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Gini-PLS Regressions

Author

Listed:
  • Stephane Mussard

    (LAMETA, Universite Montpellier I; GREDI, Universite de Sherbrooke; Ceps, Luxembourg)

  • Fattouma Souissi-Benrejab

    (LAMETA, Universite Montpellier I)

Abstract

Data contamination and excessive correlations between regressors (multicollinear- ity) constitute a standard and major problem in econometrics. Two techniques en- able solving these problems, in separate ways: the Gini regression for the former, and the PLS (partial least squares) regression for the latter. Gini-PLS regressions are proposed in order to treat extreme values and multicollinearity simultaneously.

Suggested Citation

  • Stephane Mussard & Fattouma Souissi-Benrejab, 2015. "Gini-PLS Regressions," Cahiers de recherche 17-02, Departement d'économique de l'École de gestion à l'Université de Sherbrooke, revised Jan 2017.
  • Handle: RePEc:shr:wpaper:17-02
    as

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    File URL: http://gredi.recherche.usherbrooke.ca/wpapers/GREDI-1702.pdf
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    References listed on IDEAS

    as
    1. Laure Kuhfuss & Julie Subervie, 2015. "Do agri-environmental schemes help reduce herbicide use? Evidence from a natural experiment in France," Post-Print hal-01199067, HAL.
    2. Choi, Seung-Whan, 2009. "The Effect of Outliers on Regression Analysis: Regime Type and Foreign Direct Investment," Quarterly Journal of Political Science, now publishers, vol. 4(2), pages 153-165, July.
    3. Bry, X. & Trottier, C. & Verron, T. & Mortier, F., 2013. "Supervised component generalized linear regression using a PLS-extension of the Fisher scoring algorithm," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 47-60.
    4. Bastien, Philippe & Vinzi, Vincenzo Esposito & Tenenhaus, Michel, 2005. "PLS generalised linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 48(1), pages 17-46, January.
    5. Schechtman, E. & Yitzhaki, S., 1999. "On the proper bounds of the Gini correlation," Economics Letters, Elsevier, vol. 63(2), pages 133-138, May.
    6. Antoine Beretti & Charles Figuières & Gilles Grolleau, 2014. "An Instrument that Could Turn Crowding-out into Crowding-in," Working Papers 2014.04, FAERE - French Association of Environmental and Resource Economists.
    7. Shlomo Yitzhaki, 2003. "Gini’s Mean difference: a superior measure of variability for non-normal distributions," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 285-316.
    8. E. Schechtman & S. Yitzhaki, 2003. "A Family of Correlation Coefficients Based on the Extended Gini Index," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 1(2), pages 129-146, August.
    9. Chung Dongjun & Keles Sunduz, 2010. "Sparse Partial Least Squares Classification for High Dimensional Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-32, March.
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    More about this item

    Keywords

    Gini covariance; Gini Regression; Gini-PLS Regressions; PLS Regression.;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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