There is increasing evidence of monopsony power in labor markets, with implications of lower wages and higher inequality. One popular policy recommendation is to constrain such monopsony power through more organized unions of workers, such as in local bargaining councils—collections of trade unions and employers representing specific industry-regions that consultatively bargain over and set minimum wages and working conditions for those industry-regions. This project will study the effect of such “sectoral bargaining” using South African data. Using matched employer-employee tax data from the South African Revenue Service, Bassier will match these agreements to firms as demarcated by industry and location. There are currently 39 legally recognized bargaining councils in South Africa, each covering a specific industry-region. Bargaining councils are estimated to cover 40 percent of workers in the formal sector in South Africa, concentrated mainly in the manufacturing, construction, trade, and transport industries in addition to covering the public sector. This research could give insight into how sectoral bargaining could improve worker power and mitigate the effects of monopsonistic labor markets.

This project investigates the causal effects of discriminatory assessment practices introduced by the New Deal-era federal agency, the Home Owners’ Loan Corporation. Specifically, the two researchers plan to examine HOLC’s systematic evaluation of neighborhoods and the maps it produced based on credit risk. Research has already led to the understanding that HOLC practices were a type of institutional discrimination. Data collected by the two researchers show that in 1930, about 86 percent of Black Americans lived in areas deemed hazardous (denoted in red on the maps, hence the term “redlining”) while almost 98 percent of the population in higher-rated areas was White. This research will measure how grade assignments affected the evolution of home values, income composition, and residential segregation in the short run and the long run. They will tackle the question by exploiting the fact that only cities over a certain population threshold were affected by the program. They will utilize a machine-learning algorithm to compare redlined neighborhoods with those that would have been redlined had the city been large enough to be affected by the program.

This project will use longitudinal data from two states to explore racial disparities in access to family child care centers by looking at rates of homeownership and disparities in homeownership by race. Family child care centers—licensed child care centers located within an operator’s home—make up a declining but still substantial proportion of the supply of formal child care. There are many obstacles to licensing a family child care center in a rental property, so areas with low rates of homeownership may experience a lack of access to this often more affordable child care option. Family child care centers also tend to have more flexible hours, making them especially valuable for parents working irregular or unpredictable schedules. Borowsky will conduct a market-definition analysis intended to approximate regions of common demand and supply. He will then evaluate the extent to which low rates of homeownership in a region are associated with low supply of family child care centers.

Understanding the degree to which, and how, hurricanes have had disparate effects across disadvantaged and advantaged groups in the United States is key to policymakers’ ability to craft climate policy that ensures disadvantaged communities do not bear the brunt of our warming world. Most of the literature in this area has focused on average impacts, with relatively little attention paid to heterogeneity. But even in cases where no negative impacts of natural disasters are found, on average, some subgroups may experience substantial negative effects. This project leverages newly linked administrative tax data from the IRS and demographic information from the American Community Survey and decennial census with exogenous variation in individual-level exposure to all hurricanes in the United States between 1995 and 2019. The analysis seeks to uncover a deeper understanding of the consequences of and responses to hurricanes, and how these effects differ across socioeconomic and demographic groups.

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.

An estimated 7.5 million children under 6 years old are cared for by home-based child care providers each year, which represents the majority of young children in regular nonparental care arrangements in the United States. Home-based child care programs are more affordable and accessible to a broad range of families, especially low-income, Black and Latinx, and rural families. The pandemic has drawn attention to longstanding racialized inequities in access to child care and the structural inequalities that are perpetuated due to insufficient investment in the home-based child care sector. This project will document trends over time (before, during, and after the pandemic) in access to child care subsidies for home-based care providers using administrative records data for the state of Illinois, paying particular attention to the racial composition of those receiving child care subsidies and those who serve racially diverse and economically disadvantaged families through the child care subsidy program. The analysis of the administrative records will be able to show how licensed and unlicensed providers' access to child care subsidies were affected by the pandemic, compared with one another and compared with center-based care. The two researchers will augment this analysis with in-depth interviews with home-based care providers. These qualitative interviews will explore how home-based care providers fared during the pandemic.