April 2011 

Occupational Employment 

Statistics (OES) Highlights

Using Location Quotients to Analyze 

Occupational Data 

Montana employed bartenders at 3 times the national rate in May 2009, Delaware 

employed chemists at nearly 8 times the national rate, fast food cooks were 3 times 

as concentrated in Mississippi as in other parts of the country, and computer 

software engineers were more than twice as prevalent in Virginia as elsewhere. 

These comparisons are easily made through the use of location quotients. 

Las Vegas, Paradise,

NV

Rapid City, SD

Logan, UT‐ID

Kankakee‐Bradley, IL

Panama City‐Lynn

Haven, FL

Napa, CA

Gary, IN

Huntsville, AL

Odessa, TX

Atlantic City, NJ

0 10 20 30 40 50

Janitors and cleaners, except maids and housekeeping

cleaners

Receptionists and information clerks

Dental assistants

Cashiers

Dishwashers

Massage therapists

Metal‐refining furnace operators and tenders

Aerospace engineers

Roustabouts, oil and gas

Gaming managers

Highest location quotient

Chart 1. Highest location quotients for selected occupations, May 2009
2 

Some familiar and some not-so-familiar patterns emerge when looking at location 

quotient data. For example, the areas with the highest location quotients for several 

gaming occupations included Atlantic City and several areas in Nevada. Atlantic City 

and Las Vegas also had among the highest concentrations of bartenders, as did 

areas in the northern states of Montana, Wisconsin, North Dakota, and Minnesota. 

Areas that tend to be tourist destinations had higher location quotients for leisurerelated occupations, such as high concentrations of restaurant cooks in Nantucket 

and Martha’s Vineyard and massage therapists in Napa, CA. Palm Bay-MelbourneTitusville, FL, the home of Kennedy Space Center, had one of the highest location 

quotients for aerospace engineers, while areas in Michigan, Indiana, and Ohio had 

high location quotients for several production occupations. 

Location quotients are useful for studying the composition of jobs in an area relative 

to the average, or for finding areas that have high concentrations of jobs in certain 

occupations. As measured here, a location quotient shows the occupation’s share of 

an area’s employment relative to the national average. 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, and a location quotient of 0.5 

indicates the area’s share of employment in the occupation is half the national share. 

For instance, home health aides accounted for nearly 2 percent of employment in 

North Carolina in May 2009, but less than 1 percent of employment in the United 

States, giving the occupation a location quotient of more than 2 in North Carolina. 

Location quotients show how occupations are spread out across the country. The 

location quotients for some occupations clustered around 1.0, indicating that they 

were found in similar proportions in most areas. For example, the location quotients 

for janitors ranged from 0.5 to 1.6, and those for receptionists and information clerks 
3 

ranged from 0.5 to 1.7. (Chart 1; see page 11 to view the data in table format.) 

Other occupations with relatively even geographic distributions included dental 

assistants, cashiers, and dishwashers. 

Other occupations were more concentrated and had very high location quotients in 

some areas. These were often occupations directly related to industries that are 

geographically concentrated. For example, the employment share of textile knitting 

and weaving machine setters, operators, and tenders in Dalton, GA, was nearly 197 

times the national average; this area also had high location quotients for several 

other textile and apparel production occupations, as did other southern areas such as 

Hickory-Lenoir-Morganton, NC; Anderson, SC; and Greensboro-High Point, NC. 

Some of the occupations with the highest location quotients were associated with 

geographical features such as waterways or natural resource deposits. For example, 

Houma-Bayou Cane-Thibodaux, LA, had very high location quotients for several 

water transportation occupations, including ship engineers, with a location quotient 

of 91; sailors and marine oilers, with a location quotient of 114; and captains, mates, 

and pilots of water vessels, with a location quotient of 150. Similarly, occupations 

associated with mining or oil and gas extraction tended to have very high location 

quotients in some areas. Charleston, WV, had location quotients of 52 for mine 

cutting and channeling machine operators and 66 for mining roof bolters, while 

Odessa, TX, had high concentrations of several oil-related occupations, including 

location quotients of 29 and 58, respectively, for roustabouts and oil, gas, and 

mining service unit operators. 

In some cases, more complex patterns emerge. Chart 2 shows employment and 

location quotients for brokerage clerks in the largest metropolitan areas in the United 
4 

States. In general, areas with higher employment of brokerage clerks also had 

higher location quotients for this occupation, suggesting that there is some 

advantage to having large numbers of workers in this financial services occupation 

clustered together. Because the location quotients control for area size, we might 

expect that an occupation’s employment would not be correlated with the size of the 

area. However, although the relationship was not extremely strong, brokerage clerks 

also were somewhat more likely to be employed in areas with higher overall 

employment. 

Some occupations had higher location quotients in smaller areas, such as purchasing 

agents and buyers of farm products, which were somewhat more likely to be 

concentrated in areas with low total employment. In this case, there was no 

correlation between an area’s location quotient and employment of this specific 

occupation: because areas with low overall employment also tend to have low 

employment of most individual occupations, many of the areas with high 

concentrations of purchasing agents and buyers of farm products had relatively low 

employment levels for this occupation. For example, Sioux City, IA-NE-SD, had an 

employment concentration of nearly 8 times the U.S. average for purchasing agents 

and buyers of farm products, but had employment of only 50 in this occupation. In 

contrast, the much larger New York-Northern New Jersey-Long Island, NY-NJ-PA, 

metropolitan area employed over 500 purchasing agents and buyers of farm 

products, but had a location quotient of 0.7 for this occupation. 
5 

(See page 11 to view these data in table format.) 

A closer look at two areas—Durham, NC, and Columbus, IN—is provided in charts 3 

and 4. Durham, in the heart of North Carolina’s Research Triangle, had high location 

quotients for several life science occupations, including soil and plant scientists, 

microbiologists, biochemists and biophysicists, medical scientists, and 

epidemiologists. This area also had high concentrations of other occupations 

associated with scientific research, including natural sciences managers and 

statisticians, as well as computer systems software engineers and several other 

computer occupations not shown in the chart. 

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

8,000,000

9,000,000

10,000,000

012345

Total area employment

Location quotient

Chart 2. Employment and location quotients for brokerage

clerks in major U.S. metropolitan areas, May 2009

Chicago‐Naperville‐Joliet, IL‐IN‐

WI

Dallas‐Fort Worth‐Arlington, TX

Detroit‐Warren‐Livonia, MI

Los Angeles‐Long Beach‐Santa

Ana, CA

Miami‐Fort Lauderdale‐Miami

Beach, FL

New York‐Northern New Jersey‐

Long Island, NY‐NJ‐PA

Philadelphia‐Camden‐

Wilmington, PA‐NJ‐DE‐MD

San Francisco‐Oakland‐Fremont,

CA

Seattle‐Tacoma‐Bellevue, WA

Washington‐Arlington‐

Alexandria, DC‐VA‐MD‐WV

Boston‐Cambridge‐Quincy, MA‐

NH

Note: Bubble size indicates employment of brokerage clerks in area.
6 

 (See page 12 to view these data in table format.) 

Columbus, IN, had high location quotients for a number of production occupations, 

including team assemblers; tool and die makers; inspectors, testers, sorters, 

samplers, and weighers; and several metal and plastic worker occupations. In 

addition, this area had high concentrations of several occupations associated with the 

design and engineering stages of the manufacturing process: the concentration of 

mechanical engineers was over 12 times the U.S. average, while both industrial 

engineers and mechanical drafters had concentrations nearly 7 times the U.S. 

average. 

0 2 4 6 8 10 12 14 16

Epidemiologists

Chemists

Computer software engineers, systems software

Operations research analysts

Medical scientists, except epidemiologists

Biochemists and biophysicists

Statisticians

Natural sciences managers

Microbiologists

Soil and plant scientists

Location quotient

Chart 3. Location quotients for selected occupations in

Durham, NC, May 2009
7 

(See page 12 to view these data in table format.) 

Chart 5 shows location quotients for bartenders and substance abuse and behavioral 

disorder counselors in various states. As mentioned above, Montana had the highest 

location quotient for bartenders, at 3.3 times the national average. Montana also had 

the fourth highest location quotient for substance abuse and behavioral disorder 

counselors. Several other states had location quotients in the top 10 for both 

bartenders and substance abuse and behavioral disorder counselors, including South 

Dakota, Oregon, and Vermont. However, there are exceptions, such as Nevada, 

where the location quotient for substance abuse and behavioral disorder counselors 

was smaller than every other state except West Virginia at 0.37. 

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Inspectors, testers,sorters, samplers, and weighers

Tool and die makers

Team assemblers

Heat treating equipment setters, operators, and tenders,

metal and plastic

Cutting, punching, and press machine setters, operators,

and tenders, metal and plastic

Mechanical drafters

Industrial engineers

Drilling and boring machine tool setters, operators, and

tenders, metal and plastic

Lathe and turning machine tool setters, operators, and

tenders, metal and plastic

Mechanical engineers

Location quotient

Chart 4. Location quotients for selected occupations in

Columbus, IN, May 2009
8 

(See page 12 to view these data in table format.) 

Location quotients can also help explain wage differences among areas. The 

composition of employment in an area influences the average wage in that area. All 

else equal, areas with higher employment shares of lower paid occupations such as 

fast food cooks and cashiers will tend to have lower average wages, in part because 

the concentration of employment in these occupations helps bring down the average 

area wage. The correlation coefficient on the share of fast food cooks in a state and 

the state’s cross-occupation wage was –.44, indicating that, generally, areas with 

higher concentrations of fast food cooks had lower average wages. (See chart 6.) 

0 0.5 1 1.5 2 2.5 3 3.5

Vermont

Oregon

Minnesota

South Dakota

Rhode Island

Wyoming

North Dakota

Wisconsin

Nevada

Montana

Location Quotient

Chart 5. Location quotients for bartenders and substance abuse and

behavioral disorder counselors in selected states, May 2009

Substance

abuse and

behavioral

disorder

counselors

Bartenders
9 

Areas with greater concentrations of higher paying occupations such as financial 

managers and biochemists and biophysicists tended to have higher cross-occupation 

wages. For example, states with high shares of business and financial operations 

occupations and computer and mathematical science occupations also tended to 

have higher wages: average cross-occupation wages and employment shares in 

these occupations were correlated with coefficients of 0.85 and 0.76, respectively. 

Other occupations that tended to be more concentrated in higher wage areas were 

arts, design, entertainment, sports, and media occupations. 

(See page 13 to view these data in table format.) 

$15.00

$17.00

$19.00

$21.00

$23.00

$25.00

$27.00

0.0 0.5 1.0 1.5 2.0 2.5 3.0

All‐occupations hourly mean wage

Location quotients for fast food cooks

Chart 6. State all‐occupations hourly mean wages and

location quotients for fast food cooks, May 2009
10 

The location quotients used in this highlight were calculated from May 2009 

Occupational Employment Statistics; location quotients for all occupations and areas 

are available at ftp://ftp.bls.gov/pub/special.requests/oes/oes09loc.zip. Complete 

May 2009 OES data are available from the OES home page at www.bls.gov/oes. This 

highlight was prepared by Ben Cover. For more information, please contact the OES 

program at www.bls.gov/oes/home.htm#contact. 

 
11 

Table 1. Highest location quotients for selected occupations, May 2009 

Occupation MSA Location 

Quotient 

Janitors and cleaners, except maids and 

housekeeping cleaners 

Las Vegas-Paradise, NV 1.64

Receptionists and information clerks Rapid City, SD 1.75

Dental assistants Logan, UT-ID 2.34

Cashiers Kankakee-Bradley, IL 2.65

Dishwashers Panama City-Lynn Haven, FL 2.73

Massage therapists Napa, CA 10.84

Metal-refining furnace operators and tenders Gary, IN 18.54

Aerospace engineers Huntsville, AL 19.83

Roustabouts, oil and gas Odessa, TX 29.47

Gaming managers Atlantic City, NJ 46.00

Table 2. Employment and location quotients for brokerage clerks in major U.S. 

metropolitan areas, May 2009 

Area Area 

Employment 

Occupational 

Employment 

Location 

Quotient 

Washington-Arlington-Alexandria, DC-VA-MDWV 2,857,820 630 0.46

Los Angeles-Long Beach-Santa Ana, CA 5,395,280 1,910 0.73

Dallas-Fort Worth-Arlington, TX 2,904,030 1,170 0.83

Detroit-Warren-Livonia, MI 1,766,340 740 0.88

Miami-Fort Lauderdale-Miami Beach, FL 2,207,330 970 0.92

Seattle-Tacoma-Bellevue, WA 1,670,200 800 1.00

Philadelphia-Camden-Wilmington, PA-NJ-DEMD 2,672,070 1,600 1.25

San Francisco-Oakland-Fremont, CA 1,973,500 1,590 1.67

Chicago-Naperville-Joliet, IL-IN-WI 4,319,720 3,900 1.88

Boston-Cambridge-Quincy, MA-NH 2,457,180 3,800 3.23

New York-Northern New Jersey-Long Island, 

NY-NJ-PA 

8,245,760 14,520 3.67

 
12 

Table 3. Location quotients for selected occupations in Durham, NC, 

May 2009 

Occupation Location 

quotient 

Epidemiologists 4.25 

Chemists 5.10 

Computer software engineers, systems software 5.68 

Operations research analysts 6.55 

Medical scientists, except epidemiologists 12.56 

Biochemists and biophysicists 12.89 

Statisticians 13.13 

Natural sciences managers 14.41 

Microbiologists 14.58 

Soil and plant scientists 15.33 

Table 4. Location quotients for selected occupations in 

Columbus, IN, May 2009 

Occupation Location 

quotient 

Inspectors, testers, sorters, samplers, and weighers 4.55 

Tool and die makers 4.93 

Team assemblers 5.62 

Heat treating equipment setters, operators, and tenders, metal and 

plastic 

6.19 

Cutting, punching, and press machine setters, operators, and 

tenders, metal and plastic 

6.39 

Mechanical drafters 6.86 

Industrial engineers 6.91 

Drilling and boring machine tool setters, operators, and tenders, 

metal and plastic 

9.50 

Lathe and turning machine tool setters, operators, and tenders, 

metal and plastic 

11.21 

Mechanical engineers 12.15 

Table 5. Location quotients for bartenders and substance abuse and 

behavioral disorder counselors in selected states, May 2009 

State Location quotient for 

bartenders 

Location quotient for 

counselors 

Vermont 1.44 2.37 

Oregon 1.47 1.83 

Minnesota 1.53 1.12 

South Dakota 1.80 2.20 

Rhode Island 1.94 0.95 

Wyoming 2.11 0.60 

North Dakota 2.43 1.30 

Wisconsin 2.47 0.60 

Nevada 2.73 0.37 

Montana 3.27 1.90 
Table 6. State all-occupations hourly mean wages and 

location quotients for fast food cooks, May 2009 

State Location quotient, 

fast food cooks 

State all-occupations 

hourly mean wage 

Alabama 1.66 18.03

Arizona 1.48 19.67

Arkansas 2.23 16.65

California 1.87 23.82

Colorado 0.58 22.11

Connecticut 0.84 24.50

Delaware 0.50 22.25

Florida 0.71 18.96

Georgia 1.47 19.88

Hawaii 0.93 20.56

Idaho 1.13 18.23

Illinois 1.22 22.17

Indiana 0.97 18.43

Iowa 0.79 17.77

Kansas 1.20 18.52

Kentucky 0.96 17.97

Louisiana 1.09 17.60

Maine 0.53 18.53

Maryland 0.85 23.80

Massachusetts 0.38 25.34

Michigan 1.23 20.64

Minnesota 0.75 21.60

Mississippi 2.66 16.14

Missouri 0.66 18.87

Montana 1.08 16.87

Nebraska 1.05 17.94

Nevada 1.38 19.42

New Hampshire 0.76 21.02

New Jersey 0.55 24.04

New Mexico 1.51 18.71

New York 0.71 24.42

North Carolina 0.20 18.95

North Dakota 0.61 17.31

Ohio 0.65 19.37

Oklahoma 1.88 17.22

Oregon 1.05 20.45

Pennsylvania 0.66 20.21

Rhode Island 0.39 21.31

South Carolina 1.72 17.81

South Dakota 1.50 16.02

Tennessee 0.96 17.96

Texas 0.85 19.76

Utah 1.02 18.86

Vermont 0.57 19.68

Virginia 0.61 22.29

Washington 0.50 22.97

West Virginia 0.37 16.62

Wisconsin 0.58 19.32

Wyoming 0.94 19.19