For release 10:00 a.m. (EDT), Wednesday, August 21, 2019 USDL-19-1519 

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

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

COUNTY EMPLOYMENT AND WAGES – FIRST QUARTER 2019 

From March 2018 to March 2019, employment increased in 298 of the 355 largest U.S. 

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

employment (as measured by the QCEW program) increased to 146.5 million, a 1.4 percent 

increase over the year. Midland, TX, had the largest over-the-year increase in employment with a 

gain of 5.8 percent. Employment data in this release are presented for March 2019, and average 

weekly wage data are presented for first quarter 2019. 

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

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

Bay, FL

Yakima, WA

Butte, CA

McLean, IL

Elkhart, IN

Kanawha, WV

Osceola, FL

San Francisco, CA

Montgomery, TX

Williamson, TN

Adams, CO

Williamson, TX

Ector, TX

York, SC

Atlantic, NJ

Midland, TX

Notice Regarding South Carolina Employment and Wages Data 

South Carolina QCEW data for 2018 and first quarter 2019 show unusual movements, which 

may be a result of a change in reporting. These unusual movements coincide with a 

modernization of the South Carolina unemployment insurance system. For more information 

please visit: www.bls.gov/cew/notices/2018/notice-regarding-south-carolina-employmentand-wages-data.htm. 
- 2 - 

Among the 355 largest counties, 325 had over-the-year increases in average weekly wages. In 

the first quarter of 2019, average weekly wages for the nation increased to $1,184, a 2.8 percent 

increase over the year. San Francisco, CA, had the largest first quarter over-the-year wage gain at 

10.2 percent. (See table 1.) 

Large County Employment in March 2019 

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

Within Midland, the largest employment increase occurred in natural resources and mining, 

which gained 2,745 jobs over the year (9.6 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 2,449 jobs (-21.8 percent). 

Large County Average Weekly Wage in First Quarter 2019 

San Francisco, CA, had the largest over-the-year percentage increase in average weekly wages 

(10.2 percent). Within San Francisco, an average weekly wage gain of $1,391 (77.5 percent) in 

trade, transportation, and utilities made the largest contribution to the county’s increase in 

average weekly wages. 

Elkhart, IN, had the largest over-the-year percentage decrease in average weekly wages with a 

loss of 7.6 percent. Within Elkhart, manufacturing had the largest impact, with an average 

weekly wage decrease of $137 (-12.7 percent) over the year.

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

gains and losses 

-8.0% -6.0% -4.0% -2.0% 0.0% 2.0% 4.0% 6.0% 8.0% 10.0%

Elkhart, IN

Olmsted, MN

Knox, TN

Peoria, IL

Oakland, MI

Warren, OH

Hamilton, OH

San Luis Obispo, CA

Tulsa, OK

Butte, CA

Jefferson, CO

Williamson, TX

Williamson, TN

Boulder, CO

Vanderburgh, IN

Bay, FL

San Francisco, CA
- 3 - 

Ten Largest Counties

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

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

percentage gain among the 10 largest counties (2.9 percent). Within Maricopa, professional and 

business services had the largest employment increase with a gain of 11,317 jobs (3.4 percent). 

(See table 2.)

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

weekly wages among the 10 largest counties (5.4 percent). Within King, information had the 

largest impact, with an average weekly wage increase of $337 (7.5 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. March 2019 

employment and first 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’s news release schedule is available at www.bls.gov/cew/release-calendar.htm. 

____________ 

The County Employment and Wages full data update for first quarter 2019 is scheduled to 

be released on Wednesday, September 4, 2019, at 10:00 a.m. (EDT). 

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

be released on Wednesday, November 20, 2019, at 10:00 a.m. (EST). 

County Changes for the 2019 County Employment and Wages News Releases

Counties with annual average employment of 75,000 or more in 2018 are included in this 

release and will be included in future 2019 releases. Six counties have been added to the 

publication tables: St. Johns, FL; St. Lucie, FL; Forsyth, GA; Greene, OH; Ector, TX; and 

Racine, WI.
- 4 - 

QCEW Data Now Available in Census Business Builder Version 2.6

The Quarterly Census of Employment and Wages data is now available in Census Business 

Builder Version 2.6, a suite of U.S. Census Bureau web tools that assists business owners and 

regional analysts in data-driven decision making. As the first collaboration of this type 

between the Bureau of Labor Statistics and the U.S. Census Bureau, this data-sharing project 

makes data more accessible for local users and enhances the efficiency of digital service 

delivery. The Census Business Builder is available at: www.census.gov/data/datatools/cbb.html.
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, Puerto Rico, 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 8.0

million private-sector employers

• Sample survey: 689,000 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 losses• Uses 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 2017 edition of this 

publication, which was published in September 2018, contains selected data produced by Business Employment Dynamics (BED) on 

job gains and losses, as well as selected data from the first quarter 

2018 version of this news release. Tables and additional content from

the 2017 edition of Employment and Wages Annual Averages Online 

are now available at www.bls.gov/cew/publications/employmentand-wages-annual-averages/2017/home.htm. The 2018 edition of 

Employment and Wages Annual Averages Online will be available in 

September 2019. 

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,

first quarter 2019

Employment Average weekly wage 2

County1

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-193

Ranking by

percent

change

First

quarter

2019

Percent

change,

first quarter

2018-193

Ranking by

percent

change

United States4.............................. 10,203.0 146,497.6 1.4 - $1,184 2.8 -

Jefferson, AL................................ 19.2 352.1 1.4 138 1,150 0.9 298

Madison, AL................................. 9.9 203.1 2.4 48 1,206 4.8 40

Mobile, AL.................................... 10.3 171.2 1.0 184 916 1.6 258

Montgomery, AL........................... 6.4 129.9 -0.2 308 882 1.0 292

Shelby, AL.................................... 5.9 84.8 0.1 285 1,147 4.2 60

Tuscaloosa, AL............................. 4.6 96.0 2.3 60 900 2.5 176

Anchorage, AK............................. 8.3 145.7 -0.4 325 1,159 3.5 92

Maricopa, AZ................................ 103.8 2,042.9 2.9 30 1,118 3.1 130

Pima, AZ....................................... 19.1 376.9 1.7 110 945 2.5 176

Benton, AR................................... 6.8 121.4 1.2 159 1,496 -0.2 331

Pulaski, AR................................... 14.6 251.7 1.0 184 998 2.4 191

Washington, AR........................... 6.3 109.2 1.6 118 865 1.4 269

Alameda, CA................................ 65.4 788.4 0.9 201 1,551 2.8 153

Butte, CA..................................... 8.6 81.3 -2.2 353 849 6.5 8

Contra Costa, CA......................... 33.5 367.3 -0.3 316 1,412 1.7 248

Fresno, CA................................... 37.2 390.7 3.5 15 840 0.8 303

Kern, CA....................................... 20.5 313.7 3.3 22 932 2.0 227

Los Angeles, CA........................... 505.4 4,484.6 1.4 138 1,282 3.5 92

Marin, CA..................................... 12.6 115.0 0.6 232 1,475 4.6 46

Merced, CA................................. 6.8 79.5 2.5 43 810 1.5 262

Monterey, CA............................... 14.2 178.8 0.4 254 946 3.4 102

Napa, CA..................................... 5.9 78.0 1.4 138 1,078 2.4 191

Orange, CA.................................. 125.3 1,640.1 1.2 159 1,287 1.8 241

Placer, CA.................................... 13.6 171.2 2.8 34 1,101 1.9 234

Riverside, CA............................... 67.9 752.3 2.4 48 927 4.2 60

Sacramento, CA........................... 60.6 673.6 2.3 60 1,210 3.0 136

San Bernardino, CA..................... 62.1 760.7 1.7 110 931 3.4 102

San Diego, CA.............................. 114.7 1,469.9 1.1 173 1,253 2.8 153

San Francisco, CA....................... 61.6 753.1 3.9 9 2,759 10.2 1

San Joaquin, CA.......................... 18.5 251.8 2.1 78 909 3.4 102

San Luis Obispo, CA.................... 10.6 119.7 2.0 85 966 5.9 10

San Mateo, CA............................. 28.8 408.3 2.3 60 2,645 1.0 292

Santa Barbara, CA....................... 15.7 198.0 1.1 173 1,055 3.5 92

Santa Clara, CA........................... 74.4 1,110.2 2.4 48 2,758 3.3 110

Santa Cruz, CA............................ 9.7 101.6 1.7 110 1,021 2.7 161

Solano, CA................................... 11.9 141.4 0.5 241 1,252 5.3 23

Sonoma, CA................................. 20.4 208.7 1.0 184 1,076 4.1 67

Stanislaus, CA.............................. 16.2 189.5 1.4 138 944 4.1 67

Tulare, CA.................................... 11.3 157.3 1.2 159 793 3.1 130

Ventura, CA.................................. 28.0 329.4 1.1 173 1,157 5.3 23

Yolo, CA....................................... 6.9 104.2 1.6 118 1,171 -1.2 346

Adams, CO................................... 11.4 218.7 4.0 6 1,079 3.3 110

Arapahoe, CO.............................. 22.3 328.1 0.9 201 1,442 5.5 16

Boulder, CO.................................. 15.7 185.2 2.4 48 1,409 7.5 4

Denver, CO.................................. 33.7 518.5 1.4 138 1,533 4.9 36

Douglas, CO................................. 12.4 126.4 1.0 184 1,366 -0.4 334

El Paso, CO.................................. 20.3 277.3 1.9 88 1,028 5.1 31

Jefferson, CO............................... 20.4 238.4 1.0 184 1,229 6.7 7

Larimer, CO.................................. 12.5 161.3 2.0 85 1,062 4.3 55

Weld, CO...................................... 7.6 112.1 3.6 13 1,076 3.9 72

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

first quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-193

Ranking by

percent

change

First

quarter

2019

Percent

change,

first quarter

2018-193

Ranking by

percent

change

Fairfield, CT................................. 36.5 412.3 -0.4 325 $2,070 4.3 55

Hartford, CT.................................. 29.0 506.4 -0.1 304 1,483 1.0 292

New Haven, CT............................ 25.0 363.1 0.2 275 1,125 2.4 191

New London, CT.......................... 7.7 121.3 -0.6 333 1,192 2.2 212

New Castle, DE............................ 20.6 289.8 1.2 159 1,368 -1.2 346

Sussex, DE.................................. 7.2 79.1 2.3 60 801 3.1 130

Washington, DC........................... 40.4 773.5 0.5 241 1,921 0.2 319

Alachua, FL.................................. 7.6 134.7 1.9 88 941 0.5 312

Bay, FL......................................... 5.8 73.5 -5.9 355 822 9.3 2

Brevard, FL................................... 16.5 220.8 2.5 43 976 3.5 92

Broward, FL.................................. 71.6 819.2 0.8 215 1,093 4.9 36

Collier, FL..................................... 14.9 156.2 3.1 25 954 2.1 218

Duval, FL..................................... 30.3 519.8 1.7 110 1,125 2.6 169

Escambia, FL............................... 8.4 138.1 2.4 48 906 3.3 110

Hillsborough, FL........................... 45.0 710.3 2.2 69 1,130 3.0 136

Lake, FL....................................... 8.7 100.9 2.2 69 740 3.8 75

Lee, FL......................................... 23.3 272.5 2.1 78 877 1.7 248

Leon, FL....................................... 8.9 154.2 1.8 94 875 1.7 248

Manatee, FL................................. 11.6 132.2 3.4 19 836 1.5 262

Marion, FL.................................... 8.7 105.3 2.1 78 739 2.5 176

Miami-Dade, FL............................ 101.9 1,164.7 1.8 94 1,129 1.7 248

Okaloosa, FL................................ 6.7 85.3 0.7 224 884 3.5 92

Orange, FL................................... 44.5 868.9 2.4 48 1,006 2.4 191

Osceola, FL.................................. 7.6 99.6 3.8 10 726 2.1 218

Palm Beach, FL............................ 58.7 620.7 1.5 128 1,121 3.1 130

Pasco, FL..................................... 11.6 122.4 1.8 94 759 3.7 81

Pinellas, FL................................... 34.5 440.1 0.9 201 962 2.1 218

Polk, FL........................................ 14.0 227.6 3.4 19 839 1.8 241

St. Johns, FL............................... 7.8 79.0 2.9 30 908 0.4 315

St. Lucie, FL............................... 6.8 80.3 3.0 28 777 0.3 318

Sarasota, FL................................ 16.6 175.0 1.0 184 914 -0.9 342

Seminole, FL................................ 15.6 199.9 2.4 48 975 3.0 136

Volusia, FL................................... 14.8 176.7 0.9 201 789 3.5 92

Bibb, GA....................................... 4.3 82.8 -0.6 333 874 2.6 169

Chatham, GA................................ 8.1 158.4 1.3 150 935 1.7 248

Clayton, GA.................................. 4.0 121.4 0.9 201 1,388 4.8 40

Cobb, GA...................................... 21.8 365.3 1.7 110 1,249 2.5 176

DeKalb, GA................................. 17.7 300.8 1.5 128 1,185 1.5 262

Forsyth, GA.................................. 5.9 76.7 2.6 39 958 1.7 248

Fulton, GA.................................... 43.6 890.0 2.3 60 1,711 2.6 169

Gwinnett, GA................................ 25.4 357.8 1.2 159 1,078 2.3 200

Hall, GA....................................... 4.6 89.3 2.4 48 889 1.4 269

Muscogee, GA.............................. 4.5 95.1 0.8 215 955 -0.4 334

Richmond, GA.............................. 4.4 105.1 -0.3 316 906 4.4 52

Honolulu, HI.................................. 27.8 471.8 -0.2 308 1,054 3.3 110

Maui + Kalawao, HI...................... 6.5 79.3 -0.2 308 900 3.3 110

Ada, ID......................................... 17.1 248.7 2.9 30 967 2.5 176

Champaign, IL.............................. 4.1 90.2 0.5 241 926 2.5 176

Cook, IL........................................ 138.4 2,568.4 0.1 285 1,468 3.4 102

DuPage, IL................................. 34.6 612.3 -0.3 316 1,340 2.3 200

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

first quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-193

Ranking by

percent

change

First

quarter

2019

Percent

change,

first quarter

2018-193

Ranking by

percent

change

Kane, IL........................................ 12.6 209.2 -0.5 331 $947 1.4 269

Lake, IL........................................ 20.2 332.1 0.2 275 1,729 1.9 234

McHenry, IL.................................. 7.8 94.7 -1.2 346 846 1.7 248

McLean, IL.................................... 3.4 80.9 -2.0 352 1,107 -0.9 342

Madison, IL................................... 5.4 100.4 -0.6 333 876 4.7 44

Peoria, IL...................................... 4.2 103.8 -1.3 347 1,448 -2.4 352

St. Clair, IL.................................... 5.0 91.4 -0.8 342 833 2.0 227

Sangamon, IL............................... 4.8 127.8 -0.8 342 1,057 -0.9 342

Will, IL.......................................... 14.9 241.2 0.5 241 944 4.2 60

Winnebago, IL.............................. 5.9 124.6 -1.6 348 983 4.6 46

Allen, IN........................................ 9.0 188.7 1.6 118 941 1.1 288

Elkhart, IN..................................... 4.8 135.0 -1.8 350 930 -7.6 355

Hamilton, IN.................................. 9.8 142.2 2.0 85 1,132 0.1 324

Lake, IN........................................ 10.5 186.6 0.3 263 946 2.7 161

Marion, IN..................................... 24.5 600.2 1.0 184 1,232 1.5 262

St. Joseph, IN............................... 5.8 124.0 1.4 138 868 0.8 303

Tippecanoe, IN............................. 3.5 86.8 2.2 69 960 0.4 315

Vanderburgh, IN........................... 4.8 109.7 0.9 201 962 8.2 3

Johnson, IA.................................. 4.3 83.2 -0.8 342 995 1.9 234

Linn, IA......................................... 7.0 129.9 0.3 263 1,082 4.3 55

Polk, IA........................................ 17.9 296.5 0.4 254 1,179 1.6 258

Scott, IA........................................ 5.7 89.1 -0.7 339 899 2.5 176

Johnson, KS................................. 23.8 345.4 0.4 254 1,168 3.4 102

Sedgwick, KS............................... 12.6 253.5 2.1 78 1,001 3.7 81

Shawnee, KS................................ 5.1 95.8 -0.3 316 910 0.8 303

Wyandotte, KS............................. 3.5 89.8 1.4 138 1,042 1.8 241

Boone, KY................................... 4.5 93.7 2.5 43 922 2.0 227

Fayette, KY................................... 11.2 191.5 0.0 299 952 2.8 153

Jefferson, KY................................ 25.6 466.4 0.5 241 1,140 2.1 218

Caddo, LA.................................... 7.4 111.5 -0.3 316 859 2.3 200

Calcasieu, LA............................... 5.5 102.5 -1.6 348 1,007 5.1 31

East Baton Rouge, LA.................. 16.1 267.6 0.3 263 1,050 2.2 212

Jefferson, LA................................ 14.2 188.2 -0.2 308 960 3.3 110

Lafayette, LA................................ 10.0 130.4 1.0 184 914 2.8 153

Orleans, LA.................................. 13.3 197.8 0.9 201 1,064 0.8 303

St. Tammany, LA.......................... 8.7 89.3 2.2 69 921 2.8 153

Cumberland, ME.......................... 13.7 181.8 0.9 201 1,083 3.2 125

Anne Arundel, MD........................ 15.4 270.5 0.3 263 1,194 3.3 110

Baltimore, MD............................... 21.4 378.7 0.3 263 1,122 1.4 269

Frederick, MD............................... 6.5 104.2 1.8 94 1,022 2.9 144

Harford, MD.................................. 5.9 94.2 0.9 201 1,052 5.7 13

Howard, MD................................. 10.1 171.0 0.5 241 1,389 3.3 110

Montgomery, MD.......................... 32.9 468.7 0.3 263 1,580 -0.4 334

Prince George's, MD.................... 16.3 319.3 1.4 138 1,115 0.0 326

Baltimore City, MD....................... 13.7 341.5 0.3 263 1,316 2.3 200

Barnstable, MA............................. 9.6 86.8 0.1 285 969 4.5 50

Bristol, MA.................................... 18.2 224.8 0.6 232 999 4.2 60

Essex, MA.................................... 27.2 321.5 0.2 275 1,229 3.5 92

Hampden, MA.............................. 19.1 210.0 1.6 118 1,015 3.8 75

Middlesex, MA.............................. 56.8 926.1 1.6 118 1,886 5.4 18

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

first quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-193

Ranking by

percent

change

First

quarter

2019

Percent

change,

first quarter

2018-193

Ranking by

percent

change

Norfolk, MA................................... 25.7 348.6 -0.3 316 $1,324 3.4 102

Plymouth, MA............................... 16.5 191.6 0.7 224 1,058 5.4 18

Suffolk, MA................................... 31.7 686.4 2.4 48 2,270 0.2 319

Worcester, MA.............................. 26.7 348.5 0.7 224 1,121 3.0 136

Genesee, MI................................. 6.8 132.0 -0.7 339 898 0.9 298

Ingham, MI................................... 6.0 151.3 0.0 299 1,044 0.8 303

Kalamazoo, MI............................. 5.0 120.2 0.5 241 1,100 4.7 44

Kent, MI....................................... 14.8 407.4 0.8 215 975 2.2 212

Macomb, MI.................................. 17.6 324.7 -0.1 304 1,117 -1.3 348

Oakland, MI.................................. 39.5 732.3 0.3 263 1,251 -2.0 351

Ottawa, MI.................................... 5.8 125.4 0.2 275 924 -1.0 345

Saginaw, MI.................................. 3.8 82.5 -0.5 331 897 0.1 324

Washtenaw, MI............................. 8.3 218.1 1.3 150 1,173 3.7 81

Wayne, MI.................................... 31.4 724.8 0.9 201 1,254 -0.6 340

Anoka, MN.................................... 7.8 125.0 1.1 173 998 1.3 279

Dakota, MN.................................. 10.6 186.4 -0.4 325 1,166 3.3 110

Hennepin, MN.............................. 41.6 924.6 0.8 215 1,539 2.9 144

Olmsted, MN................................ 3.8 99.0 0.2 275 1,210 -5.1 354

Ramsey, MN................................. 14.3 330.4 0.4 254 1,361 1.0 292

St. Louis, MN................................ 5.4 96.6 -0.3 316 914 4.6 46

Stearns, MN................................. 4.4 86.0 0.5 241 926 -0.3 332

Washington, MN........................... 6.0 85.6 1.0 184 953 -0.1 328

Harrison, MS................................ 4.7 85.5 0.1 285 752 0.0 326

Hinds, MS..................................... 5.8 120.1 -0.1 304 928 2.8 153

Boone, MO................................... 4.9 94.2 0.2 275 855 2.8 153

Clay, MO...................................... 5.8 102.7 -0.4 325 960 1.2 283

Greene, MO.................................. 9.2 169.2 2.2 69 847 3.7 81

Jackson, MO................................ 22.2 370.5 0.7 224 1,113 2.4 191

St. Charles, MO............................ 9.7 149.0 1.4 138 994 3.5 92

St. Louis, MO................................ 40.0 604.1 0.2 275 1,240 2.9 144

St. Louis City, MO........................ 14.9 227.8 0.2 275 1,283 2.3 200

Yellowstone, MT........................... 6.5 80.5 0.4 254 951 4.3 55

Douglas, NE................................. 19.0 336.9 0.4 254 1,057 2.3 200

Lancaster, NE............................... 10.2 169.7 -0.2 308 894 2.1 218

Clark, NV..................................... 56.8 1,014.9 3.1 25 977 0.7 309

Washoe, NV................................. 15.1 222.2 1.8 94 986 3.0 136

Hillsborough, NH.......................... 12.2 204.7 1.5 128 1,269 2.3 200

Merrimack, NH............................. 5.2 77.7 0.2 275 1,039 4.0 69

Rockingham, NH.......................... 11.1 147.9 0.8 215 1,142 4.2 60

Atlantic, NJ................................... 6.6 126.0 4.9 2 908 -0.1 328

Bergen, NJ................................... 33.3 440.6 0.8 215 1,333 1.5 262

Burlington, NJ............................... 11.1 199.6 0.1 285 1,172 1.4 269

Camden, NJ................................. 12.2 204.3 0.7 224 1,077 2.6 169

Essex, NJ.................................... 20.8 344.9 1.0 184 1,535 1.9 234

Gloucester, NJ.............................. 6.4 113.1 2.7 36 903 0.9 298

Hudson, NJ................................... 15.4 269.8 1.9 88 1,745 -0.1 328

Mercer, NJ.................................... 11.3 256.6 1.1 173 1,636 0.8 303

Middlesex, NJ.............................. 22.6 428.4 1.4 138 1,340 1.7 248

Monmouth, NJ.............................. 20.5 258.1 1.3 150 1,137 1.2 283

Morris, NJ..................................... 17.3 290.1 0.3 263 1,892 5.1 31

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

first quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-193

Ranking by

percent

change

First

quarter

2019

Percent

change,

first quarter

2018-193

Ranking by

percent

change

Ocean, NJ.................................... 13.7 166.3 2.2 69 $878 1.5 262

Passaic, NJ.................................. 12.7 165.3 0.1 285 1,051 1.5 262

Somerset, NJ............................... 10.3 187.3 1.0 184 2,139 2.5 176

Union, NJ..................................... 14.6 227.5 0.6 232 1,409 0.9 298

Bernalillo, NM............................... 19.5 329.0 0.6 232 941 2.6 169

Albany, NY................................... 10.2 232.1 0.0 299 1,142 3.0 136

Bronx, NY..................................... 18.8 323.7 1.5 128 1,086 4.6 46

Broome, NY.................................. 4.4 85.6 0.0 299 900 5.1 31

Dutchess, NY............................... 8.3 113.6 1.3 150 1,060 2.3 200

Erie, NY........................................ 24.3 468.5 0.5 241 1,017 2.4 191

Kings, NY..................................... 63.2 780.2 0.5 241 954 4.0 69

Monroe, NY.................................. 18.6 387.4 0.3 263 1,015 2.2 212

Nassau, NY.................................. 53.5 626.6 0.1 285 1,215 1.8 241

New York, NY............................... 126.7 2,500.7 1.4 138 3,153 2.1 218

Oneida, NY................................... 5.2 105.4 0.5 241 866 3.1 130

Onondaga, NY.............................. 12.6 245.3 1.1 173 1,030 1.7 248

Orange, NY.................................. 10.4 145.8 1.1 173 931 3.8 75

Queens, NY.................................. 52.8 709.9 1.8 94 1,099 2.7 161

Richmond, NY.............................. 9.9 125.9 3.7 11 1,006 2.9 144

Rockland, NY............................... 10.8 126.9 2.3 60 1,077 0.5 312

Saratoga, NY................................ 5.9 86.7 -0.4 325 1,029 3.7 81

Suffolk, NY................................... 52.7 652.3 0.9 201 1,171 2.9 144

Westchester, NY.......................... 35.9 428.2 1.0 184 1,587 4.5 50

Buncombe, NC............................. 9.6 134.4 2.6 39 848 4.3 55

Cabarrus, NC............................... 4.8 76.2 2.5 43 822 2.5 176

Catawba, NC................................ 4.5 88.5 0.5 241 857 1.9 234

Cumberland, NC........................... 6.1 120.3 0.1 285 840 5.4 18

Durham, NC................................. 8.6 208.8 3.5 15 1,482 4.2 60

Forsyth, NC.................................. 9.3 189.8 1.6 118 1,060 0.7 309

Guilford, NC.................................. 14.6 284.8 1.1 173 959 0.9 298

Mecklenburg, NC.......................... 38.8 706.6 2.5 43 1,533 1.6 258

New Hanover, NC........................ 8.5 115.9 2.1 78 908 4.4 52

Pitt, NC....................................... 3.8 77.6 0.8 215 897 5.3 23

Wake, NC..................................... 35.7 566.0 2.6 39 1,213 5.3 23

Cass, ND...................................... 7.4 118.1 1.7 110 985 1.4 269

Butler, OH..................................... 8.0 155.6 1.0 184 1,016 1.4 269

Cuyahoga, OH.............................. 36.2 719.8 0.6 232 1,176 2.3 200

Delaware, OH............................... 5.6 87.9 1.7 110 1,256 3.5 92

Franklin, OH................................. 33.3 752.0 1.2 159 1,187 3.8 75

Greene, OH.................................. 3.7 75.5 1.8 94 1,058 3.1 130

Hamilton, OH................................ 24.2 514.7 1.0 184 1,284 5.9 10

Lake, OH...................................... 6.3 95.4 1.6 118 926 4.4 52

Lorain, OH.................................... 6.2 97.0 0.7 224 860 1.8 241

Lucas, OH.................................... 10.2 206.2 -0.3 316 1,003 -0.3 332

Mahoning, OH.............................. 5.9 96.4 -0.9 345 772 3.3 110

Montgomery, OH.......................... 12.0 253.5 -0.2 308 950 2.9 144

Stark, OH..................................... 8.6 157.5 -0.2 308 842 3.2 125

Summit, OH................................. 14.4 263.7 -0.1 304 1,003 2.5 176

Warren, OH................................. 5.2 94.0 3.3 22 1,099 5.9 10

Cleveland, OK.............................. 6.0 82.8 2.4 48 781 2.8 153

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

first quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-193

Ranking by

percent

change

First

quarter

2019

Percent

change,

first quarter

2018-193

Ranking by

percent

change

Oklahoma, OK.............................. 28.3 459.4 1.3 150 $1,095 3.2 125

Tulsa, OK..................................... 22.8 359.5 1.4 138 1,072 6.1 9

Clackamas, OR............................ 15.7 167.6 2.2 69 1,033 3.0 136

Deschutes, OR............................. 9.3 82.5 1.5 128 887 2.5 176

Jackson, OR................................ 7.9 88.7 0.3 263 819 3.0 136

Lane, OR...................................... 12.8 156.3 0.4 254 845 2.4 191

Marion, OR................................... 11.5 155.3 1.5 128 901 4.0 69

Multnomah, OR............................ 36.8 514.9 1.8 94 1,200 2.5 176

Washington, OR........................... 20.5 299.4 1.2 159 1,497 5.6 15

Allegheny, PA............................... 35.6 694.9 0.6 232 1,251 1.4 269

Berks, PA..................................... 8.9 174.4 1.2 159 988 1.1 288

Bucks, PA..................................... 20.2 264.4 1.6 118 1,026 2.6 169

Butler, PA..................................... 5.1 86.3 0.2 275 1,033 5.7 13

Chester, PA.................................. 15.7 249.7 1.1 173 1,501 1.4 269

Cumberland, PA........................... 6.6 134.1 0.8 215 1,023 2.5 176

Dauphin, PA................................ 7.5 183.5 2.3 60 1,107 2.1 218

Delaware, PA............................... 14.1 224.0 1.2 159 1,265 -0.4 334

Erie, PA........................................ 6.9 120.4 0.1 285 834 1.6 258

Lackawanna, PA.......................... 5.6 96.7 -0.4 325 814 1.0 292

Lancaster, PA............................... 13.7 241.3 1.2 159 911 1.2 283

Lehigh, PA.................................... 8.8 192.6 1.3 150 1,121 3.9 72

Luzerne, PA.................................. 7.4 143.2 -0.2 308 867 3.7 81

Montgomery, PA........................... 27.8 498.1 1.5 128 1,547 3.3 110

Northampton, PA.......................... 6.8 117.1 2.8 34 955 2.7 161

Philadelphia, PA........................... 34.8 691.8 2.2 69 1,374 3.6 89

Washington, PA............................ 5.6 86.7 0.9 201 1,262 2.4 191

Westmoreland, PA....................... 9.2 132.1 0.7 224 901 2.5 176

York, PA....................................... 9.2 178.4 0.1 285 945 1.3 279

Kent, RI....................................... 5.6 75.1 0.7 224 1,021 3.8 75

Providence, RI.............................. 18.8 285.9 0.3 263 1,146 0.5 312

Charleston, SC............................. 16.8 256.9 2.6 39 1,013 3.8 75

Greenville, SC.............................. 15.1 277.3 2.3 60 942 1.0 292

Horry, SC..................................... 9.6 129.6 1.8 94 652 3.3 110

Lexington, SC............................... 7.0 119.7 1.2 159 851 5.5 16

Richland, SC................................ 10.7 224.0 0.4 254 966 2.2 212

Spartanburg, SC........................... 6.6 145.3 2.7 36 928 0.2 319

York, SC....................................... 6.3 98.5 4.7 3 972 3.4 102

Minnehaha, SD............................. 7.5 126.3 0.9 201 967 2.0 227

Davidson, TN................................ 24.3 503.7 3.4 19 1,222 -0.5 339

Hamilton, TN................................ 10.2 206.4 1.8 94 996 3.3 110

Knox, TN...................................... 13.0 239.7 1.3 150 952 -2.7 353

Rutherford, TN.............................. 6.0 132.4 1.6 118 948 5.1 31

Shelby, TN.................................... 21.2 498.3 1.2 159 1,104 2.9 144

Williamson, TN............................. 9.5 137.8 4.0 6 1,389 7.4 5

Bell, TX......................................... 5.7 119.7 0.6 232 917 4.9 36

Bexar, TX..................................... 42.8 868.1 1.3 150 1,025 2.3 200

Brazoria, TX................................. 6.1 115.6 3.5 15 1,211 0.2 319

Brazos, TX.................................... 4.7 108.8 3.0 28 803 -0.4 334

Cameron, TX................................ 6.6 140.2 0.1 285 648 3.2 125

Collin, TX...................................... 26.9 423.1 2.4 48 1,390 1.2 283

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

first quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-193

Ranking by

percent

change

First

quarter

2019

Percent

change,

first quarter

2018-193

Ranking by

percent

change

Dallas, TX..................................... 78.6 1,708.8 1.9 88 $1,464 2.9 144

Denton, TX.................................. 16.0 251.4 3.2 24 1,006 2.1 218

Ector, TX..................................... 4.2 81.4 4.4 4 1,242 5.4 18

El Paso, TX.................................. 15.6 310.1 1.3 150 759 1.2 283

Fort Bend, TX............................... 14.3 194.1 3.6 13 1,046 0.7 309

Galveston, TX............................... 6.3 110.2 1.2 159 995 -1.4 349

Harris, TX..................................... 117.4 2,333.5 1.8 94 1,551 3.9 72

Hidalgo, TX................................... 12.7 266.0 1.5 128 662 1.7 248

Jefferson, TX................................ 5.9 123.5 1.8 94 1,180 2.7 161

Lubbock, TX................................. 7.7 140.2 1.1 173 839 1.3 279

McLennan, TX.............................. 5.4 113.2 1.8 94 889 1.8 241

Midland, TX.................................. 6.0 107.2 5.8 1 1,599 4.8 40

Montgomery, TX........................... 12.2 191.7 4.0 6 1,226 5.2 29

Nueces, TX.................................. 8.3 162.4 -0.3 316 942 2.3 200

Potter, TX..................................... 4.0 76.5 0.4 254 875 2.7 161

Smith, TX..................................... 6.4 104.0 1.0 184 874 2.5 176

Tarrant, TX................................... 45.2 910.6 1.6 118 1,148 3.2 125

Travis, TX..................................... 43.0 767.0 3.5 15 1,365 3.6 89

Webb, TX..................................... 5.5 103.1 1.8 94 705 2.2 212

Williamson, TX............................. 11.6 178.3 4.3 5 1,249 6.9 6

Davis, UT..................................... 8.9 129.9 2.1 78 887 2.7 161

Salt Lake, UT................................ 47.4 710.0 2.9 30 1,130 3.3 110

Utah, UT....................................... 17.5 248.6 3.7 11 938 4.2 60

Weber, UT.................................... 6.3 108.3 1.8 94 823 2.1 218

Chittenden, VT............................. 7.1 101.2 0.9 201 1,104 4.8 40

Arlington, VA................................ 9.3 180.0 1.9 88 1,966 2.0 227

Chesterfield, VA........................... 9.6 135.0 1.0 184 937 -1.6 350

Fairfax, VA.................................... 37.6 613.3 1.7 110 1,837 2.0 227

Henrico, VA.................................. 12.0 191.5 0.6 232 1,133 1.9 234

Loudoun, VA................................ 12.9 171.7 3.1 25 1,331 3.4 102

Prince William, VA........................ 9.6 130.9 1.2 159 938 0.4 315

Alexandria City, VA...................... 6.4 90.6 -0.6 333 1,508 1.3 279

Chesapeake City, VA................... 6.3 101.3 0.1 285 864 1.9 234

Newport News City, VA................ 4.0 102.9 1.5 128 1,073 3.6 89

Norfolk City, VA........................... 6.2 140.2 -0.6 333 1,074 1.1 288

Richmond City, VA....................... 8.1 158.7 2.3 60 1,298 -0.6 340

Virginia Beach City, VA................ 12.5 176.4 0.1 285 834 2.3 200

Benton, WA.................................. 5.9 88.4 1.0 184 1,096 3.3 110

Clark, WA..................................... 15.2 162.2 1.5 128 1,047 3.7 81

King, WA...................................... 89.7 1,412.3 2.7 36 1,853 5.4 18

Kitsap, WA.................................... 6.9 90.8 2.4 48 988 3.5 92

Pierce, WA................................... 22.8 312.6 1.9 88 1,032 5.3 23

Snohomish, WA............................ 21.7 289.7 2.2 69 1,309 2.7 161

Spokane, WA............................... 16.4 223.9 1.1 173 962 2.9 144

Thurston, WA............................... 8.4 117.8 1.8 94 1,034 5.3 23

Whatcom, WA.............................. 7.3 91.8 2.1 78 958 3.7 81

Yakima, WA................................. 7.8 108.2 -3.0 354 773 2.0 227

Kanawha, WV............................... 5.7 96.2 -1.8 350 957 2.6 169

Brown, WI..................................... 7.2 157.5 0.6 232 1,012 1.8 241

Dane, WI...................................... 16.3 335.5 0.8 215 1,203 5.2 29

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

first quarter 2019 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-193

Ranking by

percent

change

First

quarter

2019

Percent

change,

first quarter

2018-193

Ranking by

percent

change

Milwaukee, WI.............................. 27.5 484.3 -0.7 339 $1,095 0.2 319

Outagamie, WI............................. 5.5 107.2 0.1 285 946 1.4 269

Racine, WI................................. 4.6 74.4 0.0 299 944 1.1 288

Waukesha, WI.............................. 13.7 241.7 0.5 241 1,167 2.4 191

Winnebago, WI............................. 3.9 92.0 -0.6 333 1,053 4.9 36

San Juan, PR............................... 10.9 241.0 0.6 (5) 674 -3.3 (5)

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

2 Average weekly wages were calculated using unrounded data.

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

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

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

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

(UCFE) programs. These 355 U.S. counties comprise 73.5 percent of the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,

first quarter 2019

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-192

First

quarter

2019

Percent

change,

first quarter

2018-192

United States3................................................................. 10,203.0 146,497.6 1.4 $1,184 2.8

 Private industry............................................................. 9,902.4 124,457.1 1.5 1,198 3.0

 Natural resources and mining.................................... 139.1 1,814.0 1.2 1,334 4.8

 Construction............................................................... 824.0 7,138.6 3.2 1,194 2.7

 Manufacturing............................................................ 354.6 12,751.4 1.6 1,419 1.2

 Trade, transportation, and utilities.............................. 1,940.1 27,104.9 0.5 975 3.8

 Information................................................................. 180.4 2,828.7 0.9 2,509 5.9

 Financial activities...................................................... 909.3 8,218.5 1.0 2,431 1.6

 Professional and business services........................... 1,887.1 20,858.3 1.6 1,589 3.5

 Education and health services................................... 1,749.3 23,017.0 1.9 965 2.7

 Leisure and hospitality............................................... 873.5 16,053.6 1.5 461 3.6

 Other services............................................................ 857.4 4,492.7 1.3 759 3.5

 Government.................................................................. 300.5 22,040.5 0.5 1,108 1.8

Los Angeles, CA.............................................................. 505.4 4,484.6 1.4 1,282 3.5

 Private industry............................................................. 499.1 3,902.1 1.4 1,258 3.8

 Natural resources and mining.................................... 0.5 6.2 4.7 1,134 -2.2

 Construction............................................................... 16.5 146.3 3.1 1,296 3.3

 Manufacturing............................................................ 12.8 340.3 0.0 1,454 5.0

 Trade, transportation, and utilities.............................. 58.9 832.5 -0.1 1,046 3.5

 Information................................................................. 12.6 210.4 -0.2 2,709 6.4

 Financial activities...................................................... 29.7 221.7 -0.5 2,427 4.0

 Professional and business services........................... 55.1 632.7 3.1 1,570 2.3

 Education and health services................................... 242.4 821.3 2.8 913 2.5

 Leisure and hospitality............................................... 38.1 538.2 2.0 682 7.4

 Other services............................................................ 28.9 151.3 0.4 768 5.5

 Government.................................................................. 6.3 582.5 0.9 1,447 1.8

Cook, IL........................................................................... 138.4 2,568.4 0.1 1,468 3.4

 Private industry............................................................. 137.1 2,275.4 0.1 1,490 3.4

 Natural resources and mining.................................... 0.1 1.3 10.3 1,110 5.2

 Construction............................................................... 11.1 71.1 -0.1 1,520 0.5

 Manufacturing............................................................ 5.7 183.7 0.3 1,391 1.1

 Trade, transportation, and utilities.............................. 28.3 464.8 -0.1 1,156 4.8

 Information................................................................. 2.5 53.0 1.4 2,434 3.5

 Financial activities...................................................... 14.0 203.2 0.6 4,054 4.0

 Professional and business services........................... 29.1 468.6 0.1 1,772 4.1

 Education and health services................................... 15.5 451.9 -0.1 1,010 1.8

 Leisure and hospitality............................................... 13.8 278.3 0.0 538 3.5

 Other services............................................................ 16.0 98.8 -0.6 986 1.1

 Government.................................................................. 1.3 293.0 0.1 1,294 2.8

New York, NY.................................................................. 126.7 2,500.7 1.4 3,153 2.1

 Private industry............................................................. 125.3 2,269.9 1.5 3,314 2.1

 Natural resources and mining.................................... 0.0 0.2 4.1 2,302 -5.5

 Construction............................................................... 2.4 43.5 0.4 2,023 3.5

 Manufacturing............................................................ 1.9 22.2 -5.8 1,797 -2.1

 Trade, transportation, and utilities.............................. 18.7 249.7 -0.3 1,570 2.5

 Information................................................................. 5.1 178.5 3.5 3,660 3.3

 Financial activities...................................................... 19.3 384.7 2.2 9,566 0.4

 Professional and business services........................... 27.3 607.4 1.1 2,825 3.0

 Education and health services................................... 10.2 368.8 2.6 1,355 1.4

 Leisure and hospitality............................................... 14.7 304.6 0.1 963 5.6

 Other services............................................................ 19.9 105.4 1.2 1,335 2.9

 Government.................................................................. 1.4 230.8 0.3 1,567 3.2

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

first quarter 2019 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-192

First

quarter

2019

Percent

change,

first quarter

2018-192

Harris, TX........................................................................ 117.4 2,333.5 1.8 $1,551 3.9

 Private industry............................................................. 116.8 2,053.5 2.1 1,605 4.0

 Natural resources and mining.................................... 1.6 68.0 3.1 5,232 7.5

 Construction............................................................... 7.8 168.6 4.3 1,505 3.2

 Manufacturing............................................................ 4.9 180.2 5.3 1,971 3.2

 Trade, transportation, and utilities.............................. 25.1 468.1 0.6 1,445 4.0

 Information................................................................. 1.2 26.5 1.1 1,739 4.9

 Financial activities...................................................... 12.5 128.3 1.1 2,472 2.1

 Professional and business services........................... 23.6 404.4 1.7 1,980 4.0

 Education and health services................................... 16.5 299.0 1.6 1,049 3.0

 Leisure and hospitality............................................... 10.5 239.4 2.6 468 2.4

 Other services............................................................ 11.8 68.2 1.6 856 2.1

 Government.................................................................. 0.6 279.9 0.0 1,154 2.2

Maricopa, AZ.................................................................... 103.8 2,042.9 2.9 1,118 3.1

 Private industry............................................................. 103.1 1,827.0 3.1 1,125 3.2

 Natural resources and mining.................................... 0.4 7.9 -4.2 1,365 2.7

 Construction............................................................... 8.3 128.3 8.2 1,171 4.8

 Manufacturing............................................................ 3.4 126.6 2.2 1,659 2.6

 Trade, transportation, and utilities.............................. 20.3 384.4 2.3 1,018 2.2

 Information................................................................. 2.0 38.1 1.8 1,687 -1.5

 Financial activities...................................................... 13.3 187.8 2.9 1,670 2.6

 Professional and business services........................... 25.3 345.9 3.4 1,217 6.0

 Education and health services................................... 12.8 322.3 3.5 1,026 1.7

 Leisure and hospitality............................................... 9.0 230.5 1.9 514 4.5

 Other services............................................................ 7.0 54.1 2.8 776 4.3

 Government.................................................................. 0.7 215.9 1.4 1,059 2.0

Dallas, TX........................................................................ 78.6 1,708.8 1.9 1,464 2.9

 Private industry............................................................. 78.0 1,533.7 2.1 1,496 3.0

 Natural resources and mining.................................... 0.5 9.2 8.2 4,787 -3.9

 Construction............................................................... 4.8 89.7 2.8 1,374 4.0

 Manufacturing............................................................ 2.8 116.2 2.9 1,925 -0.6

 Trade, transportation, and utilities.............................. 16.0 347.3 2.1 1,222 5.2

 Information................................................................. 1.4 46.1 -3.3 2,764 3.7

 Financial activities...................................................... 9.7 163.7 2.0 2,442 2.3

 Professional and business services........................... 17.8 352.1 2.3 1,681 3.4

 Education and health services................................... 9.7 202.3 1.8 1,141 3.0

 Leisure and hospitality............................................... 7.1 162.2 2.2 528 3.3

 Other services............................................................ 7.1 43.0 2.1 955 6.0

 Government.................................................................. 0.5 175.1 0.1 1,181 1.5

Orange, CA...................................................................... 125.3 1,640.1 1.2 1,287 1.8

 Private industry............................................................. 123.8 1,482.1 1.3 1,271 1.9

 Natural resources and mining.................................... 0.2 2.4 -7.6 944 13.3

 Construction............................................................... 7.6 105.4 1.5 1,438 1.3

 Manufacturing............................................................ 5.3 159.6 -0.5 1,790 0.5

 Trade, transportation, and utilities.............................. 18.4 255.6 -0.3 1,112 3.6

 Information................................................................. 1.5 25.7 -1.0 2,603 10.3

 Financial activities...................................................... 12.8 115.2 -2.2 2,200 3.6

 Professional and business services........................... 23.1 319.2 2.2 1,452 1.1

 Education and health services................................... 36.9 226.2 3.9 982 1.1

 Leisure and hospitality............................................... 9.6 225.4 2.5 515 4.7

 Other services............................................................ 7.5 47.2 1.8 760 6.4

 Government.................................................................. 1.4 158.0 0.6 1,428 0.1

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

first quarter 2019 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-192

First

quarter

2019

Percent

change,

first quarter

2018-192

San Diego, CA................................................................ 114.7 1,469.9 1.1 $1,253 2.8

 Private industry............................................................. 112.7 1,232.7 1.2 1,239 3.5

 Natural resources and mining.................................... 0.7 9.5 -0.4 779 3.3

 Construction............................................................... 7.8 82.5 -0.3 1,282 3.1

 Manufacturing............................................................ 3.5 113.7 1.7 1,975 5.8

 Trade, transportation, and utilities.............................. 15.3 220.1 -0.1 960 2.7

 Information................................................................. 1.4 23.3 -2.1 2,038 6.6

 Financial activities...................................................... 11.0 74.6 -0.9 1,772 2.0

 Professional and business services........................... 20.7 248.9 1.3 1,816 4.3

 Education and health services................................... 34.3 208.2 3.2 991 1.5

 Leisure and hospitality............................................... 9.1 199.5 2.3 524 4.0

 Other services............................................................ 8.1 52.0 1.4 662 4.4

 Government.................................................................. 2.0 237.2 0.7 1,324 -0.4

King, WA......................................................................... 89.7 1,412.3 2.7 1,853 5.4

 Private industry............................................................. 89.1 1,240.3 3.0 1,906 5.2

 Natural resources and mining.................................... 0.4 2.8 -1.6 1,206 4.1

 Construction............................................................... 6.9 73.7 3.2 1,478 3.6

 Manufacturing............................................................ 2.5 105.2 3.8 2,190 4.1

 Trade, transportation, and utilities.............................. 13.8 270.4 1.3 1,838 8.1

 Information................................................................. 2.6 116.7 9.3 4,810 7.5

 Financial activities...................................................... 6.8 70.1 1.4 2,286 2.4

 Professional and business services........................... 18.6 231.7 2.4 2,058 -1.6

 Education and health services................................... 20.8 180.3 2.2 1,088 4.4

 Leisure and hospitality............................................... 7.5 142.0 2.6 588 3.9

 Other services............................................................ 9.3 47.4 6.7 946 4.1

 Government.................................................................. 0.6 172.0 0.7 1,473 6.3

Miami-Dade, FL............................................................... 101.9 1,164.7 1.8 1,129 1.7

 Private industry............................................................. 101.6 1,023.8 1.9 1,109 1.7

 Natural resources and mining.................................... 0.5 10.5 3.5 632 2.9

 Construction............................................................... 7.2 52.5 6.6 1,039 -2.3

 Manufacturing............................................................ 2.8 41.2 2.2 1,114 19.0

 Trade, transportation, and utilities.............................. 24.8 289.7 1.0 1,024 2.4

 Information................................................................. 1.6 19.0 1.2 1,980 -2.0

 Financial activities...................................................... 11.0 76.6 0.0 2,166 1.5

 Professional and business services........................... 23.3 161.5 2.7 1,344 -2.3

 Education and health services................................... 11.3 186.2 2.5 1,003 2.3

 Leisure and hospitality............................................... 7.5 145.8 1.1 641 2.9

 Other services............................................................ 8.6 39.1 1.2 734 11.9

 Government.................................................................. 0.3 140.9 1.0 1,279 2.4

1 Average weekly wages were calculated using unrounded data.

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

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

Note: Data are preliminary. Counties selected are based on 2018 annual average employment. Includes workers covered by Unemployment Insurance

(UI) and Unemployment Compensation for Federal Employees (UCFE) programs.
Table 3. Covered establishments, employment, and wages by state,

first quarter 2019

Employment Average weekly wage 1

State

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-19

First

quarter

2019

Percent

change,

first quarter

2018-19

United States2.......................................... 10,203.0 146,497.6 1.4 $1,184 2.8

Alabama.................................................... 129.4 1,978.0 1.6 944 2.5

Alaska........................................................ 22.1 312.4 0.3 1,108 3.3

Arizona...................................................... 164.5 2,895.1 2.5 1,056 3.0

Arkansas................................................... 92.0 1,218.5 0.7 896 2.2

California................................................... 1,586.4 17,436.4 1.8 1,401 3.8

Colorado.................................................... 207.6 2,690.3 1.9 1,231 4.8

Connecticut............................................... 122.4 1,650.6 0.0 1,487 2.3

Delaware................................................... 33.2 444.1 1.3 1,199 -0.1

District of Columbia................................... 40.5 773.5 0.5 1,921 0.2

Florida....................................................... 717.6 8,894.3 2.1 1,015 2.7

Georgia...................................................... 283.8 4,488.6 2.1 1,121 2.6

Hawaii........................................................ 44.5 658.1 -0.4 1,006 3.4

Idaho......................................................... 66.2 732.3 2.7 828 2.3

Illinois........................................................ 375.1 5,912.0 0.1 1,275 2.7

Indiana....................................................... 169.7 3,059.1 1.2 963 0.9

Iowa........................................................... 103.6 1,527.1 0.1 942 2.3

Kansas...................................................... 88.8 1,379.3 0.6 940 3.2

Kentucky.................................................... 122.8 1,882.6 0.6 920 2.2

Louisiana................................................... 134.8 1,916.8 -0.1 954 2.5

Maine......................................................... 54.1 599.8 1.2 919 3.1

Maryland.................................................... 174.1 2,670.3 0.9 1,228 1.7

Massachusetts.......................................... 263.0 3,558.1 1.1 1,561 3.5

Michigan.................................................... 249.7 4,307.4 0.6 1,078 0.1

Minnesota.................................................. 180.5 2,840.8 0.5 1,203 2.3

Mississippi................................................. 74.4 1,129.8 0.4 779 1.8

Missouri..................................................... 206.7 2,788.4 0.5 986 2.6

Montana.................................................... 48.7 458.8 0.9 844 3.1

Nebraska................................................... 72.2 965.6 0.1 917 2.2

Nevada...................................................... 83.2 1,392.2 3.0 992 1.5

New Hampshire......................................... 53.0 656.2 1.2 1,156 3.1

New Jersey............................................... 276.7 4,040.2 1.3 1,399 1.7

New Mexico............................................... 61.3 825.4 1.3 890 3.2

New York.................................................. 648.9 9,453.5 1.5 1,639 2.6

North Carolina........................................... 282.4 4,458.5 2.0 1,054 3.2

North Dakota............................................. 31.7 414.3 1.5 1,021 3.3

Ohio........................................................... 300.2 5,363.2 0.7 1,035 3.0

Oklahoma.................................................. 111.3 1,617.0 1.1 953 4.3

Oregon...................................................... 160.6 1,921.9 1.3 1,060 3.3

Pennsylvania............................................. 359.9 5,850.3 1.1 1,146 2.8

Rhode Island............................................. 38.7 474.7 0.8 1,104 1.8

South Carolina.......................................... 138.2 2,110.0 2.0 901 3.0

South Dakota............................................ 34.0 419.0 0.4 865 2.7

Tennessee................................................. 166.2 3,004.2 2.0 996 1.9

Texas......................................................... 705.3 12,455.6 2.2 1,204 3.1

Utah........................................................... 106.0 1,501.4 3.0 978 3.1

Vermont..................................................... 25.9 309.1 0.4 950 3.7

Virginia...................................................... 284.6 3,896.9 1.2 1,186 2.1

Washington............................................... 250.4 3,371.1 1.8 1,368 4.9

West Virginia............................................. 51.3 687.1 0.3 896 3.2

Wisconsin.................................................. 178.1 2,838.9 0.1 992 2.6

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

first quarter 2019 - Continued

Employment Average weekly wage 1

State

Establishments,

first quarter

2019

(thousands)

March

2019

(thousands)

Percent

change,

March

2018-19

First

quarter

2019

Percent

change,

first quarter

2018-19

Wyoming................................................... 26.7 269.0 1.9 $948 3.7

Puerto Rico............................................... 45.9 875.8 2.2 553 -2.1

Virgin Islands............................................ 3.4 36.6 9.6 966 -1.0

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.