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20192026
most citedEstimation of Conditional Average Treatment Effects with High-Dimensional Data

13 citations · 17 across the 5 of their papers we have counts for

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5 papers

stat.ME2026

Identification and Robust Inference for Multiple Treatments with Possibly Invalid Instruments

Ziwei Mei, Qingliang Fan, Zijian Guo

The instrumental variable (IV) method is widely used to infer causal effects in observational studies with unmeasured confounding, but invalid instruments can compromise both popul…

stat.ME2022★ 2 cited

On the instrumental variable estimation with many weak and invalid instruments

Yiqi Lin, Frank Windmeijer, Xinyuan Song +1

We discuss the fundamental issue of identification in linear instrumental variable (IV) models with unknown IV validity. With the assumption of the "sparsest rule", which is equiva…

econ.EM2022

A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates

Qingliang Fan, Zijian Guo, Ziwei Mei

This paper proposes an overidentifying restriction test for high-dimensional linear instrumental variable models. The novelty of the proposed test is that it allows the number of c…

econ.EM2020★ 2 cited

Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments

Qingliang Fan, Yaqian Wu

Instrumental variables (IV) regression is a popular method for the estimation of the endogenous treatment effects. Conventional IV methods require all the instruments are relevant…

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,…