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An intuitive guide to wavelets for economists

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  • Patrick M. Crowley

    (Bank of Finland)

Abstract

Wavelet analysis, although used extensively in disciplines such as signal processing, engineering, medical sciences, physics and astronomy, has not yet fully entered the economics discipline. In this discussion paper, wavelet analysis is introduced in an intuitive manner, and the existing economics and finance literature that utilises wavelets is explored. Extensive examples of exploratory wavelet analysis are given, many using Canadian, US and Finnish industrial production data. Finally, potential future applications for wavelet analysis in economics are also discussed and explored.

Suggested Citation

  • Patrick M. Crowley, 2005. "An intuitive guide to wavelets for economists," GE, Growth, Math methods 0508009, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpge:0508009
    Note: Type of Document - pdf; pages: 71. Bank of Finland Research Discussion Papers 1/2005
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    References listed on IDEAS

    as
    1. Ramsey James B. & Lampart Camille, 1998. "The Decomposition of Economic Relationships by Time Scale Using Wavelets: Expenditure and Income," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(1), pages 1-22, April.
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    Citations

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    Cited by:

    1. Zagaglia, Paolo, 2006. "The Predictive Power of the Yield Spread under the Veil of Time," Research Papers in Economics 2006:4, Stockholm University, Department of Economics.
    2. Mandler, Martin & Scharnagl, Michael, 2014. "Money growth and consumer price inflation in the euro area: A wavelet analysis," Discussion Papers 33/2014, Deutsche Bundesbank.
    3. Roger Bowden & Jennifer Zhu, 2010. "Multi-scale variation, path risk and long-term portfolio management," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 783-796.
    4. Ahamada, Ibrahim & Jolivaldt, Philippe, 2013. "Time-spectral density and wavelets approaches. Comparative study. Applications to SP500 returns and US GDP," Economic Modelling, Elsevier, vol. 31(C), pages 460-466.
    5. repec:agr:journl:v:4(613):y:2017:i:4(613):p:75-88 is not listed on IDEAS
    6. 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.
    7. repec:spr:annopr:v:260:y:2018:i:1:d:10.1007_s10479-016-2215-3 is not listed on IDEAS
    8. Crowley, Patrick M. & Maraun, Douglas & Mayes, David, 2006. "How hard is the euro area core? : an evaluation of growth cycles using wavelet analysis," Research Discussion Papers 18/2006, Bank of Finland.
    9. Carla Ysusi, 2009. "Analysis of the Dynamics of Mexican Inflation Using Wavelets," Working Papers 2009-09, Banco de México.
    10. Werner Kristjanpoller R. & Alejandro Sierra C., 2014. "Relationship between the dollar, the price of copper and the IPSA indifferent time scales: An approach through Wavelet," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 17(3), pages 56-85, December.
    11. Jammazi, Rania & Aloui, Chaker, 2015. "On the interplay between energy consumption, economic growth and CO2 emission nexus in the GCC countries: A comparative analysis through wavelet approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1737-1751.
    12. Anderson Antonio Denardin & Alice Kozakevicius & Alex A. Schmidt, 2018. "Avaliação Da Medida De Núcleo De Inflação Baseada No Método Wavelet Para O Brasil," Anais do XLIV Encontro Nacional de Economia [Proceedings of the 44th Brazilian Economics Meeting] 34, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    13. Alper Ozun & Atilla Cifter, 2008. "Modeling long-term memory effect in stock prices: A comparative analysis with GPH test and Daubechies wavelets," Studies in Economics and Finance, Emerald Group Publishing, vol. 25(1), pages 38-48, March.
    14. Philippe Jolivaldt & Ibrahim Ahamada, 2010. "Filtres usuels et filtre fondé sur les ondelettes : étude comparative et application au cycle économique," Économie et Prévision, Programme National Persée, vol. 195(4), pages 149-161.
    15. Reese, Simon & Li, Yushu, 2013. "Testing for Structural Breaks in the Presence of Data Perturbations: Impacts and Wavelet Based Improvements," Working Papers 2013:36, Lund University, Department of Economics.
    16. Crowley, Patrick M. & Lee, Jim, 2005. "Decomposing the co-movement of the business cycle : a time-frequency analysis of growth cycles in the euro area," Research Discussion Papers 12/2005, Bank of Finland.
    17. Jia, Xiaoliang & An, Haizhong & Fang, Wei & Sun, Xiaoqi & Huang, Xuan, 2015. "How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective," Energy Economics, Elsevier, vol. 49(C), pages 588-598.
    18. Jia, Xiaoliang & An, Haizhong & Sun, Xiaoqi & Huang, Xuan & Wang, Lijun, 2017. "Evolution of world crude oil market integration and diversification: A wavelet-based complex network perspective," Applied Energy, Elsevier, vol. 185(P2), pages 1788-1798.
    19. Fousekis, Panos & Grigoriadis, Vasilis, 2016. "Spatial price dependence by time scale: Empirical evidence from the international butter markets," Economic Modelling, Elsevier, vol. 54(C), pages 195-204.

    More about this item

    Keywords

    statistical methodology; multiresolution analysis; wavelets; business cycles; economic growth;

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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