Full text of Third Quarter 2006 : Text File, USDL 07-0525
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Technical information: (202) 691-6567 USDL 07-0525
http://www.bls.gov/cew/
For release: 10:00 A.M. EDT
Media contact: 691-5902 Wednesday, April 11, 2007
COUNTY EMPLOYMENT AND WAGES: THIRD QUARTER 2006
In September 2006, Jefferson County, La., 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. Jefferson County, a New Or-
leans suburb, experienced an over-the-year employment gain of 22.4 percent,
compared with national job growth of 1.5 percent. Employment gains in Jef-
ferson County reflected significant recovery from substantial job losses
that occurred in September 2005 due to Hurricane Katrina. In contrast, Or-
leans County, which also was affected by Hurricane Katrina, continued to show
an over-the-year employment decline (-12.3 percent). Kent County, R.I., had
the largest over-the-year gain in average weekly wages in the third quarter
of 2006, with an increase of 18.4 percent. The U.S. average weekly wage rose
by 0.9 percent over the same time span.
Of the 325 largest counties in the United States, as measured by 2005
annual average employment, 130 had over-the-year percentage growth in em-
ployment above the national average (1.5 percent) in September 2006, and
187 experienced changes below the national average. The percent change in
average weekly wages was higher than the national average (0.9 percent) in
133 of the largest U.S. counties, but was below the national average in 184
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 8.8 million em-
ployer reports cover 135.0 million full- and part-time workers. The attached
tables contain data for the nation and for the 325 U.S. counties with annual
average employment levels of 75,000 or more in 2005. September 2006 employment
and 2006 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 2005 are avail-
able on the BLS Web site at http://www.bls.gov/cew/. Preliminary data for
third quarter 2006, along with updated data for the first and second quarters
of 2006, will be available later in April on the BLS Web site.
Large County Employment
In September 2006, national employment, as measured by the QCEW program,
was 135.0 million, up by 1.5 percent from September 2005. The 325 U.S.
counties with 75,000 or more employees accounted for 70.7 percent of total
U.S. covered employment and 76.5 percent of total covered wages. These 325
counties had a net job gain of 1,328,166 over the year, accounting for 66.0
percent of the overall U.S. employment increase. Employment rose in 256 of
the large counties from September 2005 to September 2006. Jefferson County,
La., had the largest over-the-year percentage increase in employment (22.4
percent). Snohomish, Wash., had the next largest increase, 8.2 percent,
followed by the counties of Collin, Texas (7.2 percent), Harrison, Miss.
(6.8 percent), and Montgomery, Texas (5.7 percent). The large employment
gains in Jefferson County reflected significant recovery from the substan-
tial job losses in September 2005, which were related to Hurricane Katrina.
Strong employment growth in Harrison County, which also was impacted by this
hurricane, showed that the county had begun to rebound from job losses in 2005.
(See table 1.)
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| Hurricane Katrina |
| |
| The employment and wages reported in this news release re- |
| flect the impact of Hurricane Katrina and ongoing labor market |
| trends in certain counties. The effects of Hurricane Katrina, |
| which hit the Gulf Coast on August 29, 2005, were first apparent |
| in the September QCEW employment counts and in the wage totals |
| for the third quarter of 2005. This catastrophic storm contin- |
| ued to affect monthly employment and quarterly wage totals in |
| parts of Louisiana and Mississippi in the third quarter of 2006. |
| For more information, see the QCEW section of the Katrina cover- |
| age on the BLS Web site at http://www.bls.gov/katrina/qcewques- |
| tions.htm. |
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Table A. Top 10 large counties ranked by September 2006 employment,
September 2005-06 employment growth, and September 2005-06 percent growth in
employment
----------------------------------------------------------------------------------
Employment in large counties
----------------------------------------------------------------------------------
| |
September 2006 employment| Growth in employment, | Percent growth
(thousands) | September 2005-06 | in employment,
| (thousands) | September 2005-06
----------------------------------------------------------------------------------
| |
United States .... 134,988.9| United States ..... 2,013.1| United States ..... 1.5
----------------------------|----------------------------|------------------------
| |
Los Angeles, Calif. 4,161.2| Harris, Texas ........ 79.4| Jefferson, La. ... 22.4
Cook, Ill. ......... 2,553.4| Maricopa, Ariz. ...... 76.2| Snohomish, Wash. .. 8.2
New York, N.Y. ..... 2,292.3| New York, N.Y. ....... 42.0| Collin, Texas ..... 7.2
Harris, Texas ...... 1,959.1| King, Wash. .......... 40.6| Harrison, Miss. ... 6.8
Maricopa, Ariz. .... 1,819.1| Clark, Nev. .......... 39.1| Montgomery, Texas . 5.7
Orange, Calif. ..... 1,517.9| Dallas, Texas ........ 38.3| Lake, Fla. ........ 5.5
Dallas, Texas ...... 1,466.0| Jefferson, La. ....... 35.5| Williamson, Texas . 5.5
San Diego, Calif. .. 1,321.7| Los Angeles, Calif. .. 29.2| Utah, Utah ........ 5.5
King, Wash. ........ 1,167.1| Salt Lake, Utah ...... 25.4| Douglas, Colo. .... 4.6
Miami-Dade, Fla. ... 1,008.4| Bexar, Texas ......... 24.4| Horry, S.C. ....... 4.6
| | Salt Lake, Utah ... 4.6
| |
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Employment declined in 62 counties from September 2005 to September 2006.
The largest percentage decline in employment was in Orleans County, La.
(-12.3 percent). Employment losses in Orleans County reflected the deva-
station caused by Hurricane Katrina. Trumbull, Ohio, had the next largest
employment decline (-4.5 percent), followed by the counties of Macomb, Mich.
(-4.0 percent), Oakland, Mich. (-3.5 percent), and Rock Island, Ill. (-3.0
percent).
The largest gains in the level of employment from September 2005 to
September 2006 were recorded in the counties of Harris, Texas (79,400),
Maricopa, Ariz. (76,200), New York, N.Y. (42,000), King, Wash. (40,600),
and Clark, Nev. (39,100). (See table A.)
The largest declines in employment levels occurred in Oakland, Mich.
(-25,200), followed by the counties of Orleans, La. (-21,600), Wayne,
Mich. (-20,500), Macomb, Mich. (-13,400), and Kent, Mich. (-5,500).
Large County Average Weekly Wages
The national average weekly wage in the third quarter of 2006 was $784.
Average weekly wages were higher than the national average in 111 of the
largest 325 U.S. counties. New York County, N.Y., held the top position
among the highest-paid large counties with an average weekly wage of $1,421.
Santa Clara, Calif., was second with an average weekly wage of $1,414, fol-
lowed by Arlington, Va. ($1,323), Washington, D.C. ($1,307), and San Mateo,
Calif. ($1,278). (See table B.)
- 3 -
Table B. Top 10 large counties ranked by third quarter 2006 average weekly wages,
third quarter 2005-06 growth in average weekly wages, and third quarter 2005-06
percent growth in average weekly wages
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Average weekly wage in large counties
-----------------------------------------------------------------------------------
Average weekly wage, | Growth in average weekly | Percent growth in
third quarter 2006 | wage, third quarter | average weekly wage,
| 2005-06 | third quarter 2005-06
-----------------------------------------------------------------------------------
| |
United States ......... $784| United States ........ $7| United States ........ 0.9
-----------------------------------------------------------------------------------
| |
New York, N.Y. ...... $1,421| Kent, R.I. ......... $132| Kent, R.I. .......... 18.4
Santa Clara, Calif. .. 1,414| Orleans, La. ........ 121| Orleans, La. ........ 16.2
Arlington, Va. ....... 1,323| Trumbull, Ohio ....... 85| Trumbull, Ohio ...... 12.3
Washington, D.C. ..... 1,307| Jefferson, Texas ..... 74| Jefferson, La. ...... 10.5
San Mateo, Calif. .... 1,278| Jefferson, La. ....... 69| Jefferson, Texas .... 10.5
San Francisco, Calif. 1,246| Lafayette, La. ....... 56| Mobile, Ala. ......... 8.6
Suffolk, Mass. ....... 1,208| Mobile, Ala. ......... 55| Lafayette, La. ....... 8.2
Fairfield, Conn. ..... 1,191| Ingham, Mich. ........ 52| East Baton Rouge, La. 7.4
Fairfax, Va. ......... 1,179| Morris, N.J. ......... 49| Harrison, Miss. ...... 7.2
Somerset, N.J. ....... 1,165| Vanderburgh, Ind. .... 48| Vanderburgh, Ind. .... 7.1
| East Baton Rouge, La. 48| Ingham, Mich. ........ 7.1
| Galveston, Texas ..... 48| Galveston, Texas ..... 7.1
| |
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There were 212 counties with an average weekly wage below the national
average in the third quarter of 2006. The lowest average weekly wages were
reported in Cameron County, Texas ($493), followed by the counties of Hidalgo,
Texas ($514), Horry, S.C. ($517), Webb, Texas ($525), and Yakima, Wash. ($537).
(See table 1.)
Over the year, the national average weekly wage rose by 0.9 percent.
Among the largest counties, Kent, R.I., led the nation in growth in aver-
age weekly wages, with an increase of 18.4 percent from the third quarter
of 2005. Orleans, La., was second with growth of 16.2 percent, followed
by the counties of Trumbull, Ohio (12.3 percent), and Jefferson, La., and
Jefferson, Texas (10.5 percent each). The high average weekly wage growth
rate for Orleans County was related to the disproportionate job losses in
lower-paid industries due to the impact of Hurricane Katrina. That is, the
loss of low paid jobs due to the storm boosted average wages in Orleans
County.
One hundred and twelve counties experienced over-the-year declines in
average weekly wages. Passaic, N.J., had the largest decrease, -10.2 per-
cent, followed by the counties of Williamson, Texas (-5.7 percent), Fort
Bend, Texas (-5.0 percent), Loudoun, Va. (-4.2 percent), and Ventura, Calif.
(-4.0 percent).
Ten Largest U.S. Counties
Each of the 10 largest counties (based on 2005 annual average employment
levels) reported increases in employment from September 2005 to September
2006. Maricopa County, Ariz., experienced the largest percent increase in
employment among the largest counties with a 4.4 percent increase. Within
Maricopa County, employment rose in every industry group except information.
The largest gains were in education and health services (6.2 percent), fol-
lowed by construction (5.9 percent). Harris, Texas, had the next largest
increase in employment, 4.2 percent, followed by King, Wash. (3.6 percent).
The smallest percent increase in employment occurred in Miami-Dade, Fla.
(0.6 percent), followed by Cook, Ill., and Los Angeles, Calif. (0.7 percent
each). (See table 2.)
Eight of the 10 largest U.S. counties saw over-the-year increases in
average weekly wages. King County, Wash., had the fastest growth in wages
among the 10 largest counties, with a gain of 4.7 percent. Within King
County, Wash., average weekly wages increased the most in information (19.4
percent), followed by natural resources and mining (17.4 percent). Dallas,
Texas, was second in wage growth with a gain of 2.2 percent, followed by
Harris, Texas (2.0 percent). The smallest wage gains among the 10 largest
counties occurred in New York, N.Y. (0.3 percent). San Diego, Calif. (-0.7
percent) and Orange, Calif. (-1.1 percent) experienced declines in average
weekly wages.
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Largest County by State
Table 3 shows September 2006 employment and the 2006 third quarter average
weekly wage in the largest county in each state, which is based on 2005 annual
average employment levels. (This table includes two counties--Yellowstone, Mont.,
and Laramie, Wyo.--that had employment levels below 75,000.) The employment lev-
els in the counties in table 3 in September 2006 ranged from approximately 4.2 mil-
lion in Los Angeles County, Calif., to 42,100 in Laramie County, Wyo. The highest
average weekly wage of these counties was in New York, N.Y. ($1,421), while the low-
est average weekly wage was in Yellowstone, Mont. ($637).
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/. Ad-
ditional information about the QCEW data also may be obtained by e-mailing QCEWinfo@
bls.gov or by calling (202) 691-6567.
Several BLS regional offices are issuing QCEW news releases targeted to local data users.
For links to these releases, see http://www.bls.gov/cew/cewregional.htm.
______________________________
The County Employment and Wages release for fourth quarter 2006 is scheduled to be
released on Wednesday, July 25.
- 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 2006 are preliminary and sub-
ject to revision.
For purposes of this release, large counties are defined as having em-
ployment 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 326 counties presented in this release were
derived using 2005 preliminary annual averages of employment. For 2006
data, four counties have been added to the publication tables: Douglas,
Colo., Weld, Colo., Boone, Ky., and Butler, Pa. These counties will be
included in all 2006 quarterly releases. One county, Potter, Texas, which
was published in the 2005 releases, no longer has an employment level of
75,000 or more and will be excluded in the 2006 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 employment change over time. It is important to
understand program differences and the intended uses of the program pro-
ducts. (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 8.8 | ministrative records| ments
| million establish- | submitted by 6.8 |
| 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 | by NAICS supersec- |
| industry | tors and by size of |
| | firm |
| |--Future expansions |
| | will include data at|
| | the county, MSA, and|
| | state level |
-----------|---------------------|----------------------|--------------------------
Principal |--Major uses include:|--Major uses include: |--Major uses include:
uses | -Detailed locality | -Business cycle | -Principal national
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -An analysis of em- | cators
| surveys | ployment expansion |
| | and contraction by |
| | size of firm |
-----------|---------------------|----------------------|--------------------------
Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/
Web sites | | |
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- 7 -
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 com-
plete a questionnaire, called the "Multiple Worksite Report," which provides
detailed information on the location and industry of each of their establish-
ments. The employment and wage data included in this release are derived
from microdata summaries of nearly 9 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 2005, UI and UCFE programs covered workers in 131.6 million
jobs. The estimated 126.7 million workers in these jobs (after adjust-
ment for multiple jobholders) represented 96.6 percent of civilian wage
and salary employment. Covered workers received $5.352 trillion in pay,
representing 94.5 percent of the wage and salary component of personal
income and 43.0 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.
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. Over-the-year comparisons of average
weekly wages may reflect fluctuations in average monthly employment and/or
total quarterly wages between the current quarter and prior year levels.
Average weekly wages are affected by the ratio of full-time to part-time
workers as well as the number of individuals in high-paying and low-paying
occupations and the incidence of pay periods within a quarter. For instance,
the average weekly wage of the work force could increase significantly when
there is a large decline in the number of employees that had been receiving
below-average wages. Wages may include payments to workers not present in
the employment counts because they did not work during the pay period in-
cluding the 12th of the month. When comparing average weekly wage levels
between industries, states, or quarters, 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, fed-
eral wages contain payments for six pay periods, while in other quarters
their wages include payments for seven pay periods. Over-the-year com-
parisons 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 ef-
fect on over-the-year pay comparisons can be pronounced in federal govern-
ment 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 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 estab-
lishments that exist in a county or industry at a point in time. Estab-
lishments can move in or out of a county or industry for a number of rea-
sons--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 2005
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 owner-
ship 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 adjust-
ments are administrative changes involving the classification of establish-
ments that were previously reported in the unknown or statewide county or
unknown industry categories. The adjusted data do not account for adminis-
trative changes caused by multi-unit employers who start reporting for each
individual establishment rather than as a single entity.
- 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. The 2005 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 2005 version
of this news release. This edition will also be the first to include the
data on a CD for enhanced access and usability. As a result of this change,
the printed booklet will contain only selected graphic representations of
QCEW data; the data tables themselves will be published exclusively in
electronic formats as PDF and fixed-width text files. Employment and Wages
Annual Averages, 2005 will soon be 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 2005 bulletin is available in a portable document
format (PDF) on the BLS Web site at http://www.bls.gov/cew/cewbultn05.htm.
News releases on quarterly measures of gross job flows also are available
upon request from the Division of Administrative Statistics and Labor Turn-
over (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 326 largest counties,
third quarter 2006 (2)
Employment Average weekly wage(5)
Establishments,
County (3) third quarter Percent Ranking Percent Ranking
2006 September change, by Average change, by
(thousands) 2006 September percent weekly third percent
(thousands) 2005-06(4) change wage quarter change
2005-06 (4)
United States (6)........ 8,841.2 134,988.9 1.5 - $784 0.9 -
Jefferson, AL............ 18.6 374.6 0.8 187 803 1.0 127
Madison, AL.............. 8.3 174.2 2.3 89 863 1.8 72
Mobile, AL............... 9.8 171.5 2.8 60 692 8.6 6
Montgomery, AL........... 6.6 138.5 1.0 170 669 2.5 49
Tuscaloosa, AL........... 4.3 84.5 2.9 56 673 2.7 42
Anchorage Borough, AK.... 8.2 148.8 .5 213 849 -.7 257
Maricopa, AZ............. 92.3 1,819.1 4.4 16 792 .5 165
Pima, AZ................. 19.8 368.6 2.6 68 708 1.9 70
Benton, AR............... 5.3 94.3 3.7 30 686 1.5 86
Pulaski, AR.............. 14.2 249.9 1.9 111 717 1.3 102
Washington, AR........... 5.7 93.6 2.1 99 639 1.3 102
Alameda, CA.............. 49.4 691.1 .7 192 1,054 .3 182
Contra Costa, CA......... 28.2 348.6 .7 192 979 .8 140
Fresno, CA............... 29.1 366.2 2.9 56 619 .5 165
Kern, CA................. 17.3 287.8 2.6 68 676 2.3 55
Los Angeles, CA.......... 392.8 4,161.2 .7 192 894 1.7 79
Marin, CA................ 11.8 110.4 1.1 161 985 -.5 241
Monterey, CA............. 12.2 180.4 .3 230 695 1.3 102
Orange, CA............... 95.9 1,517.9 1.1 161 897 -1.1 277
Placer, CA............... 10.5 137.8 .3 230 780 -.6 249
Riverside, CA............ 43.1 635.4 3.6 33 678 .0 203
Sacramento, CA........... 50.5 640.5 1.1 161 871 -.6 249
San Bernardino, CA....... 45.8 654.2 1.9 111 702 .6 158
San Diego, CA............ 92.5 1,321.7 .9 178 850 -.7 257
San Francisco, CA........ 44.2 537.0 1.8 116 1,246 2.6 44
San Joaquin, CA.......... 17.0 227.7 .9 178 685 -.3 225
San Luis Obispo, CA...... 9.1 105.7 .2 240 664 1.4 94
San Mateo, CA............ 23.2 337.3 1.8 116 1,278 .9 134
Santa Barbara, CA........ 13.7 186.4 .9 178 751 -.3 225
Santa Clara, CA.......... 55.9 884.9 2.3 89 1,414 . 8 140
Santa Cruz, CA........... 8.7 102.2 1.3 147 772 2.5 49
Solano, CA............... 9.9 133.1 -.1 261 752 1.1 120
Sonoma, CA............... 17.8 194.6 .4 220 785 1.2 113
Stanislaus, CA........... 13.9 179.7 -.4 277 677 1.5 86
Tulare, CA............... 8.9 152.4 2.8 60 560 1.4 94
Ventura, CA.............. 21.8 317.5 1.4 136 826 -4.0 319
Yolo, CA................. 5.4 102.2 2.3 89 760 -2.6 304
Adams, CO................ 9.4 155.2 3.1 53 744 -.8 264
Arapahoe, CO............. 19.9 277.0 1.4 136 955 2.0 65
Boulder, CO.............. 12.7 158.4 2.5 73 955 -3.6 316
Denver, CO............... 25.5 436.3 1.7 118 988 4.1 22
Douglas, CO.............. 9.0 88.5 4.6 9 779 -3.7 317
El Paso, CO.............. 17.6 245.8 1.5 131 733 -1.1 277
Jefferson, CO............ 19.0 208.7 .2 240 809 .0 203
Larimer, CO.............. 10.2 129.6 1.7 118 727 .7 154
Weld, CO................. 6.0 81.8 3.8 28 671 1.7 79
Fairfield, CT............ 32.7 418.9 1.3 147 1,191 -.5 241
Hartford, CT............. 25.0 500.4 2.3 89 945 -2.3 301
New Haven, CT............ 22.3 367.8 1.7 118 835 -1.4 288
New London, CT........... 6.8 130.4 -.2 266 810 -.2 219
New Castle, DE........... 19.6 282.8 .2 240 957 4.0 25
Washington, DC........... 32.0 674.2 .7 192 1,307 3.6 28
Alachua, FL.............. 6.4 126.5 1.6 126 679 2.4 52
Brevard, FL.............. 14.5 206.8 .0 257 738 -1.1 277
Broward, FL.............. 63.0 746.0 1.3 147 754 .9 134
Collier, FL.............. 12.3 130.7 4.3 20 721 .1 198
Duval, FL................ 25.6 463.7 2.4 83 784 2.6 44
Escambia, FL............. 7.9 130.1 .7 192 626 -.6 249
Hillsborough, FL......... 35.8 638.0 2.4 83 757 1.1 120
Lake, FL................. 6.9 84.4 5.5 6 589 -1.0 273
Lee, FL.................. 18.6 222.5 4.1 25 689 .7 154
Leon, FL................. 8.0 146.8 .6 204 694 1.5 86
Manatee, FL.............. 8.9 126.9 4.1 25 634 .3 182
Marion, FL............... 8.0 103.6 4.5 12 584 .5 165
Miami-Dade, FL........... 84.1 1,008.4 .6 204 792 1.5 86
Okaloosa, FL............. 6.0 84.4 2.9 56 642 .0 203
Orange, FL............... 34.5 682.2 3.2 51 728 .0 203
Palm Beach, FL........... 48.9 554.3 1.7 118 756 -1.6 296
Pasco, FL................ 9.4 100.4 3.5 37 589 4.2 19
Pinellas, FL............. 30.8 445.3 .3 230 682 -.4 234
Polk, FL................. 12.4 206.3 2.1 99 644 2.4 52
Sarasota, FL............. 14.9 158.9 3.5 37 675 -1.0 273
Seminole, FL............. 14.5 177.8 2.4 83 696 .9 134
Volusia, FL.............. 13.9 167.4 2.0 105 580 1.6 82
Bibb, GA................. 4.7 84.3 -1.2 306 644 -1.4 288
Chatham, GA.............. 7.4 135.3 1.9 111 676 .3 182
Clayton, GA.............. 4.4 108.7 -.4 277 738 -2.9 311
Cobb, GA................. 20.0 312.4 2.8 60 864 1.3 102
De Kalb, GA.............. 15.8 277.2 -1.1 302 854 1.8 72
Fulton, GA............... 39.6 777.7 1.3 147 1,016 1.0 127
Gwinnett, GA............. 23.0 327.2 3.3 48 830 -.4 234
Muscogee, GA............. 4.8 96.6 -2.5 315 625 -.5 241
Richmond, GA............. 4.8 103.1 -1.9 313 680 2.1 62
Honolulu, HI............. 24.0 452.2 2.3 89 744 .5 165
Ada, ID.................. 14.7 210.7 4.4 16 727 1.1 120
Champaign, IL............ 4.1 91.6 .8 187 676 .6 158
Cook, IL................. 135.0 2,553.4 .7 192 928 1.0 127
Du Page, IL.............. 34.6 597.4 .4 220 927 1.1 120
Kane, IL................. 12.1 212.5 2.1 99 718 -1.8 299
Lake, IL................. 20.3 333.8 .8 187 936 2.6 44
McHenry, IL.............. 8.1 103.0 3.4 43 693 -.3 225
McLean, IL............... 3.6 85.8 .4 220 766 .8 140
Madison, IL.............. 5.9 95.5 .3 230 651 .5 165
Peoria, IL............... 4.7 103.3 2.5 73 749 -.8 264
Rock Island, IL.......... 3.4 77.5 -3.0 318 756 .1 198
St. Clair, IL............ 5.3 95.7 1.2 156 642 .0 203
Sangamon, IL............. 5.2 130.5 -1.1 302 783 2.0 65
Will, IL................. 12.5 183.5 4.5 12 717 -1.1 277
Winnebago, IL............ 6.8 136.6 .1 252 695 1.5 86
Allen, IN................ 8.9 185.5 1.4 136 681 -.3 225
Elkhart, IN.............. 4.8 126.9 .1 252 667 -3.1 313
Hamilton, IN............. 7.0 101.6 3.7 30 767 -3.4 315
Lake, IN................. 10.0 195.6 -.4 277 704 .7 154
Marion, IN............... 23.6 583.0 .2 240 814 -.5 241
St. Joseph, IN........... 6.0 125.3 -1.1 302 667 .2 194
Vanderburgh, IN.......... 4.8 108.9 .2 240 723 7.1 10
Linn, IA................. 6.2 121.0 2.1 99 745 -2.6 304
Polk, IA................. 14.4 271.3 2.4 83 783 -1.0 273
Scott, IA................ 5.2 89.3 -.8 295 649 1.4 94
Johnson, KS.............. 20.0 312.0 3.4 43 812 -1.6 296
Sedgwick, KS............. 12.2 252.4 3.3 48 729 1.5 86
Shawnee, KS.............. 4.8 93.2 -.6 288 675 .4 173
Wyandotte, KS............ 3.2 81.1 2.9 56 770 .8 140
Boone, KY................ 3.4 74.8 -2.6 316 712 -3.0 312
Fayette, KY.............. 9.2 173.4 (7) - 715 .7 154
Jefferson, KY............ 22.5 433.2 1.7 118 775 (7) -
Caddo, LA................ 7.3 125.7 1.0 170 666 3.3 29
Calcasieu, LA............ 4.9 85.5 .6 204 654 .3 182
East Baton Rouge, LA..... 13.8 262.2 2.5 73 698 7.4 8
Jefferson, LA............ 14.4 194.2 22.4 1 727 10.5 4
Lafayette, LA............ 8.2 131.2 4.5 12 737 8.2 7
Orleans, LA.............. 11.7 154.8 -12.3 322 870 16.2 2
Cumberland, ME........... 12.0 172.6 .7 192 711 .3 182
Anne Arundel, MD......... 14.2 228.4 2.4 83 835 1.0 127
Baltimore, MD............ 21.5 374.2 -.7 289 809 .2 194
Frederick, MD............ 5.8 92.2 -.2 266 752 .4 173
Harford, MD.............. 5.5 82.2 1.4 136 759 .8 140
Howard, MD............... 8.4 143.5 1.2 156 908 -1.2 283
Montgomery, MD........... 32.4 467.1 1.3 147 1,034 .6 158
Prince Georges, MD....... 15.5 315.2 .0 257 867 -.1 212
Baltimore City, MD....... 14.1 350.5 -.4 277 911 .3 182
Barnstable, MA........... 9.3 97.8 -1.6 310 667 .6 158
Bristol, MA.............. 15.6 221.7 .0 257 693 -.4 234
Essex, MA................ 20.6 301.2 1.1 161 844 -.2 219
Hampden, MA.............. 14.1 201.7 -.1 261 733 .4 173
Middlesex, MA............ 47.1 804.6 1.6 126 1,108 -.3 225
Norfolk, MA.............. 21.5 321.6 .2 240 943 2.2 59
Plymouth, MA............. 13.8 179.6 .5 213 742 -.7 257
Suffolk, MA.............. 21.5 575.5 1.5 131 1,208 .8 140
Worcester, MA............ 20.5 322.3 .9 178 792 -.8 264
Genesee, MI.............. 8.3 146.3 -2.4 314 769 5.6 14
Ingham, MI............... 7.1 162.4 -.3 274 787 7.1 10
Kalamazoo, MI............ 5.6 116.2 -1.2 306 711 .3 182
Kent, MI................. 14.6 341.8 -1.6 310 730 1.2 113
Macomb, MI............... 18.3 322.7 -4.0 320 839 -1.1 277
Oakland, MI.............. 40.4 697.4 -3.5 319 931 .1 198
Ottawa, MI............... 5.8 115.2 .2 240 696 -.9 270
Saginaw, MI.............. 4.5 89.2 -1.5 309 722 4.6 16
Washtenaw, MI............ 8.2 195.2 -.8 295 913 1.6 82
Wayne, MI................ 33.6 769.1 -2.6 316 905 -1.5 291
Anoka, MN................ 7.9 115.7 -.9 299 748 -.5 241
Dakota, MN............... 10.4 173.4 .3 230 755 -2.6 304
Hennepin, MN............. 41.9 841.4 .2 240 982 -.9 270
Olmsted, MN.............. 3.6 90.7 .9 178 880 2.7 42
Ramsey, MN............... 15.4 333.3 -.4 277 851 -1.2 283
St. Louis, MN............ 5.8 96.3 .9 178 641 -2.4 302
Stearns, MN.............. 4.5 80.3 1.4 136 632 1.1 120
Harrison, MS............. 4.3 84.8 6.8 4 628 7.2 9
Hinds, MS................ 6.5 128.5 1.3 147 697 1.3 102
Boone, MO................ 4.5 82.6 1.6 126 620 .8 140
Clay, MO................. 5.0 87.3 -.7 289 747 -1.8 299
Greene, MO............... 8.1 154.4 2.4 83 615 -1.3 286
Jackson, MO.............. 18.6 367.8 1.0 170 799 .5 165
St. Charles, MO.......... 7.9 122.8 2.5 73 679 -.6 249
St. Louis, MO............ 33.7 625.8 .7 192 825 -.2 219
St. Louis City, MO....... 8.0 223.6 -.1 261 869 -.1 212
Douglas, NE.............. 15.4 314.5 1.2 156 734 -.9 270
Lancaster, NE............ 7.9 154.8 .6 204 649 -.6 249
Clark, NV................ 46.2 922.5 4.4 16 751 -.3 225
Washoe, NV............... 14.0 221.3 2.0 105 749 .1 198
Hillsborough, NH......... 12.5 196.8 -.3 274 861 1.1 120
Rockingham, NH........... 11.0 140.9 1.4 136 764 -2.7 308
Atlantic, NJ............. 6.9 152.5 1.4 136 694 -.3 225
Bergen, NJ............... 34.7 450.7 .6 204 969 .3 182
Burlington, NJ........... 11.6 202.0 .4 220 843 -.6 249
Camden, NJ............... 13.8 213.3 1.1 161 794 -1.5 291
Essex, NJ................ 21.7 360.1 .4 220 990 -1.1 277
Gloucester, NJ........... 6.5 104.7 .2 240 714 -.4 234
Hudson, NJ............... 14.2 236.1 -.8 295 1,061 2.9 36
Mercer, NJ............... 11.1 227.7 1.1 161 980 -.4 234
Middlesex, NJ............ 21.3 396.4 .2 240 996 3.2 30
Monmouth, NJ............. 20.8 259.2 .3 230 830 -.2 219
Morris, NJ............... 18.3 288.6 1.3 147 1,136 4.5 17
Ocean, NJ................ 12.1 152.4 .3 230 669 -.1 212
Passaic, NJ.............. 12.8 177.3 -.2 266 835 -10.2 323
Somerset, NJ............. 10.2 173.1 1.5 131 1,165 1.0 127
Union, NJ................ 15.1 229.6 .3 230 967 -.7 257
Bernalillo, NM........... 17.0 335.0 3.4 43 709 .4 173
Albany, NY............... 9.9 227.7 -.1 261 801 -.5 241
Bronx, NY................ 15.8 221.8 .6 204 789 1.8 72
Broome, NY............... 4.5 94.4 -.2 266 641 2.6 44
Dutchess, NY............. 8.3 118.4 .4 220 814 4.1 22
Erie, NY................. 23.4 454.1 -.9 299 689 .4 173
Kings, NY................ 44.0 462.9 1.0 170 691 .9 134
Monroe, NY............... 17.8 380.3 -.4 277 782 1.8 72
Nassau, NY............... 52.2 600.1 1.0 170 867 1.4 94
New York, NY............. 116.2 2,292.3 1.9 111 1,421 .3 182
Oneida, NY............... 5.3 110.1 1.3 147 605 -1.3 286
Onondaga, NY............. 12.8 250.6 -.5 285 734 2.1 62
Orange, NY............... 9.8 130.0 .3 230 676 1.2 113
Queens, NY............... 41.9 489.6 1.1 161 782 -1.4 288
Richmond, NY............. 8.5 91.3 1.9 111 711 .0 203
Rockland, NY............. 9.6 113.1 .6 204 831 2.8 38
Suffolk, NY.............. 49.6 617.2 .5 213 850 1.8 72
Westchester, NY.......... 36.3 413.9 .5 213 1,029 1.8 72
Buncombe, NC............. 7.3 112.9 2.2 96 629 2.4 52
Catawba, NC.............. 4.4 87.6 1.7 118 617 .8 140
Cumberland, NC........... 5.9 116.7 -.7 289 605 -1.5 291
Durham, NC............... 6.3 177.1 3.8 28 1,037 1.5 86
Forsyth, NC.............. 8.6 180.7 .8 187 762 -.1 212
Guilford, NC............. 13.8 275.1 .5 213 714 1.1 120
Mecklenburg, NC.......... 28.7 544.4 3.5 37 922 3.1 34
New Hanover, NC.......... 6.9 101.9 3.5 37 644 1.4 94
Wake, NC................. 25.0 426.7 3.6 33 789 1.3 102
Cass, ND................. 5.7 96.2 3.4 43 649 .2 194
Butler, OH............... 7.3 146.0 1.0 170 694 -2.4 302
Cuyahoga, OH............. 38.1 757.1 -.4 277 800 -.6 249
Franklin, OH............. 29.3 683.2 .4 220 805 .4 173
Hamilton, OH............. 24.1 525.5 -.7 289 871 .8 140
Lake, OH................. 6.9 100.5 -.4 277 646 -2.7 308
Lorain, OH............... 6.3 102.3 -.2 266 672 -3.7 317
Lucas, OH................ 10.9 225.5 -.7 289 720 1.3 102
Mahoning, OH............. 6.3 105.4 .6 204 584 .0 203
Montgomery, OH........... 13.0 273.5 -1.8 312 777 3.7 27
Stark, OH................ 9.1 162.9 -.7 289 633 .6 158
Summit, OH............... 14.9 274.8 .3 230 715 -1.7 298
Trumbull, OH............. 4.8 83.1 -4.5 321 777 12.3 3
Oklahoma, OK............. 23.0 424.0 1.5 131 708 3.2 30
Tulsa, OK................ 19.1 342.8 2.6 68 705 .3 182
Clackamas, OR............ 12.4 148.1 2.0 105 740 -.5 241
Jackson, OR.............. 6.7 85.9 1.6 126 599 -.3 225
Lane, OR................. 10.8 150.6 2.3 89 634 .3 182
Marion, OR............... 9.2 142.3 2.1 99 638 4.1 22
Multnomah, OR............ 26.8 442.5 3.3 48 803 .5 165
Washington, OR........... 15.8 247.7 3.2 51 925 -1.5 291
Allegheny, PA............ 35.3 683.8 .4 220 823 1.5 86
Berks, PA................ 9.1 169.8 2.2 96 716 1.3 102
Bucks, PA................ 20.0 264.6 1.1 161 766 .8 140
Butler, PA............... 4.7 77.6 2.5 73 668 1.2 113
Chester, PA.............. 14.9 236.0 1.4 136 983 -.2 219
Cumberland, PA........... 5.9 126.7 .5 213 733 -2.7 308
Dauphin, PA.............. 7.3 183.0 2.5 73 766 -1.5 291
Delaware, PA............. 13.6 209.7 .8 187 826 1.6 82
Erie, PA................. 7.2 129.0 -.5 285 632 .8 140
Lackawanna, PA........... 5.7 101.8 .9 178 613 -.5 241
Lancaster, PA............ 12.1 229.6 .1 252 687 -1.2 283
Lehigh, PA............... 8.4 178.3 2.5 73 781 2.9 36
Luzerne, PA.............. 7.9 143.3 -1.0 301 623 -.6 249
Montgomery, PA........... 27.5 484.6 .2 240 964 .6 158
Northampton, PA.......... 6.4 99.0 1.2 156 701 -.4 234
Philadelphia, PA......... 29.2 632.9 -.3 274 929 .8 140
Washington, PA........... 5.3 79.0 2.0 105 715 4.5 17
Westmoreland, PA......... 9.5 138.8 -1.4 308 652 2.0 65
York, PA................. 8.9 175.5 1.3 147 697 -.7 257
Kent, RI................. 5.7 83.5 .4 220 849 18.4 1
Providence, RI........... 18.2 291.1 .4 220 754 .8 140
Charleston, SC........... 13.8 203.7 2.6 68 671 -.3 225
Greenville, SC........... 13.8 231.6 1.6 126 684 -.1 212
Horry, SC................ 9.6 117.4 4.6 9 517 2.8 38
Lexington, SC............ 6.4 92.9 4.2 22 613 1.0 127
Richland, SC............. 10.7 212.7 -.8 295 705 2.3 55
Spartanburg, SC.......... 6.8 116.7 .7 192 698 2.2 59
Minnehaha, SD............ 6.3 113.4 2.0 105 668 .6 158
Davidson, TN............. 18.2 451.4 1.4 136 792 2.5 49
Hamilton, TN............. 8.5 195.0 .7 192 685 -.1 212
Knox, TN................. 10.7 226.7 3.0 54 670 .3 182
Rutherford, TN........... 4.0 99.8 3.5 37 711 6.0 13
Shelby, TN............... 20.1 509.4 .2 240 814 .0 203
Bell, TX................. 4.4 95.5 .9 178 615 3.2 30
Bexar, TX................ 31.1 704.2 3.6 33 696 3.0 35
Brazoria, TX............. 4.4 83.2 4.3 20 748 4.2 19
Brazos, TX............... 3.7 84.3 1.4 136 558 1.3 102
Cameron, TX.............. 6.3 121.4 4.1 25 493 1.4 94
Collin, TX............... 15.3 270.0 7.2 3 921 .9 134
Dallas, TX............... 67.0 1,466.0 2.7 65 961 2.2 59
Denton, TX............... 9.7 157.1 (7) - 693 (7) -
El Paso, TX.............. 13.0 264.1 1.4 136 570 2.3 55
Fort Bend, TX............ 7.5 116.4 4.4 16 820 -5.0 321
Galveston, TX............ 5.1 93.6 (7) - 723 7.1 10
Harris, TX............... 92.7 1,959.1 4.2 22 950 2.0 65
Hidalgo, TX.............. 10.1 203.7 3.7 30 514 2.8 38
Jefferson, TX............ 5.8 121.7 2.7 65 781 10.5 4
Lubbock, TX.............. 6.6 122.9 2.5 73 594 .5 165
McLennan, TX............. 4.8 102.9 1.2 156 633 1.3 102
Montgomery, TX........... 7.3 111.6 5.7 5 723 -1.0 273
Nueces, TX............... 8.0 150.0 2.1 99 671 2.6 44
Smith, TX................ 5.1 91.5 2.5 73 691 1.9 70
Tarrant, TX.............. 35.4 744.7 2.8 60 814 3.2 30
Travis, TX............... 26.6 553.0 4.5 12 883 -.1 212
Webb, TX................. 4.6 85.3 3.0 54 525 .2 194
Williamson, TX........... 6.3 108.6 5.5 6 742 -5.7 322
Davis, UT................ 7.3 101.6 4.2 22 635 -.2 219
Salt Lake, UT............ 39.4 572.1 4.6 9 729 1.4 94
Utah, UT................. 13.0 169.2 5.5 6 617 4.2 19
Weber, UT................ 5.8 91.8 2.5 73 593 1.7 79
Chittenden, VT........... 5.8 96.6 1.1 161 778 1.8 72
Arlington, VA............ 7.4 157.4 .9 178 1,323 1.2 113
Chesterfield, VA......... 7.1 118.3 2.2 96 719 2.0 65
Fairfax, VA.............. 31.8 576.3 1.7 118 1,179 -.8 264
Henrico, VA.............. 8.8 175.1 .7 192 809 -.7 257
Loudoun, VA.............. 7.6 126.4 1.0 170 966 -4.2 320
Prince William, VA....... 6.6 104.0 1.7 118 714 -.8 264
Alexandria City, VA...... 5.9 94.8 1.0 170 1,025 1.2 113
Chesapeake City, VA...... 5.4 98.9 1.5 131 639 1.6 82
Newport News City, VA.... 3.9 97.9 .1 252 711 -.4 234
Norfolk City, VA......... 5.7 141.4 -1.1 302 757 -.8 264
Richmond City, VA........ 7.0 161.5 .6 204 890 1.0 127
Virginia Beach City, VA.. 11.3 178.8 -.2 266 627 1.3 102
Clark, WA................ 11.4 131.4 2.3 89 723 .4 173
King, WA................. 75.6 1,167.1 3.6 33 1,044 4.7 15
Kitsap, WA............... 6.5 84.5 2.0 105 709 -3.3 314
Pierce, WA............... 20.0 269.4 2.6 68 716 .1 198
Snohomish, WA............ 16.9 235.3 8.2 2 798 -.7 257
Spokane, WA.............. 14.8 206.9 3.4 43 651 .9 134
Thurston, WA............. 6.6 96.9 3.5 37 733 2.8 38
Whatcom, WA.............. 6.7 80.8 2.7 65 632 3.8 26
Yakima, WA............... 7.8 108.5 2.8 60 537 2.1 62
Kanawha, WV.............. 6.1 108.1 .7 192 676 1.2 113
Brown, WI................ 6.7 149.2 -.1 261 707 2.3 55
Dane, WI................. 13.9 299.4 -.5 285 784 .8 140
Milwaukee, WI............ 21.4 497.2 .1 252 783 .4 173
Outagamie, WI............ 5.0 102.5 -.2 266 680 .4 173
Racine, WI............... 4.2 76.9 .0 257 715 -2.6 304
Waukesha, WI............. 13.3 235.8 .5 213 790 1.4 94
Winnebago, WI............ 3.8 89.1 -.2 266 737 .0 203
San Juan, PR............. 14.8 299.0 -4.3 (8) 514 1.6 (8)
1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 325 U.S. counties comprise 70.7 percent of the total covered workers
in the U.S.
2 Data are preliminary.
3 Includes areas not officially designated as counties. See Technical Note.
4 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. Covered (1) establishments, employment, and wages in the ten largest counties,
third quarter 2006 (2)
Employment Average weekly
wage (4)
Establishments,
third quarter
County by NAICS supersector 2006 Percent Percent
(thousands) September change, Average change,
2006 September weekly third
(thousands) 2005-06 (3) wage quarter
2005-06 (3)
United States (5)............................ 8,841.2 134,988.9 1.5 $784 0.9
Private industry........................... 8,562.2 113,752.0 1.7 776 .8
Natural resources and mining............. 124.0 1,895.7 3.3 761 3.7
Construction............................. 882.5 7,852.5 3.2 829 1.7
Manufacturing............................ 363.4 14,152.6 -0 5 947 .1
Trade, transportation, and utilities..... 1,899.4 25,982.1 1.1 685 .4
Information.............................. 144.9 3,034.8 - 7 1,217 .7
Financial activities..................... 852.0 8,175.1 1.0 1,133 1.9
Professional and business services....... 1,437.6 17,684.7 3.1 938 1.0
Education and health services............ 799.9 16,992.1 2.6 748 .4
Leisure and hospitality.................. 711.4 13,290.1 2.0 334 .9
Other services........................... 1,128.5 4,373.4 .8 510 1.0
Government................................. 279.0 21,236.9 .8 832 1.7
Los Angeles, CA.............................. 392.8 4,161.2 .7 894 1.7
Private industry........................... 389.1 3,608.2 .8 872 1.2
Natural resources and mining............. 0.6 12.2 7.4 1,184 -1.9
Construction............................. 14.2 160.0 2.8 896 1.8
Manufacturing............................ 15.9 463.8 -1.7 937 3.3
Trade, transportation, and utilities..... 55.6 807.9 .8 750 .8
Information.............................. 9.0 206.4 -1.6 1,486 1.3
Financial activities..................... 25.2 247.2 -.2 1,440 3.0
Professional and business services....... 43.4 603.5 1.4 978 -1.4
Education and health services............ 28.2 469.4 1.7 834 2.2
Leisure and hospitality.................. 27.1 392.5 1.9 513 2.8
Other services........................... 169.9 245.1 1.9 413 2.2
Government................................. 3.7 553.0 .2 1,038 4.6
Cook, IL..................................... 135.0 2,553.4 .7 928 1.0
Private industry........................... 133.8 2,241.8 .9 925 1.3
Natural resources and mining............. .1 1.6 -.9 1,036 7.2
Construction............................. 11.8 100.6 3.1 1,147 3.1
Manufacturing............................ 7.2 245.6 -1.8 956 -.1
Trade, transportation, and utilities..... 27.5 477.6 .3 784 3.3
Information.............................. 2.5 58.6 -3.0 1,275 -2.8
Financial activities..................... 15.5 219.5 .4 1,433 2.9
Professional and business services....... 27.6 441.4 2.5 1,135 -.1
Education and health services............ 13.2 363.4 1.8 813 1.0
Leisure and hospitality.................. 11.3 236.1 2.0 411 2.2
Other services........................... 13.4 93.8 -1.9 670 1.1
Government................................. 1.2 311.5 -.8 (6) (6)
New York, NY................................. 116.2 2,292.3 1.9 1,421 .3
Private industry........................... 115.9 1,852.5 2.4 1,519 .9
Natural resources and mining............. .0 0.1 -7.3 1,571 15.5
Construction............................. 2.2 32.4 5.1 1,395 2.0
Manufacturing............................ 3.0 38.9 -7.5 1,105 2.2
Trade, transportation, and utilities..... 21.3 241.0 1.2 1,081 1.1
Information.............................. 4.2 132.4 .5 1,825 2.9
Financial activities..................... 17.8 369.7 3.2 2,619 .7
Professional and business services....... 23.2 464.3 2.9 1,637 .7
Education and health services............ 8.3 276.2 1.5 967 -.9
Leisure and hospitality.................. 10.7 198.8 2.1 685 -.3
Other services........................... 16.8 85.3 1.2 855 4.3
Government................................. .2 439.9 -.5 1,010 -4.6
Harris, TX................................... 92.7 1,959.1 4.2 950 2.0
Private industry........................... 92.3 1,708.2 4.5 960 1.6
Natural resources and mining............. 1.4 73.7 10.7 2,286 -6.3
Construction............................. 6.3 142.0 7.1 917 6.3
Manufacturing............................ 4.6 178.4 5.5 1,204 1.4
Trade, transportation, and utilities..... 21.2 409.4 3.4 846 1.7
Information.............................. 1.3 31.9 .7 1,169 1.0
Financial activities..................... 10.1 117.4 .2 1,182 5.2
Professional and business services....... 18.0 320.2 5.1 1,074 1.4
Education and health services............ 9.7 204.0 3.6 812 .9
Leisure and hospitality.................. 7.0 170.1 4.3 358 .6
Other services........................... 10.6 56.0 1.4 551 .7
Government................................. .4 250.9 2.1 878 4.9
Maricopa, AZ................................. 92.3 1,819.1 4.4 792 .5
Private industry........................... 91.7 1,605.4 4.8 779 -.4
Natural resources and mining............. .5 8.1 2.2 682 12.9
Construction............................. 9.5 177.8 5.9 804 1.4
Manufacturing............................ 3.4 136.9 2.3 1,082 .6
Trade, transportation, and utilities..... 19.7 366.7 4.1 750 -1.8
Information.............................. 1.5 31.3 -1.3 1,024 3.7
Financial activities..................... 11.3 150.3 2.7 1,027 -.1
Professional and business services....... 19.9 316.8 5.8 756 -.4
Education and health services............ 8.9 188.6 6.2 835 -.4
Leisure and hospitality.................. 6.4 174.0 4.2 368 -1.6
Other services........................... 6.4 47.8 3.0 550 .5
Government................................. .6 213.7 1.2 897 7.3
Orange, CA................................... 95.9 1,517.9 1.1 897 -1.1
Private industry........................... 94.5 1,378.8 1.2 893 -1.0
Natural resources and mining............. .2 5.1 -16.5 636 1.4
Construction............................. 7.1 111.0 3.7 972 1.1
Manufacturing............................ 5.6 183.4 .5 1,083 2.4
Trade, transportation, and utilities..... 17.9 271.2 .2 826 .2
Information.............................. 1.4 31.1 -2.3 1,199 -3.5
Financial activities..................... 11.5 137.0 -5.1 1,381 -5.9
Professional and business services....... 19.4 280.4 3.7 931 .1
Education and health services............ 9.9 138.9 4.8 849 .4
Leisure and hospitality.................. 7.1 172.2 3.0 387 .0
Other services........................... 14.4 48.5 -1.7 549 .5
Government................................. 1.4 139.0 .3 938 -1.6
Dallas, TX................................... 67.0 1,466.0 2.7 961 2.2
Private industry........................... 66.5 1,306.9 3.0 969 2.1
Natural resources and mining............. .6 7.4 3.4 3,640 48.6
Construction............................. 4.3 80.4 2.4 877 2.5
Manufacturing............................ 3.2 148.8 2.0 1,099 -3.9
Trade, transportation, and utilities..... 14.8 303.9 1.4 907 1.8
Information.............................. 1.7 52.7 -2.0 1,300 2.9
Financial activities..................... 8.5 140.8 3.3 1,285 6.4
Professional and business services....... 14.0 263.3 4.4 1,050 2.2
Education and health services............ 6.4 139.2 4.1 876 -1.9
Leisure and hospitality.................. 5.1 128.1 4.6 436 3.1
Other services........................... 6.4 38.9 1.2 608 .7
Government................................. .4 159.1 .3 894 3.4
San Diego, CA................................ 92.5 1,321.7 .9 850 -.7
Private industry........................... 91.0 1,106.4 .9 832 -.8
Natural resources and mining............. .8 11.6 -1.6 527 .6
Construction............................. 7.3 95.0 .7 877 -1.7
Manufacturing............................ 3.3 103.6 -.7 1,112 1.6
Trade, transportation, and utilities..... 14.6 220.1 .4 695 -.3
Information.............................. 1.3 37.1 -.7 1,554 -19.2
Financial activities..................... 10.1 83.8 -.8 1,041 -3.5
Professional and business services....... 16.6 215.6 1.2 1,052 4.9
Education and health services............ 8.0 123.5 1.3 816 1.6
Leisure and hospitality.................. 6.8 160.0 3.5 397 -.3
Other services........................... 22.0 56.0 1.2 479 1.3
Government................................. 1.5 215.3 1.2 944 -.1
King, WA..................................... 75.6 1,167.1 3.6 1,044 4.7
Private industry........................... 75.2 1,015.2 4.2 1,052 4.6
Natural resources and mining............. .4 3.1 -3.7 1,193 17.4
Construction............................. 6.6 70.5 11.0 954 .1
Manufacturing............................ 2.5 112.4 11.5 1,198 -3.5
Trade, transportation, and utilities..... 14.7 221.2 1.9 876 2.8
Information.............................. 1.7 74.0 5.2 2,812 19.4
Financial activities..................... 6.8 76.0 -.4 1,247 6.5
Professional and business services....... 12.4 183.7 5.7 1,095 .3
Education and health services............ 6.3 118.2 2.3 796 .8
Leisure and hospitality.................. 5.9 110.8 2.6 423 2.4
Other services........................... 17.8 45.2 .0 537 2.7
Government................................. .5 151.9 -.4 984 4.5
Miami-Dade, FL............................... 84.1 1,008.4 .6 792 1.5
Private industry........................... 83.8 858.2 1.0 760 1.7
Natural resources and mining............. .5 8.4 -2.6 487 4.1
Construction............................. 5.8 53.2 13.6 795 -.9
Manufacturing............................ 2.6 47.5 -3.2 700 -2.2
Trade, transportation, and utilities..... 22.9 249.0 1.7 705 -.8
Information.............................. 1.6 21.4 -5.4 1,139 3.5
Financial activities..................... 10.1 71.3 3.4 1,085 .3
Professional and business services....... 16.9 138.2 -5.7 943 7.8
Education and health services............ 8.6 133.1 3.4 763 1.6
Leisure and hospitality.................. 5.6 98.4 -.3 450 (6)
Other services........................... 7.5 34.5 1.9 490 2.3
Government................................. .3 150.2 -1.4 988 1.6
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 2006 (2)
Employment Average weekly
wage (5)
Establishments,
third quarter
County (3) 2006 Percent Percent
(thousands) September change, Average change,
2006 September weekly third
(thousands) 2005-06 (4) wage quarter
2005-06 (4)
United States (6)........ 8,841.2 134,988.9 1.5 $784 0.9
Jefferson, AL............ 18.6 374.6 0.8 803 1.0
Anchorage Borough, AK.... 8.2 148.8 .5 849 -.7
Maricopa, AZ............. 92.3 1,819.1 4.4 792 .5
Pulaski, AR.............. 14.2 249.9 1.9 717 1.3
Los Angeles, CA.......... 392.8 4,161.2 .7 894 1.7
Denver, CO............... 25.5 436.3 1.7 988 4.1
Hartford, CT............. 25.0 500.4 2.3 945 -2.3
New Castle, DE........... 19.6 282.8 .2 957 4.0
Washington, DC........... 32.0 674.2 .7 1,307 3.6
Miami-Dade, FL........... 84.1 1,008.4 .6 792 1.5
Fulton, GA............... 39.6 777.7 1.3 1,016 1.0
Honolulu, HI............. 24.0 452.2 2.3 744 .5
Ada, ID.................. 14.7 210.7 4.4 727 1.1
Cook, IL................. 135.0 2,553.4 .7 928 1.0
Marion, IN............... 23.6 583.0 .2 814 -.5
Polk, IA................. 14.4 271.3 2.4 783 -1.0
Johnson, KS.............. 20.0 312.0 3.4 812 -1.6
Jefferson, KY............ 22.5 433.2 1.7 775 (7)
East Baton Rouge, LA..... 13.8 262.2 2.5 698 7.4
Cumberland, ME........... 12.0 172.6 .7 711 .3
Montgomery, MD........... 32.4 467.1 1.3 1,034 .6
Middlesex, MA............ 47.1 804.6 1.6 1,108 -.3
Wayne, MI................ 33.6 769.1 -2.6 905 -1.5
Hennepin, MN............. 41.9 841.4 .2 982 -.9
Hinds, MS................ 6.5 128.5 1.3 697 1.3
St. Louis, MO............ 33.7 625.8 .7 825 -.2
Yellowstone, MT.......... 5.5 74.8 1.6 637 3.1
Douglas, NE.............. 15.4 314.5 1.2 734 -.9
Clark, NV................ 46.2 922.5 4.4 751 -.3
Hillsborough, NH......... 12.5 196.8 -.3 861 1.1
Bergen, NJ............... 34.7 450.7 .6 969 .3
Bernalillo, NM........... 17.0 335.0 3.4 709 .4
New York, NY............. 116.2 2,292.3 1.9 1,421 .3
Mecklenburg, NC.......... 28.7 544.4 3.5 922 3.1
Cass, ND................. 5.7 96.2 3.4 649 .2
Cuyahoga, OH............. 38.1 757.1 -.4 800 -.6
Oklahoma, OK............. 23.0 424.0 1.5 708 3.2
Multnomah, OR............ 26.8 442.5 3.3 803 .5
Allegheny, PA............ 35.3 683.8 .4 823 1.5
Providence, RI........... 18.2 291.1 .4 754 .8
Greenville, SC........... 13.8 231.6 1.6 684 -.1
Minnehaha, SD............ 6.3 113.4 2.0 668 .6
Shelby, TN............... 20.1 509.4 .2 814 .0
Harris, TX............... 92.7 1,959.1 4.2 950 2.0
Salt Lake, UT............ 39.4 572.1 4.6 729 1.4
Chittenden, VT........... 5.8 96.6 1.1 778 1.8
Fairfax, VA.............. 31.8 576.3 1.7 1,179 -.8
King, WA................. 75.6 1,167.1 3.6 1,044 4.7
Kanawha, WV.............. 6.1 108.1 .7 676 1.2
Milwaukee, WI............ 21.4 497.2 .1 783 .4
Laramie, WY.............. 3.1 42.1 2.5 757 19.4
San Juan, PR............. 14.8 299.0 -4.3 514 1.6
St. Thomas, VI........... 1.8 22.0 -2.6 644 12.0
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 2006 (2)
Employment Average weekly
wage (3)
Establishments,
third quarter
State 2006 Percent Percent
(thousands) September change, Average change,
2006 September weekly third
(thousands) 2005-06 wage quarter
2005-06
United States(4)......... 8,841.2 134,988.9 1.5 $784 0.9
Alabama.................. 117.3 1,938.9 1.6 682 1.9
Alaska................... 21.1 324.8 1.4 798 .1
Arizona.................. 150.6 2,629.0 4.2 753 1.1
Arkansas................. 81.9 1,183.9 1.5 603 .7
California............... 1,270.4 15,655.0 1.5 892 .6
Colorado................. 176.9 2,260.1 2.2 819 1.4
Connecticut.............. 111.9 1,680.7 1.6 957 -.9
Delaware................. 30.2 424.6 0.5 850 3.4
District of Columbia..... 32.0 674.2 .7 1,307 3.6
Florida.................. 588.1 7,941.7 1.9 713 .7
Georgia.................. 264.5 4,039.3 2.0 752 .5
Hawaii................... 37.4 621.2 2.3 722 1.1
Idaho.................... 55.3 661.2 4.1 613 1.3
Illinois................. 350.2 5,883.6 1.1 831 .7
Indiana.................. 155.4 2,922.7 .3 687 -.3
Iowa..................... 92.8 1,480.7 1.2 641 .0
Kansas................... 85.6 1,347.3 2.4 662 .6
Kentucky................. 110.7 1,795.1 .9 656 .6
Louisiana................ 122.5 1,835.7 3.7 683 7.1
Maine.................... 49.4 610.2 .6 636 .8
Maryland................. 161.5 2,545.0 .7 858 .5
Massachusetts............ 208.8 3,228.1 .9 950 .3
Michigan................. 261.0 4,278.9 -1.8 790 .3
Minnesota................ 165.5 2,685.1 .0 784 -.6
Mississippi.............. 69.1 1,134.3 2.9 585 2.1
Missouri................. 172.1 2,725.1 1.1 691 .0
Montana.................. 41.4 434.4 2.3 581 3.0
Nebraska................. 57.8 906.9 1.1 633 .0
Nevada................... 72.4 1,287.6 3.7 751 .0
New Hampshire............ 48.9 634.9 .6 774 .3
New Jersey............... 279.8 3,984.7 .7 931 .3
New Mexico............... 52.6 826.1 4.4 654 4.0
New York................. 573.2 8,471.7 .8 950 1.1
North Carolina........... 241.5 3,982.6 1.8 700 1.6
North Dakota............. 24.7 342.2 2.0 589 1.4
Ohio..................... 291.7 5,350.9 -.1 725 .3
Oklahoma................. 97.3 1,517.6 2.2 633 3.3
Oregon................... 128.6 1,729.2 2.7 719 .7
Pennsylvania............. 335.9 5,644.8 .8 768 .5
Rhode Island............. 36.0 490.8 .8 763 3.7
South Carolina........... 132.4 1,866.0 1.8 642 1.1
South Dakota............. 29.8 389.6 2.1 571 .7
Tennessee................ 137.1 2,761.1 1.4 698 1.2
Texas.................... 536.7 10,019.0 3.6 786 2.5
Utah..................... 88.1 1,188.7 4.8 660 2.0
Vermont.................. 24.7 305.8 .6 672 1.4
Virginia................. 220.0 3,649.5 1.0 815 -.1
Washington............... 214.5 2,911.9 3.3 823 2.7
West Virginia............ 48.2 711.8 1.2 599 1.7
Wisconsin................ 161.8 2,800.8 .5 687 .1
Wyoming.................. 24.1 274.1 4.6 706 10.0
Puerto Rico.............. 60.6 1,020.9 -1.9 439 1.2
Virgin Islands........... 3.4 43.2 -2.0 692 12.5
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.