Estimating Heterogeneous Treatment Effects of Medicaid Expansions on Take-up and Crowd-out
AbstractEconomists have devoted considerable resources to estimating local average treatment effects of expansions in Medicaid eligibility for children. In this paper we use random coefficients linear probability models and switching probit models to estimate a more complete range of effects of Medicaid expansion on Medicaid take-up and crowd-out of private insurance. We demonstrate how to estimate, for Medicaid expansions, the average effect among all of those eligible, the average effect for a randomly chosen person, the effect for a marginally eligible child, and the average effect for those affected by a nonmarginal counterfactual policy change. We then estimate the average effect of Medicaid expansions among all eligible children and the average effect for those affected by a nonmarginal counterfactual Medicaid expansion since these are likely to be the most useful for policy analysis. Estimated take-up rates among average eligible children are substantially larger than take-up rates for those made eligible by a counterfactual Medicaid expansion, moreover both of these effects vary widely across demographic groups. In terms of crowd-out, we find statistically significant, though small, effects for all eligible children, but not for those affected by a counterfactual policy change.
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Bibliographic InfoPaper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16112.
Date of creation: Jun 2010
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Find related papers by JEL classification:
- H42 - Public Economics - - Publicly Provided Goods - - - Publicly Provided Private Goods
- I1 - Health, Education, and Welfare - - Health
- I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-06-26 (All new papers)
- NEP-HEA-2010-06-26 (Health Economics)
- NEP-IAS-2010-06-26 (Insurance Economics)
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- Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
- Koch, Thomas G., 2013. "Using RD design to understand heterogeneity in health insurance crowd-out," Journal of Health Economics, Elsevier, vol. 32(3), pages 599-611.
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