Errors-in-Variables Estimation with Wavelets

24 Pages Posted: 17 Jun 2009 Last revised: 20 Nov 2009

See all articles by Ramazan Gencay

Ramazan Gencay

Simon Fraser University

Nikola Gradojevic

University of Guelph, Department of Economics and Finance; University of Bologna - Rimini Center for Economic Analysis (RCEA)

Date Written: October 2009

Abstract

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.

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

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

Suggested Citation

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

Ramazan Gencay

Simon Fraser University ( email )

Department of Economics
8888 University Drive
Burnaby, British Columbia V5A 1S6
Canada

Nikola Gradojevic (Contact Author)

University of Guelph, Department of Economics and Finance ( email )

50 Stone Road East
Guelph, Ontario N1G 2W1
Canada

HOME PAGE: http://https://www.uoguelph.ca/economics/users/nikola-gradojevic

University of Bologna - Rimini Center for Economic Analysis (RCEA) ( email )

Via Patara, 3
Rimini (RN), RN 47900
Italy

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