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Could regression of stationary series be spurious?
Author(s)
Date Issued
2024
Publisher
World Scientific Pub Co Pte Ltd
ISSN
0217-5959
1793-7019
Citation
Asia-Pacific Journal of Operational Research, 2024.
Type
Peer Reviewed Journal Article
Abstract
Spurious regression, commonly associated with independent and (nearly) non-stationary time series, has been extensively studied. However, the potential for spurious outcomes in regression involving stationary time series remains largely unexplored, representing a gap in the literature. To address this gap, we propose that regression of stationary time series may yield spurious outcomes and conduct a comprehensive investigation to verify this conjecture. Additionally, we present a remedy algorithm to mitigate spurious effects and improve model interpretability. Through extensive simulations, we validate our conjecture and demonstrate the efficacy of the proposed remedy. A numerical analysis further illustrates the practical utility of our approach. This study offers a fresh perspective on spurious regression and provides a practical solution to enhance the reliability of regression analyses involving stationary time series data.
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