We develop a difference-in-differences framework to measure the persuasive impact of informational treatments on behavior. We introduce two causal parameters, the forward and backward average persuasion rates on the treated, which refine the average treatment effect on the treated. The forward rate excludes cases of "preaching to the converted," while the backward rate omits "talking to a brick wall" cases. We propose both regression-based and semiparametrically efficient estimators. The framework applies to both two-period and staggered treatment settings, including event studies, and we demonstrate its usefulness with applications to a British election and a Chinese curriculum reform.

翻译：本文构建了一个双重差分框架，用于衡量信息干预对行为的说服性影响。我们提出了两个因果参数——处理组的前向与后向平均说服率，这两个参数细化了处理组的平均处理效应。前向率排除了"向已信服者布道"的情形，而后向率则剔除了"对牛弹琴"的情形。我们提出了基于回归的估计量以及半参数有效估计量。该框架适用于双期与交错处理设定（包括事件研究），并通过英国大选与中国课程改革两个应用案例证明了其有效性。