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The Size And Power Of Bootstrap Tests

Author

Listed:
  • James G. MacKinnon

    (Queen's University)

  • Russell Davidson

    (McGill University)

Abstract
Bootstrap tests are tests for which the significance level is calculated by some sort of bootstrap procedure, which may be parametric or nonparametric. We show that, in many circumstances, the size distortion of a bootstrap P value for a test will be one whole order of magnitude smaller than that of the corresponding asymptotic P value. We also show that, at least in the parametric case, the magnitude of the distortion will depend on the shape of what we call the P value function. As regards the power of bootstrap tests, we show that the size-corrected power of a bootstrap test differs from that of the corresponding asymptotic test only by an amount of the same order of magnitude as the size distortion, and of arbitrary sign. Monte Carlo results are presented for two cases of interest: tests for serial correlation and nonnested hypothesis tests. These results confirm and illustrate the utility of our theoretical results, and they also suggest that bootstrap tests will often work extremely well in practice.

Suggested Citation

  • James G. MacKinnon & Russell Davidson, 1996. "The Size And Power Of Bootstrap Tests," Working Paper 932, Economics Department, Queen's University.
    • Handle: RePEc:qed:wpaper:932
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    References listed on IDEAS

    as
    1. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-793, May.
    2. Horowitz, J.L., 1995. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Working Papers 95-10, University of Iowa, Department of Economics.
    3. Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, vol. 61(2), pages 395-411, April.
    4. Godfrey, Leslie G, 1978. "Testing for Higher Order Serial Correlation in Regression Equations When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1303-1310, November.
    5. Weber, N. C., 1984. "On resampling techniques for regression models," Statistics & Probability Letters, Elsevier, vol. 2(5), pages 275-278, October.
    6. Davidson, Russell & MacKinnon, James G, 1987. "Implicit Alternatives and the Local Power of Test Statistics," Econometrica, Econometric Society, vol. 55(6), pages 1305-1329, November.
    7. Godfrey, L. G. & Pesaran, M. H., 1983. "Tests of non-nested regression models: Small sample adjustments and Monte Carlo evidence," Journal of Econometrics, Elsevier, vol. 21(1), pages 133-154, January.
    8. Durbin, J, 1970. "Testing for Serial Correlation in Least-Squares Regression When Some of the Regressors are Lagged Dependent Variables," Econometrica, Econometric Society, vol. 38(3), pages 410-421, May.
    9. Rothernberg, Thomas J, 1984. "Hypothesis Testing in Linear Models When the Error Covariance Matrix Is Nonscalar," Econometrica, Econometric Society, vol. 52(4), pages 827-842, July.
    10. Davidson, Russell & MacKinnon, James G., 1992. "Regression-based methods for using control variates in Monte Carlo experiments," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 203-222.
    11. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    12. Joel L. Horowitz, 1996. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Econometrics 9602009, University Library of Munich, Germany, revised 05 Mar 1996.
    13. 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.
    14. Jan F. Kiviet, 1986. "On the Rigour of Some Misspecification Tests for Modelling Dynamic Relationships," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(2), pages 241-261.
    15. Attfield, C. L. F., 1995. "A Bartlett adjustment to the likelihood ratio test for a system of equations," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 207-223.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Dennis Philip & Chihwa Kao & Giovanni Urga, 2007. "Testing for Instability in Factor Structure of Yield Curves," Center for Policy Research Working Papers 96, Center for Policy Research, Maxwell School, Syracuse University.
    2. 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.
    3. 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.
    4. Davidson, Russell & MacKinnon, James G., 2002. "Bootstrap J tests of nonnested linear regression models," Journal of Econometrics, Elsevier, vol. 109(1), pages 167-193, July.
    5. 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.
    6. 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.
    7. 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.
    8. Michael K. Andersson & Sune Karlsson, 2001. "Bootstrapping Error Component Models," Computational Statistics, Springer, vol. 16(2), pages 221-231, July.
    9. Ramses H. Abul Naga & Christopher Stapenhurst & Gaston Yalonetzky, 2024. "Inferring inequality: Testing for median-preserving spreads in ordinal data," Econometric Reviews, Taylor & Francis Journals, vol. 43(2-4), pages 156-174, April.
    10. Li, Hongyi & Xiao, Zhijie, 2000. "On bootstrapping regressions with unit root processes," Statistics & Probability Letters, Elsevier, vol. 48(3), pages 261-267, July.
    11. 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.
    12. 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.
    13. 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.
    14. Christian Peretti, 2007. "Long Memory and Hysteresis," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 363-389, Springer.
    15. 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.
    16. 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).
    17. Jeong, Jinook & Chung, Seoung, 2001. "Bootstrap tests for autocorrelation," Computational Statistics & Data Analysis, Elsevier, vol. 38(1), pages 49-69, November.

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    More about this item

    Keywords

    tests for serial correlation; bootstrapping; hypothesis testing; Non-nested hypothesis tests; P values;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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