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Gini Regressions and Heteroskedasticity

Author

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  • Arthur Charpentier

    (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique)

  • Ndéné Ka

    (UADB - Université Alioune Diop de Bambey)

  • Stéphane Mussard

    (CHROME - Détection, évaluation, gestion des risques CHROniques et éMErgents (CHROME) / Université de Nîmes - UNIMES - Université de Nîmes)

  • Oumar Hamady Ndiaye

    (CHROME - Détection, évaluation, gestion des risques CHROniques et éMErgents (CHROME) / Université de Nîmes - UNIMES - Université de Nîmes)

Abstract

We propose an Aitken estimator for Gini regression. The suggested A-Gini estimator is proven to be a U-statistics. Monte Carlo simulations are provided to deal with heteroskedasticity and to make some comparisons between the generalized least squares and the Gini regression. A Gini-White test is proposed and shows that a better power is obtained compared with the usual White test when outlying observations contaminate the data.

Suggested Citation

  • Arthur Charpentier & Ndéné Ka & Stéphane Mussard & Oumar Hamady Ndiaye, 2019. "Gini Regressions and Heteroskedasticity," Post-Print hal-02131746, HAL.
    • Handle: RePEc:hal:journl:hal-02131746
    DOI: 10.3390/econometrics7010004
    Note: View the original document on HAL open archive server: https://hal.science/hal-02131746
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    References listed on IDEAS

    as
    1. Shlomo Yitzhaki & Edna Schechtman, 2004. "The Gini Instrumental Variable, or the “double instrumental variable” estimator," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 287-313.
    2. Ndene Ka & Stephane Mussard, 2015. "l1 Regressions: Gini Estimators for Fixed Effects Panel Data," Cahiers de recherche 15-02, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    3. Ndéné Ka & Stéphane Mussard, 2016. "ℓ 1 regressions: Gini estimators for fixed effects panel data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(8), pages 1436-1446, June.
    4. Marcel Carcea & Robert Serfling, 2015. "A Gini Autocovariance Function for Time Series Modelling," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(6), pages 817-838, November.
    5. Mussard, Stéphane & Ndiaye, Oumar Hamady, 2018. "Vector autoregressive models: A Gini approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1967-1979.
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    Cited by:

    1. Anastasia Dimiski, 2020. "Factors that affect Students’ performance in Science: An application using Gini-BMA methodology in PISA 2015 dataset," Working Papers 2004, University of Guelph, Department of Economics and Finance.
    2. Vasile Preda & Luigi-Ionut Catana, 2021. "Tsallis Log-Scale-Location Models. Moments, Gini Index and Some Stochastic Orders," Mathematics, MDPI, vol. 9(11), pages 1-22, May.
    3. Ndéné Ka, 2021. "Proo-poor growth modeling in developing countries: A Gini regression approach," Economics Bulletin, AccessEcon, vol. 41(2), pages 316-327.

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    More about this item

    Keywords

    U-statistics; jackknife; heteroskedasticity; Gini;
    All these keywords.

    JEL classification:

    • B23 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Econometrics; Quantitative and Mathematical Studies
    • C - Mathematical and Quantitative Methods
    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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