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A lasso-type estimation for the Lorenz regression

Author

Listed:
  • Jacquemain, Alexandre

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Heuchenne, Cédric

    (University of Liège)

  • Pircalabelu, Eugen

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

Abstract

The Lorenz regression procedure aims to estimate the explained Gini coefficient, a quantity with a natural application in the field of inequality of opportunity. In this paper, we introduce a lasso-type estimator for the explained Gini coefficient and discuss the selection of the regularization parameter. The performance of the procedure is compared to an oracle estimator on simulated data. Finally, an illustration on real-data is provided.

Suggested Citation

  • Jacquemain, Alexandre & Heuchenne, Cédric & Pircalabelu, Eugen, 2021. "A lasso-type estimation for the Lorenz regression," LIDAM Reprints ISBA 2021027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2021027
    Note: In: Proceedings of the 22nd European Young Statistician Meeting, 2021, p. 41-45
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