This project explores how low-income people with immediate needs for cash make borrowing decisions in states where payday lending is heavily restricted versus states where it is not. It takes a qualitative approach to exploring the experiential processes that unfold across varying state policy contexts. As the author notes, there is a burgeoning line of scholarship on payday loans and states’ attempts to restrict them, but with mixed evidence on the effects on low-income borrowers. On one hand, these loans come with predatory lending rates that are often compounded for borrowers who are unable to pay back the loan in the original period and therefore roll it over, incurring more fees and often resulting in the borrower owing many times over what they originally received. On the other hand, credit is highly constrained for low-income individuals, with payday loans filling the gap. Yet there remains neither a consensus on the utility of such loans for low-income borrowers nor an understanding of how low-income individuals make decisions about borrowing. This gap limits policymakers from addressing the dual needs of credit access for low-income borrowers and the need to reduce the deleterious effects of payday lending, a gap this research will shed light on.

This project extends ongoing work by this research team on nursing home unionization and COVID-19 preparedness. The interdisciplinary team takes a mixed-methods approach to estimate the causal link between collective bargaining and workplace safety prior to and during the pandemic. The researchers have built a proprietary dataset of union status of all 15,000 nursing homes in the United States and merged it with publicly available Center for Medicare and Medicaid Services workplace-level data on COVID-19 outcomes in nursing homes. They will use this dataset to examine the impact of unionization on health and injury outcomes (and racial differences) before and during COVID-19 in the 2016–2021 period. Using an event-study difference-in-difference framework will allow them to capture the validity of parallel trends assumptions, and the proposed regression discontinuity design will help to establish the causal effect of unionization on worker COVID-19 infection outcomes. This is an important question that has significant resonance right now, as we are seeing a resurgence of union activity among major employers.

This project seeks to extend research on “deaths of despair” to look specifically at the causes of such deaths for Native Americans, and Native American women and girls in particular. Deaths of despair among Native Americans are proportionately higher than among any other group in the United States and have increased at almost twice the rate of non-Hispanic White Americans. Are the predictors of a death of despair for White constituents, especially men (joblessness, high rates of unemployment), different than those for Native American women and girls? The project will study this in the context of fracking. Preliminary analysis provides compelling, suggestive evidence that higher rates of employment and earnings among non-Hispanic White men due to extraction booms, measured by the fracking industry and building on existing literature, in proximity to Native lands and to Native American girls and women likely induces more human trafficking activity that disproportionately affects Native women and girls. In turn, this may also induce behaviors to “cope” with such contexts, such as increased alcohol and substance use and suicides among Native women and girls. The authors convincingly argue that what might reduce deaths of despair (jobs and higher wages) for one group (non-Hispanic White men) might result in higher rates of deaths of despair for another marginalized group, Native women and girls.

This project aims to provide an exhaustive analysis of how pharmaceutical mergers and acquisitions affect market competition and prices of patent-protected branded drugs involved in the deal. So far, little direct evidence exists about the impact of mergers and acquisitions activity on pharmaceutical market outcomes, partly because reliable data on prices and ownership of drugs is very difficult to obtain. The scholars will assemble a comprehensive dataset tracking the ownership of new products. This will be one of the major contributions of this project since there are no data sources that systematically track the marketing rights of each pharmaceutical product. The project examines whether prices, sales, and formulary coverage of acquired products increase after acquisition and, if so, what types of acquisitions are more likely to lead to changes in these market outcomes. This project will be the first to examine the differences in how list and net prices of pharmaceuticals respond to changes in market structure and competition. It also asks why market outcomes change. Economic theory predicts that within-market (substitute products) mergers will lead to higher prices. More recent evidence suggests that cross-market (noncompeting products) mergers also may generate upward pricing pressure in markets. The project tests these theories in the context of the pharmaceutical market. It also explores alternative explanations, such as shifts in marketing strategy, by incorporating advertising data into the analysis. Finally, the project also investigates anticompetitive effects of acquisitions in the patent-protected branded drugs market and what types of deals are more likely to have an anticompetitive effect.

This project is looking at the effects of “infant acquisitions,” or firms acquiring startups, on the incentives for startups to innovate, and the amount of overall innovation in the technology sector. It will empirically study the impact of megafirms’ tech acquisitions on venture investment by calculating the number of ventures funded and total dollars raised, and patent activities. The effect of large incumbents' acquisitions of startups on innovation has been a major concern among policymakers partly because it may have a negative effect on future investment in venture capital and innovation. Restrictions on tech mergers and acquisitions have been proposed in Europe and in the United States, yet there is still no clear evidence on how they affect venture capital investment. The project will combine three data sources: S&P Global Market Intelligence on firm taxonomy; Crunchbase data on investment deals in tech ventures; and PatentViews open-source data on patents. The combined data sources allow the researchers to paint a fuller picture of each firm’s relative position in the business and technology spaces.

This project takes a macroeconomic approach to market power. The authors will use U.S. Bureau of Labor Statistics microdata on monthly prices to study how market power affects prices for the whole U.S. economy, not just one sector. Past work has looked at mark-ups and concentration as a proxy for price, but in principle, this could help address the fundamental question of whether market power or efficiency is driving increased mark-ups. This project would provide new evidence on the linkage between market concentration and margins across industries and within industries. It would also provide evidence on how import cost shocks lead to the pass-through of those shocks to the prices paid by final consumers. The authors plan to infer market power from the degree of pass-through. A main innovation in this study is the use of novel data, which record price for different sectors.