Tyler Simko (Workshop in Applied Statistics)

This Week's Speaker

Tyler Simko (Department of Government), "School Desegregation by Redrawing District Boundaries: Evidence from New Jersey"

Abstract

Schools in the United States remain heavily segregated by race and income. Previous work demonstrates districts can reduce segregation between their schools with policies like redrawing attendance zones. Yet, the promise of such policies in many areas is limited by the fact that most school segregation occurs between school districts, and not between schools in the same district. I adapt Markov Chain Monte Carlo (MCMC) algorithms from political redistricting methodology to redraw school district boundaries that decrease segregation while maintaining desirable criteria like distance to school and using only existing school facilities. Focusing on New Jersey, where the segregation of Black and Hispanic students from White and Asian students is among the worst in the country, I demonstrate that redrawing school districts could reduce nearly 40% of existing segregation in the median New Jersey county, compared to less than 5% for redrawing attendance zones alone. Finally, I show how my proposed methodology can be applied to as few as two districts to reduce segregation in proposed “mergers,” a consolidation of small districts into one large district.

The Applied Statistics Workshop (Gov 3009) meets all academic year, Wednesdays, 12pm-1:30pm, in CGIS K354. This workshop is a forum for advanced graduate students, faculty, and visiting scholars to present and discuss methodological or empirical work in progress in an interdisciplinary setting. The workshop features a tour of Harvard's statistical innovations and applications with weekly stops in different fields and disciplines and includes occasional presentations by invited speakers.

More information is available at the Gov 3009 website: https://projects.iq.harvard.edu/applied.stats.workshop-gov3009

All interested Harvard affiliates are invited to attend.