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Adverse and Advantageous Selection in the Medicare Supplemental Market: A Bayesian Analysis of Prescription drug Expenditure

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  • Qian Li
  • Pravin K. Trivedi

Abstract

This paper develops an extended specification of the two‐part model, which controls for unobservable self‐selection and heterogeneity of health insurance, and analyzes the impact of Medicare supplemental plans on the prescription drug expenditure of the elderly, using a linked data set based on the Medicare Current Beneficiary Survey data for 2003–2004. The econometric analysis is conducted using a Bayesian econometric framework. We estimate the treatment effects for different counterfactuals and find significant evidence of endogeneity in plan choice and the presence of both adverse and advantageous selections in the supplemental insurance market. The average incentive effect is estimated to be $757 (2004 value) or 41% increase per person per year for the elderly enrolled in supplemental plans with drug coverage against the Medicare fee‐for‐service counterfactual and is $350 or 21% against the supplemental plans without drug coverage counterfactual. The incentive effect varies by different sources of drug coverage: highest for employer‐sponsored insurance plans, followed by Medigap and managed medicare plans. Copyright © 2014 John Wiley & Sons, Ltd.

Suggested Citation

  • Qian Li & Pravin K. Trivedi, 2016. "Adverse and Advantageous Selection in the Medicare Supplemental Market: A Bayesian Analysis of Prescription drug Expenditure," Health Economics, John Wiley & Sons, Ltd., vol. 25(2), pages 192-211, February.
    • Handle: RePEc:wly:hlthec:v:25:y:2016:i:2:p:192-211
    DOI: 10.1002/hec.3133
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    References listed on IDEAS

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    1. Hoogerheide, Lennart & Kleibergen, Frank & van Dijk, Herman K., 2007. "Natural conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data," Journal of Econometrics, Elsevier, vol. 138(1), pages 63-103, May.
    2. Baoping Shang & Dana P. Goldman, 2007. "Prescription Drug Coverage and Elderly Medicare Spending," NBER Working Papers 13358, National Bureau of Economic Research, Inc.
    3. Coulson, N Edward, et al, 1995. "Estimating the Moral-Hazard Effect of Supplemental Medical Insurance in the Demand for Prescription Drugs by the Elderly," American Economic Review, American Economic Association, vol. 85(2), pages 122-126, May.
    4. Lillard, L.A. & Rogowski, J. & Kington, R., 1999. "Insurance Coverage for Prescription Drugs: Effects on Use and Expenditures in the Medicare Population," Papers 99-09, RAND - Labor and Population Program.
    5. Tomas J. Philipson & Dana Goldman, 2007. "Integrated Insurance Design in the Presence of Multiple Medical Technologies," American Economic Review, American Economic Association, vol. 97(2), pages 427-432, May.
    6. Pauly Mark V. & Zeng Yuhui, 2004. "Adverse Selection and the Challenges to Stand-Alone Prescription Drug Insurance," Forum for Health Economics & Policy, De Gruyter, vol. 7(1), pages 1-22, January.
    7. Robert Kaestner & Nasreen Khan, 2012. "Medicare Part D and Its Effect on the Use of Prescription Drugs and Use of Other Health Care Services of the Elderly," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 31(2), pages 253-279, March.
    8. Sha Yang & Yuxin Chen & Greg Allenby, 2003. "Bayesian Analysis of Simultaneous Demand and Supply," Quantitative Marketing and Economics (QME), Springer, vol. 1(3), pages 251-275, September.
    9. Duan, Naihua, et al, 1983. "A Comparison of Alternative Models for the Demand for Medical Care," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 115-126, April.
    10. Nasreen Khan & Robert Kaestner & Swu Jane Lin, 2007. "Prescription Drug Insurance and Its Effect on Utilization and Health of the Elderly," NBER Working Papers 12848, National Bureau of Economic Research, Inc.
    11. Lillard, L.A. & Rogowski, J. & Kington, R., 1999. "Insurance Coverage for Prescription Drugs: Effects on Use and Expenditures in the Medicare Population," Papers 99-09, RAND - Labor and Population Program.
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