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A Highly Efficient Regression Estimator for Skewed and/or Heavy-tailed Distributed Errors

Author

Listed:
  • Lorenzo Ricci
  • Vincenzo Verardi
  • Catherine Vermandele

Abstract

This paper proposes a simple maximum likelihood regression estimator that outperforms Least Squares in terms of efficiency and mean square error for a large number of skewed and/or heavy tailed error distributions.

Suggested Citation

  • Lorenzo Ricci & Vincenzo Verardi & Catherine Vermandele, 2016. "A Highly Efficient Regression Estimator for Skewed and/or Heavy-tailed Distributed Errors," Working Papers 19, European Stability Mechanism.
    • Handle: RePEc:stm:wpaper:19
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    File URL: https://www.esm.europa.eu/sites/default/files/document/wp_19.pdf
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    References listed on IDEAS

    as
    1. Nolan, John P. & Ojeda-Revah, Diana, 2013. "Linear and nonlinear regression with stable errors," Journal of Econometrics, Elsevier, vol. 172(2), pages 186-194.
    2. Xu, Ganggang & Genton, Marc G., 2015. "Efficient maximum approximated likelihood inference for Tukey’s g-and-h distribution," Computational Statistics & Data Analysis, Elsevier, vol. 91(C), pages 78-91.
    3. Xu, Yihuan & Iglewicz, Boris & Chervoneva, Inna, 2014. "Robust estimation of the parameters of g-and-h distributions, with applications to outlier detection," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 66-80.
    4. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

    1. W. D. Walls & Jordi McKenzie, 2020. "Black swan models for the entertainment industry with an application to the movie business," Empirical Economics, Springer, vol. 59(6), pages 3019-3032, December.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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