For release 10:00 a.m. (EDT), Thursday, September 27, 2012 USDL-12-1939
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 2012
From March 2011 to March 2012, employment increased in 293 of the 328 largest U.S.
counties, the U.S. Bureau of Labor Statistics reported today. Gregg, Texas, posted
the largest increase, with a gain of 6.0 percent over the year, compared with
national job growth of 1.8 percent. Within Gregg, the largest employment increase
occurred in construction, which gained 1,948 jobs over the year (28.7 percent).
Benton, Wash., experienced the largest over-the-year decrease in employment among
the largest counties in the U.S. with a loss of 3.9 percent.
The U.S. average weekly wage increased over the year by 5.4 percent to $984 in the
first quarter of 2012. Williamson, Texas, had the largest over-the-year increase in
average weekly wages with a gain of 27.4 percent. Within Williamson, a total wage
gain of $298.1 million (49.5 percent) in the trade, transportation, and utilities
industry had the largest impact on the county’s increase in average weekly wages.
New York, N.Y., experienced the largest decrease in average weekly wages with a loss
of 6.3 percent over the year. County employment and wage data are compiled under the
Quarterly Census of Employment and Wages (QCEW) program.
Table A. Large counties ranked by March 2012 employment, March 2011-12 employment
increase, and March 2011-12 percent increase in employment
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Employment in large counties
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March 2012 employment | Increase in employment, | Percent increase in employment,
(thousands) | March 2011-12 | March 2011-12
| (thousands) |
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| |
United States 130,175.4| United States 2,338.1| United States 1.8
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| |
Los Angeles, Calif. 3,925.0| Harris, Texas 70.4| Gregg, Texas 6.0
Cook, Ill. 2,373.7| New York, N.Y. 53.0| Williamson, Tenn. 5.6
New York, N.Y. 2,360.9| Los Angeles, Calif. 52.9| Rutherford, Tenn. 5.3
Harris, Texas 2,085.3| Maricopa, Ariz. 41.4| Montgomery, Texas 4.9
Maricopa, Ariz. 1,665.1| Cook, Ill. 35.8| Harford, Md. 4.7
Dallas, Texas 1,446.5| Dallas, Texas 34.6| Kent, Mich. 4.6
Orange, Calif. 1,386.8| King, Wash. 33.6| Delaware, Ohio 4.6
San Diego, Calif. 1,253.4| Santa Clara, Calif. 30.2| Fort Bend, Texas 4.6
King, Wash. 1,144.4| Hennepin, Minn. 27.1| Kern, Calif. 4.4
Miami-Dade, Fla. 989.5| Orange, Calif. 24.1| Douglas, Colo. 4.2
| | Manatee, Fla. 4.2
| | Ottawa, Mich. 4.2
| | Washington, Pa. 4.2
| | Denton, Texas 4.2
| | Davis, Utah 4.2
| | Utah, Utah 4.2
| |
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Large County Employment
In March 2012, national employment, as measured by the QCEW program, was 130.2
million, up by 1.8 percent or 2.3 million jobs, from March 2011. The 328 U.S.
counties with 75,000 or more jobs accounted for 71.1 percent of total U.S.
employment and 77.5 percent of total wages. These 328 counties had a net job growth
of 1.6 million over the year, accounting for 70.2 percent of the overall U.S.
employment increase.
Gregg, Texas, had the largest percentage increase in employment (6.0 percent) among
the largest U.S. counties. The five counties with the largest increases in
employment level were Harris, Texas; New York, N.Y.; Los Angeles, Calif.; Maricopa,
Ariz.; and Cook, Ill. These counties had a combined over-the-year gain of 253,500,
or 10.8 percent of the overall employment increase for the U.S. (See table A.)
Employment declined in 32 of the large counties from March 2011 to March 2012.
Benton, Wash., had the largest over-the-year percentage decrease in employment (-3.9
percent). Within Benton, professional and business services was the largest
contributor to the decrease in employment with a loss of 3,103 jobs (-13.3 percent).
Madison, Ill., had the second largest percent decrease in employment, followed by
Arlington, Va. Two counties, St. Clair, Ill., and Jefferson, La., tied for the
fourth largest employment decrease. (See table 1.)
Table B. Large counties ranked by first quarter 2012 average weekly wages, first quarter 2011-12
increase in average weekly wages, and first quarter 2011-12 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 2012 | wage, first quarter 2011-12 | weekly wage, first
| | quarter 2011-12
--------------------------------------------------------------------------------------------------------
| |
United States $984| United States $50| United States 5.4
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| |
New York, N.Y. $2,464| Williamson, Texas $261| Williamson, Texas 27.4
Santa Clara, Calif. 1,957| Middlesex, N.J. 160| Middlesex, N.J. 13.6
Fairfield, Conn. 1,942| Morris, N.J. 138| Washington, Pa. 12.4
Somerset, N.J. 1,881| Lake, Ill. 126| Newport News City, Va. 12.1
San Francisco, Calif. 1,791| Collin, Texas 126| Collin, Texas 11.8
Suffolk, Mass. 1,708| San Mateo, Calif. 112| Tulsa, Okla. 11.3
San Mateo, Calif. 1,622| Washington, Pa. 110| Gregg, Texas 10.9
Arlington, Va. 1,617| Santa Clara, Calif. 103| Lake, Ill. 10.3
Washington, D.C. 1,602| Durham, N.C. 103| Peoria, Ill. 10.3
Morris, N.J. 1,595| Newport News City, Va. 100| Santa Cruz, Calif. 10.0
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Large County Average Weekly Wages
Average weekly wages for the nation increased by 5.4 percent during the year ending
in the first quarter of 2012. Among the 328 largest counties, 323 had over-the-year
increases in average weekly wages. Williamson, Texas, had the largest wage gain
among the largest U.S. counties (27.4 percent).
Of the 328 largest counties, 4 experienced over-the-year declines in average weekly
wages. New York, N.Y., had the largest average weekly wage decrease with a loss of
6.3 percent. Smaller first quarter bonus payments in 2012 contributed to this
decrease in the average weekly wage. Within New York County, total wages in
financial activities decreased by $5.3 billion (-13.4 percent) over the year.
Somerset, N.J., had the second largest decline in average weekly wages, followed by
Hudson, N.J., and Douglas, Colo. Clayton, Ga., had the smallest over-the-year
increase in average weekly wages (0.1 percent). (See table 1.)
Ten Largest U.S. Counties
All of the 10 largest counties experienced over-the-year percentage increases in
employment in March 2012. Harris, Texas, experienced the largest gain (3.5 percent).
Within Harris, professional and business services had the largest over-the-year
level increase among all private industry groups with a gain of 19,800 jobs (6.0
percent). San Diego, Calif., had the smallest percent increase in employment (1.1
percent) among the 10 largest counties. (See table 2.)
Nine of the 10 largest U.S. counties had an over-the-year increase in average weekly
wages. San Diego, Calif., experienced the largest increase in average weekly wages
(7.5 percent), largely due to substantial total wage gains over the year in
professional and business services ($291.1 million or 7.6 percent). New York, N.Y.,
had the only average weekly wage decline (-6.3 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. March 2012
employment and 2012 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 9.2 million employer
reports cover 130.2 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 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 second quarter 2012 is scheduled to be
released on Tuesday, January 8, 2013.
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| |
| County Changes for the 2012 |
| County Employment and Wages News Releases |
| |
| Counties with annual average employment of 75,000 or more in 2011 |
| are included in this release and will be included in future 2012 |
| releases. 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. One county, |
| Jackson, Ore., will be excluded. |
| |
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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 their 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- | 486,000 establish-
| submitted by 9.2 | ministrative records| ments
| million establish- | submitted by 6.7 |
| 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 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 9.1 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 2010 edition of this publication, which was published in November 2011,
contains selected data produced by Business Employment Dynamics (BED) on job gains
and losses, as well as selected data from the first quarter 2011 version of this
news release. Tables and additional content from Employment and Wages Annual Aver-
ages 2010 are now available online at http://www.bls.gov/cew/cewbultn10.htm. The
2011 edition of Employment and Wages Annual Averages Online will be available later
in 2012.
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,
first quarter 2012(2)
Employment Average weekly wage(4)
Establishments,
County(3) first quarter Percent Ranking Percent Ranking
2012 March change, by First change, by
(thousands) 2012 March percent quarter first percent
(thousands) 2011-12(5) change 2012 quarter change
2011-12(5)
United States(6)......... 9,211.8 130,175.4 1.8 - $984 5.4 -
Jefferson, AL............ 17.6 335.0 1.6 151 978 6.4 100
Madison, AL.............. 8.8 176.9 0.3 276 1,024 4.6 241
Mobile, AL............... 9.7 163.8 -0.5 315 790 6.3 110
Montgomery, AL........... 6.3 126.4 0.0 294 809 6.3 110
Tuscaloosa, AL........... 4.2 83.9 1.1 203 806 3.7 291
Anchorage Borough, AK.... 8.4 150.3 2.0 121 1,022 7.2 65
Maricopa, AZ............. 95.6 1,665.1 2.6 78 945 5.8 149
Pima, AZ................. 19.0 348.1 1.5 159 804 5.0 211
Benton, AR............... 5.5 96.1 3.1 45 1,166 5.2 194
Pulaski, AR.............. 14.3 241.5 1.0 217 861 5.6 162
Washington, AR........... 5.5 90.9 2.9 54 746 2.9 312
Alameda, CA.............. 57.9 646.5 2.5 86 1,276 7.2 65
Contra Costa, CA......... 30.7 317.2 0.9 228 1,256 4.0 276
Fresno, CA............... 31.8 325.8 1.4 175 736 3.7 291
Kern, CA................. 18.4 272.4 4.4 9 853 8.1 31
Los Angeles, CA.......... 448.8 3,925.0 1.4 175 1,090 4.2 265
Marin, CA................ 12.0 103.7 2.8 63 1,128 2.5 317
Monterey, CA............. 13.2 153.0 3.1 45 834 3.2 306
Orange, CA............... 106.0 1,386.8 1.8 137 1,095 5.2 194
Placer, CA............... 11.1 128.9 1.7 142 934 6.1 129
Riverside, CA............ 52.1 565.6 1.1 203 777 4.3 260
Sacramento, CA........... 55.3 580.1 0.8 238 1,081 6.0 139
San Bernardino, CA....... 53.0 602.4 1.0 217 790 5.2 194
San Diego, CA............ 102.3 1,253.4 1.1 203 1,076 7.5 44
San Francisco, CA........ 57.2 573.0 4.1 17 1,791 3.6 295
San Joaquin, CA.......... 18.1 199.1 1.0 217 785 4.8 224
San Luis Obispo, CA...... 9.8 102.6 2.8 63 775 4.3 260
San Mateo, CA............ 25.1 334.0 2.8 63 1,622 7.4 51
Santa Barbara, CA........ 14.8 179.0 2.9 54 924 6.5 93
Santa Clara, CA.......... 64.9 884.7 3.5 28 1,957 5.6 162
Santa Cruz, CA........... 9.3 86.9 0.9 228 902 10.0 10
Solano, CA............... 10.4 119.0 2.5 86 990 6.6 84
Sonoma, CA............... 19.4 172.2 0.6 250 867 3.1 310
Stanislaus, CA........... 15.3 158.7 1.3 184 803 7.4 51
Tulare, CA............... 9.6 137.8 2.9 54 649 4.0 276
Ventura, CA.............. 24.5 305.4 2.2 107 1,034 7.0 69
Yolo, CA................. 6.3 87.7 0.6 250 1,010 (7) -
Adams, CO................ 8.9 155.6 1.9 126 848 5.0 211
Arapahoe, CO............. 18.8 279.0 2.7 72 1,198 5.9 145
Boulder, CO.............. 12.9 158.6 3.1 45 1,126 6.6 84
Denver, CO............... 25.6 425.2 2.9 54 1,270 4.3 260
Douglas, CO.............. 9.5 92.1 4.2 10 1,077 -0.3 324
El Paso, CO.............. 16.7 233.8 0.7 242 857 5.5 166
Jefferson, CO............ 17.8 208.5 3.0 49 970 7.1 68
Larimer, CO.............. 10.0 128.3 3.0 49 826 3.6 295
Weld, CO................. 5.8 83.2 3.4 33 819 6.0 139
Fairfield, CT............ 32.6 402.3 1.8 137 1,942 2.9 312
Hartford, CT............. 25.5 485.7 1.4 175 1,320 4.4 256
New Haven, CT............ 22.3 350.9 1.6 151 1,003 5.4 179
New London, CT........... 6.9 121.4 -0.8 322 987 2.7 315
New Castle, DE........... 16.7 263.7 0.6 250 1,244 3.8 284
Washington, DC........... 35.3 712.1 1.3 184 1,602 4.0 276
Alachua, FL.............. 6.5 116.3 0.4 269 761 4.4 256
Brevard, FL.............. 14.5 187.7 -0.4 312 853 6.4 100
Broward, FL.............. 63.1 699.6 2.3 99 877 5.7 158
Collier, FL.............. 11.8 124.6 3.2 40 813 6.8 74
Duval, FL................ 26.9 437.3 -0.1 297 947 6.3 110
Escambia, FL............. 7.9 119.4 -0.4 312 725 5.4 179
Hillsborough, FL......... 37.9 589.2 2.1 115 920 4.7 233
Lake, FL................. 7.2 81.8 1.3 184 620 6.2 122
Lee, FL.................. 18.7 206.9 2.6 78 739 4.1 270
Leon, FL................. 8.2 137.5 -0.5 315 750 3.7 291
Manatee, FL.............. 9.4 106.3 4.2 10 706 5.5 166
Marion, FL............... 7.9 89.7 -0.1 297 643 5.2 194
Miami-Dade, FL........... 88.6 989.5 2.2 107 909 4.1 270
Okaloosa, FL............. 6.0 76.4 0.9 228 767 8.0 34
Orange, FL............... 36.0 676.5 3.0 49 846 5.0 211
Palm Beach, FL........... 49.5 509.4 2.5 86 934 5.2 194
Pasco, FL................ 10.0 99.8 0.9 228 624 4.7 233
Pinellas, FL............. 30.6 382.2 1.0 217 829 7.9 37
Polk, FL................. 12.4 191.9 -0.1 297 700 4.5 250
Sarasota, FL............. 14.4 139.4 2.8 63 755 4.6 241
Seminole, FL............. 13.7 157.8 2.1 115 774 5.6 162
Volusia, FL.............. 13.4 152.4 0.6 250 659 4.8 224
Bibb, GA................. 4.6 79.9 1.4 175 732 4.4 256
Chatham, GA.............. 7.6 132.0 2.3 99 801 6.2 122
Clayton, GA.............. 4.3 111.1 -0.8 322 981 0.1 323
Cobb, GA................. 21.3 301.9 2.6 78 1,057 3.9 280
De Kalb, GA.............. 17.8 276.1 0.2 283 1,034 3.5 299
Fulton, GA............... 41.1 711.7 2.2 107 1,406 5.1 205
Gwinnett, GA............. 24.0 306.3 1.7 142 940 6.3 110
Muscogee, GA............. 4.7 92.9 -0.5 315 781 4.6 241
Richmond, GA............. 4.7 99.0 -0.7 318 791 6.3 110
Honolulu, HI............. 24.5 440.6 0.8 238 870 6.1 129
Ada, ID.................. 13.7 195.1 2.9 54 810 4.5 250
Champaign, IL............ 4.2 86.9 0.4 269 795 6.1 129
Cook, IL................. 147.8 2,373.7 1.5 159 1,195 4.7 233
Du Page, IL.............. 37.0 559.8 1.9 126 1,161 6.2 122
Kane, IL................. 13.3 190.3 2.8 63 815 4.2 265
Lake, IL................. 22.0 313.4 1.3 184 1,344 10.3 8
McHenry, IL.............. 8.6 91.4 1.8 137 769 6.2 122
McLean, IL............... 3.8 85.2 0.3 276 949 5.0 211
Madison, IL.............. 6.0 93.5 -1.5 327 775 5.2 194
Peoria, IL............... 4.7 102.1 1.7 142 1,039 10.3 8
St. Clair, IL............ 5.6 93.1 -0.9 324 753 6.1 129
Sangamon, IL............. 5.3 127.8 0.1 291 946 3.4 301
Will, IL................. 15.1 198.6 2.2 107 830 5.3 186
Winnebago, IL............ 6.8 123.2 0.3 276 818 6.6 84
Allen, IN................ 9.0 173.3 1.4 175 810 8.0 34
Elkhart, IN.............. 4.9 106.9 4.1 17 750 7.3 59
Hamilton, IN............. 8.6 112.1 3.2 40 952 3.3 305
Lake, IN................. 10.4 186.0 2.0 121 852 8.4 26
Marion, IN............... 24.1 555.7 2.8 63 1,029 4.1 270
St. Joseph, IN........... 6.1 114.5 -0.3 306 760 5.6 162
Tippecanoe, IN........... 3.3 77.4 3.3 38 829 6.6 84
Vanderburgh, IN.......... 4.9 105.8 1.2 197 766 5.7 158
Johnson, IA.............. 3.6 76.9 1.8 137 836 6.2 122
Linn, IA................. 6.3 125.2 1.5 159 905 6.7 77
Polk, IA................. 15.0 266.8 2.8 63 992 5.4 179
Scott, IA................ 5.2 86.3 1.6 151 765 5.8 149
Johnson, KS.............. 22.0 306.9 3.7 25 1,016 6.4 100
Sedgwick, KS............. 12.6 238.7 0.9 228 880 7.6 42
Shawnee, KS.............. 4.9 94.5 0.5 262 795 6.7 77
Wyandotte, KS............ 3.3 82.8 4.0 19 893 8.2 29
Fayette, KY.............. 9.4 174.8 1.9 126 849 5.2 194
Jefferson, KY............ 22.0 418.4 2.4 95 955 8.6 22
Caddo, LA................ 7.5 120.2 -0.3 306 769 4.8 224
Calcasieu, LA............ 4.9 82.8 0.3 276 826 7.4 51
East Baton Rouge, LA..... 14.8 256.6 1.1 203 877 5.7 158
Jefferson, LA............ 13.9 190.1 -0.9 324 868 5.1 205
Lafayette, LA............ 9.1 137.0 3.9 22 918 7.4 51
Orleans, LA.............. 11.3 177.4 3.2 40 979 1.2 319
St. Tammany, LA.......... 7.5 78.8 2.7 72 817 6.4 100
Cumberland, ME........... 12.6 165.1 0.6 250 868 3.8 284
Anne Arundel, MD......... 14.5 234.4 3.6 27 1,042 9.3 17
Baltimore, MD............ 21.1 361.0 1.3 184 977 6.1 129
Frederick, MD............ 6.1 91.6 -0.1 297 958 4.6 241
Harford, MD.............. 5.6 86.1 4.7 5 895 5.5 166
Howard, MD............... 9.1 155.6 2.8 63 1,202 4.6 241
Montgomery, MD........... 32.8 447.6 1.1 203 1,355 3.4 301
Prince Georges, MD....... 15.5 298.8 0.5 262 984 5.0 211
Baltimore City, MD....... 13.8 327.7 -0.3 306 1,173 8.5 23
Barnstable, MA........... 9.2 80.1 2.0 121 808 6.6 84
Bristol, MA.............. 16.5 207.6 0.9 228 844 6.7 77
Essex, MA................ 22.3 298.0 1.5 159 1,006 4.7 233
Hampden, MA.............. 15.6 194.3 1.2 197 858 5.5 166
Middlesex, MA............ 50.8 811.5 1.7 142 1,459 6.3 110
Norfolk, MA.............. 24.2 314.4 1.5 159 1,133 6.5 93
Plymouth, MA............. 14.5 171.0 1.9 126 858 5.3 186
Suffolk, MA.............. 24.2 589.7 2.2 107 1,708 4.5 250
Worcester, MA............ 22.0 313.8 1.3 184 947 4.5 250
Genesee, MI.............. 7.1 128.5 1.9 126 794 6.6 84
Ingham, MI............... 6.2 152.8 0.2 283 916 5.4 179
Kalamazoo, MI............ 5.2 108.9 1.1 203 874 7.5 44
Kent, MI................. 13.6 325.7 4.6 6 847 7.2 65
Macomb, MI............... 16.6 285.4 2.4 95 982 4.4 256
Oakland, MI.............. 36.6 643.2 3.3 38 1,081 6.0 139
Ottawa, MI............... 5.4 105.3 4.2 10 747 4.6 241
Saginaw, MI.............. 4.1 81.9 2.0 121 760 0.7 321
Washtenaw, MI............ 7.8 191.3 1.9 126 974 5.8 149
Wayne, MI................ 30.5 677.0 1.9 126 1,070 4.9 218
Anoka, MN................ 7.2 107.6 2.6 78 870 4.8 224
Dakota, MN............... 9.9 168.3 0.7 242 954 7.4 51
Hennepin, MN............. 43.3 833.2 3.4 33 1,274 6.3 110
Olmsted, MN.............. 3.5 88.5 2.9 54 1,001 3.8 284
Ramsey, MN............... 14.0 312.1 1.0 217 1,116 3.0 311
St. Louis, MN............ 5.6 90.9 0.0 294 781 8.0 34
Stearns, MN.............. 4.4 79.6 2.7 72 736 5.1 205
Harrison, MS............. 4.4 81.9 -0.3 306 702 5.1 205
Hinds, MS................ 6.0 121.5 0.3 276 802 3.4 301
Boone, MO................ 4.5 85.5 3.9 22 724 4.5 250
Clay, MO................. 5.0 88.6 0.8 238 884 4.9 218
Greene, MO............... 8.0 152.3 3.9 22 707 7.3 59
Jackson, MO.............. 18.4 342.4 0.4 269 960 6.5 93
St. Charles, MO.......... 8.2 124.1 2.5 86 784 5.2 194
St. Louis, MO............ 31.8 561.0 0.2 283 1,023 5.7 158
St. Louis City, MO....... 9.1 217.0 1.3 184 1,155 9.4 14
Yellowstone, MT.......... 6.0 76.2 2.2 107 769 6.5 93
Douglas, NE.............. 17.1 311.5 1.5 159 898 5.3 186
Lancaster, NE............ 9.1 155.8 2.9 54 749 5.3 186
Clark, NV................ 47.9 807.9 1.5 159 836 5.8 149
Washoe, NV............... 13.5 180.3 0.6 250 828 4.9 218
Hillsborough, NH......... 11.8 186.2 0.6 250 1,031 5.3 186
Rockingham, NH........... 10.5 131.5 1.5 159 891 4.2 265
Atlantic, NJ............. 6.7 130.8 1.9 126 801 3.8 284
Bergen, NJ............... 33.3 423.1 1.7 142 1,207 4.9 218
Burlington, NJ........... 11.0 191.5 1.1 203 1,008 5.1 205
Camden, NJ............... 12.2 191.1 0.5 262 955 5.8 149
Essex, NJ................ 20.6 338.1 0.7 242 1,320 7.7 38
Gloucester, NJ........... 6.2 96.3 0.1 291 810 5.3 186
Hudson, NJ............... 13.9 232.0 1.0 217 1,514 -0.4 325
Mercer, NJ............... 11.0 228.3 1.3 184 1,391 7.5 44
Middlesex, NJ............ 21.8 380.2 2.3 99 1,338 13.6 2
Monmouth, NJ............. 20.0 237.5 -0.4 312 967 2.7 315
Morris, NJ............... 17.4 269.2 1.6 151 1,595 9.5 13
Ocean, NJ................ 12.2 143.6 2.3 99 769 3.8 284
Passaic, NJ.............. 12.3 169.6 0.7 242 956 5.5 166
Somerset, NJ............. 10.1 169.3 1.5 159 1,881 -1.6 326
Union, NJ................ 14.5 217.5 1.0 217 1,265 5.4 179
Bernalillo, NM........... 17.6 306.5 -0.3 306 825 5.5 166
Albany, NY............... 10.0 216.7 0.2 283 973 3.8 284
Bronx, NY................ 17.1 234.1 -0.1 297 851 4.0 276
Broome, NY............... 4.6 89.6 -0.2 303 728 3.4 301
Dutchess, NY............. 8.2 110.0 0.7 242 958 4.6 241
Erie, NY................. 23.8 449.4 1.1 203 842 6.0 139
Kings, NY................ 52.6 518.1 2.8 63 754 4.1 270
Monroe, NY............... 18.2 370.7 1.4 175 892 5.1 205
Nassau, NY............... 52.8 587.1 2.4 95 1,058 4.1 270
New York, NY............. 122.8 2,360.9 2.3 99 2,464 -6.3 327
Oneida, NY............... 5.3 103.8 -0.7 318 739 4.2 265
Onondaga, NY............. 12.9 238.4 0.5 262 874 5.3 186
Orange, NY............... 9.9 129.2 0.5 262 789 4.9 218
Queens, NY............... 46.9 513.9 2.9 54 877 3.7 291
Richmond, NY............. 9.0 91.3 0.6 250 778 2.8 314
Rockland, NY............. 10.0 113.1 0.9 228 1,055 6.2 122
Saratoga, NY............. 5.5 75.5 3.2 40 836 7.0 69
Suffolk, NY.............. 50.8 608.6 1.6 151 1,046 7.7 38
Westchester, NY.......... 36.2 401.0 0.7 242 1,399 4.7 233
Buncombe, NC............. 8.0 111.9 1.5 159 714 5.8 149
Catawba, NC.............. 4.4 78.3 0.2 283 705 1.9 318
Cumberland, NC........... 6.3 119.1 0.3 276 729 5.0 211
Durham, NC............... 7.3 182.8 2.5 86 1,381 8.1 31
Forsyth, NC.............. 9.0 173.5 2.4 95 945 5.5 166
Guilford, NC............. 14.1 261.7 1.1 203 854 6.8 74
Mecklenburg, NC.......... 32.9 563.6 2.9 54 1,274 3.2 306
New Hanover, NC.......... 7.4 95.8 1.4 175 749 3.2 306
Wake, NC................. 29.6 448.3 2.7 72 960 4.7 233
Cass, ND................. 6.1 103.8 3.7 25 829 8.4 26
Butler, OH............... 7.4 137.5 1.1 203 831 6.3 110
Cuyahoga, OH............. 35.6 689.2 1.9 126 1,003 5.4 179
Delaware, OH............. 4.3 76.8 4.6 6 1,073 7.6 42
Franklin, OH............. 29.6 659.6 2.6 78 972 5.5 166
Hamilton, OH............. 23.1 484.2 1.7 142 1,092 9.7 11
Lake, OH................. 6.4 92.1 1.5 159 802 3.8 284
Lorain, OH............... 6.0 93.6 2.3 99 796 6.1 129
Lucas, OH................ 10.1 198.5 2.2 107 837 5.3 186
Mahoning, OH............. 5.9 95.7 1.6 151 671 7.0 69
Montgomery, OH........... 12.1 241.5 1.1 203 831 6.3 110
Stark, OH................ 8.8 151.6 1.9 126 745 6.0 139
Summit, OH............... 14.3 252.8 2.0 121 897 6.7 77
Oklahoma, OK............. 24.7 424.7 2.6 78 912 9.4 14
Tulsa, OK................ 20.4 330.3 1.3 184 914 11.3 6
Clackamas, OR............ 12.7 136.6 1.5 159 840 5.5 166
Lane, OR................. 10.8 135.4 0.8 238 710 5.8 149
Marion, OR............... 9.4 127.5 -0.3 306 728 4.1 270
Multnomah, OR............ 29.6 437.4 2.7 72 979 6.8 74
Washington, OR........... 16.4 245.6 2.1 115 1,205 7.3 59
Allegheny, PA............ 35.8 675.9 1.4 175 1,067 7.7 38
Berks, PA................ 9.0 162.8 1.3 184 832 6.7 77
Bucks, PA................ 19.8 245.0 0.2 283 894 5.2 194
Butler, PA............... 4.9 82.2 2.3 99 861 6.7 77
Chester, PA.............. 15.2 234.1 0.5 262 1,255 8.5 23
Cumberland, PA........... 6.1 121.7 0.4 269 873 7.4 51
Dauphin, PA.............. 7.5 173.9 0.6 250 966 8.8 21
Delaware, PA............. 13.9 209.4 1.0 217 1,082 6.5 93
Erie, PA................. 7.7 123.6 1.2 197 746 7.3 59
Lackawanna, PA........... 5.9 96.0 -0.1 297 719 7.0 69
Lancaster, PA............ 12.7 216.5 1.0 217 775 5.9 145
Lehigh, PA............... 8.7 173.6 1.5 159 950 8.1 31
Luzerne, PA.............. 7.8 136.9 0.2 283 743 8.9 19
Montgomery, PA........... 27.5 460.7 0.6 250 1,294 7.4 51
Northampton, PA.......... 6.6 101.7 2.3 99 840 6.3 110
Philadelphia, PA......... 36.0 626.7 0.0 294 1,148 6.3 110
Washington, PA........... 5.7 84.3 4.2 10 995 12.4 3
Westmoreland, PA......... 9.5 131.4 1.7 142 761 6.1 129
York, PA................. 9.1 170.3 0.9 228 826 4.8 224
Providence, RI........... 17.2 267.1 1.2 197 970 8.5 23
Charleston, SC........... 11.8 213.9 3.4 33 834 7.5 44
Greenville, SC........... 12.0 232.9 2.6 78 820 6.6 84
Horry, SC................ 7.6 104.7 2.5 86 559 4.9 218
Lexington, SC............ 5.6 95.2 1.6 151 683 6.1 129
Richland, SC............. 9.0 204.6 1.3 184 832 4.7 233
Spartanburg, SC.......... 5.8 114.9 3.2 40 802 5.4 179
Minnehaha, SD............ 6.5 113.8 1.8 137 798 6.5 93
Davidson, TN............. 18.3 424.4 2.7 72 1,013 9.0 18
Hamilton, TN............. 8.4 183.8 2.6 78 843 7.4 51
Knox, TN................. 10.9 218.0 1.2 197 804 7.3 59
Rutherford, TN........... 4.4 101.5 5.3 3 821 5.9 145
Shelby, TN............... 19.1 466.8 2.1 115 970 6.0 139
Williamson, TN........... 6.2 96.2 5.6 2 1,125 5.9 145
Bell, TX................. 4.9 107.2 0.2 283 773 5.0 211
Bexar, TX................ 35.0 743.0 1.5 159 886 5.5 166
Brazoria, TX............. 5.0 91.8 3.4 33 943 3.2 306
Brazos, TX............... 3.9 86.2 -0.7 318 701 6.4 100
Cameron, TX.............. 6.4 129.5 1.7 142 570 5.2 194
Collin, TX............... 19.1 302.8 3.4 33 1,197 11.8 5
Dallas, TX............... 69.0 1,446.5 2.5 86 1,213 5.5 166
Denton, TX............... 11.5 182.6 4.2 10 833 6.4 100
El Paso, TX.............. 14.1 275.0 0.5 262 669 6.9 73
Fort Bend, TX............ 9.7 140.7 4.6 6 1,025 4.6 241
Galveston, TX............ 5.4 95.5 0.4 269 867 4.8 224
Gregg, TX................ 4.2 78.9 6.0 1 883 10.9 7
Harris, TX............... 102.9 2,085.3 3.5 28 1,340 6.4 100
Hidalgo, TX.............. 11.4 230.1 1.3 184 579 4.7 233
Jefferson, TX............ 5.9 122.7 1.2 197 988 7.5 44
Lubbock, TX.............. 7.1 123.9 -0.7 318 700 7.5 44
McLennan, TX............. 4.9 100.3 0.6 250 766 5.8 149
Montgomery, TX........... 9.1 138.3 4.9 4 968 8.3 28
Nueces, TX............... 7.9 154.6 2.2 107 821 9.6 12
Smith, TX................ 5.7 92.7 0.4 269 766 3.9 280
Tarrant, TX.............. 38.5 771.7 2.5 86 954 6.6 84
Travis, TX............... 31.9 595.9 3.1 45 1,063 6.1 129
Webb, TX................. 4.9 90.7 3.5 28 624 5.8 149
Williamson, TX........... 7.9 131.7 2.5 86 1,213 27.4 1
Davis, UT................ 7.2 105.0 4.2 10 763 8.2 29
Salt Lake, UT............ 37.0 578.7 3.5 28 911 6.4 100
Utah, UT................. 12.7 171.4 4.2 10 724 6.5 93
Weber, UT................ 5.4 89.8 2.1 115 682 6.2 122
Chittenden, VT........... 6.1 95.9 3.0 49 915 4.6 241
Arlington, VA............ 8.5 164.9 -1.3 326 1,617 4.3 260
Chesterfield, VA......... 7.8 115.1 1.3 184 857 3.6 295
Fairfax, VA.............. 35.1 585.1 2.1 115 1,562 5.5 166
Henrico, VA.............. 10.2 175.4 1.6 151 1,031 1.1 320
Loudoun, VA.............. 10.0 137.6 1.7 142 1,161 6.7 77
Prince William, VA....... 8.0 110.8 4.0 19 831 6.4 100
Alexandria City, VA...... 6.3 94.3 1.1 203 1,286 4.8 224
Chesapeake City, VA...... 5.7 95.0 1.5 159 757 4.8 224
Newport News City, VA.... 3.8 96.8 1.5 159 926 12.1 4
Norfolk City, VA......... 5.7 137.9 0.4 269 927 7.5 44
Richmond City, VA........ 7.1 148.4 1.0 217 1,113 3.9 280
Virginia Beach City, VA.. 11.4 161.2 0.9 228 745 3.9 280
Benton, WA............... 5.7 77.4 -3.9 328 959 0.6 322
Clark, WA................ 13.6 127.2 1.9 126 848 6.3 110
King, WA................. 82.7 1,144.4 3.0 49 1,265 6.4 100
Kitsap, WA............... 6.7 79.6 -0.2 303 868 8.9 19
Pierce, WA............... 21.8 260.8 0.6 250 840 4.5 250
Snohomish, WA............ 19.3 252.8 4.0 19 1,061 9.4 14
Spokane, WA.............. 15.9 195.5 0.7 242 806 7.3 59
Thurston, WA............. 7.5 96.3 -0.2 303 829 3.6 295
Whatcom, WA.............. 6.9 80.2 3.5 28 796 6.6 84
Yakima, WA............... 8.8 95.2 0.9 228 632 4.3 260
Kanawha, WV.............. 6.0 104.7 1.1 203 836 4.8 224
Brown, WI................ 6.5 144.3 1.1 203 836 4.2 265
Dane, WI................. 13.9 299.7 1.4 175 941 7.7 38
Milwaukee, WI............ 22.8 464.0 0.1 291 981 5.5 166
Outagamie, WI............ 5.0 100.2 1.0 217 793 5.2 194
Waukesha, WI............. 12.5 222.4 0.7 242 953 6.1 129
Winnebago, WI............ 3.6 88.0 0.3 276 869 3.5 299
San Juan, PR............. 11.3 265.0 1.7 (8) 618 3.7 (8)
(1) Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs. These 328 U.S. counties comprise 71.1 percent of the total covered workers
in the U.S.
(2) Data are preliminary.
(3) Includes areas not officially designated as counties. See Technical Note.
(4) Average weekly wages were calculated using unrounded data.
(5) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(6) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(7) Data do not meet BLS or State agency disclosure standards.
(8) This county was not included in the U.S. rankings.
Table 2. Covered(1) establishments, employment, and wages in the 10 largest counties,
first quarter 2012(2)
Employment Average weekly
wage(3)
Establishments,
first quarter
County by NAICS supersector 2012 Percent Percent
(thousands) March change, First change,
2012 March quarter first
(thousands) 2011-12(4) 2012 quarter
2011-12(4)
United States(5)............................. 9,211.8 130,175.4 1.8 $984 5.4
Private industry........................... 8,914.4 108,645.8 2.4 991 5.3
Natural resources and mining............. 129.5 1,847.8 8.6 1,197 7.5
Construction............................. 752.9 5,282.2 2.8 972 6.0
Manufacturing............................ 335.9 11,792.7 2.0 1,230 5.7
Trade, transportation, and utilities..... 1,881.9 24,782.6 1.9 815 6.4
Information.............................. 143.9 2,668.0 -0.1 1,717 6.8
Financial activities..................... 810.1 7,424.5 0.9 1,905 1.1
Professional and business services....... 1,582.7 17,536.7 3.5 1,292 6.5
Education and health services............ 923.9 19,362.2 2.0 841 6.2
Leisure and hospitality.................. 765.0 13,295.4 3.5 384 5.8
Other services........................... 1,358.3 4,418.2 1.5 582 5.4
Government................................. 297.4 21,529.7 -1.1 949 5.2
Los Angeles, CA.............................. 448.8 3,925.0 1.4 1,090 4.2
Private industry........................... 443.1 3,375.9 2.0 1,070 3.9
Natural resources and mining............. 0.4 10.0 1.4 1,660 0.2
Construction............................. 12.0 105.7 3.0 1,042 4.1
Manufacturing............................ 12.6 365.0 -0.6 1,218 6.4
Trade, transportation, and utilities..... 50.3 742.9 1.6 853 5.8
Information.............................. 8.2 188.5 -2.2 2,092 4.3
Financial activities..................... 21.6 208.1 0.6 1,987 3.9
Professional and business services....... 41.1 560.8 3.7 1,323 4.3
Education and health services............ 29.2 528.6 2.0 952 4.6
Leisure and hospitality.................. 26.9 400.5 3.7 562 -2.1
Other services........................... 213.8 243.3 0.0 452 2.5
Government................................. 5.7 549.1 -2.1 1,212 6.1
Cook, IL..................................... 147.8 2,373.7 1.5 1,195 4.7
Private industry........................... 146.4 2,074.4 1.9 1,204 4.4
Natural resources and mining............. 0.1 0.7 0.1 843 10.5
Construction............................. 12.3 56.8 0.0 1,307 2.7
Manufacturing............................ 6.6 192.3 -0.1 1,175 6.7
Trade, transportation, and utilities..... 28.7 435.5 1.2 907 6.6
Information.............................. 2.6 53.5 1.3 1,894 3.4
Financial activities..................... 15.5 183.3 -0.7 2,930 2.1
Professional and business services....... 31.2 412.1 3.7 1,510 6.3
Education and health services............ 15.5 409.6 1.7 865 3.5
Leisure and hospitality.................. 13.0 231.4 4.2 458 8.5
Other services........................... 16.3 95.7 1.4 797 6.8
Government................................. 1.4 299.3 -0.9 1,134 6.7
New York, NY................................. 122.8 2,360.9 2.3 2,464 -6.3
Private industry........................... 122.5 1,924.1 2.9 2,771 -7.3
Natural resources and mining............. 0.0 0.1 9.7 2,784 -11.1
Construction............................. 2.1 29.9 1.3 1,650 2.5
Manufacturing............................ 2.4 26.7 0.2 1,663 4.5
Trade, transportation, and utilities..... 20.8 244.7 3.9 1,321 5.6
Information.............................. 4.4 139.5 3.0 2,835 5.3
Financial activities..................... 18.9 351.5 0.2 7,511 -13.7
Professional and business services....... 25.3 475.3 3.5 2,560 -0.9
Education and health services............ 9.2 309.5 0.8 1,128 6.7
Leisure and hospitality.................. 12.9 248.2 5.9 793 4.2
Other services........................... 18.9 90.6 3.4 1,045 6.3
Government................................. 0.3 436.9 -0.5 1,112 1.7
Harris, TX................................... 102.9 2,085.3 3.5 1,340 6.4
Private industry........................... 102.4 1,829.7 4.5 1,388 6.5
Natural resources and mining............. 1.7 85.2 9.6 4,242 2.0
Construction............................. 6.5 139.2 5.6 1,198 9.3
Manufacturing............................ 4.5 185.3 7.0 1,686 5.3
Trade, transportation, and utilities..... 23.1 433.0 3.4 1,263 8.6
Information.............................. 1.3 27.9 -0.5 1,456 5.1
Financial activities..................... 10.6 112.2 0.7 1,929 4.8
Professional and business services....... 20.5 348.1 6.0 1,549 5.3
Education and health services............ 11.6 248.2 2.9 934 6.9
Leisure and hospitality.................. 8.4 188.8 5.0 420 9.4
Other services........................... 13.7 60.8 1.7 684 4.0
Government................................. 0.6 255.6 -3.4 996 3.0
Maricopa, AZ................................. 95.6 1,665.1 2.6 945 5.8
Private industry........................... 94.9 1,456.7 3.0 953 6.0
Natural resources and mining............. 0.5 8.1 8.0 1,268 9.4
Construction............................. 8.1 82.4 4.4 935 5.9
Manufacturing............................ 3.2 111.8 2.3 1,519 5.7
Trade, transportation, and utilities..... 21.9 338.7 2.5 895 5.8
Information.............................. 1.6 28.1 2.2 1,247 3.3
Financial activities..................... 11.0 141.4 3.6 1,359 7.0
Professional and business services....... 22.6 269.0 2.3 1,005 8.8
Education and health services............ 10.6 246.0 3.7 898 3.9
Leisure and hospitality.................. 7.2 182.2 3.2 429 5.1
Other services........................... 6.6 46.8 0.2 610 5.5
Government................................. 0.7 208.3 -0.7 884 3.6
Dallas, TX................................... 69.0 1,446.5 2.5 1,213 5.5
Private industry........................... 68.5 1,283.1 3.2 1,237 5.4
Natural resources and mining............. 0.6 9.5 14.5 4,827 8.4
Construction............................. 4.0 67.1 1.1 1,007 4.8
Manufacturing............................ 2.8 111.4 0.3 1,510 2.1
Trade, transportation, and utilities..... 14.9 289.9 3.7 1,058 7.5
Information.............................. 1.6 45.9 0.7 2,179 4.6
Financial activities..................... 8.6 141.0 2.7 1,896 1.8
Professional and business services....... 15.2 278.0 5.6 1,324 6.3
Education and health services............ 7.4 170.5 2.6 1,003 7.6
Leisure and hospitality.................. 5.8 129.9 3.0 489 4.9
Other services........................... 7.3 39.3 0.6 670 7.4
Government................................. 0.5 163.4 -3.2 1,024 5.0
Orange, CA................................... 106.0 1,386.8 1.8 1,095 5.2
Private industry........................... 104.6 1,243.4 2.2 1,070 4.9
Natural resources and mining............. 0.2 3.5 -16.1 735 20.1
Construction............................. 6.0 68.6 2.4 1,128 6.7
Manufacturing............................ 4.8 156.8 1.8 1,368 6.4
Trade, transportation, and utilities..... 15.8 241.5 0.6 981 6.1
Information.............................. 1.2 23.7 -0.9 1,668 -8.5
Financial activities..................... 9.5 106.2 1.4 1,789 6.9
Professional and business services....... 18.4 246.5 1.9 1,253 4.5
Education and health services............ 10.4 162.5 2.6 920 4.0
Leisure and hospitality.................. 7.2 176.8 4.4 431 5.9
Other services........................... 22.4 49.8 (6) 534 4.3
Government................................. 1.4 143.4 -1.8 1,310 7.9
San Diego, CA................................ 102.3 1,253.4 1.1 1,076 7.5
Private industry........................... 100.9 1,035.8 1.7 1,052 6.7
Natural resources and mining............. 0.7 10.0 0.4 575 7.9
Construction............................. 5.8 55.1 1.3 1,067 3.2
Manufacturing............................ 2.9 93.1 -0.8 1,557 6.7
Trade, transportation, and utilities..... 13.4 201.0 1.4 842 5.5
Information.............................. 1.1 24.3 -1.6 1,662 3.1
Financial activities..................... 8.4 68.8 1.9 1,565 17.8
Professional and business services....... 15.8 210.9 2.0 1,505 5.8
Education and health services............ 8.6 154.6 2.3 922 4.9
Leisure and hospitality.................. 7.1 154.2 2.4 430 12.0
Other services........................... 29.5 57.1 -0.6 521 4.8
Government................................. 1.4 217.6 -1.5 1,190 11.4
King, WA..................................... 82.7 1,144.4 3.0 1,265 6.4
Private industry........................... 82.2 987.2 3.6 1,287 7.1
Natural resources and mining............. 0.3 2.7 8.7 1,430 -2.1
Construction............................. 5.4 44.9 4.2 1,159 4.2
Manufacturing............................ 2.2 101.1 4.9 1,715 7.9
Trade, transportation, and utilities..... 14.5 208.1 3.3 1,082 5.9
Information.............................. 1.8 80.3 1.8 2,546 11.4
Financial activities..................... 6.2 62.7 0.2 1,794 4.5
Professional and business services....... 13.9 185.2 4.3 1,540 7.3
Education and health services............ 7.3 138.8 3.6 945 7.0
Leisure and hospitality.................. 6.5 110.2 4.6 443 5.5
Other services........................... 24.0 53.2 3.3 612 4.4
Government................................. 0.5 157.2 -0.1 1,127 1.8
Miami-Dade, FL............................... 88.6 989.5 2.2 909 4.1
Private industry........................... 88.3 851.2 3.2 895 4.8
Natural resources and mining............. 0.5 9.9 -4.0 484 16.9
Construction............................. 5.0 29.0 -7.2 862 -0.8
Manufacturing............................ 2.6 36.3 1.5 851 5.5
Trade, transportation, and utilities..... 25.5 254.1 4.2 844 4.6
Information.............................. 1.5 17.2 0.1 1,438 5.9
Financial activities..................... 9.0 66.6 4.9 1,567 -0.8
Professional and business services....... 18.4 124.8 0.8 1,108 9.1
Education and health services............ 9.9 157.2 2.0 875 6.1
Leisure and hospitality.................. 6.7 119.0 7.1 518 8.6
Other services........................... 7.9 35.1 4.1 540 4.4
Government................................. 0.4 138.3 -3.6 988 0.7
(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.
(6) Data do not meet BLS or State agency disclosure standards.
Table 3. Covered(1) establishments, employment, and wages by state,
first quarter 2012(2)
Employment Average weekly
wage(3)
Establishments,
first quarter
State 2012 Percent Percent
(thousands) March change, First change,
2012 March quarter first
(thousands) 2011-12 2012 quarter
2011-12
United States(4)......... 9,211.8 130,175.4 1.8 $984 5.4
Alabama.................. 116.1 1,822.8 0.8 808 5.6
Alaska................... 21.9 316.4 1.9 973 6.7
Arizona.................. 146.4 2,437.2 2.1 887 5.7
Arkansas................. 85.2 1,151.5 1.5 747 4.6
California............... 1,422.7 14,670.6 2.0 1,125 5.5
Colorado................. 170.4 2,230.4 2.4 1,003 5.4
Connecticut.............. 110.6 1,613.1 1.5 1,330 3.8
Delaware................. 27.4 398.8 0.8 1,071 4.2
District of Columbia..... 35.3 712.1 1.3 1,602 4.0
Florida.................. 605.4 7,377.3 2.0 837 5.4
Georgia.................. 268.3 3,815.5 1.3 931 5.2
Hawaii................... 38.4 600.3 0.9 834 5.7
Idaho.................... 53.5 596.7 1.1 692 5.0
Illinois................. 388.7 5,557.5 1.5 1,061 5.9
Indiana.................. 161.6 2,777.0 2.2 822 6.3
Iowa..................... 95.0 1,448.3 1.9 784 6.4
Kansas................... 87.8 1,314.2 1.8 803 7.2
Kentucky................. 108.3 1,750.3 1.9 785 6.4
Louisiana................ 128.5 1,863.1 1.2 836 4.9
Maine.................... 49.3 561.4 0.5 757 4.7
Maryland................. 165.1 2,492.4 1.7 1,071 6.0
Massachusetts............ 228.7 3,178.7 1.7 1,227 5.7
Michigan................. 241.6 3,865.8 2.6 920 5.5
Minnesota................ 169.9 2,586.3 2.1 989 6.1
Mississippi.............. 69.1 1,083.5 0.8 687 5.9
Missouri................. 175.1 2,593.7 1.2 838 6.5
Montana.................. 42.1 419.5 1.8 706 7.8
Nebraska................. 65.8 905.3 2.1 765 6.1
Nevada................... 72.0 1,118.4 1.4 846 5.5
New Hampshire............ 48.3 602.1 1.0 923 5.4
New Jersey............... 264.5 3,749.0 1.5 1,228 5.9
New Mexico............... 55.0 779.7 0.4 782 5.8
New York................. 603.0 8,479.4 1.7 1,357 -0.8
North Carolina........... 256.9 3,874.9 1.7 869 5.3
North Dakota............. 28.5 397.4 9.0 857 14.6
Ohio..................... 287.0 4,967.8 2.0 873 6.6
Oklahoma................. 103.9 1,525.5 2.0 806 9.4
Oregon................... 132.9 1,613.0 1.4 864 6.4
Pennsylvania............. 354.1 5,531.1 1.2 960 7.1
Rhode Island............. 35.0 443.5 1.1 931 8.0
South Carolina........... 112.0 1,797.7 1.7 764 6.0
South Dakota............. 31.2 390.4 2.1 703 6.7
Tennessee................ 141.3 2,636.7 2.4 847 6.8
Texas.................... 591.5 10,605.2 2.6 1,013 7.2
Utah..................... 83.8 1,193.1 3.2 799 6.1
Vermont.................. 24.5 296.6 1.5 774 4.6
Virginia................. 239.3 3,586.3 1.4 1,019 5.3
Washington............... 235.5 2,831.9 1.9 1,009 6.5
West Virginia............ 49.4 705.5 2.4 768 6.2
Wisconsin................ 158.9 2,639.0 1.1 827 6.2
Wyoming.................. 25.3 271.8 2.4 850 5.2
Puerto Rico.............. 48.8 931.3 0.6 521 4.6
Virgin Islands........... 3.4 42.7 -5.4 722 -2.0
(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
