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The Response of Drug Expenditures to Non-Linear Contract Design: Evidence from Medicare Part D

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Listed:
  • Liran Einav
  • Amy Finkelstein
  • Paul Schrimpf

Abstract

We study the demand response to non-linear price schedules using data on insurance contracts and prescription drug purchases in Medicare Part D. Consistent with a static response of drug use to price, we document bunching of annual drug spending as individuals enter the famous "donut hole," where insurance becomes discontinuously much less generous on the margin. Consistent with a dynamic response to price, we document a response of drug use to the future out-of-pocket price by using variation in beneficiary birth month which generates variation in contract duration during the first year of eligibility. Motivated by these two facts, we develop and estimate a dynamic model of drug use during the coverage year that allows us to quantify and explore the effects of alternative contract designs on drug expenditures. For example, our estimates suggest that "filling" the donut hole, as required under the Affordable Care Act, will increase annual drug spending by $180 per beneficiary, or about 10%. Moreover, almost half of this increase is "anticipatory," coming from beneficiaries whose spending prior to the policy change would leave them short of reaching the donut hole. We also describe the nature of the utilization response and its heterogeneity across individuals and types of drugs.

Suggested Citation

  • Liran Einav & Amy Finkelstein & Paul Schrimpf, 2013. "The Response of Drug Expenditures to Non-Linear Contract Design: Evidence from Medicare Part D," NBER Working Papers 19393, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:19393
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    References listed on IDEAS

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    1. Anthony T. Lo Sasso & Lorens A. Helmchen & Robert Kaestner, 2010. "The Effects of Consumer‐Directed Health Plans on Health Care Spending," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(1), pages 85-103, March.
    2. Martin Andreasen, 2010. "How to Maximize the Likelihood Function for a DSGE Model," Computational Economics, Springer;Society for Computational Economics, vol. 35(2), pages 127-154, February.
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    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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