I take advantage of the evolution of the regulatory and pricing environment in the first years of a large federal prescription drug insurance program for seniors-Medicare Part D-to empirically explore interactions among adverse selection, switching costs, and regulation. Using detailed administrative data, I document evidence of both adverse selection of beneficiaries across contracts and switching costs for beneficiaries in changing contracts within Medicare Part D. Motivated by this descriptive evidence, I formulate a model of contract choice that allows for both switching costs and private information about expected risk. Using this model, I show that switching costs are large and have quantitatively important implications for the sorting of individuals among contracts. How switching costs affect selection over time depends on the direction of changes in the contract space relative to the initial conditions. I find that in the present environment, on net, switching costs help sustain an adversely-selected equilibrium with large differences in risks between more and less generous contracts. I then simulate how switching costs could affect regulatory interventions that change the generosity of contracts. For example, I consider the tightening of the minimum standard requirement by "filling" the Part D donut hole as implemented under the Affordable Care Act. I find that absent any switching costs, this regulation would have eliminated the differences in risks across contracts; however, in the presence of the switching costs that I estimate, the effect of the policy is largely muted. JEL classification numbers: D12, I13, I18, G22

The economic and mortality impacts of the COVID-19 pandemic have been widely discussed, but there is limited evidence on their relationship across demographic and geographic groups. We use publicly available monthly data from January 2011 through April 2020 on all-cause death counts from the Centers for Disease Control and Prevention and employment from the Current Population Survey to estimate excess all-cause mortality and employment displacement in April 2020 in the United States. We report results nationally and separately by state and by age group. Nationally, excess all-cause mortality was 2.4 per 10,000 individuals (about 30% higher than reported COVID deaths in April) and employment displacement was 9.9 per 100 individuals. Across age groups 25 y and older, excess mortality was negatively correlated with economic damage; excess mortality was largest among the oldest (individuals 85 y and over: 39.0 per 10,000), while employment displacement was largest among the youngest (individuals 25 to 44 y: 11.6 per 100 individuals). Across states, employment displacement was positively correlated with excess mortality (correlation = 0.29). However, mortality was highly concentrated geographically, with the top two states (New York and New Jersey) each experiencing over 10 excess deaths per 10,000 and accounting for about half of national excess mortality. By contrast, employment displacement was more geographically spread, with the states with the largest point estimates (Nevada and Michigan) each experiencing over 16 percentage points employment displacement but accounting for only 7% of the national displacement. These results suggest that policy responses may differentially affect generations and geographies.

Standard theory suggests that optimal consumer cost-sharing in health insurance increases with the price elasticity of demand, yet publicly-provided drug coverage typically involves uniform cost-sharing across drugs. We investigate how private drug plans set cost-sharing in the context of Medicare Part D. We document substantial heterogeneity in the price elasticities of demand across more than 150 drugs and across more than 100 therapeutic classes, as well as substantial heterogeneity in the cost-sharing for different drugs within privately-provided plans. We find that private plans set higher consumer cost-sharing for drugs or classes with more elastic demand. Our findings suggest that benefit design may be more efficient in privately rather than publicly provided insurance.

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Timmins, and numerous seminar participants. Decarolis is grateful to the Sloan Foundation (grant 2011-5-23 ECON) for financial support. We also gratefully acknowledge support from the National Science Foundation (SES-1357705) and the National Institute on Aging (5P01AG005842-29). The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.