An official website of the United States government
For release 10:00 a.m. (EST), Tuesday, January 11, 2011 USDL-11-0014 Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew Media Contact: (202) 691-5902 * PressOffice@bls.gov County Employment and Wages Second Quarter 2010 From June 2009 to June 2010, employment declined in 192 of the 326 largest U.S. counties according to preliminary data, the U.S. Bureau of Labor Statistics reported today. Yolo, Calif., and Marion, Fla., posted the largest percentage decline, with a loss of 3.7 percent each over the year, compared with a national job decrease of 0.2 percent. Within Yolo, the largest employment decline occurred in trade, transportation, and utilities, which lost 843 jobs over the year (-4.4 percent). In Marion, financial activities had the largest over-the-year decrease in employment, shedding 1,495 jobs (-27.1 percent). Elkhart, Ind., experienced the largest over- the-year percentage increase in employment among the largest counties in the U.S. with a gain of 9.3 percent. The U.S. average weekly wage increased over the year by 3.0 percent to $865 in the second quarter of 2010. Among the large counties in the U.S., Santa Clara, Calif., had the largest over-the-year increase in average weekly wages in the second quarter of 2010, with a gain of 10.6 percent. Within Santa Clara, manufacturing had the largest impact on the county’s over-the-year increase in average weekly wages. Fort Bend, Texas, experienced the largest decline in average weekly wages with a loss of 1.7 percent over the year. County employment and wage data are compiled under the Quarterly Census of Employment and Wages (QCEW) program. Table A. Top 10 large counties ranked by June 2010 employment, June 2009-10 employment decrease, and June 2009-10 percent decrease in employment -------------------------------------------------------------------------------------------------------- Employment in large counties -------------------------------------------------------------------------------------------------------- June 2010 employment | Decrease in employment, | Percent decrease in employment, (thousands) | June 2009-10 | June 2009-10 | (thousands) | -------------------------------------------------------------------------------------------------------- | | United States 129,371.6| United States -276.5| United States -0.2 -------------------------------------------------------------------------------------------------------- | | Los Angeles, Calif. 3,890.5| Los Angeles, Calif. -62.3| Yolo, Calif. -3.7 Cook, Ill. 2,371.7| Maricopa, Ariz. -24.3| Marion, Fla. -3.7 New York, N.Y. 2,291.3| Cook, Ill. -22.7| Kane, Ill. -2.9 Harris, Texas 1,996.5| Clark, Nev. -17.5| McHenry, Ill. -2.9 Maricopa, Ariz. 1,565.2| Sacramento, Calif. -15.7| San Joaquin, Calif. -2.7 Dallas, Texas 1,415.2| Orange, Calif. -15.1| Sacramento, Calif. -2.6 Orange, Calif. 1,369.7| San Bernardino, Calif. -14.0| Durham, N.C. -2.6 San Diego, Calif. 1,253.3| Riverside, Calif. -12.8| Sedgwick, Kan. -2.5 King, Wash. 1,125.9| St. Louis, Mo. -12.3| St. Louis City, Mo. -2.5 Miami-Dade, Fla. 932.4| Alameda, Calif. -10.6| Gloucester, N.J. -2.4 | | Spokane, Wash. -2.4 | | -------------------------------------------------------------------------------------------------------- Large County Employment In June 2010, national employment, as measured by the QCEW program, was 129.4 million, down by 0.2 percent from June 2009. The 326 U.S. counties with 75,000 or more employees accounted for 70.7 percent of total U.S. employment and 71.5 percent of total wages. These 326 counties had a net job decline of 350,897 over the year, accounting for 126.9 percent of the overall U.S. employment decrease. Yolo, Calif., and Marion, Fla., both had the largest percentage decline in employment among the largest U.S. counties. The top five counties with the greatest employment level declines (Los Angeles, Calif.; Maricopa, Ariz.; Cook, Ill.; Clark, Nev.; and Sacramento, Calif.) had a combined over-the-year loss of 142,500, or 51.1 percent of the employment decline for the U.S. (See table A.) Employment rose in 120 of the large counties from June 2009 to June 2010. Elkhart, Ind., had the largest over-the-year percentage increase in employment (9.3 percent) in the nation. Manufacturing was the largest contributor to the increase in employment. In Elkhart, employment declines exceeded 10 percent from third quarter of 2008 through third quarter of 2009. Employment rebounded in December 2009, and strong job growth continued through this quarter. Kings, N.Y., experienced the second largest employment increase, followed by Allen, Ind.; Ottawa, Mich.; Macomb, Mich.; Arlington, Va.; and Benton, Wash. Table B. Top 10 large counties ranked by second quarter 2010 average weekly wages, second quarter 2009-10 increase in average weekly wages, and second quarter 2009-10 percent increase in average weekly wages -------------------------------------------------------------------------------------------------------- Average weekly wage in large counties -------------------------------------------------------------------------------------------------------- Average weekly wage, | Increase in average weekly | Percent increase in average second quarter 2010 | wage, second quarter 2009-10 | weekly wage, second | | quarter 2009-10 -------------------------------------------------------------------------------------------------------- | | United States $865| United States $25| United States 3.0 -------------------------------------------------------------------------------------------------------- | | New York, N.Y. $1,659| Santa Clara, Calif. $153| Santa Clara, Calif. 10.6 Santa Clara, Calif. 1,603| New York, N.Y. 137| New York, N.Y. 9.0 Washington, D.C. 1,506| Washington, D.C. 81| Elkhart, Ind. 7.6 Arlington, Va. 1,481| Fairfield, Conn. 79| Lake, Ind. 6.9 Fairfield, Conn. 1,395| Alexandria City, Va. 73| Rockingham, N.H. 6.4 Fairfax, Va. 1,392| Middlesex, Mass. 62| Alexandria City, Va. 6.3 San Francisco, Calif. 1,346| Durham, N.C. 61| Douglas, Colo. 6.2 Suffolk, Mass. 1,334| Arlington, Va. 59| Fairfield, Conn. 6.0 San Mateo, Calif. 1,329| Washington, Ore. 54| Champaign, Ill. 5.9 Somerset, N.J. 1,277| Douglas, Colo. 53| Butler, Pa. 5.8 | | -------------------------------------------------------------------------------------------------------- Large County Average Weekly Wages Average weekly wages for the nation increased by 3.0 percent over the year in the second quarter of 2010. Among the 326 largest counties, 301 had over-the-year increases in average weekly wages. Santa Clara, Calif., had the largest wage gain among the largest U.S. counties. (See table B.) Of the 326 largest counties, 16 experienced declines in average weekly wages. Fort Bend, Texas, led the nation in average weekly wage decline with a loss of 1.7 percent over the year. Large declines in employment (-10.0 percent) and wages (-14.0 percent) within construction had contributed significantly to the county’s overall average weekly wage loss. Baltimore City, Md., had the second largest overall decline among the counties, followed by St. Charles, Mo.; Anoka, Minn.; and Calcasieu, La. Ten Largest U.S. Counties Eight of the 10 largest counties experienced over-the-year percent declines in employment in June 2010. Los Angeles, Calif., experienced the largest decline in employment among the 10 largest counties with a 1.6 percent decrease. Within Los Angeles, other services had the largest over-the-year decline among all private industry groups with a loss of 20,933 workers (-8.0 percent). (See table 2.) New York, N.Y., experienced the largest increase in employment among the 10 largest counties. All of the 10 largest U.S. counties saw an over-the-year increase in average weekly wages. New York, N.Y., experienced the largest increase in average weekly wages among the 10 largest counties and the nation with a gain of 9.0 percent. Orange, Calif., had the smallest wage increase among the 10 largest counties. For More Information The tables included in this release contain data for the nation and for the 326 U.S. counties with annual average employment levels of 75,000 or more in 2009. June 2010 employment and 2010 second quarter average weekly wages for all states are provided in table 3 of this release. The employment and wage data by county are compiled under the 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 9.0 million employer reports cover 129.4 million full- and part- time workers. For additional information about the quarterly employment and wages data, please read the Technical Note. Data for the second quarter of 2010 will be available later at http://www.bls.gov/cew/. Additional information about the QCEW data may be obtained by calling (202) 691- 6567. Several BLS regional offices are issuing QCEW news releases targeted to local data users. For links to these releases, see http://www.bls.gov/cew/cewregional.htm. _____________ The County Employment and Wages release for third quarter 2010 is scheduled to be released on Tuesday, March 29, 2011.
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 total 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. QCEW data in this release are based on the 2007 North American Industry Classification System. Data for 2010 are preliminary and subject to revision. For purposes of this release, large counties are defined as having employment le- vels of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are pro- vided, but not used in calculating U.S. averages, rankings, or in the analysis in the text. Each year, these large counties are selected on the basis of the prelimi- nary annual average of employment for the previous year. The 327 counties presented in this release were derived using 2009 preliminary annual averages of employment. For 2010 data, two counties have been added to the publication tables: St. Tammany Parish, La., and Benton, Wash. These counties will be included in all 2010 quarter- ly releases. Ten counties, Shelby, Ala.; Butte, Calif.; Tippecanoe, Ind.; Johnson, Iowa; Saratoga, N.Y.; Trumbull, Ohio; Warren, Ohio; Kent, R.I.; Gregg, Texas; and Racine, Wis., which were published in the 2009 releases, will be excluded from this and future 2010 releases because their 2009 annual average employment levels were less than 75,000. 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' con- tinuing 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 procedure, and publication product. Differences in coverage and estimation methods can result in somewhat different measures of employment change over time. It is important to understand program dif- ferences and the intended uses of the program products. (See table.) Additional in- formation on each program can be obtained from the program Web sites shown in the table. 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 9.0 | ministrative records| ments | million establish- | submitted by 6.7 | | ments in first | million private-sec-| | quarter of 2010 | 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 fed- | establishments with | ing agriculture, pri- | eral 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 | by NAICS supersec- | | industry | tors and by size of | | | firm, and at the | | | state private-sector| | | total level | | |--Future expansions | | | will include data | | | with greater indus- | | | try detail and data | | | at the county and | | | MSA level | -----------|---------------------|----------------------|------------------------ 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 | -Analysis of employ-| cators | surveys | ment expansion and | | | contraction by size| | | of firm | | | | -----------|---------------------|----------------------|------------------------ Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/ Web sites | | | --------------------------------------------------------------------------------- Coverage Employment and wage data for workers covered by state UI laws are compiled from quarterly contribution reports submitted to the SWAs by employers. For federal ci- vilian workers covered by the Unemployment Compensation for Federal Employees (UCFE) program, employment and wage data are compiled from quarterly reports sub- mitted by four major federal payroll processing centers on behalf of all federal agencies, with the exception of a few agencies which still report directly to the individual SWA. 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. QCEW employment and wage data are derived from microdata summaries of 9.0 million employer reports of employment and wages submitted by states to the BLS in 2009. These reports are based on place of employ- ment rather than place of residence. UI and UCFE coverage is broad and has been basically comparable from state to state since 1978, when the 1976 amendments to the Federal Unemployment Tax Act became ef- fective, expanding coverage to include most State and local government employees. In 2009, UI and UCFE programs covered workers in 128.6 million jobs. The estimated 123.6 million workers in these jobs (after adjustment for multiple jobholders) represented 95.1 percent of civilian wage and salary employment. Covered workers received $5.859 trillion in pay, representing 93.4 percent of the wage and salary component of personal income and 41.5 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 domestic 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. Cover- age changes may affect the over-the-year comparisons presented in this news re- lease. 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 production 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 av- erages 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 compen- sation plans such as 401(k) plans and stock options. Over-the-year comparisons of average weekly wages may reflect fluctuations in average monthly employment and/or total quarterly wages between the current quarter and prior year levels. 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. For instance, the average weekly wage of the work force could increase significantly when there is a large decline in the number of employees that had been receiving below-average wages. Wages may include payments to workers not present in the employment counts because they did not work during the pay period including the 12th of the month. When comparing average week- ly wage levels between industries, states, or quarters, these factors should be taken into consideration. Federal government pay levels are subject to periodic, sometimes large, fluctua- tions due to a calendar effect that consists of some quarters having more pay pe- riods than others. Most federal employees are paid on a biweekly 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 pe- riods. 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 com- parison 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 oc- cur 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 employ- ers and update, if necessary, the industry, location, and ownership classification of all establishments on a 4-year cycle. Changes in establishment classification codes resulting from this process are introduced 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 indi- vidual 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 un- derlying establishment reports. This is done by modifying the prior-year levels used to calculate the over-the-year changes. Percent changes are calculated using an adjusted version of the final 2009 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 un- adjusted 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 re- lease. 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 estab- lishments. The most common adjustments for administrative change are the result of updated information about the county location of individual establishments. In- cluded in these adjustments are administrative changes involving the classification of establishments that were previously reported in the unknown or statewide county or unknown industry categories. Beginning with the first quarter of 2008, adjusted data account for administrative changes caused by multi-unit employers who start reporting for each individual establishment rather than as a single entity. 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 Stan- dards 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 referred to in this release are defined as census regions. Additional statistics and other information An annual bulletin, Employment and Wages, features comprehensive information by de- tailed industry on establishments, employment, and wages for the nation and all states. The 2008 edition of this bulletin contains selected data produced by Busi- ness Employment Dynamics (BED) on job gains and losses, as well as selected data from the first quarter 2009 version of this news release. Tables and additional content from the 2008 Employment and Wages Annual Bulletin are now available online at http://www.bls.gov/cew/cewbultn08.htm. These tables present final 2008 annual averages. The tables are included on the CD which accompanies the hardcopy version of the Annual Bulletin. Employment and Wages Annual Averages, 2008 is available for sale as a chartbook from the United States Government Printing Office, Superin- tendent of Documents, P.O. Box 371954, Pittsburgh, PA 15250, telephone (866) 512- 1800, outside Washington, D.C. Within Washington, D.C., the telephone number is (202) 512-1800. The fax number is (202) 512-2104. News releases on quarterly measures of gross job flows also are available upon re- quest 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 327 largest counties, second quarter 2010(2) Employment Average weekly wage(4) Establishments, County(3) second quarter Percent Ranking Percent Ranking 2010 June change, by Average change, by (thousands) 2010 June percent weekly second percent (thousands) 2009-10(5) change wage quarter change 2009-10(5) United States(6)......... 9,009.6 129,371.6 -0.2 - $865 3.0 - Jefferson, AL............ 17.9 332.8 -1.5 262 864 2.4 160 Madison, AL.............. 8.7 180.7 0.5 82 966 3.0 110 Mobile, AL............... 9.9 168.5 1.9 17 747 1.4 250 Montgomery, AL........... 6.4 132.1 -1.7 275 759 3.7 63 Tuscaloosa, AL........... 4.3 81.2 2.8 10 742 2.6 147 Anchorage Borough, AK.... 8.1 150.1 0.7 72 971 2.1 195 Maricopa, AZ............. 94.6 1,565.2 -1.5 262 860 1.7 226 Pima, AZ................. 19.4 338.9 (7) - 765 1.9 204 Benton, AR............... 5.4 92.8 0.6 76 839 4.5 27 Pulaski, AR.............. 15.1 245.6 0.3 95 779 -0.1 302 Washington, AR........... 5.6 91.1 (7) - 725 (7) - Alameda, CA.............. 54.3 635.1 -1.6 267 1,148 4.4 29 Contra Costa, CA......... 29.3 319.3 -2.0 285 1,061 -0.8 308 Fresno, CA............... 29.8 343.7 -0.6 167 697 1.3 252 Kern, CA................. 17.6 277.7 1.9 17 773 1.2 261 Los Angeles, CA.......... 422.4 3,890.5 -1.6 267 968 3.1 103 Marin, CA................ 11.7 102.9 0.1 112 1,059 2.9 115 Monterey, CA............. 12.7 187.1 2.3 12 741 -0.8 308 Orange, CA............... 101.7 1,369.7 -1.1 225 965 1.5 242 Placer, CA............... 10.6 126.0 -1.4 252 841 2.1 195 Riverside, CA............ 47.5 563.0 -2.2 296 729 1.7 226 Sacramento, CA........... 53.0 589.6 -2.6 310 980 3.6 70 San Bernardino, CA....... 49.2 597.3 -2.3 301 762 2.6 147 San Diego, CA............ 97.5 1,253.3 -0.5 158 934 2.3 172 San Francisco, CA........ 53.1 545.9 -0.9 202 1,346 3.2 95 San Joaquin, CA.......... 16.9 216.5 -2.7 312 752 1.8 214 San Luis Obispo, CA...... 9.5 102.0 0.6 76 731 0.8 279 San Mateo, CA............ 23.7 320.1 -0.3 144 1,329 1.5 242 Santa Barbara, CA........ 14.3 184.2 -1.0 216 818 1.1 265 Santa Clara, CA.......... 60.6 849.5 -0.5 158 1,603 10.6 1 Santa Cruz, CA........... 9.0 98.5 -2.0 285 761 1.2 261 Solano, CA............... 9.9 123.8 0.4 91 860 0.2 298 Sonoma, CA............... 18.5 176.9 -1.6 267 817 0.6 287 Stanislaus, CA........... 14.7 166.2 -0.9 202 744 2.1 195 Tulare, CA............... 9.3 151.8 -1.0 216 606 1.3 252 Ventura, CA.............. 23.6 302.7 -1.4 252 897 1.7 226 Yolo, CA................. 5.9 96.1 -3.7 315 816 -0.9 310 Adams, CO................ 9.0 151.2 -1.2 234 785 2.7 138 Arapahoe, CO............. 18.9 273.6 -0.9 202 980 1.0 269 Boulder, CO.............. 12.9 153.6 0.3 95 1,007 4.0 46 Denver, CO............... 25.3 421.7 -0.2 132 1,033 2.4 160 Douglas, CO.............. 9.4 92.1 -0.7 182 906 6.2 7 El Paso, CO.............. 16.8 235.2 -0.8 196 800 1.7 226 Jefferson, CO............ 18.0 205.9 -0.6 167 882 2.9 115 Larimer, CO.............. 10.1 129.5 0.4 91 742 2.5 154 Weld, CO................. 5.8 79.0 -0.9 202 712 3.8 53 Fairfield, CT............ 32.7 403.7 -0.2 132 1,395 6.0 8 Hartford, CT............. 25.2 487.9 -1.0 216 1,058 4.2 40 New Haven, CT............ 22.3 350.2 -0.8 196 926 2.4 160 New London, CT........... 6.9 126.3 -1.4 252 895 1.6 235 New Castle, DE........... 17.6 262.9 -1.9 283 985 2.6 147 Washington, DC........... 34.2 701.4 2.3 12 1,506 5.7 11 Alachua, FL.............. 6.7 115.4 -0.6 167 738 3.7 63 Brevard, FL.............. 14.7 189.9 -0.7 182 833 1.6 235 Broward, FL.............. 63.3 678.6 -1.2 234 816 1.5 242 Collier, FL.............. 11.9 104.7 -0.3 144 789 2.7 138 Duval, FL................ 26.8 430.4 -0.7 182 834 2.2 182 Escambia, FL............. 7.9 119.1 1.1 46 695 1.2 261 Hillsborough, FL......... 37.1 558.1 -1.2 234 840 2.3 172 Lake, FL................. 7.3 74.7 -2.3 301 616 1.0 269 Lee, FL.................. 18.9 186.9 -1.2 234 727 1.0 269 Leon, FL................. 8.2 136.1 -1.1 225 732 1.1 265 Manatee, FL.............. 9.1 105.5 -1.5 262 679 1.8 214 Marion, FL............... 8.1 88.9 -3.7 315 648 3.8 53 Miami-Dade, FL........... 85.9 932.4 -0.2 132 850 1.9 204 Okaloosa, FL............. 6.1 75.1 -1.7 275 741 1.8 214 Orange, FL............... 35.4 642.2 0.5 82 776 1.3 252 Palm Beach, FL........... 49.2 485.8 -0.8 196 858 2.5 154 Pasco, FL................ 9.9 89.1 -0.6 167 666 (7) - Pinellas, FL............. 30.7 382.5 -1.6 267 766 3.4 85 Polk, FL................. 12.4 184.5 -1.8 278 674 1.5 242 Sarasota, FL............. 14.6 130.2 -0.9 202 728 0.1 299 Seminole, FL............. 14.1 155.7 -2.2 296 739 0.8 279 Volusia, FL.............. 13.5 145.1 -2.2 296 651 2.4 160 Bibb, GA................. 4.6 79.4 -1.3 243 679 2.1 195 Chatham, GA.............. 7.6 128.1 -1.1 225 747 2.8 126 Clayton, GA.............. 4.3 102.2 (7) - 773 (7) - Cobb, GA................. 20.5 287.0 -0.7 182 894 2.4 160 De Kalb, GA.............. 17.5 275.7 -1.3 243 899 0.7 284 Fulton, GA............... 39.4 700.8 -0.7 182 1,122 2.6 147 Gwinnett, GA............. 23.4 295.7 -0.9 202 853 3.5 78 Muscogee, GA............. 4.7 93.1 (7) - 690 2.4 160 Richmond, GA............. 4.7 97.1 -1.0 216 736 1.8 214 Honolulu, HI............. 24.8 428.2 -1.7 275 809 1.0 269 Ada, ID.................. 14.2 193.6 -0.9 202 755 2.7 138 Champaign, IL............ 4.2 88.9 0.3 95 785 5.9 9 Cook, IL................. 142.8 2,371.7 -0.9 202 1,012 2.4 160 Du Page, IL.............. 36.3 552.9 -0.1 125 988 2.7 138 Kane, IL................. 13.0 193.9 -2.9 313 776 2.9 115 Lake, IL................. 21.4 317.8 -1.4 252 1,081 3.6 70 McHenry, IL.............. 8.5 95.7 -2.9 313 733 3.8 53 McLean, IL............... 3.8 86.0 0.8 67 855 2.9 115 Madison, IL.............. 6.0 93.5 1.8 22 724 4.2 40 Peoria, IL............... 4.7 99.9 0.5 82 804 2.7 138 Rock Island, IL.......... 3.5 74.2 -2.3 301 845 2.8 126 St. Clair, IL............ 5.5 93.2 -1.8 278 728 1.5 242 Sangamon, IL............. 5.3 128.1 -0.1 125 886 2.8 126 Will, IL................. 14.4 197.4 0.1 112 781 4.3 34 Winnebago, IL............ 6.9 124.5 -1.3 243 732 3.7 63 Allen, IN................ 8.9 172.2 3.5 3 732 4.3 34 Elkhart, IN.............. 4.8 102.3 9.3 1 737 7.6 3 Hamilton, IN............. 7.9 109.1 -0.5 158 816 3.2 95 Lake, IN................. 10.3 184.3 -0.7 182 771 6.9 4 Marion, IN............... 23.6 547.7 0.5 82 870 2.2 182 St. Joseph, IN........... 6.0 114.0 -0.3 144 721 1.3 252 Vanderburgh, IN.......... 4.8 104.7 1.0 53 731 3.8 53 Linn, IA................. 6.3 124.8 -0.6 167 829 4.5 27 Polk, IA................. 14.7 268.5 -1.6 267 850 3.2 95 Scott, IA................ 5.3 86.0 0.6 76 688 3.0 110 Johnson, KS.............. 20.9 297.8 -2.0 285 889 2.2 182 Sedgwick, KS............. 12.5 241.4 -2.5 308 791 0.1 299 Shawnee, KS.............. 4.9 94.7 -0.6 167 757 3.1 103 Wyandotte, KS............ 3.2 81.2 2.6 11 831 2.2 182 Fayette, KY.............. 9.5 172.3 1.0 53 798 1.8 214 Jefferson, KY............ 22.4 413.0 -0.2 132 852 3.4 85 Caddo, LA................ 7.6 123.6 1.6 30 743 3.2 95 Calcasieu, LA............ 5.1 83.8 -2.0 285 715 -1.0 313 East Baton Rouge, LA..... 15.0 252.3 -1.4 252 803 -0.4 305 Jefferson, LA............ 14.4 194.6 -0.4 151 803 2.8 126 Lafayette, LA............ 9.3 131.6 0.3 95 819 3.7 63 Orleans, LA.............. 11.0 170.8 0.9 61 920 0.9 275 St. Tammany, LA.......... 7.6 75.8 (7) - 731 (7) - Cumberland, ME........... 12.2 169.0 -1.1 225 779 3.2 95 Anne Arundel, MD......... 14.3 230.8 0.3 95 946 (7) - Baltimore, MD............ 21.1 368.0 -0.4 151 894 2.4 160 Frederick, MD............ 5.9 93.3 -0.4 151 851 2.9 115 Harford, MD.............. 5.6 82.3 1.2 42 816 3.2 95 Howard, MD............... 8.7 149.7 1.4 34 1,027 1.7 226 Montgomery, MD........... 32.3 448.3 -0.1 125 1,173 3.8 53 Prince Georges, MD....... 15.5 303.3 -1.6 267 959 2.9 115 Baltimore City, MD....... 13.5 328.7 -0.5 158 999 -1.6 316 Barnstable, MA........... 9.2 96.7 -1.2 234 738 1.5 242 Bristol, MA.............. 15.9 210.7 -0.2 132 796 2.4 160 Essex, MA................ 21.2 300.2 1.2 42 923 3.6 70 Hampden, MA.............. 14.8 196.2 0.5 82 779 0.3 292 Middlesex, MA............ 48.4 812.4 0.5 82 1,252 5.2 17 Norfolk, MA.............. 24.0 317.0 0.5 82 1,022 3.0 110 Plymouth, MA............. 14.0 174.0 -0.7 182 850 1.0 269 Suffolk, MA.............. 22.6 574.4 0.6 76 1,334 1.8 214 Worcester, MA............ 21.0 313.5 0.4 91 886 3.1 103 Genesee, MI.............. 7.5 127.8 0.7 72 728 1.1 265 Ingham, MI............... 6.5 154.4 0.9 61 854 3.5 78 Kalamazoo, MI............ 5.4 108.1 -2.0 285 785 2.7 138 Kent, MI................. 14.0 309.9 1.0 53 773 0.8 279 Macomb, MI............... 17.2 280.6 3.0 5 866 2.2 182 Oakland, MI.............. 37.8 618.1 -0.8 196 953 -0.2 304 Ottawa, MI............... 5.6 102.2 3.5 3 712 3.8 53 Saginaw, MI.............. 4.2 79.9 1.8 22 725 0.3 292 Washtenaw, MI............ 8.0 184.1 1.7 25 910 1.6 235 Wayne, MI................ 31.3 665.0 0.9 61 944 2.2 182 Anoka, MN................ 7.4 106.9 -2.3 301 827 -1.1 314 Dakota, MN............... 10.0 171.0 0.2 107 860 1.3 252 Hennepin, MN............. 44.3 812.2 0.3 95 1,073 4.4 29 Olmsted, MN.............. 3.4 88.3 -1.4 252 988 3.6 70 Ramsey, MN............... 14.4 318.0 -0.7 182 957 2.9 115 St. Louis, MN............ 5.7 94.4 0.0 121 725 4.9 22 Stearns, MN.............. 4.4 77.8 -0.5 158 683 4.1 44 Harrison, MS............. 4.5 83.3 -0.2 132 663 -0.6 306 Hinds, MS................ 6.2 123.0 -1.8 278 762 2.6 147 Boone, MO................ 4.4 82.5 1.3 38 682 0.6 287 Clay, MO................. 5.0 91.2 -1.9 283 828 2.3 172 Greene, MO............... 8.0 147.0 -1.3 243 672 0.7 284 Jackson, MO.............. 18.0 342.8 -2.3 301 872 0.7 284 St. Charles, MO.......... 8.1 122.5 0.0 121 708 -1.5 315 St. Louis, MO............ 31.6 569.1 -2.1 294 911 1.9 204 St. Louis City, MO....... 8.7 213.2 -2.5 308 921 (7) - Yellowstone, MT.......... 5.8 76.4 -1.1 225 714 3.6 70 Douglas, NE.............. 15.7 313.6 0.1 112 796 1.8 214 Lancaster, NE............ 8.1 153.5 -0.7 182 702 3.5 78 Clark, NV................ 48.0 804.1 -2.1 294 786 -0.9 310 Washoe, NV............... 13.9 184.5 -2.0 285 800 0.4 290 Hillsborough, NH......... 11.9 185.4 -1.5 262 961 5.4 15 Rockingham, NH........... 10.6 136.3 1.0 53 861 6.4 5 Atlantic, NJ............. 6.9 143.3 1.2 42 769 1.9 204 Bergen, NJ............... 33.9 431.3 -0.9 202 1,050 1.9 204 Burlington, NJ........... 11.2 197.0 -1.8 278 925 3.4 85 Camden, NJ............... 12.8 198.6 -0.5 158 880 2.1 195 Essex, NJ................ 21.1 342.0 -0.7 182 1,083 2.2 182 Gloucester, NJ........... 6.3 99.9 -2.4 306 806 3.7 63 Hudson, NJ............... 13.9 229.7 -1.0 216 1,198 3.6 70 Mercer, NJ............... 11.1 229.7 0.5 82 1,134 3.0 110 Middlesex, NJ............ 21.9 380.8 -0.7 182 1,065 2.2 182 Monmouth, NJ............. 20.4 254.4 -0.9 202 902 1.6 235 Morris, NJ............... 17.7 274.8 -1.4 252 1,230 3.4 85 Ocean, NJ................ 12.3 155.9 0.7 72 720 0.8 279 Passaic, NJ.............. 12.3 172.4 1.9 17 917 1.9 204 Somerset, NJ............. 10.1 170.2 0.1 112 1,277 2.8 126 Union, NJ................ 14.8 222.9 1.0 53 1,101 4.0 46 Bernalillo, NM........... 17.5 313.7 -1.1 225 780 1.8 214 Albany, NY............... 9.9 220.5 -1.1 225 912 0.6 287 Bronx, NY................ 16.8 237.1 1.9 17 842 1.4 250 Broome, NY............... 4.5 92.7 -1.8 278 709 2.6 147 Dutchess, NY............. 8.1 112.4 -0.6 167 916 2.0 202 Erie, NY................. 23.6 453.3 0.3 95 765 2.3 172 Kings, NY................ 49.4 499.6 3.6 2 739 0.4 290 Monroe, NY............... 18.0 373.9 0.2 107 850 2.3 172 Nassau, NY............... 52.3 596.9 -0.2 132 1,010 2.5 154 New York, NY............. 120.6 2,291.3 0.3 95 1,659 9.0 2 Oneida, NY............... 5.3 110.3 0.2 107 695 1.8 214 Onondaga, NY............. 12.8 244.1 -1.0 216 817 3.3 90 Orange, NY............... 10.0 132.2 1.1 46 784 1.3 252 Queens, NY............... 44.8 498.8 1.1 46 837 1.9 204 Richmond, NY............. 8.9 95.0 1.6 30 759 1.6 235 Rockland, NY............. 9.9 115.4 0.1 112 946 2.2 182 Suffolk, NY.............. 50.3 625.9 0.5 82 966 4.4 29 Westchester, NY.......... 36.1 408.8 -0.6 167 1,161 3.8 53 Buncombe, NC............. 7.8 110.6 1.7 25 678 2.9 115 Catawba, NC.............. 4.4 77.7 1.0 53 669 4.4 29 Cumberland, NC........... 6.2 118.6 -0.4 151 720 3.7 63 Durham, NC............... 7.1 177.0 -2.6 310 1,155 5.6 14 Forsyth, NC.............. 9.0 173.2 -1.3 243 797 3.6 70 Guilford, NC............. 14.2 255.8 -0.8 196 769 3.1 103 Mecklenburg, NC.......... 32.1 531.5 -0.2 132 984 4.7 23 New Hanover, NC.......... 7.2 95.3 -2.2 296 718 2.9 115 Wake, NC................. 28.4 436.1 0.8 67 873 5.1 19 Cass, ND................. 5.8 100.4 0.9 61 737 3.8 53 Butler, OH............... 7.2 137.9 0.8 67 767 4.6 25 Cuyahoga, OH............. 35.7 690.9 -0.6 167 882 3.8 53 Franklin, OH............. 28.9 649.5 -0.4 151 848 3.7 63 Hamilton, OH............. 23.1 488.3 -1.2 234 923 2.8 126 Lake, OH................. 6.4 94.4 -0.8 196 721 2.6 147 Lorain, OH............... 6.1 93.4 -1.1 225 698 3.9 50 Lucas, OH................ 10.3 199.2 1.3 38 743 2.2 182 Mahoning, OH............. 6.0 96.7 -0.3 144 631 2.4 160 Montgomery, OH........... 12.2 241.4 -0.5 158 772 1.8 214 Stark, OH................ 8.7 149.3 -1.6 267 664 2.2 182 Summit, OH............... 14.3 254.4 -0.5 158 773 1.0 269 Oklahoma, OK............. 24.2 412.1 0.2 107 789 2.3 172 Tulsa, OK................ 20.1 329.1 -2.0 285 783 2.5 154 Clackamas, OR............ 12.4 138.9 -1.3 243 799 2.8 126 Jackson, OR.............. 6.5 76.1 -1.6 267 670 1.8 214 Lane, OR................. 10.7 137.3 0.1 112 685 1.3 252 Marion, OR............... 9.3 136.0 -0.6 167 698 0.3 292 Multnomah, OR............ 28.4 422.8 -0.1 125 885 1.7 226 Washington, OR........... 16.0 236.6 0.3 95 994 5.7 11 Allegheny, PA............ 34.9 679.9 0.3 95 919 3.5 78 Berks, PA................ 9.0 163.0 1.3 38 786 0.3 292 Bucks, PA................ 19.6 255.0 0.4 91 839 0.1 299 Butler, PA............... 4.8 81.5 2.9 8 767 5.8 10 Chester, PA.............. 14.9 237.6 -0.4 151 1,131 1.8 214 Cumberland, PA........... 6.0 120.6 -0.7 182 807 1.3 252 Dauphin, PA.............. 7.4 180.0 -1.2 234 853 3.3 90 Delaware, PA............. 13.5 205.8 0.7 72 917 2.9 115 Erie, PA................. 7.5 123.4 1.1 46 671 0.3 292 Lackawanna, PA........... 5.8 98.0 -0.9 202 672 2.1 195 Lancaster, PA............ 12.4 220.7 -0.2 132 725 2.8 126 Lehigh, PA............... 8.6 173.1 0.6 76 823 -0.1 302 Luzerne, PA.............. 7.7 137.9 -0.7 182 680 2.4 160 Montgomery, PA........... 27.1 466.5 -1.0 216 1,068 2.8 126 Northampton, PA.......... 6.4 98.7 0.8 67 758 1.7 226 Philadelphia, PA......... 32.5 628.6 1.2 42 1,007 0.8 279 Washington, PA........... 5.5 81.1 1.4 34 777 5.0 21 Westmoreland, PA......... 9.3 134.3 0.0 121 694 3.0 110 York, PA................. 9.0 169.3 0.0 121 773 3.8 53 Providence, RI........... 17.4 269.2 -0.4 151 853 2.2 182 Charleston, SC........... 11.6 206.5 -0.2 132 768 4.6 25 Greenville, SC........... 12.0 226.4 1.7 25 758 2.8 126 Horry, SC................ 7.7 114.4 -1.3 243 546 5.2 17 Lexington, SC............ 5.6 94.0 -1.3 243 647 3.5 78 Richland, SC............. 9.0 202.8 -0.6 167 763 1.1 265 Spartanburg, SC.......... 6.0 109.4 -1.1 225 764 4.2 40 Minnehaha, SD............ 6.5 114.1 -0.5 158 704 2.3 172 Davidson, TN............. 18.1 419.4 (7) - 873 3.6 70 Hamilton, TN............. 8.4 179.2 0.3 95 761 5.1 19 Knox, TN................. 10.8 216.4 -0.3 144 735 2.7 138 Rutherford, TN........... 4.3 94.2 (7) - 806 (7) - Shelby, TN............... 19.1 466.3 -1.4 252 895 4.3 34 Williamson, TN........... 6.1 89.1 (7) - 942 3.9 50 Bell, TX................. 4.7 107.1 (7) - 714 (7) - Bexar, TX................ 33.3 727.4 1.0 53 772 3.2 95 Brazoria, TX............. 4.8 86.7 1.8 22 831 4.3 34 Brazos, TX............... 3.8 86.0 0.8 67 652 1.6 235 Cameron, TX.............. 6.3 125.0 1.4 34 562 3.3 90 Collin, TX............... 17.8 287.7 1.7 25 997 2.0 202 Dallas, TX............... 67.5 1,415.2 0.2 107 1,030 2.3 172 Denton, TX............... 10.9 173.1 1.9 17 756 1.6 235 El Paso, TX.............. 13.6 271.9 2.2 14 633 4.3 34 Fort Bend, TX............ 9.0 133.2 1.0 53 855 -1.7 317 Galveston, TX............ 5.2 95.9 2.9 8 791 -0.9 310 Harris, TX............... 99.7 1,996.5 -0.3 144 1,065 2.3 172 Hidalgo, TX.............. 10.8 220.5 2.0 15 563 3.3 90 Jefferson, TX............ 5.9 119.5 1.1 46 838 1.3 252 Lubbock, TX.............. 6.9 122.7 0.3 95 672 4.0 46 McLennan, TX............. 4.8 101.7 (7) - 704 (7) - Montgomery, TX........... 8.5 128.7 1.6 30 782 2.4 160 Nueces, TX............... 7.9 152.9 1.7 25 732 2.7 138 Potter, TX............... 3.8 73.9 -1.2 234 752 4.3 34 Smith, TX................ 5.3 92.3 0.9 61 742 3.5 78 Tarrant, TX.............. 37.2 747.5 0.1 112 873 4.4 29 Travis, TX............... 29.7 569.7 1.4 34 954 3.9 50 Webb, TX................. 4.7 85.2 0.9 61 590 5.7 11 Williamson, TX........... 7.4 122.6 1.1 46 824 4.2 40 Davis, UT................ 7.0 102.9 1.1 46 714 1.9 204 Salt Lake, UT............ 36.4 558.0 -0.2 132 810 1.5 242 Utah, UT................. 12.6 164.9 -0.1 125 679 -0.6 306 Weber, UT................ 5.5 89.6 -0.7 182 662 2.3 172 Chittenden, VT........... 5.9 91.9 -1.0 216 875 4.7 23 Arlington, VA............ 8.0 164.2 3.0 5 1,481 4.1 44 Chesterfield, VA......... 7.6 115.4 -0.9 202 798 4.0 46 Fairfax, VA.............. 34.0 580.3 0.6 76 1,392 3.2 95 Henrico, VA.............. 9.6 172.4 -0.1 125 873 1.7 226 Loudoun, VA.............. 9.2 134.9 2.0 15 1,054 3.3 90 Prince William, VA....... 7.4 106.2 1.5 33 796 3.1 103 Alexandria City, VA...... 6.1 97.1 -0.9 202 1,237 6.3 6 Chesapeake City, VA...... 5.7 95.7 -0.1 125 705 3.4 85 Newport News City, VA.... 3.9 96.3 0.1 112 811 1.9 204 Norfolk City, VA......... 5.7 136.6 -2.2 296 873 3.1 103 Richmond City, VA........ 7.2 149.0 -0.6 167 962 0.3 292 Virginia Beach City, VA.. 11.3 169.2 -0.6 167 696 2.8 126 Benton, WA............... 5.5 84.0 3.0 5 909 2.5 154 Clark, WA................ 13.0 128.2 -0.2 132 785 0.9 275 King, WA................. 80.6 1,125.9 -0.9 202 1,101 2.1 195 Kitsap, WA............... 6.6 81.8 -0.6 167 842 2.9 115 Pierce, WA............... 21.4 263.3 -1.2 234 809 2.7 138 Snohomish, WA............ 18.7 240.0 -2.0 285 923 2.8 126 Spokane, WA.............. 15.9 199.2 -2.4 306 732 1.9 204 Thurston, WA............. 7.3 97.5 -1.3 243 807 1.5 242 Whatcom, WA.............. 6.9 78.8 -1.4 252 706 0.9 275 Yakima, WA............... 8.8 106.5 -1.0 216 597 1.2 261 Kanawha, WV.............. 6.0 106.5 -0.6 167 773 0.9 275 Brown, WI................ 6.5 145.9 0.1 112 742 2.5 154 Dane, WI................. 13.7 297.5 -0.3 144 833 1.7 226 Milwaukee, WI............ 20.9 467.5 -1.4 252 866 2.2 182 Outagamie, WI............ 5.0 100.9 -1.5 262 725 3.1 103 Waukesha, WI............. 12.6 220.8 -2.0 285 852 3.5 78 Winnebago, WI............ 3.7 90.0 1.3 38 798 5.4 15 San Juan, PR............. 11.7 261.8 -3.8 (8) 592 1.5 (8) (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 326 U.S. counties comprise 70.7 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) Average weekly wages were calculated using unrounded data. (5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. (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 10 largest counties, second quarter 2010(2) Employment Average weekly wage(3) Establishments, second quarter County by NAICS supersector 2010 Percent Percent (thousands) June change, Average change, 2010 June weekly second (thousands) 2009-10(4) wage quarter 2009-10(4) United States(5)............................. 9,009.6 129,371.6 -0.2 $865 3.0 Private industry........................... 8,711.9 107,283.2 -0.5 849 3.3 Natural resources and mining............. 126.3 1,940.2 1.5 882 4.1 Construction............................. 801.1 5,657.4 -7.5 910 0.6 Manufacturing............................ 344.4 11,549.2 -1.6 1,063 5.8 Trade, transportation, and utilities..... 1,876.4 24,488.7 -0.7 733 3.2 Information.............................. 144.2 2,723.8 -3.7 1,324 4.1 Financial activities..................... 821.2 7,440.9 -2.6 1,259 6.2 Professional and business services....... 1,538.5 16,801.1 2.0 1,088 2.7 Education and health services............ 887.5 18,589.5 1.7 817 1.6 Leisure and hospitality.................. 745.0 13,518.8 -0.2 359 3.2 Other services........................... 1,246.0 4,404.9 -0.7 553 1.8 Government................................. 297.7 22,088.4 1.1 941 2.0 Los Angeles, CA.............................. 422.4 3,890.5 -1.6 968 3.1 Private industry........................... 416.8 3,298.4 -1.5 935 2.9 Natural resources and mining............. 0.5 10.8 3.3 1,107 8.2 Construction............................. 13.0 105.6 -11.7 989 -1.2 Manufacturing............................ 13.5 376.7 -3.9 1,063 3.9 Trade, transportation, and utilities..... 52.0 730.8 -0.4 781 3.4 Information.............................. 8.4 189.5 -1.0 1,667 2.3 Financial activities..................... 22.3 210.1 -2.5 1,417 2.7 Professional and business services....... 41.6 528.2 -0.4 1,144 1.6 Education and health services............ 28.7 505.0 2.0 897 2.3 Leisure and hospitality.................. 26.8 390.8 -0.8 529 2.1 Other services........................... 194.9 240.4 -8.0 458 8.3 Government................................. 5.6 592.0 -1.9 1,154 (6) Cook, IL..................................... 142.8 2,371.7 -0.9 1,012 2.4 Private industry........................... 141.4 2,057.3 -1.1 996 2.5 Natural resources and mining............. 0.1 0.9 -11.7 952 7.1 Construction............................. 12.2 67.1 -11.1 1,200 -0.2 Manufacturing............................ 6.7 193.4 -2.9 1,048 7.0 Trade, transportation, and utilities..... 27.7 429.8 -0.9 783 2.4 Information.............................. 2.6 51.5 -3.7 1,418 1.4 Financial activities..................... 15.5 190.0 -3.3 1,714 4.8 Professional and business services....... 30.0 404.1 0.9 1,277 1.5 Education and health services............ 14.8 390.5 1.3 861 1.2 Leisure and hospitality.................. 12.3 232.3 -1.1 449 4.7 Other services........................... 15.3 94.4 -2.8 739 1.4 Government................................. 1.4 314.3 0.0 1,118 2.6 New York, NY................................. 120.6 2,291.3 0.3 1,659 9.0 Private industry........................... 120.3 1,840.6 0.3 1,799 10.2 Natural resources and mining............. 0.0 0.1 -11.3 1,926 -24.3 Construction............................. 2.3 30.0 -12.7 1,523 1.6 Manufacturing............................ 2.6 26.7 -5.0 1,227 0.8 Trade, transportation, and utilities..... 21.1 234.4 1.9 1,173 4.5 Information.............................. 4.4 129.5 -2.7 2,011 3.3 Financial activities..................... 19.0 347.3 -0.2 3,611 25.8 Professional and business services....... 25.6 461.2 -0.3 1,887 4.5 Education and health services............ 9.1 294.0 1.3 1,097 2.7 Leisure and hospitality.................. 12.3 223.4 2.7 755 4.0 Other services........................... 18.5 87.6 -0.4 957 0.0 Government................................. 0.3 450.6 0.2 1,090 1.3 Harris, TX................................... 99.7 1,996.5 -0.3 1,065 2.3 Private industry........................... 99.1 1,729.1 -0.9 1,084 2.7 Natural resources and mining............. 1.6 74.7 3.1 2,732 2.2 Construction............................. 6.5 132.1 -7.8 1,056 -0.2 Manufacturing............................ 4.5 168.0 -3.0 1,323 5.8 Trade, transportation, and utilities..... 22.5 414.3 -1.0 957 1.7 Information.............................. 1.3 28.8 -4.7 1,214 1.0 Financial activities..................... 10.5 112.2 -3.1 1,295 7.1 Professional and business services....... 19.8 319.5 0.4 1,301 4.2 Education and health services............ 10.9 236.7 3.7 883 0.5 Leisure and hospitality.................. 8.0 181.3 -1.6 390 2.6 Other services........................... 13.1 60.3 0.8 614 -0.5 Government................................. 0.5 267.4 3.8 943 -0.6 Maricopa, AZ................................. 94.6 1,565.2 -1.5 860 1.7 Private industry........................... 93.9 1,385.9 -1.7 842 1.8 Natural resources and mining............. 0.5 7.6 -11.8 739 9.8 Construction............................. 9.0 81.2 -15.7 877 0.6 Manufacturing............................ 3.3 107.2 -4.2 1,264 8.0 Trade, transportation, and utilities..... 21.9 331.8 -1.1 794 2.5 Information.............................. 1.5 27.5 0.3 1,061 1.8 Financial activities..................... 11.4 132.0 -3.1 1,038 2.4 Professional and business services....... 21.8 260.7 -0.1 881 -0.1 Education and health services............ 10.3 223.5 3.6 901 -0.2 Leisure and hospitality.................. 6.8 167.1 -1.8 406 2.3 Other services........................... 6.8 46.8 0.3 570 0.5 Government................................. 0.7 179.3 -0.1 981 0.2 Dallas, TX................................... 67.5 1,415.2 0.2 1,030 2.3 Private industry........................... 67.0 1,243.0 -0.4 1,036 2.4 Natural resources and mining............. 0.6 8.4 8.3 3,107 9.8 Construction............................. 4.1 67.5 -10.2 926 2.1 Manufacturing............................ 2.9 113.7 -4.8 1,211 4.8 Trade, transportation, and utilities..... 14.8 279.4 -0.4 953 2.9 Information.............................. 1.6 45.6 -2.0 1,500 3.2 Financial activities..................... 8.5 136.5 -2.1 1,344 4.4 Professional and business services....... 14.7 257.2 1.5 1,165 2.3 Education and health services............ 6.9 164.0 4.7 978 -0.3 Leisure and hospitality.................. 5.4 131.2 0.9 444 -5.1 Other services........................... 7.0 38.8 0.1 641 0.2 Government................................. 0.5 172.2 4.4 988 1.8 Orange, CA................................... 101.7 1,369.7 -1.1 965 1.5 Private industry........................... 100.3 1,217.7 -1.0 949 1.9 Natural resources and mining............. 0.2 4.8 7.6 570 -4.4 Construction............................. 6.4 68.2 -9.1 1,037 -3.9 Manufacturing............................ 5.0 152.8 -2.0 1,166 4.4 Trade, transportation, and utilities..... 16.4 242.5 -1.4 914 2.6 Information.............................. 1.3 25.4 -6.9 1,353 4.6 Financial activities..................... 9.7 103.1 -2.7 1,375 3.9 Professional and business services....... 18.7 243.7 0.6 1,103 1.3 Education and health services............ 10.3 154.0 1.9 878 1.5 Leisure and hospitality.................. 7.1 170.9 0.0 419 2.9 Other services........................... 20.2 48.7 0.4 527 1.0 Government................................. 1.4 152.0 -2.2 1,100 -0.5 San Diego, CA................................ 97.5 1,253.3 -0.5 934 2.3 Private industry........................... 96.2 1,020.5 -0.8 903 2.8 Natural resources and mining............. 0.7 10.6 1.2 573 2.1 Construction............................. 6.4 56.2 -9.2 995 0.0 Manufacturing............................ 3.0 93.2 -2.3 1,313 5.1 Trade, transportation, and utilities..... 13.6 195.9 -1.0 746 3.5 Information.............................. 1.2 25.4 -4.1 1,363 3.4 Financial activities..................... 8.7 67.1 -3.1 1,101 3.3 Professional and business services....... 16.0 208.4 -0.3 1,254 3.6 Education and health services............ 8.4 144.4 2.5 875 2.1 Leisure and hospitality.................. 7.0 157.6 0.4 398 2.6 Other services........................... 26.7 58.4 0.3 494 3.8 Government................................. 1.4 232.8 (6) 1,069 (6) King, WA..................................... 80.6 1,125.9 -0.9 1,101 2.1 Private industry........................... 80.1 963.6 -1.2 1,100 1.8 Natural resources and mining............. 0.4 2.8 -3.2 1,214 5.6 Construction............................. 5.9 47.4 -15.0 1,098 -0.5 Manufacturing............................ 2.3 97.4 -3.9 1,418 2.8 Trade, transportation, and utilities..... 14.5 203.8 -0.3 950 2.9 Information.............................. 1.7 79.5 -0.9 1,991 3.4 Financial activities..................... 6.6 64.5 -7.0 1,283 -2.4 Professional and business services....... 13.8 175.1 1.0 1,327 3.4 Education and health services............ 6.9 131.2 0.1 913 3.5 Leisure and hospitality.................. 6.3 110.4 0.1 432 1.2 Other services........................... 21.7 51.4 10.1 596 -2.3 Government................................. 0.5 162.3 1.1 1,107 4.8 Miami-Dade, FL............................... 85.9 932.4 -0.2 850 1.9 Private industry........................... 85.6 800.2 -0.2 814 1.4 Natural resources and mining............. 0.5 7.0 -6.2 513 8.9 Construction............................. 5.5 31.2 -13.7 876 0.9 Manufacturing............................ 2.6 35.0 -6.7 777 4.4 Trade, transportation, and utilities..... 24.1 236.9 1.2 764 0.5 Information.............................. 1.5 17.3 (6) 1,328 (6) Financial activities..................... 9.3 60.7 -2.2 1,222 6.0 Professional and business services....... 18.1 121.2 -1.6 993 1.6 Education and health services............ 9.7 149.9 3.1 835 0.1 Leisure and hospitality.................. 6.4 105.7 3.0 486 2.3 Other services........................... 7.7 35.1 -0.1 544 0.7 Government................................. 0.4 132.2 -0.2 1,051 4.1 (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) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. (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 by state, second quarter 2010(2) Employment Average weekly wage(3) Establishments, second quarter State 2010 Percent Percent (thousands) June change, Average change, 2010 June weekly second (thousands) 2009-10 wage quarter 2009-10 United States(4)......... 9,009.6 129,371.6 -0.2 $865 3.0 Alabama.................. 116.6 1,831.3 -0.4 750 2.3 Alaska................... 21.3 330.6 1.2 916 2.7 Arizona.................. 147.2 2,308.7 -1.1 821 1.7 Arkansas................. 85.8 1,153.7 1.2 684 2.5 California............... 1,327.9 14,651.5 -1.0 978 3.2 Colorado................. 172.2 2,202.5 -0.9 870 2.2 Connecticut.............. 111.4 1,617.8 -1.1 1,075 4.0 Delaware................. 28.5 404.8 -0.9 876 2.1 District of Columbia..... 34.2 701.4 2.3 1,506 5.7 Florida.................. 600.0 7,043.4 -0.6 782 2.1 Georgia.................. 267.9 3,767.6 -0.9 812 2.5 Hawaii................... 38.9 584.0 -1.9 782 0.9 Idaho.................... 54.9 616.6 -1.4 651 3.0 Illinois................. 377.5 5,574.8 -0.6 910 3.1 Indiana.................. 158.0 2,734.8 1.2 732 3.1 Iowa..................... 94.6 1,459.3 -0.9 709 3.4 Kansas................... 87.6 1,315.2 -1.1 732 1.9 Kentucky................. 109.9 1,733.6 0.6 743 2.8 Louisiana................ 129.5 1,849.1 -0.1 769 2.1 Maine.................... 48.9 591.6 -0.8 699 2.6 Maryland................. 162.3 2,501.7 0.0 957 2.5 Massachusetts............ 218.7 3,199.1 0.4 1,060 3.1 Michigan................. 248.1 3,828.6 0.8 825 1.9 Minnesota................ 169.7 2,605.5 -0.3 869 3.3 Mississippi.............. 69.3 1,083.7 0.0 652 2.0 Missouri................. 173.5 2,611.5 -1.1 762 1.7 Montana.................. 42.4 432.0 -0.5 658 3.5 Nebraska................. 59.8 909.6 -0.3 696 3.3 Nevada................... 72.6 1,117.7 -2.1 796 -0.3 New Hampshire............ 48.1 612.4 -0.5 867 4.6 New Jersey............... 266.9 3,853.2 -0.3 1,028 2.6 New Mexico............... 54.4 792.1 -0.8 743 2.6 New York................. 589.0 8,503.4 0.5 1,078 5.0 North Carolina........... 251.8 3,813.0 -0.5 764 3.9 North Dakota............. 26.0 363.6 2.0 711 6.6 Ohio..................... 283.0 4,959.0 -0.4 775 2.9 Oklahoma................. 102.5 1,499.0 -0.3 717 3.0 Oregon................... 130.2 1,626.2 -0.5 786 2.5 Pennsylvania............. 341.8 5,552.8 0.6 849 2.4 Rhode Island............. 35.0 456.5 -0.6 831 3.1 South Carolina........... 111.5 1,782.5 0.0 710 3.6 South Dakota............. 30.8 401.5 0.2 631 2.8 Tennessee................ 139.5 2,583.3 0.7 776 3.3 Texas.................... 570.0 10,245.8 0.7 864 3.0 Utah..................... 83.0 1,159.2 -0.4 733 1.4 Vermont.................. 24.3 291.2 -1.0 756 4.3 Virginia................. 231.5 3,590.7 0.1 929 3.3 Washington............... 230.7 2,858.7 -0.9 898 2.0 West Virginia............ 48.6 700.5 0.4 726 2.3 Wisconsin................ 156.4 2,684.4 -0.3 746 2.5 Wyoming.................. 25.1 280.9 -1.1 789 2.7 Puerto Rico.............. 49.6 930.6 -2.6 493 1.6 Virgin Islands........... 3.6 43.9 0.7 709 -1.4 (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.