This monograph, together with its accompanying first part Cattaneo, Idrobo and Titiunik (2020), collects and expands the instructional materials we prepared for more than $40$ short courses and workshops on Regression Discontinuity (RD) methodology that we taught between 2014 and 2022. In this second monograph, we discuss several topics in RD methodology that build on and extend the analysis of RD designs introduced in Cattaneo, Idrobo and Titiunik (2020). Our first goal is to present an alternative RD conceptual framework based on local randomization ideas. This methodological approach can be useful in RD designs with discretely-valued scores, and can also be used more broadly as a complement to the continuity-based approach in other settings. Then, employing both continuity-based and local randomization approaches, we extend the canonical Sharp RD design in multiple directions: fuzzy RD designs, RD designs with discrete scores, and multi-dimensional RD designs. The goal of our two-part monograph is purposely practical and hence we focus on the empirical analysis of RD designs.
翻译:这本专著连同其所附第一部分Cattaneo、Idrobo和Titiunik(202020年),收集并扩充了我们为2014年至2022年期间我们教授的40多美元的回归脱节方法短期课程和讲习班编写的教学材料。在第二篇专著中,我们讨论了在Cattaneo、Idrobo和Titiunik(202020年)引进的RD设计分析的基础上,再现方法中的若干专题。我们的第一个目标是提出一个基于本地随机化概念的替代性RD概念框架。这一方法方法可用于分得分的RD设计,还可以更广泛地用于补充其他环境中的基于连续性的方法。然后,我们采用连续性和本地随机化的方法,将Canonic Sharp RD设计扩展为多个方向:模糊的RD设计、分数的RD设计以及多维的RD设计。我们两部专辑的目标特意实用,因此我们侧重于RD设计的经验分析。