A lasso-type estimation for the Lorenz regression

Alexandre Jacquemain, Cédric Heuchenne and Eugen Pircalabelu
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Alexandre Jacquemain: Université catholique de Louvain, LIDAM/ISBA, Belgium
Cédric Heuchenne: University of Liège
Eugen Pircalabelu: Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2021027, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

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.

Keywords: Lorenz curve; Inequality of opportunity; Single-index models; LASSO; FABS algorithm (search for similar items in EconPapers)
Pages: 5
Date: 2021-06-29
Note: In: Proceedings of the 22nd European Young Statistician Meeting, 2021, p. 41-45
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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvar:2021027

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