For release 10:00 a.m. (EDT), Thursday, June 28, 2012 USDL-12-1290
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
County Employment and Wages
Fourth Quarter 2011
From December 2010 to December 2011, employment increased in 266 of
the 322 largest U.S. counties, the U.S. Bureau of Labor Statistics
reported today. Kern, Calif., posted the largest increase, with a
gain of 5.3 percent over the year, compared with national job growth
of 1.4 percent. Within Kern, the largest employment increase occurred
in natural resources and mining, which gained 8,896 jobs over the
year (16.7 percent). Benton, Wash., experienced the largest over-the-
year decrease in employment among the largest counties in the U.S.
with a loss of 3.4 percent.
The U.S. average weekly wage decreased over the year by 1.7 percent
to $955 in the fourth quarter of 2011. This is one of only five
declines in the history of the series which dates back to 1978. (See
Technical Note.) This is the only quarter in which the average weekly
wage decline occurred while employment grew over the year and total
wages decreased (-0.5 percent). Smaller bonus payments in the fourth
quarter of 2011 contributed to the decrease in the average weekly
wage. In contrast, the average weekly wage declines posted in the
first two quarters of 2009 resulted from significant declines in both
employment and wages. During this period, total wage declines were
5.0 percent or more, while employment losses were above 3.0 percent.
In the fourth quarter of 2011, Olmsted, Minn., had the largest over-
the-year decrease in average weekly wages with a loss of 21.3
percent. Within Olmsted, a total wage decline of $287.3 million
(-29.1 percent) in the education and health services industry had the
largest impact on the county’s decrease in average weekly wages.
Table A. Large counties ranked by December 2011 employment, December 2010-11 employment
increase, and December 2010-11 percent increase in employment
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Employment in large counties
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December 2011 employment | Increase in employment, | Percent increase in employment,
(thousands) | December 2010-11 | December 2010-11
| (thousands) |
--------------------------------------------------------------------------------------------------------
| |
United States 131,254.2| United States 1,782.4| United States 1.4
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| |
Los Angeles, Calif. 3,953.7| Harris, Texas 62.7| Kern, Calif. 5.3
Cook, Ill. 2,413.1| New York, N.Y. 51.9| Fort Bend, Texas 4.5
New York, N.Y. 2,387.3| Maricopa, Ariz. 41.6| Weld, Colo. 4.3
Harris, Texas 2,081.7| Dallas, Texas 32.2| Williamson, Tenn. 4.3
Maricopa, Ariz. 1,683.7| Cook, Ill. 31.1| Utah, Utah 4.3
Dallas, Texas 1,460.4| Los Angeles, Calif. 27.5| Washington, Pa. 4.0
Orange, Calif. 1,390.2| King, Wash. 26.9| Rutherford, Tenn. 4.0
San Diego, Calif. 1,264.2| Hennepin, Minn. 23.4| Montgomery, Texas 4.0
King, Wash. 1,156.6| Oakland, Mich. 22.2| Harford, Md. 3.9
Miami-Dade, Fla. 996.2| Miami-Dade, Fla. 21.1| Webb, Texas 3.9
--------------------------------------------------------------------------------------------------------
Tulsa, Okla., experienced the largest increase in average weekly
wages with a gain of 8.6 percent over the year. County employment and
wage data are compiled under the Quarterly Census of Employment and
Wages (QCEW) program.
Large County Employment
In December 2011, national employment, as measured by the QCEW
program, was 131.3 million, up by 1.4 percent or 1.8 million jobs,
from December 2010. The 322 U.S. counties with 75,000 or more jobs
accounted for 70.7 percent of total U.S. employment and 76.4 percent
of total wages. These 322 counties had a net job growth of 1.2
million over the year, accounting for 68.8 percent of the overall
U.S. employment increase.
Kern, Calif., had the largest percentage increase in employment among
the largest U.S. counties (5.3 percent). The five counties with the
largest increases in employment level were Harris, Texas; New York,
N.Y.; Maricopa, Ariz.; Dallas, Texas; and Cook, Ill. These counties
had a combined over-the-year gain of 219,500, or 12.3 percent of the
overall employment increase for the U.S.
Employment declined in 46 of the large counties from December 2010 to
December 2011. Benton, Wash., had the largest over-the-year
percentage decrease in employment (-3.4 percent). Within Benton,
professional and business services was the largest contributor to the
decrease in employment with a loss of 2,280 jobs (-9.5 percent). St.
Clair, Ill., had the second largest employment decrease, followed by
Jackson, Ore.; Frederick, Md.; and Monmouth, N.J. (See table 1.)
Table B. Large counties ranked by fourth quarter 2011 average weekly wages, fourth quarter 2010-11
decrease in average weekly wages, and fourth quarter 2010-11 percent decrease in average weekly wages
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Average weekly wage in large counties
--------------------------------------------------------------------------------------------------------
Average weekly wage, | Decrease in average weekly | Percent decrease in average
fourth quarter 2011 | wage, fourth quarter 2010-11 | weekly wage, fourth
| | quarter 2010-11
--------------------------------------------------------------------------------------------------------
| |
United States $955| United States -$17| United States -1.7
--------------------------------------------------------------------------------------------------------
| |
New York, N.Y. $1,889| Olmsted, Minn. -$279| Olmsted, Minn. -21.3
Santa Clara, Calif. 1,836| Santa Clara, Calif. -111| Douglas, Colo. -8.6
Washington, D.C. 1,668| Douglas, Colo. -100| Williamson, Tenn. -6.7
Suffolk, Mass. 1,599| Durham, N.C. -84| Durham, N.C. -6.5
San Francisco, Calif. 1,597| Arlington, Va. -84| St. Clair, Ill. -6.2
Arlington, Va. 1,591| Fairfield, Conn. -77| Kitsap, Wash. -6.0
Fairfield, Conn. 1,589| Williamson, Tenn. -75| Santa Clara, Calif. -5.7
San Mateo, Calif. 1,556| Somerset, N.J. -74| Vanderburgh, Ind. -5.6
Fairfax, Va. 1,519| Loudoun, Va. -60| Williamson, Texas -5.3
Alexandria City, Va. 1,434| Denver, Colo. -59| Somerset, N.J. -5.0
| | Arlington, Va. -5.0
| | Loudoun, Va. -5.0
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Large County Average Weekly Wages
Average weekly wages for the nation decreased by 1.7 percent during
the year ending in the fourth quarter of 2011. Among the 322 largest
counties, 282 had over-the-year declines in average weekly wages.
Olmsted, Minn., had the largest wage loss among the
largest U.S. counties (-21.3 percent). This decline reflects a return
to normal pay in 2011 following a big payout in education and health
services in the fourth quarter of 2010.
Of the 322 largest counties, 36 experienced over-the-year increases
in average weekly wages. Tulsa, Okla., had the largest average weekly
wage increase with a gain of 8.6 percent. An acquisition within
professional and business services resulted in large payouts in the
fourth quarter of 2011, which significantly boosted the county’s
average weekly wage. Total wages in this industry in Tulsa increased
by $219.4 million (33.3 percent) over the year. Harford, Md., had the
second largest increase in average weekly wages, followed by Lake,
Ohio; Snohomish, Wash.; and Westmoreland, Pa. (See table 1.)
Ten Largest U.S. Counties
All of the 10 largest counties experienced over-the-year percentage
increases in employment in December 2011. Harris, Texas, experienced
the largest gain in employment (3.1 percent). Within Harris,
professional and business services had the largest over-the-year
level increase among all private industry groups with a gain of
16,195 jobs (5.0 percent). Orange, Calif., had the smallest percent
increase in employment among the 10 largest counties. (See table 2.)
Eight of the 10 largest U.S. counties had an over-the-year decrease
in average weekly wages. San Diego, Calif., experienced the largest
decrease in average weekly wages with a loss of 3.6 percent, largely
due to significant total wage declines over the year in financial
activities (-$226.6 million or -17.3 percent). King, Wash., had the
largest average weekly wage increase.
For More Information
The tables 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. December 2011 employment and 2011
fourth quarter average weekly wages for all states are provided in
table 3 of this release.
The employment and wage data by county are compiled under the QCEW
program, also known as the ES-202 program. The data are derived from
reports submitted by every employer subject to unemployment insurance
(UI) laws. The 9.2 million employer reports cover 131.3 million full-
and part-time workers. For additional information about the quarterly
employment and wages data, please read the Technical Note. Data for
the fourth quarter of 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 first quarter 2012 is
scheduled to be released on Thursday, September 27, 2012.
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- | 486,000 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 | | |
---------------------------------------------------------------------------------
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 2010 edition of this publication, which was published in November 2011,
contains selected data produced by Business Employment Dynamics (BED) on job gains
and losses, as well as selected data from the first quarter 2011 version of this news
release. Tables and additional content from Employment and Wages Annual Averages 2010
are now available online at http://www.bls.gov/cew/cewbultn10.htm. The 2011 edition of
Employment and Wages Annual Averages Online will be available later in 2012.
News releases on quarterly measures of gross job flows also are available upon request
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,
fourth quarter 2011(2)
Employment Average weekly wage(4)
Establishments,
County(3) fourth quarter Percent Ranking Percent Ranking
2011 December change, by Fourth change, by
(thousands) 2011 December percent quarter fourth percent
(thousands) 2010-11(5) change 2011 quarter change
2010-11(5)
United States(6)......... 9,178.6 131,254.2 1.4 - $955 -1.7 -
Jefferson, AL............ 17.7 334.7 0.9 172 964 -0.8 80
Madison, AL.............. 8.9 179.1 -0.5 291 1,077 -0.6 67
Mobile, AL............... 9.8 165.6 -0.9 306 876 1.9 9
Montgomery, AL........... 6.3 128.5 -0.7 303 877 0.5 28
Tuscaloosa, AL........... 4.2 84.5 1.0 156 828 -0.4 55
Anchorage Borough, AK.... 8.3 152.1 1.6 97 1,015 -1.2 109
Maricopa, AZ............. 96.1 1,683.7 2.5 42 929 -1.0 95
Pima, AZ................. 19.0 348.9 0.1 256 828 -1.9 167
Benton, AR............... 5.5 95.8 2.0 78 869 2.7 6
Pulaski, AR.............. 15.1 246.5 0.3 238 869 -0.5 58
Washington, AR........... 5.6 92.3 1.9 83 828 (7) -
Alameda, CA.............. 57.5 641.2 1.6 97 1,212 -3.8 280
Contra Costa, CA......... 30.6 319.5 0.7 191 1,139 -2.9 240
Fresno, CA............... 31.5 329.2 0.6 205 751 -1.8 157
Kern, CA................. 18.3 285.2 5.3 1 826 -0.8 80
Los Angeles, CA.......... 447.9 3,953.7 0.7 191 1,124 -3.2 258
Marin, CA................ 12.0 105.1 2.3 52 1,181 -1.1 105
Monterey, CA............. 13.2 147.5 2.1 70 799 -2.9 240
Orange, CA............... 106.1 1,390.2 0.6 205 1,080 -3.1 254
Placer, CA............... 11.1 128.0 2.1 70 935 -2.7 232
Riverside, CA............ 51.3 565.1 0.6 205 759 -1.6 137
Sacramento, CA........... 55.1 575.4 -0.2 283 1,042 -1.4 121
San Bernardino, CA....... 52.6 609.6 0.2 248 811 -1.6 137
San Diego, CA............ 102.3 1,264.2 1.0 156 1,041 -3.6 275
San Francisco, CA........ 56.7 572.3 3.3 20 1,597 0.8 24
San Joaquin, CA.......... 17.9 200.0 0.9 172 799 -3.0 247
San Luis Obispo, CA...... 9.9 100.0 1.1 144 798 -2.0 176
San Mateo, CA............ 24.9 333.9 2.5 42 1,556 0.1 36
Santa Barbara, CA........ 14.8 173.6 2.5 42 894 -2.6 224
Santa Clara, CA.......... 64.3 883.0 2.3 52 1,836 -5.7 313
Santa Cruz, CA........... 9.3 86.1 -0.9 306 860 -0.2 45
Solano, CA............... 10.3 120.7 0.5 222 925 -3.6 275
Sonoma, CA............... 19.4 177.9 0.6 205 895 -3.0 247
Stanislaus, CA........... 15.4 158.2 0.7 191 775 -2.1 185
Tulare, CA............... 9.6 140.4 0.9 172 669 -0.6 67
Ventura, CA.............. 24.5 301.5 0.6 205 954 -3.1 254
Yolo, CA................. 6.2 87.7 0.8 179 922 -4.9 307
Adams, CO................ 8.8 156.3 1.2 130 860 -2.4 212
Arapahoe, CO............. 18.7 282.8 3.3 20 1,108 -1.4 121
Boulder, CO.............. 12.9 158.8 2.6 38 1,114 -0.6 67
Denver, CO............... 25.4 429.3 2.2 63 1,162 -4.8 305
Douglas, CO.............. 9.4 93.5 2.9 30 1,065 -8.6 318
El Paso, CO.............. 16.7 236.5 1.0 156 870 -2.1 185
Jefferson, CO............ 17.7 208.0 2.0 78 976 -3.9 283
Larimer, CO.............. 10.0 130.2 2.5 42 857 -0.1 38
Weld, CO................. 5.8 83.2 4.3 3 808 -1.5 126
Fairfield, CT............ 32.5 412.7 1.5 109 1,589 -4.6 300
Hartford, CT............. 25.4 495.5 0.7 191 1,145 -2.5 220
New Haven, CT............ 22.3 356.3 1.0 156 1,006 -3.2 258
New London, CT........... 6.9 123.5 -1.1 311 953 -0.4 55
New Castle, DE........... 17.1 270.4 0.8 179 1,102 -1.6 137
Washington, DC........... 36.4 708.0 1.3 119 1,668 -1.2 109
Alachua, FL.............. 6.5 116.1 0.2 248 825 -1.2 109
Brevard, FL.............. 14.4 189.6 0.3 238 863 -4.7 303
Broward, FL.............. 63.1 701.2 0.8 179 891 -3.4 267
Collier, FL.............. 11.7 122.9 2.1 70 809 -4.3 294
Duval, FL................ 26.9 444.1 0.5 222 900 -4.1 289
Escambia, FL............. 7.8 120.2 0.0 267 765 -0.9 88
Hillsborough, FL......... 37.5 587.1 1.3 119 920 -2.3 202
Lake, FL................. 7.2 80.0 0.6 205 649 -1.5 126
Lee, FL.................. 18.5 201.1 1.1 144 761 -2.1 185
Leon, FL................. 8.2 138.9 -0.6 298 807 -2.7 232
Manatee, FL.............. 9.2 107.3 3.3 20 736 -0.8 80
Marion, FL............... 7.9 89.9 -0.6 298 672 -1.0 95
Miami-Dade, FL........... 87.8 996.2 2.2 63 939 -2.5 220
Orange, FL............... 35.9 672.5 2.0 78 828 -4.1 289
Palm Beach, FL........... 49.4 511.7 2.4 48 931 -4.8 305
Pasco, FL................ 9.9 100.0 -0.1 275 666 -2.8 238
Pinellas, FL............. 30.6 382.4 0.6 205 884 -1.6 137
Polk, FL................. 12.4 192.7 -1.5 314 718 -0.8 80
Sarasota, FL............. 14.4 137.5 2.1 70 800 -1.8 157
Seminole, FL............. 13.8 157.2 1.1 144 781 -2.1 185
Volusia, FL.............. 13.2 149.9 -0.1 275 673 -2.3 202
Bibb, GA................. 4.6 80.6 1.3 119 742 -2.2 195
Chatham, GA.............. 7.7 131.2 1.1 144 806 -1.9 167
Clayton, GA.............. 4.3 102.0 0.0 267 823 -0.5 58
Cobb, GA................. 21.1 297.0 1.9 83 975 -3.1 254
De Kalb, GA.............. 17.8 278.6 1.2 130 979 -1.0 95
Fulton, GA............... 41.2 735.5 1.8 89 1,238 -3.9 283
Gwinnett, GA............. 24.0 305.4 1.6 97 922 -2.6 224
Muscogee, GA............. 4.7 94.1 1.1 144 761 -2.6 224
Richmond, GA............. 4.7 98.9 0.2 248 804 -2.1 185
Honolulu, HI............. 24.6 446.3 1.2 130 882 -1.5 126
Ada, ID.................. 13.9 197.7 2.4 48 833 -4.0 286
Champaign, IL............ 4.2 87.4 -0.5 291 786 -0.6 67
Cook, IL................. 147.3 2,413.1 1.3 119 1,122 -2.9 240
Du Page, IL.............. 37.0 570.9 2.2 63 1,112 -1.1 105
Kane, IL................. 13.3 192.5 0.2 248 863 -0.9 88
Lake, IL................. 21.9 313.6 0.1 256 1,208 -4.5 298
McHenry, IL.............. 8.6 92.4 -0.6 298 820 0.6 26
McLean, IL............... 3.8 86.2 0.3 238 937 1.5 11
Madison, IL.............. 6.0 94.9 -0.7 303 791 -1.5 126
Peoria, IL............... 4.7 102.6 0.4 231 926 0.3 32
St. Clair, IL............ 5.6 96.6 -2.9 319 796 -6.2 315
Sangamon, IL............. 5.3 130.5 0.8 179 956 -0.1 38
Will, IL................. 14.9 201.4 1.1 144 827 -4.4 296
Winnebago, IL............ 6.8 125.8 0.1 256 815 -1.5 126
Allen, IN................ 9.0 174.6 1.0 156 775 -0.9 88
Elkhart, IN.............. 4.9 104.6 3.8 11 717 -2.4 212
Hamilton, IN............. 8.4 112.9 3.4 19 877 -4.2 292
Lake, IN................. 10.4 188.4 2.1 70 868 0.7 25
Marion, IN............... 23.9 558.9 1.7 94 948 -1.9 167
St. Joseph, IN........... 6.0 117.7 1.5 109 763 -4.5 298
Vanderburgh, IN.......... 4.9 107.0 2.0 78 786 -5.6 312
Linn, IA................. 6.2 126.8 0.6 205 942 1.5 11
Polk, IA................. 14.7 270.2 1.8 89 940 -3.2 258
Scott, IA................ 5.2 87.8 1.6 97 799 -0.2 45
Johnson, KS.............. 22.0 308.0 2.4 48 985 -1.0 95
Sedgwick, KS............. 12.7 240.9 0.2 248 877 -2.6 224
Shawnee, KS.............. 5.0 94.9 -0.3 286 789 -1.6 137
Wyandotte, KS............ 3.4 81.6 1.0 156 875 -2.1 185
Fayette, KY.............. 9.3 179.5 (7) - 836 -1.9 167
Jefferson, KY............ 22.0 420.1 0.5 222 915 -1.0 95
Caddo, LA................ 7.4 122.3 0.0 267 812 -0.5 58
Calcasieu, LA............ 4.8 82.0 -0.5 291 817 0.6 26
East Baton Rouge, LA..... 14.4 257.9 1.1 144 888 -3.0 247
Jefferson, LA............ 13.6 193.9 -0.9 306 896 -1.9 167
Lafayette, LA............ 8.9 136.2 2.7 33 951 -0.2 45
Orleans, LA.............. 10.9 177.1 2.6 38 987 -4.6 300
Cumberland, ME........... 12.6 171.1 0.7 191 865 -1.1 105
Anne Arundel, MD......... 14.3 235.4 2.8 32 1,025 -2.3 202
Baltimore, MD............ 20.8 366.8 0.5 222 988 -3.4 267
Frederick, MD............ 6.1 91.5 -2.0 317 943 -2.5 220
Harford, MD.............. 5.5 86.0 3.9 9 996 5.8 2
Howard, MD............... 8.9 153.4 2.2 63 1,159 -2.4 212
Montgomery, MD........... 32.4 456.5 1.0 156 1,324 -0.5 58
Prince Georges, MD....... 15.3 303.4 -0.4 288 1,009 -2.6 224
Baltimore City, MD....... 13.7 332.1 0.8 179 1,114 -3.6 275
Barnstable, MA........... 9.3 83.2 0.1 256 828 -1.3 119
Bristol, MA.............. 16.5 212.3 0.3 238 856 -0.5 58
Essex, MA................ 22.2 302.5 1.4 115 1,024 -1.8 157
Hampden, MA.............. 15.5 197.2 0.5 222 864 -2.0 176
Middlesex, MA............ 50.6 824.0 1.0 156 1,376 -3.0 247
Norfolk, MA.............. 24.2 323.8 1.2 130 1,159 -2.1 185
Plymouth, MA............. 14.4 173.9 0.6 205 903 -1.2 109
Suffolk, MA.............. 23.9 593.5 2.2 63 1,599 -2.9 240
Worcester, MA............ 22.0 319.5 1.3 119 965 -0.2 45
Genesee, MI.............. 7.1 130.3 0.9 172 829 -0.1 38
Ingham, MI............... 6.2 155.2 0.1 256 899 -3.2 258
Kalamazoo, MI............ 5.2 108.3 0.4 231 862 -2.0 176
Kent, MI................. 13.6 327.8 3.6 14 854 -1.7 151
Macomb, MI............... 16.6 287.4 2.0 78 999 1.1 19
Oakland, MI.............. 36.6 650.0 3.5 17 1,104 -1.6 137
Ottawa, MI............... 5.4 105.0 3.6 14 833 -0.6 67
Saginaw, MI.............. 4.0 83.4 2.3 52 786 -1.5 126
Washtenaw, MI............ 7.8 194.9 0.5 222 993 -1.6 137
Wayne, MI................ 30.4 684.9 2.3 52 1,075 1.2 16
Anoka, MN................ 7.2 109.4 3.1 24 867 -3.1 254
Dakota, MN............... 9.7 171.5 1.2 130 900 -4.7 303
Hennepin, MN............. 43.6 842.8 2.9 30 1,157 -4.6 300
Olmsted, MN.............. 3.4 89.0 2.1 70 1,032 -21.3 319
Ramsey, MN............... 13.9 321.3 1.8 89 1,027 -3.9 283
St. Louis, MN............ 5.6 93.3 -0.1 275 772 -1.2 109
Stearns, MN.............. 4.3 80.6 2.3 52 756 -0.5 58
Harrison, MS............. 4.5 82.5 0.0 267 685 -3.5 274
Hinds, MS................ 6.1 122.8 0.1 256 828 -2.2 195
Boone, MO................ 4.5 85.4 3.5 17 732 -1.2 109
Clay, MO................. 5.0 89.4 0.0 267 884 -0.1 38
Greene, MO............... 8.0 151.8 2.5 42 709 -2.6 224
Jackson, MO.............. 18.4 344.0 0.5 222 961 -2.0 176
St. Charles, MO.......... 8.2 125.4 2.3 52 746 -1.2 109
St. Louis, MO............ 32.0 569.5 0.4 231 1,017 -2.9 240
St. Louis City, MO....... 9.1 218.9 1.3 119 1,029 -1.5 126
Yellowstone, MT.......... 6.0 77.5 2.7 33 803 -0.1 38
Douglas, NE.............. 16.1 315.7 0.1 256 858 -2.6 224
Lancaster, NE............ 8.3 156.2 1.2 130 763 -0.9 88
Clark, NV................ 47.8 807.9 1.2 130 841 -3.4 267
Washoe, NV............... 13.7 186.3 -0.3 286 860 -1.8 157
Hillsborough, NH......... 11.9 190.7 0.7 191 1,093 -0.1 38
Rockingham, NH........... 10.6 135.3 0.9 172 923 -2.3 202
Atlantic, NJ............. 6.7 131.8 0.2 248 827 -0.2 45
Bergen, NJ............... 33.4 435.4 0.7 191 1,198 -2.4 212
Burlington, NJ........... 11.1 193.0 -0.5 291 1,020 -2.1 185
Camden, NJ............... 12.3 197.3 0.6 205 987 -4.0 286
Essex, NJ................ 20.8 343.9 0.3 238 1,178 -4.2 292
Gloucester, NJ........... 6.2 97.9 -0.9 306 853 -1.3 119
Hudson, NJ............... 13.9 233.6 0.1 256 1,268 -1.1 105
Mercer, NJ............... 11.1 229.2 0.7 191 1,260 -2.2 195
Middlesex, NJ............ 21.8 384.7 0.7 191 1,146 -2.3 202
Monmouth, NJ............. 20.1 242.1 -1.6 316 1,005 -3.0 247
Morris, NJ............... 17.4 271.6 -0.2 283 1,400 -1.5 126
Ocean, NJ................ 12.2 145.6 1.1 144 797 -3.7 278
Passaic, NJ.............. 12.3 175.4 1.4 115 1,024 2.4 7
Somerset, NJ............. 10.1 171.3 0.7 191 1,393 -5.0 308
Union, NJ................ 14.5 221.6 0.8 179 1,222 1.0 21
Bernalillo, NM........... 17.8 310.2 -0.8 305 829 -2.7 232
Albany, NY............... 10.0 220.1 -0.1 275 957 -2.2 195
Bronx, NY................ 16.9 235.6 -0.1 275 908 (7) -
Broome, NY............... 4.5 90.9 -0.5 291 749 -1.6 137
Dutchess, NY............. 8.2 113.2 0.6 205 956 -1.4 121
Erie, NY................. 23.7 459.4 0.4 231 828 -1.0 95
Kings, NY................ 52.0 518.8 2.3 52 806 -3.4 267
Monroe, NY............... 18.2 379.7 1.7 94 887 -0.6 67
Nassau, NY............... 52.7 603.4 1.3 119 1,110 -0.9 88
New York, NY............. 122.0 2,387.3 2.2 63 1,889 -2.3 202
Oneida, NY............... 5.2 106.9 -1.5 314 749 -1.7 151
Onondaga, NY............. 12.9 243.1 0.0 267 879 -1.6 137
Orange, NY............... 9.9 133.3 0.6 205 806 -1.6 137
Queens, NY............... 46.4 512.3 2.3 52 916 -2.4 212
Richmond, NY............. 9.0 93.7 1.2 130 814 -3.3 263
Rockland, NY............. 9.9 116.7 1.3 119 991 -4.3 294
Suffolk, NY.............. 50.6 621.7 0.7 191 1,056 -0.8 80
Westchester, NY.......... 36.0 410.2 0.8 179 1,278 -4.1 289
Buncombe, NC............. 8.0 113.0 0.8 179 734 -1.5 126
Catawba, NC.............. 4.4 79.2 1.0 156 730 -0.3 54
Cumberland, NC........... 6.3 120.2 0.8 179 771 0.5 28
Durham, NC............... 7.3 182.4 1.6 97 1,205 -6.5 316
Forsyth, NC.............. 9.0 174.4 1.2 130 853 -3.4 267
Guilford, NC............. 14.2 265.3 1.1 144 819 -2.4 212
Mecklenburg, NC.......... 32.8 565.5 3.1 24 1,047 -3.3 263
New Hanover, NC.......... 7.4 96.6 1.1 144 790 -1.9 167
Wake, NC................. 29.6 447.9 2.1 70 945 -1.6 137
Cass, ND................. 6.1 105.0 3.7 12 830 0.4 30
Butler, OH............... 7.4 141.4 0.6 205 821 -1.8 157
Cuyahoga, OH............. 36.1 695.8 0.9 172 971 -1.9 167
Franklin, OH............. 29.8 669.6 2.3 52 932 -0.6 67
Hamilton, OH............. 23.4 490.7 1.2 130 1,032 -1.4 121
Lake, OH................. 6.5 94.8 1.3 119 842 4.9 3
Lorain, OH............... 6.1 95.0 2.1 70 797 1.1 19
Lucas, OH................ 10.3 203.6 1.2 130 837 -1.2 109
Mahoning, OH............. 6.1 98.1 0.7 191 693 -1.8 157
Montgomery, OH........... 12.2 244.3 0.8 179 841 -2.0 176
Stark, OH................ 8.8 153.9 1.5 109 730 -1.6 137
Summit, OH............... 14.4 257.3 0.3 238 858 -1.7 151
Oklahoma, OK............. 24.7 426.4 1.6 97 902 -0.2 45
Tulsa, OK................ 20.3 333.4 1.0 156 963 8.6 1
Clackamas, OR............ 12.7 140.1 1.3 119 862 -0.6 67
Jackson, OR.............. 6.6 75.8 -2.6 318 689 -1.7 151
Lane, OR................. 10.8 136.8 0.8 179 738 -0.9 88
Marion, OR............... 9.4 128.8 -0.6 298 734 -1.2 109
Multnomah, OR............ 29.4 437.7 1.8 89 969 -1.0 95
Washington, OR........... 16.3 248.0 2.7 33 1,085 1.4 14
Allegheny, PA............ 35.5 685.4 1.2 130 1,011 -1.9 167
Berks, PA................ 9.0 164.8 0.6 205 851 -2.0 176
Bucks, PA................ 19.9 252.3 0.5 222 929 -2.3 202
Butler, PA............... 4.9 82.6 1.9 83 856 -0.1 38
Chester, PA.............. 15.2 238.6 0.1 256 1,284 1.3 15
Cumberland, PA........... 6.1 124.4 0.9 172 843 -4.0 286
Dauphin, PA.............. 7.5 174.8 -0.4 288 917 -3.8 280
Delaware, PA............. 13.7 210.3 0.1 256 1,003 -0.9 88
Erie, PA................. 7.8 125.4 1.2 130 761 0.9 22
Lackawanna, PA........... 5.9 97.8 -1.2 312 718 -3.0 247
Lancaster, PA............ 12.7 219.5 -0.1 275 787 -2.7 232
Lehigh, PA............... 8.6 177.9 1.1 144 938 -2.4 212
Luzerne, PA.............. 7.8 140.7 0.7 191 723 -3.0 247
Montgomery, PA........... 27.3 467.3 0.1 256 1,173 -2.2 195
Northampton, PA.......... 6.5 100.7 1.0 156 833 -2.0 176
Philadelphia, PA......... 34.8 632.6 -0.6 298 1,133 -2.2 195
Washington, PA........... 5.7 85.5 4.0 6 900 2.0 8
Westmoreland, PA......... 9.5 131.8 -0.1 275 803 2.9 5
York, PA................. 9.2 171.3 0.3 238 808 -3.3 263
Providence, RI........... 17.3 270.0 -0.1 275 964 -1.6 137
Charleston, SC........... 11.8 213.3 2.7 33 829 -1.2 109
Greenville, SC........... 12.2 235.1 3.0 28 814 -3.8 280
Horry, SC................ 7.6 101.9 0.2 248 569 -2.7 232
Lexington, SC............ 5.5 97.9 2.7 33 712 -1.4 121
Richland, SC............. 8.9 204.1 0.4 231 827 -0.7 77
Spartanburg, SC.......... 5.8 114.0 1.0 156 817 -0.2 45
Minnehaha, SD............ 6.6 115.3 1.5 109 814 0.9 22
Davidson, TN............. 18.1 429.9 2.3 52 1,022 -2.9 240
Hamilton, TN............. 8.4 185.2 1.1 144 861 -0.2 45
Knox, TN................. 10.7 222.1 1.9 83 842 -0.7 77
Rutherford, TN........... 4.4 100.3 4.0 6 841 -2.2 195
Shelby, TN............... 18.9 475.9 1.8 89 968 -3.7 278
Williamson, TN........... 6.1 95.1 4.3 3 1,050 -6.7 317
Bell, TX................. 4.8 108.1 1.5 109 773 1.2 16
Bexar, TX................ 34.7 741.7 1.6 97 863 -0.2 45
Brazoria, TX............. 4.9 89.6 1.6 97 909 1.5 11
Brazos, TX............... 4.0 87.2 -1.4 313 707 -1.0 95
Cameron, TX.............. 6.4 126.8 0.0 267 597 -1.8 157
Collin, TX............... 18.9 302.4 2.6 38 1,085 0.0 37
Dallas, TX............... 69.1 1,460.4 2.3 52 1,148 -2.0 176
Denton, TX............... 11.3 184.1 3.7 12 831 -1.0 95
El Paso, TX.............. 14.0 277.0 0.3 238 674 -2.3 202
Fort Bend, TX............ 9.6 140.7 4.5 2 954 -2.7 232
Galveston, TX............ 5.4 96.1 1.3 119 869 -0.5 58
Harris, TX............... 102.9 2,081.7 3.1 24 1,239 0.2 34
Hidalgo, TX.............. 11.3 229.0 1.4 115 601 -1.6 137
Jefferson, TX............ 5.9 124.0 1.6 97 966 1.2 16
Lubbock, TX.............. 7.1 125.6 -0.2 283 717 -3.4 267
McLennan, TX............. 4.9 100.7 0.4 231 773 -2.4 212
Montgomery, TX........... 9.0 137.9 4.0 6 910 -1.8 157
Nueces, TX............... 7.9 154.2 1.2 130 841 1.6 10
Smith, TX................ 5.6 94.1 0.6 205 817 -1.7 151
Tarrant, TX.............. 38.3 775.2 2.2 63 933 -4.4 296
Travis, TX............... 31.4 591.6 3.1 24 1,080 0.2 34
Webb, TX................. 4.9 91.5 3.9 9 651 -0.5 58
Williamson, TX........... 7.8 130.5 1.9 83 914 -5.3 311
Davis, UT................ 7.3 106.4 (7) - 771 (7) -
Salt Lake, UT............ 37.7 582.3 2.6 38 896 -2.9 240
Utah, UT................. 13.0 174.1 4.3 3 760 -0.8 80
Weber, UT................ 5.5 89.8 1.4 115 703 -2.1 185
Chittenden, VT........... 6.0 98.4 3.0 28 943 -1.8 157
Arlington, VA............ 8.4 168.4 0.3 238 1,591 -5.0 308
Chesterfield, VA......... 7.7 116.6 1.6 97 852 -2.5 220
Fairfax, VA.............. 34.9 592.7 1.7 94 1,519 -1.5 126
Henrico, VA.............. 10.0 175.5 1.0 156 939 -2.0 176
Loudoun, VA.............. 9.9 139.8 2.5 42 1,136 -5.0 308
Prince William, VA....... 7.9 110.9 3.2 23 848 -2.8 238
Alexandria City, VA...... 6.3 96.0 0.6 205 1,434 0.4 30
Chesapeake City, VA...... 5.7 96.4 0.2 248 751 -0.7 77
Newport News City, VA.... 3.8 98.1 1.9 83 876 -1.7 151
Norfolk City, VA......... 5.6 139.6 0.8 179 933 -2.6 224
Richmond City, VA........ 7.3 150.3 1.6 97 1,027 -3.3 263
Virginia Beach City, VA.. 11.4 162.6 0.5 222 763 -0.8 80
Benton, WA............... 5.6 77.5 -3.4 320 991 -3.2 258
Clark, WA................ 13.3 129.0 1.0 156 844 -2.3 202
King, WA................. 82.0 1,156.6 2.4 48 1,220 0.3 32
Kitsap, WA............... 6.6 81.0 -0.5 291 836 -6.0 314
Pierce, WA............... 21.4 261.8 0.0 267 842 -1.8 157
Snohomish, WA............ 18.9 252.1 3.6 14 1,001 3.0 4
Spokane, WA.............. 15.7 198.1 0.4 231 783 -0.6 67
Thurston, WA............. 7.3 96.3 -0.9 306 831 -2.1 185
Whatcom, WA.............. 6.9 79.3 1.0 156 773 -0.5 58
Yakima, WA............... 8.8 93.9 1.5 109 648 -0.8 80
Kanawha, WV.............. 6.0 106.6 1.6 97 834 -1.0 95
Brown, WI................ 6.5 146.4 0.3 238 851 -1.5 126
Dane, WI................. 14.0 304.5 1.0 156 907 -2.3 202
Milwaukee, WI............ 22.5 472.9 -0.4 288 942 -3.4 267
Outagamie, WI............ 5.0 102.1 0.6 205 797 -0.4 55
Waukesha, WI............. 12.6 224.7 0.7 191 940 -0.6 67
Winnebago, WI............ 3.7 89.6 -0.5 291 885 -1.9 167
San Juan, PR............. 11.3 272.5 0.7 (8) 655 -1.8 (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,
fourth quarter 2011(2)
Employment Average weekly
wage(3)
Establishments,
fourth quarter
County by NAICS supersector 2011 Percent Percent
(thousands) December change, Fourth change,
2011 December quarter fourth
(thousands) 2010-11(4) 2011 quarter
2010-11(4)
United States(5)............................. 9,178.6 131,254.2 1.4 $955 -1.7
Private industry........................... 8,881.5 109,730.2 1.9 957 -1.6
Natural resources and mining............. 129.2 1,848.4 7.0 1,082 1.9
Construction............................. 762.3 5,466.3 1.3 1,050 -0.9
Manufacturing............................ 337.4 11,789.5 1.9 1,169 -3.1
Trade, transportation, and utilities..... 1,880.8 25,771.9 1.7 796 -1.2
Information.............................. 144.0 2,684.6 -1.1 1,500 -0.9
Financial activities..................... 811.1 7,470.7 0.5 1,462 -1.7
Professional and business services....... 1,580.3 17,615.4 3.0 1,266 -1.8
Education and health services............ 916.6 19,305.0 1.9 904 -2.2
Leisure and hospitality.................. 762.3 13,143.3 2.2 404 -1.2
Other services........................... 1,342.4 4,414.6 1.1 600 -0.7
Government................................. 297.1 21,523.9 -1.4 944 -2.0
Los Angeles, CA.............................. 447.9 3,953.7 0.7 1,124 -3.2
Private industry........................... 442.3 3,398.7 1.2 1,117 -3.5
Natural resources and mining............. 0.4 9.5 3.4 1,413 -21.6
Construction............................. 12.3 106.5 3.5 1,113 -2.8
Manufacturing............................ 12.7 363.9 -1.6 1,140 -4.6
Trade, transportation, and utilities..... 50.7 774.0 1.5 867 -1.5
Information.............................. 8.4 193.0 -4.0 2,077 -6.5
Financial activities..................... 22.0 211.6 0.0 1,536 -3.3
Professional and business services....... 42.0 556.7 2.1 1,401 -5.7
Education and health services............ 29.3 520.9 2.0 1,053 -1.0
Leisure and hospitality.................. 27.2 401.2 2.4 911 -2.8
Other services........................... 212.4 239.1 -1.7 458 -3.6
Government................................. 5.6 555.0 -2.0 1,166 -1.2
Cook, IL..................................... 147.3 2,413.1 1.3 1,122 -2.9
Private industry........................... 145.9 2,115.1 1.6 1,124 -3.1
Natural resources and mining............. 0.1 0.8 -2.0 1,111 -2.9
Construction............................. 12.3 61.6 1.2 1,402 -1.3
Manufacturing............................ 6.6 194.3 -0.4 1,201 -3.7
Trade, transportation, and utilities..... 28.6 456.8 1.3 858 -3.3
Information.............................. 2.6 51.6 -0.6 1,571 0.4
Financial activities..................... 15.6 185.1 -1.6 2,013 1.0
Professional and business services....... 31.1 425.6 3.2 1,483 -6.1
Education and health services............ 15.5 408.0 1.8 961 -1.3
Leisure and hospitality.................. 13.0 232.9 3.1 459 -2.1
Other services........................... 16.2 95.4 1.8 804 -1.7
Government................................. 1.4 298.0 -0.7 1,109 -1.8
New York, NY................................. 122.0 2,387.3 2.2 1,889 -2.3
Private industry........................... 121.8 1,950.0 2.9 2,071 -2.9
Natural resources and mining............. 0.0 0.1 -13.2 1,666 -49.8
Construction............................. 2.1 30.2 -0.1 1,951 -2.7
Manufacturing............................ 2.4 25.9 -0.4 1,783 -7.9
Trade, transportation, and utilities..... 20.9 259.6 3.8 1,347 -0.4
Information.............................. 4.3 140.3 4.5 2,315 2.3
Financial activities..................... 19.0 356.4 0.9 4,092 -3.4
Professional and business services....... 25.3 481.6 3.3 2,263 -3.7
Education and health services............ 9.3 307.3 1.4 1,198 -0.7
Leisure and hospitality.................. 12.9 250.9 4.7 883 -3.9
Other services........................... 18.9 90.9 2.1 1,113 -0.6
Government................................. 0.3 437.3 -0.8 1,088 -0.5
Harris, TX................................... 102.9 2,081.7 3.1 1,239 0.2
Private industry........................... 102.3 1,827.4 4.1 1,273 0.1
Natural resources and mining............. 1.7 85.8 12.0 3,219 0.7
Construction............................. 6.5 134.6 2.2 1,235 0.7
Manufacturing............................ 4.5 183.5 7.4 1,555 -1.8
Trade, transportation, and utilities..... 23.0 446.8 3.5 1,104 0.4
Information.............................. 1.3 27.9 -1.6 1,393 -2.5
Financial activities..................... 10.6 112.8 0.4 1,548 -0.6
Professional and business services....... 20.5 341.3 5.0 1,568 -0.9
Education and health services............ 11.6 248.7 3.0 959 -1.6
Leisure and hospitality.................. 8.4 183.6 3.7 416 -1.0
Other services........................... 13.7 61.5 2.3 682 0.4
Government................................. 0.6 254.3 -3.5 996 -0.8
Maricopa, AZ................................. 96.1 1,683.7 2.5 929 -1.0
Private industry........................... 95.4 1,469.8 3.0 932 -1.0
Natural resources and mining............. 0.5 8.1 4.3 919 10.5
Construction............................. 8.4 81.8 2.5 976 -1.4
Manufacturing............................ 3.2 110.0 1.3 1,285 -3.3
Trade, transportation, and utilities..... 22.2 353.5 3.5 896 4.4
Information.............................. 1.6 27.3 1.2 1,230 -3.9
Financial activities..................... 11.2 141.5 5.4 1,122 -1.2
Professional and business services....... 22.8 277.4 2.3 1,022 -1.6
Education and health services............ 10.6 246.9 3.6 987 -4.3
Leisure and hospitality.................. 7.4 176.0 2.7 432 -2.5
Other services........................... 6.7 46.8 0.7 611 -1.9
Government................................. 0.7 213.9 -0.8 906 -1.4
Dallas, TX................................... 69.1 1,460.4 2.3 1,148 -2.0
Private industry........................... 68.6 1,297.1 3.1 1,164 -2.2
Natural resources and mining............. 0.6 9.9 10.2 4,425 7.9
Construction............................. 4.0 67.0 0.6 1,100 -2.1
Manufacturing............................ 2.8 114.9 1.1 1,324 -4.6
Trade, transportation, and utilities..... 15.0 297.7 3.4 1,012 -2.7
Information.............................. 1.6 45.9 0.9 1,605 -2.1
Financial activities..................... 8.6 141.7 3.2 1,483 -0.3
Professional and business services....... 15.2 277.9 4.1 1,384 -2.1
Education and health services............ 7.4 170.4 2.4 1,038 -4.2
Leisure and hospitality.................. 5.8 131.1 4.3 497 -3.7
Other services........................... 7.2 39.8 3.4 702 0.1
Government................................. 0.5 163.3 -4.2 1,022 -1.2
Orange, CA................................... 106.1 1,390.2 0.6 1,080 -3.1
Private industry........................... 104.7 1,254.0 1.3 1,086 -3.0
Natural resources and mining............. 0.2 3.3 -4.1 699 -3.7
Construction............................. 6.2 69.5 1.3 1,180 -4.6
Manufacturing............................ 4.8 153.8 0.6 1,291 -4.4
Trade, transportation, and utilities..... 15.9 254.7 0.5 985 -3.4
Information.............................. 1.2 23.4 -2.8 1,504 -7.3
Financial activities..................... 9.6 106.3 0.3 1,878 -0.1
Professional and business services....... 18.6 251.3 0.6 1,260 -3.5
Education and health services............ 10.4 160.6 1.9 1,034 -1.6
Leisure and hospitality.................. 7.2 175.7 3.3 413 -2.1
Other services........................... 22.4 48.3 -0.5 565 1.1
Government................................. 1.4 136.2 (6) 1,030 (6)
San Diego, CA................................ 102.3 1,264.2 1.0 1,041 -3.6
Private industry........................... 100.9 1,046.5 1.5 1,029 -3.3
Natural resources and mining............. 0.7 10.4 3.3 574 -2.2
Construction............................. 6.0 54.8 0.6 1,135 -3.2
Manufacturing............................ 2.9 93.1 -0.2 1,448 -2.0
Trade, transportation, and utilities..... 13.4 210.8 1.5 785 -3.1
Information.............................. 1.2 24.3 -2.4 1,605 0.4
Financial activities..................... 8.4 68.3 0.4 1,222 -17.5
Professional and business services....... 16.2 215.2 1.3 1,524 -1.5
Education and health services............ 8.5 149.4 2.2 1,009 -0.9
Leisure and hospitality.................. 7.0 155.6 1.5 441 -0.5
Other services........................... 29.4 57.9 (6) 519 -2.1
Government................................. 1.4 217.7 -1.6 1,095 -5.3
King, WA..................................... 82.0 1,156.6 2.4 1,220 0.3
Private industry........................... 81.4 1,000.4 2.9 1,229 0.2
Natural resources and mining............. 0.4 2.7 13.5 1,487 -1.5
Construction............................. 5.5 46.3 1.1 1,265 1.6
Manufacturing............................ 2.2 101.5 4.5 1,520 2.1
Trade, transportation, and utilities..... 14.5 217.3 3.1 1,028 0.3
Information.............................. 1.8 80.0 1.4 2,213 5.1
Financial activities..................... 6.2 64.5 -1.4 1,454 -0.5
Professional and business services....... 13.8 185.9 3.8 1,596 -2.2
Education and health services............ 7.2 137.5 3.2 989 -1.3
Leisure and hospitality.................. 6.4 111.6 4.0 477 -0.2
Other services........................... 23.5 53.0 1.4 587 -2.3
Government................................. 0.6 156.3 -0.6 1,162 0.5
Miami-Dade, FL............................... 87.8 996.2 2.2 939 -2.5
Private industry........................... 87.5 856.1 3.0 909 -2.8
Natural resources and mining............. 0.5 9.1 -1.5 594 14.2
Construction............................. 4.9 29.2 -6.0 917 -5.0
Manufacturing............................ 2.6 35.9 1.2 897 -2.6
Trade, transportation, and utilities..... 25.1 259.8 3.9 813 -4.0
Information.............................. 1.4 17.4 -0.4 1,371 -4.2
Financial activities..................... 9.0 63.3 2.9 1,385 -2.2
Professional and business services....... 18.2 131.3 3.8 1,229 -5.5
Education and health services............ 9.8 156.4 2.1 925 1.1
Leisure and hospitality.................. 6.6 115.0 3.9 536 0.2
Other services........................... 7.8 37.2 4.2 568 -3.2
Government................................. 0.4 140.1 -2.8 1,117 -0.4
(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,
fourth quarter 2011(2)
Employment Average weekly
wage(3)
Establishments,
fourth quarter
State 2011 Percent Percent
(thousands) December change, Fourth change,
2011 December quarter fourth
(thousands) 2010-11 2011 quarter
2010-11
United States(4)......... 9,178.6 131,254.2 1.4 $955 -1.7
Alabama.................. 116.7 1,828.3 0.2 832 -0.8
Alaska................... 21.8 311.3 1.6 982 -0.5
Arizona.................. 146.6 2,458.4 1.7 882 -1.1
Arkansas................. 84.8 1,157.1 0.9 736 -1.2
California............... 1,417.5 14,731.8 1.3 1,100 -2.7
Colorado................. 169.6 2,250.1 2.1 975 -2.6
Connecticut.............. 110.7 1,642.0 0.9 1,188 -3.1
Delaware................. 27.7 405.9 0.4 984 -1.6
District of Columbia..... 36.4 708.0 1.3 1,668 -1.2
Florida.................. 602.0 7,364.1 1.4 847 -2.8
Georgia.................. 268.9 3,826.9 1.0 885 -2.2
Hawaii................... 38.5 607.0 1.4 845 -1.5
Idaho.................... 54.0 606.4 0.8 717 -2.2
Illinois................. 388.2 5,635.9 1.1 1,013 -2.1
Indiana.................. 160.4 2,799.2 2.0 789 -1.9
Iowa..................... 93.9 1,464.2 1.1 793 -0.8
Kansas................... 88.4 1,320.1 0.7 800 -1.5
Kentucky................. 108.0 1,770.2 1.3 786 -1.0
Louisiana................ 124.8 1,870.8 1.0 850 -1.7
Maine.................... 49.2 580.9 0.4 755 -1.8
Maryland................. 162.2 2,516.4 1.1 1,058 -2.0
Massachusetts............ 227.5 3,230.8 1.3 1,192 -2.1
Michigan................. 242.3 3,911.8 2.4 933 -0.5
Minnesota................ 168.6 2,636.4 2.1 936 -3.9
Mississippi.............. 69.3 1,083.8 0.3 699 -1.1
Missouri................. 175.7 2,617.0 0.8 825 -1.7
Montana.................. 42.2 426.7 1.8 727 0.7
Nebraska................. 61.2 910.5 0.8 762 -1.3
Nevada................... 72.1 1,124.1 0.8 852 -3.2
New Hampshire............ 48.8 615.4 0.9 971 -0.7
New Jersey............... 264.8 3,811.6 0.6 1,138 -2.1
New Mexico............... 55.5 784.3 -0.3 799 -2.2
New York................. 599.5 8,618.4 1.4 1,197 -1.8
North Carolina........... 257.5 3,885.9 1.3 824 -2.0
North Dakota............. 28.1 397.0 7.6 871 7.7
Ohio..................... 289.3 5,027.6 1.3 855 -1.3
Oklahoma................. 103.4 1,530.0 1.3 817 2.6
Oregon................... 132.3 1,629.8 1.2 850 -0.2
Pennsylvania............. 351.0 5,595.1 0.7 936 -1.6
Rhode Island............. 35.0 451.9 0.1 919 -2.1
South Carolina........... 111.3 1,796.1 1.3 763 -1.5
South Dakota............. 31.4 397.0 1.5 724 1.4
Tennessee................ 139.6 2,654.9 2.1 858 -2.3
Texas.................... 588.0 10,607.9 2.4 973 -0.3
Utah..................... 85.5 1,202.8 2.8 806 -2.5
Vermont.................. 24.4 303.9 1.3 809 -0.5
Virginia................. 237.4 3,625.0 1.3 1,004 -2.4
Washington............... 231.9 2,843.6 1.4 979 -0.2
West Virginia............ 49.1 714.0 2.2 776 -0.3
Wisconsin................ 160.5 2,689.6 0.7 817 -2.4
Wyoming.................. 25.3 276.9 2.3 876 0.6
Puerto Rico.............. 48.2 960.9 0.1 552 -1.1
Virgin Islands........... 3.6 43.2 -4.0 772 -3.4
(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
