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American Economic Review Vol. 110 No. 4 2020

A Theory of Experimenters: Robustness, Randomization, and Balance

Abhijit V. Banerjee1; Sylvain Chassang2; Sergio Montero3; Erik Snowberg4

1 Department of Economics, Massachusetts Institute of Technology (email: ) · 2 Department of Economics, New York University (email: ) · 3 Department of Political Science, University of Rochester (email: ) · 4 Vancouver School of Economics, University of British Columbia (email: )

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Abstract

This paper studies the problem of experiment design by an ambiguity-averse decision-maker who trades off subjective expected performance against robust performance guarantees. This framework accounts for real-world experimenters’ preference for randomization. It also clarifies the circumstances in which randomization is optimal: when the available sample size is large and robustness is an important concern. We apply our model to shed light on the practice of rerandomization, used to improve balance across treatment and control groups. We show that rerandomization creates a trade-off between subjective performance and robust performance guarantees. However, robust performance guarantees diminish very slowly with the number of rerandomizations. This suggests that moderate levels of rerandomization usefully expand the set of acceptable compromises between subjective performance and robustness. Targeting a fixed quantile of balance is safer than targeting an absolute balance objective.

DOI
10.1257/aer.20171634
Volume
110
Issue
4
Pages
1206-1230
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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