Diversity and Transportation in School Choice

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This award funds theoretical and empirical research on school assignment mechanisms found in many US cities. School choice programs aspire to weaken the link between the housing market and access to good schools. Given existing evidence that, all else equal, students prefer to attend schools close to home, choice systems struggle to avoid scenarios where neighborhoods with good schools fill up only with students who live nearby, shutting out those who live in other parts of town. Opening up schools to pupils throughout the district, however, requires that the district to absorb transportation costs, spending funds which may otherwise be used to educate children. The projects outlined here are unified by their focus on ways to resolve conflicts between increasing access, ensuring diversity, and assigning students close to home. One strategy districts use to adjudicate claims between those from inside and outside the neighborhood is to apply a neighborhood priority for only a fraction of school seats. The PIs develop theoretical results on matching algorithms with slot-specific priority structures to cover this scenario. They also investigate whether mechanisms with richer message spaces, such as allowing students to be considered for schools either with or without busing, would accommodate a reduction in transportation costs. Finally, another important aspect of these choice plans involves developing the set of schools an applicant may rank. For instance, it may be possible to define choice menus in a flexible way so that students have options close to home and each student also has access to high quality schools. A plan with these features was recently adopted in Boston in 2013 based on our earlier work. Another project examines whether flexible choice menus provide a satisfactory compromise using data from the new choice system. The research will compare the newly submitted choices under the new choice menus to earlier forecasts in a genuine out-of-sample validation that will inform the strengths and limitations of counterfactual analysis based on structural demand models.