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U-statistic Type Tests for Structural Breaks in Linear Regression Models

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  • Pouliot, W.
  • Olmo, J.

Abstract

This article introduces a U-statistic type process that is based on a kernel function which can depend on nuisance parameters. It is shown here that this process can accommodate very easily anti-symmetric kernels very useful for detecting changing patterns in the dynamics of time series. This theory is applied to structural break hypothesis tests in linear regression models. In particular, the flexibility of these processes will be exploited to introduce a simultaneous and joint test that exhibit statistical power against changes in either intercept or slope. In contrast to the literature, these tests are able to distinguish between rejections due to changes in intercept from rejections due to changes in slope; allow control of global errors rate; and are explicitly designed to have power when the distribution error is asymmetric. These tests can also incorporate different weight functions devised to detect changes early as well as later on in the sample, and show very good performance in small samples. These tests, therefore, outperform CUSUM type tests widely employed in this literature.

Suggested Citation

  • Pouliot, W. & Olmo, J., 2008. "U-statistic Type Tests for Structural Breaks in Linear Regression Models," Working Papers 08/15, Department of Economics, City University London.
    • Handle: RePEc:cty:dpaper:08/15
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    File URL: https://openaccess.city.ac.uk/id/eprint/1590/1/0815_olmo-pouliot.pdf
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    References listed on IDEAS

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    1. Altissimo, Filippo & Corradi, Valentina, 2003. "Strong rules for detecting the number of breaks in a time series," Journal of Econometrics, Elsevier, vol. 117(2), pages 207-244, December.
    2. Kramer, Walter & Ploberger, Werner & Alt, Raimund, 1988. "Testing for Structural Change in Dynamic Models," Econometrica, Econometric Society, vol. 56(6), pages 1355-1369, November.
    3. Gombay Edit & Horváth Lajos & Husková Marie, 1996. "Estimators And Tests For Change In Variances," Statistics & Risk Modeling, De Gruyter, vol. 14(2), pages 145-160, February.
    4. Olmo Jose & Pouliot William, 2011. "Early Detection Techniques for Market Risk Failure," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-55, September.
    5. Ploberger, Werner & Kramer, Walter & Kontrus, Karl, 1989. "A new test for structural stability in the linear regression model," Journal of Econometrics, Elsevier, vol. 40(2), pages 307-318, February.
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    Cited by:

    1. Olmo, Jose & Pilbeam, Keith & Pouliot, William, 2011. "Detecting the presence of insider trading via structural break tests," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2820-2828, November.
    2. Olmo, J. & Pilbeam, K. & Pouliot, W., 2009. "Detecting the Presence of Informed Price Trading Via Structural Break Tests," Working Papers 09/10, Department of Economics, City University London.
    3. repec:cty:dpaper:10.1016/j.jbankfin.2011.03.013 is not listed on IDEAS
    4. repec:cty:dpaper:1580 is not listed on IDEAS

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