For release 10:00 a.m. (EDT), Wednesday, May 23, 2018 USDL-18-0868
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
COUNTY EMPLOYMENT AND WAGES
Fourth Quarter 2017
From December 2016 to December 2017, employment increased in 316 of the 346 largest U.S.
counties, the U.S. Bureau of Labor Statistics reported today. Midland, Texas, had the largest percentage
increase with a gain of 11.5 percent over the year, above the national job growth rate of 1.5 percent.
Within Midland, the largest employment increase occurred in natural resources and mining, which
gained 5,247 jobs over the year (27.1 percent). Shawnee, Kan., and Caddo, La., had the largest over-the-
year percentage decreases in employment among the largest counties in the U.S., with losses of 1.8
percent each. Within Shawnee, professional and business services had the largest decrease in
employment, with a loss of 1,173 jobs (-8.0 percent). Within Caddo, trade, transportation, and utilities
had the largest decrease in employment, with a loss of 769 jobs (-3.3 percent).
The U.S. average weekly wage increased 3.9 percent over the year, growing to $1,109 in the fourth
quarter of 2017. San Mateo, Calif., and Ada, Idaho, had the largest over-the-year percentage increases in
average weekly wages, with gains of 11.5 percent each. Within San Mateo, an average weekly wage
gain of $1,191 (23.1 percent) in information made the largest contribution to the county’s increase in
average weekly wages. Within Ada, an average weekly wage gain of $1,031 (51.6 percent) in
manufacturing made the largest contribution to the county’s increase in average weekly wages. Clayton,
Ga., had the largest over-the-year percentage decrease in average weekly wages with a loss of 6.7
percent. Within Clayton, trade, transportation, and utilities had the largest impact on the county’s
average weekly wage change with a decrease of $182 (-12.9 percent) over the year.
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| |
| QCEW Publication Acceleration and Conversion to Two Data Releases |
| |
| The QCEW publication process is accelerating for a more timely release. Beginning with this release, |
| QCEW data will be published in two parts. The current County Employment and Wages news release |
| will be accelerated and published first. The full QCEW data release will occur on Thursday, June 7, |
| 2018, accompanied by a data release notice. |
| |
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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 December 2017, national employment was 145.9 million (as measured by the QCEW program). Over
the year, employment increased 1.5 percent, or 2.1 million. In December 2017, the 346 U.S. counties
with 75,000 or more jobs accounted for 73.0 percent of total U.S. employment and 78.3 percent of total
wages. These 346 counties had a net job growth of 1.6 million over the year, accounting for 74.4 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 231,600 jobs, which was 10.9 percent of the overall
job increase for the U.S. (See table A.)
Employment declined in 25 of the largest counties from December 2016 to December 2017. Shawnee,
Kan., and Caddo, La., had the largest over-the-year percentage decreases in employment (-1.8 percent
each), followed by Kanawha, W. Va.; Potter, Texas; and Jefferson, La. (See table 1.)
Table A. Large counties ranked by December 2017 employment, December 2016-17 employment increase, and
December 2016-17 percent increase in employment
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Employment in large counties
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December 2017 employment | Increase in employment, | Percent increase in employment,
(thousands) | December 2016-17 | December 2016-17
| (thousands) |
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| |
United States 145,921.1| United States 2,123.0| United States 1.5
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| |
Los Angeles, Calif. 4,494.5| Los Angeles, Calif. 71.2| Midland, Texas 11.5
Cook, Ill. 2,604.2| Maricopa, Ariz. 58.5| Utah, Utah 6.0
New York, N.Y. 2,516.0| King, Wash. 38.5| Montgomery, Texas 5.9
Harris, Texas 2,293.3| New York, N.Y. 34.2| Calcasieu, La. 5.8
Maricopa, Ariz. 1,989.4| Kings, N.Y. 29.2| Elkhart, Ind. 5.4
Dallas, Texas 1,712.8| Clark, Nev. 28.7| Weld, Colo. 5.2
Orange, Calif. 1,621.4| Orange, Fla. 28.1| Rutherford, Tenn. 5.2
San Diego, Calif. 1,462.0| Dallas, Texas 28.1| Adams, Colo. 5.1
King, Wash. 1,377.5| Orange, Calif. 27.3| Clark, Wash. 4.8
Miami-Dade, Fla. 1,148.3| Santa Clara, Calif. 26.2| Yakima, Wash. 4.8
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Large County Average Weekly Wages
Average weekly wages for the nation increased to $1,109, a 3.9 percent increase, during the year ending
in the fourth quarter of 2017. Among the 346 largest counties, 339 had over-the-year increases in
average weekly wages. San Mateo, Calif., and Ada, Idaho, had the largest percentage wage increases
among the largest U.S. counties (11.5 percent each). (See table B.)
Of the 346 largest counties, 7 experienced an over-the-year decrease in average weekly wages. Clayton,
Ga., had the largest percentage decrease in average weekly wages (-6.7 percent), followed by
Champaign, Ill.; Benton, Ark.; Wyandotte, Kan.; and Rockland, N.Y. (See table 1.)
Table B. Large counties ranked by fourth quarter 2017 average weekly wages, fourth quarter 2016-17
increase in average weekly wages, and fourth quarter 2016-17 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
fourth quarter 2017 | wage, fourth quarter 2016-17 | weekly wage, fourth
| | quarter 2016-17
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| |
United States $1,109| United States $42| United States 3.9
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| |
Santa Clara, Calif. $2,576| San Mateo, Calif. $241| San Mateo, Calif. 11.5
New York, N.Y. 2,439| New York, N.Y. 229| Ada, Idaho 11.5
San Mateo, Calif. 2,341| Santa Clara, Calif. 211| New York, N.Y. 10.4
San Francisco, Calif. 2,232| San Francisco, Calif. 154| Douglas, Colo. 9.0
Suffolk, Mass. 1,986| Douglas, Colo. 108| Santa Clara, Calif. 8.9
Washington, D.C. 1,812| Ada, Idaho 108| Washington, Ore. 8.1
Arlington, Va. 1,727| King, Wash. 103| San Francisco, Calif. 7.4
Fairfield, Conn. 1,688| Suffolk, Mass. 101| Elkhart, Ind. 7.1
Fairfax, Va. 1,646| Washington, Ore. 98| King, Wash. 7.0
Middlesex, Mass. 1,613| Los Angeles, Calif. 81| Weld, Colo. 6.9
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Ten Largest U.S. Counties
All of the 10 largest counties had over-the-year percentage increases in employment in December 2017.
Maricopa, Ariz., had the largest gain (3.0 percent). Within Maricopa, construction had the largest over-
the-year employment level increase, with a gain of 10,168 jobs, or 9.7 percent. Cook, Ill., had the
smallest percentage increase in employment among the 10 largest counties (0.6 percent). Within Cook,
education and health services had the largest over-the-year employment level increase, with a gain of
6,515 jobs, or 1.5 percent. (See table 2.)
Average weekly wages increased over the year in all of the 10 largest U.S. counties. New York, N.Y.
experienced the largest percentage gain in average weekly wages (10.4 percent). Within New York,
financial activities had the largest impact on the county’s average weekly wage gain. Within financial
activities, average weekly wages increased by $1,032, or 22.4 percent, over the year. Harris, Texas, had
the smallest percentage gain in average weekly wages among the 10 largest counties (2.4 percent).
Within Harris, trade, transportation, and utilities had the largest impact on the county’s average weekly
wage growth with an increase of $49 (4.3 percent) over the year.
For More Information
The tables included in this release contain data for the nation and for the 346 U.S. counties with annual
average employment levels of 75,000 or more in 2016. December 2017 employment and fourth quarter
2017 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 145.9 million full- and part-time workers. The full
set of data for the fourth quarter of 2017 will be available on June 7, 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 fourth quarter 2017 is scheduled to be
released on Thursday, June 7, 2018. The County Employment and Wages release for first quarter
2018 is scheduled to be released on Wednesday, August 22, 2018.
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 2017 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 347 counties
presented in this release were derived using 2016 preliminary annual averages of employment. For
2017 data, three counties have been added to the publication tables: Sussex, Del.; Maui + Kalawao,
Hawaii; and Deschutes, Ore. These counties will be included in all 2017 quarterly releases. One
county, Gregg, Texas, which was published in the 2016 releases, will be excluded from this and
future 2017 releases because its 2016 annual average employment level was less than 75,000. The
counties in table 2 are selected and sorted each year based on the annual average employment from
the preceding year.
The preliminary QCEW data presented in this release may differ from data released by the
individual states. These potential differences result from the states' continuing receipt of UI data
over time and ongoing review and editing. The individual states determine their data release
timetables.
Differences between QCEW, BED, and CES employment measures
The Bureau publishes three different establishment-based employment measures for any given
quarter: 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 9.9 | ministrative records| ments
| million establish- | submitted by 7.9 |
| ments in first | million private-sec-|
| quarter of 2017 | 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 | | |
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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 9.7
million employer reports of employment and wages submitted by states to the BLS in 2016. 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 2016, UI and UCFE programs
covered workers in 141.9 million jobs. The estimated 136.6 million workers in these jobs (after
adjustment for multiple jobholders) represented 96.4 percent of civilian wage and salary
employment. Covered workers received $7.607 trillion in pay, representing 94.1 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 2016 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 347 largest counties,
fourth quarter 2017
Employment Average weekly wage(2)
Establishments,
County(1) fourth quarter Percent Ranking Percent Ranking
2017 December change, by Fourth change, by
(thousands) 2017 December percent quarter fourth percent
(thousands) 2016-17(3) change 2017 quarter change
2016-17(3)
United States(4)......... 9,969.4 145,921.1 1.5 - $1,109 3.9 -
Jefferson, AL............ 18.8 350.5 1.8 102 1,083 3.8 98
Madison, AL.............. 9.7 198.9 1.9 96 1,137 3.5 122
Mobile, AL............... 10.2 171.9 1.0 196 975 4.1 78
Montgomery, AL........... 6.5 132.3 -0.1 322 939 -0.4 340
Shelby, AL............... 5.9 85.3 0.7 240 1,031 2.6 213
Tuscaloosa, AL........... 4.6 93.9 2.2 81 913 4.6 47
Anchorage, AK............ 8.3 147.3 -1.1 341 1,104 1.9 281
Maricopa, AZ............. 97.9 1,989.4 3.0 32 1,024 2.9 180
Pima, AZ................. 18.7 372.3 1.0 196 892 3.8 98
Benton, AR............... 6.5 119.7 1.3 158 1,008 -1.4 344
Pulaski, AR.............. 14.4 253.2 0.9 215 971 2.1 264
Washington, AR........... 6.0 107.4 2.6 56 1,002 5.5 18
Alameda, CA.............. 64.0 785.6 3.0 32 1,457 5.4 22
Butte, CA................ 8.6 83.1 1.3 158 826 4.8 38
Contra Costa, CA......... 32.6 369.9 0.7 240 1,344 4.0 85
Fresno, CA............... 35.7 380.2 1.8 102 888 3.6 117
Kern, CA................. 19.2 313.6 1.1 181 888 2.5 227
Los Angeles, CA.......... 494.2 4,494.5 1.6 121 1,343 6.4 11
Marin, CA................ 12.6 116.8 1.5 135 1,400 1.8 288
Merced, CA............... 6.7 79.4 3.8 16 816 1.0 317
Monterey, CA............. 13.8 175.0 0.7 240 951 4.5 52
Napa, CA................. 5.9 74.4 1.4 144 1,119 5.6 17
Orange, CA............... 121.9 1,621.4 1.7 111 1,234 2.8 188
Placer, CA............... 13.1 164.6 4.3 12 1,107 3.1 163
Riverside, CA............ 64.7 732.3 2.8 48 873 4.7 44
Sacramento, CA........... 58.6 656.4 2.4 69 1,180 4.5 52
San Bernardino, CA....... 59.4 754.0 3.3 23 906 2.0 270
San Diego, CA............ 111.9 1,462.0 1.8 102 1,221 4.3 67
San Francisco, CA........ 61.0 730.9 2.9 38 2,232 7.4 7
San Joaquin, CA.......... 17.9 251.9 2.4 69 923 3.8 98
San Luis Obispo, CA...... 10.5 115.9 1.6 121 929 4.6 47
San Mateo, CA............ 28.5 407.5 1.8 102 2,341 11.5 1
Santa Barbara, CA........ 15.6 195.4 1.6 121 1,066 3.9 92
Santa Clara, CA.......... 73.3 1,093.4 2.5 62 2,576 8.9 5
Santa Cruz, CA........... 9.6 100.4 1.1 181 970 4.1 78
Solano, CA............... 11.6 140.8 1.3 158 1,115 4.1 78
Sonoma, CA............... 20.2 208.3 2.0 90 1,070 4.8 38
Stanislaus, CA........... 15.8 187.1 3.0 32 915 3.5 122
Tulare, CA............... 10.5 159.3 0.7 240 812 4.9 35
Ventura, CA.............. 27.4 326.3 0.8 229 1,076 3.0 171
Yolo, CA................. 6.8 101.6 2.6 56 1,151 3.9 92
Adams, CO................ 11.0 211.7 5.1 8 1,075 5.4 22
Arapahoe, CO............. 22.0 331.2 1.8 102 1,268 3.4 134
Boulder, CO.............. 15.3 183.1 2.4 69 1,277 3.5 122
Denver, CO............... 32.2 514.2 2.6 56 1,334 3.7 107
Douglas, CO.............. 12.0 123.6 2.9 38 1,314 9.0 4
El Paso, CO.............. 19.8 274.4 2.5 62 967 2.8 188
Jefferson, CO............ 20.2 236.4 2.2 81 1,112 2.4 241
Larimer, CO.............. 12.2 159.0 3.0 32 1,011 3.4 134
Weld, CO................. 7.4 106.8 5.2 6 962 6.9 10
Fairfield, CT............ 35.6 424.4 -0.4 328 1,688 0.7 325
Hartford, CT............. 28.1 514.6 0.4 281 1,296 2.6 213
New Haven, CT............ 24.3 369.7 0.5 275 1,121 2.5 227
New London, CT........... 7.6 124.5 0.7 240 1,051 2.7 200
New Castle, DE........... 19.7 293.3 0.5 275 1,195 2.5 227
Sussex, DE............... 6.8 77.0 2.7 52 817 3.2 151
Washington, DC........... 41.2 769.0 0.9 215 1,812 2.7 200
Alachua, FL.............. 7.2 131.0 1.0 196 912 5.2 28
Bay, FL.................. 5.6 77.1 1.4 144 795 1.8 288
Brevard, FL.............. 15.9 211.6 2.5 62 972 3.5 122
Broward, FL.............. 69.7 814.0 1.2 167 1,041 3.7 107
Collier, FL.............. 14.1 150.4 1.3 158 966 4.4 61
Duval, FL................ 29.5 516.7 3.2 24 1,030 2.9 180
Escambia, FL............. 8.1 135.8 2.8 48 868 4.8 38
Hillsborough, FL......... 42.5 692.4 0.7 240 1,049 4.0 85
Lake, FL................. 8.2 98.9 2.3 77 740 2.5 227
Lee, FL.................. 22.1 265.5 2.9 38 864 1.9 281
Leon, FL................. 8.7 151.1 1.0 196 894 3.8 98
Manatee, FL.............. 11.0 125.7 1.7 111 819 0.9 322
Marion, FL............... 8.4 103.2 1.2 167 756 0.7 325
Miami-Dade, FL........... 98.9 1,148.3 0.8 229 1,065 3.8 98
Okaloosa, FL............. 6.4 83.0 1.4 144 875 1.3 308
Orange, FL............... 42.4 845.4 3.4 22 969 2.5 227
Osceola, FL.............. 7.0 94.4 4.4 11 740 2.5 227
Palm Beach, FL........... 56.7 611.5 1.0 196 1,103 4.5 52
Pasco, FL................ 10.9 119.4 2.1 87 760 3.0 171
Pinellas, FL............. 33.1 432.8 1.6 121 988 2.9 180
Polk, FL................. 13.3 220.7 2.9 38 821 2.6 213
Sarasota, FL............. 16.0 171.2 1.0 196 941 4.8 38
Seminole, FL............. 15.0 194.6 3.5 21 932 3.1 163
Volusia, FL.............. 14.4 173.1 1.9 96 784 3.2 151
Bibb, GA................. 4.2 83.6 -1.0 340 840 2.8 188
Chatham, GA.............. 8.0 154.2 2.2 81 906 2.3 249
Clayton, GA.............. 4.0 126.7 1.0 196 988 -6.7 346
Cobb, GA................. 21.7 363.7 1.9 96 1,125 3.5 122
DeKalb, GA............... 17.8 301.5 0.6 255 1,086 2.5 227
Fulton, GA............... 43.1 870.2 2.4 69 1,449 5.0 33
Gwinnett, GA............. 24.6 359.9 2.7 52 1,048 2.3 249
Hall, GA................. 4.4 86.8 1.8 102 979 5.8 16
Muscogee, GA............. 4.5 94.5 0.9 215 875 4.0 85
Richmond, GA............. 4.4 105.9 0.6 255 887 2.3 249
Honolulu, HI............. 26.2 480.3 0.5 275 1,030 3.4 134
Maui + Kalawao, HI....... 6.2 78.3 0.8 229 863 1.4 304
Ada, ID.................. 16.2 238.3 3.6 20 1,044 11.5 1
Champaign, IL............ 4.0 90.9 1.0 196 933 -1.6 345
Cook, IL................. 136.9 2,604.2 0.6 255 1,283 2.6 213
DuPage, IL............... 34.3 622.3 0.4 281 1,239 2.4 241
Kane, IL................. 12.4 211.2 0.1 309 1,005 4.4 61
Lake, IL................. 20.0 338.1 1.2 167 1,411 1.0 317
McHenry, IL.............. 7.7 98.6 1.4 144 917 3.9 92
McLean, IL............... 3.4 83.3 -0.9 336 944 2.3 249
Madison, IL.............. 5.4 101.7 1.8 102 857 2.0 270
Peoria, IL............... 4.2 104.2 0.9 215 1,088 1.6 300
St. Clair, IL............ 5.0 94.8 -0.4 328 856 2.4 241
Sangamon, IL............. 4.7 129.4 -0.3 326 1,065 3.3 141
Will, IL................. 14.5 245.6 1.7 111 954 2.1 264
Winnebago, IL............ 6.0 128.1 0.1 309 904 2.8 188
Allen, IN................ 8.8 187.6 1.1 181 885 4.6 47
Elkhart, IN.............. 4.7 137.8 5.4 5 983 7.1 8
Hamilton, IN............. 9.4 140.9 1.5 135 1,036 1.2 312
Lake, IN................. 10.4 189.2 0.3 295 929 2.0 270
Marion, IN............... 24.0 601.9 0.8 229 1,086 3.2 151
St. Joseph, IN........... 5.8 123.9 -0.3 326 879 1.4 304
Tippecanoe, IN........... 3.4 84.7 0.8 229 920 3.3 141
Vanderburgh, IN.......... 4.7 110.2 1.7 111 903 3.7 107
Johnson, IA.............. 4.2 85.3 1.1 181 971 2.2 260
Linn, IA................. 6.9 131.3 0.6 255 1,119 5.9 15
Polk, IA................. 17.6 300.9 1.2 167 1,117 2.7 200
Scott, IA................ 5.6 91.4 -0.2 325 899 1.7 297
Johnson, KS.............. 23.5 349.9 1.8 102 1,089 2.3 249
Sedgwick, KS............. 12.6 250.2 0.0 317 917 1.4 304
Shawnee, KS.............. 5.1 96.7 -1.8 345 860 2.0 270
Wyandotte, KS............ 3.5 93.7 3.2 24 1,027 -1.1 343
Boone, KY................ 4.4 91.3 2.4 69 914 1.8 288
Fayette, KY.............. 10.9 199.8 1.3 158 970 0.1 338
Jefferson, KY............ 25.0 472.3 0.4 281 1,048 2.3 249
Caddo, LA................ 7.3 112.8 -1.8 345 872 1.9 281
Calcasieu, LA............ 5.4 100.3 5.8 4 971 5.1 30
East Baton Rouge, LA..... 15.8 266.2 -0.1 322 1,010 0.5 331
Jefferson, LA............ 14.1 191.9 -1.2 342 976 2.3 249
Lafayette, LA............ 9.7 129.7 -0.4 328 944 3.5 122
Orleans, LA.............. 12.9 196.1 1.0 196 1,036 3.8 98
St. Tammany, LA.......... 8.4 89.7 0.1 309 916 1.0 317
Cumberland, ME........... 14.0 185.7 2.8 48 1,007 2.7 200
Anne Arundel, MD......... 15.3 273.8 0.6 255 1,177 1.3 308
Baltimore, MD............ 21.3 381.7 -0.6 332 1,118 3.1 163
Frederick, MD............ 6.5 102.7 2.0 90 989 2.0 270
Harford, MD.............. 5.8 95.9 2.0 90 1,009 2.6 213
Howard, MD............... 10.0 171.4 0.4 281 1,331 2.5 227
Montgomery, MD........... 33.0 474.5 0.0 317 1,482 4.2 71
Prince George's, MD...... 16.0 323.8 0.4 281 1,123 3.0 171
Baltimore City, MD....... 13.7 344.9 1.4 144 1,365 4.5 52
Barnstable, MA........... 9.5 91.8 0.8 229 962 2.3 249
Bristol, MA.............. 17.7 229.6 0.6 255 979 4.0 85
Essex, MA................ 25.9 329.2 1.1 181 1,161 3.3 141
Hampden, MA.............. 18.3 211.7 1.6 121 973 2.1 264
Middlesex, MA............ 55.3 915.0 1.6 121 1,613 5.1 30
Norfolk, MA.............. 25.4 356.9 0.6 255 1,358 4.1 78
Plymouth, MA............. 16.0 195.6 2.0 90 1,033 1.8 288
Suffolk, MA.............. 30.0 679.7 1.0 196 1,986 5.4 22
Worcester, MA............ 25.5 353.8 1.4 144 1,078 2.9 180
Genesee, MI.............. 6.8 136.0 0.4 281 899 0.9 322
Ingham, MI............... 6.0 153.1 0.6 255 1,041 1.1 314
Kalamazoo, MI............ 5.0 119.8 1.2 167 1,002 2.0 270
Kent, MI................. 14.5 402.5 1.2 167 956 1.9 281
Macomb, MI............... 17.6 328.8 0.6 255 1,091 2.6 213
Oakland, MI.............. 39.5 735.1 1.0 196 1,253 3.6 117
Ottawa, MI............... 5.7 124.3 1.3 158 976 2.7 200
Saginaw, MI.............. 3.9 84.6 -0.9 336 897 3.7 107
Washtenaw, MI............ 8.3 215.6 1.7 111 1,134 3.2 151
Wayne, MI................ 30.9 725.3 0.2 302 1,212 2.4 241
Anoka, MN................ 7.3 123.5 1.5 135 1,034 4.1 78
Dakota, MN............... 10.1 188.9 0.7 240 1,044 2.9 180
Hennepin, MN............. 40.4 926.8 1.1 181 1,335 3.0 171
Olmsted, MN.............. 3.5 97.8 1.6 121 1,118 4.0 85
Ramsey, MN............... 13.6 334.5 1.3 158 1,202 3.8 98
St. Louis, MN............ 5.3 98.0 0.7 240 895 3.2 151
Stearns, MN.............. 4.4 87.1 0.6 255 907 4.3 67
Washington, MN........... 5.6 86.3 4.2 13 943 5.5 18
Harrison, MS............. 4.6 85.4 0.1 309 749 2.5 227
Hinds, MS................ 5.8 122.0 -0.9 336 884 2.1 264
Boone, MO................ 5.1 94.5 1.1 181 846 0.5 331
Clay, MO................. 5.8 106.5 2.6 56 948 1.4 304
Greene, MO............... 9.1 167.2 1.2 167 841 4.2 71
Jackson, MO.............. 22.5 370.3 0.7 240 1,103 3.4 134
St. Charles, MO.......... 9.7 147.9 1.4 144 847 1.0 317
St. Louis, MO............ 39.9 613.9 0.9 215 1,168 3.6 117
St. Louis City, MO....... 14.8 226.4 0.9 215 1,145 1.7 297
Yellowstone, MT.......... 6.9 81.4 0.3 295 924 0.5 331
Douglas, NE.............. 19.5 342.7 0.7 240 1,011 3.0 171
Lancaster, NE............ 10.6 170.3 1.5 135 882 2.9 180
Clark, NV................ 54.9 981.8 3.0 32 938 3.1 163
Washoe, NV............... 14.8 221.8 3.7 17 969 2.5 227
Hillsborough, NH......... 12.2 206.0 0.4 281 1,240 3.2 151
Merrimack, NH............ 5.2 78.1 0.8 229 1,050 3.3 141
Rockingham, NH........... 11.0 150.0 1.0 196 1,116 4.9 35
Atlantic, NJ............. 6.6 123.2 0.7 240 914 2.6 213
Bergen, NJ............... 33.3 458.4 0.9 215 1,298 1.2 312
Burlington, NJ........... 11.1 209.4 0.6 255 1,105 1.7 297
Camden, NJ............... 12.2 209.4 1.9 96 1,096 2.6 213
Essex, NJ................ 20.7 349.5 1.5 135 1,318 1.8 288
Gloucester, NJ........... 6.4 112.6 2.7 52 926 1.1 314
Hudson, NJ............... 15.3 267.9 2.5 62 1,408 3.1 163
Mercer, NJ............... 11.3 253.7 1.3 158 1,355 -0.4 340
Middlesex, NJ............ 22.5 440.4 1.9 96 1,259 1.9 281
Monmouth, NJ............. 20.2 262.9 0.6 255 1,097 2.8 188
Morris, NJ............... 17.2 295.6 1.4 144 1,582 3.9 92
Ocean, NJ................ 13.4 166.9 2.4 69 883 1.3 308
Passaic, NJ.............. 12.8 170.1 0.2 302 1,066 1.9 281
Somerset, NJ............. 10.3 190.4 0.3 295 1,568 0.3 336
Union, NJ................ 14.5 224.7 0.7 240 1,385 2.4 241
Bernalillo, NM........... 18.4 328.5 0.2 302 912 1.8 288
Albany, NY............... 10.4 236.9 -0.7 335 1,135 4.2 71
Bronx, NY................ 18.8 306.8 0.9 215 1,030 2.7 200
Broome, NY............... 4.5 87.7 -0.4 328 838 4.8 38
Dutchess, NY............. 8.4 114.9 1.0 196 1,032 2.1 264
Erie, NY................. 24.9 477.5 0.6 255 965 2.7 200
Kings, NY................ 63.0 736.4 4.1 14 920 1.8 288
Monroe, NY............... 19.0 391.5 0.6 255 1,000 2.8 188
Nassau, NY............... 54.4 646.0 1.1 181 1,242 2.0 270
New York, NY............. 128.4 2,516.0 1.4 144 2,439 10.4 3
Oneida, NY............... 5.3 106.2 0.2 302 838 3.6 117
Onondaga, NY............. 12.9 248.6 0.4 281 995 2.5 227
Orange, NY............... 10.5 146.4 1.5 135 921 3.7 107
Queens, NY............... 53.3 676.3 2.0 90 1,041 2.3 249
Richmond, NY............. 9.8 118.8 1.2 167 984 4.0 85
Rockland, NY............. 10.9 126.3 1.2 167 1,030 -0.8 342
Saratoga, NY............. 6.0 87.8 3.7 17 978 3.5 122
Suffolk, NY.............. 53.2 664.9 0.1 309 1,217 6.0 13
Westchester, NY.......... 36.4 433.5 0.6 255 1,468 4.9 35
Buncombe, NC............. 9.2 132.2 1.2 167 851 1.8 288
Catawba, NC.............. 4.4 88.7 1.8 102 841 2.6 213
Cumberland, NC........... 6.2 120.6 0.4 281 829 3.5 122
Durham, NC............... 8.4 201.9 1.0 196 1,286 2.6 213
Forsyth, NC.............. 9.1 186.8 0.5 275 1,005 3.3 141
Guilford, NC............. 14.3 282.1 -0.6 332 946 5.3 26
Mecklenburg, NC.......... 37.7 693.5 2.8 48 1,232 3.2 151
New Hanover, NC.......... 8.1 111.6 1.6 121 875 1.0 317
Wake, NC................. 34.4 553.5 2.9 38 1,117 2.5 227
Cass, ND................. 7.2 118.1 0.2 302 990 3.0 171
Butler, OH............... 7.8 157.3 2.0 90 933 0.2 337
Cuyahoga, OH............. 36.0 724.9 0.2 302 1,126 3.5 122
Delaware, OH............. 5.4 88.4 1.1 181 1,021 2.0 270
Franklin, OH............. 32.3 766.4 1.2 167 1,051 2.2 260
Hamilton, OH............. 24.0 519.7 0.7 240 1,157 3.2 151
Lake, OH................. 6.3 95.3 0.4 281 893 3.4 134
Lorain, OH............... 6.2 98.4 0.6 255 830 1.1 314
Lucas, OH................ 10.2 209.9 -0.1 322 921 2.0 270
Mahoning, OH............. 5.9 98.0 0.4 281 775 3.3 141
Montgomery, OH........... 11.9 257.7 1.1 181 920 2.8 188
Stark, OH................ 8.6 161.1 1.1 181 834 5.3 26
Summit, OH............... 14.4 268.0 0.0 317 962 2.2 260
Warren, OH............... 4.9 91.7 2.5 62 954 0.7 325
Cleveland, OK............ 5.9 82.0 1.7 111 769 0.5 331
Oklahoma, OK............. 28.4 455.9 1.4 144 1,016 3.8 98
Tulsa, OK................ 22.7 357.7 0.8 229 968 2.7 200
Clackamas, OR............ 15.1 164.5 2.5 62 1,023 3.8 98
Deschutes, OR............ 8.6 80.9 3.7 17 874 4.3 67
Jackson, OR.............. 7.5 89.3 2.4 69 833 4.0 85
Lane, OR................. 12.2 156.0 1.4 144 862 2.0 270
Marion, OR............... 10.9 152.1 1.6 121 901 4.6 47
Multnomah, OR............ 35.2 510.5 1.9 96 1,146 4.2 71
Washington, OR........... 19.5 294.7 2.4 69 1,307 8.1 6
Allegheny, PA............ 35.6 702.2 1.1 181 1,172 3.1 163
Berks, PA................ 9.0 174.3 1.1 181 971 3.4 134
Bucks, PA................ 20.1 266.1 1.3 158 1,033 1.5 301
Butler, PA............... 5.1 85.9 0.6 255 1,008 0.1 338
Chester, PA.............. 15.6 253.7 1.7 111 1,339 2.5 227
Cumberland, PA........... 6.5 135.4 0.3 295 972 5.2 28
Dauphin, PA.............. 7.6 183.3 0.9 215 1,069 3.6 117
Delaware, PA............. 14.2 227.2 1.0 196 1,146 3.3 141
Erie, PA................. 7.0 121.6 0.1 309 812 0.5 331
Lackawanna, PA........... 5.7 99.5 0.6 255 831 4.5 52
Lancaster, PA............ 13.5 241.0 1.6 121 902 2.7 200
Lehigh, PA............... 8.9 192.1 1.4 144 1,084 3.1 163
Luzerne, PA.............. 7.4 147.3 1.2 167 835 2.3 249
Montgomery, PA........... 27.8 500.4 1.0 196 1,320 2.3 249
Northampton, PA.......... 6.8 116.4 0.8 229 921 2.8 188
Philadelphia, PA......... 34.8 684.6 1.4 144 1,290 4.4 61
Washington, PA........... 5.5 87.7 2.2 81 1,181 5.1 30
Westmoreland, PA......... 9.3 134.4 0.7 240 886 6.1 12
York, PA................. 9.2 180.9 0.8 229 955 5.4 22
Providence, RI........... 18.5 290.7 0.9 215 1,116 3.2 151
Charleston, SC........... 15.4 248.9 1.6 121 979 4.7 44
Greenville, SC........... 14.1 272.9 2.3 77 953 2.8 188
Horry, SC................ 8.9 122.8 2.7 52 674 2.7 200
Lexington, SC............ 6.7 122.9 3.0 32 805 1.8 288
Richland, SC............. 10.3 221.0 0.2 302 914 3.3 141
Spartanburg, SC.......... 6.3 141.2 2.3 77 906 3.2 151
York, SC................. 5.8 94.8 3.2 24 872 2.6 213
Minnehaha, SD............ 7.3 126.8 0.9 215 949 3.0 171
Davidson, TN............. 22.8 492.5 2.6 56 1,197 2.7 200
Hamilton, TN............. 9.7 204.0 2.1 87 1,041 3.7 107
Knox, TN................. 12.3 240.7 0.4 281 979 2.1 264
Rutherford, TN........... 5.7 129.3 5.2 6 946 0.6 329
Shelby, TN............... 20.6 501.9 0.5 275 1,115 2.6 213
Williamson, TN........... 8.9 132.9 2.9 38 1,258 4.1 78
Bell, TX................. 5.5 119.5 0.6 255 925 5.5 18
Bexar, TX................ 41.5 865.4 1.0 196 980 2.7 200
Brazoria, TX............. 5.8 111.0 0.6 255 1,134 3.2 151
Brazos, TX............... 4.6 105.2 2.5 62 806 4.5 52
Cameron, TX.............. 6.5 140.5 0.5 275 652 2.2 260
Collin, TX............... 25.3 409.2 4.1 14 1,249 1.9 281
Dallas, TX............... 77.5 1,712.8 1.7 111 1,318 3.1 163
Denton, TX............... 15.2 244.7 2.9 38 1,008 4.6 47
El Paso, TX.............. 15.2 305.6 1.5 135 748 2.9 180
Fort Bend, TX............ 13.5 184.7 3.2 24 1,014 3.0 171
Galveston, TX............ 6.2 110.7 0.0 317 944 3.3 141
Harris, TX............... 115.3 2,293.3 1.1 181 1,352 2.4 241
Hidalgo, TX.............. 12.4 261.8 2.2 81 664 2.8 188
Jefferson, TX............ 5.9 121.3 -0.6 332 1,136 4.4 61
Lubbock, TX.............. 7.6 140.7 0.3 295 865 3.3 141
McLennan, TX............. 5.3 113.5 0.0 317 904 5.5 18
Midland, TX.............. 5.5 94.7 11.5 1 1,341 3.7 107
Montgomery, TX........... 11.4 183.5 5.9 3 1,073 4.4 61
Nueces, TX............... 8.3 163.5 0.8 229 930 3.7 107
Potter, TX............... 4.0 78.7 -1.3 343 907 4.1 78
Smith, TX................ 6.2 104.9 1.5 135 901 4.5 52
Tarrant, TX.............. 43.6 890.8 2.2 81 1,075 4.5 52
Travis, TX............... 41.0 737.7 2.9 38 1,278 2.4 241
Webb, TX................. 5.4 101.2 1.6 121 706 3.4 134
Williamson, TX........... 10.9 169.4 3.2 24 1,041 3.0 171
Davis, UT................ 8.6 126.4 2.3 77 897 4.2 71
Salt Lake, UT............ 45.7 701.6 3.1 31 1,056 2.7 200
Utah, UT................. 16.5 238.7 6.0 2 891 3.7 107
Weber, UT................ 6.1 106.8 3.2 24 808 2.4 241
Chittenden, VT........... 6.9 103.3 1.0 196 1,045 1.3 308
Arlington, VA............ 9.3 178.6 1.7 111 1,727 2.8 188
Chesterfield, VA......... 9.2 139.9 0.4 281 917 2.9 180
Fairfax, VA.............. 37.6 611.0 1.1 181 1,646 2.0 270
Henrico, VA.............. 11.8 196.5 1.4 144 1,043 4.3 67
Loudoun, VA.............. 12.5 165.9 2.1 87 1,270 2.6 213
Prince William, VA....... 9.4 129.7 1.5 135 949 1.5 301
Alexandria City, VA...... 6.4 93.9 -0.9 336 1,531 2.5 227
Chesapeake City, VA...... 6.1 101.2 0.4 281 844 4.2 71
Newport News City, VA.... 3.9 100.5 2.9 38 1,026 0.6 329
Norfolk City, VA......... 6.0 144.2 1.6 121 1,080 0.7 325
Richmond City, VA........ 7.8 155.2 0.1 309 1,180 3.5 122
Virginia Beach City, VA.. 12.3 177.8 0.3 295 861 3.7 107
Benton, WA............... 5.7 86.6 2.6 56 1,055 4.4 61
Clark, WA................ 14.7 158.9 4.8 9 1,022 3.9 92
King, WA................. 86.6 1,377.5 2.9 38 1,583 7.0 9
Kitsap, WA............... 6.6 88.4 1.7 111 1,009 4.8 38
Pierce, WA............... 21.8 307.3 1.6 121 976 4.7 44
Snohomish, WA............ 20.8 286.1 0.1 309 1,148 3.2 151
Spokane, WA.............. 15.6 220.2 1.2 167 921 4.5 52
Thurston, WA............. 8.3 114.8 3.2 24 969 5.0 33
Whatcom, WA.............. 7.3 89.7 1.2 167 903 6.0 13
Yakima, WA............... 7.7 107.0 4.8 9 772 4.2 71
Kanawha, WV.............. 5.7 99.3 -1.5 344 904 2.8 188
Brown, WI................ 7.0 157.3 0.7 240 989 3.9 92
Dane, WI................. 15.9 336.5 0.9 215 1,070 3.5 122
Milwaukee, WI............ 27.0 492.1 1.0 196 1,056 1.5 301
Outagamie, WI............ 5.4 108.6 0.9 215 943 2.6 213
Waukesha, WI............. 13.4 244.7 0.9 215 1,082 0.8 324
Winnebago, WI............ 3.8 94.5 0.3 295 1,039 3.5 122
San Juan, PR............. 10.4 252.6 -0.9 (5) 678 0.9 (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 346 U.S. counties comprise 73.0 percent of
the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,
fourth quarter 2017
Employment Average weekly
wage(1)
Establishments,
fourth quarter
County by NAICS supersector 2017 Percent Percent
(thousands) December change, Fourth change,
2017 December quarter fourth
(thousands) 2016-17(2) 2017 quarter
2016-17(2)
United States(3) ............................ 9,969.4 145,921.1 1.5 $1,109 3.9
Private industry........................... 9,671.1 124,015.7 1.7 1,114 4.1
Natural resources and mining............. 137.4 1,801.6 3.7 1,135 4.8
Construction............................. 792.8 6,962.2 3.7 1,282 3.9
Manufacturing............................ 347.9 12,504.4 1.2 1,331 3.6
Trade, transportation, and utilities..... 1,919.8 28,219.9 0.9 911 3.5
Information.............................. 165.0 2,825.6 0.1 2,035 8.0
Financial activities..................... 879.4 8,150.9 1.2 1,826 6.8
Professional and business services....... 1,803.3 20,625.1 1.7 1,483 4.2
Education and health services............ 1,669.5 22,468.6 1.9 995 2.4
Leisure and hospitality.................. 845.8 15,681.4 1.7 481 4.1
Other services........................... 846.4 4,441.5 1.0 746 3.8
Government................................. 298.4 21,905.4 0.2 1,076 2.6
Los Angeles, CA.............................. 494.2 4,494.5 1.6 1,343 6.4
Private industry........................... 488.0 3,914.4 1.8 1,340 7.0
Natural resources and mining............. 0.5 8.0 3.2 1,176 0.1
Construction............................. 14.5 140.3 4.5 1,332 4.6
Manufacturing............................ 12.3 343.2 -2.9 1,481 6.7
Trade, transportation, and utilities..... 54.9 859.5 0.8 994 3.9
Information.............................. 10.6 223.0 0.9 2,722 14.0
Financial activities..................... 26.7 221.9 0.4 2,186 12.7
Professional and business services....... 49.6 618.3 1.8 1,794 8.5
Education and health services............ 232.6 789.6 2.5 947 2.3
Leisure and hospitality.................. 33.9 522.3 1.3 1,074 5.9
Other services........................... 26.8 148.8 -0.2 791 7.6
Government................................. 6.2 580.2 0.4 1,363 2.8
Cook, IL..................................... 136.9 2,604.2 0.6 1,283 2.6
Private industry........................... 135.7 2,310.8 0.7 1,291 2.8
Natural resources and mining............. 0.1 1.2 17.4 1,239 -5.6
Construction............................. 10.6 72.5 0.8 1,661 2.5
Manufacturing............................ 5.8 184.8 0.5 1,369 1.0
Trade, transportation, and utilities..... 27.5 488.8 -0.3 1,009 2.5
Information.............................. 2.3 53.5 -0.8 1,838 5.7
Financial activities..................... 13.7 196.8 1.3 2,380 4.6
Professional and business services....... 28.5 482.6 0.6 1,711 2.9
Education and health services............ 15.3 450.4 1.5 1,042 1.6
Leisure and hospitality.................. 13.6 278.9 0.8 553 4.3
Other services........................... 15.4 99.0 1.7 977 2.5
Government................................. 1.3 293.4 -0.4 1,223 0.5
New York, NY................................. 128.4 2,516.0 1.4 2,439 10.4
Private industry........................... 127.5 2,246.8 1.5 2,569 10.8
Natural resources and mining............. 0.0 0.2 3.6 1,861 -9.3
Construction............................. 2.3 42.5 4.7 2,356 0.5
Manufacturing............................ 2.0 25.5 -2.6 1,681 1.7
Trade, transportation, and utilities..... 19.5 265.0 -1.2 1,546 5.6
Information.............................. 5.0 169.7 3.7 2,761 2.9
Financial activities..................... 19.5 380.3 1.9 5,637 22.4
Professional and business services....... 27.2 588.1 2.4 2,753 5.4
Education and health services............ 10.2 351.6 0.6 1,456 5.1
Leisure and hospitality.................. 14.7 309.4 0.6 1,050 2.9
Other services........................... 20.4 105.5 0.7 1,251 4.9
Government................................. 0.8 269.2 0.1 1,362 2.3
Harris, TX................................... 115.3 2,293.3 1.1 1,352 2.4
Private industry........................... 114.8 2,014.1 1.2 1,377 2.5
Natural resources and mining............. 1.6 67.2 1.7 3,255 0.1
Construction............................. 7.4 156.8 0.7 1,481 0.5
Manufacturing............................ 4.8 171.0 2.4 1,672 1.3
Trade, transportation, and utilities..... 25.0 482.2 1.1 1,178 4.3
Information.............................. 1.2 26.4 -4.6 1,584 7.7
Financial activities..................... 12.2 126.5 1.4 1,815 1.9
Professional and business services....... 23.2 394.4 1.4 1,790 2.9
Education and health services............ 16.1 292.4 0.5 1,095 1.8
Leisure and hospitality.................. 10.1 228.2 1.1 490 4.3
Other services........................... 11.6 65.9 1.4 840 1.7
Government................................. 0.5 279.3 0.5 1,173 2.5
Maricopa, AZ................................. 97.9 1,989.4 3.0 1,024 2.9
Private industry........................... 97.2 1,776.0 3.4 1,025 2.9
Natural resources and mining............. 0.4 8.7 3.5 974 4.1
Construction............................. 7.0 114.5 9.7 1,185 6.2
Manufacturing............................ 3.1 121.1 3.9 1,432 4.0
Trade, transportation, and utilities..... 18.2 393.9 1.8 919 2.8
Information.............................. 1.5 34.5 0.7 1,420 3.2
Financial activities..................... 11.1 178.9 3.1 1,344 2.1
Professional and business services....... 20.8 339.9 2.4 1,133 2.1
Education and health services............ 11.0 302.5 2.9 1,017 1.7
Leisure and hospitality.................. 8.0 218.1 3.8 495 4.0
Other services........................... 6.3 50.9 -1.0 753 4.3
Government................................. 0.7 213.5 0.0 1,012 2.7
Dallas, TX................................... 77.5 1,712.8 1.7 1,318 3.1
Private industry........................... 76.9 1,538.5 1.8 1,330 3.2
Natural resources and mining............. 0.5 9.2 14.7 3,218 -20.0
Construction............................. 4.6 88.8 2.7 1,420 3.3
Manufacturing............................ 2.8 112.6 0.8 1,584 9.9
Trade, transportation, and utilities..... 15.9 363.6 2.3 1,077 2.1
Information.............................. 1.4 48.2 -2.2 1,852 1.9
Financial activities..................... 9.6 165.4 2.2 1,802 2.3
Professional and business services....... 17.6 344.8 1.1 1,628 3.1
Education and health services............ 9.6 199.5 2.1 1,206 4.3
Leisure and hospitality.................. 6.9 160.9 1.9 560 3.3
Other services........................... 6.9 43.1 0.6 876 9.0
Government................................. 0.6 174.4 0.2 1,211 2.2
Orange, CA................................... 121.9 1,621.4 1.7 1,234 2.8
Private industry........................... 120.4 1,475.6 2.0 1,235 2.8
Natural resources and mining............. 0.2 2.5 -7.4 987 1.9
Construction............................. 6.9 103.5 4.8 1,481 6.5
Manufacturing............................ 5.0 158.2 -1.2 1,506 0.5
Trade, transportation, and utilities..... 17.2 271.1 1.2 1,055 1.0
Information.............................. 1.4 26.9 0.5 2,104 2.2
Financial activities..................... 11.6 118.5 0.0 2,187 7.6
Professional and business services....... 21.0 305.4 0.7 1,436 2.7
Education and health services............ 34.1 213.9 3.1 1,024 2.8
Leisure and hospitality.................. 8.7 217.3 2.6 552 3.4
Other services........................... 6.9 45.7 -0.4 748 2.7
Government................................. 1.5 145.8 -0.9 1,224 3.0
San Diego, CA................................ 111.9 1,462.0 1.8 1,221 4.3
Private industry........................... 110.0 1,226.5 2.0 1,198 4.5
Natural resources and mining............. 0.6 8.5 5.9 834 12.4
Construction............................. 7.0 81.5 4.0 1,329 5.7
Manufacturing............................ 3.2 109.1 0.4 1,655 4.3
Trade, transportation, and utilities..... 14.4 237.0 0.8 960 5.7
Information.............................. 1.2 24.3 -1.4 2,077 13.8
Financial activities..................... 10.3 74.6 1.3 1,581 1.5
Professional and business services....... 18.6 237.1 2.4 1,791 4.5
Education and health services............ 32.0 201.6 2.0 1,029 2.9
Leisure and hospitality.................. 8.4 192.1 0.7 528 3.1
Other services........................... 7.4 50.3 -0.5 656 1.9
Government................................. 1.9 235.5 0.7 1,335 3.0
King, WA..................................... 86.6 1,377.5 2.9 1,583 7.0
Private industry........................... 86.0 1,209.4 3.4 1,610 7.1
Natural resources and mining............. 0.4 3.0 3.8 1,321 9.8
Construction............................. 6.7 70.9 4.2 1,455 5.1
Manufacturing............................ 2.5 101.4 -1.1 1,679 1.0
Trade, transportation, and utilities..... 14.3 275.3 5.7 1,714 15.0
Information.............................. 2.3 104.5 4.9 3,127 8.9
Financial activities..................... 6.7 68.4 2.9 1,843 3.7
Professional and business services....... 18.0 227.1 2.6 1,892 3.8
Education and health services............ 18.6 174.3 2.8 1,092 3.4
Leisure and hospitality.................. 7.3 139.1 3.1 608 7.4
Other services........................... 9.2 45.4 2.3 884 3.2
Government................................. 0.5 168.2 -0.4 1,384 4.5
Miami-Dade, FL............................... 98.9 1,148.3 0.8 1,065 3.8
Private industry........................... 98.6 1,007.9 0.9 1,053 3.8
Natural resources and mining............. 0.5 9.2 1.0 643 -4.5
Construction............................. 6.6 46.0 2.0 1,031 4.8
Manufacturing............................ 2.9 41.1 1.0 985 2.8
Trade, transportation, and utilities..... 25.4 293.2 1.1 936 2.5
Information.............................. 1.5 17.8 -1.4 1,768 5.7
Financial activities..................... 10.7 76.3 0.5 1,700 3.7
Professional and business services....... 22.2 160.9 0.9 1,379 5.3
Education and health services............ 10.7 181.7 1.9 1,034 0.9
Leisure and hospitality.................. 7.4 140.7 -0.8 665 9.9
Other services........................... 8.4 39.6 -0.7 674 6.8
Government................................. 0.3 140.3 0.3 1,151 3.3
(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 2016 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,
fourth quarter 2017
Employment Average weekly
wage(1)
Establishments,
fourth quarter
State 2017 Percent Percent
(thousands) December change, Fourth change,
2017 December quarter fourth
(thousands) 2016-17 2017 quarter
2016-17
United States(2)........... 9,969.4 145,921.1 1.5 $1,109 3.9
Alabama.................... 126.5 1,955.3 1.1 928 2.9
Alaska..................... 22.1 306.7 -1.2 1,052 1.5
Arizona.................... 160.5 2,834.7 2.6 978 3.5
Arkansas................... 90.3 1,217.2 1.0 848 2.5
California................. 1,550.5 17,293.0 2.1 1,346 5.7
Colorado................... 199.3 2,653.3 2.5 1,133 4.3
Connecticut................ 119.7 1,689.7 0.3 1,317 2.2
Delaware................... 31.8 444.9 0.6 1,081 2.6
District of Columbia....... 41.2 769.0 0.9 1,812 2.7
Florida.................... 685.4 8,712.0 2.0 975 3.4
Georgia.................... 276.2 4,425.0 1.8 1,027 3.4
Hawaii..................... 42.2 664.5 0.8 984 3.1
Idaho...................... 62.6 712.4 3.0 857 7.1
Illinois................... 367.4 6,001.1 0.8 1,151 2.6
Indiana.................... 165.0 3,057.8 1.1 915 3.6
Iowa....................... 102.5 1,549.7 0.4 938 3.0
Kansas..................... 88.9 1,390.3 0.4 894 1.9
Kentucky................... 121.8 1,903.8 0.5 892 2.1
Louisiana.................. 132.4 1,918.8 0.4 933 2.1
Maine...................... 54.6 610.3 1.2 884 3.4
Maryland................... 171.5 2,683.6 0.5 1,207 3.3
Massachusetts.............. 254.7 3,582.2 1.3 1,411 4.4
Michigan................... 245.4 4,321.8 0.9 1,062 3.4
Minnesota.................. 172.6 2,875.7 1.3 1,100 3.4
Mississippi................ 74.1 1,140.6 0.5 774 2.4
Missouri................... 209.7 2,809.5 1.0 945 2.9
Montana.................... 50.1 461.4 1.0 843 2.7
Nebraska................... 74.3 980.9 0.9 901 3.0
Nevada..................... 81.1 1,351.9 3.5 955 3.2
New Hampshire.............. 52.8 661.3 0.7 1,132 3.7
New Jersey................. 273.4 4,106.9 1.6 1,262 1.8
New Mexico................. 58.5 816.7 0.6 865 2.5
New York................... 647.1 9,465.3 1.4 1,428 6.4
North Carolina............. 274.8 4,388.6 1.5 964 3.3
North Dakota............... 32.0 416.1 0.4 1,010 3.3
Ohio....................... 296.9 5,409.2 0.8 973 3.1
Oklahoma................... 111.6 1,607.8 1.2 895 3.5
Oregon..................... 153.2 1,900.4 2.0 1,014 4.5
Pennsylvania............... 357.5 5,870.4 1.2 1,075 3.5
Rhode Island............... 37.5 483.6 1.1 1,056 2.7
South Carolina............. 131.2 2,058.8 1.6 879 2.8
South Dakota............... 33.5 423.8 0.9 856 3.4
Tennessee.................. 159.2 2,984.8 1.3 1,000 3.0
Texas...................... 681.4 12,207.8 2.0 1,109 3.5
Utah....................... 102.0 1,465.5 3.6 936 2.9
Vermont.................... 25.7 314.7 0.5 919 2.5
Virginia................... 275.2 3,884.2 1.3 1,121 2.8
Washington................. 239.6 3,305.0 2.4 1,217 5.8
West Virginia.............. 50.7 693.1 0.1 847 4.7
Wisconsin.................. 175.0 2,872.6 1.0 951 3.0
Wyoming.................... 26.3 267.5 0.6 935 4.6
Puerto Rico................ 44.5 887.0 -4.4 570 2.5
Virgin Islands............. 3.4 34.3 -11.1 827 7.7
(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
