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Interpreting School Choice Treatment Effects: Results and Implications from Computational Experiments

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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.

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  • Spiro Maroulis, 2016. "Interpreting School Choice Treatment Effects: Results and Implications from Computational Experiments," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(1), pages 1-7.
    • Handle: RePEc:jas:jasssj:2015-47-3
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    File URL: https://www.jasss.org/19/1/7/7.pdf
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    References listed on IDEAS

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    1. Caroline Minter Hoxby, 2003. "School Choice and School Productivity. Could School Choice Be a Tide that Lifts All Boats?," NBER Chapters, in: The Economics of School Choice, pages 287-342, National Bureau of Economic Research, Inc.
    2. Caroline M. Hoxby, 2003. "The Economics of School Choice," NBER Books, National Bureau of Economic Research, Inc, number hox03-1.
    3. Julie Berry Cullen & Brian A Jacob & Steven Levitt, 2006. "The Effect of School Choice on Participants: Evidence from Randomized Lotteries," Econometrica, Econometric Society, vol. 74(5), pages 1191-1230, September.
    4. Philip Gleason & Melissa Clark & Christina Clark Tuttle & Emily Dwoyer, "undated". "The Evaluation of Charter School Impacts," Mathematica Policy Research Reports 3066da11915a4b04a77b38848, Mathematica Policy Research.
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    9. Philip Gleason & Melissa Clark & Christina Clark Tuttle & Emily Dwoyer, 2010. "The Evaluation of Charter School Impacts (Presentation)," Mathematica Policy Research Reports 770e250b2ef343a3b1ec8c932, Mathematica Policy Research.
    10. Vittoria Colizza & Alain Barrat & Marc Barthelemy & Alain-Jacques Valleron & Alessandro Vespignani, 2007. "Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions," PLOS Medicine, Public Library of Science, vol. 4(1), pages 1-16, January.
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    1. Bailey Borman & Medha Dalal & Christopher S. Hayter & Spiro Maroulis, 2024. "A transversal reconceptualization of entrepreneurship education: applying insights from the lean social launch framework to the entrepreneurial university," Small Business Economics, Springer, vol. 63(2), pages 549-573, August.

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