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Improving The Reliability Of Bootstrap Tests

Author

Listed:
  • James G. MacKinnon

    (Queen's University)

  • Russell Davidson

    (McGill University)

Abstract

We first propose procedures for estimating the rejection probabilities for bootstrap tests in Monte Carlo experiments without actually computing a bootstrap test for each replication. These procedures are only about twice as expensive as estimating rejection probabilities for asymptotic tersts. We then propose procedures for computing modified bootstrap P values that will often be more accurate than ordinary ones. These procedures are closely related to the double bootstrap, but they are far less computationally demanding.

Suggested Citation

  • James G. MacKinnon & Russell Davidson, 2000. "Improving The Reliability Of Bootstrap Tests," Working Paper 995, Economics Department, Queen's University.
    • Handle: RePEc:qed:wpaper:995
    as

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    File URL: https://www.econ.queensu.ca/sites/econ.queensu.ca/files/qed_wp_995.pdf
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    References listed on IDEAS

    as
    1. Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, vol. 61(2), pages 395-411, April.
    2. Davidson, Russell & MacKinnon, James G., 1984. "Convenient specification tests for logit and probit models," Journal of Econometrics, Elsevier, vol. 25(3), pages 241-262, July.
    3. Davidson, Russell & MacKinnon, James G., 1999. "The Size Distortion Of Bootstrap Tests," Econometric Theory, Cambridge University Press, vol. 15(3), pages 361-376, June.
    4. Davidson, Russell & MacKinnon, James G, 1999. "Bootstrap Testing in Nonlinear Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 487-508, May.
    5. Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
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    Citations

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    Cited by:

    1. Bodart, V. & Candelon, B. & Carpantier, J.-F., 2012. "Real exchanges rates in commodity producing countries: A reappraisal," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1482-1502.
    2. Jaap W. B. Bos & Bertrand Candelon & Claire Economidou, 2016. "Does knowledge spill over across borders and technology regimes?," Journal of Productivity Analysis, Springer, vol. 46(1), pages 63-82, August.
    3. Bruggeman, Annick & Donati, Paola & Warne, Anders, 2003. "Is the demand for euro area M3 stable?," Working Paper Series 255, European Central Bank.
    4. repec:use:tkiwps:3232 is not listed on IDEAS
    5. 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.
    6. Timothy Patrick Moran, 2006. "Statistical Inference for Measures of Inequality With a Cross-National Bootstrap Application," Sociological Methods & Research, , vol. 34(3), pages 296-333, February.
    7. 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.
    8. Matteo Mogliani & Giovanni Urga & Carlos Winograd, 2009. "Monetary disorder and financial regimes - The demand for money in Argentina, 1900-2006," Working Papers halshs-00575107, HAL.
    9. Brücker, Herbert & Fachin, Stefano & Venturini, Alessandra, 2011. "Do foreigners replace native immigrants? A panel cointegration analysis of internal migration in Italy," Economic Modelling, Elsevier, vol. 28(3), pages 1078-1089, May.
    10. Psaradakis, Zacharias, 2006. "Blockwise bootstrap testing for stationarity," Statistics & Probability Letters, Elsevier, vol. 76(6), pages 562-570, March.
    11. James Morley & Irina B. Panovska & Tara M. Sinclair, 2014. "Testing Stationarity for Unobserved Components Models," Discussion Papers 2012-41B, School of Economics, The University of New South Wales.
    12. 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.
    13. Giacomini, Raffaella & Politis, Dimitris N. & White, Halbert, 2013. "A Warp-Speed Method For Conducting Monte Carlo Experiments Involving Bootstrap Estimators," Econometric Theory, Cambridge University Press, vol. 29(3), pages 567-589, June.
    14. Stefano Fachin, 2007. "Long-run trends in internal migrations in italy: a study in panel cointegration with dependent units," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 401-428.
    15. Basher, Syed A. & Fachin, Stefano, 2008. "The long-term decline of internal migration in Canada – Ontario as a case study," MPRA Paper 6685, University Library of Munich, Germany.
    16. Stefano Fachin & Andrea Gavosto, 2010. "Trends of labour productivity in Italy: a study with panel co‐integration methods," International Journal of Manpower, Emerald Group Publishing Limited, vol. 31(7), pages 755-769, October.
    17. Russell Davidson & James MacKinnon, 2002. "Fast Double Bootstrap Tests Of Nonnested Linear Regression Models," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 419-429.
    18. Davidson, James, 2006. "Alternative bootstrap procedures for testing cointegration in fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 133(2), pages 741-777, August.

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    More about this item

    Keywords

    Double Bootstrap; Monte Carlo; Specification Test; Bootstrap P Value;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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