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 University of Exeter, School of Business and Economics in its series Discussion Papers with number
00/11.
Length: 43 pages Date of creation: 2000 Date of revision: Handle: RePEc:fth:exetec:00/11
Contact details of provider: Postal: School of Business and Economics University of Exeter Streatham Court Rennes Drive Exeter EX4 4PU Phone: (01392) 263218 Fax: (01392) 263242 Web page: http://www.exeter.ac.uk/sobe/ More information through EDIRC
Find related papers by JEL classification: C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Nunes, Luis C. & Newbold, Paul & Chung-Ming Kuan, 1996.
"Spurious number of breaks,"
Economics Letters,
Elsevier, vol. 50(2), pages 175-178, February.
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