By the year 2033, it is projected that the number of employees working in health care and social assistance will have increased by about 2.24 million from the number employed in 2023. Retail trade, however, is projected to decrease by 364,800 employees by 2033.

Short-term Occupational Projections for a 2-year time horizon are produced for the State to provide individuals and organizations with an occupational outlook to make informed decisions on individual career and organizational program development. Short-term projections are revised annually. Data are not available for geographies below the state level, including labor market regions. Data is based on second quarter averages and may be subject to seasonality. Detail may not add to summary lines due to suppression of data because of confidentiality and/or quality.

Employment by industry, occupation, and percent distribution, 2023 and projected 2033.

In 2033, the number of employees working in healthcare support occupations is projected to increase by 15.2 percent from the number in 2023. Office and administrative support employment, however, is projected to decline 3.5 percent.

The Australian Government Department of Jobs and Small Business publishes a range of labour market data on its Labour Market Information Portal website (lmip.gov.au).

The link below provides data for the employment projections by industry, occupation, skill level and region for the following five year period. Produced by the Department of Employment, these employment projections are designed to provide a guide to the future direction of the labour market, however, like all such exercises, they are subject to an inherent degree of uncertainty.

By 2033, the number of nurse practitioners is expected to increase by 44.3 percent. Additionally, the occupation of wind turbine service technician is expected to grow by 60.1 percent - reflecting the increase in electricity generated from wind in the United States.

Long-term Industry Projections for a 10-year time horizon are produced for the State and its labor market regions to provide individuals and organizations with an insight into future industry trends to make informed decisions on individual career and organizational program development. Long-term projections are revised every 2 years. Data are not available for geographies below the labor market regions. Detail may not add to summary lines due to suppression of confidential data.

By 2033, it is projected that the number of registered nurses working in the U.S., will increase by about 197,200 compared to the number of employed registered nurses in 2023. Home health and personal care aide employment is expected to increase by over 820,500, more than any other occupation in the same time span.

Short-term Industry Projections for a 2-year time horizon are produced for the State to provide individuals and organizations with an insight into future industry trends to make informed decisions on employment opportunities and organizational program development. Short-term projections are revised annually. Data are not available for geographies below the state level, including labor market regions. Data is based on second quarter averages and may be subject to seasonality. Detail may not add to summary lines due to suppression of confidential data.

Long-Term (ten-year) estimations, projections, and growth rates for industry and occupation by geographic area in Colorado provided by the Colorado Department of Labor and Employment (CDLE).

This dataset contains indicators related to employment projections by detailed occupations, workers education and training characteristics, occupational separations and openings. The occupations denominations are based on the 2016 Standard Occupational Classification.

Employment by industry, occupation, and percent distribution, 2023 and projected 2033.

Employment Rate in the United States remained unchanged at 59.70 percent in June. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

The 3-year Employment Outlooks consist of a rating (very good, good, moderate, limited or very limited) of the employment prospects as well as a narrative text that provides an assessment of the main forecast indicators, recent statistics, and value-added regional observations. Employment Outlooks are developed for each detailed occupation in all provinces, territories and economic regions of Canada, where data permits. They are updated annually. The Employment Outlooks developed until the 2015-2017 period were assessed on the basis of the National Occupational Classification (NOC) 2006, and include up to 520 occupations. Beginning with the 2016-2018 Outlooks, the NOC 2011 is used for the analysis and the Outlooks include up to 500 occupations. Outlooks and trend descriptions for the latest year (currently disseminated on Job Bank) are subject to change as new information becomes available. Every effort will be made to keep the records on the Open Data Portal as up to date as possible, though delays may occur. If you have comments or questions regarding the 3-year Employment Outlooks, please contact the Labour Market Information division at: NC-LMI-IMT-GD@hrsdc-rhdcc.gc.ca

Long-term Occupational Projections for a 10-year time horizon are provided for the State and its labor market regions to provide individuals and organizations with an occupational outlook to make informed decisions on individual career and organizational program development. Long-term projections are revised biannually. Data are not available for geographies below the labor market regions. Detail may not add to summary lines due to suppression of data because of confidentiality and/or quality.

Analysis of ‘Long-Term Occupational Employment Projections’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/8fcc2e43-5993-4f9f-b081-a7a03a805c85 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Long-term Occupational Projections for a 10-year time horizon are provided for the State and its labor market regions to provide individuals and organizations with an occupational outlook to make informed decisions on individual career and organizational program development. Long-term projections are revised biannually. Data are not available for geographies below the labor market regions. Detail may not add to summary lines due to suppression of data because of confidentiality and/or quality.

--- Original source retains full ownership of the source dataset ---

United States CBO Projection: Employment Cost Index: Annual: YoY data was reported at 3.061 % in 2029. This records an increase from the previous number of 3.059 % for 2028. United States CBO Projection: Employment Cost Index: Annual: YoY data is updated yearly, averaging 3.061 % from Dec 2011 (Median) to 2029, with 19 observations. The data reached an all-time high of 3.633 % in 2020 and a record low of 1.683 % in 2011. United States CBO Projection: Employment Cost Index: Annual: YoY data remains active status in CEIC and is reported by Congressional Budget Office. The data is categorized under Global Database’s United States – Table US.G091: Employment Cost Index: Projection.

CBO Projection: Employment Cost Index: QoQ data was reported at 3.061 % in Dec 2029. This stayed constant from the previous number of 3.061 % for Sep 2029. CBO Projection: Employment Cost Index: QoQ data is updated quarterly, averaging 3.061 % from Jun 2011 (Median) to Dec 2029, with 75 observations. The data reached an all-time high of 3.669 % in Jun 2020 and a record low of 1.850 % in Jun 2011. CBO Projection: Employment Cost Index: QoQ data remains active status in CEIC and is reported by Congressional Budget Office. The data is categorized under Global Database’s United States – Table US.G091: Employment Cost Index: Projection.

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.

This statistic illustrates the fastest projected decline in employment in the United States from 2023 to 2033, by occupation. Between 2023 and 2033, the number of word processors and typists is expected to decrease by ** percent.