Policy evaluation for temporal and/or spatial dependent experiments

Luo, Shikai, Yang, Ying, Shi, Chengchun ORCID: 0000-0001-7773-2099, 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, 86 (3). 623 - 649. ISSN 1369-7412

Text (Policy Evaluation for Temporal and or Spatial Dependent Experiments) - Accepted Version Repository staff only until 5 January 2025. Download (7MB)

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Abstract

The aim of this article 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 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 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
Official URL:	https://academic.oup.com/jrsssb
Additional Information:	© 2024 The Royal Statistical Society
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	23 Apr 2024 08:39
Last Modified:	20 Dec 2024 00:53
URI:	http://eprints.lse.ac.uk/id/eprint/122741

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