This project seeks to provide some of the first causal evidence on how concentration in the meat-processing industry affects producers, workers, and consumers across racial and income groups in the United States. Rising concentration has been especially salient in the meat-processing industry, and recent research connects market power in the product market with monopsony power in the labor market. This project will build and expand on that literature by measuring the effect of consolidation by meat processors on monopoly power in the input and product markets, and monopsony power in the labor market, and then assessing what the implications of these market conditions are on racial inequality, specifically farmer profits, conditions for workers, and prices for consumers.

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 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 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.