537 citations · 716 across the 19 of their papers we have counts for
10 papers · 1 filter
Boundary Discontinuity Designs: Theory and Practice
Matias D. Cattaneo, Rocio Titiunik, Ruiqi Rae Yu
The boundary discontinuity (BD) design is a non-experimental method for identifying causal effects that exploits a thresholding rule based on a bivariate score and a boundary curve…
Estimation and Inference in Boundary Discontinuity Designs: Distance-Based Methods
Matias D. Cattaneo, Rocio Titiunik, Ruiqi Rae Yu
We study nonparametric distance-based (isotropic) local polynomial methods for estimating the boundary average treatment effect curve, a causal functional that captures treatment e…
rdhte: Conditional Average Treatment Effects in RD Designs
Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell +2
Understanding causal heterogeneous treatment effects based on pretreatment covariates is a crucial aspect of empirical work. Building on Calonico, Cattaneo, Farrell, Palomba, and T…
Estimation and Inference in Boundary Discontinuity Designs: Location-Based Methods
Matias D. Cattaneo, Rocio Titiunik, Ruiqi Rae Yu
Boundary discontinuity designs are used to learn about causal treatment effects along a continuous assignment boundary that splits units into control and treatment groups according…
Treatment Effect Heterogeneity in Regression Discontinuity Designs
Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell +2
Empirical studies using Regression Discontinuity (RD) designs often explore heterogeneous treatment effects based on pretreatment covariates, even though no formal statistical meth…
Uncertainty Quantification in Synthetic Controls with Staggered Treatment Adoption
Matias D. Cattaneo, Yingjie Feng, Filippo Palomba +1
We propose principled prediction intervals to quantify the uncertainty of a large class of synthetic control predictions (or estimators) in settings with staggered treatment adopti…
Regression Discontinuity Designs
Matias D. Cattaneo, Rocio Titiunik
The Regression Discontinuity (RD) design is one of the most widely used non-experimental methods for causal inference and program evaluation. Over the last two decades, statistical…
The Regression Discontinuity Design
Matias D. Cattaneo, Rocio Titiunik, Gonzalo Vazquez-Bare
This handbook chapter gives an introduction to the sharp regression discontinuity design, covering identification, estimation, inference, and falsification methods.
Regression Discontinuity Designs Using Covariates
Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell +1
We study regression discontinuity designs when covariates are included in the estimation. We examine local polynomial estimators that include discrete or continuous covariates in a…
Extrapolating Treatment Effects in Multi-Cutoff Regression Discontinuity Designs
Matias D. Cattaneo, Luke Keele, Rocio Titiunik +1
In non-experimental settings, the Regression Discontinuity (RD) design is one of the most credible identification strategies for program evaluation and causal inference. However, R…