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Income and the Use of Prescription Drugs by the Elderly: Evidence from the Notch Cohorts

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  • John R. Moran
  • JKosali Ilayperuma Simon

Abstract

We use exogenous variation in Social Security payments created by the Social Security benefits notch to estimate how retirees’ use of prescription medications responds to changes in their incomes. Using data from the 1993 Wave of the AHEAD, we obtain instrumental variables estimates of the income elasticity of prescription drug use that are uniformly above one, with a middle estimate of 1.32. Simulations based on our estimates suggest that reductions in Social Security benefits similar to those incorporated in recent reform proposals would significantly reduce prescription drug use among the elderly.

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  • John R. Moran & JKosali Ilayperuma Simon, 2006. "Income and the Use of Prescription Drugs by the Elderly: Evidence from the Notch Cohorts," Journal of Human Resources, University of Wisconsin Press, vol. 41(2).
    • Handle: RePEc:uwp:jhriss:v:41:y:2006:i:2:p411-432
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    Cited by:

    1. Padmaja Ayyagari & David Frisvold, 2016. "The Impact of Social Security Income on Cognitive Function at Older Ages Full Access," American Journal of Health Economics, MIT Press, vol. 2(4), pages 463-488, Fall.
    2. Tsai, Yuping, 2015. "Social security income and the utilization of home care: Evidence from the social security notch," Journal of Health Economics, Elsevier, vol. 43(C), pages 45-55.
    3. Goda, Gopi Shah & Golberstein, Ezra & Grabowski, David C., 2011. "Income and the utilization of long-term care services: Evidence from the Social Security benefit notch," Journal of Health Economics, Elsevier, vol. 30(4), pages 719-729, July.
    4. Freyberger, Joachim & Horowitz, Joel L., 2015. "Identification and shape restrictions in nonparametric instrumental variables estimation," Journal of Econometrics, Elsevier, vol. 189(1), pages 41-53.
    5. Chen, Xi & Wang, Tianyu & Busch, Susan H., 2019. "Does money relieve depression? Evidence from social pension expansions in China," Social Science & Medicine, Elsevier, vol. 220(C), pages 411-420.
    6. Siha Lee & Kegon Teng Kok Tan, 2023. "Bequest Motives and the Social Security Notch," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 888-914, December.
    7. Joachim Freyberger & Joel L. Horowitz, 2012. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers CWP15/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Tal Gross & Jeremy Tobacman, 2014. "Dangerous Liquidity and the Demand for Health Care: Evidence from the 2008 Stimulus Payments," Journal of Human Resources, University of Wisconsin Press, vol. 49(2), pages 424-445.
    9. Florian Heiss & Daniel McFadden & Joachim Winter, 2010. "Mind the Gap! Consumer Perceptions and Choices of Medicare Part D Prescription Drug Plans," NBER Chapters, in: Research Findings in the Economics of Aging, pages 413-481, National Bureau of Economic Research, Inc.
    10. Tran, My & Gannon, Brenda & Rose, Christiern, 2023. "The effect of housing wealth on older adults’ health care utilization: Evidence from fluctuations in the U.S. housing market," Journal of Health Economics, Elsevier, vol. 88(C).
    11. Joachim Freyberger & Joel L. Horowitz, 2013. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers 31/13, Institute for Fiscal Studies.
    12. Padmaja Ayyagari & David Frisvold, 2015. "The Impact of Social Security Income on Cognitive Function at Older Ages," NBER Working Papers 21484, National Bureau of Economic Research, Inc.
    13. Terence C. Cheng & Joan Costa-Font & Nattavudh Powdthavee, 2018. "Do You Have to Win It to Fix It? A Longitudinal Study of Lottery Winners and Their Health-Care Demand," American Journal of Health Economics, MIT Press, vol. 4(1), pages 26-50, Winter.
    14. Yuping Tsai, 2018. "Social Security Income and Health Care Spending: Evidence from the Social Security Notch," Scandinavian Journal of Economics, Wiley Blackwell, vol. 120(2), pages 440-464, April.
    15. SØren Leth‐Petersen & Niels Skipper, 2014. "Income And The Use Of Prescription Drugs For Near Retirement Individuals," Health Economics, John Wiley & Sons, Ltd., vol. 23(3), pages 314-331, March.
    16. Owen O'Donnell & Eddy Van Doorslaer & Tom Van Ourti, 2013. "Health and Inequality," Tinbergen Institute Discussion Papers 13-170/V, Tinbergen Institute.
    17. John Cawley & John Moran & Kosali Simon, 2010. "The impact of income on the weight of elderly Americans," Health Economics, John Wiley & Sons, Ltd., vol. 19(8), pages 979-993, August.
    18. Joachim Freyberger & Joel L. Horowitz, 2013. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers CWP31/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Glazer Jacob & Huskamp Haiden A. & McGuire Thomas G., 2012. "A Prescription for Drug Formulary Evaluation: An Application of Price Indexes," Forum for Health Economics & Policy, De Gruyter, vol. 15(2), pages 1-26, March.
    20. Engelhardt, Gary V., 2008. "Social security and elderly homeownership," Journal of Urban Economics, Elsevier, vol. 63(1), pages 280-305, January.
    21. Thierry Nianogo & Albert Okunade & Demba Fofana & Weiwei Chen, 2016. "Determinants of US Prescription Drug Utilization using County Level Data," Health Economics, John Wiley & Sons, Ltd., vol. 25(5), pages 606-619, May.
    22. Vere, James P., 2011. "Social Security and elderly labor supply: Evidence from the Health and Retirement Study," Labour Economics, Elsevier, vol. 18(5), pages 676-686, October.
    23. Joachim Freyberger & Joel L. Horowitz, 2012. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers 15/12, Institute for Fiscal Studies.

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