Forests for Differences: Robust Causal Inference Beyond Parametric DiD

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Forests for Differences: Robust Causal Inference Beyond Parametric DiD

14 May 2025

Hugo Gobato Souto

Francisco Louzada Neto

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Papers citing "Forests for Differences: Robust Causal Inference Beyond Parametric DiD"

11 / 11 papers shown

Title
Trade-off Between Dependence and Complexity for Nonparametric Learning -- an Empirical Process Approach Nabarun Deb Debarghya Mukherjee 48 2 0 17 Jan 2024
Fairness Implications of Heterogeneous Treatment Effect Estimation with Machine Learning Methods in Policy-making Patrick Rehill Nicholas Biddle SyDa CML 62 2 0 02 Sep 2023
Stochastic Tree Ensembles for Estimating Heterogeneous Effects Nikolay M. Krantsevich Jingyu He P. R. Hahn CML 75 13 0 15 Sep 2022
DoubleML -- An Object-Oriented Implementation of Double Machine Learning in Python Philipp Bach Victor Chernozhukov Malte S. Kurz Martin Spindler VLM GP 48 36 0 07 Apr 2021
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms Alicia Curth M. Schaar CML 163 149 0 26 Jan 2021
Stochastic tree ensembles for regularized nonlinear regression Jingyu He Richard Hahn 53 30 0 09 Feb 2020
Design-based Analysis in Difference-In-Differences Settings with Staggered Adoption Susan Athey Guido Imbens 28 633 0 15 Aug 2018
Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning Sören R. Künzel Jasjeet Sekhon Peter J. Bickel Bin Yu CML 164 930 0 12 Jun 2017
Generalized Optimal Matching Methods for Causal Inference Nathan Kallus 173 108 0 26 Dec 2016
Generalized Random Forests Susan Athey J. Tibshirani Stefan Wager 339 1,371 0 05 Oct 2016
BART: Bayesian additive regression trees H. Chipman E. George R. McCulloch 158 1,796 0 19 Jun 2008