In the 2018 financial year, the 90th percentile in Australia had a household net worth reaching about 2.93 million Australian dollars. By comparison the 10th percentile had a household net worth of 31,400 Australian dollars.

Australia Equivalised Disposable Income: Share: Lowest Quintile data was reported at 7.400 % in 2020. This records a decrease from the previous number of 7.500 % for 2018. Australia Equivalised Disposable Income: Share: Lowest Quintile data is updated yearly, averaging 7.700 % from Jun 1995 (Median) to 2020, with 16 observations. The data reached an all-time high of 8.300 % in 1997 and a record low of 7.300 % in 2008. Australia Equivalised Disposable Income: Share: Lowest Quintile 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.

Australia Equivalised Disposable Income: Share: Highest Quintile data was reported at 39.800 % in 2020. This records a decrease from the previous number of 40.400 % for 2018. Australia Equivalised Disposable Income: Share: Highest Quintile data is updated yearly, averaging 38.950 % from Jun 1995 (Median) to 2020, with 16 observations. The data reached an all-time high of 41.000 % in 2008 and a record low of 37.100 % in 1997. Australia Equivalised Disposable Income: Share: Highest Quintile 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.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Au Sable, New York, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 15,950, while the mean income for the highest quintile (20% of households with the highest income) is 222,933. This indicates that the top earners earn 14 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 385,630, which is 172.98% higher compared to the highest quintile, and 2417.74% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Sable town median household income. You can refer the same here

Australia Weekly Equivalised Disposable Income: 2019-20p: Mean: Second Quintile data was reported at 710.000 AUD in 2020. This records an increase from the previous number of 684.000 AUD for 2018. Australia Weekly Equivalised Disposable Income: 2019-20p: Mean: Second Quintile data is updated yearly, averaging 549.125 AUD from Jun 1995 (Median) to 2020, with 16 observations. The data reached an all-time high of 710.000 AUD in 2020 and a record low of 422.699 AUD in 1996. Australia Weekly Equivalised Disposable Income: 2019-20p: Mean: Second Quintile 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.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Au Gres, MI, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 12,981, while the mean income for the highest quintile (20% of households with the highest income) is 146,639. This indicates that the top earners earn 11 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 216,753, which is 147.81% higher compared to the highest quintile, and 1669.77% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Gres median household income. You can refer the same here

Australia Equivalised Disposable Income: Share: Fourth Quintile data was reported at 23.000 % in 2020. This records an increase from the previous number of 22.700 % for 2018. Australia Equivalised Disposable Income: Share: Fourth Quintile data is updated yearly, averaging 23.100 % from Jun 1995 (Median) to 2020, with 16 observations. The data reached an all-time high of 23.900 % in 1996 and a record low of 22.400 % in 2014. Australia Equivalised Disposable Income: Share: Fourth Quintile 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.

In 2020, the Australian Digital Inclusion Index (ADII) results showed that people earning over ******* Australian dollars a year has the scored highest, with an ADII score of ****. The ADII scores by quintile suggest that people who earned more tended to have a much higher level of digital inclusion than those on a lower income.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Au Train Township, Michigan, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 9,401, while the mean income for the highest quintile (20% of households with the highest income) is 158,787. This indicates that the top earners earn 17 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 229,839, which is 144.75% higher compared to the highest quintile, and 2444.84% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Train township median household income. You can refer the same here

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

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Au Sable Township, Michigan, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 8,509, while the mean income for the highest quintile (20% of households with the highest income) is 131,533. This indicates that the top earners earn 15 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 197,858, which is 150.42% higher compared to the highest quintile, and 2325.28% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Sable township median household income. You can refer the same here

Australia Weekly Equivalised Disposable Income: 2019-20p: Mean: Fourth Quintile data was reported at 1,294.000 AUD in 2020. This records an increase from the previous number of 1,241.000 AUD for 2018. Australia Weekly Equivalised Disposable Income: 2019-20p: Mean: Fourth Quintile data is updated yearly, averaging 994.195 AUD from Jun 1995 (Median) to 2020, with 16 observations. The data reached an all-time high of 1,294.000 AUD in 2020 and a record low of 779.415 AUD in 1996. Australia Weekly Equivalised Disposable Income: 2019-20p: Mean: Fourth Quintile 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.

This report analyses the proportion of after-tax disposable income that is generated by households that are classified as high income earners. High income earners are defined as households that fall into the highest quintile for disposable income. To calculate the share of income that is made by high income earners, the mean income of all households in the highest quintile is divided by the sum of the mean income of each quintile. Data for this report is sourced from the Australian Bureau of Statistics and is presented in financial years.

Apple Pay users in Australia made up ** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in Australia was that they were ******, were roughly ******** years old, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in Australia was used more in online shopping than it was in offline POS.

Alipay users in Australia made up *** percent of respondents in 2025, and were likely to come from a ****** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Alipay user in Australia was that they were ****, were ******** years old, and fell in the ****** quantile in terms of income. According to Statista surveys held in 2024, less than ***** percent of all consumers in Australia at some point used Alipay in a payment transaction.

Australia Weekly Gross Income: 2015-16p: Mean: Third Quintile data was reported at 1,616.000 AUD in 2016. This records an increase from the previous number of 1,601.000 AUD for 2014. Australia Weekly Gross Income: 2015-16p: Mean: Third Quintile data is updated yearly, averaging 1,223.500 AUD from Jun 1995 (Median) to 2016, with 14 observations. The data reached an all-time high of 1,616.000 AUD in 2016 and a record low of 1,056.000 AUD in 1996. Australia Weekly Gross Income: 2015-16p: Mean: Third Quintile 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.H030: Survey of Income and Housing: Gross Household Income.

Klarna users in Australia made up ***** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of a Klarna user in Australia was that they were ****, were**********************, and fell in the ******* quantile in terms of income. According to Statista surveys held in 2024, *************** percent of all consumers in Australia at some point used Klarna in a payment transaction.

Australia Weekly Equivalised Disposable Income: 2013-14p: Mean: Highest Quintile data was reported at 2,037.000 AUD in 2014. This records an increase from the previous number of 1,903.000 AUD for 2012. Australia Weekly Equivalised Disposable Income: 2013-14p: Mean: Highest Quintile data is updated yearly, averaging 1,314.000 AUD from Jun 1995 (Median) to 2014, with 13 observations. The data reached an all-time high of 2,037.000 AUD in 2014 and a record low of 1,103.000 AUD in 1996. Australia Weekly Equivalised Disposable Income: 2013-14p: Mean: Highest Quintile 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.

Australia Weekly Equivalised Disposable Income: 2015-16p: Mean: Third Quintile data was reported at 856.000 AUD in 2016. This records a decrease from the previous number of 869.000 AUD for 2014. Australia Weekly Equivalised Disposable Income: 2015-16p: Mean: Third Quintile data is updated yearly, averaging 651.000 AUD from Jun 1995 (Median) to 2016, with 14 observations. The data reached an all-time high of 869.000 AUD in 2014 and a record low of 541.000 AUD in 1996. Australia Weekly Equivalised Disposable Income: 2015-16p: Mean: Third Quintile 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.

Australia Weekly Equivalised Disposable Income: 2015-16p: Mean: Highest Quintile data was reported at 2,009.000 AUD in 2016. This records a decrease from the previous number of 2,101.000 AUD for 2014. Australia Weekly Equivalised Disposable Income: 2015-16p: Mean: Highest Quintile data is updated yearly, averaging 1,417.000 AUD from Jun 1995 (Median) to 2016, with 14 observations. The data reached an all-time high of 2,101.000 AUD in 2014 and a record low of 1,137.000 AUD in 1996. Australia Weekly Equivalised Disposable Income: 2015-16p: Mean: Highest Quintile 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.