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

Author

Listed:
  • Reese, Simon

    (Department of Economics, Lund University)

  • Li, Yushu

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

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.

Suggested Citation

  • Reese, Simon & Li, Yushu, 2013. "Testing for Structural Breaks in the Presence of Data Perturbations: Impacts and Wavelet Based Improvements," Working Papers 2013:36, Lund University, Department of Economics.
    • Handle: RePEc:hhs:lunewp:2013_036
    as

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    File URL: http://project.nek.lu.se/publications/workpap/papers/WP13_36.pdf
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    References listed on IDEAS

    as
    1. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
    2. repec:zbw:bofrdp:2005_001 is not listed on IDEAS
    3. 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.
    4. 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.
    5. Paulo M. M. Rodrigues & Antonio Rubia, 2011. "The Effects of Additive Outliers and Measurement Errors when Testing for Structural Breaks in Variance," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(4), pages 449-468, August.
    6. Ramazan Gencay & Nikola Gradojevic, 2009. "Errors-in-Variables Estimation with No Instruments," Working Paper series 30_09, Rimini Centre for Economic Analysis.
    7. Schennach, Susanne M., 2004. "Exponential specifications and measurement error," Economics Letters, Elsevier, vol. 85(1), pages 85-91, October.
    8. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    9. Hansen, Bruce E., 1992. "Testing for parameter instability in linear models," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 517-533, August.
    10. Balke, Nathan S & Fomby, Thomas B, 1994. "Large Shocks, Small Shocks, and Economic Fluctuations: Outliers in Macroeconomic Time Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 181-200, April-Jun.
    11. Davidson, Russell, 2009. "Econometric Theory and Methods: International Edition," OUP Catalogue, Oxford University Press, number 9780195391053, Decembrie.
    12. van Bergeijk, Peter A G, 1995. "The Accuracy of International Economic Observations," Bulletin of Economic Research, Wiley Blackwell, vol. 47(1), pages 1-20, January.
    13. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    14. Johnstone, Iain & Silverman, Bernard W., 2005. "EbayesThresh: R Programs for Empirical Bayes Thresholding," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i08).
    15. John G. Cragg, 1994. "Making Good Inferences from Bad Data," Canadian Journal of Economics, Canadian Economics Association, vol. 27(4), pages 776-800, November.
    16. F. Abramovich & T. Sapatinas & B. W. Silverman, 1998. "Wavelet thresholding via a Bayesian approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(4), pages 725-749.
    17. Patrick Crowley, 2005. "An intuitive guide to wavelets for economists," Econometrics 0503017, University Library of Munich, Germany.
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    More about this item

    Keywords

    Structural breaks; measurement error; additive outliers; wavelet transform; empirical Bayes thresholding;
    All these keywords.

    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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