Abstract
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. A tendency to overreject the null hypothesis emerges for sample of moderate size, and so we suggest a small sample correction. The sequential procedure, applied to the weekly Eurodollar interest rate, detects multiple breaks over the period 1973-1995.
Original language | English (US) |
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Pages (from-to) | 207-244 |
Number of pages | 38 |
Journal | Journal of Econometrics |
Volume | 117 |
Issue number | 2 |
DOIs | |
State | Published - Dec 2003 |
Keywords
- Brownian bridge
- Law of the iterated logarithm
- Multiple structural breaks
- Sequential hypothesis testing
ASJC Scopus subject areas
- Economics and Econometrics