Collaborative Research: Evaluation of ACA Reform

Project: Research project

Project Details


Numerous proposals have been advanced over the last few months by different congressmen to replace the ACA. While much of the discussion has revolved around redistributive issues, virtually all proposals do away with the ACA participation mandate. Some proposal also advocate changing minimum coverage rules, and giving States leeway allowing for the pricing of health conditions. While there has certainly been a great deal of public discussion concerning the desirability of this reform, there has been surprisingly little formal analysis of alternative designs. Lack of consideration of alternative market rules risks adopting ill-conceived proposals whose effects - particularly for those with expensive pre-existing medical conditions - could be disastrous. The Pis argue that to analyze the recent Republican proposals requires a dynamic framework. Both the House and the Senate version of the bill repeal the individual mandate, offering replacements which entail dynamic decisions. The House version requires individuals without continuous coverage to pay a 30% surcharge in premium for one year in case she decides to re-enroll. The Senate version requires that an individual whose coverage lapses be denied insurance for six months. Under such rules current enrollment determines future premiums, making today's choice dynamic. insurance demand requires a dynamic model, and data that captures the evolution of health over time. The Pis adapt the static framework in Handel, Hendel and Whinston (2017) to evaluate these reform proposals. The goal of the project is to assess their impact on participation and welfare. The authors use information on individual-level health plan choices and health claims from large firm, to simulate the market. The distribution of health risk is quantified with a professional risk assessment software. New to this project, the key to study dynamic choices by individuals, are expectation about future health. Which are captured by health state transitions, estimated using risk scores in two consecutive years.
Effective start/end date4/15/183/31/23


  • National Science Foundation (SES-1758201)


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