Since the 1976 merger of the Raleigh City Schools and the Wake County Schools in North Carolina, the Wake County Public School System has maintained a commitment to school diversity.  For much of the history of the district’s student assignment policy, leadership focused on ensuring diversity in schools by informing school assignment with students’ race, such that individual schools’ compositions reflected the composition of the district. Beginning in the 2000-01 school year, student socioeconomic status (SES) rather than race informed school assignment, with students’ eligibility for free or reduced-price lunch (FRPL) as a proxy for SES. In addition, the district sought to ensure that no school served an overwhelming concentration of students scoring below grade level on the state’s reading assessment. Consequently, the district implemented a student assignment strategy through which no school served a student body made up of more than 40 percent FRPL students and 25 percent students reading below grade level, and this policy guided the district for the next ten years. In this study, we investigate outcomes associated with the SES-based student assignment policy over this period.

Under the assignment plan, socioeconomic integration targets were achieved by reassigning all students who lived in the same “node” (a geographic area, housing development, etc.) as a group to a school with a different socioeconomic composition from the composition of their node. The decision about which nodes to reassign was reached with information on the distance to the nearest socioeconomically different schools (with capacity), with community and school board feedback. Nevertheless, students in reassigned nodes were essentially indistinguishable from students living across the street who were not reassigned.

We exploit this differential treatment of students to isolate the causal impact of the assignment policy. We compare the outcomes of students assigned to higher-SES schools with students identical in all other ways except school assignment. We employ empirical matching strategies to match nodes of reassigned students with observationally similar students from non-reassigned nodes. These matching strategies take advantage of rich, observable node-level characteristics, including the share of students qualifying for FRPL, the node’s distance from the newly assigned school, and the average level of student achievement as well as the extent of variation in achievement among students in given nodes. Having matched each reassigned node, we use regression to compare relevant outcomes, including student achievement, within matched pairs to examine whether outcomes are different for reassigned students and whether variation in the extent of differences across matched pairs relates to differences in the characteristics of the schools to which students were assigned. Preliminary analysis reveals that over the years examined, between 1 and 5 percent of students were selected for reassignment, and compliance with reassignment occurred at a rate of about 60 percent.  These figures highlight the benefit of student-level data for understanding the impact of reassignment on subsequent student outcomes.

This work will inform the district as it considers modifying its existing assignment policy, as well as the nation, particularly given recent legal challenges to proactive school assignment strategies.