José Luis Montiel Olea, Chen Qiu, Jörg Stoye
arXiv 10 Aug 2026 · Econometrics
arXiv:2608.09027 · PDF · Extracted main text
We provide a new asymptotic framework to derive approximately optimal treatment assignments when sampling noise from data is compounded by fundamental uncertainty due to partial identification. We recenter the reduced-form parameter around its least-favorable configuration and consider drifting parameter sequences that yield both diminishing levels of sampling uncertainty and of partial identification. We characterize the limiting decision problem as a normal location shift model with a suitable limiting identified set. We apply our results to treatment choice problems with contaminated outcomes, to robust welfare analyses with partially identified consumer surplus, and to the problem of aggregating experimental estimates for policy adoption.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Hirano, Keisuke and Porter, Jack R (2009) Asymptotics for statistical treatment rules | 1.000 | 11 | 5 | 100% |
| 2 | Armstrong, Timothy B and Kolesár, Michal (2021) Sensitivity analysis using approximate moment condition models | 1.000 | 5 | 3 | 100% |
| 3 | Stoye, Jörg (2012) Minimax regret treatment choice with covariates or with limited validity of experiments self | 1.000 | 5 | 3 | 100% |
| 4 | Kohei Yata (2025) Optimal Decision Rules Under Partial Identification | 0.959 | 17 | 6 | 88% |
| 5 | Montiel Olea, José Luis and Qiu, Chen and Stoye, Jörg (2026) Decision Theory for Treatment Choice Problems with Partial Identification self | 0.874 | 8 | 2 | 100% |
| 6 | Christensen, Timothy and Moon, Hyungsik Roger and Schorfheide, Frank (2026) Optimal Discrete Decisions when Payoffs are Partially Identified | 0.874 | 7 | 2 | 100% |
| 7 | Takuya Ishihara and Toru Kitagawa (2021) Evidence Aggregation for Treatment Choice | 0.874 | 7 | 2 | 100% |
| 8 | Xu, Han (2026) Asymptotic analysis of point decisions with general loss functions | 0.874 | 5 | 2 | 100% |
| 9 | Manski, Charles F (2007) Identification for prediction and decision | 0.843 | 3 | 3 | 100% |
| 10 | Keisuke Hirano and Jack R. Porter (2020) Asymptotic analysis of statistical decision rules in econometrics | 0.811 | 4 | 2 | 100% |
Showing the top 10 of 44 scored citations.