Technical information:(202) 691-6567 USDL 09-0841
http://www.bls.gov/cew/
For release: 10:00 A.M. EDT
Media contact: (202) 691-5902 Tuesday, July 21, 2009
COUNTY EMPLOYMENT AND WAGES: FOURTH QUARTER 2008
From December 2007 to December 2008, employment declined in 285 of
the 334 largest U.S. counties, according to preliminary data released
today by the Bureau of Labor Statistics of the U.S. Department of
Labor. Elkhart County, Ind., located about 100 miles east of Chicago,
posted the largest percentage decline, with a loss of 17.8 percent
over the year, compared with a national job decrease of 2.3 percent.
Manufacturing sustained the largest employment losses in Elkhart.
Montgomery County, Texas, which is about 20 miles north of Houston,
experienced the largest over-the-year percentage increase in
employment among the largest counties in the U.S., with a gain of 2.7
percent.
St. Louis City, Mo., had the largest over-the-year gain in average
weekly wages in the fourth quarter of 2008, with an increase of 56.8
percent coming predominantly from the professional and business
services and manufacturing supersectors. The U.S. average weekly wage
rose by 2.2 percent over the same time span.
Of the 334 largest counties in the United States (as measured by
2007 annual average employment) 151 had over-the-year percentage
change in employment below the national average (-2.3 percent) in
December 2008; 174 large counties experienced changes above the
national average. The percent change in average weekly wages was
higher than the national average (2.2 percent) in 180 of the largest
U.S. counties, but was below the national average in 137 counties.
Table A. Top 10 large counties ranked by December 2008 employment, December 2007-08 employment
decrease, and December 2007-08 percent decrease in employment
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Employment in large counties
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December 2008 employment | Decrease in employment, | Percent decrease in employment,
(thousands) | December 2007-08 | December 2007-08
| (thousands) |
--------------------------------------------------------------------------------------------------------
| |
United States 133,870.4| United States -3,170.1| United States -2.3
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| |
Los Angeles, Calif. 4,152.9| Los Angeles, Calif. -147.8| Elkhart, Ind. -17.8
Cook, Ill. 2,480.0| Maricopa, Ariz. -107.2| Lee, Fla. -9.2
New York, N.Y. 2,386.4| Orange, Calif. -73.8| Sarasota, Fla. -8.1
Harris, Texas 2,078.1| Cook, Ill. -71.0| Collier, Fla. -8.0
Maricopa, Ariz. 1,741.0| Clark, Nev. -60.0| Marion, Fla. -7.9
Dallas, Texas 1,484.4| Riverside, Calif. -44.7| Macomb, Mich. -7.9
Orange, Calif. 1,451.2| Miami-Dade, Fla. -43.8| Washoe, Nev. -7.9
San Diego, Calif. 1,309.1| Broward, Fla. -43.1| Seminole, Fla. -7.5
King, Wash. 1,175.3| Wayne, Mich. -42.3| Horry, S.C. -7.1
Miami-Dade, Fla. 1,003.9| San Diego, Calif. -39.9| Riverside, Calif. -7.0
| | Genesee, Mich. -7.0
| |
| |
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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 9.2 million employer reports cover 133.9 million full- and
part-time workers.
Large County Employment
In December 2008, national employment, as measured by the QCEW
program, was 133.9 million, down by 2.3 percent from December 2007.
The 334 U.S. counties with 75,000 or more employees accounted for
71.5 percent of total U.S. employment and 77.2 percent of total
wages. These 334 counties had a net job decline of 2,467,500 over the
year, accounting for 77.8 percent of the overall U.S. employment
decrease.
Employment declined in 285 counties from December 2007 to December
2008. The largest percentage decline in employment was in Elkhart,
Ind. (-17.8 percent). Lee, Fla., had the next largest percentage
decline (-9.2 percent), followed by the counties of Sarasota, Fla.
(-8.1 percent), Collier, Fla. (-8.0 percent), and Marion, Fla., Macomb,
Mich., and Washoe, Nev. (-7.9 percent each). The largest decline in
employment levels occurred in Los Angeles, Calif. (-147,800),
followed by the counties of Maricopa, Ariz. (-107,200), Orange,
Calif. (-73,800), Cook, Ill. (-71,000), and Clark, Nev. (-60,000).
(See table A.) Combined employment losses in these five counties over
the year totaled 459,800 or 14.5 percent of the employment decline
for the U.S. as a whole.
Employment rose in 37 of the large counties from December 2007 to
December 2008. More than a third of these growing counties were
located in Texas (13 counties). Neighboring Louisiana had the second
largest number of counties (4) that experienced employment growth.
Montgomery, Texas, had the largest over-the-year percentage increase
in employment (2.7 percent) among the largest counties in the U.S.
Jefferson, Texas, had the next largest increase, 2.5 percent,
followed by the counties of Lubbock, Texas (2.4 percent), Fort Bend,
Texas (2.2 percent), and Orleans, La. (2.1 percent). The largest
gains in the level of employment from December 2007 to December 2008
were recorded in the counties of Harris, Texas (20,000), Orleans, La.
(3,500), Montgomery, Texas (3,400), Bronx, N.Y. (3,200), and
Jefferson, Texas (3,100).
Table B. Top 10 large counties ranked by fourth quarter 2008 average weekly wages, fourth quarter 2007-08
growth in average weekly wages, and fourth 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
fourth quarter 2008 | wage, fourth quarter 2007-08 | weekly wage, fourth
| | quarter 2007-08
--------------------------------------------------------------------------------------------------------
| |
United States $918| United States $20| United States 2.2
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| |
New York, N.Y. $1,856| St. Louis City, Mo. $546| St. Louis City, Mo. 56.8
Fairfield, Conn. 1,596| Mercer, N.J. 89| Clayton, Ga. 9.9
Washington, D.C. 1,570| Clayton, Ga. 77| Calcasieu, La. 9.0
Suffolk, Mass. 1,568| Washington, D.C. 76| East Baton Rouge, La. 8.0
Santa Clara, Calif. 1,566| Madison, Ala. 73| Jefferson, Texas 8.0
Arlington, Va. 1,509| Jefferson, Texas 70| Madison, Ala. 7.9
St. Louis City, Mo. 1,508| Calcasieu, La. 69| Mercer, N.J. 7.7
Somerset, N.J. 1,498| Alexandria City, Va. 69| Lake, Ind. 7.4
San Francisco, Calif. 1,491| East Baton Rouge, La. 65| Bristol, Mass. 7.3
San Mateo, Calif. 1,439| Providence, R.I. 62| Providence, R.I. 7.1
| | Newport News City, Va. 7.1
| |
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Large County Average Weekly Wages
The national average weekly wage in the fourth quarter of 2008 was
$918. Average weekly wages were higher than the national average in
106 of the largest 334 U.S. counties. New York, N.Y., held the top
position among the highest-paid large counties with an average weekly
wage of $1,856. Fairfield, Conn., was second with an average weekly
wage of $1,596, followed by Washington, D.C. ($1,570), Suffolk, Mass.
($1,568), and Santa Clara, Calif. ($1,566). (See table B.) Over the
year, the national average weekly wage rose by 2.2 percent. Among the
largest counties, St. Louis City, Mo., led the nation in growth in
average weekly wages with an increase of 56.8 percent from the fourth
quarter of 2007. Clayton, Ga., was second with growth of 9.9 percent,
followed by the counties of Calcasieu, La. (9.0 percent), and East
Baton Rouge, La. and Jefferson, Texas (8.0 percent each).
Average weekly wages are affected by the number of high-paying and
low-paying jobs in an industry. The 2.2 percent over-the-year gain in
average weekly wages for the nation is partially due to large
employment declines in several industries. The largest over-the-year
December percent employment declines were in construction (-10.2
percent), manufacturing (-6.2 percent), professional and business
services (-4.1 percent), and trade, transportation, and utilities
(-3.5 percent). (See table 2.) Trade, transportation and utilities
posted the largest number of jobs lost (-957,500) followed by
manufacturing (-850,400), construction (-749,900), and professional
and business services (-735,400). Among these industries, average
weekly wage growth was strongest in construction (4.9 percent), and
professional and business services (3.7 percent). (See Technical
Note.)
There were 228 counties with an average weekly wage below the
national average in the fourth quarter of 2008. The lowest average
weekly wage was reported in Hidalgo, Texas ($574), followed by the
counties of Horry, S.C. ($581), Cameron, Texas ($584), Webb, Texas
($600), and Yakima, Wash. ($624). (See table 1.) Forty-three large
counties experienced over-the-year declines in average weekly wages.
Pulaski, Ark., had the largest decrease (-14.3 percent), followed by
the counties of Lake, Ill. (-9.9 percent), Santa Clara, Calif. (-7.8
percent), Douglas, Colo. (-5.9 percent), and San Mateo, Calif. (-5.4
percent).
Ten Largest U.S. Counties
Nine of the 10 largest counties (based on 2007 annual average
employment levels) experienced over-the-year percent declines in
employment in December 2008. Maricopa, Ariz., experienced the largest
decline in employment among the 10 largest counties with a 5.8
percent decrease. Within Maricopa, every private industry group
except education and health services experienced employment declines,
with construction experiencing the largest decline, -25.3 percent.
(See table 2.) Orange, Calif., had the next largest decline in
employment, -4.8 percent, followed by Miami-Dade, Fla. (-4.2
percent). Harris, Texas, experienced the only percentage gain in
employment (1.0 percent) among the 10 largest counties. Within Harris
County, the largest gains in employment were in natural resources and
mining (7.1 percent) and education and health services (3.1 percent).
Dallas, Texas, had the smallest decrease in employment, -1.2 percent,
followed by New York, N.Y. (-1.3 percent).
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 4.0 percent. Within
King County, average weekly wages increased the most in the natural
resources and mining industry (11.8 percent). Miami-Dade, Fla., and
Harris, Texas, tied for second in wage growth with a gain of 2.6
percent each. The only wage decrease occurred in New York, N.Y. (-0.6
percent). Dallas, Texas, had the smallest increase in wages, 1.1
percent, followed by Orange, Calif. (1.4 percent).
Largest County by State
Table 3 shows December 2008 employment and the 2008 fourth quarter
average weekly wage in the largest county in each state, which is
based on 2007 annual average employment levels. The employment levels
in the counties in table 3 in December 2008 ranged from approximately
4.15 million in Los Angeles County, Calif., to 43,800 in Laramie
County, Wyo. The highest average weekly wage of these counties was in
New York, N.Y. ($1,856), while the lowest average weekly wage was in
Yellowstone, Mont. ($738).
For More Information
The tables included in this release contain data for the nation and
for the 334 counties with annual average employment levels of 75,000
or more in 2007. December 2008 employment and 2008 fourth-quarter
average weekly wages for all states are provided in table 4 of this
release.
For additional information about the quarterly employment and wages
data, please read the Technical Note. Final data for all states,
metropolitan statistical areas, counties, and the nation through the
fourth quarter of 2007 are available on the BLS Web site at
http://www.bls.gov/cew/. Updated data for first, second, and third
quarter 2008, as well as preliminary data for fourth quarter 2008 and
preliminary annual averages for 2008, will be available later online.
Additional information about the QCEW data 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 2009 is
scheduled to be released on Friday, October 16, 2009.
Technical Note
These data are the product of a federal-state cooperative program, the Quarterly
Census of Employment and Wages (QCEW) program, also known as the ES-202 program. The
data are derived from summaries of employment and total pay of workers covered by
state and federal unemployment insurance (UI) legislation and provided by State
Workforce Agencies (SWAs). The summaries are a result of the administration of state
unemployment insurance programs that require most employers to pay quarterly taxes
based on the employment and wages of workers covered by UI. QCEW data in this re-
lease are based on the 2007 North American Industry Classification System. Data for
2008 are preliminary and subject to revision.
For purposes of this release, large counties are defined as having employment lev-
els of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are provided,
but not used in calculating U.S. averages, rankings, or in the analysis in the text.
Each year, these large counties are selected on the basis of the preliminary annual
average of employment for the previous year. The 335 counties presented in this re-
lease were derived using 2007 preliminary annual averages of employment. For 2008
data, six counties have been added to the publication tables: Shelby, Ala., Boone,
Ky., St. Tammany, La., Yellowstone, Mont., Warren, Ohio, and Potter, Texas. These
counties will be included in all 2008 quarterly releases. The counties in table 2
are selected and sorted each year based on the annual average employment from the
preceding year.
The preliminary QCEW data presented in this release may differ from data released
by the individual states. These potential differences result from the states' con-
tinuing receipt of UI data over time and ongoing review and editing. The individual
states determine their data release timetables.
Differences between QCEW, BED, and CES employment measures
The Bureau publishes three different establishment-based employment measures for
any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED),
and Current Employment Statistics (CES)--makes use of the quarterly UI employment
reports in producing data; however, each measure has a somewhat different universe
coverage, estimation procedure, and publication product.
Differences in coverage and estimation methods can result in somewhat different
measures of employment change over time. It is important to understand program dif-
ferences and the intended uses of the program products. (See table.) Additional in-
formation on each program can be obtained from the program Web sites shown in the
table.
Summary of Major Differences between QCEW, BED, and CES Employment Measures
---------------------------------------------------------------------------------
| QCEW | BED | CES
-----------|---------------------|----------------------|------------------------
Source |--Count of UI admini-|--Count of longitudi- |--Sample survey:
| strative records | nally-linked UI ad- | 400,000 establish-
| submitted by 9.1 | ministrative records| ments
| million establish- | submitted by 7.1 |
| ments | million private-sec-|
| | tor employers |
-----------|---------------------|----------------------|------------------------
Coverage |--UI and UCFE cover- |--UI coverage, exclud-|Nonfarm wage and sal-
| age, including all | ing government, pri-| ary jobs:
| employers subject | vate households, and|--UI coverage, exclud-
| to state and fed- | establishments with | ing agriculture, pri-
| eral UI laws | zero employment | vate households, and
| | | self-employed workers
| | |--Other employment, in-
| | | cluding railroads,
| | | religious organiza-
| | | tions, and other non-
| | | UI-covered jobs
-----------|---------------------|----------------------|------------------------
Publication|--Quarterly |--Quarterly |--Monthly
frequency | -7 months after the| -8 months after the | -Usually first Friday
| end of each quar- | end of each quarter| of following month
| ter | |
-----------|---------------------|----------------------|------------------------
Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam-
file | and publishes each | quarter to longitu- | pling frame and annu-
| new quarter of UI | dinal database and | ally realigns (bench-
| data | directly summarizes | marks) sample esti-
| | gross job gains and | mates to first quar-
| | losses | ter UI levels
-----------|---------------------|----------------------|------------------------
Principal |--Provides a quarter-|--Provides quarterly |--Provides current month-
products | ly and annual uni- | employer dynamics | ly estimates of employ-
| verse count of es- | data on establish- | ment, hours, and earn-
| tablishments, em- | ment openings, clos-| ings at the MSA, state,
| ployment, and wages| ings, expansions, | and national level by
| at the county, MSA,| and contractions at | industry
| state, and national| the national level |
| levels by detailed | by NAICS supersec- |
| industry | tors and by size of |
| | firm, and at the |
| | state private-sector|
| | total level |
| |--Future expansions |
| | will include data |
| | with greater indus- |
| | try detail and data |
| | at the county and |
| | MSA level |
-----------|---------------------|----------------------|------------------------
Principal |--Major uses include:|--Major uses include: |--Major uses include:
uses | -Detailed locality | -Business cycle | -Principal national
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -Analysis of employ-| cators
| surveys | ment expansion and |
| | contraction by size|
| | of firm |
| | |
-----------|---------------------|----------------------|------------------------
Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/
Web sites | | |
---------------------------------------------------------------------------------
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. QCEW employment and wage data are derived from mi-
crodata summaries of 9.0 million employer reports of employment and wages submitted
by states to the BLS in 2007. 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. 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) represented 96.2
percent of civilian wage and salary employment. Covered workers received $6.018
trillion in pay, representing 94.6 percent of the wage and salary component of per-
sonal income and 43.6 percent of the gross domestic product.
Major exclusions from UI coverage include self-employed workers, most agricultural
workers on small farms, all members of the Armed Forces, elected officials in most
states, most employees of railroads, some domestic workers, most student workers at
schools, and employees of certain small nonprofit organizations.
State and federal UI laws change periodically. These changes may have an impact on
the employment and wages reported by employers covered under the UI program. Cover-
age changes may affect the over-the-year comparisons presented in this news release.
Concepts and methodology
Monthly employment is based on the number of workers who worked during or received
pay for the pay period including the 12th of the month. With few exceptions, all em-
ployees of covered firms are reported, including production and sales workers, cor-
poration officials, executives, supervisory personnel, and clerical workers. Work-
ers on paid vacations and part-time workers also are included.
Average weekly wage values are calculated by dividing quarterly total wages by the
average of the three monthly employment levels (all employees, as described above)
and dividing the result by 13, for the 13 weeks in the quarter. These calculations
are made using unrounded employment and wage values. The average wage values that
can be calculated using rounded data from the BLS database may differ from the aver-
ages reported. Included in the quarterly wage data are non-wage cash payments such
as bonuses, the cash value of meals and lodging when supplied, tips and other gra-
tuities, and, in some states, employer contributions to certain deferred compensa-
tion plans such as 401(k) plans and stock options. Over-the-year comparisons of av-
erage weekly wages may reflect fluctuations in average monthly employment and/or to-
tal quarterly wages between the current quarter and prior year levels.
Average weekly wages are affected by the ratio of full-time to part-time workers
as well as the number of individuals in high-paying and low-paying occupations and
the incidence of pay periods within a quarter. For instance, the average weekly wage
of the work force could increase significantly when there is a large decline in the
number of employees that had been receiving below-average wages. Wages may include
payments to workers not present in the employment counts because they did not work
during the pay period including the 12th of the month. When comparing average weekly
wage levels between industries, states, or quarters, these factors should be taken
into consideration.
Federal government pay levels are subject to periodic, sometimes large, fluctua-
tions due to a calendar effect that consists of some quarters having more pay peri-
ods than others. Most federal employees are paid on a biweekly pay schedule. As a
result of this schedule, in some quarters, federal wages contain payments for six
pay periods, while in other quarters their wages include payments for seven pay pe-
riods. Over-the-year comparisons of average weekly wages may reflect this calendar
effect. Higher growth in average weekly wages may be attributed, in part, to a com-
parison of quarterly wages for the current year, which include seven pay periods,
with year-ago wages that reflect only six pay periods. An opposite effect will occur
when wages in the current period, which contain six pay periods, are compared with
year-ago wages that include seven pay periods. The effect on over-the-year pay com-
parisons can be pronounced in federal government due to the uniform nature of fed-
eral payroll processing. This pattern may exist in private sector pay; however, be-
cause there are more pay period types (weekly, biweekly, semimonthly, monthly) it is
less pronounced. The effect is most visible in counties with large concentrations of
federal employment.
In order to ensure the highest possible quality of data, states verify with em-
ployers and update, if necessary, the industry, location, and ownership classifica-
tion of all establishments on a 4-year cycle. Changes in establishment classifica-
tion codes resulting from this process are introduced with the data reported for the
first quarter of the year. Changes resulting from improved employer reporting also
are introduced in the first quarter.
QCEW data are not designed as a time series. QCEW data are simply the sums of in-
dividual establishment records and reflect the number of establishments that exist
in a county or industry at a point in time. Establishments can move in or out of a
county or industry for a number of reasons--some reflecting economic events, others
reflecting administrative changes. For example, economic change would come from a
firm relocating into the county; administrative change would come from a company
correcting its county designation.
The over-the-year changes of employment and wages presented in this release have
been adjusted to account for most of the administrative corrections made to the un-
derlying establishment reports. This is done by modifying the prior-year levels used
to calculate the over-the-year changes. Percent changes are calculated using an ad-
justed version of the final 2007 quarterly data as the base data. The adjusted
prior-year levels used to calculate the over-the-year percent change in employment
and wages are not published. These adjusted prior-year levels do not match the unad-
justed data maintained on the BLS Web site. Over-the-year change calculations based
on data from the Web site, or from data published in prior BLS news releases, may
differ substantially from the over-the-year changes presented in this news release.
The adjusted data used to calculate the over-the-year change measures presented in
this release account for most of the administrative changes--those occurring when
employers update the industry, location, and ownership information of their estab-
lishments. The most common adjustments for administrative change are the result of
updated information about the county location of individual establishments. Included
in these adjustments are administrative changes involving the classification of es-
tablishments that were previously reported in the unknown or statewide county or un-
known industry categories. Beginning with the first quarter of 2008, adjusted data
will also account for administrative changes caused by multi-unit employers who
start reporting for each individual establishment rather than as a single entity.
The adjusted data used to calculate the over-the-year change measures presented in
any County Employment and Wages news release are valid for comparisons between the
starting and ending points (a 12-month period) used in that particular release. Com-
parisons may not be valid for any time period other than the one featured in a re-
lease even if the changes were calculated using adjusted data.
County definitions are assigned according to Federal Information Processing Stan-
dards Publications (FIPS PUBS) as issued by the National Institute of Standards and
Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of
the Information Technology Management Reform Act of 1996 and the Computer Security
Act of 1987, Public Law 104-106. Areas shown as counties include those designated as
independent cities in some jurisdictions and, in Alaska, those designated as census
areas where counties have not been created. County data also are presented for the
New England states for comparative purposes even though townships are the more com-
mon designation used in New England (and New Jersey). The regions referred to in
this release are defined as census regions.
Additional statistics and other information
An annual bulletin, Employment and Wages, features comprehensive information by
detailed industry on establishments, employment, and wages for the nation and all
states. The 2007 edition of this bulletin contains selected data produced by Busi-
ness Employment Dynamics (BED) on job gains and losses, as well as selected data
from the first quarter 2008 version of this news release. Tables and additional con-
tent from the 2007 Employment and Wages Annual Bulletin are now available online at
http://www.bls.gov/cew/cewbultn07.htm. These tables present final 2007 annual aver-
ages. The tables will also be included on the CD which accompanies the hardcopy
version of the Annual Bulletin. Employment and Wages Annual Averages, 2007 is
available for sale as a chartbook from the United States Government Printing Office,
Superintendent of Documents, P.O. Box 371954, Pittsburgh, PA 15250, telephone (866)
512-1800, outside Washington, D.C. Within Washington, D.C., the telephone number is
(202) 512-1800. The fax number is (202) 512-2104.
News releases on quarterly measures of gross job flows also are available upon re-
quest from the Division of Administrative Statistics and Labor Turnover (Business
Employment Dynamics), telephone (202) 691-6467; (http://www.bls.gov/bdm/); (e-mail:
BDMInfo@bls.gov).
Information in this release will be made available to sensory impaired individuals
upon request. Voice phone: (202) 691-5200; TDD message referral phone number: 1-800-
877-8339.
Table 1. Covered(1) establishments, employment, and wages in the 335 largest counties,
fourth quarter 2008(2)
Employment Average weekly wage(4)
Establishments,
County(3) fourth quarter Percent Ranking Percent Ranking
2008 December change, by Average change, by
(thousands) 2008 December percent weekly fourth percent
(thousands) 2007-08(5) change wage quarter change
2007-08(5)
United States(6)......... 9,177.5 133,870.4 -2.3 - $918 2.2 -
Jefferson, AL............ 19.0 355.3 -3.3 234 922 2.2 181
Madison, AL.............. 9.0 182.5 -0.4 51 997 7.9 6
Mobile, AL............... 10.2 174.5 -1.6 118 806 5.1 31
Montgomery, AL........... 6.7 135.4 -3.8 261 824 5.4 27
Shelby, AL............... 5.0 75.5 -2.1 153 842 -1.2 304
Tuscaloosa, AL........... 4.5 86.0 -1.8 131 783 2.1 188
Anchorage Borough, AK.... 8.2 148.2 1.5 8 969 4.9 35
Maricopa, AZ............. 103.6 1,741.0 -5.8 305 892 2.1 188
Pima, AZ................. 21.3 366.7 -3.4 241 805 4.5 48
Benton, AR............... 5.6 94.7 -2.2 160 844 6.3 15
Pulaski, AR.............. 15.2 250.3 -1.2 92 847 -14.3 324
Washington, AR........... 5.8 90.9 -2.4 177 747 2.2 181
Alameda, CA.............. 54.4 669.9 -4.0 267 1,161 0.1 277
Butte, CA................ 8.1 74.4 -3.1 222 698 4.6 45
Contra Costa, CA......... 30.4 335.8 -3.6 252 1,135 1.7 209
Fresno, CA............... 30.9 345.9 -1.6 118 737 1.7 209
Kern, CA................. 18.5 285.6 -1.2 92 794 4.5 48
Los Angeles, CA.......... 433.9 4,152.9 -3.4 241 1,075 1.8 204
Marin, CA................ 12.1 108.6 -2.0 145 1,152 -2.0 310
Monterey, CA............. 13.0 152.3 -3.4 241 801 3.4 95
Orange, CA............... 102.7 1,451.2 -4.8 286 1,043 1.4 235
Placer, CA............... 11.0 130.5 -5.9 311 892 1.8 204
Riverside, CA............ 47.5 593.2 -7.0 317 745 2.2 181
Sacramento, CA........... 54.7 610.8 -3.6 252 1,006 3.2 107
San Bernardino, CA....... 49.8 640.3 -5.8 305 788 3.0 122
San Diego, CA............ 100.0 1,309.1 -3.0 208 981 2.0 192
San Francisco, CA........ 52.7 574.0 -0.9 76 1,491 -2.4 314
San Joaquin, CA.......... 18.1 214.5 -4.4 282 796 3.2 107
San Luis Obispo, CA...... 9.8 101.8 -2.8 196 765 1.7 209
San Mateo, CA............ 24.2 342.4 -1.6 118 1,439 -5.4 320
Santa Barbara, CA........ 14.4 180.5 -2.0 145 868 1.6 218
Santa Clara, CA.......... 61.2 901.1 -1.7 126 1,566 -7.8 322
Santa Cruz, CA........... 9.2 90.0 -4.2 273 821 -2.3 312
Solano, CA............... 10.2 124.8 -3.1 222 903 3.9 71
Sonoma, CA............... 19.0 185.8 -4.9 291 896 3.0 122
Stanislaus, CA........... 15.1 166.7 -4.3 278 759 3.8 77
Tulare, CA............... 9.7 147.6 -3.0 208 651 3.7 81
Ventura, CA.............. 23.7 310.4 -3.4 241 926 -5.1 318
Yolo, CA................. 6.0 99.1 -2.2 160 883 3.2 107
Adams, CO................ 9.2 152.4 -2.2 160 840 1.3 237
Arapahoe, CO............. 19.3 279.7 -2.2 160 1,054 -2.8 315
Boulder, CO.............. 12.9 161.1 -0.9 76 1,047 -1.5 308
Denver, CO............... 25.6 445.0 -1.5 109 1,111 -1.3 305
Douglas, CO.............. 9.5 93.8 0.5 24 933 -5.9 321
El Paso, CO.............. 17.3 241.7 -2.9 204 834 3.9 71
Jefferson, CO............ 18.5 210.9 -0.8 70 926 2.0 192
Larimer, CO.............. 10.4 129.9 -0.4 51 837 3.1 114
Weld, CO................. 6.0 82.3 -0.9 76 765 2.5 159
Fairfield, CT............ 33.1 420.2 -2.2 160 1,596 1.1 247
Hartford, CT............. 25.6 504.5 -1.5 109 1,111 1.0 253
New Haven, CT............ 22.7 366.4 -2.2 160 978 3.3 101
New London, CT........... 7.0 130.1 -0.8 70 910 -0.4 290
New Castle, DE........... 18.3 278.7 -3.7 255 1,055 2.3 169
Washington, DC........... 34.4 687.5 0.3 29 1,570 5.1 31
Alachua, FL.............. 6.8 121.7 -2.0 145 740 -0.1 282
Brevard, FL.............. 15.0 195.7 -5.8 305 856 3.9 71
Broward, FL.............. 65.6 729.6 -5.6 302 874 0.8 259
Collier, FL.............. 12.6 125.4 -8.0 324 811 (7) -
Duval, FL................ 27.7 455.5 -4.3 278 874 0.8 259
Escambia, FL............. 8.1 122.9 -5.8 305 720 2.1 188
Hillsborough, FL......... 38.3 609.9 -6.1 312 872 2.7 143
Lake, FL................. 7.6 83.6 -5.5 300 665 -0.9 300
Lee, FL.................. 20.1 203.3 -9.2 326 760 -0.3 286
Leon, FL................. 8.3 141.9 -3.3 234 783 0.5 268
Manatee, FL.............. 9.4 114.1 -4.3 278 691 -0.7 297
Marion, FL............... 8.6 97.6 -7.9 321 657 3.5 88
Miami-Dade, FL........... 86.8 1,003.9 -4.2 273 924 2.6 151
Okaloosa, FL............. 6.2 77.1 -3.8 261 735 2.8 139
Orange, FL............... 36.3 678.3 -4.6 285 829 1.1 247
Palm Beach, FL........... 51.4 527.4 -6.3 314 914 1.6 218
Pasco, FL................ 10.4 100.9 -3.3 234 672 3.1 114
Pinellas, FL............. 32.1 410.9 -6.2 313 808 1.9 200
Polk, FL................. 12.8 199.3 -5.4 298 706 1.7 209
Sarasota, FL............. 15.4 144.4 -8.1 325 783 1.4 235
Seminole, FL............. 14.9 168.9 -7.5 320 789 -0.3 286
Volusia, FL.............. 14.2 158.2 -6.4 315 665 1.5 224
Bibb, GA................. 4.8 84.1 -1.0 80 716 1.8 204
Chatham, GA.............. 7.9 133.8 -3.3 234 799 4.4 52
Clayton, GA.............. 4.5 111.1 -4.0 267 856 9.9 2
Cobb, GA................. 21.2 312.7 -4.2 273 959 3.1 114
De Kalb, GA.............. 18.1 294.0 -3.1 222 936 1.6 218
Fulton, GA............... 39.9 732.2 -3.4 241 1,183 1.0 253
Gwinnett, GA............. 24.5 310.9 -5.3 297 894 -0.8 299
Muscogee, GA............. 4.9 94.7 -2.7 193 721 1.5 224
Richmond, GA............. 4.8 101.2 -1.4 104 770 5.5 23
Honolulu, HI............. 24.8 449.5 -2.4 177 850 3.8 77
Ada, ID.................. 15.0 202.9 -5.0 293 814 -1.1 301
Champaign, IL............ 4.2 92.0 -0.6 63 777 5.7 19
Cook, IL................. 141.0 2,480.0 -2.8 196 1,118 1.5 224
Du Page, IL.............. 36.2 586.1 -3.5 248 1,059 0.2 273
Kane, IL................. 12.8 203.3 -4.9 291 836 1.7 209
Lake, IL................. 21.2 328.0 -2.5 183 1,143 -9.9 323
McHenry, IL.............. 8.5 100.6 -3.1 222 784 -0.4 290
McLean, IL............... 3.7 85.9 -0.3 47 836 2.7 143
Madison, IL.............. 6.0 95.9 -0.6 63 770 5.5 23
Peoria, IL............... 4.8 105.3 0.0 38 869 3.5 88
Rock Island, IL.......... 3.5 79.4 -1.2 92 1,082 2.0 192
St. Clair, IL............ 5.5 96.8 -1.9 139 755 4.4 52
Sangamon, IL............. 5.2 128.8 -1.1 84 897 3.9 71
Will, IL................. 13.9 194.5 -2.0 145 824 3.5 88
Winnebago, IL............ 7.0 134.3 -3.0 208 775 3.1 114
Allen, IN................ 9.1 180.0 -3.0 208 748 -1.1 301
Elkhart, IN.............. 5.0 101.3 -17.8 327 686 -3.9 316
Hamilton, IN............. 7.8 111.3 -1.1 84 852 -1.3 305
Lake, IN................. 10.4 193.2 -2.6 189 826 7.4 8
Marion, IN............... 24.3 571.8 -2.8 196 913 2.8 139
St. Joseph, IN........... 6.1 121.0 -4.2 273 761 3.5 88
Tippecanoe, IN........... 3.4 76.8 -0.6 63 773 5.3 29
Vanderburgh, IN.......... 4.8 107.8 -0.4 51 767 5.5 23
Linn, IA................. 6.3 127.2 1.0 14 896 2.3 169
Polk, IA................. 14.9 273.7 -1.1 84 904 2.4 163
Scott, IA................ 5.2 88.8 -0.4 51 751 1.3 237
Johnson, KS.............. 20.7 316.0 -1.1 84 949 1.3 237
Sedgwick, KS............. 12.3 261.6 0.3 29 846 5.2 30
Shawnee, KS.............. 4.9 96.4 0.7 22 753 0.9 255
Wyandotte, KS............ 3.2 80.9 0.2 35 854 2.2 181
Boone, KY................ 3.4 74.5 -2.6 189 800 4.8 39
Fayette, KY.............. 9.0 178.1 (7) - 832 (7) -
Jefferson, KY............ 22.0 423.8 -3.3 234 871 1.5 224
Caddo, LA................ 7.5 125.3 -1.9 139 762 1.7 209
Calcasieu, LA............ 5.1 87.9 0.6 23 832 9.0 3
East Baton Rouge, LA..... 14.8 265.9 0.3 29 874 8.0 4
Jefferson, LA............ 14.7 200.5 -1.5 109 876 4.0 67
Lafayette, LA............ 9.1 137.4 0.5 24 911 4.8 39
Orleans, LA.............. 11.6 173.6 2.1 5 1,002 4.2 62
St. Tammany, LA.......... 7.5 75.3 -2.2 160 749 2.6 151
Cumberland, ME........... 12.2 173.4 -2.3 175 822 3.0 122
Anne Arundel, MD......... 14.5 233.3 -1.4 104 963 3.8 77
Baltimore, MD............ 21.5 374.5 -2.7 193 963 0.7 264
Frederick, MD............ 6.0 93.4 -3.1 222 890 3.1 114
Harford, MD.............. 5.6 82.6 (7) - 846 (7) -
Howard, MD............... 8.7 147.5 (7) - 1,073 3.9 71
Montgomery, MD........... 32.9 460.3 -1.3 100 1,219 1.9 200
Prince Georges, MD....... 15.7 312.5 -3.0 208 993 2.5 159
Baltimore City, MD....... 14.0 340.4 -1.6 118 1,112 1.5 224
Barnstable, MA........... 9.1 84.2 -3.2 230 813 3.2 107
Bristol, MA.............. 15.3 215.0 -3.0 208 854 7.3 9
Essex, MA................ 20.9 298.2 -1.5 109 976 3.3 101
Hampden, MA.............. 14.5 199.2 -1.4 104 867 6.4 13
Middlesex, MA............ 47.8 826.2 -0.4 51 1,296 -1.1 301
Norfolk, MA.............. 24.2 326.4 -1.1 84 1,139 2.3 169
Plymouth, MA............. 13.7 175.9 -1.9 139 894 3.5 88
Suffolk, MA.............. 21.8 593.4 -0.5 58 1,568 1.3 237
Worcester, MA............ 20.7 318.5 -2.2 160 931 2.2 181
Genesee, MI.............. 7.8 134.3 -7.0 317 804 0.2 273
Ingham, MI............... 6.8 158.3 -3.8 261 886 3.4 95
Kalamazoo, MI............ 5.6 112.1 -4.1 270 855 7.0 12
Kent, MI................. 14.3 323.8 -5.5 300 832 3.2 107
Macomb, MI............... 17.7 291.2 -7.9 321 966 5.1 31
Oakland, MI.............. 39.3 660.7 -5.4 298 1,096 4.3 58
Ottawa, MI............... 5.7 102.9 -5.2 295 794 4.3 58
Saginaw, MI.............. 4.4 81.8 -5.8 305 776 3.6 86
Washtenaw, MI............ 8.1 187.3 -3.8 261 971 1.5 224
Wayne, MI................ 32.1 709.8 -5.6 302 1,032 4.2 62
Anoka, MN................ 7.8 113.2 -3.7 255 839 1.1 247
Dakota, MN............... 10.6 172.8 -2.4 177 898 1.6 218
Hennepin, MN............. 42.5 837.8 -2.4 177 1,146 2.7 143
Olmsted, MN.............. 3.6 89.5 -1.8 131 975 6.4 13
Ramsey, MN............... 15.3 328.9 -1.3 100 980 2.3 169
St. Louis, MN............ 5.9 96.0 -1.9 139 759 4.4 52
Stearns, MN.............. 4.5 82.2 -1.2 92 700 3.6 86
Harrison, MS............. 4.6 85.0 -3.1 222 702 3.4 95
Hinds, MS................ 6.4 127.6 -1.8 131 809 3.3 101
Boone, MO................ 4.5 82.5 -0.7 69 691 3.1 114
Clay, MO................. 5.1 88.2 -3.4 241 821 -0.2 285
Greene, MO............... 8.2 155.6 -2.1 153 685 3.2 107
Jackson, MO.............. 18.8 368.6 -0.9 76 926 3.8 77
St. Charles, MO.......... 8.2 122.0 -3.0 208 733 -0.5 293
St. Louis, MO............ 32.8 600.5 -3.0 208 990 1.3 237
St. Louis City, MO....... 8.5 231.2 -1.2 92 1,508 56.8 1
Yellowstone, MT.......... 5.8 78.2 -0.2 45 738 1.2 245
Douglas, NE.............. 16.1 322.8 0.0 38 842 -2.1 311
Lancaster, NE............ 8.2 158.5 -0.1 43 726 3.7 81
Clark, NV................ 51.0 870.0 -6.5 316 856 -2.3 312
Washoe, NV............... 14.7 201.6 -7.9 321 867 0.0 280
Hillsborough, NH......... 12.4 195.9 -2.6 189 1,062 1.8 204
Rockingham, NH........... 11.0 136.1 -2.3 175 906 1.6 218
Atlantic, NJ............. 7.0 139.3 -4.0 267 818 1.7 209
Bergen, NJ............... 34.6 450.4 -2.5 183 1,188 0.4 270
Burlington, NJ........... 11.5 198.2 -3.9 266 968 3.0 122
Camden, NJ............... 13.1 205.9 -2.8 196 1,008 5.5 23
Essex, NJ................ 21.5 359.7 -2.5 183 1,170 3.3 101
Gloucester, NJ........... 6.4 104.0 -1.3 100 855 2.0 192
Hudson, NJ............... 14.1 237.1 -2.2 160 1,205 2.3 169
Mercer, NJ............... 11.3 230.4 -0.6 63 1,249 7.7 7
Middlesex, NJ............ 22.0 398.0 -3.7 255 1,148 2.2 181
Monmouth, NJ............. 20.9 254.6 -2.8 196 1,016 1.3 237
Morris, NJ............... 18.1 285.3 -2.9 204 1,351 2.5 159
Ocean, NJ................ 12.5 146.3 -2.5 183 792 2.9 131
Passaic, NJ.............. 12.6 175.4 -3.7 255 974 4.1 65
Somerset, NJ............. 10.3 173.1 -2.1 153 1,498 2.9 131
Union, NJ................ 15.1 230.8 -3.1 222 1,166 2.6 151
Bernalillo, NM........... 17.8 329.9 -2.0 145 812 3.0 122
Albany, NY............... 10.0 228.3 -1.4 104 945 4.9 35
Bronx, NY................ 16.1 230.0 1.4 10 889 (7) -
Broome, NY............... 4.5 95.5 -1.1 84 727 4.3 58
Dutchess, NY............. 8.3 116.1 -2.2 160 904 3.4 95
Erie, NY................. 23.7 464.1 -0.5 58 794 3.0 122
Kings, NY................ 46.8 488.2 0.3 29 816 3.3 101
Monroe, NY............... 18.1 382.4 -0.8 70 859 1.1 247
Nassau, NY............... 52.5 611.8 -1.7 126 1,049 1.5 224
New York, NY............. 118.9 2,386.4 -1.3 100 1,856 -0.6 294
Oneida, NY............... 5.3 112.0 -0.5 58 720 5.6 20
Onondaga, NY............. 12.8 252.9 -1.6 118 849 0.7 264
Orange, NY............... 10.0 132.6 -1.5 109 778 4.4 52
Queens, NY............... 43.7 507.0 -0.3 47 926 3.7 81
Richmond, NY............. 8.7 95.5 -0.2 45 835 4.0 67
Rockland, NY............. 9.9 117.5 -1.7 126 1,002 (7) -
Saratoga, NY............. 5.4 76.5 -2.2 160 762 3.4 95
Suffolk, NY.............. 50.6 626.9 -2.2 160 1,037 (7) -
Westchester, NY.......... 36.5 424.3 -2.2 160 1,234 -1.4 307
Buncombe, NC............. 8.2 115.9 -2.1 153 724 1.7 209
Catawba, NC.............. 4.6 83.8 -4.8 286 695 1.5 224
Cumberland, NC........... 6.3 121.9 1.0 14 711 4.9 35
Durham, NC............... 7.2 185.0 (7) - 1,131 (7) -
Forsyth, NC.............. 9.3 184.8 -2.5 183 826 2.7 143
Guilford, NC............. 14.8 275.4 -3.6 252 797 2.0 192
Mecklenburg, NC.......... 33.4 567.7 -1.7 126 1,016 1.5 224
New Hanover, NC.......... 7.5 101.0 -4.8 286 755 2.4 163
Wake, NC................. 29.2 448.8 -2.1 153 915 1.8 204
Cass, ND................. 5.9 100.7 1.5 8 778 2.1 188
Butler, OH............... 7.4 145.0 -3.8 261 788 1.3 237
Cuyahoga, OH............. 37.7 724.7 -3.0 208 926 2.0 192
Franklin, OH............. 30.0 678.4 -2.2 160 879 3.7 81
Hamilton, OH............. 24.0 514.3 -1.5 109 980 2.3 169
Lake, OH................. 6.7 99.0 -3.0 208 755 2.3 169
Lorain, OH............... 6.3 95.7 -5.0 293 742 3.2 107
Lucas, OH................ 10.7 210.6 -4.3 278 776 0.9 255
Mahoning, OH............. 6.4 100.7 -3.7 255 670 3.4 95
Montgomery, OH........... 12.9 257.6 -4.5 283 824 2.4 163
Stark, OH................ 9.0 158.3 -3.3 234 706 2.9 131
Summit, OH............... 15.0 271.3 -2.1 153 827 2.4 163
Trumbull, OH............. 4.7 75.1 -3.1 222 752 -0.1 282
Warren, OH............... 4.2 74.6 -4.1 270 763 3.0 122
Oklahoma, OK............. 23.9 427.1 0.1 36 852 5.6 20
Tulsa, OK................ 19.5 349.8 -0.1 43 838 2.3 169
Clackamas, OR............ 13.1 145.9 -4.5 283 821 0.2 273
Jackson, OR.............. 6.7 81.2 -5.7 304 665 2.3 169
Lane, OR................. 11.1 144.0 -5.8 305 711 2.6 151
Marion, OR............... 9.6 135.3 -2.9 204 711 2.3 169
Multnomah, OR............ 28.7 444.7 -2.6 189 934 2.0 192
Washington, OR........... 16.4 243.3 -4.2 273 986 -1.8 309
Allegheny, PA............ 35.3 685.4 -1.0 80 976 3.5 88
Berks, PA................ 9.2 167.8 -1.8 131 817 0.2 273
Bucks, PA................ 20.1 259.8 -3.0 208 905 2.6 151
Butler, PA............... 4.8 80.8 0.5 24 806 5.8 18
Chester, PA.............. 15.3 244.4 -0.4 51 1,181 2.2 181
Cumberland, PA........... 6.0 124.5 -1.8 131 823 3.0 122
Dauphin, PA.............. 7.4 180.8 -1.0 80 883 4.1 65
Delaware, PA............. 13.7 213.0 -0.3 47 953 1.1 247
Erie, PA................. 7.4 126.4 -1.8 131 729 4.0 67
Lackawanna, PA........... 5.9 101.2 -2.0 145 717 5.9 17
Lancaster, PA............ 12.5 226.9 -2.7 193 771 4.2 62
Lehigh, PA............... 8.8 177.6 -1.8 131 906 -0.7 297
Luzerne, PA.............. 7.9 142.5 -1.0 80 695 1.5 224
Montgomery, PA........... 27.7 488.0 -1.6 118 1,151 -0.3 286
Northampton, PA.......... 6.5 98.3 -3.3 234 805 2.7 143
Philadelphia, PA......... 31.5 637.6 -0.5 58 1,094 2.8 139
Washington, PA........... 5.4 80.5 0.9 18 814 4.5 48
Westmoreland, PA......... 9.4 135.7 -0.4 51 728 0.1 277
York, PA................. 9.2 177.6 -1.2 92 788 3.0 122
Kent, RI................. 5.7 77.6 -4.8 286 783 0.9 255
Providence, RI........... 18.1 277.8 -3.5 248 931 7.1 10
Charleston, SC........... 12.8 209.5 -1.9 139 782 -0.4 290
Greenville, SC........... 13.0 237.1 -2.8 196 795 2.7 143
Horry, SC................ 8.5 105.6 -7.1 319 581 -0.3 286
Lexington, SC............ 5.8 98.4 -1.7 126 680 1.2 245
Richland, SC............. 9.7 214.4 -2.1 153 790 3.3 101
Spartanburg, SC.......... 6.3 117.9 -5.2 295 776 4.7 42
Minnehaha, SD............ 6.4 116.8 1.2 12 741 0.8 259
Davidson, TN............. 18.6 436.1 -3.0 208 976 2.7 143
Hamilton, TN............. 8.6 189.2 -3.5 248 813 2.8 139
Knox, TN................. 11.2 228.9 -1.5 109 796 0.8 259
Rutherford, TN........... 4.3 97.5 -4.8 286 842 0.8 259
Shelby, TN............... 19.9 497.0 -3.5 248 935 0.1 277
Williamson, TN........... 6.1 87.5 -1.6 118 980 -4.9 317
Bell, TX................. 4.6 104.1 1.6 7 705 4.6 45
Bexar, TX................ 32.8 731.6 0.0 38 806 1.9 200
Brazoria, TX............. 4.7 87.8 0.0 38 871 3.9 71
Brazos, TX............... 3.9 86.9 (7) - 688 (7) -
Cameron, TX.............. 6.4 124.5 -0.5 58 584 5.4 27
Collin, TX............... 17.4 297.8 0.9 18 1,040 0.7 264
Dallas, TX............... 68.6 1,484.4 -1.2 92 1,123 1.1 247
Denton, TX............... 10.7 170.5 0.0 38 798 1.9 200
El Paso, TX.............. 13.6 273.0 -0.6 63 643 2.9 131
Fort Bend, TX............ 8.5 132.3 2.2 4 967 0.5 268
Galveston, TX............ 5.2 93.8 -4.1 270 829 0.0 280
Harris, TX............... 98.1 2,078.1 1.0 14 1,187 2.6 151
Hidalgo, TX.............. 10.7 222.4 0.9 18 574 2.0 192
Jefferson, TX............ 5.9 127.9 2.5 2 941 8.0 4
Lubbock, TX.............. 6.8 126.4 2.4 3 699 2.3 169
McLennan, TX............. 4.9 103.6 (7) - 718 2.4 163
Montgomery, TX........... 8.3 129.6 2.7 1 876 3.7 81
Nueces, TX............... 8.1 156.1 0.8 21 806 4.9 35
Potter, TX............... 3.8 77.5 1.3 11 797 (7) -
Smith, TX................ 5.3 95.7 1.2 12 809 6.2 16
Tarrant, TX.............. 37.6 770.8 -0.8 70 919 2.7 143
Travis, TX............... 29.3 578.8 0.1 36 1,009 -0.6 294
Webb, TX................. 4.8 89.4 0.4 28 600 1.5 224
Williamson, TX........... 7.3 121.6 -0.3 47 895 -5.1 318
Davis, UT................ 7.4 101.4 -2.2 160 737 0.7 264
Salt Lake, UT............ 38.9 588.6 -1.5 109 847 0.4 270
Utah, UT................. 13.3 172.2 -3.2 230 727 1.7 209
Weber, UT................ 5.7 93.0 -2.8 196 677 0.4 270
Chittenden, VT........... 6.0 95.3 -1.4 104 896 2.4 163
Arlington, VA............ 7.8 158.6 1.9 6 1,509 3.1 114
Chesterfield, VA......... 7.7 120.0 -2.9 204 825 2.9 131
Fairfax, VA.............. 34.3 589.2 -0.8 70 1,407 3.5 88
Henrico, VA.............. 9.7 178.0 -2.4 177 916 1.3 237
Loudoun, VA.............. 9.2 133.8 0.3 29 1,091 0.9 255
Prince William, VA....... 7.3 103.6 -1.2 92 816 -0.6 294
Alexandria City, VA...... 6.2 102.2 0.5 24 1,311 5.6 20
Chesapeake City, VA...... 5.8 98.5 -3.7 255 714 1.6 218
Newport News City, VA.... 4.0 99.2 -1.8 131 850 7.1 10
Norfolk City, VA......... 5.9 143.7 -1.1 84 906 4.3 58
Richmond City, VA........ 7.5 157.8 (7) - 1,024 (7) -
Virginia Beach City, VA.. 11.7 170.8 -3.0 208 726 2.5 159
Clark, WA................ 12.3 129.9 -2.8 196 817 2.9 131
King, WA................. 77.6 1,175.3 -1.5 109 1,130 4.0 67
Kitsap, WA............... 6.6 82.7 -2.4 177 822 4.6 45
Pierce, WA............... 20.8 269.4 -3.4 241 814 4.4 52
Snohomish, WA............ 17.9 250.2 -2.5 183 928 2.9 131
Spokane, WA.............. 15.5 207.2 -2.0 145 737 4.4 52
Thurston, WA............. 7.0 100.0 -0.8 70 807 2.9 131
Whatcom, WA.............. 6.9 80.6 -3.2 230 708 2.6 151
Yakima, WA............... 8.3 93.5 1.0 14 624 5.1 31
Kanawha, WV.............. 6.1 109.0 -0.6 63 799 4.7 42
Brown, WI................ 6.8 148.1 -1.9 139 821 3.1 114
Dane, WI................. 14.2 304.1 -1.1 84 878 4.8 39
Milwaukee, WI............ 21.3 495.4 -1.6 118 923 2.6 151
Outagamie, WI............ 5.1 103.6 -2.0 145 784 4.5 48
Racine, WI............... 4.2 74.7 -3.0 208 879 -0.1 282
Waukesha, WI............. 13.3 231.0 -3.2 230 920 2.3 169
Winnebago, WI............ 3.8 91.1 0.3 29 855 4.7 42
San Juan, PR............. 13.0 291.7 -2.5 (8) 621 2.3 (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,
fourth quarter 2008(2)
Employment Average weekly
wage(3)
Establishments,
fourth quarter
County by NAICS supersector 2008 Percent Percent
(thousands) December change, Average change,
2008 December weekly fourth
(thousands) 2007-08(4) wage quarter
2007-08(4)
United States(5)............................. 9,177.5 133,870.4 -2.3 $918 2.2
Private industry........................... 8,884.3 111,752.9 -2.9 919 2.0
Natural resources and mining............. 127.0 1,802.7 2.0 996 5.1
Construction............................. 881.7 6,636.1 -10.2 1,052 4.9
Manufacturing............................ 360.0 12,891.3 -6.2 1,094 1.8
Trade, transportation, and utilities..... 1,925.3 26,316.1 -3.5 766 1.1
Information.............................. 147.4 2,948.2 -3.4 1,360 0.1
Financial activities..................... 862.8 7,853.7 -3.2 1,390 -0.4
Professional and business services....... 1,537.6 17,366.1 -4.1 1,201 3.7
Education and health services............ 857.4 18,304.3 2.9 872 3.7
Leisure and hospitality.................. 742.2 12,957.7 -1.7 390 1.8
Other services........................... 1,229.1 4,445.7 -0.7 581 2.8
Government................................. 293.2 22,117.5 0.9 914 4.0
Los Angeles, CA.............................. 433.9 4,152.9 -3.4 1,075 1.8
Private industry........................... 430.0 3,552.8 -3.8 1,064 1.1
Natural resources and mining............. 0.5 10.5 -2.7 1,261 5.4
Construction............................. 14.0 136.7 -12.3 1,138 4.8
Manufacturing............................ 14.5 417.6 -5.9 1,107 3.8
Trade, transportation, and utilities..... 53.6 802.4 -5.4 833 -0.8
Information.............................. 8.8 207.5 (6) 1,889 (6)
Financial activities..................... 24.1 231.8 -5.7 1,462 -3.8
Professional and business services....... 42.6 574.2 (6) 1,306 (6)
Education and health services............ 28.1 500.0 1.8 979 3.8
Leisure and hospitality.................. 27.2 396.1 -1.6 927 5.9
Other services........................... 201.1 258.8 0.5 454 1.1
Government................................. 4.0 600.1 (6) 1,141 5.6
Cook, IL..................................... 141.0 2,480.0 -2.8 1,118 1.5
Private industry........................... 139.6 2,169.2 -3.3 1,126 1.3
Natural resources and mining............. 0.1 1.1 -5.6 998 -5.0
Construction............................. 12.4 82.8 -10.5 1,478 6.9
Manufacturing............................ 7.0 219.9 -6.5 1,119 3.0
Trade, transportation, and utilities..... 27.6 467.7 -4.9 840 -0.4
Information.............................. 2.6 56.1 -3.2 1,487 -4.3
Financial activities..................... 15.7 203.7 -4.3 2,007 0.7
Professional and business services....... 29.1 423.4 -4.8 1,525 3.5
Education and health services............ 14.0 386.1 3.1 930 1.3
Leisure and hospitality.................. 11.7 227.5 -2.2 440 0.0
Other services........................... 14.6 96.1 -0.1 783 3.2
Government................................. 1.4 310.8 0.8 1,058 2.9
New York, NY................................. 118.9 2,386.4 -1.3 1,856 -0.6
Private industry........................... 118.6 1,934.3 -1.6 2,041 -0.7
Natural resources and mining............. 0.0 0.2 -3.6 1,594 4.7
Construction............................. 2.4 36.3 0.6 1,939 0.6
Manufacturing............................ 3.0 33.7 -8.3 1,565 0.7
Trade, transportation, and utilities..... 22.0 255.2 -3.3 1,294 -1.5
Information.............................. 4.6 134.5 -1.5 2,055 -0.3
Financial activities..................... 19.2 369.0 -3.9 4,085 -1.3
Professional and business services....... 25.5 489.1 -2.4 2,173 0.6
Education and health services............ 8.9 297.7 1.6 1,133 6.0
Leisure and hospitality.................. 11.8 224.3 0.8 889 -0.7
Other services........................... 18.0 90.2 0.7 1,102 7.1
Government................................. 0.3 452.1 0.0 1,062 1.6
Harris, TX................................... 98.1 2,078.1 1.0 1,187 2.6
Private industry........................... 97.6 1,820.6 0.9 1,215 2.3
Natural resources and mining............. 1.6 85.8 7.1 2,872 (6)
Construction............................. 6.7 156.9 (6) 1,217 (6)
Manufacturing............................ 4.6 187.7 2.4 1,468 -3.4
Trade, transportation, and utilities..... 22.5 443.1 0.6 1,035 4.0
Information.............................. 1.4 32.0 -2.4 1,393 8.2
Financial activities..................... 10.6 117.9 (6) 1,517 4.7
Professional and business services....... 19.6 336.9 (6) 1,448 3.7
Education and health services............ 10.4 224.3 3.1 958 3.2
Leisure and hospitality.................. 7.6 175.2 -0.6 404 4.7
Other services........................... 11.9 59.6 0.4 673 3.2
Government................................. 0.5 257.5 1.8 988 5.2
Maricopa, AZ................................. 103.6 1,741.0 -5.8 892 2.1
Private industry........................... 102.9 1,512.8 -6.9 893 2.2
Natural resources and mining............. 0.5 9.0 -4.9 1,026 20.6
Construction............................. 11.0 115.5 -25.3 986 3.4
Manufacturing............................ 3.6 120.8 -8.0 1,217 3.6
Trade, transportation, and utilities..... 22.9 365.7 -6.8 796 0.9
Information.............................. 1.7 29.4 -4.1 1,098 3.4
Financial activities..................... 12.9 140.1 -4.8 1,066 -0.4
Professional and business services....... 23.2 289.2 -8.5 989 5.0
Education and health services............ 10.3 216.8 5.7 999 2.3
Leisure and hospitality.................. 7.4 176.8 -5.3 420 -1.4
Other services........................... 7.4 48.4 -4.9 613 2.7
Government................................. 0.7 228.2 2.0 881 0.1
Orange, CA................................... 102.7 1,451.2 -4.8 1,043 1.4
Private industry........................... 101.3 1,301.1 -5.3 1,043 1.2
Natural resources and mining............. 0.2 4.2 -9.0 665 -2.8
Construction............................. 6.9 83.3 -14.9 1,234 4.5
Manufacturing............................ 5.3 166.4 -5.7 1,226 -0.2
Trade, transportation, and utilities..... 17.2 272.3 -6.9 947 1.4
Information.............................. 1.3 29.0 -3.8 1,423 4.0
Financial activities..................... 10.7 110.0 -7.5 1,582 -2.6
Professional and business services....... 19.1 258.3 -7.6 1,259 6.0
Education and health services............ 10.0 150.8 (6) 960 (6)
Leisure and hospitality.................. 7.1 171.7 -2.2 406 1.5
Other services........................... 18.0 49.0 -0.3 569 -4.2
Government................................. 1.4 150.1 -0.8 1,044 3.2
Dallas, TX................................... 68.6 1,484.4 -1.2 1,123 1.1
Private industry........................... 68.1 1,314.7 -1.6 1,141 1.1
Natural resources and mining............. 0.6 8.5 12.6 4,744 38.9
Construction............................. 4.4 80.1 -4.3 1,075 1.7
Manufacturing............................ 3.1 129.8 -5.4 1,224 1.1
Trade, transportation, and utilities..... 15.2 308.2 -2.1 990 -4.2
Information.............................. 1.7 47.3 -4.2 1,524 3.6
Financial activities..................... 8.8 142.9 -1.2 1,429 -1.7
Professional and business services....... 15.1 275.6 -2.1 1,375 2.4
Education and health services............ 6.7 153.9 3.8 1,059 3.1
Leisure and hospitality.................. 5.4 128.5 (6) 493 (6)
Other services........................... 6.6 39.0 -1.2 682 3.6
Government................................. 0.5 169.7 2.3 984 2.2
San Diego, CA................................ 100.0 1,309.1 -3.0 981 2.0
Private industry........................... 98.8 1,082.3 -3.5 960 1.6
Natural resources and mining............. 0.8 9.4 -11.4 577 0.2
Construction............................. 7.0 70.4 -14.3 1,140 5.5
Manufacturing............................ 3.1 100.4 -3.3 1,306 0.9
Trade, transportation, and utilities..... 14.2 218.3 -6.3 759 0.7
Information.............................. 1.3 38.6 0.6 1,970 2.3
Financial activities..................... 9.5 74.2 -5.7 1,171 -1.0
Professional and business services....... 16.3 210.9 -4.4 1,238 2.0
Education and health services............ 8.2 138.3 4.2 953 3.1
Leisure and hospitality.................. 6.9 158.2 -2.3 425 3.9
Other services........................... 26.9 58.4 2.0 491 1.7
Government................................. 1.3 226.8 -0.4 1,079 2.8
King, WA..................................... 77.6 1,175.3 -1.5 1,130 4.0
Private industry........................... 77.0 1,018.2 -2.0 1,140 4.0
Natural resources and mining............. 0.4 2.9 7.0 1,573 11.8
Construction............................. 6.6 63.8 -11.6 1,197 6.8
Manufacturing............................ 2.4 108.8 -3.3 1,449 7.0
Trade, transportation, and utilities..... 14.9 221.8 -2.9 955 1.0
Information.............................. 1.8 81.4 6.1 1,982 3.9
Financial activities..................... 6.9 72.4 -5.0 1,418 2.6
Professional and business services....... 13.7 185.4 -3.3 1,378 4.6
Education and health services............ 6.5 129.3 4.6 894 3.8
Leisure and hospitality.................. 6.2 108.6 -2.5 450 1.6
Other services........................... 17.6 43.7 -0.8 631 3.6
Government................................. 0.5 157.1 1.9 1,069 4.2
Miami-Dade, FL............................... 86.8 1,003.9 -4.2 924 2.6
Private industry........................... 86.4 851.3 -4.7 907 2.3
Natural resources and mining............. 0.5 9.6 -10.6 457 -11.1
Construction............................. 6.4 42.0 -21.4 973 5.3
Manufacturing............................ 2.6 41.2 -11.7 818 1.0
Trade, transportation, and utilities..... 23.5 253.4 -4.0 814 1.2
Information.............................. 1.5 19.0 -8.1 1,266 5.2
Financial activities..................... 10.2 67.2 -7.6 1,387 0.1
Professional and business services....... 18.2 132.2 -5.2 1,229 6.6
Education and health services............ 9.4 145.9 2.8 901 1.7
Leisure and hospitality.................. 6.0 104.0 -1.9 514 0.6
Other services........................... 7.6 36.2 -3.3 579 6.0
Government................................. 0.4 152.6 -1.1 1,017 (6)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs.
(2) Data are preliminary.
(3) Average weekly wages were calculated using unrounded data.
(4) 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 2008(2)
Employment Average weekly
wage(4)
Establishments,
fourth quarter
County(3) 2008 Percent Percent
(thousands) December change, Average change,
2008 December weekly fourth
(thousands) 2007-08(5) wage quarter
2007-08(5)
United States(6)......... 9,177.5 133,870.4 -2.3 $918 2.2
Jefferson, AL............ 19.0 355.3 -3.3 922 2.2
Anchorage Borough, AK.... 8.2 148.2 1.5 969 4.9
Maricopa, AZ............. 103.6 1,741.0 -5.8 892 2.1
Pulaski, AR.............. 15.2 250.3 -1.2 847 -14.3
Los Angeles, CA.......... 433.9 4,152.9 -3.4 1,075 1.8
Denver, CO............... 25.6 445.0 -1.5 1,111 -1.3
Hartford, CT............. 25.6 504.5 -1.5 1,111 1.0
New Castle, DE........... 18.3 278.7 -3.7 1,055 2.3
Washington, DC........... 34.4 687.5 0.3 1,570 5.1
Miami-Dade, FL........... 86.8 1,003.9 -4.2 924 2.6
Fulton, GA............... 39.9 732.2 -3.4 1,183 1.0
Honolulu, HI............. 24.8 449.5 -2.4 850 3.8
Ada, ID.................. 15.0 202.9 -5.0 814 -1.1
Cook, IL................. 141.0 2,480.0 -2.8 1,118 1.5
Marion, IN............... 24.3 571.8 -2.8 913 2.8
Polk, IA................. 14.9 273.7 -1.1 904 2.4
Johnson, KS.............. 20.7 316.0 -1.1 949 1.3
Jefferson, KY............ 22.0 423.8 -3.3 871 1.5
East Baton Rouge, LA..... 14.8 265.9 0.3 874 8.0
Cumberland, ME........... 12.2 173.4 -2.3 822 3.0
Montgomery, MD........... 32.9 460.3 -1.3 1,219 1.9
Middlesex, MA............ 47.8 826.2 -0.4 1,296 -1.1
Wayne, MI................ 32.1 709.8 -5.6 1,032 4.2
Hennepin, MN............. 42.5 837.8 -2.4 1,146 2.7
Hinds, MS................ 6.4 127.6 -1.8 809 3.3
St. Louis, MO............ 32.8 600.5 -3.0 990 1.3
Yellowstone, MT.......... 5.8 78.2 -0.2 738 1.2
Douglas, NE.............. 16.1 322.8 0.0 842 -2.1
Clark, NV................ 51.0 870.0 -6.5 856 -2.3
Hillsborough, NH......... 12.4 195.9 -2.6 1,062 1.8
Bergen, NJ............... 34.6 450.4 -2.5 1,188 0.4
Bernalillo, NM........... 17.8 329.9 -2.0 812 3.0
New York, NY............. 118.9 2,386.4 -1.3 1,856 -0.6
Mecklenburg, NC.......... 33.4 567.7 -1.7 1,016 1.5
Cass, ND................. 5.9 100.7 1.5 778 2.1
Cuyahoga, OH............. 37.7 724.7 -3.0 926 2.0
Oklahoma, OK............. 23.9 427.1 0.1 852 5.6
Multnomah, OR............ 28.7 444.7 -2.6 934 2.0
Allegheny, PA............ 35.3 685.4 -1.0 976 3.5
Providence, RI........... 18.1 277.8 -3.5 931 7.1
Greenville, SC........... 13.0 237.1 -2.8 795 2.7
Minnehaha, SD............ 6.4 116.8 1.2 741 0.8
Shelby, TN............... 19.9 497.0 -3.5 935 0.1
Harris, TX............... 98.1 2,078.1 1.0 1,187 2.6
Salt Lake, UT............ 38.9 588.6 -1.5 847 0.4
Chittenden, VT........... 6.0 95.3 -1.4 896 2.4
Fairfax, VA.............. 34.3 589.2 -0.8 1,407 3.5
King, WA................. 77.6 1,175.3 -1.5 1,130 4.0
Kanawha, WV.............. 6.1 109.0 -0.6 799 4.7
Milwaukee, WI............ 21.3 495.4 -1.6 923 2.6
Laramie, WY.............. 3.2 43.8 0.3 753 2.0
San Juan, PR............. 13.0 291.7 -2.5 621 2.3
St. Thomas, VI........... 1.8 23.9 -0.3 673 -4.1
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted
for noneconomic county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin
Islands.
Table 4. Covered(1) establishments, employment, and wages by state,
fourth quarter 2008(2)
Employment Average weekly
wage(3)
Establishments,
fourth quarter
State 2008 Percent Percent
(thousands) December change, Average change,
2008 December weekly fourth
(thousands) 2007-08 wage quarter
2007-08
United States(4)......... 9,177.5 133,870.4 -2.3 $918 2.2
Alabama.................. 121.6 1,909.8 -3.1 790 3.5
Alaska................... 21.4 303.9 1.6 927 5.7
Arizona.................. 164.5 2,557.9 -5.1 848 2.7
Arkansas................. 86.5 1,168.2 -1.5 706 -1.0
California............... 1,370.0 15,288.5 -3.2 1,042 0.7
Colorado................. 177.1 2,295.8 -1.5 932 0.5
Connecticut.............. 113.5 1,688.0 -1.7 1,164 1.2
Delaware................. 29.4 416.8 -3.0 943 1.9
District of Columbia..... 34.4 687.5 0.3 1,570 5.1
Florida.................. 623.0 7,586.6 -5.3 824 1.6
Georgia.................. 276.7 3,970.3 -3.5 853 2.3
Hawaii................... 39.3 614.7 -3.5 821 3.5
Idaho.................... 57.2 634.1 -3.9 693 1.0
Illinois................. 371.5 5,795.8 -2.3 985 1.0
Indiana.................. 161.4 2,831.3 -3.4 764 2.7
Iowa..................... 94.6 1,483.7 -1.0 756 3.1
Kansas................... 87.2 1,370.2 -0.2 769 3.1
Kentucky................. 108.4 1,783.2 -2.6 754 3.0
Louisiana................ 128.5 1,907.5 0.1 829 5.9
Maine.................... 51.1 595.3 -2.1 735 4.0
Maryland................. 164.3 2,531.8 -1.9 1,010 2.4
Massachusetts............ 215.1 3,239.6 -1.1 1,154 1.8
Michigan................. 258.2 3,993.3 -4.9 903 3.6
Minnesota................ 172.0 2,658.8 -1.9 907 2.6
Mississippi.............. 71.0 1,117.2 -2.8 679 3.8
Missouri................. 175.7 2,700.9 -1.7 842 7.9
Montana.................. 43.2 433.8 -1.5 678 2.9
Nebraska................. 60.4 923.1 -0.3 730 1.0
Nevada................... 77.5 1,206.5 -6.5 862 -1.1
New Hampshire............ 49.9 626.2 -2.0 936 2.2
New Jersey............... 273.7 3,927.7 -2.4 1,123 2.8
New Mexico............... 54.9 821.2 -1.2 768 3.9
New York................. 585.9 8,677.4 -1.0 1,169 1.4
North Carolina........... 260.1 4,003.8 -3.0 793 1.9
North Dakota............. 25.8 354.4 1.9 725 5.1
Ohio..................... 293.0 5,167.5 -3.2 816 2.6
Oklahoma................. 100.8 1,559.8 0.0 755 4.9
Oregon................... 134.1 1,676.6 -3.7 808 1.3
Pennsylvania............. 344.0 5,645.8 -1.3 897 2.6
Rhode Island............. 35.9 464.3 -3.4 887 5.7
South Carolina........... 119.5 1,837.1 -3.5 731 2.1
South Dakota............. 30.8 395.2 0.4 663 2.5
Tennessee................ 143.1 2,695.7 -3.3 824 1.4
Texas.................... 566.6 10,510.8 0.4 933 2.4
Utah..................... 88.3 1,215.0 -2.1 770 1.4
Vermont.................. 25.1 304.4 -1.7 774 4.3
Virginia................. 233.5 3,656.8 -1.3 953 3.3
Washington............... 222.8 2,885.0 -1.8 918 3.7
West Virginia............ 48.9 713.8 -0.1 735 7.1
Wisconsin................ 161.1 2,753.2 -1.9 793 3.0
Wyoming.................. 25.2 284.5 1.5 850 4.3
Puerto Rico.............. 55.3 1,028.5 -2.9 528 2.3
Virgin Islands........... 3.6 45.5 -1.4 731 -0.8
(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
