The label of "essential worker" reflects society's needs but does not mean that society has compensated those workers for additional risks incurred on the job during the current pandemic. When an essential worker contracts severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), they pose a risk to the other members of their household. These members may be elderly or lack health insurance, and the household may have limited resources to care for a sick family member. 1,2 We assessed the proportion of essential workers in the US population and described the economic vulnerability of their households. Methods | We analyzed data from the Public Use Microdata Sample of the 2018 American Community Survey (ACS). The US Census Bureau chooses a random sample of US addresses each month, contacts selected households by mail, and follows up by phone and personal visit to address nonresponse. 3 The Department of Homeland Security's Cybersecurity and Infrastructure Security Agency (CISA) released an "Essential Critical Infrastructure Workforce" advisory list of occupations necessary to "continuity of functions critical to public health and safety" in March 2020 and updated that list in April 2020. 4 We matched industry and subindustry codes in the ACS to the 6-digit Standard Occupation Codes (indexed by the US Bureau of Labor Statistics) in the CISA advisory list to identify essential workers. 5 We assessed the proportion and demographic characteristics (age, sex, and race as given in response to a multiplechoice question) of essential workers by industry.

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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 the 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. For example, while a larger penalty for opting to remain uninsured reduces the uninsurance rate, it also tends to lead to unraveling of generous coverage because the newly insured are healthier and sort into less generous plans, driving down the relative prices of those plans. While risk adjustment transfers shift enrollment from lower-to higher-generosity plans, they also sometimes increase the uninsurance rate by raising the prices of less generous plans, which are the entry points into the market. We illustrate these trade-offs in an empirical sufficient statistics approach that is tightly linked to the graphical framework. Using data from Massachusetts, we show that in many policy environments these trade-offs can be empirically meaningful and can cause these policies to have unexpected consequences for overall social welfare.

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 fromMassachusetts, we illustrate these trade-offs in an empirical sufficient statistics approach that is tightly linked to the graphical framework we develop.

This cross-sectional study uses data from the National Health Interview Survey to assess the association of Medicaid expansion to working-age adults with Medicaid enrollment and health care use among older adults with low income and chronic condition limitations.