Externally Valid Selection of Experimental Sites via the k-Median Problem

Jos\'e Luis Montiel Olea, Brenda Prallon, Chen Qiu, Jörg Stoye and Yiwei Sun

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Abstract: We present a decision-theoretic justification for viewing the question of how to best choose where to experiment in order to optimize external validity as a k-median (clustering) problem, a popular problem in computer science and operations research. We present conditions under which minimizing the worst-case, welfare-based regret among all nonrandom schemes that select k sites to experiment is approximately equal - and sometimes exactly equal - to finding the k most central vectors of baseline site-level covariates. The k-median problem can be formulated as a linear integer program. Two empirical applications illustrate the theoretical and computational benefits of the suggested procedure.

Date: 2024-08
New Economics Papers: this item is included in nep-exp
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