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 will leverage variations in implementation timing of the requirement in the Coronavirus Aid, Relief, and Economic Stimulus, or CARES, Act that employers notify recently separated workers of their eligibility for Unemployment Insurance. It seeks to causally identify whether notification improves the take-up of Unemployment Insurance with an emphasis on Black and Latino workers. The author will compile a database of states’ implementation of required separation notices by employers to employees by state and year. This project is expected to yield credible evidence regarding the efficacy of these employer separation notice requirements on the receipt of Unemployment Insurance. The project will further investigate whether such requirements close the racial divide in receiving Unemployment Insurance. Given known racialized disparities in receiving these benefits, the emphasis on this is critical. The distribution of information on UI eligibility as a mechanism in attenuating (or not) racial disparities would add to policymakers’ understanding of what is driving these disparities. In the case that separation notice requirements increase the take-up of Unemployment Insurance, the project has the potential to identify a relatively low-cost intervention with large payoffs. In the case that separation notice requirements do not improve UI take-up or close racial divides, policymakers may want to reconsider the universal requirements implemented as part of the CARES Act.

This project considers the interplay between paid and unpaid care work and the relationship between care work penalties and gender, race, and class inequalities. The author makes the novel argument that prior research does not sufficiently understand the combined effects of both paid and unpaid care work penalties and how they interact. To fill this gap, this project will develop a “care-work-systems” framework to determine how pay penalties for care work impact economic inequality. The project identifies that paid and unpaid care work penalties are often viewed as separate even though they impact each other. In addition to bringing these two skeins of research literature in conversation with one another, it will also bridge the research literatures in child care and eldercare, and integrate class, in addition to race and gender, into the analysis. In addition to the theoretical contribution, it proposes an empirical study to test this framework using panel data from three countries with different care infrastructures—the United States, the United Kingdom, and Germany—to help shed light on how policies and social structures play a role in generating paid and unpaid care work penalties.

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.