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On the Robustness of Mixture Models in the Presence of Hidden Markov Regimes with Covariate-Dependent Transition Probabilities

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  • Demian Pouzo
  • Zacharias Psaradakis
  • Martín Sola

Abstract

We consider general hidden Markov models that may include exogenous covariates and whose discrete-state-space regime sequence has transition probabilities that are functions of observable variables. We show that the parameters of the observation conditional distribution are consistently estimated by quasi-maximum-likelihood even if the Markov dependence of the hidden regime sequence is not taken into account. Some related numerical results are also discussed.

Suggested Citation

  • 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.
    • Handle: RePEc:udt:wpecon:2024_04
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    References listed on IDEAS

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    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:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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