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Bootstrapping and Bartlett corrections in the cointegrated VAR model

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  • Omtzigt Pieter

    () (Department of Economics, University of Insubria, Italy)

  • Fachin Stefano

    () (University of Sapienza, Rome, Italy)

Abstract

The small sample properties of tests on long-run coefficients in cointegrated systems are still a matter of concern to applied econometricians. We compare the performance of the Bartlett correction, the bootstrap and the fast double bootstrap for tests on cointegration parameters in the maximum likelihood framework. We show by means of a theorical result and simulations that all three procedures should be based on the unrestricted estimate of the cointegration vectors. The fast double bootstrap delivers superior size correction, whereas the Bartlett correction leads to the least loss of power. However all three perform much better than the asymptotic tests and difference between them are small.

Suggested Citation

  • Omtzigt Pieter & Fachin Stefano, 2002. "Bootstrapping and Bartlett corrections in the cointegrated VAR model," Economics and Quantitative Methods qf0212, Department of Economics, University of Insubria.
  • Handle: RePEc:ins:quaeco:qf0212
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    File URL: http://eco.uninsubria.it/dipeco/Quaderni/files/QF2002_24.pdf
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    References listed on IDEAS

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    Cited by:

    1. Cubadda, Gianluca & Omtzigt, Pieter, 2005. "Small-sample improvements in the statistical analysis of seasonally cointegrated systems," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 333-348, April.
    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. Davidson, Russell & MacKinnon, James G., 2007. "Improving the reliability of bootstrap tests with the fast double bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3259-3281, April.
    4. Eriksson , Åsa, 2004. "Testing Structural Hypotheses on Cointegration Vectors: A Monte Carlo Study," Working Papers 2004:29, Lund University, Department of Economics.
    5. H. Peter Boswijk & Jurgen A. Doornik, 2004. "Identifying, estimating and testing restricted cointegrated systems: An overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 440-465.

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