{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T01:46:06Z","timestamp":1788831966103,"version":"build-2803163510"},"reference-count":75,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,4,10]],"date-time":"2024-04-10T00:00:00Z","timestamp":1712707200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,3,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>This article studies the problem of optimally allocating treatments in the presence of spillover effects, using information from a (quasi-)experiment. I introduce a method that maximizes the sample analogue of average social welfare when spillovers occur. I construct semi-parametric welfare estimators with known and unknown propensity scores and cast the optimization problem into a mixed-integer linear program, which can be solved using off-the-shelf algorithms. I derive a strong set of guarantees on regret, i.e. the difference between the maximum attainable welfare and the welfare evaluated at the estimated policy. The proposed method presents attractive features for applications: (i) it does not require network information of the target population; (ii) it exploits heterogeneity in treatment effects for targeting individuals; (iii) it does not rely on the correct specification of a particular structural model; and (iv) it accommodates constraints on the policy function. An application for targeting information on social networks illustrates the advantages of the method.<\/jats:p>","DOI":"10.1093\/restud\/rdae041","type":"journal-article","created":{"date-parts":[[2024,4,10]],"date-time":"2024-04-10T14:18:23Z","timestamp":1712758703000},"page":"1257-1292","source":"Crossref","is-referenced-by-count":16,"title":["Policy Targeting under Network Interference"],"prefix":"10.1093","volume":"92","author":[{"given":"Davide","family":"Viviano","sequence":"first","affiliation":[{"name":"Department of Economics, Harvard University ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,4,10]]},"reference":[{"key":"2025030619564716200_rdae041-B1","doi-asserted-by":"crossref","first-page":"265","DOI":"10.3982\/ECTA12675","article-title":"Sampling-Based Versus Design-Based Uncertainty in Regression 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