Model averaging with causal effects for partially linear models

Model averaging with causal effects for partially linear models

Treatment effects with heterogeneity and heteroskedasticity are widely studied and applied in many fields, such as statistics and econometrics. The conditional average treatment effect provides an excellent measure of the heterogeneous treatment effect. In this paper, we propose a model averaging es...

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Bibliographic Details
Main Authors: Xiaowei Zhang, Junliang Li
Format: Article
Language:English
Published: AIMS Press 2024-05-01
Series:AIMS Mathematics
Subjects:
model averaging
causal inference
partially linear models
conditional average treatment effect
jackknife-type criterion
Online Access:https://www.aimspress.com/article/doi/10.3934/math.2024794?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/math.2024794?viewType=HTML

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