News Release Information

12-1934-KAN

Wednesday, September 19, 2012

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Technical information:
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  • (816) 285-7000

Occupational Employment and Wages in Boulder, May 2011


Workers in the Boulder Metropolitan Statistical Area had an average (mean) hourly wage of $25.84 in May 2011, about 19 percent above the nationwide average of $21.74, according to the U.S. Bureau of Labor Statistics. Regional Commissioner Stanley W. Suchman noted that, after testing for statistical significance, wages in the local area were significantly higher than their respective national averages in 13 of the 22 major occupational groups, including life, physical, and social science; sales and related; and health care support.

When compared to the nationwide distribution, local employment was more highly concentrated in 7 of the 22 occupational groups, including computer and mathematical; life, physical, and social science; and architecture and engineering. Conversely, nine groups had employment shares significantly below their national representation, including transportation and material moving, construction and extraction, and office and administrative support. (See table A and box note at end of release.)

Table A. Occupational employment and wages by major occupational group, United States and the Boulder Metropolitan Statistical Area, and measures of statistical significance, May 2011
Major occupational group Percent of total employment Mean hourly wage
United States Boulder United States Boulder Percent difference (1)

Total, all occupations

100.0% 100.0% $21.74 $25.84* 19

Management

4.8 4.8 51.64 59.11* 14

Business and financial operations

4.8 6.4* 33.05 35.12* 6

Computer and mathematical

2.7 7.5* 37.85 42.00* 11

Architecture and engineering

1.8 3.6* 37.08 42.14* 14

Life, physical, and social science

0.8 3.0* 32.44 42.11* 30

Community and social services

1.5 1.4 21.07 20.92 -1

Legal

0.8 0.7 47.30 42.39 -10

Education, training, and library

6.6 6.9* 24.46 25.41 4

Arts, design, entertainment, sports, and media

1.3 2.3* 25.89 23.80* -8

Healthcare practitioner and technical

5.9 5.3 34.97 35.75 2

Healthcare support

3.1 2.2* 13.16 15.61* 19

Protective service

2.5 1.4* 20.54 21.63 5

Food preparation and serving related

8.7 9.7* 10.30 11.23* 9

Building and grounds cleaning and maintenance

3.3 2.6* 12.29 13.41* 9

Personal care and service

2.8 2.6 11.84 13.92* 18

Sales and related

10.6 10.8 18.04 21.59* 20

Office and administrative support

16.7 15.3* 16.40 17.76* 8

Farming, fishing, and forestry

0.3 0.2* 11.68 14.84* 27

Construction and extraction

3.9 2.2* 21.46 20.25* -6

Installation, maintenance, and repair

3.9 2.7* 20.86 21.36 2

Production

6.5 5.3* 16.45 17.67* 7

Transportation and material moving

6.7 3.4* 15.96 18.38 15

Footnotes:
(1) A positive percent difference measures how much the mean wage in Boulder is above the national mean wage, while a negative difference reflects a lower wage.
* The percent share of employment or mean hourly wage for this area is significantly different from the national average of all areas at the 90-percent confidence level.

One occupational group—computer and mathematical—was chosen to illustrate the diversity of data available for any of the 22 major occupational categories. Boulder had 11,600 jobs in computer and mathematical, accounting for 7.5 percent of local area employment, significantly higher than the 2.7-percent share nationally. The average hourly wage for this occupational group locally was $42.00, measurably above the national wage of $37.85.

With employment of 3,530, applications software developers was the largest occupation within the computer and mathematical group, followed by computer support specialists (2,300) and systems software developers (1,760). Among the higher paying jobs were network and computer systems administrators and systems software developers, with mean hourly wages of $48.95 and $47.68, respectively. At the lower end of the wage scale were computer support specialists ($29.14) and operations research analysts ($39.95). (Detailed occupational data for computer and mathematical are presented in table 1; for a complete listing of detailed occupations available go to www.bls.gov/oes/2011/may/oes_14500.htm.)

Location quotients allow us to explore the occupational make-up of a metropolitan area by comparing the composition of jobs in an area relative to the national average. (See table 1.) For example, a location quotient of 2.0 indicates that an occupation accounts for twice the share of employment in the area than it does nationally. In the Boulder Metropolitan Statistical Area, above average concentrations of employment were found in many of the occupations within the computer and mathematical group. For instance, applications software developers were employed at 5.4 times the national rate in Boulder, and computer support specialists, at 3.0 times the U.S. average. A location quotient close to 1.0 indicates that the occupation's local and national employment shares were similar.

These statistics are from the Occupational Employment Statistics (OES) survey, a federal-state cooperative program between BLS and State Workforce Agencies, in this case, the Colorado Department of Labor & Employment. The OES survey provides estimates of employment and hourly and annual wages for wage and salary workers in 22 major occupational groups and nearly 800 detailed occupations for the nation, states, metropolitan statistical areas, metropolitan divisions, and nonmetropolitan areas.

OES wage and employment data for the 22 major occupational groups in the Boulder Metropolitan Statistical Area were compared to their respective national averages based on statistical significance testing. Only those occupations with wages or employment shares above or below the national wage or share after testing for significance at the 90-percent confidence level meet the criteria.

NOTE: A value that is statistically different from another does not necessarily mean that the difference has economic or practical significance. Statistical significance is concerned with the ability to make confident statements about a universe based on a sample. It is entirely possible that a large difference between two values is not significantly different statistically, while a small difference is, since both the size and heterogeneity of the sample affect the relative error of the data being tested.


Technical Note

The Occupational Employment Statistics (OES) survey is a semiannual mail survey measuring occupational employment and wage rates for wage and salary workers in nonfarm establishments in the United States. Guam, Puerto Rico, and the Virgin Islands also are surveyed, but their data are not included in the national estimates. OES estimates are constructed from a sample of about 1.2 million establishments. Forms are mailed to approximately 200,000 establishments in May and November of each year for a 3-year period. The nationwide response rate for the May 2011 survey was 77.3 percent based on establishments and 73.3 percent based on employment. May 2011 estimates are based on responses from six semiannual panels collected over a 3-year period: May 2011, November 2010, May 2010, November 2009, May 2009, and November 2008. The sample in the Boulder Metropolitan Statistical Area included 2,049 establishments with a response rate of 76 percent. For more information about OES concepts and methodology, go to www.bls.gov/news.release/ocwage.tn.htm.

The May 2011 OES estimates mark the first set of estimates based in part on data collected using the 2010 Standard Occupational Classification (SOC) system. Nearly all the occupations in this release are 2010 SOC occupations; however, some are not. The May 2012 OES data will reflect the full set of detailed occupations in the 2010 SOC. For a list of all occupations, including 2010 SOC occupations, and how data collected on two structures were combined, see the OES Frequently Asked Questions online at www.bls.gov/oes/oes_ques.htm#Ques41.

Area definitions The substate area data published in this release reflect the standards and definitions established by the U.S. Office of Management and Budget.

The Boulder, Colo. Metropolitan Statistical Area includes Boulder County.

Additional information

OES data are available on our regional web page at www.bls.gov/ro7/home.htm. If you have additional questions, contact the Mountain-Plains Economic Analysis and Information Unit at (816) 285-7000. Information in this release will be made available to sensory impaired individuals upon request. Voice phone: (202) 691-5200; TDD message referral phone number: 1 (800) 877-8339.

Table 1. Employment and wage data from the Occupational Employment Statistics survey, by occupation, Boulder Metropolitan Statistical Area, May 2011
Occupation (1) Employment Mean wages
Level (2) Location quotient (3) Hourly Annual(4)

Computer and Mathematical Occupations

11,6002.8$42.00$87,350

Computer and Information Research Scientists

1203.944.1691,850

Computer Systems Analysts

7901.340.6984,640

Software Developers, Applications

3,5305.443.9291,350

Software Developers, Systems Software

1,7603.747.6899,170

Database Administrators

2702.043.4890,450

Network and Computer Systems Administrators*

9602.348.95101,810

Computer Support Specialists

2,3003.029.1460,610

Information Security Analysts, Web Developers, and Computer Network Architects

5401.642.3288,030

Computer Occupations, All Other*

6703.143.2089,850

Operations Research Analysts

1301.639.9583,100

Statisticians

401.241.5986,510

Footnotes:
(1) For a complete listing of all detailed occupations in Boulder, see www.bls.gov/oes/current/oes_14500.htm.
(2) Estimates for detailed occupations do not sum to the totals because the totals include occupations not shown separately. Estimates do not include self-employed workers.
(3) The location quotient is the ratio of the area concentration of occupational employment to the national average concentration. A location quotient greater than one indicates the occupation has a higher share of employment than average, and a location quotient less than one indicates the occupation is less prevalent in the area than average.
(4) Annual wages have been calculated by multiplying the hourly mean wage by a ‘year-round, full-time’ hours figure of 2,080 hours; for those occupations where there is not an hourly mean wage published, the annual wage has been directly calculated from the reported survey data.

* Occupation titles followed by an asterisk (*) have similar titles, but not necessarily the same content as 2010 SOC occupations.

 

Last Modified Date: September 19, 2012