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Bootstrap methods for heteroskedastic regression models: evidence on estimation and testing

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  • F. Cribari-Neto
  • S. G. Zarkos
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    Abstract

    This paper uses Monte Carlo simulation analysis to study the finite-sample behavior of bootstrap estimators and tests in the linear heteroskedastic model. We consider four different bootstrapping schemes, three of them specifically tailored to handle heteroskedasticity. Our results show that weighted bootstrap methods can be successfully used to estimate the variances of the least squares estimators of the linear parameters both under normality and under nonnormality. Simulation results are also given comparing the size and power of the bootstrapped Breusch-Pagan test with that of the original test and of Bartlett and Edgeworth-corrected tests. The bootstrap test was found to be robust against unfavorable regression designs.

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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Econometric Reviews.

    Volume (Year): 18 (1999)
    Issue (Month): 2 ()
    Pages: 211-228

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    Handle: RePEc:taf:emetrv:v:18:y:1999:i:2:p:211-228

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    Related research

    Keywords: Bartlett-type correction; bootstrap; Edgeworth expansion; heteroskedasticity; Lagrange multiplier test; score test; weighted bootstrap; JEL CLASSIFICATION:C12; C13; C15;

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    Cited by:
    1. Amélie Charles & Olivier Darne, 2009. "Variance ratio tests of random walk: An overview," Post-Print hal-00771078, HAL.
    2. Dufour, Jean-Marie & Khalaf, Lynda & Bernard, Jean-Thomas & Genest, Ian, 2004. "Simulation-based finite-sample tests for heteroskedasticity and ARCH effects," Journal of Econometrics, Elsevier, vol. 122(2), pages 317-347, October.
    3. Cribari-Neto, Francisco, 2004. "Asymptotic inference under heteroskedasticity of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 215-233, March.
    4. Marshall, Andrew & Tang, Leilei, 2011. "Assessing the impact of heteroskedasticity for evaluating hedge fund performance," International Review of Financial Analysis, Elsevier, vol. 20(1), pages 12-19, January.
    5. repec:slu:wpaper:2007-01 is not listed on IDEAS
    6. Godfrey, L.G., 2006. "Tests for regression models with heteroskedasticity of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2715-2733, June.
    7. repec:hal:journl:halshs-00175897 is not listed on IDEAS
    8. Malliaropulos, Dimitrios & Priestley, Richard, 1999. "Mean reversion in Southeast Asian stock markets," Journal of Empirical Finance, Elsevier, vol. 6(4), pages 355-384, October.
    9. Eduardo Lima & Benjamin Tabak, 2009. "Tests of Random Walk: A Comparison of Bootstrap Approaches," Computational Economics, Society for Computational Economics, vol. 34(4), pages 365-382, November.
    10. Francisco Cribari-Neto & Maria Lima, 2010. "Sequences of bias-adjusted covariance matrix estimators under heteroskedasticity of unknown form," Annals of the Institute of Statistical Mathematics, Springer, vol. 62(6), pages 1053-1082, December.
    11. Cajueiro, Daniel O. & Tabak, Benjamin M., 2006. "Testing for predictability in equity returns for European transition markets," Economic Systems, Elsevier, vol. 30(1), pages 56-78, March.
    12. Baumöhl, Eduard & Lyócsa, Štefan, 2014. "Volatility and dynamic conditional correlations of worldwide emerging and frontier markets," Economic Modelling, Elsevier, vol. 38(C), pages 175-183.
    13. repec:hal:cesptp:halshs-00175897 is not listed on IDEAS
    14. Dennis Coates & Jac Heckelman & Bonnie Wilson, 2011. "Special-interest groups and growth," Public Choice, Springer, vol. 147(3), pages 439-457, June.
    15. Dale Poirier, 2008. "Bayesian Interpretations of Heteroskedastic Consistent Covariance Estimators Using the Informed Bayesian Bootstrap," Working Papers 080905, University of California-Irvine, Department of Economics.

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