Partially Identifying Treatment Effects with an Application to Covering the Uninsured
We extend the nonparametric literature on partially identified probability distributions and use our analytical results to provide sharp bounds on the impact of universal health insurance on provider visits and medical expenditures. Our approach accounts for uncertainty about the reliability of self-reported insurance status as well as uncertainty created by unknown counterfactuals. We construct health insurance validation data using detailed information from the Medical Expenditure Panel Survey. Imposing relatively weak nonparametric assumptions, we estimate that under universal coverage monthly per capita provider visits and expenditures would rise by less than 8% and 16%, respectively, across the nonelderly population.
|Date of creation:||16 Apr 2005|
|Date of revision:|
|Publication status:||Published in Journal of Human Resources, April 2009, vol. 44 no. 2, pp. 409-449|
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