Errors-in-Variables and the Wavelet Multiresolution Approximation Approach: A Monte Carlo Study

Abstract

In this chapter we perform a Monte Carlo simulation study of the errors-in-variables model examined in Ramsey, Gallegati, Gallegati, and Semmler (2010) by using a wavelet multiresolution approximation approach. Differently from previous studies applying wavelets to errors-in-variables problem, we use a sequence of multiresolution approximations of the variable measured with error ranging from finer to coarser scales. Our results indicate that multiscale approximations to the variable observed with error based on the coarser scales provide an unbiased asymptotically efficient estimator that also possess good finite sample properties.

Citation

Gallegati, M. and Ramsey, J.B. (2012), "Errors-in-Variables and the Wavelet Multiresolution Approximation Approach: A Monte Carlo Study", Baltagi, B.H., Carter Hill, R., Newey, W.K. and White, H.L. (Ed.) Essays in Honor of Jerry Hausman (Advances in Econometrics, Vol. 29), Emerald Group Publishing Limited, Leeds, pp. 149-171. https://doi.org/10.1108/S0731-9053(2012)0000029011