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ℓ 1 regressions: Gini estimators for fixed effects panel data

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  • Ndéné Ka
  • Stéphane Mussard

Abstract

Panel data, frequently employed in empirical investigations, provide estimators being strongly biased in the presence of atypical observations. The aim of this work is to propose a Gini regression for panel data. It is shown that the fixed effects within-group Gini estimator is more robust than the ordinary least squares one when the data are contaminated by outliers. This semi-parametric Gini estimator is proven to be an U -statistics, consequently, it is asymptotically normal.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:japsta:v:43:y:2016:i:8:p:1436-1446
    DOI: 10.1080/02664763.2015.1103707
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    1. 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.
    2. Shlomo Yitzhaki & Peter Lambert, 2013. "The relationship between the absolute deviation from a quantile and Gini’s mean difference," METRON, Springer;Sapienza Università di Roma, vol. 71(2), pages 97-104, September.
    3. 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.
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    1. Charles Condevaux & Stéphane Mussard & Téa Ouraga & Guillaume Zambrano, 2020. "Generalized Gini linear and quadratic discriminant analyses," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 219-236, August.
    2. Arthur Charpentier & Ndéné Ka & Stéphane Mussard & Oumar Hamady Ndiaye, 2019. "Gini Regressions and Heteroskedasticity," Econometrics, MDPI, vol. 7(1), pages 1-16, January.

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