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    On the robustness of mixture models in the presence of hidden Markov Regimes with covariate-dependent transition probabilities

    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)

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    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

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