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More powerful cointegration tests with non-normal errors

Author

Listed:
  • Lee Hyejin

    ()

  • Lee Junsoo

    (Department of Economics, Finance, and Legal Studies, University of Alabama, Tuscaloosa, AL 35487, USA)

  • Im Kyungso

    (Federal deposit Insurance Corporation (FDIC), 550 17th Street, NW, Washington, DC, USA)

Abstract

In this paper, we suggest new cointegration tests that can become more powerful in the presence of non-normal errors. Non-normal errors will not pose a problem in usual cointegration tests even when they are ignored. However, we show that they can become useful sources to improve the power of the tests when we use the “residual augmented least squares” (RALS) procedure to make use of nonlinear moment conditions driven by non-normal errors. The suggested testing procedure is easy to implement and it does not require any non-linear estimation techniques. We can exploit the information on the non-normal error distribution that is already available but ignored in the usual cointegration tests. Our simulation results show significant power gains over existing cointegration tests in the presence of non-normal errors.

Suggested Citation

  • Lee Hyejin & Lee Junsoo & Im Kyungso, 2015. "More powerful cointegration tests with non-normal errors," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 397-413, September.
  • Handle: RePEc:bpj:sndecm:v:19:y:2015:i:4:p:397-413:n:1
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    References listed on IDEAS

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    1. Im, Kyung So & Schmidt, Peter, 2008. "More efficient estimation under non-normality when higher moments do not depend on the regressors, using residual augmented least squares," Journal of Econometrics, Elsevier, vol. 144(1), pages 219-233, May.
    2. Jing Li & Junsoo Lee, 2010. "ADL tests for threshold cointegration," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 241-254, July.
    3. Banerjee, Anindya, et al, 1986. "Exploring Equilibrium Relationships in Econometrics through Static Models: Some Monte Carlo Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 253-277, August.
    4. Harbo, Ingrid, et al, 1998. "Asymptotic Inference on Cointegrating Rank in Partial Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 388-399, October.
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    Cited by:

    1. Dong-Yop Oh & Hyejin Lee & Karl David Boulware, 2016. "Conventional monetary policy and the degree of interest rate pass through in the long run: a non-normal approach," Wesleyan Economics Working Papers 2016-002, Wesleyan University, Department of Economics.
    2. repec:eee:ecmode:v:67:y:2017:i:c:p:114-124 is not listed on IDEAS

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