Graduation Year

2015

Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts

Department

Economics

Reader 1

Roberto Pedace

Reader 2

Kerry Odell

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© 2015 Anna M. Stricker

Abstract

The Affordable Care Act (ACA) was designed to reduce the number of citizens who do not have health insurance, and reduce the prices of health insurance premiums. Using multiple regression analysis, the effects of the components of the ACA, along with baseline characteristics of the states, are examined in relation to ACA premium prices and the rate of uninsured. We find that premium prices are higher in states with more uninsured, and states with more obesity have more uninsured. This is most likely related to pre-ACA practice of excluding people with pre-existing conditions from health insurance coverage, yet still caring for those uninsured individuals in emergency departments and hospitals, while passing on the costs of their care to those with insurance. When examining the specific components of the ACA, we find that premium prices are lower in states that implemented state run Internet exchanges, and that less people are uninsured in states that implemented state sponsored Internet exchanges. The other elements of the ACA, namely the number of available insurance plans, and the number of ACO’s, had no effect on either the premium prices or the number of uninsured. Given the possible influence of the political opposition to the ACA on the general population’s cooperation with the ACA, the political dominance of the states was also examined, but found to have no effect on either premium price or the number of uninsured. In conclusion, we find that states with higher rates of uninsured have higher premium rates, and states with higher rates of obesity have more uninsured. After one year of the ACA, we can measure the effect of Internet exchanges on reducing premium prices and the expansion of Medicaid on reducing the uninsured.

This thesis is restricted to the Claremont Colleges current faculty, students, and staff.

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