This project will examine whether regulations increase firms’ labor market power and how changes in labor market structure vis-à-vis regulation affect worker outcomes. Some laws limit how much existing firms must comply with new regulations, while new firms must comply. One example is the Environmental Protection Agency’s New Source Review permitting requirements. The research team seeks to understand how this regulation affects employers’ labor market power. They will use data from the U.S. Census Bureau to link individual earnings with demographic and geographic information. Further, they will use data on counties and industries from the EPA to conduct a difference-in-difference analysis and a two-stage instrumental strategy to estimate the effect of regulation on local labor concentration and worker outcomes. This research will broadly inform regulatory design with worker outcomes in mind.

This project will examine the impact of supply-side child care investments on access to and stability of child care, as well as whether investments in child care vary by neighborhood. Utilizing novel mobile phone data, the authors plan to construct “real-time” measures of customer and worker flow, enabling an in-depth exploration of the dynamics of the child care workforce and consumers at a fine geographic scale with high frequency. They will then use this new data, along with data from a Minnesota grant program from the American Rescue Plan, to answer how funds given directly to providers affect the number and demographics of families served. This project will provide new evidence on the effects of investing in the supply of child care as opposed to supporting the demand side through vouchers or other subsidies.

This project seeks to understand the scale, scope, and spread of employee activism, workplace protest, and its impact on corporate stock prices in the United States. The author builds on an existing longitudinal dataset—the Dynamics of Collective Action by Stanford University—to understand employee activism and understand its use as an alternative to employees leaving the firm. She then will attempt to understand how employee activism spreads by tracking the occurrence of employee protests across industry or social movement networks. Finally, she examines how employee activism affects the share price of a corporation.

This project will first attempt to find the causal effect of exposure to the Special Supplemental Nutrition Program for Women, Infants, and Children in-utero and in childhood on one’s long-term outcomes. She will utilize a difference-in-difference design to exploit the variation in roll-out of WIC programs by county and evaluate educational attainment and economic self-sufficiency in adulthood. Using a regression discontinuity design, she will also test whether WIC funding was actually distributed to counties in a nonrandom way. In addition, she plans to examine whether and how the effect of WIC exposure is strengthened if one is also exposed to other large-scale public programs such as Head Start or the Supplemental Nutrition Assistance Program, contributing to our understanding of the long-run effects of potentially complementary income support programs.

This project will create a database of hospital mergers over the past 40 years. The database will detail the following: where health systems are merging or divesting to understand which areas/people (including demographic differences) are affected; whether that differs between for-profit and nonprofit hospitals; and whether higher-priced hospitals continue to provide higher-quality care. Beyond the dataset construction, the project will map areas with 2+, 3+, and 4+ hospitals and produce descriptive statistics at various geographic levels. The research team will track the growth in health systems that resulted from acquisitions by analyzing whether for-profit health systems were strategically acquiring hospitals in regions with more affluent, privately insured patients. This project will contribute to our understanding of the impacts of hospital mergers on equity, patient access, and quality of care.

This project will process job ads accessed through the National Labor Exchange Data Trust in a transparent and replicable way. The authors will use natural language processing tools to turn the job opening text into machine-readable data and will make the code available to other scholars.