Full text of Third Quarter 2004 : Text File, USDL 05-623
The full text on this page is automatically extracted from the file linked above and may contain errors and inconsistencies.
Technical information: (202) 691-6567 USDL 05-623
http://www.bls.gov/cew/
For release: 10:00 A.M. EDT
Media contact: 691-5902 Thursday, April 14, 2005
COUNTY EMPLOYMENT AND WAGES: THIRD QUARTER 2004
In September 2004, Rutherford County, Tenn., had the largest over-
the-year percentage increase in employment among the largest counties
in the U.S., according to preliminary data released today by the Bureau
of Labor Statistics of the U.S. Department of Labor. Rutherford County
experienced an over-the-year employment gain of 9.2 percent, compared
with national job growth of 1.3 percent. St. Joseph County, Ind., had
the largest over-the-year gain in average weekly wages in the third
quarter of 2004, with an increase of 10.4 percent. The U.S. average
weekly wage increased by 4.0 percent over the same time span.
Of the 317 largest counties in the United States, as measured by
2003 employment, 139 had over-the-year percentage growth in employment
above the national average in September 2004, and 162 experienced
changes below the national average. Average weekly wages grew faster
than the national average in 137 of the largest U.S. counties, while
the percent change in average weekly wages was below the national
average in 165 counties.
The employment and average weekly wage data by county are compiled
under the Quarterly Census of Employment and Wages (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 8.4 million employer reports cover 130.2 million full- and
part-time workers. The attached tables and charts contain data for
the nation and for the 317 U.S. counties with annual average employment
levels of 75,000 or more in 2003. In addition, data for San Juan, Puerto
Rico, are provided, but not used in calculating U.S. averages, or in the
analysis in the text. (See Technical Note.) September 2004 employment
and 2004 third-quarter average weekly wages for all states are provided
in table 4 of this release. Data for all states, metropolitan statisti-
cal areas, counties, and the nation through the second quarter of 2004
are available on the BLS Web site at http://www.bls.gov/cew/. Prelimi-
nary data for the third quarter of 2004 and revised data for the first
and second quarters of 2004 will be available in April on the BLS Web
site.
Large County Employment
In September 2004, national employment, as measured by the QCEW
program, was 130.2 million, up 1.3 percent from September 2003. The
317 U.S. counties with 75,000 or more employees accounted for 70.2 per-
cent of total U.S. covered employment and 76.1 percent of total covered
wages. These 317 counties had a net job gain of 1,073,000 over the year,
accounting for 63.8 percent of the U.S. employment increase. Employment
increased in 242 of the large counties from September 2003 to September
2004. Rutherford County, Tenn., had the largest over-the-year percentage
increase in employment (9.2 percent). Clark County, Nev., had the next
largest increase, 7.4 percent, followed by the counties of Riverside, Calif.
(7.2 percent), Elkhart, Ind. (6.8 percent), and Montgomery, Texas (6.6 per-
cent). (See table 1.)
Employment declined in 54 counties from September 2003 to September 2004.
The largest percentage decline in employment was in Trumbull County, Ohio
(-3.7 percent), followed by the counties of Tulare, Calif. (-2.7 percent),
Ingham, Mich. (-2.6 percent), Richmond, Ga. (-2.2 percent), and Okaloosa,
Fla. (-2.0 percent).
- 2 -
Table A. Top 10 counties ranked by September 2004 employment, September
2003-04 employment change, and September 2003-04 percent change in employment
--------------------------------------------------------------------------------
Employment in large counties
--------------------------------------------------------------------------------
| |
September 2004 employment | Net change in employment, | Percent change
(thousands) | September 2003-04 | in employment,
| (thousands) | September 2003-04
----------------------------|---------------------------|-----------------------
U.S. 130,248.9|U.S. 1,681.6|U.S. 1.3
----------------------------|---------------------------|-----------------------
Los Angeles, Calif. 4,019.6|Maricopa, Ariz. 58.6|Rutherford, Tenn. 9.2
Cook, Ill. 2,511.7|Clark, Nev. 56.5|Clark, Nev. 7.4
New York, N.Y. 2,201.7|Orange, Calif. 44.1|Riverside, Calif. 7.2
Harris, Texas 1,838.1|Riverside, Calif. 38.2|Elkhart, Ind. 6.8
Maricopa, Ariz. 1,633.3|Los Angeles, Calif. 29.4|Montgomery, Texas 6.6
Orange, Calif. 1,468.4|Fairfax, Va. 24.9|Lee, Fla. 6.1
Dallas, Texas 1,438.0|Miami-Dade, Fla. 20.0|Prince William, Va. 5.8
San Diego, Calif. 1,268.0|Orange, Fla. 19.8|Utah, Utah 5.3
King, Wash. 1,104.3|San Bernardino, Calif. 19.3|Loudoun, Va. 5.3
Miami-Dade, Fla. 979.5|Hillsborough, Fla. 18.8|Sarasota, Fla. 5.1
--------------------------------------------------------------------------------
The largest gains in employment from September 2003 to September 2004
were recorded in the counties of Maricopa, Ariz. (58,600), Clark, Nev.
(56,500), Orange, Calif. (44,100), Riverside, Calif. (38,200) and Los
Angeles, Calif. (29,400). (See table A.)
The largest absolute declines in employment occurred in Wayne County,
Mich. (-9,700), followed by the counties of Philadelphia, Pa. (-8,500),
Cook, Ill. (-7,100), Baltimore City, Md. (-6,800), and Milwaukee, Wis.
(-6,500).
Large County Average Weekly Wages
The national average weekly wage in the third quarter of 2004 was
$733. Average weekly wages were higher than the national average in
118 of the largest 317 U.S. counties. New York County, N.Y., held the
top position among the highest-paid large counties with an average
weekly wage of $1,327. Santa Clara County, Calif., was second with an
average weekly wage of $1,308, followed by Washington, D.C. ($1,207),
Arlington, Va. ($1,196), and Suffolk, Mass. ($1,178). (See table B.)
There were 198 counties with an average weekly wage below the
national average in the third quarter of 2004. The lowest average
weekly wages were reported in Cameron County, Texas ($468), followed
by the counties of Hidalgo, Texas ($475), Horry, S.C. ($487), Webb,
Texas ($496), and Yakima, Wash. ($500). (See table 1.)
- 3 -
Table B. Top 10 counties ranked by third quarter 2004 average weekly wages,
third quarter 2003-04 change in average weekly wages, and third quarter
2003-04 percent change in average weekly wages
--------------------------------------------------------------------------------
Average weekly wage in large counties
--------------------------------------------------------------------------------
| | Percent change in
Average weekly wage, | Change in average weekly | average weekly wage,
third quarter 2004 | wage, third quarter | third quarter
| 2003-04 | 2003-04
---------------------------|---------------------------|------------------------
U.S. $733|U.S. $28|U.S. 4.0
---------------------------|---------------------------|------------------------
New York, N.Y. $1,327|Suffolk, Mass. $98|St. Joseph, Ind. 10.4
Santa Clara, Calif. 1,308|New York, N.Y. 87|Suffolk, Mass. 9.1
Washington, D.C. 1,207|Arlington, Va. 86|Loudoun, Va. 8.4
Arlington, Va. 1,196|Washington, D.C. 85|Rockingham, N.H. 8.1
Suffolk, Mass. 1,178|Loudoun, Va. 75|Arlington, Va. 7.7
San Mateo, Calif. 1,132|Fairfield, Conn. 66|Washington, D.C. 7.6
Fairfield, Conn. 1,132|St. Joseph, Ind. 64|Catawba, N.C. 7.3
San Francisco, Calif. 1,107|Hartford, Conn. 56|Forsyth, N.C. 7.3
Somerset, N.J. 1,093|Montgomery, Md. 56|Lexington, S.C. 7.3
Fairfax, Va. 1,068|Rockingham, N.H. 55|Henrico, Va. 7.3
--------------------------------------------------------------------------------
Over the year, the national average weekly wage rose by 4.0 percent.
Among the largest counties, St. Joseph, Ind., led the nation in growth
in average weekly wages, with an increase of 10.4 percent from the third
quarter of 2003. Suffolk, Mass., was second with 9.1 percent growth,
followed by the counties of Loudoun, Va. (8.4 percent), Rockingham, N.H.
(8.1 percent), and Arlington, Va. (7.7 percent).
Seven counties experienced over-the-year declines in average weekly
wages. Kalamazoo County, Mich., had the largest decrease, -7.7 percent,
followed by the counties of Arapahoe, Colo. (-7.3 percent), Somerset,
N.J. (-6.9 percent), King, Wash. (-2.4 percent), and Santa Cruz, Calif.
(-1.3 percent).
Ten Largest U.S. Counties
Of the 10 largest U.S. counties (based on 2003 employment levels),
9 reported increases in employment, while 1 showed a decline from
September 2003 to September 2004. Maricopa County, Ariz., experienced
the fastest growth in employment among the largest counties, with a
3.7 percent increase. Within Maricopa County, employment rose in every
industry group except information. The largest gains were in construc-
tion (9.4 percent) and professional and business services (6.2 percent).
(See table 2.) Orange County, Calif., had the next largest increase in
employment, 3.1 percent, followed by Miami-Dade, Fla. (2.1 percent). The
only decrease in employment for the 10 largest counties was in Cook County,
Ill., with a 0.3 percent decline. The next lowest change in employment was
recorded in Los Angeles County, Calif. (+0.7 percent), followed by the
counties of New York, N.Y., Dallas, Texas, and Harris, Texas (+0.8 percent
each).
- 4 -
Eight of the 10 largest U.S. counties saw over-the-year increases
in average weekly wages. New York County, N.Y., had the fastest
growth in wages among the top 10 counties, 7.0 percent. Within New
York County, wages increased the most in natural resources and mining
(15.2 percent) and financial activities (14.2 percent). San Diego
County, Calif., was second in wage growth, increasing by 5.4 percent,
followed by Los Angeles County, Calif., with a gain of 4.9 percent.
The smallest wage gains among the 10 largest counties occurred in
Dallas County, Texas (3.0 percent) and Orange County, Calif. (3.3 per-
cent). King County, Wash., experienced the only decline in average
weekly wages among the largest 10 counties (-2.4 percent). The in-
formation sector in King County posted the largest drop in wages,
with a decline of 28.3 percent over the year. A change in wage
coverage for business establishments in Washington State contributed
significantly to these wage declines. See the Coverage section of the
Technical Note for more information.
Largest County by State
Table 3 shows September 2004 employment and the 2004 third-quarter
average weekly wage in the largest county in each state. (This table
includes two counties--Yellowstone, Mont., and Laramie, Wyo.--that have
employment levels below 75,000). The employment levels in these counties
in September 2004 ranged from approximately 4 million in Los Angeles County,
Calif., to 39,800 in Laramie County, Wyo. The highest average weekly wage
of these counties was in New York, N.Y. ($1,327), while the lowest average
weekly wage was in Yellowstone County, Mont. ($572).
-------------------------------------------------------------------
| Introduction of the Location Quotient Calculator |
| |
| In March 2005, the Bureau of Labor Statistics introduced a |
| new tool on its Web site for analyzing data from the Quarterly |
| Census of Employment and Wages program. The Location Quotient |
| Calculator helps data users compare industry employment levels |
| in a defined area to that of a larger area or base. For example, |
| location quotients can be used to compare state employment by |
| industry to that of the nation; or employment in a city, county, |
| metropolitan statistical area, or other defined geographic subarea|
| to that in the state. A link to the Location Quotient Calculator |
| and other relevant information can be found at http://www.bls.gov/|
| cew/cewlq.htm. |
-------------------------------------------------------------------
- 5 -
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 to-
tal 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. Data for 2004 are preliminary and sub-
ject to revision.
For purposes of this release, large counties are defined as having
employment levels of 75,000 or greater. Each year, these large counties
are selected on the basis of the preliminary annual average of employment
for the previous year. The 318 counties discussed in this release were
derived using 2003 preliminary annual averages of employment. These
counties will be included in all 2004 quarterly releases. 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' continuing 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 pro-
cedure, and publication product.
Differences in coverage and estimation methods can result in somewhat
different measures of over-the-quarter employment change. It is important
to understand program differences and the intended uses of the program
products. (See table below.) Additional information on each program can
be obtained from the program Web sites shown in the table below.
- 6 -
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 8.4 | ministrative records| ments
| million establish- | submitted by 6.5 |
| ments | million private-sec-|
| | 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 feder-| establishments with | ing agriculture, pri-
| al 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 |--Future expansions |
| industry | will include data at|
| | the county, MSA, and|
| | state level and by |
| | size of establish- |
| | ment |
-----------|---------------------|----------------------|--------------------------
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 | -Future: Employment| cators
| surveys | expansion and con- |
| | traction by size of|
| | establishment |
-----------|---------------------|----------------------|--------------------------
Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/
Web sites | | |
-----------------------------------------------------------------------------------
- 7 -
Coverage
Employment and wage data for workers covered by state UI laws and for
federal civilian workers covered by the Unemployment Compensation for
Federal Employees (UCFE) program are compiled from quarterly contribution
reports submitted to the SWAs by employers. 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. The employment and wage data included in this
release are derived from microdata summaries of more than 8 million employer
reports of employment and wages submitted by states to the BLS. These re-
ports are based on place of employment rather than place of residence.
UI and UCFE coverage is broad and basically comparable from state to
state. In 2003, UI and UCFE programs covered workers in 127.8 million
jobs. The estimated 122.9 million workers in these jobs (after adjust-
ment for multiple jobholders) represented 96.6 percent of civilian wage
and salary employment. Covered workers received $4.826 trillion in pay,
representing 94.6 percent of the wage and salary component of personal
income and 43.9 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 domes-
tic 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. Coverage changes may affect the over-the-year comparisons
presented in this news release. Effective January 1, 2004, the Washington
Employment Security Department no longer includes as covered wages an em-
ployee's income attributable to the transfer of shares of stock to the em-
ployee. This change in wage coverage pertains to all establishments in
Washington State and contributes significantly to over-the-year changes in
wages in the state in 2004.
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 pro-
duction 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 averages 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 compensation plans
such as 401(k) plans and stock options.
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.
When comparing average weekly wage levels between industries and/or states,
these factors should be taken into consideration.
- 8 -
Federal government pay levels are subject to periodic, sometimes large,
fluctuations due to a calendar effect that consists of some quarters having
more pay periods than others. Most federal employees are paid on a bi-
weekly 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 periods. 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
comparison 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 occur 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 employers and update, if necessary, the industry, location, and own-
ership classification of all establishments on a 3-year cycle. Changes
in establishment classification codes resulting from this process are in-
troduced 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 individual 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 underlying establishment reports. This is done by
modifying the prior-year levels used to calculate the over-the-year changes.
Percent changes are calcuated using an adjusted version of the final 2003
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 unadjusted
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 release.
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 establishments. The most common adjustments for
administrative change are the result of updated information about the
county location of individual establishments.
The adjusted data do not account for administrative changes caused by
(1) multi-unit employers who start reporting for each individual estab-
lishment rather than as a single entity and (2) the classification of
establishments previously reported in the unknown county or unknown in-
dustry categories.
- 9 -
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 Standards 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 re-
ferred to in this release are defined as census regions.
Additional statistics and other information
An annual bulletin, Employment and Wages, features comprehensive infor-
mation by detailed industry on establishments, employment, and wages for
the nation and all states. Employment and Wages Annual Averages, 2003
is available for sale from the BLS Publications Sales Center, P.O. Box
2145, Chicago, Illinois 60690, telephone 312-353-1880. The 2003 bulletin
will be available in April 2005 in a portable document format (PDF) on the BLS
Web site at http://www.bls.gov/cew/cewbultn03.htm.
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 318 largest counties,
third quarter 2004(2)
Employment Average weekly wage(5)
Establishments,
third quarter Percent
County(3) 2004 September Percent Ranking Average change, Ranking
(thousands) 2004 change, by weekly third by
(thousands) September percent wage quarter percent
2003-04(4) change 2003-04 change
(4)
United States(6)......... 8,421.8 130,248.9 1.3 - $733 4.0 -
Jefferson, AL............ 18.5 368.3 0.0 244 739 3.6 172
Madison, AL.............. 7.9 165.3 2.6 66 773 2.7 238
Mobile, AL............... 9.6 161.3 -0.3 261 601 2.6 247
Montgomery, AL........... 6.6 131.3 1.4 134 619 2.1 276
Tuscaloosa, AL........... 4.2 78.8 3.0 51 614 2.7 238
Anchorage Borough, AK.... 7.7 145.0 0.8 175 809 4.0 138
Maricopa, AZ............. 79.9 1,633.3 3.7 32 731 4.7 77
Pima, AZ................. 17.5 339.6 2.9 56 640 4.1 133
Benton, AR............... 4.5 86.1 4.4 16 679 4.5 102
Pulaski, AR.............. 13.3 242.6 0.9 166 669 4.7 77
Washington, AR........... 5.1 87.0 2.3 81 599 6.6 15
Alameda, CA.............. 47.7 674.8 -0.5 270 971 3.6 172
Contra Costa, CA......... 27.4 339.2 0.7 189 923 5.2 53
Fresno, CA............... 28.6 348.8 -0.4 266 591 3.5 187
Kern, CA................. 15.8 257.7 0.4 217 632 5.0 60
Los Angeles, CA.......... 360.1 4,019.6 0.7 189 833 4.9 68
Marin, CA................ 11.8 110.3 0.8 175 914 4.8 72
Monterey, CA............. 11.9 180.2 1.1 154 643 4.7 77
Orange, CA............... 89.7 1,468.4 3.1 47 840 3.3 199
Placer, CA............... 9.4 130.9 3.7 32 738 3.2 202
Riverside, CA............ 38.3 572.4 7.2 3 635 5.3 49
Sacramento, CA........... 46.5 608.8 1.4 134 817 2.4 262
San Bernardino, CA....... 41.9 600.7 3.3 40 655 4.1 133
San Diego, CA............ 86.2 1,268.0 1.4 134 800 5.4 44
San Francisco, CA........ 43.0 521.9 -0.6 277 1,107 3.4 194
San Joaquin, CA.......... 15.8 221.9 0.6 199 649 3.5 187
San Luis Obispo, CA...... 8.6 101.7 0.4 217 631 6.9 12
San Mateo, CA............ 22.7 328.7 0.0 244 1,132 0.8 301
Santa Barbara, CA........ 13.1 180.6 0.6 199 702 3.7 163
Santa Clara, CA.......... 52.3 850.8 0.7 189 1,308 3.1 209
Santa Cruz, CA........... 8.3 100.3 1.4 134 684 -1.3 308
Solano, CA............... 9.5 128.1 0.8 175 696 2.5 257
Sonoma, CA............... 17.2 193.1 1.5 121 732 2.7 238
Stanislaus, CA........... 13.1 174.9 0.3 225 632 3.8 157
Tulare, CA............... 8.5 135.9 -2.7 307 531 5.1 58
Ventura, CA.............. 20.5 302.2 0.9 166 779 1.3 296
Yolo, CA................. 5.1 98.6 1.3 141 734 5.0 60
Adams, CO................ 8.7 143.9 0.8 175 706 2.6 247
Arapahoe, CO............. 19.0 269.0 -0.3 261 870 -7.3 311
Boulder, CO.............. 11.9 153.5 2.5 73 870 0.6 304
Denver, CO............... 24.6 427.3 1.5 121 888 2.9 224
El Paso, CO.............. 16.1 237.9 1.5 121 696 2.7 238
Jefferson, CO............ 18.2 204.4 0.7 189 765 3.2 202
Larimer, CO.............. 9.3 124.4 2.1 87 689 3.1 209
Fairfield, CT............ 31.8 411.4 0.1 233 1,132 6.2 20
Hartford, CT............. 24.4 483.0 1.1 154 916 6.5 16
New Haven, CT............ 22.0 362.2 2.1 87 811 3.4 194
New London, CT........... 6.6 129.4 0.0 244 762 4.2 120
New Castle, DE........... 19.3 280.2 0.3 225 858 2.4 262
Washington, DC........... 30.1 658.3 1.2 147 1,207 7.6 6
Alachua, FL.............. 6.0 123.4 1.7 111 566 5.4 44
Brevard, FL.............. 12.9 194.5 (7) - 727 (7) -
Broward, FL.............. 58.6 687.9 1.8 105 696 3.6 172
Collier, FL.............. 10.7 115.8 3.6 35 649 4.7 77
Duval, FL................ 23.0 436.3 2.6 66 711 2.4 262
Escambia, FL............. 7.4 124.8 2.8 62 583 3.2 202
Hillsborough, FL......... 32.2 606.5 3.2 45 694 3.7 163
Lee, FL.................. 15.7 194.3 6.1 6 637 6.0 27
Leon, FL................. 7.4 143.6 1.9 98 631 3.6 172
Manatee, FL.............. 7.3 116.9 4.4 16 571 4.6 91
Marion, FL............... 6.8 90.3 4.7 13 541 3.6 172
Miami-Dade, FL........... 82.6 979.5 2.1 87 717 (7) -
Okaloosa, FL............. 5.5 79.8 -2.0 304 592 6.9 12
Orange, FL............... 30.8 624.4 3.3 40 682 5.7 33
Palm Beach, FL........... 44.2 503.7 1.1 154 720 3.9 147
Pasco, FL................ 7.7 84.0 3.1 47 534 6.2 20
Pinellas, FL............. 29.0 437.1 3.9 25 638 2.2 272
Polk, FL................. 10.8 185.7 4.4 16 601 3.6 172
Sarasota, FL............. 13.4 153.9 5.1 10 618 5.3 49
Seminole, FL............. 12.6 153.4 4.4 16 645 2.9 224
Volusia, FL.............. 12.3 149.2 (7) - 558 (7) -
Bibb, GA................. 4.7 85.9 0.5 205 623 4.4 111
Chatham, GA.............. 7.0 127.1 1.5 121 631 4.5 102
Clayton, GA.............. 4.4 106.1 (7) - 808 5.8 29
Cobb, GA................. 19.8 296.8 -1.3 293 803 3.6 172
De Kalb, GA.............. 16.9 288.7 -0.9 287 792 2.9 224
Fulton, GA............... 37.1 726.6 1.5 121 958 4.2 120
Gwinnett, GA............. 21.4 307.9 3.1 47 773 1.2 297
Muscogee, GA............. 4.7 95.9 -1.7 300 589 3.9 147
Richmond, GA............. 4.8 102.8 -2.2 305 627 4.7 77
Honolulu, HI............. 23.2 426.7 2.7 64 703 4.6 91
Ada, ID.................. 13.2 190.6 3.9 25 675 4.5 102
Champaign, IL............ 3.9 90.6 0.6 199 639 2.2 272
Cook, IL................. 126.7 2,511.7 -0.3 261 871 4.3 116
Du Page, IL.............. 32.6 577.1 0.8 175 851 2.4 262
Kane, IL................. 11.1 201.6 0.4 217 686 2.7 238
Lake, IL................. 19.0 326.9 1.2 147 874 4.5 102
McHenry, IL.............. 7.5 96.8 2.5 73 666 2.6 247
McLean, IL............... 3.4 83.9 -1.9 301 702 1.4 292
Madison, IL.............. 5.6 93.5 -1.0 290 614 4.8 72
Peoria, IL............... 4.6 98.4 2.3 81 692 4.8 72
Rock Island, IL.......... 3.4 78.3 -0.7 282 715 2.1 276
St. Clair, IL............ 5.1 92.9 -0.1 255 606 5.0 60
Sangamon, IL............. 5.1 130.3 (7) - 736 (7) -
Will, IL................. 10.8 163.9 2.9 56 698 2.2 272
Winnebago, IL............ 6.6 137.6 0.7 189 632 0.6 304
Allen, IN................ 8.7 180.5 1.2 147 658 2.7 238
Elkhart, IN.............. 4.8 126.3 6.8 4 658 5.6 34
Hamilton, IN............. 6.2 90.6 4.9 11 755 4.1 133
Lake, IN................. 9.9 193.9 0.0 244 670 4.2 120
Marion, IN............... 23.7 581.1 1.5 121 765 3.8 157
St. Joseph, IN........... 6.0 125.0 1.6 118 677 10.4 1
Vanderburgh, IN.......... 4.8 107.4 -1.3 293 628 5.4 44
Linn, IA................. 6.1 116.0 0.9 166 706 3.4 194
Polk, IA................. 14.2 261.5 1.8 105 740 4.7 77
Scott, IA................ 5.1 86.4 1.9 98 604 2.5 257
Johnson, KS.............. 18.9 296.6 1.9 98 764 3.8 157
Sedgwick, KS............. 11.6 241.3 1.2 147 689 6.5 16
Shawnee, KS.............. 4.7 94.6 -1.5 298 624 4.2 120
Fayette, KY.............. 8.8 166.5 0.8 175 681 3.7 163
Jefferson, KY............ 21.6 417.1 0.0 244 726 5.5 39
Caddo, LA................ 7.0 122.0 1.8 105 612 5.5 39
Calcasieu, LA............ 4.6 80.8 -0.4 266 598 0.7 302
East Baton Rouge, LA..... 13.1 244.9 0.8 175 618 2.0 281
Jefferson, LA............ 14.0 210.5 -0.4 266 613 4.3 116
Lafayette, LA............ 7.6 118.4 -0.5 270 635 1.6 287
Orleans, LA.............. 12.6 244.6 -1.6 299 677 1.5 290
Cumberland, ME........... 12.0 171.0 1.1 154 671 5.5 39
Anne Arundel, MD......... 13.6 215.7 2.4 77 773 3.9 147
Baltimore, MD............ 20.7 366.0 1.8 105 751 2.3 270
Frederick, MD............ 5.5 90.2 2.8 62 701 4.9 68
Howard, MD............... 8.0 138.6 0.1 233 846 5.0 60
Montgomery, MD........... 31.5 450.6 0.5 205 953 6.2 20
Prince Georges, MD....... 15.2 314.9 1.6 118 820 5.8 29
Baltimore City, MD....... 14.1 355.4 -1.9 301 825 1.2 297
Barnstable, MA........... 9.3 99.4 -0.2 258 635 4.6 91
Bristol, MA.............. 15.4 218.9 -0.5 270 672 6.2 20
Essex, MA................ 20.8 294.1 -0.9 287 800 3.1 209
Hampden, MA.............. 14.2 198.6 -1.1 291 704 6.0 27
Middlesex, MA............ 48.2 782.0 -0.5 270 1,043 4.6 91
Norfolk, MA.............. 21.9 316.2 -0.8 285 885 1.6 287
Plymouth, MA............. 13.7 175.0 1.3 141 719 4.8 72
Suffolk, MA.............. 22.4 557.5 -0.5 270 1,178 9.1 2
Worcester, MA............ 20.5 318.3 0.1 233 783 6.1 24
Genesee, MI.............. 8.6 155.3 0.4 217 715 2.6 247
Ingham, MI............... 7.0 164.9 -2.6 306 723 3.0 217
Kalamazoo, MI............ 5.5 116.1 -0.2 258 688 -7.7 312
Kent, MI................. 14.6 336.4 1.3 141 703 2.6 247
Macomb, MI............... 18.1 325.4 0.5 205 818 4.2 120
Oakland, MI.............. 41.4 717.1 -0.8 285 893 2.9 224
Ottawa, MI............... 5.8 115.1 3.0 51 672 3.9 147
Saginaw, MI.............. 4.6 89.9 -1.4 297 691 2.4 262
Washtenaw, MI............ 8.2 195.2 0.4 217 847 1.8 282
Wayne, MI................ 35.0 791.2 -1.2 292 874 4.7 77
Anoka, MN................ 7.5 113.1 1.0 161 734 4.9 68
Dakota, MN............... 9.7 169.2 2.0 93 740 2.9 224
Hennepin, MN............. 40.5 827.3 0.8 175 933 2.6 247
Olmsted, MN.............. 3.3 87.3 0.7 189 819 3.5 187
Ramsey, MN............... 14.9 329.6 0.3 225 819 2.9 224
St. Louis, MN............ 5.7 94.8 1.4 134 634 2.4 262
Stearns, MN.............. 4.2 77.7 1.2 147 611 6.1 24
Harrison, MS............. 4.6 90.0 -0.5 270 520 -0.2 306
Hinds, MS................ 6.6 130.2 0.1 233 651 4.0 138
Boone, MO................ 4.3 78.2 2.6 66 585 2.8 235
Clay, MO................. 4.9 86.9 0.5 205 698 4.5 102
Greene, MO............... 8.0 146.2 0.8 175 591 4.2 120
Jackson, MO.............. 18.7 363.3 -0.3 261 757 4.6 91
St. Charles, MO.......... 7.3 114.9 (7) - 644 3.9 147
St. Louis, MO............ 33.7 617.5 -0.1 255 778 1.4 292
St. Louis City, MO....... 8.2 224.8 (7) - 811 4.0 138
Douglas, NE.............. 14.9 309.4 0.5 205 702 3.4 194
Lancaster, NE............ 7.5 153.6 2.5 73 621 4.0 138
Clark, NV................ 39.0 822.6 7.4 2 701 4.6 91
Washoe, NV............... 12.7 209.0 4.7 13 713 2.7 238
Hillsborough, NH......... 12.4 194.2 0.8 175 828 6.3 19
Rockingham, NH........... 10.7 136.7 2.9 56 738 8.1 4
Atlantic, NJ............. 6.6 147.3 -0.3 261 666 2.9 224
Bergen, NJ............... 34.3 447.7 0.2 229 910 2.9 224
Burlington, NJ........... 11.1 198.8 1.0 161 789 3.5 187
Camden, NJ............... 13.4 210.8 3.8 29 741 2.2 272
Essex, NJ................ 21.4 357.4 0.1 233 947 4.3 116
Gloucester, NJ........... 6.1 100.4 3.9 25 679 5.4 44
Hudson, NJ............... 13.9 234.4 0.4 217 980 5.6 34
Mercer, NJ............... 10.7 217.4 -0.9 287 934 1.5 290
Middlesex, NJ............ 20.7 392.0 0.8 175 938 4.0 138
Monmouth, NJ............. 19.9 254.9 2.7 64 786 3.7 163
Morris, NJ............... 17.7 281.3 0.4 217 1,034 2.3 270
Ocean, NJ................ 11.5 148.9 3.0 51 623 3.1 209
Passaic, NJ.............. 12.5 178.1 2.0 93 786 4.2 120
Somerset, NJ............. 9.9 166.1 (7) - 1,093 -6.9 310
Union, NJ................ 14.9 232.1 (7) - 912 (7) -
Bernalillo, NM........... 16.5 315.6 1.5 121 665 2.6 247
Albany, NY............... 9.6 227.9 0.0 244 787 4.7 77
Bronx, NY................ 15.4 216.4 1.2 147 746 5.8 29
Broome, NY............... 4.5 94.3 -0.4 266 602 4.2 120
Dutchess, NY............. 7.9 116.5 1.5 121 744 1.6 287
Erie, NY................. 23.3 457.9 0.7 189 663 5.2 53
Kings, NY................ 42.0 446.5 1.7 111 665 3.6 172
Monroe, NY............... 17.7 379.9 -0.7 282 752 5.0 60
Nassau, NY............... 50.7 597.4 0.6 199 808 3.5 187
New York, NY............. 112.7 2,201.7 0.8 175 1,327 7.0 11
Oneida, NY............... 5.3 108.3 0.6 199 581 3.2 202
Onondaga, NY............. 12.6 249.0 0.9 166 687 2.8 235
Orange, NY............... 9.3 127.4 1.4 134 632 4.5 102
Queens, NY............... 40.3 478.1 0.9 166 751 1.8 282
Richmond, NY............. 8.1 88.3 1.5 121 693 4.2 120
Rockland, NY............. 9.4 110.5 0.1 233 772 3.6 172
Suffolk, NY.............. 47.7 602.1 1.1 154 797 4.2 120
Westchester, NY.......... 35.3 410.4 1.7 111 963 (7) -
Buncombe, NC............. 6.9 106.6 0.9 166 588 4.6 91
Catawba, NC.............. 4.2 86.7 1.3 141 588 7.3 7
Cumberland, NC........... 5.6 112.0 2.9 56 584 5.4 44
Durham, NC............... 6.1 166.3 0.9 166 955 3.6 172
Forsyth, NC.............. 8.4 176.3 0.5 205 761 7.3 7
Guilford, NC............. 13.6 266.5 1.5 121 674 2.7 238
Mecklenburg, NC.......... 27.2 507.2 0.5 205 838 1.8 282
New Hanover, NC.......... 6.4 92.9 4.0 23 598 4.7 77
Wake, NC................. 23.3 392.6 3.3 40 734 3.2 202
Cass, ND................. 5.4 90.0 3.7 32 610 3.9 147
Butler, OH............... 6.9 134.5 2.1 87 663 3.8 157
Cuyahoga, OH............. 38.2 759.8 0.0 244 776 4.9 68
Franklin, OH............. 29.1 685.4 0.1 233 741 3.8 157
Hamilton, OH............. 24.6 543.8 0.2 229 808 5.8 29
Lake, OH................. 6.7 98.8 0.0 244 630 3.6 172
Lorain, OH............... 6.2 102.3 0.5 205 646 5.0 60
Lucas, OH................ 10.8 226.7 0.1 233 669 1.4 292
Mahoning, OH............. 6.4 106.9 1.0 161 570 3.1 209
Montgomery, OH........... 13.2 285.7 -0.5 270 707 4.0 138
Stark, OH................ 9.1 166.8 0.0 244 596 3.7 163
Summit, OH............... 14.7 268.5 1.2 147 694 2.1 276
Trumbull, OH............. 4.8 83.5 -3.7 308 685 6.4 18
Oklahoma, OK............. 21.7 408.3 1.9 98 645 3.2 202
Tulsa, OK................ 18.2 320.0 1.0 161 667 5.0 60
Clackamas, OR............ 11.5 138.7 2.1 87 688 3.6 172
Jackson, OR.............. 6.2 81.4 3.3 40 571 3.6 172
Lane, OR................. 10.4 142.2 3.3 40 598 3.1 209
Marion, OR............... 8.5 135.7 2.6 66 580 1.4 292
Multnomah, OR............ 25.5 422.4 1.6 118 760 3.7 163
Washington, OR........... 14.6 227.7 3.2 45 877 5.5 39
Allegheny, PA............ 35.6 687.2 -0.6 277 774 3.6 172
Berks, PA................ 9.0 163.1 1.7 111 668 3.6 172
Bucks, PA................ 19.9 257.3 2.6 66 709 4.1 133
Chester, PA.............. 14.5 224.3 2.0 93 902 4.6 91
Cumberland, PA........... 5.7 126.5 1.9 98 704 2.9 224
Dauphin, PA.............. 7.0 176.0 1.5 121 736 4.8 72
Delaware, PA............. 13.5 207.7 -0.2 258 778 3.9 147
Erie, PA................. 7.2 127.9 1.8 105 586 3.0 217
Lackawanna, PA........... 5.8 98.7 1.1 154 586 4.6 91
Lancaster, PA............ 11.7 226.4 1.7 111 656 4.6 91
Lehigh, PA............... 8.4 174.2 0.4 217 726 3.7 163
Luzerne, PA.............. 8.0 141.8 -0.6 277 599 4.0 138
Montgomery, PA........... 27.6 480.6 0.3 225 909 4.7 77
Northampton, PA.......... 6.1 91.5 0.5 205 664 4.7 77
Philadelphia, PA......... 28.5 627.6 -1.3 293 869 5.3 49
Westmoreland, PA......... 9.4 136.8 3.5 37 605 4.5 102
York, PA................. 8.5 169.0 2.6 66 666 3.9 147
Kent, RI................. 5.6 81.7 0.5 205 676 2.4 262
Providence, RI........... 17.8 288.5 0.0 244 731 5.2 53
Charleston, SC........... 11.8 194.1 3.4 38 621 3.7 163
Greenville, SC........... 12.1 221.1 0.5 205 663 3.3 199
Horry, SC................ 8.0 108.4 4.6 15 487 3.0 217
Lexington, SC............ 5.5 86.3 1.8 105 589 7.3 7
Richland, SC............. 9.4 208.0 2.0 93 645 4.4 111
Spartanburg, SC.......... 6.2 115.0 -0.6 277 654 4.1 133
Minnehaha, SD............ 6.0 109.4 1.7 111 624 5.6 34
Davidson, TN............. 17.9 432.2 0.9 166 733 3.1 209
Hamilton, TN............. 8.3 191.1 1.7 111 645 3.0 217
Knox, TN................. 10.3 219.1 3.4 38 632 2.8 235
Rutherford, TN........... 3.7 91.6 9.2 1 647 0.9 300
Shelby, TN............... 19.8 495.9 0.1 233 787 6.8 14
Bell, TX................. 4.2 91.5 3.6 35 573 4.0 138
Bexar, TX................ 29.8 661.0 0.7 189 644 4.2 120
Brazoria, TX............. 4.1 76.1 0.0 244 693 3.0 217
Brazos, TX............... 3.5 78.9 1.5 121 535 2.7 238
Cameron, TX.............. 6.1 115.6 0.7 189 468 4.7 77
Collin, TX............... 12.8 211.8 (7) - 797 1.0 299
Dallas, TX............... 68.2 1,438.0 0.8 175 889 3.0 217
Denton, TX............... 8.5 133.2 2.6 66 639 2.9 224
El Paso, TX.............. 12.5 254.5 0.5 205 531 4.5 102
Fort Bend, TX............ 6.4 102.3 4.4 16 729 2.1 276
Galveston, TX............ 4.8 86.6 -1.9 301 641 3.9 147
Harris, TX............... 90.2 1,838.1 0.8 175 862 4.5 102
Hidalgo, TX.............. 9.3 185.3 3.9 25 475 4.2 120
Jefferson, TX............ 5.8 117.2 -0.1 255 661 2.6 247
Lubbock, TX.............. 6.5 118.5 2.9 56 554 0.7 302
McLennan, TX............. 4.7 99.4 2.3 81 583 1.7 286
Montgomery, TX........... 6.4 92.8 6.6 5 654 3.0 217
Nueces, TX............... 8.0 143.3 0.7 189 612 5.2 53
Potter, TX............... 3.9 76.5 0.1 233 585 5.6 34
Smith, TX................ 4.9 86.8 1.9 98 648 6.1 24
Tarrant, TX.............. 34.0 701.0 1.3 141 758 5.0 60
Travis, TX............... 25.2 516.3 2.4 77 824 2.4 262
Webb, TX................. 4.3 78.0 2.3 81 496 4.4 111
Williamson, TX........... 5.1 87.0 4.1 22 746 -0.4 307
Davis, UT................ 6.4 94.2 4.0 23 614 3.2 202
Salt Lake, UT............ 35.0 524.7 2.3 81 671 3.5 187
Utah, UT................. 11.2 152.2 5.3 8 565 2.5 257
Weber, UT................ 5.4 86.8 1.3 141 556 1.8 282
Chittenden, VT........... 5.7 96.4 2.1 87 725 5.1 58
Arlington, VA............ 7.0 155.6 (7) - 1,196 7.7 5
Chesterfield, VA......... 6.7 112.4 2.9 56 670 4.2 120
Fairfax, VA.............. 29.8 548.5 4.8 12 1,068 2.5 257
Henrico, VA.............. 8.3 166.8 1.4 134 779 7.3 7
Loudoun, VA.............. 6.3 115.2 5.3 8 970 8.4 3
Prince William, VA....... 6.0 95.9 5.8 7 664 3.8 157
Alexandria City, VA...... 5.7 92.9 0.9 166 948 4.6 91
Chesapeake City, VA...... 4.8 93.6 4.2 21 582 3.7 163
Newport News City, VA.... 3.7 97.3 2.5 73 673 4.7 77
Norfolk City, VA......... 5.6 144.5 0.1 233 722 3.4 194
Richmond City, VA........ 6.9 157.4 0.2 229 824 3.5 187
Virginia Beach City, VA.. 10.6 174.0 3.8 29 567 3.1 209
Clark, WA................ 10.4 122.1 3.8 29 685 3.3 199
King, WA................. 77.3 1,104.3 1.1 154 940 -2.4 309
Kitsap, WA............... 6.1 80.2 3.0 51 695 2.1 276
Pierce, WA............... 19.6 252.0 1.5 121 673 5.2 53
Snohomish, WA............ 16.1 212.0 3.0 51 763 2.6 247
Spokane, WA.............. 14.6 193.5 1.0 161 604 2.5 257
Thurston, WA............. 6.2 91.5 2.4 77 681 2.9 224
Yakima, WA............... 8.3 104.5 0.6 199 500 4.4 111
Kanawha, WV.............. 6.2 107.7 -0.7 282 627 4.3 116
Brown, WI................ 6.8 146.6 0.2 229 657 4.0 138
Dane, WI................. 13.9 292.4 2.3 81 715 4.4 111
Milwaukee, WI............ 22.2 492.8 -1.3 293 750 5.6 34
Outagamie, WI............ 5.0 100.7 3.1 47 653 5.5 39
Racine, WI............... 4.3 76.8 2.0 93 694 3.9 147
Waukesha, WI............. 13.5 228.9 1.9 98 759 5.3 49
Winnebago, WI............ 4.0 87.6 -0.6 277 707 4.7 77
San Juan, PR............. 13.4 324.3 2.4 77 475 2.6 247
1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 317 U.S. counties comprise 70.2 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 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
5 Average weekly wages were calculated using unrounded data.
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.
Table 2. Covered(1) establishments, employment, and wages in the ten largest counties,
third quarter 2004(2)
Employment Average weekly
wage(4)
Establishments,
third quarter
County by NAICS supersector 2004 Percent Percent
(thousands) September change, Average change,
2004 September weekly third
(thousands) 2003-04(3) wage quarter
2003-04(3)
United States(5)............................. 8,421.8 130,248.9 1.3 $733 4.0
Private industry........................... 8,149.4 109,436.9 1.4 724 4.0
Natural resources and mining............. 122.7 1,777.2 0.5 654 7.7
Construction............................. 823.7 7,167.2 3.3 769 3.4
Manufacturing............................ 370.7 14,332.0 -0.4 898 5.2
Trade, transportation, and utilities..... 1,859.1 25,216.7 0.7 648 3.8
Information.............................. 143.4 3,062.0 -2.4 1,120 1.8
Financial activities..................... 785.8 7,899.5 0.5 1,039 4.0
Professional and business services....... 1,341.4 16,486.7 3.0 859 4.4
Education and health services............ 747.7 16,097.5 2.0 704 4.5
Leisure and hospitality.................. 680.4 12,747.5 2.4 314 3.0
Other services........................... 1,082.4 4,281.7 0.2 477 3.2
Government................................. 272.3 20,812.0 0.6 781 4.1
Los Angeles, CA.............................. 360.1 4,019.6 0.7 833 4.9
Private industry........................... 356.3 3,472.9 1.2 814 5.3
Natural resources and mining............. 0.6 12.0 0.9 1,031 29.0
Construction............................. 13.1 144.4 8.0 827 4.3
Manufacturing............................ 17.1 478.5 -2.3 874 8.0
Trade, transportation, and utilities..... 53.5 776.6 1.5 706 3.7
Information.............................. 8.8 205.2 1.9 1,370 6.1
Financial activities..................... 23.0 235.6 0.7 1,269 7.8
Professional and business services....... 39.9 566.2 1.3 919 4.4
Education and health services............ 26.9 453.9 0.7 759 4.4
Leisure and hospitality.................. 25.5 373.0 1.8 505 5.9
Other services........................... 147.8 226.5 3.1 404 2.3
Government................................. 3.9 546.8 -1.9 956 3.6
Cook, IL..................................... 126.7 2,511.7 -0.3 871 4.3
Private industry........................... 125.4 2,195.1 -0.1 862 4.2
Natural resources and mining............. 0.1 1.4 (6) 1,137 (6)
Construction............................. 10.6 98.8 -4.0 1,073 3.6
Manufacturing............................ 7.6 257.7 -1.6 908 7.1
Trade, transportation, and utilities..... 26.5 477.0 0.2 732 5.5
Information.............................. 2.5 61.4 -5.5 1,206 2.5
Financial activities..................... 14.0 215.8 -1.1 1,318 4.9
Professional and business services....... 25.9 409.4 1.4 1,052 3.4
Education and health services............ 12.5 348.0 0.4 761 3.8
Leisure and hospitality.................. 10.6 226.5 1.7 378 4.4
Other services........................... 12.6 94.1 -1.2 633 3.1
Government................................. 1.2 316.5 -1.5 932 4.7
New York, NY................................. 112.7 2,201.7 0.8 1,327 7.0
Private industry........................... 112.4 1,764.4 1.0 1,404 7.4
Natural resources and mining............. 0.0 0.1 -15.6 1,124 15.2
Construction............................. 2.1 29.3 -3.5 1,312 0.8
Manufacturing............................ 3.3 45.6 -1.6 1,016 6.5
Trade, transportation, and utilities..... 21.8 233.1 1.4 996 3.2
Information.............................. 4.2 130.2 -0.9 1,723 8.0
Financial activities..................... 16.9 347.9 0.0 2,406 14.2
Professional and business services....... 22.6 430.2 0.8 1,517 5.5
Education and health services............ 8.0 267.1 1.1 923 3.0
Leisure and hospitality.................. 10.3 188.3 4.1 642 3.5
Other services........................... 16.0 81.1 0.6 776 2.8
Government................................. 0.2 437.3 -0.1 1,023 4.9
Harris, TX................................... 90.2 1,838.1 0.8 862 4.5
Private industry........................... 89.8 1,594.9 0.7 871 5.1
Natural resources and mining............. 1.3 63.1 1.5 2,018 11.1
Construction............................. 6.3 129.7 -8.1 842 6.4
Manufacturing............................ 4.6 163.9 -0.1 1,080 6.6
Trade, transportation, and utilities..... 21.2 388.5 0.2 782 2.6
Information.............................. 1.4 33.4 -1.7 1,064 3.7
Financial activities..................... 9.7 114.6 2.2 1,046 0.7
Professional and business services....... 17.1 289.7 3.7 988 8.0
Education and health services............ 9.1 188.8 0.7 781 3.6
Leisure and hospitality.................. 6.8 161.5 2.8 323 1.6
Other services........................... 10.4 57.1 1.2 513 2.6
Government................................. 0.4 243.2 1.5 796 0.1
Maricopa, AZ................................. 79.9 1,633.3 3.7 731 4.7
Private industry........................... 79.4 1,414.4 3.9 726 4.3
Natural resources and mining............. 0.5 7.6 0.4 564 12.8
Construction............................. 8.3 143.2 9.4 717 3.8
Manufacturing............................ 3.2 128.4 0.8 1,039 6.3
Trade, transportation, and utilities..... 18.3 328.5 3.9 713 3.9
Information.............................. 1.5 33.6 -7.8 857 5.2
Financial activities..................... 9.6 135.7 1.9 900 2.0
Professional and business services....... 17.7 270.4 6.2 719 6.0
Education and health services............ 7.8 167.1 5.8 776 4.7
Leisure and hospitality.................. 5.7 152.8 2.2 353 3.2
Other services........................... 5.6 44.7 1.7 499 4.0
Government................................. 0.5 218.8 2.3 766 7.0
Dallas, TX................................... 68.2 1,438.0 0.8 889 3.0
Private industry........................... 67.7 1,281.0 0.9 894 3.1
Natural resources and mining............. 0.5 6.5 5.2 2,143 -10.3
Construction............................. 4.4 76.5 0.6 798 3.4
Manufacturing............................ 3.4 144.2 1.0 1,013 5.7
Trade, transportation, and utilities..... 15.7 310.0 0.0 879 4.8
Information.............................. 1.8 59.2 -5.9 1,222 2.5
Financial activities..................... 8.7 140.1 1.0 1,115 1.4
Professional and business services....... 13.8 244.6 3.0 962 1.7
Education and health services............ 6.2 130.8 1.0 862 5.3
Leisure and hospitality.................. 5.1 126.0 1.6 401 0.3
Other services........................... 6.6 39.7 -3.4 570 2.7
Government................................. 0.5 157.0 (6) 840 (6)
Orange, CA................................... 89.7 1,468.4 3.1 840 3.3
Private industry........................... 88.3 1,328.4 3.2 835 3.3
Natural resources and mining............. 0.2 7.4 7.3 515 1.6
Construction............................. 6.6 96.3 9.3 882 2.8
Manufacturing............................ 5.9 183.8 0.9 987 5.2
Trade, transportation, and utilities..... 17.2 266.5 2.0 785 2.3
Information.............................. 1.4 32.6 -3.4 1,205 10.1
Financial activities..................... 10.0 136.8 6.1 1,361 0.8
Professional and business services....... 17.5 264.1 3.9 834 2.1
Education and health services............ 9.2 127.9 1.7 785 6.9
Leisure and hospitality.................. 6.7 165.6 3.2 368 4.0
Other services........................... 13.4 46.9 3.7 510 2.4
Government................................. 1.4 140.0 1.8 886 3.4
San Diego, CA................................ 86.2 1,268.0 1.4 800 5.4
Private industry........................... 84.8 1,058.6 1.6 780 5.5
Natural resources and mining............. 0.9 11.6 -1.4 498 6.2
Construction............................. 6.7 90.0 9.9 822 5.4
Manufacturing............................ 3.5 104.8 -0.2 1,070 9.4
Trade, transportation, and utilities..... 14.2 211.7 2.4 654 3.3
Information.............................. 1.3 36.7 -1.3 1,682 11.6
Financial activities..................... 9.1 81.2 1.4 1,012 0.5
Professional and business services....... 14.9 203.6 0.9 910 4.7
Education and health services............ 7.6 118.2 -1.0 734 6.5
Leisure and hospitality.................. 6.6 147.7 1.6 378 8.3
Other services........................... 20.0 52.8 1.4 440 3.0
Government................................. 1.4 209.4 0.1 907 5.3
King, WA..................................... 77.3 1,104.3 1.1 940 -2.4
Private industry........................... 76.7 950.8 1.1 946 -3.3
Natural resources and mining............. 0.4 3.3 -4.5 966 3.1
Construction............................. 6.2 57.9 1.6 882 1.7
Manufacturing............................ 2.6 102.2 -1.6 1,205 8.4
Trade, transportation, and utilities..... 14.8 218.7 1.5 817 4.3
Information.............................. 1.5 67.8 -1.5 2,135 -28.3
Financial activities..................... 6.2 76.0 -1.6 1,106 0.5
Professional and business services....... 12.0 163.1 4.1 1,039 4.0
Education and health services............ 6.0 110.6 3.2 729 4.6
Leisure and hospitality.................. 5.5 105.1 2.3 401 0.5
Other services........................... 21.5 46.1 -4.7 483 8.3
Government................................. 0.5 153.5 1.1 903 4.0
Miami-Dade, FL............................... 82.6 979.5 2.1 717 (6)
Private industry........................... 82.3 829.7 2.6 694 3.4
Natural resources and mining............. 0.5 8.0 6.7 437 0.9
Construction............................. 5.2 42.2 3.3 761 9.2
Manufacturing............................ 2.8 50.4 0.6 646 5.2
Trade, transportation, and utilities..... 24.0 240.4 0.5 664 3.9
Information.............................. 1.8 26.6 -3.1 1,021 9.8
Financial activities..................... 8.9 67.5 2.6 965 -0.4
Professional and business services....... 16.4 136.5 6.4 804 2.8
Education and health services............ 8.2 125.2 2.0 730 2.5
Leisure and hospitality.................. 5.6 94.6 5.7 403 3.6
Other services........................... 7.7 35.1 1.4 434 1.6
Government................................. 0.3 149.8 -0.6 849 (6)
1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs.
2 Data are preliminary.
3 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
4 Average weekly wages were calculated using unrounded data.
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 in the largest county by
state, third quarter 2004(2)
Employment Average weekly
wage(5)
Establishments,
third quarter
County(3) 2004 Percent Percent
(thousands) September change, Average change,
2004 September weekly third
(thousands) 2003-04(4) wage quarter
2003-04(4)
United States(6)......... 8,421.8 130,248.9 1.3 $733 4.0
Jefferson, AL............ 18.5 368.3 0.0 739 3.6
Anchorage Borough, AK.... 7.7 145.0 0.8 809 4.0
Maricopa, AZ............. 79.9 1,633.3 3.7 731 4.7
Pulaski, AR.............. 13.3 242.6 0.9 669 4.7
Los Angeles, CA.......... 360.1 4,019.6 0.7 833 4.9
Denver, CO............... 24.6 427.3 1.5 888 2.9
Hartford, CT............. 24.4 483.0 1.1 916 6.5
New Castle, DE........... 19.3 280.2 0.3 858 2.4
Washington, DC........... 30.1 658.3 1.2 1,207 7.6
Miami-Dade, FL........... 82.6 979.5 2.1 717 (7)
Fulton, GA............... 37.1 726.6 1.5 958 4.2
Honolulu, HI............. 23.2 426.7 2.7 703 4.6
Ada, ID.................. 13.2 190.6 3.9 675 4.5
Cook, IL................. 126.7 2,511.7 -0.3 871 4.3
Marion, IN............... 23.7 581.1 1.5 765 3.8
Polk, IA................. 14.2 261.5 1.8 740 4.7
Johnson, KS.............. 18.9 296.6 1.9 764 3.8
Jefferson, KY............ 21.6 417.1 0.0 726 5.5
Orleans, LA.............. 12.6 244.6 -1.6 677 1.5
Cumberland, ME........... 12.0 171.0 1.1 671 5.5
Montgomery, MD........... 31.5 450.6 0.5 953 6.2
Middlesex, MA............ 48.2 782.0 -0.5 1,043 4.6
Wayne, MI................ 35.0 791.2 -1.2 874 4.7
Hennepin, MN............. 40.5 827.3 0.8 933 2.6
Hinds, MS................ 6.6 130.2 0.1 651 4.0
St. Louis, MO............ 33.7 617.5 -0.1 778 1.4
Yellowstone, MT.......... 5.6 71.2 2.4 572 3.8
Douglas, NE.............. 14.9 309.4 0.5 702 3.4
Clark, NV................ 39.0 822.6 7.4 701 4.6
Hillsborough, NH......... 12.4 194.2 0.8 828 6.3
Bergen, NJ............... 34.3 447.7 0.2 910 2.9
Bernalillo, NM........... 16.5 315.6 1.5 665 2.6
New York, NY............. 112.7 2,201.7 0.8 1,327 7.0
Mecklenburg, NC.......... 27.2 507.2 0.5 838 1.8
Cass, ND................. 5.4 90.0 3.7 610 3.9
Cuyahoga, OH............. 38.2 759.8 0.0 776 4.9
Oklahoma, OK............. 21.7 408.3 1.9 645 3.2
Multnomah, OR............ 25.5 422.4 1.6 760 3.7
Allegheny, PA............ 35.6 687.2 -0.6 774 3.6
Providence, RI........... 17.8 288.5 0.0 731 5.2
Greenville, SC........... 12.1 221.1 0.5 663 3.3
Minnehaha, SD............ 6.0 109.4 1.7 624 5.6
Shelby, TN............... 19.8 495.9 0.1 787 6.8
Harris, TX............... 90.2 1,838.1 0.8 862 4.5
Salt Lake, UT............ 35.0 524.7 2.3 671 3.5
Chittenden, VT........... 5.7 96.4 2.1 725 5.1
Fairfax, VA.............. 29.8 548.5 4.8 1,068 2.5
King, WA................. 77.3 1,104.3 1.1 940 -2.4
Kanawha, WV.............. 6.2 107.7 -0.7 627 4.3
Milwaukee, WI............ 22.2 492.8 -1.3 750 5.6
Laramie, WY.............. 2.9 39.8 0.7 596 4.0
San Juan, PR............. 13.4 324.3 2.4 475 2.6
St. Thomas, VI........... 1.7 22.6 -0.5 565 3.9
1 Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs.
2 Data are preliminary.
3 Includes areas not officially designated as counties. See Technical Note.
4 Percent changes were computed from quarterly employment and pay data adjusted
for noneconomic county reclassifications. See Technical Note.
5 Average weekly wages were calculated using unrounded data.
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.
Table 4. Covered(1) establishments, employment, and wages by state,
third quarter 2004(2)
Employment Average weekly
wage(3)
Establishments,
third quarter
State 2004 Percent Percent
(thousands) September change, Average change,
2004 September weekly third
(thousands) 2003-04 wage quarter
2003-04
United States(4)......... 8,421.8 130,248.9 1.3 $733 4.0
Alabama.................. 114.4 1,858.0 1.8 629 3.6
Alaska................... 20.3 314.2 1.9 755 3.4
Arizona.................. 126.3 2,357.6 3.6 691 4.9
Arkansas................. 76.4 1,145.7 1.4 570 5.2
California............... 1,204.0 15,106.6 1.5 829 3.9
Colorado................. 164.8 2,163.4 1.8 752 1.1
Connecticut.............. 109.5 1,642.1 0.9 917 5.4
Delaware................. 29.1 414.9 2.0 769 2.1
District of Columbia..... 30.1 658.3 1.2 1,207 7.6
Florida.................. 529.1 7,397.2 2.5 655 4.5
Georgia.................. 249.2 3,837.8 0.8 711 3.8
Hawaii................... 35.7 585.6 2.9 676 4.5
Idaho.................... 49.6 608.1 3.0 569 4.0
Illinois................. 328.1 5,747.7 0.2 779 3.9
Indiana.................. 152.6 2,887.8 1.4 655 4.5
Iowa..................... 91.8 1,431.8 1.2 604 4.1
Kansas................... 82.4 1,304.8 1.2 620 4.6
Kentucky................. 106.6 1,742.9 0.8 619 4.4
Louisiana................ 116.7 1,861.1 0.1 595 2.8
Maine.................... 50.1 608.8 0.7 603 4.3
Maryland................. 155.0 2,479.5 1.2 795 4.2
Massachusetts............ 211.3 3,156.5 -0.4 907 5.5
Michigan................. 254.3 4,344.5 -0.3 757 3.4
Minnesota................ 158.1 2,629.9 1.0 753 3.2
Mississippi.............. 66.7 1,113.8 1.0 540 3.6
Missouri................. 167.8 2,656.2 0.9 655 3.0
Montana.................. 42.4 413.0 2.6 525 3.6
Nebraska................. 55.6 887.4 1.1 601 3.6
Nevada................... 63.5 1,168.5 6.5 703 4.1
New Hampshire............ 47.6 622.6 1.4 731 6.1
New Jersey............... 267.8 3,918.8 0.9 876 2.8
New Mexico............... 50.3 769.3 1.9 588 4.1
New York................. 556.3 8,307.9 0.9 891 5.3
North Carolina........... 229.9 3,814.9 1.9 654 4.1
North Dakota............. 24.3 327.2 2.0 548 4.0
Ohio..................... 288.3 5,333.0 0.4 685 4.1
Oklahoma................. 92.6 1,435.7 1.3 581 3.9
Oregon................... 120.5 1,627.6 2.5 676 3.7
Pennsylvania............. 330.9 5,531.4 0.7 722 4.3
Rhode Island............. 35.2 484.6 0.6 708 4.6
South Carolina........... 112.9 1,799.2 1.4 604 4.1
South Dakota............. 28.6 375.5 2.0 538 4.9
Tennessee................ 130.2 2,668.6 1.9 659 4.4
Texas.................... 511.6 9,357.6 1.4 719 3.6
Utah..................... 77.5 1,084.4 3.4 607 3.2
Vermont.................. 24.5 302.0 1.5 634 5.8
Virginia................. 206.5 3,522.7 2.7 757 4.6
Washington............... 213.0 2,749.9 1.7 756 0.4
West Virginia............ 47.8 693.1 1.4 559 5.1
Wisconsin................ 161.2 2,745.6 1.1 653 4.8
Wyoming.................. 22.6 253.6 1.5 590 5.0
Puerto Rico.............. 52.7 1,042.4 2.2 417 3.0
Virgin Islands........... 3.2 42.7 3.4 599 5.8
1 Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs.
2 Data are preliminary.
3 Average weekly wages were calculated using unrounded data.
4 Totals for the United States do not include data for Puerto Rico or the
Virgin Islands.