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Confidence Sets for the Date of a Structural Change at the End of a Sample

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  • Eiji Kurozumi

Abstract

This paper proposes the construction of a confidence set for the date of a structural change at the end of a sample in a linear regression model. While the break fraction, that is, the ratio of the number of observations before the break to the sample size, is typically assumed to take a value in the (0,1) open interval, we consider the case where a permissible break date is included in a fixed number of observations at the end of the sample; thus the break fraction approaches 1 as the sample size goes to infinity. We propose inverting the test for the break date to construct a confidence set while obtaining the critical values by using the subsampling method. By using Monte Carlo simulations, we show that the confidence set proposed in this paper can control the coverage rate in finite samples well while the average length of the confidence set is comparable to existing methods based on asymptotic theory with a fixed break fraction in the (0,1) interval.

Suggested Citation

  • Eiji Kurozumi, 2018. "Confidence Sets for the Date of a Structural Change at the End of a Sample," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 850-862, November.
  • Handle: RePEc:bla:jtsera:v:39:y:2018:i:6:p:850-862
    DOI: 10.1111/jtsa.12404
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    References listed on IDEAS

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    8. Sam Astill & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2017. "Tests for an end-of-sample bubble in financial time series," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 651-666, October.
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    10. Andrews, Donald W.K. & Kim, Jae-Young, 2006. "Tests for Cointegration Breakdown Over a Short Time Period," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 379-394, October.
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    12. Eiji Kurozumi & Yohei Yamamoto, 2015. "Confidence sets for the break date based on optimal tests," Econometrics Journal, Royal Economic Society, vol. 18(3), pages 412-435, October.
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    Cited by:

    1. Horváth, Lajos & Rice, Gregory & Zhao, Yuqian, 2023. "Testing for changes in linear models using weighted residuals," Journal of Multivariate Analysis, Elsevier, vol. 198(C).

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