Advanced

Are tests for smooth structural change affected by data inaccuracies?

Reese, Simon LU (2012) NEKN01 20121
Department of Economics
Abstract
The size and power of tests for smooth structural change are evaluated in the presence of random measurement error in the explanatory variable or outliers in the dependent variable of a univariate regression model. It is shown that the considered tests are robust to measurement error of a magnitude that can be found in real economic data. By contrast,outliers are found to distort both the size and the power of test for structural breaks. It is shown that the effects of outliers can be compensated by a simple wavelet-based outlier detection algorithm.
Please use this url to cite or link to this publication:
author
Reese, Simon LU
supervisor
organization
course
NEKN01 20121
year
type
H1 - Master's Degree (One Year)
subject
keywords
Structural breaks, measurement error, additive outliers, wavelet analysis
language
English
id
3115755
date added to LUP
2012-09-27 11:18:12
date last changed
2012-09-27 11:18:12
@misc{3115755,
  abstract     = {The size and power of tests for smooth structural change are evaluated in the presence of random measurement error in the explanatory variable or outliers in the dependent variable of a univariate regression model. It is shown that the considered tests are robust to measurement error of a magnitude that can be found in real economic data. By contrast,outliers are found to distort both the size and the power of test for structural breaks. It is shown that the effects of outliers can be compensated by a simple wavelet-based outlier detection algorithm.},
  author       = {Reese, Simon},
  keyword      = {Structural breaks,measurement error,additive outliers,wavelet analysis},
  language     = {eng},
  note         = {Student Paper},
  title        = {Are tests for smooth structural change affected by data inaccuracies?},
  year         = {2012},
}