A Goodness Of Fit Test For Ergodic Markov Processes
AbstractWe 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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Bibliographic InfoPaper provided by Kyoto University, Institute of Economic Research in its series KIER Working Papers with number 787.
Date of creation: Oct 2011
Date of revision:
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Postal: Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501
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More information through EDIRC
Specification test; goodness of fit; Markov processes.;
Other versions of this item:
- Vance Martin & Yoshihiko Nishiyama & John Stachurski, 2011. "A Goodness of Fit Test for Ergodic Markov Processes," ANU Working Papers in Economics and Econometrics 2011-557, Australian National University, College of Business and Economics, School of Economics.
- NEP-ALL-2011-10-22 (All new papers)
- NEP-CIS-2011-10-22 (Confederation of Independent States)
- NEP-ECM-2011-10-22 (Econometrics)
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- John Stachurski, 2006.
"Computing the Distributions of Economic Models Via Simulation,"
KIER Working Papers
615, Kyoto University, Institute of Economic Research.
- John Stachurski & Vance Martin, 2008. "Computing the Distributions of Economic Models via Simulation," Econometrica, Econometric Society, vol. 76(2), pages 443-450, 03.
- John Stachurski, 2005. "Computing the Distributions of Economic Models Via Simulation," Department of Economics - Working Papers Series 949, The University of Melbourne.
- John Stachurski & University of Melbourne, 2006. "Computing the Distributions of Economic Models via Simulation," Computing in Economics and Finance 2006 185, Society for Computational Economics.
- 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.
- 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.
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