Editing Gini coefficient (section)

{{Short description|Measure of inequality of a distribution}}
{{distinguish|text=[[Decision tree learning#Gini impurity|Gini impurity]]}}
{{For|the list of countries sorted by the Gini coefficient|List of countries by income inequality}}
{{Use dmy dates|date=August 2017}}

[[File:Global map of high inequality countries, 2022.png|alt=|thumb|400px|World map of Gini coefficients (as a %), 2022, according to the Poverty and Inequality Platform (PIP)<ref>{{cite web |author=Haddad, Cameron Nadim; Mahler, Daniel Gerszon; Diaz-Bonilla, Carolina; Hill, Ruth; Lakner, Christoph; Ibarra, Gabriel Lara |title=Inside the World Bank's new inequality indicator: The number of countries with high inequality |publisher=World Bank |url=https://blogs.worldbank.org/en/opendata/inside-the-world-bank-s-new-inequality-indicator--the-number-of- |date=2024-06-17 |access-date=2024-10-25}}</ref> 
{{legend-col|{{Legend|#2d6da6|<30}}|{{Legend|#91c4d9|30-35}}|{{Legend|#f2ddb6|35-40}}|{{Legend|#f2a488|40-45}}|{{Legend|#d66552|45-50}}|{{Legend|#a6243c|50+}}}}]]

{{Economics sidebar}}

In [[economics]], the '''Gini coefficient''' ({{IPAc-en|ˈ|dʒ|iː|n|i}} {{Respell|JEE|nee}}), also known as the '''Gini index''' or '''Gini ratio''', is a [[measure of statistical dispersion]] intended to represent the [[income distribution|income inequality]], the [[wealth distribution|wealth inequality]], or the [[consumption inequality]]<ref>{{cite web | url=https://databank.worldbank.org/metadataglossary/gender-statistics/series/SI.POV.GINI | title=Glossary &#124; DataBank }}</ref> within a nation or a [[social group]]. It was developed by Italian [[statistics|statistician]] and [[Sociology|sociologist]] [[Corrado Gini]].

The Gini coefficient measures the [[economic inequality|inequality]] among the values of a [[frequency distribution]], such as [[income]] levels. A Gini coefficient of 0 reflects perfect equality, where all income or wealth values are the same. In contrast, a Gini coefficient of 1 (or 100%) reflects maximal inequality among values, where a single individual has all the income while all others have none.<ref name="US Census Bureau">{{cite web |title=Current Population Survey (CPS) – Definitions and Explanations |url=https://www.census.gov/topics/income-poverty/income-inequality/about/metrics/gini-index.html |publisher=US Census Bureau}}</ref><ref>Note: The Gini coefficient could be near one only in a large population where a few persons have all the income. In the special case of just two people, where one has no income, and the other has all the income, the Gini coefficient is 0.5. For five people, where four have no income, and the fifth has all the income, the Gini coefficient is 0.8. See: [https://openknowledge.fao.org/handle/20.500.14283/am352e Bellù, L.G. and Liberati, P. 2006. ''Inequality Analysis: The Gini Index''. EASYPol: Resources for policy making. Rome, FAO.]</ref>

Corrado Gini proposed the Gini coefficient as a measure of [[social inequality|inequality]] of [[income inequality metrics|income]] or [[Wealth concentration|wealth]].<ref>Gini, Corrado (1936). "On the Measure of Concentration with Special Reference to Income and Statistics", Colorado College Publication, General Series No. 208, 73–79.</ref> For [[Organisation for Economic Co-operation and Development|OECD countries]] in the late 20th century, considering the effect of [[tax]]es and [[transfer payments]], the income Gini coefficient ranged between 0.24 and 0.49, with [[Slovakia]] being the lowest and [[Mexico]] the highest.<ref name=OECD1>{{cite web|title=Income distribution – Inequality: Income distribution – Inequality – Country tables |publisher=OECD |year=2012 |url=http://stats.oecd.org/Index.aspx?QueryId=26068 |url-status=dead |archive-url=https://web.archive.org/web/20141109193609/http://stats.oecd.org/Index.aspx?QueryId=26068 |archive-date=9 November 2014 }}</ref> African countries had the highest pre-tax Gini coefficients in 2008–2009, with [[South Africa]] having the world's highest, estimated to be 0.63 to 0.7.<ref>{{cite web |year=2013 |title=South Africa Snapshot, Q4 2013 |url=http://www.kpmg.com/Africa/en/KPMG-in-Africa/Documents/2013%20Q4%20snapshots/KPMG_South%20Africa%202013Q4.pdf |url-status=dead |archive-url=https://web.archive.org/web/20160402034218/http://www.kpmg.com/Africa/en/KPMG-in-Africa/Documents/2013%20Q4%20snapshots/KPMG_South%20Africa%202013Q4.pdf |archive-date=2016-04-02 |publisher=KPMG |df=dmy-all}}{{cbignore|bot=medic}}</ref><ref>{{cite web|title=Gini Coefficient|publisher=United Nations Development Program|date=2012|url=https://data.undp.org/dataset/Income-Gini-coefficient/36ku-rvrj|url-status=dead|archive-url=https://web.archive.org/web/20140712032137/https://data.undp.org/dataset/Income-Gini-coefficient/36ku-rvrj|archive-date=12 July 2014|df=dmy-all}}</ref> However, this figure drops to 0.52 after social assistance is taken into account and drops again to 0.47 after taxation.<ref name="moneywebSA">{{cite web | url=http://www.moneyweb.co.za/moneyweb-economic-trends/the-gini-is-still-in-the-bottle | title=The Gini is still in the bottle | publisher=Money Web | date=16 July 2014 | access-date=24 November 2014 | last=Schüssler | first=Mike}}</ref> Slovakia has the lowest Gini coefficient, with a Gini coefficient of 0.232.<ref>{{Cite web |title=World Bank Open Data |url=https://data.worldbank.org/ |access-date=2023-05-09 |website=World Bank Open Data}}</ref> Various sources have estimated the Gini coefficient of the global income in 2005 to be between 0.61 and 0.68.<ref name=fao2009>{{cite web|title=Poverty, Growth, and Inequality over the Next 50 Years|first=Evan|last=Hillebrand|publisher=FAO, United Nations – Economic and Social Development Department|date=June 2009|url=ftp://ftp.fao.org/docrep/fao/012/ak968e/ak968e00.pdf|archive-url=https://web.archive.org/web/20171020065423/ftp://ftp.fao.org/docrep/fao/012/ak968e/ak968e00.pdf|archive-date=2017-10-20|url-status=dead|df=dmy-all}}</ref><ref name=undp10 />

There are multiple issues in interpreting a Gini coefficient, as the same value may result from many different distribution curves. The demographic structure should be taken into account to mitigate this. Countries with an aging population or those with an increased birth rate experience an increasing pre-tax Gini coefficient even if real income distribution for working adults remains constant. Many scholars have devised over a dozen variants of the Gini coefficient.<ref>{{cite journal|title=More than a Dozen Alternative Ways of Spelling Gini|first=Shlomo|last=Yitzhaki|journal=Economic Inequality|volume=8|year=1998|pages=13–30|url=http://siteresources.worldbank.org/INTDECINEQ/Resources/morethan2002.pdf |archive-url=https://web.archive.org/web/20120803160610/http://siteresources.worldbank.org/INTDECINEQ/Resources/morethan2002.pdf |archive-date=2012-08-03 |url-status=live}}</ref><ref>{{cite web|title=Population Aging, Mobility of Quarterly Incomes, and Annual Income Inequality: Theoretical Discussion and Empirical Findings|url=https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=f1a2990b709b7be14bbe46fb7fd38dfc0a780b02|publisher=Korea Institute of Public Finance|first=Myung Jae|last=Sung|date=August 2010|citeseerx=10.1.1.365.4156}}</ref><ref name=blomq81 />