Using the GB2 Income Distribution

Duangkamon Chotikapanich; William  E. Griffiths; Gholamreza Hajargasht; Wasana Karunarathne; D.  S. Prasada Rao

doi:10.3390/econometrics6020021

Econometrics (Apr 2018)

Using the GB2 Income Distribution

Duangkamon Chotikapanich,
William E. Griffiths,
Gholamreza Hajargasht,
Wasana Karunarathne,
D. S. Prasada Rao

Affiliations

Duangkamon Chotikapanich: Monash Business School, Monash University, Melbourne VIC 3145, Australia
William E. Griffiths: Department of Economics, University of Melbourne, Melbourne VIC 3010, Australia
Gholamreza Hajargasht: Department of Accounting, Economics and Finance, Swinburne University of Technology, Hawthorn VIC 3122, Australia
Wasana Karunarathne: Department of Economics, University of Melbourne, Melbourne VIC 3010, Australia
D. S. Prasada Rao: School of Economics, University of Queensland, St. Lucia QLD 4072, Australia

DOI: https://doi.org/10.3390/econometrics6020021
Journal volume & issue: Vol. 6, no. 2
p. 21

Abstract

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To use the generalized beta distribution of the second kind (GB2) for the analysis of income and other positively skewed distributions, knowledge of estimation methods and the ability to compute quantities of interest from the estimated parameters are required. We review estimation methodology that has appeared in the literature, and summarize expressions for inequality, poverty, and pro-poor growth that can be used to compute these measures from GB2 parameter estimates. An application to data from China and Indonesia is provided.

Published in Econometrics

ISSN: 2225-1146 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Social Sciences: Economic theory. Demography: Economics as a science
Website: http://www.mdpi.com/journal/econometrics

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