首页|Robust Estimation of Average Treatment Effects with Observational Studies

Robust Estimation of Average Treatment Effects with Observational Studies

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Estimating treatment effects has always been one of the hot issues in empirical research.It brings great challenges to estimating treatment effects because heterogeneity exists in the distribution of covariates between treated and controlled groups.Propensity score methods have been widely used to adjust for heterogeneity in observational studies.However,the propensity score is usually unknown and needs to be estimated.In this article,we propose a generalized single-index model to estimate the propensity score and use the propensity score residuals to reduce the estimation bias.The finite-sample performance of the proposed method is evaluated through simulation stud-ies.We use the proposed method to evaluate the policy of"Sunshine Running"and find that the physical test scores of college students par-ticipating in the"Sunshine Running"can be improved by 3.72 points.

treatment effectpropensity scoregeneralized single-index modelpartial linear model

XIAO Li、YU Peichao

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Department of Physical Education,Guilin University of Aerospace Technology,Guilin 541004,Guangxi,China

School of Statistics and Mathematics,Zhongnan University of Economics and Law,Wuhan 430073,Hubei,China

2020 Guilin University of Aerospace Technology Teaching Group Construction Project2021 Guangxi Philosophy and Social Science Research Project2022 Guangxi Higher Education Undergraduate Teaching Reform Project

2020JXTD1921FTY0122022JGA358

2024

10.1051/wujns/2024292117

武汉大学自然科学学报(英文版)
武汉大学

武汉大学自然科学学报(英文版)

CSTPCD
影响因子：0.066
ISSN：1007-1202
年,卷(期)：2024.29(2)
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