Projected Deaths by Single Year of Age, Sex, Race, and Hispanic Origin for the United States: 2016-2060 // Source: U.S. Census Bureau, Population Division // There are four projection scenarios: 1. Main series, 2. High Immigration series, 3. Low Immigration series, and 4. Zero Immigration series. // Note: Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. // For detailed information about the methods used to create the population projections, see https://www2.census.gov/programs-surveys/popproj/technical-documentation/methodology/methodstatement17.pdf. // Population projections are estimates of the population for future dates. They are typically based on an estimated population consistent with the most recent decennial census and are produced using the cohort-component method. Projections illustrate possible courses of population change based on assumptions about future births, deaths, net international migration, and domestic migration. The Population Estimates and Projections Program provides additional information on its website: https://www.census.gov/programs-surveys/popproj.html.

Projected Population by Age Group, Sex, Race, and Hispanic Origin for the United States: 2016-2060 // Source: U.S. Census Bureau, Population Division // There are four projection scenarios: 1. Main series, 2. High Immigration series, 3. Low Immigration series, and 4. Zero Immigration series. // Note: 'In combination' means in combination with one or more other races. The sum of the five race-in-combination groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. // The projections generally do not precisely agree with population estimates available elsewhere on the Census Bureau website for methodological reasons. Where both estimates and projections are available for a given time reference, it is recommended that you use the population estimates as the measure of the current population. // For detailed information about the methods used to create the population projections, see https://www2.census.gov/programs-surveys/popproj/technical-documentation/methodology/methodstatement17.pdf. // Population projections are estimates of the population for future dates. They are typically based on an estimated population consistent with the most recent decennial census and are produced using the cohort-component method. Projections illustrate possible courses of population change based on assumptions about future births, deaths, net international migration, and domestic migration. The Population Estimates and Projections Program provides additional information on its website: https://www.census.gov/programs-surveys/popproj.html.

Every four years, the Wasatch Front’s two metropolitan planning organizations (MPOs), Wasatch Front Regional Council (WFRC) and Mountainland Association of Governments (MAG), collaborate to update a set of annual small area -- traffic analysis zone and ‘city area’, see descriptions below) -- population and employment projections for the Salt Lake City-West Valley City (WFRC), Ogden-Layton (WFRC), and Provo-Orem (MAG) urbanized areas.

These projections are primarily developed for the purpose of informing long-range transportation infrastructure and services planning done as part of the 4 year Regional Transportation Plan update cycle, as well as Utah’s Unified Transportation Plan, 2023-2050. Accordingly, the foundation for these projections is largely data describing existing conditions for a 2019 base year, the first year of the latest RTP process. The projections are included in the official travel models, which are publicly released at the conclusion of the RTP process.

Projections within the Wasatch Front urban area ( SUBAREAID = 1) were produced with using the Real Estate Market Model as described below. Socioeconomic forecasts produced for Cache MPO (Cache County, SUBAREAID = 2), Dixie MPO (Washington County, SUBAREAID = 3), Summit County (SUBAREAID = 4), and UDOT (other areas of the state, SUBAREAID = 0) all adhere to the University of Utah Gardner Policy Institute's county-level projection controls, but other modeling methods are used to arrive at the TAZ-level forecasts for these areas.

As these projections may be a valuable input to other analyses, this dataset is made available here as a public service for informational purposes only. It is solely the responsibility of the end user to determine the appropriate use of this dataset for other purposes.

Wasatch Front Real Estate Market Model (REMM) Projections

WFRC and MAG have developed a spatial statistical model using the UrbanSim modeling platform to assist in producing these annual projections. This model is called the Real Estate Market Model, or REMM for short. REMM is used for the urban portion of Weber, Davis, Salt Lake, and Utah counties. REMM relies on extensive inputs to simulate future development activity across the greater urbanized region. Key inputs to REMM include:

Demographic data from the decennial census
County-level population and employment projections -- used as REMM control totals -- are produced by the University of Utah’s Kem C. Gardner Policy Institute (GPI) funded by the Utah State Legislature
Current employment locational patterns derived from the Utah Department of Workforce Services
Land use visioning exercises and feedback, especially in regard to planned urban and local center development, with city and county elected officials and staff
Current land use and valuation GIS-based parcel data stewarded by County Assessors
Traffic patterns and transit service from the regional Travel Demand Model that together form the landscape of regional accessibility to workplaces and other destinations
Calibration of model variables to balance the fit of current conditions and dynamics at the county and regional level

‘Traffic Analysis Zone’ Projections

The annual projections are forecasted for each of the Wasatch Front’s 3,546 Traffic Analysis Zone (TAZ) geographic units. TAZ boundaries are set along roads, streams, and other physical features and average about 600 acres (0.94 square miles). TAZ sizes vary, with some TAZs in the densest areas representing only a single city block (25 acres).

‘City Area’ Projections

The TAZ-level output from the model is also available for ‘city areas’ that sum the projections for the TAZ geographies that roughly align with each city’s current boundary. As TAZs do not align perfectly with current city boundaries, the ‘city area’ summaries are not projections specific to a current or future city boundary, but the ‘city area’ summaries may be suitable surrogates or starting points upon which to base city-specific projections.

Summary Variables in the Datasets

Annual projection counts are available for the following variables (please read Key Exclusions note below):

Demographics

Household Population Count (excludes persons living in group quarters) 
Household Count (excludes group quarters) 

Employment

Typical Job Count (includes job types that exhibit typical commuting and other travel/vehicle use patterns)
Retail Job Count (retail, food service, hotels, etc)
Office Job Count (office, health care, government, education, etc)
Industrial Job Count (manufacturing, wholesale, transport, etc)
Non-Typical Job Count* (includes agriculture, construction, mining, and home-based jobs) This can be calculated by subtracting Typical Job Count from All Employment Count 
All Employment Count* (all jobs, this sums jobs from typical and non-typical sectors).

• These variables includes REMM’s attempt to estimate construction jobs in areas that experience new and re-development activity. Areas may see short-term fluctuations in Non-Typical and All Employment counts due to the temporary location of construction jobs.

Key Exclusions from TAZ and ‘City Area’ Projections

As the primary purpose for the development of these population and employment projections is to model future travel in the region, REMM-based projections do not include population or households that reside in group quarters (prisons, senior centers, dormitories, etc), as residents of these facilities typically have a very low impact on regional travel. USTM-based projections also excludes group quarter populations. Group quarters population estimates are available at the county-level from GPI and at various sub-county geographies from the Census Bureau.

Statewide Projections

Population and employment projections for the Wasatch Front area can be combined with those developed by Dixie MPO (St. George area), Cache MPO (Logan area), and the Utah Department of Transportation (for the remainder of the state) into one database for use in the Utah Statewide Travel Model (USTM). While projections for the areas outside of the Wasatch Front use different forecasting methods, they contain the same summary-level population and employment projections making similar TAZ and ‘City Area’ data available statewide. WFRC plans, in the near future, to add additional areas to these projections datasets by including the projections from the USTM model.

Abstract (en): This dataset provides annual population projections for the 50 states and the District of Columbia by age, sex, and race for the years 1986 through 2010. The projections were made using a mathematical projection model called the cohort-component method. This method allows separate assumptions to be made for each of the components of population change: births, deaths, internal migration, and international migration. The projections are consistent with the July 1, 1986 population estimates for states. In general, the projections assume a slight increase in the national levels of fertility, an increasing level of life expectancy, and a decreasing level of net international migration. Internal migration assumptions are based on the annual state-to-state migration data for the years 1975-1986. The resident population of the 50 states and the District of Columbia. Data are included for the years 1986 and 1987 as well as 1988-2010. Figures for 1986 are estimates, while those for 1987 and succeeding years are projections.

Long term population projections by sex and single year of age for York Local Authority area. These unrounded estimates are published based on ONS estimates designed to enable and encourage further calculations and analysis. However, the estimates should not be taken to be accurate to the level of detail provided. More information on the accuracy of the estimates is available in the Quality and Methodology document The estimates are produced using a variety of data sources and statistical models, including some statistical disclosure control methods, and small estimates should not be taken to refer to particular individuals. The estimated resident population of an area includes all those people who usually live there, regardless of nationality. Arriving international migrants are included in the usually resident population if they remain in the UK for at least a year. Emigrants are excluded if they remain outside the UK for at least a year. This is consistent with the United Nations definition of a long-term migrant. Armed forces stationed outside of the UK are excluded. Students are taken to be usually resident at their term time address. The population estimates reflect boundaries in place as of the reference year. Please note that “age” 999 comprises data for ages 90 and above. Source and Licence: Adapted from data from the Office for National Statistics licensed under the Open Government Licence v.1.0.

Introduction This report presents projections of population from 2015 to 2025 by age and sex for Illinois, Chicago and Illinois counties produced for the Certificate of Need (CON) Program. As actual future population trends are unknown, the projected numbers should not be considered a precise prediction of the future population; rather, these projections, calculated under a specific set of assumptions, indicate the levels of population that would result if our assumptions about each population component (births, deaths and net migration) hold true. The assumptions used in this report, and the details presented below, generally assume a continuation of current trends. Methodology These projections were produced using a demographic cohort-component projection model. In this model, each component of population change – birth, death and net migration – is projected separately for each five-year birth cohort and sex. The cohort – component method employs the following basic demographic balancing equation: P1 = P0 + B – D + NM Where: P1 = Population at the end of the period; P0 = Population at the beginning of the period; B = Resident births during the period; D = Resident deaths during the period; and NM = Net migration (Inmigration – Outmigration) during the period. The model roughly works as follows: for every five-year projection period, the base population, disaggregated by five-year age groups and sex, is “survived” to the next five-year period by applying the appropriate survival rates for each age and sex group; next, net migrants by age and sex are added to the survived population. The population under 5 years of age is generated by applying age specific birth rates to the survived females in childbearing age (15 to 49 years). Base Population These projections began with the July 1, 2010 population estimates by age and sex produced by the U.S. Census Bureau. The most recent census population of April 1, 2010 was the base for July 1, 2010 population estimates. Special Populations In 19 counties, the college dormitory population or adult inmates in correctional facilities accounted for 5 percent or more of the total population of the county; these counties were considered as special counties. There were six college dorm counties (Champaign, Coles, DeKalb, Jackson, McDonough and McLean) and 13 correctional facilities counties (Bond, Brown, Crawford, Fayette, Fulton, Jefferson, Johnson, Lawrence, Lee, Logan, Montgomery, Perry and Randolph) that qualified as special counties. When projecting the population, these special populations were first subtracted from the base populations for each special county; then they were added back to the projected population to produce the total population projections by age and sex. The base special population by age and sex from the 2010 population census was used for this purpose with the assumption that this population will remain the same throughout each projection period. Mortality Future deaths were projected by applying age and sex specific survival rates to each age and sex specific base population. The assumptions on survival rates were developed on the basis of trends of mortality rates in the individual life tables constructed for each level of geography for 1989-1991, 1999-2001 and 2009-2011. The application of five-year survival rates provides a projection of the number of persons from the initial population expected to be alive in five years. Resident deaths data by age and sex from 1989 to 2011 were provided by the Illinois Center for Health Statistics (ICHS), Illinois Department of Public Health. Fertility Total fertility rates (TFRs) were first computed for each county. For most counties, the projected 2015 TFRs were computed as the average of the 2000 and 2010 TFRs. 2010 or 2015 rates were retained for 2020 projections, depending on the birth trend of each county. The age-specific birth rates (ASBR) were next computed for each county by multiplying the 2010 ASBR by each projected TFR. Total births were then projected for each county by applying age-specific birth rates to the projected female population of reproductive ages (15 to 49 years). The total births were broken down by sex, using an assumed sex-ratio at birth. These births were survived five years applying assumed survival ratios to get the projected population for the age group 0-4. For the special counties, special populations by age and sex were taken out before computing age-specific birth rates. The resident birth data used to compute age-specific birth rates for 1989-1991, 1999-2001 and 2009-2011 came from ICHS. Births to females younger than 15 years of age were added to those of the 15-19 age group and births to women older than 49 years of age were added to the 45-49 age group. Net Migration Migration is the major component of population change in Illinois, Chicago and Illinois counties. The state is experiencing a significant loss of population through internal (domestic migration within the U.S.) net migration. Unlike data on births and deaths, migration data based on administrative records are not available on a regular basis. Most data on migration are collected through surveys or indirectly from administrative records (IRS individual tax returns). For this report, net migration trends have been reviewed using data from different sources and methods (such as residual method) from the University of Wisconsin, Madison, Illinois Department of Public Health, individual exemptions data from the Internal Revenue Service, and survey data from the U.S. Census Bureau. On the basis of knowledge gained through this review and of levels of net migration from different sources, assumptions have been made that Illinois will have annual net migrants of -40, 000, -35,000 and -30,000 during 2010-2015, 2015-2020 and 2020-2025, respectively. These figures have been distributed among the counties, using age and sex distribution of net migrants during 1995-2000. The 2000 population census was the last decennial census, which included the question “Where did you live five years ago?” The age and sex distribution of the net migrants was derived, using answers to this question. The net migration for Chicago has been derived independently, using census survival method for 1990-2000 and 2000-2010 under the assumption that the annual net migration for Chicago will be -40,000, -30,000 and -25,000 for 2010-2015, 2015-2020 and 2020-2025, respectively. The age and sex distribution from the 2000-2010 net migration was used to distribute the net migrants for the projection periods. Conclusion These projections were prepared for use by the Certificate of Need (CON) Program; they are produced using evidence-based techniques, reasonable assumptions and the best available input data. However, as assumptions of future demographic trends may contain errors, the resulting projections are unlikely to be free of errors. In general, projections of small areas are less reliable than those for larger areas, and the farther in the future projections are made, the less reliable they may become. When possible, these projections should be regularly reviewed and updated, using more recent birth, death and migration data.

Sub-provincial population estimates and projections by age and gender for a variety of region types. Customizable breakdowns for counts and additional statistics are available via BC Stats' Population App. Estimates: A population estimate is a measure of the current or historical population. BC Stats annually releases total population estimates for sub-provincial region types. These estimates are consistent in aggregate with the July 1st provincial level estimates produced by Statistics Canada. More information can be found on BC Stats' Population Estimates page. Projections: A population projection is a forecast of future population growth. BC Stats applies the Component/Cohort-Survival method to project the population. This method "grows" the population from the latest base year estimate by forecasting births, deaths and migration by age. These forecasts are based on past trends modified to account for possible future changes and, consequently, should be viewed as only one possible scenario of future population. Projections are also released annually and are as of July 1st. The methodological document, P.E.O.P.L.E. Sub-provincial Population Projections: Methodology and Assumptions, is provided only for reference. More information can be found on BC Stats' Population Projections page. Wondering about the location of a particular region or its boundaries? Check out the Administrative Boundaries page for more information.

Projected Population by Single Year of Age, Sex, Race, and Hispanic Origin for the United States: 2012 to 2060 File: 2012 National Population Projections Source: U.S. Census Bureau, Population Division Release Date: December 2012 NOTE: Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. The projections generally do not precisely agree with population estimates available elsewhere on the Census Bureau website for methodological reasons. Where both estimates and projections are available for a given time reference, we recommend that you use the population estimates as the measure of the current population. For detailed information about the methods used to create the population projections, see http://www.census.gov/population/projections/methodology/. *** The U.S. Census Bureau periodically produces projections of the United States resident population by age, sex, race, and Hispanic origin. Population projections are estimates of the population for future dates. They are typically based on an estimated population consistent with the most recent decennial census and are produced using the cohort-component method. Projections illustrate possible courses of population change based on assumptions about future births, deaths, net international migration, and domestic migration. In some cases, several series of projections are produced based on alternative assumptions for future fertility, life expectancy, net international migration, and (for state-level projections) state-to-state or domestic migration. Additional information is available on the Population Projections website: http://www.census.gov/population/projections/.

Projected Population by Age Groups, Sex, Race, and Hispanic Origin for the United States: 2014-2060 // Source: U.S. Census Bureau, Population Division // Note: 'In combination' means in combination with one or more other races. The sum of the five race-in-combination groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. // The projections generally do not precisely agree with population estimates available elsewhere on the Census Bureau website for methodological reasons. Where both estimates and projections are available for a given time reference, it is recommended that you use the population estimates as the measure of the current population. // For detailed information about the methods used to create the population projections, see https://www.census.gov/population/projections/methodology. // The population projections for the United States are produced by the Census Bureau's Population Estimates and Projections Program. Population projections are estimates of the population for future dates. They are typically based on an estimated population consistent with the most recent decennial census and are produced using the cohort-component method. Projections illustrate possible courses of population change based on assumptions about future births, deaths, net international migration, and domestic migration. The Population Estimates and Projections Program provides additional information on its website: https://www.census.gov/population/projections.

The Global 1-km Downscaled Population Base Year and Projection Grids Based on the Shared Socioeconomic Pathways, Revision 01, data set consists of global urban, rural, and total populaton for the base year 2000, and population projections at ten-year intervals for 2010-2100 at a resolution of 1-km (about 30 arc-seconds), consistent both quantitatively and qualitatively with the SSPs. This 1-km data set is a downscaled version of the one-eighth degree (7.5 arc-minutes) data published in Jones and O'Neill (2016). The downscaling methods were published in Gao (2017). Spatial demographic data are key inputs for the analysis of land use, energy use, and emissions, as well as for the assessment of climate change vulnerability, impacts, and adaptation. The SSPs are developed to support future climate and global change research and the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).

These population projections were prepared by the Australian Bureau of Statistics (ABS) for Geoscience Australia. The projections are not official ABS data and are owned by Geoscience Australia. These projections are for Statistical Areas Level 2 (SA2s) and Local Government Areas (LGAs), and are projected out from a base population as at 30 June 2022, by age and sex. Projections are for 30 June 2023 to 2032, with results disaggregated by age and sex.

Method The cohort-component method was used for these projections. In this method, the base population is projected forward annually by calculating the effect of births, deaths and migration (the components) within each age-sex cohort according to the specified fertility, mortality and overseas and internal migration assumptions. The projected usual resident population by single year of age and sex was produced in four successive stages – national, state/territory, capital city/rest of state, and finally SA2s. Assumptions were made for each level and the resulting projected components and population are constrained to the geographic level above for each year.
These projections were derived from a combination of assumptions published in Population Projections, Australia, 2022 (base) to 2071 on 23 November 2023, and historical patterns observed within each state/territory.

Projections – capital city/rest of state regions The base population is 30 June 2022 Estimated Resident Population (ERP) as published in National, state and territory population, June 2022. For fertility, the total fertility rate (at the national level) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, of 1.6 babies per woman being phased in from 2022 levels over five years to 2027, before remaining steady for the remainder of the projection span. Observed state/territory, and greater capital city level fertility differentials were applied to the national data so that established trends in the state and capital city/rest of state relativities were preserved. Mortality rates are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that mortality rates will continue to decline across Australia with state/territory differentials persisting. State/territory and capital city/rest of state differentials were used to ensure projected deaths are consistent with the historical trend. Annual net overseas migration (NOM) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, with an assumed gain (at the national level) of 400,000 in 2022-23, increasing to 315,000 in 2023-24, then declining to 225,000 in 2026-27, after which NOM is assumed to remain constant. State and capital city/rest of state shares are based on a weighted average of NOM data from 2010 to 2019 at the state and territory level to account for the impact of COVID-19. For internal migration, net gains and losses from states and territories and capital city/rest of state regions are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that net interstate migration will trend towards long-term historic average flows.

Projections – Statistical Areas Level 2 The base population for each SA2 is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. The SA2-level fertility and mortality assumptions were derived by combining the medium scenario state/territory assumptions from Population Projections, Australia, 2022 (base) to 2071, with recent fertility and mortality trends in each SA2 based on annual births (by sex) and deaths (by age and sex) published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. Assumed overseas and internal migration for each SA2 is based on SA2-specific annual overseas and internal arrivals and departures estimates published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. The internal migration data was strengthened with SA2-specific data from the 2021 Census, based on the usual residence one year before Census night question. Assumptions were applied by SA2, age and sex. Assumptions were adjusted for some SA2s, to provide more plausible future population levels, and age and sex distribution changes, including areas where populations may not age over time, for example due to significant resident student and defence force populations. Most assumption adjustments were made via the internal migration component. For some SA2s with zero or a very small population base, but where significant population growth is expected, replacement migration age/sex profiles were applied. All SA2-level components and projected projections are constrained to the medium series of capital city/rest of state data in Population Projections, Australia, 2022 (base) to 2071.

Projections – Local Government Areas The base population for each LGA is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. Projections for 30 June 2023 to 2032 were created by converting from the SA2-level population projections to LGAs by age and sex. This was done using an age-specific population correspondence, where the data for each year of the projection span were converted based on 2021 population shares across SA2s. The LGA and SA2 projections are congruous in aggregation as well as in isolation. Unlike the projections prepared at SA2 level, no LGA-specific projection assumptions were used.

Nature of projections and considerations for usage The nature of the projection method and inherent fluctuations in population dynamics mean that care should be taken when using and interpreting the projection results. The projections are not forecasts, but rather illustrate future changes which would occur if the stated assumptions were to apply over the projection period. These projections do not attempt to allow for non-demographic factors such as major government policy decisions, economic factors, catastrophes, wars and pandemics, which may affect future demographic behaviour. To illustrate a range of possible outcomes, alternative projection series for national, state/territory and capital city/rest of state areas, using different combinations of fertility, mortality, overseas and internal migration assumptions, are prepared. Alternative series are published in Population Projections, Australia, 2022 (base) to 2071. Only one series of SA2-level projections was prepared for this product. Population projections can take account of planning and other decisions by governments known at the time the projections were derived, including sub-state projections published by each state and territory government. The ABS generally does not have access to the policies or decisions of commonwealth, state and local governments and businesses that assist in accurately forecasting small area populations. Migration, especially internal migration, accounts for the majority of projected population change for most SA2s. Volatile and unpredictable small area migration trends, especially in the short-term, can have a significant effect on longer-term projection results. Care therefore should be taken with SA2s with small total populations and very small age-sex cells, especially at older ages. While these projections are calculated at the single year of age level, small numbers, and fluctuations across individual ages in the base population and projection assumptions limit the reliability of SA2-level projections at single year of age level. These fluctuations reduce and reliability improves when the projection results are aggregated to broader age groups such as the five-year age bands in this product. For areas with small elderly populations, results aggregated to 65 and over are more reliable than for the individual age groups above 65. With the exception of areas with high planned population growth, SA2s with a base total population of less than 500 have generally been held constant for the projection period in this product as their populations are too small to be reliably projected at all, however their (small) age/sex distributions may change slightly. These SA2s are listed in the appendix. The base (2022) SA2 population estimates and post-2022 projections by age and sex include small artificial cells, including 1s and 2s. These are the result of a confidentialisation process and forced additivity, to control SA2 and capital city/rest of state age/sex totals, being applied to their original values. SA2s and LGAs in this product are based on the Australian Statistical Geography Standard (ASGS) boundaries as at the 2021 Census (ASGS Edition 3). For further information, see Australian Statistical Geography Standard (ASGS) Edition 3.

Data and geography references

Source data publication: Population Projections, Australia, 2022 (base) to 2071 Geographic boundary information: Australian Statistical Geography Standard (ASGS) Edition 3 Further information: Population Projections, Australia methodology Source: Australian Bureau of Statistics (ABS)

Made possible by the Digital Atlas of Australia

The Digital Atlas of Australia is a key Australian Government initiative being led by Geoscience Australia, highlighted in the Data and Digital Government Strategy. It brings together trusted datasets from across government in an interactive, secure, and easy-to-use geospatial platform. The Australian Bureau of Statistics (ABS) is working in partnership with Geoscience Australia to establish a set of web services to make ABS data available in the Digital Atlas of Australia.

Contact the Australian Bureau of Statistics

Email geography@abs.gov.au if you have any questions or feedback about this

These population projections were prepared by the Australian Bureau of Statistics (ABS) for Geoscience Australia. The projections are not official ABS data and are owned by Geoscience Australia. These projections are for Statistical Areas Level 2 (SA2s) and Local Government Areas (LGAs), and are projected out from a base population as at 30 June 2022, by age and sex. Projections are for 30 June 2023 to 2032, with results disaggregated by age and sex.

Method The cohort-component method was used for these projections. In this method, the base population is projected forward annually by calculating the effect of births, deaths and migration (the components) within each age-sex cohort according to the specified fertility, mortality and overseas and internal migration assumptions. The projected usual resident population by single year of age and sex was produced in four successive stages – national, state/territory, capital city/rest of state, and finally SA2s. Assumptions were made for each level and the resulting projected components and population are constrained to the geographic level above for each year.
These projections were derived from a combination of assumptions published in Population Projections, Australia, 2022 (base) to 2071 on 23 November 2023, and historical patterns observed within each state/territory.

Projections – capital city/rest of state regions The base population is 30 June 2022 Estimated Resident Population (ERP) as published in National, state and territory population, June 2022. For fertility, the total fertility rate (at the national level) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, of 1.6 babies per woman being phased in from 2022 levels over five years to 2027, before remaining steady for the remainder of the projection span. Observed state/territory, and greater capital city level fertility differentials were applied to the national data so that established trends in the state and capital city/rest of state relativities were preserved. Mortality rates are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that mortality rates will continue to decline across Australia with state/territory differentials persisting. State/territory and capital city/rest of state differentials were used to ensure projected deaths are consistent with the historical trend. Annual net overseas migration (NOM) is based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, with an assumed gain (at the national level) of 400,000 in 2022-23, increasing to 315,000 in 2023-24, then declining to 225,000 in 2026-27, after which NOM is assumed to remain constant. State and capital city/rest of state shares are based on a weighted average of NOM data from 2010 to 2019 at the state and territory level to account for the impact of COVID-19. For internal migration, net gains and losses from states and territories and capital city/rest of state regions are based on the medium assumption used in Population Projections, Australia, 2022 (base) to 2071, and assume that net interstate migration will trend towards long-term historic average flows.

Projections – Statistical Areas Level 2 The base population for each SA2 is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. The SA2-level fertility and mortality assumptions were derived by combining the medium scenario state/territory assumptions from Population Projections, Australia, 2022 (base) to 2071, with recent fertility and mortality trends in each SA2 based on annual births (by sex) and deaths (by age and sex) published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. Assumed overseas and internal migration for each SA2 is based on SA2-specific annual overseas and internal arrivals and departures estimates published in Regional Population, 2021-22 and Regional Population by Age and Sex, 2022. The internal migration data was strengthened with SA2-specific data from the 2021 Census, based on the usual residence one year before Census night question. Assumptions were applied by SA2, age and sex. Assumptions were adjusted for some SA2s, to provide more plausible future population levels, and age and sex distribution changes, including areas where populations may not age over time, for example due to significant resident student and defence force populations. Most assumption adjustments were made via the internal migration component. For some SA2s with zero or a very small population base, but where significant population growth is expected, replacement migration age/sex profiles were applied. All SA2-level components and projected projections are constrained to the medium series of capital city/rest of state data in Population Projections, Australia, 2022 (base) to 2071.

Projections – Local Government Areas The base population for each LGA is the estimated resident population in each area by single year of age and sex, at 30 June 2022, as published in Regional population by age and sex, 2022 on 28 September 2023. Projections for 30 June 2023 to 2032 were created by converting from the SA2-level population projections to LGAs by age and sex. This was done using an age-specific population correspondence, where the data for each year of the projection span were converted based on 2021 population shares across SA2s. The LGA and SA2 projections are congruous in aggregation as well as in isolation. Unlike the projections prepared at SA2 level, no LGA-specific projection assumptions were used.

Nature of projections and considerations for usage The nature of the projection method and inherent fluctuations in population dynamics mean that care should be taken when using and interpreting the projection results. The projections are not forecasts, but rather illustrate future changes which would occur if the stated assumptions were to apply over the projection period. These projections do not attempt to allow for non-demographic factors such as major government policy decisions, economic factors, catastrophes, wars and pandemics, which may affect future demographic behaviour. To illustrate a range of possible outcomes, alternative projection series for national, state/territory and capital city/rest of state areas, using different combinations of fertility, mortality, overseas and internal migration assumptions, are prepared. Alternative series are published in Population Projections, Australia, 2022 (base) to 2071. Only one series of SA2-level projections was prepared for this product. Population projections can take account of planning and other decisions by governments known at the time the projections were derived, including sub-state projections published by each state and territory government. The ABS generally does not have access to the policies or decisions of commonwealth, state and local governments and businesses that assist in accurately forecasting small area populations. Migration, especially internal migration, accounts for the majority of projected population change for most SA2s. Volatile and unpredictable small area migration trends, especially in the short-term, can have a significant effect on longer-term projection results. Care therefore should be taken with SA2s with small total populations and very small age-sex cells, especially at older ages. While these projections are calculated at the single year of age level, small numbers, and fluctuations across individual ages in the base population and projection assumptions limit the reliability of SA2-level projections at single year of age level. These fluctuations reduce and reliability improves when the projection results are aggregated to broader age groups such as the five-year age bands in this product. For areas with small elderly populations, results aggregated to 65 and over are more reliable than for the individual age groups above 65. With the exception of areas with high planned population growth, SA2s with a base total population of less than 500 have generally been held constant for the projection period in this product as their populations are too small to be reliably projected at all, however their (small) age/sex distributions may change slightly. These SA2s are listed in the appendix. The base (2022) SA2 population estimates and post-2022 projections by age and sex include small artificial cells, including 1s and 2s. These are the result of a confidentialisation process and forced additivity, to control SA2 and capital city/rest of state age/sex totals, being applied to their original values. SA2s and LGAs in this product are based on the Australian Statistical Geography Standard (ASGS) boundaries as at the 2021 Census (ASGS Edition 3). For further information, see Australian Statistical Geography Standard (ASGS) Edition 3.

Made possible by the Digital Atlas of Australia The Digital Atlas of Australia is a key Australian Government initiative being led by Geoscience Australia, highlighted in the Data and Digital Government Strategy. It brings together trusted datasets from across government in an interactive, secure, and easy-to-use geospatial platform. The Australian Bureau of Statistics (ABS) is working in partnership with Geoscience Australia to establish a set of web services to make ABS data available in the Digital Atlas of Australia.

Contact the Australian Bureau of Statistics If you have questions or feedback about this web service, please email geography@abs.gov.au. To subscribe to updates about ABS web services and geospatial products, please complete this form. For information about how the ABS manages any personal information you provide view the ABS privacy policy.

Data and geography references Source data publication: Population Projections, Australia, 2022 (base)

Important Dataset Update 6/24/2020:Summit and Wasatch Counties updated.Important Dataset Update 6/12/2020:MAG area updated.Important Dataset Update 7/15/2019: This dataset now includes projections for all populated statewide traffic analysis zones (TAZs). Projections within the Wasatch Front urban area ( SUBAREAID = 1) were produced with using the Real Estate Market Model as described below. Socioeconomic forecasts produced for Cache MPO (Cache County, SUBAREAID = 2), Dixie MPO (Washington County, SUBAREAID = 3), Summit County (SUBAREAID = 4), and UDOT (other areas of the state, SUBAREAID = 0) all adhere to the University of Utah Gardner Policy Institute's county-level projection controls, but other modeling methods are used to arrive at the TAZ-level forecasts for these areas.As with any dataset that presents projections into the future, it is important to have a full understanding of the data before using it. Before using this data, you are strongly encouraged to read the metadata description below and direct any questions or feedback about this data to analytics@wfrc.org. Every four years, the Wasatch Front’s two metropolitan planning organizations (MPOs), Wasatch Front Regional Council (WFRC) and Mountainland Association of Governments (MAG), collaborate to update a set of annual small area -- traffic analysis zone and ‘city area’, see descriptions below) -- population and employment projections for the Salt Lake City-West Valley City (WFRC), Ogden-Layton (WFRC), and Provo-Orem (MAG) urbanized areas. These projections are primarily developed for the purpose of informing long-range transportation infrastructure and services planning done as part of the 4 year Regional Transportation Plan update cycle, as well as Utah’s Unified Transportation Plan, 2019-2050. Accordingly, the foundation for these projections is largely data describing existing conditions for a 2015 base year, the first year of the latest RTP process. The projections are included in the official travel models, which are publicly released at the conclusion of the RTP process. As these projections may be a valuable input to other analyses, this dataset is made available at http://data.wfrc.org/search?q=projections as a public service for informational purposes only. It is solely the responsibility of the end user to determine the appropriate use of this dataset for other purposes. Wasatch Front Real Estate Market Model (REMM) ProjectionsWFRC and MAG have developed a spatial statistical model using the UrbanSim modeling platform to assist in producing these annual projections. This model is called the Real Estate Market Model, or REMM for short. REMM is used for the urban portion of Weber, Davis, Salt Lake, and Utah counties. REMM relies on extensive inputs to simulate future development activity across the greater urbanized region. Key inputs to REMM include:Demographic data from the decennial census;County-level population and employment projections -- used as REMM control totals -- are produced by the University of Utah’s Kem C. Gardner Policy Institute (GPI) funded by the Utah State Legislature;Current employment locational patterns derived from the Utah Department of Workforce Services; Land use visioning exercises and feedback, especially in regard to planned urban and local center development, with city and county elected officials and staff;Current land use and valuation GIS-based parcel data stewarded by County Assessors;Traffic patterns and transit service from the regional Travel Demand Model that together form the landscape of regional accessibility to workplaces and other destinations; andCalibration of model variables to balance the fit of current conditions and dynamics at the county and regional level.‘Traffic Analysis Zone’ ProjectionsThe annual projections are forecasted for each of the Wasatch Front’s 2,800+ Traffic Analysis Zone (TAZ) geographic units. TAZ boundaries are set along roads, streams, and other physical features and average about 600 acres (0.94 square miles). TAZ sizes vary, with some TAZs in the densest areas representing only a single city block (25 acres). ‘City Area’ ProjectionsThe TAZ-level output from the model is also available for ‘city areas’ that sum the projections for the TAZ geographies that roughly align with each city’s current boundary. As TAZs do not align perfectly with current city boundaries, the ‘city area’ summaries are not projections specific to a current or future city boundary, but the ‘city area’ summaries may be suitable surrogates or starting points upon which to base city-specific projections.Summary Variables in the DatasetsAnnual projection counts are available for the following variables (please read Key Exclusions note below):DemographicsHousehold Population Count (excludes persons living in group quarters)Household Count (excludes group quarters)EmploymentTypical Job Count (includes job types that exhibit typical commuting and other travel/vehicle use patterns)Retail Job Count (retail, food service, hotels, etc)Office Job Count (office, health care, government, education, etc)Industrial Job Count (manufacturing, wholesale, transport, etc)Non-Typical Job Count* (includes agriculture, construction, mining, and home-based jobs) This can be calculated by subtracting Typical Job Count from All Employment Count.All Employment Count* (all jobs, this sums jobs from typical and non-typical sectors).* These variable includes REMM’s attempt to estimate construction jobs in areas that experience new and re-development activity. Areas may see short-term fluctuations in Non-Typical and All Employment counts due to the temporary location of construction jobs.Population and employment projections for the Wasatch Front area can be combined with those developed by Dixie MPO (St. George area), Cache MPO (Logan area), and the Utah Department of Transportation (for the remainder of the state) into one database for use in the Utah Statewide Travel Model (USTM). While projections for the areas outside of the Wasatch Front use different forecasting methods, they contain the same summary-level population and employment projections making similar TAZ and ‘City Area’ data available statewide. WFRC plans, in the near future, to add additional areas to these projections datasets by including the projections from the USTM model.Key Exclusions from TAZ and ‘City Area’ ProjectionsAs the primary purpose for the development of these population and employment projections is to model future travel in the region, REMM-based projections do not include population or households that reside in group quarters (prisons, senior centers, dormitories, etc), as residents of these facilities typically have a very low impact on regional travel. USTM-based projections also excludes group quarter populations. Group quarters population estimates are available at the county-level from GPI and at various sub-county geographies from the Census Bureau.

Transport for NSW provides projections of population and dwellings at the small area (Travel Zone or TZ) level for NSW. The latest version is Travel Zone Projections 2024 (TZP24), released in January 2025.

TZP24 replaces the previously published TZP22.

The projections are developed to support a strategic view of NSW and are aligned with the NSW Government Common Planning Assumptions.

The TZP24 Population & Dwellings Projections dataset covers the following variables:

• Estimated Resident Population

• Structural Private Dwellings (Regional NSW only)

• Population in Occupied Private Dwellings, by 5-year Age categories & by Sex

• Population in Non-Private Dwellings

The projections in this release, TZP24, are presented annually from 2021 to 2031 and 5-yearly from 2031 to 2066, and are in TZ21 geography.

Please note, TZP24 is based on best available data as at early 2024, and the projections incorporate results of the National Census conducted by the ABS in August 2021.

Key Data Inputs used in TZP24:

• 2024 NSW Population Projections – NSW Department of Planning, Housing & Infrastructure

• 2021 Census data - Australian Bureau of Statistics (including dwellings by occupancy, total dwellings by Mesh Block, household sizes, private dwellings by occupancy, population age and gender, persons by place of usual residence)

For a summary of the TZP24 projection method please refer to the TZP24 Factsheet.

For more detail on the projection process please refer to the TZP24 Technical Guide.

Additional land use information for workforce and employment as well as Travel Zone 2021 boundaries for NSW (TZ21) and concordance files are also available for download on the Open Data Hub.

Visualisations of the population projections are available on the Transport for NSW Website under Data and research/Reference Information.

Cautions

The TZP24 dataset represents one view of the future aligned with the NSW Government Common Planning Assumptions and population and employment projections.

The projections are not based on specific assumptions about future new transport infrastructure but do take into account known land-use developments underway or planned, and strategic plans.

• TZP24 is a strategic state-wide dataset and caution should be exercised when considering results at detailed breakdowns.

• The TZP24 outputs represent a point in time set of projections (as at early 2024).

• The projections are not government targets.

• Travel Zone (TZ) level outputs are projections only and should be used as a guide. As with all small area data, aggregating of travel zone projections to higher geographies leads to more robust results.

• As a general rule, TZ-level projections are illustrative of a possible future only.

• More specific advice about data reliability for the specific variables projected is provided in the “Read Me” page of the Excel format summary spreadsheets on the TfNSW Open Data Hub.

• Caution is advised when comparing TZP24 with the previous set of projections (TZP22) due to addition of new data sources for the most recent years, and adjustments to methodology.

Further cautions and notes can be found in the TZP24 Technical Guide

Important note:

The Department of Planning, Housing & Infrastructure (DPHI) published the 2024 NSW Population Projections in November 2024. As per DPHI’s published projections, the following variables are excluded from the published TZP24 Population and Dwellings Projections:

• Structural Private Dwellings for Travel Zones in 43 councils across Greater Sydney, Illawarra-Shoalhaven, Central Coast, Lower Hunter and Greater Newcastle

• Occupied Private Dwellings for Travel Zones in NSW.

Furthermore, in TZP24, the Structural Private Dwellings variable aligns with the 2024 Implied Dwelling projections while the Occupied Private Dwellings variable aligns with the 2024 Households projections at SA2 level prepared by DPHI.

The above variables are available upon request by contacting model.selection@transport.nsw.gov.au - Attention Place Forecasting.

Population figures over a 25-year period, by single year of age and sex for local authorities in England. 2022-based datasets are the latest projection.

Important Dataset Update 6/24/2020:Summit and Wasatch Counties updated.Important Dataset Update 6/12/2020:MAG area updated.Important Dataset Update 7/15/2019: This dataset now includes projections for all populated statewide traffic analysis zones (TAZs). Projections within the Wasatch Front urban area ( SUBAREAID = 1) were produced with using the Real Estate Market Model as described below. Socioeconomic forecasts produced for Cache MPO (Cache County, SUBAREAID = 2), Dixie MPO (Washington County, SUBAREAID = 3), Summit County (SUBAREAID = 4), and UDOT (other areas of the state, SUBAREAID = 0) all adhere to the University of Utah Gardner Policy Institute's county-level projection controls, but other modeling methods are used to arrive at the TAZ-level forecasts for these areas.As with any dataset that presents projections into the future, it is important to have a full understanding of the data before using it. Before using this data, you are strongly encouraged to read the metadata description below and direct any questions or feedback about this data to analytics@wfrc.org. Every four years, the Wasatch Front’s two metropolitan planning organizations (MPOs), Wasatch Front Regional Council (WFRC) and Mountainland Association of Governments (MAG), collaborate to update a set of annual small area -- traffic analysis zone and ‘city area’, see descriptions below) -- population and employment projections for the Salt Lake City-West Valley City (WFRC), Ogden-Layton (WFRC), and Provo-Orem (MAG) urbanized areas. These projections are primarily developed for the purpose of informing long-range transportation infrastructure and services planning done as part of the 4 year Regional Transportation Plan update cycle, as well as Utah’s Unified Transportation Plan, 2019-2050. Accordingly, the foundation for these projections is largely data describing existing conditions for a 2015 base year, the first year of the latest RTP process. The projections are included in the official travel models, which are publicly released at the conclusion of the RTP process. As these projections may be a valuable input to other analyses, this dataset is made available at http://data.wfrc.org/search?q=projections as a public service for informational purposes only. It is solely the responsibility of the end user to determine the appropriate use of this dataset for other purposes. Wasatch Front Real Estate Market Model (REMM) ProjectionsWFRC and MAG have developed a spatial statistical model using the UrbanSim modeling platform to assist in producing these annual projections. This model is called the Real Estate Market Model, or REMM for short. REMM is used for the urban portion of Weber, Davis, Salt Lake, and Utah counties. REMM relies on extensive inputs to simulate future development activity across the greater urbanized region. Key inputs to REMM include:Demographic data from the decennial census;County-level population and employment projections -- used as REMM control totals -- are produced by the University of Utah’s Kem C. Gardner Policy Institute (GPI) funded by the Utah State Legislature;Current employment locational patterns derived from the Utah Department of Workforce Services; Land use visioning exercises and feedback, especially in regard to planned urban and local center development, with city and county elected officials and staff;Current land use and valuation GIS-based parcel data stewarded by County Assessors;Traffic patterns and transit service from the regional Travel Demand Model that together form the landscape of regional accessibility to workplaces and other destinations; andCalibration of model variables to balance the fit of current conditions and dynamics at the county and regional level.‘Traffic Analysis Zone’ ProjectionsThe annual projections are forecasted for each of the Wasatch Front’s 2,800+ Traffic Analysis Zone (TAZ) geographic units. TAZ boundaries are set along roads, streams, and other physical features and average about 600 acres (0.94 square miles). TAZ sizes vary, with some TAZs in the densest areas representing only a single city block (25 acres). ‘City Area’ ProjectionsThe TAZ-level output from the model is also available for ‘city areas’ that sum the projections for the TAZ geographies that roughly align with each city’s current boundary. As TAZs do not align perfectly with current city boundaries, the ‘city area’ summaries are not projections specific to a current or future city boundary, but the ‘city area’ summaries may be suitable surrogates or starting points upon which to base city-specific projections.Summary Variables in the DatasetsAnnual projection counts are available for the following variables (please read Key Exclusions note below):DemographicsHousehold Population Count (excludes persons living in group quarters)Household Count (excludes group quarters)EmploymentTypical Job Count (includes job types that exhibit typical commuting and other travel/vehicle use patterns)Retail Job Count (retail, food service, hotels, etc)Office Job Count (office, health care, government, education, etc)Industrial Job Count (manufacturing, wholesale, transport, etc)Non-Typical Job Count* (includes agriculture, construction, mining, and home-based jobs) This can be calculated by subtracting Typical Job Count from All Employment Count.All Employment Count* (all jobs, this sums jobs from typical and non-typical sectors).* These variable includes REMM’s attempt to estimate construction jobs in areas that experience new and re-development activity. Areas may see short-term fluctuations in Non-Typical and All Employment counts due to the temporary location of construction jobs.Population and employment projections for the Wasatch Front area can be combined with those developed by Dixie MPO (St. George area), Cache MPO (Logan area), and the Utah Department of Transportation (for the remainder of the state) into one database for use in the Utah Statewide Travel Model (USTM). While projections for the areas outside of the Wasatch Front use different forecasting methods, they contain the same summary-level population and employment projections making similar TAZ and ‘City Area’ data available statewide. WFRC plans, in the near future, to add additional areas to these projections datasets by including the projections from the USTM model.Key Exclusions from TAZ and ‘City Area’ ProjectionsAs the primary purpose for the development of these population and employment projections is to model future travel in the region, REMM-based projections do not include population or households that reside in group quarters (prisons, senior centers, dormitories, etc), as residents of these facilities typically have a very low impact on regional travel. USTM-based projections also excludes group quarter populations. Group quarters population estimates are available at the county-level from GPI and at various sub-county geographies from the Census Bureau.

General Information

The Pop-AUT database was developed for the DISCC-AT project, which required subnational population projections for Austria consistent with the updated Shared Socio-Economic Pathways (SSPs). For this database, the most recent version of the nationwide SSP population projections (IIASA-WiC POP 2023) are spatially downscaled, offering a detailed perspective at the subnational level in Austria. Recognizing the relevance of this information for a wider audience, the data has been made publicly accessible through an interactive dashboard. There, users are invited to explore how the Austrian population is projected to evolve under different SSP scenarios until the end of this century.

Methodology

The downscaling process of the nationwide Shared Socioeconomic Pathways (SSP) population projections is a four-step procedure developed to obtain subnational demographic projections for Austria. In the first step, population potential surfaces for Austria are derived. These indicate the attractiveness of a location in terms of habitability and are obtained using machine learning techniques, specifically random forest models, along with geospatial information such as land use, roads, elevation, distance to cities, and elevation (see, e.g., Wang et al. 2023).

The population potential surfaces play a crucial role in distributing the Austrian population effectively across the country. Calculations are based on the 1×1 km spatial resolution database provided by Wang et al. (2023), covering all SSPs in 5-year intervals from 2020 to 2100.

Moving to the second step, the updated nationwide SSP population projections for Austria (IIASA-WiC POP 2023) are distributed to all 1×1 km grid cells within the country. This distribution is guided by the previously computed grid cell-level population potential surfaces, ensuring a more granular representation of demographic trends.

The base year for all scenarios is 2015, obtained by downscaling the UN World Population Prospects 2015 count for Austria using the WorldPop (2015) 1×1 km population count raster.

In the third step, the 1×1 km population projections are temporally interpolated to obtain yearly projections for all SSP scenarios spanning the period from 2015 to 2100.

The final step involves the spatial aggregation of the gridded SSP-consistent population projections to the administrative levels of provinces (Bundesländer), districts (Bezirke), and municipalities (Gemeinden).

Dashboard

The data can be explored interactively through a dashboard.

Data Inputs

Updated nationwide SSP population projections: IIASA-WiC POP (2023) (https://zenodo.org/records/7921989)

Population potential surfaces: Wang, X., Meng, X., & Long, Y. (2022). Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways. Scientific Data, 9(1), 563.

Shapefiles: data.gv.at

WorldPop 2015: WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00647

Version

This is version 1.0, built upon the Review-Phase 2 version of the updated nationwide SSP population projections (IIASA-WiC POP 2023). Once these projections are revised, this dataset will be accordingly updated.

File Organization

The SSP-consistent population projections for Austria are accessible in two formats: .csv files for administrative units (provinces = Bundesländer, districts = Politische Bezirke, municipalities = Gemeinden) and 1×1 km raster files in GeoTIFF and NetCDF formats. All files encompass annual population counts spanning from 2015 to 2100.

Transport for NSW provides projections of population and dwellings at the small area (Travel Zone or TZ) level for NSW. The latest version is Travel Zone Projections 2024 (TZP24), released in January 2025. TZP24 replaces the previously published TZP22. The projections are developed to support a strategic view of NSW and are aligned with the NSW Government Common Planning Assumptions. The TZP24 Population & Dwellings Projections dataset covers the following variables: Estimated Resident Population Structural Private Dwellings (Regional NSW only) Population in Occupied Private Dwellings, by 5-year Age categories & by Sex Population in Non-Private Dwellings The projections in this release, TZP24, are presented annually from 2021 to 2031 and 5-yearly from 2031 to 2066, and are in TZ21 geography. Please note, TZP24 is based on best available data as at early 2024, and the projections incorporate results of the National Census conducted by the ABS in August 2021. Key Data Inputs used in TZP24: 2024 NSW Population Projections – NSW Department of Planning, Housing & Infrastructure 2021 Census data - Australian Bureau of Statistics (including dwellings by occupancy, total dwellings by Mesh Block, household sizes, private dwellings by occupancy, population age and gender, persons by place of usual residence) For a summary of the TZP24 projection method please refer to the TZP24 Factsheet. For more detail on the projection process please refer to the TZP24 Technical Guide. Additional land use information for workforce and employment as well as Travel Zone 2021 boundaries for NSW (TZ21) and concordance files are also available for download on the Open Data Hub. Visualisations of the population projections are available on the Transport for NSW Website under Data and research/Reference Information. Cautions The TZP24 dataset represents one view of the future aligned with the NSW Government Common Planning Assumptions and population and employment projections. The projections are not based on specific assumptions about future new transport infrastructure but do take into account known land-use developments underway or planned, and strategic plans. TZP24 is a strategic state-wide dataset and caution should be exercised when considering results at detailed breakdowns. The TZP24 outputs represent a point in time set of projections (as at early 2024). The projections are not government targets. Travel Zone (TZ) level outputs are projections only and should be used as a guide. As with all small area data, aggregating of travel zone projections to higher geographies leads to more robust results. As a general rule, TZ-level projections are illustrative of a possible future only. More specific advice about data reliability for the specific variables projected is provided in the “Read Me” page of the Excel format summary spreadsheets on the TfNSW Open Data Hub. Caution is advised when comparing TZP24 with the previous set of projections (TZP22) due to addition of new data sources for the most recent years, and adjustments to methodology. Further cautions and notes can be found in the TZP24 Technical Guide Important note: The Department of Planning, Housing & Infrastructure (DPHI) published the 2024 NSW Population Projections in November 2024. As per DPHI’s published projections, the following variables are excluded from the published TZP24 Population and Dwellings Projections: Structural Private Dwellings for Travel Zones in 43 councils across Greater Sydney, Illawarra-Shoalhaven, Central Coast, Lower Hunter and Greater Newcastle Occupied Private Dwellings for Travel Zones in NSW. Furthermore, in TZP24, the Structural Private Dwellings variable aligns with the 2024 Implied Dwelling projections while the Occupied Private Dwellings variable aligns with the 2024 Households projections at SA2 level prepared by DPHI. The above variables are available upon request by contacting model.selection@transport.nsw.gov.au - Attention Place Forecasting.

Data tables providing period and cohort life expectancy (ex) and projected population using the current mortality projections method and a proposed new method.

This layer shares SEDAC's population projections for U.S. counties for 2020-2100 in increments of 5 years, for each of five population projection scenarios known as Shared Socioeconomic Pathways (SSPs). This layer supports mapping, data visualizations, analysis and data exports. Before using this layer, read: The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview by Keywan Riahi, Detlef P. van Vuuren, Elmar Kriegler, Jae Edmonds, Brian C. O’Neill, Shinichiro Fujimori, Nico Bauer, Katherine Calvin, Rob Dellink, Oliver Fricko, Wolfgang Lutz, Alexander Popp, Jesus Crespo Cuaresma, Samir KC, Marian Leimbach, Leiwen Jiang, Tom Kram, Shilpa Rao, Johannes Emmerling, Kristie Ebi, Tomoko Hasegawa, Petr Havlik, Florian Humpenöder, Lara Aleluia Da Silva, Steve Smith, Elke Stehfest, Valentina Bosetti, Jiyong Eom, David Gernaat, Toshihiko Masui, Joeri Rogelj, Jessica Strefler, Laurent Drouet, Volker Krey, Gunnar Luderer, Mathijs Harmsen, Kiyoshi Takahashi, Lavinia Baumstark, Jonathan C. Doelman, Mikiko Kainuma, Zbigniew Klimont, Giacomo Marangoni, Hermann Lotze-Campen, Michael Obersteiner, Andrzej Tabeau, Massimo Tavoni. Global Environmental Change, Volume 42, 2017, Pages 153-168, ISSN 0959-3780, https://doi.org/10.1016/j.gloenvcha.2016.05.009. From the 2017 paper: "The SSPs are part of a new scenario framework, established by the climate change research community in order to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The long-term demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature." According to SEDAC, the purpose of this data is: "To provide subnational (county) population projection scenarios for the United States essential for understanding long-term demographic changes, planning for the future, and decision-making in a variety of applications." According to Francesco Bassetti of Foresight, "The SSP’s baseline worlds are useful because they allow us to see how different socioeconomic factors impact climate change. They include: a world of sustainability-focused growth and equality (SSP1); a “middle of the road” world where trends broadly follow their historical patterns (SSP2); a fragmented world of “resurgent nationalism” (SSP3); a world of ever-increasing inequality (SSP4);a world of rapid and unconstrained growth in economic output and energy use (SSP5).There are seven sublayers, each with county boundaries and an identical set of attribute fields containing projections for these seven groupings across the five SSPs and nine decades.Total PopulationBlack Non-Hispanic PopulationWhite Non-Hispanic PopulationOther Non-Hispanic PopulationHispanic PopulationMale PopulationFemale Population Methodology: Documentation for the Georeferenced U.S. County-Level Population Projections, Total and by Sex, Race and Age, Based on the SSPs, v1 (2020 – 2100) Data currency: This layer was created from a shapefile downloaded April 18, 2023 from SEDAC's Georeferenced U.S. County-Level Population Projections, Total and by Sex, Race and Age, Based on the SSPs, v1 (2020 – 2100) Enhancements found in this layer: Every field was given a field alias and field description created from SEDAC's Data Dictionary downloaded April 18, 2023. Citation: Hauer, M., and Center for International Earth Science Information Network - CIESIN - Columbia University. 2021. Georeferenced U.S. County-Level Population Projections, Total and by Sex, Race and Age, Based on the SSPs, 2020-2100. Palisades, New York: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/dv72-s254. Accessed 18 April 2023. Hauer, M. E. 2019. Population Projections for U.S. Counties by Age, Sex, and Race Controlled to Shared Socioeconomic Pathway. Scientific Data 6: 190005. https://doi.org/10.1038/sdata.2019.5. Distribution Liability: CIESIN follows procedures designed to ensure that data disseminated by CIESIN are of reasonable quality. If, despite these procedures, users encounter apparent errors or misstatements in the data, they should contact SEDAC User Services at +1 845-465-8920 or via email at ciesin.info@ciesin.columbia.edu. Neither CIESIN nor NASA verifies or guarantees the accuracy, reliability, or completeness of any data provided. CIESIN provides this data without warranty of any kind whatsoever, either expressed or implied. CIESIN shall not be liable for incidental, consequential, or special damages arising out of the use of any data provided by CIESIN.