IDEAS home Printed from https://ideas.repec.org/p/udt/wpecon/2023_01.html
   My bibliography  Save this paper

A Note on Quasi-Maximum-Likelihood Estimation in Hidden Markov Models with Covariate-Dependent Transition Probabilities

Author

Listed:
  • Demian Pouzo
  • Zacharias Psaradakis
  • Martín Sola

Abstract

We consider hidden Markov models with a discrete-valued regime sequence whose transition probabilities are covariate-dependent. We show that consistent estimation of the parameters of the conditional distribution of the observable variables is possible via quasi-maximum-likelihood based on a (misspecified) mixture model without Markov dependence. Some related numerical results are also discussed.

Suggested Citation

  • Demian Pouzo & Zacharias Psaradakis & Martín Sola, 2023. "A Note on Quasi-Maximum-Likelihood Estimation in Hidden Markov Models with Covariate-Dependent Transition Probabilities," Department of Economics Working Papers 2023_01, Universidad Torcuato Di Tella.
    • Handle: RePEc:udt:wpecon:2023_01
    as

    Download full text from publisher

    File URL: https://www.utdt.edu/download.php?fname=_168149387494391800.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Levine, David, 1983. "A remark on serial correlation in maximum likelihood," Journal of Econometrics, Elsevier, vol. 23(3), pages 337-342, December.
    2. Andrew V. Carter & Douglas G. Steigerwald, 2012. "Testing for Regime Switching: A Comment," Econometrica, Econometric Society, vol. 80(4), pages 1809-1812, July.
    3. Engel, Charles & Hakkio, Craig S, 1996. "The Distribution of Exchange Rates in the EMS," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 1(1), pages 55-67, January.
    4. Tobias Rydén & Timo Teräsvirta & Stefan Åsbrink, 1998. "Stylized facts of daily return series and the hidden Markov model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 217-244.
    5. Engel, Charles & Hamilton, James D, 1990. "Long Swings in the Dollar: Are They in the Data and Do Markets Know It?," American Economic Review, American Economic Association, vol. 80(4), pages 689-713, September.
    6. Bates, Charles & White, Halbert, 1985. "A Unified Theory of Consistent Estimation for Parametric Models," Econometric Theory, Cambridge University Press, vol. 1(2), pages 151-178, August.
    7. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2022. "Maximum Likelihood Estimation in Markov Regime‐Switching Models With Covariate‐Dependent Transition Probabilities," Econometrica, Econometric Society, vol. 90(4), pages 1681-1710, July.
    8. Jin Seo Cho & Halbert White, 2007. "Testing for Regime Switching," Econometrica, Econometric Society, vol. 75(6), pages 1671-1720, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2022. "Maximum Likelihood Estimation in Markov Regime‐Switching Models With Covariate‐Dependent Transition Probabilities," Econometrica, Econometric Society, vol. 90(4), pages 1681-1710, July.
    2. 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.
    3. Andrew Ang & Allan Timmermann, 2012. "Regime Changes and Financial Markets," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 313-337, October.
    4. Clarida, Richard H. & Sarno, Lucio & Taylor, Mark P. & Valente, Giorgio, 2003. "The out-of-sample success of term structure models as exchange rate predictors: a step beyond," Journal of International Economics, Elsevier, vol. 60(1), pages 61-83, May.
    5. 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.
    6. Cheung, Yin-Wong & Erlandsson, Ulf G., 2005. "Exchange Rates and Markov Switching Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 314-320, July.
    7. Sarno, Lucio & Valente, Giorgio, 2005. "Empirical exchange rate models and currency risk: some evidence from density forecasts," Journal of International Money and Finance, Elsevier, vol. 24(2), pages 363-385, March.
    8. Gianna Boero & Emanuela Marrocu, 2005. "Evaluating non-linear models on point and interval forecasts: an application with exchange rates," BNL Quarterly Review, Banca Nazionale del Lavoro, vol. 58(232), pages 91-120.
    9. Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2020. "Markov-Switching Three-Pass Regression Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 285-302, April.
    10. Terra, Cristina & Valladares, Frederico, 2010. "Real exchange rate misalignments," International Review of Economics & Finance, Elsevier, vol. 19(1), pages 119-144, January.
    11. Carter Andrew V. & Steigerwald Douglas G., 2013. "Markov Regime-Switching Tests: Asymptotic Critical Values," Journal of Econometric Methods, De Gruyter, vol. 2(1), pages 25-34, July.
    12. 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.
    13. Polbin, Andrey & Shumilov, Andrei & Bedin, Andrei & Kulikov, Alexander, 2019. "Modeling real exchange rate of the Russian ruble using Markov regime switching approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 32-50.
    14. Huang, Yu-Lieh, 2012. "Measuring business cycles: A temporal disaggregation model with regime switching," Economic Modelling, Elsevier, vol. 29(2), pages 283-290.
    15. Boris Blagov, 2018. "Financial crises and time-varying risk premia in a small open economy: a Markov-switching DSGE model for Estonia," Empirical Economics, Springer, vol. 54(3), pages 1017-1060, May.
    16. Chevallier, Julien, 2011. "Evaluating the carbon-macroeconomy relationship: Evidence from threshold vector error-correction and Markov-switching VAR models," Economic Modelling, Elsevier, vol. 28(6), pages 2634-2656.
    17. Candelon, Bertrand & Metiu, Norbert & Straetmans, Stefan, 2013. "Disentangling economic recessions and depressions," Discussion Papers 43/2013, Deutsche Bundesbank.
    18. Lucio Sarno, 2003. "Nonlinear Exchange Rate Models: A Selective Overview," Rivista di Politica Economica, SIPI Spa, vol. 93(4), pages 3-46, July-Augu.
    19. Lucio Sarno & Giorgio Valente & Mark E. Wohar, 2004. "Monetary Fundamentals and Exchange Rate Dynamics under Different Nominal Regimes," Economic Inquiry, Western Economic Association International, vol. 42(2), pages 179-193, April.
    20. Polbin, Andrey & Shumilov, Andrei & Bedin, Andrey & Kulikov, Alexander, 2019. "Модель Реального Обменного Курса Рубля С Марковскими Переключениями Режимов [Modeling real exchange rate of the Russian ruble using Markov regime-switching approach]," MPRA Paper 93310, University Library of Munich, Germany.

    More about this item

    Keywords

    Consistency; covariate-dependent transition probabilities; hidden Markov model; mixture model; quasi-maximum-likelihood; misspecified model.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:udt:wpecon:2023_01. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: María Cecilia Lafuente (email available below). General contact details of provider: https://edirc.repec.org/data/deutdar.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.