Sample 1 - State of California
email this articles/publicationsEmailPrinter Friendly versionPrinter VersionMost Popular Most Popularfind related articles/publicationsRelated Info

How are Employment Projections Built?


Industry Projections

Analysts use employment trends and current economic data to forecast both California and county changes in Industry employment over time.  Industry projections are a primary data source for projecting changes in occupational employment.

Industry analysts forecast anticipated changes within industry employment levels using both ES-202 and Current Economic Statistics (CES) program data.  Summary level industry projections are produced:

  • Based on historical employment by two or three-digit Standard Industry Classification (SIC) codes.
  • Disaggregated into their three-digit industry components using base year proportions.
County projections are adjusted based on information provided by local area analysts.

For more  Industry Projections methodology.  See data here.

Occupational Projections

Analysts apply staffing patterns from the Occupational Employment Statistics (OES) survey to industry employment to forecast California and county changes in Occupational employment over time.  Occupational projections produce:
  • A distribution of occupations or staffing patterns for each industry.
  • Aggregate occupational projections.
Occupational analysts forecast anticipated changes in occupational employment based on several factors:
  • Industry growth or decline - changes in the number, size, and type of employers.
  • BLS change factors applied to base year staffing patterns to produce staffing patterns for the projected year.

    These change factors anticipate:
    1. Shifts in occupations due to technological change
    2. Innovations
    3. Response to changes in governmental policies and other factors

  • For County Projections, adjustments suggested by local area analysts based on local information


For Occupational Projections methodology.  See data here.



 
Ratings: Would you recommend this Article?
Not At All  1 -   2 -   3 -   4 -   5 - Highly
Average Ratings: 2.95, Total 14515 Votes