This paper evaluates the welfare costs induced by limiting the number of choices in deferred acceptance mechanisms. I show that when the number of choices is capped, some students have to be strategic and that increasing the size of the submittable list can result in better matches, and therefore lead to welfare improvement. I use Iranian college entrance dataset to estimate a novel discrete choice model for centralized university systems, in which I relax the independence of unobserved preference shocks assumption. I validate the model with out-of-sample data from a quasi-experimental policy change, in which the list cap was increased by 50 percent. In my counterfactual analysis, I calculate that a list cap of 10 choices instead of 100 would incur a 14.2 percent welfare loss. This is equivalent to a 453 km increase in the home-university distance, which is 2.6 times the average distance traveled by Iranian students. I also show that a more restrictive list cap does not affect students at the top and bottom of the ranking, but hurts students with average scores and benefits students in the lower quartile.

This paper explains why higher education inequality persists even in countries with free tertiary education systems. We argue that in systems with competitive admissions, free public universities may paradoxically exacerbate inequality by intensifying competition for test preparation and pre-college educational investments. Using nationally representative data, we demonstrate that students from higher-income backgrounds invest substantially in nationwide entrance exam preparation and attain higher ranks. Through an equilibrium model of educational investment and college choice, we show how this pre-college ”arms race” can lead to wealthy students dominating admission to selective universities, even in a tuition-free system. Our structural estimation reveals that making colleges completely free does not change the income distribution of students in highly selective programs. We further assess directed college subsidies as well as college preparation programs for lower-income studies. Our findings suggest that the equity goals of free higher education may be better served by targeted interventions that address underlying educational disparities rather than universal tuition subsidies.

This work aims to investigate the role of information sharing in labor market as a key determinant of temporal dynamics and suboptimality of educated labor supply using a dynamic choice model of college majors and jobs. Exploiting a directed search model of the labor market, choice dynamics are assessed in a network of potential workers who receive new information on their productivity in different industries and observe posted wages in skilled-labor sub-markets. The case of the Dot-Com boom effect on the enrollment of different college majors is studied. While the social network connectivity in different U.S. states is considered as the information diffusion criterion, the effect of wages on college majors' enrollment is examined exploiting a multinomial choice model. In the case where sub-market wages are derived from the competitive search equilibrium, difference between the semiparametric estimation results highlights the underestimation of wage effect on enrollment decisions.

We examine the differential effects of public and private transit modes on the sorting of individuals within a city. Our study focuses on the case of Houston, a sprawling metropolis that has experienced significant transportation developments in the past two decades, including the expansion of the Katy Freeway and the introduction of METRORail. Our findings indicate that high-income individuals tend to reside along the freeway, contributing to a suburban trend in Houston, whereas the introduction of public transit has attracted low-income individuals to its vicinity. Currently, we are working to assess the distributional welfare effects of different transit infrastructure modes using a quantitative spatial model, highlighting the important consideration of heterogeneous elasticities of commute choices to commute costs for different types of workers.

Peer effects in social networks have been extensively studied by economists, yet the specific characteristics of influencers who drive these effects remain underexplored. This research aims to identify and analyze the key characteristics of influencers within adolescent social networks, particularly those affecting smoking behaviors. Using data from the Add Health dataset, we estimate the peer effects on smoking initiation and apply a key-player policy to assess the impact of removing specific individuals from the network. Using the theoretical framework, we compute counterfactual smoking decisions in these altered networks, which allows us to identify the adolescents whose removal leads to the largest reduction in the number of smokers. We find that the most influential individuals, or "key players," are typically white girls with access to cigarettes at home and parents who smoke. These key players also tend to be more extroverted, with larger and more symmetrical friendship networks, highlighting the role of both social and environmental factors in shaping peer influence on smoking behavior.