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 …

Examining a shock to the salience of the sustainability of the US mutual fund market, we
present causal evidence that investors marketwide value sustainability: being categorized …

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

The most remarkable global climate agreement to date, the Paris Agreement of 2015
requires all countries to set emissions-reduction commitments. However, experts say that the …

Governments regularly subsidize new ventures to spur innovation. This paper conducts the
first large-sample, quasi-experimental evaluation of R&D subsidies. I use data on ranked …

An extensive theoretical and qualitative literature stresses the promise of instructional
practices and content aligned with minority students' experiences. Ethnic studies courses …

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 …

We consider inference in regression discontinuity designs when the running variable only
takes a moderate number of distinct values. In particular, we study the common practice of …