Online privacy protection has gained momentum in recent years and has prompted both government regulations and private-sector initiatives. A central element of this movement is the removal of third-party cookies from web browsers, which are widely employed to track online user behavior and implement targeted ads. 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 the phase-out of third-party cookies on Chrome, the market-leading browser. The counterfactual analysis suggests that an outright ban would reduce overall publisher revenue by 30% and advertiser surplus by 16%. 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 advantages over their competitors and gain a larger surplus from the ban.

This paper studies whether commitment devices mitigate self-control problems in consumer credit markets. Using data from a major fintech lender, we analyze a refinancing policy that introduced a "direct-pay" option, under which funds are sent directly to creditors rather than borrowers. A difference-in-differences design shows that the policy reduces defaults among eligible borrowers by 11%, while adopters cut default risk by roughly half. We then estimate a structural model of borrowing and repayment behavior. Counterfactuals suggest that self-control frictions account for about 35% of pre-policy defaults. Net of borrower selection and interest-rate incentives, commitment meaningfully improves repayment outcomes.

This paper 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 compatibility. 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 resulted in significant creative misalignment between authors and publishers. The merger also triggered 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 consumer markets. This research extends merger evaluation beyond consumer impact, providing a framework for analyzing the broader consequences of mergers on labor markets characterized by worker-firm complementarities.

This paper 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 an endogenous network formation model in which 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. These findings highlight the economic value of informal relationships and offer new empirical tools for measuring network effects in private capital markets.

Where fiscal capacity is weak, disorder and bad institutions reinforce each other: crisis raises the return to the institution, and the institution keeps disorder in supply. I study that trap when the bad institution is the sale of office in late Qing China. A location recusal rule barred officials from serving in their home provinces, so the two legs fall on different units: origin-side purchase captures the fiscal response to crisis, and destination-side roster composition captures the governance consequence. Linking historical records of personnel and unrest, I find that serious unrest demanding revenue expansion was associated with more first appointments of purchased officials; prefectures that then received a more heavily purchased roster recorded more serious unrest. The sale of office eased a revenue shortfall only by pricing local authority; that composition then fed disorder, and the trap remained.