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Inference Related to Locally Ordered and Common Breaks in a Multivariate System with Joined Segmented Trends

Author

Listed:
  • Ye Li

    (Boston University)

  • Pierre Perron

    (Boston University)

Abstract

The issues addressed in this paper are related to testing for common breaks and constructing conÖdence intervals for locally ordered breaks in bivariate linear time trend regressions with changes in the slopes such that series are joined at the break dates. The common break test considered is a likelihood ratio type test. The null hypothesis is that one of the break dates from one series is common with one of the break dates from the other one, while the alternative hypothesis is that the breaks dates are not the same and need not be separated by a positive fraction of the sample size. In both cases, the estimation method is quasi-maximum likelihood. We provide results about the consistency, rate of convergence and asymptotic distribution of the test statistic and about the limit distribution of the estimates of the locally ordered break dates. Simulation results show that both the test and the coverage rate provided by the limit distribution have good Önite sample properties.

Suggested Citation

  • Ye Li & Pierre Perron, 2013. "Inference Related to Locally Ordered and Common Breaks in a Multivariate System with Joined Segmented Trends," Boston University - Department of Economics - Working Papers Series 2013-010, Boston University - Department of Economics.
    • Handle: RePEc:bos:wpaper:wp2013-010
    as

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    File URL: http://www.bu.edu/econ/files/2014/05/Perron-Inference-Related-to-Locally-Ordered-April-2013.pdf
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    References listed on IDEAS

    as
    1. Oka, Tatsushi & Perron, Pierre, 2018. "Testing for common breaks in a multiple equations system," Journal of Econometrics, Elsevier, vol. 204(1), pages 66-85.
    2. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    3. Perron, Pierre & Zhu, Xiaokang, 2005. "Structural breaks with deterministic and stochastic trends," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 65-119.
    4. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    5. Zhongjun Qu & Pierre Perron, 2007. "Estimating and Testing Structural Changes in Multivariate Regressions," Econometrica, Econometric Society, vol. 75(2), pages 459-502, March.
    6. Pierre Perron & Francisco Estrada & Benjamín Martínez-López, 2012. "Statistical evidence about human influence on the climate system," Boston University - Department of Economics - Working Papers Series WP2012-012, Boston University - Department of Economics.
    7. Jushan Bai, 2000. "Vector Autoregressive Models with Structural Changes in Regression Coefficients and in Variance-Covariance Matrices," Annals of Economics and Finance, Society for AEF, vol. 1(2), pages 303-339, November.
    8. Jushan Bai & Robin L. Lumsdaine & James H. Stock, 1998. "Testing For and Dating Common Breaks in Multivariate Time Series," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 395-432.
    Full references (including those not matched with items on IDEAS)

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