IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/6866.html
   My bibliography  Save this paper

Nonparametric test for causality with long-range dependence

Author

Listed:
  • Hidalgo, Javier

Abstract

This paper introduces a nonparametric Granger-causality test for covariance stationary linear processes under, possibly, the presence of long-range dependence. We show that the test is consistent and has power against contiguous alternatives converging to the parametric rate T-½. Since the test is based on estimates of the parameters of the representation of a VAR model as a, possibly, two-sided infinite distributed lag model, we first show that a modification of Hannan's (1963, 1967) estimator is root-T consistent and asymptotically normal for the coefficients of such a representation. When the data is long-range dependent this method of estimation becomes more attractive than Least Squares, since the latter can be neither root-T consistent nor asymptotically normal as is the case with short-range dependent data.

Suggested Citation

  • Hidalgo, Javier, 2000. "Nonparametric test for causality with long-range dependence," LSE Research Online Documents on Economics 6866, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:6866
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/6866/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Matteo Farnè & Angela Montanari, 2022. "A Bootstrap Method to Test Granger-Causality in the Frequency Domain," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 935-966, March.
    2. Hidalgo, J., 2008. "Specification testing for regression models with dependent data," Journal of Econometrics, Elsevier, vol. 143(1), pages 143-165, March.
    3. Fabiano Mello da Silva & Daniel Arruda Coronel & Kelmara Mendes Vieira, 2014. "Causality and Cointegration Analysis between Macroeconomic Variables and the Bovespa," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-9, February.
    4. Hidalgo, Javier, 2002. "Consistent order selection with strongly dependent data and its application to efficient estimation," LSE Research Online Documents on Economics 6856, London School of Economics and Political Science, LSE Library.
    5. Dietmar Bauer & Alex Maynard, 2010. "Persistence-robust Granger causality testing," Working Papers 1011, University of Guelph, Department of Economics and Finance.
    6. Cleiton Guollo Taufemback, 2023. "Non‐parametric short‐ and long‐run Granger causality testing in the frequency domain," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 69-92, January.
    7. Yushu Li, 2015. "Estimate Long Memory Causality Relationship by Wavelet Method," Computational Economics, Springer;Society for Computational Economics, vol. 45(4), pages 531-544, April.
    8. Nishiyama, Yoshihiko & Hitomi, Kohtaro & Kawasaki, Yoshinori & Jeong, Kiho, 2011. "A consistent nonparametric test for nonlinear causality—Specification in time series regression," Journal of Econometrics, Elsevier, vol. 165(1), pages 112-127.
    9. Javier Hidalgo, 2007. "Specification Testing Forregression Models Withdependent Data," STICERD - Econometrics Paper Series 518, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    10. Bai, Zhidong & Wong, Wing-Keung & Zhang, Bingzhi, 2010. "Multivariate linear and nonlinear causality tests," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(1), pages 5-17.
    11. Aviral Tiwari & Mihai Mutascu, 2014. "A revisit on the tax burden distribution and GDP growth: fresh evidence using a consistent nonparametric test for causality for the USA," Empirical Economics, Springer, vol. 46(3), pages 961-972, May.
    12. Hidalgo, Javier, 2003. "A bootstrap causality test for covariance stationary processes," LSE Research Online Documents on Economics 6848, London School of Economics and Political Science, LSE Library.
    13. Hidalgo, Javier, 2007. "Specification testing for regression models with dependent data," LSE Research Online Documents on Economics 6799, London School of Economics and Political Science, LSE Library.
    14. Bauer, Dietmar & Maynard, Alex, 2012. "Persistence-robust surplus-lag Granger causality testing," Journal of Econometrics, Elsevier, vol. 169(2), pages 293-300.
    15. Hidalgo, J., 2005. "A bootstrap causality test for covariance stationary processes," Journal of Econometrics, Elsevier, vol. 126(1), pages 115-143, May.
    16. Javier Hidalgo, 2003. "A Bootstrap Causality Test for Covariance Stationary Processes," STICERD - Econometrics Paper Series 462, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    17. Li, Yushu, 2012. "Estimating Long Memory Causality Relationships by a Wavelet Method," Working Papers 2012:15, Lund University, Department of Economics.
    18. Fermanian, Jean-David & Wegkamp, Marten H., 2012. "Time-dependent copulas," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 19-29.
    19. Hidalgo, Javier, 2002. "Consistent order selection with strongly dependent data and its application to efficient estimation," Journal of Econometrics, Elsevier, vol. 110(2), pages 213-239, October.
    20. Baghli, Mustapha, 2006. "A model-free characterization of causality," Economics Letters, Elsevier, vol. 91(3), pages 380-388, June.
    21. Javier Hidalgo, 2002. "Consistent Order Selection with Strongly Dependent Data and its Application to Efficient Estimation," STICERD - Econometrics Paper Series 430, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    More about this item

    Keywords

    Causality; long-range dependence; spectral analysis; distributed lag model; consistent test;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: 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:ehl:lserod:6866. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    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.