Technical information: (202) 691-6567 USDL 07-0021 http://www.bls.gov/cew/ For release: 10:00 A.M. EST Media contact: 691-5902 Thursday, January 11, 2007 COUNTY EMPLOYMENT AND WAGES: SECOND QUARTER 2006 In June 2006, Collin County, Texas, had the largest over-the-year percent- age increase in employment among the largest counties in the U.S., according to preliminary data released today by the Bureau of Labor Statistics of the U.S. Department of Labor. Collin County, a Dallas suburb, experienced an over- the-year employment gain of 8.2 percent, compared with national job growth of 2.0 percent. Orleans County (New Orleans), La., had the largest over-the-year gain in average weekly wages in the second quarter of 2006, with an increase of 28.0 percent. The high average weekly wage growth rate for Orleans County re- flected the disproportionate job losses in lower-paid industries due to Hurri- cane Katrina. The U.S. average weekly wage increased by 4.4 percent over the same time span. Of the 325 largest counties in the United States, as measured by 2005 annual average employment, 142 had over-the-year percentage growth in employment above the national average (2.0 percent) in June 2006, and 167 experienced changes below the national average. The percent change in average weekly wages was higher than the national average (4.4 percent) in 141 of the largest U.S. counties, but was below the national average in 175 counties. The employment and average weekly wage data by county are compiled under the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from reports submitted by every employer subject to unemployment insurance (UI) laws. The 8.8 million employer reports cover 135.5 million full- and part-time workers. The attached tables contain data for the nation and for the 325 U.S. coun- ties with annual average employment levels of 75,000 or more in 2005. June 2006 employment and 2006 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 2005 are available on the BLS Web site at http://www.bls.gov/cew/. Preliminary data for first and second quarters of 2006 will be available later in January on the BLS Web site. Large County Employment In June 2006, national employment, as measured by the QCEW program, was 135.5 million, an increase of 2.0 percent from June 2005. The 325 U.S. counties with 75,000 or more employees accounted for 70.7 percent of total U.S. covered employment and 76.5 percent of total covered wages. These 325 counties had a net job gain of 1,758,531 over the year, accounting for 65.6 percent of the overall U.S. employment increase. Employment increased in 270 of the large counties from June 2005 to June 2006. Collin, Texas, had the lar- gest over-the-year percentage increase in employment (8.2 percent). Lafayette, La., had the next largest increase, 7.0 percent, followed by the counties of Utah, Utah (6.7 percent) and Lee, Fla., and Montgomery, Texas (6.5 percent each). (See table 1.) -------------------------------------------------------------------------- | Hurricane Katrina | | | | The employment and wages reported in this news release reflect the | | impact of Hurricane Katrina and ongoing labor market trends in certain | | counties. The effects of Hurricane Katrina, which hit the Gulf Coast | | on August 29, 2005, were first apparent in the September QCEW employ- | | ment counts and the wage totals for the third quarter of 2005. This | | catastrophic storm continues to affect monthly employment and quarterly | | wage totals in parts of Louisiana and Mississippi in the second quarter | | of 2006. For more information, see the QCEW section of the Katrina | | coverage on the BLS Web site at http://www.bls.gov/katrina/qcewques- | | tions.htm. | -------------------------------------------------------------------------- - 2 - Table A. Top 10 large counties ranked by June 2006 employment, June 2005-06 employment growth, and June 2005-06 percent growth in employment ------------------------------------------------------------------------------------- Employment in large counties ------------------------------------------------------------------------------------- June 2006 employment | Growth in employment, | Percent growth (thousands) | June 2005-06 | in employment, | (thousands) | June 2005-06 ------------------------------------------------------------------------------------- | | United States 135,481.1| United States 2,678.8| United States 2.0 -----------------------------|----------------------------|-------------------------- | | Los Angeles, Calif. 4,196.7| Maricopa, Ariz. 95.8| Collin, Texas 8.2 Cook, Ill. 2,565.5| Los Angeles, Calif. 80.7| Lafayette, La. 7.0 New York, N.Y. 2,312.6| Harris, Texas 77.1| Utah, Utah 6.7 Harris, Texas 1,941.2| Clark, Nev. 51.0| Lee, Fla. 6.5 Maricopa, Ariz. 1,784.4| New York, N.Y. 49.7| Montgomery, Texas 6.5 Orange, Calif. 1,530.4| Dallas, Texas 46.9| Davis, Utah 6.2 Dallas, Texas 1,462.9| King, Wash. 41.3| Douglas, Colo. 6.0 San Diego, Calif. 1,327.9| Cook, Ill. 35.8| Clark, Nev. 5.9 King, Wash. 1,160.2| Riverside, Calif. 30.4| Lake, Fla. 5.8 Miami-Dade, Fla. 993.7| Santa Clara, Calif. 28.5| Ada, Idaho 5.8 ------------------------------------------------------------------------------------- Employment declined in 40 counties from June 2005 to June 2006. The largest percentage decline in employment was in Orleans County, La. (-37.2 percent), followed by the counties of Harrison, Miss. (-14.7 percent) and Jefferson, La. (-10.2 percent). Employment losses in these three Gulf Coast counties reflected the devastation caused by Hurricane Katrina. Boone, Ky., had the next largest employment decline (-3.2 percent), followed by Oakland, Mich. (-2.8 percent). The largest gains in the level of employment from June 2005 to June 2006 were recorded in the counties of Maricopa, Ariz. (95,800), Los Angeles, Calif. (80,700), Harris, Texas (77,100), Clark, Nev. (51,000), and New York, N.Y. (49,700). (See table A.) The largest declines in employment levels occurred in the Katrina-affected counties of Orleans, La. (-90,900) and Jefferson, La. (-22,200), followed by the counties of Oakland, Mich. (-20,100), Wayne, Mich. (-13,700), and Harrison, Miss. (-13,400). Large County Average Weekly Wages The national average weekly wage in the second quarter of 2006 was $784. Average weekly wages were higher than the national average in 110 of the largest 325 U.S. counties. New York County, N.Y., held the top position among the highest-paid large counties with an average weekly wage of $1,453. Santa Clara, Calif., was second with an average weekly wage of $1,386, followed by Arlington, Va. ($1,335), Washington, D.C. ($1,300), and Somerset, N.J. ($1,242). (See table B.) - 3 - Table B. Top 10 large counties ranked by second quarter 2006 average weekly wages, second quarter 2005-06 growth in average weekly wages, and second quarter 2005-06 percent growth in average weekly wages ---------------------------------------------------------------------------------------- Average weekly wage in large counties ---------------------------------------------------------------------------------------- Average weekly wage, | Growth in average weekly | Percent growth in second quarter 2006 | wage, second quarter | average weekly wage, | 2005-06 | second quarter 2005-06 ---------------------------------------------------------------------------------------- | | United States $784| United States $33| United States 4.4 ---------------------------------------------------------------------------------------- | | New York, N.Y. $1,453| Orleans, La. $194| Orleans, La. 28.0 Santa Clara, Calif. 1,386| Somerset, N.J. 113| Jefferson, La. 16.3 Arlington, Va. 1,335| New York, N.Y. 105| Harrison, Miss. 15.2 Washington, D.C. 1,300| Jefferson, La. 102| Rock Island, Ill. 10.5 Somerset, N.J. 1,242| Marin, Calif. 85| Somerset, N.J. 10.0 San Francisco, Calif. 1,231| Harrison, Miss. 85| Lafayette, La. 9.9 Suffolk, Mass. 1,228| Alexandria City, Va. 82| Oklahoma, Okla. 9.6 Fairfield, Conn. 1,221| Middlesex, N.J. 81| Calcasieu, La. 9.0 Fairfax, Va. 1,209| New Castle, Del. 77| Middlesex, N.J. 8.8 San Mateo, Calif. 1,203| Hudson, N.J. 76| Marin, Calif. 8.6 | | New Castle, Del. 8.6 ---------------------------------------------------------------------------------------- There were 214 counties with an average weekly wage below the national average in the second quarter of 2006. The lowest average weekly wages were reported in Cameron County, Texas ($484), followed by the counties of Hidalgo, Texas ($494), Horry, S.C. ($527), and Webb, Texas, and Yakima, Wash. ($530 each). (See table 1.) Over the year, the national average weekly wage rose by 4.4 percent. Among the largest counties, Orleans, La., led the nation in growth in average weekly wages, with an increase of 28.0 percent from the second quarter of 2005. Jefferson, La., was second with growth of 16.3 percent, followed by the counties of Harrison, Miss. (15.2 percent), Rock Island, Ill. (10.5 percent), and Somerset, N.J. (10.0 percent). The high average weekly wage growth rates for Orleans, Harrison, and Jefferson Counties were related to the disproportionate job losses in lower-paid industries due to the impact of Hurricane Katrina. That is, the loss of low paid jobs due to the storm boosted average wages in those areas. Ten counties experienced over-the-year declines in average weekly wages. San Mateo, Calif., and McLean, Ill., had the largest declines, -5.0 percent each, followed by the counties of Clayton, Ga. (-3.8 percent), Webb, Texas (-2.0 percent), and Rockingham, N.H. (-1.2 percent). Ten Largest U.S. Counties Each of the 10 largest counties (based on 2005 annual average employment levels), reported increases in employment from June 2005 to June 2006. Mari- copa County, Ariz., experienced the fastest growth in employment among the largest counties, with a 5.7 percent increase. Within Maricopa County, em- ployment rose in every industry group except two--natural resources and mining, and information. The largest gains were in construction (11.6 percent), followed by education and health services, and leisure and hospitality (6.0 percent each). Harris, Texas, had the next largest increase in employment, 4.1 percent, followed by King, Wash. (3.7 percent). The smallest employment gains occurred in San Diego, Calif., and Cook County, Ill. (1.4 percent each), followed by Orange, Calif., and Miami-Dade, Fla. (1.8 percent each). (See table 2.) All of the 10 largest U.S. counties saw over-the-year increases in average weekly wages. New York County, N.Y., had the fastest growth in wages among the 10 largest counties, with a gain of 7.8 percent. Within New York County, N.Y., average weekly wages increased the most in natural resources and mining (11.2 percent), a very small sector. Increases in financial activities (10.8 percent), however, had a larger impact on the county’s wage growth. Harris, Texas, was second in wage growth, with a gain of 7.5 percent, followed by Orange, Calif. (6.3 percent). The smallest wage gains among the 10 largest counties occurred in Miami-Dade, Fla. (3.0 percent), Los Angeles, Calif. (3.6 percent), and Cook, Ill. (4.3 percent). - 4 - Largest County by State Table 3 shows June 2006 employment and the 2006 second quarter average weekly wage in the largest county in each state, which is based on 2005 annual average employment levels. (This table includes two counties-- Yellowstone, Mont., and Laramie, Wyo.--that had employment levels below 75,000.) The employment levels in these counties in June 2006 ranged from approximately 4.2 million in Los Angeles County, Calif., to 42,500 in Laramie County, Wyo. The highest average weekly wage of these counties was in New York, N.Y. ($1,453), while the lowest average weekly wage was in Yellowstone, Mont. ($623). For More Information For additional information about the quarterly employment and wages data, please read the Technical Note or visit the QCEW Web site at http:// www.bls.gov/cew/. Additional information about the QCEW data also may be obtained by e-mailing QCEWinfo@bls.gov or by calling (202) 691-6567. Several BLS regional offices are issuing QCEW news releases designed for 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 2006 is scheduled to be released on Wednesday, April 11. - 5 - Technical Note These data are the product of a federal-state cooperative program, the Quarterly Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The data are derived from summaries of employment and to- tal pay of workers covered by state and federal unemployment insurance (UI) legislation and provided by State Workforce Agencies (SWAs). The summaries are a result of the administration of state unemployment insurance programs that require most employers to pay quarterly taxes based on the employment and wages of workers covered by UI. Data for 2006 are preliminary and sub- ject to revision. For purposes of this release, large counties are defined as having em- ployment levels of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are provided, but not used in calculating U.S. averages, rankings, or in the analysis in the text. Each year, these large counties are selected on the basis of the preliminary annual average of employment for the previous year. The 326 counties presented in this release were derived using 2005 preliminary annual averages of employment. For 2006 data, four counties have been added to the publication tables: Douglas, Colo., Weld, Colo., Boone, Ky., and Butler, Pa. These counties will be included in all 2006 quarterly releases. One county, Potter, Texas, which was published in the 2005 releases, no longer has an employment level of 75,000 or more and will be excluded in the 2006 releases. The counties in table 2 are selected and sorted each year based on the annual average employment from the preceding year. The preliminary QCEW data presented in this release may differ from data released by the individual states. These potential differences result from the states' continuing receipt of UI data over time and ongoing review and editing. The individual states determine their data release timetables. Differences between QCEW, BED, and CES employment measures The Bureau publishes three different establishment-based employment measures for any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED), and Current Employment Statistics (CES)--makes use of the quarterly UI employment reports in producing data; however, each measure has a somewhat different universe coverage, estimation pro- cedure, and publication product. Differences in coverage and estimation methods can result in somewhat different measures of employment change over time. It is important to understand program differences and the intended uses of the program pro- ducts. (See table below.) Additional information on each program can be obtained from the program Web sites shown in the table below. - 6 - Summary of Major Differences between QCEW, BED, and CES Employment Measures -------------------------------------------------------------------------------- | QCEW | BED | CES -----------|---------------------|----------------------|----------------------- Source |--Count of UI admini-|--Count of longitudi- |--Sample survey: | strative records | nally-linked UI ad- | 400,000 establish- | submitted by 8.8 | ministrative records| ments | million establish- | submitted by 6.8 | | ments | million private-sec-| | | tor employers | -----------|---------------------|----------------------|----------------------- Coverage |--UI and UCFE cover- |--UI coverage, exclud-|Nonfarm wage and sal- | age, including all | ing government, pri-| ary jobs: | employers subject | vate households, and|--UI coverage, exclud- | to state and feder-| establishments with | ing agriculture, pri- | al UI laws | zero employment | vate households, and | | | self-employed workers | | |--Other employment, in- | | | cluding railroads, | | | religious organiza- | | | tions, and other non- | | | UI-covered jobs -----------|---------------------|----------------------|----------------------- Publication|--Quarterly |--Quarterly |--Monthly frequency | -7 months after the| -8 months after the | -Usually first Friday | end of each quar- | end of each quarter| of following month | ter | | -----------|---------------------|----------------------|----------------------- Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam- file | and publishes each | quarter to longitu- | pling frame and annu- | new quarter of UI | dinal database and | ally realigns (bench- | data | directly summarizes | marks) sample esti- | | gross job gains and | mates to first quar- | | losses | ter UI levels -----------|---------------------|----------------------|------------------------ Principal |--Provides a quarter-|--Provides quarterly |--Provides current month- products | ly and annual uni- | employer dynamics | ly estimates of employ- | verse count of es- | data on establish- | ment, hours, and earn- | tablishments, em- | ment openings, clos-| ings at the MSA, state, | ployment, and wages| ings, expansions, | and national level by | at the county, MSA,| and contractions at | industry | state, and national| the national level | | levels by detailed | by NAICS supersec- | | industry | tors and by size of | | | firm | | |--Future expansions | | | will include data at| | | the county, MSA, and| | | state level | -----------|---------------------|----------------------|-------------------------- Principal |--Major uses include:|--Major uses include: |--Major uses include: uses | -Detailed locality | -Business cycle | -Principal national | data | analysis | economic indicator | -Periodic universe | -Analysis of employ-| -Official time series | counts for bench- | er dynamics under- | for employment change | marking sample | lying economic ex- | measures | survey estimates | pansions and con- | -Input into other ma- | -Sample frame for | tractions | jor economic indi- | BLS establishment | -An analysis of em- | cators | surveys | ployment expansion | | | and contraction by | | | size of firm | -----------|---------------------|----------------------|-------------------------- Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/ Web sites | | | ----------------------------------------------------------------------------------- - 7 - Coverage Employment and wage data for workers covered by state UI laws are compiled from quarterly contribution reports submitted to the SWAs by employers. For federal civilian workers covered by the Unemployment Compensation for Federal Employees (UCFE) program, employment and wage data are compiled from quarterly reports that are sent to the appropriate SWA by the specific federal agency. In addition to the quarterly contribution reports, employers who operate multiple establishments within a state com- plete a questionnaire, called the "Multiple Worksite Report," which provides detailed information on the location and industry of each of their establish- ments. The employment and wage data included in this release are derived from microdata summaries of nearly 9 million employer reports of employment and wages submitted by states to the BLS. These reports are based on place of employment rather than place of residence. UI and UCFE coverage is broad and basically comparable from state to state. In 2005, UI and UCFE programs covered workers in 131.6 million jobs. The estimated 126.7 million workers in these jobs (after adjust- ment for multiple jobholders) represented 96.6 percent of civilian wage and salary employment. Covered workers received $5.352 trillion in pay, representing 94.5 percent of the wage and salary component of personal income and 43.0 percent of the gross domestic product. Major exclusions from UI coverage include self-employed workers, most agricultural workers on small farms, all members of the Armed Forces, elected officials in most states, most employees of railroads, some domes- tic workers, most student workers at schools, and employees of certain small nonprofit organizations. State and federal UI laws change periodically. These changes may have an impact on the employment and wages reported by employers covered under the UI program. Coverage changes may affect the over-the-year comparisons presented in this news release. Concepts and methodology Monthly employment is based on the number of workers who worked during or received pay for the pay period including the 12th of the month. With few exceptions, all employees of covered firms are reported, including pro- duction and sales workers, corporation officials, executives, supervisory personnel, and clerical workers. Workers on paid vacations and part-time workers also are included. Average weekly wage values are calculated by dividing quarterly total wages by the average of the three monthly employment levels (all employees, as described above) and dividing the result by 13, for the 13 weeks in the quarter. These calculations are made using unrounded employment and wage values. The average wage values that can be calculated using rounded data from the BLS database may differ from the averages reported. Included in the quarterly wage data are non-wage cash payments such as bonuses, the cash value of meals and lodging when supplied, tips and other gratuities, and, in some states, employer contributions to certain deferred compensation plans such as 401(k) plans and stock options. Over-the-year comparisons of average weekly wages may reflect fluctuations in average monthly employment and/or total quarterly wages between the current quarter and prior year levels. Average weekly wages are affected by the ratio of full-time to part-time workers as well as the number of individuals in high-paying and low-paying occupations and the incidence of pay periods within a quarter. For instance, the average weekly wage of the work force could increase significantly when there is a large decline in the number of employees that had been receiving below-average wages. Wages may include payments to workers not present in the employment counts because they did not work during the pay period in- cluding the 12th of the month. When comparing average weekly wage levels between industries, states, or quarters, these factors should be taken into consideration. - 8 - Federal government pay levels are subject to periodic, sometimes large, fluctuations due to a calendar effect that consists of some quarters having more pay periods than others. Most federal employees are paid on a bi- weekly pay schedule. As a result of this schedule, in some quarters, fed- eral wages contain payments for six pay periods, while in other quarters their wages include payments for seven pay periods. Over-the-year com- parisons of average weekly wages may reflect this calendar effect. Higher growth in average weekly wages may be attributed, in part, to a comparison of quarterly wages for the current year, which include seven pay periods, with year-ago wages that reflect only six pay periods. An opposite effect will occur when wages in the current period, which contain six pay periods, are compared with year-ago wages that include seven pay periods. The ef- fect on over-the-year pay comparisons can be pronounced in federal govern- ment due to the uniform nature of federal payroll processing. This pattern may exist in private sector pay, however, because there are more pay period types (weekly, biweekly, semimonthly, monthly) it is less pronounced. The effect is most visible in counties with large concentrations of federal employment. In order to ensure the highest possible quality of data, states verify with employers and update, if necessary, the industry, location, and own- ership classification of all establishments on a 3-year cycle. Changes in establishment classification codes resulting from this process are in- troduced with the data reported for the first quarter of the year. Changes resulting from improved employer reporting also are introduced in the first quarter. QCEW data are not designed as a time series. QCEW data are simply the sums of individual establishment records and reflect the number of estab- lishments that exist in a county or industry at a point in time. Estab- lishments can move in or out of a county or industry for a number of rea- sons--some reflecting economic events, others reflecting administrative changes. For example, economic change would come from a firm relocating into the county; administrative change would come from a company correcting its county designation. The over-the-year changes of employment and wages presented in this release have been adjusted to account for most of the administrative corrections made to the underlying establishment reports. This is done by modifying the prior-year levels used to calculate the over-the-year changes. Percent changes are calcuated using an adjusted version of the final 2005 quarterly data as the base data. The adjusted prior-year levels used to calculate the over-the-year percent change in employment and wages are not published. These adjusted prior-year levels do not match the unadjusted data maintained on the BLS Web site. Over-the-year change calculations based on data from the Web site, or from data published in prior BLS news releases, may differ substantially from the over-the-year changes presented in this news release. The adjusted data used to calculate the over-the-year change measures presented in this release account for most of the administrative changes-- those occurring when employers update the industry, location, and owner- ship information of their establishments. The most common adjustments for administrative change are the result of updated information about the county location of individual establishments. Included in these adjust- ments are administrative changes involving the classification of establish- ments that were previously reported in the unknown or statewide county or unknown industry categories. The adjusted data do not account for adminis- trative changes caused by multi-unit employers who start reporting for each individual establishment rather than as a single entity. - 9 - The adjusted data used to calculate the over-the-year change measures presented in any County Employment and Wages news release are valid for comparisons between the starting and ending points (a 12-month period) used in that particular release. Comparisons may not be valid for any time period other than the one featured in a release even if the changes were calculated using adjusted data. County definitions are assigned according to Federal Information Processing Standards Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104- 106. Areas shown as counties include those designated as independent cities in some jurisdictions and, in Alaska, those designated as census areas where counties have not been created. County data also are presented for the New England states for comparative purposes even though townships are the more common designation used in New England (and New Jersey). The regions re- ferred to in this release are defined as census regions. Additional statistics and other information An annual bulletin, Employment and Wages, features comprehensive infor- mation by detailed industry on establishments, employment, and wages for the nation and all states. The 2005 edition of this bulletin contains selected data produced by Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the fourth quarter 2005 version of this news release. This edition will also be the first to include the data on a CD for enhanced access and usability. As a result of this change, the printed booklet will contain only selected graphic representations of QCEW data; the data tables themselves will be published exclusively in electronic formats as PDF and fixed-width text files. Employment and Wages Annual Averages, 2005 will be available for sale in late 2006 from the United States Government Printing Office, Superintendent of Documents, P.O. Box 371954, Pittsburgh, PA 15250, telephone 866-512-1800, outside of Washington, D.C. Within Washington, D.C., the telephone number is 202-512-1800. The fax number is 202-512-2104. Also, the 2005 bulletin will be available in a por- table document format (PDF) on the BLS Web site at http://www.bls.gov/cew/ cewbultn05.htm. News releases on quarterly measures of gross job flows also are available upon request from the Division of Administrative Statistics and Labor Turn- over (Business Employment Dynamics), telephone 202-691-6467; http://www.bls. gov/bdm/; e-mail: BDMInfo@bls.gov. Information in this release will be made available to sensory impaired individuals upon request. Voice phone: 202-691-5200; TDD message referral phone number: 1-800-877-8339. Table 1. Covered (1) establishments, employment, and wages in the 326 largest counties, second quarter 2006 (2) Employment Average weekly wage (5) Establishments, County (3) second quarter Percent Ranking Percent Ranking 2006 June change, by Average change, by (thousands) 2006 June percent weekly second percent (thousands) 2005-06 (4) change wage quarter change 2005-06 (4) United States (6)......... 8,774.8 135,481.1 2.0 - $784 4.4 - Jefferson, AL............ 18.6 375.9 1.4 184 782 2.4 262 Madison, AL.............. 8.3 173.2 2.7 96 828 4.2 157 Mobile, AL............... 9.8 171.8 2.6 104 668 7.7 23 Montgomery, AL........... 6.6 139.2 2.6 104 695 7.9 19 Tuscaloosa, AL........... 4.3 84.2 3.5 57 679 4.5 133 Anchorage Borough, AK.... 8.0 150.7 4.4 35 839 3.3 217 Maricopa, AZ............. 91.2 1,784.4 5.7 11 794 4.5 133 Pima, AZ................. 19.6 360.7 4.3 37 700 2.5 261 Benton, AR............... 5.2 94.7 5.0 20 721 3.1 231 Pulaski, AR.............. 14.1 249.9 2.0 143 707 2.8 248 Washington, AR........... 5.6 94.9 4.5 32 645 4.2 157 Alameda, CA.............. 48.8 691.8 1.4 184 1,044 5.7 60 Contra Costa, CA......... 27.9 352.8 1.9 151 993 4.1 165 Fresno, CA............... 28.7 359.6 3.3 67 632 5.0 94 Kern, CA................. 17.0 281.8 4.2 39 679 5.9 53 Los Angeles, CA.......... 387.2 4,196.7 2.0 143 882 3.6 198 Marin, CA................ 11.7 110.9 1.7 163 1,074 8.6 10 Monterey, CA............. 12.1 181.7 -1.3 309 703 4.1 165 Orange, CA............... 95.5 1,530.4 1.8 156 916 6.3 44 Placer, CA............... 10.4 139.2 2.4 113 772 3.6 198 Riverside, CA............ 42.5 644.7 5.0 20 691 5.5 69 Sacramento, CA........... 49.5 644.6 2.7 96 864 6.0 49 San Bernardino, CA....... 45.0 659.1 2.8 92 704 4.5 133 San Diego, CA............ 91.6 1,327.9 1.4 184 850 4.7 117 San Francisco, CA........ 43.9 541.2 3.5 57 1,231 5.7 60 San Joaquin, CA.......... 16.7 230.2 2.5 110 690 6.0 49 San Luis Obispo, CA...... 9.0 108.6 3.3 67 644 3.7 195 San Mateo, CA............ 23.1 337.4 2.1 138 1,203 -5.0 321 Santa Barbara, CA........ 13.5 191.9 0.6 234 752 4.2 157 Santa Clara, CA.......... 55.2 887.6 3.3 67 1,386 5.4 74 Santa Cruz, CA........... 8.6 103.8 1.7 163 738 3.9 182 Solano, CA............... 9.8 133.5 1.9 151 751 4.0 175 Sonoma, CA............... 17.6 197.5 2.3 124 781 5.0 94 Stanislaus, CA........... 13.7 177.4 -0.3 284 670 4.4 142 Tulare, CA............... 8.8 153.4 2.7 96 562 6.4 43 Ventura, CA.............. 21.7 324.1 2.4 113 840 3.2 224 Yolo, CA................. 5.3 101.1 1.0 204 731 2.7 253 Adams, CO................ 9.3 156.0 4.1 41 730 3.8 189 Arapahoe, CO............. 19.6 279.9 1.5 180 938 5.0 94 Boulder, CO.............. 12.5 158.6 2.2 130 951 5.8 56 Denver, CO............... 25.2 435.4 2.4 113 940 1.7 285 Douglas, CO.............. 8.8 90.3 6.0 7 777 2.6 257 El Paso, CO.............. 17.3 250.8 3.3 67 724 3.3 217 Jefferson, CO............ 18.7 210.8 0.6 234 784 1.8 279 Larimer, CO.............. 10.0 130.7 1.7 163 686 3.0 237 Weld, CO................. 5.9 81.7 4.5 32 649 2.0 276 Fairfield, CT............ 32.5 425.5 1.5 180 1,221 4.5 133 Hartford, CT............. 24.9 503.8 (7) - 969 (7) - New Haven, CT............ 22.3 375.0 (7) - 837 (7) - New London, CT........... 6.8 130.5 -0.3 284 801 -0.2 313 New Castle, DE........... 19.5 285.0 1.4 184 968 8.6 10 Washington, DC........... 31.2 677.9 0.4 246 1,300 5.3 81 Alachua, FL.............. 6.4 122.2 2.4 113 642 0.6 303 Brevard, FL.............. 14.5 209.6 2.1 138 765 4.7 117 Broward, FL.............. 63.1 753.4 2.9 85 763 3.2 224 Collier, FL.............. 12.3 128.5 5.5 13 757 6.2 45 Duval, FL................ 25.4 461.7 3.4 63 773 5.2 84 Escambia, FL............. 7.8 128.3 2.0 143 639 5.1 88 Hillsborough, FL......... 35.7 633.5 2.1 138 754 6.2 45 Lake, FL................. 6.8 80.9 5.8 9 615 7.9 19 Lee, FL.................. 18.5 220.3 6.5 4 704 4.6 126 Leon, FL................. 7.9 144.8 1.0 204 679 5.1 88 Manatee, FL.............. 8.8 126.3 5.5 13 650 5.2 84 Marion, FL............... 7.9 102.8 5.1 19 601 5.6 65 Miami-Dade, FL........... 84.1 993.7 1.8 156 786 3.0 237 Okaloosa, FL............. 6.0 84.3 (7) - 660 4.6 126 Orange, FL............... 34.3 671.8 3.8 49 747 6.6 41 Palm Beach, FL........... 48.8 557.7 3.2 76 793 6.0 49 Pasco, FL................ 9.3 94.7 5.3 15 607 4.8 107 Pinellas, FL............. 31.0 448.6 2.6 104 687 3.5 203 Polk, FL................. 12.3 204.1 3.0 82 633 4.1 165 Sarasota, FL............. 14.8 157.3 4.9 23 704 5.1 88 Seminole, FL............. 14.4 176.3 4.2 39 720 5.9 53 Volusia, FL.............. 13.8 164.3 3.3 67 593 3.3 217 Bibb, GA................. 4.8 85.5 -1.9 311 639 0.9 300 Chatham, GA.............. 7.4 136.1 3.0 82 670 5.8 56 Clayton, GA.............. 4.4 108.8 (7) - 718 -3.8 320 Cobb, GA................. 20.0 311.7 4.8 25 849 3.0 237 De Kalb, GA.............. 16.3 286.9 2.3 124 846 3.2 224 Fulton, GA............... 39.6 775.0 2.0 143 1,006 3.4 212 Gwinnett, GA............. 22.6 323.2 3.3 67 805 1.8 279 Muscogee, GA............. 4.9 99.6 1.8 156 606 0.3 307 Richmond, GA............. 4.9 105.3 -.3 284 658 3.9 182 Honolulu, HI............. 24.2 452.3 2.3 124 726 3.7 195 Ada, ID.................. 14.6 210.6 5.8 9 744 7.4 27 Champaign, IL............ 4.0 91.0 0.4 246 652 1.6 288 Cook, IL................. 134.0 2,565.5 1.4 184 942 4.3 148 Du Page, IL.............. 34.4 603.7 1.4 184 913 3.6 198 Kane, IL................. 12.0 212.6 1.8 156 727 4.5 133 Lake, IL................. 20.1 339.1 1.9 151 944 4.8 107 McHenry, IL.............. 8.1 104.4 3.1 78 696 4.0 175 McLean, IL............... 3.5 85.2 1.4 184 760 -5.0 321 Madison, IL.............. 5.8 95.8 .5 240 654 3.0 237 Peoria, IL............... 4.7 104.2 2.7 96 741 4.1 165 Rock Island, IL.......... 3.4 79.9 0.5 240 779 10.5 4 St. Clair, IL............ 5.3 94.8 0.3 253 642 5.1 88 Sangamon, IL............. 5.2 133.0 0.0 271 766 4.4 142 Will, IL................. 12.4 183.9 5.6 12 723 3.0 237 Winnebago, IL............ 6.8 137.9 0.2 260 666 1.2 294 Allen, IN................ 8.8 182.7 2.6 104 684 2.4 262 Elkhart, IN.............. 4.8 131.1 3.8 49 698 2.6 257 Hamilton, IN............. 7.0 102.0 4.0 44 758 2.6 257 Lake, IN................. 10.0 195.1 0.7 226 689 0.0 311 Marion, IN............... 23.5 582.7 0.8 217 819 4.7 117 St. Joseph, IN........... 6.0 124.5 -1.1 305 677 3.5 203 Vanderburgh, IN.......... 4.7 108.5 0.7 226 658 3.9 182 Linn, IA................. 6.2 122.4 2.8 92 736 3.1 231 Polk, IA................. 14.3 274.0 2.9 85 780 5.8 56 Scott, IA................ 5.1 91.0 1.1 200 630 0.6 303 Johnson, KS.............. 19.8 306.1 0.2 260 812 4.8 107 Sedgwick, KS............. 12.1 249.9 2.7 96 733 4.3 148 Shawnee, KS.............. 4.8 93.7 -0.9 302 696 5.1 88 Wyandotte, KS............ 3.2 79.4 3.8 49 787 5.4 74 Boone, KY................ 3.3 74.3 -3.2 314 743 1.6 288 Fayette, KY.............. 9.0 171.4 0.1 266 723 4.8 107 Jefferson, KY............ 22.1 434.9 1.8 156 778 4.1 165 Caddo, LA................ 7.3 126.9 2.9 85 663 3.9 182 Calcasieu, LA............ 4.9 85.4 -1.1 305 657 9.0 8 East Baton Rouge, LA..... 13.7 262.1 4.8 25 699 8.5 12 Jefferson, LA............ 14.5 194.6 -10.2 315 727 16.3 2 Lafayette, LA............ 8.2 130.4 7.0 2 724 9.9 6 Orleans, LA.............. 11.9 153.3 -37.2 317 887 28.0 1 Cumberland, ME........... 12.0 175.5 1.6 171 708 3.5 203 Anne Arundel, MD......... 14.2 228.4 3.1 78 829 4.7 117 Baltimore, MD............ 21.6 379.8 0.8 217 811 5.6 65 Frederick, MD............ 5.9 94.0 1.0 204 752 5.3 81 Harford, MD.............. 5.6 84.1 3.3 67 711 1.1 296 Howard, MD............... 8.4 145.9 2.6 104 904 4.1 165 Montgomery, MD........... 32.7 471.2 1.7 163 1,037 4.6 126 Prince Georges, MD....... 15.6 315.5 0.7 226 854 3.4 212 Baltimore City, MD....... 14.1 350.5 -0.4 289 914 4.9 101 Barnstable, MA........... 9.2 100.6 -0.7 297 683 4.3 148 Bristol, MA.............. 15.5 223.8 -0.4 289 730 6.1 47 Essex, MA................ 20.5 303.1 1.0 204 842 4.2 157 Hampden, MA.............. 14.1 202.1 0.0 271 722 4.8 107 Middlesex, MA............ 46.9 812.0 1.6 171 1,110 4.5 133 Norfolk, MA.............. 21.4 326.1 0.8 217 974 8.2 16 Plymouth, MA............. 13.7 182.1 0.4 246 777 4.9 101 Suffolk, MA.............. 21.5 575.4 1.6 171 1,228 4.9 101 Worcester, MA............ 20.3 325.4 1.0 204 815 4.9 101 Genesee, MI.............. 8.2 148.3 -0.7 297 733 4.0 175 Ingham, MI............... 7.0 163.3 2.4 113 766 4.2 157 Kalamazoo, MI............ 5.5 116.7 -0.7 297 712 4.1 165 Kent, MI................. 14.4 344.6 0.5 240 723 2.3 266 Macomb, MI............... 18.1 331.3 -1.9 311 824 -0.7 316 Oakland, MI.............. 40.0 709.8 -2.8 313 924 1.1 296 Ottawa, MI............... 5.8 114.0 -0.6 296 681 1.8 279 Saginaw, MI.............. 4.5 88.9 (7) - 714 5.9 53 Washtenaw, MI............ 8.1 192.4 -1.0 304 880 2.8 248 Wayne, MI................ 33.3 781.6 -1.7 310 904 0.9 300 Anoka, MN................ 8.3 117.5 2.0 143 808 4.1 165 Dakota, MN............... 10.9 178.2 3.3 67 790 4.2 157 Hennepin, MN............. 43.9 850.5 2.0 143 978 4.0 175 Olmsted, MN.............. 3.7 92.0 2.1 138 811 3.2 224 Ramsey, MN............... 16.1 335.6 2.2 130 878 3.3 217 St. Louis, MN............ 6.1 97.4 1.2 195 667 8.1 17 Stearns, MN.............. 4.6 80.1 1.8 156 618 2.3 266 Harrison, MS............. 4.3 78.0 -14.7 316 646 15.2 3 Hinds, MS................ 6.5 128.5 0.9 213 691 5.5 69 Boone, MO................ 4.5 82.5 2.0 143 623 1.6 288 Clay, MO................. 5.0 90.1 0.9 213 744 7.1 30 Greene, MO............... 8.1 153.8 2.7 96 608 2.7 253 Jackson, MO.............. 18.6 369.6 0.7 226 802 3.5 203 St. Charles, MO.......... 7.8 123.2 2.9 85 691 1.8 279 St. Louis, MO............ 33.7 631.6 1.0 204 859 5.3 81 St. Louis City, MO....... 8.0 223.1 -0.2 282 853 -0.4 314 Douglas, NE.............. 15.3 315.8 1.0 204 749 8.4 14 Lancaster, NE............ 7.9 155.9 0.8 217 636 4.6 126 Clark, NV................ 45.0 919.3 5.9 8 750 0.1 308 Washoe, NV............... 13.8 220.4 3.9 48 736 2.1 274 Hillsborough, NH......... 12.5 197.6 0.0 271 847 1.3 293 Rockingham, NH........... 11.0 142.0 1.9 151 769 -1.2 318 Atlantic, NJ............. 6.9 154.8 1.3 192 711 1.7 285 Bergen, NJ............... 34.5 454.3 0.4 246 983 3.6 198 Burlington, NJ........... 11.5 206.8 0.5 240 844 4.7 117 Camden, NJ............... 13.6 215.8 1.6 171 822 5.2 84 Essex, NJ................ 21.5 362.4 0.3 253 1,008 4.3 148 Gloucester, NJ........... 6.4 107.7 2.8 92 743 6.0 49 Hudson, NJ............... 14.1 236.3 -0.4 289 1,063 7.7 23 Mercer, NJ............... 11.1 232.5 1.6 171 1,005 7.4 27 Middlesex, NJ............ 21.1 402.6 0.3 253 1,004 8.8 9 Monmouth, NJ............. 20.6 266.1 0.6 234 845 4.3 148 Morris, NJ............... 18.1 294.0 0.8 217 1,118 1.4 292 Ocean, NJ................ 12.0 158.8 1.5 180 684 4.0 175 Passaic, NJ.............. 12.6 180.7 0.0 271 849 1.0 298 Somerset, NJ............. 10.2 176.8 1.7 163 1,242 10.0 5 Union, NJ................ 15.0 232.8 -0.1 278 996 5.5 69 Bernalillo, NM........... 17.0 332.7 3.5 57 704 2.8 248 Albany, NY............... 9.8 229.4 0.0 271 815 4.6 126 Bronx, NY................ 15.8 224.4 0.8 217 760 3.5 203 Broome, NY............... 4.5 95.6 -0.5 292 629 1.0 298 Dutchess, NY............. 8.3 119.5 -0.1 278 798 1.8 279 Erie, NY................. 23.4 458.7 0.0 271 692 3.3 217 Kings, NY................ 43.7 464.1 1.6 171 691 3.1 231 Monroe, NY............... 17.7 386.1 -0.5 292 788 0.6 303 Nassau, NY............... 52.1 607.3 0.2 260 886 2.7 253 New York, NY............. 115.7 2,312.6 2.2 130 1,453 7.8 22 Oneida, NY............... 5.3 112.5 1.2 195 614 3.2 224 Onondaga, NY............. 12.7 253.1 0.1 266 738 4.5 133 Orange, NY............... 9.8 131.2 0.2 260 698 2.6 257 Queens, NY............... 41.6 488.1 1.2 195 792 5.0 94 Richmond, NY............. 8.4 91.8 0.2 260 708 2.0 276 Rockland, NY............. 9.6 115.7 0.8 217 846 2.3 266 Suffolk, NY.............. 49.4 630.7 0.7 226 848 4.2 157 Westchester, NY.......... 36.2 420.7 0.4 246 1,058 5.5 69 Buncombe, NC............. 7.3 112.2 3.6 55 620 3.2 224 Catawba, NC.............. 4.4 88.1 2.8 92 621 4.7 117 Cumberland, NC........... 5.8 118.1 2.2 130 603 4.9 101 Durham, NC............... 6.4 175.7 4.5 32 1,002 1.8 279 Forsyth, NC.............. 8.6 182.2 2.4 113 723 2.7 253 Guilford, NC............. 14.0 275.2 1.0 204 712 4.4 142 Mecklenburg, NC.......... 28.7 536.8 3.5 57 913 4.0 175 New Hanover, NC.......... 7.0 100.0 4.8 25 633 3.8 189 Wake, NC................. 25.1 426.5 5.0 20 776 3.1 231 Cass, ND................. 5.8 95.6 3.5 57 642 4.7 117 Butler, OH............... 7.3 145.1 2.3 124 688 0.0 311 Cuyahoga, OH............. 38.1 761.4 -0.1 278 824 5.8 56 Franklin, OH............. 29.2 685.9 0.9 213 775 2.1 274 Hamilton, OH............. 24.1 532.0 0.0 271 838 3.7 195 Lake, OH................. 6.9 103.0 0.3 253 663 4.7 117 Lorain, OH............... 6.3 102.8 -0.5 292 692 6.8 38 Lucas, OH................ 10.9 227.0 -0.5 292 694 0.6 303 Mahoning, OH............. 6.4 105.5 0.4 246 579 3.8 189 Montgomery, OH........... 13.0 278.3 -0.7 297 732 1.9 278 Stark, OH................ 9.1 163.6 -0.9 302 629 5.4 74 Summit, OH............... 14.9 275.4 1.7 163 721 -0.4 314 Trumbull, OH............. 4.8 85.7 (7) - 689 3.3 217 Oklahoma, OK............. 22.8 421.8 2.1 138 708 9.6 7 Tulsa, OK................ 18.9 343.3 3.5 57 722 7.1 30 Clackamas, OR............ 12.3 149.5 2.7 96 735 3.1 231 Jackson, OR.............. 6.7 84.4 1.7 163 609 4.6 126 Lane, OR................. 10.8 150.9 2.7 96 626 3.0 237 Marion, OR............... 9.1 141.8 1.4 184 627 4.0 175 Multnomah, OR............ 26.7 442.0 3.4 63 799 3.5 203 Washington, OR........... 15.6 249.1 4.0 44 866 1.2 294 Allegheny, PA............ 34.9 692.5 0.8 217 829 4.4 142 Berks, PA................ 9.0 169.7 2.2 130 711 2.9 245 Bucks, PA................ 19.8 268.4 1.3 192 773 3.5 203 Butler, PA............... 4.7 77.9 1.1 200 663 5.4 74 Chester, PA.............. 14.7 238.0 1.8 156 1,030 5.0 94 Cumberland, PA........... 5.9 126.8 0.7 226 736 3.8 189 Dauphin, PA.............. 7.2 185.0 2.2 130 767 3.6 198 Delaware, PA............. 13.5 209.8 0.1 266 829 4.3 148 Erie, PA................. 7.2 129.7 -1.1 305 618 2.3 266 Lackawanna, PA........... 5.7 101.3 0.5 240 608 2.4 262 Lancaster, PA............ 11.9 231.6 0.6 234 672 1.5 291 Lehigh, PA............... 8.3 178.0 1.6 171 771 3.1 231 Luzerne, PA.............. 7.8 144.5 -0.1 278 611 0.8 302 Montgomery, PA........... 27.3 490.4 0.7 226 975 4.8 107 Northampton, PA.......... 6.3 98.7 1.0 204 698 2.9 245 Philadelphia, PA......... 29.0 632.6 0.5 240 903 4.4 142 Washington, PA........... 5.3 79.8 2.0 143 673 3.2 224 Westmoreland, PA......... 9.4 140.0 -1.2 308 649 8.3 15 York, PA................. 8.8 174.5 1.5 180 707 5.1 88 Kent, RI................. 5.6 83.9 0.3 253 714 3.9 182 Providence, RI........... 18.1 288.9 0.3 253 779 5.7 60 Charleston, SC........... 13.0 202.1 0.8 217 677 7.1 30 Greenville, SC........... 13.0 229.7 1.6 171 698 2.9 245 Horry, SC................ 8.9 120.5 4.7 28 527 5.6 65 Lexington, SC............ 6.0 91.2 2.4 113 607 2.2 271 Richland, SC............. 10.0 204.2 0.2 260 684 5.4 74 Spartanburg, SC.......... 6.6 116.0 0.1 266 693 4.1 165 Minnehaha, SD............ 6.2 114.5 2.2 130 644 3.5 203 Davidson, TN............. 18.1 446.8 3.4 63 808 7.9 19 Hamilton, TN............. 8.5 192.7 2.2 130 690 5.0 94 Knox, TN................. 10.6 224.4 2.9 85 676 2.3 266 Rutherford, TN........... 4.0 97.5 2.3 124 723 4.3 148 Shelby, TN............... 20.0 505.7 1.2 195 795 5.7 60 Bell, TX................. 4.4 96.0 2.5 110 601 3.8 189 Bexar, TX................ 30.9 701.5 3.6 55 696 6.6 41 Brazoria, TX............. 4.4 82.4 5.2 16 745 3.9 182 Brazos, TX............... 3.7 84.1 (7) - 558 (7) - Cameron, TX.............. 6.3 121.8 4.6 29 484 4.8 107 Collin, TX............... 15.0 264.8 8.2 1 902 0.1 308 Dallas, TX............... 66.6 1,462.9 3.3 67 956 4.9 101 Denton, TX............... 9.6 155.8 (7) - 682 4.8 107 El Paso, TX.............. 12.9 261.8 1.9 151 556 3.0 237 Fort Bend, TX............ 7.5 114.3 2.9 85 815 6.7 40 Galveston, TX............ 5.0 94.2 4.6 29 703 4.8 107 Harris, TX............... 92.0 1,941.2 4.1 41 959 7.5 25 Hidalgo, TX.............. 10.0 205.3 3.4 63 494 4.2 157 Jefferson, TX............ 5.8 122.1 2.9 85 728 6.9 35 Lubbock, TX.............. 6.6 121.5 2.4 113 604 7.1 30 McLennan, TX............. 4.8 102.6 0.6 234 622 2.8 248 Montgomery, TX........... 7.3 110.9 6.5 4 727 5.2 84 Nueces, TX............... 8.0 150.9 2.4 113 656 6.8 38 Smith, TX................ 5.1 91.8 2.5 110 681 7.1 30 Tarrant, TX.............. 35.2 741.6 3.0 82 815 5.7 60 Travis, TX............... 26.2 545.4 3.1 78 880 4.5 133 Webb, TX................. 4.6 84.5 4.6 29 530 -2.0 319 Williamson, TX........... 6.2 106.9 4.4 35 765 0.1 308 Davis, UT................ 7.1 103.6 6.2 6 648 8.0 18 Salt Lake, UT............ 38.6 567.2 5.2 16 720 4.5 133 Utah, UT................. 12.7 167.0 6.7 3 600 5.4 74 Weber, UT................ 5.8 92.4 3.7 52 602 6.9 35 Chittenden, VT........... 5.7 95.7 -0.3 284 769 3.9 182 Arlington, VA............ 7.4 160.3 2.3 124 1,335 5.5 69 Chesterfield, VA......... 7.1 121.2 3.7 52 702 3.4 212 Fairfax, VA.............. 31.7 582.2 2.4 113 1,209 2.8 248 Henrico, VA.............. 8.8 175.8 1.1 200 830 3.4 212 Loudoun, VA.............. 7.6 127.5 2.4 113 994 5.0 94 Prince William, VA....... 6.6 107.3 4.3 37 714 5.6 65 Alexandria City, VA...... 5.9 94.9 0.3 253 1,046 8.5 12 Chesapeake City, VA...... 5.3 100.9 4.9 23 634 4.6 126 Newport News City, VA.... 3.9 99.3 0.9 213 713 3.5 203 Norfolk City, VA......... 5.7 144.5 -0.7 297 775 6.9 35 Richmond City, VA........ 7.0 163.1 1.6 171 881 4.1 165 Virginia Beach City, VA.. 11.3 184.0 2.6 104 632 7.3 29 Clark, WA................ 11.1 131.6 4.1 41 716 3.8 189 King, WA................. 74.7 1,160.2 3.7 52 988 6.1 47 Kitsap, WA............... 6.3 85.8 3.1 78 732 7.5 25 Pierce, WA............... 19.6 267.6 3.2 76 707 4.7 117 Snohomish, WA............ 16.7 235.7 5.2 16 817 5.4 74 Spokane, WA.............. 14.5 207.5 4.0 44 637 3.4 212 Thurston, WA............. 6.4 98.1 4.0 44 704 2.2 271 Whatcom, WA.............. 6.6 81.3 1.2 195 606 2.2 271 Yakima, WA............... 7.5 108.5 0.4 246 530 4.3 148 Kanawha, WV.............. 6.1 109.5 0.7 226 694 3.0 237 Brown, WI................ 6.8 150.5 0.6 234 674 -0.7 316 Dane, WI................. 14.0 301.2 1.1 200 751 3.3 217 Milwaukee, WI............ 21.6 496.2 0.1 266 788 4.8 107 Outagamie, WI............ 5.0 104.1 -0.2 282 677 2.4 262 Racine, WI............... 4.3 77.7 -0.3 284 731 4.3 148 Waukesha, WI............. 13.4 238.8 1.3 192 791 4.4 142 Winnebago, WI............ 3.9 90.4 1.7 163 733 1.7 285 San Juan, PR............. 14.7 304.2 -2.7 (8) 510 3.9 (8) 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 325 U.S. counties comprise 65.6 percent of the total covered workers in the U.S. 2 Data are preliminary. 3 Includes areas not officially designated as counties. See Technical Note. 4 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. 5 Average weekly wages were calculated using unrounded data. 6 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. 7 Data do not meet BLS or State agency disclosure standards. 8 This county was not included in the U.S. rankings. Table 2. Covered (1) establishments, employment, and wages in the ten largest counties, second quarter 2006 (2) Employment Average weekly wage (4) Establishments, second quarter County by NAICS supersector 2006 Percent Percent (thousands) June change, Average change, 2006 June weekly second (thousands) 2005-06 (3) wage quarter 2005-06 (3) United States (5)............................ 8,774.8 135,481.1 2.0 $784 4.4 Private industry........................... 8,496.4 114,201.0 2.2 774 4.6 Natural resources and mining............. 123.8 1,904.1 2.7 790 13.3 Construction............................. 875.1 7,870.8 5.5 820 5.8 Manufacturing............................ 364.2 14,256.1 -0.1 952 4.2 Trade, transportation, and utilities..... 1,895.9 26,042.5 1.5 682 4.0 Information.............................. 144.2 3,065.0 -0.1 1,188 4.7 Financial activities..................... 846.1 8,219.2 1.9 1,141 5.4 Professional and business services....... 1,425.8 17,646.2 4.2 944 4.4 Education and health services............ 794.6 16,871.9 2.7 735 4.4 Leisure and hospitality.................. 708.1 13,570.7 2.0 330 4.8 Other services........................... 1,109.9 4,446.1 1.2 509 4.3 Government................................. 278.3 21,280.1 1.0 836 3.3 Los Angeles, CA.............................. 387.2 4,196.7 2.0 882 3.6 Private industry........................... 383.3 3,607.8 2.3 864 4.2 Natural resources and mining............. 0.6 12.0 4.8 1,317 20.6 Construction............................. 14.1 158.4 6.1 876 3.9 Manufacturing............................ 15.9 468.3 -1.0 938 5.2 Trade, transportation, and utilities..... 55.8 804.7 1.8 749 4.3 Information.............................. 8.9 210.4 4.6 1,433 -2.9 Financial activities..................... 25.1 249.3 1.9 1,368 5.6 Professional and business services....... 43.2 600.9 (6) 1,007 6.3 Education and health services............ 28.2 463.3 2.0 810 4.0 Leisure and hospitality.................. 27.1 394.2 2.4 491 4.9 Other services........................... 164.3 246.0 4.0 410 2.8 Government................................. 3.9 588.9 0.1 993 0.5 Cook, IL..................................... 134.0 2,565.5 1.4 942 4.3 Private industry........................... 132.8 2,246.9 1.6 936 4.8 Natural resources and mining............. 0.1 1.5 -2.4 998 7.3 Construction............................. 11.7 100.6 5.3 1,147 6.2 Manufacturing............................ 7.3 246.7 -2.2 960 4.9 Trade, transportation, and utilities..... 27.4 480.5 0.7 771 4.6 Information.............................. 2.5 59.5 -2.5 1,308 6.9 Financial activities..................... 15.0 220.8 1.1 1,477 7.4 Professional and business services....... 27.5 436.6 3.7 1,186 2.0 Education and health services............ 13.2 360.2 1.9 799 4.6 Leisure and hospitality.................. 11.3 240.1 3.3 416 8.9 Other services........................... 13.4 96.5 0.0 676 6.0 Government................................. 1.2 318.7 0.0 983 0.8 New York, NY................................. 115.7 2,312.6 2.2 1,453 7.8 Private industry........................... 115.5 1,860.5 2.8 1,557 7.4 Natural resources and mining............. 0.0 0.1 4.2 1,272 11.2 Construction............................. 2.2 31.6 7.1 1,386 7.9 Manufacturing............................ 3.0 39.8 -6.2 1,066 -0.8 Trade, transportation, and utilities..... 21.3 241.4 1.5 1,100 6.6 Information.............................. 4.2 132.1 1.4 1,826 6.8 Financial activities..................... 17.6 369.5 3.2 2,810 10.8 Professional and business services....... 23.1 466.0 3.2 1,660 4.5 Education and health services............ 8.1 279.5 2.1 956 6.5 Leisure and hospitality.................. 10.5 201.2 2.5 711 6.6 Other services........................... 16.7 85.2 -0.1 876 7.4 Government................................. 0.2 452.1 -0.3 1,028 9.4 Harris, TX................................... 92.0 1,941.2 4.1 959 7.5 Private industry........................... 91.6 1,695.4 4.6 976 7.6 Natural resources and mining............. 1.4 71.2 8.7 2,680 17.2 Construction............................. 6.3 141.6 8.7 912 7.5 Manufacturing............................ 4.6 176.3 5.4 1,189 4.7 Trade, transportation, and utilities..... 21.2 406.2 3.4 862 5.6 Information.............................. 1.3 32.2 0.0 1,150 4.5 Financial activities..................... 10.0 116.8 1.6 1,180 7.2 Professional and business services....... 17.9 317.6 6.3 1,075 6.6 Education and health services............ 9.6 201.9 3.9 806 4.5 Leisure and hospitality.................. 7.0 170.6 2.3 366 9.3 Other services........................... 10.7 57.1 1.6 553 4.3 Government................................. 0.4 245.8 0.9 843 6.3 Maricopa, AZ................................. 91.2 1,784.4 5.7 794 4.5 Private industry........................... 90.7 1,601.1 6.0 782 5.2 Natural resources and mining............. 0.5 9.8 -2.7 644 18.4 Construction............................. 9.2 181.4 11.6 806 6.1 Manufacturing............................ 3.4 137.5 2.8 1,076 6.0 Trade, transportation, and utilities..... 19.3 361.7 4.7 765 3.9 Information.............................. 1.5 31.9 -2.7 942 3.6 Financial activities..................... 11.0 149.7 4.8 1,020 3.4 Professional and business services....... 19.5 311.5 5.9 769 5.2 Education and health services............ 8.7 185.1 6.0 829 6.4 Leisure and hospitality.................. 6.4 175.9 6.0 383 9.4 Other services........................... 6.4 48.2 3.6 556 7.8 Government................................. 0.6 183.4 2.8 892 0.2 Orange, CA................................... 95.5 1,530.4 1.8 916 6.3 Private industry........................... 94.1 1,375.7 1.7 907 6.1 Natural resources and mining............. 0.2 6.9 0.2 549 -6.8 Construction............................. 7.1 109.0 5.8 945 4.8 Manufacturing............................ 5.6 183.8 0.3 1,137 11.8 Trade, transportation, and utilities..... 18.0 270.6 0.8 845 3.8 Information.............................. 1.4 31.4 -2.6 1,226 3.2 Financial activities..................... 11.4 139.5 -1.1 1,381 4.2 Professional and business services....... 19.3 275.6 2.8 966 8.7 Education and health services............ 9.9 136.5 3.2 811 4.1 Leisure and hospitality.................. 7.1 173.4 3.2 392 5.7 Other services........................... 14.1 49.0 -0.1 542 4.2 Government................................. 1.4 154.6 2.6 995 7.7 Dallas, TX................................... 66.6 1,462.9 3.3 956 4.9 Private industry........................... 66.1 1,304.6 3.7 966 5.0 Natural resources and mining............. 0.5 7.5 4.7 2,925 39.2 Construction............................. 4.3 80.4 3.0 924 8.5 Manufacturing............................ 3.2 148.0 2.7 1,118 5.5 Trade, transportation, and utilities..... 14.9 303.9 2.5 916 4.3 Information.............................. 1.7 53.0 -1.4 1,271 5.0 Financial activities..................... 8.4 140.3 3.8 1,249 5.4 Professional and business services....... 13.9 261.4 6.5 1,039 0.8 Education and health services............ 6.3 137.0 4.2 906 7.6 Leisure and hospitality.................. 5.1 129.7 3.1 422 5.0 Other services........................... 6.5 40.5 1.0 604 6.3 Government................................. 0.4 158.3 0.5 874 4.0 San Diego, CA................................ 91.6 1,327.9 1.4 850 4.7 Private industry........................... 90.2 1,105.9 1.7 830 4.3 Natural resources and mining............. 0.8 11.6 -5.3 522 0.6 Construction............................. 7.3 95.9 2.9 862 3.0 Manufacturing............................ 3.3 105.1 -0.4 1,117 4.5 Trade, transportation, and utilities..... 14.7 218.9 2.4 691 2.1 Information.............................. 1.3 37.2 -1.3 1,839 19.9 Financial activities..................... 10.1 84.8 1.2 1,065 1.9 Professional and business services....... 16.5 215.4 1.0 1,013 5.0 Education and health services............ 8.0 122.9 1.1 785 4.7 Leisure and hospitality.................. 6.8 157.8 3.9 376 3.3 Other services........................... 21.3 56.3 2.7 468 2.6 Government................................. 1.4 222.0 0.1 949 6.5 King, WA..................................... 74.7 1,160.2 3.7 988 6.1 Private industry........................... 74.2 1,006.5 4.3 996 6.8 Natural resources and mining............. 0.4 3.4 2.8 1,172 5.7 Construction............................. 6.6 67.6 14.5 940 5.5 Manufacturing............................ 2.5 111.6 4.6 1,368 8.7 Trade, transportation, and utilities..... 14.7 220.2 2.3 859 5.3 Information.............................. 1.7 72.9 5.0 1,754 4.7 Financial activities..................... 6.8 76.8 2.3 1,232 6.9 Professional and business services....... 12.4 180.6 7.5 1,156 8.3 Education and health services............ 6.2 117.9 2.5 774 4.0 Leisure and hospitality.................. 5.8 110.0 1.9 417 5.6 Other services........................... 17.1 45.5 0.1 532 6.0 Government................................. 0.5 153.7 0.0 939 2.1 Miami-Dade, FL............................... 84.1 993.7 1.8 786 3.0 Private industry........................... 83.8 860.3 2.0 763 5.0 Natural resources and mining............. 0.5 8.9 4.1 459 1.1 Construction............................. 5.7 51.9 14.6 850 7.7 Manufacturing............................ 2.6 47.9 -3.2 727 7.4 Trade, transportation, and utilities..... 22.9 248.7 2.8 731 5.3 Information.............................. 1.7 21.8 -5.5 1,108 5.4 Financial activities..................... 10.0 71.8 4.8 1,096 4.2 Professional and business services....... 16.8 138.8 -3.8 888 1.8 Education and health services............ 8.5 131.1 3.4 764 5.8 Leisure and hospitality.................. 5.6 99.8 -1.1 457 (6) Other services........................... 7.6 35.0 3.8 497 2.9 Government................................. 0.3 133.4 0.1 924 -4.8 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. 2 Data are preliminary. 3 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. 4 Average weekly wages were calculated using unrounded data. 5 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. 6 Data do not meet BLS or State agency disclosure standards. Table 3. Covered (1) establishments, employment, and wages in the largest county by state, second quarter 2006 (2) Employment Average weekly wage (5) Establishments, second quarter County (3) 2006 Percent Percent (thousands) June change, Average change, 2006 June weekly second (thousands) 2005-06 (4) wage quarter 2005-06 (4) United States (6)........ 8,774.8 135,481.1 2.0 $784 4.4 Jefferson, AL............ 18.6 375.9 1.4 782 2.4 Anchorage Borough, AK.... 8.0 150.7 4.4 839 3.3 Maricopa, AZ............. 91.2 1,784.4 5.7 794 4.5 Pulaski, AR.............. 14.1 249.9 2.0 707 2.8 Los Angeles, CA.......... 387.2 4,196.7 2.0 882 3.6 Denver, CO............... 25.2 435.4 2.4 940 1.7 Hartford, CT............. 24.9 503.8 (7) 969 (7) New Castle, DE........... 19.5 285.0 1.4 968 8.6 Washington, DC........... 31.2 677.9 0.4 1,300 5.3 Miami-Dade, FL........... 84.1 993.7 1.8 786 3.0 Fulton, GA............... 39.6 775.0 2.0 1,006 3.4 Honolulu, HI............. 24.2 452.3 2.3 726 3.7 Ada, ID.................. 14.6 210.6 5.8 744 7.4 Cook, IL................. 134.0 2,565.5 1.4 942 4.3 Marion, IN............... 23.5 582.7 0.8 819 4.7 Polk, IA................. 14.3 274.0 2.9 780 5.8 Johnson, KS.............. 19.8 306.1 0.2 812 4.8 Jefferson, KY............ 22.1 434.9 1.8 778 4.1 East Baton Rouge, LA..... 13.7 262.1 4.8 699 8.5 Cumberland, ME........... 12.0 175.5 1.6 708 3.5 Montgomery, MD........... 32.7 471.2 1.7 1,037 4.6 Middlesex, MA............ 46.9 812.0 1.6 1,110 4.5 Wayne, MI................ 33.3 781.6 -1.7 904 0.9 Hennepin, MN............. 43.9 850.5 2.0 978 4.0 Hinds, MS................ 6.5 128.5 0.9 691 5.5 St. Louis, MO............ 33.7 631.6 1.0 859 5.3 Yellowstone, MT.......... 5.5 75.6 3.7 623 3.0 Douglas, NE.............. 15.3 315.8 1.0 749 8.4 Clark, NV................ 45.0 919.3 5.9 750 0.1 Hillsborough, NH......... 12.5 197.6 0.0 847 1.3 Bergen, NJ............... 34.5 454.3 0.4 983 3.6 Bernalillo, NM........... 17.0 332.7 3.5 704 2.8 New York, NY............. 115.7 2,312.6 2.2 1,453 7.8 Mecklenburg, NC.......... 28.7 536.8 3.5 913 4.0 Cass, ND................. 5.8 95.6 3.5 642 4.7 Cuyahoga, OH............. 38.1 761.4 -0.1 824 5.8 Oklahoma, OK............. 22.8 421.8 2.1 708 9.6 Multnomah, OR............ 26.7 442.0 3.4 799 3.5 Allegheny, PA............ 34.9 692.5 0.8 829 4.4 Providence, RI........... 18.1 288.9 0.3 779 5.7 Greenville, SC........... 13.0 229.7 1.6 698 2.9 Minnehaha, SD............ 6.2 114.5 2.2 644 3.5 Shelby, TN............... 20.0 505.7 1.2 795 5.7 Harris, TX............... 92.0 1,941.2 4.1 959 7.5 Salt Lake, UT............ 38.6 567.2 5.2 720 4.5 Chittenden, VT........... 5.7 95.7 -0.3 769 3.9 Fairfax, VA.............. 31.7 582.2 2.4 1,209 2.8 King, WA................. 74.7 1,160.2 3.7 988 6.1 Kanawha, WV.............. 6.1 109.5 0.7 694 3.0 Milwaukee, WI............ 21.6 496.2 0.1 788 4.8 Laramie, WY.............. 3.1 42.5 3.0 644 8.4 San Juan, PR............. 14.7 304.2 -2.7 510 3.9 St. Thomas, VI........... 1.8 23.2 0.9 640 2.7 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. 2 Data are preliminary. 3 Includes areas not officially designated as counties. See Technical Note. 4 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. 5 Average weekly wages were calculated using unrounded data. 6 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. 7 Data do not meet BLS or State agency disclosure standards. Table 4. Covered (1) establishments, employment, and wages by state, second quarter 2006 (2) Employment Average weekly wage (3) Establishments, second quarter State 2006 Percent Percent (thousands) June change, Average change, 2006 June weekly second (thousands) 2005-06 wage quarter 2005-06 United States (4)........ 8,774.8 135,481.1 2.0 $784 4.4 Alabama.................. 116.5 1,944.8 2.3 672 4.3 Alaska................... 20.8 327.2 3.8 788 4.2 Arizona.................. 148.7 2,581.3 5.7 753 4.1 Arkansas................. 81.1 1,185.3 2.4 612 3.2 California............... 1,249.0 15,733.0 2.4 888 4.5 Colorado................. 174.2 2,277.7 2.8 794 3.3 Connecticut.............. 111.5 1,700.6 1.5 971 2.8 Delaware................. 30.0 430.4 2.0 851 6.8 District of Columbia..... 31.2 677.9 0.4 1,300 5.3 Florida.................. 586.6 7,889.6 3.2 722 4.8 Georgia.................. 263.8 4,054.1 3.2 743 3.1 Hawaii................... 37.4 621.8 2.5 704 4.0 Idaho.................... 54.7 660.0 5.7 612 7.4 Illinois................. 347.4 5,912.4 1.7 837 4.1 Indiana.................. 154.6 2,917.5 0.9 684 3.0 Iowa..................... 92.5 1,502.9 1.9 639 4.1 Kansas................... 84.8 1,339.5 1.2 667 5.0 Kentucky................. 109.2 1,797.2 1.2 672 3.4 Louisiana................ 122.2 1,831.7 -3.9 680 10.2 Maine.................... 49.1 616.0 0.8 632 3.8 Maryland................. 162.9 2,567.8 1.6 855 4.7 Massachusetts............ 207.8 3,256.7 1.1 963 5.1 Michigan................. 256.7 4,320.8 -1.0 783 1.8 Minnesota................ 173.0 2,731.9 2.3 789 4.0 Mississippi.............. 68.6 1,127.4 0.9 587 5.6 Missouri................. 171.7 2,743.6 1.6 703 3.7 Montana.................. 41.2 442.8 4.3 575 4.0 Nebraska................. 57.4 915.6 1.1 632 5.7 Nevada................... 70.7 1,284.6 5.2 748 1.4 New Hampshire............ 48.6 639.1 1.2 774 2.5 New Jersey............... 277.5 4,053.9 1.0 948 5.1 New Mexico............... 52.6 824.4 5.0 653 4.6 New York................. 570.4 8,566.2 1.0 962 5.4 North Carolina........... 241.1 3,965.0 3.0 690 3.8 North Dakota............. 25.3 342.4 2.7 591 5.3 Ohio..................... 291.5 5,396.5 0.4 716 3.3 Oklahoma................. 96.2 1,512.5 3.0 639 7.4 Oregon................... 127.9 1,732.5 3.0 710 3.3 Pennsylvania............. 332.2 5,675.5 1.0 766 3.9 Rhode Island............. 35.9 490.7 0.6 755 4.7 South Carolina........... 125.0 1,858.5 1.5 646 4.2 South Dakota............. 29.6 396.1 2.3 563 4.3 Tennessee................ 136.1 2,749.2 2.2 703 4.9 Texas.................... 532.8 9,965.6 3.8 781 5.8 Utah..................... 86.4 1,182.9 5.6 655 5.3 Vermont.................. 24.6 307.7 1.1 665 3.1 Virginia................. 219.6 3,697.5 2.1 822 4.4 Washington............... 210.9 2,911.9 3.0 799 5.1 West Virginia............ 48.3 714.3 1.6 636 3.9 Wisconsin................ 162.6 2,828.3 1.1 685 3.3 Wyoming.................. 23.9 278.6 5.1 685 10.3 Puerto Rico.............. 60.0 1,039.6 -0.4 435 4.1 Virgin Islands........... 3.4 45.3 3.2 679 5.6 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.