5 papers
Uniform Estimation and Inference for Nonparametric Partitioning-Based M-Estimators
Matias D. Cattaneo, Yingjie Feng, Boris Shigida
This paper presents uniform estimation and inference theory for a large class of nonparametric partitioning-based M-estimators. The main theoretical results include: (i) uniform co…
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…
Binscatter Regressions
Matias D. Cattaneo, Richard K. Crump, Max H. Farrell +1
We introduce the package Binsreg, which implements the binscatter methods developed by Cattaneo, Crump, Farrell, and Feng (2024b,a). The package includes seven commands: binsreg, b…
Nonlinear Binscatter Methods
Matias D. Cattaneo, Richard K. Crump, Max H. Farrell +1
Binscatters are a powerful tool for empirical work in the social, behavioral, and biomedical sciences. Available tools rely on least squares estimation of the conditional mean. We…
On Binscatter
Matias D. Cattaneo, Richard K. Crump, Max H. Farrell +1
Binscatter is a popular method for visualizing bivariate relationships and conducting informal specification testing. We study the properties of this method formally and develop en…