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 (Note: The HTML and text versions of this News Release posted on December 28, 2005, contained editing errors; however, the employee compensation data were correct. The PDF version of this News Release did not contain editing errors. On March 30, 2006, the HTML and text versions were modified so that the wording is the same as in the PDF version.) 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. Pay relatives averaged across all occupations were significantly different statistically from the national average in 66 of the 78 areas. 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? 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 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.(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 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: (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 statistical significance test for area-to-area comparisons calculated this way, and therefore 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 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. (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 (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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) (Average pay for all occupations nationally = 100. Average pay nationally for each occupational group shown = 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. Technical Note Because the NCS is a sample survey, pay relatives derived from NCS are subject to sampling error. Sampling error for pay relatives are differences that occur between the pay relatives estimated from the sample and the true pay relatives derived from the population. Pay relatives estimated from different samples selected using the same sample design may differ from one another. It is important to assess whether differences between each pay relative and the pay relative for the nation as a whole is likely to be the result of sampling error or of true differences in pay levels. Those areas whose difference is likely to be due to true differences in pay levels are denoted with an asterisk (*) in Table 1. To perform this assessment a test of statistical significance is conducted. The test constructs a 90-percent confidence interval that assumes the given area’s true pay relative is equal to the national average. The confidence interval is constructed so that there is a 90 percent probability the pay relative calculated from any one sample is contained within the confidence interval. If from a single sample a calculated pay relative falls within the confidence interval, then the pay relative is not statistically significant and the hypothesis that the true pay relative is equal to the national average is accepted. However, if the pay relative falls outside of the constructed confidence interval then the pay relative is statistically significant at the 10-percent level. The hypothesis that the given area’s pay relative is equal to the pay relative for the nation is rejected and one can conclude with reasonable confidence that the true pay relative is different from the national average. In addition to sampling error, pay relatives are subject to a variety of sources that can adversely 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. The pay relative regression methodology introduces another type of error. Regression models are subject to specification error. The significance test does not specifically measure specification error. However, care was taken to minimize this form of error by an extensive search across specifications for the model that performs best in terms of predictive accuracy. For more details on the statistical significance test, see Maury B. Gittleman, "Pay Relatives for Metropolitan Areas in the U.S.," Monthly Labor Review, March 2005, pp. 46-53.