Technical information: (202) 691-6567 USDL 08-0455
http://www.bls.gov/cew/
For release: 10:00 A.M. EDT
Media contact: 691-5902 Wednesday, April 9, 2008
COUNTY EMPLOYMENT AND WAGES: THIRD QUARTER 2007
In September 2007, Orleans County, La., had the largest over-the-
year percentage increase in employment among the largest counties in
the U.S., according to preliminary data released today by the Bureau
of Labor Statistics of the U.S. Department of Labor. Orleans County,
which includes the city of New Orleans, experienced an over-the-year
employment gain of 8.6 percent, compared with national job growth of
0.9 percent. Clayton County, Ga., had the largest over-the-year gain
in average weekly wages in the third quarter of 2007, with an
increase of 23.9 percent due to increases in wage disbursements in
the trade, transportation, and utilities supersector during the
quarter. The U.S. average weekly wage rose by 4.3 percent over the
same time span.
Of the 328 largest counties in the United States, as measured by
2006 annual average employment, 130 had over-the-year percentage
growth in employment above the national average (0.9 percent) in
September 2007; 179 large counties experienced changes below the
national average. The percent change in average weekly wages was
higher than the national average (4.3 percent) in 101 of the largest
U.S. counties, but was below the national average in 207 counties.
Table A. Top 10 large counties ranked by September 2007 employment, September 2006-07 employment growth,
and September 2006-07 percent growth in employment
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Employment in large counties
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September 2007 employment | Growth in employment, | Percent growth in employment,
(thousands) | September 2006-07 | September 2006-07
| (thousands) |
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| |
United States 136,246.9| United States 1,216.7| United States 0.9
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| |
Los Angeles, Calif. 4,191.6| Harris, Texas 74.7| Orleans, La. 8.6
Cook, Ill. 2,541.5| New York, N.Y. 46.8| Fort Bend, Texas 7.1
New York, N.Y. 2,350.3| Dallas, Texas 32.7| Williamson, Tenn. 5.8
Harris, Texas 2,028.0| King, Wash. 26.6| Wake, N.C. 5.2
Maricopa, Ariz. 1,825.1| Wake, N.C. 22.3| Utah, Utah 5.0
Orange, Calif. 1,503.8| Mecklenburg, N.C. 21.8| Hidalgo, Texas 4.5
Dallas, Texas 1,487.3| Tarrant, Texas 19.8| Snohomish, Wash. 4.4
San Diego, Calif. 1,325.9| Salt Lake, Utah 19.5| Mecklenburg, N.C. 4.0
King, Wash. 1,182.8| Bexar, Texas 18.1| Charleston, S.C. 3.8
Miami-Dade, Fla. 1,012.4| San Francisco, Calif. 18.0| Harris, Texas 3.8
| | Arlington, Va. 3.8
| |
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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 number of employer reports surpassed the 9.0 million mark
this quarter; the number of employer reports crossed the 8.0 million
mark in third quarter 2001. The employer reports in third quarter
2007 cover 136.2 million full- and part-time workers. The attached
tables contain data for the nation and for the 328 U.S. counties with
annual average employment levels of 75,000 or more in 2006. September
2007 employment and 2007 third-quarter average weekly wages for all
states are provided in table 4 of this release. Final data for all
states, metropolitan statistical areas, counties, and the nation
through the fourth quarter of 2006 are available on the BLS Web site
at http://www.bls.gov/cew/. Preliminary data for first and second
quarter 2007 also are available on the BLS Web site. Updated data for
first and second quarter 2007 and preliminary data for third quarter
2007 will be available later in April on the BLS Web site.
Large County Employment
In September 2007, national employment, as measured by the QCEW
program, was 136.2 million, up by 0.9 percent from September 2006.
The 328 U.S. counties with 75,000 or more employees accounted for
70.9 percent of total U.S. employment and 76.7 percent of total
wages. These 328 counties had a net job gain of 742,807 over the
year, accounting for 61.1 percent of the overall U.S. employment
increase. Employment rose in 217 of the large counties from September
2006 to September 2007. Orleans County, La., had the largest over-
the-year percentage increase in employment (8.6 percent). Fort Bend,
Texas, had the next largest increase, 7.1 percent, followed by the
counties of Williamson, Tenn. (5.8 percent), Wake, N.C. (5.2
percent), and Utah, Utah (5.0 percent). The large employment gains in
Orleans County reflected significant recovery from the substantial
job losses that occurred in 2005 and 2006, which were related to
Hurricane Katrina. (See table 1.)
Employment declined in 86 counties from September 2006 to September
2007. The largest percentage decline in employment was in Trumbull
County, Ohio (-5.7 percent). Collier, Fla., had the next largest
employment decline (-5.4 percent), followed by the counties of
Sarasota, Fla. (-4.3 percent), Manatee, Fla. (-4.2 percent), and
Atlantic, N.J. (-3.8 percent).
The largest gains in the level of employment from September 2006 to
September 2007 were recorded in the counties of Harris, Texas
(74,700), New York, N.Y. (46,800), Dallas, Texas (32,700), King,
Wash. (26,600), and Wake, N.C. (22,300). (See table A.) The largest
decline in employment levels occurred in Orange, Calif. (-19,100),
followed by the counties of Wayne, Mich. (-18,000), Oakland, Mich.
(-9,600), Pinellas, Fla. (-9,500), and Macomb, Mich. (-9,400).
Table B. Top 10 large counties ranked by third quarter 2007 average weekly wages, third quarter 2006-07
growth in average weekly wages, and third quarter 2006-07 percent growth in average weekly wages
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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
third quarter 2007 | wage, third quarter 2006-07 | weekly wage, third
| | quarter 2006-07
--------------------------------------------------------------------------------------------------------
| |
United States $818| United States $34| United States 4.3
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| |
Santa Clara, Calif. $1,585| Clayton, Ga. $177| Clayton, Ga. 23.9
New York, N.Y. 1,544| Santa Clara, Calif. 167| Muscogee, Ga. 12.1
Washington, D.C. 1,376| New York, N.Y. 123| Santa Clara, Calif. 11.8
Arlington, Va. 1,364| Fairfield, Conn. 100| Rock Island, Ill. 11.5
San Mateo, Calif. 1,322| Suffolk, Mass. 93| Davidson, Tenn. 9.1
Suffolk, Mass. 1,299| Rock Island, Ill. 87| Weld, Colo. 8.7
Fairfield, Conn. 1,298| King, Wash. 84| New York, N.Y. 8.7
San Francisco, Calif. 1,286| Muscogee, Ga. 75| Fairfield, Conn. 8.3
Fairfax, Va. 1,243| Davidson, Tenn. 72| Kitsap, Wash. 8.3
Somerset, N.J. 1,210| Washington, D.C. 69| Butler, Ohio 8.1
| |
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Large County Average Weekly Wages
The national average weekly wage in the third quarter of 2007 was
$818. Average weekly wages were higher than the national average in
112 of the largest 328 U.S. counties. Santa Clara, Calif., held the
top position among the highest-paid large counties with an average
weekly wage of $1,585. New York County, N.Y., was second with an
average weekly wage of $1,544, followed by Washington, D.C. ($1,376),
Arlington, Va. ($1,364), and San Mateo, Calif. ($1,322). (See table
B.)
There were 215 counties with an average weekly wage below the
national average in the third quarter of 2007. The lowest average
weekly wage was reported in Cameron County, Texas ($518), followed by
the counties of Hidalgo, Texas ($529), Horry, S.C. ($536), Webb,
Texas ($548), and Yakima, Wash. ($568). (See table 1.)
Over the year, the national average weekly wage rose by 4.3
percent. Among the largest counties, Clayton County, Ga., led the
nation in growth in average weekly wages, with an increase of 23.9
percent from the third quarter of 2006. Muscogee, Ga., was second
with growth of 12.1 percent, followed by the counties of Santa Clara,
Calif. (11.8 percent), Rock Island, Ill. (11.5 percent), and
Davidson, Tenn. (9.1 percent).
Ten large counties experienced over-the-year declines in average
weekly wages. Among the five largest decreases in wages, Trumbull,
Ohio, had the greatest decline (-10.6 percent), followed by the
counties of Vanderburgh, Ind. (-6.1 percent), Genesee, Mich. (-4.0
percent), Saginaw, Mich. (-3.1 percent), and Montgomery, Ohio (-3.0
percent).
Ten Largest U.S. Counties
Seven of the 10 largest counties (based on 2006 annual average
employment levels) experienced over-the-year percent increases in
employment in September 2007. Harris, Texas, experienced the largest
percent gain in employment among the 10 largest counties with a 3.8
percent increase. Within Harris County, the largest gains in
employment were in construction (5.5 percent) and education and
health services (5.4 percent). King, Wash., had the next largest
increase in employment, 2.3 percent, followed by Dallas, Texas (2.2
percent). September employment levels remained stable over the year
in both San Diego, Calif., and Cook, Ill. (0.0 percent each). Orange,
Calif., experienced a 1.3 percent decrease in employment over the
year. Within Orange County, five industry groups experienced
employment declines, with financial activities experiencing the
largest decline, -9.8 percent. (See table 2.)
Each of the 10 largest U.S. counties saw an over-the-year increase
in average weekly wages. New York, N.Y., had the fastest growth in
wages among the 10 largest counties, with a gain of 8.7 percent.
Within New York County, average weekly wages increased the most in
the financial activities industry (16.3 percent), followed by the
natural resources and mining industry (11.8 percent). Because natural
resources and mining is a small industry in New York County, its
over-the-year average weekly wage growth had little impact on the
county’s overall average weekly wage growth. King, Wash., was second
in wage growth with a gain of 8.0 percent, followed by Harris, Texas
(6.7 percent). The smallest wage gain among the 10 largest counties
occurred in Orange, Calif. (2.6 percent), followed by Cook, Ill. (3.3
percent), and Los Angeles, Calif. (3.4 percent).
Largest County by State
Table 3 shows September 2007 employment and the 2007 third quarter
average weekly wage in the largest county in each state, which is
based on 2006 annual average employment levels. (This table includes
two counties--Yellowstone, Mont., and Laramie, Wyo.--that had
employment levels below 75,000 in 2006.) The employment levels in the
counties in table 3 in September 2007 ranged from approximately 4.19
million in Los Angeles County, Calif., to 43,900 in Laramie County,
Wyo. The highest average weekly wage of these counties was in New
York, N.Y. ($1,544), while the lowest average weekly wage was in
Yellowstone, Mont. ($672).
For More Information
For additional information about the quarterly employment and wages
data, please read the Technical Note or visit the QCEW Web site at
http://www.bls.gov/cew/. Additional information about the QCEW data
also may be obtained by calling (202) 691-6567.
Several BLS regional offices are issuing QCEW news releases
targeted to local data users. For links to these releases, see
http://www.bls.gov/cew/cewregional.htm.
____________________________________________________
The County Employment and Wages release for fourth quarter 2007 is
scheduled to be released on Thursday, July 24, 2008.
Technical Note
These data are the product of a federal-state cooperative program, the Quarterly
Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The
data are derived from summaries of employment and total pay of workers covered by
state and federal unemployment insurance (UI) legislation and provided by State
Workforce Agencies (SWAs). The summaries are a result of the administration of state
unemployment insurance programs that require most employers to pay quarterly taxes
based on the employment and wages of workers covered by UI. QCEW data in this re-
lease are based on the 2007 North American Industry Classification System. Data for
2007 are preliminary and subject to revision.
For purposes of this release, large counties are defined as having employment lev-
els of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are provided,
but not used in calculating U.S. averages, rankings, or in the analysis in the text.
Each year, these large counties are selected on the basis of the preliminary annual
average of employment for the previous year. The 329 counties presented in this re-
lease were derived using 2006 preliminary annual averages of employment. For 2007
data, four counties have been added to the publication tables: Butte, Calif., Tippe-
canoe, Ind., Saratoga, N.Y., and Williamson, Tenn. These counties will be included
in all 2007 quarterly releases. One county, Boone, Ky., which was published in the
2006 releases, will be excluded from this and future 2007 releases because its 2006
average annual employment level was less than 75,000. The counties in table 2 are
selected and sorted each year based on the annual average employment from the
preceding year.
The preliminary QCEW data presented in this release may differ from data released
by the individual states. These potential differences result from the states' con-
tinuing receipt of UI data over time and ongoing review and editing. The individual
states determine their data release timetables.
Differences between QCEW, BED, and CES employment measures
The Bureau publishes three different establishment-based employment measures for
any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED),
and Current Employment Statistics (CES)--makes use of the quarterly UI employment
reports in producing data; however, each measure has a somewhat different universe
coverage, estimation procedure, and publication product.
Differences in coverage and estimation methods can result in somewhat different
measures of employment change over time. It is important to understand program dif-
ferences and the intended uses of the program products. (See table.) Additional in-
formation on each program can be obtained from the program Web sites shown in the
table.
Summary of Major Differences between QCEW, BED, and CES Employment Measures
---------------------------------------------------------------------------------
| QCEW | BED | CES
-----------|---------------------|----------------------|------------------------
Source |--Count of UI admini-|--Count of longitudi- |--Sample survey:
| strative records | nally-linked UI ad- | 400,000 establish-
| submitted by 9.0 | ministrative records| ments
| million establish- | submitted by 6.9 |
| ments | million private-sec-|
| | tor employers |
-----------|---------------------|----------------------|------------------------
Coverage |--UI and UCFE cover- |--UI coverage, exclud-|Nonfarm wage and sal-
| age, including all | ing government, pri-| ary jobs:
| employers subject | vate households, and|--UI coverage, exclud-
| to state and fed- | establishments with | ing agriculture, pri-
| eral UI laws | zero employment | vate households, and
| | | self-employed workers
| | |--Other employment, in-
| | | cluding railroads,
| | | religious organiza-
| | | tions, and other non-
| | | UI-covered jobs
-----------|---------------------|----------------------|------------------------
Publication|--Quarterly |--Quarterly |--Monthly
frequency | -7 months after the| -8 months after the | -Usually first Friday
| end of each quar- | end of each quarter| of following month
| ter | |
-----------|---------------------|----------------------|------------------------
Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam-
file | and publishes each | quarter to longitu- | pling frame and annu-
| new quarter of UI | dinal database and | ally realigns (bench-
| data | directly summarizes | marks) sample esti-
| | gross job gains and | mates to first quar-
| | losses | ter UI levels
-----------|---------------------|----------------------|------------------------
Principal |--Provides a quarter-|--Provides quarterly |--Provides current month-
products | ly and annual uni- | employer dynamics | ly estimates of employ-
| verse count of es- | data on establish- | ment, hours, and earn-
| tablishments, em- | ment openings, clos-| ings at the MSA, state,
| ployment, and wages| ings, expansions, | and national level by
| at the county, MSA,| and contractions at | industry
| state, and national| the national level |
| levels by detailed | by NAICS supersec- |
| industry | tors and by size of |
| | firm, and at the |
| | state private-sector|
| | total level |
| |--Future expansions |
| | will include data |
| | with greater indus- |
| | try detail and data |
| | at the county and |
| | MSA level |
-----------|---------------------|----------------------|------------------------
Principal |--Major uses include:|--Major uses include: |--Major uses include:
uses | -Detailed locality | -Business cycle | -Principal national
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -Analysis of employ-| cators
| surveys | ment expansion and |
| | contraction by size|
| | of firm |
| | |
-----------|---------------------|----------------------|------------------------
Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/
Web sites | | |
---------------------------------------------------------------------------------
Coverage
Employment and wage data for workers covered by state UI laws are compiled from
quarterly contribution reports submitted to the SWAs by employers. For federal ci-
vilian workers covered by the Unemployment Compensation for Federal Employees (UCFE)
program, employment and wage data are compiled from quarterly reports submitted by
four major federal payroll processing centers on behalf of all federal agencies,
with the exception of a few agencies which still report directly to the individual
SWA. In addition to the quarterly contribution reports, employers who operate multi-
ple establishments within a state complete a questionnaire, called the "Multiple
Worksite Report," which provides detailed information on the location and industry
of each of their establishments. The employment and wage data included in this re-
lease are derived from microdata summaries of 9.0 million employer reports of em-
ployment and wages submitted by states to the BLS. These reports are based on place
of employment rather than place of residence.
UI and UCFE coverage is broad and basically comparable from state to state. In
2006, UI and UCFE programs covered workers in 133.8 million jobs. The estimated
128.9 million workers in these jobs (after adjustment for multiple jobholders) rep-
resented 96.4 percent of civilian wage and salary employment. Covered workers re-
ceived $5.693 trillion in pay, representing 94.3 percent of the wage and salary com-
ponent of personal income and 43.1 percent of the gross domestic product.
Major exclusions from UI coverage include self-employed workers, most agricultural
workers on small farms, all members of the Armed Forces, elected officials in most
states, most employees of railroads, some domestic workers, most student workers at
schools, and employees of certain small nonprofit organizations.
State and federal UI laws change periodically. These changes may have an impact on
the employment and wages reported by employers covered under the UI program. Cover-
age changes may affect the over-the-year comparisons presented in this news release.
Concepts and methodology
Monthly employment is based on the number of workers who worked during or received
pay for the pay period including the 12th of the month. With few exceptions, all em-
ployees of covered firms are reported, including production and sales workers, cor-
poration officials, executives, supervisory personnel, and clerical workers. Work-
ers on paid vacations and part-time workers also are included.
Average weekly wage values are calculated by dividing quarterly total wages by the
average of the three monthly employment levels (all employees, as described above)
and dividing the result by 13, for the 13 weeks in the quarter. These calculations
are made using unrounded employment and wage values. The average wage values that
can be calculated using rounded data from the BLS database may differ from the aver-
ages reported. Included in the quarterly wage data are non-wage cash payments such
as bonuses, the cash value of meals and lodging when supplied, tips and other gra-
tuities, and, in some states, employer contributions to certain deferred compensa-
tion plans such as 401(k) plans and stock options. Over-the-year comparisons of av-
erage weekly wages may reflect fluctuations in average monthly employment and/or to-
tal quarterly wages between the current quarter and prior year levels.
Average weekly wages are affected by the ratio of full-time to part-time workers
as well as the number of individuals in high-paying and low-paying occupations and
the incidence of pay periods within a quarter. For instance, the average weekly wage
of the work force could increase significantly when there is a large decline in the
number of employees that had been receiving below-average wages. Wages may include
payments to workers not present in the employment counts because they did not work
during the pay period including the 12th of the month. When comparing average weekly
wage levels between industries, states, or quarters, these factors should be taken
into consideration.
Federal government pay levels are subject to periodic, sometimes large, fluctua-
tions due to a calendar effect that consists of some quarters having more pay peri-
ods than others. Most federal employees are paid on a biweekly pay schedule. As a
result of this schedule, in some quarters, federal wages contain payments for six
pay periods, while in other quarters their wages include payments for seven pay pe-
riods. Over-the-year comparisons of average weekly wages may reflect this calendar
effect. Higher growth in average weekly wages may be attributed, in part, to a com-
parison of quarterly wages for the current year, which include seven pay periods,
with year-ago wages that reflect only six pay periods. An opposite effect will occur
when wages in the current period, which contain six pay periods, are compared with
year-ago wages that include seven pay periods. The effect on over-the-year pay com-
parisons can be pronounced in federal government due to the uniform nature of fed-
eral payroll processing. This pattern may exist in private sector pay; however, be-
cause there are more pay period types (weekly, biweekly, semimonthly, monthly) it is
less pronounced. The effect is most visible in counties with large concentrations of
federal employment.
In order to ensure the highest possible quality of data, states verify with em-
ployers and update, if necessary, the industry, location, and ownership classifica-
tion of all establishments on a 4-year cycle. Changes in establishment classifica-
tion codes resulting from this process are introduced with the data reported for the
first quarter of the year. Changes resulting from improved employer reporting also
are introduced in the first quarter.
QCEW data are not designed as a time series. QCEW data are simply the sums of in-
dividual establishment records and reflect the number of establishments that exist
in a county or industry at a point in time. Establishments can move in or out of a
county or industry for a number of reasons--some reflecting economic events, others
reflecting administrative changes. For example, economic change would come from a
firm relocating into the county; administrative change would come from a company
correcting its county designation.
The over-the-year changes of employment and wages presented in this release have
been adjusted to account for most of the administrative corrections made to the un-
derlying establishment reports. This is done by modifying the prior-year levels used
to calculate the over-the-year changes. Percent changes are calculated using an ad-
justed version of the final 2006 quarterly data as the base data. The adjusted
prior-year levels used to calculate the over-the-year percent change in employment
and wages are not published. These adjusted prior-year levels do not match the unad-
justed data maintained on the BLS Web site. Over-the-year change calculations based
on data from the Web site, or from data published in prior BLS news releases, may
differ substantially from the over-the-year changes presented in this news release.
The adjusted data used to calculate the over-the-year change measures presented in
this release account for most of the administrative changes--those occurring when
employers update the industry, location, and ownership information of their estab-
lishments. The most common adjustments for administrative change are the result of
updated information about the county location of individual establishments. Included
in these adjustments are administrative changes involving the classification of es-
tablishments that were previously reported in the unknown or statewide county or un-
known industry categories. The adjusted data do not account for administrative
changes caused by multi-unit employers who start reporting for each individual es-
tablishment rather than as a single entity.
The adjusted data used to calculate the over-the-year change measures presented in
any County Employment and Wages news release are valid for comparisons between the
starting and ending points (a 12-month period) used in that particular release. Com-
parisons may not be valid for any time period other than the one featured in a re-
lease even if the changes were calculated using adjusted data.
County definitions are assigned according to Federal Information Processing Stan-
dards Publications (FIPS PUBS) as issued by the National Institute of Standards and
Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of
the Information Technology Management Reform Act of 1996 and the Computer Security
Act of 1987, Public Law 104-106. Areas shown as counties include those designated as
independent cities in some jurisdictions and, in Alaska, those designated as census
areas where counties have not been created. County data also are presented for the
New England states for comparative purposes even though townships are the more com-
mon designation used in New England (and New Jersey). The regions referred to in
this release are defined as census regions.
Additional statistics and other information
An annual bulletin, Employment and Wages, features comprehensive information by
detailed industry on establishments, employment, and wages for the nation and all
states. The 2006 edition of this bulletin will contain selected data produced by
Business Employment Dynamics (BED) on job gains and losses, as well as selected data
from the first quarter 2007 version of this news release. As with the 2005 edition,
this edition will include the data on a CD for enhanced access and usability with
the printed booklet containing selected graphic representations of QCEW data; the
data tables themselves will be published exclusively in electronic formats as PDFs.
Employment and Wages Annual Averages, 2006 will be available for sale in early 2008
from the United States Government Printing Office, Superintendent of Documents, P.O.
Box 371954, Pittsburgh, PA 15250, telephone (866) 512-1800, outside Washington, D.C.
Within Washington, D.C., the telephone number is (202) 512-1800. The fax number is
(202) 512-2104. Also, the 2006 bulletin is available in a portable document format
(PDF) on the BLS Web site at http://www.bls.gov/cew/cewbultn06.htm.
News releases on quarterly measures of gross job flows also are available upon re-
quest from the Division of Administrative Statistics and Labor Turnover (Business
Employment Dynamics), telephone (202) 691-6467; (http://www.bls.gov/bdm/); (e-mail:
BDMInfo@bls.gov).
Information in this release will be made available to sensory impaired individuals
upon request. Voice phone: (202) 691-5200; TDD message referral phone number: 1-800-
877-8339.
Table 1. Covered(1) establishments, employment, and wages in the 329 largest counties,
third quarter 2007(2)
Employment Average weekly wage(4)
Establishments,
County(3) third quarter Percent Ranking Percent Ranking
2007 September change, by Average change, by
(thousands) 2007 September percent weekly third percent
(thousands) 2006-07(5) change wage quarter change
2006-07(5)
United States(6)......... 9,012.8 136,246.9 0.9 - $818 4.3 -
Jefferson, AL............ 18.9 363.6 (7) - 837 (7) -
Madison, AL.............. 8.7 178.8 3.4 14 896 3.7 149
Mobile, AL............... 10.0 173.6 1.5 84 697 0.6 298
Montgomery, AL........... 6.7 138.6 0.0 218 692 3.3 193
Tuscaloosa, AL........... 4.4 86.8 1.8 73 701 3.7 149
Anchorage Borough, AK.... 8.1 149.2 0.2 200 894 5.5 48
Maricopa, AZ............. 99.3 1,825.1 0.2 200 822 3.8 140
Pima, AZ................. 21.0 373.9 (7) - 731 (7) -
Benton, AR............... 5.5 96.0 1.1 112 713 3.6 168
Pulaski, AR.............. 14.7 250.9 0.6 157 751 4.3 102
Washington, AR........... 5.7 93.0 -0.2 234 663 3.3 193
Alameda, CA.............. 49.8 690.8 -0.5 257 1,080 2.1 261
Butte, CA................ 7.7 77.2 -1.1 282 641 6.3 27
Contra Costa, CA......... 28.2 345.5 -1.0 278 1,003 2.8 223
Fresno, CA............... 29.3 373.9 1.1 112 643 3.7 149
Kern, CA................. 17.5 291.6 0.2 200 720 7.0 15
Los Angeles, CA.......... 401.9 4,191.6 0.4 181 925 3.4 188
Marin, CA................ 11.5 109.1 0.6 157 1,021 4.5 92
Monterey, CA............. 12.3 182.0 0.5 168 738 6.2 32
Orange, CA............... 95.3 1,503.8 -1.3 289 924 2.6 236
Placer, CA............... 10.6 138.9 -0.2 234 810 4.1 117
Riverside, CA............ 43.8 629.5 -1.4 291 702 3.7 149
Sacramento, CA........... 51.8 640.7 -0.3 239 905 3.5 177
San Bernardino, CA....... 46.6 661.5 0.0 218 724 3.3 193
San Diego, CA............ 92.7 1,325.9 0.0 218 887 4.4 98
San Francisco, CA........ 44.8 563.4 3.3 17 1,286 3.4 188
San Joaquin, CA.......... 17.4 231.2 0.7 146 715 4.1 117
San Luis Obispo, CA...... 9.2 107.0 1.4 93 689 3.0 211
San Mateo, CA............ 23.0 343.1 1.2 106 1,322 3.6 168
Santa Barbara, CA........ 13.7 189.2 2.0 57 780 (7) -
Santa Clara, CA.......... 56.9 902.3 1.7 76 1,585 11.8 3
Santa Cruz, CA........... 8.7 103.6 1.0 122 750 -1.3 310
Solano, CA............... 9.8 129.3 0.1 211 788 3.4 188
Sonoma, CA............... 18.0 196.4 0.8 137 814 3.8 140
Stanislaus, CA........... 14.3 179.2 -1.1 282 696 3.1 204
Tulare, CA............... 9.0 153.6 0.6 157 585 3.7 149
Ventura, CA.............. 21.9 317.2 -0.5 257 840 2.4 248
Yolo, CA................. 5.6 104.2 (7) - 759 0.1 305
Adams, CO................ 9.5 155.7 0.5 168 768 3.4 188
Arapahoe, CO............. 20.1 284.0 2.7 35 960 0.4 303
Boulder, CO.............. 13.0 161.1 2.3 47 989 4.0 125
Denver, CO............... 26.0 448.4 2.7 35 995 0.9 293
Douglas, CO.............. 9.6 91.7 2.9 32 832 5.9 36
El Paso, CO.............. 18.0 249.4 1.5 84 762 4.0 125
Jefferson, CO............ 19.2 212.5 1.3 100 841 3.7 149
Larimer, CO.............. 10.4 133.6 3.0 23 753 3.9 134
Weld, CO................. 6.1 84.6 3.1 20 727 8.7 6
Fairfield, CT............ 32.8 423.7 1.4 93 1,298 8.3 8
Hartford, CT............. 25.4 504.9 0.8 137 1,002 6.3 27
New Haven, CT............ 22.6 367.7 0.2 200 883 5.5 48
New London, CT........... 6.9 131.0 0.8 137 855 5.6 45
New Castle, DE........... 18.8 282.3 -0.4 248 955 0.0 306
Washington, DC........... 32.1 679.0 0.6 157 1,376 5.3 60
Alachua, FL.............. 6.6 128.8 1.7 76 689 1.6 279
Brevard, FL.............. 14.8 201.6 -2.5 303 771 4.8 79
Broward, FL.............. 65.0 747.5 -0.4 248 774 2.8 223
Collier, FL.............. 12.5 124.0 -5.4 314 748 3.5 177
Duval, FL................ 26.2 465.1 0.4 181 833 6.7 18
Escambia, FL............. 8.0 130.8 -0.1 230 649 3.5 177
Hillsborough, FL......... 36.9 639.0 0.0 218 778 2.5 240
Lake, FL................. 7.2 82.9 0.3 194 595 1.0 292
Lee, FL.................. 19.6 215.4 -3.7 310 703 2.0 267
Leon, FL................. 8.2 146.3 -0.2 234 724 4.3 102
Manatee, FL.............. 9.0 121.7 -4.2 312 653 2.7 228
Marion, FL............... 8.4 101.5 -2.3 301 594 1.7 274
Miami-Dade, FL........... 86.4 1,012.4 0.4 181 826 4.3 102
Okaloosa, FL............. 6.2 81.9 -2.8 306 675 5.0 67
Orange, FL............... 36.3 686.4 1.0 122 756 3.8 140
Palm Beach, FL........... 50.2 547.0 0.1 211 807 6.3 27
Pasco, FL................ 9.9 99.2 -0.9 275 584 -0.5 308
Pinellas, FL............. 31.5 434.4 -2.1 299 709 4.3 102
Polk, FL................. 12.6 202.2 -1.3 289 655 1.2 288
Sarasota, FL............. 15.1 151.6 -4.3 313 701 3.7 149
Seminole, FL............. 15.1 177.8 -0.6 263 708 1.7 274
Volusia, FL.............. 14.0 165.1 -1.4 291 594 2.4 248
Bibb, GA................. 4.7 83.3 0.5 168 658 2.5 240
Chatham, GA.............. 7.5 137.6 2.7 35 705 4.1 117
Clayton, GA.............. 4.4 114.9 1.3 100 919 23.9 1
Cobb, GA................. 20.5 319.3 0.8 137 874 0.5 302
De Kalb, GA.............. 16.3 296.6 -0.4 248 875 2.6 236
Fulton, GA............... 40.0 762.2 1.2 106 1,058 2.9 216
Gwinnett, GA............. 23.6 327.2 1.9 67 869 6.8 17
Muscogee, GA............. 4.8 97.1 -1.1 282 696 12.1 2
Richmond, GA............. 4.9 101.9 -0.4 248 709 4.1 117
Honolulu, HI............. 24.6 451.0 -0.4 248 786 5.8 40
Ada, ID.................. 15.2 213.9 1.1 112 749 2.9 216
Champaign, IL............ 4.1 92.4 0.7 146 705 4.8 79
Cook, IL................. 138.0 2,541.5 0.0 218 961 3.3 193
Du Page, IL.............. 35.6 600.0 0.0 218 980 5.8 40
Kane, IL................. 12.6 212.7 -0.5 257 742 2.8 223
Lake, IL................. 20.8 338.7 1.1 112 972 2.9 216
McHenry, IL.............. 8.4 104.8 1.1 112 713 2.3 254
McLean, IL............... 3.6 86.2 0.8 137 782 1.8 272
Madison, IL.............. 6.0 96.3 0.4 181 663 1.5 283
Peoria, IL............... 4.7 104.7 1.0 122 774 3.3 193
Rock Island, IL.......... 3.5 79.1 1.5 84 844 11.5 4
St. Clair, IL............ 5.4 96.8 0.7 146 673 4.8 79
Sangamon, IL............. 5.2 130.3 0.0 218 818 4.3 102
Will, IL................. 13.3 194.4 3.0 23 728 1.4 284
Winnebago, IL............ 6.9 138.3 1.6 81 712 2.3 254
Allen, IN................ 9.0 184.4 -0.5 257 692 1.6 279
Elkhart, IN.............. 4.9 126.0 -0.9 275 681 2.1 261
Hamilton, IN............. 7.5 111.5 (7) - 802 (7) -
Lake, IN................. 10.2 195.1 -0.3 239 734 4.9 71
Marion, IN............... 24.1 584.8 1.2 106 830 2.1 261
St. Joseph, IN........... 6.0 125.5 0.0 218 684 2.7 228
Tippecanoe, IN........... 3.2 77.0 0.4 181 707 1.7 274
Vanderburgh, IN.......... 4.8 107.3 -1.5 296 678 -6.1 315
Linn, IA................. 6.3 123.7 2.1 56 791 6.5 23
Polk, IA................. 14.7 274.6 2.0 57 804 2.9 216
Scott, IA................ 5.2 89.4 0.4 181 680 4.5 92
Johnson, KS.............. 20.2 319.2 2.4 44 830 2.0 267
Sedgwick, KS............. 12.1 258.5 2.4 44 737 1.2 288
Shawnee, KS.............. 4.8 95.1 1.6 81 690 2.2 259
Wyandotte, KS............ 3.2 81.8 1.8 73 779 0.9 293
Fayette, KY.............. 9.1 174.9 0.7 146 734 2.8 223
Jefferson, KY............ 22.2 437.5 1.2 106 791 2.1 261
Caddo, LA................ 7.3 126.6 1.1 112 678 1.3 287
Calcasieu, LA............ 4.8 86.0 0.4 181 696 5.0 67
East Baton Rouge, LA..... 13.9 264.4 1.9 67 742 5.4 55
Jefferson, LA............ 13.8 197.0 1.2 106 754 3.7 149
Lafayette, LA............ 8.5 135.5 3.1 20 778 5.7 44
Orleans, LA.............. 10.2 166.2 8.6 1 887 1.1 290
Cumberland, ME........... 12.3 174.7 0.9 131 738 3.8 140
Anne Arundel, MD......... 14.4 233.5 0.5 168 875 3.7 149
Baltimore, MD............ 21.7 377.0 0.6 157 836 4.0 125
Frederick, MD............ 6.0 95.6 0.7 146 796 5.6 45
Harford, MD.............. 5.7 84.3 0.3 194 811 6.7 18
Howard, MD............... 8.5 147.7 0.9 131 945 3.7 149
Montgomery, MD........... 32.7 460.9 -0.3 239 1,090 5.1 64
Prince Georges, MD....... 15.6 317.6 1.2 106 901 3.9 134
Baltimore City, MD....... 14.1 346.3 0.5 168 937 3.1 204
Barnstable, MA........... 9.2 98.0 0.3 194 690 3.4 188
Bristol, MA.............. 15.6 221.2 -0.6 263 724 4.5 92
Essex, MA................ 20.8 301.5 0.2 200 881 4.3 102
Hampden, MA.............. 14.2 200.5 -0.6 263 760 3.5 177
Middlesex, MA............ 47.5 818.3 1.4 93 1,176 5.9 36
Norfolk, MA.............. 22.2 326.0 1.1 112 960 1.6 279
Plymouth, MA............. 13.8 179.1 -0.3 239 760 2.6 236
Suffolk, MA.............. 21.8 587.0 2.0 57 1,299 7.7 13
Worcester, MA............ 20.8 322.3 0.2 200 833 5.3 60
Genesee, MI.............. 7.9 142.5 -3.2 309 736 -4.0 314
Ingham, MI............... 6.8 161.6 -0.7 271 781 -1.1 309
Kalamazoo, MI............ 5.5 115.7 -1.1 282 737 3.5 177
Kent, MI................. 14.2 340.9 -0.8 273 735 1.1 290
Macomb, MI............... 17.8 315.2 -2.9 307 877 4.8 79
Oakland, MI.............. 39.1 692.0 -1.4 291 958 3.1 204
Ottawa, MI............... 5.7 112.3 -2.6 304 711 1.9 271
Saginaw, MI.............. 4.3 86.5 -2.9 307 697 -3.1 313
Washtenaw, MI............ 8.0 191.6 -1.9 298 954 4.5 92
Wayne, MI................ 32.2 747.7 -2.4 302 930 3.1 204
Anoka, MN................ 8.2 116.7 0.6 157 769 2.9 216
Dakota, MN............... 11.1 177.2 1.9 67 772 2.1 261
Hennepin, MN............. 44.3 849.5 0.8 137 1,043 5.4 55
Olmsted, MN.............. 3.7 91.7 1.4 93 904 3.2 199
Ramsey, MN............... 16.1 337.0 0.9 131 896 5.5 48
St. Louis, MN............ 6.2 98.4 2.0 57 667 4.2 110
Stearns, MN.............. 4.7 82.8 3.0 23 657 4.0 125
Harrison, MS............. 4.5 87.4 2.0 57 643 2.7 228
Hinds, MS................ 6.4 127.8 -0.3 239 717 3.0 211
Boone, MO................ 4.6 83.3 0.7 146 633 2.4 248
Clay, MO................. 5.1 91.2 3.0 23 779 3.5 177
Greene, MO............... 8.2 158.8 3.0 23 637 3.6 168
Jackson, MO.............. 18.8 371.0 1.3 100 826 3.6 168
St. Charles, MO.......... 8.2 124.7 0.9 131 694 2.4 248
St. Louis, MO............ 33.3 611.9 0.5 168 873 6.3 27
St. Louis City, MO....... 8.5 234.2 -1.0 278 887 1.4 284
Douglas, NE.............. 15.7 318.8 1.0 122 782 6.5 23
Lancaster, NE............ 8.0 158.0 (7) - 666 2.5 240
Clark, NV................ 48.8 920.2 -0.3 239 796 5.9 36
Washoe, NV............... 14.4 220.6 -0.4 248 776 3.7 149
Hillsborough, NH......... 12.5 197.9 0.4 181 899 4.4 98
Rockingham, NH........... 11.1 140.7 0.0 218 783 2.5 240
Atlantic, NJ............. 7.1 148.5 -3.8 311 719 4.1 117
Bergen, NJ............... 34.9 454.2 0.3 194 1,009 3.9 134
Burlington, NJ........... 11.5 203.9 -0.2 234 871 3.1 204
Camden, NJ............... 13.3 210.1 -1.0 278 833 4.0 125
Essex, NJ................ 21.5 357.4 -0.9 275 1,022 3.2 199
Gloucester, NJ........... 6.3 104.2 0.1 211 746 5.1 64
Hudson, NJ............... 14.0 237.7 0.6 157 1,110 4.2 110
Mercer, NJ............... 11.3 223.9 0.7 146 1,027 5.5 48
Middlesex, NJ............ 22.1 411.0 1.1 112 996 -0.1 307
Monmouth, NJ............. 21.1 257.5 -0.7 271 874 4.9 71
Morris, NJ............... 18.3 286.1 -1.1 282 1,142 0.4 303
Ocean, NJ................ 12.6 153.6 0.2 200 679 2.0 267
Passaic, NJ.............. 12.7 176.6 -1.1 282 853 2.4 248
Somerset, NJ............. 10.3 174.1 -0.6 263 1,210 5.8 40
Union, NJ................ 15.3 234.8 (7) - 1,056 (7) -
Bernalillo, NM........... 17.6 335.2 0.5 168 732 3.1 204
Albany, NY............... 10.0 227.4 0.2 200 830 4.3 102
Bronx, NY................ 15.8 221.9 0.7 146 813 2.5 240
Broome, NY............... 4.5 95.8 1.6 81 662 2.5 240
Dutchess, NY............. 8.4 116.8 -1.4 291 841 2.9 216
Erie, NY................. 23.5 457.5 0.5 168 715 3.0 211
Kings, NY................ 45.2 469.0 1.5 84 718 4.1 117
Monroe, NY............... 18.0 379.3 -0.3 239 805 3.1 204
Nassau, NY............... 52.5 603.4 0.1 211 914 5.2 63
New York, NY............. 118.0 2,350.3 2.0 57 1,544 8.7 6
Oneida, NY............... 5.3 109.9 -0.2 234 652 4.0 125
Onondaga, NY............. 12.8 254.6 1.4 93 756 2.7 228
Orange, NY............... 10.0 131.3 0.7 146 686 1.6 279
Queens, NY............... 42.9 503.3 2.6 39 814 4.1 117
Richmond, NY............. 8.7 92.9 0.8 137 748 4.8 79
Rockland, NY............. 9.8 115.9 2.0 57 870 3.8 140
Saratoga, NY............. 5.4 76.6 0.6 157 694 4.0 125
Suffolk, NY.............. 50.3 626.9 0.9 131 891 4.7 86
Westchester, NY.......... 36.5 420.5 1.4 93 1,068 3.8 140
Buncombe, NC............. 8.0 117.6 2.9 32 648 3.7 149
Catawba, NC.............. 4.6 89.1 0.7 146 633 3.6 168
Cumberland, NC........... 6.2 118.1 1.1 112 650 7.4 14
Durham, NC............... 6.9 185.5 3.7 12 1,105 6.5 23
Forsyth, NC.............. 9.2 185.6 0.5 168 756 0.9 293
Guilford, NC............. 14.7 282.9 2.2 51 722 2.1 261
Mecklenburg, NC.......... 32.2 572.6 4.0 8 923 0.8 296
New Hanover, NC.......... 7.5 107.0 3.5 13 675 5.5 48
Wake, NC................. 28.0 453.5 5.2 4 808 3.5 177
Cass, ND................. 5.8 98.5 2.4 44 688 6.2 32
Butler, OH............... 7.3 148.7 1.8 73 751 8.1 10
Cuyahoga, OH............. 37.6 747.6 -0.8 273 832 3.6 168
Franklin, OH............. 29.5 690.2 1.3 100 831 3.2 199
Hamilton, OH............. 24.0 522.0 0.4 181 890 2.2 259
Lake, OH................. 6.7 100.9 0.2 200 669 3.7 149
Lorain, OH............... 6.3 99.6 -2.7 305 701 4.5 92
Lucas, OH................ 10.6 223.4 -1.0 278 732 1.7 274
Mahoning, OH............. 6.3 105.6 0.5 168 600 2.7 228
Montgomery, OH........... 12.8 268.7 -2.1 299 754 -3.0 312
Stark, OH................ 9.0 162.8 -0.3 239 643 1.7 274
Summit, OH............... 14.9 274.2 -0.1 230 740 3.5 177
Trumbull, OH............. 4.7 78.8 -5.7 315 690 -10.6 316
Oklahoma, OK............. 23.5 424.8 1.0 122 748 5.6 45
Tulsa, OK................ 19.4 348.2 2.3 47 743 5.4 55
Clackamas, OR............ 12.7 151.0 1.7 76 763 3.2 199
Jackson, OR.............. 6.7 86.2 0.3 194 627 4.7 86
Lane, OR................. 11.1 151.8 0.8 137 660 3.9 134
Marion, OR............... 9.4 143.9 1.3 100 661 3.3 193
Multnomah, OR............ 27.4 451.1 2.5 42 840 4.5 92
Washington, OR........... 16.1 251.8 0.4 181 967 4.7 86
Allegheny, PA............ 35.4 686.2 0.6 157 864 4.9 71
Berks, PA................ 9.1 168.6 -0.5 257 764 6.7 18
Bucks, PA................ 20.2 265.3 0.2 200 787 2.7 228
Butler, PA............... 4.8 80.3 2.2 51 806 (7) -
Chester, PA.............. 15.0 241.5 2.3 47 1,015 (7) -
Cumberland, PA........... 6.0 126.8 0.1 211 762 3.7 149
Dauphin, PA.............. 7.3 182.1 -0.4 248 804 5.0 67
Delaware, PA............. 13.6 211.1 1.1 112 844 2.6 236
Erie, PA................. 7.3 128.8 0.1 211 657 4.0 125
Lackawanna, PA........... 5.8 101.8 -0.4 248 629 2.4 248
Lancaster, PA............ 12.3 230.2 0.4 181 702 2.0 267
Lehigh, PA............... 8.6 178.5 0.0 218 837 7.0 15
Luzerne, PA.............. 7.9 142.8 0.1 211 653 4.8 79
Montgomery, PA........... 27.3 486.8 0.5 168 995 3.5 177
Northampton, PA.......... 6.5 100.5 1.0 122 717 2.3 254
Philadelphia, PA......... 30.3 630.8 -0.3 239 976 5.1 64
Washington, PA........... 5.3 79.5 0.4 181 722 0.7 297
Westmoreland, PA......... 9.5 137.7 -0.6 263 656 0.6 298
York, PA................. 9.1 178.4 1.4 93 728 4.7 86
Kent, RI................. 5.7 82.0 -0.6 263 725 4.2 110
Providence, RI........... 18.2 288.3 -1.5 296 779 -2.4 311
Charleston, SC........... 12.0 212.7 3.8 9 703 4.8 79
Greenville, SC........... 12.4 238.2 1.9 67 707 3.5 177
Horry, SC................ 8.3 119.3 1.0 122 536 3.7 149
Lexington, SC............ 5.6 96.5 2.2 51 640 4.6 91
Richland, SC............. 9.2 216.7 1.5 84 724 2.7 228
Spartanburg, SC.......... 6.0 119.9 2.0 57 710 2.3 254
Minnehaha, SD............ 6.3 115.5 2.7 35 695 4.4 98
Davidson, TN............. 18.5 449.0 (7) - 860 9.1 5
Hamilton, TN............. 8.7 194.8 -0.1 230 711 3.8 140
Knox, TN................. 11.1 229.7 1.0 122 695 3.7 149
Rutherford, TN........... 4.2 100.1 0.5 168 719 1.4 284
Shelby, TN............... 20.1 511.0 0.2 200 850 4.4 98
Williamson, TN........... 5.8 86.8 5.8 3 858 0.6 298
Bell, TX................. 4.5 98.6 3.0 23 644 4.9 71
Bexar, TX................ 31.9 721.4 2.6 39 715 3.5 177
Brazoria, TX............. 4.5 85.8 3.2 18 793 6.3 27
Brazos, TX............... 3.7 85.3 (7) - 629 (7) -
Cameron, TX.............. 6.5 122.6 0.6 157 518 5.5 48
Collin, TX............... 16.2 283.8 3.2 18 981 5.5 48
Dallas, TX............... 67.7 1,487.3 2.2 51 1,002 4.2 110
Denton, TX............... 10.2 166.1 3.0 23 716 2.9 216
El Paso, TX.............. 13.2 269.8 2.0 57 593 4.0 125
Fort Bend, TX............ 7.9 124.6 7.1 2 854 4.3 102
Galveston, TX............ 5.2 96.2 (7) - 776 (7) -
Harris, TX............... 95.1 2,028.0 3.8 9 1,015 6.7 18
Hidalgo, TX.............. 10.4 211.8 4.5 6 529 2.5 240
Jefferson, TX............ 5.8 124.5 1.9 67 787 0.6 298
Lubbock, TX.............. 6.7 122.8 1.0 122 616 3.0 211
McLennan, TX............. 4.9 105.0 1.7 76 656 3.8 140
Montgomery, TX........... 7.8 122.1 (7) - 740 3.6 168
Nueces, TX............... 8.1 151.6 1.5 84 709 6.0 34
Smith, TX................ 5.2 92.6 0.9 131 715 3.6 168
Tarrant, TX.............. 36.4 769.0 2.6 39 830 2.3 254
Travis, TX............... 28.0 572.6 3.1 20 911 2.7 228
Webb, TX................. 4.7 88.3 2.8 34 548 4.2 110
Williamson, TX........... 6.7 119.1 (7) - 781 (7) -
Davis, UT................ 7.1 104.2 2.5 42 666 4.9 71
Salt Lake, UT............ 38.6 591.0 3.4 14 771 5.8 40
Utah, UT................. 12.9 177.6 5.0 5 646 4.9 71
Weber, UT................ 5.7 95.0 3.4 14 615 3.7 149
Chittenden, VT........... 5.9 95.8 -0.4 248 812 4.2 110
Arlington, VA............ 7.5 154.5 3.8 9 1,364 3.6 168
Chesterfield, VA......... 7.5 121.3 1.3 100 748 3.7 149
Fairfax, VA.............. 32.9 584.9 0.7 146 1,243 5.3 60
Henrico, VA.............. 9.2 180.3 3.0 23 833 2.5 240
Loudoun, VA.............. 8.3 129.0 1.5 84 1,011 4.7 86
Prince William, VA....... 6.9 103.9 -0.6 263 755 6.0 34
Alexandria City, VA...... 6.1 99.8 -1.4 291 1,130 6.4 26
Chesapeake City, VA...... 5.6 100.2 0.5 168 662 3.8 140
Newport News City, VA.... 4.0 99.2 1.5 84 753 5.9 36
Norfolk City, VA......... 5.8 143.0 0.8 137 822 7.9 12
Richmond City, VA........ 7.4 158.2 (7) - 945 (7) -
Virginia Beach City, VA.. 11.6 177.8 0.6 157 650 4.2 110
Clark, WA................ 11.9 134.0 1.5 84 749 3.7 149
King, WA................. 76.3 1,182.8 2.3 47 1,129 8.0 11
Kitsap, WA............... 6.6 83.9 -0.1 230 770 8.3 8
Pierce, WA............... 20.4 278.0 2.0 57 755 5.4 55
Snohomish, WA............ 17.7 255.0 4.4 7 842 5.0 67
Spokane, WA.............. 15.1 210.6 1.9 67 681 4.9 71
Thurston, WA............. 6.8 99.8 3.0 23 782 6.7 18
Whatcom, WA.............. 6.9 82.7 2.2 51 659 3.9 134
Yakima, WA............... 7.9 108.1 -0.5 257 568 5.4 55
Kanawha, WV.............. 6.1 108.8 0.3 194 704 4.1 117
Brown, WI................ 6.7 150.4 0.0 218 719 1.8 272
Dane, WI................. 14.1 306.2 (7) - 783 (7) -
Milwaukee, WI............ 21.2 497.8 0.0 218 802 2.8 223
Outagamie, WI............ 5.0 104.8 1.7 76 712 4.9 71
Racine, WI............... 4.2 76.4 -1.1 282 738 3.2 199
Waukesha, WI............. 13.3 236.4 -0.6 263 814 3.0 211
Winnebago, WI............ 3.8 90.4 0.4 181 765 3.9 134
San Juan, PR............. 13.6 289.0 -2.7 (8) 538 3.5 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 328 U.S. counties comprise 70.9 percent of the total covered workers
in the U.S.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(7) Data do not meet BLS or State agency disclosure standards.
(8) This county was not included in the U.S. rankings.
Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties,
third quarter 2007(2)
Employment Average weekly
wage(3)
Establishments,
third quarter
County by NAICS supersector 2007 Percent Percent
(thousands) September change, Average change,
2007 September weekly third
(thousands) 2006-07(4) wage quarter
2006-07(4)
United States(5)............................. 9,012.8 136,246.9 0.9 $818 4.3
Private industry........................... 8,721.6 114,790.8 0.9 810 4.5
Natural resources and mining............. 124.7 1,931.5 1.7 820 7.8
Construction............................. 895.5 7,774.4 -1.0 876 5.7
Manufacturing............................ 361.4 13,845.4 -2.2 987 4.3
Trade, transportation, and utilities..... 1,916.9 26,299.2 1.2 707 3.2
Information.............................. 144.3 3,033.1 0.0 1,274 4.6
Financial activities..................... 871.8 8,123.2 -0.7 1,200 5.9
Professional and business services....... 1,484.6 18,017.6 1.7 998 6.4
Education and health services............ 825.8 17,506.6 2.9 775 3.6
Leisure and hospitality.................. 726.7 13,562.6 1.9 348 4.2
Other services........................... 1,162.9 4,433.8 1.2 531 4.1
Government................................. 291.2 21,456.1 1.0 859 3.2
Los Angeles, CA.............................. 401.9 4,191.6 0.4 925 3.4
Private industry........................... 397.9 3,626.2 0.1 901 3.1
Natural resources and mining............. 0.5 12.7 5.0 1,095 -8.3
Construction............................. 14.3 160.4 -0.9 945 5.4
Manufacturing............................ 15.2 444.7 (6) 961 (6)
Trade, transportation, and utilities..... 55.3 811.9 -0.1 765 2.0
Information.............................. 8.8 216.3 8.5 1,520 -0.3
Financial activities..................... 25.2 243.7 -2.6 1,483 (6)
Professional and business services....... 43.4 608.9 -0.3 1,051 6.3
Education and health services............ 28.2 480.4 1.8 851 (6)
Leisure and hospitality.................. 27.1 401.1 1.8 518 2.8
Other services........................... 179.8 246.0 0.0 439 5.8
Government................................. 4.0 565.4 2.3 1,080 (6)
Cook, IL..................................... 138.0 2,541.5 0.0 961 3.3
Private industry........................... 136.6 2,232.8 0.2 958 3.6
Natural resources and mining............. 0.1 1.3 -7.7 1,063 3.5
Construction............................. 12.1 98.2 -1.6 1,207 5.5
Manufacturing............................ 7.1 237.2 -1.9 981 3.0
Trade, transportation, and utilities..... 27.6 472.2 -0.9 776 -0.5
Information.............................. 2.5 58.4 0.6 1,402 9.1
Financial activities..................... 15.8 215.4 -1.5 1,547 7.8
Professional and business services....... 28.2 441.6 0.9 1,179 3.1
Education and health services............ 13.6 369.2 1.6 843 3.7
Leisure and hospitality.................. 11.6 240.0 2.2 430 4.6
Other services........................... 13.8 95.0 0.7 691 3.0
Government................................. 1.4 308.7 -0.9 985 2.3
New York, NY................................. 118.0 2,350.3 2.0 1,544 8.7
Private industry........................... 117.7 1,906.7 2.3 1,667 9.6
Natural resources and mining............. 0.0 0.1 -1.9 1,749 11.8
Construction............................. 2.3 35.8 6.9 1,461 5.3
Manufacturing............................ 3.1 37.5 -4.7 1,158 3.0
Trade, transportation, and utilities..... 22.1 248.2 1.7 1,124 4.3
Information.............................. 4.4 135.6 1.0 1,916 4.5
Financial activities..................... 18.7 380.0 2.0 3,047 16.3
Professional and business services....... 24.6 482.2 2.3 1,769 8.6
Education and health services............ 8.6 283.3 2.0 1,011 4.8
Leisure and hospitality.................. 11.2 208.5 3.3 728 6.1
Other services........................... 17.4 87.2 1.5 889 3.7
Government................................. 0.3 443.5 0.7 1,014 1.5
Harris, TX................................... 95.1 2,028.0 3.8 1,015 6.7
Private industry........................... 94.5 1,783.4 4.3 1,027 7.1
Natural resources and mining............. 1.5 78.4 (6) 2,580 (6)
Construction............................. 6.6 151.5 5.5 968 6.1
Manufacturing............................ 4.6 182.2 3.5 1,290 7.7
Trade, transportation, and utilities..... 21.7 424.7 3.9 901 6.0
Information.............................. 1.3 32.8 2.6 1,258 9.1
Financial activities..................... 10.5 120.7 2.0 1,256 7.3
Professional and business services....... 18.9 341.2 4.9 1,156 7.5
Education and health services............ 10.0 214.7 5.4 824 1.7
Leisure and hospitality.................. 7.3 176.2 3.2 366 2.2
Other services........................... 11.0 58.4 3.9 595 7.6
Government................................. 0.5 244.6 0.6 922 3.1
Maricopa, AZ................................. 99.3 1,825.1 0.2 822 3.8
Private industry........................... 98.6 1,605.3 -0.1 811 4.1
Natural resources and mining............. 0.5 8.5 2.9 723 6.0
Construction............................. 10.6 165.8 -7.6 834 3.9
Manufacturing............................ 3.6 132.2 -3.7 1,116 3.2
Trade, transportation, and utilities..... 21.6 374.9 2.0 777 3.5
Information.............................. 1.6 30.4 -0.7 1,030 0.4
Financial activities..................... 12.7 148.6 -2.4 1,024 0.0
Professional and business services....... 21.8 316.8 0.3 825 9.1
Education and health services............ 9.7 198.9 4.4 879 5.5
Leisure and hospitality.................. 7.2 177.6 1.4 387 5.7
Other services........................... 7.2 50.1 2.2 570 5.2
Government................................. 0.7 219.9 2.8 908 1.2
Orange, CA................................... 95.3 1,503.8 -1.3 924 2.6
Private industry........................... 93.9 1,359.9 -1.7 922 2.8
Natural resources and mining............. 0.2 5.2 5.9 623 0.2
Construction............................. 7.1 105.0 -5.5 1,025 4.1
Manufacturing............................ 5.4 175.8 (6) 1,101 (6)
Trade, transportation, and utilities..... 17.8 281.0 1.2 868 3.8
Information.............................. 1.4 30.0 -1.8 1,262 3.8
Financial activities..................... 11.4 123.7 -9.8 1,377 -0.1
Professional and business services....... 19.3 273.7 -3.1 1,003 (6)
Education and health services............ 9.9 142.7 3.2 870 3.1
Leisure and hospitality.................. 7.1 175.1 2.3 410 5.9
Other services........................... 14.4 47.7 -1.2 569 4.2
Government................................. 1.4 143.8 3.4 941 0.2
Dallas, TX................................... 67.7 1,487.3 2.2 1,002 4.2
Private industry........................... 67.2 1,323.2 2.2 1,012 4.2
Natural resources and mining............. 0.6 7.3 (6) 2,962 (6)
Construction............................. 4.4 84.6 4.3 901 3.1
Manufacturing............................ 3.1 142.2 -1.9 1,174 7.5
Trade, transportation, and utilities..... 15.0 306.9 2.0 960 6.0
Information.............................. 1.7 48.1 (6) 1,385 (6)
Financial activities..................... 8.8 144.5 1.6 1,366 6.4
Professional and business services....... 14.6 274.8 4.3 1,109 4.6
Education and health services............ 6.6 146.2 5.0 895 2.4
Leisure and hospitality.................. 5.2 127.6 1.7 434 -1.8
Other services........................... 6.5 39.3 3.0 609 3.7
Government................................. 0.5 164.1 2.7 919 2.9
San Diego, CA................................ 92.7 1,325.9 0.0 887 4.4
Private industry........................... 91.4 1,108.6 -0.2 869 4.3
Natural resources and mining............. 0.8 11.9 -1.4 556 6.7
Construction............................. 7.3 87.1 -8.2 947 6.0
Manufacturing............................ 3.2 102.3 (6) 1,175 5.8
Trade, transportation, and utilities..... 14.6 221.4 0.3 736 5.9
Information.............................. 1.3 38.0 2.1 1,707 9.8
Financial activities..................... 9.9 79.7 -4.6 1,106 5.3
Professional and business services....... 16.5 218.0 0.1 1,082 3.3
Education and health services............ 8.1 129.0 (6) 834 2.5
Leisure and hospitality.................. 6.9 164.8 2.5 408 2.5
Other services........................... 22.9 56.4 1.1 485 1.0
Government................................. 1.3 217.2 0.9 987 4.4
King, WA..................................... 76.3 1,182.8 2.3 1,129 8.0
Private industry........................... 75.7 1,032.4 2.8 1,145 8.6
Natural resources and mining............. 0.4 3.2 8.6 1,153 -6.9
Construction............................. 6.8 74.7 9.4 1,032 8.3
Manufacturing............................ 2.5 112.8 2.0 1,252 4.7
Trade, transportation, and utilities..... 14.7 219.9 1.9 891 2.8
Information.............................. 1.8 76.3 4.1 3,114 10.5
Financial activities..................... 7.0 75.5 -1.6 1,287 3.3
Professional and business services....... 13.0 190.4 3.9 1,326 19.6
Education and health services............ 6.3 120.3 2.1 840 5.3
Leisure and hospitality.................. 6.1 113.7 2.9 443 4.7
Other services........................... 17.2 45.5 1.1 572 7.5
Government................................. 0.5 150.5 -1.0 1,019 3.6
Miami-Dade, FL............................... 86.4 1,012.4 0.4 826 4.3
Private industry........................... 86.0 860.4 0.2 796 4.9
Natural resources and mining............. 0.5 8.2 -3.7 489 -0.8
Construction............................. 6.4 53.2 -1.3 825 3.9
Manufacturing............................ 2.6 46.4 -4.7 741 5.6
Trade, transportation, and utilities..... 23.4 251.7 0.5 752 6.7
Information.............................. 1.5 20.4 -0.7 1,205 6.6
Financial activities..................... 10.5 71.7 -0.1 1,155 6.0
Professional and business services....... 17.6 133.0 -3.4 974 3.4
Education and health services............ 9.0 138.0 3.8 811 6.6
Leisure and hospitality.................. 5.8 100.8 2.2 448 -0.4
Other services........................... 7.6 35.4 1.8 514 5.3
Government................................. 0.3 152.0 1.2 1,005 1.7
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs.
(2) Data are preliminary.
(3) Average weekly wages were calculated using unrounded data.
(4) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(5) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(6) Data do not meet BLS or State agency disclosure standards.
Table 3. Covered(1) establishments, employment, and wages in the largest county by
state, third quarter 2007(2)
Employment Average weekly
wage(4)
Establishments,
third quarter
County(3) 2007 Percent Percent
(thousands) September change, Average change,
2007 September weekly third
(thousands) 2006-07(5) wage quarter
2006-07(5)
United States(6)......... 9,012.8 136,246.9 0.9 $818 4.3
Jefferson, AL............ 18.9 363.6 (7) 837 (7)
Anchorage Borough, AK.... 8.1 149.2 0.2 894 5.5
Maricopa, AZ............. 99.3 1,825.1 0.2 822 3.8
Pulaski, AR.............. 14.7 250.9 0.6 751 4.3
Los Angeles, CA.......... 401.9 4,191.6 0.4 925 3.4
Denver, CO............... 26.0 448.4 2.7 995 0.9
Hartford, CT............. 25.4 504.9 0.8 1,002 6.3
New Castle, DE........... 18.8 282.3 -0.4 955 0.0
Washington, DC........... 32.1 679.0 0.6 1,376 5.3
Miami-Dade, FL........... 86.4 1,012.4 0.4 826 4.3
Fulton, GA............... 40.0 762.2 1.2 1,058 2.9
Honolulu, HI............. 24.6 451.0 -0.4 786 5.8
Ada, ID.................. 15.2 213.9 1.1 749 2.9
Cook, IL................. 138.0 2,541.5 0.0 961 3.3
Marion, IN............... 24.1 584.8 1.2 830 2.1
Polk, IA................. 14.7 274.6 2.0 804 2.9
Johnson, KS.............. 20.2 319.2 2.4 830 2.0
Jefferson, KY............ 22.2 437.5 1.2 791 2.1
East Baton Rouge, LA..... 13.9 264.4 1.9 742 5.4
Cumberland, ME........... 12.3 174.7 0.9 738 3.8
Montgomery, MD........... 32.7 460.9 -0.3 1,090 5.1
Middlesex, MA............ 47.5 818.3 1.4 1,176 5.9
Wayne, MI................ 32.2 747.7 -2.4 930 3.1
Hennepin, MN............. 44.3 849.5 0.8 1,043 5.4
Hinds, MS................ 6.4 127.8 -0.3 717 3.0
St. Louis, MO............ 33.3 611.9 0.5 873 6.3
Yellowstone, MT.......... 5.7 77.6 3.3 672 5.5
Douglas, NE.............. 15.7 318.8 1.0 782 6.5
Clark, NV................ 48.8 920.2 -0.3 796 5.9
Hillsborough, NH......... 12.5 197.9 0.4 899 4.4
Bergen, NJ............... 34.9 454.2 0.3 1,009 3.9
Bernalillo, NM........... 17.6 335.2 0.5 732 3.1
New York, NY............. 118.0 2,350.3 2.0 1,544 8.7
Mecklenburg, NC.......... 32.2 572.6 4.0 923 0.8
Cass, ND................. 5.8 98.5 2.4 688 6.2
Cuyahoga, OH............. 37.6 747.6 -0.8 832 3.6
Oklahoma, OK............. 23.5 424.8 1.0 748 5.6
Multnomah, OR............ 27.4 451.1 2.5 840 4.5
Allegheny, PA............ 35.4 686.2 0.6 864 4.9
Providence, RI........... 18.2 288.3 -1.5 779 -2.4
Greenville, SC........... 12.4 238.2 1.9 707 3.5
Minnehaha, SD............ 6.3 115.5 2.7 695 4.4
Shelby, TN............... 20.1 511.0 0.2 850 4.4
Harris, TX............... 95.1 2,028.0 3.8 1,015 6.7
Salt Lake, UT............ 38.6 591.0 3.4 771 5.8
Chittenden, VT........... 5.9 95.8 -0.4 812 4.2
Fairfax, VA.............. 32.9 584.9 0.7 1,243 5.3
King, WA................. 76.3 1,182.8 2.3 1,129 8.0
Kanawha, WV.............. 6.1 108.8 0.3 704 4.1
Milwaukee, WI............ 21.2 497.8 0.0 802 2.8
Laramie, WY.............. 3.2 43.9 3.4 691 -9.1
San Juan, PR............. 13.6 289.0 -2.7 538 3.5
St. Thomas, VI........... 1.8 23.2 1.3 636 -0.3
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted
for noneconomic county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin
Islands.
(7) Data do not meet BLS or State agency disclosure standards.
Table 4. Covered(1) establishments, employment, and wages by state,
third quarter 2007(2)
Employment Average weekly
wage(3)
Establishments,
third quarter
State 2007 Percent Percent
(thousands) September change, Average change,
2007 September weekly third
(thousands) 2006-07 wage quarter
2006-07
United States(4)......... 9,012.8 136,246.9 0.9 $818 4.3
Alabama.................. 119.9 1,959.0 1.1 707 3.7
Alaska................... 21.2 327.3 0.7 840 5.4
Arizona.................. 160.6 2,644.9 0.5 783 4.1
Arkansas................. 83.4 1,184.5 0.3 629 4.1
California............... 1,314.1 15,755.0 0.7 932 4.5
Colorado................. 180.9 2,314.3 2.4 844 3.2
Connecticut.............. 112.9 1,696.9 1.0 1,021 6.6
Delaware................. 29.1 425.2 0.1 860 1.2
District of Columbia..... 32.1 679.0 0.6 1,376 5.3
Florida.................. 606.8 7,879.9 -0.9 741 4.1
Georgia.................. 272.4 4,089.4 1.2 782 4.1
Hawaii................... 38.7 624.4 0.3 760 5.4
Idaho.................... 57.0 675.5 2.2 634 3.4
Illinois................. 361.6 5,917.6 0.6 866 4.0
Indiana.................. 159.2 2,937.4 0.5 702 2.2
Iowa..................... 93.9 1,494.5 0.9 668 4.2
Kansas................... 85.8 1,368.7 1.7 680 2.7
Kentucky................. 110.5 1,814.3 1.0 676 3.0
Louisiana................ 120.9 1,880.8 2.7 716 4.5
Maine.................... 50.4 615.3 0.7 660 3.9
Maryland................. 164.0 2,563.7 0.7 892 4.1
Massachusetts............ 211.6 3,261.0 1.0 1,002 5.5
Michigan................. 257.6 4,218.2 -1.4 808 2.4
Minnesota................ 177.6 2,713.3 0.9 822 4.6
Mississippi.............. 70.2 1,142.2 0.6 607 3.8
Missouri................. 175.7 2,746.7 0.8 719 4.2
Montana.................. 42.8 446.1 2.7 608 4.6
Nebraska................. 59.0 922.7 1.7 666 5.4
Nevada................... 75.2 1,286.4 -0.1 792 5.5
New Hampshire............ 49.5 637.2 0.3 799 3.2
New Jersey............... 275.1 3,985.2 0.1 965 3.7
New Mexico............... 53.9 830.4 0.8 682 4.1
New York................. 580.3 8,585.3 1.3 1,009 6.1
North Carolina........... 254.3 4,104.1 2.4 719 3.5
North Dakota............. 25.2 347.4 1.5 621 5.8
Ohio..................... 290.8 5,331.9 -0.2 745 2.8
Oklahoma................. 99.6 1,548.2 1.8 666 5.5
Oregon................... 131.2 1,751.7 1.2 750 4.2
Pennsylvania............. 339.7 5,673.4 0.5 802 4.4
Rhode Island............. 36.2 486.1 -1.0 759 -0.1
South Carolina........... 116.6 1,904.7 1.7 664 3.6
South Dakota............. 30.3 397.5 2.0 598 4.7
Tennessee................ 141.3 2,774.4 0.5 728 4.3
Texas.................... 551.3 10,304.9 2.9 825 5.0
Utah..................... 87.1 1,231.6 3.6 696 5.5
Vermont.................. 25.0 305.2 -0.2 699 4.0
Virginia................. 229.3 3,686.6 1.0 857 5.0
Washington............... 218.7 2,976.5 2.1 878 6.7
West Virginia............ 48.9 713.8 0.3 623 4.0
Wisconsin................ 159.0 2,802.3 -0.1 705 2.6
Wyoming.................. 24.6 284.3 3.6 734 4.1
Puerto Rico.............. 57.1 1,008.0 -1.1 453 2.5
Virgin Islands........... 3.5 45.0 0.7 682 -0.3
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs.
(2) Data are preliminary.
(3) Average weekly wages were calculated using unrounded data.
(4) Totals for the United States do not include data for Puerto Rico or the
Virgin Islands.
United States Department of Labor
