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Functional Sequential Treatment Allocation With Covariates

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  • Kock, Anders Bredahl
  • Preinerstorfer, David
  • Veliyev, Bezirgen

Abstract

We consider a sequential treatment problem with covariates. Given a realization of the covariate vector, instead of targeting the treatment with highest conditional expectation, the decision-maker targets the treatment which maximizes a general functional of the conditional potential outcome distribution, e.g., a conditional quantile, trimmed mean, or a socioeconomic functional such as an inequality, welfare, or poverty measure. We develop expected regret lower bounds for this problem and construct a near minimax optimal sequential assignment policy.

Suggested Citation

  • Kock, Anders Bredahl & Preinerstorfer, David & Veliyev, Bezirgen, 2024. "Functional Sequential Treatment Allocation With Covariates," Econometric Theory, Cambridge University Press, vol. 40(6), pages 1211-1252, December.
    • Handle: RePEc:cup:etheor:v:40:y:2024:i:6:p:1211-1252_1
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    Cited by:

    1. is not listed on IDEAS
    2. Keisuke Hirano & Jack R. Porter, 2023. "Asymptotic Representations for Sequential Decisions, Adaptive Experiments, and Batched Bandits," Papers 2302.03117, arXiv.org, revised Feb 2025.
    3. Kitagawa, Toru & Wang, Guanyi, 2023. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," Journal of Econometrics, Elsevier, vol. 232(1), pages 109-131.
    4. Toru Kitagawa & Guanyi Wang, 2021. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP28/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Kock, Anders Bredahl & Preinerstorfer, David & Veliyev, Bezirgen, 2023. "Treatment recommendation with distributional targets," Journal of Econometrics, Elsevier, vol. 234(2), pages 624-646.

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