Errors-in-Variables Estimation with No Instruments

Ramazan Gencay and Nikola Gradojevic

Working Paper series from Rimini Centre for Economic Analysis

Abstract: This paper develops a wavelet (spectral) approach to estimate the parameters of a linear regression model where the regress and 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 regress and 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 (search for similar items in EconPapers)
JEL-codes: C1 C12 C2 C22 F31 G0 G1 (search for similar items in EconPapers)
Date: 2009-01
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:rim:rimwps:30_09

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