Rachel Weber, Ph.D.
Stephanie Farmer, Ph.D.
Our study sheds light on the multiple, often conflicting interests that school districts must balance to plan for the capital needs of school-age populations. We investigate the factors that led to the closure of public schools in Chicago between 2000 and 2013. We reverse engineer the school closure decisions under two mayoral administrations by constructing a logit model that estimates the decision to close schools that were open as of 2000 as a function of physical, student, geographic, political, and neighborhood demographic factors. Our findings reveal that building utilization and student performance were predictors of these closures, but so was the race of students in each school. Specifically schools with larger shares of African American students had a higher probability of closure than schools with comparable test scores, locations, and utilization rates. Whether administrators explicitly considered the race of a school’s students in planning decisions or whether race in our model was a proxy for other unmeasured characteristics, the cumulative effect of technical decisions interacting with a racially differentiated education environment forced African American students and their families to bear the burden of these administrative disruptions.