Technical information:(202) 691-6567 USDL 08-1459
http://www.bls.gov/cew/
For release: 10:00 A.M. EDT
Media contact: 691-5902 Friday, October 17, 2008
(NOTE: This news release was reissued on Tuesday, November 4,
2008, to correct two items in the Large County Average Weekly
Wages section on page 3. In the second sentence of the first paragraph,
the number of counties with average weekly wages higher than the
national average was corrected from "183" to "92". In the first
sentence of the second paragraph, the number of counties with
average weekly wages below the national average was corrected from
"137" to "241". No other changers were made.)
COUNTY EMPLOYMENT AND WAGES: FIRST QUARTER 2008
In March 2008, 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 5.0 percent, compared with national job growth of
0.4 percent. Westmoreland County, Pa., near Pittsburgh, had the
largest over-the-year gain in average weekly wages in the first
quarter of 2008, with an increase of 14.9 percent due to an increase
in the professional and business services supersector. The U.S.
average weekly wage rose by 2.4 percent over the same time span.
Of the 334 largest counties in the United States, as measured by
2007 annual average employment, 146 had over-the-year percentage
growth in employment above the national average (0.4 percent) in
March 2008; 178 large counties experienced changes below the national
average. The percent change in average weekly wages was higher than
the national average (2.4 percent) in 183 of the largest U.S.
counties but was below the national average in 137 counties.
Table A. Top 10 large counties ranked by March 2008 employment, March 2007-08 employment growth,
and March 2007-08 percent growth in employment
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Employment in large counties
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March 2008 employment | Growth in employment, | Percent growth in employment,
(thousands) | March 2007-08 | March 2007-08
| (thousands) |
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| |
United States 134,761.1| United States 481.0| United States 0.4
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| |
Los Angeles, Calif. 4,229.6| Harris, Texas 67.2| Orleans, La. 5.0
Cook, Ill. 2,490.4| New York, N.Y. 38.7| Fort Bend, Texas 4.7
New York, N.Y. 2,376.0| King, Wash. 31.0| Montgomery, Texas 4.7
Harris, Texas 2,046.5| Dallas, Texas 29.1| Williamson, Texas 4.6
Maricopa, Ariz. 1,805.2| Bexar, Texas 20.2| Douglas, Colo. 4.1
Orange, Calif. 1,504.9| Tarrant, Texas 17.6| Potter, Texas 4.1
Dallas, Texas 1,489.7| Santa Clara, Calif. 16.8| Cass, N.D. 3.8
San Diego, Calif. 1,327.6| San Francisco, Calif. 16.1| El Paso, Texas 3.7
King, Wash. 1,186.2| Los Angeles, Calif. 15.2| Yakima, Wash. 3.6
Miami-Dade, Fla. 1,029.9| Wake, N.C. 15.2| Wake, N.C. 3.5
| |
| |
| |
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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 134.8 million full- and
part-time workers. The attached tables contain data for the nation
and for the 334 U.S. counties with annual average employment levels
of 75,000 or more in 2007. March 2008 employment and 2008 first-
quarter average weekly wages for all states are provided in table 4
of this release. Data for all states, metropolitan statistical areas,
counties, and the nation through the fourth quarter of 2007 are
available on the BLS Web site at http://www.bls.gov/cew. Preliminary
data for first quarter 2008 and final data for 2007 will be available
later in October on the BLS Web site.
Large County Employment
In March 2008, national employment, as measured by the QCEW
program, was 134.8 million, up by 0.4 percent from March 2007. The
334 U.S. counties with 75,000 or more employees accounted for 71.5
percent of total U.S. employment and 78.3 percent of total wages.
These 334 counties had a net job gain of 198,000 over the year,
accounting for 41.2 percent of the overall U.S. employment increase.
Employment rose in 189 of the large counties from March 2007 to March
2008. Orleans County, La., had the largest over-the-year percentage
increase in employment (5.0 percent). Fort Bend, Texas, and
Montgomery, Texas, tied for the next largest increase, 4.7 percent,
followed by the counties of Williamson, Texas (4.6 percent), and
Douglas, Colo., and Potter, Texas (4.1 percent each).
Employment declined in 129 counties from March 2007 to March 2008.
The largest percentage decline in employment was in Lee, Fla. (-8.1
percent). Collier, Fla., had the next largest employment decline
(-7.4 percent), followed by the counties of Genesee, Mich. (-6.5
percent), Saginaw, Mich. (-5.2 percent), and Marion, Fla., (-5.1
percent).
The largest gains in the level of employment from March 2007 to
March 2008 were recorded in the counties of Harris, Texas (67,200),
New York, N.Y. (38,700), King, Wash. (31,000), Dallas, Texas
(29,100), and Bexar, Texas (20,200). (See table A.) The largest
decline in employment levels occurred in Maricopa, Ariz. (-25,100),
followed by the counties of Hillsborough, Fla. (-23,700), Wayne,
Mich. (-23,000), Oakland, Mich. (-19,500), and Lee, Fla. (-19,400).
Table B. Top 10 large counties ranked by first quarter 2008 average weekly wages, first quarter 2007-08
growth in average weekly wages, and first quarter 2007-08 percent growth in average weekly wages
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Average weekly wage in large counties
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Average weekly wage, | Growth in average weekly | Percent growth in average
first quarter 2008 | wage, first quarter 2007-08 | weekly wage, first
| | quarter 2007-08
--------------------------------------------------------------------------------------------------------
| |
United States $905| United States $21| United States 2.4
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| |
New York, N.Y. $2,805| Somerset, N.J. $146| Westmoreland, Pa. 14.9
Fairfield, Conn. 1,905| Westmoreland, Pa. 98| Williamson, Texas 10.8
Somerset, N.J. 1,765| Williamson, Texas 89| Somerset, N.J. 9.0
Suffolk, Mass. 1,708| Hudson, N.J. 87| San Luis Obispo, Calif. 8.3
San Francisco, Calif. 1,639| Mercer, N.J. 66| Jefferson, Texas 7.9
Santa Clara, Calif. 1,631| New London, Conn. 64| New London, Conn. 7.3
Hudson, N.J. 1,528| Jefferson, Texas 63| Adams, Colo. 6.8
Washington, D.C. 1,488| Washington, D.C. 62| Pima, Ariz. 6.7
Arlington, Va. 1,473| Hennepin, Minn. 59| Clayton, Ga. 6.7
San Mateo, Calif. 1,457| McLean, Ill. 58| McLean, Ill. 6.7
| Hillsborough, N.H. 58|
| Washington, Ore. 58|
| |
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Large County Average Weekly Wages
The national average weekly wage in the first quarter of 2008 was
$905. Average weekly wages were higher than the national average in
92 of the largest 334 U.S. counties. New York, N.Y., held the top
position among the highest-paid large counties with an average weekly
wage of $2,805. Fairfield, Conn., was second with an average weekly
wage of $1,905, followed by Somerset, N.J. ($1,765), Suffolk, Mass.
($1,708), and San Francisco, Calif. ($1,639). (See table B.)
There were 241 counties with an average weekly wage below the
national average in the first quarter of 2008. The lowest average
weekly wage was reported in Cameron County, Texas ($523), followed by
the counties of Hidalgo, Texas ($532), Horry, S.C. ($534), Webb,
Texas ($554), and Yakima, Wash. ($587). (See table 1.)
Over the year, the national average weekly wage rose by 2.4
percent. Among the largest counties, Westmoreland, Pa., led the
nation in growth in average weekly wages, with an increase of 14.9
percent from the first quarter of 2007. Williamson, Texas, was second
with growth of 10.8 percent, followed by the counties of Somerset,
N.J. (9.0 percent), San Luis Obispo, Calif. (8.3 percent), and
Jefferson, Texas (7.9 percent).
Thirty-four large counties experienced over-the-year declines in
average weekly wages. Trumbull, Ohio, had the largest decrease (-17.2
percent), followed by the counties of Saginaw, Mich. (-4.4 percent),
Rockingham, N.H. (-3.9 percent), Fairfield, Conn. (-3.8 percent), and
Mecklenburg, N.C. (-3.4 percent).
Ten Largest U.S. Counties
Five of the 10 largest counties (based on 2007 annual average
employment levels) experienced over-the-year percent increases in
employment in March 2008. Harris, Texas, experienced the largest
percent gain in employment (3.4 percent) among the 10 largest
counties. Within Harris County, the largest gains in employment were
in natural resources and mining (5.5 percent) and construction (5.4
percent). King, Wash., had the next largest increase in employment,
2.7 percent, followed by Dallas, Texas (2.0 percent). Maricopa,
Ariz., experienced the largest decline in employment among the 10
largest counties with a 1.4 percent decrease. Within Maricopa, six
industry groups experienced employment declines, with construction
experiencing the largest decline, -14.2 percent. Orange, Calif., had
the next largest decline in employment, -1.1 percent, followed by
Miami-Dade, Fla. (-1.0 percent). (See table 2.)
Nine of the 10 largest U.S. counties saw an over-the-year increase
in average weekly wages. King, Wash., had the fastest growth in wages
among the 10 largest counties, with a gain of 4.2 percent. Within
King County, average weekly wages increased the most in the
information industry (12.8 percent), followed by the other services
industry (7.7 percent). Harris, Texas, was second in wage growth with
a gain of 3.8 percent, followed by Cook, Ill. (2.7 percent). The
smallest wage gain occurred in Orange, Calif. (1.2 percent), followed
by Maricopa, Ariz. (1.3 percent). The only wage decline among the 10
largest counties occurred in New York, N.Y. (-1.0 percent).
Within New York County, two industry groups experienced over-the-
year wage declines in the first quarter of 2008--manufacturing
(-4.1 percent) and financial activities (-3.7 percent). Financial
activities employs ten times more workers than manufacturing in New
York County and had the county's highest average weekly wages. The
declines for the first quarter of 2008 follow over-the-year average
weekly wage gains of 14.6 percent in manufacturing and 24.2 percent
in financial activities in the first quarter of 2007.
Largest County by State
Table 3 shows March 2008 employment and the 2008 first quarter
average weekly wage in the largest county in each state, which is
based on 2007 annual average employment levels. (This table includes
one county--Laramie, Wyo.--that had an employment level below 75,000
in 2007.) The employment levels in the counties in table 3 in March
2008 ranged from approximately 4.23 million in Los Angeles County,
Calif., to 43,100 in Laramie County, Wyo. The highest average weekly
wage of these counties was in New York, N.Y. ($2,805), while the
lowest average weekly wage was in Yellowstone, Mont. ($695).
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 second quarter 2008 is
scheduled to be released on Tuesday, January 13, 2009.
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| |
| County Changes for the 2008 County Employment and Wages |
| News Releases: Six Counties Added |
| |
| Counties with annual average employment of 75,000 or more in 2007 |
| are included in this release. For 2008 data, six counties have |
| been added to the publication tables: Shelby, Ala., Boone, Ky., |
| St. Tammany, La., Yellowstone, Mont., Warren, Ohio, and Potter, |
| Texas. |
| |
| |
| |
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Technical Note
These data are the product of a federal-state cooperative program, the Quarterly
Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The
data are derived from summaries of employment and total pay of workers covered by
state and federal unemployment insurance (UI) legislation and provided by State
Workforce Agencies (SWAs). The summaries are a result of the administration of state
unemployment insurance programs that require most employers to pay quarterly taxes
based on the employment and wages of workers covered by UI. QCEW data in this re-
lease are based on the 2007 North American Industry Classification System. Data for
2008 are preliminary and subject to revision.
For purposes of this release, large counties are defined as having employment lev-
els of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are provided,
but not used in calculating U.S. averages, rankings, or in the analysis in the text.
Each year, these large counties are selected on the basis of the preliminary annual
average of employment for the previous year. The 335 counties presented in this re-
lease were derived using 2007 preliminary annual averages of employment. For 2008
data, six counties have been added to the publication tables: Shelby, Ala., Boone,
Ky., St. Tammany, La., Yellowstone, Mont., Warren, Ohio, and Potter, Texas. These
counties will be included in all 2008 quarterly releases. The counties in table 2
are selected and sorted each year based on the annual average employment from the
preceding year.
The preliminary QCEW data presented in this release may differ from data released
by the individual states. These potential differences result from the states' con-
tinuing receipt of UI data over time and ongoing review and editing. The individual
states determine their data release timetables.
Differences between QCEW, BED, and CES employment measures
The Bureau publishes three different establishment-based employment measures for
any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED),
and Current Employment Statistics (CES)--makes use of the quarterly UI employment
reports in producing data; however, each measure has a somewhat different universe
coverage, estimation procedure, and publication product.
Differences in coverage and estimation methods can result in somewhat different
measures of employment change over time. It is important to understand program dif-
ferences and the intended uses of the program products. (See table.) Additional in-
formation on each program can be obtained from the program Web sites shown in the
table.
Summary of Major Differences between QCEW, BED, and CES Employment Measures
---------------------------------------------------------------------------------
| QCEW | BED | CES
-----------|---------------------|----------------------|------------------------
Source |--Count of UI admini-|--Count of longitudi- |--Sample survey:
| strative records | nally-linked UI ad- | 400,000 establish-
| submitted by 9.1 | ministrative records| ments
| million establish- | submitted by 7.1 |
| ments | million private-sec-|
| | tor employers |
-----------|---------------------|----------------------|------------------------
Coverage |--UI and UCFE cover- |--UI coverage, exclud-|Nonfarm wage and sal-
| age, including all | ing government, pri-| ary jobs:
| employers subject | vate households, and|--UI coverage, exclud-
| to state and fed- | establishments with | ing agriculture, pri-
| eral UI laws | zero employment | vate households, and
| | | self-employed workers
| | |--Other employment, in-
| | | cluding railroads,
| | | religious organiza-
| | | tions, and other non-
| | | UI-covered jobs
-----------|---------------------|----------------------|------------------------
Publication|--Quarterly |--Quarterly |--Monthly
frequency | -7 months after the| -8 months after the | -Usually first Friday
| end of each quar- | end of each quarter| of following month
| ter | |
-----------|---------------------|----------------------|------------------------
Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam-
file | and publishes each | quarter to longitu- | pling frame and annu-
| new quarter of UI | dinal database and | ally realigns (bench-
| data | directly summarizes | marks) sample esti-
| | gross job gains and | mates to first quar-
| | losses | ter UI levels
-----------|---------------------|----------------------|------------------------
Principal |--Provides a quarter-|--Provides quarterly |--Provides current month-
products | ly and annual uni- | employer dynamics | ly estimates of employ-
| verse count of es- | data on establish- | ment, hours, and earn-
| tablishments, em- | ment openings, clos-| ings at the MSA, state,
| ployment, and wages| ings, expansions, | and national level by
| at the county, MSA,| and contractions at | industry
| state, and national| the national level |
| levels by detailed | by NAICS supersec- |
| industry | tors and by size of |
| | firm, and at the |
| | state private-sector|
| | total level |
| |--Future expansions |
| | will include data |
| | with greater indus- |
| | try detail and data |
| | at the county and |
| | MSA level |
-----------|---------------------|----------------------|------------------------
Principal |--Major uses include:|--Major uses include: |--Major uses include:
uses | -Detailed locality | -Business cycle | -Principal national
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -Analysis of employ-| cators
| surveys | ment expansion and |
| | contraction by size|
| | of firm |
| | |
-----------|---------------------|----------------------|------------------------
Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/
Web sites | | |
---------------------------------------------------------------------------------
Coverage
Employment and wage data for workers covered by state UI laws are compiled from
quarterly contribution reports submitted to the SWAs by employers. For federal ci-
vilian workers covered by the Unemployment Compensation for Federal Employees (UCFE)
program, employment and wage data are compiled from quarterly reports submitted by
four major federal payroll processing centers on behalf of all federal agencies,
with the exception of a few agencies which still report directly to the individual
SWA. In addition to the quarterly contribution reports, employers who operate multi-
ple establishments within a state complete a questionnaire, called the "Multiple
Worksite Report," which provides detailed information on the location and industry
of each of their establishments. The employment and wage data included in this re-
lease are derived from microdata summaries of 9.1 million employer reports of em-
ployment and wages submitted by states to the BLS. These reports are based on place
of employment rather than place of residence.
UI and UCFE coverage is broad and basically comparable from state to state. In
2007, UI and UCFE programs covered workers in 135.4 million jobs. The estimated
130.3 million workers in these jobs (after adjustment for multiple jobholders) rep-
resented 96.2 percent of civilian wage and salary employment. Covered workers re-
ceived $6.018 trillion in pay, representing 94.6 percent of the wage and salary com-
ponent of personal income and 43.6 percent of the gross domestic product.
Major exclusions from UI coverage include self-employed workers, most agricultural
workers on small farms, all members of the Armed Forces, elected officials in most
states, most employees of railroads, some domestic workers, most student workers at
schools, and employees of certain small nonprofit organizations.
State and federal UI laws change periodically. These changes may have an impact on
the employment and wages reported by employers covered under the UI program. Cover-
age changes may affect the over-the-year comparisons presented in this news release.
Concepts and methodology
Monthly employment is based on the number of workers who worked during or received
pay for the pay period including the 12th of the month. With few exceptions, all em-
ployees of covered firms are reported, including production and sales workers, cor-
poration officials, executives, supervisory personnel, and clerical workers. Work-
ers on paid vacations and part-time workers also are included.
Average weekly wage values are calculated by dividing quarterly total wages by the
average of the three monthly employment levels (all employees, as described above)
and dividing the result by 13, for the 13 weeks in the quarter. These calculations
are made using unrounded employment and wage values. The average wage values that
can be calculated using rounded data from the BLS database may differ from the aver-
ages reported. Included in the quarterly wage data are non-wage cash payments such
as bonuses, the cash value of meals and lodging when supplied, tips and other gra-
tuities, and, in some states, employer contributions to certain deferred compensa-
tion plans such as 401(k) plans and stock options. Over-the-year comparisons of av-
erage weekly wages may reflect fluctuations in average monthly employment and/or to-
tal quarterly wages between the current quarter and prior year levels.
Average weekly wages are affected by the ratio of full-time to part-time workers
as well as the number of individuals in high-paying and low-paying occupations and
the incidence of pay periods within a quarter. For instance, the average weekly wage
of the work force could increase significantly when there is a large decline in the
number of employees that had been receiving below-average wages. Wages may include
payments to workers not present in the employment counts because they did not work
during the pay period including the 12th of the month. When comparing average weekly
wage levels between industries, states, or quarters, these factors should be taken
into consideration.
Federal government pay levels are subject to periodic, sometimes large, fluctua-
tions due to a calendar effect that consists of some quarters having more pay peri-
ods than others. Most federal employees are paid on a biweekly pay schedule. As a
result of this schedule, in some quarters, federal wages contain payments for six
pay periods, while in other quarters their wages include payments for seven pay pe-
riods. Over-the-year comparisons of average weekly wages may reflect this calendar
effect. Higher growth in average weekly wages may be attributed, in part, to a com-
parison of quarterly wages for the current year, which include seven pay periods,
with year-ago wages that reflect only six pay periods. An opposite effect will occur
when wages in the current period, which contain six pay periods, are compared with
year-ago wages that include seven pay periods. The effect on over-the-year pay com-
parisons can be pronounced in federal government due to the uniform nature of fed-
eral payroll processing. This pattern may exist in private sector pay; however, be-
cause there are more pay period types (weekly, biweekly, semimonthly, monthly) it is
less pronounced. The effect is most visible in counties with large concentrations of
federal employment.
In order to ensure the highest possible quality of data, states verify with em-
ployers and update, if necessary, the industry, location, and ownership classifica-
tion of all establishments on a 4-year cycle. Changes in establishment classifica-
tion codes resulting from this process are introduced with the data reported for the
first quarter of the year. Changes resulting from improved employer reporting also
are introduced in the first quarter.
QCEW data are not designed as a time series. QCEW data are simply the sums of in-
dividual establishment records and reflect the number of establishments that exist
in a county or industry at a point in time. Establishments can move in or out of a
county or industry for a number of reasons--some reflecting economic events, others
reflecting administrative changes. For example, economic change would come from a
firm relocating into the county; administrative change would come from a company
correcting its county designation.
The over-the-year changes of employment and wages presented in this release have
been adjusted to account for most of the administrative corrections made to the un-
derlying establishment reports. This is done by modifying the prior-year levels used
to calculate the over-the-year changes. Percent changes are calculated using an ad-
justed version of the final 2007 quarterly data as the base data. The adjusted
prior-year levels used to calculate the over-the-year percent change in employment
and wages are not published. These adjusted prior-year levels do not match the unad-
justed data maintained on the BLS Web site. Over-the-year change calculations based
on data from the Web site, or from data published in prior BLS news releases, may
differ substantially from the over-the-year changes presented in this news release.
The adjusted data used to calculate the over-the-year change measures presented in
this release account for most of the administrative changes--those occurring when
employers update the industry, location, and ownership information of their estab-
lishments. The most common adjustments for administrative change are the result of
updated information about the county location of individual establishments. Included
in these adjustments are administrative changes involving the classification of es-
tablishments that were previously reported in the unknown or statewide county or un-
known industry categories. Beginning with the first quarter of 2008, adjusted data
will also account for administrative changes caused by multi-unit employers who
start reporting for each individual establishment rather than as a single entity.
The adjusted data used to calculate the over-the-year change measures presented in
any County Employment and Wages news release are valid for comparisons between the
starting and ending points (a 12-month period) used in that particular release. Com-
parisons may not be valid for any time period other than the one featured in a re-
lease even if the changes were calculated using adjusted data.
County definitions are assigned according to Federal Information Processing Stan-
dards Publications (FIPS PUBS) as issued by the National Institute of Standards and
Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of
the Information Technology Management Reform Act of 1996 and the Computer Security
Act of 1987, Public Law 104-106. Areas shown as counties include those designated as
independent cities in some jurisdictions and, in Alaska, those designated as census
areas where counties have not been created. County data also are presented for the
New England states for comparative purposes even though townships are the more com-
mon designation used in New England (and New Jersey). The regions referred to in
this release are defined as census regions.
Additional statistics and other information
An annual bulletin, Employment and Wages, features comprehensive information by
detailed industry on establishments, employment, and wages for the nation and all
states. The 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. Em-
ployment and Wages Annual Averages, 2006 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 335 largest counties,
first quarter 2008(2)
Employment Average weekly wage(4)
Establishments,
County(3) first quarter Percent Ranking Percent Ranking
2008 March change, by Average change, by
(thousands) 2008 March percent weekly first percent
(thousands) 2007-08(5) change wage quarter change
2007-08(5)
United States(6)......... 9,112.7 134,761.1 0.4 - $905 2.4 -
Jefferson, AL............ 19.0 359.3 -1.3 277 914 4.0 62
Madison, AL.............. 8.9 181.4 3.4 11 919 3.3 112
Mobile, AL............... 10.1 176.0 0.5 139 710 2.7 158
Montgomery, AL........... 6.8 138.9 -0.4 226 723 1.4 233
Shelby, AL............... 5.0 75.8 2.5 23 878 0.9 260
Tuscaloosa, AL........... 4.5 86.0 -0.5 230 718 2.9 140
Anchorage Borough, AK.... 8.1 144.4 0.6 120 916 4.7 38
Maricopa, AZ............. 101.7 1,805.2 -1.4 282 867 1.3 239
Pima, AZ................. 21.2 373.5 -1.5 283 778 6.7 8
Benton, AR............... 5.6 95.7 -0.9 257 880 4.9 30
Pulaski, AR.............. 14.8 250.4 0.9 93 791 4.8 35
Washington, AR........... 5.7 91.7 -1.3 277 690 4.9 30
Alameda, CA.............. 51.8 686.6 -0.6 237 1,146 1.0 253
Butte, CA................ 8.0 75.6 0.2 168 640 1.7 224
Contra Costa, CA......... 29.5 341.6 -0.8 249 1,109 -0.5 304
Fresno, CA............... 30.7 339.8 -0.9 257 689 3.3 112
Kern, CA................. 18.4 267.5 0.1 180 758 3.6 89
Los Angeles, CA.......... 425.0 4,229.6 0.4 147 992 2.1 204
Marin, CA................ 12.0 109.0 0.7 107 1,073 3.4 103
Monterey, CA............. 12.7 160.6 2.3 27 800 1.7 224
Orange, CA............... 100.1 1,504.9 -1.1 264 1,019 1.2 243
Placer, CA............... 11.0 137.7 -2.3 302 829 -0.1 295
Riverside, CA............ 46.5 624.8 -2.9 311 751 1.9 217
Sacramento, CA........... 54.3 632.7 -1.2 272 962 3.6 89
San Bernardino, CA....... 49.2 656.3 -2.3 302 741 2.2 199
San Diego, CA............ 97.8 1,327.6 0.0 190 945 1.9 217
San Francisco, CA........ 47.2 564.5 2.9 16 1,639 -0.4 300
San Joaquin, CA.......... 18.1 218.5 -2.1 296 731 3.2 122
San Luis Obispo, CA...... 9.5 105.8 0.3 154 741 8.3 4
San Mateo, CA............ 24.1 343.9 1.3 70 1,457 0.6 271
Santa Barbara, CA........ 14.3 186.7 0.6 120 821 0.9 260
Santa Clara, CA.......... 60.0 912.0 1.9 48 1,631 3.1 129
Santa Cruz, CA........... 9.1 92.7 -1.2 272 819 -2.3 320
Solano, CA............... 10.2 124.8 -2.4 305 837 1.2 243
Sonoma, CA............... 18.7 192.9 0.7 107 817 1.7 224
Stanislaus, CA........... 14.9 171.2 -0.8 249 713 2.6 163
Tulare, CA............... 9.5 144.1 1.9 48 608 3.4 103
Ventura, CA.............. 23.0 318.9 -1.1 264 924 -0.6 307
Yolo, CA................. 5.9 100.8 0.5 139 806 -0.5 304
Adams, CO................ 9.3 154.4 3.1 14 813 6.8 7
Arapahoe, CO............. 19.5 281.6 1.9 48 1,081 2.3 192
Boulder, CO.............. 12.9 161.8 2.1 39 1,068 3.5 97
Denver, CO............... 25.7 445.9 1.6 60 1,166 4.2 56
Douglas, CO.............. 9.5 91.9 4.1 5 952 6.3 11
El Paso, CO.............. 17.6 244.2 0.0 190 788 3.7 80
Jefferson, CO............ 18.7 209.7 1.2 77 899 1.8 221
Larimer, CO.............. 10.4 128.1 1.4 65 755 2.0 212
Weld, CO................. 6.1 82.8 1.7 56 718 4.7 38
Fairfield, CT............ 32.9 418.1 1.2 77 1,905 -3.8 325
Hartford, CT............. 25.5 503.7 1.2 77 1,188 0.3 283
New Haven, CT............ 22.7 366.2 0.6 120 924 1.2 243
New London, CT........... 6.9 128.4 0.3 154 939 7.3 6
New Castle, DE........... 18.4 279.9 -0.2 212 1,130 -0.2 297
Washington, DC........... 32.5 680.8 1.1 84 1,488 4.3 52
Alachua, FL.............. 6.9 122.6 (7) - 725 (7) -
Brevard, FL.............. 15.2 204.8 -2.3 302 777 1.2 243
Broward, FL.............. 66.6 757.1 -1.9 292 815 -0.4 300
Collier, FL.............. 12.8 134.6 -7.4 330 750 -1.4 315
Duval, FL................ 27.3 466.7 -1.8 290 888 2.8 151
Escambia, FL............. 8.1 128.3 -2.5 307 675 2.6 163
Hillsborough, FL......... 38.0 633.8 -3.6 321 843 4.2 56
Lake, FL................. 7.4 86.5 -3.3 317 595 2.6 163
Lee, FL.................. 20.3 219.3 -8.1 331 718 2.1 204
Leon, FL................. 8.3 145.0 -2.4 305 717 2.9 140
Manatee, FL.............. 9.5 115.4 0.0 190 664 0.2 286
Marion, FL............... 8.8 104.2 -5.1 327 609 1.8 221
Miami-Dade, FL........... 88.2 1,029.9 -1.0 262 871 1.5 231
Okaloosa, FL............. 6.2 80.1 -3.5 320 681 3.2 122
Orange, FL............... 37.5 701.4 -0.4 226 796 3.1 129
Palm Beach, FL........... 51.6 552.2 -3.3 317 851 0.4 279
Pasco, FL................ 10.2 104.3 -0.3 219 594 1.0 253
Pinellas, FL............. 32.1 433.4 -3.3 317 742 3.6 89
Polk, FL................. 13.0 210.0 -1.8 290 664 2.8 151
Sarasota, FL............. 15.6 157.6 -4.8 326 717 0.6 271
Seminole, FL............. 15.4 178.6 -2.0 294 745 2.1 204
Volusia, FL.............. 14.3 168.2 -4.1 324 616 2.2 199
Bibb, GA................. 4.6 83.8 -0.6 237 693 3.1 129
Chatham, GA.............. 7.6 136.8 -1.3 277 736 (7) -
Clayton, GA.............. 4.4 113.6 0.6 120 810 6.7 8
Cobb, GA................. 20.8 318.5 -0.3 219 969 -2.6 323
De Kalb, GA.............. 16.9 300.2 -0.1 203 962 0.2 286
Fulton, GA............... 39.4 749.3 0.6 120 1,268 0.1 290
Gwinnett, GA............. 23.7 321.7 -1.1 264 876 0.0 292
Muscogee, GA............. 4.9 96.3 -0.7 243 708 3.4 103
Richmond, GA............. 4.8 101.5 0.2 168 727 4.0 62
Honolulu, HI............. 24.6 452.8 0.0 190 800 3.6 89
Ada, ID.................. 15.3 209.2 -0.5 230 746 -2.4 321
Champaign, IL............ 4.1 91.4 0.5 139 705 4.0 62
Cook, IL................. 138.2 2,490.4 -0.5 230 1,147 2.7 158
Du Page, IL.............. 35.9 590.6 -0.1 203 1,058 1.3 239
Kane, IL................. 12.7 205.7 -1.2 272 763 3.0 136
Lake, IL................. 21.0 326.0 0.2 168 1,134 0.4 279
McHenry, IL.............. 8.4 100.1 -0.1 203 729 1.7 224
McLean, IL............... 3.7 85.2 0.2 168 918 6.7 8
Madison, IL.............. 6.0 95.9 0.9 93 704 3.5 97
Peoria, IL............... 4.8 104.3 1.4 65 840 3.2 122
Rock Island, IL.......... 3.5 79.3 0.6 120 863 2.0 212
St. Clair, IL............ 5.4 95.9 0.2 168 673 3.1 129
Sangamon, IL............. 5.2 128.3 0.1 180 849 4.9 30
Will, IL................. 13.5 192.7 2.3 27 757 3.1 129
Winnebago, IL............ 6.9 135.5 -0.2 212 751 2.9 140
Allen, IN................ 9.1 178.2 -2.8 308 726 1.4 233
Elkhart, IN.............. 5.0 120.2 -3.6 321 703 0.1 290
Hamilton, IN............. 7.6 109.4 1.7 56 897 3.7 80
Lake, IN................. 10.3 192.7 -0.1 203 752 2.6 163
Marion, IN............... 24.2 575.0 0.3 154 953 2.5 177
St. Joseph, IN........... 6.1 122.1 -0.9 257 740 6.2 13
Tippecanoe, IN........... 3.3 75.3 -1.6 287 765 4.4 48
Vanderburgh, IN.......... 4.8 106.5 -0.9 257 728 3.7 80
Linn, IA................. 6.3 124.1 2.3 27 834 2.3 192
Polk, IA................. 14.8 271.7 1.6 60 905 2.3 192
Scott, IA................ 5.2 88.0 0.7 107 698 4.3 52
Johnson, KS.............. 20.2 316.7 1.5 63 938 2.9 140
Sedgwick, KS............. 12.0 259.2 1.3 70 836 -1.1 312
Shawnee, KS.............. 4.8 94.6 0.3 154 736 2.8 151
Wyandotte, KS............ 3.2 80.2 0.5 139 805 2.0 212
Boone, KY................ 3.6 74.4 2.2 37 751 2.2 199
Fayette, KY.............. 9.4 174.3 -0.4 226 767 0.8 263
Jefferson, KY............ 22.7 426.6 0.3 154 849 0.7 267
Caddo, LA................ 7.3 126.0 0.8 101 693 2.4 184
Calcasieu, LA............ 4.8 86.2 -1.1 264 749 5.8 19
East Baton Rouge, LA..... 14.1 265.1 1.4 65 814 4.9 30
Jefferson, LA............ 13.8 199.5 0.3 154 797 3.8 73
Lafayette, LA............ 8.6 135.3 2.0 42 817 3.9 70
Orleans, LA.............. 10.2 171.6 5.0 1 1,005 2.7 158
St. Tammany, LA.......... 7.1 74.8 -1.2 272 689 4.7 38
Cumberland, ME........... 12.4 169.6 0.7 107 824 5.0 28
Anne Arundel, MD......... 14.6 232.5 0.6 120 928 3.2 122
Baltimore, MD............ 21.7 374.7 0.0 190 901 2.5 177
Frederick, MD............ 6.0 94.1 -0.5 230 863 3.6 89
Harford, MD.............. 5.7 82.2 -1.9 292 826 2.6 163
Howard, MD............... 8.7 147.9 0.6 120 1,025 2.0 212
Montgomery, MD........... 33.0 455.7 -0.4 226 1,238 2.1 204
Prince Georges, MD....... 15.8 314.5 0.4 147 913 2.8 151
Baltimore City, MD....... 14.1 340.7 -0.8 249 1,033 4.1 60
Barnstable, MA........... 9.1 82.7 -0.5 230 748 3.5 97
Bristol, MA.............. 15.5 214.8 -0.8 249 770 4.9 30
Essex, MA................ 20.8 296.3 1.2 77 922 0.4 279
Hampden, MA.............. 14.2 196.9 0.2 168 824 3.1 129
Middlesex, MA............ 47.5 814.4 1.3 70 1,285 3.0 136
Norfolk, MA.............. 22.8 320.0 0.8 101 1,066 2.6 163
Plymouth, MA............. 13.8 173.7 0.3 154 798 2.4 184
Suffolk, MA.............. 21.7 587.3 1.5 63 1,708 3.4 103
Worcester, MA............ 20.7 318.3 0.2 168 875 3.6 89
Genesee, MI.............. 7.8 134.7 -6.5 329 750 -0.9 310
Ingham, MI............... 6.8 159.8 -1.0 262 819 2.8 151
Kalamazoo, MI............ 5.5 114.1 -2.2 299 773 4.0 62
Kent, MI................. 14.2 330.2 -1.1 264 770 1.0 253
Macomb, MI............... 17.7 302.0 -3.2 313 879 -1.3 314
Oakland, MI.............. 39.0 668.6 -2.8 308 1,021 1.2 243
Ottawa, MI............... 5.7 105.8 -2.2 299 715 0.3 283
Saginaw, MI.............. 4.3 81.8 -5.2 328 717 -4.4 327
Washtenaw, MI............ 8.0 187.5 -2.8 308 947 -2.0 318
Wayne, MI................ 32.1 724.6 -3.1 312 1,013 1.7 224
Anoka, MN................ 7.9 112.4 -1.1 264 796 2.7 158
Dakota, MN............... 10.7 172.8 0.1 180 870 3.4 103
Hennepin, MN............. 42.9 837.2 0.4 147 1,188 5.2 24
Olmsted, MN.............. 3.6 89.3 0.9 93 910 -2.5 322
Ramsey, MN............... 15.5 327.4 0.1 180 1,006 2.3 192
St. Louis, MN............ 6.0 95.8 1.3 70 691 2.5 177
Stearns, MN.............. 4.6 81.2 0.7 107 683 4.4 48
Harrison, MS............. 4.6 86.9 1.9 48 667 1.1 252
Hinds, MS................ 6.4 127.3 -0.1 203 755 0.8 263
Boone, MO................ 4.6 82.8 0.4 147 655 3.8 73
Clay, MO................. 5.1 89.1 -0.7 243 809 0.6 271
Greene, MO............... 8.2 155.4 -0.6 237 638 1.8 221
Jackson, MO.............. 18.7 370.0 0.6 120 894 3.0 136
St. Charles, MO.......... 8.2 120.8 -2.1 296 741 0.7 267
St. Louis, MO............ 32.8 600.2 -1.1 264 953 5.4 22
St. Louis City, MO....... 8.5 232.3 0.7 107 1,033 1.9 217
Yellowstone, MT.......... 5.7 77.1 2.0 42 695 3.4 103
Douglas, NE.............. 15.7 317.4 2.0 42 814 2.6 163
Lancaster, NE............ 8.0 155.9 1.2 77 683 2.1 204
Clark, NV................ 50.2 917.5 -0.6 237 854 5.3 23
Washoe, NV............... 14.6 209.5 -3.2 313 796 3.8 73
Hillsborough, NH......... 12.3 195.0 0.0 190 982 6.3 11
Rockingham, NH........... 10.9 134.4 -0.7 243 839 -3.9 326
Atlantic, NJ............. 7.1 142.2 -0.1 203 790 3.3 112
Bergen, NJ............... 35.1 447.7 0.1 180 1,150 4.0 62
Burlington, NJ........... 11.6 202.4 0.0 190 921 2.4 184
Camden, NJ............... 13.2 207.4 0.0 190 882 0.8 263
Essex, NJ................ 21.6 362.0 0.1 180 1,190 0.5 276
Gloucester, NJ........... 6.3 103.0 0.6 120 784 4.7 38
Hudson, NJ............... 14.1 236.6 0.7 107 1,528 6.0 15
Mercer, NJ............... 11.4 229.3 2.0 42 1,206 5.8 19
Middlesex, NJ............ 22.3 403.8 -0.3 219 1,167 2.9 140
Monmouth, NJ............. 21.1 254.9 0.1 180 935 3.3 112
Morris, NJ............... 18.4 284.3 -1.5 283 1,388 2.1 204
Ocean, NJ................ 12.6 146.2 0.2 168 725 1.4 233
Passaic, NJ.............. 12.7 177.5 -0.3 219 894 0.8 263
Somerset, NJ............. 10.4 172.8 0.5 139 1,765 9.0 3
Union, NJ................ 15.3 234.4 1.0 88 1,231 0.7 267
Bernalillo, NM........... 17.6 331.4 -0.2 212 758 3.7 80
Albany, NY............... 9.9 225.8 -0.1 203 858 2.0 212
Bronx, NY................ 15.9 224.6 2.2 37 803 2.3 192
Broome, NY............... 4.5 95.0 0.6 120 695 3.4 103
Dutchess, NY............. 8.4 115.2 -0.8 249 906 3.7 80
Erie, NY................. 23.6 453.4 0.3 154 762 0.0 292
Kings, NY................ 45.6 478.3 2.1 39 730 -1.2 313
Monroe, NY............... 18.0 376.4 -0.3 219 863 3.2 122
Nassau, NY............... 52.5 601.3 0.6 120 958 -2.1 319
New York, NY............. 118.5 2,376.0 1.7 56 2,805 -1.0 311
Oneida, NY............... 5.3 109.5 0.4 147 676 0.9 260
Onondaga, NY............. 12.8 248.6 0.5 139 804 2.4 184
Orange, NY............... 10.0 130.2 0.8 101 723 1.4 233
Queens, NY............... 43.2 499.9 2.3 27 852 3.1 129
Richmond, NY............. 8.7 93.1 0.1 180 745 2.1 204
Rockland, NY............. 9.8 115.6 1.9 48 949 3.4 103
Saratoga, NY............. 5.4 74.9 -0.2 212 743 3.8 73
Suffolk, NY.............. 50.5 618.0 1.0 88 892 0.2 286
Westchester, NY.......... 36.6 418.5 0.6 120 1,311 -0.2 297
Buncombe, NC............. 8.1 115.8 1.1 84 657 3.3 112
Catawba, NC.............. 4.6 86.8 -2.1 296 662 1.5 231
Cumberland, NC........... 6.3 119.1 0.5 139 657 4.6 42
Durham, NC............... 7.0 184.9 1.0 88 1,237 2.6 163
Forsyth, NC.............. 9.3 186.3 0.6 120 827 5.1 26
Guilford, NC............. 14.9 281.0 0.2 168 770 1.0 253
Mecklenburg, NC.......... 32.8 571.2 2.1 39 1,181 -3.4 324
New Hanover, NC.......... 7.5 104.5 0.0 190 704 3.7 80
Wake, NC................. 28.6 452.1 3.5 10 877 1.2 243
Cass, ND................. 5.8 98.1 3.8 7 715 5.6 21
Butler, OH............... 7.4 146.9 0.6 120 778 3.9 70
Cuyahoga, OH............. 37.8 725.6 -1.7 288 907 -0.4 300
Franklin, OH............. 29.9 674.4 -0.1 203 906 1.2 243
Hamilton, OH............. 24.1 511.0 0.0 190 961 1.2 243
Lake, OH................. 6.8 98.8 -0.6 237 731 1.0 253
Lorain, OH............... 6.3 95.9 -4.2 325 721 1.7 224
Lucas, OH................ 10.8 212.7 -2.0 294 771 -0.5 304
Mahoning, OH............. 6.4 100.5 -1.5 283 618 1.0 253
Montgomery, OH........... 12.9 259.2 -3.2 313 804 -1.5 316
Stark, OH................ 9.1 160.1 -0.2 212 679 1.3 239
Summit, OH............... 15.0 270.8 0.6 120 814 2.9 140
Trumbull, OH............. 4.7 75.5 -3.2 313 709 -17.2 328
Warren, OH............... 4.2 76.0 -0.7 243 747 (7) -
Oklahoma, OK............. 23.8 424.9 1.3 70 788 5.2 24
Tulsa, OK................ 19.4 348.8 1.1 84 823 4.0 62
Clackamas, OR............ 13.0 150.8 0.9 93 789 2.6 163
Jackson, OR.............. 6.8 81.8 -1.7 288 620 0.6 271
Lane, OR................. 11.0 149.6 0.1 180 657 2.5 177
Marion, OR............... 9.6 138.2 0.7 107 675 2.7 158
Multnomah, OR............ 28.3 449.5 1.7 56 885 2.4 184
Washington, OR........... 16.4 249.1 -0.2 212 1,020 6.0 15
Allegheny, PA............ 35.4 677.2 0.3 154 952 0.5 276
Berks, PA................ 9.2 167.9 0.2 168 770 2.4 184
Bucks, PA................ 20.3 262.0 0.5 139 849 2.3 192
Butler, PA............... 4.8 78.8 0.8 101 750 6.1 14
Chester, PA.............. 15.2 241.7 2.0 42 1,118 0.3 283
Cumberland, PA........... 6.0 125.1 0.3 154 794 2.3 192
Dauphin, PA.............. 7.4 180.0 0.1 180 842 1.4 233
Delaware, PA............. 13.8 209.1 0.6 120 959 3.7 80
Erie, PA................. 7.3 125.4 -1.1 264 683 2.4 184
Lackawanna, PA........... 5.8 100.4 -0.9 257 645 2.4 184
Lancaster, PA............ 12.4 227.3 0.7 107 729 2.8 151
Lehigh, PA............... 8.7 176.4 0.2 168 872 0.7 267
Luzerne, PA.............. 7.9 140.2 0.0 190 674 -0.7 308
Montgomery, PA........... 27.6 486.3 1.0 88 1,189 1.0 253
Northampton, PA.......... 6.5 99.2 0.8 101 772 3.9 70
Philadelphia, PA......... 30.4 630.8 -0.3 219 1,064 2.6 163
Washington, PA........... 5.3 78.1 1.2 77 762 3.5 97
Westmoreland, PA......... 9.5 133.6 -0.5 230 757 14.9 1
York, PA................. 9.1 176.3 0.6 120 759 3.3 112
Kent, RI................. 5.7 78.0 -3.6 321 773 1.2 243
Providence, RI........... 18.1 279.3 -2.2 299 896 4.2 56
Charleston, SC........... 12.1 209.4 0.7 107 733 4.3 52
Greenville, SC........... 12.5 240.6 0.9 93 733 2.9 140
Horry, SC................ 8.3 113.9 -1.3 277 534 -0.4 300
Lexington, SC............ 5.6 97.3 0.9 93 639 2.9 140
Richland, SC............. 9.4 215.6 0.0 190 771 2.9 140
Spartanburg, SC.......... 6.1 119.9 0.7 107 783 3.2 122
Minnehaha, SD............ 6.3 114.6 2.5 23 736 4.5 46
Davidson, TN............. 18.8 438.8 0.4 147 898 4.1 60
Hamilton, TN............. 8.7 195.0 1.2 77 742 2.2 199
Knox, TN................. 11.2 230.5 2.3 27 711 0.6 271
Rutherford, TN........... 4.3 100.4 1.4 65 741 -1.9 317
Shelby, TN............... 20.2 502.6 -0.2 212 883 5.1 26
Williamson, TN........... 6.1 87.0 2.3 27 939 2.8 151
Bell, TX................. 4.6 102.3 2.6 20 674 5.0 28
Bexar, TX................ 32.2 729.6 2.9 16 788 2.9 140
Brazoria, TX............. 4.6 87.4 1.8 55 867 3.7 80
Brazos, TX............... 3.8 84.2 (7) - 637 (7) -
Cameron, TX.............. 6.5 125.2 1.1 84 523 4.6 42
Collin, TX............... 16.8 293.3 (7) - 1,059 (7) -
Dallas, TX............... 67.8 1,489.7 2.0 42 1,119 2.6 163
Denton, TX............... 10.4 168.2 2.7 18 744 3.3 112
El Paso, TX.............. 13.4 273.6 3.7 8 599 0.0 292
Fort Bend, TX............ 8.2 127.8 4.7 2 968 4.0 62
Galveston, TX............ 5.2 96.9 3.1 14 840 4.6 42
Harris, TX............... 96.6 2,046.5 3.4 11 1,172 3.8 73
Hidalgo, TX.............. 10.6 221.2 3.4 11 532 3.5 97
Jefferson, TX............ 5.9 124.9 -0.8 249 856 7.9 5
Lubbock, TX.............. 6.8 122.9 2.5 23 626 3.6 89
McLennan, TX............. 4.9 103.3 1.3 70 694 4.4 48
Montgomery, TX........... 8.1 125.1 4.7 2 797 3.2 122
Nueces, TX............... 8.1 155.0 2.6 20 754 6.0 15
Potter, TX............... 3.8 76.4 4.1 5 739 (7) -
Smith, TX................ 5.2 94.1 2.3 27 711 3.3 112
Tarrant, TX.............. 37.1 770.1 2.3 27 885 2.5 177
Travis, TX............... 28.6 577.5 2.4 26 974 3.6 89
Webb, TX................. 4.8 88.6 1.4 65 554 1.3 239
Williamson, TX........... 7.1 121.2 4.6 4 912 10.8 2
Davis, UT................ 7.2 101.7 -0.6 237 671 2.1 204
Salt Lake, UT............ 38.2 587.6 1.9 48 811 3.0 136
Utah, UT................. 13.0 173.1 -0.3 219 651 4.3 52
Weber, UT................ 5.7 95.0 1.6 60 617 2.5 177
Chittenden, VT........... 5.9 93.5 -0.5 230 896 6.0 15
Arlington, VA............ 7.6 153.1 1.0 88 1,473 1.7 224
Chesterfield, VA......... 7.5 120.1 -0.8 249 790 3.3 112
Fairfax, VA.............. 33.2 585.0 0.8 101 1,376 0.4 279
Henrico, VA.............. 9.4 179.6 0.4 147 998 -0.8 309
Loudoun, VA.............. 8.7 130.2 1.9 48 1,105 2.5 177
Prince William, VA....... 7.0 102.6 0.2 168 761 2.6 163
Alexandria City, VA...... 6.1 99.8 0.3 154 1,180 4.0 62
Chesapeake City, VA...... 5.7 99.3 -1.3 277 672 1.4 233
Newport News City, VA.... 4.0 99.5 -0.1 203 794 4.6 42
Norfolk City, VA......... 5.8 143.6 -0.7 243 826 -0.2 297
Richmond City, VA........ 7.4 157.8 0.7 107 1,114 4.4 48
Virginia Beach City, VA.. 11.6 172.7 -0.7 243 683 3.8 73
Clark, WA................ 12.0 132.0 0.6 120 770 3.5 97
King, WA................. 76.8 1,186.2 2.7 18 1,125 4.2 56
Kitsap, WA............... 6.6 83.8 0.3 154 744 2.6 163
Pierce, WA............... 20.4 273.9 0.7 107 804 4.8 35
Snohomish, WA............ 17.8 254.2 2.3 27 895 0.2 286
Spokane, WA.............. 15.0 209.4 1.3 70 701 3.4 103
Thurston, WA............. 6.8 100.9 2.6 20 769 3.8 73
Whatcom, WA.............. 6.9 83.0 2.3 27 683 4.8 35
Yakima, WA............... 7.7 97.7 3.6 9 587 3.3 112
Kanawha, WV.............. 6.1 106.5 -1.2 272 765 3.7 80
Brown, WI................ 6.7 146.8 0.0 190 787 4.5 46
Dane, WI................. 14.0 299.3 0.3 154 859 1.9 217
Milwaukee, WI............ 21.0 494.8 0.9 93 893 2.2 199
Outagamie, WI............ 5.1 101.8 0.3 154 737 2.6 163
Racine, WI............... 4.2 74.1 -1.5 283 784 2.9 140
Waukesha, WI............. 13.3 230.6 -0.8 249 867 0.5 276
Winnebago, WI............ 3.8 89.2 0.9 93 823 -0.1 295
San Juan, PR............. 13.5 284.1 -2.4 (8) 593 3.1 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 334 U.S. counties comprise 71.5 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,
first quarter 2008(2)
Employment Average weekly
wage(3)
Establishments,
first quarter
County by NAICS supersector 2008 Percent Percent
(thousands) March change, Average change,
2008 March weekly first
(thousands) 2007-08(4) wage quarter
2007-08(4)
United States(5)............................. 9,112.7 134,761.1 0.4 $905 2.4
Private industry........................... 8,820.9 112,728.2 0.2 913 2.4
Natural resources and mining............. 125.3 1,731.8 2.7 1,020 10.5
Construction............................. 890.0 7,020.0 -4.1 898 4.8
Manufacturing............................ 361.3 13,529.8 -2.3 1,079 1.9
Trade, transportation, and utilities..... 1,923.2 26,031.1 0.2 745 1.9
Information.............................. 144.9 3,013.5 -0.1 1,469 2.3
Financial activities..................... 872.4 8,005.6 -1.7 1,898 0.2
Professional and business services....... 1,504.2 17,691.9 0.5 1,131 4.2
Education and health services............ 838.9 17,845.8 3.0 767 3.6
Leisure and hospitality.................. 731.2 13,112.5 1.3 360 2.9
Other services........................... 1,194.1 4,444.1 1.0 547 3.4
Government................................. 291.8 22,032.9 1.3 868 2.7
Los Angeles, CA.............................. 425.0 4,229.6 0.4 992 2.1
Private industry........................... 421.0 3,617.0 -0.1 975 2.1
Natural resources and mining............. 0.5 11.4 -5.0 1,745 13.8
Construction............................. 14.0 149.6 -5.5 975 2.6
Manufacturing............................ 14.8 440.0 -3.4 1,084 5.0
Trade, transportation, and utilities..... 54.2 803.6 0.0 792 1.1
Information.............................. 8.5 214.6 2.2 1,723 0.5
Financial activities..................... 24.4 240.6 -4.3 1,807 0.3
Professional and business services....... 42.4 597.5 -1.5 1,165 4.3
Education and health services............ 27.9 492.5 2.9 848 3.4
Leisure and hospitality.................. 26.7 397.9 1.2 528 3.5
Other services........................... 192.2 250.0 1.3 441 4.8
Government................................. 4.0 612.6 3.2 1,088 1.5
Cook, IL..................................... 138.2 2,490.4 -0.5 1,147 2.7
Private industry........................... 136.8 2,178.2 -0.5 1,167 2.9
Natural resources and mining............. 0.1 1.0 -10.7 919 -6.5
Construction............................. 12.1 84.3 -4.9 1,315 9.2
Manufacturing............................ 7.0 229.4 -3.0 1,062 1.8
Trade, transportation, and utilities..... 27.4 465.9 -1.1 838 2.7
Information.............................. 2.5 57.5 0.4 1,820 0.2
Financial activities..................... 15.7 209.6 -2.4 2,905 4.5
Professional and business services....... 28.5 431.2 -0.1 1,403 3.2
Education and health services............ 13.7 373.1 1.9 833 3.3
Leisure and hospitality.................. 11.5 226.6 1.2 412 1.2
Other services........................... 14.2 95.6 0.6 721 2.9
Government................................. 1.4 312.2 -0.5 1,006 1.3
New York, NY................................. 118.5 2,376.0 1.7 2,805 -1.0
Private industry........................... 118.3 1,923.2 1.9 3,229 -1.4
Natural resources and mining............. 0.0 0.2 -4.5 2,375 23.3
Construction............................. 2.3 36.2 8.9 1,596 8.6
Manufacturing............................ 3.0 36.0 -6.3 1,499 -4.1
Trade, transportation, and utilities..... 21.7 246.4 0.8 1,211 0.8
Information.............................. 4.4 134.1 0.7 2,698 5.0
Financial activities..................... 18.7 377.6 0.7 9,840 -3.7
Professional and business services....... 24.7 489.3 1.9 2,343 3.8
Education and health services............ 8.7 293.1 1.5 989 3.9
Leisure and hospitality.................. 11.3 213.9 3.7 766 2.7
Other services........................... 17.6 87.8 1.8 1,105 7.6
Government................................. 0.3 452.8 0.8 1,004 1.7
Harris, TX................................... 96.6 2,046.5 3.4 1,172 3.8
Private industry........................... 96.1 1,791.5 3.5 1,212 3.9
Natural resources and mining............. 1.5 80.0 5.5 3,698 13.5
Construction............................. 6.7 157.0 5.4 1,042 3.6
Manufacturing............................ 4.7 184.1 2.7 1,524 2.8
Trade, transportation, and utilities..... 22.2 426.9 3.3 1,068 1.6
Information.............................. 1.4 32.6 0.0 1,363 -4.0
Financial activities..................... 10.6 120.3 0.9 1,701 1.3
Professional and business services....... 19.3 337.7 3.6 1,293 4.0
Education and health services............ 10.2 216.5 4.6 839 3.1
Leisure and hospitality.................. 7.5 176.8 3.0 384 2.7
Other services........................... 11.4 58.5 1.7 632 5.3
Government................................. 0.5 255.0 2.9 893 2.1
Maricopa, AZ................................. 101.7 1,805.2 -1.4 867 1.3
Private industry........................... 101.0 1,580.7 -1.9 865 1.1
Natural resources and mining............. 0.5 8.7 -4.2 991 22.5
Construction............................. 11.0 144.5 -14.2 884 2.4
Manufacturing............................ 3.6 127.3 -4.6 1,252 5.0
Trade, transportation, and utilities..... 22.4 372.2 -0.1 805 -1.2
Information.............................. 1.7 30.9 3.5 1,164 0.9
Financial activities..................... 13.0 145.0 -4.4 1,238 -0.8
Professional and business services....... 22.6 306.8 -1.9 870 1.6
Education and health services............ 9.9 206.5 4.6 879 3.4
Leisure and hospitality.................. 7.3 187.1 0.6 405 0.0
Other services........................... 7.2 50.5 1.0 577 4.2
Government................................. 0.7 224.5 2.8 880 3.0
Orange, CA................................... 100.1 1,504.9 -1.1 1,019 1.2
Private industry........................... 98.7 1,347.3 -1.4 1,001 0.9
Natural resources and mining............. 0.2 6.5 0.7 563 -0.2
Construction............................. 7.0 94.5 -8.2 1,080 0.7
Manufacturing............................ 5.3 174.2 -2.2 1,188 3.0
Trade, transportation, and utilities..... 17.5 276.2 -0.4 918 -1.2
Information.............................. 1.4 29.7 -2.7 1,544 10.9
Financial activities..................... 11.0 115.7 -13.6 1,722 (6)
Professional and business services....... 19.0 273.9 -1.7 1,124 3.7
Education and health services............ 9.9 146.8 4.2 863 3.0
Leisure and hospitality.................. 7.1 175.1 3.5 397 0.3
Other services........................... 15.3 47.9 1.7 560 0.4
Government................................. 1.4 157.6 1.5 1,170 3.0
Dallas, TX................................... 67.8 1,489.7 2.0 1,119 2.6
Private industry........................... 67.3 1,322.2 1.9 1,145 2.5
Natural resources and mining............. 0.6 8.0 13.6 3,497 20.2
Construction............................. 4.4 84.0 3.7 953 1.6
Manufacturing............................ 3.1 135.4 -3.3 1,320 1.0
Trade, transportation, and utilities..... 15.1 304.5 1.4 1,003 2.8
Information.............................. 1.7 49.6 0.3 1,694 5.2
Financial activities..................... 8.8 144.1 (6) 1,869 2.2
Professional and business services....... 14.7 279.0 3.8 1,236 3.3
Education and health services............ 6.6 148.6 3.6 891 3.7
Leisure and hospitality.................. 5.3 128.8 2.6 509 -2.9
Other services........................... 6.5 38.9 1.7 625 3.1
Government................................. 0.5 167.4 2.6 913 3.4
San Diego, CA................................ 97.8 1,327.6 0.0 945 1.9
Private industry........................... 96.5 1,098.1 -0.5 936 1.7
Natural resources and mining............. 0.8 11.3 0.7 534 4.3
Construction............................. 7.1 78.0 -12.3 985 3.4
Manufacturing............................ 3.2 103.1 -0.2 1,316 5.5
Trade, transportation, and utilities..... 14.4 216.1 -1.7 772 3.8
Information.............................. 1.3 38.2 1.9 1,910 -4.8
Financial activities..................... 9.7 76.4 -6.5 1,329 -2.4
Professional and business services....... 16.1 217.2 -0.2 1,170 3.5
Education and health services............ 8.1 135.2 4.1 840 3.1
Leisure and hospitality.................. 6.9 160.4 2.0 422 1.7
Other services........................... 24.3 55.9 1.4 482 0.6
Government................................. 1.3 229.5 2.7 986 2.2
King, WA..................................... 76.8 1,186.2 2.7 1,125 4.2
Private industry........................... 76.3 1,030.4 2.9 1,142 4.3
Natural resources and mining............. 0.4 3.1 0.4 1,621 -0.5
Construction............................. 6.9 71.3 4.9 1,086 6.7
Manufacturing............................ 2.5 112.5 1.4 1,443 4.9
Trade, transportation, and utilities..... 15.1 220.2 2.1 958 1.9
Information.............................. 1.8 77.8 5.2 2,144 12.8
Financial activities..................... 7.1 76.1 0.3 1,651 -1.8
Professional and business services....... 13.7 189.6 3.3 1,306 3.7
Education and health services............ 6.5 124.4 4.2 837 5.5
Leisure and hospitality.................. 6.2 110.0 3.6 447 -1.1
Other services........................... 16.2 45.4 0.6 599 7.7
Government................................. 0.5 155.8 1.5 1,010 3.0
Miami-Dade, FL............................... 88.2 1,029.9 -1.0 871 1.5
Private industry........................... 87.8 876.6 -1.2 837 1.2
Natural resources and mining............. 0.5 10.8 -6.5 465 -1.5
Construction............................. 6.5 50.9 -11.4 812 1.0
Manufacturing............................ 2.7 46.0 -6.3 774 2.1
Trade, transportation, and utilities..... 23.5 253.7 -0.2 777 1.0
Information.............................. 1.6 20.1 -3.6 1,354 -3.2
Financial activities..................... 10.6 70.5 -3.0 1,483 4.0
Professional and business services....... 17.9 135.6 -4.1 992 0.7
Education and health services............ 9.4 141.7 3.9 796 3.2
Leisure and hospitality.................. 5.9 107.0 0.1 506 1.8
Other services........................... 7.6 37.2 2.5 526 1.3
Government................................. 0.4 153.3 0.2 1,062 2.5
(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, first quarter 2008(2)
Employment Average weekly
wage(4)
Establishments,
first quarter
County(3) 2008 Percent Percent
(thousands) March change, Average change,
2008 March weekly first
(thousands) 2007-08(5) wage quarter
2007-08(5)
United States(6)......... 9,112.7 134,761.1 0.4 $905 2.4
Jefferson, AL............ 19.0 359.3 -1.3 914 4.0
Anchorage Borough, AK.... 8.1 144.4 0.6 916 4.7
Maricopa, AZ............. 101.7 1,805.2 -1.4 867 1.3
Pulaski, AR.............. 14.8 250.4 0.9 791 4.8
Los Angeles, CA.......... 425.0 4,229.6 0.4 992 2.1
Denver, CO............... 25.7 445.9 1.6 1,166 4.2
Hartford, CT............. 25.5 503.7 1.2 1,188 0.3
New Castle, DE........... 18.4 279.9 -0.2 1,130 -0.2
Washington, DC........... 32.5 680.8 1.1 1,488 4.3
Miami-Dade, FL........... 88.2 1,029.9 -1.0 871 1.5
Fulton, GA............... 39.4 749.3 0.6 1,268 0.1
Honolulu, HI............. 24.6 452.8 0.0 800 3.6
Ada, ID.................. 15.3 209.2 -0.5 746 -2.4
Cook, IL................. 138.2 2,490.4 -0.5 1,147 2.7
Marion, IN............... 24.2 575.0 0.3 953 2.5
Polk, IA................. 14.8 271.7 1.6 905 2.3
Johnson, KS.............. 20.2 316.7 1.5 938 2.9
Jefferson, KY............ 22.7 426.6 0.3 849 0.7
East Baton Rouge, LA..... 14.1 265.1 1.4 814 4.9
Cumberland, ME........... 12.4 169.6 0.7 824 5.0
Montgomery, MD........... 33.0 455.7 -0.4 1,238 2.1
Middlesex, MA............ 47.5 814.4 1.3 1,285 3.0
Wayne, MI................ 32.1 724.6 -3.1 1,013 1.7
Hennepin, MN............. 42.9 837.2 0.4 1,188 5.2
Hinds, MS................ 6.4 127.3 -0.1 755 0.8
St. Louis, MO............ 32.8 600.2 -1.1 953 5.4
Yellowstone, MT.......... 5.7 77.1 2.0 695 3.4
Douglas, NE.............. 15.7 317.4 2.0 814 2.6
Clark, NV................ 50.2 917.5 -0.6 854 5.3
Hillsborough, NH......... 12.3 195.0 0.0 982 6.3
Bergen, NJ............... 35.1 447.7 0.1 1,150 4.0
Bernalillo, NM........... 17.6 331.4 -0.2 758 3.7
New York, NY............. 118.5 2,376.0 1.7 2,805 -1.0
Mecklenburg, NC.......... 32.8 571.2 2.1 1,181 -3.4
Cass, ND................. 5.8 98.1 3.8 715 5.6
Cuyahoga, OH............. 37.8 725.6 -1.7 907 -0.4
Oklahoma, OK............. 23.8 424.9 1.3 788 5.2
Multnomah, OR............ 28.3 449.5 1.7 885 2.4
Allegheny, PA............ 35.4 677.2 0.3 952 0.5
Providence, RI........... 18.1 279.3 -2.2 896 4.2
Greenville, SC........... 12.5 240.6 0.9 733 2.9
Minnehaha, SD............ 6.3 114.6 2.5 736 4.5
Shelby, TN............... 20.2 502.6 -0.2 883 5.1
Harris, TX............... 96.6 2,046.5 3.4 1,172 3.8
Salt Lake, UT............ 38.2 587.6 1.9 811 3.0
Chittenden, VT........... 5.9 93.5 -0.5 896 6.0
Fairfax, VA.............. 33.2 585.0 0.8 1,376 0.4
King, WA................. 76.8 1,186.2 2.7 1,125 4.2
Kanawha, WV.............. 6.1 106.5 -1.2 765 3.7
Milwaukee, WI............ 21.0 494.8 0.9 893 2.2
Laramie, WY.............. 3.2 43.1 2.6 704 4.5
San Juan, PR............. 13.5 284.1 -2.4 593 3.1
St. Thomas, VI........... 1.8 24.1 3.1 637 -2.5
(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.
Table 4. Covered(1) establishments, employment, and wages by state,
first quarter 2008(2)
Employment Average weekly
wage(3)
Establishments,
first quarter
State 2008 Percent Percent
(thousands) March change, Average change,
2008 March weekly first
(thousands) 2007-08 wage quarter
2007-08
United States(4)......... 9,112.7 134,761.1 0.4 $905 2.4
Alabama.................. 121.7 1,947.0 -0.2 740 3.2
Alaska................... 21.1 303.0 1.0 866 4.2
Arizona.................. 162.7 2,639.7 -1.3 820 2.4
Arkansas................. 85.2 1,178.4 -0.1 667 4.1
California............... 1,345.1 15,561.5 0.1 1,008 2.1
Colorado................. 178.2 2,300.0 1.7 920 3.6
Connecticut.............. 113.2 1,683.9 1.2 1,254 -0.6
Delaware................. 29.0 418.4 0.5 987 0.1
District of Columbia..... 32.5 680.8 1.1 1,488 4.3
Florida.................. 631.0 7,918.6 -2.2 777 1.8
Georgia.................. 276.4 4,060.9 0.1 847 1.3
Hawaii................... 39.0 628.1 0.2 773 3.5
Idaho.................... 57.6 645.3 0.2 635 0.3
Illinois................. 365.0 5,796.1 0.1 980 2.6
Indiana.................. 160.1 2,858.7 -0.7 757 2.4
Iowa..................... 94.2 1,469.8 0.9 710 3.6
Kansas................... 86.0 1,363.2 1.0 737 2.4
Kentucky................. 112.9 1,794.0 0.1 714 2.4
Louisiana................ 121.7 1,887.3 1.3 765 4.8
Maine.................... 50.8 584.1 0.5 701 3.5
Maryland................. 164.8 2,530.3 0.0 963 2.8
Massachusetts............ 212.7 3,203.1 0.9 1,143 3.3
Michigan................. 259.1 4,058.8 -1.8 857 0.9
Minnesota................ 173.5 2,644.8 0.6 908 4.0
Mississippi.............. 71.0 1,138.2 0.8 634 3.3
Missouri................. 175.2 2,708.0 0.0 768 3.5
Montana.................. 42.9 432.4 0.9 625 4.3
Nebraska................. 59.1 912.2 1.4 687 3.2
Nevada................... 76.7 1,266.3 -1.2 839 4.7
New Hampshire............ 48.9 621.2 0.3 863 3.4
New Jersey............... 276.3 3,939.9 0.5 1,133 3.3
New Mexico............... 54.5 823.8 0.6 717 4.7
New York................. 582.3 8,555.0 1.3 1,399 0.1
North Carolina........... 258.4 4,069.1 0.9 788 1.3
North Dakota............. 25.4 343.3 2.6 652 6.2
Ohio..................... 294.4 5,189.1 -1.0 798 1.0
Oklahoma................. 100.4 1,560.0 1.6 707 4.7
Oregon................... 133.8 1,713.1 0.3 776 2.9
Pennsylvania............. 341.5 5,608.8 0.5 869 2.4
Rhode Island............. 35.9 464.8 -1.5 851 2.3
South Carolina........... 117.4 1,888.3 0.1 695 2.8
South Dakota............. 30.3 389.4 2.0 632 5.2
Tennessee................ 143.4 2,746.4 0.6 761 3.3
Texas.................... 558.7 10,420.8 2.8 903 3.6
Utah..................... 86.7 1,220.2 1.4 718 3.2
Vermont.................. 24.8 300.8 -0.3 735 4.4
Virginia................. 229.2 3,653.5 0.2 918 2.0
Washington............... 218.9 2,928.6 2.1 899 3.7
West Virginia............ 48.8 700.3 0.3 679 4.0
Wisconsin................ 159.7 2,734.3 0.2 760 2.2
Wyoming.................. 24.8 277.2 2.9 779 6.7
Puerto Rico.............. 57.1 1,004.5 -1.6 489 2.7
Virgin Islands........... 3.5 46.5 1.1 708 3.4
(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) Totals for the United States do not include data for Puerto Rico or the
Virgin Islands.
United States Department of Labor
