Could regression of stationary series be spurious?

Wing-Keung Wong, Yushan Cheng and Mu Yue
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Wing-Keung Wong: Department of Finance, Fintech Center, and Big Data Research Center, Asia University; Department of Medical Research, China Medical University Hospital, Taiwan; Department of Economics and Finance, The Hang Seng University of Hong Kong
Yushan Cheng: School of Mathematics and Statistics, Xi’an Jiaotong University, China
Mu Yue: Engineering Systems and Design, Singapore University of Technology & Design

No 2503, Economic Growth Centre Working Paper Series from Nanyang Technological University, School of Social Sciences, Economic Growth Centre

Abstract: Most of the literature on spurious regression has found that regression of independent and (nearly) non-stationary time series could result in spurious outcomes. Very few studies address the issue of whether regression of stationary time series could also result in spurious outcomes and the study is not comprehensive and thorough. To bridge the gap in the literature, we first conjecture that regression of stationary time series could also result in spurious outcomes. We then examine whether the conjecture holds by providing a comprehensive and thorough study. We further provide a remedy algorithm to correct the spurious problem and improve the interpretability of the model. Extensive simulations are carried out to support our conjecture and demonstrate the effectiveness of the remedy. To demonstrate the applicability of our proposed approach and address the issue of spuriousness, we conduct a numerical analysis and demonstrate the usefulness of our proposed remedy algorithm.

Keywords: spurious regression; stationarity; non-stationarity; autoregressive model. (search for similar items in EconPapers)
JEL-codes: C01 C15 C22 C58 C60 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2025-03
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Persistent link: https://EconPapers.repec.org/RePEc:nan:wpaper:2503

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