For release 10:00 a.m. (EDT), Wednesday, September 7, 2016 USDL-16-1806 

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 2016 

From March 2015 to March 2016, employment increased in 318 of the 344 largest U.S. counties, the 

U.S. Bureau of Labor Statistics reported today. Williamson, Tenn., had the largest percentage increase 

with a gain of 7.9 percent over the year, above the national job growth rate of 2.0 percent. Within 

Williamson, the largest employment increase occurred in professional and business services, which 

gained 3,598 jobs over the year (11.9 percent). Midland, Texas, had the largest over-the-year percentage 

decrease in employment among the largest counties in the U.S., with a loss of 9.0 percent. Within 

Midland, natural resources and mining had the largest decrease in employment, with a loss of 3,292 jobs 

(-15.0 percent). County employment and wage data are from the Quarterly Census of Employment and 

Wages (QCEW) program, which provides the only detailed quarterly and annual universe count of 

establishments, employment, and wages at the county, MSA, state, and national levels by detailed 

industry. These detailed data are published within 6 months following the end of each calendar quarter. 

The U.S. average weekly wage decreased 0.5 percent over the year, declining to $1,043 in the first 

quarter of 2016. This is one of only seven declines in the history of the series which dates back to 1978. 

McLean, Ill., had the largest over-the-year percentage decrease in average weekly wages with a loss of 

13.3 percent. Within McLean, an average weekly wage loss of $659 (-31.4 percent) in financial 

activities made the largest contribution to the county’s decrease in average weekly wages. Clayton, Ga., 

experienced the largest percentage increase in average weekly wages with a gain of 15.5 percent over 

the year. Within Clayton, trade, transportation, and utilities had the largest impact on the county’s 

average weekly wage growth with an increase of $305 (23.7 percent) over the year. 

Chart 1. Large counties ranked by percent increase in 

employment, March 2015-16 

(U.S. average = 2.0 percent)

Chart 2. Large counties ranked by percent decline in 

average weekly wages, first quarter 2015-16 

(U.S. average = -0.5 percent) 

5

6

7

8

Williamson,

Tenn.

Utah,

Utah

Loudoun,

Va.

Rutherford,

Tenn.

Lee,

Fla.

Percent

-14

-12

-10

-8

McLean,

Ill.

Washington,

Pa.

Lafayette,

La.

Mercer,

N.J.

Williamson,

Texas

Percent
- 2 - 

Large County Employment 

In March 2016, national employment was 140.1 million (as measured by the QCEW program). Over the 

year, employment increased 2.0 percent, or 2.7 million. In March 2016, the 344 U.S. counties with 

75,000 or more jobs accounted for 72.6 percent of total U.S. employment and 78.8 percent of total 

wages. These 344 counties had a net job growth of 2.1 million over the year, accounting for 77.9 percent 

of the overall U.S. employment increase. (See chart 3.) The five counties with the largest increases in 

employment levels had a combined over-the-year employment gain of 277,300 jobs, which was 10.3 

percent of the overall job increase for the U.S. (See table A.) 

Employment declined in 25 of the largest counties from March 2015 to March 2016. Midland, Texas, 

had the largest over-the-year percentage decrease in employment (-9.0 percent), followed by Lafayette, 

La.; Gregg, Texas; McLean, Ill.; and Weld, Colo. (See table 1.) 

Table A. Large counties ranked by March 2016 employment, March 2015-16 employment increase, and 

March 2015-16 percent increase in employment 

 

Employment in large counties 

 

March 2016 employment Increase in employment, Percent increase in employment, 

(thousands) March 2015-16 March 2015-16 

 (thousands) 

United States 140,070.8 United States 2,683.0 United States 2.0 

Los Angeles, Calif. 4,309.9 Los Angeles, Calif. 79.7 Williamson, Tenn. 7.9

Cook, Ill. 2,515.9 Maricopa, Ariz. 58.9 Utah, Utah 6.7

New York, N.Y. 2,396.8 Dallas, Texas 49.4 Loudoun, Va. 6.2

Harris, Texas 2,256.9 New York, N.Y. 44.8 Rutherford, Tenn. 5.5

Maricopa, Ariz. 1,864.4 King, Wash. 44.5 Lee, Fla. 5.1

Dallas, Texas 1,614.7 Orange, Calif. 35.8 Benton, Ark. 5.0

Orange, Calif. 1,545.7 San Francisco, Calif. 32.1 Osceola, Fla. 5.0

San Diego, Calif. 1,388.4 Fulton, Ga. 31.4 San Francisco, Calif. 4.8

King, Wash. 1,294.1 Riverside, Calif. 31.0 Riverside, Calif. 4.7

Miami-Dade, Fla. 1,107.3 San Diego, Calif. 30.9 Washoe, Nev. 4.7

 Cook, Ill. 30.9 Horry, S.C. 4.7

Large County Average Weekly Wages 

Average weekly wages for the nation decreased to $1,043, a 0.5 percent decrease, during the year ending 

in the first quarter of 2016. Among the 344 largest counties, 167 had over-the-year decreases in average 

weekly wages. (See chart 4.) McLean, Ill., had the largest percentage wage decrease among the largest 

U.S. counties (-13.3 percent). (See table B.) 

Of the 344 largest counties, 164 experienced over-the-year increases in average weekly wages. Clayton, 

Ga., had the largest percentage increase in average weekly wages (15.5 percent), followed by King, 

Wash.; San Mateo, Calif.; Ventura, Calif.; and Merrimack, N.H. (See table 1.) 
- 3 - 

Table B. Large counties ranked by first quarter 2016 average weekly wages, first quarter 2015-16 

decrease in average weekly wages, and first quarter 2015-16 percent decrease in average weekly wages 

 

Average weekly wage in large counties 

 

Average weekly wage, Decrease in average weekly Percent decrease in average 

first quarter 2016 wage, first quarter 2015-16 weekly wage, first 

 quarter 2015-16 

United States $1,043 United States -$5 United States -0.5 

New York, N.Y. $2,783 Washington, Pa. -$146 McLean, Ill. -13.3

Santa Clara, Calif. 2,210 McLean, Ill. -137 Washington, Pa. -12.0

San Mateo, Calif. 2,195 Mercer, N.J. -129 Lafayette, La. -10.3

San Francisco, Calif. 2,054 Lafayette, La. -98 Mercer, N.J. -8.5

Somerset, N.J. 2,022 Somerset, N.J. -93 Williamson, Texas -7.8

Fairfield, Conn. 1,899 Williamson, Texas -85 Orange, Calif. -6.4

Suffolk, Mass. 1,890 Orange, Calif. -78 Allegheny, Pa. -6.2

Washington, D.C. 1,766 Midland, Texas -76 Tulsa, Okla. -5.9

Arlington, Va. 1,734 Allegheny, Pa. -75 Gregg, Texas -5.9

Morris, N.J. 1,696 Morris, N.J. -74 St. Louis, Minn. -5.8

 Harris, Texas -74 

Ten Largest U.S. Counties 

Among the 10 largest counties, 9 had over-the-year percentage increases in employment in March 2016. 

King, Wash., had the largest gain (3.6 percent). Within King, professional and business services had the 

largest over-the-year employment level increase, with a gain of 9,047 jobs, or 4.4 percent. Harris, Texas, 

had the only percentage decrease in employment among the 10 largest counties (-1.2 percent). (See table 

2.) 

Average weekly wages decreased over the year in 8 of the 10 largest U.S. counties. Orange, Calif., 

experienced the largest percentage loss in average weekly wages (-6.4 percent). Within Orange, 

professional and business services had the largest impact on the county’s average weekly wage decline. 

Within professional and business services, average weekly wages decreased by $388, or -22.4 percent, 

over the year. King, Wash., had the largest percentage gain in average weekly wages among the 10 

largest counties (5.1 percent). 

 
- 4 - 

For More Information

The tables and charts included in this release contain data for the nation and for the 344 U.S. counties 

with annual average employment levels of 75,000 or more in 2015. March 2016 employment and 2016 

first quarter average weekly wages for all states are provided in table 3 of this release. 

The data are derived from reports submitted by every employer subject to unemployment insurance (UI) 

laws. The 9.7 million employer reports cover 140.1 million full- and part-time workers. Data for the first 

quarter of 2016 will be available electronically later at www.bls.gov/cew/. For additional information 

about the quarterly employment and wages data, please read the Technical Note. Additional information 

about the QCEW data may be obtained by calling (202) 691-6567. 

Several BLS regional offices issue QCEW news releases targeted to local data users. For links to these 

releases, see www.bls.gov/cew/cewregional.htm. 

 

The County Employment and Wages release for second quarter 2016 is scheduled to be released 

on Wednesday, December 7, 2016. 

County Changes for the 2016 County Employment and Wages News Releases 

Counties with annual average employment of 75,000 or more in 2015 are included in this release and 

will be included in future 2016 releases. Four counties have been added to the publication tables: 

Merced, Calif.; Napa, Calif.; Bay, Fla.; and Merrimack, N.H. Two counties, Black Hawk, Iowa, and 

Ector, Texas, which were published in the 2015 releases, will be excluded from this and future 2016 

releases because their 2015 annual average employment levels were less than 75,000. 

Change in Oregon Public University Classification 

Prior to this release, public universities in the state of Oregon were classified in QCEW under state 

government ownership. Beginning with data in this release for first quarter 2016, QCEW classifies 

these establishments in local government ownership. The industry classification for these institutions 

has not changed. 

This change in ownership resulted from the passage in 2011 and 2013 of state legislation which 

created a new legal entity called “universities with governing boards.” Public universities in Oregon 

were reorganized in 2014 and 2015 under this new legal entity. They are now independent public 

bodies that can establish their budgets without state approval. This new political subdivision will be 

classified under local government ownership. 

For more information, contact the Oregon Labor Market Information group at sf202_or@bls.gov. 
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 2012 North American Industry 

Classification System. Data for 2016 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 345 counties 

presented in this release were derived using 2015 preliminary annual averages of employment. For 2016 data, four counties have 

been added to the publication tables: Merced, Calif.; Napa, Calif.; 

Bay, Fla.; and Merrimack, N.H. These counties will be included in 

all 2016 quarterly releases. Two counties, Black Hawk, Iowa, and 

Ector, Texas, which were published in the 2015 releases, will be 

excluded from this and future 2016 releases because their 2015 annual average employment levels were less than 75,000. 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 9.7 million establishments in first quarter of 2016 

 Count of longitudinally-linked UI administrative records submitted by 

7.6 million private-sector employers 

 Sample survey: 623,000 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 6 months after the end of 

each quarter 

 Quarterly 

— 7 months after the end of each 

quarter 

 Monthly 

— Usually first Friday of following 

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, 

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 national 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. Each of these measures—

QCEW, Business Employment Dynamics (BED), and Current Employment Statistics (CES)—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 9.5 million employer 

reports of employment and wages submitted by states to the BLS in 

2015. 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 2015, UI and 

UCFE programs covered workers in 139.5 million jobs. The estimated 

134.4 million workers in these jobs (after adjustment for multiple jobholders) represented 96.5 percent of civilian wage and salary employment. Covered workers received $7.385 trillion in pay, representing 

94.0 percent of the wage and salary component of personal income 

and 40.9 percent of the gross domestic product. 

Major exclusions from UI coverage include self-employed workers, most agricultural workers on small farms, all members of the 

Armed Forces, elected officials in most states, most employees of railroads, some domestic workers, most student workers at schools, and 

employees of certain small nonprofit organizations. 

State and federal UI laws change periodically. These changes may 

have an impact on the employment and wages reported by employers 

covered under the UI program. Coverage changes may affect the 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—some reflecting economic events, others reflecting 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 2015 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 account for 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 2014 edition of this 

publication, which was published in September 2015, contains selected data produced by Business Employment Dynamics (BED) on 

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

2015 version of this news release. Tables and additional content from 

the 2014 edition of Employment and Wages Annual Averages Online 

are now available at http://www.bls.gov/cew/cewbultn14.htm. The 

2015 edition of Employment and Wages Annual Averages Online will 

be available in September 2016. 

News releases on quarterly measures of gross job flows also are 

available upon request from the Division of Administrative Statistics 

and Labor Turnover (Business Employment Dynamics), telephone 

(202) 691-6467; (http://www.bls.gov/bdm/); (e-mail: 

BDMInfo@bls.gov). 

Information in this release will be made available to sensory impaired individuals upon request. Voice phone: (202) 691-5200; TDD 

message referral phone number: 1-800-877-8339. 
Table 1. Covered establishments, employment, and wages in the 345 largest counties,

first quarter 2016

Employment Average weekly wage 2

County1

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-163

Ranking by

percent

change

First

quarter

2016

Percent

change,

first quarter

2015-163

Ranking by

percent

change

United States4.............................. 9,693.5 140,070.8 2.0 - $1,043 -0.5 -

Jefferson, AL................................ 18.1 337.5 0.9 273 1,030 -3.5 311

Madison, AL................................. 9.3 189.9 3.4 55 1,066 1.1 88

Mobile, AL.................................... 9.9 168.4 0.8 283 819 -1.7 254

Montgomery, AL........................... 6.4 130.0 1.5 224 810 0.7 114

Shelby, AL.................................... 5.6 83.5 1.6 211 991 0.3 144

Tuscaloosa, AL............................. 4.4 90.9 0.1 316 800 0.5 129

Anchorage Borough, AK............... 8.4 149.3 -1.1 331 1,065 -2.9 300

Maricopa, AZ................................ 94.8 1,864.4 3.3 63 972 -1.5 247

Pima, AZ....................................... 18.7 359.2 1.2 251 829 1.3 72

Benton, AR................................... 6.0 113.4 5.0 6 1,266 -2.8 298

Pulaski, AR................................... 14.4 246.4 1.9 176 896 1.0 98

Washington, AR........................... 5.9 102.4 3.6 44 798 3.2 14

Alameda, CA................................ 60.6 739.0 2.0 168 1,353 1.3 72

Butte, CA..................................... 8.1 79.1 2.4 130 723 0.1 155

Contra Costa, CA......................... 31.2 354.0 3.4 55 1,285 -1.2 233

Fresno, CA................................... 33.1 365.1 2.4 130 774 0.8 108

Kern, CA....................................... 17.9 294.7 -0.8 326 847 -2.4 287

Los Angeles, CA........................... 464.3 4,309.9 1.9 176 1,138 2.1 34

Marin, CA..................................... 12.3 112.5 1.7 200 1,282 3.8 8

Merced, CA................................. 6.3 72.8 0.9 273 742 1.2 79

Monterey, CA............................... 13.4 169.4 0.3 310 852 0.5 129

Napa, CA..................................... 5.7 73.6 0.7 289 957 1.8 47

Orange, CA.................................. 113.9 1,545.7 2.4 130 1,143 -6.4 338

Placer, CA.................................... 12.3 153.6 4.6 12 995 1.0 98

Riverside, CA............................... 58.7 686.0 4.7 9 823 -4.5 325

Sacramento, CA........................... 54.7 630.6 2.7 109 1,102 -0.3 191

San Bernardino, CA..................... 54.9 694.1 2.4 130 822 1.2 79

San Diego, CA.............................. 105.9 1,388.4 2.3 142 1,108 -2.0 270

San Francisco, CA....................... 59.4 696.4 4.8 8 2,054 -2.1 277

San Joaquin, CA.......................... 17.4 234.2 3.6 44 821 0.7 114

San Luis Obispo, CA.................... 10.2 115.7 1.4 235 821 2.0 38

San Mateo, CA............................. 27.4 383.9 2.6 116 2,195 4.8 3

Santa Barbara, CA....................... 15.1 192.4 0.3 310 933 0.1 155

Santa Clara, CA........................... 69.7 1,025.7 3.1 78 2,210 1.9 42

Santa Cruz, CA............................ 9.5 98.3 2.0 168 881 3.2 14

Solano, CA................................... 10.8 134.2 3.5 50 1,070 1.9 42

Sonoma, CA................................. 19.5 198.9 2.4 130 923 0.0 165

Stanislaus, CA.............................. 14.9 179.3 2.7 109 840 1.7 59

Tulare, CA.................................... 9.8 152.7 1.9 176 708 2.8 18

Ventura, CA.................................. 25.8 319.6 0.2 314 1,083 4.4 4

Yolo, CA....................................... 6.5 97.2 1.0 263 1,028 0.7 114

Adams, CO................................... 10.3 193.6 2.7 109 941 1.1 88

Arapahoe, CO.............................. 21.3 317.2 2.6 116 1,248 -0.2 187

Boulder, CO.................................. 14.6 174.0 2.3 142 1,176 -1.6 250

Denver, CO.................................. 30.4 485.3 2.8 99 1,312 -3.0 301

Douglas, CO................................. 11.4 113.9 3.0 86 1,195 -2.1 277

El Paso, CO.................................. 18.5 259.3 3.6 44 877 -0.8 219

Jefferson, CO............................... 19.4 229.6 2.4 130 1,024 0.5 129

Larimer, CO.................................. 11.5 148.3 3.8 33 897 -1.0 222

Weld, CO...................................... 6.9 99.2 -2.6 339 895 -3.8 316

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 345 largest counties,

first quarter 2016 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-163

Ranking by

percent

change

First

quarter

2016

Percent

change,

first quarter

2015-163

Ranking by

percent

change

Fairfield, CT................................. 35.0 419.6 0.9 273 $1,899 -1.7 254

Hartford, CT.................................. 27.3 501.1 0.3 310 1,363 -3.1 305

New Haven, CT............................ 23.6 359.4 1.0 263 1,042 0.7 114

New London, CT.......................... 7.3 120.6 1.4 235 1,033 -0.1 177

New Castle, DE............................ 19.2 282.8 0.7 289 1,224 -3.7 314

Washington, DC........................... 38.7 749.6 2.0 168 1,766 0.4 137

Alachua, FL.................................. 7.0 126.5 3.3 63 807 0.6 123

Bay, FL......................................... 5.5 78.2 1.6 211 711 0.1 155

Brevard, FL................................... 15.2 197.4 2.0 168 846 -1.6 250

Broward, FL.................................. 67.8 780.4 2.8 99 926 0.2 147

Collier, FL..................................... 13.3 143.8 2.4 130 844 2.2 32

Duval, FL..................................... 28.3 482.9 3.1 78 991 -0.2 187

Escambia, FL............................... 8.1 129.2 3.1 78 783 2.1 34

Hillsborough, FL........................... 40.4 667.4 3.8 33 977 0.4 137

Lake, FL....................................... 7.8 92.7 3.2 69 653 0.8 108

Lee, FL......................................... 20.9 254.1 5.1 5 771 1.3 72

Leon, FL....................................... 8.5 145.3 1.3 242 780 0.6 123

Manatee, FL................................. 10.3 121.0 3.2 69 749 3.5 11

Marion, FL.................................... 8.1 98.9 2.2 150 671 1.4 70

Miami-Dade, FL............................ 95.9 1,107.3 2.7 109 972 -0.3 191

Okaloosa, FL................................ 6.2 81.4 3.0 86 795 -1.1 224

Orange, FL................................... 40.0 789.2 3.7 41 895 0.6 123

Osceola, FL.................................. 6.4 88.4 5.0 6 665 -0.7 216

Palm Beach, FL............................ 54.2 591.1 4.3 18 995 -0.6 211

Pasco, FL..................................... 10.5 113.1 3.7 41 670 1.8 47

Pinellas, FL................................... 32.1 416.8 2.5 124 865 0.0 165

Polk, FL........................................ 12.8 209.8 2.9 94 754 2.4 24

Sarasota, FL................................ 15.4 164.1 2.8 99 800 1.1 88

Seminole, FL................................ 14.5 180.0 4.5 14 833 0.2 147

Volusia, FL................................... 13.9 167.6 3.3 63 694 0.3 144

Bibb, GA....................................... 4.5 81.2 2.3 142 778 0.9 102

Chatham, GA................................ 8.6 147.0 2.7 109 833 -1.9 264

Clayton, GA.................................. 4.5 120.4 4.0 28 1,146 15.5 1

Cobb, GA...................................... 23.7 342.8 3.4 55 1,128 0.6 123

DeKalb, GA................................. 19.7 290.6 1.5 224 1,085 1.5 66

Fulton, GA.................................... 46.8 808.9 4.0 28 1,562 2.8 18

Gwinnett, GA................................ 26.8 339.4 3.2 69 989 -0.9 220

Hall, GA....................................... 4.7 81.9 4.6 12 810 -1.6 250

Muscogee, GA.............................. 4.9 92.8 0.1 316 851 1.2 79

Richmond, GA.............................. 4.8 103.9 -0.3 320 825 -0.4 201

Honolulu, HI.................................. 25.5 470.1 1.3 242 935 1.9 42

Ada, ID......................................... 14.4 222.3 4.2 21 839 -3.9 317

Champaign, IL.............................. 4.4 87.8 -0.8 326 859 0.9 102

Cook, IL........................................ 154.9 2,515.9 1.2 251 1,278 -0.2 187

DuPage, IL................................. 38.4 605.2 1.2 251 1,204 0.4 137

Kane, IL........................................ 13.8 202.0 1.0 263 860 0.2 147

Lake, IL........................................ 22.4 325.4 1.0 263 1,532 -3.2 307

McHenry, IL.................................. 8.8 93.8 1.2 251 805 -0.5 207

McLean, IL.................................... 3.8 82.6 -2.7 340 893 -13.3 343

Madison, IL................................... 6.0 96.0 0.3 310 782 -2.1 277

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 345 largest counties,

first quarter 2016 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-163

Ranking by

percent

change

First

quarter

2016

Percent

change,

first quarter

2015-163

Ranking by

percent

change

Peoria, IL...................................... 4.6 99.1 -0.9 328 $1,035 -3.2 307

St. Clair, IL.................................... 5.5 92.5 0.5 303 761 0.9 102

Sangamon, IL............................... 5.3 128.2 -0.1 319 988 -1.1 224

Will, IL.......................................... 16.2 219.9 2.0 168 851 0.2 147

Winnebago, IL.............................. 6.7 126.1 0.9 273 832 -1.4 243

Allen, IN........................................ 8.8 180.4 1.9 176 835 -0.7 216

Elkhart, IN..................................... 4.7 126.3 3.4 55 849 1.8 47

Hamilton, IN.................................. 9.1 134.0 4.4 16 1,027 -0.4 201

Lake, IN........................................ 10.4 183.3 -0.4 321 850 -4.2 319

Marion, IN..................................... 23.9 583.6 1.4 235 1,069 -0.4 201

St. Joseph, IN............................... 5.8 121.3 3.0 86 781 -1.1 224

Tippecanoe, IN............................. 3.4 81.8 0.8 283 871 0.2 147

Vanderburgh, IN........................... 4.8 105.6 0.8 283 799 -3.0 301

Johnson, IA.................................. 4.1 82.0 1.1 260 906 1.1 88

Linn, IA......................................... 6.6 128.3 0.4 306 954 -4.6 328

Polk, IA........................................ 16.9 288.5 2.5 124 1,058 -1.3 239

Scott, IA........................................ 5.5 89.1 0.9 273 793 0.0 165

Johnson, KS................................. 22.9 331.4 0.9 273 1,041 -4.3 322

Sedgwick, KS............................... 12.7 248.3 0.9 273 871 -4.2 319

Shawnee, KS................................ 5.3 95.9 0.6 295 844 3.3 13

Wyandotte, KS............................. 3.6 89.0 1.8 192 951 -1.9 264

Boone, KY................................... 4.3 82.3 3.8 33 853 2.2 32

Fayette, KY................................... 10.7 187.6 1.7 200 861 -2.4 287

Jefferson, KY................................ 25.1 454.0 2.8 99 1,013 -0.3 191

Caddo, LA.................................... 7.2 114.3 -1.0 330 776 -2.0 270

Calcasieu, LA............................... 5.0 94.2 2.8 99 889 3.6 10

East Baton Rouge, LA.................. 15.0 269.8 1.0 263 930 -1.5 247

Jefferson, LA................................ 13.4 191.9 -1.2 332 875 -1.0 222

Lafayette, LA................................ 9.3 132.1 -5.5 342 857 -10.3 341

Orleans, LA.................................. 12.0 193.1 1.8 192 981 -2.0 270

St. Tammany, LA.......................... 7.8 87.1 2.0 168 852 -3.0 301

Cumberland, ME.......................... 13.5 173.0 1.9 176 935 1.1 88

Anne Arundel, MD........................ 15.0 260.9 2.1 158 1,068 -0.5 207

Baltimore, MD............................... 21.2 372.6 1.7 200 993 0.0 165

Frederick, MD............................... 6.4 98.5 1.8 192 940 -2.5 293

Harford, MD.................................. 5.8 89.6 1.5 224 961 -2.1 277

Howard, MD................................. 9.9 165.6 2.6 116 1,233 -0.4 201

Montgomery, MD.......................... 32.7 459.0 1.4 235 1,403 -0.6 211

Prince George's, MD.................... 15.8 306.6 1.5 224 1,022 -1.9 264

Baltimore City, MD....................... 13.6 333.3 1.2 251 1,210 -2.6 295

Barnstable, MA............................. 9.3 85.7 3.0 86 846 0.7 114

Bristol, MA.................................... 17.1 219.1 2.3 142 896 -4.3 322

Essex, MA.................................... 24.0 317.1 1.7 200 1,069 1.8 47

Hampden, MA.............................. 17.5 204.2 1.5 224 921 0.7 114

Middlesex, MA.............................. 53.4 873.3 1.8 192 1,568 -3.5 311

Norfolk, MA................................... 24.7 343.1 2.4 130 1,191 0.4 137

Plymouth, MA............................... 15.2 184.0 2.4 130 916 1.8 47

Suffolk, MA................................... 27.8 646.0 2.7 109 1,890 -1.2 233

Worcester, MA.............................. 24.0 334.6 1.7 200 996 1.8 47

Genesee, MI................................. 6.9 131.5 0.8 283 808 -1.8 260

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 345 largest counties,

first quarter 2016 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-163

Ranking by

percent

change

First

quarter

2016

Percent

change,

first quarter

2015-163

Ranking by

percent

change

Ingham, MI................................... 6.0 147.7 2.9 94 $951 0.0 165

Kalamazoo, MI............................. 5.0 115.8 2.2 150 961 0.8 108

Kent, MI....................................... 14.2 388.1 3.0 86 870 1.6 63

Macomb, MI.................................. 17.6 314.2 2.3 142 1,028 2.7 20

Oakland, MI.................................. 39.0 706.1 2.3 142 1,147 -0.1 177

Ottawa, MI.................................... 5.6 120.0 4.5 14 816 -2.4 287

Saginaw, MI.................................. 4.0 83.7 1.9 176 801 1.9 42

Washtenaw, MI............................. 8.1 205.6 2.1 158 1,047 1.2 79

Wayne, MI.................................... 30.6 699.6 1.0 263 1,156 1.1 88

Anoka, MN.................................... 6.7 118.0 1.4 235 901 -1.2 233

Dakota, MN.................................. 9.3 181.9 0.5 303 997 -1.7 254

Hennepin, MN.............................. 38.3 888.5 2.2 150 1,361 -1.9 264

Olmsted, MN................................ 3.2 95.1 4.1 25 1,162 1.1 88

Ramsey, MN................................. 12.6 323.1 1.0 263 1,215 -3.1 305

St. Louis, MN................................ 5.1 94.5 -0.9 328 786 -5.8 334

Stearns, MN................................. 4.1 83.4 0.4 306 822 3.5 11

Washington, MN........................... 5.2 78.5 3.2 69 856 -1.7 254

Harrison, MS................................ 4.5 83.7 1.6 211 702 -1.1 224

Hinds, MS..................................... 5.9 120.5 0.7 289 850 1.1 88

Boone, MO................................... 4.8 92.2 2.6 116 770 -0.3 191

Clay, MO...................................... 5.5 99.8 3.8 33 896 1.2 79

Greene, MO.................................. 8.5 161.7 1.7 200 740 -1.9 264

Jackson, MO................................ 20.9 359.3 1.6 211 1,030 2.1 34

St. Charles, MO............................ 9.0 141.3 2.5 124 856 0.1 155

St. Louis, MO................................ 36.0 592.2 1.6 211 1,074 -2.3 284

St. Louis City, MO........................ 13.1 222.2 1.3 242 1,147 -2.4 287

Yellowstone, MT........................... 6.5 80.4 1.6 211 822 -1.4 243

Douglas, NE................................. 18.8 332.8 1.9 176 947 -1.5 247

Lancaster, NE............................... 10.0 166.6 1.9 176 802 0.6 123

Clark, NV..................................... 55.6 923.8 2.8 99 866 1.5 66

Washoe, NV................................. 14.8 205.6 4.7 9 853 0.2 147

Hillsborough, NH.......................... 12.2 197.7 1.9 176 1,085 1.3 72

Merrimack, NH............................. 5.1 75.6 1.2 251 907 4.3 5

Rockingham, NH.......................... 10.8 142.8 3.1 78 982 0.0 165

Atlantic, NJ................................... 6.6 121.7 1.2 251 838 0.5 129

Bergen, NJ................................... 33.1 440.3 1.3 242 1,227 -0.3 191

Burlington, NJ............................... 11.1 198.0 2.3 142 1,035 -2.2 282

Camden, NJ................................. 12.1 198.7 3.5 50 960 0.2 147

Essex, NJ.................................... 20.6 338.4 1.9 176 1,362 0.3 144

Gloucester, NJ.............................. 6.3 103.1 3.3 63 840 -1.2 233

Hudson, NJ................................... 14.7 248.6 3.2 69 1,523 -1.4 243

Mercer, NJ.................................... 11.2 241.8 2.9 94 1,395 -8.5 340

Middlesex, NJ.............................. 22.1 409.0 2.2 150 1,299 -2.1 277

Monmouth, NJ.............................. 20.2 251.8 3.1 78 1,006 1.2 79

Morris, NJ..................................... 17.1 283.9 2.1 158 1,696 -4.2 319

Ocean, NJ.................................... 13.0 156.8 3.7 41 809 2.3 29

Passaic, NJ.................................. 12.4 164.9 1.0 263 981 1.3 72

Somerset, NJ............................... 10.1 181.4 2.9 94 2,022 -4.4 324

Union, NJ..................................... 14.3 216.4 (5) - 1,324 (5) -

Bernalillo, NM............................... 18.3 319.4 1.3 242 841 -0.4 201

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 345 largest counties,

first quarter 2016 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-163

Ranking by

percent

change

First

quarter

2016

Percent

change,

first quarter

2015-163

Ranking by

percent

change

Albany, NY................................... 10.4 230.0 0.7 289 $1,023 2.0 38

Bronx, NY..................................... 18.7 300.2 1.2 251 927 2.5 23

Broome, NY.................................. 4.6 86.2 0.5 303 758 0.4 137

Dutchess, NY............................... 8.5 109.5 0.6 295 954 -0.6 211

Erie, NY........................................ 24.8 459.9 1.1 260 893 0.9 102

Kings, NY..................................... 61.1 678.4 3.8 33 825 1.5 66

Monroe, NY.................................. 18.9 381.3 1.7 200 923 -1.1 224

Nassau, NY.................................. 54.1 614.0 2.2 150 1,128 2.4 24

New York, NY............................... 130.3 2,396.8 1.9 176 2,783 -1.9 264

Oneida, NY................................... 5.4 102.3 0.7 289 771 1.3 72

Onondaga, NY.............................. 13.1 241.0 0.9 273 916 1.9 42

Orange, NY.................................. 10.4 138.3 1.6 211 826 1.8 47

Queens, NY.................................. 52.2 639.1 3.0 86 963 2.6 21

Richmond, NY.............................. 9.8 113.5 2.6 116 865 4.2 6

Rockland, NY............................... 10.6 118.1 1.8 192 1,007 -0.5 207

Saratoga, NY................................ 5.9 82.4 2.1 158 881 0.0 165

Suffolk, NY................................... 52.7 635.9 1.5 224 1,060 1.2 79

Westchester, NY.......................... 36.7 417.1 1.9 176 1,416 0.1 155

Buncombe, NC............................. 8.9 125.6 4.3 18 738 1.7 59

Catawba, NC................................ 4.4 84.6 4.0 28 748 -1.2 233

Cumberland, NC........................... 6.3 119.6 1.5 224 751 1.8 47

Durham, NC................................. 8.1 193.1 1.8 192 1,315 -3.7 314

Forsyth, NC.................................. 9.3 181.3 1.2 251 1,019 0.4 137

Guilford, NC.................................. 14.4 275.3 1.6 211 871 -3.4 310

Mecklenburg, NC.......................... 36.8 652.1 4.1 25 1,365 -1.8 260

New Hanover, NC........................ 7.8 107.2 3.4 55 802 2.4 24

Wake, NC..................................... 32.9 517.6 4.2 21 1,053 1.2 79

Cass, ND...................................... 6.9 114.3 0.6 295 895 -2.2 282

Butler, OH..................................... 7.6 147.9 3.6 44 900 -0.1 177

Cuyahoga, OH.............................. 35.6 707.5 0.9 273 1,048 -2.0 270

Delaware, OH............................... 5.0 82.7 3.3 63 1,096 0.0 165

Franklin, OH................................. 31.1 724.2 3.1 78 1,041 0.1 155

Hamilton, OH................................ 23.6 501.2 1.6 211 1,106 -1.1 224

Lake, OH...................................... 6.3 93.3 0.8 283 833 0.0 165

Lorain, OH.................................... 6.2 95.3 1.0 263 782 -2.7 297

Lucas, OH.................................... 10.1 207.5 2.4 130 886 0.5 129

Mahoning, OH.............................. 5.9 96.6 0.2 314 683 -2.6 295

Montgomery, OH.......................... 12.0 251.5 2.4 130 843 -1.3 239

Stark, OH..................................... 8.6 155.9 0.6 295 726 -4.5 325

Summit, OH................................. 14.1 261.1 0.6 295 946 1.0 98

Warren, OH................................. 4.7 88.8 3.9 31 912 0.2 147

Cleveland, OK.............................. 5.5 81.3 0.7 289 700 -0.3 191

Oklahoma, OK.............................. 27.4 444.8 -0.6 324 951 -5.2 332

Tulsa, OK..................................... 22.0 347.1 -0.5 322 921 -5.9 335

Clackamas, OR............................ 14.5 154.7 3.2 69 916 0.5 129

Jackson, OR................................ 7.2 83.3 3.6 44 751 0.9 102

Lane, OR...................................... 12.0 148.5 2.5 124 749 -0.9 220

Marion, OR................................... 10.4 145.3 3.5 50 784 1.7 59

Multnomah, OR............................ 33.9 487.5 3.4 55 1,065 3.7 9

Washington, OR........................... 18.8 277.9 2.8 99 1,247 -2.3 284

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 345 largest counties,

first quarter 2016 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-163

Ranking by

percent

change

First

quarter

2016

Percent

change,

first quarter

2015-163

Ranking by

percent

change

Allegheny, PA............................... 35.7 678.1 0.4 306 $1,128 -6.2 337

Berks, PA..................................... 9.0 169.4 1.5 224 878 -0.5 207

Bucks, PA..................................... 19.8 255.3 1.9 176 929 -0.1 177

Butler, PA..................................... 5.0 84.0 1.5 224 902 -1.8 260

Chester, PA.................................. 15.5 244.9 1.8 192 1,343 -2.5 293

Cumberland, PA........................... 6.4 130.2 2.2 150 907 -0.7 216

Dauphin, PA................................ 7.5 177.2 1.4 235 984 -4.7 329

Delaware, PA............................... 14.0 216.9 1.3 242 1,117 -1.3 239

Erie, PA........................................ 7.1 121.0 -1.4 334 769 -0.1 177

Lackawanna, PA.......................... 5.8 96.3 0.6 295 751 0.0 165

Lancaster, PA............................... 13.3 230.3 2.7 109 823 1.1 88

Lehigh, PA.................................... 8.7 183.0 2.3 142 1,004 0.0 165

Luzerne, PA.................................. 7.5 142.1 1.3 242 772 -2.4 287

Montgomery, PA........................... 27.5 477.3 2.1 158 1,371 -0.3 191

Northampton, PA.......................... 6.7 109.1 3.1 78 881 -0.1 177

Philadelphia, PA........................... 35.1 654.2 1.5 224 1,206 -1.7 254

Washington, PA............................ 5.5 84.4 -2.5 338 1,066 -12.0 342

Westmoreland, PA....................... 9.3 131.3 1.0 263 791 0.1 155

York, PA....................................... 9.0 174.7 1.6 211 862 0.8 108

Providence, RI.............................. 17.5 280.7 1.5 224 1,038 -3.2 307

Charleston, SC............................. 14.4 238.2 3.4 55 894 1.6 63

Greenville, SC.............................. 14.0 259.1 2.5 124 860 -0.1 177

Horry, SC..................................... 8.8 118.3 4.7 9 587 0.5 129

Lexington, SC............................... 6.6 114.2 2.8 99 757 1.6 63

Richland, SC................................ 9.6 214.8 1.7 200 868 0.7 114

Spartanburg, SC........................... 6.1 130.3 3.5 50 848 2.3 29

York, SC....................................... 5.3 85.7 2.5 124 806 0.4 137

Minnehaha, SD............................. 7.0 122.4 1.3 242 881 1.7 59

Davidson, TN................................ 21.2 462.0 3.9 31 1,097 1.8 47

Hamilton, TN................................ 9.2 194.7 2.8 99 882 0.8 108

Knox, TN...................................... 11.8 233.4 2.6 116 875 2.0 38

Rutherford, TN.............................. 5.2 117.8 5.5 4 848 -1.1 224

Shelby, TN.................................... 20.1 487.2 1.6 211 991 -1.7 254

Williamson, TN............................. 8.1 121.3 7.9 1 1,198 -4.9 330

Bell, TX......................................... 5.0 118.0 4.1 25 842 2.6 21

Bexar, TX..................................... 38.0 832.4 2.1 158 934 -0.3 191

Brazoria, TX................................. 5.3 102.7 -0.6 324 1,065 -0.4 201

Brazos, TX.................................... 4.2 99.5 2.1 158 725 -0.1 177

Cameron, TX................................ 6.3 136.5 0.6 295 592 0.0 165

Collin, TX...................................... 22.1 370.4 3.3 63 1,272 2.3 29

Dallas, TX..................................... 71.8 1,614.7 3.2 69 1,291 -1.2 233

Denton, TX.................................. 13.3 222.1 4.2 21 923 2.1 34

El Paso, TX.................................. 14.3 292.1 1.7 200 691 -0.3 191

Fort Bend, TX............................... 11.8 170.7 1.4 235 982 -3.9 317

Galveston, TX............................... 5.8 105.1 3.8 33 919 3.0 16

Gregg, TX..................................... 4.2 74.4 -4.4 341 829 -5.9 335

Harris, TX..................................... 109.3 2,256.9 -1.2 332 1,381 -5.1 331

Hidalgo, TX................................... 11.8 249.5 1.6 211 614 1.0 98

Jefferson, TX................................ 5.8 122.2 -1.5 335 1,080 -0.6 211

Lubbock, TX................................. 7.2 135.3 1.7 200 759 -0.1 177

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 345 largest counties,

first quarter 2016 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-163

Ranking by

percent

change

First

quarter

2016

Percent

change,

first quarter

2015-163

Ranking by

percent

change

McLennan, TX.............................. 5.0 108.2 2.1 158 $804 1.8 47

Midland, TX.................................. 5.3 83.2 -9.0 343 1,261 -5.7 333

Montgomery, TX........................... 10.4 167.0 1.6 211 1,025 -2.8 298

Nueces, TX.................................. 8.1 159.0 -2.3 337 846 -3.6 313

Potter, TX..................................... 3.9 78.3 0.4 306 787 -1.1 224

Smith, TX..................................... 5.9 100.8 2.4 130 794 -0.6 211

Tarrant, TX................................... 40.3 837.2 2.1 158 1,005 -1.6 250

Travis, TX..................................... 37.0 690.3 2.9 94 1,173 2.4 24

Webb, TX..................................... 5.0 97.1 0.8 283 650 -2.0 270

Williamson, TX............................. 9.5 154.0 3.5 50 1,009 -7.8 339

Davis, UT..................................... 8.0 117.3 3.2 69 796 0.9 102

Salt Lake, UT................................ 42.5 659.8 3.8 33 973 0.7 114

Utah, UT....................................... 14.8 215.2 6.7 2 794 0.8 108

Weber, UT.................................... 5.8 101.3 2.0 168 726 1.3 72

Chittenden, VT............................. 6.6 99.7 0.1 316 954 1.4 70

Arlington, VA................................ 9.5 170.9 3.1 78 1,734 -0.2 187

Chesterfield, VA........................... 8.8 132.3 4.3 18 840 -2.3 284

Fairfax, VA.................................... 37.8 588.1 2.2 150 1,622 -1.8 260

Henrico, VA.................................. 11.5 187.6 2.6 116 1,028 -4.5 325

Loudoun, VA................................ 12.1 155.9 6.2 3 1,193 -1.1 224

Prince William, VA........................ 9.2 123.7 4.4 16 838 1.2 79

Alexandria City, VA...................... 6.7 93.8 0.6 295 1,400 -0.1 177

Chesapeake City, VA................... 6.1 97.3 1.9 176 763 0.1 155

Newport News City, VA................ 3.9 95.5 -1.9 336 1,016 -2.4 287

Norfolk City, VA........................... 5.9 140.2 1.1 260 987 -2.0 270

Richmond City, VA....................... 7.8 152.6 3.2 69 1,173 -3.0 301

Virginia Beach City, VA................ 12.1 173.0 3.0 86 765 -1.3 239

Benton, WA.................................. 5.6 82.2 1.9 176 986 1.8 47

Clark, WA..................................... 13.9 147.4 4.2 21 906 0.7 114

King, WA...................................... 84.6 1,294.1 3.6 44 1,456 5.1 2

Kitsap, WA.................................... 6.6 85.4 2.2 150 887 0.1 155

Pierce, WA................................... 21.4 288.8 3.4 55 895 0.6 123

Snohomish, WA............................ 20.2 280.1 2.8 99 1,124 2.0 38

Spokane, WA............................... 15.4 212.3 3.0 86 852 0.1 155

Thurston, WA............................... 8.0 107.9 3.8 33 900 2.4 24

Whatcom, WA.............................. 7.1 86.3 2.1 158 825 1.1 88

Yakima, WA................................. 7.7 105.1 2.0 168 680 3.0 16

Kanawha, WV............................... 5.9 101.9 -0.5 322 855 -0.3 191

Brown, WI..................................... 6.7 151.1 1.7 200 906 1.8 47

Dane, WI...................................... 15.0 322.9 2.6 116 1,005 0.5 129

Milwaukee, WI.............................. 25.9 482.0 0.9 273 997 -2.0 270

Outagamie, WI............................. 5.2 104.6 1.9 176 856 1.5 66

Waukesha, WI.............................. 12.9 233.9 1.3 242 1,022 -1.4 243

Winnebago, WI............................. 3.7 91.1 1.8 192 991 4.2 6

San Juan, PR............................... 10.8 245.1 -1.6 (6) 634 0.0 (6)

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 Data do not meet BLS or state agency disclosure standards.

6 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 344 U.S. counties comprise 72.6 percent of the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,

first quarter 2016

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-162

First

quarter

2016

Percent

change,

first quarter

2015-162

United States3................................................................. 9,693.5 140,070.8 2.0 $1,043 -0.5

 Private industry............................................................. 9,394.9 118,350.0 2.1 1,049 -0.6

 Natural resources and mining.................................... 137.5 1,768.9 -8.9 1,190 -7.9

 Construction............................................................... 768.3 6,363.7 5.4 1,053 3.8

 Manufacturing............................................................ 343.6 12,241.8 -0.2 1,259 -1.3

 Trade, transportation, and utilities.............................. 1,917.9 26,541.7 1.7 858 0.1

 Information................................................................. 155.8 2,767.3 0.9 2,009 3.1

 Financial activities...................................................... 853.9 7,851.0 1.7 2,111 -2.2

 Professional and business services........................... 1,745.3 19,626.4 2.1 1,375 -1.3

 Education and health services................................... 1,573.9 21,474.4 2.6 865 0.1

 Leisure and hospitality............................................... 813.6 15,065.3 3.2 408 2.5

 Other services............................................................ 829.6 4,317.1 1.7 665 1.4

 Government.................................................................. 298.6 21,720.8 0.9 1,008 0.2

Los Angeles, CA.............................................................. 464.3 4,309.9 1.9 1,138 2.1

 Private industry............................................................. 458.2 3,741.0 1.9 1,111 1.8

 Natural resources and mining.................................... 0.5 9.2 -4.7 1,627 1.6

 Construction............................................................... 13.4 130.1 6.9 1,104 3.1

 Manufacturing............................................................ 12.3 359.3 -2.3 1,348 1.9

 Trade, transportation, and utilities.............................. 53.0 800.5 0.6 916 2.7

 Information................................................................. 9.3 226.8 1.1 2,145 6.5

 Financial activities...................................................... 24.8 215.9 1.0 2,200 -1.3

 Professional and business services........................... 46.5 587.8 0.5 1,363 1.7

 Education and health services................................... 216.4 742.0 2.6 812 1.8

 Leisure and hospitality............................................... 31.5 491.7 3.5 586 3.4

 Other services............................................................ 26.8 144.1 0.2 672 2.3

 Government.................................................................. 6.1 568.9 1.6 1,324 3.6

Cook, IL........................................................................... 154.9 2,515.9 1.2 1,278 -0.2

 Private industry............................................................. 153.6 2,220.1 1.4 1,294 0.2

 Natural resources and mining.................................... 0.1 1.1 27.2 1,134 3.8

 Construction............................................................... 12.5 67.8 5.7 1,434 6.4

 Manufacturing............................................................ 6.4 185.1 -0.9 1,257 2.1

 Trade, transportation, and utilities.............................. 30.3 465.1 1.4 972 0.2

 Information................................................................. 2.6 51.9 1.0 2,078 0.0

 Financial activities...................................................... 15.5 189.1 0.5 3,409 -1.6

 Professional and business services........................... 32.7 459.2 0.8 1,566 0.8

 Education and health services................................... 16.5 438.7 1.2 916 1.9

 Leisure and hospitality............................................... 14.2 261.6 3.4 476 0.6

 Other services............................................................ 17.5 95.3 -0.2 897 -2.0

 Government.................................................................. 1.3 295.8 0.3 1,161 -2.6

New York, NY.................................................................. 130.3 2,396.8 1.9 2,783 -1.9

 Private industry............................................................. 129.4 2,131.8 2.0 2,969 -2.2

 Natural resources and mining.................................... 0.0 0.2 0.7 2,942 -3.1

 Construction............................................................... 2.2 39.6 8.6 1,825 5.4

 Manufacturing............................................................ 2.1 26.8 -1.0 1,552 -3.7

 Trade, transportation, and utilities.............................. 19.7 251.8 -2.6 1,407 4.0

 Information................................................................. 4.9 152.7 0.2 3,210 1.8

 Financial activities...................................................... 19.3 370.4 2.3 8,498 -5.2

 Professional and business services........................... 27.5 547.2 2.8 2,598 -1.7

 Education and health services................................... 9.8 341.0 1.7 1,226 1.4

 Leisure and hospitality............................................... 13.6 287.5 1.9 828 2.9

 Other services............................................................ 20.0 99.7 0.1 1,213 5.0

 Government.................................................................. 0.8 265.1 1.1 1,273 3.1

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

first quarter 2016 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-162

First

quarter

2016

Percent

change,

first quarter

2015-162

Harris, TX........................................................................ 109.3 2,256.9 -1.2 $1,381 -5.1

 Private industry............................................................. 108.8 1,983.1 -1.7 1,422 -5.5

 Natural resources and mining.................................... 1.8 79.4 -16.6 4,456 -2.5

 Construction............................................................... 6.9 164.6 2.0 1,347 0.9

 Manufacturing............................................................ 4.7 173.5 -12.5 1,680 -8.1

 Trade, transportation, and utilities.............................. 24.4 463.7 0.0 1,260 -4.3

 Information................................................................. 1.1 26.4 -2.0 1,499 -2.2

 Financial activities...................................................... 11.3 120.9 0.8 2,123 -4.8

 Professional and business services........................... 22.4 382.9 -2.8 1,686 -3.2

 Education and health services................................... 15.0 282.7 2.9 967 2.2

 Leisure and hospitality............................................... 9.3 224.8 3.3 433 1.6

 Other services............................................................ 11.4 63.6 -1.3 772 -2.0

 Government.................................................................. 0.6 273.8 2.0 1,083 0.5

Maricopa, AZ.................................................................... 94.8 1,864.4 3.3 972 -1.5

 Private industry............................................................. 94.1 1,653.0 3.7 975 -2.1

 Natural resources and mining.................................... 0.4 8.4 -1.7 1,019 -13.6

 Construction............................................................... 6.9 99.8 5.2 974 1.0

 Manufacturing............................................................ 3.1 115.5 1.1 1,451 -4.6

 Trade, transportation, and utilities.............................. 18.8 362.3 2.3 903 -0.6

 Information................................................................. 1.5 34.7 2.0 1,351 -3.9

 Financial activities...................................................... 10.9 164.2 4.9 1,431 -3.2

 Professional and business services........................... 21.0 316.2 3.2 1,057 -3.5

 Education and health services................................... 10.6 278.6 3.4 927 0.7

 Leisure and hospitality............................................... 7.4 209.4 2.7 448 -0.9

 Other services............................................................ 6.0 50.3 1.0 658 0.3

 Government.................................................................. 0.7 211.3 0.0 946 3.2

Dallas, TX........................................................................ 71.8 1,614.7 3.2 1,291 -1.2

 Private industry............................................................. 71.3 1,440.3 3.2 1,315 -1.4

 Natural resources and mining.................................... 0.6 8.6 -9.9 4,945 0.7

 Construction............................................................... 4.1 81.2 3.9 1,130 3.0

 Manufacturing............................................................ 2.7 108.2 0.0 1,690 -2.2

 Trade, transportation, and utilities.............................. 15.4 327.5 3.8 1,073 -2.5

 Information................................................................. 1.3 47.5 0.0 2,440 1.5

 Financial activities...................................................... 8.8 154.0 2.8 2,146 -0.4

 Professional and business services........................... 16.2 326.7 2.9 1,450 0.3

 Education and health services................................... 8.9 191.3 4.7 1,018 -2.5

 Leisure and hospitality............................................... 6.2 153.7 5.5 497 -1.0

 Other services............................................................ 6.7 41.0 -0.2 774 -1.3

 Government.................................................................. 0.5 174.4 3.1 1,097 0.4

Orange, CA...................................................................... 113.9 1,545.7 2.4 1,143 -6.4

 Private industry............................................................. 112.4 1,392.0 2.4 1,119 -7.4

 Natural resources and mining.................................... 0.2 3.4 6.2 919 -4.1

 Construction............................................................... 6.5 93.1 6.1 1,234 4.1

 Manufacturing............................................................ 4.9 153.6 -1.0 1,413 0.4

 Trade, transportation, and utilities.............................. 16.7 253.1 -0.5 1,010 -3.1

 Information................................................................. 1.2 25.3 2.2 2,013 -0.5

 Financial activities...................................................... 10.8 113.9 2.3 1,903 -2.4

 Professional and business services........................... 20.1 289.1 0.8 1,341 -22.4

 Education and health services................................... 29.8 197.6 3.6 888 1.6

 Leisure and hospitality............................................... 8.3 207.3 4.4 460 0.4

 Other services............................................................ 6.8 45.1 3.2 677 3.8

 Government.................................................................. 1.5 153.7 2.5 1,355 1.3

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

first quarter 2016 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-162

First

quarter

2016

Percent

change,

first quarter

2015-162

San Diego, CA................................................................ 105.9 1,388.4 2.3 $1,108 -2.0

 Private industry............................................................. 104.0 1,157.8 2.4 1,086 -2.2

 Natural resources and mining.................................... 0.7 9.4 0.0 616 1.8

 Construction............................................................... 6.4 73.3 9.3 1,109 1.4

 Manufacturing............................................................ 3.1 106.2 0.5 1,612 -7.5

 Trade, transportation, and utilities.............................. 14.1 214.2 0.0 896 2.5

 Information................................................................. 1.1 23.0 -3.9 1,803 6.9

 Financial activities...................................................... 9.6 70.5 1.8 1,585 -2.9

 Professional and business services........................... 17.7 228.8 1.8 1,586 -5.3

 Education and health services................................... 29.7 190.7 2.7 877 -0.2

 Leisure and hospitality............................................... 7.9 183.3 2.5 464 3.1

 Other services............................................................ 7.4 49.4 1.0 576 0.9

 Government.................................................................. 1.9 230.7 1.8 1,223 -0.9

King, WA......................................................................... 84.6 1,294.1 3.6 1,456 5.1

 Private industry............................................................. 84.1 1,127.5 3.7 1,488 5.5

 Natural resources and mining.................................... 0.4 3.0 17.6 2,762 95.7

 Construction............................................................... 6.3 65.1 7.2 1,247 3.9

 Manufacturing............................................................ 2.4 105.0 -1.8 1,716 -4.2

 Trade, transportation, and utilities.............................. 14.5 243.8 3.8 1,358 10.8

 Information................................................................. 2.1 92.7 8.1 3,464 14.2

 Financial activities...................................................... 6.5 66.3 2.7 2,013 0.1

 Professional and business services........................... 16.7 216.3 4.4 1,699 2.6

 Education and health services................................... 19.5 164.3 3.2 943 0.5

 Leisure and hospitality............................................... 7.0 128.5 3.9 503 2.4

 Other services............................................................ 8.8 42.7 2.5 846 4.2

 Government.................................................................. 0.5 166.6 2.4 1,237 1.6

Miami-Dade, FL............................................................... 95.9 1,107.3 2.7 972 -0.3

 Private industry............................................................. 95.5 969.9 3.0 956 -0.4

 Natural resources and mining.................................... 0.5 10.0 2.6 518 1.6

 Construction............................................................... 6.0 42.3 10.8 930 3.4

 Manufacturing............................................................ 2.8 40.2 4.8 894 -0.9

 Trade, transportation, and utilities.............................. 26.5 277.5 0.5 884 0.1

 Information................................................................. 1.5 17.9 -0.1 1,750 7.5

 Financial activities...................................................... 10.4 74.0 1.8 1,852 -0.8

 Professional and business services........................... 21.0 152.6 3.7 1,131 -1.4

 Education and health services................................... 10.2 172.3 3.6 901 -3.1

 Leisure and hospitality............................................... 7.2 142.1 4.6 568 4.0

 Other services............................................................ 8.2 40.3 4.1 586 0.2

 Government.................................................................. 0.3 137.4 0.7 1,087 0.8

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 2015 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 2016

Employment Average weekly wage 1

State

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-16

First

quarter

2016

Percent

change,

first quarter

2015-16

United States2.......................................... 9,693.5 140,070.8 2.0 $1,043 -0.5

Alabama.................................................... 121.3 1,902.6 1.6 842 -0.2

Alaska........................................................ 22.2 317.6 -1.4 1,028 -2.0

Arizona...................................................... 152.6 2,679.8 2.8 918 -0.8

Arkansas................................................... 88.7 1,191.1 2.1 793 0.5

California................................................... 1,458.8 16,455.5 2.6 1,206 0.0

Colorado.................................................... 190.2 2,514.6 2.4 1,057 -1.3

Connecticut............................................... 116.8 1,650.6 0.6 1,362 -1.4

Delaware................................................... 31.0 429.7 1.5 1,072 -3.0

District of Columbia................................... 38.7 749.6 2.0 1,766 0.4

Florida....................................................... 659.1 8,301.8 3.5 887 0.2

Georgia...................................................... 297.3 4,215.1 3.0 1,008 1.9

Hawaii........................................................ 40.1 645.1 1.4 896 1.7

Idaho......................................................... 56.9 670.4 3.5 725 -1.5

Illinois........................................................ 408.8 5,800.6 1.2 1,126 -0.5

Indiana....................................................... 162.2 2,949.5 1.9 853 -0.5

Iowa........................................................... 101.2 1,518.2 0.9 844 -0.4

Kansas...................................................... 89.9 1,362.3 0.4 833 -2.0

Kentucky.................................................... 122.5 1,843.9 1.9 823 0.1

Louisiana................................................... 127.5 1,910.5 -0.8 860 -2.6

Maine......................................................... 52.3 580.5 1.8 804 1.1

Maryland.................................................... 169.2 2,591.7 1.9 1,103 -0.8

Massachusetts.......................................... 242.7 3,414.8 2.1 1,327 -1.0

Michigan.................................................... 240.2 4,163.7 2.1 976 0.7

Minnesota.................................................. 160.1 2,750.1 1.5 1,065 -1.2

Mississippi................................................. 72.7 1,121.0 1.7 713 0.4

Missouri..................................................... 193.2 2,729.5 1.9 879 -0.3

Montana.................................................... 46.5 447.8 1.8 751 0.3

Nebraska................................................... 71.5 956.6 1.4 817 0.0

Nevada...................................................... 81.4 1,264.1 3.0 875 1.2

New Hampshire......................................... 50.9 635.1 1.9 998 1.6

New Jersey............................................... 269.7 3,909.7 2.4 1,268 -1.7

New Mexico............................................... 57.9 800.4 0.0 792 -1.6

New York.................................................. 642.1 9,042.2 2.0 1,456 -0.3

North Carolina........................................... 272.5 4,220.3 3.0 928 -0.2

North Dakota............................................. 31.9 409.4 -6.2 908 -7.6

Ohio........................................................... 293.0 5,236.2 1.8 913 -0.8

Oklahoma.................................................. 109.1 1,578.6 -0.9 833 -4.1

Oregon...................................................... 148.6 1,808.2 3.2 929 1.2

Pennsylvania............................................. 355.2 5,662.2 1.1 1,012 -1.9

Rhode Island............................................. 36.6 464.6 1.9 985 -2.2

South Carolina.......................................... 125.6 1,974.6 2.7 806 0.8

South Dakota............................................ 32.7 410.5 0.9 771 1.2

Tennessee................................................. 152.9 2,859.2 3.3 887 0.3

Texas......................................................... 630.8 11,638.7 0.7 1,066 -2.1

Utah........................................................... 94.4 1,369.2 3.8 849 0.6

Vermont..................................................... 24.7 304.6 0.1 832 1.0

Virginia...................................................... 263.7 3,748.1 2.6 1,057 -1.2

Washington............................................... 239.2 3,147.7 3.1 1,121 3.0

West Virginia............................................. 50.1 683.9 -1.2 782 -1.3

Wisconsin.................................................. 170.0 2,771.4 1.3 875 -0.2

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

first quarter 2016 - Continued

Employment Average weekly wage 1

State

Establishments,

first quarter

2016

(thousands)

March

2016

(thousands)

Percent

change,

March

2015-16

First

quarter

2016

Percent

change,

first quarter

2015-16

Wyoming................................................... 26.0 267.9 -3.7 $850 -4.7

Puerto Rico............................................... 46.2 895.2 -1.2 520 -0.4

Virgin Islands............................................ 3.3 38.6 0.4 769 2.9

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.
Chart 3. Percent change in employment in counties with 75,000 or more employees,

March 2015-16 (U.S. average = 2.0 percent)

Higher than U.S. average

U.S. average or lower

Source: Bureau of Labor Statistics
Chart 4. Percent change in average weekly wage in counties with 75,000 or more

employees, first quarter 2015-16 (U.S. average = -0.5 percent)

Higher than U.S. average

U.S. average or lower

Source: Bureau of Labor Statistics