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Detecting multiple mean breaks at unknown points in official time series

  • Cappelli, Carmela
  • Penny, Richard N.
  • Rea, William S.
  • Reale, Marco

In this paper, we propose a computationally effective approach to detect multiple structural breaks in the mean occurring at unknown dates. We present a non-parametric approach that exploits, in the framework of least squares regression trees, the contiguity property of data generating processes in time series data. The proposed approach is applied first to simulated data and then to the Quarterly Gross Domestic Product in New Zealand to assess some of anomalous observations indicated by the seasonal adjustment procedure implemented in X12-ARIMA are actually structural breaks.

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File URL: http://www.sciencedirect.com/science/article/pii/S0378475408000475
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Article provided by Elsevier in its journal Mathematics and Computers in Simulation (MATCOM).

Volume (Year): 78 (2008)
Issue (Month): 2 ()
Pages: 351-356

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Handle: RePEc:eee:matcom:v:78:y:2008:i:2:p:351-356
Contact details of provider: Web page: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/

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  1. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
  2. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
  3. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-52, April.
  4. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 117-128, Fall.
  5. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
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