11月27日 木曜日 経済学セミナー開催のお知らせ
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【日 時】2025年11月27日 木曜日 17:00～18:30（90分）
当日14:30～セミナー前まで個別面談（下記に調整用URLあり）
【報告者】坂口 翔政 氏
東京大学 経済学部 講師
【報告論文】The Identification Power of Combining Experimental and Observational Data for Distributional Treatment Effect Parameters
【要旨】This study investigates the identification power gained by combining experimental data, in which treatment is randomized, with observational data, in which treatment is self-selected, for distributional treatment effect (DTE) parameters. While experimental data identify average treatment effects, many DTE parameters, such as the distribution of individual treatment effects, are only partially identified. We examine whether and how combining these two data sources tightens the identified set for such parameters. For broad classes of DTE parameters, we derive nonparametric sharp bounds under the combined data and clarify the mechanism through which data combination improves identification relative to using experimental data alone. Our analysis highlights that self-selection in observational data is a key source of identification power. We establish necessary and sufficient conditions under which the combined data shrink the identified set, showing that such shrinkage generally occurs unless selection-on-observables holds in the observational data. We also propose a linear programming approach to compute sharp bounds that can incorporate additional structural restrictions, such as positive dependence between potential outcomes and the generalized Roy model. An empirical application using data on negative campaign advertisements in the 2008 U.S. presidential election illustrates the practical relevance of the proposed approach.
【論文link】 https://arxiv.org/abs/2508.12206
【開催方法】第二教授研究館4階 第6会議室での対面開催
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