For release 10:00 a.m. (EDT), Wednesday, May 20, 2020 USDL-20-1012 

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

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

COUNTY EMPLOYMENT AND WAGES – FOURTH QUARTER 2019 

From December 2018 to December 2019, employment increased in 285 of the 355 largest U.S. 

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

employment (as measured by the QCEW program) increased to 149.9 million, a 1.2 percent 

increase over the year. Cleveland, OK, had the largest over-the-year increase in employment 

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

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

Among the 355 largest counties, 341 had over-the-year increases in average weekly wages. In 

the fourth quarter of 2019, average weekly wages for the nation increased to $1,185, a 3.5 

percent increase over the year. Santa Cruz, CA, had the largest fourth quarter over-the-year wage 

gain at 20.7 percent. (See table 1.)

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

losses

-5% -3% -1% 1% 3% 5%

Ector, TX

Elkhart, IN

Calcasieu, LA

Peoria, IL

Midland, TX

Richmond, NY

Maricopa, AZ

Travis, TX

Benton, WA

Williamson, TX

St. Charles, MO

York, SC

Lexington, SC

Adams, CO

Cleveland, OK
- 2 - 

Large County Employment in December 2019 

Cleveland, OK, had the largest over-the-year percentage increase in employment (5.8 percent). 

Within Cleveland, the largest employment increase occurred in trade, transportation, and 

utilities, which gained 4,579 jobs over the year (28.7 percent).

Ector, TX, experienced the largest over-the-year percentage decrease in employment, with a loss

of 4.2 percent. Within Ector, natural resources and mining had the largest employment decrease 

with a loss of 2,297 jobs (-15.2 percent). 

Large County Average Weekly Wage in Fourth Quarter 2019 

Santa Cruz, CA, had the largest over-the-year percentage increase in average weekly wages (20.7 

percent). Within Santa Cruz, an average weekly wage gain of $1,679 (109.0 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 7.1 percent. Within Linn, manufacturing had the largest impact, with an average weekly wage 

decrease of $646 (-27.7 percent) over the year.

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

largest gains and losses 

-8% -6% -4% -2% 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20%

Linn, IA

Tippecanoe, IN

Williamson, TN

Wake, NC

Brazoria, TX

Genesee, MI

King, WA

Union, NJ

San Luis Obispo, CA

San Mateo, CA

Boone, MO

Clay, MO

Douglas, CO

Williamson, TX

Santa Cruz, CA
- 3 - 

Ten Largest Counties

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

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

percentage gain among the 10 largest counties (3.5 percent). Within Maricopa, education and 

health services had the largest employment increase with a gain of 14,967 jobs (4.6 percent). 

(See table 2.)

In fourth quarter 2019, King, WA, experienced the largest over-the-year percentage gain in 

average weekly wages among the 10 largest counties (7.8 percent). Within King, information had 

the largest impact, with an average weekly wage increase of $336 (9.4 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. December 2019 

employment and fourth 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 fourth quarter 2019 is scheduled

to be released on Wednesday, June 3, 2020, at 10:00 a.m. (EDT). 

The County Employment and Wages news release for first quarter 2020 is scheduled to be 

released on Wednesday, August 19, 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,

fourth quarter 2019

Employment Average weekly wage 2

County1

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-193

Ranking by

percent

change

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-193

Ranking by

percent

change

United States4.............................. 10,384.1 149,857.1 1.2 - $1,185 3.5 -

Jefferson, AL................................ 19.4 358.0 0.7 204 1,142 0.8 336

Madison, AL................................. 10.1 210.6 3.0 20 1,238 5.0 45

Mobile, AL.................................... 10.4 174.3 0.0 286 1,001 1.9 293

Montgomery, AL........................... 6.5 131.0 -0.6 322 996 3.4 161

Shelby, AL.................................... 6.0 85.6 -0.3 303 1,099 1.4 322

Tuscaloosa, AL............................. 4.7 98.4 1.7 94 939 2.4 255

Anchorage, AK............................. 8.3 147.0 -0.5 314 1,199 3.3 172

Maricopa, AZ................................ 108.0 2,132.1 3.5 9 1,108 4.0 109

Pima, AZ....................................... 19.3 382.6 0.4 241 971 4.9 49

Benton, AR................................... 6.9 125.5 3.0 20 1,113 4.0 109

Pulaski, AR................................... 14.7 253.3 -0.5 314 1,010 3.0 203

Washington, AR........................... 6.4 111.6 1.8 86 1,009 3.0 203

Alameda, CA................................ 66.7 798.9 0.1 273 1,577 3.5 149

Butte, CA..................................... 8.6 82.8 0.0 286 907 4.6 60

Contra Costa, CA......................... 34.3 371.6 0.1 273 1,415 1.7 304

Fresno, CA................................... 38.3 401.8 2.2 59 942 4.4 71

Kern, CA....................................... 21.6 331.4 1.1 160 967 4.8 53

Los Angeles, CA........................... 518.6 4,589.5 1.2 144 1,437 4.1 98

Marin, CA..................................... 12.8 118.3 1.6 104 1,499 2.3 261

Merced, CA................................. 6.9 79.0 0.1 273 888 4.1 98

Monterey, CA............................... 14.4 181.3 0.4 241 1,001 4.1 98

Napa, CA..................................... 6.0 76.8 0.6 220 1,188 2.6 234

Orange, CA.................................. 129.4 1,664.7 0.8 199 1,297 4.6 60

Placer, CA.................................... 14.0 174.1 2.0 73 1,182 5.5 27

Riverside, CA............................... 70.1 779.7 3.0 20 918 4.2 91

Sacramento, CA........................... 62.5 686.8 1.5 114 1,272 4.0 109

San Bernardino, CA..................... 63.9 797.7 2.7 39 973 4.4 71

San Diego, CA.............................. 117.7 1,512.7 1.5 114 1,311 4.1 98

San Francisco, CA....................... 62.4 776.3 3.0 20 2,523 2.3 261

San Joaquin, CA.......................... 18.7 262.0 2.8 34 995 3.4 161

San Luis Obispo, CA.................... 10.7 118.2 0.9 184 1,051 8.1 7

San Mateo, CA............................. 29.4 423.5 2.7 39 2,622 8.2 6

Santa Barbara, CA....................... 15.9 211.5 1.9 81 1,120 4.1 98

Santa Clara, CA........................... 76.1 1,138.5 1.9 81 2,825 5.6 21

Santa Cruz, CA............................ 9.8 102.7 1.7 94 1,241 20.7 1

Solano, CA................................... 12.0 143.7 -0.4 305 1,200 4.0 109

Sonoma, CA................................. 20.6 212.5 0.2 266 1,201 6.1 16

Stanislaus, CA.............................. 16.5 190.9 1.1 160 991 5.1 41

Tulare, CA.................................... 11.6 163.1 -0.4 305 850 4.9 49

Ventura, CA.................................. 28.4 334.5 1.2 144 1,165 6.0 18

Yolo, CA....................................... 7.2 106.1 1.0 175 1,235 2.1 279

Adams, CO................................... 11.7 233.0 5.1 2 1,121 2.6 234

Arapahoe, CO.............................. 23.0 338.2 1.5 114 1,354 4.3 79

Boulder, CO.................................. 16.2 191.8 3.0 20 1,418 4.5 66

Denver, CO.................................. 35.2 535.3 2.3 53 1,458 3.0 203

Douglas, CO................................. 12.9 133.5 2.8 34 1,511 17.2 3

El Paso, CO.................................. 21.0 286.8 2.2 59 1,043 2.8 222

Jefferson, CO............................... 21.2 245.0 1.5 114 1,221 0.7 339

Larimer, CO.................................. 12.9 166.8 2.0 73 1,094 3.0 203

Weld, CO...................................... 8.0 114.4 2.3 53 1,045 3.2 181

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

fourth quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-193

Ranking by

percent

change

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-193

Ranking by

percent

change

Fairfield, CT................................. 37.0 421.6 -1.0 338 $1,756 2.7 226

Hartford, CT.................................. 29.4 517.8 0.0 286 1,385 4.2 91

New Haven, CT............................ 25.3 374.3 -0.1 295 1,191 5.6 21

New London, CT.......................... 7.8 122.3 -1.4 346 1,101 2.9 213

New Castle, DE............................ 21.4 298.5 0.9 184 1,252 2.1 279

Sussex, DE.................................. 7.6 81.5 1.9 81 874 4.8 53

Washington, DC........................... 41.6 782.4 0.8 199 1,992 2.5 246

Alachua, FL.................................. 7.6 135.9 1.1 160 977 2.2 272

Bay, FL......................................... 5.9 74.3 1.2 144 879 3.9 117

Brevard, FL................................... 16.7 225.6 1.3 138 1,054 5.3 31

Broward, FL.................................. 72.7 844.2 1.7 94 1,098 3.2 181

Collier, FL..................................... 15.4 158.7 1.9 81 1,027 2.3 261

Duval, FL..................................... 31.4 537.4 1.6 104 1,092 1.8 296

Escambia, FL............................... 8.5 140.2 2.1 66 917 2.7 226

Hillsborough, FL........................... 46.2 731.8 3.4 11 1,120 3.6 140

Lake, FL....................................... 8.9 104.2 2.0 73 793 2.1 279

Lee, FL......................................... 23.9 277.7 2.6 43 935 3.9 117

Leon, FL....................................... 9.2 155.1 0.5 231 941 3.4 161

Manatee, FL................................. 11.8 135.3 2.3 53 890 4.1 98

Marion, FL.................................... 8.9 108.0 1.7 94 810 5.6 21

Miami-Dade, FL............................ 103.9 1,188.8 1.6 104 1,137 2.6 234

Okaloosa, FL................................ 6.8 85.4 1.6 104 956 2.1 279

Orange, FL................................... 45.9 884.5 2.0 73 1,047 4.2 91

Osceola, FL.................................. 7.8 101.6 2.8 34 788 4.1 98

Palm Beach, FL............................ 59.6 631.6 1.5 114 1,150 2.3 261

Pasco, FL..................................... 11.7 124.8 0.9 184 831 4.9 49

Pinellas, FL................................... 35.1 446.6 1.2 144 1,070 4.4 71

Polk, FL........................................ 14.5 235.0 2.6 43 867 2.0 289

St. Johns, FL............................... 8.1 81.8 3.2 15 904 1.3 324

St. Lucie, FL............................... 7.1 82.5 3.1 17 846 4.6 60

Sarasota, FL................................ 16.9 175.4 0.9 184 971 -0.8 348

Seminole, FL................................ 15.9 205.1 2.0 73 1,004 2.9 213

Volusia, FL................................... 15.4 175.3 -0.4 305 855 6.1 16

Bibb, GA....................................... 4.3 83.6 0.3 251 889 2.2 272

Chatham, GA................................ 8.4 159.5 1.0 175 977 5.2 33

Clayton, GA.................................. 4.2 125.1 0.7 204 1,093 4.1 98

Cobb, GA...................................... 22.6 379.8 2.0 73 1,195 3.7 133

DeKalb, GA................................. 18.4 306.9 1.5 114 1,167 3.5 149

Forsyth, GA.................................. 6.1 78.4 0.9 184 1,046 4.4 71

Fulton, GA.................................... 45.5 914.1 1.5 114 1,517 3.1 196

Gwinnett, GA................................ 26.3 367.6 2.2 59 1,088 1.6 310

Hall, GA....................................... 4.7 91.3 1.5 114 1,031 3.9 117

Muscogee, GA.............................. 4.6 95.6 0.5 231 857 1.8 296

Richmond, GA.............................. 4.6 105.9 0.6 220 936 3.2 181

Honolulu, HI.................................. 27.3 473.4 -1.1 340 1,108 3.7 133

Maui + Kalawao, HI...................... 6.7 81.5 -0.7 327 930 4.3 79

Ada, ID......................................... 16.9 256.3 3.2 15 1,106 1.5 315

Champaign, IL.............................. 4.1 92.9 1.4 132 980 3.4 161

Cook, IL........................................ 140.1 2,636.5 0.3 251 1,369 2.5 246

DuPage, IL................................. 34.9 617.2 -0.9 335 1,301 1.5 315

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

fourth quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-193

Ranking by

percent

change

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-193

Ranking by

percent

change

Kane, IL........................................ 12.7 211.9 -1.1 340 $1,033 2.3 261

Lake, IL........................................ 20.5 339.7 -0.7 327 1,458 0.8 336

McHenry, IL.................................. 8.0 96.7 -0.8 331 927 2.2 272

McLean, IL.................................... 3.4 82.3 0.0 286 991 2.6 234

Madison, IL................................... 5.4 103.1 0.7 204 917 1.3 324

Peoria, IL...................................... 4.2 103.6 -2.4 352 1,157 4.9 49

St. Clair, IL.................................... 5.0 93.6 -0.9 335 907 4.3 79

Sangamon, IL............................... 4.8 132.0 2.0 73 1,128 6.0 18

Will, IL.......................................... 15.2 254.0 2.1 66 971 0.9 333

Winnebago, IL.............................. 5.9 126.3 -1.2 343 967 -0.4 345

Allen, IN........................................ 9.1 194.0 0.7 204 956 4.3 79

Elkhart, IN..................................... 4.8 132.3 -3.2 354 964 3.0 203

Hamilton, IN.................................. 9.9 145.1 2.1 66 1,095 4.3 79

Lake, IN........................................ 10.4 190.4 0.3 251 978 -0.7 347

Marion, IN..................................... 25.2 613.3 1.1 160 1,150 3.4 161

St. Joseph, IN............................... 5.8 125.8 0.2 266 929 3.2 181

Tippecanoe, IN............................. 3.6 86.6 -0.2 298 988 -5.8 354

Vanderburgh, IN........................... 4.8 109.6 -0.6 322 916 3.7 133

Johnson, IA.................................. 4.4 84.0 0.4 241 1,026 2.1 279

Linn, IA......................................... 7.1 132.6 0.5 231 1,079 -7.1 355

Polk, IA........................................ 18.3 305.3 1.0 175 1,167 3.0 203

Scott, IA........................................ 5.8 90.7 -1.1 340 961 3.1 196

Johnson, KS................................. 24.0 361.8 2.3 53 1,163 3.1 196

Sedgwick, KS............................... 12.7 261.4 1.8 86 968 2.4 255

Shawnee, KS................................ 5.1 96.6 -0.1 295 917 2.8 222

Wyandotte, KS............................. 3.5 92.4 -0.3 303 1,136 4.7 58

Boone, KY................................... 4.5 100.1 3.0 20 960 3.3 172

Fayette, KY................................... 11.2 199.2 2.2 59 1,023 3.6 140

Jefferson, KY................................ 25.4 480.4 1.2 144 1,152 5.4 29

Caddo, LA.................................... 7.4 111.3 -1.5 348 941 3.5 149

Calcasieu, LA............................... 5.5 100.4 -2.9 353 1,065 2.2 272

East Baton Rouge, LA.................. 16.5 265.4 -2.1 350 1,087 1.2 328

Jefferson, LA................................ 14.4 192.1 0.4 241 1,047 4.1 98

Lafayette, LA................................ 10.2 132.0 -0.4 305 978 0.9 333

Orleans, LA.................................. 13.7 202.7 2.3 53 1,084 3.2 181

St. Tammany, LA.......................... 8.9 91.3 1.2 144 964 2.1 279

Cumberland, ME.......................... 14.0 188.8 1.1 160 1,088 5.4 29

Anne Arundel, MD........................ 15.4 278.2 0.7 204 1,219 3.5 149

Baltimore, MD............................... 21.4 386.7 0.6 220 1,178 2.3 261

Frederick, MD............................... 6.5 105.7 0.6 220 1,058 3.7 133

Harford, MD.................................. 6.0 97.1 -0.5 314 1,074 4.3 79

Howard, MD................................. 10.1 175.5 1.8 86 1,429 4.2 91

Montgomery, MD.......................... 33.0 477.4 0.3 251 1,532 2.4 255

Prince George's, MD.................... 16.6 325.1 0.1 273 1,207 4.4 71

Baltimore City, MD....................... 13.9 347.7 1.1 160 1,430 5.2 33

Barnstable, MA............................. 9.7 91.5 -0.4 305 1,041 3.8 126

Bristol, MA.................................... 17.8 231.1 -0.4 305 1,064 4.2 91

Essex, MA.................................... 27.2 328.6 0.1 273 1,225 3.4 161

Hampden, MA.............................. 18.7 215.1 0.0 286 1,002 2.3 261

Middlesex, MA.............................. 56.8 953.7 1.5 114 1,724 4.3 79

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

fourth quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-193

Ranking by

percent

change

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-193

Ranking by

percent

change

Norfolk, MA................................... 25.6 357.8 0.1 273 $1,402 -0.6 346

Plymouth, MA............................... 16.5 197.6 0.3 251 1,094 2.3 261

Suffolk, MA................................... 32.0 708.1 2.5 48 2,146 3.9 117

Worcester, MA.............................. 26.5 357.7 0.7 204 1,141 4.5 66

Genesee, MI................................. 7.3 139.0 0.9 184 987 7.5 10

Ingham, MI................................... 6.6 155.6 0.9 184 1,126 4.6 60

Kalamazoo, MI............................. 5.5 121.5 -0.6 322 1,052 0.8 336

Kent, MI....................................... 16.2 414.0 0.4 241 1,026 3.7 133

Macomb, MI.................................. 19.2 334.1 0.7 204 1,147 3.2 181

Oakland, MI.................................. 43.2 753.0 -0.1 295 1,311 3.6 140

Ottawa, MI.................................... 6.3 128.6 1.1 160 1,002 1.7 304

Saginaw, MI.................................. 4.1 84.9 -0.4 305 943 2.4 255

Washtenaw, MI............................. 9.2 224.0 1.4 132 1,204 2.6 234

Wayne, MI.................................... 35.4 746.1 0.7 204 1,264 4.1 98

Anoka, MN.................................... 7.9 128.3 0.3 251 1,092 4.2 91

Dakota, MN.................................. 10.8 192.1 -0.2 298 1,180 1.4 322

Hennepin, MN.............................. 41.5 943.5 0.2 266 1,425 4.0 109

Olmsted, MN................................ 3.8 101.8 1.6 104 1,319 4.4 71

Ramsey, MN................................. 14.3 335.8 0.1 273 1,255 2.5 246

St. Louis, MN................................ 5.4 97.8 -0.8 331 983 2.7 226

Stearns, MN................................. 4.4 87.7 0.3 251 949 1.8 296

Washington, MN........................... 6.1 89.3 1.8 86 987 2.5 246

Harrison, MS................................ 4.6 86.5 0.4 241 789 2.3 261

Hinds, MS..................................... 5.7 120.1 -0.4 305 937 3.0 203

Boone, MO................................... 5.0 95.9 1.3 138 969 8.5 5

Clay, MO...................................... 5.9 105.7 0.6 220 1,041 8.7 4

Greene, MO.................................. 9.4 172.4 1.0 175 916 7.0 12

Jackson, MO................................ 22.8 377.9 0.5 231 1,184 2.8 222

St. Charles, MO............................ 10.0 156.9 4.0 5 929 5.6 21

St. Louis, MO................................ 41.0 618.2 0.7 204 1,225 -0.3 342

St. Louis City, MO........................ 15.3 230.5 0.2 266 1,222 3.2 181

Yellowstone, MT........................... 6.7 82.8 0.5 231 1,005 1.5 315

Douglas, NE................................. 18.8 346.3 0.8 199 1,091 5.2 33

Lancaster, NE............................... 10.0 174.1 0.5 231 948 5.0 45

Clark, NV..................................... 57.2 1,045.3 2.9 28 1,005 1.6 310

Washoe, NV................................. 15.3 230.8 2.2 59 1,060 3.2 181

Hillsborough, NH.......................... 12.4 208.7 0.6 220 1,293 3.6 140

Merrimack, NH............................. 5.3 78.8 0.7 204 1,100 3.5 149

Rockingham, NH.......................... 11.2 153.1 1.1 160 1,171 1.6 310

Atlantic, NJ................................... 6.7 128.1 -0.2 298 970 3.5 149

Bergen, NJ................................... 33.8 457.0 0.7 204 1,352 2.4 255

Burlington, NJ............................... 11.3 204.5 0.5 231 1,176 2.7 226

Camden, NJ................................. 12.5 208.9 0.4 241 1,155 3.2 181

Essex, NJ.................................... 21.3 353.0 1.0 175 1,403 2.3 261

Gloucester, NJ.............................. 6.5 118.2 1.5 114 958 2.0 289

Hudson, NJ................................... 15.9 276.8 1.1 160 1,482 2.7 226

Mercer, NJ.................................... 11.5 266.1 1.2 144 1,450 -0.8 348

Middlesex, NJ.............................. 22.9 440.4 0.1 273 1,312 1.3 324

Monmouth, NJ.............................. 20.6 267.1 1.2 144 1,153 1.9 293

Morris, NJ..................................... 17.3 300.1 1.2 144 1,691 4.3 79

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

fourth quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-193

Ranking by

percent

change

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-193

Ranking by

percent

change

Ocean, NJ.................................... 13.9 171.0 2.1 66 $944 3.7 133

Passaic, NJ.................................. 13.0 169.9 1.3 138 1,091 1.2 328

Somerset, NJ............................... 10.4 191.6 -0.6 322 1,628 0.1 341

Union, NJ..................................... 14.9 232.9 0.1 273 1,462 7.9 8

Bernalillo, NM............................... 20.5 338.4 1.3 138 984 3.9 117

Albany, NY................................... 10.4 235.5 -1.0 338 1,203 3.1 196

Bronx, NY..................................... 19.4 330.3 1.0 175 1,158 4.1 98

Broome, NY.................................. 4.4 86.4 -1.6 349 923 5.0 45

Dutchess, NY............................... 8.5 115.1 -0.9 335 1,101 4.8 53

Erie, NY........................................ 24.6 477.5 -0.4 305 1,041 3.6 140

Kings, NY..................................... 66.0 819.6 0.7 204 1,023 4.3 79

Monroe, NY.................................. 19.0 394.7 0.0 286 1,047 3.1 196

Nassau, NY.................................. 54.6 645.2 0.0 286 1,291 2.7 226

New York, NY............................... 129.9 2,579.8 0.9 184 2,502 4.3 79

Oneida, NY................................... 5.3 106.6 0.0 286 899 3.5 149

Onondaga, NY.............................. 12.8 251.1 0.3 251 1,072 1.8 296

Orange, NY.................................. 10.8 150.5 0.4 241 996 3.3 172

Queens, NY.................................. 54.5 728.1 1.4 132 1,159 2.1 279

Richmond, NY.............................. 10.2 132.3 3.5 9 1,094 1.0 332

Rockland, NY............................... 11.2 132.4 2.2 59 1,064 1.6 310

Saratoga, NY................................ 6.0 90.1 0.3 251 1,049 2.9 213

Suffolk, NY................................... 53.9 669.2 -0.5 314 1,279 3.0 203

Westchester, NY.......................... 36.4 438.6 -0.5 314 1,526 4.4 71

Buncombe, NC............................. 10.0 136.4 1.4 132 917 2.5 246

Cabarrus, NC............................... 4.9 78.6 1.5 114 856 3.5 149

Catawba, NC................................ 4.5 89.2 -0.7 327 885 2.7 226

Cumberland, NC........................... 6.3 122.3 0.7 204 869 -0.9 350

Durham, NC................................. 8.7 213.4 3.0 20 1,388 2.2 272

Forsyth, NC.................................. 9.5 193.6 1.9 81 1,045 3.5 149

Guilford, NC.................................. 14.8 288.4 1.0 175 992 4.0 109

Mecklenburg, NC.......................... 39.6 727.5 2.9 28 1,316 3.7 133

New Hanover, NC........................ 8.7 119.3 2.9 28 936 2.9 213

Pitt, NC....................................... 3.8 78.2 -0.2 298 914 1.7 304

Wake, NC..................................... 36.6 582.9 2.7 39 1,213 -3.3 352

Cass, ND...................................... 7.4 121.6 1.3 138 1,059 3.3 172

Butler, OH..................................... 8.1 160.0 0.6 220 981 2.6 234

Cuyahoga, OH.............................. 36.4 736.9 0.2 266 1,197 4.5 66

Delaware, OH............................... 5.7 90.2 0.6 220 1,108 4.0 109

Franklin, OH................................. 34.1 780.2 1.5 114 1,123 3.2 181

Greene, OH.................................. 3.8 77.8 0.6 220 1,159 4.5 66

Hamilton, OH................................ 24.5 524.7 0.5 231 1,240 1.6 310

Lake, OH...................................... 6.3 97.2 0.6 220 940 2.0 289

Lorain, OH.................................... 6.3 98.5 0.3 251 889 2.9 213

Lucas, OH.................................... 10.1 210.8 0.4 241 1,006 6.9 13

Mahoning, OH.............................. 5.9 98.2 -0.6 322 817 2.6 234

Montgomery, OH.......................... 12.1 258.2 0.2 266 989 3.3 172

Stark, OH..................................... 8.7 159.6 -0.5 314 874 2.5 246

Summit, OH................................. 14.6 270.1 0.2 266 1,009 1.2 328

Warren, OH................................. 5.3 98.1 3.3 13 1,038 2.2 272

Cleveland, OK.............................. 6.1 88.9 5.8 1 825 2.6 234

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

fourth quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-193

Ranking by

percent

change

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-193

Ranking by

percent

change

Oklahoma, OK.............................. 28.7 469.9 1.1 160 $1,066 1.8 296

Tulsa, OK..................................... 22.9 368.9 0.7 204 1,014 1.3 324

Clackamas, OR............................ 15.8 171.6 2.5 48 1,109 3.4 161

Deschutes, OR............................. 9.4 86.4 3.0 20 967 5.6 21

Jackson, OR................................ 7.9 91.7 1.6 104 897 6.2 15

Lane, OR...................................... 12.9 159.5 0.7 204 918 3.8 126

Marion, OR................................... 11.6 160.1 2.6 43 983 4.6 60

Multnomah, OR............................ 37.0 528.7 1.7 94 1,251 3.6 140

Washington, OR........................... 20.6 306.2 1.0 175 1,407 7.3 11

Allegheny, PA............................... 36.0 708.1 0.3 251 1,255 4.2 91

Berks, PA..................................... 9.0 178.0 0.9 184 1,012 2.5 246

Bucks, PA..................................... 20.5 270.9 1.0 175 1,075 2.3 261

Butler, PA..................................... 5.1 87.6 0.1 273 1,063 2.8 222

Chester, PA.................................. 16.0 255.8 0.8 199 1,420 2.9 213

Cumberland, PA........................... 6.6 139.1 1.5 114 1,036 3.4 161

Dauphin, PA................................ 7.5 188.0 1.2 144 1,130 3.2 181

Delaware, PA............................... 14.3 232.1 1.7 94 1,186 2.7 226

Erie, PA........................................ 6.9 121.6 -0.8 331 861 2.5 246

Lackawanna, PA.......................... 5.7 98.4 -0.7 327 866 1.5 315

Lancaster, PA............................... 13.9 249.0 1.2 144 954 3.0 203

Lehigh, PA.................................... 8.9 198.8 1.5 114 1,148 5.1 41

Luzerne, PA.................................. 7.5 147.8 1.1 160 896 1.9 293

Montgomery, PA........................... 28.2 513.0 1.1 160 1,387 2.1 279

Northampton, PA.......................... 6.9 121.0 1.4 132 964 1.8 296

Philadelphia, PA........................... 35.4 712.6 1.8 86 1,400 6.4 14

Washington, PA............................ 5.6 87.9 -1.4 346 1,135 3.1 196

Westmoreland, PA....................... 9.3 134.4 0.3 251 931 1.5 315

York, PA....................................... 9.3 182.9 0.5 231 1,002 1.7 304

Kent, RI....................................... 5.6 77.0 -1.3 345 1,006 3.9 117

Providence, RI.............................. 19.0 294.3 0.9 184 1,129 1.8 296

Charleston, SC............................. 17.2 260.6 1.1 160 1,056 5.2 33

Greenville, SC.............................. 15.5 282.0 0.9 184 999 3.8 126

Horry, SC..................................... 9.8 129.1 1.6 104 721 4.8 53

Lexington, SC............................... 7.1 126.9 4.1 3 876 3.8 126

Richland, SC................................ 10.8 225.9 0.9 184 969 4.6 60

Spartanburg, SC........................... 6.7 148.5 1.5 114 922 1.7 304

York, SC....................................... 6.5 102.7 4.1 3 939 3.4 161

Minnehaha, SD............................. 7.8 129.7 0.9 184 1,018 3.9 117

Davidson, TN................................ 25.0 522.1 3.3 13 1,249 1.5 315

Hamilton, TN................................ 10.4 211.7 1.2 144 1,050 2.1 279

Knox, TN...................................... 13.2 244.6 0.9 184 1,025 3.2 181

Rutherford, TN.............................. 6.2 137.4 1.2 144 1,000 2.6 234

Shelby, TN.................................... 21.4 510.1 0.6 220 1,156 -0.3 342

Williamson, TN............................. 9.8 144.0 3.4 11 1,368 -5.0 353

Bell, TX......................................... 5.8 123.0 1.4 132 992 4.0 109

Bexar, TX..................................... 43.6 891.1 1.6 104 1,055 3.2 181

Brazoria, TX................................. 6.2 117.9 1.8 86 1,121 -1.2 351

Brazos, TX.................................... 4.8 111.3 2.9 28 848 5.0 45

Cameron, TX................................ 6.6 143.7 1.3 138 701 2.9 213

Collin, TX...................................... 28.1 443.0 2.9 28 1,336 3.4 161

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

fourth quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-193

Ranking by

percent

change

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-193

Ranking by

percent

change

Dallas, TX..................................... 80.1 1,786.4 2.8 34 $1,398 3.6 140

Denton, TX.................................. 16.6 267.1 2.7 39 1,025 3.6 140

Ector, TX..................................... 4.2 80.2 -4.2 355 1,272 -0.3 342

El Paso, TX.................................. 15.6 317.3 1.1 160 798 3.0 203

Fort Bend, TX............................... 14.6 202.0 2.6 43 1,039 1.8 296

Galveston, TX............................... 6.4 112.3 2.5 48 1,026 4.4 71

Harris, TX..................................... 118.6 2,375.0 1.2 144 1,426 2.5 246

Hidalgo, TX................................... 12.7 273.0 2.8 34 705 3.5 149

Jefferson, TX................................ 5.9 124.2 1.2 144 1,150 2.1 279

Lubbock, TX................................. 7.9 144.1 1.8 86 916 3.3 172

McLennan, TX.............................. 5.5 115.4 1.1 160 953 5.2 33

Midland, TX.................................. 6.1 107.1 -2.3 351 1,529 0.9 333

Montgomery, TX........................... 12.4 194.9 1.7 94 1,127 1.1 331

Nueces, TX.................................. 8.3 165.0 0.7 204 982 2.2 272

Potter, TX..................................... 4.0 78.2 1.6 104 972 3.2 181

Smith, TX..................................... 6.5 104.9 0.3 251 962 2.9 213

Tarrant, TX................................... 45.9 944.2 2.0 73 1,141 2.9 213

Travis, TX..................................... 44.3 795.4 3.6 8 1,412 3.9 117

Webb, TX..................................... 5.6 105.6 1.2 144 750 2.0 289

Williamson, TX............................. 12.0 186.3 3.8 6 1,300 19.5 2

Davis, UT..................................... 9.2 134.1 2.3 53 973 4.8 53

Salt Lake, UT................................ 50.0 734.7 2.4 51 1,155 5.3 31

Utah, UT....................................... 18.6 256.8 2.9 28 993 5.8 20

Weber, UT.................................... 6.5 111.0 2.6 43 867 3.2 181

Chittenden, VT............................. 7.2 103.4 -0.2 298 1,138 3.8 126

Arlington, VA................................ 9.2 184.8 2.4 51 1,963 4.7 58

Chesterfield, VA........................... 9.5 141.2 1.8 86 970 3.3 172

Fairfax, VA.................................... 37.2 631.3 2.1 66 1,735 3.3 172

Henrico, VA.................................. 12.0 193.7 0.1 273 1,102 2.4 255

Loudoun, VA................................ 12.9 177.2 3.1 17 1,360 0.2 340

Prince William, VA........................ 9.7 133.9 0.9 184 1,028 3.5 149

Alexandria City, VA...................... 6.3 91.1 -0.5 314 1,645 1.7 304

Chesapeake City, VA................... 6.3 104.1 1.7 94 903 4.3 79

Newport News City, VA................ 4.0 104.9 0.8 199 1,105 3.4 161

Norfolk City, VA........................... 6.2 142.4 0.1 273 1,173 3.5 149

Richmond City, VA....................... 8.1 159.6 1.5 114 1,268 5.6 21

Virginia Beach City, VA................ 12.5 179.4 0.4 241 911 3.8 126

Benton, WA.................................. 6.1 91.7 3.8 6 1,123 3.1 196

Clark, WA..................................... 15.7 166.1 1.5 114 1,128 5.2 33

King, WA...................................... 91.0 1,459.8 3.1 17 1,818 7.8 9

Kitsap, WA.................................... 7.0 93.3 2.2 59 1,094 3.6 140

Pierce, WA................................... 23.6 321.3 2.1 66 1,073 4.3 79

Snohomish, WA............................ 21.9 294.2 1.5 114 1,233 3.9 117

Spokane, WA............................... 16.9 230.8 1.7 94 1,003 5.1 41

Thurston, WA............................... 8.8 119.2 1.7 94 1,078 5.5 27

Whatcom, WA.............................. 7.5 91.9 0.3 251 984 4.5 66

Yakima, WA................................. 8.2 108.7 1.6 104 851 5.2 33

Kanawha, WV............................... 5.6 96.9 -1.2 343 959 2.6 234

Brown, WI..................................... 7.4 160.4 0.1 273 1,060 2.6 234

Dane, WI...................................... 16.8 347.6 2.1 66 1,185 5.2 33

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

fourth quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-193

Ranking by

percent

change

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-193

Ranking by

percent

change

Milwaukee, WI.............................. 28.4 490.2 -0.5 314 $1,119 3.3 172

Outagamie, WI............................. 5.7 110.0 0.0 286 1,024 2.6 234

Racine, WI................................. 4.8 75.4 -0.8 331 1,023 3.8 126

Waukesha, WI.............................. 14.1 247.9 0.5 231 1,195 5.1 41

Winnebago, WI............................. 4.0 93.9 0.3 251 1,089 1.5 315

San Juan, PR............................... 11.5 252.6 1.6 (5) 688 -0.3 (5)

1 Includes areas not officially designated as counties. See Technical Note.

2 Average weekly wages were calculated using unrounded data.

3 Percent changes were computed from employment and pay data adjusted for noneconomic county reclassifications. See Technical Note.

4 Totals for the United States do not include data for Puerto Rico or the Virgin Islands.

5 This county was not included in the U.S. rankings.

Note: Data are preliminary. Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees

(UCFE) programs. These 355 U.S. counties comprise 73.7 percent of the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,

fourth quarter 2019

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-192

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-192

United States3................................................................. 10,384.1 149,857.1 1.2 $1,185 3.5

 Private industry............................................................. 10,081.7 127,640.0 1.2 1,189 3.8

 Natural resources and mining.................................... 140.7 1,804.9 -2.0 1,212 2.6

 Construction............................................................... 841.3 7,427.5 1.8 1,367 3.7

 Manufacturing............................................................ 357.5 12,755.4 -0.3 1,393 3.0

 Trade, transportation, and utilities.............................. 1,951.4 28,526.8 0.9 968 3.4

 Information................................................................. 189.8 2,858.2 1.2 2,314 6.6

 Financial activities...................................................... 926.6 8,402.6 1.6 1,906 4.4

 Professional and business services........................... 1,939.2 21,450.3 1.2 1,595 3.8

 Education and health services................................... 1,790.0 23,425.9 1.8 1,053 2.9

 Leisure and hospitality............................................... 890.2 16,249.3 1.3 523 4.0

 Other services............................................................ 869.9 4,564.9 1.4 802 3.8

 Government.................................................................. 302.4 22,217.1 0.8 1,166 2.8

Los Angeles, CA.............................................................. 518.6 4,589.5 1.2 1,437 4.1

 Private industry............................................................. 512.3 4,002.0 1.3 1,426 4.2

 Natural resources and mining.................................... 0.5 5.8 -11.0 1,159 2.3

 Construction............................................................... 17.2 150.0 1.1 1,475 5.6

 Manufacturing............................................................ 12.7 338.7 -0.5 1,518 4.5

 Trade, transportation, and utilities.............................. 59.6 875.4 0.2 1,075 3.1

 Information................................................................. 13.8 198.8 1.4 3,143 2.5

 Financial activities...................................................... 30.9 226.9 0.9 2,210 6.3

 Professional and business services........................... 57.7 652.6 1.3 1,877 3.6

 Education and health services................................... 247.5 848.5 3.4 999 3.4

 Leisure and hospitality............................................... 40.4 550.4 1.5 1,208 5.9

 Other services............................................................ 29.5 153.5 0.6 848 4.7

 Government.................................................................. 6.4 587.5 0.1 1,513 3.3

Cook, IL........................................................................... 140.1 2,636.5 0.3 1,369 2.5

 Private industry............................................................. 138.8 2,341.8 0.3 1,379 2.8

 Natural resources and mining.................................... 0.1 1.4 7.2 1,333 1.5

 Construction............................................................... 11.2 75.7 2.1 1,754 3.3

 Manufacturing............................................................ 5.7 183.8 -0.5 1,439 3.0

 Trade, transportation, and utilities.............................. 28.6 490.6 0.1 1,082 2.4

 Information................................................................. 2.6 53.3 0.8 2,057 3.7

 Financial activities...................................................... 14.2 207.8 1.5 2,562 4.0

 Professional and business services........................... 29.4 482.8 -0.8 1,812 3.8

 Education and health services................................... 15.6 457.6 0.7 1,104 -1.0

 Leisure and hospitality............................................... 14.0 289.8 1.5 589 3.3

 Other services............................................................ 16.4 98.3 -2.2 1,040 4.5

 Government.................................................................. 1.3 294.7 0.2 1,290 0.6

New York, NY.................................................................. 129.9 2,579.8 0.9 2,502 4.3

 Private industry............................................................. 128.5 2,343.8 0.9 2,582 4.5

 Natural resources and mining.................................... 0.0 0.2 10.9 2,130 0.7

 Construction............................................................... 2.4 43.2 -4.9 2,443 4.3

 Manufacturing............................................................ 1.8 21.5 -3.2 1,759 -0.1

 Trade, transportation, and utilities.............................. 18.5 266.7 -1.1 1,558 4.0

 Information................................................................. 5.2 184.7 2.8 3,264 7.5

 Financial activities...................................................... 19.4 391.5 1.4 4,909 2.7

 Professional and business services........................... 27.9 635.9 1.0 2,916 5.3

 Education and health services................................... 10.2 369.5 1.6 1,548 2.3

 Leisure and hospitality............................................... 14.8 315.7 0.1 1,172 5.4

 Other services............................................................ 20.2 108.8 1.5 1,336 3.2

 Government.................................................................. 1.4 236.0 0.4 1,716 1.1

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

fourth quarter 2019 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-192

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-192

Harris, TX........................................................................ 118.6 2,375.0 1.2 $1,426 2.5

 Private industry............................................................. 118.0 2,089.0 1.0 1,447 2.3

 Natural resources and mining.................................... 1.6 65.5 -4.2 3,478 5.6

 Construction............................................................... 7.8 168.7 1.6 1,588 3.9

 Manufacturing............................................................ 4.9 180.2 0.4 1,718 1.8

 Trade, transportation, and utilities.............................. 25.2 485.9 0.1 1,228 2.2

 Information................................................................. 1.3 26.6 2.4 1,594 3.4

 Financial activities...................................................... 12.9 132.0 2.4 1,951 3.0

 Professional and business services........................... 24.0 413.9 1.6 1,865 0.5

 Education and health services................................... 16.8 304.3 1.1 1,157 3.8

 Leisure and hospitality............................................... 10.7 241.1 2.2 527 3.7

 Other services............................................................ 11.9 69.1 0.9 923 4.4

 Government.................................................................. 0.6 286.0 2.3 1,276 4.2

Maricopa, AZ.................................................................... 108.0 2,132.1 3.5 1,108 4.0

 Private industry............................................................. 107.2 1,912.7 3.7 1,109 4.0

 Natural resources and mining.................................... 0.5 8.1 2.0 1,037 1.0

 Construction............................................................... 8.6 134.7 6.2 1,279 2.9

 Manufacturing............................................................ 3.5 130.7 3.0 1,580 7.3

 Trade, transportation, and utilities.............................. 21.0 416.0 2.9 980 3.0

 Information................................................................. 2.3 39.4 2.1 1,505 2.6

 Financial activities...................................................... 14.1 197.1 4.9 1,479 7.1

 Professional and business services........................... 26.9 364.5 3.4 1,214 1.9

 Education and health services................................... 13.6 338.3 4.6 1,068 2.8

 Leisure and hospitality............................................... 9.3 228.6 2.4 542 4.6

 Other services............................................................ 7.0 55.1 3.2 829 6.4

 Government.................................................................. 0.7 219.4 1.7 1,101 3.6

Dallas, TX........................................................................ 80.1 1,786.4 2.8 1,398 3.6

 Private industry............................................................. 79.6 1,607.6 2.9 1,407 3.5

 Natural resources and mining.................................... 0.5 9.6 2.8 3,334 0.0

 Construction............................................................... 4.9 93.4 2.5 1,509 4.8

 Manufacturing............................................................ 2.9 119.3 4.0 1,525 1.1

 Trade, transportation, and utilities.............................. 16.4 377.2 3.0 1,162 2.7

 Information................................................................. 1.5 45.3 -1.3 2,002 5.4

 Financial activities...................................................... 10.1 169.7 2.8 1,947 6.0

 Professional and business services........................... 18.3 374.1 3.8 1,731 3.6

 Education and health services................................... 10.0 206.2 1.7 1,257 2.3

 Leisure and hospitality............................................... 7.3 167.9 3.2 596 4.2

 Other services............................................................ 7.2 43.9 1.7 899 5.5

 Government.................................................................. 0.5 178.8 1.7 1,311 3.5

Orange, CA...................................................................... 129.4 1,664.7 0.8 1,297 4.6

 Private industry............................................................. 128.0 1,518.7 0.8 1,293 4.7

 Natural resources and mining.................................... 0.2 2.2 0.8 1,020 5.6

 Construction............................................................... 7.9 105.9 0.3 1,600 3.1

 Manufacturing............................................................ 5.3 160.2 -0.6 1,621 3.8

 Trade, transportation, and utilities.............................. 18.8 267.4 0.0 1,116 3.4

 Information................................................................. 1.6 26.1 -0.8 2,103 6.4

 Financial activities...................................................... 13.4 118.8 1.8 2,253 9.4

 Professional and business services........................... 24.3 328.1 -0.3 1,519 5.4

 Education and health services................................... 38.6 233.4 3.9 1,043 2.7

 Leisure and hospitality............................................... 9.9 227.6 1.0 569 5.8

 Other services............................................................ 7.8 48.9 2.3 796 4.6

 Government.................................................................. 1.4 146.0 0.0 1,335 3.6

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

fourth quarter 2019 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-192

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-192

San Diego, CA................................................................ 117.7 1,512.7 1.5 $1,311 4.1

 Private industry............................................................. 115.7 1,269.8 1.5 1,284 4.4

 Natural resources and mining.................................... 0.7 9.6 8.2 813 -2.3

 Construction............................................................... 8.1 84.3 1.1 1,411 5.8

 Manufacturing............................................................ 3.5 116.9 2.6 1,738 3.1

 Trade, transportation, and utilities.............................. 15.5 232.5 -0.3 955 4.7

 Information................................................................. 1.4 23.3 -1.6 2,166 8.6

 Financial activities...................................................... 11.4 77.7 1.6 1,749 3.6

 Professional and business services........................... 21.5 258.5 2.7 1,983 4.6

 Education and health services................................... 35.5 215.3 3.4 1,069 3.2

 Leisure and hospitality............................................... 9.3 198.1 -0.5 568 3.1

 Other services............................................................ 8.3 53.4 2.0 695 2.5

 Government.................................................................. 2.0 242.9 1.3 1,453 3.0

King, WA......................................................................... 91.0 1,459.8 3.1 1,818 7.8

 Private industry............................................................. 90.3 1,286.1 3.4 1,859 8.1

 Natural resources and mining.................................... 0.4 3.0 1.9 1,357 -3.3

 Construction............................................................... 7.0 75.1 0.2 1,622 5.1

 Manufacturing............................................................ 2.5 105.3 0.8 1,768 3.8

 Trade, transportation, and utilities.............................. 13.6 289.2 4.7 1,920 8.9

 Information................................................................. 2.7 125.4 9.0 3,911 9.4

 Financial activities...................................................... 6.9 72.0 2.8 2,084 9.9

 Professional and business services........................... 18.8 239.3 2.8 2,192 8.0

 Education and health services................................... 21.7 184.0 2.5 1,165 3.1

 Leisure and hospitality............................................... 7.5 144.2 0.7 672 4.2

 Other services............................................................ 9.2 48.6 7.7 989 7.6

 Government.................................................................. 0.6 173.7 1.1 1,513 4.1

Miami-Dade, FL............................................................... 103.9 1,188.8 1.6 1,137 2.6

 Private industry............................................................. 103.6 1,047.4 1.7 1,124 2.6

 Natural resources and mining.................................... 0.5 9.4 3.1 696 2.7

 Construction............................................................... 7.4 52.2 0.7 1,128 5.2

 Manufacturing............................................................ 2.8 42.0 2.0 1,055 3.9

 Trade, transportation, and utilities.............................. 24.6 303.4 1.5 1,000 3.3

 Information................................................................. 1.6 19.6 1.4 1,610 -2.3

 Financial activities...................................................... 11.2 77.4 0.6 1,812 -0.4

 Professional and business services........................... 24.1 168.6 2.8 1,526 4.2

 Education and health services................................... 11.7 189.1 2.0 1,096 2.4

 Leisure and hospitality............................................... 7.7 144.6 0.9 670 0.3

 Other services............................................................ 9.1 39.0 0.4 715 3.5

 Government.................................................................. 0.3 141.3 0.5 1,231 2.6

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,

fourth quarter 2019

Employment Average weekly wage 1

State

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-19

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-19

United States2.......................................... 10,384.1 149,857.1 1.2 $1,185 3.5

Alabama.................................................... 131.3 2,007.9 1.0 985 2.6

Alaska........................................................ 22.6 309.9 0.6 1,139 3.2

Arizona...................................................... 168.8 2,999.8 2.7 1,059 4.1

Arkansas................................................... 92.8 1,232.9 0.5 898 3.2

California................................................... 1,625.3 17,836.3 1.5 1,457 4.7

Colorado.................................................... 211.7 2,772.6 2.2 1,227 4.0

Connecticut............................................... 123.7 1,687.4 -0.7 1,383 3.8

Delaware................................................... 34.6 455.3 0.8 1,136 2.6

District of Columbia................................... 41.6 782.5 0.8 1,992 2.5

Florida....................................................... 735.6 9,085.5 2.0 1,044 3.6

Georgia...................................................... 296.0 4,576.1 1.7 1,090 3.6

Hawaii........................................................ 44.9 665.1 -0.8 1,053 3.5

Idaho......................................................... 65.3 756.9 3.1 918 3.1

Illinois........................................................ 380.1 6,043.5 0.2 1,221 2.7

Indiana....................................................... 169.5 3,106.0 0.6 969 3.0

Iowa........................................................... 104.6 1,560.4 0.1 984 1.9

Kansas...................................................... 88.7 1,410.7 0.6 959 3.5

Kentucky.................................................... 121.5 1,928.3 0.8 955 3.2

Louisiana................................................... 136.4 1,927.7 -0.5 993 2.5

Maine......................................................... 54.2 620.2 0.7 955 5.3

Maryland.................................................... 175.3 2,728.1 0.9 1,271 3.5

Massachusetts.......................................... 262.1 3,660.8 0.9 1,511 3.8

Michigan.................................................... 266.4 4,385.3 0.4 1,115 3.4

Minnesota.................................................. 182.3 2,912.8 0.4 1,177 3.2

Mississippi................................................. 75.1 1,145.0 0.0 818 3.2

Missouri..................................................... 212.1 2,846.2 0.9 1,010 3.0

Montana.................................................... 51.6 474.1 1.1 918 3.4

Nebraska................................................... 71.4 990.9 0.7 969 4.2

Nevada...................................................... 85.2 1,435.5 2.7 1,030 2.4

New Hampshire......................................... 54.6 671.3 0.8 1,192 2.9

New Jersey............................................... 281.6 4,157.4 0.8 1,332 2.5

New Mexico............................................... 63.9 844.0 1.5 942 4.0

New York.................................................. 650.3 9,691.0 0.8 1,499 3.7

North Carolina........................................... 290.1 4,546.9 1.9 1,036 2.4

North Dakota............................................. 32.1 424.6 0.5 1,085 2.6

Ohio........................................................... 302.7 5,477.2 0.5 1,037 3.1

Oklahoma.................................................. 112.4 1,639.4 0.3 945 1.4

Oregon...................................................... 161.5 1,969.3 1.6 1,100 4.6

Pennsylvania............................................. 364.6 5,985.9 0.8 1,143 3.6

Rhode Island............................................. 39.0 489.8 0.6 1,099 1.1

South Carolina.......................................... 140.8 2,144.8 1.2 931 4.0

South Dakota............................................ 34.5 430.7 0.6 916 3.5

Tennessee................................................. 168.9 3,085.4 1.6 1,047 1.6

Texas......................................................... 718.5 12,793.0 2.0 1,187 3.4

Utah........................................................... 111.3 1,547.8 2.5 1,022 5.0

Vermont..................................................... 26.1 314.0 -0.4 987 3.5

Virginia...................................................... 285.5 3,978.7 1.2 1,204 3.4

Washington............................................... 253.7 3,457.7 2.2 1,370 6.4

West Virginia............................................. 51.2 690.3 -2.0 904 -1.4

Wisconsin.................................................. 183.2 2,898.0 0.2 1,022 3.3

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

fourth quarter 2019 - Continued

Employment Average weekly wage 1

State

Establishments,

fourth quarter

2019

(thousands)

December

2019

(thousands)

Percent

change,

December

2018-19

Fourth

quarter

2019

Percent

change,

fourth quarter

2018-19

Wyoming................................................... 27.1 276.3 1.4 $1,007 3.0

Puerto Rico............................................... 48.4 910.7 1.5 575 -0.2

Virgin Islands............................................ 3.3 39.2 10.8 1,065 13.5

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.