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Experimental Evidence: From the ACA to New Drugs

Paper Session

Saturday, Jan. 4, 2020 2:30 PM - 4:30 PM (PDT)

Manchester Grand Hyatt, Solana Beach AB
Hosted By: Health Economics Research Organization & American Economic Association
  • Chair: Donald Yett, University of Southern California

Nudging Take-up of Subsidized Insurance: Evidence from Massachusetts

Keith Marzilli Ericson
,
Boston University
Tim Layton
,
Harvard University
Adrianna McIntyre
,
Harvard University
Adam Sacarny
,
Columbia University

Abstract

Incomplete take-up of free and low-cost health insurance remains a puzzle. Failure to enroll in coverage has consequences for the uninsured as well as the health care providers and state budgets that bear the costs of uncompensated care. Moreover, if the marginal enrollee is healthier on average, increasing enrollment may improve competition and reduce premiums in the market by improving the risk pool. Research from other contexts suggests that behavioral frictions or mistakes may play an important role in determining whether households complete the enrollment process.

We conducted a randomized trial to test “nudges” (letters sent by postal mail) that could increase enrollment in the Massachusetts Health Connector, the state marketplace through which eligible residents can obtain subsidized private coverage. Nudges were targeted to households that were determined eligible for financial assistance but—for unknown reasons—failed to enroll in an insurance plan. Our study design employs three treatment arms: a generic reminder letter, a personalized reminder letter, and a personalized reminder letter with a simplified (check-the-box) enrollment option.

Enrollment in the Connector involves typically involves a complicated process including calling a number to retrieve a password and then filling out a series of forms on a website. Our intervention tests whether the onerous process acts as a barrier to enrollment, and, if so, who is screened out of insurance. We focus our attention on two characteristics of the marginal enrollees: (1) health status and (2) valuation of insurance. For health status, we use health information from the Massachusetts All-Payer Claims Database, and we use this information to characterize the extent to which there is adverse selection into the market on this margin. For valuation of insurance, we use exogenous variation in the price of insurance in the Connector caused by discontinuous changes in subsidy amounts at particular income thresholds to estimate

Health Insurance and Mortality: Experimental Evidence from Taxpayer Outreach

Ithai Lurie
,
U.S. Treasury Department
Janet McCubbin
,
U.S. Treasury Department
Jacob Goldin
,
Stanford University

Abstract

We evaluate a randomized pilot study in which the IRS sent informational letters to 3.9 million households that paid a tax penalty for lacking health insurance coverage under the Affordable Care Act. Drawing on administrative data, we study the effect of the pilot on taxpayers’ subsequent health insurance enrollment and mortality. We find the pilot led to increased coverage in the two years following treatment and that this additional coverage reduced mortality among middle-aged adults over the same time period. Our results provide the first experimental evidence that health insurance reduces mortality.

A Model of a Randomized Experiment with an Application to the PROWESS Clinical Trial

Amanda Ellen Kowalski
,
University of Michigan

Abstract

I develop a model of a randomized experiment with a binary intervention and a binary outcome. Potential outcomes in the intervention and control groups give rise to four types of participants. Fixing ideas such that the outcome is mortality, some participants would live regardless, others would be saved, others would be killed, and others would die regardless. These potential outcome types are not observable. However, I use the model to develop estimators of the number of participants of each type. The model relies on the randomization within the experiment and on deductive reasoning. I apply the model to an important clinical trial, the PROWESS trial, and I perform a Monte Carlo simulation calibrated to estimates from the trial. The reduced form from the trial shows a reduction in mortality, which provided a rationale for FDA approval. However, I find that the intervention killed two participants for every three it saved.
Discussant(s)
Joseph Doyle
,
Massachusetts Institute of Technology
Mark Shepard
,
Harvard University
Jonathan Kolstad
,
University of California-Berkeley
JEL Classifications
  • I1 - Health