Dynamic Spatial Competition in Early Education: an Equilibrium Analysis of the Preschool Market in Pennsylvania (Job Market Paper)
High-quality preschool is one of the most cost-effective educational interventions, yet the United States invests little in early childhood education. Recent policy discussions call for increasing preschool enrollment and raising the quality provided, especially for disadvantaged children, but equilibrium responses of private providers which make up most of the market generate trade-offs between these objectives. Supply expansion may lower incentives to invest in quality, and price responses to demand subsidies can increase the costs faced by non-subsidized parents. This paper develops a dynamic model of the preschool market to evaluate the effectiveness of policies at achieving these objectives. The model nests a static equilibrium model of spatial competition and preschool choice within a dynamic model of providers’ entry, exit and quality investments. I estimate this model using data on the universe of child-care centers in Pennsylvania. I use the model to simulate the aggregate and distributional consequences of proposed approaches to early education expansion. I find that policies focused on expanding supply raise access but decrease the quality children attend due to parents’ value for proximity. Demand subsidies generate market expansion, but on their own do not create sufficient incentives for providers to invest in quality. Among the simulated policies, the most cost-effective at expanding high-quality enrollment combine demand subsidies targeted to low-income families with financial support to providers serving disadvantaged children. These policies increase access by reducing exit of providers, and expand high-quality enrollment for low-income children through subsidies. In addition, these targeted policies generate spillovers to the educational quality of non-targeted families by creating incentives for centers to invest in quality.
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.