UQICD - A New Source of Series on International Comparisons of Prices, Incomes and Inequality

Inequality by Region

This new module introduced in UQICD 3.0 focuses on inequality statistics for different regions of the world. This module complements the UQICD real incomes regional module on economic aggregates such as real, nominal and constant 2011 price GDP for different regions and regional groupings. The levels of inequality along with data on real per capita incomes can provide an indication of the level of welfare at the regional level.

The user can download regional GDP; Gini and Theil's measures of inequality; and shares of the bottom and top 1% and 10% of the populations for different geographical regions, World Bank income groupings, and for the OECD and the EU (as at December 2019) and for different years. Data is available for 159 countries that are included in the computations for this module (see detailed information).

The user is advised to consult the UQ International Comparisons Database: UQICD User Guide V3.0 for details of the income distributions included in the data base. Econometric methodology used in the estimation of income distributions is described in the User Guide, and further details can be found in various publications and working papers.

Inequality measures by country are also available.


Select Data Series to Download

View the notes on the regions.

Available regions:


Selected regions:

Available years:


Selected years:

Region and time period identifiers
description: Region Code Identifier
details: A short code to identify each region
source: Our Identifier

description: Year
details: Year
source: NA

description: The geographical, Income or Admin regions
details: The geographical, income or administrative regions defined by the World Bank
source: World Bank

These provide information on: GDP in PPP terms and at current prices and regional total population.
description: Total population
details: Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered as a part of the population of their country of origin. The values shown are midyear estimates (Definition from WDI)
source: UN data base

description: Regional GDP in PPP terms and current prices
details: Regional GDP in PPP terms and current prices computed from RGDP by country from the Regional Incomes Module
source: Our estimates

The Gini measure of inequality for the region with the same specific income distribution fitted to income distribution data in each country of the region.
description: Gini coefficient for lognormal distribution
details: The Gini measure of inequality for the region when income disribution in each country of the region is modelled using lognormal distribution. Details about lognormal distribution can be found in UQICD User Guide Version 3.0.
source: Our estimates

description: Gini coefficient for Pareto-lognormal distribution
details: The Gini measure of inequality for the region when income disribution in each country of the region is modelled using a mixed Pareto-lognormal distributions Details about Pareto-lognormal distribution can be found in UQICD User Guide Version 3.0.
source: Our estimates

description: Gini coefficient for GB2 distribution
details: The Gini measure of inequality for the region when income disribution in each country of the region is modelled using generalized beta-2 distribution. Details about GB2 distribution can be found in UQICD User Guide Version 3.0.
source: Our estimates

description: Gini coefficient for mixture of lognormal distributions
details: The Gini measure of inequality for the region when income disribution in each country of the region is modelled using a mixture of lognormal distributions. Details about lognormal distribution can be found in UQICD User Guide Version 3.0.
source: Our estimates

Theil's L measure of regional inequality with the same specific income distribution fitted to income distribution data in each country of the region
description: Theil's L measure of regional inequality for lognormal distribution
details: This is an additively decomposible measure of inequality in the region computed using Theil's L-measure of inequality when income disribution in each country of the region is modelled using lognormal distribution. Commonly used in decomposition of inequality into within and between sub-groups of population. Details of Theil's L measure are provided in Module 2 on Inequality in the UQICD User Guide V.3.0.
source: Our estimates

description: Theil's L measure of regional inequality for Pareto-lognormal distribution
details: This is an additively decomposible measure of inequality in the region computed using Theil's L-measure of inequality when income disribution in each country of the region is modelled using Pareto-lognormal distribution. Commonly used in decomposition of inequality into within and between sub-groups of population. Details of Theil's L measure are provided in Module 2 on Inequality in the UQICD User Guide V.3.0.
source: Our estimates

description: Theil's L measure of regional inequality for GB2 distribution
details: This is an additively decomposible measure of inequality in the region computed using Theil's L-measure of inequality when income disribution in each country of the region is modelled using GB2 distribution. Commonly used in decomposition of inequality into within and between sub-groups of population. Details of Theil's L measure are provided in Module 2 on Inequality in the UQICD User Guide V.3.0.
source: Our estimates

description: Theil's L measure of regional inequality for mixture of lognormal distributions
details: This is an additively decomposible measure of inequality in the region computed using Theil's L-measure of inequality when income disribution in each country of the region is modelled using mixture of lognormal distributions. Commonly used in decomposition of inequality into within and between sub-groups of population. Details of Theil's L measure are provided in Module 2 on Inequality in the UQICD User Guide V.3.0.
source: Our estimates

Theil's L-measure of within-country inequality with the same specific income distribution fitted to income distribution data in each country of the region
description: Theil's L-measure of within-country inequality with lognormal distribution
details: This is a population share weighted average of inequality within each country measured using Theil's L-measure when income disribution in each country of the region is modelled using lognormal distribution.
source: Our estimates

description: Theil's L-measure of within-country inequality with Pareto-lognormal distribution
details: This is a population share weighted average of inequality within each country measured using Theil's L-measure when income disribution in each country of the region is modelled using Pareto-lognormal distribution.
source: Our estimates

description: Theil's L-measure of within-country inequality with GB2 distribution
details: This is a population share weighted average of inequality within each country measured using Theil's L-measure when income disribution in each country of the region is modelled using GB2.
source: Our estimates

description: Theil's L-measure of within-country inequality with mixture of lognormal distributions
details: This is a population share weighted average of inequality within each country measured using Theil's L-measure when income disribution in each country of the region is modelled using mixture of lognormal distributions.
source: Our estimates

Theil's L-measure of between country inequality with the same specific income distribution fitted to income distribution data in each country of the region
description: Theil's L-measure of between country inequality with lognormal
details: This is a measure of inequality across countries in the region using average or per capital real GDP in each country along with its population when income disribution in each country of the region is modelled using lognormal distribution. This between-country inequality measure serves as an indication of convergence in incomes across countries of the region.
source: Our estimates

description: Theil's L-measure of between country inequality with Pareto-lognormal
details: This is a measure of inequality across countries in the region using average or per capital real GDP in each country along with its population when income disribution in each country of the region is modelled using Pareto-lognormal distribution. This between-country inequality measure serves as an indication of convergence in incomes across countries of the region.
source: Our estimates

description: Theil's L-measure of between country inequality with GB2
details: This is a measure of inequality across countries in the region using average or per capital real GDP in each country along with its population when income disribution in each country of the region is modelled using GB2 distribution. This between-country inequality measure serves as an indication of convergence in incomes across countries of the region.
source: Our estimates

description: Theil's L-measure of between country inequality with mixture of lognormal
details: This is a measure of inequality across countries in the region using average or per capital real GDP in each country along with its population when income disribution in each country of the region is modelled using mixture of lognormal distributions. This between-country inequality measure serves as an indication of convergence in incomes across countries of the region.
source: Our estimates

Income share of the poorest 10 percent of the populationin the region with the same specific income distribution fitted to income distribution data in each country of the region

description: Share of the poorest 10 percent population with lognormal
details: Income share of the poorest 10 percent of the populationin the region when lognormal distribution is used to model income distribution in each country of the region. This share would be less than or equal to 10 percent.
source: Our estimates

description: Share of the poorest 10 percent population with Pareto-lognormal
details: Income share of the poorest 10 percent of the populationin the region when mixture of Pareto and lognormal distribution is used to model income distribution in each country of the region. This share would be less than or equal to 10 percent.
source: Our estimates

description: Share of the poorest 10 percent population with GB2
details: Income share of the poorest 10 percent of the populationin the region when GB2 distribution is used to model income distribution in each country of the region. This share would be less than or equal to 10 percent.
source: Our estimates

description: Share of the poorest 10 percent population with mixture of lognormal distributions
details: Income share of the poorest 10 percent of the populationin the region when mixtures of lognormal distribution are used to model income distribution in each country of the region. This share would be less than or equal to 10 percent.
source: Our estimates

Income share of the poorest 30 percent of the population in the region with the same specific income distribution fitted to income distribution data in each country of the region
description: Share of the poorest 30 percent population with lognormal
details: Income share of the poorest 30 percent of the populationin the region when lognormal distribution is used to model income distribution in each country of the region. This share would be less than or equal to 30 percent.
source: Our estimates

description: Share of the poorest 30 percent population with Pareto-lognormal
details: Income share of the poorest 30 percent of the populationin the region when mixture of Pareto and lognormal distribution is used to model income distribution in each country of the region. This share would be less than or equal to 30 percent.
source: Our estimates

description: Share of the poorest 30 percent population with GB2
details: Income share of the poorest 30 percent of the populationin the region when GB2 distribution is used to model income distribution in each country of the region. This share would be less than or equal to 30 percent.
source: Our estimates

description: Share of the poorest 30 percent population with mixture of lognormal distributions
details: Income share of the poorest 30 percent of the populationin the region when mixtures of lognormal distribution are used to model income distribution in each country of the region. This share would be less than or equal to 30 percent.
source: Our estimates

Income share of the richest 10 percent of the population in the region with the same specific income distribution fitted to income distribution data in each country of the region
description: Share of the richest 10 percent population with lognormal
details: Income share of the richest 10 percent of the populationin the region when lognormal distribution is used to model income distribution in each country of the region. This share would be greater than or equal to 10 percent.
source: Our estimates

description: Share of the richest 10 percent population with Pareto-lognormal
details: Income share of the richest 10 percent of the populationin the region when mixture of Pareto and lognormal distribution is used to model income distribution in each country of the region. This share would be greater than or equal to 10 percent.
source: Our estimates

description: Share of the richest 10 percent population with GB2
details: Income share of the richest 10 percent of the populationin the region when GB2 distribution is used to model income distribution in each country of the region. This share would be greater than or equal to 10 percent.
source: Our estimates

description: Share of the richest 10 percent population with mixture of lognormal distributions
details: Income share of the richest 10 percent of the populationin the region when mixtures of lognormal distribution are used to model income distribution in each country of the region. This share would be greater than or equal to 10 percent.
source: Our estimates

Income share of the richest 1 percent of the population in the region with the same specific income distribution fitted to income distribution data in each country of the region
description: Share of the richest 1 percent population with lognormal
details: Income share of the richest 1 percent of the populationin the region when lognormal distribution is used to model income distribution in each country of the region. This share would be greater than or equal to 1 percent.
source: Our estimates

description: Share of the richest 1 percent population with Pareto-lognormal
details: Income share of the richest 1 percent of the populationin the region when mixture of Pareto and lognormal distribution is used to model income distribution in each country of the region. This share would be greater than or equal to 1 percent.
source: Our estimates

description: Share of the richest 1 percent population with GB2
details: Income share of the richest 1 percent of the populationin the region when GB2 distribution is used to model income distribution in each country of the region. This share would be greater than or equal to 1 percent.
source: Our estimates

description: Share of the richest 1 percent population with mixture of lognormal distributions
details: Income share of the richest 1 percent of the populationin the region when mixtures of lognormal distribution are used to model income distribution in each country of the region. This share would be greater than or equal to 1 percent.
source: Our estimates

Cite UQICD

Cite UQICD:

Rao, D.S. Prasada, A. N. Rambaldi, G. Hajargasht, D. Chotikapanich and W.E. Griffiths, UQ International Comparisons Database: UQICD V3.0, School of Economics, The University of Queensland, St Lucia, QLD 4072, Australia. 2022.