Essays in Empirical Industrial Organization and Corporate Finance

Citation

Shi, Ke (2025) Essays in Empirical Industrial Organization and Corporate Finance. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/nb4s-x295. https://resolver.caltech.edu/CaltechTHESIS:05262025-173203112

Abstract

This thesis consists of three chapters.

Chapter 1 introduces a novel empirical framework to assess the impact of ownership consolidation on labor markets, addressing growing concerns about labor market power. I develop a two-sided matching model tailored to the creative labor force, a segment characterized by strong worker-firm complementarities. Applying this model to a major merger in the U.S. publishing industry, I leverage rich text data to analyze its effects on the author labor market. Counterfactual merger simulations reveal a trade-off between efficiency gains, creative misalignment, and redistributive effects. While the merger alleviated capacity constraints, post-merger integration led to significant creative misalignment between authors and publishers. The merger also induced substantial value transfers from competing publishers and authors to the merged entity, with established authors bearing the heaviest losses. Notably, the merger's anticompetitive effects manifested primarily in labor markets rather than in consumer markets. This research extends merger evaluation beyond consumer impact, offering a framework to analyze the broader consequences of mergers in labor markets characterized by worker-firm complementarities.

Chapter 2, coauthored with Miguel Alcobendas, Shunto J. Kobayashi, and Matthew Shum, studies the impact of online privacy protection, which has gained momentum in recent years and spurred both government regulations and private-sector initiatives. A centerpiece of this movement is the removal of third-party cookies, which are widely employed to track online user behavior and implement targeted ads, from web browsers. Using banner ad auction data from Yahoo, we study the effect of a third-party cookie ban on the online advertising market. We first document stylized facts about the value of third-party cookies to advertisers. Adopting a structural approach to recover advertisers' valuations from their bids in these auctions, we simulate a few counterfactual scenarios to quantify the impact of Google's plan to phase out third-party cookies from Chrome, its market-leading browser. Our counterfactual analysis suggests that an outright ban would reduce publisher revenue by 54% and advertiser surplus by 40%. The introduction of alternative tracking technologies under Google's Privacy Sandbox initiative would partially offset these losses. In either case, we find that big tech firms can leverage their informational advantage over their competitors and gain a larger surplus from the ban.

Chapter 3 examines how informal and formal networks shape performance in the venture capital (VC) industry. Using data on all U.S.-based VC investments from 1990 to 2009, supplemented with partner-level educational and employment histories from LinkedIn, I develop a structural framework that connects three types of networks: coinvestment ties, historical affiliations, and latent social connections. In the baseline model, VC performance is a function of peer performance, capturing network spillovers through a micro-founded production function. To address endogeneity in network formation, I extend the model using a two-step instrumental variables strategy that leverages variation in past professional and alumni ties. Finally, I introduce endogenous network formation where VCs strategically choose connections based on expected peer quality, allowing for the recovery of latent social networks from equilibrium outcomes. Across specifications, better-connected VCs exhibit significantly higher exit rates. Estimates from the endogenous model suggest that a 1% increase in social connectedness raises a VC's exit rate by 0.2 percentage points, while a 1% improvement in peer performance leads to a 0.74 percentage point increase in connection intensity. Informal relationships thus carry measurable economic weight, and the empirical approach developed here provides a new lens for identifying network effects in private capital markets.

Thesis Files