For release 10:00 a.m. (EDT), Wednesday, September 6, 2017 USDL-17-1220
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 2017
From March 2016 to March 2017, employment increased in 299 of the 346 largest U.S. counties, the
U.S. Bureau of Labor Statistics reported today. York, S.C., had the largest percentage increase with a
gain of 6.8 percent over the year, above the national job growth rate of 1.6 percent. Within York, the
largest employment increase occurred in professional and business services, which gained 3,539 jobs
over the year (40.3 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 2.7 percent. Within Kanawha, trade,
transportation, and utilities had the largest decrease in employment, with a loss of 692 jobs (-3.9
percent).
The U.S. average weekly wage increased 6.6 percent over the year, growing to $1,111 in the first
quarter of 2017. McLean, Ill., had the largest over-the-year percentage increase in average weekly wages
with a gain of 27.8 percent. Within McLean, an average weekly wage gain of $1,006 (69.9 percent) in
financial activities made the largest contribution to the county’s increase in average weekly wages.
Peoria, Ill., experienced the only percentage decrease in average weekly wages with a loss of 1.1 percent
over the year. Within Peoria, manufacturing had the largest impact on the county’s average weekly wage
change with a decrease of $605 (-31.3 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 6 months following the end of each quarter.
Large County Employment
In March 2017, national employment was 142.3 million (as measured by the QCEW program). Over the
year, employment increased 1.6 percent, or 2.2 million. In March 2017, the 346 U.S. counties with
75,000 or more jobs accounted for 72.8 percent of total U.S. employment and 79.0 percent of total
wages. These 346 counties had a net job growth of 1.7 million over the year, accounting for 76.1 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 219,100 jobs, which was 10.0 percent of the overall
job increase for the U.S. (See table A.)
Employment declined in 39 of the largest counties from March 2016 to March 2017. Kanawha, W.Va.,
had the largest over-the-year percentage decrease in employment (-2.7 percent), followed by Lafayette,
La.; Anchorage, Alaska; Oklahoma, Okla.; Peoria, Ill.; and Atlantic, N.J. (See table 1.)
Table A. Large counties ranked by March 2017 employment, March 2016-17 employment increase, and
March 2016-17 percent increase in employment
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Employment in large counties
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March 2017 employment | Increase in employment, | Percent increase in employment,
(thousands) | March 2016-17 | March 2016-17
| (thousands) |
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| |
United States 142,309.2| United States 2,180.3| United States 1.6
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| |
Los Angeles, Calif. 4,359.4| Los Angeles, Calif. 54.8| York, S.C. 6.8
Cook, Ill. 2,531.8| Maricopa, Ariz. 48.5| Davis, Utah 4.9
New York, N.Y. 2,436.8| Dallas, Texas 41.5| Williamson, Tenn. 4.6
Harris, Texas 2,265.1| King, Wash. 41.5| Merced, Calif. 4.5
Maricopa, Ariz. 1,914.1| Clark, Nev. 32.8| Deschutes, Ore. 4.5
Dallas, Texas 1,662.0| Orange, Calif. 32.3| Utah, Utah 4.5
Orange, Calif. 1,580.2| New York, N.Y. 30.5| Clark, Wash. 4.2
San Diego, Calif. 1,421.4| San Diego, Calif. 29.1| Collier, Fla. 3.8
King, Wash. 1,335.4| Fulton, Ga. 28.2| Denton, Texas 3.8
Miami-Dade, Fla. 1,130.2| Santa Clara, Calif. 26.2| Brevard, Fla. 3.7
| | Rutherford, Tenn. 3.7
| | Collin, Texas 3.7
| | Galveston, Texas 3.7
| | Thurston, Wash. 3.7
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Large County Average Weekly Wages
Average weekly wages for the nation increased to $1,111, a 6.6 percent increase, during the year ending
in the first quarter of 2017. Among the 346 largest counties, 345 had over-the-year increases in average
weekly wages. McLean, Ill., had the largest percentage wage increase among the largest U.S. counties
(27.8 percent). (See table B.)
Of the 346 largest counties, 1 experienced an over-the-year decrease in average weekly wages. Peoria,
Ill., had the only percentage decrease in average weekly wages (-1.1 percent). Somerset, N.J., had the
smallest percentage wage increase, followed by Fairfield, Conn.; Lafayette, La.; and Winnebago, Wis.
(See table 1.)
Table B. Large counties ranked by first quarter 2017 average weekly wages, first quarter 2016-17
increase in average weekly wages, and first 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
first quarter 2017 | wage, first quarter 2016-17 | weekly wage, first
| | quarter 2016-17
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| |
United States $1,111| United States $69| United States 6.6
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| |
New York, N.Y. $2,954| McLean, Ill. $248| McLean, Ill. 27.8
Santa Clara, Calif. 2,450| Santa Clara, Calif. 232| Elkhart, Ind. 15.1
San Mateo, Calif. 2,385| San Francisco, Calif. 203| Midland, Texas 14.3
San Francisco, Calif. 2,264| San Mateo, Calif. 183| Benton, Ark. 14.2
Somerset, N.J. 2,026| Benton, Ark. 179| Williamson, Texas 12.4
Suffolk, Mass. 2,016| Midland, Texas 179| New Castle, Del. 12.0
Fairfield, Conn. 1,939| New York, N.Y. 174| Stearns, Minn. 11.4
Washington, D.C. 1,885| New Castle, Del. 147| Yolo, Calif. 11.3
Arlington, Va. 1,847| King, Wash. 146| Washington, Ark. 11.0
Morris, N.J. 1,766| Middlesex, Mass. 142| Ramsey, Minn. 11.0
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Ten Largest U.S. Counties
Among the 10 largest counties, 9 had over-the-year percentage increases in employment in March 2017.
King, Wash., had the largest gain (3.2 percent). Within King, trade, transportation, and utilities had the
largest over-the-year employment level increase, with a gain of 14,813 jobs, or 6.1 percent. Harris,
Texas, had the only percentage decrease in employment among the 10 largest counties (-0.2 percent).
Within Harris, manufacturing had the largest over-the-year employment level decrease, with a loss of
8,503 jobs, or -4.8 percent. (See table 2.)
Average weekly wages increased over the year in all 10 of the largest U.S. counties. King, Wash.,
experienced the largest percentage gain in average weekly wages (10.0 percent). Within King,
information had the largest impact on the county’s average weekly wage growth. Within information,
average weekly wages increased by $496, or 14.4 percent, over the year. Harris, Texas, had the lowest
percent gain in average weekly wages among the 10 largest counties (3.9 percent). Within Harris, trade,
transportation, and utilities had the largest impact on the county’s average weekly wage growth with an
increase of $77 (6.1 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. March 2017 employment and 2017 first quarter
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 9.9 million employer reports cover 142.3 million full- and part-time workers. Data for the
first quarter of 2017 will be available later 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 release for second quarter 2017 is scheduled to be released
on Tuesday, December 5, 2017.
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| |
| County Changes |
| |
| Counties with annual average employment of 75,000 or more in 2016 are included in this release and |
| will be included in future 2017 releases. Three counties have been added to these publication tables: |
| Sussex, Del.; Maui + Kalawao, Hawaii; and Deschutes, Ore. One county, Gregg, Texas, which was |
| published in the 2016 releases, is excluded from this and future 2017 releases because its 2016 annual |
| average employment level was less than 75,000. |
| |
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| |
| Industry Changes |
| |
| Beginning with this release, the QCEW program now uses the 2017 version of the North American |
| Industry Classification System (NAICS) as the basis for the assignment and tabulation of economic data |
| by industry. For more information on the change to NAICS, please see the Federal Register notice at |
| www.census.gov/eos/www/naics/federal_register_notices/notices/fr08au16.pdf. For information on the |
| use of the 2017 version of NAICS in QCEW, see www.bls.gov/cew/naics2017.htm. |
| |
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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 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. Each of these measures--QCEW, Business Employment Dynamics (BED), and Current
Employment Statistics (CES)--makes use of the quarterly UI employment reports in producing
data; however, each measure has a somewhat different universe coverage, estimation procedure,
and publication product.
Differences in coverage and estimation methods can result in somewhat different measures of
employment change over time. It is important to understand program 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- | 634,000 establish-
| submitted by 9.9 | ministrative records| ments
| million establish- | submitted by 7.7 |
| 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 6 months | -7 months after the | -Usually first Friday
| after the end of | end of each quarter| of following month
| each quarter | |
-----------|---------------------|----------------------|------------------------
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 national
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -Analysis of employ-| cators
| surveys | ment expansion and |
| | contraction by size|
| | of firm |
| | |
-----------|---------------------|----------------------|------------------------
Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/ces/
Web sites | | |
---------------------------------------------------------------------------------
Coverage
Employment and wage data for workers covered by state UI laws are compiled from quarterly
contribution reports submitted to the SWAs by employers. For federal 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—some reflecting economic events, others reflecting administrative changes. For example,
economic change would come from a firm relocating into the county; administrative change would
come from a company correcting its county designation.
The over-the-year changes of employment and wages presented in this release have been adjusted
to account for most of the administrative corrections made to the 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
account for 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 2015 edition
of this publication, which was published in September 2016, contains selected data produced by
Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the
first quarter 2016 version of this news release. Tables and additional content from the 2015 edition
of Employment and Wages Annual Averages Online are now available at
www.bls.gov/cew/cewbultn15.htm. The 2016 edition of Employment and Wages Annual Averages
Online will be available in September 2017.
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,
first quarter 2017
Employment Average weekly wage(2)
Establishments,
County(1) first quarter Percent Ranking Percent Ranking
2017 March change, by First change, by
(thousands) 2017 March percent quarter first percent
(thousands) 2016-17(3) change 2017 quarter change
2016-17(3)
United States(4)......... 9,864.2 142,309.2 1.6 - $1,111 6.6 -
Jefferson, AL............ 18.4 341.7 1.3 190 1,099 7.1 118
Madison, AL.............. 9.5 193.9 2.3 98 1,126 5.6 233
Mobile, AL............... 10.1 170.0 0.7 248 871 6.3 183
Montgomery, AL........... 6.4 132.0 1.6 168 862 6.6 158
Shelby, AL............... 5.8 83.8 0.2 287 1,058 7.0 126
Tuscaloosa, AL........... 4.5 92.2 1.8 143 833 5.0 267
Anchorage, AK............ 8.3 146.7 -1.7 344 1,103 3.5 330
Maricopa, AZ............. 95.8 1,914.1 2.6 79 1,050 8.1 60
Pima, AZ................. 18.7 366.2 1.5 176 885 7.1 118
Benton, AR............... 6.3 116.7 2.6 79 1,444 14.2 4
Pulaski, AR.............. 14.5 248.5 0.7 248 948 6.2 189
Washington, AR........... 6.0 104.5 2.0 127 881 11.0 9
Alameda, CA.............. 61.7 763.6 2.8 65 1,462 8.3 50
Butte, CA................ 8.3 81.6 2.9 55 775 7.3 98
Contra Costa, CA......... 31.7 364.4 2.0 127 1,352 5.8 215
Fresno, CA............... 34.0 372.3 1.8 143 804 4.1 310
Kern, CA................. 18.2 301.0 2.4 95 890 5.5 239
Los Angeles, CA.......... 474.6 4,359.4 1.3 190 1,216 7.2 109
Marin, CA................ 12.4 114.6 2.1 114 1,339 5.0 267
Merced, CA............... 6.4 76.1 4.5 4 806 7.6 81
Monterey, CA............. 13.4 172.8 2.2 107 900 6.0 205
Napa, CA................. 5.8 75.8 3.1 43 1,005 5.8 215
Orange, CA............... 117.1 1,580.2 2.1 114 1,228 7.4 92
Placer, CA............... 12.7 160.0 3.6 15 1,063 7.3 98
Riverside, CA............ 60.9 705.7 2.9 55 870 6.4 170
Sacramento, CA........... 56.0 640.7 2.2 107 1,152 5.3 249
San Bernardino, CA....... 56.7 718.9 3.2 34 880 7.7 73
San Diego, CA............ 108.2 1,421.4 2.1 114 1,171 6.1 199
San Francisco, CA........ 59.7 714.1 3.0 50 2,264 9.8 21
San Joaquin, CA.......... 17.5 241.3 3.1 43 851 3.7 321
San Luis Obispo, CA...... 10.3 117.0 3.3 31 862 4.6 289
San Mateo, CA............ 27.7 398.5 3.1 43 2,385 8.3 50
Santa Barbara, CA........ 15.3 192.6 0.2 287 1,018 9.5 25
Santa Clara, CA.......... 71.0 1,056.8 2.5 85 2,450 10.5 13
Santa Cruz, CA........... 9.5 100.0 1.9 138 961 9.1 30
Solano, CA............... 11.1 136.0 1.1 209 1,131 5.9 210
Sonoma, CA............... 19.7 203.2 1.8 143 979 6.4 170
Stanislaus, CA........... 15.0 183.6 3.1 43 882 5.0 267
Tulare, CA............... 10.1 154.5 1.7 157 760 7.5 90
Ventura, CA.............. 26.4 322.7 0.7 248 1,111 3.0 334
Yolo, CA................. 6.6 99.3 2.1 114 1,148 11.3 8
Adams, CO................ 10.8 200.0 3.4 26 1,024 8.8 38
Arapahoe, CO............. 21.8 323.2 1.9 138 1,328 6.6 158
Boulder, CO.............. 15.1 177.7 2.7 73 1,281 8.5 44
Denver, CO............... 31.7 499.4 2.7 73 1,401 7.1 118
Douglas, CO.............. 11.9 117.3 2.5 85 1,273 6.2 189
El Paso, CO.............. 19.3 266.6 3.4 26 949 8.3 50
Jefferson, CO............ 20.0 228.7 -0.3 320 1,126 10.1 15
Larimer, CO.............. 11.9 153.3 3.0 50 988 9.9 19
Weld, CO................. 7.2 103.6 3.5 23 982 10.0 17
Fairfield, CT............ 35.2 414.8 -1.0 338 1,939 1.8 344
Hartford, CT............. 27.7 503.3 0.4 274 1,416 3.9 316
New Haven, CT............ 23.9 360.2 0.3 280 1,087 4.6 289
New London, CT........... 7.4 122.0 1.3 190 1,135 9.8 21
New Castle, DE........... 19.5 284.0 0.3 280 1,370 12.0 6
Sussex, DE............... 6.6 74.5 3.2 34 760 8.1 60
Washington, DC........... 39.5 760.7 1.2 201 1,885 7.0 126
Alachua, FL.............. 7.1 129.5 2.5 85 877 9.5 25
Bay, FL.................. 5.6 77.3 -0.6 331 744 4.5 296
Brevard, FL.............. 15.6 205.6 3.7 10 922 9.0 34
Broward, FL.............. 69.3 799.1 2.2 107 1,001 7.6 81
Collier, FL.............. 13.9 149.3 3.8 8 875 4.4 298
Duval, FL................ 29.4 496.9 2.9 55 1,046 5.4 244
Escambia, FL............. 8.3 133.1 2.7 73 846 8.9 37
Hillsborough, FL......... 42.0 677.1 1.6 168 1,061 8.4 45
Lake, FL................. 8.1 96.6 3.6 15 681 4.6 289
Lee, FL.................. 22.0 263.1 3.6 15 832 8.2 54
Leon, FL................. 8.7 147.4 0.5 269 843 7.9 63
Manatee, FL.............. 10.8 123.9 2.9 55 795 6.0 205
Marion, FL............... 8.3 101.1 2.3 98 697 4.3 302
Miami-Dade, FL........... 98.0 1,130.2 1.9 138 1,053 8.2 54
Okaloosa, FL............. 6.3 82.5 1.4 181 846 7.1 118
Orange, FL............... 41.7 817.5 3.2 34 942 5.5 239
Osceola, FL.............. 6.8 91.2 2.9 55 699 5.3 249
Palm Beach, FL........... 56.0 606.8 2.8 65 1,050 5.7 228
Pasco, FL................ 10.9 116.8 3.1 43 715 6.7 148
Pinellas, FL............. 32.9 425.1 2.1 114 913 5.3 249
Polk, FL................. 13.1 216.7 3.2 34 812 8.8 38
Sarasota, FL............. 15.9 169.7 3.0 50 856 7.3 98
Seminole, FL............. 14.9 186.2 3.2 34 902 7.9 63
Volusia, FL.............. 14.2 172.2 2.8 65 743 7.4 92
Bibb, GA................. 4.2 82.2 -0.2 314 838 7.2 109
Chatham, GA.............. 8.2 150.9 1.8 143 900 9.1 30
Clayton, GA.............. 4.0 121.8 1.0 218 1,181 3.0 334
Cobb, GA................. 22.0 353.9 2.5 85 1,192 6.1 199
DeKalb, GA............... 17.9 296.2 1.8 143 1,148 5.3 249
Fulton, GA............... 43.2 839.3 3.5 23 1,653 5.5 239
Gwinnett, GA............. 24.7 349.8 3.0 50 1,055 7.8 68
Hall, GA................. 4.4 84.4 2.9 55 874 8.2 54
Muscogee, GA............. 4.6 93.4 1.5 176 885 4.4 298
Richmond, GA............. 4.5 104.2 0.9 229 870 6.1 199
Honolulu, HI............. 26.3 474.5 0.7 248 999 7.2 109
Maui + Kalawao, HI....... 6.2 76.8 1.1 209 846 6.7 148
Ada, ID.................. 15.3 229.2 3.2 34 895 6.7 148
Champaign, IL............ 4.4 88.9 0.0 300 889 3.7 321
Cook, IL................. 154.2 2,531.8 0.4 274 1,365 6.9 135
DuPage, IL............... 38.3 614.4 0.7 248 1,275 6.3 183
Kane, IL................. 13.8 206.5 1.0 218 915 5.8 215
Lake, IL................. 22.4 325.1 -0.5 328 1,650 6.5 163
McHenry, IL.............. 8.7 95.2 0.8 237 847 5.6 233
McLean, IL............... 3.7 82.8 -0.6 331 1,141 27.8 1
Madison, IL.............. 6.0 98.4 2.4 95 821 4.1 310
Peoria, IL............... 4.5 98.7 -1.3 341 1,025 -1.1 346
St. Clair, IL............ 5.5 92.8 0.0 300 795 4.3 302
Sangamon, IL............. 5.2 127.0 -0.2 314 1,022 3.0 334
Will, IL................. 16.2 233.5 3.4 26 893 4.8 278
Winnebago, IL............ 6.6 124.4 -0.8 335 921 10.3 14
Allen, IN................ 8.8 182.7 1.2 201 895 7.3 98
Elkhart, IN.............. 4.7 130.9 3.3 31 977 15.1 2
Hamilton, IN............. 9.3 137.5 2.7 73 1,093 6.4 170
Lake, IN................. 10.4 185.1 0.7 248 898 5.8 215
Marion, IN............... 23.9 588.3 0.6 259 1,157 8.2 54
St. Joseph, IN........... 5.8 122.4 0.4 274 824 5.0 267
Tippecanoe, IN........... 3.4 83.2 1.3 190 914 5.2 255
Vanderburgh, IN.......... 4.8 107.1 1.4 181 863 8.4 45
Johnson, IA.............. 4.2 83.4 2.1 114 952 5.7 228
Linn, IA................. 6.8 128.5 0.1 294 1,020 6.5 163
Polk, IA................. 17.2 293.4 1.3 190 1,145 8.2 54
Scott, IA................ 5.6 89.9 1.0 218 855 7.8 68
Johnson, KS.............. 23.9 337.6 1.8 143 1,110 6.7 148
Sedgwick, KS............. 12.8 247.3 -0.4 325 944 8.6 42
Shawnee, KS.............. 5.2 96.8 1.4 181 879 4.4 298
Wyandotte, KS............ 3.6 89.8 2.2 107 1,011 5.2 255
Boone, KY................ 4.4 85.0 2.5 85 914 6.9 135
Fayette, KY.............. 11.0 192.0 2.0 127 901 5.3 249
Jefferson, KY............ 25.4 460.1 1.5 176 1,096 8.2 54
Caddo, LA................ 7.3 112.8 -1.0 338 814 5.9 210
Calcasieu, LA............ 5.2 96.6 1.8 143 917 4.1 310
East Baton Rouge, LA..... 15.5 268.7 0.0 300 1,009 7.7 73
Jefferson, LA............ 13.9 190.7 -0.5 328 925 6.4 170
Lafayette, LA............ 9.5 129.2 -2.3 345 872 2.0 343
Orleans, LA.............. 12.5 191.7 0.0 300 1,023 4.7 284
St. Tammany, LA.......... 8.3 87.6 0.3 280 876 2.6 340
Cumberland, ME........... 14.0 176.2 1.7 157 1,015 8.8 38
Anne Arundel, MD......... 15.2 267.3 2.0 127 1,120 4.8 278
Baltimore, MD............ 21.4 372.6 -0.1 308 1,075 7.7 73
Frederick, MD............ 6.4 99.8 1.0 218 985 4.6 289
Harford, MD.............. 5.8 91.4 1.3 190 1,008 4.8 278
Howard, MD............... 10.1 167.9 0.6 259 1,309 6.2 189
Montgomery, MD........... 32.9 466.4 1.2 201 1,499 5.2 255
Prince George's, MD...... 15.9 317.7 2.9 55 1,086 6.1 199
Baltimore City, MD....... 13.6 334.6 0.7 248 1,253 3.8 318
Barnstable, MA........... 9.5 86.0 0.3 280 909 7.3 98
Bristol, MA.............. 17.5 221.6 1.0 218 967 9.6 24
Essex, MA................ 25.2 317.9 -0.4 325 1,147 7.5 90
Hampden, MA.............. 18.0 205.3 0.3 280 965 4.8 278
Middlesex, MA............ 54.7 885.5 1.4 181 1,716 9.0 34
Norfolk, MA.............. 25.4 345.7 0.4 274 1,264 8.1 60
Plymouth, MA............. 15.8 186.5 1.1 209 965 5.8 215
Suffolk, MA.............. 29.3 665.0 2.2 107 2,016 6.0 205
Worcester, MA............ 25.0 340.4 1.1 209 1,082 9.0 34
Genesee, MI.............. 6.8 131.6 -0.3 320 840 3.6 325
Ingham, MI............... 6.0 150.8 1.9 138 987 3.8 318
Kalamazoo, MI............ 5.0 117.5 1.5 176 1,031 7.4 92
Kent, MI................. 14.3 394.8 1.7 157 929 6.8 140
Macomb, MI............... 17.5 323.1 1.4 181 1,110 9.3 28
Oakland, MI.............. 39.2 715.6 1.8 143 1,233 6.5 163
Ottawa, MI............... 5.6 122.1 2.0 127 894 10.1 15
Saginaw, MI.............. 3.9 83.0 -0.1 308 857 7.7 73
Washtenaw, MI............ 8.1 210.4 2.1 114 1,109 6.4 170
Wayne, MI................ 30.5 710.6 1.6 168 1,226 6.8 140
Anoka, MN................ 7.0 121.0 2.1 114 948 4.9 274
Dakota, MN............... 9.7 183.5 0.6 259 1,063 6.4 170
Hennepin, MN............. 37.7 905.0 2.5 85 1,471 7.6 81
Olmsted, MN.............. 3.3 95.4 0.8 237 1,231 5.7 228
Ramsey, MN............... 13.0 331.3 2.1 114 1,347 11.0 9
St. Louis, MN............ 5.2 96.2 0.7 248 831 6.4 170
Stearns, MN.............. 4.2 85.8 2.1 114 910 11.4 7
Washington, MN........... 5.4 81.5 2.8 65 923 7.6 81
Harrison, MS............. 4.6 84.9 1.2 201 733 4.7 284
Hinds, MS................ 5.8 120.6 -0.5 328 887 5.2 255
Boone, MO................ 4.9 93.6 1.4 181 826 7.3 98
Clay, MO................. 5.7 103.3 3.2 34 940 5.0 267
Greene, MO............... 8.8 164.6 2.0 127 804 8.4 45
Jackson, MO.............. 21.6 365.2 2.0 127 1,066 3.6 325
St. Charles, MO.......... 9.3 145.6 2.3 98 914 6.8 140
St. Louis, MO............ 38.0 599.3 0.9 229 1,149 7.0 126
St. Louis City, MO....... 14.1 222.2 0.3 280 1,185 3.3 331
Yellowstone, MT.......... 6.6 80.2 0.3 280 899 8.8 38
Douglas, NE.............. 18.9 335.6 1.2 201 1,005 6.7 148
Lancaster, NE............ 10.2 166.9 0.2 287 846 5.4 244
Clark, NV................ 56.0 957.8 3.5 23 922 6.7 148
Washoe, NV............... 14.5 212.4 3.6 15 910 6.8 140
Hillsborough, NH......... 12.1 199.9 1.0 218 1,140 5.4 244
Merrimack, NH............ 5.1 76.1 0.6 259 964 6.4 170
Rockingham, NH........... 10.8 145.3 1.7 157 1,042 6.0 205
Atlantic, NJ............. 6.6 120.2 -1.3 341 886 5.6 233
Bergen, NJ............... 33.3 439.5 1.1 209 1,288 6.2 189
Burlington, NJ........... 11.0 201.7 2.3 98 1,102 6.2 189
Camden, NJ............... 12.1 202.3 1.8 143 1,010 5.4 244
Essex, NJ................ 20.6 340.4 1.6 168 1,466 7.0 126
Gloucester, NJ........... 6.4 107.2 3.6 15 875 4.8 278
Hudson, NJ............... 15.2 259.8 3.6 15 1,632 7.2 109
Mercer, NJ............... 11.2 243.9 0.2 287 1,483 4.1 310
Middlesex, NJ............ 22.3 419.2 2.7 73 1,326 3.1 332
Monmouth, NJ............. 20.2 251.8 0.6 259 1,070 5.7 228
Morris, NJ............... 17.1 284.5 0.4 274 1,766 4.1 310
Ocean, NJ................ 13.2 159.3 1.6 168 847 4.7 284
Passaic, NJ.............. 12.7 166.9 0.9 229 1,015 3.6 325
Somerset, NJ............. 10.2 184.1 0.8 237 2,026 0.9 345
Union, NJ................ 14.4 216.9 0.6 259 1,423 7.6 81
Bernalillo, NM........... 18.3 321.9 0.5 269 896 6.7 148
Albany, NY............... 10.4 233.4 0.7 248 1,075 5.8 215
Bronx, NY................ 18.8 298.7 0.2 287 971 5.0 267
Broome, NY............... 4.6 86.3 0.2 287 813 7.4 92
Dutchess, NY............. 8.5 110.6 0.5 269 1,010 6.8 140
Erie, NY................. 24.9 465.3 0.8 237 957 7.0 126
Kings, NY................ 62.4 700.2 3.2 34 864 5.1 260
Monroe, NY............... 19.1 380.6 -0.1 308 971 5.3 249
Nassau, NY............... 54.2 619.4 1.3 190 1,175 4.4 298
New York, NY............. 129.2 2,436.8 1.3 190 2,954 6.3 183
Oneida, NY............... 5.4 104.3 1.7 157 815 5.8 215
Onondaga, NY............. 13.0 240.1 0.0 300 961 5.1 260
Orange, NY............... 10.5 140.1 0.8 237 888 7.6 81
Queens, NY............... 52.9 654.6 2.7 73 1,010 4.7 284
Richmond, NY............. 9.8 114.7 1.4 181 903 4.3 302
Rockland, NY............. 10.8 121.2 1.8 143 1,042 3.7 321
Saratoga, NY............. 6.0 83.3 1.4 181 952 8.4 45
Suffolk, NY.............. 53.1 642.9 0.6 259 1,116 5.1 260
Westchester, NY.......... 36.6 421.8 1.0 218 1,465 3.8 318
Buncombe, NC............. 9.1 128.6 2.3 98 796 8.4 45
Catawba, NC.............. 4.4 86.9 2.6 79 826 10.9 11
Cumberland, NC........... 6.2 118.9 -0.4 325 790 4.9 274
Durham, NC............... 8.3 198.4 2.1 114 1,388 5.8 215
Forsyth, NC.............. 9.2 182.2 0.5 269 1,093 7.8 68
Guilford, NC............. 14.2 277.7 0.6 259 930 6.5 163
Mecklenburg, NC.......... 36.9 672.1 2.5 85 1,469 7.8 68
New Hanover, NC.......... 8.0 110.2 3.1 43 852 6.1 199
Wake, NC................. 33.7 532.5 2.8 65 1,104 4.6 289
Cass, ND................. 7.1 115.2 0.9 229 941 5.5 239
Butler, OH............... 7.8 152.1 2.4 95 991 9.9 19
Cuyahoga, OH............. 35.8 709.4 0.1 294 1,114 6.7 148
Delaware, OH............. 5.3 85.3 2.1 114 1,171 7.3 98
Franklin, OH............. 31.7 737.5 2.3 98 1,106 6.2 189
Hamilton, OH............. 23.8 506.2 0.8 237 1,207 6.5 163
Lake, OH................. 6.3 93.4 -0.3 320 878 5.9 210
Lorain, OH............... 6.2 96.2 0.9 229 835 7.3 98
Lucas, OH................ 10.1 206.6 -0.3 320 946 7.0 126
Mahoning, OH............. 5.9 95.2 -0.1 308 733 7.0 126
Montgomery, OH........... 11.8 250.4 0.0 300 904 7.9 63
Stark, OH................ 8.5 156.2 -0.2 314 773 6.6 158
Summit, OH............... 14.3 262.0 0.1 294 979 3.7 321
Warren, OH............... 4.9 89.7 1.1 209 996 5.8 215
Cleveland, OK............ 5.7 79.4 -0.3 320 744 6.4 170
Oklahoma, OK............. 27.8 440.0 -1.5 343 1,028 7.1 118
Tulsa, OK................ 22.2 346.5 -0.8 335 981 7.2 109
Clackamas, OR............ 14.6 160.5 3.3 31 964 5.1 260
Deschutes, OR............ 8.2 77.6 4.5 4 822 7.3 98
Jackson, OR.............. 7.3 85.4 2.9 55 773 3.1 332
Lane, OR................. 11.9 153.1 2.8 65 802 6.2 189
Marion, OR............... 10.5 149.6 2.5 85 843 7.7 73
Multnomah, OR............ 34.4 498.3 1.8 143 1,109 2.6 340
Washington, OR........... 19.0 286.1 2.8 65 1,357 9.1 30
Allegheny, PA............ 35.8 685.0 0.8 237 1,203 7.2 109
Berks, PA................ 9.0 169.4 0.1 294 938 7.2 109
Bucks, PA................ 20.0 259.5 1.8 143 981 6.7 148
Butler, PA............... 5.1 83.7 -0.9 337 961 7.0 126
Chester, PA.............. 15.5 246.4 1.1 209 1,408 6.2 189
Cumberland, PA........... 6.5 131.3 0.9 229 960 5.6 233
Dauphin, PA.............. 7.6 177.9 0.1 294 1,060 5.8 215
Delaware, PA............. 14.2 220.0 1.2 201 1,220 7.9 63
Erie, PA................. 7.0 119.6 -1.0 338 799 4.3 302
Lackawanna, PA........... 5.8 96.4 -0.1 308 778 4.0 315
Lancaster, PA............ 13.5 233.3 1.2 201 881 6.5 163
Lehigh, PA............... 8.9 184.7 0.7 248 1,063 6.5 163
Luzerne, PA.............. 7.5 141.8 -0.2 314 825 7.4 92
Montgomery, PA........... 27.7 484.8 1.0 218 1,449 5.7 228
Northampton, PA.......... 6.8 113.0 3.1 43 917 2.7 338
Philadelphia, PA......... 35.4 667.1 2.2 107 1,274 5.8 215
Washington, PA........... 5.5 84.3 0.0 300 1,183 9.1 30
Westmoreland, PA......... 9.3 131.1 -0.6 331 841 5.9 210
York, PA................. 9.2 176.0 0.8 237 911 6.2 189
Providence, RI........... 18.1 281.5 -0.1 308 1,115 7.6 81
Charleston, SC........... 15.0 243.7 2.3 98 949 6.6 158
Greenville, SC........... 13.4 264.3 2.0 127 907 5.8 215
Horry, SC................ 8.4 122.9 2.6 79 628 6.8 140
Lexington, SC............ 6.4 115.7 1.8 143 820 8.6 42
Richland, SC............. 9.9 218.9 1.3 190 931 7.1 118
Spartanburg, SC.......... 6.1 136.1 3.6 15 891 4.5 296
York, SC................. 5.5 92.6 6.8 1 895 10.9 11
Minnehaha, SD............ 7.1 124.0 1.6 168 924 4.9 274
Davidson, TN............. 22.2 474.5 3.0 50 1,150 4.9 274
Hamilton, TN............. 9.5 198.6 1.7 157 944 7.4 92
Knox, TN................. 12.1 235.0 0.8 237 941 7.9 63
Rutherford, TN........... 5.5 123.1 3.7 10 907 7.7 73
Shelby, TN............... 20.4 488.2 0.7 248 1,059 7.1 118
Williamson, TN........... 8.5 127.0 4.6 3 1,287 7.1 118
Bell, TX................. 5.4 117.8 1.0 218 882 5.9 210
Bexar, TX................ 40.6 850.9 1.8 143 983 5.6 233
Brazoria, TX............. 5.7 104.8 0.6 259 1,115 3.6 325
Brazos, TX............... 4.5 102.3 2.1 114 765 6.4 170
Cameron, TX.............. 6.5 138.6 1.1 209 614 4.2 307
Collin, TX............... 24.2 391.6 3.7 10 1,330 4.8 278
Dallas, TX............... 75.6 1,662.0 2.6 79 1,376 6.9 135
Denton, TX............... 14.6 235.4 3.8 8 988 7.2 109
El Paso, TX.............. 15.0 300.2 2.0 127 730 6.0 205
Fort Bend, TX............ 12.9 176.6 1.7 157 1,023 2.9 337
Galveston, TX............ 6.2 109.9 3.7 10 951 2.7 338
Harris, TX............... 114.3 2,265.1 -0.2 314 1,443 3.9 316
Hidalgo, TX.............. 12.2 255.0 2.0 127 642 5.4 244
Jefferson, TX............ 5.9 122.7 0.5 269 1,139 6.1 199
Lubbock, TX.............. 7.5 138.0 1.5 176 796 5.2 255
McLennan, TX............. 5.2 112.3 2.3 98 854 6.9 135
Midland, TX.............. 5.4 85.6 1.7 157 1,428 14.3 3
Montgomery, TX........... 11.1 172.5 1.6 168 1,072 4.7 284
Nueces, TX............... 8.3 163.5 1.9 138 913 7.7 73
Potter, TX............... 3.9 78.4 -0.6 331 818 5.1 260
Smith, TX................ 6.1 101.8 1.4 181 832 6.3 183
Tarrant, TX.............. 42.5 863.4 2.8 65 1,063 6.3 183
Travis, TX............... 39.9 717.4 2.9 55 1,252 6.9 135
Webb, TX................. 5.3 99.6 2.5 85 675 4.2 307
Williamson, TX........... 10.4 162.5 3.6 15 1,135 12.4 5
Davis, UT................ 8.2 123.7 4.9 2 826 4.2 307
Salt Lake, UT............ 43.3 676.2 2.5 85 1,038 6.7 148
Utah, UT................. 15.5 225.1 4.5 4 849 7.3 98
Weber, UT................ 5.9 102.8 2.2 107 784 7.8 68
Chittenden, VT........... 6.8 99.8 -0.2 314 1,014 6.4 170
Arlington, VA............ 9.2 174.3 1.7 157 1,847 6.6 158
Chesterfield, VA......... 8.9 132.8 0.4 274 915 9.2 29
Fairfax, VA.............. 37.1 594.7 1.1 209 1,748 7.7 73
Henrico, VA.............. 11.4 190.5 0.8 237 1,119 9.7 23
Loudoun, VA.............. 12.1 160.8 3.4 26 1,239 3.6 325
Prince William, VA....... 9.2 125.3 1.7 157 900 7.3 98
Alexandria City, VA...... 6.4 93.2 0.0 300 1,467 5.0 267
Chesapeake City, VA...... 6.0 98.4 0.9 229 831 8.3 50
Newport News City, VA.... 3.9 96.5 0.1 294 1,064 4.6 289
Norfolk City, VA......... 5.8 141.6 1.2 201 1,025 4.3 302
Richmond City, VA........ 7.6 155.1 1.7 157 1,247 6.8 140
Virginia Beach City, VA.. 12.1 174.9 0.9 229 801 5.1 260
Benton, WA............... 5.8 85.0 3.4 26 1,039 5.6 233
Clark, WA................ 14.6 152.7 4.2 7 968 7.6 81
King, WA................. 86.8 1,335.4 3.2 34 1,601 10.0 17
Kitsap, WA............... 6.7 86.1 0.8 237 930 6.4 170
Pierce, WA............... 22.0 298.0 2.9 55 949 6.3 183
Snohomish, WA............ 20.8 282.3 0.6 259 1,186 5.8 215
Spokane, WA.............. 15.7 215.0 1.6 168 906 7.2 109
Thurston, WA............. 8.2 112.1 3.7 10 932 5.1 260
Whatcom, WA.............. 7.3 88.1 2.6 79 883 7.0 126
Yakima, WA............... 7.8 107.2 2.3 98 725 6.8 140
Kanawha, WV.............. 5.8 98.7 -2.7 346 915 7.6 81
Brown, WI................ 6.7 153.1 1.3 190 962 6.4 170
Dane, WI................. 15.1 328.8 2.0 127 1,098 9.5 25
Milwaukee, WI............ 25.8 481.7 0.2 287 1,058 6.2 189
Outagamie, WI............ 5.1 106.4 1.3 190 900 5.5 239
Waukesha, WI............. 12.7 238.2 1.0 218 1,068 4.6 289
Winnebago, WI............ 3.7 92.4 1.0 218 1,016 2.5 342
San Juan, PR............. 10.8 242.7 -1.2 (5) 633 1.0 (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 72.8 percent of
the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,
first quarter 2017
Employment Average weekly
wage(1)
Establishments,
first quarter
County by NAICS supersector 2017 Percent Percent
(thousands) March change, First change,
2017 March quarter first
(thousands) 2016-17(2) 2017 quarter
2016-17(2)
United States(3) ............................ 9,864.2 142,309.2 1.6 $1,111 6.6
Private industry........................... 9,565.9 120,451.2 1.7 1,121 7.0
Natural resources and mining............. 136.7 1,746.4 -0.1 1,218 5.3
Construction............................. 781.7 6,595.2 3.3 1,130 7.5
Manufacturing............................ 347.0 12,303.9 0.0 1,353 7.2
Trade, transportation, and utilities..... 1,917.5 26,775.5 0.8 916 7.1
Information.............................. 160.4 2,797.2 0.5 2,210 10.0
Financial activities..................... 866.2 7,993.6 1.6 2,279 7.9
Professional and business services....... 1,771.5 19,981.9 1.8 1,470 6.6
Education and health services............ 1,633.4 22,041.4 2.4 919 6.5
Leisure and hospitality.................. 829.4 15,454.4 2.1 432 6.1
Other services........................... 841.2 4,383.4 1.2 710 6.9
Government................................. 298.3 21,858.0 0.7 1,056 5.0
Los Angeles, CA.............................. 474.6 4,359.4 1.3 1,216 7.2
Private industry........................... 468.4 3,782.7 1.3 1,192 8.0
Natural resources and mining............. 0.5 7.7 -6.1 1,262 7.3
Construction............................. 13.7 133.8 2.0 1,188 7.7
Manufacturing............................ 12.2 347.7 -3.9 1,438 6.3
Trade, transportation, and utilities..... 53.1 809.6 0.6 975 8.5
Information.............................. 9.4 219.5 -3.6 2,350 10.3
Financial activities..................... 25.3 216.6 0.5 2,388 8.6
Professional and business services....... 47.1 596.9 1.7 1,496 10.2
Education and health services............ 221.1 763.2 2.2 874 8.4
Leisure and hospitality.................. 32.5 506.8 2.4 621 6.0
Other services........................... 26.5 145.2 -0.5 707 6.0
Government................................. 6.3 576.7 1.3 1,374 3.3
Cook, IL..................................... 154.2 2,531.8 0.4 1,365 6.9
Private industry........................... 152.9 2,237.5 0.6 1,384 7.0
Natural resources and mining............. 0.1 1.1 1.3 1,069 3.7
Construction............................. 12.3 68.3 0.3 1,483 3.7
Manufacturing............................ 6.3 183.4 -0.6 1,350 7.4
Trade, transportation, and utilities..... 30.0 463.2 0.1 1,063 8.8
Information.............................. 2.6 50.2 -0.7 2,190 3.0
Financial activities..................... 15.3 191.3 1.1 3,688 7.5
Professional and business services....... 32.6 464.3 -0.4 1,673 7.2
Education and health services............ 16.4 441.9 0.7 968 7.0
Leisure and hospitality.................. 14.3 270.9 2.4 504 6.1
Other services........................... 17.6 96.5 0.3 947 5.5
Government................................. 1.3 294.3 -0.6 1,218 5.7
New York, NY................................. 129.2 2,436.8 1.3 2,954 6.3
Private industry........................... 128.4 2,170.4 1.4 3,155 6.4
Natural resources and mining............. 0.0 0.2 -6.3 2,715 -0.6
Construction............................. 2.3 40.0 -0.8 1,918 5.8
Manufacturing............................ 2.1 25.2 -5.9 1,699 6.1
Trade, transportation, and utilities..... 19.3 249.6 -0.9 1,502 7.3
Information.............................. 4.9 158.8 2.9 3,390 6.0
Financial activities..................... 19.5 368.0 -0.8 9,424 10.7
Professional and business services....... 26.9 564.2 1.9 2,625 1.3
Education and health services............ 10.0 351.3 1.6 1,282 5.2
Leisure and hospitality.................. 13.8 294.3 1.8 877 5.9
Other services........................... 20.5 102.5 0.9 1,276 5.8
Government................................. 0.8 266.4 0.5 1,306 2.9
Harris, TX................................... 114.3 2,265.1 -0.2 1,443 3.9
Private industry........................... 113.7 1,985.8 -0.5 1,490 4.1
Natural resources and mining............. 1.6 65.9 -7.4 4,687 9.0
Construction............................. 7.3 158.2 -2.6 1,431 6.4
Manufacturing............................ 4.8 167.9 -4.8 1,821 6.7
Trade, transportation, and utilities..... 25.1 464.4 -0.3 1,349 6.1
Information.............................. 1.2 27.0 -1.7 1,632 9.2
Financial activities..................... 12.0 125.0 1.6 2,311 7.3
Professional and business services....... 23.2 388.5 -0.8 1,813 1.1
Education and health services............ 16.0 290.7 2.3 1,007 5.0
Leisure and hospitality.................. 9.9 230.3 1.1 446 3.2
Other services........................... 11.7 65.9 1.1 821 6.3
Government................................. 0.6 279.3 2.1 1,111 3.0
Maricopa, AZ................................. 95.8 1,914.1 2.6 1,050 8.1
Private industry........................... 95.1 1,701.2 2.8 1,054 8.0
Natural resources and mining............. 0.4 8.5 1.9 1,191 15.2
Construction............................. 6.8 105.7 4.8 1,070 10.2
Manufacturing............................ 3.1 114.9 -1.3 1,535 5.9
Trade, transportation, and utilities..... 18.2 368.9 1.7 966 7.3
Information.............................. 1.4 34.4 0.5 1,542 14.4
Financial activities..................... 10.6 173.0 5.4 1,555 8.4
Professional and business services....... 20.4 322.7 1.3 1,142 8.2
Education and health services............ 10.5 290.0 3.1 995 7.3
Leisure and hospitality.................. 7.5 217.3 3.1 479 7.2
Other services........................... 5.8 50.1 -2.7 817 23.6
Government................................. 0.7 213.0 0.8 1,013 8.1
Dallas, TX................................... 75.6 1,662.0 2.6 1,376 6.9
Private industry........................... 75.0 1,488.9 2.9 1,403 7.1
Natural resources and mining............. 0.5 8.0 -2.5 6,316 28.9
Construction............................. 4.5 86.6 4.8 1,267 11.5
Manufacturing............................ 2.7 111.0 0.4 1,919 13.1
Trade, transportation, and utilities..... 15.9 335.9 2.9 1,128 7.0
Information.............................. 1.4 49.2 1.9 2,549 3.8
Financial activities..................... 9.3 162.0 3.9 2,299 7.1
Professional and business services....... 17.0 337.3 3.1 1,516 4.8
Education and health services............ 9.4 196.3 2.8 1,065 4.9
Leisure and hospitality.................. 6.7 158.7 3.0 509 4.7
Other services........................... 7.0 42.4 0.6 829 8.5
Government................................. 0.6 173.1 -0.4 1,147 4.7
Orange, CA................................... 117.1 1,580.2 2.1 1,228 7.4
Private industry........................... 115.6 1,424.7 2.2 1,208 7.9
Natural resources and mining............. 0.2 3.0 0.6 868 -11.6
Construction............................. 6.6 97.8 3.0 1,361 9.5
Manufacturing............................ 4.9 156.6 -0.9 1,590 11.1
Trade, transportation, and utilities..... 16.7 255.9 0.7 1,092 9.2
Information.............................. 1.3 26.6 1.0 2,311 14.3
Financial activities..................... 11.0 117.1 1.4 2,058 8.6
Professional and business services....... 20.1 291.2 1.8 1,403 4.9
Education and health services............ 31.3 208.0 3.7 940 6.8
Leisure and hospitality.................. 8.5 211.2 1.9 499 9.0
Other services........................... 6.8 45.4 1.4 712 7.4
Government................................. 1.5 155.5 1.2 1,413 4.1
San Diego, CA................................ 108.2 1,421.4 2.1 1,171 6.1
Private industry........................... 106.3 1,187.2 2.1 1,149 6.3
Natural resources and mining............. 0.6 8.9 -6.3 697 12.1
Construction............................. 6.6 77.4 4.2 1,198 8.3
Manufacturing............................ 3.2 107.1 0.6 1,767 11.2
Trade, transportation, and utilities..... 14.1 222.8 0.9 968 3.9
Information.............................. 1.1 24.0 -0.1 1,912 4.0
Financial activities..................... 9.8 72.1 1.3 1,750 10.5
Professional and business services....... 17.7 228.5 0.6 1,592 3.0
Education and health services............ 30.2 196.2 2.1 965 10.5
Leisure and hospitality.................. 8.2 190.0 2.4 495 6.2
Other services........................... 7.2 50.0 1.3 622 7.6
Government................................. 1.9 234.2 2.3 1,280 5.0
King, WA..................................... 86.8 1,335.4 3.2 1,601 10.0
Private industry........................... 86.3 1,165.1 3.4 1,638 10.5
Natural resources and mining............. 0.4 2.7 -3.1 1,184 -41.9
Construction............................. 6.6 68.2 5.6 1,367 10.0
Manufacturing............................ 2.5 101.7 -3.5 1,890 10.3
Trade, transportation, and utilities..... 14.4 256.7 6.1 1,533 13.0
Information.............................. 2.2 100.2 6.5 3,949 14.4
Financial activities..................... 6.6 66.6 3.0 2,118 5.8
Professional and business services....... 17.6 220.2 2.1 1,797 6.0
Education and health services............ 19.4 170.6 3.2 1,055 12.8
Leisure and hospitality.................. 7.2 133.8 3.5 545 9.0
Other services........................... 9.2 44.3 2.5 885 4.4
Government................................. 0.5 170.3 2.0 1,346 6.4
Miami-Dade, FL............................... 98.0 1,130.2 1.9 1,053 8.2
Private industry........................... 97.6 990.4 1.9 1,031 7.7
Natural resources and mining............. 0.5 10.1 0.6 587 13.8
Construction............................. 6.5 45.7 7.7 989 6.2
Manufacturing............................ 2.9 41.0 1.7 934 5.8
Trade, transportation, and utilities..... 25.9 280.7 1.0 964 8.7
Information.............................. 1.6 18.2 1.3 1,977 13.4
Financial activities..................... 10.7 77.8 4.3 2,010 8.1
Professional and business services....... 21.8 156.8 2.8 1,215 7.9
Education and health services............ 10.5 178.1 2.2 952 5.7
Leisure and hospitality.................. 7.3 140.9 -1.1 587 3.5
Other services........................... 8.4 39.8 1.0 630 9.0
Government................................. 0.3 139.8 1.9 1,209 11.5
(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,
first quarter 2017
Employment Average weekly
wage(1)
Establishments,
first quarter
State 2017 Percent Percent
(thousands) March change, First change,
2017 March quarter first
(thousands) 2016-17 2017 quarter
2016-17
United States(2)........... 9,864.2 142,309.2 1.6 $1,111 6.6
Alabama.................... 123.7 1,928.9 1.4 893 6.2
Alaska..................... 22.1 312.8 -1.8 1,061 3.9
Arizona.................... 156.8 2,743.0 2.4 991 8.1
Arkansas................... 89.6 1,199.9 0.7 859 8.5
California................. 1,512.5 16,831.4 2.3 1,295 7.6
Colorado................... 196.1 2,573.2 2.3 1,136 7.5
Connecticut................ 118.0 1,651.5 0.1 1,417 4.0
Delaware................... 31.6 433.2 0.8 1,185 10.7
District of Columbia....... 39.5 760.7 1.2 1,885 7.0
Florida.................... 679.4 8,532.6 2.8 949 7.2
Georgia.................... 276.1 4,317.1 2.7 1,068 6.1
Hawaii..................... 41.5 653.6 0.9 954 6.8
Idaho...................... 60.2 690.4 3.0 775 7.0
Illinois................... 408.2 5,842.0 0.5 1,195 6.3
Indiana.................... 164.1 2,985.8 1.2 918 7.6
Iowa....................... 101.4 1,518.3 0.0 899 6.5
Kansas..................... 90.9 1,368.0 0.4 888 6.7
Kentucky................... 124.1 1,864.1 1.1 879 6.9
Louisiana.................. 130.4 1,901.3 -0.5 906 5.5
Maine...................... 54.4 586.7 1.0 860 7.2
Maryland................... 171.0 2,626.0 1.2 1,171 5.8
Massachusetts.............. 251.3 3,464.0 1.1 1,428 7.7
Michigan................... 241.9 4,230.6 1.7 1,041 6.8
Minnesota.................. 164.7 2,806.4 2.1 1,149 7.9
Mississippi................ 73.2 1,122.9 0.1 750 5.3
Missouri................... 201.7 2,767.0 1.4 930 5.9
Montana.................... 47.6 451.5 1.4 800 6.5
Nebraska................... 72.0 960.7 0.4 868 6.4
Nevada..................... 81.3 1,311.6 3.8 932 6.9
New Hampshire.............. 51.4 643.2 1.2 1,070 7.3
New Jersey................. 272.0 3,955.1 1.5 1,333 5.0
New Mexico................. 58.2 803.3 0.2 838 5.9
New York................... 646.6 9,159.3 1.3 1,541 5.9
North Carolina............. 270.0 4,287.0 1.8 991 6.9
North Dakota............... 31.8 405.7 -1.0 953 5.0
Ohio....................... 294.8 5,278.3 0.8 976 6.7
Oklahoma................... 109.8 1,563.9 -1.0 883 5.9
Oregon..................... 149.4 1,855.0 2.5 984 5.4
Pennsylvania............... 358.6 5,712.3 0.8 1,078 6.5
Rhode Island............... 37.1 465.4 0.3 1,055 7.2
South Carolina............. 125.9 2,017.9 2.2 864 7.3
South Dakota............... 33.0 413.4 0.7 819 6.2
Tennessee.................. 156.8 2,906.2 1.8 945 6.7
Texas...................... 668.0 11,924.5 1.7 1,124 5.5
Utah....................... 96.7 1,411.3 3.1 905 6.6
Vermont.................... 25.3 305.6 0.2 889 6.7
Virginia................... 265.5 3,796.3 1.4 1,129 6.9
Washington................. 241.1 3,225.9 2.6 1,215 8.6
West Virginia.............. 49.8 678.2 -0.8 837 7.6
Wisconsin.................. 171.0 2,803.7 1.1 933 6.8
Wyoming.................... 26.0 262.4 -2.3 880 3.3
Puerto Rico................ 46.2 887.7 -0.9 526 1.2
Virgin Islands............. 3.4 38.7 0.0 797 3.1
(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
