Technical information: (202) 691-6567 USDL 05-1295 http://www.bls.gov/cew/ For release: 10:00 A.M. EDT Media contact: 691-5902 Tuesday, July 19, 2005 COUNTY EMPLOYMENT AND WAGES: FOURTH QUARTER 2004 In December 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 8.9 percent, compared with national job growth of 1.7 percent. Williamson County, Texas, had the largest over-the- year gain in average weekly wages in the fourth quarter of 2004, with an increase of 17.8 percent. The U.S. average weekly wage increased by 5.7 percent over the same time span. Of the 317 largest counties in the United States, as measured by 2003 employment, 150 had over-the-year percentage growth in jobs above the national average in December 2004, and 153 experienced changes below the national average. Average weekly wages grew faster than the national av- erage in 133 of the largest U.S. counties, while the percent change in average weekly wages was below the national average in 177 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 8.5 million employer reports cover 131.6 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.) December 2004 employment and 2004 fourth-quarter average weekly wages for all states are provided in table 4 of this release. Data for all states, metropolitan statistical areas, counties, and the nation through the third quarter of 2004 are available on the BLS Web site at http://www.bls.gov/cew/. Preliminary data for the fourth quarter of 2004 and revised data for the first, second, and third quarters of 2004 will be available in July on the BLS Web site. ---------------------------------------------------------------------- | QCEW-Based Regional News Releases | | | | Several BLS regional offices have recently begun issuing QCEW- | | based news releases targeted to local users and media markets. For | | links to these releases, see http://www.bls.gov/cew/cewregional.htm. | ---------------------------------------------------------------------- - 2 - Table A. Top 10 counties ranked by December 2004 employment, December 2003-04 employment change, and December 2003-04 percent change in employment --------------------------------------------------------------------------------- Employment in large counties --------------------------------------------------------------------------------- | | December 2004 employment | Net change in employment, | Percent change (thousands) | December 2003-04 | in employment, | (thousands) | December 2003-04 ---------------------------|----------------------------|------------------------ U.S. 131,560.7|U.S. 2,198.4|U.S. 1.7 ---------------------------|----------------------------|------------------------ Los Angeles, Calif. 4,123.1|Maricopa, Ariz. 75.7|Rutherford, Tenn. 8.9 Cook, Ill. 2,529.3|Clark, Nev. 58.9|Manatee, Fla. 8.7 New York, N.Y. 2,266.8|Los Angeles, Calif. 58.5|Clark, Nev. 7.5 Harris, Texas 1,861.3|Riverside, Calif. 40.6|Riverside, Calif. 7.4 Maricopa, Ariz. 1,696.8|Hillsborough, Fla. 30.8|Loudoun, Va. 6.9 Orange, Calif. 1,464.8|Orange, Calif. 28.9|Prince William, Va. 6.6 Dallas, Texas 1,458.4|Orange, Fla. 27.2|Lee, Fla. 6.1 San Diego, Calif. 1,296.9|Dallas, Texas 26.1|Marion, Fla. 6.0 King, Wash. 1,117.2|Fairfax, Va. 25.4|Sarasota, Fla. 5.8 Miami-Dade, Fla. 1,007.1|Broward, Fla. 24.8|Hamilton, Ind. 5.8 --------------------------------------------------------------------------------- Large County Employment In December 2004, national employment, as measured by the QCEW program, was 131.6 million, up 1.7 percent from December 2003. The 317 largest U.S. counties accounted for 70.6 percent of total U.S. covered employment and 76.7 percent of total covered wages. These 317 counties had a net job gain of 1,543,850 over the year, accounting for 70.2 percent of the U.S. employment increase. Employment rose in 270 of the large counties from December 2003 to December 2004. Rutherford County, Tenn., had the largest over-the-year percentage gain (8.9 percent). Manatee, Fla., had the next largest increase, 8.7 percent, followed by Clark, Nev. (7.5 percent), River- side, Calif. (7.4 percent), and Loudoun, Va. (6.9 percent). (See table 1.) Employment declined in 38 counties from December 2003 to December 2004. The largest percentage decline was in McLean, Ill. (-2.9 percent), followed by Trumbull, Ohio (-1.8 percent), Wayne, Mich. (-1.5 percent), Saginaw, Mich. (-1.4 percent), and Okaloosa, Fla., Madison, Ill., and Ingham, Mich. (-1.3 percent each). The largest gains in employment from December 2003 to December 2004 were recorded in Maricopa, Ariz. (75,700), Clark, Nev. (58,900), Los Angeles, Calif. (58,500), Riverside, Calif. (40,600), and Hillsborough, Fla. (30,800). (See table A.) The largest declines in employment occurred in Wayne, Mich. (-12,600), followed by Allegheny, Pa. (-3,900), Montgomery, Ohio (-2,900), Orleans, La. (-2,800), and McLean, Ill. (-2,500). Large County Average Weekly Wages The national average weekly wage in the fourth quarter of 2004 was $812. Average weekly wages were higher than the national average in 110 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 $1,608. Santa Clara, Calif., was second with an average weekly wage of $1,460, fol- lowed by Fairfield, Conn. ($1,430), Suffolk, Mass. ($1,363), and San Mateo, Calif. ($1,324). (See table B.) - 3 - Table B. Top 10 counties ranked by fourth quarter 2004 average weekly wages, fourth quarter 2003-04 change in average weekly wages, and fourth quarter 2003-04 percent change in average weekly wages ------------------------------------------------------------------------------ Average weekly wage in large counties ------------------------------------------------------------------------------ | | Average weekly wage, | Change in average weekly| Percent change in fourth quarter 2004 | wage, fourth quarter | average weekly wage, | 2003-04 | fourth quarter 2003-04 ------------------------------------------------------------------------------ U.S. $812|U.S. $44|U.S. 5.7 ---------------------------|-------------------------|------------------------ New York, N.Y. $1,608|Williamson, Texas $135|Williamson, Texas 17.8 Santa Clara, Calif. 1,460|Santa Clara, Calif. 127|Rock Island, Ill. 14.8 Fairfield, Conn. 1,430|New York, N.Y. 125|Ventura, Calif. 12.6 Suffolk, Mass. 1,363|Fairfield, Conn. 120|Henrico, Va. 12.5 San Mateo, Calif. 1,324|Rock Island, Ill. 116|St. Louis, Minn. 11.0 Washington, D.C. 1,305|Suffolk, Mass. 116|Washington, Ark. 10.6 Arlington, Va. 1,291|Ventura, Calif. 102|Hennepin, Minn. 9.6 San Francisco, Calif. 1,274|San Mateo, Calif. 101|Santa Clara, Calif. 9.5 Fairfax, Va. 1,239|Henrico, Va. 96|Suffolk, Mass. 9.3 Somerset, N.J. 1,235|Essex, N.J. 93|Rockingham, N.H. 9.3 | |Essex, N.J. 9.3 ------------------------------------------------------------------------------ There were 204 counties with an average weekly wage below the national average in the fourth quarter of 2004. The lowest average weekly wages were reported in Cameron, Texas ($500), followed by Hidalgo, Texas ($504), Webb, Texas ($540), Yakima, Wash. ($541), and Horry, S.C. ($558). (See table 1.) From the fourth quarter 2003 to the fourth quarter 2004, the national average weekly wage rose by 5.7 percent. Among the largest counties, Williamson, Texas, led the nation in growth in average weekly wages, with an increase of 17.8 percent from the fourth quarter of 2003. Rock Island, Ill., was second with 14.8 percent growth, followed by Ventura, Calif. (12.6 percent), Henrico, Va. (12.5 percent), and St. Louis, Minn. (11.0 percent). No counties experienced over-the-year declines in average weekly wages. Kalamazoo, Mich., had the smallest increase in average weekly wages, 0.5 percent, followed by Richmond, N.Y. (0.7 percent), Genesee and Macomb, Mich. (0.9 percent each), and Ingham, Mich. (1.0 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 remained constant from December 2003 to December 2004. Maricopa, Ariz., experienced the fastest growth in employment among the 10 largest counties, with a 4.7 percent increase. Within Maricopa County, employment rose in every industry group except information. The largest gains were in construction (12.9 percent) and education and health services (7.0 percent). (See table 2.) Miami-Dade, Fla., had the next largest increase in employment, 2.4 percent, followed by Orange, Calif. (2.0 percent). The smallest employment gains occurred in New York, N.Y. (0.9 percent) and Harris, Texas (1.3 percent). The only county of the ten largest counties in the United States that did not have an increase in employment was Cook County, Ill., whose employment remained constant. - 4 - All of the 10 largest U.S. counties saw over-the-year increases in average weekly wages. New York, N.Y., had the fastest growth in wages among the top 10 counties, 8.4 percent. Within New York County, wages increased the most in natural resources and mining (26.1 percent) and financial activities (14.0 percent). Harris, Texas, was second in wage growth, increasing by 7.8 percent, followed by Orange, Calif., with a gain of 7.1 percent. The smallest wage gains among the 10 largest counties occurred in King, Wash. (3.8 percent), followed by Dallas, Texas (5.1 percent) and Maricopa, Ariz. (5.7 percent). Largest County by State Table 3 shows December 2004 employment and the 2004 fourth-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 December 2004 ranged from approximately 4.1 million in Los Angeles, Calif., to 39,500 in Laramie, Wyo. The highest average weekly wage of these counties was in New York, N.Y. ($1,608), while the lowest average weekly wage was in Laramie, Wyo. ($630). - 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 8.5 | 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 is now available 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, fourth quarter 2004(2) Employment Average weekly wage(5) Establishments, fourth quarter Percent County(3) 2004 December Percent Ranking Average change, Ranking (thousands) 2004 change, by weekly fourth by (thousands) December percent wage quarter percent 2003-04(4) change 2003-04 change (4) United States(6)......... 8,487.6 131,560.7 1.7 - $812 5.7 - Jefferson, AL............ 18.8 373.6 0.0 272 833 9.2 12 Madison, AL.............. 8.0 167.1 3.6 46 847 3.2 284 Mobile, AL............... 9.7 165.5 2.3 104 669 7.0 66 Montgomery, AL........... 6.6 133.2 2.1 114 721 3.4 276 Tuscaloosa, AL........... 4.2 79.8 3.2 60 713 8.7 17 Anchorage Borough, AK.... 7.7 142.2 1.4 178 830 5.2 166 Maricopa, AZ............. 80.4 1,696.8 4.7 23 801 5.7 134 Pima, AZ................. 17.6 348.9 3.4 53 701 4.8 193 Benton, AR............... 4.6 87.2 4.8 21 726 6.9 73 Pulaski, AR.............. 13.4 245.7 1.2 189 757 5.6 139 Washington, AR........... 5.2 87.8 2.7 82 668 10.6 6 Alameda, CA.............. 48.1 676.3 -0.2 281 1,056 7.4 49 Contra Costa, CA......... 27.6 344.4 1.2 189 1,010 8.4 20 Fresno, CA............... 29.0 332.3 2.1 114 651 6.0 117 Kern, CA................. 16.0 252.9 3.1 67 684 6.0 117 Los Angeles, CA.......... 366.8 4,123.1 1.4 178 959 6.1 110 Marin, CA................ 11.8 112.6 1.6 160 1,062 6.0 117 Monterey, CA............. 11.9 149.8 -0.2 281 701 4.0 247 Orange, CA............... 90.3 1,464.8 2.0 121 938 7.1 60 Placer, CA............... 9.5 132.3 5.0 17 791 8.2 27 Riverside, CA............ 38.9 590.8 7.4 4 677 4.6 206 Sacramento, CA........... 47.2 608.3 1.6 160 866 3.8 256 San Bernardino, CA....... 42.6 621.9 3.8 38 711 4.6 206 San Diego, CA............ 87.2 1,296.9 1.9 127 872 6.5 89 San Francisco, CA........ 43.3 528.7 -0.4 293 1,274 7.8 34 San Joaquin, CA.......... 16.0 216.5 3.7 41 705 4.1 243 San Luis Obispo, CA...... 8.7 98.3 0.2 259 674 6.6 84 San Mateo, CA............ 22.9 333.7 0.7 226 1,324 8.3 24 Santa Barbara, CA........ 13.2 172.7 -0.5 294 786 8.7 17 Santa Clara, CA.......... 52.8 861.6 1.0 203 1,460 9.5 8 Santa Cruz, CA........... 8.4 92.2 2.9 75 767 6.1 110 Solano, CA............... 9.6 126.4 0.7 226 753 7.0 66 Sonoma, CA............... 17.3 190.2 0.5 243 796 6.4 97 Stanislaus, CA........... 13.2 168.2 2.3 104 666 4.6 206 Tulare, CA............... 8.6 133.2 0.4 248 577 7.1 60 Ventura, CA.............. 20.7 305.3 1.2 189 913 12.6 3 Yolo, CA................. 5.1 95.7 1.7 151 758 7.7 38 Adams, CO................ 8.7 143.0 1.9 127 781 7.0 66 Arapahoe, CO............. 18.9 271.9 0.8 218 983 7.4 49 Boulder, CO.............. 11.9 155.5 3.4 53 959 3.8 256 Denver, CO............... 24.5 429.1 1.7 151 990 5.9 123 El Paso, CO.............. 16.1 239.3 2.2 108 742 5.2 166 Jefferson, CO............ 18.1 207.0 1.4 178 825 5.2 166 Larimer, CO.............. 9.3 122.9 1.8 135 733 3.2 284 Fairfield, CT............ 31.9 418.0 0.6 235 1,430 9.2 12 Hartford, CT............. 24.4 487.7 0.9 209 1,016 7.4 49 New Haven, CT............ 22.1 368.4 1.6 160 885 2.9 289 New London, CT........... 6.7 129.9 0.8 218 847 3.3 279 New Castle, DE........... 19.5 286.5 0.9 209 980 6.9 73 Washington, DC........... 30.3 659.6 0.6 235 1,305 5.5 146 Alachua, FL.............. 6.1 127.8 3.2 60 619 4.4 219 Brevard, FL.............. 12.9 198.2 3.3 57 780 8.9 15 Broward, FL.............. 59.2 716.6 3.6 46 802 7.5 47 Collier, FL.............. 10.9 129.5 5.0 17 741 5.3 159 Duval, FL................ 23.3 447.8 3.6 46 800 5.5 146 Escambia, FL............. 7.5 126.3 3.6 46 649 8.3 24 Hillsborough, FL......... 32.5 631.7 5.1 16 776 5.4 151 Lee, FL.................. 15.9 207.2 6.1 7 708 8.8 16 Leon, FL................. 7.5 148.0 2.9 75 690 4.1 243 Manatee, FL.............. 7.6 129.8 8.7 2 628 6.6 84 Marion, FL............... 6.9 94.2 6.0 8 607 5.6 139 Miami-Dade, FL........... 83.2 1,007.1 2.4 95 822 6.3 105 Okaloosa, FL............. 5.6 79.7 -1.3 307 640 7.7 38 Orange, FL............... 30.8 645.0 4.4 30 757 6.5 89 Palm Beach, FL........... 44.6 547.5 4.7 23 815 4.8 193 Pasco, FL................ 7.8 87.9 5.6 12 586 3.5 272 Pinellas, FL............. 29.2 445.2 3.1 67 720 4.2 238 Polk, FL................. 10.9 198.4 4.0 36 643 3.9 252 Sarasota, FL............. 13.7 161.1 5.8 9 706 7.1 60 Seminole, FL............. 12.5 159.7 5.7 11 745 8.1 30 Volusia, FL.............. 12.4 158.1 4.3 32 620 5.6 139 Bibb, GA................. 4.7 87.1 0.1 267 670 3.7 263 Chatham, GA.............. 7.2 131.0 3.7 41 685 6.7 76 Clayton, GA.............. 4.4 107.6 (7) - 830 6.4 97 Cobb, GA................. 20.1 306.3 0.8 218 880 3.5 272 De Kalb, GA.............. 17.1 294.6 0.8 218 875 5.4 151 Fulton, GA............... 37.8 745.4 3.2 60 1,055 5.8 129 Gwinnett, GA............. 21.8 312.0 3.4 53 848 3.3 279 Muscogee, GA............. 4.7 97.6 -0.2 281 625 4.2 238 Richmond, GA............. 4.8 105.7 -0.2 281 678 6.1 110 Honolulu, HI............. 23.4 441.3 3.3 57 756 7.2 58 Ada, ID.................. 13.4 193.4 4.8 21 742 8.2 27 Champaign, IL............ 4.0 91.2 0.8 218 672 2.0 304 Cook, IL................. 127.7 2,529.3 0.0 272 985 6.7 76 Du Page, IL.............. 33.1 584.3 1.2 189 975 5.9 123 Kane, IL................. 11.3 203.0 1.1 198 763 6.1 110 Lake, IL................. 19.3 324.3 1.7 151 1,032 5.7 134 McHenry, IL.............. 7.6 96.7 3.2 60 737 5.7 134 McLean, IL............... 3.4 83.5 -2.9 313 796 5.0 178 Madison, IL.............. 5.7 93.9 -1.3 307 694 4.2 238 Peoria, IL............... 4.6 100.0 2.2 108 787 5.6 139 Rock Island, IL.......... 3.4 78.0 0.9 209 902 14.8 2 St. Clair, IL............ 5.1 92.6 -1.2 306 646 7.0 66 Sangamon, IL............. 5.1 130.2 -0.2 281 772 2.8 293 Will, IL................. 11.0 163.1 2.4 95 769 4.9 186 Winnebago, IL............ 6.6 137.9 0.7 226 702 4.3 227 Allen, IN................ 8.7 180.7 0.4 248 712 5.0 178 Elkhart, IN.............. 4.8 124.4 5.4 14 712 3.8 256 Hamilton, IN............. 6.3 91.2 5.8 9 833 6.4 97 Lake, IN................. 9.9 194.6 1.5 172 733 6.4 97 Marion, IN............... 23.8 586.8 1.6 160 833 4.1 243 St. Joseph, IN........... 6.0 127.2 1.8 135 684 1.9 306 Vanderburgh, IN.......... 4.8 108.4 0.2 259 684 2.9 289 Linn, IA................. 6.1 118.2 2.1 114 791 8.2 27 Polk, IA................. 14.3 264.0 1.8 135 817 7.5 47 Scott, IA................ 5.1 87.7 2.4 95 684 6.0 117 Johnson, KS.............. 19.0 300.7 2.4 95 841 7.3 54 Sedgwick, KS............. 11.7 245.0 1.9 127 730 4.4 219 Shawnee, KS.............. 4.7 95.0 -0.5 294 683 6.7 76 Fayette, KY.............. 8.9 167.8 0.4 248 741 6.5 89 Jefferson, KY............ 21.9 424.3 0.9 209 807 6.5 89 Caddo, LA................ 7.1 123.0 1.6 160 673 3.9 252 Calcasieu, LA............ 4.6 83.6 1.3 185 664 5.9 123 East Baton Rouge, LA..... 13.1 250.1 1.8 135 688 4.2 238 Jefferson, LA............ 14.0 215.5 0.3 255 687 6.0 117 Lafayette, LA............ 7.6 121.5 -0.1 276 715 5.8 129 Orleans, LA.............. 12.6 247.7 -1.1 305 753 5.5 146 Cumberland, ME........... 12.3 173.4 0.8 218 769 7.1 60 Anne Arundel, MD......... 13.8 218.2 2.5 91 839 4.9 186 Baltimore, MD............ 21.0 374.0 2.7 82 854 6.4 97 Frederick, MD............ 5.6 91.7 3.0 71 765 5.5 146 Howard, MD............... 8.1 141.1 0.3 255 952 8.3 24 Montgomery, MD........... 31.9 458.2 1.2 189 1,067 6.3 105 Prince Georges, MD....... 15.3 319.2 1.9 127 865 4.6 206 Baltimore City, MD....... 14.2 358.8 -0.6 298 929 6.2 108 Barnstable, MA........... 9.3 88.8 0.8 218 724 4.8 193 Bristol, MA.............. 15.5 221.4 0.4 248 726 3.6 270 Essex, MA................ 21.0 294.5 -0.3 288 865 2.6 296 Hampden, MA.............. 14.3 201.8 1.3 185 749 2.9 289 Middlesex, MA............ 48.7 791.6 0.1 267 1,146 5.4 151 Norfolk, MA.............. 22.1 320.1 0.2 259 1,007 4.6 206 Plymouth, MA............. 13.8 176.3 2.4 95 799 4.3 227 Suffolk, MA.............. 22.5 564.1 0.5 243 1,363 9.3 9 Worcester, MA............ 20.6 319.6 0.0 272 830 3.5 272 Genesee, MI.............. 8.5 156.5 -0.3 288 801 0.9 313 Ingham, MI............... 6.9 168.2 -1.3 307 773 1.0 312 Kalamazoo, MI............ 5.5 116.4 -0.1 276 737 0.5 316 Kent, MI................. 14.5 339.6 0.7 226 778 4.7 198 Macomb, MI............... 17.9 327.6 0.5 243 897 0.9 313 Oakland, MI.............. 41.0 724.8 -0.1 276 1,007 2.3 300 Ottawa, MI............... 5.7 111.4 1.5 172 739 2.2 302 Saginaw, MI.............. 4.5 90.7 -1.4 310 753 1.1 311 Washtenaw, MI............ 8.1 199.6 1.1 198 904 1.8 307 Wayne, MI................ 34.6 804.2 -1.5 311 950 3.7 263 Anoka, MN................ 7.5 113.8 1.8 135 812 7.8 34 Dakota, MN............... 9.9 170.5 1.8 135 822 7.7 38 Hennepin, MN............. 41.0 840.1 1.5 172 1,049 9.6 7 Olmsted, MN.............. 3.3 87.5 0.8 218 792 3.8 256 Ramsey, MN............... 15.0 330.7 1.0 203 917 5.0 178 St. Louis, MN............ 5.7 94.9 2.0 121 689 11.0 5 Stearns, MN.............. 4.2 79.2 2.4 95 665 5.1 174 Harrison, MS............. 4.6 90.1 0.6 235 572 5.3 159 Hinds, MS................ 6.6 130.2 -1.0 303 713 4.9 186 Boone, MO................ 4.3 79.3 2.8 79 627 4.7 198 Clay, MO................. 4.9 86.3 -0.2 281 752 4.9 186 Greene, MO............... 8.0 148.4 2.0 121 617 4.8 193 Jackson, MO.............. 18.7 367.2 0.6 235 816 4.5 213 St. Charles, MO.......... 7.4 116.3 (7) - 694 4.4 219 St. Louis, MO............ 33.8 626.2 0.6 235 863 5.2 166 St. Louis City, MO....... 8.2 223.1 (7) - 888 6.5 89 Douglas, NE.............. 15.0 312.1 0.3 255 757 7.4 49 Lancaster, NE............ 7.6 153.7 1.9 127 656 4.0 247 Clark, NV................ 40.0 839.0 7.5 3 770 7.7 38 Washoe, NV............... 12.8 211.1 5.5 13 769 3.9 252 Hillsborough, NH......... 12.3 197.7 0.9 209 933 6.4 97 Rockingham, NH........... 10.7 136.6 2.2 108 873 9.3 9 Atlantic, NJ............. 6.6 145.5 0.9 209 742 5.8 129 Bergen, NJ............... 34.4 456.5 0.2 259 1,067 3.7 263 Burlington, NJ........... 11.2 203.2 1.8 135 864 5.0 178 Camden, NJ............... 13.4 213.8 3.7 41 863 3.0 288 Essex, NJ................ 21.5 366.1 0.4 248 1,090 9.3 9 Gloucester, NJ........... 6.1 103.0 4.0 36 760 6.1 110 Hudson, NJ............... 14.0 238.4 0.5 243 1,054 6.7 76 Mercer, NJ............... 10.8 222.4 -0.5 294 1,064 7.6 44 Middlesex, NJ............ 20.7 399.1 1.2 189 1,046 5.9 123 Monmouth, NJ............. 20.0 257.7 2.8 79 910 2.6 296 Morris, NJ............... 17.8 285.1 0.2 259 1,221 7.0 66 Ocean, NJ................ 11.5 144.3 1.9 127 744 7.7 38 Passaic, NJ.............. 12.5 181.0 1.6 160 899 5.6 139 Somerset, NJ............. 10.0 169.1 -0.6 298 1,235 4.7 198 Union, NJ................ 15.0 235.4 (7) - 1,066 (7) - Bernalillo, NM........... 16.4 318.6 1.9 127 727 5.2 166 Albany, NY............... 9.6 232.0 -0.2 281 817 2.0 304 Bronx, NY................ 15.4 219.4 1.4 178 769 3.5 272 Broome, NY............... 4.4 95.9 0.7 226 624 1.3 310 Dutchess, NY............. 7.9 120.0 2.2 108 809 4.3 227 Erie, NY................. 23.3 464.6 0.7 226 713 4.5 213 Kings, NY................ 42.1 458.1 1.8 135 735 3.7 263 Monroe, NY............... 17.7 388.6 0.4 248 780 4.3 227 Nassau, NY............... 50.9 614.8 0.9 209 924 2.7 295 New York, NY............. 112.9 2,266.8 0.9 209 1,608 8.4 20 Oneida, NY............... 5.3 111.6 2.2 108 627 4.7 198 Onondaga, NY............. 12.6 250.8 1.2 189 768 4.6 206 Orange, NY............... 9.3 130.2 2.1 114 696 4.5 213 Queens, NY............... 40.3 484.6 1.2 189 817 2.3 300 Richmond, NY............. 8.1 91.3 1.2 189 733 0.7 315 Rockland, NY............. 9.4 115.2 1.6 160 864 3.7 263 Suffolk, NY.............. 47.8 611.3 1.1 198 878 4.8 193 Westchester, NY.......... 35.4 421.6 1.8 135 1,101 6.2 108 Buncombe, NC............. 6.9 109.3 2.5 91 650 5.7 134 Catawba, NC.............. 4.3 88.1 1.4 178 630 2.9 289 Cumberland, NC........... 5.7 113.9 2.9 75 604 4.5 213 Durham, NC............... 6.1 169.8 2.3 104 1,025 7.2 58 Forsyth, NC.............. 8.4 179.5 1.6 160 764 4.5 213 Guilford, NC............. 13.7 271.4 2.4 95 739 4.7 198 Mecklenburg, NC.......... 27.4 519.3 2.1 114 948 8.1 30 New Hanover, NC.......... 6.4 93.4 4.5 29 655 3.8 256 Wake, NC................. 23.6 400.5 3.6 46 817 4.5 213 Cass, ND................. 5.5 90.4 4.3 32 687 9.0 14 Butler, OH............... 6.9 134.7 1.0 203 740 7.6 44 Cuyahoga, OH............. 38.3 764.3 0.2 259 864 7.6 44 Franklin, OH............. 29.3 698.3 0.6 235 808 5.6 139 Hamilton, OH............. 24.6 549.3 0.6 235 872 4.9 186 Lake, OH................. 6.7 99.7 0.3 255 687 7.3 54 Lorain, OH............... 6.2 102.0 0.6 235 714 5.6 139 Lucas, OH................ 10.8 228.2 -0.6 298 746 4.3 227 Mahoning, OH............. 6.4 106.5 0.7 226 624 7.4 49 Montgomery, OH........... 13.2 286.1 -1.0 303 780 3.7 263 Stark, OH................ 9.2 168.8 1.4 178 649 6.7 76 Summit, OH............... 14.8 270.1 1.3 185 784 8.4 20 Trumbull, OH............. 4.8 84.1 -1.8 312 746 2.2 302 Oklahoma, OK............. 21.9 411.7 1.6 160 698 4.0 247 Tulsa, OK................ 18.3 327.6 2.6 88 731 7.3 54 Clackamas, OR............ 11.6 141.5 3.6 46 752 5.0 178 Jackson, OR.............. 6.3 82.2 3.2 60 597 4.4 219 Lane, OR................. 10.4 143.4 3.8 38 643 4.4 219 Marion, OR............... 8.6 129.8 3.0 71 628 2.4 298 Multnomah, OR............ 25.6 429.6 1.7 151 815 4.2 238 Washington, OR........... 14.7 231.3 4.4 30 906 1.6 308 Allegheny, PA............ 35.6 691.6 -0.6 298 848 5.7 134 Berks, PA................ 9.0 166.2 2.6 88 730 3.7 263 Bucks, PA................ 20.3 259.3 1.8 135 800 4.0 247 Chester, PA.............. 14.7 228.3 1.8 135 1,049 8.4 20 Cumberland, PA........... 5.7 126.9 1.4 178 756 5.4 151 Dauphin, PA.............. 7.0 177.1 2.7 82 809 7.0 66 Delaware, PA............. 13.6 212.1 0.1 267 875 4.7 198 Erie, PA................. 7.2 128.2 2.0 121 645 5.4 151 Lackawanna, PA........... 5.8 100.4 1.8 135 636 7.3 54 Lancaster, PA............ 11.7 227.9 2.1 114 712 5.0 178 Lehigh, PA............... 8.4 174.9 0.9 209 826 5.0 178 Luzerne, PA.............. 8.0 142.3 -0.5 294 647 6.1 110 Montgomery, PA........... 27.4 488.3 0.1 267 1,016 8.1 30 Northampton, PA.......... 6.2 92.7 1.6 160 719 5.4 151 Philadelphia, PA......... 28.8 638.7 -0.1 276 971 7.1 60 Westmoreland, PA......... 9.4 137.5 3.3 57 656 6.5 89 York, PA................. 8.7 171.7 3.0 71 706 5.5 146 Kent, RI................. 5.6 83.2 1.0 203 724 4.0 247 Providence, RI........... 17.9 289.8 -0.3 288 784 2.8 293 Charleston, SC........... 11.9 196.2 3.7 41 666 4.7 198 Greenville, SC........... 12.3 227.1 1.7 151 719 5.3 159 Horry, SC................ 8.0 102.0 4.9 19 558 6.5 89 Lexington, SC............ 5.6 87.6 1.7 151 635 6.9 73 Richland, SC............. 9.6 210.9 1.7 151 697 5.3 159 Spartanburg, SC.......... 6.3 116.9 0.2 259 694 3.4 276 Minnehaha, SD............ 6.0 110.3 1.6 160 663 3.3 279 Davidson, TN............. 17.9 439.2 2.1 114 828 5.9 123 Hamilton, TN............. 8.3 194.9 1.7 151 706 3.2 284 Knox, TN................. 10.4 221.1 3.2 60 707 4.4 219 Rutherford, TN........... 3.7 94.2 8.9 1 748 4.9 186 Shelby, TN............... 19.7 505.5 1.1 198 838 5.4 151 Bell, TX................. 4.2 93.9 4.1 34 602 5.8 129 Bexar, TX................ 30.0 663.1 0.1 267 721 7.0 66 Brazoria, TX............. 4.1 77.4 1.7 151 753 5.3 159 Brazos, TX............... 3.5 79.2 1.5 172 566 5.4 151 Cameron, TX.............. 6.1 116.7 0.7 226 500 4.4 219 Collin, TX............... 13.0 217.9 (7) - 893 (7) - Dallas, TX............... 68.3 1,458.4 1.8 135 1,001 5.1 174 Denton, TX............... 8.7 138.5 3.4 53 700 6.5 89 El Paso, TX.............. 12.5 255.9 0.7 226 579 5.3 159 Fort Bend, TX............ 6.6 103.7 4.6 27 806 5.1 174 Galveston, TX............ 4.8 88.2 1.6 160 690 3.6 270 Harris, TX............... 90.8 1,861.3 1.3 185 978 7.8 34 Hidalgo, TX.............. 9.5 194.9 4.1 34 504 3.3 279 Jefferson, TX............ 5.8 117.8 -0.3 288 771 6.6 84 Lubbock, TX.............. 6.5 119.7 2.6 88 603 5.2 166 McLennan, TX............. 4.7 98.8 1.0 203 633 4.3 227 Montgomery, TX........... 6.4 94.8 5.4 14 737 3.4 276 Nueces, TX............... 8.0 144.9 1.1 198 681 6.6 84 Potter, TX............... 3.9 77.2 0.0 272 628 5.2 166 Smith, TX................ 4.9 88.3 2.0 121 701 6.4 97 Tarrant, TX.............. 34.0 708.8 1.9 127 827 4.3 227 Travis, TX............... 25.3 525.5 3.2 60 923 6.7 76 Webb, TX................. 4.3 79.9 2.5 91 540 4.9 186 Williamson, TX........... 5.2 88.9 4.7 23 893 17.8 1 Davis, UT................ 6.5 94.3 3.8 38 642 4.7 198 Salt Lake, UT............ 35.8 535.9 2.8 79 743 6.0 117 Utah, UT................. 11.6 154.3 4.6 27 615 4.4 219 Weber, UT................ 5.5 88.7 1.8 135 593 3.3 279 Chittenden, VT........... 5.7 97.0 1.5 172 780 1.4 309 Arlington, VA............ 7.1 158.2 2.9 75 1,291 7.7 38 Chesterfield, VA......... 6.8 115.5 2.3 104 752 7.9 33 Fairfax, VA.............. 30.0 561.3 4.7 23 1,239 6.7 76 Henrico, VA.............. 8.3 172.2 2.5 91 864 12.5 4 Loudoun, VA.............. 6.4 118.1 6.9 5 1,035 5.1 174 Prince William, VA....... 6.1 99.0 6.6 6 732 5.8 129 Alexandria City, VA...... 5.7 94.8 2.7 82 1,049 6.6 84 Chesapeake City, VA...... 4.9 94.8 2.7 82 644 6.3 105 Newport News City, VA.... 3.7 99.5 2.2 108 736 5.9 123 Norfolk City, VA......... 5.6 145.6 0.2 259 782 4.3 227 Richmond City, VA........ 7.0 160.6 1.8 135 914 6.4 97 Virginia Beach City, VA.. 10.7 176.0 3.1 67 643 6.1 110 Clark, WA................ 10.6 123.4 4.9 19 714 5.3 159 King, WA................. 78.2 1,117.2 1.8 135 973 3.8 256 Kitsap, WA............... 6.2 81.6 3.0 71 692 2.4 298 Pierce, WA............... 19.9 254.8 3.5 52 699 4.3 227 Snohomish, WA............ 16.2 215.5 3.7 41 787 4.1 243 Spokane, WA.............. 14.8 196.2 2.7 82 630 4.3 227 Thurston, WA............. 6.3 91.8 1.5 172 696 3.9 252 Yakima, WA............... 8.4 87.5 2.0 121 541 4.6 206 Kanawha, WV.............. 6.2 108.5 -0.8 302 689 5.0 178 Brown, WI................ 6.7 147.6 0.4 248 772 8.6 19 Dane, WI................. 13.7 298.4 2.4 95 770 3.1 287 Milwaukee, WI............ 21.7 499.7 -0.3 288 824 6.7 76 Outagamie, WI............ 5.0 101.6 3.1 67 705 5.2 166 Racine, WI............... 4.3 76.7 0.5 243 815 7.1 60 Waukesha, WI............. 13.3 231.0 2.4 95 821 3.8 256 Winnebago, WI............ 3.9 87.3 -0.1 276 798 7.8 34 San Juan, PR............. 13.6 338.0 1.0 203 535 4.3 227 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 317 U.S. counties comprise 70.6 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, fourth quarter 2004(2) Employment Average weekly wage(4) Establishments, fourth quarter County by NAICS supersector 2004 Percent Percent (thousands) December change, Average change, 2004 December weekly fourth (thousands) 2003-04(3) wage quarter 2003-04(3) United States(5)............................. 8,487.6 131,560.7 1.7 $812 5.7 Private industry........................... 8,215.2 110,295.2 1.9 816 6.0 Natural resources and mining............. 123.0 1,592.9 2.1 758 7.8 Construction............................. 828.7 6,999.3 4.6 865 3.2 Manufacturing............................ 369.7 14,281.7 -0.1 985 4.3 Trade, transportation, and utilities..... 1,860.9 26,305.1 1.3 704 5.9 Information.............................. 143.3 3,102.1 -1.9 1,239 8.7 Financial activities..................... 792.7 7,985.2 1.4 1,238 8.6 Professional and business services....... 1,349.9 16,664.6 3.4 1,016 7.3 Education and health services............ 751.5 16,374.2 2.4 773 5.6 Leisure and hospitality.................. 684.3 12,363.1 2.6 346 3.3 Other services........................... 1,100.4 4,288.3 0.2 518 4.6 Government................................. 272.4 21,265.6 0.6 794 4.9 Los Angeles, CA.............................. 366.8 4,123.1 1.4 959 6.1 Private industry........................... 363.0 3,539.4 1.9 960 6.8 Natural resources and mining............. 0.6 10.7 1.4 1,277 37.5 Construction............................. 13.1 142.0 7.1 939 6.5 Manufacturing............................ 17.0 476.8 -1.6 959 6.8 Trade, transportation, and utilities..... 53.4 810.9 2.4 782 6.5 Information.............................. 8.9 221.7 7.9 1,720 8.4 Financial activities..................... 23.1 238.9 0.9 1,363 8.9 Professional and business services....... 40.0 576.4 2.0 1,132 7.6 Education and health services............ 26.9 463.2 1.5 870 5.7 Leisure and hospitality.................. 25.8 378.0 2.1 782 0.9 Other services........................... 153.9 219.8 -0.3 442 4.2 Government................................. 3.8 583.7 -1.0 957 2.9 Cook, IL..................................... 127.7 2,529.3 0.0 985 6.7 Private industry........................... 126.4 2,214.5 0.2 992 6.7 Natural resources and mining............. 0.1 1.3 6.9 1,124 14.5 Construction............................. 10.8 94.5 -2.2 1,191 1.4 Manufacturing............................ 7.5 256.8 -1.7 1,039 7.0 Trade, transportation, and utilities..... 26.6 495.1 0.0 803 6.8 Information.............................. 2.5 62.6 -2.2 1,317 11.8 Financial activities..................... 14.2 217.3 -0.2 1,579 6.9 Professional and business services....... 26.1 412.7 2.0 1,307 7.7 Education and health services............ 12.6 357.8 1.5 832 5.3 Leisure and hospitality.................. 10.7 217.4 -0.2 390 4.3 Other services........................... 12.7 94.2 -0.9 695 5.8 Government................................. 1.2 314.8 -1.8 939 7.6 New York, NY................................. 112.9 2,266.8 0.9 1,608 8.4 Private industry........................... 112.7 1,815.5 1.2 1,760 8.1 Natural resources and mining............. 0.0 0.1 -5.9 1,536 26.1 Construction............................. 2.1 28.7 0.0 1,591 1.8 Manufacturing............................ 3.3 45.0 -1.8 1,437 13.0 Trade, transportation, and utilities..... 21.8 248.0 2.1 1,180 0.9 Information.............................. 4.2 129.6 -1.6 1,839 4.2 Financial activities..................... 16.9 353.1 0.6 3,468 14.0 Professional and business services....... 22.5 443.8 1.9 1,826 6.5 Education and health services............ 8.0 278.5 1.6 956 4.3 Leisure and hospitality.................. 10.3 194.9 1.8 834 6.4 Other services........................... 16.1 83.6 0.5 910 3.5 Government................................. 0.2 451.3 -0.4 998 9.4 Harris, TX................................... 90.8 1,861.3 1.3 978 7.8 Private industry........................... 90.4 1,620.7 1.8 999 7.5 Natural resources and mining............. 1.3 64.7 2.9 2,400 9.5 Construction............................. 6.3 133.2 -1.8 938 2.4 Manufacturing............................ 4.6 164.3 0.9 1,223 10.6 Trade, transportation, and utilities..... 21.2 406.8 1.5 870 6.0 Information.............................. 1.4 33.3 -3.0 1,161 6.1 Financial activities..................... 9.8 115.1 2.2 1,257 6.7 Professional and business services....... 17.3 291.7 3.6 1,168 8.4 Education and health services............ 9.2 191.7 1.7 879 8.7 Leisure and hospitality.................. 6.8 159.2 2.4 356 6.6 Other services........................... 10.5 56.4 0.3 557 4.1 Government................................. 0.5 240.5 -2.0 839 10.2 Maricopa, AZ................................. 80.4 1,696.8 4.7 801 5.7 Private industry........................... 79.9 1,472.4 5.1 800 5.8 Natural resources and mining............. 0.5 10.6 6.9 632 17.0 Construction............................. 8.3 148.5 12.9 819 5.1 Manufacturing............................ 3.2 130.0 1.9 1,071 2.0 Trade, transportation, and utilities..... 18.3 350.6 4.3 757 5.7 Information.............................. 1.5 34.2 -7.6 952 8.8 Financial activities..................... 9.7 139.6 4.3 1,024 9.9 Professional and business services....... 17.7 278.8 6.8 833 7.1 Education and health services............ 7.9 172.2 7.0 879 4.5 Leisure and hospitality.................. 5.8 160.2 2.8 370 1.9 Other services........................... 5.5 44.5 0.1 539 8.0 Government................................. 0.5 224.4 2.2 807 5.4 Dallas, TX................................... 68.3 1,458.4 1.8 1,001 5.1 Private industry........................... 67.9 1,299.8 1.9 1,021 5.1 Natural resources and mining............. 0.5 6.6 2.6 2,429 -11.6 Construction............................. 4.4 75.7 3.6 921 2.0 Manufacturing............................ 3.4 145.0 2.1 1,136 6.3 Trade, transportation, and utilities..... 15.6 319.1 0.9 950 6.7 Information.............................. 1.8 58.7 -4.7 1,350 5.1 Financial activities..................... 8.7 142.0 1.6 1,304 7.0 Professional and business services....... 13.9 250.4 3.8 1,188 2.5 Education and health services............ 6.3 132.9 2.6 956 7.5 Leisure and hospitality.................. 5.2 126.2 1.7 455 5.3 Other services........................... 6.6 39.8 -2.5 611 4.4 Government................................. 0.5 158.6 1.5 831 3.9 Orange, CA................................... 90.3 1,464.8 2.0 938 7.1 Private industry........................... 88.9 1,335.9 2.5 942 7.3 Natural resources and mining............. 0.2 6.0 -1.7 594 1.9 Construction............................. 6.7 91.7 4.6 1,019 5.9 Manufacturing............................ 5.9 184.2 0.7 1,093 5.9 Trade, transportation, and utilities..... 17.2 280.7 2.2 858 5.9 Information.............................. 1.4 33.2 -2.0 1,235 7.9 Financial activities..................... 10.1 140.1 8.2 1,520 11.7 Professional and business services....... 17.5 259.6 1.5 1,020 8.1 Education and health services............ 9.3 130.3 2.3 876 3.4 Leisure and hospitality.................. 6.7 162.3 1.7 366 2.5 Other services........................... 13.7 47.3 3.2 547 4.2 Government................................. 1.4 128.9 -2.7 897 4.8 San Diego, CA................................ 87.2 1,296.9 1.9 872 6.5 Private industry........................... 85.8 1,077.4 2.1 865 6.7 Natural resources and mining............. 0.9 11.1 0.6 551 10.2 Construction............................. 6.7 89.3 10.2 949 9.1 Manufacturing............................ 3.5 105.4 0.5 1,134 1.3 Trade, transportation, and utilities..... 14.1 224.3 2.7 693 6.5 Information.............................. 1.3 37.6 2.0 1,881 18.0 Financial activities..................... 9.1 80.7 0.3 1,152 7.6 Professional and business services....... 15.0 209.1 1.5 1,065 6.5 Education and health services............ 7.6 120.9 -0.3 833 6.7 Leisure and hospitality.................. 6.6 145.7 1.4 369 5.1 Other services........................... 21.0 53.1 3.4 461 3.6 Government................................. 1.4 219.5 0.5 905 5.5 King, WA..................................... 78.2 1,117.2 1.8 973 3.8 Private industry........................... 77.7 960.4 1.9 987 4.3 Natural resources and mining............. 0.4 2.9 4.3 1,216 9.3 Construction............................. 6.3 56.8 5.5 954 3.7 Manufacturing............................ 2.6 102.7 0.7 1,189 1.4 Trade, transportation, and utilities..... 14.9 227.2 1.4 859 6.3 Information.............................. 1.5 68.5 -1.4 1,946 5.9 Financial activities..................... 6.3 76.5 -0.3 1,157 3.7 Professional and business services....... 12.1 164.2 4.8 1,195 3.1 Education and health services............ 6.0 113.0 4.1 785 5.7 Leisure and hospitality.................. 5.5 102.9 2.8 416 3.2 Other services........................... 22.0 45.7 -4.6 508 10.4 Government................................. 0.5 156.8 1.1 887 0.6 Miami-Dade, FL............................... 83.2 1,007.1 2.4 822 6.3 Private industry........................... 82.9 853.9 2.9 800 6.4 Natural resources and mining............. 0.5 10.4 2.1 453 8.6 Construction............................. 5.2 43.7 7.2 845 6.3 Manufacturing............................ 2.8 49.7 -0.7 722 3.9 Trade, transportation, and utilities..... 23.9 249.3 0.8 747 6.4 Information.............................. 1.8 26.8 -3.8 1,116 11.2 Financial activities..................... 8.9 68.6 3.8 1,161 7.7 Professional and business services....... 16.6 142.2 7.3 1,024 6.4 Education and health services............ 8.2 126.0 1.8 794 4.3 Leisure and hospitality.................. 5.6 98.1 4.6 452 3.4 Other services........................... 7.7 35.1 0.4 480 6.4 Government................................. 0.3 153.2 0.1 947 7.5 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. Table 3. Covered(1) establishments, employment, and wages in the largest county by state, fourth quarter 2004(2) Employment Average weekly wage(5) Establishments, fourth quarter County(3) 2004 Percent Percent (thousands) December change, Average change, 2004 December weekly fourth (thousands) 2003-04(4) wage quarter 2003-04(4) United States(6)......... 8,487.6 131,560.7 1.7 $812 5.7 Jefferson, AL............ 18.8 373.6 0.0 833 9.2 Anchorage Borough, AK.... 7.7 142.2 1.4 830 5.2 Maricopa, AZ............. 80.4 1,696.8 4.7 801 5.7 Pulaski, AR.............. 13.4 245.7 1.2 757 5.6 Los Angeles, CA.......... 366.8 4,123.1 1.4 959 6.1 Denver, CO............... 24.5 429.1 1.7 990 5.9 Hartford, CT............. 24.4 487.7 0.9 1,016 7.4 New Castle, DE........... 19.5 286.5 0.9 980 6.9 Washington, DC........... 30.3 659.6 0.6 1,305 5.5 Miami-Dade, FL........... 83.2 1,007.1 2.4 822 6.3 Fulton, GA............... 37.8 745.4 3.2 1,055 5.8 Honolulu, HI............. 23.4 441.3 3.3 756 7.2 Ada, ID.................. 13.4 193.4 4.8 742 8.2 Cook, IL................. 127.7 2,529.3 0.0 985 6.7 Marion, IN............... 23.8 586.8 1.6 833 4.1 Polk, IA................. 14.3 264.0 1.8 817 7.5 Johnson, KS.............. 19.0 300.7 2.4 841 7.3 Jefferson, KY............ 21.9 424.3 0.9 807 6.5 Orleans, LA.............. 12.6 247.7 -1.1 753 5.5 Cumberland, ME........... 12.3 173.4 0.8 769 7.1 Montgomery, MD........... 31.9 458.2 1.2 1,067 6.3 Middlesex, MA............ 48.7 791.6 0.1 1,146 5.4 Wayne, MI................ 34.6 804.2 -1.5 950 3.7 Hennepin, MN............. 41.0 840.1 1.5 1,049 9.6 Hinds, MS................ 6.6 130.2 -1.0 713 4.9 St. Louis, MO............ 33.8 626.2 0.6 863 5.2 Yellowstone, MT.......... 5.5 71.8 3.9 637 4.8 Douglas, NE.............. 15.0 312.1 0.3 757 7.4 Clark, NV................ 40.0 839.0 7.5 770 7.7 Hillsborough, NH......... 12.3 197.7 0.9 933 6.4 Bergen, NJ............... 34.4 456.5 0.2 1,067 3.7 Bernalillo, NM........... 16.4 318.6 1.9 727 5.2 New York, NY............. 112.9 2,266.8 0.9 1,608 8.4 Mecklenburg, NC.......... 27.4 519.3 2.1 948 8.1 Cass, ND................. 5.5 90.4 4.3 687 9.0 Cuyahoga, OH............. 38.3 764.3 0.2 864 7.6 Oklahoma, OK............. 21.9 411.7 1.6 698 4.0 Multnomah, OR............ 25.6 429.6 1.7 815 4.2 Allegheny, PA............ 35.6 691.6 -0.6 848 5.7 Providence, RI........... 17.9 289.8 -0.3 784 2.8 Greenville, SC........... 12.3 227.1 1.7 719 5.3 Minnehaha, SD............ 6.0 110.3 1.6 663 3.3 Shelby, TN............... 19.7 505.5 1.1 838 5.4 Harris, TX............... 90.8 1,861.3 1.3 978 7.8 Salt Lake, UT............ 35.8 535.9 2.8 743 6.0 Chittenden, VT........... 5.7 97.0 1.5 780 1.4 Fairfax, VA.............. 30.0 561.3 4.7 1,239 6.7 King, WA................. 78.2 1,117.2 1.8 973 3.8 Kanawha, WV.............. 6.2 108.5 -0.8 689 5.0 Milwaukee, WI............ 21.7 499.7 -0.3 824 6.7 Laramie, WY.............. 2.9 39.5 -0.1 630 5.5 San Juan, PR............. 13.6 338.0 1.0 535 4.3 St. Thomas, VI........... 1.7 22.9 -3.4 628 5.7 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. Table 4. Covered(1) establishments, employment, and wages by state, fourth quarter 2004(2) Employment Average weekly wage(3) Establishments, fourth quarter State 2004 Percent Percent (thousands) December change, Average change, 2004 December weekly fourth (thousands) 2003-04 wage quarter 2003-04 United States(4)......... 8,487.6 131,560.7 1.7 $812 5.7 Alabama.................. 116.0 1,882.0 2.3 695 5.8 Alaska................... 20.2 288.4 2.1 780 4.4 Arizona.................. 127.6 2,459.0 4.4 752 5.9 Arkansas................. 77.0 1,149.1 1.4 623 6.0 California............... 1,229.4 15,163.8 1.7 928 6.7 Colorado................. 164.3 2,181.7 2.2 830 5.9 Connecticut.............. 109.6 1,663.8 1.0 1,056 6.3 Delaware................. 29.5 418.0 2.1 883 7.0 District of Columbia..... 30.3 659.6 0.6 1,305 5.5 Florida.................. 534.2 7,729.7 3.7 736 6.5 Georgia.................. 253.0 3,916.5 2.1 772 5.0 Hawaii................... 35.9 603.0 3.3 723 6.6 Idaho.................... 50.3 597.8 3.6 618 6.6 Illinois................. 331.3 5,773.7 0.6 877 6.0 Indiana.................. 152.8 2,883.9 1.1 706 4.6 Iowa..................... 91.8 1,441.9 1.6 667 6.5 Kansas................... 82.8 1,317.5 1.5 668 5.9 Kentucky................. 107.9 1,761.9 1.2 679 5.3 Louisiana................ 117.1 1,890.3 0.7 658 4.9 Maine.................... 51.1 600.9 0.9 661 4.8 Maryland................. 156.9 2,506.0 1.7 879 5.8 Massachusetts............ 212.9 3,169.2 0.4 1,007 5.6 Michigan................. 253.7 4,348.5 -0.3 835 3.3 Minnesota................ 159.5 2,635.3 1.6 835 7.5 Mississippi.............. 66.9 1,116.7 0.8 586 4.8 Missouri................. 168.8 2,670.4 1.4 709 4.9 Montana.................. 41.7 409.3 3.2 572 4.2 Nebraska................. 55.8 891.8 0.9 648 5.7 Nevada................... 64.6 1,186.1 6.7 768 6.5 New Hampshire............ 47.7 624.0 1.4 840 6.5 New Jersey............... 269.2 3,964.7 1.1 1,001 5.7 New Mexico............... 50.0 773.2 2.2 645 5.0 New York................. 556.7 8,466.9 1.0 1,016 5.8 North Carolina........... 230.7 3,844.9 2.3 714 5.2 North Dakota............. 24.4 326.2 2.7 599 6.4 Ohio..................... 289.0 5,350.3 0.5 754 5.9 Oklahoma................. 93.1 1,458.8 2.2 627 5.0 Oregon................... 120.8 1,623.5 2.8 719 3.5 Pennsylvania............. 332.5 5,573.2 0.9 796 6.0 Rhode Island............. 35.4 482.6 0.4 765 3.5 South Carolina........... 114.4 1,811.0 2.0 655 5.0 South Dakota............. 28.8 371.2 1.6 581 3.9 Tennessee................ 130.7 2,704.3 2.3 728 5.5 Texas.................... 514.2 9,479.9 1.9 800 6.1 Utah..................... 79.5 1,100.6 3.3 664 5.2 Vermont.................. 24.6 304.7 1.1 676 2.3 Virginia................. 208.1 3,568.2 2.7 841 6.9 Washington............... 215.4 2,718.0 2.5 790 4.1 West Virginia............ 48.0 695.4 1.4 620 5.6 Wisconsin................ 158.7 2,755.2 1.4 719 5.4 Wyoming.................. 22.6 247.9 2.6 641 4.1 Puerto Rico.............. 53.5 1,098.0 1.9 468 3.8 Virgin Islands........... 3.2 43.7 1.0 670 6.3 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.