Knowledge that Transforms

I exploit a natural experiment in Indian schools to study how being integrated with poor students affects the social behaviors and academic outcomes of rich students. Using administrative data, lab and field experiments to measure outcomes, I find that having poor classmates makes rich students (i) more prosocial, generous, and egalitarian; and (ii) less likely to discriminate against poor students, and more willing to socialize with them. These effects are driven by personal interactions between rich and poor students. In contrast, I find mixed but overall modest impacts on rich students’ academic achievement.

We propose novel approaches to estimating student preferences with data from matching mechanisms, especially the Gale-Shapley deferred acceptance. Even if the mechanism is strategy-proof, assuming that students truthfully rank schools in applications may be restrictive. We show that when students are ranked strictly by some ex ante known priority index (e.g., test scores), stability is a plausible and weaker assumption, implying that every student is matched with her favorite school/college among those she qualifies for ex post. The methods are illustrated in simulations and applied to school choice in Paris. We discuss when each approach is more appropriate in real-life settings.

This paper presents a dynamic equilibrium model of a taxi market. The model is estimated using data from New York City yellow cabs. Two salient features by which most taxi markets deviate from the efficient market ideal are, first, matching frictions created by the need for both market sides to physically search for trading partners, and second, regulatory limitations to entry. To assess the importance of these features, we use the model to simulate the effect of changes in entry, alternative matching technologies, and different market density. We use the geographical features of the matching process to back out unobserved demand through a matching simulation. The matching function exhibits increasing returns to scale, which is important to understand the impact of changes in this market and has welfare implications. For instance, although alternative dispatch platforms can be more efficient than street-hailing, platform competition is harmful because it reduces effective density.