Program evaluation methods are widely applied in economics to assess the effects of policy
interventions and other treatments of interest. In this article, we describe the main …

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 …

In this Element, which continues our discussion in Foundations, the authors provide an
accessible and practical guide for the analysis and interpretation of Regression …

This article introduces an intuitive and easy-to-implement nonparametric density estimator
based on local polynomial techniques. The estimator is fully boundary adaptive and …

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

We describe a major upgrade to the Stata (and R) rdrobust package, which provides a wide
array of estimation, inference, and falsification methods for the analysis and interpretation of …

We study regression discontinuity designs when covariates are included in the estimation.
We examine local polynomial estimators that include discrete or continuous covariates in an …

In this article, we introduce two community-contributed commands, rddensity and
rdbwdensity, that implement automatic manipulation tests based on density discontinuity …

Randomization inference or permutation tests are only sporadically used in economics and
other social sciences—this despite a steep increase in randomization in field and laboratory …

We consider a regression discontinuity (RD) design where the treatment is received if a
score is above a cutoff, but the cutoff may vary for each unit in the sample instead of being …