For release 10:00 a.m. (EST), Tuesday, January 8, 2013 USDL-13-0013
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
County Employment and Wages
Second Quarter 2012
From June 2011 to June 2012, employment increased in 287 of the 328
largest U.S. counties, the U.S. Bureau of Labor Statistics reported
today. Yakima, Wash., posted the largest increase, with a gain of 8.2
percent over the year, compared with national job growth of 1.8
percent. Within Yakima, the largest employment increase occurred in
natural resources and mining, which gained 8,646 jobs over the year
(34.6 percent). Madison, Ill., St. Clair, Ill., and Clay, Mo., had
the largest over-the-year decreases in employment among the largest
counties in the U.S. with losses of 2.0 percent each. County
employment and wage data are compiled under the Quarterly Census of
Employment and Wages (QCEW) program, which produces detailed
information on local employment and wages within 7 months after the
end of each quarter.
The U.S. average weekly wage increased over the year by 1.3 percent
to $903 in the second quarter of 2012. Washington, Ore., had the
largest over-the-year increase in average weekly wages with a gain of
8.5 percent. Within Washington County, a total wage gain of $159.4
million (16.0 percent) in the manufacturing industry had the largest
contribution to the increase in average weekly wages. Within this
industry, large payouts, which included bonuses, significantly
boosted the county’s average weekly wages. Williamson, Texas,
experienced the largest decrease in average weekly wages with a loss
of 17.0 percent over the year.
Table A. Large counties ranked by June 2012 employment, June 2011-12 employment
increase, and June 2011-12 percent increase in employment
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Employment in large counties
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June 2012 employment | Increase in employment, | Percent increase in employment,
(thousands) | June 2011-12 | June 2011-12
| (thousands) |
--------------------------------------------------------------------------------------------------------
| |
United States 132,896.0| United States 2,366.8| United States 1.8
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| |
Los Angeles, Calif. 3,961.9| Harris, Texas 78.3| Yakima, Wash. 8.2
Cook, Ill. 2,428.3| Los Angeles, Calif. 64.1| Montgomery, Texas 5.7
New York, N.Y. 2,392.0| New York, N.Y. 56.2| Elkhart, Ind. 5.6
Harris, Texas 2,121.7| Dallas, Texas 46.1| Williamson, Tenn. 5.5
Maricopa, Ariz. 1,635.4| Maricopa, Ariz. 44.3| Delaware, Ohio 5.4
Dallas, Texas 1,475.1| King, Wash. 34.7| Utah, Utah 5.0
Orange, Calif. 1,416.5| Orange, Calif. 33.4| Rutherford, Tenn. 4.9
San Diego, Calif. 1,283.3| Santa Clara, Calif. 32.8| Kern, Calif. 4.8
King, Wash. 1,174.4| Cook, Ill. 31.0| Lafayette, La. 4.8
Miami-Dade, Fla. 974.6| San Diego, Calif. 26.7| Gregg, Texas 4.8
| |
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Large County Employment
In June 2012, national employment, as measured by the QCEW program,
was 132.9 million, up by 1.8 percent or 2.4 million, from June 2011.
The 328 U.S. counties with 75,000 or more jobs accounted for 70.9
percent of total U.S. employment and 76.2 percent of total wages.
These 328 counties had a net job growth of 1.7 million over the year,
accounting for 73.3 percent of the overall U.S. employment increase.
Yakima, Wash., had the largest percentage increase in employment (8.2
percent) among the largest U.S. counties. The five counties with the
largest increases in employment level were Harris, Texas; Los
Angeles, Calif.; New York, N.Y.; Dallas, Texas; and Maricopa, Ariz.
These counties had a combined over-the-year gain of 289,000, or 12.2
percent of the overall employment increase for the U.S. (See table
A.)
Employment declined in 38 of the large counties from June 2011 to
June 2012. Three counties, Madison, Ill., St. Clair, Ill., and Clay,
Mo., had the largest over-the-year percentage decreases in employment
(-2.0 percent each). Within Madison, construction was the largest
contributor to the decrease in employment with a loss of 998 jobs
(-17.9 percent). The largest employment decrease in St. Clair
occurred within local government in the education and health services
industry, which lost 463 jobs (-6.1 percent), followed by
construction where 452 jobs were lost (-10.9 percent) within the
private sector. Within Clay, manufacturing had the largest employment
decline, with a loss of 1,584 jobs (-15.2 percent). Benton, Wash.,
had the second largest percentage decrease in employment, followed by
New London, Conn. (See table 1.)
Table B. Large counties ranked by second quarter 2012 average weekly wages, second quarter 2011-12
increase in average weekly wages, and second quarter 2011-12 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
second quarter 2012 | wage, second quarter 2011-12 | weekly wage, second
| | quarter 2011-12
--------------------------------------------------------------------------------------------------------
| |
United States $903| United States $12| United States 1.3
--------------------------------------------------------------------------------------------------------
| |
Santa Clara, Calif. $1,754| San Mateo, Calif. $100| Washington, Ore. 8.5
New York, N.Y. 1,646| Washington, Ore. 88| Washington, Pa. 7.8
Washington, D.C. 1,544| Washington, Pa. 64| McLean, Ill. 7.2
San Mateo, Calif. 1,515| McLean, Ill. 62| San Mateo, Calif. 7.1
Arlington, Va. 1,493| Jefferson, Texas 55| Weld, Colo. 6.4
San Francisco, Calif. 1,487| Davidson, Tenn. 52| Jefferson, Texas 6.3
Fairfield, Conn. 1,425| Franklin, Ohio 50| Davidson, Tenn. 5.8
Fairfax, Va. 1,422| San Francisco, Calif. 48| Franklin, Ohio 5.6
Suffolk, Mass. 1,381| Weld, Colo. 47| Lucas, Ohio 5.0
Somerset, N.J. 1,345| Harris, Texas 46| Lake, Ind. 4.8
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Large County Average Weekly Wages
Average weekly wages for the nation increased by 1.3 percent during
the year ending in the second quarter of 2012. Among the 328 largest
counties, 233 had over-the-year increases in average weekly wages.
Washington, Ore., had the largest wage gain among the largest U.S.
counties (8.5 percent).
Of the 328 largest counties, 86 experienced over-the-year declines in
average weekly wages. Williamson, Texas, had the largest average
weekly wage decrease with a loss of 17.0 percent. Within Williamson,
total wages in trade, transportation, and utilities decreased by
$212.4 million (-30.5 percent) over the year. This decline reflects a
return to pay levels seen previously following a big payout in the
second quarter of 2011. Williamson also received large payouts in
this industry in the first quarter of 2012. Kitsap, Wash., had the
second largest decline in average weekly wages, followed by
Arlington, Va., Durham, N.C., and Benton, Wash. (See table 1.)
Ten Largest U.S. Counties
All of the 10 largest counties experienced over-the-year percentage
increases in employment in June 2012. Harris, Texas, experienced the
largest gain (3.8 percent). Within Harris, professional and business
services had the largest over-the-year level increase among all
private industry groups with a gain of 20,285 jobs (6.0 percent).
Cook, Ill., had the smallest percentage increase in employment (1.3
percent) among the 10 largest counties. (See table 2.)
Nine of the 10 largest U.S. counties had an over-the-year increase in
average weekly wages. Harris, Texas, experienced the largest increase
in average weekly wages (4.1 percent), largely due to substantial
total wage gains over the year in trade, transportation, and
utilities ($960.6 million or 17.3 percent). Miami-Dade, Fla., had the
only average weekly wage decline (-0.5 percent) among the 10 largest
counties.
For More Information
The tables included in this release contain data for the nation and
for the 328 U.S. counties with annual average employment levels of
75,000 or more in 2011. June 2012 employment and 2012 second 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 9.2 million employer reports cover 132.9 million full-
and part-time workers. For additional information about the quarterly
employment and wages data, please read the Technical Note. Data for
the second quarter of 2012 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 third quarter 2012 is
scheduled to be released on Thursday, March 28, 2013.
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 2012 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 329 counties presented
in this release were derived using 2011 preliminary annual averages of employment.
For 2012 data, seven counties have been added to the publication tables: Okaloosa,
Fla.; Tippecanoe, Ind.; Johnson, Iowa; St. Tammany, La.; Saratoga, N.Y.; Delaware,
Ohio; and Gregg, Texas. These counties will be included in all 2012 quarterly re-
leases. One county, Jackson, Ore., which was published in the 2011 releases, will
be excluded from this and future 2012 releases because its 2011 annual average
employment level was 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- | 486,000 establish-
| submitted by 9.2 | ministrative records| ments
| million establish- | submitted by 6.8 |
| ments in first | million private-sec-|
| quarter of 2012 | 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 to an-
| new quarter of UI | dinal database and | nually realign sample-
| data | directly summarizes | based estimates to pop-
| | gross job gains and | ulation estimates to
| | losses | population counts (ben-
| | | chmarking)
-----------|---------------------|----------------------|------------------------
Principal |--Provides a quarter-|--Provides quarterly |--Provides current month-
products | ly and annual uni- | employer dynamics | ly estimates of employ-
| verse count of es- | data on establish- | ment, hours, and earn-
| tablishments, em- | ment openings, clos-| ings at the MSA, state,
| ployment, and wages| ings, expansions, | and national level by
| at the county, MSA,| and contractions at | industry
| state, and national| the national level |
| levels by detailed | by NAICS supersec- |
| industry | tors and by size of |
| | firm, and at the |
| | state private-sector|
| | total level |
| |--Future expansions |
| | will include data |
| | with greater indus- |
| | try detail and data |
| | at the county and |
| | MSA level |
-----------|---------------------|----------------------|------------------------
Principal |--Major uses include:|--Major uses include: |--Major uses include:
uses | -Detailed locality | -Business cycle | -Principal national
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -Analysis of employ-| cators
| surveys | ment expansion and |
| | contraction by size|
| | of firm |
| | |
-----------|---------------------|----------------------|------------------------
Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/
Web sites | | |
---------------------------------------------------------------------------------
Coverage
Employment and wage data for workers covered by state UI laws are compiled from
quarterly contribution reports submitted to the SWAs by employers. For federal ci-
vilian workers covered by the Unemployment Compensation for Federal Employees
(UCFE) program, employment and wage data are compiled from quarterly reports sub-
mitted by four major federal payroll processing centers on behalf of all federal
agencies, with the exception of a few agencies which still report directly to the
individual SWA. In addition to the quarterly contribution reports, employers who
operate multiple establishments within a state complete a questionnaire, called the
"Multiple Worksite Report," which provides detailed information on the location and
industry of each of their establishments. QCEW employment and wage data are derived
from microdata summaries of 9.1 million employer reports of employment and wages
submitted by states to the BLS in 2011. 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 2011, UI and UCFE programs covered workers in 129.4 million jobs. The estimated
124.8 million workers in these jobs (after adjustment for multiple jobholders)
represented 95.7 percent of civilian wage and salary employment. Covered workers
received $6.217 trillion in pay, representing 93.3 percent of the wage and salary
component of personal income and 41.2 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 2011 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 2011 edition of this publication, which was published in October 2012,
contains selected data produced by Business Employment Dynamics (BED) on job gains
and losses, as well as selected data from the first quarter 2012 version of this
news release. Tables and additional content from Employment and Wages Annual Aver-
ages 2011 are now available online at http://www.bls.gov/cew/cewbultn11.htm. The
2012 edition of Employment and Wages Annual Averages Online will be available later
in 2013.
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 329 largest counties,
second quarter 2012(2)
Employment Average weekly wage(4)
Establishments,
County(3) second quarter Percent Ranking Percent Ranking
2012 June change, by Second change, by
(thousands) 2012 June percent quarter second percent
(thousands) 2011-12(5) change 2012 quarter change
2011-12(5)
United States(6)......... 9,224.5 132,896.0 1.8 - $903 1.3 -
Jefferson, AL............ 17.6 338.2 1.5 168 913 3.4 32
Madison, AL.............. 8.9 178.5 0.1 280 1,010 0.9 182
Mobile, AL............... 9.7 164.2 -1.0 317 791 1.7 120
Montgomery, AL........... 6.3 128.3 1.3 184 783 0.0 234
Tuscaloosa, AL........... 4.2 84.7 2.4 86 792 1.8 111
Anchorage Borough, AK.... 8.3 155.5 2.1 107 998 0.9 182
Maricopa, AZ............. 95.5 1,635.4 2.8 64 905 2.6 74
Pima, AZ................. 19.1 343.5 1.9 130 795 0.4 211
Benton, AR............... 5.5 97.4 2.1 107 844 3.2 37
Pulaski, AR.............. 14.4 243.6 0.9 222 825 1.6 128
Washington, AR........... 5.5 92.7 2.2 100 728 -1.0 289
Alameda, CA.............. 58.4 660.2 2.7 72 1,181 0.2 221
Contra Costa, CA......... 31.0 326.3 2.2 100 1,091 -0.5 269
Fresno, CA............... 32.3 351.8 3.2 44 702 -0.3 254
Kern, CA................. 18.6 299.7 4.8 8 813 2.9 53
Los Angeles, CA.......... 452.9 3,961.9 1.6 158 1,006 1.3 142
Marin, CA................ 12.0 107.0 3.6 27 1,122 1.5 133
Monterey, CA............. 13.3 187.0 1.5 168 770 2.3 82
Orange, CA............... 106.6 1,416.5 2.4 86 1,014 1.3 142
Placer, CA............... 11.2 131.4 3.0 57 898 2.7 66
Riverside, CA............ 52.8 575.1 2.3 98 749 1.1 163
Sacramento, CA........... 55.6 592.7 1.7 151 1,018 1.4 140
San Bernardino, CA....... 53.7 609.8 1.4 176 791 2.3 82
San Diego, CA............ 102.8 1,283.3 2.1 107 989 0.9 182
San Francisco, CA........ 58.1 585.8 4.3 15 1,487 3.3 33
San Joaquin, CA.......... 18.2 216.3 2.0 122 758 -0.5 269
San Luis Obispo, CA...... 9.9 106.5 3.4 34 750 -1.4 302
San Mateo, CA............ 25.3 342.1 4.3 15 1,515 7.1 4
Santa Barbara, CA........ 14.9 189.4 2.0 122 863 3.1 43
Santa Clara, CA.......... 65.6 903.1 3.8 22 1,754 1.2 153
Santa Cruz, CA........... 9.4 99.3 1.7 151 834 4.0 20
Solano, CA............... 10.5 122.1 2.0 122 909 0.2 221
Sonoma, CA............... 19.6 176.5 1.5 168 842 -1.2 294
Stanislaus, CA........... 15.5 168.2 2.8 64 761 1.3 142
Tulare, CA............... 9.6 150.9 0.3 266 634 2.3 82
Ventura, CA.............. 24.7 308.1 1.1 204 926 -0.3 254
Yolo, CA................. 6.3 92.2 2.2 100 934 4.1 17
Adams, CO................ 8.9 161.9 2.4 86 834 2.6 74
Arapahoe, CO............. 18.9 288.9 3.0 57 1,041 1.8 111
Boulder, CO.............. 13.1 162.2 2.7 72 1,048 2.0 101
Denver, CO............... 26.0 435.9 3.6 27 1,088 1.0 170
Douglas, CO.............. 9.7 97.3 4.2 17 980 0.1 228
El Paso, CO.............. 16.8 240.1 0.7 235 843 2.2 87
Jefferson, CO............ 17.8 214.7 1.8 140 907 0.9 182
Larimer, CO.............. 10.1 135.9 3.3 41 782 3.7 25
Weld, CO................. 5.8 85.2 3.7 24 786 6.4 5
Fairfield, CT............ 32.8 413.5 1.8 140 1,425 -2.9 318
Hartford, CT............. 25.7 496.6 1.3 184 1,097 -0.1 243
New Haven, CT............ 22.4 358.0 0.9 222 952 0.7 196
New London, CT........... 6.9 125.5 -1.3 324 926 2.1 96
New Castle, DE........... 17.0 265.6 0.1 280 1,071 1.9 108
Washington, DC........... 35.5 717.9 0.9 222 1,544 0.3 215
Alachua, FL.............. 6.5 115.8 0.7 235 786 1.0 170
Brevard, FL.............. 14.4 188.2 -0.3 298 829 -3.2 321
Broward, FL.............. 63.2 698.7 2.0 122 830 -0.6 276
Collier, FL.............. 11.8 110.6 4.2 17 781 -1.9 311
Duval, FL................ 27.1 438.1 1.3 184 862 1.5 133
Escambia, FL............. 7.9 117.3 -0.8 313 736 1.0 170
Hillsborough, FL......... 37.9 576.6 2.4 86 868 1.0 170
Lake, FL................. 7.2 77.6 2.1 107 614 -0.5 269
Lee, FL.................. 18.6 196.2 2.0 122 730 -0.1 243
Leon, FL................. 8.2 134.8 -0.8 313 768 0.0 234
Manatee, FL.............. 9.3 100.7 2.5 83 712 -0.8 285
Marion, FL............... 7.9 89.7 1.2 196 654 -0.3 254
Miami-Dade, FL........... 88.9 974.6 2.3 98 876 -0.5 269
Okaloosa, FL............. 6.1 77.0 1.2 196 750 -0.7 282
Orange, FL............... 36.1 672.8 3.2 44 790 -0.4 262
Palm Beach, FL........... 49.6 499.9 2.8 64 873 -0.2 252
Pasco, FL................ 10.0 92.5 1.5 168 664 -0.3 254
Pinellas, FL............. 30.6 382.6 1.3 184 805 0.5 205
Polk, FL................. 12.4 184.1 0.7 235 698 2.0 101
Sarasota, FL............. 14.4 134.5 3.0 57 751 0.3 215
Seminole, FL............. 13.8 156.6 1.9 130 757 -0.3 254
Volusia, FL.............. 13.3 147.1 1.3 184 668 1.7 120
Bibb, GA................. 4.6 80.4 1.1 204 708 2.9 53
Chatham, GA.............. 7.7 134.0 2.4 86 755 0.0 234
Clayton, GA.............. 4.3 111.9 -0.1 291 869 2.2 87
Cobb, GA................. 21.4 303.1 1.9 130 959 3.0 51
De Kalb, GA.............. 17.9 276.2 -0.3 298 957 3.2 37
Fulton, GA............... 41.5 723.8 3.1 51 1,171 2.0 101
Gwinnett, GA............. 24.1 308.2 1.2 196 887 2.4 80
Muscogee, GA............. 4.6 94.2 -0.1 291 716 0.6 200
Richmond, GA............. 4.7 97.0 -1.0 317 784 2.9 53
Honolulu, HI............. 24.6 443.0 2.1 107 844 1.7 120
Ada, ID.................. 13.7 200.8 2.9 62 778 0.4 211
Champaign, IL............ 4.3 87.3 0.1 280 789 4.2 13
Cook, IL................. 148.8 2,428.3 1.3 184 1,052 1.3 142
Du Page, IL.............. 37.2 576.6 1.8 140 1,054 2.1 96
Kane, IL................. 13.3 196.8 1.6 158 795 -0.1 243
Lake, IL................. 22.1 331.3 1.5 168 1,156 2.2 87
McHenry, IL.............. 8.7 96.0 0.9 222 744 0.0 234
McLean, IL............... 3.8 86.9 1.1 204 926 7.2 3
Madison, IL.............. 6.0 94.4 -2.0 326 742 1.1 163
Peoria, IL............... 4.7 103.9 1.5 168 869 3.1 43
St. Clair, IL............ 5.6 92.5 -2.0 326 735 0.0 234
Sangamon, IL............. 5.3 130.2 -1.1 321 928 1.2 153
Will, IL................. 15.2 205.8 1.0 210 794 -0.3 254
Winnebago, IL............ 6.8 126.8 0.4 262 774 3.5 30
Allen, IN................ 8.9 176.5 0.7 235 734 -2.1 312
Elkhart, IN.............. 4.8 112.4 5.6 3 747 2.8 61
Hamilton, IN............. 8.5 114.5 0.7 235 840 2.8 61
Lake, IN................. 10.4 190.4 1.8 140 846 4.8 10
Marion, IN............... 24.0 565.7 3.6 27 905 1.3 142
St. Joseph, IN........... 6.0 116.2 0.4 262 751 2.7 66
Tippecanoe, IN........... 3.3 78.8 4.6 11 776 0.0 234
Vanderburgh, IN.......... 4.8 104.9 -1.0 317 728 -1.1 292
Johnson, IA.............. 3.6 78.0 1.7 151 826 2.9 53
Linn, IA................. 6.3 128.9 1.0 210 846 1.1 163
Polk, IA................. 15.1 275.0 2.7 72 882 1.0 170
Scott, IA................ 5.2 89.5 1.8 140 738 3.9 22
Johnson, KS.............. 21.0 313.3 3.4 34 929 2.0 101
Sedgwick, KS............. 12.3 240.6 1.2 196 818 0.2 221
Shawnee, KS.............. 4.8 94.7 0.6 246 771 -1.0 289
Wyandotte, KS............ 3.2 85.4 3.6 27 839 -1.4 302
Fayette, KY.............. 9.5 178.5 1.7 151 808 -1.6 308
Jefferson, KY............ 22.5 427.9 2.1 107 895 1.8 111
Caddo, LA................ 7.6 120.5 -0.3 298 767 0.5 205
Calcasieu, LA............ 4.9 84.9 1.6 158 764 1.3 142
East Baton Rouge, LA..... 15.0 254.7 2.7 72 855 3.1 43
Jefferson, LA............ 14.0 191.5 -1.0 317 824 0.5 205
Lafayette, LA............ 9.2 139.3 4.8 8 891 4.2 13
Orleans, LA.............. 11.4 175.7 3.1 51 902 -2.7 316
St. Tammany, LA.......... 7.6 79.2 1.2 196 740 -1.2 294
Cumberland, ME........... 12.7 174.3 1.8 140 807 0.9 182
Anne Arundel, MD......... 14.6 242.4 3.6 27 958 -0.8 285
Baltimore, MD............ 21.2 366.1 1.1 204 917 1.8 111
Frederick, MD............ 6.2 94.2 0.5 253 889 2.7 66
Harford, MD.............. 5.6 88.2 3.2 44 917 2.8 61
Howard, MD............... 9.2 162.0 2.7 72 1,106 2.7 66
Montgomery, MD........... 33.1 455.8 1.4 176 1,222 1.2 153
Prince Georges, MD....... 15.6 302.6 0.0 288 979 -0.4 262
Baltimore City, MD....... 13.9 329.9 0.1 280 1,020 -1.4 302
Barnstable, MA........... 8.9 101.1 3.3 41 758 0.4 211
Bristol, MA.............. 16.0 214.1 0.1 280 826 -1.3 299
Essex, MA................ 21.4 312.1 1.8 140 953 -3.0 319
Hampden, MA.............. 15.3 201.0 1.6 158 832 2.2 87
Middlesex, MA............ 48.8 833.8 2.1 107 1,342 -3.2 321
Norfolk, MA.............. 23.3 325.5 2.0 122 1,055 0.9 182
Plymouth, MA............. 13.9 181.4 3.1 51 867 -0.7 282
Suffolk, MA.............. 23.2 598.1 2.0 122 1,381 -0.7 282
Worcester, MA............ 21.3 320.6 0.9 222 910 0.0 234
Genesee, MI.............. 7.2 130.1 0.3 266 741 0.7 196
Ingham, MI............... 6.3 153.7 -0.4 305 839 1.7 120
Kalamazoo, MI............ 5.3 110.3 0.9 222 814 1.9 108
Kent, MI................. 14.0 337.9 4.4 14 801 1.6 128
Macomb, MI............... 17.1 294.9 1.5 168 916 3.3 33
Oakland, MI.............. 37.9 667.5 3.4 34 1,003 1.3 142
Ottawa, MI............... 5.5 110.2 2.4 86 744 2.8 61
Saginaw, MI.............. 4.2 83.4 0.1 280 727 1.0 170
Washtenaw, MI............ 8.1 192.6 3.4 34 964 3.1 43
Wayne, MI................ 31.4 690.2 1.6 158 975 1.5 133
Anoka, MN................ 7.2 112.1 1.9 130 868 0.8 192
Dakota, MN............... 9.9 176.2 1.3 184 880 -0.9 288
Hennepin, MN............. 41.4 850.1 2.1 107 1,120 0.3 215
Olmsted, MN.............. 3.5 92.1 2.8 64 1,031 1.7 120
Ramsey, MN............... 14.1 320.5 0.8 230 1,003 0.9 182
St. Louis, MN............ 5.6 95.0 -0.7 311 726 -3.2 321
Stearns, MN.............. 4.4 81.5 1.8 140 722 3.3 33
Harrison, MS............. 4.4 84.1 0.3 266 670 0.3 215
Hinds, MS................ 5.9 120.7 -1.1 321 793 1.9 108
Boone, MO................ 4.5 86.6 2.9 62 714 2.6 74
Clay, MO................. 5.1 87.4 -2.0 326 816 1.5 133
Greene, MO............... 8.0 154.0 3.6 27 695 2.2 87
Jackson, MO.............. 18.6 349.0 1.0 210 920 3.1 43
St. Charles, MO.......... 8.3 127.1 1.3 184 738 3.8 24
St. Louis, MO............ 32.1 567.5 -0.3 298 956 3.7 25
St. Louis City, MO....... 9.3 217.3 1.0 210 953 -3.1 320
Yellowstone, MT.......... 6.0 78.9 2.1 107 766 4.4 12
Douglas, NE.............. 17.3 318.6 1.7 151 810 -0.4 262
Lancaster, NE............ 9.3 157.8 2.1 107 732 1.5 133
Clark, NV................ 48.5 822.0 1.9 130 807 0.1 228
Washoe, NV............... 13.5 185.4 0.7 235 809 0.1 228
Hillsborough, NH......... 12.0 190.5 1.4 176 977 -1.2 294
Rockingham, NH........... 10.6 139.1 1.9 130 848 -0.5 269
Atlantic, NJ............. 6.7 145.6 3.4 34 765 -2.3 313
Bergen, NJ............... 33.1 433.6 1.4 176 1,127 3.6 28
Burlington, NJ........... 10.9 196.6 1.0 210 963 1.8 111
Camden, NJ............... 12.1 195.1 0.4 262 899 0.7 196
Essex, NJ................ 20.4 339.5 0.7 235 1,096 -2.6 315
Gloucester, NJ........... 6.1 99.2 0.5 253 789 -1.4 302
Hudson, NJ............... 13.8 233.8 1.4 176 1,233 0.0 234
Mercer, NJ............... 10.9 232.8 1.1 204 1,155 -2.8 317
Middlesex, NJ............ 21.7 387.6 2.4 86 1,068 -2.4 314
Monmouth, NJ............. 19.9 252.6 0.2 278 905 -1.8 310
Morris, NJ............... 17.2 275.8 0.7 235 1,266 1.3 142
Ocean, NJ................ 12.2 159.2 1.9 130 739 0.8 192
Passaic, NJ.............. 12.2 173.0 0.6 246 928 0.2 221
Somerset, NJ............. 10.0 175.6 1.0 210 1,345 2.6 74
Union, NJ................ 14.3 221.7 0.7 235 1,130 0.1 228
Bernalillo, NM........... 17.6 309.8 -0.4 305 799 2.2 87
Albany, NY............... 10.0 221.9 1.2 196 929 -0.3 254
Bronx, NY................ 17.1 237.2 0.5 253 868 -0.1 243
Broome, NY............... 4.5 91.7 -0.1 291 733 1.4 140
Dutchess, NY............. 8.2 111.6 -0.3 298 960 1.1 163
Erie, NY................. 23.8 460.0 0.6 246 793 1.8 111
Kings, NY................ 52.9 522.7 2.8 64 736 -0.4 262
Monroe, NY............... 18.2 380.1 0.6 246 862 0.9 182
Nassau, NY............... 52.6 603.4 1.4 176 1,042 0.6 200
New York, NY............. 122.7 2,392.0 2.4 86 1,646 0.2 221
Oneida, NY............... 5.3 107.2 -0.6 308 741 1.0 170
Onondaga, NY............. 12.9 243.5 -0.4 305 849 3.2 37
Orange, NY............... 9.9 133.5 0.2 278 807 -0.1 243
Queens, NY............... 47.1 521.6 2.2 100 846 -0.1 243
Richmond, NY............. 9.0 92.5 -0.1 291 770 -0.5 269
Rockland, NY............. 10.0 117.0 0.5 253 989 -0.6 276
Saratoga, NY............. 5.6 80.7 3.1 51 815 1.6 128
Suffolk, NY.............. 50.8 641.9 1.0 210 974 -0.6 276
Westchester, NY.......... 36.1 413.8 0.1 280 1,195 -0.8 285
Buncombe, NC............. 8.1 112.9 1.9 130 681 1.5 133
Catawba, NC.............. 4.4 79.2 0.8 230 686 1.3 142
Cumberland, NC........... 6.3 119.1 -0.7 311 739 -1.3 299
Durham, NC............... 7.4 185.7 2.2 100 1,180 -3.6 325
Forsyth, NC.............. 9.0 173.6 1.6 158 811 -0.5 269
Guilford, NC............. 14.2 259.5 -0.2 296 783 0.8 192
Mecklenburg, NC.......... 33.3 562.0 2.7 72 1,000 0.5 205
New Hanover, NC.......... 7.4 96.8 0.3 266 738 1.2 153
Wake, NC................. 29.8 459.5 3.1 51 890 0.9 182
Cass, ND................. 6.1 107.9 4.6 11 789 2.7 66
Butler, OH............... 7.4 139.6 1.3 184 789 0.8 192
Cuyahoga, OH............. 35.6 706.1 1.9 130 916 2.2 87
Delaware, OH............. 4.4 81.4 5.4 5 881 0.9 182
Franklin, OH............. 29.6 672.1 2.5 83 935 5.6 8
Hamilton, OH............. 23.2 494.7 1.6 158 970 1.0 170
Lake, OH................. 6.4 95.9 0.9 222 760 0.5 205
Lorain, OH............... 6.0 97.1 3.0 57 751 2.9 53
Lucas, OH................ 10.1 203.5 2.8 64 804 5.0 9
Mahoning, OH............. 5.9 97.9 2.2 100 651 0.6 200
Montgomery, OH........... 12.1 246.0 1.0 210 788 0.4 211
Stark, OH................ 8.8 155.0 1.9 130 688 0.0 234
Summit, OH............... 14.3 258.5 1.2 196 803 1.6 128
Oklahoma, OK............. 24.9 432.3 2.8 64 832 0.1 228
Tulsa, OK................ 20.5 335.7 1.6 158 837 2.7 66
Clackamas, OR............ 12.7 141.3 2.4 86 847 1.3 142
Lane, OR................. 10.8 138.8 0.4 262 712 1.1 163
Marion, OR............... 9.4 134.3 1.1 204 730 0.7 196
Multnomah, OR............ 29.8 442.3 2.1 107 920 -0.3 254
Washington, OR........... 16.5 252.2 2.6 81 1,122 8.5 1
Allegheny, PA............ 35.6 693.5 1.0 210 966 2.0 101
Berks, PA................ 9.0 164.4 0.1 280 812 0.5 205
Bucks, PA................ 19.7 253.2 0.3 266 878 2.1 96
Butler, PA............... 4.9 84.6 0.5 253 829 -1.2 294
Chester, PA.............. 15.1 239.1 0.0 288 1,158 -0.1 243
Cumberland, PA........... 6.1 125.5 1.6 158 853 2.3 82
Dauphin, PA.............. 7.5 178.3 -0.6 308 890 1.0 170
Delaware, PA............. 13.9 212.9 1.4 176 962 1.2 153
Erie, PA................. 7.7 126.7 0.3 266 722 1.7 120
Lackawanna, PA........... 5.9 96.7 -1.2 323 685 -0.4 262
Lancaster, PA............ 12.7 222.9 1.0 210 749 1.2 153
Lehigh, PA............... 8.7 178.3 0.5 253 885 2.7 66
Luzerne, PA.............. 7.8 139.8 -0.3 298 711 2.0 101
Montgomery, PA........... 27.5 471.9 1.5 168 1,111 2.4 80
Northampton, PA.......... 6.6 103.6 0.9 222 787 1.0 170
Philadelphia, PA......... 35.4 629.4 -0.1 291 1,070 4.1 17
Washington, PA........... 5.6 87.3 2.4 86 887 7.8 2
Westmoreland, PA......... 9.5 135.7 0.7 235 726 0.3 215
York, PA................. 9.1 171.3 -0.3 298 781 -1.1 292
Providence, RI........... 17.3 271.6 0.6 246 888 -1.0 289
Charleston, SC........... 11.9 219.9 3.4 34 773 -1.2 294
Greenville, SC........... 12.1 235.8 2.5 83 789 0.3 215
Horry, SC................ 7.6 118.3 0.3 266 532 1.3 142
Lexington, SC............ 5.6 96.9 2.7 72 687 3.9 22
Richland, SC............. 8.9 204.1 0.6 246 802 3.1 43
Spartanburg, SC.......... 5.8 114.8 3.2 44 801 2.2 87
Minnehaha, SD............ 6.6 118.3 2.7 72 763 3.2 37
Davidson, TN............. 18.2 429.2 2.4 86 950 5.8 7
Hamilton, TN............. 8.4 186.0 2.2 100 798 1.8 111
Knox, TN................. 10.9 218.8 0.7 235 778 1.7 120
Rutherford, TN........... 4.4 101.9 4.9 7 825 4.0 20
Shelby, TN............... 19.0 472.6 2.1 107 949 3.2 37
Williamson, TN........... 6.2 98.1 5.5 4 959 -1.4 302
Bell, TX................. 4.9 108.7 1.3 184 738 1.0 170
Bexar, TX................ 35.1 751.1 2.0 122 799 0.1 228
Brazoria, TX............. 5.0 93.3 4.1 19 899 4.2 13
Brazos, TX............... 4.0 86.3 2.6 81 689 1.5 133
Cameron, TX.............. 6.4 129.9 1.4 176 571 0.2 221
Collin, TX............... 19.2 310.6 4.1 19 1,048 -0.4 262
Dallas, TX............... 68.9 1,475.1 3.2 44 1,074 2.0 101
Denton, TX............... 11.5 186.7 3.7 24 794 1.0 170
El Paso, TX.............. 14.0 277.3 1.3 184 653 0.6 200
Fort Bend, TX............ 9.8 144.1 4.6 11 908 2.5 79
Galveston, TX............ 5.4 98.1 1.3 184 815 0.2 221
Gregg, TX................ 4.2 78.7 4.8 8 837 1.8 111
Harris, TX............... 103.2 2,121.7 3.8 22 1,165 4.1 17
Hidalgo, TX.............. 11.4 228.0 0.8 230 583 2.3 82
Jefferson, TX............ 5.8 123.2 0.5 253 929 6.3 6
Lubbock, TX.............. 7.1 125.6 1.0 210 689 0.6 200
McLennan, TX............. 4.9 101.4 0.3 266 744 3.3 33
Montgomery, TX........... 9.1 142.2 5.7 2 867 3.6 28
Nueces, TX............... 7.9 156.8 3.3 41 804 4.7 11
Smith, TX................ 5.7 93.9 0.8 230 767 1.2 153
Tarrant, TX.............. 38.6 784.7 2.4 86 895 -0.2 252
Travis, TX............... 32.1 605.7 3.4 34 1,009 3.7 25
Webb, TX................. 4.9 91.1 2.7 72 635 3.1 43
Williamson, TX........... 8.0 135.2 3.2 44 860 -17.0 328
Davis, UT................ 7.3 110.1 3.2 44 723 -0.6 276
Salt Lake, UT............ 37.6 591.7 4.0 21 855 2.6 74
Utah, UT................. 12.9 178.8 5.0 6 706 -1.3 299
Weber, UT................ 5.4 90.8 1.8 140 692 3.0 51
Chittenden, VT........... 6.1 97.9 1.8 140 918 2.9 53
Arlington, VA............ 8.5 167.3 -0.8 313 1,493 -3.8 326
Chesterfield, VA......... 7.8 118.3 2.1 107 813 1.6 128
Fairfax, VA.............. 35.1 598.1 2.1 107 1,422 -0.4 262
Henrico, VA.............. 10.2 179.4 2.8 64 896 1.2 153
Loudoun, VA.............. 10.0 144.2 3.7 24 1,076 2.9 53
Prince William, VA....... 8.0 115.2 3.5 33 812 1.1 163
Alexandria City, VA...... 6.2 95.9 1.6 158 1,293 2.8 61
Chesapeake City, VA...... 5.7 96.2 0.0 288 741 4.2 13
Newport News City, VA.... 3.8 94.7 -0.8 313 861 1.8 111
Norfolk City, VA......... 5.6 138.6 0.3 266 877 -0.1 243
Richmond City, VA........ 7.1 148.5 0.3 266 966 -1.6 308
Virginia Beach City, VA.. 11.4 169.8 1.0 210 706 -1.5 307
Benton, WA............... 5.7 83.0 -1.7 325 922 -3.4 324
Clark, WA................ 13.5 131.5 1.8 140 826 2.1 96
King, WA................. 82.2 1,174.4 3.0 57 1,167 2.9 53
Kitsap, WA............... 6.7 81.2 -0.6 308 823 -4.2 327
Pierce, WA............... 21.7 265.3 0.8 230 837 1.7 120
Snohomish, WA............ 19.2 258.2 3.1 51 974 2.2 87
Spokane, WA.............. 15.9 200.6 0.3 266 764 1.2 153
Thurston, WA............. 7.5 97.6 -0.2 296 818 -0.6 276
Whatcom, WA.............. 6.9 81.4 1.7 151 777 3.5 30
Yakima, WA............... 8.8 110.5 8.2 1 617 1.1 163
Kanawha, WV.............. 6.0 105.5 0.5 253 814 2.1 96
Brown, WI................ 6.5 149.3 0.5 253 779 3.2 37
Dane, WI................. 14.1 308.6 2.1 107 871 -0.1 243
Milwaukee, WI............ 23.1 473.3 1.2 196 877 -0.6 276
Outagamie, WI............ 5.1 104.4 1.7 151 752 1.2 153
Waukesha, WI............. 12.6 231.7 0.6 246 895 3.1 43
Winnebago, WI............ 3.6 90.1 0.3 266 839 2.7 66
San Juan, PR............. 11.4 264.2 2.8 (7) 596 -0.3 (7)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 328 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) This county was not included in the U.S. rankings.
Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties,
second quarter 2012(2)
Employment Average weekly
wage(3)
Establishments,
second quarter
County by NAICS supersector 2012 Percent Percent
(thousands) June change, Second change,
2012 June quarter second
(thousands) 2011-12(4) 2012 quarter
2011-12(4)
United States(5)............................. 9,224.5 132,896.0 1.8 $903 1.3
Private industry........................... 8,928.1 111,708.5 2.4 891 1.9
Natural resources and mining............. 130.2 2,120.8 7.1 996 3.8
Construction............................. 748.7 5,726.3 1.7 966 3.3
Manufacturing............................ 335.3 11,996.6 2.0 1,111 1.6
Trade, transportation, and utilities..... 1,883.2 25,240.5 1.7 768 2.1
Information.............................. 143.8 2,686.3 0.0 1,437 2.8
Financial activities..................... 809.7 7,540.1 1.3 1,320 2.6
Professional and business services....... 1,589.9 17,985.5 3.7 1,153 1.7
Education and health services............ 926.8 19,330.2 2.0 847 1.4
Leisure and hospitality.................. 769.1 14,307.6 3.5 374 2.5
Other services........................... 1,375.6 4,552.6 1.7 576 2.1
Government................................. 296.4 21,187.6 -1.2 964 -1.0
Los Angeles, CA.............................. 452.9 3,961.9 1.6 1,006 1.3
Private industry........................... 447.3 3,414.8 2.3 977 1.7
Natural resources and mining............. 0.4 9.7 0.6 1,287 5.8
Construction............................. 12.1 109.3 3.4 1,046 4.2
Manufacturing............................ 12.6 367.7 -0.2 1,067 -1.5
Trade, transportation, and utilities..... 50.8 750.7 1.6 826 2.7
Information.............................. 8.3 187.1 -1.8 1,749 3.3
Financial activities..................... 21.9 210.6 1.1 1,459 2.7
Professional and business services....... 41.9 569.4 4.2 1,222 1.2
Education and health services............ 29.6 527.2 2.2 958 2.0
Leisure and hospitality.................. 27.3 420.2 5.4 543 -0.5
Other services........................... 217.6 242.8 -1.3 457 4.6
Government................................. 5.6 547.0 -2.1 1,187 0.3
Cook, IL..................................... 148.8 2,428.3 1.3 1,052 1.3
Private industry........................... 147.4 2,128.9 1.7 1,034 1.2
Natural resources and mining............. 0.1 0.8 -5.4 955 6.9
Construction............................. 12.4 64.9 -2.8 1,241 1.5
Manufacturing............................ 6.6 194.9 0.3 1,100 1.1
Trade, transportation, and utilities..... 28.9 441.8 0.6 826 0.6
Information.............................. 2.7 54.3 0.0 1,535 2.1
Financial activities..................... 15.6 185.2 -0.5 1,812 1.0
Professional and business services....... 31.4 425.7 3.6 1,328 1.8
Education and health services............ 15.6 410.4 2.2 881 2.2
Leisure and hospitality.................. 13.2 249.5 3.2 469 1.3
Other services........................... 16.4 98.1 1.1 777 1.8
Government................................. 1.4 299.4 -1.2 1,174 1.9
New York, NY................................. 122.7 2,392.0 2.4 1,646 0.2
Private industry........................... 122.4 1,956.8 3.0 1,769 0.2
Natural resources and mining............. 0.0 0.1 3.5 1,652 -7.7
Construction............................. 2.1 31.3 2.6 1,621 0.0
Manufacturing............................ 2.4 26.3 -0.6 1,202 -2.3
Trade, transportation, and utilities..... 20.7 249.8 3.1 1,233 0.2
Information.............................. 4.3 143.8 4.1 2,046 2.3
Financial activities..................... 18.8 355.2 -0.5 3,249 1.5
Professional and business services....... 25.3 488.0 3.1 2,025 0.5
Education and health services............ 9.2 303.5 1.2 1,120 0.1
Leisure and hospitality.................. 12.9 257.2 7.0 763 0.3
Other services........................... 18.9 92.6 3.5 1,022 5.3
Government................................. 0.3 435.3 0.0 1,101 -1.2
Harris, TX................................... 103.2 2,121.7 3.8 1,165 4.1
Private industry........................... 102.6 1,869.5 4.8 1,191 4.4
Natural resources and mining............. 1.7 87.9 9.4 2,933 -4.0
Construction............................. 6.5 139.9 5.5 1,143 4.2
Manufacturing............................ 4.5 189.4 7.1 1,415 2.7
Trade, transportation, and utilities..... 23.2 441.0 3.6 1,141 13.4
Information.............................. 1.3 28.0 -0.6 1,337 4.0
Financial activities..................... 10.7 114.2 2.3 1,423 3.0
Professional and business services....... 20.6 357.6 6.0 1,374 2.4
Education and health services............ 11.7 251.5 3.5 898 0.4
Leisure and hospitality.................. 8.5 195.8 5.2 398 1.5
Other services........................... 13.7 62.9 1.3 660 3.0
Government................................. 0.6 252.2 -2.7 979 0.5
Maricopa, AZ................................. 95.5 1,635.4 2.8 905 2.6
Private industry........................... 94.8 1,456.7 3.0 890 2.7
Natural resources and mining............. 0.5 7.8 -5.6 828 10.0
Construction............................. 8.0 86.0 4.0 941 5.4
Manufacturing............................ 3.2 113.7 3.2 1,329 -0.6
Trade, transportation, and utilities..... 21.5 338.2 1.7 838 2.4
Information.............................. 1.6 28.5 2.6 1,123 2.6
Financial activities..................... 10.9 141.4 2.8 1,107 3.8
Professional and business services....... 22.2 270.6 3.2 953 3.8
Education and health services............ 10.5 243.0 3.2 927 1.8
Leisure and hospitality.................. 7.2 175.5 2.8 419 4.5
Other services........................... 6.6 47.3 -0.5 606 2.9
Government................................. 0.7 178.7 1.5 1,014 2.1
Dallas, TX................................... 68.9 1,475.1 3.2 1,074 2.0
Private industry........................... 68.4 1,313.4 3.9 1,082 2.4
Natural resources and mining............. 0.6 9.9 12.9 3,563 15.4
Construction............................. 4.0 70.2 3.3 1,003 4.3
Manufacturing............................ 2.8 112.7 0.9 1,294 6.0
Trade, transportation, and utilities..... 14.9 294.5 3.6 992 2.0
Information.............................. 1.5 46.4 1.6 1,615 0.8
Financial activities..................... 8.5 143.0 3.2 1,446 3.8
Professional and business services....... 15.2 286.8 6.9 1,188 1.1
Education and health services............ 7.5 172.7 2.8 964 -1.7
Leisure and hospitality.................. 5.8 135.7 3.9 446 0.7
Other services........................... 7.2 41.0 1.7 677 2.0
Government................................. 0.5 161.7 -1.9 1,011 -1.0
Orange, CA................................... 106.6 1,416.5 2.4 1,014 1.3
Private industry........................... 105.3 1,271.5 2.9 1,000 1.6
Natural resources and mining............. 0.2 3.5 -12.8 736 12.5
Construction............................. 6.0 70.7 0.7 1,126 4.4
Manufacturing............................ 4.8 158.6 1.4 1,236 0.3
Trade, transportation, and utilities..... 16.1 245.1 0.8 948 1.8
Information.............................. 1.2 24.0 -1.9 1,390 -1.5
Financial activities..................... 9.6 107.6 2.7 1,501 2.6
Professional and business services....... 18.7 260.2 5.4 1,140 0.2
Education and health services............ 10.6 161.5 1.8 939 3.1
Leisure and hospitality.................. 7.2 183.9 5.2 445 4.5
Other services........................... 23.1 50.1 2.4 563 5.4
Government................................. 1.4 145.0 -1.6 1,135 -0.8
San Diego, CA................................ 102.8 1,283.3 2.1 989 0.9
Private industry........................... 101.4 1,063.1 2.7 966 2.1
Natural resources and mining............. 0.7 10.9 9.0 634 6.2
Construction............................. 5.8 57.6 2.9 1,048 2.5
Manufacturing............................ 2.9 93.6 -0.8 1,355 1.7
Trade, transportation, and utilities..... 13.5 205.4 1.8 802 3.6
Information.............................. 1.1 24.5 0.3 1,479 0.2
Financial activities..................... 8.4 70.0 2.9 1,188 2.9
Professional and business services....... 16.1 216.4 3.3 1,379 1.6
Education and health services............ 8.7 155.7 2.5 939 3.0
Leisure and hospitality.................. 7.1 163.7 3.7 414 2.7
Other services........................... 30.2 59.5 2.7 503 -1.6
Government................................. 1.4 220.2 -0.6 1,099 -3.6
King, WA..................................... 82.2 1,174.4 3.0 1,167 2.9
Private industry........................... 81.7 1,015.7 3.6 1,171 3.2
Natural resources and mining............. 0.3 3.0 7.5 1,372 -7.5
Construction............................. 5.3 49.3 6.2 1,143 1.2
Manufacturing............................ 2.2 103.3 5.6 1,417 -0.3
Trade, transportation, and utilities..... 14.3 214.6 3.7 1,019 2.9
Information.............................. 1.7 81.8 1.6 2,243 9.4
Financial activities..................... 6.2 63.4 0.7 1,383 0.9
Professional and business services....... 13.7 191.2 5.5 1,434 2.0
Education and health services............ 7.2 138.5 2.7 968 4.5
Leisure and hospitality.................. 6.4 117.1 3.0 444 2.8
Other services........................... 24.3 53.6 0.4 606 4.7
Government................................. 0.5 158.7 -0.3 1,143 1.2
Miami-Dade, FL............................... 88.9 974.6 2.3 876 -0.5
Private industry........................... 88.5 851.4 3.1 832 -0.1
Natural resources and mining............. 0.5 7.5 2.1 533 1.9
Construction............................. 5.0 29.6 -3.1 808 -6.6
Manufacturing............................ 2.6 35.6 -2.1 795 -1.4
Trade, transportation, and utilities..... 25.8 255.4 3.5 780 -0.3
Information.............................. 1.5 17.1 0.3 1,365 -8.2
Financial activities..................... 9.1 67.3 5.4 1,241 -1.7
Professional and business services....... 18.6 126.0 2.3 1,047 1.7
Education and health services............ 9.9 157.6 2.1 856 0.8
Leisure and hospitality.................. 6.8 118.4 5.9 505 4.8
Other services........................... 7.9 35.7 4.3 540 1.5
Government................................. 0.4 123.2 -3.1 1,156 -0.3
(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 2011 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.
Table 3. Covered(1) establishments, employment, and wages by state,
second quarter 2012(2)
Employment Average weekly
wage(3)
Establishments,
second quarter
State 2012 Percent Percent
(thousands) June change, Second change,
2012 June quarter second
(thousands) 2011-12 2012 quarter
2011-12
United States(4)......... 9,224.5 132,896.0 1.8 $903 1.3
Alabama.................. 116.1 1,841.7 0.9 783 2.0
Alaska................... 21.8 342.9 2.1 955 1.5
Arizona.................. 147.3 2,393.9 2.6 862 2.1
Arkansas................. 85.4 1,157.4 1.1 717 2.1
California............... 1,434.5 15,045.8 2.4 1,034 1.8
Colorado................. 171.4 2,291.8 2.5 918 2.0
Connecticut.............. 111.3 1,650.0 1.2 1,111 -0.4
Delaware................. 27.6 409.3 0.2 948 2.4
District of Columbia..... 35.5 717.9 0.9 1,544 0.3
Florida.................. 606.9 7,233.7 2.0 805 0.4
Georgia.................. 269.5 3,854.7 1.4 848 1.9
Hawaii................... 38.4 603.7 2.1 812 1.8
Idaho.................... 53.5 626.1 1.5 673 0.9
Illinois................. 391.4 5,698.0 1.1 953 1.6
Indiana.................. 160.5 2,832.6 2.3 763 1.9
Iowa..................... 95.2 1,502.7 1.5 743 2.5
Kansas................... 84.6 1,334.4 1.7 763 1.1
Kentucky................. 109.8 1,780.7 1.6 772 1.6
Louisiana................ 129.2 1,877.2 1.6 806 1.5
Maine.................... 49.4 601.8 1.2 719 1.0
Maryland................. 166.9 2,550.2 1.5 992 0.7
Massachusetts............ 219.0 3,301.5 1.9 1,109 -1.2
Michigan................. 239.4 3,984.0 2.1 859 1.7
Minnesota................ 168.7 2,695.1 1.5 907 1.1
Mississippi.............. 68.6 1,087.4 0.6 681 2.9
Missouri................. 176.9 2,629.1 0.4 791 2.2
Montana.................. 42.4 442.0 2.0 700 2.6
Nebraska................. 66.7 930.9 2.0 719 0.7
Nevada................... 72.6 1,141.7 1.6 815 -0.1
New Hampshire............ 48.9 623.8 1.4 891 0.3
New Jersey............... 262.3 3,884.0 1.4 1,056 0.0
New Mexico............... 55.1 791.9 0.4 783 2.6
New York................. 603.3 8,701.2 1.5 1,096 0.4
North Carolina........... 259.0 3,919.1 1.5 787 0.5
North Dakota............. 29.2 420.3 9.9 854 11.1
Ohio..................... 287.4 5,104.0 1.9 817 2.8
Oklahoma................. 104.4 1,543.4 1.9 768 2.7
Oregon................... 133.1 1,663.9 1.6 837 2.3
Pennsylvania............. 352.3 5,645.9 0.7 893 2.1
Rhode Island............. 35.3 463.1 0.9 859 -0.3
South Carolina........... 111.5 1,830.7 1.5 736 1.4
South Dakota............. 31.3 412.8 1.9 677 3.2
Tennessee................ 141.0 2,669.1 2.0 816 2.8
Texas.................... 592.9 10,779.5 3.0 922 2.6
Utah..................... 84.8 1,225.8 3.6 766 1.3
Vermont.................. 24.7 300.2 1.0 792 2.6
Virginia................. 238.1 3,659.9 1.2 952 0.3
Washington............... 234.6 2,948.3 2.4 947 2.2
West Virginia............ 49.3 712.3 1.4 776 1.4
Wisconsin................ 160.0 2,749.7 1.4 778 1.4
Wyoming.................. 25.5 288.9 1.6 842 2.7
Puerto Rico.............. 49.2 933.3 1.8 499 0.6
Virgin Islands........... 3.5 40.2 -8.6 819 9.8
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs.
(2) Data are preliminary.
(3) Average weekly wages were calculated using unrounded data.
(4) Totals for the United States do not include data for Puerto Rico or the
Virgin Islands.
United States Department of Labor
