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: December 29, 2010