Exploring health outcomes by stochastic multi-objective acceptability analysis: an application to Italian regions
Raffaele Lagravinese,
Paolo Liberati and
Giuliano Resce ()
No 1703, Working Papers. Collection B: Regional and sectoral economics from Universidade de Vigo, GEN - Governance and Economics research Network
Abstract:
This paper introduces the Stochastic Multi-Objective Acceptability Analysis (SMAA) in order to investigate the evolution of mortality rates in the Italian regions over the period 1990-2013. We propose to explore the overall outcome of health care by a Composite Index (CI) of mortality based on the combination of standardized mortality rates for seventeen different diseases. From a methodological standpoint, we propose to overcome the arbitrary of the weighting process, by using the SMAA, which is a methodology that allows to rank regions considering the whole set of possible vectors of weights. Moreover, we explore the spatial segregation in health using the multidimensional generalization of the Gini index, and introducing the multidimensional generalization of ANOGI. The unprecedented use of SMAA in health sector allows to explore regional multidimensional paths beyond the order of importance given to the single dimensions. Our analysis shows that in the 24 years considered there has been no convergence path in terms of health care outcome in Italy, neither between nor within regions.
Keywords: Stochastic Multi-Objective Acceptability Analysis; Composite Indicators; Health; Spatial Inequality; ANOGI (search for similar items in EconPapers)
JEL-codes: C44 H75 I14 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2017-07
New Economics Papers: this item is included in nep-eur, nep-geo, nep-hea, nep-ore and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
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http://infogen.webs.uvigo.es/WPB/WP1703.pdf First version, 2017 (application/pdf)
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Persistent link: https://EconPapers.repec.org/RePEc:gov:wpregi:1703
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