Medicaid’s effect on single women’s labor supply: Evidence from the introduction of Medicaid, by Erin Strumpf (JHE)
This paper examines the impact of the introduction of the Medicaid program on labor supply decisions among single women in the late 1960s and early 1970s. I use a differences-in-differences-in-differences methodology to estimate the effect of Medicaid on eligible women’s labor force participation, using variation in the timing of Medicaid implementation across states and in eligibility across demographic groups. Using March supplements to the CPS from 1963 to 1975, I find no evidence that women who were eligible for Medicaid decreased their labor supply relative to ineligible women, in contrast to clear theoretical predictions of a negative supply response. Positive point estimates suggest that health benefits from health insurance coverage may have contributed to relative increases in labor supply. These results add to an emerging consensus that public health insurance programs for low-income parents and children may be able to improve access to care without substantial indirect costs from labor supply distortions.
The United States aspires to use information from comparative effectiveness research (CER) to reduce waste and contain costs without instituting a formal rationing mechanism or compromising patient or physician autonomy with regard to treatment choices. With such ambitious goals, traditional combinations of research designs and analytical methods used in CER may lead to disappointing results. In this paper, I study how alternate regimes of comparative effectiveness information help shape the marginal benefits (demand) curve in the population and how such perceived demand curves impact decision-making at the individual patient level and welfare at the societal level. I highlight the need to individualize comparative effectiveness research in order to generate the true (normative) demand curve for treatments. I discuss methodological principles that guide research designs for such studies. Using an example of the comparative effect of substance abuse treatments on crime, I use novel econometric methods to salvage individualized information from an existing dataset.