Technical information: (202) 691-6567 USDL 05-1976 http://www.bls.gov/cew/ For release: 10:00 A.M. EDT Media contact: 691-5902 Thursday, October 20, 2005 COUNTY EMPLOYMENT AND WAGES: FIRST QUARTER 2005 In March 2005, Clark County, Nev., 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. Clark County experienced an over-the-year employment gain of 7.6 percent, compared with national job growth of 1.7 percent. Collier County, Fla., had the largest over-the-year gain in average weekly wages in the first quarter of 2005, with an increase of 10.7 percent. The U.S. average weekly wage increased by 2.2 percent over the same time span. Of the 322 largest counties in the United States, as measured by 2004 annual average employment, 118 had over-the-year percentage growth in em- ployment above the national average in March 2005, and 186 experienced changes below the national average. Average weekly wages grew faster than the national average in 130 of the largest U.S. counties, while the percent change in average weekly wages was below the national average in 173 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 129.8 million full- and part-time workers. The attached tables and charts contain data for the nation and for the 322 U.S. counties with annual average employment levels of 75,000 or more in 2004. In addition, data for San Juan, Puerto Rico, are provided, but not used in calculating U.S. averages, rankings, or in the analysis in the text. March 2005 employment and 2005 first-quarter average weekly wages for all states are provided in table 4 of this release. Data for all states, metro- politan statistical areas, counties, and the nation through the fourth quar- ter of 2004 are available on the BLS Web site at http://www.bls.gov/cew/. Preliminary data for the first quarter of 2005 and final data for 2004 will be available later in October on the BLS Web site. ----------------------------------------------------------------- | Five Counties Added to the 2005 County Employment | | and Wages News Releases | | | | Counties with employment of 75,000 or more are included in this | | release. For 2005 data, five counties have been added to the | | publication tables: Lake, Fla., Wyandotte, Kan., Harford, Md., | | Washington, Pa., and Whatcom, Wash. All counties published in | | the 2004 releases continue to have employment levels of 75,000 | | or more and will be included in the 2005 releases. | ----------------------------------------------------------------- - 2 - Table A. Top 10 counties ranked by March 2005 employment, March 2004-05 employment change, and March 2004-05 percent change in employment --------------------------------------------------------------------------------- Employment in large counties --------------------------------------------------------------------------------- | | March 2005 employment | Net change in employment, | Percent change (thousands) | March 2004-05 | in employment, | (thousands) | March 2004-05 ---------------------------|----------------------------|------------------------ U.S. 129,802.3|U.S. 2,146.7|U.S. 1.7 ---------------------------|----------------------------|------------------------ Los Angeles, Calif. 4,051.2|Maricopa, Ariz. 85.1|Clark, Nev. 7.6 Cook, Ill. 2,466.4|Clark, Nev. 59.9|Lee, Fla. 7.5 New York, N.Y. 2,221.5|Orange, Calif. 32.8|Rutherford, Tenn. 7.1 Harris, Texas 1,840.9|Harris, Texas 30.6|Seminole, Fla. 6.9 Maricopa, Ariz. 1,685.4|Riverside, Calif. 29.8|Montgomery, Texas 6.1 Orange, Calif. 1,477.6|San Bernardino, Calif. 29.2|Benton, Ark. 5.7 Dallas, Texas 1,402.1|Palm Beach, Fla. 25.0|Lake, Fla. 5.4 San Diego, Calif. 1,282.1|Broward, Fla. 24.4|Williamson, Texas 5.4 King, Wash. 1,093.0|Hillsborough, Fla. 22.3|Maricopa, Ariz. 5.3 Miami-Dade, Fla. 994.9|Fairfax, Va. 21.3|Utah, Utah 5.3 | |Whatcom, Wash. 5.3 --------------------------------------------------------------------------------- Large County Employment In March 2005, national employment, as measured by the QCEW program, was 129.8 million, up by 1.7 percent from March 2004. The 322 U.S. counties with 75,000 or more employees accounted for 70.8 percent of total U.S. covered employment and 77.5 percent of total covered wages. These 322 counties had a net job gain of 1,324,000 over the year, accounting for 61.7 percent of the U.S. employment increase. Employment increased in 254 of the large counties from March 2004 to March 2005. Clark County, Nev., had the largest over-the-year percentage increase in employment (7.6 percent). Lee, Fla., had the next largest increase, 7.5 percent, followed by the counties of Rutherford, Tenn. (7.1 percent), Seminole, Fla. (6.9 percent), and Montgomery, Texas (6.1 percent). (See table 1.) Employment declined in 51 counties from March 2004 to March 2005. The largest percentage decline in employment was in Bibb County, Ga. (-1.9 percent), followed by the counties of McLean, Ill. (-1.7 percent), Broome, N.Y. (-1.5 percent), and Madison, Ill., and St. Louis City, Mo. (-1.4 percent each). The largest gains in employment from March 2004 to March 2005 were recorded in the counties of Maricopa, Ariz. (85,100), Clark, Nev. (59,900), Orange, Calif. (32,800), Harris, Texas (30,600), and Riverside, Calif. (29,800). (See table A.) The largest decline in employment occurred in Wayne County, Mich. (-8,300), followed by the counties of Allegheny, Pa. (-5,400), Erie, N.Y. (-3,500), St. Louis City, Mo. (-3,100), and Milwaukee, Wis. (-2,800). Large County Average Weekly Wages The national average weekly wage in the first quarter of 2005 was $775. Average weekly wages were higher than the national average in 101 of the largest 322 U.S. counties. New York County, N.Y., held the top position among the highest-paid large counties with an average weekly wage of $2,025. Fairfield County, Conn., was second with an average weekly wage of $1,613, followed by Suffolk, Mass. ($1,390), Santa Clara, Calif. ($1,372), and San Francisco, Calif. ($1,368). (See table B.) - 3 - Table B. Top 10 counties ranked by first quarter 2005 average weekly wages, first quarter 2004-05 change in average weekly wages, and first quarter 2004-05 percent change in average weekly wages ------------------------------------------------------------------------------ Average weekly wage in large counties ------------------------------------------------------------------------------ | | Average weekly wage, | Change in average weekly| Percent change in first quarter 2005 | wage, first quarter | average weekly wage, | 2004-05 | first quarter 2004-05 ---------------------------|-------------------------|------------------------ U.S. $775|U.S. $17|U.S. 2.2 ---------------------------|-------------------------|------------------------ New York, N.Y. $2,025|Fairfield, Conn. $115|Collier, Fla. 10.7 Fairfield, Conn. 1,613|New York, N.Y. 111|Cumberland, Pa. 9.3 Suffolk, Mass. 1,390|Hudson, N.J. 102|Hudson, N.J. 9.0 Santa Clara, Calif. 1,372|Henrico, Va. 69|Henrico, Va. 8.4 San Francisco, Calif. 1,368|Collier, Fla. 68|Fairfield, Conn. 7.7 Somerset, N.J. 1,343|Cumberland, Pa. 67|Rock Island, Ill. 7.7 Arlington, Va. 1,286|Mecklenburg, N.C. 57|Trumbull, Ohio 7.3 Washington, D.C. 1,277|Washington, D.C. 52|Tuscaloosa, Ala. 7.0 Hudson, N.J. 1,236|Rock Island, Ill. 52|Peoria, Ill. 6.8 San Mateo, Calif. 1,220|Harris, Texas 52|Jefferson, Texas 6.5 | | ------------------------------------------------------------------------------ There were 220 counties with an average weekly wage below the national average in the first quarter of 2005. The lowest average weekly wages were reported in Cameron County, Texas ($460), followed by the counties of Hidalgo, Texas ($463), Horry, S.C. ($479), Webb, Texas ($490), and Yakima, Wash. ($516). (See table 1.) Over the year, the national average weekly wage rose by 2.2 percent. Among the largest counties, Collier, Fla., led the nation in growth in average weekly wages, with an increase of 10.7 percent from the first quarter of 2004. Cumberland, Pa., was second with 9.3 percent growth, followed by the counties of Hudson, N.J. (9.0 percent), Henrico, Va. (8.4 percent), and Fairfield, Conn., and Rock Island, Ill. (7.7 percent each). Thirty-five counties experienced over-the-year declines in average weekly wages. Clayton County, Ga., had the largest decrease, -6.0 per- cent, followed by the counties of Marin, Calif. (-5.6 percent), Hamilton, Ind. (-4.3 percent), McLean, Ill. (-2.8 percent), and St. Louis, Minn. (-2.7 percent). Ten Largest U.S. Counties Of the 10 largest U.S. counties (based on 2004 annual average employment levels), 8 reported increases in employment, while 2 showed a decline from March 2004 to March 2005. Maricopa County, Ariz., experienced the fastest growth in employment among the largest counties, with a 5.3 percent increase. Within Maricopa County, employment rose in every industry group except infor- mation. The largest gains were in construction (15.1 percent) and professional and business services (7.5 percent). (See table 2.) Orange County, Calif., had the next largest increase in employment, 2.3 percent, followed by Miami- Dade, Fla. (1.9 percent). The smallest employment gain occurred in New York, N.Y. (0.8 percent). Both Cook County, Ill., and Los Angeles, Calif. experi- enced a 0.1 percent decrease in employment over the year. - 4 - All of the 10 largest U.S. counties saw over-the-year increases in average weekly wages. New York County, N.Y., and Harris, Texas, had the fastest growth in wages among the 10 largest counties, increasing by 5.8 percent each. Within New York County, wages increased the most in manufacturing (25.7 percent) and natural resources and mining (14.4 percent). Within Harris County, wages increased most in natural resources and mining (17.4 percent) and manufacturing (12.1 percent). King, Wash., and Miami-Dade, Fla., were second in wage growth, increasing by 2.9 percent each. The smallest wage gains among the 10 largest counties occurred in San Diego County, Calif. (1.4 percent), and Dallas, Texas, and Maricopa, Ariz. (1.5 percent each). Largest County by State Table 3 shows March 2005 employment and the 2005 first 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 March 2005 ranged from approximately 4.1 million in Los Angeles County, Calif., to 39,500 in Laramie County, Wyo. The highest average weekly wage of these counties was in New York, N.Y. ($2,025), while the lowest average weekly wage was in Yellowstone County, Mont. ($596). ------------------------------------------------------------------ | Regional Quarterly Census of Employment | | and Wages News Releases | | | | Several BLS regional offices have recently begun issuing QCEW | | news releases targeted to local data users. For links to these | | releases, see http://www.bls.gov/cew/cewregional.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 2005 are preliminary and sub- ject to revision. For purposes of this release, large counties are defined as having em- ployment 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 323 counties presented in this release were derived using 2004 preliminary annual averages of employment. All of the 318 counties that were published in the 2004 releases are included in the 2005 releases. The following counties grew enough in 2004 to be included in the 2005 releases: Lake, Fla., Wyandotte, Kan., Harford, Md., Washington, Pa., and Whatcom, Wash. These counties will be included in all 2005 quar- terly 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 2004, UI and UCFE programs covered workers in 129.3 million jobs. The estimated 124.4 million workers in these jobs (after adjust- ment for multiple jobholders) represented 96.6 percent of civilian wage and salary employment. Covered workers received $5.088 trillion in pay, representing 94.4 percent of the wage and salary component of personal income and 43.4 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. Beginning with the first quarter of 2005, Oregon implemented a change in their state UI laws. This change extended UI coverage to providers of home care for the elderly. These providers are now considered state workers for purposes of UI benefits. 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 2004 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. The 2004 edition of this bulletin contains selected data produced by Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the fourth quarter 2004 version of this news release. Employment and Wages Annual Averages, 2004 will be available for sale in late 2005 from the United States Government Printing Office, Superintendent of Documents, P.O. Box 371954, Pittsburgh, PA 15250, telephone 866-512-1800, outside of Washington, D.C. Within Washington, D.C., the telephone number is 202-512-1800. The fax number is 202-512-2104. Also, the 2004 bulletin will be available in a portable document format (PDF) on the BLS Web site at http://www.bls.gov/cew/cewbultn04.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 323 largest counties, first quarter 2005(2) Employment Average weekly wage(5) Establishments, County(3) first quarter Percent Ranking Percent Ranking 2005 March change, by Average change, by (thousands) 2005 March percent weekly first percent (thousands) 2004-05(4) change wage quarter change 2004-05(4) United States(6)......... 8,543.2 129,802.3 1.7 - $775 2.2 - Jefferson, AL............ 18.7 366.3 -0.6 287 788 2.6 105 Madison, AL.............. 8.1 165.6 2.5 83 799 5.1 17 Mobile, AL............... 9.7 165.1 3.3 54 608 3.1 73 Montgomery, AL........... 6.6 132.3 1.2 156 631 2.1 141 Tuscaloosa, AL........... 4.2 80.0 3.4 49 626 7.0 8 Anchorage Borough, AK.... 7.8 139.6 1.2 156 793 1.5 182 Maricopa, AZ............. 81.2 1,685.4 5.3 9 746 1.5 182 Pima, AZ................. 17.8 350.6 3.2 58 647 3.2 67 Benton, AR............... 4.7 88.3 5.7 6 771 -0.5 287 Pulaski, AR.............. 13.4 241.8 1.4 139 683 2.2 131 Washington, AR........... 5.2 88.0 4.2 32 585 3.2 67 Alameda, CA.............. 48.5 674.5 0.1 250 997 2.9 86 Contra Costa, CA......... 27.9 338.4 0.2 248 1,021 5.0 19 Fresno, CA............... 29.4 324.6 2.6 80 600 1.4 194 Kern, CA................. 16.4 249.0 3.5 45 652 0.0 275 Los Angeles, CA.......... 373.9 4,051.2 -0.1 262 864 2.0 148 Marin, CA................ 11.8 108.1 0.8 200 933 -5.6 312 Monterey, CA............. 12.0 157.7 0.6 223 697 3.0 83 Orange, CA............... 91.4 1,477.6 2.3 92 893 2.2 131 Placer, CA............... 9.7 133.5 3.6 41 749 3.5 50 Riverside, CA............ 40.0 598.4 5.2 12 652 0.9 230 Sacramento, CA........... 48.1 616.9 2.3 92 855 2.5 111 San Bernardino, CA....... 43.7 627.1 4.9 20 654 0.8 240 San Diego, CA............ 88.4 1,282.1 1.2 156 816 1.4 194 San Francisco, CA........ 43.5 519.9 0.7 209 1,368 3.8 37 San Joaquin, CA.......... 16.3 215.4 1.3 149 638 -0.6 289 San Luis Obispo, CA...... 8.8 101.3 0.8 200 621 2.1 141 San Mateo, CA............ 22.9 325.0 -0.5 278 1,220 1.2 206 Santa Barbara, CA........ 13.3 179.5 0.3 243 733 3.7 41 Santa Clara, CA.......... 53.2 850.1 1.0 177 1,372 2.1 141 Santa Cruz, CA........... 8.5 92.3 1.0 177 723 -2.4 307 Solano, CA............... 9.7 127.4 1.9 109 715 0.1 271 Sonoma, CA............... 17.4 187.8 0.0 255 737 3.7 41 Stanislaus, CA........... 13.5 169.5 4.0 34 635 1.0 221 Tulare, CA............... 8.6 133.2 2.5 83 530 1.0 221 Ventura, CA.............. 21.0 313.6 1.3 149 861 4.5 26 Yolo, CA................. 5.2 96.4 1.2 156 704 4.3 29 Adams, CO................ 8.8 144.2 3.0 68 712 0.3 262 Arapahoe, CO............. 19.1 268.0 1.3 149 943 1.5 182 Boulder, CO.............. 12.0 152.7 3.2 58 919 -0.3 279 Denver, CO............... 24.4 418.1 1.0 177 976 3.8 37 El Paso, CO.............. 16.3 235.2 2.0 105 692 0.9 230 Jefferson, CO............ 18.2 203.2 1.9 109 795 3.7 41 Larimer, CO.............. 9.4 121.5 2.2 97 670 1.2 206 Fairfield, CT............ 31.8 406.5 0.3 243 1,613 7.7 5 Hartford, CT............. 24.4 480.1 1.2 156 1,041 3.4 58 New Haven, CT............ 22.1 357.9 0.5 236 816 1.0 221 New London, CT........... 6.7 127.9 1.8 115 784 -0.8 294 New Castle, DE........... 19.6 278.6 0.1 250 1,005 4.9 20 Washington, DC........... 30.5 661.7 1.1 168 1,277 4.2 31 Alachua, FL.............. 6.1 123.0 (7) - 591 (7) - Brevard, FL.............. 13.3 201.1 3.6 41 701 -0.3 279 Broward, FL.............. 60.0 722.8 3.5 45 732 3.1 73 Collier, FL.............. 11.1 130.0 2.7 75 702 10.7 1 Duval, FL................ 23.9 444.7 3.2 58 766 2.7 96 Escambia, FL............. 7.5 128.0 3.1 64 589 3.2 67 Hillsborough, FL......... 33.2 628.9 3.7 40 732 1.5 182 Lake, FL................. 6.0 79.9 5.4 7 536 2.5 111 Lee, FL.................. 16.6 210.5 7.5 2 649 5.4 16 Leon, FL................. 7.6 144.7 0.0 255 625 1.3 198 Manatee, FL.............. 7.9 129.9 4.4 30 560 3.3 62 Marion, FL............... 7.1 96.7 (7) - 541 1.9 153 Miami-Dade, FL........... 83.6 994.9 1.9 109 748 2.9 86 Okaloosa, FL............. 5.8 81.2 4.5 27 593 4.4 27 Orange, FL............... 31.4 660.0 (7) - 703 (7) - Palm Beach, FL........... 45.7 549.1 4.8 23 769 5.8 12 Pasco, FL................ 8.1 91.9 (7) - 518 (7) - Pinellas, FL............. 29.6 434.6 -0.3 269 659 3.3 62 Polk, FL................. 11.3 201.9 3.6 41 582 2.8 92 Sarasota, FL............. 14.0 155.3 5.1 16 640 2.4 120 Seminole, FL............. 13.0 162.3 6.9 4 691 4.7 25 Volusia, FL.............. 12.8 162.3 3.5 45 550 3.8 37 Bibb, GA................. 4.7 85.5 -1.9 312 632 2.9 86 Chatham, GA.............. 7.1 129.5 1.6 127 629 1.5 182 Clayton, GA.............. 4.3 108.2 1.8 115 740 -6.0 313 Cobb, GA................. 19.9 303.3 0.9 186 830 2.3 126 De Kalb, GA.............. 16.9 288.9 0.8 200 845 2.2 131 Fulton, GA............... 37.3 729.7 0.9 186 1,076 3.0 83 Gwinnett, GA............. 21.7 309.2 1.6 127 804 0.9 230 Muscogee, GA............. 4.7 96.6 0.6 223 606 0.5 254 Richmond, GA............. 4.7 104.5 -0.6 287 625 2.5 111 Honolulu, HI............. 23.6 436.2 3.0 68 693 1.5 182 Ada, ID.................. 13.5 192.2 4.5 27 667 1.7 165 Champaign, IL............ 4.0 89.7 0.7 209 619 -0.3 279 Cook, IL................. 128.4 2,466.4 -0.1 262 983 2.8 92 Du Page, IL.............. 33.2 569.9 0.9 186 918 3.5 50 Kane, IL................. 11.5 197.7 1.8 115 689 1.5 182 Lake, IL................. 19.4 315.6 1.0 177 955 2.5 111 McHenry, IL.............. 7.7 94.0 2.1 99 644 -0.9 297 McLean, IL............... 3.4 80.4 -1.7 311 716 -2.8 310 Madison, IL.............. 5.7 92.8 -1.4 308 640 3.2 67 Peoria, IL............... 4.6 99.8 2.4 87 759 6.8 9 Rock Island, IL.......... 3.4 77.2 0.9 186 728 7.7 5 St. Clair, IL............ 5.1 92.8 0.6 223 591 1.7 165 Sangamon, IL............. 5.1 128.9 -0.2 267 753 4.0 33 Will, IL................. 11.2 161.1 2.1 99 689 0.9 230 Winnebago, IL............ 6.7 134.5 -1.0 300 652 2.7 96 Allen, IN................ 8.9 177.4 0.0 255 658 -0.3 279 Elkhart, IN.............. 4.9 123.9 3.8 38 635 1.6 169 Hamilton, IN............. 6.6 91.4 5.2 12 781 -4.3 311 Lake, IN................. 10.1 190.3 1.2 156 671 1.8 160 Marion, IN............... 24.0 575.1 1.4 139 818 1.0 221 St. Joseph, IN........... 6.1 124.2 0.5 236 636 1.6 169 Vanderburgh, IN.......... 4.8 107.2 0.3 243 644 2.1 141 Linn, IA................. 6.1 117.0 2.1 99 725 2.3 126 Polk, IA................. 14.1 259.9 1.9 109 792 1.5 182 Scott, IA................ 5.1 86.2 3.6 41 607 2.0 148 Johnson, KS.............. 19.0 294.1 1.7 119 817 0.0 275 Sedgwick, KS............. 11.8 239.5 1.1 168 706 3.7 41 Shawnee, KS.............. 4.8 93.8 -0.9 299 632 1.3 198 Wyandotte, KS............ 3.2 74.7 1.0 177 728 -0.5 287 Fayette, KY.............. 8.8 167.5 2.4 87 684 -2.3 305 Jefferson, KY............ 21.7 415.8 1.0 177 742 -1.1 299 Caddo, LA................ 7.1 122.0 2.3 92 600 -1.3 300 Calcasieu, LA............ 4.7 83.0 1.4 139 639 3.4 58 East Baton Rouge, LA..... 13.1 246.2 0.1 250 654 3.2 67 Jefferson, LA............ 14.0 213.0 -0.3 269 633 3.3 62 Lafayette, LA............ 7.7 120.1 2.7 75 642 2.6 105 Orleans, LA.............. 12.6 244.5 -1.1 303 738 2.2 131 Cumberland, ME........... 11.6 165.1 0.0 255 707 1.6 169 Anne Arundel, MD......... 14.0 217.9 1.4 139 792 2.5 111 Baltimore, MD............ 21.2 356.0 0.7 209 785 1.0 221 Frederick, MD............ 5.7 90.0 0.9 186 725 -2.4 307 Harford, MD.............. 5.4 79.3 2.0 105 704 6.2 11 Howard, MD............... 8.2 135.4 -0.5 278 875 3.1 73 Montgomery, MD........... 32.4 452.6 1.6 127 1,041 2.6 105 Prince Georges, MD....... 15.5 310.5 -0.4 274 797 1.1 213 Baltimore City, MD....... 14.0 357.5 0.1 250 909 1.6 169 Barnstable, MA........... 9.4 82.5 -0.8 294 653 0.9 230 Bristol, MA.............. 15.6 216.0 -0.5 278 661 1.8 160 Essex, MA................ 21.1 287.8 -0.7 292 803 1.6 169 Hampden, MA.............. 14.4 195.4 -0.5 278 728 3.1 73 Middlesex, MA............ 48.9 775.9 0.5 236 1,097 2.2 131 Norfolk, MA.............. 22.2 311.4 -0.5 278 916 0.1 271 Plymouth, MA............. 14.0 170.7 2.0 105 705 -0.3 279 Suffolk, MA.............. 22.6 556.6 0.7 209 1,390 -1.0 298 Worcester, MA............ 20.7 312.4 -0.6 287 754 1.3 198 Genesee, MI.............. 8.5 147.0 (7) - 710 (7) - Ingham, MI............... 7.1 162.4 (7) - 754 (7) - Kalamazoo, MI............ 5.5 115.0 -0.1 262 721 -2.3 305 Kent, MI................. 14.6 332.0 0.9 186 692 1.6 169 Macomb, MI............... 18.0 320.3 -0.3 269 830 0.6 251 Oakland, MI.............. 40.9 703.0 -0.3 269 932 1.2 206 Ottawa, MI............... 5.8 109.6 1.4 139 676 3.2 67 Saginaw, MI.............. 4.6 88.0 -0.7 292 686 1.6 169 Washtenaw, MI............ 8.2 193.9 0.4 239 859 -0.8 294 Wayne, MI................ 34.4 783.3 -1.1 303 892 0.2 267 Anoka, MN................ 7.4 110.5 1.7 119 720 1.0 221 Dakota, MN............... 9.7 166.3 1.2 156 755 0.3 262 Hennepin, MN............. 40.0 815.7 1.4 139 999 1.4 194 Olmsted, MN.............. 3.3 86.1 -0.6 287 860 1.1 213 Ramsey, MN............... 14.7 323.1 1.0 177 875 -0.6 289 St. Louis, MN............ 5.7 91.9 0.9 186 618 -2.7 309 Stearns, MN.............. 4.2 76.2 0.8 200 583 0.3 262 Harrison, MS............. 4.6 90.7 1.6 127 561 4.3 29 Hinds, MS................ 6.5 128.0 -0.8 294 653 0.9 230 Boone, MO................ 4.3 79.0 3.4 49 573 1.2 206 Clay, MO................. 5.0 86.1 1.1 168 693 1.5 182 Greene, MO............... 8.0 147.7 2.7 75 576 2.7 96 Jackson, MO.............. 18.7 360.7 0.6 223 776 1.3 198 St. Charles, MO.......... 7.5 115.7 4.8 23 652 1.2 206 St. Louis, MO............ 33.9 612.3 0.6 223 819 0.7 246 St. Louis City, MO....... 8.2 219.4 -1.4 308 910 0.9 230 Douglas, NE.............. 14.9 304.9 0.7 209 708 -0.6 289 Lancaster, NE............ 7.6 151.5 2.1 99 610 0.2 267 Clark, NV................ 40.9 844.7 7.6 1 718 3.5 50 Washoe, NV............... 13.1 206.7 4.3 31 705 1.9 153 Hillsborough, NH......... 12.2 192.6 0.7 209 827 2.6 105 Rockingham, NH........... 10.7 132.0 1.2 156 766 0.4 255 Atlantic, NJ............. 6.7 142.0 1.2 156 676 0.7 246 Bergen, NJ............... 34.2 442.4 0.0 255 982 1.9 153 Burlington, NJ........... 11.2 198.2 1.1 168 801 0.4 255 Camden, NJ............... 13.5 208.7 1.5 135 756 -0.7 293 Essex, NJ................ 21.2 355.6 -0.1 262 1,050 1.1 213 Gloucester, NJ........... 6.2 100.9 3.4 49 679 0.7 246 Hudson, NJ............... 13.9 235.5 0.4 239 1,236 9.0 3 Mercer, NJ............... 10.8 218.9 2.6 80 990 0.4 255 Middlesex, NJ............ 20.7 386.8 -0.3 269 1,022 0.6 251 Monmouth, NJ............. 20.0 249.0 0.7 209 836 1.6 169 Morris, NJ............... 17.7 278.0 -0.8 294 1,190 3.7 41 Ocean, NJ................ 11.5 140.3 0.9 186 649 1.9 153 Passaic, NJ.............. 12.5 174.9 0.8 200 805 1.6 169 Somerset, NJ............. 10.0 166.3 0.1 250 1,343 1.5 182 Union, NJ................ 14.9 226.7 (7) - 1,004 (7) - Bernalillo, NM........... 16.6 313.7 1.1 168 657 1.9 153 Albany, NY............... 9.6 225.7 -0.4 274 780 0.0 275 Bronx, NY................ 15.6 219.0 2.6 80 705 2.2 131 Broome, NY............... 4.5 92.9 -1.5 310 602 2.0 148 Dutchess, NY............. 7.9 116.6 0.6 223 801 3.5 50 Erie, NY................. 23.2 449.9 -0.8 294 680 0.7 246 Kings, NY................ 42.3 451.5 1.7 119 660 -0.3 279 Monroe, NY............... 17.6 379.8 0.9 186 744 -1.8 303 Nassau, NY............... 51.0 588.0 -0.1 262 860 3.4 58 New York, NY............. 113.4 2,221.5 0.8 200 2,025 5.8 12 Oneida, NY............... 5.3 107.3 0.7 209 587 0.9 230 Onondaga, NY............. 12.7 244.7 0.6 223 694 0.1 271 Orange, NY............... 9.4 125.7 0.6 223 648 4.0 33 Queens, NY............... 40.3 471.5 1.1 168 759 1.9 153 Richmond, NY............. 8.2 88.2 0.6 223 664 0.8 240 Rockland, NY............. 9.4 111.0 1.2 156 806 1.0 221 Suffolk, NY.............. 48.2 593.6 0.3 243 787 0.4 255 Westchester, NY.......... 35.6 407.5 0.7 209 1,102 3.1 73 Buncombe, NC............. 7.0 108.3 3.4 49 575 1.8 160 Catawba, NC.............. 4.3 86.5 -0.4 274 580 3.6 47 Cumberland, NC........... 5.8 115.1 4.0 34 558 2.2 131 Durham, NC............... 6.2 168.9 1.0 177 1,032 -2.0 304 Forsyth, NC.............. 8.4 177.3 1.8 115 729 -0.3 279 Guilford, NC............. 13.7 269.8 1.7 119 686 1.6 169 Mecklenburg, NC.......... 27.4 513.7 3.2 58 1,048 5.8 12 New Hanover, NC.......... 6.6 93.2 5.2 12 611 4.8 23 Wake, NC................. 23.7 394.7 2.9 70 765 1.1 213 Cass, ND................. 5.5 88.5 3.2 58 610 0.8 240 Butler, OH............... 7.0 133.7 0.4 239 679 3.3 62 Cuyahoga, OH............. 38.1 740.8 0.0 255 813 2.8 92 Franklin, OH............. 29.1 671.3 0.7 209 776 2.0 148 Hamilton, OH............. 24.6 529.4 -0.5 278 850 2.4 120 Lake, OH................. 6.8 98.8 1.3 149 662 4.4 27 Lorain, OH............... 6.3 99.8 -1.3 307 653 2.2 131 Lucas, OH................ 10.9 222.0 (7) - 705 (7) - Mahoning, OH............. 6.5 104.2 0.7 209 555 -1.6 302 Montgomery, OH........... 13.2 279.1 -0.4 274 725 2.7 96 Stark, OH................ 9.3 165.1 0.7 209 597 1.0 221 Summit, OH............... 14.9 266.4 1.7 119 714 -0.4 286 Trumbull, OH............. 4.8 82.7 -1.0 300 704 7.3 7 Oklahoma, OK............. 22.2 406.2 1.3 149 657 1.7 165 Tulsa, OK................ 18.4 324.5 3.1 64 686 2.2 131 Clackamas, OR............ 11.7 141.4 4.9 20 695 1.6 169 Jackson, OR.............. 6.4 80.8 4.9 20 562 1.1 213 Lane, OR................. 10.4 143.1 4.2 32 586 2.3 126 Marion, OR............... 8.7 131.4 5.0 17 594 0.8 240 Multnomah, OR............ 25.6 424.2 3.1 64 778 2.2 131 Washington, OR........... 14.8 230.4 5.0 17 890 -0.6 289 Allegheny, PA............ 35.7 672.8 -0.8 294 817 1.4 194 Berks, PA................ 9.1 161.3 1.2 156 667 2.5 111 Bucks, PA................ 20.4 255.4 1.4 139 723 1.3 198 Chester, PA.............. 15.0 225.9 1.6 127 985 3.5 50 Cumberland, PA........... 5.8 123.3 -1.0 300 784 9.3 2 Dauphin, PA.............. 7.1 173.9 1.9 109 764 0.7 246 Delaware, PA............. 13.8 206.8 -0.5 278 799 0.6 251 Erie, PA................. 7.2 125.8 1.6 127 582 0.9 230 Lackawanna, PA........... 5.9 98.3 1.7 119 573 1.1 213 Lancaster, PA............ 12.0 224.9 1.5 135 640 1.3 198 Lehigh, PA............... 8.4 172.0 0.8 200 758 2.7 96 Luzerne, PA.............. 8.2 140.7 0.9 186 590 -0.8 294 Montgomery, PA........... 27.8 476.1 0.6 223 1,010 0.2 267 Northampton, PA.......... 6.4 92.5 1.3 149 668 2.9 86 Philadelphia, PA......... 29.7 631.7 1.1 168 895 0.4 255 Washington, PA........... 5.3 74.1 0.9 186 629 1.6 169 Westmoreland, PA......... 9.7 136.4 1.4 139 591 3.0 83 York, PA................. 8.9 171.4 2.8 72 669 0.0 275 Kent, RI................. 5.6 79.8 0.2 248 682 0.3 262 Providence, RI........... 18.0 281.0 -0.5 278 764 1.3 198 Charleston, SC........... 12.1 194.4 2.4 87 629 3.3 62 Greenville, SC........... 12.4 222.8 1.4 139 658 0.8 240 Horry, SC................ 8.2 103.7 4.6 25 479 0.4 255 Lexington, SC............ 5.7 87.8 5.0 17 570 4.8 23 Richland, SC............. 9.6 205.1 2.8 72 643 2.4 120 Spartanburg, SC.......... 6.3 115.0 0.3 243 682 3.5 50 Minnehaha, SD............ 6.0 108.2 2.3 92 635 3.8 37 Davidson, TN............. 17.9 431.8 1.6 127 765 2.4 120 Hamilton, TN............. 8.3 191.1 1.2 156 640 2.1 141 Knox, TN................. 10.4 215.5 1.5 135 639 1.1 213 Rutherford, TN........... 3.7 93.9 7.1 3 657 0.9 230 Shelby, TN............... 19.7 494.2 0.7 209 759 0.3 262 Bell, TX................. 4.2 93.8 (7) - 560 3.5 50 Bexar, TX................ 30.0 663.0 1.9 109 688 2.5 111 Brazoria, TX............. 4.2 78.5 2.1 99 751 1.1 213 Brazos, TX............... 3.6 79.0 0.4 239 542 2.7 96 Cameron, TX.............. 6.2 115.8 -0.5 278 460 3.6 47 Collin, TX............... 14.0 238.3 (7) - 908 (7) - Dallas, TX............... 65.9 1,402.1 1.0 177 954 1.5 182 Denton, TX............... 9.2 144.6 3.8 38 650 2.5 111 El Paso, TX.............. 12.6 254.4 1.4 139 529 3.1 73 Fort Bend, TX............ 7.1 107.5 2.8 72 820 3.1 73 Galveston, TX............ 4.8 86.5 0.9 186 673 4.0 33 Harris, TX............... 89.9 1,840.9 1.7 119 950 5.8 12 Hidalgo, TX.............. 9.6 197.4 4.6 25 463 2.7 96 Jefferson, TX............ 5.8 116.6 0.7 209 718 6.5 10 Lubbock, TX.............. 6.5 118.3 2.4 87 551 0.4 255 McLennan, TX............. 4.8 101.4 1.6 127 605 4.9 20 Montgomery, TX........... 7.0 100.8 6.1 5 670 2.8 92 Nueces, TX............... 8.0 146.8 1.5 135 614 2.5 111 Potter, TX............... 3.7 71.4 -1.1 303 587 2.4 120 Smith, TX................ 5.0 89.4 3.3 54 631 1.9 153 Tarrant, TX.............. 34.6 705.7 2.2 97 775 2.0 148 Travis, TX............... 25.0 521.8 3.3 54 866 3.1 73 Webb, TX................. 4.4 79.3 1.1 168 490 3.6 47 Williamson, TX........... 5.8 99.5 5.4 7 802 2.3 126 Davis, UT................ 6.5 93.0 3.2 58 594 -1.5 301 Salt Lake, UT............ 35.4 529.0 3.4 49 680 1.3 198 Utah, UT................. 11.5 152.8 5.3 9 560 2.9 86 Weber, UT................ 5.5 87.8 1.1 168 538 0.2 267 Chittenden, VT........... 5.7 93.4 0.8 200 766 4.9 20 Arlington, VA............ 7.1 152.4 0.9 186 1,286 3.5 50 Chesterfield, VA......... 6.8 112.9 2.0 105 694 3.9 36 Fairfax, VA.............. 30.4 555.9 4.0 34 1,181 2.1 141 Henrico, VA.............. 8.4 170.4 2.9 70 891 8.4 4 Loudoun, VA.............. 6.8 116.3 5.2 12 1,005 3.1 73 Prince William, VA....... 6.2 97.4 3.5 45 654 2.7 96 Alexandria City, VA...... 5.7 92.3 0.6 223 972 5.1 17 Chesapeake City, VA...... 5.0 93.9 2.4 87 576 1.2 206 Newport News City, VA.... 3.8 98.4 2.1 99 672 3.1 73 Norfolk City, VA......... 5.6 145.4 0.9 186 723 0.8 240 Richmond City, VA........ 7.0 157.5 0.6 223 907 0.1 271 Virginia Beach City, VA.. 10.8 172.8 3.1 64 584 2.6 105 Clark, WA................ 10.2 123.1 4.5 27 675 2.1 141 King, WA................. 73.3 1,093.0 1.7 119 948 2.9 86 Kitsap, WA............... 6.1 80.8 2.3 92 659 (7) - Pierce, WA............... 18.9 253.7 3.3 54 683 2.4 120 Snohomish, WA............ 15.8 216.6 4.0 34 761 3.7 41 Spokane, WA.............. 14.0 194.1 2.5 83 609 1.5 182 Thurston, WA............. 6.1 92.6 2.7 75 676 2.7 96 Whatcom, WA.............. 6.3 77.2 5.3 9 578 2.3 126 Yakima, WA............... 7.4 90.3 2.7 75 516 2.6 105 Kanawha, WV.............. 6.2 106.3 -1.1 303 660 1.7 165 Brown, WI................ 6.7 143.7 -0.2 267 689 4.2 31 Dane, WI................. 13.8 291.6 2.5 83 740 1.8 160 Milwaukee, WI............ 21.5 485.6 -0.6 287 785 1.8 160 Outagamie, WI............ 5.0 99.1 1.3 149 667 1.2 206 Racine, WI............... 4.3 74.5 0.0 255 677 1.0 221 Waukesha, WI............. 13.3 225.2 0.6 223 765 3.4 58 Winnebago, WI............ 3.9 85.6 0.8 200 753 1.6 169 San Juan, PR............. 13.9 316.4 0.6 (8) 511 5.8 (8) 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 322 U.S. counties comprise 70.8 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. 8 This county was not included in the U.S. rankings. Table 2. Covered(1) establishments, employment, and wages in the ten largest counties, first quarter 2005(2) Employment Average weekly wage(4) Establishments, first quarter County by NAICS supersector 2005 Percent Percent (thousands) March change, Average change, 2005 March weekly first (thousands) 2004-05(3) wage quarter 2004-05(3) United States(5)............................. 8,543.2 129,802.3 1.7 $775 2.2 Private industry........................... 8,267.3 108,445.3 1.9 777 2.5 Natural resources and mining............. 122.8 1,586.6 2.3 781 8.0 Construction............................. 834.9 6,782.2 4.1 750 2.5 Manufacturing............................ 368.2 14,153.4 -0.2 940 2.6 Trade, transportation, and utilities..... 1,865.7 25,176.2 1.5 657 1.7 Information.............................. 142.4 3,036.8 -2.5 1,245 1.5 Financial activities..................... 803.4 7,921.1 1.4 1,479 4.6 Professional and business services....... 1,359.5 16,499.3 3.7 938 3.3 Education and health services............ 759.1 16,348.2 2.1 665 1.4 Leisure and hospitality.................. 686.2 12,308.8 2.3 313 0.6 Other services........................... 1,102.7 4,280.6 0.4 474 1.3 Government................................. 276.0 21,357.0 0.7 767 1.2 Los Angeles, CA.............................. 373.9 4,051.2 -0.1 864 2.0 Private industry........................... 370.0 3,464.6 0.0 848 2.7 Natural resources and mining............. 0.6 11.6 1.6 1,115 -19.7 Construction............................. 13.4 142.2 4.7 808 3.3 Manufacturing............................ 16.6 467.1 -4.3 895 4.2 Trade, transportation, and utilities..... 53.4 778.4 1.3 712 2.7 Information.............................. 8.8 199.4 -9.3 1,562 6.5 Financial activities..................... 23.3 239.3 0.5 1,559 5.3 Professional and business services....... 40.4 565.8 1.9 983 4.2 Education and health services............ 27.3 459.0 -0.7 729 2.0 Leisure and hospitality.................. 25.9 370.9 2.1 452 -3.2 Other services........................... 160.0 229.8 3.0 395 1.3 Government................................. 3.9 586.6 -0.2 965 -0.2 Cook, IL..................................... 128.4 2,466.4 -0.1 983 2.8 Private industry........................... 127.2 2,147.6 0.1 992 3.0 Natural resources and mining............. 0.1 1.2 -0.1 971 0.7 Construction............................. 10.7 85.4 -2.3 1,135 5.0 Manufacturing............................ 7.5 253.2 -1.4 962 6.1 Trade, transportation, and utilities..... 26.8 468.0 -0.2 746 2.9 Information.............................. 2.5 60.8 -2.2 1,495 4.0 Financial activities..................... 14.3 214.1 -0.5 2,150 2.0 Professional and business services....... 26.3 403.4 2.1 1,241 3.1 Education and health services............ 12.7 353.5 1.2 713 1.7 Leisure and hospitality.................. 10.7 209.2 -1.1 358 1.4 Other services........................... 12.8 93.7 -2.2 627 2.3 Government................................. 1.2 318.7 -0.9 921 1.1 New York, NY................................. 113.4 2,221.5 0.8 2,025 5.8 Private industry........................... 113.2 1,776.9 1.1 2,303 6.8 Natural resources and mining............. 0.0 0.1 7.1 2,002 14.4 Construction............................. 2.1 28.4 0.7 1,327 3.2 Manufacturing............................ 3.2 43.2 -6.4 1,437 25.7 Trade, transportation, and utilities..... 21.7 232.0 1.1 1,072 2.5 Information.............................. 4.1 127.1 -0.1 2,238 5.2 Financial activities..................... 17.0 348.7 0.0 6,199 9.3 Professional and business services....... 22.5 438.7 1.3 1,907 6.5 Education and health services............ 8.0 276.2 1.1 884 3.9 Leisure and hospitality.................. 10.3 190.1 1.8 678 1.0 Other services........................... 16.2 82.5 0.5 855 5.9 Government................................. 0.2 444.6 -0.3 922 -4.9 Harris, TX................................... 89.9 1,840.9 1.7 950 5.8 Private industry........................... 89.4 1,594.4 1.9 978 6.2 Natural resources and mining............. 1.3 65.1 5.9 3,004 17.4 Construction............................. 6.2 132.0 -0.2 837 1.9 Manufacturing............................ 4.5 164.2 1.4 1,270 12.1 Trade, transportation, and utilities..... 20.9 385.5 0.8 870 2.7 Information.............................. 1.3 31.8 -4.6 1,174 4.1 Financial activities..................... 9.8 114.7 1.6 1,318 4.0 Professional and business services....... 17.3 291.6 5.1 1,019 5.9 Education and health services............ 9.2 192.1 2.1 720 -1.9 Leisure and hospitality.................. 6.7 158.9 0.9 339 4.0 Other services........................... 10.4 54.5 -1.9 520 0.0 Government................................. 0.5 246.5 0.1 768 1.9 Maricopa, AZ................................. 81.2 1,685.4 5.3 746 1.5 Private industry........................... 80.6 1,476.6 5.8 747 1.4 Natural resources and mining............. 0.5 9.0 2.6 574 2.3 Construction............................. 8.4 152.6 15.1 724 2.0 Manufacturing............................ 3.2 130.5 1.9 1,116 4.4 Trade, transportation, and utilities..... 18.4 342.6 5.1 720 0.0 Information.............................. 1.4 32.3 -7.2 967 5.5 Financial activities..................... 9.9 142.7 6.3 1,058 7.5 Professional and business services....... 17.8 280.2 7.5 717 -3.5 Education and health services............ 8.0 172.5 5.7 748 1.1 Leisure and hospitality.................. 5.8 165.6 2.6 346 -1.7 Other services........................... 5.6 45.9 0.8 494 2.7 Government................................. 0.6 208.9 2.2 736 2.9 Orange, CA................................... 91.4 1,477.6 2.3 893 2.2 Private industry........................... 90.0 1,325.4 2.4 881 2.2 Natural resources and mining............. 0.2 6.7 -11.7 541 0.4 Construction............................. 6.7 94.2 3.2 915 4.0 Manufacturing............................ 5.8 183.8 0.7 1,023 0.3 Trade, transportation, and utilities..... 17.3 267.0 1.4 816 -1.2 Information.............................. 1.4 32.7 -1.6 1,256 1.0 Financial activities..................... 10.3 139.0 4.9 1,549 7.9 Professional and business services....... 17.8 261.2 5.6 897 1.1 Education and health services............ 9.4 130.9 1.4 769 3.9 Leisure and hospitality.................. 6.8 161.8 1.0 343 -1.2 Other services........................... 14.1 47.4 2.0 507 0.8 Government................................. 1.4 152.1 1.0 996 1.3 Dallas, TX................................... 65.9 1,402.1 1.0 954 1.5 Private industry........................... 65.4 1,243.2 1.0 972 1.4 Natural resources and mining............. 0.5 6.9 2.0 2,614 8.2 Construction............................. 4.3 74.2 3.9 833 5.8 Manufacturing............................ 3.3 143.3 0.5 1,172 6.9 Trade, transportation, and utilities..... 14.9 298.3 1.0 874 0.8 Information.............................. 1.7 54.1 -5.1 1,369 -6.1 Financial activities..................... 8.4 133.7 1.2 1,496 4.8 Professional and business services....... 13.6 237.4 1.0 1,017 -0.1 Education and health services............ 6.1 130.7 0.7 801 -1.5 Leisure and hospitality.................. 4.9 121.8 1.1 437 -5.6 Other services........................... 6.5 40.1 -0.8 569 1.6 Government................................. 0.5 158.9 1.4 809 2.1 San Diego, CA................................ 88.4 1,282.1 1.2 816 1.4 Private industry........................... 87.0 1,062.6 1.4 806 2.0 Natural resources and mining............. 0.8 11.1 -4.8 465 2.0 Construction............................. 6.8 88.8 3.6 811 2.0 Manufacturing............................ 3.5 104.3 0.6 1,095 1.4 Trade, transportation, and utilities..... 14.2 212.6 1.3 673 3.9 Information.............................. 1.3 37.4 2.9 1,633 -6.0 Financial activities..................... 9.2 82.0 0.1 1,224 5.2 Professional and business services....... 15.1 207.7 1.8 954 1.6 Education and health services............ 7.8 120.8 -0.8 711 2.9 Leisure and hospitality.................. 6.6 143.3 2.2 356 3.2 Other services........................... 21.5 54.2 3.0 433 -0.9 Government................................. 1.4 219.5 0.2 867 -1.1 King, WA..................................... 73.3 1,093.0 1.7 948 2.9 Private industry........................... 72.7 939.9 2.0 957 2.9 Natural resources and mining............. 0.4 3.3 4.2 1,269 6.5 Construction............................. 6.2 55.8 3.6 889 2.4 Manufacturing............................ 2.6 103.8 2.6 1,214 7.1 Trade, transportation, and utilities..... 14.5 213.7 1.7 832 2.3 Information.............................. 1.6 68.7 1.2 1,666 1.6 Financial activities..................... 6.3 74.2 -1.0 1,370 3.8 Professional and business services....... 11.9 162.4 4.9 1,109 -1.6 Education and health services............ 6.1 113.2 3.4 708 2.9 Leisure and hospitality.................. 5.5 99.7 0.5 426 8.7 Other services........................... 17.8 45.0 -3.6 490 5.8 Government................................. 0.5 153.1 -0.2 892 3.4 Miami-Dade, FL............................... 83.6 994.9 1.9 748 2.9 Private industry........................... 83.3 841.3 2.2 726 2.1 Natural resources and mining............. 0.5 11.1 -2.6 380 4.1 Construction............................. 5.3 43.6 9.1 759 7.2 Manufacturing............................ 2.7 49.3 -4.0 688 3.6 Trade, transportation, and utilities..... 24.0 241.5 1.2 688 3.0 Information.............................. 1.8 23.6 (6) 1,155 (6) Financial activities..................... 9.1 68.0 3.4 1,207 0.8 Professional and business services....... 16.5 141.7 7.1 829 1.7 Education and health services............ 8.2 124.9 0.9 704 -2.6 Leisure and hospitality.................. 5.6 98.5 1.5 420 4.7 Other services........................... 7.6 34.7 -0.1 439 1.6 Government................................. 0.3 153.6 0.3 867 6.1 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, first quarter 2005(2) Employment Average weekly wage(5) Establishments, first quarter County(3) 2005 Percent Percent (thousands) March change, Average change, 2005 March weekly first (thousands) 2004-05(4) wage quarter 2004-05(4) United States(6)......... 8,543.2 129,802.3 1.7 $775 2.2 Jefferson, AL............ 18.7 366.3 -0.6 788 2.6 Anchorage Borough, AK.... 7.8 139.6 1.2 793 1.5 Maricopa, AZ............. 81.2 1,685.4 5.3 746 1.5 Pulaski, AR.............. 13.4 241.8 1.4 683 2.2 Los Angeles, CA.......... 373.9 4,051.2 -0.1 864 2.0 Denver, CO............... 24.4 418.1 1.0 976 3.8 Hartford, CT............. 24.4 480.1 1.2 1,041 3.4 New Castle, DE........... 19.6 278.6 0.1 1,005 4.9 Washington, DC........... 30.5 661.7 1.1 1,277 4.2 Miami-Dade, FL........... 83.6 994.9 1.9 748 2.9 Fulton, GA............... 37.3 729.7 0.9 1,076 3.0 Honolulu, HI............. 23.6 436.2 3.0 693 1.5 Ada, ID.................. 13.5 192.2 4.5 667 1.7 Cook, IL................. 128.4 2,466.4 -0.1 983 2.8 Marion, IN............... 24.0 575.1 1.4 818 1.0 Polk, IA................. 14.1 259.9 1.9 792 1.5 Johnson, KS.............. 19.0 294.1 1.7 817 0.0 Jefferson, KY............ 21.7 415.8 1.0 742 -1.1 Orleans, LA.............. 12.6 244.5 -1.1 738 2.2 Cumberland, ME........... 11.6 165.1 0.0 707 1.6 Montgomery, MD........... 32.4 452.6 1.6 1,041 2.6 Middlesex, MA............ 48.9 775.9 0.5 1,097 2.2 Wayne, MI................ 34.4 783.3 -1.1 892 0.2 Hennepin, MN............. 40.0 815.7 1.4 999 1.4 Hinds, MS................ 6.5 128.0 -0.8 653 0.9 St. Louis, MO............ 33.9 612.3 0.6 819 0.7 Yellowstone, MT.......... 5.3 71.2 3.4 596 5.1 Douglas, NE.............. 14.9 304.9 0.7 708 -0.6 Clark, NV................ 40.9 844.7 7.6 718 3.5 Hillsborough, NH......... 12.2 192.6 0.7 827 2.6 Bergen, NJ............... 34.2 442.4 0.0 982 1.9 Bernalillo, NM........... 16.6 313.7 1.1 657 1.9 New York, NY............. 113.4 2,221.5 0.8 2,025 5.8 Mecklenburg, NC.......... 27.4 513.7 3.2 1,048 5.8 Cass, ND................. 5.5 88.5 3.2 610 0.8 Cuyahoga, OH............. 38.1 740.8 0.0 813 2.8 Oklahoma, OK............. 22.2 406.2 1.3 657 1.7 Multnomah, OR............ 25.6 424.2 3.1 778 2.2 Allegheny, PA............ 35.7 672.8 -0.8 817 1.4 Providence, RI........... 18.0 281.0 -0.5 764 1.3 Greenville, SC........... 12.4 222.8 1.4 658 0.8 Minnehaha, SD............ 6.0 108.2 2.3 635 3.8 Shelby, TN............... 19.7 494.2 0.7 759 0.3 Harris, TX............... 89.9 1,840.9 1.7 950 5.8 Salt Lake, UT............ 35.4 529.0 3.4 680 1.3 Chittenden, VT........... 5.7 93.4 0.8 766 4.9 Fairfax, VA.............. 30.4 555.9 4.0 1,181 2.1 King, WA................. 73.3 1,093.0 1.7 948 2.9 Kanawha, WV.............. 6.2 106.3 -1.1 660 1.7 Milwaukee, WI............ 21.5 485.6 -0.6 785 1.8 Laramie, WY.............. 2.9 39.5 1.3 601 2.6 San Juan, PR............. 13.9 316.4 0.6 511 5.8 St. Thomas, VI........... 1.7 23.2 -1.1 583 4.3 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, first quarter 2005(2) Employment Average weekly wage(3) Establishments, first quarter State 2005 Percent Percent (thousands) March change, Average change, 2005 March weekly first (thousands) 2004-05 wage quarter 2004-05 United States(4)......... 8,543.2 129,802.3 1.7 $775 2.2 Alabama.................. 116.0 1,871.5 2.0 642 2.6 Alaska................... 20.3 290.3 2.0 744 1.5 Arizona.................. 129.3 2,459.7 5.0 698 2.3 Arkansas................. 77.5 1,144.8 1.7 579 2.8 California............... 1,247.9 15,064.5 1.9 872 2.0 Colorado................. 166.7 2,158.6 2.4 787 2.2 Connecticut.............. 109.8 1,624.7 0.8 1,084 3.9 Delaware................. 29.7 407.9 1.2 878 4.0 District of Columbia..... 30.5 661.7 1.1 1,277 4.2 Florida.................. 547.0 7,731.0 3.5 679 3.5 Georgia.................. 252.9 3,877.0 1.5 742 1.9 Hawaii................... 36.1 597.6 3.1 669 2.0 Idaho.................... 50.9 594.2 4.2 561 1.6 Illinois................. 333.4 5,644.9 0.5 848 2.9 Indiana.................. 155.3 2,838.7 1.1 667 0.9 Iowa..................... 91.5 1,419.5 1.9 616 1.7 Kansas................... 82.9 1,290.7 0.9 631 1.4 Kentucky................. 107.4 1,741.2 1.8 628 0.6 Louisiana................ 118.0 1,873.8 0.6 619 2.8 Maine.................... 48.1 573.2 -0.5 614 1.7 Maryland................. 159.5 2,458.0 1.1 831 2.0 Massachusetts............ 214.7 3,094.8 0.1 964 1.2 Michigan................. 255.8 4,218.3 -0.4 780 1.2 Minnesota................ 156.7 2,559.7 1.3 783 0.8 Mississippi.............. 67.6 1,113.1 1.3 545 2.3 Missouri................. 170.0 2,644.2 1.8 671 0.9 Montana.................. 39.8 403.8 3.2 533 3.5 Nebraska................. 55.8 879.8 1.5 600 0.8 Nevada................... 66.1 1,187.6 6.7 714 2.6 New Hampshire............ 47.3 606.9 0.8 745 2.8 New Jersey............... 269.5 3,863.5 0.8 963 1.8 New Mexico............... 50.6 765.0 2.2 596 2.1 New York................. 558.2 8,242.3 0.8 1,096 3.7 North Carolina........... 233.1 3,808.0 2.3 687 2.7 North Dakota............. 24.5 320.4 2.6 550 1.5 Ohio..................... 290.7 5,228.6 0.4 706 2.0 Oklahoma................. 93.9 1,453.9 2.5 591 1.9 Oregon................... 122.1 1,621.6 4.2 685 1.5 Pennsylvania............. 338.0 5,481.0 1.0 747 1.5 Rhode Island............. 35.4 466.9 0.5 736 1.2 South Carolina........... 116.1 1,800.3 1.5 611 2.5 South Dakota............. 28.9 365.1 2.0 544 2.4 Tennessee................ 131.7 2,665.2 1.8 660 1.4 Texas.................... 517.4 9,454.6 2.2 760 3.1 Utah..................... 78.9 1,091.9 3.9 607 1.3 Vermont.................. 24.4 297.5 0.9 639 3.9 Virginia................. 211.3 3,525.7 2.4 794 2.7 Washington............... 204.2 2,702.3 2.6 766 2.4 West Virginia............ 47.6 683.6 1.1 583 2.5 Wisconsin................ 159.5 2,687.0 1.4 668 1.7 Wyoming.................. 22.8 246.2 3.0 606 3.9 Puerto Rico.............. 55.5 1,048.2 1.4 433 3.3 Virgin Islands........... 3.4 44.2 2.1 650 13.4 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.