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Technical information: (202) 691-6567 USDL 08-0455 http://www.bls.gov/cew/ For release: 10:00 A.M. EDT Media contact: 691-5902 Wednesday, April 9, 2008 COUNTY EMPLOYMENT AND WAGES: THIRD QUARTER 2007 In September 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 8.6 percent, compared with national job growth of 0.9 percent. Clayton County, Ga., had the largest over-the-year gain in average weekly wages in the third quarter of 2007, with an increase of 23.9 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 4.3 percent over the same time span. Of the 328 largest counties in the United States, as measured by 2006 annual average employment, 130 had over-the-year percentage growth in employment above the national average (0.9 percent) in September 2007; 179 large counties experienced changes below the national average. The percent change in average weekly wages was higher than the national average (4.3 percent) in 101 of the largest U.S. counties, but was below the national average in 207 counties. Table A. Top 10 large counties ranked by September 2007 employment, September 2006-07 employment growth, and September 2006-07 percent growth in employment -------------------------------------------------------------------------------------------------------- Employment in large counties -------------------------------------------------------------------------------------------------------- September 2007 employment | Growth in employment, | Percent growth in employment, (thousands) | September 2006-07 | September 2006-07 | (thousands) | -------------------------------------------------------------------------------------------------------- | | United States 136,246.9| United States 1,216.7| United States 0.9 -------------------------------------------------------------------------------------------------------- | | Los Angeles, Calif. 4,191.6| Harris, Texas 74.7| Orleans, La. 8.6 Cook, Ill. 2,541.5| New York, N.Y. 46.8| Fort Bend, Texas 7.1 New York, N.Y. 2,350.3| Dallas, Texas 32.7| Williamson, Tenn. 5.8 Harris, Texas 2,028.0| King, Wash. 26.6| Wake, N.C. 5.2 Maricopa, Ariz. 1,825.1| Wake, N.C. 22.3| Utah, Utah 5.0 Orange, Calif. 1,503.8| Mecklenburg, N.C. 21.8| Hidalgo, Texas 4.5 Dallas, Texas 1,487.3| Tarrant, Texas 19.8| Snohomish, Wash. 4.4 San Diego, Calif. 1,325.9| Salt Lake, Utah 19.5| Mecklenburg, N.C. 4.0 King, Wash. 1,182.8| Bexar, Texas 18.1| Charleston, S.C. 3.8 Miami-Dade, Fla. 1,012.4| San Francisco, Calif. 18.0| Harris, Texas 3.8 | | Arlington, Va. 3.8 | | -------------------------------------------------------------------------------------------------------- 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 number of employer reports surpassed the 9.0 million mark this quarter; the number of employer reports crossed the 8.0 million mark in third quarter 2001. The employer reports in third quarter 2007 cover 136.2 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. September 2007 employment and 2007 third-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 and second quarter 2007 also are available on the BLS Web site. Updated data for first and second quarter 2007 and preliminary data for third quarter 2007 will be available later in April on the BLS Web site. Large County Employment In September 2007, national employment, as measured by the QCEW program, was 136.2 million, up by 0.9 percent from September 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 742,807 over the year, accounting for 61.1 percent of the overall U.S. employment increase. Employment rose in 217 of the large counties from September 2006 to September 2007. Orleans County, La., had the largest over- the-year percentage increase in employment (8.6 percent). Fort Bend, Texas, had the next largest increase, 7.1 percent, followed by the counties of Williamson, Tenn. (5.8 percent), Wake, N.C. (5.2 percent), and Utah, Utah (5.0 percent). The large employment gains in Orleans County 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 86 counties from September 2006 to September 2007. The largest percentage decline in employment was in Trumbull County, Ohio (-5.7 percent). Collier, Fla., had the next largest employment decline (-5.4 percent), followed by the counties of Sarasota, Fla. (-4.3 percent), Manatee, Fla. (-4.2 percent), and Atlantic, N.J. (-3.8 percent). The largest gains in the level of employment from September 2006 to September 2007 were recorded in the counties of Harris, Texas (74,700), New York, N.Y. (46,800), Dallas, Texas (32,700), King, Wash. (26,600), and Wake, N.C. (22,300). (See table A.) The largest decline in employment levels occurred in Orange, Calif. (-19,100), followed by the counties of Wayne, Mich. (-18,000), Oakland, Mich. (-9,600), Pinellas, Fla. (-9,500), and Macomb, Mich. (-9,400). Table B. Top 10 large counties ranked by third quarter 2007 average weekly wages, third quarter 2006-07 growth in average weekly wages, and third 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 average third quarter 2007 | wage, third quarter 2006-07 | weekly wage, third | | quarter 2006-07 -------------------------------------------------------------------------------------------------------- | | United States $818| United States $34| United States 4.3 -------------------------------------------------------------------------------------------------------- | | Santa Clara, Calif. $1,585| Clayton, Ga. $177| Clayton, Ga. 23.9 New York, N.Y. 1,544| Santa Clara, Calif. 167| Muscogee, Ga. 12.1 Washington, D.C. 1,376| New York, N.Y. 123| Santa Clara, Calif. 11.8 Arlington, Va. 1,364| Fairfield, Conn. 100| Rock Island, Ill. 11.5 San Mateo, Calif. 1,322| Suffolk, Mass. 93| Davidson, Tenn. 9.1 Suffolk, Mass. 1,299| Rock Island, Ill. 87| Weld, Colo. 8.7 Fairfield, Conn. 1,298| King, Wash. 84| New York, N.Y. 8.7 San Francisco, Calif. 1,286| Muscogee, Ga. 75| Fairfield, Conn. 8.3 Fairfax, Va. 1,243| Davidson, Tenn. 72| Kitsap, Wash. 8.3 Somerset, N.J. 1,210| Washington, D.C. 69| Butler, Ohio 8.1 | | -------------------------------------------------------------------------------------------------------- Large County Average Weekly Wages The national average weekly wage in the third quarter of 2007 was $818. Average weekly wages were higher than the national average in 112 of the largest 328 U.S. counties. Santa Clara, Calif., held the top position among the highest-paid large counties with an average weekly wage of $1,585. New York County, N.Y., was second with an average weekly wage of $1,544, followed by Washington, D.C. ($1,376), Arlington, Va. ($1,364), and San Mateo, Calif. ($1,322). (See table B.) There were 215 counties with an average weekly wage below the national average in the third quarter of 2007. The lowest average weekly wage was reported in Cameron County, Texas ($518), followed by the counties of Hidalgo, Texas ($529), Horry, S.C. ($536), Webb, Texas ($548), and Yakima, Wash. ($568). (See table 1.) Over the year, the national average weekly wage rose by 4.3 percent. Among the largest counties, Clayton County, Ga., led the nation in growth in average weekly wages, with an increase of 23.9 percent from the third quarter of 2006. Muscogee, Ga., was second with growth of 12.1 percent, followed by the counties of Santa Clara, Calif. (11.8 percent), Rock Island, Ill. (11.5 percent), and Davidson, Tenn. (9.1 percent). Ten large counties experienced over-the-year declines in average weekly wages. Among the five largest decreases in wages, Trumbull, Ohio, had the greatest decline (-10.6 percent), followed by the counties of Vanderburgh, Ind. (-6.1 percent), Genesee, Mich. (-4.0 percent), Saginaw, Mich. (-3.1 percent), and Montgomery, Ohio (-3.0 percent). Ten Largest U.S. Counties Seven of the 10 largest counties (based on 2006 annual average employment levels) experienced over-the-year percent increases in employment in September 2007. Harris, Texas, experienced the largest percent gain in employment among the 10 largest counties with a 3.8 percent increase. Within Harris County, the largest gains in employment were in construction (5.5 percent) and education and health services (5.4 percent). King, Wash., had the next largest increase in employment, 2.3 percent, followed by Dallas, Texas (2.2 percent). September employment levels remained stable over the year in both San Diego, Calif., and Cook, Ill. (0.0 percent each). Orange, Calif., experienced a 1.3 percent decrease in employment over the year. Within Orange County, five industry groups experienced employment declines, with financial activities experiencing the largest decline, -9.8 percent. (See table 2.) Each of the 10 largest U.S. counties saw an over-the-year increase in average weekly wages. New York, N.Y., had the fastest growth in wages among the 10 largest counties, with a gain of 8.7 percent. Within New York County, average weekly wages increased the most in the financial activities industry (16.3 percent), followed by the natural resources and mining industry (11.8 percent). Because natural resources and mining is a small industry in New York County, its over-the-year average weekly wage growth had little impact on the county’s overall average weekly wage growth. King, Wash., was second in wage growth with a gain of 8.0 percent, followed by Harris, Texas (6.7 percent). The smallest wage gain among the 10 largest counties occurred in Orange, Calif. (2.6 percent), followed by Cook, Ill. (3.3 percent), and Los Angeles, Calif. (3.4 percent). Largest County by State Table 3 shows September 2007 employment and the 2007 third 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 September 2007 ranged from approximately 4.19 million in Los Angeles County, Calif., to 43,900 in Laramie County, Wyo. The highest average weekly wage of these counties was in New York, N.Y. ($1,544), while the lowest average weekly wage was in Yellowstone, Mont. ($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 fourth quarter 2007 is scheduled to be released on Thursday, July 24, 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 re- lease 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 lev- els 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 329 counties presented in this re- lease were derived using 2006 preliminary annual averages of employment. For 2007 data, four counties have been added to the publication tables: Butte, Calif., Tippe- canoe, Ind., Saratoga, N.Y., and Williamson, Tenn. These counties will be included in all 2007 quarterly releases. One county, Boone, Ky., which was published in the 2006 releases, will be excluded from this and future 2007 releases because 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 released by the individual states. These potential differences result from the states' con- tinuing receipt of UI data over time and ongoing review and editing. The individual states determine their data release timetables. Differences between QCEW, BED, and CES employment measures The Bureau publishes three different establishment-based employment measures for any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED), and Current Employment Statistics (CES)--makes use of the quarterly UI employment reports in producing data; however, each measure has a somewhat different universe coverage, estimation procedure, and publication product. Differences in coverage and estimation methods can result in somewhat different measures of employment change over time. It is important to understand program dif- ferences and the intended uses of the program products. (See table.) Additional in- formation on each program can be obtained from the program Web sites shown in the table. Summary of Major Differences between QCEW, BED, and CES Employment Measures --------------------------------------------------------------------------------- | QCEW | BED | CES -----------|---------------------|----------------------|------------------------ Source |--Count of UI admini-|--Count of longitudi- |--Sample survey: | strative records | nally-linked UI ad- | 400,000 establish- | submitted by 9.0 | ministrative records| ments | million establish- | submitted by 6.9 | | 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 submitted by four major federal payroll processing centers on behalf of all federal agencies, with the exception of a few agencies which still report directly to the individual SWA. In addition to the quarterly contribution reports, employers who operate multi- ple establishments within a state complete a questionnaire, called the "Multiple Worksite Report," which provides detailed information on the location and industry of each of their establishments. The employment and wage data included in this re- lease are derived from microdata summaries of 9.0 million employer reports of em- ployment 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 agricultural workers on small farms, all members of the Armed Forces, elected officials in most states, most employees of railroads, some domestic workers, most student workers at schools, and employees of certain small nonprofit organizations. State and federal UI laws change periodically. These changes may have an impact on the employment and wages reported by employers covered under the UI program. Cover- age changes may affect the over-the-year comparisons presented in this news 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 em- ployees of covered firms are reported, including production and sales workers, cor- poration officials, executives, supervisory personnel, and clerical workers. Work- ers 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 aver- ages 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 gra- tuities, and, in some states, employer contributions to certain deferred compensa- tion plans such as 401(k) plans and stock options. Over-the-year comparisons of av- erage weekly wages may reflect fluctuations in average monthly employment and/or to- tal quarterly wages between the current quarter and prior year levels. Average weekly wages are affected by the ratio of full-time to part-time workers as well as the number of individuals in high-paying and low-paying occupations and the incidence of pay periods within a quarter. For instance, the average weekly wage of the work force could increase significantly when there is a large decline in the number of employees that had been receiving below-average wages. Wages may include payments to workers not present in the employment counts because they did not work during the pay period including the 12th of the month. When comparing average 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 occur when wages in the current period, which contain six pay periods, are compared with year-ago wages that include seven pay periods. The effect on over-the-year pay com- parisons can be pronounced in federal government due to the uniform nature of fed- eral payroll processing. This pattern may exist in private sector pay; however, be- cause 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 em- ployers and update, if necessary, the industry, location, and ownership classifica- tion of all establishments on a 4-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 in- dividual 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 ad- justed 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 unad- justed data maintained on the BLS Web site. Over-the-year change calculations based on data from the Web site, or from data published in prior BLS news releases, may differ substantially from the over-the-year changes presented in this news release. The adjusted data used to calculate the over-the-year change measures presented in this release account for most of the administrative changes--those occurring when employers update the industry, location, and ownership information of their 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. Com- parisons may not be valid for any time period other than the one featured in a re- lease even if the changes were calculated using adjusted data. County definitions are assigned according to Federal Information Processing Stan- dards Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104-106. Areas shown as counties include those designated as independent cities in some jurisdictions and, in Alaska, those designated as census areas where counties have not been created. County data also are presented for the New England states for comparative purposes even though townships are the more com- mon designation used in New England (and New Jersey). The regions referred to in this release are defined as census regions. Additional statistics and other information An annual bulletin, Employment and Wages, features comprehensive information by 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 is 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 re- quest from the Division of Administrative Statistics and Labor Turnover (Business Employment Dynamics), telephone (202) 691-6467; (http://www.bls.gov/bdm/); (e-mail: BDMInfo@bls.gov). Information in this release will be made available to sensory impaired individuals upon request. Voice phone: (202) 691-5200; TDD message referral phone number: 1-800- 877-8339.
Table 1. Covered(1) establishments, employment, and wages in the 329 largest counties, third quarter 2007(2) Employment Average weekly wage(4) Establishments, County(3) third quarter Percent Ranking Percent Ranking 2007 September change, by Average change, by (thousands) 2007 September percent weekly third percent (thousands) 2006-07(5) change wage quarter change 2006-07(5) United States(6)......... 9,012.8 136,246.9 0.9 - $818 4.3 - Jefferson, AL............ 18.9 363.6 (7) - 837 (7) - Madison, AL.............. 8.7 178.8 3.4 14 896 3.7 149 Mobile, AL............... 10.0 173.6 1.5 84 697 0.6 298 Montgomery, AL........... 6.7 138.6 0.0 218 692 3.3 193 Tuscaloosa, AL........... 4.4 86.8 1.8 73 701 3.7 149 Anchorage Borough, AK.... 8.1 149.2 0.2 200 894 5.5 48 Maricopa, AZ............. 99.3 1,825.1 0.2 200 822 3.8 140 Pima, AZ................. 21.0 373.9 (7) - 731 (7) - Benton, AR............... 5.5 96.0 1.1 112 713 3.6 168 Pulaski, AR.............. 14.7 250.9 0.6 157 751 4.3 102 Washington, AR........... 5.7 93.0 -0.2 234 663 3.3 193 Alameda, CA.............. 49.8 690.8 -0.5 257 1,080 2.1 261 Butte, CA................ 7.7 77.2 -1.1 282 641 6.3 27 Contra Costa, CA......... 28.2 345.5 -1.0 278 1,003 2.8 223 Fresno, CA............... 29.3 373.9 1.1 112 643 3.7 149 Kern, CA................. 17.5 291.6 0.2 200 720 7.0 15 Los Angeles, CA.......... 401.9 4,191.6 0.4 181 925 3.4 188 Marin, CA................ 11.5 109.1 0.6 157 1,021 4.5 92 Monterey, CA............. 12.3 182.0 0.5 168 738 6.2 32 Orange, CA............... 95.3 1,503.8 -1.3 289 924 2.6 236 Placer, CA............... 10.6 138.9 -0.2 234 810 4.1 117 Riverside, CA............ 43.8 629.5 -1.4 291 702 3.7 149 Sacramento, CA........... 51.8 640.7 -0.3 239 905 3.5 177 San Bernardino, CA....... 46.6 661.5 0.0 218 724 3.3 193 San Diego, CA............ 92.7 1,325.9 0.0 218 887 4.4 98 San Francisco, CA........ 44.8 563.4 3.3 17 1,286 3.4 188 San Joaquin, CA.......... 17.4 231.2 0.7 146 715 4.1 117 San Luis Obispo, CA...... 9.2 107.0 1.4 93 689 3.0 211 San Mateo, CA............ 23.0 343.1 1.2 106 1,322 3.6 168 Santa Barbara, CA........ 13.7 189.2 2.0 57 780 (7) - Santa Clara, CA.......... 56.9 902.3 1.7 76 1,585 11.8 3 Santa Cruz, CA........... 8.7 103.6 1.0 122 750 -1.3 310 Solano, CA............... 9.8 129.3 0.1 211 788 3.4 188 Sonoma, CA............... 18.0 196.4 0.8 137 814 3.8 140 Stanislaus, CA........... 14.3 179.2 -1.1 282 696 3.1 204 Tulare, CA............... 9.0 153.6 0.6 157 585 3.7 149 Ventura, CA.............. 21.9 317.2 -0.5 257 840 2.4 248 Yolo, CA................. 5.6 104.2 (7) - 759 0.1 305 Adams, CO................ 9.5 155.7 0.5 168 768 3.4 188 Arapahoe, CO............. 20.1 284.0 2.7 35 960 0.4 303 Boulder, CO.............. 13.0 161.1 2.3 47 989 4.0 125 Denver, CO............... 26.0 448.4 2.7 35 995 0.9 293 Douglas, CO.............. 9.6 91.7 2.9 32 832 5.9 36 El Paso, CO.............. 18.0 249.4 1.5 84 762 4.0 125 Jefferson, CO............ 19.2 212.5 1.3 100 841 3.7 149 Larimer, CO.............. 10.4 133.6 3.0 23 753 3.9 134 Weld, CO................. 6.1 84.6 3.1 20 727 8.7 6 Fairfield, CT............ 32.8 423.7 1.4 93 1,298 8.3 8 Hartford, CT............. 25.4 504.9 0.8 137 1,002 6.3 27 New Haven, CT............ 22.6 367.7 0.2 200 883 5.5 48 New London, CT........... 6.9 131.0 0.8 137 855 5.6 45 New Castle, DE........... 18.8 282.3 -0.4 248 955 0.0 306 Washington, DC........... 32.1 679.0 0.6 157 1,376 5.3 60 Alachua, FL.............. 6.6 128.8 1.7 76 689 1.6 279 Brevard, FL.............. 14.8 201.6 -2.5 303 771 4.8 79 Broward, FL.............. 65.0 747.5 -0.4 248 774 2.8 223 Collier, FL.............. 12.5 124.0 -5.4 314 748 3.5 177 Duval, FL................ 26.2 465.1 0.4 181 833 6.7 18 Escambia, FL............. 8.0 130.8 -0.1 230 649 3.5 177 Hillsborough, FL......... 36.9 639.0 0.0 218 778 2.5 240 Lake, FL................. 7.2 82.9 0.3 194 595 1.0 292 Lee, FL.................. 19.6 215.4 -3.7 310 703 2.0 267 Leon, FL................. 8.2 146.3 -0.2 234 724 4.3 102 Manatee, FL.............. 9.0 121.7 -4.2 312 653 2.7 228 Marion, FL............... 8.4 101.5 -2.3 301 594 1.7 274 Miami-Dade, FL........... 86.4 1,012.4 0.4 181 826 4.3 102 Okaloosa, FL............. 6.2 81.9 -2.8 306 675 5.0 67 Orange, FL............... 36.3 686.4 1.0 122 756 3.8 140 Palm Beach, FL........... 50.2 547.0 0.1 211 807 6.3 27 Pasco, FL................ 9.9 99.2 -0.9 275 584 -0.5 308 Pinellas, FL............. 31.5 434.4 -2.1 299 709 4.3 102 Polk, FL................. 12.6 202.2 -1.3 289 655 1.2 288 Sarasota, FL............. 15.1 151.6 -4.3 313 701 3.7 149 Seminole, FL............. 15.1 177.8 -0.6 263 708 1.7 274 Volusia, FL.............. 14.0 165.1 -1.4 291 594 2.4 248 Bibb, GA................. 4.7 83.3 0.5 168 658 2.5 240 Chatham, GA.............. 7.5 137.6 2.7 35 705 4.1 117 Clayton, GA.............. 4.4 114.9 1.3 100 919 23.9 1 Cobb, GA................. 20.5 319.3 0.8 137 874 0.5 302 De Kalb, GA.............. 16.3 296.6 -0.4 248 875 2.6 236 Fulton, GA............... 40.0 762.2 1.2 106 1,058 2.9 216 Gwinnett, GA............. 23.6 327.2 1.9 67 869 6.8 17 Muscogee, GA............. 4.8 97.1 -1.1 282 696 12.1 2 Richmond, GA............. 4.9 101.9 -0.4 248 709 4.1 117 Honolulu, HI............. 24.6 451.0 -0.4 248 786 5.8 40 Ada, ID.................. 15.2 213.9 1.1 112 749 2.9 216 Champaign, IL............ 4.1 92.4 0.7 146 705 4.8 79 Cook, IL................. 138.0 2,541.5 0.0 218 961 3.3 193 Du Page, IL.............. 35.6 600.0 0.0 218 980 5.8 40 Kane, IL................. 12.6 212.7 -0.5 257 742 2.8 223 Lake, IL................. 20.8 338.7 1.1 112 972 2.9 216 McHenry, IL.............. 8.4 104.8 1.1 112 713 2.3 254 McLean, IL............... 3.6 86.2 0.8 137 782 1.8 272 Madison, IL.............. 6.0 96.3 0.4 181 663 1.5 283 Peoria, IL............... 4.7 104.7 1.0 122 774 3.3 193 Rock Island, IL.......... 3.5 79.1 1.5 84 844 11.5 4 St. Clair, IL............ 5.4 96.8 0.7 146 673 4.8 79 Sangamon, IL............. 5.2 130.3 0.0 218 818 4.3 102 Will, IL................. 13.3 194.4 3.0 23 728 1.4 284 Winnebago, IL............ 6.9 138.3 1.6 81 712 2.3 254 Allen, IN................ 9.0 184.4 -0.5 257 692 1.6 279 Elkhart, IN.............. 4.9 126.0 -0.9 275 681 2.1 261 Hamilton, IN............. 7.5 111.5 (7) - 802 (7) - Lake, IN................. 10.2 195.1 -0.3 239 734 4.9 71 Marion, IN............... 24.1 584.8 1.2 106 830 2.1 261 St. Joseph, IN........... 6.0 125.5 0.0 218 684 2.7 228 Tippecanoe, IN........... 3.2 77.0 0.4 181 707 1.7 274 Vanderburgh, IN.......... 4.8 107.3 -1.5 296 678 -6.1 315 Linn, IA................. 6.3 123.7 2.1 56 791 6.5 23 Polk, IA................. 14.7 274.6 2.0 57 804 2.9 216 Scott, IA................ 5.2 89.4 0.4 181 680 4.5 92 Johnson, KS.............. 20.2 319.2 2.4 44 830 2.0 267 Sedgwick, KS............. 12.1 258.5 2.4 44 737 1.2 288 Shawnee, KS.............. 4.8 95.1 1.6 81 690 2.2 259 Wyandotte, KS............ 3.2 81.8 1.8 73 779 0.9 293 Fayette, KY.............. 9.1 174.9 0.7 146 734 2.8 223 Jefferson, KY............ 22.2 437.5 1.2 106 791 2.1 261 Caddo, LA................ 7.3 126.6 1.1 112 678 1.3 287 Calcasieu, LA............ 4.8 86.0 0.4 181 696 5.0 67 East Baton Rouge, LA..... 13.9 264.4 1.9 67 742 5.4 55 Jefferson, LA............ 13.8 197.0 1.2 106 754 3.7 149 Lafayette, LA............ 8.5 135.5 3.1 20 778 5.7 44 Orleans, LA.............. 10.2 166.2 8.6 1 887 1.1 290 Cumberland, ME........... 12.3 174.7 0.9 131 738 3.8 140 Anne Arundel, MD......... 14.4 233.5 0.5 168 875 3.7 149 Baltimore, MD............ 21.7 377.0 0.6 157 836 4.0 125 Frederick, MD............ 6.0 95.6 0.7 146 796 5.6 45 Harford, MD.............. 5.7 84.3 0.3 194 811 6.7 18 Howard, MD............... 8.5 147.7 0.9 131 945 3.7 149 Montgomery, MD........... 32.7 460.9 -0.3 239 1,090 5.1 64 Prince Georges, MD....... 15.6 317.6 1.2 106 901 3.9 134 Baltimore City, MD....... 14.1 346.3 0.5 168 937 3.1 204 Barnstable, MA........... 9.2 98.0 0.3 194 690 3.4 188 Bristol, MA.............. 15.6 221.2 -0.6 263 724 4.5 92 Essex, MA................ 20.8 301.5 0.2 200 881 4.3 102 Hampden, MA.............. 14.2 200.5 -0.6 263 760 3.5 177 Middlesex, MA............ 47.5 818.3 1.4 93 1,176 5.9 36 Norfolk, MA.............. 22.2 326.0 1.1 112 960 1.6 279 Plymouth, MA............. 13.8 179.1 -0.3 239 760 2.6 236 Suffolk, MA.............. 21.8 587.0 2.0 57 1,299 7.7 13 Worcester, MA............ 20.8 322.3 0.2 200 833 5.3 60 Genesee, MI.............. 7.9 142.5 -3.2 309 736 -4.0 314 Ingham, MI............... 6.8 161.6 -0.7 271 781 -1.1 309 Kalamazoo, MI............ 5.5 115.7 -1.1 282 737 3.5 177 Kent, MI................. 14.2 340.9 -0.8 273 735 1.1 290 Macomb, MI............... 17.8 315.2 -2.9 307 877 4.8 79 Oakland, MI.............. 39.1 692.0 -1.4 291 958 3.1 204 Ottawa, MI............... 5.7 112.3 -2.6 304 711 1.9 271 Saginaw, MI.............. 4.3 86.5 -2.9 307 697 -3.1 313 Washtenaw, MI............ 8.0 191.6 -1.9 298 954 4.5 92 Wayne, MI................ 32.2 747.7 -2.4 302 930 3.1 204 Anoka, MN................ 8.2 116.7 0.6 157 769 2.9 216 Dakota, MN............... 11.1 177.2 1.9 67 772 2.1 261 Hennepin, MN............. 44.3 849.5 0.8 137 1,043 5.4 55 Olmsted, MN.............. 3.7 91.7 1.4 93 904 3.2 199 Ramsey, MN............... 16.1 337.0 0.9 131 896 5.5 48 St. Louis, MN............ 6.2 98.4 2.0 57 667 4.2 110 Stearns, MN.............. 4.7 82.8 3.0 23 657 4.0 125 Harrison, MS............. 4.5 87.4 2.0 57 643 2.7 228 Hinds, MS................ 6.4 127.8 -0.3 239 717 3.0 211 Boone, MO................ 4.6 83.3 0.7 146 633 2.4 248 Clay, MO................. 5.1 91.2 3.0 23 779 3.5 177 Greene, MO............... 8.2 158.8 3.0 23 637 3.6 168 Jackson, MO.............. 18.8 371.0 1.3 100 826 3.6 168 St. Charles, MO.......... 8.2 124.7 0.9 131 694 2.4 248 St. Louis, MO............ 33.3 611.9 0.5 168 873 6.3 27 St. Louis City, MO....... 8.5 234.2 -1.0 278 887 1.4 284 Douglas, NE.............. 15.7 318.8 1.0 122 782 6.5 23 Lancaster, NE............ 8.0 158.0 (7) - 666 2.5 240 Clark, NV................ 48.8 920.2 -0.3 239 796 5.9 36 Washoe, NV............... 14.4 220.6 -0.4 248 776 3.7 149 Hillsborough, NH......... 12.5 197.9 0.4 181 899 4.4 98 Rockingham, NH........... 11.1 140.7 0.0 218 783 2.5 240 Atlantic, NJ............. 7.1 148.5 -3.8 311 719 4.1 117 Bergen, NJ............... 34.9 454.2 0.3 194 1,009 3.9 134 Burlington, NJ........... 11.5 203.9 -0.2 234 871 3.1 204 Camden, NJ............... 13.3 210.1 -1.0 278 833 4.0 125 Essex, NJ................ 21.5 357.4 -0.9 275 1,022 3.2 199 Gloucester, NJ........... 6.3 104.2 0.1 211 746 5.1 64 Hudson, NJ............... 14.0 237.7 0.6 157 1,110 4.2 110 Mercer, NJ............... 11.3 223.9 0.7 146 1,027 5.5 48 Middlesex, NJ............ 22.1 411.0 1.1 112 996 -0.1 307 Monmouth, NJ............. 21.1 257.5 -0.7 271 874 4.9 71 Morris, NJ............... 18.3 286.1 -1.1 282 1,142 0.4 303 Ocean, NJ................ 12.6 153.6 0.2 200 679 2.0 267 Passaic, NJ.............. 12.7 176.6 -1.1 282 853 2.4 248 Somerset, NJ............. 10.3 174.1 -0.6 263 1,210 5.8 40 Union, NJ................ 15.3 234.8 (7) - 1,056 (7) - Bernalillo, NM........... 17.6 335.2 0.5 168 732 3.1 204 Albany, NY............... 10.0 227.4 0.2 200 830 4.3 102 Bronx, NY................ 15.8 221.9 0.7 146 813 2.5 240 Broome, NY............... 4.5 95.8 1.6 81 662 2.5 240 Dutchess, NY............. 8.4 116.8 -1.4 291 841 2.9 216 Erie, NY................. 23.5 457.5 0.5 168 715 3.0 211 Kings, NY................ 45.2 469.0 1.5 84 718 4.1 117 Monroe, NY............... 18.0 379.3 -0.3 239 805 3.1 204 Nassau, NY............... 52.5 603.4 0.1 211 914 5.2 63 New York, NY............. 118.0 2,350.3 2.0 57 1,544 8.7 6 Oneida, NY............... 5.3 109.9 -0.2 234 652 4.0 125 Onondaga, NY............. 12.8 254.6 1.4 93 756 2.7 228 Orange, NY............... 10.0 131.3 0.7 146 686 1.6 279 Queens, NY............... 42.9 503.3 2.6 39 814 4.1 117 Richmond, NY............. 8.7 92.9 0.8 137 748 4.8 79 Rockland, NY............. 9.8 115.9 2.0 57 870 3.8 140 Saratoga, NY............. 5.4 76.6 0.6 157 694 4.0 125 Suffolk, NY.............. 50.3 626.9 0.9 131 891 4.7 86 Westchester, NY.......... 36.5 420.5 1.4 93 1,068 3.8 140 Buncombe, NC............. 8.0 117.6 2.9 32 648 3.7 149 Catawba, NC.............. 4.6 89.1 0.7 146 633 3.6 168 Cumberland, NC........... 6.2 118.1 1.1 112 650 7.4 14 Durham, NC............... 6.9 185.5 3.7 12 1,105 6.5 23 Forsyth, NC.............. 9.2 185.6 0.5 168 756 0.9 293 Guilford, NC............. 14.7 282.9 2.2 51 722 2.1 261 Mecklenburg, NC.......... 32.2 572.6 4.0 8 923 0.8 296 New Hanover, NC.......... 7.5 107.0 3.5 13 675 5.5 48 Wake, NC................. 28.0 453.5 5.2 4 808 3.5 177 Cass, ND................. 5.8 98.5 2.4 44 688 6.2 32 Butler, OH............... 7.3 148.7 1.8 73 751 8.1 10 Cuyahoga, OH............. 37.6 747.6 -0.8 273 832 3.6 168 Franklin, OH............. 29.5 690.2 1.3 100 831 3.2 199 Hamilton, OH............. 24.0 522.0 0.4 181 890 2.2 259 Lake, OH................. 6.7 100.9 0.2 200 669 3.7 149 Lorain, OH............... 6.3 99.6 -2.7 305 701 4.5 92 Lucas, OH................ 10.6 223.4 -1.0 278 732 1.7 274 Mahoning, OH............. 6.3 105.6 0.5 168 600 2.7 228 Montgomery, OH........... 12.8 268.7 -2.1 299 754 -3.0 312 Stark, OH................ 9.0 162.8 -0.3 239 643 1.7 274 Summit, OH............... 14.9 274.2 -0.1 230 740 3.5 177 Trumbull, OH............. 4.7 78.8 -5.7 315 690 -10.6 316 Oklahoma, OK............. 23.5 424.8 1.0 122 748 5.6 45 Tulsa, OK................ 19.4 348.2 2.3 47 743 5.4 55 Clackamas, OR............ 12.7 151.0 1.7 76 763 3.2 199 Jackson, OR.............. 6.7 86.2 0.3 194 627 4.7 86 Lane, OR................. 11.1 151.8 0.8 137 660 3.9 134 Marion, OR............... 9.4 143.9 1.3 100 661 3.3 193 Multnomah, OR............ 27.4 451.1 2.5 42 840 4.5 92 Washington, OR........... 16.1 251.8 0.4 181 967 4.7 86 Allegheny, PA............ 35.4 686.2 0.6 157 864 4.9 71 Berks, PA................ 9.1 168.6 -0.5 257 764 6.7 18 Bucks, PA................ 20.2 265.3 0.2 200 787 2.7 228 Butler, PA............... 4.8 80.3 2.2 51 806 (7) - Chester, PA.............. 15.0 241.5 2.3 47 1,015 (7) - Cumberland, PA........... 6.0 126.8 0.1 211 762 3.7 149 Dauphin, PA.............. 7.3 182.1 -0.4 248 804 5.0 67 Delaware, PA............. 13.6 211.1 1.1 112 844 2.6 236 Erie, PA................. 7.3 128.8 0.1 211 657 4.0 125 Lackawanna, PA........... 5.8 101.8 -0.4 248 629 2.4 248 Lancaster, PA............ 12.3 230.2 0.4 181 702 2.0 267 Lehigh, PA............... 8.6 178.5 0.0 218 837 7.0 15 Luzerne, PA.............. 7.9 142.8 0.1 211 653 4.8 79 Montgomery, PA........... 27.3 486.8 0.5 168 995 3.5 177 Northampton, PA.......... 6.5 100.5 1.0 122 717 2.3 254 Philadelphia, PA......... 30.3 630.8 -0.3 239 976 5.1 64 Washington, PA........... 5.3 79.5 0.4 181 722 0.7 297 Westmoreland, PA......... 9.5 137.7 -0.6 263 656 0.6 298 York, PA................. 9.1 178.4 1.4 93 728 4.7 86 Kent, RI................. 5.7 82.0 -0.6 263 725 4.2 110 Providence, RI........... 18.2 288.3 -1.5 296 779 -2.4 311 Charleston, SC........... 12.0 212.7 3.8 9 703 4.8 79 Greenville, SC........... 12.4 238.2 1.9 67 707 3.5 177 Horry, SC................ 8.3 119.3 1.0 122 536 3.7 149 Lexington, SC............ 5.6 96.5 2.2 51 640 4.6 91 Richland, SC............. 9.2 216.7 1.5 84 724 2.7 228 Spartanburg, SC.......... 6.0 119.9 2.0 57 710 2.3 254 Minnehaha, SD............ 6.3 115.5 2.7 35 695 4.4 98 Davidson, TN............. 18.5 449.0 (7) - 860 9.1 5 Hamilton, TN............. 8.7 194.8 -0.1 230 711 3.8 140 Knox, TN................. 11.1 229.7 1.0 122 695 3.7 149 Rutherford, TN........... 4.2 100.1 0.5 168 719 1.4 284 Shelby, TN............... 20.1 511.0 0.2 200 850 4.4 98 Williamson, TN........... 5.8 86.8 5.8 3 858 0.6 298 Bell, TX................. 4.5 98.6 3.0 23 644 4.9 71 Bexar, TX................ 31.9 721.4 2.6 39 715 3.5 177 Brazoria, TX............. 4.5 85.8 3.2 18 793 6.3 27 Brazos, TX............... 3.7 85.3 (7) - 629 (7) - Cameron, TX.............. 6.5 122.6 0.6 157 518 5.5 48 Collin, TX............... 16.2 283.8 3.2 18 981 5.5 48 Dallas, TX............... 67.7 1,487.3 2.2 51 1,002 4.2 110 Denton, TX............... 10.2 166.1 3.0 23 716 2.9 216 El Paso, TX.............. 13.2 269.8 2.0 57 593 4.0 125 Fort Bend, TX............ 7.9 124.6 7.1 2 854 4.3 102 Galveston, TX............ 5.2 96.2 (7) - 776 (7) - Harris, TX............... 95.1 2,028.0 3.8 9 1,015 6.7 18 Hidalgo, TX.............. 10.4 211.8 4.5 6 529 2.5 240 Jefferson, TX............ 5.8 124.5 1.9 67 787 0.6 298 Lubbock, TX.............. 6.7 122.8 1.0 122 616 3.0 211 McLennan, TX............. 4.9 105.0 1.7 76 656 3.8 140 Montgomery, TX........... 7.8 122.1 (7) - 740 3.6 168 Nueces, TX............... 8.1 151.6 1.5 84 709 6.0 34 Smith, TX................ 5.2 92.6 0.9 131 715 3.6 168 Tarrant, TX.............. 36.4 769.0 2.6 39 830 2.3 254 Travis, TX............... 28.0 572.6 3.1 20 911 2.7 228 Webb, TX................. 4.7 88.3 2.8 34 548 4.2 110 Williamson, TX........... 6.7 119.1 (7) - 781 (7) - Davis, UT................ 7.1 104.2 2.5 42 666 4.9 71 Salt Lake, UT............ 38.6 591.0 3.4 14 771 5.8 40 Utah, UT................. 12.9 177.6 5.0 5 646 4.9 71 Weber, UT................ 5.7 95.0 3.4 14 615 3.7 149 Chittenden, VT........... 5.9 95.8 -0.4 248 812 4.2 110 Arlington, VA............ 7.5 154.5 3.8 9 1,364 3.6 168 Chesterfield, VA......... 7.5 121.3 1.3 100 748 3.7 149 Fairfax, VA.............. 32.9 584.9 0.7 146 1,243 5.3 60 Henrico, VA.............. 9.2 180.3 3.0 23 833 2.5 240 Loudoun, VA.............. 8.3 129.0 1.5 84 1,011 4.7 86 Prince William, VA....... 6.9 103.9 -0.6 263 755 6.0 34 Alexandria City, VA...... 6.1 99.8 -1.4 291 1,130 6.4 26 Chesapeake City, VA...... 5.6 100.2 0.5 168 662 3.8 140 Newport News City, VA.... 4.0 99.2 1.5 84 753 5.9 36 Norfolk City, VA......... 5.8 143.0 0.8 137 822 7.9 12 Richmond City, VA........ 7.4 158.2 (7) - 945 (7) - Virginia Beach City, VA.. 11.6 177.8 0.6 157 650 4.2 110 Clark, WA................ 11.9 134.0 1.5 84 749 3.7 149 King, WA................. 76.3 1,182.8 2.3 47 1,129 8.0 11 Kitsap, WA............... 6.6 83.9 -0.1 230 770 8.3 8 Pierce, WA............... 20.4 278.0 2.0 57 755 5.4 55 Snohomish, WA............ 17.7 255.0 4.4 7 842 5.0 67 Spokane, WA.............. 15.1 210.6 1.9 67 681 4.9 71 Thurston, WA............. 6.8 99.8 3.0 23 782 6.7 18 Whatcom, WA.............. 6.9 82.7 2.2 51 659 3.9 134 Yakima, WA............... 7.9 108.1 -0.5 257 568 5.4 55 Kanawha, WV.............. 6.1 108.8 0.3 194 704 4.1 117 Brown, WI................ 6.7 150.4 0.0 218 719 1.8 272 Dane, WI................. 14.1 306.2 (7) - 783 (7) - Milwaukee, WI............ 21.2 497.8 0.0 218 802 2.8 223 Outagamie, WI............ 5.0 104.8 1.7 76 712 4.9 71 Racine, WI............... 4.2 76.4 -1.1 282 738 3.2 199 Waukesha, WI............. 13.3 236.4 -0.6 263 814 3.0 211 Winnebago, WI............ 3.8 90.4 0.4 181 765 3.9 134 San Juan, PR............. 13.6 289.0 -2.7 (8) 538 3.5 (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, third quarter 2007(2) Employment Average weekly wage(3) Establishments, third quarter County by NAICS supersector 2007 Percent Percent (thousands) September change, Average change, 2007 September weekly third (thousands) 2006-07(4) wage quarter 2006-07(4) United States(5)............................. 9,012.8 136,246.9 0.9 $818 4.3 Private industry........................... 8,721.6 114,790.8 0.9 810 4.5 Natural resources and mining............. 124.7 1,931.5 1.7 820 7.8 Construction............................. 895.5 7,774.4 -1.0 876 5.7 Manufacturing............................ 361.4 13,845.4 -2.2 987 4.3 Trade, transportation, and utilities..... 1,916.9 26,299.2 1.2 707 3.2 Information.............................. 144.3 3,033.1 0.0 1,274 4.6 Financial activities..................... 871.8 8,123.2 -0.7 1,200 5.9 Professional and business services....... 1,484.6 18,017.6 1.7 998 6.4 Education and health services............ 825.8 17,506.6 2.9 775 3.6 Leisure and hospitality.................. 726.7 13,562.6 1.9 348 4.2 Other services........................... 1,162.9 4,433.8 1.2 531 4.1 Government................................. 291.2 21,456.1 1.0 859 3.2 Los Angeles, CA.............................. 401.9 4,191.6 0.4 925 3.4 Private industry........................... 397.9 3,626.2 0.1 901 3.1 Natural resources and mining............. 0.5 12.7 5.0 1,095 -8.3 Construction............................. 14.3 160.4 -0.9 945 5.4 Manufacturing............................ 15.2 444.7 (6) 961 (6) Trade, transportation, and utilities..... 55.3 811.9 -0.1 765 2.0 Information.............................. 8.8 216.3 8.5 1,520 -0.3 Financial activities..................... 25.2 243.7 -2.6 1,483 (6) Professional and business services....... 43.4 608.9 -0.3 1,051 6.3 Education and health services............ 28.2 480.4 1.8 851 (6) Leisure and hospitality.................. 27.1 401.1 1.8 518 2.8 Other services........................... 179.8 246.0 0.0 439 5.8 Government................................. 4.0 565.4 2.3 1,080 (6) Cook, IL..................................... 138.0 2,541.5 0.0 961 3.3 Private industry........................... 136.6 2,232.8 0.2 958 3.6 Natural resources and mining............. 0.1 1.3 -7.7 1,063 3.5 Construction............................. 12.1 98.2 -1.6 1,207 5.5 Manufacturing............................ 7.1 237.2 -1.9 981 3.0 Trade, transportation, and utilities..... 27.6 472.2 -0.9 776 -0.5 Information.............................. 2.5 58.4 0.6 1,402 9.1 Financial activities..................... 15.8 215.4 -1.5 1,547 7.8 Professional and business services....... 28.2 441.6 0.9 1,179 3.1 Education and health services............ 13.6 369.2 1.6 843 3.7 Leisure and hospitality.................. 11.6 240.0 2.2 430 4.6 Other services........................... 13.8 95.0 0.7 691 3.0 Government................................. 1.4 308.7 -0.9 985 2.3 New York, NY................................. 118.0 2,350.3 2.0 1,544 8.7 Private industry........................... 117.7 1,906.7 2.3 1,667 9.6 Natural resources and mining............. 0.0 0.1 -1.9 1,749 11.8 Construction............................. 2.3 35.8 6.9 1,461 5.3 Manufacturing............................ 3.1 37.5 -4.7 1,158 3.0 Trade, transportation, and utilities..... 22.1 248.2 1.7 1,124 4.3 Information.............................. 4.4 135.6 1.0 1,916 4.5 Financial activities..................... 18.7 380.0 2.0 3,047 16.3 Professional and business services....... 24.6 482.2 2.3 1,769 8.6 Education and health services............ 8.6 283.3 2.0 1,011 4.8 Leisure and hospitality.................. 11.2 208.5 3.3 728 6.1 Other services........................... 17.4 87.2 1.5 889 3.7 Government................................. 0.3 443.5 0.7 1,014 1.5 Harris, TX................................... 95.1 2,028.0 3.8 1,015 6.7 Private industry........................... 94.5 1,783.4 4.3 1,027 7.1 Natural resources and mining............. 1.5 78.4 (6) 2,580 (6) Construction............................. 6.6 151.5 5.5 968 6.1 Manufacturing............................ 4.6 182.2 3.5 1,290 7.7 Trade, transportation, and utilities..... 21.7 424.7 3.9 901 6.0 Information.............................. 1.3 32.8 2.6 1,258 9.1 Financial activities..................... 10.5 120.7 2.0 1,256 7.3 Professional and business services....... 18.9 341.2 4.9 1,156 7.5 Education and health services............ 10.0 214.7 5.4 824 1.7 Leisure and hospitality.................. 7.3 176.2 3.2 366 2.2 Other services........................... 11.0 58.4 3.9 595 7.6 Government................................. 0.5 244.6 0.6 922 3.1 Maricopa, AZ................................. 99.3 1,825.1 0.2 822 3.8 Private industry........................... 98.6 1,605.3 -0.1 811 4.1 Natural resources and mining............. 0.5 8.5 2.9 723 6.0 Construction............................. 10.6 165.8 -7.6 834 3.9 Manufacturing............................ 3.6 132.2 -3.7 1,116 3.2 Trade, transportation, and utilities..... 21.6 374.9 2.0 777 3.5 Information.............................. 1.6 30.4 -0.7 1,030 0.4 Financial activities..................... 12.7 148.6 -2.4 1,024 0.0 Professional and business services....... 21.8 316.8 0.3 825 9.1 Education and health services............ 9.7 198.9 4.4 879 5.5 Leisure and hospitality.................. 7.2 177.6 1.4 387 5.7 Other services........................... 7.2 50.1 2.2 570 5.2 Government................................. 0.7 219.9 2.8 908 1.2 Orange, CA................................... 95.3 1,503.8 -1.3 924 2.6 Private industry........................... 93.9 1,359.9 -1.7 922 2.8 Natural resources and mining............. 0.2 5.2 5.9 623 0.2 Construction............................. 7.1 105.0 -5.5 1,025 4.1 Manufacturing............................ 5.4 175.8 (6) 1,101 (6) Trade, transportation, and utilities..... 17.8 281.0 1.2 868 3.8 Information.............................. 1.4 30.0 -1.8 1,262 3.8 Financial activities..................... 11.4 123.7 -9.8 1,377 -0.1 Professional and business services....... 19.3 273.7 -3.1 1,003 (6) Education and health services............ 9.9 142.7 3.2 870 3.1 Leisure and hospitality.................. 7.1 175.1 2.3 410 5.9 Other services........................... 14.4 47.7 -1.2 569 4.2 Government................................. 1.4 143.8 3.4 941 0.2 Dallas, TX................................... 67.7 1,487.3 2.2 1,002 4.2 Private industry........................... 67.2 1,323.2 2.2 1,012 4.2 Natural resources and mining............. 0.6 7.3 (6) 2,962 (6) Construction............................. 4.4 84.6 4.3 901 3.1 Manufacturing............................ 3.1 142.2 -1.9 1,174 7.5 Trade, transportation, and utilities..... 15.0 306.9 2.0 960 6.0 Information.............................. 1.7 48.1 (6) 1,385 (6) Financial activities..................... 8.8 144.5 1.6 1,366 6.4 Professional and business services....... 14.6 274.8 4.3 1,109 4.6 Education and health services............ 6.6 146.2 5.0 895 2.4 Leisure and hospitality.................. 5.2 127.6 1.7 434 -1.8 Other services........................... 6.5 39.3 3.0 609 3.7 Government................................. 0.5 164.1 2.7 919 2.9 San Diego, CA................................ 92.7 1,325.9 0.0 887 4.4 Private industry........................... 91.4 1,108.6 -0.2 869 4.3 Natural resources and mining............. 0.8 11.9 -1.4 556 6.7 Construction............................. 7.3 87.1 -8.2 947 6.0 Manufacturing............................ 3.2 102.3 (6) 1,175 5.8 Trade, transportation, and utilities..... 14.6 221.4 0.3 736 5.9 Information.............................. 1.3 38.0 2.1 1,707 9.8 Financial activities..................... 9.9 79.7 -4.6 1,106 5.3 Professional and business services....... 16.5 218.0 0.1 1,082 3.3 Education and health services............ 8.1 129.0 (6) 834 2.5 Leisure and hospitality.................. 6.9 164.8 2.5 408 2.5 Other services........................... 22.9 56.4 1.1 485 1.0 Government................................. 1.3 217.2 0.9 987 4.4 King, WA..................................... 76.3 1,182.8 2.3 1,129 8.0 Private industry........................... 75.7 1,032.4 2.8 1,145 8.6 Natural resources and mining............. 0.4 3.2 8.6 1,153 -6.9 Construction............................. 6.8 74.7 9.4 1,032 8.3 Manufacturing............................ 2.5 112.8 2.0 1,252 4.7 Trade, transportation, and utilities..... 14.7 219.9 1.9 891 2.8 Information.............................. 1.8 76.3 4.1 3,114 10.5 Financial activities..................... 7.0 75.5 -1.6 1,287 3.3 Professional and business services....... 13.0 190.4 3.9 1,326 19.6 Education and health services............ 6.3 120.3 2.1 840 5.3 Leisure and hospitality.................. 6.1 113.7 2.9 443 4.7 Other services........................... 17.2 45.5 1.1 572 7.5 Government................................. 0.5 150.5 -1.0 1,019 3.6 Miami-Dade, FL............................... 86.4 1,012.4 0.4 826 4.3 Private industry........................... 86.0 860.4 0.2 796 4.9 Natural resources and mining............. 0.5 8.2 -3.7 489 -0.8 Construction............................. 6.4 53.2 -1.3 825 3.9 Manufacturing............................ 2.6 46.4 -4.7 741 5.6 Trade, transportation, and utilities..... 23.4 251.7 0.5 752 6.7 Information.............................. 1.5 20.4 -0.7 1,205 6.6 Financial activities..................... 10.5 71.7 -0.1 1,155 6.0 Professional and business services....... 17.6 133.0 -3.4 974 3.4 Education and health services............ 9.0 138.0 3.8 811 6.6 Leisure and hospitality.................. 5.8 100.8 2.2 448 -0.4 Other services........................... 7.6 35.4 1.8 514 5.3 Government................................. 0.3 152.0 1.2 1,005 1.7 (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, third quarter 2007(2) Employment Average weekly wage(4) Establishments, third quarter County(3) 2007 Percent Percent (thousands) September change, Average change, 2007 September weekly third (thousands) 2006-07(5) wage quarter 2006-07(5) United States(6)......... 9,012.8 136,246.9 0.9 $818 4.3 Jefferson, AL............ 18.9 363.6 (7) 837 (7) Anchorage Borough, AK.... 8.1 149.2 0.2 894 5.5 Maricopa, AZ............. 99.3 1,825.1 0.2 822 3.8 Pulaski, AR.............. 14.7 250.9 0.6 751 4.3 Los Angeles, CA.......... 401.9 4,191.6 0.4 925 3.4 Denver, CO............... 26.0 448.4 2.7 995 0.9 Hartford, CT............. 25.4 504.9 0.8 1,002 6.3 New Castle, DE........... 18.8 282.3 -0.4 955 0.0 Washington, DC........... 32.1 679.0 0.6 1,376 5.3 Miami-Dade, FL........... 86.4 1,012.4 0.4 826 4.3 Fulton, GA............... 40.0 762.2 1.2 1,058 2.9 Honolulu, HI............. 24.6 451.0 -0.4 786 5.8 Ada, ID.................. 15.2 213.9 1.1 749 2.9 Cook, IL................. 138.0 2,541.5 0.0 961 3.3 Marion, IN............... 24.1 584.8 1.2 830 2.1 Polk, IA................. 14.7 274.6 2.0 804 2.9 Johnson, KS.............. 20.2 319.2 2.4 830 2.0 Jefferson, KY............ 22.2 437.5 1.2 791 2.1 East Baton Rouge, LA..... 13.9 264.4 1.9 742 5.4 Cumberland, ME........... 12.3 174.7 0.9 738 3.8 Montgomery, MD........... 32.7 460.9 -0.3 1,090 5.1 Middlesex, MA............ 47.5 818.3 1.4 1,176 5.9 Wayne, MI................ 32.2 747.7 -2.4 930 3.1 Hennepin, MN............. 44.3 849.5 0.8 1,043 5.4 Hinds, MS................ 6.4 127.8 -0.3 717 3.0 St. Louis, MO............ 33.3 611.9 0.5 873 6.3 Yellowstone, MT.......... 5.7 77.6 3.3 672 5.5 Douglas, NE.............. 15.7 318.8 1.0 782 6.5 Clark, NV................ 48.8 920.2 -0.3 796 5.9 Hillsborough, NH......... 12.5 197.9 0.4 899 4.4 Bergen, NJ............... 34.9 454.2 0.3 1,009 3.9 Bernalillo, NM........... 17.6 335.2 0.5 732 3.1 New York, NY............. 118.0 2,350.3 2.0 1,544 8.7 Mecklenburg, NC.......... 32.2 572.6 4.0 923 0.8 Cass, ND................. 5.8 98.5 2.4 688 6.2 Cuyahoga, OH............. 37.6 747.6 -0.8 832 3.6 Oklahoma, OK............. 23.5 424.8 1.0 748 5.6 Multnomah, OR............ 27.4 451.1 2.5 840 4.5 Allegheny, PA............ 35.4 686.2 0.6 864 4.9 Providence, RI........... 18.2 288.3 -1.5 779 -2.4 Greenville, SC........... 12.4 238.2 1.9 707 3.5 Minnehaha, SD............ 6.3 115.5 2.7 695 4.4 Shelby, TN............... 20.1 511.0 0.2 850 4.4 Harris, TX............... 95.1 2,028.0 3.8 1,015 6.7 Salt Lake, UT............ 38.6 591.0 3.4 771 5.8 Chittenden, VT........... 5.9 95.8 -0.4 812 4.2 Fairfax, VA.............. 32.9 584.9 0.7 1,243 5.3 King, WA................. 76.3 1,182.8 2.3 1,129 8.0 Kanawha, WV.............. 6.1 108.8 0.3 704 4.1 Milwaukee, WI............ 21.2 497.8 0.0 802 2.8 Laramie, WY.............. 3.2 43.9 3.4 691 -9.1 San Juan, PR............. 13.6 289.0 -2.7 538 3.5 St. Thomas, VI........... 1.8 23.2 1.3 636 -0.3 (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, third quarter 2007(2) Employment Average weekly wage(3) Establishments, third quarter State 2007 Percent Percent (thousands) September change, Average change, 2007 September weekly third (thousands) 2006-07 wage quarter 2006-07 United States(4)......... 9,012.8 136,246.9 0.9 $818 4.3 Alabama.................. 119.9 1,959.0 1.1 707 3.7 Alaska................... 21.2 327.3 0.7 840 5.4 Arizona.................. 160.6 2,644.9 0.5 783 4.1 Arkansas................. 83.4 1,184.5 0.3 629 4.1 California............... 1,314.1 15,755.0 0.7 932 4.5 Colorado................. 180.9 2,314.3 2.4 844 3.2 Connecticut.............. 112.9 1,696.9 1.0 1,021 6.6 Delaware................. 29.1 425.2 0.1 860 1.2 District of Columbia..... 32.1 679.0 0.6 1,376 5.3 Florida.................. 606.8 7,879.9 -0.9 741 4.1 Georgia.................. 272.4 4,089.4 1.2 782 4.1 Hawaii................... 38.7 624.4 0.3 760 5.4 Idaho.................... 57.0 675.5 2.2 634 3.4 Illinois................. 361.6 5,917.6 0.6 866 4.0 Indiana.................. 159.2 2,937.4 0.5 702 2.2 Iowa..................... 93.9 1,494.5 0.9 668 4.2 Kansas................... 85.8 1,368.7 1.7 680 2.7 Kentucky................. 110.5 1,814.3 1.0 676 3.0 Louisiana................ 120.9 1,880.8 2.7 716 4.5 Maine.................... 50.4 615.3 0.7 660 3.9 Maryland................. 164.0 2,563.7 0.7 892 4.1 Massachusetts............ 211.6 3,261.0 1.0 1,002 5.5 Michigan................. 257.6 4,218.2 -1.4 808 2.4 Minnesota................ 177.6 2,713.3 0.9 822 4.6 Mississippi.............. 70.2 1,142.2 0.6 607 3.8 Missouri................. 175.7 2,746.7 0.8 719 4.2 Montana.................. 42.8 446.1 2.7 608 4.6 Nebraska................. 59.0 922.7 1.7 666 5.4 Nevada................... 75.2 1,286.4 -0.1 792 5.5 New Hampshire............ 49.5 637.2 0.3 799 3.2 New Jersey............... 275.1 3,985.2 0.1 965 3.7 New Mexico............... 53.9 830.4 0.8 682 4.1 New York................. 580.3 8,585.3 1.3 1,009 6.1 North Carolina........... 254.3 4,104.1 2.4 719 3.5 North Dakota............. 25.2 347.4 1.5 621 5.8 Ohio..................... 290.8 5,331.9 -0.2 745 2.8 Oklahoma................. 99.6 1,548.2 1.8 666 5.5 Oregon................... 131.2 1,751.7 1.2 750 4.2 Pennsylvania............. 339.7 5,673.4 0.5 802 4.4 Rhode Island............. 36.2 486.1 -1.0 759 -0.1 South Carolina........... 116.6 1,904.7 1.7 664 3.6 South Dakota............. 30.3 397.5 2.0 598 4.7 Tennessee................ 141.3 2,774.4 0.5 728 4.3 Texas.................... 551.3 10,304.9 2.9 825 5.0 Utah..................... 87.1 1,231.6 3.6 696 5.5 Vermont.................. 25.0 305.2 -0.2 699 4.0 Virginia................. 229.3 3,686.6 1.0 857 5.0 Washington............... 218.7 2,976.5 2.1 878 6.7 West Virginia............ 48.9 713.8 0.3 623 4.0 Wisconsin................ 159.0 2,802.3 -0.1 705 2.6 Wyoming.................. 24.6 284.3 3.6 734 4.1 Puerto Rico.............. 57.1 1,008.0 -1.1 453 2.5 Virgin Islands........... 3.5 45.0 0.7 682 -0.3 (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.