This project will analyze how the labor market absorbs an increase in the minimum wage. Utilizing the case study of Costa Rica’s highly binding and relatively more comprehensive minimum wage policy that includes multiple wage floors based on workers’ skill levels, the author will use employer-employee microdata and administrative data to explain how minimum wages shape the earnings distribution and the labor market equilibrium.

Environmental inequity is intertwined with income inequality in a variety of ways. Demand for housing, for example, is higher in cleaner areas than in polluted ones, and, at the same time, evidence is accumulating that the communities in which children grow up have long-lasting impacts on their economic and other social outcomes. Other research finds that pollution exposure in utero and in early childhood can have lifelong effects on economic outcomes, suggesting pollution may be one important characteristic of the communities in which children grow up. This project engages with these issues by investigating the relationships among race/ethnicity, income, pollution, and human capital in Pittsburgh from 1910 to 2010. The two main areas of research are sorting by race that leads to inequality in pollution exposure, and the effects of childhood exposure to pollution on adult income. Although limited to Pittsburgh, it is a strategic site. Once considered "Hell with a lid off" because of the intense pollution arising from the furnaces of the steel industry, exposure to pollution used to be extremely high in the early 20th century but has since declined dramatically, allowing for the comparison over time. To do this, the authors will take advantage of never-before-used historical data and link it to demographic characteristics of individuals with known residential locations to pollution exposure, jobs, and future outcomes. An anonymized version of these data will be made publicly available, creating a valuable resource for future research.

This project will construct a database of new work from 1900 to 2020 by compiling a list of job titles from the U.S. Census Bureau’s Alphabetical Index of Occupations. Previous research on “new work” measures the introduction of new job titles beginning in 1964 and documents that new work is performed by high-skilled workers and in cities. Preliminary work in this project indicates that at least some of these previously documented patterns may not have been true in the middle of the 20th century. The authors’ aim is: to chart the evolution of new work over 12 decades; to assess the potentially varying importance of new work in job creation and skill demands during different epochs in this period; and to test a set of economic hypotheses about where and when new work arises. The project has the potential to provide insight into why the locus of job creation, measured in terms of occupations, industries, skill demands, and wage levels has varied across decades, and the role of new technologies in the creation of new work. In addition to compiling job titles from U.S. Census data, the researchers will link the text of patents to new job titles to explore the impact of new technologies on jobs, and will link to the Consumer Expenditure Survey to measure demand shifts for the relatively recent period (from 1980 onward) to test the hypothesis that demand shifts may lead to new work.

This research promises to advance our understanding of employment scarring by empirically teasing out the racial differences in long-term consequences of deep U.S. economic downturns for those who are relatively young when a recession hits. Focusing on the 1980 recession, which was both deep and long, the author will use a triple-difference approach to examine the recession’s long-run effects by comparing the incomes in adulthood of teens (ages 14 to 17) and young adults (ages 18 to 22) (first difference), living in counties with a more-severe versus less-severe recessions (second difference), who are Black or Hispanic versus White (third difference). Using the differences in the severity of the recession across local areas as an identifying variation, the author will utilize individual-level data from the National Longitudinal Survey of Youth in 1979, along with county-level location data with special access from the U.S. Bureau of Labor Statistics. The 1980 recession is far enough in the past to allow a study of the outcomes of the sample when individuals are in their mid-30s to mid-40s years of age. This research is poised to provide insight into the long-run effects of recessions on Black and Hispanic youth who resided in regions where the recession was deepest, adding nuance to our understanding of the “scarring” effects of recessions on young workers by adding a racial component. Givin the current economic situation, it is clear why this research is relevant to current policy debates.

Recent research finds that most, if not all, of the growth in earnings inequality in the United States may be explained by the growth in inequality across firms or establishments. This finding is consistent with research showing that workers in outsourced establishments—such as call centers, janitorial service companies, or security services—receive lower pay and benefits than those workers doing the same jobs but who are employed by lead or primary firms. But our knowledge of the extent and impact of outsourcing on a broader set of workers is limited, in large part because of data constraints. This study will provide evidence based on rigorous, quantitative analysis of the extent to which outsourcing has contributed to inequality in the United States. The study will rely on Longitudinal Employer-Household Dynamics data linked with American Community Suvey data and will use the methodology established in a previous paper based on German data. A key shortcoming of the LEHD data is that it does not have information on occupation. By linking to ACS data, the authors will be able to observe occupation for a subset of those in the LEHD dataset and to assess the effects of outsourcing on outcomes besides earnings—most critically, health insurance.

Previous research indicates that wealth inequality in the United States has increased since the mid-20th century and is much higher than income inequality. Wealth inequality is particularly worrisome since wealth provides many advantages, including securing against shocks and transferability to the next generation. Yet despite the relevance of wealth for our understanding of inequality and mobility, available data on wealth inequality is limited. This project will make an important contribution by drawing on tax data linked to external data on housing equity to overcome the limitations of survey data and by linking these data across generations within families and by generating geographic aggregates at small-scale geographical levels. This will allow the author to answer pressing questions, such as how concentrated wealth is locally and the stickiness of the wealth distribution across generations.