For release 10:00 a.m. (ET), Wednesday, November 18, 2020 USDL-20-2131
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
COUNTY EMPLOYMENT AND WAGES – SECOND QUARTER 2020
From June 2019 to June 2020, employment decreased in all of the 357 largest U.S. counties, the U.S.
Bureau of Labor Statistics reported today. In June 2020, national employment (as measured by the
QCEW program) decreased to 135.1 million, a 9.4-percent decrease over the year. Atlantic, NJ, had the
largest over-the-year decrease in employment with a loss of 34.2 percent. Employment data in this
release are presented for June 2020, and average weekly wage data are presented for second quarter
2020. Employment in most of the country was impacted by the COVID-19 pandemic and efforts to
contain it.
Among the 357 largest counties, 352 had over-the-year increases in average weekly wages. In the
second quarter of 2020, average weekly wages for the nation increased to $1,188, an 8.6-percent
increase over the year. Atlantic, NJ, had the largest second quarter over-the-year wage gain at 22.5
percent. (See table 1.) The increases in average weekly wages largely reflect substantial employment
loss among lower-paid industries.
Large County Employment in June 2020
Atlantic, NJ, had the largest over-the-year percentage decrease in employment (-34.2 percent). Within
Atlantic, the largest employment decrease occurred in leisure and hospitality, which lost 33,336 jobs
over the year (-75.2 percent).
Cleveland, OK, and Utah, UT, both experienced the smallest over-the-year percentage decrease in
employment, each with a loss of 0.2 percent. Within Cleveland, leisure and hospitality had the largest
employment decrease with a loss of 1,838 jobs (-13.7 percent). Within Utah, leisure and hospitality had
the largest employment decrease with a loss of 2,297 jobs (-9.9 percent).
Large County Average Weekly Wage in Second Quarter 2020
Atlantic, NJ, had the largest over-the-year percentage increase in average weekly wages (+22.5 percent).
Within Atlantic, an average weekly wage gain of $143 (+24.2 percent) in leisure and hospitality made
the largest contribution to the county’s increase in average weekly wages.
Ector, TX, had the largest over-the-year percentage decrease in average weekly wages with a loss of 6.6
percent. Within Ector, natural resources and mining had the largest impact, with an average weekly
wage decrease of $84 (-4.7 percent) over the year.
Ten Largest Counties
All of the 10 largest counties had over-the-year percentage decreases in employment. In June 2020, New
York, NY, had the largest over-the-year employment percentage loss (-18.8 percent). Within New York,
leisure and hospitality had the largest employment decrease with a loss of 208,495 jobs (-66.1 percent).
(See table 2.)
All of the 10 largest counties had over-the-year percentage increases in average weekly wages. In
second quarter 2020, New York, NY, experienced the largest over-the-year percentage gain in average
weekly wages (+14.9 percent). Within New York, leisure and hospitality had the largest impact, with an
average weekly wage increase of $149 (+15.5 percent) over the year.
For More Information
The tables included in this release contain data for the nation and for the 357 U.S. counties with annual
average employment levels of 75,000 or more in 2019. June 2020 employment and second quarter 2020
average weekly wages for all states are provided in table 3 of this release.
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/regional-resources.htm.
QCEW data are available in the Census Business Builder suite of web tools assisting business owners
and regional analysts in data-driven decision making at www.census.gov/data/data-tools/cbb.html.
The QCEW news release schedule is available at www.bls.gov/cew/release-calendar.htm.
____________
The County Employment and Wages full data update for second quarter 2020 is scheduled to be
released on Wednesday, December 2, 2020, at 10:00 a.m. (ET).
The County Employment and Wages news release for third quarter 2020 is scheduled to be
released on Wednesday, February 24, 2021, at 10:00 a.m. (ET).
__________________________________________________________________________________________________________
Special Notice: Imputation Methodology Improvements
QCEW implemented improvements to imputation methodology, effective with second quarter 2020
processing. QCEW imputation creates estimated values for non-respondent employers for the first
two quarters of non-response. After two quarters of non-response, establishments are converted
from non-respondents to establishment deaths. Usually, non-respondents account for less than 5
percent of QCEW employment. BLS expected substantially higher than usual numbers of non-respondent
employers in the second quarter of 2020 due to the coronavirus (COVID-19) pandemic and efforts to
contain it. The national employment response rate for second quarter declined by 0.4 percent.
Changes to state response rates varied. For more information on QCEW response rates,
see www.bls.gov/cew/response-rates/home.htm.
QCEW implemented three improvements to imputation methodology. First, BLS summarized counts of
the regular state unemployment insurance claims by employer to identify employers who may have
ceased operations, either temporarily or permanently. These employers were treated as business
deaths rather than being treated as late respondents. Second, for employers that are expected to
still be in operation during the reference time period, BLS modified the imputation formula to
use reported data for similar employers to create imputed levels of employment and wages. Third,
state QCEW staff used unemployment insurance claims information as a supplement to aid their
review of imputed and reported QCEW data.
BLS applied these changes to data for non-respondent employers in the first and second quarters
of 2020. The impact on first quarter 2020 was negligible. The impact on second quarter 2020
employment was a decline of 0.2 percent, or a decline of about 270,000 from what would have been
reported for June 2020 employment. Total wages decreased by 0.1 percent. For more information on
QCEW imputation methodology and the impact of the improved methods, see
www.bls.gov/cew/additional-resources/imputation-methodology.htm.
__________________________________________________________________________________________________________
__________________________________________________________________________________________________________
Coronavirus (COVID-19) Pandemic Impact on Second Quarter 2020 QCEW Data
Response rate tables for the second quarter of 2020 are available at
www.bls.gov/covid19/county-employment-and-wages-covid-19-impact-second-quarter-2020.htm.
For more information about the effects of the COVID-19 pandemic on QCEW data, see
www.bls.gov/covid19/effects-of-covid-19-pandemic-on-county-employment-and-wages-data.htm.
__________________________________________________________________________________________________________
Technical Note
Special technical note: This technical note describes the procedures regularly used for the
Quarterly Census of Employment and Wages (QCEW) program. Due to COVID-19, some of the
procedures described in this technical note have been modified. The modifications are briefly
described in the box notes in this news release and are described in more detail at
www.bls.gov/covid19/effects-of-covid-19-pandemic-on-county-employment-and-wages-data.htm
and also at www.bls.gov/cew/additional-resources/imputation-methodology.htm.
These data are the product of a federal-state cooperative program, the Quarterly Census of
Employment and Wages 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 2020 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, PR, 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 358 counties presented in
this release were derived using 2019 preliminary annual averages of employment. For 2020 data,
three counties have been added to the publication tables: Baldwin, AL; Iredell, NC; and Gregg,
TX. One county has been dropped from the publication tables: Bay, FL. These counties will be
included or excluded, respectively, in all 2020 quarterly releases. The counties in table 2 are
selected and sorted each year based on the annual average employment from the preceding year.
The preliminary QCEW data presented in this release may differ from data released by the
individual states. These potential differences result from the states' continuing receipt of UI data
over time and ongoing review and editing. The individual states determine their data release
timetables.
Differences between QCEW, BED, and CES employment measures
The Bureau publishes three different establishment-based employment measures for any given
quarter: QCEW, Business Employment Dynamics (BED), and Current Employment Statistics
(CES). Each of these measures makes use of the quarterly UI employment reports in producing
data; however, each measure has a somewhat different universe coverage, estimation procedure,
and publication product.
Differences in coverage and estimation methods can result in somewhat different measures of
employment change over time. It is important to understand program differences and the intended
uses of the program products. (See table.) Additional information on each program can be obtained
from the program Web sites shown in the table.
Summary of Major Differences between QCEW, BED, and CES Employment Measures
----------------------------------------------------------------------------------
| QCEW | BED | CES
-----------|---------------------|----------------------|------------------------
Source |--Count of UI admini-|--Count of longitudi- |--Sample survey:
| strative records | nally-linked UI ad- | 697,000 establish-
| submitted by 10.4 | ministrative records| ments
| million establish- | submitted by 8.3 |
| ments in first | million private-sec-|
| quarter of 2020 | 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,
| | | including railroads,
| | | religious organiza-
| | | tions, and other non-
| | | UI-covered jobs
-----------|---------------------|----------------------|------------------------
Publication|--Quarterly |--Quarterly |--Monthly
frequency | -Within 5 months | -7 months after the | -Usually the 3rd
| after the end of | end of each quarter| Friday after the end
| each quarter | | of the week including
| | | the 12th of the month
-----------|---------------------|----------------------|------------------------
Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sa-
file | and publishes each | quarter to longitu- | mpling frame and to
| new quarter of UI | dinal database and | annually realign sam-
| data | directly summarizes | plebased estimates to
| | gross job gains and | population counts
| | losses | (benchmarking)
-----------|---------------------|----------------------|------------------------
Principal |--Provides a quarter-|--Provides quarterly |--Provides current mon-
products | ly and annual uni- | employer dynamics | thly estimates of emp-
| verse count of es- | data on establish- | loyment, hours, and
| tablishments, em- | ment openings, clos-| earnings at the MSA,
| ployment, and wages| ings, expansions, | state, and national
| at the county, MSA,| and contractions at | level by 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 |--Detailed locality |--Business cycle |--Principal federal
uses | data | analysis | economic indicator
| | | (PFEI)
|--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 10.2
million employer reports of employment and wages submitted by states to the BLS in 2019. 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 2019, UI and UCFE programs
covered workers in 148.1 million jobs. The estimated 142.5 million workers in these jobs (after
adjustment for multiple jobholders) represented 97.1 percent of civilian wage and salary
employment. Covered workers received $8.769 trillion in pay, representing 94.2 percent of the
wage and salary component of personal income and 40.9 percent of the gross domestic product.
Major exclusions from UI coverage include self-employed workers, most agricultural workers on
small farms, all members of the Armed Forces, elected officials in most states, most employees of
railroads, some domestic workers, most student workers at schools, and employees of certain small
nonprofit organizations.
State and federal UI laws change periodically. These changes may have an impact on the
employment and wages reported by employers covered under the UI program. Coverage changes
may affect the over-the-year comparisons presented in this news release.
Concepts and methodology
Monthly employment is based on the number of workers who worked during or received pay for
the pay period including the 12th of the month. With few exceptions, all employees of covered
firms are reported, including production and sales workers, corporation officials, executives,
supervisory personnel, and clerical workers. Workers on paid vacations and part-time workers also
are included.
Average weekly wage values are calculated by dividing quarterly total wages by the average of the
three monthly employment levels (all employees, as described above) and dividing the result by
13, for the 13 weeks in the quarter. These calculations are made using unrounded employment and
wage values. The average wage values that can be calculated using rounded data from the BLS
database may differ from the averages reported. Included in the quarterly wage data are non-wage
cash payments such as bonuses, the cash value of meals and lodging when supplied, tips and other
gratuities, and, in some states, employer contributions to certain deferred compensation plans such
as 401(k) plans and stock options. Over-the-year comparisons of average weekly wages may
reflect fluctuations in average monthly employment and/or total quarterly wages between the
current quarter and prior year levels.
Average weekly wages are affected by the ratio of full-time to part-time workers as well as the
number of individuals in high-paying and low-paying occupations and the incidence of pay periods
within a quarter. For instance, the average weekly wage of the workforce could increase
significantly when there is a large decline in the number of employees that had been receiving
below-average wages. Wages may include payments to workers not present in the employment
counts because they did not work during the pay period including the 12th of the month. When
comparing average weekly wage levels between industries, states, or quarters, these factors should
be taken into consideration.
Wages measured by QCEW may be subject to periodic and sometimes large fluctuations. This
variability may be due to calendar effects resulting from some quarters having more pay dates than
others. The effect is most visible in counties with a dominant employer. In particular, this effect
has been observed in counties where government employers represent a large fraction of overall
employment. Similar calendar effects can result from private sector pay practices. However, these
effects are typically less pronounced for two reasons: employment is less concentrated in a single
private employer, and private employers use a variety of pay period types (weekly, biweekly,
semimonthly, monthly).
For example, the effect on over-the-year pay comparisons can be pronounced in federal
government due to the uniform nature of federal payroll processing. Most federal employees are
paid on a biweekly pay schedule. As a result, in some quarters federal wages include six pay dates,
while in other quarters there are seven pay dates. Over-the-year comparisons of average weekly
wages may also reflect this calendar effect. Growth in average weekly wages may be attributed, in
part, to a comparison of quarterly wages for the current year, which include seven pay dates, with
year-ago wages that reflect only six pay dates. An opposite effect will occur when wages in the
current quarter reflecting six pay dates are compared with year-ago wages for a quarter including
seven pay dates.
In order to ensure the highest possible quality of data, states verify with employers and update, if
necessary, the industry, location, and ownership classification of all establishments on a 3-year
cycle. Changes in establishment classification codes resulting from this process are introduced with
the data reported for the first quarter of the year. Changes resulting from improved employer
reporting also are introduced in the first quarter.
QCEW data are not designed as a time series. QCEW data are simply the sums of individual
establishment records and reflect the number of establishments that exist in a county or industry at
a point in time. Establishments can move in or out of a county or industry for a number of reasons
that reflect economic events or administrative changes. For example, economic change would
come from a firm relocating into the county; administrative change would come from a company
correcting its county designation.
The over-the-year changes of employment and wages presented in this release have been adjusted
to account for most of the administrative corrections made to the underlying establishment reports.
This is done by modifying the prior-year levels used to calculate the over-the-year changes.
Percent changes are calculated using an adjusted version of the final 2019 quarterly data as the
base data. The adjusted prior-year levels used to calculate the over-the-year percent change in
employment and wages are not published. These adjusted prior-year levels do not match the
unadjusted data maintained on the BLS Web site. Over-the-year change calculations based on data
from the Web site, or from data published in prior BLS news releases, may differ substantially
from the over-the-year changes presented in this news release.
The adjusted data used to calculate the over-the-year change measures presented in this release
eliminate the effect of most of the administrative changes (those occurring when employers update
the industry, location, and ownership information of their establishments). The most common
adjustments for administrative change are the result of updated information about the county
location of individual establishments. Included in these adjustments are administrative changes
involving the classification of establishments that were previously reported in the unknown or
statewide county or unknown industry categories. Adjusted data account for improvements in
reporting employment and wages for individual and multi-unit establishments. To accomplish this,
adjustments were implemented to account for: administrative changes caused by multi-unit
employers who start reporting for each individual establishment rather than as a single entity (first
quarter of 2008); selected large administrative changes in employment and wages (second quarter
of 2011); and state verified improvements in reporting of employment and wages (third quarter of
2014). These adjustments allow QCEW to include county employment and wage growth rates in
this news release that would otherwise not meet publication standards.
The adjusted data used to calculate the over-the-year change measures presented in any County
Employment and Wages news release are valid for comparisons between the starting and ending
points (a 12-month period) used in that particular release. Comparisons may not be valid for any
time period other than the one featured in a release even if the changes were calculated using
adjusted data.
County definitions are assigned according to Federal Information Processing Standards
Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after
approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology
Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104-106.
Areas shown as counties include those designated as independent cities in some jurisdictions and,
in Alaska, those designated as census areas where counties have not been created. County data also
are presented for the New England states for comparative purposes even though townships are the
more common designation used in New England (and New Jersey). The regions referred to in this
release are defined as census regions.
Additional statistics and other information
Employment and Wages Annual Averages Online features comprehensive information by detailed
industry on establishments, employment, and wages for the nation and all states. The 2019 edition
of this publication, which was published in September 2020, contains selected data produced by
Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the
first quarter 2020 version of this news release. Tables and additional content from the 2019 edition
of Employment and Wages Annual Averages Online are now available at
www.bls.gov/cew/publications/employment-and-wages-annual-averages/2019/home.htm. The
2020 edition of Employment and Wages Annual Averages Online will be available in September
2021.
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 358 largest counties,
second quarter 2020
Employment Average weekly wage(2)
Establishments,
County(1) second quarter Percent Ranking Percent Ranking
2020 June change, by Second change, by
(thousands) 2020 June percent quarter second percent
(thousands) 2019-20(3) change 2020 quarter change
2019-20(3)
United States(4)......... 10,451.0 135,114.4 -9.4 - $1,188 8.6 -
Baldwin, AL.............. 6.6 74.1 -6.7 88 782 8.6 156
Jefferson, AL............ 19.3 328.8 -7.7 130 1,115 5.0 317
Madison, AL.............. 10.1 198.4 -3.8 19 1,255 8.8 144
Mobile, AL............... 10.4 160.2 -6.7 88 961 6.3 275
Montgomery, AL........... 6.4 121.7 -7.9 136 936 5.9 289
Shelby, AL............... 5.9 80.0 -6.3 75 1,056 4.7 323
Tuscaloosa, AL........... 4.6 86.9 -10.3 219 908 3.2 340
Anchorage, AK............ 8.3 133.9 -10.5 226 1,262 11.1 76
Maricopa, AZ............. 110.7 1,924.6 -4.6 30 1,137 7.7 209
Pima, AZ................. 19.5 350.5 -6.4 77 990 8.0 193
Benton, AR............... 7.0 121.7 -1.4 4 1,327 11.1 76
Pulaski, AR.............. 14.5 233.6 -7.8 132 1,014 7.0 246
Washington, AR........... 6.4 103.7 -6.2 71 968 6.7 260
Alameda, CA.............. 66.7 707.9 -10.9 241 1,648 10.2 98
Butte, CA................ 8.4 74.1 -8.4 152 916 8.8 144
Contra Costa, CA......... 34.6 329.4 -12.1 269 1,486 10.7 86
Fresno, CA............... 38.5 382.4 -6.2 71 932 6.5 266
Kern, CA................. 21.9 306.9 -9.2 181 991 8.9 140
Los Angeles, CA.......... 518.8 3,945.3 -12.2 272 1,333 8.9 140
Marin, CA................ 12.7 100.6 -13.7 311 1,617 15.6 8
Merced, CA............... 7.0 77.8 -6.6 86 891 7.0 246
Monterey, CA............. 14.4 195.2 -8.8 167 983 6.3 275
Napa, CA................. 6.0 70.2 -14.6 320 1,186 9.2 130
Orange, CA............... 130.0 1,442.0 -12.7 285 1,334 11.4 64
Placer, CA............... 14.2 157.5 -9.4 189 1,221 13.3 22
Riverside, CA............ 71.4 703.6 -8.1 143 957 8.4 167
Sacramento, CA........... 63.3 634.6 -7.4 117 1,326 11.0 83
San Bernardino, CA....... 65.1 735.2 -5.3 46 993 7.5 219
San Diego, CA............ 118.2 1,325.1 -11.2 248 1,315 10.6 88
San Francisco, CA........ 61.9 663.4 -12.8 288 2,643 8.6 156
San Joaquin, CA.......... 19.0 248.0 -5.1 38 1,008 7.8 204
San Luis Obispo, CA...... 10.8 106.3 -12.8 288 1,034 8.3 177
San Mateo, CA............ 29.3 372.7 -10.6 231 2,812 18.1 4
Santa Barbara, CA........ 16.0 199.7 -5.1 38 1,138 8.5 159
Santa Clara, CA.......... 76.1 1,022.0 -9.1 179 3,045 16.5 6
Santa Cruz, CA........... 9.8 97.5 -12.7 285 1,136 12.9 23
Solano, CA............... 12.0 129.7 -10.0 211 1,250 7.8 204
Sonoma, CA............... 20.4 187.0 -12.0 265 1,177 10.0 102
Stanislaus, CA........... 16.6 181.0 -7.5 121 1,013 9.2 130
Tulare, CA............... 11.8 161.2 -5.0 36 850 8.7 151
Ventura, CA.............. 28.3 306.5 -8.5 157 1,194 11.9 46
Yolo, CA................. 7.3 102.6 -6.9 95 1,233 8.3 177
Adams, CO................ 12.1 217.2 -4.4 27 1,130 6.6 264
Arapahoe, CO............. 23.4 315.3 -6.5 81 1,349 8.3 177
Boulder, CO.............. 16.4 174.2 -8.2 146 1,428 9.5 116
Denver, CO............... 35.9 475.2 -11.3 251 1,485 10.6 88
Douglas, CO.............. 13.2 126.6 -5.2 42 1,324 7.5 219
El Paso, CO.............. 21.4 269.3 -6.2 71 1,061 8.5 159
Jefferson, CO............ 21.6 229.2 -7.4 117 1,240 10.4 94
Larimer, CO.............. 13.2 155.9 -7.3 115 1,090 11.6 57
Weld, CO................. 8.2 104.7 -9.3 183 1,025 2.4 348
Fairfield, CT............ 36.8 366.1 -13.7 311 1,751 11.7 52
Hartford, CT............. 29.3 459.0 -11.4 254 1,383 9.8 106
New Haven, CT............ 25.2 333.0 -10.1 214 1,227 11.5 59
New London, CT........... 7.8 101.4 -18.9 348 1,236 17.3 5
New Castle, DE........... 21.3 266.4 -9.3 183 1,279 8.1 188
Sussex, DE............... 7.6 79.9 -10.5 226 872 12.4 36
Washington, DC........... 41.6 701.7 -10.0 211 1,987 11.7 52
Alachua, FL.............. 7.6 124.2 -5.5 50 979 5.6 299
Brevard, FL.............. 16.7 212.7 -3.2 13 1,063 6.6 264
Broward, FL.............. 73.4 738.6 -9.0 176 1,084 6.8 258
Collier, FL.............. 15.5 134.7 -5.5 50 1,018 7.3 229
Duval, FL................ 31.3 497.0 -4.7 34 1,074 6.9 250
Escambia, FL............. 8.6 133.6 -2.8 11 893 6.1 279
Hillsborough, FL......... 46.7 663.9 -4.6 30 1,107 6.4 269
Lake, FL................. 9.0 95.0 -3.6 17 793 5.7 294
Lee, FL.................. 24.0 245.8 -5.6 52 946 6.4 269
Leon, FL................. 9.1 141.1 -6.0 64 927 7.2 234
Manatee, FL.............. 11.9 119.1 -5.2 42 876 4.7 323
Marion, FL............... 8.9 104.5 -2.2 6 795 5.4 309
Miami-Dade, FL........... 105.6 1,036.8 -9.3 183 1,109 5.5 302
Okaloosa, FL............. 6.8 82.1 -4.3 24 1,015 8.8 144
Orange, FL............... 46.6 688.2 -19.9 351 1,051 10.3 96
Osceola, FL.............. 8.0 82.9 -14.4 316 797 5.7 294
Palm Beach, FL........... 60.1 561.6 -7.5 121 1,138 7.6 215
Pasco, FL................ 11.8 113.2 -2.5 8 834 6.0 285
Pinellas, FL............. 35.1 414.7 -5.7 54 1,001 5.6 299
Polk, FL................. 14.6 220.8 -1.4 4 869 3.0 344
St. Johns, FL............ 8.2 74.8 -3.4 15 911 8.1 188
St. Lucie, FL............ 7.2 73.5 -3.3 14 875 3.2 340
Sarasota, FL............. 17.0 159.4 -5.2 42 941 5.5 302
Seminole, FL............. 16.1 186.9 -6.2 71 1,033 8.7 151
Volusia, FL.............. 15.3 160.4 -7.0 103 855 8.4 167
Bibb, GA................. 4.5 77.7 -5.8 56 872 5.2 315
Chatham, GA.............. 8.7 146.7 -9.5 190 952 6.1 279
Clayton, GA.............. 4.3 97.3 -20.5 353 1,089 2.6 345
Cobb, GA................. 23.3 341.4 -8.8 167 1,179 4.9 321
DeKalb, GA............... 19.0 280.8 -7.2 111 1,175 7.2 234
Forsyth, GA.............. 6.3 74.3 -4.6 30 1,015 6.4 269
Fulton, GA............... 46.9 809.3 -10.3 219 1,514 7.9 200
Gwinnett, GA............. 27.1 337.9 -6.7 88 1,056 3.6 334
Hall, GA................. 4.8 86.3 -3.7 18 964 3.5 337
Muscogee, GA............. 4.7 88.8 -6.0 64 884 7.8 204
Richmond, GA............. 4.7 97.5 -6.0 64 959 8.0 193
Honolulu, HI............. 27.7 385.0 -17.7 343 1,158 11.9 46
Maui + Kalawao, HI....... 6.8 54.6 -32.6 356 981 10.6 88
Ada, ID.................. 17.6 248.5 -2.6 10 1,017 7.1 241
Champaign, IL............ 4.1 85.3 -7.2 111 1,042 10.7 86
Cook, IL................. 138.4 2,297.3 -13.1 299 1,372 9.6 114
DuPage, IL............... 34.5 554.0 -12.4 277 1,290 7.4 226
Kane, IL................. 12.6 189.3 -13.1 299 1,031 8.5 159
Lake, IL................. 20.1 310.7 -11.7 260 1,500 9.7 109
McHenry, IL.............. 7.8 89.4 -10.7 235 933 7.9 200
McLean, IL............... 3.3 74.4 -9.5 190 1,075 12.8 24
Madison, IL.............. 5.3 96.3 -6.9 95 885 6.2 277
Peoria, IL............... 4.1 94.5 -10.8 237 1,143 7.4 226
St. Clair, IL............ 5.0 81.9 -11.6 259 942 11.3 68
Sangamon, IL............. 4.8 118.9 -9.2 181 1,110 6.8 258
Will, IL................. 15.1 231.8 -9.0 176 995 7.2 234
Winnebago, IL............ 5.9 112.0 -12.4 277 955 8.2 182
Allen, IN................ 9.2 177.9 -7.8 132 943 6.9 250
Elkhart, IN.............. 4.8 124.0 -8.6 162 908 -1.5 353
Hamilton, IN............. 10.0 137.5 -6.9 95 1,099 9.1 133
Lake, IN................. 10.6 171.3 -9.9 202 944 4.2 327
Marion, IN............... 24.9 552.4 -8.7 166 1,170 8.4 167
St. Joseph, IN........... 5.9 113.3 -9.8 200 941 7.3 229
Tippecanoe, IN........... 3.8 79.1 -7.1 106 971 3.6 334
Vanderburgh, IN.......... 4.8 98.8 -9.9 202 902 3.2 340
Johnson, IA.............. 4.4 77.2 -7.5 121 1,094 10.2 98
Linn, IA................. 7.1 122.3 -8.0 138 1,096 7.6 215
Polk, IA................. 18.3 282.3 -8.5 157 1,176 10.8 84
Scott, IA................ 5.8 84.0 -9.9 202 934 7.7 209
Johnson, KS.............. 24.5 333.2 -6.4 77 1,207 9.1 133
Sedgwick, KS............. 12.9 229.2 -11.3 251 945 4.7 323
Shawnee, KS.............. 5.1 90.6 -5.9 61 917 5.3 312
Wyandotte, KS............ 3.6 86.3 -4.4 27 1,098 4.2 327
Boone, KY................ 4.6 89.9 -5.9 61 969 3.1 343
Fayette, KY.............. 11.6 179.4 -8.4 152 1,055 9.4 123
Jefferson, KY............ 26.3 427.8 -9.6 194 1,154 8.4 167
Caddo, LA................ 7.4 100.5 -9.3 183 916 6.9 250
Calcasieu, LA............ 5.5 85.1 -17.1 340 984 2.4 348
East Baton Rouge, LA..... 16.8 233.1 -10.9 241 1,076 5.5 302
Jefferson, LA............ 14.5 168.8 -11.4 254 1,056 8.8 144
Lafayette, LA............ 10.3 118.5 -9.7 198 945 5.0 317
Orleans, LA.............. 14.0 158.8 -20.3 352 1,165 18.2 3
St. Tammany, LA.......... 9.0 83.1 -8.4 152 973 9.3 126
Cumberland, ME........... 13.9 167.2 -12.9 294 1,124 14.5 14
Anne Arundel, MD......... 15.5 246.2 -12.2 272 1,309 12.5 33
Baltimore, MD............ 21.2 340.4 -11.5 256 1,194 10.6 88
Frederick, MD............ 6.6 94.0 -12.6 283 1,108 11.9 46
Harford, MD.............. 5.9 87.1 -9.9 202 1,161 11.5 59
Howard, MD............... 10.2 154.6 -12.8 288 1,490 12.5 33
Montgomery, MD........... 33.0 420.8 -12.3 274 1,590 11.7 52
Prince George's, MD...... 16.4 280.6 -14.2 315 1,275 12.3 39
Baltimore City, MD....... 13.8 319.3 -7.6 126 1,329 3.7 333
Barnstable, MA........... 9.7 85.7 -21.1 355 1,076 16.1 7
Bristol, MA.............. 17.8 200.3 -14.4 316 1,124 11.1 76
Essex, MA................ 27.6 283.5 -15.3 330 1,311 13.7 19
Hampden, MA.............. 18.8 182.9 -14.5 318 1,037 11.1 76
Middlesex, MA............ 57.0 835.4 -12.3 274 1,880 14.0 16
Norfolk, MA.............. 25.6 299.2 -17.3 342 1,425 12.7 29
Plymouth, MA............. 16.5 167.7 -17.9 344 1,180 14.0 16
Suffolk, MA.............. 32.1 611.3 -13.6 309 2,053 13.4 21
Worcester, MA............ 26.5 312.7 -12.5 282 1,199 12.8 24
Genesee, MI.............. 7.3 119.0 -12.3 274 925 7.2 234
Ingham, MI............... 6.6 136.6 -11.0 244 1,140 9.5 116
Kalamazoo, MI............ 5.8 109.6 -11.7 260 1,071 9.1 133
Kent, MI................. 16.3 351.7 -15.4 333 1,059 13.5 20
Macomb, MI............... 19.2 291.2 -13.5 304 1,114 6.0 285
Oakland, MI.............. 43.2 648.3 -14.8 325 1,278 8.4 167
Ottawa, MI............... 6.3 117.6 -10.0 211 957 6.0 285
Saginaw, MI.............. 4.1 73.7 -13.8 313 947 9.0 137
Washtenaw, MI............ 9.3 189.6 -12.0 265 1,260 9.2 130
Wayne, MI................ 36.1 639.8 -13.5 304 1,282 11.8 49
Anoka, MN................ 8.0 119.2 -9.1 179 1,110 7.1 241
Dakota, MN............... 11.0 174.9 -10.3 219 1,167 9.5 116
Hennepin, MN............. 42.0 830.7 -12.4 277 1,470 9.1 133
Olmsted, MN.............. 3.9 91.4 -9.9 202 1,332 14.6 12
Ramsey, MN............... 14.5 299.9 -11.2 248 1,288 8.5 159
St. Louis, MN............ 5.5 87.3 -13.5 304 991 8.3 177
Stearns, MN.............. 4.5 80.0 -8.5 157 966 8.4 167
Washington, MN........... 6.3 82.0 -9.8 200 1,016 9.0 137
Harrison, MS............. 4.6 78.9 -10.1 214 818 9.5 116
Hinds, MS................ 5.6 111.6 -6.6 86 925 6.1 279
Boone, MO................ 5.0 87.8 -6.9 95 990 12.4 36
Clay, MO................. 6.0 99.8 -6.7 88 960 1.8 350
Greene, MO............... 9.6 160.4 -5.8 56 906 8.1 188
Jackson, MO.............. 23.2 347.8 -8.3 148 1,154 5.3 312
St. Charles, MO.......... 10.1 145.1 -5.4 48 954 7.7 209
St. Louis, MO............ 41.6 551.3 -9.7 198 1,221 7.3 229
St. Louis City, MO....... 15.7 201.8 -11.9 264 1,243 7.9 200
Yellowstone, MT.......... 6.6 80.1 -3.4 15 978 6.5 266
Douglas, NE.............. 19.2 319.1 -7.0 103 1,083 8.2 182
Lancaster, NE............ 10.2 161.3 -6.4 77 943 9.3 126
Clark, NV................ 57.1 830.0 -18.9 348 1,026 8.8 144
Washoe, NV............... 15.2 207.3 -8.8 167 1,065 8.7 151
Hillsborough, NH......... 12.4 186.6 -10.5 226 1,306 11.3 68
Merrimack, NH............ 5.2 71.1 -9.5 190 1,091 9.4 123
Rockingham, NH........... 11.3 137.7 -11.0 244 1,205 11.8 49
Atlantic, NJ............. 6.7 90.8 -34.2 357 1,104 22.5 1
Bergen, NJ............... 33.7 372.5 -17.0 338 1,364 10.6 88
Burlington, NJ........... 11.3 180.8 -12.7 285 1,202 8.8 144
Camden, NJ............... 12.5 178.5 -13.5 304 1,172 11.7 52
Essex, NJ................ 21.2 295.6 -15.3 330 1,447 11.2 73
Gloucester, NJ........... 6.6 101.9 -11.3 251 996 9.5 116
Hudson, NJ............... 16.1 234.0 -15.0 326 1,550 7.8 204
Mercer, NJ............... 11.4 238.2 -9.6 194 1,508 11.4 64
Middlesex, NJ............ 22.9 380.2 -12.0 265 1,364 10.5 93
Monmouth, NJ............. 20.6 226.8 -18.1 345 1,197 15.0 10
Morris, NJ............... 17.3 258.7 -13.6 309 1,667 8.2 182
Ocean, NJ................ 13.9 151.4 -16.9 337 955 12.8 24
Passaic, NJ.............. 12.9 142.9 -15.1 329 1,140 11.1 76
Somerset, NJ............. 10.4 169.0 -13.0 296 1,780 9.7 109
Union, NJ................ 15.0 200.4 -13.5 304 1,465 12.0 43
Bernalillo, NM........... 20.1 304.3 -8.8 167 1,009 9.7 109
Albany, NY............... 10.4 211.1 -10.3 219 1,277 8.3 177
Bronx, NY................ 19.2 288.0 -11.5 256 1,204 8.0 193
Broome, NY............... 4.4 75.6 -13.2 301 1,010 12.8 24
Dutchess, NY............. 8.5 98.1 -15.0 326 1,199 11.3 68
Erie, NY................. 24.5 407.8 -14.7 322 1,106 12.1 41
Kings, NY................ 66.6 688.2 -14.6 320 1,058 10.3 96
Monroe, NY............... 18.9 344.3 -13.4 302 1,126 11.6 57
Nassau, NY............... 54.5 533.1 -17.0 338 1,388 14.2 15
New York, NY............. 131.1 2,048.7 -18.8 347 2,427 14.9 11
Oneida, NY............... 5.3 94.4 -12.4 277 947 8.9 140
Onondaga, NY............. 12.7 221.5 -13.0 296 1,095 9.5 116
Orange, NY............... 10.8 129.5 -15.0 326 1,085 12.6 30
Queens, NY............... 54.1 592.5 -18.2 346 1,174 7.8 204
Richmond, NY............. 10.1 110.1 -15.7 334 1,158 12.0 43
Rockland, NY............. 11.3 112.2 -15.3 330 1,154 11.1 76
Saratoga, NY............. 6.1 78.0 -16.2 335 1,170 12.6 30
Suffolk, NY.............. 53.8 579.5 -16.5 336 1,296 12.0 43
Westchester, NY.......... 36.4 367.7 -17.1 340 1,721 21.7 2
Buncombe, NC............. 10.3 114.7 -14.7 322 916 8.5 159
Cabarrus, NC............. 5.2 72.2 -6.5 81 862 6.9 250
Catawba, NC.............. 4.6 81.7 -7.6 126 851 2.5 346
Cumberland, NC........... 6.5 112.1 -7.5 121 887 3.9 331
Durham, NC............... 9.1 205.9 -5.4 48 1,478 8.4 167
Forsyth, NC.............. 9.7 174.6 -8.6 162 1,021 6.9 250
Guilford, NC............. 15.1 260.1 -8.5 157 986 3.8 332
Iredell, NC.............. 5.8 73.2 -4.3 24 983 5.4 309
Mecklenburg, NC.......... 41.5 671.3 -6.3 75 1,331 8.4 167
New Hanover, NC.......... 9.0 110.0 -7.5 121 961 9.7 109
Pitt, NC................. 3.9 71.8 -7.1 106 913 5.7 294
Wake, NC................. 38.6 534.4 -7.2 111 1,207 7.3 229
Cass, ND................. 7.6 113.2 -6.8 93 1,070 7.5 219
Butler, OH............... 8.0 146.3 -7.8 132 1,024 8.2 182
Cuyahoga, OH............. 36.2 668.0 -9.6 194 1,168 8.2 182
Delaware, OH............. 5.8 83.7 -10.1 214 1,142 11.4 64
Franklin, OH............. 34.2 711.2 -6.9 95 1,142 7.6 215
Greene, OH............... 3.7 72.9 -4.7 34 1,224 9.9 103
Hamilton, OH............. 24.5 476.4 -9.6 194 1,234 6.5 266
Lake, OH................. 6.3 90.1 -8.8 167 956 7.2 234
Lorain, OH............... 6.3 91.9 -8.4 152 879 6.2 277
Lucas, OH................ 10.1 188.6 -10.9 241 959 5.5 302
Mahoning, OH............. 5.9 88.8 -9.9 202 821 8.7 151
Montgomery, OH........... 12.2 236.6 -7.7 130 968 4.8 322
Stark, OH................ 8.6 147.6 -8.3 148 836 4.1 330
Summit, OH............... 14.5 246.7 -8.3 148 1,010 6.4 269
Warren, OH............... 5.3 92.0 -8.0 138 1,075 8.1 188
Cleveland, OK............ 6.1 80.9 -0.2 1 865 7.5 219
Oklahoma, OK............. 28.6 438.2 -6.0 64 1,059 6.1 279
Tulsa, OK................ 22.8 338.1 -6.9 95 1,017 5.5 302
Clackamas, OR............ 15.7 155.0 -9.9 202 1,130 9.3 126
Deschutes, OR............ 9.5 79.4 -9.3 183 1,015 12.8 24
Jackson, OR.............. 8.0 84.6 -7.1 106 922 8.9 140
Lane, OR................. 12.9 142.5 -10.6 231 938 9.8 106
Marion, OR............... 11.6 150.2 -7.4 117 1,015 9.3 126
Multnomah, OR............ 36.6 455.2 -12.8 288 1,293 11.2 73
Washington, OR........... 20.5 278.7 -8.6 162 1,516 11.3 68
Allegheny, PA............ 35.7 633.3 -10.6 231 1,267 8.5 159
Berks, PA................ 8.9 156.1 -11.5 256 1,042 7.1 241
Bucks, PA................ 20.4 232.8 -14.5 318 1,115 11.5 59
Butler, PA............... 5.1 81.9 -8.3 148 1,076 8.2 182
Chester, PA.............. 15.9 227.8 -10.8 237 1,543 11.1 76
Cumberland, PA........... 6.6 126.2 -7.9 136 1,088 8.0 193
Dauphin, PA.............. 7.5 167.5 -12.0 265 1,170 9.8 106
Delaware, PA............. 14.2 196.8 -13.4 302 1,251 11.3 68
Erie, PA................. 6.9 108.5 -13.0 296 916 11.4 64
Lackawanna, PA........... 5.6 86.5 -11.8 262 922 11.5 59
Lancaster, PA............ 13.8 221.7 -10.7 235 979 8.1 188
Lehigh, PA............... 8.8 175.0 -11.2 248 1,133 9.4 123
Luzerne, PA.............. 7.4 131.4 -10.5 226 930 9.0 137
Montgomery, PA........... 28.0 450.2 -12.4 277 1,446 11.5 59
Northampton, PA.......... 6.9 104.7 -12.6 283 1,003 8.0 193
Philadelphia, PA......... 35.1 610.8 -12.9 294 1,380 9.9 103
Washington, PA........... 5.5 78.3 -13.9 314 1,107 5.3 312
Westmoreland, PA......... 9.2 121.7 -10.4 224 932 7.1 241
York, PA................. 9.2 164.0 -9.3 183 1,026 7.7 209
Kent, RI................. 5.6 66.8 -14.7 322 1,070 15.3 9
Providence, RI........... 19.1 253.2 -12.8 288 1,198 12.1 41
Charleston, SC........... 17.6 236.1 -10.3 219 1,064 9.7 109
Greenville, SC........... 15.9 256.8 -7.8 132 997 6.7 260
Horry, SC................ 10.0 124.9 -12.1 269 723 11.2 73
Lexington, SC............ 7.3 118.3 -2.5 8 865 5.5 302
Richland, SC............. 11.0 206.0 -7.1 106 970 8.6 156
Spartanburg, SC.......... 6.8 141.7 -5.2 42 920 0.3 351
York, SC................. 6.8 94.9 -6.1 69 960 9.5 116
Minnehaha, SD............ 7.8 123.6 -5.0 36 1,013 8.5 159
Davidson, TN............. 25.4 460.4 -10.6 231 1,215 8.4 167
Hamilton, TN............. 10.6 194.7 -6.1 69 990 4.2 327
Knox, TN................. 13.3 226.7 -5.3 46 983 6.4 269
Rutherford, TN........... 6.3 123.7 -6.9 95 934 -2.7 355
Shelby, TN............... 21.5 465.2 -7.6 126 1,156 5.8 290
Williamson, TN........... 10.0 130.9 -6.5 81 1,354 6.9 250
Bell, TX................. 5.9 116.7 -3.9 20 982 5.4 309
Bexar, TX................ 43.7 815.1 -7.1 106 1,047 5.8 290
Brazoria, TX............. 6.3 110.1 -5.9 61 1,134 3.4 338
Brazos, TX............... 4.8 98.0 -5.6 52 881 9.9 103
Cameron, TX.............. 6.6 136.6 -4.1 21 698 6.1 279
Collin, TX............... 28.7 415.5 -5.8 56 1,350 7.5 219
Dallas, TX............... 80.2 1,623.5 -5.8 56 1,361 4.5 326
Denton, TX............... 16.9 249.5 -5.1 38 1,031 7.1 241
Ector, TX................ 4.2 65.9 -19.3 350 1,142 -6.6 357
El Paso, TX.............. 15.7 292.3 -5.7 54 810 7.4 226
Fort Bend, TX............ 15.1 186.1 -5.8 56 1,026 5.0 317
Galveston, TX............ 6.4 106.0 -6.0 64 1,029 5.6 299
Gregg, TX................ 4.3 68.2 -10.8 237 919 0.2 352
Harris, TX............... 119.2 2,179.4 -7.3 115 1,352 3.4 338
Hidalgo, TX.............. 12.8 253.0 -4.3 24 704 7.0 246
Jefferson, TX............ 5.8 110.1 -10.2 217 1,101 5.7 294
Lubbock, TX.............. 7.9 134.9 -4.6 30 918 7.9 200
McLennan, TX............. 5.5 111.1 -2.3 7 943 7.0 246
Midland, TX.............. 6.2 87.8 -21.0 354 1,404 -4.6 356
Montgomery, TX........... 12.7 181.7 -6.7 88 1,145 5.0 317
Nueces, TX............... 8.3 151.4 -8.5 157 948 2.5 346
Potter, TX............... 4.0 73.7 -4.5 29 954 6.7 260
Smith, TX................ 6.5 100.8 -4.1 21 928 5.7 294
Tarrant, TX.............. 46.4 867.9 -6.5 81 1,129 5.1 316
Travis, TX............... 44.9 733.1 -6.4 77 1,417 9.6 114
Webb, TX................. 5.6 95.0 -8.8 167 753 7.7 209
Williamson, TX........... 12.4 175.1 -5.1 38 1,193 11.8 49
Davis, UT................ 9.3 132.2 -0.9 3 986 10.8 84
Salt Lake, UT............ 50.3 691.0 -4.2 23 1,146 8.8 144
Utah, UT................. 18.5 248.5 -0.2 1 984 10.2 98
Weber, UT................ 6.5 106.1 -2.9 12 875 7.6 215
Chittenden, VT........... 7.2 91.0 -12.8 288 1,192 14.6 12
Arlington, VA............ 9.1 170.3 -8.9 173 1,926 12.2 40
Chesterfield, VA......... 9.4 128.8 -6.9 95 966 6.7 260
Fairfax, VA.............. 36.9 576.7 -8.1 143 1,776 8.0 193
Henrico, VA.............. 11.8 173.9 -10.8 237 1,112 8.5 159
Loudoun, VA.............. 13.0 158.4 -12.1 269 1,362 12.6 30
Prince William, VA....... 9.7 122.2 -11.0 244 1,048 11.7 52
Alexandria City, VA...... 6.2 81.1 -11.8 262 1,610 10.1 101
Chesapeake City, VA...... 6.3 96.9 -7.0 103 904 7.2 234
Newport News City, VA.... 4.0 97.0 -7.2 111 1,090 5.8 290
Norfolk City, VA......... 6.1 128.9 -9.9 202 1,188 8.4 167
Richmond City, VA........ 8.0 140.6 -10.5 226 1,308 12.5 33
Virginia Beach City, VA.. 12.4 164.5 -10.4 224 924 10.4 94
Benton, WA............... 6.1 87.4 -9.9 202 1,147 5.8 290
Clark, WA................ 15.7 152.4 -8.4 152 1,122 7.3 229
King, WA................. 90.3 1,312.9 -8.9 173 1,945 13.9 18
Kitsap, WA............... 7.0 86.2 -6.8 93 1,137 7.7 209
Pierce, WA............... 23.7 292.9 -8.1 143 1,090 6.0 285
Snohomish, WA............ 22.1 268.5 -8.9 173 1,262 6.9 250
Spokane, WA.............. 16.9 214.9 -7.6 126 1,007 6.1 279
Thurston, WA............. 8.8 110.3 -7.4 117 1,117 8.7 151
Whatcom, WA.............. 7.6 83.8 -10.2 217 1,007 6.4 269
Yakima, WA............... 8.0 117.0 -8.0 138 829 7.2 234
Kanawha, WV.............. 5.6 88.6 -9.5 190 954 3.6 334
Brown, WI................ 7.3 148.0 -8.0 138 1,007 7.5 219
Dane, WI................. 16.3 317.9 -9.0 176 1,231 12.4 36
Milwaukee, WI............ 27.5 437.9 -11.0 244 1,108 8.0 193
Outagamie, WI............ 5.6 102.3 -8.2 146 988 6.9 250
Racine, WI............... 4.7 70.3 -8.6 162 960 5.5 302
Waukesha, WI............. 13.8 231.5 -8.0 138 1,145 7.5 219
Winnebago, WI............ 4.0 87.8 -6.5 81 1,033 -2.6 354
San Juan, PR............. 10.9 213.4 -10.7 (5) 681 6.2 (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 357 U.S. counties comprise 72.9 percent of
the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,
second quarter 2020
Employment Average weekly
wage(1)
Establishments,
second quarter
County by NAICS supersector 2020 Percent Percent
(thousands) June change, Second change,
2020 June quarter second
(thousands) 2019-20(2) 2020 quarter
2019-20(2)
United States(3) ............................ 10,451.0 135,114.4 -9.4 $1,188 8.6
Private industry........................... 10,148.9 114,475.9 -10.1 1,179 8.7
Natural resources and mining............. 140.4 1,854.0 -10.1 1,087 -2.2
Construction............................. 844.6 7,269.3 -4.9 1,215 1.2
Manufacturing............................ 358.0 11,965.4 -7.2 1,331 2.6
Trade, transportation, and utilities..... 1,946.3 25,726.3 -6.1 979 5.8
Information.............................. 195.4 2,597.7 -10.1 2,444 12.7
Financial activities..................... 939.4 8,121.3 -2.9 1,757 7.1
Professional and business services....... 1,963.0 19,711.7 -7.4 1,521 6.4
Education and health services............ 1,857.3 21,580.9 -6.5 1,027 5.1
Leisure and hospitality.................. 887.7 11,755.1 -31.2 463 -0.9
Other services........................... 817.7 3,729.8 -18.3 862 13.6
Government................................. 302.0 20,638.4 -5.5 1,237 7.6
Los Angeles, CA.............................. 518.8 3,945.3 -12.2 1,333 8.9
Private industry........................... 512.4 3,389.2 -13.2 1,294 8.9
Natural resources and mining............. 0.6 6.3 4.1 1,048 -6.2
Construction............................. 17.6 146.0 -2.8 1,342 3.5
Manufacturing............................ 12.6 310.5 -9.0 1,491 7.0
Trade, transportation, and utilities..... 59.8 746.7 -10.2 1,067 6.1
Information.............................. 13.8 152.1 -22.2 2,759 9.1
Financial activities..................... 31.2 205.9 -6.6 2,036 5.8
Professional and business services....... 58.4 566.8 -10.4 1,613 6.9
Education and health services............ 247.8 785.6 -4.4 961 5.4
Leisure and hospitality.................. 40.7 355.2 -36.0 752 9.0
Other services........................... 29.8 114.0 -25.7 951 22.2
Government................................. 6.4 556.1 -5.5 1,562 6.9
Cook, IL..................................... 138.4 2,297.3 -13.1 1,372 9.6
Private industry........................... 137.2 2,023.6 -13.7 1,359 9.4
Natural resources and mining............. 0.1 1.7 13.6 1,217 0.2
Construction............................. 11.1 71.8 -9.9 1,545 2.3
Manufacturing............................ 5.6 173.7 -7.1 1,271 0.3
Trade, transportation, and utilities..... 28.3 425.3 -9.5 1,101 5.1
Information.............................. 2.6 49.4 -7.5 2,276 8.5
Financial activities..................... 14.2 201.9 -3.0 2,305 5.4
Professional and business services....... 29.1 431.8 -10.8 1,651 5.4
Education and health services............ 16.0 418.8 -7.4 1,092 7.9
Leisure and hospitality.................. 13.8 165.3 -46.2 557 -4.0
Other services........................... 15.6 83.7 -16.7 1,109 14.6
Government................................. 1.3 273.7 -8.3 1,467 10.2
New York, NY................................. 131.1 2,048.7 -18.8 2,427 14.9
Private industry........................... 129.7 1,818.4 -20.7 2,516 16.6
Natural resources and mining............. 0.0 0.2 14.6 2,374 -20.0
Construction............................. 2.4 35.5 -17.0 1,960 -0.9
Manufacturing............................ 1.8 13.8 -37.7 1,860 23.7
Trade, transportation, and utilities..... 18.3 178.1 -30.2 1,714 10.6
Information.............................. 5.8 167.1 -14.9 3,232 13.1
Financial activities..................... 19.6 380.3 -4.0 3,960 6.1
Professional and business services....... 29.3 527.5 -11.5 2,557 5.8
Education and health services............ 10.3 325.6 -9.0 1,588 9.5
Leisure and hospitality.................. 14.5 107.0 -66.1 1,109 15.5
Other services........................... 19.9 79.1 -26.6 1,596 23.1
Government................................. 1.5 230.3 -0.6 1,727 3.1
Harris, TX................................... 119.2 2,179.4 -7.3 1,352 3.4
Private industry........................... 118.7 1,901.4 -8.4 1,365 3.3
Natural resources and mining............. 1.6 55.7 -18.2 3,304 5.9
Construction............................. 7.9 155.4 -9.2 1,403 0.6
Manufacturing............................ 4.9 164.8 -8.9 1,597 0.4
Trade, transportation, and utilities..... 25.3 444.2 -5.1 1,197 0.6
Information.............................. 1.3 22.9 -13.9 1,637 8.8
Financial activities..................... 12.9 125.2 -3.6 1,764 3.5
Professional and business services....... 24.1 387.4 -6.5 1,668 1.6
Education and health services............ 17.2 290.5 -3.9 1,105 3.0
Leisure and hospitality.................. 10.8 192.6 -21.7 459 -8.4
Other services........................... 11.6 60.5 -12.1 902 4.4
Government................................. 0.6 278.0 1.0 1,266 6.3
Maricopa, AZ................................. 110.7 1,924.6 -4.6 1,137 7.7
Private industry........................... 110.0 1,751.2 -4.1 1,125 7.6
Natural resources and mining............. 0.5 7.8 -4.9 1,050 2.4
Construction............................. 8.8 131.7 0.1 1,195 3.0
Manufacturing............................ 3.5 128.1 -1.7 1,535 2.5
Trade, transportation, and utilities..... 21.6 385.3 -0.1 1,018 5.7
Information.............................. 2.4 33.9 -13.2 1,755 21.5
Financial activities..................... 14.6 191.4 1.9 1,509 11.4
Professional and business services....... 28.0 333.7 -3.7 1,174 4.4
Education and health services............ 13.9 314.4 -1.4 1,052 3.3
Leisure and hospitality.................. 9.3 178.3 -20.7 510 -3.4
Other services........................... 7.2 46.6 -12.4 846 7.4
Government................................. 0.7 173.4 -9.6 1,240 8.2
Dallas, TX................................... 80.2 1,623.5 -5.8 1,361 4.5
Private industry........................... 79.7 1,452.7 -6.2 1,366 4.4
Natural resources and mining............. 0.5 7.8 -10.0 2,468 -1.6
Construction............................. 5.0 89.5 -5.1 1,332 2.5
Manufacturing............................ 2.8 114.1 -3.7 1,484 -1.8
Trade, transportation, and utilities..... 16.2 340.0 -2.0 1,199 3.5
Information.............................. 1.5 44.2 -6.4 2,070 4.9
Financial activities..................... 10.0 157.9 -1.1 1,881 2.0
Professional and business services....... 18.5 341.2 -5.0 1,569 1.6
Education and health services............ 10.0 193.7 -4.2 1,169 1.2
Leisure and hospitality.................. 7.3 126.6 -24.5 525 1.2
Other services........................... 7.2 36.4 -18.5 1,011 12.7
Government................................. 0.5 170.8 -1.4 1,317 6.0
Orange, CA................................... 130.0 1,442.0 -12.7 1,334 11.4
Private industry........................... 128.6 1,298.2 -13.1 1,317 11.6
Natural resources and mining............. 0.2 2.2 -5.6 925 1.1
Construction............................. 8.0 101.2 -5.3 1,469 1.4
Manufacturing............................ 5.3 146.4 -8.5 1,641 8.0
Trade, transportation, and utilities..... 18.7 231.0 -9.2 1,144 7.7
Information.............................. 1.6 23.0 -10.8 2,278 13.9
Financial activities..................... 13.4 112.4 -3.8 2,078 12.5
Professional and business services....... 24.3 293.3 -9.5 1,511 9.5
Education and health services............ 39.1 211.4 -5.8 1,002 4.3
Leisure and hospitality.................. 9.9 139.4 -39.7 504 -7.0
Other services........................... 7.9 37.9 -21.5 853 14.5
Government................................. 1.4 143.9 -8.4 1,473 7.2
San Diego, CA................................ 118.2 1,325.1 -11.2 1,315 10.6
Private industry........................... 116.3 1,101.6 -12.0 1,269 11.0
Natural resources and mining............. 0.7 10.1 -2.4 785 1.8
Construction............................. 8.2 80.9 -2.5 1,332 4.4
Manufacturing............................ 3.6 112.5 -4.6 1,662 3.9
Trade, transportation, and utilities..... 15.5 199.4 -9.4 991 10.6
Information.............................. 1.4 21.2 -10.0 2,037 0.9
Financial activities..................... 11.5 72.6 -4.3 1,693 10.8
Professional and business services....... 21.8 237.1 -5.8 1,740 5.4
Education and health services............ 35.9 197.4 -5.9 1,018 5.2
Leisure and hospitality.................. 9.3 132.5 -35.8 519 -5.5
Other services........................... 8.3 37.8 -29.3 765 18.6
Government................................. 2.0 223.5 -6.8 1,527 6.9
King, WA..................................... 90.3 1,312.9 -8.9 1,945 13.9
Private industry........................... 89.6 1,145.2 -9.6 2,000 14.7
Natural resources and mining............. 0.4 2.9 -11.8 1,321 -5.4
Construction............................. 6.9 70.9 -7.3 1,422 -4.2
Manufacturing............................ 2.5 94.9 -10.4 1,773 4.4
Trade, transportation, and utilities..... 13.4 263.6 -4.2 2,190 11.8
Information.............................. 2.7 127.5 4.4 4,319 14.4
Financial activities..................... 7.2 67.2 -3.2 2,034 12.2
Professional and business services....... 19.0 226.5 -4.2 2,027 7.7
Education and health services............ 21.0 167.5 -6.6 1,142 2.1
Leisure and hospitality.................. 7.3 85.4 -42.7 594 -6.9
Other services........................... 9.2 38.9 -20.7 1,055 11.1
Government................................. 0.6 167.7 -3.8 1,579 9.0
Miami-Dade, FL............................... 105.6 1,036.8 -9.3 1,109 5.5
Private industry........................... 105.3 913.8 -10.1 1,082 5.0
Natural resources and mining............. 0.5 8.9 3.9 726 6.3
Construction............................. 7.2 52.0 -0.9 1,052 1.3
Manufacturing............................ 2.8 39.7 -4.6 950 1.2
Trade, transportation, and utilities..... 24.5 262.0 -9.0 994 4.2
Information.............................. 1.6 16.7 -12.4 1,812 4.4
Financial activities..................... 11.4 74.0 -3.0 1,681 5.0
Professional and business services....... 24.5 153.6 -6.3 1,282 -1.5
Education and health services............ 12.8 177.0 -3.8 1,050 3.3
Leisure and hospitality.................. 7.7 95.8 -33.4 615 -3.5
Other services........................... 8.1 32.1 -16.9 732 7.6
Government................................. 0.3 122.9 -2.7 1,289 6.7
(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 2019 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,
second quarter 2020
Employment Average weekly
wage(1)
Establishments,
second quarter
State 2020 Percent Percent
(thousands) June change, Second change,
2020 June quarter second
(thousands) 2019-20 2020 quarter
2019-20
United States(2)........... 10,451.0 135,114.4 -9.4 $1,188 8.6
Alabama.................... 131.2 1,868.7 -6.4 964 5.9
Alaska..................... 22.7 296.2 -12.7 1,195 11.2
Arizona.................... 170.7 2,708.4 -5.1 1,090 7.9
Arkansas................... 93.0 1,156.5 -5.5 924 7.3
California................. 1,633.1 15,911.2 -10.2 1,468 10.9
Colorado................... 216.4 2,545.9 -8.0 1,226 8.7
Connecticut................ 123.4 1,483.6 -12.3 1,407 11.3
Delaware................... 34.5 416.0 -9.3 1,156 9.0
District of Columbia....... 41.7 701.8 -10.0 1,987 11.7
Florida.................... 738.0 8,113.8 -7.1 1,032 6.6
Georgia.................... 307.2 4,196.0 -7.0 1,075 5.7
Hawaii..................... 45.9 524.9 -20.1 1,108 12.0
Idaho...................... 67.9 748.3 -2.3 882 7.6
Illinois................... 379.6 5,391.8 -11.3 1,218 8.6
Indiana.................... 171.6 2,865.7 -7.3 960 5.6
Iowa....................... 104.7 1,458.8 -8.0 978 8.4
Kansas..................... 90.0 1,306.0 -7.0 969 7.1
Kentucky................... 125.4 1,754.0 -8.2 970 6.4
Louisiana.................. 137.8 1,710.1 -11.0 985 6.7
Maine...................... 53.8 572.5 -10.8 980 12.3
Maryland................... 175.8 2,430.3 -11.2 1,305 10.7
Massachusetts.............. 263.1 3,178.8 -14.3 1,570 14.0
Michigan................... 268.5 3,850.9 -12.9 1,114 9.5
Minnesota.................. 185.4 2,644.6 -10.5 1,200 9.0
Mississippi................ 73.8 1,063.1 -6.4 812 5.9
Missouri................... 215.9 2,622.2 -7.5 1,015 7.1
Montana.................... 51.5 459.5 -4.9 919 9.1
Nebraska................... 72.9 932.3 -6.0 960 8.0
Nevada..................... 85.9 1,191.6 -15.4 1,048 9.1
New Hampshire.............. 54.8 605.4 -10.5 1,215 11.5
New Jersey................. 284.1 3,570.3 -14.6 1,376 11.3
New Mexico................. 62.4 757.0 -9.4 958 7.8
New York................... 652.0 8,142.6 -15.9 1,520 12.8
North Carolina............. 296.2 4,205.4 -6.9 1,038 6.9
North Dakota............... 32.4 390.1 -9.7 1,061 3.3
Ohio....................... 302.3 5,049.8 -8.0 1,031 7.0
Oklahoma................... 112.1 1,521.3 -6.3 940 4.4
Oregon..................... 160.9 1,789.3 -9.6 1,143 10.3
Pennsylvania............... 362.8 5,314.5 -11.1 1,170 9.2
Rhode Island............... 39.5 429.3 -13.2 1,172 13.1
South Carolina............. 144.4 1,991.0 -7.2 928 6.9
South Dakota............... 34.7 415.9 -5.9 912 9.0
Tennessee.................. 171.1 2,847.2 -6.6 1,016 5.3
Texas...................... 727.4 11,807.1 -6.3 1,156 5.0
Utah....................... 111.6 1,474.8 -3.0 1,017 9.1
Vermont.................... 26.1 271.8 -13.6 1,055 13.6
Virginia................... 283.3 3,635.2 -8.8 1,218 9.4
Washington................. 253.8 3,207.1 -8.4 1,424 10.6
West Virginia.............. 51.3 634.9 -9.4 933 4.9
Wisconsin.................. 179.2 2,690.0 -8.7 1,014 8.0
Wyoming.................... 27.2 260.5 -9.6 965 3.7
Puerto Rico................ 46.1 798.7 -7.9 556 4.7
Virgin Islands............. 3.4 35.4 -7.0 1,016 6.9
(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
