Pouzo, D. and Psaradakis, Zacharias and Sola, M. (2022) Maximum Likelihood Estimation in Markov Regime-Switching Models with Covariate-Dependent Transition Probabilities. Econometrica 90 (4), pp. 1681-1710. ISSN 0012-9682.
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Abstract
This paper considers maximum likelihood (ML) estimation in a large class of models with hidden Markov regimes. We investigate consistency of the ML estimator and local asymptotic normality for the models under general conditions which allow for autoregressive dynamics in the observable process, Markov regime sequences with covariate-dependent transition matrices, and possible model misspecification. A Monte Carlo study examines the finite-sample properties of the ML estimator in correctly specified and misspecified models. An empirical application is also discussed.
Metadata
| Item Type: | Article |
|---|---|
| Keyword(s) / Subject(s): | Autoregressive model, consistency, covariate-dependent transition probabilities, covariance matrix estimation, hidden Markov model, Markov-switching model, maximum likelihood, local asymptotic normality, misspecified models |
| School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
| Depositing User: | Zacharias Psaradakis |
| Date Deposited: | 10 Mar 2022 13:39 |
| Last Modified: | 02 Aug 2023 18:15 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/47550 |
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