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dc.contributor.authorKarlsson, Martin
dc.contributor.authorIversen, Tor
dc.contributor.authorØien, Henning
dc.date.accessioned2019-02-05T16:28:03Z
dc.date.accessioned2019-09-27T12:29:21Z
dc.date.available2019-02-05T16:28:03Z
dc.date.available2019-09-27T12:29:21Z
dc.date.issued2018-10
dc.identifier.citationKarlsson M, Iversen T, Øien H: Aging and Health Care Costs. In: Hamilton. Oxford Research Encyclopedias: Economics and Finance, 2018. Oxford University Pressen
dc.identifier.isbn9780190625979
dc.identifier.urihttps://hdl.handle.net/10642/7584
dc.description.abstractAn open issue in the economics literature is whether health care expenditure (HCE) is so concentrated in the last years before death that the age profiles in spending will change when longevity increases. The seminal article “Ageing of Population and Health Care Expenditure: A Red Herring?” by Zweifel and colleagues argued that that age is a distraction in explaining growth in HCE. The argument was based on the observation that age did not predict HCE after controlling for time to death (TTD). The authors were soon criticized for the use of a Heckman selection model in this context. Most of the recent literature makes use of variants of a two-part model and seems to give some role to age as well in the explanation. Age seems to matter more for long-term care expenditures (LTCE) than for acute hospital care. When disability is accounted for, the effects of age and TTD diminish. Not many articles validate their approach by comparing properties of different estimation models. In order to evaluate popular models used in the literature and to gain an understanding of the divergent results of previous studies, an empirical analysis based on a claims data set from Germany is conducted. This analysis generates a number of useful insights. There is a significant age gradient in HCE, most for LTCE, and costs of dying are substantial. These “costs of dying” have, however, a limited impact on the age gradient in HCE. These findings are interpreted as evidence against the “red herring” hypothesis as initially stated. The results indicate that the choice of estimation method makes little difference and if they differ, ordinary least squares regression tends to perform better than the alternatives. When validating the methods out of sample and out of period, there is no evidence that including TTD leads to better predictions of aggregate future HCE. It appears that the literature might benefit from focusing on the predictive power of the estimators instead of their actual fit to the data within the sample.en
dc.language.isoenen
dc.publisherOxford University Pressen
dc.rightsThis material was originally published in Oxford Research Encyclopedia of Economics and Finance, edited by Jonathan H. Hamilton, and has been reproduced by permission of Oxford University Press http://dx.doi.org/10.1093/acrefore/9780190625979.013.24. For permission to reuse this material, please visit http://global.oup.com/academic/rights.en
dc.subjectPopulation agingen
dc.subjectHealth care costsen
dc.subjectLong-term careen
dc.subjectMortalityen
dc.subjectPredictionsen
dc.titleAging and Health Care Costsen
dc.typeChapter
dc.typeChapteren
dc.typePeer revieweden
dc.date.updated2019-02-05T16:28:03Z
dc.description.versionpublishedVersionen
dc.identifier.doihttp://dx.doi.org/10.1093/acrefore/9780190625979.013.24
dc.identifier.cristin1670174
dc.source.isbn9780190625979


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