In March 2007, Orleans 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. Orleans County, which in-
cludes the city of New Orleans, experienced an over-the-year employment
gain of 15.0 percent compared with national job growth of 1.4 percent.
Harrison County, Miss., followed closely behind Orleans with an over-the-
year gain of 14.5 percent. Employment gains in Orleans and Harrison coun-
ties reflected significant recovery following substantial job losses that
occurred in September 2005 due to Hurricane Katrina. Trumbull County,
Ohio, had the largest over-the-year gain in average weekly wages in the
first quarter of 2007, with an increase of 22.3 percent. The U.S. average
weekly wage rose by 5.1 percent over the same time span.
Of the 328 largest counties in the United States, as measured by 2006
annual average employment, 117 had over-the-year percentage growth in
employment above the national average (1.4 percent) in March 2007 and 196
experienced changes below the national average. The percent change in
average weekly wages was higher than the national average (5.1 percent)
in 77 of the largest U.S. counties, but was below the national average in
240 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 8.9 million
employer reports cover 134.3 million full- and part-time workers. The
attached tables contain data for the nation and for the 328 U.S. counties
with annual average employment levels of 75,000 or more in 2006. March 2007
employment and 2007 first-quarter average weekly wages for all states are
provided in table 4 of this release. Data for all states, metropolitan
statistical areas, counties, and the nation through the fourth quarter of
2006 are available on the BLS Web site at http://www.bls.gov/cew/. Pre-
liminary data for first quarter 2007 and final data for 2006 will be avail-
able later in October on the BLS Web site.
———————————————————————
| Changes to County Employment and Wages Data |
| |
| Beginning with the Quarterly Census of Employment and Wages |
| (QCEW) data presented in this release, the Bureau of Labor Statis- |
| tics is introducing the 2007 North American Industry Classification |
| System (NAICS 2007). The conversion to NAICS 2007 resulted in |
| minor changes to the data and more accurately reflects the under- |
| lying business activities in selected industries. For further in- |
| formation on the NAICS 2007 revision and its effect on QCEW data, |
| see the note on page 6 and the U.S. Census Bureau Web site at |
| http://www.census.gov/epcd/naics07/index.html. |
———————————————————————
– 2 –
Table A. Top 10 large counties ranked by March 2007 employment, March 2006-07
employment growth, and March 2006-07 percent growth in employment
————————————————————————————
Employment in large counties
————————————————————————————
| |
March 2007 employment | Growth in employment, | Percent growth
(thousands) | March 2006-07 | in employment,
| (thousands) | March 2006-07
————————————————————————————
| |
United States ….. 134,320.6| United States ….. 1,801.9| United States …… 1.4
—————————–|—————————-|————————-
| |
Los Angeles, Calif. . 4,210.2| Harris, Texas …….. 72.5| Orleans, La. …… 15.0
Cook, Ill. ………. 2,510.1| New York, N.Y. ……. 52.9| Harrison, Miss. … 14.5
New York, N.Y. …… 2,331.5| Dallas, Texas …….. 46.0| Utah, Utah …….. 7.3
Harris, Texas ……. 1,985.7| King, Wash. ………. 41.1| Williamson, Texas . 7.0
Maricopa, Ariz. ….. 1,828.2| Mecklenburg, N.C. …. 32.8| Jefferson, La. …. 6.6
Orange, Calif. …… 1,516.1| Maricopa, Ariz. …… 30.5| Mecklenburg, N.C. . 6.2
Dallas, Texas ……. 1,469.4| Travis, Texas …….. 25.4| New Hanover, N.C. . 6.2
San Diego, Calif. … 1,319.8| Salt Lake, Utah …… 25.4| Williamson, Tenn. . 6.0
King, Wash. ……… 1,157.5| Wake, N.C. ……….. 22.6| Wake, N.C. …….. 5.4
Miami-Dade, Fla. …. 1,025.1| Orleans, La. ……… 21.8| Montgomery, Texas . 5.3
| |
————————————————————————————
Large County Employment
In March 2007, national employment, as measured by the QCEW program, was
134.3 million, up by 1.4 percent from March 2006. The 328 U.S. counties with
75,000 or more employees accounted for 71.1 percent of total U.S. covered em-
ployment and 78.2 percent of total covered wages. These 328 counties had a
net job gain of 1,192,248 over the year, accounting for 66.2 percent of the
overall U.S. employment increase. Employment rose in 255 of the large counties
from March 2006 to March 2007. Orleans County, La., had the largest over-the-
year percentage increase in employment (15.0 percent). Harrison, Miss., had
the next largest increase, 14.5 percent, followed by the counties of Utah, Utah
(7.3 percent), Williamson, Texas (7.0 percent), and Jefferson, La. (6.6 percent).
The large employment gains in Orleans, Harrison, and Jefferson counties reflected
significant recovery from the substantial job losses in September 2005, which
were related to Hurricane Katrina. (See table 1.)
Employment declined in 61 counties from March 2006 to March 2007. The
largest percentage decline in employment was in Trumbull County, Ohio (-6.2
percent). Macomb, Mich., had the next largest employment decline (-3.8 percent),
followed by the counties of Wayne, Mich., and Montgomery, Ohio (-3.2 percent each),
and Elkhart, Ind. (-2.9 percent). In each of these five counties, the greatest
number of jobs lost occurred in the manufacturing sector.
The largest gains in the level of employment from March 2006 to March
2007 were recorded in the counties of Harris, Texas (72,500), New York, N.Y.
(52,900), Dallas, Texas (46,000), King, Wash. (41,100), and Mecklenburg, N.C.
(32,800). (See table A.)
The largest decline in employment levels occurred in Wayne, Mich. (-24,600),
followed by the counties of Macomb, Mich. (-12,400), Oakland, Mich. (-10,600),
Montgomery, Ohio (-8,700), and Pinellas, Fla. (-5,400). Each of the 10 large
counties in Michigan experienced employment declines in March 2007.
– 3 –
Table B. Top 10 large counties ranked by first quarter 2007 average weekly wages,
first quarter 2006-07 growth in average weekly wages, and first quarter 2006-07
percent growth in average weekly wages
————————————————————————————
Average weekly wage in large counties
————————————————————————————
Average weekly wage, | Growth in average weekly | Percent growth in
first quarter 2007 | wage, first quarter | average weekly wage,
| 2006-07 | first quarter 2006-07
————————————————————————————
| |
United States ……… $885| United States …….. $43| United States ……. 5.1
————————————————————————————
| |
New York, N.Y. …… $2,821| New York, N.Y. …… $403| Trumbull, Ohio …… 22.3
Fairfield, Conn. …. 1,979| Suffolk, Mass. …… 162| New York, N.Y. …… 16.7
Suffolk, Mass. …… 1,659| Trumbull, Ohio …… 157| Cobb, Ga. ……….. 11.2
San Francisco, Calif. 1,639| Fairfield, Conn. …. 137| Suffolk, Mass. …… 10.8
Somerset, N.J. …… 1,615| Somerset, N.J. …… 133| Clay, Mo. ……….. 9.7
Santa Clara, Calif. . 1,584| San Francisco, Calif. 124| Montgomery, Ohio …. 9.3
San Mateo, Calif. … 1,447| Hudson, N.J. …….. 115| Somerset, N.J. …… 9.0
Arlington, Va. …… 1,447| Westchester, N.Y. … 107| Westchester, N.Y. … 8.9
Hudson, N.J. …….. 1,434| San Mateo, Calif. … 106| Hudson, N.J. …….. 8.7
Washington, D.C. …. 1,428| Cobb, Ga. ……….. 100| East Baton Rouge, La. 8.6
| |
————————————————————————————
Large County Average Weekly Wages
The national average weekly wage in the first quarter of 2007 was $885.
Average weekly wages were higher than the national average in 92 of the
largest 328 U.S. counties. New York County, N.Y., held the top position
among the highest-paid large counties with an average weekly wage of $2,821.
Fairfield, Conn., was second with an average weekly wage of $1,979, followed
by Suffolk, Mass. ($1,659), San Francisco, Calif. ($1,639), and Somerset, N.J.
($1,615). (See table B.)
There were 236 counties with an average weekly wage below the national
average in the first quarter of 2007. The lowest average weekly wage was
reported in Cameron County, Texas ($502), followed by the counties of
Hidalgo, Texas ($516), Horry, S.C. ($536), Webb, Texas ($542), and Yakima,
Wash. ($569). (See table 1.)
Over the year, the national average weekly wage rose by 5.1 percent. Among
the largest counties, Trumbull, Ohio, led the nation in growth in average
weekly wages with an increase of 22.3 percent from the first quarter of 2006.
New York, N.Y., was second with growth of 16.7 percent, followed by the counties
of Cobb, Ga. (11.2 percent), Suffolk, Mass. (10.8 percent), and Clay, Mo. (9.7
percent). New York County experienced substantial over-the-year wage growth
which had a significant impact on national average weekly wage growth in the
first quarter of 2007. Without New York County’s over-the-year employment and
wage growth, national average weekly wage growth would have been 4.2 percent;
a 0.9 percentage point reduction.
Fourteen counties experienced over-the-year declines in average weekly
wages. Bibb, Ga., and Loudoun, Va., led the nation in declines (-3.0 percent
each), followed by the counties of Orleans, La., and Norfolk, Mass. (-2.7 per-
cent each), and Arapahoe, Colo., Sarasota, Fla., and Peoria, Ill. (-1.8 percent
each).
– 4 –
Ten Largest U.S. Counties
Each of the 10 largest counties (based on 2006 annual average employment
levels) reported increases in employment from March 2006 to March 2007. Harris,
Texas, experienced the largest percentage gain in employment among the largest
counties with a 3.8 percent increase. Within Harris County, employment rose in
every industry group. The largest gains were in natural resources and mining
(11.0 percent) and manufacturing (5.6 percent). King, Wash., had the next
largest increase in employment, 3.7 percent, followed by Dallas, Texas (3.2
percent). The smallest percentage increase in employment occurred in Orange,
Calif. (0.1 percent), followed by San Diego, Calif., and Los Angeles, Calif.
(0.4 percent each). (See table 2.)
Each of the 10 largest U.S. counties saw over-the-year increases in
average weekly wages. New York, N.Y., had the fastest growth in wages
among the 10 largest counties with a gain of 16.7 percent. Within New
York County, average weekly wages increased the most in financial activ-
ities (24.2 percent) and in manufacturing (14.6 percent). Harris, Texas,
was second in wage growth with a gain of 8.5 percent, followed by Cook, Ill.
(6.5 percent). The smallest wage gains among the 10 largest counties oc-
curred in San Diego, Calif., and Orange, Calif. (3.2 percent each) and Los
Angeles, Calif. (3.3 percent).
Largest County by State
Table 3 shows March 2007 employment and the 2007 first quarter average
weekly wage in the largest county in each state, which is based on 2006
annual average employment levels. (This table includes two counties–
Yellowstone, Mont., and Laramie, Wyo.–that had employment levels below
75,000 in 2006.) The employment levels in the counties in table 3 in March
2007 ranged from approximately 4.2 million in Los Angeles County, Calif.,
to 41,900 in Laramie County, Wyo. The highest average weekly wage of these
counties was in New York, N.Y. ($2,821) while the lowest average weekly wage
was in Yellowstone, Mont. ($672).
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 calling (202) 691-6567.
– 5 –
For a more detailed analysis of employment declines experienced in the
manufacturing sector’s automotive component in various Midwestern states,
see the paper entitled “Automotive industries: Concentration and change,”
Issues in Labor Statistics, Summary 07-04/July 2007. For links to this and
other Issues in Labor Statistics papers utilizing QCEW data, see http://www.
bls.gov/cew/cewissus.htm.
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 second quarter 2007 is
scheduled to be released on Thursday, January 17, 2008.
——————————————————————–
| County Changes for the 2007 County Employment |
| and Wages News Releases |
| |
| Counties with employment of 75,000 or more in 2006 are |
| included in this release. For 2007 data, four counties have |
| been added to the publication tables: Butte, Calif., Tippecanoe, |
| Ind., Saratoga, N.Y., and Williamson, Tenn. One county, Boone, |
| Ky., which had data for 2006 published in the 2006 releases, will |
| be excluded from 2007 releases because its 2006 annual average |
| employment level was less than 75,000. |
——————————————————————–
– 6 –
———————————————————————
| Industry Changes to County Employment and Wages Data |
| |
| In an effort to enhance the comparability of industrial employ- |
| ment and wage statistics across Mexico, Canada, and the United |
| States, and reflect economic activities within industries more ac- |
| curately, the North American Industry Classification System (NAICS) |
| is revised periodically. In conjunction with its counterparts in |
| Mexico and Canada, the U.S. Office of Management and Budget deve- |
| loped NAICS 2007. |
| |
| The conversion to NAICS 2007 resulted in minor revisions re- |
| flecting content changes within the Agriculture, forestry, fishing, |
| and hunting sector and the Manufacturing sector; the restructuring |
| of the Telecommunications subsector; the elimination of the Real |
| estate and investment trusts industry within the Finance and in- |
| surance sector; and minor content changes within the Professional, |
| scientific, and technical services sector. Several industry titles |
| and descriptions also were updated. This revision was introduced |
| by the Bureau of Labor Statistics (BLS) with the release of first |
| quarter 2007 QCEW data. This revision had a minimal impact on |
| QCEW data. Approximately 1 percent of both employment and estab- |
| lishments and 2 percent of total wages were reclassified into dif- |
| ferent industries as a result of the revision. |
| |
| With the introduction of this revision, some industries were |
| directly transferred to new industries while others were split into |
| two or more industries, with the original industry often retaining |
| a portion of the establishments, employment, and wages. Of the |
| 1,179 industries used by BLS under NAICS 2002, 8 industries were |
| directly moved to new industries created by the NAICS 2007 revision.|
| Involved in these direct transfers were 41,821 establishments, |
| 829,263 employees, and $12.6 billion in total wages. In addition, |
| 13 industries were split into 2 or more industries. In all, 27,457 |
| establishments, 662,125 employees, and $16.5 billion in total wages |
| changed industries via these split transfers. |
| |
| A total of 69,278 establishments, 1,491,388 employees, and $29.1 |
| billion in total wages changed industries in first quarter 2007 due |
| to this revision. This represents 37 percent of the overall |
| 186,702 establishments, 43 percent of the overall 3,478,087 em- |
| ployees, and 55 percent of the overall $52.9 billion in total wages |
| affected by an administrative industry change in first quarter 2007.|
| (See Technical Note.) All figures cited are preliminary and all |
| employment figures cited reflect March 2007 data. For further in- |
| formation on the NAICS 2007 revision, see the U.S. Census Bureau |
| Web site at http://www.census.gov/epcd/naics07/index.html. |
| |
| More information on the NAICS 2007 revision, including the im- |
| plementation schedules of other BLS programs, will be posted on the |
| BLS Web site as it becomes available. |
———————————————————————
– 7 –
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 in-
surance programs that require most employers to pay quarterly taxes based
on the employment and wages of workers covered by UI. QCEW data in this
release are based on the 2007 North American Industry Classification
System. Data for 2007 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 329 counties presented in this release were
derived using 2006 preliminary annual averages of employment. For 2007
data, four counties have been added to the publication tables: Butte,
Calif., Tippecanoe, Ind., Saratoga, N.Y., and Williamson, Tenn. These
counties will be included in all 2007 quarterly releases. One county,
Boone, Ky., which was published in the 2006 releases, will be excluded from
this and future 2007 releases because its 2006 annual average employment
level was less than 75,000. The counties in table 2 are selected and
sorted each year based on the annual average employment from the preceding
year.
The preliminary QCEW data presented in this release may differ from
data released by the individual states. These potential differences result
from the states’ 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 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 pro-
ducts. (See table below.) Additional information on each program can
be obtained from the program Web sites shown in the table below.
– 8 –
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 8.9 | ministrative records| ments
| million establish- | submitted by 7.0 |
| 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 fed- | establishments with | ing agriculture, pri-
| eral UI laws | zero employment | vate households, and
| | | self-employed workers
| | |–Other employment, in-
| | | cluding railroads,
| | | religious organiza-
| | | tions, and other non-
| | | UI-covered jobs
———–|———————|———————-|————————
Publication|–Quarterly |–Quarterly |–Monthly
frequency | -7 months after the| -8 months after the | -Usually first Friday
| end of each quar- | end of each quarter| of following month
| ter | |
———–|———————|———————-|————————
Use of UI |–Directly summarizes|–Links each new UI |–Uses UI file as a sam-
file | and publishes each | quarter to longitu- | pling frame and annu-
| new quarter of UI | dinal database and | ally realigns (bench-
| data | directly summarizes | marks) sample esti-
| | gross job gains and | mates to first quar-
| | losses | ter UI levels
———–|———————|———————-|————————
Principal |–Provides a quarter-|–Provides quarterly |–Provides current month-
products | ly and annual uni- | employer dynamics | ly estimates of employ-
| verse count of es- | data on establish- | ment, hours, and earn-
| tablishments, em- | ment openings, clos-| ings at the MSA, state,
| ployment, and wages| ings, expansions, | and national level by
| at the county, MSA,| and contractions at | industry
| state, and national| the national level |
| levels by detailed | by NAICS supersec- |
| industry | tors, at the state |
| | private-sector total|
| | level, and by size |
| | of firm |
| |–Future expansions |
| | will include data |
| | with greater indus- |
| | try detail and data |
| | at the county and |
| | MSA level |
———–|———————|———————-|————————
Principal |–Major uses include:|–Major uses include: |–Major uses include:
uses | -Detailed locality | -Business cycle | -Principal national
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -Analysis of employ-| cators
| surveys | ment expansion and |
| | contraction by size|
| | of firm |
| | |
———–|———————|———————-|————————
Program |–www.bls.gov/cew/ |–www.bls.gov/bdm/ |–www.bls.gov/ces/
Web sites | | |
———————————————————————————
– 9 –
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 contri-
bution 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 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 2006, UI and UCFE programs covered workers in 133.8 million
jobs. The estimated 128.9 million workers in these jobs (after adjust-
ment for multiple jobholders) represented 96.4 percent of civilian wage
and salary employment. Covered workers received $5.693 trillion in pay,
representing 94.3 percent of the wage and salary component of personal
income and 43.1 percent of the gross domestic product.
Major exclusions from UI coverage include self-employed workers, most
agricultural workers on small farms, all members of the Armed Forces,
elected officials in most states, most employees of railroads, some do-
mestic workers, most student workers at schools, and employees of cer-
tain 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
production and sales workers, corporation officials, executives, supervi-
sory 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 compensa-
tion plans such as 401(k) plans and stock options. Over-the-year compari-
sons of average weekly wages may reflect fluctuations in average monthly
employment and/or total quarterly wages between the current quarter and
prior-year levels.
– 10 –
Average weekly wages are affected by the ratio of full-time to part-
time workers as well as the number of individuals in high-paying and
low-paying occupations and the incidence of pay periods within a quarter.
For instance, the average weekly wage of the work force could increase
significantly when there is a large decline in the number of employees
that had been receiving below-average wages. Wages may include payments
to workers not present in the employment counts because they did not work
during the pay period including the 12th of the month. When comparing
average 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 bi-
weekly pay schedule. As a result of this schedule, in some quarters, federal
wages contain payments for six pay periods, while in other quarters their
wages include payments for seven pay periods. Over-the-year comparisons of
average weekly wages may reflect this calendar effect. Higher growth in
average weekly wages may be attributed, in part, to a comparison of quarterly
wages for the current year, which include seven pay periods, with year-ago
wages that reflect only six pay periods. An opposite effect will occur when
wages in the current period, which contain six pay periods, are compared with
year-ago wages that include seven pay periods. The effect on over-the-year
pay comparisons can be pronounced in federal government due to the uniform
nature of federal payroll processing. This pattern may exist in private
sector pay; however, because there are more pay period types (weekly, biweekly,
semimonthly, monthly) it is less pronounced. The effect is most visible in
counties with large 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 owner-
ship classification of all establishments on a 3-year cycle. Changes in
establishment classification codes resulting from this process are intro-
duced 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 establish-
ments 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 re-
flecting economic events, others reflecting administrative changes. For example,
economic change would come from a firm relocating into the county; administra-
tive 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 2006 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.
– 11 –
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 ad-
ministrative 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 in-
dustry categories. The adjusted data do not account for administrative
changes caused by multi-unit employers who start reporting for each indi-
vidual 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 re-
ferred 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 2006 edition of this bulletin will
contain selected data produced by Business Employment Dynamics (BED) on job
gains and losses, as well as selected data from the first quarter 2007 ver-
sion of this news release. As with the 2005 edition, this edition will
include the data on a CD for enhanced access and usability with the printed
booklet containing selected graphic representations of QCEW data; the data
tables themselves will be published exclusively in electronic formats as
PDFs. Employment and Wages Annual Averages, 2006 will be available for sale
in early 2008 from the United States Government Printing Office, Superintend-
ent of Documents, P.O. Box 371954, Pittsburgh, PA 15250, telephone (866) 512-
1800, outside Washington, D.C. Within Washington, D.C., the telephone number
is (202) 512-1800. The fax number is (202) 512-2104.
News releases on quarterly measures of gross job flows also are available
upon 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 re-
ferral phone number: 1-800-877-8339.
Table 1. Covered(1) establishments, employment, and wages in the 329 largest counties,
first quarter 2007(2)
Employment Average weekly wage(4)
Establishments,
County(3) first quarter Percent Ranking Percent Ranking
2007 March change, by Average change, by
(thousands) 2007 March percent weekly first percent
(thousands) 2006-07(5) change wage quarter change
2006-07(5)
United States(6)……… 8,947.1 134,320.6 1.4 – $885 5.1 –
Jefferson, AL………… 18.8 366.0 1.1 139 878 4.3 135
Madison, AL………….. 8.5 174.9 3.6 33 892 2.5 252
Mobile, AL…………… 10.0 175.0 2.8 56 692 4.7 111
Montgomery, AL……….. 6.7 139.3 1.9 88 713 3.9 169
Tuscaloosa, AL……….. 4.4 87.0 2.5 64 700 4.0 156
Anchorage Borough, AK…. 8.1 143.6 0.8 163 875 4.7 111
Maricopa, AZ…………. 95.5 1,828.2 1.7 99 857 4.4 129
Pima, AZ…………….. 20.6 375.7 1.9 88 733 4.4 129
Benton, AR…………… 5.4 96.3 3.3 39 838 5.5 62
Pulaski, AR………….. 14.5 248.6 0.4 216 756 3.6 185
Washington, AR……….. 5.6 92.6 0.4 216 661 5.4 65
Alameda, CA………….. 50.3 686.0 0.4 216 1,139 3.4 199
Butte, CA……………. 7.8 75.7 1.4 118 620 3.7 179
Contra Costa, CA……… 28.4 344.2 0.2 240 1,116 5.0 84
Fresno, CA…………… 29.8 342.0 1.6 109 667 4.9 88
Kern, CA…………….. 17.7 266.1 0.7 182 735 5.8 51
Los Angeles, CA………. 401.3 4,210.2 0.4 216 974 3.3 204
Marin, CA……………. 11.6 107.8 2.1 79 1,043 4.5 121
Monterey, CA…………. 12.4 156.8 2.8 56 791 3.3 204
Orange, CA…………… 95.8 1,516.1 0.1 250 1,001 3.2 212
Placer, CA…………… 10.5 139.9 2.4 69 832 4.7 111
Riverside, CA………… 44.1 638.0 0.2 240 741 5.0 84
Sacramento, CA……….. 51.9 638.5 0.2 240 933 2.1 267
San Bernardino, CA……. 47.2 666.3 1.1 139 726 3.7 179
San Diego, CA………… 93.3 1,319.8 0.4 216 930 3.2 212
San Francisco, CA…….. 45.0 548.1 2.5 64 1,639 8.2 12
San Joaquin, CA………. 17.4 221.3 0.3 231 710 4.6 117
San Luis Obispo, CA…… 9.2 105.7 1.8 95 684 3.2 212
San Mateo, CA………… 23.2 338.5 1.4 118 1,447 7.9 15
Santa Barbara, CA…….. 13.8 184.2 0.4 216 816 4.1 147
Santa Clara, CA………. 56.6 893.4 2.3 73 1,584 0.1 308
Santa Cruz, CA……….. 8.8 94.2 0.9 158 846 4.4 129
Solano, CA…………… 10.0 126.9 -0.4 282 831 5.1 78
Sonoma, CA…………… 18.0 190.7 0.7 182 805 2.2 261
Stanislaus, CA……….. 14.3 171.5 -0.3 272 697 4.0 156
Tulare, CA…………… 9.0 139.6 1.0 149 593 3.1 221
Ventura, CA………….. 21.9 321.7 0.4 216 939 6.3 35
Yolo, CA…………….. 5.6 99.7 0.8 163 805 6.3 35
Adams, CO……………. 9.3 150.8 -0.1 262 764 1.7 283
Arapahoe, CO…………. 19.9 276.8 2.0 84 1,062 -1.8 317
Boulder, CO………….. 12.8 158.5 3.6 33 1,030 4.8 101
Denver, CO…………… 25.5 436.9 3.0 49 1,120 4.9 88
Douglas, CO………….. 9.2 88.4 4.5 18 896 4.2 139
El Paso, CO………….. 17.6 244.1 0.6 195 761 3.3 204
Jefferson, CO………… 18.9 207.5 1.2 131 886 4.0 156
Larimer, CO………….. 10.2 126.3 1.7 99 742 2.8 237
Weld, CO…………….. 6.0 81.6 3.8 27 687 2.5 252
Fairfield, CT………… 32.7 415.8 1.5 113 1,979 7.4 20
Hartford, CT…………. 25.2 498.2 1.3 127 1,183 6.5 31
New Haven, CT………… 22.5 364.4 0.1 250 914 5.2 73
New London, CT……….. 6.8 127.9 0.1 250 876 3.9 169
New Castle, DE……….. 19.1 281.1 0.2 240 1,131 1.9 277
Washington, DC……….. 31.9 674.4 1.1 139 1,428 4.7 111
Alachua, FL………….. 6.6 128.4 2.5 64 690 4.1 147
Brevard, FL………….. 14.8 205.8 -1.7 311 772 2.9 234
Broward, FL………….. 64.4 761.7 1.0 149 814 2.4 255
Collier, FL………….. 12.4 141.3 0.5 205 772 6.0 45
Duval, FL……………. 26.0 468.7 1.4 118 868 2.8 237
Escambia, FL…………. 8.0 131.1 0.1 250 663 3.1 221
Hillsborough, FL……… 36.8 654.9 1.2 131 809 2.8 237
Lake, FL…………….. 7.0 83.7 0.5 205 592 0.7 301
Lee, FL……………… 19.1 231.1 0.7 182 714 0.6 303
Leon, FL…………….. 8.1 147.9 0.9 158 698 3.3 204
Manatee, FL………….. 9.0 129.2 -1.1 303 651 2.7 243
Marion, FL…………… 8.3 105.4 1.6 109 599 1.7 283
Miami-Dade, FL……….. 85.8 1,025.1 1.4 118 862 3.9 169
Okaloosa, FL…………. 6.1 82.1 -2.0 315 670 3.1 221
Orange, FL…………… 35.7 692.8 3.0 49 774 2.1 267
Palm Beach, FL……….. 49.9 562.2 -0.3 272 855 5.9 50
Pasco, FL……………. 9.7 101.6 0.3 231 591 4.8 101
Pinellas, FL…………. 31.4 442.8 -1.2 305 719 1.4 291
Polk, FL…………….. 12.6 211.0 1.0 149 648 3.0 232
Sarasota, FL…………. 15.1 160.5 -0.2 267 716 -1.8 317
Seminole, FL…………. 14.9 177.4 0.0 256 737 3.7 179
Volusia, FL………….. 14.0 171.4 0.3 231 608 4.8 101
Bibb, GA…………….. 4.7 83.6 -0.3 272 674 -3.0 322
Chatham, GA………….. 7.4 138.0 4.7 14 701 1.4 291
Clayton, GA………….. 4.3 112.9 1.4 118 759 0.9 299
Cobb, GA…………….. 20.3 318.3 1.2 131 995 11.2 3
De Kalb, GA………….. 16.2 297.8 -0.3 272 957 5.7 55
Fulton, GA…………… 39.5 758.9 2.4 69 1,258 7.1 21
Gwinnett, GA…………. 23.3 325.0 3.6 33 883 0.7 301
Muscogee, GA…………. 4.8 96.8 -2.6 317 685 5.1 78
Richmond, GA…………. 4.8 103.4 -1.0 301 699 3.2 212
Honolulu, HI…………. 24.5 452.1 0.7 182 771 3.9 169
Ada, ID……………… 15.0 209.6 1.9 88 768 5.6 57
Champaign, IL………… 4.1 91.2 1.0 149 678 3.5 189
Cook, IL…………….. 136.9 2,510.1 0.8 163 1,117 6.5 31
Du Page, IL………….. 35.3 589.2 0.4 216 1,040 3.5 189
Kane, IL…………….. 12.4 206.2 0.4 216 741 0.3 306
Lake, IL…………….. 20.6 323.3 0.9 158 1,128 4.1 147
McHenry, IL………….. 8.3 99.9 1.0 149 718 3.2 212
McLean, IL…………… 3.6 84.7 1.4 118 862 -0.1 310
Madison, IL………….. 5.9 94.8 0.7 182 683 1.5 287
Peoria, IL…………… 4.7 102.8 1.9 88 815 -1.8 317
Rock Island, IL………. 3.5 78.4 0.4 216 847 2.3 258
St. Clair, IL………… 5.3 95.7 2.4 69 650 2.0 271
Sangamon, IL…………. 5.2 128.3 -0.7 295 808 3.9 169
Will, IL…………….. 13.0 185.2 3.6 33 736 2.1 267
Winnebago, IL………… 6.9 135.6 1.1 139 731 3.7 179
Allen, IN……………. 9.0 182.9 0.9 158 718 2.3 258
Elkhart, IN………….. 4.9 124.7 -2.9 318 703 0.0 309
Hamilton, IN…………. 7.4 107.2 3.9 26 865 2.2 261
Lake, IN…………….. 10.1 192.5 0.4 216 735 1.9 277
Marion, IN…………… 24.0 573.7 0.8 163 930 3.4 199
St. Joseph, IN……….. 6.0 122.8 -0.3 272 699 3.2 212
Tippecanoe, IN……….. 3.2 76.1 1.5 113 736 3.1 221
Vanderburgh, IN………. 4.8 107.2 -1.1 303 706 2.0 271
Linn, IA…………….. 6.2 121.1 1.6 109 816 5.3 70
Polk, IA…………….. 14.6 267.5 1.9 88 887 3.3 204
Scott, IA……………. 5.2 87.4 0.4 216 670 1.7 283
Johnson, KS………….. 19.9 312.8 4.4 19 910 3.2 212
Sedgwick, KS…………. 12.0 254.8 3.4 38 848 6.4 34
Shawnee, KS………….. 4.8 94.6 1.8 95 721 4.0 156
Wyandotte, KS………… 3.2 80.6 (7) – 784 1.0 298
Fayette, KY………….. 9.2 174.7 2.6 63 763 5.1 78
Jefferson, KY………… 22.2 426.8 0.5 205 846 5.8 51
Caddo, LA……………. 7.3 125.0 -0.5 288 678 4.1 147
Calcasieu, LA………… 4.8 86.9 2.3 73 711 1.3 294
East Baton Rouge, LA….. 13.8 261.6 0.5 205 772 8.6 10
Jefferson, LA………… 13.8 198.1 6.6 5 771 0.8 300
Lafayette, LA………… 8.3 132.5 4.3 21 787 8.0 14
Orleans, LA………….. 10.2 167.8 15.0 1 964 -2.7 320
Cumberland, ME……….. 12.3 168.7 1.2 131 785 4.0 156
Anne Arundel, MD……… 14.4 229.4 1.1 139 900 4.0 156
Baltimore, MD………… 21.8 374.4 0.0 256 882 3.8 178
Frederick, MD………… 6.0 94.0 0.0 256 832 4.8 101
Harford, MD………….. 5.7 83.1 0.3 231 802 3.1 221
Howard, MD…………… 8.5 145.4 0.8 163 1,001 4.2 139
Montgomery, MD……….. 32.8 457.4 0.2 240 1,213 6.6 30
Prince Georges, MD……. 15.6 313.2 0.8 163 891 3.0 232
Baltimore City, MD……. 14.0 344.0 0.1 250 995 4.5 121
Barnstable, MA……….. 9.2 82.7 -0.7 295 724 3.7 179
Bristol, MA………….. 15.7 216.4 -0.6 290 735 4.1 147
Essex, MA……………. 20.5 291.5 0.3 231 917 4.0 156
Hampden, MA………….. 14.0 196.1 -0.3 272 802 4.3 135
Middlesex, MA………… 47.0 802.0 1.2 131 1,250 6.0 45
Norfolk, MA………….. 21.6 318.0 0.6 195 1,042 -2.7 320
Plymouth, MA…………. 13.8 173.6 0.2 240 782 4.8 101
Suffolk, MA………….. 21.6 576.7 2.4 69 1,659 10.8 4
Worcester, MA………… 20.6 316.6 0.5 205 848 3.3 204
Genesee, MI………….. 8.0 143.0 -2.4 316 760 2.0 271
Ingham, MI…………… 6.9 159.8 -1.0 301 802 3.1 221
Kalamazoo, MI………… 5.5 116.2 -0.2 267 746 1.5 287
Kent, MI…………….. 14.3 336.0 -0.4 282 760 4.0 156
Macomb, MI…………… 17.9 310.7 -3.8 321 893 4.0 156
Oakland, MI………….. 39.4 687.4 -1.5 309 1,009 3.4 199
Ottawa, MI…………… 5.8 107.9 -1.7 311 716 1.8 281
Saginaw, MI………….. 4.4 86.1 -0.3 272 745 4.1 147
Washtenaw, MI………… 8.0 192.2 -1.3 308 970 6.1 42
Wayne, MI……………. 32.7 744.8 -3.2 319 999 7.5 17
Anoka, MN……………. 8.0 113.1 -0.1 262 778 2.6 249
Dakota, MN…………… 10.6 171.6 -0.1 262 840 3.6 185
Hennepin, MN…………. 42.8 837.9 0.8 163 1,128 6.9 24
Olmsted, MN………….. 3.6 88.8 0.8 163 933 4.9 88
Ramsey, MN…………… 15.7 328.2 0.5 205 977 5.6 57
St. Louis, MN………… 5.9 93.9 0.1 250 675 3.2 212
Stearns, MN………….. 4.5 80.7 3.2 40 654 2.2 261
Harrison, MS…………. 4.4 84.8 14.5 2 662 -0.3 313
Hinds, MS……………. 6.5 127.8 -0.4 282 753 4.9 88
Boone, MO……………. 4.5 82.5 1.0 149 632 2.9 234
Clay, MO…………….. 5.0 89.5 -0.4 282 805 9.7 5
Greene, MO…………… 8.1 156.4 2.8 56 631 2.8 237
Jackson, MO………….. 18.6 369.0 1.4 118 873 3.6 185
St. Charles, MO………. 8.0 122.5 1.7 99 741 6.2 41
St. Louis, MO………… 33.0 605.1 1.1 139 903 1.2 295
St. Louis City, MO……. 8.5 229.3 -1.7 311 1,020 3.1 221
Douglas, NE………….. 15.5 311.4 0.7 182 794 1.5 287
Lancaster, NE………… 7.9 153.5 1.0 149 666 3.1 221
Clark, NV……………. 47.6 922.6 1.9 88 811 5.3 70
Washoe, NV…………… 14.2 216.5 0.7 182 767 4.4 129
Hillsborough, NH……… 12.4 195.2 -0.2 267 922 4.2 139
Rockingham, NH……….. 10.9 134.8 0.8 163 874 6.8 27
Atlantic, NJ…………. 7.1 143.2 -1.2 305 763 5.0 84
Bergen, NJ…………… 35.3 447.9 0.6 195 1,110 4.4 129
Burlington, NJ……….. 11.6 202.3 -1.2 305 899 4.8 101
Camden, NJ…………… 13.4 207.8 -0.3 272 876 5.4 65
Essex, NJ……………. 21.8 360.6 0.2 240 1,184 5.6 57
Gloucester, NJ……….. 6.4 103.0 -0.3 272 748 2.2 261
Hudson, NJ…………… 14.1 234.5 -0.2 267 1,434 8.7 9
Mercer, NJ…………… 11.3 222.1 0.5 205 1,140 6.9 24
Middlesex, NJ………… 22.3 406.7 0.7 182 1,135 5.1 78
Monmouth, NJ…………. 21.1 253.5 0.0 256 902 0.6 303
Morris, NJ…………… 18.4 287.1 0.6 195 1,363 5.2 73
Ocean, NJ……………. 12.7 145.6 0.2 240 716 2.0 271
Passaic, NJ………….. 12.8 177.1 -1.5 309 888 2.4 255
Somerset, NJ…………. 10.4 171.9 -0.6 290 1,615 9.0 7
Union, NJ……………. 15.5 229.2 -0.4 282 1,235 (7) –
Bernalillo, NM……….. 17.5 332.3 1.5 113 732 3.4 199
Albany, NY…………… 9.8 225.3 0.6 195 838 1.6 286
Bronx, NY……………. 15.8 219.1 -0.6 290 788 5.1 78
Broome, NY…………… 4.5 94.6 1.2 131 671 3.5 189
Dutchess, NY…………. 8.3 115.8 -0.7 295 875 4.5 121
Erie, NY…………….. 23.3 451.5 0.6 195 764 6.3 35
Kings, NY……………. 44.4 464.8 1.9 88 742 4.8 101
Monroe, NY…………… 17.8 376.6 -0.3 272 835 3.5 189
Nassau, NY…………… 52.2 598.1 0.8 163 983 7.5 17
New York, NY…………. 116.7 2,331.5 2.3 73 2,821 16.7 2
Oneida, NY…………… 5.3 108.9 1.5 113 671 6.8 27
Onondaga, NY…………. 12.8 246.5 0.5 205 788 4.4 129
Orange, NY…………… 9.9 128.2 -0.2 267 715 3.9 169
Queens, NY…………… 42.1 487.7 2.1 79 831 3.5 189
Richmond, NY…………. 8.5 91.9 3.2 40 733 3.5 189
Rockland, NY…………. 9.7 113.1 1.6 109 913 4.0 156
Saratoga, NY…………. 5.3 74.6 0.3 231 715 4.5 121
Suffolk, NY………….. 49.7 607.8 0.8 163 891 4.6 117
Westchester, NY………. 36.2 413.6 1.5 113 1,308 8.9 8
Buncombe, NC…………. 7.8 114.3 3.8 27 638 4.1 147
Catawba, NC………….. 4.6 89.4 2.7 59 656 1.9 277
Cumberland, NC……….. 6.2 118.5 1.7 99 628 5.2 73
Durham, NC…………… 6.8 182.2 4.1 24 1,204 6.1 42
Forsyth, NC………….. 9.2 184.8 1.8 95 791 4.1 147
Guilford, NC…………. 14.6 280.5 2.1 79 766 5.7 55
Mecklenburg, NC………. 31.7 565.0 6.2 6 1,220 4.9 88
New Hanover, NC………. 7.4 105.1 6.2 6 678 (7) –
Wake, NC…………….. 27.5 439.6 5.4 9 867 4.2 139
Cass, ND…………….. 5.6 94.5 2.7 59 678 4.5 121
Butler, OH…………… 7.3 145.8 3.7 30 750 2.6 249
Cuyahoga, OH…………. 38.0 740.6 -0.4 282 914 5.4 65
Franklin, OH…………. 29.4 677.7 0.7 182 896 6.9 24
Hamilton, OH…………. 24.1 513.8 -0.6 290 956 4.7 111
Lake, OH…………….. 6.8 99.4 0.2 240 725 4.8 101
Lorain, OH…………… 6.3 99.4 -0.6 290 710 2.6 249
Lucas, OH……………. 10.8 219.4 -1.8 314 773 2.7 243
Mahoning, OH…………. 6.3 102.7 0.0 256 620 4.0 156
Montgomery, OH……….. 12.9 267.5 -3.2 319 832 9.3 6
Stark, OH……………. 9.1 159.8 -0.8 298 672 4.2 139
Summit, OH…………… 15.0 269.0 0.0 256 793 4.8 101
Trumbull, OH…………. 4.8 78.9 -6.2 322 860 22.3 1
Oklahoma, OK…………. 23.2 419.5 0.8 163 751 -0.8 314
Tulsa, OK……………. 19.2 344.8 2.5 64 792 -1.7 316
Clackamas, OR………… 13.0 149.4 2.9 52 768 3.5 189
Jackson, OR………….. 6.9 83.4 2.3 73 615 2.0 271
Lane, OR…………….. 11.3 149.5 1.8 95 641 2.7 243
Marion, OR…………… 9.5 137.0 2.7 59 661 4.9 88
Multnomah, OR………… 27.7 443.0 3.1 46 864 2.7 243
Washington, OR……….. 16.4 248.7 1.3 127 964 -0.1 310
Allegheny, PA………… 35.5 676.7 0.8 163 946 8.1 13
Berks, PA……………. 9.1 167.7 1.4 118 752 3.6 185
Bucks, PA……………. 20.5 262.8 1.1 139 830 4.5 121
Butler, PA…………… 4.8 78.1 3.1 46 714 5.6 57
Chester, PA………….. 15.0 236.4 2.0 84 1,117 2.9 234
Cumberland, PA……….. 6.0 124.6 0.2 240 776 2.2 261
Dauphin, PA………….. 7.3 179.6 0.8 163 834 5.2 73
Delaware, PA…………. 13.7 208.4 1.7 99 926 5.6 57
Erie, PA…………….. 7.3 126.5 0.8 163 669 5.5 62
Lackawanna, PA……….. 5.8 101.0 0.6 195 634 3.1 221
Lancaster, PA………… 12.2 225.3 0.6 195 708 2.2 261
Lehigh, PA…………… 8.7 175.9 1.1 139 868 6.0 45
Luzerne, PA………….. 8.0 140.0 -0.8 298 679 6.1 42
Montgomery, PA……….. 27.7 483.5 0.8 163 1,176 5.4 65
Northampton, PA………. 6.5 98.1 0.7 182 745 4.2 139
Philadelphia, PA……… 29.7 631.8 -0.1 262 1,038 5.8 51
Washington, PA……….. 5.3 77.4 1.3 127 732 4.9 88
Westmoreland, PA……… 9.5 135.0 0.3 231 659 2.5 252
York, PA…………….. 9.0 175.1 0.8 163 737 3.9 169
Kent, RI…………….. 5.7 81.2 0.4 216 784 7.0 23
Providence, RI……….. 18.2 284.5 0.5 205 857 6.3 35
Charleston, SC……….. 14.0 208.3 4.8 11 708 1.9 277
Greenville, SC……….. 14.1 235.6 2.5 64 713 2.3 258
Horry, SC……………. 9.9 114.7 4.8 11 536 2.1 267
Lexington, SC………… 6.6 95.0 3.6 33 621 1.5 287
Richland, SC…………. 10.9 215.3 1.7 99 749 1.4 291
Spartanburg, SC………. 7.0 118.0 2.1 79 754 2.0 271
Minnehaha, SD………… 6.2 112.0 2.0 84 708 3.7 179
Davidson, TN…………. 18.4 444.9 0.7 182 857 6.3 35
Hamilton, TN…………. 8.5 192.3 1.0 149 728 3.9 169
Knox, TN…………….. 10.9 224.4 2.1 79 705 3.5 189
Rutherford, TN……….. 4.1 97.8 0.8 163 758 7.1 21
Shelby, TN…………… 20.0 505.4 0.6 195 842 3.3 204
Williamson, TN……….. 5.6 83.4 6.0 8 914 4.9 88
Bell, TX…………….. 4.4 97.5 3.2 40 635 3.3 204
Bexar, TX……………. 31.5 707.1 2.9 52 768 3.4 199
Brazoria, TX…………. 4.5 85.6 2.9 52 839 1.8 281
Brazos, TX…………… 3.7 84.2 0.5 205 597 5.3 70
Cameron, TX………….. 6.4 123.4 2.3 73 502 5.0 84
Collin, TX…………… 15.8 274.9 4.4 19 1,055 5.1 78
Dallas, TX…………… 67.5 1,469.4 3.2 40 1,092 5.2 73
Denton, TX…………… 10.0 163.8 4.7 14 723 3.9 169
El Paso, TX………….. 13.2 265.1 1.0 149 597 5.5 62
Fort Bend, TX………… 7.8 121.0 (7) – 934 5.4 65
Galveston, TX………… 5.2 94.8 (7) – 801 (7) –
Harris, TX…………… 94.5 1,985.7 3.8 27 1,125 8.5 11
Hidalgo, TX………….. 10.3 213.0 3.7 30 516 4.0 156
Jefferson, TX………… 5.8 129.0 0.9 158 782 4.7 111
Lubbock, TX………….. 6.7 120.2 0.7 182 618 1.1 297
McLennan, TX…………. 4.8 102.9 1.7 99 669 4.9 88
Montgomery, TX……….. 7.7 119.1 5.3 10 774 0.3 306
Nueces, TX…………… 8.1 151.3 1.2 131 712 4.9 88
Smith, TX……………. 5.2 92.4 1.7 99 691 3.1 221
Tarrant, TX………….. 36.0 754.1 2.7 59 865 3.2 212
Travis, TX…………… 27.4 566.2 4.7 14 944 0.5 305
Webb, TX…………….. 4.7 87.2 4.2 23 542 2.8 237
Williamson, TX……….. 6.6 114.7 7.0 4 826 -1.0 315
Davis, UT……………. 7.0 101.7 4.0 25 656 2.8 237
Salt Lake, UT………… 37.6 577.6 4.6 17 788 5.8 51
Utah, UT…………….. 12.6 172.8 7.3 3 623 6.0 45
Weber, UT……………. 5.6 93.9 4.3 21 604 4.3 135
Chittenden, VT……….. 5.8 93.5 0.5 205 846 -0.2 312
Arlington, VA………… 7.5 150.5 (7) – 1,447 2.4 255
Chesterfield, VA……… 7.3 120.4 1.4 118 765 3.1 221
Fairfax, VA………….. 32.5 579.5 1.2 131 1,371 4.3 135
Henrico, VA………….. 9.0 178.5 3.2 40 1,008 7.7 16
Loudoun, VA………….. 8.0 126.5 1.7 99 1,081 -3.0 322
Prince William, VA……. 6.8 101.9 -0.9 300 744 4.2 139
Alexandria City, VA…… 6.0 99.9 (7) – 1,136 (7) –
Chesapeake City, VA…… 5.5 99.6 0.4 216 661 4.8 101
Newport News City, VA…. 4.0 99.1 1.3 127 761 7.5 17
Norfolk City, VA……… 5.8 143.4 1.7 99 826 6.7 29
Richmond City, VA…….. 7.4 157.3 (7) – 1,071 (7) –
Virginia Beach City, VA.. 11.5 174.9 0.3 231 661 4.9 88
Clark, WA……………. 11.5 130.8 2.0 84 746 3.5 189
King, WA…………….. 75.1 1,157.5 3.7 30 1,080 3.5 189
Kitsap, WA…………… 6.4 83.5 0.4 216 727 4.0 156
Pierce, WA…………… 19.9 272.0 3.0 49 768 4.9 88
Snohomish, WA………… 17.2 248.0 4.8 11 895 6.5 31
Spokane, WA………….. 14.7 206.7 2.9 52 680 4.5 121
Thurston, WA…………. 6.6 98.4 3.2 40 743 4.1 147
Whatcom, WA………….. 6.7 81.2 3.1 46 653 4.6 117
Yakima, WA…………… 7.6 94.1 2.3 73 569 2.7 243
Kanawha, WV………….. 6.1 108.1 0.6 195 743 4.9 88
Brown, WI……………. 6.6 146.7 -0.1 262 755 1.2 295
Dane, WI…………….. 13.7 298.3 0.8 163 848 4.6 117
Milwaukee, WI………… 20.7 489.6 0.3 231 875 4.2 139
Outagamie, WI………… 4.9 101.6 1.1 139 724 2.7 243
Racine, WI…………… 4.2 74.4 -0.5 288 765 6.3 35
Waukesha, WI…………. 13.0 232.4 0.7 182 860 4.5 121
Winnebago, WI………… 3.7 88.6 1.1 139 824 6.0 45
San Juan, PR…………. 13.5 293.9 -3.3 (8) 573 7.1 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 328 U.S. counties comprise 71.1 percent of the total covered workers
in the U.S.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(7) Data do not meet BLS or State agency disclosure standards.
(8) This county was not included in the U.S. rankings.
Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties,
first quarter 2007(2)
Employment Average weekly
wage(3)
Establishments,
first quarter
County by NAICS supersector 2007 Percent Percent
(thousands) March change, Average change,
2007 March weekly first
(thousands) 2006-07(4) wage quarter
2006-07(4)
United States(5)……………………….. 8,947.1 134,320.6 1.4 $885 5.1
Private industry……………………… 8,667.5 112,574.0 1.4 892 5.2
Natural resources and mining…………. 123.7 1,683.1 3.2 925 4.0
Construction……………………….. 885.8 7,298.4 0.0 859 4.4
Manufacturing………………………. 361.2 13,862.4 -1.7 1,061 3.8
Trade, transportation, and utilities….. 1,906.6 25,963.5 1.4 731 3.4
Information………………………… 143.0 3,011.6 -0.8 1,438 4.6
Financial activities………………… 865.2 8,139.4 0.5 1,891 12.2
Professional and business services……. 1,455.9 17,617.5 2.7 1,083 6.2
Education and health services………… 813.1 17,314.4 2.8 740 3.6
Leisure and hospitality……………… 716.7 12,938.1 2.4 351 4.2
Other services……………………… 1,154.7 4,395.2 1.6 527 3.9
Government…………………………… 279.6 21,746.6 1.1 850 4.4
Los Angeles, CA………………………… 401.3 4,210.2 0.4 974 3.3
Private industry……………………… 397.3 3,616.3 0.3 957 3.5
Natural resources and mining…………. 0.5 12.3 6.0 1,512 19.9
Construction……………………….. 14.1 158.9 2.2 952 7.4
Manufacturing………………………. 15.4 453.9 -3.0 1,034 3.4
Trade, transportation, and utilities….. 55.7 807.7 0.8 785 2.1
Information………………………… 8.8 210.0 2.3 1,733 2.9
Financial activities………………… 25.2 247.9 (6) 1,806 8.9
Professional and business services……. 43.1 607.9 -0.1 1,108 1.1
Education and health services………… 28.0 478.6 1.1 825 3.5
Leisure and hospitality……………… 26.9 392.6 1.9 518 5.1
Other services……………………… 179.6 246.3 1.0 421 4.5
Government…………………………… 4.0 593.9 (6) 1,079 2.7
Cook, IL………………………………. 136.9 2,510.1 0.8 1,117 6.5
Private industry……………………… 135.7 2,197.0 1.0 1,133 6.8
Natural resources and mining…………. 0.1 1.2 -3.6 992 0.5
Construction……………………….. 11.9 88.3 -1.0 1,202 2.7
Manufacturing………………………. 7.1 237.9 -1.2 1,044 5.3
Trade, transportation, and utilities….. 27.5 472.5 0.4 818 2.8
Information………………………… 2.6 58.3 -0.5 1,799 9.9
Financial activities………………… 15.7 216.7 -0.3 2,780 15.9
Professional and business services……. 27.9 429.6 1.9 1,353 4.4
Education and health services………… 13.4 368.6 2.5 804 4.8
Leisure and hospitality……………… 11.4 224.2 2.5 407 5.2
Other services……………………… 13.8 95.1 0.0 701 5.1
Government…………………………… 1.2 313.1 -0.8 1,007 4.5
New York, NY…………………………… 116.7 2,331.5 2.3 2,821 16.7
Private industry……………………… 116.5 1,883.8 2.8 3,261 17.4
Natural resources and mining…………. 0.0 0.1 -10.0 2,411 -4.0
Construction……………………….. 2.2 32.7 5.4 1,469 5.8
Manufacturing………………………. 2.9 37.3 -5.0 1,591 14.6
Trade, transportation, and utilities….. 21.2 242.2 1.6 1,202 6.6
Information………………………… 4.1 131.7 0.7 2,586 6.2
Financial activities………………… 17.9 372.3 2.7 10,156 24.2
Professional and business services……. 23.4 475.5 3.1 2,258 10.1
Education and health services………… 8.4 289.7 1.8 954 3.1
Leisure and hospitality……………… 10.7 202.9 3.4 769 4.5
Other services……………………… 17.0 84.9 1.3 961 5.7
Government…………………………… 0.2 447.7 0.4 982 3.3
Harris, TX…………………………….. 94.5 1,985.7 3.8 1,125 8.5
Private industry……………………… 94.1 1,737.8 4.1 1,160 8.6
Natural resources and mining…………. 1.4 76.7 11.0 3,237 3.4
Construction……………………….. 6.3 148.1 4.5 1,009 7.8
Manufacturing………………………. 4.5 179.2 5.6 1,483 6.6
Trade, transportation, and utilities….. 21.2 411.7 2.3 1,048 10.0
Information………………………… 1.3 32.6 4.6 1,419 8.1
Financial activities………………… 10.3 119.2 2.7 1,673 13.9
Professional and business services……. 18.4 328.9 4.1 1,227 9.7
Education and health services………… 9.8 206.9 4.4 800 4.2
Leisure and hospitality……………… 7.0 171.2 2.5 374 1.9
Other services……………………… 10.8 56.9 1.8 602 5.6
Government…………………………… 0.4 248.0 1.5 882 6.7
Maricopa, AZ…………………………… 95.5 1,828.2 1.7 857 4.4
Private industry……………………… 94.9 1,609.9 1.5 856 4.3
Natural resources and mining…………. 0.5 9.2 4.1 818 9.5
Construction……………………….. 10.0 166.1 -6.5 867 1.8
Manufacturing………………………. 3.5 133.2 -2.0 1,190 0.3
Trade, transportation, and utilities….. 20.2 370.3 2.1 819 5.5
Information………………………… 1.6 29.8 -5.1 1,157 6.6
Financial activities………………… 12.1 151.3 0.4 1,250 3.6
Professional and business services……. 20.6 315.6 3.5 850 8.3
Education and health services………… 9.2 194.8 4.7 849 5.2
Leisure and hospitality……………… 6.7 184.0 3.4 404 6.9
Other services……………………… 6.8 49.9 4.9 558 2.0
Government…………………………… 0.6 218.3 2.9 859 4.1
Orange, CA…………………………….. 95.8 1,516.1 0.1 1,001 3.2
Private industry……………………… 94.4 1,361.1 -0.2 986 2.9
Natural resources and mining…………. 0.2 6.4 -7.1 555 4.9
Construction……………………….. 7.1 103.5 -2.5 1,074 5.4
Manufacturing………………………. 5.5 177.5 (6) 1,157 (6)
Trade, transportation, and utilities….. 17.9 275.0 -0.3 916 (6)
Information………………………… 1.4 30.4 -3.3 1,431 0.1
Financial activities………………… 11.5 134.2 (6) 1,660 3.4
Professional and business services……. 19.3 276.8 (6) 1,048 (6)
Education and health services………… 9.8 139.9 2.9 848 4.4
Leisure and hospitality……………… 7.0 169.8 2.8 392 6.5
Other services……………………… 14.6 47.6 -0.1 558 4.3
Government…………………………… 1.4 155.0 2.9 1,140 5.4
Dallas, TX…………………………….. 67.5 1,469.4 3.2 1,092 5.2
Private industry……………………… 67.0 1,306.2 3.4 1,116 5.1
Natural resources and mining…………. 0.5 7.0 -4.6 2,910 -3.5
Construction……………………….. 4.3 81.0 4.4 943 5.1
Manufacturing………………………. 3.2 143.6 0.3 1,352 7.0
Trade, transportation, and utilities….. 14.7 302.5 2.1 980 3.5
Information………………………… 1.7 48.6 -5.2 1,616 5.2
Financial activities………………… 8.6 146.1 3.3 1,816 10.9
Professional and business services……. 14.1 267.1 6.1 1,166 3.8
Education and health services………… 6.4 143.3 6.9 856 1.7
Leisure and hospitality……………… 5.1 124.5 3.9 517 7.9
Other services……………………… 6.3 38.2 -2.9 605 3.4
Government…………………………… 0.5 163.2 1.8 895 4.6
San Diego, CA………………………….. 93.3 1,319.8 0.4 930 3.2
Private industry……………………… 92.0 1,096.3 0.3 920 2.6
Natural resources and mining…………. 0.8 11.3 -3.0 513 2.0
Construction……………………….. 7.3 88.5 -5.7 950 2.0
Manufacturing………………………. 3.3 102.8 -1.7 1,248 3.7
Trade, transportation, and utilities….. 14.7 219.6 1.1 745 2.3
Information………………………… 1.3 37.6 1.6 1,994 -13.1
Financial activities………………… 10.1 81.8 -2.7 1,362 7.8
Professional and business services……. 16.5 214.8 0.2 1,135 6.1
Education and health services………… 8.1 127.5 2.3 813 4.5
Leisure and hospitality……………… 6.9 156.8 3.5 416 6.4
Other services……………………… 23.1 55.6 2.4 475 2.4
Government…………………………… 1.3 223.5 1.1 977 6.3
King, WA………………………………. 75.1 1,157.5 3.7 1,080 3.5
Private industry……………………… 74.6 1,004.1 4.2 1,095 3.4
Natural resources and mining…………. 0.4 3.1 4.7 1,618 16.4
Construction……………………….. 6.8 68.6 12.3 1,017 5.3
Manufacturing………………………. 2.5 111.2 2.9 1,374 -3.0
Trade, transportation, and utilities….. 14.9 216.2 2.9 940 4.7
Information………………………… 1.8 74.1 7.1 1,907 4.4
Financial activities………………… 7.0 76.1 -0.8 1,673 9.4
Professional and business services……. 12.8 183.5 6.4 1,258 2.3
Education and health services………… 6.3 119.7 3.2 793 1.4
Leisure and hospitality……………… 6.0 106.8 4.0 451 1.3
Other services……………………… 16.1 44.8 1.8 557 6.3
Government…………………………… 0.5 153.4 0.1 988 4.9
Miami-Dade, FL…………………………. 85.8 1,025.1 1.4 862 3.9
Private industry……………………… 85.5 872.1 1.4 830 3.8
Natural resources and mining…………. 0.5 11.5 1.2 455 -4.8
Construction……………………….. 6.0 53.4 6.5 831 -1.8
Manufacturing………………………. 2.6 48.0 -2.0 763 1.2
Trade, transportation, and utilities….. 23.1 251.2 0.9 773 4.2
Information………………………… 1.5 20.8 -0.5 1,383 6.8
Financial activities………………… 10.3 71.3 0.0 1,442 5.9
Professional and business services……. 17.3 137.2 -2.0 981 6.6
Education and health services………… 8.8 135.2 3.4 772 4.0
Leisure and hospitality……………… 5.7 104.4 2.3 498 -1.8
Other services……………………… 7.6 35.7 3.4 520 8.6
Government…………………………… 0.3 153.0 1.5 1,044 4.5
(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) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(5) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(6) Data do not meet BLS or State agency disclosure standards.
Table 3. Covered(1) establishments, employment, and wages in the largest county by
state, first quarter 2007(2)
Employment Average weekly
wage(4)
Establishments,
first quarter
County(3) 2007 Percent Percent
(thousands) March change, Average change,
2007 March weekly first
(thousands) 2006-07(5) wage quarter
2006-07(5)
United States(6)……… 8,947.1 134,320.6 1.4 $885 5.1
Jefferson, AL………… 18.8 366.0 1.1 878 4.3
Anchorage Borough, AK…. 8.1 143.6 0.8 875 4.7
Maricopa, AZ…………. 95.5 1,828.2 1.7 857 4.4
Pulaski, AR………….. 14.5 248.6 0.4 756 3.6
Los Angeles, CA………. 401.3 4,210.2 0.4 974 3.3
Denver, CO…………… 25.5 436.9 3.0 1,120 4.9
Hartford, CT…………. 25.2 498.2 1.3 1,183 6.5
New Castle, DE……….. 19.1 281.1 0.2 1,131 1.9
Washington, DC……….. 31.9 674.4 1.1 1,428 4.7
Miami-Dade, FL……….. 85.8 1,025.1 1.4 862 3.9
Fulton, GA…………… 39.5 758.9 2.4 1,258 7.1
Honolulu, HI…………. 24.5 452.1 0.7 771 3.9
Ada, ID……………… 15.0 209.6 1.9 768 5.6
Cook, IL…………….. 136.9 2,510.1 0.8 1,117 6.5
Marion, IN…………… 24.0 573.7 0.8 930 3.4
Polk, IA…………….. 14.6 267.5 1.9 887 3.3
Johnson, KS………….. 19.9 312.8 4.4 910 3.2
Jefferson, KY………… 22.2 426.8 0.5 846 5.8
East Baton Rouge, LA….. 13.8 261.6 0.5 772 8.6
Cumberland, ME……….. 12.3 168.7 1.2 785 4.0
Montgomery, MD……….. 32.8 457.4 0.2 1,213 6.6
Middlesex, MA………… 47.0 802.0 1.2 1,250 6.0
Wayne, MI……………. 32.7 744.8 -3.2 999 7.5
Hennepin, MN…………. 42.8 837.9 0.8 1,128 6.9
Hinds, MS……………. 6.5 127.8 -0.4 753 4.9
St. Louis, MO………… 33.0 605.1 1.1 903 1.2
Yellowstone, MT………. 5.6 75.5 3.6 672 5.5
Douglas, NE………….. 15.5 311.4 0.7 794 1.5
Clark, NV……………. 47.6 922.6 1.9 811 5.3
Hillsborough, NH……… 12.4 195.2 -0.2 922 4.2
Bergen, NJ…………… 35.3 447.9 0.6 1,110 4.4
Bernalillo, NM……….. 17.5 332.3 1.5 732 3.4
New York, NY…………. 116.7 2,331.5 2.3 2,821 16.7
Mecklenburg, NC………. 31.7 565.0 6.2 1,220 4.9
Cass, ND…………….. 5.6 94.5 2.7 678 4.5
Cuyahoga, OH…………. 38.0 740.6 -0.4 914 5.4
Oklahoma, OK…………. 23.2 419.5 0.8 751 -0.8
Multnomah, OR………… 27.7 443.0 3.1 864 2.7
Allegheny, PA………… 35.5 676.7 0.8 946 8.1
Providence, RI……….. 18.2 284.5 0.5 857 6.3
Greenville, SC……….. 14.1 235.6 2.5 713 2.3
Minnehaha, SD………… 6.2 112.0 2.0 708 3.7
Shelby, TN…………… 20.0 505.4 0.6 842 3.3
Harris, TX…………… 94.5 1,985.7 3.8 1,125 8.5
Salt Lake, UT………… 37.6 577.6 4.6 788 5.8
Chittenden, VT……….. 5.8 93.5 0.5 846 -0.2
Fairfax, VA………….. 32.5 579.5 1.2 1,371 4.3
King, WA…………….. 75.1 1,157.5 3.7 1,080 3.5
Kanawha, WV………….. 6.1 108.1 0.6 743 4.9
Milwaukee, WI………… 20.7 489.6 0.3 875 4.2
Laramie, WY………….. 3.1 41.9 2.1 673 6.2
San Juan, PR…………. 13.5 293.9 -3.3 573 7.1
St. Thomas, VI……….. 1.8 23.5 -0.6 653 6.0
(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) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted
for noneconomic county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin
Islands.
Table 4. Covered(1) establishments, employment, and wages by state,
first quarter 2007(2)
Employment Average weekly
wage(3)
Establishments,
first quarter
State 2007 Percent Percent
(thousands) March change, Average change,
2007 March weekly first
(thousands) 2006-07 wage quarter
2006-07
United States(4)……… 8,947.1 134,320.6 1.4 $885 5.1
Alabama……………… 118.8 1,953.7 1.6 716 3.5
Alaska………………. 21.0 299.8 1.1 831 5.2
Arizona……………… 156.1 2,667.2 1.8 803 4.7
Arkansas…………….. 82.5 1,179.9 0.7 642 3.2
California…………… 1,311.2 15,569.4 1.2 988 3.9
Colorado…………….. 177.0 2,262.4 2.3 889 3.6
Connecticut………….. 112.3 1,665.0 0.9 1,263 6.1
Delaware…………….. 29.4 416.6 0.4 986 2.1
District of Columbia….. 31.9 674.4 1.1 1,428 4.7
Florida……………… 601.6 8,093.4 0.9 764 3.4
Georgia……………… 268.0 4,065.1 1.9 837 4.9
Hawaii………………. 38.6 626.4 1.6 748 4.2
Idaho……………….. 56.1 645.0 3.4 636 4.6
Illinois…………….. 355.5 5,795.7 1.1 956 4.6
Indiana……………… 157.6 2,880.8 0.4 739 2.9
Iowa………………… 92.8 1,457.6 0.8 686 3.6
Kansas………………. 84.7 1,349.1 2.7 720 4.7
Kentucky…………….. 110.7 1,791.5 0.9 699 4.0
Louisiana……………. 119.7 1,863.5 4.2 730 4.4
Maine……………….. 50.2 582.1 0.9 677 3.7
Maryland…………….. 163.9 2,527.0 0.6 939 4.6
Massachusetts………… 208.9 3,167.5 1.0 1,110 6.1
Michigan…………….. 257.5 4,130.2 -1.7 851 4.0
Minnesota……………. 168.8 2,629.6 0.0 873 5.2
Mississippi………….. 69.8 1,127.3 1.1 616 3.2
Missouri…………….. 173.0 2,710.1 1.1 744 2.9
Montana……………… 41.9 428.8 3.0 600 4.9
Nebraska…………….. 57.8 899.3 1.1 667 2.8
Nevada………………. 73.8 1,282.3 1.8 802 4.8
New Hampshire………… 48.5 619.8 0.4 836 4.6
New Jersey…………… 278.7 3,926.6 0.2 1,097 5.6
New Mexico…………… 53.3 819.3 3.2 685 5.9
New York…………….. 574.0 8,441.3 1.3 1,397 11.8
North Carolina……….. 249.1 4,034.3 3.2 779 4.7
North Dakota…………. 24.6 334.5 1.7 615 4.8
Ohio………………… 292.3 5,241.0 -0.3 793 5.3
Oklahoma…………….. 97.9 1,534.3 1.9 676 1.3
Oregon………………. 133.5 1,707.8 2.3 755 2.7
Pennsylvania…………. 339.6 5,589.6 0.9 849 5.1
Rhode Island…………. 36.0 472.2 0.8 834 7.1
South Carolina……….. 134.7 1,885.9 3.0 677 2.3
South Dakota…………. 29.8 381.9 2.4 602 3.4
Tennessee……………. 139.1 2,732.5 0.7 738 4.7
Texas……………….. 545.9 10,143.0 3.3 872 5.6
Utah………………… 84.9 1,203.9 5.1 696 5.3
Vermont……………… 24.7 300.0 -0.2 704 2.3
Virginia…………….. 225.9 3,644.6 1.0 901 4.4
Washington…………… 213.4 2,869.9 3.1 868 4.3
West Virginia………… 48.3 700.3 0.3 652 4.2
Wisconsin……………. 157.5 2,727.7 0.5 745 3.9
Wyoming……………… 24.1 269.1 4.8 730 9.3
Puerto Rico………….. 56.5 1,024.5 -2.3 476 5.3
Virgin Islands……….. 3.4 45.6 -0.3 687 6.3
(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.
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