6533b851fe1ef96bd12a8f03
RESEARCH PRODUCT
The dynamic interdependence in the demand of primary and emergency secondary care: A hidden Markov approach
Mauro LaudicellaPaolo Li DonniPaolo Li Donnisubject
Economics and Econometrics050208 financeComputer science05 social sciencesExtension (predicate logic)Bivariate analysis01 natural sciencesUnobservablePrimary and Secondary Care Latent Markov ModelSecondary careReduction (complexity)010104 statistics & probability0502 economics and businessEconometricsSubstitution effect0101 mathematics050207 economicsHidden Markov modelSocial Sciences (miscellaneous)Count dataPanel datadescription
This paper develops an extension of the class of finite mixture models for longitudinal count data to the bivariate case by using a trivariate reduction technique and 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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-01-01 | Journal of Applied Econometrics |