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For release 10:00 a.m. (EDT), Thursday, September 29, 2011 USDL-11-1397 Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew Media Contact: (202) 691-5902 * PressOffice@bls.gov County Employment and Wages First Quarter 2011 From March 2010 to March 2011, employment increased in 256 of the 322 largest U.S. counties, the U.S. Bureau of Labor Statistics reported today. Elkhart, Ind., posted the largest percentage increase, with a gain of 6.2 percent over the year, compared with national job growth of 1.3 percent. Within Elkhart, the largest employment increase occurred in manufacturing, which gained 5,125 jobs over the year (12.4 percent). Sacramento, Calif., experienced the largest over-the- year percentage decrease in employment among the largest counties in the U.S. with a loss of 1.6 percent. The U.S. average weekly wage increased over the year by 5.2 percent to $935 in the first quarter of 2011. Among the large counties in the U.S., Peoria, Ill., had the largest over-the-year increase in average weekly wages in the first quarter of 2011 with a gain of 18.9 percent. Within Peoria, professional and business services had the largest impact on the county’s over-the-year increase in average weekly wages. Williamson, Texas, experienced the largest decline in average weekly wages with a loss of 3.8 percent over the year. County employment and wage data are compiled under the Quarterly Census of Employment and Wages (QCEW) program. Table A. Large counties ranked by March 2011 employment, March 2010-11 employment increase, and March 2010-11 percent increase in employment -------------------------------------------------------------------------------------------------------- Employment in large counties -------------------------------------------------------------------------------------------------------- March 2011 employment | Increase in employment, | Percent increase in employment, (thousands) | March 2010-11 | March 2010-11 | (thousands) | -------------------------------------------------------------------------------------------------------- | | United States 127,851.0| United States 1,622.8| United States 1.3 -------------------------------------------------------------------------------------------------------- | | Los Angeles, Calif. 3,887.9| Harris, Texas 44.6| Elkhart, Ind. 6.2 Cook, Ill. 2,333.9| New York, N.Y. 43.4| Ottawa, Mich. 4.7 New York, N.Y. 2,304.1| Los Angeles, Calif. 37.3| Washington, Pa. 4.3 Harris, Texas 2,014.4| Orange, Calif. 26.7| Prince William, Va. 4.3 Maricopa, Ariz. 1,628.8| Dallas, Texas 26.7| Benton, Wash. 4.3 Dallas, Texas 1,416.9| Santa Clara, Calif. 24.6| Butler, Pa. 4.2 Orange, Calif. 1,370.6| Cook, Ill. 22.9| Loudoun, Va. 4.2 San Diego, Calif. 1,239.7| Maricopa, Ariz. 21.1| Williamson, Tenn. 4.1 King, Wash. 1,117.2| King, Wash. 20.0| Washington, Ore. 4.0 Miami-Dade, Fla. 967.7| Hennepin, Minn. 19.3| Collier, Fla. 3.8 | | -------------------------------------------------------------------------------------------------------- Large County Employment In March 2011, national employment, as measured by the QCEW program, was 127.9 million, up by 1.3 percent or 1.6 million workers, from March 2010. The 322 U.S. counties with 75,000 or more employees accounted for 70.7 percent of total U.S. employment and 77.4 percent of total wages. These 322 counties had a net job growth of 1,054,300 over the year, accounting for 65.0 percent of the overall U.S. employment increase. Elkhart, Ind., had the largest percentage increase in employment among the largest U.S. counties (6.2 percent). The five counties with the largest increases in employment level were Harris, Texas; New York, N.Y.; Los Angeles, Calif.; Orange, Calif.; and Dallas, Texas. These counties had a combined over-the-year gain of 178,700, or 11.0 percent of the employment increase for the U.S. Employment declined in 53 of the large counties from March 2010 to March 2011. Sacramento, Calif., had the largest over-the-year percentage decrease in employment (-1.6 percent). Within Sacramento, construction was the largest contributor to the decrease in employment with a loss of 9.5 percent. Montgomery, Ala., and Atlantic, N.J., tied for the second largest employment decrease, followed by San Joaquin, Calif., Marion, Fla., and Champaign, Ill., which tied for the third largest decline. (See table 1.) Table B. Large counties ranked by first quarter 2011 average weekly wages, first quarter 2010-11 increase in average weekly wages, and first quarter 2010-11 percent increase in average weekly wages -------------------------------------------------------------------------------------------------------- Average weekly wage in large counties -------------------------------------------------------------------------------------------------------- Average weekly wage, | Increase in average weekly | Percent increase in average first quarter 2011 | wage, first quarter 2010-11 | weekly wage, first | | quarter 2010-11 -------------------------------------------------------------------------------------------------------- | | United States $935| United States $46| United States 5.2 -------------------------------------------------------------------------------------------------------- | | New York, N.Y. $2,634| New York, N.Y. $222| Peoria, Ill. 18.9 Fairfield, Conn. 1,888| Santa Clara, Calif. 205| Santa Clara, Calif. 12.4 Somerset, N.J. 1,867| Peoria, Ill. 150| Macomb, Mich. 12.0 Santa Clara, Calif. 1,863| Somerset, N.J. 114| Clayton, Ga. 11.9 San Francisco, Calif. 1,723| San Francisco, Calif. 112| Wayne, Mich. 11.3 Suffolk, Mass. 1,625| Fulton, Ga. 111| Brazoria, Texas 10.0 Arlington, Va. 1,549| Wayne, Mich. 104| Saginaw, Mich. 9.8 Washington, D.C. 1,540| Fairfield, Conn. 102| Stark, Ohio 9.7 Hudson, N.J. 1,509| Hartford, Conn. 102| Butler, Pa. 9.3 San Mateo, Calif. 1,485| Macomb, Mich. 101| New York, N.Y. 9.2 | | -------------------------------------------------------------------------------------------------------- Large County Average Weekly Wages Average weekly wages for the nation increased by 5.2 percent over the year in the first quarter of 2011. Among the 322 largest counties, 315 had over-the-year increases in average weekly wages. Peoria, Ill., had the largest wage gain among the largest U.S. counties (18.9 percent). Of the 322 largest counties, 3 experienced declines in average weekly wages. Williamson, Texas, had the largest wage decline with a loss of 3.8 percent over the year. Trade, transportation, and utilities contributed significantly to the county’s overall average weekly wage loss. Hudson, N.J., had the second largest percent decline in average weekly wages among the counties, followed by Durham, N.C. (See table 1.) Ten Largest U.S. Counties All of the 10 largest counties experienced over-the-year percent increases in employment in March 2011. Harris, Texas, experienced the largest gain in employment (2.3 percent). Within Harris, professional and business services had the largest over-the-year increase among all private industry groups with a gain of 16,522 workers (5.3 percent). Los Angeles, Calif., and Cook, Ill., both had the smallest percent increase in employment. (See table 2.) All of the 10 largest U.S. counties had an over-the-year increase in average weekly wages. New York, N.Y., experienced the largest increase in average weekly wages with a gain of 9.2 percent. Within New York, the largest impact on the county’s average weekly wage growth occurred in financial activities, largely due to significant total wage gains over the year ($5,287.0 million or 15.4 percent). Orange, Calif., had the smallest average weekly wage increase. For More Information The tables and charts included in this release contain data for the nation and for the 322 U.S. counties with annual average employment levels of 75,000 or more in 2010. March 2011 employment and 2011 first 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 9.1 million employer reports cover 127.9 million full- and part-time workers. For additional information about the quarterly employment and wages data, please read the Technical Note. Data for the first quarter of 2011 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 second quarter 2011 is scheduled to be released on Tuesday, January 10, 2012. -------------------------------------------------------------------------------------- | | | Industry Changes to Quarterly Census of Employment and Wages Data | | | | Beginning with the Quarterly Census of Employment and Wages data | | presented in this release, the Bureau of Labor Statistics is introducing | | the 2012 version of the North American Industry Classification System as | | the basis for the assignment and tabulation of economic data by industry. | | For more information on the change, please see the Federal Register notice | | at http://www.census.gov/eos/www/naics/federal_register_notices/notices/fr17au11.pdf.| | For more information on the impact of the change, please see | | http://www.bls.gov/cew/naics2012.htm. | | | -------------------------------------------------------------------------------------- -------------------------------------------------------------------------------------- | | | County Changes for the 2011 County Employment and Wages News Releases | | | | Counties with annual average employment of 75,000 or more in 2010 are included | | in this release and will be included in future 2011 releases. Four counties | | will be excluded: Okaloosa, Fla., Rock Island, Ill., St. Tammany, La., and | | Potter, Texas. No counties have been added to the publication tables. | | | --------------------------------------------------------------------------------------
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 2012 North American Industry Classification System. Data for 2011 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 323 counties presented in this release were derived using 2010 preliminary annual averages of employment. For 2011 data, four counties, Okaloosa, Fla., Rock Island, Ill., St. Tammany, La., and Potter, Texas, which were published in the 2010 releases, will be excluded from this and future 2011 releases because their 2010 annual average employment levels were less than 75,000. No counties have been added to the publication tables. 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- | 440,000 establish- | submitted by 9.1 | ministrative records| ments | million establish- | submitted by 6.7 | | ments in first | million private-sec-| | quarter of 2011 | 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 2010. 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 2010, UI and UCFE programs covered workers in 127.8 million jobs. The estimated 123.2 million workers in these jobs (after adjustment for multiple jobholders) represented 95.3 percent of civilian wage and salary employment. Covered workers received $5.976 trillion in pay, representing 93.3 percent of the wage and salary component of personal income and 41.1 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 2010 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 Employment and Wages Annual Averages Online features comprehensive information by detailed industry on establishments, employment, and wages for the nation and all states. The 2009 edition of this publication, which was published in March 2011, contains selected data produced by Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the first quarter 2010 version of this news release. This web-only publication has replaced the print version of the annual bulletin, Employment and Wages Annual Averages. Tables and additional content from Employment and Wages Annual Averages Online, 2009 are now available online at http://www.bls.gov/cew/cewbultn09.htm. The 2010 edition of Employment and Wages Annual Averages Online will be available later in 2011. 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 323 largest counties, first quarter 2011(2) Employment Average weekly wage(4) Establishments, County(3) first quarter Percent Ranking Percent Ranking 2011 March change, by First change, by (thousands) 2011 March percent quarter first percent (thousands) 2010-11(5) change 2011 quarter change 2010-11(5) United States(6)......... 9,074.3 127,851.0 1.3 - $935 5.2 - Jefferson, AL............ 17.8 328.8 -0.5 280 919 4.9 99 Madison, AL.............. 8.8 176.4 -0.8 294 978 4.4 134 Mobile, AL............... 9.8 165.0 0.9 169 741 4.7 111 Montgomery, AL........... 6.3 127.2 -1.5 314 764 4.1 157 Tuscaloosa, AL........... 4.2 83.1 1.5 106 778 5.9 64 Anchorage Borough, AK.... 8.1 147.4 1.7 86 958 2.6 264 Maricopa, AZ............. 93.8 1,628.8 1.3 132 889 5.1 89 Pima, AZ................. 18.9 344.0 -0.7 290 768 4.2 148 Benton, AR............... 5.4 92.5 (7) - 1,110 6.5 45 Pulaski, AR.............. 15.1 241.6 0.3 229 819 5.5 80 Washington, AR........... 5.5 89.2 (7) - 726 4.6 116 Alameda, CA.............. 56.4 632.2 -0.1 264 1,183 4.0 165 Contra Costa, CA......... 30.3 312.6 -0.1 264 1,210 6.4 49 Fresno, CA............... 30.9 322.4 1.6 97 709 3.4 200 Kern, CA................. 18.0 259.5 1.8 80 790 4.2 148 Los Angeles, CA.......... 438.0 3,887.9 1.0 158 1,046 6.6 43 Marin, CA................ 11.9 101.5 2.4 42 1,103 7.2 29 Monterey, CA............. 13.0 148.1 -0.3 274 808 1.6 301 Orange, CA............... 104.8 1,370.6 2.0 65 1,035 3.3 213 Placer, CA............... 10.9 126.2 1.3 132 876 4.5 125 Riverside, CA............ 50.1 559.0 -0.1 264 748 3.2 219 Sacramento, CA........... 54.3 573.9 -1.6 316 1,025 5.1 89 San Bernardino, CA....... 51.5 592.0 -0.3 274 754 3.3 213 San Diego, CA............ 100.7 1,239.7 1.4 118 1,003 7.2 29 San Francisco, CA........ 55.1 548.6 2.9 26 1,723 7.0 35 San Joaquin, CA.......... 17.4 196.0 -1.4 311 752 3.2 219 San Luis Obispo, CA...... 9.7 100.0 1.1 148 742 2.1 285 San Mateo, CA............ 24.6 322.3 1.5 106 1,485 1.6 301 Santa Barbara, CA........ 14.6 173.9 1.4 118 869 5.1 89 Santa Clara, CA.......... 63.1 857.3 3.0 19 1,863 12.4 2 Santa Cruz, CA........... 9.1 87.3 1.5 106 814 2.1 285 Solano, CA............... 10.2 118.1 0.2 242 921 2.7 260 Sonoma, CA............... 18.9 174.9 1.6 97 846 3.4 200 Stanislaus, CA........... 15.2 156.5 -0.2 271 748 2.5 268 Tulare, CA............... 9.5 134.7 1.1 148 622 2.8 248 Ventura, CA.............. 24.3 300.6 1.4 118 964 4.4 134 Yolo, CA................. 6.2 89.0 (7) - 892 (7) - Adams, CO................ 8.8 151.3 0.8 180 806 4.1 157 Arapahoe, CO............. 18.6 272.0 2.0 65 1,130 2.7 260 Boulder, CO.............. 12.8 153.1 1.7 86 1,050 3.9 170 Denver, CO............... 25.0 417.8 2.0 65 1,212 5.0 94 Douglas, CO.............. 9.3 87.9 0.6 196 1,069 7.1 34 El Paso, CO.............. 16.7 232.0 1.4 118 812 2.9 242 Jefferson, CO............ 17.7 200.3 0.5 206 929 3.7 183 Larimer, CO.............. 9.9 124.4 1.2 139 795 5.3 83 Weld, CO................. 5.7 80.6 3.6 12 776 7.6 22 Fairfield, CT............ 32.4 396.3 2.3 49 1,888 5.7 73 Hartford, CT............. 25.3 481.1 1.1 148 1,260 8.8 11 New Haven, CT............ 22.2 344.3 0.9 169 956 4.7 111 New London, CT........... 6.9 122.0 0.0 257 960 4.7 111 New Castle, DE........... 17.5 261.9 1.6 97 1,194 6.3 51 Washington, DC........... 34.8 702.3 2.5 35 1,540 2.4 272 Alachua, FL.............. 6.5 115.4 0.2 242 730 3.5 197 Brevard, FL.............. 14.3 187.1 -0.5 280 801 2.2 279 Broward, FL.............. 61.8 682.9 0.3 229 834 3.2 219 Collier, FL.............. 11.5 119.6 3.8 10 767 4.1 157 Duval, FL................ 26.5 439.1 1.8 80 891 3.1 226 Escambia, FL............. 7.8 120.1 0.8 180 690 4.2 148 Hillsborough, FL......... 36.6 574.6 0.7 188 880 4.5 125 Lake, FL................. 7.1 79.3 1.1 148 586 2.8 248 Lee, FL.................. 18.2 199.9 1.4 118 711 4.3 143 Leon, FL................. 8.1 137.9 0.4 216 722 1.0 310 Manatee, FL.............. 9.3 104.1 0.3 229 668 3.6 188 Marion, FL............... 7.8 89.0 -1.4 311 614 2.8 248 Miami-Dade, FL........... 85.5 967.7 1.9 74 874 3.4 200 Orange, FL............... 35.2 655.7 2.1 56 805 4.4 134 Palm Beach, FL........... 48.7 496.5 0.7 188 886 4.4 134 Pasco, FL................ 9.7 98.6 2.4 42 596 2.8 248 Pinellas, FL............. 30.1 379.7 -1.1 304 765 2.8 248 Polk, FL................. 12.3 191.4 -0.5 280 668 3.9 170 Sarasota, FL............. 14.2 135.3 1.4 118 722 2.4 272 Seminole, FL............. 13.7 154.4 -0.5 280 735 3.1 226 Volusia, FL.............. 13.2 151.0 -0.7 290 629 2.8 248 Bibb, GA................. 4.6 79.0 0.1 249 699 2.5 268 Chatham, GA.............. 7.6 128.0 0.7 188 752 3.9 170 Clayton, GA.............. 4.2 101.5 1.0 158 844 11.9 4 Cobb, GA................. 20.6 285.6 0.7 188 962 4.0 165 De Kalb, GA.............. 17.4 272.4 1.0 158 992 6.0 60 Fulton, GA............... 39.7 710.8 1.2 139 1,370 8.8 11 Gwinnett, GA............. 23.4 298.6 2.7 30 879 3.4 200 Muscogee, GA............. 4.6 92.8 0.9 169 749 5.9 64 Richmond, GA............. 4.6 99.3 1.7 86 743 3.9 170 Honolulu, HI............. 24.5 436.5 1.5 106 821 3.1 226 Ada, ID.................. 14.0 190.0 0.4 216 773 4.9 99 Champaign, IL............ 4.2 86.3 -1.4 311 750 2.9 242 Cook, IL................. 145.1 2,333.9 1.0 158 1,145 5.8 70 Du Page, IL.............. 36.5 546.6 1.8 80 1,076 3.4 200 Kane, IL................. 13.2 187.8 0.9 169 777 2.8 248 Lake, IL................. 21.7 303.1 (7) - 1,230 (7) - McHenry, IL.............. 8.6 89.7 -0.5 280 727 4.5 125 McLean, IL............... 3.8 84.8 0.1 249 904 2.1 285 Madison, IL.............. 6.0 94.3 2.0 65 738 2.1 285 Peoria, IL............... 4.7 99.8 2.5 35 944 18.9 1 St. Clair, IL............ 5.5 93.6 0.6 196 709 2.0 293 Sangamon, IL............. 5.3 125.9 1.2 139 907 3.4 200 Will, IL................. 14.7 192.9 0.9 169 793 5.0 94 Winnebago, IL............ 6.8 122.9 0.3 229 769 7.6 22 Allen, IN................ 9.0 170.4 2.1 56 747 4.0 165 Elkhart, IN.............. 4.9 102.5 6.2 1 698 5.4 82 Hamilton, IN............. 8.3 107.8 2.5 35 924 6.6 43 Lake, IN................. 10.3 181.1 0.6 196 791 5.6 77 Marion, IN............... 23.8 542.2 1.0 158 987 3.6 188 St. Joseph, IN........... 6.0 114.9 0.7 188 723 3.1 226 Vanderburgh, IN.......... 4.8 104.0 0.1 249 729 5.7 73 Linn, IA................. 6.2 123.4 1.7 86 847 3.9 170 Polk, IA................. 14.5 260.6 -0.5 280 940 4.9 99 Scott, IA................ 5.2 84.2 1.1 148 725 6.1 57 Johnson, KS.............. 21.1 295.8 1.5 106 955 2.5 268 Sedgwick, KS............. 12.5 237.6 0.1 249 816 6.9 37 Shawnee, KS.............. 4.9 93.9 -1.1 304 751 4.3 143 Wyandotte, KS............ 3.3 79.3 1.8 80 826 4.4 134 Fayette, KY.............. 9.6 169.5 1.7 86 811 6.0 60 Jefferson, KY............ 22.6 407.9 1.3 132 873 3.4 200 Caddo, LA................ 7.5 120.4 0.5 206 736 6.8 38 Calcasieu, LA............ 5.0 82.2 0.2 242 768 4.8 105 East Baton Rouge, LA..... 14.7 254.2 0.1 249 831 2.8 248 Jefferson, LA............ 14.0 192.1 0.4 216 831 3.6 188 Lafayette, LA............ 9.1 132.0 2.3 49 847 4.7 111 Orleans, LA.............. 11.1 173.1 1.2 139 983 3.0 236 Cumberland, ME........... 12.5 164.1 1.3 132 835 4.8 105 Anne Arundel, MD......... 14.5 224.7 1.1 148 958 (7) - Baltimore, MD............ 21.1 357.7 0.3 229 920 2.3 276 Frederick, MD............ 6.0 90.4 0.3 229 904 5.9 64 Harford, MD.............. 5.6 81.4 2.5 35 844 4.5 125 Howard, MD............... 8.9 147.7 2.5 35 1,141 6.5 45 Montgomery, MD........... 32.9 445.7 2.0 65 1,311 3.9 170 Prince Georges, MD....... 15.7 297.8 0.6 196 933 2.1 285 Baltimore City, MD....... 13.7 327.8 0.6 196 1,081 3.7 183 Barnstable, MA........... 9.3 78.3 0.1 249 759 4.5 125 Bristol, MA.............. 16.6 205.0 1.4 118 791 6.3 51 Essex, MA................ 22.0 291.6 1.7 86 955 6.3 51 Hampden, MA.............. 15.5 191.7 1.4 118 812 1.0 310 Middlesex, MA............ 49.9 796.6 0.9 169 1,370 7.3 27 Norfolk, MA.............. 24.8 309.4 0.5 206 1,066 4.5 125 Plymouth, MA............. 14.5 166.6 0.6 196 815 5.0 94 Suffolk, MA.............. 23.5 574.8 1.4 118 1,625 5.0 94 Worcester, MA............ 21.8 309.2 1.6 97 908 7.2 29 Genesee, MI.............. 7.3 126.1 0.0 257 742 8.3 15 Ingham, MI............... 6.4 151.0 -0.4 277 879 6.0 60 Kalamazoo, MI............ 5.3 106.2 0.9 169 816 5.0 94 Kent, MI................. 13.7 310.0 3.0 19 792 3.4 200 Macomb, MI............... 16.8 277.6 3.0 19 941 12.0 3 Oakland, MI.............. 37.0 618.7 2.7 30 1,019 7.5 24 Ottawa, MI............... 5.5 101.2 4.7 2 714 6.1 57 Saginaw, MI.............. 4.1 79.1 1.6 97 760 9.8 7 Washtenaw, MI............ 8.0 188.9 2.1 56 925 1.1 307 Wayne, MI................ 30.7 660.6 1.5 106 1,021 11.3 5 Anoka, MN................ 7.1 104.0 0.3 229 829 7.2 29 Dakota, MN............... 9.7 165.0 0.3 229 895 3.6 188 Hennepin, MN............. 43.5 805.9 2.4 42 1,197 7.7 20 Olmsted, MN.............. 3.4 85.4 -0.3 274 968 3.4 200 Ramsey, MN............... 13.9 310.1 0.2 242 1,093 6.2 55 St. Louis, MN............ 5.7 91.2 0.2 242 722 5.6 77 Stearns, MN.............. 4.3 77.2 2.5 35 700 2.2 279 Harrison, MS............. 4.5 82.0 0.7 188 668 1.7 300 Hinds, MS................ 6.0 121.6 -1.1 304 778 3.9 170 Boone, MO................ 4.4 82.0 1.0 158 692 3.1 226 Clay, MO................. 5.0 89.3 0.8 180 850 2.4 272 Greene, MO............... 8.0 147.0 -0.6 287 661 4.6 116 Jackson, MO.............. 18.0 338.9 0.0 257 894 1.6 301 St. Charles, MO.......... 8.1 120.2 2.2 53 744 1.6 301 St. Louis, MO............ 31.8 560.8 0.1 249 973 3.6 188 St. Louis City, MO....... 8.8 212.1 -0.6 287 1,037 2.8 248 Yellowstone, MT.......... 5.9 74.6 0.0 257 721 4.6 116 Douglas, NE.............. 15.8 307.4 0.9 169 853 3.1 226 Lancaster, NE............ 8.1 151.5 0.4 216 711 3.6 188 Clark, NV................ 47.2 795.2 0.4 216 790 1.8 297 Washoe, NV............... 13.6 179.9 -0.8 294 789 3.4 200 Hillsborough, NH......... 11.8 185.0 1.3 132 975 5.9 64 Rockingham, NH........... 10.5 129.7 1.3 132 857 5.7 73 Atlantic, NJ............. 6.8 128.3 -1.5 314 772 2.8 248 Bergen, NJ............... 33.5 420.2 0.6 196 1,152 2.8 248 Burlington, NJ........... 11.1 189.1 -1.1 304 957 3.5 197 Camden, NJ............... 12.4 191.3 -0.9 298 903 5.7 73 Essex, NJ................ 20.9 336.0 -0.8 294 1,229 4.5 125 Gloucester, NJ........... 6.2 96.4 0.3 229 766 1.1 307 Hudson, NJ............... 13.8 229.4 0.0 257 1,509 -1.5 317 Mercer, NJ............... 11.2 226.1 0.5 206 1,283 5.3 83 Middlesex, NJ............ 21.9 371.7 -0.2 271 1,191 4.6 116 Monmouth, NJ............. 20.2 237.4 -0.7 290 945 2.7 260 Morris, NJ............... 17.4 264.9 -0.5 280 1,462 2.5 268 Ocean, NJ................ 12.2 140.2 -0.2 271 746 3.2 219 Passaic, NJ.............. 12.2 169.1 0.5 206 921 3.1 226 Somerset, NJ............. 10.1 164.9 0.4 216 1,867 6.5 45 Union, NJ................ 14.6 215.1 -0.9 298 1,199 1.9 294 Bernalillo, NM........... 17.6 308.5 -0.4 277 781 2.6 264 Albany, NY............... 10.0 215.2 -0.9 298 937 2.9 242 Bronx, NY................ 17.0 234.1 0.8 180 818 3.2 219 Broome, NY............... 4.5 89.5 -1.0 302 703 4.5 125 Dutchess, NY............. 8.1 109.3 -0.1 264 917 1.8 297 Erie, NY................. 23.7 444.8 0.5 206 794 4.6 116 Kings, NY................ 50.9 503.9 3.7 11 725 1.1 307 Monroe, NY............... 18.1 366.1 0.5 206 847 3.4 200 Nassau, NY............... 52.7 578.6 0.4 216 1,015 3.3 213 New York, NY............. 121.9 2,304.1 1.9 74 2,634 9.2 10 Oneida, NY............... 5.3 104.6 -1.3 310 708 4.1 157 Onondaga, NY............. 12.8 236.8 -0.1 264 831 4.3 143 Orange, NY............... 10.0 128.2 1.5 106 755 2.2 279 Queens, NY............... 45.7 494.0 1.6 97 844 4.2 148 Richmond, NY............. 9.0 90.8 1.8 80 758 3.6 188 Rockland, NY............. 9.9 112.0 1.2 139 991 2.6 264 Suffolk, NY.............. 50.8 596.3 0.7 188 972 4.2 148 Westchester, NY.......... 36.2 397.8 1.0 158 1,332 1.4 305 Buncombe, NC............. 7.8 110.5 2.1 56 676 4.8 105 Catawba, NC.............. 4.4 78.4 2.8 28 692 7.5 24 Cumberland, NC........... 6.2 118.9 1.3 132 695 4.2 148 Durham, NC............... 7.1 177.8 1.4 118 1,276 -0.5 316 Forsyth, NC.............. 8.9 170.6 -0.8 294 891 7.9 18 Guilford, NC............. 14.0 260.6 1.7 86 802 4.8 105 Mecklenburg, NC.......... 31.9 546.4 2.8 28 1,231 7.3 27 New Hanover, NC.......... 7.2 96.2 2.1 56 741 4.2 148 Wake, NC................. 28.6 437.2 3.3 14 917 1.9 294 Cass, ND................. 5.9 100.2 3.0 19 765 6.7 41 Butler, OH............... 7.3 136.5 0.4 216 781 0.5 314 Cuyahoga, OH............. 35.7 675.4 0.5 206 953 7.4 26 Franklin, OH............. 29.2 644.1 1.4 118 920 4.4 134 Hamilton, OH............. 23.1 478.5 0.8 180 992 4.1 157 Lake, OH................. 6.5 90.9 0.4 216 774 3.6 188 Lorain, OH............... 6.1 91.3 2.5 35 750 7.0 35 Lucas, OH................ 10.3 196.4 1.5 106 793 5.9 64 Mahoning, OH............. 6.1 94.5 1.7 86 632 4.6 116 Montgomery, OH........... 12.2 238.9 0.8 180 782 3.3 213 Stark, OH................ 8.7 148.5 2.2 53 703 9.7 8 Summit, OH............... 14.3 248.9 0.3 229 841 2.2 279 Oklahoma, OK............. 24.4 413.5 2.0 65 837 5.5 80 Tulsa, OK................ 20.2 324.5 0.2 242 825 5.1 89 Clackamas, OR............ 12.5 135.2 0.6 196 798 3.4 200 Jackson, OR.............. 6.5 73.2 -1.1 304 644 2.7 260 Lane, OR................. 10.8 134.7 0.9 169 672 3.4 200 Marion, OR............... 9.3 128.0 -1.0 302 699 1.9 294 Multnomah, OR............ 29.0 424.9 2.0 65 918 5.2 85 Washington, OR........... 16.2 239.4 4.0 9 1,120 6.8 38 Allegheny, PA............ 35.1 666.8 1.5 106 997 5.2 85 Berks, PA................ 9.0 161.7 1.4 118 780 4.0 165 Bucks, PA................ 19.6 244.9 0.5 206 855 3.1 226 Butler, PA............... 4.8 80.2 4.2 6 799 9.3 9 Chester, PA.............. 14.9 233.3 1.1 148 1,164 2.9 242 Cumberland, PA........... 6.0 120.5 1.1 148 815 3.7 183 Dauphin, PA.............. 7.4 173.3 0.4 216 889 4.6 116 Delaware, PA............. 13.6 205.3 1.7 86 1,003 3.7 183 Erie, PA................. 7.6 121.9 3.2 15 695 6.8 38 Lackawanna, PA........... 5.8 96.4 -0.4 277 665 2.9 242 Lancaster, PA............ 12.4 214.0 0.4 216 734 4.7 111 Lehigh, PA............... 8.6 170.4 2.0 65 879 3.8 180 Luzerne, PA.............. 7.7 136.3 1.0 158 684 4.1 157 Montgomery, PA........... 27.1 456.4 0.2 242 1,198 2.1 285 Northampton, PA.......... 6.4 97.6 0.6 196 791 4.6 116 Philadelphia, PA......... 33.7 628.0 1.2 139 1,079 4.5 125 Washington, PA........... 5.5 80.2 4.3 3 867 8.8 11 Westmoreland, PA......... 9.3 128.8 1.1 148 716 6.1 57 York, PA................. 9.0 168.2 1.6 97 789 3.5 197 Providence, RI........... 17.4 263.9 0.0 257 895 2.3 276 Charleston, SC........... 11.6 206.6 2.9 26 774 5.9 64 Greenville, SC........... 12.1 228.3 2.7 30 770 5.2 85 Horry, SC................ 7.5 101.9 0.4 216 534 2.9 242 Lexington, SC............ 5.6 93.5 0.9 169 650 4.0 165 Richland, SC............. 8.8 201.8 -0.9 298 794 3.1 226 Spartanburg, SC.......... 5.8 110.9 1.5 106 761 2.6 264 Minnehaha, SD............ 6.5 111.9 1.4 118 748 4.9 99 Davidson, TN............. 18.1 415.0 1.0 158 927 3.2 219 Hamilton, TN............. 8.4 181.0 2.0 65 785 0.1 315 Knox, TN................. 10.7 215.4 1.9 74 750 3.0 236 Rutherford, TN........... 4.3 95.7 1.6 97 771 2.1 285 Shelby, TN............... 18.9 458.0 0.1 249 915 4.9 99 Williamson, TN........... 6.1 89.6 4.1 8 1,054 4.4 134 Bell, TX................. 4.7 106.9 2.4 42 736 4.1 157 Bexar, TX................ 33.8 730.6 1.4 118 838 6.5 45 Brazoria, TX............. 4.9 87.8 3.2 15 922 10.0 6 Brazos, TX............... 3.9 86.7 -1.1 304 659 3.0 236 Cameron, TX.............. 6.4 126.5 1.5 106 546 3.0 236 Collin, TX............... 18.2 291.0 3.1 17 1,075 5.8 70 Dallas, TX............... 67.9 1,416.9 1.9 74 1,156 5.2 85 Denton, TX............... 11.1 175.2 3.0 19 780 3.9 170 El Paso, TX.............. 13.8 272.8 0.8 180 626 3.3 213 Fort Bend, TX............ 9.2 133.0 2.4 42 979 8.2 16 Galveston, TX............ 5.3 95.1 2.6 34 827 4.4 134 Harris, TX............... 100.9 2,014.4 2.3 49 1,258 7.7 20 Hidalgo, TX.............. 11.0 226.0 2.3 49 556 3.2 219 Jefferson, TX............ 6.0 120.9 1.9 74 920 8.1 17 Lubbock, TX.............. 7.0 124.4 2.2 53 653 2.8 248 McLennan, TX............. 4.8 99.8 0.3 229 727 3.0 236 Montgomery, TX........... 8.7 130.8 3.0 19 886 7.9 18 Nueces, TX............... 7.9 152.7 -0.1 264 748 6.4 49 Smith, TX................ 5.4 92.0 0.9 169 739 3.8 180 Tarrant, TX.............. 37.6 750.5 1.7 86 900 3.3 213 Travis, TX............... 30.5 576.1 2.7 30 1,002 6.0 60 Webb, TX................. 4.8 87.6 2.4 42 590 4.8 105 Williamson, TX........... 7.6 128.4 3.0 19 953 -3.8 318 Davis, UT................ 7.1 100.8 (7) - 704 2.3 276 Salt Lake, UT............ 36.2 559.5 1.7 86 856 3.8 180 Utah, UT................. 12.5 164.9 3.1 17 681 3.7 183 Weber, UT................ 5.4 87.9 -0.1 264 642 2.4 272 Chittenden, VT........... 5.9 92.8 2.1 56 878 3.1 226 Arlington, VA............ 8.2 166.6 3.6 12 1,549 0.8 313 Chesterfield, VA......... 7.5 113.0 0.8 180 830 4.1 157 Fairfax, VA.............. 34.4 572.9 2.1 56 1,479 4.4 134 Henrico, VA.............. 9.7 171.5 1.2 139 1,027 6.3 51 Loudoun, VA.............. 9.7 134.7 4.2 6 1,093 2.1 285 Prince William, VA....... 7.6 108.3 4.3 3 808 1.3 306 Alexandria City, VA...... 6.2 93.6 (7) - 1,226 (7) - Chesapeake City, VA...... 5.7 94.0 1.0 158 724 4.2 148 Newport News City, VA.... 3.8 95.3 0.6 196 826 4.3 143 Norfolk City, VA......... 5.7 137.7 0.7 188 861 3.6 188 Richmond City, VA........ 7.0 148.5 1.1 148 1,071 4.9 99 Virginia Beach City, VA.. 11.2 159.4 -0.7 290 717 5.8 70 Benton, WA............... 5.7 80.8 4.3 3 959 4.8 105 Clark, WA................ 13.3 125.7 0.4 216 800 4.3 143 King, WA................. 83.1 1,117.2 1.8 80 1,185 5.6 77 Kitsap, WA............... 6.7 80.2 0.0 257 798 1.8 297 Pierce, WA............... 21.8 259.3 0.3 229 821 3.0 236 Snohomish, WA............ 19.2 241.1 2.1 56 968 8.8 11 Spokane, WA.............. 15.9 194.3 -0.6 287 751 4.6 116 Thurston, WA............. 7.4 96.5 0.3 229 800 1.0 310 Whatcom, WA.............. 7.0 77.7 1.6 97 745 6.7 41 Yakima, WA............... 8.9 95.0 1.2 139 606 2.2 279 Kanawha, WV.............. 5.9 104.4 1.2 139 797 5.1 89 Brown, WI................ 6.6 142.6 0.5 206 803 4.2 148 Dane, WI................. 14.0 293.6 1.5 106 878 6.2 55 Milwaukee, WI............ 21.6 464.6 1.0 158 929 7.2 29 Outagamie, WI............ 5.0 99.1 2.1 56 747 3.9 170 Waukesha, WI............. 12.7 217.9 2.4 42 902 3.9 170 Winnebago, WI............ 3.7 88.5 1.9 74 831 2.2 279 San Juan, PR............. 11.9 259.7 -2.5 (8) 598 -0.2 (8) (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 322 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, first quarter 2011(2) Employment Average weekly wage(3) Establishments, first quarter County by NAICS supersector 2011 Percent Percent (thousands) March change, First change, 2011 March quarter first (thousands) 2010-11(4) 2011 quarter 2010-11(4) United States(5)............................. 9,074.3 127,851.0 1.3 $935 5.2 Private industry........................... 8,776.1 106,054.4 1.8 941 5.7 Natural resources and mining............. 127.3 1,701.7 5.3 1,116 9.7 Construction............................. 774.2 5,137.6 -0.9 917 2.6 Manufacturing............................ 339.8 11,556.7 1.9 1,164 7.8 Trade, transportation, and utilities..... 1,875.9 24,316.5 1.3 766 5.5 Information.............................. 143.9 2,659.8 -1.8 1,609 9.7 Financial activities..................... 811.3 7,354.6 -0.3 1,886 10.2 Professional and business services....... 1,553.4 16,972.0 4.1 1,212 5.1 Education and health services............ 902.8 18,941.2 1.9 793 3.1 Leisure and hospitality.................. 752.2 12,842.6 2.3 363 2.8 Other services........................... 1,297.0 4,349.8 1.2 559 3.5 Government................................. 298.2 21,796.6 -1.3 902 2.0 Los Angeles, CA.............................. 438.0 3,887.9 1.0 1,046 6.6 Private industry........................... 432.4 3,321.8 1.6 1,030 7.6 Natural resources and mining............. 0.5 10.0 -0.9 1,645 7.2 Construction............................. 12.7 102.4 -2.8 1,000 4.0 Manufacturing............................ 13.2 368.7 -0.7 1,149 7.1 Trade, transportation, and utilities..... 51.5 735.0 1.7 804 5.8 Information.............................. 8.3 186.1 1.0 1,997 10.1 Financial activities..................... 22.1 209.6 -0.5 1,907 12.0 Professional and business services....... 41.2 546.4 2.1 1,265 6.2 Education and health services............ 28.8 511.8 2.7 912 4.9 Leisure and hospitality.................. 26.9 387.9 2.9 589 13.9 Other services........................... 205.8 243.0 -2.6 442 5.2 Government................................. 5.7 566.1 -2.4 1,139 2.5 Cook, IL..................................... 145.1 2,333.9 1.0 1,145 5.8 Private industry........................... 143.7 2,033.8 1.6 1,154 6.1 Natural resources and mining............. 0.1 0.8 -2.9 782 -5.1 Construction............................. 12.2 56.4 -2.8 1,276 -0.2 Manufacturing............................ 6.6 193.7 1.0 1,104 7.6 Trade, transportation, and utilities..... 28.1 427.4 1.5 841 8.5 Information.............................. 2.6 51.3 -1.1 1,849 8.4 Financial activities..................... 15.4 184.8 -2.0 2,867 15.7 Professional and business services....... 30.4 400.1 2.6 1,432 1.6 Education and health services............ 15.1 402.1 3.0 835 2.3 Leisure and hospitality.................. 12.6 219.8 2.4 422 5.0 Other services........................... 15.8 93.3 0.8 743 3.5 Government................................. 1.4 300.1 -2.8 1,085 (6) New York, NY................................. 121.9 2,304.1 1.9 2,634 9.2 Private industry........................... 121.6 1,865.2 3.0 2,995 8.9 Natural resources and mining............. 0.0 0.2 25.6 2,745 22.8 Construction............................. 2.2 29.7 -2.5 1,609 4.1 Manufacturing............................ 2.5 25.6 -1.3 1,644 9.1 Trade, transportation, and utilities..... 21.1 234.7 3.2 1,252 6.5 Information.............................. 4.4 131.8 1.1 2,751 11.4 Financial activities..................... 19.0 351.8 2.6 8,684 12.3 Professional and business services....... 25.4 460.8 2.9 2,512 3.5 Education and health services............ 9.3 302.8 0.7 1,065 5.1 Leisure and hospitality.................. 12.6 232.3 6.7 762 8.1 Other services........................... 18.9 87.4 2.1 1,270 7.2 Government................................. 0.3 438.9 -2.3 1,095 4.1 Harris, TX................................... 100.9 2,014.4 2.3 1,258 7.7 Private industry........................... 100.4 1,749.9 2.7 1,302 8.1 Natural resources and mining............. 1.6 77.4 7.3 4,206 7.5 Construction............................. 6.5 131.5 -2.4 1,092 2.7 Manufacturing............................ 4.5 172.6 4.0 1,607 9.4 Trade, transportation, and utilities..... 22.6 419.4 2.2 1,167 8.5 Information.............................. 1.3 28.2 -1.6 1,378 6.7 Financial activities..................... 10.5 111.6 -0.3 1,882 13.9 Professional and business services....... 20.0 326.7 5.3 1,441 (6) Education and health services............ 11.3 240.6 2.6 876 4.2 Leisure and hospitality.................. 8.1 180.9 3.0 384 0.8 Other services........................... 13.5 60.1 1.5 658 7.5 Government................................. 0.6 264.4 -0.6 968 3.1 Maricopa, AZ................................. 93.8 1,628.8 1.3 889 5.1 Private industry........................... 93.1 1,412.8 1.8 898 5.4 Natural resources and mining............. 0.5 7.6 5.0 1,152 16.4 Construction............................. 8.5 77.7 -2.5 884 1.7 Manufacturing............................ 3.2 107.8 1.0 1,439 13.6 Trade, transportation, and utilities..... 21.7 331.8 1.4 847 6.8 Information.............................. 1.5 27.0 0.6 1,208 6.5 Financial activities..................... 11.0 134.2 1.7 1,270 7.4 Professional and business services....... 22.0 264.7 2.7 925 3.0 Education and health services............ 10.4 237.5 2.9 864 1.6 Leisure and hospitality.................. 6.9 176.0 2.3 409 1.7 Other services........................... 6.6 47.9 2.4 585 5.0 Government................................. 0.7 215.9 -2.0 829 2.5 Dallas, TX................................... 67.9 1,416.9 1.9 1,156 5.2 Private industry........................... 67.3 1,248.2 2.2 1,180 5.5 Natural resources and mining............. 0.6 8.7 11.5 4,366 10.2 Construction............................. 4.0 66.2 0.2 960 2.8 Manufacturing............................ 2.9 113.7 -0.2 1,501 16.7 Trade, transportation, and utilities..... 14.8 280.1 1.8 982 3.9 Information.............................. 1.6 45.5 0.0 2,078 11.7 Financial activities..................... 8.4 137.6 0.9 1,879 8.3 Professional and business services....... 14.8 263.0 3.8 1,251 1.2 Education and health services............ 7.1 166.2 3.4 941 2.2 Leisure and hospitality.................. 5.6 127.8 3.3 474 -1.0 Other services........................... 7.1 38.8 2.2 628 3.6 Government................................. 0.5 168.7 -0.3 975 1.9 Orange, CA................................... 104.8 1,370.6 2.0 1,035 3.3 Private industry........................... 103.4 1,224.2 2.4 1,014 3.8 Natural resources and mining............. 0.2 4.3 -15.9 635 12.6 Construction............................. 6.3 67.1 -0.4 1,049 1.5 Manufacturing............................ 5.0 150.3 1.3 1,239 3.8 Trade, transportation, and utilities..... 16.1 242.5 0.4 944 5.4 Information.............................. 1.2 24.0 -3.1 1,796 -1.1 Financial activities..................... 9.7 103.4 1.7 1,629 2.5 Professional and business services....... 18.6 248.5 3.9 1,204 5.2 Education and health services............ 10.3 159.0 (6) 883 3.8 Leisure and hospitality.................. 7.2 168.9 3.6 408 4.9 Other services........................... 21.6 48.8 1.6 516 3.0 Government................................. 1.4 146.4 -1.6 1,214 0.9 San Diego, CA................................ 100.7 1,239.7 1.4 1,003 7.2 Private industry........................... 99.2 1,017.7 1.7 989 8.4 Natural resources and mining............. 0.7 11.4 2.8 491 1.2 Construction............................. 6.2 54.7 -0.2 1,033 5.5 Manufacturing............................ 3.0 92.5 -0.1 1,458 9.1 Trade, transportation, and utilities..... 13.6 195.4 0.9 797 7.3 Information.............................. 1.2 24.3 -2.6 1,624 12.5 Financial activities..................... 8.5 67.1 0.4 1,343 8.7 Professional and business services....... 16.0 210.1 2.2 1,432 13.4 Education and health services............ 8.4 146.5 2.9 880 4.0 Leisure and hospitality.................. 7.0 152.5 1.5 387 2.4 Other services........................... 28.3 56.7 0.7 499 4.2 Government................................. 1.4 222.0 0.0 1,068 2.2 King, WA..................................... 83.1 1,117.2 1.8 1,185 5.6 Private industry........................... 82.5 959.8 2.2 1,198 6.1 Natural resources and mining............. 0.4 2.5 -0.3 1,492 -3.4 Construction............................. 5.8 43.5 -4.5 1,108 0.1 Manufacturing............................ 2.3 97.6 0.8 1,579 14.0 Trade, transportation, and utilities..... 14.9 204.8 3.3 1,029 8.4 Information.............................. 1.8 79.0 1.0 2,280 5.2 Financial activities..................... 6.5 63.4 -1.7 1,647 6.9 Professional and business services....... 14.2 177.6 4.8 1,431 5.8 Education and health services............ 7.2 134.3 3.4 887 3.5 Leisure and hospitality.................. 6.5 105.3 1.3 424 -2.3 Other services........................... 22.9 51.7 2.7 591 2.1 Government................................. 0.6 157.4 -0.1 1,107 2.5 Miami-Dade, FL............................... 85.5 967.7 1.9 874 3.4 Private industry........................... 85.1 824.4 2.8 856 4.6 Natural resources and mining............. 0.5 10.0 3.6 409 10.5 Construction............................. 4.9 30.5 -2.5 872 6.0 Manufacturing............................ 2.6 35.1 -1.2 821 1.0 Trade, transportation, and utilities..... 24.3 243.2 3.2 799 5.1 Information.............................. 1.4 17.5 -1.3 1,424 3.1 Financial activities..................... 8.9 61.1 1.2 1,593 10.2 Professional and business services....... 17.8 126.5 3.6 1,024 2.9 Education and health services............ 9.6 152.7 2.6 831 5.6 Leisure and hospitality.................. 6.4 110.2 3.6 481 3.2 Other services........................... 7.7 36.0 4.1 523 1.0 Government................................. 0.4 143.3 -2.6 974 -1.6 (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. (2) Data are preliminary. Counties selected are based on 2010 annual average employment. (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, first quarter 2011(2) Employment Average weekly wage(3) Establishments, first quarter State 2011 Percent Percent (thousands) March change, First change, 2011 March quarter first (thousands) 2010-11 2011 quarter 2010-11 United States(4)......... 9,074.3 127,851.0 1.3 $935 5.2 Alabama.................. 116.3 1,808.5 0.3 766 4.2 Alaska................... 21.2 310.1 2.0 912 3.8 Arizona.................. 144.8 2,392.1 0.7 837 4.9 Arkansas................. 85.7 1,133.5 0.3 715 6.1 California............... 1,376.1 14,413.8 1.2 1,066 6.2 Colorado................. 169.0 2,179.8 1.3 952 4.4 Connecticut.............. 110.6 1,589.2 1.4 1,282 6.3 Delaware................. 28.3 396.0 2.1 1,026 5.7 District of Columbia..... 34.8 702.3 2.5 1,540 2.4 Florida.................. 591.2 7,235.9 1.2 794 3.8 Georgia.................. 266.7 3,771.0 1.4 885 5.7 Hawaii................... 38.6 593.8 1.2 790 3.1 Idaho.................... 54.2 590.3 -0.1 659 4.1 Illinois................. 382.7 5,472.4 1.2 1,003 6.0 Indiana.................. 159.7 2,717.1 1.9 772 4.5 Iowa..................... 93.7 1,419.3 0.6 738 4.5 Kansas................... 87.9 1,293.3 0.6 748 4.0 Kentucky................. 110.8 1,715.6 1.5 737 3.7 Louisiana................ 127.4 1,841.3 0.9 798 4.5 Maine.................... 49.5 558.6 0.1 723 4.8 Maryland................. 164.9 2,452.1 1.3 1,010 3.6 Massachusetts............ 226.4 3,116.5 1.2 1,159 5.8 Michigan................. 244.0 3,757.7 2.2 872 7.1 Minnesota................ 167.2 2,530.7 1.4 935 6.0 Mississippi.............. 69.1 1,074.8 0.6 650 3.2 Missouri................. 173.9 2,562.3 0.3 786 3.0 Montana.................. 42.0 412.2 0.4 656 3.6 Nebraska................. 60.0 886.2 0.7 721 3.9 Nevada................... 71.3 1,102.6 0.4 802 3.0 New Hampshire............ 47.5 596.3 1.1 876 5.2 New Jersey............... 265.0 3,701.1 0.0 1,160 3.5 New Mexico............... 54.7 776.5 -0.1 738 3.1 New York................. 596.9 8,336.5 1.2 1,368 6.7 North Carolina........... 252.3 3,809.6 1.6 825 4.3 North Dakota............. 26.6 364.5 5.0 748 9.5 Ohio..................... 286.5 4,870.6 1.4 819 4.6 Oklahoma................. 102.8 1,491.5 1.0 739 5.3 Oregon................... 131.0 1,590.3 1.3 812 4.6 Pennsylvania............. 344.7 5,459.3 1.5 896 4.6 Rhode Island............. 35.0 438.1 0.1 863 3.4 South Carolina........... 110.1 1,767.2 1.4 722 4.5 South Dakota............. 30.9 382.3 1.3 659 4.1 Tennessee................ 139.5 2,575.9 1.7 793 3.8 Texas.................... 577.2 10,324.3 2.2 946 5.9 Utah..................... 82.7 1,156.9 2.0 753 3.4 Vermont.................. 24.2 291.9 0.9 741 3.8 Virginia................. 233.1 3,539.9 1.5 968 4.0 Washington............... 235.3 2,785.3 1.2 947 5.2 West Virginia............ 48.5 689.3 1.0 723 4.5 Wisconsin................ 156.8 2,609.5 1.6 779 5.3 Wyoming.................. 25.0 265.2 1.0 808 4.4 Puerto Rico.............. 50.6 923.0 -2.6 500 0.8 Virgin Islands........... 3.5 45.1 0.4 738 1.0 (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.