For release 10:00 a.m. (EST), Wednesday, November 20, 2019 USDL-19-2050
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 2019
From June 2018 to June 2019, employment increased in 279 of the 355 largest U.S. counties, the
U.S. Bureau of Labor Statistics reported today. In June 2019, national employment (as measured
by the QCEW program) increased to 149.1 million, a 1.1 percent increase over the year. Adams,
CO, had the largest over-the-year increase in employment with a gain of 5.3 percent.
Employment data in this release are presented for June 2019, and average weekly wage data are
presented for second quarter 2019.
Among the 355 largest counties, 347 had over-the-year increases in average weekly wages. In
the second quarter of 2019, average weekly wages for the nation increased to $1,095, a 3.8
percent increase over the year. Benton, AR, had the largest second quarter over-the-year wage
gain at 16.3 percent. (See table 1.)
Large County Employment in June 2019
Adams, CO, had the largest over-the-year percentage increase in employment (5.3 percent).
Within Adams, the largest employment increase occurred in trade, transportation, and utilities,
which gained 3,592 jobs over the year (6.4 percent).
Bay, FL, experienced the largest over-the-year percentage decrease in employment, with a loss
of 6.4 percent. Within Bay, leisure and hospitality had the largest employment decrease with a
loss of 2,572 jobs (-15.5 percent).
Large County Average Weekly Wage in Second Quarter 2019
Benton, AR, had the largest over-the-year percentage increase in average weekly wages (16.3
percent). Within Benton, an average weekly wage gain of $557 (35.0 percent) in professional
and business services made the largest contribution to the county’s increase in average weekly
wages.
McLean, IL, had the largest over-the-year percentage decrease in average weekly wages with a
loss of 5.8 percent. Within McLean, financial activities had the largest impact, with an average
weekly wage decrease of $321 (-17.8 percent) over the year.
Ten Largest Counties
All of the 10 largest counties had over-the-year percentage increases in employment and average
weekly wages. In June 2019, Maricopa, AZ, had the largest over-the-year employment
percentage gain among the 10 largest counties (3.1 percent). Within Maricopa, education and
health services had the largest employment increase with a gain of 12,096 jobs (4.0 percent).
(See table 2.)
In second quarter 2019, King, WA, experienced the largest over-the-year percentage gain in
average weekly wages among the 10 largest counties (6.6 percent). Within King, information had
the largest impact, with an average weekly wage increase of $378 (11.1 percent) over the year.
For More Information
The tables included in this release contain data for the nation and for the 355 U.S. counties with
annual average employment levels of 75,000 or more in 2018. June 2019 employment and
second quarter 2019 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.
QCEW’s news release schedule is available at www.bls.gov/cew/release-calendar.htm.
____________
The County Employment and Wages full data update for second quarter 2019 is scheduled
to be released on Wednesday, December 4, 2019, at 10:00 a.m. (EST).
The County Employment and Wages news release for third quarter 2019 is scheduled to be
released on Thursday, February 20, 2020, at 10:00 a.m. (EST).
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 2019 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 356 counties presented in
this release were derived using 2018 preliminary annual averages of employment. For 2019 data,
six counties have been added to the publication tables: St. Johns, FL; St. Lucie, FL; Forsyth, GA;
Greene, OH; Ector, TX; and Racine, WI. These counties will be included in all 2019 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- | 689,000 establish-
| submitted by 10.2 | ministrative records| ments
| million establish- | submitted by 8.0 |
| ments in first | million private-sec-|
| quarter of 2019 | 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 | | |
---------------------------------------------------------------------------------
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 10.0
million employer reports of employment and wages submitted by states to the BLS in 2018. 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 2018, UI and UCFE programs
covered workers in 146.1 million jobs. The estimated 140.5 million workers in these jobs (after
adjustment for multiple jobholders) represented 96.2 percent of civilian wage and salary
employment. Covered workers received $8.368 trillion in pay, representing 94.2 percent of the
wage and salary component of personal income and 40.7 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 2018 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 356 largest counties,
second quarter 2019
Employment Average weekly wage(2)
Establishments,
County(1) second quarter Percent Ranking Percent Ranking
2019 June change, by Second change, by
(thousands) 2019 June percent quarter second percent
(thousands) 2018-19(3) change 2019 quarter change
2018-19(3)
United States(4)......... 10,252.0 149,089.2 1.1 - $1,095 3.8 -
Jefferson, AL............ 19.2 354.6 0.8 184 1,062 2.6 258
Madison, AL.............. 10.0 205.9 2.3 54 1,153 4.7 53
Mobile, AL............... 10.3 172.0 0.4 236 904 3.3 187
Montgomery, AL........... 6.4 131.5 -0.5 317 891 3.6 156
Shelby, AL............... 5.9 85.5 -0.2 298 1,013 3.1 210
Tuscaloosa, AL........... 4.6 96.1 2.9 26 883 2.7 253
Anchorage, AK............ 8.3 150.3 -0.3 308 1,143 3.4 176
Maricopa, AZ............. 105.5 2,010.9 3.1 17 1,056 3.8 133
Pima, AZ................. 19.3 370.6 1.0 160 917 3.7 148
Benton, AR............... 6.8 122.3 1.6 102 1,197 16.3 1
Pulaski, AR.............. 14.6 254.0 0.7 197 949 3.2 200
Washington, AR........... 6.3 109.6 0.9 174 904 4.0 110
Alameda, CA.............. 65.7 797.9 0.4 236 1,495 5.7 15
Butte, CA................ 8.6 81.2 -3.4 354 843 5.8 12
Contra Costa, CA......... 33.7 372.3 0.1 269 1,332 4.6 66
Fresno, CA............... 37.6 406.8 1.3 131 875 5.7 15
Kern, CA................. 20.9 334.4 1.9 78 912 4.7 53
Los Angeles, CA.......... 508.5 4,495.1 1.1 150 1,225 4.2 95
Marin, CA................ 12.6 117.6 0.6 209 1,393 -2.0 352
Merced, CA............... 6.8 83.2 1.9 78 810 2.4 272
Monterey, CA............. 14.3 214.8 1.1 150 925 2.3 280
Napa, CA................. 6.0 82.3 1.4 120 1,086 4.3 87
Orange, CA............... 126.3 1,656.4 1.6 102 1,193 2.9 232
Placer, CA............... 13.8 173.2 2.0 69 1,082 3.6 156
Riverside, CA............ 68.3 759.8 2.3 54 880 3.3 187
Sacramento, CA........... 61.1 677.9 1.8 84 1,185 3.9 123
San Bernardino, CA....... 62.8 768.4 2.0 69 922 4.8 48
San Diego, CA............ 115.5 1,491.0 1.2 140 1,189 4.7 53
San Francisco, CA........ 61.8 761.0 3.4 9 2,430 15.5 2
San Joaquin, CA.......... 18.6 260.2 2.5 42 933 5.3 25
San Luis Obispo, CA...... 10.6 122.4 1.9 78 950 4.7 53
San Mateo, CA............ 29.0 416.7 2.6 36 2,373 1.1 338
Santa Barbara, CA........ 15.8 210.5 2.4 45 1,050 1.7 327
Santa Clara, CA.......... 74.9 1,123.2 1.8 84 2,612 1.5 333
Santa Cruz, CA........... 9.7 112.2 2.3 54 1,008 2.3 280
Solano, CA............... 11.9 144.8 0.4 236 1,163 8.0 6
Sonoma, CA............... 20.5 212.3 0.0 280 1,070 5.4 21
Stanislaus, CA........... 16.3 194.8 1.0 160 929 4.9 46
Tulare, CA............... 11.4 171.5 0.5 224 781 5.8 12
Ventura, CA.............. 28.0 334.3 1.0 160 1,069 3.2 200
Yolo, CA................. 7.0 108.4 1.2 140 1,178 3.3 187
Adams, CO................ 11.5 227.2 5.3 1 1,065 4.5 71
Arapahoe, CO............. 22.6 337.8 1.2 140 1,244 3.9 123
Boulder, CO.............. 15.9 190.3 2.7 32 1,306 5.7 15
Denver, CO............... 34.2 532.4 1.5 113 1,338 5.3 25
Douglas, CO.............. 12.6 133.4 2.3 54 1,246 5.8 12
El Paso, CO.............. 20.6 285.7 2.4 45 976 3.8 133
Jefferson, CO............ 20.7 246.4 1.4 120 1,125 4.1 102
Larimer, CO.............. 12.6 167.8 1.6 102 977 5.2 30
Weld, CO................. 7.7 114.7 3.3 10 1,001 5.0 39
Fairfield, CT............ 36.8 425.3 -0.7 330 1,572 5.5 20
Hartford, CT............. 29.2 516.5 -0.7 330 1,260 3.3 187
New Haven, CT............ 25.2 368.4 -0.9 336 1,101 3.0 220
New London, CT........... 7.7 125.2 -1.1 340 1,056 4.0 110
New Castle, DE........... 20.9 293.3 0.6 209 1,177 3.2 200
Sussex, DE............... 7.4 89.1 2.6 36 776 4.0 110
Washington, DC........... 40.3 780.3 0.5 224 1,778 3.8 133
Alachua, FL.............. 7.5 131.7 1.1 150 925 5.2 30
Bay, FL.................. 5.8 75.7 -6.4 355 841 9.2 3
Brevard, FL.............. 16.5 221.4 2.7 32 995 4.7 53
Broward, FL.............. 71.5 813.1 0.8 184 1,013 1.7 327
Collier, FL.............. 15.0 142.4 2.0 69 950 2.2 290
Duval, FL................ 30.7 520.6 1.8 84 1,003 2.8 243
Escambia, FL............. 8.4 137.3 1.9 78 844 4.3 87
Hillsborough, FL......... 45.0 694.9 2.7 32 1,040 3.7 148
Lake, FL................. 8.7 96.6 2.1 63 756 3.6 156
Lee, FL.................. 23.5 259.1 2.1 63 889 2.9 232
Leon, FL................. 8.9 150.5 1.0 160 864 2.7 253
Manatee, FL.............. 11.6 125.3 3.0 21 840 1.2 336
Marion, FL............... 8.8 104.5 1.9 78 759 2.7 253
Miami-Dade, FL........... 101.7 1,141.3 1.6 102 1,052 5.0 39
Okaloosa, FL............. 6.7 85.3 1.4 120 932 5.0 39
Orange, FL............... 44.9 857.2 2.2 60 956 4.1 102
Osceola, FL.............. 7.6 96.9 3.7 6 750 2.7 253
Palm Beach, FL........... 58.4 607.5 1.6 102 1,057 4.1 102
Pasco, FL................ 11.5 115.2 2.1 63 788 4.0 110
Pinellas, FL............. 34.5 438.0 0.6 209 948 4.1 102
Polk, FL................. 14.2 220.9 3.1 17 842 5.1 36
St. Johns, FL............ 7.9 77.3 2.2 60 845 1.7 327
St. Lucie, FL............ 6.9 76.3 3.3 10 846 5.0 39
Sarasota, FL............. 16.5 167.7 0.5 224 893 2.8 243
Seminole, FL............. 15.6 199.3 2.4 45 950 3.1 210
Volusia, FL.............. 15.0 170.0 0.0 280 796 3.2 200
Bibb, GA................. 4.3 82.3 -1.3 343 829 3.4 176
Chatham, GA.............. 8.1 159.1 1.3 131 905 2.0 303
Clayton, GA.............. 4.1 123.3 0.3 249 1,062 3.9 123
Cobb, GA................. 21.9 374.1 1.5 113 1,112 4.6 66
DeKalb, GA............... 17.8 302.3 0.4 236 1,097 4.2 95
Forsyth, GA.............. 6.0 78.2 2.5 42 955 3.4 176
Fulton, GA............... 43.8 905.4 2.4 45 1,404 4.0 110
Gwinnett, GA............. 25.5 360.2 1.0 160 1,018 4.6 66
Hall, GA................. 4.6 89.3 2.0 69 936 3.5 166
Muscogee, GA............. 4.5 93.9 -0.6 327 823 3.3 187
Richmond, GA............. 4.5 103.9 -0.2 298 883 2.9 232
Honolulu, HI............. 27.2 463.9 -1.4 347 1,039 3.5 166
Maui + Kalawao, HI....... 6.6 80.1 -1.6 350 889 4.3 87
Ada, ID.................. 17.3 254.9 3.0 21 949 2.8 243
Champaign, IL............ 4.1 91.5 1.1 150 943 3.6 156
Cook, IL................. 139.2 2,635.8 0.5 224 1,251 2.5 266
DuPage, IL............... 34.7 630.1 -0.2 298 1,199 3.3 187
Kane, IL................. 12.7 218.3 0.0 280 947 2.8 243
Lake, IL................. 20.3 350.0 -0.2 298 1,370 -2.5 353
McHenry, IL.............. 7.9 99.3 -1.4 347 867 3.8 133
McLean, IL............... 3.4 82.3 -0.1 291 950 -5.8 355
Madison, IL.............. 5.4 100.8 -1.0 338 847 2.8 243
Peoria, IL............... 4.2 105.4 -1.7 352 1,057 0.5 346
St. Clair, IL............ 5.0 91.9 -0.7 330 854 3.4 176
Sangamon, IL............. 4.8 130.9 -0.2 298 1,044 3.3 187
Will, IL................. 15.1 251.5 1.3 131 920 2.3 280
Winnebago, IL............ 5.9 127.8 -1.5 349 893 3.1 210
Allen, IN................ 9.0 192.6 1.5 113 883 2.6 258
Elkhart, IN.............. 4.8 136.0 -2.9 353 922 -1.9 351
Hamilton, IN............. 9.7 147.1 2.0 69 1,009 3.3 187
Lake, IN................. 10.3 190.3 0.5 224 904 3.0 220
Marion, IN............... 24.3 606.9 0.7 197 1,082 3.1 210
St. Joseph, IN........... 5.8 125.6 1.1 150 878 3.1 210
Tippecanoe, IN........... 3.5 85.2 0.2 261 934 4.5 71
Vanderburgh, IN.......... 4.8 109.5 -0.4 313 872 5.4 21
Johnson, IA.............. 4.4 83.6 -0.7 330 991 1.0 340
Linn, IA................. 7.0 133.6 0.1 269 1,020 1.2 336
Polk, IA................. 18.1 307.3 0.6 209 1,059 1.0 340
Scott, IA................ 5.8 93.3 0.3 249 867 3.0 220
Johnson, KS.............. 23.5 355.7 0.8 184 1,106 3.7 148
Sedgwick, KS............. 12.5 257.6 2.6 36 904 2.4 272
Shawnee, KS.............. 5.0 96.9 0.8 184 874 -2.9 354
Wyandotte, KS............ 3.4 89.7 -1.0 338 1,059 5.0 39
Boone, KY................ 4.4 95.3 1.3 131 941 3.9 123
Fayette, KY.............. 11.1 196.4 1.3 131 959 2.6 258
Jefferson, KY............ 25.4 473.2 0.2 261 1,063 3.0 220
Caddo, LA................ 7.4 111.0 -1.3 343 858 2.0 303
Calcasieu, LA............ 5.5 103.6 -0.6 327 961 3.4 176
East Baton Rouge, LA..... 16.2 260.6 -0.7 330 1,016 3.0 220
Jefferson, LA............ 14.3 190.2 0.0 280 971 3.6 156
Lafayette, LA............ 10.0 130.1 0.6 209 899 2.3 280
Orleans, LA.............. 13.4 198.7 2.1 63 987 2.2 290
St. Tammany, LA.......... 8.7 90.9 2.6 36 899 3.3 187
Cumberland, ME........... 14.0 191.1 0.3 249 980 4.3 87
Anne Arundel, MD......... 15.3 276.7 0.0 280 1,159 4.7 53
Baltimore, MD............ 21.4 384.3 0.4 236 1,076 3.5 166
Frederick, MD............ 6.5 106.9 1.7 97 988 3.6 156
Harford, MD.............. 5.9 95.8 -0.5 317 1,032 3.8 133
Howard, MD............... 10.1 177.1 1.0 160 1,316 3.7 148
Montgomery, MD........... 33.0 479.5 0.1 269 1,421 2.2 290
Prince George's, MD...... 16.3 324.6 1.8 84 1,137 2.2 290
Baltimore City, MD....... 13.7 344.2 -0.3 308 1,282 4.8 48
Barnstable, MA........... 9.7 108.4 -0.3 308 926 3.5 166
Bristol, MA.............. 18.1 232.9 -0.1 291 1,015 4.2 95
Essex, MA................ 27.3 332.4 -0.3 308 1,156 -0.7 350
Hampden, MA.............. 18.9 213.3 0.8 184 932 2.1 297
Middlesex, MA............ 56.9 950.5 1.6 102 1,650 5.2 30
Norfolk, MA.............. 25.7 360.3 0.1 269 1,265 4.1 102
Plymouth, MA............. 16.6 202.6 0.6 209 1,039 3.0 220
Suffolk, MA.............. 31.8 701.8 2.4 45 1,800 5.3 25
Worcester, MA............ 26.6 355.5 0.4 236 1,068 2.6 258
Genesee, MI.............. 7.3 137.9 0.1 269 874 2.0 303
Ingham, MI............... 6.5 153.0 0.2 261 1,041 3.8 133
Kalamazoo, MI............ 5.4 122.4 -0.1 291 1,002 3.5 166
Kent, MI................. 16.0 414.5 0.1 269 932 3.3 187
Macomb, MI............... 18.9 334.9 -0.5 317 1,052 2.3 280
Oakland, MI.............. 42.6 758.9 0.3 249 1,181 1.6 332
Ottawa, MI............... 6.2 130.6 -0.5 317 905 2.6 258
Saginaw, MI.............. 4.0 85.1 0.0 280 868 3.8 133
Washtenaw, MI............ 9.1 215.5 1.1 150 1,157 2.7 253
Wayne, MI................ 34.8 738.3 0.3 249 1,143 2.1 297
Anoka, MN................ 7.8 130.1 0.9 174 1,042 2.8 243
Dakota, MN............... 10.7 194.3 1.0 160 1,064 2.2 290
Hennepin, MN............. 41.6 945.3 1.2 140 1,345 1.9 316
Olmsted, MN.............. 3.8 101.4 -0.3 308 1,160 3.1 210
Ramsey, MN............... 14.4 337.5 0.8 184 1,188 3.7 148
St. Louis, MN............ 5.4 100.8 -0.1 291 916 3.0 220
Stearns, MN.............. 4.4 88.5 0.2 261 889 2.5 266
Washington, MN........... 6.1 90.3 0.7 197 931 2.4 272
Harrison, MS............. 4.6 87.8 0.9 174 747 1.9 316
Hinds, MS................ 5.7 120.0 -0.2 298 879 2.0 303
Boone, MO................ 4.9 94.1 0.4 236 881 5.3 25
Clay, MO................. 5.8 106.1 -0.5 317 943 3.3 187
Greene, MO............... 9.3 170.3 1.9 78 837 1.5 333
Jackson, MO.............. 22.4 379.1 0.9 174 1,095 3.4 176
St. Charles, MO.......... 9.8 153.1 1.8 84 887 4.5 71
St. Louis, MO............ 40.2 611.5 -0.5 317 1,137 -0.3 348
St. Louis City, MO....... 15.0 229.2 -0.4 313 1,151 3.6 156
Yellowstone, MT.......... 6.6 82.8 0.3 249 921 2.3 280
Douglas, NE.............. 19.1 342.7 0.3 249 1,002 4.4 79
Lancaster, NE............ 10.2 172.1 0.0 280 863 1.9 316
Clark, NV................ 57.0 1,022.8 2.8 29 943 3.1 210
Washoe, NV............... 15.3 227.3 2.0 69 979 3.7 148
Hillsborough, NH......... 12.3 208.3 0.8 184 1,172 4.0 110
Merrimack, NH............ 5.3 78.9 0.4 236 998 1.1 338
Rockingham, NH........... 11.2 154.5 0.5 224 1,082 5.0 39
Atlantic, NJ............. 6.6 136.8 0.7 197 899 -0.6 349
Bergen, NJ............... 33.3 451.4 0.6 209 1,234 2.9 232
Burlington, NJ........... 11.1 207.0 0.6 209 1,088 2.0 303
Camden, NJ............... 12.2 208.5 -0.1 291 1,046 3.6 156
Essex, NJ................ 20.9 349.8 0.8 184 1,305 3.3 187
Gloucester, NJ........... 6.4 114.8 2.4 45 910 2.0 303
Hudson, NJ............... 15.4 271.1 1.3 131 1,426 1.8 321
Mercer, NJ............... 11.3 262.7 0.7 197 1,347 2.8 243
Middlesex, NJ............ 22.6 434.3 0.3 249 1,233 3.2 200
Monmouth, NJ............. 20.4 275.6 0.3 249 1,041 2.1 297
Morris, NJ............... 17.2 299.7 0.2 261 1,544 2.9 232
Ocean, NJ................ 13.7 182.6 2.0 69 848 2.5 266
Passaic, NJ.............. 12.6 167.8 -0.1 291 1,027 2.3 280
Somerset, NJ............. 10.3 194.2 0.0 280 1,626 4.4 79
Union, NJ................ 14.6 230.8 0.0 280 1,313 3.4 176
Bernalillo, NM........... 19.7 332.9 0.8 184 921 4.0 110
Albany, NY............... 10.2 234.8 -0.9 336 1,181 3.5 166
Bronx, NY................ 18.7 325.0 0.8 184 1,117 5.7 15
Broome, NY............... 4.4 87.6 -0.5 317 894 3.5 166
Dutchess, NY............. 8.3 114.7 0.1 269 1,076 3.2 200
Erie, NY................. 24.1 476.7 -0.2 298 986 3.9 123
Kings, NY................ 62.8 794.6 0.5 224 955 4.5 71
Monroe, NY............... 18.6 396.0 0.6 209 1,009 2.1 297
Nassau, NY............... 53.3 642.2 -0.6 327 1,216 3.4 176
New York, NY............. 126.1 2,532.1 1.1 150 2,109 4.3 87
Oneida, NY............... 5.2 107.3 0.2 261 870 4.8 48
Onondaga, NY............. 12.6 253.7 1.4 120 1,003 2.3 280
Orange, NY............... 10.4 150.7 1.3 131 963 2.6 258
Queens, NY............... 52.6 720.6 1.6 102 1,088 2.4 272
Richmond, NY............. 9.8 128.6 3.9 2 1,034 3.7 148
Rockland, NY............. 10.8 132.0 2.2 60 1,038 1.8 321
Saratoga, NY............. 5.9 92.3 -1.2 341 1,040 4.0 110
Suffolk, NY.............. 52.7 688.5 -0.4 313 1,157 2.0 303
Westchester, NY.......... 35.6 440.4 -0.1 291 1,417 4.7 53
Buncombe, NC............. 9.7 134.9 1.8 84 840 4.5 71
Cabarrus, NC............. 4.9 77.2 2.8 29 802 4.4 79
Catawba, NC.............. 4.5 89.1 0.1 269 829 2.1 297
Cumberland, NC........... 6.2 121.3 0.6 209 853 4.0 110
Durham, NC............... 8.6 211.5 3.8 5 1,312 4.5 71
Forsyth, NC.............. 9.3 191.3 1.6 102 944 1.8 321
Guilford, NC............. 14.6 284.6 0.8 184 948 5.2 30
Mecklenburg, NC.......... 39.0 717.6 3.0 21 1,225 2.0 303
New Hanover, NC.......... 8.5 118.7 2.4 45 873 5.4 21
Pitt, NC................. 3.8 77.1 1.0 160 863 4.0 110
Wake, NC................. 36.0 581.5 2.4 45 1,143 3.8 133
Cass, ND................. 7.4 121.3 2.1 63 994 4.4 79
Butler, OH............... 8.0 158.0 1.2 140 939 4.2 95
Cuyahoga, OH............. 36.2 739.0 0.4 236 1,082 2.3 280
Delaware, OH............. 5.6 91.8 0.6 209 1,047 4.7 53
Franklin, OH............. 33.6 765.2 0.8 184 1,060 3.5 166
Greene, OH............... 3.7 76.1 1.8 84 1,117 4.7 53
Hamilton, OH............. 24.2 527.5 0.7 197 1,158 4.7 53
Lake, OH................. 6.3 98.9 1.1 150 894 4.4 79
Lorain, OH............... 6.2 100.9 0.6 209 825 2.2 290
Lucas, OH................ 10.2 211.4 1.4 120 905 3.2 200
Mahoning, OH............. 5.9 98.4 -1.3 343 755 3.0 220
Montgomery, OH........... 12.0 257.6 0.2 261 923 2.9 232
Stark, OH................ 8.6 160.7 -0.4 313 806 3.2 200
Summit, OH............... 14.4 269.4 0.1 269 947 3.2 200
Warren, OH............... 5.2 99.8 3.6 8 998 8.6 5
Cleveland, OK............ 6.0 82.1 1.7 97 800 3.0 220
Oklahoma, OK............. 28.3 463.8 0.9 174 1,000 3.0 220
Tulsa, OK................ 22.7 362.6 1.1 150 964 2.4 272
Clackamas, OR............ 15.6 171.7 1.8 84 1,030 2.6 258
Deschutes, OR............ 9.3 87.4 2.6 36 900 4.8 48
Jackson, OR.............. 7.9 90.9 0.1 269 848 5.7 15
Lane, OR................. 12.8 159.2 0.3 249 856 2.8 243
Marion, OR............... 11.5 161.5 1.0 160 922 3.9 123
Multnomah, OR............ 36.6 520.6 1.8 84 1,164 4.9 46
Washington, OR........... 20.5 304.7 1.5 113 1,364 1.8 321
Allegheny, PA............ 35.7 710.1 0.4 236 1,168 3.8 133
Berks, PA................ 9.0 177.1 1.0 160 969 1.7 327
Bucks, PA................ 20.3 274.7 1.4 120 996 2.5 266
Butler, PA............... 5.1 88.8 0.7 197 994 2.1 297
Chester, PA.............. 15.8 256.0 0.9 174 1,387 3.0 220
Cumberland, PA........... 6.6 137.0 1.2 140 1,009 4.1 102
Dauphin, PA.............. 7.5 190.2 1.4 120 1,065 5.2 30
Delaware, PA............. 14.2 228.0 0.7 197 1,128 3.9 123
Erie, PA................. 7.0 123.6 0.1 269 812 2.3 280
Lackawanna, PA........... 5.6 97.9 -1.2 341 821 2.0 303
Lancaster, PA............ 13.8 247.7 1.0 160 904 5.2 30
Lehigh, PA............... 8.9 197.7 0.8 184 1,036 4.1 102
Luzerne, PA.............. 7.5 145.7 -0.5 317 856 2.0 303
Montgomery, PA........... 27.9 510.2 1.2 140 1,297 4.0 110
Northampton, PA.......... 6.9 119.1 2.4 45 930 3.8 133
Philadelphia, PA......... 35.0 697.4 1.5 113 1,251 3.8 133
Washington, PA........... 5.6 90.6 0.5 224 1,050 4.1 102
Westmoreland, PA......... 9.3 135.9 0.5 224 870 3.0 220
York, PA................. 9.2 180.5 -0.2 298 952 3.5 166
Kent, RI................. 5.6 77.9 0.5 224 934 2.4 272
Providence, RI........... 18.9 290.0 0.3 249 1,065 3.1 210
Charleston, SC........... 16.9 262.8 2.0 69 964 4.7 53
Greenville, SC........... 15.2 280.8 1.4 120 934 2.5 266
Horry, SC................ 9.7 141.2 0.4 236 649 3.8 133
Lexington, SC............ 7.1 121.5 0.9 174 816 4.2 95
Richland, SC............. 10.7 223.5 0.0 280 901 2.9 232
Spartanburg, SC.......... 6.6 146.5 2.5 42 915 5.9 11
York, SC................. 6.4 100.9 3.3 10 873 3.8 133
Minnehaha, SD............ 7.6 130.1 1.2 140 935 4.4 79
Davidson, TN............. 24.5 514.7 3.3 10 1,124 3.9 123
Hamilton, TN............. 10.2 208.4 1.4 120 946 1.9 316
Knox, TN................. 13.0 239.6 0.6 209 921 0.1 347
Rutherford, TN........... 6.1 134.1 2.3 54 961 2.9 232
Shelby, TN............... 21.1 504.8 0.7 197 1,090 5.1 36
Williamson, TN........... 9.6 140.5 3.2 14 1,263 4.5 71
Bell, TX................. 5.7 120.8 1.0 160 931 3.4 176
Bexar, TX................ 43.1 876.3 1.5 113 990 5.4 21
Brazoria, TX............. 6.1 116.6 2.7 32 1,098 2.0 303
Brazos, TX............... 4.7 104.6 3.0 21 803 1.0 340
Cameron, TX.............. 6.6 142.2 1.0 160 659 4.6 66
Collin, TX............... 27.2 432.5 2.6 36 1,258 1.7 327
Dallas, TX............... 78.8 1,737.1 2.1 63 1,304 4.8 48
Denton, TX............... 16.1 257.7 3.7 6 971 2.4 272
Ector, TX................ 4.2 80.5 1.2 140 1,219 3.9 123
El Paso, TX.............. 15.6 308.5 1.0 160 756 3.1 210
Fort Bend, TX............ 14.3 197.4 3.2 14 980 3.2 200
Galveston, TX............ 6.3 112.5 1.4 120 972 6.3 8
Harris, TX............... 117.3 2,349.3 1.7 97 1,306 2.8 243
Hidalgo, TX.............. 12.7 265.1 1.7 97 657 2.0 303
Jefferson, TX............ 5.9 122.4 -0.2 298 1,061 2.0 303
Lubbock, TX.............. 7.8 141.2 0.9 174 850 1.0 340
McLennan, TX............. 5.4 113.9 1.1 150 875 0.7 344
Midland, TX.............. 6.0 108.6 3.1 17 1,450 4.3 87
Montgomery, TX........... 12.2 192.2 3.0 21 1,073 0.6 345
Nueces, TX............... 8.3 165.2 0.4 236 925 3.4 176
Potter, TX............... 4.0 76.9 0.7 197 887 2.5 266
Smith, TX................ 6.4 103.5 0.5 224 883 2.8 243
Tarrant, TX.............. 45.2 920.9 1.2 140 1,078 3.9 123
Travis, TX............... 43.2 779.6 3.2 14 1,292 4.4 79
Webb, TX................. 5.6 104.2 1.8 84 697 1.8 321
Williamson, TX........... 11.8 182.8 3.9 2 1,066 5.3 25
Davis, UT................ 9.0 134.5 2.3 54 903 4.0 110
Salt Lake, UT............ 48.3 723.8 2.9 26 1,055 4.6 66
Utah, UT................. 17.6 251.2 3.9 2 893 3.6 156
Weber, UT................ 6.4 109.4 3.1 17 813 2.9 232
Chittenden, VT........... 7.1 103.6 0.4 236 1,039 1.9 316
Arlington, VA............ 9.2 183.9 1.8 84 1,704 2.9 232
Chesterfield, VA......... 9.5 138.2 0.9 174 910 2.9 232
Fairfax, VA.............. 37.0 629.7 1.6 102 1,647 4.5 71
Henrico, VA.............. 11.9 195.0 0.0 280 1,022 4.3 87
Loudoun, VA.............. 12.8 179.0 2.8 29 1,216 2.6 258
Prince William, VA....... 9.6 136.8 1.6 102 940 1.8 321
Alexandria City, VA...... 6.3 93.1 -0.2 298 1,471 4.2 95
Chesapeake City, VA...... 6.2 102.9 0.5 224 849 2.4 272
Newport News City, VA.... 4.0 104.0 0.7 197 1,030 4.3 87
Norfolk City, VA......... 6.1 141.9 -0.7 330 1,095 3.5 166
Richmond City, VA........ 8.1 157.6 1.5 113 1,160 4.2 95
Virginia Beach City, VA.. 12.4 184.0 0.6 209 839 3.7 148
Benton, WA............... 6.1 96.6 1.3 131 1,083 6.1 10
Clark, WA................ 15.4 165.8 1.6 102 1,048 5.0 39
King, WA................. 90.1 1,445.1 2.9 26 1,709 6.6 7
Kitsap, WA............... 6.9 92.6 2.0 69 1,054 3.6 156
Pierce, WA............... 23.3 318.3 1.4 120 1,028 5.1 36
Snohomish, WA............ 21.8 294.2 1.8 84 1,179 3.8 133
Spokane, WA.............. 16.7 231.3 1.7 97 947 4.4 79
Thurston, WA............. 8.6 118.6 1.3 131 1,034 4.7 53
Whatcom, WA.............. 7.4 93.5 0.9 174 945 3.8 133
Yakima, WA............... 8.1 127.2 -1.3 343 773 4.7 53
Kanawha, WV.............. 5.7 97.5 -1.6 350 916 2.2 290
Brown, WI................ 7.3 162.2 0.6 209 929 3.1 210
Dane, WI................. 16.5 346.1 1.8 84 1,105 6.3 8
Milwaukee, WI............ 28.1 491.7 -0.5 317 1,025 4.0 110
Outagamie, WI............ 5.6 111.2 -0.5 317 928 3.3 187
Racine, WI............... 4.7 77.3 0.3 249 908 1.3 335
Waukesha, WI............. 13.8 251.6 0.7 197 1,064 3.4 176
Winnebago, WI............ 4.0 94.1 0.2 261 1,055 9.1 4
San Juan, PR............. 11.2 240.4 0.5 (5) 639 -3.3 (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 355 U.S. counties comprise 73.4 percent of
the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,
second quarter 2019
Employment Average weekly
wage(1)
Establishments,
second quarter
County by NAICS supersector 2019 Percent Percent
(thousands) June change, Second change,
2019 June quarter second
(thousands) 2018-19(2) 2019 quarter
2018-19(2)
United States(3) ............................ 10,252.0 149,089.2 1.1 $1,095 3.8
Private industry........................... 9,951.2 127,278.4 1.2 1,085 3.8
Natural resources and mining............. 139.6 2,062.7 -0.2 1,115 3.5
Construction............................. 830.8 7,619.6 2.4 1,201 3.6
Manufacturing............................ 356.0 12,862.0 0.9 1,297 2.9
Trade, transportation, and utilities..... 1,944.7 27,415.8 0.3 927 4.3
Information.............................. 184.2 2,856.0 1.0 2,168 5.3
Financial activities..................... 913.8 8,357.3 1.1 1,638 3.2
Professional and business services....... 1,901.1 21,300.7 1.6 1,429 4.5
Education and health services............ 1,757.4 22,968.4 1.7 979 3.1
Leisure and hospitality.................. 879.6 17,040.9 1.1 467 4.2
Other services........................... 861.0 4,618.6 1.0 754 4.0
Government................................. 300.8 21,810.7 0.4 1,150 3.3
Los Angeles, CA.............................. 508.5 4,495.1 1.1 1,225 4.2
Private industry........................... 502.1 3,909.5 1.2 1,189 3.7
Natural resources and mining............. 0.5 6.3 -4.0 1,099 4.9
Construction............................. 16.7 149.4 2.5 1,295 4.8
Manufacturing............................ 12.8 339.9 -0.1 1,387 4.4
Trade, transportation, and utilities..... 59.4 833.8 0.0 1,008 5.5
Information.............................. 13.0 193.0 1.3 2,547 5.2
Financial activities..................... 30.1 223.6 -0.2 1,920 3.0
Professional and business services....... 55.9 634.2 1.9 1,514 2.3
Education and health services............ 243.8 822.4 2.4 910 3.5
Leisure and hospitality.................. 38.9 552.2 2.0 691 1.6
Other services........................... 29.3 153.3 0.0 779 0.9
Government................................. 6.4 585.7 0.2 1,463 6.6
Cook, IL..................................... 139.2 2,635.8 0.5 1,251 2.5
Private industry........................... 138.0 2,337.2 0.5 1,241 2.7
Natural resources and mining............. 0.1 1.5 10.9 1,192 1.9
Construction............................. 11.2 80.3 0.4 1,508 3.1
Manufacturing............................ 5.7 185.6 0.5 1,262 1.0
Trade, transportation, and utilities..... 28.5 472.8 -0.1 1,049 4.6
Information.............................. 2.5 53.0 1.1 2,057 5.6
Financial activities..................... 14.1 208.3 1.7 2,188 3.6
Professional and business services....... 29.2 479.2 1.2 1,565 -0.2
Education and health services............ 15.6 450.6 0.0 1,014 3.0
Leisure and hospitality.................. 13.9 304.5 0.8 580 3.8
Other services........................... 16.2 100.9 -1.0 967 3.5
Government................................. 1.3 298.6 0.0 1,328 1.0
New York, NY................................. 126.1 2,532.1 1.1 2,109 4.3
Private industry........................... 124.7 2,300.7 1.1 2,153 4.4
Natural resources and mining............. 0.0 0.2 11.8 2,655 31.8
Construction............................. 2.4 44.0 -1.5 1,982 3.7
Manufacturing............................ 1.8 22.5 -4.8 1,553 3.5
Trade, transportation, and utilities..... 18.6 253.8 -0.5 1,546 2.4
Information.............................. 5.1 182.8 3.5 2,883 6.1
Financial activities..................... 19.4 392.5 1.6 3,746 2.4
Professional and business services....... 27.5 624.1 1.1 2,396 5.4
Education and health services............ 10.2 357.1 2.1 1,449 4.4
Leisure and hospitality.................. 14.7 314.0 0.2 953 5.1
Other services........................... 19.7 105.9 0.2 1,295 5.1
Government................................. 1.4 231.4 0.8 1,674 2.6
Harris, TX................................... 117.3 2,349.3 1.7 1,306 2.8
Private industry........................... 116.7 2,074.2 1.9 1,321 2.7
Natural resources and mining............. 1.6 68.0 2.1 3,027 -1.4
Construction............................. 7.8 170.1 4.0 1,401 2.9
Manufacturing............................ 4.9 181.6 3.9 1,606 0.0
Trade, transportation, and utilities..... 25.2 468.9 0.3 1,194 3.5
Information.............................. 1.2 26.7 1.8 1,510 3.9
Financial activities..................... 12.7 130.1 2.1 1,704 3.3
Professional and business services....... 23.6 411.6 1.9 1,638 3.0
Education and health services............ 16.6 301.0 1.5 1,075 3.2
Leisure and hospitality.................. 10.6 245.4 2.3 501 4.6
Other services........................... 11.8 69.4 1.5 866 6.1
Government................................. 0.6 275.0 0.3 1,193 3.8
Maricopa, AZ................................. 105.5 2,010.9 3.1 1,056 3.8
Private industry........................... 104.8 1,819.3 3.1 1,046 4.0
Natural resources and mining............. 0.4 8.2 -1.9 1,024 8.4
Construction............................. 8.5 131.9 8.3 1,157 6.8
Manufacturing............................ 3.5 128.4 2.5 1,505 1.8
Trade, transportation, and utilities..... 20.6 384.7 2.1 965 4.1
Information.............................. 2.1 38.0 0.4 1,429 4.8
Financial activities..................... 13.6 189.9 3.4 1,355 2.8
Professional and business services....... 26.2 345.4 3.4 1,118 3.2
Education and health services............ 13.3 316.1 4.0 1,019 3.6
Leisure and hospitality.................. 9.1 222.2 1.7 529 5.8
Other services........................... 7.0 54.1 1.0 790 5.6
Government................................. 0.7 191.6 2.6 1,145 2.9
Dallas, TX................................... 78.8 1,737.1 2.1 1,304 4.8
Private industry........................... 78.2 1,563.7 2.3 1,311 5.0
Natural resources and mining............. 0.5 9.4 7.5 3,327 -4.0
Construction............................. 4.9 93.1 3.0 1,309 3.3
Manufacturing............................ 2.8 118.5 3.0 1,526 6.6
Trade, transportation, and utilities..... 16.2 351.1 1.9 1,143 5.5
Information.............................. 1.4 46.3 -1.5 1,980 9.4
Financial activities..................... 9.8 166.9 2.7 1,817 6.4
Professional and business services....... 17.8 361.1 2.8 1,540 5.3
Education and health services............ 9.8 203.5 2.2 1,152 2.1
Leisure and hospitality.................. 7.2 168.2 2.0 523 0.2
Other services........................... 7.1 44.6 1.5 910 6.2
Government................................. 0.5 173.4 0.4 1,243 3.4
Orange, CA................................... 126.3 1,656.4 1.6 1,193 2.9
Private industry........................... 124.9 1,499.3 1.8 1,177 2.9
Natural resources and mining............. 0.2 2.4 -7.1 927 1.9
Construction............................. 7.7 107.1 1.3 1,444 5.9
Manufacturing............................ 5.3 160.0 -0.2 1,516 0.7
Trade, transportation, and utilities..... 18.5 255.7 -0.4 1,062 4.3
Information.............................. 1.6 25.6 -3.2 2,055 1.0
Financial activities..................... 12.9 115.9 -1.4 1,852 4.4
Professional and business services....... 23.5 326.1 4.1 1,373 2.3
Education and health services............ 37.4 224.9 3.4 962 2.8
Leisure and hospitality.................. 9.7 232.5 3.3 541 6.1
Other services........................... 7.6 48.5 1.3 744 3.2
Government................................. 1.4 157.0 0.1 1,345 3.3
San Diego, CA................................ 115.5 1,491.0 1.2 1,189 4.7
Private industry........................... 113.5 1,252.0 1.5 1,147 4.8
Natural resources and mining............. 0.7 10.6 5.1 773 1.3
Construction............................. 7.8 84.3 0.2 1,279 6.0
Manufacturing............................ 3.5 115.0 1.6 1,595 6.3
Trade, transportation, and utilities..... 15.4 220.6 -0.1 902 5.6
Information.............................. 1.4 23.1 -2.7 2,039 10.5
Financial activities..................... 11.1 75.8 -0.5 1,538 2.9
Professional and business services....... 20.9 253.4 2.8 1,659 4.5
Education and health services............ 34.7 209.0 3.1 974 2.9
Leisure and hospitality.................. 9.1 206.4 1.2 548 5.2
Other services........................... 8.2 53.2 1.3 660 3.8
Government................................. 2.0 239.1 0.0 1,406 4.1
King, WA..................................... 90.1 1,445.1 2.9 1,709 6.6
Private industry........................... 89.5 1,270.7 3.2 1,745 6.7
Natural resources and mining............. 0.4 3.2 3.6 1,359 -4.0
Construction............................. 6.9 76.2 3.0 1,479 5.0
Manufacturing............................ 2.5 106.0 3.6 1,689 2.3
Trade, transportation, and utilities..... 13.7 276.7 2.6 1,958 4.5
Information.............................. 2.6 122.3 8.5 3,771 11.1
Financial activities..................... 6.8 71.5 1.1 1,814 6.3
Professional and business services....... 18.5 235.7 2.8 1,899 5.9
Education and health services............ 21.3 180.6 2.5 1,117 3.9
Leisure and hospitality.................. 7.4 149.6 1.2 637 6.7
Other services........................... 9.3 49.0 7.1 950 5.3
Government................................. 0.6 174.4 0.9 1,449 5.6
Miami-Dade, FL............................... 101.7 1,141.3 1.6 1,052 5.0
Private industry........................... 101.4 1,015.0 1.7 1,032 5.3
Natural resources and mining............. 0.5 8.6 1.8 682 1.9
Construction............................. 7.3 51.7 3.1 1,047 8.3
Manufacturing............................ 2.8 41.9 3.1 942 5.5
Trade, transportation, and utilities..... 24.6 287.6 1.3 960 4.0
Information.............................. 1.6 19.0 2.9 1,735 2.6
Financial activities..................... 10.9 75.8 -0.2 1,596 4.4
Professional and business services....... 23.4 164.4 1.7 1,295 9.8
Education and health services............ 11.3 182.9 1.9 1,025 3.3
Leisure and hospitality.................. 7.6 142.8 2.0 639 5.1
Other services........................... 8.6 38.8 1.1 672 3.5
Government................................. 0.3 126.3 0.3 1,208 3.4
(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 2018 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 2019
Employment Average weekly
wage(1)
Establishments,
second quarter
State 2019 Percent Percent
(thousands) June change, Second change,
2019 June quarter second
(thousands) 2018-19 2019 quarter
2018-19
United States(2)........... 10,252.0 149,089.2 1.1 $1,095 3.8
Alabama.................... 129.6 1,993.7 1.1 911 3.4
Alaska..................... 22.3 338.9 0.7 1,078 3.6
Arizona.................... 166.5 2,843.3 2.6 1,010 3.8
Arkansas................... 91.9 1,222.5 0.6 862 4.6
California................. 1,595.3 17,717.4 1.5 1,325 4.7
Colorado................... 210.2 2,765.7 2.2 1,128 4.9
Connecticut................ 123.0 1,690.8 -0.8 1,266 3.9
Delaware................... 33.8 458.0 0.8 1,057 3.4
District of Columbia....... 40.3 780.4 0.5 1,778 3.8
Florida.................... 716.5 8,722.9 1.8 968 3.9
Georgia.................... 285.1 4,507.1 1.7 1,016 3.9
Hawaii..................... 44.7 652.2 -1.2 992 3.7
Idaho...................... 67.5 765.1 2.6 820 3.3
Illinois................... 378.3 6,074.7 0.3 1,122 2.4
Indiana.................... 167.7 3,089.8 0.5 910 3.1
Iowa....................... 104.2 1,584.7 0.1 902 2.5
Kansas..................... 87.9 1,403.0 0.6 905 2.8
Kentucky................... 121.3 1,909.7 0.3 911 3.3
Louisiana.................. 135.0 1,920.2 -0.2 923 2.4
Maine...................... 54.3 639.6 0.4 874 3.7
Maryland................... 174.3 2,733.6 0.7 1,178 3.3
Massachusetts.............. 262.9 3,690.1 0.9 1,377 4.3
Michigan................... 261.9 4,419.7 0.1 1,018 2.4
Minnesota.................. 182.4 2,952.6 0.8 1,101 2.6
Mississippi................ 73.7 1,135.9 0.4 767 2.0
Missouri................... 208.3 2,836.7 0.3 948 2.5
Montana.................... 49.5 483.1 1.0 843 3.3
Nebraska................... 72.6 991.5 0.1 889 3.5
Nevada..................... 83.7 1,408.8 2.6 961 3.2
New Hampshire.............. 53.7 676.1 0.8 1,090 4.0
New Jersey................. 276.9 4,182.5 0.7 1,236 3.0
New Mexico................. 61.7 834.0 1.0 888 4.3
New York................... 651.9 9,682.8 1.0 1,347 3.9
North Carolina............. 284.7 4,527.3 2.0 970 3.9
North Dakota............... 31.9 431.8 1.3 1,026 4.1
Ohio....................... 300.7 5,486.7 0.4 965 3.4
Oklahoma................... 111.2 1,618.5 0.5 900 3.1
Oregon..................... 160.2 1,976.5 1.3 1,036 3.8
Pennsylvania............... 362.1 5,972.1 0.8 1,070 3.8
Rhode Island............... 38.8 494.5 0.7 1,034 3.4
South Carolina............. 139.0 2,144.2 1.3 867 3.7
South Dakota............... 34.1 441.8 0.4 838 3.8
Tennessee.................. 166.4 3,047.8 1.8 964 3.3
Texas...................... 707.8 12,585.6 2.0 1,102 3.8
Utah....................... 107.5 1,526.1 3.0 936 4.1
Vermont.................... 26.1 314.0 0.0 929 2.7
Virginia................... 281.9 3,981.6 1.0 1,113 3.7
Washington................. 251.3 3,500.6 1.8 1,288 5.9
West Virginia.............. 51.5 700.4 -0.6 889 2.4
Wisconsin.................. 181.0 2,945.3 0.3 940 4.1
Wyoming.................... 26.9 287.6 1.7 932 3.4
Puerto Rico................ 47.0 867.7 1.5 531 -1.8
Virgin Islands............. 3.4 37.0 10.0 919 8.8
(1) Average weekly wages were calculated using unrounded data.
(2) Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
Note: Data are preliminary. Includes workers covered by Unemployment Insurance (UI) and
Unemployment Compensation for Federal Employees (UCFE) programs.
United States Department of Labor
