For release 10:00 a.m. (EST), Thursday, February 20, 2020 USDL-20-0300 

Technical Information: (202) 691-6567 • QCEWInfo@bls.gov • www.bls.gov/cew 

Media Contact: (202) 691-5902 • PressOffice@bls.gov 

COUNTY EMPLOYMENT AND WAGES – THIRD QUARTER 2019 

From September 2018 to September 2019, employment increased in 283 of the 355 largest U.S. 

counties, the U.S. Bureau of Labor Statistics reported today. In September 2019, national 

employment (as measured by the QCEW program) increased to 148.6 million, a 1.1 percent 

increase over the year. New Hanover, NC, had the largest over-the-year increase in employment 

with a gain of 5.8 percent. Employment data in this release are presented for September 2019, 

and average weekly wage data are presented for third quarter 2019. 

Among the 355 largest counties, 350 had over-the-year increases in average weekly wages. In 

the third quarter of 2019, average weekly wages for the nation increased to $1,093, a 3.6 percent 

increase over the year. Boulder, CO, had the largest third quarter over-the-year wage gain at 18.4 

percent. (See table 1.)

Chart 1. Percent change in employment, September 2018 to September 2019, by largest gains and losses 

-6.0% -4.0% -2.0% 0.0% 2.0% 4.0% 6.0%

Bay, FL

Elkhart, IN

Calcasieu, LA

Peoria, IL

Butte, CA

Benton, WA

Denton, TX

Rockland, NY

San Francisco, CA

Williamson, TN

Cleveland, OK

Weld, CO

Williamson, TX

Durham, NC

York, SC

Richmond, NY

Adams, CO

New Hanover, NC
- 2 -

Large County Employment in September 2019

New Hanover, NC, had the largest over-the-year percentage increase in employment (5.8 

percent). Within New Hanover, the largest employment increase occurred in leisure and 

hospitality, which gained 1,725 jobs over the year (10.2 percent).

Bay, FL, experienced the largest over-the-year percentage decrease in employment, with a loss

of 5.9 percent. Within Bay, education and health services had the largest employment decrease 

with a loss of 2,347 jobs (-21.1 percent).

Large County Average Weekly Wage in Third Quarter 2019

Boulder, CO, had the largest over-the-year percentage increase in average weekly wages (18.4

percent). Within Boulder, an average weekly wage gain of $1,016 (51.8 percent) in professional 

and business services made the largest contribution to the county’s increase in average weekly 

wages.

Linn, IA, had the largest over-the-year percentage decrease in average weekly wages with a loss 

of 2.6 percent. Within Linn, manufacturing had the largest impact, with an average weekly wage

decrease of $285 (-14.7 percent) over the year.

Chart 2. Percent change in average weekly wage, third quarter 2018 to third quarter 2019, by 

largest gains and losses

-3.0% -1.0% 1.0% 3.0% 5.0% 7.0% 9.0% 11.0% 13.0% 15.0% 17.0% 19.0%

Linn, IA

Chatham, GA

McLean, IL

Santa Clara, CA

San Mateo, CA

Warren, OH

Yolo, CA

Utah, UT

Weld, CO

San Francisco, CA

Montgomery, AL

Bay, FL

Lake, OH

Williamson, TX

Sangamon, IL

Boulder, CO
- 3 -

Ten Largest Counties

All of the 10 largest counties had over-the-year percentage increases in employment and average 

weekly wages. In September 2019, Maricopa, AZ, had the largest over-the-year employment

percentage gain among the 10 largest counties (3.2 percent). Within Maricopa, education and 

health services had the largest employment increase with a gain of 14,264 jobs (4.5 percent).

(See table 2.)

In third quarter 2019, Dallas, TX, experienced the largest over-the-year percentage gain in 

average weekly wages among the 10 largest counties (4.9 percent). Within Dallas, professional 

and business services had the largest impact, with an average weekly wage increase of $93 (6.5

percent) over the year.

For More Information

The tables and charts 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. September 2019

employment and third 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/datatools/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 third quarter 2019 is scheduled

to be released on Wednesday, March 4, 2020, at 10:00 a.m. (EST). 

The County Employment and Wages news release for fourth quarter 2019 is scheduled to 

be released on Wednesday, May 20, 2020, at 10:00 a.m. (EDT). 
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.

Summary of Major Differences between QCEW, BED, and CES Employment Measures

QCEW BED CES

Source Count of UI administrative records 

submitted by 10.2 million establishments in first quarter of 2019

Count of longitudinally-linked UI administrative records submitted by 8.2 

million private-sector employers

Sample survey: 697,000 establishments

Coverage UI and UCFE coverage, including 

all employers subject to state and 

federal UI laws

UI coverage, excluding government, 

private households, and establishments with zero employment

Nonfarm wage and salary jobs:

UI coverage, excluding agriculture, private 

households, and self-employed workers

Other employment, including railroads, 

religious organizations, and other nonUI-covered jobs

Publication frequency

Quarterly

— Within 5 months after the end of 

each quarter

Quarterly

— 7 months after the end of each 

quarter

Monthly

— Usually the 3rd Friday after the end 

of the week including the 12th of the 

month

Use of UI file Directly summarizes and publishes 

each new quarter of UI data

Links each new UI quarter to longitudinal database and directly summarizes gross job gains and lossesUses UI file as a sampling frame and to 

annually realign sample-based estimates 

to population counts (benchmarking)

Principal

products

Provides a quarterly and annual universe count of establishments, employment, and wages at the county, 

metropolitan statistical area (MSA), 

state, and national levels by detailed 

industry

Provides quarterly employer dynamics data on establishment openings,

closings, expansions, and contractions 

at the national level by NAICS supersectors and by size of firm, and at the 

state private-sector total level 

Future expansions will include data 

with greater industry detail and data 

at the county and MSA level 

Provides current monthly estimates of 

employment, hours, and earnings at the 

MSA, state, and national level by industry

Principal uses Major uses include:

— Detailed locality data

— Periodic universe counts for 

benchmarking sample survey estimates

— Sample frame for BLS establishment surveys

Major uses include:

— Business cycle analysis

— Analysis of employer dynamics 

underlying economic expansions 

and contractions

— Analysis of employment expansion and contraction by size of 

firm

Major uses include:

— Principal federal economic indicator

— Official time series for employment 

change measures

— Input into other major economic indicators

Program Web 

sites

www.bls.gov/cew www.bls.gov/bdm www.bls.gov/ces
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.

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 overthe-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 parttime 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-theyear 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-theyear 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/employmentand-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,

third quarter 2019

Employment Average weekly wage 2

County1

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-193

Ranking by

percent

change

Third

quarter

2019

Percent

change,

third quarter

2018-193

Ranking by

percent

change

United States4.............................. 10,325.3 148,556.5 1.1 - $1,093 3.6 -

Jefferson, AL................................ 19.3 353.6 1.1 153 1,055 2.9 238

Madison, AL................................. 10.1 206.3 3.0 25 1,194 4.9 42

Mobile, AL.................................... 10.4 171.7 0.5 226 922 2.9 238

Montgomery, AL........................... 6.5 129.9 -0.8 333 909 8.5 6

Shelby, AL.................................... 6.0 84.4 -0.8 333 1,009 1.7 314

Tuscaloosa, AL............................. 4.7 98.2 2.2 60 887 3.4 182

Anchorage, AK............................. 8.3 150.8 -0.1 294 1,150 3.4 182

Maricopa, AZ................................ 106.6 2,068.7 3.2 17 1,060 4.5 66

Pima, AZ....................................... 19.3 375.8 0.8 196 934 3.8 132

Benton, AR................................... 6.8 123.5 2.5 45 1,012 4.8 47

Pulaski, AR................................... 14.6 250.4 -0.6 321 961 4.2 93

Washington, AR........................... 6.3 110.8 1.0 171 882 4.5 66

Alameda, CA................................ 66.2 792.6 0.1 274 1,490 4.2 93

Butte, CA..................................... 8.6 83.4 -2.4 351 866 4.8 47

Contra Costa, CA......................... 33.9 368.7 -0.2 301 1,311 4.4 78

Fresno, CA................................... 37.9 409.4 1.5 110 856 3.9 122

Kern, CA....................................... 21.3 347.3 2.5 45 907 3.8 132

Los Angeles, CA........................... 511.6 4,499.4 1.0 171 1,225 3.7 151

Marin, CA..................................... 12.7 116.5 0.9 186 1,328 3.1 212

Merced, CA................................. 6.8 85.6 2.9 31 846 3.5 168

Monterey, CA............................... 14.3 214.1 1.1 153 936 2.4 276

Napa, CA..................................... 6.0 82.6 1.5 110 1,077 4.1 103

Orange, CA.................................. 127.5 1,649.2 1.1 153 1,204 4.3 85

Placer, CA.................................... 13.9 173.1 2.1 64 1,101 4.8 47

Riverside, CA............................... 69.0 756.0 2.4 51 881 4.1 103

Sacramento, CA........................... 61.8 679.6 1.8 84 1,183 4.1 103

San Bernardino, CA..................... 63.4 769.9 1.7 93 927 3.9 122

San Diego, CA.............................. 116.3 1,490.2 1.5 110 1,197 4.1 103

San Francisco, CA....................... 62.0 765.2 3.5 10 2,273 7.6 7

San Joaquin, CA.......................... 18.7 260.7 1.2 142 937 4.6 60

San Luis Obispo, CA.................... 10.7 119.6 1.0 171 946 4.5 66

San Mateo, CA............................. 29.2 419.1 3.1 21 2,366 -0.1 351

Santa Barbara, CA....................... 15.8 209.3 2.6 43 1,041 3.6 157

Santa Clara, CA........................... 75.5 1,121.9 1.8 84 2,447 -0.3 352

Santa Cruz, CA............................ 9.8 109.6 1.3 132 992 5.1 31

Solano, CA................................... 11.9 144.4 0.7 206 1,142 4.4 78

Sonoma, CA................................. 20.6 215.2 1.0 171 1,090 4.3 85

Stanislaus, CA.............................. 16.4 197.5 0.8 196 949 0.2 349

Tulare, CA.................................... 11.5 169.6 0.6 217 787 4.7 55

Ventura, CA.................................. 28.1 328.8 1.0 171 1,065 4.3 85

Yolo, CA....................................... 7.1 108.4 1.8 84 1,199 7.2 10

Adams, CO................................... 11.7 228.9 5.3 2 1,092 3.6 157

Arapahoe, CO.............................. 23.2 335.5 1.6 102 1,284 5.0 38

Boulder, CO.................................. 16.2 189.5 2.9 31 1,547 18.4 1

Denver, CO.................................. 35.4 533.2 2.1 64 1,369 5.1 31

Douglas, CO................................. 12.9 130.9 2.5 45 1,236 6.1 15

El Paso, CO.................................. 21.1 285.0 2.5 45 1,000 4.6 60

Jefferson, CO............................... 21.2 244.3 1.9 76 1,149 4.7 55

Larimer, CO.................................. 12.9 167.3 2.3 54 1,014 5.4 21

Weld, CO...................................... 8.0 115.7 3.8 7 1,052 7.5 8

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 356 largest counties,

third quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-193

Ranking by

percent

change

Third

quarter

2019

Percent

change,

third quarter

2018-193

Ranking by

percent

change

Fairfield, CT................................. 37.0 418.0 -0.6 321 $1,475 0.8 342

Hartford, CT.................................. 29.3 513.3 0.0 284 1,254 3.6 157

New Haven, CT............................ 25.4 370.0 0.2 261 1,092 2.6 261

New London, CT.......................... 7.8 122.9 -1.2 342 1,048 1.4 328

New Castle, DE............................ 21.3 291.8 0.7 206 1,201 3.4 182

Sussex, DE.................................. 7.5 86.1 2.8 35 782 3.2 202

Washington, DC........................... 41.6 776.3 0.6 217 1,851 2.5 267

Alachua, FL.................................. 7.5 134.4 1.0 171 937 2.7 257

Bay, FL......................................... 5.8 74.7 -5.9 355 815 8.7 5

Brevard, FL................................... 16.6 221.8 1.8 84 958 1.9 305

Broward, FL.................................. 72.1 819.4 0.5 226 1,000 4.1 103

Collier, FL..................................... 15.2 145.8 2.2 60 920 4.0 114

Duval, FL..................................... 31.1 525.2 1.7 93 1,008 2.9 238

Escambia, FL............................... 8.4 137.9 1.4 122 856 4.5 66

Hillsborough, FL........................... 45.7 708.0 2.8 35 1,046 3.8 132

Lake, FL....................................... 8.8 101.3 1.9 76 741 2.5 267

Lee, FL......................................... 23.7 264.3 2.1 64 854 3.6 157

Leon, FL....................................... 9.0 152.9 0.6 217 901 4.6 60

Manatee, FL................................. 11.7 128.0 3.1 21 840 4.0 114

Marion, FL.................................... 8.9 105.1 1.9 76 735 3.4 182

Miami-Dade, FL............................ 102.9 1,157.2 1.3 132 1,039 3.6 157

Okaloosa, FL................................ 6.8 85.7 1.9 76 894 5.7 17

Orange, FL................................... 45.5 868.5 1.9 76 958 3.1 212

Osceola, FL.................................. 7.7 99.8 3.2 17 720 1.6 320

Palm Beach, FL............................ 59.0 606.6 1.3 132 1,009 2.3 283

Pasco, FL..................................... 11.7 122.7 1.1 153 775 5.2 25

Pinellas, FL................................... 34.8 438.4 0.8 196 931 3.3 195

Polk, FL........................................ 14.4 228.3 2.7 37 822 2.5 267

St. Johns, FL............................... 8.0 79.0 2.3 54 851 3.0 227

St. Lucie, FL............................... 7.0 79.9 3.0 25 788 1.4 328

Sarasota, FL................................ 16.7 169.5 1.3 132 898 3.9 122

Seminole, FL................................ 15.7 200.2 1.4 122 929 0.9 339

Volusia, FL................................... 15.2 173.5 -0.6 321 763 2.1 292

Bibb, GA....................................... 4.3 82.6 -0.4 308 847 1.7 314

Chatham, GA................................ 8.2 156.8 0.4 238 909 -1.6 354

Clayton, GA.................................. 4.1 123.6 2.3 54 1,100 1.9 305

Cobb, GA...................................... 22.1 375.9 1.6 102 1,131 4.1 103

DeKalb, GA................................. 18.0 301.2 0.7 206 1,099 2.2 288

Forsyth, GA.................................. 6.0 77.5 2.1 64 968 5.2 25

Fulton, GA.................................... 44.5 900.1 1.1 153 1,422 3.6 157

Gwinnett, GA................................ 25.8 362.2 2.0 69 1,007 1.6 320

Hall, GA....................................... 4.6 89.6 0.1 274 915 4.8 47

Muscogee, GA.............................. 4.5 93.6 -0.4 308 850 3.3 195

Richmond, GA.............................. 4.5 104.5 1.4 122 919 3.3 195

Honolulu, HI.................................. 27.4 465.8 -0.5 314 1,059 3.8 132

Maui + Kalawao, HI...................... 6.7 80.0 -0.1 294 906 4.6 60

Ada, ID......................................... 17.6 254.8 3.2 17 970 4.5 66

Champaign, IL.............................. 4.2 91.8 1.1 153 947 3.7 151

Cook, IL........................................ 139.7 2,617.8 0.1 274 1,244 3.8 132

DuPage, IL................................. 34.9 615.9 -0.7 327 1,221 2.8 252

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 356 largest counties,

third quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-193

Ranking by

percent

change

Third

quarter

2019

Percent

change,

third quarter

2018-193

Ranking by

percent

change

Kane, IL........................................ 12.7 213.4 0.5 226 $948 2.6 261

Lake, IL........................................ 20.4 341.4 -0.7 327 1,302 3.3 195

McHenry, IL.................................. 7.9 97.8 -0.9 336 846 2.3 283

McLean, IL.................................... 3.4 82.2 -0.4 308 986 -0.5 353

Madison, IL................................... 5.4 103.2 1.1 153 840 3.8 132

Peoria, IL...................................... 4.2 103.7 -2.6 352 1,066 1.9 305

St. Clair, IL.................................... 5.0 92.7 -0.9 336 859 5.3 22

Sangamon, IL............................... 4.8 131.7 -0.7 327 1,177 12.8 2

Will, IL.......................................... 15.1 250.5 1.7 93 916 3.2 202

Winnebago, IL.............................. 6.0 125.7 -2.0 350 928 3.0 227

Allen, IN........................................ 9.1 191.2 1.1 153 879 3.0 227

Elkhart, IN..................................... 4.8 132.4 -3.8 354 890 0.3 347

Hamilton, IN.................................. 9.8 143.9 1.0 171 1,018 2.5 267

Lake, IN........................................ 10.4 189.4 0.1 274 925 1.5 325

Marion, IN..................................... 24.5 608.7 1.2 142 1,098 4.7 55

St. Joseph, IN............................... 5.8 125.4 0.5 226 891 4.8 47

Tippecanoe, IN............................. 3.5 87.0 1.2 142 924 1.5 325

Vanderburgh, IN........................... 4.8 108.7 -1.0 339 883 5.5 18

Johnson, IA.................................. 4.4 83.8 0.3 246 1,014 1.9 305

Linn, IA......................................... 7.1 132.3 0.7 206 1,010 -2.6 355

Polk, IA........................................ 18.2 303.0 0.9 186 1,078 3.4 182

Scott, IA........................................ 5.8 91.7 0.3 246 891 3.1 212

Johnson, KS................................. 24.3 353.5 1.2 142 1,074 3.1 212

Sedgwick, KS............................... 12.8 257.7 1.7 93 894 1.6 320

Shawnee, KS................................ 5.1 96.0 -0.6 321 872 2.5 267

Wyandotte, KS............................. 3.5 91.7 0.2 261 1,036 4.5 66

Boone, KY................................... 4.5 94.9 1.5 110 917 3.9 122

Fayette, KY................................... 11.3 196.6 1.1 153 938 3.4 182

Jefferson, KY................................ 25.8 472.4 0.5 226 1,037 5.1 31

Caddo, LA.................................... 7.4 110.5 -1.1 341 856 2.0 295

Calcasieu, LA............................... 5.5 100.8 -3.0 353 980 2.0 295

East Baton Rouge, LA.................. 16.4 263.5 -1.6 348 1,010 2.6 261

Jefferson, LA................................ 14.4 188.0 0.0 284 945 3.8 132

Lafayette, LA................................ 10.1 130.6 0.5 226 922 3.1 212

Orleans, LA.................................. 13.6 199.2 1.9 76 993 3.2 202

St. Tammany, LA.......................... 8.8 90.0 1.6 102 899 3.5 168

Cumberland, ME.......................... 13.9 188.1 0.7 206 1,007 4.0 114

Anne Arundel, MD........................ 15.3 274.9 -0.1 294 1,139 4.7 55

Baltimore, MD............................... 21.3 375.9 -0.3 304 1,061 1.3 333

Frederick, MD............................... 6.5 105.3 1.0 171 1,007 5.1 31

Harford, MD.................................. 5.9 94.4 -1.3 344 1,053 3.6 157

Howard, MD................................. 10.1 175.7 1.5 110 1,320 2.9 238

Montgomery, MD.......................... 32.8 473.7 0.3 246 1,404 3.9 122

Prince George's, MD.................... 16.4 318.0 -0.5 314 1,156 5.5 18

Baltimore City, MD....................... 13.7 343.6 -0.7 327 1,239 2.9 238

Barnstable, MA............................. 9.7 102.4 -0.4 308 914 4.3 85

Bristol, MA.................................... 18.1 229.2 0.6 217 973 4.2 93

Essex, MA.................................... 27.6 327.4 0.1 274 1,154 5.2 25

Hampden, MA.............................. 19.0 214.2 0.2 261 947 1.7 314

Middlesex, MA.............................. 57.0 939.3 1.6 102 1,625 4.4 78

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 356 largest counties,

third quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-193

Ranking by

percent

change

Third

quarter

2019

Percent

change,

third quarter

2018-193

Ranking by

percent

change

Norfolk, MA................................... 25.7 352.4 -0.4 308 $1,216 3.7 151

Plymouth, MA............................... 16.6 197.1 0.2 261 1,036 6.1 15

Suffolk, MA................................... 32.1 700.7 2.4 51 1,784 4.3 85

Worcester, MA.............................. 26.7 352.9 0.2 261 1,063 1.9 305

Genesee, MI................................. 7.4 137.9 0.6 217 877 2.3 283

Ingham, MI................................... 6.7 155.4 1.0 171 994 2.2 288

Kalamazoo, MI............................. 5.5 120.7 -0.5 314 993 4.2 93

Kent, MI....................................... 16.3 405.1 0.3 246 960 3.7 151

Macomb, MI.................................. 19.3 331.2 0.3 246 1,049 1.6 320

Oakland, MI.................................. 43.5 745.3 0.0 284 1,165 1.9 305

Ottawa, MI.................................... 6.3 130.2 0.8 196 921 2.8 252

Saginaw, MI.................................. 4.1 84.6 -0.1 294 861 3.2 202

Washtenaw, MI............................. 9.3 221.2 2.0 69 1,179 3.2 202

Wayne, MI.................................... 35.7 736.3 0.4 238 1,150 3.2 202

Anoka, MN.................................... 7.8 128.3 0.7 206 1,094 3.8 132

Dakota, MN.................................. 10.7 191.5 0.0 284 1,057 4.0 114

Hennepin, MN.............................. 41.1 939.0 0.5 226 1,322 2.4 276

Olmsted, MN................................ 3.8 100.7 0.1 274 1,279 3.8 132

Ramsey, MN................................. 14.2 337.0 0.1 274 1,196 2.3 283

St. Louis, MN................................ 5.4 98.0 -1.0 339 915 3.0 227

Stearns, MN................................. 4.4 88.0 0.2 261 943 3.5 168

Washington, MN........................... 6.1 88.2 0.9 186 908 3.1 212

Harrison, MS................................ 4.6 86.9 0.9 186 722 1.1 338

Hinds, MS..................................... 5.7 119.8 0.0 284 910 4.0 114

Boone, MO................................... 5.0 95.2 0.5 226 896 6.7 13

Clay, MO...................................... 5.8 105.3 0.0 284 920 2.0 295

Greene, MO.................................. 9.3 170.8 1.5 110 838 0.8 342

Jackson, MO................................ 22.6 375.6 0.4 238 1,070 2.5 267

St. Charles, MO............................ 9.8 153.8 3.0 25 862 2.9 238

St. Louis, MO................................ 40.5 609.5 0.3 246 1,131 4.3 85

St. Louis City, MO........................ 15.1 231.4 0.3 246 1,172 4.7 55

Yellowstone, MT........................... 6.7 82.8 0.4 238 919 3.5 168

Douglas, NE................................. 19.3 341.7 0.9 186 1,027 3.8 132

Lancaster, NE............................... 10.3 172.6 0.2 261 891 4.0 114

Clark, NV..................................... 57.0 1,025.9 2.3 54 950 3.9 122

Washoe, NV................................. 15.3 227.3 1.4 122 1,007 4.1 103

Hillsborough, NH.......................... 12.3 205.5 0.5 226 1,146 3.0 227

Merrimack, NH............................. 5.3 78.0 0.3 246 1,018 2.9 238

Rockingham, NH.......................... 11.2 153.0 1.1 153 1,048 3.8 132

Atlantic, NJ................................... 6.6 130.8 -1.2 342 877 2.7 257

Bergen, NJ................................... 33.5 446.3 1.0 171 1,238 3.3 195

Burlington, NJ............................... 11.1 201.9 0.3 246 1,096 3.1 212

Camden, NJ................................. 12.2 206.5 -0.1 294 1,038 5.2 25

Essex, NJ.................................... 20.9 345.9 0.9 186 1,330 5.0 38

Gloucester, NJ.............................. 6.4 114.5 2.9 31 890 1.4 328

Hudson, NJ................................... 15.4 268.8 1.0 171 1,384 0.4 345

Mercer, NJ.................................... 11.3 260.1 1.1 153 1,296 3.0 227

Middlesex, NJ.............................. 22.7 432.4 0.3 246 1,216 3.1 212

Monmouth, NJ.............................. 20.4 265.2 0.7 206 1,032 1.3 333

Morris, NJ..................................... 17.3 294.5 0.7 206 1,534 4.5 66

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 356 largest counties,

third quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-193

Ranking by

percent

change

Third

quarter

2019

Percent

change,

third quarter

2018-193

Ranking by

percent

change

Ocean, NJ.................................... 13.8 174.8 2.0 69 $850 3.5 168

Passaic, NJ.................................. 12.6 166.6 1.0 171 1,005 1.7 314

Somerset, NJ............................... 10.3 188.7 -0.3 304 1,518 1.6 320

Union, NJ..................................... 14.7 228.0 0.7 206 1,272 0.3 347

Bernalillo, NM............................... 20.2 334.8 1.2 142 939 4.4 78

Albany, NY................................... 10.2 233.8 -0.7 327 1,122 4.3 85

Bronx, NY..................................... 18.8 324.0 1.1 153 1,131 4.5 66

Broome, NY.................................. 4.3 85.6 -1.3 344 887 5.2 25

Dutchess, NY............................... 8.3 113.8 0.0 284 1,041 3.8 132

Erie, NY........................................ 24.2 473.4 -0.7 327 953 2.9 238

Kings, NY..................................... 63.1 796.4 1.1 153 953 4.2 93

Monroe, NY.................................. 18.6 391.4 0.0 284 1,009 4.5 66

Nassau, NY.................................. 53.3 628.3 0.1 274 1,162 3.2 202

New York, NY............................... 125.9 2,515.1 1.2 142 2,055 2.9 238

Oneida, NY................................... 5.2 105.2 0.5 226 838 3.5 168

Onondaga, NY.............................. 12.6 249.2 0.3 246 997 3.9 122

Orange, NY.................................. 10.4 147.8 0.8 196 918 5.0 38

Queens, NY.................................. 52.8 718.6 1.3 132 1,076 2.9 238

Richmond, NY.............................. 9.8 127.8 4.7 3 1,028 2.8 252

Rockland, NY............................... 10.9 130.3 3.5 10 998 2.0 295

Saratoga, NY................................ 5.9 89.5 -0.4 308 978 1.9 305

Suffolk, NY................................... 52.7 669.2 0.0 284 1,158 3.1 212

Westchester, NY.......................... 35.5 428.7 -0.6 321 1,308 2.5 267

Buncombe, NC............................. 9.8 135.1 1.0 171 846 3.3 195

Cabarrus, NC............................... 4.9 76.6 2.0 69 806 5.2 25

Catawba, NC................................ 4.5 88.5 -0.5 314 830 3.2 202

Cumberland, NC........................... 6.2 119.9 1.5 110 848 2.8 252

Durham, NC................................. 8.6 211.5 4.1 5 1,327 1.9 305

Forsyth, NC.................................. 9.4 191.1 1.8 84 967 2.5 267

Guilford, NC.................................. 14.7 285.0 0.3 246 925 2.0 295

Mecklenburg, NC.......................... 39.4 716.8 2.7 37 1,214 3.6 157

New Hanover, NC........................ 8.6 117.8 5.8 1 873 1.4 328

Pitt, NC....................................... 3.8 77.7 1.5 110 906 4.6 60

Wake, NC..................................... 36.3 574.6 3.3 15 1,157 5.3 22

Cass, ND...................................... 7.3 121.5 1.5 110 991 3.7 151

Butler, OH..................................... 8.1 158.3 0.6 217 945 3.5 168

Cuyahoga, OH.............................. 36.3 731.6 0.2 261 1,084 3.1 212

Delaware, OH............................... 5.6 89.5 0.4 238 1,046 4.5 66

Franklin, OH................................. 33.9 764.2 0.6 217 1,096 2.5 267

Greene, OH.................................. 3.7 76.5 1.6 102 1,081 3.0 227

Hamilton, OH................................ 24.4 523.1 0.5 226 1,186 6.4 14

Lake, OH...................................... 6.3 97.4 1.7 93 913 9.9 4

Lorain, OH.................................... 6.3 99.0 1.1 153 823 0.9 339

Lucas, OH.................................... 10.2 208.8 0.2 261 933 1.5 325

Mahoning, OH.............................. 5.9 98.2 -0.1 294 767 2.0 295

Montgomery, OH.......................... 12.1 255.8 0.0 284 925 2.8 252

Stark, OH..................................... 8.7 159.1 -0.5 314 810 2.0 295

Summit, OH................................. 14.5 267.4 -0.2 301 927 1.2 336

Warren, OH................................. 5.3 97.7 2.4 51 1,144 7.2 10

Cleveland, OK.............................. 6.0 86.3 3.8 7 777 2.0 295

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 356 largest counties,

third quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-193

Ranking by

percent

change

Third

quarter

2019

Percent

change,

third quarter

2018-193

Ranking by

percent

change

Oklahoma, OK.............................. 28.5 465.6 0.8 196 $1,000 2.6 261

Tulsa, OK..................................... 22.8 364.0 1.3 132 969 2.9 238

Clackamas, OR............................ 15.7 170.5 2.0 69 1,040 3.1 212

Deschutes, OR............................. 9.3 86.7 2.5 45 907 5.1 31

Jackson, OR................................ 7.9 92.0 0.2 261 849 3.8 132

Lane, OR...................................... 12.8 158.6 0.4 238 856 3.5 168

Marion, OR................................... 11.5 161.8 1.5 110 908 3.9 122

Multnomah, OR............................ 36.7 519.9 1.4 122 1,159 2.9 238

Washington, OR........................... 20.5 304.3 1.7 93 1,371 3.4 182

Allegheny, PA............................... 35.9 704.8 0.3 246 1,147 3.4 182

Berks, PA..................................... 9.0 176.2 0.8 196 967 1.3 333

Bucks, PA..................................... 20.4 269.5 1.2 142 981 1.9 305

Butler, PA..................................... 5.1 87.8 0.7 206 995 0.4 345

Chester, PA.................................. 15.8 254.0 1.2 142 1,271 1.4 328

Cumberland, PA........................... 6.6 136.7 1.0 171 981 2.0 295

Dauphin, PA................................ 7.5 186.5 0.7 206 1,063 4.0 114

Delaware, PA............................... 14.2 227.3 0.9 186 1,105 2.4 276

Erie, PA........................................ 7.0 122.6 -0.9 336 816 3.0 227

Lackawanna, PA.......................... 5.6 97.2 -0.8 333 813 2.3 283

Lancaster, PA............................... 13.8 246.2 1.1 153 908 3.5 168

Lehigh, PA.................................... 8.9 196.5 0.9 186 1,045 3.7 151

Luzerne, PA.................................. 7.5 146.1 0.2 261 848 2.0 295

Montgomery, PA........................... 28.0 505.4 1.3 132 1,287 3.5 168

Northampton, PA.......................... 6.9 119.0 1.8 84 905 1.7 314

Philadelphia, PA........................... 35.2 704.1 1.6 102 1,290 4.5 66

Washington, PA............................ 5.6 88.6 -0.2 301 1,047 1.7 314

Westmoreland, PA....................... 9.3 134.6 0.3 246 889 2.7 257

York, PA....................................... 9.2 180.9 0.2 261 939 2.7 257

Kent, RI....................................... 5.6 76.4 0.1 274 939 2.6 261

Providence, RI.............................. 18.8 290.7 0.3 246 1,011 2.1 292

Charleston, SC............................. 17.1 258.9 3.0 25 965 4.8 47

Greenville, SC.............................. 15.4 279.0 1.7 93 910 2.1 292

Horry, SC..................................... 9.8 135.2 3.2 17 660 4.3 85

Lexington, SC............................... 7.2 122.0 2.7 37 841 5.1 31

Richland, SC................................ 10.8 225.6 1.3 132 923 3.5 168

Spartanburg, SC........................... 6.7 147.0 2.7 37 889 2.9 238

York, SC....................................... 6.5 100.6 4.4 4 876 3.8 132

Minnehaha, SD............................. 7.7 128.8 0.9 186 946 2.4 276

Davidson, TN................................ 24.8 520.0 3.4 14 1,179 4.1 103

Hamilton, TN................................ 10.4 209.4 1.3 132 963 4.2 93

Knox, TN...................................... 13.1 241.4 0.8 196 936 2.4 276

Rutherford, TN.............................. 6.1 134.4 1.4 122 939 3.8 132

Shelby, TN.................................... 21.2 504.1 0.8 196 1,061 0.2 349

Williamson, TN............................. 9.7 141.3 3.7 9 1,251 4.1 103

Bell, TX......................................... 5.7 120.9 1.3 132 916 4.2 93

Bexar, TX..................................... 43.4 878.4 1.2 142 965 3.8 132

Brazoria, TX................................. 6.1 116.6 2.0 69 1,095 0.9 339

Brazos, TX.................................... 4.7 109.2 2.2 60 815 3.6 157

Cameron, TX................................ 6.6 141.5 1.5 110 659 4.9 42

Collin, TX...................................... 27.4 432.0 3.0 25 1,278 3.1 212

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 356 largest counties,

third quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-193

Ranking by

percent

change

Third

quarter

2019

Percent

change,

third quarter

2018-193

Ranking by

percent

change

Dallas, TX..................................... 79.3 1,750.7 2.7 37 $1,303 4.9 42

Denton, TX.................................. 16.3 260.9 3.5 10 962 3.0 227

Ector, TX..................................... 4.2 81.1 -1.3 344 1,227 2.4 276

El Paso, TX.................................. 15.6 312.9 1.4 122 765 4.2 93

Fort Bend, TX............................... 14.5 195.8 2.2 60 977 3.5 168

Galveston, TX............................... 6.3 110.1 0.9 186 959 4.1 103

Harris, TX..................................... 117.9 2,350.4 1.9 76 1,315 3.1 212

Hidalgo, TX................................... 12.7 265.0 2.3 54 683 3.6 157

Jefferson, TX................................ 5.9 123.1 1.9 76 1,084 3.5 168

Lubbock, TX................................. 7.8 141.6 1.1 153 861 4.1 103

McLennan, TX.............................. 5.5 114.4 1.4 122 892 4.4 78

Midland, TX.................................. 6.1 107.7 0.5 226 1,459 3.4 182

Montgomery, TX........................... 12.4 192.0 2.6 43 1,061 4.2 93

Nueces, TX.................................. 8.3 163.4 1.1 153 937 2.9 238

Potter, TX..................................... 4.0 77.1 1.6 102 888 3.3 195

Smith, TX..................................... 6.4 103.4 0.4 238 893 5.1 31

Tarrant, TX................................... 45.5 923.3 1.6 102 1,079 4.9 42

Travis, TX..................................... 43.9 779.9 3.1 21 1,312 4.8 47

Webb, TX..................................... 5.6 103.0 0.8 196 712 2.2 288

Williamson, TX............................. 11.9 181.4 3.9 6 1,143 12.3 3

Davis, UT..................................... 9.0 134.7 2.3 54 873 3.8 132

Salt Lake, UT................................ 49.1 726.1 2.7 37 1,081 4.5 66

Utah, UT....................................... 18.1 255.1 3.3 15 914 7.4 9

Weber, UT.................................... 6.4 109.3 3.0 25 831 2.6 261

Chittenden, VT............................. 7.2 103.3 0.2 261 1,065 5.0 38

Arlington, VA................................ 9.1 182.9 2.5 45 1,744 3.0 227

Chesterfield, VA........................... 9.4 135.4 1.1 153 926 4.4 78

Fairfax, VA.................................... 36.6 622.2 1.5 110 1,651 4.0 114

Henrico, VA.................................. 11.8 191.7 -0.5 314 1,023 3.9 122

Loudoun, VA................................ 12.6 174.8 2.9 31 1,228 0.5 344

Prince William, VA........................ 9.6 132.8 1.0 171 960 3.4 182

Alexandria City, VA...................... 6.2 89.5 -1.6 348 1,505 3.4 182

Chesapeake City, VA................... 6.2 101.1 1.4 122 860 4.2 93

Newport News City, VA................ 3.9 103.3 1.2 142 1,019 4.9 42

Norfolk City, VA........................... 6.1 139.6 0.1 274 1,063 4.6 60

Richmond City, VA....................... 8.0 158.7 1.8 84 1,198 6.8 12

Virginia Beach City, VA................ 12.3 177.9 0.6 217 823 3.9 122

Benton, WA.................................. 6.1 94.3 3.5 10 1,099 2.4 276

Clark, WA..................................... 15.5 165.5 1.7 93 1,060 4.8 47

King, WA...................................... 90.7 1,445.3 3.1 21 1,814 3.6 157

Kitsap, WA.................................... 7.0 92.4 2.1 64 1,014 3.4 182

Pierce, WA................................... 23.5 320.3 1.7 93 1,039 5.3 22

Snohomish, WA............................ 21.9 293.3 2.0 69 1,167 3.8 132

Spokane, WA............................... 16.8 231.0 1.8 84 953 4.4 78

Thurston, WA............................... 8.7 119.4 1.2 142 1,051 5.5 18

Whatcom, WA.............................. 7.4 91.5 0.6 217 932 3.8 132

Yakima, WA................................. 8.1 127.1 1.4 122 790 3.1 212

Kanawha, WV............................... 5.7 96.3 -1.5 347 950 3.5 168

Brown, WI..................................... 7.4 159.1 -0.6 321 947 3.2 202

Dane, WI...................................... 16.6 342.3 1.8 84 1,062 3.2 202

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 356 largest counties,

third quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-193

Ranking by

percent

change

Third

quarter

2019

Percent

change,

third quarter

2018-193

Ranking by

percent

change

Milwaukee, WI.............................. 28.3 488.2 -0.5 314 $1,008 3.0 227

Outagamie, WI............................. 5.7 108.7 -0.3 304 917 2.2 288

Racine, WI................................. 4.8 75.5 -0.3 304 910 1.2 336

Waukesha, WI.............................. 14.0 246.3 0.4 238 1,054 3.1 212

Winnebago, WI............................. 4.0 92.7 -0.1 294 968 3.4 182

San Juan, PR............................... 11.4 242.9 1.7 (5) 637 -0.9 (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,

third quarter 2019

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-192

Third

quarter

2019

Percent

change,

third quarter

2018-192

United States3................................................................. 10,325.3 148,556.5 1.1 $1,093 3.6

 Private industry............................................................. 10,022.4 126,655.3 1.2 1,086 3.7

 Natural resources and mining.................................... 140.3 2,036.2 -0.4 1,112 3.8

 Construction............................................................... 838.1 7,646.3 2.5 1,224 3.7

 Manufacturing............................................................ 357.2 12,774.8 0.3 1,269 1.7

 Trade, transportation, and utilities.............................. 1,948.8 27,339.7 0.4 924 3.9

 Information................................................................. 186.8 2,839.0 1.5 2,221 2.7

 Financial activities...................................................... 919.6 8,328.4 1.4 1,614 3.7

 Professional and business services........................... 1,921.0 21,301.3 1.3 1,419 4.3

 Education and health services................................... 1,775.3 23,112.6 1.8 996 3.4

 Leisure and hospitality............................................... 885.7 16,576.0 1.1 479 5.0

 Other services............................................................ 865.5 4,530.8 1.1 760 4.1

 Government.................................................................. 302.9 21,901.2 0.8 1,135 3.2

Los Angeles, CA.............................................................. 511.6 4,499.4 1.0 1,225 3.7

 Private industry............................................................. 505.2 3,927.0 1.3 1,184 3.6

 Natural resources and mining.................................... 0.5 6.6 1.5 1,082 -3.0

 Construction............................................................... 17.1 150.8 2.1 1,323 5.8

 Manufacturing............................................................ 12.8 337.8 -0.4 1,354 1.8

 Trade, transportation, and utilities.............................. 59.6 835.1 -0.6 1,015 4.9

 Information................................................................. 13.3 203.0 4.3 2,455 1.3

 Financial activities...................................................... 30.4 221.8 -0.2 1,857 2.5

 Professional and business services........................... 56.8 638.9 1.7 1,481 2.3

 Education and health services................................... 245.2 832.8 2.9 926 3.7

 Leisure and hospitality............................................... 39.5 546.4 1.6 705 7.1

 Other services............................................................ 29.5 153.5 0.9 829 10.4

 Government.................................................................. 6.5 572.4 -0.5 1,515 4.3

Cook, IL........................................................................... 139.7 2,617.8 0.1 1,244 3.8

 Private industry............................................................. 138.4 2,320.0 0.1 1,251 3.8

 Natural resources and mining.................................... 0.1 1.5 7.5 1,210 4.8

 Construction............................................................... 11.2 81.0 2.2 1,538 3.0

 Manufacturing............................................................ 5.7 183.6 0.1 1,276 2.7

 Trade, transportation, and utilities.............................. 28.5 468.6 -0.5 1,036 5.1

 Information................................................................. 2.6 53.7 3.0 2,027 3.9

 Financial activities...................................................... 14.1 207.4 1.6 2,161 1.4

 Professional and business services........................... 29.4 480.9 -0.6 1,565 3.9

 Education and health services................................... 15.6 451.3 0.0 1,058 3.6

 Leisure and hospitality............................................... 14.0 295.9 0.8 597 6.4

 Other services............................................................ 16.2 95.8 -2.5 976 3.7

 Government.................................................................. 1.3 297.8 0.6 1,186 3.1

New York, NY.................................................................. 125.9 2,515.1 1.2 2,055 2.9

 Private industry............................................................. 124.4 2,282.2 1.2 2,101 3.0

 Natural resources and mining.................................... 0.0 0.3 18.1 2,060 9.0

 Construction............................................................... 2.4 43.8 -3.2 1,949 2.5

 Manufacturing............................................................ 1.8 21.8 -4.2 1,513 1.5

 Trade, transportation, and utilities.............................. 18.3 251.0 -1.0 1,460 2.4

 Information................................................................. 5.1 182.5 3.8 2,851 -1.7

 Financial activities...................................................... 19.2 388.5 2.1 3,437 2.1

 Professional and business services........................... 27.5 618.5 1.1 2,395 4.1

 Education and health services................................... 10.1 358.3 1.7 1,435 3.9

 Leisure and hospitality............................................... 14.6 308.6 0.8 993 6.1

 Other services............................................................ 19.5 105.4 1.0 1,252 -1.8

 Government.................................................................. 1.4 232.9 1.2 1,599 2.4

 See footnotes at end of table.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,

third quarter 2019 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-192

Third

quarter

2019

Percent

change,

third quarter

2018-192

Harris, TX........................................................................ 117.9 2,350.4 1.9 $1,315 3.1

 Private industry............................................................. 117.3 2,073.8 1.9 1,325 3.2

 Natural resources and mining.................................... 1.6 67.0 -0.6 3,247 7.4

 Construction............................................................... 7.8 173.8 5.7 1,379 2.8

 Manufacturing............................................................ 4.9 180.7 1.8 1,591 0.2

 Trade, transportation, and utilities.............................. 25.2 468.8 0.3 1,189 3.2

 Information................................................................. 1.2 26.1 2.4 1,564 2.8

 Financial activities...................................................... 12.8 130.8 2.7 1,691 3.2

 Professional and business services........................... 23.7 411.2 1.8 1,645 2.1

 Education and health services................................... 16.7 303.1 1.4 1,067 4.0

 Leisure and hospitality............................................... 10.6 241.7 2.7 514 7.5

 Other services............................................................ 11.8 68.9 2.1 849 4.6

 Government.................................................................. 0.6 276.6 1.8 1,241 3.3

Maricopa, AZ.................................................................... 106.6 2,068.7 3.2 1,060 4.5

 Private industry............................................................. 105.9 1,851.0 3.5 1,050 4.6

 Natural resources and mining.................................... 0.5 7.5 2.5 1,035 4.2

 Construction............................................................... 8.6 133.0 7.4 1,157 5.4

 Manufacturing............................................................ 3.5 129.4 3.0 1,391 3.6

 Trade, transportation, and utilities.............................. 20.8 388.9 1.5 955 3.1

 Information................................................................. 2.2 38.2 3.1 1,460 -0.5

 Financial activities...................................................... 13.7 192.4 4.0 1,405 9.3

 Professional and business services........................... 26.4 352.4 3.9 1,124 4.7

 Education and health services................................... 13.4 331.1 4.5 1,050 3.3

 Leisure and hospitality............................................... 9.1 223.2 2.4 524 4.0

 Other services............................................................ 7.0 54.4 1.9 794 6.4

 Government.................................................................. 0.7 217.7 1.5 1,147 3.2

Dallas, TX........................................................................ 79.3 1,750.7 2.7 1,303 4.9

 Private industry............................................................. 78.8 1,573.6 2.8 1,312 5.1

 Natural resources and mining.................................... 0.5 9.4 4.2 3,581 7.0

 Construction............................................................... 4.9 93.0 3.5 1,323 2.0

 Manufacturing............................................................ 2.9 119.1 4.1 1,587 7.5

 Trade, transportation, and utilities.............................. 16.4 353.9 1.8 1,146 4.5

 Information................................................................. 1.4 45.9 -0.3 1,983 6.0

 Financial activities...................................................... 9.9 168.0 3.1 1,767 4.1

 Professional and business services........................... 18.0 366.8 3.7 1,532 6.5

 Education and health services................................... 9.9 204.7 1.6 1,134 3.0

 Leisure and hospitality............................................... 7.2 167.9 3.6 551 7.2

 Other services............................................................ 7.1 43.7 1.4 854 2.3

 Government.................................................................. 0.5 177.1 1.4 1,220 2.4

Orange, CA...................................................................... 127.5 1,649.2 1.1 1,204 4.3

 Private industry............................................................. 126.1 1,499.5 1.0 1,194 4.5

 Natural resources and mining.................................... 0.2 2.3 -6.5 912 3.1

 Construction............................................................... 7.8 107.6 -0.7 1,469 4.9

 Manufacturing............................................................ 5.3 159.1 -0.7 1,512 2.4

 Trade, transportation, and utilities.............................. 18.6 255.6 -0.6 1,067 4.2

 Information................................................................. 1.6 25.5 -2.4 2,133 1.8

 Financial activities...................................................... 13.1 116.7 0.2 1,997 10.7

 Professional and business services........................... 23.8 327.4 2.1 1,349 4.4

 Education and health services................................... 38.0 228.5 3.6 996 3.4

 Leisure and hospitality............................................... 9.8 228.5 1.4 538 3.7

 Other services............................................................ 7.7 48.3 0.9 769 6.1

 Government.................................................................. 1.4 149.7 2.4 1,318 3.1

 See footnotes at end of table.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,

third quarter 2019 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-192

Third

quarter

2019

Percent

change,

third quarter

2018-192

San Diego, CA................................................................ 116.3 1,490.2 1.5 $1,197 4.1

 Private industry............................................................. 114.2 1,254.7 1.6 1,160 3.8

 Natural resources and mining.................................... 0.7 10.5 8.9 799 2.2

 Construction............................................................... 8.0 85.7 1.0 1,302 6.0

 Manufacturing............................................................ 3.6 115.3 2.1 1,630 4.0

 Trade, transportation, and utilities.............................. 15.5 221.2 -0.1 907 4.9

 Information................................................................. 1.4 23.1 -2.1 2,492 9.6

 Financial activities...................................................... 11.2 76.2 0.7 1,552 6.0

 Professional and business services........................... 21.2 255.2 2.7 1,626 1.3

 Education and health services................................... 35.0 211.2 3.3 996 3.0

 Leisure and hospitality............................................... 9.3 203.2 0.7 546 4.6

 Other services............................................................ 8.3 52.9 1.3 681 3.3

 Government.................................................................. 2.0 235.5 1.2 1,401 5.2

King, WA......................................................................... 90.7 1,445.3 3.1 1,814 3.6

 Private industry............................................................. 90.0 1,275.1 3.4 1,855 3.4

 Natural resources and mining.................................... 0.4 3.0 -3.0 1,288 -7.9

 Construction............................................................... 7.0 76.7 1.6 1,500 5.5

 Manufacturing............................................................ 2.5 105.6 2.6 1,650 3.0

 Trade, transportation, and utilities.............................. 13.7 279.1 3.3 1,750 3.2

 Information................................................................. 2.6 124.5 8.1 5,367 -2.7

 Financial activities...................................................... 6.8 71.7 1.7 1,812 6.8

 Professional and business services........................... 18.6 238.6 3.7 1,873 5.3

 Education and health services................................... 21.6 181.0 2.9 1,108 4.2

 Leisure and hospitality............................................... 7.5 146.9 1.6 644 3.2

 Other services............................................................ 9.3 48.1 5.4 939 7.2

 Government.................................................................. 0.6 170.1 0.9 1,507 4.9

Miami-Dade, FL............................................................... 102.9 1,157.2 1.3 1,039 3.6

 Private industry............................................................. 102.6 1,017.7 1.5 1,008 3.7

 Natural resources and mining.................................... 0.5 8.5 5.9 679 -0.7

 Construction............................................................... 7.3 52.3 2.6 1,012 2.7

 Manufacturing............................................................ 2.8 41.8 2.2 937 3.2

 Trade, transportation, and utilities.............................. 24.6 287.6 0.9 941 3.6

 Information................................................................. 1.6 19.2 3.8 1,610 -2.4

 Financial activities...................................................... 11.1 75.7 0.3 1,596 6.3

 Professional and business services........................... 23.8 165.2 2.7 1,201 2.1

 Education and health services................................... 11.6 185.2 1.5 1,024 4.3

 Leisure and hospitality............................................... 7.7 142.4 0.8 633 4.6

 Other services............................................................ 8.8 38.2 -1.1 676 4.3

 Government.................................................................. 0.3 139.5 0.5 1,277 3.2

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,

third quarter 2019

Employment Average weekly wage 1

State

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-19

Third

quarter

2019

Percent

change,

third quarter

2018-19

United States2.......................................... 10,325.3 148,556.5 1.1 $1,093 3.6

Alabama.................................................... 130.9 1,989.5 1.1 919 3.8

Alaska........................................................ 22.4 338.0 1.2 1,105 3.7

Arizona...................................................... 168.0 2,913.4 2.6 1,018 4.5

Arkansas................................................... 92.3 1,222.8 0.0 841 3.8

California................................................... 1,608.8 17,713.1 1.4 1,309 3.8

Colorado.................................................... 212.1 2,749.0 2.4 1,170 6.1

Connecticut............................................... 123.6 1,676.6 -0.3 1,236 2.3

Delaware................................................... 34.4 453.2 1.1 1,078 3.3

District of Columbia................................... 41.6 776.4 0.6 1,851 2.5

Florida....................................................... 724.8 8,838.2 1.7 955 3.4

Georgia...................................................... 289.8 4,509.7 1.4 1,026 3.4

Hawaii........................................................ 44.9 654.1 -0.3 1,012 3.9

Idaho......................................................... 68.3 765.2 2.9 838 4.1

Illinois........................................................ 380.6 6,023.1 0.0 1,125 3.6

Indiana....................................................... 168.5 3,083.5 0.3 914 3.5

Iowa........................................................... 104.5 1,556.9 0.1 914 3.0

Kansas...................................................... 89.8 1,395.9 0.4 893 2.9

Kentucky.................................................... 122.9 1,910.8 0.7 884 3.4

Louisiana................................................... 136.0 1,913.5 -0.3 923 2.6

Maine......................................................... 54.3 632.6 0.9 887 4.2

Maryland.................................................... 173.6 2,696.9 0.2 1,169 3.6

Massachusetts.......................................... 264.1 3,642.5 0.9 1,359 4.2

Michigan.................................................... 268.2 4,375.8 0.2 1,021 3.0

Minnesota.................................................. 180.6 2,917.8 0.4 1,107 3.0

Mississippi................................................. 74.6 1,135.8 0.1 768 2.7

Missouri..................................................... 209.8 2,826.5 0.6 942 3.9

Montana.................................................... 50.6 478.9 1.2 848 3.9

Nebraska................................................... 73.3 984.7 0.3 908 4.0

Nevada...................................................... 84.6 1,412.2 2.1 973 4.1

New Hampshire......................................... 54.2 667.9 0.8 1,075 3.4

New Jersey............................................... 278.1 4,104.0 0.9 1,217 3.0

New Mexico............................................... 62.8 842.1 1.7 899 5.1

New York.................................................. 651.0 9,575.4 1.1 1,314 3.3

North Carolina........................................... 287.7 4,501.3 2.2 972 3.6

North Dakota............................................. 31.9 428.4 0.9 1,028 3.3

Ohio........................................................... 302.1 5,443.3 0.3 976 3.1

Oklahoma.................................................. 111.8 1,628.8 0.5 897 2.6

Oregon...................................................... 160.7 1,970.7 1.4 1,037 3.2

Pennsylvania............................................. 363.4 5,947.9 0.8 1,064 3.2

Rhode Island............................................. 38.9 491.3 0.6 991 2.8

South Carolina.......................................... 141.1 2,132.4 2.2 866 3.7

South Dakota............................................ 34.3 433.4 0.4 855 3.4

Tennessee................................................. 167.8 3,060.8 1.9 966 2.8

Texas......................................................... 713.5 12,603.2 2.1 1,109 4.1

Utah........................................................... 109.1 1,535.2 2.8 954 4.8

Vermont..................................................... 26.1 311.0 0.0 927 4.3

Virginia...................................................... 279.6 3,931.4 1.0 1,125 4.0

Washington............................................... 252.6 3,489.8 2.1 1,335 4.3

West Virginia............................................. 51.6 694.4 -1.8 897 0.3

Wisconsin.................................................. 182.2 2,893.8 0.1 929 3.1

 See footnotes at end of table.
Table 3. Covered establishments, employment, and wages by state,

third quarter 2019 - Continued

Employment Average weekly wage 1

State

Establishments,

third quarter

2019

(thousands)

September

2019

(thousands)

Percent

change,

September

2018-19

Third

quarter

2019

Percent

change,

third quarter

2018-19

Wyoming................................................... 27.0 283.1 1.5 $942 4.2

Puerto Rico............................................... 47.9 878.9 1.9 528 -0.8

Virgin Islands............................................ 3.3 37.8 9.6 1,012 12.8

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.