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Bayesian Interpretations of Heteroskedastic Consistent Covariance Estimators Using the Informed Bayesian Bootstrap

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  • Dale J. Poirier

Abstract

This article provides Bayesian interpretations for White's heteroskedastic consistent (HC) covariance estimator, and various modifications of it, in linear regression models. An informed Bayesian bootstrap provides a useful framework.

Suggested Citation

  • Dale J. Poirier, 2011. "Bayesian Interpretations of Heteroskedastic Consistent Covariance Estimators Using the Informed Bayesian Bootstrap," Econometric Reviews, Taylor & Francis Journals, vol. 30(4), pages 457-468, August.
    • Handle: RePEc:taf:emetrv:v:30:y:2011:i:4:p:457-468
    DOI: 10.1080/07474938.2011.553542
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    References listed on IDEAS

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    1. Giuseppe Ragusa, 2007. "Bayesian Likelihoods for Moment Condition Models," Working Papers 060714, University of California-Irvine, Department of Economics.
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    Cited by:

    1. Philippe Goulet Coulombe, 2020. "The Macroeconomy as a Random Forest," Papers 2006.12724, arXiv.org, revised Mar 2021.
    2. Philippe Goulet Coulombe, 2021. "The Macroeconomy as a Random Forest," Working Papers 21-05, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    3. Matt Taddy & Matt Gardner & Liyun Chen & David Draper, 2016. "A Nonparametric Bayesian Analysis of Heterogenous Treatment Effects in Digital Experimentation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 661-672, October.
    4. Norets, Andriy, 2015. "Bayesian regression with nonparametric heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 409-419.
    5. Lin, Eric S. & Chou, Ta-Sheng, 2012. "A note on Bayesian interpretations of HCCME-type refinements for nonlinear GMM models," Economics Letters, Elsevier, vol. 116(3), pages 494-497.
    6. Lewis, Gabriel, 2022. "Heteroskedasticity and Clustered Covariances from a Bayesian Perspective," MPRA Paper 116662, University Library of Munich, Germany.

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