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Searching for cointegration in a dynamic system

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  • Zhongjun Qu

Abstract

, which can be zero, stable cointegrating vectors against the alternative hypothesis of more than r 0 cointegrating vectors existing in some subsample. The tests proposed follow Breitung (2002). They are non-parametric in nature and are invariant to linear transformations of the series. A distinctive feature is that they allow us to detect the hidden cointegration when the system is affected by an unknown number of regime changes of unknown timing. We analyse the limiting distributions and provide tables of critical values. Various extensions are then discussed which incorporate a priori information to improve the power. A simple correction is also proposed to yield improved finite sample performance. Finally simulations are conducted to evaluate the size and power in finite samples. Copyright Royal Economic Society 2007

Suggested Citation

  • Zhongjun Qu, 2007. "Searching for cointegration in a dynamic system," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 580-604, November.
    • Handle: RePEc:ect:emjrnl:v:10:y:2007:i:3:p:580-604
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    Cited by:

    1. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," Working Papers halshs-00564897, HAL.
    2. Davidson, James & Monticini, Andrea, 2010. "Tests for cointegration with structural breaks based on subsamples," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2498-2511, November.
    3. Lukáš ČECHURA & Tereza TAUSSIGOVÁ, 2013. "Avian influenza and structural change in the Czech poultry industry," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 59(1), pages 38-47.
    4. Ahmed, Walid M.A. & Sleem, Mohamed A.E., 2023. "Short- and long-run determinants of the price behavior of US clean energy stocks: A dynamic ARDL simulations approach," Energy Economics, Elsevier, vol. 124(C).
    5. Kejriwal, Mohitosh & Perron, Pierre, 2010. "Testing for Multiple Structural Changes in Cointegrated Regression Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(4), pages 503-522.
    6. Skrobotov, Anton, 2021. "Structural breaks in cointegration models: Multivariate case," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 83-106.
    7. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.
    8. Karsten Schweikert, 2020. "Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions," Papers 2001.07949, arXiv.org, revised Apr 2021.
    9. Karsten Schweikert, 2022. "Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 83-104, January.
    10. Pierre Perron & Yohei Yamamoto, 2021. "Testing for Changes in Forecasting Performance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 148-165, January.
    11. Clark, Steven P. & Coggin, T. Daniel, 2011. "Was there a U.S. house price bubble? An econometric analysis using national and regional panel data," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(2), pages 189-200, May.
    12. Luis F. Martins & Paulo M. M. Rodrigues, 2022. "Tests for segmented cointegration: an application to US governments budgets," Empirical Economics, Springer, vol. 63(2), pages 567-600, August.
    13. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "Time-Varying Comovement of Foreign Exchange Markets," Papers 1610.04334, arXiv.org.
    14. Razvan Pascalau & Junsoo Lee & Saban Nazlioglu & Yan (Olivia) Lu, 2022. "Johansen‐type cointegration tests with a Fourier function," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 828-852, September.
    15. Martins, Luis F. & Gabriel, Vasco J., 2014. "Modelling long run comovements in equity markets: A flexible approach," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 288-295.
    16. Peri, Massimo & Baldi, Lucia, 2013. "The effect of biofuel policies on feedstock market: Empirical evidence for rapeseed oil prices in EU," Resource and Energy Economics, Elsevier, vol. 35(1), pages 18-37.
    17. Wang, Yiming, 2011. "The stability of long-run money demand in the United States: A new approach," Economics Letters, Elsevier, vol. 111(1), pages 60-63, April.

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