This project asks how the racial composition of workers’ professional networks affect their wage growth and access to outside opportunities. Existing research has estimated that the inclusion of underrepresented workers in the U.S. economy since 1960 significantly contributed to U.S. GDP growth. Yet racial divides in earnings and opportunities persist. Understanding the sources of these gaps is critical for understanding growing income inequality and fostering broad-based growth. While many explanations have been proposed, relatively little is known about the extent of U.S. labor market segregation and its consequences today. This project will use restricted firm-level data to explore the role of workers’ professional networks in the persistence of race disparities in the U.S. labor market. Building on recent work showing that workers are able to renegotiate their wages when labor demand increases in their networks, and that referred workers are often similar to referrers in terms of age, gender, and race, the author proposes to estimate the impact of changes in the composition of the professional networks of workers to investigate whether the impact of an increase in local labor demand is sensitive to the size of the professional networks for underrepresented groups. This analysis will then be used to calibrate a search model that estimates the contribution of labor market segregation to the wage gap.
Archives: Grant
The Impact of Natural Disasters on Firm and Labor Dynamics
This project will explore the impact of natural disasters on small businesses and whether effects differ depending on the demographics of the entrepreneurs running those businesses. Understanding how the composition of local economies changes after disasters because of the demise of some firms and the startup of others can explain a lot about what makes a particular place more or less resilient. Research shows that there is a lot of startup activity following a natural disaster, but this could be misleading if it is generated from rebuilding and doesn’t fully factor in displaced workers or shuttered businesses, which will have larger long-term effects. This project will look at the impact of natural disasters on firms’ entry/exit, survival, and financial performances. It will also look at whether these effects vary by entrepreneur demographics, their socioeconomic backgrounds, the types of firms and in which industries, market power, and competitive setting.
Low-Income Borrowers and Payday Lenders: A Qualitative Study
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.
Inequality and Targeting of Disaggregated Policy
This project explores the question of how policy shocks propagate through the economy. The researchers will build a large dataset using Danish Bank and Danish government administrative data to build matrices of income, consumption, and production in different regions and sectors, as well as how income, consumption, and production in different regions and sectors are interconnected. This “disaggregated economic account” will be used to trace out how a shock that hits one part of the economy propagates to other parts and determine the aggregate impact of the shock. The resulting model will help define optimal policy responses to different kinds of shocks, to measure how certain shocks affect income inequality and growth, and to identify the most important channels that propagate shocks. Tracing how a shock in one sector filters through the economy is only possible with this type of administrative data linked in this way.
Municipal Neighborhood Effects: Estimating the Independent Association between Childhood Jurisdiction and Life Outcomes
This project examines associations between municipality of residence during childhood and upward mobility. Notably, the project creates a new dataset by identifying municipalities across the United States and documenting and categorizing municipal policies for comparison. Research on municipalities is hampered because a single repository or dataset containing all municipalities and their characteristics and policies does not exist. In addition to the potential data contribution, from a policy solution standpoint, understanding municipal policy is critically important. It is neither practical nor reasonable to propose solutions for mobility that operate just at the neighborhood or commuting-zone level, outside of the context of local governance. City and county governments need to know what they can reasonably do within their jurisdictions in order to increase mobility. While the proposed study, like many others in this space, does not attempt to identify causality, the descriptive work has the potential to be telling since it could provide municipalities with evidence of how they are succeeding or failing at supporting upward mobility for their residents.
HBCU Enrollment and Longer-Term Outcomes
This proposal will utilize a large and comprehensive dataset to evaluate whether historically Black colleges and universities, or HBCUs, can narrow or close racial gaps on numerous measures of economic well-being, not just typical measures such as income. The dataset links College Board SAT data with credit bureau data and National Student Clearinghouse data. It includes students who took the SATs between 2004 and 2010, tracking them from high school through college, and will allow the authors to look at financial outcomes at age 30. Using these data, the authors will compare the longer-term outcomes for Black students who attend these schools versus similar students who applied to but did not attend one. The authors will explore several outcomes, including those where racial disparities exist, such as college-related debt, other forms of debt, and whether the individual has a mortgage (a proxy for homeownership). The credit data also give a more complete picture of income than earnings since it covers all types of income. Existing research shows how important social supports and social capital are to economic mobility. This project will shed light on the distinctive social and psychological value-added features of historically Black colleges and universities.
Labor Unions and Workplace Safety Before and During the COVID-19 Pandemic
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.
The Effects of Tech M&As on Innovation Incentives
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.
The Price Effects of Market Power
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.
The Effects of the Child Tax Credit on the Economic Wellbeing of Families with Low Incomes
This project examines the effects of the expanded refundable Child Tax Credit on household economic well-being, including material hardship, debt, savings, and employment, with a focus on racial implications. The monthly Child Tax Credit, issued during the COVID-19 pandemic, was novel and represented a departure from how the United States typically provides assistance to low-income families via yearly cash transfers through the tax system or in-kind provisions, such as through the Supplemental Nutrition Assistance Program. The expanded Child Tax Credit also was short-lived, issued only from July 2021 to December 2021. Existing evidence, including some from this proposed study’s investigators, reveals the monthly CTC payments reduced poverty, and especially child poverty, despite high underemployment or unemployment during the COVID-19 pandemic. The contribution of this project is its investigation of nonincome outcomes, such as material hardship and food insecurity rates relative to the monthly CTC payments. The project also will consider racialized effects, which are important since early evidence reveals that Black and Latino families were disproportionately less likely to receive, or were delayed in receipt of, the monthly CTC payments. The study will rely on data from an app from Propel Inc., a financial services firm serving low-income Americans. The app allows low-income families manage their SNAP benefits.