537 citations · 887 across the 42 of their papers we have counts for
20 papers · 1 filter
Robust Inference for Convex Pairwise Difference Estimators
Matias D. Cattaneo, Michael Jansson, Kenichi Nagasawa
This paper develops distribution theory and bootstrap-based inference methods for a broad class of convex pairwise difference estimators. These estimators minimize a kernel-weighte…
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…
Continuity of the Distribution Function of the argmax of a Gaussian Process
Matias D. Cattaneo, Gregory Fletcher Cox, Michael Jansson +1
Certain extremum estimators have asymptotic distributions that are non-Gaussian, yet characterizable as the distribution of the of a Gaussian process. This paper presents…
Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators
Matias D. Cattaneo, Max H. Farrell, Michael Jansson +1
The density weighted average derivative (DWAD) of a regression function is a canonical parameter of interest in economics. Classical first-order large sample distribution theory fo…
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…
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…
Local Regression Distribution Estimators
Matias D. Cattaneo, Michael Jansson, Xinwei Ma
This paper investigates the large sample properties of local regression distribution estimators, which include a class of boundary adaptive density estimators as a prime example. F…
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.
Average Density Estimators: Efficiency and Bootstrap Consistency
Matias D. Cattaneo, Michael Jansson
This paper highlights a tension between semiparametric efficiency and bootstrap consistency in the context of a canonical semiparametric estimation problem, namely the problem of e…
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…
Simple Local Polynomial Density Estimators
Matias D. Cattaneo, Michael Jansson, Xinwei Ma
This paper introduces an intuitive and easy-to-implement nonparametric density estimator based on local polynomial techniques. The estimator is fully boundary adaptive and automati…
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…
Characteristic-Sorted Portfolios: Estimation and Inference
Matias D. Cattaneo, Richard K. Crump, Max H. Farrell +1
Portfolio sorting is ubiquitous in the empirical finance literature, where it has been widely used to identify pricing anomalies. Despite its popularity, little attention has been…
Optimal Bandwidth Choice for Robust Bias Corrected Inference in Regression Discontinuity Designs
Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell
Modern empirical work in Regression Discontinuity (RD) designs often employs local polynomial estimation and inference with a mean square error (MSE) optimal bandwidth choice. This…
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…
Coverage Error Optimal Confidence Intervals for Local Polynomial Regression
Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell
This paper studies higher-order inference properties of nonparametric local polynomial regression methods under random sampling. We prove Edgeworth expansions for statistics an…
Two-Step Estimation and Inference with Possibly Many Included Covariates
Matias D. Cattaneo, Michael Jansson, Xinwei Ma
We study the implications of including many covariates in a first-step estimate entering a two-step estimation procedure. We find that a first order bias emerges when the number of…
A Random Attention Model
Matias D. Cattaneo, Xinwei Ma, Yusufcan Masatlioglu +1
This paper illustrates how one can deduce preference from observed choices when attention is not only limited but also random. In contrast to earlier approaches, we introduce a Ran…