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Estimate Long Memory Causality Relationship by Wavelet Method

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  • Yushu Li

Abstract

The traditional causality relationship proposed by Granger (Econometrica 37(3):424–438, 1969 ) assumes the relationships between variables are short range dependence with the same integrated order.Chen (J Forecast 25(3):193–200, 2006 , J Forecast 27:607–620, 2008 ) proposed a bivariate model which can catch the long-range dependence among the two variables and the series do not need to be fractionally co-integrated. A fractional integrated transfer function is introduced to catch the long-range dependence in this bivariate causality model and a pseudo spectrum based estimator is proposed to estimate the long memory parameter in the transfer function. In recent years, a wavelet domain-based method has gained popularity in estimations of long memory parameter in unit series. No extension to bi-series or multi-series has been made and this paper aims to fill this gap. We will construct an estimator for the long memory parameter in the bi-variable causality model in the wavelet domain. The theoretical background is derived and Monte Carlo simulation is used to investigate the performance of the estimator. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • 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.
    • Handle: RePEc:kap:compec:v:45:y:2015:i:4:p:531-544
    DOI: 10.1007/s10614-014-9434-y
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    References listed on IDEAS

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    1. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
    2. repec:zbw:bofrdp:2005_001 is not listed on IDEAS
    3. Thornton, Daniel L & Batten, Dallas S, 1985. "Lag-Length Selection and Tests of Granger Causality between Money and Income," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 17(2), pages 164-178, May.
    4. Morten Ørregaard Nielsen & Per Houmann Frederiksen, 2005. "Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 405-443.
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    6. Javier Hidalgo, 2000. "Nonparametric Test for Causality with Long-Range Dependence," Econometrica, Econometric Society, vol. 68(6), pages 1465-1490, November.
    7. Mark J. Jensen, 2004. "Semiparametric Bayesian Inference of Long‐Memory Stochastic Volatility Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(6), pages 895-922, November.
    8. Wen-Den Chen, 2006. "Estimating the long memory granger causality effect with a spectrum estimator," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(3), pages 193-200.
    9. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    10. Mark J. Jensen, 1997. "Using Wavelets to Obtain a Consistent Ordinary Least Squares Estimator of the Long Memory Parameter," Econometrics 9710002, University Library of Munich, Germany.
    11. 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.
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    13. repec:zbw:bofrdp:2005_027 is not listed on IDEAS
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    Cited by:

    1. Bjørn Gunnar Hansen & Yushu Li, 2017. "An Analysis of Past World Market Prices of Feed and Milk and Predictions for the Future," Agribusiness, John Wiley & Sons, Ltd., vol. 33(2), pages 175-193, April.

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    More about this item

    Keywords

    Granger causality; Long memory; Monte Carlo simulation; Wavelet domain; C22; C38; C63;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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