Communications for Statistical Applications and Methods

  • 제23권6호
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  • Pages.587-592
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  • 2016
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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Nonparametric test for cointegration rank using Cholesky factor bootstrap

  • Lee, Jin (Department of Economics, Ewha Womans University)
  • 투고 : 2016.09.01
  • 심사 : 2016.11.02
  • 발행 : 2016.11.30
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초록

It is a long-standing issue to correctly determine the number of long-run relationships among time series processes. We revisit nonparametric test for cointegration rank and propose bootstrap refinements. Consistent with model-free nature of the tests, we make use of Cholesky factor bootstrap methods, which require weak conditions for data generating processes. Simulation studies show that the original Breitung's test have difficulty in obtaining the correct size due to dependence in cointegrated errors. Our proposed bootstrapped tests considerably mitigate size distortions and represent a complementary approach to other bootstrap refinements, including sieve methods.

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참고문헌

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