Technical information:(202) 691-6567 USDL 09-0032
http://www.bls.gov/cew/
For release: 10:00 A.M. EST
Media contact: 691-5902 Tuesday, January 13, 2009
COUNTY EMPLOYMENT AND WAGES: SECOND QUARTER 2008
From June 2007 to June 2008, employment declined in more than half
of the largest U.S. counties, according to preliminary data released
today by the Bureau of Labor Statistics of the U.S. Department of
Labor. Lee County, Fla., which contains the Cape Coral-Fort Myers
area, posted the largest percentage decline, with a loss of 8.8
percent over the year, compared with a national job decrease of 0.3
percent. Orleans County, La., which includes the city of New Orleans,
experienced the largest over-the-year percentage increase in
employment among the largest counties in the U.S., with a gain of 5.6
percent.
Rock Island County, Ill., had the largest over-the-year gain in
average weekly wages in the second quarter of 2008, with an increase
of 10.5 percent coming largely from the manufacturing supersector.
The U.S. average weekly wage rose by 2.6 percent over the same time
span.
Of the 334 largest counties in the United States (as measured by
2007 annual average employment) 159 had over-the-year percentage
growth in employment above the national average (-0.3 percent) in
June 2008; 157 large counties experienced changes below the national
average. The percent change in average weekly wages was higher than
the national average (2.6 percent) in 157 of the largest U.S.
counties but was below the national average in 162 counties.
Table A. Top 10 large counties ranked by June 2008 employment, June 2007-08 employment growth,
and June 2007-08 percent growth in employment
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Employment in large counties
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June 2008 employment | Growth in employment, | Percent growth in employment,
(thousands) | June 2007-08 | June 2007-08
| (thousands) |
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| |
United States 136,631.8| United States -397.0| United States -0.3
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| |
Los Angeles, Calif. 4,229.7| Harris, Texas 56.1| Orleans, La. 5.6
Cook, Ill. 2,533.4| New York, N.Y. 24.0| Williamson, Texas 4.3
New York, N.Y. 2,392.5| King, Wash. 20.0| Fort Bend, Texas 4.2
Harris, Texas 2,073.4| Dallas, Texas 17.1| Tulare, Calif. 4.0
Maricopa, Ariz. 1,741.0| Bexar, Texas 15.0| Montgomery, Texas 3.8
Orange, Calif. 1,502.4| Tarrant, Texas 13.3| Bell, Texas 3.6
Dallas, Texas 1,498.9| Santa Clara, Calif. 9.3| Cass, N.D. 3.5
San Diego, Calif. 1,336.7| Orleans, La. 9.2| Brazos, Texas 3.0
King, Wash. 1,201.4| Travis, Texas 9.0| Denton, Texas 3.0
Miami-Dade, Fla. 992.7| Washington, D.C. 7.9| Harris, Texas 2.8
| |
| |
| |
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The employment and average weekly wage data by county are compiled
under the Quarterly Census of Employment and Wages (QCEW) program,
also known as the ES-202 program. The data are derived from reports
submitted by every employer subject to unemployment insurance (UI)
laws. The 9.1 million employer reports cover 136.6 million full- and
part-time workers. The attached tables contain data for the nation
and for the 334 U.S. counties with annual average employment levels of
75,000 or more in 2007. June 2008 employment and 2008 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 2007 are available on the BLS Web site at
http://www.bls.gov/cew/. Preliminary data for first quarter 2008 also are
available on the BLS Web site. Updated data for first quarter 2008 and
preliminary data for second quarter 2008 will be available later in January
on the BLS Web site.
Large County Employment
In June 2008, national employment, as measured by the QCEW program,
was 136.6 million, down by 0.3 percent from June 2007. The 334 U.S.
counties with 75,000 or more employees accounted for 71.3 percent of
total U.S. employment and 76.8 percent of total wages. These 334
counties had a net job decline of 407,700 over the year, which
exceeds the overall U.S. employment decline by 3 percent, or 11,000
jobs.
Employment declined in 188 counties from June 2007 to June 2008.
The largest percentage decline in employment was in Lee, Fla. (-8.8
percent). Collier, Fla., had the next largest percentage decline (-
6.8 percent), followed by the counties of Sarasota, Fla., and
Elkhart, Ind. (-6.5 percent each), and Marion, Fla. (-6.0 percent).
The largest decline in employment levels occurred in Maricopa, Ariz.
(-55,100), followed by the counties of Riverside, Calif. (-29,400),
Hillsborough, Fla. (-27,100), Orange, Calif. (-26,100), and Palm
Beach, Fla. (-25,700). Combined employment losses in these five
counties over the year totaled 163,400, or 41 percent of the
employment decline for the U.S. as a whole.
Employment rose in 125 of the large counties from June 2007 to June
2008. Orleans County, La., had the largest over-the-year percentage
increase in employment (5.6 percent). Williamson, Texas, had the next
largest increase, 4.3 percent, followed by the counties of Fort Bend,
Texas (4.2 percent), Tulare, Calif. (4.0 percent), and Montgomery,
Texas (3.8 percent). The largest gains in the level of employment from
June 2007 to June 2008 were recorded in the counties of Harris, Texas
(56,100), New York, N.Y. (24,000), King, Wash. (20,000), Dallas,
Texas (17,100), and Bexar, Texas (15,000). (See table A.)
Table B. Top 10 large counties ranked by second quarter 2008 average weekly wages, second quarter 2007-08
growth in average weekly wages, and second quarter 2007-08 percent growth in average weekly wages
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Average weekly wage in large counties
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Average weekly wage, | Growth in average weekly | Percent growth in average
second quarter 2008 | wage, second quarter 2007-08 | weekly wage, second
| | quarter 2007-08
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| |
United States $841| United States $21| United States 2.6
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| |
New York, N.Y. $1,569| Rock Island, Ill. $82| Rock Island, Ill. 10.5
Santa Clara, Calif. 1,529| Washington, D.C. 80| Weld, Colo. 10.4
Washington, D.C. 1,433| Weld, Colo. 72| Utah, Utah 9.4
Arlington, Va. 1,376| St. Louis City, Mo. 62| Whatcom, Wash. 8.3
San Francisco, Calif. 1,334| Middlesex, Mass. 61| East Baton Rouge, La. 7.8
Fairfield, Conn. 1,325| Utah, Utah 60| Montgomery, Texas 7.3
Fairfax, Va. 1,317| East Baton Rouge, La. 57| St. Louis City, Mo. 6.9
Suffolk, Mass. 1,309| Montgomery, Texas 54| Cumberland, N.C. 6.1
San Mateo, Calif. 1,291| Whatcom, Wash. 53| Oklahoma, Okla. 6.0
Somerset, N.J. 1,277| Jefferson, Colo. 49| Jefferson, Colo. 5.9
| | Washington, D.C. 5.9
| |
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Large County Average Weekly Wages
The national average weekly wage in the second quarter of 2008 was
$841. Average weekly wages were higher than the national average in
109 of the largest 334 U.S. counties. New York, N.Y., held the top
position among the highest-paid large counties with an average weekly
wage of $1,569. Santa Clara, Calif., was second with an average
weekly wage of $1,529, followed by Washington, D.C. ($1,433),
Arlington, Va. ($1,376), and San Francisco, Calif. ($1,334). (See
table B.)
There were 224 counties with an average weekly wage below the
national average in the second quarter of 2008. The lowest average
weekly wage was reported in Cameron County, Texas ($535), followed by
the counties of Hidalgo, Texas ($538), Horry, S.C. ($539), Webb,
Texas ($562), and Yakima, Wash. ($580). (See table 1.)
Over the year, the national average weekly wage rose by 2.6
percent. Among the largest counties, Rock Island, Ill., led the
nation in growth in average weekly wages, with an increase of 10.5
percent from the second quarter of 2007. Weld, Colo., was second with
growth of 10.4 percent, followed by the counties of Utah, Utah (9.4
percent), Whatcom, Wash. (8.3 percent), and East Baton Rouge, La.
(7.8 percent).
Twenty-six large counties experienced over-the-year declines in
average weekly wages. Clayton, Ga., had the largest decrease (-43.7
percent), followed by the counties of Boone, Ky. (-10.0 percent),
Ventura, Calif., and Trumbull, Ohio (-4.8 percent each), and Queens,
N.Y. (-4.3 percent).
Ten Largest U.S. Counties
Four of the 10 largest counties (based on 2007 annual average
employment levels) experienced over-the-year percent increases in
employment in June 2008. Harris, Texas, experienced the largest
percent gain in employment (2.8 percent) among the 10 largest
counties. Within Harris County, the largest gains in employment were
in natural resources and mining (6.0 percent) and construction (4.9
percent). King, Wash., had the next largest increase in employment,
1.7 percent, followed by Dallas, Texas (1.2 percent). Maricopa,
Ariz., experienced the largest decline in employment among the 10
largest counties with a 3.1 percent decrease. Within Maricopa, nine
industry groups experienced employment declines, with construction
experiencing the largest decline, -18.8 percent. Miami-Dade, Fla.,
had the next largest decline in employment, -2.1 percent, followed by
Orange, Calif. (-1.7 percent). (See table 2.)
Nine of the 10 largest U.S. counties saw an over-the-year increase
in average weekly wages. San Diego, Calif., had the fastest growth in
wages among the 10 largest counties, with a gain of 4.2 percent.
Within San Diego County, average weekly wages increased the most in
the information industry (22.9 percent), followed by government (6.4
percent). Harris, Texas, was second in wage growth with a gain of 3.9
percent, followed by Miami-Dade, Fla. (3.1 percent). The smallest
wage gain occurred in Orange, Calif. (0.2 percent), followed by Cook,
Ill. (1.9 percent). The only wage decline among the 10 largest
counties occurred in Dallas, Texas (-0.2 percent).
Largest County by State
Table 3 shows June 2008 employment and the 2008 second quarter
average weekly wage in the largest county in each state, which is
based on 2007 annual average employment levels. (This table includes
one county--Laramie, Wyo.--that had an employment level below 75,000
in 2007.) The employment levels in the counties in table 3 in June
2008 ranged from approximately 4.23 million in Los Angeles County,
Calif., to 44,600 in Laramie County, Wyo. The highest average weekly
wage of these counties was in New York, N.Y. ($1,569), while the
lowest average weekly wage was in Minnehaha, S.D. ($682).
For More Information
For additional information about the quarterly employment and wages
data, please read the Technical Note or visit the QCEW Web site at
http://www.bls.gov/cew/. Additional information about the QCEW data
also may be obtained by calling (202) 691-6567.
Several BLS regional offices are issuing QCEW news releases
targeted to local data users. For links to these releases, see
http://www.bls.gov/cew/cewregional.htm.
The County Employment and Wages release for third quarter 2008 is
scheduled to be released on Wednesday, April 8, 2009.
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
2008 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 335 counties presented in this re-
lease were derived using 2007 preliminary annual averages of employment. For 2008
data, six counties have been added to the publication tables: Shelby, Ala., Boone,
Ky., St. Tammany, La., Yellowstone, Mont., Warren, Ohio, and Potter, Texas. These
counties will be included in all 2008 quarterly 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' 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 9.1 | ministrative records| ments
| million establish- | submitted by 7.1 |
| 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 | | |
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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 9.1 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
2007, UI and UCFE programs covered workers in 135.4 million jobs. The estimated
130.3 million workers in these jobs (after adjustment for multiple jobholders) rep-
resented 96.2 percent of civilian wage and salary employment. Covered workers re-
ceived $6.018 trillion in pay, representing 94.6 percent of the wage and salary com-
ponent of personal income and 43.6 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 2007 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. Beginning with the first quarter of 2008, adjusted data
will also account for administrative changes caused by multi-unit employers who
start reporting for each individual establishment rather than as a single entity.
The adjusted data used to calculate the over-the-year change measures presented in
any County Employment and Wages news release are valid for comparisons between the
starting and ending points (a 12-month 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 2007 edition of this bulletin contains selected data produced by Busi-
ness Employment Dynamics (BED) on job gains and losses, as well as selected data
from the first quarter 2008 version of this news release. Tables and additional con-
tent from the 2007 Employment and Wages Annual Bulletin are now available online at
http://www.bls.gov/cew/cewbultn07.htm. These tables present final 2007 annual av-
erages. The tables will also be included on the CD which accompanies the hardcopy
version of the Annual Bulletin. Employment and Wages Annual Averages, 2007 is ex-
pected to be available for sale as a chartbook by the end of the first quarter of
2009 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.
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 335 largest counties,
second quarter 2008(2)
Employment Average weekly wage(4)
Establishments,
County(3) second quarter Percent Ranking Percent Ranking
2008 June change, by Average change, by
(thousands) 2008 June percent weekly second percent
(thousands) 2007-08(5) change wage quarter change
2007-08(5)
United States(6)......... 9,107.3 136,631.8 -0.3 - $841 2.6 -
Jefferson, AL............ 19.0 362.3 -0.8 200 840 1.9 218
Madison, AL.............. 8.9 183.4 2.5 14 892 3.4 88
Mobile, AL............... 10.1 177.0 1.4 34 706 3.4 88
Montgomery, AL........... 6.8 139.3 -1.2 232 734 5.5 16
Shelby, AL............... 5.0 76.4 -0.1 141 776 0.9 273
Tuscaloosa, AL........... 4.5 86.2 -0.6 191 724 4.3 41
Anchorage Borough, AK.... 8.2 151.1 1.5 33 914 2.5 166
Maricopa, AZ............. 102.2 1,741.0 -3.1 302 845 2.1 203
Pima, AZ................. 21.2 364.8 -1.9 277 748 2.0 212
Benton, AR............... 5.6 96.3 0.0 126 786 5.4 17
Pulaski, AR.............. 14.9 251.4 -0.1 141 765 3.2 109
Washington, AR........... 5.8 93.2 -1.0 215 698 1.6 242
Alameda, CA.............. 53.5 688.9 -0.8 200 1,094 1.0 270
Butte, CA................ 7.9 76.4 -1.2 232 645 4.2 43
Contra Costa, CA......... 29.7 344.9 -1.5 253 1,057 3.2 109
Fresno, CA............... 30.1 366.3 -0.4 172 687 3.3 94
Kern, CA................. 18.1 288.3 0.5 88 748 3.3 94
Los Angeles, CA.......... 421.0 4,229.7 -0.2 153 946 2.6 158
Marin, CA................ 11.9 111.3 0.9 60 1,067 1.5 248
Monterey, CA............. 12.7 185.9 0.9 60 751 1.6 242
Orange, CA............... 101.2 1,502.4 -1.7 267 954 0.2 294
Placer, CA............... 10.9 139.0 -2.1 282 815 -0.1 302
Riverside, CA............ 46.2 622.5 -4.5 316 719 2.0 212
Sacramento, CA........... 53.5 634.9 -1.8 273 944 3.5 79
San Bernardino, CA....... 48.2 655.4 -2.6 295 740 1.8 228
San Diego, CA............ 98.3 1,336.7 -0.4 172 926 4.2 43
San Francisco, CA........ 51.3 576.9 (7) - 1,334 1.1 268
San Joaquin, CA.......... 17.7 231.4 -1.3 241 739 2.6 158
San Luis Obispo, CA...... 9.7 107.6 -1.9 277 713 1.7 237
San Mateo, CA............ 24.0 344.6 0.5 88 1,291 0.5 285
Santa Barbara, CA........ 14.3 194.9 0.3 105 800 2.3 186
Santa Clara, CA.......... 59.7 917.6 1.0 53 1,529 1.6 242
Santa Cruz, CA........... 9.0 104.3 -0.8 200 756 0.8 275
Solano, CA............... 10.0 127.8 -2.1 282 853 4.5 31
Sonoma, CA............... 18.6 194.6 -1.7 267 826 2.5 166
Stanislaus, CA........... 14.6 179.8 -0.9 209 718 2.9 129
Tulare, CA............... 9.4 160.9 4.0 4 591 2.2 194
Ventura, CA.............. 23.5 320.0 -1.5 253 867 -4.8 324
Yolo, CA................. 5.8 103.1 -1.2 232 812 4.9 24
Adams, CO................ 9.3 158.7 2.1 19 770 2.7 145
Arapahoe, CO............. 19.6 286.6 0.5 88 961 0.3 291
Boulder, CO.............. 13.0 164.8 2.0 23 976 0.4 289
Denver, CO............... 25.9 453.9 1.0 53 1,019 2.9 129
Douglas, CO.............. 9.6 96.2 2.7 11 906 (7) -
El Paso, CO.............. 17.7 249.1 -1.0 215 773 2.8 137
Jefferson, CO............ 18.8 215.8 0.6 78 873 5.9 10
Larimer, CO.............. 10.4 134.3 0.1 114 725 0.7 278
Weld, CO................. 6.1 84.7 1.2 41 763 10.4 2
Fairfield, CT............ 33.0 428.2 0.6 78 1,325 0.8 275
Hartford, CT............. 25.6 515.0 0.5 88 1,013 -2.1 320
New Haven, CT............ 22.7 371.0 -0.5 182 897 2.2 194
New London, CT........... 7.0 133.5 1.7 28 879 3.3 94
New Castle, DE........... 18.3 281.5 -1.1 225 965 (7) -
Washington, DC........... 32.6 691.4 1.2 41 1,433 5.9 10
Alachua, FL.............. 6.8 120.9 (7) - 696 (7) -
Brevard, FL.............. 15.1 201.8 -3.4 305 806 4.0 54
Broward, FL.............. 66.3 742.2 -3.3 304 796 2.3 186
Collier, FL.............. 12.7 118.7 -6.8 327 783 (7) -
Duval, FL................ 27.4 462.5 -2.4 293 806 1.8 228
Escambia, FL............. 8.2 125.1 -4.1 311 674 3.1 117
Hillsborough, FL......... 38.0 611.6 -4.2 315 802 2.4 175
Lake, FL................. 7.4 80.6 -5.1 322 623 3.8 66
Lee, FL.................. 20.2 204.2 -8.8 328 730 2.4 175
Leon, FL................. 8.3 142.2 -1.6 259 715 3.3 94
Manatee, FL.............. 9.4 113.1 0.8 67 674 -1.9 319
Marion, FL............... 8.7 100.5 -6.0 324 624 3.3 94
Miami-Dade, FL........... 88.2 992.7 -2.1 282 838 3.1 117
Okaloosa, FL............. 6.2 78.8 -4.5 316 702 2.9 129
Orange, FL............... 37.4 681.8 -1.8 273 767 2.4 175
Palm Beach, FL........... 51.6 529.5 -4.6 319 836 2.8 137
Pasco, FL................ 10.3 94.9 -3.1 302 648 3.3 94
Pinellas, FL............. 31.9 423.3 -3.7 310 734 3.4 88
Polk, FL................. 12.9 197.4 -3.5 307 661 2.3 186
Sarasota, FL............. 15.5 145.0 -6.5 325 728 1.3 259
Seminole, FL............. 15.2 174.8 -3.6 308 745 1.6 242
Volusia, FL.............. 14.2 158.0 -5.5 323 636 2.7 145
Bibb, GA................. 4.6 85.5 0.5 88 646 1.3 259
Chatham, GA.............. 7.6 136.1 -2.2 290 723 4.0 54
Clayton, GA.............. 4.4 113.0 -2.1 282 764 -43.7 327
Cobb, GA................. 20.7 318.9 -0.3 160 876 1.5 248
De Kalb, GA.............. 16.8 298.8 -0.5 182 892 -0.2 303
Fulton, GA............... 39.1 741.3 -0.4 172 1,079 -0.4 305
Gwinnett, GA............. 23.5 319.1 -2.4 293 840 1.0 270
Muscogee, GA............. 4.8 96.6 -1.2 232 671 4.8 27
Richmond, GA............. 4.8 100.9 -0.5 182 711 3.9 58
Honolulu, HI............. 24.6 450.5 -1.0 215 790 4.2 43
Ada, ID.................. 15.2 212.8 -1.5 253 748 0.1 295
Champaign, IL............ 4.1 92.6 0.0 126 715 5.0 22
Cook, IL................. 139.3 2,533.4 -0.8 200 999 1.9 218
Du Page, IL.............. 35.9 601.4 -1.0 215 982 2.5 166
Kane, IL................. 12.8 212.3 -2.1 282 756 1.9 218
Lake, IL................. 21.1 343.8 -0.1 141 1,046 0.5 285
McHenry, IL.............. 8.5 106.2 0.2 110 732 1.9 218
McLean, IL............... 3.7 86.7 0.5 88 806 3.1 117
Madison, IL.............. 5.9 96.3 -0.5 182 698 5.8 12
Peoria, IL............... 4.8 106.1 0.1 114 786 2.5 166
Rock Island, IL.......... 3.5 80.6 -0.1 141 861 10.5 1
St. Clair, IL............ 5.4 97.7 1.0 53 689 4.1 49
Sangamon, IL............. 5.2 130.8 -0.6 191 842 5.4 17
Will, IL................. 13.7 199.9 1.2 41 761 2.7 145
Winnebago, IL............ 6.9 137.9 -1.0 215 711 2.6 158
Allen, IN................ 9.1 182.1 -0.6 191 706 1.6 242
Elkhart, IN.............. 5.0 119.8 -6.5 325 702 -1.7 318
Hamilton, IN............. 7.7 115.1 2.1 19 797 -0.7 310
Lake, IN................. 10.3 195.8 -0.8 200 744 4.9 24
Marion, IN............... 24.2 580.9 -0.2 153 844 2.1 203
St. Joseph, IN........... 6.1 123.7 -1.4 246 714 2.6 158
Tippecanoe, IN........... 3.3 75.7 -1.7 267 721 3.4 88
Vanderburgh, IN.......... 4.8 107.4 -0.3 160 698 2.9 129
Linn, IA................. 6.3 127.4 0.9 60 792 2.6 158
Polk, IA................. 14.8 279.5 0.8 67 822 1.4 253
Scott, IA................ 5.2 90.9 0.2 110 670 2.3 186
Johnson, KS.............. 20.4 321.5 0.8 67 884 1.3 259
Sedgwick, KS............. 12.2 264.6 1.8 25 786 1.3 259
Shawnee, KS.............. 4.9 97.9 1.7 28 715 -0.8 313
Wyandotte, KS............ 3.2 82.2 2.2 17 808 2.0 212
Boone, KY................ 3.6 75.1 1.3 37 754 -10.0 326
Fayette, KY.............. 9.4 179.2 (7) - 772 2.5 166
Jefferson, KY............ 22.9 435.0 -1.6 259 822 1.7 237
Caddo, LA................ 7.3 125.5 0.0 126 715 2.7 145
Calcasieu, LA............ 4.9 88.6 -0.1 141 721 4.9 24
East Baton Rouge, LA..... 14.1 259.7 1.8 25 790 7.8 5
Jefferson, LA............ 13.8 201.9 1.1 48 772 2.5 166
Lafayette, LA............ 8.7 136.4 0.6 78 811 4.5 31
Orleans, LA.............. 10.3 173.2 5.6 1 920 4.2 43
St. Tammany, LA.......... 7.1 75.6 -0.7 197 685 3.6 72
Cumberland, ME........... 12.2 176.9 0.6 78 756 1.9 218
Anne Arundel, MD......... 14.6 237.5 0.0 126 891 3.0 126
Baltimore, MD............ 21.7 379.7 -0.5 182 859 2.9 129
Frederick, MD............ 6.0 95.7 -0.9 209 806 2.9 129
Harford, MD.............. 5.7 84.9 -2.0 280 762 0.0 300
Howard, MD............... 8.7 151.3 0.1 114 973 1.9 218
Montgomery, MD........... 33.1 462.8 -0.8 200 1,110 1.6 242
Prince Georges, MD....... 15.7 317.7 0.3 105 926 3.9 58
Baltimore City, MD....... 14.0 341.3 -1.0 215 1,004 3.0 126
Barnstable, MA........... 9.2 101.4 -1.6 259 725 2.5 166
Bristol, MA.............. 15.5 221.4 -1.4 246 773 2.4 175
Essex, MA................ 20.9 305.6 0.0 126 902 2.7 145
Hampden, MA.............. 14.3 202.2 -0.5 182 766 2.4 175
Middlesex, MA............ 47.5 834.5 0.8 67 1,240 5.2 19
Norfolk, MA.............. 23.3 329.6 -0.5 182 1,013 2.7 145
Plymouth, MA............. 13.8 180.7 -1.0 215 829 3.1 117
Suffolk, MA.............. 21.7 596.6 0.9 60 1,309 2.2 194
Worcester, MA............ 20.6 324.9 -1.2 232 869 3.3 94
Genesee, MI.............. 7.8 138.3 -4.7 320 728 0.1 295
Ingham, MI............... 6.8 162.6 -1.0 215 822 3.5 79
Kalamazoo, MI............ 5.5 115.6 -2.1 282 776 4.4 35
Kent, MI................. 14.2 335.2 -2.1 282 767 2.4 175
Macomb, MI............... 17.6 308.3 -4.5 316 881 2.4 175
Oakland, MI.............. 39.0 682.7 -3.6 308 991 4.5 31
Ottawa, MI............... 5.7 109.7 -2.2 290 703 1.2 265
Saginaw, MI.............. 4.3 84.2 -4.8 321 693 2.2 194
Washtenaw, MI............ 8.1 187.5 -1.5 253 902 -2.3 321
Wayne, MI................ 32.0 735.3 -2.8 297 952 2.1 203
Anoka, MN................ 7.9 115.4 -1.9 277 840 1.1 268
Dakota, MN............... 10.7 177.6 -1.8 273 847 3.5 79
Hennepin, MN............. 42.8 851.5 -0.4 172 1,069 0.7 278
Olmsted, MN.............. 3.6 91.4 -0.9 209 863 3.5 79
Ramsey, MN............... 15.4 335.3 0.0 126 920 1.3 259
St. Louis, MN............ 5.9 99.4 -0.2 153 709 0.4 289
Stearns, MN.............. 4.6 82.9 0.0 126 658 3.9 58
Harrison, MS............. 4.6 87.6 0.6 78 656 0.6 281
Hinds, MS................ 6.4 127.5 0.2 110 733 2.9 129
Boone, MO................ 4.6 83.4 -0.1 141 663 3.1 117
Clay, MO................. 5.1 89.5 -3.0 301 794 -0.8 313
Greene, MO............... 8.2 155.4 -1.2 232 662 5.1 20
Jackson, MO.............. 18.7 374.0 0.7 71 863 3.9 58
St. Charles, MO.......... 8.2 125.6 -1.4 246 702 0.6 281
St. Louis, MO............ 32.8 615.1 -0.7 197 907 2.6 158
St. Louis City, MO....... 8.5 233.9 0.0 126 958 6.9 7
Yellowstone, MT.......... 5.8 78.3 0.6 78 688 1.8 228
Douglas, NE.............. 15.8 324.6 1.3 37 788 2.7 145
Lancaster, NE............ 8.0 159.2 0.4 102 670 2.6 158
Clark, NV................ 50.4 918.9 -1.2 232 796 3.0 126
Washoe, NV............... 14.6 210.7 -4.1 311 788 2.1 203
Hillsborough, NH......... 12.3 198.6 0.0 126 928 0.5 285
Rockingham, NH........... 11.0 141.4 -1.6 259 814 -3.8 322
Atlantic, NJ............. 7.2 152.1 -0.2 153 754 1.8 228
Bergen, NJ............... 35.2 455.7 -0.9 209 1,030 0.9 273
Burlington, NJ........... 11.7 205.3 -1.5 253 905 3.5 79
Camden, NJ............... 13.3 212.5 -0.4 172 875 0.0 300
Essex, NJ................ 21.8 363.4 -0.6 191 1,060 0.3 291
Gloucester, NJ........... 6.4 105.6 -0.9 209 778 2.2 194
Hudson, NJ............... 14.3 237.5 -0.3 160 1,133 2.8 137
Mercer, NJ............... 11.5 233.0 0.7 71 1,092 3.4 88
Middlesex, NJ............ 22.5 405.0 -2.0 280 1,049 3.3 94
Monmouth, NJ............. 21.2 269.2 -0.1 141 891 1.8 228
Morris, NJ............... 18.5 291.5 -2.1 282 1,182 -0.7 310
Ocean, NJ................ 12.7 160.2 -0.1 141 712 1.9 218
Passaic, NJ.............. 12.9 180.6 -0.3 160 888 1.4 253
Somerset, NJ............. 10.5 177.4 -0.8 200 1,277 -0.4 305
Union, NJ................ 15.3 237.9 -0.6 191 1,074 2.1 203
Bernalillo, NM........... 17.5 334.5 -0.5 182 748 3.3 94
Albany, NY............... 10.0 230.1 0.1 114 881 2.7 145
Bronx, NY................ 15.9 227.4 0.9 60 820 2.6 158
Broome, NY............... 4.5 97.4 0.1 114 688 3.5 79
Dutchess, NY............. 8.4 117.8 -1.4 246 880 4.4 35
Erie, NY................. 23.6 466.1 1.2 41 747 3.2 109
Kings, NY................ 45.9 482.5 1.1 48 728 2.1 203
Monroe, NY............... 18.1 386.5 -0.1 141 823 2.2 194
Nassau, NY............... 52.5 615.4 -0.3 160 962 0.6 281
New York, NY............. 118.6 2,392.5 1.0 53 1,569 2.0 212
Oneida, NY............... 5.3 113.1 0.1 114 678 2.4 175
Onondaga, NY............. 12.8 256.1 -0.3 160 786 3.3 94
Orange, NY............... 10.0 134.0 0.0 126 752 3.6 72
Queens, NY............... 43.3 508.3 1.4 34 840 -4.3 323
Richmond, NY............. 8.8 94.5 -0.2 153 755 3.6 72
Rockland, NY............. 9.8 118.9 0.1 114 932 4.1 49
Saratoga, NY............. 5.4 79.4 0.1 114 719 1.8 228
Suffolk, NY.............. 50.6 642.6 -0.2 153 922 3.6 72
Westchester, NY.......... 36.5 430.8 -0.3 160 1,140 2.2 194
Buncombe, NC............. 8.1 116.5 -0.1 141 658 2.5 166
Catawba, NC.............. 4.7 85.8 -3.4 305 663 2.8 137
Cumberland, NC........... 6.3 120.2 0.5 88 679 6.1 8
Durham, NC............... 7.0 186.5 1.3 37 1,085 2.4 175
Forsyth, NC.............. 9.3 187.8 0.9 60 761 -1.4 317
Guilford, NC............. 14.9 279.2 -0.7 197 746 1.5 248
Mecklenburg, NC.......... 33.1 569.1 1.1 48 945 1.4 253
New Hanover, NC.......... 7.5 103.8 -1.7 267 686 3.3 94
Wake, NC................. 28.7 453.6 1.4 34 839 2.7 145
Cass, ND................. 5.9 101.2 3.5 7 699 4.2 43
Butler, OH............... 7.4 147.7 0.5 88 745 3.6 72
Cuyahoga, OH............. 38.0 743.4 -1.6 259 871 3.3 94
Franklin, OH............. 30.1 684.1 -0.9 209 817 1.4 253
Hamilton, OH............. 24.2 522.6 -0.2 153 893 3.2 109
Lake, OH................. 6.8 102.7 -1.1 225 697 0.1 295
Lorain, OH............... 6.3 101.1 -1.3 241 689 0.6 281
Lucas, OH................ 10.8 215.9 -2.3 292 723 0.3 291
Mahoning, OH............. 6.5 104.0 -1.7 267 609 2.4 175
Montgomery, OH........... 13.0 264.0 -2.9 300 761 0.5 285
Stark, OH................ 9.1 161.9 -1.5 253 661 3.1 117
Summit, OH............... 15.1 275.4 -0.3 160 769 1.9 218
Trumbull, OH............. 4.7 76.6 -4.1 311 697 -4.8 324
Warren, OH............... 4.2 80.1 -1.4 246 695 1.2 265
Oklahoma, OK............. 23.9 425.0 0.7 71 777 6.0 9
Tulsa, OK................ 19.4 351.2 1.1 48 766 3.2 109
Clackamas, OR............ 12.7 152.1 0.1 114 780 2.0 212
Jackson, OR.............. 6.6 83.0 -2.8 297 648 2.5 166
Lane, OR................. 10.8 151.3 -1.3 241 668 3.2 109
Marion, OR............... 9.4 144.1 -0.3 160 677 3.7 70
Multnomah, OR............ 27.8 452.3 0.7 71 862 2.4 175
Washington, OR........... 16.0 251.3 -0.8 200 942 3.5 79
Allegheny, PA............ 35.4 697.6 0.0 126 898 3.1 117
Berks, PA................ 9.3 170.3 -0.4 172 771 3.6 72
Bucks, PA................ 20.4 268.6 -0.6 191 845 4.4 35
Butler, PA............... 4.8 81.7 0.9 60 735 5.0 22
Chester, PA.............. 15.2 247.4 1.2 41 1,108 2.8 137
Cumberland, PA........... 6.1 127.0 -0.5 182 787 1.4 253
Dauphin, PA.............. 7.4 186.6 -0.1 141 815 1.0 270
Delaware, PA............. 13.8 211.7 0.3 105 890 3.2 109
Erie, PA................. 7.4 129.9 -0.8 200 677 4.2 43
Lackawanna, PA........... 5.9 101.7 -1.1 225 652 3.5 79
Lancaster, PA............ 12.4 233.4 0.5 88 713 2.3 186
Lehigh, PA............... 8.8 181.9 0.3 105 844 3.7 70
Luzerne, PA.............. 7.9 143.9 -1.1 225 654 2.0 212
Montgomery, PA........... 27.7 496.5 0.6 78 1,027 1.3 259
Northampton, PA.......... 6.5 100.7 -0.4 172 741 2.3 186
Philadelphia, PA......... 30.8 634.2 0.1 114 991 4.4 35
Washington, PA........... 5.3 82.0 1.2 41 737 2.8 137
Westmoreland, PA......... 9.5 139.0 -0.3 160 693 5.8 12
York, PA................. 9.2 178.5 0.6 78 743 1.8 228
Kent, RI................. 5.7 80.4 -4.1 311 735 1.7 237
Providence, RI........... 18.1 283.0 -2.6 295 825 3.3 94
Charleston, SC........... 12.4 216.1 0.7 71 716 2.7 145
Greenville, SC........... 12.6 242.6 0.5 88 737 2.1 203
Horry, SC................ 8.4 125.5 -1.8 273 539 -0.9 315
Lexington, SC............ 5.7 98.9 0.7 71 634 1.9 218
Richland, SC............. 9.4 215.4 -1.1 225 735 2.9 129
Spartanburg, SC.......... 6.1 120.4 -1.2 232 736 4.0 54
Minnehaha, SD............ 6.4 118.2 1.9 24 682 0.7 278
Davidson, TN............. 18.7 437.0 -1.4 246 850 3.5 79
Hamilton, TN............. 8.7 195.3 0.5 88 720 0.8 275
Knox, TN................. 11.2 229.8 0.7 71 711 0.1 295
Rutherford, TN........... 4.4 99.2 0.0 126 745 -0.7 310
Shelby, TN............... 20.1 501.0 -1.7 267 850 1.8 228
Williamson, TN........... 6.0 89.6 1.1 48 891 -0.4 305
Bell, TX................. 4.6 103.4 3.6 6 659 4.1 49
Bexar, TX................ 32.4 735.1 2.1 19 735 -0.5 308
Brazoria, TX............. 4.6 86.6 0.0 126 829 3.6 72
Brazos, TX............... 3.8 81.9 3.0 8 634 4.6 29
Cameron, TX.............. 6.5 124.9 1.3 37 535 5.1 20
Collin, TX............... 17.0 296.9 (7) - 977 (7) -
Dallas, TX............... 68.1 1,498.9 1.2 41 1,010 -0.2 303
Denton, TX............... 10.5 170.7 3.0 8 720 1.4 253
El Paso, TX.............. 13.4 269.8 2.1 19 603 1.5 248
Fort Bend, TX............ 8.3 130.2 4.2 3 894 3.1 117
Galveston, TX............ 5.2 97.6 (7) - 798 (7) -
Harris, TX............... 97.0 2,073.4 2.8 10 1,070 3.9 58
Hidalgo, TX.............. 10.6 218.0 2.2 17 538 3.9 58
Jefferson, TX............ 5.9 126.0 0.5 88 821 5.7 14
Lubbock, TX.............. 6.8 124.0 2.3 16 639 3.4 88
McLennan, TX............. 4.9 103.9 (7) - 666 4.6 29
Montgomery, TX........... 8.2 126.0 3.8 5 794 7.3 6
Nueces, TX............... 8.1 156.2 2.7 11 723 3.1 117
Potter, TX............... 3.8 76.8 2.6 13 744 (7) -
Smith, TX................ 5.3 94.9 2.5 14 724 3.9 58
Tarrant, TX.............. 37.3 774.5 1.8 25 841 -1.2 316
Travis, TX............... 28.7 582.0 1.6 31 925 2.1 203
Webb, TX................. 4.8 88.9 0.5 88 562 1.8 228
Williamson, TX........... 7.1 123.7 4.3 2 801 1.9 218
Davis, UT................ 7.2 105.7 -1.0 215 688 2.7 145
Salt Lake, UT............ 38.3 592.0 0.6 78 779 0.1 295
Utah, UT................. 13.0 176.2 -1.3 241 696 9.4 3
Weber, UT................ 5.7 95.3 -0.4 172 656 5.6 15
Chittenden, VT........... 6.0 95.0 -1.2 232 835 4.1 49
Arlington, VA............ 7.7 156.8 1.0 53 1,376 1.5 248
Chesterfield, VA......... 7.6 122.0 -1.6 259 759 3.8 66
Fairfax, VA.............. 33.7 592.4 0.1 114 1,317 3.8 66
Henrico, VA.............. 9.5 181.0 -1.1 225 870 -0.5 308
Loudoun, VA.............. 8.9 135.0 1.6 31 1,049 3.3 94
Prince William, VA....... 7.1 106.8 -0.3 160 766 4.1 49
Alexandria City, VA...... 6.1 101.2 0.6 78 1,205 3.9 58
Chesapeake City, VA...... 5.8 99.8 -1.6 259 668 2.3 186
Newport News City, VA.... 4.0 99.8 -1.3 241 757 4.4 35
Norfolk City, VA......... 5.8 145.8 0.0 126 837 2.1 203
Richmond City, VA........ 7.5 159.1 0.0 126 957 2.2 194
Virginia Beach City, VA.. 11.6 180.1 -0.4 172 662 2.2 194
Clark, WA................ 12.1 134.2 0.4 102 770 2.8 137
King, WA................. 76.6 1,201.4 1.7 28 1,056 2.8 137
Kitsap, WA............... 6.6 84.4 -0.4 172 779 3.2 109
Pierce, WA............... 20.4 276.5 -0.3 160 779 4.7 28
Snohomish, WA............ 17.8 257.2 0.2 110 875 1.7 237
Spokane, WA.............. 15.2 213.4 0.5 88 691 3.3 94
Thurston, WA............. 6.9 101.6 1.0 53 771 3.8 66
Whatcom, WA.............. 6.8 84.1 0.4 102 688 8.3 4
Yakima, WA............... 7.8 105.7 -2.8 297 580 4.5 31
Kanawha, WV.............. 6.1 108.9 -1.1 225 752 4.3 41
Brown, WI................ 6.8 151.1 -1.0 215 725 2.7 145
Dane, WI................. 14.2 308.2 0.3 105 807 4.0 54
Milwaukee, WI............ 21.4 502.8 -0.1 141 853 4.4 35
Outagamie, WI............ 5.1 106.6 0.1 114 711 2.3 186
Racine, WI............... 4.2 77.2 -1.4 246 757 1.2 265
Waukesha, WI............. 13.4 237.4 -1.6 259 831 1.7 237
Winnebago, WI............ 3.8 92.7 1.0 53 769 2.7 145
San Juan, PR............. 13.4 284.2 -2.3 (8) 571 4.2 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 334 U.S. counties comprise 71.3 percent of the total covered workers
in the U.S.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(7) Data do not meet BLS or State agency disclosure standards.
(8) This county was not included in the U.S. rankings.
Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties,
second quarter 2008(2)
Employment Average weekly
wage(3)
Establishments,
second quarter
County by NAICS supersector 2008 Percent Percent
(thousands) June change, Average change,
2008 June weekly second
(thousands) 2007-08(4) wage quarter
2007-08(4)
United States(5)............................. 9,107.3 136,631.8 -0.3 $841 2.6
Private industry........................... 8,815.2 114,859.8 -0.6 828 2.2
Natural resources and mining............. 125.6 1,994.2 1.6 903 8.0
Construction............................. 889.7 7,388.5 -5.8 902 4.6
Manufacturing............................ 360.7 13,565.7 -2.8 1,009 1.5
Trade, transportation, and utilities..... 1,925.1 26,212.9 -0.7 718 0.4
Information.............................. 145.7 3,029.2 -1.0 1,282 2.2
Financial activities..................... 868.4 8,041.1 -2.2 1,207 0.1
Professional and business services....... 1,516.8 17,924.3 -0.6 1,045 4.6
Education and health services............ 844.4 17,877.9 2.8 787 3.6
Leisure and hospitality.................. 735.4 13,987.8 0.6 351 2.6
Other services........................... 1,180.4 4,558.5 0.7 543 3.0
Government................................. 292.1 21,772.0 1.2 911 4.2
Los Angeles, CA.............................. 421.0 4,229.7 -0.2 946 2.6
Private industry........................... 417.0 3,613.1 -0.6 922 2.9
Natural resources and mining............. 0.5 11.4 -7.7 1,321 16.2
Construction............................. 13.9 148.0 -7.9 992 5.4
Manufacturing............................ 14.7 438.4 -3.4 1,025 3.5
Trade, transportation, and utilities..... 53.9 799.9 -0.7 776 0.3
Information.............................. 8.7 220.3 5.0 1,551 1.6
Financial activities..................... 24.2 237.1 -5.1 1,402 -0.8
Professional and business services....... 42.4 589.7 (6) 1,126 7.5
Education and health services............ 27.9 483.1 2.7 863 3.7
Leisure and hospitality.................. 26.8 408.9 1.0 522 3.6
Other services........................... 188.6 254.6 0.1 446 4.2
Government................................. 4.0 616.6 2.5 1,091 0.9
Cook, IL..................................... 139.3 2,533.4 -0.8 999 1.9
Private industry........................... 137.9 2,220.2 -0.9 989 1.6
Natural resources and mining............. 0.1 1.2 -10.7 911 -7.5
Construction............................. 12.3 93.9 -5.5 1,236 5.1
Manufacturing............................ 7.0 230.0 -3.3 1,000 1.9
Trade, transportation, and utilities..... 27.5 468.8 -1.4 790 0.5
Information.............................. 2.5 57.4 0.0 1,450 1.6
Financial activities..................... 15.8 210.1 -3.3 1,682 3.8
Professional and business services....... 28.7 437.8 -1.2 1,241 0.8
Education and health services............ 13.8 373.4 2.2 846 2.2
Leisure and hospitality.................. 11.6 246.0 1.3 436 3.8
Other services........................... 14.4 98.2 1.2 720 3.4
Government................................. 1.4 313.2 -0.6 1,067 3.9
New York, NY................................. 118.6 2,392.5 1.0 1,569 2.0
Private industry........................... 118.3 1,940.6 1.2 1,691 2.1
Natural resources and mining............. 0.0 0.2 0.0 3,487 45.4
Construction............................. 2.4 37.3 4.2 1,525 6.1
Manufacturing............................ 3.0 36.0 -5.3 1,286 1.5
Trade, transportation, and utilities..... 21.7 249.2 -0.2 1,166 2.2
Information.............................. 4.4 136.1 0.6 1,997 5.2
Financial activities..................... 18.9 379.0 -0.7 3,047 -0.1
Professional and business services....... 25.0 498.4 1.6 1,832 4.3
Education and health services............ 8.7 288.1 1.5 1,027 4.1
Leisure and hospitality.................. 11.5 219.6 3.3 744 2.3
Other services........................... 17.8 89.3 1.9 951 6.6
Government................................. 0.3 451.9 0.3 1,052 1.5
Harris, TX................................... 97.0 2,073.4 2.8 1,070 3.9
Private industry........................... 96.5 1,821.8 2.7 1,089 3.8
Natural resources and mining............. 1.5 83.6 6.0 3,077 (6)
Construction............................. 6.7 160.5 4.9 1,048 7.0
Manufacturing............................ 4.7 187.4 3.1 1,299 2.4
Trade, transportation, and utilities..... 22.3 431.2 2.5 930 1.6
Information.............................. 1.4 32.5 -1.1 1,248 -1.0
Financial activities..................... 10.6 119.6 -0.8 1,303 4.6
Professional and business services....... 19.4 342.4 1.9 1,223 4.6
Education and health services............ 10.3 218.8 3.8 867 2.8
Leisure and hospitality.................. 7.5 183.7 2.6 380 0.5
Other services........................... 11.5 60.5 2.5 622 4.4
Government................................. 0.5 251.6 3.1 935 4.6
Maricopa, AZ................................. 102.2 1,741.0 -3.1 845 2.1
Private industry........................... 101.6 1,558.3 -3.4 826 1.6
Natural resources and mining............. 0.5 9.4 -3.8 761 8.4
Construction............................. 11.0 138.8 -18.8 875 4.0
Manufacturing............................ 3.6 126.9 -4.8 1,146 2.4
Trade, transportation, and utilities..... 22.7 368.7 -1.3 779 -3.0
Information.............................. 1.7 30.9 -0.2 1,013 0.2
Financial activities..................... 13.0 144.2 -4.5 1,041 -0.9
Professional and business services....... 22.7 298.7 -4.9 862 6.7
Education and health services............ 10.0 208.5 5.9 893 3.8
Leisure and hospitality.................. 7.3 180.5 -0.1 395 0.5
Other services........................... 7.3 50.9 -1.4 577 3.2
Government................................. 0.7 182.7 0.0 988 4.4
Orange, CA................................... 101.2 1,502.4 -1.7 954 0.2
Private industry........................... 99.8 1,343.7 -2.1 937 -0.2
Natural resources and mining............. 0.2 5.6 -6.9 570 -6.3
Construction............................. 7.0 91.1 -13.0 1,076 3.9
Manufacturing............................ 5.3 173.5 -3.0 1,121 -2.1
Trade, transportation, and utilities..... 17.4 273.6 -1.7 900 1.7
Information.............................. 1.3 29.8 0.1 1,358 3.1
Financial activities..................... 10.9 114.6 -10.5 1,347 -5.7
Professional and business services....... 18.9 269.3 -3.4 1,059 4.0
Education and health services............ 9.9 147.4 4.6 861 4.0
Leisure and hospitality.................. 7.1 180.9 2.8 415 1.2
Other services........................... 16.5 50.3 3.2 550 -0.4
Government................................. 1.4 158.7 1.4 1,099 3.5
Dallas, TX................................... 68.1 1,498.9 1.2 1,010 -0.2
Private industry........................... 67.6 1,332.6 1.0 1,016 -0.7
Natural resources and mining............. 0.6 8.3 16.6 3,143 8.6
Construction............................. 4.4 86.0 2.7 924 -1.2
Manufacturing............................ 3.1 134.1 -4.0 1,149 -3.4
Trade, transportation, and utilities..... 15.2 304.7 0.3 943 -2.7
Information.............................. 1.7 49.1 -0.9 1,394 2.4
Financial activities..................... 8.8 145.7 1.1 1,318 -0.9
Professional and business services....... 14.8 282.4 2.7 1,121 0.0
Education and health services............ 6.6 148.3 2.8 963 -1.1
Leisure and hospitality.................. 5.3 132.8 1.2 463 5.9
Other services........................... 6.5 40.1 -0.9 627 4.0
Government................................. 0.5 166.3 2.4 962 4.5
San Diego, CA................................ 98.3 1,336.7 -0.4 926 4.2
Private industry........................... 97.0 1,107.0 -0.8 898 3.6
Natural resources and mining............. 0.8 11.6 0.6 556 2.2
Construction............................. 7.0 78.2 -13.0 971 5.1
Manufacturing............................ 3.2 103.0 0.2 1,207 2.0
Trade, transportation, and utilities..... 14.2 215.3 -2.4 737 0.8
Information.............................. 1.3 38.8 2.9 2,311 22.9
Financial activities..................... 9.6 76.5 -5.9 1,085 -2.5
Professional and business services....... 16.1 217.0 -0.8 1,112 3.2
Education and health services............ 8.1 134.1 3.6 847 5.1
Leisure and hospitality.................. 6.8 166.7 1.1 405 4.4
Other services........................... 25.1 58.7 1.9 474 -0.4
Government................................. 1.3 229.7 1.6 1,059 6.4
King, WA..................................... 76.6 1,201.4 1.7 1,056 2.8
Private industry........................... 76.1 1,043.7 1.7 1,059 2.5
Natural resources and mining............. 0.4 3.1 -3.9 1,320 8.2
Construction............................. 6.8 72.1 -0.9 1,071 6.9
Manufacturing............................ 2.4 112.2 0.2 1,330 -4.0
Trade, transportation, and utilities..... 15.0 220.7 0.7 912 1.0
Information.............................. 1.8 79.4 4.8 1,903 3.9
Financial activities..................... 7.0 75.2 -1.2 1,291 1.3
Professional and business services....... 13.6 193.4 2.8 1,237 5.1
Education and health services............ 6.5 126.1 4.6 849 4.7
Leisure and hospitality.................. 6.1 115.1 1.4 434 1.6
Other services........................... 16.6 46.3 2.0 618 8.2
Government................................. 0.5 157.7 2.0 1,034 4.3
Miami-Dade, FL............................... 88.2 992.7 -2.1 838 3.1
Private industry........................... 87.9 859.4 -2.4 804 2.2
Natural resources and mining............. 0.5 8.3 -10.8 479 -4.0
Construction............................. 6.6 47.3 -16.4 838 1.0
Manufacturing............................ 2.6 44.5 -8.5 738 1.8
Trade, transportation, and utilities..... 23.4 251.9 -1.4 757 1.9
Information.............................. 1.5 19.9 -4.0 1,381 17.4
Financial activities..................... 10.5 69.7 -4.1 1,149 0.0
Professional and business services....... 18.0 132.9 -3.9 988 3.9
Education and health services............ 9.3 141.8 3.5 811 1.6
Leisure and hospitality.................. 5.9 103.2 -0.8 475 3.3
Other services........................... 7.6 36.4 0.0 531 0.8
Government................................. 0.4 133.3 -0.5 1,039 6.7
(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, second quarter 2008(2)
Employment Average weekly
wage(4)
Establishments,
second quarter
County(3) 2008 Percent Percent
(thousands) June change, Average change,
2008 June weekly second
(thousands) 2007-08(5) wage quarter
2007-08(5)
United States(6)......... 9,107.3 136,631.8 -0.3 $841 2.6
Jefferson, AL............ 19.0 362.3 -0.8 840 1.9
Anchorage Borough, AK.... 8.2 151.1 1.5 914 2.5
Maricopa, AZ............. 102.2 1,741.0 -3.1 845 2.1
Pulaski, AR.............. 14.9 251.4 -0.1 765 3.2
Los Angeles, CA.......... 421.0 4,229.7 -0.2 946 2.6
Denver, CO............... 25.9 453.9 1.0 1,019 2.9
Hartford, CT............. 25.6 515.0 0.5 1,013 -2.1
New Castle, DE........... 18.3 281.5 -1.1 965 (7)
Washington, DC........... 32.6 691.4 1.2 1,433 5.9
Miami-Dade, FL........... 88.2 992.7 -2.1 838 3.1
Fulton, GA............... 39.1 741.3 -0.4 1,079 -0.4
Honolulu, HI............. 24.6 450.5 -1.0 790 4.2
Ada, ID.................. 15.2 212.8 -1.5 748 0.1
Cook, IL................. 139.3 2,533.4 -0.8 999 1.9
Marion, IN............... 24.2 580.9 -0.2 844 2.1
Polk, IA................. 14.8 279.5 0.8 822 1.4
Johnson, KS.............. 20.4 321.5 0.8 884 1.3
Jefferson, KY............ 22.9 435.0 -1.6 822 1.7
East Baton Rouge, LA..... 14.1 259.7 1.8 790 7.8
Cumberland, ME........... 12.2 176.9 0.6 756 1.9
Montgomery, MD........... 33.1 462.8 -0.8 1,110 1.6
Middlesex, MA............ 47.5 834.5 0.8 1,240 5.2
Wayne, MI................ 32.0 735.3 -2.8 952 2.1
Hennepin, MN............. 42.8 851.5 -0.4 1,069 0.7
Hinds, MS................ 6.4 127.5 0.2 733 2.9
St. Louis, MO............ 32.8 615.1 -0.7 907 2.6
Yellowstone, MT.......... 5.8 78.3 0.6 688 1.8
Douglas, NE.............. 15.8 324.6 1.3 788 2.7
Clark, NV................ 50.4 918.9 -1.2 796 3.0
Hillsborough, NH......... 12.3 198.6 0.0 928 0.5
Bergen, NJ............... 35.2 455.7 -0.9 1,030 0.9
Bernalillo, NM........... 17.5 334.5 -0.5 748 3.3
New York, NY............. 118.6 2,392.5 1.0 1,569 2.0
Mecklenburg, NC.......... 33.1 569.1 1.1 945 1.4
Cass, ND................. 5.9 101.2 3.5 699 4.2
Cuyahoga, OH............. 38.0 743.4 -1.6 871 3.3
Oklahoma, OK............. 23.9 425.0 0.7 777 6.0
Multnomah, OR............ 27.8 452.3 0.7 862 2.4
Allegheny, PA............ 35.4 697.6 0.0 898 3.1
Providence, RI........... 18.1 283.0 -2.6 825 3.3
Greenville, SC........... 12.6 242.6 0.5 737 2.1
Minnehaha, SD............ 6.4 118.2 1.9 682 0.7
Shelby, TN............... 20.1 501.0 -1.7 850 1.8
Harris, TX............... 97.0 2,073.4 2.8 1,070 3.9
Salt Lake, UT............ 38.3 592.0 0.6 779 0.1
Chittenden, VT........... 6.0 95.0 -1.2 835 4.1
Fairfax, VA.............. 33.7 592.4 0.1 1,317 3.8
King, WA................. 76.6 1,201.4 1.7 1,056 2.8
Kanawha, WV.............. 6.1 108.9 -1.1 752 4.3
Milwaukee, WI............ 21.4 502.8 -0.1 853 4.4
Laramie, WY.............. 3.2 44.6 2.0 706 3.1
San Juan, PR............. 13.4 284.2 -2.3 571 4.2
St. Thomas, VI........... 1.8 23.8 1.5 661 3.1
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted
for noneconomic county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin
Islands.
(7) Data do not meet BLS or State agency disclosure standards.
Table 4. Covered(1) establishments, employment, and wages by state,
second quarter 2008(2)
Employment Average weekly
wage(3)
Establishments,
second quarter
State 2008 Percent Percent
(thousands) June change, Average change,
2008 June weekly second
(thousands) 2007-08 wage quarter
2007-08
United States(4)......... 9,107.3 136,631.8 -0.3 $841 2.6
Alabama.................. 121.7 1,955.4 -0.5 720 3.3
Alaska................... 21.3 330.6 1.4 860 3.1
Arizona.................. 163.2 2,543.9 -2.6 806 2.4
Arkansas................. 85.6 1,183.5 -0.2 661 3.4
California............... 1,322.4 15,760.3 -0.5 955 2.2
Colorado................. 179.3 2,346.3 0.8 858 3.1
Connecticut.............. 113.4 1,722.3 0.5 1,036 0.3
Delaware................. 29.1 427.3 -0.9 862 -0.8
District of Columbia..... 32.6 691.4 1.2 1,433 5.9
Florida.................. 627.5 7,620.1 -3.4 762 2.6
Georgia.................. 276.6 4,059.7 -0.6 787 -0.6
Hawaii................... 39.1 623.9 -1.3 764 3.9
Idaho.................... 57.5 671.9 -0.9 636 1.6
Illinois................. 367.1 5,930.0 -0.4 893 2.3
Indiana.................. 160.4 2,906.5 -0.9 715 1.9
Iowa..................... 93.9 1,521.2 0.1 683 2.9
Kansas................... 86.6 1,389.1 1.2 720 2.4
Kentucky................. 113.5 1,818.9 -0.5 718 2.6
Louisiana................ 122.1 1,900.3 1.2 750 5.5
Maine.................... 50.8 620.3 0.1 676 2.7
Maryland................. 165.6 2,577.7 -0.3 920 2.8
Massachusetts............ 213.4 3,310.4 0.1 1,044 3.6
Michigan................. 258.4 4,163.3 -2.2 825 2.4
Minnesota................ 173.6 2,733.9 -0.5 849 1.8
Mississippi.............. 71.0 1,139.1 0.1 635 4.4
Missouri................. 175.2 2,761.6 0.0 752 3.4
Montana.................. 43.1 450.3 0.1 629 2.9
Nebraska................. 59.5 936.1 0.5 676 3.4
Nevada................... 76.9 1,271.8 -1.9 797 2.7
New Hampshire............ 49.3 641.9 -0.4 835 1.5
New Jersey............... 278.7 4,054.4 -0.4 1,004 1.6
New Mexico............... 54.4 837.2 0.6 715 4.2
New York................. 583.5 8,758.2 0.6 1,040 2.3
North Carolina........... 258.9 4,083.6 -0.1 735 2.4
North Dakota............. 25.6 356.4 2.5 654 5.8
Ohio..................... 294.6 5,315.0 -1.3 757 2.3
Oklahoma................. 101.0 1,556.0 1.0 701 5.3
Oregon................... 131.3 1,747.4 -0.8 764 3.0
Pennsylvania............. 343.2 5,743.3 0.1 827 3.1
Rhode Island............. 35.9 481.6 -2.2 796 2.8
South Carolina........... 118.3 1,907.5 -0.6 681 2.4
South Dakota............. 30.5 409.0 1.2 606 2.9
Tennessee................ 143.2 2,752.7 -0.4 745 1.9
Texas.................... 561.4 10,510.3 2.2 849 2.5
Utah..................... 86.9 1,234.3 0.1 716 2.6
Vermont.................. 25.0 305.6 -0.9 718 3.0
Virginia................. 231.1 3,720.4 -0.3 885 3.0
Washington............... 219.3 3,000.9 0.3 862 3.4
West Virginia............ 48.9 715.3 0.0 695 5.1
Wisconsin................ 160.9 2,836.8 -0.5 730 3.1
Wyoming.................. 25.0 296.7 2.7 780 5.4
Puerto Rico.............. 56.9 997.8 -2.0 475 3.5
Virgin Islands........... 3.5 45.9 -2.2 703 -0.6
(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.
United States Department of Labor
