School Desegregation Through Redrawing of District Boundaries: Evidence From New Jersey

• In Event: Resident to Student Displacement: Examining Gentrification’s School Enrollment Implications in 21st-Century Los Angeles County

Abstract

U.S. school segregation is largely driven by patterns of residential segregation, as the vast majority of public school students attend the school they are geographically assigned to by the “attendance zone” set by their local school district (Monarrez, 2022; Richards, 2014). A long history of work in operations research and related fields has demonstrated that attendance zones can be redrawn to reduce racial segregation while meeting relevant constraints like minimizing student travel time (e.g., Smilowitz and Keppler, 2020; Gillani et al., 2023). However, such “within-district” policies are limited by the fact that approximately two-thirds of US school segregation occurs between school districts, and not between schools in the same district (e.g., Owens et al., 2016). This means that methods like redrawing attendance zones that do not alter school district lines may be less effective in many of the most segregated areas of the United States, such as the Northeast and Great Lakes Midwest, which often feature small districts (Fischel, 2009). While others have suggested that redrawing school district boundaries may be a promising policy to combat segregation, methodological evidence that alternative, realistic boundaries could be drawn is limited (e.g., Tractenberg et al., 2019; Gillani et al., 2023).
In this paper, I evaluate the effectiveness of redrawing school district lines for racial integration. I adapt methodological advances in simulation algorithms from the political redistricting and operations research literatures to create alternative school district boundaries under a wide range of scenarios. I employ Markov Chain Monte Carlo algorithms (Cannon et al., 2023) to draw realistic plans that incorporate minimal impacts on desirable characteristics like student travel distance to school and use only existing school facilities. I focus on New Jersey, where segregation of Black and Hispanic students from White and Asian students is among the worst in the country.
I find consistent evidence that redrawing school district lines could reduce nearly 40% of school segregation in the median New Jersey county. Further, the strong algorithmic constraints ensure these improvements require no new school infrastructure, make minimal changes to school enrollment, and keep students assigned to schools close to their homes. Plans that redraw attendance zones alone without changing district lines can reduce less than 5% of existing segregation in the median county. Put another way, my results demonstrate that existing school district boundaries, often drawn at the municipality-level, are a major barrier to integration.
Beyond demonstrating the extent of possibilities for integration under various policy scenarios, I also show that my proposed methodology can successfully integrate schools via “mergers” — consolidations of two or more adjacent districts. While state and local policymakers often voluntarily consider district consolidation for various administrative and financial reasons, my results demonstrate that mergers can be promising opportunities for promoting integration as well. These results have immediate local relevance — in 2022, Governor Phil Murphy signed S3488, a bill providing financial incentives for school districts to consolidate with others around them, which several efforts already under discussion.

Author

• Tyler Simko, Harvard University