Three tests of information asymmetry among Medicaid adults

Article

Abstract

Information asymmetry has well known efficiency consequences for health insurance markets. Unlike private insurance, Medicaid programs are designed to attract clinically and socioeconomically vulnerable patients, and allow limited enrollee cost sharing. This suggests that the Medicaid expansion authorized by the Affordable Care Act may attract an adversely selected population that poses unknown utilization, and hence, financial risks to its federal and state financers. In this study, I test for information asymmetry by examining whether unobserved determinants of Medicaid enrollment are correlated with unobserved determinants of emergency department and primary care visits, using the Medical Expenditure Panel Survey. I use instrumental variables, correlation tests, and a simulation analysis to test for correlated unobservables. I find evidence of information asymmetry in Medicaid for emergency care use, but not primary care visits, once certain demographic and health variables are controlled. Since new Medicaid enrollees may not have “baseline” claims or diagnostic data, it may be helpful to collect information on their self-rated health status and disease history, such as obesity and heart attacks. Controlling for these variables may improve forecasts of health care use among Medicaid enrollees, and can reduce estimation bias in non-experimental studies of Medicaid.

Keywords

Medicaid Moral hazard Adverse selection Econometrics 

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Health Care PolicyHarvard Medical SchoolBostonUSA

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