Regional population methodology

Estimated resident population (ERP) is the official estimate of the Australian population, which links people to a place of usual residence within Australia. Usual residence is the address at which a person considers themselves to currently live. ERP includes all people who usually live in Australia (regardless of nationality, citizenship or visa status), with the exception of people present for foreign military, consular or diplomatic reasons. 

ERP, or population estimates, for Australia and it's states and territories (from now on referred to as states) are prepared quarterly and released around six months after the reference date in National, state and territory population.

Annual population estimates as at 30 June are then prepared for areas below the state level and released in this product. Estimates are prepared at the Statistical Area Level 2 and Local Government Area levels, according to the Australian Statistical Geography Standard (ASGS), and are aggregated or split to create estimates for other geographies. Population estimates are available in this product for Statistical Areas Levels 2 to 4, Greater Capital City Statistical Areas, Local Government Areas, Significant Urban Areas, Remoteness Areas, and Commonwealth and State Electoral Divisions.

The 2021 Census of Population and Housing was conducted on 10 August 2021. Preliminary rebased estimates for 30 June 2017 to 2021, based on the 2021 Census, will be available in a special issue of this product planned for release in the second half of 2022. Age and sex breakdowns of these estimates will be released in Regional population by age and sex shortly after. Final Census-based estimates for June 2017 through to June 2021 are scheduled for release in 2023. Totals will be released in Regional population while age-sex breakdowns will be released in Regional population by age and sex.

Statistics in this release are impacted by the COVID-19 pandemic and the resulting Australian Government closure of the international border from 20 March 2020. 

Prior to 2016, the absence of reliable migration data below the state level meant that sub-state populations were estimated using a regression model, which modelled changes in population against indicator data between the two most recent Censuses. These indicator data sources included dwelling approvals, and Medicare and electoral roll counts. Changes in these indicators were used to estimate changes in the population of each area since the last Census.

In Census years, both preliminary estimates (derived from updating ERP from the previous Census) and 'rebased' population estimates (based on the current Census) are prepared. Differences between these two sets of estimates are referred to as intercensal differences. Rebased estimates of SA2 populations for previous intercensal years are derived by apportioning the intercensal difference across the five years, while constraining to state totals. Rebased 2012 to 2015 estimates were generally derived by adding one-fifth of the 2016 intercensal difference to the previous estimate of the 2012 population, two-fifths to the previous estimate of the 2013 population, and so on. Intercensal difference was apportioned based on the unrebased growth rate for some areas (e.g. newly established areas).

The sub-state estimates in this product are subject to some error. Some caution should be exercised when using the estimates, especially for areas with very small populations.

An indication of the accuracy of ERP can be gauged by assessing the size and direction of intercensal differences. For Australia as at 30 June 2016, the preliminary (unrebased) ERP under-estimated the final rebased ERP by 0.1% (24,900 people). For the states and territories, the 2016 intercensal differences ranged from -1.4% (Victoria) to +2.0% (Northern Territory).

To assess the quality of SA2-based estimates prepared using the component method, experimental estimates updated from 2011 Census-based estimates were prepared using the component method, and compared with rebased 2016 estimates. The average of the absolute values of the intercensal differences for these SA2 component-based estimates (excluding areas with less than 1,000 people) was 3.4%. This was slightly lower than the average of the absolute values of intercensal differences for regression-based estimates over the same period (3.5%), which was the method used to create the published preliminary 2016 estimates.

The table below shows that the intercensal differences for the 2016 experimental component-based estimates generally decreased with increasing population size; that is, SA2s with large populations recorded the smallest percentage differences while small SA2s had the largest percentage differences.

To meet the competing demands for accuracy and timeliness, there are several versions of sub-state population estimates. Preliminary estimates are available around nine months after the reference date with revised estimates 12 months later. Rebased and final estimates are made available after each Census, when revisions are made to the estimates for all years in the previous intercensal period.

The status of annual sub-state ERP and components changes over time, from preliminary to revised to final, as new component data becomes available at the state level. With each release, ERP for the previous year is revised due to revisions to the component data at the state level. No updated sub-state data is used for these revisions. The table below shows the current status of sub-state ERP and the components of population change at the state level (for those years where the component method was used to prepare sub-state ERP).

Natural increase (births minus deaths) for sub-state areas is calculated using information provided by each state/territory registry of births, deaths and marriages. The data is coded based on the place of usual residence of the mother for births, and the place of usual residence of the deceased for deaths. It is aggregated to SA2 and LGA levels and constrained to published state estimates of births and deaths.

The estimates of births and deaths in this product are prepared for financial years to correspond with the 30 June reference date for sub-state ERP. To produce timely sub-state estimates, preliminary births and deaths data are prepared using year of registration as a proxy for year of occurrence.

Preliminary births and deaths are prepared by breaking down preliminary state-level data. Later, when the state-level data is updated, the sub-state data is updated accordingly and released in the next issue of this product. 

The sub-state births and deaths data in this product is not coherent with the sub-state data released in Births, Australia and Deaths, Australia which is for calendar years and has a different scope.

The movement of people from overseas to Australia's sub-state areas and vice-versa cannot be directly measured and is estimated by breaking down overseas migrant arrivals and departures at the state level to sub-state areas, using information from the most recent Census. The state-level overseas migration data is sourced from Department of Home Affairs processing systems, visa information, and incoming passenger cards, and is published in National, state and territory population.

Regional overseas migration estimate (ROME) arrivals are estimated based on counts of people who identified in the Census that they were living overseas one year ago, at SA2 level. This distribution is used to break down state arrivals each year up until the next Census. To account for changes to the distribution of overseas arrivals within a state between Censuses (e.g. in high growth areas or inner-city areas with changing numbers of temporary migrants), adjustments may be made based on up-to-date indicator data including counts of Temporary Skills Shortage visa holders and overseas students. 

For ROME departures, a model distributes state-level overseas migrant departures to SA2s. This model is based on a range of information from the Census - mainly the number of people who arrived in each area from overseas in the last year. More weighting is given to areas that have high SEIFA Index of Education and Occupation scores and more than 20% of their total population born overseas. Of all the models evaluated, this model was selected as it best estimated population change between the last two Censuses. As with overseas arrivals, overseas departures may be adjusted based on additional information sources.

LGA estimates of ROME arrivals and departures are prepared by converting from SA2-level ROME arrivals and departures, using a population-weighted correspondence.

Preliminary ROME arrivals and departures are prepared by breaking down preliminary state-level data. Later, when the state-level data is updated, the sub-state data is updated accordingly and released in the next issue of this product.

The movement of people between and within Australia's states and territories cannot be directly measured and is estimated using administrative data. Internal migration is estimated based on a combination of Census data (usual address one year ago), Medicare change of address data (provided by Services Australia), and Department of Defence records (for military personnel only). 

Medicare is Australia's universal health insurance scheme and covers the vast majority of Australian residents. De-identified Medicare change of address counts are aggregated to SA2 and LGA levels. There are some people who are part of ERP but are not covered by Medicare, such as certain temporary visa holders. For others there is a time delay from when they move residence to when they update their address details with Medicare. To account for these issues, factors are applied to calibrate this data to internal migration data from the Census. These factors are applied by age, sex, state and move type (arrival or departure). Medicare data received for the year ending 30 September is used to estimate internal migration for the year ending 30 June. This assumes that on average the time between a person moving house and registering their change of address with Medicare is three months. 

As many defence force personnel do not interact with Medicare, defence movements data is used to supplement the Medicare data. Aggregated defence force personnel movements are converted from postcode to SA2 and LGA levels. This data reflects the time of move, and is therefore not lagged.

The Medicare and defence data are combined to prepare regional internal migration estimates (RIME) at SA2 and LGA levels. Interstate RIME moves are constrained to estimates of interstate migration as published in National, state and territory population.

RIME was previously prepared and released in Migration, Australia for financial years up to 2015-16. This old series of RIME was experimental in that it was prepared independently of and is not directly comparable with ERP nor with RIME prepared for 2016-17 onwards, due to different methods and source data used. The old RIME series used Medicare change of address data aggregated to postcodes, which was converted to SA2/LGA, and was supplied to the ABS quarterly meaning that one person could record up to four moves in a financial year. RIME for 2016-17 onwards uses change of address data coded directly to ASGS areas, and is supplied and calculated on an annual basis consistent with the definition of population change over a financial year.

June 2021: Medicare change of address data showed an implausibly high number of moves for 2020-21 due to widespread updating of Medicare records as people got vaccinated for COVID-19. To treat for this, under-count adjustments applied in previous years have been revised for 2020-21.

The Australian Statistical Geography Standard (ASGS) brings together in one framework all of the regions which the ABS and many other organisations use to collect, release and analyse geographically classified statistics. The ASGS classification structures are split into two broad groups, ABS Structures and Non-ABS Structures.

The ABS Structures are defined and maintained by the ABS, and remain unchanged for the five years between Censuses. Further information on the ABS Structures for which population estimates are available in this product is contained in:

• Australian Statistical Geography Standard: Volume 1 - Main Structure and Greater Capital City Statistical Areas, July 2016 for Statistical Areas Level 2 to 4 and Greater Capital City Statistical Areas
• Australian Statistical Geography Standard: Volume 4 - Significant Urban Areas, Urban Centres and Localities, Sections of State, July 2016 for Significant Urban Areas 
• Australian Statistical Geography Standard: Volume 5 - Remoteness Structure, July 2016 for Remoteness Areas 

The Non-ABS Structures are not defined or maintained by the ABS, and generally represent administrative regions. As the Non-ABS Structures represent regions that are subject to ongoing change, the ABS releases updates to these Structures each year where significant change has occurred. Further information on the Non-ABS Structures for which population estimates are available in this product is contained in:

• Australian Statistical Geography Standard: Volume 3 - Non ABS Structures, July 2018 for Commonwealth Electoral Divisions
• Australian Statistical Geography Standard: Volume 3 - Non ABS Structures, June 2020 for State Electoral Divisions
• Australian Statistical Geography Standard (ASGS) Edition 3 - Non ABS Structures, June 2021 for Local Government Areas and Commonwealth Electoral Divisions

Maps of the statistical areas defined in the ASGS are available in the online mapping tool ABS Maps.

The area figures used in this product were calculated using ABS standard Geographic Information System software from the digital boundaries of the ASGS. 

When boundaries for Non-ABS Structures such as Local Government Areas (LGAs) change, historical population estimates for these new boundaries are prepared to enable the comparison of regional populations over time. The table below shows changes to LGA boundaries involving population that occurred between the 2020 and 2021 editions of the ASGS.

The centre of population of a region is a point that describes a centre point of the region's population, and is calculated in this product based on SA1s. Due to the inherent imprecision in small area estimates, the centre of population should be considered indicative and not ascribed to an exact location. The use of different geographical level data in the calculation of the centre of population can result in different locations.

The population density of each region in this product has been calculated by dividing its ERP by its area in square kilometres. The result is expressed as a number of people per square kilometre.

In this product, ERP is also presented in one square kilometre grid format. The population grid offers a consistently sized spatial unit and gives a refined model of population distribution, particularly for the non-urban areas of Australia. It is also an established, easy to understand and readily comparable international standard which enables users to make local, national and international comparisons of population density.

The population grid is prepared using SA1 population estimates. Within each populated SA1, all known residential dwelling locations were identified using sources such as the Geocoded National Address File and the population distributed equally across the residential dwellings. The average value assigned to each dwelling was then summed within each one square kilometre grid cell across the country.

The population grid is provided in ESRI Grid format and Geo TIFF format, which are recommended for users proficient in the use of Geographic Information System software.

The ABS collects statistical information under the authority of the Census and Statistics Act, 1905. This requires that statistical output shall not be published or disseminated in a manner that is likely to enable the identification of a particular person or organisation.

To guard against identification or disclosure of confidential information, a procedure is applied to confidentialise sub-state ERP and components, which are also subsequently constrained so that they add to relevant state estimates. As a result of this confidentialisation method, and forced additivity, estimates of under three people should be regarded as synthetic and only exist to ensure additivity to higher levels.

ABS statistics draw extensively on information provided freely by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated: without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.