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Testing for Common Breaks in a Multiple Equations System

Author

Listed:
  • Pierre Perron

    () (Department of Economics, Boston University)

  • Tatsushi Oka

    () (National University of Singapore)

Abstract

The issue addressed in this paper is that of testing for common breaks across or within equations. Our framework is very general and allows integrated regressors and trends as well as stationary regressors. The null hypothesis is that some subsets of the parameters (either regression coecients or elements of the covariance matrix of the errors) share one or more common break dates, with the break dates in the system asymptotically distinct so that each regime is separated by some positive fraction of the sample size. Under the alternative hypothesis, the break dates are not the same and also need not be separated by a positive fraction of the sample size. The test con- sidered is the quasi-likelihood ratio test assuming normal errors, though as usual the limit distribution of the test remains valid with non-normal errors. Also of indepen- dent interest, we provide results about the consistency and rate of convergence when searching over all possible partitions subject only to the requirement that each regime contains at least as many observations as the number of parameters in the model. Sim- ulation results show that the test has good nite sample properties. We also provide an application to various measures of in ation to illustrate its usefulness.

Suggested Citation

  • Pierre Perron & Tatsushi Oka, 2011. "Testing for Common Breaks in a Multiple Equations System," Boston University - Department of Economics - Working Papers Series WP2011-057, Boston University - Department of Economics.
  • Handle: RePEc:bos:wpaper:wp2011-057
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    References listed on IDEAS

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    Cited by:

    1. Richard S. J. Tol & Francisco Estrada & Carlos Gay-García, 2012. "The persistence of shocks in GDP and the estimation of the potential economic costs of climate change," Working Paper Series 4312, Department of Economics, University of Sussex.
    2. Blatt, Dominik & Candelon, Bertrand & Manner, Hans, 2015. "Detecting contagion in a multivariate time series system: An application to sovereign bond markets in Europe," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 1-13.
    3. Yunjong Eo & James Morley, 2015. "Likelihood‐ratio‐based confidence sets for the timing of structural breaks," Quantitative Economics, Econometric Society, vol. 6(2), pages 463-497, July.
    4. Ye Li & Pierre Perron, 2017. "Inference on locally ordered breaks in multiple regressions," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 289-353, March.
    5. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    6. 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.
    7. Manner, Hans & Blatt, Dominik & Candelon, Bertrand, 2014. "Detecting financial contagion in a multivariate system," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100411, Verein für Socialpolitik / German Economic Association.

    More about this item

    Keywords

    change-point; segmented regressions; break dates; hypothesis testing; model selection; system of regressions.;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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