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A Goodness Of Fit Test For Ergodic Markov Processes

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Author Info

  • Vance Martin

    (Department of Economics, The University of Melbourne)

  • Yoshihiko Nishiyama

    (Institute of Economic Research, Kyoto University)

  • John Stachurski

    (Research School of Economics, Australian National University)

Abstract

We introduce a goodness of fit test for ergodic Markov processes. Our test compares the data against the set of stationary densities implied by the class of models specified in the null hypothesis, and rejects if no model in the class yields a stationary density that matches with the data. No alternative needs to be specified in order to implement the test. Although our test compares densities it involves no smoothing parameters, and is powerful against 1√n local alternatives.

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File URL: http://www.kier.kyoto-u.ac.jp/DP/DP787.pdf
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Bibliographic Info

Paper provided by Kyoto University, Institute of Economic Research in its series KIER Working Papers with number 787.

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Date of creation: Oct 2011
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Handle: RePEc:kyo:wpaper:787

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Keywords: Specification test; goodness of fit; Markov processes.;

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  1. John Stachurski, 2006. "Computing the Distributions of Economic Models Via Simulation," KIER Working Papers, Kyoto University, Institute of Economic Research 615, Kyoto University, Institute of Economic Research.
  2. Nishimura, Kazuo & Stachurski, John, 2005. "Stability of stochastic optimal growth models: a new approach," Journal of Economic Theory, Elsevier, Elsevier, vol. 122(1), pages 100-118, May.
  3. Chen, Song Xi & Gao, Jiti & Tang, Chenghong, 2005. "A test for model specification of diffusion processes," MPRA Paper 11976, University Library of Munich, Germany, revised Feb 2007.
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