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

José Luis Montiel Olea, Brenda Prallon, Chen Qiu, Jörg Stoye, Yiwei Sun

arXiv 17 Aug 2024 · Econometrics

arXiv:2408.09187 · PDF · DOI · OpenAlex · Extracted main text

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 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.

Citation extraction

60
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Gechter, M., K. Hirano, J. Lee, M. Mahmud, O. Mondal, J. Morduch, S.… (2024) Selecting Experimental Sites for External Validity1.000244100%
2Egami, N. and D. D. I. Lee (2024) Designing Multi-Context Studies for External Validity: Site Selection via Synthetic Purposive Sampling1.000223100%
3Ishihara, T. and T. Kitagawa (2021) Evidence Aggregation for Treatment Choice, ArXiv:2108.06473 [econ.EM], https://doi.org/10.48550/arXiv.2108.064731.00063100%
4Williamson, D. P. and D. B. Shmoys (2011) The design of approximation algorithms1.00053100%
5Yata, K (2021) Optimal Decision Rules Under Partial Identification, ArXiv:2111.04926 [econ.EM], https://doi.org/10.48550/arXiv.2111.049260.9416583%
6Montiel Olea, J. L., C. Qiu, and J. Stoye (2025) Decision Theory for Treatment Choice Problems with Partial Identification0.89911573%
7Stoye, J (2012) Minimax regret treatment choice with covariates or with limited validity of experiments self0.8434475%
8Lee, J. N., J. Morduch, S. Ravindran, A. Shonchoy, and H. Zaman (2021) Poverty and migration in the digital age: Experimental evidence on mobile banking in Bangladesh0.693111100%
9Naumann, E., L. F. Stoetzer, and G. Pietrantuono (2018) Attitudes towards highly skilled and low-skilled immigration in Europe: A survey experiment in 15 European countries0.6443267%
10Abadie, A., A. Diamond, and J. Hainmueller (2010) Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program0.64422100%

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Cited by, within the corpus

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Citing paperIntensityMentionsSections
1Learning What to Learn: Experimental Design when Combining Experimental with Observational Evidence0.73732
2Epsilon-Minimax Solutions of Statistical Decision Problems0.69351
3Generalizability with ignorance in mind: learning what we do (not) know for archetypes discovery0.64422
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5Statistical Decisions and Partial Identification: With Application to Boundary Discontinuity Design0.40511