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 …

Many empirical questions in economics and other social sciences depend on causal effects
of programs or policies. In the last two decades, much research has been done on the …

In this paper, we discuss recent developments in econometrics that we view as important for
empirical researchers working on policy evaluation questions. We focus on three main …

In the regression‐discontinuity (RD) design, units are assigned to treatment based on
whether their value of an observed covariate exceeds a known cutoff. In this design, local …

In this article, we introduce three commands to conduct robust data-driven statistical
inference in regression-discontinuity (RD) designs. First, we present rdrobust, a command …

Exploratory data analysis plays a central role in applied statistics and econometrics. In the
popular regression-discontinuity (RD) design, the use of graphical analysis has been …

Featuring engaging examples from diverse disciplines, this book explains how to use
modern approaches to quasi-experimentation to derive credible estimates of treatment …

We investigate the choice of the bandwidth for the regression discontinuity estimator. We
focus on estimation by local linear regression, which was shown to have attractive properties …

It is common in regression discontinuity analysis to control for third, fourth, or higher-degree
polynomials of the forcing variable. There appears to be a perception that such methods are …

Fiscal rules are laws aimed at reducing the incentive to accumulate debt, and many
countries adopt them to discipline local governments. Yet, their effectiveness is disputed …