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Timothy J. Layton
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Journal Articles
Publisher: Journals Gateway
The Review of Economics and Statistics 1–32.
Published: 05 March 2025
Abstract
View articletitled, Reducing Administrative Barriers Increases Take-Up of Subsidized Health Insurance Coverage: Evidence from a Field Experiment
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for article titled, Reducing Administrative Barriers Increases Take-Up of Subsidized Health Insurance Coverage: Evidence from a Field Experiment
Administrative barriers to social insurance program take-up are pervasive, including in subsidized health insurance. We conducted a randomized controlled trial with Massachusetts' Affordable Care Act marketplace to reduce these barriers and other behavioral frictions. We find that a “check the box” streamlined enrollment intervention raises enrollment by 10.5%, more than personalized reminder letters (7.6% increase) or generic reminder letters (4.3% increase). Effects are concentrated among individuals eligible for zero-premium plans, who faced no further administrative burdens of setting up payments. Producing this enrollment effect through premium reduction would cost about $7 million in subsidies, highlighting the importance of these burdens.
Includes: Supplementary data
Journal Articles
Publisher: Journals Gateway
The Review of Economics and Statistics (2023) 105 (2): 237–257.
Published: 03 March 2023
Abstract
View articletitled, The Two-Margin Problem in Insurance Markets
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for article titled, The Two-Margin Problem in Insurance Markets
Insurance markets often feature consumer sorting along both an extensive margin (whether to buy) and an intensive margin (which plan to buy). We present a new graphical theoretical framework that extends a workhorse model to incorporate both selection margins simultaneously. A key insight from our framework is that policies aimed at addressing one margin of selection often involve an economically meaningful trade-off on the other margin in terms of prices, enrollment, and welfare. Using data from Massachusetts, we illustrate these trade-offs in an empirical sufficient statistics approach that is tightly linked to the graphical framework we develop.
Includes: Supplementary data