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Credible School Value-Added with Undersubscribed School Lotteries

Author

Listed:
  • Joshua Angrist

    (MIT and NBER)

  • Peter Hull

    (Brown University and NBER)

  • Parag A. Pathak

    (MIT and NBER)

  • Christopher Walters

    (University of California Berkeley and NBER)

Abstract

We introduce two empirical strategies harnessing the randomness in school assignment mechanisms to measure school value-added. The first estimator controls for the probability of school assignment, treating take-up as ignorable. We test this assumption using randomness in assignments. The second approach uses assignments as instrumental variables (IVs) for low-dimensional models of value-added and forms empirical Bayes posteriors from these IV estimates. Both strategies solve the underidentification challenge arising from school undersubscription. Models controlling for assignment risk and lagged achievement in Denver and New York City yield reliable value-added estimates. Estimates from models with lower-quality achievement controls are improved by IV.

Suggested Citation

  • Joshua Angrist & Peter Hull & Parag A. Pathak & Christopher Walters, 2024. "Credible School Value-Added with Undersubscribed School Lotteries," The Review of Economics and Statistics, MIT Press, vol. 106(1), pages 1-19, January.
    • Handle: RePEc:tpr:restat:v:106:y:2024:i:1:p:1-19
    DOI: 10.1162/rest_a_01149
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    Cited by:

    1. Ellen Sahlström & Mikko Silliman, 2024. "The Extent and Consequences of Teacher Biases against Immigrants," CESifo Working Paper Series 11050, CESifo.
    2. Sahlström, Ellen & Silliman, Mikko, 2024. "The Extent and Consequences of Teacher Biases against Immigrants," IZA Discussion Papers 16899, Institute of Labor Economics (IZA).

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