On Bias in the Estimation of Structural Break Points

Liang Jiang, Xiaohu Wang Wang and Jun Yu
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Liang Jiang: Singapore Management University
Xiaohu Wang Wang: The Chinese University of Hong Kong

No 22-2014, Working Papers from Singapore Management University, School of Economics

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.

Keywords: Structural change; Bias reduction; Indirect estimation; Break point (search for similar items in EconPapers)
JEL-codes: C11 C46 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2014-12
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-ore and nep-sea
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Published in SMU Economics and Statistics Working Paper Series

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