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Constrained inference in multiple regression with structural changes

Author

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  • Chen Fuqi
  • Nkurunziza Sévérien

    (Mathematics and Statistics, University of Windsor, 401 Sunset Avenue, Windsor, Ontario N9B 3P4, Canada)

Abstract

In this paper, we study an inference problem for the regression coefficients in some multivariate regression models with multiple change-points occurring at unknown times, when the regression coefficients may satisfy some restrictions. The hypothesized restriction is more general than that given in recent literature. Under a weaker assumption than that given in recent literature, we derive the joint asymptotic normality of the restricted and unrestricted estimators. Finally, we construct a test for the hypothesized restriction and derive its asymptotic power.

Suggested Citation

  • Chen Fuqi & Nkurunziza Sévérien, 2014. "Constrained inference in multiple regression with structural changes," Statistics & Risk Modeling, De Gruyter, vol. 31(3-4), pages 1-21, December.
    • Handle: RePEc:bpj:strimo:v:31:y:2014:i:3-4:p:21:n:2
    DOI: 10.1515/strm-2012-1154
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    References listed on IDEAS

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    1. Perron, Pierre & Yabu, Tomoyoshi, 2009. "Testing for Shifts in Trend With an Integrated or Stationary Noise Component," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 369-396.
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    3. Gombay, Edit & Serban, Daniel, 2009. "Monitoring parameter change in time series models," Journal of Multivariate Analysis, Elsevier, vol. 100(4), pages 715-725, April.
    4. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    5. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
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