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The Power of Bootstrap Tests

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  • Davidson, Russell
  • MacKinnon, James G.

Abstract

Bootstrap tests are tests for which the signicance level is calculated using some variant of the bootstrap which may be parametric or nonparametric We show that the power of a bootstrap test will generally be very close to the power of the asymptotic test on which it is based provided that both tests are properly adjusted to have the correct size We also discuss the loss of power that can occur when the number of bootstrap samples is relatively small Some Monte Carlo results for two forms of omitted variable test in logit models are presented These illustrate the theoretical results of the paper and demonstrate that the sizeadjusted power of asymptotic tests can vary greatly depending on the method used for size adjustment

Suggested Citation

  • Davidson, Russell & MacKinnon, James G., 1996. "The Power of Bootstrap Tests," Queen's Institute for Economic Research Discussion Papers 273372, Queen's University - Department of Economics.
    • Handle: RePEc:ags:queddp:273372
    DOI: 10.22004/ag.econ.273372
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    References listed on IDEAS

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    1. F. H. C. Marriott, 1979. "Barnard's Monte Carlo Tests: How Many Simulations?," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 28(1), pages 75-77, March.
    2. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    3. 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.
    4. Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, vol. 61(2), pages 395-411, April.
    5. Horowitz, J., 1996. "Bootstrap Critical Values For Tests Based On The Smoothed Maximum Score Estimator," SFB 373 Discussion Papers 1996,44, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Davidson, Russell & MacKinnon, James G., 1999. "The Size Distortion Of Bootstrap Tests," Econometric Theory, Cambridge University Press, vol. 15(3), pages 361-376, June.
    7. Hall, Peter & Horowitz, Joel L, 1996. "Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators," Econometrica, Econometric Society, vol. 64(4), pages 891-916, July.
    8. 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.
    9. Horowitz, J. L., 1995. "Bootstrap Methods In Econometrics: Theory And Numerical Performance," SFB 373 Discussion Papers 1995,63, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    10. Joel L. Horowitz, 1996. "Bootstrap Critical Values for Tests Based on the Smoothed Maximum Score Estimator," Econometrics 9603003, University Library of Munich, Germany.
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    Citations

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    Cited by:

    1. Andersson, Michael K. & Gredenhoff, Mikael P., 1998. "Robust Testing for Fractional Integration Using the Bootstrap," SSE/EFI Working Paper Series in Economics and Finance 218, Stockholm School of Economics.
    2. Flachaire, Emmanuel, 1999. "A better way to bootstrap pairs," Economics Letters, Elsevier, vol. 64(3), pages 257-262, September.
    3. Alessandra Canepa & Raymond O'Brien, 2000. "The Size and Power of Bootstrap Tests for Linear Restrictions in Misspecified Cointegrating Relationships," Econometric Society World Congress 2000 Contributed Papers 1807, Econometric Society.
    4. L. G. Godfrey & C. D. Orme, 1999. "The robustness, reliabiligy and power of heteroskedasticity tests," Econometric Reviews, Taylor & Francis Journals, vol. 18(2), pages 169-194.
    5. Coakley, Jerry & Fuertes, Ana-Maria, 2006. "Testing for sign and amplitude asymmetries using threshold autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 30(4), pages 623-654, April.
    6. Michael K. Andersson & Sune Karlsson, 2001. "Bootstrapping Error Component Models," Computational Statistics, Springer, vol. 16(2), pages 221-231, July.
    7. 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.
    8. Tor Jacobson & Johan Lyhagen & Rolf Larsson & Marianne Nessén, 2008. "Inflation, exchange rates and PPP in a multivariate panel cointegration model," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 58-79, March.
    9. Christian Peretti, 2007. "Long Memory and Hysteresis," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 363-389, Springer.
    10. Andersson, Michael K. & Gredenhoff, Mikael P., 1997. "Bootstrap Testing for Fractional Integration," SSE/EFI Working Paper Series in Economics and Finance 188, Stockholm School of Economics.
    11. Jeong, Jinook & Chung, Seoung, 2001. "Bootstrap tests for autocorrelation," Computational Statistics & Data Analysis, Elsevier, vol. 38(1), pages 49-69, November.
    12. 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.
    13. Pinkse, Joris & Slade, Margaret E., 1998. "Contracting in space: An application of spatial statistics to discrete-choice models," Journal of Econometrics, Elsevier, vol. 85(1), pages 125-154, July.
    14. Siani, Carole & de Peretti, Christian, 2007. "Analysing the performance of bootstrap neural tests for conditional heteroskedasticity in ARCH-M models," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2442-2460, February.
    15. Christian de Peretti, 2003. "Bilateral Bootstrap Tests for Long Memory: An Application to the Silver Market," Computational Economics, Springer;Society for Computational Economics, vol. 22(2), pages 187-212, October.
    16. Ramses H. Abul Naga & Christopher Stapenhurstz & Gaston Yalonetzky, 2021. "Inferring Inequality: Testing for Median-Preserving Spreads in Ordinal Data," Working Papers 2021-01, Universidad de Málaga, Department of Economic Theory, Málaga Economic Theory Research Center.
    17. Li, Hongyi & Xiao, Zhijie, 2000. "On bootstrapping regressions with unit root processes," Statistics & Probability Letters, Elsevier, vol. 48(3), pages 261-267, July.
    18. Martin, Michael A., 2007. "Bootstrap hypothesis testing for some common statistical problems: A critical evaluation of size and power properties," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6321-6342, August.
    19. Dirk Hoorelbeke, 2004. "Bootstrap correcting the score test," Econometric Society 2004 North American Summer Meetings 228, Econometric Society.
    20. Monfardini, Chiara, 2003. "An illustration of Cox's non-nested testing procedure for logit and probit models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 425-444, March.
    21. Beck, Tobias, 2021. "How the honesty oath works: Quick, intuitive truth telling under oath," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 94(C).

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