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Semiparametric inference in multivariate fractionally cointegrated systems

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  • Hualde, J.
  • Robinson, P.M.

Abstract

A semiparametric multivariate fractionally cointegrated system is considered, integration orders possibly being unknown and I(0) unobservable inputs having nonparametric spectral density. Two estimates of the vector of cointegrating parameters [nu] are considered. One involves inverse spectral weighting and the other is unweighted but uses a spectral estimate at frequency zero. Both corresponding Wald statistics for testing linear restrictions on [nu] are shown to have a standard null [chi]2 limit distribution under quite general conditions. Notably, this outcome is irrespective of whether cointegrating relations are "strong" (when the difference between integration orders of observables and cointegrating errors exceeds 1/2), or "weak" (when that difference is less than 1/2), or when both cases are involved. Finite-sample properties are examined in a Monte Carlo study and an empirical example is presented.

Suggested Citation

  • Hualde, J. & Robinson, P.M., 2010. "Semiparametric inference in multivariate fractionally cointegrated systems," Journal of Econometrics, Elsevier, vol. 157(2), pages 492-511, August.
  • Handle: RePEc:eee:econom:v:157:y:2010:i:2:p:492-511
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