Welcome! I am a Ph.D. Candidate in Economics at the California Institute of Technology (Caltech). Prior to Caltech, I received my B.A. in Economics and Mathematics from New York University Abu Dhabi (NYUAD).
I am an applied microeconomist and my research fields are industrial organization and finance. I study innovation, entrepreneurship, and antitrust regulations.
I am on the 2024-25 job market.
This paper introduces a novel empirical framework to assess the impact of market consolidation on labor markets, addressing growing concerns about labor market power in high-skilled industries. I develop a two-sided matching model that captures key features of labor market dynamics, including non-monetary preferences and 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. My structural estimation and counterfactual simulations reveal a trade-off between efficiency gains and redistributive effects. While the merger increased overall social welfare by improving matches for the merged company, it led to significant value shifts from other publishers and authors to the merged entity, with established authors experiencing the greatest losses. Notably, the merger's anticompetitive effects primarily arose in the labor market rather than affecting consumer welfare. 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.
Online privacy protection 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 recoup part of the loss. 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.
Networks play a key role in enabling information flow and improving fund performances in the venture capital (VC) industry. However, the often-used coinvestment networks do not reflect the true social connections, i.e., the informal and personal ties between VC partners. In this paper, I connect three VC networks—coinvestment, past, and social—and study their impact on VC performances with a structural network model. To address the endogeneity issues in this setting, I exploit exogenous variations in VC partners' past connections through professional and alumni networks. Furthermore, to incorporate social networks, I endogenize network formations and structurally recover the unobserved, underlying social connections from VCs' equilibrium performance outcomes. I find that social networks have a significant effect on VC performances. Counterfactual experiments suggest that the industry suffers in terms of both welfare and equality from this reliance on personal connections.
We analyze the effect of commitment devices designed to mitigate self-control problems in consumer credit markets. We draw on data from a large peer-to-peer (P2P) lending platform that introduced a "direct-pay" disbursement method for debt refinancing. Instead of dispersing cash, the direct-pay option transfers the loan directly to the borrower's existing creditors, with the goal of curbing impulsive, discretionary spending and screening for creditworthy borrowers. We find that borrowers who choose the direct-pay option achieve lower default rates compared to those who receive cash, suggesting success in attracting creditworthy borrowers and promoting responsible financial decisions. To analyze the complicated dynamics in this setting, we further develop and estimate a dynamic structural model of borrowers' disbursement choices and repayment outcomes. Using counterfactual simulations, we find that self-control problems account for 10% of the defaults in the market and that introducing the direct-pay option reduces default rates by 8%. We also explore alternative strategies for alleviating self-control problems in consumer lending.
I show that socioeconomic diversity and business representation in the government could contribute to the development of private enterprises. I study the institution of selling public offices during the late imperial Qing and show that it had a positive impact on early industrialization in China. In traditional Chinese society, merchants had relatively low social status and their businesses were frequently subject to government extortion and appropriation. By taking advantage of the office-selling program, the merchants were able to gain increased representation within the imperial bureaucracy. This, in turn, had a positive spillover effect on the private sector and early industrialization. I argue that changes in bureaucratic composition did not necessarily enhance the institutional environment for businesses. Instead, a more plausible mechanism is that purchasing officials had more progressive ideologies, preferences, and relationships with business interests, ultimately reducing the occurrences of arbitrary government interference and extortion.