EconBase
← All papers

Statistical Inference of Optimal Allocations I: Regularities and their Implications

Kai Feng, Han Hong, Denis Nekipelov

arXiv 27 Mar 2024 · Econometrics · 1 citations (OpenAlex)

arXiv:2403.18248 · PDF · DOI · OpenAlex · Extracted main text

Abstract

In this paper, we develop a functional differentiability approach for solving statistical optimal allocation problems. We derive Hadamard differentiability of the value functions through analyzing the properties of the sorting operator using tools from geometric measure theory. Building on our Hadamard differentiability results, we apply the functional delta method to obtain the asymptotic properties of the value function process for the binary constrained optimal allocation problem and the plug-in ROC curve estimator. Moreover, the convexity of the optimal allocation value functions facilitates demonstrating the degeneracy of first order derivatives with respect to the policy. We then present a double / debiased estimator for the value functions. Importantly, the conditions that validate Hadamard differentiability justify the margin assumption from the statistical classification literature for the fast convergence rate of plug-in methods.

Citation extraction

106
references
288
in-text mentions
106
distinct cited
1
self-citations
41,143
main-text words

appendix boundary found by appendix_titled_section at “Appendix for manuscript” · 51% of the source is main text. Read the extracted text to check this.

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
1Audibert, Jean-Yves and Tsybakov, Alexandre B (2007) Fast learning rates for plug-in classifiers1.000123100%
2Chernozhukov, Victor and Chetverikov, Denis and Demirer, Mert and Du… (2018) Double/debiased machine learning for treatment and structural parameters1.00073100%
3Chernozhukov, Victor and Escanciano, Juan Carlos and Ichimura, Hideh… (2022) Locally robust semiparametric estimation1.00073100%
4Devroye, Luc and Györfi, László and Lugosi, Gábor (1996) A Probabilistic Theory of Pattern Recognition1.00073100%
5Chernozhukov, Victor and Fernández-Val, Iván and Luo, Ye (2018) The sorted effects method: discovering heterogeneous effects beyond their averages0.96721790%
6Chen, Xiaohong and Linton, Oliver and Van Keilegom, Ingrid (2003) Estimation of semiparametric models when the criterion function is not smooth0.88810370%
7Zhou, Zhengyuan and Athey, Susan and Wager, Stefan (2023) Offline multi-action policy learning: Generalization and optimization0.87472100%
8Chen, Xi and Chernozhukov, Victor and Fernández-Val, Iván and Kostys… (2021) Shape-enforcing operators for generic point and interval estimators of functions0.87452100%
9Semenova, Vira (2023) Debiased machine learning of set-identified linear models0.87452100%
10Luedtke, Alexander R and van der Laan, Mark J (2016) Optimal individualized treatments in resource-limited settings0.84333100%

Showing the top 10 of 106 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
1Statistical tests for replacing human decision makers with algorithms0.64422
2Thin Sets Are Not Equally Thin: Minimax Learning of Submanifold Integrals0.40511
3Inference on Welfare and Value Functionals under Optimal Treatment Assignment0.40511
4Semiparametric Efficiency in Policy Learning with General Treatments0.40511