27 citations · 79 across the 11 of their papers we have counts for
13 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…
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…
Optimal Estimation of Large-Dimensional Nonlinear Factor Models
Yingjie Feng
This paper studies optimal estimation of large-dimensional nonlinear factor models. The key challenge is that the observed variables are possibly nonlinear functions of some latent…
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…
Beta-Sorted Portfolios
Matias D. Cattaneo, Richard K. Crump, Weining Wang +1
Beta-sorted portfolios---portfolios comprised of assets with similar covariation with selected risk factors---are a popular tool in empirical finance to analyze models of (conditio…
scpi: Uncertainty Quantification for Synthetic Control Methods
Matias D. Cattaneo, Yingjie Feng, Filippo Palomba +1
The synthetic control method offers a way to quantify the effect of an intervention using weighted averages of untreated units to approximate the counterfactual outcome that the tr…
Uniform Inference for Kernel Density Estimators with Dyadic Data
Matias D. Cattaneo, Yingjie Feng, William G. Underwood
Dyadic data is often encountered when quantities of interest are associated with the edges of a network. As such it plays an important role in statistics, econometrics and many oth…
Causal Inference in Possibly Nonlinear Factor Models
Yingjie Feng
This paper develops a causal inference method for treatment effects models with noisily measured confounders. The key feature is that a large number of noisy proxies are available…
Prediction Intervals for Synthetic Control Methods
Matias D. Cattaneo, Yingjie Feng, Rocio Titiunik
Uncertainty quantification is a fundamental problem in the analysis and interpretation of synthetic control (SC) methods. We develop conditional prediction intervals in the SC fram…
lspartition: Partitioning-Based Least Squares Regression
Matias D. Cattaneo, Max H. Farrell, Yingjie Feng
Nonparametric partitioning-based least squares regression is an important tool in empirical work. Common examples include regressions based on splines, wavelets, and piecewise poly…
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…
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…
Large Sample Properties of Partitioning-Based Series Estimators
Matias D. Cattaneo, Max H. Farrell, Yingjie Feng
We present large sample results for partitioning-based least squares nonparametric regression, a popular method for approximating conditional expectation functions in statistics, e…