Interpreting school choice treatment effects: Results and implications from computational experiments

Research output: Contribution to journalArticle

Abstract

Providing parents and students a choice to attend schools other than their assigned neighborhood school has been a leading theme in recent education reform. To evaluate the effects of such choice-based programs, researchers have taken advantage of the randomization that occurs in student assignment lotteries put in place to deal with oversubscription to popular schools and pilot programs. In this study, I used an agent-based model of the transition to school choice as platform for examining the sensitivity of school choice treatment effects from lottery-based studies to differences in student preferences and program participation rates across hypothetical study populations. I found that districts with higher participation rates had lower treatment effects, even when there were no differences in the distributions of school quality and student preferences between districts. This is because capacity constraints increasingly limited the amount of students who are able to attend the highest quality schools, causing the magnitude of the treatment effect to fall. I discuss the implications of this finding for interpreting the results of lottery-based studies involving choice schools.

Original languageEnglish (US)
Article number7
JournalJASSS
Volume19
Issue number1
DOIs
StatePublished - Jan 2016

Keywords

  • Causal Inference
  • Education
  • Public Policy
  • School Choice

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Social Sciences(all)

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