Policy evaluation for temporal and/or spatial dependent experiments

Luo, Shikai, Yang, Ying, Shi, Chengchun, Yao, Fang, Ye, Jieping and Zhu, Hongtu (2024) Policy evaluation for temporal and/or spatial dependent experiments. Journal of the Royal Statistical Society. Series B: Statistical Methodology. ISSN 1369-7412

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Abstract

The aim of this paper is to establish a causal link between the policies implemented by technology companies and the outcomes they yield within intricate temporal and/or spatial dependent experiments. We propose a novel temporal/spatio-temporal Varying Coefficient Decision Process (VCDP) model, capable of effectively capturing the evolving treatment effects in situations characterized by temporal and/or spatial dependence. Our methodology encompasses the decomposition of the Average Treatment Effect (ATE) into the Direct Effect (DE) and the Indirect Effect (IE). We subsequently devise comprehensive procedures for estimating and making inferences about both DE and IE. Additionally, we provide a rigorous analysis of the statistical properties of these procedures, such as asymptotic power. To substantiate the effectiveness of our approach, we carry out extensive simulations and real data analyses.

Item Type:	Article
Additional Information:	© 2024 The Royal Statistical Society
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	23 Apr 2024 08:39
Last Modified:	29 Apr 2024 09:02
URI:	http://eprints.lse.ac.uk/id/eprint/122741

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