Chart book: Occupational Employment and Wages, May 2009

This chart book, Occupational Employment and Wages, 2009, includes graphs, maps, tables, and text describing the U.S. occupational workforce in May 2009. 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, 2009 chart book (complete book as PDF, 7 MB)

Page-by-page breakout:

  • Cover, Preface, Acknowledgments, 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 largest occupations in the United States, May 2009 (HTML) (PDF)
  • Figure 2. Employment and mean wages for the smallest occupations in the United States, May 2009 (HTML) (PDF)
  • Figure 3. Percentile wages for mechanics occupations, May 2009 (HTML) (PDF)
  • Figure 4. Employment and hourly mean wages of largest occupations with wages near the U.S. mean, May 2009 (HTML) (PDF)
  • Figure 5. Hourly mean wages for selected construction trade occupations, May 2009 (HTML) (PDF)
  • Figure 6. Hourly mean wages for selected construction helper occupations, May 2009 (HTML) (PDF)
  • Figure 7. Distribution of employment by wage range for selected occupations, May 2009 (HTML) (PDF)
  • Figure 8. Distribution of employment by industry sector for selected occupational groups with high unemployment rates, May 2009 (HTML) (PDF)
  • Figure 9. Distribution of employment by industry sector for selected occupational groups with low unemployment rates, May 2009 (HTML) (PDF)
  • Figure 10. Employment, mean hourly wages, and measures of concentration for selected occupations with high geographic concentrations, May 2009 (HTML) (PDF)
  • Figure 11. Employment, mean hourly wages, and measures of concentration for selected occupations with low geographic concentrations, May 2009 (HTML) (PDF)


  • Industry focus (HTML)

  • Figure 12. Employment and wages for occupations with the largest employment in the electric power generation industry, May 2009 (HTML) (PDF)
  • Figure 13. Employment and wages for occupations with the largest employment in the natural gas distribution industry, May 2009 (HTML) (PDF)
  • Figure 14. Employment of the largest occupations in the heavy and civil engineering construction industry, May 2009 (HTML) (PDF)
  • Figure 15. Mean hourly wages of the largest occupations in the heavy and civil engineering construction industry, May 2009 (HTML) (PDF)
  • Figure 16. Employment and wages for the largest occupations in the private sector (HTML) (PDF)
  • Figure 17. Employment and wages for the largest occupations in local government (HTML) (PDF)
  • Figure 18. Employment and wages for the largest occupations in State government (HTML) (PDF)
  • Figure 19. Employment and wages for the largest occupations in Federal Government (HTML) (PDF)
  • Figure 20. Employment shares of selected teaching occupations in elementary and secondary schools by ownership, May 2009 (HTML) (PDF)
  • Figure 21. Wages of selected teaching occupations in elementary and secondary schools by ownership, May 2009 (HTML) (PDF)
  • Figure 22. Industries with the highest employment concentrations for selected occupations, May 2009 (HTML) (PDF)
  • Figure 23. Employment and hourly mean wages for the largest occupations in the newspaper, periodical, book, and directory publishers industry, May 2009 (HTML) (PDF)


  • State and area focus (HTML)

  • Figure 24. Figure 24 Employment in production occupations, per 1,000 jobs, by State, May 2009 (HTML) (PDF)
  • Figure 25. Mean annual wage of production occupations by State, May 2009 (HTML) (PDF)
  • Figure 26. Employment concentrations for select occupations in the Gulf States, May 2009 (HTML) (PDF)
  • Figure 27. States with the highest concentrations of selected occupations, May 2009 (HTML) (PDF)
  • Figure 28. States with the highest concentrations in each engineering occupation, May 2009 (HTML) (PDF)
  • Figure 29. Employment in architecture and engineering occupations, per 1,000 jobs, by area, May 2009 (HTML) (PDF)
  • Figure 30. Mean annual wage of architecture and engineering occupations, by area, May 2009 (HTML) (PDF)
  • Figure 31. Employment by occupational group in the New Orleans-Metairie-Kenner, LA, area, May 2005 and May 2009 (HTML) (PDF)
  • Figure 32. Occupations in the New Orleans-Metairie-Kenner, LA, area, with large declines in employment between May 2005 to May 2009 (HTML) (PDF)
  • Figure 33. Hourly mean wages for occupational groups in the New York metropolitan divisions (HTML) (PDF)
  • Figure 34. Wages of selected occupations in New York-Northern New Jersey-Long Island, NY-NJ-PA, metropolitan statistical area divisions, May 2009 (HTML) (PDF)
  • Figure 35. Distribution of employment in Palm Coast, FL; Weirton-Steubenville, WV-OH; and the United States, by occupational group, May 2009 (HTML) (PDF)
  • Figure 36. Hourly mean wages in Palm Coast, FL; Weirton-Steubenville, WV-OH; and the United States, by occupational group, May 2009 (HTML) (PDF)
  • Figure 37. Employment shares for selected occupations in Palm Coast, FL, and the United States, May 2009 (HTML) (PDF)
  • Figure 38. Employment shares for selected occupations in Weirton-Steubenville, WV-OH, and the United States, May 2009 (HTML) (PDF)
  • Figure 39. Distribution of employment in metropolitan and nonmetropolitan areas, by occupational groups, May 2009 (HTML) (PDF)
  • Figure 40. Occupations with the highest concentration of employment in metropolitan areas, May 2009 (HTML) (PDF)
  • Figure 41. Occupations found primarily in nonmetropolitan areas, May 2009 (HTML) (PDF)
  • Figure 42. Occupations with the largest percentage wage differences between metropolitan and nonmetropolitan areas, May 2009 (HTML) (PDF)


Preface

This chartbook, Occupational Employment and Wages, 2009, 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 334 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 2006 and May 2009. Wage data for all establishments were updated to the May 2009 reference period, and employment data were updated to the average of the November 2008 and the May 2009 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.

Data users can create customized tables using the OES database search tool, or download complete OES data in zipped Excel format from www.bls.gov/oes/oes_dl.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 OESinfo@bls.gov.

Organization of charts and applications of OES data

The presentation of figures in this chartbook is intended to demonstrate a variety of applications of OES data. Figures are organized into four categories: the first focuses on detailed occupations, the second highlights patterns of specific industries, and the third and fourth focus on labor markets of States and local areas.

Some examples of useful applications of OES data:

  • Detailed occupational data can be used by jobseekers 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 jobseekers 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 statistics 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—the mix of employment by occupation in a particular geographic area or industry—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 different 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 levels of 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 in some of the figures is the average employment for May 2009 and November 2008. Employment is defined for the OES survey 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 whether the employees work part time or full time. 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 2009 survey was 78.2 percent based on establishments and 74.5 percent based on employment. More information on sampling and estimation methodology can be found in the survey methods and reliability statement on the OES Web site at www.bls.gov/oes/current/methods_statement.pdf.

Acknowledgments

The information in this chartbook is possible due to the 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 chartbook with contributions from Benjamin Cover, John Jones, Joe Kane, Clayton Lindsay, Laurie Salmon, Michael Soloy, George Stamas, Zachary Warren, and Audrey Watson. Cover art, typesetting, and layout were performed by Bruce Boyd and editorial services were provided by Maureen Soyars, both in the Office of Publications and Special Studies.

 

Last Modified Date: June 13, 2013