Gini-stable Lorenz curves and their relation to the generalised Pareto distribution

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Bertoli-Barsotti, Lucio, Gagolewski, Marek, Siudem, Grzegorz, Żogała-Siudem, Barbara
Format: Preprint
Veröffentlicht: 2023
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866914640743628800
author Bertoli-Barsotti, Lucio
Gagolewski, Marek
Siudem, Grzegorz
Żogała-Siudem, Barbara
author_facet Bertoli-Barsotti, Lucio
Gagolewski, Marek
Siudem, Grzegorz
Żogała-Siudem, Barbara
contents We introduce an iterative discrete information production process where we can extend ordered normalised vectors by new elements based on a simple affine transformation, while preserving the predefined level of inequality, G, as measured by the Gini index. Then, we derive the family of empirical Lorenz curves of the corresponding vectors and prove that it is stochastically ordered with respect to both the sample size and G which plays the role of the uncertainty parameter. We prove that asymptotically, we obtain all, and only, Lorenz curves generated by a new, intuitive parametrisation of the finite-mean Pickands' Generalised Pareto Distribution (GPD) that unifies three other families, namely: the Pareto Type II, exponential, and scaled beta distributions. The family is not only totally ordered with respect to the parameter G, but also, thanks to our derivations, has a nice underlying interpretation. Our result may thus shed a new light on the genesis of this family of distributions. Our model fits bibliometric, informetric, socioeconomic, and environmental data reasonably well. It is quite user-friendly for it only depends on the sample size and its Gini index.
format Preprint
id arxiv_https___arxiv_org_abs_2304_07480
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Gini-stable Lorenz curves and their relation to the generalised Pareto distribution
Bertoli-Barsotti, Lucio
Gagolewski, Marek
Siudem, Grzegorz
Żogała-Siudem, Barbara
Physics and Society
Econometrics
Applications
We introduce an iterative discrete information production process where we can extend ordered normalised vectors by new elements based on a simple affine transformation, while preserving the predefined level of inequality, G, as measured by the Gini index. Then, we derive the family of empirical Lorenz curves of the corresponding vectors and prove that it is stochastically ordered with respect to both the sample size and G which plays the role of the uncertainty parameter. We prove that asymptotically, we obtain all, and only, Lorenz curves generated by a new, intuitive parametrisation of the finite-mean Pickands' Generalised Pareto Distribution (GPD) that unifies three other families, namely: the Pareto Type II, exponential, and scaled beta distributions. The family is not only totally ordered with respect to the parameter G, but also, thanks to our derivations, has a nice underlying interpretation. Our result may thus shed a new light on the genesis of this family of distributions. Our model fits bibliometric, informetric, socioeconomic, and environmental data reasonably well. It is quite user-friendly for it only depends on the sample size and its Gini index.
title Gini-stable Lorenz curves and their relation to the generalised Pareto distribution
topic Physics and Society
Econometrics
Applications
url https://arxiv.org/abs/2304.07480