Pouzo, D. and Psaradakis, Zacharias and Sola, M. (2025) On the robustness of mixture models in the presence of hidden Markov Regimes with covariate-dependent transition probabilities. Econometric Theory , ISSN 0266-4666. (In Press)
![]() |
Text
mixture_ET_final.pdf - Author's Accepted Manuscript Available under License Creative Commons Attribution. Download (385kB) |
Abstract
This paper studies the robustness of quasi-maximum-likelihood estimation in hidden Markov models when the regime-switching structure is misspecified. Specifically, we examine the case where the data-generating process features a hidden Markov regime sequence with covariate-dependent transition probabilities, but estimation proceeds under a simplified mixture model that assumes regimes are independent and identically distributed. We show that the parameters governing the conditional distribution of the observables can still be consistently estimated under this misspecification, provided certain regularity conditions hold. Our results highlight a practical benefit of using computationally simpler mixture models in settings where regime dependence is complex or difficult to model directly.
Metadata
Item Type: | Article |
---|---|
Keyword(s) / Subject(s): | Consistency, covariate-dependent transition probabilities, identifiability, hidden Markov model, mixture model, quasi-maximum-likelihood, misspecified model |
School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
Depositing User: | Zacharias Psaradakis |
Date Deposited: | 06 May 2025 07:54 |
Last Modified: | 24 Sep 2025 08:02 |
URI: | https://eprints.bbk.ac.uk/id/eprint/55525 |
Statistics
Additional statistics are available via IRStats2.