The Australian Census Longitudinal Dataset (ACLD) brings together a 5% sample from the 2006 Census with records from the 2011 Census to create a research tool for exploring how Australian society is changing over time. In taking a longitudinal view of Australians, the ACLD may uncover new insights into the dynamics and transitions that drive social and economic change over time, conveying how these vary for diverse population groups and geographies. It is envisaged that the 2016 and successive Censuses will be added in the future, as well as administrative data sets. The ACLD is released in ABS TableBuilder and as a microdata product in the ABS Data Laboratory. \r \r The Census of Population and Housing is conducted every five years and aims to measure accurately the number of people and dwellings in Australia on Census Night. \r \r Microdata products are the most detailed information available from a Census or survey and are generally the responses to individual questions on the questionnaire. They also include derived data from answers to two or more questions and are released with the approval of the Australian Statistician.\r The following microdata products are available for this longitudinal dataset: \r •ACLD in TableBuilder - an online tool for creating tables and graphs. \r •ACLD in ABS Data Laboratory (ABSDL) - for in-depth analysis using a range of statistical software packages.\r \r

This data set was created through use of the Australian Bureau of Statistics' Table Builder feature: http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/2016%20TableBuilder.

This data set is provided under a Creative Commons Attribution 4.0 International license. The license can be viewed here: http://www.abs.gov.au/copyright.

This dataset presents the employment rate of the population in small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). This indicator is the number and proportion of people employed. The rate is calculated as the number employed divided by the total number in that Age/Sex group (excluding Not Stated). Note that the denominator for the total employment rate is total population aged 15-64. All indicators were extracted from the ABS Tablebuilder system using the usual residence profile. For usual residence data, the ABS moves people back to where they live, rather than using the location the data were collected (place of enumeration). Usual residence data is preferred for individual level data because it removes the effect of respondents travelling or holidaying. For more information please view the NATSEM Technical Report.

Custom dataset compiled using Australian Bureau of Statistics TableBuilder to extract 2021 Australian Census data: SEXP Sex by POA (UR) by AGE5P Age in Five Year Groups and YARRP Year of Arrival in Australia (ranges). Findings based on use of ABS TableBuilder data. Analysis and compilation by Phillip Keen, The Kirby Institute, UNSW Sydney.

Dataset provides the count of persons by place of work based on their occupation level (ANZSCO - 2DIGIT) within the Local Government Area's as recorded for the 2006, 2011, 2016 and 2021 Census years. Australian Bureau of Statistics extracts from ABS Tablebuilder are used for the construction of the dataset. This dataset is best utilised to generate a view of occupations within the geographic area.

The workforce dataset contains monthly workforce sizes from July 2005 to June 2018 in the eight Australian capital cities with estimated stratification by indoor and outdoor workers. It is included in both csv and rda format. It includes variables for:

• Year
• Month
• GCCSA (Greater Capital City Statistical Area, which is used to define capital cities)
• Date (using the first day of the month)
• fulltime: Fulltime workers
• parttime: Parttime workers
• n. Overall workers
• outorin. Estimated indoor or outdoor status

This data are derived from the Australian Bureau of Statistics (ABS) Labour Force, Australia, Detailed, LM1 dataset: LM1 - Labour force status by age, greater capital city and rest of state (ASGS), marital status and sex, February 1978 onwards (pivot table). Occupational data from the 2006, 2011 and 2016 Census of Population and Housing (ABS Census TableBuilder Basic data) were used to stratify this dataset into indoor and outdoor classifications as per the "Indooroutdoor classification.xlsx" file. For the Census data, GCCSA for the place of work was used, not the place of usual residence.

Occupations were defined by the Australian and New Zealand Standard Classification of Occupations (ANZSCO). Each 6-digit ANZSCO occupation (the lowest level classification) was manually cross-matched with their corresponding occupation(s) from the Canadian National Occupation System (NOC). ANZSCO and NOC share a similar structure, because they are both derived from the International Standard Classification of Occupations. NOC occupations listed with an “L3 location” (include main duties with outdoor work for at least part of the working day) were classified as outdoors, including occupations with multiple locations. Occupations without a listing of "L3 location" were classified as indoors (no outdoor work). 6-digit ANZSCO occupations were then aggregated to 4-digit unit groups to match the ABS Census TableBuilder Basic data. These data were further aggregated into indoor and outdoor workers.

The 4-digit ANZSCO unit groups’ indoor and outdoor classifications are listed in "Indooroutdoor classification.xlsx."

ANZSCO occupations associated with both indoor and outdoor listings were classified based on the more common listing, with indoors being selected in the event of a tie. The cross-matching of ANZSCO and NOC occupation was checked against two previous cross-matches used in published Australian studies utilising older ANZSCO and NOC versions. One of these cross-matches, the original cross-match, was validated with a strong correlation between ANZSCO and NOC for outdoor work (Smith, Peter M. Comparing Imputed Occupational Exposure Classifications With Self-reported Occupational Hazards Among Australian Workers. 2013).

To stratify the ABS Labour Force detailed data by indoors or outdoors, workers from the ABS Census 2006, 2011 and 2016 data were first classified as indoors or outdoors. To extend the indoor and outdoor classification proportions from 2005 to 2018, the population counts were (1) stratified by workplace GCCSA (standardised to the 2016 metrics), (2) logit-transformed and then interpolated using cubic splines and extrapolated linearly for each month, and (3) back-transformed to the normal population scale. For the 2006 Census, workplace location was reported by Statistical Local Area and then converted to GCCSA. This interpolation method was also used to estimate the 1-monthly worker count for Darwin relative to the rest of Northern Territory (ABS worker 1-monthly counts are reported only for Northern Territory collectively).

ABS data are owned by the Commonwealth Government under a CC BY 4.0 license. The attached datasets are derived and aggregated from ABS data.

This dataset presents the volunteering rate of the population in small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). This indicator is the number and proportion of people in the area who have done unpaid voluntary work through an organisation or group in the last 12 months. All indicators were extracted from the ABS Tablebuilder system using the usual residence profile. For usual residence data, the ABS moves people back to where they live, rather than using the location the data were collected (place of enumeration). Usual residence data is preferred for individual level data because it removes the effect of respondents travelling or holidaying. For more information please view the NATSEM Technical Report.

Acknowledgements

The use and distribution of the data are governed by the Singapore Open Data Licence. More information can be found at < https://data.gov.sg/open-data-licence#acceptance >

Source of the raw data < https://www.tablebuilder.singstat.gov.sg/publicfacing/initApiList.action >

Code

If you are interested in the source code to extract the data, visit my GitHub page for more information.

Contains demographic profile information for workers from the Australian Bureau of Statistics (ABS) 2016 Census of Population and Housing. Data has been aggregated based on work location. This data has been derived from the ABS Census TableBuilder online data tool (http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/2016%20TableBuilder) by Australian Bureau of Statistics, used under CC 4.0.

Acknowledgements

The use and distribution of the data are governed by the Singapore Open Data Licence. More information can be found at < https://data.gov.sg/open-data-licence#acceptance >

Source of the raw data < https://www.tablebuilder.singstat.gov.sg/publicfacing/initApiList.action >

This dataset presents the marital status of the population by sex in small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). This indicator is the number and proportion of people in each of the Registered Marital Status (MSTP) categories by sex. All indicators were extracted from the ABS Tablebuilder system using the usual residence profile. For usual residence data, the ABS moves people back to where they live, rather than using the location the data were collected (place of enumeration). Usual residence data is preferred for individual level data because it removes the effect of respondents travelling or holidaying. For more information please view the NATSEM Technical Report. Please note: AURIN has spatially enabled the original data provided directly from NATSEM. Where data values are NULL, the data is either unpublished or not applicable mathematically. The treatment of Not Stated and Overseas Visitor data is to exclude them from both the numerator and the denominator. Methodology between the 2016 NATSEM and 2011 OECD data release may have changed, please refer to the technical report for parity status and specific changes.

This dataset presents the migration rate in small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). The migration rate is the proportion of people in the area who were not born in Australia, that is, who have migrated to Australia in the past. All indicators were extracted from the ABS Tablebuilder system using the usual residence profile. For usual residence data, the ABS moves people back to where they live, rather than using the location the data were collected (place of enumeration). Usual residence data is preferred for individual level data because it removes the effect of respondents travelling or holidaying. For more information please view the NATSEM Technical Report. Please note: AURIN has spatially enabled the original data provided directly from NATSEM. Where data values are NULL, the data is either unpublished or not applicable mathematically. In the calculation, Inadequately Described, At sea, Not Stated and Overseas Visitor were excluded from both the numerator and denominator as there is no information on these respondents. Methodology between the 2016 NATSEM and 2011 OECD data release may have changed, please refer to the technical report for parity status and specific changes.

Acknowledgements

The use and distribution of the data are governed by the Singapore Open Data Licence. More information can be found at < https://data.gov.sg/open-data-licence#acceptance >

Source of the raw data < https://www.tablebuilder.singstat.gov.sg/publicfacing/initApiList.action >

Definition

M1 = Currency in Active Circulation + Private Sector Demand Deposits with Banks M2 = M1 + Quasi-money M3 = M2+ Net Deposits with Non-bank Financial Institutions (NBFIs)

Acknowledgements

The use and distribution of the data are governed by the Singapore Open Data Licence. More information can be found at < https://data.gov.sg/open-data-licence#acceptance >

Source of the raw data < https://www.tablebuilder.singstat.gov.sg/publicfacing/initApiList.action >

Acknowledgements

The use and distribution of the data are governed by the Singapore Open Data Licence. More information can be found at < https://data.gov.sg/open-data-licence#acceptance >

Source of the raw data < https://www.tablebuilder.singstat.gov.sg/publicfacing/initApiList.action >

This dataset presents the social and economic indicators for the indigenous population of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical …Show full descriptionThis dataset presents the social and economic indicators for the indigenous population of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The data has been provided by The National Centre for Social and Economic Modelling (NATSEM) and includes the following indicators: age, sex, employment, education level, occupation, school attendance, language, household relationships, family types, household tenure type, household income, motor vehicles and household family composition. All indicators were extracted from the ABS Tablebuilder system using the usual residence profile. For usual residence data, the ABS moves people back to where they live, rather than using the location the data were collected (place of enumeration). Usual residence data is preferred for individual level data because it removes the effect of respondents travelling or holidaying. All rates were calculated as a proportion of all Indigenous people in the area, excluding any Not Stated or Overseas Visitors. Therefore, summing the rates across all categories for an indicator will give a total of 100%. For more information please view the NATSEM Technical Report. Please note: AURIN has spatially enabled the original data provided directly from NATSEM. Where data values are NULL, the data is either unpublished or not applicable mathematically. Methodology between the 2016 NATSEM and 2011 OECD data release may have changed, please refer to the technical report for parity status and specific changes. Copyright attribution: University of Canberra - National Centre for Social and Economic Modelling, (2018): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 4.0 International (CC BY 4.0)

This dataset presents the dependency rate of the population in small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). The dependency rate is the number of people of working age (20-64) divided by the number of people of retirement age (65 and over). All indicators were extracted from the ABS Tablebuilder system using the usual residence profile. For usual residence data, the ABS moves people back to where they live, rather than using the location the data were collected (place of enumeration). Usual residence data is preferred for individual level data because it removes the effect of respondents travelling or holidaying. The treatment of Not Stated data is to exclude them from both the numerator and the denominator. For more information please view the NATSEM Technical Report. Please note: AURIN has spatially enabled the original data provided directly from NATSEM. Where data values are NULL, the data is either unpublished or not applicable mathematically. Methodology between the 2016 NATSEM and 2011 OECD data release may have changed, please refer to the technical report for parity status and specific changes.

Dataset contains the count of persons aged over 15 years by place of work based on their employment status and hours worked as recorded for the 2021 Census. Australian Bureau of Statistics extracts from ABS Tablebuilder are used for the construction of the dataset. This dataset should be utilised for labour force analysis only, not overall employment data by industry.

Dataset contains the count of persons aged over 15 years by place of work based on their employment status and hours worked as recorded for the 2021 Census. Australian Bureau of Statistics extracts from ABS Tablebuilder are used for the construction of the dataset. This dataset should be utilised for labour force analysis only, not overall employment data by industry.

Dataset contains the count of persons aged over 15 years by place of work based on their employment status and hours worked as recorded for the 2021 Census. Australian Bureau of Statistics extracts from ABS Tablebuilder are used for the construction of the dataset. This dataset should be utilised for labour force analysis only, not overall employment data by industry.