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For release 10:00 a.m. (EDT), Friday, October 16, 2009 USDL-09-1241 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 2009 From March 2008 to March 2009, employment declined in 323 of the 334 largest U.S. counties according to preliminary data, the U.S. Bureau of Labor Statistics reported today. Elkhart County, Ind., located about 100 miles east of Chicago, posted the largest percentage decline, with a loss of 23.4 percent over the year, compared with a national job decrease of 4.2 percent. Nearly 80 percent of the employment decline in Elkhart occurred in manufacturing, which lost 22,100 jobs over the year. Arlington County, Va., experienced the largest over-the-year percentage increase in employment among the largest counties in the U.S., with a gain of 2.6 percent. The U.S. average weekly wage fell by 2.5 percent in the first quarter of 2009. This is the largest over-the-year decline in U.S. average weekly wages dating back to 1978, when these quarterly data were first comparable. (See Technical Note.) The financial activities supersector sustained the largest decline in average weekly wages, with a decrease of 15.9 percent. Total wages for this industry fell by $37.9 billion over the year. New York County, N.Y., had the largest over-the-year decrease in average weekly wages in the first quarter of 2009, with a loss of 23.4 percent. The area’s substantial over-the-year wage declines, which were largely attributable to lower bonus payments in financial activities, had a significant impact on the national average weekly wage trend in the first quarter of 2009. Excluding New York County, the national average weekly wage decrease is 1.3 percent--a difference of 1.2 percentage points. Table A. Top 10 large counties ranked by March 2009 employment, March 2008-09 employment decrease, and March 2008-09 percent decrease in employment -------------------------------------------------------------------------------------------------------- Employment in large counties -------------------------------------------------------------------------------------------------------- March 2009 employment | Decrease in employment, | Percent decrease in employment, (thousands) | March 2008-09 | March 2008-09 | (thousands) | -------------------------------------------------------------------------------------------------------- | | United States 128,992.2| United States -5,676.3| United States -4.2 -------------------------------------------------------------------------------------------------------- | | Los Angeles, Calif. 3,996.3| Los Angeles, Calif. -206.5| Elkhart, Ind. -23.4 Cook, Ill. 2,381.5| Maricopa, Ariz. -133.9| Macomb, Mich. -10.8 New York, N.Y. 2,290.3| Cook, Ill. -108.4| Marion, Fla. -10.5 Harris, Texas 2,028.4| Orange, Calif. -102.8| Washoe, Nev. -10.4 Maricopa, Ariz. 1,671.0| New York, N.Y. -84.9| Horry, S.C. -10.2 Dallas, Texas 1,425.7| Clark, Nev. -83.3| Seminole, Fla. -9.7 Orange, Calif. 1,399.5| Miami-Dade, Fla. -62.8| Ottawa, Mich. -9.7 San Diego, Calif. 1,263.0| San Diego, Calif. -61.6| Catawba, N.C. -9.7 King, Wash. 1,135.9| Wayne, Mich. -59.0| Lee, Fla. -9.5 Miami-Dade, Fla. 963.9| Broward, Fla. -58.6| Sarasota, Fla. -9.5 | | -------------------------------------------------------------------------------------------------------- Of the 334 largest counties in the United States (as measured by 2008 annual average employment), 154 had over-the-year percentage changes in employment equal to or below the national average (-4.2 percent) in March 2009; 178 large counties experienced changes above the national average. The percent change in average weekly wages was equal to or lower than the national average (-2.5 percent) in 76 of the largest U.S. counties but was above the national average in 255 counties. The employment and average weekly wage data by county are compiled under the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from reports submitted by every employer subject to unemployment insurance (UI) laws. The 9.1 million employer reports cover 129 million full- and part-time workers. Large County Employment In March 2009, national employment, as measured by the QCEW program, was 129 million, down by 4.2 percent from March 2008. The 334 U.S. counties with 75,000 or more employees accounted for 71.5 percent of total U.S. employment and 77.7 percent of total wages. These 334 counties had a net job decline of 4,160,200 over the year, accounting for 73.3 percent of the overall U.S. employment decrease. Employment declined in 323 counties from March 2008 to March 2009. The largest percentage decline in employment was in Elkhart, Ind. (-23.4 percent). Macomb, Mich., had the next largest percentage decline (-10.8 percent), followed by the counties of Marion, Fla. (-10.5 percent), Washoe, Nev. (-10.4 percent), and Horry, S.C. (-10.2 percent). The largest decline in employment levels occurred in Los Angeles, Calif. (-206,500), followed by the counties of Maricopa, Ariz. (-133,900), Cook, Ill. (-108,400), Orange, Calif. (-102,800), and New York, N.Y. (-84,900). (See table A.) Combined employment losses in these five counties over the year totaled 636,500 or 11.2 percent of the employment decline for the U.S. as a whole. Employment rose in eight of the large counties from March 2008 to March 2009. None of the large counties grew by more than three percent over the year. Arlington, Va., had the largest over-the-year percentage increase in employment (2.6 percent) among the largest counties in the U.S. Montgomery, Texas, had the next largest increase (1.5 percent), followed by the counties of Fort Bend, Texas (1.2 percent), Bronx, N.Y. (1.1 percent), and Anchorage, Alaska, and East Baton Rouge, La. (0.3 percent each). The largest gains in the level of employment from March 2008 to March 2009 were recorded in the counties of Arlington, Va. (3,900), Bronx, N.Y. (2,400), Montgomery, Texas (1,900), Fort Bend, Texas (1,500), and East Baton Rouge, La. (900). Table B. Top 10 large counties ranked by first quarter 2009 average weekly wages, first quarter 2008-09 decrease in average weekly wages, and first quarter 2008-09 percent decrease in average weekly wages -------------------------------------------------------------------------------------------------------- Average weekly wage in large counties -------------------------------------------------------------------------------------------------------- Average weekly wage, | Decrease in average weekly | Percent decrease in average first quarter 2009 | wage, first quarter 2008-09 | weekly wage, first | | quarter 2008-09 -------------------------------------------------------------------------------------------------------- | | United States $882| United States -$23| United States -2.5 -------------------------------------------------------------------------------------------------------- | | New York, N.Y. $2,149| New York, N.Y. -$657| New York, N.Y. -23.4 San Mateo, Calif. 1,786| Fairfield, Conn. -192| Mecklenburg, N.C. -10.3 Fairfield, Conn. 1,735| Suffolk, Mass. -155| Fairfield, Conn. -10.0 Somerset, N.J. 1,734| Hudson, N.J. -150| Hudson, N.J. -9.7 Suffolk, Mass. 1,558| Mecklenburg, N.C. -121| Suffolk, Mass. -9.0 San Francisco, Calif. 1,523| San Francisco, Calif. -100| Westmoreland, Pa. -8.9 Santa Clara, Calif. 1,519| Westchester, N.Y. -92| Elkhart, Ind. -8.7 Arlington, Va. 1,472| Hennepin, Minn. -80| Trumbull, Ohio -7.1 Washington, D.C. 1,461| Union, N.J. -72| Westchester, N.Y. -7.0 Hudson, N.J. 1,394| Santa Clara, Calif. -70| Hennepin, Minn. -6.7 Morris, N.J. 1,394| | | | -------------------------------------------------------------------------------------------------------- Large County Average Weekly Wages Average weekly wages for the nation fell 2.5 percent over the year in the first quarter of 2009. This is the largest over-the-year decline in U.S. average weekly wages dating back to 1978. During that time span, over-the- year declines in average weekly wages occurred in only two other quarters: first quarter 1993 (-0.9 percent) and fourth quarter 1994 (-1.1 percent). The average weekly wages in those two quarters declined because employment growth outpaced total wage growth; in the first quarter of 2009, both employment and wages decreased. Among the 334 largest counties, 202 had over-the-year decreases in average weekly wages this quarter. The largest wage losses occurred in New York, N.Y., with a decline of 23.4 percent from the first quarter of 2008. Mecklenburg, N.C., had the second largest decline (-10.3 percent), followed by the counties of Fairfield, Conn. (-10.0 percent), Hudson, N.J. (-9.7 percent), and Suffolk, Mass. (-9.0 percent). (See table B.) Of the 334 largest counties, 120 experienced growth in average weekly wages. San Mateo, Calif., led the nation in growth in average weekly wages with an increase of 23.7 percent from the first quarter of 2008. Benton, Ark., was second with a gain of 16.7 percent, followed by the counties of Solano, Calif. (16.0 percent), Pulaski, Ark. (10.7 percent), and Peoria, Ill. (6.2 percent). The national average weekly wage in the first quarter of 2009 was $882. Average weekly wages were higher than the national average in 103 of the 334 largest U.S. counties. Three of the five counties with the highest average weekly wages in the nation were also among the five counties with the largest over-the-year losses in average weekly wages. Despite suffering the largest average weekly wage losses in the nation, New York, N.Y., held the top position among the highest-paid large counties with an average weekly wage of $2,149. San Mateo, Calif., was second with an average weekly wage of $1,786, followed by Fairfield, Conn. ($1,735), Somerset, N.J. ($1,734), and Suffolk, Mass. ($1,558). There were 230 counties with an average weekly wage below the national average in the first quarter of 2009. The lowest average weekly wage was reported in Horry, S.C. ($525), followed by the counties of Cameron, Texas ($527), Hidalgo, Texas ($538), Webb, Texas ($552), and Lake, Fla. ($576). (See table 1.) Average weekly wages are affected not only by changes in total wages but also by employment changes in high- and low-paying industries. (See Technical Note.) The 2.5-percent over-the-year decrease in average weekly wages for the nation was partially due to large employment declines in high- paying industries such as manufacturing. (See table 2.) Ten Largest U.S. Counties All of the 10 largest counties (based on 2008 annual average employment levels) experienced over-the-year percent declines in employment in March 2009. Maricopa, Ariz., experienced the largest decline in employment among the 10 largest counties with a 7.4 percent decrease. Within Maricopa, every private industry group except education and health services experienced employment declines, with construction experiencing the largest decline (-30.7 percent). (See table 2.) Orange, Calif., had the next largest decline in employment, -6.8 percent, followed by Miami-Dade, Fla. (-6.1 percent). Harris, Texas, experienced the smallest decline in employment (-1.1 percent) among the 10 largest counties. Dallas, Texas (-3.3 percent), and New York, N.Y. (-3.6 percent), had the second and third smallest employment losses, respectively. Nine of the 10 largest U.S. counties saw an over-the-year decrease in average weekly wages. The nation-leading 23.4-percent wage decrease in New York, N.Y., was fueled by significant wage losses in the finance industry (-35.2 percent). New York’s average weekly wage loss was followed by Cook, Ill. (-5.4 percent), and Dallas, Texas (-3.3 percent). San Diego, Calif., had the smallest decrease in wages (-1.1 percent), followed by Miami-Dade, Fla. (-1.2 percent). The only wage increase occurred in King, Wash. (0.2 percent). Largest County by State Table 3 shows March 2009 employment and the 2009 first quarter average weekly wage in the largest county in each state, which is based on 2008 annual average employment levels. The employment levels in the counties in table 3 in March 2009 ranged from approximately four million in Los Angeles County, Calif., to 42,900 in Laramie County, Wyo. The highest average weekly wage of these counties was in New York, N.Y. ($2,149), while the lowest average weekly wage was in Yellowstone, Mont. ($697). For More Information The tables included in this release contain data for the nation and for the 334 U.S. counties with annual average employment levels of 75,000 or more in 2008. March 2009 employment and 2009 first-quarter average weekly wages for all states are provided in table 4 of this release. For additional information about the quarterly employment and wages data, please read the Technical Note. Data for the first quarter of 2009 and final data for 2008 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 2009 is scheduled to be released on Wednesday, January 13, 2010. ---------------------------------------------------------------------- | | | County Changes for the 2009 | | County Employment and Wages News Releases | | | | Counties with annual average employment of 75,000 or more in 2008 | | are included in this release and will be included in future 2009 | | releases. For 2009 data, two counties have been added to the | | publication tables: Johnson, Iowa, and Gregg, Texas. Two counties, | | Boone, Ky., and St. Tammany, La., will be excluded from 2009 | | releases. | | | ----------------------------------------------------------------------
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 unem- ployment 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 cov- ered by UI. QCEW data in this release are based on the 2007 North American Industry Classification System. Data for 2009 are preliminary and subject to revision. For purposes of this release, large counties are defined as having employment levels of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are provided, but not used in calculating U.S. av- erages, rankings, or in the analysis in the text. Each year, these large counties are selected on the basis of the preliminary annual av- erage of employment for the previous year. The 335 counties presented in this release were derived using 2008 preliminary annual averages of employment. For 2009 data, two counties have been added to the publi- cation tables: Johnson, Iowa, and Gregg, Texas. These counties will be included in all 2009 quarterly releases. Two counties, Boone, Ky., and St. Tammany, La., which were published in the 2008 releases, will be excluded from this and future 2009 releases because their 2008 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 em- ployment from the preceding year. The preliminary QCEW data presented in this release may differ from data released by the individual states. These potential differences result from the states' continuing receipt of UI data over time and ongoing review and editing. The individual states determine their data release timetables. Differences between QCEW, BED, and CES employment measures The Bureau publishes three different establishment-based employment measures for any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED), and Current Employment Statistics (CES)-- makes use of the quarterly UI employment reports in producing data; however, each measure has a somewhat different universe coverage, es- timation 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 differences and the intended uses of the program products. (See table.) Additional information 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 9.1 | ministrative records| ments | million establish- | submitted by 7.0 | | ments in first | million private-sec-| | quarter 2009 | 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 civilian workers covered by the Unemployment Compensation for Federal Employees (UCFE) program, employment and wage data are compiled from quarterly reports submitted by four major fed- eral 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 es- tablishments. QCEW employment and wage data are derived from microdata summaries of 9.1 million employer reports of employment and wages sub- mitted by states to the BLS in 2008. These reports are based on place of employment 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 Un- employment Tax Act became effective, expanding coverage to include most State and local government employees. In 2008, UI and UCFE pro- grams covered workers in 134.8 million jobs. The estimated 129.4 mil- lion workers in these jobs (after adjustment for multiple jobholders) represented 95.5 percent of civilian wage and salary employment. Cov- ered workers received $6.142 trillion in pay, representing 93.8 per- cent of the wage and salary component of personal income and 42.5 per- cent 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. Coverage changes may affect the over-the-year comparisons presented in this news release. Concepts and methodology Monthly employment is based on the number of workers who worked dur- ing or received pay for the pay period including the 12th of the month. With few exceptions, all employees of covered firms are re- ported, 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 em- ployees, as described above) and dividing the result by 13, for the 13 weeks in the quarter. These calculations are made using unrounded em- ployment and wage values. The average wage values that can be calcu- lated 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 compensation 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 le- vels. 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 quar- ter. For instance, the average weekly wage of the work force could in- crease significantly when there is a large decline in the number of employees that had been receiving below-average wages. Wages may in- clude 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 weekly wage levels between industries, states, or quarters, these factors should be taken into consideration. Federal government pay levels are subject to periodic, sometimes large, fluctuations due to a calendar effect that consists of some quarters having more pay periods than others. Most federal employees are paid on a 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 at- tributed, in part, to a comparison of quarterly wages for the current year, which include seven pay periods, with year-ago wages that re- flect only six pay periods. An opposite effect will occur when wages in the current period, which contain six pay periods, are compared with year-ago wages that include seven pay periods. The effect on over-the-year pay comparisons can be pronounced in federal government due to the uniform nature of federal payroll processing. This pattern may exist in private sector pay; however, because there are more pay period types (weekly, biweekly, semimonthly, monthly) it is less pro- nounced. 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 veri- fy with employers 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 individual establishment records and reflect the number of es- tablishments 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 adminis- trative changes. For example, economic change would come from a firm relocating into the county; administrative change would come from a company correcting its county designation. The over-the-year changes of employment and wages presented in this release have been adjusted to account for most of the administrative corrections made to the underlying establishment reports. This is done by modifying the prior-year levels used to calculate the over-the-year changes. Percent changes are calculated using an adjusted version of the final 2008 quarterly data as the base data. The adjusted prior- year levels used to calculate the over-the-year percent change in em- ployment and wages are not published. These adjusted prior-year levels do not match the unadjusted data maintained on the BLS Web site. Over- the-year change calculations based on data from the Web site, or from data published in prior BLS news releases, may differ substantially from the over-the-year changes presented in this news release. The adjusted data used to calculate the over-the-year change measures presented in this release account for most of the administrative changes--those occurring when employers update the industry, location, and ownership information of their establishments. The most common ad- justments for administrative change are the result of updated informa- tion about the county location of individual establishments. Included in these adjustments are administrative changes involving the classi- fication of establishments that were previously reported in the un- known or statewide county or unknown industry categories. Beginning with the first quarter of 2008, adjusted data account for administra- tive 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 pe- riod) used in that particular release. Comparisons may not be valid for any time period other than the one featured in a release even if the changes were calculated using adjusted data. County definitions are assigned according to Federal Information Processing Standards Publications (FIPS PUBS) as issued by the Nation- al Institute of Standards and Technology, after approval by the Secre- tary of Commerce pursuant to Section 5131 of the Information Technolo- gy Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104-106. Areas shown as counties include those desig- nated 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 compara- tive 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 in- formation by detailed industry on establishments, employment, and wag- es for the nation and all states. The 2007 edition of this bulletin contains selected data produced by Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the first quar- ter 2008 version of this news release. Tables and additional content from the 2007 Employment and Wages Annual Bulletin are now available online at http://www.bls.gov/cew/cewbultn07.htm. These tables present final 2007 annual averages. The tables are included on the CD which accompanies the hardcopy version of the Annual Bulletin. Em- ployment and Wages Annual Averages, 2007 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 request from the Division of Administrative Statistics and Labor Turnover (Business Employment Dynamics), telephone (202) 691-6467; (http://www.bls.gov/bdm/); (e-mail: BDMInfo@bls.gov). Information in this release will be made available to sensory im- paired individuals upon request. Voice phone: (202) 691-5200; TDD mes- sage referral phone number: 1-800-877-8339.
Table 1. Covered(1) establishments, employment, and wages in the 335 largest counties, first quarter 2009(2) Employment Average weekly wage(4) Establishments, County(3) first quarter Percent Ranking Percent Ranking 2009 March change, by Average change, by (thousands) 2009 March percent weekly first percent (thousands) 2008-09(5) change wage quarter change 2008-09(5) United States(6)......... 9,113.9 128,992.2 -4.2 - $882 -2.5 - Jefferson, AL............ 18.6 341.2 -5.1 242 890 -2.5 256 Madison, AL.............. 8.9 178.7 -1.8 38 930 1.3 49 Mobile, AL............... 10.0 168.9 -4.1 174 713 0.4 96 Montgomery, AL........... 6.5 131.4 -5.2 249 726 0.4 96 Shelby, AL............... 5.0 72.1 -5.1 242 867 -1.0 183 Tuscaloosa, AL........... 4.4 83.4 -3.7 137 731 2.0 30 Anchorage Borough, AK.... 8.1 144.8 0.3 5 928 1.3 49 Maricopa, AZ............. 104.0 1,671.0 -7.4 304 854 -1.3 200 Pima, AZ................. 21.2 356.5 -5.1 242 746 -3.7 290 Benton, AR............... 5.6 91.4 -4.6 211 1,029 16.7 2 Pulaski, AR.............. 15.0 244.7 -2.3 62 877 10.7 4 Washington, AR........... 5.8 88.8 -3.3 111 684 -1.0 183 Alameda, CA.............. 54.4 647.7 -6.1 276 1,109 -3.1 275 Butte, CA................ 8.1 71.2 -5.4 259 654 2.5 21 Contra Costa, CA......... 30.5 324.8 -5.0 235 1,088 -1.6 229 Fresno, CA............... 31.0 327.1 -4.3 189 688 -0.3 137 Kern, CA................. 18.4 258.0 -3.8 148 767 1.1 59 Los Angeles, CA.......... 431.2 3,996.3 -4.9 229 967 -2.4 252 Marin, CA................ 11.9 103.2 -5.3 255 1,051 -1.9 240 Monterey, CA............. 12.9 151.1 -6.1 276 789 -0.9 178 Orange, CA............... 102.3 1,399.5 -6.8 294 992 -2.7 260 Placer, CA............... 11.0 127.5 -7.7 308 844 1.1 59 Riverside, CA............ 48.8 575.6 -8.3 318 743 -0.7 160 Sacramento, CA........... 55.1 605.3 -4.5 205 970 0.6 86 San Bernardino, CA....... 51.0 619.9 -6.4 284 735 -0.7 160 San Diego, CA............ 99.6 1,263.0 -4.7 216 934 -1.1 187 San Francisco, CA........ 52.5 551.7 -3.5 122 1,523 -6.2 319 San Joaquin, CA.......... 18.2 207.8 -5.0 235 723 -0.8 173 San Luis Obispo, CA...... 9.9 100.9 -4.8 221 753 1.1 59 San Mateo, CA............ 24.2 326.4 -4.8 221 1,786 23.7 1 Santa Barbara, CA........ 14.4 177.6 -4.7 216 826 0.9 73 Santa Clara, CA.......... 61.4 863.3 -5.3 255 1,519 -4.4 301 Santa Cruz, CA........... 9.1 88.7 -4.2 179 818 0.2 109 Solano, CA............... 10.3 121.1 -4.4 200 1,016 16.0 3 Sonoma, CA............... 18.9 178.0 -7.3 301 807 -1.3 200 Stanislaus, CA........... 15.2 160.5 -6.3 283 717 0.7 83 Tulare, CA............... 9.7 136.9 -4.7 216 603 -0.7 160 Ventura, CA.............. 24.0 304.7 -5.7 267 912 -1.7 234 Yolo, CA................. 6.1 96.9 -3.8 148 808 0.2 109 Adams, CO................ 9.1 149.7 -4.6 211 798 -1.4 206 Arapahoe, CO............. 19.3 270.7 -4.2 179 1,074 -0.2 134 Boulder, CO.............. 12.9 153.5 -3.7 137 1,016 -4.0 296 Denver, CO............... 25.6 424.1 -4.3 189 1,139 -2.7 260 Douglas, CO.............. 9.5 88.9 -3.8 148 990 3.9 8 El Paso, CO.............. 17.3 234.2 -4.1 174 797 1.1 59 Jefferson, CO............ 18.3 203.7 -3.1 103 894 -1.2 196 Larimer, CO.............. 10.2 124.9 -2.6 75 762 0.8 77 Weld, CO................. 6.0 80.5 -2.7 79 723 1.0 68 Fairfield, CT............ 33.0 401.5 -4.0 169 1,735 -10.0 329 Hartford, CT............. 25.6 488.4 -3.1 103 1,142 -3.9 294 New Haven, CT............ 22.6 350.6 -4.4 200 911 -1.1 187 New London, CT........... 7.0 125.9 -2.4 69 941 0.0 121 New Castle, DE........... 18.2 268.1 -5.2 249 1,114 -0.8 173 Washington, DC........... 33.3 679.2 -0.1 10 1,461 -1.9 240 Alachua, FL.............. 6.8 116.6 -5.0 235 740 2.4 24 Brevard, FL.............. 14.9 192.1 -6.9 298 788 1.7 35 Broward, FL.............. 64.1 699.1 -7.7 308 812 -0.7 160 Collier, FL.............. 12.2 122.6 -8.6 320 722 -3.9 294 Duval, FL................ 27.3 444.0 -5.2 249 848 -4.3 299 Escambia, FL............. 8.2 120.0 -7.4 304 678 0.6 86 Hillsborough, FL......... 38.0 585.9 -7.5 306 859 1.8 32 Lake, FL................. 7.5 82.7 -6.8 294 576 -2.9 268 Lee, FL.................. 19.5 201.9 -9.5 323 694 -3.3 278 Leon, FL................. 8.3 139.1 -4.2 179 726 1.7 35 Manatee, FL.............. 9.5 114.8 -6.0 274 646 -1.8 237 Marion, FL............... 8.4 94.2 -10.5 330 608 0.2 109 Miami-Dade, FL........... 84.7 963.9 -6.1 276 858 -1.2 196 Okaloosa, FL............. 6.1 77.1 -4.0 169 693 1.6 37 Orange, FL............... 36.0 653.8 -7.7 308 785 -1.5 217 Palm Beach, FL........... 50.2 510.7 -7.8 311 844 -1.5 217 Pasco, FL................ 10.2 96.8 -7.3 301 603 1.5 41 Pinellas, FL............. 31.6 402.3 -6.7 291 740 -0.4 143 Polk, FL................. 12.8 197.8 -6.5 286 652 -1.2 196 Sarasota, FL............. 15.1 140.5 -9.5 323 718 0.0 121 Seminole, FL............. 14.5 161.6 -9.7 325 735 -0.9 178 Volusia, FL.............. 14.1 155.3 -7.8 311 606 -1.6 229 Bibb, GA................. 4.7 80.8 -4.3 189 691 0.3 102 Chatham, GA.............. 7.8 129.7 -5.9 268 734 1.8 32 Clayton, GA.............. 4.5 108.4 -4.8 221 772 -4.9 307 Cobb, GA................. 21.0 302.6 -5.4 259 951 -1.2 196 De Kalb, GA.............. 18.0 282.7 -5.1 242 939 -1.1 187 Fulton, GA............... 39.6 711.1 -5.0 235 1,212 -3.7 290 Gwinnett, GA............. 24.1 300.0 -6.8 294 853 -2.3 250 Muscogee, GA............. 4.8 92.5 -4.5 205 693 -1.7 234 Richmond, GA............. 4.8 99.6 -2.8 87 728 0.3 102 Honolulu, HI............. 24.8 438.9 -3.4 117 801 0.4 96 Ada, ID.................. 14.8 194.0 -7.3 301 749 0.7 83 Champaign, IL............ 4.2 88.3 -3.5 122 729 3.1 12 Cook, IL................. 141.1 2,381.5 -4.4 200 1,084 -5.4 311 Du Page, IL.............. 36.2 556.2 -5.5 264 1,028 -3.4 281 Kane, IL................. 12.8 192.7 -7.2 300 755 -0.7 160 Lake, IL................. 21.2 311.0 -5.0 235 1,120 -1.4 206 McHenry, IL.............. 8.5 94.3 -5.9 268 705 -3.3 278 McLean, IL............... 3.7 84.3 -1.4 29 893 -2.7 260 Madison, IL.............. 5.9 91.9 -4.3 189 714 1.4 46 Peoria, IL............... 4.8 100.5 -4.3 189 895 6.2 5 Rock Island, IL.......... 3.5 75.5 -4.8 221 888 2.9 15 St. Clair, IL............ 5.5 94.2 -2.3 62 696 3.6 10 Sangamon, IL............. 5.3 126.3 -1.9 44 863 1.6 37 Will, IL................. 14.1 187.2 -3.7 137 749 -1.1 187 Winnebago, IL............ 7.0 126.1 -6.7 291 743 -1.1 187 Allen, IN................ 9.1 169.4 -5.1 242 717 -1.5 217 Elkhart, IN.............. 5.0 92.0 -23.4 332 642 -8.7 325 Hamilton, IN............. 7.9 108.1 -3.1 103 837 -6.5 321 Lake, IN................. 10.4 184.2 -4.6 211 756 0.4 96 Marion, IN............... 24.2 547.1 -4.2 179 932 -2.5 256 St. Joseph, IN........... 6.1 115.1 -6.2 281 715 -3.2 277 Tippecanoe, IN........... 3.3 73.7 -2.7 79 764 0.0 121 Vanderburgh, IN.......... 4.8 102.9 -3.6 126 709 -2.7 260 Johnson, IA.............. 3.5 74.9 0.2 7 769 1.3 49 Linn, IA................. 6.3 123.9 -0.2 12 825 -1.1 187 Polk, IA................. 14.9 265.9 -2.0 48 892 -1.3 200 Scott, IA................ 5.3 84.7 -3.9 161 695 -0.1 130 Johnson, KS.............. 20.6 302.4 -3.6 126 906 -3.5 284 Sedgwick, KS............. 12.3 251.6 -2.8 87 789 -5.4 311 Shawnee, KS.............. 4.9 93.1 -1.5 32 748 1.9 31 Wyandotte, KS............ 3.2 78.4 -1.4 29 771 -4.2 298 Fayette, KY.............. 9.3 168.0 -4.5 205 776 1.4 46 Jefferson, KY............ 22.0 407.6 -4.3 189 841 -0.9 178 Caddo, LA................ 7.4 122.4 -2.4 69 699 0.6 86 Calcasieu, LA............ 4.9 86.0 -1.4 29 758 2.2 26 East Baton Rouge, LA..... 14.4 263.0 0.3 5 829 1.5 41 Jefferson, LA............ 13.9 195.3 -2.1 51 799 0.4 96 Lafayette, LA............ 8.9 133.8 -0.7 15 827 1.3 49 Orleans, LA.............. 10.5 168.9 -0.6 14 959 -4.7 304 Cumberland, ME........... 12.2 163.7 -3.4 117 794 -3.5 284 Anne Arundel, MD......... 14.5 225.0 -3.5 122 929 -0.3 137 Baltimore, MD............ 21.4 363.1 -3.8 148 887 -1.4 206 Frederick, MD............ 6.0 91.3 -3.3 111 886 2.7 18 Harford, MD.............. 5.6 79.9 -2.5 74 810 -1.5 217 Howard, MD............... 8.8 142.2 -3.7 137 1,038 0.9 73 Montgomery, MD........... 32.7 444.0 -2.0 48 1,234 -0.6 153 Prince Georges, MD....... 15.8 305.1 -3.0 99 921 1.1 59 Baltimore City, MD....... 13.9 326.8 -3.6 126 1,011 -2.0 243 Barnstable, MA........... 9.0 78.5 -5.2 249 742 -0.7 160 Bristol, MA.............. 15.3 204.9 -5.0 235 747 -2.9 268 Essex, MA................ 20.7 286.3 -3.5 122 895 -3.0 270 Hampden, MA.............. 14.6 191.4 -2.8 87 794 -3.6 287 Middlesex, MA............ 47.3 791.7 -3.0 99 1,276 -0.5 149 Norfolk, MA.............. 23.2 308.5 -3.1 103 1,020 -4.0 296 Plymouth, MA............. 13.6 167.5 -3.4 117 787 -1.4 206 Suffolk, MA.............. 21.7 574.8 -2.4 69 1,558 -9.0 327 Worcester, MA............ 20.6 306.8 -3.7 137 858 -1.8 237 Genesee, MI.............. 7.7 127.1 -5.9 268 715 -4.4 301 Ingham, MI............... 6.7 151.5 -5.4 259 812 -0.6 153 Kalamazoo, MI............ 5.5 108.3 -5.9 268 784 1.8 32 Kent, MI................. 14.2 302.4 -8.1 315 780 0.8 77 Macomb, MI............... 17.5 270.5 -10.8 331 849 -3.0 270 Oakland, MI.............. 38.8 618.3 -7.8 311 973 -4.8 306 Ottawa, MI............... 5.7 95.9 -9.7 325 695 -2.1 246 Saginaw, MI.............. 4.3 77.6 -6.4 284 698 -2.8 264 Washtenaw, MI............ 8.1 181.7 -3.4 117 932 -1.3 200 Wayne, MI................ 31.8 671.7 -8.1 315 936 (7) - Anoka, MN................ 7.5 106.2 -5.3 255 796 -0.1 130 Dakota, MN............... 10.3 166.4 -3.6 126 860 -1.1 187 Hennepin, MN............. 41.2 800.8 -4.4 200 1,108 -6.7 322 Olmsted, MN.............. 3.4 87.3 -1.9 44 933 2.6 19 Ramsey, MN............... 14.9 315.9 -3.8 148 1,011 0.7 83 St. Louis, MN............ 5.8 91.7 -4.3 189 710 2.6 19 Stearns, MN.............. 4.4 76.0 -5.4 259 697 1.6 37 Harrison, MS............. 4.6 83.3 -4.2 179 676 1.3 49 Hinds, MS................ 6.3 126.2 -0.7 15 759 0.9 73 Boone, MO................ 4.5 80.5 -2.6 75 661 1.1 59 Clay, MO................. 4.9 86.5 -3.6 126 785 -3.4 281 Greene, MO............... 8.1 150.1 -3.6 126 644 0.8 77 Jackson, MO.............. 18.4 357.0 -3.7 137 897 0.3 102 St. Charles, MO.......... 8.2 118.3 -3.3 111 714 -4.3 299 St. Louis, MO............ 32.2 578.1 -3.9 161 960 0.6 86 St. Louis City, MO....... 8.5 222.0 -5.3 255 1,024 -1.3 200 Yellowstone, MT.......... 5.8 75.1 -2.7 79 697 0.1 114 Douglas, NE.............. 15.7 310.5 -2.1 51 855 4.9 6 Lancaster, NE............ 8.1 153.6 -2.4 69 681 -0.4 143 Clark, NV................ 50.4 834.2 -9.1 321 814 -4.7 304 Washoe, NV............... 14.6 187.8 -10.4 329 785 -1.4 206 Hillsborough, NH......... 12.2 187.9 -3.6 126 927 -5.5 314 Rockingham, NH........... 10.7 128.9 -4.3 189 823 -2.1 246 Atlantic, NJ............. 7.0 134.0 -6.2 281 745 -5.6 315 Bergen, NJ............... 34.3 428.5 -3.9 161 1,109 -3.1 275 Burlington, NJ........... 11.4 195.7 -3.9 161 915 -1.5 217 Camden, NJ............... 13.0 197.1 -4.8 221 877 0.1 114 Essex, NJ................ 21.2 346.5 -3.8 148 1,153 -3.8 292 Gloucester, NJ........... 6.3 100.4 -3.1 103 776 -1.1 187 Hudson, NJ............... 14.0 232.5 -2.9 97 1,394 -9.7 328 Mercer, NJ............... 11.1 224.9 -2.6 75 1,157 -5.3 310 Middlesex, NJ............ 21.9 380.5 -5.9 268 1,135 -1.5 217 Monmouth, NJ............. 20.7 243.5 -4.3 189 918 -1.5 217 Morris, NJ............... 18.0 272.7 -3.7 137 1,394 -1.6 229 Ocean, NJ................ 12.3 140.8 -3.8 148 721 -0.8 173 Passaic, NJ.............. 12.5 167.8 -5.9 268 909 1.2 58 Somerset, NJ............. 10.3 167.8 -3.2 109 1,734 -2.0 243 Union, NJ................ 14.9 218.5 -5.5 264 1,116 -6.1 317 Bernalillo, NM........... 17.8 317.7 -4.2 179 770 1.6 37 Albany, NY............... 10.0 222.4 -1.8 38 881 2.1 27 Bronx, NY................ 16.3 228.7 1.1 4 803 -0.6 153 Broome, NY............... 4.5 92.3 -3.0 99 692 -0.6 153 Dutchess, NY............. 8.3 112.2 -2.7 79 900 -0.7 160 Erie, NY................. 23.7 444.3 -2.1 51 759 -0.7 160 Kings, NY................ 47.4 474.9 -0.7 15 725 -1.0 183 Monroe, NY............... 18.1 369.9 -1.8 38 828 -3.8 292 Nassau, NY............... 52.5 582.9 -2.6 75 962 0.1 114 New York, NY............. 119.1 2,290.3 -3.6 126 2,149 -23.4 331 Oneida, NY............... 5.3 107.1 -2.2 57 678 0.1 114 Onondaga, NY............. 12.8 243.0 -2.8 87 800 0.0 121 Orange, NY............... 10.0 127.0 -2.8 87 726 0.3 102 Queens, NY............... 44.0 489.5 -2.7 79 828 -2.8 264 Richmond, NY............. 8.8 91.2 -2.3 62 733 -1.5 217 Rockland, NY............. 9.9 111.7 -2.8 87 927 -0.7 160 Saratoga, NY............. 5.4 73.2 -2.2 57 724 -1.8 237 Suffolk, NY.............. 50.5 597.4 -3.6 126 922 2.8 16 Westchester, NY.......... 36.4 401.9 -3.8 148 1,224 -7.0 323 Buncombe, NC............. 8.2 110.5 -4.1 174 655 -0.3 137 Catawba, NC.............. 4.6 78.6 -9.7 325 625 -5.4 311 Cumberland, NC........... 6.4 118.6 -0.4 13 659 0.3 102 Durham, NC............... 7.2 181.9 -1.0 22 1,224 -2.8 264 Forsyth, NC.............. 9.3 179.4 -3.7 137 805 -3.0 270 Guilford, NC............. 14.9 263.7 -6.0 274 757 -1.7 234 Mecklenburg, NC.......... 33.5 543.6 -4.6 211 1,058 -10.3 330 New Hanover, NC.......... 7.6 97.2 -6.8 294 706 0.6 86 Wake, NC................. 29.3 432.4 -4.0 169 880 0.2 109 Cass, ND................. 5.8 97.0 -1.1 23 717 0.1 114 Butler, OH............... 7.4 137.3 -6.1 276 769 -0.5 149 Cuyahoga, OH............. 37.6 693.4 -4.5 205 892 -1.5 217 Franklin, OH............. 29.9 651.7 -3.1 103 897 -0.8 173 Hamilton, OH............. 23.9 491.6 -3.8 148 949 -1.4 206 Lake, OH................. 6.7 94.6 -4.1 174 720 -1.4 206 Lorain, OH............... 6.3 92.5 -5.2 249 716 -0.3 137 Lucas, OH................ 10.8 198.6 -6.5 286 772 0.0 121 Mahoning, OH............. 6.4 95.8 -4.3 189 622 0.8 77 Montgomery, OH........... 12.8 244.1 -5.6 266 777 -3.0 270 Stark, OH................ 9.0 151.2 -5.4 259 677 0.4 96 Summit, OH............... 15.0 257.0 -5.1 242 811 -0.2 134 Trumbull, OH............. 4.7 69.3 -8.4 319 659 -7.1 324 Warren, OH............... 4.3 72.2 -4.3 189 730 -1.6 229 Oklahoma, OK............. 23.7 415.2 -1.9 44 790 -0.1 130 Tulsa, OK................ 19.5 337.5 -3.3 111 802 -2.0 243 Clackamas, OR............ 12.7 140.2 -7.1 299 779 -1.3 200 Jackson, OR.............. 6.5 75.3 -7.9 314 628 1.1 59 Lane, OR................. 10.9 135.8 -9.3 322 655 -0.3 137 Marion, OR............... 9.3 131.2 -5.1 242 689 2.1 27 Multnomah, OR............ 27.9 425.8 -4.9 229 873 -1.4 206 Washington, OR........... 16.0 233.2 -6.5 286 1,006 -1.4 206 Allegheny, PA............ 35.2 664.9 -1.8 38 953 0.5 94 Berks, PA................ 9.1 160.9 -4.2 179 764 -0.7 160 Bucks, PA................ 19.8 249.5 -4.8 221 845 -0.7 160 Butler, PA............... 4.8 77.3 -1.9 44 736 -0.7 160 Chester, PA.............. 15.2 235.7 -2.3 62 1,114 -0.4 143 Cumberland, PA........... 6.0 121.0 -3.7 137 797 1.1 59 Dauphin, PA.............. 7.4 176.6 -2.2 57 848 0.6 86 Delaware, PA............. 13.6 203.2 -2.8 87 941 -2.4 252 Erie, PA................. 7.4 121.5 -3.3 111 688 0.6 86 Lackawanna, PA........... 5.9 98.9 -2.8 87 646 0.0 121 Lancaster, PA............ 12.4 217.7 -4.2 179 720 -1.5 217 Lehigh, PA............... 8.8 169.4 -3.8 148 858 -1.4 206 Luzerne, PA.............. 7.9 137.0 -1.8 38 668 -0.9 178 Montgomery, PA........... 27.5 467.1 -3.7 137 1,162 -2.4 252 Northampton, PA.......... 6.5 96.7 -3.2 109 769 -0.1 130 Philadelphia, PA......... 31.1 624.5 -1.1 23 1,050 -1.4 206 Washington, PA........... 5.4 77.5 -1.3 26 783 2.5 21 Westmoreland, PA......... 9.4 130.3 -2.7 79 689 -8.9 326 York, PA................. 9.1 169.6 -4.1 174 756 -0.3 137 Kent, RI................. 5.6 73.2 -6.6 290 758 -2.1 246 Providence, RI........... 17.8 265.6 -4.9 229 865 -3.5 284 Charleston, SC........... 12.0 201.7 -4.7 216 739 0.8 77 Greenville, SC........... 12.5 226.2 -6.1 276 731 -0.7 160 Horry, SC................ 8.1 104.0 -10.2 328 525 -0.9 178 Lexington, SC............ 5.6 94.6 -3.9 161 629 -1.6 229 Richland, SC............. 9.3 207.9 -4.2 179 782 1.0 68 Spartanburg, SC.......... 6.1 112.4 -8.2 317 749 -3.6 287 Minnehaha, SD............ 6.4 113.1 -0.7 15 720 -1.9 240 Davidson, TN............. 18.5 420.5 -3.8 148 876 -1.1 187 Hamilton, TN............. 8.6 180.0 -6.5 286 754 1.3 49 Knox, TN................. 11.1 217.6 -4.8 221 715 0.1 114 Rutherford, TN........... 4.3 93.4 -7.6 307 737 -0.5 149 Shelby, TN............... 19.8 478.5 -4.8 221 861 -3.4 281 Williamson, TN........... 6.1 84.8 -2.8 87 949 0.0 121 Bell, TX................. 4.6 102.7 0.0 9 680 1.5 41 Bexar, TX................ 32.7 717.8 -1.5 32 774 -1.5 217 Brazoria, TX............. 4.7 85.4 -2.8 87 821 -5.1 309 Brazos, TX............... 3.9 86.6 (7) - 644 (7) - Cameron, TX.............. 6.4 122.5 -2.3 62 527 0.8 77 Collin, TX............... 17.3 283.2 (7) - 1,030 (7) - Dallas, TX............... 67.9 1,425.7 -3.3 111 1,085 -3.3 278 Denton, TX............... 10.7 166.6 -1.6 34 763 0.1 114 El Paso, TX.............. 13.6 266.8 -2.1 51 603 0.3 102 Fort Bend, TX............ 8.5 129.9 1.2 3 956 -0.6 153 Galveston, TX............ 5.2 90.5 -6.7 291 864 3.1 12 Gregg, TX................ 4.0 72.9 -2.9 97 736 -0.4 143 Harris, TX............... 97.9 2,028.4 -1.1 23 1,143 -2.6 258 Hidalgo, TX.............. 10.6 218.9 -1.7 35 538 1.3 49 Jefferson, TX............ 5.9 124.0 -0.8 19 863 1.1 59 Lubbock, TX.............. 6.8 123.1 -0.1 10 633 1.3 49 McLennan, TX............. 4.8 101.0 -1.3 26 696 0.6 86 Montgomery, TX........... 8.3 126.9 1.5 2 794 -1.0 183 Nueces, TX............... 8.0 154.1 -1.3 26 734 -2.8 264 Potter, TX............... 3.8 75.3 0.2 7 714 -0.4 143 Smith, TX................ 5.3 92.3 -1.8 38 720 1.3 49 Tarrant, TX.............. 37.3 752.4 -2.2 57 862 -2.3 250 Travis, TX............... 29.3 563.2 -2.2 57 950 -2.6 258 Webb, TX................. 4.8 86.4 -2.3 62 552 -0.4 143 Williamson, TX........... 7.3 119.7 -1.7 35 857 -6.2 319 Davis, UT................ 7.2 97.5 -4.5 205 682 0.9 73 Salt Lake, UT............ 37.4 561.4 -4.2 179 820 1.0 68 Utah, UT................. 12.8 164.5 -5.0 235 659 1.5 41 Weber, UT................ 5.6 90.7 -4.9 229 625 1.0 68 Chittenden, VT........... 6.0 91.3 -2.4 69 869 -3.0 270 Arlington, VA............ 7.8 157.3 2.6 1 1,472 0.0 121 Chesterfield, VA......... 7.6 115.0 -4.0 169 784 -0.8 173 Fairfax, VA.............. 34.2 568.5 -2.1 51 1,389 0.3 102 Henrico, VA.............. 9.7 173.4 -3.7 137 947 -5.0 308 Loudoun, VA.............. 9.2 128.2 -1.7 35 1,053 -4.6 303 Prince William, VA....... 7.4 100.0 -3.0 99 773 1.4 46 Alexandria City, VA...... 6.2 98.0 -0.9 20 1,200 1.5 41 Chesapeake City, VA...... 5.8 94.7 -4.6 211 701 4.2 7 Newport News City, VA.... 4.0 96.0 -3.6 126 790 -0.5 149 Norfolk City, VA......... 5.9 140.0 -2.1 51 851 3.0 14 Richmond City, VA........ 7.4 152.5 -3.9 161 1,035 -6.1 317 Virginia Beach City, VA.. 11.6 163.9 -4.7 216 687 1.0 68 Clark, WA................ 12.0 126.4 -4.0 169 772 0.5 94 King, WA................. 75.4 1,135.9 -3.9 161 1,127 0.2 109 Kitsap, WA............... 6.4 81.6 -2.7 79 771 3.8 9 Pierce, WA............... 20.2 264.6 -3.6 126 797 -0.6 153 Snohomish, WA............ 17.5 241.2 -5.2 249 893 -0.2 134 Spokane, WA.............. 15.0 199.8 -4.4 200 724 3.3 11 Thurston, WA............. 6.8 98.2 -2.3 62 786 2.1 27 Whatcom, WA.............. 6.7 79.5 -3.9 161 702 2.8 16 Yakima, WA............... 7.9 94.2 -3.8 148 600 2.4 24 Kanawha, WV.............. 6.0 106.0 -0.9 20 785 2.5 21 Brown, WI................ 6.6 142.5 -3.4 117 775 -1.5 217 Dane, WI................. 13.8 292.1 -2.7 79 840 -2.1 246 Milwaukee, WI............ 20.7 471.9 -4.5 205 882 -0.6 153 Outagamie, WI............ 5.0 100.0 -3.8 148 717 -2.4 252 Racine, WI............... 4.1 70.7 -4.9 229 756 -3.6 287 Waukesha, WI............. 12.9 220.5 -4.9 229 866 0.0 121 Winnebago, WI............ 3.7 86.6 -2.0 48 777 -5.7 316 San Juan, PR............. 12.6 275.5 -2.7 (8) 593 0.2 (8) (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 334 U.S. counties comprise 71.5 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 2009(2) Employment Average weekly wage(3) Establishments, first quarter County by NAICS supersector 2009 Percent Percent (thousands) March change, Average change, 2009 March weekly first (thousands) 2008-09(4) wage quarter 2008-09(4) United States(5)............................. 9,113.9 128,992.2 -4.2 $882 -2.5 Private industry........................... 8,819.8 106,866.1 -5.1 882 -3.3 Natural resources and mining............. 126.3 1,670.1 -3.8 993 -2.3 Construction............................. 860.9 5,937.8 -15.4 906 0.9 Manufacturing............................ 356.4 12,096.6 -10.6 1,062 -1.3 Trade, transportation, and utilities..... 1,912.2 24,597.3 -5.5 733 -1.6 Information.............................. 148.0 2,858.8 -5.0 1,439 -2.0 Financial activities..................... 853.1 7,651.3 -4.4 1,596 -15.9 Professional and business services....... 1,533.8 16,534.8 -6.4 1,129 -0.2 Education and health services............ 861.3 18,245.7 2.2 776 1.2 Leisure and hospitality.................. 739.1 12,715.3 -3.1 351 -2.2 Other services........................... 1,234.6 4,357.1 -2.1 543 -0.5 Government................................. 294.2 22,126.1 0.5 884 1.6 Los Angeles, CA.............................. 431.2 3,996.3 -4.9 967 -2.4 Private industry........................... 427.3 3,395.0 -5.7 945 -3.0 Natural resources and mining............. 0.5 10.7 -6.2 1,479 -15.8 Construction............................. 14.0 123.3 -17.4 973 0.3 Manufacturing............................ 14.4 401.4 -9.3 1,063 -1.8 Trade, transportation, and utilities..... 54.0 744.8 -7.2 776 -1.5 Information.............................. 8.9 197.3 -7.3 1,755 1.8 Financial activities..................... 24.0 223.4 -6.8 1,577 -12.1 Professional and business services....... 43.3 541.8 -8.3 1,149 -2.1 Education and health services............ 28.6 499.8 1.1 865 2.4 Leisure and hospitality.................. 27.5 384.1 -3.9 519 -2.4 Other services........................... 202.9 258.5 3.0 424 -3.9 Government................................. 3.9 601.3 -0.3 1,090 -0.2 Cook, IL..................................... 141.1 2,381.5 -4.4 1,084 -5.4 Private industry........................... 139.8 2,069.2 -5.0 1,093 -6.3 Natural resources and mining............. 0.1 0.9 -3.7 792 -12.8 Construction............................. 12.3 71.9 -14.4 1,317 0.5 Manufacturing............................ 6.9 206.7 -9.5 1,013 -4.1 Trade, transportation, and utilities..... 27.5 438.8 -6.5 797 -4.3 Information.............................. 2.6 53.5 (6) 1,644 -8.7 Financial activities..................... 15.6 197.7 -5.0 2,397 -17.4 Professional and business services....... 29.1 398.3 -8.0 1,403 -0.6 Education and health services............ 14.1 385.9 3.1 839 1.0 Leisure and hospitality.................. 11.9 216.4 -3.6 404 -2.9 Other services........................... 14.7 94.8 -1.4 729 1.1 Government................................. 1.4 312.3 0.0 1,022 1.6 New York, NY................................. 119.1 2,290.3 -3.6 2,149 -23.4 Private industry........................... 118.8 1,837.8 -4.4 2,425 -24.9 Natural resources and mining............. 0.0 0.2 1.3 1,967 -16.9 Construction............................. 2.4 34.0 -7.2 1,479 -6.4 Manufacturing............................ 2.9 30.4 -15.3 1,365 -8.3 Trade, transportation, and utilities..... 21.7 230.7 -6.6 1,136 -5.4 Information.............................. 4.5 129.0 -4.7 2,449 -7.9 Financial activities..................... 19.0 355.9 -6.2 6,379 -35.2 Professional and business services....... 25.4 463.7 -5.6 2,095 -10.2 Education and health services............ 8.8 293.9 0.7 998 0.8 Leisure and hospitality.................. 11.9 208.9 -3.0 725 -5.0 Other services........................... 18.2 86.9 -1.3 999 -9.0 Government................................. 0.3 452.6 0.0 1,017 1.2 Harris, TX................................... 97.9 2,028.4 -1.1 1,143 -2.6 Private industry........................... 97.4 1,766.7 -1.5 1,175 -3.1 Natural resources and mining............. 1.5 82.8 (6) 3,483 -5.5 Construction............................. 6.7 149.0 -6.5 1,051 0.0 Manufacturing............................ 4.6 182.5 -2.0 1,411 -7.0 Trade, transportation, and utilities..... 22.3 418.9 -1.5 1,029 -3.1 Information.............................. 1.4 31.3 -3.4 1,314 -3.2 Financial activities..................... 10.5 116.2 -3.9 1,511 -12.7 Professional and business services....... 19.6 321.4 -4.5 1,321 2.1 Education and health services............ 10.4 224.3 3.9 851 1.3 Leisure and hospitality.................. 7.7 179.8 1.2 374 -2.3 Other services........................... 11.9 59.1 0.3 628 -0.8 Government................................. 0.5 261.7 2.2 926 3.7 Maricopa, AZ................................. 104.0 1,671.0 -7.4 854 -1.3 Private industry........................... 103.3 1,444.9 -8.6 852 -1.3 Natural resources and mining............. 0.5 8.5 -1.0 855 -14.2 Construction............................. 10.8 100.5 -30.7 877 -0.9 Manufacturing............................ 3.5 111.9 -11.2 1,227 -2.1 Trade, transportation, and utilities..... 23.2 344.5 -7.7 801 -0.7 Information.............................. 1.7 29.0 -5.0 1,166 0.0 Financial activities..................... 12.8 137.5 -4.9 1,145 -7.5 Professional and business services....... 23.0 270.4 -11.5 896 3.1 Education and health services............ 10.3 214.8 3.6 875 0.0 Leisure and hospitality.................. 7.5 178.1 -5.2 398 -1.7 Other services........................... 7.3 47.8 -6.5 567 -1.2 Government................................. 0.7 226.1 0.5 868 -1.3 Dallas, TX................................... 67.9 1,425.7 -3.3 1,085 -3.3 Private industry........................... 67.3 1,257.6 -3.8 1,103 -3.9 Natural resources and mining............. 0.6 8.3 (6) 3,066 -13.0 Construction............................. 4.3 76.3 -9.8 942 -0.8 Manufacturing............................ 3.1 123.7 -8.2 1,267 -3.8 Trade, transportation, and utilities..... 15.0 287.9 (6) 964 -4.1 Information.............................. 1.7 46.7 -6.5 1,823 (6) Financial activities..................... 8.7 140.3 (6) 1,632 -13.3 Professional and business services....... 14.8 255.0 -6.4 1,219 -2.5 Education and health services............ 6.7 154.6 4.5 920 3.1 Leisure and hospitality.................. 5.4 126.3 (6) 499 -1.4 Other services........................... 6.7 37.7 -3.0 624 0.8 Government................................. 0.5 168.0 0.7 950 3.6 Orange, CA................................... 102.3 1,399.5 -6.8 992 -2.7 Private industry........................... 100.9 1,244.8 -7.4 967 -3.6 Natural resources and mining............. 0.2 5.1 -16.0 561 -3.4 Construction............................. 6.9 78.3 -18.1 1,072 -1.0 Manufacturing............................ 5.3 159.9 -8.8 1,148 -3.1 Trade, transportation, and utilities..... 17.3 253.7 -8.5 916 -0.1 Information.............................. 1.4 28.2 -4.8 1,567 0.8 Financial activities..................... 10.7 106.7 (6) 1,502 -12.0 Professional and business services....... 19.4 244.0 -10.4 1,121 -2.4 Education and health services............ 10.2 150.7 1.7 873 1.6 Leisure and hospitality.................. 7.2 167.0 -4.7 382 -3.3 Other services........................... 19.2 47.7 -3.0 513 -4.6 Government................................. 1.4 154.7 -1.8 1,188 1.5 San Diego, CA................................ 99.6 1,263.0 -4.7 934 -1.1 Private industry........................... 98.3 1,035.8 -5.5 916 -1.9 Natural resources and mining............. 0.7 9.7 -13.8 540 0.7 Construction............................. 7.0 64.1 -18.1 975 -0.3 Manufacturing............................ 3.1 99.3 (6) 1,309 0.2 Trade, transportation, and utilities..... 14.4 197.1 -7.9 744 (6) Information.............................. 1.3 37.8 -1.2 1,604 -16.1 Financial activities..................... 9.4 71.4 -6.0 1,257 -5.6 Professional and business services....... 16.5 201.2 -6.9 1,208 2.7 Education and health services............ 8.3 142.2 3.2 851 1.7 Leisure and hospitality.................. 7.0 152.2 -5.6 393 -6.9 Other services........................... 27.6 57.4 0.2 466 -2.1 Government................................. 1.3 227.2 -0.4 1,017 2.7 King, WA..................................... 75.4 1,135.9 -3.9 1,127 0.2 Private industry........................... 74.9 979.2 -4.6 1,136 -0.5 Natural resources and mining............. 0.4 2.8 -9.6 1,553 -1.2 Construction............................. 6.4 57.1 -18.7 1,130 4.1 Manufacturing............................ 2.4 104.2 -7.2 1,366 -5.5 Trade, transportation, and utilities..... 14.7 206.7 -5.7 967 1.5 Information.............................. 1.8 80.7 4.0 2,125 -0.9 Financial activities..................... 6.8 69.7 -6.7 1,579 -5.0 Professional and business services....... 13.6 176.9 -6.8 1,311 0.2 Education and health services............ 6.6 130.4 5.1 857 2.4 Leisure and hospitality.................. 6.1 105.0 -4.2 422 -5.8 Other services........................... 16.3 45.8 0.6 634 5.8 Government................................. 0.5 156.6 0.8 1,074 6.0 Miami-Dade, FL............................... 84.7 963.9 -6.1 858 -1.2 Private industry........................... 84.4 813.6 -6.9 818 -1.8 Natural resources and mining............. 0.5 10.0 -8.8 403 -12.6 Construction............................. 6.1 37.7 -25.4 861 6.6 Manufacturing............................ 2.6 38.4 -16.7 783 0.3 Trade, transportation, and utilities..... 23.0 238.8 -6.0 765 -0.6 Information.............................. 1.5 18.5 -7.1 1,308 -3.5 Financial activities..................... 9.8 63.7 -9.0 1,353 -9.7 Professional and business services....... 17.7 124.5 -8.7 992 0.1 Education and health services............ 9.4 144.1 1.8 801 1.0 Leisure and hospitality.................. 5.9 102.0 -4.2 471 -1.5 Other services........................... 7.5 35.3 -5.5 529 -0.4 Government................................. 0.4 150.3 -1.7 1,074 0.8 (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. (2) Data are preliminary. (3) Average weekly wages were calculated using unrounded data. (4) 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 in the largest county by state, first quarter 2009(2) Employment Average weekly wage(4) Establishments, first quarter County(3) 2009 Percent Percent (thousands) March change, Average change, 2009 March weekly first (thousands) 2008-09(5) wage quarter 2008-09(5) United States(6)......... 9,113.9 128,992.2 -4.2 $882 -2.5 Jefferson, AL............ 18.6 341.2 -5.1 890 -2.5 Anchorage Borough, AK.... 8.1 144.8 0.3 928 1.3 Maricopa, AZ............. 104.0 1,671.0 -7.4 854 -1.3 Pulaski, AR.............. 15.0 244.7 -2.3 877 10.7 Los Angeles, CA.......... 431.2 3,996.3 -4.9 967 -2.4 Denver, CO............... 25.6 424.1 -4.3 1,139 -2.7 Hartford, CT............. 25.6 488.4 -3.1 1,142 -3.9 New Castle, DE........... 18.2 268.1 -5.2 1,114 -0.8 Washington, DC........... 33.3 679.2 -0.1 1,461 -1.9 Miami-Dade, FL........... 84.7 963.9 -6.1 858 -1.2 Fulton, GA............... 39.6 711.1 -5.0 1,212 -3.7 Honolulu, HI............. 24.8 438.9 -3.4 801 0.4 Ada, ID.................. 14.8 194.0 -7.3 749 0.7 Cook, IL................. 141.1 2,381.5 -4.4 1,084 -5.4 Marion, IN............... 24.2 547.1 -4.2 932 -2.5 Polk, IA................. 14.9 265.9 -2.0 892 -1.3 Johnson, KS.............. 20.6 302.4 -3.6 906 -3.5 Jefferson, KY............ 22.0 407.6 -4.3 841 -0.9 East Baton Rouge, LA..... 14.4 263.0 0.3 829 1.5 Cumberland, ME........... 12.2 163.7 -3.4 794 -3.5 Montgomery, MD........... 32.7 444.0 -2.0 1,234 -0.6 Middlesex, MA............ 47.3 791.7 -3.0 1,276 -0.5 Wayne, MI................ 31.8 671.7 -8.1 936 (7) Hennepin, MN............. 41.2 800.8 -4.4 1,108 -6.7 Hinds, MS................ 6.3 126.2 -0.7 759 0.9 St. Louis, MO............ 32.2 578.1 -3.9 960 0.6 Yellowstone, MT.......... 5.8 75.1 -2.7 697 0.1 Douglas, NE.............. 15.7 310.5 -2.1 855 4.9 Clark, NV................ 50.4 834.2 -9.1 814 -4.7 Hillsborough, NH......... 12.2 187.9 -3.6 927 -5.5 Bergen, NJ............... 34.3 428.5 -3.9 1,109 -3.1 Bernalillo, NM........... 17.8 317.7 -4.2 770 1.6 New York, NY............. 119.1 2,290.3 -3.6 2,149 -23.4 Mecklenburg, NC.......... 33.5 543.6 -4.6 1,058 -10.3 Cass, ND................. 5.8 97.0 -1.1 717 0.1 Cuyahoga, OH............. 37.6 693.4 -4.5 892 -1.5 Oklahoma, OK............. 23.7 415.2 -1.9 790 -0.1 Multnomah, OR............ 27.9 425.8 -4.9 873 -1.4 Allegheny, PA............ 35.2 664.9 -1.8 953 0.5 Providence, RI........... 17.8 265.6 -4.9 865 -3.5 Greenville, SC........... 12.5 226.2 -6.1 731 -0.7 Minnehaha, SD............ 6.4 113.1 -0.7 720 -1.9 Shelby, TN............... 19.8 478.5 -4.8 861 -3.4 Harris, TX............... 97.9 2,028.4 -1.1 1,143 -2.6 Salt Lake, UT............ 37.4 561.4 -4.2 820 1.0 Chittenden, VT........... 6.0 91.3 -2.4 869 -3.0 Fairfax, VA.............. 34.2 568.5 -2.1 1,389 0.3 King, WA................. 75.4 1,135.9 -3.9 1,127 0.2 Kanawha, WV.............. 6.0 106.0 -0.9 785 2.5 Milwaukee, WI............ 20.7 471.9 -4.5 882 -0.6 Laramie, WY.............. 3.2 42.9 -1.4 714 1.7 San Juan, PR............. 12.6 275.5 -2.7 593 0.2 St. Thomas, VI........... 1.9 23.3 -3.5 629 -1.1 (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. (2) Data are preliminary. (3) Includes areas not officially designated as counties. See Technical Note. (4) 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.
Table 4. Covered(1) establishments, employment, and wages by state, first quarter 2009(2) Employment Average weekly wage(3) Establishments, first quarter State 2009 Percent Percent (thousands) March change, Average change, 2009 March weekly first (thousands) 2008-09 wage quarter 2008-09 United States(4)......... 9,113.9 128,992.2 -4.2 $882 -2.5 Alabama.................. 119.2 1,844.6 -5.2 736 -0.4 Alaska................... 21.3 303.5 0.1 887 2.5 Arizona.................. 164.6 2,459.7 -6.9 807 -1.3 Arkansas................. 86.4 1,144.5 -2.9 695 4.2 California............... 1,369.6 14,742.5 -5.0 994 -1.2 Colorado................. 176.6 2,211.0 -3.9 913 -0.8 Connecticut.............. 113.0 1,620.1 -3.8 1,189 -5.6 Delaware................. 29.3 399.9 -5.1 975 -0.8 District of Columbia..... 33.3 679.2 -0.1 1,461 -1.9 Florida.................. 612.2 7,352.2 -7.0 771 -0.8 Georgia.................. 274.4 3,835.9 -5.4 831 -1.4 Hawaii................... 39.2 599.1 -4.9 775 0.4 Idaho.................... 56.7 603.4 -6.3 638 0.3 Illinois................. 372.2 5,552.0 -4.2 951 -3.0 Indiana.................. 161.3 2,701.1 -5.6 739 -2.4 Iowa..................... 94.6 1,432.5 -2.5 709 -0.1 Kansas................... 87.3 1,326.2 -2.6 719 -2.3 Kentucky................. 109.1 1,710.0 -4.6 712 -0.3 Louisiana................ 124.2 1,867.4 -1.1 772 0.8 Maine.................... 51.0 563.1 -3.7 688 -1.9 Maryland................. 164.5 2,452.8 -3.1 964 0.1 Massachusetts............ 213.0 3,102.8 -3.3 1,101 -3.7 Michigan................. 253.8 3,765.9 -7.2 825 -3.7 Minnesota................ 168.6 2,538.5 -4.0 882 -2.9 Mississippi.............. 71.0 1,087.9 -4.5 633 -0.2 Missouri................. 173.7 2,618.3 -3.4 771 0.1 Montana.................. 42.9 413.9 -4.2 628 0.5 Nebraska................. 59.6 894.8 -2.0 699 1.7 Nevada................... 76.6 1,150.8 -9.1 810 -3.5 New Hampshire............ 48.8 601.2 -3.2 837 -3.0 New Jersey............... 271.3 3,775.1 -4.0 1,100 -2.8 New Mexico............... 54.9 794.1 -3.5 723 0.7 New York................. 588.1 8,332.4 -2.6 1,207 -13.8 North Carolina........... 260.6 3,852.4 -5.2 766 -2.8 North Dakota............. 25.6 341.8 -0.4 666 2.0 Ohio..................... 293.6 4,937.1 -4.9 790 -1.0 Oklahoma................. 100.5 1,517.0 -2.0 709 -0.3 Oregon................... 130.7 1,602.8 -6.3 772 -0.6 Pennsylvania............. 342.4 5,449.4 -2.9 862 -0.7 Rhode Island............. 35.5 441.8 -4.9 831 -2.4 South Carolina........... 115.3 1,779.4 -5.9 692 -0.4 South Dakota............. 30.6 382.9 -1.7 630 -0.3 Tennessee................ 142.7 2,586.1 -5.7 751 -1.3 Texas.................... 564.9 10,237.9 -1.8 886 -1.9 Utah..................... 85.3 1,162.2 -4.6 726 1.1 Vermont.................. 24.8 291.7 -3.2 719 -2.0 Virginia................. 232.6 3,541.6 -3.0 920 0.1 Washington............... 216.4 2,810.6 -3.8 906 0.8 West Virginia............ 48.4 690.2 -1.4 704 4.0 Wisconsin................ 156.8 2,619.0 -4.3 747 -1.6 Wyoming.................. 25.1 272.1 -2.0 778 -0.1 Puerto Rico.............. 53.4 967.1 -4.1 496 1.4 Virgin Islands........... 3.6 44.6 -4.3 685 -3.1 (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) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.