The dynamic interdependence in the demand of primary and emergency secondary care

A hidden Markov approach

Bibliographic Data

ID21653611
AuthorsMauro Laudicella (0000-0001-5322-4452, DaCHE‐Danish Center for Health Economics University of Southern Denmark Odense Denmark), Paolo Li Donni (0000-0001-9074-5089, DaCHE‐Danish Center for Health Economics University of Southern Denmark Odense Denmark, corresponding author)
Year2022
Volume37
Issue3
Pages521-536
Publication date2022-04-01
Open AccessYes
TypeARTICLE
VenueJournal of Applied Econometrics (JOURNAL)
Journal identifiersISSN: 1099-1255 • E-ISSN: 0883-7252
PublisherWiley (PUBLISHER • GB)
DOI10.1002/jae.2882
OpenAlexW3162905475
LanguageEN
Citations received1
References cited35

This paper develops an extension of the class of finite mixture models for longitudinal count data to the bivariate case by using a hidden Markov chain approach. The model allows for disentangling unobservable time‐varying heterogeneity from the dynamic effect of utilisation of primary and secondary care and measuring their potential substitution effect. Three points of supports adequately describe the distribution of the latent states suggesting the existence of three profiles of low, medium and high users who shows persistency in their behaviour, but not permanence as some switch to their neighbour's profile

Bivariate analysis · Econometrics · Economics · Hidden Markov model · Markov chain · Markov model · Statistics · Unobservable · Computer Science · Global Health Care Issues · Mathematics · Urban, Neighborhood, and Segregation Studies · Artificial Intelligence

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Open DOIOpen Access