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A Robust Bayesian Approach For Unit Root Testing

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  • Conigliani, Caterina
  • Spezzaferri, Fulvio

Abstract

In this paper we deal with the identification of an autoregressive model for an observed time series and the detection of a unit root in its characteristic polynomial. This is a big issue concerned with distinguishing stationary time series from time series for which differencing is required to induce stationarity. We consider a Bayesian approach, and particular attention is devoted to the problem of the sensitivity of the standard Bayesian analysis with respect to the choice of the prior distribution for the autoregressive coefficients.We thank three anonymous referees for their useful comments, which have improved the final version of the paper.

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  • Conigliani, Caterina & Spezzaferri, Fulvio, 2007. "A Robust Bayesian Approach For Unit Root Testing," Econometric Theory, Cambridge University Press, vol. 23(3), pages 440-463, June.
    • Handle: RePEc:cup:etheor:v:23:y:2007:i:03:p:440-463_07
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    Cited by:

    1. Márcio Alves Diniz & C.A.B.Pereira & J.M.Stern, 2008. "FBST for Unit Root Problems," Working Papers 08_11, Universidade de São Paulo, Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto.

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