This project studies discrimination in online retail grocery stores. Do different consumers get charged a different price based on their perceived race? To answer this question, the author will implement a massive data collection exercise using web scraping. The data will combine firm-level data on products and prices with geography and aggregate socioeconomic indicators. This provides information on the underlying consumers in those areas. In the first phase of the project, the shopper’s race is based solely on geography. Future phases of the project will attempt to use browsing history to find racial differences in the shoppers. Web crawlers will be used to collect prices based on location to understand how online prices faced by consumers vary across socioeconomic and racial groups (imputed based on location). This research will identify whether online shopping allows retailers to price discriminate in ways that are harder to do in person.

This project will examine the effect of common ownership of technology startups by venture capitalists on those firms’ outcomes, such as shutdowns, exits via mergers or acquisitions, and Initial Public Offerings. The author seeks to contribute to the literature on how common ownership may impact competition and innovation by studying spillovers among technology startups in the portfolios of multiple venture capital firms. It will explore two questions: Do venture capitalists’ common ownership of technology startups have anticompetitive effects, and by affecting startups’ outcomes, can common ownership impact the market structure of technology industries? The focus on the technology sector allows the author to look at competition between like firms. Because venture capitalists have a lot of decision-making power, the author theorizes that the effects could be strong since venture capital firms focus on the innovation pipeline. Therefore, the project expects to speak to how competition can be stifled in the seed stages of venture funding. The project will proceed in three stages: Develop a stylized analytical model to highlight the main incentives at play; present reduced-form evidence on the effects of common ownership on startups’ outcomes; and develop a structural matching model of venture capital firms and startups.

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.

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.

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.

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.