Estimating the Effect of Treatments Allocated by Randomized Waiting Lists

Clément Chaisemartin and Luc Behaghel
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Clément Chaisemartin: UC Santa Barbara - University of California [Santa Barbara] - UC - University of California

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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.

Keywords: Waiting lists; Non-takers; Non compliance; Instrumental variable; Local average treatment effect; Randomized controlled trials (search for similar items in EconPapers)
Date: 2020-07
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Citations: View citations in EconPapers (6)

Published in Econometrica, 2020, 88 (4), pp.1453-1477. ⟨10.3982/ECTA16032⟩

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Related works:
Journal Article: Estimating the Effect of Treatments Allocated by Randomized Waiting Lists (2020)
Working Paper: Estimating the Effect of Treatments Allocated by Randomized Waiting Lists (2020)
Working Paper: Estimating the Effect of Treatments Allocated by Randomized Waiting Lists (2019)
Working Paper: Estimating the effect of treatments allocated by randomized waiting lists (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-02973595

DOI: 10.3982/ECTA16032

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