Bureau of Labor Statistics Washington, D.C. 20212 

Technical Contact: USDL: 07-1455 

(202) 691-6199 NCSinfo@bls.gov 

Media Contact: FOR RELEASE: 10:00 A.M. EDT 

(202) 691-5902 WEDNESDAY, SEPTEMBER 26, 2007 

Internet address: 

http://www.bls.gov/ncs/ocs/home.htm 

(This news release was reissued on Wednesday, May 26, 2010, to remove table asterisks that have 

incorrectly indicated statistically significant differences between some estimates. News release text 

references to statistical significance have also been removed. Pay relative estimates have not changed. 

For more information, see http://www.bls.gov/ncs.)

OCCUPATIONAL PAY COMPARISONS AMONG METROPOLITAN AREAS, 2006 

Average pay in the San Francisco metropolitan area was 19 percent above the national average in 2006, 

the highest among the 78 metropolitan areas studied by the National Compensation Survey (NCS), the Bureau 

of Labor Statistics of the U.S. Department of Labor reported today. In contrast, pay was lowest in the 

Brownsville, Texas metropolitan area with a pay relative of 78, meaning Brownsville workers earned an 

average of 78 cents for every dollar earned by workers nationwide. Using data from the NCS, pay relatives—a 

means of assessing pay differences—are available for each of the 9 major occupational groups within 78 

metropolitan areas, as well as averaged across all occupations for each area. (See table 1.) Table A below lists 

the five highest and five lowest paying metropolitan areas among those studied in the NCS. In addition, similar 

area-to-area comparisons have been calculated for all 78 areas and will soon be available on the BLS website at 

http://www.bls.gov/ncs/ocs/payrel.htm. 

Table A. Highest and lowest metropolitan area pay relative rankings (of 78 metropolitan areas surveyed) 

 Rank Metropolitan Area Pay Relative

 1. San Francisco-Oakland-San Jose, CA 119 

 2. New York-Northern New Jersey-Long Island, NY-NJ-CT-PA 114 

 3. Salinas, CA 113 

 4. Boston-Worcester-Lawrence, MA-NH-ME-CT 112 

 Hartford, CT 112 

74. Corpus Christi, TX 87 

Great Falls, MT 87 

Johnstown, PA 87 

Springfield, MO 87 

78. Brownsville-Harlingen-San Benito, TX 78 

United States 

Department News of Labor 
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A pay relative is a calculation of pay—wages, salaries, commissions, and production bonuses—for a 

given metropolitan area relative to the nation as a whole. The calculation controls for differences among areas 

in occupational composition, establishment and occupational characteristics, and the fact that data are collected 

for areas at different times during the year. Simple pay comparisons calculating the ratio of the average pay for 

an area versus the entire United States in percentage terms would not control for interarea differences in 

occupational composition and other factors, which may have an effect on pay relatives. More information on 

pay relative controls and calculations are available in the Technical Note. 

The pay relative in 2006 for workers in construction and extraction occupations in the San Francisco 

area was 122, meaning the pay in San Francisco for that occupational group averaged 22 percent more than the 

national average pay for that occupational group. By contrast, the pay relative for workers in construction and 

extraction occupations in the Brownsville, Texas area was 67, meaning pay for workers in those occupations 

averaged 33 percent less than the national average. 

The National Compensation Survey (NCS), introduced in 1997, collects earnings and other data on 

employee compensation covering over 800 detailed occupations in 152 metropolitan and nonmetropolitan areas. 

Average occupational earnings from the NCS are published annually for 78 metropolitan areas and for the 

United States as a whole. Beginning in 2006, the NCS implemented a number of significant survey changes 

including imputing for temporary non-response situations and benchmarking estimated employment. For more 

details on these changes, see the article at http://www.bls.gov/opub/cwc/cm20070122ar01p1.htm. 

Data users are cautioned not to use yearly differences in area and occupational pay group differences in 

pay relatives to infer changes in underlying economic conditions. 

 
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Table 1. Pay relatives for major occupational groups in metropolitan areas, National Compensation Survey, June 2006(Average pay nationally for all occupations and for each occupational group shown = 100.)

Metropolitan Area1 All occupations Management, business, and financial Professional and related Service Sales and related Office and administrative support Construction and extraction Installation, maintenance, and repair Production Transportation and material moving

United States .................................................... 100 100 100 100 100 100 100 100 100 100

Amarillo, TX ...................................................... 88 93 85 87 90 87 83 81 89 92

Anchorage, AK ................................................. 109 104 100 121 108 106 125 111 115 110

Atlanta, GA ....................................................... 102 102 102 97 97 104 93 102 103 107

Augusta-Aiken, GA-SC ..................................... 94 89 100 89 83 96 95 97 98 96

Austin-San Marcos, TX ..................................... 95 91 95 93 100 97 88 100 94 91Birmingham, AL ................................................ 94 92 95 101 94 96 84 99 87 98Bloomington, IN ................................................ 90 89 97 90 78 88 78 85 97 104

Boston-Worcester-Lawrence, MA-NH-ME-CT .. 112 110 108 113 106 113 124 115 108 111

Brownsville-Harlingen-San Benito, TX ............. 78 73 95 76 75 77 67 78 76 76

Buffalo-Niagara Falls, NY ................................. 100 91 91 106 105 99 111 100 111 101Charleston-North Charleston, SC ..................... 93 98 94 86 101 93 80 82 101 104

Charlotte-Gastonia-Rock Hill, NC-SC ............... 101 99 93 98 109 102 92 98 104 99

Chicago-Gary-Kenosha, IL-IN-WI ..................... 108 104 107 107 106 109 125 114 104 106

Cincinnati-Hamilton, OH-KY-IN ........................ 98 93 99 103 94 98 90 98 100 99Cleveland-Akron, OH ........................................ 100 96 101 98 95 101 101 102 105 106Columbus, OH .................................................. 100 100 92 100 105 99 98 100 96 101

Corpus Christi, TX ............................................ 87 92 94 83 88 84 92 81 89 86

Dallas-Fort Worth, TX ....................................... 98 100 101 96 103 99 90 95 91 99

Dayton-Springfield, OH ..................................... 98 99 92 96 97 92 100 106 107 105

Denver-Boulder-Greeley, CO ........................... 102 99 102 99 104 102 91 105 103 98Detroit-Ann Arbor-Flint, MI ................................ 106 97 104 101 101 105 110 97 118 108

Elkhart-Goshen, IN ........................................... 96 96 94 96 95 92 109 92 98 101

Fort Collins-Loveland, CO ................................ 100 94 95 94 106 101 99 104 95 111Grand Rapids-Muskegon-Holland, MI .............. 101 93 97 104 109 100 106 96 102 101Great Falls, MT ................................................. 87 85 76 94 88 80 118 100 96 92

Greensboro-Winston Salem-High Point, NC .... 95 91 94 95 86 97 91 98 101 104

Greenville-Spartanburg-Anderson, SC ............. 94 95 90 97 91 93 82 84 105 95

Hartford, CT ...................................................... 112 108 108 119 108 112 114 108 111 107

Hickory-Morganton-Lenoir, NC ......................... 95 89 89 90 91 95 98 91 100 102

Honolulu, HI ...................................................... 105 105 104 110 105 99 113 115 106 104

Houston-Galveston-Brazoria, TX ...................... 96 100 98 87 95 98 91 95 100 95

Huntsville, AL .................................................... 96 94 96 95 100 96 91 90 100 93

Indianapolis, IN ................................................. 97 82 97 97 95 98 93 95 108 99

Iowa City, IA ..................................................... 98 95 95 102 92 101 101 102 101 96

Johnstown, PA .................................................. 87 86 91 89 86 84 96 88 84 82

Kansas City, MO-KS ......................................... 99 93 95 95 96 100 108 104 104 97Knoxville, TN .................................................... 92 103 98 84 98 95 85 87 89 96

Lincoln, NE ....................................................... 89 85 88 91 85 87 85 93 91 91

Los Angeles-Riverside-Orange County, CA ..... 107 106 109 109 115 106 110 106 99 102

Louisville, KY-IN ............................................... 96 91 96 103 99 98 110 94 99 94Melbourne-Titusville-Palm Bay, FL ................... 93 85 81 101 96 89 92 101 105 103

Memphis, TN-AR-MS ....................................... 95 96 92 91 104 98 94 98 97 96

See footnotes at end of table.
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Table 1. Pay relatives for major occupational groups in metropolitan areas, National Compensation Survey, June 2006 — Continued(Average pay nationally for all occupations and for each occupational group shown = 100.)

Metropolitan Area1 All occupations Management, business, and financial Professional and related Service Sales and related Office and administrative support Construction and extraction Installation, maintenance, and repair Production Transportation and material moving

Miami-Fort Lauderdale, FL ............................... 96 107 95 96 95 96 91 93 97 98

Milwaukee-Racine, WI ...................................... 102 100 97 100 102 104 110 101 106 107Minneapolis-St. Paul, MN-WI ........................... 108 101 104 118 109 103 113 107 117 107

Mobile, AL ......................................................... 88 81 85 84 95 90 94 98 96 91

New Orleans, LA .............................................. 95 90 96 91 101 96 90 91 95 100

New York-Northern New Jersey- Long Island,

NY-NJ-CT-PA ................................................. 114 114 116 114 112 114 128 114 105 110

Norfolk-VA Beach-Newport News, VA-NC ....... 91 87 90 95 94 91 87 94 93 89

Ocala, FL .......................................................... 90 88 88 92 93 88 83 106 95 103Oklahoma City, OK ........................................... 91 87 85 91 93 89 101 108 89 87

Orlando, FL ....................................................... 93 94 88 94 101 90 91 93 85 106

Philadelphia-Wilmington-Atlantic City,

PA-NJ-DE-MD ................................................ 105 106 107 105 100 106 106 112 100 108

Phoenix-Mesa, AZ ............................................ 97 99 101 96 107 101 82 100 96 100Pittsburgh, PA ................................................... 96 91 97 98 89 97 96 96 99 96

Portland-Salem, OR-WA .................................. 104 104 95 112 110 105 114 110 101 100Providence-Fall River-Warwick, RI-MA ............ 108 109 111 112 103 106 104 108 112 105

Reading, PA ..................................................... 102 105 94 101 106 102 102 100 99 102Reno, NV .......................................................... 98 97 95 99 101 99 96 111 98 101Richland-Kennewick-Pasco, WA ...................... 103 96 95 113 105 100 111 93 98 100Richmond-Petersburg, VA ................................ 98 98 95 98 99 99 92 99 102 100

Rochester, NY .................................................. 97 89 97 104 96 98 94 89 100 100Rockford, IL ...................................................... 100 90 97 99 100 97 111 104 103 104

Sacramento-Yolo, CA ....................................... 106 102 107 111 102 104 103 118 111 108

Salinas, CA ....................................................... 113 115 121 115 129 111 132 110 95 104

San Antonio, TX ............................................... 89 93 91 87 84 91 97 97 96 86

San Diego, CA .................................................. 108 106 110 112 106 105 107 107 104 101

San Francisco-Oakland-San Jose, CA ............. 119 114 117 123 124 122 122 117 108 108

Seattle-Tacoma-Bremerton, WA ...................... 109 103 99 119 111 108 111 106 117 113Springfield, MA ................................................. 109 104 109 105 113 110 105 110 108 115

Springfield, MO ................................................. 87 82 88 84 91 86 77 91 94 89

St. Louis, MO-IL ................................................ 101 97 99 94 100 99 117 107 104 108

Tallahassee, FL ................................................ 91 81 90 96 92 91 88 87 95 93

Tampa-St. Petersburg-Clearwater, FL ............. 95 89 91 95 98 100 97 94 93 103Visalia-Tulare-Porterville, CA ........................... 99 101 98 101 102 97 92 93 105 97Washington-Baltimore, DC-MD-VA-WV ........... 107 103 107 106 106 111 100 116 108 106

York, PA ........................................................... 97 102 98 98 91 95 102 99 96 103

Youngstown-Warren, OH ................................. 96 96 93 91 92 92 99 95 102 110

1 A metropolitan area can be a Metropolitan Statistical Area (MSA) or Consolidated Metropolitan Statistical Area (CMSA) as defined by the Office of Management and Budget, 1994.
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Technical Note 

Pay relative controls and calculations 

Pay relatives control for differences among areas in occupational composition as well as establishment 

and occupational characteristics. Metropolitan areas often differ greatly in the composition of establishments 

and occupations that are available to the local workforce. For example, in Brownsville, Texas, the ratio of 

workers in the high-paying management, business, and financial occupational group to the number of workers 

in all occupations is under 6 percent, whereas nationally this ratio is over 8 percent.1 In addition to these 

factors, the NCS collects compensation data for metropolitan areas at different times during the year. Payroll 

reference dates differ between areas which makes direct comparisons between areas difficult. 

The pay relative approach controls for these differences to isolate the geographic effect on wage 

determination. To illustrate the importance of controlling for these effects, consider the following example. 

The average pay for professional and related workers in San Francisco is $37.57 and the average pay for 

professional and related workers in the entire United States is $29.76.2 A simple pay comparison can be 

calculated from the ratio of the two average pay levels, multiplied by 100 to express the comparison as a 

percentage. The pay comparison in the example is calculated as: 

 ($37.57  $29.76)  100  126 

This comparison does not control for differences between San Francisco and the nation in the mix of 

occupations, industries, and other factors. A more accurate estimate of the geographic effect of wages in San 

Francisco can be obtained by taking these differences into account. Controlling for differences in occupational 

composition, establishment and occupational characteristics, and the payroll reference date in San Francisco 

relative to the nation as the whole, the pay relative for professional and related occupations in San Francisco is 

equal to 117. 

Historical data

Historical pay relative data are available for 1992-1996, 1998, 2002, 2004, and 2005. There are several 

differences between the recent pay relatives and the pay relatives for earlier years, including different industry 

and occupation classification systems, varying methodology, and different survey designs. These differences 

limit comparability. The pay relatives for 2004, 2005, and 2006 were calculated using the same industry and 

occupation classification systems, methodology, and survey design. Nonetheless, comparisons between the 

estimates for these years should be made only with a high degree of caution. 

Survey methodology 

Pay relatives were estimated using a multivariate regression technique methodology to control for 

interarea differences. This technique controls for the following ten characteristics: 

 Occupational type 

 Industry type 

 Work level 

 Full-time / part-time status 

 Time / incentive status 

 Union / nonunion status 

 Ownership type 
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 Profit / non-profit status 

 Establishment employment 

 Payroll reference date 

Even accounting for the characteristics used in the current regression analysis, there is still wage 

variation across the areas. The variation is due to differences in wage determinants that were not included in 

the model. Examples of these determinants include price levels, environmental amenities such as a pleasant 

climate, and cultural amenities. 

The pay relatives in this release, as with estimates from any sample survey, are subject to sampling and 

non-sampling errors. Sampling errors are differences that occur between the pay relatives estimated from the 

sample and the true pay relatives derived from the population. Pay relatives are also subject to a variety of nonsampling errors that can influence the estimates. The NCS may be unable to obtain information for some 

establishments; there may be difficulties with survey definitions; respondents may be unable to provide correct 

information, or mistakes in recording or coding the data may occur. Non-sampling errors of these kinds were 

not specifically measured. However, they are expected to be minimal due to the extensive training of the field 

economists who gathered the survey data, computer edits of the data, and detailed data review. 

For more details, see Maury B. Gittleman, "Pay Relatives for Metropolitan Areas in the U.S." Monthly 

Labor Review, March 2005, pp. 46-53, and Parastou Karen Shahpoori, "Pay Relatives for Major Metropolitan 

Areas," Compensation and Working Conditions, Spring 2003. 

1

 Data for this example are based on the May 2006 Occupational Employment and Wage Estimates, 

http://www.bls.gov/oes/current/oessrcma.htm. 2

 Average pay for professional workers in San Francisco and for the United States are based on wage estimates published in the San 

Francisco–Oakland–San Jose, CA National Compensation Survey, March 2006 and the National Compensation Survey: Occupational 

Wages in the United States, June 2006, http://www.bls.gov/ncs/ocs/compub.htm.