An Introduction to Wavelets for Economists
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|Length:||41 pages 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.|
|Date of creation:||2002|
|Date of revision:|
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References listed on IDEAS
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- Mark J. Jensen, 1997.
"Using Wavelets to Obtain a Consistent Ordinary Least Squares Estimator of the Long Memory Parameter,"
- Jensen, Mark J, 1999. "Using wavelets to obtain a consistent ordinary least squares estimator of the long-memory parameter," MPRA Paper 39152, University Library of Munich, Germany.
- Davidson, Russell & Labys, Walter C & Lesourd, Jean-Baptiste, 1998.
"Wavelet Analysis of Commodity Price Behavior,"
Society for Computational Economics, vol. 11(1-2), pages 103-28, April.
- Ramsey, James B. & Lampart, Camille, 1998. "Decomposition Of Economic Relationships By Timescale Using Wavelets," Macroeconomic Dynamics, Cambridge University Press, vol. 2(01), pages 49-71, March.
- 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.
- Nason, G.P. & von Sachs, R., 1999. "Wavelets in Time Series Analysis," Papers 9901, Catholique de Louvain - Institut de statistique.
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