{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T13:59:23Z","timestamp":1763387963020,"version":"3.45.0"},"reference-count":49,"publisher":"The Econometric Society","issue":"4","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["QE"],"abstract":"<jats:p>\n                    I study the problem of a decision maker choosing a policy that allocates treatment to a heterogeneous population on the basis of experimental data that includes only a subset of possible treatment values. The effects of new treatments are partially identified by shape restrictions on treatment response. Policies are compared according to the minimax regret criterion, and I show that the empirical analog of the population decision problem has a tractable linear\u2010 and integer\u2010programming formulation. I prove that the rate at which the maximum regret of the estimated policy converges to the lowest possible maximum regret is the maximum of\n                    <jats:italic>N<\/jats:italic>\n                    <jats:sup>\u22121\/2<\/jats:sup>\n                    and the rate at which conditional average treatment effects are estimated in the experimental data. In an application to designing targeted subsidies for electrical grid connections in rural Kenya, I find that nearly the entire population should be given a treatment not implemented in the experiment, reducing maximum regret by over 60% compared to the policy that restricts to the treatments implemented in the experiment.\n                  <\/jats:p>","DOI":"10.3982\/qe2477","type":"journal-article","created":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T13:54:47Z","timestamp":1763387687000},"page":"1409-1456","source":"Crossref","is-referenced-by-count":0,"title":["Policy learning with new treatments"],"prefix":"10.3982","volume":"16","author":[{"given":"Samuel D.","family":"Higbee","sequence":"first","affiliation":[{"name":"Department of Economics, University of North Carolina at Chapel Hill"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2359","published-online":{"date-parts":[[2025]]},"reference":[{"key":"quan200393-bib-0001","unstructured":"Adjaho, Christopher and Timothy Christensen (2023), \u201cExternally valid policy choice.\u201d arXiv:2205.05561 [econ] (visited on 04\/03\/2025). 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