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.
MLA
Chaisemartin, Clément de, and Luc Behaghel. “Estimating the Effect of Treatments Allocated by Randomized Waiting Lists.” Econometrica, vol. 88, .no 4, Econometric Society, 2020, pp. 1453-1477, https://doi.org/10.3982/ECTA16032
Chicago
Chaisemartin, Clément de, and Luc Behaghel. “Estimating the Effect of Treatments Allocated by Randomized Waiting Lists.” Econometrica, 88, .no 4, (Econometric Society: 2020), 1453-1477. https://doi.org/10.3982/ECTA16032
APA
Chaisemartin, C. d., & Behaghel, L. (2020). Estimating the Effect of Treatments Allocated by Randomized Waiting Lists. Econometrica, 88(4), 1453-1477. https://doi.org/10.3982/ECTA16032
We are deeply saddened by the passing of Kate Ho, the John L. Weinberg Professor of Economics and Business Policy at Princeton University and a Fellow of the Econometric Society. Kate was a brilliant IO economist and scholar whose impact on the profession will resonate for many years to come.
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