IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v41y2011i3p565-571.html
   My bibliography  Save this article

A note on spurious significance in regressions involving I(0) and I(1) variables

Author

Listed:
  • Chris Stewart

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:empeco:v:41:y:2011:i:3:p:565-571
    DOI: 10.1007/s00181-010-0404-5
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00181-010-0404-5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00181-010-0404-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. D. Ventosa-Santaulària, 2009. "Spurious Regression," Journal of Probability and Statistics, Hindawi, vol. 2009, pages 1-27, August.
    2. P. C. B. Phillips & S. N. Durlauf, 1986. "Multiple Time Series Regression with Integrated Processes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 473-495.
    3. Sun, Yixiao, 2006. "Spurious regressions between stationary generalized long memory processes," Economics Letters, Elsevier, vol. 90(3), pages 446-454, March.
    4. Park, Joon Y. & Phillips, Peter C.B., 1989. "Statistical Inference in Regressions with Integrated Processes: Part 2," Econometric Theory, Cambridge University Press, vol. 5(1), pages 95-131, April.
    5. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    6. Clive Granger & Namwon Hyung & Yongil Jeon, 2001. "Spurious regressions with stationary series," Applied Economics, Taylor & Francis Journals, vol. 33(7), pages 899-904.
    7. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
    8. Uwe Hassler, 2003. "Nonsense regressions due to neglected time-varying means," Statistical Papers, Springer, vol. 44(2), pages 169-182, April.
    9. Nelson, Charles R & Kang, Heejoon, 1984. "Pitfalls in the Use of Time as an Explanatory Variable in Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(1), pages 73-82, January.
    10. Haldrup, Niels, 1994. "The asymptotics of single-equation cointegration regressions with I(1) and I(2) variables," Journal of Econometrics, Elsevier, vol. 63(1), pages 153-181, July.
    11. Antonio E. Noriega & Daniel Ventosa‐Santaulària, 2007. "Spurious Regression and Trending Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(3), pages 439-444, June.
    12. Marmol, Francesc, 1998. "Spurious regression theory with nonstationary fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 84(2), pages 233-250, June.
    13. Thomas Mikosch & Casper G. de Vries, 2006. "Tail Probabilities for Regression Estimators," Tinbergen Institute Discussion Papers 06-085/2, Tinbergen Institute.
    14. Kim, Tae-Hwan & Lee, Young-Sook & Newbold, Paul, 2004. "Spurious regressions with stationary processes around linear trends," Economics Letters, Elsevier, vol. 83(2), pages 257-262, May.
    15. Marmol, Francesc, 1996. "Nonsense Regressions between Integrated Processes of Different Orders," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(3), pages 525-536, August.
    16. Tsay, Wen-Jen & Chung, Ching-Fan, 2000. "The spurious regression of fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 96(1), pages 155-182, May.
    17. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    18. Stewart, Chris, 2006. "Spurious correlation of I(0) regressors in models with an I(1) dependent variable," Economics Letters, Elsevier, vol. 91(2), pages 184-189, May.
    19. Francesc Marmol, 1995. "SPURIOUS REGRESSIONS BETWEEN I(d) PROCESSES," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(3), pages 313-321, May.
    20. Thomas Mikosch & Catalin Starica, 2004. "Non-stationarities in financial time series, the long range dependence and the IGARCH effects," Econometrics 0412005, University Library of Munich, Germany.
    21. Hassler, Uwe, 1996. "Spurious regressions when stationary regressors are included," Economics Letters, Elsevier, vol. 50(1), pages 25-31, January.
    22. Durlauf, Steven N & Phillips, Peter C B, 1988. "Trends versus Random Walks in Time Series Analysis," Econometrica, Econometric Society, vol. 56(6), pages 1333-1354, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Herzer Dierk, 2022. "Semi-endogenous Versus Schumpeterian Growth Models: A Critical Review of the Literature and New Evidence," Review of Economics, De Gruyter, vol. 73(1), pages 1-55, April.
    2. Kilian, Lutz & Zhou, Xiaoqing, 2020. "Oil Prices, Gasoline Prices and Inflation Expectations: A New Model and New Facts," CEPR Discussion Papers 15168, C.E.P.R. Discussion Papers.
    3. Daniela Osterrieder & Daniel Ventosa-Santaulària & J. Eduardo Vera-Valdés, 2015. "Unbalanced Regressions and the Predictive Equation," CREATES Research Papers 2015-09, Department of Economics and Business Economics, Aarhus University.
    4. Pietro Giorgio Lovaglio & Mario Mezzanzanica & Emilio Colombo, 2020. "Comparing time series characteristics of official and web job vacancy data," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 85-98, February.
    5. Engsted, Tom & Pedersen, Thomas Q., 2015. "Predicting returns and rent growth in the housing market using the rent-price ratio: Evidence from the OECD countries," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 257-275.
    6. David Strauss & Daniel Ventosa-Santaularia, 2023. "Does r-g cause wealth inequality? The case of the United States/¿La r-g causa la desigualdad de la riqueza? El caso de Estados Unidos," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 38(2), pages 183-224.
    7. Balaguer, Jacint & Ripollés, Jordi, 2018. "The dynamics pattern of price dispersion in retail fuel markets," Energy Economics, Elsevier, vol. 74(C), pages 546-564.
    8. Tuomas Malinen, 2011. "Income Inequality and Savings: A Reassessment of the Relationship in Cointegrated Panels," DEGIT Conference Papers c016_076, DEGIT, Dynamics, Economic Growth, and International Trade.
    9. Hao Jin & Si Zhang & Jinsuo Zhang, 2017. "Spurious regression due to neglected of non-stationary volatility," Computational Statistics, Springer, vol. 32(3), pages 1065-1081, September.
    10. Pietro Giorgio Lovaglio, 2022. "Do job vacancies variations anticipate employment variations by sector? Some preliminary evidence from Italy," LABOUR, CEIS, vol. 36(1), pages 71-93, March.
    11. Lutz Kilian & Xiaoqing Zhou, 2022. "Oil prices, gasoline prices, and inflation expectations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 867-881, August.
    12. Tuomas, Malinen, 2011. "Inequality and savings: a reassesment of the relationship in cointegrated panels," MPRA Paper 33350, University Library of Munich, Germany.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Noriega Antonio E. & Ventosa-Santaulària Daniel, 2011. "A Simple Test for Spurious Regressions," Working Papers 2011-05, Banco de México.
    2. Stewart, Chris, 2006. "Spurious correlation of I(0) regressors in models with an I(1) dependent variable," Economics Letters, Elsevier, vol. 91(2), pages 184-189, May.
    3. D. Ventosa-Santaulària, 2009. "Spurious Regression," Journal of Probability and Statistics, Hindawi, vol. 2009, pages 1-27, August.
    4. Mármol, Francesc, 1999. "How spurious features arise in case of fractional cointegration," DES - Working Papers. Statistics and Econometrics. WS 6349, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Antonio E. Noriega & Daniel Ventosa‐Santaulària, 2007. "Spurious Regression and Trending Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(3), pages 439-444, June.
    6. Zhang, Lingxiang, 2013. "Partial unit root and linear spurious regression: A Monte Carlo simulation study," Economics Letters, Elsevier, vol. 118(1), pages 189-191.
    7. 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.
    8. Antonio E. Noriega & School of Economics, University of Guanajuato & Daniel Ventosa-Santaulà ria & School of Economics, University of Guanajuato, 2006. "Spurious regression and econometric trends," Computing in Economics and Finance 2006 151, Society for Computational Economics.
    9. Antonio E. Noriega & Daniel Ventosa‐Santaulària, 2006. "Spurious Regression Under Broken‐Trend Stationarity," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(5), pages 671-684, September.
    10. Phillips, Peter C.B., 2005. "Challenges of trending time series econometrics," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(5), pages 401-416.
    11. Noriega, Antonio E. & Ventosa-Santaulària, Daniel, 2005. "Spurious regression under deterministic and stochastic trends," MPRA Paper 58772, University Library of Munich, Germany.
    12. Hao Jin & Si Zhang & Jinsuo Zhang, 2017. "Spurious regression due to neglected of non-stationary volatility," Computational Statistics, Springer, vol. 32(3), pages 1065-1081, September.
    13. Jin, Hao & Zhang, Jinsuo & Zhang, Si & Yu, Cong, 2013. "The spurious regression of AR(p) infinite-variance sequence in the presence of structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 25-40.
    14. Peter C. B. Phillips & Xiaohu Wang & Yonghui Zhang, 2019. "HAR Testing for Spurious Regression in Trend," Econometrics, MDPI, vol. 7(4), pages 1-28, December.
    15. Kim, Chang Sik & Lee, Sungro, 2011. "Spurious regressions driven by excessive volatility," Economics Letters, Elsevier, vol. 113(3), pages 292-297.
    16. 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.
    17. Marmol, Francesc, 1998. "Spurious regression theory with nonstationary fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 84(2), pages 233-250, June.
    18. Ferson, Wayne E. & Sarkissian, Sergei & Simin, Timothy, 2008. "Asset Pricing Models with Conditional Betas and Alphas: The Effects of Data Snooping and Spurious Regression," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(2), pages 331-353, June.
    19. Hassler, Uwe, 1999. "Nonsense regressions due to time-varying means," DES - Working Papers. Statistics and Econometrics. WS 6361, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. Peter C.B. Phillips, 1994. "Nonstationary Time Series and Cointegration: Recent Books and Themes for the Future," Cowles Foundation Discussion Papers 1081, Cowles Foundation for Research in Economics, Yale University.

    More about this item

    Keywords

    Spurious significance; Unbalanced regression; C01; C15;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:empeco:v:41:y:2011:i:3:p:565-571. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.