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

Author

Listed:
  • Zacharias Psaradakis

    (Birkbeck, University of London)

  • Martin Sola

    (Universidad Torcuato di Tella, Argentina)

Abstract

This paper proposes a model which allows for discrete stochastic breaks in the time-varying transition probabilities of Markov-switching models with autoregressive dynamics. An extensive simulation study is undertaken to examine the properties of the maximum-likelihood estimator and related statistics, and to investigate the implications of misspecification due to unaccounted changes in the parameters of the Markov transition mechanism. An empirical application that examines the relationship between Argentinian sovereign bond spreads and output growth is also discussed.

Suggested Citation

  • Zacharias Psaradakis & Martin Sola, 2017. "Markov-Switching Models with State-Dependent Time-Varying Transition Probabilities," Birkbeck Working Papers in Economics and Finance 1702, Birkbeck, Department of Economics, Mathematics & Statistics.
    • Handle: RePEc:bbk:bbkefp:1702
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    File URL: https://eprints.bbk.ac.uk/id/eprint/19116
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    References listed on IDEAS

    as
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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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