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Spurious Regression

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  • D. Ventosa-Santaulària

Abstract

The spurious regression phenomenon in least squares occurs for a wide range of data generating processes, such as driftless unit roots, unit roots with drift, long memory, trend and broken-trend stationarity. Indeed, spurious regressions have played a fundamental role in the building of modern time series econometrics and have revolutionized many of the procedures used in applied macroeconomics. Spin-offs from this research range from unit-root tests to cointegration and error-correction models. This paper provides an overview of results about spurious regression, pulled from disperse sources, and explains their implications.

Suggested Citation

  • D. Ventosa-Santaulària, 2009. "Spurious Regression," Journal of Probability and Statistics, Hindawi, vol. 2009, pages 1-27, August.
    • Handle: RePEc:hin:jnljps:802975
    DOI: 10.1155/2009/802975
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    2. Chris Stewart, 2011. "A note on spurious significance in regressions involving I(0) and I(1) variables," Empirical Economics, Springer, vol. 41(3), pages 565-571, December.
    3. Faruq-Uz-Zaman, Muhammad, 2021. "Contribution of Factors Affecting Crop Production in Bangladesh: An Empirical Analysis with Production Function Approach," OSF Preprints kxaym, Center for Open Science.
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    5. Sproule, Robert & Gosselin, Gabriel, 2023. "Is the research agenda for calendar anomalies “much do about nothing”?," MPRA Paper 117001, University Library of Munich, Germany.
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    7. García-Belmonte, Lizeth & Ventosa-Santaulària, Daniel, 2011. "Spurious regression and lurking variables," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 2004-2010.
    8. Akinci, Dervis Ahmet & Matousek, Roman & Radić, Nemanja & Stewart, Chris, 2013. "Monetary policy and the banking sector in Turkey," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 269-285.
    9. Heagney, E.C. & Falster, D.S. & Kovač, M., 2021. "Land clearing in south-eastern Australia: Drivers, policy effects and implications for the future," Land Use Policy, Elsevier, vol. 102(C).
    10. Ghouse, Ghulam & Khan, Saud Ahmed & Rehman, Atiq Ur, 2018. "ARDL model as a remedy for spurious regression: problems, performance and prospectus," MPRA Paper 83973, University Library of Munich, Germany.
    11. Kruse Robinson & Ventosa-Santaulària Daniel & Noriega Antonio E., 2017. "Changes in persistence, spurious regressions and the Fisher hypothesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(3), pages 1-28, June.
    12. Sizova, Natalia, 2014. "A frequency-domain alternative to long-horizon regressions with application to return predictability," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 261-272.
    13. Gueorgui I. Kolev, 2011. "The "spurious regression problem" in the classical regression model framework," Economics Bulletin, AccessEcon, vol. 31(1), pages 925-937.

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    14. Travaglini, Guido, 2007. "The U.S. Dynamic Taylor Rule With Multiple Breaks, 1984-2001," MPRA Paper 3419, University Library of Munich, Germany, revised 15 Jun 2007.
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    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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