covers 2004 to 2017 annual data source: Australian Bureau of Statistics cat no. 6333.0 tbls 3 and 4.

Wages in Australia increased to 1510.90 AUD/Week in the fourth quarter of 2024 from 1480.90 AUD/Week in the second quarter of 2024. This dataset provides - Australia Average Weekly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Au Gres. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Au Gres, the median income for all workers aged 15 years and older, regardless of work hours, was $42,500 for males and $31,607 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 26% between the median incomes of males and females in Au Gres. With women, regardless of work hours, earning 74 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Au Gres.

- Full-time workers, aged 15 years and older: In Au Gres, among full-time, year-round workers aged 15 years and older, males earned a median income of $94,318, while females earned $40,417, leading to a 57% gender pay gap among full-time workers. This illustrates that women earn 43 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a lower gender pay gap percentage. This indicates that Au Gres offers better opportunities for women in non-full-time positions.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

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.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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

Wages in Manufacturing in Australia increased to 1740.70 AUD/Week in the fourth quarter of 2024 from 1668.60 AUD/Week in the second quarter of 2024. This dataset provides - Australia Average Weekly Wages In Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Au Train township. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Au Train township, the median income for all workers aged 15 years and older, regardless of work hours, was $45,650 for males and $21,181 for females.

These income figures highlight a substantial gender-based income gap in Au Train township. Women, regardless of work hours, earn 46 cents for each dollar earned by men. This significant gender pay gap, approximately 54%, underscores concerning gender-based income inequality in the township of Au Train township.

- Full-time workers, aged 15 years and older: In Au Train township, among full-time, year-round workers aged 15 years and older, males earned a median income of $62,500, while females earned $42,350, leading to a 32% gender pay gap among full-time workers. This illustrates that women earn 68 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Au Train township, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

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.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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

This dataset presents data on income (including Government allowances) available from the ABS Data by Region statistics. This release of Data by Region presents various data for 2011-2019 and Census of Population and Housing data for 2011 and 2016 and is based on the Local Government Area (LGA) 2019 boundaries. The dataset includes information in the following specified areas of income: Estimates of Personal Income, Gross Capital Gains, Selected Government Pensions and Allowances, Total Personal Income (Weekly) and Equivalised Total Household Income. Data by Region contains a standard set of data for each region type, depending on the availability of statistics for particular geographies. Data are sourced from a wide variety of collections, both ABS and non-ABS. When analysing these statistics, care needs to be taken as time periods, definitions, methodologies, scope and coverage can differ across collections. Where available, data have been presented as a time series - to enable users to assess changes over time. However, when looked at on a period to period basis, some series may sometimes appear volatile. When analysing the data, users are encouraged to consider the longer term behaviour of the series, where this extra information is available. For more information please visit the Explanatory Notes.

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

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Melbourne. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Melbourne, the median income for all workers aged 15 years and older, regardless of work hours, was $28,500 for males and $19,909 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 30% between the median incomes of males and females in Melbourne. With women, regardless of work hours, earning 70 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Melbourne.

- Full-time workers, aged 15 years and older: In Melbourne, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,750, while females earned $50,500, leading to a 21% gender pay gap among full-time workers. This illustrates that women earn 79 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Melbourne, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

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.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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

This dataset presents aggregated data regarding employee jobs and median employee income per job, classified by industry subdivision at Statistical Area Level 2 (SA2). The data spans over the 2017-18 financial year and is aggregated to the 2016 SA2 boundaries.

Jobs in Australia provide aggregate statistics and are sourced from the Linked Employer-Employee Dataset (LEED). It provides new information about filled jobs in Australia, the people who hold them, and their employers. An 'employee Job' refers to a job for which the occupant receives remuneration in wages, salary, payment in kind, or piece rates. This excludes self-employment jobs held by Owner-Managers of Unincorporated Enterprises (OMUE).

The job counts in this release differ from the filled job estimates from other sources such as the Australian Labour Account and the Labour Force Australia. The Jobs in Australia release provides insights into all jobs held throughout the year, while the Labour Account data provides the number of filled jobs at a point-in-time each quarter (and annually for the financial year reference period), and Labour Force Survey data measures the number of people employed each month.

For more information on the release please visit the Australian Bureau of Statistics

This release provides statistics on the number and nature of jobs, the people who hold them, and their employers. These statistics can be used to understand regional labour markets or to identify the impact of major changes in local communities. The release also provides new insights into the number of jobs people hold, the duration of jobs, and the industries and employment income of concurrent jobs.

The scope of these data includes individuals who submitted an individual tax return to the Australian Taxation Office (ATO), individuals who had a Pay As You Go (PAYG) payment summary issued by an employer and their employers.

AURIN has spatially enabled the original data. The following additional changes were made:

• Where data was not published for confidential reasons, "np" in the original data, the records have been set to null.

• Total values may be higher than the sum of the published components due to this confidentialisation.

About this dataset

Context

The dataset presents the median household income across different racial categories in Au Sable charter 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 charter township population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 94.09% of the total residents in Au Sable charter township. Notably, the median household income for White households is $46,614. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $46,614.

https://i.neilsberg.com/ch/au-sable-charter-township-mi-median-household-income-by-race.jpeg" alt="Au Sable charter township median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 charter township.
• Median household income: Median household income, adjusting for inflation, presented in 2022-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 charter township median household income by race. You can refer the same here

In the 2018 financial year, the average gross weekly household income in New South Wales, Australia was 2,445 Australian dollars and an equivalized disposable income of 1,232 Australian dollars. The state or territory with the lowest gross income and the only one with an average gross income below 2,000 Australian dollars was Tasmania.

This dataset presents aggregated data regarding all of the jobs within the relevant statistical regions, including their number and median income. The data spans over the 2015/16 financial year and …Show full descriptionThis dataset presents aggregated data regarding all of the jobs within the relevant statistical regions, including their number and median income. The data spans over the 2015/16 financial year and is aggregated to the 2016 Statistical Level 3 (SA3) boundaries. Jobs in Australia is a new release that provides aggregate statistics from the recently developed Linked Employer-Employee Dataset (LEED). It provides new information about filled jobs in Australia, the people who hold them, and their employers. Jobs in Australia describes all job relationships accumulated over the course of a year. This means that job counts in this publication are higher than the estimates of filled jobs published in the quarterly Australian Labour Account, which provides a point-in-time, or stock measure. These statistics about jobs also differ from Labour Force Survey statistics, which estimate the number of people who held a job in each month. The purpose of this publication is to provide new information about the number and nature of filled jobs in Australia, the people who hold them, and their employers. It includes information about multiple job-holding and employment in local areas. Jobs in Australia counts all jobs held during the reference year. This complements and expands on quarterly stock estimates of filled jobs presented in the Australian Labour Account. This data is Australian Bureau of Statistics (ABS) data (catalogue number: 6160.0) used with permission from the ABS. For more information on the release please visit the Australian Bureau of Statistics. Please note: AURIN has spatially enabled the original data. Where data was not published for confidential reasons, "np" in the original data, the records have been set to null. Total values may be higher than the sum of the published components due to this confidentialisation. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2018): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 4.0 International (CC BY 4.0)

Disposable Personal Income in Australia increased to 424884 AUD Million in the first quarter of 2025 from 415014 AUD Million in the fourth quarter of 2024. This dataset provides - Australia Disposable Personal Income - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This data relates to the average annual family income of broadacre and dairy farm properties which responded to the ABARE annual farm survey over a three year period from 1996 -1997 to 1998 -1999. Average annual family income is calculated as the family share of farm income plus any wages (that are included as farm costs for taxation assessment) paid to the owner manager, spouse and dependant children, plus all off-farm income of owner manager and spouse. The data is reported at the Statistical Division (SD) level for Australia. This data relates to broadacre and dairy farms run by owner managers and has been collected by annual farm survey interview and is supplemented by information in the farm accounts. The data is presented at a scale of 25000000. The following attributes are contained within the dataset; Sd code a a unique 3 digit code for Statistical Divisions (SD), Sd name a the name of the Statistical Division (SD), Faminc a the average annual farm family income for the period 1996-1997 to 1998-1999. RSE a the relative standard error of the average farm equity ratio for the period 1996-1997 to 1998-1999. Ag_land_ha a hectares of agricultural land use in the Statistical Division (SD). Note that metropolitan areas are assigned a value of -99999, whilst areas with no data are assigned a value of -88888.

See further metadata for more detail.

Australia Standardised Price-Income Ratio: sa data was reported at 149.268 Ratio in Dec 2024. This records a decrease from the previous number of 152.371 Ratio for Sep 2024. Australia Standardised Price-Income Ratio: sa data is updated quarterly, averaging 82.643 Ratio from Mar 1970 (Median) to Dec 2024, with 220 observations. The data reached an all-time high of 153.422 Ratio in Jun 2024 and a record low of 62.554 Ratio in Sep 1983. Australia Standardised Price-Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Australia – Table AU.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Quarterly. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database. The long-term average is calculated over the whole period available when the indicator begins after 1980 or after 1980 if the indicator is longer. This value is used as a reference value. The ratio is calculated by dividing the indicator source on this long-term average, and indexed to a reference value equal to 100.

Context

The Bureau of Labor Statistics reported that, in 2013, female full-time workers had median weekly earnings of $706, compared to men's median weekly earnings of $860. Women aged 35 years and older earned 74% to 80% of the earnings of their male counterparts. https://en.wikipedia.org › wiki › Gender_pay_gap_in_the_United_States

Content

What is the gender pay gap 2019? Study after study has identified a persistent gender pay gap. A PayScale report found that women still make only $0.79 for each dollar men make in 2019. A Bureau of Labor Statistics (BLS) analysis discovered that in 2018, median weekly earnings for female full-time wage and salary workers was 81% of men's earnings.Jul 11, 2019 https://www.forbes.com/sites/shaharziv/2019/07/11/gender-pay-gap-bigger-than-you-thnk/#36ca335f7d8a.

Acknowledgements

Linked through data.gov.au for discoverability and availability. This dataset was originally found on data.gov.au https://data.gov.au/data/dataset/a5776c56-bdde-4643-a3fd-dcc2775d7d7a ***Photo by Samantha Sophia on Unsplash.

Inspiration

Great females scientists: Mileva Maric', Frances "Poppy" Northcut, Hedy Lamarr, Marie Sklodowska Curie and Ada Lovelace. If you don't know them yet, just search on Google.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Au Gres township. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Au Gres township, the median income for all workers aged 15 years and older, regardless of work hours, was $43,158 for males and $25,121 for females.

These income figures highlight a substantial gender-based income gap in Au Gres township. Women, regardless of work hours, earn 58 cents for each dollar earned by men. This significant gender pay gap, approximately 42%, underscores concerning gender-based income inequality in the township of Au Gres township.

- Full-time workers, aged 15 years and older: In Au Gres township, among full-time, year-round workers aged 15 years and older, males earned a median income of $58,958, while females earned $37,308, leading to a 37% gender pay gap among full-time workers. This illustrates that women earn 63 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Au Gres township, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

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.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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

This dataset presents aggregated data regarding all of the jobs within the relevant statistical regions, including their number and median income. The data spans over the 2013/14 financial year and …Show full descriptionThis dataset presents aggregated data regarding all of the jobs within the relevant statistical regions, including their number and median income. The data spans over the 2013/14 financial year and is aggregated to the 2016 Statistical Level 2 (SA2) boundaries. Jobs in Australia is a new release that provides aggregate statistics from the recently developed Linked Employer-Employee Dataset (LEED). It provides new information about filled jobs in Australia, the people who hold them, and their employers. Jobs in Australia describes all job relationships accumulated over the course of a year. This means that job counts in this publication are higher than the estimates of filled jobs published in the quarterly Australian Labour Account, which provides a point-in-time, or stock measure. These statistics about jobs also differ from Labour Force Survey statistics, which estimate the number of people who held a job in each month. The purpose of this publication is to provide new information about the number and nature of filled jobs in Australia, the people who hold them, and their employers. It includes information about multiple job-holding and employment in local areas. Jobs in Australia counts all jobs held during the reference year. This complements and expands on quarterly stock estimates of filled jobs presented in the Australian Labour Account. This data is Australian Bureau of Statistics (ABS) data (catalogue number: 6160.0) used with permission from the ABS. For more information on the release please visit the Australian Bureau of Statistics. Please note: AURIN has spatially enabled the original data. Where data was not published for confidential reasons, "np" in the original data, the records have been set to null. Total values may be higher than the sum of the published components due to this confidentialisation. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2018): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 4.0 International (CC BY 4.0)

This dataset presents aggregated data regarding all of the jobs within the relevant statistical regions, including their number and median income. The data spans over the 2012/13 financial year and …Show full descriptionThis dataset presents aggregated data regarding all of the jobs within the relevant statistical regions, including their number and median income. The data spans over the 2012/13 financial year and is aggregated to the 2016 Greater Capital City Statistical Area (GCCSA) boundaries. Jobs in Australia is a new release that provides aggregate statistics from the recently developed Linked Employer-Employee Dataset (LEED). It provides new information about filled jobs in Australia, the people who hold them, and their employers. Jobs in Australia describes all job relationships accumulated over the course of a year. This means that job counts in this publication are higher than the estimates of filled jobs published in the quarterly Australian Labour Account, which provides a point-in-time, or stock measure. These statistics about jobs also differ from Labour Force Survey statistics, which estimate the number of people who held a job in each month. The purpose of this publication is to provide new information about the number and nature of filled jobs in Australia, the people who hold them, and their employers. It includes information about multiple job-holding and employment in local areas. Jobs in Australia counts all jobs held during the reference year. This complements and expands on quarterly stock estimates of filled jobs presented in the Australian Labour Account. This data is Australian Bureau of Statistics (ABS) data (catalogue number: 6160.0) used with permission from the ABS. For more information on the release please visit the Australian Bureau of Statistics. Please note: AURIN has spatially enabled the original data. Where data was not published for confidential reasons, "np" in the original data, the records have been set to null. Total values may be higher than the sum of the published components due to this confidentialisation. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2018): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 4.0 International (CC BY 4.0)

This dataset presents aggregated data regarding the number of employed people and their respective median income by the relvant statistical regions. The data spans over the 2011/12 financial year …Show full descriptionThis dataset presents aggregated data regarding the number of employed people and their respective median income by the relvant statistical regions. The data spans over the 2011/12 financial year and is aggregated to the 2016 Statistical Level 3 (SA3) boundaries. Jobs in Australia is a new release that provides aggregate statistics from the recently developed Linked Employer-Employee Dataset (LEED). It provides new information about filled jobs in Australia, the people who hold them, and their employers. Jobs in Australia describes all job relationships accumulated over the course of a year. This means that job counts in this publication are higher than the estimates of filled jobs published in the quarterly Australian Labour Account, which provides a point-in-time, or stock measure. These statistics about jobs also differ from Labour Force Survey statistics, which estimate the number of people who held a job in each month. The purpose of this publication is to provide new information about the number and nature of filled jobs in Australia, the people who hold them, and their employers. It includes information about multiple job-holding and employment in local areas. Jobs in Australia counts all jobs held during the reference year. This complements and expands on quarterly stock estimates of filled jobs presented in the Australian Labour Account. This data is Australian Bureau of Statistics (ABS) data (catalogue number: 6160.0) used with permission from the ABS. For more information on the release please visit the Australian Bureau of Statistics. Please note: AURIN has spatially enabled the original data. Where data was not published for confidential reasons, "np" in the original data, the records have been set to null. Total values may be higher than the sum of the published components due to this confidentialisation. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2018): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 4.0 International (CC BY 4.0)