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Testing for Multiple Structural Breaks in Multivariate Long Memory Regression Models

Author

Listed:
  • Paulo M.M. Rodrigues
  • Vivien Less
  • Philipp Sibbertsen

Abstract

This paper focuses on the estimation and testing of multiple breaks that occur at unknown dates in multivariate long memory time series regression models, allowing for fractional cointegration. A likelihood-ratio based approach for estimating the breaks in the parameters and in the covariance of a system of long memory time series regressions is proposed. The limiting distributions as well as the consistency of the estimators are derived. Furthermore, a testing procedure to determine the unknown number of breaks is introduced which is based on iterative testing on the regression residuals. A Monte Carlo exercise shows the good finite sample properties of our novel approach, and empirical applications on inflation series of France and Germany and on benchmark government bonds of eight euro area countries illustrate theusefulness of the proposed procedures.

Suggested Citation

  • Paulo M.M. Rodrigues & Vivien Less & Philipp Sibbertsen, 2025. "Testing for Multiple Structural Breaks in Multivariate Long Memory Regression Models," Working Papers w202503, Banco de Portugal, Economics and Research Department.
    • Handle: RePEc:ptu:wpaper:w202503
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    References listed on IDEAS

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    1. Fabrizio Iacone & Stephen J. Leybourne & A. M. Robert Taylor, 2014. "A FIXED- b TEST FOR A BREAK IN LEVEL AT AN UNKNOWN TIME UNDER FRACTIONAL INTEGRATION," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 40-54, January.
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    4. Hassler, Uwe & Rodrigues, Paulo M.M. & Rubia, Antonio, 2014. "Persistence in the banking industry: Fractional integration and breaks in memory," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 95-112.
    5. Stefanos Kechagias & Vladas Pipiras, 2015. "Definitions And Representations Of Multivariate Long-Range Dependent Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(1), pages 1-25, January.
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    7. Sibbertsen, Philipp & Leschinski, Christian & Busch, Marie, 2018. "A multivariate test against spurious long memory," Journal of Econometrics, Elsevier, vol. 203(1), pages 33-49.
    8. Morana Claudio, 2002. "Common Persistent Factors in Inflation and Excess Nominal Money Growth and a New Measure of Core Inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-40, November.
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    10. Paulo M. M. Rodrigues & Philipp Sibbertsen & Michelle Voges, 2024. "The stability of government bond markets’ equilibrium and the interdependence of lending rates," Empirical Economics, Springer, vol. 67(6), pages 2503-2538, December.
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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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