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A Goodness Of Fit Test For Ergodic Markov Processes

Author

Listed:
  • 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.

Suggested Citation

  • Vance Martin & Yoshihiko Nishiyama & John Stachurski, 2011. "A Goodness Of Fit Test For Ergodic Markov Processes," KIER Working Papers 787, Kyoto University, Institute of Economic Research.
    • Handle: RePEc:kyo:wpaper:787
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    References listed on IDEAS

    as
    1. John Stachurski & Vance Martin, 2008. "Computing the Distributions of Economic Models via Simulation," Econometrica, Econometric Society, vol. 76(2), pages 443-450, March.
    2. 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.
    3. Nishimura, Kazuo & Stachurski, John, 2005. "Stability of stochastic optimal growth models: a new approach," Journal of Economic Theory, Elsevier, vol. 122(1), pages 100-118, May.
    Full references (including those not matched with items on IDEAS)

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    Keywords

    Specification test; goodness of fit; Markov processes.;

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