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Residual-based block bootstrap for cointegration testing


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  • Rosa Badillo
  • Jorge Belaire-Franch
  • Carmelo Reverte


We propose a new testing procedure to determine the rank of cointegration. This new method is based on the nonparametric resampling procedure, so-called Residual-Based Block Bootstrap (RBB), which is developed by Paparoditis and Politis (2003) in the context of unit root testing. Through Monte Carlo experiments we show that, in small samples, the RBB cointegration test has good power properties in relation to the other two well-known tests for cointegration, such as the Augmented Dickey-Fuller (ADF), applied to the residual of a cointegrating regression, and the Johansen's maximum eigenvalue tests. Likewise, this article looks at the influence played by the correlation of the 'X' variables with the errors of the cointegrating regression on the size and power properties of the above cointegration tests. In particular, we show that, when this correlation decreases, the RBB test for cointegration is the most powerful one.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics Letters.

Volume (Year): 17 (2010)
Issue (Month): 10 ()
Pages: 999-1003

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Handle: RePEc:taf:apeclt:v:17:y:2010:i:10:p:999-1003

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Cited by:
  1. 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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