Centre for Development Economics,
Delhi School of Economics
ANNOUNCE A SEMINAR
Disruptive Interactions: Long-run Peer Effects of Disciplinary Schools
Anjali Priya Verma (Department of Economics, The University of Texas at Austin)
(joint with A. Yonah Mesiselman)
Thursday,2 December 2021, 6:00 PM IST.
This paper studies the long-run effects of disruptive peers in disciplinary schools on the educational and labor market outcomes of students placed at these institutions. Evidence suggests that students who are removed from regular schools and placed at disciplinary schools tend to have significantly worse future outcomes. We provide causal evidence that the composition of peers at these institutions plays an important role in explaining this link. We use rich administrative data of high school students in Texas which provides a detailed record of each student’s disciplinary placements, including their exact date of placement and assignment duration. This allows us to identify the relevant peers for each student based on their overlap at the institution. Leveraging within school-year variation in peer composition at each institution, we ask whether a student who overlaps with particularly disruptive peers has worse subsequent outcomes. We show that exposure to peers in the highest quintile of disruptiveness relative to lowest quintile, when placed at a disciplinary school, increases students’ subsequent removals (5-8% per year); reduces their educational attainment — lower high-school graduation (6%), college enrollment (7%), and college graduation (17%); and worsens labor market outcomes — lower employment (2.5%) and earnings (6.5%). Moreover, these effects are stronger when students have a similar peer group in terms of the reason for removal, or when the distribution of disruptiveness among peers is more concentrated than dispersed around the mean. Our findings draw attention to an unintended consequence of student removal to disciplinary schools and highlight how brief exposures to disruptive peers can shape an individual’s long-run trajectories.