Medicaid vs. Marketplace Coverage for Near-Poor Adults: Effects on Out-of-Pocket Spending and Coverage

Monday, June 11, 2018: 10:00 AM
Azalea - Garden Level (Emory Conference Center Hotel)

Presenter: Fredric Blavin

Co-Authors: Michael Karpman; Genevieve Kenney; Benjamin Sommers

Discussant: Andrew Mulcahy


In states that expanded Medicaid eligibility under the ACA, non-elderly adults with incomes between 100 and 138 percent of the federal poverty level (FPL) are generally eligible for Medicaid, with no premiums and minimal cost-sharing. In states that did not expand eligibility, these adults may qualify for premium tax credits to purchase Marketplace plans that have out-of-pocket (OOP) premiums and cost-sharing requirements. We use 2010-2015 data to estimate the effects of Medicaid expansion on coverage and OOP expenses, compared with access to Marketplace coverage.

Data and Methods

We use the Current Population Survey and state Medicaid expansion decisions as a natural experiment to estimate the impact of access to the Medicaid expansion on OOP health expenses, compared with access to subsidized marketplace coverage. For this analysis, we estimate difference-in-differences (DD) models to compare key spending outcomes— total OOP expenses, OOP premium expenses, and cost-sharing—for those in Medicaid expansion states versus those in nonexpansion states. We estimate: 1) an OLS model where the dependent variable is the individual’s level of expenses; 2) a linear probability model where the dependent variable is equal to one if the person’s total family OOP spending exceeds 10 percent of family income (high OOP burden); and 3) a two-part model to account for the large share of zeros in the data.

We do not use CPS health insurance information in our main model because of a fundamental redesign of the health insurance questionnaire in 2014 that precludes direct comparisons to estimates from prior years. Instead, we use data from the 2010-2015 American Community Survey (ACS) to assess the impacts of Medicaid expansion on coverage status in this income group. For the ACS analysis, we estimate linear probability DD models where the dependent variables are indicators for being uninsured, covered by Medicaid, covered by employer health insurance, and covered by direct purchase coverage.

We compare changes in key coverage and OOP spending outcomes for nonelderly adults with incomes between 100 and 138% FPL in expansion states versus those in nonexpansion states, controlling for changes in demographic characteristics and state and year fixed effects. We use replicate weights to generate empirically derived standard error estimates.


Medicaid expansion was associated with a 4.5 percentage-point reduction in the probability of being uninsured, a $344 decline in average total OOP spending, a 4.1 percentage-point decline in high OOP spending burden, and a 7.7 percentage-point decline in the probability of having any OOP spending. Sensitivity analyses show that these results are robust to alternative specifications, including attempts to address measurement error in income and inclusion of states with early and late Medicaid expansions. We also find that individuals in expansion and nonexpansion states had similar trends in outcomes prior to the expansion period.


Low-income adults eligible for premium tax credits and cost-sharing reductions are more likely to face medical financial burdens compared to similar individuals eligible for Medicaid coverage. These findings are important given the greater flexibility that states may have in shaping their Medicaid programs and proposed changes to other ACA provisions.