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Testing the red herring hypothesis on an aggregated level: ageing, time-to-death and care costs for older people in Sweden

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  • Martin Karlsson
  • Florian Klohn
Abstract
In this paper we test the ‘red herring’ hypothesis for expenditures on long-term care (LTC). The main contribution of this paper is to assess the ‘red herring’ hypothesis by using the probability of dying as a measure for time-to-death (TTD). In addition, we implement models that allow for age-specific TTD effects on LTC utilization as well as sex-specific effects. We also focus on total, institutional and domiciliary LTC separately. For our analysis we use high quality administrative data from Sweden. Our analysis is based on fixed effects estimates. We use our findings to project future LTC expenditures and show that, although TTD is a relevant predictor, age itself remains the main driver of LTC expenditures. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Martin Karlsson & Florian Klohn, 2014. "Testing the red herring hypothesis on an aggregated level: ageing, time-to-death and care costs for older people in Sweden," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(5), pages 533-551, June.
    • Handle: RePEc:spr:eujhec:v:15:y:2014:i:5:p:533-551
    DOI: 10.1007/s10198-013-0493-0
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    9. Friedrich Breyer & Normann Lorenz & Thomas Niebel, 2015. "Health care expenditures and longevity: is there a Eubie Blake effect?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(1), pages 95-112, January.
    10. Alfons Palangkaraya & Jongsay Yong, 2009. "Population ageing and its implications on aggregate health care demand: empirical evidence from 22 OECD countries," International Journal of Health Economics and Management, Springer, vol. 9(4), pages 391-402, December.
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    12. Martin Karlsson & Tor Iversen & Henning Øien, 2012. "Scandinavian Long-Term Care Financing," Palgrave Macmillan Books, in: Joan Costa-Font & Christophe Courbage (ed.), Financing Long-Term Care in Europe, chapter 14, pages 254-278, Palgrave Macmillan.
    13. de Meijer, Claudine & Koopmanschap, Marc & d' Uva, Teresa Bago & van Doorslaer, Eddy, 2011. "Determinants of long-term care spending: Age, time to death or disability?," Journal of Health Economics, Elsevier, vol. 30(2), pages 425-438, March.
    14. Mickael Bech & Terkel Christiansen & Ehsan Khoman & Jørgen Lauridsen & Martin Weale, 2011. "Ageing and health care expenditure in EU-15," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 12(5), pages 469-478, October.
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    Cited by:

    1. Joan Costa‐Font & Cristina Vilaplana‐Prieto, 2020. "‘More than one red herring'? Heterogeneous effects of ageing on health care utilisation," Health Economics, John Wiley & Sons, Ltd., vol. 29(S1), pages 8-29, October.
    2. Kuhn, Michael & Frankovic, Ivan & Wrzaczek, Stefan, 2017. "Medical Progress, Demand for Health Care, and Economic Performance," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168249, Verein für Socialpolitik / German Economic Association.
    3. Howdon, Daniel & Rice, Nigel, 2018. "Health care expenditures, age, proximity to death and morbidity: Implications for an ageing population," Journal of Health Economics, Elsevier, vol. 57(C), pages 60-74.
    4. Ivan Frankovic & Michael Kuhn & Stefan Wrzaczek, 2016. "Medical Care within an OLG Economy with Realistic Demography," VID Working Papers 1603, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
    5. Caravaggio, Nicola & Resce, Giuliano, 2023. "Enhancing Healthcare Cost Forecasting: A Machine Learning Model for Resource Allocation in Heterogeneous Regions," Economics & Statistics Discussion Papers esdp23090, University of Molise, Department of Economics.
    6. Norton, E.C., 2016. "Health and Long-Term Care," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 951-989, Elsevier.
    7. Jonas Krämer & Jonas Schreyögg, 2019. "Demand-side determinants of rising hospital admissions in Germany: the role of ageing," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(5), pages 715-728, July.
    8. Friedrich Breyer & Normann Lorenz, 2021. "The “red herring” after 20 years: ageing and health care expenditures," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(5), pages 661-667, July.
    9. Breyer Friedrich, 2015. "Demographischer Wandel und Gesundheitsausgaben: Theorie, Empirie und Politikimplikationen," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 16(3), pages 215-230, October.
    10. Anne Mason & Idaira Rodriguez Santana & María José Aragón & Nigel Rice & Martin Chalkley & Raphael Wittenberg & Jose-Luis Fernandez, 2019. "Drivers of health care expenditure: Final report," Working Papers 169cherp, Centre for Health Economics, University of York.
    11. Bahnsen, Lewe & Fetzer, Stefan & Franke, Fabian & Hagist, Christian, 2020. "Gone with the windfall – Germany's Second LTC Strengthening Act and its intergenerational implications," The Journal of the Economics of Ageing, Elsevier, vol. 17(C).

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    More about this item

    Keywords

    Mortality; Long-term care; Red herring; I10; H51; J14; C23;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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