Key information about Australia Gini Coefficient

• Australia Gini Coefficient was reported at 0.324 NA in Jun 2020.
• This records a decrease from the previous number of 0.328 NA for Jun 2018.
• Australia Gini Coefficient data is updated yearly, averaging 0.313 NA from Jun 1995 to 2020, with 16 observations.
• The data reached an all-time high of 0.336 NA in 2008 and a record low of 0.292 NA in 1997.
• Australia Gini Coefficient data remains active status in CEIC and is reported by Australian Bureau of Statistics.
• The data is categorized under Global Database’s Australia – Table AU.H028: Survey of Income and Housing: Equivalized Disposable Household Income.

These data contain Gini coefficient estimates (2001 and 2011), for different regions in Australia.

When referencing this material, please cite: Fleming, D. and Measham, T. (2015) 'Income inequality across Australian Regions during the mining boom: 2011-11'. Australian Geographer 46(2), 201-214.

Australia: Gini income inequality index: The latest value from 2018 is 34.3 index points, an increase from 33.7 index points in 2016. In comparison, the world average is 35.68 index points, based on data from 91 countries. Historically, the average for Australia from 1981 to 2018 is 33.52 index points. The minimum value, 31.3 index points, was reached in 1981 while the maximum of 35.4 index points was recorded in 2008.

Australia Gini Coefficient (GINI Index): World Bank Estimate data was reported at 34.300 % in 2018. This records an increase from the previous number of 33.700 % for 2016. Australia Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 33.500 % from Dec 1981 (Median) to 2018, with 12 observations. The data reached an all-time high of 35.400 % in 2008 and a record low of 31.300 % in 1981. Australia Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Social: Poverty and Inequality. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

This dataset provides values for GINI INDEX WB DATA.HTML. reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The average for 2021 based on 1 countries was 27.1 index points. The highest value was in Tonga: 27.1 index points and the lowest value was in Tonga: 27.1 index points. The indicator is available from 1963 to 2023. Below is a chart for all countries where data are available.

Australia Gini Coefficient data was reported at 0.343 NA in 2018. This records an increase from the previous number of 0.337 NA for 2016. Australia Gini Coefficient data is updated yearly, averaging 0.335 NA from Dec 1981 (Median) to 2018, with 12 observations. The data reached an all-time high of 0.354 NA in 2008 and a record low of 0.313 NA in 1981. Australia Gini Coefficient data remains active status in CEIC and is reported by Our World in Data. The data is categorized under Global Database’s Australia – Table AU.OWID.ESG: Social: Gini Coefficient: Annual.

Abstract

This file contains data on Gini coefficients, cumulative quintile shares, explanations regarding the basis on which the Gini coefficient was computed, and the source of the information. There are two data-sets, one containing the "high quality" sample and the other one including all the information (of lower quality) that had been collected.

The database was constructed for the production of the following paper:

Deininger, Klaus and Lyn Squire, "A New Data Set Measuring Income Inequality", The World Bank Economic Review, 10(3): 565-91, 1996.

This article presents a new data set on inequality in the distribution of income. The authors explain the criteria they applied in selecting data on Gini coefficients and on individual quintile groups’ income shares. Comparison of the new data set with existing compilations reveals that the data assembled here represent an improvement in quality and a significant expansion in coverage, although differences in the definition of the underlying data might still affect intertemporal and international comparability. Based on this new data set, the authors do not find a systematic link between growth and changes in aggregate inequality. They do find a strong positive relationship between growth and reduction of poverty.

Geographic coverage

In what follows, we provide brief descriptions of main features for individual countries that are included in the data-base. Without being comprehensive, these notes are intended to indicate some of the considerations underlying our decision to include or exclude certain observations.

Argentina Various permanent household surveys, all covering urban centers only, have been regularly conducted since 1972 and are quoted in a wide variety of sources and years, e.g., for 1980 (World Bank 1992), 1985 (Altimir 1994), and 1989 (World Bank 1992). Estimates for 1963, 1965, 1969/70, 1970/71, 1974, 1975, 1980, and 1981 (Altimir 1987) are based only on Greater Buenos Aires. Estimates for 1961, 1963, 1970 (Jain 1975) and for 1970 (van Ginneken 1984) have only limited geographic coverage and do not satisfy our minimum criteria.

Despite the many urban surveys, there are no income distribution data that are representative of the population as a whole. References to national income distribution for the years 1953, 1959, and 1961(CEPAL 1968 in Altimir 1986 ) are based on extrapolation from national accounts and have therefore not been included. Data for 1953 and 1961 from Weisskoff (1970) , from Lecaillon (1984) , and from Cromwell (1977) are also excluded.

Australia Household surveys, the result of which is reported in the statistical yearbook, have been conducted in 1968/9, 1975/6, 1978/9, 1981, 1985, 1986, 1989, and 1990.

Data for 1962 (Cromwell, 1977) and 1966/67 (Sawyer 1976) were excluded as they covered only tax payers. Jain's data for 1970 was excluded because it covered income recipients only. Data from Podder (1972) for 1967/68, from Jain (1975) for the same year, from UN (1985) for 78/79, from Sunders and Hobbes (1993) for 1986 and for 1989 were excluded given the availability of the primary sources. Data from Bishop (1991) for 1981/82, from Buhman (1988) for 1981/82, from Kakwani (1986) for 1975/76, and from Sunders and Hobbes (1993) for 1986 were utilized to test for the effect of different definitions. The values for 1967 used by Persson and Tabellini and Alesina and Rodrik (based on Paukert and Jain) are close to the ones reported in the Statistical Yearbook for 1969.

Austria: In addition to data referring to the employed population (Guger 1989), national household surveys for 1987 and 1991 are included in the LIS data base. As these data do not include income from self-employment, we do not report them in our high quality data-set.

Bahamas Data for Ginis and shares are available for 1973, 1977, 1979, 1986, 1988, 1989, 1991, 1992, and 1993 in government reports on population censuses and household budget surveys, and for 1973 and 1975 from UN (1981). Estimates for 1970 (Jain 1975), 1973, 1975, 1977, and 1979 (Fields 1989) have been excluded given the availability of primary sources.

Bangladesh Data from household surveys for 1973/74, 1976/77, 1977/78, 1981/82, and 1985/86 are available from the Statistical Yearbook, complemented by household-survey based information from Chen (1995) and the World Development Report. Household surveys with rural coverage for 1959, 1960, 1963/64, 1965, 1966/67 and 1968/69, and with urban coverage for 1963/64, 1965, 1966/67, and 1968/69 are also available from the Statistical yearbook. Data for 1963/64 ,1964 and 1966/67, (Jain 1975) are not included due to limited geographic coverage, We also excluded secondary sources for 1973/74, 1976/77, 1981/82 (Fields 1989), 1977 (UN 1981), 1983 (Milanovic 1994), and 1985/86 due to availability of the primary source.

Barbados National household surveys have been conducted in 1951/52 and 1978/79 (Downs, 1988). Estimates based on personal tax returns, reported consistently for 1951-1981 (Holder and Prescott, 1989), had to be excluded as they exclude the non-wage earning population. Jain's figure (used by Alesina and Rodrik) is based on the same source.

Belgium Household surveys with national coverage are available for 1978/79 (UN 1985), and for 1985, 1988, and 1992 (LIS 1995). Earlier data for 1969, 1973, 1975, 1976 and 1977 (UN 1981) refer to taxable households only and are not included.

Bolivia The only survey with national coverage is the 1990 LSMS (World Development Report). Surveys for 1986 and 1989 cover the main cities only (Psacharopoulos et al. 1992) and are therefore not included. Data for 1968 (Cromwell 1977) do not refer to a clear definition and is therefore excluded.

Botswana The only survey with national coverage was conducted in 1985-1986 (Chen et al 1993); surveys in 74/75 and 85/86 included rural areas only (UN 1981). We excluded Gini estimates for 1971/72 that refer to the economically active population only (Jain 1975), as well as 1974/75 and 1985/86 (Valentine 1993) due to lack of national coverage or consistency in definition.

Brazil Data from 1960, 1970, 1974/75, 1976, 1977, 1978, 1980, 1982, 1983, 1985, 1987 and 1989 are available from the statistical yearbook, in addition to data for 1978 (Fields 1987) and for 1979 (Psacharopoulos et al. 1992). Other sources have been excluded as they were either not of national coverage, based on wage earners only, or because a more consistent source was available.

Bulgaria: Data from household surveys are available for 1963-69 (in two year intervals), for 1970-90 (on an annual basis) from the Statistical yearbook and for 1991 - 93 from household surveys by the World Bank (Milanovic and Ying).

Burkina Faso A priority survey has been undertaken in 1995.

Central African Republic: Except for a household survey conducted in 1992, no information was available.

Cameroon The only data are from a 1983/4 household budget survey (World Bank Poverty Assessment).

Canada Gini- and share data for the 1950-61 (in irregular intervals), 1961-81 (biennially), and 1981-91 (annually) are available from official sources (Statistical Yearbook for years before 1971 and Income Distributions by Size in Canada for years since 1973, various issues). All other references seem to be based on these primary sources.

Chad: An estimate for 1958 is available in the literature, and used by Alesina and Rodrik and Persson and Tabellini but was not included due to lack of primary sources.

Chile The first nation-wide survey that included not only employment income was carried out in 1968 (UN 1981). This is complemented by household survey-based data for 1971 (Fields 1989), 1989, and 1994. Other data that refer either only to part of the population or -as in the case of a long series available from World Bank country operations- are not clearly based on primary sources, are excluded.

China Annual household surveys from 1980 to 1992, conducted separately in rural and urban areas, were consolidated by Ying (1995), based on the statistical yearbook. Data from other secondary sources are excluded due to limited geographic and population coverage and data from Chen et al (1993) for 1985 and 1990 have not been included, to maintain consistency of sources..

Colombia The first household survey with national coverage was conducted in 1970 (DANE 1970). In addition, there are data for 1971, 1972, 1974 CEPAL (1986), and for 1978, 1988/89, and 1991 (World Bank Poverty Assessment 1992 and Chen et al. 1995). Data referring to years before 1970 -including the 1964 estimate used in Persson and Tabellini were excluded, as were estimates for the wage earning population only.

Costa Rica Data on Gini coefficients and quintile shares are available for 1961, 1971 (Cespedes 1973),1977 (OPNPE 1982), 1979 (Fields 1989), 1981 (Chen et al 1993), 1983 (Bourguignon and Morrison 1989), 1986 (Sauma-Fiatt 1990), and 1989 (Chen et al 1993). Gini coefficients for 1971 (Gonzalez-Vega and Cespedes in Rottenberg 1993), 1973 and 1985 (Bourguignon and Morrison 1989) cover urban areas only and were excluded.

Cote d'Ivoire: Data based on national-level household surveys (LSMS) are available for 1985, 1986, 1987, 1988, and 1995. Information for the 1970s (Schneider 1991) is based on national accounting information and therefore excluded

Cuba Official information on income distribution is limited. Data from secondary sources are available for 1953, 1962, 1973, and 1978, relying on personal wage income, i.e. excluding the population that is not economically active (Brundenius 1984).

Czech Republic Household surveys for 1993 and 1994 were obtained from Milanovic and Ying. While it is in principle possible to go back further, splitting national level surveys for the former Czechoslovakia into their independent parts, we decided not to do so as the same argument could be used to

AU: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 11.700 % in 2018. This records an increase from the previous number of 10.700 % for 2016. AU: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 10.400 % from Dec 1981 (Median) to 2018, with 12 observations. The data reached an all-time high of 11.700 % in 2018 and a record low of 9.700 % in 2004. AU: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

The data are a collection of Gini coefficients derived from taxation statistics published by the Australian Taxation Office (ATO). The data are available at the national, state and gender level. PhD related and intended to correctly identify the relationship between income inequality an economic growth.

AU: Income Share Held by Lowest 10% data was reported at 2.700 % in 2018. This records a decrease from the previous number of 2.800 % for 2016. AU: Income Share Held by Lowest 10% data is updated yearly, averaging 2.750 % from Dec 1981 (Median) to 2018, with 12 observations. The data reached an all-time high of 3.000 % in 2004 and a record low of 2.600 % in 1989. AU: Income Share Held by Lowest 10% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Social: Poverty and Inequality. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Educational resources and lesson plans based on Income Inequality (Gini Coefficients) for Australian regions data collection Lineage: Fleming, David; Measham, Tom (2015): Income Inequality (Gini Coefficients) for Australian regions. v1. CSIRO. Data Collection. https://doi.org/10.4225/08/55093772960E4

AU: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data was reported at 0.400 % in 2015. This records an increase from the previous number of 0.330 % for 2009. AU: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data is updated yearly, averaging 0.365 % from Dec 2009 (Median) to 2015, with 2 observations. The data reached an all-time high of 0.400 % in 2015 and a record low of 0.330 % in 2009. AU: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Social: Poverty and Inequality. Proportion of population spending more than 25% of household consumption or income on out-of-pocket health care expenditure. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory. Geneva: World Health Organization; 2023. (https://www.who.int/data/gho/data/themes/topics/financial-protection);Weighted average;This is the Sustainable Development Goal indicator 3.8.2[https://unstats.un.org/sdgs/metadata/].

This table contains estimates of Incomes (Median Equivalised, Median Disposable), Poverty (using the proportion of people below a half median equivalised disposable household income poverty line), Inequality (using the Gini coefficient) and financial stress (Had no access to emergency money, Can't afford a night out once a fortnight and Leaving low income from benefit). Leaving low income from benefit is the gross earning (expressed as a percentage of average full time earnings) required for a family to reach a 60% of median household income threshold from benefits of last resort (State welfare payments or income support). All estimates were derived using a spatial microsimulation model which used the Survey of Income and Housing and the 2011 Census data as base datasets, so they are synthetic estimates. This table forms part of the AURIN Social Indicators project.

This dataset presents the synthetically modeled indicators of the population in small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The synthetic indicators produced by the spatial micro-simulation model (SpatialMSM) are: median income, equivalised disposable median income, Gini coefficient and housing stress. The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). NATSEM's spatial micro-simulation model uses a technique that takes a survey and re-weights it to small area Census data. SpatialMSM18F is the application of the NATSEM Spatial Micro-simulation model using the ABS Survey of Income and Housing 2015/2016 and the 2016 Census of Population and Housing at the SA2 level (Tanton et al. 2011). All the indicators from the SpatialMSM model are synthetic, so there is some model error as well as other error from the survey. Therefore, they are not as accurate as the Census data used. For more information please view the NATSEM Technical Report. Please note: AURIN has spatially enabled the original data provided directly from NATSEM.

基尼系数在12-01-2018达0.343NA，相较于12-01-2016的0.337NA有所增长。基尼系数数据按年更新，12-01-1981至12-01-2018期间平均值为0.335NA，共12份观测结果。该数据的历史最高值出现于12-01-2008，达0.354NA，而历史最低值则出现于12-01-1981，为0.313NA。CEIC提供的基尼系数数据处于定期更新的状态，数据来源于Our World in Data，数据归类于全球数据库的澳大利亚 – Table AU.OWID.ESG: Social: Gini Coefficient: Annual。

La moyenne pour 2021 était de 36.92 index points. La valeur la plus élevée était au Malaisie: 40.7 index points et la valeur la plus basse était au Inde: 32.8 index points. Vous trouverez ci-dessous un graphique pour tous les pays où les données sont disponibles.

This dataset presents the synthetically modeled indicators of the population in small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The synthetic indicators produced by the spatial micro-simulation model (SpatialMSM) are: median income, equivalised disposable median income, Gini coefficient and housing stress. The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). NATSEM's spatial micro-simulation model uses a technique that takes a survey and re-weights it to small area Census data. SpatialMSM18F is the application of the NATSEM Spatial Micro-simulation model using the ABS Survey of Income and Housing 2015/2016 and the 2016 Census of Population and Housing at the SA2 level (Tanton et al. 2011). All the indicators from the SpatialMSM model are synthetic, so there is some model error as well as other error from the survey. Therefore, they are not as accurate as the Census data used. For more information please view the NATSEM Technical Report. Please note:

AURIN has spatially enabled the original data provided directly from NATSEM.

Where data values are NULL, the data is either unpublished or not applicable mathematically.

The treatment of Not Stated and Overseas Visitor data is to exclude them from both the numerator and the denominator.

Methodology between the 2016 NATSEM and 2011 OECD data release may have changed, please refer to the technical report for parity status and specific changes.

Cette statistique présente l'indice de Gini des pays membres de l'Union européenne en 2022. Cette année-là, la Bulgarie avait l'indice de Gini le plus élevé de l'Union européenne (38,4), ce qui signifie que le pays avait le niveau d'inégalité le plus élevé parmi les pays européens. Inversement, la Slovaquie a obtenu l'indice le plus bas parmi les pays de l'UE pour 2022, avec un coefficient de 21,2, ce qui suggère qu'il s'agit de la société la plus égalitaire d'Europe. Quant à la France, avec un indice de 29,8, elle se situait légèrement au-dessus de la moyenne des pays de l'UE.

L'indice de Gini est une mesure de l'inégalité au sein des pays, un coefficient faible indiquant plus d'égalité, et un coefficient élevé moins d'égalité dans la distribution de la richesse disponible parmi les habitants.

La moyenne pour 2021 était de 30.7 index points. La valeur la plus élevée était au Bulgarie: 39 index points et la valeur la plus basse était au République slovaque: 24.1 index points. Vous trouverez ci-dessous un graphique pour tous les pays où les données sont disponibles.