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Flexible Small Area Estimation of Theil Index using Mixtures of Beta

Authors: De Nicolò, S.; Ferrante, M. R.; Pacei, S.;

Flexible Small Area Estimation of Theil Index using Mixtures of Beta

Abstract

The aim of the paper is to propose a small area estimation model for Theil Index, an entropy-based measure used to quantify economic inequality, industrial concentration and, in general, the disparity related to economic phenomena. We developed an area-level model of its relative index, i.e. Theil index over its maximum, which has a more manageable support between 0 and 1. Classical proposals in area-level context for measures on (0,1) are mostly based on proportions modelling and show limitations when dealing with asymmetric heavy-tailed data, such as in our case. We propose a model with alternative distributional assumptions based on a particular Beta mixture with unconstrained mean modeling, estimated under a Hierarchical Bayes approach. An application to ITSILC income data is provided, showing that our proposal yields a more flexible framework in comparison with Beta regression with unmatched sampling and linking models.

Country
Italy
Keywords

Beta Mixtures, Inequality Mapping, Small Area Estimation, Theil Index.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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