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An Introduction to Wavelets for Economists

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  • Christoph Schleicher

Abstract

Wavelets are mathematical expansions that transform data from the time domain into different layers of frequency levels. Compared to standard Fourier analysis, they have the advantage of being localized both in time and in the frequency domain, and enable the researcher to observe and analyze data at different scales. While their theoretical foundations were completed by the late 1980s, the 1990s saw a rapid spread to a wide range of applied sciences. A number of successful applications indicate that wavelets are on the verge of entering mainstream econometrics. This paper gives an informal and non-technical introduction to wavelets, and describes their potential for the economic researcher.

Suggested Citation

  • Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
    • Handle: RePEc:bca:bocawp:02-3
    DOI: 10.34989/swp-2002-3
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    References listed on IDEAS

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    1. Davidson, Russell & Labys, Walter C & Lesourd, Jean-Baptiste, 1998. "Wavelet Analysis of Commodity Price Behavior," Computational Economics, Springer;Society for Computational Economics, vol. 11(1-2), pages 103-128, April.
    2. Rainer Von Sachs & Brenda Macgibbon, 2000. "Non‐parametric Curve Estimation by Wavelet Thresholding with Locally Stationary Errors," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(3), pages 475-499, September.
    3. Michael H. Neumann, 1996. "Spectral Density Estimation Via Nonlinear Wavelet Methods For Stationary Non‐Gaussian Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 17(6), pages 601-633, November.
    4. Hong, Yongmiao & Lee, Jin, 2001. "One-Sided Testing For Arch Effects Using Wavelets," Econometric Theory, Cambridge University Press, vol. 17(6), pages 1051-1081, December.
    5. John Geweke & Susan Porter‐Hudak, 1983. "The Estimation And Application Of Long Memory Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 221-238, July.
    6. 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.
    7. Ramsey, James B. & Lampart, Camille, 1998. "Decomposition Of Economic Relationships By Timescale Using Wavelets," Macroeconomic Dynamics, Cambridge University Press, vol. 2(1), pages 49-71, March.
    8. Nason, G.P. & von Sachs, R., 1999. "Wavelets in Time Series Analysis," Papers 9901, Catholique de Louvain - Institut de statistique.
    9. Paul Conway & David Frame, 2000. "A spectral analysis of New Zealand output gaps using Fourier and wavelet techniques," Reserve Bank of New Zealand Discussion Paper Series DP2000/06, Reserve Bank of New Zealand.
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    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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