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Time To Drop Time-To-Death? –Unravelling The Determinants of LTC Spending In The Netherlands

Author

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  • de Meijer C
  • Koopmanschap M
  • Bago d
  • Uva T
  • van Doorslaer E

Abstract

A better understanding of what drives long term care (LTC) expenditures is important for all countries with aging populations. We employ unique new data sources to analyze the determinants of LTC spending in the Netherlands. First, we use two-part models, to analyze institutional LTC and homecare expenditures for the entire 55+ population, conditioning not only on age, sex, time-to-death (TTD), but also on cause-of-death and co-residence status. These have profound effects. Those living alone, as well as those who deceased from diabetes, mental illness, stroke, diseases of the respiratory or digestive system have higher LTC expenditures, while a neoplasm death resulted in lower expenditures. Secondly, we examine homecare expenditures among a sample of non-institutionalized individuals conditioning, additionally, on morbidity and disability. Finally, we reconsider the roles of age and TTD, when controlling for the most important determinants of LTC use - morbidity, disability and co-residence - andillustrate their relevance for forecasting LTC expenditures. Our analysis reveals that TTD is not a predictor of homecare expenditures when disability is controlled for, while age and co-residence are. We therefore conclude that it is time to drop time-to-death from LTC expenditure models as it merely acts as a proxy for disability status.

Suggested Citation

  • de Meijer C & Koopmanschap M & Bago d & Uva T & van Doorslaer E, 2009. "Time To Drop Time-To-Death? –Unravelling The Determinants of LTC Spending In The Netherlands," Health, Econometrics and Data Group (HEDG) Working Papers 09/33, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:09/33
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    References listed on IDEAS

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    1. Andreas Werblow & Stefan Felder & Peter Zweifel, 2007. "Population ageing and health care expenditure: a school of 'red herrings'?," Health Economics, John Wiley & Sons, Ltd., vol. 16(10), pages 1109-1126.
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    4. Andrew M. Jones, 2012. "health econometrics," The New Palgrave Dictionary of Economics, Palgrave Macmillan.
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    6. Manning, Willard G., 1998. "The logged dependent variable, heteroscedasticity, and the retransformation problem," Journal of Health Economics, Elsevier, vol. 17(3), pages 283-295, June.
    7. France Weaver & Sally C. Stearns & Edward C. Norton & William Spector, 2009. "Proximity to death and participation in the long-term care market," Health Economics, John Wiley & Sons, Ltd., vol. 18(8), pages 867-883.
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    Cited by:

    1. Karlsson, Martin & Klohn, Florian, 2011. "Some notes on how to catch a red herring: Ageing, time-to-death & care costs for older people in Sweden," Darmstadt Discussion Papers in Economics 207, Darmstadt University of Technology, Department of Law and Economics.
    2. Yu, Tiffany Hui-Kuang & Wang, David Han-Min & Wu, Kuo-Lun, 2015. "Reexamining the red herring effect on healthcare expenditures," Journal of Business Research, Elsevier, vol. 68(4), pages 783-787.
    3. Karlsson, Martin & Klohn, Florian, 2011. "Some notes on how to catch a red herring - Ageing, time-to-death and care costs for older people in Sweden," HERO On line Working Paper Series 2011:6, Oslo University, Health Economics Research Programme.

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