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

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Listed:
  • Jos'e Luis Montiel Olea
  • Brenda Prallon
  • Chen Qiu
  • Jorg Stoye
  • Yiwei Sun

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.

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  • Jos'e Luis Montiel Olea & Brenda Prallon & Chen Qiu & Jorg Stoye & Yiwei Sun, 2024. "Externally Valid Selection of Experimental Sites via the k-Median Problem," Papers 2408.09187, arXiv.org.
    • Handle: RePEc:arx:papers:2408.09187
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    References listed on IDEAS

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    2. Jean N. Lee & Jonathan Morduch & Saravana Ravindran & Abu Shonchoy & Hassan Zaman, 2021. "Poverty and Migration in the Digital Age: Experimental Evidence on Mobile Banking in Bangladesh," American Economic Journal: Applied Economics, American Economic Association, vol. 13(1), pages 38-71, January.
    3. Eva Vivalt, 2020. "How Much Can We Generalize From Impact Evaluations?," Journal of the European Economic Association, European Economic Association, vol. 18(6), pages 3045-3089.
    4. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    5. Stoye, Jörg, 2012. "Minimax regret treatment choice with covariates or with limited validity of experiments," Journal of Econometrics, Elsevier, vol. 166(1), pages 138-156.
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