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Markov-Switching Models with State-Dependent Time-Varying Transition Probabilities

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  • Psaradakis, Zacharias
  • Sola, Martin

Abstract

Markov-switching models with covariate-dependent transition functions that are subject to exogenous discrete stochastic changes are considered. These changes are associated with simultaneous stochastic changes in the covariance structure of the observable variables. Simulation experiments are carried out to assess the quality of large-sample approximations to the distributions of the maximum-likelihood estimator and of related statistics in such a model, and to examine the implications of misspecification due to unaccounted breaks in the transition mechanism. The practical use of the model is illustrated by analyzing the relationship between Argentinian sovereign bond spreads and output growth.

Suggested Citation

  • Psaradakis, Zacharias & Sola, Martin, 2024. "Markov-Switching Models with State-Dependent Time-Varying Transition Probabilities," Econometrics and Statistics, Elsevier, vol. 29(C), pages 49-63.
    • Handle: RePEc:eee:ecosta:v:29:y:2024:i:c:p:49-63
    DOI: 10.1016/j.ecosta.2021.04.007
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    More about this item

    Keywords

    Markov-switching models; Maximum likelihood; Monte Carlo experiments; Time-varying transition probabilities;
    All these keywords.

    JEL classification:

    • 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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