The regression discontinuity (RD) design is one of the most widely used nonexperimental
methods for causal inference and program evaluation. Over the last two decades, statistical …

Modern empirical work in regression discontinuity (RD) designs often employs local
polynomial estimation and inference with a mean square error (MSE) optimal bandwidth …

In this paper we detail the entire Regression Discontinuity Design (RDD) history, including
its origins in the 1960s, and its two main waves of formalization in the 1970s and 2000s …

The standard regression discontinuity (RD) design deals with a binary treatment. Many
empirical applications of RD designs involve continuous treatments. This article establishes …

In this article, we investigate the problem of nonparametrically estimating a conditional
quantile function with mixed discrete and continuous covariates. A local linear smoothing …

We propose a new specification test for assessing the validity of fuzzy regression
discontinuity designs (FRD‐validity). We derive a new set of testable implications …

This paper develops a novel wild bootstrap procedure to construct robust bias-corrected
valid confidence intervals for fuzzy regression discontinuity designs, providing an intuitive …

The Regression Discontinuity Design (RDD) has proven to be a compelling and transparent
research design to estimate treatment effects. We provide a review of the main assumptions …

Regression discontinuity is a popular tool for analyzing economic policies or treatment
interventions. This research extends the classic static RD model to a dynamic framework …

Abstract Following Efron (2014), we propose an algorithm for estimating treatment effects for
use by researchers employing a regression-discontinuity (RD) design. This algorithm …