13 citations · 21 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…
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,…
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…