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Thirty Years of Heteroskedasticity-Robust Inference

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  • James G. MacKinnon

    () (Queen's University)

Abstract

White (1980) marked the beginning of a new era for inference in econometrics. It introduced the revolutionary idea of inference that is robust to heteroskedasticity of unknown form, an idea that was very soon extended to other forms of robust inference and also led to many new estimation methods. This paper discusses the development of heteroskedasticity-robust inference since 1980. There have been two principal lines of investigation. One approach has been to modify White's original estimator to improve its finite-sample properties, and the other has been to use bootstrap methods. The relation between these two approaches, and some ways in which they may be combined, are discussed. Finally, a simulation experiment compares various methods and shows how far heteroskedasticity-robust inference has come in just over thirty years.

Suggested Citation

  • James G. MacKinnon, 2012. "Thirty Years of Heteroskedasticity-Robust Inference," Working Papers 1268, Queen's University, Department of Economics.
  • Handle: RePEc:qed:wpaper:1268
    as

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    File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_1268.pdf
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    References listed on IDEAS

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    Cited by:

    1. Romano, Joseph P. & Wolf, Michael, 2017. "Resurrecting weighted least squares," Journal of Econometrics, Elsevier, vol. 197(1), pages 1-19.
    2. Startz, Richard, 2012. "Bayesian Heteroskedasticity-Robust Standard Errors," University of California at Santa Barbara, Economics Working Paper Series qt69c4x8m9, Department of Economics, UC Santa Barbara.

    More about this item

    Keywords

    wild bootstrap; HCCME; power; finite-sample;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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