Job Market Paper

Who Did the ACA Medicaid Expansion Impact? Using Linear Discriminant Analysis to Estimate the Probability of Being a Complier [Paper] Revise & Resubmit: Health Economics

Abstract: What is the likelihood of being a complier in the ACA Medicaid expansion? Using linear discriminant analysis (LDA), I estimate how characteristics relating to socioe- conomic status and race/ethnicity affect the likelihood that an individual will be a complier, defined as those induced by the expansion to obtain Medicaid coverage. Across multiple specifications, part-time and full-time workers are more likely than non-workers to be compliers. Not only is this result more prominent for Black individuals, but they also are more likely to be compliers compared to other racial/ethnic groups. This paper not only serves to identify the types of individuals who were directly impacted by the expansion, but it also introduces a new approach that combines complier analysis with techniques from machine learning.

Working Papers

Laying Down the Welcome Mat: The Impact of the ACA Medicaid Expansion on Health Coverage for Previously Eligible Children [Draft]

Abstract: In this paper, I estimate the effects of the Patient Protection and Affordable Care Act Medicaid Expansion on health coverage among families with children who were previously eligible for Medicaid prior to the expansion. I utilize the American Community Survey (ACS) from 2012 to 2017 and adopt a difference-in-differences approach that measures the changes in health coverage for Medicaid/CHIP eligible children before and after the ACA Medicaid expansion. I find that there are modest yet significant increases in public coverage across all years for children who were previously eligible for Medicaid and CHIP prior to the expansion, providing evidence of a "welcome mat" effect. However, I observe significant crowding out in employer-sponsored insurance for children who were previously eligible as well as children who became newly eligible under the new adjusted gross income (MAGI) thresholds established after 2014.

Works In Progress

  • Assessing the Effectiveness of Risk Adjustment Systems in Recognizing Dual Diagnosis and Co-occurring Conditions for Mental Health and Substance Use Disorders