Technical information: (202) 691-6567 USDL 05-623 http://www.bls.gov/cew/ For release: 10:00 A.M. EDT Media contact: 691-5902 Thursday, April 14, 2005 COUNTY EMPLOYMENT AND WAGES: THIRD QUARTER 2004 In September 2004, Rutherford County, Tenn., had the largest over- the-year percentage increase in employment among the largest counties in the U.S., according to preliminary data released today by the Bureau of Labor Statistics of the U.S. Department of Labor. Rutherford County experienced an over-the-year employment gain of 9.2 percent, compared with national job growth of 1.3 percent. St. Joseph County, Ind., had the largest over-the-year gain in average weekly wages in the third quarter of 2004, with an increase of 10.4 percent. The U.S. average weekly wage increased by 4.0 percent over the same time span. Of the 317 largest counties in the United States, as measured by 2003 employment, 139 had over-the-year percentage growth in employment above the national average in September 2004, and 162 experienced changes below the national average. Average weekly wages grew faster than the national average in 137 of the largest U.S. counties, while the percent change in average weekly wages was below the national average in 165 counties. The employment and average weekly wage data by county are compiled under the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from reports submitted by every employer subject to unemployment insurance (UI) laws. The 8.4 million employer reports cover 130.2 million full- and part-time workers. The attached tables and charts contain data for the nation and for the 317 U.S. counties with annual average employment levels of 75,000 or more in 2003. In addition, data for San Juan, Puerto Rico, are provided, but not used in calculating U.S. averages, or in the analysis in the text. (See Technical Note.) September 2004 employment and 2004 third-quarter average weekly wages for all states are provided in table 4 of this release. Data for all states, metropolitan statisti- cal areas, counties, and the nation through the second quarter of 2004 are available on the BLS Web site at http://www.bls.gov/cew/. Prelimi- nary data for the third quarter of 2004 and revised data for the first and second quarters of 2004 will be available in April on the BLS Web site. Large County Employment In September 2004, national employment, as measured by the QCEW program, was 130.2 million, up 1.3 percent from September 2003. The 317 U.S. counties with 75,000 or more employees accounted for 70.2 per- cent of total U.S. covered employment and 76.1 percent of total covered wages. These 317 counties had a net job gain of 1,073,000 over the year, accounting for 63.8 percent of the U.S. employment increase. Employment increased in 242 of the large counties from September 2003 to September 2004. Rutherford County, Tenn., had the largest over-the-year percentage increase in employment (9.2 percent). Clark County, Nev., had the next largest increase, 7.4 percent, followed by the counties of Riverside, Calif. (7.2 percent), Elkhart, Ind. (6.8 percent), and Montgomery, Texas (6.6 per- cent). (See table 1.) Employment declined in 54 counties from September 2003 to September 2004. The largest percentage decline in employment was in Trumbull County, Ohio (-3.7 percent), followed by the counties of Tulare, Calif. (-2.7 percent), Ingham, Mich. (-2.6 percent), Richmond, Ga. (-2.2 percent), and Okaloosa, Fla. (-2.0 percent). - 2 - Table A. Top 10 counties ranked by September 2004 employment, September 2003-04 employment change, and September 2003-04 percent change in employment -------------------------------------------------------------------------------- Employment in large counties -------------------------------------------------------------------------------- | | September 2004 employment | Net change in employment, | Percent change (thousands) | September 2003-04 | in employment, | (thousands) | September 2003-04 ----------------------------|---------------------------|----------------------- U.S. 130,248.9|U.S. 1,681.6|U.S. 1.3 ----------------------------|---------------------------|----------------------- Los Angeles, Calif. 4,019.6|Maricopa, Ariz. 58.6|Rutherford, Tenn. 9.2 Cook, Ill. 2,511.7|Clark, Nev. 56.5|Clark, Nev. 7.4 New York, N.Y. 2,201.7|Orange, Calif. 44.1|Riverside, Calif. 7.2 Harris, Texas 1,838.1|Riverside, Calif. 38.2|Elkhart, Ind. 6.8 Maricopa, Ariz. 1,633.3|Los Angeles, Calif. 29.4|Montgomery, Texas 6.6 Orange, Calif. 1,468.4|Fairfax, Va. 24.9|Lee, Fla. 6.1 Dallas, Texas 1,438.0|Miami-Dade, Fla. 20.0|Prince William, Va. 5.8 San Diego, Calif. 1,268.0|Orange, Fla. 19.8|Utah, Utah 5.3 King, Wash. 1,104.3|San Bernardino, Calif. 19.3|Loudoun, Va. 5.3 Miami-Dade, Fla. 979.5|Hillsborough, Fla. 18.8|Sarasota, Fla. 5.1 -------------------------------------------------------------------------------- The largest gains in employment from September 2003 to September 2004 were recorded in the counties of Maricopa, Ariz. (58,600), Clark, Nev. (56,500), Orange, Calif. (44,100), Riverside, Calif. (38,200) and Los Angeles, Calif. (29,400). (See table A.) The largest absolute declines in employment occurred in Wayne County, Mich. (-9,700), followed by the counties of Philadelphia, Pa. (-8,500), Cook, Ill. (-7,100), Baltimore City, Md. (-6,800), and Milwaukee, Wis. (-6,500). Large County Average Weekly Wages The national average weekly wage in the third quarter of 2004 was $733. Average weekly wages were higher than the national average in 118 of the largest 317 U.S. counties. New York County, N.Y., held the top position among the highest-paid large counties with an average weekly wage of $1,327. Santa Clara County, Calif., was second with an average weekly wage of $1,308, followed by Washington, D.C. ($1,207), Arlington, Va. ($1,196), and Suffolk, Mass. ($1,178). (See table B.) There were 198 counties with an average weekly wage below the national average in the third quarter of 2004. The lowest average weekly wages were reported in Cameron County, Texas ($468), followed by the counties of Hidalgo, Texas ($475), Horry, S.C. ($487), Webb, Texas ($496), and Yakima, Wash. ($500). (See table 1.) - 3 - Table B. Top 10 counties ranked by third quarter 2004 average weekly wages, third quarter 2003-04 change in average weekly wages, and third quarter 2003-04 percent change in average weekly wages -------------------------------------------------------------------------------- Average weekly wage in large counties -------------------------------------------------------------------------------- | | Percent change in Average weekly wage, | Change in average weekly | average weekly wage, third quarter 2004 | wage, third quarter | third quarter | 2003-04 | 2003-04 ---------------------------|---------------------------|------------------------ U.S. $733|U.S. $28|U.S. 4.0 ---------------------------|---------------------------|------------------------ New York, N.Y. $1,327|Suffolk, Mass. $98|St. Joseph, Ind. 10.4 Santa Clara, Calif. 1,308|New York, N.Y. 87|Suffolk, Mass. 9.1 Washington, D.C. 1,207|Arlington, Va. 86|Loudoun, Va. 8.4 Arlington, Va. 1,196|Washington, D.C. 85|Rockingham, N.H. 8.1 Suffolk, Mass. 1,178|Loudoun, Va. 75|Arlington, Va. 7.7 San Mateo, Calif. 1,132|Fairfield, Conn. 66|Washington, D.C. 7.6 Fairfield, Conn. 1,132|St. Joseph, Ind. 64|Catawba, N.C. 7.3 San Francisco, Calif. 1,107|Hartford, Conn. 56|Forsyth, N.C. 7.3 Somerset, N.J. 1,093|Montgomery, Md. 56|Lexington, S.C. 7.3 Fairfax, Va. 1,068|Rockingham, N.H. 55|Henrico, Va. 7.3 -------------------------------------------------------------------------------- Over the year, the national average weekly wage rose by 4.0 percent. Among the largest counties, St. Joseph, Ind., led the nation in growth in average weekly wages, with an increase of 10.4 percent from the third quarter of 2003. Suffolk, Mass., was second with 9.1 percent growth, followed by the counties of Loudoun, Va. (8.4 percent), Rockingham, N.H. (8.1 percent), and Arlington, Va. (7.7 percent). Seven counties experienced over-the-year declines in average weekly wages. Kalamazoo County, Mich., had the largest decrease, -7.7 percent, followed by the counties of Arapahoe, Colo. (-7.3 percent), Somerset, N.J. (-6.9 percent), King, Wash. (-2.4 percent), and Santa Cruz, Calif. (-1.3 percent). Ten Largest U.S. Counties Of the 10 largest U.S. counties (based on 2003 employment levels), 9 reported increases in employment, while 1 showed a decline from September 2003 to September 2004. Maricopa County, Ariz., experienced the fastest growth in employment among the largest counties, with a 3.7 percent increase. Within Maricopa County, employment rose in every industry group except information. The largest gains were in construc- tion (9.4 percent) and professional and business services (6.2 percent). (See table 2.) Orange County, Calif., had the next largest increase in employment, 3.1 percent, followed by Miami-Dade, Fla. (2.1 percent). The only decrease in employment for the 10 largest counties was in Cook County, Ill., with a 0.3 percent decline. The next lowest change in employment was recorded in Los Angeles County, Calif. (+0.7 percent), followed by the counties of New York, N.Y., Dallas, Texas, and Harris, Texas (+0.8 percent each). - 4 - Eight of the 10 largest U.S. counties saw over-the-year increases in average weekly wages. New York County, N.Y., had the fastest growth in wages among the top 10 counties, 7.0 percent. Within New York County, wages increased the most in natural resources and mining (15.2 percent) and financial activities (14.2 percent). San Diego County, Calif., was second in wage growth, increasing by 5.4 percent, followed by Los Angeles County, Calif., with a gain of 4.9 percent. The smallest wage gains among the 10 largest counties occurred in Dallas County, Texas (3.0 percent) and Orange County, Calif. (3.3 per- cent). King County, Wash., experienced the only decline in average weekly wages among the largest 10 counties (-2.4 percent). The in- formation sector in King County posted the largest drop in wages, with a decline of 28.3 percent over the year. A change in wage coverage for business establishments in Washington State contributed significantly to these wage declines. See the Coverage section of the Technical Note for more information. Largest County by State Table 3 shows September 2004 employment and the 2004 third-quarter average weekly wage in the largest county in each state. (This table includes two counties--Yellowstone, Mont., and Laramie, Wyo.--that have employment levels below 75,000). The employment levels in these counties in September 2004 ranged from approximately 4 million in Los Angeles County, Calif., to 39,800 in Laramie County, Wyo. The highest average weekly wage of these counties was in New York, N.Y. ($1,327), while the lowest average weekly wage was in Yellowstone County, Mont. ($572). ------------------------------------------------------------------- | Introduction of the Location Quotient Calculator | | | | In March 2005, the Bureau of Labor Statistics introduced a | | new tool on its Web site for analyzing data from the Quarterly | | Census of Employment and Wages program. The Location Quotient | | Calculator helps data users compare industry employment levels | | in a defined area to that of a larger area or base. For example, | | location quotients can be used to compare state employment by | | industry to that of the nation; or employment in a city, county, | | metropolitan statistical area, or other defined geographic subarea| | to that in the state. A link to the Location Quotient Calculator | | and other relevant information can be found at http://www.bls.gov/| | cew/cewlq.htm. | ------------------------------------------------------------------- - 5 - Technical Note These data are the product of a federal-state cooperative program, the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from summaries of employment and to- tal pay of workers covered by state and federal unemployment insurance (UI) legislation and provided by State Workforce Agencies (SWAs). The summaries are a result of the administration of state unemployment insurance programs that require most employers to pay quarterly taxes based on the employment and wages of workers covered by UI. Data for 2004 are preliminary and sub- ject to revision. For purposes of this release, large counties are defined as having employment levels of 75,000 or greater. Each year, these large counties are selected on the basis of the preliminary annual average of employment for the previous year. The 318 counties discussed in this release were derived using 2003 preliminary annual averages of employment. These counties will be included in all 2004 quarterly releases. The counties in table 2 are selected and sorted each year based on the annual average employment from the preceding year. The preliminary QCEW data presented in this release may differ from data released by the individual states. These potential differences result from the states' continuing receipt of UI data over time and ongoing review and editing. The individual states determine their data release timetables. Differences between QCEW, BED, and CES employment measures The Bureau publishes three different establishment-based employment measures for any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED), and Current Employment Statistics (CES)--makes use of the quarterly UI employment reports in producing data; however, each measure has a somewhat different universe coverage, estimation pro- cedure, and publication product. Differences in coverage and estimation methods can result in somewhat different measures of over-the-quarter employment change. It is important to understand program differences and the intended uses of the program products. (See table below.) Additional information on each program can be obtained from the program Web sites shown in the table below. - 6 - Summary of Major Differences between QCEW, BED, and CES Employment Measures -------------------------------------------------------------------------------- | QCEW | BED | CES -----------|---------------------|----------------------|----------------------- Source |--Count of UI admini-|--Count of longitudi- |--Sample survey: | strative records | nally-linked UI ad- | 400,000 establish- | submitted by 8.4 | ministrative records| ments | million establish- | submitted by 6.5 | | ments | million private-sec-| | | tor employers | -----------|---------------------|----------------------|----------------------- Coverage |--UI and UCFE cover- |--UI coverage, exclud-|Nonfarm wage and sal- | age, including all | ing government, pri-| ary jobs: | employers subject | vate households, and|--UI coverage, exclud- | to state and feder-| establishments with | ing agriculture, pri- | al UI laws | zero employment | vate households, and | | | self-employed workers | | |--Other employment, in- | | | cluding railroads, | | | religious organiza- | | | tions, and other non- | | | UI-covered jobs -----------|---------------------|----------------------|----------------------- Publication|--Quarterly |--Quarterly |--Monthly frequency | -7 months after the| -8 months after the | -Usually first Friday | end of each quar- | end of each quarter| of following month | ter | | -----------|---------------------|----------------------|----------------------- Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam- file | and publishes each | quarter to longitu- | pling frame and annu- | new quarter of UI | dinal database and | ally realigns (bench- | data | directly summarizes | marks) sample esti- | | gross job gains and | mates to first quar- | | losses | ter UI levels -----------|---------------------|----------------------|------------------------ Principal |--Provides a quarter-|--Provides quarterly |--Provides current month- products | ly and annual uni- | employer dynamics | ly estimates of employ- | verse count of es- | data on establish- | ment, hours, and earn- | tablishments, em- | ment openings, clos-| ings at the MSA, state, | ployment, and wages| ings, expansions, | and national level by | at the county, MSA,| and contractions at | industry | state, and national| the national level | | levels by detailed |--Future expansions | | industry | will include data at| | | the county, MSA, and| | | state level and by | | | size of establish- | | | ment | -----------|---------------------|----------------------|-------------------------- Principal |--Major uses include:|--Major uses include: |--Major uses include: uses | -Detailed locality | -Business cycle | -Principal national | data | analysis | economic indicator | -Periodic universe | -Analysis of employ-| -Official time series | counts for bench- | er dynamics under- | for employment change | marking sample | lying economic ex- | measures | survey estimates | pansions and con- | -Input into other ma- | -Sample frame for | tractions | jor economic indi- | BLS establishment | -Future: Employment| cators | surveys | expansion and con- | | | traction by size of| | | establishment | -----------|---------------------|----------------------|-------------------------- Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/ Web sites | | | ----------------------------------------------------------------------------------- - 7 - Coverage Employment and wage data for workers covered by state UI laws and for federal civilian workers covered by the Unemployment Compensation for Federal Employees (UCFE) program are compiled from quarterly contribution reports submitted to the SWAs by employers. In addition to the quarterly contribution reports, employers who operate multiple establishments within a state complete a questionnaire, called the "Multiple Worksite Report," which provides detailed information on the location and industry of each of their establishments. The employment and wage data included in this release are derived from microdata summaries of more than 8 million employer reports of employment and wages submitted by states to the BLS. These re- ports are based on place of employment rather than place of residence. UI and UCFE coverage is broad and basically comparable from state to state. In 2003, UI and UCFE programs covered workers in 127.8 million jobs. The estimated 122.9 million workers in these jobs (after adjust- ment for multiple jobholders) represented 96.6 percent of civilian wage and salary employment. Covered workers received $4.826 trillion in pay, representing 94.6 percent of the wage and salary component of personal income and 43.9 percent of the gross domestic product. Major exclusions from UI coverage include self-employed workers, most agricultural workers on small farms, all members of the Armed Forces, elected officials in most states, most employees of railroads, some domes- tic workers, most student workers at schools, and employees of certain small nonprofit organizations. State and federal UI laws change periodically. These changes may have an impact on the employment and wages reported by employers covered under the UI program. Coverage changes may affect the over-the-year comparisons presented in this news release. Effective January 1, 2004, the Washington Employment Security Department no longer includes as covered wages an em- ployee's income attributable to the transfer of shares of stock to the em- ployee. This change in wage coverage pertains to all establishments in Washington State and contributes significantly to over-the-year changes in wages in the state in 2004. Concepts and methodology Monthly employment is based on the number of workers who worked during or received pay for the pay period including the 12th of the month. With few exceptions, all employees of covered firms are reported, including pro- duction and sales workers, corporation officials, executives, supervisory personnel, and clerical workers. Workers on paid vacations and part-time workers also are included. Average weekly wage values are calculated by dividing quarterly total wages by the average of the three monthly employment levels (all employees, as described above) and dividing the result by 13, for the 13 weeks in the quarter. These calculations are made using unrounded employment and wage values. The average wage values that can be calculated using rounded data from the BLS database may differ from the averages reported. Included in the quarterly wage data are non-wage cash payments such as bonuses, the cash value of meals and lodging when supplied, tips and other gratuities, and, in some states, employer contributions to certain deferred compensation plans such as 401(k) plans and stock options. Average weekly wages are affected by the ratio of full-time to part- time workers as well as the number of individuals in high-paying and low- paying occupations and the incidence of pay periods within a quarter. When comparing average weekly wage levels between industries and/or states, these factors should be taken into consideration. - 8 - Federal government pay levels are subject to periodic, sometimes large, fluctuations due to a calendar effect that consists of some quarters having more pay periods than others. Most federal employees are paid on a bi- weekly pay schedule. As a result of this schedule, in some quarters, federal wages contain payments for six pay periods, while in other quarters their wages include payments for seven pay periods. Over-the-year comparisons of average weekly wages may reflect this calendar effect. Higher growth in average weekly wages may be attributed, in part, to a comparison of quarterly wages for the current year, which include seven pay periods, with year-ago wages that reflect only six pay periods. An opposite effect will occur when wages in the current period, which contain six pay periods, are compared with year-ago wages that include seven pay periods. The effect on over-the-year pay comparisons can be pronounced in federal government due to the uniform nature of federal payroll processing. This pattern may exist in private sector pay, however, because there are more pay period types (weekly, biweekly, semimonthly, monthly) it is less pronounced. The effect is most visible in counties with large concentra- tions of federal employment. In order to ensure the highest possible quality of data, states verify with employers and update, if necessary, the industry, location, and own- ership classification of all establishments on a 3-year cycle. Changes in establishment classification codes resulting from this process are in- troduced with the data reported for the first quarter of the year. Changes resulting from improved employer reporting also are introduced in the first quarter. QCEW data are not designed as a time series. QCEW data are simply the sums of individual establishment records and reflect the number of establishments that exist in a county or industry at a point in time. Establishments can move in or out of a county or industry for a number of reasons--some reflecting economic events, others reflecting administrative changes. For example, economic change would come from a firm relocating into the county; administrative change would come from a company correcting its county designation. The over-the-year changes of employment and wages presented in this release have been adjusted to account for most of the administrative corrections made to the underlying establishment reports. This is done by modifying the prior-year levels used to calculate the over-the-year changes. Percent changes are calcuated using an adjusted version of the final 2003 quarterly data as the base data. The adjusted prior-year levels used to calculate the over-the-year percent change in employment and wages are not published. These adjusted prior-year levels do not match the unadjusted data maintained on the BLS Web site. Over-the-year change calculations based on data from the Web site, or from data published in prior BLS news releases, may differ substantially from the over-the-year changes presented in this news release. The adjusted data used to calculate the over-the-year change measures presented in this release account for most of the administrative changes-- those occurring when employers update the industry, location, and ownership information of their establishments. The most common adjustments for administrative change are the result of updated information about the county location of individual establishments. The adjusted data do not account for administrative changes caused by (1) multi-unit employers who start reporting for each individual estab- lishment rather than as a single entity and (2) the classification of establishments previously reported in the unknown county or unknown in- dustry categories. - 9 - The adjusted data used to calculate the over-the-year change measures presented in any County Employment and Wages news release are valid for comparisons between the starting and ending points (a 12-month period) used in that particular release. Comparisons may not be valid for any time period other than the one featured in a release even if the changes were calculated using adjusted data. County definitions are assigned according to Federal Information Processing Standards Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104- 106. Areas shown as counties include those designated as independent cities in some jurisdictions and, in Alaska, those designated as census areas where counties have not been created. County data also are presented for the New England states for comparative purposes even though townships are the more common designation used in New England (and New Jersey). The regions re- ferred to in this release are defined as census regions. Additional statistics and other information An annual bulletin, Employment and Wages, features comprehensive infor- mation by detailed industry on establishments, employment, and wages for the nation and all states. Employment and Wages Annual Averages, 2003 is available for sale from the BLS Publications Sales Center, P.O. Box 2145, Chicago, Illinois 60690, telephone 312-353-1880. The 2003 bulletin will be available in April 2005 in a portable document format (PDF) on the BLS Web site at http://www.bls.gov/cew/cewbultn03.htm. News releases on quarterly measures of gross job flows also are available upon request from the Division of Administrative Statistics and Labor Turnover (Business Employment Dynamics), telephone 202-691-6467; (http://www.bls.gov/bdm/); (e-mail: BDMInfo@bls.gov). Information in this release will be made available to sensory impaired individuals upon request. Voice phone: 202-691-5200; TDD message referral phone number: 1-800-877-8339. Table 1. Covered(1) establishments, employment, and wages in the 318 largest counties, third quarter 2004(2) Employment Average weekly wage(5) Establishments, third quarter Percent County(3) 2004 September Percent Ranking Average change, Ranking (thousands) 2004 change, by weekly third by (thousands) September percent wage quarter percent 2003-04(4) change 2003-04 change (4) United States(6)......... 8,421.8 130,248.9 1.3 - $733 4.0 - Jefferson, AL............ 18.5 368.3 0.0 244 739 3.6 172 Madison, AL.............. 7.9 165.3 2.6 66 773 2.7 238 Mobile, AL............... 9.6 161.3 -0.3 261 601 2.6 247 Montgomery, AL........... 6.6 131.3 1.4 134 619 2.1 276 Tuscaloosa, AL........... 4.2 78.8 3.0 51 614 2.7 238 Anchorage Borough, AK.... 7.7 145.0 0.8 175 809 4.0 138 Maricopa, AZ............. 79.9 1,633.3 3.7 32 731 4.7 77 Pima, AZ................. 17.5 339.6 2.9 56 640 4.1 133 Benton, AR............... 4.5 86.1 4.4 16 679 4.5 102 Pulaski, AR.............. 13.3 242.6 0.9 166 669 4.7 77 Washington, AR........... 5.1 87.0 2.3 81 599 6.6 15 Alameda, CA.............. 47.7 674.8 -0.5 270 971 3.6 172 Contra Costa, CA......... 27.4 339.2 0.7 189 923 5.2 53 Fresno, CA............... 28.6 348.8 -0.4 266 591 3.5 187 Kern, CA................. 15.8 257.7 0.4 217 632 5.0 60 Los Angeles, CA.......... 360.1 4,019.6 0.7 189 833 4.9 68 Marin, CA................ 11.8 110.3 0.8 175 914 4.8 72 Monterey, CA............. 11.9 180.2 1.1 154 643 4.7 77 Orange, CA............... 89.7 1,468.4 3.1 47 840 3.3 199 Placer, CA............... 9.4 130.9 3.7 32 738 3.2 202 Riverside, CA............ 38.3 572.4 7.2 3 635 5.3 49 Sacramento, CA........... 46.5 608.8 1.4 134 817 2.4 262 San Bernardino, CA....... 41.9 600.7 3.3 40 655 4.1 133 San Diego, CA............ 86.2 1,268.0 1.4 134 800 5.4 44 San Francisco, CA........ 43.0 521.9 -0.6 277 1,107 3.4 194 San Joaquin, CA.......... 15.8 221.9 0.6 199 649 3.5 187 San Luis Obispo, CA...... 8.6 101.7 0.4 217 631 6.9 12 San Mateo, CA............ 22.7 328.7 0.0 244 1,132 0.8 301 Santa Barbara, CA........ 13.1 180.6 0.6 199 702 3.7 163 Santa Clara, CA.......... 52.3 850.8 0.7 189 1,308 3.1 209 Santa Cruz, CA........... 8.3 100.3 1.4 134 684 -1.3 308 Solano, CA............... 9.5 128.1 0.8 175 696 2.5 257 Sonoma, CA............... 17.2 193.1 1.5 121 732 2.7 238 Stanislaus, CA........... 13.1 174.9 0.3 225 632 3.8 157 Tulare, CA............... 8.5 135.9 -2.7 307 531 5.1 58 Ventura, CA.............. 20.5 302.2 0.9 166 779 1.3 296 Yolo, CA................. 5.1 98.6 1.3 141 734 5.0 60 Adams, CO................ 8.7 143.9 0.8 175 706 2.6 247 Arapahoe, CO............. 19.0 269.0 -0.3 261 870 -7.3 311 Boulder, CO.............. 11.9 153.5 2.5 73 870 0.6 304 Denver, CO............... 24.6 427.3 1.5 121 888 2.9 224 El Paso, CO.............. 16.1 237.9 1.5 121 696 2.7 238 Jefferson, CO............ 18.2 204.4 0.7 189 765 3.2 202 Larimer, CO.............. 9.3 124.4 2.1 87 689 3.1 209 Fairfield, CT............ 31.8 411.4 0.1 233 1,132 6.2 20 Hartford, CT............. 24.4 483.0 1.1 154 916 6.5 16 New Haven, CT............ 22.0 362.2 2.1 87 811 3.4 194 New London, CT........... 6.6 129.4 0.0 244 762 4.2 120 New Castle, DE........... 19.3 280.2 0.3 225 858 2.4 262 Washington, DC........... 30.1 658.3 1.2 147 1,207 7.6 6 Alachua, FL.............. 6.0 123.4 1.7 111 566 5.4 44 Brevard, FL.............. 12.9 194.5 (7) - 727 (7) - Broward, FL.............. 58.6 687.9 1.8 105 696 3.6 172 Collier, FL.............. 10.7 115.8 3.6 35 649 4.7 77 Duval, FL................ 23.0 436.3 2.6 66 711 2.4 262 Escambia, FL............. 7.4 124.8 2.8 62 583 3.2 202 Hillsborough, FL......... 32.2 606.5 3.2 45 694 3.7 163 Lee, FL.................. 15.7 194.3 6.1 6 637 6.0 27 Leon, FL................. 7.4 143.6 1.9 98 631 3.6 172 Manatee, FL.............. 7.3 116.9 4.4 16 571 4.6 91 Marion, FL............... 6.8 90.3 4.7 13 541 3.6 172 Miami-Dade, FL........... 82.6 979.5 2.1 87 717 (7) - Okaloosa, FL............. 5.5 79.8 -2.0 304 592 6.9 12 Orange, FL............... 30.8 624.4 3.3 40 682 5.7 33 Palm Beach, FL........... 44.2 503.7 1.1 154 720 3.9 147 Pasco, FL................ 7.7 84.0 3.1 47 534 6.2 20 Pinellas, FL............. 29.0 437.1 3.9 25 638 2.2 272 Polk, FL................. 10.8 185.7 4.4 16 601 3.6 172 Sarasota, FL............. 13.4 153.9 5.1 10 618 5.3 49 Seminole, FL............. 12.6 153.4 4.4 16 645 2.9 224 Volusia, FL.............. 12.3 149.2 (7) - 558 (7) - Bibb, GA................. 4.7 85.9 0.5 205 623 4.4 111 Chatham, GA.............. 7.0 127.1 1.5 121 631 4.5 102 Clayton, GA.............. 4.4 106.1 (7) - 808 5.8 29 Cobb, GA................. 19.8 296.8 -1.3 293 803 3.6 172 De Kalb, GA.............. 16.9 288.7 -0.9 287 792 2.9 224 Fulton, GA............... 37.1 726.6 1.5 121 958 4.2 120 Gwinnett, GA............. 21.4 307.9 3.1 47 773 1.2 297 Muscogee, GA............. 4.7 95.9 -1.7 300 589 3.9 147 Richmond, GA............. 4.8 102.8 -2.2 305 627 4.7 77 Honolulu, HI............. 23.2 426.7 2.7 64 703 4.6 91 Ada, ID.................. 13.2 190.6 3.9 25 675 4.5 102 Champaign, IL............ 3.9 90.6 0.6 199 639 2.2 272 Cook, IL................. 126.7 2,511.7 -0.3 261 871 4.3 116 Du Page, IL.............. 32.6 577.1 0.8 175 851 2.4 262 Kane, IL................. 11.1 201.6 0.4 217 686 2.7 238 Lake, IL................. 19.0 326.9 1.2 147 874 4.5 102 McHenry, IL.............. 7.5 96.8 2.5 73 666 2.6 247 McLean, IL............... 3.4 83.9 -1.9 301 702 1.4 292 Madison, IL.............. 5.6 93.5 -1.0 290 614 4.8 72 Peoria, IL............... 4.6 98.4 2.3 81 692 4.8 72 Rock Island, IL.......... 3.4 78.3 -0.7 282 715 2.1 276 St. Clair, IL............ 5.1 92.9 -0.1 255 606 5.0 60 Sangamon, IL............. 5.1 130.3 (7) - 736 (7) - Will, IL................. 10.8 163.9 2.9 56 698 2.2 272 Winnebago, IL............ 6.6 137.6 0.7 189 632 0.6 304 Allen, IN................ 8.7 180.5 1.2 147 658 2.7 238 Elkhart, IN.............. 4.8 126.3 6.8 4 658 5.6 34 Hamilton, IN............. 6.2 90.6 4.9 11 755 4.1 133 Lake, IN................. 9.9 193.9 0.0 244 670 4.2 120 Marion, IN............... 23.7 581.1 1.5 121 765 3.8 157 St. Joseph, IN........... 6.0 125.0 1.6 118 677 10.4 1 Vanderburgh, IN.......... 4.8 107.4 -1.3 293 628 5.4 44 Linn, IA................. 6.1 116.0 0.9 166 706 3.4 194 Polk, IA................. 14.2 261.5 1.8 105 740 4.7 77 Scott, IA................ 5.1 86.4 1.9 98 604 2.5 257 Johnson, KS.............. 18.9 296.6 1.9 98 764 3.8 157 Sedgwick, KS............. 11.6 241.3 1.2 147 689 6.5 16 Shawnee, KS.............. 4.7 94.6 -1.5 298 624 4.2 120 Fayette, KY.............. 8.8 166.5 0.8 175 681 3.7 163 Jefferson, KY............ 21.6 417.1 0.0 244 726 5.5 39 Caddo, LA................ 7.0 122.0 1.8 105 612 5.5 39 Calcasieu, LA............ 4.6 80.8 -0.4 266 598 0.7 302 East Baton Rouge, LA..... 13.1 244.9 0.8 175 618 2.0 281 Jefferson, LA............ 14.0 210.5 -0.4 266 613 4.3 116 Lafayette, LA............ 7.6 118.4 -0.5 270 635 1.6 287 Orleans, LA.............. 12.6 244.6 -1.6 299 677 1.5 290 Cumberland, ME........... 12.0 171.0 1.1 154 671 5.5 39 Anne Arundel, MD......... 13.6 215.7 2.4 77 773 3.9 147 Baltimore, MD............ 20.7 366.0 1.8 105 751 2.3 270 Frederick, MD............ 5.5 90.2 2.8 62 701 4.9 68 Howard, MD............... 8.0 138.6 0.1 233 846 5.0 60 Montgomery, MD........... 31.5 450.6 0.5 205 953 6.2 20 Prince Georges, MD....... 15.2 314.9 1.6 118 820 5.8 29 Baltimore City, MD....... 14.1 355.4 -1.9 301 825 1.2 297 Barnstable, MA........... 9.3 99.4 -0.2 258 635 4.6 91 Bristol, MA.............. 15.4 218.9 -0.5 270 672 6.2 20 Essex, MA................ 20.8 294.1 -0.9 287 800 3.1 209 Hampden, MA.............. 14.2 198.6 -1.1 291 704 6.0 27 Middlesex, MA............ 48.2 782.0 -0.5 270 1,043 4.6 91 Norfolk, MA.............. 21.9 316.2 -0.8 285 885 1.6 287 Plymouth, MA............. 13.7 175.0 1.3 141 719 4.8 72 Suffolk, MA.............. 22.4 557.5 -0.5 270 1,178 9.1 2 Worcester, MA............ 20.5 318.3 0.1 233 783 6.1 24 Genesee, MI.............. 8.6 155.3 0.4 217 715 2.6 247 Ingham, MI............... 7.0 164.9 -2.6 306 723 3.0 217 Kalamazoo, MI............ 5.5 116.1 -0.2 258 688 -7.7 312 Kent, MI................. 14.6 336.4 1.3 141 703 2.6 247 Macomb, MI............... 18.1 325.4 0.5 205 818 4.2 120 Oakland, MI.............. 41.4 717.1 -0.8 285 893 2.9 224 Ottawa, MI............... 5.8 115.1 3.0 51 672 3.9 147 Saginaw, MI.............. 4.6 89.9 -1.4 297 691 2.4 262 Washtenaw, MI............ 8.2 195.2 0.4 217 847 1.8 282 Wayne, MI................ 35.0 791.2 -1.2 292 874 4.7 77 Anoka, MN................ 7.5 113.1 1.0 161 734 4.9 68 Dakota, MN............... 9.7 169.2 2.0 93 740 2.9 224 Hennepin, MN............. 40.5 827.3 0.8 175 933 2.6 247 Olmsted, MN.............. 3.3 87.3 0.7 189 819 3.5 187 Ramsey, MN............... 14.9 329.6 0.3 225 819 2.9 224 St. Louis, MN............ 5.7 94.8 1.4 134 634 2.4 262 Stearns, MN.............. 4.2 77.7 1.2 147 611 6.1 24 Harrison, MS............. 4.6 90.0 -0.5 270 520 -0.2 306 Hinds, MS................ 6.6 130.2 0.1 233 651 4.0 138 Boone, MO................ 4.3 78.2 2.6 66 585 2.8 235 Clay, MO................. 4.9 86.9 0.5 205 698 4.5 102 Greene, MO............... 8.0 146.2 0.8 175 591 4.2 120 Jackson, MO.............. 18.7 363.3 -0.3 261 757 4.6 91 St. Charles, MO.......... 7.3 114.9 (7) - 644 3.9 147 St. Louis, MO............ 33.7 617.5 -0.1 255 778 1.4 292 St. Louis City, MO....... 8.2 224.8 (7) - 811 4.0 138 Douglas, NE.............. 14.9 309.4 0.5 205 702 3.4 194 Lancaster, NE............ 7.5 153.6 2.5 73 621 4.0 138 Clark, NV................ 39.0 822.6 7.4 2 701 4.6 91 Washoe, NV............... 12.7 209.0 4.7 13 713 2.7 238 Hillsborough, NH......... 12.4 194.2 0.8 175 828 6.3 19 Rockingham, NH........... 10.7 136.7 2.9 56 738 8.1 4 Atlantic, NJ............. 6.6 147.3 -0.3 261 666 2.9 224 Bergen, NJ............... 34.3 447.7 0.2 229 910 2.9 224 Burlington, NJ........... 11.1 198.8 1.0 161 789 3.5 187 Camden, NJ............... 13.4 210.8 3.8 29 741 2.2 272 Essex, NJ................ 21.4 357.4 0.1 233 947 4.3 116 Gloucester, NJ........... 6.1 100.4 3.9 25 679 5.4 44 Hudson, NJ............... 13.9 234.4 0.4 217 980 5.6 34 Mercer, NJ............... 10.7 217.4 -0.9 287 934 1.5 290 Middlesex, NJ............ 20.7 392.0 0.8 175 938 4.0 138 Monmouth, NJ............. 19.9 254.9 2.7 64 786 3.7 163 Morris, NJ............... 17.7 281.3 0.4 217 1,034 2.3 270 Ocean, NJ................ 11.5 148.9 3.0 51 623 3.1 209 Passaic, NJ.............. 12.5 178.1 2.0 93 786 4.2 120 Somerset, NJ............. 9.9 166.1 (7) - 1,093 -6.9 310 Union, NJ................ 14.9 232.1 (7) - 912 (7) - Bernalillo, NM........... 16.5 315.6 1.5 121 665 2.6 247 Albany, NY............... 9.6 227.9 0.0 244 787 4.7 77 Bronx, NY................ 15.4 216.4 1.2 147 746 5.8 29 Broome, NY............... 4.5 94.3 -0.4 266 602 4.2 120 Dutchess, NY............. 7.9 116.5 1.5 121 744 1.6 287 Erie, NY................. 23.3 457.9 0.7 189 663 5.2 53 Kings, NY................ 42.0 446.5 1.7 111 665 3.6 172 Monroe, NY............... 17.7 379.9 -0.7 282 752 5.0 60 Nassau, NY............... 50.7 597.4 0.6 199 808 3.5 187 New York, NY............. 112.7 2,201.7 0.8 175 1,327 7.0 11 Oneida, NY............... 5.3 108.3 0.6 199 581 3.2 202 Onondaga, NY............. 12.6 249.0 0.9 166 687 2.8 235 Orange, NY............... 9.3 127.4 1.4 134 632 4.5 102 Queens, NY............... 40.3 478.1 0.9 166 751 1.8 282 Richmond, NY............. 8.1 88.3 1.5 121 693 4.2 120 Rockland, NY............. 9.4 110.5 0.1 233 772 3.6 172 Suffolk, NY.............. 47.7 602.1 1.1 154 797 4.2 120 Westchester, NY.......... 35.3 410.4 1.7 111 963 (7) - Buncombe, NC............. 6.9 106.6 0.9 166 588 4.6 91 Catawba, NC.............. 4.2 86.7 1.3 141 588 7.3 7 Cumberland, NC........... 5.6 112.0 2.9 56 584 5.4 44 Durham, NC............... 6.1 166.3 0.9 166 955 3.6 172 Forsyth, NC.............. 8.4 176.3 0.5 205 761 7.3 7 Guilford, NC............. 13.6 266.5 1.5 121 674 2.7 238 Mecklenburg, NC.......... 27.2 507.2 0.5 205 838 1.8 282 New Hanover, NC.......... 6.4 92.9 4.0 23 598 4.7 77 Wake, NC................. 23.3 392.6 3.3 40 734 3.2 202 Cass, ND................. 5.4 90.0 3.7 32 610 3.9 147 Butler, OH............... 6.9 134.5 2.1 87 663 3.8 157 Cuyahoga, OH............. 38.2 759.8 0.0 244 776 4.9 68 Franklin, OH............. 29.1 685.4 0.1 233 741 3.8 157 Hamilton, OH............. 24.6 543.8 0.2 229 808 5.8 29 Lake, OH................. 6.7 98.8 0.0 244 630 3.6 172 Lorain, OH............... 6.2 102.3 0.5 205 646 5.0 60 Lucas, OH................ 10.8 226.7 0.1 233 669 1.4 292 Mahoning, OH............. 6.4 106.9 1.0 161 570 3.1 209 Montgomery, OH........... 13.2 285.7 -0.5 270 707 4.0 138 Stark, OH................ 9.1 166.8 0.0 244 596 3.7 163 Summit, OH............... 14.7 268.5 1.2 147 694 2.1 276 Trumbull, OH............. 4.8 83.5 -3.7 308 685 6.4 18 Oklahoma, OK............. 21.7 408.3 1.9 98 645 3.2 202 Tulsa, OK................ 18.2 320.0 1.0 161 667 5.0 60 Clackamas, OR............ 11.5 138.7 2.1 87 688 3.6 172 Jackson, OR.............. 6.2 81.4 3.3 40 571 3.6 172 Lane, OR................. 10.4 142.2 3.3 40 598 3.1 209 Marion, OR............... 8.5 135.7 2.6 66 580 1.4 292 Multnomah, OR............ 25.5 422.4 1.6 118 760 3.7 163 Washington, OR........... 14.6 227.7 3.2 45 877 5.5 39 Allegheny, PA............ 35.6 687.2 -0.6 277 774 3.6 172 Berks, PA................ 9.0 163.1 1.7 111 668 3.6 172 Bucks, PA................ 19.9 257.3 2.6 66 709 4.1 133 Chester, PA.............. 14.5 224.3 2.0 93 902 4.6 91 Cumberland, PA........... 5.7 126.5 1.9 98 704 2.9 224 Dauphin, PA.............. 7.0 176.0 1.5 121 736 4.8 72 Delaware, PA............. 13.5 207.7 -0.2 258 778 3.9 147 Erie, PA................. 7.2 127.9 1.8 105 586 3.0 217 Lackawanna, PA........... 5.8 98.7 1.1 154 586 4.6 91 Lancaster, PA............ 11.7 226.4 1.7 111 656 4.6 91 Lehigh, PA............... 8.4 174.2 0.4 217 726 3.7 163 Luzerne, PA.............. 8.0 141.8 -0.6 277 599 4.0 138 Montgomery, PA........... 27.6 480.6 0.3 225 909 4.7 77 Northampton, PA.......... 6.1 91.5 0.5 205 664 4.7 77 Philadelphia, PA......... 28.5 627.6 -1.3 293 869 5.3 49 Westmoreland, PA......... 9.4 136.8 3.5 37 605 4.5 102 York, PA................. 8.5 169.0 2.6 66 666 3.9 147 Kent, RI................. 5.6 81.7 0.5 205 676 2.4 262 Providence, RI........... 17.8 288.5 0.0 244 731 5.2 53 Charleston, SC........... 11.8 194.1 3.4 38 621 3.7 163 Greenville, SC........... 12.1 221.1 0.5 205 663 3.3 199 Horry, SC................ 8.0 108.4 4.6 15 487 3.0 217 Lexington, SC............ 5.5 86.3 1.8 105 589 7.3 7 Richland, SC............. 9.4 208.0 2.0 93 645 4.4 111 Spartanburg, SC.......... 6.2 115.0 -0.6 277 654 4.1 133 Minnehaha, SD............ 6.0 109.4 1.7 111 624 5.6 34 Davidson, TN............. 17.9 432.2 0.9 166 733 3.1 209 Hamilton, TN............. 8.3 191.1 1.7 111 645 3.0 217 Knox, TN................. 10.3 219.1 3.4 38 632 2.8 235 Rutherford, TN........... 3.7 91.6 9.2 1 647 0.9 300 Shelby, TN............... 19.8 495.9 0.1 233 787 6.8 14 Bell, TX................. 4.2 91.5 3.6 35 573 4.0 138 Bexar, TX................ 29.8 661.0 0.7 189 644 4.2 120 Brazoria, TX............. 4.1 76.1 0.0 244 693 3.0 217 Brazos, TX............... 3.5 78.9 1.5 121 535 2.7 238 Cameron, TX.............. 6.1 115.6 0.7 189 468 4.7 77 Collin, TX............... 12.8 211.8 (7) - 797 1.0 299 Dallas, TX............... 68.2 1,438.0 0.8 175 889 3.0 217 Denton, TX............... 8.5 133.2 2.6 66 639 2.9 224 El Paso, TX.............. 12.5 254.5 0.5 205 531 4.5 102 Fort Bend, TX............ 6.4 102.3 4.4 16 729 2.1 276 Galveston, TX............ 4.8 86.6 -1.9 301 641 3.9 147 Harris, TX............... 90.2 1,838.1 0.8 175 862 4.5 102 Hidalgo, TX.............. 9.3 185.3 3.9 25 475 4.2 120 Jefferson, TX............ 5.8 117.2 -0.1 255 661 2.6 247 Lubbock, TX.............. 6.5 118.5 2.9 56 554 0.7 302 McLennan, TX............. 4.7 99.4 2.3 81 583 1.7 286 Montgomery, TX........... 6.4 92.8 6.6 5 654 3.0 217 Nueces, TX............... 8.0 143.3 0.7 189 612 5.2 53 Potter, TX............... 3.9 76.5 0.1 233 585 5.6 34 Smith, TX................ 4.9 86.8 1.9 98 648 6.1 24 Tarrant, TX.............. 34.0 701.0 1.3 141 758 5.0 60 Travis, TX............... 25.2 516.3 2.4 77 824 2.4 262 Webb, TX................. 4.3 78.0 2.3 81 496 4.4 111 Williamson, TX........... 5.1 87.0 4.1 22 746 -0.4 307 Davis, UT................ 6.4 94.2 4.0 23 614 3.2 202 Salt Lake, UT............ 35.0 524.7 2.3 81 671 3.5 187 Utah, UT................. 11.2 152.2 5.3 8 565 2.5 257 Weber, UT................ 5.4 86.8 1.3 141 556 1.8 282 Chittenden, VT........... 5.7 96.4 2.1 87 725 5.1 58 Arlington, VA............ 7.0 155.6 (7) - 1,196 7.7 5 Chesterfield, VA......... 6.7 112.4 2.9 56 670 4.2 120 Fairfax, VA.............. 29.8 548.5 4.8 12 1,068 2.5 257 Henrico, VA.............. 8.3 166.8 1.4 134 779 7.3 7 Loudoun, VA.............. 6.3 115.2 5.3 8 970 8.4 3 Prince William, VA....... 6.0 95.9 5.8 7 664 3.8 157 Alexandria City, VA...... 5.7 92.9 0.9 166 948 4.6 91 Chesapeake City, VA...... 4.8 93.6 4.2 21 582 3.7 163 Newport News City, VA.... 3.7 97.3 2.5 73 673 4.7 77 Norfolk City, VA......... 5.6 144.5 0.1 233 722 3.4 194 Richmond City, VA........ 6.9 157.4 0.2 229 824 3.5 187 Virginia Beach City, VA.. 10.6 174.0 3.8 29 567 3.1 209 Clark, WA................ 10.4 122.1 3.8 29 685 3.3 199 King, WA................. 77.3 1,104.3 1.1 154 940 -2.4 309 Kitsap, WA............... 6.1 80.2 3.0 51 695 2.1 276 Pierce, WA............... 19.6 252.0 1.5 121 673 5.2 53 Snohomish, WA............ 16.1 212.0 3.0 51 763 2.6 247 Spokane, WA.............. 14.6 193.5 1.0 161 604 2.5 257 Thurston, WA............. 6.2 91.5 2.4 77 681 2.9 224 Yakima, WA............... 8.3 104.5 0.6 199 500 4.4 111 Kanawha, WV.............. 6.2 107.7 -0.7 282 627 4.3 116 Brown, WI................ 6.8 146.6 0.2 229 657 4.0 138 Dane, WI................. 13.9 292.4 2.3 81 715 4.4 111 Milwaukee, WI............ 22.2 492.8 -1.3 293 750 5.6 34 Outagamie, WI............ 5.0 100.7 3.1 47 653 5.5 39 Racine, WI............... 4.3 76.8 2.0 93 694 3.9 147 Waukesha, WI............. 13.5 228.9 1.9 98 759 5.3 49 Winnebago, WI............ 4.0 87.6 -0.6 277 707 4.7 77 San Juan, PR............. 13.4 324.3 2.4 77 475 2.6 247 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 317 U.S. counties comprise 70.2 percent of the total covered workers in the U.S. 2 Data are preliminary. 3 Includes areas not officially designated as counties. See Technical Note. 4 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. 5 Average weekly wages were calculated using unrounded data. 6 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. 7 Data do not meet BLS or State agency disclosure standards. Table 2. Covered(1) establishments, employment, and wages in the ten largest counties, third quarter 2004(2) Employment Average weekly wage(4) Establishments, third quarter County by NAICS supersector 2004 Percent Percent (thousands) September change, Average change, 2004 September weekly third (thousands) 2003-04(3) wage quarter 2003-04(3) United States(5)............................. 8,421.8 130,248.9 1.3 $733 4.0 Private industry........................... 8,149.4 109,436.9 1.4 724 4.0 Natural resources and mining............. 122.7 1,777.2 0.5 654 7.7 Construction............................. 823.7 7,167.2 3.3 769 3.4 Manufacturing............................ 370.7 14,332.0 -0.4 898 5.2 Trade, transportation, and utilities..... 1,859.1 25,216.7 0.7 648 3.8 Information.............................. 143.4 3,062.0 -2.4 1,120 1.8 Financial activities..................... 785.8 7,899.5 0.5 1,039 4.0 Professional and business services....... 1,341.4 16,486.7 3.0 859 4.4 Education and health services............ 747.7 16,097.5 2.0 704 4.5 Leisure and hospitality.................. 680.4 12,747.5 2.4 314 3.0 Other services........................... 1,082.4 4,281.7 0.2 477 3.2 Government................................. 272.3 20,812.0 0.6 781 4.1 Los Angeles, CA.............................. 360.1 4,019.6 0.7 833 4.9 Private industry........................... 356.3 3,472.9 1.2 814 5.3 Natural resources and mining............. 0.6 12.0 0.9 1,031 29.0 Construction............................. 13.1 144.4 8.0 827 4.3 Manufacturing............................ 17.1 478.5 -2.3 874 8.0 Trade, transportation, and utilities..... 53.5 776.6 1.5 706 3.7 Information.............................. 8.8 205.2 1.9 1,370 6.1 Financial activities..................... 23.0 235.6 0.7 1,269 7.8 Professional and business services....... 39.9 566.2 1.3 919 4.4 Education and health services............ 26.9 453.9 0.7 759 4.4 Leisure and hospitality.................. 25.5 373.0 1.8 505 5.9 Other services........................... 147.8 226.5 3.1 404 2.3 Government................................. 3.9 546.8 -1.9 956 3.6 Cook, IL..................................... 126.7 2,511.7 -0.3 871 4.3 Private industry........................... 125.4 2,195.1 -0.1 862 4.2 Natural resources and mining............. 0.1 1.4 (6) 1,137 (6) Construction............................. 10.6 98.8 -4.0 1,073 3.6 Manufacturing............................ 7.6 257.7 -1.6 908 7.1 Trade, transportation, and utilities..... 26.5 477.0 0.2 732 5.5 Information.............................. 2.5 61.4 -5.5 1,206 2.5 Financial activities..................... 14.0 215.8 -1.1 1,318 4.9 Professional and business services....... 25.9 409.4 1.4 1,052 3.4 Education and health services............ 12.5 348.0 0.4 761 3.8 Leisure and hospitality.................. 10.6 226.5 1.7 378 4.4 Other services........................... 12.6 94.1 -1.2 633 3.1 Government................................. 1.2 316.5 -1.5 932 4.7 New York, NY................................. 112.7 2,201.7 0.8 1,327 7.0 Private industry........................... 112.4 1,764.4 1.0 1,404 7.4 Natural resources and mining............. 0.0 0.1 -15.6 1,124 15.2 Construction............................. 2.1 29.3 -3.5 1,312 0.8 Manufacturing............................ 3.3 45.6 -1.6 1,016 6.5 Trade, transportation, and utilities..... 21.8 233.1 1.4 996 3.2 Information.............................. 4.2 130.2 -0.9 1,723 8.0 Financial activities..................... 16.9 347.9 0.0 2,406 14.2 Professional and business services....... 22.6 430.2 0.8 1,517 5.5 Education and health services............ 8.0 267.1 1.1 923 3.0 Leisure and hospitality.................. 10.3 188.3 4.1 642 3.5 Other services........................... 16.0 81.1 0.6 776 2.8 Government................................. 0.2 437.3 -0.1 1,023 4.9 Harris, TX................................... 90.2 1,838.1 0.8 862 4.5 Private industry........................... 89.8 1,594.9 0.7 871 5.1 Natural resources and mining............. 1.3 63.1 1.5 2,018 11.1 Construction............................. 6.3 129.7 -8.1 842 6.4 Manufacturing............................ 4.6 163.9 -0.1 1,080 6.6 Trade, transportation, and utilities..... 21.2 388.5 0.2 782 2.6 Information.............................. 1.4 33.4 -1.7 1,064 3.7 Financial activities..................... 9.7 114.6 2.2 1,046 0.7 Professional and business services....... 17.1 289.7 3.7 988 8.0 Education and health services............ 9.1 188.8 0.7 781 3.6 Leisure and hospitality.................. 6.8 161.5 2.8 323 1.6 Other services........................... 10.4 57.1 1.2 513 2.6 Government................................. 0.4 243.2 1.5 796 0.1 Maricopa, AZ................................. 79.9 1,633.3 3.7 731 4.7 Private industry........................... 79.4 1,414.4 3.9 726 4.3 Natural resources and mining............. 0.5 7.6 0.4 564 12.8 Construction............................. 8.3 143.2 9.4 717 3.8 Manufacturing............................ 3.2 128.4 0.8 1,039 6.3 Trade, transportation, and utilities..... 18.3 328.5 3.9 713 3.9 Information.............................. 1.5 33.6 -7.8 857 5.2 Financial activities..................... 9.6 135.7 1.9 900 2.0 Professional and business services....... 17.7 270.4 6.2 719 6.0 Education and health services............ 7.8 167.1 5.8 776 4.7 Leisure and hospitality.................. 5.7 152.8 2.2 353 3.2 Other services........................... 5.6 44.7 1.7 499 4.0 Government................................. 0.5 218.8 2.3 766 7.0 Dallas, TX................................... 68.2 1,438.0 0.8 889 3.0 Private industry........................... 67.7 1,281.0 0.9 894 3.1 Natural resources and mining............. 0.5 6.5 5.2 2,143 -10.3 Construction............................. 4.4 76.5 0.6 798 3.4 Manufacturing............................ 3.4 144.2 1.0 1,013 5.7 Trade, transportation, and utilities..... 15.7 310.0 0.0 879 4.8 Information.............................. 1.8 59.2 -5.9 1,222 2.5 Financial activities..................... 8.7 140.1 1.0 1,115 1.4 Professional and business services....... 13.8 244.6 3.0 962 1.7 Education and health services............ 6.2 130.8 1.0 862 5.3 Leisure and hospitality.................. 5.1 126.0 1.6 401 0.3 Other services........................... 6.6 39.7 -3.4 570 2.7 Government................................. 0.5 157.0 (6) 840 (6) Orange, CA................................... 89.7 1,468.4 3.1 840 3.3 Private industry........................... 88.3 1,328.4 3.2 835 3.3 Natural resources and mining............. 0.2 7.4 7.3 515 1.6 Construction............................. 6.6 96.3 9.3 882 2.8 Manufacturing............................ 5.9 183.8 0.9 987 5.2 Trade, transportation, and utilities..... 17.2 266.5 2.0 785 2.3 Information.............................. 1.4 32.6 -3.4 1,205 10.1 Financial activities..................... 10.0 136.8 6.1 1,361 0.8 Professional and business services....... 17.5 264.1 3.9 834 2.1 Education and health services............ 9.2 127.9 1.7 785 6.9 Leisure and hospitality.................. 6.7 165.6 3.2 368 4.0 Other services........................... 13.4 46.9 3.7 510 2.4 Government................................. 1.4 140.0 1.8 886 3.4 San Diego, CA................................ 86.2 1,268.0 1.4 800 5.4 Private industry........................... 84.8 1,058.6 1.6 780 5.5 Natural resources and mining............. 0.9 11.6 -1.4 498 6.2 Construction............................. 6.7 90.0 9.9 822 5.4 Manufacturing............................ 3.5 104.8 -0.2 1,070 9.4 Trade, transportation, and utilities..... 14.2 211.7 2.4 654 3.3 Information.............................. 1.3 36.7 -1.3 1,682 11.6 Financial activities..................... 9.1 81.2 1.4 1,012 0.5 Professional and business services....... 14.9 203.6 0.9 910 4.7 Education and health services............ 7.6 118.2 -1.0 734 6.5 Leisure and hospitality.................. 6.6 147.7 1.6 378 8.3 Other services........................... 20.0 52.8 1.4 440 3.0 Government................................. 1.4 209.4 0.1 907 5.3 King, WA..................................... 77.3 1,104.3 1.1 940 -2.4 Private industry........................... 76.7 950.8 1.1 946 -3.3 Natural resources and mining............. 0.4 3.3 -4.5 966 3.1 Construction............................. 6.2 57.9 1.6 882 1.7 Manufacturing............................ 2.6 102.2 -1.6 1,205 8.4 Trade, transportation, and utilities..... 14.8 218.7 1.5 817 4.3 Information.............................. 1.5 67.8 -1.5 2,135 -28.3 Financial activities..................... 6.2 76.0 -1.6 1,106 0.5 Professional and business services....... 12.0 163.1 4.1 1,039 4.0 Education and health services............ 6.0 110.6 3.2 729 4.6 Leisure and hospitality.................. 5.5 105.1 2.3 401 0.5 Other services........................... 21.5 46.1 -4.7 483 8.3 Government................................. 0.5 153.5 1.1 903 4.0 Miami-Dade, FL............................... 82.6 979.5 2.1 717 (6) Private industry........................... 82.3 829.7 2.6 694 3.4 Natural resources and mining............. 0.5 8.0 6.7 437 0.9 Construction............................. 5.2 42.2 3.3 761 9.2 Manufacturing............................ 2.8 50.4 0.6 646 5.2 Trade, transportation, and utilities..... 24.0 240.4 0.5 664 3.9 Information.............................. 1.8 26.6 -3.1 1,021 9.8 Financial activities..................... 8.9 67.5 2.6 965 -0.4 Professional and business services....... 16.4 136.5 6.4 804 2.8 Education and health services............ 8.2 125.2 2.0 730 2.5 Leisure and hospitality.................. 5.6 94.6 5.7 403 3.6 Other services........................... 7.7 35.1 1.4 434 1.6 Government................................. 0.3 149.8 -0.6 849 (6) 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. 2 Data are preliminary. 3 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. 4 Average weekly wages were calculated using unrounded data. 5 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. 6 Data do not meet BLS or State agency disclosure standards. Table 3. Covered(1) establishments, employment, and wages in the largest county by state, third quarter 2004(2) Employment Average weekly wage(5) Establishments, third quarter County(3) 2004 Percent Percent (thousands) September change, Average change, 2004 September weekly third (thousands) 2003-04(4) wage quarter 2003-04(4) United States(6)......... 8,421.8 130,248.9 1.3 $733 4.0 Jefferson, AL............ 18.5 368.3 0.0 739 3.6 Anchorage Borough, AK.... 7.7 145.0 0.8 809 4.0 Maricopa, AZ............. 79.9 1,633.3 3.7 731 4.7 Pulaski, AR.............. 13.3 242.6 0.9 669 4.7 Los Angeles, CA.......... 360.1 4,019.6 0.7 833 4.9 Denver, CO............... 24.6 427.3 1.5 888 2.9 Hartford, CT............. 24.4 483.0 1.1 916 6.5 New Castle, DE........... 19.3 280.2 0.3 858 2.4 Washington, DC........... 30.1 658.3 1.2 1,207 7.6 Miami-Dade, FL........... 82.6 979.5 2.1 717 (7) Fulton, GA............... 37.1 726.6 1.5 958 4.2 Honolulu, HI............. 23.2 426.7 2.7 703 4.6 Ada, ID.................. 13.2 190.6 3.9 675 4.5 Cook, IL................. 126.7 2,511.7 -0.3 871 4.3 Marion, IN............... 23.7 581.1 1.5 765 3.8 Polk, IA................. 14.2 261.5 1.8 740 4.7 Johnson, KS.............. 18.9 296.6 1.9 764 3.8 Jefferson, KY............ 21.6 417.1 0.0 726 5.5 Orleans, LA.............. 12.6 244.6 -1.6 677 1.5 Cumberland, ME........... 12.0 171.0 1.1 671 5.5 Montgomery, MD........... 31.5 450.6 0.5 953 6.2 Middlesex, MA............ 48.2 782.0 -0.5 1,043 4.6 Wayne, MI................ 35.0 791.2 -1.2 874 4.7 Hennepin, MN............. 40.5 827.3 0.8 933 2.6 Hinds, MS................ 6.6 130.2 0.1 651 4.0 St. Louis, MO............ 33.7 617.5 -0.1 778 1.4 Yellowstone, MT.......... 5.6 71.2 2.4 572 3.8 Douglas, NE.............. 14.9 309.4 0.5 702 3.4 Clark, NV................ 39.0 822.6 7.4 701 4.6 Hillsborough, NH......... 12.4 194.2 0.8 828 6.3 Bergen, NJ............... 34.3 447.7 0.2 910 2.9 Bernalillo, NM........... 16.5 315.6 1.5 665 2.6 New York, NY............. 112.7 2,201.7 0.8 1,327 7.0 Mecklenburg, NC.......... 27.2 507.2 0.5 838 1.8 Cass, ND................. 5.4 90.0 3.7 610 3.9 Cuyahoga, OH............. 38.2 759.8 0.0 776 4.9 Oklahoma, OK............. 21.7 408.3 1.9 645 3.2 Multnomah, OR............ 25.5 422.4 1.6 760 3.7 Allegheny, PA............ 35.6 687.2 -0.6 774 3.6 Providence, RI........... 17.8 288.5 0.0 731 5.2 Greenville, SC........... 12.1 221.1 0.5 663 3.3 Minnehaha, SD............ 6.0 109.4 1.7 624 5.6 Shelby, TN............... 19.8 495.9 0.1 787 6.8 Harris, TX............... 90.2 1,838.1 0.8 862 4.5 Salt Lake, UT............ 35.0 524.7 2.3 671 3.5 Chittenden, VT........... 5.7 96.4 2.1 725 5.1 Fairfax, VA.............. 29.8 548.5 4.8 1,068 2.5 King, WA................. 77.3 1,104.3 1.1 940 -2.4 Kanawha, WV.............. 6.2 107.7 -0.7 627 4.3 Milwaukee, WI............ 22.2 492.8 -1.3 750 5.6 Laramie, WY.............. 2.9 39.8 0.7 596 4.0 San Juan, PR............. 13.4 324.3 2.4 475 2.6 St. Thomas, VI........... 1.7 22.6 -0.5 565 3.9 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. 2 Data are preliminary. 3 Includes areas not officially designated as counties. See Technical Note. 4 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. 5 Average weekly wages were calculated using unrounded data. 6 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. 7 Data do not meet BLS or State agency disclosure standards. Table 4. Covered(1) establishments, employment, and wages by state, third quarter 2004(2) Employment Average weekly wage(3) Establishments, third quarter State 2004 Percent Percent (thousands) September change, Average change, 2004 September weekly third (thousands) 2003-04 wage quarter 2003-04 United States(4)......... 8,421.8 130,248.9 1.3 $733 4.0 Alabama.................. 114.4 1,858.0 1.8 629 3.6 Alaska................... 20.3 314.2 1.9 755 3.4 Arizona.................. 126.3 2,357.6 3.6 691 4.9 Arkansas................. 76.4 1,145.7 1.4 570 5.2 California............... 1,204.0 15,106.6 1.5 829 3.9 Colorado................. 164.8 2,163.4 1.8 752 1.1 Connecticut.............. 109.5 1,642.1 0.9 917 5.4 Delaware................. 29.1 414.9 2.0 769 2.1 District of Columbia..... 30.1 658.3 1.2 1,207 7.6 Florida.................. 529.1 7,397.2 2.5 655 4.5 Georgia.................. 249.2 3,837.8 0.8 711 3.8 Hawaii................... 35.7 585.6 2.9 676 4.5 Idaho.................... 49.6 608.1 3.0 569 4.0 Illinois................. 328.1 5,747.7 0.2 779 3.9 Indiana.................. 152.6 2,887.8 1.4 655 4.5 Iowa..................... 91.8 1,431.8 1.2 604 4.1 Kansas................... 82.4 1,304.8 1.2 620 4.6 Kentucky................. 106.6 1,742.9 0.8 619 4.4 Louisiana................ 116.7 1,861.1 0.1 595 2.8 Maine.................... 50.1 608.8 0.7 603 4.3 Maryland................. 155.0 2,479.5 1.2 795 4.2 Massachusetts............ 211.3 3,156.5 -0.4 907 5.5 Michigan................. 254.3 4,344.5 -0.3 757 3.4 Minnesota................ 158.1 2,629.9 1.0 753 3.2 Mississippi.............. 66.7 1,113.8 1.0 540 3.6 Missouri................. 167.8 2,656.2 0.9 655 3.0 Montana.................. 42.4 413.0 2.6 525 3.6 Nebraska................. 55.6 887.4 1.1 601 3.6 Nevada................... 63.5 1,168.5 6.5 703 4.1 New Hampshire............ 47.6 622.6 1.4 731 6.1 New Jersey............... 267.8 3,918.8 0.9 876 2.8 New Mexico............... 50.3 769.3 1.9 588 4.1 New York................. 556.3 8,307.9 0.9 891 5.3 North Carolina........... 229.9 3,814.9 1.9 654 4.1 North Dakota............. 24.3 327.2 2.0 548 4.0 Ohio..................... 288.3 5,333.0 0.4 685 4.1 Oklahoma................. 92.6 1,435.7 1.3 581 3.9 Oregon................... 120.5 1,627.6 2.5 676 3.7 Pennsylvania............. 330.9 5,531.4 0.7 722 4.3 Rhode Island............. 35.2 484.6 0.6 708 4.6 South Carolina........... 112.9 1,799.2 1.4 604 4.1 South Dakota............. 28.6 375.5 2.0 538 4.9 Tennessee................ 130.2 2,668.6 1.9 659 4.4 Texas.................... 511.6 9,357.6 1.4 719 3.6 Utah..................... 77.5 1,084.4 3.4 607 3.2 Vermont.................. 24.5 302.0 1.5 634 5.8 Virginia................. 206.5 3,522.7 2.7 757 4.6 Washington............... 213.0 2,749.9 1.7 756 0.4 West Virginia............ 47.8 693.1 1.4 559 5.1 Wisconsin................ 161.2 2,745.6 1.1 653 4.8 Wyoming.................. 22.6 253.6 1.5 590 5.0 Puerto Rico.............. 52.7 1,042.4 2.2 417 3.0 Virgin Islands........... 3.2 42.7 3.4 599 5.8 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. 2 Data are preliminary. 3 Average weekly wages were calculated using unrounded data. 4 Totals for the United States do not include data for Puerto Rico or the Virgin Islands.