IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v26y2021i1p1087-1100.html
   My bibliography  Save this article

Cointegration tests at the quantiles

Author

Listed:
  • Marilena Furno

Abstract

A cointegration test for quantile regressions is proposed and implemented using Italian data. The test relies on auxiliary quantile regression to verify the stationarity of the residuals of the cointegrating equation. According to the problem under analysis, the cointegrating equation may or may not model a structural break, to verify cointegration with or without break. The existing test by Xiao, Journal of Econometrics (2009), 150, 248–260 is a fluctuation type test, which is closely related to Qu, Journal of Econometrics (2008), 146, 170–184 on structural break in quantile regressions. The link between the two tests makes unclear if the fluctuation test verifies cointegration, stability, or possibly cointegration and stability mixed together. Two real data case studies and a Monte Carlo experiment complete the analysis.

Suggested Citation

  • Marilena Furno, 2021. "Cointegration tests at the quantiles," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1087-1100, January.
  • Handle: RePEc:wly:ijfiec:v:26:y:2021:i:1:p:1087-1100
    DOI: 10.1002/ijfe.1837
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.1837
    Download Restriction: no

    File URL: https://libkey.io/10.1002/ijfe.1837?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
    ---><---

    References listed on IDEAS

    as
    1. Matei Demetrescu, 2010. "On the Dickey–Fuller test with White standard errors," Statistical Papers, Springer, vol. 51(1), pages 11-25, January.
    2. Jesús Clemente & María Dolores Gadea & Antonio Montañés & Marcelo Reyes, 2017. "Structural Breaks, Inflation and Interest Rates: Evidence from the G7 Countries," Econometrics, MDPI, vol. 5(1), pages 1-17, February.
    3. Noor Ghazali & Shamshubariah Ramlee, 2003. "A long memory test of the long-run Fisher effect in the G7 countries," Applied Financial Economics, Taylor & Francis Journals, vol. 13(10), pages 763-769.
    4. Xiao, Zhijie, 2009. "Quantile cointegrating regression," Journal of Econometrics, Elsevier, vol. 150(2), pages 248-260, June.
    5. Koenker, Roger & Zhao, Quanshui, 1996. "Conditional Quantile Estimation and Inference for Arch Models," Econometric Theory, Cambridge University Press, vol. 12(5), pages 793-813, December.
    6. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    7. Qu, Zhongjun, 2008. "Testing for structural change in regression quantiles," Journal of Econometrics, Elsevier, vol. 146(1), pages 170-184, September.
    8. Roger Koenker & Zhijie Xiao, 2004. "Unit Root Quantile Autoregression Inference," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 775-787, January.
    9. Uwe Hassler, 2003. "Nonsense regressions due to neglected time-varying means," Statistical Papers, Springer, vol. 44(2), pages 169-182, April.
    10. Hansen, Bruce E., 1995. "Rethinking the Univariate Approach to Unit Root Testing: Using Covariates to Increase Power," Econometric Theory, Cambridge University Press, vol. 11(5), pages 1148-1171, October.
    11. Zivot, Eric, 2000. "The Power Of Single Equation Tests For Cointegration When The Cointegrating Vector Is Prespecified," Econometric Theory, Cambridge University Press, vol. 16(3), pages 407-439, June.
    12. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2012. "Unit root testing under a local break in trend," Journal of Econometrics, Elsevier, vol. 167(1), pages 140-167.
    13. Marilena Furno, 2012. "Tests for structural break in quantile regressions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(4), pages 493-515, October.
    14. Valerie Mignon & Sandrine Lardic, 2003. "Fractional cointegration between nominal interest rates and inflation: A re-examination of the Fisher relationship in the G7 countries," Economics Bulletin, AccessEcon, vol. 3(14), pages 1-10.
    15. Oka, Tatsushi & Qu, Zhongjun, 2011. "Estimating structural changes in regression quantiles," Journal of Econometrics, Elsevier, vol. 162(2), pages 248-267, June.
    16. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    17. Gregory, Allan W & Hansen, Bruce E, 1996. "Tests for Cointegration in Models with Regime and Trend Shifts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(3), pages 555-560, August.
    18. Gregory, Allan W. & Hansen, Bruce E., 1996. "Residual-based tests for cointegration in models with regime shifts," Journal of Econometrics, Elsevier, vol. 70(1), pages 99-126, January.
    19. Saikkonen, Pentti, 1991. "Asymptotically Efficient Estimation of Cointegration Regressions," Econometric Theory, Cambridge University Press, vol. 7(1), pages 1-21, March.
    Full references (including those not matched with items on IDEAS)

    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. Christou, Christina & Gupta, Rangan & Nyakabawo, Wendy & Wohar, Mark E., 2018. "Do house prices hedge inflation in the US? A quantile cointegration approach," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 15-26.
    2. Kuriyama Nina, 2016. "Testing cointegration in quantile regressions with an application to the term structure of interest rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(2), pages 107-121, April.
    3. Cho, Jin Seo & Kim, Tae-hwan & Shin, Yongcheol, 2015. "Quantile cointegration in the autoregressive distributed-lag modeling framework," Journal of Econometrics, Elsevier, vol. 188(1), pages 281-300.
    4. Hosseinkouchack, Mehdi & Wolters, Maik H., 2013. "Do large recessions reduce output permanently?," Economics Letters, Elsevier, vol. 121(3), pages 516-519.
    5. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    6. Troster, Victor & Shahbaz, Muhammad & Uddin, Gazi Salah, 2018. "Renewable energy, oil prices, and economic activity: A Granger-causality in quantiles analysis," Energy Economics, Elsevier, vol. 70(C), pages 440-452.
    7. Emanuele Russo & Neil Foster-McGregor, 2022. "Characterizing growth instability: new evidence on unit roots and structural breaks in countries’ long run trajectories," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 713-756, April.
    8. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," Working Papers halshs-00564897, HAL.
    9. Christian Bauer & Sebastian Weber, 2016. "The Efficiency of Monetary Policy when Guiding Inflation Expectations," Research Papers in Economics 2016-14, University of Trier, Department of Economics.
    10. Hyejin Lee & Dong-Yop Oh & Ming Meng, 2019. "Stationarity and cointegration of health care expenditure and GDP: evidence from tests with smooth structural shifts," Empirical Economics, Springer, vol. 57(2), pages 631-652, August.
    11. Boetel, Brenda L. & Liu, Donald J., 2008. "Incorporating Structural Changes in Agricultural and Food Price Analysis: An Application to the U.S. Beef and Pork Sectors," Working Papers 44076, University of Minnesota, The Food Industry Center.
    12. Zhou, Mi & Wang, Huixia Judy & Tang, Yanlin, 2015. "Sequential change point detection in linear quantile regression models," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 98-103.
    13. Galvao Jr., Antonio F., 2009. "Unit root quantile autoregression testing using covariates," Journal of Econometrics, Elsevier, vol. 152(2), pages 165-178, October.
    14. Mishra, Shekhar & Sharif, Arshian & Khuntia, Sashikanta & Meo, Muhammad Saeed & Rehman Khan, Syed Abdul, 2019. "Does oil prices impede Islamic stock indices? Fresh insights from wavelet-based quantile-on-quantile approach," Resources Policy, Elsevier, vol. 62(C), pages 292-304.
    15. 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.
    16. Tarlok Singh, 2017. "Are Current Account Deficits in the OECD Countries Sustainable? Robust Evidence from Time-Series Estimators," The International Trade Journal, Taylor & Francis Journals, vol. 31(1), pages 29-64, January.
    17. Wolters Maik H. & Tillmann Peter, 2015. "The changing dynamics of US inflation persistence: a quantile regression approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 161-182, April.
    18. Haiqi Li Author-Name-First: Haiqi & Jing Zhang & Chaowen Zheng, 2023. "Estimating and Testing for Functional Coefficient Quantile Cointegrating Regression," Economics Discussion Papers em-dp2023-07, Department of Economics, University of Reading.
    19. Russo, Emanuele & Foster-McGregor, Neil & Verspagen, Bart, 2019. "Characterizing growth instability: new evidence on unit roots and structural breaks in long run time series," MERIT Working Papers 2019-026, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    20. Chang, Bisharat Hussain & Sharif, Arshian & Aman, Ameenullah & Suki, Norazah Mohd & Salman, Asma & Khan, Syed Abdul Rehman, 2020. "The asymmetric effects of oil price on sectoral Islamic stocks: New evidence from quantile-on-quantile regression approach," Resources Policy, Elsevier, vol. 65(C).

    More about this item

    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:wly:ijfiec:v:26:y:2021:i:1:p:1087-1100. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.