bayesian Analysis of Long Memory and Persistence using ARFIMA Models," Working Papers gkoop-95-01, University of Toronto, Department of Economics.
    • Handle: RePEc:tor:tecipa:gkoop-95-01
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    More about this item

    Keywords

    Fractionally Integrated Models; Impulse Responses; Time Series; Trend Stationarity; Unit Root;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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