Australia Employment: Technicians and Trades Workers data was reported at 1,967.392 Person th in Nov 2024. This records an increase from the previous number of 1,948.350 Person th for Aug 2024. Australia Employment: Technicians and Trades Workers data is updated quarterly, averaging 1,497.384 Person th from Aug 1986 (Median) to Nov 2024, with 154 observations. The data reached an all-time high of 1,974.333 Person th in May 2024 and a record low of 1,236.877 Person th in Nov 1992. Australia Employment: Technicians and Trades Workers data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G027: Employment: by Sex and by Occupation.

Full Time Employment in Australia increased by 38692 in May of 2025. This dataset provides the latest reported value for - Australia Full Time Employment Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Australia Employment: Full Time: Males: Community and Personal Service Workers data was reported at 336.120 Person th in Feb 2025. This records an increase from the previous number of 312.211 Person th for Nov 2024. Australia Employment: Full Time: Males: Community and Personal Service Workers data is updated quarterly, averaging 188.763 Person th from Aug 1986 (Median) to Feb 2025, with 155 observations. The data reached an all-time high of 336.120 Person th in Feb 2025 and a record low of 116.841 Person th in May 1987. Australia Employment: Full Time: Males: Community and Personal Service Workers data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G028: Employment: by Sex and by Occupation: Full Time.

Graph and download economic data for Infra-Annual Labor Statistics: Working-Age Population Male: From 25 to 54 Years for Australia (LFWA25MAAUQ647S) from Q2 1978 to Q1 2025 about 25 to 54 years, working-age, Australia, males, and population.

Part Time Employment in Australia decreased to -41146 Persons in May from 29004 Persons in April of 2025. This dataset provides - Australia Part Time Employment- actual values, historical data, forecast, chart, statistics, economic calendar and news.

The 2019 APS employee census was administered to all available Australian Public Service (APS) employees. This census approach provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The census' content is designed to establish the views of APS employees on workplace issues such as leadership, learning and development, and job satisfaction. The census ran from 6 May to 7 June 2019. Overall, 104,471 APS employees responded to the employee census, a response rate of 77%.

Please be aware that the very large number of respondents to the employee census means these files are over 200 mb in size. Downloading and opening these files may take some time.

TECHNICAL NOTES

Three files are available for download.

• 2019 APS employee census - Questionnaire: This contains the 2019 APS employee census questionnaire.

• 2019 APS employee census - 5 point dataset.csv: This file contains individual responses to the 2019 APS employee census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document.

• 2019 APS employee census - 5 point dataset.sav: This file contains individual responses to the 2019 APS employee census for use with the SPSS software package.

To protect the privacy and confidentiality of respondents to the 2019 APS employee census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author.

A recommended short citation is: 2019 APS employee census data, Australian Public Service Commission.

Any queries can be directed to research@apsc.gov.au.

The ATO (Australian Tax Office) made a dataset openly available (see links) showing all the Australian Salary and Wages (2002, 2006, 2010, 2014) by detailed occupation (around 1,000) and over 100 SA4 regions. Sole Trader sales and earnings are also provided. This open data (csv) is now packaged into a database (*.sql) with 45 sample SQL queries (backupSQL[date]_public.txt).See more description at related Figshare #datavis record. Versions:V5: Following #datascience course, I have made main data (individual salary and wages) available as csv and Jupyter Notebook. Checksum matches #dataTotals. In 209,xxx rows.Also provided Jobs, and SA4(Locations) description files as csv. More details at: Where are jobs growing/shrinking? Figshare DOI: 4056282 (linked below). Noted 1% discrepancy ($6B) in 2010 wages total - to follow up.#dataTotals - Salary and WagesYearWorkers (M)Earnings ($B) 20028.528520069.4372201010.2481201410.3584#dataTotal - Sole TradersYearWorkers (M)Sales ($B)Earnings ($B)20020.9611320061.0881920101.11122620141.19630#links See ATO request for data at ideascale link below.See original csv open data set (CC-BY) at data.gov.au link below.This database was used to create maps of change in regional employment - see Figshare link below (m9.figshare.4056282).#packageThis file package contains a database (analysing the open data) in SQL package and sample SQL text, interrogating the DB. DB name: test. There are 20 queries relating to Salary and Wages.#analysisThe database was analysed and outputs provided on Nectar(.org.au) resources at: http://118.138.240.130.(offline)This is only resourced for max 1 year, from July 2016, so will expire in June 2017. Hence the filing here. The sample home page is provided here (and pdf), but not all the supporting files, which may be packaged and added later. Until then all files are available at the Nectar URL. Nectar URL now offline - server files attached as package (html_backup[date].zip), including php scripts, html, csv, jpegs.#installIMPORT: DB SQL dump e.g. test_2016-12-20.sql (14.8Mb)1.Started MAMP on OSX.1.1 Go to PhpMyAdmin2. New Database: 3. Import: Choose file: test_2016-12-20.sql -> Go (about 15-20 seconds on MacBookPro 16Gb, 2.3 Ghz i5)4. four tables appeared: jobTitles 3,208 rows | salaryWages 209,697 rows | soleTrader 97,209 rows | stateNames 9 rowsplus views e.g. deltahair, Industrycodes, states5. Run test query under **#; Sum of Salary by SA4 e.g. 101 $4.7B, 102 $6.9B#sampleSQLselect sa4,(select sum(count) from salaryWageswhere year = '2014' and sa4 = sw.sa4) as thisYr14,(select sum(count) from salaryWageswhere year = '2010' and sa4 = sw.sa4) as thisYr10,(select sum(count) from salaryWageswhere year = '2006' and sa4 = sw.sa4) as thisYr06,(select sum(count) from salaryWageswhere year = '2002' and sa4 = sw.sa4) as thisYr02from salaryWages swgroup by sa4order by sa4

The number of employed persons in Australia decreased to 14620.65 Thousand in May of 2025 from 14623.10 Thousand in April of 2025. This dataset provides - Australia Employed Persons - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset presents aggregated data regarding all of the jobs within the relevant statistical regions, including the number of employee jobs and median employee income per job by sex, classified by Statistical Area Level 2 (SA2). The data spans from 2011-12 to 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. 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.

Graph and download economic data for Infra-Annual Labor Statistics: Working-Age Population Total: From 15 to 64 Years for Australia (LFWA64TTAUA647S) from 1978 to 2024 about working-age, 15 to 64 years, Australia, and population.

Australia Employment: Community and Personal Service Workers data was reported at 1,672.703 Person th in Nov 2024. This records an increase from the previous number of 1,653.785 Person th for Aug 2024. Australia Employment: Community and Personal Service Workers data is updated quarterly, averaging 843.633 Person th from Aug 1986 (Median) to Nov 2024, with 154 observations. The data reached an all-time high of 1,700.324 Person th in May 2024 and a record low of 376.141 Person th in Feb 1987. Australia Employment: Community and Personal Service Workers data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G027: Employment: by Sex and by Occupation.

Employment in services (% of total employment) (modeled ILO estimate) in Australia was reported at 78.74 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Australia - Employment in services (% of total employment) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

The 2013 APS employee census was administered to all available Australian Public Service (APS) employees. This census approach provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The census ran from 15 May to 14 June 2013. Overall, 102,219 employees responded to the employee census, a response rate of 66%.

Please be aware that the very large number of respondents to the employee census means these files are up to 200 mb in size. Downloading and opening these files may take some time.

TECHNICAL NOTES

Three files are available for download.

• 2013 APS employee census - Questionnaire: This contains the 2013 APS employee census questionnaire.

• 2013 APS employee census - 5 point dataset.csv: This file contains individual responses to the 2013 employee census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document.

• 2013 APS employee census - 5 point dataset.sav: This file contains individual responses to the 2013 employee census for use with the SPSS software package.

To protect the privacy and confidentiality of respondents to the 2013 APS employee census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author.

A recommended short citation is: 2013 APS employee census data, Australian Public Service Commission.

Any queries can be directed to research@apsc.gov.au.

This dataset presents information about employee income by age and sex. The data covers the financial years 2011-12 to 2017-18, and is based on Statistical Area Level 4 (SA4) according to the 2016 edition of the Australian Statistical Geography Standard (ASGS).

Employee income is the total (or gross) income received as a return to labour from an employer or from a person's own incorporated business (when they are employed by this business). The data used in deriving employee income comes from both Individual Tax Returns (ITR) and payment summaries (where an individual has not lodged an ITR).

All monetary values are presented as gross pre-tax dollars, as far as possible. This means they reflect income before deductions and loses, and before any taxation or levies (e.g. the Medicare levy or the temporary budget repair levy) are applied. The amounts shown are nominal, they have not been adjusted for inflation. The income presented in this release has been categorised into income types, these categories have been devised by the Australian Bureau of Statistics (ABS) to closely align to ABS definitions of income.

The statistics in this release are compiled from the Linked Employer Employee Dataset (LEED), a cross-sectional database based on administrative data from the Australian taxation system. The LEED includes more than 120 million tax records over seven consecutive years between 2011-12 and 2017-18.

Please note:

• All personal income tax statistics included in LEED were provided in de-identified form with no home address or date of birth. Addresses were coded to the ASGS and date of birth was converted to an age at 30 June of the reference year prior to data provision.

• To minimise the risk of identifying individuals in aggregate statistics, perturbation has been applied to the statistics in this release. Perturbation involves small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics, while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. Some cells have also been suppressed due to low counts.

• Totals may not align with the sum of their components due to missing or unpublished information in the underlying data and perturbation.

For further information please visit the Australian Bureau of Statistics.

AURIN has made the following changes to the original data:

• Spatially enabled the original data.

• Set 'np' (not published to protect the confidentiality of individuals or businesses) values to Null.

This dataset presents information about employee income. The data covers the financial years 2011-12 to 2017-18, and is based on Statistical Area Level 2 (SA2) according to the 2016 edition of the Australian Statistical Geography Standard (ASGS).

Employee income is the total (or gross) income received as a return to labour from an employer or from a person's own incorporated business (when they are employed by this business). The data used in deriving employee income comes from both Individual Tax Returns (ITR) and payment summaries (where an individual has not lodged an ITR).

All monetary values are presented as gross pre-tax dollars, as far as possible. This means they reflect income before deductions and loses, and before any taxation or levies (e.g. the Medicare levy or the temporary budget repair levy) are applied. The amounts shown are nominal, they have not been adjusted for inflation. The income presented in this release has been categorised into income types, these categories have been devised by the Australian Bureau of Statistics (ABS) to closely align to ABS definitions of income.

The statistics in this release are compiled from the Linked Employer Employee Dataset (LEED), a cross-sectional database based on administrative data from the Australian taxation system. The LEED includes more than 120 million tax records over seven consecutive years between 2011-12 and 2017-18.

Please note:

• All personal income tax statistics included in LEED were provided in de-identified form with no home address or date of birth. Addresses were coded to the ASGS and date of birth was converted to an age at 30 June of the reference year prior to data provision.

• To minimise the risk of identifying individuals in aggregate statistics, perturbation has been applied to the statistics in this release. Perturbation involves small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics, while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. Some cells have also been suppressed due to low counts.

• Totals may not align with the sum of their components due to missing or unpublished information in the underlying data and perturbation.

For further information please visit the Australian Bureau of Statistics.

AURIN has made the following changes to the original data:

• Spatially enabled the original data.

• Set 'np' (not published to protect the confidentiality of individuals or businesses) values to Null.

Australia Employment: Part Time: Males: Sales Workers data was reported at 193.531 Person th in Feb 2025. This records a decrease from the previous number of 208.376 Person th for Nov 2024. Australia Employment: Part Time: Males: Sales Workers data is updated quarterly, averaging 126.508 Person th from Aug 1986 (Median) to Feb 2025, with 155 observations. The data reached an all-time high of 220.829 Person th in Aug 2024 and a record low of 36.451 Person th in May 1988. Australia Employment: Part Time: Males: Sales Workers data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G029: Employment: by Sex and by Occupation: Part Time.

Australia Employment: Clerical and Administrative Workers data was reported at 1,926.710 Person th in Nov 2024. This records an increase from the previous number of 1,848.269 Person th for Aug 2024. Australia Employment: Clerical and Administrative Workers data is updated quarterly, averaging 1,557.698 Person th from Aug 1986 (Median) to Nov 2024, with 154 observations. The data reached an all-time high of 1,930.873 Person th in Nov 2023 and a record low of 1,246.316 Person th in Aug 1986. Australia Employment: Clerical and Administrative Workers data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G027: Employment: by Sex and by Occupation.

Abstract

Previous surveys on labor migration from Pacific Island countries are often cross-sectional, not readily available, and focusing on one migration scheme, country, or issue and hence incompatible. Such limitation of existing data restricts analysis of a range of policy-relevant issues that present themselves over the migrants' life cycle such as those on migration pathways, long-term changes in household livelihood, and trajectory of migrants’ labor market outcomes, despite the significant impacts of labor migration on the economy of the Pacific Island countries. To address these shortfalls in the Pacific migration data landscape, the PLMS is designed to be longitudinal, spanning multiple labor sending and receiving countries and collecting omnibus information on both migrants, their households and non-migrant households. The survey allows for disaggregation and reliable comparative analysis both within and across countries and labor mobility schemes. This open-access and high-quality data will facilitate more research about the Pacific migration, help inform and improve Pacific migration policy deliberations, and engender broader positive change in the Pacific data ecosystem.

Geographic coverage

Tonga: Tongatapu, ‘Eua, Vava’u, Ha’apai, Ongo Niua. Vanuatu: Malampa, Penama, Sanma, Shefa, Tafea, Torba. Kiribati: Abaiang, Abemama, Aranuka, Arorae, Banaba, Beru, Butaritari, Kiritimati, Maiana, Makin, Marakei, Nikunau, Nonouti, North Tabiteuea, North Tarawa, Onotoa, South Tabiteuea, South Tarawa, Tabuaeran, Tamana, Teraina.

Analysis unit

• Households in Kiribati, Tonga, and Vanuatu.
• Temporary migrant workers from Kiribati, Tonga and Vanuatu who participated in the Pacific Australia Labour Mobility scheme in Australia and the Recognised Seasonal Employers scheme in New Zealand

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling frame: The PLMS sample was designed based on a Total Survey Error framework, seeking to minimize errors and bias at every stage of the process throughout preparation and implementation.

The worker sample frame is an extensive list of approximately 11,600 migrant workers from Kiribati, Tonga and Vanuatu who had participated in the RSE and PALM schemes. Due to the different modes of interviews, sampling strategies for the face-to-face segment of the household survey in Tonga was different from the rest of the surveys implemented via phone interviews. The face-to-face segment of the household survey selected households using Probability Proportional to Size sampling based on the latest population census listing and our worker sample frame, with technical inputs from the Tonga Statistics Department. The phone-based segment of the household survey used a combination of Probability Proportional to Size sampling based on the existing sample frame and random digit dialing. The design of the sample benefited from technical inputs from the Tonga Statistics Departments and the Vanuatu National Statistics Office, as well as World Bank staff from Kiribati.

As participation in the survey is voluntary, a worker might agree to participate while their household did not, and vice versa. Because of this, the survey did not achieve a complete one-to-one match between interviewed workers and sending households. Of all interviewed respondents, 418 workers in the worker survey are linked to their households in the household survey. However, after removing incomplete interviews, 341 worker-household pairs remain. They are matched by either pre-assigned serial ID numbers or contact details collected in the household and worker surveys during the post-fieldwork data cleaning process.

Sampling deviation

The survey was originally planned to be conducted face-to-face and was so for most of the collection of household data in Tonga. However, due to COVID-19, it was switched to phone-based mode and the survey instruments were adjusted accordingly to better suit the phone-based data collection while ensuring data quality. In particular, the household questionnaire was shortened, and sampling strategy changed to a combination of Probability Proportional to Size sampling based on the existing household listing and random digit dialing.

Compared to in-person data collection, the usual caveats of potential biases in phone-based survey related to disproportional phone ownership and connectivity apply here. The random digit dialing approach provides data representative of the phone-owning population. Yet due to lack of information, it is difficult to judge whether sending households in Kiribati, Tonga, and Vanuatu are more or less likely to own a phone and/or respond positively to survey request than non-sending households.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

• The questionnaires were jointly designed in English by the World Bank and researchers at the Development Policy Centre, Australian National University. They were translated into Bislama, Gilbertese and Tongan, scripted into CAPI/CATI programs, tested and piloted before being finalized. The design of the questionnaires and the samples benefited from technical inputs from the Tonga Statistics Departments, Pacific consultants, and academic experts specialized in Pacific labor mobility and remittances.
• Enumerators are native speakers from the labor-sending countries covered in the survey and were trained to elicit information asked in the questionnaire in local languages.
• The phone-based household questionnaire is moderately shorter than the in-person version.

Cleaning operations

The published data have been cleaned and anonymized. All incomplete interview records have been removed from the final datasets. The anonymization process followed the theory of Statistical Disclosure Control for microdata, aiming to minimize re-identification risk, i.e. the risk that the identity of an individual (or a household) described by a specific record could be determined with a high level of confidence. The anonymization process employs the k-anonymity method to calculate the re-identification risk. Risk measurement, anonymization and utility measurement for the PLMS were done using sdcMicro, an add-on package for the statistical software R for Statistical Disclosure Control (SDC) of microdata.

Since the household questionnaire was shortened when the survey switched from face-to-face to phone-based data collection, there face-to-face datasets and phone-based datasets are not identical, but they are consistent and can be harmonized. The mapping guide enclosed in this publication provides a guide to data users to wish to harmonize them.

Household expenditure variables in the household dataset and individual wage variable in the household member dataset are in USD. Local currencies were converted into USD based on the following exchange rates: 1 Tongan Pa'anga= 0.42201412 USD; 1 Vanuatu Vatu= 0.0083905322 USD; 1 Kiribati dollar= 0.66942499 USD.

Response rate

Face-to-face segment of the PLMS household survey: not applicable. Phone-based segment of the PLMS household survey: 26%. The PLMS Worker survey: 31%

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 2015-16 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.

This dataset presents aggregated data regarding all of the jobs within the relevant statistical regions, including the number of employee jobs and median employee income per job by sex, classified by Statistical Area Level 3 (SA3). The data spans from 2014-15 to 2018-19 financial year and is aggregated to the 2016 SA3 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.

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.

• Totals are higher than the sum of their components due to data which could not be classified to component characteristics.