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On Bias in the Estimation of Structural Break Points

Author

Listed:
  • Liang Jiang

    (Singapore Management University)

  • Xiaohu Wang

    (The Chinese University of Hong Kong)

  • Jun Yu

    () (Singapore Management University)

Abstract

Based on the Girsanov theorem, this paper obtains the exact finite sample distribution of the maximum likelihood estimator of structural break points in a continuous time model. The exact finite sample theory suggests that, in empirically realistic situations, there is a strong finite sample bias in the estimator of structural break points. This property is shared by least squares estimator of both the absolute structural break point and the fractional structural break point in discrete time models. A simulation-based method based on the indirect estimation approach is proposed to reduce the bias both in continuous time and discrete time models. Monte Carlo studies show that the indirect estimation method achieves substantial bias reductions. However, since the binding function has a slope less than one, the variance of the indirect estimator is larger than that of the original estimator.

Suggested Citation

  • Liang Jiang & Xiaohu Wang & Jun Yu, 2014. "On Bias in the Estimation of Structural Break Points," Working Papers 22-2014, Singapore Management University, School of Economics.
  • Handle: RePEc:siu:wpaper:22-2014
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    File URL: https://mercury.smu.edu.sg/rsrchpubupload/26370/22-2014.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Structural change; Bias reduction; Indirect estimation; Break point;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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