Bureau of Labor Statistics Washington, D.C. 20212 

Technical Contact: USDL: 05-2382 

(202) 691-6199 ocltinfo@bls.gov 

Media Contact: FOR RELEASE: 10:00 A.M. (EST) 

(202) 691-5902 WEDNESDAY, DECEMBER 28, 2005 

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 RELATIVES, 2004 

The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor has produced occupational “pay 

relatives” to facilitate comparisons of occupational pay between metropolitan areas and the United States as a 

whole. BLS periodically has issued occupational pay relatives using data from the National Compensation 

Survey (NCS) and its predecessor surveys, and now plans to publish them annually. Using data for 2004 from 

the NCS, pay relatives have been prepared for each of 9 major occupational groups within 78 Metropolitan 

Statistical Areas (MSAs), as well as averaged across all occupations for each area. 

The pay relative in 2004 for workers in construction and extraction occupations in the San Francisco 

MSA was 127, meaning the pay in San Francisco in that occupational group averaged 27 percent more than the 

national average pay for workers in that occupational group (table 1). The pay relative averaged across all 

occupations for workers in the San Francisco MSA was 117, meaning that pay on average was 17 percent more 

in that area than for the nation as a whole. By contrast, the pay relative for workers in construction and 

extraction occupations in the Brownsville, TX MSA, was 70, meaning pay for workers in those occupations 

averaged 30 percent less than the national average. Pay averaged across all occupations in the Brownsville 

MSA was 19 percent below the national average. The pay relatives averaged for workers in all occupations in 

San Francisco and Brownsville were, respectively, the highest and lowest among the 78 areas. In addition to 

these examples of area-to-national comparisons, area-to-area comparisons can be derived using these pay 

relatives. 

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

employee compensation covering over 820 detailed occupations in 152 metropolitan and non-metropolitan 

areas. Average occupational earnings from the NCS are published annually for more than 80 metropolitan areas 

and for the United States as a whole. 

What is a pay relative? 

United States 

Department News of Labor 
2 

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. 

Metropolitan areas differ greatly in the types of occupations that are available to the local workforce. 

For example, the proportion of San Francisco's workers who are employed as computer programmers is 

approximately 48 percent greater than the national average.i Similarly, the composition of establishment and 

occupational characteristics—such as whether an establishment is for profit or not-for-profit or whether an 

occupation is union or nonunion—varies by area. 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 workers in San Francisco is $38.66 and the average pay for professional 

workers in the entire US is $29.40.ii 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: 

   13110040.29$66.38$

However, this comparison does not control for the interarea difference in occupational composition. 

Some of the 31 percent pay premium in San Francisco relative to the nation as a whole is due to the higher 

concentration of highly compensated professional workers—such as computer programmers—in San Francisco. 

A more accurate estimate of the geographic effect on wage determination in San Francisco can be obtained by 

taking into account this and other differences. Controlling for the differences in occupation 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 occupations in San Francisco is equal to 118. 

Using multivariate regression analysis 

A statistical technique called multivariate regression analysis controls for interarea differences. It 

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 

 Profit / non-profit status 

 Establishment employment 

 Payroll reference date 
3 

Even accounting for these characteristics, 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. 

For more detailed information on the pay relative methodology, see Maury B. Gittleman, "Pay Relatives 

for Metropolitan Areas in the U.S.," Monthly Labor Review, March 2005, pp. 46-53. 

Results 

Table 1 presents July 2004 pay relatives averaged across all occupations covered by the NCS survey and 

nine occupational groups in 78 metropolitan areas. This table represents the first presentation of NCS wage 

data using the 2000 Standard Occupational Classification System (SOC). For more detailed information on 

SOC, see the BLS website: http://www.bls.gov/soc/home.htm. 

The occupational groups are: 

(1) management, business, and financial occupations 

(2) professional and related occupations 

(3) service occupations 

(4) sales and related occupations 

(5) office and administrative support occupations 

(6) construction and extraction occupations 

(7) installation, maintenance, and repair occupations 

(8) production occupations 

(9) transportation and material movement occupations 

Comparisons between areas 

The pay relatives presented in Table 1 are area-to-national comparisons. However, it is easy to derive 

area-to-area comparisons from them. To do so, divide the pay relative for the occupational group and area in 

question by the pay relative for the same occupational group in the area to which the first is being compared. 

Then multiply the result by 100 so that the comparison is expressed as a percentage. 

For example, the pay relative for professional occupations in San Francisco is 118 and the pay relative 

for professional occupations in Los Angeles is 111. The San Francisco-to-Los Angeles pay relative for 

professional occupations is calculated as: 

   106100111118

In the example, there is approximately a 6 percent pay premium for professional occupations in San 

Francisco relative to the same occupational group in Los Angeles. 

Differences between the 2004 pay relatives and historical pay relatives 

Historical pay relative data are available for 2002iii, 1998iv, and 1992–1996.v There are several 

differences between the 2004 pay relatives and the historical pay relatives, including different industry and 

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

comparability. 
4 

The 2004 pay relatives use the 2002 North American Industry Classification System (NAICS) to define 

industry type. Occupation type and the occupational groups presented in Table 1 are defined using the Standard 

Occupational Classification System (SOC). The 2002 and 1992–1996 pay relatives defined industry type using 

the Standard Industry Classification (SIC) system. Occupation type and occupational groups for the 2002, 

1998, and 1992–1996 pay relatives were defined using the Occupational Classification System (OCS). 

The 2004 and 2002 pay relatives used a similar multivariate regression technique methodology to 

calculate pay relatives. The 1998 and 1992–1996 pay relatives were calculated using a weighted cell means 

methodology. The methodology controlled for fewer characteristics: 

 Occupational type 

 Work level 

 Payroll reference date 

The 2004, 2002, and 1998 pay relatives were derived from the National Compensation Survey (NCS). 

The 1992–1996 pay relatives were derived from the Occupational Compensation Survey (OCS). The NCS and 

OCS have significantly different sample designs. For example, the OCS collected wage data for sampled 

establishments with 50 or more employees. The NCS collects data for all sampled establishments. 

Additionally, the OCS collected wage data for a fixed list of jobs. The NCS collects wage data for randomly 

selected jobs. 
5 

Table 1. Pay relatives for major occupational groups in metropolitan areas, National Compensation Survey, July 2004(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 ...................................................... 91 89 87 89 88 90 89 90 110 97

Anchorage, AK ................................................. 111 110 109 119 101 107 130 108 122 114

Atlanta, GA ....................................................... 103 101 99 102 107 105 103 108 100 103Augusta-Aiken, GA-SC ..................................... 95 94 97 89 88 93 88 98 99 96

Austin-San Marcos, TX ..................................... 97 95 95 102 100 102 93 103 90 87

Birmingham, AL ................................................ 94 104 97 97 92 92 76 100 93 94Bloomington, IN ................................................ 93 102 87 93 96 88 98 92 98 101

Boston-Worcester-Lawrence, MA-NH-ME-CT .. 112 110 109 114 106 117 117 111 109 119

Brownsville-Harlingen-San Benito, TX ............. 81 78 95 81 80 81 70 80 73 77

Buffalo-Niagara Falls, NY ................................. 102 92 97 108 100 102 101 101 105 101Charleston-North Charleston, SC ..................... 96 105 98 86 93 99 81 89 93 102

Charlotte-Gastonia-Rock Hill, NC-SC ............... 98 97 91 94 102 101 89 98 104 103

Chicago-Gary-Kenosha, IL-IN-WI ..................... 106 103 103 105 108 108 123 105 103 109

Cincinnati-Hamilton, OH-KY-IN ........................ 101 95 98 104 104 100 102 98 108 100Cleveland-Akron, OH ........................................ 101 101 101 99 97 99 96 105 106 105Columbus, OH .................................................. 97 90 96 96 100 99 112 98 92 98

Corpus Christi, TX ............................................ 88 95 93 84 90 86 80 84 90 85

Dallas-Fort Worth, TX ....................................... 99 103 100 95 101 100 96 98 94 99

Dayton-Springfield, OH ..................................... 99 93 96 94 102 96 99 99 112 104

Denver-Boulder-Greeley, CO ........................... 102 101 99 101 97 101 96 106 104 104

Detroit-Ann Arbor-Flint, MI ................................ 106 102 107 101 98 108 110 104 115 109Elkhart-Goshen, IN ........................................... 94 92 99 92 95 92 99 87 95 94

Fort Collins-Loveland, CO ................................ 97 88 95 97 96 99 99 100 96 100Grand Rapids-Muskegon-Holland, MI .............. 104 101 100 101 106 100 106 101 107 107

Great Falls, MT ................................................. 87 85 83 92 82 81 122 100 101 88

Greensboro-Winston Salem-High Point, NC .... 99 95 98 97 88 100 93 102 104 104

Greenville-Spartanburg-Anderson, SC ............. 96 93 94 93 91 99 90 88 103 97

Hartford, CT ...................................................... 113 107 109 124 114 111 138 111 112 110

Hickory-Morganton-Lenoir, NC ......................... 99 88 93 98 90 100 81 97 103 111Honolulu, HI ...................................................... 104 104 106 107 105 102 102 107 94 106

Houston-Galveston-Brazoria, TX ...................... 97 107 102 88 98 97 94 95 96 93

Huntsville, AL .................................................... 97 98 99 95 96 97 89 95 98 94

Indianapolis, IN ................................................. 98 94 98 96 82 104 95 99 106 104Iowa City, IA ..................................................... 100 99 98 104 91 103 104 92 99 105

Johnstown, PA .................................................. 87 95 84 90 90 83 84 107 85 80Kansas City, MO-KS ......................................... 98 87 93 98 105 101 103 94 109 100

Knoxville, TN .................................................... 95 105 91 89 92 99 86 92 93 94

Lincoln, NE ....................................................... 92 93 87 95 91 90 82 96 94 95

Los Angeles-Riverside-Orange County, CA ..... 107 108 111 111 109 107 110 109 97 101

Louisville, KY-IN ............................................... 100 103 102 105 98 100 104 91 92 99Melbourne-Titusville-Palm Bay, FL ................... 92 89 86 95 96 92 90 101 89 100Memphis, TN-AR-MS ....................................... 96 94 89 93 94 92 111 103 94 101

See footnotes at end of table.
6 

Table 1. Pay relatives for major occupational groups in metropolitan areas, National Compensation Survey, July 2004 — 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 ............................... 93 98 97 91 94 93 84 93 89 92

Milwaukee-Racine, WI ...................................... 105 100 95 100 120 102 105 111 117 107Minneapolis-St. Paul, MN-WI ........................... 109 103 104 119 105 105 116 108 111 119

Mobile, AL ......................................................... 90 90 93 85 88 92 91 90 91 98

New Orleans, LA .............................................. 90 87 93 83 109 84 85 89 86 94

New York-Northern New Jersey- Long Island,

NY-NJ-CT-PA ................................................. 110 111 115 110 107 114 127 100 102 113

Norfolk-VA Beach-Newport News, VA-NC ....... 93 94 93 91 98 96 87 92 86 93

Ocala, FL .......................................................... 92 98 88 87 91 97 81 94 86 104

Oklahoma City, OK ........................................... 91 86 88 88 91 89 86 93 97 93

Orlando, FL ....................................................... 91 91 89 86 100 92 87 104 90 92Philadelphia-Wilmington-Atlantic City,

PA-NJ-DE-MD ................................................ 107 107 108 106 112 108 106 107 101 108

Phoenix-Mesa, AZ ............................................ 102 98 101 94 130 106 90 106 102 100Pittsburgh, PA ................................................... 97 96 96 99 94 99 91 95 94 101

Portland-Salem, OR-WA .................................. 100 97 93 109 102 102 108 105 99 103Providence-Fall River-Warwick, RI-MA ............ 108 103 110 117 113 109 98 88 100 115

Reading, PA ..................................................... 104 108 101 103 103 102 100 98 104 108

Reno, NV .......................................................... 99 93 95 102 111 91 101 114 93 100Richland-Kennewick-Pasco, WA ...................... 100 98 99 105 105 92 99 92 104 100Richmond-Petersburg, VA ................................ 99 95 97 99 99 98 88 97 101 104

Rochester, NY .................................................. 99 101 97 107 96 95 95 89 102 100Rockford, IL ...................................................... 101 84 102 98 93 93 111 115 107 103

Sacramento-Yolo, CA ....................................... 108 106 112 113 108 106 105 112 106 110

Salinas, CA ....................................................... 110 108 117 111 119 110 118 109 100 96

San Antonio, TX ............................................... 92 91 93 87 97 95 79 83 100 95

San Diego, CA .................................................. 108 109 117 111 111 103 108 108 100 102

San Francisco-Oakland-San Jose, CA ............. 117 117 118 121 113 120 127 116 110 113

Seattle-Tacoma-Bremerton, WA ...................... 105 95 98 116 103 105 115 102 108 105Springfield, MA ................................................. 94 103 107 106 110 110 107 109 110 65

Springfield, MO ................................................. 89 91 88 89 88 86 83 90 95 94

St. Louis, MO-IL ................................................ 98 95 95 95 105 98 112 95 97 109

Tallahassee, FL ................................................ 86 83 86 84 99 88 91 79 83 108

Tampa-St. Petersburg-Clearwater, FL ............. 94 99 90 92 106 93 88 101 93 100Visalia-Tulare-Porterville, CA ........................... 98 95 105 98 101 96 87 99 93 91

Washington-Baltimore, DC-MD-VA-WV ........... 105 101 108 105 101 110 103 101 102 98

York, PA ........................................................... 98 106 101 97 102 93 91 100 94 101Youngstown-Warren, OH ................................. 98 89 94 88 101 87 99 96 111 111

1 A metropolitan area can be a Metropolitan Statistical Area (MSA) or Combined Statistical Area (CSA) as defined by the Office of Management and Budget, 1994.
7 

Technical Note 

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 NCS" Monthly 

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

Areas," Compensation and Working Conditions Online, April 28, 2003. 

 

i

 The proportion of computer programmers in San Francisco relative to the nation as a whole was calculated using total employment 

estimates found in the November 2004 Metropolitan Area Occupational Employment and Wage Estimates publication, 

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

ii 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, April 2004 and the National Compensation Survey: Occupational 

Wages in the United States, July 2004, http://www.bls.gov/ncs/ocs/compub.htm. iii For more information, see Maury B. Gittleman, "Pay Relatives for Metropolitan Areas in the U.S.," Monthly Labor Review, March 

2005, pp. 46-53. 

iv For more information, see Parastou Karen Shahpoori, "Pay Relatives for Major Metropolitan Areas," Compensation and Working 

Conditions, Spring 2003. v

 For more information, see the Occupational Compensation Survey Publications List (1992-1996), 

http://www.bls.gov/ncs/ocspubs.htm.