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Ranking Treatment Saturations under Clustered Network Interference

Seungjin Han, Julius Owusu, Youngki Shin

arXiv 17 Jun 2026 · Econometrics

arXiv:2606.18590 · PDF · DOI · OpenAlex · Extracted main text

Abstract

In this paper, we study how to rank a finite set of treatment saturations for a target population with clustered network interference. We propose an empirical success (ES) ranking rule that, for each pair of saturations, selects the saturation level with the higher estimated welfare using data from a two-stage randomized saturation design. We adopt the statistical decision theory framework with additively separable regret loss to assess the performance of the ES ranking rule. We derive non-asymptotic upper bounds on the maximum regret of the ES ranking rule that depend on the within-cluster network only through a single combinatorial summary of its dependency structure. We exploit these bounds to characterize a quasi-optimal first-stage saturation distribution within the two-stage randomized saturation design. We further show that the ES ranking rule is asymptotically optimal among threshold ranking rules in the sense of minimizing an upper bound on the worst-case regret.

Citation extraction

43
references
101
in-text mentions
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distinct cited
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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
1Manski, C. F (2004) Statistical treatment rules for heterogeneous populations1.00095100%
2Baird, S., J. A. Bohren, C. McIntosh, and B. Özler (2018) Optimal design of experiments in the presence of interference1.00084100%
3Hirano, K. and J. R. Porter (2009) Asymptotics for statistical treatment rules0.9098375%
4Manski, C. F. and A. Tetenov (2016) Sufficient trial size to inform clinical practice0.73732100%
5Cohen, A. and H. B. Sackrowitz (2005) Decision theory results for one-sided multiple comparison procedures0.71411436%
6Hudgens, M. G. and M. E. Halloran (2008) Toward causal inference with interference0.69361100%
7Crépon, B., E. Duflo, M. Gurgand, R. Rathelot, and P. Zamora (2013) Do labor market policies have displacement effects? Evidence from a clustered randomized experiment0.64422100%
8Manski, C. F (1993) Identification of endogenous social effects: The reflection problem0.64422100%
9Tetenov, A (2012) Statistical treatment choice based on asymmetric minimax regret criteria0.64422100%
10Janson, S (2004) Large deviations for sums of partly dependent random variables0.58510320%

Showing the top 10 of 43 scored citations.