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A Note on Wavelet Correlation and Cointegration

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  • Fernández Macho, Francisco Javier

Abstract

In a recent paper Leong-Huang:2010 {Journal of Applied Statistics 37, 215–233} proposed a wavelet-correlation-based approach to test for cointegration between two time series. However, correlation and cointegration are two different concepts even when wavelet analysis is used. It is known that statistics based on nonstationary integrated variables have non-standard asymptotic distributions. However, wavelet analysis offsets the integrating order of nonstationary series so that traditional asymptotics on stationary variables suffices to ascertain the statistical properties of wavelet-based statistics. Based on this, this note shows that wavelet correlations cannot be used as a test of cointegration.

Suggested Citation

  • Fernández Macho, Francisco Javier, 2013. "A Note on Wavelet Correlation and Cointegration," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    • Handle: RePEc:ehu:biltok:10862
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    References listed on IDEAS

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    1. Søren Johansen, 2007. "Correlation, regression, and cointegration of nonstationary economic time series," CREATES Research Papers 2007-35, Department of Economics and Business Economics, Aarhus University.
    2. Chee Kian Leong & Weihong Huang, 2010. "Testing for spurious and cointegrated regressions: A wavelet approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(2), pages 215-233.
    3. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
    4. Søren Johansen, 2012. "The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 6(2), June.
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    Keywords

    econometric methods; integrated process; spectral analysis; time series models; unit roots; wavelet analysis.;
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