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Model-based asymptotic inference on the effect of infrequent large shocks on cointegrated variables

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  • Georgiev, Iliyan
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    Abstract

    Quasi-maximum-likelihood (QML) estimation of a model combining cointegration in the conditional mean and rare large shocks (outliers) with a factor structure in the innovations is studied. The goal is not only to robustify inference on the conditional-mean parameters, but also to find regularities and conduct inference on the instantaneous and long-run effect of the large shocks. Given the cointegration rank and the factor order, [chi]2 asymptotic inference is obtained for the cointegration vectors, the short-run parameters, and the direction of each column of both the factor loading matrix and the matrix of long-run impacts of the large shocks. Large shocks, whose location is assumed unknown a priori, can be detected and classified consistently into the factor components.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 158 (2010)
    Issue (Month): 1 (September)
    Pages: 37-50

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    Handle: RePEc:eee:econom:v:158:y:2010:i:1:p:37-50

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    Web page: http://www.elsevier.com/locate/jeconom

    Related research

    Keywords: Cointegration Vector autoregression Rare events Impulse response;

    References

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    13. Hong-Tu Zhu & Heping Zhang, 2004. "Hypothesis testing in mixture regression models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 3-16.
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    15. Leybourne, Stephen J. & Newbold, Paul, 2000. "BEHAVIOR OF DICKEY FULLER t-TESTS WHEN THERE IS A BREAK UNDER THE ALTERNATIVE HYPOTHESIS," Econometric Theory, Cambridge University Press, vol. 16(05), pages 779-789, October.
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