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Monitoring structural change in dynamic econometric models

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  • Zeileis, Achim
  • Leisch, Friedrich
  • Kleiber, Christian
  • Hornik, Kurt

Abstract

The classical approach to testing for structural change employs retrospective tests using a historical data set of a given length. Here we consider a wide array of fluctuation-type tests in a monitoring situation – given a history period for which a regression relationship is known to be stable, we test whether incoming data are consistent with the previously established relationship. Procedures based on estimates of the regression coefficients are extended in three directions: we introduce (a) procedures based on OLS residuals, (b) rescaled statistics and (c) alternative asymptotic boundaries. Compared to the existing tests our extensions offer better power against certain alternatives, improved size in finite samples for dynamic models and ease of computation respectively. We apply our methods to two data sets, German M1 money demand and U.S. labor productivity.

Suggested Citation

  • Zeileis, Achim & Leisch, Friedrich & Kleiber, Christian & Hornik, Kurt, 2002. "Monitoring structural change in dynamic econometric models," Technical Reports 2002,07, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  • Handle: RePEc:zbw:sfb475:200207
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    References listed on IDEAS

    as
    1. Zeileis, Achim & Leisch, Friedrich & Hornik, Kurt & Kleiber, Christian, 2002. "strucchange: An R Package for Testing for Structural Change in Linear Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i02).
    2. Lutkepohl, Helmut & Terasvirta, Timo & Wolters, Jurgen, 1999. "Investigating Stability and Linearity of a German M1 Money Demand Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 511-525, Sept.-Oct.
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    4. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
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    More about this item

    Keywords

    Online monitoring; CUSUM; MOSUM; moving estimates; recursive estimates;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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