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A Method for Disentangling Multiple Treatments from a Regression Discontinuity Design

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  • Michael Gilraine
Abstract
In many settings, a policy discontinuity comprises several treatments that cannot be separately identified using a standard regression discontinuity design. I propose a method for identifying distinct treatment components from a single discontinuity by exploiting the asymmetry between entities entering versus exiting treatment. Using data from New York City for 2009–13, I apply my strategy to the discontinuity associated with the introduction of class size caps—a widespread approach for reducing class sizes. I find that class size reductions increase student achievement, although these gains are counteracted by a newly hired teacher effect. The method has broad potential applicability.

Suggested Citation

  • Michael Gilraine, 2020. "A Method for Disentangling Multiple Treatments from a Regression Discontinuity Design," Journal of Labor Economics, University of Chicago Press, vol. 38(4), pages 1267-1311.
  • Handle: RePEc:ucp:jlabec:doi:10.1086/706740
    DOI: 10.1086/706740
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    Cited by:

    1. Maximilian Bach & Stephan Sievert, 2019. "Birth Cohort Size Variation and the Estimation of Class Size Effects," Discussion Papers of DIW Berlin 1817, DIW Berlin, German Institute for Economic Research.
    2. TANAKA Ryuichi & WANG Tong, 2024. "How do Classmates Matter for the Class-size Effects?," Discussion papers 24004, Research Institute of Economy, Trade and Industry (RIETI).
    3. Nicolai T. Borgen & Lars J. Kirkebøen & Andreas Kotsadam & Oddbjørn Raaum, 2022. "Do funds for more teachers improve student outcomes?," Discussion Papers 982, Statistics Norway, Research Department.
    4. Penney, Jeffrey, 2023. "Same race teachers do not necessarily raise academic achievement," Economics Letters, Elsevier, vol. 223(C).
    5. Michael Gilraine & Hugh Macartney & Robert McMillan, 2018. "Estimating the Direct and Indirect Effects of Major Education Reforms," NBER Working Papers 24191, National Bureau of Economic Research, Inc.

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