Testing for Multiple Structural Breaks in Multivariate Long Memory Regression Models

Paulo M.M. Rodrigues, Vivien Less and Philipp Sibbertsen

Working Papers from Banco de Portugal, Economics and Research Department

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.

JEL-codes: C12 C22 C58 G15 (search for similar items in EconPapers)
Date: 2025
New Economics Papers: this item is included in nep-ecm and nep-ets
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Working Paper: Testing for Multiple Structural Breaks in Multivariate Long Memory Regression Models (2025)
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Persistent link: https://EconPapers.repec.org/RePEc:ptu:wpaper:w202503

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