Bayesian Analysis of Long Memory and Persistence using ARFIMA Models

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Published in RePEc

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 AGAINST ARIMA
PERSISTENCE USING
BAYESIAN ANALYSIS
ARFIMA MODELS
UNCERTAINTY
LONG MEMORY
IMPULSE

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Version 1, RePEc
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