Optimal Policy Learning for Multi-Action Treatment with Risk Preference using Stata
Fuente:
arXiv
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866914027741904896 |
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| author | Cerulli, Giovanni |
| author_facet | Cerulli, Giovanni |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_06851 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Optimal Policy Learning for Multi-Action Treatment with Risk Preference using Stata Cerulli, Giovanni Econometrics 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. |
| title | Optimal Policy Learning for Multi-Action Treatment with Risk Preference using Stata |
| topic | Econometrics |
| url | https://arxiv.org/abs/2509.06851 |