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Strong Rules for Detecting the Number of Breaks in a Time Series

  • Filippo Altissimo

    (Bank of Italy)

  • Valentina Corradi

    (Queen Mary and Westfield College)

This paper proposes a new approach for detecting the number of structural breaks in a time series when estimation of the breaks is performed one at the time. We consider the case of shifts in the mean of a possibly nonlinear process, allowing for dependent and heterogeneous observations. This is accomplished through a simple, sequential, almost sure rule ensuring that, in large samples, both the probabilities of overestimating and underestimating the number of breaks are zero. A new estimator for the long run variance which is consistent also in the presence of neglected breaks is proposed. The finite sample behavior is investigated via a simulation exercise. The sequential procedure, applied to the weekly Eurodollar interest rate, detects multiple breaks over the period 1973-1995.

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Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 0574.

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Date of creation: 01 Aug 2000
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Handle: RePEc:ecm:wc2000:0574
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  1. Corradi, Valentina, 1999. "Deciding Between I(0) And I(1) Via Flil-Based Bounds," Econometric Theory, Cambridge University Press, vol. 15(05), pages 643-663, October.
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