For release 10:00 a.m. (EST), Tuesday, January 11, 2011 USDL-11-0014
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 2010
From June 2009 to June 2010, employment declined in 192 of the 326 largest U.S.
counties according to preliminary data, the U.S. Bureau of Labor Statistics reported
today. Yolo, Calif., and Marion, Fla., posted the largest percentage decline, with a
loss of 3.7 percent each over the year, compared with a national job decrease of 0.2
percent. Within Yolo, the largest employment decline occurred in trade,
transportation, and utilities, which lost 843 jobs over the year (-4.4 percent). In
Marion, financial activities had the largest over-the-year decrease in employment,
shedding 1,495 jobs (-27.1 percent). Elkhart, Ind., experienced the largest over-
the-year percentage increase in employment among the largest counties in the U.S.
with a gain of 9.3 percent.
The U.S. average weekly wage increased over the year by 3.0 percent to $865 in the
second quarter of 2010. Among the large counties in the U.S., Santa Clara, Calif.,
had the largest over-the-year increase in average weekly wages in the second quarter
of 2010, with a gain of 10.6 percent. Within Santa Clara, manufacturing had the
largest impact on the county’s over-the-year increase in average weekly wages. Fort
Bend, Texas, experienced the largest decline in average weekly wages with a loss of
1.7 percent over the year. County employment and wage data are compiled under the
Quarterly Census of Employment and Wages (QCEW) program.
Table A. Top 10 large counties ranked by June 2010 employment, June 2009-10 employment
decrease, and June 2009-10 percent decrease in employment
--------------------------------------------------------------------------------------------------------
Employment in large counties
--------------------------------------------------------------------------------------------------------
June 2010 employment | Decrease in employment, | Percent decrease in employment,
(thousands) | June 2009-10 | June 2009-10
| (thousands) |
--------------------------------------------------------------------------------------------------------
| |
United States 129,371.6| United States -276.5| United States -0.2
--------------------------------------------------------------------------------------------------------
| |
Los Angeles, Calif. 3,890.5| Los Angeles, Calif. -62.3| Yolo, Calif. -3.7
Cook, Ill. 2,371.7| Maricopa, Ariz. -24.3| Marion, Fla. -3.7
New York, N.Y. 2,291.3| Cook, Ill. -22.7| Kane, Ill. -2.9
Harris, Texas 1,996.5| Clark, Nev. -17.5| McHenry, Ill. -2.9
Maricopa, Ariz. 1,565.2| Sacramento, Calif. -15.7| San Joaquin, Calif. -2.7
Dallas, Texas 1,415.2| Orange, Calif. -15.1| Sacramento, Calif. -2.6
Orange, Calif. 1,369.7| San Bernardino, Calif. -14.0| Durham, N.C. -2.6
San Diego, Calif. 1,253.3| Riverside, Calif. -12.8| Sedgwick, Kan. -2.5
King, Wash. 1,125.9| St. Louis, Mo. -12.3| St. Louis City, Mo. -2.5
Miami-Dade, Fla. 932.4| Alameda, Calif. -10.6| Gloucester, N.J. -2.4
| | Spokane, Wash. -2.4
| |
--------------------------------------------------------------------------------------------------------
Large County Employment
In June 2010, national employment, as measured by the QCEW program, was 129.4
million, down by 0.2 percent from June 2009. The 326 U.S. counties with 75,000 or
more employees accounted for 70.7 percent of total U.S. employment and 71.5 percent
of total wages. These 326 counties had a net job decline of 350,897 over the year,
accounting for 126.9 percent of the overall U.S. employment decrease.
Yolo, Calif., and Marion, Fla., both had the largest percentage decline in
employment among the largest U.S. counties. The top five counties with the greatest
employment level declines (Los Angeles, Calif.; Maricopa, Ariz.; Cook, Ill.; Clark,
Nev.; and Sacramento, Calif.) had a combined over-the-year loss of 142,500, or 51.1
percent of the employment decline for the U.S. (See table A.)
Employment rose in 120 of the large counties from June 2009 to June 2010. Elkhart,
Ind., had the largest over-the-year percentage increase in employment (9.3 percent)
in the nation. Manufacturing was the largest contributor to the increase in
employment. In Elkhart, employment declines exceeded 10 percent from third quarter
of 2008 through third quarter of 2009. Employment rebounded in December 2009, and
strong job growth continued through this quarter. Kings, N.Y., experienced the
second largest employment increase, followed by Allen, Ind.; Ottawa, Mich.; Macomb,
Mich.; Arlington, Va.; and Benton, Wash.
Table B. Top 10 large counties ranked by second quarter 2010 average weekly wages, second quarter 2009-10
increase in average weekly wages, and second quarter 2009-10 percent increase in average weekly wages
--------------------------------------------------------------------------------------------------------
Average weekly wage in large counties
--------------------------------------------------------------------------------------------------------
Average weekly wage, | Increase in average weekly | Percent increase in average
second quarter 2010 | wage, second quarter 2009-10 | weekly wage, second
| | quarter 2009-10
--------------------------------------------------------------------------------------------------------
| |
United States $865| United States $25| United States 3.0
--------------------------------------------------------------------------------------------------------
| |
New York, N.Y. $1,659| Santa Clara, Calif. $153| Santa Clara, Calif. 10.6
Santa Clara, Calif. 1,603| New York, N.Y. 137| New York, N.Y. 9.0
Washington, D.C. 1,506| Washington, D.C. 81| Elkhart, Ind. 7.6
Arlington, Va. 1,481| Fairfield, Conn. 79| Lake, Ind. 6.9
Fairfield, Conn. 1,395| Alexandria City, Va. 73| Rockingham, N.H. 6.4
Fairfax, Va. 1,392| Middlesex, Mass. 62| Alexandria City, Va. 6.3
San Francisco, Calif. 1,346| Durham, N.C. 61| Douglas, Colo. 6.2
Suffolk, Mass. 1,334| Arlington, Va. 59| Fairfield, Conn. 6.0
San Mateo, Calif. 1,329| Washington, Ore. 54| Champaign, Ill. 5.9
Somerset, N.J. 1,277| Douglas, Colo. 53| Butler, Pa. 5.8
| |
--------------------------------------------------------------------------------------------------------
Large County Average Weekly Wages
Average weekly wages for the nation increased by 3.0 percent over the year in the
second quarter of 2010. Among the 326 largest counties, 301 had over-the-year
increases in average weekly wages. Santa Clara, Calif., had the largest wage gain
among the largest U.S. counties. (See table B.) Of the 326 largest counties, 16
experienced declines in average weekly wages.
Fort Bend, Texas, led the nation in average weekly wage decline with a loss of 1.7
percent over the year. Large declines in employment (-10.0 percent) and wages (-14.0
percent) within construction had contributed significantly to the county’s overall
average weekly wage loss. Baltimore City, Md., had the second largest overall
decline among the counties, followed by St. Charles, Mo.; Anoka, Minn.; and
Calcasieu, La.
Ten Largest U.S. Counties
Eight of the 10 largest counties experienced over-the-year percent declines in
employment in June 2010. Los Angeles, Calif., experienced the largest decline in
employment among the 10 largest counties with a 1.6 percent decrease. Within Los
Angeles, other services had the largest over-the-year decline among all private
industry groups with a loss of 20,933 workers (-8.0 percent). (See table 2.) New
York, N.Y., experienced the largest increase in employment among the 10 largest
counties.
All of the 10 largest U.S. counties saw an over-the-year increase in average weekly
wages. New York, N.Y., experienced the largest increase in average weekly wages
among the 10 largest counties and the nation with a gain of 9.0 percent. Orange,
Calif., had the smallest wage increase among the 10 largest counties.
For More Information
The tables included in this release contain data for the nation and for the 326 U.S.
counties with annual average employment levels of 75,000 or more in 2009. June 2010
employment and 2010 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 9.0 million employer
reports cover 129.4 million full- and part- time workers. For additional information
about the quarterly employment and wages data, please read the Technical Note. Data
for the second quarter of 2010 will be available later at http://www.bls.gov/cew/.
Additional information about the QCEW data may be obtained by calling (202) 691-
6567.
Several BLS regional offices are issuing QCEW news releases targeted to local data
users. For links to these releases, see http://www.bls.gov/cew/cewregional.htm.
_____________
The County Employment and Wages release for third quarter 2010 is scheduled to be
released on Tuesday, March 29, 2011.
Technical Note
These data are the product of a federal-state cooperative program, the Quarterly
Census of Employment and Wages (QCEW) program, also known as the ES-202 program.
The data are derived from summaries of employment and total pay of workers covered
by state and federal unemployment insurance (UI) legislation and provided by State
Workforce Agencies (SWAs). The summaries are a result of the administration of
state unemployment insurance programs that require most employers to pay quarterly
taxes based on the employment and wages of workers covered by UI. QCEW data in this
release are based on the 2007 North American Industry Classification System. Data
for 2010 are preliminary and subject to revision.
For purposes of this release, large counties are defined as having employment le-
vels of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are pro-
vided, but not used in calculating U.S. averages, rankings, or in the analysis in
the text. Each year, these large counties are selected on the basis of the prelimi-
nary annual average of employment for the previous year. The 327 counties presented
in this release were derived using 2009 preliminary annual averages of employment.
For 2010 data, two counties have been added to the publication tables: St. Tammany
Parish, La., and Benton, Wash. These counties will be included in all 2010 quarter-
ly releases. Ten counties, Shelby, Ala.; Butte, Calif.; Tippecanoe, Ind.; Johnson,
Iowa; Saratoga, N.Y.; Trumbull, Ohio; Warren, Ohio; Kent, R.I.; Gregg, Texas; and
Racine, Wis., which were published in the 2009 releases, will be excluded from this
and future 2010 releases because their 2009 annual average employment levels were
less than 75,000. The counties in table 2 are selected and sorted each year based
on the annual average employment from the preceding year.
The preliminary QCEW data presented in this release may differ from data released
by the individual states. These potential differences result from the states' con-
tinuing receipt of UI data over time and ongoing review and editing. The individual
states determine their data release timetables.
Differences between QCEW, BED, and CES employment measures
The Bureau publishes three different establishment-based employment measures for
any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED),
and Current Employment Statistics (CES)--makes use of the quarterly UI employment
reports in producing data; however, each measure has a somewhat different universe
coverage, estimation procedure, and publication product.
Differences in coverage and estimation methods can result in somewhat different
measures of employment change over time. It is important to understand program dif-
ferences and the intended uses of the program products. (See table.) Additional in-
formation on each program can be obtained from the program Web sites shown in the
table.
Summary of Major Differences between QCEW, BED, and CES Employment Measures
---------------------------------------------------------------------------------
| QCEW | BED | CES
-----------|---------------------|----------------------|------------------------
Source |--Count of UI admini-|--Count of longitudi- |--Sample survey:
| strative records | nally-linked UI ad- | 400,000 establish-
| submitted by 9.0 | ministrative records| ments
| million establish- | submitted by 6.7 |
| ments in first | million private-sec-|
| quarter of 2010 | tor employers |
-----------|---------------------|----------------------|------------------------
Coverage |--UI and UCFE cover- |--UI coverage, exclud-|Nonfarm wage and sal-
| age, including all | ing government, pri-| ary jobs:
| employers subject | vate households, and|--UI coverage, exclud-
| to state and fed- | establishments with | ing agriculture, pri-
| eral UI laws | zero employment | vate households, and
| | | self-employed workers
| | |--Other employment, in-
| | | cluding railroads,
| | | religious organiza-
| | | tions, and other non-
| | | UI-covered jobs
-----------|---------------------|----------------------|------------------------
Publication|--Quarterly |--Quarterly |--Monthly
frequency | -7 months after the| -8 months after the | -Usually first Friday
| end of each quar- | end of each quarter| of following month
| ter | |
-----------|---------------------|----------------------|------------------------
Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam-
file | and publishes each | quarter to longitu- | pling frame and annu-
| new quarter of UI | dinal database and | ally realigns (bench-
| data | directly summarizes | marks) sample esti-
| | gross job gains and | mates to first quar-
| | losses | ter UI levels
-----------|---------------------|----------------------|------------------------
Principal |--Provides a quarter-|--Provides quarterly |--Provides current month-
products | ly and annual uni- | employer dynamics | ly estimates of employ-
| verse count of es- | data on establish- | ment, hours, and earn-
| tablishments, em- | ment openings, clos-| ings at the MSA, state,
| ployment, and wages| ings, expansions, | and national level by
| at the county, MSA,| and contractions at | industry
| state, and national| the national level |
| levels by detailed | by NAICS supersec- |
| industry | tors and by size of |
| | firm, and at the |
| | state private-sector|
| | total level |
| |--Future expansions |
| | will include data |
| | with greater indus- |
| | try detail and data |
| | at the county and |
| | MSA level |
-----------|---------------------|----------------------|------------------------
Principal |--Major uses include:|--Major uses include: |--Major uses include:
uses | -Detailed locality | -Business cycle | -Principal national
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -Analysis of employ-| cators
| surveys | ment expansion and |
| | contraction by size|
| | of firm |
| | |
-----------|---------------------|----------------------|------------------------
Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/
Web sites | | |
---------------------------------------------------------------------------------
Coverage
Employment and wage data for workers covered by state UI laws are compiled from
quarterly contribution reports submitted to the SWAs by employers. For federal ci-
vilian workers covered by the Unemployment Compensation for Federal Employees
(UCFE) program, employment and wage data are compiled from quarterly reports sub-
mitted by four major federal payroll processing centers on behalf of all federal
agencies, with the exception of a few agencies which still report directly to the
individual SWA. In addition to the quarterly contribution reports, employers who
operate multiple establishments within a state complete a questionnaire, called the
"Multiple Worksite Report," which provides detailed information on the location and
industry of each of their establishments. QCEW employment and wage data are derived
from microdata summaries of 9.0 million employer reports of employment and wages
submitted by states to the BLS in 2009. These reports are based on place of employ-
ment rather than place of residence.
UI and UCFE coverage is broad and has been basically comparable from state to state
since 1978, when the 1976 amendments to the Federal Unemployment Tax Act became ef-
fective, expanding coverage to include most State and local government employees.
In 2009, UI and UCFE programs covered workers in 128.6 million jobs. The estimated
123.6 million workers in these jobs (after adjustment for multiple jobholders)
represented 95.1 percent of civilian wage and salary employment. Covered workers
received $5.859 trillion in pay, representing 93.4 percent of the wage and salary
component of personal income and 41.5 percent of the gross domestic product.
Major exclusions from UI coverage include self-employed workers, most agricultural
workers on small farms, all members of the Armed Forces, elected officials in most
states, most employees of railroads, some domestic workers, most student workers at
schools, and employees of certain small nonprofit organizations.
State and federal UI laws change periodically. These changes may have an impact on
the employment and wages reported by employers covered under the UI program. Cover-
age changes may affect the over-the-year comparisons presented in this news re-
lease.
Concepts and methodology
Monthly employment is based on the number of workers who worked during or received
pay for the pay period including the 12th of the month. With few exceptions, all
employees of covered firms are reported, including production and sales workers,
corporation officials, executives, supervisory personnel, and clerical workers.
Workers on paid vacations and part-time workers also are included.
Average weekly wage values are calculated by dividing quarterly total wages by the
average of the three monthly employment levels (all employees, as described above)
and dividing the result by 13, for the 13 weeks in the quarter. These calculations
are made using unrounded employment and wage values. The average wage values that
can be calculated using rounded data from the BLS database may differ from the av-
erages reported. Included in the quarterly wage data are non-wage cash payments
such as bonuses, the cash value of meals and lodging when supplied, tips and other
gratuities, and, in some states, employer contributions to certain deferred compen-
sation plans such as 401(k) plans and stock options. Over-the-year comparisons of
average weekly wages may reflect fluctuations in average monthly employment and/or
total quarterly wages between the current quarter and prior year levels.
Average weekly wages are affected by the ratio of full-time to part-time workers as
well as the number of individuals in high-paying and low-paying occupations and the
incidence of pay periods within a quarter. For instance, the average weekly wage of
the work force could increase significantly when there is a large decline in the
number of employees that had been receiving below-average wages. Wages may include
payments to workers not present in the employment counts because they did not work
during the pay period including the 12th of the month. When comparing average week-
ly wage levels between industries, states, or quarters, these factors should be
taken into consideration.
Federal government pay levels are subject to periodic, sometimes large, fluctua-
tions due to a calendar effect that consists of some quarters having more pay pe-
riods than others. Most federal employees are paid on a biweekly pay schedule. As a
result of this schedule, in some quarters, federal wages contain payments for six
pay periods, while in other quarters their wages include payments for seven pay pe-
riods. Over-the-year comparisons of average weekly wages may reflect this calendar
effect. Higher growth in average weekly wages may be attributed, in part, to a com-
parison of quarterly wages for the current year, which include seven pay periods,
with year-ago wages that reflect only six pay periods. An opposite effect will oc-
cur when wages in the current period, which contain six pay periods, are compared
with year-ago wages that include seven pay periods. The effect on over-the-year pay
comparisons can be pronounced in federal government due to the uniform nature of
federal payroll processing. This pattern may exist in private sector pay; however,
because there are more pay period types (weekly, biweekly, semimonthly, monthly) it
is less pronounced. The effect is most visible in counties with large concentra-
tions of federal employment.
In order to ensure the highest possible quality of data, states verify with employ-
ers and update, if necessary, the industry, location, and ownership classification
of all establishments on a 4-year cycle. Changes in establishment classification
codes resulting from this process are introduced with the data reported for the
first quarter of the year. Changes resulting from improved employer reporting also
are introduced in the first quarter.
QCEW data are not designed as a time series. QCEW data are simply the sums of indi-
vidual establishment records and reflect the number of establishments that exist in
a county or industry at a point in time. Establishments can move in or out of a
county or industry for a number of reasons--some reflecting economic events, others
reflecting administrative changes. For example, economic change would come from a
firm relocating into the county; administrative change would come from a company
correcting its county designation.
The over-the-year changes of employment and wages presented in this release have
been adjusted to account for most of the administrative corrections made to the un-
derlying establishment reports. This is done by modifying the prior-year levels
used to calculate the over-the-year changes. Percent changes are calculated using
an adjusted version of the final 2009 quarterly data as the base data. The adjusted
prior-year levels used to calculate the over-the-year percent change in employment
and wages are not published. These adjusted prior-year levels do not match the un-
adjusted data maintained on the BLS Web site. Over-the-year change calculations
based on data from the Web site, or from data published in prior BLS news releases,
may differ substantially from the over-the-year changes presented in this news re-
lease.
The adjusted data used to calculate the over-the-year change measures presented in
this release account for most of the administrative changes--those occurring when
employers update the industry, location, and ownership information of their estab-
lishments. The most common adjustments for administrative change are the result of
updated information about the county location of individual establishments. In-
cluded in these adjustments are administrative changes involving the classification
of establishments that were previously reported in the unknown or statewide county
or unknown industry categories. Beginning with the first quarter of 2008, adjusted
data account for administrative changes caused by multi-unit employers who start
reporting for each individual establishment rather than as a single entity.
The adjusted data used to calculate the over-the-year change measures presented in
any County Employment and Wages news release are valid for comparisons between the
starting and ending points (a 12-month period) used in that particular release.
Comparisons may not be valid for any time period other than the one featured in a
release even if the changes were calculated using adjusted data.
County definitions are assigned according to Federal Information Processing Stan-
dards Publications (FIPS PUBS) as issued by the National Institute of Standards and
Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of
the Information Technology Management Reform Act of 1996 and the Computer Security
Act of 1987, Public Law 104-106. Areas shown as counties include those designated
as independent cities in some jurisdictions and, in Alaska, those designated as
census areas where counties have not been created. County data also are presented
for the New England states for comparative purposes even though townships are the
more common designation used in New England (and New Jersey). The regions referred
to in this release are defined as census regions.
Additional statistics and other information
An annual bulletin, Employment and Wages, features comprehensive information by de-
tailed industry on establishments, employment, and wages for the nation and all
states. The 2008 edition of this bulletin contains selected data produced by Busi-
ness Employment Dynamics (BED) on job gains and losses, as well as selected data
from the first quarter 2009 version of this news release. Tables and additional
content from the 2008 Employment and Wages Annual Bulletin are now available online
at http://www.bls.gov/cew/cewbultn08.htm. These tables present final 2008 annual
averages. The tables are included on the CD which accompanies the hardcopy version
of the Annual Bulletin. Employment and Wages Annual Averages, 2008 is available
for sale as a chartbook from the United States Government Printing Office, Superin-
tendent of Documents, P.O. Box 371954, Pittsburgh, PA 15250, telephone (866) 512-
1800, outside Washington, D.C. Within Washington, D.C., the telephone number is
(202) 512-1800. The fax number is (202) 512-2104.
News releases on quarterly measures of gross job flows also are available upon re-
quest from the Division of Administrative Statistics and Labor Turnover (Business
Employment Dynamics), telephone (202) 691-6467; (http://www.bls.gov/bdm/); (e-mail:
BDMInfo@bls.gov).
Information in this release will be made available to sensory impaired individuals
upon request. Voice phone: (202) 691-5200; TDD message referral phone number: 1-
800-877-8339.
Table 1. Covered(1) establishments, employment, and wages in the 327 largest counties,
second quarter 2010(2)
Employment Average weekly wage(4)
Establishments,
County(3) second quarter Percent Ranking Percent Ranking
2010 June change, by Average change, by
(thousands) 2010 June percent weekly second percent
(thousands) 2009-10(5) change wage quarter change
2009-10(5)
United States(6)......... 9,009.6 129,371.6 -0.2 - $865 3.0 -
Jefferson, AL............ 17.9 332.8 -1.5 262 864 2.4 160
Madison, AL.............. 8.7 180.7 0.5 82 966 3.0 110
Mobile, AL............... 9.9 168.5 1.9 17 747 1.4 250
Montgomery, AL........... 6.4 132.1 -1.7 275 759 3.7 63
Tuscaloosa, AL........... 4.3 81.2 2.8 10 742 2.6 147
Anchorage Borough, AK.... 8.1 150.1 0.7 72 971 2.1 195
Maricopa, AZ............. 94.6 1,565.2 -1.5 262 860 1.7 226
Pima, AZ................. 19.4 338.9 (7) - 765 1.9 204
Benton, AR............... 5.4 92.8 0.6 76 839 4.5 27
Pulaski, AR.............. 15.1 245.6 0.3 95 779 -0.1 302
Washington, AR........... 5.6 91.1 (7) - 725 (7) -
Alameda, CA.............. 54.3 635.1 -1.6 267 1,148 4.4 29
Contra Costa, CA......... 29.3 319.3 -2.0 285 1,061 -0.8 308
Fresno, CA............... 29.8 343.7 -0.6 167 697 1.3 252
Kern, CA................. 17.6 277.7 1.9 17 773 1.2 261
Los Angeles, CA.......... 422.4 3,890.5 -1.6 267 968 3.1 103
Marin, CA................ 11.7 102.9 0.1 112 1,059 2.9 115
Monterey, CA............. 12.7 187.1 2.3 12 741 -0.8 308
Orange, CA............... 101.7 1,369.7 -1.1 225 965 1.5 242
Placer, CA............... 10.6 126.0 -1.4 252 841 2.1 195
Riverside, CA............ 47.5 563.0 -2.2 296 729 1.7 226
Sacramento, CA........... 53.0 589.6 -2.6 310 980 3.6 70
San Bernardino, CA....... 49.2 597.3 -2.3 301 762 2.6 147
San Diego, CA............ 97.5 1,253.3 -0.5 158 934 2.3 172
San Francisco, CA........ 53.1 545.9 -0.9 202 1,346 3.2 95
San Joaquin, CA.......... 16.9 216.5 -2.7 312 752 1.8 214
San Luis Obispo, CA...... 9.5 102.0 0.6 76 731 0.8 279
San Mateo, CA............ 23.7 320.1 -0.3 144 1,329 1.5 242
Santa Barbara, CA........ 14.3 184.2 -1.0 216 818 1.1 265
Santa Clara, CA.......... 60.6 849.5 -0.5 158 1,603 10.6 1
Santa Cruz, CA........... 9.0 98.5 -2.0 285 761 1.2 261
Solano, CA............... 9.9 123.8 0.4 91 860 0.2 298
Sonoma, CA............... 18.5 176.9 -1.6 267 817 0.6 287
Stanislaus, CA........... 14.7 166.2 -0.9 202 744 2.1 195
Tulare, CA............... 9.3 151.8 -1.0 216 606 1.3 252
Ventura, CA.............. 23.6 302.7 -1.4 252 897 1.7 226
Yolo, CA................. 5.9 96.1 -3.7 315 816 -0.9 310
Adams, CO................ 9.0 151.2 -1.2 234 785 2.7 138
Arapahoe, CO............. 18.9 273.6 -0.9 202 980 1.0 269
Boulder, CO.............. 12.9 153.6 0.3 95 1,007 4.0 46
Denver, CO............... 25.3 421.7 -0.2 132 1,033 2.4 160
Douglas, CO.............. 9.4 92.1 -0.7 182 906 6.2 7
El Paso, CO.............. 16.8 235.2 -0.8 196 800 1.7 226
Jefferson, CO............ 18.0 205.9 -0.6 167 882 2.9 115
Larimer, CO.............. 10.1 129.5 0.4 91 742 2.5 154
Weld, CO................. 5.8 79.0 -0.9 202 712 3.8 53
Fairfield, CT............ 32.7 403.7 -0.2 132 1,395 6.0 8
Hartford, CT............. 25.2 487.9 -1.0 216 1,058 4.2 40
New Haven, CT............ 22.3 350.2 -0.8 196 926 2.4 160
New London, CT........... 6.9 126.3 -1.4 252 895 1.6 235
New Castle, DE........... 17.6 262.9 -1.9 283 985 2.6 147
Washington, DC........... 34.2 701.4 2.3 12 1,506 5.7 11
Alachua, FL.............. 6.7 115.4 -0.6 167 738 3.7 63
Brevard, FL.............. 14.7 189.9 -0.7 182 833 1.6 235
Broward, FL.............. 63.3 678.6 -1.2 234 816 1.5 242
Collier, FL.............. 11.9 104.7 -0.3 144 789 2.7 138
Duval, FL................ 26.8 430.4 -0.7 182 834 2.2 182
Escambia, FL............. 7.9 119.1 1.1 46 695 1.2 261
Hillsborough, FL......... 37.1 558.1 -1.2 234 840 2.3 172
Lake, FL................. 7.3 74.7 -2.3 301 616 1.0 269
Lee, FL.................. 18.9 186.9 -1.2 234 727 1.0 269
Leon, FL................. 8.2 136.1 -1.1 225 732 1.1 265
Manatee, FL.............. 9.1 105.5 -1.5 262 679 1.8 214
Marion, FL............... 8.1 88.9 -3.7 315 648 3.8 53
Miami-Dade, FL........... 85.9 932.4 -0.2 132 850 1.9 204
Okaloosa, FL............. 6.1 75.1 -1.7 275 741 1.8 214
Orange, FL............... 35.4 642.2 0.5 82 776 1.3 252
Palm Beach, FL........... 49.2 485.8 -0.8 196 858 2.5 154
Pasco, FL................ 9.9 89.1 -0.6 167 666 (7) -
Pinellas, FL............. 30.7 382.5 -1.6 267 766 3.4 85
Polk, FL................. 12.4 184.5 -1.8 278 674 1.5 242
Sarasota, FL............. 14.6 130.2 -0.9 202 728 0.1 299
Seminole, FL............. 14.1 155.7 -2.2 296 739 0.8 279
Volusia, FL.............. 13.5 145.1 -2.2 296 651 2.4 160
Bibb, GA................. 4.6 79.4 -1.3 243 679 2.1 195
Chatham, GA.............. 7.6 128.1 -1.1 225 747 2.8 126
Clayton, GA.............. 4.3 102.2 (7) - 773 (7) -
Cobb, GA................. 20.5 287.0 -0.7 182 894 2.4 160
De Kalb, GA.............. 17.5 275.7 -1.3 243 899 0.7 284
Fulton, GA............... 39.4 700.8 -0.7 182 1,122 2.6 147
Gwinnett, GA............. 23.4 295.7 -0.9 202 853 3.5 78
Muscogee, GA............. 4.7 93.1 (7) - 690 2.4 160
Richmond, GA............. 4.7 97.1 -1.0 216 736 1.8 214
Honolulu, HI............. 24.8 428.2 -1.7 275 809 1.0 269
Ada, ID.................. 14.2 193.6 -0.9 202 755 2.7 138
Champaign, IL............ 4.2 88.9 0.3 95 785 5.9 9
Cook, IL................. 142.8 2,371.7 -0.9 202 1,012 2.4 160
Du Page, IL.............. 36.3 552.9 -0.1 125 988 2.7 138
Kane, IL................. 13.0 193.9 -2.9 313 776 2.9 115
Lake, IL................. 21.4 317.8 -1.4 252 1,081 3.6 70
McHenry, IL.............. 8.5 95.7 -2.9 313 733 3.8 53
McLean, IL............... 3.8 86.0 0.8 67 855 2.9 115
Madison, IL.............. 6.0 93.5 1.8 22 724 4.2 40
Peoria, IL............... 4.7 99.9 0.5 82 804 2.7 138
Rock Island, IL.......... 3.5 74.2 -2.3 301 845 2.8 126
St. Clair, IL............ 5.5 93.2 -1.8 278 728 1.5 242
Sangamon, IL............. 5.3 128.1 -0.1 125 886 2.8 126
Will, IL................. 14.4 197.4 0.1 112 781 4.3 34
Winnebago, IL............ 6.9 124.5 -1.3 243 732 3.7 63
Allen, IN................ 8.9 172.2 3.5 3 732 4.3 34
Elkhart, IN.............. 4.8 102.3 9.3 1 737 7.6 3
Hamilton, IN............. 7.9 109.1 -0.5 158 816 3.2 95
Lake, IN................. 10.3 184.3 -0.7 182 771 6.9 4
Marion, IN............... 23.6 547.7 0.5 82 870 2.2 182
St. Joseph, IN........... 6.0 114.0 -0.3 144 721 1.3 252
Vanderburgh, IN.......... 4.8 104.7 1.0 53 731 3.8 53
Linn, IA................. 6.3 124.8 -0.6 167 829 4.5 27
Polk, IA................. 14.7 268.5 -1.6 267 850 3.2 95
Scott, IA................ 5.3 86.0 0.6 76 688 3.0 110
Johnson, KS.............. 20.9 297.8 -2.0 285 889 2.2 182
Sedgwick, KS............. 12.5 241.4 -2.5 308 791 0.1 299
Shawnee, KS.............. 4.9 94.7 -0.6 167 757 3.1 103
Wyandotte, KS............ 3.2 81.2 2.6 11 831 2.2 182
Fayette, KY.............. 9.5 172.3 1.0 53 798 1.8 214
Jefferson, KY............ 22.4 413.0 -0.2 132 852 3.4 85
Caddo, LA................ 7.6 123.6 1.6 30 743 3.2 95
Calcasieu, LA............ 5.1 83.8 -2.0 285 715 -1.0 313
East Baton Rouge, LA..... 15.0 252.3 -1.4 252 803 -0.4 305
Jefferson, LA............ 14.4 194.6 -0.4 151 803 2.8 126
Lafayette, LA............ 9.3 131.6 0.3 95 819 3.7 63
Orleans, LA.............. 11.0 170.8 0.9 61 920 0.9 275
St. Tammany, LA.......... 7.6 75.8 (7) - 731 (7) -
Cumberland, ME........... 12.2 169.0 -1.1 225 779 3.2 95
Anne Arundel, MD......... 14.3 230.8 0.3 95 946 (7) -
Baltimore, MD............ 21.1 368.0 -0.4 151 894 2.4 160
Frederick, MD............ 5.9 93.3 -0.4 151 851 2.9 115
Harford, MD.............. 5.6 82.3 1.2 42 816 3.2 95
Howard, MD............... 8.7 149.7 1.4 34 1,027 1.7 226
Montgomery, MD........... 32.3 448.3 -0.1 125 1,173 3.8 53
Prince Georges, MD....... 15.5 303.3 -1.6 267 959 2.9 115
Baltimore City, MD....... 13.5 328.7 -0.5 158 999 -1.6 316
Barnstable, MA........... 9.2 96.7 -1.2 234 738 1.5 242
Bristol, MA.............. 15.9 210.7 -0.2 132 796 2.4 160
Essex, MA................ 21.2 300.2 1.2 42 923 3.6 70
Hampden, MA.............. 14.8 196.2 0.5 82 779 0.3 292
Middlesex, MA............ 48.4 812.4 0.5 82 1,252 5.2 17
Norfolk, MA.............. 24.0 317.0 0.5 82 1,022 3.0 110
Plymouth, MA............. 14.0 174.0 -0.7 182 850 1.0 269
Suffolk, MA.............. 22.6 574.4 0.6 76 1,334 1.8 214
Worcester, MA............ 21.0 313.5 0.4 91 886 3.1 103
Genesee, MI.............. 7.5 127.8 0.7 72 728 1.1 265
Ingham, MI............... 6.5 154.4 0.9 61 854 3.5 78
Kalamazoo, MI............ 5.4 108.1 -2.0 285 785 2.7 138
Kent, MI................. 14.0 309.9 1.0 53 773 0.8 279
Macomb, MI............... 17.2 280.6 3.0 5 866 2.2 182
Oakland, MI.............. 37.8 618.1 -0.8 196 953 -0.2 304
Ottawa, MI............... 5.6 102.2 3.5 3 712 3.8 53
Saginaw, MI.............. 4.2 79.9 1.8 22 725 0.3 292
Washtenaw, MI............ 8.0 184.1 1.7 25 910 1.6 235
Wayne, MI................ 31.3 665.0 0.9 61 944 2.2 182
Anoka, MN................ 7.4 106.9 -2.3 301 827 -1.1 314
Dakota, MN............... 10.0 171.0 0.2 107 860 1.3 252
Hennepin, MN............. 44.3 812.2 0.3 95 1,073 4.4 29
Olmsted, MN.............. 3.4 88.3 -1.4 252 988 3.6 70
Ramsey, MN............... 14.4 318.0 -0.7 182 957 2.9 115
St. Louis, MN............ 5.7 94.4 0.0 121 725 4.9 22
Stearns, MN.............. 4.4 77.8 -0.5 158 683 4.1 44
Harrison, MS............. 4.5 83.3 -0.2 132 663 -0.6 306
Hinds, MS................ 6.2 123.0 -1.8 278 762 2.6 147
Boone, MO................ 4.4 82.5 1.3 38 682 0.6 287
Clay, MO................. 5.0 91.2 -1.9 283 828 2.3 172
Greene, MO............... 8.0 147.0 -1.3 243 672 0.7 284
Jackson, MO.............. 18.0 342.8 -2.3 301 872 0.7 284
St. Charles, MO.......... 8.1 122.5 0.0 121 708 -1.5 315
St. Louis, MO............ 31.6 569.1 -2.1 294 911 1.9 204
St. Louis City, MO....... 8.7 213.2 -2.5 308 921 (7) -
Yellowstone, MT.......... 5.8 76.4 -1.1 225 714 3.6 70
Douglas, NE.............. 15.7 313.6 0.1 112 796 1.8 214
Lancaster, NE............ 8.1 153.5 -0.7 182 702 3.5 78
Clark, NV................ 48.0 804.1 -2.1 294 786 -0.9 310
Washoe, NV............... 13.9 184.5 -2.0 285 800 0.4 290
Hillsborough, NH......... 11.9 185.4 -1.5 262 961 5.4 15
Rockingham, NH........... 10.6 136.3 1.0 53 861 6.4 5
Atlantic, NJ............. 6.9 143.3 1.2 42 769 1.9 204
Bergen, NJ............... 33.9 431.3 -0.9 202 1,050 1.9 204
Burlington, NJ........... 11.2 197.0 -1.8 278 925 3.4 85
Camden, NJ............... 12.8 198.6 -0.5 158 880 2.1 195
Essex, NJ................ 21.1 342.0 -0.7 182 1,083 2.2 182
Gloucester, NJ........... 6.3 99.9 -2.4 306 806 3.7 63
Hudson, NJ............... 13.9 229.7 -1.0 216 1,198 3.6 70
Mercer, NJ............... 11.1 229.7 0.5 82 1,134 3.0 110
Middlesex, NJ............ 21.9 380.8 -0.7 182 1,065 2.2 182
Monmouth, NJ............. 20.4 254.4 -0.9 202 902 1.6 235
Morris, NJ............... 17.7 274.8 -1.4 252 1,230 3.4 85
Ocean, NJ................ 12.3 155.9 0.7 72 720 0.8 279
Passaic, NJ.............. 12.3 172.4 1.9 17 917 1.9 204
Somerset, NJ............. 10.1 170.2 0.1 112 1,277 2.8 126
Union, NJ................ 14.8 222.9 1.0 53 1,101 4.0 46
Bernalillo, NM........... 17.5 313.7 -1.1 225 780 1.8 214
Albany, NY............... 9.9 220.5 -1.1 225 912 0.6 287
Bronx, NY................ 16.8 237.1 1.9 17 842 1.4 250
Broome, NY............... 4.5 92.7 -1.8 278 709 2.6 147
Dutchess, NY............. 8.1 112.4 -0.6 167 916 2.0 202
Erie, NY................. 23.6 453.3 0.3 95 765 2.3 172
Kings, NY................ 49.4 499.6 3.6 2 739 0.4 290
Monroe, NY............... 18.0 373.9 0.2 107 850 2.3 172
Nassau, NY............... 52.3 596.9 -0.2 132 1,010 2.5 154
New York, NY............. 120.6 2,291.3 0.3 95 1,659 9.0 2
Oneida, NY............... 5.3 110.3 0.2 107 695 1.8 214
Onondaga, NY............. 12.8 244.1 -1.0 216 817 3.3 90
Orange, NY............... 10.0 132.2 1.1 46 784 1.3 252
Queens, NY............... 44.8 498.8 1.1 46 837 1.9 204
Richmond, NY............. 8.9 95.0 1.6 30 759 1.6 235
Rockland, NY............. 9.9 115.4 0.1 112 946 2.2 182
Suffolk, NY.............. 50.3 625.9 0.5 82 966 4.4 29
Westchester, NY.......... 36.1 408.8 -0.6 167 1,161 3.8 53
Buncombe, NC............. 7.8 110.6 1.7 25 678 2.9 115
Catawba, NC.............. 4.4 77.7 1.0 53 669 4.4 29
Cumberland, NC........... 6.2 118.6 -0.4 151 720 3.7 63
Durham, NC............... 7.1 177.0 -2.6 310 1,155 5.6 14
Forsyth, NC.............. 9.0 173.2 -1.3 243 797 3.6 70
Guilford, NC............. 14.2 255.8 -0.8 196 769 3.1 103
Mecklenburg, NC.......... 32.1 531.5 -0.2 132 984 4.7 23
New Hanover, NC.......... 7.2 95.3 -2.2 296 718 2.9 115
Wake, NC................. 28.4 436.1 0.8 67 873 5.1 19
Cass, ND................. 5.8 100.4 0.9 61 737 3.8 53
Butler, OH............... 7.2 137.9 0.8 67 767 4.6 25
Cuyahoga, OH............. 35.7 690.9 -0.6 167 882 3.8 53
Franklin, OH............. 28.9 649.5 -0.4 151 848 3.7 63
Hamilton, OH............. 23.1 488.3 -1.2 234 923 2.8 126
Lake, OH................. 6.4 94.4 -0.8 196 721 2.6 147
Lorain, OH............... 6.1 93.4 -1.1 225 698 3.9 50
Lucas, OH................ 10.3 199.2 1.3 38 743 2.2 182
Mahoning, OH............. 6.0 96.7 -0.3 144 631 2.4 160
Montgomery, OH........... 12.2 241.4 -0.5 158 772 1.8 214
Stark, OH................ 8.7 149.3 -1.6 267 664 2.2 182
Summit, OH............... 14.3 254.4 -0.5 158 773 1.0 269
Oklahoma, OK............. 24.2 412.1 0.2 107 789 2.3 172
Tulsa, OK................ 20.1 329.1 -2.0 285 783 2.5 154
Clackamas, OR............ 12.4 138.9 -1.3 243 799 2.8 126
Jackson, OR.............. 6.5 76.1 -1.6 267 670 1.8 214
Lane, OR................. 10.7 137.3 0.1 112 685 1.3 252
Marion, OR............... 9.3 136.0 -0.6 167 698 0.3 292
Multnomah, OR............ 28.4 422.8 -0.1 125 885 1.7 226
Washington, OR........... 16.0 236.6 0.3 95 994 5.7 11
Allegheny, PA............ 34.9 679.9 0.3 95 919 3.5 78
Berks, PA................ 9.0 163.0 1.3 38 786 0.3 292
Bucks, PA................ 19.6 255.0 0.4 91 839 0.1 299
Butler, PA............... 4.8 81.5 2.9 8 767 5.8 10
Chester, PA.............. 14.9 237.6 -0.4 151 1,131 1.8 214
Cumberland, PA........... 6.0 120.6 -0.7 182 807 1.3 252
Dauphin, PA.............. 7.4 180.0 -1.2 234 853 3.3 90
Delaware, PA............. 13.5 205.8 0.7 72 917 2.9 115
Erie, PA................. 7.5 123.4 1.1 46 671 0.3 292
Lackawanna, PA........... 5.8 98.0 -0.9 202 672 2.1 195
Lancaster, PA............ 12.4 220.7 -0.2 132 725 2.8 126
Lehigh, PA............... 8.6 173.1 0.6 76 823 -0.1 302
Luzerne, PA.............. 7.7 137.9 -0.7 182 680 2.4 160
Montgomery, PA........... 27.1 466.5 -1.0 216 1,068 2.8 126
Northampton, PA.......... 6.4 98.7 0.8 67 758 1.7 226
Philadelphia, PA......... 32.5 628.6 1.2 42 1,007 0.8 279
Washington, PA........... 5.5 81.1 1.4 34 777 5.0 21
Westmoreland, PA......... 9.3 134.3 0.0 121 694 3.0 110
York, PA................. 9.0 169.3 0.0 121 773 3.8 53
Providence, RI........... 17.4 269.2 -0.4 151 853 2.2 182
Charleston, SC........... 11.6 206.5 -0.2 132 768 4.6 25
Greenville, SC........... 12.0 226.4 1.7 25 758 2.8 126
Horry, SC................ 7.7 114.4 -1.3 243 546 5.2 17
Lexington, SC............ 5.6 94.0 -1.3 243 647 3.5 78
Richland, SC............. 9.0 202.8 -0.6 167 763 1.1 265
Spartanburg, SC.......... 6.0 109.4 -1.1 225 764 4.2 40
Minnehaha, SD............ 6.5 114.1 -0.5 158 704 2.3 172
Davidson, TN............. 18.1 419.4 (7) - 873 3.6 70
Hamilton, TN............. 8.4 179.2 0.3 95 761 5.1 19
Knox, TN................. 10.8 216.4 -0.3 144 735 2.7 138
Rutherford, TN........... 4.3 94.2 (7) - 806 (7) -
Shelby, TN............... 19.1 466.3 -1.4 252 895 4.3 34
Williamson, TN........... 6.1 89.1 (7) - 942 3.9 50
Bell, TX................. 4.7 107.1 (7) - 714 (7) -
Bexar, TX................ 33.3 727.4 1.0 53 772 3.2 95
Brazoria, TX............. 4.8 86.7 1.8 22 831 4.3 34
Brazos, TX............... 3.8 86.0 0.8 67 652 1.6 235
Cameron, TX.............. 6.3 125.0 1.4 34 562 3.3 90
Collin, TX............... 17.8 287.7 1.7 25 997 2.0 202
Dallas, TX............... 67.5 1,415.2 0.2 107 1,030 2.3 172
Denton, TX............... 10.9 173.1 1.9 17 756 1.6 235
El Paso, TX.............. 13.6 271.9 2.2 14 633 4.3 34
Fort Bend, TX............ 9.0 133.2 1.0 53 855 -1.7 317
Galveston, TX............ 5.2 95.9 2.9 8 791 -0.9 310
Harris, TX............... 99.7 1,996.5 -0.3 144 1,065 2.3 172
Hidalgo, TX.............. 10.8 220.5 2.0 15 563 3.3 90
Jefferson, TX............ 5.9 119.5 1.1 46 838 1.3 252
Lubbock, TX.............. 6.9 122.7 0.3 95 672 4.0 46
McLennan, TX............. 4.8 101.7 (7) - 704 (7) -
Montgomery, TX........... 8.5 128.7 1.6 30 782 2.4 160
Nueces, TX............... 7.9 152.9 1.7 25 732 2.7 138
Potter, TX............... 3.8 73.9 -1.2 234 752 4.3 34
Smith, TX................ 5.3 92.3 0.9 61 742 3.5 78
Tarrant, TX.............. 37.2 747.5 0.1 112 873 4.4 29
Travis, TX............... 29.7 569.7 1.4 34 954 3.9 50
Webb, TX................. 4.7 85.2 0.9 61 590 5.7 11
Williamson, TX........... 7.4 122.6 1.1 46 824 4.2 40
Davis, UT................ 7.0 102.9 1.1 46 714 1.9 204
Salt Lake, UT............ 36.4 558.0 -0.2 132 810 1.5 242
Utah, UT................. 12.6 164.9 -0.1 125 679 -0.6 306
Weber, UT................ 5.5 89.6 -0.7 182 662 2.3 172
Chittenden, VT........... 5.9 91.9 -1.0 216 875 4.7 23
Arlington, VA............ 8.0 164.2 3.0 5 1,481 4.1 44
Chesterfield, VA......... 7.6 115.4 -0.9 202 798 4.0 46
Fairfax, VA.............. 34.0 580.3 0.6 76 1,392 3.2 95
Henrico, VA.............. 9.6 172.4 -0.1 125 873 1.7 226
Loudoun, VA.............. 9.2 134.9 2.0 15 1,054 3.3 90
Prince William, VA....... 7.4 106.2 1.5 33 796 3.1 103
Alexandria City, VA...... 6.1 97.1 -0.9 202 1,237 6.3 6
Chesapeake City, VA...... 5.7 95.7 -0.1 125 705 3.4 85
Newport News City, VA.... 3.9 96.3 0.1 112 811 1.9 204
Norfolk City, VA......... 5.7 136.6 -2.2 296 873 3.1 103
Richmond City, VA........ 7.2 149.0 -0.6 167 962 0.3 292
Virginia Beach City, VA.. 11.3 169.2 -0.6 167 696 2.8 126
Benton, WA............... 5.5 84.0 3.0 5 909 2.5 154
Clark, WA................ 13.0 128.2 -0.2 132 785 0.9 275
King, WA................. 80.6 1,125.9 -0.9 202 1,101 2.1 195
Kitsap, WA............... 6.6 81.8 -0.6 167 842 2.9 115
Pierce, WA............... 21.4 263.3 -1.2 234 809 2.7 138
Snohomish, WA............ 18.7 240.0 -2.0 285 923 2.8 126
Spokane, WA.............. 15.9 199.2 -2.4 306 732 1.9 204
Thurston, WA............. 7.3 97.5 -1.3 243 807 1.5 242
Whatcom, WA.............. 6.9 78.8 -1.4 252 706 0.9 275
Yakima, WA............... 8.8 106.5 -1.0 216 597 1.2 261
Kanawha, WV.............. 6.0 106.5 -0.6 167 773 0.9 275
Brown, WI................ 6.5 145.9 0.1 112 742 2.5 154
Dane, WI................. 13.7 297.5 -0.3 144 833 1.7 226
Milwaukee, WI............ 20.9 467.5 -1.4 252 866 2.2 182
Outagamie, WI............ 5.0 100.9 -1.5 262 725 3.1 103
Waukesha, WI............. 12.6 220.8 -2.0 285 852 3.5 78
Winnebago, WI............ 3.7 90.0 1.3 38 798 5.4 15
San Juan, PR............. 11.7 261.8 -3.8 (8) 592 1.5 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 326 U.S. counties comprise 70.7 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,
second quarter 2010(2)
Employment Average weekly
wage(3)
Establishments,
second quarter
County by NAICS supersector 2010 Percent Percent
(thousands) June change, Average change,
2010 June weekly second
(thousands) 2009-10(4) wage quarter
2009-10(4)
United States(5)............................. 9,009.6 129,371.6 -0.2 $865 3.0
Private industry........................... 8,711.9 107,283.2 -0.5 849 3.3
Natural resources and mining............. 126.3 1,940.2 1.5 882 4.1
Construction............................. 801.1 5,657.4 -7.5 910 0.6
Manufacturing............................ 344.4 11,549.2 -1.6 1,063 5.8
Trade, transportation, and utilities..... 1,876.4 24,488.7 -0.7 733 3.2
Information.............................. 144.2 2,723.8 -3.7 1,324 4.1
Financial activities..................... 821.2 7,440.9 -2.6 1,259 6.2
Professional and business services....... 1,538.5 16,801.1 2.0 1,088 2.7
Education and health services............ 887.5 18,589.5 1.7 817 1.6
Leisure and hospitality.................. 745.0 13,518.8 -0.2 359 3.2
Other services........................... 1,246.0 4,404.9 -0.7 553 1.8
Government................................. 297.7 22,088.4 1.1 941 2.0
Los Angeles, CA.............................. 422.4 3,890.5 -1.6 968 3.1
Private industry........................... 416.8 3,298.4 -1.5 935 2.9
Natural resources and mining............. 0.5 10.8 3.3 1,107 8.2
Construction............................. 13.0 105.6 -11.7 989 -1.2
Manufacturing............................ 13.5 376.7 -3.9 1,063 3.9
Trade, transportation, and utilities..... 52.0 730.8 -0.4 781 3.4
Information.............................. 8.4 189.5 -1.0 1,667 2.3
Financial activities..................... 22.3 210.1 -2.5 1,417 2.7
Professional and business services....... 41.6 528.2 -0.4 1,144 1.6
Education and health services............ 28.7 505.0 2.0 897 2.3
Leisure and hospitality.................. 26.8 390.8 -0.8 529 2.1
Other services........................... 194.9 240.4 -8.0 458 8.3
Government................................. 5.6 592.0 -1.9 1,154 (6)
Cook, IL..................................... 142.8 2,371.7 -0.9 1,012 2.4
Private industry........................... 141.4 2,057.3 -1.1 996 2.5
Natural resources and mining............. 0.1 0.9 -11.7 952 7.1
Construction............................. 12.2 67.1 -11.1 1,200 -0.2
Manufacturing............................ 6.7 193.4 -2.9 1,048 7.0
Trade, transportation, and utilities..... 27.7 429.8 -0.9 783 2.4
Information.............................. 2.6 51.5 -3.7 1,418 1.4
Financial activities..................... 15.5 190.0 -3.3 1,714 4.8
Professional and business services....... 30.0 404.1 0.9 1,277 1.5
Education and health services............ 14.8 390.5 1.3 861 1.2
Leisure and hospitality.................. 12.3 232.3 -1.1 449 4.7
Other services........................... 15.3 94.4 -2.8 739 1.4
Government................................. 1.4 314.3 0.0 1,118 2.6
New York, NY................................. 120.6 2,291.3 0.3 1,659 9.0
Private industry........................... 120.3 1,840.6 0.3 1,799 10.2
Natural resources and mining............. 0.0 0.1 -11.3 1,926 -24.3
Construction............................. 2.3 30.0 -12.7 1,523 1.6
Manufacturing............................ 2.6 26.7 -5.0 1,227 0.8
Trade, transportation, and utilities..... 21.1 234.4 1.9 1,173 4.5
Information.............................. 4.4 129.5 -2.7 2,011 3.3
Financial activities..................... 19.0 347.3 -0.2 3,611 25.8
Professional and business services....... 25.6 461.2 -0.3 1,887 4.5
Education and health services............ 9.1 294.0 1.3 1,097 2.7
Leisure and hospitality.................. 12.3 223.4 2.7 755 4.0
Other services........................... 18.5 87.6 -0.4 957 0.0
Government................................. 0.3 450.6 0.2 1,090 1.3
Harris, TX................................... 99.7 1,996.5 -0.3 1,065 2.3
Private industry........................... 99.1 1,729.1 -0.9 1,084 2.7
Natural resources and mining............. 1.6 74.7 3.1 2,732 2.2
Construction............................. 6.5 132.1 -7.8 1,056 -0.2
Manufacturing............................ 4.5 168.0 -3.0 1,323 5.8
Trade, transportation, and utilities..... 22.5 414.3 -1.0 957 1.7
Information.............................. 1.3 28.8 -4.7 1,214 1.0
Financial activities..................... 10.5 112.2 -3.1 1,295 7.1
Professional and business services....... 19.8 319.5 0.4 1,301 4.2
Education and health services............ 10.9 236.7 3.7 883 0.5
Leisure and hospitality.................. 8.0 181.3 -1.6 390 2.6
Other services........................... 13.1 60.3 0.8 614 -0.5
Government................................. 0.5 267.4 3.8 943 -0.6
Maricopa, AZ................................. 94.6 1,565.2 -1.5 860 1.7
Private industry........................... 93.9 1,385.9 -1.7 842 1.8
Natural resources and mining............. 0.5 7.6 -11.8 739 9.8
Construction............................. 9.0 81.2 -15.7 877 0.6
Manufacturing............................ 3.3 107.2 -4.2 1,264 8.0
Trade, transportation, and utilities..... 21.9 331.8 -1.1 794 2.5
Information.............................. 1.5 27.5 0.3 1,061 1.8
Financial activities..................... 11.4 132.0 -3.1 1,038 2.4
Professional and business services....... 21.8 260.7 -0.1 881 -0.1
Education and health services............ 10.3 223.5 3.6 901 -0.2
Leisure and hospitality.................. 6.8 167.1 -1.8 406 2.3
Other services........................... 6.8 46.8 0.3 570 0.5
Government................................. 0.7 179.3 -0.1 981 0.2
Dallas, TX................................... 67.5 1,415.2 0.2 1,030 2.3
Private industry........................... 67.0 1,243.0 -0.4 1,036 2.4
Natural resources and mining............. 0.6 8.4 8.3 3,107 9.8
Construction............................. 4.1 67.5 -10.2 926 2.1
Manufacturing............................ 2.9 113.7 -4.8 1,211 4.8
Trade, transportation, and utilities..... 14.8 279.4 -0.4 953 2.9
Information.............................. 1.6 45.6 -2.0 1,500 3.2
Financial activities..................... 8.5 136.5 -2.1 1,344 4.4
Professional and business services....... 14.7 257.2 1.5 1,165 2.3
Education and health services............ 6.9 164.0 4.7 978 -0.3
Leisure and hospitality.................. 5.4 131.2 0.9 444 -5.1
Other services........................... 7.0 38.8 0.1 641 0.2
Government................................. 0.5 172.2 4.4 988 1.8
Orange, CA................................... 101.7 1,369.7 -1.1 965 1.5
Private industry........................... 100.3 1,217.7 -1.0 949 1.9
Natural resources and mining............. 0.2 4.8 7.6 570 -4.4
Construction............................. 6.4 68.2 -9.1 1,037 -3.9
Manufacturing............................ 5.0 152.8 -2.0 1,166 4.4
Trade, transportation, and utilities..... 16.4 242.5 -1.4 914 2.6
Information.............................. 1.3 25.4 -6.9 1,353 4.6
Financial activities..................... 9.7 103.1 -2.7 1,375 3.9
Professional and business services....... 18.7 243.7 0.6 1,103 1.3
Education and health services............ 10.3 154.0 1.9 878 1.5
Leisure and hospitality.................. 7.1 170.9 0.0 419 2.9
Other services........................... 20.2 48.7 0.4 527 1.0
Government................................. 1.4 152.0 -2.2 1,100 -0.5
San Diego, CA................................ 97.5 1,253.3 -0.5 934 2.3
Private industry........................... 96.2 1,020.5 -0.8 903 2.8
Natural resources and mining............. 0.7 10.6 1.2 573 2.1
Construction............................. 6.4 56.2 -9.2 995 0.0
Manufacturing............................ 3.0 93.2 -2.3 1,313 5.1
Trade, transportation, and utilities..... 13.6 195.9 -1.0 746 3.5
Information.............................. 1.2 25.4 -4.1 1,363 3.4
Financial activities..................... 8.7 67.1 -3.1 1,101 3.3
Professional and business services....... 16.0 208.4 -0.3 1,254 3.6
Education and health services............ 8.4 144.4 2.5 875 2.1
Leisure and hospitality.................. 7.0 157.6 0.4 398 2.6
Other services........................... 26.7 58.4 0.3 494 3.8
Government................................. 1.4 232.8 (6) 1,069 (6)
King, WA..................................... 80.6 1,125.9 -0.9 1,101 2.1
Private industry........................... 80.1 963.6 -1.2 1,100 1.8
Natural resources and mining............. 0.4 2.8 -3.2 1,214 5.6
Construction............................. 5.9 47.4 -15.0 1,098 -0.5
Manufacturing............................ 2.3 97.4 -3.9 1,418 2.8
Trade, transportation, and utilities..... 14.5 203.8 -0.3 950 2.9
Information.............................. 1.7 79.5 -0.9 1,991 3.4
Financial activities..................... 6.6 64.5 -7.0 1,283 -2.4
Professional and business services....... 13.8 175.1 1.0 1,327 3.4
Education and health services............ 6.9 131.2 0.1 913 3.5
Leisure and hospitality.................. 6.3 110.4 0.1 432 1.2
Other services........................... 21.7 51.4 10.1 596 -2.3
Government................................. 0.5 162.3 1.1 1,107 4.8
Miami-Dade, FL............................... 85.9 932.4 -0.2 850 1.9
Private industry........................... 85.6 800.2 -0.2 814 1.4
Natural resources and mining............. 0.5 7.0 -6.2 513 8.9
Construction............................. 5.5 31.2 -13.7 876 0.9
Manufacturing............................ 2.6 35.0 -6.7 777 4.4
Trade, transportation, and utilities..... 24.1 236.9 1.2 764 0.5
Information.............................. 1.5 17.3 (6) 1,328 (6)
Financial activities..................... 9.3 60.7 -2.2 1,222 6.0
Professional and business services....... 18.1 121.2 -1.6 993 1.6
Education and health services............ 9.7 149.9 3.1 835 0.1
Leisure and hospitality.................. 6.4 105.7 3.0 486 2.3
Other services........................... 7.7 35.1 -0.1 544 0.7
Government................................. 0.4 132.2 -0.2 1,051 4.1
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs.
(2) Data are preliminary.
(3) Average weekly wages were calculated using unrounded data.
(4) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(5) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(6) Data do not meet BLS or State agency disclosure standards.
Table 3. Covered(1) establishments, employment, and wages by state,
second quarter 2010(2)
Employment Average weekly
wage(3)
Establishments,
second quarter
State 2010 Percent Percent
(thousands) June change, Average change,
2010 June weekly second
(thousands) 2009-10 wage quarter
2009-10
United States(4)......... 9,009.6 129,371.6 -0.2 $865 3.0
Alabama.................. 116.6 1,831.3 -0.4 750 2.3
Alaska................... 21.3 330.6 1.2 916 2.7
Arizona.................. 147.2 2,308.7 -1.1 821 1.7
Arkansas................. 85.8 1,153.7 1.2 684 2.5
California............... 1,327.9 14,651.5 -1.0 978 3.2
Colorado................. 172.2 2,202.5 -0.9 870 2.2
Connecticut.............. 111.4 1,617.8 -1.1 1,075 4.0
Delaware................. 28.5 404.8 -0.9 876 2.1
District of Columbia..... 34.2 701.4 2.3 1,506 5.7
Florida.................. 600.0 7,043.4 -0.6 782 2.1
Georgia.................. 267.9 3,767.6 -0.9 812 2.5
Hawaii................... 38.9 584.0 -1.9 782 0.9
Idaho.................... 54.9 616.6 -1.4 651 3.0
Illinois................. 377.5 5,574.8 -0.6 910 3.1
Indiana.................. 158.0 2,734.8 1.2 732 3.1
Iowa..................... 94.6 1,459.3 -0.9 709 3.4
Kansas................... 87.6 1,315.2 -1.1 732 1.9
Kentucky................. 109.9 1,733.6 0.6 743 2.8
Louisiana................ 129.5 1,849.1 -0.1 769 2.1
Maine.................... 48.9 591.6 -0.8 699 2.6
Maryland................. 162.3 2,501.7 0.0 957 2.5
Massachusetts............ 218.7 3,199.1 0.4 1,060 3.1
Michigan................. 248.1 3,828.6 0.8 825 1.9
Minnesota................ 169.7 2,605.5 -0.3 869 3.3
Mississippi.............. 69.3 1,083.7 0.0 652 2.0
Missouri................. 173.5 2,611.5 -1.1 762 1.7
Montana.................. 42.4 432.0 -0.5 658 3.5
Nebraska................. 59.8 909.6 -0.3 696 3.3
Nevada................... 72.6 1,117.7 -2.1 796 -0.3
New Hampshire............ 48.1 612.4 -0.5 867 4.6
New Jersey............... 266.9 3,853.2 -0.3 1,028 2.6
New Mexico............... 54.4 792.1 -0.8 743 2.6
New York................. 589.0 8,503.4 0.5 1,078 5.0
North Carolina........... 251.8 3,813.0 -0.5 764 3.9
North Dakota............. 26.0 363.6 2.0 711 6.6
Ohio..................... 283.0 4,959.0 -0.4 775 2.9
Oklahoma................. 102.5 1,499.0 -0.3 717 3.0
Oregon................... 130.2 1,626.2 -0.5 786 2.5
Pennsylvania............. 341.8 5,552.8 0.6 849 2.4
Rhode Island............. 35.0 456.5 -0.6 831 3.1
South Carolina........... 111.5 1,782.5 0.0 710 3.6
South Dakota............. 30.8 401.5 0.2 631 2.8
Tennessee................ 139.5 2,583.3 0.7 776 3.3
Texas.................... 570.0 10,245.8 0.7 864 3.0
Utah..................... 83.0 1,159.2 -0.4 733 1.4
Vermont.................. 24.3 291.2 -1.0 756 4.3
Virginia................. 231.5 3,590.7 0.1 929 3.3
Washington............... 230.7 2,858.7 -0.9 898 2.0
West Virginia............ 48.6 700.5 0.4 726 2.3
Wisconsin................ 156.4 2,684.4 -0.3 746 2.5
Wyoming.................. 25.1 280.9 -1.1 789 2.7
Puerto Rico.............. 49.6 930.6 -2.6 493 1.6
Virgin Islands........... 3.6 43.9 0.7 709 -1.4
(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
