1 citations · 1 across the 7 of their papers we have counts for
7 papers
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…
Accuracy Limits of Causal Trees for Individualized Treatment Effects
Matias D. Cattaneo, Jason M. Klusowski, Ruiqi Rae Yu
Recursive decision trees are widely used to estimate heterogeneous causal treatment effects in experimental and observational studies. These methods are typically implemented using…
rd2d: Causal Inference in Boundary Discontinuity Designs
Matias D. Cattaneo, Rocio Titiunik, Ruiqi Rae Yu
Boundary Discontinuity (BD) designs are used in empirical research to learn about causal treatment effects along a continuous assignment boundary defined by a bivariate score. Thes…
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…
Robust Inference for the Direct Average Treatment Effect with Treatment Assignment Interference
Matias D. Cattaneo, Yihan He, Ruiqi Rae Yu
This paper develops methods for uncertainty quantification in causal inference settings with random network interference. We study the large-sample distributional properties of the…
Strong Approximations for Empirical Processes Indexed by Lipschitz Functions
Matias D. Cattaneo, Ruiqi Rae Yu
This paper presents new uniform Gaussian strong approximations for empirical processes indexed by classes of functions based on -variate random vectors (). First, a unif…