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Identification of Changes in Mean with Regression Trees: An Application to Market Research

Author

Listed:
  • William Rea
  • Marco Reale
  • Carmela Cappelli
  • Jennifer Brown

Abstract

In this article we present a computationally efficient method for finding multiple structural breaks at unknown dates based on regression trees. We outline the procedure and present the results of a simulation study to assess the performance of the method and to compare it with the procedure proposed by Bai and Perron. We find the tree-based method performs well in long series which are impractical to analyze with current methods. We apply these methods plus the CUSUM test to the market share of Crest toothpaste between 1958 and 1963.

Suggested Citation

  • William Rea & Marco Reale & Carmela Cappelli & Jennifer Brown, 2010. "Identification of Changes in Mean with Regression Trees: An Application to Market Research," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 754-777.
    • Handle: RePEc:taf:emetrv:v:29:y:2010:i:5-6:p:754-777
    DOI: 10.1080/07474938.2010.482001
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    Citations

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    Cited by:

    1. Arturo Leccadito & Omar Rachedi & Giovanni Urga, 2015. "True Versus Spurious Long Memory: Some Theoretical Results and a Monte Carlo Comparison," Econometric Reviews, Taylor & Francis Journals, vol. 34(4), pages 452-479, April.
    2. Lu, Huidi & van der Lans, Ralf & Helsen, Kristiaan & Gauri, Dinesh K., 2023. "DEPART: Decomposing prices using atheoretical regression trees," International Journal of Research in Marketing, Elsevier, vol. 40(4), pages 781-800.
    3. Carmela Cappelli & Francesca Iorio & Angela Maddaloni & Pierpaolo D’Urso, 2021. "Atheoretical Regression Trees for classifying risky financial institutions," Annals of Operations Research, Springer, vol. 299(1), pages 1357-1377, April.

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