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Health insurance system and resilience to epidemics

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dc.contributor.authorHong, Jimin-
dc.contributor.authorSeog, Sung Hun-
dc.date.accessioned2023-03-13T07:40:03Z-
dc.date.available2023-03-13T07:40:03Z-
dc.date.created2023-02-27-
dc.date.issued2023-01-
dc.identifier.issn0272-4332-
dc.identifier.urihttp://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/43376-
dc.description.abstractWe theoretically analyze the resilience (efficiency) of health insurance systems and diverse factors including trace and test technology, infection and contagion rates, and social distancing/lockdown policy, in coping with contagious diseases like COVID-19. Our findings can be summarized as follows. First, public insurance is more resilient than market insurance, as the former's investment in test technology is made at the social optimum, whereas the latter's investment is less. The decentralized behavior of competing insurers leads to a less resilient outcome. Second, resilience decreases as the market becomes more competitive because the externality effect becomes more severe. Third, a higher contagion rate, a more cost-efficient test technology or a higher initial infection rate unless it is not too high, leads to a higher test accuracy level. Fourth, the socially optimal social distancing/lockdown policy is determined by comparison between its relative costs and the benefit from contagion reduction.-
dc.language영어-
dc.language.isoen-
dc.publisherWILEY-
dc.relation.isPartOfRISK ANALYSIS-
dc.titleHealth insurance system and resilience to epidemics-
dc.typeArticle-
dc.identifier.doi10.1111/risa.14005-
dc.type.rimsART-
dc.identifier.bibliographicCitationRISK ANALYSIS, v.43, no.1, pp.97 - 114-
dc.description.journalClass1-
dc.identifier.wosid000852443500001-
dc.identifier.scopusid2-s2.0-85137784331-
dc.citation.endPage114-
dc.citation.number1-
dc.citation.startPage97-
dc.citation.titleRISK ANALYSIS-
dc.citation.volume43-
dc.contributor.affiliatedAuthorHong, Jimin-
dc.identifier.urlhttps://onlinelibrary.wiley.com/doi/epdf/10.1111/risa.14005-
dc.type.docTypeArticle; Early Access-
dc.description.isOpenAccessN-
dc.subject.keywordAuthorepidemic-
dc.subject.keywordAuthormarket insurance-
dc.subject.keywordAuthorpublic insurance-
dc.subject.keywordAuthorresilience-
dc.subject.keywordAuthorsocial distancing-
dc.subject.keywordAuthorlockdown-
dc.subject.keywordAuthortrace and test-
dc.subject.keywordPlusHOUSING INSURANCE-
dc.subject.keywordPlusSELF-PROTECTION-
dc.subject.keywordPlusLOSS-PREVENTION-
dc.subject.keywordPlusMONOPOLY-
dc.subject.keywordPlusSARS-
dc.subject.keywordPlusEXTERNALITIES-
dc.subject.keywordPlusCOMPETITION-
dc.subject.keywordPlusEFFICIENCY-
dc.subject.keywordPlusMODEL-
dc.subject.keywordPlusRISK-
dc.relation.journalResearchAreaPublic, Environmental & Occupational Health-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalResearchAreaMathematical Methods In Social Sciences-
dc.relation.journalWebOfScienceCategoryPublic, Environmental & Occupational Health-
dc.relation.journalWebOfScienceCategoryMathematics, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategorySocial Sciences, Mathematical Methods-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
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College of Natural Sciences (Department of Statistics and Actuarial Science)
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