During the COVID-19 lockdowns, forgivable loans or grants to firms became a large-scale countercyclical income support strategy. This project studies the effect of such programs on short- and medium-run outcomes for U.S. firms and workers using $125 million in grants to 12,129 small businesses administered by the state of Minnesota via random lottery. The dataset will link the full set of program applicants and awardees to business and individual tax records and to credit histories. The authors will use the random assignment of grants to investigate the causal impact of loans on firm employment and payroll, borrowing and delinquency, and worker attachment to recipient firms. The Minnesota program closely mirrors the design of the federal Paycheck Protection Program but provides for a much cleaner research design due to the random lottery for recipients. Supporting small businesses during economic downturns is critical, but more evidence is needed to inform effective policy design of direct support to firms. This research promises to provide such evidence.

This project will explore the effect of large-scale business openings subsidized with tax and related incentives to estimate the effect of these public investments on labor markets—not just on wages, but also on the skills demanded by employers post-opening. The author will use data on government subsidized projects from 2013–2019, including manufacturing, distribution centers, headquarters and data centers, as well as runner-up locations for these projects, to help identify the causal effect of the “million-dollar projects.” This research will provide new insights on the spillover effects of public investments when designing place-based policy.

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 explores the causes and implications of the resilience of public-sector unions after the U.S. Supreme Court’s decision in Janus v. AFSCME, which effectively made the entire public sector right-to-work. The research team will field a national survey of 4,000 full-time, nonmanagerial, union-eligible public-sector workers to shed light on two questions: Why didn’t the Supreme Court decision in Janus cause a large decrease in public-sector union membership? And what can spark increased unionization efforts among public-sector workers in the United States? This project is poised to inform what options there may be for boosting union membership in the public sector.

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.