For release 10:00 a.m. (EDT), Thursday, June 30, 2011 USDL-11-0962
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
County Employment and Wages
Fourth Quarter 2010
From December 2009 to December 2010, employment increased in 220 of
the 326 largest U.S. counties, the U.S. Bureau of Labor Statistics
reported today. Elkhart, Ind., posted the largest percentage
increase, with a gain of 5.2 percent over the year, compared with
national job growth of 0.9 percent. Within Elkhart, the largest
employment increase occurred in manufacturing, which gained 4,185
jobs over the year (10.3 percent). Manatee, Fla., experienced the
largest over-the-year percentage decrease in employment among the
largest counties in the U.S. with a loss of 4.0 percent.
The U.S. average weekly wage increased over the year by 3.0 percent
to $971 in the fourth quarter of 2010. Among the large counties in
the U.S., Olmsted, Minn., had the largest over-the-year increase in
average weekly wages in the fourth quarter of 2010 with a gain of
31.9 percent. Within Olmsted, education and health services had the
largest impact on the county’s over-the-year increase in average
weekly wages. Union, N.J., experienced the largest decline in average
weekly wages with a loss of 2.8 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 December 2010 employment, December 2009-10 employment
increase, and December 2009-10 percent increase in employment
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Employment in large counties
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December 2010 employment | Increase in employment, | Percent increase in employment,
(thousands) | December 2009-10 | December 2009-10
| (thousands) |
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| |
United States 129,451.6| United States 1,139.2| United States 0.9
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| |
Los Angeles, Calif. 3,931.6| New York, N.Y. 37.5| Elkhart, Ind. 5.2
Cook, Ill. 2,379.8| Harris, Texas 35.6| Benton, Wash. 5.0
New York, N.Y. 2,335.9| Dallas, Texas 22.4| Peoria, Ill. 4.0
Harris, Texas 2,019.3| Maricopa, Ariz. 18.8| Washington, Pa. 4.0
Maricopa, Ariz. 1,643.9| Cook, Ill. 15.9| Lehigh, Pa. 3.7
Dallas, Texas 1,429.9| Kings, N.Y. 15.8| Montgomery, Texas 3.6
Orange, Calif. 1,382.0| King, Wash. 15.7| Kings, N.Y. 3.2
San Diego, Calif. 1,256.1| Travis, Texas 15.2| Washington, Ore. 3.2
King, Wash. 1,131.8| Santa Clara, Calif. 14.0| Denton, Texas 3.2
Miami-Dade, Fla. 970.3| Hennepin, Minn. 12.8| Arlington, Va. 3.0
| |
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Large County Employment
In December 2010, national employment, as measured by the QCEW
program, was 129.5 million, up by 0.9 percent or 1.1 million workers,
from December 2009. The 326 U.S. counties with 75,000 or more
employees accounted for 70.9 percent of total U.S. employment and
76.8 percent of total wages. These 326 counties had a net job growth
of 704,131 over the year, accounting for 61.8 percent of the overall
U.S. employment increase.
Elkhart, Ind., had the largest percentage increase in employment
among the largest U.S. counties. The five counties with the largest
increases in employment level (New York, N.Y.; Harris, Texas; Dallas,
Texas; Maricopa, Ariz.; and Cook, Ill.) had a combined over-the-year
gain of 130,200, or 11.4 percent of the employment increase for the
U.S.
Employment declined in 83 of the large counties from December 2009 to
December 2010. Manatee, Fla., had the largest over-the-year
percentage decrease in employment (-4.0 percent) in the nation.
Within Manatee, professional and business services was the largest
contributor to the decrease in employment with a loss of 14.0
percent. San Joaquin, Calif., experienced the second largest
employment decrease, followed by Volusia, Fla., Marion, Fla., and
Broome, N.Y.
Table B. Top 10 large counties ranked by fourth quarter 2010 average weekly wages, fourth quarter 2009-10
increase in average weekly wages, and fourth quarter 2009-10 percent increase in average weekly wages
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Average weekly wage in large counties
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Average weekly wage, | Increase in average weekly | Percent increase in average
fourth quarter 2010 | wage, fourth quarter 2009-10 | weekly wage, fourth
| | quarter 2009-10
--------------------------------------------------------------------------------------------------------
| |
United States $971| United States $28| United States 3.0
--------------------------------------------------------------------------------------------------------
| |
Santa Clara, Calif. $1,943| Olmsted, Minn. $317| Olmsted, Minn. 31.9
New York, N.Y. 1,929| Santa Clara, Calif. 245| Santa Clara, Calif. 14.4
Washington, D.C. 1,688| Williamson, Tenn. 92| Williamson, Tenn. 9.0
Fairfield, Conn. 1,668| Rock Island, Ill. 90| Rock Island, Ill. 8.1
Arlington, Va. 1,668| San Mateo, Calif. 86| Lake, Ind. 7.6
Suffolk, Mass. 1,651| Arlington, Va. 76| Ottawa, Mich. 6.6
San Francisco, Calif. 1,573| Washington, D.C. 72| Lafayette, La. 6.5
San Mateo, Calif. 1,564| Fulton, Ga. 70| Jefferson, Colo. 6.4
Fairfax, Va. 1,541| Suffolk, Mass. 70| Weld, Colo. 6.2
Somerset, N.J. 1,448| Middlesex, Mass. 69| Lorain, Ohio 6.2
| Alexandria City, Va. 69|
| |
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Large County Average Weekly Wages
Average weekly wages for the nation increased by 3.0 percent over the
year in the fourth quarter of 2010. Among the 326 largest counties,
294 had over-the-year increases in average weekly wages. Olmsted,
Minn., had the largest wage gain among the largest U.S. counties,
31.9 percent. This increase was largely due to a 55.1 percent
increase in average weekly wages in education and health services.
Union, N.J., had the largest wage decline with a loss of 2.8 percent
over the year. Professional and business services contributed
significantly to the county’s overall average weekly wage loss.
Montgomery, Ala., and Montgomery, Pa., had the second largest percent
decline in average weekly wages among the counties, followed by
Collin, Texas, Benton, Ark., and Williamson, Texas.
Ten Largest U.S. Counties
Nine of the 10 largest counties experienced over-the-year percent
increases in employment in December 2010. Harris, Texas, experienced
the largest gain in employment with a 1.8 percent increase. Within
Harris, trade, transportation, and utilities had the largest over-
the-year increase among all private industry groups with a gain of
7,830 workers (1.8 percent). (See table 2.) Employment was unchanged
in Los Angeles, Calif., over the year.
All of the 10 largest U.S. counties had an over-the-year increase in
average weekly wages. San Diego, Calif., experienced the largest
increase in average weekly wages with a gain of 5.3 percent. Within
San Diego, the largest impact on the county’s average weekly wage
growth occurred in professional and business services, where total
wages increased by $268.7 million over the year (6.8 percent).
Maricopa, Ariz., had the smallest wage increase.
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. December 2010 employment and 2010 fourth
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 9.1 million employer reports cover 129.5 million full-
and part- time workers. For additional information about the
quarterly employment and wages data, please read the Technical Note.
Data for the fourth 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 first quarter 2011 is
scheduled to be released on Thursday, September 29, 2011.
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| |
| Upcoming Industry Changes to Quarterly Census of Employment and Wages Data |
| |
| The 2010 data will be the last from the Quarterly Census of Employment |
| and Wages (QCEW) program using the 2007 version of the North American |
| Industry Classification System (NAICS). Beginning with the release of |
| first quarter 2011 data, the program will switch to the 2012 version of |
| the North American Industry Classification System as the basis for the |
| assignment and tabulation of economic data by industry. For more |
| information on the change, please see the Federal Register notice at |
| http://www.census.gov/eos/www/naics/federal_register_notices/notices/fr12my10.pdf. |
| |
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Technical Note
These data are the product of a federal-state cooperative program, the Quarterly
Census of Employment and Wages (QCEW) program, also known as the ES-202 program.
The data are derived from summaries of employment and total pay of workers covered
by state and federal unemployment insurance (UI) legislation and provided by State
Workforce Agencies (SWAs). The summaries are a result of the administration of
state unemployment insurance programs that require most employers to pay quarterly
taxes based on the employment and wages of workers covered by UI. QCEW data in this
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 | | |
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Coverage
Employment and wage data for workers covered by state UI laws are compiled from
quarterly contribution reports submitted to the SWAs by employers. For federal ci-
vilian workers covered by the Unemployment Compensation for Federal Employees
(UCFE) program, employment and wage data are compiled from quarterly reports 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 Online Annual Averages, features comprehensive
information by detailed industry on establishments, employment, and wages for the nation
and all states. The 2009 online 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,
fourth quarter 2010(2)
Employment Average weekly wage(4)
Establishments,
County(3) fourth quarter Percent Ranking Percent Ranking
2010 December change, by Average change, by
(thousands) 2010 December percent weekly fourth percent
(thousands) 2009-10(5) change wage quarter change
2009-10(5)
United States(6)......... 9,093.5 129,451.6 0.9 - $971 3.0 -
Jefferson, AL............ 17.9 332.7 -0.8 284 972 2.6 144
Madison, AL.............. 8.8 179.9 0.0 221 1,087 3.8 71
Mobile, AL............... 9.9 166.3 0.8 151 856 3.0 124
Montgomery, AL........... 6.3 129.4 -0.7 280 873 -2.1 316
Tuscaloosa, AL........... 4.3 83.6 1.8 47 832 4.3 45
Anchorage Borough, AK.... 8.1 149.3 1.1 116 1,031 2.1 192
Maricopa, AZ............. 94.6 1,643.9 1.2 103 937 1.1 251
Pima, AZ................. 19.1 347.1 -0.9 287 846 1.8 210
Benton, AR............... 5.4 93.9 2.0 35 839 -1.6 313
Pulaski, AR.............. 14.9 244.9 0.2 206 872 0.8 271
Washington, AR........... 5.5 90.6 1.7 52 805 3.7 74
Alameda, CA.............. 56.1 631.2 -0.5 268 1,260 4.9 29
Contra Costa, CA......... 30.1 315.0 -1.4 304 1,175 3.9 59
Fresno, CA............... 30.8 326.0 0.5 173 766 0.9 264
Kern, CA................. 18.0 267.1 2.5 21 859 4.8 32
Los Angeles, CA.......... 437.6 3,931.6 0.0 221 1,158 5.2 19
Marin, CA................ 12.0 103.7 1.4 84 1,197 3.6 80
Monterey, CA............. 13.0 144.6 2.2 29 822 -0.1 296
Orange, CA............... 104.5 1,382.0 0.9 139 1,112 4.4 41
Placer, CA............... 11.0 125.5 1.7 52 960 (7) -
Riverside, CA............ 49.2 556.8 -0.9 287 772 2.1 192
Sacramento, CA........... 54.1 577.1 -1.7 307 1,059 4.0 53
San Bernardino, CA....... 50.8 605.4 -0.1 234 825 2.5 152
San Diego, CA............ 100.4 1,256.1 0.5 173 1,075 5.3 17
San Francisco, CA........ 54.8 557.9 1.7 52 1,573 1.7 220
San Joaquin, CA.......... 17.4 197.8 -2.5 315 822 1.0 255
San Luis Obispo, CA...... 9.8 97.8 1.4 84 804 0.6 279
San Mateo, CA............ 24.4 323.5 0.3 199 1,564 5.8 12
Santa Barbara, CA........ 14.7 169.1 0.0 221 919 2.6 144
Santa Clara, CA.......... 62.6 862.3 1.6 69 1,943 14.4 2
Santa Cruz, CA........... 9.2 86.7 0.1 215 848 2.8 133
Solano, CA............... 10.2 123.0 0.3 199 945 4.0 53
Sonoma, CA............... 19.0 176.6 1.0 125 930 4.6 37
Stanislaus, CA........... 15.2 157.0 0.9 139 792 0.5 282
Tulare, CA............... 9.5 140.1 -0.5 268 668 0.3 287
Ventura, CA.............. 24.2 300.9 1.2 103 983 2.7 141
Yolo, CA................. 6.2 92.4 (7) - 915 (7) -
Adams, CO................ 8.9 148.9 0.5 173 875 3.1 118
Arapahoe, CO............. 18.7 272.8 1.1 116 1,116 1.5 232
Boulder, CO.............. 12.8 154.5 1.3 93 1,122 5.2 19
Denver, CO............... 25.1 426.5 1.9 41 1,215 5.4 16
Douglas, CO.............. 9.3 91.0 0.7 163 1,165 -1.2 311
El Paso, CO.............. 16.7 234.2 0.5 173 891 3.1 118
Jefferson, CO............ 17.8 204.3 0.2 206 1,031 6.4 8
Larimer, CO.............. 9.9 127.0 1.7 52 858 1.8 210
Weld, CO................. 5.7 79.4 2.9 11 820 6.2 9
Fairfield, CT............ 32.7 407.4 1.3 93 1,668 3.9 59
Hartford, CT............. 25.3 491.3 0.9 139 1,177 1.7 220
New Haven, CT............ 22.4 352.8 -0.4 259 1,039 2.8 133
New London, CT........... 6.9 125.0 -0.4 259 956 1.5 232
New Castle, DE........... 17.4 267.7 1.1 116 1,123 4.9 29
Washington, DC........... 35.5 698.5 1.6 69 1,688 4.5 38
Alachua, FL.............. 6.6 115.7 -1.1 298 837 3.2 111
Brevard, FL.............. 14.4 188.9 -0.3 251 906 1.0 255
Broward, FL.............. 62.4 692.4 0.2 206 923 2.4 161
Collier, FL.............. 11.6 119.4 0.9 139 849 1.7 220
Duval, FL................ 26.6 439.2 1.0 125 939 2.8 133
Escambia, FL............. 7.8 120.3 0.8 151 771 1.6 226
Hillsborough, FL......... 36.7 575.3 0.2 206 939 1.1 251
Lake, FL................. 7.2 79.5 -0.9 287 671 -0.6 303
Lee, FL.................. 18.4 198.1 0.9 139 775 -1.0 309
Leon, FL................. 8.2 139.7 0.3 199 831 1.7 220
Manatee, FL.............. 9.4 103.5 -4.0 316 741 2.1 192
Marion, FL............... 7.9 89.5 -1.9 312 680 0.6 279
Miami-Dade, FL........... 85.7 970.3 0.9 139 966 1.4 236
Okaloosa, FL............. 6.0 74.1 -0.9 287 801 0.3 287
Orange, FL............... 35.4 661.2 1.9 41 862 1.2 246
Palm Beach, FL........... 49.0 499.9 -0.2 246 977 1.0 255
Pasco, FL................ 9.7 97.9 1.0 125 686 0.9 264
Pinellas, FL............. 30.7 384.7 -1.0 295 891 4.9 29
Polk, FL................. 12.3 193.5 -0.1 234 728 -0.7 305
Sarasota, FL............. 14.4 135.2 -0.1 234 814 1.2 246
Seminole, FL............. 13.8 156.4 -0.4 259 795 0.4 285
Volusia, FL.............. 13.3 149.2 -2.1 314 692 1.8 210
Bibb, GA................. 4.6 79.8 -0.3 251 755 0.8 271
Chatham, GA.............. 7.6 128.4 1.0 125 823 1.2 246
Clayton, GA.............. 4.2 103.4 (7) - 820 (7) -
Cobb, GA................. 20.8 288.4 0.5 173 997 3.2 111
De Kalb, GA.............. 17.6 275.4 -1.0 295 993 2.1 192
Fulton, GA............... 39.9 715.4 (7) - 1,289 5.7 13
Gwinnett, GA............. 23.6 300.7 1.7 52 942 3.7 74
Muscogee, GA............. 4.7 92.3 0.4 187 777 2.6 144
Richmond, GA............. 4.7 98.4 -0.5 268 820 2.8 133
Honolulu, HI............. 24.8 440.6 1.1 116 896 2.4 161
Ada, ID.................. 14.2 193.0 0.0 221 868 5.2 19
Champaign, IL............ 4.2 87.6 -1.8 309 793 -0.3 300
Cook, IL................. 144.6 2,379.8 0.7 163 1,157 1.8 210
Du Page, IL.............. 36.5 556.0 1.4 84 1,125 3.6 80
Kane, IL................. 13.1 191.8 0.8 151 867 1.5 232
Lake, IL................. 21.6 309.2 -0.8 284 1,255 4.8 32
McHenry, IL.............. 8.6 92.9 -0.8 284 817 3.4 97
McLean, IL............... 3.8 85.6 (7) - 925 2.2 180
Madison, IL.............. 6.0 94.5 2.1 31 801 0.5 282
Peoria, IL............... 4.7 101.7 4.0 3 926 3.8 71
Rock Island, IL.......... 3.5 74.3 0.2 206 1,206 8.1 4
St. Clair, IL............ 5.5 94.4 0.1 215 803 2.3 170
Sangamon, IL............. 5.3 127.9 1.2 103 952 2.5 152
Will, IL................. 14.5 195.5 1.2 103 864 3.3 102
Winnebago, IL............ 6.9 125.0 0.8 151 828 3.9 59
Allen, IN................ 9.0 172.5 1.7 52 782 1.0 255
Elkhart, IN.............. 4.9 101.4 5.2 1 739 -0.7 305
Hamilton, IN............. 8.1 109.6 1.5 77 912 3.6 80
Lake, IN................. 10.3 184.6 0.4 187 859 7.6 5
Marion, IN............... 23.7 549.3 0.4 187 965 2.3 170
St. Joseph, IN........... 6.0 115.2 -0.3 251 796 -0.3 300
Vanderburgh, IN.......... 4.8 104.8 0.5 173 835 6.1 11
Linn, IA................. 6.3 126.5 2.0 35 923 4.5 38
Polk, IA................. 14.7 266.4 0.0 221 969 3.9 59
Scott, IA................ 5.2 86.3 1.4 84 796 4.2 49
Johnson, KS.............. 21.1 300.4 0.9 139 994 1.1 251
Sedgwick, KS............. 12.6 240.5 -0.4 259 900 3.2 111
Shawnee, KS.............. 4.9 93.8 0.4 187 811 2.3 170
Wyandotte, KS............ 3.3 80.3 1.7 52 893 0.0 295
Fayette, KY.............. 9.6 177.7 (7) - 847 -0.1 296
Jefferson, KY............ 22.5 416.8 1.7 52 924 1.7 220
Caddo, LA................ 7.5 122.0 0.8 151 817 2.5 152
Calcasieu, LA............ 4.9 82.4 -0.9 287 806 2.8 133
East Baton Rouge, LA..... 14.6 255.7 -1.7 307 904 0.9 264
Jefferson, LA............ 13.9 195.5 0.4 187 911 1.4 236
Lafayette, LA............ 9.1 132.4 1.6 69 946 6.5 7
Orleans, LA.............. 11.0 172.4 1.4 84 1,036 3.0 124
St. Tammany, LA.......... 7.3 76.1 0.7 163 816 (7) -
Cumberland, ME........... 12.5 170.1 1.0 125 875 1.4 236
Anne Arundel, MD......... 14.5 230.0 1.3 93 1,054 (7) -
Baltimore, MD............ 21.3 367.1 -0.1 234 1,022 1.7 220
Frederick, MD............ 6.0 93.1 1.2 103 966 3.4 97
Harford, MD.............. 5.6 82.6 1.4 84 940 4.3 45
Howard, MD............... 8.9 148.7 (7) - 1,182 4.4 41
Montgomery, MD........... 32.9 451.5 1.0 125 1,326 2.2 180
Prince Georges, MD....... 15.7 305.3 0.4 187 1,040 1.0 255
Baltimore City, MD....... 13.7 326.8 -0.4 259 1,157 4.0 53
Barnstable, MA........... 9.3 83.2 0.1 215 836 0.5 282
Bristol, MA.............. 16.4 211.0 1.6 69 860 -0.8 307
Essex, MA................ 21.7 298.4 1.8 47 1,040 2.5 152
Hampden, MA.............. 15.3 196.2 1.7 52 881 -1.1 310
Middlesex, MA............ 49.3 817.3 1.2 103 1,411 5.1 24
Norfolk, MA.............. 24.5 318.6 1.7 52 1,188 3.1 118
Plymouth, MA............. 14.3 172.4 0.5 173 915 0.8 271
Suffolk, MA.............. 23.1 580.1 2.0 35 1,651 4.4 41
Worcester, MA............ 21.5 314.7 1.3 93 969 2.0 198
Genesee, MI.............. 7.4 128.7 0.8 151 834 0.8 271
Ingham, MI............... 6.5 153.6 0.6 169 936 2.6 144
Kalamazoo, MI............ 5.4 107.8 -0.4 259 880 4.4 41
Kent, MI................. 13.9 314.9 2.5 21 871 1.8 210
Macomb, MI............... 17.0 280.2 1.9 41 990 2.0 198
Oakland, MI.............. 37.5 623.3 1.5 77 1,127 2.9 131
Ottawa, MI............... 5.6 100.4 (7) - 842 6.6 6
Saginaw, MI.............. 4.2 81.0 1.0 125 800 1.1 251
Washtenaw, MI............ 8.1 193.6 (7) - 1,009 2.7 141
Wayne, MI................ 31.2 665.1 0.0 221 1,065 3.1 118
Anoka, MN................ 7.1 104.9 -0.7 280 894 4.1 51
Dakota, MN............... 9.7 168.5 0.0 221 950 3.6 80
Hennepin, MN............. 43.1 817.0 1.6 69 1,211 5.0 26
Olmsted, MN.............. 3.3 87.0 -0.2 246 1,312 31.9 1
Ramsey, MN............... 13.9 317.6 0.2 206 1,070 3.1 118
St. Louis, MN............ 5.6 93.3 0.4 187 781 3.9 59
Stearns, MN.............. 4.3 78.4 0.2 206 761 2.0 198
Harrison, MS............. 4.5 82.5 -0.2 246 710 -1.4 312
Hinds, MS................ 6.1 122.9 -1.8 309 847 2.2 180
Boone, MO................ 4.5 82.7 1.3 93 738 3.4 97
Clay, MO................. 5.0 90.9 1.7 52 916 3.9 59
Greene, MO............... 8.0 148.0 -1.0 295 728 2.4 161
Jackson, MO.............. 18.2 341.8 -0.6 275 975 2.5 152
St. Charles, MO.......... 8.2 122.5 2.3 28 754 0.9 264
St. Louis, MO............ 31.9 567.0 -0.6 275 1,046 4.1 51
St. Louis City, MO....... 8.9 216.4 -0.4 259 1,048 3.9 59
Yellowstone, MT.......... 5.9 75.5 -0.2 246 803 4.7 35
Douglas, NE.............. 15.9 315.5 1.2 103 881 0.7 278
Lancaster, NE............ 8.2 154.4 1.1 116 769 2.4 161
Clark, NV................ 47.2 798.2 -1.5 306 870 -0.3 300
Washoe, NV............... 13.7 186.7 -0.3 251 877 1.0 255
Hillsborough, NH......... 12.0 188.4 0.5 173 1,095 2.8 133
Rockingham, NH........... 10.6 134.0 1.5 77 946 1.8 210
Atlantic, NJ............. 6.9 131.5 -1.8 309 824 -0.6 303
Bergen, NJ............... 34.1 433.8 0.2 206 1,229 1.9 205
Burlington, NJ........... 11.3 193.3 -0.9 287 1,044 3.1 118
Camden, NJ............... 12.8 195.9 -1.2 301 1,030 1.8 210
Essex, NJ................ 21.4 342.3 -1.1 298 1,231 1.9 205
Gloucester, NJ........... 6.3 99.0 -1.4 304 870 0.6 279
Hudson, NJ............... 14.1 232.9 0.3 199 1,276 2.6 144
Mercer, NJ............... 11.4 226.9 -0.3 251 1,283 5.0 26
Middlesex, NJ............ 22.3 382.6 -0.5 268 1,178 1.0 255
Monmouth, NJ............. 20.6 245.5 -0.1 234 1,035 0.3 287
Morris, NJ............... 17.8 271.3 -1.1 298 1,420 -0.9 308
Ocean, NJ................ 12.4 144.4 -0.1 234 828 1.3 242
Passaic, NJ.............. 12.5 173.0 0.9 139 1,004 0.8 271
Somerset, NJ............. 10.2 168.0 -0.1 234 1,448 2.8 133
Union, NJ................ 14.9 221.8 0.1 215 1,200 -2.8 318
Bernalillo, NM........... 17.8 312.9 -1.3 302 849 -0.2 299
Albany, NY............... 10.0 219.8 -0.9 287 981 2.2 180
Bronx, NY................ 16.8 234.3 0.5 173 927 0.2 291
Broome, NY............... 4.5 91.3 -1.9 312 762 1.5 232
Dutchess, NY............. 8.2 112.4 0.3 199 976 3.2 111
Erie, NY................. 23.6 456.7 0.9 139 838 2.3 170
Kings, NY................ 50.2 506.0 3.2 7 837 0.2 291
Monroe, NY............... 18.1 373.0 0.3 199 895 1.0 255
Nassau, NY............... 52.6 597.6 0.4 187 1,119 0.9 264
New York, NY............. 121.4 2,335.9 1.6 69 1,929 2.5 152
Oneida, NY............... 5.3 108.3 -0.4 259 762 1.3 242
Onondaga, NY............. 12.8 243.6 -0.6 275 896 2.2 180
Orange, NY............... 10.0 132.2 0.8 151 822 2.4 161
Queens, NY............... 45.3 500.3 1.0 125 941 0.9 264
Richmond, NY............. 8.9 95.9 (7) - 827 (7) -
Rockland, NY............. 9.9 114.9 0.7 163 1,035 3.2 111
Suffolk, NY.............. 50.5 612.8 0.5 173 1,067 1.6 226
Westchester, NY.......... 36.2 406.6 0.1 215 1,333 3.0 124
Buncombe, NC............. 7.9 111.9 1.0 125 747 0.1 294
Catawba, NC.............. 4.4 78.3 1.5 77 734 1.4 236
Cumberland, NC........... 6.2 119.1 -0.1 234 769 2.7 141
Durham, NC............... 7.3 179.8 0.6 169 1,282 3.3 102
Forsyth, NC.............. 9.0 174.8 -0.3 251 876 3.3 102
Guilford, NC............. 14.2 261.7 0.7 163 840 2.1 192
Mecklenburg, NC.......... 32.2 547.8 2.2 29 1,081 3.9 59
New Hanover, NC.......... 7.3 94.9 -0.1 234 803 0.4 285
Wake, NC................. 28.8 437.5 1.5 77 963 3.9 59
Cass, ND................. 5.9 101.1 2.1 31 826 3.9 59
Butler, OH............... 7.3 140.0 1.1 116 841 2.8 133
Cuyahoga, OH............. 36.2 690.7 0.4 187 989 5.2 19
Franklin, OH............. 29.5 658.0 1.5 77 938 2.2 180
Hamilton, OH............. 23.4 486.8 -0.1 234 1,044 3.5 90
Lake, OH................. 6.5 93.3 1.2 103 804 3.5 90
Lorain, OH............... 6.1 92.9 1.0 125 787 6.2 9
Lucas, OH................ 10.4 201.6 1.9 41 847 1.8 210
Mahoning, OH............. 6.2 98.2 0.9 139 707 3.5 90
Montgomery, OH........... 12.3 241.6 0.0 221 857 1.4 236
Stark, OH................ 8.8 151.8 1.7 52 741 3.6 80
Summit, OH............... 14.5 256.8 1.2 103 873 3.9 59
Oklahoma, OK............. 24.3 418.5 2.5 21 907 4.3 45
Tulsa, OK................ 20.3 332.1 0.0 221 887 4.5 38
Clackamas, OR............ 12.4 138.4 0.5 173 869 3.3 102
Jackson, OR.............. 6.5 77.5 1.4 84 700 1.6 226
Lane, OR................. 10.8 135.6 0.1 215 745 2.2 180
Marion, OR............... 9.3 129.6 -0.5 268 744 2.2 180
Multnomah, OR............ 28.9 429.2 2.0 35 979 2.5 152
Washington, OR........... 16.1 240.8 3.2 7 1,070 4.0 53
Allegheny, PA............ 34.9 674.8 0.7 163 1,033 3.3 102
Berks, PA................ 9.0 163.5 1.2 103 869 2.5 152
Bucks, PA................ 19.6 252.1 1.1 116 953 1.9 205
Butler, PA............... 4.8 80.9 2.5 21 855 3.8 71
Chester, PA.............. 14.9 237.8 0.4 187 1,264 2.0 198
Cumberland, PA........... 6.0 121.4 0.0 221 886 1.8 210
Dauphin, PA.............. 7.5 175.9 -0.6 275 955 3.0 124
Delaware, PA............. 13.6 209.1 1.7 52 1,011 0.9 264
Erie, PA................. 7.6 123.9 2.7 17 754 2.4 161
Lackawanna, PA........... 5.9 98.5 -0.7 280 741 1.0 255
Lancaster, PA............ 12.4 219.7 0.8 151 811 2.9 131
Lehigh, PA............... 8.6 177.2 3.7 5 956 4.0 53
Luzerne, PA.............. 7.7 138.5 0.9 139 745 1.4 236
Montgomery, PA........... 27.2 466.4 0.3 199 1,200 -2.1 316
Northampton, PA.......... 6.4 99.3 1.3 93 847 2.5 152
Philadelphia, PA......... 33.0 634.3 1.3 93 1,156 1.2 246
Washington, PA........... 5.5 81.3 4.0 3 881 2.4 161
Westmoreland, PA......... 9.4 131.9 0.8 151 780 3.7 74
York, PA................. 9.1 170.3 1.3 93 838 3.2 111
Providence, RI........... 17.6 269.2 0.6 169 980 3.0 124
Charleston, SC........... 11.6 207.4 2.9 11 843 2.3 170
Greenville, SC........... 12.0 229.1 2.4 26 843 2.3 170
Horry, SC................ 7.5 101.3 1.1 116 585 0.2 291
Lexington, SC............ 5.6 93.5 -0.9 287 717 1.3 242
Richland, SC............. 8.8 203.6 -0.4 259 836 0.8 271
Spartanburg, SC.......... 5.9 112.8 0.8 151 819 2.0 198
Minnehaha, SD............ 6.5 113.5 0.5 173 806 3.7 74
Davidson, TN............. 18.1 422.7 0.8 151 1,051 5.6 14
Hamilton, TN............. 8.4 183.1 2.7 17 864 5.2 19
Knox, TN................. 10.8 218.0 0.4 187 847 3.5 90
Rutherford, TN........... 4.3 95.6 (7) - 861 (7) -
Shelby, TN............... 19.0 472.0 -0.2 246 1,010 3.3 102
Williamson, TN........... 6.1 90.5 2.8 14 1,110 9.0 3
Bell, TX................. 4.7 106.9 2.4 26 769 (7) -
Bexar, TX................ 33.8 728.4 1.2 103 865 2.2 180
Brazoria, TX............. 4.8 87.6 2.6 20 897 4.2 49
Brazos, TX............... 3.9 87.7 0.5 173 714 2.6 144
Cameron, TX.............. 6.4 125.9 1.2 103 610 2.2 180
Collin, TX............... 18.2 292.0 2.9 11 1,091 -1.8 315
Dallas, TX............... 68.1 1,429.9 1.6 69 1,167 3.4 97
Denton, TX............... 11.0 175.9 3.2 7 836 0.8 271
El Paso, TX.............. 13.7 274.9 1.7 52 692 1.3 242
Fort Bend, TX............ 9.1 133.1 2.1 31 981 3.3 102
Galveston, TX............ 5.3 95.8 2.8 14 902 3.2 111
Harris, TX............... 100.7 2,019.3 1.8 47 1,234 3.5 90
Hidalgo, TX.............. 10.9 225.1 2.0 35 611 2.3 170
Jefferson, TX............ 6.0 122.4 2.5 21 953 3.3 102
Lubbock, TX.............. 6.9 125.4 1.7 52 743 3.6 80
McLennan, TX............. 4.8 100.4 -0.3 251 792 2.6 144
Montgomery, TX........... 8.6 131.1 3.6 6 918 4.3 45
Nueces, TX............... 8.0 152.3 0.9 139 826 4.0 53
Potter, TX............... 3.9 75.1 0.8 151 839 5.1 24
Smith, TX................ 5.4 93.2 1.0 125 829 2.2 180
Tarrant, TX.............. 37.6 758.7 1.7 52 978 3.4 97
Travis, TX............... 30.2 576.5 2.7 17 1,092 5.3 17
Webb, TX................. 4.8 87.6 1.8 47 653 5.5 15
Williamson, TX........... 7.5 122.4 2.1 31 887 -1.6 313
Davis, UT................ 7.2 100.2 1.0 125 784 2.3 170
Salt Lake, UT............ 37.2 568.2 1.2 103 923 3.7 74
Utah, UT................. 12.9 167.3 1.8 47 767 3.5 90
Weber, UT................ 5.6 88.2 -0.6 275 720 2.4 161
Chittenden, VT........... 5.9 95.3 2.0 35 961 2.1 192
Arlington, VA............ 8.2 166.0 3.0 10 1,668 4.8 32
Chesterfield, VA......... 7.6 114.5 -0.5 268 879 3.0 124
Fairfax, VA.............. 34.4 585.9 1.9 41 1,541 3.6 80
Henrico, VA.............. 9.8 173.3 1.7 52 958 1.2 246
Loudoun, VA.............. 9.6 135.4 2.8 14 1,194 3.0 124
Prince William, VA....... 7.6 106.3 1.9 41 871 2.6 144
Alexandria City, VA...... 6.2 96.4 -1.3 302 1,441 5.0 26
Chesapeake City, VA...... 5.7 96.7 1.0 125 763 -0.1 296
Newport News City, VA.... 3.9 96.6 -0.1 234 889 1.9 205
Norfolk City, VA......... 5.7 137.5 0.0 221 962 1.8 210
Richmond City, VA........ 7.2 149.0 -0.3 251 1,066 4.7 35
Virginia Beach City, VA.. 11.4 163.0 -0.7 280 768 1.6 226
Benton, WA............... 5.7 79.6 5.0 2 1,023 3.9 59
Clark, WA................ 13.5 128.0 1.3 93 860 2.0 198
King, WA................. 83.9 1,131.8 1.4 84 1,216 3.6 80
Kitsap, WA............... 6.8 81.4 0.0 221 890 3.5 90
Pierce, WA............... 22.2 262.5 0.2 206 864 2.2 180
Snohomish, WA............ 19.4 243.2 1.6 69 971 0.3 287
Spokane, WA.............. 16.4 197.2 -0.5 268 788 1.9 205
Thurston, WA............. 7.5 97.2 0.0 221 848 2.3 170
Whatcom, WA.............. 7.1 77.8 0.6 169 758 3.3 102
Yakima, WA............... 9.1 92.2 1.4 84 653 2.0 198
Kanawha, WV.............. 6.0 105.8 -0.1 234 840 2.4 161
Brown, WI................ 6.6 144.8 1.0 125 868 1.6 226
Dane, WI................. 14.0 300.1 1.1 116 928 3.6 80
Milwaukee, WI............ 21.6 473.2 0.5 173 968 2.3 170
Outagamie, WI............ 5.0 101.1 0.4 187 801 1.6 226
Waukesha, WI............. 12.8 222.3 1.3 93 951 3.6 80
Winnebago, WI............ 3.7 89.8 1.5 77 902 3.7 74
San Juan, PR............. 11.7 269.9 -3.2 (8) 669 2.8 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 326 U.S. counties comprise 70.9 percent of the total covered workers
in the U.S.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(7) Data do not meet BLS or State agency disclosure standards.
(8) This county was not included in the U.S. rankings.
Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties,
fourth quarter 2010(2)
Employment Average weekly
wage(3)
Establishments,
fourth quarter
County by NAICS supersector 2010 Percent Percent
(thousands) December change, Average change,
2010 December weekly fourth
(thousands) 2009-10(4) wage quarter
2009-10(4)
United States(5)............................. 9,093.5 129,451.6 0.9 $971 3.0
Private industry........................... 8,795.6 107,606.5 1.2 973 3.2
Natural resources and mining............. 127.7 1,723.4 4.6 1,056 7.1
Construction............................. 790.8 5,392.7 -2.9 1,060 0.6
Manufacturing............................ 342.8 11,569.9 0.7 1,206 5.1
Trade, transportation, and utilities..... 1,882.5 25,333.3 1.1 806 2.9
Information.............................. 144.7 2,715.0 -1.8 1,513 4.5
Financial activities..................... 816.7 7,431.1 -0.9 1,487 4.4
Professional and business services....... 1,557.6 17,073.9 3.4 1,289 4.1
Education and health services............ 899.7 18,949.5 1.8 924 1.4
Leisure and hospitality.................. 751.9 12,850.8 1.8 409 2.5
Other services........................... 1,289.6 4,363.2 0.5 604 2.5
Government................................. 298.0 21,845.1 -0.8 962 2.1
Los Angeles, CA.............................. 437.6 3,931.6 0.0 1,158 5.2
Private industry........................... 432.0 3,358.5 0.4 1,156 5.6
Natural resources and mining............. 0.5 9.6 4.2 1,797 21.3
Construction............................. 13.1 102.8 -5.8 1,148 -0.7
Manufacturing............................ 13.5 371.6 -1.1 1,204 3.4
Trade, transportation, and utilities..... 52.2 761.8 0.8 884 3.4
Information.............................. 8.5 198.5 0.8 2,234 9.3
Financial activities..................... 22.5 211.5 -0.6 1,601 7.2
Professional and business services....... 42.1 540.9 1.7 1,464 8.6
Education and health services............ 29.0 511.8 (6) 1,065 (6)
Leisure and hospitality.................. 27.3 387.9 1.2 931 2.0
Other services........................... 204.3 243.6 -4.5 477 6.0
Government................................. 5.6 573.0 -2.4 1,165 2.6
Cook, IL..................................... 144.6 2,379.8 0.7 1,157 1.8
Private industry........................... 143.2 2,079.8 1.1 1,161 1.7
Natural resources and mining............. 0.1 0.9 0.8 1,154 3.3
Construction............................. 12.3 61.5 -8.0 1,420 0.6
Manufacturing............................ 6.7 194.9 0.0 1,251 7.8
Trade, transportation, and utilities..... 27.8 448.2 1.5 888 5.8
Information.............................. 2.6 51.1 -3.6 1,550 -3.4
Financial activities..................... 15.4 188.5 -1.7 1,979 -4.5
Professional and business services....... 30.4 414.2 3.2 1,584 3.2
Education and health services............ 15.0 398.9 2.7 976 0.1
Leisure and hospitality.................. 12.5 224.1 1.4 469 3.5
Other services........................... 15.6 93.4 -0.8 822 3.8
Government................................. 1.4 299.9 -2.4 1,129 2.8
New York, NY................................. 121.4 2,335.9 1.6 1,929 2.5
Private industry........................... 121.1 1,894.9 2.4 2,126 2.4
Natural resources and mining............. 0.0 0.1 5.0 3,306 58.3
Construction............................. 2.2 30.2 -3.1 1,966 -4.9
Manufacturing............................ 2.5 26.8 0.9 1,915 22.4
Trade, transportation, and utilities..... 21.0 249.0 3.1 1,350 2.7
Information.............................. 4.4 131.5 0.0 2,279 6.8
Financial activities..................... 19.0 352.9 2.2 4,222 0.6
Professional and business services....... 25.5 469.3 2.3 2,328 5.1
Education and health services............ 9.2 303.0 1.2 1,203 1.8
Leisure and hospitality.................. 12.4 236.2 5.1 922 -0.5
Other services........................... 18.7 88.8 0.7 1,117 -0.4
Government................................. 0.3 441.0 (6) 1,094 (6)
Harris, TX................................... 100.7 2,019.3 1.8 1,234 3.5
Private industry........................... 100.2 1,755.8 2.2 1,269 3.7
Natural resources and mining............. 1.6 76.3 6.4 3,203 1.8
Construction............................. 6.5 130.3 -2.6 1,206 -1.6
Manufacturing............................ 4.5 171.7 1.9 1,588 5.0
Trade, transportation, and utilities..... 22.6 432.0 1.8 1,101 5.4
Information.............................. 1.3 28.3 -4.8 1,423 2.9
Financial activities..................... 10.5 112.9 0.1 1,542 4.9
Professional and business services....... 19.9 324.4 (6) 1,579 5.7
Education and health services............ 11.2 240.4 3.3 977 -1.3
Leisure and hospitality.................. 8.2 178.4 2.2 420 1.4
Other services........................... 13.4 60.1 3.2 682 3.5
Government................................. 0.6 263.6 -0.6 1,004 1.3
Maricopa, AZ................................. 94.6 1,643.9 1.2 937 1.1
Private industry........................... 93.9 1,428.3 1.6 940 1.6
Natural resources and mining............. 0.5 7.9 -0.4 822 -4.1
Construction............................. 8.7 79.5 -3.9 990 -1.6
Manufacturing............................ 3.2 107.5 -1.1 1,332 3.9
Trade, transportation, and utilities..... 21.8 346.4 1.0 862 4.2
Information.............................. 1.5 27.5 5.3 1,252 0.6
Financial activities..................... 11.2 134.6 0.0 1,131 2.6
Professional and business services....... 21.9 271.3 2.8 1,032 1.8
Education and health services............ 10.4 235.9 (6) 1,028 (6)
Leisure and hospitality.................. 6.9 170.4 1.8 444 1.1
Other services........................... 6.8 46.3 2.8 636 -3.0
Government................................. 0.7 215.7 -1.6 919 -2.2
Dallas, TX................................... 68.1 1,429.9 1.6 1,167 3.4
Private industry........................... 67.6 1,259.4 1.7 1,185 3.6
Natural resources and mining............. 0.6 8.9 16.7 3,908 3.9
Construction............................. 4.0 67.5 -0.3 1,125 -0.8
Manufacturing............................ 2.9 112.8 -1.8 1,372 7.8
Trade, transportation, and utilities..... 14.9 288.4 1.0 1,046 5.3
Information.............................. 1.6 45.0 -1.6 1,643 3.6
Financial activities..................... 8.5 137.0 0.1 1,486 4.2
Professional and business services....... 14.9 266.0 4.0 1,403 2.1
Education and health services............ 7.1 167.6 3.8 1,080 1.1
Leisure and hospitality.................. 5.5 127.0 1.8 527 2.9
Other services........................... 7.1 38.3 -0.1 704 5.4
Government................................. 0.5 170.5 1.0 1,034 1.5
Orange, CA................................... 104.5 1,382.0 0.9 1,112 4.4
Private industry........................... 103.1 1,237.8 1.2 1,119 4.8
Natural resources and mining............. 0.2 3.3 -3.5 677 5.3
Construction............................. 6.4 67.3 -0.8 1,237 2.6
Manufacturing............................ 5.0 151.7 0.4 1,368 5.8
Trade, transportation, and utilities..... 16.4 254.7 0.4 1,008 3.9
Information.............................. 1.3 24.6 -4.3 1,625 1.1
Financial activities..................... 9.8 105.6 1.1 1,871 13.4
Professional and business services....... 18.9 248.3 2.2 1,308 2.4
Education and health services............ 10.4 158.2 (6) 1,045 (6)
Leisure and hospitality.................. 7.2 169.3 1.2 422 1.9
Other services........................... 21.1 48.4 -0.5 560 0.9
Government................................. 1.4 144.1 -1.7 1,057 1.1
San Diego, CA................................ 100.4 1,256.1 0.5 1,075 5.3
Private industry........................... 99.1 1,029.5 0.6 1,065 5.7
Natural resources and mining............. 0.7 9.0 1.7 627 2.3
Construction............................. 6.4 54.5 -5.8 1,174 -0.8
Manufacturing............................ 3.0 92.8 (6) 1,482 (6)
Trade, transportation, and utilities..... 13.7 207.1 0.5 809 3.1
Information.............................. 1.2 24.9 -3.7 1,607 9.5
Financial activities..................... 8.7 68.2 -0.2 1,477 24.5
Professional and business services....... 16.2 209.0 -0.7 1,559 7.3
Education and health services............ 8.5 147.9 2.5 1,013 2.4
Leisure and hospitality.................. 7.0 152.3 2.0 444 1.1
Other services........................... 27.9 58.3 1.4 530 4.1
Government................................. 1.4 226.6 0.0 1,124 (6)
King, WA..................................... 83.9 1,131.8 1.4 1,216 3.6
Private industry........................... 83.3 974.5 1.7 1,226 3.7
Natural resources and mining............. 0.4 2.5 -5.1 1,472 9.3
Construction............................. 6.0 45.7 -5.5 1,244 -1.0
Manufacturing............................ 2.3 97.1 -0.7 1,489 -0.9
Trade, transportation, and utilities..... 15.0 212.3 2.5 1,036 4.2
Information.............................. 1.8 79.3 1.3 2,093 3.6
Financial activities..................... 6.6 64.4 -2.5 1,449 -4.7
Professional and business services....... 14.4 180.6 5.0 1,625 11.5
Education and health services............ 7.1 133.4 1.5 1,004 3.4
Leisure and hospitality.................. 6.5 107.5 1.6 480 2.3
Other services........................... 23.3 51.7 5.6 596 -0.3
Government................................. 0.6 157.3 -0.2 1,156 (6)
Miami-Dade, FL............................... 85.7 970.3 0.9 966 1.4
Private industry........................... 85.3 826.1 1.6 938 1.5
Natural resources and mining............. 0.5 9.1 -5.1 522 8.3
Construction............................. 5.1 31.0 -6.5 982 0.8
Manufacturing............................ 2.6 34.4 -3.9 934 2.4
Trade, transportation, and utilities..... 24.5 249.0 2.8 849 1.2
Information.............................. 1.5 17.3 -3.0 1,419 3.2
Financial activities..................... 9.0 61.6 -0.2 1,412 0.9
Professional and business services....... 18.0 126.6 2.0 1,291 4.3
Education and health services............ 9.7 151.8 1.1 930 1.5
Leisure and hospitality.................. 6.4 109.6 5.2 534 -0.9
Other services........................... 7.7 35.5 1.5 591 2.4
Government................................. 0.4 144.2 -2.5 1,122 0.9
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs.
(2) Data are preliminary.
(3) Average weekly wages were calculated using unrounded data.
(4) 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,
fourth quarter 2010(2)
Employment Average weekly
wage(3)
Establishments,
fourth quarter
State 2010 Percent Percent
(thousands) December change, Average change,
2010 December weekly fourth
(thousands) 2009-10 wage quarter
2009-10
United States(4)......... 9,093.5 129,451.6 0.9 $971 3.0
Alabama.................. 116.9 1,823.8 0.3 839 2.4
Alaska................... 21.3 306.6 1.4 987 2.9
Arizona.................. 146.2 2,417.0 0.5 892 1.4
Arkansas................. 84.6 1,143.4 0.5 738 1.8
California............... 1,375.4 14,561.6 0.6 1,128 5.0
Colorado................. 169.8 2,203.9 0.9 1,001 3.7
Connecticut.............. 111.3 1,628.6 0.5 1,226 2.8
Delaware................. 28.2 404.9 1.5 1,003 4.4
District of Columbia..... 35.5 698.5 1.6 1,688 4.5
Florida.................. 595.6 7,258.9 0.7 871 1.8
Georgia.................. 268.7 3,790.7 0.7 906 3.4
Hawaii................... 38.9 598.0 0.8 859 1.9
Idaho.................... 54.9 601.7 -0.4 733 3.5
Illinois................. 381.4 5,573.7 0.9 1,035 2.9
Indiana.................. 158.4 2,743.6 1.2 804 2.9
Iowa..................... 94.7 1,446.1 0.6 797 3.4
Kansas................... 88.3 1,311.7 0.2 812 2.5
Kentucky................. 110.5 1,747.7 1.3 794 1.7
Louisiana................ 126.5 1,849.5 0.3 863 3.5
Maine.................... 49.5 578.3 -0.1 769 1.3
Maryland................. 164.6 2,488.6 1.0 1,080 2.7
Massachusetts............ 223.5 3,188.2 1.4 1,217 3.3
Michigan................. 246.4 3,817.3 1.3 938 2.7
Minnesota................ 165.5 2,579.6 0.6 974 5.0
Mississippi.............. 69.6 1,081.6 0.4 706 1.3
Missouri................. 175.1 2,596.8 -0.1 839 2.8
Montana.................. 42.3 419.5 0.1 721 3.6
Nebraska................. 60.7 902.9 0.7 772 2.0
Nevada................... 71.5 1,114.5 -0.8 880 0.6
New Hampshire............ 48.5 610.0 0.6 978 2.1
New Jersey............... 270.0 3,792.0 -0.2 1,161 1.5
New Mexico............... 55.3 786.7 -0.1 817 2.8
New York................. 593.4 8,507.7 1.0 1,219 2.1
North Carolina........... 253.4 3,831.7 0.7 840 2.7
North Dakota............. 26.5 368.8 4.3 809 7.6
Ohio..................... 287.6 4,963.5 1.1 865 3.0
Oklahoma................. 102.6 1,506.9 1.2 797 4.5
Oregon................... 130.9 1,609.4 1.0 852 2.8
Pennsylvania............. 343.6 5,547.3 1.3 951 2.0
Rhode Island............. 35.2 450.8 0.5 940 3.1
South Carolina........... 109.7 1,770.6 1.2 775 1.6
South Dakota............. 31.0 391.1 1.4 714 3.8
Tennessee................ 139.6 2,599.4 1.1 878 3.5
Texas.................... 575.5 10,352.8 2.0 977 3.4
Utah..................... 84.8 1,170.2 1.1 827 3.9
Vermont.................. 24.3 299.3 0.9 814 1.1
Virginia................. 234.4 3,578.5 0.8 1,028 3.3
Washington............... 238.9 2,803.1 1.0 981 2.9
West Virginia............ 48.7 698.0 0.6 778 3.5
Wisconsin................ 158.6 2,665.9 1.1 836 3.2
Wyoming.................. 25.1 270.5 1.3 872 4.9
Puerto Rico.............. 49.8 956.7 -2.3 559 1.5
Virgin Islands........... 3.6 44.9 2.0 805 8.3
(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
