Technical information:(202) 691-6567 USDL 08-1014
http://www.bls.gov/cew/
For release: 10:00 A.M. EDT
Media contact: 691-5902 Thursday, July 24, 2008
COUNTY EMPLOYMENT AND WAGES: FOURTH QUARTER 2007
In December 2007, Fort Bend County, Texas, 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. Fort Bend
County, which contains a portion of southwest Houston, experienced an
over-the-year employment gain of 7.4 percent, compared with national
job growth of 0.8 percent. Pulaski County, Ark., which includes
Little Rock, had the largest over-the-year gain in average weekly
wages in the fourth quarter of 2007, with an increase of 26.2 percent
due to gains in the information supersector. The U.S. average weekly
wage rose by 4.2 percent over the same time span.
Of the 328 largest counties in the United States, as measured by
2006 annual average employment, 126 had over-the-year percentage
growth in employment above the national average (0.8 percent) in
December 2007; 182 large counties experienced changes below the
national average. The percent change in average weekly wages was
higher than the national average (4.2 percent) in 128 of the largest
U.S. counties, but was below the national average in 186 counties.
Table A. Top 10 large counties ranked by December 2007 employment, December 2006-07 employment growth,
and December 2006-07 percent growth in employment
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Employment in large counties
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December 2007 employment | Growth in employment, | Percent growth in employment,
(thousands) | December 2006-07 | December 2006-07
| (thousands) |
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| |
United States 137,027.3| United States 1,089.1| United States 0.8
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| |
Los Angeles, Calif. 4,293.4| Harris, Texas 73.2| Fort Bend, Texas 7.4
Cook, Ill. 2,556.2| New York, N.Y. 52.0| Monterey, Calif. 5.2
New York, N.Y. 2,419.9| King, Wash. 35.2| Williamson, Tenn. 4.5
Harris, Texas 2,061.4| Los Angeles, Calif. 32.9| Madison, Ala. 4.0
Maricopa, Ariz. 1,848.2| Dallas, Texas 31.3| San Francisco, Calif. 4.0
Orange, Calif. 1,517.7| San Francisco, Calif. 21.8| Wake, N.C. 3.9
Dallas, Texas 1,504.8| Bexar, Texas 18.8| Hidalgo, Texas 3.9
San Diego, Calif. 1,340.3| Tarrant, Texas 17.3| Harris, Texas 3.7
King, Wash. 1,194.1| Wake, N.C. 17.1| Tulare, Calif. 3.6
Miami-Dade, Fla. 1,032.1| Travis, Texas 16.4| Denton, Texas 3.6
| | Arlington, Va. 3.6
| |
| |
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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 137.0 million full- and
part-time workers. The attached tables contain data for the nation
and for the 328 U.S. counties with annual average employment levels
of 75,000 or more in 2006. December 2007 employment and 2007 fourth-
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, second, and third quarter 2007 also are
available on the BLS Web site. Updated data for first, second, and
third quarter 2007 and preliminary data for fourth quarter 2007 will
be available later in July on the BLS Web site.
Large County Employment
In December 2007, national employment, as measured by the QCEW
program, was 137.0 million, up by 0.8 percent from December 2006. The
328 U.S. counties with 75,000 or more employees accounted for 71.2
percent of total U.S. employment and 77.2 percent of total wages.
These 328 counties had a net job gain of 666,400 over the year,
accounting for 61.2 percent of the overall U.S. employment increase.
Employment rose in 201 of the large counties from December 2006 to
December 2007. Fort Bend County, Texas, had the largest over-the-year
percentage increase in employment (7.4 percent). Monterey, Calif.,
had the next largest increase, 5.2 percent, followed by the counties
of Williamson, Tenn. (4.5 percent), and Madison, Ala., and San
Francisco, Calif. (4.0 percent each).
Employment declined in 98 counties from December 2006 to December
2007. The largest percentage decline in employment was in Trumbull
County, Ohio (-5.7 percent). Lee, Fla., had the next largest
employment decline (-5.5 percent), followed by the counties of
Collier, Fla. (-5.1 percent), Sarasota, Fla. (-4.1 percent), and
Manatee, Fla., and Saginaw, Mich. (-3.7 percent each).
The largest gains in the level of employment from December 2006 to
December 2007 were recorded in the counties of Harris, Texas
(73,200), New York, N.Y. (52,000), King, Wash. (35,200), Los Angeles,
Calif. (32,900), and Dallas, Texas (31,300). (See table A.) The
largest decline in employment levels occurred in Orange, Calif.
(-25,300), followed by the counties of Wayne, Mich. (-19,900), Lee,
Fla. (-12,700), Pinellas, Fla. (-11,500), and Oakland, Mich.(-9,100).
Table B. Top 10 large counties ranked by fourth quarter 2007 average weekly wages, fourth quarter 2006-07
growth in average weekly wages, and fourth 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
fourth quarter 2007 | wage, fourth quarter 2006-07 | weekly wage, fourth
| | quarter 2006-07
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| |
United States $898| United States $36| United States 4.2
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| |
New York, N.Y. $1,862| Pulaski, Ark. $205| Pulaski, Ark. 26.2
Santa Clara, Calif. 1,700| Lake, Ill. 171| Williamson, Texas 16.5
Fairfield, Conn. 1,575| Williamson, Texas 134| Lake, Ill. 15.6
Suffolk, Mass. 1,546| Santa Clara, Calif. 126| Douglas, Colo. 12.6
San Francisco, Calif. 1,529| Somerset, N.J. 123| Westmoreland, Pa. 9.8
San Mateo, Calif. 1,513| San Mateo, Calif. 112| Olmsted, Minn. 9.4
Washington, D.C. 1,506| Douglas, Colo. 110| Somerset, N.J. 9.2
Somerset, N.J. 1,461| Middlesex, Mass. 94| Williamson, Tenn. 8.2
Arlington, Va. 1,458| Washington, D.C. 82| San Mateo, Calif. 8.0
Fairfax, Va. 1,358| Olmsted, Minn. 79| Santa Clara, Calif. 8.0
| |
| |
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Large County Average Weekly Wages
The national average weekly wage in the fourth quarter of 2007 was
$898. Average weekly wages were higher than the national average in
106 of the largest 328 U.S. counties. New York, N.Y., held the top
position among the highest-paid large counties with an average weekly
wage of $1,862. Santa Clara, Calif., was second with an average
weekly wage of $1,700, followed by Fairfield, Conn. ($1,575),
Suffolk, Mass. ($1,546), and San Francisco, Calif. ($1,529). (See
table B.)
There were 222 counties with an average weekly wage below the
national average in the fourth quarter of 2007. The lowest average
weekly wage was reported in Cameron County, Texas ($555), followed by
the counties of Hidalgo, Texas ($562), Horry, S.C. ($582), Webb,
Texas ($590), and Yakima, Wash. ($596). (See table 1.)
Over the year, the national average weekly wage rose by 4.2
percent. Among the largest counties, Pulaski County, Ark., led the
nation in growth in average weekly wages, with an increase of 26.2
percent from the fourth quarter of 2006. Williamson, Texas, was
second with growth of 16.5 percent, followed by the counties of Lake,
Ill. (15.6 percent), Douglas, Colo. (12.6 percent), and Westmoreland,
Pa. (9.8 percent).
Eight large counties experienced over-the-year declines in average
weekly wages. Among the five largest decreases in wages, Rockingham,
N.H., had the greatest decline (-12.4 percent), followed by the
counties of Trumbull, Ohio (-7.2 percent), Sedgwick, Kan. (-4.1
percent), Lake, Fla. (-3.9 percent), and Montgomery, Ohio (-2.4
percent).
Ten Largest U.S. Counties
Six of the 10 largest counties (based on 2006 annual average
employment levels) experienced over-the-year percent increases in
employment in December 2007. Harris, Texas, experienced the largest
percent gain in employment among the 10 largest counties with a 3.7
percent increase. Within Harris County, the largest gains in
employment were in construction (6.9 percent) and other services (4.7
percent). King, Wash., had the next largest increase in employment,
3.0 percent, followed by New York, N.Y. (2.2 percent). Orange,
Calif., experienced the largest decline in employment among the 10
largest counties with a 1.6 percent decrease. Within Orange County,
four industry groups experienced employment declines, with financial
activities experiencing the largest drop, -12.4 percent. Maricopa,
Ariz., and Cook, Ill., had the next largest decline in employment
(-0.1 percent each). (See table 2.)
Each of the 10 largest U.S. counties saw an over-the-year increase
in average weekly wages. Harris, Texas, had the fastest growth in
wages among the 10 largest counties, with a gain of 5.9 percent.
Within Harris County, average weekly wages increased the most in the
natural resources and mining industry (14.2 percent), followed by the
manufacturing industry (12.5 percent). Cook, Ill., was second in wage
growth with a gain of 4.8 percent, followed by San Diego, Calif. (4.4
percent). The smallest wage gain among the 10 largest counties
occurred in Miami-Dade, Fla. (0.6 percent), followed by Maricopa,
Ariz. (2.0 percent), and Orange, Calif. (2.8 percent).
Largest County by State
Table 3 shows December 2007 employment and the 2007 fourth 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 December 2007 ranged from approximately 4.29
million in Los Angeles County, Calif., to 43,500 in Laramie County,
Wyo. The highest average weekly wage of these counties was in New
York, N.Y. ($1,862), while the lowest average weekly wage was in
Yellowstone, Mont. ($729).
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 first quarter 2008 is
scheduled to be released on Friday, October 17, 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 have been included
in all 2007 quarterly releases. One county, Boone, Ky., which was published in the
2006 releases, has been excluded from all 2007 releases because its 2006 annual av-
erage 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 9.1 | 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 | | |
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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
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 contains selected data produced by Busi-
ness 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 includes 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 have been published exclusively in electronic formats as PDFs. The
2006 bulletin is available in a 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,
fourth quarter 2007(2)
Employment Average weekly wage(4)
Establishments,
County(3) fourth quarter Percent Ranking Percent Ranking
2007 December change, by Average change, by
(thousands) 2007 December percent weekly fourth percent
(thousands) 2006-07(5) change wage quarter change
2006-07(5)
United States(6)......... 9,064.5 137,027.3 0.8 - $898 4.2 -
Jefferson, AL............ 19.0 367.5 (7) - 901 3.4 186
Madison, AL.............. 8.8 182.1 4.0 4 925 3.6 164
Mobile, AL............... 10.1 177.3 2.7 28 767 1.5 289
Montgomery, AL........... 6.8 140.5 1.4 87 782 1.8 278
Tuscaloosa, AL........... 4.4 87.0 0.1 189 768 1.1 297
Anchorage Borough, AK.... 8.1 146.2 0.8 127 924 5.0 76
Maricopa, AZ............. 100.3 1,848.2 -0.1 215 875 2.0 271
Pima, AZ................. 21.0 377.1 -0.6 250 770 3.5 172
Benton, AR............... 5.6 96.3 0.1 189 791 4.8 86
Pulaski, AR.............. 14.8 253.6 1.2 97 986 26.2 1
Washington, AR........... 5.7 93.2 -0.6 250 735 2.5 245
Alameda, CA.............. 51.2 692.7 0.3 173 1,165 5.1 68
Butte, CA................ 7.9 76.5 0.0 202 669 5.9 35
Contra Costa, CA......... 29.2 348.0 -0.8 263 1,117 5.9 35
Fresno, CA............... 30.2 352.7 -0.3 233 724 4.9 80
Kern, CA................. 18.2 288.5 1.2 97 761 5.4 53
Los Angeles, CA.......... 418.1 4,293.4 0.8 127 1,054 3.7 152
Marin, CA................ 11.9 110.9 0.9 119 1,170 2.5 245
Monterey, CA............. 12.6 156.9 5.2 2 773 1.0 299
Orange, CA............... 99.1 1,517.7 -1.6 290 1,027 2.8 226
Placer, CA............... 10.9 136.8 -0.1 215 875 0.8 300
Riverside, CA............ 45.5 634.1 -0.9 265 730 2.7 236
Sacramento, CA........... 53.5 633.6 0.3 173 974 4.6 101
San Bernardino, CA....... 48.3 672.9 -0.1 215 766 2.8 226
San Diego, CA............ 96.4 1,340.3 0.1 189 963 4.4 116
San Francisco, CA........ 46.3 573.2 4.0 4 1,529 4.7 94
San Joaquin, CA.......... 17.8 223.6 0.0 202 771 3.6 164
San Luis Obispo, CA...... 9.4 105.1 1.2 97 750 4.6 101
San Mateo, CA............ 23.8 347.6 0.7 131 1,513 8.0 9
Santa Barbara, CA........ 14.2 183.1 0.7 131 852 4.9 80
Santa Clara, CA.......... 59.1 913.9 1.5 81 1,700 8.0 9
Santa Cruz, CA........... 8.9 94.4 2.0 56 851 5.2 62
Solano, CA............... 10.1 127.7 0.1 189 870 6.9 20
Sonoma, CA............... 18.5 194.1 0.2 181 873 3.7 152
Stanislaus, CA........... 14.7 173.1 -0.6 250 733 3.2 198
Tulare, CA............... 9.3 152.4 3.6 9 629 5.4 53
Ventura, CA.............. 22.7 319.0 -1.0 269 979 3.5 172
Yolo, CA................. 5.8 101.9 1.8 61 860 (7) -
Adams, CO................ 9.2 158.2 3.4 14 827 5.6 46
Arapahoe, CO............. 19.6 285.5 2.1 50 1,087 6.5 26
Boulder, CO.............. 12.7 162.5 1.7 68 1,064 4.1 131
Denver, CO............... 25.5 448.2 2.0 56 1,129 5.6 46
Douglas, CO.............. 9.4 93.5 3.3 16 983 12.6 4
El Paso, CO.............. 17.6 248.3 0.5 150 803 3.9 141
Jefferson, CO............ 18.7 214.1 1.7 68 907 6.3 28
Larimer, CO.............. 10.3 130.5 1.7 68 812 3.6 164
Weld, CO................. 6.0 83.3 1.3 91 744 4.8 86
Fairfield, CT............ 33.0 432.8 1.3 91 1,575 4.3 123
Hartford, CT............. 25.5 511.1 0.7 131 1,100 5.2 62
New Haven, CT............ 22.7 374.5 0.0 202 946 3.7 152
New London, CT........... 6.9 131.2 0.7 131 914 5.4 53
New Castle, DE........... 18.3 289.1 -0.2 224 1,031 3.0 219
Washington, DC........... 32.4 681.6 0.7 131 1,506 5.8 40
Alachua, FL.............. 6.7 122.9 (7) - 743 (7) -
Brevard, FL.............. 14.8 203.1 -2.3 300 830 3.1 207
Broward, FL.............. 66.0 759.9 -1.0 269 864 0.5 302
Collier, FL.............. 12.6 133.7 -5.1 310 839 1.9 275
Duval, FL................ 26.4 467.8 -0.5 243 870 2.7 236
Escambia, FL............. 8.1 130.3 -1.2 277 705 2.5 245
Hillsborough, FL......... 37.2 655.8 0.0 202 846 3.7 152
Lake, FL................. 7.2 84.2 0.4 157 649 -3.9 313
Lee, FL.................. 19.8 218.3 -5.5 311 765 2.0 271
Leon, FL................. 8.2 146.6 -1.7 293 780 6.8 22
Manatee, FL.............. 9.1 127.6 -3.7 307 693 2.5 245
Marion, FL............... 8.5 102.2 -3.1 305 637 0.3 306
Miami-Dade, FL........... 87.8 1,032.1 0.0 202 902 0.6 301
Okaloosa, FL............. 6.2 80.0 (7) - 715 3.2 198
Orange, FL............... 36.8 700.9 1.5 81 821 4.5 108
Palm Beach, FL........... 51.0 567.0 -0.6 250 900 2.5 245
Pasco, FL................ 9.9 101.2 -0.7 259 652 3.5 172
Pinellas, FL............. 31.9 436.3 -2.6 302 790 3.5 172
Polk, FL................. 12.8 208.8 -1.5 287 694 2.4 254
Sarasota, FL............. 15.2 154.8 -4.1 309 766 0.0 307
Seminole, FL............. 15.3 179.0 -1.1 275 794 1.5 289
Volusia, FL.............. 14.1 164.7 -1.5 287 654 1.2 296
Bibb, GA................. 4.7 84.2 -0.3 233 703 1.7 283
Chatham, GA.............. 7.6 137.3 0.0 202 766 3.7 152
Clayton, GA.............. 4.3 115.2 0.6 143 779 2.5 245
Cobb, GA................. 20.6 323.0 0.9 119 927 1.4 292
De Kalb, GA.............. 16.3 300.0 -0.9 265 916 2.1 268
Fulton, GA............... 40.3 771.5 1.1 106 1,173 2.8 226
Gwinnett, GA............. 23.7 326.6 -0.2 224 902 2.3 261
Muscogee, GA............. 4.8 97.0 -0.8 263 716 6.5 26
Richmond, GA............. 4.8 103.5 0.1 189 728 2.4 254
Honolulu, HI............. 24.7 461.0 0.1 189 819 4.1 131
Ada, ID.................. 15.2 213.1 0.4 157 823 0.5 302
Champaign, IL............ 4.1 92.5 0.6 143 734 4.1 131
Cook, IL................. 138.5 2,556.2 -0.1 215 1,101 4.8 86
Du Page, IL.............. 35.8 604.8 0.0 202 1,056 3.5 172
Kane, IL................. 12.6 212.2 0.1 189 820 2.4 254
Lake, IL................. 21.0 335.3 1.3 91 1,266 15.6 3
McHenry, IL.............. 8.4 103.8 0.8 127 784 1.4 292
McLean, IL............... 3.7 86.0 0.3 173 814 2.0 271
Madison, IL.............. 6.0 96.7 1.2 97 731 2.5 245
Peoria, IL............... 4.8 105.2 0.4 157 841 2.9 223
Rock Island, IL.......... 3.5 79.8 1.1 106 1,063 6.8 22
St. Clair, IL............ 5.4 98.0 1.6 75 724 4.9 80
Sangamon, IL............. 5.3 130.4 0.0 202 862 4.6 101
Will, IL................. 13.4 195.9 3.5 12 797 1.1 297
Winnebago, IL............ 6.9 138.6 0.7 131 750 2.6 240
Allen, IN................ 9.0 184.5 -1.2 277 759 4.8 86
Elkhart, IN.............. 4.9 123.4 -0.5 243 714 3.2 198
Hamilton, IN............. 7.5 111.7 (7) - 859 (7) -
Lake, IN................. 10.2 197.7 0.4 157 768 3.9 141
Marion, IN............... 23.9 588.6 0.6 143 888 2.5 245
St. Joseph, IN........... 6.0 126.0 -0.5 243 736 4.2 129
Tippecanoe, IN........... 3.2 76.7 -0.7 259 735 4.0 137
Vanderburgh, IN.......... 4.8 107.9 -0.2 224 729 3.3 191
Linn, IA................. 6.3 125.8 2.2 46 876 5.7 44
Polk, IA................. 14.8 276.7 1.8 61 883 3.6 164
Scott, IA................ 5.2 89.3 -0.5 243 740 4.4 116
Johnson, KS.............. 20.4 318.7 1.4 87 926 4.8 86
Sedgwick, KS............. 12.2 260.5 1.2 97 811 -4.1 314
Shawnee, KS.............. 4.9 95.8 2.4 37 749 4.8 86
Wyandotte, KS............ 3.2 81.1 0.4 157 840 2.7 236
Fayette, KY.............. 9.3 179.3 0.3 173 812 4.4 116
Jefferson, KY............ 22.5 439.6 0.4 157 859 3.4 186
Caddo, LA................ 7.3 128.0 2.0 56 750 4.3 123
Calcasieu, LA............ 4.8 86.7 -0.6 250 765 5.1 68
East Baton Rouge, LA..... 14.1 268.3 1.8 61 812 5.3 59
Jefferson, LA............ 13.8 202.9 1.8 61 845 3.7 152
Lafayette, LA............ 8.5 136.6 3.4 14 869 5.8 40
Orleans, LA.............. 10.2 172.0 (7) - 957 (7) -
Cumberland, ME........... 12.4 177.4 1.0 114 798 3.6 164
Anne Arundel, MD......... 14.5 235.6 0.5 150 924 3.1 207
Baltimore, MD............ 21.8 383.6 0.2 181 959 4.9 80
Frederick, MD............ 6.0 96.4 -0.6 250 857 6.2 29
Harford, MD.............. 5.7 84.7 0.1 189 803 3.6 164
Howard, MD............... 8.6 147.9 -0.3 233 1,031 3.1 207
Montgomery, MD........... 33.0 466.4 -0.1 215 1,195 4.9 80
Prince Georges, MD....... 15.7 322.3 1.9 59 968 3.5 172
Baltimore City, MD....... 14.2 348.4 -0.2 224 1,092 7.4 14
Barnstable, MA........... 9.2 86.8 -1.2 277 790 3.9 141
Bristol, MA.............. 15.6 221.7 -1.3 283 796 3.4 186
Essex, MA................ 20.8 302.1 0.5 150 945 3.2 198
Hampden, MA.............. 14.3 201.7 -0.4 238 815 3.3 191
Middlesex, MA............ 47.6 827.5 1.2 97 1,307 7.7 11
Norfolk, MA.............. 22.6 330.3 0.9 119 1,117 4.7 94
Plymouth, MA............. 13.9 178.8 -1.0 269 864 3.8 149
Suffolk, MA.............. 21.8 594.7 1.9 59 1,546 3.8 149
Worcester, MA............ 20.8 324.6 0.0 202 915 6.8 22
Genesee, MI.............. 7.9 143.9 -3.2 306 802 2.8 226
Ingham, MI............... 6.8 163.1 0.2 181 859 4.4 116
Kalamazoo, MI............ 5.5 116.5 -1.0 269 799 3.9 141
Kent, MI................. 14.1 341.0 -1.1 275 804 1.6 285
Macomb, MI............... 17.7 313.3 -2.5 301 922 3.7 152
Oakland, MI.............. 39.0 696.6 -1.3 283 1,049 1.8 278
Ottawa, MI............... 5.7 108.1 -2.2 299 761 0.0 307
Saginaw, MI.............. 4.3 86.3 -3.7 307 756 0.5 302
Washtenaw, MI............ 8.0 194.1 -1.2 277 957 3.5 172
Wayne, MI................ 32.1 751.0 -2.6 302 991 2.2 264
Anoka, MN................ 7.8 117.5 0.9 119 831 2.3 261
Dakota, MN............... 10.6 176.8 0.4 157 883 5.7 44
Hennepin, MN............. 42.4 858.4 0.7 131 1,116 6.2 29
Olmsted, MN.............. 3.6 91.3 0.9 119 916 9.4 6
Ramsey, MN............... 15.4 334.3 0.0 202 953 5.4 53
St. Louis, MN............ 5.9 98.1 1.6 75 726 4.3 123
Stearns, MN.............. 4.5 83.2 2.5 34 676 1.3 295
Harrison, MS............. 4.6 87.0 1.6 75 680 1.9 275
Hinds, MS................ 6.4 130.6 1.0 114 785 3.4 186
Boone, MO................ 4.6 82.8 -0.3 233 671 3.7 152
Clay, MO................. 5.1 91.2 0.7 131 823 5.5 50
Greene, MO............... 8.3 159.2 2.5 34 663 4.9 80
Jackson, MO.............. 18.9 372.1 0.6 143 893 3.7 152
St. Charles, MO.......... 8.3 125.8 1.2 97 737 3.2 198
St. Louis, MO............ 33.2 618.4 0.1 189 977 7.5 12
St. Louis City, MO....... 8.5 234.0 -0.1 215 962 2.6 240
Douglas, NE.............. 15.9 323.0 1.2 97 860 5.5 50
Lancaster, NE............ 8.1 159.0 (7) - 700 3.2 198
Clark, NV................ 49.8 929.0 0.8 127 875 7.2 16
Washoe, NV............... 14.6 219.1 -1.3 283 865 5.4 53
Hillsborough, NH......... 12.5 201.1 0.0 202 1,039 4.5 108
Rockingham, NH........... 11.1 138.8 -1.2 277 892 -12.4 316
Atlantic, NJ............. 7.1 145.7 -1.6 290 800 2.6 240
Bergen, NJ............... 35.0 464.3 0.3 173 1,185 5.6 46
Burlington, NJ........... 11.6 205.6 -0.7 259 939 3.3 191
Camden, NJ............... 13.3 212.3 -0.4 238 953 2.3 261
Essex, NJ................ 21.6 368.7 0.4 157 1,135 2.4 254
Gloucester, NJ........... 6.3 106.3 -0.4 238 832 5.6 46
Hudson, NJ............... 14.1 241.4 1.1 106 1,170 4.5 108
Mercer, NJ............... 11.4 229.9 (7) - 1,151 5.2 62
Middlesex, NJ............ 22.2 415.2 -0.3 233 1,130 1.6 285
Monmouth, NJ............. 21.1 260.0 -0.1 215 1,003 4.7 94
Morris, NJ............... 18.4 292.0 -2.0 296 1,316 1.9 275
Ocean, NJ................ 12.6 148.9 -0.5 243 772 1.4 292
Passaic, NJ.............. 12.7 182.4 -0.2 224 937 1.5 289
Somerset, NJ............. 10.3 176.3 -0.6 250 1,461 9.2 7
Union, NJ................ 15.3 238.8 (7) - 1,138 (7) -
Bernalillo, NM........... 17.8 337.2 0.5 150 785 3.3 191
Albany, NY............... 10.0 231.0 0.1 189 894 -0.8 310
Bronx, NY................ 15.7 225.8 0.7 131 863 4.0 137
Broome, NY............... 4.5 96.6 0.4 157 696 3.9 141
Dutchess, NY............. 8.3 118.6 -1.4 286 872 2.2 264
Erie, NY................. 23.5 465.9 0.7 131 772 1.8 278
Kings, NY................ 45.2 484.2 2.2 46 789 3.1 207
Monroe, NY............... 18.0 385.8 0.1 189 849 4.6 101
Nassau, NY............... 52.5 623.6 0.5 150 1,030 4.4 116
New York, NY............. 118.0 2,419.9 2.2 46 1,862 4.1 131
Oneida, NY............... 5.3 112.7 0.4 157 683 1.8 278
Onondaga, NY............. 12.8 256.7 1.1 106 844 5.2 62
Orange, NY............... 10.0 133.6 1.1 106 744 2.6 240
Queens, NY............... 42.8 509.4 2.1 50 894 5.1 68
Richmond, NY............. 8.6 95.5 0.2 181 804 5.1 68
Rockland, NY............. 9.8 119.1 1.7 68 953 5.1 68
Saratoga, NY............. 5.4 77.9 1.0 114 735 3.4 186
Suffolk, NY.............. 50.1 639.1 1.2 97 997 4.8 86
Westchester, NY.......... 36.4 432.7 1.5 81 1,248 3.3 191
Buncombe, NC............. 8.1 118.8 2.3 41 712 3.5 172
Catawba, NC.............. 4.7 88.4 -1.5 287 687 2.4 254
Cumberland, NC........... 6.3 120.6 1.8 61 675 6.0 33
Durham, NC............... 7.0 186.8 1.6 75 1,151 7.2 16
Forsyth, NC.............. 9.3 189.8 1.1 106 803 2.2 264
Guilford, NC............. 14.9 286.3 0.7 131 781 1.8 278
Mecklenburg, NC.......... 32.6 578.6 2.7 28 1,000 3.1 207
New Hanover, NC.......... 7.6 106.3 2.1 50 736 4.7 94
Wake, NC................. 28.5 459.8 3.9 6 893 3.0 219
Cass, ND................. 5.8 99.1 3.2 17 762 5.2 62
Butler, OH............... 7.4 150.2 2.1 50 776 4.3 123
Cuyahoga, OH............. 37.7 750.9 -0.5 243 909 3.9 141
Franklin, OH............. 29.7 698.8 1.1 106 847 1.6 285
Hamilton, OH............. 24.0 525.8 0.2 181 960 4.7 94
Lake, OH................. 6.7 101.7 -0.1 215 739 2.8 226
Lorain, OH............... 6.2 98.8 -2.1 298 723 2.8 226
Lucas, OH................ 10.7 222.4 -1.8 294 765 2.4 254
Mahoning, OH............. 6.3 105.2 -0.1 215 655 3.5 172
Montgomery, OH........... 12.8 269.0 -1.8 294 807 -2.4 312
Stark, OH................ 9.1 163.3 0.4 157 686 3.5 172
Summit, OH............... 14.9 276.9 0.4 157 809 2.8 226
Trumbull, OH............. 4.7 78.5 -5.7 312 752 -7.2 315
Oklahoma, OK............. 23.7 426.2 1.0 114 806 6.1 32
Tulsa, OK................ 19.6 348.9 0.9 119 818 5.1 68
Clackamas, OR............ 12.7 152.5 1.4 87 816 2.9 223
Jackson, OR.............. 6.8 86.0 -0.6 250 651 4.0 137
Lane, OR................. 11.1 152.6 0.3 173 693 3.1 207
Marion, OR............... 9.5 139.1 1.8 61 694 3.6 164
Multnomah, OR............ 27.6 458.1 2.4 37 915 5.3 59
Washington, OR........... 16.2 253.2 -0.2 224 1,007 6.6 25
Allegheny, PA............ 35.4 692.7 0.6 143 942 2.8 226
Berks, PA................ 9.3 171.4 -0.4 238 813 5.2 62
Bucks, PA................ 20.3 267.9 0.0 202 880 3.5 172
Butler, PA............... 4.8 80.4 1.3 91 766 (7) -
Chester, PA.............. 15.1 245.3 2.4 37 1,154 3.7 152
Cumberland, PA........... 6.0 126.7 -0.9 265 799 3.2 198
Dauphin, PA.............. 7.4 182.8 0.2 181 846 2.2 264
Delaware, PA............. 13.6 214.0 0.9 119 940 2.4 254
Erie, PA................. 7.3 128.6 0.3 173 701 4.5 108
Lackawanna, PA........... 5.8 102.9 -0.4 238 680 2.6 240
Lancaster, PA............ 12.3 232.1 0.4 157 742 1.6 285
Lehigh, PA............... 8.7 180.3 0.4 157 915 5.8 40
Luzerne, PA.............. 7.9 143.1 -0.2 224 686 5.1 68
Montgomery, PA........... 27.5 495.3 0.3 173 1,152 5.3 59
Northampton, PA.......... 6.5 101.4 2.3 41 781 2.8 226
Philadelphia, PA......... 30.2 639.7 0.1 189 1,068 5.8 40
Washington, PA........... 5.3 79.3 0.7 131 783 7.4 14
Westmoreland, PA......... 9.5 136.4 -1.2 277 728 9.8 5
York, PA................. 9.2 180.5 1.4 87 763 1.7 283
Kent, RI................. 5.8 81.4 -2.8 304 775 4.4 116
Providence, RI........... 18.3 288.4 -2.0 296 868 2.0 271
Charleston, SC........... 12.2 213.4 2.7 28 785 7.5 12
Greenville, SC........... 12.6 241.6 1.7 68 769 3.1 207
Horry, SC................ 8.4 111.4 -1.0 269 582 0.5 302
Lexington, SC............ 5.7 97.8 2.4 37 673 3.9 141
Richland, SC............. 9.3 217.1 -0.5 243 759 2.8 226
Spartanburg, SC.......... 6.1 120.9 1.3 91 746 3.2 198
Minnehaha, SD............ 6.3 116.0 1.8 61 734 4.4 116
Davidson, TN............. 18.5 452.0 (7) - 953 4.3 123
Hamilton, TN............. 8.7 196.7 0.4 157 788 3.0 219
Knox, TN................. 11.1 232.2 1.5 81 787 3.0 219
Rutherford, TN........... 4.3 101.2 2.5 34 837 4.5 108
Shelby, TN............... 20.1 516.0 -0.2 224 935 5.5 50
Williamson, TN........... 5.9 87.8 4.5 3 1,020 8.2 8
Bell, TX................. 4.5 99.7 1.7 68 671 4.8 86
Bexar, TX................ 32.1 730.9 2.6 32 793 4.5 108
Brazoria, TX............. 4.6 87.3 2.7 28 840 4.6 101
Brazos, TX............... 3.8 85.6 (7) - 658 (7) -
Cameron, TX.............. 6.5 124.8 1.0 114 555 5.1 68
Collin, TX............... 16.5 290.0 (7) - 1,015 (7) -
Dallas, TX............... 67.9 1,504.8 2.1 50 1,112 3.8 149
Denton, TX............... 10.3 170.0 3.6 9 792 2.7 236
El Paso, TX.............. 13.3 275.3 2.9 21 625 3.6 164
Fort Bend, TX............ 8.1 129.0 7.4 1 967 5.9 35
Galveston, TX............ 5.2 98.5 (7) - 828 6.2 29
Harris, TX............... 96.1 2,061.4 3.7 8 1,152 5.9 35
Hidalgo, TX.............. 10.5 219.9 3.9 6 562 3.3 191
Jefferson, TX............ 5.9 124.4 0.0 202 867 4.2 129
Lubbock, TX.............. 6.7 124.0 1.1 106 683 4.6 101
McLennan, TX............. 4.9 105.0 1.7 68 702 3.5 172
Montgomery, TX........... 7.9 125.4 (7) - 847 (7) -
Nueces, TX............... 8.2 154.9 2.1 50 764 4.1 131
Smith, TX................ 5.3 94.9 2.8 25 760 3.1 207
Tarrant, TX.............. 36.7 777.0 2.3 41 897 2.9 223
Travis, TX............... 28.3 579.2 2.9 21 1,012 (7) -
Webb, TX................. 4.9 90.0 2.9 21 590 3.1 207
Williamson, TX........... 6.9 121.8 (7) - 947 16.5 2
Davis, UT................ 7.2 103.3 1.5 81 729 2.1 268
Salt Lake, UT............ 39.0 599.7 2.8 25 843 5.0 76
Utah, UT................. 13.1 177.5 2.9 21 714 5.0 76
Weber, UT................ 5.8 95.6 2.8 25 673 3.5 172
Chittenden, VT........... 5.9 96.5 0.1 189 875 5.9 35
Arlington, VA............ 7.6 157.0 3.6 9 1,458 4.7 94
Chesterfield, VA......... 7.5 123.3 0.6 143 800 3.1 207
Fairfax, VA.............. 33.1 593.2 0.6 143 1,358 4.5 108
Henrico, VA.............. 9.2 182.8 1.6 75 903 -0.1 309
Loudoun, VA.............. 8.4 132.2 2.6 32 1,084 2.1 268
Prince William, VA....... 6.9 104.9 -0.9 265 817 7.2 16
Alexandria City, VA...... 6.0 101.8 -1.0 269 1,240 3.9 141
Chesapeake City, VA...... 5.7 101.6 -0.7 259 701 3.1 207
Newport News City, VA.... 4.0 100.7 0.5 150 794 3.5 172
Norfolk City, VA......... 5.8 144.0 -0.6 250 866 3.7 152
Richmond City, VA........ 7.4 160.2 (7) - 1,013 (7) -
Virginia Beach City, VA.. 11.6 178.4 0.4 157 709 3.2 198
Clark, WA................ 12.1 133.6 1.6 75 793 3.7 152
King, WA................. 77.0 1,194.1 3.0 20 1,088 4.1 131
Kitsap, WA............... 6.7 84.7 0.5 150 787 3.3 191
Pierce, WA............... 20.8 278.4 2.3 41 780 5.0 76
Snohomish, WA............ 17.8 256.1 3.2 17 905 6.0 33
Spokane, WA.............. 15.4 211.0 1.5 81 706 4.3 123
Thurston, WA............. 6.9 100.6 3.1 19 785 4.7 94
Whatcom, WA.............. 6.9 83.3 3.5 12 689 7.0 19
Yakima, WA............... 8.0 92.8 2.2 46 596 4.0 137
Kanawha, WV.............. 6.1 109.5 0.2 181 764 5.4 53
Brown, WI................ 6.8 151.3 0.9 119 795 4.6 101
Dane, WI................. 14.1 308.3 (7) - 834 (7) -
Milwaukee, WI............ 21.3 502.9 0.2 181 900 4.5 108
Outagamie, WI............ 5.1 106.5 2.3 41 754 3.1 207
Racine, WI............... 4.2 76.4 -1.6 290 884 6.9 20
Waukesha, WI............. 13.4 238.3 -0.2 224 892 -2.3 311
Winnebago, WI............ 3.8 90.9 1.3 91 813 2.5 245
San Juan, PR............. 13.4 300.4 -3.9 (8) 607 4.5 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 328 U.S. counties comprise 71.2 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,
fourth quarter 2007(2)
Employment Average weekly
wage(3)
Establishments,
fourth quarter
County by NAICS supersector 2007 Percent Percent
(thousands) December change, Average change,
2007 December weekly fourth
(thousands) 2006-07(4) wage quarter
2006-07(4)
United States(5)............................. 9,064.5 137,027.3 0.8 $898 4.2
Private industry........................... 8,773.2 115,110.2 0.7 901 4.0
Natural resources and mining............. 125.5 1,769.5 2.8 948 8.6
Construction............................. 893.7 7,383.8 -2.1 1,002 5.5
Manufacturing............................ 360.8 13,748.3 -2.0 1,075 3.8
Trade, transportation, and utilities..... 1,919.0 27,258.0 0.8 758 3.4
Information.............................. 145.2 3,048.3 -0.6 1,358 5.1
Financial activities..................... 872.2 8,105.2 -1.5 1,395 3.6
Professional and business services....... 1,497.1 18,098.9 1.7 1,157 5.7
Education and health services............ 830.4 17,781.1 3.1 841 3.7
Leisure and hospitality.................. 728.7 13,174.3 1.8 383 4.1
Other services........................... 1,185.8 4,469.7 1.7 564 3.3
Government................................. 291.2 21,917.0 1.2 879 4.9
Los Angeles, CA.............................. 418.1 4,293.4 0.8 1,054 3.7
Private industry........................... 414.1 3,688.0 0.5 1,050 3.7
Natural resources and mining............. 0.5 10.9 -1.3 1,202 19.5
Construction............................. 14.3 155.1 -2.1 1,087 5.2
Manufacturing............................ 15.1 441.5 (6) 1,066 (6)
Trade, transportation, and utilities..... 55.1 849.5 0.4 847 2.2
Information.............................. 8.9 215.6 5.6 1,794 -2.0
Financial activities..................... 25.0 241.9 -3.9 1,520 2.2
Professional and business services....... 43.4 616.2 -0.7 1,311 10.2
Education and health services............ 28.1 490.0 2.3 943 1.7
Leisure and hospitality.................. 27.2 400.9 1.1 865 3.3
Other services........................... 187.1 254.5 5.2 451 2.0
Government................................. 4.0 605.4 2.6 1,081 (6)
Cook, IL..................................... 138.5 2,556.2 -0.1 1,101 4.8
Private industry........................... 137.1 2,247.9 0.0 1,111 4.8
Natural resources and mining............. 0.1 1.1 -11.5 1,054 -5.2
Construction............................. 12.2 92.4 -2.6 1,379 4.3
Manufacturing............................ 7.1 236.6 -2.3 1,089 2.3
Trade, transportation, and utilities..... 27.6 492.4 -0.8 845 3.2
Information.............................. 2.6 58.9 0.6 1,547 8.7
Financial activities..................... 15.9 215.0 -1.9 1,981 13.3
Professional and business services....... 28.4 443.8 0.6 1,469 4.3
Education and health services............ 13.6 374.7 2.3 918 1.7
Leisure and hospitality.................. 11.6 232.5 (6) 441 5.0
Other services........................... 14.0 96.1 0.6 758 5.0
Government................................. 1.4 308.3 -0.9 1,028 4.0
New York, NY................................. 118.0 2,419.9 2.2 1,862 4.1
Private industry........................... 117.7 1,967.9 2.6 2,050 4.2
Natural resources and mining............. 0.0 0.1 7.0 1,511 10.2
Construction............................. 2.4 36.4 9.9 1,911 8.3
Manufacturing............................ 3.1 36.9 -4.3 1,560 8.2
Trade, transportation, and utilities..... 22.0 265.1 2.0 1,309 2.7
Information.............................. 4.4 136.0 1.2 2,059 0.1
Financial activities..................... 18.6 383.6 1.8 4,129 4.7
Professional and business services....... 24.6 497.4 (6) 2,170 (6)
Education and health services............ 8.6 294.7 1.4 1,062 3.8
Leisure and hospitality.................. 11.2 221.3 4.4 895 -4.2
Other services........................... 17.5 89.3 1.9 988 -0.8
Government................................. 0.3 452.0 0.3 1,045 2.0
Harris, TX................................... 96.1 2,061.4 3.7 1,152 5.9
Private industry........................... 95.6 1,809.3 4.0 1,182 5.9
Natural resources and mining............. 1.5 80.1 (6) 3,098 14.2
Construction............................. 6.7 155.5 6.9 1,130 3.4
Manufacturing............................ 4.6 183.4 2.7 1,518 12.5
Trade, transportation, and utilities..... 22.0 441.2 3.7 997 4.4
Information.............................. 1.4 32.6 0.4 1,289 6.1
Financial activities..................... 10.7 120.8 1.5 1,443 4.2
Professional and business services....... 19.2 342.5 4.4 1,373 2.8
Education and health services............ 10.2 216.8 (6) 926 2.7
Leisure and hospitality.................. 7.4 175.5 3.1 385 2.1
Other services........................... 11.3 59.2 4.7 654 6.9
Government................................. 0.5 252.2 1.5 940 5.3
Maricopa, AZ................................. 100.3 1,848.2 -0.1 875 2.0
Private industry........................... 99.7 1,624.4 -0.6 874 1.7
Natural resources and mining............. 0.5 9.6 0.2 846 8.6
Construction............................. 10.8 153.4 -10.8 954 3.1
Manufacturing............................ 3.6 131.5 (6) 1,173 -4.7
Trade, transportation, and utilities..... 22.0 392.4 1.5 794 0.9
Information.............................. 1.6 30.6 -1.8 1,068 -1.0
Financial activities..................... 12.9 147.4 -4.4 1,071 -2.6
Professional and business services....... 22.4 319.2 0.2 938 7.3
Education and health services............ 9.8 203.8 4.8 971 4.2
Leisure and hospitality.................. 7.3 184.8 2.6 424 4.7
Other services........................... 7.2 50.5 1.1 601 6.6
Government................................. 0.7 223.7 3.0 880 4.3
Orange, CA................................... 99.1 1,517.7 -1.6 1,027 2.8
Private industry........................... 97.7 1,366.6 -1.9 1,029 2.1
Natural resources and mining............. 0.2 4.6 1.0 666 3.7
Construction............................. 7.1 98.2 -8.0 1,180 4.0
Manufacturing............................ 5.3 175.1 (6) 1,236 5.3
Trade, transportation, and utilities..... 17.7 293.1 (6) 938 4.2
Information.............................. 1.4 30.4 -0.5 1,368 -1.7
Financial activities..................... 11.3 119.7 -12.4 1,620 -0.6
Professional and business services....... 19.3 272.2 -3.9 1,168 4.5
Education and health services............ 9.9 145.3 4.7 941 2.6
Leisure and hospitality.................. 7.0 174.9 2.4 401 4.4
Other services........................... 15.1 48.6 1.9 602 3.8
Government................................. 1.4 151.1 0.4 1,011 10.0
Dallas, TX................................... 67.9 1,504.8 2.1 1,112 3.8
Private industry........................... 67.4 1,338.5 2.1 1,131 3.7
Natural resources and mining............. 0.6 7.4 (6) 3,412 (6)
Construction............................. 4.4 83.7 2.7 1,058 3.8
Manufacturing............................ 3.1 141.4 -1.3 1,231 7.7
Trade, transportation, and utilities..... 15.1 316.1 1.6 1,037 6.8
Information.............................. 1.7 48.4 (6) 1,503 (6)
Financial activities..................... 8.7 145.1 0.7 1,457 -2.1
Professional and business services....... 14.8 278.1 3.7 1,338 3.4
Education and health services............ 6.6 148.7 4.9 1,021 2.6
Leisure and hospitality.................. 5.4 129.2 4.0 497 2.7
Other services........................... 6.5 39.5 2.6 658 3.1
Government................................. 0.5 166.2 2.3 960 5.5
San Diego, CA................................ 96.4 1,340.3 0.1 963 4.4
Private industry........................... 95.1 1,112.9 -0.1 945 3.7
Natural resources and mining............. 0.8 10.7 2.7 576 -2.2
Construction............................. 7.3 81.7 -10.3 1,080 5.1
Manufacturing............................ 3.2 103.6 (6) 1,302 7.9
Trade, transportation, and utilities..... 14.5 231.0 -0.7 750 3.3
Information.............................. 1.3 38.9 2.6 1,913 12.5
Financial activities..................... 9.9 78.6 -5.3 1,172 0.4
Professional and business services....... 16.5 217.4 0.8 1,216 2.5
Education and health services............ 8.1 130.7 3.4 927 3.3
Leisure and hospitality.................. 6.9 160.3 1.9 410 3.8
Other services........................... 23.8 56.2 0.4 489 -0.8
Government................................. 1.3 227.4 1.5 1,050 7.4
King, WA..................................... 77.0 1,194.1 3.0 1,088 4.1
Private industry........................... 76.5 1,040.0 3.3 1,098 3.9
Natural resources and mining............. 0.4 2.7 4.5 1,407 6.1
Construction............................. 6.8 72.5 9.9 1,119 8.2
Manufacturing............................ 2.5 112.4 1.4 1,353 -1.2
Trade, transportation, and utilities..... 14.7 227.9 2.3 944 4.8
Information.............................. 1.8 76.8 3.7 1,920 2.2
Financial activities..................... 7.0 76.0 -0.7 1,378 2.3
Professional and business services....... 13.3 192.6 5.1 1,320 5.8
Education and health services............ 6.4 123.4 4.0 863 5.5
Leisure and hospitality.................. 6.1 111.4 3.0 443 3.7
Other services........................... 17.6 44.2 2.1 607 8.2
Government................................. 0.5 154.1 1.0 1,026 5.9
Miami-Dade, FL............................... 87.8 1,032.1 0.0 902 0.6
Private industry........................... 87.4 877.9 -0.2 888 0.2
Natural resources and mining............. 0.5 10.4 -1.3 516 6.2
Construction............................. 6.4 50.6 (6) 935 (6)
Manufacturing............................ 2.6 45.7 -5.2 817 2.1
Trade, transportation, and utilities..... 23.5 260.2 0.3 808 -0.7
Information.............................. 1.5 20.7 1.0 1,205 0.8
Financial activities..................... 10.6 71.6 -1.8 1,397 4.6
Professional and business services....... 17.8 135.8 (6) 1,147 (6)
Education and health services............ 9.2 139.4 3.6 883 3.9
Leisure and hospitality.................. 5.9 104.2 1.6 509 5.8
Other services........................... 7.7 36.5 2.9 543 3.8
Government................................. 0.4 154.2 1.2 981 2.4
(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, fourth quarter 2007(2)
Employment Average weekly
wage(4)
Establishments,
fourth quarter
County(3) 2007 Percent Percent
(thousands) December change, Average change,
2007 December weekly fourth
(thousands) 2006-07(5) wage quarter
2006-07(5)
United States(6)......... 9,064.5 137,027.3 0.8 $898 4.2
Jefferson, AL............ 19.0 367.5 (7) 901 3.4
Anchorage Borough, AK.... 8.1 146.2 0.8 924 5.0
Maricopa, AZ............. 100.3 1,848.2 -0.1 875 2.0
Pulaski, AR.............. 14.8 253.6 1.2 986 26.2
Los Angeles, CA.......... 418.1 4,293.4 0.8 1,054 3.7
Denver, CO............... 25.5 448.2 2.0 1,129 5.6
Hartford, CT............. 25.5 511.1 0.7 1,100 5.2
New Castle, DE........... 18.3 289.1 -0.2 1,031 3.0
Washington, DC........... 32.4 681.6 0.7 1,506 5.8
Miami-Dade, FL........... 87.8 1,032.1 0.0 902 0.6
Fulton, GA............... 40.3 771.5 1.1 1,173 2.8
Honolulu, HI............. 24.7 461.0 0.1 819 4.1
Ada, ID.................. 15.2 213.1 0.4 823 0.5
Cook, IL................. 138.5 2,556.2 -0.1 1,101 4.8
Marion, IN............... 23.9 588.6 0.6 888 2.5
Polk, IA................. 14.8 276.7 1.8 883 3.6
Johnson, KS.............. 20.4 318.7 1.4 926 4.8
Jefferson, KY............ 22.5 439.6 0.4 859 3.4
East Baton Rouge, LA..... 14.1 268.3 1.8 812 5.3
Cumberland, ME........... 12.4 177.4 1.0 798 3.6
Montgomery, MD........... 33.0 466.4 -0.1 1,195 4.9
Middlesex, MA............ 47.6 827.5 1.2 1,307 7.7
Wayne, MI................ 32.1 751.0 -2.6 991 2.2
Hennepin, MN............. 42.4 858.4 0.7 1,116 6.2
Hinds, MS................ 6.4 130.6 1.0 785 3.4
St. Louis, MO............ 33.2 618.4 0.1 977 7.5
Yellowstone, MT.......... 5.7 78.2 3.6 729 5.5
Douglas, NE.............. 15.9 323.0 1.2 860 5.5
Clark, NV................ 49.8 929.0 0.8 875 7.2
Hillsborough, NH......... 12.5 201.1 0.0 1,039 4.5
Bergen, NJ............... 35.0 464.3 0.3 1,185 5.6
Bernalillo, NM........... 17.8 337.2 0.5 785 3.3
New York, NY............. 118.0 2,419.9 2.2 1,862 4.1
Mecklenburg, NC.......... 32.6 578.6 2.7 1,000 3.1
Cass, ND................. 5.8 99.1 3.2 762 5.2
Cuyahoga, OH............. 37.7 750.9 -0.5 909 3.9
Oklahoma, OK............. 23.7 426.2 1.0 806 6.1
Multnomah, OR............ 27.6 458.1 2.4 915 5.3
Allegheny, PA............ 35.4 692.7 0.6 942 2.8
Providence, RI........... 18.3 288.4 -2.0 868 2.0
Greenville, SC........... 12.6 241.6 1.7 769 3.1
Minnehaha, SD............ 6.3 116.0 1.8 734 4.4
Shelby, TN............... 20.1 516.0 -0.2 935 5.5
Harris, TX............... 96.1 2,061.4 3.7 1,152 5.9
Salt Lake, UT............ 39.0 599.7 2.8 843 5.0
Chittenden, VT........... 5.9 96.5 0.1 875 5.9
Fairfax, VA.............. 33.1 593.2 0.6 1,358 4.5
King, WA................. 77.0 1,194.1 3.0 1,088 4.1
Kanawha, WV.............. 6.1 109.5 0.2 764 5.4
Milwaukee, WI............ 21.3 502.9 0.2 900 4.5
Laramie, WY.............. 3.2 43.5 2.0 738 7.1
San Juan, PR............. 13.4 300.4 -3.9 607 4.5
St. Thomas, VI........... 1.8 24.0 0.9 703 3.2
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted
for noneconomic county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin
Islands.
(7) Data do not meet BLS or State agency disclosure standards.
Table 4. Covered(1) establishments, employment, and wages by state,
fourth quarter 2007(2)
Employment Average weekly
wage(3)
Establishments,
fourth quarter
State 2007 Percent Percent
(thousands) December change, Average change,
2007 December weekly fourth
(thousands) 2006-07 wage quarter
2006-07
United States(4)......... 9,064.5 137,027.3 0.8 $898 4.2
Alabama.................. 121.1 1,971.0 1.2 762 3.3
Alaska................... 21.1 299.4 1.0 877 4.9
Arizona.................. 160.9 2,693.3 -0.1 827 2.6
Arkansas................. 84.1 1,187.6 0.7 712 9.2
California............... 1,340.6 15,794.7 0.8 1,035 4.8
Colorado................. 177.7 2,329.9 2.0 927 5.7
Connecticut.............. 113.2 1,717.8 0.7 1,149 4.5
Delaware................. 28.6 428.8 0.3 926 3.3
District of Columbia..... 32.4 681.6 0.7 1,506 5.8
Florida.................. 614.5 8,024.3 -1.3 810 2.8
Georgia.................. 275.0 4,111.5 0.6 835 2.8
Hawaii................... 38.9 637.2 0.7 793 4.1
Idaho.................... 57.2 660.2 1.7 686 2.1
Illinois................. 363.7 5,933.0 0.6 975 5.1
Indiana.................. 158.2 2,929.1 0.1 745 3.0
Iowa..................... 94.0 1,498.5 0.7 732 4.9
Kansas................... 86.3 1,372.7 1.2 745 2.6
Kentucky................. 111.7 1,830.5 0.8 732 3.4
Louisiana................ 121.1 1,903.1 2.3 783 4.7
Maine.................... 50.6 608.8 0.8 707 4.1
Maryland................. 165.2 2,580.1 0.4 986 4.7
Massachusetts............ 212.7 3,270.9 0.7 1,133 5.4
Michigan................. 256.9 4,194.9 -1.2 873 2.5
Minnesota................ 170.9 2,708.7 0.8 883 5.1
Mississippi.............. 70.6 1,148.9 0.7 654 3.8
Missouri................. 176.1 2,746.2 0.3 780 5.3
Montana.................. 42.9 440.4 2.1 659 5.4
Nebraska................. 59.6 925.2 1.3 723 5.2
Nevada................... 76.5 1,290.8 0.4 872 6.7
New Hampshire............ 49.7 638.8 0.3 914 -0.3
New Jersey............... 275.8 4,027.4 0.2 1,092 3.5
New Mexico............... 54.5 831.7 1.1 738 4.8
New York................. 579.2 8,762.7 1.4 1,152 4.2
North Carolina........... 257.3 4,127.7 1.5 777 3.5
North Dakota............. 25.4 347.7 2.0 690 7.3
Ohio..................... 291.4 5,336.8 -0.2 795 2.8
Oklahoma................. 100.1 1,556.1 1.3 721 6.2
Oregon................... 131.4 1,740.5 0.9 798 4.6
Pennsylvania............. 340.5 5,712.8 0.5 873 4.2
Rhode Island............. 36.1 480.9 -1.5 838 2.6
South Carolina........... 118.0 1,904.0 1.0 716 4.1
South Dakota............. 30.3 393.5 1.7 647 5.4
Tennessee................ 141.8 2,790.3 0.9 813 4.0
Texas.................... 555.4 10,460.8 3.0 911 4.6
Utah..................... 88.1 1,241.8 2.8 758 4.6
Vermont.................. 24.9 309.1 -0.2 743 4.9
Virginia................. 227.6 3,709.0 0.7 921 3.8
Washington............... 221.4 2,936.0 2.6 885 4.6
West Virginia............ 48.8 716.8 0.4 683 4.1
Wisconsin................ 159.8 2,803.9 0.3 769 3.1
Wyoming.................. 24.7 279.6 3.0 815 7.1
Puerto Rico.............. 56.5 1,055.2 -1.4 517 4.4
Virgin Islands........... 3.5 46.0 0.6 738 3.9
(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
