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Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time.
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Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by four-digit Standard Industrial Classification 2007.
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Annual estimates of paid hours worked, weekly, hourly and annual earnings for UK employees by sex, and full-time and part-time, by region and four-digit Standard Occupational Classification.
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TwitterThe Annual Survey of Hours and Earnings (ASHE) is a UK wide survey that provides a wide range of information on earnings and hours worked. The Office for National Statistics (ONS) carries out ASHE in Great Britain and it is carried out by the Northern Ireland Statistics and Research Agency (NISRA) in Northern Ireland. The sample used comprises approximately 1% of all employees in Northern Ireland who were covered by Pay As You Earn (PAYE) schemes.
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TwitterThis bulletin is the twelfth annual publication in respect of Northern Ireland Civil Service pay. The statistics relate to annual pay for the year ending March 2022, but also contains trend data for 10 years. Median pay is analysed, broken down by:
This release was originally published on 9 June 2022 with 2021 ONS and ASHE data. It has now been updated with 2022 ONS data (published on 13 October 2022) and ASHE data (published on 26 October 2022).
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TwitterThe Annual Survey of Hours and Earnings, 2020: Synthetic Data Pilot is a synthetic version of the Annual Survey of Hours and Earnings (ASHE) study available via Trusted Research Environments (TREs).
ASHE is one of the most extensive surveys of the earnings of individuals in the UK. Data on the wages, paid hours of work, and pensions arrangements of nearly one per cent of the working population are collected. Other variables relating to age, occupation and industrial classification are also available. The ASHE sample is drawn from National Insurance records for working individuals, and the survey forms are sent to their respective employers to complete. ASHE is available for research projects demonstrating public good to accredited or approved researchers via TREs such as the Office for National Statistics Secure Research Service (SRS) or the UK Data Service Secure Lab (at SN 6689). To access collections stored within TREs, researchers need to undergo an accreditation process. Gaining access to data in a secure environment can be time and resource intensive. This pilot has created a low fidelity, low disclosure risk synthetic version of ASHE data, which can be made available to researchers more quickly while they wait for access to the real data.The synthetic data were created using the Synthpop package in R. The sample method was used; this takes a simple random sample with replacement from the real values. The project was carried out in the period between 19th December 2022 and 3rd January 2023. Further information is available within the documentation. User feedback received through this pilot will help the ONS to maximise benefits of data access and further explore the feasibility of synthesising more data in future. The ASHE synthetic data contain the same variables as ASHE for each individual, relating to wages, hours of work, pension arrangements, and occupation and industrial classifications. There are also variables for age, gender and full/part-time status. Because ASHE data are collected by the employer, there are also variables relating to the organisation employing the individual. These include employment size and legal status (e.g. public company). Various geography variables are included in the data files. The year variable in this synthetic dataset is 2020.
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TwitterThe TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Edge refers to the linear topological primitives that make up MTDB. The All Lines Shapefile contains linear features such as roads, railroads, and hydrography. Additional attribute data associated with the linear features found in the All Lines Shapefile are available in relationship (.dbf) files that users must download separately. The All Lines Shapefile contains the geometry and attributes of each topological primitive edge. Each edge has a unique TIGER/Line identifier (TLID) value.
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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 Ashe County. 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 2021
Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Ashe County, the median income for all workers aged 15 years and older, regardless of work hours, was $31,640 for males and $24,719 for females.
These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Ashe County. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecounty of Ashe County.
- Full-time workers, aged 15 years and older: In Ashe County, among full-time, year-round workers aged 15 years and older, males earned a median income of $44,437, while females earned $40,643, resulting in a 9% gender pay gap among full-time workers. This illustrates that women earn 91 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the county of Ashe County.Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Ashe County.
https://i.neilsberg.com/ch/ashe-county-nc-income-by-gender.jpeg" alt="Ashe County, NC gender based income disparity">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.
Gender classifications include:
Employment type classifications include:
Variables / Data Columns
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 Ashe County median household income by gender. You can refer the same here
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This dataset tracks annual black student percentage from 2022 to 2023 for Ashe County Early College High School vs. North Carolina and Ashe County Schools
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TwitterThe Annual Survey of Hours and Earnings, 2020: Synthetic Data Pilot is a synthetic version of the Annual Survey of Hours and Earnings (ASHE) study available via Trusted Research Environments (TREs).
ASHE is one of the most extensive surveys of the earnings of individuals in the UK. Data on the wages, paid hours of work, and pensions arrangements of nearly one per cent of the working population are collected. Other variables relating to age, occupation and industrial classification are also available. The ASHE sample is drawn from National Insurance records for working individuals, and the survey forms are sent to their respective employers to complete. ASHE is available for research projects demonstrating public good to accredited or approved researchers via TREs such as the Office for National Statistics Secure Research Service (SRS) or the UK Data Service Secure Lab (at SN 6689). To access collections stored within TREs, researchers need to undergo an accreditation process.
Gaining access to data in a secure environment can be time and resource intensive. This pilot has created a low fidelity, low disclosure risk synthetic version of ASHE data, which can be made available to researchers more quickly while they wait for access to the real data.
The synthetic data were created using the Synthpop package in R. The sample method was used; this takes a simple random sample with replacement from the real values. The project was carried out in the period between 19th December 2022 and 3rd January 2023. Further information is available within the documentation.
User feedback received through this pilot will help the ONS to maximise benefits of data access and further explore the feasibility of synthesising more data in future.
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TwitterThe TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Relationship File (ADDR.dbf) contains the attributes of each address range. Each address range applies to a single edge and has a unique address range identifier (ARID) value. The edge to which an address range applies can be determined by linking the address range to the All Lines Shapefile (EDGES.shp) using the permanent topological edge identifier (TLID) attribute. Multiple address ranges can apply to the same edge since an edge can have multiple address ranges. Note that the most inclusive address range associated with each side of a street edge already appears in the All Lines Shapefile (EDGES.shp). The TIGER/Line Files contain potential address ranges, not individual addresses. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.
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Context
The dataset tabulates the Ashe County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Ashe County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of Ashe County was 27,063, a 0% increase year-by-year from 2022. Previously, in 2022, Ashe County population was 27,062, an increase of 1.14% compared to a population of 26,757 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Ashe County increased by 2,615. In this period, the peak population was 27,226 in the year 2010. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
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 Ashe County Population by Year. You can refer the same here
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TwitterThe TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county equivalent area. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. Single-address address ranges have been suppressed to maintain the confidentiality of the addresses they describe. Multiple coincident address range feature edge records are represented in the shapefile if more than one left or right address ranges are associated to the edge. The ADDRFEAT shapefile contains a record for each address range to street name combination. Address range associated to more than one street name are also represented by multiple coincident address range feature edge records. Note that the ADDRFEAT shapefile includes all unsuppressed address ranges compared to the All Lines Shapefile (EDGES.shp) which only includes the most inclusive address range associated with each side of a street edge. The TIGER/Line shapefile contain potential address ranges, not individual addresses. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.
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Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Ashe County. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Ashe County. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2022
In terms of income distribution across age cohorts, in Ashe County, householders within the 25 to 44 years age group have the highest median household income at $63,860, followed by those in the 45 to 64 years age group with an income of $58,553. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $41,364. Notably, householders within the under 25 years age group, had the lowest median household income at $33,406.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
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 Ashe County median household income by age. You can refer the same here
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset presents the mean household income for each of the five quintiles in Ashe County, NC, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.
Key observations
https://i.neilsberg.com/ch/ashe-county-nc-mean-household-income-by-quintiles.jpeg" alt="Mean household income by quintiles in Ashe County, NC (in 2022 inflation-adjusted dollars))">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
Variables / Data Columns
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 Ashe County median household income. You can refer the same here
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TwitterRevision note:
April 2025
DCMS and digital sector October 2020 to September 2023 employment data tables including the full set of additional breakdowns for all years have been re-published.
November 2024
We have made some small revisions to both the DCMS and digital October 2021 to September 2023 employment tables, due to the identification of an error.
For DCMS sectors, October 2022 to September 2023 data tables have been re-published and for October 2021 to September 2022, headline data at sector-level has been re-published.
For Digital sectors, the October 2022 to September 2023 table has been re-published for Digital and Telecoms sectors and total filled jobs for digital subsectors. For October 2021 to September 2022, headline data has been published for the Digital and Telecoms sectors.
The full set of additional breakdowns for these tables will be re-published in due course.
26 March 2024: The Economic Estimates: Digital Sector Earnings Annual Gross Pay 2023 table has been corrected and re-published following the identification of an error. No other Digital or DCMS Earnings or Employment tables are affected by this change.
These Economic Estimates are used to provide an estimate of the contribution of DCMS sectors, and separately the digital sector, to the UK economy, measured by employment (number of filled jobs) and employee median earnings. These estimates are calculated based on the Office for National Statistics (ONS) Annual Population Survey (APS) and Annual Survey of Hours and Earnings (ASHE) respectively.
These statistics cover the contributions of the following DCMS sectors to the UK economy;
civil society
creative industries
cultural sector
gambling
sport
Tourism is not included as the data is not yet available. The release also includes estimates for the audio visual sector and computer games sector.
Users should note that there is overlap between DCMS sector definitions. In particular, several cultural sector industries are simultaneously creative industries.
A definition for each sector is available in the tables published alongside this release. Further information on all these sectors is available in the associated technical report along with details of methods and data limitations.
Between October 2022 to September 2023, there were 4.0 million total filled jobs in the included DCMS sectors, an increase of 393,000 (10.9%) since pre-pandemic (2019) and 55,000 (1.4%) since the previous equivalent 12-month period.
Since pre-pandemic (2019), driving the growth in included DCMS sector employment was the creative industries (16.3% increase). Over this period, employment also grew in the civil society sector (8.0% increase), cultural sector (1.3% increase), and gambling sector (4.8% increase), however, remained below 2019 (pre-pandemic) levels in the sports sector (2.5% decrease).
As of April 2023, median annual earnings for employees in the included DCMS sectors were £30,164; 1.7% greater than the UK overall (£29,669). Median annual earnings for included DCMS sectors have grown in line with the UK overall compared to the previous year, both growing by 6.9%. However, compared to pre-pandemic, median annual earnings have grown faster in included DCMS sectors, an increase of 22.8%, than for the UK overall, which grew 19.0%.
Employees in the creative industries (£39,366) and cultural sector (£31,014) had higher median annual earnings than the UK overall but employees in the civil society (£27,409), sport (£21,000) and gambling sectors (£26,164) had lower median annual earnings.
As of April 2023, for every £1.00 earned by a man employed in the included DCMS sectors, a woman earns £0.80. Meaning a gender pay gap of 19.8%, larger than the UK overall (14.2%). This is a 0.2 percentage point decrease from last year (20.0%), and a 3.1 percentage point decrease from pre-pandemic (22.9%).
These statistics also cover the contributions of the following digital sectors to the UK economy
digital sector
Of which: telecoms
Users should note that the telecoms sector sits wholly within the digital sector.
A definition for each sector is available in the tables published alongside this release. Further information on all these sectors is available in the associated technical report along with details of methods and data limitations
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset illustrates the median household income in Ashe County, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.
Key observations:
From 2010 to 2021, the median household income for Ashe County increased by $892 (1.91%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.
Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 4 years and declined for 7 years.
https://i.neilsberg.com/ch/ashe-county-nc-median-household-income-trend.jpeg" alt="Ashe County, NC median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.
Years for which data is available:
Variables / Data Columns
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 Ashe County median household income. You can refer the same here
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by work-based region to local and unitary authority level.
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This dataset tracks annual science proficiency from 2021 to 2022 for P.s. 161 Arthur Ashe School vs. New York and New York City Geographic District #28
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TwitterThis paper provides an overview of eight work quality indicators sourced from the Northern Ireland Labour Force Survey (LFS) and Annual Survey of Hours and Earnings (ASHE).
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time.