Entropy based European income distributions and inequality measures

Sofia Villas-Boas, Qiuzi Fu and George Judge ()

Physica A: Statistical Mechanics and its Applications, 2019, vol. 514, issue C, 686-698

Abstract: In this paper, instead of likelihood based methods that are fragile under model uncertainty, we use entropy based methods on time-ordered household income data to recover income distribution information on European countries and obtain an inequality income measure. For information recovery, we use a family of information theoretic entropy divergence measures to obtain income probability density functions and the corresponding inequality measures, which reflect how European country based economic behavioral systems are performing, and in terms of dynamics have changed over time.

Keywords: Income probability distribution function; Micro income data; Information theoretic methods; Cressie–Read divergence; Entropy maximization; Pareto’s law; (PDFs) (search for similar items in EconPapers)
JEL-codes: C1 C10 C24 D31 E21 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:514:y:2019:i:c:p:686-698

DOI: 10.1016/j.physa.2018.09.121

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