For release 10:00 a.m. (EDT), Wednesday, June 7, 2017 USDL-17-0769
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 2016
From December 2015 to December 2016, employment increased in 280 of the 344 largest U.S.
counties, the U.S. Bureau of Labor Statistics reported today. Williamson, Tenn., had the largest
percentage increase with a gain of 5.1 percent over the year, above the national job growth rate of 1.2
percent. Within Williamson, the largest employment increase occurred in professional and business
services, which gained 1,995 jobs over the year (6.0 percent). Lafayette, La., had the largest over-the-
year percentage decrease in employment among the largest counties in the U.S., with a loss of 5.1
percent. Within Lafayette, natural resources and mining had the largest decrease in employment, with a
loss of 2,397 jobs (-19.8 percent).
The U.S. average weekly wage decreased 1.5 percent over the year, declining to $1,067 in the fourth
quarter of 2016. This is one of only eight declines in the history of the series, which dates back to 1978.
The 1.5 percent decline in average weekly wages was the largest decline since fourth quarter 2011, when
average weekly wages decreased by 1.7 percent. The most recent decline occurred in first quarter 2016,
when the U.S. average weekly wage decreased 0.6 percent over the year. McLean, Ill., had the largest
over-the-year percentage decrease in average weekly wages with a loss of 9.2 percent. Within McLean,
an average weekly wage loss of $178 (-10.9 percent) in financial activities made the largest contribution
to the county’s decrease in average weekly wages. Clayton, Ga., experienced the largest percentage
increase in average weekly wages with a gain of 11.3 percent over the year. Within Clayton, trade,
transportation, and utilities had the largest impact on the county’s average weekly wage growth with an
increase of $265 (25.3 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 December 2016, national employment was 143.7 million (as measured by the QCEW program). Over
the year, employment increased 1.2 percent, or 1.8 million. In December 2016, the 344 U.S. counties
with 75,000 or more jobs accounted for 72.8 percent of total U.S. employment and 78.1 percent of total
wages. These 344 counties had a net job growth of 1.4 million over the year, accounting for 80.7 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 215,600 jobs, which was 12.2 percent of the overall
job increase for the U.S. (See table A.)
Employment declined in 58 of the largest counties from December 2015 to December 2016. Lafayette,
La., had the largest over-the-year percentage decrease in employment (-5.1 percent), followed by Gregg,
Texas; Midland, Texas; Erie, Pa.; and Kanawha, W.Va. (See table 1.)
Table A. Large counties ranked by December 2016 employment, December 2015-16 employment increase, and
December 2015-16 percent increase in employment
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Employment in large counties
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December 2016 employment | Increase in employment, | Percent increase in employment,
(thousands) | December 2015-16 | December 2015-16
| (thousands) |
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| |
United States 143,749.9| United States 1,773.6| United States 1.2
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| |
Los Angeles, Calif. 4,415.7| Los Angeles, Calif. 50.2| Williamson, Tenn. 5.1
Cook, Ill. 2,590.2| Dallas, Texas 45.7| York, S.C. 4.6
New York, N.Y. 2,471.6| Maricopa, Ariz. 45.2| Williamson, Texas 4.5
Harris, Texas 2,272.0| King, Wash. 42.7| Utah, Utah 4.5
Maricopa, Ariz. 1,926.9| Orange, Calif. 31.8| Northampton, Pa. 4.4
Dallas, Texas 1,688.4| Fulton, Ga. 30.4| Brevard, Fla. 4.2
Orange, Calif. 1,588.8| Santa Clara, Calif. 25.7| Seminole, Fla. 4.2
San Diego, Calif. 1,427.5| Clark, Nev. 23.7| Galveston, Texas 4.0
King, Wash. 1,340.4| San Diego, Calif. 21.8| Thurston, Wash. 4.0
Miami-Dade, Fla. 1,132.9| Orange, Fla. 21.5| Benton, Wash. 3.8
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Large County Average Weekly Wages
Average weekly wages for the nation declined to $1,067, a 1.5 percent decrease, during the year ending
in the fourth quarter of 2016. Among the 344 largest counties, 290 had over-the-year decreases in
average weekly wages. McLean, Ill., had the largest percentage wage decrease among the largest U.S.
counties (-9.2 percent). (See table B.)
Of the 344 largest counties, 48 experienced over-the-year increases in average weekly wages. Clayton,
Ga., had the largest percentage increase in average weekly wages (11.3 percent), followed by
Washington, Pa.; Marin, Calif.; Elkhart, Ind.; San Francisco, Calif.; and Champaign, Ill. (See table 1.)
Table B. Large counties ranked by fourth quarter 2016 average weekly wages, fourth quarter 2015-16
decrease in average weekly wages, and fourth quarter 2015-16 percent decrease in average weekly wages
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Average weekly wage in large counties
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Average weekly wage, | Decrease in average weekly | Percent decrease in average
fourth quarter 2016 | wage, fourth quarter 2015-16 | weekly wage, fourth
| | quarter 2015-16
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| |
United States $1,067| United States -$16| United States -1.5
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| |
Santa Clara, Calif. $2,365| McLean, Ill. -$93| McLean, Ill. -9.2
New York, N.Y. 2,212| Douglas, Colo. -88| Clay, Mo. -8.3
San Mateo, Calif. 2,098| Clay, Mo. -83| Lafayette, La. -8.0
San Francisco, Calif. 2,068| Morris, N.J. -80| Douglas, Colo. -6.8
Suffolk, Mass. 1,888| Lafayette, La. -79| Passaic, N.J. -6.0
Washington, D.C. 1,763| Washington, Ore. -75| Washington, Ore. -5.8
Arlington, Va. 1,677| Passaic, N.J. -67| Tarrant, Texas -5.7
Fairfield, Conn. 1,676| Fairfield, Conn. -66| Sedgwick, Kan. -5.5
Fairfax, Va. 1,610| Lake, Ill. -65| Harford, Md. -5.4
Somerset, N.J. 1,563| Harris, Texas -65| Fort Bend, Texas -5.2
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Ten Largest U.S. Counties
Among the 10 largest counties, 9 had over-the-year percentage increases in employment in December
2016. King, Wash., had the largest gain (3.3 percent). Within King, trade, transportation, and utilities
had the largest over-the-year employment level increase, with a gain of 11,720 jobs, or 4.7 percent.
Harris, Texas, had the only percentage decrease in employment among the 10 largest counties (-1.3
percent). Within Harris, manufacturing had the largest over-the-year employment level decrease, with a
loss of 14,974 jobs, or -8.3 percent. (See table 2.)
Average weekly wages decreased over the year in 9 of the 10 largest U.S. counties. Harris, Texas,
experienced the largest percentage loss in average weekly wages (-4.7 percent). Within Harris,
professional and business services had the largest impact on the county’s average weekly wage decline.
Within professional and business services, average weekly wages decreased by $92, or -5.2 percent,
over the year. King, Wash., had the only percentage gain in average weekly wages among the 10 largest
counties (3.5 percent). Within King, trade, transportation, and utilities had the largest impact on the
county’s average weekly wage growth with an increase of $249 (20.2 percent) over the year.
For More Information
The tables included in this release contain data for the nation and for the 344 U.S. counties with annual
average employment levels of 75,000 or more in 2015. December 2016 employment and 2016 fourth
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 143.7 million full- and part-time workers. Data for the
fourth quarter of 2016 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 first quarter 2017 is scheduled to be released on
Wednesday, September 6, 2017.
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| |
| Upcoming Industry Changes to QCEW Data |
| |
| Beginning with the release of first quarter 2017 data, the program will switch to 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, please see the Federal |
| Register notice at www.census.gov/eos/www/naics/federal_register_notices/notices/fr08au16.pdf. |
| |
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Technical Note
These data are the product of a federal-state cooperative program, the Quarterly Census of
Employment and Wages (QCEW) program, also known as the ES-202 program. The data are
derived from summaries of employment and total pay of workers covered by state and federal
unemployment insurance (UI) legislation and provided by State Workforce Agencies (SWAs). The
summaries are a result of the administration of state unemployment insurance programs that
require most employers to pay quarterly taxes based on the employment and wages of workers
covered by UI. QCEW data in this release are based on the 2012 North American Industry
Classification System (NAICS). Data for 2016 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 345 counties
presented in this release were derived using 2015 preliminary annual averages of employment. For
2016 data, four counties have been added to the publication tables: Merced, Calif.; Napa, Calif.;
Bay, Fla.; and Merrimack, N.H. These counties will be included in all 2016 quarterly releases. Two
counties, Black Hawk, Iowa, and Ector, Texas, which were published in the 2015 releases, will be
excluded from this and future 2016 releases because their 2015 annual average employment levels
were less than 75,000. The counties in table 2 are selected and sorted each year based on the annual
average employment from the preceding year.
The preliminary QCEW data presented in this release may differ from data released by the
individual states. These potential differences result from the states' 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 9.7 | ministrative records| ments
| million establish- | submitted by 7.7 |
| ments in first | million private-sec-|
| quarter of 2016 | 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, met-| and contractions at | industry
| ropolitan statisti-| the national level |
| cal area (MSA), | by NAICS supersec- |
| state, and national| tors and by size of |
| levels by detailed | firm, and at the |
| industry | 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 9.5
million employer reports of employment and wages submitted by states to the BLS in 2015. 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 2015, UI and UCFE programs
covered workers in 139.5 million jobs. The estimated 134.4 million workers in these jobs (after
adjustment for multiple jobholders) represented 96.5 percent of civilian wage and salary
employment. Covered workers received $7.385 trillion in pay, representing 94.0 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 2015 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 BDMInfo@bls.gov.
Information in this release will be made available to sensory impaired individuals upon request.
Voice phone: (202) 691-5200; TDD message referral phone number: (800) 877-8339.
Table 1. Covered establishments, employment, and wages in the 345 largest counties,
fourth quarter 2016
Employment Average weekly wage(2)
Establishments,
County(1) fourth quarter Percent Ranking Percent Ranking
2016 December change, by Fourth change, by
(thousands) 2016 December percent quarter fourth percent
(thousands) 2015-16(3) change 2016 quarter change
2015-16(3)
United States(4)......... 9,869.9 143,749.9 1.2 - $1,067 -1.5 -
Jefferson, AL............ 18.5 343.9 0.5 242 1,043 -0.7 95
Madison, AL.............. 9.5 195.2 1.8 114 1,098 -4.0 311
Mobile, AL............... 10.0 169.7 -0.4 308 938 -0.5 76
Montgomery, AL........... 6.4 132.6 1.2 172 942 -0.6 84
Shelby, AL............... 5.8 84.4 -0.4 308 998 -2.2 223
Tuscaloosa, AL........... 4.5 92.5 -0.3 302 873 -1.0 120
Anchorage, AK............ 8.4 149.2 -2.1 338 1,082 -4.9 327
Maricopa, AZ............. 96.5 1,926.9 2.4 76 994 -2.3 233
Pima, AZ................. 18.8 367.2 1.3 164 860 -3.4 288
Benton, AR............... 6.2 117.5 3.1 32 1,017 -2.5 242
Pulaski, AR.............. 14.5 250.7 0.6 230 949 -2.6 252
Washington, AR........... 5.9 104.7 1.8 114 950 -0.2 60
Alameda, CA.............. 61.4 760.6 2.0 105 1,377 -1.9 191
Butte, CA................ 8.2 81.3 1.8 114 790 -1.3 144
Contra Costa, CA......... 31.7 364.3 2.0 105 1,289 0.2 39
Fresno, CA............... 33.6 371.4 1.8 114 857 1.2 16
Kern, CA................. 18.1 310.3 0.8 211 868 -2.0 198
Los Angeles, CA.......... 472.0 4,415.7 1.1 184 1,256 -0.6 84
Marin, CA................ 12.5 115.3 1.2 172 1,378 4.3 3
Merced, CA............... 6.4 75.9 3.2 28 807 1.3 15
Monterey, CA............. 13.4 170.2 2.4 76 915 -0.2 60
Napa, CA................. 5.8 73.2 0.4 250 1,065 -0.2 60
Orange, CA............... 116.3 1,588.8 2.0 105 1,200 -0.6 84
Placer, CA............... 12.5 157.4 2.9 48 1,083 2.0 10
Riverside, CA............ 60.1 707.1 3.1 32 835 -0.5 76
Sacramento, CA........... 55.8 643.7 2.0 105 1,132 -0.4 70
San Bernardino, CA....... 56.1 725.7 -0.1 287 890 0.5 33
San Diego, CA............ 107.8 1,427.5 1.6 139 1,170 -1.5 164
San Francisco, CA........ 59.9 715.5 2.7 58 2,068 3.7 5
San Joaquin, CA.......... 17.4 242.6 3.4 20 893 -0.3 67
San Luis Obispo, CA...... 10.3 113.7 1.9 110 884 -2.5 242
San Mateo, CA............ 27.6 398.8 1.7 130 2,098 -1.5 164
Santa Barbara, CA........ 15.3 192.0 0.0 281 1,025 -1.2 138
Santa Clara, CA.......... 70.9 1,064.0 2.5 71 2,365 0.9 18
Santa Cruz, CA........... 9.5 99.4 1.6 139 933 -2.0 198
Solano, CA............... 11.0 138.2 1.9 110 1,074 -0.9 110
Sonoma, CA............... 19.6 203.5 1.5 146 1,018 -2.5 242
Stanislaus, CA........... 14.9 182.3 1.5 146 884 0.0 49
Tulare, CA............... 10.0 160.0 3.1 32 772 0.9 18
Ventura, CA.............. 26.4 322.2 -0.1 287 1,044 -1.6 168
Yolo, CA................. 6.6 98.2 0.9 205 1,106 -3.7 301
Adams, CO................ 10.5 202.0 3.6 14 1,022 -1.3 144
Arapahoe, CO............. 21.6 324.6 1.6 139 1,227 -1.8 183
Boulder, CO.............. 14.7 179.9 3.0 39 1,237 -2.4 237
Denver, CO............... 30.7 501.7 2.8 50 1,287 -0.4 70
Douglas, CO.............. 11.6 118.9 1.8 114 1,204 -6.8 341
El Paso, CO.............. 18.5 268.0 2.7 58 943 -1.4 149
Jefferson, CO............ 21.5 234.4 0.7 223 1,072 -0.9 110
Larimer, CO.............. 11.6 154.0 2.5 71 980 -0.6 84
Weld, CO................. 6.8 100.4 0.2 264 900 -2.9 268
Fairfield, CT............ 35.2 426.8 -0.9 322 1,676 -3.8 306
Hartford, CT............. 27.6 512.3 0.3 257 1,264 -3.2 282
New Haven, CT............ 23.8 368.5 0.4 250 1,094 -2.8 266
New London, CT........... 7.4 123.3 0.8 211 1,023 -3.3 286
New Castle, DE........... 19.5 291.3 -0.8 318 1,166 -2.6 252
Washington, DC........... 39.5 760.9 0.5 242 1,763 0.1 40
Alachua, FL.............. 7.1 130.3 3.0 39 864 -5.1 333
Bay, FL.................. 5.5 76.1 0.3 257 783 -0.6 84
Brevard, FL.............. 15.5 206.1 4.2 6 941 -1.6 168
Broward, FL.............. 68.7 802.5 1.8 114 1,000 -1.9 191
Collier, FL.............. 13.7 150.2 3.6 14 915 -4.5 323
Duval, FL................ 29.0 499.0 2.6 65 1,001 -1.2 138
Escambia, FL............. 8.2 131.7 2.8 50 830 -3.3 286
Hillsborough, FL......... 41.5 686.9 2.3 89 1,010 -2.6 252
Lake, FL................. 8.0 96.0 3.2 28 721 -2.4 237
Lee, FL.................. 21.7 259.8 2.5 71 844 0.4 37
Leon, FL................. 8.7 148.3 2.1 98 860 -2.6 252
Manatee, FL.............. 10.6 122.7 1.2 172 809 -0.9 110
Marion, FL............... 8.2 102.7 3.5 19 750 -0.1 55
Miami-Dade, FL........... 97.5 1,132.9 1.3 164 1,029 -2.5 242
Okaloosa, FL............. 6.3 81.4 1.9 110 869 -1.0 120
Orange, FL............... 41.2 813.7 2.7 58 940 -0.5 76
Osceola, FL.............. 6.7 90.1 2.1 98 724 -0.5 76
Palm Beach, FL........... 55.5 602.8 2.4 76 1,055 -2.4 237
Pasco, FL................ 10.7 117.1 3.0 39 738 -1.5 164
Pinellas, FL............. 32.6 428.2 2.4 76 965 -1.6 168
Polk, FL................. 13.0 215.0 2.1 98 799 -2.2 223
Sarasota, FL............. 15.7 169.1 2.9 48 902 -1.0 120
Seminole, FL............. 14.8 188.1 4.2 6 897 0.0 49
Volusia, FL.............. 14.1 170.9 3.7 11 761 0.1 40
Bibb, GA................. 4.6 83.0 1.4 156 816 -2.6 252
Chatham, GA.............. 8.8 150.4 1.7 130 886 -3.7 301
Clayton, GA.............. 4.5 124.1 2.2 90 1,006 11.3 1
Cobb, GA................. 24.2 353.4 2.6 65 1,094 -1.9 191
DeKalb, GA............... 20.0 298.7 1.2 172 1,067 0.5 33
Fulton, GA............... 47.9 845.7 3.7 11 1,387 -2.0 198
Gwinnett, GA............. 27.4 350.2 2.6 65 1,022 -1.2 138
Hall, GA................. 4.7 84.4 2.4 76 929 0.1 40
Muscogee, GA............. 5.0 94.0 0.7 223 841 -3.7 301
Richmond, GA............. 4.8 105.5 0.6 230 869 -1.8 183
Honolulu, HI............. 25.7 478.7 0.3 257 994 -1.0 120
Ada, ID.................. 15.1 230.0 3.6 14 937 -0.4 70
Champaign, IL............ 4.3 89.9 -0.8 318 946 3.7 5
Cook, IL................. 152.6 2,590.2 0.6 230 1,250 -1.6 168
DuPage, IL............... 37.9 616.7 -0.1 287 1,209 -2.6 252
Kane, IL................. 13.7 209.9 0.2 264 963 -0.9 110
Lake, IL................. 22.3 332.4 -0.3 302 1,376 -4.5 323
McHenry, IL.............. 8.7 96.7 0.1 268 891 -2.0 198
McLean, IL............... 3.8 83.8 -0.7 316 918 -9.2 344
Madison, IL.............. 6.0 100.5 1.7 130 838 -3.8 306
Peoria, IL............... 4.5 100.2 -2.1 338 990 -2.3 233
St. Clair, IL............ 5.4 94.4 -0.1 287 830 -2.0 198
Sangamon, IL............. 5.2 127.6 -1.3 327 1,024 -3.5 289
Will, IL................. 16.1 236.8 3.1 32 938 -2.5 242
Winnebago, IL............ 6.6 128.0 -1.4 330 875 -2.5 242
Allen, IN................ 8.8 185.5 0.6 230 848 -2.3 233
Elkhart, IN.............. 4.7 130.3 3.3 24 918 4.0 4
Hamilton, IN............. 9.2 138.0 2.0 105 1,018 0.1 40
Lake, IN................. 10.4 188.5 -0.1 287 910 0.1 40
Marion, IN............... 23.9 598.0 0.7 223 1,053 -0.8 104
St. Joseph, IN........... 5.7 124.3 0.8 211 861 0.6 29
Tippecanoe, IN........... 3.4 83.6 0.7 223 895 -1.1 127
Vanderburgh, IN.......... 4.8 108.1 0.6 230 873 -1.4 149
Johnson, IA.............. 4.2 84.3 2.8 50 951 0.1 40
Linn, IA................. 6.7 129.9 -0.7 316 1,057 -1.1 127
Polk, IA................. 17.2 296.5 1.8 114 1,089 -0.7 95
Scott, IA................ 5.6 91.5 0.2 264 876 -3.1 275
Johnson, KS.............. 23.7 344.2 1.4 156 1,065 -2.9 268
Sedgwick, KS............. 12.8 250.1 0.0 281 903 -5.5 337
Shawnee, KS.............. 5.2 98.5 1.2 172 843 -1.4 149
Wyandotte, KS............ 3.6 91.9 2.2 90 1,035 -0.3 67
Boone, KY................ 4.4 87.4 2.4 76 905 -2.0 198
Fayette, KY.............. 10.9 196.5 -0.3 302 968 3.5 7
Jefferson, KY............ 25.4 469.7 1.9 110 1,026 -2.2 223
Caddo, LA................ 7.3 114.6 -1.2 324 859 -1.9 191
Calcasieu, LA............ 5.2 94.7 1.0 194 922 -4.2 317
East Baton Rouge, LA..... 15.4 269.1 -0.2 296 1,005 -1.0 120
Jefferson, LA............ 13.8 194.8 -0.8 318 957 -2.2 223
Lafayette, LA............ 9.4 129.8 -5.1 344 913 -8.0 342
Orleans, LA.............. 12.4 194.5 -0.2 296 996 -2.1 213
St. Tammany, LA.......... 8.1 88.8 -0.2 296 906 -2.2 223
Cumberland, ME........... 13.9 180.4 1.1 184 981 -2.3 233
Anne Arundel, MD......... 15.1 271.8 1.4 156 1,159 0.9 18
Baltimore, MD............ 21.3 380.8 0.0 281 1,085 -0.6 84
Frederick, MD............ 6.4 101.0 0.3 257 971 -3.6 294
Harford, MD.............. 5.8 93.6 -0.4 308 982 -5.4 336
Howard, MD............... 10.0 169.1 0.7 223 1,298 -1.6 168
Montgomery, MD........... 32.9 471.7 0.8 211 1,422 -0.8 104
Prince George's, MD...... 16.0 322.1 2.4 76 1,094 -1.1 127
Baltimore City, MD....... 13.7 341.0 0.6 230 1,307 0.5 33
Barnstable, MA........... 9.5 91.0 0.9 205 940 -1.8 183
Bristol, MA.............. 17.5 228.3 1.6 139 941 -4.4 319
Essex, MA................ 24.8 324.4 0.4 250 1,124 -2.5 242
Hampden, MA.............. 18.1 210.2 1.0 194 952 -4.1 315
Middlesex, MA............ 54.3 900.3 1.2 172 1,529 -2.0 198
Norfolk, MA.............. 25.2 354.2 1.1 184 1,307 -1.4 149
Plymouth, MA............. 15.7 190.9 1.5 146 1,013 -2.1 213
Suffolk, MA.............. 28.9 669.9 2.1 98 1,888 -3.2 282
Worcester, MA............ 24.8 344.8 0.8 211 1,046 -3.6 294
Genesee, MI.............. 6.9 135.4 0.6 230 889 -3.6 294
Ingham, MI............... 6.0 151.9 2.2 90 1,032 0.1 40
Kalamazoo, MI............ 5.0 118.2 1.4 156 985 -1.4 149
Kent, MI................. 14.3 398.0 1.6 139 936 -1.4 149
Macomb, MI............... 17.6 322.8 1.0 194 1,069 -2.7 259
Oakland, MI.............. 39.2 731.9 1.5 146 1,201 -1.7 181
Ottawa, MI............... 5.6 122.5 1.7 130 952 0.4 37
Saginaw, MI.............. 3.9 85.7 -0.3 302 865 -0.9 110
Washtenaw, MI............ 8.1 211.3 1.5 146 1,100 -1.4 149
Wayne, MI................ 30.5 722.7 1.7 130 1,188 -1.8 183
Anoka, MN................ 6.8 121.9 1.3 164 988 -4.6 325
Dakota, MN............... 9.5 188.3 1.0 194 1,010 -3.9 309
Hennepin, MN............. 41.1 920.7 2.2 90 1,290 -1.1 127
Olmsted, MN.............. 3.3 96.1 1.1 184 1,073 0.9 18
Ramsey, MN............... 12.8 328.5 -0.1 287 1,166 -1.6 168
St. Louis, MN............ 5.1 96.9 -0.1 287 870 0.1 40
Stearns, MN.............. 4.2 86.1 0.5 242 868 -1.8 183
Washington, MN........... 5.2 82.1 0.5 242 899 -0.2 60
Harrison, MS............. 4.6 84.9 0.1 268 731 0.0 49
Hinds, MS................ 5.9 121.9 -0.2 296 870 -2.1 213
Boone, MO................ 4.9 93.5 0.6 230 841 1.9 11
Clay, MO................. 5.6 104.0 3.4 20 921 -8.3 343
Greene, MO............... 8.6 165.7 1.0 194 807 -1.1 127
Jackson, MO.............. 21.2 367.4 1.8 114 1,070 -2.2 223
St. Charles, MO.......... 9.1 145.6 1.3 164 839 -3.6 294
St. Louis, MO............ 36.9 604.3 0.1 268 1,131 -1.6 168
St. Louis City, MO....... 13.5 225.2 0.0 281 1,124 -1.6 168
Yellowstone, MT.......... 6.5 81.0 -0.5 312 916 -0.8 104
Douglas, NE.............. 19.6 340.7 0.7 223 986 -0.8 104
Lancaster, NE............ 10.5 169.5 0.1 268 853 0.0 49
Clark, NV................ 56.4 952.7 2.6 65 909 -1.2 138
Washoe, NV............... 15.0 215.3 3.4 20 942 -1.4 149
Hillsborough, NH......... 12.3 204.2 1.0 194 1,202 -4.9 327
Merrimack, NH............ 5.1 77.5 1.0 194 1,017 -2.7 259
Rockingham, NH........... 10.9 149.1 1.2 172 1,064 -4.9 327
Atlantic, NJ............. 6.6 122.7 -1.7 335 885 -1.3 144
Bergen, NJ............... 33.2 458.7 0.8 211 1,289 -2.7 259
Burlington, NJ........... 11.1 208.1 3.0 39 1,077 -4.2 317
Camden, NJ............... 12.2 205.5 1.7 130 1,076 -1.1 127
Essex, NJ................ 20.7 343.9 0.9 205 1,297 -0.2 60
Gloucester, NJ........... 6.4 109.6 3.0 39 918 -2.4 237
Hudson, NJ............... 15.2 260.6 3.3 24 1,355 -1.6 168
Mercer, NJ............... 11.2 252.0 0.4 250 1,346 -0.1 55
Middlesex, NJ............ 22.4 430.4 3.0 39 1,240 -2.2 223
Monmouth, NJ............. 20.2 260.2 0.6 230 1,068 -2.1 213
Morris, NJ............... 17.1 290.9 0.1 268 1,524 -5.0 332
Ocean, NJ................ 13.1 162.5 1.4 156 871 -3.1 275
Passaic, NJ.............. 12.6 170.1 1.1 184 1,042 -6.0 340
Somerset, NJ............. 10.2 187.6 1.3 164 1,563 -0.7 95
Union, NJ................ 14.5 221.9 1.1 184 1,362 -0.4 70
Bernalillo, NM........... 18.3 327.8 1.2 172 895 -1.4 149
Albany, NY............... 10.4 237.1 1.2 172 1,094 -1.5 164
Bronx, NY................ 18.8 302.7 -0.3 302 1,007 0.6 29
Broome, NY............... 4.6 88.0 0.1 268 799 -4.1 315
Dutchess, NY............. 8.5 112.7 -0.2 296 1,010 -2.7 259
Erie, NY................. 24.9 473.8 0.2 264 941 -2.1 213
Kings, NY................ 62.3 705.6 3.0 39 906 -1.4 149
Monroe, NY............... 19.1 390.0 0.5 242 973 -3.5 289
Nassau, NY............... 54.5 640.4 1.7 130 1,220 -1.4 149
New York, NY............. 129.8 2,471.6 0.7 223 2,212 -1.1 127
Oneida, NY............... 5.4 105.7 1.6 139 811 -3.0 272
Onondaga, NY............. 13.1 248.1 0.5 242 972 -2.1 213
Orange, NY............... 10.5 144.1 1.8 114 886 -2.5 242
Queens, NY............... 53.0 664.0 2.4 76 1,019 -0.9 110
Richmond, NY............. 9.8 118.3 2.2 90 940 -2.4 237
Rockland, NY............. 10.9 124.1 2.8 50 1,037 -3.2 282
Saratoga, NY............. 6.0 84.5 -0.1 287 945 -2.9 268
Suffolk, NY.............. 53.3 661.4 0.9 205 1,147 -3.5 289
Westchester, NY.......... 36.8 431.1 1.2 172 1,395 -3.7 301
Buncombe, NC............. 9.1 130.3 3.1 32 837 -0.7 95
Catawba, NC.............. 4.4 87.3 3.1 32 818 -1.3 144
Cumberland, NC........... 6.2 120.4 0.1 268 799 -1.8 183
Durham, NC............... 8.2 198.7 1.2 172 1,254 -1.6 168
Forsyth, NC.............. 9.2 184.8 0.4 250 953 -2.2 223
Guilford, NC............. 14.3 283.9 0.8 211 898 -3.1 275
Mecklenburg, NC.......... 37.3 674.2 2.1 98 1,193 -0.7 95
New Hanover, NC.......... 8.0 110.5 2.7 58 865 -0.2 60
Wake, NC................. 33.7 541.5 3.2 28 1,085 0.7 25
Cass, ND................. 7.2 117.8 0.6 230 961 -1.7 181
Butler, OH............... 7.6 154.1 1.1 184 925 -2.5 242
Cuyahoga, OH............. 35.8 723.3 0.1 268 1,088 -0.7 95
Delaware, OH............. 5.1 86.2 2.6 65 996 -0.6 84
Franklin, OH............. 31.7 759.2 2.8 50 1,023 -4.4 319
Hamilton, OH............. 23.8 514.8 1.4 156 1,119 -2.0 198
Lake, OH................. 6.3 94.2 -1.0 323 865 -2.9 268
Lorain, OH............... 6.2 97.8 0.8 211 825 -2.5 242
Lucas, OH................ 10.1 211.0 -0.4 308 903 -4.0 311
Mahoning, OH............. 5.9 98.7 -0.5 312 746 -2.2 223
Montgomery, OH........... 11.9 255.6 0.3 257 896 -3.0 272
Stark, OH................ 8.6 158.7 0.1 268 795 -3.2 282
Summit, OH............... 14.3 268.6 0.6 230 944 -1.4 149
Warren, OH............... 4.8 89.8 1.5 146 946 -1.3 144
Cleveland, OK............ 5.6 80.5 -1.2 324 766 -1.9 191
Oklahoma, OK............. 27.8 449.7 -1.4 330 975 -4.9 327
Tulsa, OK................ 22.1 353.4 -0.6 314 942 -3.6 294
Clackamas, OR............ 14.6 159.6 2.4 76 987 -1.0 120
Jackson, OR.............. 7.3 87.3 2.4 76 803 1.5 12
Lane, OR................. 11.9 153.9 2.4 76 845 0.8 24
Marion, OR............... 10.4 149.4 2.8 50 861 0.7 25
Multnomah, OR............ 34.2 498.8 1.8 114 1,099 -0.1 55
Washington, OR........... 19.0 288.2 2.8 50 1,209 -5.8 339
Allegheny, PA............ 35.8 693.9 0.3 257 1,140 -1.1 127
Berks, PA................ 9.0 172.6 0.5 242 941 -3.1 275
Bucks, PA................ 20.0 263.1 1.5 146 1,021 -1.8 183
Butler, PA............... 5.0 85.3 -0.3 302 1,004 0.7 25
Chester, PA.............. 15.5 251.2 0.8 211 1,308 -3.5 289
Cumberland, PA........... 6.5 134.0 0.5 242 921 -3.6 294
Dauphin, PA.............. 7.5 180.6 0.4 250 1,030 -4.9 327
Delaware, PA............. 14.1 224.1 1.1 184 1,111 -3.0 272
Erie, PA................. 7.0 121.8 -2.2 340 809 -4.0 311
Lackawanna, PA........... 5.8 99.1 1.0 194 797 -1.6 168
Lancaster, PA............ 13.4 237.2 1.5 146 877 -3.1 275
Lehigh, PA............... 8.8 189.1 -0.2 296 1,051 -2.1 213
Luzerne, PA.............. 7.5 144.6 -1.9 337 816 -0.5 76
Montgomery, PA........... 27.7 493.5 1.3 164 1,288 -3.1 275
Northampton, PA.......... 6.8 115.4 4.4 5 896 -3.7 301
Philadelphia, PA......... 35.1 676.1 2.1 98 1,235 -3.9 309
Washington, PA........... 5.5 85.3 -1.3 327 1,110 4.9 2
Westmoreland, PA......... 9.3 133.3 -1.6 334 833 -4.0 311
York, PA................. 9.1 178.5 0.8 211 909 -2.0 198
Providence, RI........... 18.0 287.7 0.1 268 1,077 -2.2 223
Charleston, SC........... 14.9 245.0 1.7 130 937 0.9 18
Greenville, SC........... 13.9 266.6 1.3 164 932 -0.5 76
Horry, SC................ 8.7 117.9 3.1 32 654 0.0 49
Lexington, SC............ 6.3 119.3 1.8 114 794 -0.4 70
Richland, SC............. 10.1 219.7 0.9 205 885 -2.6 252
Spartanburg, SC.......... 6.1 136.7 3.3 24 877 -2.1 213
York, SC................. 5.4 91.7 4.6 2 851 0.5 33
Minnehaha, SD............ 7.2 126.1 1.8 114 921 -0.9 110
Davidson, TN............. 21.8 481.3 3.0 39 1,163 -0.9 110
Hamilton, TN............. 9.4 199.6 1.3 164 1,004 -2.7 259
Knox, TN................. 12.0 239.6 1.5 146 959 -2.0 198
Rutherford, TN........... 5.4 121.0 2.6 65 947 -0.6 84
Shelby, TN............... 20.3 500.3 0.0 281 1,087 -0.8 104
Williamson, TN........... 8.5 127.8 5.1 1 1,208 -2.0 198
Bell, TX................. 5.2 118.0 0.1 268 883 -0.5 76
Bexar, TX................ 40.4 855.8 2.2 90 956 -1.1 127
Brazoria, TX............. 5.6 107.3 1.7 130 1,049 -3.8 306
Brazos, TX............... 4.5 102.5 1.5 146 785 0.9 18
Cameron, TX.............. 6.5 140.4 1.2 172 640 -2.0 198
Collin, TX............... 23.9 389.5 3.4 20 1,222 -0.7 95
Dallas, TX............... 75.6 1,688.4 2.8 50 1,279 -0.9 110
Denton, TX............... 14.4 232.4 3.7 11 969 -0.9 110
El Paso, TX.............. 14.8 302.3 1.8 114 729 -2.0 198
Fort Bend, TX............ 12.7 177.2 1.8 114 976 -5.2 335
Galveston, TX............ 6.2 110.0 4.0 8 918 -1.6 168
Gregg, TX................ 4.3 74.1 -3.5 343 862 -5.1 333
Harris, TX............... 113.7 2,272.0 -1.3 327 1,319 -4.7 326
Hidalgo, TX.............. 12.2 256.1 3.0 39 648 -2.0 198
Jefferson, TX............ 5.8 121.4 -1.5 332 1,081 -2.8 266
Lubbock, TX.............. 7.5 140.1 2.2 90 835 -0.4 70
McLennan, TX............. 5.2 112.8 2.1 98 859 -1.0 120
Midland, TX.............. 5.4 84.8 -2.9 342 1,297 2.4 9
Montgomery, TX........... 10.9 171.3 1.1 184 1,024 -1.8 183
Nueces, TX............... 8.3 162.6 0.1 268 901 -2.7 259
Potter, TX............... 4.0 79.8 0.0 281 874 0.0 49
Smith, TX................ 6.1 103.1 0.8 211 865 -2.0 198
Tarrant, TX.............. 42.3 876.2 2.5 71 1,027 -5.7 338
Travis, TX............... 39.5 717.2 2.4 76 1,244 1.1 17
Webb, TX................. 5.3 100.0 1.4 156 683 -3.5 289
Williamson, TX........... 10.2 162.5 4.5 3 1,007 -0.7 95
Davis, UT................ 8.3 122.8 3.6 14 862 -0.2 60
Salt Lake, UT............ 44.3 682.1 2.7 58 1,028 -0.7 95
Utah, UT................. 15.6 225.1 4.5 3 858 -1.2 138
Weber, UT................ 5.9 103.2 1.4 156 791 0.6 29
Chittenden, VT........... 6.8 102.0 -0.6 314 1,033 -3.6 294
Arlington, VA............ 9.4 174.3 0.8 211 1,677 -1.4 149
Chesterfield, VA......... 9.1 138.7 -1.5 332 901 0.7 25
Fairfax, VA.............. 37.9 604.5 1.0 194 1,610 -0.6 84
Henrico, VA.............. 11.7 192.6 0.6 230 1,009 -1.1 127
Loudoun, VA.............. 12.2 161.8 2.2 90 1,233 -0.1 55
Prince William, VA....... 9.4 128.4 1.8 114 931 -0.5 76
Alexandria City, VA...... 6.6 94.9 -1.2 324 1,497 -0.8 104
Chesapeake City, VA...... 6.1 100.2 1.0 194 808 -2.1 213
Newport News City, VA.... 3.9 97.3 -1.7 335 1,017 0.6 29
Norfolk City, VA......... 5.9 141.8 -0.8 318 1,072 -3.1 275
Richmond City, VA........ 7.8 155.1 2.4 76 1,139 -1.1 127
Virginia Beach City, VA.. 12.3 176.2 0.3 257 836 -1.9 191
Benton, WA............... 5.7 84.3 3.8 10 1,013 -4.4 319
Clark, WA................ 14.5 151.5 3.2 28 985 1.4 13
King, WA................. 86.4 1,340.4 3.3 24 1,479 3.5 7
Kitsap, WA............... 6.6 87.1 0.9 205 969 -1.4 149
Pierce, WA............... 21.9 301.3 3.6 14 932 -1.2 138
Snohomish, WA............ 20.8 285.1 1.1 184 1,114 -1.9 191
Spokane, WA.............. 15.7 217.6 2.7 58 882 -0.3 67
Thurston, WA............. 8.2 111.8 4.0 8 934 1.4 13
Whatcom, WA.............. 7.3 88.4 2.5 71 852 0.1 40
Yakima, WA............... 7.8 102.3 2.7 58 736 -0.1 55
Kanawha, WV.............. 5.8 101.7 -2.2 340 881 -1.6 168
Brown, WI................ 6.8 155.7 1.0 194 956 -2.1 213
Dane, WI................. 15.2 334.0 1.8 114 1,033 -4.4 319
Milwaukee, WI............ 26.1 487.8 -0.1 287 1,041 -0.6 84
Outagamie, WI............ 5.2 107.3 0.4 250 920 -0.6 84
Waukesha, WI............. 12.9 239.6 0.1 268 1,073 -1.4 149
Winnebago, WI............ 3.7 93.9 1.6 139 1,005 -2.7 259
San Juan, PR............. 10.7 255.8 -0.2 (5) 672 -0.7 (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 344 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,
fourth quarter 2016
Employment Average weekly
wage(1)
Establishments,
fourth quarter
County by NAICS supersector 2016 Percent Percent
(thousands) December change, Fourth change,
2016 December quarter fourth
(thousands) 2015-16(2) 2016 quarter
2015-16(2)
United States(3) ............................ 9,869.9 143,749.9 1.2 $1,067 -1.5
Private industry........................... 9,570.8 121,881.5 1.3 1,070 -1.7
Natural resources and mining............. 138.1 1,741.7 -4.7 1,106 -5.1
Construction............................. 784.5 6,677.4 2.0 1,234 0.1
Manufacturing............................ 345.7 12,298.6 -0.4 1,285 -3.1
Trade, transportation, and utilities..... 1,924.2 27,968.1 1.1 880 -2.2
Information.............................. 159.2 2,809.0 0.0 1,884 -1.5
Financial activities..................... 865.0 8,034.0 1.5 1,706 -0.4
Professional and business services....... 1,779.7 20,259.2 1.0 1,419 -1.4
Education and health services............ 1,626.7 21,994.4 2.2 973 -2.0
Leisure and hospitality.................. 827.9 15,365.3 1.8 461 -0.2
Other services........................... 840.2 4,387.5 1.1 719 -0.7
Government................................. 299.1 21,868.4 0.8 1,049 -0.2
Los Angeles, CA.............................. 472.0 4,415.7 1.1 1,256 -0.6
Private industry........................... 465.8 3,838.1 1.1 1,246 -0.8
Natural resources and mining............. 0.5 8.7 0.3 1,411 -7.0
Construction............................. 13.9 133.2 1.5 1,276 0.7
Manufacturing............................ 12.3 350.9 -3.3 1,385 1.2
Trade, transportation, and utilities..... 53.3 844.4 0.9 961 -0.1
Information.............................. 9.6 225.9 -0.3 2,306 -8.5
Financial activities..................... 25.3 219.9 0.5 1,932 0.8
Professional and business services....... 47.9 605.5 -0.1 1,631 0.9
Education and health services............ 218.5 758.7 1.9 929 -0.1
Leisure and hospitality.................. 32.6 512.7 2.8 986 0.4
Other services........................... 26.8 148.0 0.8 736 -0.1
Government................................. 6.2 577.6 1.6 1,325 0.1
Cook, IL..................................... 152.6 2,590.2 0.6 1,250 -1.6
Private industry........................... 151.3 2,289.0 0.6 1,255 -1.7
Natural resources and mining............. 0.1 1.0 -7.9 1,324 -1.3
Construction............................. 12.2 71.5 0.4 1,625 -0.1
Manufacturing............................ 6.3 185.5 -1.0 1,355 -3.6
Trade, transportation, and utilities..... 29.7 491.9 0.6 980 0.4
Information.............................. 2.7 55.7 4.6 1,705 -5.3
Financial activities..................... 15.1 193.2 0.4 2,284 -0.8
Professional and business services....... 32.4 473.4 -0.3 1,669 -1.6
Education and health services............ 16.3 441.1 1.2 1,028 -2.0
Leisure and hospitality.................. 14.2 273.5 0.9 526 -2.6
Other services........................... 17.3 96.3 -0.4 955 -1.1
Government................................. 1.3 301.3 0.8 1,207 -1.1
New York, NY................................. 129.8 2,471.6 0.7 2,212 -1.1
Private industry........................... 128.9 2,202.4 0.8 2,319 -1.4
Natural resources and mining............. 0.0 0.2 9.1 2,094 4.8
Construction............................. 2.2 40.2 -1.0 2,343 1.1
Manufacturing............................ 2.1 26.3 -5.0 1,649 -1.1
Trade, transportation, and utilities..... 19.3 265.9 -1.7 1,474 -1.3
Information.............................. 4.8 162.9 0.4 2,808 0.5
Financial activities..................... 19.2 371.5 -0.2 4,587 -0.4
Professional and business services....... 27.4 564.9 1.4 2,599 -3.3
Education and health services............ 9.9 346.8 0.3 1,390 0.8
Leisure and hospitality.................. 13.7 303.8 1.4 1,014 -1.6
Other services........................... 20.3 103.3 0.5 1,195 -1.0
Government................................. 0.8 269.2 0.5 1,335 2.6
Harris, TX................................... 113.7 2,272.0 -1.3 1,319 -4.7
Private industry........................... 113.2 1,993.6 -1.8 1,344 -5.1
Natural resources and mining............. 1.8 72.9 -13.4 3,416 -3.3
Construction............................. 7.2 155.9 -4.1 1,477 -2.6
Manufacturing............................ 4.8 166.3 -8.3 1,652 -2.3
Trade, transportation, and utilities..... 25.0 477.2 -0.8 1,121 -5.5
Information.............................. 1.2 27.3 0.7 1,478 -2.4
Financial activities..................... 11.9 124.5 1.4 1,768 -3.3
Professional and business services....... 23.2 384.1 -3.7 1,693 -5.2
Education and health services............ 15.9 292.3 2.7 1,080 -1.3
Leisure and hospitality.................. 9.8 226.8 2.1 470 -0.6
Other services........................... 11.7 64.8 -0.5 822 -1.8
Government................................. 0.6 278.4 2.4 1,142 -0.5
Maricopa, AZ................................. 96.5 1,926.9 2.4 994 -2.3
Private industry........................... 95.7 1,713.5 2.6 995 -2.1
Natural resources and mining............. 0.4 8.3 0.4 935 -1.6
Construction............................. 6.9 103.1 4.0 1,116 -0.7
Manufacturing............................ 3.1 115.7 -1.3 1,375 -5.0
Trade, transportation, and utilities..... 18.5 386.8 2.5 893 -2.3
Information.............................. 1.5 34.4 -1.1 1,386 1.5
Financial activities..................... 10.8 173.2 5.7 1,316 0.5
Professional and business services....... 20.9 331.7 1.0 1,108 -1.3
Education and health services............ 10.7 289.8 3.0 993 -4.2
Leisure and hospitality.................. 7.6 207.9 2.0 477 -2.3
Other services........................... 6.0 49.6 -0.5 722 0.7
Government................................. 0.7 213.4 0.7 985 -4.1
Dallas, TX................................... 75.6 1,688.4 2.8 1,279 -0.9
Private industry........................... 75.0 1,514.5 3.1 1,290 -1.3
Natural resources and mining............. 0.6 8.6 -6.4 4,042 13.5
Construction............................. 4.5 86.3 5.1 1,368 2.5
Manufacturing............................ 2.7 110.0 1.1 1,420 -6.2
Trade, transportation, and utilities..... 16.0 355.8 3.2 1,079 -3.1
Information.............................. 1.4 48.9 0.9 1,821 -0.1
Financial activities..................... 9.3 161.1 4.4 1,759 -0.7
Professional and business services....... 17.0 342.1 2.7 1,574 0.2
Education and health services............ 9.4 197.5 2.5 1,153 -1.1
Leisure and hospitality.................. 6.7 160.3 4.3 542 -1.8
Other services........................... 7.0 42.7 2.1 808 -1.3
Government................................. 0.6 174.0 0.3 1,184 2.7
Orange, CA................................... 116.3 1,588.8 2.0 1,200 -0.6
Private industry........................... 114.9 1,442.2 2.2 1,201 -0.8
Natural resources and mining............. 0.2 2.7 3.8 965 4.2
Construction............................. 6.7 96.5 1.7 1,390 0.9
Manufacturing............................ 4.9 157.1 -0.1 1,493 -0.9
Trade, transportation, and utilities..... 16.8 265.6 -0.6 1,044 -0.5
Information.............................. 1.3 25.8 2.8 2,069 1.6
Financial activities..................... 10.9 118.1 0.9 2,038 1.8
Professional and business services....... 20.6 304.7 4.0 1,407 -3.8
Education and health services............ 30.5 204.6 3.1 996 -3.7
Leisure and hospitality.................. 8.5 210.9 2.1 529 7.5
Other services........................... 6.8 46.5 2.7 734 0.1
Government................................. 1.5 146.6 1.0 1,189 1.4
San Diego, CA................................ 107.8 1,427.5 1.6 1,170 -1.5
Private industry........................... 105.9 1,194.0 1.5 1,145 -2.2
Natural resources and mining............. 0.6 7.9 -8.3 744 1.6
Construction............................. 6.7 77.1 5.4 1,272 0.7
Manufacturing............................ 3.2 106.5 -0.9 1,586 -10.4
Trade, transportation, and utilities..... 14.1 229.0 0.3 846 -2.5
Information.............................. 1.1 23.5 -1.5 1,759 0.6
Financial activities..................... 9.7 72.8 1.7 1,548 0.2
Professional and business services....... 18.0 232.9 -0.7 1,764 0.3
Education and health services............ 30.0 195.1 2.0 1,007 -2.8
Leisure and hospitality.................. 8.1 190.2 3.6 513 3.2
Other services........................... 7.3 50.5 1.0 647 1.6
Government................................. 1.9 233.5 1.8 1,295 1.3
King, WA..................................... 86.4 1,340.4 3.3 1,479 3.5
Private industry........................... 85.9 1,171.5 3.4 1,501 3.9
Natural resources and mining............. 0.4 2.9 -3.0 1,208 -9.3
Construction............................. 6.5 68.2 6.2 1,386 0.3
Manufacturing............................ 2.5 102.0 -3.9 1,662 0.0
Trade, transportation, and utilities..... 14.5 261.7 4.7 1,484 20.2
Information.............................. 2.2 99.8 9.2 2,865 -1.7
Financial activities..................... 6.6 67.9 3.0 1,773 2.0
Professional and business services....... 17.5 220.5 1.7 1,828 0.2
Education and health services............ 19.5 169.7 4.1 1,055 -0.3
Leisure and hospitality.................. 7.2 134.5 3.8 572 0.5
Other services........................... 9.1 44.4 3.6 858 1.7
Government................................. 0.5 168.9 2.4 1,326 0.8
Miami-Dade, FL............................... 97.5 1,132.9 1.3 1,029 -2.5
Private industry........................... 97.2 993.1 1.2 1,016 -1.7
Natural resources and mining............. 0.5 9.0 -6.7 684 4.7
Construction............................. 6.4 44.6 7.0 986 -1.9
Manufacturing............................ 2.9 40.5 1.2 968 -2.0
Trade, transportation, and utilities..... 26.4 289.3 -0.1 911 -2.4
Information.............................. 1.5 18.1 2.1 1,682 0.2
Financial activities..................... 10.6 75.3 0.5 1,636 -1.2
Professional and business services....... 21.5 158.1 1.8 1,314 -1.2
Education and health services............ 10.4 176.0 2.4 1,036 -2.1
Leisure and hospitality.................. 7.2 141.0 0.5 606 -2.1
Other services........................... 8.3 40.1 1.3 634 -2.3
Government................................. 0.3 139.8 1.8 1,119 -7.3
(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 2015 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 2016
Employment Average weekly
wage(1)
Establishments,
fourth quarter
State 2016 Percent Percent
(thousands) December change, Fourth change,
2016 December quarter fourth
(thousands) 2015-16 2016 quarter
2015-16
United States(2)........... 9,869.9 143,749.9 1.2 $1,067 -1.5
Alabama.................... 123.6 1,932.6 0.7 901 -1.3
Alaska..................... 22.3 310.0 -1.9 1,038 -5.2
Arizona.................... 156.9 2,760.1 2.1 945 -2.2
Arkansas................... 89.4 1,205.4 0.4 827 -1.4
California................. 1,509.9 16,923.3 1.9 1,271 -0.3
Colorado................... 192.6 2,588.6 2.0 1,086 -1.5
Connecticut................ 117.7 1,685.5 0.0 1,289 -3.4
Delaware................... 31.5 441.2 -0.1 1,055 -2.9
District of Columbia....... 39.5 760.9 0.5 1,763 0.6
Florida.................... 673.4 8,538.9 2.7 942 -1.8
Georgia.................... 305.5 4,349.3 2.4 993 -0.9
Hawaii..................... 40.7 658.3 0.7 954 -0.3
Idaho...................... 59.7 691.6 3.2 800 -0.4
Illinois................... 404.3 5,947.6 0.4 1,122 -2.0
Indiana.................... 162.7 3,021.7 0.9 883 -0.9
Iowa....................... 101.7 1,542.0 0.1 911 -1.0
Kansas..................... 90.8 1,384.5 0.1 877 -2.2
Kentucky................... 123.8 1,894.2 0.6 874 -1.4
Louisiana.................. 129.7 1,907.4 -1.6 914 -2.9
Maine...................... 54.1 602.6 0.8 855 -2.1
Maryland................... 170.5 2,666.7 1.0 1,169 -0.4
Massachusetts.............. 249.2 3,530.4 1.3 1,352 -2.4
Michigan................... 242.0 4,283.0 1.5 1,026 -1.6
Minnesota.................. 164.2 2,839.7 1.2 1,062 -1.1
Mississippi................ 74.4 1,134.0 0.0 756 -1.8
Missouri................... 196.4 2,783.2 0.9 918 -1.7
Montana.................... 46.6 456.5 0.7 822 0.5
Nebraska................... 74.2 972.4 0.0 876 -0.5
Nevada..................... 82.7 1,307.8 2.7 924 -1.2
New Hampshire.............. 52.3 656.9 1.3 1,092 -4.1
New Jersey................. 271.6 4,042.1 1.4 1,239 -1.9
New Mexico................. 58.3 811.4 0.0 844 -2.5
New York................... 647.2 9,332.5 1.2 1,342 -2.3
North Carolina............. 269.9 4,326.3 1.8 932 -0.7
North Dakota............... 32.2 414.4 -3.2 978 -4.2
Ohio....................... 294.0 5,365.6 0.7 943 -2.3
Oklahoma................... 109.7 1,587.7 -1.2 864 -3.5
Oregon..................... 149.2 1,860.7 2.4 970 -1.0
Pennsylvania............... 356.9 5,799.8 0.7 1,039 -2.3
Rhode Island............... 37.1 478.3 0.0 1,027 -1.6
South Carolina............. 126.7 2,024.3 1.8 855 -0.6
South Dakota............... 33.2 419.9 0.5 828 -0.5
Tennessee.................. 155.5 2,947.5 1.8 970 -1.1
Texas...................... 662.5 11,974.7 1.2 1,072 -2.5
Utah....................... 98.4 1,415.1 2.9 910 -0.3
Vermont.................... 25.3 312.6 0.1 897 -2.4
Virginia................... 270.2 3,831.6 0.6 1,091 -0.3
Washington................. 240.2 3,227.9 2.8 1,150 1.7
West Virginia.............. 50.7 693.1 -1.6 809 -2.5
Wisconsin.................. 172.7 2,842.4 0.5 924 -2.0
Wyoming.................... 26.1 265.8 -3.9 894 -4.7
Puerto Rico................ 45.7 928.2 -0.3 555 -1.9
Virgin Islands............. 3.4 38.5 0.2 769 -1.8
(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
