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Bootstrap Co-integration Rank Testing: The Effect of Bias-Correcting Parameter Estimates

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  • Giuseppe Cavaliere
  • A. M. Robert Taylor
  • Carsten Trenkler

Abstract

type="main" xml:id="obes12090-abs-0001"> Bootstrap-based methods for bias-correcting the first-stage parameter estimates used in some recently developed bootstrap implementations of co-integration rank tests are investigated. The procedure constructs estimates of the bias in the original parameter estimates by using the average bias in the corresponding parameter estimates taken across a large number of auxiliary bootstrap replications. A number of possible implementations of this procedure are discussed and concrete recommendations made on the basis of finite sample performance evaluated by Monte Carlo simulation methods. The results show that bootstrap-based bias-correction methods can significantly improve the small sample performance of the bootstrap co-integration rank tests.

Suggested Citation

  • Giuseppe Cavaliere & A. M. Robert Taylor & Carsten Trenkler, 2015. "Bootstrap Co-integration Rank Testing: The Effect of Bias-Correcting Parameter Estimates," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(5), pages 740-759, October.
  • Handle: RePEc:bla:obuest:v:77:y:2015:i:5:p:740-759
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    File URL: http://hdl.handle.net/10.1111/obes.2015.77.issue-5
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    References listed on IDEAS

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    1. Giuseppe Cavaliere & Anders Rahbek & A. M. Robert Taylor, 2010. "Bootstrap Sequential Determination of the Co-integration Rank in VAR Models," Discussion Papers 10-07, University of Copenhagen. Department of Economics.
    2. Anders Rygh Swensen, 2006. "Bootstrap Algorithms for Testing and Determining the Cointegration Rank in VAR Models -super-1," Econometrica, Econometric Society, vol. 74(6), pages 1699-1714, November.
    3. Giuseppe Cavaliere & Anders Rahbek & A. M. Robert Taylor, 2014. "Bootstrap Determination of the Co-Integration Rank in Heteroskedastic VAR Models," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 606-650, August.
    4. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2010. "Testing for co-integration in vector autoregressions with non-stationary volatility," Journal of Econometrics, Elsevier, vol. 158(1), pages 7-24, September.
    5. Giuseppe Cavaliere & A. M. Robert Taylor & Carsten Trenkler, 2013. "Bootstrap Cointegration Rank Testing: The Role of Deterministic Variables and Initial Values in the Bootstrap Recursion," Econometric Reviews, Taylor & Francis Journals, vol. 32(7), pages 814-847, October.
    6. 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.
    7. Giuseppe Cavaliere & Anders Rahbek & Taylor A.M.Robert, 2011. "Bootstrap determination of the co-integration rank in VAR models," Quaderni di Dipartimento 9, Department of Statistics, University of Bologna.
    8. Ling, Shiqing & McAleer, Michael, 2002. "Stationarity and the existence of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 109-117, January.
    9. Tom Engsted & Thomas Q. Pedersen, 2014. "Bias-Correction in Vector Autoregressive Models: A Simulation Study," Econometrics, MDPI, Open Access Journal, vol. 2(1), pages 1-27, March.
    10. Giuseppe Cavaliere & Luca Fanelli & Attilio Gardini, 2008. "International dynamic risk sharing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 1-16.
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    Cited by:

    1. 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.
    2. Luca Benati & Robert Lucas, Jr. & Juan Nicolini & Warren Weber, 2016. "International Evidence on Long Run Money Demand," Working Papers id:11152, eSocialSciences.

    More about this item

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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