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The Size and Power of Bootstrap and Bartlett-Corrected Tests of Hypotheses on the Cointegrating Vectors

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  • Pieter Omtzigt
  • Stefano Fachin

Abstract

In this paper we compare Bartlett-corrected, bootstrap, and fast double bootstrap tests on maximum likelihood estimates of cointegration parameters. The key result is that both the bootstrap and the Bartlett-corrected tests must be based on the unrestricted estimates of the cointegrating vectors: procedures based on the restricted estimates have almost no power. The small sample size bias of the asymptotic test appears so severe as to advise strongly against its use with the sample sizes commonly available; the fast double bootstrap test minimizes size bias, while the Bartlett-corrected test is somehow more powerful.

Suggested Citation

  • Pieter Omtzigt & Stefano Fachin, 2006. "The Size and Power of Bootstrap and Bartlett-Corrected Tests of Hypotheses on the Cointegrating Vectors," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 41-60.
  • Handle: RePEc:taf:emetrv:v:25:y:2006:i:1:p:41-60
    DOI: 10.1080/07474930500545439
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    References listed on IDEAS

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    1. Russell Davidson & James G. MacKinnon, 2000. "Improving the Reliability of Bootstrap Tests," Working Papers 995, Queen's University, Department of Economics.
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    Cited by:

    1. Tang, Chor-Foon & Lau, Evan, 2011. "The Behaviour of Disaggregated Public Expenditures and Income in Malaysia," Review of Applied Economics, Review of Applied Economics, vol. 7(1-2).
    2. Boswijk, H. Peter & Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2016. "Inference on co-integration parameters in heteroskedastic vector autoregressions," Journal of Econometrics, Elsevier, vol. 192(1), pages 64-85.
    3. Gunnar BÃ¥rdsen & Luca Fanelli, 2015. "Frequentist Evaluation of Small DSGE Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 307-322, July.
    4. Takamitsu Kurita, 2009. "A note on small-sample correction for hypothesis testing on cointegrating vectors: recursive Monte Carlo analysis," Economics Bulletin, AccessEcon, vol. 29(3), pages 1588-1595.
    5. Binet, Marie-Estelle & Pentecôte, Jean-Sébastien, 2015. "Macroeconomic idiosyncrasies and European monetary unification: A sceptical long run view," Economic Modelling, Elsevier, vol. 51(C), pages 412-423.
    6. Zohrabyan, Tatevik & Leatham, David J. & Bessler, David A., 2008. "Cointegration Analysis of Regional House Prices in U.S," Proceedings: 2007 Agricultural and Rural Finance Markets in Transition, October 4-5, 2007, St. Louis, Missouri 48138, Regional Research Committee NC-1014: Agricultural and Rural Finance Markets in Transition.
    7. Ahlgren, N. & Antell, J., 2008. "Bootstrap and fast double bootstrap tests of cointegration rank with financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4754-4767, June.
    8. Swensen, Anders Rygh, 2011. "A bootstrap algorithm for testing cointegration rank in VAR models in the presence of stationary variables," Journal of Econometrics, Elsevier, vol. 165(2), pages 152-162.
    9. Tang, Chor Foon & Tan, Bee Wah & Ozturk, Ilhan, 2016. "Energy consumption and economic growth in Vietnam," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1506-1514.
    10. Di Iorio, Francesca & Fachin, Stefano, 2007. "Cointegration testing in dependent panels with breaks," MPRA Paper 3139, University Library of Munich, Germany.
    11. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Carsten Jentsch & Dimitris N. Politis & Efstathios Paparoditis, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 416-441, May.

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