This project examines the source of racial and ethnic inequality among the highly educated workforce in the United States by focusing on how educational credentials translate into U.S. labor market outcomes. The racial and ethnic wage divide is the largest and has expanded the most among highly educated workers, despite the fact that people of color in the United States are registering higher educational attainment. This project seeks to shed light on that by exploring how educational credentials translate into positions in the U.S. labor market and whether there are mismatches. Specifically, the project will investigate vertical and horizontal dimensions of education-occupation mismatches. Vertical mismatch refers to a mismatch between a worker's educational credentials and the level of education required for the occupation, such as a college graduate working as a retail sales associate. Horizontal mismatch refers to a mismatch between a worker's field of study and the type of education required for the occupation, for example, an engineering major working as an accountant. Lu will incorporate a demand-based measure of mismatch using online job-posting data compiled by Burning Glass Technologies, in addition to pooling two decades of nationally representative longitudinal data from the Survey of Income and Program Participation. She will investigate which dimensions of mismatch and which processes in the employment relationship drive racial and ethnic labor market inequality by exploring initial occupational allocation, subsequent occupational trajectory, and wage consequences of mismatch. Lu also will investigate how educational stratification factors into ethnic/racial disparities by looking at degree levels, fields of study, and college quality.

When humans undertake physically intensive tasks, the body must release heat to maintain a safe internal temperature. Worker safety organizations have strict guidelines for climate conditions under which it is safe for workers to perform strenuous manual labor. Rising temperatures from climate change will increase the risk of heat stress, making outdoor work more difficult. This study seeks to quantify these implications for capital accumulation, growth, and consumption by building a discrete time growth model of a closed economy. Unlike standard climate-economy models, Casey, Fried, and Gibson will account for differences in the way that climate affects the production of investment goods and services, compared to consumption goods and services. The model is designed to capture how vulnerability to climate change differs between consumption and investment sectors and how this difference evolves over time. It builds on past work by considering climate change as a determinant of productivity and considering a more disaggregated representation of the economy.

U.S. unemployment due to the onset of the coronavirus pandemic was widespread, as was U.S. economic insecurity. In terms of consumption, aggregate retail sales fell by 16 percent in April 2020, the largest fall on record. While retail spending recovered by mid-July, spending on services remained significantly depressed. In contrast to aggregate spending and U.S. labor market data, there is little real-time data on the impact of the coronavirus pandemic on consumer spending inequality. This project will use a new transaction-level, real-time dataset from Earnest Research to measure consumer spending inequality in the United States and assess the impact of the pandemic on consumption inequality. The dataset contains information on a panel of 6 million households and is updated with a delay of just 1 week. Abdelwahed and Robbins will be able to study the outflows of spending, as well as the inflows of payments from wages and salaries, stimulus payments, and other government transfers into the households’ accounts, allowing them to construct a series on various ratios of spending between the top and bottom percentiles in order to study changes in consumer spending inequality along the distribution. They will also measure the effects of the pandemic on consumption of those who lost their jobs or experienced lower incomes and will compare them to individuals who retained their jobs. Abdelwahed and Robbins will estimate the impact of government stimulus payments and Unemployment Insurance on consumer spending inequality and consumption patterns. The data will be released publicly at the aggregate level at both the state and county levels, and the two researchers plan to release quarterly reports, providing other researchers and policymakers with a valuable new data source.

Manufacturing jobs in the United States were widely considered to provide an important opportunity for less-educated workers to climb the U.S. economic ladder by offering high pay and stable careers. Research shows that the decline in manufacturing jobs since the 1970s coincided with a decline in upward mobility: Children born in the 1980s are less likely to grow up to earn as much as their parents than children born in the 1950s were, particularly in the post-industrial heartland. This project examines how increases in high-wage manufacturing work opportunity affected individual opportunity following the industrial mobilization for World War II. Garin and Rothbaum will exploit the fact that the siting of new plants was based on idiosyncratic short-run strategic considerations, leading to the construction of massive new publicly financed manufacturing plants in places that would not have been chosen by private firms. This historical dynamic gives rise to an ideal laboratory for studying how public investments that create high-wage employment impact upward mobility in the long run. The authors have digitized data on the locations of World War II manufacturing facilities using the War Production Board data books. Focusing on children who grew up in those areas in the 1940s, the two researchers will then trace those individuals’ income trajectories using the later-20th century Current Population Survey data linked to Social Security Administration-based income histories to examine mobility rates.

Johnson and Levine seek to understand how enforcement of government safety regulations affects workers’ wages and how the effect differs across groups of workers based on income, race, and ethnicity in the United States. While prior work focused on whether inspections lower subsequent workplace injuries and affect overall establishment payroll, scholars don’t know much, if anything, about the impact of inspections on individual workers’ wages. If regulatory enforcement lowers wages at the same time it improves health and safety, then the overall effects on worker well-being may be mixed. The two researchers will utilize the randomness of inspections by the U.S. Occupational Safety and Health Administration. This setting offers a unique opportunity to evaluate the effects of inspections as if examining a randomized controlled trial. Johnson and Levine plan to compare the trajectories of establishments (and workers at those establishments) randomly selected for inspection to those eligible but not selected for inspection. Inspection data will be linked to the Longitudinal Employer-Household Dynamics data series. In addition to yielding new evidence about the impact of safety and health regulatory enforcement on workers’ wages, this work also has the potential to contribute to the current literature on monopsony power in labor markets by investigating whether the effect of inspections on wages varies by local labor market concentration.

In virtually all areas of the U.S. healthcare service sector, physicians are barred from referring patients to entities in which they have an ownership stake. But this is not the case for the dialysis industry, which is exempt from such restrictions. Joint ventures between physicians and dialysis facilities exist at nearly 20 percent of facilities. This research will explore how physicians’ ownership ties with dialysis firms affect steering, spending, and outcomes. Using data obtained from a Freedom of Information Act request from the Centers for Medicare and Medicaid Services, Eliason, McDevitt, and Roberts will construct a first-of-its-kind dataset that tracks the ownership of dialysis facilities, including whether physicians have an ownership stake. They will add in data on dialysis providers and patients, including detailed Medicare claims and rich information on patient characteristics and health outcomes. An event-study analysis will allow the three researchers to test whether there is a clear trend-break in new patient arrivals and referrals when parties enter into a joint venture in order to examine how integration affects competition. The analysis will enable the researchers to study how patient caseloads and referrals at unintegrated facilities change after a nearby rival forms a joint venture, along with the impact of vertical integration on patient outcomes such as hospitalizations and mortality, as well as overall Medicare spending. Prior research has found that Black, Latinx, and low-income patients suffer disproportionately from kidney failure and often receive worse care, potentially making these groups especially vulnerable to providers’ growing market power and physicians’ conflicting interests.