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Optimal Policy Learning for Multi-Action Treatment with Risk Preference using Stata

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  • Giovanni Cerulli

Abstract

This paper presents the Stata community-distributed command "opl_ma_fb" (and the companion command "opl_ma_vf"), for implementing the first-best Optimal Policy Learning (OPL) algorithm to estimate the best treatment assignment given the observation of an outcome, a multi-action (or multi-arm) treatment, and a set of observed covariates (features). It allows for different risk preferences in decision-making (i.e., risk-neutral, linear risk-averse, and quadratic risk-averse), and provides a graphical representation of the optimal policy, along with an estimate of the maximal welfare (i.e., the value-function estimated at optimal policy) using regression adjustment (RA), inverse-probability weighting (IPW), and doubly robust (DR) formulas.

Suggested Citation

  • Giovanni Cerulli, 2025. "Optimal Policy Learning for Multi-Action Treatment with Risk Preference using Stata," Papers 2509.06851, arXiv.org.
    • Handle: RePEc:arx:papers:2509.06851
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    References listed on IDEAS

    as
    1. Giovanni Cerulli, 2025. "Optimal policy learning using Stata," Stata Journal, StataCorp LLC, vol. 25(2), pages 309-343, June.
    2. Matias D. Cattaneo & David M. Drukker & Ashley D. Holland, 2013. "Estimation of multivalued treatment effects under conditional independence," Stata Journal, StataCorp LLC, vol. 13(3), pages 407-450, September.
    3. Asaf Cassel & Shie Mannor & Assaf Zeevi, 2023. "A General Framework for Bandit Problems Beyond Cumulative Objectives," Mathematics of Operations Research, INFORMS, vol. 48(4), pages 2196-2232, November.
    4. Toru Kitagawa & Aleksey Tetenov, 2018. "Who Should Be Treated? Empirical Welfare Maximization Methods for Treatment Choice," Econometrica, Econometric Society, vol. 86(2), pages 591-616, March.
    5. Dimitris Bertsimas & Nathan Kallus, 2020. "From Predictive to Prescriptive Analytics," Management Science, INFORMS, vol. 66(3), pages 1025-1044, March.
    6. Bhattacharya, Debopam & Dupas, Pascaline, 2012. "Inferring welfare maximizing treatment assignment under budget constraints," Journal of Econometrics, Elsevier, vol. 167(1), pages 168-196.
    7. Giovanni Cerulli, 2023. "Optimal treatment assignment of a threshold-based policy: empirical protocol and related issues," Applied Economics Letters, Taylor & Francis Journals, vol. 30(8), pages 1010-1017, May.
    8. Susan Athey & Stefan Wager, 2021. "Policy Learning With Observational Data," Econometrica, Econometric Society, vol. 89(1), pages 133-161, January.
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