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Optimal treatment assignment rules under capacity constraints

Keita Sunada, Kohei Izumi

arXiv 13 Jun 2025 · Econometrics

arXiv:2506.12225 · PDF · Extracted main text

Abstract

We study treatment assignment problems under capacity constraints, where a planner aims to maximize social welfare by assigning treatments based on observable covariates. Such constraints, common when treatments are costly or limited in supply, introduce nontrivial challenges for deriving optimal statistical assignment rules because the planner needs to coordinate treatment assignment probabilities across the entire covariate distribution. To address these challenges, we reformulate the planner's constrained maximization problem as an optimal transport problem, which makes the problem effectively unconstrained. We then establish local asymptotic optimality results of assignment rules using a limits of experiments framework. Finally, we illustrate our method with a voucher assignment problem for private secondary school attendance using data from Angrist et al. (2006)

Citation extraction

48
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118
in-text mentions
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main-text words

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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
1Hirano, Keisuke, Porter, Jack R (2009) Asymptotics for statistical treatment rules1.000144100%
2Angrist, Joshua, Bettinger, Eric, Kremer, Michael (2006) Long-term educational consequences of secondary school vouchers: Evidence from administrative records in Colombia1.00085100%
3Xu, Han (2024) Asymptotic analysis of point decisions with general loss functions0.9285380%
4Christensen, Timothy, Moon, Hyungsik Roger, Schorfheide, Frank (2025) Optimal decision rules when payoffs are partially identified0.89421771%
5Adjaho, Christopher, Christensen, Timothy (2023) Externally valid policy choice0.81142100%
6Aradillas Fernández, Andrés, Montiel Olea, José Luis, Qiu, Chen, Sto… (2024) Robust Bayes treatment choice with partial identification0.64422100%
7Kido, Daido (2023) Locally asymptotically minimax statistical treatment rules under partial identification0.64422100%
8Kido, Daido (2022) Distributionally robust policy learning with wasserstein distance0.64422100%
9Villani, Cédric (2009) Optimal Transport: Old and New0.6308525%
10Nutz, Marcel (2022) Introduction to entropic optimal transport0.58510230%

Showing the top 10 of 48 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1An econometrician's guide to optimal transport0.51121
2Who With Whom? Learning Optimal Matching Policies0.40511
3Distributional Change in Ordinal Data with Missing Observations: Minimal Mobility and Partial Identification0.40511