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Take-up of a social benefit is usually defined as receiving a benefit for which an individual or household is eligible. The take-up rate is the fraction of those eligible for a program who participate and receive a benefit or service. We survey estimates of take-up of social benefits around the world, discuss alternative theories of reasons for incomplete take-up, and survey the empirical evidence on the importance of different factors. We find a wide range of take-up rates around the world which follow some general patterns but are not easily explained. Theories of incomplete take-up include those involving low monetary or utility gains, stigma of receipt, monetary and nonmonetary costs of program participation, imperfect information, administrative barriers, and mismeasurement. The types of individuals who do and do not take up a program is argued to be determined by the joint distribution of gains and losses across those types, which ones face the largest administrative burden of participation and largest information deficits, and face more program operator error. There is a large body of evidence showing the importance of benefit gain and earnings losses from take-up but a smaller body of evidence on other factors, which shows that administrative barriers and costs, lack of information, and stigma all appear to be important for different programs. While there are no easy solutions to the problem of incomplete take-up, policies to at least lessen the problem are argued to be available, although generally not without increased government expenditure.

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The recession induced by the COVID-19 pandemic resulted in major declines in employment of women, both from the demand side as firms reduced employment and from the supply side resulting from school closures and the closing of many child care facilities. We provide projections of possible impacts of this reduction on less-educated women's future human capital framed within the traditional Mincerian model that implies that wage growth falls if a recession reduces the growth of work experience. We develop a new and modified form of the Mincerian log wage equation which we argue captures the effect of women's work experience on their human capital in a way superior to the traditional form of that equation. Using that modified form, we estimate the impact of recession-induced loss of work experience on wages. Our model, estimated on pre-COVID data, incorporates special features anticipated to be of importance in the pandemic, including the degree to which negative aggregate shocks occur to pandemic-specific industries, whether the impact of shocks varies by telecommuting occupation, and how the impact varies with the presence of preschool and school-age children who are affected by school and child-care facility closures. We find that wage losses one year out from 2020 are relatively modest on average, generally less than one percent, with the largest for married women without children in the home. But losses are greater for married women at young ages, mothers with very young children, and for those working in COVID-impacted industries. School and child care closures increase projected negative wage impacts for married mothers by an additional 50 percent.