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Bootstrapping the Trace Statistic in VAR Models: Monte Carlo Results and Applications

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  • van Giersbergen, Noud P A

Abstract

This paper investigates through Monte Carlo experiments both size and power properties of a bootstrapped trace statistic in two prototypical DGPs. The Monte Carlo results indicate that the ordinary bootstrap has similar size and power properties as inference procedures based on asymptotic critical values. Considering empirical size, the stationary bootstrap is found to provide a uniform improvement over the ordinary bootstrap if the dynamics is underspecified. The use of the stationary bootstrap as a diagnostic tool is suggested. In two illustrative examples this seems to work, and again it appears that the bootstrap incorporates the finite-sample correction required for the asymptotic critical values to apply. Copyright 1996 by Blackwell Publishing Ltd

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Bibliographic Info

Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

Volume (Year): 58 (1996)
Issue (Month): 2 (May)
Pages: 391-408

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Handle: RePEc:bla:obuest:v:58:y:1996:i:2:p:391-408

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Cited by:
  1. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2010. "Cointegration Rank Testing Under Conditional Heteroskedasticity," Econometric Theory, Cambridge University Press, vol. 26(06), pages 1719-1760, December.
  2. Brada, Josef C. & Kutan, Ali M. & Zhou, Su, 2005. "Real and monetary convergence between the European Union's core and recent member countries: A rolling cointegration approach," Journal of Banking & Finance, Elsevier, vol. 29(1), pages 249-270, January.
  3. Woo, Kai-Yin, 1999. "Cointegration analysis of the intensity of the ERM currencies under the European Monetary System," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 9(4), pages 393-405, November.
  4. Guiseppe Cavaliere & Anders Rahbek & A.M.Robert Taylor, 2010. "Bootstrap Sequential Determination of the Co-integration Rank in VAR Models," CREATES Research Papers 2010-07, School of Economics and Management, University of Aarhus.
  5. Carsten Trenkler, 2008. "Determining p-values for systems cointegration tests with a prior adjustment for deterministic terms," Computational Statistics, Springer, vol. 23(1), pages 19-39, January.
  6. Kascha, Christian & Trenkler, Carsten, 2011. "Bootstrapping the likelihood ratio cointegration test in error correction models with unknown lag order," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1008-1017, February.
  7. Kirstin Hubrich & Helmut Lutkepohl & Pentti Saikkonen, 2001. "A Review Of Systems Cointegration Tests," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 247-318.
  8. Harris, R. I. D. & Judge, G., 1998. "Small sample testing for cointegration using the bootstrap approach," Economics Letters, Elsevier, vol. 58(1), pages 31-37, January.
  9. Josef C. Brada & Ali M. Kutan & Su Zhou, 2002. "Real and Monetary Convergence within the European Union and Between the European Union and Candidate Countries: A Rolling Cointegration Approach," William Davidson Institute Working Papers Series 458, William Davidson Institute at the University of Michigan.
  10. H. Peter Boswijk & Jean-Pierre Urbain, 1997. "Lagrance-multiplier tersts for weak exogeneity: a synthesis," Econometric Reviews, Taylor & Francis Journals, vol. 16(1), pages 21-38.
  11. Li, Hongyi & Xiao, Zhijie, 2000. "On bootstrapping regressions with unit root processes," Statistics & Probability Letters, Elsevier, vol. 48(3), pages 261-267, July.
  12. Ahlgren, Niklas & Antell, Jan, 2006. "Bootstrap and Fast Double Bootstrap Tests of Cointegration Rank with Financial Time Series," Working Papers 519, Hanken School of Economics.
  13. Hjelm, Göran, 2001. "The Dynamic Response of the Budget Balance to Tax, Spending and Output Shocks: Does Model Specification Matter?," Working Papers 2001:2, Lund University, Department of Economics.

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