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A bootstrap algorithm for testing cointegration rank in VAR models in the presence of stationary variables

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  • Swensen, Anders Rygh
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    Abstract

    In this paper, a bootstrap algorithm for a reduced rank vector autoregressive (VAR) model which also includes stationary regressors, is analyzed. It is shown that the bootstrap distribution for estimating the rank converges to the distribution derived from the usual asymptotic framework. Because the asymptotic distribution will typically depend on unknown parameters, bootstrap distributions are of considerable interest in this context. The result of an application and some Monte Carlo experiments are also presented.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 165 (2011)
    Issue (Month): 2 ()
    Pages: 152-162

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    Handle: RePEc:eee:econom:v:165:y:2011:i:2:p:152-162

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

    Related research

    Keywords: VAR models; Reduced rank; Stationary regressors; Bootstrap;

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    Cited by:
    1. Rushdi, Mustabshira & Kim, Jae H. & Silvapulle, Param, 2012. "ARDL bounds tests and robust inference for the long run relationship between real stock returns and inflation in Australia," Economic Modelling, Elsevier, vol. 29(3), pages 535-543.
    2. Jentsch, Carsten & Paparoditis, Efstathios & Politis, Dimitris N., 2014. "Block Bootstrap Theory for Multivariate Integrated and Cointegrated Processes," Working Papers 14-18, University of Mannheim, Department of Economics.

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