For release 10:00 a.m. (EDT), Thursday, March 28, 2013 USDL-13-0542
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
County Employment and Wages
Third Quarter 2012
From September 2011 to September 2012, employment increased in 276 of
the 328 largest U.S. counties, the U.S. Bureau of Labor Statistics
reported today. Elkhart, Ind., posted the largest increase, with a
gain of 6.9 percent over the year, compared with national job growth
of 1.6 percent. Within Elkhart, the largest employment increase
occurred in manufacturing, which gained 4,734 jobs over the year
(10.1 percent). Benton, Wash., had the largest over-the-year decrease
in employment among the largest counties in the U.S. with a loss of
5.2 percent. County employment and wage data are compiled under the
Quarterly Census of Employment and Wages (QCEW) program, which
produces detailed information on county employment and wages within 7
months after the end of each quarter.
The U.S. average weekly wage decreased over the year by 1.1 percent
to $906 in the third quarter of 2012. This is one of only six over-
the-year average weekly wage declines dating back to 1978, when the
first comparable quarterly data are available. (See Technical Note.)
Average weekly wages declined in every industry except for
information, in which wages increased by 1.3 percent. Wage declines
were also widespread across states, with the notable exception of a
6.3 percent increase in North Dakota. Yolo, Calif., had the largest
over-the-year decrease in average weekly wages with a loss of 7.0
percent. Within Yolo, a total wage decline of $102.9 million (-19.1
percent) in government had the largest contribution to the decrease
in average weekly wages. San Mateo, Calif., experienced the largest
increase in average weekly wages with a gain of 7.3 percent over the
year.
Table A. Large counties ranked by September 2012 employment, September 2011-12 employment
increase, and September 2011-12 percent increase in employment
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Employment in large counties
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September 2012 employment | Increase in employment, | Percent increase in employment,
(thousands) | September 2011-12 | September 2011-12
| (thousands) |
--------------------------------------------------------------------------------------------------------
| |
United States 132,624.7| United States 2,024.9| United States 1.6
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| |
Los Angeles, Calif. 3,983.5| Los Angeles, Calif. 81.6| Elkhart, Ind. 6.9
Cook, Ill. 2,424.6| Harris, Texas 78.6| Rutherford, Tenn. 6.8
New York, N.Y. 2,385.9| New York, N.Y. 52.4| Kern, Calif. 5.9
Harris, Texas 2,128.2| Maricopa, Ariz. 40.0| Montgomery, Texas 5.5
Maricopa, Ariz. 1,674.5| Dallas, Texas 38.3| Utah, Utah 5.3
Dallas, Texas 1,478.5| Santa Clara, Calif. 28.9| Fort Bend, Texas 4.3
Orange, Calif. 1,407.6| Orange, Calif. 28.6| Lexington, S.C. 4.2
San Diego, Calif. 1,283.3| King, Wash. 27.7| Cass, N.D. 4.1
King, Wash. 1,171.9| Cook, Ill. 24.6| Travis, Texas 3.9
Miami-Dade, Fla. 990.7| San Diego, Calif. 22.8| Washington, Ark. 3.8
| | Denver, Colo. 3.8
| | Delaware, Ohio 3.8
| | Harris, Texas 3.8
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Large County Employment
In September 2012, national employment, as measured by the QCEW
program, was 132.6 million, up by 1.6 percent or 2.0 million, from
September 2011. The 328 U.S. counties with 75,000 or more jobs
accounted for 71.0 percent of total U.S. employment and 76.3 percent
of total wages. These 328 counties had a net job growth of 1.5
million over the year, accounting for 74.3 percent of the overall
U.S. employment increase.
Elkhart, Ind., had the largest percentage increase in employment (6.9
percent) among the largest U.S. counties. The five counties with the
largest increases in employment level were Los Angeles, Calif.;
Harris, Texas; New York, N.Y.; Maricopa, Ariz.; and Dallas, Texas.
These counties had a combined over-the-year employment gain of
290,900, or 14.4 percent of the overall job increase for the U.S.
(See table A.)
Employment declined in 49 of the large counties from September 2011
to September 2012. Benton, Wash., had the largest over-the-year
percentage decrease in employment (-5.2 percent). Within Benton,
professional and business services was the largest contributor to the
decrease in employment with a loss of 3,677 jobs (-15.8 percent).
Jefferson, Texas, had the second largest percentage decrease in
employment, followed by Vanderburgh, Ind.; Sangamon, Ill.; and Hinds,
Miss. (See table 1.)
Table B. Large counties ranked by third quarter 2012 average weekly wages, third quarter 2011-12
decrease in average weekly wages, and third quarter 2011-12 percent decrease in average weekly wages
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Average weekly wage in large counties
--------------------------------------------------------------------------------------------------------
Average weekly wage, | Decrease in average weekly | Percent decrease in average
third quarter 2012 | wage, third quarter 2011-12 | weekly wage, third
| | quarter 2011-12
--------------------------------------------------------------------------------------------------------
| |
United States $906| United States -$10| United States -1.1
--------------------------------------------------------------------------------------------------------
| |
Santa Clara, Calif. $1,800| Benton, Wash. -$68| Yolo, Calif. -7.0
New York, N.Y. 1,626| Yolo, Calif. -66| Rockingham, N.H. -6.9
San Mateo, Calif. 1,537| Rockingham, N.H. -62| Lake, Ohio -6.9
Washington, D.C. 1,514| Fairfield, Conn. -58| Benton, Wash. -6.9
Arlington, Va. 1,488| Lake, Ohio -58| Montgomery, Ala. -5.9
San Francisco, Calif. 1,473| Arlington, Va. -57| York, Pa. -5.6
Fairfax, Va. 1,410| Hudson, N.J. -52| Brevard, Fla. -5.5
Suffolk, Mass. 1,397| Brevard, Fla. -49| Brown, Wis. -5.1
Fairfield, Conn. 1,371| Montgomery, Ala. -48| Erie, Pa. -4.6
King, Wash. 1,354| York, Pa. -48| Winnebago, Ill. -4.5
| | Monmouth, N.J. -4.5
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Large County Average Weekly Wages
Average weekly wages for the nation decreased by 1.1 percent during
the year ending in the third quarter of 2012. Among the 328 largest
counties, 274 had over-the-year declines in average weekly wages.
Yolo, Calif., had the largest wage decline among the largest U.S.
counties (-7.0 percent).
Of the 328 largest counties, 46 experienced over-the-year increases
in average weekly wages. San Mateo, Calif., had the largest average
weekly wage increase with a gain of 7.3 percent. Within San Mateo,
total wages in professional and business services grew by $439.3
million (25.7 percent) over the year. Douglas, Colo., had the second
largest increase in average weekly wages, followed by Pinellas, Fla.
Two counties, Clayton, Ga., and King, Wash., tied for the fourth
largest percentage increase. (See table 1.)
Ten Largest U.S. Counties
All of the 10 largest counties had over-the-year percentage increases
in employment in September 2012. Harris, Texas, had the largest gain
(3.8 percent). Within Harris, professional and business services had
the largest over-the-year level increase among all private industry
groups with a gain of 19,152 jobs (5.6 percent). Cook, Ill., had the
smallest percentage increase in employment (1.0 percent) among the 10
largest counties. (See table 2.)
Nine of the 10 largest U.S. counties had over-the-year decreases in
average weekly wages. Maricopa, Ariz., experienced the largest
decline in average weekly wages (-2.1 percent). Within Maricopa,
education and health services had the largest impact on the county’s
average weekly wage decline. Within this industry, employment grew by
5,374 (2.2 percent) while total wages paid to those workers decreased
by $59.9 million (-2.1 percent). King, Wash., had the only average
weekly wage increase (2.3 percent) among the 10 largest counties.
For More Information
The tables included in this release contain data for the nation and
for the 328 U.S. counties with annual average employment levels of
75,000 or more in 2011. September 2012 employment and 2012 third
quarter average weekly wages for all states are provided in table 3
of this release.
The employment and wage data by county are compiled under the QCEW
program, also known as the ES-202 program. The data are derived from
reports submitted by every employer subject to unemployment insurance
(UI) laws. The 9.2 million employer reports cover 132.6 million full-
and part-time workers. For additional information about the quarterly
employment and wages data, please read the Technical Note. Data for
the third quarter of 2012 will be available later at
http://www.bls.gov/cew/. Additional information about the QCEW data
may be obtained by calling (202) 691-6567.
Several BLS regional offices are issuing QCEW news releases targeted
to local data users. For links to these releases, see
http://www.bls.gov/cew/cewregional.htm.
_____________
The County Employment and Wages release for fourth quarter 2012 is
scheduled to be released on Thursday, June 27, 2013.
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| |
| Hurricane Sandy |
| |
| Hurricane Sandy made landfall in the United States on October 29, |
| 2012, after the QCEW third quarter reference period. Any impact will |
| be reflected in the fourth quarter release. This event did not |
| warrant changes to QCEW methodology. |
| |
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Technical Note
These data are the product of a federal-state cooperative program, the Quarterly
Census of Employment and Wages (QCEW) program, also known as the ES-202 program.
The data are derived from summaries of employment and total pay of workers covered
by state and federal unemployment insurance (UI) legislation and provided by State
Workforce Agencies (SWAs). The summaries are a result of the administration of
state unemployment insurance programs that require most employers to pay quarterly
taxes based on the employment and wages of workers covered by UI. QCEW data in this
release are based on the 2012 North American Industry Classification System. Data
for 2012 are preliminary and subject to revision.
For purposes of this release, large counties are defined as having employment le-
vels of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are pro-
vided, but not used in calculating U.S. averages, rankings, or in the analysis in
the text. Each year, these large counties are selected on the basis of the prelimi-
nary annual average of employment for the previous year. The 329 counties presented
in this release were derived using 2011 preliminary annual averages of employment.
For 2012 data, seven counties have been added to the publication tables: Okaloosa,
Fla.; Tippecanoe, Ind.; Johnson, Iowa; St. Tammany, La.; Saratoga, N.Y.; Delaware,
Ohio; and Gregg, Texas. These counties will be included in all 2012 quarterly re-
leases. One county, Jackson, Ore., which was published in the 2011 releases, will
be excluded from this and future 2012 releases because its 2011 annual average
employment levels were less than 75,000. The counties in table 2 are selected and
sorted each year based on the annual average employment from the preceding year.
The preliminary QCEW data presented in this release may differ from data released
by the individual states. These potential differences result from the states' con-
tinuing receipt of UI data over time and ongoing review and editing. The individual
states determine their data release timetables.
Differences between QCEW, BED, and CES employment measures
The Bureau publishes three different establishment-based employment measures for
any given quarter. Each of these measures--QCEW, Business Employment Dynamics (BED),
and Current Employment Statistics (CES)--makes use of the quarterly UI employment
reports in producing data; however, each measure has a somewhat different universe
coverage, estimation procedure, and publication product.
Differences in coverage and estimation methods can result in somewhat different
measures of employment change over time. It is important to understand program dif-
ferences and the intended uses of the program products. (See table.) Additional in-
formation on each program can be obtained from the program Web sites shown in the
table.
Summary of Major Differences between QCEW, BED, and CES Employment Measures
---------------------------------------------------------------------------------
| QCEW | BED | CES
-----------|---------------------|----------------------|------------------------
Source |--Count of UI admini-|--Count of longitudi- |--Sample survey:
| strative records | nally-linked UI ad- | 557,000 establish-
| submitted by 9.2 | ministrative records| ments
| million establish- | submitted by 6.8 |
| ments in first | million private-sec-|
| quarter of 2012 | 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 to an-
| new quarter of UI | dinal database and | nually realign sample-
| data | directly summarizes | based estimates to pop-
| | gross job gains and | ulation estimates to
| | losses | population counts (ben-
| | | chmarking)
-----------|---------------------|----------------------|------------------------
Principal |--Provides a quarter-|--Provides quarterly |--Provides current month-
products | ly and annual uni- | employer dynamics | ly estimates of employ-
| verse count of es- | data on establish- | ment, hours, and earn-
| tablishments, em- | ment openings, clos-| ings at the MSA, state,
| ployment, and wages| ings, expansions, | and national level by
| at the county, MSA,| and contractions at | industry
| state, and national| the national level |
| levels by detailed | by NAICS supersec- |
| industry | tors and by size of |
| | firm, and at the |
| | state private-sector|
| | total level |
| |--Future expansions |
| | will include data |
| | with greater indus- |
| | try detail and data |
| | at the county and |
| | MSA level |
-----------|---------------------|----------------------|------------------------
Principal |--Major uses include:|--Major uses include: |--Major uses include:
uses | -Detailed locality | -Business cycle | -Principal national
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -Analysis of employ-| cators
| surveys | ment expansion and |
| | contraction by size|
| | of firm |
| | |
-----------|---------------------|----------------------|------------------------
Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/
Web sites | | |
---------------------------------------------------------------------------------
Coverage
Employment and wage data for workers covered by state UI laws are compiled from
quarterly contribution reports submitted to the SWAs by employers. For federal ci-
vilian workers covered by the Unemployment Compensation for Federal Employees
(UCFE) program, employment and wage data are compiled from quarterly reports sub-
mitted by four major federal payroll processing centers on behalf of all federal
agencies, with the exception of a few agencies which still report directly to the
individual SWA. In addition to the quarterly contribution reports, employers who
operate multiple establishments within a state complete a questionnaire, called the
"Multiple Worksite Report," which provides detailed information on the location and
industry of each of their establishments. QCEW employment and wage data are derived
from microdata summaries of 9.1 million employer reports of employment and wages
submitted by states to the BLS in 2011. These reports are based on place of employ-
ment rather than place of residence.
UI and UCFE coverage is broad and has been basically comparable from state to state
since 1978, when the 1976 amendments to the Federal Unemployment Tax Act became ef-
fective, expanding coverage to include most State and local government employees.
In 2011, UI and UCFE programs covered workers in 129.4 million jobs. The estimated
124.8 million workers in these jobs (after adjustment for multiple jobholders)
represented 95.7 percent of civilian wage and salary employment. Covered workers
received $6.217 trillion in pay, representing 93.3 percent of the wage and salary
component of personal income and 41.2 percent of the gross domestic product.
Major exclusions from UI coverage include self-employed workers, most agricultural
workers on small farms, all members of the Armed Forces, elected officials in most
states, most employees of railroads, some domestic workers, most student workers at
schools, and employees of certain small nonprofit organizations.
State and federal UI laws change periodically. These changes may have an impact on
the employment and wages reported by employers covered under the UI program. Cover-
age changes may affect the over-the-year comparisons presented in this news re-
lease.
Concepts and methodology
Monthly employment is based on the number of workers who worked during or received
pay for the pay period including the 12th of the month. With few exceptions, all
employees of covered firms are reported, including production and sales workers,
corporation officials, executives, supervisory personnel, and clerical workers.
Workers on paid vacations and part-time workers also are included.
Average weekly wage values are calculated by dividing quarterly total wages by the
average of the three monthly employment levels (all employees, as described above)
and dividing the result by 13, for the 13 weeks in the quarter. These calculations
are made using unrounded employment and wage values. The average wage values that
can be calculated using rounded data from the BLS database may differ from the av-
erages reported. Included in the quarterly wage data are non-wage cash payments
such as bonuses, the cash value of meals and lodging when supplied, tips and other
gratuities, and, in some states, employer contributions to certain deferred compen-
sation plans such as 401(k) plans and stock options. Over-the-year comparisons of
average weekly wages may reflect fluctuations in average monthly employment and/or
total quarterly wages between the current quarter and prior year levels.
Average weekly wages are affected by the ratio of full-time to part-time workers as
well as the number of individuals in high-paying and low-paying occupations and the
incidence of pay periods within a quarter. For instance, the average weekly wage of
the work force could increase significantly when there is a large decline in the
number of employees that had been receiving below-average wages. Wages may include
payments to workers not present in the employment counts because they did not work
during the pay period including the 12th of the month. When comparing average week-
ly wage levels between industries, states, or quarters, these factors should be
taken into consideration.
Federal government pay levels are subject to periodic, sometimes large, fluctua-
tions due to a calendar effect that consists of some quarters having more pay pe-
riods than others. Most federal employees are paid on a biweekly pay schedule. As a
result of this schedule, in some quarters, federal wages contain payments for six
pay periods, while in other quarters their wages include payments for seven pay pe-
riods. Over-the-year comparisons of average weekly wages may reflect this calendar
effect. Higher growth in average weekly wages may be attributed, in part, to a com-
parison of quarterly wages for the current year, which include seven pay periods,
with year-ago wages that reflect only six pay periods. An opposite effect will oc-
cur when wages in the current period, which contain six pay periods, are compared
with year-ago wages that include seven pay periods. The effect on over-the-year pay
comparisons can be pronounced in federal government due to the uniform nature of
federal payroll processing. This pattern may exist in private sector pay; however,
because there are more pay period types (weekly, biweekly, semimonthly, monthly) it
is less pronounced. The effect is most visible in counties with large concentra-
tions of federal employment.
In order to ensure the highest possible quality of data, states verify with employ-
ers and update, if necessary, the industry, location, and ownership classification
of all establishments on a 4-year cycle. Changes in establishment classification
codes resulting from this process are introduced with the data reported for the
first quarter of the year. Changes resulting from improved employer reporting also
are introduced in the first quarter.
QCEW data are not designed as a time series. QCEW data are simply the sums of indi-
vidual establishment records and reflect the number of establishments that exist in
a county or industry at a point in time. Establishments can move in or out of a
county or industry for a number of reasons--some reflecting economic events, others
reflecting administrative changes. For example, economic change would come from a
firm relocating into the county; administrative change would come from a company
correcting its county designation.
The over-the-year changes of employment and wages presented in this release have
been adjusted to account for most of the administrative corrections made to the un-
derlying establishment reports. This is done by modifying the prior-year levels
used to calculate the over-the-year changes. Percent changes are calculated using
an adjusted version of the final 2011 quarterly data as the base data. The adjusted
prior-year levels used to calculate the over-the-year percent change in employment
and wages are not published. These adjusted prior-year levels do not match the un-
adjusted data maintained on the BLS Web site. Over-the-year change calculations
based on data from the Web site, or from data published in prior BLS news releases,
may differ substantially from the over-the-year changes presented in this news re-
lease.
The adjusted data used to calculate the over-the-year change measures presented in
this release account for most of the administrative changes--those occurring when
employers update the industry, location, and ownership information of their estab-
lishments. The most common adjustments for administrative change are the result of
updated information about the county location of individual establishments. In-
cluded in these adjustments are administrative changes involving the classification
of establishments that were previously reported in the unknown or statewide county
or unknown industry categories. Beginning with the first quarter of 2008, adjusted
data account for administrative changes caused by multi-unit employers who start
reporting for each individual establishment rather than as a single entity.
The adjusted data used to calculate the over-the-year change measures presented in
any County Employment and Wages news release are valid for comparisons between the
starting and ending points (a 12-month period) used in that particular release.
Comparisons may not be valid for any time period other than the one featured in a
release even if the changes were calculated using adjusted data.
County definitions are assigned according to Federal Information Processing Stan-
dards Publications (FIPS PUBS) as issued by the National Institute of Standards and
Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of
the Information Technology Management Reform Act of 1996 and the Computer Security
Act of 1987, Public Law 104-106. Areas shown as counties include those designated
as independent cities in some jurisdictions and, in Alaska, those designated as
census areas where counties have not been created. County data also are presented
for the New England states for comparative purposes even though townships are the
more common designation used in New England (and New Jersey). The regions referred
to in this release are defined as census regions.
Additional statistics and other information
Employment and Wages Annual Averages Online features comprehensive information by
detailed industry on establishments, employment, and wages for the nation and all
states. The 2011 edition of this publication, which was published in October 2012,
contains selected data produced by Business Employment Dynamics (BED) on job gains
and losses, as well as selected data from the first quarter 2012 version of this
news release. Tables and additional content from Employment and Wages Annual Aver-
ages 2011 are now available online at http://www.bls.gov/cew/cewbultn11.htm. The
2012 edition of Employment and Wages Annual Averages Online will be available later
in 2013.
News releases on quarterly measures of gross job flows also are available upon re-
quest from the Division of Administrative Statistics and Labor Turnover (Business
Employment Dynamics), telephone (202) 691-6467; (http://www.bls.gov/bdm/); (e-mail:
BDMInfo@bls.gov).
Information in this release will be made available to sensory impaired individuals
upon request. Voice phone: (202) 691-5200; TDD message referral phone number: 1-800-
877-8339.
Table 1. Covered(1) establishments, employment, and wages in the 329 largest counties,
third quarter 2012(2)
Employment Average weekly wage(4)
Establishments,
County(3) third quarter Percent Ranking Percent Ranking
2012 September change, by Third change, by
(thousands) 2012 September percent quarter third percent
(thousands) 2011-12(5) change 2012 quarter change
2011-12(5)
United States(6)......... 9,165.4 132,624.7 1.6 - $906 -1.1 -
Jefferson, AL............ 17.7 336.3 1.0 186 910 -1.4 147
Madison, AL.............. 8.9 178.6 0.1 273 1,005 -3.0 276
Mobile, AL............... 9.7 164.2 -0.7 307 802 -4.3 316
Montgomery, AL........... 6.3 128.1 1.5 140 765 -5.9 324
Tuscaloosa, AL........... 4.2 85.6 1.5 140 792 -0.6 86
Anchorage Borough, AK.... 8.3 157.0 1.1 177 1,010 -0.6 86
Maricopa, AZ............. 96.1 1,674.5 2.4 54 886 -2.1 213
Pima, AZ................. 19.1 346.8 1.3 161 787 -1.1 116
Benton, AR............... 5.5 97.1 0.9 200 885 1.7 9
Pulaski, AR.............. 14.4 243.1 0.3 256 819 -2.3 228
Washington, AR........... 5.6 93.8 3.8 10 728 -2.5 250
Alameda, CA.............. 53.8 664.1 3.1 30 1,188 -2.9 271
Contra Costa, CA......... 28.6 326.0 2.4 54 1,126 2.2 6
Fresno, CA............... 28.7 351.9 1.1 177 710 -1.5 155
Kern, CA................. 16.8 312.7 5.9 3 783 -2.7 262
Los Angeles, CA.......... 412.7 3,983.5 2.1 89 1,002 -1.7 173
Marin, CA................ 11.6 107.0 3.5 22 1,069 -0.6 86
Monterey, CA............. 12.3 186.5 2.3 67 783 -0.8 102
Orange, CA............... 102.8 1,407.6 2.1 89 1,024 -1.4 147
Placer, CA............... 10.7 131.2 2.4 54 906 0.4 32
Riverside, CA............ 48.1 569.4 2.8 40 726 -3.7 304
Sacramento, CA........... 49.5 591.4 1.8 117 1,007 -1.5 155
San Bernardino, CA....... 47.6 612.5 1.9 110 771 -2.8 265
San Diego, CA............ 101.0 1,283.3 1.8 117 993 -2.0 202
San Francisco, CA........ 53.8 593.9 3.6 17 1,473 1.0 19
San Joaquin, CA.......... 16.1 208.9 0.2 261 786 -1.8 186
San Luis Obispo, CA...... 9.4 107.3 3.5 22 738 -2.0 202
San Mateo, CA............ 24.4 342.9 3.6 17 1,537 7.3 1
Santa Barbara, CA........ 14.1 188.1 2.2 79 850 -3.4 300
Santa Clara, CA.......... 62.0 907.7 3.3 26 1,800 -1.5 155
Santa Cruz, CA........... 8.8 98.0 2.5 49 851 1.4 14
Solano, CA............... 9.5 122.6 2.4 54 910 -1.2 127
Sonoma, CA............... 18.1 181.0 2.6 47 856 -3.1 283
Stanislaus, CA........... 13.6 170.0 1.5 140 776 -0.9 108
Tulare, CA............... 8.8 146.6 -1.4 317 636 0.0 47
Ventura, CA.............. 23.6 303.1 2.3 67 936 0.2 41
Yolo, CA................. 6.2 99.2 2.3 67 882 -7.0 328
Adams, CO................ 9.1 161.0 2.0 97 839 -2.6 255
Arapahoe, CO............. 19.2 288.3 2.9 36 1,052 -3.0 276
Boulder, CO.............. 13.3 161.5 1.7 123 1,072 0.4 32
Denver, CO............... 26.5 438.2 3.8 10 1,111 -1.8 186
Douglas, CO.............. 9.9 96.0 3.6 17 1,030 5.4 2
El Paso, CO.............. 17.1 239.1 0.7 221 846 -1.6 165
Jefferson, CO............ 18.1 214.4 2.2 79 919 -1.4 147
Larimer, CO.............. 10.3 134.7 2.2 79 813 -1.1 116
Weld, CO................. 5.9 86.7 3.7 14 798 0.0 47
Fairfield, CT............ 33.0 409.5 0.8 209 1,371 -4.1 311
Hartford, CT............. 25.7 494.7 1.0 186 1,079 -1.7 173
New Haven, CT............ 22.5 356.5 0.8 209 956 -1.6 165
New London, CT........... 7.0 123.6 -1.1 315 902 -3.3 296
New Castle, DE........... 17.1 265.7 -0.2 285 1,039 -1.7 173
Washington, DC........... 36.1 714.9 0.6 233 1,514 -0.7 96
Alachua, FL.............. 6.6 116.9 0.7 221 749 -1.7 173
Brevard, FL.............. 14.4 186.6 -0.3 290 836 -5.5 322
Broward, FL.............. 63.6 701.1 2.3 67 838 -2.4 240
Collier, FL.............. 11.9 112.7 2.4 54 776 -1.1 116
Duval, FL................ 27.2 442.7 2.0 97 862 -1.3 140
Escambia, FL............. 8.0 120.0 1.0 186 702 -3.8 306
Hillsborough, FL......... 38.3 582.9 1.7 123 863 -2.3 228
Lake, FL................. 7.3 81.1 2.3 67 630 -0.6 86
Lee, FL.................. 18.8 199.1 1.4 151 728 -1.2 127
Leon, FL................. 8.2 137.7 -0.1 280 755 -0.5 83
Manatee, FL.............. 9.3 101.6 2.0 97 692 -3.8 306
Marion, FL............... 7.9 90.2 1.6 134 621 -2.1 213
Miami-Dade, FL........... 89.6 990.7 2.0 97 857 -1.7 173
Okaloosa, FL............. 6.0 76.0 -0.9 312 744 -2.1 213
Orange, FL............... 36.4 682.0 2.4 54 795 -1.9 194
Palm Beach, FL........... 49.8 498.7 2.1 89 862 -1.6 165
Pasco, FL................ 10.0 99.2 1.7 123 624 -1.4 147
Pinellas, FL............. 30.8 381.8 0.9 200 842 4.3 3
Polk, FL................. 12.4 188.4 1.2 171 708 -0.6 86
Sarasota, FL............. 14.5 136.4 2.7 45 733 -1.2 127
Seminole, FL............. 13.9 158.1 1.4 151 747 -0.7 96
Volusia, FL.............. 13.4 149.8 0.7 221 644 -1.1 116
Bibb, GA................. 4.6 80.3 0.7 221 708 -3.8 306
Chatham, GA.............. 7.8 133.9 2.3 67 777 -2.0 202
Clayton, GA.............. 4.3 110.6 -0.7 307 894 2.3 4
Cobb, GA................. 21.6 300.2 1.1 177 959 0.2 41
De Kalb, GA.............. 17.9 275.2 -0.6 303 944 -1.7 173
Fulton, GA............... 41.9 724.3 2.4 54 1,165 -2.5 250
Gwinnett, GA............. 24.3 308.5 1.0 186 892 -3.3 296
Muscogee, GA............. 4.7 93.7 -0.6 303 727 -0.4 76
Richmond, GA............. 4.7 98.3 0.4 253 791 -1.2 127
Honolulu, HI............. 24.6 443.7 1.6 134 862 -0.9 108
Ada, ID.................. 13.6 202.0 2.1 89 790 -1.1 116
Champaign, IL............ 4.3 88.4 0.6 233 816 1.6 10
Cook, IL................. 149.3 2,424.6 1.0 186 1,032 -1.5 155
Du Page, IL.............. 37.3 572.5 1.8 117 1,056 -0.2 62
Kane, IL................. 13.3 196.9 1.5 140 810 -2.3 228
Lake, IL................. 22.2 326.9 1.3 161 1,148 1.5 11
McHenry, IL.............. 8.7 94.5 0.5 241 757 -3.1 283
McLean, IL............... 3.8 86.8 1.3 161 878 -3.3 296
Madison, IL.............. 6.0 95.0 -1.0 314 752 -2.8 265
Peoria, IL............... 4.7 104.0 1.7 123 853 -2.5 250
St. Clair, IL............ 5.6 93.7 -1.8 323 753 -3.2 291
Sangamon, IL............. 5.3 127.7 -2.1 325 944 0.0 47
Will, IL................. 15.3 205.0 0.9 200 796 -2.0 202
Winnebago, IL............ 6.8 126.0 0.8 209 761 -4.5 318
Allen, IN................ 9.0 176.9 1.0 186 743 -3.1 283
Elkhart, IN.............. 4.8 112.1 6.9 1 737 -0.3 68
Hamilton, IN............. 8.5 115.5 1.2 171 843 -2.4 240
Lake, IN................. 10.4 191.9 1.8 117 858 1.4 14
Marion, IN............... 24.0 569.4 2.6 47 931 -1.6 165
St. Joseph, IN........... 6.0 117.4 0.0 277 750 -0.7 96
Tippecanoe, IN........... 3.3 79.8 2.9 36 762 -2.3 228
Vanderburgh, IN.......... 4.8 104.6 -2.2 326 722 -2.4 240
Johnson, IA.............. 3.6 78.3 0.9 200 856 0.4 32
Linn, IA................. 6.3 126.6 0.5 241 874 -1.4 147
Polk, IA................. 15.1 273.7 1.9 110 905 -1.0 113
Scott, IA................ 5.3 88.8 0.9 200 746 -1.3 140
Johnson, KS.............. 21.1 311.2 2.3 67 917 -1.8 186
Sedgwick, KS............. 12.3 239.4 0.5 241 809 -2.2 220
Shawnee, KS.............. 4.8 94.6 -0.7 307 764 -3.0 276
Wyandotte, KS............ 3.2 85.6 2.9 36 854 -1.6 165
Fayette, KY.............. 9.6 180.7 2.2 79 816 -1.9 194
Jefferson, KY............ 22.7 429.5 2.8 40 882 -0.6 86
Caddo, LA................ 7.6 119.5 -1.6 321 741 -4.1 311
Calcasieu, LA............ 4.9 84.4 1.9 110 785 -1.9 194
East Baton Rouge, LA..... 15.0 259.2 1.5 140 850 -0.2 62
Jefferson, LA............ 14.0 188.8 -1.6 321 847 -3.1 283
Lafayette, LA............ 9.2 136.5 0.9 200 878 -3.1 283
Orleans, LA.............. 11.4 174.5 0.8 209 895 -3.1 283
St. Tammany, LA.......... 7.6 79.1 2.1 89 769 -2.9 271
Cumberland, ME........... 12.7 172.4 0.6 233 799 -1.6 165
Anne Arundel, MD......... 14.6 241.9 3.5 22 978 -2.7 262
Baltimore, MD............ 21.3 364.5 1.5 140 930 -2.6 255
Frederick, MD............ 6.2 93.8 1.6 134 879 -2.4 240
Harford, MD.............. 5.6 87.8 2.3 67 891 -2.7 262
Howard, MD............... 9.2 159.8 2.0 97 1,111 -1.7 173
Montgomery, MD........... 33.5 452.4 0.7 221 1,236 -0.2 62
Prince Georges, MD....... 15.6 301.0 0.2 261 981 -2.4 240
Baltimore City, MD....... 14.0 332.5 0.7 221 1,072 -0.4 76
Barnstable, MA........... 9.0 96.1 2.0 97 746 -1.5 155
Bristol, MA.............. 16.1 212.9 0.1 273 816 -1.1 116
Essex, MA................ 21.6 308.3 1.4 151 946 -1.8 186
Hampden, MA.............. 15.5 197.9 -0.3 290 831 -1.2 127
Middlesex, MA............ 49.2 829.8 1.7 123 1,318 -0.3 68
Norfolk, MA.............. 23.4 323.0 1.3 161 1,033 -2.2 220
Plymouth, MA............. 14.0 178.4 2.2 79 838 -0.5 83
Suffolk, MA.............. 23.6 598.7 1.3 161 1,397 -2.1 213
Worcester, MA............ 21.4 317.8 0.2 261 910 -1.9 194
Genesee, MI.............. 7.2 129.4 0.0 277 744 -4.1 311
Ingham, MI............... 6.4 154.1 -0.7 307 850 -1.0 113
Kalamazoo, MI............ 5.4 110.2 0.7 221 838 -1.2 127
Kent, MI................. 14.1 337.1 2.9 36 799 -2.3 228
Macomb, MI............... 17.3 292.8 1.7 123 902 -2.4 240
Oakland, MI.............. 38.4 666.4 3.2 29 997 -1.4 147
Ottawa, MI............... 5.6 111.4 2.3 67 738 -1.2 127
Saginaw, MI.............. 4.2 83.5 -0.5 297 741 -2.2 220
Washtenaw, MI............ 8.1 194.6 2.4 54 977 0.8 23
Wayne, MI................ 31.7 690.3 1.2 171 984 -2.0 202
Anoka, MN................ 7.2 111.9 1.7 123 874 -0.1 55
Dakota, MN............... 9.9 172.8 1.1 177 882 -0.1 55
Hennepin, MN............. 43.1 850.1 2.0 97 1,133 0.4 32
Olmsted, MN.............. 3.4 91.3 1.9 110 954 0.7 25
Ramsey, MN............... 14.0 323.1 0.3 256 990 -3.3 296
St. Louis, MN............ 5.6 94.7 0.1 273 778 -1.1 116
Stearns, MN.............. 4.4 81.4 1.4 151 726 -3.2 291
Harrison, MS............. 4.4 82.6 -0.1 280 668 -2.8 265
Hinds, MS................ 5.9 119.7 -1.9 324 783 -1.1 116
Boone, MO................ 4.5 87.5 3.3 26 736 0.4 32
Clay, MO................. 5.1 87.6 -0.8 311 804 -2.2 220
Greene, MO............... 8.1 154.7 3.0 32 693 -2.8 265
Jackson, MO.............. 18.8 348.7 1.5 140 914 -1.7 173
St. Charles, MO.......... 8.3 127.6 2.3 67 713 -2.6 255
St. Louis, MO............ 32.3 568.5 0.3 256 963 -0.8 102
St. Louis City, MO....... 9.5 218.1 -0.5 297 1,001 -1.2 127
Yellowstone, MT.......... 6.1 79.2 2.3 67 755 -1.9 194
Douglas, NE.............. 17.7 316.7 1.7 123 853 -0.9 108
Lancaster, NE............ 9.4 158.6 2.5 49 742 -0.5 83
Clark, NV................ 48.9 821.0 1.9 110 804 -3.5 302
Washoe, NV............... 13.6 186.1 0.4 253 827 -2.6 255
Hillsborough, NH......... 12.0 189.1 1.0 186 970 -3.0 276
Rockingham, NH........... 10.6 138.1 1.5 140 843 -6.9 325
Atlantic, NJ............. 6.6 136.4 0.6 233 761 -3.2 291
Bergen, NJ............... 32.8 428.5 0.9 200 1,079 -0.6 86
Burlington, NJ........... 10.9 195.2 2.1 89 949 -2.4 240
Camden, NJ............... 12.0 192.0 0.2 261 893 -1.2 127
Essex, NJ................ 20.3 335.9 0.2 261 1,118 -1.9 194
Gloucester, NJ........... 6.1 97.2 0.2 261 798 -2.1 213
Hudson, NJ............... 13.8 233.0 1.2 171 1,236 -4.0 310
Mercer, NJ............... 10.8 228.9 0.8 209 1,207 -0.8 102
Middlesex, NJ............ 21.6 387.3 2.0 97 1,069 -3.2 291
Monmouth, NJ............. 19.7 243.6 0.6 233 887 -4.5 318
Morris, NJ............... 17.1 271.9 0.8 209 1,299 0.2 41
Ocean, NJ................ 12.2 152.2 1.3 161 721 -2.0 202
Passaic, NJ.............. 12.2 170.0 0.2 261 890 -2.9 271
Somerset, NJ............. 10.0 171.7 1.0 186 1,327 -1.3 140
Union, NJ................ 14.2 219.0 1.1 177 1,140 -0.6 86
Bernalillo, NM........... 17.8 309.9 -0.3 290 809 -3.0 276
Albany, NY............... 10.1 219.9 0.5 241 953 -1.7 173
Bronx, NY................ 17.2 237.2 1.0 186 878 -1.2 127
Broome, NY............... 4.6 89.8 -0.2 285 720 -2.0 202
Dutchess, NY............. 8.3 110.8 -0.3 290 900 -2.6 255
Erie, NY................. 24.0 457.3 -0.1 280 786 -3.6 303
Kings, NY................ 53.7 519.6 2.4 54 747 -1.6 165
Monroe, NY............... 18.4 373.9 -0.2 285 877 -1.2 127
Nassau, NY............... 53.0 594.7 2.0 97 980 -0.8 102
New York, NY............. 123.7 2,385.9 2.2 79 1,626 -1.3 140
Oneida, NY............... 5.3 104.9 -1.5 319 713 -1.7 173
Onondaga, NY............. 13.0 242.6 0.2 261 832 -1.3 140
Orange, NY............... 9.9 131.3 -0.2 285 751 -3.1 283
Queens, NY............... 47.7 526.4 2.4 54 852 -2.2 220
Richmond, NY............. 9.1 92.7 1.1 177 784 -2.5 250
Rockland, NY............. 10.0 114.5 0.2 261 986 1.0 19
Saratoga, NY............. 5.6 78.2 1.6 134 804 0.4 32
Suffolk, NY.............. 51.1 622.7 0.5 241 1,022 -0.3 68
Westchester, NY.......... 36.2 405.6 -0.1 280 1,160 1.0 19
Buncombe, NC............. 8.0 115.3 3.1 30 699 -1.8 186
Catawba, NC.............. 4.4 79.4 2.0 97 682 -2.3 228
Cumberland, NC........... 6.3 117.2 -1.5 319 747 -2.2 220
Durham, NC............... 7.4 185.3 2.4 54 1,220 -2.9 271
Forsyth, NC.............. 9.0 174.8 1.8 117 838 -1.8 186
Guilford, NC............. 14.2 263.0 0.5 241 810 0.0 47
Mecklenburg, NC.......... 33.3 570.9 2.5 49 1,055 0.7 25
New Hanover, NC.......... 7.4 97.9 2.5 49 727 -2.3 228
Wake, NC................. 29.8 457.1 3.0 32 899 0.7 25
Cass, ND................. 6.2 108.4 4.1 8 828 0.7 25
Butler, OH............... 7.4 139.5 0.2 261 800 -1.7 173
Cuyahoga, OH............. 35.7 703.4 1.5 140 934 0.8 23
Delaware, OH............. 4.4 80.3 3.8 10 874 -2.0 202
Franklin, OH............. 29.8 672.2 1.4 151 917 -3.4 300
Hamilton, OH............. 23.2 492.3 1.4 151 1,028 1.8 7
Lake, OH................. 6.4 94.0 -0.6 303 782 -6.9 325
Lorain, OH............... 6.0 94.4 0.8 209 753 -2.2 220
Lucas, OH................ 10.1 202.4 1.7 123 789 -2.1 213
Mahoning, OH............. 5.9 98.6 1.0 186 666 -2.6 255
Montgomery, OH........... 12.1 243.6 0.7 221 799 -2.0 202
Stark, OH................ 8.8 154.5 1.0 186 700 -2.4 240
Summit, OH............... 14.3 256.4 0.6 233 822 -0.1 55
Oklahoma, OK............. 25.0 429.9 1.4 151 880 -2.3 228
Tulsa, OK................ 20.6 336.0 1.3 161 855 -1.6 165
Clackamas, OR............ 12.8 141.1 2.0 97 834 -0.4 76
Lane, OR................. 10.9 137.9 1.2 171 716 0.0 47
Marion, OR............... 9.5 135.7 -0.5 297 711 -0.6 86
Multnomah, OR............ 30.2 442.8 2.0 97 938 0.1 45
Washington, OR........... 16.6 251.0 2.2 79 1,111 -0.8 102
Allegheny, PA............ 35.7 684.5 0.8 209 988 1.5 11
Berks, PA................ 9.0 164.7 1.1 177 844 1.0 19
Bucks, PA................ 19.7 246.6 -0.6 303 869 -0.9 108
Butler, PA............... 4.9 83.0 -0.5 297 834 -2.3 228
Chester, PA.............. 15.1 236.0 0.1 273 1,128 0.3 38
Cumberland, PA........... 6.1 124.6 1.4 151 829 -3.2 291
Dauphin, PA.............. 7.5 174.8 1.0 186 898 -1.5 155
Delaware, PA............. 13.9 209.9 0.6 233 954 -2.2 220
Erie, PA................. 7.7 125.7 -0.4 294 734 -4.6 320
Lackawanna, PA........... 5.9 97.1 -0.9 312 697 -2.0 202
Lancaster, PA............ 12.8 220.5 0.7 221 756 -2.3 228
Lehigh, PA............... 8.7 176.8 0.5 241 868 -2.9 271
Luzerne, PA.............. 7.7 139.8 0.2 261 716 -2.1 213
Montgomery, PA........... 27.4 465.8 1.2 171 1,109 -0.4 76
Northampton, PA.......... 6.6 103.7 1.4 151 799 -1.5 155
Philadelphia, PA......... 36.1 631.9 0.9 200 1,085 -2.4 240
Washington, PA........... 5.6 85.8 0.2 261 873 -0.3 68
Westmoreland, PA......... 9.5 133.5 0.5 241 737 -4.2 314
York, PA................. 9.1 172.3 0.5 241 806 -5.6 323
Providence, RI........... 17.5 272.0 0.7 221 889 -2.6 255
Charleston, SC........... 12.0 217.7 2.5 49 800 -0.7 96
Greenville, SC........... 12.1 234.4 1.5 140 805 -0.2 62
Horry, SC................ 7.7 111.6 0.6 233 554 -1.1 116
Lexington, SC............ 5.7 98.9 4.2 7 697 -1.4 147
Richland, SC............. 8.9 203.5 1.1 177 786 -2.8 265
Spartanburg, SC.......... 5.8 115.1 1.8 117 766 -2.0 202
Minnehaha, SD............ 6.6 117.4 2.8 40 776 0.0 47
Davidson, TN............. 18.5 434.1 2.2 79 945 -0.2 62
Hamilton, TN............. 8.5 185.7 1.5 140 803 -1.7 173
Knox, TN................. 10.9 219.6 -0.4 294 793 1.1 18
Rutherford, TN........... 4.4 104.5 6.8 2 798 -1.1 116
Shelby, TN............... 19.1 469.8 1.0 186 954 0.2 41
Williamson, TN........... 6.3 98.2 3.7 14 969 1.5 11
Bell, TX................. 4.9 108.9 1.7 123 749 -0.9 108
Bexar, TX................ 35.3 752.6 2.2 79 818 -0.6 86
Brazoria, TX............. 5.0 92.8 1.9 110 876 -1.9 194
Brazos, TX............... 4.0 88.7 3.6 17 721 -0.1 55
Cameron, TX.............. 6.4 128.2 1.3 161 580 -1.4 147
Collin, TX............... 19.4 309.7 3.7 14 1,057 0.3 38
Dallas, TX............... 69.4 1,478.5 2.7 45 1,085 -1.3 140
Denton, TX............... 11.6 185.2 3.0 32 824 0.6 30
El Paso, TX.............. 14.1 277.2 0.7 221 654 -2.5 250
Fort Bend, TX............ 9.9 144.2 4.3 6 928 -0.3 68
Galveston, TX............ 5.5 95.7 0.5 241 804 -4.4 317
Gregg, TX................ 4.2 78.3 2.1 89 834 -0.4 76
Harris, TX............... 103.7 2,128.2 3.8 10 1,154 -0.3 68
Hidalgo, TX.............. 11.5 225.6 0.8 209 584 -2.3 228
Jefferson, TX............ 5.9 120.2 -2.9 327 913 -0.7 96
Lubbock, TX.............. 7.1 126.1 1.6 134 716 1.8 7
McLennan, TX............. 4.9 102.0 0.8 209 735 -2.8 265
Montgomery, TX........... 9.2 143.2 5.5 4 868 -0.3 68
Nueces, TX............... 7.9 156.0 2.8 40 801 0.3 38
Smith, TX................ 5.7 92.2 -0.4 294 780 -1.5 155
Tarrant, TX.............. 38.8 786.1 2.3 67 909 -1.0 113
Travis, TX............... 32.4 607.3 3.9 9 1,003 -0.8 102
Webb, TX................. 4.9 91.0 2.1 89 637 1.4 14
Williamson, TX........... 8.0 132.7 1.6 134 914 -1.8 186
Davis, UT................ 7.3 109.1 1.9 110 741 -3.0 276
Salt Lake, UT............ 38.2 594.9 3.6 17 858 -1.5 155
Utah, UT................. 13.1 181.3 5.3 5 704 -1.7 173
Weber, UT................ 5.5 90.5 1.3 161 672 -2.3 228
Chittenden, VT........... 6.1 98.9 1.4 151 870 -1.9 194
Arlington, VA............ 8.6 165.1 -1.4 317 1,488 -3.7 304
Chesterfield, VA......... 7.9 116.5 2.2 79 826 -0.1 55
Fairfax, VA.............. 35.3 590.1 0.8 209 1,410 -2.4 240
Henrico, VA.............. 10.3 178.9 2.4 54 898 -1.5 155
Loudoun, VA.............. 10.2 142.0 3.0 32 1,077 -3.1 283
Prince William, VA....... 8.1 113.0 3.3 26 828 -1.8 186
Alexandria City, VA...... 6.3 96.3 0.9 200 1,266 -0.2 62
Chesapeake City, VA...... 5.8 94.5 -1.2 316 725 -1.2 127
Newport News City, VA.... 3.8 96.6 0.7 221 871 -1.2 127
Norfolk City, VA......... 5.7 137.6 -0.5 297 908 0.6 30
Richmond City, VA........ 7.2 148.9 0.5 241 1,001 -1.1 116
Virginia Beach City, VA.. 11.5 165.0 1.3 161 723 -0.1 55
Benton, WA............... 5.8 79.1 -5.2 328 913 -6.9 325
Clark, WA................ 13.8 131.0 2.0 97 849 1.2 17
King, WA................. 83.2 1,171.9 2.4 54 1,354 2.3 4
Kitsap, WA............... 6.7 80.3 -0.5 297 885 -0.7 96
Pierce, WA............... 21.9 266.0 0.5 241 840 -0.4 76
Snohomish, WA............ 19.4 259.7 2.8 40 996 0.7 25
Spokane, WA.............. 16.1 200.9 0.8 209 780 -0.3 68
Thurston, WA............. 7.6 96.9 1.0 186 847 -0.4 76
Whatcom, WA.............. 7.0 80.7 0.3 256 758 0.0 47
Yakima, WA............... 8.9 113.7 3.4 25 620 0.0 47
Kanawha, WV.............. 6.0 104.9 -0.1 280 781 -3.0 276
Brown, WI................ 6.6 148.6 1.7 123 779 -5.1 321
Dane, WI................. 14.2 306.5 1.1 177 842 -3.9 309
Milwaukee, WI............ 23.4 473.7 0.3 256 879 -4.2 314
Outagamie, WI............ 5.1 102.3 0.4 253 771 0.1 45
Waukesha, WI............. 12.7 227.9 0.0 277 887 -1.3 140
Winnebago, WI............ 3.6 89.4 -0.2 285 829 -0.1 55
San Juan, PR............. 11.3 264.0 2.0 (7) 601 -0.5 (7)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 328 U.S. counties comprise 71.0 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) This county was not included in the U.S. rankings.
Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties,
third quarter 2012(2)
Employment Average weekly
wage(3)
Establishments,
third quarter
County by NAICS supersector 2012 Percent Percent
(thousands) September change, Third change,
2012 September quarter third
(thousands) 2011-12(4) 2012 quarter
2011-12(4)
United States(5)............................. 9,165.4 132,624.7 1.6 $906 -1.1
Private industry........................... 8,869.4 111,530.4 1.9 897 -1.1
Natural resources and mining............. 130.9 2,105.2 3.7 984 -0.2
Construction............................. 750.0 5,795.2 1.0 982 -0.8
Manufacturing............................ 335.6 11,990.0 1.5 1,108 -1.7
Trade, transportation, and utilities..... 1,889.4 25,186.9 1.3 772 -0.9
Information.............................. 143.6 2,661.8 -0.4 1,540 1.3
Financial activities..................... 811.0 7,519.8 1.1 1,314 -0.7
Professional and business services....... 1,601.6 18,046.0 2.9 1,146 -0.2
Education and health services............ 935.4 19,438.8 1.7 867 -1.7
Leisure and hospitality.................. 773.0 14,012.3 2.9 381 -1.8
Other services........................... 1,273.7 4,548.6 2.9 571 -2.7
Government................................. 296.0 21,094.2 -0.5 954 -1.2
Los Angeles, CA.............................. 412.7 3,983.5 2.1 1,002 -1.7
Private industry........................... 407.0 3,457.5 2.2 976 -1.7
Natural resources and mining............. 0.4 9.6 0.3 2,194 -4.4
Construction............................. 12.1 110.3 1.6 1,044 0.0
Manufacturing............................ 12.5 366.3 0.1 1,128 1.8
Trade, transportation, and utilities..... 50.9 754.3 1.4 822 -0.8
Information.............................. 8.3 190.4 -0.7 1,734 1.4
Financial activities..................... 21.9 211.1 1.7 1,460 -0.8
Professional and business services....... 42.1 573.7 3.6 1,208 -3.8
Education and health services............ 29.6 529.5 1.8 954 -3.1
Leisure and hospitality.................. 27.4 419.1 3.8 546 -4.4
Other services........................... 176.6 274.2 2.5 433 -2.5
Government................................. 5.7 525.9 1.2 1,180 -1.3
Cook, IL..................................... 149.3 2,424.6 1.0 1,032 -1.5
Private industry........................... 148.0 2,128.2 1.2 1,021 -1.7
Natural resources and mining............. 0.1 0.9 -8.7 1,012 1.3
Construction............................. 12.4 65.4 -3.5 1,291 0.1
Manufacturing............................ 6.6 194.3 0.3 1,075 -1.6
Trade, transportation, and utilities..... 29.1 441.8 0.5 837 0.4
Information.............................. 2.7 53.7 -0.7 1,513 -1.6
Financial activities..................... 15.6 184.2 -0.6 1,705 -2.1
Professional and business services....... 31.5 430.7 2.8 1,278 -2.0
Education and health services............ 15.8 411.2 1.8 902 -2.6
Leisure and hospitality.................. 13.3 246.4 2.2 474 -1.7
Other services........................... 16.5 96.1 0.4 784 0.0
Government................................. 1.4 296.5 -0.3 1,114 0.2
New York, NY................................. 123.7 2,385.9 2.2 1,626 -1.3
Private industry........................... 123.4 1,951.2 2.8 1,737 -1.8
Natural resources and mining............. 0.0 0.2 7.9 1,428 -6.7
Construction............................. 2.1 32.0 2.9 1,627 -1.2
Manufacturing............................ 2.4 26.6 0.7 1,104 -5.6
Trade, transportation, and utilities..... 20.8 250.7 3.0 1,226 3.6
Information.............................. 4.4 143.5 3.6 2,153 2.0
Financial activities..................... 18.8 351.9 -1.1 3,020 -2.6
Professional and business services....... 25.5 488.7 3.5 1,951 -2.3
Education and health services............ 9.3 305.4 1.9 1,211 0.7
Leisure and hospitality.................. 13.0 251.6 5.1 769 -0.1
Other services........................... 19.1 92.2 3.2 996 -0.3
Government................................. 0.3 434.7 0.0 1,126 0.3
Harris, TX................................... 103.7 2,128.2 3.8 1,154 -0.3
Private industry........................... 103.1 1,878.9 4.6 1,169 -0.3
Natural resources and mining............. 1.7 89.4 8.3 2,869 -4.7
Construction............................. 6.4 142.2 5.0 1,143 0.4
Manufacturing............................ 4.5 191.1 6.3 1,429 0.5
Trade, transportation, and utilities..... 23.4 442.0 3.4 1,028 0.2
Information.............................. 1.3 27.9 -1.5 1,378 2.7
Financial activities..................... 10.6 114.1 1.3 1,447 2.9
Professional and business services....... 20.7 360.7 5.6 1,354 -0.8
Education and health services............ 11.8 253.9 3.8 936 -1.8
Leisure and hospitality.................. 8.5 193.6 5.6 401 -2.9
Other services........................... 13.7 63.1 2.7 656 -0.5
Government................................. 0.6 249.3 -1.3 1,042 -0.6
Maricopa, AZ................................. 96.1 1,674.5 2.4 886 -2.1
Private industry........................... 95.4 1,466.5 2.7 879 -2.0
Natural resources and mining............. 0.5 6.8 3.4 901 2.0
Construction............................. 7.9 89.1 5.6 937 -0.1
Manufacturing............................ 3.2 113.6 2.9 1,278 -3.8
Trade, transportation, and utilities..... 21.5 339.1 1.6 829 -2.0
Information.............................. 1.6 28.0 1.7 1,138 -2.4
Financial activities..................... 10.9 142.4 2.8 1,110 1.2
Professional and business services....... 22.3 273.0 2.9 931 -1.4
Education and health services............ 10.6 248.2 2.2 899 -4.4
Leisure and hospitality.................. 7.3 176.1 2.5 426 -1.8
Other services........................... 6.6 46.0 -1.1 604 -0.3
Government................................. 0.7 208.0 0.6 940 -3.0
Dallas, TX................................... 69.4 1,478.5 2.7 1,085 -1.3
Private industry........................... 68.9 1,314.8 3.1 1,090 -1.3
Natural resources and mining............. 0.6 10.0 16.1 3,171 -3.0
Construction............................. 3.9 70.8 3.6 1,019 -1.2
Manufacturing............................ 2.8 112.4 0.4 1,229 0.2
Trade, transportation, and utilities..... 15.1 295.3 2.9 1,011 -1.2
Information.............................. 1.5 46.8 2.8 1,635 -1.6
Financial activities..................... 8.6 143.1 2.2 1,409 -1.4
Professional and business services....... 15.2 287.5 4.6 1,198 -2.4
Education and health services............ 7.6 174.0 2.5 1,011 -0.1
Leisure and hospitality.................. 5.9 134.2 4.0 492 -4.1
Other services........................... 7.3 40.0 -1.5 675 -0.4
Government................................. 0.5 163.7 -0.5 1,050 -1.1
Orange, CA................................... 102.8 1,407.6 2.1 1,024 -1.4
Private industry........................... 101.5 1,276.7 2.4 1,013 -1.2
Natural resources and mining............. 0.2 3.0 -10.3 712 -0.7
Construction............................. 6.0 73.6 3.3 1,155 1.8
Manufacturing............................ 4.8 158.2 0.2 1,275 -4.0
Trade, transportation, and utilities..... 16.1 246.3 1.0 942 -2.4
Information.............................. 1.2 23.9 -1.0 1,629 3.9
Financial activities..................... 9.5 108.8 2.8 1,554 1.1
Professional and business services....... 18.7 258.4 3.4 1,133 -1.1
Education and health services............ 10.6 162.2 1.5 932 -3.7
Leisure and hospitality.................. 7.3 184.2 3.8 469 6.8
Other services........................... 19.0 51.6 1.9 532 0.0
Government................................. 1.4 131.0 -0.6 1,136 -3.4
San Diego, CA................................ 101.0 1,283.3 1.8 993 -2.0
Private industry........................... 99.6 1,068.5 2.3 960 -1.2
Natural resources and mining............. 0.7 10.4 7.4 599 -4.9
Construction............................. 5.8 57.3 1.8 1,033 -4.5
Manufacturing............................ 2.9 93.9 -0.2 1,495 7.4
Trade, transportation, and utilities..... 13.5 206.0 0.9 789 -0.1
Information.............................. 1.1 24.6 0.6 1,573 -2.7
Financial activities..................... 8.4 70.3 2.8 1,202 2.2
Professional and business services....... 16.3 216.7 2.4 1,286 -1.7
Education and health services............ 8.7 155.6 1.3 947 -4.7
Leisure and hospitality.................. 7.2 164.7 3.4 436 -2.5
Other services........................... 27.9 63.5 5.4 506 -10.0
Government................................. 1.4 214.8 -0.4 1,168 -4.3
King, WA..................................... 83.2 1,171.9 2.4 1,354 2.3
Private industry........................... 82.7 1,018.7 2.8 1,381 2.5
Natural resources and mining............. 0.4 3.0 5.5 1,372 6.8
Construction............................. 5.3 51.5 5.9 1,151 -2.5
Manufacturing............................ 2.2 104.3 4.2 1,468 -2.5
Trade, transportation, and utilities..... 14.4 215.4 3.3 1,041 3.0
Information.............................. 1.8 81.0 0.1 4,549 9.0
Financial activities..................... 6.2 63.6 1.3 1,437 4.1
Professional and business services....... 13.9 192.6 4.2 1,475 2.5
Education and health services............ 7.3 137.3 1.6 959 -3.0
Leisure and hospitality.................. 6.4 116.6 2.2 489 1.2
Other services........................... 24.8 53.3 0.3 604 0.2
Government................................. 0.5 153.2 0.2 1,174 0.3
Miami-Dade, FL............................... 89.6 990.7 2.0 857 -1.7
Private industry........................... 89.2 852.2 2.6 840 -1.8
Natural resources and mining............. 0.5 7.5 1.8 552 3.2
Construction............................. 5.0 30.8 1.0 835 -4.4
Manufacturing............................ 2.6 35.6 -1.4 808 -7.0
Trade, transportation, and utilities..... 26.0 254.9 2.1 784 -0.9
Information.............................. 1.5 17.2 0.3 1,322 -2.8
Financial activities..................... 9.2 67.5 3.3 1,232 -3.4
Professional and business services....... 18.7 126.9 2.5 1,021 -1.3
Education and health services............ 9.9 157.9 1.9 879 -2.4
Leisure and hospitality.................. 6.8 117.9 5.4 537 4.1
Other services........................... 7.9 34.7 2.4 543 -1.8
Government................................. 0.4 138.4 -1.7 966 -1.2
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs.
(2) Data are preliminary. Counties selected are based on 2011 annual average employment.
(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.
Table 3. Covered(1) establishments, employment, and wages by state,
third quarter 2012(2)
Employment Average weekly
wage(3)
Establishments,
third quarter
State 2012 Percent Percent
(thousands) September change, Third change,
2012 September quarter third
(thousands) 2011-12 2012 quarter
2011-12
United States(4)......... 9,165.4 132,624.7 1.6 $906 -1.1
Alabama.................. 116.1 1,833.5 0.6 784 -2.4
Alaska................... 22.0 343.6 0.6 961 -0.2
Arizona.................. 148.5 2,437.5 2.2 846 -2.0
Arkansas................. 85.8 1,156.7 0.3 708 -1.0
California............... 1,328.5 15,109.1 2.8 1,036 -1.2
Colorado................. 174.4 2,284.6 2.2 936 -1.3
Connecticut.............. 111.6 1,638.9 0.8 1,087 -2.8
Delaware................. 27.8 407.3 0.1 925 -2.5
District of Columbia..... 36.1 714.9 0.6 1,514 -0.7
Florida.................. 611.5 7,307.9 1.9 800 -1.4
Georgia.................. 271.2 3,841.2 1.1 854 -1.5
Hawaii................... 38.5 605.5 1.7 827 -1.0
Idaho.................... 53.3 630.4 1.1 687 -1.4
Illinois................. 393.5 5,688.6 1.1 945 -1.4
Indiana.................. 160.4 2,849.9 1.8 772 -1.7
Iowa..................... 95.4 1,486.7 1.1 756 -0.5
Kansas................... 84.7 1,325.5 1.0 761 -1.4
Kentucky................. 111.3 1,779.5 1.2 751 -1.7
Louisiana................ 129.1 1,864.3 0.3 805 -1.8
Maine.................... 49.6 597.0 0.2 722 -1.6
Maryland................. 167.5 2,533.3 1.4 1,007 -1.6
Massachusetts............ 221.2 3,271.6 1.2 1,102 -1.2
Michigan................. 239.5 3,984.2 1.5 862 -1.5
Minnesota................ 170.2 2,675.4 1.1 915 0.0
Mississippi.............. 68.7 1,089.4 0.6 672 -1.2
Missouri................. 178.2 2,628.8 0.7 793 -1.2
Montana.................. 42.7 441.6 1.8 689 0.3
Nebraska................. 67.9 924.4 2.0 742 -0.5
Nevada................... 73.1 1,140.1 1.5 820 -3.0
New Hampshire............ 49.2 620.6 1.1 874 -3.1
New Jersey............... 260.9 3,811.2 1.1 1,053 -1.8
New Mexico............... 55.5 788.7 0.0 761 -2.3
New York................. 608.8 8,616.8 1.2 1,088 -1.1
North Carolina........... 258.8 3,934.1 1.6 806 -0.2
North Dakota............. 29.7 422.2 7.8 872 6.3
Ohio..................... 288.0 5,073.0 1.1 828 -0.7
Oklahoma................. 104.7 1,545.6 1.3 779 -0.5
Oregon................... 134.2 1,667.3 1.2 834 0.0
Pennsylvania............. 353.0 5,598.4 0.6 899 -1.3
Rhode Island............. 35.5 460.5 0.8 855 -1.9
South Carolina........... 112.7 1,814.7 1.3 738 -1.1
South Dakota............. 31.4 405.3 1.6 683 -0.1
Tennessee................ 141.8 2,674.3 1.7 814 -0.6
Texas.................... 596.1 10,773.4 2.7 930 -0.2
Utah..................... 86.0 1,231.0 3.3 766 -1.8
Vermont.................. 24.5 302.0 1.2 763 -1.8
Virginia................. 241.9 3,631.1 0.9 960 -1.5
Washington............... 237.3 2,944.6 1.5 1,024 1.3
West Virginia............ 49.6 715.4 0.5 724 -2.4
Wisconsin................ 161.6 2,718.7 0.7 770 -2.7
Wyoming.................. 25.6 284.7 0.0 828 -0.5
Puerto Rico.............. 48.8 933.4 2.1 506 0.0
Virgin Islands........... 3.5 38.6 -9.8 711 -1.1
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs.
(2) Data are preliminary.
(3) Average weekly wages were calculated using unrounded data.
(4) Totals for the United States do not include data for Puerto Rico or the
Virgin Islands.
United States Department of Labor
