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Errors-in-Variables Estimation with Wavelets

Ramazan Gencay

Simon Fraser University

Nikola Gradojevic

IÉSEG School of Management; University of Bologna - Rimini Center for Economic Analysis (RCEA)

October 2009

This paper develops a wavelet (spectral) approach to estimate the parameters of a linear regression model where the regressand and the regressors are persistent processes and contain a measurement error. We propose a wavelet filtering approach which does not require instruments and yields unbiased and consistent estimates for the intercept and the slope parameters. Our Monte Carlo results also show that the wavelet approach is particularly effective when measurement errors for the regressand and the regressor are serially correlated. With this paper, we hope to bring a fresh perspective and stimulate further theoretical research in this area.

Number of Pages in PDF File: 24

Keywords: Cointegration, discrete wavelet transformation, maximum overlap wavelet transformation, energy decomposition, errors-in-variables, persistence

JEL Classification: C1, C2, C12, C22, F31, G0, G1

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Date posted: June 17, 2009 ; Last revised: November 20, 2009

Suggested Citation

Gencay, Ramazan and Gradojevic, Nikola, Errors-in-Variables Estimation with Wavelets (October 2009). Available at SSRN: http://ssrn.com/abstract=1420999 or http://dx.doi.org/10.2139/ssrn.1420999

Contact Information

Ramazan Gencay
Simon Fraser University ( email )
Department of Economics
8888 University Drive
Burnaby, British Columbia V5A 1S6
Nikola Gradojevic (Contact Author)
IÉSEG School of Management ( email )
3, rue de la Digue
Lille, 59000
HOME PAGE: http://goo.gl/2mUIP
University of Bologna - Rimini Center for Economic Analysis (RCEA) ( email )
Via Patara, 3
Rimini (RN), RN 47900
Feedback to SSRN

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References:  43
Citations:  2

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