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Testing Providers' Moral Hazard Caused By a Health Care Report Card Policy


  • Yijuan Chen


  • Juergen Meinecke



This paper focuses on testing providers' moral hazard caused by a health care report card policy. We argue that, to indicate providers' moral hazard, empirical approaches should be based on understanding that the policy may cause different sides of participants to take actions. Neglecting this, an estimation strategy will estimate treatment effects that only capture the mixture of the providers' and patients' actions, and therefore cannot identify either side's action. We propose a simple remedy to the estimation strategy in the previous literature: Restricting to data before the report cards are published and setting the date when providers' performance start being recorded as the effective date of the policy. The U.S. state of Pennsylvania started collecting information on mortality outcomes for coronary artery bypass graft (CABG) surgery in 1990. The first report cards were published in 1992. Using U.S. Nationwide Inpatient Sample data from 1988 to 1992, we find insignificant quantity and incidence effects of the report-card policy before report cards are published. This means that the report card policy has not affected the likelihood that heart patients receive CABG surgery and it has not led hospitals to select patients strategically.

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  • Yijuan Chen & Juergen Meinecke, 2010. "Testing Providers' Moral Hazard Caused By a Health Care Report Card Policy," ANU Working Papers in Economics and Econometrics 2010-527, Australian National University, College of Business and Economics, School of Economics.
  • Handle: RePEc:acb:cbeeco:2010-527

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    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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