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A New Bayesian Unit Root Test in Stochastic Volatility Models

  • Yong Li

    ()

    (Business School, Sun Yat-Sen University)

  • Jun Yu

    ()

    (School of Economics, Singapore Management University)

A new posterior odds analysis is proposed to test for a unit root in volatility dynamics in the context of stochastic volatility models. This analysis extends the Bayesian unit root test of So and Li (1999, Journal of Business Economic Statistics) in two important ways. First, a numerically more stable algorithm is introduced to compute the Bayes factor, taking into account the special structure of the competing models. Owing to its numerical stability, the algorithm overcomes the problem of diverged “size” in the marginal likelihood approach. Second, to improve the “power” of the unit root test, a mixed prior specification with random weights is employed. It is shown that the posterior odds ratio is the by-product of Bayesian estimation and can be easily computed by MCMC methods. A simulation study examines the “size” and “power” performances of the new method. An empirical study, based on time series data covering the subprime crisis, reveals some interesting results.

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Paper provided by Singapore Management University, School of Economics in its series Working Papers with number 21-2010.

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Length: 23 pages
Date of creation: Oct 2010
Date of revision: Oct 2010
Publication status: Published in SMU Economics and Statistics Working Paper Series
Handle: RePEc:siu:wpaper:21-2010
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  2. Francis W. Ahking, 2004. "The Power of the "Objective" Bayesian Unit-Root Test," Working papers 2004-14, University of Connecticut, Department of Economics.
  3. Andersen, Torben G. & Chung, Hyung-Jin & Sorensen, Bent E., 1999. "Efficient method of moments estimation of a stochastic volatility model: A Monte Carlo study," Journal of Econometrics, Elsevier, vol. 91(1), pages 61-87, July.
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  7. Perron, P. & Ng, S., 1994. "Useful Modifications to Some Unit Root Tests with Dependent Errors and Their Local Asymptotic Properties," Cahiers de recherche 9427, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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  12. Christopher A. Sims, 1988. "Bayesian skepticism on unit root econometrics," Discussion Paper / Institute for Empirical Macroeconomics 3, Federal Reserve Bank of Minneapolis.
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