Technical information: (202) 691-6567 USDL 06-1859 http://www.bls.gov/cew/ For release: 10:00 A.M. EDT Media contact: 691-5902 Thursday, October 26, 2006 COUNTY EMPLOYMENT AND WAGES: FIRST QUARTER 2006 In March 2006, Collin County, Texas, had the largest over-the-year percentage increase in employment among the largest counties in the U.S., according to preliminary data released today by the Bureau of Labor Statistics of the U.S. Department of Labor. Collin County, a Dallas suburb, experienced an over-the-year employment gain of 7.8 percent compared with national job growth of 2.2 percent. Orleans County (New Orleans), La., had the largest over-the-year gain in average weekly wages in the first quarter of 2006, with an increase of 33.3 percent. The high average weekly wage growth rate for Orleans County was related to the disproportionate job and pay losses in lower-paid industries due to the impact of Hurricane Katrina. The U.S. average weekly wage increased by 8.1 percent over the same time span. Of the 325 largest counties in the United States, as measured by 2005 annual average employment, 133 had over-the-year percentage growth in em- ployment above the national average in March 2006, and 184 experienced changes below the national average. Average weekly wages grew faster than the national average in 127 of the largest U.S. counties, while the percent change in average weekly wages was below the national average in 193 counties. The employment and average weekly wage data by county are compiled under the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from reports submitted by every employer subject to unemployment insurance (UI) laws. The 8.8 million em- ployer reports cover 132.6 million full- and part-time workers. The at- tached tables contain data for the nation and for the 325 U.S. counties with annual average employment levels of 75,000 or more in 2005. March 2006 employment and 2006 first-quarter average weekly wages for all states are provided in table 4 of this release. Data for all states, metropolitan statistical areas, counties, and the nation through the fourth quarter of 2005 are available on the BLS Web site at http://www.bls.gov/cew/. Prelim- inary data for first quarter of 2006 and final data for 2005 will be avail- able later in October on the BLS Web site. Large County Employment In March 2006, national employment, as measured by the QCEW program, was 132.6 million, up by 2.2 percent from March 2005. The 325 U.S. counties with 75,000 or more employees accounted for 70.9 percent of total U.S. covered employment and 77.7 percent of total covered wages. These 325 counties had a net job gain of 1,864,798 over the year, accounting for 65.4 percent of the U.S. employment increase. Employment increased in 289 of the large counties from March 2005 to March 2006. Collin, Texas, had the largest over-the-year percentage increase in employment (7.8 percent). Lee, Fla., had the next largest increase, 7.7 percent, followed by the counties of Brazoria, Texas (7.5 percent), and Manatee, Fla., and Clark, Nev. (7.2 percent each). (See table 1.) ------------------------------------------------------------------- | | | County Changes for the 2006 County Employment and Wages News | | Releases: Four Counties Added and One County Dropped | | | | Counties with employment of 75,000 or more are included in | | this release. For 2006 data, four counties have been added to | | the publication tables: Douglas, Colo., Weld, Colo., Boone, Ky., | | and Butler, Pa. One county, Potter, Texas, which had data for | | 2005 published in the 2005 releases, will be excluded from this | | and future 2006 releases because it no longer has an employment | | level of 75,000 or more. | | | ------------------------------------------------------------------- - 2 - Table A. Top 10 large counties ranked by March 2006 employment, March 2005-06 employment growth, and March 2005-06 percent growth in employment ------------------------------------------------------------------------------------- Employment in large counties ------------------------------------------------------------------------------------- March 2006 employment | Growth in employment, | Percent growth (thousands) | March 2005-06 | in employment, | (thousands) | March 2005-06 ------------------------------------------------------------------------------------- | | U.S. 132,613.1| U.S. 2,852.5| U.S. 2.2 -----------------------------|----------------------------|------------------------- | | Los Angeles, Calif. 4,179.3| Los Angeles, Calif. 107.7| Collin, Texas 7.8 Cook, Ill. 2,502.0| Maricopa, Ariz. 102.1| Lee, Fla. 7.7 New York, N.Y. 2,271.0| Harris, Texas 83.0| Brazoria, Texas 7.5 Harris, Texas 1,924.0| Clark, Nev. 60.9| Manatee, Fla. 7.2 Maricopa, Ariz. 1,791.4| Dallas, Texas 44.3| Clark, Nev. 7.2 Orange, Calif. 1,512.1| New York, N.Y. 40.9| Lake, Fla. 7.0 Dallas, Texas 1,439.9| Orange, Calif. 36.2| Pasco, Fla. 6.9 San Diego, Calif. 1,313.3| King, Wash. 34.7| Seminole, Fla. 6.6 King, Wash. 1,126.8| Riverside, Calif. 30.9| Collier, Fla. 6.4 Miami-Dade, Fla. 1,014.5| Cook, Ill. 28.0| Will, Ill. 6.4 | | Hamilton, Ind. 6.4 ------------------------------------------------------------------------------------- Employment declined in 32 counties from March 2005 to March 2006. The largest percentage decline in employment was in Orleans County, La. (-38.7 percent), followed by the counties of Harrison, Miss. (-18.8 percent), and Jefferson, La. (-11.7 percent). Employment losses in these three Gulf Coast counties reflected the devastation caused by Hurricane Katrina. Monterey, Calif., had the next largest employment decline (-3.6 percent), followed by Boone, Ky. (-3.3 percent). The largest gains in employment from March 2005 to March 2006 were recorded in the counties of Los Angeles, Calif. (107,700), Maricopa, Ariz. (102,100), Harris, Texas (83,000), Clark, Nev. (60,900), and Dallas, Texas (44,300). (See table A.) The largest declines in employment occurred in the Katrina-affected counties of Orleans, La. (-93,500), Jefferson, La. (-25,000), and Harrison, Miss. (-17,100), followed by the counties of Oakland, Mich. (-14,200), and Wayne, Mich. (-12,600). Large County Average Weekly Wages The national average weekly wage in the first quarter of 2006 was $838. Average weekly wages were higher than the national average in 101 of the largest 325 U.S. counties. New York County, N.Y., held the top position among the highest-paid large counties with an average weekly wage of $2,223. Fairfield, Conn., was second with an average weekly wage of $1,836, followed by Santa Clara, Calif. ($1,584), Somerset, N.J. ($1,522), and San Francisco, Calif. ($1,519). (See table B.) - 3 - Table B. Top 10 large counties ranked by first quarter 2006 average weekly wages, first quarter 2005-06 growth in average weekly wages, and first quarter 2005-06 percent growth in average weekly wages ---------------------------------------------------------------------------------------- Average weekly wage in large counties ---------------------------------------------------------------------------------------- Average weekly wage, | Growth in average weekly | Percent growth in first quarter 2006 | wage, first quarter | average weekly wage, | 2005-06 | first quarter 2005-06 ---------------------------------------------------------------------------------------- | | U.S. $838| U.S. $63| U.S. 8.1 ---------------------------------------------------------------------------------------- | | New York, N.Y. $2,223| Orleans, La. $244| Orleans, La. 33.3 Fairfield, Conn. 1,836| Fairfield, Conn. 224| McLean, Ill. 20.5 Santa Clara, Calif. 1,584| Santa Clara, Calif. 213| Jefferson, La. 19.0 Somerset, N.J. 1,522| New York, N.Y. 195| Harrison, Miss. 18.0 San Francisco, Calif. 1,519| Somerset, N.J. 158| Montgomery, Texas 17.0 Suffolk, Mass. 1,494| Norfolk, Mass. 153| Norfolk, Mass. 16.7 Arlington, Va. 1,402| McLean, Ill. 146| Santa Clara, Calif. 15.5 Washington, D.C. 1,371| San Francisco, Calif. 144| Oklahoma, Okla. 15.3 San Mateo, Calif. 1,338| Arapahoe, Colo. 143| Arapahoe, Colo. 15.2 Hudson, N.J. 1,316| Fairfax, Va. 133| Sarasota, Fla. 14.1 ---------------------------------------------------------------------------------------- There were 222 counties with an average weekly wage below the national average in the first quarter of 2006. The lowest average weekly wages were reported in Cameron County, Texas ($477), followed by the counties of Hidalgo, Texas ($490), Horry, S.C. ($524), Webb, Texas ($527), and Yakima, Wash. ($550). (See table 1.) Over the year, the national average weekly wage rose by 8.1 percent. Among the largest counties, Orleans, La., led the nation in growth in average weekly wages, with an increase of 33.3 percent from the first quarter of 2005. McLean, Ill., was second with growth of 20.5 percent, followed by the counties of Jefferson, La. (19.0 percent), Harrison, Miss. (18.0 percent), and Montgomery, Texas (17.0 percent). The high average weekly wage growth rates for Orleans, Harrison, and Jefferson Counties were related to the disproportionate job and pay losses in lower-paid industries due to the impact of Hurricane Katrina. Two counties experienced over-the-year declines in average weekly wages. Cumberland County, Pa., had the largest decrease, -3.7 percent, followed by Trumbull, Ohio (-0.4 percent). The lowest over-the-year increases in average weekly wages were in Clayton, Ga. (1.3 percent), Kalamazoo, Mich. (1.9 percent), and Benton, Ark. (2.2 percent). Ten Largest U.S. Counties Of the 10 largest U.S. counties (based on 2005 annual average employment levels), all reported increases in employment from March 2005 to March 2006. Maricopa County, Ariz., experienced the fastest growth in employment among the largest counties, with a 6.0 percent increase. Within Maricopa County, employment rose in every industry group except two--natural resources and mining, and information. The largest gains were in construction (13.8 per- cent) and education and health services (7.3 percent). Harris, Texas, had the next largest increase in employment, 4.5 percent, followed by Dallas, Texas, and King, Wash. (3.2 percent each). The smallest employment gains occurred in Cook County, Ill., (1.1 percent), followed by San Diego, Calif. (1.6 percent), and New York, N.Y. (1.8 percent). (See table 2.) - 4 - All of the 10 largest U.S. counties saw over-the-year increases in average weekly wages. Miami-Dade, Fla., had the fastest growth in wages among the 10 largest counties, increasing by 11.0 percent. Within Miami- Dade County, average weekly wages increased the most in natural resources and mining (20.3 percent). San Diego, Calif., was second in wage growth, increasing by 10.8 percent, followed by Maricopa, Ariz. (10.5 percent). The smallest wage gains among the 10 largest counties occurred in Cook, Ill. (6.5 percent), followed by Orange, Calif. (8.2 percent), and Dallas, Texas (8.4 percent). Largest County by State Table 3 shows March 2006 employment and the 2006 first quarter average weekly wage in the largest county in each state, which is based on 2005 annual average employment levels. (This table includes two counties-- Yellowstone, Mont., and Laramie, Wyo.--that have employment levels below 75,000.) The employment levels in these counties in March 2006 ranged from approximately 4.2 million in Los Angeles County, Calif., to 41,000 in Laramie County, Wyo. The highest average weekly wage of these counties was in New York, N.Y. ($2,223), while the lowest average weekly wage was in Laramie, Wyo. ($633). Due to substantial job losses related to Hurricane Katrina, Orleans County was replaced by East Baton Rouge as the largest county in Louisiana in 2005. For More Information For additional information about the quarterly employment and wages data, please read the Technical Note or visit the QCEW Web site at http://www.bls.gov/cew/. Additional information about the QCEW data also may be obtained by e-mailing QCEWinfo@bls.gov or 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. --------------------------------------------------------------------- | Hurricane Katrina | | | | The measures of employment and wages reported in this news | | release reflect the impact of Hurricane Katrina and ongoing labor | | market trends. The effects of Hurricane Katrina, which hit the | | Gulf Coast on August 29, 2005, were first reflected in the Sep- | | tember QCEW employment counts and the wage totals for the third | | quarter of 2005. The impact of this catastrophic storm in parts | | of Louisiana and Mississippi continue to be reflected in monthly | | employment and quarterly wage totals in the first quarter of 2006. | | For more information, see the QCEW section of the Katrina coverage | | on the BLS Web site (http://www.bls.gov/katrina/qcewquestions.htm). | | | --------------------------------------------------------------------- - 5 - Technical Note These data are the product of a federal-state cooperative program, the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from summaries of employment and to- tal pay of workers covered by state and federal unemployment insurance (UI) legislation and provided by State Workforce Agencies (SWAs). The summaries are a result of the administration of state unemployment insurance programs that require most employers to pay quarterly taxes based on the employment and wages of workers covered by UI. Data for 2006 are preliminary and sub- ject to revision. For purposes of this release, large counties are defined as having em- ployment levels of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are provided, but not used in calculating U.S. averages, rankings, or in the analysis in the text. Each year, these large counties are selected on the basis of the preliminary annual average of employment for the previous year. The 326 counties presented in this release were derived using 2005 preliminary annual averages of employment. For 2006 data, four counties have been added to the publication tables: Douglas, Colo., Weld, Colo., Boone, Ky., and Butler, Pa. These counties will be included in all 2006 quarterly releases. One county, Potter, Texas, which was published in the 2005 releases, no longer has an employment level of 75,000 or more and will be excluded in the 2006 releases. The counties in table 2 are selected and sorted each year based on the annual average employment from the preceding year. The preliminary QCEW data presented in this release may differ from data released by the individual states. These potential differences result from the states' continuing receipt of UI data over time and ongoing review and editing. The individual states determine their data release timetables. Differences between QCEW, BED, and CES employment measures The Bureau publishes three different establishment-based employment measures for any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED), and Current Employment Statistics (CES)--makes use of the quarterly UI employment reports in producing data; however, each measure has a somewhat different universe coverage, estimation pro- cedure, and publication product. Differences in coverage and estimation methods can result in somewhat different measures of employment change over time. It is important to understand program differences and the intended uses of the program pro- ducts. (See table below.) Additional information on each program can be obtained from the program Web sites shown in the table below. - 6 - Summary of Major Differences between QCEW, BED, and CES Employment Measures -------------------------------------------------------------------------------- | QCEW | BED | CES -----------|---------------------|----------------------|----------------------- Source |--Count of UI admini-|--Count of longitudi- |--Sample survey: | strative records | nally-linked UI ad- | 400,000 establish- | submitted by 8.8 | ministrative records| ments | million establish- | submitted by 6.8 | | ments | million private-sec-| | | tor employers | -----------|---------------------|----------------------|----------------------- Coverage |--UI and UCFE cover- |--UI coverage, exclud-|Nonfarm wage and sal- | age, including all | ing government, pri-| ary jobs: | employers subject | vate households, and|--UI coverage, exclud- | to state and feder-| establishments with | ing agriculture, pri- | al UI laws | zero employment | vate households, and | | | self-employed workers | | |--Other employment, in- | | | cluding railroads, | | | religious organiza- | | | tions, and other non- | | | UI-covered jobs -----------|---------------------|----------------------|----------------------- Publication|--Quarterly |--Quarterly |--Monthly frequency | -7 months after the| -8 months after the | -Usually first Friday | end of each quar- | end of each quarter| of following month | ter | | -----------|---------------------|----------------------|----------------------- Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam- file | and publishes each | quarter to longitu- | pling frame and annu- | new quarter of UI | dinal database and | ally realigns (bench- | data | directly summarizes | marks) sample esti- | | gross job gains and | mates to first quar- | | losses | ter UI levels -----------|---------------------|----------------------|------------------------ Principal |--Provides a quarter-|--Provides quarterly |--Provides current month- products | ly and annual uni- | employer dynamics | ly estimates of employ- | verse count of es- | data on establish- | ment, hours, and earn- | tablishments, em- | ment openings, clos-| ings at the MSA, state, | ployment, and wages| ings, expansions, | and national level by | at the county, MSA,| and contractions at | industry | state, and national| the national level | | levels by detailed | by NAICS supersec- | | industry | tors and by size of | | | firm | | |--Future expansions | | | will include data at| | | the county, MSA, and| | | state 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 | -An analysis of em- | cators | surveys | ployment expansion | | | and contraction by | | | size of firm | -----------|---------------------|----------------------|-------------------------- Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/ Web sites | | | ----------------------------------------------------------------------------------- - 7 - Coverage Employment and wage data for workers covered by state UI laws 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 that are sent to the appropriate SWA by the specific federal agency. In addition to the quarterly contribution reports, employers who operate multiple establishments within a state com- plete a questionnaire, called the "Multiple Worksite Report," which provides detailed information on the location and industry of each of their establish- ments. The employment and wage data included in this release are derived from microdata summaries of nearly 9 million employer reports of employment and wages submitted by states to the BLS. These reports are based on place of employment rather than place of residence. UI and UCFE coverage is broad and basically comparable from state to state. In 2005, UI and UCFE programs covered workers in 131.6 million jobs. The estimated 126.7 million workers in these jobs (after adjust- ment for multiple jobholders) represented 96.6 percent of civilian wage and salary employment. Covered workers received $5.352 trillion in pay, representing 94.5 percent of the wage and salary component of personal income and 43.0 percent of the gross domestic product. Major exclusions from UI coverage include self-employed workers, most agricultural workers on small farms, all members of the Armed Forces, elected officials in most states, most employees of railroads, some domes- tic workers, most student workers at schools, and employees of certain small nonprofit organizations. State and federal UI laws change periodically. These changes may have an impact on the employment and wages reported by employers covered under the UI program. Coverage changes may affect the over-the-year comparisons presented in this news release. Concepts and methodology Monthly employment is based on the number of workers who worked during or received pay for the pay period including the 12th of the month. With few exceptions, all employees of covered firms are reported, including pro- duction and sales workers, corporation officials, executives, supervisory personnel, and clerical workers. Workers on paid vacations and part-time workers also are included. Average weekly wage values are calculated by dividing quarterly total wages by the average of the three monthly employment levels (all employees, as described above) and dividing the result by 13, for the 13 weeks in the quarter. These calculations are made using unrounded employment and wage values. The average wage values that can be calculated using rounded data from the BLS database may differ from the averages reported. Included in the quarterly wage data are non-wage cash payments such as bonuses, the cash value of meals and lodging when supplied, tips and other gratuities, and, in some states, employer contributions to certain deferred compensation plans such as 401(k) plans and stock options. 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 in- cluding the 12th of the month. When comparing average weekly wage levels between industries, states, or quarters, these factors should be taken into consideration. - 8 - Federal government pay levels are subject to periodic, sometimes large, fluctuations due to a calendar effect that consists of some quarters having more pay periods than others. Most federal employees are paid on a bi- weekly pay schedule. As a result of this schedule, in some quarters, fed- eral wages contain payments for six pay periods, while in other quarters their wages include payments for seven pay periods. Over-the-year com- parisons of average weekly wages may reflect this calendar effect. Higher growth in average weekly wages may be attributed, in part, to a comparison of quarterly wages for the current year, which include seven pay periods, with year-ago wages that reflect only six pay periods. An opposite effect will occur when wages in the current period, which contain six pay periods, are compared with year-ago wages that include seven pay periods. The ef- fect on over-the-year pay comparisons can be pronounced in federal govern- ment 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 concentrations of federal employment. In order to ensure the highest possible quality of data, states verify with employers and update, if necessary, the industry, location, and own- ership classification of all establishments on a 3-year cycle. Changes in establishment classification codes resulting from this process are in- troduced with the data reported for the first quarter of the year. Changes resulting from improved employer reporting also are introduced in the first quarter. QCEW data are not designed as a time series. QCEW data are simply the sums of individual establishment records and reflect the number of estab- lishments that exist in a county or industry at a point in time. Estab- lishments can move in or out of a county or industry for a number of rea- sons--some reflecting economic events, others reflecting administrative changes. For example, economic change would come from a firm relocating into the county; administrative change would come from a company correcting its county designation. The over-the-year changes of employment and wages presented in this release have been adjusted to account for most of the administrative corrections made to the underlying establishment reports. This is done by modifying the prior-year levels used to calculate the over-the-year changes. Percent changes are calcuated using an adjusted version of the final 2005 quarterly data as the base data. The adjusted prior-year levels used to calculate the over-the-year percent change in employment and wages are not published. These adjusted prior-year levels do not match the unadjusted data maintained on the BLS Web site. Over-the-year change calculations based on data from the Web site, or from data published in prior BLS news releases, may differ substantially from the over-the-year changes presented in this news release. The adjusted data used to calculate the over-the-year change measures presented in this release account for most of the administrative changes-- those occurring when employers update the industry, location, and owner- ship information of their establishments. The most common adjustments for administrative change are the result of updated information about the county location of individual establishments. Included in these adjust- ments are administrative changes involving the classification of establish- ments that were previously reported in the unknown or statewide county or unknown industry categories. The adjusted data do not account for adminis- trative changes caused by multi-unit employers who start reporting for each individual establishment rather than as a single entity. - 9 - The adjusted data used to calculate the over-the-year change measures presented in any County Employment and Wages news release are valid for comparisons between the starting and ending points (a 12-month period) used in that particular release. Comparisons may not be valid for any time period other than the one featured in a release even if the changes were calculated using adjusted data. County definitions are assigned according to Federal Information Processing Standards Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104- 106. Areas shown as counties include those designated as independent cities in some jurisdictions and, in Alaska, those designated as census areas where counties have not been created. County data also are presented for the New England states for comparative purposes even though townships are the more common designation used in New England (and New Jersey). The regions re- ferred to in this release are defined as census regions. Additional statistics and other information An annual bulletin, Employment and Wages, features comprehensive infor- mation by detailed industry on establishments, employment, and wages for the nation and all states. The 2005 edition of this bulletin contains selected data produced by Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the fourth quarter 2005 version of this news release. This edition will also be the first to include the data on a CD for enhanced access and usability. As a result of this change, the printed booklet will contain only selected graphic representations of QCEW data; the data tables themselves will be published exclusively in electronic formats as PDF and fixed-width text files. Employment and Wages Annual Averages, 2005 will be available for sale in late 2006 from the United States Government Printing Office, Superintendent of Documents, P.O. Box 371954, Pittsburgh, PA 15250, telephone 866-512-1800, outside of Washington, D.C. Within Washington, D.C., the telephone number is 202-512-1800. The fax number is 202-512-2104. Also, the 2005 bulletin will be available in a por- table document format (PDF) on the BLS Web site at http://www.bls.gov/cew/ cewbultn05.htm. News releases on quarterly measures of gross job flows also are available upon request from the Division of Administrative Statistics and Labor Turn- over (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 326 largest counties, first quarter 2006 (2) Employment Average weekly wage (5) Establishments, County (3) first quarter Percent Ranking Percent Ranking 2006 March change, by Average change, by (thousands) 2006 March percent weekly first percent (thousands) 2005-06 (4) change wage quarter change 2005-06 (4) United States (6)........ 8,770.7 132,613.1 2.2 - $838 8.1 - Jefferson, AL............ 18.6 371.4 1.1 208 845 7.2 181 Madison, AL.............. 8.2 170.6 2.7 103 866 8.4 105 Mobile, AL............... 9.8 170.7 3.2 77 659 9.7 54 Montgomery, AL........... 6.6 136.7 3.3 72 683 8.6 97 Tuscaloosa, AL........... 4.3 84.1 5.0 28 669 6.9 201 Anchorage Borough, AK.... 8.0 142.1 1.8 157 836 5.4 284 Maricopa, AZ............. 89.1 1,791.4 6.0 15 822 10.5 32 Pima, AZ................. 19.3 366.7 4.2 46 704 9.0 79 Benton, AR............... 5.1 92.9 5.4 19 792 2.2 319 Pulaski, AR.............. 14.0 247.3 2.5 120 728 6.6 219 Washington, AR........... 5.6 92.4 5.0 28 627 7.5 160 Alameda, CA.............. 49.4 683.9 1.1 208 1,099 9.9 47 Contra Costa, CA......... 28.3 342.3 0.3 274 1,073 5.1 288 Fresno, CA............... 29.6 333.7 2.8 100 637 6.5 227 Kern, CA................. 17.2 262.5 5.1 26 692 6.0 259 Los Angeles, CA.......... 392.0 4,179.3 2.6 111 944 9.3 65 Marin, CA................ 11.8 107.2 0.7 244 1,010 7.6 155 Monterey, CA............. 12.2 152.1 -3.6 319 767 10.4 35 Orange, CA............... 95.5 1,512.1 2.5 120 967 8.2 123 Placer, CA............... 10.4 136.7 2.7 103 793 8.0 131 Riverside, CA............ 42.8 632.8 5.1 26 707 8.4 105 Sacramento, CA........... 50.1 639.6 2.9 94 911 7.1 189 San Bernardino, CA....... 46.0 654.7 3.8 60 700 7.7 145 San Diego, CA............ 92.2 1,313.3 1.6 172 904 10.8 28 San Francisco, CA........ 44.6 533.0 2.9 94 1,519 10.5 32 San Joaquin, CA.......... 16.9 217.8 0.2 279 682 7.1 189 San Luis Obispo, CA...... 9.0 104.3 1.6 172 666 7.4 164 San Mateo, CA............ 23.3 333.8 2.1 139 1,338 10.0 44 Santa Barbara, CA........ 13.6 184.0 2.7 103 786 7.1 189 Santa Clara, CA.......... 55.4 871.7 3.0 91 1,584 15.5 7 Santa Cruz, CA........... 8.7 93.0 1.6 172 819 12.3 16 Solano, CA............... 10.0 129.6 1.6 172 780 7.7 145 Sonoma, CA............... 17.8 188.3 0.8 234 784 6.8 207 Stanislaus, CA........... 13.9 171.5 1.4 189 677 6.6 219 Tulare, CA............... 8.8 137.7 1.4 189 575 9.1 73 Ventura, CA.............. 21.8 321.0 1.8 157 891 4.5 298 Yolo, CA................. 5.4 97.4 1.8 157 765 9.1 73 Adams, CO................ 9.1 150.9 4.1 48 762 8.1 128 Arapahoe, CO............. 19.4 272.0 1.8 157 1,081 15.2 9 Boulder, CO.............. 12.3 154.2 1.6 172 987 7.2 181 Denver, CO............... 25.0 424.7 1.6 172 1,065 8.8 88 Douglas, CO.............. 8.6 84.0 5.3 22 853 9.5 62 El Paso, CO.............. 17.0 242.5 3.0 91 739 6.6 219 Jefferson, CO............ 18.6 204.3 0.5 262 849 6.8 207 Larimer, CO.............. 9.9 124.0 1.8 157 719 7.2 181 Weld, CO................. 5.8 78.3 4.0 53 672 10.7 29 Fairfield, CT............ 32.5 409.3 1.1 208 1,836 13.9 11 Hartford, CT............. 24.8 487.3 1.6 172 1,112 6.6 219 New Haven, CT............ 22.2 362.4 1.3 195 872 6.9 201 New London, CT........... 6.8 128.0 -0.2 295 847 8.3 113 New Castle, DE........... 19.6 280.2 0.7 244 1,113 10.3 37 Washington, DC........... 31.4 664.9 0.3 274 1,371 7.3 175 Alachua, FL.............. 6.4 126.1 2.1 139 614 4.8 293 Brevard, FL.............. 14.4 209.4 2.6 111 746 6.6 219 Broward, FL.............. 63.3 753.5 3.3 72 791 (7) - Collier, FL.............. 12.3 140.6 6.4 9 729 3.6 310 Duval, FL................ 25.5 460.2 3.3 72 841 9.9 47 Escambia, FL............. 7.9 130.4 3.2 77 642 8.6 97 Hillsborough, FL......... 35.9 644.1 4.2 46 782 8.3 113 Lake, FL................. 6.8 84.8 7.0 6 587 9.5 62 Lee, FL.................. 18.5 227.4 7.7 2 708 9.6 56 Leon, FL................. 7.9 147.9 1.8 157 648 4.0 307 Manatee, FL.............. 8.8 129.9 7.2 4 636 9.8 53 Marion, FL............... 7.8 103.0 4.4 40 587 7.7 145 Miami-Dade, FL........... 85.9 1,014.5 2.2 134 826 11.0 25 Okaloosa, FL............. 6.1 83.2 4.7 34 648 9.3 65 Orange, FL............... 34.1 674.6 3.6 63 757 6.9 201 Palm Beach, FL........... 48.8 568.9 3.5 64 806 4.4 301 Pasco, FL................ 9.2 100.5 6.9 7 563 8.9 84 Pinellas, FL............. 31.2 450.1 3.2 77 710 8.2 123 Polk, FL................. 12.3 212.3 4.1 48 624 7.2 181 Sarasota, FL............. 14.7 161.3 4.9 30 729 14.1 10 Seminole, FL............. 14.2 176.9 6.6 8 709 4.4 301 Volusia, FL.............. 13.7 169.6 4.3 45 574 5.7 269 Bibb, GA................. 4.7 85.2 -0.4 302 697 10.5 32 Chatham, GA.............. 7.3 134.2 2.9 94 687 9.6 56 Clayton, GA.............. 4.4 108.2 0.3 274 754 1.3 321 Cobb, GA................. 20.2 315.6 3.1 87 895 7.4 164 De Kalb, GA.............. 16.8 293.4 1.6 172 907 7.7 145 Fulton, GA............... 38.2 748.3 1.9 150 1,164 7.7 145 Gwinnett, GA............. 22.4 315.7 3.5 64 898 11.4 22 Muscogee, GA............. 4.8 98.3 1.3 195 655 8.1 128 Richmond, GA............. 4.8 107.3 2.8 100 670 7.4 164 Honolulu, HI............. 24.0 448.2 2.6 111 742 7.1 189 Ada, ID.................. 14.3 204.6 6.2 12 730 9.3 65 Champaign, IL............ 4.0 90.1 1.2 202 657 6.3 242 Cook, IL................. 132.7 2,502.0 1.1 208 1,047 6.5 227 Du Page, IL.............. 34.1 581.6 1.4 189 1,006 9.2 70 Kane, IL................. 11.9 203.2 1.8 157 740 7.7 145 Lake, IL................. 19.9 319.1 0.8 234 1,065 10.9 27 McHenry, IL.............. 8.0 97.9 3.9 56 689 7.0 197 McLean, IL............... 3.5 83.8 2.7 103 858 20.5 2 Madison, IL.............. 5.8 93.2 -0.1 291 673 6.0 259 Peoria, IL............... 4.7 100.6 1.6 172 829 8.1 128 Rock Island, IL.......... 3.4 75.3 1.3 195 838 13.4 12 St. Clair, IL............ 5.3 93.1 0.5 262 636 7.4 164 Sangamon, IL............. 5.2 129.3 0.1 284 776 2.8 318 Will, IL................. 12.2 174.0 6.4 9 719 4.7 296 Winnebago, IL............ 6.8 134.4 0.0 290 704 7.6 155 Allen, IN................ 8.9 181.7 2.5 120 700 6.2 250 Elkhart, IN.............. 4.8 128.8 3.9 56 702 10.4 35 Hamilton, IN............. 7.0 98.4 6.4 9 830 6.4 234 Lake, IN................. 10.0 192.4 0.7 244 718 6.7 214 Marion, IN............... 23.6 572.9 0.2 279 900 10.0 44 St. Joseph, IN........... 6.0 123.3 -0.7 307 676 6.3 242 Vanderburgh, IN.......... 4.8 108.4 1.1 208 693 7.8 141 Linn, IA................. 6.1 118.9 1.4 189 774 6.9 201 Polk, IA................. 14.3 264.4 2.4 125 859 8.3 113 Scott, IA................ 5.2 87.2 1.1 208 660 9.1 73 Johnson, KS.............. 19.8 299.4 0.7 244 883 8.5 101 Sedgwick, KS............. 12.1 246.8 3.4 68 796 12.7 14 Shawnee, KS.............. 4.8 92.1 -1.4 312 694 10.2 42 Wyandotte, KS............ 3.2 77.0 2.0 145 779 7.4 164 Boone, KY................ 3.3 73.7 -3.3 318 722 3.0 316 Fayette, KY.............. 9.0 169.3 0.9 229 725 6.3 242 Jefferson, KY............ 22.3 424.0 1.9 150 799 7.4 164 Caddo, LA................ 7.3 126.1 3.3 72 647 8.7 93 Calcasieu, LA............ 4.8 84.4 2.2 134 698 9.2 70 East Baton Rouge, LA..... 13.6 260.3 6.2 12 709 7.9 136 Jefferson, LA............ 14.4 188.0 -11.7 320 752 19.0 3 Lafayette, LA............ 8.1 127.4 5.8 17 723 12.6 15 Orleans, LA.............. 12.1 148.1 -38.7 322 977 33.3 1 Cumberland, ME........... 11.9 166.7 1.1 208 751 6.1 255 Anne Arundel, MD......... 14.2 222.2 2.3 130 863 8.0 131 Baltimore, MD............ 21.5 374.5 2.3 130 851 6.5 227 Frederick, MD............ 5.8 91.9 2.1 139 788 9.0 79 Harford, MD.............. 5.5 81.5 3.2 77 775 10.7 29 Howard, MD............... 8.4 141.9 3.1 87 948 9.1 73 Montgomery, MD........... 32.6 462.3 2.4 125 1,133 8.8 88 Prince Georges, MD....... 15.4 311.5 0.7 244 865 8.5 101 Baltimore City, MD....... 14.0 348.0 -0.5 304 951 6.4 234 Barnstable, MA........... 9.1 83.3 0.8 234 696 6.6 219 Bristol, MA.............. 15.3 217.5 0.7 244 704 6.0 259 Essex, MA................ 20.3 291.2 1.0 223 880 9.7 54 Hampden, MA.............. 14.0 196.5 0.5 262 766 5.4 284 Middlesex, MA............ 46.5 791.3 1.9 150 1,177 7.2 181 Norfolk, MA.............. 21.3 315.3 0.6 257 1,069 16.7 6 Plymouth, MA............. 13.6 172.7 1.1 208 742 5.5 278 Suffolk, MA.............. 21.3 563.5 1.2 202 1,494 7.3 175 Worcester, MA............ 20.2 314.8 0.8 234 820 9.0 79 Genesee, MI.............. 8.3 145.6 -1.0 310 745 5.1 288 Ingham, MI............... 7.0 160.8 -1.2 311 778 5.6 275 Kalamazoo, MI............ 5.5 116.2 0.3 274 733 1.9 320 Kent, MI................. 14.5 338.8 1.0 223 728 5.7 269 Macomb, MI............... 18.1 323.6 -0.6 305 856 3.4 312 Oakland, MI.............. 40.3 694.0 -2.0 315 977 5.4 284 Ottawa, MI............... 5.8 109.4 -0.2 295 704 4.6 297 Saginaw, MI.............. 4.5 85.8 -2.9 317 719 5.4 284 Washtenaw, MI............ 8.2 195.0 -0.2 295 911 6.4 234 Wayne, MI................ 33.7 772.6 -1.6 314 923 3.1 315 Anoka, MN................ 8.3 113.5 2.0 145 755 4.9 292 Dakota, MN............... 10.9 170.9 2.6 111 811 7.6 155 Hennepin, MN............. 43.9 831.4 1.8 157 1,047 4.8 293 Olmsted, MN.............. 3.7 88.8 2.9 94 892 3.8 309 Ramsey, MN............... 16.2 327.4 1.6 172 928 6.3 242 St. Louis, MN............ 6.1 93.6 2.1 139 653 5.7 269 Stearns, MN.............. 4.6 78.2 3.2 77 635 10.1 43 Harrison, MS............. 4.4 73.5 -18.8 321 663 18.0 4 Hinds, MS................ 6.5 128.7 0.9 229 715 8.8 88 Boone, MO................ 4.4 81.9 3.4 68 615 7.1 189 Clay, MO................. 5.1 88.0 2.7 103 728 5.1 288 Greene, MO............... 8.1 152.4 3.3 72 613 6.4 234 Jackson, MO.............. 18.8 364.7 0.8 234 844 8.9 84 St. Charles, MO.......... 7.8 119.8 3.1 87 695 6.3 242 St. Louis, MO............ 33.9 616.3 0.7 244 900 9.9 47 St. Louis City, MO....... 8.0 219.5 0.1 284 981 7.4 164 Douglas, NE.............. 15.4 308.1 1.0 223 778 9.9 47 Lancaster, NE............ 7.9 151.8 0.5 262 644 5.7 269 Clark, NV................ 44.2 905.4 7.2 4 769 6.8 207 Washoe, NV............... 13.7 214.8 4.0 53 734 4.0 307 Hillsborough, NH......... 12.4 195.0 1.3 195 886 7.3 175 Rockingham, NH........... 10.9 134.0 1.7 169 816 6.7 214 Atlantic, NJ............. 6.8 143.8 0.6 257 731 8.3 113 Bergen, NJ............... 34.6 443.4 0.4 269 1,061 7.9 136 Burlington, NJ........... 11.5 202.6 1.9 150 853 7.2 181 Camden, NJ............... 13.6 209.5 1.5 185 824 8.0 131 Essex, NJ................ 21.6 360.5 1.4 189 1,121 6.7 214 Gloucester, NJ........... 6.4 104.0 3.9 56 742 9.1 73 Hudson, NJ............... 14.1 235.5 0.1 284 1,316 6.2 250 Mercer, NJ............... 11.1 227.3 2.6 111 1,068 7.4 164 Middlesex, NJ............ 21.2 395.0 0.9 229 1,083 5.6 275 Monmouth, NJ............. 20.6 253.2 1.6 172 885 5.5 278 Morris, NJ............... 18.1 284.3 1.0 223 1,286 8.3 113 Ocean, NJ................ 11.9 144.7 1.9 150 701 8.7 93 Passaic, NJ.............. 12.7 179.1 2.2 134 864 7.5 160 Somerset, NJ............. 10.2 172.4 3.5 64 1,522 11.6 20 Union, NJ................ 15.0 228.3 0.3 274 1,106 9.6 56 Bernalillo, NM........... 16.9 328.0 4.4 40 705 7.3 175 Albany, NY............... 9.7 226.0 -0.1 291 820 5.5 278 Bronx, NY................ 15.7 221.9 1.2 202 745 5.8 265 Broome, NY............... 4.5 94.3 1.1 208 641 6.3 242 Dutchess, NY............. 8.2 116.9 0.1 284 835 4.4 301 Erie, NY................. 23.3 449.5 -0.1 291 715 6.4 234 Kings, NY................ 43.3 458.5 1.6 172 705 7.3 175 Monroe, NY............... 17.7 378.3 -0.1 291 806 8.2 123 Nassau, NY............... 51.8 590.4 0.5 262 909 5.7 269 New York, NY............. 115.3 2,271.0 1.8 157 2,223 9.6 56 Oneida, NY............... 5.3 107.7 0.4 269 614 5.0 291 Onondaga, NY............. 12.7 245.5 0.7 244 753 7.7 145 Orange, NY............... 9.7 128.3 1.8 157 689 6.8 207 Queens, NY............... 41.1 477.6 1.1 208 801 6.0 259 Richmond, NY............. 8.3 88.7 0.6 257 703 6.2 250 Rockland, NY............. 9.5 111.4 0.6 257 877 8.8 88 Suffolk, NY.............. 49.0 599.8 0.6 257 848 7.8 141 Westchester, NY.......... 36.1 407.6 0.5 262 1,193 8.0 131 Buncombe, NC............. 7.2 109.9 1.3 195 614 7.2 181 Catawba, NC.............. 4.4 87.3 1.2 202 642 11.5 21 Cumberland, NC........... 5.8 116.4 0.8 234 595 6.8 207 Durham, NC............... 6.4 173.0 2.4 125 1,137 10.3 37 Forsyth, NC.............. 8.6 181.3 2.0 145 761 4.5 298 Guilford, NC............. 13.9 273.8 1.3 195 726 6.5 227 Mecklenburg, NC.......... 28.3 530.6 3.2 77 1,167 8.4 105 New Hanover, NC.......... 6.8 97.8 4.5 37 663 9.0 79 Wake, NC................. 24.7 416.8 4.8 33 829 8.5 101 Cass, ND................. 5.8 92.1 4.1 48 649 6.6 219 Butler, OH............... 7.3 141.5 1.7 169 725 5.8 265 Cuyahoga, OH............. 38.3 745.0 0.1 284 865 6.5 227 Franklin, OH............. 29.4 675.5 1.4 189 837 7.9 136 Hamilton, OH............. 24.2 523.4 0.7 244 909 6.7 214 Lake, OH................. 6.9 98.9 -0.2 295 690 3.4 312 Lorain, OH............... 6.3 100.1 0.2 279 690 5.5 278 Lucas, OH................ 11.0 224.2 1.1 208 749 6.1 255 Mahoning, OH............. 6.4 102.4 1.5 185 595 8.0 131 Montgomery, OH........... 13.1 275.0 -0.2 295 758 4.4 301 Stark, OH................ 9.2 160.2 -0.7 307 644 8.8 88 Summit, OH............... 15.0 268.6 1.1 208 756 6.5 227 Trumbull, OH............. 4.9 84.3 -1.4 312 701 -0.4 322 Oklahoma, OK............. 22.7 420.0 2.6 111 755 15.3 8 Tulsa, OK................ 18.9 339.5 4.4 40 774 13.0 13 Clackamas, OR............ 12.3 145.3 2.8 100 741 6.0 259 Jackson, OR.............. 6.6 81.6 0.8 234 597 6.2 250 Lane, OR................. 10.7 146.9 2.6 111 622 6.3 242 Marion, OR............... 9.0 133.6 1.7 169 629 6.1 255 Multnomah, OR............ 26.5 432.1 2.6 111 839 7.7 145 Washington, OR........... 15.5 242.9 4.9 30 965 8.3 113 Allegheny, PA............ 35.0 674.7 0.9 229 871 7.1 189 Berks, PA................ 9.1 165.7 2.3 130 725 8.5 101 Bucks, PA................ 19.7 259.9 2.2 134 793 9.2 70 Butler, PA............... 4.7 75.1 0.9 229 671 7.2 181 Chester, PA.............. 15.0 231.1 1.8 157 1,083 9.9 47 Cumberland, PA........... 5.8 124.7 1.1 208 757 -3.7 323 Dauphin, PA.............. 7.1 178.7 2.4 125 789 3.4 312 Delaware, PA............. 13.6 206.4 0.4 269 895 11.9 18 Erie, PA................. 7.2 126.1 0.5 262 632 8.4 105 Lackawanna, PA........... 5.7 100.3 1.9 150 615 7.0 197 Lancaster, PA............ 11.9 224.2 0.4 269 691 8.3 113 Lehigh, PA............... 8.3 174.1 3.0 91 815 7.1 189 Luzerne, PA.............. 7.9 141.6 0.8 234 639 8.3 113 Montgomery, PA........... 27.9 482.2 1.5 185 1,118 10.6 31 Northampton, PA.......... 6.3 96.8 2.0 145 714 6.4 234 Philadelphia, PA......... 29.2 632.0 0.4 269 979 9.3 65 Washington, PA........... 5.4 76.7 2.5 120 695 9.3 65 Westmoreland, PA......... 9.5 135.9 0.2 279 639 9.0 79 York, PA................. 8.8 173.5 2.1 139 709 6.0 259 Kent, RI................. 5.7 80.5 0.7 244 734 7.5 160 Providence, RI........... 18.2 282.0 0.1 284 802 4.8 293 Charleston, SC........... 12.8 197.3 1.8 157 681 8.6 97 Greenville, SC........... 12.8 228.1 2.3 130 695 5.6 275 Horry, SC................ 8.7 109.4 5.3 22 524 9.6 56 Lexington, SC............ 6.0 89.9 2.2 134 614 8.3 113 Richland, SC............. 9.9 211.1 3.4 68 700 8.9 84 Spartanburg, SC.......... 6.5 115.5 0.2 279 742 8.6 97 Minnehaha, SD............ 6.1 110.7 2.6 111 683 7.6 155 Davidson, TN............. 18.0 442.1 3.1 87 812 5.7 269 Hamilton, TN............. 8.5 190.4 (7) - 699 (7) - Knox, TN................. 10.6 219.3 2.4 125 682 6.7 214 Rutherford, TN........... 4.0 97.8 4.4 40 710 7.9 136 Shelby, TN............... 20.0 502.4 1.5 185 813 7.3 175 Bell, TX................. 4.3 94.7 1.2 202 610 9.1 73 Bexar, TX................ 30.7 693.2 3.9 56 738 7.4 164 Brazoria, TX............. 4.4 83.7 7.5 3 822 9.9 47 Brazos, TX............... 3.7 84.0 6.0 15 564 4.1 306 Cameron, TX.............. 6.3 120.5 4.0 53 477 4.4 301 Collin, TX............... 14.9 258.4 7.8 1 990 7.5 160 Dallas, TX............... 66.5 1,439.9 3.2 77 1,033 8.4 105 Denton, TX............... 9.5 155.4 (7) - 679 6.3 242 El Paso, TX.............. 13.0 262.6 3.2 77 568 7.4 164 Fort Bend, TX............ 7.4 113.1 4.5 37 883 7.8 141 Galveston, TX............ 5.0 91.3 3.7 61 755 12.0 17 Harris, TX............... 91.8 1,924.0 4.5 37 1,033 8.7 93 Hidalgo, TX.............. 9.9 207.2 4.6 36 490 5.8 265 Jefferson, TX............ 5.8 123.0 4.9 30 761 6.4 234 Lubbock, TX.............. 6.5 119.9 1.2 202 609 10.3 37 McLennan, TX............. 4.8 101.4 -0.2 295 637 5.5 278 Montgomery, TX........... 7.2 107.7 6.1 14 785 17.0 5 Nueces, TX............... 8.0 150.2 2.7 103 685 11.7 19 Smith, TX................ 5.1 90.9 1.3 195 669 6.5 227 Tarrant, TX.............. 35.1 730.5 2.9 94 839 8.4 105 Travis, TX............... 26.0 541.2 4.1 48 934 7.7 145 Webb, TX................. 4.5 83.7 5.4 19 527 7.8 141 Williamson, TX........... 6.1 104.9 4.7 34 838 4.5 298 Davis, UT................ 7.0 97.7 5.2 25 635 6.9 201 Salt Lake, UT............ 37.7 553.3 4.4 40 744 9.4 64 Utah, UT................. 12.3 161.3 5.6 18 589 6.9 201 Weber, UT................ 5.7 89.7 2.0 145 579 7.6 155 Chittenden, VT........... 5.7 93.1 -0.6 305 847 11.0 25 Arlington, VA............ 7.3 157.0 1.6 172 1,402 8.2 123 Chesterfield, VA......... 7.0 117.0 3.2 77 738 7.0 197 Fairfax, VA.............. 31.6 568.4 2.5 120 1,314 11.3 24 Henrico, VA.............. 8.7 172.9 1.0 223 919 2.9 317 Loudoun, VA.............. 7.4 123.9 4.1 48 1,114 11.4 22 Prince William, VA....... 6.5 102.7 5.4 19 717 9.6 56 Alexandria City, VA...... 5.9 93.0 1.0 223 1,054 8.9 84 Chesapeake City, VA...... 5.3 99.0 (7) - 631 8.2 123 Newport News City, VA.... 3.9 98.4 0.8 234 711 6.8 207 Norfolk City, VA......... 5.6 141.1 -2.0 315 768 6.1 255 Richmond City, VA........ 7.0 161.4 2.7 103 987 8.7 93 Virginia Beach City, VA.. 11.2 175.8 1.1 208 630 8.4 105 Clark, WA................ 10.8 127.6 3.7 61 722 6.6 219 King, WA................. 74.1 1,126.8 3.2 77 1,041 10.3 37 Kitsap, WA............... 6.3 83.5 2.9 94 698 6.2 250 Pierce, WA............... 19.3 262.0 3.5 64 737 7.4 164 Snohomish, WA............ 16.4 228.7 5.3 22 839 10.0 44 Spokane, WA.............. 14.3 201.4 3.4 68 651 6.4 234 Thurston, WA............. 6.3 95.2 2.7 103 715 5.8 265 Whatcom, WA.............. 6.5 78.6 2.1 139 625 7.9 136 Yakima, WA............... 7.4 92.0 1.9 150 550 7.0 197 Kanawha, WV.............. 6.1 107.3 0.8 234 706 7.1 189 Brown, WI................ 6.8 145.5 0.7 244 744 8.3 113 Dane, WI................. 14.1 294.5 0.7 244 812 10.3 37 Milwaukee, WI............ 21.8 486.6 -0.3 301 843 8.4 105 Outagamie, WI............ 5.0 100.0 -0.4 302 705 5.5 278 Racine, WI............... 4.3 74.3 -0.8 309 722 6.8 207 Waukesha, WI............. 13.5 229.1 0.7 244 823 7.7 145 Winnebago, WI............ 3.9 86.8 1.1 208 777 3.5 311 San Juan, PR............. 14.7 306.0 -2.4 (8) 531 3.1 (8) 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 325 U.S. counties comprise 70.9 percent of the total covered workers in the U.S. 2 Data are preliminary. 3 Includes areas not officially designated as counties. See Technical Note. 4 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. 5 Average weekly wages were calculated using unrounded data. 6 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. 7 Data do not meet BLS or State agency disclosure standards. 8 This county was not included in the U.S. rankings. Table 2. Covered (1) establishments, employment, and wages in the ten largest counties, first quarter 2006 (2) Employment Average weekly wage (4) Establishments, first quarter County by NAICS supersector 2006 Percent Percent (thousands) March change, Average change, 2006 March weekly first (thousands) 2005-06 (3) wage quarter 2005-06 (3) United States (5)............................ 8,770.7 132,613.1 2.2 $838 8.1 Private industry........................... 8,492.7 111,080.5 2.5 843 8.5 Natural resources and mining............. 123.5 1,634.5 2.7 882 13.2 Construction............................. 867.6 7,296.6 7.3 823 9.9 Manufacturing............................ 365.3 14,104.7 -0.4 1,022 8.7 Trade, transportation, and utilities..... 1,890.9 25,624.0 1.8 708 7.8 Information.............................. 144.0 3,041.5 -0.1 1,374 10.4 Financial activities..................... 840.5 8,101.5 2.3 1,629 9.9 Professional and business services....... 1,413.1 17,153.3 4.2 1,020 8.7 Education and health services............ 790.1 16,830.1 2.8 714 7.5 Leisure and hospitality.................. 703.7 12,626.1 2.4 338 8.0 Other services........................... 1,127.3 4,320.5 0.8 508 7.2 Government................................. 277.9 21,532.5 0.8 808 5.3 Los Angeles, CA.............................. 392.0 4,179.3 2.6 944 9.3 Private industry........................... 388.2 3,591.9 3.0 927 9.4 Natural resources and mining............. 0.5 10.8 -4.8 1,067 -6.7 Construction............................. 14.0 154.1 8.0 883 8.5 Manufacturing............................ 16.1 469.5 -0.8 1,002 11.6 Trade, transportation, and utilities..... 55.3 803.3 2.4 768 8.3 Information.............................. 9.0 214.5 4.9 1,649 4.7 Financial activities..................... 24.7 248.0 2.5 1,680 8.5 Professional and business services....... 42.6 593.1 4.3 1,103 13.2 Education and health services............ 28.1 471.1 2.7 804 10.9 Leisure and hospitality.................. 27.1 383.9 3.3 503 11.3 Other services........................... 170.4 242.9 6.4 403 2.8 Government................................. 3.8 587.4 0.3 1,046 8.5 Cook, IL..................................... 132.7 2,502.0 1.1 1,047 6.5 Private industry........................... 131.5 2,186.2 1.4 1,061 7.1 Natural resources and mining............. 0.1 1.3 8.0 1,032 6.6 Construction............................. 11.4 89.2 4.8 1,182 5.0 Manufacturing............................ 7.3 245.7 -3.3 987 3.0 Trade, transportation, and utilities..... 27.2 471.5 0.3 803 8.1 Information.............................. 2.5 59.4 -2.5 1,628 9.2 Financial activities..................... 14.9 216.8 0.7 2,411 12.2 Professional and business services....... 27.3 423.4 3.8 1,286 3.9 Education and health services............ 13.1 361.0 2.2 765 7.1 Leisure and hospitality.................. 11.1 219.2 3.1 388 9.0 Other services........................... 13.2 93.7 -0.3 668 6.4 Government................................. 1.2 315.8 -0.6 953 2.6 New York, NY................................. 115.3 2,271.0 1.8 2,223 9.6 Private industry........................... 115.0 1,824.7 2.2 2,524 9.5 Natural resources and mining............. 0.0 0.1 1.0 2,606 53.7 Construction............................. 2.1 29.7 3.7 1,387 4.7 Manufacturing............................ 3.1 39.2 -8.5 1,349 11.9 Trade, transportation, and utilities..... 21.4 237.9 2.1 1,139 6.5 Information.............................. 4.2 129.6 0.4 2,445 9.2 Financial activities..................... 17.5 361.5 2.5 6,879 11.3 Professional and business services....... 23.1 454.2 2.7 2,067 6.9 Education and health services............ 8.1 281.5 1.5 929 5.8 Leisure and hospitality.................. 10.5 195.2 1.9 734 9.7 Other services........................... 16.7 84.0 0.8 912 7.2 Government................................. 0.2 446.2 0.3 998 8.6 Harris, TX................................... 91.8 1,924.0 4.5 1,033 8.7 Private industry........................... 91.4 1,673.1 4.9 1,067 9.1 Natural resources and mining............. 1.4 70.8 9.3 3,120 3.4 Construction............................. 6.3 141.5 7.6 948 13.4 Manufacturing............................ 4.6 171.9 4.8 1,398 10.3 Trade, transportation, and utilities..... 21.3 402.7 4.2 953 9.8 Information.............................. 1.3 31.5 -1.3 1,311 12.1 Financial activities..................... 10.0 116.6 2.1 1,464 10.4 Professional and business services....... 17.9 313.1 6.9 1,106 8.2 Education and health services............ 9.5 199.1 3.2 767 6.5 Leisure and hospitality.................. 7.0 166.6 4.0 367 8.9 Other services........................... 10.7 56.0 2.2 566 9.3 Government................................. 0.4 250.9 1.8 809 5.3 Maricopa, AZ................................. 89.1 1,791.4 6.0 822 10.5 Private industry........................... 88.5 1,579.3 6.7 822 10.3 Natural resources and mining............. 0.5 8.9 -0.8 741 17.1 Construction............................. 9.0 175.7 13.8 856 18.4 Manufacturing............................ 3.4 136.2 4.1 1,184 6.3 Trade, transportation, and utilities..... 19.0 361.1 5.0 777 8.7 Information.............................. 1.5 32.1 -2.0 1,078 11.7 Financial activities..................... 10.8 148.2 5.8 1,213 12.6 Professional and business services....... 18.9 301.0 6.3 787 9.6 Education and health services............ 8.5 183.5 7.3 810 9.9 Leisure and hospitality.................. 6.2 176.4 5.1 381 10.8 Other services........................... 6.2 46.8 1.7 552 12.2 Government................................. 0.6 212.1 1.2 820 11.4 Orange, CA................................... 95.5 1,512.1 2.5 967 8.2 Private industry........................... 94.1 1,361.3 2.8 955 8.3 Natural resources and mining............. 0.2 7.0 -4.7 538 -0.6 Construction............................. 7.0 106.2 10.9 1,008 10.2 Manufacturing............................ 5.7 183.4 0.5 1,143 11.4 Trade, transportation, and utilities..... 17.9 270.8 2.0 884 8.3 Information.............................. 1.4 32.0 -0.9 1,414 11.9 Financial activities..................... 11.3 140.9 1.3 1,599 3.4 Professional and business services....... 19.0 271.4 4.2 997 10.5 Education and health services............ 9.8 135.4 2.9 818 6.6 Leisure and hospitality.................. 7.0 166.3 2.9 369 7.3 Other services........................... 14.7 47.8 0.3 540 6.3 Government................................. 1.4 150.7 -0.9 1,075 7.6 Dallas, TX................................... 66.5 1,439.9 3.2 1,033 8.4 Private industry........................... 66.0 1,279.9 3.5 1,057 8.9 Natural resources and mining............. 0.5 7.3 7.1 3,020 16.5 Construction............................. 4.3 78.6 6.0 884 5.0 Manufacturing............................ 3.2 147.1 3.4 1,261 7.1 Trade, transportation, and utilities..... 14.9 300.4 2.2 944 9.4 Information.............................. 1.7 52.6 -2.5 1,526 12.4 Financial activities..................... 8.4 138.7 3.8 1,644 10.2 Professional and business services....... 14.0 255.4 7.1 1,109 7.3 Education and health services............ 6.3 135.2 3.9 841 5.3 Leisure and hospitality.................. 5.1 122.4 0.1 489 15.3 Other services........................... 6.5 39.8 -1.3 613 8.1 Government................................. 0.4 160.0 0.8 843 4.1 San Diego, CA................................ 92.2 1,313.3 1.6 904 10.8 Private industry........................... 90.8 1,092.2 1.9 901 11.8 Natural resources and mining............. 0.8 11.4 -2.5 511 12.8 Construction............................. 7.3 92.9 4.9 937 15.3 Manufacturing............................ 3.4 104.1 -1.5 1,207 10.9 Trade, transportation, and utilities..... 14.6 217.0 2.0 729 7.8 Information.............................. 1.3 36.7 -2.1 2,349 39.9 Financial activities..................... 9.9 86.0 4.0 1,294 5.9 Professional and business services....... 16.2 215.4 1.8 1,056 10.8 Education and health services............ 8.0 123.9 1.3 779 10.3 Leisure and hospitality.................. 6.8 150.0 3.6 392 10.1 Other services........................... 22.4 54.7 0.7 464 7.7 Government................................. 1.4 221.2 0.2 917 6.1 King, WA..................................... 74.1 1,126.8 3.2 1,041 10.3 Private industry........................... 73.6 974.4 3.8 1,056 10.8 Natural resources and mining............. 0.4 3.3 1.7 1,325 1.6 Construction............................. 6.4 62.8 12.8 961 8.3 Manufacturing............................ 2.5 109.6 4.6 1,413 16.9 Trade, transportation, and utilities..... 14.7 215.3 1.8 916 9.8 Information.............................. 1.7 69.7 1.2 1,817 9.2 Financial activities..................... 6.7 75.7 2.3 1,534 11.8 Professional and business services....... 12.3 174.5 7.3 1,200 9.9 Education and health services............ 6.2 116.0 2.5 781 10.8 Leisure and hospitality.................. 5.7 103.1 2.6 447 4.9 Other services........................... 16.9 44.5 -0.6 527 8.0 Government................................. 0.5 152.4 -0.4 942 5.5 Miami-Dade, FL............................... 85.9 1,014.5 2.2 826 11.0 Private industry........................... 85.6 861.6 2.6 801 10.9 Natural resources and mining............. 0.5 11.1 4.0 445 20.3 Construction............................. 5.7 49.6 13.4 851 13.0 Manufacturing............................ 2.7 48.3 -1.1 756 9.7 Trade, transportation, and utilities..... 23.8 247.4 2.3 744 9.6 Information.............................. 1.7 22.3 -3.1 1,269 11.5 Financial activities..................... 10.0 71.1 3.9 1,334 11.4 Professional and business services....... 17.1 140.0 -2.0 932 13.0 Education and health services............ 8.6 131.5 4.9 749 6.7 Leisure and hospitality.................. 5.8 102.1 1.9 505 (6) Other services........................... 7.7 34.5 2.3 481 8.6 Government................................. 0.3 152.9 -0.4 965 12.2 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. 2 Data are preliminary. 3 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. 4 Average weekly wages were calculated using unrounded data. 5 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. 6 Data do not meet BLS or State agency disclosure standards. Table 3. Covered (1) establishments, employment, and wages in the largest county by state, first quarter 2006 (2) Employment Average weekly wage (5) Establishments, first quarter County (3) 2006 Percent Percent (thousands) March change, Average change, 2006 March weekly first (thousands) 2005-06 (4) wage quarter 2005-06 (4) United States (6)........ 8,770.7 132,613.1 2.2 $838 8.1 Jefferson, AL............ 18.6 371.4 1.1 845 7.2 Anchorage Borough, AK.... 8.0 142.1 1.8 836 5.4 Maricopa, AZ............. 89.1 1,791.4 6.0 822 10.5 Pulaski, AR.............. 14.0 247.3 2.5 728 6.6 Los Angeles, CA.......... 392.0 4,179.3 2.6 944 9.3 Denver, CO............... 25.0 424.7 1.6 1,065 8.8 Hartford, CT............. 24.8 487.3 1.6 1,112 6.6 New Castle, DE........... 19.6 280.2 0.7 1,113 10.3 Washington, DC........... 31.4 664.9 0.3 1,371 7.3 Miami-Dade, FL........... 85.9 1,014.5 2.2 826 11.0 Fulton, GA............... 38.2 748.3 1.9 1,164 7.7 Honolulu, HI............. 24.0 448.2 2.6 742 7.1 Ada, ID.................. 14.3 204.6 6.2 730 9.3 Cook, IL................. 132.7 2,502.0 1.1 1,047 6.5 Marion, IN............... 23.6 572.9 0.2 900 10.0 Polk, IA................. 14.3 264.4 2.4 859 8.3 Johnson, KS.............. 19.8 299.4 0.7 883 8.5 Jefferson, KY............ 22.3 424.0 1.9 799 7.4 East Baton Rouge, LA..... 13.6 260.3 6.2 709 7.9 Cumberland, ME........... 11.9 166.7 1.1 751 6.1 Montgomery, MD........... 32.6 462.3 2.4 1,133 8.8 Middlesex, MA............ 46.5 791.3 1.9 1,177 7.2 Wayne, MI................ 33.7 772.6 -1.6 923 3.1 Hennepin, MN............. 43.9 831.4 1.8 1,047 4.8 Hinds, MS................ 6.5 128.7 0.9 715 8.8 St. Louis, MO............ 33.9 616.3 0.7 900 9.9 Yellowstone, MT.......... 5.4 72.9 2.3 635 6.7 Douglas, NE.............. 15.4 308.1 1.0 778 9.9 Clark, NV................ 44.2 905.4 7.2 769 6.8 Hillsborough, NH......... 12.4 195.0 1.3 886 7.3 Bergen, NJ............... 34.6 443.4 0.4 1,061 7.9 Bernalillo, NM........... 16.9 328.0 4.4 705 7.3 New York, NY............. 115.3 2,271.0 1.8 2,223 9.6 Mecklenburg, NC.......... 28.3 530.6 3.2 1,167 8.4 Cass, ND................. 5.8 92.1 4.1 649 6.6 Cuyahoga, OH............. 38.3 745.0 0.1 865 6.5 Oklahoma, OK............. 22.7 420.0 2.6 755 15.3 Multnomah, OR............ 26.5 432.1 2.6 839 7.7 Allegheny, PA............ 35.0 674.7 0.9 871 7.1 Providence, RI........... 18.2 282.0 0.1 802 4.8 Greenville, SC........... 12.8 228.1 2.3 695 5.6 Minnehaha, SD............ 6.1 110.7 2.6 683 7.6 Shelby, TN............... 20.0 502.4 1.5 813 7.3 Harris, TX............... 91.8 1,924.0 4.5 1,033 8.7 Salt Lake, UT............ 37.7 553.3 4.4 744 9.4 Chittenden, VT........... 5.7 93.1 -0.6 847 11.0 Fairfax, VA.............. 31.6 568.4 2.5 1,314 11.3 King, WA................. 74.1 1,126.8 3.2 1,041 10.3 Kanawha, WV.............. 6.1 107.3 0.8 706 7.1 Milwaukee, WI............ 21.8 486.6 -0.3 843 8.4 Laramie, WY.............. 3.1 40.9 3.6 633 5.3 San Juan, PR............. 14.7 306.0 -2.4 531 3.1 St. Thomas, VI........... 1.8 23.3 0.6 616 5.5 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. 2 Data are preliminary. 3 Includes areas not officially designated as counties. See Technical Note. 4 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. 5 Average weekly wages were calculated using unrounded data. 6 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. Table 4. Covered (1) establishments, employment, and wages by state, first quarter 2006 (2) Employment Average weekly wage (3) Establishments, first quarter State 2006 Percent Percent (thousands) March change, Average change, 2006 March weekly first (thousands) 2005-06 wage quarter 2005-06 United States (4)........ 8,770.7 132,613.1 2.2 $838 8.1 Alabama.................. 116.1 1,923.6 2.6 690 7.6 Alaska................... 20.6 296.3 2.0 791 6.5 Arizona.................. 145.1 2,613.3 6.0 767 10.2 Arkansas................. 80.5 1,171.6 2.5 621 7.1 California............... 1,279.8 15,422.5 2.7 952 9.2 Colorado................. 172.2 2,211.3 2.5 858 9.2 Connecticut.............. 111.2 1,640.1 1.1 1,191 10.0 Delaware................. 30.1 415.0 1.7 965 9.8 District of Columbia..... 31.4 664.9 0.3 1,371 7.3 Florida.................. 587.0 8,014.1 3.7 735 8.2 Georgia.................. 260.2 3,989.2 2.8 799 7.7 Hawaii................... 37.1 615.1 2.7 719 7.5 Idaho.................... 53.4 623.3 5.0 609 8.6 Illinois................. 344.4 5,733.7 1.6 913 7.7 Indiana.................. 155.2 2,870.4 1.1 717 7.5 Iowa..................... 92.2 1,445.7 1.8 662 7.5 Kansas................... 84.7 1,317.1 1.7 686 8.7 Kentucky................. 108.8 1,769.9 1.8 671 6.8 Louisiana................ 121.6 1,793.1 -4.1 697 12.6 Maine.................... 48.9 577.5 0.9 652 6.2 Maryland................. 161.6 2,511.2 2.1 897 7.9 Massachusetts............ 205.8 3,136.3 1.3 1,045 8.4 Michigan................. 257.3 4,207.8 -0.6 816 4.7 Minnesota................ 173.0 2,633.0 2.7 827 5.8 Mississippi.............. 68.6 1,112.1 0.0 597 9.3 Missouri................. 172.2 2,680.5 1.6 724 7.7 Montana.................. 40.6 416.8 3.3 572 7.3 Nebraska................. 57.6 888.4 1.0 648 8.0 Nevada................... 70.0 1,260.0 6.2 764 6.7 New Hampshire............ 48.0 617.1 1.7 800 7.5 New Jersey............... 278.6 3,933.9 1.8 1,037 7.6 New Mexico............... 51.8 795.5 4.0 647 8.6 New York................. 566.9 8,329.2 1.0 1,193 8.8 North Carolina........... 238.4 3,905.5 2.4 744 7.8 North Dakota............. 25.2 328.8 2.8 586 6.9 Ohio..................... 293.3 5,267.2 0.8 751 6.5 Oklahoma................. 95.9 1,505.6 3.5 660 11.9 Oregon................... 126.8 1,669.7 2.9 734 7.3 Pennsylvania............. 334.3 5,551.7 1.6 807 8.0 Rhode Island............. 35.9 468.2 0.4 777 5.6 South Carolina........... 122.5 1,834.1 1.9 661 8.2 South Dakota............. 29.4 373.2 2.2 581 6.6 Tennessee................ 135.1 2,717.7 2.3 705 6.8 Texas.................... 530.4 9,850.2 4.0 824 8.6 Utah..................... 84.4 1,147.2 5.0 660 8.9 Vermont.................. 24.5 300.5 0.9 688 7.7 Virginia................. 218.2 3,613.3 2.5 862 8.6 Washington............... 208.1 2,784.0 3.1 833 8.7 West Virginia............ 48.2 697.7 2.0 625 7.2 Wisconsin................ 164.1 2,712.2 0.8 716 7.5 Wyoming.................. 23.5 256.8 5.0 667 9.3 Puerto Rico.............. 59.6 1,048.1 0.2 450 3.9 Virgin Islands........... 3.4 45.6 2.8 664 2.3 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. 2 Data are preliminary. 3 Average weekly wages were calculated using unrounded data. 4 Totals for the United States do not include data for Puerto Rico or the Virgin Islands.