FAIRNESS OF NATIONAL HEALTH SERVICE IN ITALY: A BIVARIATE CORRELATED RANDOM EFFECTS MODEL
Antonello Maruotti ()
No 308, Working Papers from CREI Università degli Studi Roma Tre
In this paper we consider a possible way of measuring equity in health as the absence of systematic disparities in health (or in the major social determinants of health) between groups with different levels of underlying social advantage/disadvantage. Starting from the fairness approach developed by the World Health Organization, we propose to extend the analysis of fairness in nancing contribution through a generalized linear mixed models framework by introducing a bivariate correlated random effects model. We aim at analyzing the burden of health care payment on Italian households by modeling catastrophic payments and impoverishment due to health care expenditures. For this purpose, we describe a bivariate model for binary data, where association between the outcomes is modeled through outcome-speci c latent effects which are assumed to be correlated; we show how model parameters can be estimated in a nite mixture context. By using such model speci cation, the fairness of the Italian national health service is investigated.
Keywords: fairness; health care; random e ects models; binary data; non parametric maximum likelihood. (search for similar items in EconPapers)
Date: 2008, Revised 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://host.uniroma3.it/centri/crei/pubblicazioni/ ... 008/CREI_03_2008.pdf First version, 2008 (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:rcr:wpaper:03_08
Access Statistics for this paper
More papers in Working Papers from CREI Università degli Studi Roma Tre Contact information at EDIRC.
Bibliographic data for series maintained by Francesca Vaino ().