For release 10:00 a.m. (EDT), Tuesday, October 19, 2010 USDL-10-1449
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
County Employment and Wages
First Quarter 2010
From March 2009 to March 2010, employment declined in 296 of the 326
largest U.S. counties according to preliminary data, the U.S. Bureau
of Labor Statistics reported today. Collier, Fla., posted the largest
percentage decline, with a loss of 6.0 percent over the year,
compared with a national job decrease of 2.1 percent. Forty-five
percent of the employment decline in Collier occurred in natural
resources and mining, which lost 3,282 jobs over the year (-41.2
percent). Elkhart, Ind., experienced the largest over-the-year
percentage increase in employment among the largest counties in the
U.S. with a gain of 5.7 percent.
The U.S. average weekly wage increased over the year by 0.8 percent
to $889 in the first quarter of 2010. Among the large counties in
the U.S., New York, N.Y., had the largest over-the-year increase in
average weekly wages in the first quarter of 2010, with a gain of
11.9 percent. Within New York, financial activities had the largest
over-the-year increase in average weekly wages with a gain of 22.7
percent. San Mateo, Calif., experienced the largest decline in
average weekly wages with a loss of 17.7 percent over the year.
County employment and wage data are compiled under the Quarterly
Census of Employment and Wages (QCEW) program.
Table A. Top 10 large counties ranked by March 2010 employment, March 2009-10 employment
decrease, and March 2009-10 percent decrease in employment
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Employment in large counties
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March 2010 employment | Decrease in employment, | Percent decrease in employment,
(thousands) | March 2009-10 | March 2009-10
| (thousands) |
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| |
United States 126,281.7| United States -2,646.7| United States -2.1
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| |
Los Angeles, Calif. 3,863.3| Los Angeles, Calif. -133.9| Collier, Fla. -6.0
Cook, Ill. 2,311.0| Cook, Ill. -69.1| Sedgwick, Kan. -5.8
New York, N.Y. 2,255.5| Maricopa, Ariz. -64.0| Marion, Fla. -5.2
Harris, Texas 1,970.8| Orange, Calif. -58.2| Clark, Nev. -5.1
Maricopa, Ariz. 1,606.6| Harris, Texas -49.8| San Bernardino, Calif. -5.0
Dallas, Texas 1,392.8| Clark, Nev. -42.5| McHenry, Ill. -4.8
Orange, Calif. 1,342.8| New York, N.Y. -38.2| Contra Costa, Calif. -4.7
San Diego, Calif. 1,229.8| King, Wash. -35.5| Seminole, Fla. -4.6
King, Wash. 1,098.9| San Diego, Calif. -35.2| Gloucester, N.J. -4.6
Miami-Dade, Fla. 947.4| San Bernardino, Calif. -30.9| Tulsa, Okla. -4.6
| |
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Large County Employment
In March 2010, national employment, as measured by the QCEW program,
was 126.3 million, down by 2.1 percent from March 2009. The 326 U.S.
counties with 75,000 or more employees accounted for 70.9 percent of
total U.S. employment and 77.5 percent of total wages. These 326
counties had a net job decline of 2,075,200 over the year, accounting
for 78.4 percent of the overall U.S. employment decrease.
Collier, Fla., had the largest percentage decline in employment among
the largest U.S. counties. The top five counties with the greatest
employment level declines (Los Angeles, Calif.; Cook, Ill.; Maricopa,
Ariz.; Orange, Calif.; and Harris, Texas) had a combined over-the-
year loss of 375,000, or 14.2 percent of the employment decline for
the U.S. as a whole. (See table A.)
Employment rose in 22 of the large counties from March 2009 to March
2010. Elkhart, Ind., had the largest over-the-year percentage
increase in employment (5.7 percent) in the nation. Within Elkhart,
manufacturing was the largest contributor to the increase in
employment. Benton, Wash., experienced the second largest employment
increase, followed by Arlington, Va.; Kings, N.Y.; Washington, D.C.;
and Passaic, N.J.
Table B. Top 10 large counties ranked by first quarter 2010 average weekly wages, first quarter 2009-10
increase in average weekly wages, and first quarter 2009-10 percent increase in average weekly wages
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Average weekly wage in large counties
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Average weekly wage, | Increase in average weekly | Percent increase in average
first quarter 2010 | wage, first quarter 2009-10 | weekly wage, first
| | quarter 2009-10
--------------------------------------------------------------------------------------------------------
| |
United States $889| United States $7| United States 0.8
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| |
New York, N.Y. $2,404| New York, N.Y. $255| New York, N.Y. 11.9
Fairfield, Conn. 1,787| Hudson, N.J. 147| Hudson, N.J. 10.6
Somerset, N.J. 1,745| Santa Clara, Calif. 133| Santa Clara, Calif. 8.7
Santa Clara, Calif. 1,655| Mecklenburg, N.C. 89| Mecklenburg, N.C. 8.4
San Francisco, Calif. 1,594| San Francisco, Calif. 82| San Francisco, Calif. 5.4
Suffolk, Mass. 1,557| Arlington, Va. 53| Winnebago, Wis. 4.8
Hudson, N.J. 1,538| Fairfield, Conn. 51| Williamson, Tenn. 4.6
Arlington, Va. 1,520| Mercer, N.J. 50| Hamilton, Tenn. 4.4
Washington, D.C. 1,505| Contra Costa, Calif. 46| Mercer, N.J. 4.3
San Mateo, Calif. 1,469| Durham, N.C. 45| Washington, Ore. 4.3
| |
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Large County Average Weekly Wages
Average weekly wages for the nation increased by 0.8 percent over the
year in the first quarter of 2010. Among the 326 largest counties,
147 had over-the-year increases in average weekly wages. New York,
N.Y. had the largest wage gain among the largest U.S. counties. (See
table B.) Of the 326 largest counties, 165 experienced declines in
average weekly wages.
San Mateo, Calif., led the nation in average weekly wage decline with
a loss of 17.7 percent over the year. In the county, manufacturing
had the largest over-the-year decline in average weekly wages (-58.2
percent) due to a large payout related to an acquisition in first
quarter of 2009. Solano, Calif., had the second largest overall
decline among the counties, followed by Pulaski, Ark.; Peoria, Ill.;
and Stark, Ohio.
Ten Largest U.S. Counties
All of the 10 largest counties experienced over-the-year percent
declines in employment in March 2010. Orange, Calif., experienced the
largest decline in employment among the 10 largest counties with a
4.2 percent decrease. Within Orange, every private industry group
except education and health services experienced an employment
decline, with construction experiencing the largest decline (-15.2
percent). (See table 2.) New York, N.Y., experienced the smallest
decline in employment among the 10 largest counties.
Five of the 10 largest U.S. counties saw an over-the-year increase in
average weekly wages. New York, N.Y., experienced the largest
increase in average weekly wages among the 10 largest counties and
the nation with a gain of 11.9 percent. Miami-Dade, Fla., had the
largest wage decline among the 10 largest counties.
For More Information
The tables included in this release contain data for the nation and
for the 326 U.S. counties with annual average employment levels of
75,000 or more in 2009. March 2010 employment and 2010 first 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 9.0 million employer reports cover 126.3 million full-
and part- time workers. For additional information about the
quarterly employment and wages data, please read the Technical Note.
Data for the first quarter of 2010 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 second quarter 2010 is
scheduled to be released on Tuesday, January 11, 2011.
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| |
| QCEW Beta Products |
| |
| The QCEW State and County Map Application was released on June 30, |
| 2010 (http://beta.bls.gov/maps). This new feature of the BLS website |
| provides users with supersector industry employment and wages at the |
| national, state, and county levels. Data are presented in map, |
| tabular, and downloadable formats. |
| |
| QCEW flat files are available in a new format as of October 19, |
| 2010 on the BLS website at ftp://ftp.bls.gov/public/cew/beta. The |
| new format was developed to be easier to use than the existing |
| format. Files will be available in both formats for approximately |
| one year. Please direct comments on the new file format to |
| QCEWInfo@bls.gov. For more information, see the readme file |
| available on the ftp directory listed above. |
| |
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| |
| Changes for the 2010 County Employment and Wages News Release |
| |
| Effective with this release, the "Covered establishments, employment,|
| and wages in the largest county by state" table (formerly Table 3), |
| along with the associated text on the largest county by state, has |
| been removed. |
| |
| Counties with annual average employment of 75,000 or more in 2009 |
| are included in this release and will be included in future 2010 |
| releases. For 2010 data, two counties have been added to the |
| publication tables: St. Tammany Parish, La., and Benton, Wash. Ten |
| Counties will be excluded from 2010 releases: Shelby, Ala.; Butte, |
| Calif.; Tippecanoe, Ind.; Johnson, Iowa; Saratoga, N.Y.; Trumbull, |
| Ohio; Warren, Ohio; Kent, R.I.; Gregg, Texas; and Racine, Wis. |
| |
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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 2007 North American Industry Classification System. Data
for 2010 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 327 counties presented
in this release were derived using 2009 preliminary annual averages of employment.
For 2010 data, two counties have been added to the publication tables: St. Tammany
Parish, La., and Benton, Wash. These counties will be included in all 2010 quarter-
ly releases. Ten counties, Shelby, Ala.; Butte, Calif.; Tippecanoe, Ind.; Johnson,
Iowa; Saratoga, N.Y.; Trumbull, Ohio; Warren, Ohio; Kent, R.I.; Gregg, Texas; and
Racine, Wis., which were published in the 2009 releases, will be excluded from this
and future 2010 releases because their 2009 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- | 400,000 establish-
| submitted by 9.0 | ministrative records| ments
| million establish- | submitted by 6.8 |
| ments in first | million private-sec-|
| quarter of 2010 | 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 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 9.0 million employer reports of employment and wages
submitted by states to the BLS in 2009. 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 2009, UI and UCFE programs covered workers in 128.6 million jobs. The estimated
123.6 million workers in these jobs (after adjustment for multiple jobholders)
represented 95.1 percent of civilian wage and salary employment. Covered workers
received $5.859 trillion in pay, representing 93.4 percent of the wage and salary
component of personal income and 41.5 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 2009 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
An annual bulletin, Employment and Wages, features comprehensive information by de-
tailed industry on establishments, employment, and wages for the nation and all
states. The 2008 edition of this bulletin contains selected data produced by Busi-
ness Employment Dynamics (BED) on job gains and losses, as well as selected data
from the first quarter 2009 version of this news release. Tables and additional
content from the 2008 Employment and Wages Annual Bulletin are now available online
at http://www.bls.gov/cew/cewbultn08.htm. These tables present final 2008 annual
averages. The tables are included on the CD which accompanies the hardcopy version
of the Annual Bulletin. Employment and Wages Annual Averages, 2008 is available
for sale as a chartbook from the United States Government Printing Office, Superin-
tendent 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 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 327 largest counties,
first quarter 2010(2)
Employment Average weekly wage(4)
Establishments,
County(3) first quarter Percent Ranking Percent Ranking
2010 March change, by Average change, by
(thousands) 2010 March percent weekly first percent
(thousands) 2009-10(5) change wage quarter change
2009-10(5)
United States(6)......... 9,043.6 126,281.7 -2.1 - $889 0.8 -
Jefferson, AL............ 18.0 331.3 -2.6 210 880 -1.2 228
Madison, AL.............. 8.8 177.1 -0.7 45 938 0.6 117
Mobile, AL............... 9.9 164.0 -2.5 202 707 -0.8 204
Montgomery, AL........... 6.4 129.7 -1.4 92 741 1.9 47
Tuscaloosa, AL........... 4.3 82.2 -1.2 76 746 2.1 42
Anchorage Borough, AK.... 8.1 144.8 -0.2 29 933 0.0 148
Maricopa, AZ............. 95.1 1,606.6 -3.8 289 848 -0.8 204
Pima, AZ................. 19.6 345.5 -3.0 242 739 -0.9 214
Benton, AR............... 5.5 91.3 -2.1 161 1,038 1.8 54
Pulaski, AR.............. 15.1 240.7 -2.0 153 779 -11.3 318
Washington, AR........... 5.6 89.4 1.1 7 691 0.7 105
Alameda, CA.............. 54.3 629.9 -3.4 269 1,142 2.2 36
Contra Costa, CA......... 29.8 310.3 -4.7 313 1,140 4.2 11
Fresno, CA............... 30.7 316.1 -3.6 282 686 -0.1 156
Kern, CA................. 18.2 253.1 -2.1 161 760 -0.7 196
Los Angeles, CA.......... 431.4 3,863.3 -3.4 269 978 1.0 93
Marin, CA................ 11.6 99.2 -3.2 257 1,040 -0.7 196
Monterey, CA............. 12.8 148.1 -2.2 174 797 1.0 93
Orange, CA............... 101.6 1,342.8 -4.2 303 1,001 1.2 85
Placer, CA............... 10.7 124.4 -3.1 248 843 -0.6 188
Riverside, CA............ 48.2 553.4 -4.4 308 728 -1.2 228
Sacramento, CA........... 54.4 583.8 -3.5 275 974 0.5 124
San Bernardino, CA....... 50.5 588.9 -5.0 315 732 0.0 148
San Diego, CA............ 98.5 1,229.8 -2.8 224 930 -0.6 188
San Francisco, CA........ 52.9 537.7 -3.1 248 1,594 5.4 5
San Joaquin, CA.......... 17.6 200.8 -3.7 286 721 0.1 141
San Luis Obispo, CA...... 9.6 97.6 -4.0 296 729 -2.8 291
San Mateo, CA............ 23.8 313.8 -3.2 257 1,469 -17.7 320
Santa Barbara, CA........ 14.3 171.1 -3.5 275 830 0.5 124
Santa Clara, CA.......... 60.9 832.2 -3.4 269 1,655 8.7 3
Santa Cruz, CA........... 9.1 85.6 -4.1 300 791 -2.8 291
Solano, CA............... 10.2 119.9 -1.0 57 888 -12.0 319
Sonoma, CA............... 18.6 171.2 -3.8 289 820 1.5 73
Stanislaus, CA........... 15.1 156.5 -2.0 153 735 2.2 36
Tulare, CA............... 9.4 133.2 -2.8 224 604 0.3 135
Ventura, CA.............. 23.7 295.2 -3.8 289 923 1.7 60
Yolo, CA................. 6.0 92.9 -4.0 296 820 1.5 73
Adams, CO................ 9.0 145.2 -3.2 257 771 -3.6 306
Arapahoe, CO............. 18.9 266.6 -1.6 112 1,088 0.6 117
Boulder, CO.............. 12.8 150.2 -2.1 161 1,011 -0.5 182
Denver, CO............... 25.2 413.6 -2.1 161 1,158 1.8 54
Douglas, CO.............. 9.4 87.5 -2.1 161 1,003 1.2 85
El Paso, CO.............. 16.8 229.1 -2.2 174 790 -0.8 204
Jefferson, CO............ 18.0 200.0 -2.2 174 899 0.7 105
Larimer, CO.............. 10.0 123.0 -1.6 112 755 -1.0 219
Weld, CO................. 5.8 77.7 -3.7 286 722 -0.1 156
Fairfield, CT............ 32.7 387.7 -3.3 262 1,787 2.9 20
Hartford, CT............. 25.2 475.0 -2.8 224 1,162 1.8 54
New Haven, CT............ 22.4 341.7 -2.6 210 911 -0.2 165
New London, CT........... 6.9 121.7 -3.4 269 918 -2.3 282
New Castle, DE........... 17.7 257.4 -4.1 300 1,123 0.8 100
Washington, DC........... 34.3 685.2 1.2 5 1,505 2.8 25
Alachua, FL.............. 6.7 114.9 -2.3 186 709 -4.1 311
Brevard, FL.............. 14.6 188.7 -2.1 161 793 0.4 127
Broward, FL.............. 63.0 680.6 -3.1 248 807 -0.7 196
Collier, FL.............. 11.8 114.8 -6.0 319 739 1.9 47
Duval, FL................ 26.7 430.4 -2.9 234 861 1.4 76
Escambia, FL............. 7.9 120.1 -0.1 24 659 -2.7 290
Hillsborough, FL......... 37.0 570.3 -3.1 248 842 -1.9 266
Lake, FL................. 7.3 79.2 -4.0 296 572 -1.0 219
Lee, FL.................. 18.7 197.7 -3.1 248 682 -1.6 252
Leon, FL................. 8.2 138.4 -1.3 83 713 -1.7 256
Manatee, FL.............. 9.2 110.7 -1.6 112 632 -2.6 289
Marion, FL............... 8.0 89.7 -5.2 317 600 -1.2 228
Miami-Dade, FL........... 84.8 947.4 -2.0 153 845 -1.3 237
Okaloosa, FL............. 6.0 75.6 -1.8 129 706 1.3 79
Orange, FL............... 35.1 641.7 -2.2 174 774 -0.9 214
Palm Beach, FL........... 49.0 494.6 -3.1 248 855 1.4 76
Pasco, FL................ 9.8 95.9 -2.5 202 579 -2.2 279
Pinellas, FL............. 30.5 390.7 -1.8 129 738 -0.3 169
Polk, FL................. 12.3 192.0 -3.9 293 643 -1.4 242
Sarasota, FL............. 14.6 133.9 -4.0 296 706 -1.8 261
Seminole, FL............. 13.9 154.7 -4.6 310 714 -3.1 298
Volusia, FL.............. 13.4 152.3 -2.9 234 614 1.3 79
Bibb, GA................. 4.6 78.9 -2.7 218 682 -0.7 196
Chatham, GA.............. 7.6 127.6 -1.8 129 726 -1.5 246
Clayton, GA.............. 4.3 101.6 (7) - 756 (7) -
Cobb, GA................. 20.5 283.4 -3.1 248 923 -1.1 225
De Kalb, GA.............. 17.4 274.8 -2.6 210 943 0.0 148
Fulton, GA............... 39.2 696.4 -2.9 234 1,262 2.9 20
Gwinnett, GA............. 23.3 292.3 -2.8 224 844 -1.2 228
Muscogee, GA............. 4.7 91.7 -1.3 83 705 1.9 47
Richmond, GA............. 4.7 98.1 -0.9 51 718 -1.6 252
Honolulu, HI............. 24.9 429.6 -2.3 186 797 -0.4 176
Ada, ID.................. 14.3 189.4 -1.7 121 739 -1.6 252
Champaign, IL............ 4.2 87.0 -1.3 83 732 0.4 127
Cook, IL................. 142.9 2,311.0 -2.9 234 1,083 -0.1 156
Du Page, IL.............. 36.3 535.6 -2.9 234 1,043 1.3 79
Kane, IL................. 13.0 186.7 -4.2 303 750 -0.4 176
Lake, IL................. 21.4 300.6 -3.4 269 1,154 3.2 18
McHenry, IL.............. 8.6 90.1 -4.8 314 699 -0.9 214
McLean, IL............... 3.7 84.2 -0.8 47 885 -1.1 225
Madison, IL.............. 6.0 91.8 -0.9 51 724 2.1 42
Peoria, IL............... 4.7 97.3 -3.5 275 794 -11.0 317
Rock Island, IL.......... 3.5 73.3 -3.0 242 868 -2.1 275
St. Clair, IL............ 5.5 92.7 -1.9 144 697 -0.3 169
Sangamon, IL............. 5.3 124.7 -1.0 57 877 1.7 60
Will, IL................. 14.4 187.0 -2.6 210 754 0.4 127
Winnebago, IL............ 6.9 122.3 -3.5 275 714 -3.8 309
Allen, IN................ 9.0 166.2 -1.1 67 718 0.1 141
Elkhart, IN.............. 4.9 97.6 5.7 1 664 3.6 14
Hamilton, IN............. 8.0 104.7 -3.5 275 866 2.9 20
Lake, IN................. 10.4 179.8 -2.4 190 746 -1.5 246
Marion, IN............... 24.0 540.4 -1.1 67 951 1.8 54
St. Joseph, IN........... 6.1 113.0 -2.2 174 696 -2.5 285
Vanderburgh, IN.......... 4.8 103.6 0.1 19 690 -3.0 296
Linn, IA................. 6.3 121.6 -1.9 144 813 -1.2 228
Polk, IA................. 14.6 262.3 -1.5 98 898 0.7 105
Scott, IA................ 5.2 83.2 -1.8 129 683 -1.7 256
Johnson, KS.............. 20.9 291.9 -3.2 257 932 2.9 20
Sedgwick, KS............. 12.4 237.1 -5.8 318 762 -3.4 303
Shawnee, KS.............. 4.9 93.1 -1.2 76 725 -2.8 291
Wyandotte, KS............ 3.2 78.3 -0.6 42 787 1.7 60
Fayette, KY.............. 9.4 165.6 -1.8 129 767 -0.5 182
Jefferson, KY............ 22.2 402.6 -1.3 83 845 0.2 138
Caddo, LA................ 7.6 120.1 -1.5 98 695 -0.4 176
Calcasieu, LA............ 5.0 83.1 -3.6 282 728 -4.2 312
East Baton Rouge, LA..... 14.9 256.6 -2.3 186 802 -3.5 304
Jefferson, LA............ 14.3 191.7 -1.8 129 800 0.1 141
Lafayette, LA............ 9.3 129.2 -3.6 282 808 -2.2 279
Orleans, LA.............. 11.0 171.3 1.0 8 957 -0.3 169
St. Tammany, LA.......... 7.5 74.6 -0.8 47 679 -2.9 295
Cumberland, ME........... 12.1 163.7 -1.5 98 803 0.8 100
Anne Arundel, MD......... 14.3 222.6 -0.8 47 944 1.7 60
Baltimore, MD............ 21.2 359.5 -1.7 121 899 0.9 98
Frederick, MD............ 5.9 89.9 -2.4 190 853 -3.5 304
Harford, MD.............. 5.6 79.6 0.0 23 809 -0.6 188
Howard, MD............... 8.7 142.5 -0.5 37 1,068 2.6 28
Montgomery, MD........... 32.2 436.3 -1.6 112 1,260 2.4 31
Prince Georges, MD....... 15.5 295.4 -3.5 275 918 -0.1 156
Baltimore City, MD....... 13.4 319.3 -2.7 218 1,049 3.1 19
Barnstable, MA........... 9.1 77.9 -1.0 57 726 -1.9 266
Bristol, MA.............. 15.7 201.3 -1.9 144 749 0.1 141
Essex, MA................ 21.0 284.9 -0.6 42 903 1.0 93
Hampden, MA.............. 14.8 189.0 -1.4 92 803 1.4 76
Middlesex, MA............ 48.0 790.0 -1.1 67 1,274 0.2 138
Norfolk, MA.............. 23.8 306.1 -1.0 57 1,026 0.8 100
Plymouth, MA............. 13.8 164.7 -1.8 129 780 -0.9 214
Suffolk, MA.............. 22.3 565.0 -1.1 67 1,557 -0.9 214
Worcester, MA............ 20.9 303.3 -1.5 98 849 -1.2 228
Genesee, MI.............. 7.6 124.7 -3.0 242 691 -3.1 298
Ingham, MI............... 6.6 150.5 -1.2 76 833 2.6 28
Kalamazoo, MI............ 5.5 105.2 -3.3 262 778 -0.5 182
Kent, MI................. 14.0 297.7 -1.5 98 769 -1.5 246
Macomb, MI............... 17.3 267.4 -1.9 144 847 -0.2 165
Oakland, MI.............. 38.0 595.9 -3.8 289 952 -2.4 284
Ottawa, MI............... 5.6 96.1 0.3 17 674 -3.3 302
Saginaw, MI.............. 4.3 77.2 -0.4 35 692 -1.0 219
Washtenaw, MI............ 8.1 183.7 0.1 19 915 -1.8 261
Wayne, MI................ 31.4 645.5 -3.9 293 922 -1.7 256
Anoka, MN................ 7.4 102.7 -3.3 262 773 -3.1 298
Dakota, MN............... 10.0 164.0 -1.3 83 867 1.2 85
Hennepin, MN............. 43.5 791.1 -1.4 92 1,106 -0.1 156
Olmsted, MN.............. 3.4 85.3 -2.8 224 937 0.5 124
Ramsey, MN............... 14.4 308.6 -2.4 190 1,031 1.9 47
St. Louis, MN............ 5.8 90.9 -1.1 67 680 -3.7 307
Stearns, MN.............. 4.3 75.2 -1.8 129 693 -0.6 188
Harrison, MS............. 4.5 82.4 -1.0 57 676 -0.1 156
Hinds, MS................ 6.2 122.9 -2.2 174 754 -0.4 176
Boone, MO................ 4.4 81.2 0.9 10 670 1.7 60
Clay, MO................. 5.0 88.6 -2.7 218 829 3.6 14
Greene, MO............... 8.0 147.9 -1.5 98 632 -2.0 272
Jackson, MO.............. 18.1 338.9 -3.6 282 878 -1.7 256
St. Charles, MO.......... 8.2 115.7 -3.3 262 733 1.9 47
St. Louis, MO............ 31.6 562.1 -3.3 262 938 -3.0 296
St. Louis City, MO....... 8.6 210.6 (7) - 978 -0.3 169
Yellowstone, MT.......... 5.8 74.5 -0.6 42 688 -1.3 237
Douglas, NE.............. 15.6 304.3 -1.7 121 827 -3.2 301
Lancaster, NE............ 8.0 150.8 -1.8 129 686 0.4 127
Clark, NV................ 48.8 793.0 -5.1 316 775 -4.8 314
Washoe, NV............... 14.1 180.7 -3.5 275 768 -2.3 282
Hillsborough, NH......... 11.9 181.7 -2.7 218 921 -0.5 182
Rockingham, NH........... 10.6 128.2 -0.1 24 815 -1.0 219
Atlantic, NJ............. 7.0 130.3 -2.4 190 752 0.7 105
Bergen, NJ............... 34.3 419.7 -2.2 174 1,119 1.0 93
Burlington, NJ........... 11.3 189.8 -3.3 262 931 1.7 60
Camden, NJ............... 12.9 194.0 -1.3 83 859 -1.2 228
Essex, NJ................ 21.4 339.8 -1.6 112 1,173 2.4 31
Gloucester, NJ........... 6.3 96.4 -4.6 310 760 -1.8 261
Hudson, NJ............... 14.0 228.0 -2.2 174 1,538 10.6 2
Mercer, NJ............... 11.2 222.5 -1.5 98 1,208 4.3 9
Middlesex, NJ............ 22.1 375.1 -1.6 112 1,146 0.4 127
Monmouth, NJ............. 20.7 239.5 -1.9 144 922 0.7 105
Morris, NJ............... 18.0 266.0 -2.9 234 1,421 2.0 45
Ocean, NJ................ 12.4 140.5 -0.5 37 725 0.7 105
Passaic, NJ.............. 12.4 168.8 1.2 5 889 -1.8 261
Somerset, NJ............. 10.2 163.7 -1.8 129 1,745 -0.6 188
Union, NJ................ 14.9 216.9 (7) - 1,177 (7) -
Bernalillo, NM........... 17.4 309.5 -2.1 161 760 -1.3 237
Albany, NY............... 9.9 217.1 -2.0 153 907 2.8 25
Bronx, NY................ 16.5 231.4 0.7 13 791 -1.5 246
Broome, NY............... 4.5 90.6 -2.4 190 672 -2.5 285
Dutchess, NY............. 8.1 110.3 -1.9 144 897 -0.7 196
Erie, NY................. 23.4 441.7 -0.5 37 757 -0.1 156
Kings, NY................ 48.6 483.9 1.4 4 718 -1.0 219
Monroe, NY............... 17.8 364.1 -1.3 83 820 -0.8 204
Nassau, NY............... 52.1 576.2 -1.5 98 985 2.0 45
New York, NY............. 118.3 2,255.5 -1.7 121 2,404 11.9 1
Oneida, NY............... 5.3 106.0 -0.9 51 679 0.4 127
Onondaga, NY............. 12.7 237.1 -2.2 174 795 -0.4 176
Orange, NY............... 9.9 125.7 -1.0 57 743 2.2 36
Queens, NY............... 44.3 485.1 -0.3 32 812 -1.0 219
Richmond, NY............. 8.8 90.9 -1.1 67 728 -0.3 169
Rockland, NY............. 9.8 110.0 -1.8 129 966 0.7 105
Suffolk, NY.............. 50.0 591.4 -1.5 98 929 0.8 100
Westchester, NY.......... 35.8 393.1 -2.3 186 1,319 (7) -
Buncombe, NC............. 7.8 108.3 -1.6 112 654 -0.2 165
Catawba, NC.............. 4.4 76.4 -2.4 190 643 2.9 20
Cumberland, NC........... 6.2 117.6 -0.7 45 672 2.4 31
Durham, NC............... 7.1 175.1 -4.1 300 1,272 3.7 13
Forsyth, NC.............. 8.9 172.1 -3.0 242 827 2.2 36
Guilford, NC............. 14.1 255.6 -2.5 202 767 1.5 73
Mecklenburg, NC.......... 31.9 532.1 -2.1 161 1,150 8.4 4
New Hanover, NC.......... 7.2 94.5 -2.6 210 714 1.1 90
Wake, NC................. 28.2 423.6 -1.9 144 902 2.7 27
Cass, ND................. 5.8 97.3 0.5 15 718 0.0 148
Butler, OH............... 7.3 135.3 -1.5 98 775 0.6 117
Cuyahoga, OH............. 36.0 673.1 -2.7 218 885 -0.8 204
Franklin, OH............. 29.0 638.1 -1.8 129 884 -1.1 225
Hamilton, OH............. 23.3 476.2 -2.8 224 953 0.4 127
Lake, OH................. 6.5 90.5 -4.3 305 747 3.8 12
Lorain, OH............... 6.1 88.9 -4.4 308 697 -2.0 272
Lucas, OH................ 10.4 194.1 -2.2 174 752 -2.5 285
Mahoning, OH............. 6.1 93.3 -2.4 190 609 -1.9 266
Montgomery, OH........... 12.3 236.5 -2.9 234 753 -2.8 291
Stark, OH................ 8.7 145.7 -3.7 286 641 -5.6 316
Summit, OH............... 14.4 248.7 -2.8 224 823 1.6 69
Oklahoma, OK............. 24.2 403.7 -2.8 224 800 1.1 90
Tulsa, OK................ 20.2 324.6 -4.6 310 788 -2.1 275
Clackamas, OR............ 12.5 134.6 -3.4 269 775 0.0 148
Jackson, OR.............. 6.5 73.9 -2.0 153 625 -0.5 182
Lane, OR................. 10.8 133.4 -1.7 121 650 -0.8 204
Marion, OR............... 9.3 129.2 -1.4 92 687 -0.4 176
Multnomah, OR............ 28.3 415.7 -2.1 161 874 0.0 148
Washington, OR........... 16.0 230.1 -2.0 153 1,048 4.3 9
Allegheny, PA............ 34.8 656.0 -1.2 76 951 0.1 141
Berks, PA................ 9.0 159.1 -1.1 67 750 -2.1 275
Bucks, PA................ 19.6 244.5 -1.8 129 831 -1.7 256
Butler, PA............... 4.8 76.8 -0.1 24 734 -0.3 169
Chester, PA.............. 14.9 231.4 -2.0 153 1,132 1.3 79
Cumberland, PA........... 6.0 118.5 -2.7 218 787 -1.3 237
Dauphin, PA.............. 7.4 173.0 -2.1 161 849 0.0 148
Delaware, PA............. 13.5 201.2 -1.0 57 965 2.4 31
Erie, PA................. 7.5 117.9 -3.0 242 654 -4.8 314
Lackawanna, PA........... 5.8 96.6 -2.0 153 648 0.6 117
Lancaster, PA............ 12.5 213.2 -2.2 174 702 -2.2 279
Lehigh, PA............... 8.7 166.9 -1.0 57 848 -1.2 228
Luzerne, PA.............. 7.7 134.6 -1.0 57 661 -1.3 237
Montgomery, PA........... 27.2 454.0 -2.6 210 1,174 1.2 85
Northampton, PA.......... 6.5 96.5 -0.4 35 755 -2.1 275
Philadelphia, PA......... 31.9 619.4 -0.9 51 1,035 -1.4 242
Washington, PA........... 5.4 76.5 -1.7 121 796 0.1 141
Westmoreland, PA......... 9.3 127.3 -2.5 202 676 -1.9 266
York, PA................. 9.0 165.5 -2.4 190 761 0.7 105
Providence, RI........... 17.4 262.3 -1.5 98 876 1.3 79
Charleston, SC........... 11.6 201.2 -1.4 92 737 -0.7 196
Greenville, SC........... 12.0 222.9 -1.2 76 732 0.0 148
Horry, SC................ 7.6 101.2 -2.1 161 519 -1.5 246
Lexington, SC............ 5.6 92.5 -2.8 224 624 -0.8 204
Richland, SC............. 9.1 202.8 -1.5 98 774 -1.8 261
Spartanburg, SC.......... 6.0 109.1 -2.5 202 748 -0.1 156
Minnehaha, SD............ 6.4 110.3 -2.4 190 713 -0.8 204
Davidson, TN............. 18.2 412.4 -1.5 98 901 2.6 28
Hamilton, TN............. 8.4 177.1 -1.7 121 785 4.4 8
Knox, TN................. 10.8 212.4 -2.1 161 725 1.1 90
Rutherford, TN........... 4.3 93.4 -0.2 29 761 3.4 17
Shelby, TN............... 19.2 462.1 -3.3 262 870 0.7 105
Williamson, TN........... 6.0 85.6 (7) - 1,002 4.6 7
Bell, TX................. 4.6 104.6 (7) - 708 (7) -
Bexar, TX................ 33.2 719.5 0.1 19 786 1.8 54
Brazoria, TX............. 4.8 85.0 -1.7 121 838 -1.4 242
Brazos, TX............... 3.8 87.2 0.5 15 640 -0.6 188
Cameron, TX.............. 6.4 124.1 0.9 10 531 0.6 117
Collin, TX............... 17.7 281.8 -0.3 32 1,017 -0.7 196
Dallas, TX............... 67.7 1,392.8 -1.9 144 1,093 0.7 105
Denton, TX............... 10.8 168.8 -0.1 24 746 -2.5 285
El Paso, TX.............. 13.5 269.7 1.0 8 608 0.8 100
Fort Bend, TX............ 8.9 129.2 -1.6 112 909 -4.6 313
Galveston, TX............ 5.2 93.4 (7) - 815 (7) -
Harris, TX............... 99.5 1,970.8 -2.5 202 1,168 2.2 36
Hidalgo, TX.............. 10.8 219.8 0.6 14 540 0.2 138
Jefferson, TX............ 5.9 118.8 -2.9 234 852 -1.2 228
Lubbock, TX.............. 6.9 121.6 -0.9 51 637 1.0 93
McLennan, TX............. 4.8 99.6 (7) - 708 1.7 60
Montgomery, TX........... 8.5 125.7 -1.3 83 799 0.4 127
Nueces, TX............... 7.9 153.1 -1.1 67 704 -3.7 307
Potter, TX............... 3.8 73.0 -2.4 190 731 (7) -
Smith, TX................ 5.3 90.5 -1.4 92 712 -1.4 242
Tarrant, TX.............. 37.3 740.9 -1.3 83 875 1.7 60
Travis, TX............... 29.7 565.3 0.1 19 972 2.1 42
Webb, TX................. 4.7 85.1 -1.5 98 561 1.6 69
Williamson, TX........... 7.4 120.0 -0.1 24 867 1.9 47
Davis, UT................ 7.0 97.2 -0.3 32 688 0.9 98
Salt Lake, UT............ 36.2 551.1 -1.8 129 827 0.6 117
Utah, UT................. 12.5 160.5 -2.4 190 657 -0.2 165
Weber, UT................ 5.5 87.9 -3.1 248 626 0.3 135
Chittenden, VT........... 5.9 90.6 -0.5 37 852 -2.0 272
Arlington, VA............ 8.0 160.4 1.6 3 1,520 3.6 14
Chesterfield, VA......... 7.6 112.0 -2.5 202 798 1.9 47
Fairfax, VA.............. 34.1 563.1 -1.0 57 1,419 2.2 36
Henrico, VA.............. 9.7 168.8 -3.0 242 967 1.8 54
Loudoun, VA.............. 9.2 128.7 0.2 18 1,071 1.6 69
Prince William, VA....... 7.4 101.2 0.8 12 773 -0.1 156
Alexandria City, VA...... 6.1 96.0 -0.8 47 1,223 2.3 35
Chesapeake City, VA...... 5.7 93.2 -1.8 129 702 1.2 85
Newport News City, VA.... 3.9 95.0 -1.2 76 791 0.1 141
Norfolk City, VA......... 5.7 136.3 -2.6 210 834 -1.9 266
Richmond City, VA........ 7.2 147.5 -2.5 202 1,025 -0.8 204
Virginia Beach City, VA.. 11.3 161.3 -1.2 76 677 -1.9 266
Benton, WA............... 5.4 77.4 5.0 2 915 1.6 69
Clark, WA................ 12.7 125.4 -0.9 51 763 -0.5 182
King, WA................. 79.0 1,098.9 -3.1 248 1,120 -0.6 188
Kitsap, WA............... 6.5 80.1 -1.9 144 783 1.7 60
Pierce, WA............... 21.0 258.2 -2.6 210 794 0.3 135
Snohomish, WA............ 18.3 235.9 -3.2 257 890 0.7 105
Spokane, WA.............. 15.6 195.3 -2.4 190 716 -0.7 196
Thurston, WA............. 7.1 96.1 -2.1 161 794 0.6 117
Whatcom, WA.............. 6.8 76.4 -3.9 293 697 -0.6 188
Yakima, WA............... 8.7 94.0 -0.2 29 592 -0.8 204
Kanawha, WV.............. 6.0 103.8 -2.2 174 757 -3.8 309
Brown, WI................ 6.5 141.3 -1.1 67 772 -0.3 169
Dane, WI................. 13.7 288.5 -1.6 112 826 -1.5 246
Milwaukee, WI............ 20.8 458.5 -2.8 224 867 -1.6 252
Outagamie, WI............ 5.0 96.0 -4.3 305 723 1.3 79
Waukesha, WI............. 12.7 211.9 -4.3 305 871 0.7 105
Winnebago, WI............ 3.7 86.2 -0.5 37 815 4.8 6
San Juan, PR............. 11.6 265.7 -3.6 (8) 600 0.8 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 326 U.S. counties comprise 70.9 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 2010(2)
Employment Average weekly
wage(3)
Establishments,
first quarter
County by NAICS supersector 2010 Percent Percent
(thousands) March change, Average change,
2010 March weekly first
(thousands) 2009-10(4) wage quarter
2009-10(4)
United States(5)............................. 9,043.6 126,281.7 -2.1 $889 0.8
Private industry........................... 8,746.4 104,193.4 -2.5 890 1.0
Natural resources and mining............. 125.9 1,615.4 -3.3 1,019 2.7
Construction............................. 806.6 5,192.5 -12.4 894 -1.3
Manufacturing............................ 345.6 11,343.0 -6.2 1,081 1.7
Trade, transportation, and utilities..... 1,875.7 23,997.7 -2.4 727 -0.7
Information.............................. 144.0 2,707.0 -5.2 1,468 2.1
Financial activities..................... 824.9 7,380.6 -3.4 1,711 7.2
Professional and business services....... 1,528.2 16,314.2 -1.2 1,153 2.0
Education and health services............ 880.9 18,587.8 1.7 770 -0.8
Leisure and hospitality.................. 740.1 12,534.9 -1.5 353 0.6
Other services........................... 1,267.8 4,296.4 -1.5 540 -0.4
Government................................. 297.2 22,088.3 -0.1 883 -0.2
Los Angeles, CA.............................. 431.4 3,863.3 -3.4 978 1.0
Private industry........................... 425.9 3,280.3 -3.4 958 1.2
Natural resources and mining............. 0.5 10.1 -5.0 1,635 10.3
Construction............................. 13.1 104.6 -16.0 966 -0.5
Manufacturing............................ 13.6 373.5 -6.6 1,080 1.8
Trade, transportation, and utilities..... 51.6 720.9 -2.8 764 -1.0
Information.............................. 8.4 190.6 -2.9 1,805 2.0
Financial activities..................... 22.5 208.0 -4.3 1,736 9.4
Professional and business services....... 41.2 524.0 -3.6 1,178 1.1
Education and health services............ 28.4 510.9 0.7 859 -0.8
Leisure and hospitality.................. 26.7 374.8 -2.9 520 0.6
Other services........................... 205.5 248.6 -4.0 421 -0.7
Government................................. 5.5 583.0 -3.1 1,093 0.3
Cook, IL..................................... 142.9 2,311.0 -2.9 1,083 -0.1
Private industry........................... 141.5 2,002.3 -3.1 1,088 -0.5
Natural resources and mining............. 0.1 0.8 -7.1 840 5.7
Construction............................. 12.1 58.6 -15.8 1,289 -1.1
Manufacturing............................ 6.7 192.0 -6.4 1,028 1.5
Trade, transportation, and utilities..... 27.5 420.1 -3.5 777 -2.0
Information.............................. 2.6 51.1 -5.4 1,676 2.5
Financial activities..................... 15.4 189.0 -4.5 2,465 2.2
Professional and business services....... 29.7 389.6 -2.8 1,417 0.9
Education and health services............ 14.6 389.0 0.6 815 -2.7
Leisure and hospitality.................. 12.2 215.0 -1.3 402 -0.5
Other services........................... 15.2 92.3 -3.7 720 -1.5
Government................................. 1.4 308.7 -1.3 1,045 2.2
New York, NY................................. 118.3 2,255.5 -1.7 2,404 11.9
Private industry........................... 118.0 1,806.6 -1.9 2,743 13.1
Natural resources and mining............. 0.0 0.1 -15.7 2,233 -0.7
Construction............................. 2.2 30.2 -13.2 1,532 3.7
Manufacturing............................ 2.6 26.4 -10.5 1,503 9.9
Trade, transportation, and utilities..... 20.9 225.6 -2.2 1,175 3.8
Information.............................. 4.3 127.6 -4.5 2,504 2.4
Financial activities..................... 18.7 341.6 -3.7 7,709 22.7
Professional and business services....... 24.7 446.9 -3.2 2,422 10.9
Education and health services............ 8.9 300.2 2.1 1,013 1.1
Leisure and hospitality.................. 11.9 215.6 1.9 707 -1.9
Other services........................... 18.2 85.6 -3.2 1,174 18.1
Government................................. 0.3 448.9 -0.8 1,045 2.8
Harris, TX................................... 99.5 1,970.8 -2.5 1,168 2.2
Private industry........................... 98.9 1,704.4 -3.1 1,204 2.6
Natural resources and mining............. 1.6 71.7 -3.6 3,911 12.9
Construction............................. 6.5 133.4 -10.4 1,039 -1.1
Manufacturing............................ 4.5 167.1 -7.4 1,490 7.3
Trade, transportation, and utilities..... 22.5 410.7 -2.9 1,084 1.4
Information.............................. 1.3 28.7 -6.3 1,284 -2.1
Financial activities..................... 10.5 112.0 -3.5 1,645 7.7
Professional and business services....... 19.8 310.1 -4.0 1,333 0.2
Education and health services............ 10.9 233.9 4.4 841 -1.4
Leisure and hospitality.................. 7.9 176.6 -1.6 381 1.9
Other services........................... 13.0 59.0 0.2 617 -2.5
Government................................. 0.5 266.3 2.0 937 0.9
Maricopa, AZ................................. 95.1 1,606.6 -3.8 848 -0.8
Private industry........................... 94.4 1,386.6 -4.0 854 0.2
Natural resources and mining............. 0.5 7.6 -11.6 971 13.7
Construction............................. 9.1 80.2 -20.7 866 -1.8
Manufacturing............................ 3.3 105.6 -9.1 1,272 3.3
Trade, transportation, and utilities..... 21.8 331.0 -3.0 796 0.0
Information.............................. 1.5 27.0 -2.3 1,156 -2.4
Financial activities..................... 11.4 133.2 -3.1 1,176 2.5
Professional and business services....... 21.6 258.1 -4.4 893 0.0
Education and health services............ 10.2 224.7 3.7 862 -1.3
Leisure and hospitality.................. 6.8 172.1 -3.6 403 1.3
Other services........................... 6.8 46.1 -0.8 549 -2.3
Government................................. 0.7 219.9 -2.7 811 -6.5
Dallas, TX................................... 67.7 1,392.8 -1.9 1,093 0.7
Private industry........................... 67.2 1,223.5 -2.3 1,113 0.9
Natural resources and mining............. 0.6 7.8 0.6 3,466 14.2
Construction............................. 4.2 66.6 -12.6 955 1.0
Manufacturing............................ 3.0 113.2 -8.2 1,271 0.9
Trade, transportation, and utilities..... 14.8 276.3 -2.7 954 0.1
Information.............................. 1.6 45.1 -3.9 1,852 1.2
Financial activities..................... 8.5 135.6 -3.1 1,729 5.9
Professional and business services....... 14.8 253.2 -0.6 1,228 -0.5
Education and health services............ 6.9 161.5 4.4 919 -0.4
Leisure and hospitality.................. 5.5 125.3 -0.8 487 -2.2
Other services........................... 7.0 38.0 0.1 607 -2.7
Government................................. 0.5 169.3 0.8 952 0.1
Orange, CA................................... 101.6 1,342.8 -4.2 1,001 1.2
Private industry........................... 100.2 1,194.0 -4.2 976 1.1
Natural resources and mining............. 0.2 5.0 -2.3 524 -6.9
Construction............................. 6.5 66.4 -15.2 1,038 -3.3
Manufacturing............................ 5.0 149.3 -7.3 1,209 5.9
Trade, transportation, and utilities..... 16.3 239.9 -3.7 896 -0.7
Information.............................. 1.3 25.1 -10.4 1,814 15.2
Financial activities..................... 9.9 103.3 -3.8 1,579 5.5
Professional and business services....... 18.5 235.4 -4.4 1,132 0.5
Education and health services............ 10.1 154.5 1.2 852 -1.4
Leisure and hospitality.................. 7.0 162.4 -2.9 391 3.2
Other services........................... 20.5 47.5 -1.2 502 -2.3
Government................................. 1.4 148.8 -3.8 1,197 0.8
San Diego, CA................................ 98.5 1,229.8 -2.8 930 -0.6
Private industry........................... 97.2 1,004.0 -3.3 912 -0.8
Natural resources and mining............. 0.7 9.8 -2.5 530 -2.6
Construction............................. 6.5 55.1 -14.3 982 0.6
Manufacturing............................ 3.0 92.6 -6.2 1,354 3.3
Trade, transportation, and utilities..... 13.7 192.9 -2.9 740 -1.7
Information.............................. 1.2 25.3 -5.9 1,423 1.9
Financial activities..................... 8.7 67.1 -4.0 1,233 -2.1
Professional and business services....... 15.9 204.0 -4.0 1,260 0.2
Education and health services............ 8.3 146.2 1.5 844 -0.6
Leisure and hospitality.................. 7.0 149.7 -1.6 381 -2.8
Other services........................... 27.9 57.0 -1.2 479 0.4
Government................................. 1.3 225.8 -0.6 1,010 -0.7
King, WA..................................... 79.0 1,098.9 -3.1 1,120 -0.6
Private industry........................... 78.5 941.8 -3.7 1,129 -0.5
Natural resources and mining............. 0.4 2.8 2.9 1,491 -5.0
Construction............................. 5.8 45.7 -19.4 1,112 -1.8
Manufacturing............................ 2.3 96.9 -6.8 1,383 1.2
Trade, transportation, and utilities..... 14.4 199.1 -3.2 961 -0.4
Information.............................. 1.7 78.4 -3.2 2,136 0.2
Financial activities..................... 6.5 64.6 -7.5 1,542 -2.3
Professional and business services....... 13.5 170.1 -3.5 1,350 2.4
Education and health services............ 6.7 130.2 -0.2 857 -0.1
Leisure and hospitality.................. 6.2 104.0 -1.4 434 2.6
Other services........................... 21.0 50.0 8.3 574 -4.5
Government................................. 0.5 157.1 0.6 1,066 -0.8
Miami-Dade, FL............................... 84.8 947.4 -2.0 845 -1.3
Private industry........................... 84.4 801.0 -1.9 819 0.4
Natural resources and mining............. 0.5 9.7 -5.7 379 -5.3
Construction............................. 5.5 31.7 -17.1 831 -2.7
Manufacturing............................ 2.6 34.6 -10.8 827 5.9
Trade, transportation, and utilities..... 23.6 234.6 -1.3 763 -0.3
Information.............................. 1.5 17.7 -4.7 1,370 3.3
Financial activities..................... 9.2 60.6 -4.0 1,439 6.2
Professional and business services....... 17.7 122.9 -1.8 988 0.3
Education and health services............ 9.6 148.2 2.1 792 -0.9
Leisure and hospitality.................. 6.2 105.5 1.3 466 -1.7
Other services........................... 7.6 34.8 -1.4 519 -1.9
Government................................. 0.4 146.4 -2.8 988 -7.9
(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.
Table 3. Covered(1) establishments, employment, and wages by state,
first quarter 2010(2)
Employment Average weekly
wage(3)
Establishments,
first quarter
State 2010 Percent Percent
(thousands) March change, Average change,
2010 March weekly first
(thousands) 2009-10 wage quarter
2009-10
United States(4)......... 9,043.6 126,281.7 -2.1 $889 0.8
Alabama.................. 117.0 1,803.7 -2.1 737 0.0
Alaska................... 21.2 304.4 0.2 878 -0.9
Arizona.................. 148.9 2,373.3 -3.5 800 -0.9
Arkansas................. 86.0 1,133.6 -1.0 674 -2.9
California............... 1,367.1 14,280.4 -3.0 1,003 0.9
Colorado................. 171.7 2,151.3 -2.7 912 -0.1
Connecticut.............. 111.6 1,566.7 -3.2 1,206 1.3
Delaware................. 28.5 388.4 -2.9 971 -0.5
District of Columbia..... 34.3 685.2 1.2 1,505 2.8
Florida.................. 595.5 7,162.0 -2.6 766 -0.5
Georgia.................. 269.0 3,728.2 -2.6 837 0.6
Hawaii................... 39.3 585.6 -2.4 767 -0.9
Idaho.................... 55.3 591.8 -1.6 634 -0.6
Illinois................. 376.9 5,406.6 -2.6 946 -0.4
Indiana.................. 160.2 2,666.1 -1.3 739 0.0
Iowa..................... 94.0 1,410.0 -1.6 707 -0.1
Kansas................... 87.8 1,286.4 -2.9 718 -0.1
Kentucky................. 109.2 1,690.8 -1.1 712 0.0
Louisiana................ 128.6 1,827.6 -2.1 762 -1.4
Maine.................... 48.9 557.7 -0.9 691 0.4
Maryland................. 162.1 2,414.4 -1.6 977 1.5
Massachusetts............ 216.7 3,071.0 -1.2 1,098 -0.2
Michigan................. 250.9 3,677.2 -2.3 815 -1.2
Minnesota................ 168.8 2,493.9 -1.8 883 0.2
Mississippi.............. 69.9 1,068.6 -1.8 633 0.0
Missouri................. 173.1 2,554.7 -2.4 762 -0.9
Montana.................. 42.2 411.0 -0.6 634 1.0
Nebraska................. 59.4 880.4 -1.7 694 -0.7
Nevada................... 73.9 1,097.8 -4.6 780 -3.7
New Hampshire............ 47.7 589.9 -1.7 833 -0.6
New Jersey............... 269.6 3,710.7 -1.5 1,121 1.8
New Mexico............... 54.2 777.3 -2.0 716 -0.8
New York................. 586.1 8,239.4 -1.1 1,281 6.1
North Carolina........... 250.8 3,752.2 -2.5 791 3.1
North Dakota............. 25.8 347.2 1.5 684 2.5
Ohio..................... 285.3 4,806.4 -2.7 783 -0.8
Oklahoma................. 102.7 1,474.2 -3.0 705 -0.4
Oregon................... 130.3 1,570.1 -1.9 776 0.5
Pennsylvania............. 341.3 5,376.6 -1.3 858 -0.3
Rhode Island............. 35.1 437.1 -1.1 836 0.7
South Carolina........... 111.9 1,742.0 -1.9 692 -0.1
South Dakota............. 30.8 377.2 -1.4 634 0.6
Tennessee................ 139.9 2,535.5 -1.7 764 1.6
Texas.................... 569.5 10,101.3 -1.3 893 0.8
Utah..................... 82.7 1,135.8 -2.2 729 0.3
Vermont.................. 24.3 288.6 -1.0 716 -0.4
Virginia................. 231.6 3,489.1 -1.3 932 1.3
Washington............... 226.0 2,752.4 -2.2 899 -0.4
West Virginia............ 48.5 682.3 -1.1 693 -1.6
Wisconsin................ 156.8 2,565.5 -2.1 741 -0.8
Wyoming.................. 25.0 262.2 -3.8 775 -0.4
Puerto Rico.............. 49.2 943.4 -2.6 497 0.0
Virgin Islands........... 3.6 44.9 0.5 720 5.1
(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
