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Errors-in-Variables Estimation with Wavelets


Gençay, Ramazan; Gradojevic, Nikola (2011). Errors-in-Variables Estimation with Wavelets. Journal of Statistical Computation and Simulation, 81(11):1545-1564.

Abstract

This paper proposes 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 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.

Abstract

This paper proposes 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 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.

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21 citations in Web of Science®
26 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Banking and Finance
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Physical Sciences > Modeling and Simulation
Social Sciences & Humanities > Statistics, Probability and Uncertainty
Physical Sciences > Applied Mathematics
Scope:Discipline-based scholarship (basic research)
Language:English
Date:2011
Deposited On:23 Aug 2023 13:26
Last Modified:29 Jun 2024 01:38
Publisher:Taylor & Francis
ISSN:0094-9655
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1080/00949655.2010.495073
Other Identification Number:merlin-id:5961
  • Content: Accepted Version
  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)