Technical information: (202) 691-6567

http://www.bls.gov/cew/

Media contact: 691-5902

USDL 06-638

For release: 10:00 A.M. EDT

Wednesday, April 12, 2006

COUNTY EMPLOYMENT AND WAGES: THIRD QUARTER 2005

In September 2005, Lee County, Fla., had the largest over-the-year percentage increase in employment

among the largest counties in the United States, according to preliminary data released today by the Bureau

of Labor Statistics of the U.S. Department of Labor. Lee County, which includes Fort Myers, experienced

an over-the-year employment gain of 11.4 percent, compared with national job growth of 2.0 percent.

Passaic County, N.J., an area north of Newark, had the largest over-the-year gain in average weekly wages

in the third quarter of 2005, with an increase of 19.0 percent. The U.S. average weekly wage increased by

6.1 percent over the same time span.

Of the 322 largest counties in the U.S., as measured by 2004 annual average employment, 136 had

over-the-year percentage growth in employment above the national average in September 2005, and 173

experienced changes below the national average. (See chart 1.) Average weekly wages grew faster than the

national average in 132 of the largest U.S. counties, while the percent change in average weekly wages was

below the national average in 173 counties. (See chart 2.)

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 employers subject to unemployment insurance (UI) laws. The 8.6 million employer reports cover 132.9 million full- and part-time workers. The attached tables and charts contain data for the

 Hurricanes Katrina and Rita

The measures of employment and wages reported in this news release reflect the impact of Hurricane Katrina and ongoing labor market trends. Hurricane Katrina hit the Gulf

Coast on August 29, 2005, with catastrophic effects in parts of Louisiana, Mississippi, and

Alabama. This event occurred after the August QCEW reference period and before the

September period. Its effects are first reflected in the September QCEW employment counts

and the wage totals for the third quarter of 2005. QCEW nonresponse adjustment methods

were modified for September 2005 to better reflect the impact of the hurricane in parts of

Louisiana and Mississippi. For more information, see the QCEW section of the Katrina

coverage on the BLS Web site (http://www.bls.gov/katrina/qcewquestions.htm).

Hurricane Rita made landfall September 24, after the September reference period. The

impact of this event did not warrant changes to QCEW methodology for the third quarter of

2005.
2

Los Angeles, Calif. 4,105 Maricopa, Ariz. 105.5 Lee, Fla. 11.4

Cook, Ill. 2,529 Los Angeles, Calif. 72.1 Seminole, Fla. 10.7

New York, N.Y. 2,243 Harris, Texas 61.9 Collier, Fla. 8.2

Harris, Texas 1,882 Clark, Nev. 58.7 Kern, Calif. 7.6

Maricopa, Ariz. 1,735 Broward, Fla. 44.9 Lake, Fla. 7.4

Orange, Calif. 1,498 Orange, Fla. 40.0 Volusia, Fla. 7.4

Dallas, Texas 1,431 New York, N.Y. 37.0 Clark, Nev. 7.1

San Diego, Calif. 1,301 Miami-Dade, Fla. 32.0 Polk, Fla. 6.9

King, Wash. 1,129 Orange, Calif. 31.6 Maricopa, Ariz. 6.5

Miami-Dade, Fla. 1,003 San Bernardino, Calif. 31.1 Broward, Fla. 6.5

Employment in large counties

September 2005 employment

 (thousands)

 Growth in employment,

 September 2004-05

 (thousands)

Percent growth in employment,

 September 2004-05

U.S. 132,929.3 U.S. 2,614.4 U.S. 2.0

nation and for the 322 U.S. counties with annual average employment levels of 75,000 or more in 2004.

September 2005 employment and 2005 third-quarter average weekly wages for all states are provided in

table 4 of this release. Final data for all states, metropolitan statistical areas, counties, and the nation through

the fourth quarter of 2004 are available on the BLS Web site at http://www.bls.gov/cew/. Preliminary data

for first, second, and third quarters of 2005 will be available later in April on the BLS Web site.

Large County Employment

In September 2005, national employment, as measured by the QCEW program, was 132.9 million, up

by 2.0 percent from September 2004. The 322 U.S. counties with 75,000 or more employees accounted

for 70.6 percent of total U.S. covered employment and 76.4 percent of total covered wages. These 322

counties had a net job gain of 1,776,000 over the year, accounting for 67.9 percent of the U.S. employment increase. Employment increased in 275 of the large counties from September 2004 to September

2005. Lee County, Fla., had the largest over-the-year percentage increase in employment (11.4 percent).

Seminole, Fla., had the next largest increase, 10.7 percent, followed by the counties of Collier, Fla. (8.2

percent), Kern, Calif. (7.6 percent), and Lake and Volusia, Fla. (7.4 percent each). (See table 1.)

Employment declined in 35 large counties from September 2004 to September 2005. The largest percentage decline in employment was in Orleans County, La. (-26.3 percent), followed by the counties of

Jefferson, La. (-25.6 percent), and Harrison, Miss. (-13.9 percent). Employment losses in these three Gulf

Coast counties reflected the devastation caused by Hurricane Katrina. Hinds, Miss., located farther inland

and within 100 miles of the path of Katrina, had the next largest employment decline (-2.1 percent). Winnebago, Ill., followed with a 1.4 percent decline.

The largest gains in employment from September 2004 to September 2005 were recorded in the counties

of Maricopa, Ariz. (105,500), Los Angeles, Calif. (72,100), Harris, Texas (61,900), Clark, Nev. (58,700),

and Broward, Fla. (44,900). (See table A.)

The largest decline in employment occurred in Orleans County, La. (-63,600), followed by the counties

of Jefferson, La. (-54,400), Harrison, Miss. (-12,500), Wayne, Mich. (-9,900), and Hinds, Miss. (-2,700).

Table A. Top 10 counties ranked by September 2005 employment, September 2004-05 employment

growth, and September 2004-05 percent growth in employment
3

New York, N.Y. $1,419 Passaic, N.J. $148 Passaic, N.J. 19.0

Santa Clara, Calif. 1,403 San Mateo, Calif. 143 Fort Bend, Texas 15.4

Arlington, Va. 1,292 Boulder, Colo. 120 Boulder, Colo. 13.8

San Mateo, Calif. 1,268 Fairfax, Va. 117 San Mateo, Calif. 12.7

Washington, D.C. 1,265 Fort Bend, Texas 115 Harrison, Miss. 12.7

San Francisco, Calif. 1,219 San Francisco, Calif. 108 Fairfax, Va. 10.9

Suffolk, Mass. 1,198 Santa Clara, Calif. 95 Ventura, Calif. 10.7

Fairfield, Conn. 1,197 New York, N.Y. 93 Orleans, La. 10.7

Fairfax, Va. 1,188 Arlington, Va. 92 Montgomery, Texas 10.5

Somerset, N.J. 1,148 Alameda, Calif. 83 Collier, Fla. 10.4

Marin, Calif. 83

Ventura, Calif. 83

U.S. $777 U.S. $45 U.S. 6.1

Average weekly wage in large counties

 Average weekly wage,

 third quarter 2005

 Percent growth in average

 weekly wage, third

 quarter 2004-05

 Growth in average weekly

 wage, third quarter 2004-05

Table B. Top 10 counties ranked by third quarter 2005 average weekly wages, third quarter

2004-05 growth in average weekly wages, and third quarter 2004-05 percent growth in average

weekly wages

Large County Average Weekly Wages

The national average weekly wage in the third quarter of 2005 was $777. Average weekly wages were

higher than the national average in 115 of the largest 322 U.S. counties. New York County, N.Y., held the

top position among the highest-paid large counties with an average weekly wage of $1,419. Santa Clara,

Calif., was second with an average weekly wage of $1,403, followed by Arlington, Va. ($1,292), San Mateo,

Calif. ($1,268), and Washington, D.C. ($1,265). (See table B.)

There were 206 counties with an average weekly wage below the national average in the third quarter of

2005. The lowest average weekly wages were reported in Cameron County, Texas ($486), followed by the

counties of Hidalgo, Texas ($499), Horry, S.C. ($505), and Webb, Texas, and Yakima, Wash. ($525

each). (See table 1.)

Over the year, the national average weekly wage rose by 6.1 percent. Among the largest counties,

Passaic, N.J., led the nation in growth in average weekly wages, with an increase of 19.0 percent from the

third quarter of 2004. Fort Bend, Texas, was second with 15.4 percent growth, followed by the counties

of Boulder, Colo. (13.8 percent), and San Mateo, Calif., and Harrison, Miss. (12.7 percent each). The

average weekly wage growth rate for Harrison, Miss., and the 10.7 percent wage gain for Orleans, La.,

were boosted as a result of the disproportionate job and pay losses in lower-paid industries following

Hurricane Katrina.

Five counties experienced over-the-year declines in average weekly wages. Clayton County, Ga., had

the largest decrease, -5.1 percent, followed by the counties of Benton, Ark. (-1.2 percent), Trumbull, Ohio

(-0.6 percent), Saginaw, Mich. (-0.4 percent), and St. Joseph, Ind. (-0.1 percent).
4

Ten Largest U.S. Counties

Of the 10 largest U.S. counties (based on 2004 annual average employment levels), all reported increases in employment from September 2004 to September 2005. Maricopa County, Ariz., experienced

the fastest growth in employment among the largest counties, with a 6.5 percent increase. Within Maricopa

County, employment rose in every industry group except information. The largest gains were in construction

(15.0 percent) and professional and business services (8.2 percent). (See table 2.) Harris, Texas, had the

next largest increase in employment, 3.4 percent, followed by Miami-Dade, Fla. (3.3 percent). The smallest

employment gains occurred in Cook County, Ill. (0.7 percent), followed by the counties of San Diego, Calif.

(1.6 percent), and New York, N.Y. (1.7 percent).

All of the 10 largest U.S. counties saw over-the-year increases in average weekly wages. Miami-Dade,

Fla., had the fastest growth in wages among the 10 largest counties, 8.9 percent. Within Miami-Dade

County, wages increased the most in government (13.2 percent) and manufacturing (11.2 percent). Maricopa, Ariz., was second in wage growth, with a gain of 8.1 percent, followed by Harris County, Texas (7.8

percent). The smallest wage gains among the 10 largest counties occurred in Los Angeles, Calif., and Cook,

Ill. (5.5 percent each), followed by Dallas County, Texas (6.6 percent).

Largest County by State

Table 3 shows September 2005 employment and the 2005 third-quarter average weekly wage in the

largest county in each state (based on 2004 annual average employment levels). (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 2005 ranged from approximately 4.1 million in Los

Angeles County, Calif., to 41,000 in Laramie County, Wyo. The highest average weekly wage of these

counties was in New York, N.Y. ($1,419), while the lowest average weekly wage was in Yellowstone,

Mont. ($619).

For More Information

For additional information about the quarterly employment and wages data, please read the Technical

Note or visit the QCEW Web site at http://www.bls.gov/cew/. Additional information about the QCEW

data also may be obtained by e-mailing QCEWinfo@bls.gov or by calling (202) 691-6567.

 Regional Quarterly Census of Employment and Wages News Releases

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.
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. Data for 2005 are preliminary

and subject to revision.

For purposes of this release, large counties are defined as

having employment levels of 75,000 or greater. In addition,

data for San Juan, Puerto Rico, are provided, 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 preliminary annual average of employment for the

previous year. The 323 counties presented in this release were

derived using 2004 preliminary annual averages of

employment. All of the 318 counties that were published in the

2004 releases are included in the 2005 releases. The following

counties grew enough in 2004 to be included in the 2005

releases: Lake, Fla., Wyandotte, Kan., Harford, Md.,

Washington, Pa., and Whatcom, Wash. These counties will be

included in all 2005 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

Source Count of UI administrative records Count of longitudinally-linked UI Sample survey: 400,000 establishsubmitted by 8.6 million establish- administrative records submitted by ments

ments 6.7 million private-sector employers

Coverage UI and UCFE coverage, including UI coverage, excluding govern- Nonfarm wage and salary jobs:

all employers subject to state and ment, private households, and estab- UI coverage, excluding agriculture,

federal UI laws lishments with zero employment private households, and self-employed workers

Other employment, including railroads, religious organizations, and

other non-UI-covered jobs

Publication Quarterly Quarterly Monthly

frequency - 7 months after the end of each - 8 months after the end of each - Usually first Friday of following

quarter quarter month

Use of UI file Directly summarizes and pub- Links each new UI quarter to Uses UI file as a sampling frame

 lishes each new quarter of UI longitudinal database and directly and annually realigns (benchmarks)

 data summarizes gross job gains sample estimates to first quarter

 and losses

Principal Provides a quarterly and annual Provides quarterly employer dy- Provides current monthly estimates

products universe count of estab- namics data on establishment open- of employment, hours, and earnings

lishments, employment, and ings, closings, expansions, and con- at the MSA, state, and national levwages at the county, MSA, tractions at the national level by el by industry

state, and national levels by NAICS supersectors and by size

detailed industry of firm

Future expansions will include data

at the county, MSA, and state level

Principal uses Major uses include: Major uses include: Major uses include:

- Detailed locality data - Business cycle analysis - Principal national economic

- Periodic universe counts for - Analysis of employer dynamics indicator

benchmarking sample survey underlying economic expansions - Official time series for

estimates and contractions employment change measures

- Sample frame for BLS - Analysis of employment expan- - Input into other major economic

establishment surveys sion and contraction by size of indicators

firm

Program www.bls.gov/cew/ www.bls.gov/bdm/ www.bls.gov/ces/

Web sites

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Summary of Major Differences between QCEW, BED, and CES Employment Measures

 QCEW BED CES

•

UI levels
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 differences and the

intended uses of the program products. (See table on the

previous page.) Additional information on each program can

be obtained from the program Web sites shown in the table on

the previous page.

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 civilian workers

covered by the Unemployment Compensation for Federal

Employees (UCFE) program, employment and wage data are

compiled from quarterly reports that are sent to the appropriate

SWA by the specific federal agency. 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 reports 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 2004, UI and UCFE programs covered

workers in 129.3 million jobs. The estimated 124.4 million

workers in these jobs (after adjustment for multiple jobholders)

represented 96.6 percent of civilian wage and salary employment. Covered workers received $5.088 trillion in pay,

representing 94.4 percent of the wage and salary component of

personal income and 43.4 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.

Coverage changes may affect the over-the-year comparisons

presented in this news release. Beginning with the first quarter

of 2005, Oregon implemented a change in their state UI laws.

This change extended UI coverage to providers of home care

for the elderly. These providers are now considered state

workers for purposes of UI benefits.

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

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.

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 highpaying 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 weekly wage levels between industries,

states, or quarters, these factors should be taken into

consideration.

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 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 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 concentrations 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 ownership classification of all

establishments on a 3-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 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 calculated using an adjusted version of the final

2004 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 prioryear 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. Included 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. The adjusted data do not 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 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 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 detailed industry on establishments, employment, and wages for the nation and all

states. The 2004 edition of this bulletin contains selected data

produced by Business Employment Dynamics (BED) on job

gains and losses, as well as selected data from the fourth

quarter 2004 version of this news release. Employment and

Wages Annual Averages, 2004 is now available for sale from

the United States Government Printing Office, Superintendent

of Documents, P.O. Box 371954, Pittsburgh, PA 15250,

telephone 866-512-1800, outside of Washington, D.C. Within

Washington, D.C., the telephone number is 202-512-1800. The

fax number is 202-512-2104. Also, the 2004 bulletin is available

in a portable document format (PDF) on the BLS Web site at

http://www.bls.gov/cew/cewbultn04.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. Covered1 establishments, employment, and wages in the 323 largest counties,

third quarter 20052

County3

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage5

September

2005

(thousands)

Percent

change,

September

2004-054

Ranking by

percent

change

Average

weekly

wage

Percent

change,

third quarter

2004-054

Ranking by

percent

change

United States6 .................... 8,634.7 132,929.3 2.0 - $777 6.1 - 

Jefferson, AL ...................... 18.8 372.8 1.3 186 796 7.7 51

Madison, AL ....................... 8.2 169.6 2.5 103 847 9.3 14

Mobile, AL .......................... 9.8 166.4 3.2 72 638 6.2 126

Montgomery, AL ................ 6.7 136.0 3.3 67 658 6.3 120

Tuscaloosa, AL .................. 4.2 81.9 4.4 43 655 6.7 98

Anchorage Borough, AK .... 7.9 148.0 1.9 141 857 5.8 153

Maricopa, AZ ..................... 84.3 1,735.0 6.5 9 790 8.1 35

Pima, AZ ............................ 18.3 356.9 3.6 61 697 8.7 23

Benton, AR ........................ 4.9 90.8 5.3 22 673 -1.2 313

Pulaski, AR ........................ 13.5 245.7 1.3 186 709 6.1 133

Washington, AR ................. 5.3 91.3 5.0 28 634 5.3 194

Alameda, CA ...................... 47.5 681.8 0.3 256 1,053 8.6 26

Contra Costa, CA ............... 27.1 343.1 0.5 243 973 5.6 168

Fresno, CA ......................... 28.6 354.6 1.7 155 616 3.9 266

Kern, CA ............................ 16.4 280.5 7.6 4 658 (7) - 

Los Angeles, CA ................ 370.3 4,105.4 1.8 150 879 5.5 174

Marin, CA ........................... 11.5 110.2 0.6 237 988 9.2 15

Monterey, CA ..................... 11.8 179.8 0.2 265 687 6.7 98

Orange, CA ........................ 90.3 1,497.5 2.2 122 907 7.1 71

Placer, CA .......................... 9.7 134.8 (7) - 783 (7) - 

Riverside, CA ..................... 39.9 610.6 5.3 22 680 7.1 71

Sacramento, CA ................ 47.6 630.6 2.6 99 878 7.9 42

San Bernardino, CA ........... 43.0 637.2 5.1 25 698 6.6 105

San Diego, CA ................... 87.6 1,301.3 1.6 164 855 7.3 60

San Francisco, CA ............. 42.8 528.9 1.4 176 1,219 9.7 12

San Joaquin, CA ................ 16.1 224.8 1.0 209 686 6.0 142

San Luis Obispo, CA ......... 8.7 104.4 1.5 167 655 3.8 271

San Mateo, CA .................. 22.4 329.0 0.3 256 1,268 12.7 4

Santa Barbara, CA ............. 13.1 186.1 2.3 114 751 7.1 71

Santa Clara, CA ................. 52.7 864.2 1.7 155 1,403 7.3 60

Santa Cruz, CA .................. 8.4 100.4 0.1 271 750 9.8 11

Solano, CA ......................... 9.5 131.7 1.7 155 753 8.7 23

Sonoma, CA ...................... 17.1 193.4 -0.2 287 772 5.5 174

Stanislaus, CA ................... 13.2 177.9 1.5 167 671 5.8 153

Tulare, CA .......................... 8.4 144.1 5.1 25 556 5.3 194

Ventura, CA ....................... 20.7 312.5 2.0 137 861 10.7 7

Yolo, CA ............................. 5.2 100.7 1.2 192 784 6.7 98

Adams, CO ........................ 9.1 150.2 3.0 83 755 6.9 86

Arapahoe, CO .................... 19.6 273.0 1.6 164 935 7.3 60

Boulder, CO ....................... 12.4 155.5 2.1 130 989 13.8 3

Denver, CO ........................ 25.1 429.4 1.7 155 947 6.6 105

El Paso, CO ....................... 16.9 241.9 2.2 122 741 6.5 111

Jefferson, CO ..................... 18.8 208.0 2.0 137 810 6.0 142

Larimer, CO ....................... 9.8 127.3 2.1 130 722 4.6 240

Fairfield, CT ....................... 32.2 413.7 0.9 221 1,197 5.7 159

Hartford, CT ....................... 24.6 488.6 1.2 192 968 5.6 168

New Haven, CT ................. 22.2 361.9 0.0 276 845 4.2 258

New London, CT ................ 6.7 130.6 0.8 227 812 6.6 105

New Castle, DE ................. 19.8 281.2 0.3 256 921 7.5 56

Washington, DC ................. 30.7 666.4 0.8 227 1,265 4.5 244

See footnotes at end of table.
Table 1. Covered1 establishments, employment, and wages in the 323 largest counties,

third quarter 20052 — Continued

County3

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage5

September

2005

(thousands)

Percent

change,

September

2004-054

Ranking by

percent

change

Average

weekly

wage

Percent

change,

third quarter

2004-054

Ranking by

percent

change

Alachua, FL ........................ 6.2 124.4 (7) - $665 (7) - 

Brevard, FL ........................ 13.9 204.1 5.4 19 746 2.1 301

Broward, FL ....................... 61.6 738.1 6.5 9 746 6.9 86

Collier, FL .......................... 11.7 125.1 8.2 3 722 10.4 10

Duval, FL ........................... 24.6 452.7 4.9 32 765 6.8 93

Escambia, FL ..................... 7.6 127.2 2.9 86 632 8.2 33

Hillsborough, FL ................. 34.5 626.2 4.1 48 745 7.3 60

Lake, FL ............................. 6.4 80.7 7.4 5 600 8.9 21

Lee, FL ............................... 17.4 214.0 11.4 1 685 7.9 42

Leon, FL ............................. 7.8 148.8 3.2 72 679 7.8 47

Manatee, FL ....................... 8.2 122.5 5.6 17 624 9.1 18

Marion, FL .......................... 7.5 98.7 (7) - 580 (7) - 

Miami-Dade, FL ................. 84.4 1,003.2 3.3 67 781 8.9 21

Okaloosa, FL ..................... 6.0 83.6 6.0 15 642 9.6 13

Orange, FL ......................... 32.6 665.8 6.4 11 729 6.9 86

Palm Beach, FL ................. 47.2 546.3 (7) - 768 6.7 98

Pasco, FL ........................... 8.6 94.2 (7) - 565 (7) - 

Pinellas, FL ........................ 30.4 441.9 1.5 167 687 7.7 51

Polk, FL .............................. 11.7 201.8 6.9 8 629 4.8 223

Sarasota, FL ...................... 14.7 158.9 3.8 54 679 9.2 15

Seminole, FL ...................... 13.6 171.5 10.7 2 699 7.0 79

Volusia, FL ......................... 13.3 164.3 7.4 5 571 3.6 279

Bibb, GA ............................ 4.7 85.1 -1.2 305 653 4.5 244

Chatham, GA ..................... 7.2 132.0 2.6 99 674 7.2 68

Clayton, GA ....................... 4.4 109.6 3.3 67 765 -5.1 314

Cobb, GA ........................... 20.2 313.1 4.5 41 857 7.1 71

De Kalb, GA ....................... 17.0 291.5 1.1 202 843 7.3 60

Fulton, GA .......................... 38.0 744.4 2.2 122 1,007 4.9 218

Gwinnett, GA ..................... 22.3 319.7 3.6 61 828 6.0 142

Muscogee, GA ................... 4.8 98.7 2.3 114 627 6.6 105

Richmond, GA ................... 4.8 104.6 1.9 141 667 6.4 115

Honolulu, HI ....................... 23.8 441.7 3.2 72 740 5.3 194

Ada, ID ............................... 13.9 201.2 5.4 19 719 6.4 115

Champaign, IL ................... 4.0 91.4 1.2 192 670 3.2 289

Cook, IL ............................. 131.0 2,529.4 0.7 232 920 5.5 174

Du Page, IL ........................ 33.7 587.8 1.5 167 913 7.0 79

Kane, IL ............................. 11.6 208.0 2.8 88 732 6.1 133

Lake, IL .............................. 19.6 329.9 0.6 237 909 3.9 266

McHenry, IL ....................... 7.8 99.6 2.7 94 694 4.8 223

McLean, IL ......................... 3.5 85.8 1.9 141 760 8.6 26

Madison, IL ........................ 5.8 94.2 0.2 265 648 5.5 174

Peoria, IL ........................... 4.6 100.6 2.4 109 753 8.5 30

Rock Island, IL ................... 3.4 79.9 1.9 141 755 5.6 168

St. Clair, IL ......................... 5.2 94.3 0.4 252 641 6.3 120

Sangamon, IL .................... 5.2 131.8 0.6 237 767 4.8 223

Will, IL ................................ 11.7 172.4 3.2 72 727 4.2 258

Winnebago, IL .................... 6.7 136.4 -1.4 309 685 (7) - 

Allen, IN ............................. 8.7 182.7 0.7 232 683 4.0 263

Elkhart, IN .......................... 4.8 126.8 0.3 256 687 4.4 248

Hamilton, IN ....................... 6.6 96.9 4.3 44 795 4.7 232

See footnotes at end of table.
Table 1. Covered1 establishments, employment, and wages in the 323 largest counties,

third quarter 20052 — Continued

County3

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage5

September

2005

(thousands)

Percent

change,

September

2004-054

Ranking by

percent

change

Average

weekly

wage

Percent

change,

third quarter

2004-054

Ranking by

percent

change

Lake, IN ............................. 10.0 195.6 1.0 209 $700 4.5 244

Marion, IN .......................... 23.5 584.0 0.5 243 819 7.1 71

St. Joseph, IN .................... 6.0 126.7 -0.5 297 666 -0.1 310

Vanderburgh, IN ................ 4.8 108.5 1.0 209 676 7.5 56

Linn, IA ............................... 6.1 118.3 1.7 155 763 8.1 35

Polk, IA .............................. 14.2 265.6 1.9 141 792 6.9 86

Scott, IA ............................. 5.1 89.9 3.9 52 641 6.3 120

Johnson, KS ...................... 19.4 302.9 1.7 155 823 7.9 42

Sedgwick, KS ..................... 11.8 244.0 0.7 232 727 5.7 159

Shawnee, KS ..................... 4.7 94.0 -0.8 300 673 8.0 39

Wyandotte, KS ................... 3.2 78.3 1.2 192 764 2.3 299

Fayette, KY ........................ 8.8 169.8 2.4 109 711 3.8 271

Jefferson, KY ..................... 21.6 425.3 1.4 176 761 5.5 174

Caddo, LA .......................... 7.2 124.1 2.3 114 647 5.4 188

Calcasieu, LA ..................... 4.8 85.0 4.7 35 654 9.0 19

East Baton Rouge, LA ....... 13.3 256.2 4.8 34 653 5.2 203

Jefferson, LA ...................... 14.3 158.3 -25.6 312 656 6.0 142

Lafayette, LA ...................... 7.9 125.1 6.2 13 680 6.8 93

Orleans, LA ........................ 12.9 178.2 -26.3 313 742 10.7 7

Cumberland, ME ................ 11.7 171.3 -0.1 279 710 6.0 142

Anne Arundel, MD ............. 14.0 224.3 2.2 122 817 6.8 93

Baltimore, MD .................... 21.0 374.1 1.4 176 808 7.3 60

Frederick, MD .................... 5.7 92.5 2.2 122 748 7.0 79

Harford, MD ....................... 5.4 81.5 2.5 103 754 9.0 19

Howard, MD ....................... 8.2 140.0 2.5 103 921 8.0 39

Montgomery, MD ............... 32.0 462.4 2.6 99 1,027 8.0 39

Prince Georges, MD .......... 15.4 316.0 0.4 252 869 6.2 126

Baltimore City, MD ............. 13.9 352.1 0.3 256 908 8.1 35

Barnstable, MA .................. 9.6 99.3 0.0 276 664 4.9 218

Bristol, MA ......................... 16.0 221.0 0.2 265 695 3.4 285

Essex, MA .......................... 21.4 296.7 0.1 271 848 7.1 71

Hampden, MA .................... 14.8 201.7 1.4 176 731 3.8 271

Middlesex, MA ................... 49.8 791.8 0.9 221 1,110 6.5 111

Norfolk, MA ........................ 22.6 319.5 0.6 237 923 4.3 255

Plymouth, MA .................... 14.3 178.5 1.4 176 748 3.6 279

Suffolk, MA ........................ 22.9 566.3 1.5 167 1,198 1.6 307

Worcester, MA ................... 21.1 318.6 -0.5 297 799 2.3 299

Genesee, MI ...................... 8.4 149.9 (7) - 736 1.1 308

Ingham, MI ......................... 7.1 163.8 (7) - 741 2.9 292

Kalamazoo, MI ................... 5.5 117.9 0.8 227 708 3.4 285

Kent, MI ............................. 14.6 347.1 2.9 86 721 2.7 295

Macomb, MI ....................... 18.2 332.4 1.1 202 849 4.0 263

Oakland, MI ....................... 40.8 720.6 -0.1 279 935 4.7 232

Ottawa, MI ......................... 5.8 115.3 0.2 265 705 4.9 218

Saginaw, MI ....................... 4.5 89.8 (7) - 689 -0.4 311

Washtenaw, MI .................. 8.2 194.1 -1.0 303 891 5.3 194

Wayne, MI .......................... 34.2 789.3 -1.2 305 910 4.8 223

Anoka, MN ......................... 7.8 115.6 1.8 150 751 2.0 302

Dakota, MN ........................ 10.3 171.8 0.6 237 777 4.4 248

Hennepin, MN .................... 41.9 837.8 1.4 176 990 6.1 133

See footnotes at end of table.
Table 1. Covered1 establishments, employment, and wages in the 323 largest counties,

third quarter 20052 — Continued

County3

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage5

September

2005

(thousands)

Percent

change,

September

2004-054

Ranking by

percent

change

Average

weekly

wage

Percent

change,

third quarter

2004-054

Ranking by

percent

change

Olmsted, MN ...................... 3.5 89.4 1.4 176 $854 3.1 291

Ramsey, MN ...................... 15.5 334.1 1.2 192 864 5.6 168

St. Louis, MN ..................... 5.9 95.0 0.0 276 655 3.5 283

Stearns, MN ....................... 4.4 78.3 1.9 141 628 3.5 283

Harrison, MS ...................... 4.6 77.8 -13.9 311 586 12.7 4

Hinds, MS .......................... 6.5 126.9 -2.1 310 689 5.5 174

Boone, MO ......................... 4.4 81.4 4.2 46 615 5.3 194

Clay, MO ............................ 5.0 87.9 1.0 209 761 8.6 26

Greene, MO ....................... 8.0 150.9 3.5 63 623 5.2 203

Jackson, MO ...................... 18.7 364.2 0.3 256 794 4.6 240

St. Charles, MO ................. 7.6 118.7 2.8 88 682 5.6 168

St. Louis, MO ..................... 33.8 622.5 1.0 209 828 6.4 115

St. Louis City, MO .............. 8.1 224.2 -0.1 279 869 7.7 51

Douglas, NE ....................... 15.2 310.3 0.5 243 741 5.6 168

Lancaster, NE .................... 7.8 154.3 0.6 237 653 5.3 194

Clark, NV ........................... 42.3 883.1 7.1 7 752 7.3 60

Washoe, NV ....................... 13.3 217.1 3.8 54 747 4.8 223

Hillsborough, NH ................ 12.3 197.6 1.7 155 854 3.3 288

Rockingham, NH ................ 10.8 138.8 1.3 186 784 6.1 133

Atlantic, NJ ......................... 6.7 149.3 1.1 202 698 4.5 244

Bergen, NJ ......................... 34.2 450.2 0.5 243 964 5.9 149

Burlington, NJ .................... 11.3 200.5 0.5 243 853 7.8 47

Camden, NJ ....................... 13.5 210.8 0.5 243 804 7.9 42

Essex, NJ ........................... 21.3 358.4 0.7 232 998 5.3 194

Gloucester, NJ ................... 6.3 105.2 4.0 49 712 4.7 232

Hudson, NJ ........................ 14.1 239.1 1.5 167 1,024 4.0 263

Mercer, NJ ......................... 10.9 223.6 2.8 88 987 5.2 203

Middlesex, NJ .................... 20.8 392.4 -0.1 279 960 2.0 302

Monmouth, NJ ................... 20.2 257.8 1.2 192 828 5.1 209

Morris, NJ .......................... 17.9 283.7 -0.1 279 1,086 5.2 203

Ocean, NJ .......................... 11.7 150.4 1.0 209 669 7.7 51

Passaic, NJ ........................ 12.6 176.3 -0.2 287 929 19.0 1

Somerset, NJ ..................... 10.1 171.3 3.2 72 1,148 4.4 248

Union, NJ ........................... 14.9 226.7 (7) - 977 (7) - 

Bernalillo, NM .................... 16.5 323.4 2.6 99 707 6.2 126

Albany, NY ......................... 9.7 229.3 0.2 265 804 1.9 305

Bronx, NY .......................... 15.7 221.2 1.9 141 772 2.8 294

Broome, NY ....................... 4.5 94.8 0.4 252 623 3.7 275

Dutchess, NY ..................... 8.1 117.5 -0.1 279 783 5.5 174

Erie, NY ............................. 23.4 457.2 -0.4 293 690 3.9 266

Kings, NY ........................... 42.8 457.5 2.2 122 686 3.2 289

Monroe, NY ........................ 17.8 382.7 0.8 227 766 2.0 302

Nassau, NY ........................ 51.6 597.8 0.4 252 862 (7) - 

New York, NY .................... 114.3 2,243.4 1.7 155 1,419 7.0 79

Oneida, NY ........................ 5.4 108.9 0.2 265 613 4.1 260

Onondaga, NY ................... 12.8 251.7 1.0 209 718 3.9 266

Orange, NY ........................ 9.6 129.6 0.9 221 670 5.5 174

Queens, NY ....................... 40.8 484.6 1.3 186 794 5.7 159

Richmond, NY .................... 8.2 89.7 0.8 227 709 2.5 298

Rockland, NY ..................... 9.5 112.4 1.6 164 806 4.8 223

See footnotes at end of table.
Table 1. Covered1 establishments, employment, and wages in the 323 largest counties,

third quarter 20052 — Continued

County3

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage5

September

2005

(thousands)

Percent

change,

September

2004-054

Ranking by

percent

change

Average

weekly

wage

Percent

change,

third quarter

2004-054

Ranking by

percent

change

Suffolk, NY ......................... 48.8 609.8 0.3 256 $836 5.0 213

Westchester, NY ................ 35.9 411.9 0.3 256 1,005 4.1 260

Buncombe, NC .................. 7.1 109.7 2.1 130 613 4.8 223

Catawba, NC ..................... 4.3 86.0 -1.1 304 611 3.7 275

Cumberland, NC ................ 5.8 117.0 3.2 72 614 5.5 174

Durham, NC ....................... 6.2 170.1 1.8 150 1,019 6.8 93

Forsyth, NC ........................ 8.5 180.3 1.7 155 763 0.7 309

Guilford, NC ....................... 13.6 272.5 1.2 192 710 5.5 174

Mecklenburg, NC ............... 27.7 527.4 3.7 58 894 6.9 86

New Hanover, NC .............. 6.6 97.7 4.6 37 639 7.0 79

Wake, NC .......................... 24.0 409.9 4.3 44 778 6.3 120

Cass, ND ........................... 5.7 93.0 3.3 67 648 6.2 126

Butler, OH .......................... 7.1 139.0 2.4 109 703 5.7 159

Cuyahoga, OH ................... 38.1 755.8 0.1 271 802 3.4 285

Franklin, OH ....................... 29.2 686.1 1.1 202 802 8.5 30

Hamilton, OH ..................... 24.5 541.6 -0.4 293 862 7.1 71

Lake, OH ............................ 6.9 100.8 1.1 202 657 3.8 271

Lorain, OH ......................... 6.3 102.0 -1.3 307 698 7.9 42

Lucas, OH .......................... 10.9 227.7 -0.1 279 707 5.7 159

Mahoning, OH .................... 6.5 108.4 1.3 186 590 3.7 275

Montgomery, OH ............... 13.2 282.3 -0.8 300 747 5.7 159

Stark, OH ........................... 9.3 167.4 0.1 271 634 6.6 105

Summit, OH ....................... 15.0 273.9 1.5 167 729 4.4 248

Trumbull, OH ..................... 4.8 84.0 -0.1 279 684 -0.6 312

Oklahoma, OK ................... 22.5 415.7 1.5 167 685 6.4 115

Tulsa, OK ........................... 18.6 334.0 4.2 46 701 5.7 159

Clackamas, OR .................. 12.0 145.1 4.6 37 739 7.3 60

Jackson, OR ...................... 6.5 84.8 4.0 49 600 5.1 209

Lane, OR ........................... 10.6 147.3 3.7 58 633 5.9 149

Marion, OR ........................ 9.0 139.6 2.8 88 613 5.5 174

Multnomah, OR .................. 26.2 430.5 2.4 109 798 5.3 194

Washington, OR ................ 15.2 237.7 4.0 49 943 7.2 68

Allegheny, PA .................... 35.0 682.9 -0.3 292 811 4.6 240

Berks, PA ........................... 9.0 165.5 1.8 150 705 5.4 188

Bucks, PA .......................... 20.5 262.3 1.3 186 757 6.5 111

Chester, PA ....................... 15.1 231.7 2.3 114 986 8.2 33

Cumberland, PA ................ 5.8 125.8 -0.2 287 748 6.3 120

Dauphin, PA ....................... 7.2 177.3 0.9 221 780 5.8 153

Delaware, PA ..................... 13.6 208.6 0.1 271 813 2.9 292

Erie, PA .............................. 7.2 129.6 1.2 192 626 5.2 203

Lackawanna, PA ................ 5.7 100.6 2.1 130 617 4.9 218

Lancaster, PA .................... 11.9 229.7 1.5 167 696 6.1 133

Lehigh, PA ......................... 8.4 175.5 1.0 209 762 5.0 213

Luzerne, PA ....................... 7.9 144.3 1.0 209 627 4.7 232

Montgomery, PA ................ 28.0 483.5 1.1 202 956 5.5 174

Northampton, PA ............... 6.2 95.5 3.0 83 696 4.3 255

Philadelphia, PA ................ 29.1 633.9 0.9 221 921 6.0 142

Washington, PA ................. 5.4 76.3 0.7 232 675 6.5 111

Westmoreland, PA ............. 9.6 140.4 1.0 209 642 7.5 56

York, PA ............................. 8.8 173.4 2.1 130 705 6.0 142

See footnotes at end of table.
Table 1. Covered1 establishments, employment, and wages in the 323 largest counties,

third quarter 20052 — Continued

County3

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage5

September

2005

(thousands)

Percent

change,

September

2004-054

Ranking by

percent

change

Average

weekly

wage

Percent

change,

third quarter

2004-054

Ranking by

percent

change

Kent, RI .............................. 5.7 82.7 1.2 192 $715 6.1 133

Providence, RI ................... 18.2 290.8 0.9 221 750 2.7 295

Charleston, SC .................. 12.5 199.6 2.8 88 674 8.5 30

Greenville, SC .................... 12.7 227.4 2.5 103 688 3.9 266

Horry, SC ........................... 8.5 112.1 4.6 37 505 4.6 240

Lexington, SC .................... 5.9 88.3 4.6 37 608 4.3 255

Richland, SC ...................... 9.8 206.7 -0.4 293 685 6.2 126

Spartanburg, SC ................ 6.4 115.6 -0.2 287 684 5.7 159

Minnehaha, SD .................. 6.1 111.3 2.3 114 666 6.7 98

Davidson, TN ..................... 17.9 446.0 3.2 72 773 5.0 213

Hamilton, TN ...................... 8.4 193.2 1.0 209 686 6.2 126

Knox, TN ............................ 10.4 220.6 1.1 202 666 5.5 174

Rutherford, TN ................... 3.8 95.9 3.9 52 668 3.6 279

Shelby, TN ......................... 19.7 505.9 1.9 141 814 3.7 275

Bell, TX .............................. 4.3 94.4 5.0 28 596 4.4 248

Bexar, TX ........................... 30.2 677.9 3.2 72 675 5.0 213

Brazoria, TX ....................... 4.3 80.1 3.2 72 719 4.7 232

Brazos, TX ......................... 3.6 82.6 3.8 54 551 1.7 306

Cameron, TX ..................... 6.2 117.0 1.9 141 486 3.6 279

Collin, TX ........................... 14.3 250.4 6.3 12 913 6.9 86

Dallas, TX .......................... 66.1 1,431.1 2.0 137 940 6.6 105

Denton, TX ......................... 9.3 149.5 4.9 32 687 6.7 98

El Paso, TX ........................ 12.8 260.1 2.3 114 558 5.5 174

Fort Bend, TX .................... 7.2 111.0 2.7 94 860 15.4 2

Galveston, TX .................... 4.9 87.7 3.3 67 671 4.7 232

Harris, TX ........................... 90.4 1,882.0 3.4 66 930 7.8 47

Hidalgo, TX ........................ 9.7 196.2 5.0 28 499 5.1 209

Jefferson, TX ..................... 5.8 117.7 2.1 130 711 6.9 86

Lubbock, TX ....................... 6.5 120.2 2.2 122 590 6.1 133

McLennan, TX ................... 4.8 101.9 0.5 243 627 5.4 188

Montgomery, TX ................ 7.1 104.8 6.2 13 727 10.5 9

Nueces, TX ........................ 8.0 147.2 2.5 103 654 7.4 59

Potter, TX ........................... 3.7 72.0 1.4 176 631 5.3 194

Smith, TX ........................... 5.0 89.7 2.0 137 680 5.4 188

Tarrant, TX ......................... 34.7 719.8 2.3 114 789 5.8 153

Travis, TX .......................... 25.4 531.0 3.8 54 882 6.7 98

Webb, TX ........................... 4.4 82.2 5.3 22 525 6.1 133

Williamson, TX ................... 6.0 102.0 5.1 25 785 5.9 149

Davis, UT ........................... 6.8 97.5 3.5 63 636 5.0 213

Salt Lake, UT ..................... 36.9 547.1 4.5 41 719 7.0 79

Utah, UT ............................ 11.9 160.8 5.8 16 591 4.8 223

Weber, UT ......................... 5.6 89.5 2.8 88 583 4.9 218

Chittenden, VT ................... 5.7 95.5 -0.9 302 764 5.4 188

Arlington, VA ...................... 7.2 154.3 0.5 243 1,292 7.7 51

Chesterfield, VA ................. 6.8 115.2 3.2 72 710 5.7 159

Fairfax, VA ......................... 30.8 569.6 3.7 58 1,188 10.9 6

Henrico, VA ........................ 8.6 172.4 2.2 122 816 5.2 203

Loudoun, VA ...................... 7.0 123.1 5.5 18 1,008 4.7 232

Prince William, VA ............. 6.4 102.0 5.4 19 721 8.7 23

Alexandria City, VA ............ 5.8 94.2 1.2 192 1,013 7.1 71

See footnotes at end of table.
Table 1. Covered1 establishments, employment, and wages in the 323 largest counties,

third quarter 20052 — Continued

County3

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage5

September

2005

(thousands)

Percent

change,

September

2004-054

Ranking by

percent

change

Average

weekly

wage

Percent

change,

third quarter

2004-054

Ranking by

percent

change

Chesapeake City, VA ......... 5.1 96.4 2.5 103 $627 8.1 35

Newport News City, VA ..... 3.8 98.6 1.4 176 719 6.8 93

Norfolk City, VA ................. 5.6 144.4 -0.2 287 761 5.8 153

Richmond City, VA ............. 7.0 161.9 2.7 94 876 7.0 79

Virginia Beach City, VA ...... 10.9 179.1 3.5 63 619 8.6 26

Clark, WA ........................... 10.7 128.2 5.0 28 720 5.4 188

King, WA ............................ 75.2 1,129.1 2.7 94 997 7.2 68

Kitsap, WA ......................... 6.3 82.6 3.0 83 734 5.8 153

Pierce, WA ......................... 19.5 262.0 3.1 82 715 6.4 115

Snohomish, WA ................. 16.3 217.4 2.1 130 802 5.1 209

Spokane, WA ..................... 14.5 199.3 2.7 94 643 6.1 133

Thurston, WA ..................... 6.3 93.6 2.4 109 714 4.7 232

Whatcom, WA .................... 6.5 78.6 4.7 35 609 7.8 47

Yakima, WA ....................... 7.7 105.8 1.8 150 525 4.4 248

Kanawha, WV .................... 6.2 107.4 -0.5 297 668 6.2 126

Brown, WI .......................... 6.8 148.8 1.0 209 695 5.9 149

Dane, WI ............................ 14.0 300.8 2.3 114 780 9.2 15

Milwaukee, WI ................... 21.8 494.8 0.3 256 785 4.8 223

Outagamie, WI ................... 5.0 101.3 -0.4 293 678 4.1 260

Racine, WI ......................... 4.3 76.1 -1.3 307 737 6.3 120

Waukesha, WI ................... 13.5 232.5 0.5 243 781 2.6 297

Winnebago, WI .................. 3.9 89.3 1.4 176 737 4.4 248

San Juan, PR ..................... 14.3 313.4 -2.2 (8) 504 4.6 (8) 

1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs.

These 322 U.S. counties comprise 70.6 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. 8 This county was not included in the U.S. rankings.
Table 2. Covered1 establishments, employment, and wages in the ten largest counties,

third quarter 20052

County by NAICS supersector

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage4

September

2005

(thousands)

Percent

change,

September

2004-053

Average

weekly

wage

Percent

change,

third quarter

2004-053

United States5 .................................................... 8,634.7 132,929.3 2.0 $777 6.1

Private industry .............................................. 8,357.6 111,846.5 2.2 770 6.4

Natural resources and mining .................... 122.9 1,834.7 3.3 732 12.1

Construction ............................................... 851.0 7,581.2 5.4 816 6.3

Manufacturing ............................................ 365.9 14,218.1 -0.9 946 5.3

Trade, transportation, and utilities .............. 1,873.5 25,666.2 1.6 682 5.2

Information ................................................. 142.3 3,057.1 -0.2 1,207 8.3

Financial activities ...................................... 816.5 8,084.8 2.2 1,113 7.1

Professional and business services ........... 1,378.4 17,138.0 4.0 929 8.0

Education and health services ................... 769.3 16,557.0 2.7 745 5.8

Leisure and hospitality ............................... 693.9 13,006.0 1.8 331 5.4

Other services ............................................ 1,104.0 4,329.4 0.9 505 5.9

Government ................................................... 277.1 21,082.9 1.2 817 4.6

Los Angeles, CA ................................................ 370.3 4,105.4 1.8 879 5.5

Private industry .............................................. 366.4 3,554.9 1.9 862 5.9

Natural resources and mining .................... 0.5 11.4 -2.4 1,207 17.6

Construction ............................................... 13.2 154.6 6.6 891 8.9

Manufacturing ............................................ 16.1 467.5 -3.0 908 4.4

Trade, transportation, and utilities .............. 52.6 794.4 1.8 745 5.4

Information ................................................. 8.5 211.2 2.4 1,456 5.1

Financial activities ...................................... 23.2 245.0 2.4 1,409 11.1

Professional and business services ........... 39.8 587.0 4.5 987 6.9

Education and health services ................... 27.1 459.5 0.4 816 7.7

Leisure and hospitality ............................... 25.6 382.8 1.8 498 0.0

Other services ............................................ 159.5 241.0 6.4 407 1.2

Government ................................................... 3.9 550.5 0.8 994 4.2

Cook, IL .............................................................. 131.0 2,529.4 0.7 920 5.5

Private industry .............................................. 129.7 2,214.7 0.9 915 5.9

Natural resources and mining .................... 0.1 1.5 9.7 989 5.0

Construction ............................................... 11.2 97.4 -0.4 1,110 3.4

Manufacturing ............................................ 7.5 252.3 -2.1 958 6.0

Trade, transportation, and utilities .............. 27.0 475.0 -0.1 759 3.8

Information ................................................. 2.5 60.4 -1.4 1,315 8.9

Financial activities ...................................... 14.6 218.3 0.8 1,394 4.0

Professional and business services ........... 26.8 423.8 3.1 1,143 8.3

Education and health services ................... 12.9 357.3 2.2 808 6.2

Leisure and hospitality ............................... 11.0 229.1 1.3 403 6.9

Other services ............................................ 13.0 95.0 -0.6 664 6.1

Government ................................................... 1.2 314.7 -0.7 959 3.3

New York, NY ..................................................... 114.3 2,243.4 1.7 1,419 7.0

Private industry .............................................. 114.0 1,801.7 1.8 1,507 7.5

Natural resources and mining .................... 0.0 0.1 6.3 1,407 26.1

Construction ............................................... 2.1 29.9 2.1 1,363 4.0

Manufacturing ............................................ 3.1 42.1 -7.6 1,101 10.2

Trade, transportation, and utilities .............. 21.4 237.2 1.2 1,071 7.7

Information ................................................. 4.1 130.7 0.8 1,777 3.6

Financial activities ...................................... 17.3 356.3 2.0 2,605 8.3

Professional and business services ........... 22.6 447.6 2.3 1,632 7.9

Education and health services ................... 8.0 269.1 0.9 979 6.5

Leisure and hospitality ............................... 10.4 192.0 0.7 679 6.8

Other services ............................................ 16.4 83.6 1.9 822 6.2

Government ................................................... 0.2 441.7 1.0 1,064 4.0

See footnotes at end of table.
Table 2. Covered1 establishments, employment, and wages in the ten largest counties,

third quarter 20052 — Continued

County by NAICS supersector

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage4

September

2005

(thousands)

Percent

change,

September

2004-053

Average

weekly

wage

Percent

change,

third quarter

2004-053

Harris, TX ........................................................... 90.4 1,882.0 3.4 $930 7.8

Private industry .............................................. 90.0 1,636.5 3.7 944 8.3

Natural resources and mining .................... 1.3 67.1 6.7 2,409 18.3

Construction ............................................... 6.2 132.7 4.0 867 4.7

Manufacturing ............................................ 4.6 169.9 4.6 1,188 10.2

Trade, transportation, and utilities .............. 21.0 396.3 3.0 829 6.3

Information ................................................. 1.3 32.1 -2.3 1,152 7.7

Financial activities ...................................... 9.8 117.1 2.3 1,127 7.0

Professional and business services ........... 17.6 302.8 5.5 1,062 7.7

Education and health services ................... 9.3 196.4 3.6 807 2.7

Leisure and hospitality ............................... 6.8 162.7 1.5 356 9.9

Other services ............................................ 10.5 55.4 0.4 547 5.8

Government ................................................... 0.4 245.5 1.5 837 4.6

Maricopa, AZ ...................................................... 84.3 1,735.0 6.5 790 8.1

Private industry .............................................. 83.7 1,524.0 7.2 785 8.1

Natural resources and mining .................... 0.5 7.9 2.5 607 6.5

Construction ............................................... 8.6 165.9 15.0 798 11.3

Manufacturing ............................................ 3.3 133.2 2.6 1,077 4.5

Trade, transportation, and utilities .............. 18.7 350.4 6.4 765 7.6

Information ................................................. 1.4 31.5 -2.1 991 14.4

Financial activities ...................................... 10.1 146.1 6.9 1,032 14.7

Professional and business services ........... 18.3 294.9 8.2 761 5.7

Education and health services ................... 8.2 177.1 5.8 841 7.5

Leisure and hospitality ............................... 6.0 165.4 6.0 376 7.4

Other services ............................................ 5.8 45.9 1.6 547 9.2

Government ................................................... 0.6 211.0 1.7 836 8.2

Orange, CA ........................................................ 90.3 1,497.5 2.2 907 7.1

Private industry .............................................. 88.9 1,359.2 2.5 903 7.1

Natural resources and mining .................... 0.2 5.5 -4.3 629 10.5

Construction ............................................... 6.7 105.4 6.9 962 9.4

Manufacturing ............................................ 5.7 182.9 -0.7 1,059 6.6

Trade, transportation, and utilities .............. 17.0 270.9 1.1 829 5.5

Information ................................................. 1.4 32.2 -0.9 1,250 3.6

Financial activities ...................................... 10.3 144.1 4.5 1,466 6.5

Professional and business services ........... 17.7 271.4 5.7 926 7.8

Education and health services ................... 9.4 131.6 1.8 845 8.2

Leisure and hospitality ............................... 6.7 166.4 0.6 388 6.0

Other services ............................................ 13.8 48.7 2.6 550 7.2

Government ................................................... 1.4 138.3 -1.2 951 7.5

Dallas, TX ........................................................... 66.1 1,431.1 2.0 940 6.6

Private industry .............................................. 65.6 1,272.6 2.2 949 6.9

Natural resources and mining .................... 0.5 7.3 7.8 2,432 10.3

Construction ............................................... 4.3 78.4 5.0 856 8.4

Manufacturing ............................................ 3.3 146.0 0.5 1,135 12.3

Trade, transportation, and utilities .............. 14.8 301.8 0.9 895 5.2

Information ................................................. 1.7 53.8 -0.1 1,257 4.5

Financial activities ...................................... 8.3 136.0 1.5 1,213 8.3

Professional and business services ........... 13.7 250.9 5.4 1,021 5.7

Education and health services ................... 6.2 134.0 2.0 901 5.1

Leisure and hospitality ............................... 5.0 122.6 0.3 429 5.7

Other services ............................................ 6.5 38.5 -0.1 606 5.2

Government ................................................... 0.5 158.5 0.0 867 4.0

See footnotes at end of table.
Table 2. Covered1 establishments, employment, and wages in the ten largest counties,

third quarter 20052 — Continued

County by NAICS supersector

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage4

September

2005

(thousands)

Percent

change,

September

2004-053

Average

weekly

wage

Percent

change,

third quarter

2004-053

San Diego, CA ................................................... 87.6 1,301.3 1.6 $855 7.3

Private industry .............................................. 86.2 1,088.1 1.6 838 7.7

Natural resources and mining .................... 0.8 11.3 -1.8 534 8.1

Construction ............................................... 6.8 93.7 2.5 897 9.4

Manufacturing ............................................ 3.4 103.7 -0.6 1,102 4.1

Trade, transportation, and utilities .............. 14.1 218.6 2.6 691 6.0

Information ................................................. 1.3 37.6 1.4 1,903 12.2

Financial activities ...................................... 9.3 83.5 1.3 1,077 6.4

Professional and business services ........... 15.0 210.8 1.5 999 9.8

Education and health services ................... 7.7 120.9 0.6 804 10.1

Leisure and hospitality ............................... 6.6 153.0 2.3 399 5.6

Other services ............................................ 21.1 55.0 1.2 478 6.2

Government ................................................... 1.4 213.2 1.8 944 4.9

King, WA ............................................................ 75.2 1,129.1 2.7 997 7.2

Private industry .............................................. 74.8 976.9 3.2 1,005 7.7

Natural resources and mining .................... 0.4 3.2 0.6 1,009 7.5

Construction ............................................... 6.4 63.6 10.5 954 8.3

Manufacturing ............................................ 2.6 100.2 -1.9 1,245 3.1

Trade, transportation, and utilities .............. 14.6 219.1 1.3 854 4.8

Information ................................................. 1.6 70.6 3.5 2,347 18.8

Financial activities ...................................... 6.4 76.4 1.9 1,166 5.2

Professional and business services ........... 12.1 174.6 7.6 1,090 5.1

Education and health services ................... 6.1 115.9 4.2 792 9.5

Leisure and hospitality ............................... 5.7 108.0 3.3 413 3.3

Other services ............................................ 18.8 45.2 -2.7 527 9.8

Government ................................................... 0.5 152.2 -0.3 940 3.6

Miami-Dade, FL .................................................. 84.4 1,003.2 3.3 781 8.9

Private industry .............................................. 84.1 850.5 3.5 750 7.9

Natural resources and mining .................... 0.5 8.5 6.2 478 8.9

Construction ............................................... 5.6 46.5 11.6 805 6.8

Manufacturing ............................................ 2.7 48.6 -2.5 717 11.2

Trade, transportation, and utilities .............. 24.0 244.5 2.0 716 7.2

Information ................................................. 1.8 23.0 (6) 1,097 (6) 

Financial activities ...................................... 9.5 69.8 4.3 1,076 11.0

Professional and business services ........... 16.8 144.8 7.5 886 10.2

Education and health services ................... 8.4 128.7 2.9 758 4.0

Leisure and hospitality ............................... 5.8 97.7 3.4 434 7.7

Other services ............................................ 7.7 35.0 0.8 476 9.7

Government ................................................... 0.3 152.7 1.9 961 13.2

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. Covered1 establishments, employment, and wages in the largest county

by state, third quarter 20052

County3

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage5

September

2005

(thousands)

Percent

change,

September

2004-054

Average

weekly

wage

Percent

change,

third quarter

2004-054

United States6 .................... 8,634.7 132,929.3 2.0 $777 6.1

Jefferson, AL ...................... 18.8 372.8 1.3 796 7.7

Anchorage Borough, AK .... 7.9 148.0 1.9 857 5.8

Maricopa, AZ ..................... 84.3 1,735.0 6.5 790 8.1

Pulaski, AR ........................ 13.5 245.7 1.3 709 6.1

Los Angeles, CA ................ 370.3 4,105.4 1.8 879 5.5

Denver, CO ........................ 25.1 429.4 1.7 947 6.6

Hartford, CT ....................... 24.6 488.6 1.2 968 5.6

New Castle, DE ................. 19.8 281.2 0.3 921 7.5

Washington, DC ................. 30.7 666.4 0.8 1,265 4.5

Miami-Dade, FL ................. 84.4 1,003.2 3.3 781 8.9

Fulton, GA .......................... 38.0 744.4 2.2 1,007 4.9

Honolulu, HI ....................... 23.8 441.7 3.2 740 5.3

Ada, ID ............................... 13.9 201.2 5.4 719 6.4

Cook, IL ............................. 131.0 2,529.4 0.7 920 5.5

Marion, IN .......................... 23.5 584.0 0.5 819 7.1

Polk, IA .............................. 14.2 265.6 1.9 792 6.9

Johnson, KS ...................... 19.4 302.9 1.7 823 7.9

Jefferson, KY ..................... 21.6 425.3 1.4 761 5.5

Orleans, LA ........................ 12.9 178.2 -26.3 742 10.7

Cumberland, ME ................ 11.7 171.3 -0.1 710 6.0

Montgomery, MD ............... 32.0 462.4 2.6 1,027 8.0

Middlesex, MA ................... 49.8 791.8 0.9 1,110 6.5

Wayne, MI .......................... 34.2 789.3 -1.2 910 4.8

Hennepin, MN .................... 41.9 837.8 1.4 990 6.1

Hinds, MS .......................... 6.5 126.9 -2.1 689 5.5

St. Louis, MO ..................... 33.8 622.5 1.0 828 6.4

Yellowstone, MT ................ 5.4 73.6 3.0 619 8.2

Douglas, NE ....................... 15.2 310.3 0.5 741 5.6

Clark, NV ........................... 42.3 883.1 7.1 752 7.3

Hillsborough, NH ................ 12.3 197.6 1.7 854 3.3

Bergen, NJ ......................... 34.2 450.2 0.5 964 5.9

Bernalillo, NM .................... 16.5 323.4 2.6 707 6.2

New York, NY .................... 114.3 2,243.4 1.7 1,419 7.0

Mecklenburg, NC ............... 27.7 527.4 3.7 894 6.9

Cass, ND ........................... 5.7 93.0 3.3 648 6.2

Cuyahoga, OH ................... 38.1 755.8 0.1 802 3.4

Oklahoma, OK ................... 22.5 415.7 1.5 685 6.4

Multnomah, OR .................. 26.2 430.5 2.4 798 5.3

Allegheny, PA .................... 35.0 682.9 -0.3 811 4.6

Providence, RI ................... 18.2 290.8 0.9 750 2.7

Greenville, SC .................... 12.7 227.4 2.5 688 3.9

Minnehaha, SD .................. 6.1 111.3 2.3 666 6.7

Shelby, TN ......................... 19.7 505.9 1.9 814 3.7

Harris, TX ........................... 90.4 1,882.0 3.4 930 7.8

Salt Lake, UT ..................... 36.9 547.1 4.5 719 7.0

Chittenden, VT ................... 5.7 95.5 -0.9 764 5.4

Fairfax, VA ......................... 30.8 569.6 3.7 1,188 10.9

King, WA ............................ 75.2 1,129.1 2.7 997 7.2

Kanawha, WV .................... 6.2 107.4 -0.5 668 6.2

Milwaukee, WI ................... 21.8 494.8 0.3 785 4.8

See footnotes at end of table.
Table 3. Covered1 establishments, employment, and wages in the largest county

by state, third quarter 20052 — Continued

County3

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage5

September

2005

(thousands)

Percent

change,

September

2004-054

Average

weekly

wage

Percent

change,

third quarter

2004-054

Laramie, WY ...................... 3.0 41.0 3.1 $634 6.6

San Juan, PR ..................... 14.3 313.4 -2.2 504 4.6

St. Thomas, VI ................... 1.8 22.6 0.2 575 1.4

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.
Table 4. Covered1 establishments, employment, and wages by state, 

third quarter 20052

State

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage3

September

2005

(thousands)

Percent

change,

September

2004-05

Average

weekly

wage

Percent

change,

third quarter

2004-05

United States4 .................... 8,634.7 132,929.3 2.0 $777 6.1

Alabama ............................. 117.1 1,905.9 2.5 669 6.4

Alaska ................................ 20.7 320.2 1.8 797 5.6

Arizona ............................... 135.9 2,511.8 6.0 748 8.2

Arkansas ............................ 77.9 1,165.7 1.9 599 4.9

California ............................ 1,237.6 15,443.3 2.5 887 7.0

Colorado ............................ 171.8 2,212.1 2.3 808 7.3

Connecticut ........................ 110.8 1,655.2 0.8 966 5.3

Delaware ............................ 30.1 420.1 1.3 823 7.0

District of Columbia ............ 30.7 666.4 0.8 1,265 4.5

Florida ................................ 564.9 7,801.6 5.5 708 8.1

Georgia .............................. 257.3 3,960.8 3.2 748 5.2

Hawaii ................................ 36.5 606.0 3.2 714 5.8

Idaho .................................. 52.4 635.5 4.5 605 6.0

Illinois ................................. 339.7 5,820.7 1.2 825 5.9

Indiana ............................... 153.2 2,916.3 1.0 689 5.2

Iowa ................................... 91.8 1,461.1 1.9 641 6.1

Kansas ............................... 83.1 1,315.3 0.5 659 6.5

Kentucky ............................ 107.2 1,779.5 1.9 651 5.2

Louisiana ........................... 120.3 1,770.8 -4.9 637 6.9

Maine ................................. 48.5 606.0 -0.5 631 4.6

Maryland ............................ 158.3 2,526.5 1.9 854 7.6

Massachusetts ................... 219.0 3,193.3 0.8 947 4.5

Michigan ............................ 257.2 4,353.1 -0.1 787 4.1

Minnesota .......................... 165.1 2,671.9 1.4 790 4.9

Mississippi ......................... 68.0 1,098.4 -1.4 573 5.9

Missouri ............................. 170.9 2,696.2 1.6 691 5.5

Montana ............................. 40.5 424.2 2.7 563 7.4

Nebraska ........................... 56.9 896.7 1.1 633 5.3

Nevada .............................. 67.7 1,242.5 6.3 750 6.7

New Hampshire ................. 47.8 630.7 1.2 772 5.8

New Jersey ........................ 272.7 3,960.8 1.2 928 5.8

New Mexico ....................... 50.5 791.0 3.0 629 6.8

New York ........................... 564.1 8,394.8 0.9 941 5.7

North Carolina .................... 234.2 3,903.7 1.9 690 5.7

North Dakota ...................... 24.9 335.4 2.4 581 6.0

Ohio ................................... 291.4 5,360.6 0.5 723 5.5

Oklahoma .......................... 94.3 1,482.5 2.8 612 5.7

Oregon ............................... 124.8 1,683.4 3.5 714 5.6

Pennsylvania ..................... 335.9 5,597.6 1.1 764 5.7

Rhode Island ...................... 35.9 488.9 1.0 736 4.1

South Carolina ................... 119.8 1,831.2 1.6 637 5.6

South Dakota ..................... 29.2 381.6 1.6 567 5.4

Tennessee ......................... 132.8 2,724.0 2.0 689 4.6

Texas ................................. 521.6 9,659.3 3.1 767 6.7

Utah ................................... 82.1 1,135.1 4.7 647 6.6

Vermont ............................. 24.6 303.4 0.2 663 4.7

Virginia ............................... 213.4 3,617.7 2.7 815 7.7

Washington ........................ 210.4 2,820.6 2.5 801 6.5

West Virginia ...................... 48.2 702.9 1.3 589 5.4

Wisconsin .......................... 161.7 2,783.4 1.2 688 5.4

See footnotes at end of table.
Table 4. Covered1 establishments, employment, and wages by state, 

third quarter 20052 — Continued

State

Establishments,

third quarter

2005

(thousands)

Employment Average weekly wage3

September

2005

(thousands)

Percent

change,

September

2004-05

Average

weekly

wage

Percent

change,

third quarter

2004-05

Wyoming ............................ 23.3 263.4 3.8 $638 8.0

Puerto Rico ........................ 57.2 1,037.4 -0.6 435 3.8

Virgin Islands ..................... 3.5 44.0 3.0 616 2.8

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.
Chart 1. Percent change in employment in counties with 75,000 emp

September 200405 (U.S. Average = 2.0%)

Note: The following counties have fewer than 75,000 employees

but are included because they are the largest county in their state

or territory: Laramie, Wyo., Yellowstone, Mont., and St. Thomas, V.I.

So

Ap
Chart 2. Percent change in average weekly wage in counties with 75,

or more, third quarter 200405 (U.S. Average = 6.1%)

Note: The following counties have fewer than 75,000 employees

but are included because they are the largest county in their state

or territory: Laramie, Wyo., Yellowstone, Mont., and St. Thomas, V.I.

So

Ap