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Small sample improvements in the threshold cointegration test using residual-based moving block bootstrap


  • Yang, Zheng
  • Tian, Zheng
  • Yuan, Zixia


A residual-based moving block bootstrap procedure for testing the null hypothesis of linear cointegration versus cointegration with threshold effects is proposed. When the regressors and errors of the models are serially and contemporaneously correlated, our test compares favourably with the SupLM test proposed by Gonzalo and Pitarakis. Indeed, shortcomings of the former motivated the development of our test. The small sample performance of the bootstrap test is investigated by Monte Carlo simulations, and the results show that the test performs better than the SupLM test.

Suggested Citation

  • Yang, Zheng & Tian, Zheng & Yuan, Zixia, 2008. "Small sample improvements in the threshold cointegration test using residual-based moving block bootstrap," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(4), pages 507-513.
  • Handle: RePEc:eee:matcom:v:78:y:2008:i:4:p:507-513 DOI: 10.1016/j.matcom.2007.06.005

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    References listed on IDEAS

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    6. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
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    9. Cook, Steven, 2007. "A threshold cointegration test with increased power," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 73(6), pages 386-392.
    10. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
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    15. Mehmet Caner & Bruce E. Hansen, 2001. "Threshold Autoregression with a Unit Root," Econometrica, Econometric Society, vol. 69(6), pages 1555-1596, November.
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    17. Li, Hongyi & Maddala, G. S., 1997. "Bootstrapping cointegrating regressions," Journal of Econometrics, Elsevier, vol. 80(2), pages 297-318, October.
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    Cited by:

    1. Mora, Juan & Mora-López, Llanos, 2010. "Comparing distributions with bootstrap techniques: An application to global solar radiation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(4), pages 811-819.


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