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(Non)Randomization: A Theory of Quasi-Experimental Evaluation of School Quality

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Abstract

In centralized school admissions systems, rationing at oversubscribed schools often uses lotteries in addition to preferences. This partly random assignment is used by empirical researchers to identify the effect of entering a school on outcomes like test scores. This paper formally studies if the two most popular empirical research designs successfully extract a random assignment. For a class of data-generating mechanisms containing those used in practice, I show: One research design extracts a random assignment under a mechanism if and almost only if the mechanism is strategy-proof for schools. In contrast, the other research design does not necessarily extract a random assignment under any mechanism.

Suggested Citation

  • Yusuki Narita, 2016. "(Non)Randomization: A Theory of Quasi-Experimental Evaluation of School Quality," Cowles Foundation Discussion Papers 2056, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:2056
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    File URL: http://cowles.yale.edu/sites/default/files/files/pub/d20/d2056.pdf
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    References listed on IDEAS

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    1. Adrienne M. Lucas & Isaac M. Mbiti, 2014. "Effects of School Quality on Student Achievement: Discontinuity Evidence from Kenya," American Economic Journal: Applied Economics, American Economic Association, vol. 6(3), pages 234-263, July.
    2. Atila Abdulkadiroğlu & Joshua D. Angrist & Yusuke Narita & Parag A. Pathak, 2017. "Research Design Meets Market Design: Using Centralized Assignment for Impact Evaluation," Econometrica, Econometric Society, vol. 85, pages 1373-1432, September.
    3. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    4. Atila Abdulkadiroğlu & Joshua Angrist & Parag Pathak, 2014. "The Elite Illusion: Achievement Effects at Boston and New York Exam Schools," Econometrica, Econometric Society, vol. 82(1), pages 137-196, January.
    5. Alexander Shapiro & Jos Berge, 2002. "Statistical inference of minimum rank factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 67(1), pages 79-94, March.
    6. Joshua D. Angrist & Peter D. Hull & Parag A. Pathak & Christopher R. Walters, 2017. "Leveraging Lotteries for School Value-Added: Testing and Estimation," The Quarterly Journal of Economics, Oxford University Press, vol. 132(2), pages 871-919.
    7. Beuermann, Diether & Jackson, C. Kirabo & Sierra, Ricardo, 2015. "Privately Managed Public Secondary Schools and Academic Achievement in Trinidad and Tobago: Evidence from Rule-Based Student Assignments," IDB Publications (Working Papers) 7308, Inter-American Development Bank.
    8. Lars Kirkebøen & Edwin Leuven & Magne Mogstad, 2014. "Field of Study, Earnings, and Self-Selection," NBER Working Papers 20816, National Bureau of Economic Research, Inc.
    9. Diether Beuermann & C. Kirabo Jackson & Ricardo Sierra, 2015. "Privately Managed Public Secondary Schools and Academic Achievement in Trinidad and Tobago: Evidence from Rule-Based Student Assignments," IDB Publications (Working Papers) 91836, Inter-American Development Bank.
    10. Nikhil Agarwal & Paulo Somaini, 2018. "Demand Analysis Using Strategic Reports: An Application to a School Choice Mechanism," Econometrica, Econometric Society, vol. 86(2), pages 391-444, March.
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    Keywords

    Matching Market Design; Natural Experiment; Program Evaluation; Random Assignment; Quasi-Experimental Research Design; School Eectiveness;

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