As the U.S. economy emerges from the coronavirus recession, public policies to support women’s ability to return to work and stay in the workforce will be necessary for economic recovery. This study seeks to assess if paid sick leave reduces short-term income volatility and increases long-term economic security through improved job attachment among women, particularly those who are less likely to have access to paid sick leave in the absence of paid sick leave mandates. Using the American Community Survey, Slopen will conduct analyses at the state and county level using the five states and 21 counties that implemented paid sick leave as the treatment group. She will exploit the variation in the timing of the implementation of mandates at the state or county level using a difference-in-differences approach to estimate the effect of paid sick leave mandates on women’s labor force participation, continuity of employment, weekly hours worked, income, and poverty. She also will identify effects on subpopulations most likely to lack access to paid sick leave in the absence of mandates.

This project seeks to answer two questions: What are the welfare effects of third-degree price discrimination, and what are the effects of third-degree price discrimination on the take-up of newer and better technologies? Goel will address this question in the context of a particular type of implantable medical device: defibrillators. The implantable medical device industry has three features that make it a compelling setting to study. First, manufacturers are able to prevent hospitals from disclosing prices, allowing them to charge different prices for the same device in different hospitals. Second, the industry is very concentrated, with more than 95 percent of the market share captured by just four firms. And third, there is a lot of product variety. On average, a manufacturer offers six brands of this particular device per year from 2014–2019. Goel will utilize a rich dataset with purchase volumes, prices, and characteristics of defibrillators, and will combine this with approval information from the U.S. Food and Drug Administration. She will then estimate a model of supply and demand, and conduct a counterfactual analysis in which third-degree price discrimination is banned in order to understand the dynamics of price discrimination.

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.

There is a significant racial divide in homeownership, as well as wealth, in the United States. In 2018, 73 percent of White householders owned their homes, compared to only 42 percent of Black householders, and the typical White household owned 20 times as much wealth as the typical Black household. A number of factors may explain this disparity, but one key contributor is the positive association between wealth and the ability of renters to transition to homeownership. This project will consider nonparental family members as potential sources of financial assistance to prospective homeowners. Utilizing the Panel Study of Income Dynamics, Bucknor will measure household wealth, parental wealth, grandparental wealth, and extended-family wealth, including businesses owned, transaction accounts, real estate, stocks, vehicles, home equity, and other assets, minus all debts. This research is poised to add to our understanding of intergenerational transmission of wealth and the far-reaching impacts of structural racism, and give insight into policies that may be effective in addressing persistent racial wealth inequality.

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.

There is a large literature exploring the tension between increasing minimum wages in order to raise the hourly wages of workers and having these increases offset by reductions in overall employment or hours worked by low-wage employees. Understanding the distributional impacts of minimum wage increases is therefore essential. This project seeks to provide some of the first empirical evidence on how minimum wage reforms change firms’ occupational composition, distribution of hours, and scheduling practices. To do this, the authors will leverage shift-level microdata for the near-universe of employees and contract workers at U.S. nursing homes from the Payroll Based Journal program. The nursing home industry is an attractive setting for this research as it is a major employer of low-wage workers, especially certified nursing assistants, who provide the majority of patient care at nursing homes, are typically paid at or just above the minimum wage, and the majority of whom are immigrants and women of color. Moreover, many low-wage staff intend to work in the industry throughout their careers, in stark contrast to more heavily studied low-wage industries such as restaurants and retail, where many workers expect to leave the industry quickly. Accordingly, wage policies in the nursing home sector have the potential to not only affect the economic well-being of low-income workers but also shape gender and racial pay divides. In addition, the nursing home industry is of particular interest to regulators and policymakers since Medicaid and Medicare finance the vast majority of long-term care, and policies that affect the wages of employees in this sector will correspondingly affect state and federal budgets. Employment or composition changes may also have important consequences for quality of care.