Treatment effects in regression discontinuity designs (RDDs) are often estimated using local regression methods. However, global approximation methods are generally deemed inefficient. In this paper, we propose a semiparametric framework tailored for estimating treatment effects in RDDs. Our global approach conceptualizes the identification of treatment effects within RDDs as a partially linear modeling problem, with the linear component capturing the treatment effect. Furthermore, we utilize the P-spline method to approximate the nonparametric function and develop procedures for inferring treatment effects within this framework. We demonstrate through Monte Carlo simulations that the proposed method performs well across various scenarios. Furthermore, we illustrate using real-world datasets that our global approach may result in more reliable inference.

翻译：断点回归设计（RDD）中的处理效应通常采用局部回归方法估计。然而，全局逼近方法普遍被认为效率较低。本文提出一个专为RDD中处理效应估计设计的半参数框架。我们的全局方法将RDD中处理效应的识别概念化为一个部分线性建模问题，其中线性分量捕捉处理效应。进一步，我们利用P-样条方法逼近非参数函数，并在此框架下开发了处理效应推断程序。蒙特卡洛模拟表明，所提方法在不同场景下表现良好。此外，通过真实数据集验证，我们的全局方法能够产生更可靠的推断结果。