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Flat Priors vs. Ignorance Priors in the Analysis of the AR(1) Model

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  • Kim, In-Moo
  • Maddala, G S

Abstract

This paper compares, by a Monte-Carlo study based on an AR(1) model, the performance of the flat prior and the ignorance prior suggested by Phillips. It argues that the ignorance prior gives heavy weight to values of the autoregressive parameter [rho] higher than 1, and hence distorts the sample evidence as summarized in the likelihood function. It yields bimodal posterior distributions, with the second mode at [rho] higher than 1, even when the true value of [rho] is substantially less than 1. Copyright 1991 by John Wiley & Sons, Ltd.

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  • Kim, In-Moo & Maddala, G S, 1991. "Flat Priors vs. Ignorance Priors in the Analysis of the AR(1) Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 375-380, Oct.-Dec..
    • Handle: RePEc:jae:japmet:v:6:y:1991:i:4:p:375-80
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    Cited by:

    1. Magris Martin & Iosifidis Alexandros, 2021. "Approximate Bayes factors for unit root testing," Papers 2102.10048, arXiv.org, revised Feb 2021.

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