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

In: Essays in Honor of Jerry Hausman

Author

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  • Marco Gallegati
  • James B. Ramsey

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.

Suggested Citation

  • Marco Gallegati & James B. Ramsey, 2012. "Errors-in-Variables and the Wavelet Multiresolution Approximation Approach: A Monte Carlo Study," Advances in Econometrics, in: Essays in Honor of Jerry Hausman, pages 149-171, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(2012)0000029011
    DOI: 10.1108/S0731-9053(2012)0000029011
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