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Estimating the Effect of Treatments Allocated by Randomized Waiting Lists

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  • Clément de Chaisemartin
  • Luc Behaghel

Abstract

Oversubscribed treatments are often allocated using randomized waiting lists. Applicants are ranked randomly, and treatment offers are made following that ranking until all seats are filled. To estimate causal effects, researchers often compare applicants getting and not getting an offer. We show that those two groups are not statistically comparable. Therefore, the estimator arising from that comparison is inconsistent when the number of waitlists goes to infinity. We propose a new estimator, and show that it is consistent, provided the waitlists have at least two seats. Finally, we revisit an application, and we show that using our estimator can lead to a statistically significant difference with respect to the results obtained using the commonly used estimator.

Suggested Citation

  • Clément de Chaisemartin & Luc Behaghel, 2020. "Estimating the Effect of Treatments Allocated by Randomized Waiting Lists," Econometrica, Econometric Society, vol. 88(4), pages 1453-1477, July.
  • Handle: RePEc:wly:emetrp:v:88:y:2020:i:4:p:1453-1477
    DOI: 10.3982/ECTA16032
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    2. Araya, Federico & Le Barbanchon, Thomas & Ubfal, Diego, 2019. "The Effects of Working while in School: Evidence from Uruguayan Lotteries," CEPR Discussion Papers 13826, C.E.P.R. Discussion Papers.

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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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