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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

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.

Suggested Citation

  • F. Cribari-Neto & S. G. Zarkos, 1999. "Bootstrap methods for heteroskedastic regression models: evidence on estimation and testing," Econometric Reviews, Taylor & Francis Journals, vol. 18(2), pages 211-228.
  • Handle: RePEc:taf:emetrv:v:18:y:1999:i:2:p:211-228
    DOI: 10.1080/07474939908800440
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    Citations

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    Cited by:

    1. Malliaropulos, Dimitrios & Priestley, Richard, 1999. "Mean reversion in Southeast Asian stock markets," Journal of Empirical Finance, Elsevier, vol. 6(4), pages 355-384, October.
    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. Michael O'Hara & Christopher F. Parmeter, 2013. "Nonparametric Generalized Least Squares in Applied Regression Analysis," Pacific Economic Review, Wiley Blackwell, vol. 18(4), pages 456-474, October.
    5. Lyócsa, Štefan, 2014. "Growth-returns nexus: Evidence from three Central and Eastern European countries," Economic Modelling, Elsevier, vol. 42(C), pages 343-355.
    6. 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.
    7. Dennis Coates & Jac Heckelman & Bonnie Wilson, 2011. "Special-interest groups and growth," Public Choice, Springer, vol. 147(3), pages 439-457, June.
    8. Kenneth W. Clements & H. Y. Izan & Yihui Lan, 2009. "A Stochastic Measure of International Competitiveness-super-," International Review of Finance, International Review of Finance Ltd., vol. 9(1-2), pages 51-81.
    9. 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.
    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;The Institute of Statistical Mathematics, 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. 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.
    13. Amélie Charles & Olivier Darné, 2009. "Variance-Ratio Tests Of Random Walk: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 503-527, July.
    14. Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Similarity of emerging market returns under changing market conditions: Markets in the ASEAN-4, Latin America, Middle East, and BRICs," Economic Systems, Elsevier, vol. 39(2), pages 253-268.
    15. Emmanuel Flachaire, 2002. "Bootstrapping heteroskedasticity consistent covariance matrix estimator," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00175897, HAL.
    16. Eduard Baumöhl & Štefan Lyócsa, 2014. "Risk-Return Convergence in CEE Stock Markets: Structural Breaks and Market Volatility," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(5), pages 352-373, November.
    17. 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.
    18. Eduard Baum??hl & ??tefan Ly??csa, 2014. "How smooth is the stock market integration of CEE-3?," William Davidson Institute Working Papers Series wp1079, William Davidson Institute at the University of Michigan.
    19. Lyocsa, Stefan, 2015. "Predicting changes in the output of OECD countries: An international network perspective," MPRA Paper 65774, University Library of Munich, Germany.

    More about this item

    Keywords

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

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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