Optimal policy learning under budget and coverage constraints: A Stata implementation

Giovanni Cerulli

UK Stata Conference 2026 from Stata Users Group

Abstract: This presentation introduces opl_budget, a new community-contributed command for optimal policy learning under budget and minimum coverage constraints. Using estimated conditional average treatment effects (CATEs) and heterogeneous treatment costs, the command computes welfare-maximizing binary treatment assignment rules subject to a fixed budget and a minimum number of treated units. The command reports welfare gains, treatment coverage, and total policy costs and also allows evaluation of user-defined treatment rules for comparative policy analysis. An empirical example illustrates the use of the command in data-driven policy design and causal inference applications.

References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:lsug26:16

Access Statistics for this paper

More papers in UK Stata Conference 2026 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().