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Using the GB2 Income Distribution

Monash Business School, Monash University, Melbourne VIC 3145, Australia
Department of Economics, University of Melbourne, Melbourne VIC 3010, Australia
Department of Accounting, Economics and Finance, Swinburne University of Technology, Hawthorn VIC 3122, Australia
School of Economics, University of Queensland, St. Lucia QLD 4072, Australia
Author to whom correspondence should be addressed.
Econometrics 2018, 6(2), 21;
Received: 9 February 2018 / Revised: 29 March 2018 / Accepted: 4 April 2018 / Published: 18 April 2018
(This article belongs to the Special Issue Econometrics and Income Inequality)
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. View Full-Text
Keywords: inequality; poverty; pro-poor growth; GMM estimation inequality; poverty; pro-poor growth; GMM estimation
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MDPI and ACS Style

Chotikapanich, D.; Griffiths, W.E.; Hajargasht, G.; Karunarathne, W.; Rao, D.S.P. Using the GB2 Income Distribution. Econometrics 2018, 6, 21.

AMA Style

Chotikapanich D, Griffiths WE, Hajargasht G, Karunarathne W, Rao DSP. Using the GB2 Income Distribution. Econometrics. 2018; 6(2):21.

Chicago/Turabian Style

Chotikapanich, Duangkamon, William E. Griffiths, Gholamreza Hajargasht, Wasana Karunarathne, and D. S.P. Rao. 2018. "Using the GB2 Income Distribution" Econometrics 6, no. 2: 21.

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