4 papers
Optimal Policy Learning under Budget and Coverage Constraints
Giovanni Cerulli
We study optimal policy learning under combined budget and minimum coverage constraints. We show that the problem admits a knapsack-type structure and that the optimal policy can b…
Risk-Adjusted Policy Learning and the Social Cost of Uncertainty: Theory and Evidence from CAP evaluation
Giovanni Cerulli, Francesco Caracciolo
This paper develops a risk-adjusted alternative to standard optimal policy learning (OPL) for observational data by importing Roy's (1952) safety-first principle into the treatment…
Optimal Policy Learning for Multi-Action Treatment with Risk Preference using Stata
Giovanni Cerulli
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) algor…
Optimal Policy Learning with Observational Data in Multi-Action Scenarios: Estimation, Risk Preference, and Potential Failures
Giovanni Cerulli
This paper deals with optimal policy learning (OPL) with observational data, i.e. data-driven optimal decision-making, in multi-action (or multi-arm) settings, where a finite set o…