For release 10:00 a.m. (EDT), Thursday, September 29, 2011 USDL-11-1397
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
County Employment and Wages
First Quarter 2011
From March 2010 to March 2011, employment increased in 256 of the 322
largest U.S. counties, the U.S. Bureau of Labor Statistics reported
today. Elkhart, Ind., posted the largest percentage increase, with a
gain of 6.2 percent over the year, compared with national job growth
of 1.3 percent. Within Elkhart, the largest employment increase
occurred in manufacturing, which gained 5,125 jobs over the year
(12.4 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 1.6 percent.
The U.S. average weekly wage increased over the year by 5.2 percent
to $935 in the first quarter of 2011. Among the large counties in the
U.S., Peoria, Ill., had the largest over-the-year increase in average
weekly wages in the first quarter of 2011 with a gain of 18.9
percent. Within Peoria, professional and business services had the
largest impact on the county’s over-the-year increase in average
weekly wages. Williamson, Texas, experienced the largest decline in
average weekly wages with a loss of 3.8 percent over the year. County
employment and wage data are compiled under the Quarterly Census of
Employment and Wages (QCEW) program.
Table A. Large counties ranked by March 2011 employment, March 2010-11 employment
increase, and March 2010-11 percent increase in employment
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Employment in large counties
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March 2011 employment | Increase in employment, | Percent increase in employment,
(thousands) | March 2010-11 | March 2010-11
| (thousands) |
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| |
United States 127,851.0| United States 1,622.8| United States 1.3
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| |
Los Angeles, Calif. 3,887.9| Harris, Texas 44.6| Elkhart, Ind. 6.2
Cook, Ill. 2,333.9| New York, N.Y. 43.4| Ottawa, Mich. 4.7
New York, N.Y. 2,304.1| Los Angeles, Calif. 37.3| Washington, Pa. 4.3
Harris, Texas 2,014.4| Orange, Calif. 26.7| Prince William, Va. 4.3
Maricopa, Ariz. 1,628.8| Dallas, Texas 26.7| Benton, Wash. 4.3
Dallas, Texas 1,416.9| Santa Clara, Calif. 24.6| Butler, Pa. 4.2
Orange, Calif. 1,370.6| Cook, Ill. 22.9| Loudoun, Va. 4.2
San Diego, Calif. 1,239.7| Maricopa, Ariz. 21.1| Williamson, Tenn. 4.1
King, Wash. 1,117.2| King, Wash. 20.0| Washington, Ore. 4.0
Miami-Dade, Fla. 967.7| Hennepin, Minn. 19.3| Collier, Fla. 3.8
| |
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Large County Employment
In March 2011, national employment, as measured by the QCEW program,
was 127.9 million, up by 1.3 percent or 1.6 million workers, from
March 2010. The 322 U.S. counties with 75,000 or more employees
accounted for 70.7 percent of total U.S. employment and 77.4 percent
of total wages. These 322 counties had a net job growth of 1,054,300
over the year, accounting for 65.0 percent of the overall U.S.
employment increase.
Elkhart, Ind., had the largest percentage increase in employment
among the largest U.S. counties (6.2 percent). The five counties with
the largest increases in employment level were Harris, Texas; New
York, N.Y.; Los Angeles, Calif.; Orange, Calif.; and Dallas, Texas.
These counties had a combined over-the-year gain of 178,700, or 11.0
percent of the employment increase for the U.S.
Employment declined in 53 of the large counties from March 2010 to
March 2011. Sacramento, Calif., had the largest over-the-year
percentage decrease in employment (-1.6 percent). Within Sacramento,
construction was the largest contributor to the decrease in
employment with a loss of 9.5 percent. Montgomery, Ala., and
Atlantic, N.J., tied for the second largest employment decrease,
followed by San Joaquin, Calif., Marion, Fla., and Champaign, Ill.,
which tied for the third largest decline. (See table 1.)
Table B. Large counties ranked by first quarter 2011 average weekly wages, first quarter 2010-11
increase in average weekly wages, and first quarter 2010-11 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
first quarter 2011 | wage, first quarter 2010-11 | weekly wage, first
| | quarter 2010-11
--------------------------------------------------------------------------------------------------------
| |
United States $935| United States $46| United States 5.2
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| |
New York, N.Y. $2,634| New York, N.Y. $222| Peoria, Ill. 18.9
Fairfield, Conn. 1,888| Santa Clara, Calif. 205| Santa Clara, Calif. 12.4
Somerset, N.J. 1,867| Peoria, Ill. 150| Macomb, Mich. 12.0
Santa Clara, Calif. 1,863| Somerset, N.J. 114| Clayton, Ga. 11.9
San Francisco, Calif. 1,723| San Francisco, Calif. 112| Wayne, Mich. 11.3
Suffolk, Mass. 1,625| Fulton, Ga. 111| Brazoria, Texas 10.0
Arlington, Va. 1,549| Wayne, Mich. 104| Saginaw, Mich. 9.8
Washington, D.C. 1,540| Fairfield, Conn. 102| Stark, Ohio 9.7
Hudson, N.J. 1,509| Hartford, Conn. 102| Butler, Pa. 9.3
San Mateo, Calif. 1,485| Macomb, Mich. 101| New York, N.Y. 9.2
| |
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Large County Average Weekly Wages
Average weekly wages for the nation increased by 5.2 percent over the
year in the first quarter of 2011. Among the 322 largest counties,
315 had over-the-year increases in average weekly wages. Peoria, Ill.,
had the largest wage gain among the largest U.S. counties (18.9 percent).
Of the 322 largest counties, 3 experienced declines in average weekly
wages. Williamson, Texas, had the largest wage decline with a loss of
3.8 percent over the year. Trade, transportation, and utilities
contributed significantly to the county’s overall average weekly wage
loss. Hudson, N.J., had the second largest percent decline in average
weekly wages among the counties, followed by Durham, N.C. (See table
1.)
Ten Largest U.S. Counties
All of the 10 largest counties experienced over-the-year percent
increases in employment in March 2011. Harris, Texas, experienced the
largest gain in employment (2.3 percent). Within Harris, professional
and business services had the largest over-the-year increase among
all private industry groups with a gain of 16,522 workers (5.3
percent). Los Angeles, Calif., and Cook, Ill., both had the smallest
percent increase in employment. (See table 2.)
All of the 10 largest U.S. counties had an over-the-year increase in
average weekly wages. New York, N.Y., experienced the largest
increase in average weekly wages with a gain of 9.2 percent. Within
New York, the largest impact on the county’s average weekly wage
growth occurred in financial activities, largely due to significant
total wage gains over the year ($5,287.0 million or 15.4 percent).
Orange, Calif., had the smallest average weekly wage increase.
For More Information
The tables and charts included in this release contain data for the
nation and for the 322 U.S. counties with annual average employment
levels of 75,000 or more in 2010. March 2011 employment and 2011
first 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 127.9 million full-
and part-time workers. For additional information about the
quarterly employment and wages data, please read the Technical Note.
Data for the first quarter of 2011 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 second quarter 2011 is
scheduled to be released on Tuesday, January 10, 2012.
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| |
| Industry Changes to Quarterly Census of Employment and Wages Data |
| |
| Beginning with the Quarterly Census of Employment and Wages data |
| presented in this release, the Bureau of Labor Statistics is introducing |
| 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/fr17au11.pdf.|
| For more information on the impact of the change, please see |
| http://www.bls.gov/cew/naics2012.htm. |
| |
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| |
| County Changes for the 2011 County Employment and Wages News Releases |
| |
| Counties with annual average employment of 75,000 or more in 2010 are included |
| in this release and will be included in future 2011 releases. Four counties |
| will be excluded: Okaloosa, Fla., Rock Island, Ill., St. Tammany, La., and |
| Potter, Texas. No counties have been added to the publication tables. |
| |
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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 2012 North American Industry Classification System. Data
for 2011 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 323 counties presented
in this release were derived using 2010 preliminary annual averages of employment.
For 2011 data, four counties, Okaloosa, Fla., Rock Island, Ill., St. Tammany, La.,
and Potter, Texas, which were published in the 2010 releases, will be excluded from
this and future 2011 releases because their 2010 annual average employment levels
were less than 75,000. No counties have been added to the publication tables.
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- | 440,000 establish-
| submitted by 9.1 | ministrative records| ments
| million establish- | submitted by 6.7 |
| ments in first | million private-sec-|
| quarter of 2011 | 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 2010. 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 2010, UI and UCFE programs covered workers in 127.8 million jobs. The estimated
123.2 million workers in these jobs (after adjustment for multiple jobholders)
represented 95.3 percent of civilian wage and salary employment. Covered workers
received $5.976 trillion in pay, representing 93.3 percent of the wage and salary
component of personal income and 41.1 percent of the gross domestic product.
Major exclusions from UI coverage include self-employed workers, most agricultural
workers on small farms, all members of the Armed Forces, elected officials in most
states, most employees of railroads, some domestic workers, most student workers at
schools, and employees of certain small nonprofit organizations.
State and federal UI laws change periodically. These changes may have an impact on
the employment and wages reported by employers covered under the UI program. Cover-
age changes may affect the over-the-year comparisons presented in this news 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 2010 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
Employment and Wages Annual Averages Online features comprehensive information
by detailed industry on establishments, employment, and wages for the nation and
all states. The 2009 edition of this publication, which was published in March 2011,
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 print version of the
annual bulletin, Employment and Wages Annual Averages. Tables and additional content
from Employment and Wages Annual Averages Online, 2009 are now available online at
http://www.bls.gov/cew/cewbultn09.htm. The 2010 edition of Employment and Wages
Annual Averages Online will be available later in 2011.
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 323 largest counties,
first quarter 2011(2)
Employment Average weekly wage(4)
Establishments,
County(3) first quarter Percent Ranking Percent Ranking
2011 March change, by First change, by
(thousands) 2011 March percent quarter first percent
(thousands) 2010-11(5) change 2011 quarter change
2010-11(5)
United States(6)......... 9,074.3 127,851.0 1.3 - $935 5.2 -
Jefferson, AL............ 17.8 328.8 -0.5 280 919 4.9 99
Madison, AL.............. 8.8 176.4 -0.8 294 978 4.4 134
Mobile, AL............... 9.8 165.0 0.9 169 741 4.7 111
Montgomery, AL........... 6.3 127.2 -1.5 314 764 4.1 157
Tuscaloosa, AL........... 4.2 83.1 1.5 106 778 5.9 64
Anchorage Borough, AK.... 8.1 147.4 1.7 86 958 2.6 264
Maricopa, AZ............. 93.8 1,628.8 1.3 132 889 5.1 89
Pima, AZ................. 18.9 344.0 -0.7 290 768 4.2 148
Benton, AR............... 5.4 92.5 (7) - 1,110 6.5 45
Pulaski, AR.............. 15.1 241.6 0.3 229 819 5.5 80
Washington, AR........... 5.5 89.2 (7) - 726 4.6 116
Alameda, CA.............. 56.4 632.2 -0.1 264 1,183 4.0 165
Contra Costa, CA......... 30.3 312.6 -0.1 264 1,210 6.4 49
Fresno, CA............... 30.9 322.4 1.6 97 709 3.4 200
Kern, CA................. 18.0 259.5 1.8 80 790 4.2 148
Los Angeles, CA.......... 438.0 3,887.9 1.0 158 1,046 6.6 43
Marin, CA................ 11.9 101.5 2.4 42 1,103 7.2 29
Monterey, CA............. 13.0 148.1 -0.3 274 808 1.6 301
Orange, CA............... 104.8 1,370.6 2.0 65 1,035 3.3 213
Placer, CA............... 10.9 126.2 1.3 132 876 4.5 125
Riverside, CA............ 50.1 559.0 -0.1 264 748 3.2 219
Sacramento, CA........... 54.3 573.9 -1.6 316 1,025 5.1 89
San Bernardino, CA....... 51.5 592.0 -0.3 274 754 3.3 213
San Diego, CA............ 100.7 1,239.7 1.4 118 1,003 7.2 29
San Francisco, CA........ 55.1 548.6 2.9 26 1,723 7.0 35
San Joaquin, CA.......... 17.4 196.0 -1.4 311 752 3.2 219
San Luis Obispo, CA...... 9.7 100.0 1.1 148 742 2.1 285
San Mateo, CA............ 24.6 322.3 1.5 106 1,485 1.6 301
Santa Barbara, CA........ 14.6 173.9 1.4 118 869 5.1 89
Santa Clara, CA.......... 63.1 857.3 3.0 19 1,863 12.4 2
Santa Cruz, CA........... 9.1 87.3 1.5 106 814 2.1 285
Solano, CA............... 10.2 118.1 0.2 242 921 2.7 260
Sonoma, CA............... 18.9 174.9 1.6 97 846 3.4 200
Stanislaus, CA........... 15.2 156.5 -0.2 271 748 2.5 268
Tulare, CA............... 9.5 134.7 1.1 148 622 2.8 248
Ventura, CA.............. 24.3 300.6 1.4 118 964 4.4 134
Yolo, CA................. 6.2 89.0 (7) - 892 (7) -
Adams, CO................ 8.8 151.3 0.8 180 806 4.1 157
Arapahoe, CO............. 18.6 272.0 2.0 65 1,130 2.7 260
Boulder, CO.............. 12.8 153.1 1.7 86 1,050 3.9 170
Denver, CO............... 25.0 417.8 2.0 65 1,212 5.0 94
Douglas, CO.............. 9.3 87.9 0.6 196 1,069 7.1 34
El Paso, CO.............. 16.7 232.0 1.4 118 812 2.9 242
Jefferson, CO............ 17.7 200.3 0.5 206 929 3.7 183
Larimer, CO.............. 9.9 124.4 1.2 139 795 5.3 83
Weld, CO................. 5.7 80.6 3.6 12 776 7.6 22
Fairfield, CT............ 32.4 396.3 2.3 49 1,888 5.7 73
Hartford, CT............. 25.3 481.1 1.1 148 1,260 8.8 11
New Haven, CT............ 22.2 344.3 0.9 169 956 4.7 111
New London, CT........... 6.9 122.0 0.0 257 960 4.7 111
New Castle, DE........... 17.5 261.9 1.6 97 1,194 6.3 51
Washington, DC........... 34.8 702.3 2.5 35 1,540 2.4 272
Alachua, FL.............. 6.5 115.4 0.2 242 730 3.5 197
Brevard, FL.............. 14.3 187.1 -0.5 280 801 2.2 279
Broward, FL.............. 61.8 682.9 0.3 229 834 3.2 219
Collier, FL.............. 11.5 119.6 3.8 10 767 4.1 157
Duval, FL................ 26.5 439.1 1.8 80 891 3.1 226
Escambia, FL............. 7.8 120.1 0.8 180 690 4.2 148
Hillsborough, FL......... 36.6 574.6 0.7 188 880 4.5 125
Lake, FL................. 7.1 79.3 1.1 148 586 2.8 248
Lee, FL.................. 18.2 199.9 1.4 118 711 4.3 143
Leon, FL................. 8.1 137.9 0.4 216 722 1.0 310
Manatee, FL.............. 9.3 104.1 0.3 229 668 3.6 188
Marion, FL............... 7.8 89.0 -1.4 311 614 2.8 248
Miami-Dade, FL........... 85.5 967.7 1.9 74 874 3.4 200
Orange, FL............... 35.2 655.7 2.1 56 805 4.4 134
Palm Beach, FL........... 48.7 496.5 0.7 188 886 4.4 134
Pasco, FL................ 9.7 98.6 2.4 42 596 2.8 248
Pinellas, FL............. 30.1 379.7 -1.1 304 765 2.8 248
Polk, FL................. 12.3 191.4 -0.5 280 668 3.9 170
Sarasota, FL............. 14.2 135.3 1.4 118 722 2.4 272
Seminole, FL............. 13.7 154.4 -0.5 280 735 3.1 226
Volusia, FL.............. 13.2 151.0 -0.7 290 629 2.8 248
Bibb, GA................. 4.6 79.0 0.1 249 699 2.5 268
Chatham, GA.............. 7.6 128.0 0.7 188 752 3.9 170
Clayton, GA.............. 4.2 101.5 1.0 158 844 11.9 4
Cobb, GA................. 20.6 285.6 0.7 188 962 4.0 165
De Kalb, GA.............. 17.4 272.4 1.0 158 992 6.0 60
Fulton, GA............... 39.7 710.8 1.2 139 1,370 8.8 11
Gwinnett, GA............. 23.4 298.6 2.7 30 879 3.4 200
Muscogee, GA............. 4.6 92.8 0.9 169 749 5.9 64
Richmond, GA............. 4.6 99.3 1.7 86 743 3.9 170
Honolulu, HI............. 24.5 436.5 1.5 106 821 3.1 226
Ada, ID.................. 14.0 190.0 0.4 216 773 4.9 99
Champaign, IL............ 4.2 86.3 -1.4 311 750 2.9 242
Cook, IL................. 145.1 2,333.9 1.0 158 1,145 5.8 70
Du Page, IL.............. 36.5 546.6 1.8 80 1,076 3.4 200
Kane, IL................. 13.2 187.8 0.9 169 777 2.8 248
Lake, IL................. 21.7 303.1 (7) - 1,230 (7) -
McHenry, IL.............. 8.6 89.7 -0.5 280 727 4.5 125
McLean, IL............... 3.8 84.8 0.1 249 904 2.1 285
Madison, IL.............. 6.0 94.3 2.0 65 738 2.1 285
Peoria, IL............... 4.7 99.8 2.5 35 944 18.9 1
St. Clair, IL............ 5.5 93.6 0.6 196 709 2.0 293
Sangamon, IL............. 5.3 125.9 1.2 139 907 3.4 200
Will, IL................. 14.7 192.9 0.9 169 793 5.0 94
Winnebago, IL............ 6.8 122.9 0.3 229 769 7.6 22
Allen, IN................ 9.0 170.4 2.1 56 747 4.0 165
Elkhart, IN.............. 4.9 102.5 6.2 1 698 5.4 82
Hamilton, IN............. 8.3 107.8 2.5 35 924 6.6 43
Lake, IN................. 10.3 181.1 0.6 196 791 5.6 77
Marion, IN............... 23.8 542.2 1.0 158 987 3.6 188
St. Joseph, IN........... 6.0 114.9 0.7 188 723 3.1 226
Vanderburgh, IN.......... 4.8 104.0 0.1 249 729 5.7 73
Linn, IA................. 6.2 123.4 1.7 86 847 3.9 170
Polk, IA................. 14.5 260.6 -0.5 280 940 4.9 99
Scott, IA................ 5.2 84.2 1.1 148 725 6.1 57
Johnson, KS.............. 21.1 295.8 1.5 106 955 2.5 268
Sedgwick, KS............. 12.5 237.6 0.1 249 816 6.9 37
Shawnee, KS.............. 4.9 93.9 -1.1 304 751 4.3 143
Wyandotte, KS............ 3.3 79.3 1.8 80 826 4.4 134
Fayette, KY.............. 9.6 169.5 1.7 86 811 6.0 60
Jefferson, KY............ 22.6 407.9 1.3 132 873 3.4 200
Caddo, LA................ 7.5 120.4 0.5 206 736 6.8 38
Calcasieu, LA............ 5.0 82.2 0.2 242 768 4.8 105
East Baton Rouge, LA..... 14.7 254.2 0.1 249 831 2.8 248
Jefferson, LA............ 14.0 192.1 0.4 216 831 3.6 188
Lafayette, LA............ 9.1 132.0 2.3 49 847 4.7 111
Orleans, LA.............. 11.1 173.1 1.2 139 983 3.0 236
Cumberland, ME........... 12.5 164.1 1.3 132 835 4.8 105
Anne Arundel, MD......... 14.5 224.7 1.1 148 958 (7) -
Baltimore, MD............ 21.1 357.7 0.3 229 920 2.3 276
Frederick, MD............ 6.0 90.4 0.3 229 904 5.9 64
Harford, MD.............. 5.6 81.4 2.5 35 844 4.5 125
Howard, MD............... 8.9 147.7 2.5 35 1,141 6.5 45
Montgomery, MD........... 32.9 445.7 2.0 65 1,311 3.9 170
Prince Georges, MD....... 15.7 297.8 0.6 196 933 2.1 285
Baltimore City, MD....... 13.7 327.8 0.6 196 1,081 3.7 183
Barnstable, MA........... 9.3 78.3 0.1 249 759 4.5 125
Bristol, MA.............. 16.6 205.0 1.4 118 791 6.3 51
Essex, MA................ 22.0 291.6 1.7 86 955 6.3 51
Hampden, MA.............. 15.5 191.7 1.4 118 812 1.0 310
Middlesex, MA............ 49.9 796.6 0.9 169 1,370 7.3 27
Norfolk, MA.............. 24.8 309.4 0.5 206 1,066 4.5 125
Plymouth, MA............. 14.5 166.6 0.6 196 815 5.0 94
Suffolk, MA.............. 23.5 574.8 1.4 118 1,625 5.0 94
Worcester, MA............ 21.8 309.2 1.6 97 908 7.2 29
Genesee, MI.............. 7.3 126.1 0.0 257 742 8.3 15
Ingham, MI............... 6.4 151.0 -0.4 277 879 6.0 60
Kalamazoo, MI............ 5.3 106.2 0.9 169 816 5.0 94
Kent, MI................. 13.7 310.0 3.0 19 792 3.4 200
Macomb, MI............... 16.8 277.6 3.0 19 941 12.0 3
Oakland, MI.............. 37.0 618.7 2.7 30 1,019 7.5 24
Ottawa, MI............... 5.5 101.2 4.7 2 714 6.1 57
Saginaw, MI.............. 4.1 79.1 1.6 97 760 9.8 7
Washtenaw, MI............ 8.0 188.9 2.1 56 925 1.1 307
Wayne, MI................ 30.7 660.6 1.5 106 1,021 11.3 5
Anoka, MN................ 7.1 104.0 0.3 229 829 7.2 29
Dakota, MN............... 9.7 165.0 0.3 229 895 3.6 188
Hennepin, MN............. 43.5 805.9 2.4 42 1,197 7.7 20
Olmsted, MN.............. 3.4 85.4 -0.3 274 968 3.4 200
Ramsey, MN............... 13.9 310.1 0.2 242 1,093 6.2 55
St. Louis, MN............ 5.7 91.2 0.2 242 722 5.6 77
Stearns, MN.............. 4.3 77.2 2.5 35 700 2.2 279
Harrison, MS............. 4.5 82.0 0.7 188 668 1.7 300
Hinds, MS................ 6.0 121.6 -1.1 304 778 3.9 170
Boone, MO................ 4.4 82.0 1.0 158 692 3.1 226
Clay, MO................. 5.0 89.3 0.8 180 850 2.4 272
Greene, MO............... 8.0 147.0 -0.6 287 661 4.6 116
Jackson, MO.............. 18.0 338.9 0.0 257 894 1.6 301
St. Charles, MO.......... 8.1 120.2 2.2 53 744 1.6 301
St. Louis, MO............ 31.8 560.8 0.1 249 973 3.6 188
St. Louis City, MO....... 8.8 212.1 -0.6 287 1,037 2.8 248
Yellowstone, MT.......... 5.9 74.6 0.0 257 721 4.6 116
Douglas, NE.............. 15.8 307.4 0.9 169 853 3.1 226
Lancaster, NE............ 8.1 151.5 0.4 216 711 3.6 188
Clark, NV................ 47.2 795.2 0.4 216 790 1.8 297
Washoe, NV............... 13.6 179.9 -0.8 294 789 3.4 200
Hillsborough, NH......... 11.8 185.0 1.3 132 975 5.9 64
Rockingham, NH........... 10.5 129.7 1.3 132 857 5.7 73
Atlantic, NJ............. 6.8 128.3 -1.5 314 772 2.8 248
Bergen, NJ............... 33.5 420.2 0.6 196 1,152 2.8 248
Burlington, NJ........... 11.1 189.1 -1.1 304 957 3.5 197
Camden, NJ............... 12.4 191.3 -0.9 298 903 5.7 73
Essex, NJ................ 20.9 336.0 -0.8 294 1,229 4.5 125
Gloucester, NJ........... 6.2 96.4 0.3 229 766 1.1 307
Hudson, NJ............... 13.8 229.4 0.0 257 1,509 -1.5 317
Mercer, NJ............... 11.2 226.1 0.5 206 1,283 5.3 83
Middlesex, NJ............ 21.9 371.7 -0.2 271 1,191 4.6 116
Monmouth, NJ............. 20.2 237.4 -0.7 290 945 2.7 260
Morris, NJ............... 17.4 264.9 -0.5 280 1,462 2.5 268
Ocean, NJ................ 12.2 140.2 -0.2 271 746 3.2 219
Passaic, NJ.............. 12.2 169.1 0.5 206 921 3.1 226
Somerset, NJ............. 10.1 164.9 0.4 216 1,867 6.5 45
Union, NJ................ 14.6 215.1 -0.9 298 1,199 1.9 294
Bernalillo, NM........... 17.6 308.5 -0.4 277 781 2.6 264
Albany, NY............... 10.0 215.2 -0.9 298 937 2.9 242
Bronx, NY................ 17.0 234.1 0.8 180 818 3.2 219
Broome, NY............... 4.5 89.5 -1.0 302 703 4.5 125
Dutchess, NY............. 8.1 109.3 -0.1 264 917 1.8 297
Erie, NY................. 23.7 444.8 0.5 206 794 4.6 116
Kings, NY................ 50.9 503.9 3.7 11 725 1.1 307
Monroe, NY............... 18.1 366.1 0.5 206 847 3.4 200
Nassau, NY............... 52.7 578.6 0.4 216 1,015 3.3 213
New York, NY............. 121.9 2,304.1 1.9 74 2,634 9.2 10
Oneida, NY............... 5.3 104.6 -1.3 310 708 4.1 157
Onondaga, NY............. 12.8 236.8 -0.1 264 831 4.3 143
Orange, NY............... 10.0 128.2 1.5 106 755 2.2 279
Queens, NY............... 45.7 494.0 1.6 97 844 4.2 148
Richmond, NY............. 9.0 90.8 1.8 80 758 3.6 188
Rockland, NY............. 9.9 112.0 1.2 139 991 2.6 264
Suffolk, NY.............. 50.8 596.3 0.7 188 972 4.2 148
Westchester, NY.......... 36.2 397.8 1.0 158 1,332 1.4 305
Buncombe, NC............. 7.8 110.5 2.1 56 676 4.8 105
Catawba, NC.............. 4.4 78.4 2.8 28 692 7.5 24
Cumberland, NC........... 6.2 118.9 1.3 132 695 4.2 148
Durham, NC............... 7.1 177.8 1.4 118 1,276 -0.5 316
Forsyth, NC.............. 8.9 170.6 -0.8 294 891 7.9 18
Guilford, NC............. 14.0 260.6 1.7 86 802 4.8 105
Mecklenburg, NC.......... 31.9 546.4 2.8 28 1,231 7.3 27
New Hanover, NC.......... 7.2 96.2 2.1 56 741 4.2 148
Wake, NC................. 28.6 437.2 3.3 14 917 1.9 294
Cass, ND................. 5.9 100.2 3.0 19 765 6.7 41
Butler, OH............... 7.3 136.5 0.4 216 781 0.5 314
Cuyahoga, OH............. 35.7 675.4 0.5 206 953 7.4 26
Franklin, OH............. 29.2 644.1 1.4 118 920 4.4 134
Hamilton, OH............. 23.1 478.5 0.8 180 992 4.1 157
Lake, OH................. 6.5 90.9 0.4 216 774 3.6 188
Lorain, OH............... 6.1 91.3 2.5 35 750 7.0 35
Lucas, OH................ 10.3 196.4 1.5 106 793 5.9 64
Mahoning, OH............. 6.1 94.5 1.7 86 632 4.6 116
Montgomery, OH........... 12.2 238.9 0.8 180 782 3.3 213
Stark, OH................ 8.7 148.5 2.2 53 703 9.7 8
Summit, OH............... 14.3 248.9 0.3 229 841 2.2 279
Oklahoma, OK............. 24.4 413.5 2.0 65 837 5.5 80
Tulsa, OK................ 20.2 324.5 0.2 242 825 5.1 89
Clackamas, OR............ 12.5 135.2 0.6 196 798 3.4 200
Jackson, OR.............. 6.5 73.2 -1.1 304 644 2.7 260
Lane, OR................. 10.8 134.7 0.9 169 672 3.4 200
Marion, OR............... 9.3 128.0 -1.0 302 699 1.9 294
Multnomah, OR............ 29.0 424.9 2.0 65 918 5.2 85
Washington, OR........... 16.2 239.4 4.0 9 1,120 6.8 38
Allegheny, PA............ 35.1 666.8 1.5 106 997 5.2 85
Berks, PA................ 9.0 161.7 1.4 118 780 4.0 165
Bucks, PA................ 19.6 244.9 0.5 206 855 3.1 226
Butler, PA............... 4.8 80.2 4.2 6 799 9.3 9
Chester, PA.............. 14.9 233.3 1.1 148 1,164 2.9 242
Cumberland, PA........... 6.0 120.5 1.1 148 815 3.7 183
Dauphin, PA.............. 7.4 173.3 0.4 216 889 4.6 116
Delaware, PA............. 13.6 205.3 1.7 86 1,003 3.7 183
Erie, PA................. 7.6 121.9 3.2 15 695 6.8 38
Lackawanna, PA........... 5.8 96.4 -0.4 277 665 2.9 242
Lancaster, PA............ 12.4 214.0 0.4 216 734 4.7 111
Lehigh, PA............... 8.6 170.4 2.0 65 879 3.8 180
Luzerne, PA.............. 7.7 136.3 1.0 158 684 4.1 157
Montgomery, PA........... 27.1 456.4 0.2 242 1,198 2.1 285
Northampton, PA.......... 6.4 97.6 0.6 196 791 4.6 116
Philadelphia, PA......... 33.7 628.0 1.2 139 1,079 4.5 125
Washington, PA........... 5.5 80.2 4.3 3 867 8.8 11
Westmoreland, PA......... 9.3 128.8 1.1 148 716 6.1 57
York, PA................. 9.0 168.2 1.6 97 789 3.5 197
Providence, RI........... 17.4 263.9 0.0 257 895 2.3 276
Charleston, SC........... 11.6 206.6 2.9 26 774 5.9 64
Greenville, SC........... 12.1 228.3 2.7 30 770 5.2 85
Horry, SC................ 7.5 101.9 0.4 216 534 2.9 242
Lexington, SC............ 5.6 93.5 0.9 169 650 4.0 165
Richland, SC............. 8.8 201.8 -0.9 298 794 3.1 226
Spartanburg, SC.......... 5.8 110.9 1.5 106 761 2.6 264
Minnehaha, SD............ 6.5 111.9 1.4 118 748 4.9 99
Davidson, TN............. 18.1 415.0 1.0 158 927 3.2 219
Hamilton, TN............. 8.4 181.0 2.0 65 785 0.1 315
Knox, TN................. 10.7 215.4 1.9 74 750 3.0 236
Rutherford, TN........... 4.3 95.7 1.6 97 771 2.1 285
Shelby, TN............... 18.9 458.0 0.1 249 915 4.9 99
Williamson, TN........... 6.1 89.6 4.1 8 1,054 4.4 134
Bell, TX................. 4.7 106.9 2.4 42 736 4.1 157
Bexar, TX................ 33.8 730.6 1.4 118 838 6.5 45
Brazoria, TX............. 4.9 87.8 3.2 15 922 10.0 6
Brazos, TX............... 3.9 86.7 -1.1 304 659 3.0 236
Cameron, TX.............. 6.4 126.5 1.5 106 546 3.0 236
Collin, TX............... 18.2 291.0 3.1 17 1,075 5.8 70
Dallas, TX............... 67.9 1,416.9 1.9 74 1,156 5.2 85
Denton, TX............... 11.1 175.2 3.0 19 780 3.9 170
El Paso, TX.............. 13.8 272.8 0.8 180 626 3.3 213
Fort Bend, TX............ 9.2 133.0 2.4 42 979 8.2 16
Galveston, TX............ 5.3 95.1 2.6 34 827 4.4 134
Harris, TX............... 100.9 2,014.4 2.3 49 1,258 7.7 20
Hidalgo, TX.............. 11.0 226.0 2.3 49 556 3.2 219
Jefferson, TX............ 6.0 120.9 1.9 74 920 8.1 17
Lubbock, TX.............. 7.0 124.4 2.2 53 653 2.8 248
McLennan, TX............. 4.8 99.8 0.3 229 727 3.0 236
Montgomery, TX........... 8.7 130.8 3.0 19 886 7.9 18
Nueces, TX............... 7.9 152.7 -0.1 264 748 6.4 49
Smith, TX................ 5.4 92.0 0.9 169 739 3.8 180
Tarrant, TX.............. 37.6 750.5 1.7 86 900 3.3 213
Travis, TX............... 30.5 576.1 2.7 30 1,002 6.0 60
Webb, TX................. 4.8 87.6 2.4 42 590 4.8 105
Williamson, TX........... 7.6 128.4 3.0 19 953 -3.8 318
Davis, UT................ 7.1 100.8 (7) - 704 2.3 276
Salt Lake, UT............ 36.2 559.5 1.7 86 856 3.8 180
Utah, UT................. 12.5 164.9 3.1 17 681 3.7 183
Weber, UT................ 5.4 87.9 -0.1 264 642 2.4 272
Chittenden, VT........... 5.9 92.8 2.1 56 878 3.1 226
Arlington, VA............ 8.2 166.6 3.6 12 1,549 0.8 313
Chesterfield, VA......... 7.5 113.0 0.8 180 830 4.1 157
Fairfax, VA.............. 34.4 572.9 2.1 56 1,479 4.4 134
Henrico, VA.............. 9.7 171.5 1.2 139 1,027 6.3 51
Loudoun, VA.............. 9.7 134.7 4.2 6 1,093 2.1 285
Prince William, VA....... 7.6 108.3 4.3 3 808 1.3 306
Alexandria City, VA...... 6.2 93.6 (7) - 1,226 (7) -
Chesapeake City, VA...... 5.7 94.0 1.0 158 724 4.2 148
Newport News City, VA.... 3.8 95.3 0.6 196 826 4.3 143
Norfolk City, VA......... 5.7 137.7 0.7 188 861 3.6 188
Richmond City, VA........ 7.0 148.5 1.1 148 1,071 4.9 99
Virginia Beach City, VA.. 11.2 159.4 -0.7 290 717 5.8 70
Benton, WA............... 5.7 80.8 4.3 3 959 4.8 105
Clark, WA................ 13.3 125.7 0.4 216 800 4.3 143
King, WA................. 83.1 1,117.2 1.8 80 1,185 5.6 77
Kitsap, WA............... 6.7 80.2 0.0 257 798 1.8 297
Pierce, WA............... 21.8 259.3 0.3 229 821 3.0 236
Snohomish, WA............ 19.2 241.1 2.1 56 968 8.8 11
Spokane, WA.............. 15.9 194.3 -0.6 287 751 4.6 116
Thurston, WA............. 7.4 96.5 0.3 229 800 1.0 310
Whatcom, WA.............. 7.0 77.7 1.6 97 745 6.7 41
Yakima, WA............... 8.9 95.0 1.2 139 606 2.2 279
Kanawha, WV.............. 5.9 104.4 1.2 139 797 5.1 89
Brown, WI................ 6.6 142.6 0.5 206 803 4.2 148
Dane, WI................. 14.0 293.6 1.5 106 878 6.2 55
Milwaukee, WI............ 21.6 464.6 1.0 158 929 7.2 29
Outagamie, WI............ 5.0 99.1 2.1 56 747 3.9 170
Waukesha, WI............. 12.7 217.9 2.4 42 902 3.9 170
Winnebago, WI............ 3.7 88.5 1.9 74 831 2.2 279
San Juan, PR............. 11.9 259.7 -2.5 (8) 598 -0.2 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 322 U.S. counties comprise 70.7 percent of the total covered workers
in the U.S.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(7) Data do not meet BLS or State agency disclosure standards.
(8) This county was not included in the U.S. rankings.
Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties,
first quarter 2011(2)
Employment Average weekly
wage(3)
Establishments,
first quarter
County by NAICS supersector 2011 Percent Percent
(thousands) March change, First change,
2011 March quarter first
(thousands) 2010-11(4) 2011 quarter
2010-11(4)
United States(5)............................. 9,074.3 127,851.0 1.3 $935 5.2
Private industry........................... 8,776.1 106,054.4 1.8 941 5.7
Natural resources and mining............. 127.3 1,701.7 5.3 1,116 9.7
Construction............................. 774.2 5,137.6 -0.9 917 2.6
Manufacturing............................ 339.8 11,556.7 1.9 1,164 7.8
Trade, transportation, and utilities..... 1,875.9 24,316.5 1.3 766 5.5
Information.............................. 143.9 2,659.8 -1.8 1,609 9.7
Financial activities..................... 811.3 7,354.6 -0.3 1,886 10.2
Professional and business services....... 1,553.4 16,972.0 4.1 1,212 5.1
Education and health services............ 902.8 18,941.2 1.9 793 3.1
Leisure and hospitality.................. 752.2 12,842.6 2.3 363 2.8
Other services........................... 1,297.0 4,349.8 1.2 559 3.5
Government................................. 298.2 21,796.6 -1.3 902 2.0
Los Angeles, CA.............................. 438.0 3,887.9 1.0 1,046 6.6
Private industry........................... 432.4 3,321.8 1.6 1,030 7.6
Natural resources and mining............. 0.5 10.0 -0.9 1,645 7.2
Construction............................. 12.7 102.4 -2.8 1,000 4.0
Manufacturing............................ 13.2 368.7 -0.7 1,149 7.1
Trade, transportation, and utilities..... 51.5 735.0 1.7 804 5.8
Information.............................. 8.3 186.1 1.0 1,997 10.1
Financial activities..................... 22.1 209.6 -0.5 1,907 12.0
Professional and business services....... 41.2 546.4 2.1 1,265 6.2
Education and health services............ 28.8 511.8 2.7 912 4.9
Leisure and hospitality.................. 26.9 387.9 2.9 589 13.9
Other services........................... 205.8 243.0 -2.6 442 5.2
Government................................. 5.7 566.1 -2.4 1,139 2.5
Cook, IL..................................... 145.1 2,333.9 1.0 1,145 5.8
Private industry........................... 143.7 2,033.8 1.6 1,154 6.1
Natural resources and mining............. 0.1 0.8 -2.9 782 -5.1
Construction............................. 12.2 56.4 -2.8 1,276 -0.2
Manufacturing............................ 6.6 193.7 1.0 1,104 7.6
Trade, transportation, and utilities..... 28.1 427.4 1.5 841 8.5
Information.............................. 2.6 51.3 -1.1 1,849 8.4
Financial activities..................... 15.4 184.8 -2.0 2,867 15.7
Professional and business services....... 30.4 400.1 2.6 1,432 1.6
Education and health services............ 15.1 402.1 3.0 835 2.3
Leisure and hospitality.................. 12.6 219.8 2.4 422 5.0
Other services........................... 15.8 93.3 0.8 743 3.5
Government................................. 1.4 300.1 -2.8 1,085 (6)
New York, NY................................. 121.9 2,304.1 1.9 2,634 9.2
Private industry........................... 121.6 1,865.2 3.0 2,995 8.9
Natural resources and mining............. 0.0 0.2 25.6 2,745 22.8
Construction............................. 2.2 29.7 -2.5 1,609 4.1
Manufacturing............................ 2.5 25.6 -1.3 1,644 9.1
Trade, transportation, and utilities..... 21.1 234.7 3.2 1,252 6.5
Information.............................. 4.4 131.8 1.1 2,751 11.4
Financial activities..................... 19.0 351.8 2.6 8,684 12.3
Professional and business services....... 25.4 460.8 2.9 2,512 3.5
Education and health services............ 9.3 302.8 0.7 1,065 5.1
Leisure and hospitality.................. 12.6 232.3 6.7 762 8.1
Other services........................... 18.9 87.4 2.1 1,270 7.2
Government................................. 0.3 438.9 -2.3 1,095 4.1
Harris, TX................................... 100.9 2,014.4 2.3 1,258 7.7
Private industry........................... 100.4 1,749.9 2.7 1,302 8.1
Natural resources and mining............. 1.6 77.4 7.3 4,206 7.5
Construction............................. 6.5 131.5 -2.4 1,092 2.7
Manufacturing............................ 4.5 172.6 4.0 1,607 9.4
Trade, transportation, and utilities..... 22.6 419.4 2.2 1,167 8.5
Information.............................. 1.3 28.2 -1.6 1,378 6.7
Financial activities..................... 10.5 111.6 -0.3 1,882 13.9
Professional and business services....... 20.0 326.7 5.3 1,441 (6)
Education and health services............ 11.3 240.6 2.6 876 4.2
Leisure and hospitality.................. 8.1 180.9 3.0 384 0.8
Other services........................... 13.5 60.1 1.5 658 7.5
Government................................. 0.6 264.4 -0.6 968 3.1
Maricopa, AZ................................. 93.8 1,628.8 1.3 889 5.1
Private industry........................... 93.1 1,412.8 1.8 898 5.4
Natural resources and mining............. 0.5 7.6 5.0 1,152 16.4
Construction............................. 8.5 77.7 -2.5 884 1.7
Manufacturing............................ 3.2 107.8 1.0 1,439 13.6
Trade, transportation, and utilities..... 21.7 331.8 1.4 847 6.8
Information.............................. 1.5 27.0 0.6 1,208 6.5
Financial activities..................... 11.0 134.2 1.7 1,270 7.4
Professional and business services....... 22.0 264.7 2.7 925 3.0
Education and health services............ 10.4 237.5 2.9 864 1.6
Leisure and hospitality.................. 6.9 176.0 2.3 409 1.7
Other services........................... 6.6 47.9 2.4 585 5.0
Government................................. 0.7 215.9 -2.0 829 2.5
Dallas, TX................................... 67.9 1,416.9 1.9 1,156 5.2
Private industry........................... 67.3 1,248.2 2.2 1,180 5.5
Natural resources and mining............. 0.6 8.7 11.5 4,366 10.2
Construction............................. 4.0 66.2 0.2 960 2.8
Manufacturing............................ 2.9 113.7 -0.2 1,501 16.7
Trade, transportation, and utilities..... 14.8 280.1 1.8 982 3.9
Information.............................. 1.6 45.5 0.0 2,078 11.7
Financial activities..................... 8.4 137.6 0.9 1,879 8.3
Professional and business services....... 14.8 263.0 3.8 1,251 1.2
Education and health services............ 7.1 166.2 3.4 941 2.2
Leisure and hospitality.................. 5.6 127.8 3.3 474 -1.0
Other services........................... 7.1 38.8 2.2 628 3.6
Government................................. 0.5 168.7 -0.3 975 1.9
Orange, CA................................... 104.8 1,370.6 2.0 1,035 3.3
Private industry........................... 103.4 1,224.2 2.4 1,014 3.8
Natural resources and mining............. 0.2 4.3 -15.9 635 12.6
Construction............................. 6.3 67.1 -0.4 1,049 1.5
Manufacturing............................ 5.0 150.3 1.3 1,239 3.8
Trade, transportation, and utilities..... 16.1 242.5 0.4 944 5.4
Information.............................. 1.2 24.0 -3.1 1,796 -1.1
Financial activities..................... 9.7 103.4 1.7 1,629 2.5
Professional and business services....... 18.6 248.5 3.9 1,204 5.2
Education and health services............ 10.3 159.0 (6) 883 3.8
Leisure and hospitality.................. 7.2 168.9 3.6 408 4.9
Other services........................... 21.6 48.8 1.6 516 3.0
Government................................. 1.4 146.4 -1.6 1,214 0.9
San Diego, CA................................ 100.7 1,239.7 1.4 1,003 7.2
Private industry........................... 99.2 1,017.7 1.7 989 8.4
Natural resources and mining............. 0.7 11.4 2.8 491 1.2
Construction............................. 6.2 54.7 -0.2 1,033 5.5
Manufacturing............................ 3.0 92.5 -0.1 1,458 9.1
Trade, transportation, and utilities..... 13.6 195.4 0.9 797 7.3
Information.............................. 1.2 24.3 -2.6 1,624 12.5
Financial activities..................... 8.5 67.1 0.4 1,343 8.7
Professional and business services....... 16.0 210.1 2.2 1,432 13.4
Education and health services............ 8.4 146.5 2.9 880 4.0
Leisure and hospitality.................. 7.0 152.5 1.5 387 2.4
Other services........................... 28.3 56.7 0.7 499 4.2
Government................................. 1.4 222.0 0.0 1,068 2.2
King, WA..................................... 83.1 1,117.2 1.8 1,185 5.6
Private industry........................... 82.5 959.8 2.2 1,198 6.1
Natural resources and mining............. 0.4 2.5 -0.3 1,492 -3.4
Construction............................. 5.8 43.5 -4.5 1,108 0.1
Manufacturing............................ 2.3 97.6 0.8 1,579 14.0
Trade, transportation, and utilities..... 14.9 204.8 3.3 1,029 8.4
Information.............................. 1.8 79.0 1.0 2,280 5.2
Financial activities..................... 6.5 63.4 -1.7 1,647 6.9
Professional and business services....... 14.2 177.6 4.8 1,431 5.8
Education and health services............ 7.2 134.3 3.4 887 3.5
Leisure and hospitality.................. 6.5 105.3 1.3 424 -2.3
Other services........................... 22.9 51.7 2.7 591 2.1
Government................................. 0.6 157.4 -0.1 1,107 2.5
Miami-Dade, FL............................... 85.5 967.7 1.9 874 3.4
Private industry........................... 85.1 824.4 2.8 856 4.6
Natural resources and mining............. 0.5 10.0 3.6 409 10.5
Construction............................. 4.9 30.5 -2.5 872 6.0
Manufacturing............................ 2.6 35.1 -1.2 821 1.0
Trade, transportation, and utilities..... 24.3 243.2 3.2 799 5.1
Information.............................. 1.4 17.5 -1.3 1,424 3.1
Financial activities..................... 8.9 61.1 1.2 1,593 10.2
Professional and business services....... 17.8 126.5 3.6 1,024 2.9
Education and health services............ 9.6 152.7 2.6 831 5.6
Leisure and hospitality.................. 6.4 110.2 3.6 481 3.2
Other services........................... 7.7 36.0 4.1 523 1.0
Government................................. 0.4 143.3 -2.6 974 -1.6
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs.
(2) Data are preliminary. Counties selected are based on 2010 annual average employment.
(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,
first quarter 2011(2)
Employment Average weekly
wage(3)
Establishments,
first quarter
State 2011 Percent Percent
(thousands) March change, First change,
2011 March quarter first
(thousands) 2010-11 2011 quarter
2010-11
United States(4)......... 9,074.3 127,851.0 1.3 $935 5.2
Alabama.................. 116.3 1,808.5 0.3 766 4.2
Alaska................... 21.2 310.1 2.0 912 3.8
Arizona.................. 144.8 2,392.1 0.7 837 4.9
Arkansas................. 85.7 1,133.5 0.3 715 6.1
California............... 1,376.1 14,413.8 1.2 1,066 6.2
Colorado................. 169.0 2,179.8 1.3 952 4.4
Connecticut.............. 110.6 1,589.2 1.4 1,282 6.3
Delaware................. 28.3 396.0 2.1 1,026 5.7
District of Columbia..... 34.8 702.3 2.5 1,540 2.4
Florida.................. 591.2 7,235.9 1.2 794 3.8
Georgia.................. 266.7 3,771.0 1.4 885 5.7
Hawaii................... 38.6 593.8 1.2 790 3.1
Idaho.................... 54.2 590.3 -0.1 659 4.1
Illinois................. 382.7 5,472.4 1.2 1,003 6.0
Indiana.................. 159.7 2,717.1 1.9 772 4.5
Iowa..................... 93.7 1,419.3 0.6 738 4.5
Kansas................... 87.9 1,293.3 0.6 748 4.0
Kentucky................. 110.8 1,715.6 1.5 737 3.7
Louisiana................ 127.4 1,841.3 0.9 798 4.5
Maine.................... 49.5 558.6 0.1 723 4.8
Maryland................. 164.9 2,452.1 1.3 1,010 3.6
Massachusetts............ 226.4 3,116.5 1.2 1,159 5.8
Michigan................. 244.0 3,757.7 2.2 872 7.1
Minnesota................ 167.2 2,530.7 1.4 935 6.0
Mississippi.............. 69.1 1,074.8 0.6 650 3.2
Missouri................. 173.9 2,562.3 0.3 786 3.0
Montana.................. 42.0 412.2 0.4 656 3.6
Nebraska................. 60.0 886.2 0.7 721 3.9
Nevada................... 71.3 1,102.6 0.4 802 3.0
New Hampshire............ 47.5 596.3 1.1 876 5.2
New Jersey............... 265.0 3,701.1 0.0 1,160 3.5
New Mexico............... 54.7 776.5 -0.1 738 3.1
New York................. 596.9 8,336.5 1.2 1,368 6.7
North Carolina........... 252.3 3,809.6 1.6 825 4.3
North Dakota............. 26.6 364.5 5.0 748 9.5
Ohio..................... 286.5 4,870.6 1.4 819 4.6
Oklahoma................. 102.8 1,491.5 1.0 739 5.3
Oregon................... 131.0 1,590.3 1.3 812 4.6
Pennsylvania............. 344.7 5,459.3 1.5 896 4.6
Rhode Island............. 35.0 438.1 0.1 863 3.4
South Carolina........... 110.1 1,767.2 1.4 722 4.5
South Dakota............. 30.9 382.3 1.3 659 4.1
Tennessee................ 139.5 2,575.9 1.7 793 3.8
Texas.................... 577.2 10,324.3 2.2 946 5.9
Utah..................... 82.7 1,156.9 2.0 753 3.4
Vermont.................. 24.2 291.9 0.9 741 3.8
Virginia................. 233.1 3,539.9 1.5 968 4.0
Washington............... 235.3 2,785.3 1.2 947 5.2
West Virginia............ 48.5 689.3 1.0 723 4.5
Wisconsin................ 156.8 2,609.5 1.6 779 5.3
Wyoming.................. 25.0 265.2 1.0 808 4.4
Puerto Rico.............. 50.6 923.0 -2.6 500 0.8
Virgin Islands........... 3.5 45.1 0.4 738 1.0
(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
