{"title":"利用目标优化方案设计:来自节能实验的证据","authors":"Todd D. Gerarden, Muxi Yang","doi":"10.1086/722833","DOIUrl":null,"url":null,"abstract":"We investigate the potential for targeted treatment assignment rules to improve the performance of a large-scale behavioral intervention to encourage households to conserve energy. We derive treatment rules based on observable household characteristics that maximize the expected benefits of the intervention. Targeting treatment using transparent and easily implemented rules could yield significant gains; the energy savings from optimal treatment assignments are predicted to be double those achieved by the intervention as implemented. Predicted cost savings from targeting are even larger. Our results underscore the potential for targeted treatment assignment to generate significant benefits in many domains.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Using Targeting to Optimize Program Design: Evidence from an Energy Conservation Experiment\",\"authors\":\"Todd D. Gerarden, Muxi Yang\",\"doi\":\"10.1086/722833\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We investigate the potential for targeted treatment assignment rules to improve the performance of a large-scale behavioral intervention to encourage households to conserve energy. We derive treatment rules based on observable household characteristics that maximize the expected benefits of the intervention. Targeting treatment using transparent and easily implemented rules could yield significant gains; the energy savings from optimal treatment assignments are predicted to be double those achieved by the intervention as implemented. Predicted cost savings from targeting are even larger. Our results underscore the potential for targeted treatment assignment to generate significant benefits in many domains.\",\"PeriodicalId\":47114,\"journal\":{\"name\":\"Journal of the Association of Environmental and Resource Economists\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2022-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Association of Environmental and Resource Economists\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1086/722833\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Association of Environmental and Resource Economists","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1086/722833","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Using Targeting to Optimize Program Design: Evidence from an Energy Conservation Experiment
We investigate the potential for targeted treatment assignment rules to improve the performance of a large-scale behavioral intervention to encourage households to conserve energy. We derive treatment rules based on observable household characteristics that maximize the expected benefits of the intervention. Targeting treatment using transparent and easily implemented rules could yield significant gains; the energy savings from optimal treatment assignments are predicted to be double those achieved by the intervention as implemented. Predicted cost savings from targeting are even larger. Our results underscore the potential for targeted treatment assignment to generate significant benefits in many domains.