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Optimal Test for Markov Switching Parameters

Author

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  • Marine Carrasco
  • Liang Hu
  • Werner Ploberger

Abstract

This paper proposes a class of optimal tests for the constancy of parameters in random coefficients models. Our testing procedure covers the class of Hamilton's models, where the parameters vary according to an unobservable Markov chain, but also applies to nonlinear models where the random coefficients need not be Markov. We show that the contiguous alternatives converge to the null hypothesis at a rate that is slower than the standard rate. Therefore, standard approaches do not apply. We use Bartlett‐type identities for the construction of the test statistics. This has several desirable properties. First, it only requires estimating the model under the null hypothesis where the parameters are constant. Second, the proposed test is asymptotically optimal in the sense that it maximizes a weighted power function. We derive the asymptotic distribution of our test under the null and local alternatives. Asymptotically valid bootstrap critical values are also proposed.

Suggested Citation

  • Marine Carrasco & Liang Hu & Werner Ploberger, 2014. "Optimal Test for Markov Switching Parameters," Econometrica, Econometric Society, vol. 82(2), pages 765-784, March.
  • Handle: RePEc:wly:emetrp:v:82:y:2014:i:2:p:765-784
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    File URL: http://hdl.handle.net/10.1111/ecta.2014.82.issue-2.x
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    Cited by:

    1. Andreou, Elena & Werker, Bas J.M., 2015. "Residual-based rank specification tests for AR–GARCH type models," Journal of Econometrics, Elsevier, vol. 185(2), pages 305-331.
    2. Houda Rharrabti Zaid, 2015. "Transmission du stress financier de la zone euro aux Pays de l’Europe Centrale et Orientale," EconomiX Working Papers 2015-37, University of Paris Nanterre, EconomiX.
    3. repec:eee:ecmode:v:68:y:2018:i:c:p:1-10 is not listed on IDEAS
    4. Luke Hartigan, 2015. "Changes in the Factor Structure of the U.S. Economy: Permanent Breaks or Business Cycle Regimes?," Discussion Papers 2015-17, School of Economics, The University of New South Wales.
    5. Timo Teräsvirta, 2017. "Nonlinear models in macroeconometrics," CREATES Research Papers 2017-32, Department of Economics and Business Economics, Aarhus University.
    6. Maddalena Cavicchioli, 2015. "Likelihood Ratio Test and Information Criteria for Markov Switching Var Models: An Application to the Italian Macroeconomy," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 1(3), pages 315-332, November.
    7. Sergei Koulayev & Marc Rysman & Scott Schuh & Joanna Stavins, 2016. "Explaining adoption and use of payment instruments by US consumers," RAND Journal of Economics, RAND Corporation, vol. 47(2), pages 293-325, May.
    8. Jean-Marie Dufour & Richard Luger, 2017. "Identification-robust moment-based tests for Markov switching in autoregressive models," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 713-727, October.
    9. Anwar Khayat, 2015. "Negative Policy Rates, Banking Flows and Exchange Rates," Working Papers halshs-01203609, HAL.
    10. Lajos Horvath & Lorenzo Trapani, "undated". "Testing for randomness in a random coefficient autoregression model," Discussion Papers 18/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    11. Anwar Khayat, 2015. "Negative Policy Rates, Banking Flows and Exchange Rates," AMSE Working Papers 1538, Aix-Marseille School of Economics, Marseille, France, revised Sep 2015.
    12. repec:eee:macchp:v2-163 is not listed on IDEAS
    13. repec:eee:intfor:v:34:y:2018:i:4:p:622-635 is not listed on IDEAS
    14. Thomas Walther & Lanouar Charfeddine & Tony Klein, 2018. "Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?," Working Papers on Finance 1816, University of St. Gallen, School of Finance.

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