Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/171142
Authors: 
Banerjee, Abhijit
Chassang, Sylvain
Montero, Sergio
Snowberg, Erik
Year of Publication: 
2017
Series/Report no.: 
CESifo Working Paper 6678
Abstract: 
This paper proposes a decision-theoretic framework for experiment design. We model experimenters as ambiguity-averse decision-makers, who make trade-offs between subjective expected performance and robustness. This framework accounts for experimenters’ preference for randomization, and clarifies the circumstances in which randomization is optimal: when the available sample size is large enough or robustness is an important concern. We illustrate the practical value of such a framework by studying the issue of rerandomization. Rerandomization creates a trade-off between subjective performance and robustness. However, robustness loss grows very slowly with the number of times one randomizes. This argues for rerandomizing in most environments.
Subjects: 
experiment design
robustness
ambiguity aversion
randomization
rerandomization
JEL: 
C90
D78
D81
Document Type: 
Working Paper

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