Chart book: Occupational Employment and Wages, May 2008

This chart book, Occupational Employment and Wages, 2008, includes graphs, maps, tables, and text describing the U.S. occupational workforce in May 2008. It contains Occupational Employment Statistics (OES) employment and wage data for occupations employed in different industries, States, and metropolitan and nonmetropolitan areas. The material cited below is drawn from this chart book.


Charts, Maps, and Tables

Occupational Employment and Wages, 2008 chart book (complete book as PDF, 7 MB)

Page-by-page breakout:

  • Cover, Preface, Acknowledgements, and Contents (PDF)
  • Organization of charts and applications of OES data (PDF)
  • OES survey coverage, scope, and concept definitions (PDF)


  • Occupation focus (HTML)

  • Figure 1. Employment and mean wages for the smallest occupations in the United States, May 2008 (HTML) (PDF)
  • Figure 2. Employment and mean wages for the largest occupations in the United States, May 2008 (HTML) (PDF)
  • Figure 3. Employment and median hourly wages of occupations with wages near the U.S. median, May 2008 (HTML) (PDF)
  • Figure 4. Number of occupations with wages near the U.S. median, and employment in these occupations, by occupational group, May 2008 (HTML) (PDF)
  • Figure 5. Wages of selected health therapists, May 2008 (HTML) (PDF)
  • Figure 6. Profile of writing occupations, May 2008 (HTML) (PDF)
  • Figure 7. Employment of writers and authors, by industry, May 2008 (HTML) (PDF)
  • Figure 8. Growth in the nominal mean annual wage, by occupational group, 200208 (HTML) (PDF)


  • Occupations within industries (HTML)

  • Figure 9. Wages of counselors in selected industries, May 2008 (HTML) (PDF)
  • Figure 10. Employment of reporters and correspondents by medium, May 2004 and May 2008 (HTML) (PDF)
  • Figure 11. Occupations with employment concentrated primarily in a single industry, May 2008 (HTML) (PDF)
  • Figure 12. Industries with employment concentrated primarily in a single occupation, May 2008 (HTML) (PDF)
  • Figure 13. Mean wages of computer scientists, systems analysts, and software engineers in selected industries, May 2008 (HTML) (PDF)
  • Figure 14. Mean wages of network and database occupations and of programming occupations in selected industries, May 2008 (HTML) (PDF)


  • Industry focus (HTML)

  • Figure 15. Employment in selected healthcare occupations in the health care and social assistance sector in May 2004, and the occupations' employment growth from May 2004 to May 2008 (HTML) (PDF)
  • Figure 16. Employment and mean wages of the largest occupations in the health insurance industry, May 2008 (HTML) (PDF)
  • Figure 17. Wage distributions for selected occupations in full-service restaurants, May 2008 (HTML) (PDF)
  • Figure 18. Wage ranges for selected occupations in the chemical manufacturing industry, by education and training category, May 2008 (HTML) (PDF)
  • Figure 19. Mean annual wages of the largest occupations in selected mining industries, May 2008 (HTML) (PDF)
  • Figure 20. Employment in the largest occupations of selected mining industries, May 2008 (HTML) (PDF)
  • Figure 21. Largest occupations in the industry supersector with the second-highest number of job openings: professional and business services, May 2008 (HTML) (PDF)


  • State focus (HTML)

  • Figure 22. Distribution of employment in the United States and in Michigan, by occupational group, May 2008 (HTML) (PDF)
  • Figure 23. Wages and employment of selected occupations in Michigan, May 2008 (HTML) (PDF)
  • Figure 24. Wages of structural metal fabricators and fitters, for selected States, May 2008 (HTML) (PDF)
  • Figure 25. Correlation between States' rates of separations due to mass layoffs and each occupational group's proportion of employment, May 2008 (HTML) (PDF)
  • Figure 26. Differences between States' mean wages and the U.S. mean wage, May 2008 (HTML) (PDF)
  • Figure 27. Decomposition of changes in States' real average wages from November 2002 to May 2007 (HTML) (PDF)
  • Figure 28. Employment in computer and mathematical occupations, per 1,000 workers, by State, May 2008 (HTML) (PDF)
  • Figure 29. Mean annual wage of computer and mathematical occupations, by State, May 2008 (HTML) (PDF)


  • Area focus (HTML)

  • Figure 30. Occupations found primarily in nonmetropolitan areas, May 2008 (HTML) (PDF)
  • Figure 31. Occupations with the highest concentration of employment in metropolitan areas, May 2008 (HTML) (PDF)
  • Figure 32. Distribution of employment in the United States and in Durham, NC, May 2008 (HTML) (PDF)
  • Figure 33. Detailed occupations with the highest concentrations of employment in Durham, NC, relative to the occupations' corresponding employment concentrations in the United States, May 2008 (HTML) (PDF)
  • Figure 34. Differences between North Carolina metropolitan area wages and the U.S. mean wage, May 2008 (HTML) (PDF)
  • Figure 35. Employment in transportation and material moving occupations, per 1,000 workers, by area, May 2008 (HTML) (PDF)
  • Figure 36. Mean annual wage of transportation and material moving occupations, by area, May 2008 (HTML) (PDF)


  • Link to the OES website and electronic version of the chart book (PDF)

Preface

This chart book, Occupational Employment and Wages, 2008, is a product of the Occupational Employment Statistics (OES) program of the U.S. Bureau of Labor Statistics (BLS). The OES program produces employment and wage estimates for more than 800 occupations by geographic area and industry.

For every occupation, the OES program has data on the total U.S. employment and the distribution of wages, including the mean wage and the 10th, 25th, 50th (median), 75th, and 90th percentiles. Occupational data for geographic areas include employment and wages for each of the 50 States, the District of Columbia, Puerto Rico, Guam, and the U.S. Virgin Islands. Local area data are available for 377 Metropolitan Statistical Areas (MSAs), 34 metropolitan divisions within 11 of the largest MSAs, and 174 nonmetropolitan areas. National industry-specific estimates are available by industry sector and for 290 industries.

The OES survey is a cooperative effort between BLS and the State workforce agencies. Employment and wage data for more than 800 occupations were collected from a sample of 1.2 million business establishments, employing more than 80 million workers, in 6 semiannual panels between November 2005 and May 2008. Wage data for all establishments were updated to the May 2008 reference period, and employment data were updated to the average of the November 2007 and the May 2008 reference periods. Information on OES sampling and estimation methodology is provided in the survey methods and reliability statement at www.bls.gov/oes/current/methods_statement.pdf.

The OES Web site, www.bls.gov/oes/, presents additional data tables that include cross-industry occupational employment and wage data for the Nation, States, metropolitan areas, metropolitan divisions, and nonmetropolitan areas; national occupational employment and wage data by industry; and profiles for all occupations. Data users also can create customized tables using the OES database search tool, or download complete OES data in zipped XLS format from www.bls.gov/oes/tables.htm. Material in this publication is in the public domain and, with appropriate citation, may be reproduced without permission. Questions about OES data can be directed to the information phone line at (202) 691-6569 or sent to OES information.

Organization of charts and applications of OES data

This chart book's presentation of figures is intended to demonstrate a variety of applications of OES data. Figures are organized into five categories: The first focuses on detailed occupations, the second focuses on occupational variability by industry, the third highlights patterns of specific industries, and the fourth and fifth focus on labor markets of States and local areas.

Some examples of useful applications of OES data:

  • Detailed occupational data can be used by job seekers or employers to study wages for workers in certain occupations and to assess wage variation within and across occupations. Wage variation within an occupation can result from several factors, including industry, geographic location, or a worker's individual experience or qualifications. Useful data for job seekers include information on the industries or geographic areas that have the highest employment or the highest average wages for an occupation. Career and guidance counselors can use OES data to examine information on the possible occupational choices of their clients.

  • Industry-specific occupational data can be used by human resources professionals in salary negotiations or to ensure that their wages are competitive with those of other businesses in their area or industry. Information on the types of jobs within an industry can be used to compare average staffing patterns with that of one's own company. Occupational employment by industry may be useful in assessing the impact of shifts in technology and other macroeconomic trends on the types of jobs available. BLS and State government employment projections programs use OES data as an input to their employment projections, which can be used to predict training and education demands.

  • Geographic area information can be used to assess labor market features of a particular area. OES State level data can be used to make assessments about the diversity of a State's economy or to make comparisons among States. The occupational composition of employment can provide clues to how a State or regional economy can hold up in adverse conditions that affect a certain sector of the economy. Differences in both occupational composition and occupational wage rates also help explain differences in average wages across States. For example, States with high average wages may have larger employment shares of high-paying occupations, higher wages within each occupation, or some combination of both factors.

  • Like State data, metropolitan and nonmetropolitan area data can be used to study the diversity of local area economies. Businesses can use data to see whether it might be beneficial to relocate to a particular area. OES wage data can be used to compare wages across alternative areas as part of an analysis of labor costs. OES occupational employment data may indicate whether workers are available in occupations that the business will need. For example, businesses that require computer specialists or skilled production workers may want to identify areas that have high employment in these occupations.

OES survey coverage, scope, and concept definitions

The OES survey covers all full- and part-time wage and salary workers in nonfarm industries. The survey does not include the self-employed, owners and partners in unincorporated firms, workers in private households, or unpaid family workers.

An occupation is a set of activities or tasks that employees are paid to perform. Employees who perform essentially the same tasks are in the same occupation, whether or not they are in the same industry. Workers who may be classified in more than one occupation are classified in the occupation that requires the highest level of skill. If there is no measurable difference in skill requirements, workers are included in the occupation in which they spend the most time. All occupations are classified by the 2000 Standard Occupational Classification (SOC) system.

An industry is a group of establishments that have similar production processes or provide similar services. For example, all establishments that manufacture automobiles are in the same industry. A given industry, or even a particular establishment in that industry, might have employees in many different occupations. The North American Industry Classification System (NAICS) groups similar establishments into industries.

The employment shown is the average employment for the most recent May and November. Employment is defined as the number of workers who can be classified as full- or part-time employees, including workers on paid vacations or other types of paid leave; workers on unpaid short-term absences; salaried officers, executives, and staff members of incorporated firms; employees temporarily assigned to other units; and employees for whom the reporting unit is their permanent duty station, regardless of whether that unit prepares their paycheck.

Wages for the OES survey are straight-time, gross pay, exclusive of premium pay. Included are base rate; cost-of-living allowances; guaranteed pay; hazardous-duty pay; incentive pay, including commissions and production bonuses; tips; and on-call pay. Excluded are back pay, jury duty pay, overtime pay, severance pay, shift differentials, non-production bonuses, employer cost for supplementary benefits, and tuition reimbursements.

Respondents are asked to report the number of employees paid within specific wage intervals, regardless of part- or full-time status. The responding establishment can reference either the hourly or the annual rate for full-time workers but are instructed to report the hourly rate for part-time workers. Intervals are defined both as hourly rates and the corresponding annual rates, where the annual rate for an occupation is calculated by multiplying the hourly wage rate by a typical work year of 2,080 hours.

Geographic areas are defined by the Office of Management and Budget. Guam, Puerto Rico, and the U.S. Virgin Islands are also surveyed; their data are not included in this publication, but are published on the OES Web site. The nationwide response rate for the May 2008 survey was 78.25 percent based on establishments and 74.28 percent based on employment. More information on sampling and estimation methodology can be found in the survey methods and reliability statement on the BLS Web site at: www.bls.gov/oes/current/methods_statement.pdf.

Acknowledgements

The information provided in this chart book is possible due to cooperation of more than a million business establishments that provide information on their workers to their State workforce agency and the U.S. Bureau of Labor Statistics (BLS). State workforce agencies within each State collect and verify almost all data provided. BLS selects the sample, produces the estimates, and provides technical procedures and financial support to the States. BLS also collects a small portion of the data from employers.

BLS produced this chart book under the general guidance and direction of Dixie Sommers, Assistant Commissioner for Occupational Statistics and Employment Projections, and George D. Stamas, Chief, Division of Occupational Employment Statistics. Laurie Salmon, manager of Publications and Analysis in Occupational Employment Statistics, provided planning and day-to-day direction. Dina Itkin and Rebecca Keller coordinated the production of the chart book. The tables, charts, and maps were prepared by Benjamin Cover, Jeffrey Holt, Dina Itkin, John Jones, Rebecca Keller, Clayton Lindsay, Michael Soloy, Zachary Warren, and Audrey Watson. Cover art, typesetting, and layout were furnished by Keith Tapscott, and editorial services were provided by Casey Homan, Division of Publishing, William Parks II, Chief.

 

Last Modified Date: April 2, 2010