For release 10:00 a.m. (EDT), Tuesday, March 29, 2011 USDL-11-0434
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov *
www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
County Employment and Wages
Third Quarter 2010
From September 2009 to September 2010, employment increased in 162 of
the 326 largest U.S. counties according to preliminary data, the U.S.
Bureau of Labor Statistics reported today. Elkhart, Ind., posted the
largest percentage increase, with a gain of 6.8 percent over the
year, compared with national job growth of 0.2 percent. Within
Elkhart, the largest employment increase occurred in manufacturing,
which gained 5,570 jobs over the year (14.2 percent). Sacramento,
Calif., experienced the largest over-the-year percentage decrease in
employment among the largest counties in the U.S. with a loss of 3.7
percent. Within Sacramento, state government had the largest
percentage decrease in employment with a loss of 7.5 percent.
The U.S. average weekly wage increased over the year by 3.4 percent
to $870 in the third quarter of 2010. Among the large counties in the
U.S., Rock Island, Ill., had the largest over-the-year increase in
average weekly wages in the third quarter of 2010 with a gain of 12.2
percent. Within Rock Island, professional and business services had
the largest impact on the county’s over-the-year increase in average
weekly wages. Sacramento, Calif., experienced the only decline in
average weekly wages among the largest U.S. counties with a loss of
2.2 percent over the year. County employment and wage data are
compiled under the Quarterly Census of Employment and Wages (QCEW)
program.
Table A. Top 10 large counties ranked by September 2010 employment, September 2009-10 employment
increase, and September 2009-10 percent increase in employment
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Employment in large counties
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September 2010 employment | Increase in employment, | Percent increase in employment,
(thousands) | September 2009-10 | September 2009-10
| (thousands) |
--------------------------------------------------------------------------------------------------------
| |
United States 128,440.4| United States 310.8| United States 0.2
--------------------------------------------------------------------------------------------------------
Los Angeles, Calif. 3,844.5| New York, N.Y. 26.9| Elkhart, Ind. 6.8
Cook, Ill. 2,354.8| Harris, Texas 21.2| Denton, Texas 3.2
New York, N.Y. 2,273.0| Washington, D.C. 13.7| Bell, Texas 3.1
Harris, Texas 1,995.8| Dallas, Texas 12.7| Arlington, Va. 3.1
Maricopa, Ariz. 1,597.0| Hennepin, Minn. 11.0| Washington, Pa. 2.7
Dallas, Texas 1,415.0| Travis, Texas 10.9| Benton, Wash. 2.6
Orange, Calif. 1,348.8| Kings, N.Y. 9.7| Washtenaw, Mich. 2.5
San Diego, Calif. 1,238.6| Philadelphia, Pa. 9.7| Boone, Mo. 2.5
King, Wash. 1,121.8| Fairfax, Va. 7.5| Brazoria, Texas 2.5
Miami-Dade, Fla. 940.9| Bexar, Texas 7.4| Hamilton, Tenn. 2.4
| | Collin, Texas 2.4
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Large County Employment
In September 2010, national employment, as measured by the QCEW
program, was 128.4 million, up by 0.2 percent, or 310,800 workers,
from September 2009. The 326 U.S. counties with 75,000 or more
employees accounted for 70.6 percent of total U.S. employment and
76.1 percent of total wages. These 326 counties had a net job growth
of 80,826 over the year, accounting for 26.0 percent of the overall
U.S. employment increase.
Elkhart, Ind., had the largest percentage increase in employment
among the largest U.S. counties. The top five counties with the
greatest increases in employment level (New York, N.Y.; Harris,
Texas; Washington, D.C.; Dallas, Texas; and Hennepin, Minn.) had a
combined over-the-year gain of 85,500, or 27.5 percent of the
employment increase for the U.S.
Employment declined in 149 of the large counties from September 2009
to September 2010. Sacramento, Calif., had the largest over-the-year
percentage decrease in employment (-3.7 percent) in the nation. At
the supersector level, public administration within state government
was the largest contributor to the decrease in employment with a loss
of 7.1 percent. San Joaquin, Calif., experienced the second largest
employment decrease, followed by Marion, Fla., East Baton Rouge, La.,
and Pinellas, Fla.
Table B. Top 10 large counties ranked by third quarter 2010 average weekly wages, third quarter 2009-10
increase in average weekly wages, and third quarter 2009-10 percent increase in average weekly wages
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Average weekly wage in large counties
--------------------------------------------------------------------------------------------------------
Average weekly wage, | Increase in average weekly | Percent increase in average
third quarter 2010 | wage, third quarter 2009-10 | weekly wage, third
| | quarter 2009-10
--------------------------------------------------------------------------------------------------------
| |
United States $870| United States $29| United States 3.4
--------------------------------------------------------------------------------------------------------
| |
Santa Clara, Calif. $1,662| Santa Clara, Calif. $153| Rock Island, Ill. 12.2
New York, N.Y. 1,572| Rock Island, Ill. 105| Benton, Ark. 10.4
Arlington, Va. 1,505| Middlesex, Mass. 98| Santa Clara, Calif. 10.1
Washington, D.C. 1,471| Arlington, Va. 92| Anoka, Minn. 8.9
Fairfax, Va. 1,374| Benton, Ark. 79| Butler, Pa. 8.8
San Francisco, Calif. 1,358| Washington, Ore. 71| Clay, Mo. 8.5
San Mateo, Calif. 1,351| Fairfield, Conn. 70| Middlesex, Mass. 8.3
Suffolk, Mass. 1,346| New York, N.Y. 70| Lake, Ind. 7.4
Fairfield, Conn. 1,339| Clay, Mo. 69| Washington, Ore. 7.3
Middlesex, Mass. 1,285| Anoka, Minn. 68| Tuscaloosa, Ala. 7.1
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Large County Average Weekly Wages
Average weekly wages for the nation increased by 3.4 percent over the
year in the third quarter of 2010. Among the 326 largest counties,
319 had over-the-year increases in average weekly wages. Rock Island,
Ill., had the largest wage gain among the largest U.S. counties.
Of the 326 largest counties, only one, Sacramento, Calif.,
experienced an average weekly wage decline with a loss of 2.2 percent
over the year. Large declines in total wages (-19.1 percent) within
state government contributed significantly to the county’s overall
average weekly wage loss. Orleans, La., had the smallest overall
increase among the counties, followed by San Luis Obispo, Calif.,
Prince Georges, Md., and Marion, Ore.
Ten Largest U.S. Counties
Six of the 10 largest counties experienced over-the-year percent
increases in employment in September 2010. New York, N.Y.,
experienced the largest gain in employment among the 10 largest
counties with a 1.2 percent increase. Within New York, professional
and business services had the largest over-the-year increase among
all private industry groups with a gain of 8,396 workers (1.9
percent). (See table 2.) Los Angeles, Calif., experienced the largest
decline in employment among the 10 largest counties.
All of the 10 largest U.S. counties saw an over-the-year increase in
average weekly wages. New York, N.Y., and King, Wash., experienced
the largest increase in average weekly wages among the 10 largest
counties with a gain of 4.7 percent each. Within New York, the
largest impact on the county’s average weekly wage growth occurred in
financial activities, where total wages increased by $832.0 million
over the year (6.7 percent). In King County, information had the
largest impact on average weekly wage growth with an increase of
$227.6 million over the year (6.5 percent). Miami-Dade, Fla., had the
smallest wage increase among the 10 largest counties.
For More Information
The tables included in this release contain data for the nation and
for the 326 U.S. counties with annual average employment levels of
75,000 or more in 2009. September 2010 employment and 2010 third
quarter average weekly wages for all states are provided in table 3
of this release.
The employment and wage data by county are compiled under the 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 9.0 million employer reports cover 128.4 million full-
and part- time workers. For additional information about the
quarterly employment and wages data, please read the Technical Note.
Data for the third quarter of 2010 will be available later at
http://www.bls.gov/cew/. 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 fourth quarter 2010 is
scheduled to be released on Thursday, June 30, 2011.
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
release are based on the 2007 North American Industry Classification System. Data
for 2010 are preliminary and subject to revision.
For purposes of this release, large counties are defined as having employment le-
vels of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are pro-
vided, 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 prelimi-
nary annual average of employment for the previous year. The 327 counties presented
in this release were derived using 2009 preliminary annual averages of employment.
For 2010 data, two counties have been added to the publication tables: St. Tammany
Parish, La., and Benton, Wash. These counties will be included in all 2010 quarter-
ly releases. Ten counties, Shelby, Ala.; Butte, Calif.; Tippecanoe, Ind.; Johnson,
Iowa; Saratoga, N.Y.; Trumbull, Ohio; Warren, Ohio; Kent, R.I.; Gregg, Texas; and
Racine, Wis., which were published in the 2009 releases, will be excluded from this
and future 2010 releases because their 2009 annual average employment levels were
less than 75,000. The counties in table 2 are selected and sorted each year based
on the annual average employment from the preceding year.
The preliminary QCEW data presented in this release may differ from data released
by the individual states. These potential differences result from the states' con-
tinuing receipt of UI data over time and ongoing review and editing. The individual
states determine their data release timetables.
Differences between QCEW, BED, and CES employment measures
The Bureau publishes three different establishment-based employment measures for
any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED),
and Current Employment Statistics (CES)--makes use of the quarterly UI employment
reports in producing data; however, each measure has a somewhat different universe
coverage, estimation procedure, and publication product.
Differences in coverage and estimation methods can result in somewhat different
measures of employment change over time. It is important to understand program dif-
ferences and the intended uses of the program products. (See table.) Additional in-
formation on each program can be obtained from the program Web sites shown in the
table.
Summary of Major Differences between QCEW, BED, and CES Employment Measures
---------------------------------------------------------------------------------
| QCEW | BED | CES
-----------|---------------------|----------------------|------------------------
Source |--Count of UI admini-|--Count of longitudi- |--Sample survey:
| strative records | nally-linked UI ad- | 400,000 establish-
| submitted by 9.0 | ministrative records| ments
| million establish- | submitted by 6.7 |
| ments in first | million private-sec-|
| quarter of 2010 | 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 sub-
mitted 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 multiple 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 microdata summaries of 9.0 million employer reports of employment and wages
submitted by states to the BLS in 2009. These reports are based on place of employ-
ment rather than place of residence.
UI and UCFE coverage is broad and has been basically comparable from state to state
since 1978, when the 1976 amendments to the Federal Unemployment Tax Act became ef-
fective, expanding coverage to include most State and local government employees.
In 2009, UI and UCFE programs covered workers in 128.6 million jobs. The estimated
123.6 million workers in these jobs (after adjustment for multiple jobholders)
represented 95.1 percent of civilian wage and salary employment. Covered workers
received $5.859 trillion in pay, representing 93.4 percent of the wage and salary
component of personal income and 41.5 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 re-
lease.
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
employees of covered firms are reported, including production and sales workers,
corporation officials, executives, supervisory personnel, and clerical workers.
Workers 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 av-
erages 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
gratuities, and, in some states, employer contributions to certain deferred compen-
sation plans such as 401(k) plans and stock options. Over-the-year comparisons of
average weekly wages may reflect fluctuations in average monthly employment and/or
total 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 week-
ly 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 pe-
riods 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 oc-
cur 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
comparisons can be pronounced in federal government due to the uniform nature of
federal payroll processing. This pattern may exist in private sector pay; however,
because there are more pay period types (weekly, biweekly, semimonthly, monthly) it
is less pronounced. The effect is most visible in counties with large concentra-
tions of federal employment.
In order to ensure the highest possible quality of data, states verify with employ-
ers and update, if necessary, the industry, location, and ownership classification
of all establishments on a 4-year cycle. Changes in establishment classification
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 indi-
vidual 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 adjusted version of the final 2009 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 un-
adjusted 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 re-
lease.
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. In-
cluded in these adjustments are administrative changes involving the classification
of establishments that were previously reported in the unknown or statewide county
or unknown industry categories. Beginning with the first quarter of 2008, adjusted
data 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.
Comparisons may not be valid for any time period other than the one featured in a
release 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 common 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 Annual Averages, features comprehensive
information by detailed industry on establishments, employment, and wages for the nation
and all states. The 2009 edition of this bulletin contains selected data produced
by Business Employment Dynamics (BED) on job gains and losses, as well as selected data
from the first quarter 2010 version of this news release. This web-only publication has
replaced the annual print bulletin, Employment and Wages Annual Averages. The March 2010
issue of this annual bulletin was the final one to be issued on paper. Tables and
additional content from the 2009 Employment and Wages Annual Bulletin are now available
online at http://www.bls.gov/cew/cewbultn09.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 327 largest counties,
third quarter 2010(2)
Employment Average weekly wage(4)
Establishments,
County(3) third quarter Percent Ranking Percent Ranking
2010 September change, by Average change, by
(thousands) 2010 September percent weekly third percent
(thousands) 2009-10(5) change wage quarter change
2009-10(5)
United States(6)......... 9,044.4 128,440.4 0.2 - $870 3.4 -
Jefferson, AL............ 17.8 329.4 -1.0 258 882 2.4 214
Madison, AL.............. 8.7 178.0 -0.4 203 1,004 3.8 97
Mobile, AL............... 9.9 167.0 2.2 16 769 3.2 146
Montgomery, AL........... 6.4 128.4 -1.1 264 779 4.3 62
Tuscaloosa, AL........... 4.3 83.2 1.4 46 783 7.1 10
Anchorage Borough, AK.... 8.1 152.1 1.0 68 975 3.3 137
Maricopa, AZ............. 95.0 1,597.0 -0.5 211 859 2.4 214
Pima, AZ................. 19.3 341.4 -2.0 309 769 2.1 233
Benton, AR............... 5.4 93.0 1.0 68 835 10.4 2
Pulaski, AR.............. 15.1 244.1 0.8 87 797 0.9 301
Washington, AR........... 5.5 90.6 2.0 18 721 4.3 62
Alameda, CA.............. 54.6 631.0 -0.8 242 1,155 4.2 71
Contra Costa, CA......... 29.3 314.2 -1.3 276 1,050 2.2 223
Fresno, CA............... 30.2 346.4 -0.6 219 684 2.1 233
Kern, CA................. 17.7 279.3 1.3 52 747 2.3 221
Los Angeles, CA.......... 427.0 3,844.5 -0.8 242 972 3.1 158
Marin, CA................ 11.6 101.7 1.5 37 1,027 1.5 275
Monterey, CA............. 12.8 179.1 0.6 107 752 1.1 294
Orange, CA............... 101.7 1,348.8 -0.1 172 975 2.8 183
Placer, CA............... 10.6 124.6 0.3 131 849 1.3 284
Riverside, CA............ 47.8 544.1 -1.4 283 721 1.3 284
Sacramento, CA........... 52.9 570.8 -3.7 320 920 -2.2 320
San Bernardino, CA....... 49.6 588.3 -1.3 276 756 1.3 284
San Diego, CA............ 97.7 1,238.6 0.4 128 943 2.7 193
San Francisco, CA........ 53.3 549.7 0.9 73 1,358 3.7 108
San Joaquin, CA.......... 17.0 203.9 -3.3 319 759 1.9 256
San Luis Obispo, CA...... 9.5 98.6 -0.6 219 722 0.3 316
San Mateo, CA............ 23.8 317.9 0.2 142 1,351 3.4 128
Santa Barbara, CA........ 14.3 178.4 -0.2 186 831 4.0 83
Santa Clara, CA.......... 61.0 845.2 0.8 87 1,662 10.1 3
Santa Cruz, CA........... 9.0 96.4 -0.9 249 782 3.2 146
Solano, CA............... 10.0 122.0 -1.4 283 856 1.5 275
Sonoma, CA............... 18.6 177.7 -0.2 186 840 2.1 233
Stanislaus, CA........... 14.9 166.1 0.5 120 741 0.5 314
Tulare, CA............... 9.3 148.4 -0.7 230 610 1.0 298
Ventura, CA.............. 23.5 293.6 -0.3 194 887 2.7 193
Yolo, CA................. 6.0 97.2 -2.2 313 862 2.6 202
Adams, CO................ 9.0 148.4 -1.1 264 813 3.0 167
Arapahoe, CO............. 19.0 270.3 -0.3 194 1,016 2.1 233
Boulder, CO.............. 13.0 152.5 0.2 142 1,038 6.6 12
Denver, CO............... 25.5 423.6 1.5 37 1,049 0.9 301
Douglas, CO.............. 9.6 90.1 0.1 152 925 2.1 233
El Paso, CO.............. 17.0 233.2 -0.3 194 825 3.3 137
Jefferson, CO............ 18.1 202.9 -0.6 219 905 3.1 158
Larimer, CO.............. 10.1 128.6 1.0 68 783 1.2 291
Weld, CO................. 5.9 79.0 -0.1 172 755 5.3 29
Fairfield, CT............ 32.8 401.1 0.6 107 1,339 5.5 27
Hartford, CT............. 25.3 485.1 0.1 152 1,065 4.3 62
New Haven, CT............ 22.3 349.2 0.2 142 941 3.2 146
New London, CT........... 7.0 125.0 -1.2 271 899 3.5 122
New Castle, DE........... 17.7 263.2 -0.1 172 1,013 2.8 183
Washington, DC........... 35.0 693.8 2.0 18 1,471 1.2 291
Alachua, FL.............. 6.6 115.3 -0.9 249 773 3.8 97
Brevard, FL.............. 14.5 186.1 -0.9 249 840 3.8 97
Broward, FL.............. 62.2 673.2 -0.5 211 824 3.1 158
Collier, FL.............. 11.6 105.6 0.3 131 762 3.1 158
Duval, FL................ 26.7 432.2 0.6 107 832 2.5 209
Escambia, FL............. 8.0 119.6 -0.4 203 695 2.1 233
Hillsborough, FL......... 36.8 556.8 -0.7 230 844 1.7 266
Lake, FL................. 7.2 77.3 -1.7 300 620 4.2 71
Lee, FL.................. 18.5 187.0 -0.7 230 710 0.9 301
Leon, FL................. 8.2 137.8 -1.1 264 762 2.0 246
Manatee, FL.............. 9.1 99.3 -0.9 249 681 0.6 310
Marion, FL............... 7.9 88.1 -2.6 317 611 0.8 306
Miami-Dade, FL........... 85.0 940.9 0.3 131 853 1.5 275
Okaloosa, FL............. 6.1 74.5 -2.1 311 727 3.0 167
Orange, FL............... 35.2 644.4 0.8 87 782 2.9 175
Palm Beach, FL........... 48.6 478.0 -0.7 230 841 3.6 116
Pasco, FL................ 9.8 95.8 1.3 52 609 3.4 128
Pinellas, FL............. 30.5 378.5 -2.4 316 760 3.7 108
Polk, FL................. 12.3 186.0 -0.6 219 699 2.8 183
Sarasota, FL............. 14.4 129.7 -1.5 291 720 2.0 246
Seminole, FL............. 13.9 154.5 -1.3 276 712 2.0 246
Volusia, FL.............. 13.3 147.5 -2.2 313 640 3.6 116
Bibb, GA................. 4.6 78.8 -1.7 300 694 1.8 261
Chatham, GA.............. 7.6 127.6 0.2 142 746 2.1 233
Clayton, GA.............. 4.3 101.7 (7) - 800 (7) -
Cobb, GA................. 20.7 283.8 0.0 163 911 3.3 137
De Kalb, GA.............. 17.5 271.6 -1.2 271 923 2.7 193
Fulton, GA............... 39.7 704.3 0.6 107 1,122 2.2 223
Gwinnett, GA............. 23.5 296.0 0.9 73 848 1.4 282
Muscogee, GA............. 4.7 91.6 0.1 152 708 1.3 284
Richmond, GA............. 4.7 96.4 -0.5 211 769 2.4 214
Honolulu, HI............. 24.8 429.5 0.2 142 834 2.0 246
Ada, ID.................. 14.2 193.0 0.2 142 778 2.9 175
Champaign, IL............ 4.2 87.9 -0.8 242 770 3.4 128
Cook, IL................. 143.4 2,354.8 -0.4 203 1,008 3.2 146
Du Page, IL.............. 36.3 546.9 (7) - 1,010 4.4 59
Kane, IL................. 13.0 191.2 -0.9 249 784 2.6 202
Lake, IL................. 21.4 311.7 -1.2 271 1,052 5.1 32
McHenry, IL.............. 8.6 94.5 -1.5 291 735 4.3 62
McLean, IL............... 3.8 85.3 (7) - 871 3.9 90
Madison, IL.............. 6.0 93.6 0.0 163 735 2.7 193
Peoria, IL............... 4.7 99.8 1.9 23 841 5.1 32
Rock Island, IL.......... 3.5 74.7 0.5 120 964 12.2 1
St. Clair, IL............ 5.5 93.9 -0.1 172 730 2.2 223
Sangamon, IL............. 5.3 128.0 1.4 46 907 3.1 158
Will, IL................. 14.4 195.7 0.8 87 773 3.5 122
Winnebago, IL............ 6.9 123.7 0.1 152 759 2.8 183
Allen, IN................ 8.9 171.8 1.1 61 738 5.0 42
Elkhart, IN.............. 4.8 102.3 6.8 1 716 5.1 32
Hamilton, IN............. 7.9 109.2 0.5 120 829 4.1 75
Lake, IN................. 10.2 181.9 -1.2 271 786 7.4 8
Marion, IN............... 23.5 546.0 -0.1 172 881 3.0 167
St. Joseph, IN........... 6.0 115.8 0.1 152 716 1.1 294
Vanderburgh, IN.......... 4.8 104.6 0.9 73 720 2.7 193
Linn, IA................. 6.2 124.6 1.0 68 826 3.3 137
Polk, IA................. 14.7 265.0 -1.3 276 856 2.9 175
Scott, IA................ 5.2 85.4 0.0 163 721 4.9 45
Johnson, KS.............. 20.9 295.9 -0.7 230 891 3.7 108
Sedgwick, KS............. 12.4 237.3 -1.7 300 780 3.3 137
Shawnee, KS.............. 4.9 92.8 -0.7 230 736 2.2 223
Wyandotte, KS............ 3.2 80.1 1.7 32 827 1.1 294
Fayette, KY.............. 9.5 174.1 1.6 33 782 2.2 223
Jefferson, KY............ 22.4 410.4 0.3 131 845 4.1 75
Caddo, LA................ 7.7 120.5 0.5 120 750 6.1 17
Calcasieu, LA............ 5.1 81.5 -1.7 300 760 4.4 59
East Baton Rouge, LA..... 15.1 253.1 -2.6 317 825 1.2 291
Jefferson, LA............ 14.6 192.5 -0.1 172 825 4.8 47
Lafayette, LA............ 9.4 130.9 1.4 46 851 6.6 12
Orleans, LA.............. 11.4 169.2 1.5 37 924 0.1 319
St. Tammany, LA.......... 7.7 74.8 0.0 163 761 (7) -
Cumberland, ME........... 12.3 168.2 -0.2 186 791 2.5 209
Anne Arundel, MD......... 14.4 228.5 0.7 96 941 (7) -
Baltimore, MD............ 21.2 360.2 -0.6 219 904 3.2 146
Frederick, MD............ 5.9 93.0 0.9 73 870 2.6 202
Harford, MD.............. 5.6 81.7 1.1 61 882 5.1 32
Howard, MD............... 8.8 147.2 1.8 28 1,045 2.2 223
Montgomery, MD........... 32.5 446.3 0.9 73 1,189 3.3 137
Prince Georges, MD....... 15.6 300.8 0.0 163 953 0.3 316
Baltimore City, MD....... 13.6 324.6 -0.4 203 1,001 1.7 266
Barnstable, MA........... 9.2 94.9 0.3 131 720 2.1 233
Bristol, MA.............. 16.2 208.7 0.6 107 785 3.8 97
Essex, MA................ 21.4 296.3 1.5 37 932 5.1 32
Hampden, MA.............. 15.0 194.7 0.7 96 805 1.0 298
Middlesex, MA............ 48.8 804.4 0.6 107 1,285 8.3 7
Norfolk, MA.............. 24.3 314.2 0.7 96 1,004 4.1 75
Plymouth, MA............. 14.2 172.4 0.1 152 811 2.8 183
Suffolk, MA.............. 22.8 572.7 1.2 58 1,346 1.4 282
Worcester, MA............ 21.3 310.3 0.9 73 905 6.1 17
Genesee, MI.............. 7.5 126.3 -1.7 300 740 2.9 175
Ingham, MI............... 6.5 152.8 1.2 58 852 4.0 83
Kalamazoo, MI............ 5.4 107.7 -1.0 258 793 3.4 128
Kent, MI................. 13.9 312.7 2.3 12 780 1.7 266
Macomb, MI............... 17.1 277.4 1.9 23 889 4.2 71
Oakland, MI.............. 37.6 614.3 -0.1 172 968 3.1 158
Ottawa, MI............... 5.6 104.5 1.9 23 720 5.0 42
Saginaw, MI.............. 4.2 80.1 -0.3 194 750 6.8 11
Washtenaw, MI............ 8.1 187.6 2.5 7 963 0.8 306
Wayne, MI................ 31.3 663.0 0.1 152 964 5.1 32
Anoka, MN................ 7.1 105.0 -1.1 264 831 8.9 4
Dakota, MN............... 9.6 166.1 0.1 152 821 3.1 158
Hennepin, MN............. 43.3 806.1 1.4 46 1,090 4.0 83
Olmsted, MN.............. 3.3 87.1 -0.8 242 919 2.9 175
Ramsey, MN............... 13.9 317.9 -0.1 172 969 5.4 28
St. Louis, MN............ 5.6 93.5 0.7 96 717 4.5 55
Stearns, MN.............. 4.3 78.1 0.7 96 731 4.0 83
Harrison, MS............. 4.5 82.3 -1.6 297 665 2.2 223
Hinds, MS................ 6.1 121.8 -2.0 309 771 1.7 266
Boone, MO................ 4.5 82.7 2.5 7 702 1.6 272
Clay, MO................. 5.0 90.9 -0.4 203 879 8.5 6
Greene, MO............... 8.0 146.8 -1.6 297 684 2.7 193
Jackson, MO.............. 18.1 340.6 -1.4 283 870 2.4 214
St. Charles, MO.......... 8.2 122.5 2.3 12 703 2.5 209
St. Louis, MO............ 31.7 560.8 -1.5 291 913 2.1 233
St. Louis City, MO....... 8.7 216.4 -1.8 306 942 3.4 128
Yellowstone, MT.......... 5.9 76.1 -0.6 219 711 3.0 167
Douglas, NE.............. 15.8 311.0 0.1 152 817 2.8 183
Lancaster, NE............ 8.1 154.0 -0.1 172 708 1.3 284
Clark, NV................ 47.0 792.7 -2.1 311 810 0.6 310
Washoe, NV............... 13.6 185.2 -1.5 291 816 2.1 233
Hillsborough, NH......... 11.9 185.1 -0.3 194 945 1.5 275
Rockingham, NH........... 10.6 134.3 1.1 61 823 4.0 83
Atlantic, NJ............. 6.8 136.4 -1.4 283 765 3.9 90
Bergen, NJ............... 33.6 424.6 -0.1 172 1,058 2.1 233
Burlington, NJ........... 11.1 191.0 -1.9 308 941 3.9 90
Camden, NJ............... 12.7 193.1 -1.5 291 876 3.7 108
Essex, NJ................ 20.9 332.8 -1.8 306 1,088 3.1 158
Gloucester, NJ........... 6.3 97.1 -2.3 315 803 5.9 20
Hudson, NJ............... 13.8 227.4 -0.8 242 1,234 5.1 32
Mercer, NJ............... 11.1 226.9 1.3 52 1,104 3.2 146
Middlesex, NJ............ 21.9 375.8 -0.6 219 1,052 3.0 167
Monmouth, NJ............. 20.3 245.5 -0.2 186 904 1.8 261
Morris, NJ............... 17.6 267.5 -0.7 230 1,238 (7) -
Ocean, NJ................ 12.3 149.4 -0.7 230 712 1.7 266
Passaic, NJ.............. 12.3 169.6 1.8 28 903 1.5 275
Somerset, NJ............. 10.1 163.9 -0.5 211 1,255 1.0 298
Union, NJ................ 14.7 218.1 -0.2 186 1,074 2.5 209
Bernalillo, NM........... 17.6 312.1 -1.5 291 796 1.9 256
Albany, NY............... 9.9 217.0 -1.4 283 945 4.8 47
Bronx, NY................ 16.8 232.6 0.6 107 876 2.9 175
Broome, NY............... 4.5 91.5 -1.4 283 716 3.9 90
Dutchess, NY............. 8.1 110.3 -0.1 172 904 1.8 261
Erie, NY................. 23.6 450.3 0.3 131 773 4.6 54
Kings, NY................ 49.8 489.2 2.0 18 755 2.2 223
Monroe, NY............... 18.0 368.4 0.3 131 853 5.7 23
Nassau, NY............... 52.5 582.0 -0.2 186 966 4.3 62
New York, NY............. 120.9 2,273.0 1.2 58 1,572 4.7 50
Oneida, NY............... 5.3 106.6 -1.3 276 713 5.3 29
Onondaga, NY............. 12.8 241.1 -1.0 258 816 4.2 71
Orange, NY............... 10.0 129.8 0.6 107 751 3.0 167
Queens, NY............... 45.2 494.5 0.7 96 845 0.8 306
Richmond, NY............. 8.9 93.1 1.1 61 782 2.8 183
Rockland, NY............. 9.9 111.4 -0.3 194 928 2.8 183
Suffolk, NY.............. 50.5 607.8 0.5 120 997 4.3 62
Westchester, NY.......... 36.1 399.1 -0.4 203 1,109 4.7 50
Buncombe, NC............. 7.8 111.3 1.5 37 698 4.5 55
Catawba, NC.............. 4.4 77.1 0.9 73 672 4.8 47
Cumberland, NC........... 6.2 117.0 -0.8 242 734 6.2 16
Durham, NC............... 7.2 177.6 -1.4 283 1,156 0.5 314
Forsyth, NC.............. 8.9 172.2 -1.4 283 792 3.4 128
Guilford, NC............. 14.1 257.3 0.2 142 783 3.8 97
Mecklenburg, NC.......... 32.0 533.8 -0.2 186 972 2.2 223
New Hanover, NC.......... 7.2 96.0 -0.3 194 735 3.2 146
Wake, NC................. 28.4 431.8 0.6 107 861 3.2 146
Cass, ND................. 5.9 100.2 1.1 61 759 3.4 128
Butler, OH............... 7.3 138.1 0.6 107 783 5.0 42
Cuyahoga, OH............. 36.0 686.2 0.0 163 882 3.5 122
Franklin, OH............. 29.3 649.5 0.9 73 890 4.5 55
Hamilton, OH............. 23.3 482.9 -1.1 264 960 3.7 108
Lake, OH................. 6.5 93.4 0.8 87 719 3.8 97
Lorain, OH............... 6.1 92.8 0.7 96 712 4.7 50
Lucas, OH................ 10.4 200.2 0.5 120 768 3.4 128
Mahoning, OH............. 6.1 97.4 0.2 142 636 3.2 146
Montgomery, OH........... 12.3 239.5 -0.7 230 784 2.9 175
Stark, OH................ 8.8 149.4 0.4 128 678 4.3 62
Summit, OH............... 14.5 253.2 0.0 163 777 2.6 202
Oklahoma, OK............. 24.2 411.9 0.8 87 813 1.6 272
Tulsa, OK................ 20.1 326.9 -1.3 276 795 2.7 193
Clackamas, OR............ 12.5 137.4 -0.1 172 803 2.6 202
Jackson, OR.............. 6.5 76.4 -1.1 264 651 0.9 301
Lane, OR................. 10.8 134.8 -0.3 194 680 1.3 284
Marion, OR............... 9.3 136.4 -0.7 230 693 0.3 316
Multnomah, OR............ 28.7 422.0 0.6 107 893 3.2 146
Washington, OR........... 16.1 237.4 2.3 12 1,042 7.3 9
Allegheny, PA............ 34.8 671.7 0.9 73 917 4.4 59
Berks, PA................ 8.9 161.8 0.9 73 792 3.9 90
Bucks, PA................ 19.5 249.0 0.3 131 842 2.2 223
Butler, PA............... 4.8 80.3 1.9 23 795 8.8 5
Chester, PA.............. 14.8 234.8 0.5 120 1,069 3.7 108
Cumberland, PA........... 6.0 119.8 -0.5 211 809 3.2 146
Dauphin, PA.............. 7.4 175.7 -1.2 271 846 3.0 167
Delaware, PA............. 13.4 203.8 0.8 87 924 4.3 62
Erie, PA................. 7.6 123.7 2.0 18 716 5.9 20
Lackawanna, PA........... 5.8 97.1 -1.0 258 682 3.5 122
Lancaster, PA............ 12.3 218.0 0.1 152 745 1.8 261
Lehigh, PA............... 8.6 171.4 0.9 73 870 2.4 214
Luzerne, PA.............. 7.7 137.8 0.3 131 699 4.5 55
Montgomery, PA........... 26.9 458.0 -0.9 249 1,058 3.8 97
Northampton, PA.......... 6.4 97.7 0.4 128 780 4.1 75
Philadelphia, PA......... 32.8 627.8 1.6 33 1,054 3.4 128
Washington, PA........... 5.5 80.8 2.7 5 809 6.6 12
Westmoreland, PA......... 9.3 132.1 0.7 96 722 5.6 26
York, PA................. 9.0 169.4 0.3 131 781 4.3 62
Providence, RI........... 17.5 268.7 0.7 96 859 4.1 75
Charleston, SC........... 11.7 204.8 1.6 33 768 3.2 146
Greenville, SC........... 12.0 224.8 1.8 28 758 3.8 97
Horry, SC................ 7.7 108.9 -1.0 258 541 1.5 275
Lexington, SC............ 5.6 92.4 -1.3 276 670 4.0 83
Richland, SC............. 8.9 201.6 -0.6 219 785 2.1 233
Spartanburg, SC.......... 5.9 110.6 -0.4 203 748 3.6 116
Minnehaha, SD............ 6.5 112.5 -0.5 211 760 5.1 32
Davidson, TN............. 18.1 418.3 0.3 131 886 3.3 137
Hamilton, TN............. 8.4 180.8 2.4 10 780 5.1 32
Knox, TN................. 10.8 217.4 0.8 87 748 4.0 83
Rutherford, TN........... 4.3 94.7 (7) - 769 (7) -
Shelby, TN............... 19.1 463.8 -1.1 264 903 5.7 23
Williamson, TN........... 6.1 87.8 (7) - 901 0.8 306
Bell, TX................. 4.7 105.9 3.1 3 748 (7) -
Bexar, TX................ 33.5 719.5 1.0 68 778 3.3 137
Brazoria, TX............. 4.8 86.3 2.5 7 839 5.7 23
Brazos, TX............... 3.9 88.4 (7) - 664 1.8 261
Cameron, TX.............. 6.4 123.8 1.1 61 560 1.3 284
Collin, TX............... 18.0 285.9 2.4 10 999 2.0 246
Dallas, TX............... 67.8 1,415.0 0.9 73 1,032 2.0 246
Denton, TX............... 11.0 172.6 3.2 2 761 1.7 266
El Paso, TX.............. 13.6 271.1 2.2 16 636 2.7 193
Fort Bend, TX............ 9.0 131.0 1.3 52 879 2.3 221
Galveston, TX............ 5.2 94.1 1.5 37 809 0.9 301
Harris, TX............... 100.0 1,995.8 1.1 61 1,083 3.9 90
Hidalgo, TX.............. 10.8 216.8 1.5 37 575 2.0 246
Jefferson, TX............ 6.0 120.0 1.8 28 867 3.3 137
Lubbock, TX.............. 6.9 122.1 -0.3 194 666 3.9 90
McLennan, TX............. 4.8 100.7 -0.9 249 727 5.1 32
Montgomery, TX........... 8.6 128.0 2.3 12 808 5.2 31
Nueces, TX............... 7.9 152.4 1.5 37 745 3.8 97
Potter, TX............... 3.8 74.2 0.7 96 745 3.5 122
Smith, TX................ 5.4 91.5 0.8 87 767 4.1 75
Tarrant, TX.............. 37.5 743.5 0.7 96 881 4.9 45
Travis, TX............... 29.9 568.4 2.0 18 967 3.6 116
Webb, TX................. 4.7 85.2 1.4 46 595 3.7 108
Williamson, TX........... 7.5 120.2 1.5 37 793 1.1 294
Davis, UT................ 7.1 101.5 0.9 73 699 2.5 209
Salt Lake, UT............ 36.7 559.2 0.5 120 822 2.0 246
Utah, UT................. 12.7 165.9 0.9 73 687 3.5 122
Weber, UT................ 5.5 87.9 -1.0 258 661 0.6 310
Chittenden, VT........... 5.9 93.9 1.9 23 870 2.0 246
Arlington, VA............ 8.1 163.2 3.1 3 1,505 6.5 15
Chesterfield, VA......... 7.6 112.8 -0.5 211 806 3.6 116
Fairfax, VA.............. 34.2 576.7 1.3 52 1,374 4.1 75
Henrico, VA.............. 9.7 168.0 -0.1 172 882 3.6 116
Loudoun, VA.............. 9.4 131.4 1.6 33 1,038 2.4 214
Prince William, VA....... 7.5 104.1 1.3 52 801 1.5 275
Alexandria City, VA...... 6.2 95.3 -1.6 297 1,247 3.1 158
Chesapeake City, VA...... 5.7 95.1 0.2 142 708 1.9 256
Newport News City, VA.... 3.9 95.0 -0.4 203 803 1.9 256
Norfolk City, VA......... 5.7 135.8 -0.9 249 849 2.9 175
Richmond City, VA........ 7.2 148.1 -0.5 211 964 1.6 272
Virginia Beach City, VA.. 11.4 164.0 -0.6 219 692 3.7 108
Benton, WA............... 5.7 81.8 2.6 6 959 6.1 17
Clark, WA................ 13.4 127.6 0.0 163 799 2.7 193
King, WA................. 83.0 1,121.8 0.1 152 1,234 4.7 50
Kitsap, WA............... 6.8 80.7 -0.9 249 821 3.0 167
Pierce, WA............... 22.0 264.4 -0.2 186 821 2.6 202
Snohomish, WA............ 19.2 240.5 -0.6 219 937 5.9 20
Spokane, WA.............. 16.3 197.7 -1.7 300 737 2.4 214
Thurston, WA............. 7.4 96.4 -0.7 230 813 0.6 310
Whatcom, WA.............. 7.1 78.2 -0.6 219 709 2.6 202
Yakima, WA............... 9.1 111.3 -0.8 242 599 2.0 246
Kanawha, WV.............. 6.0 105.4 0.0 163 772 2.8 183
Brown, WI................ 6.5 144.1 0.6 107 773 3.8 97
Dane, WI................. 13.8 294.4 0.6 107 837 1.9 256
Milwaukee, WI............ 21.2 467.3 -0.7 230 856 2.8 183
Outagamie, WI............ 5.0 100.4 -0.1 172 737 4.1 75
Waukesha, WI............. 12.7 220.6 0.2 142 865 3.8 97
Winnebago, WI............ 3.7 89.0 1.4 46 792 2.1 233
San Juan, PR............. 11.6 256.5 -3.8 (8) 608 2.5 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 326 U.S. counties comprise 70.6 percent of the total covered workers
in the U.S.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(7) Data do not meet BLS or State agency disclosure standards.
(8) This county was not included in the U.S. rankings.
Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties,
third quarter 2010(2)
Employment Average weekly
wage(3)
Establishments,
third quarter
County by NAICS supersector 2010 Percent Percent
(thousands) September change, Average change,
2010 September weekly third
(thousands) 2009-10(4) wage quarter
2009-10(4)
United States(5)............................. 9,044.4 128,440.4 0.2 $870 3.4
Private industry........................... 8,746.3 107,007.4 0.4 861 4.0
Natural resources and mining............. 126.9 1,926.7 3.3 884 5.7
Construction............................. 796.6 5,686.9 -4.6 946 1.3
Manufacturing............................ 343.4 11,584.3 -0.3 1,074 6.8
Trade, transportation, and utilities..... 1,877.4 24,381.8 -0.2 742 4.4
Information.............................. 144.5 2,701.5 -2.3 1,416 7.4
Financial activities..................... 818.0 7,379.9 -1.7 1,235 4.6
Professional and business services....... 1,544.9 16,869.8 3.3 1,093 3.1
Education and health services............ 893.5 18,661.9 1.9 842 2.8
Leisure and hospitality.................. 748.6 13,292.8 0.7 370 3.6
Other services........................... 1,267.9 4,342.8 -0.1 562 3.5
Government................................. 298.0 21,433.0 -0.8 918 1.2
Los Angeles, CA.............................. 427.0 3,844.5 -0.8 972 3.1
Private industry........................... 421.4 3,311.1 -0.3 948 3.6
Natural resources and mining............. 0.5 10.8 5.9 1,903 45.9
Construction............................. 13.0 104.2 -9.3 1,010 -1.6
Manufacturing............................ 13.5 374.1 -1.7 1,079 4.6
Trade, transportation, and utilities..... 52.2 732.2 0.1 783 2.9
Information.............................. 8.5 196.9 1.2 1,644 3.1
Financial activities..................... 22.4 209.4 -1.1 1,456 8.4
Professional and business services....... 42.0 528.2 0.9 1,145 1.1
Education and health services............ 29.0 508.8 2.6 931 2.6
Leisure and hospitality.................. 27.1 390.4 0.9 544 2.6
Other services........................... 200.8 248.5 -5.9 451 7.9
Government................................. 5.6 533.4 -4.0 1,123 1.1
Cook, IL..................................... 143.4 2,354.8 -0.4 1,008 3.2
Private industry........................... 142.0 2,055.8 -0.1 1,000 3.5
Natural resources and mining............. 0.1 1.0 -8.4 1,051 7.5
Construction............................. 12.2 67.2 -10.0 1,228 -3.3
Manufacturing............................ 6.7 194.3 -1.0 1,069 6.3
Trade, transportation, and utilities..... 27.7 428.9 0.2 784 3.2
Information.............................. 2.6 51.0 -3.5 1,439 6.4
Financial activities..................... 15.4 187.9 -2.8 1,644 7.6
Professional and business services....... 30.2 407.7 2.6 1,259 1.7
Education and health services............ 14.9 391.0 (6) 903 (6)
Leisure and hospitality.................. 12.4 230.9 0.2 463 4.5
Other services........................... 15.4 92.5 (6) 761 5.3
Government................................. 1.4 298.9 -2.5 1,067 1.5
New York, NY................................. 120.9 2,273.0 1.2 1,572 4.7
Private industry........................... 120.6 1,834.9 1.6 1,685 4.6
Natural resources and mining............. 0.0 0.1 -5.0 1,853 -9.3
Construction............................. 2.2 30.5 -7.0 1,608 3.5
Manufacturing............................ 2.5 26.7 -2.5 1,256 6.1
Trade, transportation, and utilities..... 21.1 233.4 2.2 1,130 2.4
Information.............................. 4.4 131.0 -0.8 2,042 7.8
Financial activities..................... 19.0 348.8 1.3 2,903 5.5
Professional and business services....... 25.6 458.2 1.9 1,880 3.8
Education and health services............ 9.1 290.0 1.7 1,147 5.5
Leisure and hospitality.................. 12.3 223.3 3.2 756 3.7
Other services........................... 18.6 86.3 0.2 1,026 9.5
Government................................. 0.3 438.1 -0.6 1,098 3.8
Harris, TX................................... 100.0 1,995.8 1.1 1,083 3.9
Private industry........................... 99.4 1,734.1 1.0 1,095 4.6
Natural resources and mining............. 1.6 75.2 4.0 2,692 3.9
Construction............................. 6.5 133.6 -3.4 1,038 0.6
Manufacturing............................ 4.5 169.0 0.4 1,357 6.6
Trade, transportation, and utilities..... 22.5 415.8 0.2 969 5.4
Information.............................. 1.3 27.9 -5.1 1,298 6.1
Financial activities..................... 10.4 111.4 -2.8 1,283 5.5
Professional and business services....... 19.8 322.3 2.8 1,310 4.6
Education and health services............ 11.1 238.7 3.5 902 3.7
Leisure and hospitality.................. 8.0 179.2 1.2 398 2.3
Other services........................... 13.2 59.8 3.0 620 2.1
Government................................. 0.6 261.7 (6) 1,003 (6)
Maricopa, AZ................................. 95.0 1,597.0 -0.5 859 2.4
Private industry........................... 94.3 1,382.4 -0.3 851 2.9
Natural resources and mining............. 0.5 6.5 -12.0 787 9.8
Construction............................. 8.9 80.4 -10.0 892 2.4
Manufacturing............................ 3.2 106.6 -2.6 1,250 9.6
Trade, transportation, and utilities..... 22.0 328.7 -1.0 797 4.2
Information.............................. 1.5 26.7 1.3 1,118 2.2
Financial activities..................... 11.3 131.2 -2.1 1,025 2.9
Professional and business services....... 22.0 259.5 0.7 896 0.4
Education and health services............ 10.4 231.5 (6) 919 (6)
Leisure and hospitality.................. 6.9 165.5 0.3 409 3.0
Other services........................... 6.8 45.1 -0.3 571 2.5
Government................................. 0.7 214.6 -1.8 915 -0.7
Dallas, TX................................... 67.8 1,415.0 0.9 1,032 2.0
Private industry........................... 67.3 1,246.2 0.9 1,035 2.0
Natural resources and mining............. 0.6 8.4 10.9 2,861 0.1
Construction............................. 4.0 69.2 -3.6 944 -0.4
Manufacturing............................ 2.9 113.1 -3.8 1,174 2.2
Trade, transportation, and utilities..... 14.9 279.8 0.1 961 2.9
Information.............................. 1.6 45.1 -0.3 1,507 3.5
Financial activities..................... 8.5 136.0 -0.8 1,329 2.5
Professional and business services....... 14.8 261.7 3.7 1,175 1.2
Education and health services............ 7.0 165.3 3.4 962 2.2
Leisure and hospitality.................. 5.5 128.5 1.7 462 2.0
Other services........................... 7.0 38.2 1.7 642 1.4
Government................................. 0.5 168.9 1.0 1,005 1.5
Orange, CA................................... 101.7 1,348.8 -0.1 975 2.8
Private industry........................... 100.4 1,215.9 0.3 966 3.2
Natural resources and mining............. 0.2 3.9 -1.9 620 -2.7
Construction............................. 6.4 67.9 -5.0 1,073 -3.1
Manufacturing............................ 5.0 151.0 -0.4 1,244 9.0
Trade, transportation, and utilities..... 16.4 243.5 -0.4 905 4.3
Information.............................. 1.3 24.3 -8.2 1,463 8.0
Financial activities..................... 9.8 104.0 0.2 1,363 5.2
Professional and business services....... 18.8 244.0 2.0 1,092 0.3
Education and health services............ 10.4 154.5 2.9 940 1.4
Leisure and hospitality.................. 7.1 171.7 0.1 431 4.9
Other services........................... 20.7 48.4 0.5 539 2.5
Government................................. 1.4 132.9 -2.9 1,060 0.2
San Diego, CA................................ 97.7 1,238.6 0.4 943 2.7
Private industry........................... 96.3 1,021.5 0.4 917 2.8
Natural resources and mining............. 0.7 10.7 5.6 582 0.7
Construction............................. 6.4 55.7 -5.5 1,045 0.6
Manufacturing............................ 3.0 93.0 0.1 1,326 7.2
Trade, transportation, and utilities..... 13.7 196.4 -0.3 742 1.6
Information.............................. 1.2 25.0 -2.8 1,572 10.1
Financial activities..................... 8.6 66.9 -1.4 1,119 4.0
Professional and business services....... 16.2 210.8 1.8 1,223 0.2
Education and health services............ 8.4 145.5 2.8 907 2.4
Leisure and hospitality.................. 7.0 157.4 0.3 425 4.9
Other services........................... 27.3 57.7 0.1 540 11.6
Government................................. 1.4 217.1 0.2 1,069 (6)
King, WA..................................... 83.0 1,121.8 0.1 1,234 4.7
Private industry........................... 82.4 967.6 0.1 1,248 4.6
Natural resources and mining............. 0.4 2.9 -4.4 1,162 9.5
Construction............................. 6.0 49.1 -8.8 1,134 1.1
Manufacturing............................ 2.3 97.3 -2.4 1,455 10.4
Trade, transportation, and utilities..... 14.9 204.5 0.4 977 6.8
Information.............................. 1.8 79.9 1.0 3,605 6.4
Financial activities..................... 6.6 64.6 -4.4 1,297 -1.3
Professional and business services....... 14.3 177.8 3.2 1,329 4.7
Education and health services............ 7.0 130.3 0.2 930 3.6
Leisure and hospitality.................. 6.5 109.8 -0.1 456 0.2
Other services........................... 22.8 51.4 8.6 572 -4.7
Government................................. 0.6 154.2 0.1 1,142 (6)
Miami-Dade, FL............................... 85.0 940.9 0.3 853 1.5
Private industry........................... 84.7 797.9 0.7 819 1.7
Natural resources and mining............. 0.5 6.8 -0.2 489 0.6
Construction............................. 5.3 31.4 -9.3 859 -0.2
Manufacturing............................ 2.6 34.7 -4.3 805 5.6
Trade, transportation, and utilities..... 24.1 236.4 1.9 757 1.6
Information.............................. 1.5 17.1 -1.5 1,289 5.5
Financial activities..................... 9.0 60.4 -1.0 1,216 5.6
Professional and business services....... 17.8 121.5 0.4 993 -2.8
Education and health services............ 9.6 149.6 1.0 862 4.5
Leisure and hospitality.................. 6.3 104.8 3.7 497 4.6
Other services........................... 7.7 34.8 1.5 553 2.6
Government................................. 0.4 143.0 -1.8 1,047 1.1
(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 by state,
third quarter 2010(2)
Employment Average weekly
wage(3)
Establishments,
third quarter
State 2010 Percent Percent
(thousands) September change, Average change,
2010 September weekly third
(thousands) 2009-10 wage quarter
2009-10
United States(4)......... 9,044.4 128,440.4 0.2 $870 3.4
Alabama.................. 116.8 1,813.9 -0.1 774 4.0
Alaska................... 21.4 333.5 1.3 926 4.4
Arizona.................. 147.2 2,342.3 -0.9 821 2.6
Arkansas................. 85.6 1,147.0 0.8 684 3.8
California............... 1,347.5 14,469.7 -0.3 982 3.3
Colorado................. 173.2 2,183.8 -0.2 898 2.5
Connecticut.............. 111.4 1,611.9 0.0 1,069 4.3
Delaware................. 28.4 404.7 0.8 902 2.4
District of Columbia..... 35.0 693.8 2.0 1,471 1.2
Florida.................. 595.2 7,045.3 0.0 780 2.8
Georgia.................. 268.2 3,749.9 -0.1 823 2.7
Hawaii................... 38.9 585.6 -0.1 804 2.2
Idaho.................... 55.0 616.8 -1.1 667 3.1
Illinois................. 378.6 5,539.5 0.0 916 4.0
Indiana.................. 157.2 2,736.7 0.8 742 3.9
Iowa..................... 94.3 1,439.8 -0.5 719 3.6
Kansas................... 87.5 1,296.1 -1.0 731 3.5
Kentucky................. 110.1 1,728.3 0.8 729 3.3
Louisiana................ 131.0 1,834.8 0.0 790 3.9
Maine.................... 49.2 589.4 -0.6 714 3.6
Maryland................. 163.8 2,469.7 0.5 966 2.7
Massachusetts............ 221.1 3,169.8 0.8 1,069 4.5
Michigan................. 247.6 3,825.9 0.9 840 3.8
Minnesota................ 164.7 2,574.3 0.4 875 4.7
Mississippi.............. 69.5 1,077.4 0.0 653 2.8
Missouri................. 174.5 2,596.8 -0.5 764 2.7
Montana.................. 42.4 428.7 0.0 647 1.6
Nebraska................. 60.0 899.8 -0.2 708 2.8
Nevada................... 71.2 1,106.8 -1.7 815 1.2
New Hampshire............ 48.4 608.9 0.1 854 2.9
New Jersey............... 265.6 3,759.0 -0.4 1,024 2.8
New Mexico............... 54.8 785.9 -1.0 745 2.9
New York................. 591.6 8,364.2 0.5 1,057 4.3
North Carolina........... 251.7 3,806.2 -0.3 768 3.1
North Dakota............. 26.4 366.1 3.0 726 6.8
Ohio..................... 286.4 4,942.1 0.3 791 3.4
Oklahoma................. 102.2 1,487.5 -0.2 726 4.0
Oregon................... 131.0 1,620.5 0.3 791 3.1
Pennsylvania............. 341.0 5,500.9 0.9 860 4.1
Rhode Island............. 35.2 456.0 0.8 826 4.2
South Carolina........... 111.4 1,763.7 0.5 714 3.9
South Dakota............. 30.9 393.7 0.4 660 4.3
Tennessee................ 139.6 2,578.3 0.8 777 4.3
Texas.................... 572.4 10,204.5 1.5 876 3.7
Utah..................... 83.7 1,160.6 0.5 740 2.2
Vermont.................. 24.4 294.3 0.5 752 2.6
Virginia................. 232.9 3,544.1 0.4 930 3.8
Washington............... 237.0 2,855.7 -0.3 953 4.0
West Virginia............ 48.4 699.4 1.1 702 4.3
Wisconsin................ 157.6 2,657.7 0.5 752 3.6
Wyoming.................. 25.2 278.9 0.0 793 4.9
Puerto Rico.............. 49.6 910.0 -2.7 502 1.6
Virgin Islands........... 3.6 43.5 2.3 754 4.3
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs.
(2) Data are preliminary.
(3) Average weekly wages were calculated using unrounded data.
(4) Totals for the United States do not include data for Puerto Rico or the
Virgin Islands.
United States Department of Labor
