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Bayesian Inference for a Threshold Autoregression with a Unit Root

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  • Penelope Smith

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

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    Abstract

    A Bayesian approach to distinguishing between nonlinear and unit root behavior offers several practical advantages over equivalent frequentist procedures. Foremost among these advantages is the simplicity of the test. This paper compares the small sample power and size properties of a joint Bayesian test for a unit root and a threshold effect with Caner and Hansen's (2001) frequentist strategy. The results from Monte Carlo experiments indicate that the simpler Bayesian test performs at least as well as Caner and Hansen's procedure.

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    File URL: http://www.melbourneinstitute.com/downloads/working_paper_series/wp2006n20.pdf
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    Bibliographic Info

    Paper provided by Melbourne Institute of Applied Economic and Social Research, The University of Melbourne in its series Melbourne Institute Working Paper Series with number wp2006n20.

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    Length: 40 pages
    Date of creation: Oct 2006
    Date of revision:
    Handle: RePEc:iae:iaewps:wp2006n20

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    Postal: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Victoria 3010 Australia
    Phone: +61 3 8344 2100
    Fax: +61 3 8344 2111
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    Web page: http://www.melbourneinstitute.com/
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    1. Donald W.K. Andrews, 1992. "The Large Sample Correspondence Between Classical Hypothesis Tests and Bayesian Posterior Odds Tests," Cowles Foundation Discussion Papers 1035, Cowles Foundation for Research in Economics, Yale University.
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    3. Erdem Basci & Mehmet Caner, 2005. "Are Real Exchange Rates Nonlinear or Nonstationary? Evidence from a new Threshold Unit Root Test," International Finance 0512001, EconWPA.
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    7. Donald W.K. Andrews & Werner Ploberger, 1992. "Optimal Tests When a Nuisance Parameter Is Present Only Under the Alternative," Cowles Foundation Discussion Papers 1015, Cowles Foundation for Research in Economics, Yale University.
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    21. Jae-Young Kim, 1998. "Large Sample Properties of Posterior Densities, Bayesian Information Criterion and the Likelihood Principle in Nonstationary Time Series Models," Econometrica, Econometric Society, vol. 66(2), pages 359-380, March.
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