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Audrey Watson
United States workers held over 130 million jobs in May 2013—but what kind of jobs were they? Over 21 million were office and administrative support jobs, including 2.8 million general office clerks and 2.4 million customer service representatives. Another 14 million jobs were in sales occupations, primarily retail salespersons and cashiers, and nearly 12 million jobs were in food service occupations. Although most of the largest occupations were low paying, STEM (science, technology, engineering, and mathematics) jobs and other occupations requiring postsecondary education often had much higher wages. This Spotlight on Statistics uses data from the Occupational Employment Statistics program to provide an overview of occupational employment and wages in May 2013, with an emphasis on STEM jobs and occupational data by typical entry-level education required.
Occupation | Employment (millions) |
---|---|
Retail salespersons | 4.5 |
Cashiers | 3.3 |
Combined food preparation and serving workers, including fast food | 3.0 |
Office clerks, general | 2.8 |
Registered nurses | 2.7 |
Waiters and waitresses | 2.4 |
Customer service representatives | 2.4 |
Laborers and freight, stock, and material movers, hand | 2.3 |
Secretaries and administrative assistants, except legal, medical, and executive | 2.2 |
Janitors and cleaners, except maids and housekeeping cleaners | 2.1 |
Ten occupations accounted for more than 1 in every 5 jobs in May 2013. Two sales occupations—retail salespersons and cashiers—were the largest individual occupations, with employment of 4.5 million and 3.3 million, respectively. The largest occupations also included combined food preparation and serving workers, waiters and waitresses, registered nurses, and general office clerks.
Occupation | Annual mean wage |
---|---|
Retail salespersons | $25,370 |
Cashiers | 20,420 |
Combined food preparation and serving workers, including fast food | 18,880 |
Office clerks, general | 29,990 |
Registered nurses | 68,910 |
Waiters and waitresses | 20,880 |
Customer service representatives | 33,370 |
Laborers and freight, stock, and material movers, hand | 26,690 |
Secretaries and administrative assistants, except legal, medical, and executive | 34,000 |
Janitors and cleaners, except maids and housekeeping cleaners | 25,140 |
All occupations | 46,440 |
Of the 10 largest occupations, only registered nurses had an average wage above the U.S. all-occupations mean of $46,440, and three occupations—combined food preparation and serving workers, including fast food; cashiers; and waiters and waitresses—were among the lowest paying occupations overall.
Occupational group | Employment (millions) | Annual mean wage |
---|---|---|
All occupations | – | $46,440 |
Management | 6.5 | 110,550 |
Business and financial operations | 6.7 | 71,020 |
Computer and mathematical | 3.7 | 82,010 |
Architecture and engineering | 2.4 | 80,100 |
Life, physical, and social science | 1.1 | 69,400 |
Community and social service | 1.9 | 44,710 |
Legal | 1.0 | 99,620 |
Education, training, and library | 8.4 | 51,500 |
Arts, design, entertainment, sports, and media | 1.8 | 55,580 |
Healthcare practitioners and technical | 7.8 | 74,740 |
Healthcare support | 3.9 | 28,300 |
Protective service | 3.3 | 43,510 |
Food preparation and serving related | 11.9 | 21,580 |
Building and grounds cleaning and maintenance | 4.3 | 26,010 |
Personal care and service | 4.0 | 24,710 |
Sales and related | 14.1 | 38,200 |
Office and administrative support | 21.4 | 34,900 |
Farming, fishing, and forestry | 0.4 | 24,330 |
Construction and extraction | 5.1 | 45,630 |
Installation, maintenance, and repair | 5.1 | 44,420 |
Production | 8.8 | 34,930 |
Transportation and material moving | 9.0 | 33,860 |
About 36 percent of jobs were in office and administrative support, sales, or food preparation and serving occupations. The smallest occupational groups included legal occupations and life, physical, and social science occupations, each representing less than 1 percent of total employment.
Food preparation and serving related occupations was the lowest paying occupational group, with an annual mean wage of $21,580. Other low-paying occupational groups included personal care and service and farming, fishing, and forestry. Management, legal, and computer and mathematical occupations were the highest paying occupational groups.
Occupation (1) | Employment |
---|---|
Bookkeeping, accounting, and auditing clerks | 1,586,380 |
Maintenance and repair workers, general | 1,249,080 |
Automotive service technicians and mechanics | 604,990 |
Billing and posting clerks | 493,840 |
Inspectors, testers, sorters, samplers, and weighers | 471,750 |
Welders, cutters, solderers, and brazers | 352,250 |
Dental assistants | 309,540 |
Insurance claims and policy processing clerks | 236,160 |
Loan interviewers and clerks | 213,270 |
Painters, construction and maintenance | 192,890 |
Self-enrichment education teachers | 187,180 |
Dispatchers, except police, fire, and ambulance | 185,270 |
Footnotes: (1) These are occupations with the highest employment among occupations having median wages within 5 percent of the all-occupations median of $35,080. |
Ninety occupations, representing about 10.4 million jobs, had median wages that fell within 5 percent of the all-occupations median of $35,080. Most of these occupations were office and administrative support; construction and extraction; installation, maintenance, and repair; or production occupations. Within these four occupational groups, the largest occupations with median wages near the all-occupations median included bookkeeping, accounting, and auditing clerks; general maintenance and repair workers; and automotive service technicians and mechanics. Dental assistants and self-enrichment education teachers also had wages near the all-occupations median. The median wage represents the wage earned by workers in the middle of the wage distribution, meaning that half of jobs paid less than this amount and the other half paid more.
Occupation | Federal executive branch and postal service | State government | Local government |
---|---|---|---|
Elementary school teachers, except special education | 0 | 7,830 | 1,205,900 |
Teacher assistants | 0 | 37,230 | 891,700 |
Secondary school teachers, except special and career/technical education | 0 | 6,780 | 829,020 |
Police and sheriff's patrol officers | 12,570 | 70,020 | 547,700 |
Substitute teachers | 0 | 5,660 | 560,010 |
Middle school teachers, except special and career/technical education | 0 | 2,360 | 560,730 |
Office clerks, general | 21,510 | 182,140 | 314,710 |
Janitors and cleaners, except maids and housekeeping cleaners | 27,280 | 72,700 | 405,440 |
Secretaries and administrative assistants, except legal, medical, and executive | 19,400 | 128,250 | 337,720 |
Registered nurses | 69,930 | 132,800 | 256,710 |
Local government made up about two-thirds of public sector employment. Five of the 10 occupations with the highest employment in the public sector were teachers or teacher assistants; these occupations were found almost entirely in local government.
Occupation | Federal executive branch and postal service | State government | Local government |
---|---|---|---|
Police and sheriff's patrol officers | 12,570 | 61,190 | 542,450 |
Correctional officers and jailers | 16,340 | 232,350 | 160,980 |
Postal service mail carriers | 307,480 | 0 | 0 |
Firefighters | 7,560 | 5,490 | 275,240 |
Business operations specialists, all other | 165,670 | 54,770 | 39,370 |
Office clerks, general | 21,510 | 62,480 | 174,480 |
Secretaries and administrative assistants, except legal, medical, and executive | 19,400 | 50,940 | 109,660 |
Maintenance and repair workers, general | 17,270 | 21,320 | 110,090 |
Registered nurses | 69,930 | 37,760 | 37,550 |
Highway maintenance workers | 40 | 38,340 | 94,680 |
If state and local government schools and hospitals are excluded, the occupations with the highest public sector employment included police and sheriff’s patrol officers, correctional officers and jailers, postal service mail carriers, and firefighters. Of the occupations shown, only postal service mail carriers and all other business operations specialists were found primarily or entirely in federal government. Correctional officers and jailers was the largest occupation in state government, and police and sheriff’s patrol officers was the largest occupation in local government.
Typical entry level education | Employment | Percent of total employment |
---|---|---|
Less than high school | 36,116,050 | 27.2 |
High school diploma or equivalent | 51,519,730 | 38.9 |
Some college, no degree | 1,909,330 | 1.4 |
Postsecondary nondegree award | 7,874,230 | 5.9 |
Associate's degree | 5,719,860 | 4.3 |
Bachelor's degree | 23,829,150 | 18.0 |
Master's degree | 2,214,480 | 1.7 |
Doctoral or professional degree | 3,405,980 | 2.6 |
About 39 percent of employment was in occupations that typically required a high school diploma or the equivalent for entry, and another 27 percent of employment was in occupations that typically required less than a high school diploma for entry. Slightly over one-third of employment was in occupations that typically required some type of postsecondary education for entry, with a bachelor’s degree the most common type of postsecondary education required.
Typical entry-level educational requirements may differ from the educational attainment of workers currently employed in the occupation because, for example, some workers may have more education than is typically required for entry into their occupations, or the requirements for new entrants may be different from the educational attainment of workers already employed in the occupation.
Typical entry level education | Annual mean wage |
---|---|
Less than high school | $23,840 |
High school diploma or equivalent | 41,170 |
Some college, no degree | 35,460 |
Postsecondary nondegree award | 38,810 |
Associate's degree | 60,080 |
Bachelor's degree | 79,590 |
Master's degree | 70,330 |
Doctoral or professional degree | 117,750 |
All occupations | 46,440 |
Average wages were generally higher for occupations that required more education. For example, annual mean wages were $23,840 for occupations typically requiring less than a high school diploma for entry, $41,170 for occupations typically requiring high school or the equivalent, and $60,080 for occupations typically requiring an associate’s degree. However, wages did not always rise with higher educational requirements. For example, occupations in the master’s degree category paid $9,260 less on average than occupations in the bachelor’s degree category. This difference reflects the types of occupations in each educational category. Most of the largest occupations in the master’s degree category were associated with education, health care, or community and social service. A number of these occupations had relatively low wages compared with the types of occupations prevalent in the bachelor’s degree category.
Occupation (1) | Annual mean wage |
---|---|
Transportation, storage, and distribution managers | $91,220 |
First-line supervisors of non-retail sales workers | 82,890 |
First-line supervisors of police and detectives | 82,710 |
Real estate brokers | 82,380 |
Commercial pilots | 80,800 |
Detectives and criminal investigators | 79,030 |
Nuclear power reactor operators | 78,400 |
Power distributors and dispatchers | 76,580 |
Elevator installers and repairers | 76,220 |
Gaming managers | 73,760 |
All high school occupations | 41,170 |
All occupations | 46,440 |
Footnotes: (1) Excludes residual ("all other") occupations. |
The annual mean wage was $41,170 for all occupations typically requiring high school or the equivalent for entry, but some individual occupations in this educational category had much higher wages. Several of these were managerial or supervisory occupations. Other high-paying occupations in this educational category were real estate brokers, commercial pilots, and detectives and criminal investigators. Although these occupations did not typically require postsecondary education for entry, most had other requirements to attain competency, such as work experience in a related field, apprenticeship, or moderate- or long-term on-the-job training. In addition, some of these occupations had relatively low employment. For example, gaming managers, nuclear power reactor operators, and power distributors and dispatchers each had fewer than 12,000 jobs nationwide.
Industry | Percent of industry employment in occupations typically requiring a bachelor's degree for entry |
---|---|
Software publishers | 72.8 |
Computer systems design and related services | 70.3 |
Securities and commodity exchanges | 66.8 |
Securities and commodity contracts intermediation and brokerage | 66.7 |
Other financial investment activities | 64.6 |
Computer and peripheral equipment manufacturing | 64.2 |
Monetary authorities – central bank | 59.7 |
Specialized design services | 59.4 |
Architectural, engineering, and related services | 56.4 |
Elementary and secondary schools | 55.8 |
All industries | 18.0 |
Occupations that typically required a bachelor’s degree for entry represented about 18 percent of all employment, but made up the majority of employment in certain industries. These included three industries related to computers and information technology: software publishers, computer systems design and related services, and computer and peripheral equipment manufacturing. Several financial services industries also had high percentages of occupations typically requiring bachelor’s degrees for entry. The high educational requirements in these industries were reflected in high wages. Except for elementary and secondary schools, all of the industries shown had mean wages significantly higher than the $46,440 average across all industries, including annual means of over $100,000 in both securities and commodity exchanges and securities and commodity contracts intermediation and brokerage.
State | Percent of employment in occupations typically requiring a bachelor's degree for entry | Employment in occupations typically requiring a bachelor's degree for entry | Annual mean wage in occupations typically requiring a bachelor's degree for entry |
---|---|---|---|
Alabama | 15.0% | 277,330 | $70,120 |
Alaska | 18.8 | 60,770 | 82,390 |
Arizona | 18.0 | 446,390 | 72,570 |
Arkansas | 14.1 | 162,280 | 62,160 |
California | 20.3 | 2,989,710 | 91,610 |
Colorado | 20.2 | 463,740 | 80,340 |
Connecticut | 21.7 | 354,330 | 90,500 |
Delaware | 19.4 | 79,820 | 84,470 |
District of Columbia | 32.2 | 214,640 | 99,980 |
Florida | 14.7 | 1,096,600 | 71,030 |
Georgia | 18.9 | 732,500 | 76,480 |
Hawaii | 16.5 | 99,520 | 69,450 |
Idaho | 16.7 | 102,330 | 61,780 |
Illinois | 19.4 | 1,104,000 | 77,870 |
Indiana | 14.7 | 420,340 | 67,520 |
Iowa | 15.9 | 237,160 | 64,690 |
Kansas | 15.9 | 212,350 | 68,930 |
Kentucky | 14.4 | 257,490 | 66,640 |
Louisiana | 13.6 | 256,200 | 68,360 |
Maine | 16.4 | 95,270 | 64,530 |
Maryland | 22.0 | 557,570 | 87,690 |
Massachusetts | 22.7 | 740,620 | 91,960 |
Michigan | 17.8 | 710,150 | 73,940 |
Minnesota | 19.0 | 511,290 | 78,910 |
Mississippi | 13.3 | 144,470 | 59,330 |
Missouri | 17.3 | 456,540 | 68,330 |
Montana | 14.6 | 64,050 | 57,230 |
Nebraska | 15.7 | 145,690 | 66,320 |
Nevada | 12.7 | 146,390 | 72,980 |
New Hampshire | 17.7 | 109,540 | 77,450 |
New Jersey | 19.2 | 732,030 | 90,120 |
New Mexico | 17.2 | 134,740 | 68,560 |
New York | 19.6 | 1,688,300 | 94,450 |
North Carolina | 16.3 | 643,750 | 74,750 |
North Dakota | 14.0 | 59,250 | 65,550 |
Ohio | 17.1 | 875,170 | 72,790 |
Oklahoma | 16.1 | 251,550 | 66,440 |
Oregon | 18.3 | 300,470 | 71,930 |
Pennsylvania | 16.5 | 928,560 | 76,770 |
Rhode Island | 18.3 | 83,670 | 83,420 |
South Carolina | 15.0 | 273,260 | 66,480 |
South Dakota | 14.2 | 57,110 | 59,950 |
Tennessee | 15.3 | 414,370 | 69,920 |
Texas | 17.3 | 1,890,090 | 79,050 |
Utah | 18.2 | 225,680 | 68,500 |
Vermont | 18.2 | 54,340 | 65,310 |
Virginia | 22.3 | 808,730 | 86,260 |
Washington | 21.0 | 593,320 | 84,690 |
West Virginia | 13.7 | 96,890 | 59,310 |
Wisconsin | 15.8 | 427,640 | 68,910 |
Wyoming | 14.7 | 41,110 | 64,650 |
The percentage of jobs in occupations typically requiring a bachelor’s degree for entry varied by state, reflecting in part the different mix of industries in each state. Compared with a national average of 18 percent, 32 percent of jobs in the District of Columbia were in occupations that typically required a bachelor’s degree for entry. Massachusetts, Virginia, Maryland, and Connecticut each had between 21 and 23 percent of employment in occupations with this educational requirement. At the other end of the spectrum, four states—West Virginia, Louisiana, Mississippi, and Nevada—each had less than 14 percent of employment in occupations that typically required a bachelor’s degree for entry.
STEM category | Employment (millions) |
---|---|
Computer occupations | 3.6 |
Engineers | 1.5 |
Drafters, engineering technicians, and mapping technicians | 0.7 |
STEM-related management | 0.6 |
STEM-related sales | 0.4 |
Life and physical science technicians | 0.3 |
Life scientists | 0.3 |
Physical scientists | 0.3 |
STEM-related postsecondary teachers | 0.2 |
Architects, surveyors, and cartographers | 0.2 |
Mathematical science occupations | 0.1 |
Note: STEM occupations are defined here to include computer and mathematical, architecture and engineering, and life and physical science occupations; managerial and postsecondary teaching occupations related to these functional areas; and sales occupations requiring scientific or technical knowledge at the postsecondary level. |
There were nearly 8.2 million STEM (science, technology, engineering, and mathematics) jobs, making up about 6.2 percent of total U.S. employment. Computer occupations represented the largest subgroup of STEM occupations, making up about 44 percent of total STEM employment. Engineers was the second-largest STEM subgroup. Mathematical science occupations made up less than 2 percent of total STEM employment. Although other definitions of STEM are possible, the STEM occupations group is defined here to consist of 100 different occupations, including computer and mathematical, architecture and engineering, and life and physical science occupations; managerial and postsecondary teaching occupations related to these functional areas; and sales occupations requiring scientific or technical knowledge at the postsecondary level.
Occupation | Employment |
---|---|
Software developers, applications | 643,830 |
Computer user support specialists | 541,250 |
Computer systems analysts | 507,100 |
Software developers, systems software | 373,510 |
Network and computer systems administrators | 362,310 |
Sales representatives, wholesale and manufacturing, technical and scientific products | 352,830 |
Computer and information systems managers | 319,080 |
Computer programmers | 312,340 |
Civil engineers | 262,170 |
Mechanical engineers | 258,630 |
Note: STEM occupations are defined here to include computer and mathematical, architecture and engineering, and life and physical science occupations; managerial and postsecondary teaching occupations related to these functional areas; and sales occupations requiring scientific or technical knowledge at the postsecondary level. |
Seven of the 10 largest STEM occupations were computer related, including applications software developers, computer user support specialists, and computer systems analysts. Wholesale and manufacturing sales representatives of technical and scientific products was the largest STEM occupation that was not specifically computer related. Civil engineers and mechanical engineers also were among the largest STEM occupations. The smallest STEM occupations (not shown) included mathematical technicians, astronomers, and postsecondary teachers of forest and conservation science, each with employment of less than 2,500.
Occupation | Annual mean wage |
---|---|
Petroleum engineers | $149,180 |
Architectural and engineering managers | 136,540 |
Natural sciences managers | 132,850 |
Computer and information systems managers | 132,570 |
Physicists | 117,040 |
All STEM occupations | 83,940 |
All occupations | 46,440 |
Environmental science and protection technicians, including health | 45,470 |
Biological technicians | 43,710 |
Surveying and mapping technicians | 43,540 |
Forest and conservation technicians | 37,720 |
Agricultural and food science technicians | 37,010 |
Note: STEM occupations are defined here to include computer and mathematical, architecture and engineering, and life and physical science occupations; managerial and postsecondary teaching occupations related to these functional areas; and sales occupations requiring scientific or technical knowledge at the postsecondary level. |
Most STEM occupations were high paying: the annual mean wage for STEM occupations was $83,940, compared with $46,440 for all occupations and $43,980 for non-STEM occupations. Only 5 of the 100 STEM occupations had mean wages that were significantly below the all-occupations average; all of these were technician occupations. The highest paying STEM occupations included petroleum engineers, physicists, and the three STEM-related management occupations. High wages for STEM occupations were explained in part by high educational requirements. Nearly all STEM occupations typically required an associate’s degree or higher for entry; by comparison, occupations requiring an associate’s degree or higher for entry made up only about 27 percent of overall U.S. employment.
Industry | STEM employment as a percentage of industry employment |
---|---|
Computer systems design and related services | 67.0 |
Architectural, engineering, and related services | 64.0 |
Software publishers | 62.3 |
Computer and peripheral equipment manufacturing | 59.4 |
Scientific research and development services | 55.6 |
Data processing, hosting, and related services | 45.2 |
Communications equipment manufacturing | 42.5 |
Navigational, measuring, electromedical, and control instruments manufacturing | 38.0 |
Semiconductor and other electronic component manufacturing | 37.9 |
Aerospace product and parts manufacturing | 32.4 |
All industries | 6.2 |
Note: STEM occupations are defined here to include computer and mathematical, architecture and engineering, and life and physical science occupations; managerial and postsecondary teaching occupations related to these functional areas; and sales occupations requiring scientific or technical knowledge at the postsecondary level. |
Some industries relied heavily on STEM workers, while other industries had very low concentrations of STEM occupations. Industries with the highest concentrations of STEM employment included computer systems design and related services, with STEM occupations making up about two-thirds of industry employment; architectural, engineering, and related services; software publishers; and several "high-tech" manufacturing industries, such as computer and peripheral equipment manufacturing. Industries with the lowest percentages of STEM employment (not shown) included several retail trade and food service industries, child day care services, and nursing care facilities, each with less than 0.1 percent of industry employment in STEM occupations.
Metropolitan area name | STEM occupations as a percentage of total area employment | Employment in STEM occupations |
---|---|---|
Abilene, TX | 3.0% | 1,890 |
Akron, OH | 6.6 | 21,020 |
Albany, GA | 3.4 | 2,000 |
Albany-Schenectady-Troy, NY | 7.6 | 32,280 |
Albuquerque, NM | 7.6 | 28,010 |
Alexandria, LA | 2.8 | 1,690 |
Allentown-Bethlehem-Easton, PA-NJ | 4.8 | 16,090 |
Altoona, PA | 2.5 | 1,420 |
Amarillo, TX | 3.8 | 4,180 |
Ames, IA | 11.7 | 4,840 |
Anchorage, AK | 7.2 | 12,580 |
Anderson, IN | 2.2 | 830 |
Anderson, SC | 2.3 | 1,400 |
Ann Arbor, MI | 11.0 | 22,280 |
Anniston-Oxford, AL | 3.0 | 1,290 |
Appleton, WI | 3.9 | 4,490 |
Asheville, NC | 2.9 | 5,060 |
Athens-Clarke County, GA | 4.5 | 3,490 |
Atlanta-Sandy Springs-Marietta, GA | 7.0 | 162,600 |
Atlantic City-Hammonton, NJ | 3.3 | 4,430 |
Auburn-Opelika, AL | 5.0 | 2,560 |
Augusta-Richmond County, GA-SC | 5.4 | 10,850 |
Austin-Round Rock-San Marcos, TX | 11.3 | 96,360 |
Bakersfield-Delano, CA | 5.3 | 15,320 |
Baltimore-Towson, MD | 8.4 | 107,450 |
Bangor, ME | 3.7 | 2,330 |
Barnstable Town, MA | 3.8 | 3,730 |
Baton Rouge, LA | 5.5 | 20,020 |
Battle Creek, MI | 4.3 | 2,270 |
Bay City, MI | 2.8 | 950 |
Beaumont-Port Arthur, TX | 4.3 | 6,760 |
Bellingham, WA | 4.8 | 3,650 |
Bend, OR | 4.2 | 2,610 |
Billings, MT | 4.6 | 3,800 |
Binghamton, NY | 6.1 | 6,300 |
Birmingham-Hoover, AL | 5.6 | 27,600 |
Bismarck, ND | 5.6 | 3,830 |
Blacksburg-Christiansburg-Radford, VA | 8.5 | 5,400 |
Bloomington, IN | 7.1 | 5,150 |
Bloomington-Normal, IL | 7.3 | 6,350 |
Boise City-Nampa, ID | 7.4 | 19,970 |
Boston-Cambridge-Quincy, MA-NH | 10.6 | 268,330 |
Boulder, CO | 15.7 | 25,580 |
Bowling Green, KY | 3.8 | 2,240 |
Bremerton-Silverdale, WA | 8.8 | 6,830 |
Bridgeport-Stamford-Norwalk, CT | 6.5 | 27,410 |
Brownsville-Harlingen, TX | 1.4 | 1,800 |
Brunswick, GA | 2.2 | 840 |
Buffalo-Niagara Falls, NY | 5.0 | 26,740 |
Burlington, NC | 2.5 | 1,370 |
Burlington-South Burlington, VT | 9.0 | 10,540 |
Canton-Massillon, OH | 3.1 | 5,190 |
Cape Coral-Fort Myers, FL | 2.7 | 5,600 |
Cape Girardeau-Jackson, MO-IL | 2.5 | 1,060 |
Carson City, NV | 6.9 | 1,770 |
Casper, WY | 4.4 | 1,870 |
Cedar Rapids, IA | 8.0 | 11,090 |
Champaign-Urbana, IL | 5.5 | 5,320 |
Charleston, WV | 3.8 | 5,440 |
Charleston-North Charleston-Summerville, SC | 6.3 | 18,460 |
Charlotte-Gastonia-Rock Hill, NC-SC | 6.5 | 56,870 |
Charlottesville, VA | 6.3 | 6,190 |
Chattanooga, TN-GA | 4.1 | 9,330 |
Cheyenne, WY | 5.5 | 2,450 |
Chicago-Joliet-Naperville, IL-IN-WI | 5.9 | 255,060 |
Chico, CA | 2.8 | 1,940 |
Cincinnati-Middletown, OH-KY-IN | 6.7 | 66,320 |
Clarksville, TN-KY | 3.4 | 2,770 |
Cleveland, TN | 3.9 | 1,510 |
Cleveland-Elyria-Mentor, OH | 6.0 | 60,290 |
Coeur d'Alene, ID | 3.8 | 2,020 |
College Station-Bryan, TX | 8.8 | 8,470 |
Colorado Springs, CO | 8.7 | 21,390 |
Columbia, MO | 6.2 | 5,470 |
Columbia, SC | 5.6 | 19,310 |
Columbus, GA-AL | 5.0 | 5,580 |
Columbus, IN | 12.7 | 5,960 |
Columbus, OH | 7.6 | 71,810 |
Corpus Christi, TX | 3.1 | 5,660 |
Corvallis, OR | 15.3 | 5,050 |
Crestview-Fort Walton Beach-Destin, FL | 8.8 | 6,580 |
Cumberland, MD-WV | 3.4 | 1,260 |
Dallas-Fort Worth-Arlington, TX | 7.5 | 228,580 |
Dalton, GA | 3.7 | 2,270 |
Danbury, CT | 4.9 | 3,380 |
Danville, IL | 3.3 | 890 |
Danville, VA | 1.8 | 670 |
Davenport-Moline-Rock Island, IA-IL | 4.7 | 8,480 |
Dayton, OH | 7.8 | 28,750 |
Decatur, AL | 5.0 | 2,640 |
Decatur, IL | 2.4 | 1,160 |
Deltona-Daytona Beach-Ormond Beach, FL | 3.0 | 4,630 |
Denver-Aurora-Broomfield, CO | 9.1 | 116,490 |
Des Moines-West Des Moines, IA | 6.4 | 21,230 |
Detroit-Warren-Livonia, MI | 8.7 | 157,070 |
Dothan, AL | 2.1 | 1,170 |
Dover, DE | 3.9 | 2,380 |
Dubuque, IA | 5.2 | 2,980 |
Duluth, MN-WI | 4.6 | 5,710 |
Durham-Chapel Hill, NC | 14.1 | 39,100 |
Eau Claire, WI | 4.7 | 3,710 |
El Centro, CA | 1.9 | 990 |
El Paso, TX | 2.7 | 7,730 |
Elizabethtown, KY | 4.0 | 1,890 |
Elkhart-Goshen, IN | 3.3 | 3,790 |
Elmira, NY | 2.6 | 940 |
Erie, PA | 3.2 | 4,030 |
Eugene-Springfield, OR | 4.9 | 6,840 |
Evansville, IN-KY | 3.6 | 6,090 |
Fairbanks, AK | 8.3 | 2,950 |
Fargo, ND-MN | 5.2 | 6,760 |
Farmington, NM | 2.9 | 1,440 |
Fayetteville, NC | 3.2 | 3,990 |
Fayetteville-Springdale-Rogers, AR-MO | 5.5 | 11,470 |
Flagstaff, AZ | 5.0 | 2,810 |
Flint, MI | 2.8 | 3,750 |
Florence, SC | 3.7 | 3,000 |
Florence-Muscle Shoals, AL | 2.5 | 1,300 |
Fond du Lac, WI | 4.1 | 1,830 |
Fort Collins-Loveland, CO | 10.2 | 13,940 |
Fort Smith, AR-OK | 2.4 | 2,650 |
Fort Wayne, IN | 4.5 | 9,070 |
Fresno, CA | 3.0 | 9,600 |
Gadsden, AL | 1.1 | 360 |
Gainesville, FL | 6.7 | 8,010 |
Gainesville, GA | 2.7 | 2,020 |
Glens Falls, NY | 1.9 | 1,000 |
Goldsboro, NC | 2.5 | 990 |
Grand Forks, ND-MN | 4.2 | 2,090 |
Grand Junction, CO | 3.3 | 1,910 |
Grand Rapids-Wyoming, MI | 5.6 | 22,090 |
Great Falls, MT | 3.3 | 1,140 |
Greeley, CO | 3.7 | 3,210 |
Green Bay, WI | 5.3 | 8,760 |
Greensboro-High Point, NC | 4.6 | 15,920 |
Greenville, NC | 3.9 | 2,970 |
Greenville-Mauldin-Easley, SC | 6.6 | 20,120 |
Gulfport-Biloxi, MS | 4.4 | 4,440 |
Hagerstown-Martinsburg, MD-WV | 4.6 | 4,620 |
Hanford-Corcoran, CA | 1.8 | 670 |
Harrisburg-Carlisle, PA | 6.7 | 20,580 |
Harrisonburg, VA | 3.2 | 1,890 |
Hartford-West Hartford-East Hartford, CT | 7.9 | 44,320 |
Hattiesburg, MS | 2.5 | 1,420 |
Hickory-Lenoir-Morganton, NC | 2.4 | 3,400 |
Hinesville-Fort Stewart, GA | 4.4 | 740 |
Holland-Grand Haven, MI | 6.9 | 7,300 |
Honolulu, HI | 5.2 | 23,120 |
Hot Springs, AR | 2.3 | 790 |
Houma-Bayou Cane-Thibodaux, LA | 2.4 | 2,330 |
Houston-Sugar Land-Baytown, TX | 8.0 | 221,930 |
Huntington-Ashland, WV-KY-OH | 3.0 | 3,190 |
Huntsville, AL | 16.1 | 33,860 |
Idaho Falls, ID | 4.1 | 2,080 |
Indianapolis-Carmel, IN | 6.8 | 62,120 |
Iowa City, IA | 7.0 | 6,240 |
Ithaca, NY | 4.9 | 2,420 |
Jackson, MI | 6.3 | 3,520 |
Jackson, MS | 3.9 | 9,690 |
Jackson, TN | 2.6 | 1,500 |
Jacksonville, FL | 5.2 | 30,550 |
Jacksonville, NC | 2.4 | 1,050 |
Janesville, WI | 2.8 | 1,720 |
Jefferson City, MO | 6.3 | 4,540 |
Johnson City, TN | 3.8 | 2,920 |
Johnstown, PA | 3.5 | 1,960 |
Jonesboro, AR | 2.0 | 1,000 |
Joplin, MO | 2.8 | 2,160 |
Kalamazoo-Portage, MI | 6.3 | 8,130 |
Kankakee-Bradley, IL | 2.1 | 840 |
Kansas City, MO-KS | 6.9 | 67,640 |
Kennewick-Pasco-Richland, WA | 11.1 | 10,940 |
Killeen-Temple-Fort Hood, TX | 3.6 | 4,660 |
Kingsport-Bristol-Bristol, TN-VA | 4.7 | 5,390 |
Kingston, NY | 2.2 | 1,230 |
Knoxville, TN | 5.7 | 18,550 |
La Crosse, WI-MN | 3.5 | 2,600 |
Lafayette, IN | 6.2 | 5,380 |
Lafayette, LA | 4.9 | 7,610 |
Lake Charles, LA | 3.6 | 3,230 |
Lake Havasu City-Kingman, AZ | 2.6 | 1,150 |
Lakeland-Winter Haven, FL | 3.3 | 6,480 |
Lancaster, PA | 3.6 | 7,940 |
Lansing-East Lansing, MI | 7.6 | 15,000 |
Laredo, TX | 1.8 | 1,670 |
Las Cruces, NM | 6.5 | 4,420 |
Las Vegas-Paradise, NV | 2.7 | 22,560 |
Lawrence, KS | 4.6 | 2,070 |
Lawton, OK | 3.5 | 1,430 |
Lebanon, PA | 2.0 | 990 |
Leominster-Fitchburg-Gardner, MA | 2.7 | 1,240 |
Lewiston, ID-WA | 3.5 | 840 |
Lewiston-Auburn, ME | 2.8 | 1,290 |
Lexington-Fayette, KY | 6.1 | 15,310 |
Lima, OH | 2.7 | 1,300 |
Lincoln, NE | 6.5 | 10,780 |
Little Rock-North Little Rock-Conway, AR | 5.3 | 17,730 |
Logan, UT-ID | 6.0 | 2,970 |
Longview, TX | 2.8 | 2,790 |
Longview, WA | 2.6 | 870 |
Los Angeles-Long Beach-Santa Ana, CA | 6.3 | 339,780 |
Louisville-Jefferson County, KY-IN | 4.4 | 27,020 |
Lubbock, TX | 3.4 | 4,370 |
Lynchburg, VA | 4.8 | 4,660 |
Macon, GA | 3.5 | 3,300 |
Madera-Chowchilla, CA | 2.6 | 990 |
Madison, WI | 10.1 | 34,790 |
Manchester, NH | 6.2 | 6,290 |
Manhattan, KS | 5.8 | 2,890 |
Mankato-North Mankato, MN | 4.3 | 2,050 |
Mansfield, OH | 3.0 | 1,470 |
McAllen-Edinburg-Mission, TX | 1.8 | 4,190 |
Medford, OR | 3.6 | 2,770 |
Memphis, TN-MS-AR | 4.1 | 24,260 |
Merced, CA | 2.2 | 1,320 |
Miami-Fort Lauderdale-Pompano Beach, FL | 3.9 | 89,730 |
Michigan City-La Porte, IN | 2.9 | 1,190 |
Midland, TX | 8.2 | 6,750 |
Milwaukee-Waukesha-West Allis, WI | 6.2 | 50,540 |
Minneapolis-St. Paul-Bloomington, MN-WI | 8.0 | 142,510 |
Missoula, MT | 5.8 | 3,200 |
Mobile, AL | 4.9 | 8,180 |
Modesto, CA | 2.5 | 3,890 |
Monroe, LA | 2.9 | 2,170 |
Monroe, MI | 5.4 | 2,080 |
Montgomery, AL | 5.3 | 8,440 |
Morgantown, WV | 6.4 | 4,030 |
Morristown, TN | 3.0 | 1,300 |
Mount Vernon-Anacortes, WA | 4.2 | 1,800 |
Muncie, IN | 3.8 | 1,680 |
Muskegon-Norton Shores, MI | 3.3 | 1,870 |
Myrtle Beach-North Myrtle Beach-Conway, SC | 1.7 | 1,860 |
Napa, CA | 2.6 | 1,730 |
Naples-Marco Island, FL | 2.1 | 2,510 |
Nashville-Davidson--Murfreesboro--Franklin, TN | 5.3 | 42,180 |
New Bedford, MA | 2.0 | 1,290 |
New Haven, CT | 5.6 | 15,360 |
New Orleans-Metairie-Kenner, LA | 4.3 | 22,490 |
New York-Northern New Jersey-Long Island, NY-NJ-PA | 5.5 | 464,950 |
Niles-Benton Harbor, MI | 4.7 | 2,660 |
North Port-Bradenton-Sarasota, FL | 3.0 | 7,380 |
Norwich-New London, CT-RI | 8.8 | 11,170 |
Ocala, FL | 2.2 | 2,020 |
Ocean City, NJ | 1.1 | 400 |
Odessa, TX | 3.0 | 2,150 |
Ogden-Clearfield, UT | 6.0 | 12,200 |
Oklahoma City, OK | 6.3 | 37,760 |
Olympia, WA | 9.1 | 8,760 |
Omaha-Council Bluffs, NE-IA | 6.2 | 28,380 |
Orlando-Kissimmee-Sanford, FL | 5.0 | 52,240 |
Oshkosh-Neenah, WI | 5.0 | 4,550 |
Owensboro, KY | 2.3 | 1,140 |
Oxnard-Thousand Oaks-Ventura, CA | 7.2 | 21,130 |
Palm Bay-Melbourne-Titusville, FL | 10.9 | 20,760 |
Palm Coast, FL | 2.2 | 420 |
Panama City-Lynn Haven-Panama City Beach, FL | 4.8 | 3,370 |
Parkersburg-Marietta-Vienna, WV-OH | 3.5 | 2,340 |
Pascagoula, MS | 6.3 | 3,370 |
Pensacola-Ferry Pass-Brent, FL | 4.0 | 6,120 |
Peoria, IL | 8.4 | 15,260 |
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 6.8 | 182,180 |
Phoenix-Mesa-Glendale, AZ | 7.1 | 126,810 |
Pine Bluff, AR | 4.2 | 1,400 |
Pittsburgh, PA | 6.4 | 72,520 |
Pittsfield, MA | 5.8 | 1,940 |
Pocatello, ID | 5.0 | 1,670 |
Port St. Lucie, FL | 3.0 | 3,700 |
Portland-South Portland-Biddeford, ME | 5.5 | 10,790 |
Portland-Vancouver-Hillsboro, OR-WA | 8.5 | 86,830 |
Portsmouth, NH-ME | 10.5 | 5,950 |
Poughkeepsie-Newburgh-Middletown, NY | 5.0 | 12,260 |
Prescott, AZ | 2.7 | 1,480 |
Providence-Fall River-Warwick, RI-MA | 5.1 | 27,790 |
Provo-Orem, UT | 7.7 | 14,440 |
Pueblo, CO | 3.2 | 1,770 |
Punta Gorda, FL | 2.7 | 1,110 |
Racine, WI | 3.1 | 2,320 |
Raleigh-Cary, NC | 10.3 | 54,910 |
Rapid City, SD | 4.0 | 2,440 |
Reading, PA | 3.7 | 6,180 |
Redding, CA | 4.1 | 2,320 |
Reno-Sparks, NV | 4.5 | 8,650 |
Richmond, VA | 6.5 | 39,390 |
Riverside-San Bernardino-Ontario, CA | 3.2 | 38,210 |
Roanoke, VA | 3.5 | 5,190 |
Rochester, MN | 8.3 | 8,660 |
Rochester, NY | 6.7 | 33,160 |
Rochester-Dover, NH-ME | 7.7 | 4,120 |
Rockford, IL | 3.5 | 5,020 |
Rocky Mount, NC | 3.5 | 1,890 |
Rome, GA | 2.9 | 1,010 |
Sacramento--Arden-Arcade--Roseville, CA | 8.2 | 68,770 |
Saginaw-Saginaw Township North, MI | 5.9 | 4,820 |
Salem, OR | 4.3 | 6,100 |
Salinas, CA | 2.9 | 4,530 |
Salisbury, MD | 3.2 | 1,640 |
Salt Lake City, UT | 7.3 | 47,180 |
San Angelo, TX | 2.4 | 1,110 |
San Antonio-New Braunfels, TX | 5.1 | 44,990 |
San Diego-Carlsbad-San Marcos, CA | 9.5 | 122,600 |
San Francisco-Oakland-Fremont, CA | 10.7 | 218,660 |
San Jose-Sunnyvale-Santa Clara, CA | 20.4 | 189,990 |
San Luis Obispo-Paso Robles, CA | 5.0 | 5,120 |
Sandusky, OH | 2.7 | 960 |
Santa Barbara-Santa Maria-Goleta, CA | 6.5 | 11,300 |
Santa Cruz-Watsonville, CA | 6.1 | 5,250 |
Santa Fe, NM | 4.9 | 2,890 |
Santa Rosa-Petaluma, CA | 4.7 | 8,230 |
Savannah, GA | 3.7 | 5,690 |
Scranton--Wilkes-Barre, PA | 3.1 | 7,840 |
Seattle-Tacoma-Bellevue, WA | 12.3 | 209,880 |
Sebastian-Vero Beach, FL | 2.8 | 1,300 |
Sheboygan, WI | 5.2 | 2,870 |
Sherman-Denison, TX | 3.3 | 1,360 |
Shreveport-Bossier City, LA | 2.8 | 4,780 |
Sioux City, IA-NE-SD | 2.8 | 2,010 |
Sioux Falls, SD | 4.5 | 6,390 |
South Bend-Mishawaka, IN-MI | 3.9 | 4,810 |
Spartanburg, SC | 4.5 | 5,470 |
Spokane, WA | 4.6 | 9,180 |
Springfield, IL | 4.6 | 4,810 |
Springfield, MA-CT | 4.3 | 12,320 |
Springfield, MO | 3.6 | 6,750 |
Springfield, OH | 3.1 | 1,440 |
St. Cloud, MN | 3.4 | 3,320 |
St. George, UT | 2.5 | 1,240 |
St. Joseph, MO-KS | 2.9 | 1,530 |
St. Louis, MO-IL | 6.3 | 81,910 |
State College, PA | 9.3 | 6,080 |
Steubenville-Weirton, OH-WV | 3.4 | 1,340 |
Stockton, CA | 2.5 | 5,050 |
Sumter, SC | 3.3 | 1,100 |
Syracuse, NY | 5.6 | 16,720 |
Tallahassee, FL | 7.0 | 11,010 |
Tampa-St. Petersburg-Clearwater, FL | 5.4 | 62,110 |
Terre Haute, IN | 3.4 | 2,250 |
Texarkana-Texarkana, TX-AR | 1.8 | 980 |
Toledo, OH | 4.3 | 12,910 |
Topeka, KS | 4.7 | 5,070 |
Trenton-Ewing, NJ | 10.2 | 22,060 |
Tucson, AZ | 7.2 | 25,280 |
Tulsa, OK | 5.0 | 21,210 |
Tuscaloosa, AL | 3.8 | 3,490 |
Tyler, TX | 3.6 | 3,370 |
Utica-Rome, NY | 3.7 | 4,550 |
Valdosta, GA | 2.0 | 970 |
Vallejo-Fairfield, CA | 3.9 | 4,800 |
Victoria, TX | 3.6 | 1,840 |
Vineland-Millville-Bridgeton, NJ | 1.5 | 890 |
Virginia Beach-Norfolk-Newport News, VA-NC | 7.2 | 52,380 |
Visalia-Porterville, CA | 2.1 | 2,760 |
Waco, TX | 4.0 | 4,080 |
Warner Robins, GA | 9.3 | 5,280 |
Washington-Arlington-Alexandria, DC-VA-MD-WV | 12.4 | 362,710 |
Waterbury, CT | 2.8 | 1,790 |
Waterloo-Cedar Falls, IA | 3.4 | 3,050 |
Wausau, WI | 5.3 | 3,480 |
Wenatchee-East Wenatchee, WA | 3.9 | 1,530 |
Wheeling, WV-OH | 2.4 | 1,490 |
Wichita Falls, TX | 2.1 | 1,200 |
Wichita, KS | 6.1 | 17,290 |
Williamsport, PA | 3.8 | 2,010 |
Wilmington, NC | 5.0 | 7,000 |
Winchester, VA-WV | 3.0 | 1,610 |
Winston-Salem, NC | 4.0 | 8,160 |
Worcester, MA-CT | 6.6 | 16,150 |
Yakima, WA | 2.4 | 1,920 |
York-Hanover, PA | 4.0 | 6,950 |
Youngstown-Warren-Boardman, OH-PA | 2.7 | 5,910 |
Yuba City, CA | 3.0 | 1,110 |
Yuma, AZ | 4.6 | 2,690 |
The prevalence of STEM occupations varied geographically. Compared with a national average of 6 percent, over 20 percent of employment in San Jose-Sunnyvale-Santa Clara, California, was in STEM occupations, including high concentrations of computer and information research scientists, electronics engineers, computer hardware engineers, systems software developers, and physicists. Corvallis, Oregon; Boulder, Colorado; and Huntsville, Alabama, each had more than 15 percent of area employment in STEM occupations. STEM jobs made up about 1.5 percent of employment or less in Vineland-Millville-Bridgeton, New Jersey; Brownsville-Harlingen, Texas; Ocean City, New Jersey; and Gadsden, Alabama.
Area | Location quotient | Employment | Annual mean wage |
---|---|---|---|
Midland, TX | 55.5 | 1,210 | 156,510 |
Casper, WY | 18.6 | 210 | 123,070 |
Houston-Sugar Land-Baytown, TX | 17.2 | 12,520 | 163,490 |
Anchorage, AK | 12.3 | 570 | 166,840 |
Oklahoma City, OK | 10.3 | 1,620 | 158,170 |
Bakersfield-Delano, CA | 8.2 | 620 | 129,680 |
Lafayette, LA | 7.2 | 290 | 126,680 |
Tulsa, OK | 7.2 | 800 | 155,670 |
Although some STEM occupations, such as computer user support specialists, were spread more evenly across geographic areas, others were highly geographically concentrated. Just over half of all petroleum engineers were found in the 8 metropolitan areas shown in the chart. Petroleum engineers had a location quotient of nearly 56 in Midland, Texas, indicating that petroleum engineers as a percentage of total employment was 56 times as high in Midland as in the U.S. as a whole. Houston-Sugar Land-Baytown, Texas, had one of the highest concentrations of petroleum engineers as well as the highest absolute number of jobs in this occupation (12,520). High employment concentrations didn’t always indicate high employment levels, however. Although Casper, Wyoming, had a location quotient of 18.6 for petroleum engineers, this translated into only 210 jobs.
Occupation | Percent of occupation's employment in nonmetropolitan areas |
---|---|
Mine shuttle car operators | 74.3 |
Loading machine operators, underground mining | 73.5 |
Logging equipment operators | 71.3 |
Log graders and scalers | 69.9 |
Fallers | 69.8 |
Roof bolters, mining | 63.3 |
Logging workers, all other | 61.4 |
Continuous mining machine operators | 60.4 |
Mine cutting and channeling machine operators | 59.2 |
Forest and conservation technicians | 56.2 |
All occupations | 13.1 |
About 13 percent of all nonfarm employment was found in nonmetropolitan areas, but nonmetropolitan areas accounted for the majority of employment in certain occupations. Most of the occupations found primarily in nonmetropolitan areas were associated with mining or logging. For example, 74 percent of both mine shuttle car operators and underground mining loading machine operators and 63 percent of mining roof bolters were employed in nonmetropolitan areas. Logging occupations found primarily in nonmetropolitan areas included logging equipment operators, log graders and scalers, and fallers. Outside of mining- and logging-related occupations, the occupations most concentrated in nonmetropolitan areas included slaughterers and meat packers and postmasters and mail superintendents (not shown).
Occupation | Percent of occupation's employment in large metropolitan areas |
---|---|
Political scientists | 81.9 |
Fashion designers | 79.3 |
Actors | 76.7 |
Flight attendants | 76.6 |
Makeup artists, theatrical and performance | 71.5 |
Agents and business managers of artists, performers, and athletes | 70.4 |
Subway and streetcar operators | 68.8 |
Media and communication workers, all other | 67.7 |
Film and video editors | 67.5 |
Economists | 66.4 |
All occupations | 34.6 |
Fifteen metropolitan areas had employment of over 1.5 million each in May 2013. These large metropolitan areas made up about 35 percent of total U.S. employment, but an even higher percentage of employment in some occupations. Several of the occupations concentrated in the largest metropolitan areas were related to arts, design, and entertainment, including fashion designers, actors, theatrical and performance makeup artists, and business managers of artists, performers, and athletes. New York-Northern New Jersey-Long Island, New York-New Jersey-Pennsylvania, and Los Angeles-Long Beach-Santa Ana, California, accounted for the majority of employment in these four occupations. Two social science occupations—political scientists and economists—also were concentrated in the largest metropolitan areas, with Washington-Arlington-Alexandria, D.C.-Va.-Md.-W.Va., having the highest employment of both occupations.
Audrey Watson is an economist in the Division of Occupational Employment Statistics, U.S. Bureau of Labor Statistics. Email: watson.audrey@bls.gov.
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. OES data available from BLS include cross-industry occupational employment and wage estimates for the nation; over 600 areas, including states and the District of Columbia, metropolitan statistical areas (MSAs), metropolitan divisions, nonmetropolitan areas, and territories; national industry-specific estimates at the NAICS sector, 3-, 4-, and selected 5- and 6-digit industry levels; and national estimates by ownership across all industries and for schools and hospitals. Some of the data used in this Spotlight for employment and wages by typical entry-level education required, STEM occupations, and nonmetropolitan and large metropolitan areas are based on special tabulations of the May 2013 OES data. Publicly available OES data can be found on the OES home page at www.bls.gov/oes/.
Estimates by typical entry-level education required are based on education and training categories assigned by the BLS Employment Projections program.
This Spotlight uses one of many possible definitions of STEM occupations. Guidance on alternative definitions can be found at www.bls.gov/soc/home.htm#crosswalks.
The STEM data used in this Spotlight are available as a downloadable XLS spreadsheet at www.bls.gov/oes/stem_13.xls.
For more information on STEM occupations, see Science, technology, engineering, and mathematics (STEM) occupations: a visual essay and An overview of employment and wages in science, technology, engineering, and math (STEM) groups.
More information on the geographic distribution of occupations is available in the following articles: