For release 10:00 a.m. (ET), Wednesday, August 19, 2020 USDL-20-1588
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
COUNTY EMPLOYMENT AND WAGES – FIRST QUARTER 2020
From March 2019 to March 2020, employment increased in 202 of the 357 largest U.S. counties, the
U.S. Bureau of Labor Statistics reported today. In March 2020, national employment (as measured by
the QCEW program) increased to 147.1 million, a 0.4-percent increase over the year. St. Johns, FL, had
the largest over-the-year increase in employment with a gain of 3.7 percent. Employment data in this
release are presented for March 2020, and average weekly wage data are presented for first quarter 2020.
Among the 357 largest counties, 335 had over-the-year increases in average weekly wages. In the first
quarter of 2020, average weekly wages for the nation increased to $1,222, a 3.3-percent increase over
the year. McLean, IL, had the largest first quarter over-the-year wage gain at 13.3 percent. (See table 1.)
Large County Employment in March 2020
St. Johns, FL, had the largest over-the-year percentage increase in employment (+3.7 percent). Within
St. Johns, the largest employment increase occurred in leisure and hospitality, which gained 599 jobs
over the year (+3.8 percent).
Ector, TX, experienced the largest over-the-year percentage decrease in employment, with a loss of 5.5
percent. Within Ector, natural resources and mining had the largest employment decrease with a loss of
2,263 jobs (-15.2 percent).
Large County Average Weekly Wage in First Quarter 2020
McLean, IL, had the largest over-the-year percentage increase in average weekly wages (+13.3 percent).
Within McLean, an average weekly wage gain of $491 (+21.9 percent) in financial activities made the
largest contribution to the county’s increase in average weekly wages.
Peoria, IL, had the largest over-the-year percentage decrease in average weekly wages with a loss of
12.8 percent. Within Peoria, manufacturing had the largest impact, with an average weekly wage
decrease of $1,253 (-29.2 percent) over the year.
Ten Largest Counties
Six of the 10 largest counties had over-the-year percentage increases in employment. In March 2020,
Maricopa, AZ, had the largest over-the-year employment percentage gain among the 10 largest counties
(+2.5 percent). Within Maricopa, education and health services had the largest employment increase
with a gain of 13,126 jobs (+4.0 percent). (See table 2.)
All of the 10 largest counties had over-the-year percentage increases in average weekly wages. In first
quarter 2020, San Diego, CA, experienced the largest over-the-year percentage gain in average weekly
wages among the 10 largest counties (+5.6 percent). Within San Diego, professional and business
services had the largest impact, with an average weekly wage increase of $149 (+8.4 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. March 2020 employment and first 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 first quarter 2020 is scheduled to be
released on Wednesday, September 2, 2020, at 10:00 a.m. (ET).
The County Employment and Wages news release for second quarter 2020 is scheduled to be
released on Wednesday, November 18, 2020, at 10:00 a.m. (ET).
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| |
| County Changes for the 2020 County Employment and Wages News Releases |
| |
| Counties with annual average employment of 75,000 or more in 2019 are included in this release |
| and will be included in future 2020 releases. 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. |
| |
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| |
| Special Notice: Possible Imputation Methodology Improvements |
| |
| QCEW may implement 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. Usually, non-respondents account for less than five percent of QCEW |
| employment. However, BLS expects substantially higher than usual numbers of non-respondent |
| employers in second quarter 2020 due to the coronavirus (COVID-19) pandemic and efforts to |
| contain it. |
| |
| Research is ongoing on the implementation of three potential improvements to imputation |
| methodology. First, summary counts of claims for the regular state unemployment insurance |
| benefits per employer may help identify employers who have ceased operations, rather than being |
| identified as late respondents. Second, for employers that are expected to still be in operation, |
| the imputation formula may be modified to use reported data for similar employers to create |
| imputed levels of employment and wages. Third, state QCEW staff may use unemployment insurance |
| claims information as a supplement to their review of imputed and reported QCEW data. |
| |
| If implemented, these changes may result in larger than usual revisions to QCEW estimates for |
| first quarter 2020. For more information on QCEW imputation methodology, see |
| www.bls.gov/cew/additional-resources/imputation-methodology.htm. |
| |
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| |
| QCEW Data and Response Impacted by the COVID-19 Pandemic |
| |
| Beginning with this release of first quarter 2020 data, the Quarterly Census of Employment and |
| Wages (QCEW) program will publish response rate tables for establishments, employment, and total |
| quarterly wages. Tables for the first quarter of 2020 are available at |
| www.bls.gov/covid19/county-employment-and-wages-covid-19-impact-first-quarter-2020.htm. |
| For more information about the effects of the COVID-19 pandemic on QCEW data, please visit |
| www.bls.gov/covid19/effects-of-covid-19-pandemic-on-county-employment-and-wages-data.htm. |
| |
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Technical Note
These data are the product of a federal-state cooperative program, the Quarterly Census of
Employment and Wages (QCEW) program, also known as the ES-202 program. The data are
derived from summaries of employment and total pay of workers covered by state and federal
unemployment insurance (UI) legislation and provided by State Workforce Agencies (SWAs). The
summaries are a result of the administration of state unemployment insurance programs that
require most employers to pay quarterly taxes based on the employment and wages of workers
covered by UI. QCEW data in this release are based on the 2017 North American Industry
Classification System (NAICS). Data for 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 8.2 |
| 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, in-
| | | cluding railroads,
| | | religious organiza-
| | | tions, and other non-
| | | UI-covered jobs
-----------|---------------------|----------------------|------------------------
Publication|--Quarterly |--Quarterly |--Monthly
frequency | -Within 5 months | -7 months after the | -Usually the 3rd Friday
| after the end of | end of each quarter| after the end of the
| each quarter | | week including
| | | the 12th of the month
-----------|---------------------|----------------------|------------------------
Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam-
file | and publishes each | quarter to longitu- | pling frame and to an-
| new quarter of UI | dinal database and | nually realign sample-
| data | directly summarizes | based estimates to pop-
| | gross job gains and | ulation counts (bench-
| | losses | marking)
-----------|---------------------|----------------------|------------------------
Principal |--Provides a quarter-|--Provides quarterly |--Provides current month-
products | ly and annual uni- | employer dynamics | ly estimates of employ-
| verse count of es- | data on establish- | ment, hours, and earn-
| tablishments, em- | ment openings, clos-| ings at the MSA, state,
| ployment, and wages| ings, expansions, | and national level by
| at the county, MSA,| and contractions at | industry
| state, and national| the national level |
| levels by detailed | by NAICS supersec- |
| industry | tors and by size of |
| | firm, and at the |
| | state private-sector|
| | total level |
| |--Future expansions |
| | will include data |
| | with greater indus- |
| | try detail and data |
| | at the county and |
| | MSA level |
-----------|---------------------|----------------------|------------------------
Principal |--Major uses include:|--Major uses include: |--Major uses include:
uses | -Detailed locality | -Business cycle | -Principal federal
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -Analysis of employ-| cators
| surveys | ment expansion and |
| | contraction by size|
| | of firm |
| | |
-----------|---------------------|----------------------|------------------------
Program |--www.bls.gov/cew |--www.bls.gov/bdm |--www.bls.gov/ces
Web sites | | |
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Coverage
Employment and wage data for workers covered by state UI laws are compiled from quarterly
contribution reports submitted to the SWAs by employers. For federal civilian workers covered by
the Unemployment Compensation for Federal Employees (UCFE) program, employment and
wage data are compiled from quarterly reports submitted by four major federal payroll processing
centers on behalf of all federal agencies, with the exception of a few agencies which still report
directly to the individual SWA. In addition to the quarterly contribution reports, employers who
operate multiple establishments within a state complete a questionnaire, called the "Multiple
Worksite Report," which provides detailed information on the location and industry of each of their
establishments. QCEW employment and wage data are derived from microdata summaries of 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 2018 edition
of this publication, which was published in September 2019, contains selected data produced by
Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the
first quarter 2019 version of this news release. Tables and additional content from the 2018 edition
of Employment and Wages Annual Averages Online are now available at
www.bls.gov/cew/publications/employment-and-wages-annual-averages/2018/home.htm. The
2019 edition of Employment and Wages Annual Averages Online will be available in September
2020.
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,
first quarter 2020
Employment Average weekly wage(2)
Establishments,
County(1) first quarter Percent Ranking Percent Ranking
2020 March change, by First change, by
(thousands) 2020 March percent quarter first percent
(thousands) 2019-20(3) change 2020 quarter change
2019-20(3)
United States(4)......... 10,447.2 147,088.9 0.4 - $1,222 3.3 -
Baldwin, AL.............. 6.7 76.1 0.0 203 737 2.9 187
Jefferson, AL............ 19.6 351.3 -0.2 231 1,177 1.2 301
Madison, AL.............. 10.2 208.6 2.8 10 1,267 5.1 30
Mobile, AL............... 10.5 171.6 0.2 182 941 3.0 176
Montgomery, AL........... 6.5 130.3 -0.3 240 917 4.3 72
Shelby, AL............... 6.0 84.0 -0.6 263 1,147 1.5 287
Tuscaloosa, AL........... 4.7 97.4 0.9 101 922 2.7 201
Anchorage, AK............ 8.3 144.2 -0.7 272 1,179 1.7 274
Maricopa, AZ............. 109.4 2,094.8 2.5 15 1,158 3.9 109
Pima, AZ................. 19.4 380.1 -0.1 213 992 4.8 38
Benton, AR............... 7.0 126.4 3.0 7 1,509 1.6 285
Pulaski, AR.............. 14.7 247.9 -1.3 317 1,030 3.6 128
Washington, AR........... 6.5 111.4 1.4 60 898 3.3 158
Alameda, CA.............. 66.9 792.6 0.3 166 1,619 4.4 62
Butte, CA................ 8.6 81.2 0.6 133 868 2.4 230
Contra Costa, CA......... 34.6 368.3 -0.6 263 1,462 3.6 128
Fresno, CA............... 38.6 392.9 1.3 68 879 4.3 72
Kern, CA................. 21.9 314.8 0.3 166 968 3.5 142
Los Angeles, CA.......... 519.4 4,496.6 0.2 182 1,334 4.2 76
Marin, CA................ 12.8 114.2 0.6 133 1,566 1.4 291
Merced, CA............... 7.0 78.7 0.9 101 861 4.7 42
Monterey, CA............. 14.4 179.2 0.3 166 977 3.5 142
Napa, CA................. 6.0 77.3 -0.6 263 1,122 4.2 76
Orange, CA............... 129.7 1,633.7 -0.1 213 1,335 3.4 150
Placer, CA............... 14.1 174.8 1.9 35 1,157 5.4 26
Riverside, CA............ 71.3 770.6 1.6 51 935 1.0 307
Sacramento, CA........... 63.2 689.5 1.5 54 1,264 4.9 34
San Bernardino, CA....... 64.9 785.5 2.5 15 965 3.7 121
San Diego, CA............ 118.4 1,486.2 0.7 122 1,315 5.6 21
San Francisco, CA........ 62.1 759.1 1.0 91 2,772 0.8 312
San Joaquin, CA.......... 19.0 258.7 2.3 20 942 3.2 165
San Luis Obispo, CA...... 10.8 118.5 -0.7 272 974 -0.7 346
San Mateo, CA............ 29.4 417.4 2.1 31 2,913 9.5 4
Santa Barbara, CA........ 16.0 209.0 2.2 25 1,068 3.4 150
Santa Clara, CA.......... 76.2 1,121.3 0.9 101 2,896 5.1 30
Santa Cruz, CA........... 9.8 101.3 -0.5 257 1,104 8.6 5
Solano, CA............... 12.0 142.4 0.5 146 1,279 2.5 224
Sonoma, CA............... 20.5 209.8 0.4 158 1,137 6.0 16
Stanislaus, CA........... 16.5 192.7 1.2 69 974 3.3 158
Tulare, CA............... 11.7 160.3 2.3 20 823 3.4 150
Ventura, CA.............. 28.4 331.4 0.5 146 1,195 3.6 128
Yolo, CA................. 7.2 106.0 0.5 146 1,175 0.3 327
Adams, CO................ 12.0 225.2 3.3 5 1,123 4.4 62
Arapahoe, CO............. 23.2 331.2 0.8 110 1,501 4.0 98
Boulder, CO.............. 16.3 187.8 1.4 60 1,457 3.7 121
Denver, CO............... 35.7 527.6 1.2 69 1,619 5.5 23
Douglas, CO.............. 13.1 130.3 2.6 12 1,433 5.7 19
El Paso, CO.............. 21.4 283.6 1.5 54 1,040 1.2 301
Jefferson, CO............ 21.5 241.3 0.9 101 1,254 1.8 267
Larimer, CO.............. 13.0 163.9 1.0 91 1,080 1.7 274
Weld, CO................. 8.1 113.0 0.3 166 1,166 8.1 6
Fairfield, CT............ 37.0 405.9 -1.4 324 2,072 0.0 336
Hartford, CT............. 29.5 506.9 -0.2 231 1,521 2.5 224
New Haven, CT............ 25.4 364.6 0.1 192 1,146 1.8 267
New London, CT........... 7.8 118.7 -2.0 345 1,226 3.0 176
New Castle, DE........... 21.4 289.1 -0.3 240 1,431 1.1 306
Sussex, DE............... 7.6 80.0 0.6 133 839 4.9 34
Washington, DC........... 42.3 778.0 0.6 133 1,994 3.8 114
Alachua, FL.............. 7.6 134.1 0.0 203 986 4.4 62
Brevard, FL.............. 16.7 223.4 1.7 45 1,034 6.4 10
Broward, FL.............. 73.4 822.4 0.3 166 1,117 2.7 201
Collier, FL.............. 15.5 157.0 0.3 166 997 4.6 51
Duval, FL................ 31.4 525.4 0.7 122 1,153 2.3 241
Escambia, FL............. 8.6 141.8 2.1 31 927 2.4 230
Hillsborough, FL......... 46.8 722.8 2.4 19 1,170 3.1 174
Lake, FL................. 9.0 104.3 1.6 51 752 4.0 98
Lee, FL.................. 24.0 275.7 0.7 122 912 4.1 87
Leon, FL................. 9.2 153.0 -0.1 213 896 2.3 241
Manatee, FL.............. 12.0 134.4 1.5 54 870 4.1 87
Marion, FL............... 8.9 107.7 1.0 91 754 2.7 201
Miami-Dade, FL........... 104.9 1,167.5 0.0 203 1,158 2.8 195
Okaloosa, FL............. 6.8 86.5 0.6 133 941 5.7 19
Orange, FL............... 46.5 871.9 0.4 158 1,040 3.6 128
Osceola, FL.............. 7.9 101.9 1.9 35 750 3.2 165
Palm Beach, FL........... 60.3 621.0 0.1 192 1,172 4.6 51
Pasco, FL................ 11.9 124.1 1.1 79 793 4.1 87
Pinellas, FL............. 35.3 441.9 0.0 203 997 3.5 142
Polk, FL................. 14.6 234.5 2.3 20 873 3.9 109
St. Johns, FL............ 8.2 81.9 3.7 1 942 4.2 76
St. Lucie, FL............ 7.2 81.8 1.8 41 823 6.1 15
Sarasota, FL............. 17.0 173.7 -1.0 291 953 4.7 42
Seminole, FL............. 16.0 200.8 -0.1 213 1,006 3.5 142
Volusia, FL.............. 15.4 176.6 -0.8 281 817 4.2 76
Bibb, GA................. 4.4 82.9 -0.1 213 892 2.2 250
Chatham, GA.............. 8.6 161.9 1.1 79 946 1.2 301
Clayton, GA.............. 4.2 121.7 -0.8 281 1,365 2.9 187
Cobb, GA................. 23.0 373.1 1.1 79 1,266 1.4 291
DeKalb, GA............... 18.7 302.6 0.2 182 1,233 3.6 128
Forsyth, GA.............. 6.3 77.2 0.5 146 994 4.1 87
Fulton, GA............... 46.2 900.9 0.8 110 1,793 4.5 56
Gwinnett, GA............. 26.6 362.2 1.2 69 1,096 1.4 291
Hall, GA................. 4.8 90.8 1.4 60 946 6.8 9
Muscogee, GA............. 4.6 94.8 -0.5 257 954 0.5 323
Richmond, GA............. 4.6 105.5 0.8 110 934 2.2 250
Honolulu, HI............. 27.5 467.1 -1.1 300 1,083 2.9 187
Maui + Kalawao, HI....... 6.8 80.2 -1.2 308 927 3.2 165
Ada, ID.................. 17.3 256.9 3.3 5 1,012 4.3 72
Champaign, IL............ 4.1 91.3 0.7 122 964 4.2 76
Cook, IL................. 139.6 2,560.7 -0.6 263 1,504 2.7 201
DuPage, IL............... 34.8 604.1 -1.4 324 1,366 2.0 259
Kane, IL................. 12.7 205.6 -1.9 340 970 2.6 214
Lake, IL................. 20.3 329.5 -1.3 317 1,767 2.7 201
McHenry, IL.............. 7.9 93.8 -1.7 335 867 2.7 201
McLean, IL............... 3.3 80.9 0.3 166 1,261 13.3 1
Madison, IL.............. 5.4 102.1 -0.4 251 863 0.3 327
Peoria, IL............... 4.2 102.3 -1.7 335 1,317 -12.8 357
St. Clair, IL............ 5.0 90.3 -1.3 317 866 3.0 176
Sangamon, IL............. 4.8 127.0 -0.8 281 1,110 4.7 42
Will, IL................. 15.2 245.0 1.1 79 936 -1.1 349
Winnebago, IL............ 5.9 122.2 -1.8 338 945 2.3 241
Allen, IN................ 9.2 188.2 -0.8 281 974 3.9 109
Elkhart, IN.............. 4.8 130.1 -3.4 355 976 3.8 114
Hamilton, IN............. 10.0 143.2 0.6 133 1,167 3.8 114
Lake, IN................. 10.6 183.5 -1.9 340 952 0.7 319
Marion, IN............... 24.9 592.5 -1.1 300 1,278 3.9 109
St. Joseph, IN........... 5.9 122.2 -1.5 329 896 3.6 128
Tippecanoe, IN........... 3.8 85.2 -1.5 329 984 2.2 250
Vanderburgh, IN.......... 4.8 106.4 -2.2 350 916 -4.9 356
Johnson, IA.............. 4.5 82.7 -0.2 231 1,030 3.3 158
Linn, IA................. 7.1 129.2 -0.6 263 1,128 4.3 72
Polk, IA................. 18.4 298.3 0.5 146 1,232 4.0 98
Scott, IA................ 5.8 88.5 -0.9 287 922 2.8 195
Johnson, KS.............. 24.3 349.8 1.2 69 1,204 3.0 176
Sedgwick, KS............. 12.9 257.0 0.8 110 1,013 1.4 291
Shawnee, KS.............. 5.1 95.4 0.4 158 947 4.5 56
Wyandotte, KS............ 3.5 90.3 0.4 158 1,078 3.8 114
Boone, KY................ 4.5 96.5 2.3 20 949 3.4 150
Fayette, KY.............. 11.5 193.1 0.7 122 989 3.6 128
Jefferson, KY............ 26.0 465.6 0.2 182 1,172 2.6 214
Caddo, LA................ 7.4 108.9 -1.9 340 879 2.3 241
Calcasieu, LA............ 5.5 97.0 -5.4 356 1,007 -1.1 349
East Baton Rouge, LA..... 16.6 261.6 -2.7 354 1,074 2.6 214
Jefferson, LA............ 14.6 188.3 -0.6 263 987 3.1 174
Lafayette, LA............ 10.3 130.7 -0.3 240 929 1.9 263
Orleans, LA.............. 13.9 197.0 -0.9 287 1,078 1.4 291
St. Tammany, LA.......... 9.0 89.7 0.7 122 935 2.4 230
Cumberland, ME........... 13.9 181.9 -0.3 240 1,133 4.4 62
Anne Arundel, MD......... 15.5 272.1 -0.3 240 1,237 3.6 128
Baltimore, MD............ 21.3 374.2 -1.4 324 1,165 4.0 98
Frederick, MD............ 6.6 103.4 -1.2 308 1,071 4.7 42
Harford, MD.............. 5.9 92.9 -1.3 317 1,089 4.8 38
Howard, MD............... 10.2 173.1 -0.1 213 1,456 4.4 62
Montgomery, MD........... 33.0 466.7 -0.7 272 1,653 4.5 56
Prince George's, MD...... 16.4 317.4 -1.3 317 1,156 4.2 76
Baltimore City, MD....... 13.9 344.6 0.8 110 1,353 2.6 214
Barnstable, MA........... 9.7 85.9 -1.0 291 993 2.9 187
Bristol, MA.............. 17.9 225.3 -0.4 251 1,014 1.7 274
Essex, MA................ 27.6 319.5 -1.1 300 1,244 1.5 287
Hampden, MA.............. 18.8 208.1 -1.2 308 1,027 1.6 285
Middlesex, MA............ 57.0 929.1 0.4 158 1,925 2.0 259
Norfolk, MA.............. 25.7 344.0 -1.4 324 1,360 2.6 214
Plymouth, MA............. 16.5 189.9 -1.2 308 1,075 1.7 274
Suffolk, MA.............. 32.2 700.9 0.8 110 2,351 4.1 87
Worcester, MA............ 26.6 349.4 -0.1 213 1,157 3.4 150
Genesee, MI.............. 7.3 131.7 0.3 166 921 4.7 42
Ingham, MI............... 6.6 152.4 -0.5 257 1,074 2.8 195
Kalamazoo, MI............ 5.5 121.7 -0.2 231 1,085 0.3 327
Kent, MI................. 16.2 408.9 -0.5 257 999 2.3 241
Macomb, MI............... 19.1 325.5 -1.2 308 1,112 -0.4 341
Oakland, MI.............. 43.0 733.3 -1.0 291 1,279 2.3 241
Ottawa, MI............... 6.3 127.2 0.8 110 955 3.2 165
Saginaw, MI.............. 4.0 81.5 -2.0 345 915 1.8 267
Washtenaw, MI............ 9.2 219.7 0.0 203 1,208 3.2 165
Wayne, MI................ 35.6 722.5 -0.7 272 1,281 1.8 267
Anoka, MN................ 7.9 125.7 -0.1 213 1,036 4.6 51
Dakota, MN............... 10.9 185.8 -0.8 281 1,193 2.5 224
Hennepin, MN............. 41.7 924.1 -0.1 213 1,583 2.7 201
Olmsted, MN.............. 3.8 100.5 1.6 51 1,243 2.6 214
Ramsey, MN............... 14.4 328.5 -0.6 263 1,354 -0.5 343
St. Louis, MN............ 5.5 95.6 -1.3 317 935 2.4 230
Stearns, MN.............. 4.4 85.2 -0.9 287 987 6.4 10
Washington, MN........... 6.2 86.7 0.7 122 966 1.5 287
Harrison, MS............. 4.6 86.6 1.2 69 761 1.3 298
Hinds, MS................ 5.6 118.1 -1.1 300 955 3.7 121
Boone, MO................ 5.0 94.6 0.1 192 909 6.4 10
Clay, MO................. 6.0 105.0 1.4 60 1,000 4.1 87
Greene, MO............... 9.5 169.8 0.3 166 859 1.4 291
Jackson, MO.............. 23.1 372.1 0.2 182 1,155 4.0 98
St. Charles, MO.......... 10.1 153.8 2.2 25 993 -0.1 338
St. Louis, MO............ 41.4 602.0 -0.3 240 1,263 1.7 274
St. Louis City, MO....... 15.5 226.3 -0.7 272 1,315 2.3 241
Yellowstone, MT.......... 6.6 81.7 1.7 45 953 0.3 327
Douglas, NE.............. 19.1 338.7 0.9 101 1,101 4.1 87
Lancaster, NE............ 10.1 171.2 0.5 146 919 3.0 176
Clark, NV................ 58.2 1,028.6 1.1 79 1,018 4.1 87
Washoe, NV............... 15.3 224.4 1.0 91 1,027 4.2 76
Hillsborough, NH......... 12.4 204.0 -0.3 240 1,314 3.6 128
Merrimack, NH............ 5.2 77.1 -0.4 251 1,061 2.4 230
Rockingham, NH........... 11.2 149.1 0.8 110 1,149 0.8 312
Atlantic, NJ............. 6.8 126.2 -0.6 263 940 2.7 201
Bergen, NJ............... 34.0 437.6 0.3 166 1,374 3.2 165
Burlington, NJ........... 11.4 200.6 0.5 146 1,224 3.8 114
Camden, NJ............... 12.6 204.8 0.1 192 1,111 3.3 158
Essex, NJ................ 21.4 344.6 0.2 182 1,578 2.7 201
Gloucester, NJ........... 6.6 114.9 1.9 35 928 2.5 224
Hudson, NJ............... 16.2 272.0 -0.2 231 1,783 2.4 230
Mercer, NJ............... 11.5 259.0 0.6 133 1,681 2.4 230
Middlesex, NJ............ 23.0 423.3 -0.2 231 1,396 3.6 128
Monmouth, NJ............. 20.8 260.4 0.5 146 1,169 2.8 195
Morris, NJ............... 17.5 290.7 -0.1 213 2,091 9.6 3
Ocean, NJ................ 14.0 167.0 0.7 122 897 2.4 230
Passaic, NJ.............. 13.1 165.8 0.9 101 1,070 2.6 214
Somerset, NJ............. 10.5 186.3 -1.0 291 2,172 1.3 298
Union, NJ................ 15.1 228.5 -0.7 272 1,540 10.0 2
Bernalillo, NM........... 20.6 332.7 0.8 110 974 3.7 121
Albany, NY............... 10.5 229.9 -1.2 308 1,187 4.0 98
Bronx, NY................ 19.4 323.2 0.6 133 1,108 1.8 267
Broome, NY............... 4.4 83.6 -1.9 340 927 3.0 176
Dutchess, NY............. 8.5 111.7 -2.1 349 1,086 1.8 267
Erie, NY................. 24.7 465.0 -1.0 291 1,048 3.0 176
Kings, NY................ 67.0 806.8 -0.3 240 975 3.2 165
Monroe, NY............... 19.1 384.7 -1.1 300 1,050 3.3 158
Nassau, NY............... 54.9 618.6 -1.1 300 1,259 3.7 121
New York, NY............. 132.7 2,498.6 0.0 203 3,270 3.5 142
Oneida, NY............... 5.3 104.2 -1.0 291 896 3.3 158
Onondaga, NY............. 12.8 244.1 -0.6 263 1,052 2.5 224
Orange, NY............... 10.8 147.4 -0.4 251 969 4.1 87
Queens, NY............... 54.7 708.5 0.1 192 1,110 0.6 321
Richmond, NY............. 10.2 130.8 1.8 41 1,024 2.3 241
Rockland, NY............. 11.3 127.4 0.3 166 1,092 1.4 291
Saratoga, NY............. 6.1 87.4 0.1 192 1,047 1.7 274
Suffolk, NY.............. 54.2 646.0 -1.7 335 1,196 2.1 256
Westchester, NY.......... 36.6 421.8 -2.0 345 1,683 6.3 13
Buncombe, NC............. 10.3 132.6 -1.2 308 870 2.4 230
Cabarrus, NC............. 5.1 77.8 1.7 45 857 4.0 98
Catawba, NC.............. 4.6 87.9 -0.1 213 851 -0.8 347
Cumberland, NC........... 6.5 120.2 -0.5 257 832 -0.6 345
Durham, NC............... 9.1 219.6 2.2 25 1,564 2.7 201
Forsyth, NC.............. 9.8 191.1 0.5 146 1,129 6.3 13
Guilford, NC............. 15.2 286.0 0.1 192 998 4.2 76
Iredell, NC.............. 5.8 77.5 2.5 15 974 3.2 165
Mecklenburg, NC.......... 41.6 723.4 2.2 25 1,601 5.1 30
New Hanover, NC.......... 9.0 118.0 1.0 91 927 2.2 250
Pitt, NC................. 3.9 76.9 -1.5 329 921 3.0 176
Wake, NC................. 38.6 570.8 1.5 54 1,254 4.7 42
Cass, ND................. 7.5 119.6 1.1 79 1,021 3.5 142
Butler, OH............... 8.1 156.6 0.0 203 1,054 3.5 142
Cuyahoga, OH............. 36.5 717.7 -0.7 272 1,219 4.1 87
Delaware, OH............. 5.8 87.5 -0.1 213 1,289 4.0 98
Franklin, OH............. 34.3 757.0 0.5 146 1,223 3.3 158
Greene, OH............... 3.8 76.5 0.8 110 1,114 5.6 21
Hamilton, OH............. 24.7 514.0 -0.1 213 1,307 1.7 274
Lake, OH................. 6.4 94.8 -0.4 251 940 1.7 274
Lorain, OH............... 6.3 95.6 -1.1 300 872 1.2 301
Lucas, OH................ 10.2 205.0 -0.9 287 1,035 2.8 195
Mahoning, OH............. 5.9 95.4 -1.3 317 783 1.7 274
Montgomery, OH........... 12.1 252.5 -0.3 240 992 4.0 98
Stark, OH................ 8.7 156.0 -1.2 308 846 0.8 312
Summit, OH............... 14.6 263.8 0.0 203 1,022 2.0 259
Warren, OH............... 5.3 96.0 1.9 35 1,102 0.2 333
Cleveland, OK............ 6.1 85.6 3.4 4 785 0.8 312
Oklahoma, OK............. 28.7 459.2 -0.4 251 1,079 -1.7 353
Tulsa, OK................ 23.0 359.4 -0.1 213 1,072 0.3 327
Clackamas, OR............ 15.9 168.1 0.7 122 1,089 5.2 28
Deschutes, OR............ 9.5 85.5 3.5 2 938 5.9 17
Jackson, OR.............. 8.0 90.3 1.4 60 861 5.5 23
Lane, OR................. 13.0 157.4 0.6 133 883 4.7 42
Marion, OR............... 11.7 156.9 0.7 122 946 5.2 28
Multnomah, OR............ 37.1 518.8 0.5 146 1,255 4.8 38
Washington, OR........... 20.8 301.1 -0.1 213 1,524 2.1 256
Allegheny, PA............ 35.7 686.3 -0.7 272 1,310 4.5 56
Berks, PA................ 8.9 174.7 0.6 133 1,026 3.8 114
Bucks, PA................ 20.5 262.2 0.1 192 1,046 1.9 263
Butler, PA............... 5.1 86.7 0.1 192 1,046 1.3 298
Chester, PA.............. 15.9 249.8 0.4 158 1,536 1.9 263
Cumberland, PA........... 6.6 135.0 0.7 122 1,053 2.7 201
Dauphin, PA.............. 7.5 183.7 0.2 182 1,144 3.4 150
Delaware, PA............. 14.2 223.0 -0.5 257 1,252 -0.3 340
Erie, PA................. 6.9 120.2 -1.1 300 849 2.0 259
Lackawanna, PA........... 5.6 95.6 -1.2 308 849 3.5 142
Lancaster, PA............ 13.9 244.2 1.0 91 940 3.2 165
Lehigh, PA............... 8.8 192.0 -0.2 231 1,130 0.9 309
Luzerne, PA.............. 7.5 144.7 0.2 182 880 1.7 274
Montgomery, PA........... 28.1 501.9 0.0 203 1,609 4.4 62
Northampton, PA.......... 6.9 118.6 0.9 101 979 2.7 201
Philadelphia, PA......... 35.3 702.0 0.8 110 1,393 0.9 309
Washington, PA........... 5.6 85.5 -2.2 350 1,302 2.8 195
Westmoreland, PA......... 9.3 130.7 -1.0 291 910 1.0 307
York, PA................. 9.3 178.1 -0.2 231 963 1.9 263
Kent, RI................. 5.7 74.0 -2.0 345 1,013 0.4 325
Providence, RI........... 19.2 285.9 -0.1 213 1,183 3.0 176
Charleston, SC........... 17.4 256.4 -0.1 213 1,010 -0.2 339
Greenville, SC........... 15.8 276.1 0.2 182 973 3.0 176
Horry, SC................ 9.9 129.1 -0.8 281 674 3.7 121
Lexington, SC............ 7.3 121.7 1.9 35 865 1.5 287
Richland, SC............. 10.8 222.2 0.4 158 983 1.7 274
Spartanburg, SC.......... 6.8 149.1 0.3 166 928 0.8 312
York, SC................. 6.7 101.0 2.2 25 996 1.8 267
Minnehaha, SD............ 7.8 127.7 1.1 79 1,014 4.9 34
Davidson, TN............. 25.4 513.2 1.8 41 1,282 4.7 42
Hamilton, TN............. 10.6 206.8 0.4 158 1,031 3.4 150
Knox, TN................. 13.4 241.4 1.0 91 989 3.8 114
Rutherford, TN........... 6.3 134.4 1.5 54 947 0.0 336
Shelby, TN............... 21.6 495.5 -0.3 240 1,117 0.8 312
Williamson, TN........... 10.0 140.6 2.6 12 1,449 3.7 121
Bell, TX................. 5.8 121.6 1.4 60 924 0.4 325
Bexar, TX................ 43.9 874.5 0.5 146 1,063 3.6 128
Brazoria, TX............. 6.2 117.2 1.0 91 1,187 -1.3 351
Brazos, TX............... 4.8 110.0 1.0 91 839 4.5 56
Cameron, TX.............. 6.7 142.9 1.2 69 666 3.6 128
Collin, TX............... 28.6 441.7 2.2 25 1,455 4.4 62
Dallas, TX............... 80.1 1,734.5 2.0 34 1,499 2.4 230
Denton, TX............... 16.8 265.2 1.8 41 1,026 4.2 76
Ector, TX................ 4.3 78.6 -5.5 357 1,249 -0.4 341
El Paso, TX.............. 15.7 313.5 0.8 110 779 2.9 187
Fort Bend, TX............ 14.9 198.7 2.3 20 1,051 1.2 301
Galveston, TX............ 6.4 111.9 1.1 79 1,047 4.8 38
Gregg, TX................ 4.3 75.2 -1.4 324 930 2.2 250
Harris, TX............... 118.9 2,346.4 0.6 133 1,554 0.2 333
Hidalgo, TX.............. 12.8 270.9 2.5 15 682 2.6 214
Jefferson, TX............ 5.9 121.9 -1.5 329 1,146 0.9 309
Lubbock, TX.............. 7.9 141.3 0.9 101 877 3.9 109
McLennan, TX............. 5.5 114.1 1.2 69 927 4.0 98
Midland, TX.............. 6.2 107.2 -2.6 353 1,612 -1.5 352
Montgomery, TX........... 12.7 196.1 1.2 69 1,204 0.8 312
Nueces, TX............... 8.4 161.3 -1.5 329 972 3.6 128
Potter, TX............... 4.0 76.8 0.3 166 900 2.2 250
Smith, TX................ 6.5 105.3 0.3 166 901 2.9 187
Tarrant, TX.............. 46.3 927.1 1.2 69 1,173 2.4 230
Travis, TX............... 44.7 788.0 2.6 12 1,451 5.5 23
Webb, TX................. 5.6 103.5 -0.1 213 723 2.7 201
Williamson, TX........... 12.3 185.8 3.0 7 1,341 7.8 7
Davis, UT................ 9.1 133.2 3.0 7 926 4.6 51
Salt Lake, UT............ 49.3 723.3 1.9 35 1,188 5.0 33
Utah, UT................. 18.3 251.2 1.5 54 993 -3.8 355
Weber, UT................ 6.4 109.4 1.0 91 859 4.1 87
Chittenden, VT........... 7.2 99.4 -2.2 350 1,136 2.6 214
Arlington, VA............ 9.2 185.0 1.1 79 2,018 2.5 224
Chesterfield, VA......... 9.4 136.5 1.4 60 972 4.9 34
Fairfax, VA.............. 36.9 619.0 1.1 79 1,914 4.4 62
Henrico, VA.............. 11.9 192.0 0.2 182 1,184 4.4 62
Loudoun, VA.............. 12.9 174.3 1.4 60 1,361 2.3 241
Prince William, VA....... 9.7 132.3 0.3 166 981 5.4 26
Alexandria City, VA...... 6.2 88.1 -1.8 338 1,507 0.7 319
Chesapeake City, VA...... 6.3 104.0 1.7 45 895 4.4 62
Newport News City, VA.... 4.0 104.2 0.6 133 1,062 -0.8 347
Norfolk City, VA......... 6.1 140.0 -1.5 329 1,117 3.4 150
Richmond City, VA........ 8.0 157.5 -0.7 272 1,359 4.5 56
Virginia Beach City, VA.. 12.4 175.3 -0.3 240 869 4.2 76
Benton, WA............... 6.2 90.8 2.7 11 1,141 4.2 76
Clark, WA................ 15.8 164.1 1.1 79 1,108 5.9 17
King, WA................. 91.1 1,433.5 1.7 45 1,925 4.6 51
Kitsap, WA............... 7.1 91.8 0.9 101 1,057 6.9 8
Pierce, WA............... 23.9 318.6 1.7 45 1,066 3.6 128
Snohomish, WA............ 22.2 293.1 1.2 69 1,264 -3.4 354
Spokane, WA.............. 17.0 229.9 2.1 31 989 2.9 187
Thurston, WA............. 8.9 118.3 0.6 133 1,070 4.0 98
Whatcom, WA.............. 7.6 92.1 0.3 166 987 2.9 187
Yakima, WA............... 8.2 111.3 3.5 2 810 4.7 42
Kanawha, WV.............. 5.6 94.9 -1.9 340 979 2.1 256
Brown, WI................ 7.2 156.1 0.0 203 1,029 0.6 321
Dane, WI................. 16.2 342.8 1.1 79 1,185 -0.5 343
Milwaukee, WI............ 27.2 480.6 -1.0 291 1,131 3.0 176
Outagamie, WI............ 5.6 107.4 0.1 192 951 0.5 323
Racine, WI............... 4.7 73.4 -1.0 291 971 2.6 214
Waukesha, WI............. 13.7 241.1 -0.2 231 1,169 0.1 335
Winnebago, WI............ 3.9 92.1 0.1 192 1,057 0.3 327
San Juan, PR............. 11.3 243.5 1.3 (5) 671 -0.3 (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 73.7 percent of
the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,
first quarter 2020
Employment Average weekly
wage(1)
Establishments,
first quarter
County by NAICS supersector 2020 Percent Percent
(thousands) March change, First change,
2020 March quarter first
(thousands) 2019-20(2) 2020 quarter
2019-20(2)
United States(3) ............................ 10,447.2 147,088.9 0.4 $1,222 3.3
Private industry........................... 10,145.2 124,839.4 0.3 1,237 3.3
Natural resources and mining............. 140.4 1,766.7 -2.3 1,341 0.3
Construction............................. 843.8 7,272.0 1.6 1,235 3.5
Manufacturing............................ 358.7 12,653.3 -1.0 1,436 1.3
Trade, transportation, and utilities..... 1,950.2 27,192.9 0.4 999 2.8
Information.............................. 193.0 2,883.2 0.8 2,655 5.8
Financial activities..................... 933.2 8,328.5 1.3 2,539 4.6
Professional and business services....... 1,946.4 21,001.1 0.8 1,648 3.4
Education and health services............ 1,802.7 23,349.0 1.1 995 3.2
Leisure and hospitality.................. 894.7 15,714.1 -2.3 477 3.5
Other services........................... 872.7 4,485.7 -0.2 786 3.6
Government................................. 302.0 22,249.6 0.8 1,136 2.7
Los Angeles, CA.............................. 519.4 4,496.6 0.2 1,334 4.2
Private industry........................... 513.1 3,909.7 0.1 1,309 4.2
Natural resources and mining............. 0.5 5.8 5.9 1,146 -3.1
Construction............................. 17.3 148.6 1.1 1,350 4.0
Manufacturing............................ 12.7 336.3 -1.3 1,508 3.5
Trade, transportation, and utilities..... 59.6 825.9 -0.6 1,093 4.5
Information.............................. 13.6 218.4 2.7 2,738 1.1
Financial activities..................... 30.9 221.1 0.8 2,546 5.1
Professional and business services....... 57.5 627.4 -1.3 1,649 5.6
Education and health services............ 249.1 843.2 2.6 947 4.0
Leisure and hospitality.................. 40.5 528.4 -2.2 707 4.1
Other services........................... 29.7 152.6 0.7 796 3.5
Government................................. 6.3 586.9 0.4 1,506 4.5
Cook, IL..................................... 139.6 2,560.7 -0.6 1,504 2.7
Private industry........................... 138.4 2,262.7 -0.9 1,532 2.7
Natural resources and mining............. 0.1 1.5 18.0 1,210 6.9
Construction............................. 11.2 68.5 -2.9 1,549 1.8
Manufacturing............................ 5.7 183.4 -1.0 1,421 1.5
Trade, transportation, and utilities..... 28.5 461.6 -0.8 1,150 0.3
Information.............................. 2.6 52.7 -0.8 2,601 5.1
Financial activities..................... 14.1 206.1 1.6 4,178 2.9
Professional and business services....... 29.3 467.5 -1.1 1,826 2.4
Education and health services............ 15.6 454.9 0.5 1,043 3.3
Leisure and hospitality.................. 14.0 268.9 -4.3 551 2.2
Other services........................... 16.4 97.1 -1.9 1,028 4.6
Government................................. 1.3 298.0 1.6 1,288 2.5
New York, NY................................. 132.7 2,498.6 0.0 3,270 3.5
Private industry........................... 131.2 2,263.3 0.0 3,445 3.6
Natural resources and mining............. 0.0 0.2 25.0 2,757 2.9
Construction............................. 2.4 42.3 -1.9 2,076 2.9
Manufacturing............................ 1.8 20.6 -5.2 1,693 0.8
Trade, transportation, and utilities..... 18.6 249.3 -1.3 1,668 4.2
Information.............................. 5.7 195.9 2.6 3,811 6.2
Financial activities..................... 19.7 391.1 0.9 9,752 3.1
Professional and business services....... 29.1 588.9 1.0 2,993 2.9
Education and health services............ 10.4 374.1 1.3 1,412 4.1
Leisure and hospitality.................. 14.8 289.8 -5.3 964 -0.3
Other services........................... 20.3 105.5 -1.2 1,400 4.6
Government................................. 1.5 235.3 0.0 1,574 1.1
Harris, TX................................... 118.9 2,346.4 0.6 1,554 0.2
Private industry........................... 118.4 2,059.9 0.4 1,604 -0.1
Natural resources and mining............. 1.6 65.0 -4.7 5,302 1.4
Construction............................. 7.8 170.2 0.0 1,539 3.4
Manufacturing............................ 5.0 176.4 -1.5 1,864 -3.1
Trade, transportation, and utilities..... 25.2 465.9 -0.3 1,442 -0.1
Information.............................. 1.3 25.7 -1.1 1,780 2.1
Financial activities..................... 12.8 130.6 2.2 2,462 -0.1
Professional and business services....... 24.0 413.1 2.1 1,989 -1.4
Education and health services............ 16.9 303.9 1.2 1,083 3.8
Leisure and hospitality.................. 10.7 236.3 -1.8 479 2.4
Other services........................... 11.9 70.0 2.4 903 5.1
Government................................. 0.6 286.5 2.4 1,191 3.2
Maricopa, AZ................................. 109.4 2,094.8 2.5 1,158 3.9
Private industry........................... 108.6 1,875.9 2.6 1,164 3.9
Natural resources and mining............. 0.5 8.1 3.5 1,376 0.8
Construction............................. 8.7 132.8 4.6 1,233 5.2
Manufacturing............................ 3.6 131.7 2.6 1,651 0.1
Trade, transportation, and utilities..... 21.3 396.9 2.7 1,042 3.6
Information.............................. 2.4 38.6 -0.1 1,849 8.6
Financial activities..................... 14.4 193.5 4.4 1,798 7.6
Professional and business services....... 27.3 353.0 2.5 1,232 1.7
Education and health services............ 13.8 337.5 4.0 1,055 2.8
Leisure and hospitality.................. 9.4 230.0 -1.2 543 5.6
Other services........................... 7.1 53.5 1.0 796 2.6
Government................................. 0.7 218.9 1.4 1,112 4.9
Dallas, TX................................... 80.1 1,734.5 2.0 1,499 2.4
Private industry........................... 79.6 1,555.6 2.0 1,530 2.3
Natural resources and mining............. 0.5 8.6 2.1 4,216 -0.8
Construction............................. 4.9 92.7 2.2 1,425 3.0
Manufacturing............................ 2.9 118.3 1.9 1,960 2.3
Trade, transportation, and utilities..... 16.1 352.3 2.0 1,247 1.9
Information.............................. 1.5 46.5 0.0 2,832 2.4
Financial activities..................... 10.0 161.7 2.6 2,543 2.5
Professional and business services....... 18.2 364.6 3.1 1,705 0.8
Education and health services............ 10.0 204.8 1.8 1,197 5.1
Leisure and hospitality.................. 7.3 161.9 -0.3 549 4.6
Other services........................... 7.2 42.5 -1.5 978 2.7
Government................................. 0.5 178.9 2.3 1,235 4.2
Orange, CA................................... 129.7 1,633.7 -0.1 1,335 3.4
Private industry........................... 128.3 1,474.3 -0.3 1,319 3.5
Natural resources and mining............. 0.2 2.3 -1.6 928 -0.9
Construction............................. 7.9 103.1 -1.1 1,500 4.2
Manufacturing............................ 5.3 157.0 -1.5 1,723 -3.7
Trade, transportation, and utilities..... 18.6 252.2 -0.9 1,160 4.3
Information.............................. 1.6 25.6 -2.4 2,572 0.5
Financial activities..................... 13.3 117.0 1.6 2,378 6.7
Professional and business services....... 24.0 314.2 -1.5 1,570 7.7
Education and health services............ 39.0 233.0 2.8 1,003 2.1
Leisure and hospitality.................. 10.0 220.2 -1.8 538 4.5
Other services........................... 7.9 49.2 4.3 746 -1.6
Government................................. 1.4 159.4 1.3 1,484 2.8
San Diego, CA................................ 118.4 1,486.2 0.7 1,315 5.6
Private industry........................... 116.4 1,243.8 0.7 1,305 5.8
Natural resources and mining............. 0.7 9.9 5.3 782 2.4
Construction............................. 8.1 81.7 0.3 1,345 5.1
Manufacturing............................ 3.6 118.0 1.2 2,029 2.3
Trade, transportation, and utilities..... 15.5 218.1 -0.6 1,019 6.7
Information.............................. 1.4 23.3 -0.8 2,074 4.3
Financial activities..................... 11.5 76.5 1.9 1,923 7.6
Professional and business services....... 21.5 254.5 1.9 1,930 8.4
Education and health services............ 36.0 216.2 2.8 1,016 3.4
Leisure and hospitality.................. 9.4 192.2 -2.6 536 2.5
Other services........................... 8.3 52.2 -0.3 670 3.4
Government................................. 2.0 242.4 0.6 1,368 4.5
King, WA..................................... 91.1 1,433.5 1.7 1,925 4.6
Private industry........................... 90.4 1,257.0 1.6 1,980 4.6
Natural resources and mining............. 0.4 2.9 2.4 1,214 0.4
Construction............................. 7.0 75.1 1.9 1,568 5.8
Manufacturing............................ 2.5 101.8 -4.0 1,894 -13.5
Trade, transportation, and utilities..... 13.7 279.1 3.3 1,864 4.1
Information.............................. 2.7 126.3 7.9 5,194 8.3
Financial activities..................... 7.2 69.9 1.8 2,425 5.2
Professional and business services....... 19.0 238.2 3.0 2,113 4.0
Education and health services............ 21.1 180.4 0.7 1,116 2.5
Leisure and hospitality.................. 7.6 135.4 -4.0 617 4.6
Other services........................... 9.3 47.9 1.0 1,000 7.1
Government................................. 0.6 176.5 2.6 1,534 4.1
Miami-Dade, FL............................... 104.9 1,167.5 0.0 1,158 2.8
Private industry........................... 104.5 1,026.4 -0.1 1,137 2.9
Natural resources and mining............. 0.5 10.2 -2.3 655 3.6
Construction............................. 7.4 52.7 0.1 1,082 5.4
Manufacturing............................ 2.8 41.3 0.4 998 -10.4
Trade, transportation, and utilities..... 24.4 287.3 -0.7 1,065 4.2
Information.............................. 1.6 18.8 -1.4 2,051 3.2
Financial activities..................... 11.2 76.7 0.0 2,285 5.9
Professional and business services....... 24.0 166.4 1.4 1,345 0.6
Education and health services............ 11.6 188.6 1.4 1,035 3.0
Leisure and hospitality.................. 7.7 142.4 -3.4 667 5.5
Other services........................... 9.0 38.7 -1.6 699 -4.0
Government................................. 0.3 141.1 0.2 1,310 2.5
(1) Average weekly wages were calculated using unrounded data.
(2) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic
county reclassifications. See Technical Note.
(3) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
Note: Data are preliminary. Counties selected are based on 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,
first quarter 2020
Employment Average weekly
wage(1)
Establishments,
first quarter
State 2020 Percent Percent
(thousands) March change, First change,
2020 March quarter first
(thousands) 2019-20 2020 quarter
2019-20
United States(2)........... 10,447.2 147,088.9 0.4 $1,222 3.3
Alabama.................... 132.6 1,983.8 0.3 974 3.2
Alaska..................... 22.6 312.8 -0.1 1,130 2.1
Arizona.................... 170.4 2,957.2 1.9 1,098 4.4
Arkansas................... 93.6 1,220.5 0.2 922 3.0
California................. 1,631.1 17,570.5 0.8 1,459 4.2
Colorado................... 214.5 2,725.2 1.2 1,284 4.3
Connecticut................ 124.1 1,639.4 -0.7 1,510 1.5
Delaware................... 34.6 443.7 -0.3 1,251 1.7
District of Columbia....... 42.3 778.1 0.6 1,994 3.8
Florida.................... 740.5 8,975.1 0.8 1,051 3.6
Georgia.................... 301.5 4,522.2 0.9 1,159 3.4
Hawaii..................... 45.4 655.5 -1.0 1,033 3.0
Idaho...................... 66.8 755.2 3.1 864 4.2
Illinois................... 381.5 5,872.9 -0.7 1,302 2.3
Indiana.................... 171.1 3,028.5 -1.0 994 3.2
Iowa....................... 104.8 1,523.4 -0.2 978 3.7
Kansas..................... 89.8 1,383.3 0.2 969 3.2
Kentucky................... 124.0 1,884.9 0.1 943 2.5
Louisiana.................. 137.4 1,897.0 -1.3 969 1.7
Maine...................... 53.9 601.0 0.1 955 4.0
Maryland................... 175.7 2,661.5 -0.4 1,277 4.1
Massachusetts.............. 263.3 3,565.1 -0.2 1,605 3.0
Michigan................... 267.0 4,281.4 -0.6 1,103 2.3
Minnesota.................. 183.9 2,838.2 -0.1 1,235 2.7
Mississippi................ 73.9 1,128.1 -0.2 801 2.8
Missouri................... 214.8 2,795.7 0.3 1,016 3.0
Montana.................... 50.6 465.2 1.5 869 3.1
Nebraska................... 72.3 972.4 0.8 956 4.1
Nevada..................... 86.1 1,410.8 1.3 1,033 4.2
New Hampshire.............. 54.3 657.0 0.2 1,194 3.3
New Jersey................. 285.8 4,052.7 0.4 1,455 3.9
New Mexico................. 64.0 835.6 0.9 923 3.7
New York................... 657.2 9,415.7 -0.3 1,693 3.3
North Carolina............. 296.0 4,501.1 0.9 1,094 4.1
North Dakota............... 32.2 414.3 0.0 1,046 2.4
Ohio....................... 304.4 5,349.6 -0.3 1,063 2.9
Oklahoma................... 112.8 1,598.0 -1.3 949 -0.5
Oregon..................... 162.4 1,938.9 0.7 1,103 4.2
Pennsylvania............... 363.5 5,851.3 0.0 1,177 2.7
Rhode Island............... 39.5 473.9 -0.2 1,132 2.7
South Carolina............. 142.7 2,112.8 0.1 922 2.2
South Dakota............... 34.7 420.6 0.4 901 4.2
Tennessee.................. 171.2 3,033.5 1.0 1,027 3.1
Texas...................... 725.7 12,626.2 1.2 1,232 2.4
Utah....................... 109.8 1,526.8 1.8 1,026 3.2
Vermont.................... 26.1 303.9 -1.8 980 3.3
Virginia................... 282.9 3,921.0 0.6 1,233 4.0
Washington................. 255.6 3,427.3 1.7 1,414 3.8
West Virginia.............. 51.2 674.9 -1.8 904 0.9
Wisconsin.................. 178.2 2,836.5 -0.2 1,008 1.7
Wyoming.................... 27.2 268.5 -0.5 955 0.6
Puerto Rico................ 47.5 886.4 1.0 551 0.0
Virgin Islands............. 3.3 40.1 5.7 1,046 6.3
(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
