Marcia Hultman

Cabinet Secretary

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Labor Market Information Center

Employment Projections - Technical Notes

 

Executive Summary

Employment forecasts are presented on this website for both industries and occupations, for a longer-term period (10 years) and a short-term (two years), and for statewide South Dakota as well as for sub-state areas (the Metropolitan Statistical Areas and a balance of state area).

Long-term statewide employment projections by industry and occupation are completed every other year and published on the even-numbered year. Sub-state employment projections are also completed every other year, and published on the odd-numbered years. Only the most recent set of projections data is available for any area at any given time; data for prior periods is not available.

The industry employment projections are designed to:

  • Identify industries in which job openings are expected to occur.
  • Identify rapidly-growing, stable or declining industries.

The occupational employment projections are designed to:

  • Identify rapidly-growing, stable or declining occupations.
  • Indicate the projected demand for workers in occupations.

Recommended Uses of the Projections Data

  • Planning for future training needs
  • Analyzing future industry and occupational needs
  • Aiding workforce recruiting efforts
  • Analyzing occupational supply/demand

As mentioned above, the projections for each area (alternating between statewide and sub-state) are prepared every two years and are NOT updated between publication years. During the projections process, the past round of industry projections are reviewed and adjusted as necessary to reflect events that have recently occurred or are anticipated to occur during the projections period, based upon the availability of reliable and quantifiable data.

The projections should be used with other sources of information when making important decisions about business expansion, educational program development and career choices.

Please note: Terms in bold are further explained in the glossary at the end of this document.

Assumptions & Limitations

The projections reflect studies of past and present industrial trends. They illustrate what is likely to happen, barring major changes from past trends. These projections are based largely on the same major economic assumptions the U.S. Bureau of Labor Statistics (BLS) uses to develop national projections. These assumptions are:

  • Certain fundamental conditions will prevail throughout the projections period in the institutional framework of the U.S. and state economy; fluctuations in economic activity due to the business cycle will continue to occur.
  • Recent technological and scientific trends will continue.
  • Attitudes toward work, education, income and leisure will not change significantly; for example, the average workweek will not change markedly.
  • Population growth rates will not differ significantly from the U.S. Census Bureau data presently available.
  • No major events, such as war or other catastrophic events (including pandemics such as COVID-19), will occur that will significantly alter the industrial structure of the economy, the occupational staffing patterns or the rate of long-term growth.

The projections are not intended to be precise point estimates of employment for each industry or occupation. It is unlikely that the projections data will precisely predict actual employment developments due to unforeseen state, national and international trends and policies. However, the basic trends should prove accurate and aid in successful decision making. Users should view the projected worker estimates as indicators of relative magnitude and direction rather than estimates of absolute values and use the data as a starting point when studying expected occupational employment levels.

A special note about the COVID-19 pandemic: As mentioned above, the projections methodology includes a general assumption no major catastrophic event or natural disaster will significantly affect economic activities during the projections period. The COVID-19 pandemic is a perfect example. It rocked the nation and the world in 2020; and the long-term employment projections to 2030 have a base year of 2020. In other words, 2020 annual employment estimates were used when modeling employment to 2030. It is especially difficult to quantifiably predict the pandemic's impact on certain South Dakota industries to 2030, because there is not yet data available to provide insights into the long-term effects.

Methodology


Industry Projections

The first step in the employment projections process involves the development of industry projections. The future employment in individual industries is the primary determinant in projecting occupational demand, because each industry has a unique occupational structure.

To begin the process of developing industrial projections, a "total employment" time series is constructed. The series is assembled at the four-digit North American Industry Classification System (NAICS) level, based on data collected from business establishments through the Quarterly Census of Employment and Wages (QCEW) program and supplemented with employment data from the Current Employment Statistics (CES) program. Data from the Current Population Survey (CPS), which is administered by the U.S. Census Bureau for the BLS is also utilized. The series contains data on traditional wage and salary employment as well as self-employment and agricultural employment. Agricultural employment data from the QCEW program is supplemented with agricultural data from the U.S. Bureau of Economic Analysis.

Estimates of non-covered employment (NCE) collected via a survey are utilized in creating historical staffing patterns for religious organizations, schools and other establishments that are presumed not to be covered by unemployment insurance. The Current Population Survey (CPS) is used to determine self-employed, agricultural employment, and private household employment. After edits and adjustments, the total employment time series serves as the input for the initial industry projections.

Industry projections also utilize several national and state variables. BLS produces the national variable inputs, which includes economic indicators such as Real Gross Domestic Product and the U.S. unemployment rate. State variable inputs consist largely of population trends, and real and nominal personal income.

In order to produce projections and promote consistency across 50 states, South Dakota utilizes the Employment Projections System, a national standard which was developed by a consortium of states working in cooperation with the Employment and Training Administration of the U.S. Department of Labor. The system provides the capability to perform projections incorporating accepted statistical methods and techniques. Industry employment projections are developed using a number of shift-share, time series and regression types of economic models. Once the initial industry projections are completed, results are reviewed and adjusted as necessary to reflect events that have recently occurred or are anticipated to occur during the projections period for which reliable and quantifiable data are available.

Micro-Matrix: Staffing Patterns for Industries

The second step in the employment projections process involves the micro-matrix, a table arraying occupational staffing patterns for each industry. The matrix encompasses more than 800 detailed occupations cross-classified by more than 270 four-digit NAICS industries.

The main component in the construction of the micro-matrix is the Occupational Employment and Wage Statistics (OEWS) survey data. The OEWS survey, conducted by the Labor Market Information Center in cooperation with the BLS, is a semi-annual survey whose sample is based on establishments in the nonagricultural wage and salary sectors of the economy. Designed to provide current estimates of occupational employment for each industry, the OEWS sample is surveyed over a three-year rotating cycle. Approximately 6,500 establishments are contacted over the three-year cycle. For the 2022-2032 projections, OEWS data for fourth quarter 2019, all data for 2020 and 2021 and second quarter 2022 were used. For short-term (2023-2025) projections, OEWS data for fourth quarter 2019, all data for 2020 and 2021, and second quarter 2022 were used.

Following a review and minor modifications, staffing pattern data collected from the most recently completed OEWS survey comprises the nonfarm wage and salary micro-matrix for the base year. Consistent with the "total employment" approach, additional data are used to supplement areas not covered by the OEWS survey.

Occupational Projections

Thirdly, once the total employment micro-matrix is complete, the industry projections created during the first step are merged with the micro-matrix results from the second step. The employment projections for each four-digit industry are applied to the appropriate micro-matrix ratios to derive occupational projections by industry. Another important national component used in developing South Dakota occupational projections are BLS change factors, which are coefficients developed to account for shifts, or changes, in industry staffing patterns that may occur over time. The development of these factors begins with the review of historical data to identify trends. Factors underlying these trends are then identified through analytical studies of specific industries and occupations, technological change, and a wide variety of other economic data. Then, judgments are made as to how the pattern will change in the future. Factors underlying this change are numerous, including technological developments affecting production and products, innovations in the ways business is conducted, modifications of organizational patterns, responses to government policies, and decisions to add new products and services or stop offering old ones. The change projected for a specific occupation may be small, moderate, or significant; the precise percentage reflects the judgment of the staff members based on the analyses described above that relate to that occupation. Once projected staffing patterns are available, they are used to allocate each industry's projected employment to detailed occupations. These estimates can then be summed across industries to yield total employment for each detailed occupation. Thus, the projected employment of an occupation is determined by staffing pattern changes, the projected growth in the industries in which that occupation resides, and technological/organizational change factors.

National occupational staffing patterns or employment totals for agricultural workers, self-employed and unpaid family workers are added to the cross-industry wage and salary occupational employment totals.

In addition to the employment projections generated using the process outlined above, occupational demand estimates are also calculated.

Number of openings created due to employment change represents the difference between the base employment in an occupation and the projection; if the projection for an occupation is negative, then openings due to change are set to zero. This includes employment level changes due to business expansion, as well as changes in staffing patterns for an industry. For example, several years ago hospitals began hiring a higher proportion of registered nurses and fewer LPNs to maximize the skills available in return for expenditures on personnel costs, to help meet record keeping requirements and to help ensure they were offering the highest level of healthcare possible.

Number of openings created by the need to replace individuals exiting the labor force entirely (for reasons including retirement and death, etc.) is estimated by multiplying occupational employment estimates by national exit rates supplied by the BLS. Labor force exits are more common at older ages as workers retire, but can occur at any age.

Number of openings created by the need to replace individuals transferring occupations is estimated by multiplying occupational employment estimates by national occupational transfer rates supplied by the BLS. The occupational transfer rates reflect workers who permanently leave one occupation to enter another occupation. This estimate of openings does not count workers who change jobs but remain in the same occupation.

Total openings are the summation of openings due to employment change, openings to replace individuals exiting the labor force entirely AND openings to replace workers permanently transferring from one occupation to another occupation. Annualized results are calculated by dividing by 10 for long-term projections or by two years for short-term projections, the number of years in the respective projection period.

For more information on the methodology used to estimate occupational demand, visit the BLS website.

South Dakota industry and occupational employment projections rely heavily on national industry and occupational employment projections produced by BLS. BLS produces nationwide employment projections every year. South Dakota projections are based on BLS national projections, which can be found on the BLS website.

The results are then evaluated by labor market analysts for reasonableness and consistency between industries and occupations. Projections are carefully reviewed and adjusted as needed, factoring in anticipated or known labor market trends that could dramatically affect employment.

Glossary

Change Factors
These coefficients are developed by BLS to account for changes in industry staffing patterns over time. A detailed explanation of change factors is contained in the national projection methods on the BLS website.

Current Employment Statistics (CES)
Each month the CES program surveys businesses and government agencies in order to provide detailed industry data on employment, hours and earnings of workers on nonfarm payrolls. This program is administered in South Dakota by the Labor Market Information Center in cooperation with the Bureau of Labor Statistics.

BLS, with the assistance of the Labor Market Information Center, surveys approximately 1,500 South Dakota businesses and government agencies, representing approximately 3,000 work sites for the CES program. Nationally, about 145,000 businesses and government agencies representing approximately 697,000 individual work sites, are surveyed each month. CES data is used by federal and state agencies to determine current economic trends.

Base Number of Jobs
This total employment estimate is primarily based on data from South Dakota's Covered Employment and Wages (QCEW) program and the Current Employment Statistics (CES) program.

Estimates for agricultural-related employment not covered in the above programs, self-employed workers, and private household workers are derived from the Current Population Survey (CPS) administered by the U.S. Bureau of Census for BLS. Estimates of non-covered employment (NCE) (employees not covered by unemployment insurance) were collected via the Current Employment Statistics program to determine a historical staffing pattern for religious organizations, schools and other establishments with non-covered employment.

South Dakota's total 2022 base year employment used in the projections was 511,117. For comparison purposes, South Dakota's 2022 total employment in not seasonally adjusted labor force estimates for South Dakota (estimated through the Local Area Unemployment Statistics (LAUS) program) was 464,946; the 2022 total workers covered by unemployment insurance (as recorded in the Quarterly Census of Employment and Wages (QCEW) program) was 443,194; and the 2022 total number of nonfarm wage and salaried workers (as estimated through the Current Employment Statistics program) was 452,600.

Projected Number of Jobs
This total employment estimate is produced using forecasting software that utilizes a variety of mathematical models, including regression analyses, to produce a projected employment estimate.

This process takes into account state relationships to national factors on such data elements as population and personal income statistics.

Geographic Areas for Which Projections Data is Available
The industry and occupational employment projections are available for statewide South Dakota, the Metropolitan Statistical Areas (MSA) and a Broad Geographic Area type called Balance of State. See our Definitions page for definitions and a list of counties included in the MSAs and the Balance of State. Please note: Statewide employment projections for a 10-year period are completed every other year, followed by completion the next year of the sub-state projections for the MSAs and the Broad Geographic Areas.

Local Area Unemployment Statistics (LAUS)
The LAUS program produces monthly and annual employment, unemployment, and labor force data for census regions and divisions, states, counties, metropolitan areas and many cities, by place of residence. This program is administered in South Dakota by the Labor Market Information Center in cooperation with the Bureau of Labor Statistics.

This information provides useful knowledge about an area's economic well being by providing useful data on the number and percentage of people in an area maintaining or searching for employment.

North American Industry Classification System (NAICS)
The NAICS system provides a standard industrial classification system which allows government and business analysts to directly compare industrial production statistics collected and published in the three North American Free Trade Agreement countries. For more information see the U.S. Census Bureau website.

Occupational Employment and Wage Statistics (OEWS)
The OEWS program surveys business establishments to produce employment and wage estimates for over 800 occupations. This program is administered in South Dakota by the Labor Market Information Center in cooperation with the Bureau of Labor Statistics.

These estimates include the number of people employed in certain occupations and the wages paid. Self-employed persons are not included in the estimates.

Data are available for the United States, all states, metropolitan areas and sub-state geographical areas. South Dakota gathers occupational information on more than 600 occupations statewide.

Non-Covered Employment (NCE)
Not all workers are covered by South Dakota Unemployment Insurance law. South Dakota wage and salaried workers not covered include railroad employees, government elected officials, election workers, work-study students and religious organization employees. (Some religious organizations may opt to provide unemployment insurance coverage to their employees; these employees are included in the base year and projected worker levels. Nonprofit organizations may be required to be covered by unemployment insurance, depending upon whether or not they meet specific employment requirements.

Smaller businesses may also be exempted from coverage if they do not meet unemployment insurance law minimum payroll and employment criteria. Businesses who hire only a few workers on a part-time or seasonal basis, such as agricultural businesses, make up a large part of the exempted group.

Quarterly Census of Employment and Wages (QCEW)
The South Dakota QCEW program publishes a quarterly count of employment and wages covered by unemployment insurance as reported by employers; covered workers account for almost 96 percent of wage and salaried workers in South Dakota. This program is administered in South Dakota by the Labor Market Information Center in cooperation with BLS.

The QCEW data is available at the state, metropolitan and county level by industry. This data provides a good measure of the economic well-being of an area and are used to establish industry trends.

In addition, because the QCEW program is considered the "universe," other programs (such as CES) draw their sample of whom to survey from this program.

Average Annual Openings
The demand for workers needed yearly (average annual openings) is based on three factors: the number of jobs expected to be available due to growth (or employment change), the number of jobs expected to be available due to the need to replace workers exiting the labor force completely (or exits), and the number of jobs expected to be available due to the need to replace workers transferring from one occupation to another (or transfers).

Total average openings are the summation of job openings due to all three factors.

Annualized results are calculated by dividing by 10 for long-term projections or by two for short-term projections, the number of years in the respective projection period. Please Note: Average annual openings is an estimate that results from division; is it is not the number of job vacancies in any specific year within the projections period.

Change - Number of openings created due to employment change represents the difference between the base employment in an occupation and the projection; if the projection for an occupation is negative, then openings due to change are set to zero. Positive employment change, or growth, includes employment level changes due to business expansion, as well as changes in an industry's staffing pattern.

Exits - Number of openings created by the need to replace individuals exiting the labor force entirely (for reasons including retirement and death, etc.) is estimated by multiplying occupational employment estimates by national exit rates supplied by the BLS. Labor force exits are more common at older ages as workers retire, but can occur at any age.

Transfers - Number of openings created by the need to replace individuals transferring occupations is estimated by multiplying occupational employment estimates by national occupational transfer rates supplied by the BLS. The occupational transfer rates reflect workers who permanently leave one occupation to enter another occupation. This estimate of openings does not count workers who change jobs but remain in the same occupation.

For more information on the average annual demand estimates, visit the BLS website.

Resources

Standard Occupational Classification System (SOC)

Classification of Instructional Programs (CIP)

North American Industry Classification System (NAICS)

Understanding BLS Employment Projections YouTube video