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

Zacharias Psaradakis and Martin Sola

Econometrics and Statistics, 2024, vol. 29, issue C, 49-63

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.

Keywords: Markov-switching models; Maximum likelihood; Monte Carlo experiments; Time-varying transition probabilities (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S2452306221000575
Full text for ScienceDirect subscribers only. Contains open access articles

Related works:
Working Paper: Markov-Switching Models with State-Dependent Time-Varying Transition Probabilities (2017)
Working Paper: Markov-Switching Models with State-Dependent Time-Varying Transition Probabilities (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:29:y:2024:i:c:p:49-63

DOI: 10.1016/j.ecosta.2021.04.007

Access Statistics for this article

Econometrics and Statistics is currently edited by E.J. Kontoghiorghes, H. Van Dijk and A.M. Colubi

More articles in Econometrics and Statistics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().