A Theory of Experimenters
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.
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Copy CitationAbhijit Banerjee, Sylvain Chassang, Sergio Montero, and Erik Snowberg, "A Theory of Experimenters," NBER Working Paper 23867 (2017), https://doi.org/10.3386/w23867.
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