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dc.contributor.authorCarmignani, Fabrizio
dc.contributor.authorShankar, Sriram
dc.contributor.authorTan, Eng Joo
dc.contributor.authorTang, Kam Ki
dc.date.accessioned2017-07-27T01:31:05Z
dc.date.available2017-07-27T01:31:05Z
dc.date.issued2014
dc.date.modified2014-01-23T22:37:42Z
dc.identifier.issn1618-7598
dc.identifier.doi10.1007/s10198-013-0492-1
dc.identifier.urihttp://hdl.handle.net/10072/56045
dc.description.abstractBackground The literature is full of lively discussion on the determinants of population health outcomes. However, different papers focus on small and different sets of variables according to their research agenda. Because many of these variables are measures of different aspects of development and are thus correlated, the results for one variable can be sensitive to the inclusion/exclusion of others. Method We tested for the robustness of potential predictors of population health using the extreme bounds analysis. Population health was measured by life expectancy at birth and infant mortality rate. Results We found that only about half a dozen variables are robust predictors for life expectancy and infant mortality rate. Among them, adolescent fertility rate, improved water sources, and gender equality are the most robust. All institutional variables and environment variables are systematically non-robust predictors of population health. Conclusion The results highlight the importance of robustness tests in identifying predictors or potential determinants of population health, and cast doubts on the findings of previous studies that fail to do so.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.publisher.placeGermany
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom515
dc.relation.ispartofpageto531
dc.relation.ispartofissue5
dc.relation.ispartofjournalEuropean Journal of Health Economics
dc.relation.ispartofvolume15
dc.rights.retentionY
dc.subject.fieldofresearchApplied economics
dc.subject.fieldofresearchHealth economics
dc.subject.fieldofresearchPublic health
dc.subject.fieldofresearchPolicy and administration
dc.subject.fieldofresearchcode3801
dc.subject.fieldofresearchcode380108
dc.subject.fieldofresearchcode4206
dc.subject.fieldofresearchcode4407
dc.titleIdentifying covariates of population health using extreme bound analysis
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Business School, Department of Accounting, Finance and Economics
gro.date.issued2013
gro.hasfulltextNo Full Text
gro.griffith.authorCarmignani, Fabrizio


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