Wavelet Analysis and Denoising: New Tools for Economists

Iolanda Lo Cascio
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Iolanda Lo Cascio: Queen Mary, University of London

No 600, Working Papers from Queen Mary University of London, School of Economics and Finance

Abstract: This paper surveys the techniques of wavelets analysis and the associated methods of denoising. The Discrete Wavelet Transform and its undecimated version, the Maximum Overlapping Discrete Wavelet Transform, are described. The methods of wavelets analysis can be used to show how the frequency content of the data varies with time. This allows us to pinpoint in time such events as major structural breaks. The sparse nature of the wavelets representation also facilitates the process of noise reduction by nonlinear wavelet shrinkage, which can be used to reveal the underlying trends in economic data. An application of these techniques to the UK real GDP (1873-2001) is described. The purpose of the analysis is to reveal the true structure of the data - including its local irregularities and abrupt changes - and the results are surprising.

Keywords: Wavelets; Denoising; Structural breaks; Trend estimation (search for similar items in EconPapers)
JEL-codes: C14 C22 C53 (search for similar items in EconPapers)
Date: 2007-05-01
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Persistent link: https://EconPapers.repec.org/RePEc:qmw:qmwecw:600

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