Unbiased Estimation of the Average Treatment Effect in Cluster-Randomized Experiments

Middleton Joel A. and Aronow Peter M. ()
Additional contact information
Middleton Joel A.: Department of Political Science, University of California Berkeley, Berkeley, CA, USA
Aronow Peter M.: Department of Political Science, Yale University, New Haven, CT, USA

Statistics, Politics and Policy, 2015, vol. 6, issue 1-2, 39-75

Abstract: Many estimators of the average treatment effect, including the difference-in-means, may be biased when clusters of units are allocated to treatment. This bias remains even when the number of units within each cluster grows asymptotically large. In this paper, we propose simple, unbiased, location-invariant, and covariate-adjusted estimators of the average treatment effect in experiments with random allocation of clusters, along with associated variance estimators. We then analyze a cluster-randomized field experiment on voter mobilization in the US, demonstrating that the proposed estimators have precision that is comparable, if not superior, to that of existing, biased estimators of the average treatment effect.

Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://doi.org/10.1515/spp-2013-0002 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:statpp:v:6:y:2015:i:1-2:p:39-75:n:1

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/spp/html

DOI: 10.1515/spp-2013-0002

Access Statistics for this article

Statistics, Politics and Policy is currently edited by Joel A. Middleton

More articles in Statistics, Politics and Policy from De Gruyter
Bibliographic data for series maintained by Peter Golla ().