No. The BLS projections assume a labor market in equilibrium, i.e., one where overall labor supply meets labor demand except for some degree of frictional unemployment. For a discussion of the basic projection methodology, see the BLS Handbook of Methods.
Furthermore, attempts to ascribe shortages or surpluses to BLS projections are based on an incorrect comparison of the total employment and total labor force projections, two separate and fundamentally different measures. The total employment projection is a count of jobs and the labor force projection is a count of individuals. Users of these data should not assume that the difference between the projected increase in the labor force and the projected increase in employment implies a labor shortage or surplus. For a discussion of labor shortages in the context of long-term projection models, see page 10 of "Employment projections to 2012: concepts and context," by Michael W. Horrigan, February 2004 Monthly Labor Review.
The economic, employment, and labor force projections are updated annually; the most recent projections are for 2020–30 and were released on the BLS web site on September 8, 2021. The projections also are published in the Monthly Labor Review at the same time as the release.
The projections have a 10 year span. The current projections cover the 2020–30 decade.
No, BLS only prepares 10-year projections. Most states prepare both long- and short-term projections for their state and local areas. State projections are available from http://www.projectionscentral.org.
The fastest growing occupations can be found in this table and reflect jobs with the largest rate of change, in terms of percentage.
The industries with the fastest growth rates can be found in this table and reflect industries with the largest annual rate of change, in terms of percentage.
The projections are available only for the terminal year.
BLS prepares projections only for the nation as a whole. Projections of industry and occupational employment are prepared by each state, using input from the BLS National projections. Contact information for State labor market information offices is available at https://www.bls.gov/bls/ofolist.htm.
Employment projections from previous years are available in projections issues of the Monthly Labor Review and in archived news releases. Data files for a limited number of previous projections are available on request. Projections for previous periods are not always comparable to the latest projections, however, because of changes in industry and occupational classifications, historical data revision, and changes in projections procedures.
The historical data in the Employment Projections program’s National Employment Matrix combines employment data from several different sources. Data on industries comes primarily from the Current Employment Statistics (CES) program. This employment is distributed to occupations using staffing patterns from the Occupational Employment and Wage Statistics (OEWS) survey. In addition, the matrix incorporates data for industries not covered by CES and OES – agriculture and private households – from the Current Population Survey (CPS), as well as employment data for self-employed workers. A more detailed description of data sources is available at https://www.bls.gov/emp/documentation/projections-methods.htm.
The analysis underlying the BLS employment projections focuses on long-term structural change and growth and assumes a full employment economy in the target year. To the extent that recessions can cause long-term structural change, they may impact the projections. However, BLS does not project recessions.
The BLS projections do not make a distinction between full-time and part-time jobs since the data sources – Current Employment Statistics (CES), Occupational Employment and Wage Statistics (OEWS), and Quarterly Census of Employment and Wages (QCEW) - do not distinguish between these two job characteristics.
New technologies can impact projected employment through two channels. The first is through projections of industry employment. BLS projects both industry output and industry employment. New technologies can make workers more productive, which would reduce the number of workers needed to produce a given level of output. Depending on how fast output is projected to grow, this could lead to either a slower rate of employment growth in an industry, or a decline in employment in an industry.
The second way new technologies can impact employment is through changes in occupational staffing patterns. Staffing patterns describe the types of workers needed to produce an industry's output. Some technologies are expected to impact certain types of workers more than others, so their introduction may result in a reduction in the relative demand for one type of worker in favor of demand for other types of workers. This results in varying growth rates for occupations within an industry.
BLS conducts research on new technologies and other factors expected to impact the projections. Sometimes these technologies are already impacting employment, in which case BLS researches whether the impacts are expected to increase (as the technology becomes more widely adopted), remain constant, or decrease (as the benefits of the technology become fully realized). Other technologies have not yet begun impacting employment, in which case BLS makes assumptions about what its potential impact will be over the projection period.
BLS research on the impact of new technologies uses both quantitative and qualitative approaches. Historically, the impacts of technological change are visible in productivity data for industries and in shifting patterns of occupational employment data. These impacts visible in the historical data reflect the combined effects of all the technological change that is occurring. Qualitative assessments of the impacts of technological change in the past, the potential impact in the future, and the potential impacts of newly emerging technologies are synthesized with quantitative methods to develop the employment projections. The BLS projections reflect the impact of all factors and cannot be used to isolate the impact of a single factor or technology.
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Last Modified Date: September 8, 2021