87 datasets found
  1. Distribution of household income Australia FY 2020

    • statista.com
    Updated Apr 3, 2024
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    Statista (2024). Distribution of household income Australia FY 2020 [Dataset]. https://www.statista.com/statistics/614195/distribution-of-household-income-australia/
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    Dataset updated
    Apr 3, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Australia
    Description

    In financial year 2020, over 460 thousand households in Australia had a gross weekly household income of 6,000 Australian dollars or more. On the other end of the spectrum, over 30,000 households had a negative income and around over 32,000 had no income.

  2. A

    Australia Household Income per Capita

    • ceicdata.com
    Updated Dec 15, 2018
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    CEICdata.com (2018). Australia Household Income per Capita [Dataset]. https://www.ceicdata.com/en/indicator/australia/annual-household-income-per-capita
    Explore at:
    Dataset updated
    Dec 15, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 1, 2000 - Jun 1, 2020
    Area covered
    Australia
    Description

    Key information about Australia Household Income per Capita

    • Australia Annual Household Income per Capita reached 30,914.027 USD in Jun 2020, compared with the previous value of 34,767.371 USD in Jun 2018.
    • Australia Annual Household Income per Capita data is updated yearly, available from Jun 1995 to Jun 2020, with an averaged value of 25,207.153 USD.
    • The data reached an all-time high of 43,819.349 USD in Jun 2012 and a record low of 15,753.318 USD in Jun 2001.
    • In the latest reports, Retail Sales of Australia grew 4.217 % YoY in May 2023.

    CEIC calculates Annual Household Income per Capita from annual Weekly Average Household Income multiplied by 52, annual Number of Household and quarterly Total Population and converts it into USD. The Australian Bureau of Statistics provides Average Household Income in local currency, Number of Household and Total Population. Federal Reserve Board average market exchange rate is used for currency conversions. Household Income per Capita is in annual frequency, ending in June of each year. Household Income per Capita prior to 2008 based on 2017-2018 price.

  3. Distribution of disposable personal income Australia FY 2020

    • statista.com
    Updated Apr 3, 2024
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    Statista (2024). Distribution of disposable personal income Australia FY 2020 [Dataset]. https://www.statista.com/statistics/614234/distribution-of-disposable-personal-income-australia/
    Explore at:
    Dataset updated
    Apr 3, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Australia
    Description

    In financial year 2020, over two million people in Australia had a disposable personal income of 2,000 Australian dollars or more per week. On the other end of the spectrum, around 400,000 people had 99 Australian dollars or less in disposable income on a weekly basis.

  4. Australia Gross Disposable Income

    • ceicdata.com
    Updated Jun 15, 2021
    + more versions
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    CEICdata.com (2021). Australia Gross Disposable Income [Dataset]. https://www.ceicdata.com/en/australia/sna08-gross-income-and-use-of-gross-disposable-income/gross-disposable-income
    Explore at:
    Dataset updated
    Jun 15, 2021
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    Australia
    Variables measured
    Gross Disposable Income
    Description

    Australia Gross Disposable Income data was reported at 695,764.000 AUD mn in Dec 2024. This records an increase from the previous number of 663,997.000 AUD mn for Sep 2024. Australia Gross Disposable Income data is updated quarterly, averaging 104,987.000 AUD mn from Sep 1959 (Median) to Dec 2024, with 262 observations. The data reached an all-time high of 695,764.000 AUD mn in Dec 2024 and a record low of 3,951.000 AUD mn in Mar 1960. Australia Gross Disposable Income 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.A071: SNA08: Gross Income and Use of Gross Disposable Income.

  5. N

    Median Household Income by Racial Categories in Au Sable Township, Michigan...

    • neilsberg.com
    csv, json
    Updated Mar 1, 2025
    + more versions
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    Neilsberg Research (2025). Median Household Income by Racial Categories in Au Sable Township, Michigan (, in 2023 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/insights/au-sable-township-mi-median-household-income-by-race/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Mar 1, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Au Sable Township, Michigan
    Variables measured
    Median Household Income for Asian Population, Median Household Income for Black Population, Median Household Income for White Population, Median Household Income for Some other race Population, Median Household Income for Two or more races Population, Median Household Income for American Indian and Alaska Native Population, Median Household Income for Native Hawaiian and Other Pacific Islander Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the median household income within each racial category idetified by the US Census Bureau, we conducted an initial analysis and categorization of the data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). It is important to note that the median household income estimates exclusively represent the identified racial categories and do not incorporate any ethnicity classifications. Households are categorized, and median incomes are reported based on the self-identified race of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the median household income across different racial categories in Au Sable township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

    Key observations

    Based on our analysis of the distribution of Au Sable township population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 91.48% of the total residents in Au Sable township. Notably, the median household income for White households is $43,958. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $43,958.

    Content

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

    Racial categories include:

    • White
    • Black or African American
    • American Indian and Alaska Native
    • Asian
    • Native Hawaiian and Other Pacific Islander
    • Some other race
    • Two or more races (multiracial)

    Variables / Data Columns

    • Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Au Sable township.
    • Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

    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 by race. You can refer the same here

  6. Income Inequality (Gini Coefficients) for Australian regions

    • data.csiro.au
    • researchdata.edu.au
    Updated Mar 18, 2015
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    David A. Fleming Munoz; Thomas Measham (2015). Income Inequality (Gini Coefficients) for Australian regions [Dataset]. http://doi.org/10.4225/08/55093772960E4
    Explore at:
    Dataset updated
    Mar 18, 2015
    Dataset provided by
    CSIROhttp://www.csiro.au/
    Authors
    David A. Fleming Munoz; Thomas Measham
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2001 - Dec 31, 2011
    Area covered
    Australia
    Dataset funded by
    CSIROhttp://www.csiro.au/
    Description

    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.

  7. A

    Australia Household Income: Gross Disposable Income

    • ceicdata.com
    Updated Aug 4, 2021
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    CEICdata.com (2021). Australia Household Income: Gross Disposable Income [Dataset]. https://www.ceicdata.com/en/australia/sna08-household-saving-ratio-and-household-income/household-income-gross-disposable-income
    Explore at:
    Dataset updated
    Aug 4, 2021
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    Australia
    Variables measured
    Saving
    Description

    Australia Household Income: Gross Disposable Income data was reported at 421,840.000 AUD mn in Dec 2024. This records a decrease from the previous number of 435,293.000 AUD mn for Sep 2024. Australia Household Income: Gross Disposable Income data is updated quarterly, averaging 72,770.500 AUD mn from Sep 1959 (Median) to Dec 2024, with 262 observations. The data reached an all-time high of 435,293.000 AUD mn in Sep 2024 and a record low of 2,931.000 AUD mn in Jun 1960. Australia Household Income: Gross Disposable Income 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.A287: SNA08: Household Saving Ratio and Household Income.

  8. g

    ABS - Personal Income - Total Income Distribution (SA2) 2017-2018 |...

    • gimi9.com
    Updated Jul 31, 2025
    + more versions
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    (2025). ABS - Personal Income - Total Income Distribution (SA2) 2017-2018 | gimi9.com [Dataset]. https://gimi9.com/dataset/au_au-govt-abs-abs-personal-income-total-income-distribution-sa2-2017-18-sa2-2016/
    Explore at:
    Dataset updated
    Jul 31, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset presents information about total income distribution. The data covers the financial year of 2017-2018, and is based on Statistical Area Level 2 (SA2) according to the 2016 edition of the Australian Statistical Geography Standard (ASGS). Total Income is the sum of all reported income derived from Employee income, Own unincorporated business, Superannuation, Investments and Other income. Total income does not include the non-lodger population. Government pensions, benefits or allowances are excluded from the Australian Bureau of Statistics (ABS) income data and do not appear in Other income or Total income. Pension recipients can fall below the income threshold that necessitates them lodging a tax return, or they may only receive tax free pensions or allowances. Hence they will be missing from the personal income tax data set. Recent estimates from the ABS Survey of Income and Housing (which records Government pensions and allowances) suggest that this component can account for between 9% to 11% of Total income. All monetary values are presented as gross pre-tax dollars, as far as possible. This means they reflect income before deductions and loses, and before any taxation or levies (e.g. the Medicare levy or the temporary budget repair levy) are applied. The amounts shown are nominal, they have not been adjusted for inflation. The income presented in this release has been categorised into income types, these categories have been devised by the ABS to closely align to ABS definitions of income. The statistics in this release are compiled from the Linked Employer Employee Dataset (LEED), a cross-sectional database based on administrative data from the Australian taxation system. The LEED includes more than 120 million tax records over seven consecutive years between 2011-12 and 2017-18. Please note: All personal income tax statistics included in LEED were provided in de-identified form with no home address or date of birth. Addresses were coded to the ASGS and date of birth was converted to an age at 30 June of the reference year prior to data provision. To minimise the risk of identifying individuals in aggregate statistics, perturbation has been applied to the statistics in this release. Perturbation involves small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics, while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. Some cells have also been suppressed due to low counts. Totals may not align with the sum of their components due to missing or unpublished information in the underlying data and perturbation. For further information please visit the Australian Bureau of Statistics. AURIN has made the following changes to the original data: Spatially enabled the original data. Set 'np' (not published to protect the confidentiality of individuals or businesses) values to Null.

  9. N

    Median Household Income by Racial Categories in Au Gres, MI (, in 2023...

    • neilsberg.com
    csv, json
    Updated Mar 1, 2025
    + more versions
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    Neilsberg Research (2025). Median Household Income by Racial Categories in Au Gres, MI (, in 2023 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/research/datasets/e08d038e-f665-11ef-a994-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Mar 1, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Michigan, Au Gres
    Variables measured
    Median Household Income for Asian Population, Median Household Income for Black Population, Median Household Income for White Population, Median Household Income for Some other race Population, Median Household Income for Two or more races Population, Median Household Income for American Indian and Alaska Native Population, Median Household Income for Native Hawaiian and Other Pacific Islander Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the median household income within each racial category idetified by the US Census Bureau, we conducted an initial analysis and categorization of the data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). It is important to note that the median household income estimates exclusively represent the identified racial categories and do not incorporate any ethnicity classifications. Households are categorized, and median incomes are reported based on the self-identified race of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the median household income across different racial categories in Au Gres. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

    Key observations

    Based on our analysis of the distribution of Au Gres population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 87.27% of the total residents in Au Gres. Notably, the median household income for White households is $68,571. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $68,571.

    Content

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

    Racial categories include:

    • White
    • Black or African American
    • American Indian and Alaska Native
    • Asian
    • Native Hawaiian and Other Pacific Islander
    • Some other race
    • Two or more races (multiracial)

    Variables / Data Columns

    • Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Au Gres.
    • Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

    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 by race. You can refer the same here

  10. Australia Equivalised Disposable Income: Share: Highest Quintile

    • ceicdata.com
    Updated Mar 15, 2023
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    CEICdata.com (2023). Australia Equivalised Disposable Income: Share: Highest Quintile [Dataset]. https://www.ceicdata.com/en/australia/survey-of-income-and-housing-equivalized-disposable-household-income/equivalised-disposable-income-share-highest-quintile
    Explore at:
    Dataset updated
    Mar 15, 2023
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 1, 2000 - Jun 1, 2020
    Area covered
    Australia
    Variables measured
    Household Income and Expenditure Survey
    Description

    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.

  11. Number of households Australia FY 2018, by income per week

    • statista.com
    Updated Apr 3, 2024
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    Statista (2024). Number of households Australia FY 2018, by income per week [Dataset]. https://www.statista.com/statistics/805356/australia-household-breakdown-by-weekly-income/
    Explore at:
    Dataset updated
    Apr 3, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Australia
    Description

    In the 2018 financial year, around 567,000 households in Australia had a household income of between 400 and 499 Australian dollars per week. The largest grouping of households in one income range was households earning 3,000 to 3,499 Australian dollars per week.

  12. Share of national income across wealth groups Australia 2012-2022

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Share of national income across wealth groups Australia 2012-2022 [Dataset]. https://www.statista.com/statistics/1468540/australia-share-of-national-income-across-wealth-groups/
    Explore at:
    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Australia
    Description

    In 2022, the wealthiest top one percent of Australians held *** percent of the national income. The bottom ** percent of Australians had **** percent of the national income.

  13. N

    Au Sable, New York annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Au Sable, New York annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/ba948f68-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Au Sable, New York
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Au Sable town. The dataset can be utilized to gain insights into gender-based income distribution within the Au Sable town population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Au Sable town, among individuals aged 15 years and older with income, there were 1,107 men and 1,295 women in the workforce. Among them, 471 men were engaged in full-time, year-round employment, while 322 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 5.52% fell within the income range of under $24,999, while none of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 28.87% of men in full-time roles earned incomes exceeding $100,000, while 17.39% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

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

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 by race. You can refer the same here

  14. w

    Measuring Income Inequality (Deininger and Squire) Database 1890-1996 -...

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Oct 26, 2023
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    Klaus W. Deininger and Lyn Squire (2023). Measuring Income Inequality (Deininger and Squire) Database 1890-1996 - Argentina, Australia, Austria...and 99 more [Dataset]. https://microdata.worldbank.org/index.php/catalog/1790
    Explore at:
    Dataset updated
    Oct 26, 2023
    Dataset authored and provided by
    Klaus W. Deininger and Lyn Squire
    Time period covered
    1890 - 1996
    Area covered
    Australia
    Description

    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

  15. N

    Au Gres, MI annual income distribution by work experience and gender...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Au Gres, MI annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/au-gres-mi-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Au Gres, Michigan
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Au Gres. The dataset can be utilized to gain insights into gender-based income distribution within the Au Gres population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Au Gres, among individuals aged 15 years and older with income, there were 408 men and 375 women in the workforce. Among them, 114 men were engaged in full-time, year-round employment, while 69 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 3.51% fell within the income range of under $24,999, while none of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 47.37% of men in full-time roles earned incomes exceeding $100,000, while none of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

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

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 by race. You can refer the same here

  16. N

    Au Train Township, Michigan annual income distribution by work experience...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Neilsberg Research (2025). Au Train Township, Michigan annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/ba949062-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Au Train Township, Michigan
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Au Train township. The dataset can be utilized to gain insights into gender-based income distribution within the Au Train township population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Au Train township, among individuals aged 15 years and older with income, there were 455 men and 423 women in the workforce. Among them, 142 men were engaged in full-time, year-round employment, while 97 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 4.23% fell within the income range of under $24,999, while 9.28% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 13.38% of men in full-time roles earned incomes exceeding $100,000, while 16.49% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

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

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 by race. You can refer the same here

  17. Distribution of wealth within age groups Australia FY 2023

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Distribution of wealth within age groups Australia FY 2023 [Dataset]. https://www.statista.com/statistics/1468518/australia-distribution-of-wealth-within-age-groups/
    Explore at:
    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Australia
    Description

    In Australia, ** percent of all national wealth was owned by the wealthiest ten percent of the population in 2023. Within the age group of 65 years or older, the wealthiest ten percent also own ** percent of the wealth, while the lowest ** percent own just ** percent.

  18. N

    Au Sable charter Township, Michigan annual income distribution by work...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Neilsberg Research (2025). Au Sable charter Township, Michigan annual income distribution by work experience and gender dataset: Number of individuals ages 15+ with income, 2023 // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/ba948eea-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Au Sable Township, Michigan
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time, Number of males working full time for a given income bracket, Number of males working part time for a given income bracket, Number of females working full time for a given income bracket, Number of females working part time for a given income bracket
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To portray the number of individuals for both the genders (Male and Female), within each income bracket we conducted an initial analysis and categorization of the American Community Survey data. Households are categorized, and median incomes are reported based on the self-identified gender of the head of the household. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Au Sable charter township. The dataset can be utilized to gain insights into gender-based income distribution within the Au Sable charter township population, aiding in data analysis and decision-making..

    Key observations

    • Employment patterns: Within Au Sable charter township, among individuals aged 15 years and older with income, there were 864 men and 1,055 women in the workforce. Among them, 293 men were engaged in full-time, year-round employment, while 266 women were in full-time, year-round roles.
    • Annual income under $24,999: Of the male population working full-time, 11.60% fell within the income range of under $24,999, while 21.43% of the female population working full-time was represented in the same income bracket.
    • Annual income above $100,000: 8.87% of men in full-time roles earned incomes exceeding $100,000, while 8.65% of women in full-time positions earned within this income bracket.
    • Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)
    Content

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

    Income brackets:

    • $1 to $2,499 or loss
    • $2,500 to $4,999
    • $5,000 to $7,499
    • $7,500 to $9,999
    • $10,000 to $12,499
    • $12,500 to $14,999
    • $15,000 to $17,499
    • $17,500 to $19,999
    • $20,000 to $22,499
    • $22,500 to $24,999
    • $25,000 to $29,999
    • $30,000 to $34,999
    • $35,000 to $39,999
    • $40,000 to $44,999
    • $45,000 to $49,999
    • $50,000 to $54,999
    • $55,000 to $64,999
    • $65,000 to $74,999
    • $75,000 to $99,999
    • $100,000 or more

    Variables / Data Columns

    • Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
    • Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
    • Part-Time Males: The count of males employed part-time and earning within a specified income bracket
    • Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
    • Part-Time Females: The count of females employed part-time and earning within a specified income bracket

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    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 charter township median household income by race. You can refer the same here

  19. a

    ABS - Personal Income - Total Income Distribution (LGA) 2015-2016 - Dataset...

    • data.aurin.org.au
    Updated Mar 5, 2025
    + more versions
    Share
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    (2025). ABS - Personal Income - Total Income Distribution (LGA) 2015-2016 - Dataset - AURIN [Dataset]. https://data.aurin.org.au/dataset/au-govt-abs-abs-personal-income-total-income-distribution-lga-2015-16-lga2018
    Explore at:
    Dataset updated
    Mar 5, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset presents information about total income distribution. The data covers the financial year of 2015-2016, and is based on Local Government Areas (LGA) according to the 2016 edition of the Australian Statistical Geography Standard (ASGS). Total Income is the sum of all reported income derived from Employee income, Own unincorporated business, Superannuation, Investments and Other income. Total income does not include the non-lodger population. Government pensions, benefits or allowances are excluded from the Australian Bureau of Statistics (ABS) income data and do not appear in Other income or Total income. Pension recipients can fall below the income threshold that necessitates them lodging a tax return, or they may only receive tax free pensions or allowances. Hence they will be missing from the personal income tax data set. Recent estimates from the ABS Survey of Income and Housing (which records Government pensions and allowances) suggest that this component can account for between 9% to 11% of Total income. All monetary values are presented as gross pre-tax dollars, as far as possible. This means they reflect income before deductions and loses, and before any taxation or levies (e.g. the Medicare levy or the temporary budget repair levy) are applied. The amounts shown are nominal, they have not been adjusted for inflation. The income presented in this release has been categorised into income types, these categories have been devised by the ABS to closely align to ABS definitions of income. The statistics in this release are compiled from the Linked Employer Employee Dataset (LEED), a cross-sectional database based on administrative data from the Australian taxation system. The LEED includes more than 120 million tax records over seven consecutive years between 2011-12 and 2017-18. Please note: All personal income tax statistics included in LEED were provided in de-identified form with no home address or date of birth. Addresses were coded to the ASGS and date of birth was converted to an age at 30 June of the reference year prior to data provision.

  20. T

    Australia Disposable Personal Income

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 20, 2015
    Share
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    TRADING ECONOMICS (2015). Australia Disposable Personal Income [Dataset]. https://tradingeconomics.com/australia/disposable-personal-income
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    json, csv, excel, xmlAvailable download formats
    Dataset updated
    Aug 20, 2015
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Sep 30, 1959 - Jun 30, 2025
    Area covered
    Australia
    Description

    Disposable Personal Income in Australia increased to 427893 AUD Million in the second quarter of 2025 from 425287 AUD Million in the first quarter of 2025. This dataset provides - Australia Disposable Personal Income - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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Statista (2024). Distribution of household income Australia FY 2020 [Dataset]. https://www.statista.com/statistics/614195/distribution-of-household-income-australia/
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Distribution of household income Australia FY 2020

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Dataset updated
Apr 3, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Australia
Description

In financial year 2020, over 460 thousand households in Australia had a gross weekly household income of 6,000 Australian dollars or more. On the other end of the spectrum, over 30,000 households had a negative income and around over 32,000 had no income.

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