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.

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.

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.

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.

Progressive taxation is highly polarized in the United States because some states have millionaire taxes while others have no state income tax at all. The 2017 tax reform legislation, the Tax Cuts and Jobs Act, amplified these differences by capping the state and local tax, or SALT, deduction. This effectively reduced top tax rates in some states while increasing them in others, leading some, including governors, to worry that this new tax differential will set off a wave of millionaire tax flight and a new “race to the bottom” in state taxes on the rich. Using confidential data from IRS tax returns, the author will examine elite mobility and embeddedness in the wake of the 2017 tax reform. The author seeks to understand if the rich are more likely to move when their tax rates are high, whether the TCJA-induced tax differential led to greater migration, and, conditional on moving, how much this tax reform increased the likelihood that moves are to lower-tax destinations. These questions are of great importance as state and local taxes are essential for states’ capacity to provide services and alleviate inequality. And while previous work shows the existence of effects among particular job classes, this paper would provide policy-relevant estimates for the universe of high-earners in recent U.S. history.