Technical information:(202) 691-6567 USDL 08-0064 http://www.bls.gov/cew/ For release: 10:00 A.M. EST Media contact: 691-5902 Thursday, January 17, 2008 COUNTY EMPLOYMENT AND WAGES: SECOND QUARTER 2007 In June 2007, Orleans County, La., 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. Orleans County, which includes the city of New Orleans, experienced an over-the-year employment gain of 10.8 percent, compared with national job growth of 1.2 percent. Harrison County, Miss., followed closely behind Orleans with an over-the-year gain of 10.3 percent. Employment gains in Orleans and Harrison counties reflected significant recovery following substantial job losses that occurred in 2005 and 2006 due to Hurricane Katrina. Clayton County, Ga., had the largest over-the- year gain in average weekly wages in the second quarter of 2007, with an increase of 87.3 percent due to increases in wage disbursements in the trade, transportation, and utilities supersector during the quarter. The U.S. average weekly wage rose by 4.6 percent over the same time span. Of the 328 largest counties in the United States, as measured by 2006 annual average employment, 126 had over-the-year percentage growth in employment above the national average (1.2 percent) in June 2007; 184 large counties experienced changes below the national average. The percent change in average weekly wages was higher than the national average (4.6 percent) in 109 of the largest U.S. counties, but was below the national average in 199 counties. Table A. Top 10 large counties ranked by June 2007 employment, June 2006-07 employment growth, and June 2006-07 percent growth in employment -------------------------------------------------------------------------------------------------------- Employment in large counties -------------------------------------------------------------------------------------------------------- | | June 2007 employment | Growth in employment, | Percent growth (thousands) | June 2006-07 | in employment, | (thousands) | June 2006-07 -------------------------------------------------------------------------------------------------------- | | United States 137,018.2| United States 1,599.0| United States 1.2 | | -------------------------------------------------------------------------------------------------------- | | Los Angeles, Calif. 4,229.3| Harris, Texas 85.5| Orleans, La. 10.8 Cook, Ill. 2,559.5| Dallas, Texas 46.0| Harrison, Miss. 10.3 New York, N.Y. 2,363.8| New York, N.Y. 43.8| Utah, Utah 6.7 Harris, Texas 2,023.3| King, Wash. 33.4| Williamson, Tenn. 6.4 Maricopa, Ariz. 1,798.0| Los Angeles, Calif. 28.5| Wake, N.C. 5.9 Orange, Calif. 1,519.5| Wake, N.C. 25.2| Brazoria, Texas 5.3 Dallas, Texas 1,492.6| Mecklenburg, N.C. 25.0| Montgomery, Texas 5.3 San Diego, Calif. 1,334.7| Salt Lake, Utah 23.8| Charleston, S.C. 5.0 King, Wash. 1,182.2| Travis, Texas 22.7| Lafayette, La. 4.8 Miami-Dade, Fla. 1,002.1| Bexar, Texas 20.2| Snohomish, Wash. 4.7 | | -------------------------------------------------------------------------------------------------------- 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 8.9 million employer reports cover 137.0 million full- and part-time workers. The attached tables contain data for the nation and for the 328 U.S. counties with annual average employment levels of 75,000 or more in 2006. June 2007 employment and 2007 second- quarter average weekly wages for all states are provided in table 4 of this release. Final data for all states, metropolitan statistical areas, counties, and the nation through the fourth quarter of 2006 are available on the BLS Web site at http://www.bls.gov/cew/. Preliminary data for first quarter 2007 also are available on the BLS Web site. Updated data for first quarter 2007 and preliminary data for second quarter 2007 will be available later in January on the BLS Web site. Large County Employment In June 2007, national employment, as measured by the QCEW program, was 137.0 million, up by 1.2 percent from June 2006. The 328 U.S. counties with 75,000 or more employees accounted for 70.9 percent of total U.S. employment and 76.7 percent of total wages. These 328 counties had a net job gain of 1,051,335 over the year, accounting for 65.7 percent of the overall U.S. employment increase. Employment rose in 235 of the large counties from June 2006 to June 2007. Orleans County, La., had the largest over-the-year percentage increase in employment (10.8 percent). Harrison, Miss., had the next largest increase, 10.3 percent, followed by the counties of Utah, Utah (6.7 percent), Williamson, Tenn. (6.4 percent), and Wake, N.C. (5.9 percent). The large employment gains in Orleans and Harrison counties reflected significant recovery from the substantial job losses that occurred in 2005 and 2006, which were related to Hurricane Katrina. (See table 1.) Employment declined in 77 counties from June 2006 to June 2007. The largest percentage decline in employment was in Trumbull County, Ohio (-6.3 percent). Macomb, Mich., had the next largest employment decline (-3.6 percent), followed by the counties of Manatee, Fla., and Genesee, Mich. (-3.1 percent each), and Wayne, Mich., and Montgomery, Ohio (-2.9 percent each). The largest gains in the level of employment from June 2006 to June 2007 were recorded in the counties of Harris, Texas (85,500), Dallas, Texas (46,000), New York, N.Y. (43,800), King, Wash. (33,400), and Los Angeles, Calif. (28,500). (See table A.) The largest decline in employment levels occurred in Wayne, Mich. (-22,500), followed by the counties of Orange, Calif. (-16,000), Macomb, Mich. (-12,000), Oakland, Mich. (-8,200), and Montgomery, Ohio (-8,000). Table B. Top 10 large counties ranked by second quarter 2007 average weekly wages, second quarter 2006-07 growth in average weekly wages, and second quarter 2006-07 percent growth in average weekly wages -------------------------------------------------------------------------------------------------------- Average weekly wage in large counties -------------------------------------------------------------------------------------------------------- Average weekly wage, | Growth in average weekly | Percent growth in second quarter 2007 | wage, second quarter | average weekly wage, | 2006-07 | second quarter 2006-07 -------------------------------------------------------------------------------------------------------- | | United States $820| United States $36| United States 4.6 | | -------------------------------------------------------------------------------------------------------- | | New York, N.Y. $1,540| Clayton, Ga. $633| Clayton, Ga. 87.3 Santa Clara, Calif. 1,504| Santa Clara, Calif. 115| Queens, N.Y. 12.7 Clayton, Ga. 1,358| Queens, N.Y. 100| Rockingham, N.H. 10.1 Washington, D.C. 1,357| Somerset, N.J. 98| Ventura, Calif. 9.2 Arlington, Va. 1,352| San Francisco, Calif. 97| Lake, Ill. 9.1 San Francisco, Calif. 1,323| New York, N.Y. 92| San Luis Obispo, Calif. 8.7 Fairfield, Conn. 1,311| Fairfield, Conn. 87| Santa Clara, Calif. 8.3 Somerset, N.J. 1,286| Lake, Ill. 87| Douglas, Colo. 8.2 Suffolk, Mass. 1,284| Hennepin, Minn. 79| Somerset, N.J. 8.2 San Mateo, Calif. 1,277| Rockingham, N.H. 78| Hennepin, Minn. 8.1 | | Fort Bend, Texas 8.1 | | -------------------------------------------------------------------------------------------------------- Large County Average Weekly Wages The national average weekly wage in the second quarter of 2007 was $820. Average weekly wages were higher than the national average in 110 of the largest 328 U.S. counties. New York County, N.Y., held the top position among the highest-paid large counties with an average weekly wage of $1,540. Santa Clara, Calif., was second with an average weekly wage of $1,504, followed by Clayton County, Ga. ($1,358), Washington, D.C. ($1,357), and Arlington, Va. ($1,352). (See table B.) There were 218 counties with an average weekly wage below the national average in the second quarter of 2007. The lowest average weekly wage was reported in Cameron County, Texas ($515), followed by the counties of Hidalgo, Texas ($518), Horry, S.C., and Webb, Texas ($545 each), and Yakima, Wash. ($555). (See table 1.) Over the year, the national average weekly wage rose by 4.6 percent. Among the largest counties, Clayton County, Ga., led the nation in growth in average weekly wages, with an increase of 87.3 percent from the second quarter of 2006. Queens, N.Y., was second with growth of 12.7 percent, followed by the counties of Rockingham, N.H. (10.1 percent), Ventura, Calif. (9.2 percent), and Lake, Ill. (9.1 percent). Six large counties experienced over-the-year declines in average weekly wages. Among the five largest decreases in wages, Saginaw, Mich., had the greatest decline (-5.2 percent), followed by the counties of Orleans, La. (-2.9 percent), Lake, Fla. (-1.1 percent), Genesee, Mich. (-1.0 percent), and Lorain, Ohio (-0.9 percent). Ten Largest U.S. Counties Nine of the 10 largest counties (based on 2006 annual average employment levels) reported increases in employment from June 2006 to June 2007. Harris, Texas, experienced the largest percent gain in employment among the 10 largest counties with a 4.4 percent increase. Within Harris County, employment rose in every industry group. The largest gains were in natural resources and mining (10.4 percent) and construction (7.6 percent). Dallas, Texas, had the next largest increase in employment, 3.2 percent, followed by King, Wash. (2.9 percent). The smallest percent increase in employment occurred in San Diego, Calif., and Cook, Ill. (0.2 percent each). Orange, Calif., experienced the only decline in employment among the 10 largest counties with a 1.0 percent decrease. Within Orange County, five industry groups experienced employment declines with financial activities experiencing the largest decline, -7.7 percent. (See table 2.) Each of the 10 largest U.S. counties saw an over-the-year increase in average weekly wages. Harris, Texas, had the fastest growth in wages among the 10 largest counties, with a gain of 6.9 percent. Within Harris County, average weekly wages increased the most in the information industry (10.0 percent), followed by the other services industry (8.0 percent). New York, N.Y., was second in wage growth with a gain of 6.4 percent, followed by Dallas, Texas (5.4 percent). The smallest wage gain among the 10 largest counties occurred in Orange, Calif. (3.4 percent), followed by Miami-Dade, Fla., and King, Wash. (3.8 percent each). Largest County by State Table 3 shows June 2007 employment and the 2007 second quarter average weekly wage in the largest county in each state, which is based on 2006 annual average employment levels. (This table includes two counties--Yellowstone, Mont., and Laramie, Wyo.--that had employment levels below 75,000 in 2006.) The employment levels in the counties in table 3 in June 2007 ranged from approximately 4.2 million in Los Angeles County, Calif., to 43,400 in Laramie County, Wyo. The highest average weekly wage of these counties was in New York, N.Y. ($1,540), while the lowest average weekly wage was in Cass, N.D. ($672). 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 calling (202) 691-6567. Several BLS regional offices are issuing QCEW news releases targeted to local data users. For links to these releases, see http://www.bls.gov/cew/cewregional.htm. ____________________________________________________ The County Employment and Wages release for third quarter 2007 is scheduled to be released on Wednesday, April 9, 2008. Technical Note These data are the product of a federal-state cooperative program, the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from summaries of employment and total pay of workers covered by state and federal unemployment insurance (UI) legislation and provided by State Workforce Agencies (SWAs). The summaries are a result of the administration of state unemployment insurance programs that require most employers to pay quarterly taxes based on the employment and wages of workers covered by UI. QCEW data in this release are based on the 2007 North American Industry Classification System. Data for 2007 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 pro- vided, but not used in calculating U.S. averages, rankings, or in the analysis in the text. Each year, these large counties are selected on the basis of the prelimi- nary annual average of employment for the previous year. The 329 counties presented in this release were derived using 2006 preliminary annual averages of employment. For 2007 data, four counties have been added to the publication tables: Butte, Calif., Tippecanoe, Ind., Saratoga, N.Y., and Williamson, Tenn. These counties will be included in all 2007 quarterly releases. One county, Boone, Ky., which was pub- lished in the 2006 releases, will be excluded from this and future 2007 releases be- cause its 2006 average annual employment level was less than 75,000. The counties in table 2 are selected and sorted each year based on the annual average employment from the preceding year. The preliminary QCEW data presented in this release may differ from data re- leased 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 em- ployment reports in producing data; however, each measure has a somewhat different universe coverage, estimation procedure, and publication product. Differences in coverage and estimation methods can result in somewhat different measures of employment change over time. It is important to understand program dif- ferences and the intended uses of the program products. (See table.) Additional 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 8.9 | ministrative records| ments | million establish- | submitted by 6.9 | | 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 fed- | establishments with | ing agriculture, pri- | eral UI laws | zero employment | vate households, and | | | self-employed workers | | |--Other employment, in- | | | cluding railroads, | | | religious organiza- | | | tions, and other non- | | | UI-covered jobs -----------|---------------------|----------------------|------------------------ Publication|--Quarterly |--Quarterly |--Monthly frequency | -7 months after the| -8 months after the | -Usually first Friday | end of each quar- | end of each quarter| of following month | ter | | -----------|---------------------|----------------------|------------------------ Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam- file | and publishes each | quarter to longitu- | pling frame and annu- | new quarter of UI | dinal database and | ally realigns (bench- | data | directly summarizes | marks) sample esti- | | gross job gains and | mates to first quar- | | losses | ter UI levels -----------|---------------------|----------------------|------------------------ Principal |--Provides a quarter-|--Provides quarterly |--Provides current month- products | ly and annual uni- | employer dynamics | ly estimates of employ- | verse count of es- | data on establish- | ment, hours, and earn- | tablishments, em- | ment openings, clos-| ings at the MSA, state, | ployment, and wages| ings, expansions, | and national level by | at the county, MSA,| and contractions at | industry | state, and national| the national level | | levels by detailed | by NAICS supersec- | | industry | tors and by size of | | | firm, and at the | | | state private-sector| | | total level | | |--Future expansions | | | will include data | | | with greater indus- | | | try detail and data | | | at the county and | | | MSA level | -----------|---------------------|----------------------|------------------------ Principal |--Major uses include:|--Major uses include: |--Major uses include: uses | -Detailed locality | -Business cycle | -Principal national | data | analysis | economic indicator | -Periodic universe | -Analysis of employ-| -Official time series | counts for bench- | er dynamics under- | for employment change | marking sample | lying economic ex- | measures | survey estimates | pansions and con- | -Input into other ma- | -Sample frame for | tractions | jor economic indi- | BLS establishment | -Analysis of employ-| cators | surveys | ment expansion and | | | contraction by size| | | of firm | | | | -----------|---------------------|----------------------|------------------------ Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/ Web sites | | | --------------------------------------------------------------------------------- Coverage Employment and wage data for workers covered by state UI laws are compiled from quarterly contribution reports submitted to the SWAs by employers. For federal ci- vilian workers covered by the Unemployment Compensation for Federal Employees (UCFE) program, employment and wage data are compiled from quarterly reports 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 complete a questionnaire, called the "Multiple Worksite Report," which provides de- tailed information on the location and industry of each of their establishments. The employment and wage data included in this release are derived from microdata summaries of 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 2006, UI and UCFE programs covered workers in 133.8 million jobs. The estimated 128.9 million workers in these jobs (after adjustment for multiple jobholders) rep- resented 96.4 percent of civilian wage and salary employment. Covered workers re- ceived $5.693 trillion in pay, representing 94.3 percent of the wage and salary com- ponent of personal income and 43.1 percent of the gross domestic product. Major exclusions from UI coverage include self-employed workers, most agricul- tural workers on small farms, all members of the Armed Forces, elected officials in most states, most employees of railroads, some domestic workers, most student work- ers 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 re- lease. Concepts and methodology Monthly employment is based on the number of workers who worked during or re- ceived pay for the pay period including the 12th of the month. With few exceptions, all employees of covered firms are reported, including production and sales workers, corporation officials, executives, supervisory personnel, and clerical workers. Workers on paid vacations and part-time workers also are included. Average weekly wage values are calculated by dividing quarterly total wages by the average of the three monthly employment levels (all employees, as described above) and dividing the result by 13, for the 13 weeks in the quarter. These calcu- lations are made using unrounded employment and wage values. The average wage val- ues 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 pay- ments 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 compari- sons 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 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, fluctua- tions due to a calendar effect that consists of some quarters having more pay peri- ods than others. Most federal employees are paid on a biweekly pay schedule. As a result of this schedule, in some quarters, federal wages contain payments for six pay periods, while in other quarters their wages include payments for seven pay pe- riods. Over-the-year comparisons of average weekly wages may reflect this calendar effect. Higher growth in average weekly wages may be attributed, in part, to a com- parison of quarterly wages for the current year, which include seven pay periods, with year-ago wages that reflect only six pay periods. An opposite effect will oc- cur when wages in the current period, which contain six pay periods, are compared with year-ago wages that include seven pay periods. The effect on over-the-year pay comparisons can be pronounced in federal government due to the uniform nature of federal payroll processing. This pattern may exist in private sector pay; however, because there are more pay period types (weekly, biweekly, semimonthly, monthly) it is less pronounced. The effect is most visible in counties with large concentra- tions of federal employment. In order to ensure the highest possible quality of data, states verify with em- ployers and update, if necessary, the industry, location, and ownership classifica- tion of all establishments on a 3-year cycle. Changes in establishment classifica- tion 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 establishments that exist in a county or industry at a point in time. Establishments can move in or out of a county or industry for a number of reasons--some reflecting economic events, others reflecting administrative changes. For example, economic change would come from a firm relocating into the county; administrative change would come from a company correcting its county designation. The over-the-year changes of employment and wages presented in this release have been adjusted to account for most of the administrative corrections made to the un- derlying establishment reports. This is done by modifying the prior-year levels used to calculate the over-the-year changes. Percent changes are calculated using an adjusted version of the final 2006 quarterly data as the base data. The adjusted prior-year levels used to calculate the over-the-year percent change in employment and wages are not published. These adjusted prior-year levels do not match the un- adjusted data maintained on the BLS Web site. Over-the-year change calculations based on data from the Web site, or from data published in prior BLS news releases, may differ substantially from the over-the-year changes presented in this news re- lease. The adjusted data used to calculate the over-the-year change measures presented in this release account for most of the administrative changes--those occurring when employers update the industry, location, and ownership information of their estab- lishments. The most common adjustments for administrative change are the result of updated information about the county location of individual establishments. Included in these adjustments are administrative changes involving the classification of es- tablishments that were previously reported in the unknown or statewide county or un- known industry categories. The adjusted data do not account for administrative changes caused by multi-unit employers who start reporting for each individual es- tablishment rather than as a single entity. The adjusted data used to calculate the over-the-year change measures presented in any County Employment and Wages news release are valid for comparisons between the starting and ending points (a 12-month period) used in that particular release. Comparisons may not be valid for any time period other than the one featured in a release even if the changes were calculated using adjusted data. County definitions are assigned according to Federal Information Processing 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 Secu- rity 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 pre- sented 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 information by detailed industry on establishments, employment, and wages for the nation and all states. The 2006 edition of this bulletin will contain selected data produced by Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the first quarter 2007 version of this news release. As with the 2005 edition, this edition will include the data on a CD for enhanced access and usability with the printed booklet containing selected graphic representations of QCEW data; the data tables themselves will be published exclusively in electronic formats as PDFs. Employment and Wages Annual Averages, 2006 will be available for sale in early 2008 from the United States Government Printing Office, Superintendent 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. Also, the 2006 bulletin will be available in a portable document format (PDF) on the BLS Web site at http://www.bls.gov/cew/cewbultn06.htm. News releases on quarterly measures of gross job flows also are available upon request from the Division of Administrative Statistics and Labor Turnover (Business Employment Dynamics), telephone (202) 691-6467; (http://www.bls.gov/bdm/); (e-mail: BDMInfo@bls.gov). Information in this release will be made available to sensory impaired individu- als 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 329 largest counties, second quarter 2007(2) Employment Average weekly wage(4) Establishments, County(3) second quarter Percent Ranking Percent Ranking 2007 June change, by Average change, by (thousands) 2007 June percent weekly second percent (thousands) 2006-07(5) change wage quarter change 2006-07(5) United States(6)......... 8,945.9 137,018.2 1.2 - $820 4.6 - Jefferson, AL............ 18.9 365.4 (7) - 823 5.2 78 Madison, AL.............. 8.7 178.3 3.8 22 864 4.3 136 Mobile, AL............... 10.0 174.1 1.6 101 682 1.8 291 Montgomery, AL........... 6.7 140.0 0.6 187 698 0.3 312 Tuscaloosa, AL........... 4.4 86.1 1.8 92 697 2.3 274 Anchorage Borough, AK.... 8.1 148.9 -1.3 300 887 5.7 54 Maricopa, AZ............. 97.7 1,798.0 0.9 158 827 3.9 163 Pima, AZ................. 20.8 369.7 2.1 75 733 4.9 91 Benton, AR............... 5.5 96.2 1.6 101 745 2.8 247 Pulaski, AR.............. 14.6 251.8 0.6 187 740 4.2 144 Washington, AR........... 5.7 93.8 -0.8 286 687 6.0 46 Alameda, CA.............. 49.1 690.4 -0.3 256 1,088 3.8 170 Butte, CA................ 7.5 76.8 0.0 236 621 4.9 91 Contra Costa, CA......... 27.8 348.6 -1.1 295 1,027 (7) - Fresno, CA............... 28.8 364.6 0.5 198 669 6.0 46 Kern, CA................. 17.2 285.1 0.2 220 726 6.9 18 Los Angeles, CA.......... 394.6 4,229.3 0.7 176 924 4.9 91 Marin, CA................ 11.4 109.4 0.1 226 1,056 0.3 312 Monterey, CA............. 12.1 181.3 -0.8 286 744 6.1 43 Orange, CA............... 94.7 1,519.5 -1.0 292 952 3.4 213 Placer, CA............... 10.4 141.1 1.0 146 822 6.2 39 Riverside, CA............ 43.1 645.8 -0.5 270 707 2.5 265 Sacramento, CA........... 51.0 645.7 0.1 226 913 5.7 54 San Bernardino, CA....... 45.6 666.1 -0.1 243 728 4.1 148 San Diego, CA............ 91.7 1,334.7 0.2 220 890 4.8 98 San Francisco, CA........ 44.1 555.6 (7) - 1,323 7.9 12 San Joaquin, CA.......... 17.1 232.1 -0.5 270 724 5.4 66 San Luis Obispo, CA...... 9.1 109.6 1.4 114 703 8.7 6 San Mateo, CA............ 22.8 342.1 1.2 127 1,277 6.2 39 Santa Barbara, CA........ 13.6 192.9 0.7 176 784 (7) - Santa Clara, CA.......... 55.9 905.1 2.0 81 1,504 8.3 7 Santa Cruz, CA........... 8.6 105.0 1.2 127 758 3.0 236 Solano, CA............... 9.7 129.8 -0.6 275 815 7.7 13 Sonoma, CA............... 17.7 196.7 -0.4 260 807 3.3 217 Stanislaus, CA........... 14.0 179.7 1.1 136 705 5.2 78 Tulare, CA............... 8.8 153.9 0.0 236 583 4.3 136 Ventura, CA.............. 21.7 322.2 -1.0 292 913 9.2 4 Yolo, CA................. 5.4 104.7 0.8 168 775 6.7 23 Adams, CO................ 9.4 156.5 0.3 210 750 2.7 254 Arapahoe, CO............. 20.0 285.9 2.2 67 959 2.3 274 Boulder, CO.............. 12.9 161.9 2.9 36 972 2.3 274 Denver, CO............... 25.8 446.5 2.6 44 989 5.3 73 Douglas, CO.............. 9.4 93.6 3.1 31 848 8.2 8 El Paso, CO.............. 17.9 251.3 0.2 220 752 3.9 163 Jefferson, CO............ 19.1 215.3 1.6 101 826 5.2 78 Larimer, CO.............. 10.3 134.0 2.4 57 720 5.0 85 Weld, CO................. 6.1 84.0 2.5 54 692 6.8 20 Fairfield, CT............ 32.8 428.3 1.3 122 1,311 7.1 17 Hartford, CT............. 25.3 512.0 1.5 108 1,035 6.7 23 New Haven, CT............ 22.5 372.9 -0.4 260 878 4.6 110 New London, CT........... 6.9 131.3 0.7 176 851 6.4 33 New Castle, DE........... 18.8 284.4 -0.3 256 981 1.6 295 Washington, DC........... 31.9 683.2 0.8 168 1,357 4.3 136 Alachua, FL.............. 6.6 124.4 2.1 75 659 3.1 228 Brevard, FL.............. 14.8 205.4 -1.9 306 780 2.2 279 Broward, FL.............. 64.7 760.2 1.1 136 778 2.0 288 Collier, FL.............. 12.4 125.6 -2.5 311 822 7.7 13 Duval, FL................ 26.2 468.1 2.0 81 793 2.7 254 Escambia, FL............. 8.0 129.5 0.6 187 654 2.7 254 Hillsborough, FL......... 36.8 642.3 1.1 136 781 4.4 130 Lake, FL................. 7.2 79.8 1.2 127 603 -1.1 318 Lee, FL.................. 19.5 218.5 -0.9 290 719 2.1 284 Leon, FL................. 8.1 144.1 0.9 158 694 3.9 163 Manatee, FL.............. 9.0 122.4 -3.1 316 678 3.8 170 Marion, FL............... 8.3 103.6 0.5 198 605 1.3 301 Miami-Dade, FL........... 85.9 1,002.1 1.0 146 814 3.8 170 Okaloosa, FL............. 6.2 82.0 -2.5 311 680 3.2 221 Orange, FL............... 36.0 685.1 2.6 44 746 -0.1 315 Palm Beach, FL........... 49.9 549.5 0.1 226 819 3.3 217 Pasco, FL................ 9.7 94.8 0.7 176 627 3.5 204 Pinellas, FL............. 31.4 439.2 -1.2 297 708 2.9 244 Polk, FL................. 12.6 201.1 -0.9 290 647 2.1 284 Sarasota, FL............. 15.1 152.7 -2.5 311 719 3.0 236 Seminole, FL............. 15.0 176.9 -0.4 260 736 2.8 247 Volusia, FL.............. 14.0 163.4 -0.4 260 615 3.7 183 Bibb, GA................. 4.7 84.1 -0.7 282 638 0.5 309 Chatham, GA.............. 7.5 138.6 3.9 19 695 2.8 247 Clayton, GA.............. 4.4 115.6 2.2 67 1,358 87.3 1 Cobb, GA................. 20.4 319.8 1.2 127 858 0.8 307 De Kalb, GA.............. 16.2 297.0 -1.0 292 896 5.4 66 Fulton, GA............... 39.6 759.6 1.6 101 1,082 6.2 39 Gwinnett, GA............. 23.4 327.3 2.6 44 831 5.2 78 Muscogee, GA............. 4.9 97.6 -2.1 307 641 6.0 46 Richmond, GA............. 4.8 102.4 -0.4 260 684 3.6 194 Honolulu, HI............. 24.7 454.8 0.5 198 758 4.0 154 Ada, ID.................. 15.3 215.7 2.0 81 748 0.5 309 Champaign, IL............ 4.1 92.9 1.9 86 679 4.6 110 Cook, IL................. 137.6 2,559.5 0.2 220 981 4.1 148 Du Page, IL.............. 35.5 605.9 0.0 236 956 4.8 98 Kane, IL................. 12.5 215.5 0.4 207 741 2.5 265 Lake, IL................. 20.7 342.8 0.9 158 1,040 9.1 5 McHenry, IL.............. 8.3 105.7 0.7 176 717 1.7 292 McLean, IL............... 3.6 86.2 1.3 122 781 2.8 247 Madison, IL.............. 5.9 97.1 0.8 168 662 1.2 302 Peoria, IL............... 4.7 106.4 2.1 75 765 3.1 228 Rock Island, IL.......... 3.5 79.9 -0.6 275 779 0.1 314 St. Clair, IL............ 5.4 96.4 1.4 114 662 3.1 228 Sangamon, IL............. 5.2 131.7 -0.6 275 797 3.8 170 Will, IL................. 13.2 195.4 3.4 26 739 1.7 292 Winnebago, IL............ 6.9 139.8 1.7 95 691 3.6 194 Allen, IN................ 9.0 182.9 0.3 210 696 1.6 295 Elkhart, IN.............. 4.9 128.3 -2.2 309 714 2.3 274 Hamilton, IN............. 7.4 112.4 (7) - 802 (7) - Lake, IN................. 10.2 197.0 0.9 158 708 2.8 247 Marion, IN............... 24.0 582.2 0.7 176 826 1.0 305 St. Joseph, IN........... 6.0 125.2 0.6 187 697 3.0 236 Tippecanoe, IN........... 3.2 76.6 1.7 95 700 3.1 228 Vanderburgh, IN.......... 4.8 107.5 -0.8 286 679 3.5 204 Linn, IA................. 6.2 126.2 2.9 36 771 4.6 110 Polk, IA................. 14.5 277.4 2.0 81 811 4.2 144 Scott, IA................ 5.2 90.4 -0.8 286 656 4.0 154 Johnson, KS.............. 20.1 318.1 3.1 31 867 4.8 98 Sedgwick, KS............. 12.1 259.9 3.9 19 779 6.4 33 Shawnee, KS.............. 4.8 96.7 2.3 62 723 4.2 144 Wyandotte, KS............ 3.2 80.7 2.2 67 798 1.4 299 Fayette, KY.............. 9.1 178.4 3.5 25 754 4.6 110 Jefferson, KY............ 21.9 443.4 2.2 67 810 4.1 148 Caddo, LA................ 7.3 126.1 -0.2 251 687 3.2 221 Calcasieu, LA............ 4.8 88.3 3.3 28 688 3.9 163 East Baton Rouge, LA..... 13.8 257.5 0.4 207 736 4.5 122 Jefferson, LA............ 13.7 199.3 2.6 44 755 3.3 217 Lafayette, LA............ 8.4 136.0 4.8 9 778 6.6 27 Orleans, LA.............. 10.0 168.3 10.8 1 872 -2.9 319 Cumberland, ME........... 12.3 176.1 0.1 226 741 4.5 122 Anne Arundel, MD......... 14.4 236.0 1.0 146 865 3.8 170 Baltimore, MD............ 21.8 380.6 0.1 226 847 4.8 98 Frederick, MD............ 6.0 96.6 0.0 236 783 4.0 154 Harford, MD.............. 5.7 86.0 0.0 236 753 5.9 50 Howard, MD............... 8.5 149.6 0.9 158 950 5.0 85 Montgomery, MD........... 32.8 466.7 0.3 210 1,108 6.7 23 Prince Georges, MD....... 15.6 317.4 1.1 136 893 4.4 130 Baltimore City, MD....... 14.0 346.5 0.5 198 973 6.3 37 Barnstable, MA........... 9.2 102.4 1.4 114 708 3.7 183 Bristol, MA.............. 15.6 224.3 -0.1 243 758 3.8 170 Essex, MA................ 20.7 304.7 0.6 187 879 4.5 122 Hampden, MA.............. 14.0 202.8 -0.1 243 748 3.7 183 Middlesex, MA............ 47.2 826.7 1.5 108 1,179 6.0 46 Norfolk, MA.............. 21.9 330.5 1.0 146 986 1.2 302 Plymouth, MA............. 13.8 182.2 -0.7 282 803 3.6 194 Suffolk, MA.............. 21.7 589.1 2.5 54 1,284 4.7 107 Worcester, MA............ 20.7 327.9 0.8 168 843 3.7 183 Genesee, MI.............. 7.9 144.1 -3.1 316 725 -1.0 317 Ingham, MI............... 6.8 162.6 -0.6 275 800 4.4 130 Kalamazoo, MI............ 5.5 117.5 0.0 236 744 4.6 110 Kent, MI................. 14.2 342.3 -0.5 270 746 2.8 247 Macomb, MI............... 17.8 320.6 -3.6 318 862 4.6 110 Oakland, MI.............. 39.1 704.7 -1.2 297 949 2.7 254 Ottawa, MI............... 5.7 111.8 -2.2 309 696 2.5 265 Saginaw, MI.............. 4.4 87.9 -1.4 303 678 -5.2 320 Washtenaw, MI............ 7.9 189.9 -1.3 300 925 5.1 83 Wayne, MI................ 32.4 755.2 -2.9 314 933 2.6 260 Anoka, MN................ 8.1 117.0 -0.4 260 835 3.1 228 Dakota, MN............... 10.7 180.1 0.9 158 819 3.5 204 Hennepin, MN............. 43.4 856.2 0.4 207 1,059 8.1 10 Olmsted, MN.............. 3.6 92.1 0.7 176 837 3.6 194 Ramsey, MN............... 15.8 334.3 -0.4 260 908 3.4 213 St. Louis, MN............ 6.0 98.1 1.0 146 710 6.4 33 Stearns, MN.............. 4.6 82.5 3.0 34 634 2.6 260 Harrison, MS............. 4.5 86.4 10.3 2 653 0.9 306 Hinds, MS................ 6.5 128.1 -0.6 275 714 3.6 194 Boone, MO................ 4.6 83.3 1.1 136 643 3.2 221 Clay, MO................. 5.1 92.5 0.7 176 799 6.8 20 Greene, MO............... 8.2 157.4 2.6 44 629 3.5 204 Jackson, MO.............. 18.8 373.1 1.4 114 832 4.0 154 St. Charles, MO.......... 8.2 127.0 2.8 42 700 1.2 302 St. Louis, MO............ 33.1 618.2 0.6 187 883 2.4 270 St. Louis City, MO....... 8.5 233.1 -1.5 304 897 5.0 85 Douglas, NE.............. 15.6 320.7 1.1 136 767 2.5 265 Lancaster, NE............ 8.0 159.0 (7) - 653 2.4 270 Clark, NV................ 48.4 930.0 1.1 136 773 3.1 228 Washoe, NV............... 14.3 219.9 -0.2 251 770 4.6 110 Hillsborough, NH......... 12.4 198.7 0.3 210 922 (7) - Rockingham, NH........... 11.0 143.2 0.9 158 847 10.1 3 Atlantic, NJ............. 7.1 153.2 -2.1 307 738 3.8 170 Bergen, NJ............... 35.4 462.0 0.9 158 1,022 3.5 204 Burlington, NJ........... 11.7 208.1 -0.7 282 873 2.7 254 Camden, NJ............... 13.4 214.0 -0.4 260 874 5.9 50 Essex, NJ................ 21.9 364.6 0.2 220 1,062 5.5 65 Gloucester, NJ........... 6.4 107.0 0.1 226 758 4.0 154 Hudson, NJ............... 14.2 237.3 0.6 187 1,099 3.7 183 Mercer, NJ............... 11.4 226.7 -0.1 243 1,048 5.2 78 Middlesex, NJ............ 22.5 416.8 1.1 136 1,020 1.4 299 Monmouth, NJ............. 21.2 268.1 0.0 236 875 3.6 194 Morris, NJ............... 18.6 296.0 0.5 198 1,191 6.1 43 Ocean, NJ................ 12.8 159.5 -0.1 243 700 2.6 260 Passaic, NJ.............. 12.9 179.9 -1.3 300 875 3.7 183 Somerset, NJ............. 10.4 178.0 -0.3 256 1,286 8.2 8 Union, NJ................ 15.5 238.7 1.3 122 1,055 (7) - Bernalillo, NM........... 17.6 337.7 1.5 108 724 3.0 236 Albany, NY............... 9.9 229.0 0.1 226 855 4.1 148 Bronx, NY................ 15.8 224.4 0.6 187 805 5.6 59 Broome, NY............... 4.5 97.5 1.6 101 664 4.6 110 Dutchess, NY............. 8.3 119.4 -0.2 251 842 4.5 122 Erie, NY................. 23.4 458.9 -0.2 251 724 4.3 136 Kings, NY................ 44.8 472.4 1.8 92 714 3.8 170 Monroe, NY............... 17.9 385.8 -0.1 243 804 1.9 290 Nassau, NY............... 52.3 616.6 0.8 168 953 5.9 50 New York, NY............. 117.1 2,363.8 1.9 86 1,540 6.4 33 Oneida, NY............... 5.3 112.8 0.3 210 668 6.2 39 Onondaga, NY............. 12.8 256.0 1.0 146 762 3.4 213 Orange, NY............... 10.0 132.9 0.6 187 729 3.6 194 Queens, NY............... 42.5 501.2 2.3 62 886 12.7 2 Richmond, NY............. 8.6 93.8 1.7 95 734 3.7 183 Rockland, NY............. 9.7 117.8 1.7 95 900 6.5 30 Saratoga, NY............. 5.3 78.8 2.3 62 703 5.7 54 Suffolk, NY.............. 50.1 640.0 0.8 168 891 4.1 148 Westchester, NY.......... 36.4 430.4 2.1 75 1,119 5.7 54 Buncombe, NC............. 7.9 116.7 4.0 18 644 3.9 163 Catawba, NC.............. 4.6 89.5 1.4 114 646 4.0 154 Cumberland, NC........... 6.1 119.3 1.2 127 639 5.6 59 Durham, NC............... 6.8 182.7 2.6 44 1,059 5.6 59 Forsyth, NC.............. 9.2 186.8 1.9 86 770 6.8 20 Guilford, NC............. 14.6 282.2 2.1 75 735 3.1 228 Mecklenburg, NC.......... 31.8 565.3 4.6 11 929 1.5 297 New Hanover, NC.......... 7.4 105.7 4.3 14 663 4.6 110 Wake, NC................. 27.5 451.8 5.9 5 813 4.5 122 Cass, ND................. 5.7 97.9 2.4 57 672 4.8 98 Butler, OH............... 7.3 146.8 1.5 108 715 3.6 194 Cuyahoga, OH............. 37.6 757.6 -0.3 256 842 2.1 284 Franklin, OH............. 29.3 694.7 1.5 108 805 3.7 183 Hamilton, OH............. 24.0 526.7 0.1 226 867 3.3 217 Lake, OH................. 6.8 103.7 0.5 198 697 5.6 59 Lorain, OH............... 6.3 101.4 -1.2 297 685 -0.9 316 Lucas, OH................ 10.7 223.5 -1.5 304 713 2.9 244 Mahoning, OH............. 6.3 106.3 1.2 127 601 3.8 170 Montgomery, OH........... 12.8 271.6 -2.9 314 759 3.7 183 Stark, OH................ 9.0 163.5 -0.4 260 642 2.2 279 Summit, OH............... 14.9 275.5 -0.2 251 756 5.0 85 Trumbull, OH............. 4.7 80.5 -6.3 319 732 6.6 27 Oklahoma, OK............. 23.5 421.3 0.7 176 729 2.5 265 Tulsa, OK................ 19.4 347.4 2.3 62 742 2.9 244 Clackamas, OR............ 12.7 151.7 1.2 127 764 3.8 170 Jackson, OR.............. 6.8 85.5 1.1 136 633 3.9 163 Lane, OR................. 11.0 153.3 1.7 95 646 3.2 221 Marion, OR............... 9.4 144.5 1.9 86 652 4.0 154 Multnomah, OR............ 27.3 450.5 2.5 54 842 5.4 66 Washington, OR........... 16.0 252.9 0.5 198 911 5.4 66 Allegheny, PA............ 35.3 697.8 1.0 146 874 4.7 107 Berks, PA................ 9.1 171.3 1.0 146 743 4.5 122 Bucks, PA................ 20.3 270.1 0.5 198 809 4.8 98 Butler, PA............... 4.8 80.9 2.4 57 702 4.9 91 Chester, PA.............. 15.0 243.7 2.1 75 1,078 4.6 110 Cumberland, PA........... 6.0 127.5 0.9 158 777 5.6 59 Dauphin, PA.............. 7.3 186.0 0.6 187 808 5.3 73 Delaware, PA............. 13.6 212.9 2.2 67 858 3.5 204 Erie, PA................. 7.2 130.4 0.7 176 651 5.3 73 Lackawanna, PA........... 5.8 102.8 1.1 136 631 3.8 170 Lancaster, PA............ 12.3 232.1 0.3 210 697 3.7 183 Lehigh, PA............... 8.6 181.6 1.4 114 812 5.3 73 Luzerne, PA.............. 7.9 145.1 0.8 168 641 4.9 91 Montgomery, PA........... 27.4 494.7 1.0 146 1,011 4.6 110 Northampton, PA.......... 6.5 100.7 1.5 108 723 3.6 194 Philadelphia, PA......... 30.0 633.0 -0.1 243 948 4.9 91 Washington, PA........... 5.3 81.0 1.4 114 716 5.9 50 Westmoreland, PA......... 9.5 139.9 -0.1 243 655 0.6 308 York, PA................. 9.1 177.9 1.9 86 730 3.0 236 Kent, RI................. 5.7 83.2 -0.4 260 717 3.9 163 Providence, RI........... 18.2 291.2 0.1 226 801 2.0 288 Charleston, SC........... 12.0 213.8 5.0 8 698 3.1 228 Greenville, SC........... 12.3 238.6 2.8 42 716 2.3 274 Horry, SC................ 8.2 125.5 3.4 26 545 3.4 213 Lexington, SC............ 5.6 95.8 2.9 36 615 1.5 297 Richland, SC............. 9.2 217.2 3.1 31 711 2.4 270 Spartanburg, SC.......... 6.0 119.7 2.6 44 708 2.8 247 Minnehaha, SD............ 6.3 116.3 2.4 57 677 5.3 73 Davidson, TN............. 18.5 446.5 0.1 226 818 0.4 311 Hamilton, TN............. 8.6 194.9 0.7 176 715 3.8 170 Knox, TN................. 11.0 227.9 1.4 114 707 4.6 110 Rutherford, TN........... 4.2 98.2 1.2 127 753 4.7 107 Shelby, TN............... 20.1 512.0 0.8 168 830 4.8 98 Williamson, TN........... 5.7 87.5 6.4 4 895 6.7 23 Bell, TX................. 4.5 97.6 1.7 95 630 4.8 98 Bexar, TX................ 31.7 722.3 2.9 36 738 6.3 37 Brazoria, TX............. 4.5 86.6 5.3 6 800 7.4 16 Brazos, TX............... 3.7 80.6 (7) - 613 (7) - Cameron, TX.............. 6.4 123.5 1.0 146 515 6.6 27 Collin, TX............... 16.0 280.9 3.9 19 946 4.2 144 Dallas, TX............... 67.6 1,492.6 3.2 30 1,011 5.4 66 Denton, TX............... 10.1 165.6 3.6 24 709 3.2 221 El Paso, TX.............. 13.2 265.6 1.6 101 591 6.1 43 Fort Bend, TX............ 7.9 123.9 (7) - 878 8.1 10 Galveston, TX............ 5.2 97.9 (7) - 762 (7) - Harris, TX............... 94.7 2,023.3 4.4 12 1,026 6.9 18 Hidalgo, TX.............. 10.4 213.5 4.4 12 518 4.0 154 Jefferson, TX............ 5.8 125.0 2.4 57 774 5.7 54 Lubbock, TX.............. 6.7 121.4 1.3 122 620 2.1 284 McLennan, TX............. 4.9 104.6 2.0 81 639 2.6 260 Montgomery, TX........... 7.7 121.3 5.3 6 738 2.6 260 Nueces, TX............... 8.1 153.1 2.3 62 701 6.5 30 Smith, TX................ 5.2 93.2 1.6 101 696 2.2 279 Tarrant, TX.............. 36.2 763.5 2.6 44 847 4.3 136 Travis, TX............... 27.6 573.1 4.1 17 905 3.0 236 Webb, TX................. 4.7 88.2 4.3 14 545 2.4 270 Williamson, TX........... 6.7 118.5 (7) - 791 4.1 148 Davis, UT................ 7.1 105.7 2.2 67 670 3.2 221 Salt Lake, UT............ 38.3 590.3 4.2 16 776 7.6 15 Utah, UT................. 12.8 178.1 6.7 3 637 6.5 30 Weber, UT................ 5.7 95.7 3.3 28 623 3.5 204 Chittenden, VT........... 5.8 95.4 -0.5 270 804 4.4 130 Arlington, VA............ 7.5 154.5 1.8 92 1,352 2.7 254 Chesterfield, VA......... 7.4 123.2 0.5 198 731 4.3 136 Fairfax, VA.............. 32.6 592.2 1.0 146 1,269 4.9 91 Henrico, VA.............. 9.1 183.4 3.8 22 876 4.5 122 Loudoun, VA.............. 8.1 131.7 2.9 36 1,016 2.2 279 Prince William, VA....... 6.9 106.5 -1.1 295 738 3.5 204 Alexandria City, VA...... 6.0 100.7 -0.5 270 1,160 5.6 59 Chesapeake City, VA...... 5.6 100.5 -0.7 282 653 3.5 204 Newport News City, VA.... 4.0 100.7 1.9 86 725 1.7 292 Norfolk City, VA......... 5.8 144.7 0.2 220 815 4.5 122 Richmond City, VA........ 7.4 159.4 (7) - 936 (7) - Virginia Beach City, VA.. 11.5 182.4 0.3 210 650 4.0 154 Clark, WA................ 11.7 133.8 1.3 122 750 5.0 85 King, WA................. 75.9 1,182.2 2.9 36 1,028 3.8 170 Kitsap, WA............... 6.5 84.7 -0.6 275 756 3.0 236 Pierce, WA............... 20.3 277.0 2.6 44 744 5.4 66 Snohomish, WA............ 17.5 255.8 4.7 10 862 5.4 66 Spokane, WA.............. 15.0 212.5 2.6 44 669 5.0 85 Thurston, WA............. 6.7 101.1 3.0 34 743 5.1 83 Whatcom, WA.............. 6.8 83.8 2.2 67 634 4.4 130 Yakima, WA............... 7.8 108.8 0.3 210 555 4.3 136 Kanawha, WV.............. 6.1 110.1 0.3 210 721 3.7 183 Brown, WI................ 6.7 153.1 1.2 127 705 4.4 130 Dane, WI................. 14.0 305.4 1.0 146 785 4.8 98 Milwaukee, WI............ 21.1 503.5 0.9 158 818 4.3 136 Outagamie, WI............ 5.0 107.2 2.2 67 699 3.6 194 Racine, WI............... 4.2 77.8 -0.6 275 750 3.2 221 Waukesha, WI............. 13.2 241.2 0.3 210 813 3.0 236 Winnebago, WI............ 3.8 91.9 0.6 187 748 2.2 279 San Juan, PR............. 13.6 293.5 -2.8 (8) 546 7.5 (8) (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 328 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) Average weekly wages were calculated using unrounded data. (5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. (6) Totals for the United States do not include data for Puerto Rico or the Virgin Islands. (7) Data do not meet BLS or State agency disclosure standards. (8) This county was not included in the U.S. rankings. Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties, second quarter 2007(2) Employment Average weekly wage(3) Establishments, second quarter County by NAICS supersector 2007 Percent Percent (thousands) June change, Average change, 2007 June weekly second (thousands) 2006-07(4) wage quarter 2006-07(4) United States(5)............................. 8,945.9 137,018.2 1.2 $820 4.6 Private industry........................... 8,655.0 115,502.9 1.2 810 4.7 Natural resources and mining............. 124.1 1,955.3 2.3 838 6.2 Construction............................. 889.2 7,834.7 -0.6 863 5.2 Manufacturing............................ 361.0 13,954.1 -2.1 993 4.3 Trade, transportation, and utilities..... 1,909.4 26,388.1 1.4 715 4.8 Information.............................. 143.5 3,054.6 -0.3 1,255 5.5 Financial activities..................... 867.5 8,218.0 0.0 1,206 5.8 Professional and business services....... 1,468.2 18,027.5 2.2 999 5.7 Education and health services............ 817.5 17,375.3 2.9 760 3.4 Leisure and hospitality.................. 721.6 13,888.6 2.3 342 4.0 Other services........................... 1,138.3 4,516.7 1.5 527 3.7 Government................................. 290.8 21,515.3 1.3 875 4.5 Los Angeles, CA.............................. 394.6 4,229.3 0.7 924 4.9 Private industry........................... 390.5 3,623.3 0.3 899 4.2 Natural resources and mining............. 0.5 12.6 5.2 1,124 -15.2 Construction............................. 14.1 161.0 0.6 944 7.6 Manufacturing............................ 15.3 451.1 (6) 983 (6) Trade, transportation, and utilities..... 55.3 808.4 0.3 782 4.5 Information.............................. 8.7 212.3 (6) 1,528 3.8 Financial activities..................... 25.0 246.2 -2.0 1,420 4.1 Professional and business services....... 43.0 608.0 0.1 1,048 4.6 Education and health services............ 27.9 469.5 0.8 838 3.7 Leisure and hospitality.................. 27.0 403.1 2.0 504 2.4 Other services........................... 173.6 251.0 1.7 431 4.6 Government................................. 4.0 606.0 3.0 1,078 (6) Cook, IL..................................... 137.6 2,559.5 0.2 981 4.1 Private industry........................... 136.3 2,246.2 0.5 973 4.0 Natural resources and mining............. 0.1 1.4 -2.3 997 1.2 Construction............................. 12.1 98.7 -1.5 1,174 2.7 Manufacturing............................ 7.1 239.5 -1.6 983 2.6 Trade, transportation, and utilities..... 27.6 476.9 -0.4 788 2.9 Information.............................. 2.5 58.7 0.1 1,418 7.9 Financial activities..................... 15.8 218.9 -0.5 1,620 9.6 Professional and business services....... 28.1 442.6 1.9 1,229 3.1 Education and health services............ 13.5 366.2 2.0 826 3.1 Leisure and hospitality.................. 11.5 242.4 1.5 421 1.4 Other services........................... 13.8 96.9 -0.2 697 3.1 Government................................. 1.4 313.3 -1.8 1,037 5.1 New York, NY................................. 117.1 2,363.8 1.9 1,540 6.4 Private industry........................... 116.8 1,913.3 2.3 1,659 6.6 Natural resources and mining............. 0.0 0.1 -3.1 2,638 106.3 Construction............................. 2.3 35.2 7.6 1,504 9.5 Manufacturing............................ 3.1 38.2 -4.5 1,265 18.1 Trade, transportation, and utilities..... 21.9 249.1 1.7 1,141 4.8 Information.............................. 4.3 135.5 0.4 1,897 4.3 Financial activities..................... 18.4 379.6 2.3 3,042 8.2 Professional and business services....... 24.3 486.5 2.6 1,771 7.2 Education and health services............ 8.5 284.7 1.1 993 3.8 Leisure and hospitality.................. 11.1 209.0 3.1 732 4.0 Other services........................... 17.2 87.1 1.7 897 2.4 Government................................. 0.3 450.6 0.2 1,037 3.4 Harris, TX................................... 94.7 2,023.3 4.4 1,026 6.9 Private industry........................... 94.2 1,779.4 4.9 1,044 7.0 Natural resources and mining............. 1.5 78.7 10.4 2,857 6.6 Construction............................. 6.5 152.9 7.6 979 7.5 Manufacturing............................ 4.6 181.3 4.0 1,273 7.5 Trade, transportation, and utilities..... 21.5 421.2 3.7 917 6.4 Information.............................. 1.3 33.1 3.8 1,258 10.0 Financial activities..................... 10.4 120.6 2.5 1,242 5.6 Professional and business services....... 18.7 339.8 5.3 1,156 7.5 Education and health services............ 9.9 210.2 4.4 841 4.1 Leisure and hospitality.................. 7.2 179.2 5.0 377 2.7 Other services........................... 10.9 58.7 2.0 597 8.0 Government................................. 0.5 243.9 1.2 894 4.6 Maricopa, AZ................................. 97.7 1,798.0 0.9 827 3.9 Private industry........................... 97.1 1,614.4 0.8 812 3.7 Natural resources and mining............. 0.5 9.8 -2.8 703 9.3 Construction............................. 10.3 169.4 -7.6 842 4.6 Manufacturing............................ 3.5 133.5 -2.9 1,118 3.6 Trade, transportation, and utilities..... 20.9 373.0 2.7 805 4.8 Information.............................. 1.6 31.0 -0.8 1,014 7.0 Financial activities..................... 12.4 150.8 -0.6 1,052 3.4 Professional and business services....... 21.0 316.7 1.9 803 4.3 Education and health services............ 9.4 195.9 4.8 857 3.5 Leisure and hospitality.................. 7.0 179.2 1.9 390 2.1 Other services........................... 7.0 51.0 3.4 564 2.0 Government................................. 0.7 183.6 1.6 946 5.2 Orange, CA................................... 94.7 1,519.5 -1.0 952 3.4 Private industry........................... 93.3 1,363.2 -1.3 939 2.8 Natural resources and mining............. 0.2 6.2 -6.8 588 10.7 Construction............................. 7.1 105.6 -3.5 1,016 7.2 Manufacturing............................ 5.4 177.1 (6) 1,150 (6) Trade, transportation, and utilities..... 17.8 278.2 0.4 892 (6) Information.............................. 1.4 30.1 -2.2 1,340 7.5 Financial activities..................... 11.4 128.1 -7.7 1,445 (6) Professional and business services....... 19.2 274.6 (6) 1,000 (6) Education and health services............ 9.8 139.6 2.9 833 3.3 Leisure and hospitality.................. 7.0 175.1 1.7 410 5.1 Other services........................... 14.0 48.4 -0.4 561 4.1 Government................................. 1.4 156.3 1.1 1,062 6.7 Dallas, TX................................... 67.6 1,492.6 3.2 1,011 5.4 Private industry........................... 67.1 1,330.0 3.2 1,022 5.4 Natural resources and mining............. 0.6 7.1 -4.7 2,879 -1.1 Construction............................. 4.4 84.1 4.4 935 1.4 Manufacturing............................ 3.2 144.2 -0.4 1,202 8.1 Trade, transportation, and utilities..... 15.0 307.2 2.3 974 6.1 Information.............................. 1.7 48.6 -4.6 1,371 7.3 Financial activities..................... 8.7 145.7 2.8 1,331 5.2 Professional and business services....... 14.4 274.3 5.9 1,108 5.8 Education and health services............ 6.6 144.7 6.6 968 6.8 Leisure and hospitality.................. 5.2 131.2 3.6 430 2.6 Other services........................... 6.4 40.6 1.2 602 2.9 Government................................. 0.5 162.5 2.9 920 5.0 San Diego, CA................................ 91.7 1,334.7 0.2 890 4.8 Private industry........................... 90.4 1,108.8 -0.1 868 4.7 Natural resources and mining............. 0.8 11.6 -4.1 540 4.0 Construction............................. 7.2 90.9 -6.5 916 6.3 Manufacturing............................ 3.2 102.4 (6) 1,190 6.6 Trade, transportation, and utilities..... 14.6 219.8 0.3 730 5.8 Information.............................. 1.3 37.5 0.5 1,873 1.7 Financial activities..................... 9.9 81.5 -3.3 1,108 3.5 Professional and business services....... 16.4 217.9 0.6 1,076 6.0 Education and health services............ 8.0 127.1 (6) 812 4.1 Leisure and hospitality.................. 6.9 163.6 2.8 389 3.5 Other services........................... 22.1 56.6 1.1 482 2.8 Government................................. 1.3 225.9 1.7 996 4.8 King, WA..................................... 75.9 1,182.2 2.9 1,028 3.8 Private industry........................... 75.4 1,027.6 3.3 1,033 3.5 Natural resources and mining............. 0.4 3.3 3.4 1,224 1.4 Construction............................. 6.8 72.9 11.0 1,002 6.5 Manufacturing............................ 2.5 112.0 1.9 1,386 0.8 Trade, transportation, and utilities..... 14.8 219.5 2.0 903 6.1 Information.............................. 1.8 75.8 5.0 1,829 4.1 Financial activities..................... 7.0 76.4 -1.0 1,272 3.3 Professional and business services....... 12.9 188.1 4.4 1,180 1.1 Education and health services............ 6.3 120.6 2.7 812 4.5 Leisure and hospitality.................. 6.0 113.7 3.9 427 2.4 Other services........................... 16.7 45.4 0.9 571 7.9 Government................................. 0.5 154.6 0.6 995 6.0 Miami-Dade, FL............................... 85.9 1,002.1 1.0 814 3.8 Private industry........................... 85.6 868.2 0.8 788 3.7 Natural resources and mining............. 0.5 9.2 0.3 496 6.0 Construction............................. 6.2 53.5 1.5 841 -1.1 Manufacturing............................ 2.6 48.0 -1.7 735 1.9 Trade, transportation, and utilities..... 23.1 252.6 0.9 747 2.3 Information.............................. 1.5 20.7 -0.7 1,163 4.6 Financial activities..................... 10.4 71.6 -0.9 1,161 5.6 Professional and business services....... 17.3 136.4 -1.5 949 7.5 Education and health services............ 8.9 135.4 3.1 796 4.6 Leisure and hospitality.................. 5.7 101.8 1.3 458 2.5 Other services........................... 7.6 35.7 1.9 525 5.8 Government................................. 0.3 133.9 2.4 969 4.8 (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, second quarter 2007(2) Employment Average weekly wage(4) Establishments, second quarter County(3) 2007 Percent Percent (thousands) June change, Average change, 2007 June weekly second (thousands) 2006-07(5) wage quarter 2006-07(5) United States(6)......... 8,945.9 137,018.2 1.2 $820 4.6 Jefferson, AL............ 18.9 365.4 (7) 823 5.2 Anchorage Borough, AK.... 8.1 148.9 -1.3 887 5.7 Maricopa, AZ............. 97.7 1,798.0 0.9 827 3.9 Pulaski, AR.............. 14.6 251.8 0.6 740 4.2 Los Angeles, CA.......... 394.6 4,229.3 0.7 924 4.9 Denver, CO............... 25.8 446.5 2.6 989 5.3 Hartford, CT............. 25.3 512.0 1.5 1,035 6.7 New Castle, DE........... 18.8 284.4 -0.3 981 1.6 Washington, DC........... 31.9 683.2 0.8 1,357 4.3 Miami-Dade, FL........... 85.9 1,002.1 1.0 814 3.8 Fulton, GA............... 39.6 759.6 1.6 1,082 6.2 Honolulu, HI............. 24.7 454.8 0.5 758 4.0 Ada, ID.................. 15.3 215.7 2.0 748 0.5 Cook, IL................. 137.6 2,559.5 0.2 981 4.1 Marion, IN............... 24.0 582.2 0.7 826 1.0 Polk, IA................. 14.5 277.4 2.0 811 4.2 Johnson, KS.............. 20.1 318.1 3.1 867 4.8 Jefferson, KY............ 21.9 443.4 2.2 810 4.1 East Baton Rouge, LA..... 13.8 257.5 0.4 736 4.5 Cumberland, ME........... 12.3 176.1 0.1 741 4.5 Montgomery, MD........... 32.8 466.7 0.3 1,108 6.7 Middlesex, MA............ 47.2 826.7 1.5 1,179 6.0 Wayne, MI................ 32.4 755.2 -2.9 933 2.6 Hennepin, MN............. 43.4 856.2 0.4 1,059 8.1 Hinds, MS................ 6.5 128.1 -0.6 714 3.6 St. Louis, MO............ 33.1 618.2 0.6 883 2.4 Yellowstone, MT.......... 5.6 77.7 2.4 675 8.3 Douglas, NE.............. 15.6 320.7 1.1 767 2.5 Clark, NV................ 48.4 930.0 1.1 773 3.1 Hillsborough, NH......... 12.4 198.7 0.3 922 (7) Bergen, NJ............... 35.4 462.0 0.9 1,022 3.5 Bernalillo, NM........... 17.6 337.7 1.5 724 3.0 New York, NY............. 117.1 2,363.8 1.9 1,540 6.4 Mecklenburg, NC.......... 31.8 565.3 4.6 929 1.5 Cass, ND................. 5.7 97.9 2.4 672 4.8 Cuyahoga, OH............. 37.6 757.6 -0.3 842 2.1 Oklahoma, OK............. 23.5 421.3 0.7 729 2.5 Multnomah, OR............ 27.3 450.5 2.5 842 5.4 Allegheny, PA............ 35.3 697.8 1.0 874 4.7 Providence, RI........... 18.2 291.2 0.1 801 2.0 Greenville, SC........... 12.3 238.6 2.8 716 2.3 Minnehaha, SD............ 6.3 116.3 2.4 677 5.3 Shelby, TN............... 20.1 512.0 0.8 830 4.8 Harris, TX............... 94.7 2,023.3 4.4 1,026 6.9 Salt Lake, UT............ 38.3 590.3 4.2 776 7.6 Chittenden, VT........... 5.8 95.4 -0.5 804 4.4 Fairfax, VA.............. 32.6 592.2 1.0 1,269 4.9 King, WA................. 75.9 1,182.2 2.9 1,028 3.8 Kanawha, WV.............. 6.1 110.1 0.3 721 3.7 Milwaukee, WI............ 21.1 503.5 0.9 818 4.3 Laramie, WY.............. 3.1 43.4 1.9 685 6.7 San Juan, PR............. 13.6 293.5 -2.8 546 7.5 St. Thomas, VI........... 1.8 23.4 -0.1 643 -0.2 (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, second quarter 2007(2) Employment Average weekly wage(3) Establishments, second quarter State 2007 Percent Percent (thousands) June change, Average change, 2007 June weekly second (thousands) 2006-07 wage quarter 2006-07 United States(4)......... 8,945.9 137,018.2 1.2 $820 4.6 Alabama.................. 120.1 1,965.4 1.1 697 3.6 Alaska................... 21.1 325.8 -0.5 832 5.6 Arizona.................. 158.9 2,612.4 1.2 786 4.4 Arkansas................. 82.7 1,186.5 0.3 639 4.2 California............... 1,291.3 15,832.5 0.8 935 5.4 Colorado................. 179.4 2,326.9 2.2 832 4.8 Connecticut.............. 112.5 1,714.2 0.9 1,033 6.4 Delaware................. 29.1 430.2 0.0 870 2.2 District of Columbia..... 31.9 683.2 0.8 1,357 4.3 Florida.................. 604.8 7,894.2 0.2 743 3.2 Georgia.................. 270.4 4,091.5 1.4 792 6.5 Hawaii................... 38.6 631.2 1.4 736 4.2 Idaho.................... 57.1 679.1 3.0 626 2.3 Illinois................. 358.6 5,956.3 0.8 874 4.4 Indiana.................. 158.2 2,933.4 0.5 702 2.6 Iowa..................... 93.4 1,518.6 0.9 664 3.9 Kansas................... 85.7 1,370.7 2.0 702 4.8 Kentucky................. 109.8 1,828.2 1.7 700 4.2 Louisiana................ 119.9 1,880.2 3.2 711 4.1 Maine.................... 50.0 619.6 0.6 658 4.1 Maryland................. 164.0 2,584.9 0.7 899 5.3 Massachusetts............ 210.1 3,300.7 1.2 1,008 4.8 Michigan................. 257.1 4,252.9 -1.4 807 2.9 Minnesota................ 170.7 2,730.9 0.0 834 5.6 Mississippi.............. 69.7 1,137.4 0.9 609 3.6 Missouri................. 174.7 2,764.6 0.8 727 3.4 Montana.................. 42.3 449.8 1.7 611 6.3 Nebraska................. 58.7 930.9 1.6 654 3.5 Nevada................... 74.7 1,297.9 1.0 776 3.7 New Hampshire............ 49.0 643.7 0.7 823 6.3 New Jersey............... 278.1 4,066.7 0.4 989 4.3 New Mexico............... 53.7 833.3 1.1 686 5.2 New York................. 576.8 8,688.8 1.3 1,020 5.9 North Carolina........... 251.0 4,090.5 3.0 718 4.1 North Dakota............. 25.1 347.7 1.5 619 4.7 Ohio..................... 290.5 5,384.6 -0.1 740 3.4 Oklahoma................. 99.1 1,538.5 1.6 665 4.1 Oregon................... 130.8 1,761.6 1.7 742 4.5 Pennsylvania............. 338.7 5,740.3 1.1 802 4.6 Rhode Island............. 36.1 492.9 0.3 774 2.5 South Carolina........... 115.8 1,917.4 3.0 665 2.9 South Dakota............. 30.1 404.3 2.1 590 4.8 Tennessee................ 140.7 2,768.7 0.7 729 3.6 Texas.................... 548.7 10,296.1 3.4 827 5.9 Utah..................... 86.3 1,233.7 4.4 698 6.6 Vermont.................. 24.7 306.6 -0.5 698 5.0 Virginia................. 227.4 3,731.5 1.0 859 4.4 Washington............... 216.7 2,989.8 2.7 835 4.6 West Virginia............ 48.7 717.1 0.3 659 3.6 Wisconsin................ 158.2 2,845.8 0.4 709 3.7 Wyoming.................. 24.4 288.3 3.3 739 8.0 Puerto Rico.............. 56.9 1,020.7 -1.6 460 6.0 Virgin Islands........... 3.4 46.9 3.4 707 4.1 (1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. (2) Data are preliminary. (3) Average weekly wages were calculated using unrounded data. (4) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.