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 …

Propensity score matching (PSM) has become a popular approach to estimate causal
treatment effects. It is widely applied when evaluating labour market policies, but empirical …

Linear instrumental variable estimators, such as two-stage least squares (TSLS), are
commonly interpreted as estimating positively weighted averages of causal effects, referred …

Generalized random forests Page 1 The Annals of Statistics 2019, Vol. 47, No. 2, 1148–1178
https://doi.org/10.1214/18-AOS1709 © Institute of Mathematical Statistics, 2019 GENERALIZED …

Gun violence is the most pressing public safety problem in US cities. We report results from
a randomized controlled trial (N= 2,456) of a community-researcher partnership called the …

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

We develop a framework for welfare analysis of interventions designed to increase take-up
of social safety net programs in the presence of potential behavioral biases. We calibrate the …

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 many areas, practitioners seek to use observational data to learn a treatment assignment
policy that satisfies application‐specific constraints, such as budget, fairness, simplicity, or …

Abstract Communities across the United States are reconsidering the public safety benefits
of prosecuting nonviolent misdemeanor offenses, yet there is little empirical evidence to …