Dynamic Spatial Competition in Early Education: an Equilibrium Analysis of the Preschool Market in Pennsylvania (Draft) July 2026
IIOC Rising Star prize 2023, EARIE Young Economist Essay Award 2023
High-quality preschool generates large social returns, yet U.S. preschool markets feature unequal access, high prices, and low quality. Using Pennsylvania data, I develop and estimate a dynamic spatial competition model of pricing, entry, exit, and quality investment. I evaluate broader demand subsidies and increased quality-tiered reimbursements in the short and medium run. Broader subsidies raise middle-income enrollment and, over time, high-quality supply, but price increases push some low-income children out of preschool. By contrast, quality reimbursements raise low-income children’s high-quality enrollment, while induced investment expands access for unsubsidized families. Equilibrium marginal values of public funds exceed one for both policies.
Inefficiencies in Local Infrastructure: Evidence from Drinking Water in California with Giulia Brancaccio and Karam Kang (Draft) April 2026
Local elected officials oversee critical infrastructure investments, yet limited electoral competition may weaken the alignment between local policy and residents’ welfare. Using new data on investment and performance for California’s drinking-water municipal utilities, we document that jurisdictions with weaker electoral competition exhibit higher water pollution and respond less to public investment aid. We then build and estimate a dynamic model in which residents differentially value water quality and vote accordingly, while office-seeking politicians weigh administrative costs against re-election prospects when choosing investments. Residents’ preferences are identified from housing transactions at jurisdiction boundaries and electoral incentives are identified by exploiting variation in voter welfare gains from investment. Counterfactual increases in accountability reallocate investment toward high-need jurisdictions, reduce pollution, and generate progressive welfare gains. Limited accountability also dampens the effectiveness of federal and state subsidies by diverting funds away from high-return investments.
Wait Times for Surgery in the U.S.: Measurement and Allocative Efficiency in Private Insurance with Michael Dickstein and Guillaume Fréchette
In the face of limited health care resources, waiting time often serves as a rationing mechanism in health systems around the world. We evaluate the efficiency and equity consequences of rationing via queues in the context of surgical care. Focusing on the U.S. private insurance market, we first develop a new measure of wait time that captures the complete patient trajectory—including visits for primary care, laboratory testing, and medical imaging—along the path to surgery. Exploiting exogenous variation due to weekly congestion within a patient’s insurance network, we show that patients who wait a month more spend 1% more on hospital care, are 1.1% more likely to be readmitted to a hospital, and fill 2.6% more opioid prescriptions in the six months following a surgery. The effects of waiting on hospital outcomes are more pronounced for surgeries that follow a cancer diagnosis, while the effects on opioids are largest for orthopedic surgeries. We further quantify misallocation of wait times relative to the planner’s ideal. We identify heterogeneous effects of waiting, but those patient groups who suffer the highest costs from delay do not uniformly experience shorter waits. We illustrate how positive prioritization—say, by providing physicians information on the treatment effects of waiting by patient type—could reduce payments to hospitals and improve patient health outcomes.
News Media Concentration and Content Diversity with Nicolas Longuet Marx and Marguerite Obolensky
The rise in political polarization over the recent years has fostered scrutiny of the structure of the news industry’ s influence on political outcomes. How should policymakers regulate news producers when they value news diversity and large publishers shape the ideological landscape? To answer this question, we develop an empirical model of competition for readership and advertisers between news producers. We recover the topic content and ideological positions of 200 major U.S. daily newspapers using recent advances in Natural Language Processing on millions of published articles. We find that over the period 2007-2017, the median newspaper in our sample got closer to the ideology of the Democratic party. Second, we embed these topics and ideal points in a demand model for differentiated products with heterogeneous readers. Our model shows that rich readers lean democrat and consume more news about social and political questions while the elderly are more conservative and care more about local news. Using the estimated demand model and data on advertising contracts and readership, we can recover the cost of producing each type of content. Given this model of news supply, we intend to use our framework to provide recommendations on antitrust rules weighing both consumer welfare and ideological diversity.