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Estimating the effect of treatments allocated by randomized waiting lists

Clement de Chaisemartin, Luc Behaghel

arXiv 3 Nov 2015 · Statistics — Methodology · publishedEconometrica (2020) · 37 citations (OpenAlex)

arXiv:1511.01453 · PDF · DOI · OpenAlex · Extracted main text

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. We propose a new estimator, and show that it is consistent. Finally, we revisit an application, and we show that using our estimator can lead to sizably different results from those obtained using the commonly used estimator.

Citation extraction

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appendix boundary found by appendix_command · 56% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Blattman \ Annan (2016) `Can employment reduce lawlessness and rebellion? a field experiment with high-risk men in a fragile state', American Political…0.87482100%
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3Behaghel, de Chaisemartin \ Gurgand (2017) `Ready for boarding? the effects of a boarding school for disadvantaged students', American Economic Journal: Applied Economics…0.64422100%
4Angrist \ Pischke (2008) Mostly harmless econometrics: An empiricist's companion, Princeton university press0.5112250%
5Neyman (1923) `On the application of probability theory to agricultural experiments0.51121100%
6Angrist, Imbens \ Rubin (1996) `Identification of causal effects using instrumental variables', Journal of the American Statistical Association 91(434), pp0.40511100%
7Imbens \ Angrist (1994) `Identification and estimation of local average treatment effects', Econometrica 62(2), pp0.40511100%
8Abadie, Angrist \ Imbens (2002) `Instrumental variables estimates of the effect of subsidized training on the quantiles of trainee earnings', Econometrica 70(1)…0.40511100%
9Abadie, Athey, Imbens \ Wooldridge (2017) `Sampling-based vs0.40511100%
10Crépon, Devoto, Duflo \ Parienté (2015) `Estimating the impact of microcredit on those who take it up: Evidence from a randomized experiment in morocco', American Econo…0.40511100%

Showing the top 10 of 15 scored citations.