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Chapter 13.
Employment Projections
Projections Data Base
The BLS approach to employment projections requires specialized data, much of which is assembled especially for this purpose. But all of the data used in the projections process comes from existing general-purpose statistical surveys and programs. The task of BLS in this case is to adapt these sources to the particular needs of the projections system and, most importantly, to meld them into a coherent overall picture of the industrial and occupational structure of the economy.
The data requirements of the system fall into four broad areas: population and labor force, Gross Domestic Product (GDP) by detailed product, interindustry production, and industry and occupational employment. Data on the size and work status of the population by age, sex, race and ethnicity are available through the decennial population census and the monthly Current Population Survey (CPS), a survey of households. Only minor adjustments are required to provide the demographic data base, which supports the labor force projections. These sources, particularly the CPS are also important in assembling other types of data.
Final demand by detailed product is mostly extracted from the U.S. National Income and Product Accounts. The BLS system uses time series data on more than 200 product groupings derived from this source.
The U.S. Input-Output Accounts are the source of two critical items, the use and make tables and the bridge tables. The use and make tables define the structure of interindustry production, and the bridge tables allocate the final demand product groups to detailed commodities. Input-output tables like these are the area of greatest difficulty in data development. The United States, like many other countries, does not produce detailed annual input-output tables; its benchmark tables are released every 5 years and analyze the survey period from about 5 years earlier. Generally, BLS updates the latest benchmark tables (currently 2002) to a more recent year or years by estimating the commodity and industry sums and then applying a balancing procedure, commonly referred to as RAS1, in order to adjust the base matrix to the new sums. Although a procedural update is not ideal, it does provide a more up-to-date starting point for the projections and can yield information about trends in the technical coefficients that is useful for the projections process.
The bridge tables are an integral part of the input-output accounts and share the same problem of lack of timely data. The approach to updating them is also similar except that explicit adjustments are used in place of the more mechanical RAS balancing technique. In addition to updating the input-output and bridge tables, numerous adjustments are made to provide consistency with the industry and occupational employment data.
A time-series data base on commodity and industry output is maintained for each sector in the BLS system. These time-series are key variables in the projection system and are also used in updating the benchmark input-output table. The series are based on a variety of primary source data, such as annual surveys of manufacturers, of wholesale trade, and of service, as well as other annual and monthly surveys conducted by the Bureau of the Census. Additional data sources include estimates of revenue and various output that come from the Energy Information Agency, the Department of Agriculture, and the Internal Revenue Service. BLS assembles these data sources into a set of industry output measures that are consistent both over time and with the benchmark input-output table.
Time series on employment and hours by industry are generally derived from two BLS sources for different groups of workers: (1) The Current Employment Statistics survey, an establishment survey, for nonagricultural wage and salary employment, production worker employment, and weekly hours; and (2) the Current Population Survey, a household survey, for agricultural employment, self-employed and unpaid family worker jobs and hours, and private household workers.
Data needed to develop the occupational staffing pattern matrix are derived from several sources. For all except a few industries, information on the occupational distribution of wage and salary workers by industry (staffing patterns) is derived from the Occupational Employment Statistics (OES) survey conducted by State Workforce Agencies under a BLS-State cooperative program. The OES program surveys about 200,000 establishments per panel (every 6 months), taking 3 years to fully collect the sample of 1.2 million establishments. About 800 detailed occupations from the Standard Occupational Classification (SOC) are surveyed across more than 450 industries. The industry classifications correspond to the sector, which are 3, 4, and 5-digit North American Industry Classification System (NAICS) industrial groups. In developing the base-year matrix, occupations that have fewer than 5,000 workers are generally aggregated into similar larger occupations or appropriate residuals. Also, industries with staffing patterns that are comparable to the residual employing fewer than 50,000 workers are aggregated into residuals within the same 3-digit NAICS group.
In some industries, adjustments are made to OES survey staffing patterns because some occupations are not listed separately in the survey questionnaire but are included in a residual category. To develop economy-wide employment estimates for these occupations, it is necessary to disaggregate data from OES survey residuals. Data from the decennial census are used for these adjustments.
Adjustments also must be made to staffing patterns derived from sources other than the OES survey. For example, the occupational classifications used to group Federal Government workers are more detailed than those used in the matrix. Similarly, estimates of occupational employment for workers who are self-employed, unpaid family members, and in the private household industry and agriculture, except agricultural services, are derived from the CPS and must be adjusted to make them comparable to the occupational classification used in the matrix.
After these data have been assembled, they are grouped in a matrix showing occupational employment distribution by industry. Because these percentages are derived from surveys conducted in different years, they are applied to total industry employment estimates for the base year to develop occupational employment estimates.
BLS is committed to maintaining and improving this data base. For example, ongoing efforts include making the data comparable and using crosswalks to account for changes in industry and occupational classification systems.
Footnotes
1 Ronald E. Miller and Peter D. Blair, Input-Output
Analysis: Foundations and Extensions (Prentice-Hall,
Inc., Englewood Cliffs, NJ, 1985), 276-294.
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References
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