Occupational Pay Relatives news release text
OCCUPATIONAL PAY RELATIVES, 2004
Workers in the San Francisco Metropolitan Statistical Area (MSA) had the highest average pay for all occupations, 17 percent above the national average in 2004. The pay for workers in construction and extraction occupations in this area averaged 27 percent above the national average. The pay for all occupations in the Brownsville, TX MSA was the lowest, 19 percent below the national average. For workers in construction and extraction occupations in this area, pay averaged 30 percent below the national average. To facilitate comparisons of occupational pay between metropolitan areas and the United States as a whole, the Bureau of Labor Statistics (BLS) of the U.S. Department of Labor has produced occupational "pay relatives" using data for 2004 from its National Compensation Survey (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. Pay relatives calculated for all occupations were significantly different from the national average in 66 of the 78 areas.
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. BLS periodically has issued occupational pay relatives using wage data, and now plans to publish them annually.
What is a pay relative?
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.(1) Similarly, the composition of establishment andoccupational 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(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:
($38.66/$29.40) X 100 = 131
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
Even accounting for these characteristics, there is still significant 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.
An additional feature of this type of analysis is the ability to perform statistical significance tests. An asterisk (*) in the table indicates that the pay relative is statistically significant (i.e., the pay for the given occupation in that area is too different from the national average to be accounted for by the randomness of the survey’s sample).
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 for 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:
(118/111) X 100 = 106
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. However, there is no significance test for area-to-area comparisons calculated this way. The difference in average pay between San Francisco and Los Angeles in the example may or may not be statistically significant.
Differences between the 2004 pay relatives and historical pay relatives
Historical pay relative data are available for 2002(3), 1998(4), and 1992-1996.(5) 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.
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 Occupation Classification (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.
Footnotes
(1) 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.
(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, April 2004 and the National Compensation Survey: Occupational Wages in the United States, July 2004, http://www.bls.gov/ncs/ocs/compub.htm.
(3) For more information, see Maury B. Gittleman, "Pay Relatives for Metropolitan Areas in the U.S." Monthly Labor Review, March 2005, pp. 46-53.
(4) For more information, see Parastou Karen Shahpoori, "Pay Relatives for Major Metropolitan Areas," Compensation and Working Conditions, Spring 2003.
(5) For more information, see the Occupational Compensation Survey Publications List (1992 - 1996), http://www.bls.gov/ncs/ocspubs.htm.
TABLE 1.
Pay relatives for major occupational groups in metropolitan areas,
National Compensation Survey, July 2004
(For each major group, average pay for all occupations = 100)
Management,
Metropolitan Area(1) All business, Professional
occupations and and related
financial
United States...................... 100 100 100
Amarillo, TX....................... 91* 89* 87*
Anchorage, AK...................... 111* 110* 109*
Atlanta, GA........................ 103* 101 99
Augusta-Aiken, GA-SC............... 95* 94* 97*
Austin-San Marcos, TX.............. 97* 95* 95*
Birmingham, AL..................... 94* 104* 97*
Bloomington, IN.................... 93* 102 87*
Boston-Worcester-Lawrence,
MA-NH-ME-CT........................ 112* 110* 109*
Brownsville-Harlingen-San Benito,
TX................................. 81* 78* 95*
Buffalo-Niagara Falls, NY.......... 102* 92* 97*
Charleston-North Charleston, SC.... 96* 105 98*
Charlotte-Gastonia-Rock Hill, NC-SC 98 97 91*
Chicago-Gary-Kenosha, IL-IN-W...... 106* 103 103*
Cincinnati-Hamilton, OH-KY-IN...... 101 95* 98
Cleveland-Akron, OH................ 101 101 101
Columbus, OH....................... 97* 90* 96*
Corpus Christi, TX................. 88* 95 93*
Dallas-Fort Worth, TX.............. 99 103 100
Dayton-Springfield, OH............. 99* 93* 96*
Denver-Boulder-Greeley, CO......... 102 101 99
Detroit-Ann Arbor-Flint, MI........ 106* 102 107*
Elkhart-Goshen, IN................. 94* 92* 99
Fort Collins-Loveland, CO.......... 97* 88* 95*
Grand Rapids-Muskegon-Holland, MI.. 104* 101 100
Great Falls, MT.................... 87* 85* 83*
Greensboro-Winston Salem-High
Point, NC.......................... 99* 95* 98*
Greenville-Spartanburg-Anderson, SC 96* 93* 94*
Hartford, CT....................... 113* 107* 109*
Hickory-Morganton-Lenoir, NC....... 99* 88* 93*
Honolulu, HI....................... 104* 104 106*
Houston-Galveston-Brazoria, TX..... 97* 107* 102
Huntsville, AL..................... 97* 98 99
Indianapolis, IN................... 98 94* 98
Iowa City, IA...................... 100 99 98
(Continued)
(For each major group, average pay for all occupations = 100)
Office and
Metropolitan Area(1) Service Sales and administrat-
related ive support
United States...................... 100 100 100
Amarillo, TX....................... 89* 88* 90*
Anchorage, AK...................... 119* 101 107*
Atlanta, GA........................ 102 107* 105*
Augusta-Aiken, GA-SC............... 89* 88* 93*
Austin-San Marcos, TX.............. 102* 100 102
Birmingham, AL..................... 97* 92* 92*
Bloomington, IN.................... 93* 96* 88*
Boston-Worcester-Lawrence,
MA-NH-ME-CT........................ 114* 106 117*
Brownsville-Harlingen-San Benito,
TX................................. 81* 80* 81*
Buffalo-Niagara Falls, NY.......... 108* 100 102*
Charleston-North Charleston, SC.... 86* 93* 99
Charlotte-Gastonia-Rock Hill, NC-SC 94* 102 101
Chicago-Gary-Kenosha, IL-IN-W...... 105* 108* 108*
Cincinnati-Hamilton, OH-KY-IN...... 104 104 100
Cleveland-Akron, OH................ 99 97 99
Columbus, OH....................... 96 100 99
Corpus Christi, TX................. 84* 90* 86*
Dallas-Fort Worth, TX.............. 95* 101 100
Dayton-Springfield, OH............. 94* 102 96*
Denver-Boulder-Greeley, CO......... 101 97 101
Detroit-Ann Arbor-Flint, MI........ 101 98 108*
Elkhart-Goshen, IN................. 92* 95* 92*
Fort Collins-Loveland, CO.......... 97* 96* 99*
Grand Rapids-Muskegon-Holland, MI.. 101* 106* 100
Great Falls, MT.................... 92* 82* 81*
Greensboro-Winston Salem-High
Point, NC.......................... 97* 88* 100
Greenville-Spartanburg-Anderson, SC 93* 91* 99
Hartford, CT....................... 124* 114* 111*
Hickory-Morganton-Lenoir, NC....... 98* 90* 100
Honolulu, HI....................... 107* 105 102
Houston-Galveston-Brazoria, TX..... 88* 98 97*
Huntsville, AL..................... 95 96 97
Indianapolis, IN................... 96 82 104*
Iowa City, IA...................... 104* 91* 103*
(Continued)
(For each major group, average pay for all occupations = 100)
Construction Installation,
Metropolitan Area1 and maintenance,
extraction and repair
United States...................... 100 100
Amarillo, TX....................... 89* 90*
Anchorage, AK...................... 130* 108*
Atlanta, GA........................ 103 108*
Augusta-Aiken, GA-SC............... 88* 98
Austin-San Marcos, TX.............. 93* 103
Birmingham, AL..................... 76* 100
Bloomington, IN.................... 98 92*
Boston-Worcester-Lawrence,
MA-NH-ME-CT........................ 117* 111*
Brownsville-Harlingen-San Benito,
TX................................. 70* 80*
Buffalo-Niagara Falls, NY.......... 101 101
Charleston-North Charleston, SC.... 81* 89*
Charlotte-Gastonia-Rock Hill, NC-SC 89* 98
Chicago-Gary-Kenosha, IL-IN-W...... 123* 105*
Cincinnati-Hamilton, OH-KY-IN...... 102 98
Cleveland-Akron, OH................ 96 105*
Columbus, OH....................... 112* 98
Corpus Christi, TX................. 80* 84*
Dallas-Fort Worth, TX.............. 96 98
Dayton-Springfield, OH............. 99 99
Denver-Boulder-Greeley, CO......... 96 106*
Detroit-Ann Arbor-Flint, MI........ 110* 104
Elkhart-Goshen, IN................. 99 87*
Fort Collins-Loveland, CO.......... 99 100
Grand Rapids-Muskegon-Holland, MI.. 106* 101
Great Falls, MT.................... 122* 100
Greensboro-Winston Salem-High
Point, NC.......................... 93* 102
Greenville-Spartanburg-Anderson, SC 90* 88*
Hartford, CT....................... 138* 111
Hickory-Morganton-Lenoir, NC....... 81* 97*
Honolulu, HI....................... 102 107
Houston-Galveston-Brazoria, TX..... 94* 95
Huntsville, AL..................... 89 95
Indianapolis, IN................... 95 99
Iowa City, IA...................... 104* 92*
(Continued)
(For each major group, average pay for all occupations = 100)
Transportat-
Metropolitan Area(1) Production ion and
material
moving
United States...................... 100 100
Amarillo, TX....................... 110* 97
Anchorage, AK...................... 122* 114*
Atlanta, GA........................ 100 103
Augusta-Aiken, GA-SC............... 99 96
Austin-San Marcos, TX.............. 90* 87*
Birmingham, AL..................... 93* 94*
Bloomington, IN.................... 98 101
Boston-Worcester-Lawrence,
MA-NH-ME-CT........................ 109* 119*
Brownsville-Harlingen-San Benito,
TX................................. 73* 77*
Buffalo-Niagara Falls, NY.......... 105* 101
Charleston-North Charleston, SC.... 93* 102
Charlotte-Gastonia-Rock Hill, NC-SC 104 103
Chicago-Gary-Kenosha, IL-IN-W...... 103 109*
Cincinnati-Hamilton, OH-KY-IN...... 108* 100
Cleveland-Akron, OH................ 106* 105*
Columbus, OH....................... 92* 98
Corpus Christi, TX................. 90* 85*
Dallas-Fort Worth, TX.............. 94* 99
Dayton-Springfield, OH............. 112* 104*
Denver-Boulder-Greeley, CO......... 104 104
Detroit-Ann Arbor-Flint, MI........ 115* 109*
Elkhart-Goshen, IN................. 95* 94*
Fort Collins-Loveland, CO.......... 96* 100
Grand Rapids-Muskegon-Holland, MI.. 107* 107*
Great Falls, MT.................... 101 88*
Greensboro-Winston Salem-High
Point, NC.......................... 104* 104*
Greenville-Spartanburg-Anderson, SC 103* 97*
Hartford, CT....................... 112* 110*
Hickory-Morganton-Lenoir, NC....... 103* 111*
Honolulu, HI....................... 94 106
Houston-Galveston-Brazoria, TX..... 96 93*
Huntsville, AL..................... 98 94
Indianapolis, IN................... 106* 104
Iowa City, IA...................... 99 105*
(Continued)
(For each major group, average pay for all occupations = 100)
Management,
Metropolitan Area1 All business, Professional
occupations and and related
financial
Johnstown, PA...................... 87* 95* 84*
Kansas City, MO-KS................. 98* 87* 93*
Knoxville, TN...................... 95* 105* 91*
Lincoln, NE........................ 92* 93* 87*
Los Angeles-Riverside-Orange
County, CA......................... 107* 108* 111*
Louisville, KY-IN.................. 100 103* 102*
Melbourne-Titusville-Palm Bay, FL.. 92* 89* 86*
Memphis, TN-AR-MS.................. 96* 94* 89*
Miami-Fort Lauderdale, FL.......... 93* 98 97
Milwaukee-Racine, WI............... 105* 100 95*
Minneapolis-St. Paul, MN-WI........ 109* 103 104*
Mobile, AL......................... 90* 90* 93*
New Orleans, LA.................... 90* 87* 93*
New York-Northern New Jersey-Long
Island, NY-NJ-CT-PA................ 110* 111* 115*
Norfolk-VA Beach-Newport News,
VA-NC.............................. 93* 94* 93*
Ocala, FL.......................... 92* 98 88*
Oklahoma City, OK.................. 91* 86* 88*
Orlando, FL........................ 91* 91 89*
Philadelphia-Wilmington-Atlantic
City, PA-NJ-DE-MD.................. 107* 107* 108*
Phoenix-Mesa, AZ................... 102 98 101
Pittsburgh, PA..................... 97* 96 96*
Portland-Salem, OR-WA.............. 100 97 93*
Providence-Fall River-Warwick,
RI-MA.............................. 108* 103 110*
Reading, PA........................ 104* 108* 101
Reno, NV........................... 99* 93* 95*
Richland-Kennewick-Pasco, WA....... 100 98 99
Richmond-Petersburg, VA............ 99* 95* 97*
Rochester, NY...................... 99 101 97*
Rockford, IL....................... 101* 84* 102*
Sacramento-Yolo, CA................ 108* 106* 112*
Salinas, CA........................ 110* 108* 117*
St. Louis, MO-IL................... 98* 95 95*
San Antonio, TX.................... 92* 91* 93*
San Diego, CA...................... 108* 109* 117*
San Francisco-Oakland-San Jose, CA. 117* 117* 118*
(Continued)
(For each major group, average pay for all occupations = 100)
Office and
Metropolitan Area(1) Service Sales and administrat-
related ive support
Johnstown, PA...................... 90* 90* 83*
Kansas City, MO-KS................. 98 105 101
Knoxville, TN...................... 89* 92* 99
Lincoln, NE........................ 95* 91* 90*
Los Angeles-Riverside-Orange
County, CA......................... 111* 109* 107*
Louisville, KY-IN.................. 105* 98 100
Melbourne-Titusville-Palm Bay, FL.. 95* 96* 92*
Memphis, TN-AR-MS.................. 93* 94* 92*
Miami-Fort Lauderdale, FL.......... 91* 94 93*
Milwaukee-Racine, WI............... 100 120 102
Minneapolis-St. Paul, MN-WI........ 119* 105 105*
Mobile, AL......................... 85* 88* 92*
New Orleans, LA.................... 83* 109* 84*
New York-Northern New Jersey-Long
Island, NY-NJ-CT-PA................ 110* 107* 114*
Norfolk-VA Beach-Newport News,
VA-NC.............................. 91* 98 96*
Ocala, FL.......................... 87* 91* 97*
Oklahoma City, OK.................. 88* 91* 89*
Orlando, FL........................ 86* 100 92*
Philadelphia-Wilmington-Atlantic
City, PA-NJ-DE-MD.................. 106* 112* 108*
Phoenix-Mesa, AZ................... 94* 130* 106*
Pittsburgh, PA..................... 99 94* 99
Portland-Salem, OR-WA.............. 109* 102 102
Providence-Fall River-Warwick,
RI-MA.............................. 117* 113* 109*
Reading, PA........................ 103* 103 102*
Reno, NV........................... 102* 111* 91*
Richland-Kennewick-Pasco, WA....... 105* 105* 92*
Richmond-Petersburg, VA............ 99 99 98*
Rochester, NY...................... 107* 96* 95*
Rockford, IL....................... 98* 93* 93*
Sacramento-Yolo, CA................ 113* 108 106*
Salinas, CA........................ 111* 119* 110*
St. Louis, MO-IL................... 95* 105 98
San Antonio, TX.................... 87* 97* 95*
San Diego, CA...................... 111* 111 103
San Francisco-Oakland-San Jose, CA. 121* 113* 120*
(Continued)
(For each major group, average pay for all occupations = 100)
Construction Installation,
Metropolitan Area(1) and maintenance,
extraction and repair
Johnstown, PA...................... 84* 107*
Kansas City, MO-KS................. 103 94
Knoxville, TN...................... 86* 92*
Lincoln, NE........................ 82* 96*
Los Angeles-Riverside-Orange
County, CA......................... 110* 109*
Louisville, KY-IN.................. 104* 91*
Melbourne-Titusville-Palm Bay, FL.. 90* 101
Memphis, TN-AR-MS.................. 111* 103*
Miami-Fort Lauderdale, FL.......... 84* 93
Milwaukee-Racine, WI............... 105 111*
Minneapolis-St. Paul, MN-WI........ 116* 108
Mobile, AL......................... 91* 90*
New Orleans, LA.................... 85* 89*
New York-Northern New Jersey-Long
Island, NY-NJ-CT-PA................ 127* 100
Norfolk-VA Beach-Newport News,
VA-NC.............................. 87* 92*
Ocala, FL.......................... 81* 94*
Oklahoma City, OK.................. 86* 93*
Orlando, FL........................ 87* 104
Philadelphia-Wilmington-Atlantic
City, PA-NJ-DE-MD.................. 106 107*
Phoenix-Mesa, AZ................... 90* 106
Pittsburgh, PA..................... 91* 95*
Portland-Salem, OR-WA.............. 108 105
Providence-Fall River-Warwick,
RI-MA.............................. 98 88*
Reading, PA........................ 100 98
Reno, NV........................... 101 114*
Richland-Kennewick-Pasco, WA....... 99 92*
Richmond-Petersburg, VA............ 88* 97*
Rochester, NY...................... 95* 89*
Rockford, IL....................... 111* 115*
Sacramento-Yolo, CA................ 105 112*
Salinas, CA........................ 118* 109*
St. Louis, MO-IL................... 112* 95
San Antonio, TX.................... 79* 83*
San Diego, CA...................... 108* 108*
San Francisco-Oakland-San Jose, CA. 127* 116*
(Continued)
(For each major group, average pay for all occupations = 100)
Transportat-
Metropolitan Area1 Production ion and
material
moving
Johnstown, PA...................... 85* 80*
Kansas City, MO-KS................. 109* 100
Knoxville, TN...................... 93* 94*
Lincoln, NE........................ 94* 95*
Los Angeles-Riverside-Orange
County, CA......................... 97 101
Louisville, KY-IN.................. 92* 99
Melbourne-Titusville-Palm Bay, FL.. 89* 100
Memphis, TN-AR-MS.................. 94* 101
Miami-Fort Lauderdale, FL.......... 89* 92*
Milwaukee-Racine, WI............... 117* 107*
Minneapolis-St. Paul, MN-WI........ 111* 119*
Mobile, AL......................... 91* 98
New Orleans, LA.................... 86* 94*
New York-Northern New Jersey-Long
Island, NY-NJ-CT-PA................ 102 113*
Norfolk-VA Beach-Newport News,
VA-NC.............................. 86* 93*
Ocala, FL.......................... 86* 104*
Oklahoma City, OK.................. 97* 93*
Orlando, FL........................ 90 92*
Philadelphia-Wilmington-Atlantic
City, PA-NJ-DE-MD.................. 101 108
Phoenix-Mesa, AZ................... 102 100
Pittsburgh, PA..................... 94* 101
Portland-Salem, OR-WA.............. 99 103
Providence-Fall River-Warwick,
RI-MA.............................. 100 115*
Reading, PA........................ 104* 108*
Reno, NV........................... 93* 100
Richland-Kennewick-Pasco, WA....... 104* 100
Richmond-Petersburg, VA............ 101 104*
Rochester, NY...................... 102* 100
Rockford, IL....................... 107* 103*
Sacramento-Yolo, CA................ 106 110*
Salinas, CA........................ 100 96*
St. Louis, MO-IL................... 97 109*
San Antonio, TX.................... 100 95*
San Diego, CA...................... 100 102
San Francisco-Oakland-San Jose, CA. 110* 113*
(Continued)
(For each major group, average pay for all occupations = 100)
Management,
Metropolitan Area(1) All business, Professional
occupations and and related
financial
Seattle-Tacoma-Bremerton, WA....... 105* 95* 98
Springfield, MA.................... 94* 103* 107*
Springfield, MO.................... 89* 91* 88*
Tallahassee, FL.................... 86* 83* 86*
Tampa-St. Petersburg-Clearwater, FL 94* 99 90*
Visalia-Tulare-Porterville, CA..... 98* 95* 105*
Washington-Baltimore, DC-MD-VA-WV.. 105* 101 108*
York, PA........................... 98* 106* 101
Youngstown-Warren, OH.............. 98* 89* 94*
(Continued)
(For each major group, average pay for all occupations = 100)
Office and
Metropolitan Area(1) Service Sales and administrat-
related ive support
Seattle-Tacoma-Bremerton, WA....... 116* 103 105*
Springfield, MA.................... 106* 110* 110*
Springfield, MO.................... 89* 88* 86*
Tallahassee, FL.................... 84* 99 88*
Tampa-St. Petersburg-Clearwater, FL 92 106 93*
Visalia-Tulare-Porterville, CA..... 98* 101 96*
Washington-Baltimore, DC-MD-VA-WV.. 105* 101 110*
York, PA........................... 97* 102 93*
Youngstown-Warren, OH.............. 88* 101 87*
(Continued)
(For each major group, average pay for all occupations = 100)
Construction Installation,
Metropolitan Area1 and maintenance,
extraction and repair
Seattle-Tacoma-Bremerton, WA....... 115* 102
Springfield, MA.................... 107* 109*
Springfield, MO.................... 83* 90*
Tallahassee, FL.................... 91* 79*
Tampa-St. Petersburg-Clearwater, FL 88* 101
Visalia-Tulare-Porterville, CA..... 87* 99
Washington-Baltimore, DC-MD-VA-WV.. 103 101
York, PA........................... 91* 100
Youngstown-Warren, OH.............. 99 96*
(Continued)
(For each major group, average pay for all occupations = 100)
Transportat-
Metropolitan Area1 Production ion and
material
moving
Seattle-Tacoma-Bremerton, WA....... 108* 105*
Springfield, MA.................... 110* 65*
Springfield, MO.................... 95* 94*
Tallahassee, FL.................... 83* 108*
Tampa-St. Petersburg-Clearwater, FL 93* 100
Visalia-Tulare-Porterville, CA..... 93* 91*
Washington-Baltimore, DC-MD-VA-WV.. 102 98
York, PA........................... 94* 101
Youngstown-Warren, OH.............. 111* 111*
* The pay relative for this area is significantly different
from the national average of all areas at the 10% level of
significance. For additional details, see the technical memo.
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.