For release 10:00 a.m. (EDT), Wednesday, August 22, 2018 USDL-18-1355
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 2018
From March 2017 to March 2018, employment increased in 314 of the 349 largest U.S. counties, the
U.S. Bureau of Labor Statistics reported today. Midland, Texas, had the largest percentage increase with
a gain of 12.6 percent over the year, above the national job growth rate of 1.6 percent. Within Midland,
the largest employment increase occurred in natural resources and mining, which gained 5,728 jobs over
the year (26.5 percent). Kanawha, W.Va., had the largest over-the-year percentage decrease in
employment among the largest counties in the U.S., with a loss of 1.4 percent. Within Kanawha, the
largest employment decrease occurred in state government, which lost 390 jobs (-3.4 percent) over the
year.
The U.S. average weekly wage increased 3.7 percent over the year, growing to $1,152 in the first
quarter of 2018. Peoria, Ill., had the largest over-the-year percentage increase in average weekly wages,
with a gain of 23.8 percent. Within Peoria, an average weekly wage gain of $1,802 (60.6 percent) in
manufacturing made the largest contribution to the county’s increase in average weekly wages. Forsyth,
N.C., had the largest over-the-year percentage decrease in average weekly wages with a loss of 4.8
percent. Within Forsyth, professional and business services had the largest impact on the county’s
average weekly wage change with a decrease of $304 (-18.7 percent) over the year.
County employment and wage data are from the Quarterly Census of Employment and Wages (QCEW)
program, which provides the only detailed quarterly and annual universe count of establishments,
employment, and wages at the county, metropolitan statistical area, state, and national levels by detailed
industry. These data are published within 5 months following the end of each quarter.
Large County Employment
In March 2018, national employment was 144.6 million (as measured by the QCEW program). Over the
year, employment increased by 1.6 percent, or 2.3 million. In March 2018, the 349 U.S. counties with
75,000 or more jobs accounted for 73.1 percent of total U.S. employment and 79.2 percent of total
wages. These 349 counties had a net job growth of 1.6 million over the year, accounting for 72.4 percent
of the overall U.S. employment increase. The 5 counties with the largest increases in employment levels
had a combined over-the-year employment gain of 237,600 jobs, which was 10.5 percent of the overall
job increase for the U.S. (See table A.)
Employment declined in 31 of the largest counties from March 2017 to March 2018. Kanawha, W.Va.,
had the largest over-the-year percentage decrease in employment (-1.4 percent), followed by Saginaw,
Mich.; Alexandria City, Va.; Jefferson, Texas; Montgomery, Ala.; and Caddo, La. (See table 1.)
Table A. Large counties ranked by March 2018 employment, March 2017-18 employment increase, and
March 2017-18 percent increase in employment
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Employment in large counties
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March 2018 employment | Increase in employment, | Percent increase in employment,
(thousands) | March 2017-18 | March 2017-18
| (thousands) |
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| |
United States 144,562.9| United States 2,269.1| United States 1.6
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| |
Los Angeles, Calif. 4,424.4| Los Angeles, Calif. 69.8| Midland, Texas 12.6
Cook, Ill. 2,565.0| Maricopa, Ariz. 61.5| Utah, Utah 6.0
New York, N.Y. 2,446.5| King, Wash. 39.6| Boone, Ky. 5.9
Harris, Texas 2,287.9| Kings, N.Y. 33.9| Montgomery, Texas 5.6
Maricopa, Ariz. 1,983.6| Orange, Calif. 32.8| Calcasieu, La. 5.0
Dallas, Texas 1,684.9| San Diego, Calif. 29.7| Weld, Colo. 4.7
Orange, Calif. 1,617.5| Harris, Texas 29.2| Elkhart, Ind. 4.7
San Diego, Calif. 1,452.7| Orange, Fla. 28.4| Kings, N.Y. 4.7
King, Wash. 1,375.1| Fulton, Ga. 25.7| Adams, Colo. 4.5
Miami-Dade, Fla. 1,147.0| Dallas, Texas 25.7| Ada, Idaho 4.5
| | Clark, Wash. 4.5
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Large County Average Weekly Wages
Average weekly wages for the nation increased to $1,152, a 3.7 percent increase, during the year ending
in the first quarter of 2018. Among the 349 largest counties, 336 had over-the-year increases in average
weekly wages. Peoria, Ill., had the largest percentage wage increase among the largest U.S. counties
(23.8 percent). (See table B.)
Of the 349 largest counties, 13 experienced an over-the-year decrease in average weekly wages. Forsyth,
N.C., had the largest percentage decrease in average weekly wages (-4.8 percent), followed by
Washington, Ark.; McLean, Ill.; Newport News City, Va.; and Lexington, S.C. (See table 1.)
Table B. Large counties ranked by first quarter 2018 average weekly wages, first quarter 2017-18
increase in average weekly wages, and first quarter 2017-18 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 2018 | wage, first quarter 2017-2018 | weekly wage, first
| | quarter 2017-2018
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| |
United States $1,152| United States $41| United States 3.7
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| |
New York, N.Y. $3,087| Peoria, Ill. $277| Peoria, Ill. 23.8
Santa Clara, Calif. 2,651| Suffolk, Mass. 245| Suffolk, Mass. 12.1
San Mateo, Calif. 2,606| San Francisco, Calif. 225| Clayton, Ga. 11.3
San Francisco, Calif. 2,485| Santa Clara, Calif. 221| King, Wash. 10.1
Suffolk, Mass. 2,268| San Mateo, Calif. 169| San Francisco, Calif. 10.0
Somerset, N.J. 2,078| King, Wash. 162| Utah, Utah 9.7
Fairfield, Conn. 1,959| Clayton, Ga. 134| Santa Clara, Calif. 9.1
Arlington, Va. 1,925| Hudson, N.J. 125| Muscogee, Ga. 8.7
Washington, D.C. 1,917| Snohomish, Wash. 101| Hillsborough, N.H. 8.6
Morris, N.J. 1,808| Hillsborough, N.H. 98| Snohomish, Wash. 8.6
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Ten Largest U.S. Counties
All of the 10 largest counties had over-the-year percentage increases in employment in March 2018.
Maricopa, Ariz., had the largest gain (3.2 percent). Within Maricopa, education and health services had
the largest over-the-year employment level increase, with a gain of 12,239 jobs, or 4.1 percent. Cook,
Ill., had the smallest percentage increase in employment among the 10 largest counties (0.7 percent).
Within Cook, education and health services had the largest over-the-year employment level increase,
with a gain of 6,161 jobs, or 1.4 percent. (See table 2.)
Average weekly wages increased over the year in all of the 10 largest U.S. counties. King, Wash.,
experienced the largest percentage gain in average weekly wages (10.1 percent). Within King,
professional and business services had the largest impact on the county’s average weekly wage gain.
Within professional and business services, average weekly wages increased by $305, or 16.9 percent,
over the year. Los Angeles, Calif., had the smallest percentage gain in average weekly wages among the
10 largest counties (2.3 percent). Within Los Angeles, manufacturing had the largest impact on the
county’s average weekly wage growth with an increase of $73 (5.1 percent) over the year.
For More Information
The tables included in this release contain data for the nation and for the 349 U.S. counties with annual
average employment levels of 75,000 or more in 2017. March 2018 employment and first quarter 2018
average weekly wages for all states are provided in table 3 of this release.
The data are derived from reports submitted by employers who are subject to unemployment insurance
(UI) laws. The 10.0 million employer reports cover 144.6 million full- and part-time workers. The full
set of data for the first quarter of 2018 will be available on September 5, 2018, at www.bls.gov/cew.
Additional information about the quarterly employment and wages data is available in the Technical
Note. More information about QCEW data may be obtained by calling (202) 691-6567.
The most current news release on quarterly measures of gross job flows is available from QCEW
Business Employment Dynamics at www.bls.gov/news.release/pdf/cewbd.pdf.
Several BLS regional offices issue QCEW news releases targeted to local data users. Links to these
releases are available at www.bls.gov/cew/cewregional.htm.
_____________
The County Employment and Wages full data update for first quarter 2018 is scheduled to be
released on Wednesday, September 5, 2018.
The County Employment and Wages release for second quarter 2018 is scheduled to be released
on Wednesday, November 21, 2018.
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| |
| County Changes for the 2018 County Employment and Wages News Releases |
| |
| Counties with annual average employment of 75,000 or more in 2017 are included in this release and |
| will be included in future 2018 releases. Three counties have been added to the publication tables: |
| Cabarrus, N.C.; Pitt, N.C.; and Kent, R.I. |
| |
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| |
| Change in QCEW Oregon Classification of Services for the Elderly and Disabled |
| |
| Prior to this release, some Oregon workers employed in the services for the elderly and disabled |
| industry were classified in QCEW under state government ownership. Beginning with data in this release |
| for first quarter 2018, QCEW classifies most of these workers in private ownership. This change in |
| ownership resulted from the passage of state legislation in 2017. The industry classification for |
| these workers has not changed. For more information, contact the Oregon Labor Market Information |
| group at sf202_or@bls.gov. |
| |
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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 2017 North American Industry
Classification System (NAICS). Data for 2018 are preliminary and subject to revision.
For purposes of this release, large counties are defined as having employment levels of 75,000 or
greater. In addition, data for San Juan, Puerto Rico, are provided, but not used in calculating U.S.
averages, rankings, or in the analysis in the text. Each year, these large counties are selected on the
basis of the preliminary annual average of employment for the previous year. The 349 counties
presented in this release were derived using 2017 preliminary annual averages of employment. For
2018 data, three counties have been added to the publication tables: Cabarrus, N.C.; Pitt, N.C.; and
Kent, R.I. These counties will be included in all 2018 quarterly releases. The counties in table 2 are
selected and sorted each year based on the annual average employment from the preceding year.
The preliminary QCEW data presented in this release may differ from data released by the
individual states. These potential differences result from the states' continuing receipt of UI data
over time and ongoing review and editing. The individual states determine their data release
timetables.
Differences between QCEW, BED, and CES employment measures
The Bureau publishes three different establishment-based employment measures for any given
quarter: QCEW, Business Employment Dynamics (BED), and Current Employment Statistics
(CES). Each of these measures makes use of the quarterly UI employment reports in producing
data; however, each measure has a somewhat different universe coverage, estimation procedure,
and publication product.
Differences in coverage and estimation methods can result in somewhat different measures of
employment change over time. It is important to understand program differences and the intended
uses of the program products. (See table.) Additional information 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- | 651,000 establish-
| submitted by 10.0 | ministrative records| ments
| million establish- | submitted by 7.9 |
| ments in first | million private-sec-|
| quarter of 2018 | 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 | -Within 5 months | -7 months after the | -Usually the 3rd Friday
| after the end of | end of each quarter| after the end of the
| each quarter | | week including
| | | the 12th of the month
-----------|---------------------|----------------------|------------------------
Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam-
file | and publishes each | quarter to longitu- | pling frame and to an-
| new quarter of UI | dinal database and | nually realign sample-
| data | directly summarizes | based estimates to pop-
| | gross job gains and | ulation counts (bench-
| | losses | marking)
-----------|---------------------|----------------------|------------------------
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 federal
| 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 civilian workers covered by
the Unemployment Compensation for Federal Employees (UCFE) program, employment and wage data are
compiled from quarterly reports submitted 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 9.8 million
employer reports of employment and wages submitted by states to the BLS in 2017. These reports
are based on place of employment 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 effective, expanding
coverage to include most state and local government employees. In 2017, UI and UCFE programs
covered workers in 143.9 million jobs. The estimated 138.6 million workers in these jobs (after
adjustment for multiple jobholders) represented 96.4 percent of civilian wage and salary
employment. Covered workers received $7.968 trillion in pay, representing 94.3 percent of the
wage and salary component of personal income and 40.9 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. Coverage changes
may affect the over-the-year comparisons presented in this news release.
Concepts and methodology
Monthly employment is based on the number of workers who worked during or received pay for
the pay period including the 12th of the month. With few exceptions, all employees of covered
firms are reported, including production and sales workers, corporation officials, executives,
supervisory personnel, and clerical workers. Workers on paid vacations and part-time workers also
are included.
Average weekly wage values are calculated by dividing quarterly total wages by the average of the
three monthly employment levels (all employees, as described above) and dividing the result by
13, for the 13 weeks in the quarter. These calculations are made using unrounded employment and
wage values. The average wage values that can be calculated using rounded data from the BLS
database may differ from the averages reported. Included in the quarterly wage data are non-wage
cash payments such as bonuses, the cash value of meals and lodging when supplied, tips and other
gratuities, and, in some states, employer contributions to certain deferred compensation plans such
as 401(k) plans and stock options. Over-the-year comparisons of average weekly wages may
reflect fluctuations in average monthly employment and/or total quarterly wages between the
current quarter and prior year levels.
Average weekly wages are affected by the ratio of full-time to part-time workers as well as the
number of individuals in high-paying and low-paying occupations and the incidence of pay periods
within a quarter. For instance, the average weekly wage of the workforce could increase
significantly when there is a large decline in the number of employees that had been receiving
below-average wages. Wages may include payments to workers not present in the employment
counts because they did not work during the pay period including the 12th of the month. When
comparing average weekly wage levels between industries, states, or quarters, these factors should
be taken into consideration.
Wages measured by QCEW may be subject to periodic and sometimes large fluctuations. This
variability may be due to calendar effects resulting from some quarters having more pay dates than
others. The effect is most visible in counties with a dominant employer. In particular, this effect
has been observed in counties where government employers represent a large fraction of overall
employment. Similar calendar effects can result from private sector pay practices. However, these
effects are typically less pronounced for two reasons: employment is less concentrated in a single
private employer, and private employers use a variety of pay period types (weekly, biweekly,
semimonthly, monthly).
For example, the effect on over-the-year pay comparisons can be pronounced in federal
government due to the uniform nature of federal payroll processing. Most federal employees are
paid on a biweekly pay schedule. As a result, in some quarters federal wages include six pay dates,
while in other quarters there are seven pay dates. Over-the-year comparisons of average weekly
wages may also reflect this calendar effect. Growth in average weekly wages may be attributed, in
part, to a comparison of quarterly wages for the current year, which include seven pay dates, with
year-ago wages that reflect only six pay dates. An opposite effect will occur when wages in the
current quarter reflecting six pay dates are compared with year-ago wages for a quarter including
seven pay dates.
In order to ensure the highest possible quality of data, states verify with employers and update, if
necessary, the industry, location, and ownership classification of all establishments on a 3-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 individual
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
that reflect economic events or administrative changes. For example, economic change would
come from a firm relocating into the county; administrative change would come from a company
correcting its county designation.
The over-the-year changes of employment and wages presented in this release have been adjusted
to account for most of the administrative corrections made to the underlying establishment reports.
This is done by modifying the prior-year levels used to calculate the over-the-year changes.
Percent changes are calculated using an adjusted version of the final 2017 quarterly data as the
base data. The adjusted prior-year levels used to calculate the over-the-year percent change in
employment and wages are not published. These adjusted prior-year levels do not match the
unadjusted data maintained on the BLS Web site. Over-the-year change calculations based on data
from the Web site, or from data published in prior BLS news releases, may differ substantially
from the over-the-year changes presented in this news release.
The adjusted data used to calculate the over-the-year change measures presented in this release
eliminate the effect of most of the administrative changes (those occurring when employers update
the industry, location, and ownership information of their establishments). The most common
adjustments for administrative change are the result of updated information about the county
location of individual establishments. Included in these adjustments are administrative changes
involving the classification of establishments that were previously reported in the unknown or
statewide county or unknown industry categories. Adjusted data account for improvements in
reporting employment and wages for individual and multi-unit establishments. To accomplish this,
adjustments were implemented to account for: administrative changes caused by multi-unit
employers who start reporting for each individual establishment rather than as a single entity (first
quarter of 2008); selected large administrative changes in employment and wages (second quarter
of 2011); and state verified improvements in reporting of employment and wages (third quarter of
2014). These adjustments allow QCEW to include county employment and wage growth rates in
this news release that would otherwise not meet publication standards.
The adjusted data used to calculate the over-the-year change measures presented in any County
Employment and Wages news release are valid for comparisons between the starting and ending
points (a 12-month period) used in that particular release. Comparisons may not be valid for any
time period other than the one featured in a release even if the changes were calculated using
adjusted data.
County definitions are assigned according to Federal Information Processing Standards
Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after
approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology
Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104-106.
Areas shown as counties include those designated as independent cities in some jurisdictions and,
in Alaska, those designated as census areas where counties have not been created. County data also
are presented for the New England states for comparative purposes even though townships are the
more common designation used in New England (and New Jersey). The regions 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 2016 edition
of this publication, which was published in September 2017, contains selected data produced by
Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the
first quarter 2017 version of this news release. Tables and additional content from the 2016 edition
of Employment and Wages Annual Averages Online are now available at
www.bls.gov/cew/cewbultn16.htm. The 2017 edition of Employment and Wages Annual Averages
Online will be available in September 2018.
News releases on quarterly measures of gross job flows also are available from BED at
www.bls.gov/bdm, (202) 691-6467, or data.bls.gov/cgi-bin/forms/bdm.
Information in this release will be made available to sensory impaired individuals upon request.
Voice phone: (202) 691-5200; TDD message referral phone number: (800) 877-8339.
Table 1. Covered establishments, employment, and wages in the 350 largest counties,
first quarter 2018
Employment Average weekly wage(2)
Establishments,
County(1) first quarter Percent Ranking Percent Ranking
2018 March change, by First change, by
(thousands) 2018 March percent quarter first percent
(thousands) 2017-18(3) change 2018 quarter change
2017-18(3)
United States(4)......... 10,008.0 144,562.9 1.6 - $1,152 3.7 -
Jefferson, AL............ 18.7 347.1 1.7 129 1,134 3.3 141
Madison, AL.............. 9.7 198.3 2.5 62 1,152 2.6 206
Mobile, AL............... 10.2 169.7 -0.2 325 901 3.2 152
Montgomery, AL........... 6.4 130.9 -0.9 344 870 0.7 322
Shelby, AL............... 5.8 84.8 1.2 181 1,101 4.0 85
Tuscaloosa, AL........... 4.6 93.6 1.4 158 878 5.1 34
Anchorage, AK............ 8.3 146.3 -0.1 319 1,120 2.5 214
Maricopa, AZ............. 99.0 1,983.6 3.2 36 1,084 3.3 141
Pima, AZ................. 18.9 368.4 0.9 222 921 4.1 78
Benton, AR............... 6.6 119.8 1.8 122 1,502 2.8 190
Pulaski, AR.............. 14.5 249.4 0.2 300 977 3.3 141
Washington, AR........... 6.1 107.7 2.9 48 852 -3.1 348
Alameda, CA.............. 64.0 779.8 2.4 70 1,516 4.2 70
Butte, CA................ 8.6 83.3 1.7 129 800 3.6 121
Contra Costa, CA......... 32.6 369.1 1.2 181 1,396 3.6 121
Fresno, CA............... 35.8 377.1 0.8 232 834 3.7 111
Kern, CA................. 19.4 303.0 0.6 267 914 2.9 180
Los Angeles, CA.......... 492.3 4,424.4 1.6 140 1,252 2.3 243
Marin, CA................ 12.5 114.7 1.2 181 1,415 7.1 14
Merced, CA............... 6.7 78.1 2.1 93 796 -1.1 342
Monterey, CA............. 13.8 178.4 3.4 29 926 3.0 172
Napa, CA................. 5.9 77.1 1.1 200 1,059 5.4 27
Orange, CA............... 121.6 1,617.5 2.1 93 1,258 3.2 152
Placer, CA............... 13.2 166.0 3.4 29 1,081 2.0 273
Riverside, CA............ 65.1 732.6 3.1 38 890 2.8 190
Sacramento, CA........... 58.5 655.7 2.3 76 1,174 2.4 228
San Bernardino, CA....... 59.8 744.5 3.1 38 902 3.0 172
San Diego, CA............ 111.7 1,452.7 2.1 93 1,218 3.9 93
San Francisco, CA........ 60.7 730.5 2.9 48 2,485 10.0 5
San Joaquin, CA.......... 18.0 248.2 2.0 103 879 3.3 141
San Luis Obispo, CA...... 10.4 117.6 0.8 232 919 4.3 65
San Mateo, CA............ 28.3 399.3 1.7 129 2,606 6.9 16
Santa Barbara, CA........ 15.5 195.8 1.7 129 1,019 0.2 335
Santa Clara, CA.......... 73.1 1,085.4 2.2 84 2,651 9.1 7
Santa Cruz, CA........... 9.6 101.2 1.0 212 992 3.9 93
Solano, CA............... 11.5 139.5 2.0 103 1,194 6.0 20
Sonoma, CA............... 20.1 206.9 1.6 140 1,030 5.2 29
Stanislaus, CA........... 15.8 186.9 2.4 70 905 2.7 197
Tulare, CA............... 10.6 154.9 -0.7 340 771 2.8 190
Ventura, CA.............. 27.4 326.0 0.7 247 1,100 -0.9 340
Yolo, CA................. 6.8 101.9 1.9 113 1,189 2.9 180
Adams, CO................ 11.2 209.0 4.5 9 1,046 2.4 228
Arapahoe, CO............. 22.3 328.0 1.7 129 1,377 3.5 124
Boulder, CO.............. 15.5 181.2 2.3 76 1,312 2.5 214
Denver, CO............... 33.0 511.0 2.9 48 1,458 4.1 78
Douglas, CO.............. 12.2 123.1 2.3 76 1,337 3.9 93
El Paso, CO.............. 20.1 272.4 2.2 84 977 3.2 152
Jefferson, CO............ 20.5 235.4 2.2 84 1,155 2.6 206
Larimer, CO.............. 12.4 158.4 3.1 38 1,026 4.4 59
Weld, CO................. 7.5 108.2 4.7 6 1,040 6.0 20
Fairfield, CT............ 35.7 414.5 -0.3 335 1,959 0.4 329
Hartford, CT............. 28.2 504.6 0.2 300 1,467 3.7 111
New Haven, CT............ 24.5 362.0 0.3 293 1,100 2.3 243
New London, CT........... 7.6 122.3 -0.2 325 1,167 3.3 141
New Castle, DE........... 19.9 286.6 0.8 232 1,386 1.2 315
Sussex, DE............... 6.9 77.0 3.6 21 788 3.8 101
Washington, DC........... 41.3 770.2 1.2 181 1,917 1.9 278
Alachua, FL.............. 7.2 132.0 1.4 158 940 7.3 13
Bay, FL.................. 5.7 78.3 1.0 212 756 2.0 273
Brevard, FL.............. 16.1 213.9 3.3 32 940 2.1 264
Broward, FL.............. 70.1 808.9 1.3 170 1,047 4.9 39
Collier, FL.............. 14.2 152.0 1.3 170 929 5.2 29
Duval, FL................ 29.8 513.4 3.3 32 1,100 5.0 36
Escambia, FL............. 8.2 134.8 1.4 158 879 3.4 132
Hillsborough, FL......... 43.0 686.9 1.6 140 1,105 4.0 85
Lake, FL................. 8.3 98.6 1.8 122 712 4.2 70
Lee, FL.................. 22.4 267.9 3.0 41 858 2.9 180
Leon, FL................. 8.8 150.8 2.3 76 865 3.3 141
Manatee, FL.............. 11.1 125.6 1.5 149 821 4.3 65
Marion, FL............... 8.5 103.0 1.4 158 723 4.0 85
Miami-Dade, FL........... 99.8 1,147.0 1.4 158 1,101 4.5 56
Okaloosa, FL............. 6.5 85.1 2.1 93 855 1.3 310
Orange, FL............... 43.0 846.8 3.5 25 982 4.1 78
Osceola, FL.............. 7.2 94.5 4.0 16 713 1.9 278
Palm Beach, FL........... 57.3 613.1 1.6 140 1,086 3.1 160
Pasco, FL................ 11.1 120.1 2.9 48 733 2.4 228
Pinellas, FL............. 33.5 435.9 2.4 70 947 4.1 78
Polk, FL................. 13.5 219.6 1.2 181 824 1.4 307
Sarasota, FL............. 16.1 173.0 1.8 122 924 7.7 11
Seminole, FL............. 15.1 193.8 3.6 21 940 4.3 65
Volusia, FL.............. 14.5 174.4 1.2 181 762 2.6 206
Bibb, GA................. 4.2 82.8 1.0 212 855 2.4 228
Chatham, GA.............. 8.1 156.3 3.5 25 932 3.1 160
Clayton, GA.............. 4.0 121.3 1.8 122 1,320 11.3 3
Cobb, GA................. 22.1 361.3 2.0 103 1,218 1.7 293
DeKalb, GA............... 17.9 298.7 0.8 232 1,169 2.4 228
Fulton, GA............... 43.9 868.9 3.0 41 1,672 0.3 332
Gwinnett, GA............. 25.2 353.2 2.2 84 1,054 0.4 329
Hall, GA................. 4.5 87.4 2.2 84 879 1.9 278
Muscogee, GA............. 4.6 94.9 1.2 181 963 8.7 8
Richmond, GA............. 4.4 106.3 1.9 113 867 -0.1 337
Honolulu, HI............. 26.2 474.8 -0.2 325 1,015 1.8 285
Maui + Kalawao, HI....... 6.3 78.1 0.8 232 882 4.4 59
Ada, ID.................. 15.8 239.9 4.5 9 943 5.1 34
Champaign, IL............ 4.0 89.6 0.3 293 912 2.5 214
Cook, IL................. 138.7 2,565.0 0.7 247 1,420 3.7 111
DuPage, IL............... 34.6 612.0 -0.1 319 1,309 2.7 197
Kane, IL................. 12.5 211.6 0.6 267 953 2.6 206
Lake, IL................. 20.3 328.8 2.0 103 1,686 4.6 51
McHenry, IL.............. 7.8 95.7 0.7 247 861 2.0 273
McLean, IL............... 3.4 82.7 -0.3 335 1,114 -2.5 347
Madison, IL.............. 5.4 100.6 2.6 59 837 1.3 310
Peoria, IL............... 4.2 105.4 2.8 53 1,440 23.8 1
St. Clair, IL............ 5.1 93.0 -0.7 340 809 0.9 321
Sangamon, IL............. 4.8 128.9 -0.2 325 1,069 4.4 59
Will, IL................. 14.7 239.1 1.0 212 911 2.5 214
Winnebago, IL............ 6.0 125.5 0.4 282 942 2.3 243
Allen, IN................ 8.9 185.1 1.1 200 929 3.8 101
Elkhart, IN.............. 4.7 137.5 4.7 6 1,006 3.8 101
Hamilton, IN............. 9.5 139.8 2.3 76 1,134 3.8 101
Lake, IN................. 10.4 185.9 0.7 247 920 2.1 264
Marion, IN............... 24.2 591.9 0.5 273 1,218 5.0 36
St. Joseph, IN........... 5.8 122.3 -0.1 319 857 3.8 101
Tippecanoe, IN........... 3.4 83.9 1.2 181 964 6.6 17
Vanderburgh, IN.......... 4.8 108.4 1.9 113 888 2.3 243
Johnson, IA.............. 4.3 84.0 0.5 273 976 2.4 228
Linn, IA................. 6.9 129.3 0.7 247 1,039 1.9 278
Polk, IA................. 17.6 296.6 1.1 200 1,163 1.7 293
Scott, IA................ 5.7 89.4 -0.2 325 876 2.5 214
Johnson, KS.............. 23.3 344.0 1.8 122 1,131 1.8 285
Sedgwick, KS............. 12.5 247.8 0.3 293 967 2.4 228
Shawnee, KS.............. 5.0 96.3 -0.5 339 903 2.3 243
Wyandotte, KS............ 3.4 88.2 1.1 200 1,025 2.1 264
Boone, KY................ 4.5 91.1 5.9 3 905 0.1 336
Fayette, KY.............. 11.1 191.4 0.1 310 925 2.5 214
Jefferson, KY............ 25.4 464.4 0.6 267 1,118 2.0 273
Caddo, LA................ 7.2 111.6 -0.9 344 833 2.2 253
Calcasieu, LA............ 5.4 101.9 5.0 5 969 4.1 78
East Baton Rouge, LA..... 15.8 267.8 0.4 282 1,024 2.4 228
Jefferson, LA............ 14.0 188.3 -0.8 342 935 1.0 319
Lafayette, LA............ 9.7 129.3 0.0 315 889 2.2 253
Orleans, LA.............. 12.9 194.8 0.7 247 1,059 4.0 85
St. Tammany, LA.......... 8.4 87.3 1.1 200 901 2.9 180
Cumberland, ME........... 13.8 183.9 4.0 16 1,055 3.9 93
Anne Arundel, MD......... 15.2 268.7 0.7 247 1,165 3.9 93
Baltimore, MD............ 21.2 375.6 0.2 300 1,109 3.1 160
Frederick, MD............ 6.4 101.4 1.4 158 984 -0.1 337
Harford, MD.............. 5.8 92.8 1.8 122 989 -1.4 343
Howard, MD............... 10.0 168.3 -0.2 325 1,348 2.6 206
Montgomery, MD........... 32.7 469.1 0.2 300 1,586 5.9 22
Prince George's, MD...... 16.0 316.2 0.5 273 1,112 2.2 253
Baltimore City, MD....... 13.6 343.1 2.5 62 1,277 1.8 285
Barnstable, MA........... 9.6 86.4 0.2 300 926 2.2 253
Bristol, MA.............. 17.8 222.6 0.0 315 954 -1.5 344
Essex, MA................ 26.2 320.6 0.5 273 1,180 3.1 160
Hampden, MA.............. 18.6 206.1 0.7 247 982 1.8 285
Middlesex, MA............ 55.7 908.8 1.7 129 1,795 4.2 70
Norfolk, MA.............. 25.5 349.8 0.8 232 1,288 1.3 310
Plymouth, MA............. 16.2 189.6 1.3 170 1,003 4.2 70
Suffolk, MA.............. 30.5 669.0 1.8 122 2,268 12.1 2
Worcester, MA............ 25.8 345.4 0.7 247 1,094 1.3 310
Genesee, MI.............. 6.8 132.5 0.4 282 889 1.7 293
Ingham, MI............... 6.0 151.1 0.2 300 1,034 4.7 46
Kalamazoo, MI............ 5.0 119.1 0.8 232 1,046 1.7 293
Kent, MI................. 14.5 403.4 2.2 84 950 2.3 243
Macomb, MI............... 17.6 329.1 2.2 84 1,141 2.6 206
Oakland, MI.............. 39.4 727.9 1.3 170 1,277 3.1 160
Ottawa, MI............... 5.6 124.7 1.6 140 935 4.8 41
Saginaw, MI.............. 3.9 82.1 -1.3 348 901 5.3 28
Washtenaw, MI............ 8.2 213.5 1.6 140 1,132 2.3 243
Wayne, MI................ 31.0 716.5 0.7 247 1,268 3.8 101
Anoka, MN................ 7.3 122.0 0.7 247 985 3.7 111
Dakota, MN............... 10.1 185.5 -0.2 325 1,100 2.4 228
Hennepin, MN............. 41.4 919.2 1.0 212 1,497 1.7 293
Olmsted, MN.............. 3.5 98.0 1.7 129 1,270 3.5 124
Ramsey, MN............... 13.6 328.1 0.4 282 1,346 -1.0 341
St. Louis, MN............ 5.4 96.4 0.2 300 870 4.7 46
Stearns, MN.............. 4.4 85.3 -0.1 319 932 1.6 302
Washington, MN........... 5.7 84.6 2.1 93 954 2.6 206
Harrison, MS............. 4.6 85.2 0.1 310 754 2.9 180
Hinds, MS................ 5.8 120.6 -0.8 342 903 1.9 278
Boone, MO................ 5.0 93.6 0.2 300 829 0.5 326
Clay, MO................. 5.7 102.6 1.5 149 951 1.8 285
Greene, MO............... 9.1 165.8 1.2 181 813 1.2 315
Jackson, MO.............. 22.2 366.2 -0.3 335 1,087 1.7 293
St. Charles, MO.......... 9.7 146.5 0.7 247 959 5.2 29
St. Louis, MO............ 39.5 600.9 0.7 247 1,202 4.9 39
St. Louis City, MO....... 14.8 227.8 1.4 158 1,249 3.9 93
Yellowstone, MT.......... 6.6 80.2 -0.1 319 912 1.4 307
Douglas, NE.............. 19.0 336.5 0.3 293 1,034 3.0 172
Lancaster, NE............ 10.3 169.5 1.3 170 877 3.7 111
Clark, NV................ 55.0 982.8 2.6 59 970 5.0 36
Washoe, NV............... 14.9 218.2 2.3 76 956 5.2 29
Hillsborough, NH......... 12.1 201.9 0.4 282 1,242 8.6 9
Merrimack, NH............ 5.1 77.2 1.1 200 1,002 4.2 70
Rockingham, NH........... 10.9 145.9 0.8 232 1,085 3.8 101
Atlantic, NJ............. 6.6 119.8 -0.2 325 907 2.3 243
Bergen, NJ............... 33.3 439.3 1.3 170 1,315 2.1 264
Burlington, NJ........... 11.1 202.5 1.4 158 1,138 3.2 152
Camden, NJ............... 12.1 203.9 0.4 282 1,045 3.7 111
Essex, NJ................ 20.7 341.8 0.6 267 1,506 2.6 206
Gloucester, NJ........... 6.4 110.2 2.7 56 893 2.1 264
Hudson, NJ............... 15.3 262.3 0.7 247 1,753 7.7 11
Mercer, NJ............... 11.2 247.4 1.3 170 1,531 2.4 228
Middlesex, NJ............ 22.5 424.1 1.0 212 1,363 2.9 180
Monmouth, NJ............. 20.2 255.6 1.4 158 1,120 4.8 41
Morris, NJ............... 17.2 289.7 1.2 181 1,808 1.5 305
Ocean, NJ................ 13.5 164.0 3.2 36 862 1.7 293
Passaic, NJ.............. 12.7 165.1 0.4 282 1,043 2.2 253
Somerset, NJ............. 10.3 184.7 0.7 247 2,078 2.5 214
Union, NJ................ 14.5 225.3 2.1 93 1,400 0.4 329
Bernalillo, NM........... 18.7 326.0 0.3 293 916 2.1 264
Albany, NY............... 10.4 231.2 -0.2 325 1,102 2.7 197
Bronx, NY................ 19.1 316.8 1.7 129 1,040 2.7 197
Broome, NY............... 4.5 85.5 0.1 310 869 4.6 51
Dutchess, NY............. 8.4 111.9 0.9 222 1,036 2.4 228
Erie, NY................. 24.7 464.6 0.6 267 996 3.0 172
Kings, NY................ 63.8 756.7 4.7 6 920 2.0 273
Monroe, NY............... 19.0 384.0 0.8 232 1,002 3.2 152
Nassau, NY............... 54.3 628.7 1.5 149 1,195 2.7 197
New York, NY............. 128.9 2,446.5 1.0 212 3,087 2.9 180
Oneida, NY............... 5.3 105.0 0.3 293 843 3.2 152
Onondaga, NY............. 12.8 241.6 0.8 232 1,002 3.0 172
Orange, NY............... 10.5 144.0 2.4 70 899 1.2 315
Queens, NY............... 53.8 693.7 1.9 113 1,071 1.8 285
Richmond, NY............. 10.0 120.7 1.4 158 971 2.8 190
Rockland, NY............. 11.0 124.1 2.4 70 1,064 2.2 253
Saratoga, NY............. 6.0 86.7 2.9 48 992 3.3 141
Suffolk, NY.............. 53.2 645.1 -0.1 319 1,143 1.2 315
Westchester, NY.......... 36.4 424.6 0.9 222 1,526 3.3 141
Buncombe, NC............. 9.4 131.1 2.2 84 815 2.5 214
Cabarrus, NC............. 4.8 75.7 2.2 84 793 2.1 264
Catawba, NC.............. 4.4 87.8 0.5 273 841 1.8 285
Cumberland, NC........... 6.3 120.1 0.9 222 800 1.4 307
Durham, NC............... 8.4 202.0 1.9 113 1,428 2.9 180
Forsyth, NC.............. 9.2 185.4 1.4 158 1,052 -4.8 349
Guilford, NC............. 14.5 281.1 0.9 222 953 2.5 214
Mecklenburg, NC.......... 38.4 688.2 2.0 103 1,518 3.5 124
New Hanover, NC.......... 8.3 113.1 1.5 149 874 2.2 253
Pitt, NC................. 3.8 77.4 2.8 53 853 2.8 190
Wake, NC................. 35.2 552.2 3.0 41 1,151 3.7 111
Cass, ND................. 7.2 116.0 0.7 247 970 3.1 160
Butler, OH............... 7.9 153.2 1.5 149 1,005 1.3 310
Cuyahoga, OH............. 36.0 715.6 0.9 222 1,150 3.0 172
Delaware, OH............. 5.4 86.2 1.9 113 1,205 2.7 197
Franklin, OH............. 32.3 744.3 1.6 140 1,148 3.0 172
Hamilton, OH............. 23.9 510.5 0.5 273 1,209 0.6 325
Lake, OH................. 6.3 93.8 0.7 247 888 2.1 264
Lorain, OH............... 6.2 96.4 1.1 200 848 2.8 190
Lucas, OH................ 10.1 207.3 0.2 300 998 5.7 23
Mahoning, OH............. 5.9 96.1 0.5 273 747 2.5 214
Montgomery, OH........... 11.9 253.6 1.2 181 920 2.4 228
Stark, OH................ 8.6 158.7 1.5 149 816 4.6 51
Summit, OH............... 14.3 262.8 0.4 282 981 1.0 319
Warren, OH............... 5.1 91.7 1.0 212 1,035 3.5 124
Cleveland, OK............ 5.9 81.1 2.1 93 759 2.2 253
Oklahoma, OK............. 28.3 452.0 2.1 93 1,064 4.0 85
Tulsa, OK................ 22.7 355.0 1.5 149 1,010 2.5 214
Clackamas, OR............ 15.3 163.7 1.1 200 1,008 4.0 85
Deschutes, OR............ 8.8 81.2 4.1 14 868 3.7 111
Jackson, OR.............. 7.6 88.5 3.3 32 791 2.3 243
Lane, OR................. 12.3 155.4 1.2 181 827 3.4 132
Marion, OR............... 11.0 152.7 2.0 103 867 2.8 190
Multnomah, OR............ 35.6 507.2 1.7 129 1,170 5.2 29
Washington, OR........... 19.7 293.6 2.5 62 1,419 4.7 46
Allegheny, PA............ 35.5 691.3 1.2 181 1,238 3.1 160
Berks, PA................ 9.0 171.8 1.2 181 976 4.2 70
Bucks, PA................ 20.0 261.8 1.2 181 1,002 2.5 214
Butler, PA............... 5.1 84.9 0.1 310 967 0.5 326
Chester, PA.............. 15.6 247.7 1.3 170 1,479 4.2 70
Cumberland, PA........... 6.5 132.7 0.4 282 997 3.5 124
Dauphin, PA.............. 7.5 180.5 1.9 113 1,085 2.5 214
Delaware, PA............. 14.2 222.5 1.2 181 1,272 4.3 65
Erie, PA................. 7.0 120.2 0.0 315 825 3.1 160
Lackawanna, PA........... 5.7 97.2 1.2 181 808 4.1 78
Lancaster, PA............ 13.6 238.3 2.1 93 902 2.2 253
Lehigh, PA............... 8.8 188.9 2.0 103 1,073 0.7 322
Luzerne, PA.............. 7.4 143.6 1.3 170 837 1.6 302
Montgomery, PA........... 27.7 490.0 1.0 212 1,497 3.5 124
Northampton, PA.......... 6.8 113.4 0.4 282 932 1.7 293
Philadelphia, PA......... 34.9 677.2 1.5 149 1,322 3.4 132
Washington, PA........... 5.5 86.0 1.6 140 1,228 3.3 141
Westmoreland, PA......... 9.3 131.9 0.5 273 880 4.5 56
York, PA................. 9.2 178.0 0.9 222 936 3.3 141
Kent, RI................. 5.5 74.2 0.9 222 978 2.2 253
Providence, RI........... 18.5 284.0 0.8 232 1,145 3.1 160
Charleston, SC........... 15.6 249.3 2.5 62 981 3.4 132
Greenville, SC........... 14.5 271.6 2.5 62 936 2.7 197
Horry, SC................ 9.2 126.6 2.8 53 631 0.5 326
Lexington, SC............ 6.8 118.8 3.4 29 803 -2.2 345
Richland, SC............. 10.4 221.6 0.1 310 945 1.9 278
Spartanburg, SC.......... 6.4 141.1 3.7 20 927 4.6 51
York, SC................. 5.9 94.3 3.0 41 935 3.4 132
Minnehaha, SD............ 7.3 125.3 1.1 200 948 2.7 197
Davidson, TN............. 23.2 488.4 2.7 56 1,228 6.2 19
Hamilton, TN............. 9.9 203.5 2.0 103 963 2.4 228
Knox, TN................. 12.4 237.3 0.9 222 982 4.4 59
Rutherford, TN........... 5.8 129.3 3.5 25 906 0.3 332
Shelby, TN............... 20.8 492.5 1.1 200 1,074 1.6 302
Williamson, TN........... 9.0 132.7 4.2 13 1,280 2.1 264
Bell, TX................. 5.5 118.4 0.8 232 876 0.7 322
Bexar, TX................ 41.6 860.6 1.2 181 1,009 2.5 214
Brazoria, TX............. 5.9 110.9 1.7 129 1,206 3.5 124
Brazos, TX............... 4.6 105.8 3.3 32 805 5.5 25
Cameron, TX.............. 6.5 139.3 1.5 149 628 2.3 243
Collin, TX............... 25.6 409.9 3.6 21 1,374 3.4 132
Dallas, TX............... 77.4 1,684.9 1.6 140 1,426 3.4 132
Denton, TX............... 15.3 242.1 2.3 76 984 0.3 332
El Paso, TX.............. 15.3 304.0 0.8 232 744 2.9 180
Fort Bend, TX............ 13.6 185.3 4.3 12 1,050 3.2 152
Galveston, TX............ 6.2 109.0 0.0 315 1,013 7.0 15
Harris, TX............... 115.4 2,287.9 1.3 170 1,495 3.5 124
Hidalgo, TX.............. 12.5 261.3 1.9 113 657 2.7 197
Jefferson, TX............ 5.9 122.2 -1.1 346 1,172 4.5 56
Lubbock, TX.............. 7.6 139.0 0.9 222 830 4.3 65
McLennan, TX............. 5.3 111.8 0.2 300 895 4.8 41
Midland, TX.............. 5.6 99.6 12.6 1 1,510 5.7 23
Montgomery, TX........... 11.6 185.0 5.6 4 1,150 5.5 25
Nueces, TX............... 8.3 163.3 -0.3 335 920 1.8 285
Potter, TX............... 3.9 77.7 0.3 293 847 3.8 101
Smith, TX................ 6.3 102.4 1.0 212 856 3.8 101
Tarrant, TX.............. 43.9 887.6 2.1 93 1,108 4.4 59
Travis, TX............... 41.4 738.6 2.7 56 1,307 4.0 85
Webb, TX................. 5.5 100.9 1.1 200 690 2.4 228
Williamson, TX........... 11.1 169.7 3.8 19 1,171 3.4 132
Davis, UT................ 8.6 127.1 2.0 103 867 4.7 46
Salt Lake, UT............ 44.9 692.1 2.5 62 1,081 4.1 78
Utah, UT................. 16.4 239.9 6.0 2 930 9.7 6
Weber, UT................ 6.1 106.1 3.5 25 808 3.1 160
Chittenden, VT........... 6.9 100.4 1.1 200 1,055 3.6 121
Arlington, VA............ 9.3 175.9 1.2 181 1,925 3.9 93
Chesterfield, VA......... 9.2 136.2 1.9 113 942 3.1 160
Fairfax, VA.............. 37.5 603.9 1.4 158 1,802 3.0 172
Henrico, VA.............. 11.7 189.9 1.3 170 1,113 1.5 305
Loudoun, VA.............. 12.5 165.4 2.6 59 1,289 3.1 160
Prince William, VA....... 9.4 128.4 2.5 62 936 4.0 85
Alexandria City, VA...... 6.4 91.5 -1.2 347 1,499 2.4 228
Chesapeake City, VA...... 6.1 101.1 2.0 103 850 2.2 253
Newport News City, VA.... 3.9 100.7 4.1 14 1,037 -2.4 346
Norfolk City, VA......... 6.0 142.7 0.7 247 1,052 2.9 180
Richmond City, VA........ 7.8 155.1 0.7 247 1,308 4.4 59
Virginia Beach City, VA.. 12.3 175.6 -0.2 325 823 3.4 132
Benton, WA............... 5.7 87.8 3.6 21 1,060 1.9 278
Clark, WA................ 14.6 159.8 4.5 9 1,011 4.8 41
King, WA................. 86.3 1,375.1 3.0 41 1,761 10.1 4
Kitsap, WA............... 6.6 88.5 3.0 41 960 3.7 111
Pierce, WA............... 21.8 306.9 2.4 70 979 3.7 111
Snohomish, WA............ 20.7 284.6 0.7 247 1,278 8.6 9
Spokane, WA.............. 15.6 220.8 2.5 62 934 3.3 141
Thurston, WA............. 8.3 115.7 3.0 41 981 4.7 46
Whatcom, WA.............. 7.3 90.3 2.3 76 923 4.8 41
Yakima, WA............... 7.7 111.9 4.0 16 758 4.6 51
Kanawha, WV.............. 5.7 98.2 -1.4 349 934 1.7 293
Brown, WI................ 7.0 156.6 1.7 129 997 3.9 93
Dane, WI................. 15.8 332.1 0.8 232 1,144 4.2 70
Milwaukee, WI............ 26.8 485.5 0.5 273 1,096 3.8 101
Outagamie, WI............ 5.4 106.6 0.6 267 930 3.2 152
Waukesha, WI............. 13.3 239.9 0.4 282 1,142 6.5 18
Winnebago, WI............ 3.8 93.2 0.8 232 1,006 -0.7 339
San Juan, PR............. 10.4 241.8 -1.0 (5) 696 10.1 (5)
(1) Includes areas not officially designated as counties. See Technical Note.
(2) Average weekly wages were calculated using unrounded data.
(3) Percent changes were computed from employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(4) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
(5) This county was not included in the U.S. rankings.
Note: Data are preliminary. Includes workers covered by Unemployment Insurance (UI) and Unemployment
Compensation for Federal Employees (UCFE) programs. These 349 U.S. counties comprise 73.1 percent of
the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,
first quarter 2018
Employment Average weekly
wage(1)
Establishments,
first quarter
County by NAICS supersector 2018 Percent Percent
(thousands) March change, First change,
2018 March quarter first
(thousands) 2017-18(2) 2018 quarter
2017-18(2)
United States(3) ............................ 10,008.0 144,562.9 1.6 $1,152 3.7
Private industry........................... 9,709.0 122,643.6 1.8 1,164 3.8
Natural resources and mining............. 137.1 1,792.7 2.3 1,280 5.7
Construction............................. 796.3 6,896.4 4.0 1,166 3.4
Manufacturing............................ 349.7 12,529.8 1.6 1,407 4.3
Trade, transportation, and utilities..... 1,919.3 26,979.5 1.1 942 3.4
Information.............................. 167.1 2,804.9 0.3 2,373 6.5
Financial activities..................... 883.7 8,108.5 1.3 2,388 4.8
Professional and business services....... 1,812.1 20,497.9 1.9 1,530 3.7
Education and health services............ 1,684.4 22,524.5 1.8 942 2.7
Leisure and hospitality.................. 849.9 15,763.7 1.6 446 3.5
Other services........................... 846.2 4,427.1 1.0 734 3.2
Government................................. 298.9 21,919.3 0.2 1,088 2.4
Los Angeles, CA.............................. 492.3 4,424.4 1.6 1,252 2.3
Private industry........................... 486.0 3,847.1 1.8 1,227 2.2
Natural resources and mining............. 0.5 6.1 -19.5 1,172 20.3
Construction............................. 14.4 140.4 3.8 1,262 6.4
Manufacturing............................ 12.2 342.6 -2.2 1,518 5.1
Trade, transportation, and utilities..... 54.4 826.0 0.6 1,016 2.8
Information.............................. 10.3 207.9 4.9 2,572 1.1
Financial activities..................... 26.7 219.1 0.3 2,385 -0.1
Professional and business services....... 48.8 600.5 0.8 1,535 0.7
Education and health services............ 233.7 794.9 1.9 896 4.7
Leisure and hospitality.................. 33.6 520.7 1.7 639 2.7
Other services........................... 26.5 148.5 -1.0 732 4.3
Government................................. 6.2 577.3 0.0 1,421 3.4
Cook, IL..................................... 138.7 2,565.0 0.7 1,420 3.7
Private industry........................... 137.5 2,273.1 0.8 1,441 3.9
Natural resources and mining............. 0.1 1.2 4.7 1,048 1.3
Construction............................. 10.7 70.5 2.9 1,517 3.0
Manufacturing............................ 5.8 183.5 0.4 1,378 2.1
Trade, transportation, and utilities..... 27.9 464.6 0.1 1,101 3.6
Information.............................. 2.4 52.2 -0.3 2,340 6.1
Financial activities..................... 13.9 196.9 0.4 3,882 5.6
Professional and business services....... 29.0 472.3 0.9 1,737 3.8
Education and health services............ 15.5 450.9 1.4 992 2.7
Leisure and hospitality.................. 13.8 279.0 0.8 518 2.6
Other services........................... 15.8 100.3 2.6 980 4.4
Government................................. 1.2 291.9 -0.5 1,260 2.9
New York, NY................................. 128.9 2,446.5 1.0 3,087 2.9
Private industry........................... 127.5 2,217.8 1.2 3,248 2.9
Natural resources and mining............. 0.0 0.2 16.3 2,326 -6.7
Construction............................. 2.3 42.4 3.6 1,967 3.1
Manufacturing............................ 2.0 24.1 -3.3 1,831 7.0
Trade, transportation, and utilities..... 19.4 249.7 -1.4 1,525 3.0
Information.............................. 5.0 173.5 3.6 3,536 4.8
Financial activities..................... 19.5 379.2 2.1 9,440 0.9
Professional and business services....... 27.3 581.1 0.9 2,757 3.6
Education and health services............ 10.2 354.8 0.8 1,345 5.1
Leisure and hospitality.................. 14.8 303.8 1.2 910 4.2
Other services........................... 20.4 104.1 1.3 1,281 2.2
Government................................. 1.4 228.7 -0.2 1,521 2.5
Harris, TX................................... 115.4 2,287.9 1.3 1,495 3.5
Private industry........................... 114.9 2,007.9 1.4 1,545 3.6
Natural resources and mining............. 1.6 65.8 -1.3 4,887 4.8
Construction............................. 7.5 159.9 2.2 1,463 2.7
Manufacturing............................ 4.8 171.1 1.8 1,926 6.2
Trade, transportation, and utilities..... 24.8 464.9 1.7 1,393 3.2
Information.............................. 1.2 26.0 -4.4 1,643 2.1
Financial activities..................... 12.2 127.4 1.4 2,423 3.5
Professional and business services....... 23.2 396.6 1.5 1,900 4.7
Education and health services............ 16.1 292.6 1.1 1,019 2.1
Leisure and hospitality.................. 10.2 234.1 1.4 456 2.9
Other services........................... 11.7 66.4 0.2 837 1.6
Government................................. 0.6 280.0 0.5 1,129 1.5
Maricopa, AZ................................. 99.0 1,983.6 3.2 1,084 3.3
Private industry........................... 98.3 1,771.3 3.6 1,089 3.3
Natural resources and mining............. 0.4 8.3 2.5 1,319 9.7
Construction............................. 7.4 117.5 9.2 1,131 5.6
Manufacturing............................ 3.2 122.2 5.3 1,632 7.2
Trade, transportation, and utilities..... 18.6 378.6 2.5 995 3.2
Information.............................. 1.5 36.8 0.9 1,715 10.6
Financial activities..................... 11.5 179.7 3.1 1,638 6.7
Professional and business services....... 21.7 332.1 2.7 1,144 0.5
Education and health services............ 11.4 310.4 4.1 1,005 0.4
Leisure and hospitality.................. 8.2 226.9 3.2 496 3.8
Other services........................... 6.5 52.3 1.2 757 -6.5
Government................................. 0.7 212.3 -0.3 1,039 2.6
Dallas, TX................................... 77.4 1,684.9 1.6 1,426 3.4
Private industry........................... 76.8 1,510.0 1.7 1,456 3.5
Natural resources and mining............. 0.5 8.3 20.0 5,013 0.1
Construction............................. 4.7 86.9 1.0 1,318 3.3
Manufacturing............................ 2.8 111.8 1.4 1,956 2.2
Trade, transportation, and utilities..... 15.9 343.8 3.4 1,165 3.3
Information.............................. 1.4 49.7 -3.5 2,659 4.0
Financial activities..................... 9.6 163.1 0.8 2,375 2.9
Professional and business services....... 17.6 344.4 1.8 1,628 4.6
Education and health services............ 9.6 197.8 0.9 1,107 3.7
Leisure and hospitality.................. 6.9 159.5 1.6 509 0.4
Other services........................... 7.0 42.4 -1.2 913 10.9
Government................................. 0.6 174.9 0.0 1,164 2.5
Orange, CA................................... 121.6 1,617.5 2.1 1,258 3.2
Private industry........................... 120.2 1,460.6 2.2 1,240 3.5
Natural resources and mining............. 0.2 2.5 -15.5 850 -4.4
Construction............................. 6.8 103.0 4.5 1,426 6.1
Manufacturing............................ 5.0 158.2 -0.9 1,682 5.9
Trade, transportation, and utilities..... 17.1 255.3 1.0 1,086 1.7
Information.............................. 1.4 25.7 -2.2 2,381 4.8
Financial activities..................... 11.6 117.5 -0.3 2,101 2.9
Professional and business services....... 20.8 305.7 2.2 1,455 4.1
Education and health services............ 34.3 216.1 3.0 977 4.2
Leisure and hospitality.................. 8.7 217.8 2.1 501 5.5
Other services........................... 6.8 45.1 -2.3 715 1.7
Government................................. 1.4 157.0 0.9 1,428 0.6
San Diego, CA................................ 111.7 1,452.7 2.1 1,218 3.9
Private industry........................... 109.8 1,217.5 2.5 1,196 3.9
Natural resources and mining............. 0.6 9.5 5.8 755 7.5
Construction............................. 6.9 82.2 5.9 1,257 5.1
Manufacturing............................ 3.3 109.4 1.5 1,865 4.6
Trade, transportation, and utilities..... 14.4 219.7 0.5 947 3.4
Information.............................. 1.2 23.3 -1.5 1,888 0.7
Financial activities..................... 10.2 74.4 0.9 1,745 1.0
Professional and business services....... 18.4 243.8 3.4 1,733 5.4
Education and health services............ 32.2 200.9 1.8 984 3.1
Leisure and hospitality.................. 8.3 193.0 1.0 505 3.5
Other services........................... 7.3 50.2 -0.7 638 2.7
Government................................. 1.9 235.2 -0.2 1,330 4.1
King, WA..................................... 86.3 1,375.1 3.0 1,761 10.1
Private industry........................... 85.8 1,204.3 3.4 1,814 10.9
Natural resources and mining............. 0.4 2.7 -5.2 1,183 1.4
Construction............................. 6.7 71.5 4.6 1,426 4.2
Manufacturing............................ 2.5 101.3 -0.3 2,113 11.8
Trade, transportation, and utilities..... 14.0 267.1 4.3 1,709 11.8
Information.............................. 2.3 105.9 5.4 4,461 13.5
Financial activities..................... 6.7 69.6 4.4 2,237 6.3
Professional and business services....... 18.0 226.9 2.6 2,105 16.9
Education and health services............ 18.6 176.6 3.9 1,043 -1.1
Leisure and hospitality.................. 7.3 138.3 2.9 566 3.5
Other services........................... 9.2 44.5 1.5 912 4.9
Government................................. 0.5 170.9 0.3 1,385 2.9
Miami-Dade, FL............................... 99.8 1,147.0 1.4 1,101 4.5
Private industry........................... 99.5 1,007.6 1.6 1,080 4.7
Natural resources and mining............. 0.5 10.0 0.2 615 5.1
Construction............................. 6.8 49.2 1.4 1,066 7.5
Manufacturing............................ 2.9 40.4 0.9 930 3.2
Trade, transportation, and utilities..... 25.3 283.8 1.0 1,011 4.6
Information.............................. 1.6 18.8 0.2 2,003 0.9
Financial activities..................... 10.8 76.2 0.5 2,087 3.5
Professional and business services....... 22.4 161.1 2.5 1,300 6.5
Education and health services............ 10.8 182.7 2.8 972 1.7
Leisure and hospitality.................. 7.5 144.4 1.2 652 10.9
Other services........................... 8.5 39.5 -0.2 656 4.8
Government................................. 0.3 139.4 -0.2 1,248 3.0
(1) Average weekly wages were calculated using unrounded data.
(2) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(3) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
Note: Data are preliminary. Counties selected are based on 2017 annual average employment.
Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal
Employees (UCFE) programs.
Table 3. Covered establishments, employment, and wages by state,
first quarter 2018
Employment Average weekly
wage(1)
Establishments,
first quarter
State 2018 Percent Percent
(thousands) March change, First change,
2018 March quarter first
(thousands) 2017-18 2018 quarter
2017-18
United States(2)........... 10,008.0 144,562.9 1.6 $1,152 3.7
Alabama.................... 126.2 1,948.9 1.1 919 2.9
Alaska..................... 22.0 311.2 -0.5 1,074 2.3
Arizona.................... 162.2 2,822.5 2.8 1,025 3.5
Arkansas................... 90.7 1,211.4 0.9 879 2.4
California................. 1,548.3 17,152.5 2.1 1,352 4.4
Colorado................... 202.6 2,639.5 2.5 1,175 3.4
Connecticut................ 120.1 1,651.9 0.1 1,447 2.4
Delaware................... 32.2 438.7 1.2 1,202 1.3
District of Columbia....... 41.3 770.2 1.2 1,917 1.9
Florida.................... 693.2 8,716.8 2.2 988 4.1
Georgia.................... 281.4 4,409.1 2.3 1,095 2.3
Hawaii..................... 42.5 658.4 0.3 974 2.3
Idaho...................... 61.2 712.6 3.5 809 4.3
Illinois................... 373.7 5,909.3 1.0 1,241 3.9
Indiana.................... 166.9 3,018.8 1.2 954 3.9
Iowa....................... 102.6 1,525.8 0.5 921 2.4
Kansas..................... 88.3 1,370.6 0.2 912 2.7
Kentucky................... 123.4 1,873.7 0.5 901 2.5
Louisiana.................. 132.3 1,914.7 0.5 932 3.0
Maine...................... 53.8 592.1 0.9 891 3.6
Maryland................... 171.4 2,646.9 0.9 1,209 3.2
Massachusetts.............. 257.1 3,509.9 1.1 1,510 5.6
Michigan................... 245.5 4,289.0 1.4 1,078 3.4
Minnesota.................. 174.2 2,823.6 0.7 1,175 2.1
Mississippi................ 73.8 1,125.9 0.1 765 2.1
Missouri................... 207.4 2,777.6 0.5 960 3.1
Montana.................... 48.6 455.5 1.0 819 2.4
Nebraska................... 72.2 966.0 0.4 898 3.6
Nevada..................... 81.8 1,351.6 3.0 977 4.8
New Hampshire.............. 52.1 648.2 0.8 1,122 4.9
New Jersey................. 273.7 3,997.6 1.3 1,373 3.0
New Mexico................. 59.3 813.3 1.0 862 2.9
New York................... 649.1 9,318.9 1.8 1,597 3.4
North Carolina............. 279.2 4,370.6 1.8 1,022 3.0
North Dakota............... 31.6 408.2 0.6 988 3.7
Ohio....................... 297.5 5,328.5 0.9 1,005 2.9
Oklahoma................... 111.3 1,600.9 1.8 914 3.5
Oregon..................... 154.9 1,894.3 2.0 1,026 4.3
Pennsylvania............... 358.1 5,787.2 1.4 1,115 3.4
Rhode Island............... 37.6 469.9 1.1 1,086 3.2
South Carolina............. 133.6 2,067.4 2.2 877 1.7
South Dakota............... 33.5 417.5 1.0 842 2.8
Tennessee.................. 161.0 2,950.0 1.6 978 3.5
Texas...................... 686.3 12,179.2 2.0 1,168 3.9
Utah....................... 100.7 1,458.8 3.3 949 4.9
Vermont.................... 25.7 307.1 0.4 917 3.1
Virginia................... 276.4 3,854.4 1.5 1,162 3.0
Washington................. 239.1 3,316.1 2.8 1,306 7.7
West Virginia.............. 50.8 684.8 0.6 868 3.6
Wisconsin.................. 173.2 2,831.7 1.0 968 3.8
Wyoming.................... 26.2 263.7 0.3 914 3.9
Puerto Rico................ 44.3 856.7 -3.8 563 7.0
Virgin Islands............. 3.3 33.3 -15.5 969 24.4
(1) Average weekly wages were calculated using unrounded data.
(2) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
Note: Data are preliminary. Includes workers covered by Unemployment Insurance (UI) and
Unemployment Compensation for Federal Employees (UCFE) programs.
United States Department of Labor
