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Testing for Structural Breaks in the Presence of Data Perturbations: Impacts and Wavelet Based Improvements

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  • Reese, Simon

    ()

    (Department of Economics, Lund University)

  • Li, Yushu

    ()

    (Department of Business and Management Science, Norwegian School of Economics)

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Abstract

This paper investigates how classical measurement error and additive outliers influence tests for structural change based on F-statistics. We derive theoretically the impact of general additive disturbances in the regressors on the asymptotic distribution of these tests for structural change . The small sample properties in the case of classical measurement error and additive outliers are investigated via Monte Carlo simulations, revealing that sizes are biased upwards and that powers are reduced. Two wavelet based denoising methods are used to reduce these distortions. We show that these two methods can significantly improve the performance of structural break tests.

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File URL: http://project.nek.lu.se/publications/workpap/papers/WP13_36.pdf
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Paper provided by Lund University, Department of Economics in its series Working Papers with number 2013:36.

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Length: 17 pages
Date of creation: 11 Oct 2013
Date of revision:
Publication status: Published as Reese, Simon and Yushu Li, 'Testing for Structural Breaks in the Presence of Data Perturbations: Impacts and Wavelet Based Improvements' in Journal of Statistical Computation and Simulation, 2015, pages 3468-3479.
Handle: RePEc:hhs:lunewp:2013_036
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Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund,Sweden

Phone: +46 +46 222 0000
Fax: +46 +46 2224613
Web page: http://www.nek.lu.se/en

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Keywords: Structural breaks; measurement error; additive outliers; wavelet transform; empirical Bayes thresholding;

Find related papers by JEL classification:

  • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
  • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
  • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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  2. Balke, Nathan S. & Fomby, Thomas B., 1991. "Large shocks, small shocks, and economic fluctuations: outliers in macroeconomic times series," Working Papers 9101, Federal Reserve Bank of Dallas.
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  10. Paulo M.M. Rodrigues & Antonio Rubia, 2010. "The Effects of Additive Outliers and Measurement Errors when Testing for Structural Breaks in Variance," Working Papers w201011, Banco de Portugal, Economics and Research Department.
  11. Schennach, Susanne M., 2004. "Exponential specifications and measurement error," Economics Letters, Elsevier, vol. 85(1), pages 85-91, October.
  12. Kim, Dukpa & Perron, Pierre, 2009. "Assessing the relative power of structural break tests using a framework based on the approximate Bahadur slope," Journal of Econometrics, Elsevier, vol. 149(1), pages 26-51, April.
  13. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
  14. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843 Elsevier.
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