This dataset presents the unemployment 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 of people unemployed, and the unemployment rate is the number of people unemployed divided by the number of people in the labour force. 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 Where data values are NULL, the data is either unpublished or not applicable mathematically.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 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. 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 synthetically modeled indicators 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 synthetic indicators produced by the spatial micro-simulation model (SpatialMSM) are: median income, equivalised disposable median income, Gini coefficient and housing stress. The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). NATSEM's spatial micro-simulation model uses a technique that takes a survey and re-weights it to small area Census data. SpatialMSM18F is the application of the NATSEM Spatial Micro-simulation model using the ABS Survey of Income and Housing 2015/2016 and the 2016 Census of Population and Housing at the SA2 level (Tanton et al. 2011). All the indicators from the SpatialMSM model are synthetic, so there is some model error as well as other error from the survey. Therefore, they are not as accurate as the Census data used. 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.

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.

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. 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 synthetically modeled indicators relating to the financials of the population of small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The synthetic indicators are produced by the spatial micro-simulation model (SpatialMSM). The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). NATSEM’s spatial microsimulation model uses a technique that takes a survey and reweights it to small area Census data. SpatialMSM18 is the application of the NATSEM Spatial Microsimulation model using the Household, Income and Labour Dynamics in Australia (HILDA) dataset, the ABS Housing Expenditure Survey (for financial stress) and the 2016 Census of Population and Housing at the SA2 level (Tanton et al. 2011). All the indicators from the SpatialMSM model are synthetic, so there is some model error as well as other error from the survey. Therefore, they are not as accurate as the Census data used. Data in this dataset comes from NATSEM's spatial microsimulation model. Estimates are for financial stress, trust and life satisfaction. A description of the model, and validation, can be found in the accompanying 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 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 data is SA2 based SEIFA data on The Index of Economic Resources, 2016. Data is based upon 2016 ASGS boundaries. Socio-Economic Indexes for Areas (SEIFA) is an ABS product that ranks areas in Australia according to relative socio-economic advantage and disadvantage. The indexes are based on information from the five-yearly Census of Population and Housing. SEIFA 2016 has been created from Census 2016 data and consists of four indexes: The Index of Relative Socio-economic Disadvantage (IRSD); The Index of Relative Socio-economic Advantage and Disadvantage (IRSAD); The Index of Education and Occupation (IEO); The Index of Economic Resources (IER). Each index is a summary of a different subset of Census variables and focuses on a different aspect of socio-economic advantage and disadvantage. This data is ABS data (catalogue number: 2033.0.55.001) used with permission from the Australian Bureau of Statistics. For more information on this data please visit the Australian Bureau of Statistics.

This data is SA2 based SEIFA data on The Index of Relative Socio-economic Disadvantage, 2016. Data is based upon 2016 ASGS boundaries. Socio-Economic Indexes for Areas (SEIFA) is an ABS product that ranks areas in Australia according to relative socio-economic advantage and disadvantage. The indexes are based on information from the five-yearly Census of Population and Housing. SEIFA 2016 has been created from Census 2016 data and consists of four indexes: The Index of Relative Socio-economic Disadvantage (IRSD); The Index of Relative Socio-economic Advantage and Disadvantage (IRSAD); The Index of Education and Occupation (IEO); The Index of Economic Resources (IER). Each index is a summary of a different subset of Census variables and focuses on a different aspect of socio-economic advantage and disadvantage. This data is ABS data (catalogue number: 2033.0.55.001) used with permission from the Australian Bureau of Statistics. For more information on this data please visit the Australian Bureau of Statistics.