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Maximum Likelihood Estimation in Markov Regime-Switching Models with Covariate-Dependent Transition Probabilities

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  • Demian Pouzo
  • Zacharias Psaradakis
  • Martín Sola

Abstract

This paper considers maximum likelihood (ML) estimation in a large class of models with hidden Markov regimes. We investigate consistency of the ML estimator and local asymptotic normality for the models under general conditions which allow for autoregressive dynamics in the observable process, Markov regime sequences with covariate-dependent transition matrices, and possible model misspecification. A Monte Carlo study examines the finite-sample properties of the ML estimator in correctly specified and misspecified models. An empirical application is also discussed.

Suggested Citation

  • Demian Pouzo & Zacharias Psaradakis & Martín Sola, 2021. "Maximum Likelihood Estimation in Markov Regime-Switching Models with Covariate-Dependent Transition Probabilities," Department of Economics Working Papers 2021_07, Universidad Torcuato Di Tella.
    • Handle: RePEc:udt:wpecon:2021_07
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    Cited by:

    1. Zacharias Psaradakis & Martin Sola & Francisco Rapetti & Patricio Yunis, 2024. "The Role of Consumer Sentiment in the Stock Market: A Multivariate Dynamic Mixture Model with Threshold Effects," Department of Economics Working Papers 2024_02, Universidad Torcuato Di Tella.
    2. 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.
    3. 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.
    4. Hiroyuki Okawa, 2023. "Markov-Regime Switches in Oil Markets: The Fear Factor Dynamics," JRFM, MDPI, vol. 16(2), pages 1-20, January.
    5. Chaojun Li & Yan Liu, 2020. "Asymptotic Properties of the Maximum Likelihood Estimator in Regime-Switching Models with Time-Varying Transition Probabilities," Papers 2010.04930, arXiv.org, revised Dec 2021.
    6. Jochmans, Koen & Higgins, Ayden, 2022. "Learning Markov Processes with Latent Variables From Longitudinal Data," TSE Working Papers 22-1366, Toulouse School of Economics (TSE).
    7. Demian Pouzo & Zacharias Psaradakis & Martín Sola, 2024. "On the Robustness of Mixture Models in the Presence of Hidden Markov Regimes with Covariate-Dependent Transition Probabilities," Department of Economics Working Papers 2024_04, Universidad Torcuato Di Tella.

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    More about this item

    Keywords

    Autoregressive model; consistency; covariatedependent transition probabilities; hidden Markov model; Markov-switching model; maximum likelihood; local asymptotic normality; misspecified models;
    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

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