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A Unified Approach to Structural Change Tests Based on ML Scores, F Statistics, and OLS Residuals

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  • Achim Zeileis

Abstract

Three classes of structural change tests (or tests for parameter instability) that have been receiving much attention in both the statistics and the econometrics communities but have been developed in rather loosely connected lines of research are unified by embedding them into the framework of generalized M-fluctuation tests (Zeileis and Hornik, 2003). These classes are tests based on maximum likelihood scores (including the Nyblom-Hansen test), on F statistics (sup�F, ave�F, exp�F tests), and on OLS residuals (OLS-based CUSUM and MOSUM tests). We show that (representatives from) these classes are special cases of the generalized M-fluctuation tests, based on the same functional central limit theorem but employing different functionals for capturing excessive fluctuations. After embedding these tests into the same framework and thus understanding the relationship between these procedures for testing in historical samples, it is shown how the tests can also be extended to a monitoring situation. This is achieved by establishing a general M-fluctuation monitoring procedure and then applying the different functionals corresponding to monitoring with ML scores, F statistics, and OLS residuals. In particular, an extension of the sup�F test to a monitoring scenario is suggested and illustrated on a real-world data set.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Econometric Reviews.

Volume (Year): 24 (2005)
Issue (Month): 4 ()
Pages: 445-466

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Handle: RePEc:taf:emetrv:v:24:y:2005:i:4:p:445-466

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Related research

Keywords: Aggregation functional; Fluctuation test; Functional central limit theorem; Monitoring; Nyblom-Hansen test; OLS-based CUSUM test; Parameter instability; Structural change; sup� F test;

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Blog mentions

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  1. Let’s Party!
    by diffuseprior in DiffusePrioR on 2012-06-06 17:51:06
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Cited by:
  1. Groen, Jan J J & Kapetanios, George & Price, Simon, 2009. "Multivariate methods for monitoring structural change," Bank of England working papers 369, Bank of England.
  2. Achim Zeileis & Torsten Hothorn, 2013. "A toolbox of permutation tests for structural change," Statistical Papers, Springer, vol. 54(4), pages 931-954, November.
  3. Yi-Hsuan Lee & Alina Davier, 2013. "Monitoring Scale Scores over Time via Quality Control Charts, Model-Based Approaches, and Time Series Techniques," Psychometrika, Springer, vol. 78(3), pages 557-575, July.
  4. Jan Verbesselt & Achim Zeileis & Martin Herold, 2011. "Near Real-Time Disturbance Detection in Terrestrial Ecosystems Using Satellite Image Time Series: Drought Detection in Somalia," Working Papers 2011-18, Faculty of Economics and Statistics, University of Innsbruck.
  5. Edgar Merkle & Achim Zeileis, 2013. "Tests of Measurement Invariance Without Subgroups: A Generalization of Classical Methods," Psychometrika, Springer, vol. 78(1), pages 59-82, January.
  6. Fried, Roland, 2007. "On the robust detection of edges in time series filtering," Technical Reports 2007,20, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  7. Makram El-Shagi & Sebastian Giesen, 2010. "Testing for Structural Breaks at Unknown Time: A Steeplechase," IWH Discussion Papers 19, Halle Institute for Economic Research.
  8. Zeileis, Achim & Shah, Ajay & Patnaik, Ila, 2010. "Testing, monitoring, and dating structural changes in exchange rate regimes," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1696-1706, June.
  9. Martin Wagner & Achim Zeileis, 2012. "Heterogeneity of Regional Growth in the European Union," Working Papers 2012-20, Faculty of Economics and Statistics, University of Innsbruck.
  10. Jamel Jouini, 2010. "Bootstrap methods for single structural change tests: power versus corrected size and empirical illustration," Statistical Papers, Springer, vol. 51(1), pages 85-109, January.
  11. Thomas Windberger & Achim Zeileis, 2011. "Structural Breaks in Inflation Dynamics within the European Monetary Union," Working Papers 2011-12, Faculty of Economics and Statistics, University of Innsbruck.
  12. Fried, Roland, 2007. "On the robust detection of edges in time series filtering," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 1063-1074, October.

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