Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Wages in Manufacturing in China increased to 103932 CNY/Year in 2023 from 97528 CNY/Year in 2022. This dataset provides - China Average Yearly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.
The data set recorded the statistical data of the average salary and index of employed non-private sector employees in Qinghai Province in major years from 1978 to 2020, divided by year and regions such as Xining city, Haidong Prefecture, Haibei Prefecture, Huangnan Prefecture, Hainan Prefecture, Goluo Prefecture, Yushu Prefecture and Haixi Prefecture. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 17 data tables, which are: Average wages and indices of major years 1978-2004 XLS, 1978-2005 XLS, 1978-2006 XLS, 1978-2007 Average Wages and Indices of Employed Staff in non-private Sector of major years 1978-2011 XLS, main years 1978-2009 XLS, main years 1978-2010 XLS, Main years 1978-2011 Main years Average Wage and Index of Employed Staff and Workers in Non-private Sector, 1981-2012, main years Average Wage and Index of Employed Staff and workers in Non-private Sector, 1981-2013. XLS, main years Average wage and index of Employed Staff and workers in Non-private Sector, 1981-2014. Average Wage and index of Employed Staff and Workers in non-private Sector in major years 1981-2015 XLS, Average Wage and Index of Employed Staff and workers in Non-private Sector in major years 1981-2016 XLS, average Wage and Index of Employed Staff and workers in Non-private Sector in major years 1981-2017 XLS, Average Wage and Index of Employed Staff and Workers in Non-private Units in Main years 1981-2018. XLS, Average wage of Employed Staff in Non-private Units by Industry and Region in Qinghai Province (2019). XLS, Average wage of Employed Staff in Non-private Units by Industry and Region in Qinghai Province (2020). For example, the 2018 table has 4 fields: Field 1: Year Field 2: region Field 3: Average salary Field 4: Index
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Disposable Personal Income in China increased to 54188 CNY in 2024 from 51821 CNY in 2023. This dataset provides - China Disposable Income per Capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Wages in Spain increased 3.83 percent in March of 2025 over the same month in the previous year. This dataset provides - Spain Wage Growth- actual values, historical data, forecast, chart, statistics, economic calendar and news.
This data set records the statistical data of the average wages of employees in urban collective units of Qinghai Province from 1978 to 2006, which are divided by industry, region and purpose. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains four data tables, which are: the average wages of employees in different industries of urban collective units (2003). XLS, the average wages of employees in different industries of urban collective units from 1978 to 2001. XLS, the average wages of employees in different industries of urban collective units from 1978 to 2002. XLS, the average wages of employees in different industries of urban collective units from 2004. XLS, and the average wages of employees in different industries of urban collective units from 2006. XLS ls。 The data table structure is the same. For example, the data table in 2006 has four fields: Field 1: year Field 2: Industry Field 3: Region Field 4: amount
This data set records the statistical data of average wages of employees in different industries and regions of Qinghai Province from 1978 to 2010. The data are divided by project, total of the whole province, Xining, Haidong, Haibei, Huangnan, Hainan, Yushu, Guoluo and Haixi. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 10 tables, which are: average wages of employees by industry and region (2006). XLS, average wages of employees by industry and region (2007). XLS, average wages of employees by industry and region (2008). XLS, average wages of employees by industry and region (2009). Xls, average wages of employees by industry and region (2010). XLS, average wages of employees by industry and region (2003). XLS The average wages of employees in different industries were 1978-2001.xls, 1978-2002.xls, 2004.xls and 2006.xls. The data table structure is the same. For example, the data table in 2009 has 10 fields: Field 1: Project Field 2: province total Field 3: Xining City Field 4: Haidong region Field 5: Haibei Prefecture Field 6: huangnanzhou Field 7: Hainan Field 8: Golog Field 9: Yushu prefecture Field 10: Haixi
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 East Allen township. The dataset can be utilized to gain insights into gender-based income distribution within the East Allen township population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for East Allen township median household income by race. You can refer the same here
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset provides information on poverty-level wages in the United States from 1973 to 2022.
It includes data on both annual and hourly poverty-level wages, as well as wage shares for different income brackets.
The dataset is based on the Economic Policy Institute’s State of Working America Data Library, which offers comprehensive economic data for analyzing trends and patterns in the labor market.
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USA Wage Comparison for College vs. High School
Productivity and Hourly Compensation
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 Beaufort. The dataset can be utilized to gain insights into gender-based income distribution within the Beaufort population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Beaufort median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Minimum Wages in Taiwan increased to 28590 TWD/Month in 2025 from 27470 TWD/Month in 2024. This dataset provides - Taiwan Minimum Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 Huron. The dataset can be utilized to gain insights into gender-based income distribution within the Huron population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/huron-ca-income-distribution-by-gender-and-employment-type.jpeg" alt="Huron, CA gender and employment-based income distribution analysis (Ages 15+)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Huron median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 Alleghany County. The dataset can be utilized to gain insights into gender-based income distribution within the Alleghany County population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Alleghany County median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 Bar Harbor town. The dataset can be utilized to gain insights into gender-based income distribution within the Bar Harbor town population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/bar-harbor-me-income-distribution-by-gender-and-employment-type.jpeg" alt="Bar Harbor, Maine gender and employment-based income distribution analysis (Ages 15+)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Bar Harbor town median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
China Real Wage Index: Urban Non-private data was reported at 2,593.000 1978=100 in 2023. This records an increase from the previous number of 2,457.100 1978=100 for 2022. China Real Wage Index: Urban Non-private data is updated yearly, averaging 370.000 1978=100 from Dec 1979 (Median) to 2023, with 45 observations. The data reached an all-time high of 2,593.000 1978=100 in 2023 and a record low of 106.600 1978=100 in 1979. China Real Wage Index: Urban Non-private data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Labour Market – Table CN.GC: Real Wage Index.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 Dawson County. The dataset can be utilized to gain insights into gender-based income distribution within the Dawson County population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Dawson County median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 Buckhannon. The dataset can be utilized to gain insights into gender-based income distribution within the Buckhannon population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/buckhannon-wv-income-distribution-by-gender-and-employment-type.jpeg" alt="Buckhannon, WV gender and employment-based income distribution analysis (Ages 15+)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Buckhannon median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 North Oaks. The dataset can be utilized to gain insights into gender-based income distribution within the North Oaks population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/north-oaks-mn-income-distribution-by-gender-and-employment-type.jpeg" alt="North Oaks, MN gender and employment-based income distribution analysis (Ages 15+)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for North Oaks median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 Baldwin City. The dataset can be utilized to gain insights into gender-based income distribution within the Baldwin City population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/baldwin-city-ks-income-distribution-by-gender-and-employment-type.jpeg" alt="Baldwin City, KS gender and employment-based income distribution analysis (Ages 15+)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Baldwin City median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 Lee County. The dataset can be utilized to gain insights into gender-based income distribution within the Lee County population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/lee-county-va-income-distribution-by-gender-and-employment-type.jpeg" alt="Lee County, VA gender and employment-based income distribution analysis (Ages 15+)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Lee County median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 Somerdale. The dataset can be utilized to gain insights into gender-based income distribution within the Somerdale population, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/somerdale-nj-income-distribution-by-gender-and-employment-type.jpeg" alt="Somerdale, NJ gender and employment-based income distribution analysis (Ages 15+)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Somerdale median household income by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Wages in Manufacturing in China increased to 103932 CNY/Year in 2023 from 97528 CNY/Year in 2022. This dataset provides - China Average Yearly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.