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12/31/2022
Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators
The density weighted average derivative (DWAD) of a regression function ...
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10/28/2020
Deep Learning for Individual Heterogeneity
We propose a methodology for effectively modeling individual heterogenei...
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06/01/2019
lspartition: Partitioning-Based Least Squares Regression
Nonparametric partitioning-based least squares regression is an importan...
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06/01/2019
nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference
Nonparametric kernel density and local polynomial regression estimators ...
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02/25/2019
Binscatter Regressions
We introduce the Stata (and R) package Binsreg, which implements the bin...
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02/25/2019
On Binscatter
Binscatter is very popular in applied microeconomics. It provides a flex...
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09/26/2018
Deep Neural Networks for Estimation and Inference: Application to Causal Effects and Other Semiparametric Estimands
We study deep neural networks and their use in semiparametric inference....
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09/11/2018
Regression Discontinuity Designs Using Covariates
We study regression discontinuity designs when covariates are included i...
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09/10/2018
Characteristic-Sorted Portfolios: Estimation and Inference
Portfolio sorting is ubiquitous in the empirical finance literature, whe...
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09/01/2018
Optimal Bandwidth Choice for Robust Bias Corrected Inference in Regression Discontinuity Designs
Modern empirical work in Regression Discontinuity (RD) designs employs l...
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08/04/2018
Coverage Error Optimal Confidence Intervals
We propose a framework for ranking confidence interval estimators in ter...
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04/13/2018