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20162026
most citedEstimation of Conditional Average Treatment Effects with High-Dimensional Data

13 citations · 21 across the 8 of their papers we have counts for

collaborators

8 papers

econ.EM2026

Testing for Monotone Equilibrium Strategies in Games of Incomplete Information

Yu-Chin Hsu, Tong Li, Chu-An Liu +1

This paper develops a unified framework for testing monotonicity of Bayesian Nash equilibrium strategies in unobserved types in games of incomplete information. We show that, under…

econ.EM2023★ 1 cited

Doubly Robust Estimation of Direct and Indirect Quantile Treatment Effects with Machine Learning

Yu-Chin Hsu, Martin Huber, Yu-Min Yen

We suggest double/debiased machine learning estimators of direct and indirect quantile treatment effects under a selection-on-observables assumption. This permits disentangling the…

econ.EM2021★ 3 cited

Inference for ROC Curves Based on Estimated Predictive Indices

Yu-Chin Hsu, Robert P. Lieli

We provide a comprehensive theory of conducting in-sample statistical inference about receiver operating characteristic (ROC) curves that are based on predicted values from a first…

econ.EM2021

Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data

Yu-Chin Hsu, Martin Huber, Ying-Ying Lee +1

While most treatment evaluations focus on binary interventions, a growing literature also considers continuously distributed treatments. We propose a Cramér-von Mises-type test for…

econ.EM2019★ 13 cited

Estimation of Conditional Average Treatment Effects with High-Dimensional Data

Qingliang Fan, Yu-Chin Hsu, Robert P. Lieli +1

Given the unconfoundedness assumption, we propose new nonparametric estimators for the reduced dimensional conditional average treatment effect (CATE) function. In the first stage,…

econ.EM2018

Testing for Unobserved Heterogeneous Treatment Effects with Observational Data

Yu-Chin Hsu, Ta-Cheng Huang, Haiqing Xu

Unobserved heterogeneous treatment effects have been emphasized in the recent policy evaluation literature (see e.g., Heckman and Vytlacil, 2005). This paper proposes a nonparametr…

stat.ME2017★ 4 cited

Robust Uniform Inference for Quantile Treatment Effects in Regression Discontinuity Designs

Harold D. Chiang, Yu-Chin Hsu, Yuya Sasaki

The practical importance of inference with robustness against large bandwidths for causal effects in regression discontinuity and kink designs is widely recognized. Existing robust…

stat.ME2016

Testing for unobserved heterogeneous treatment effects

YuChin Hsu, TaCheng Huang, Haiqing Xu

Unobserved heterogeneous treatment effects have been emphasized in recent policy evaluation literature. In this paper, we extend Lu and White (2014)'s testing method for unobserved…