For release 10:00 a.m. (EDT), Thursday, September 17, 2015 USDL-15-1788 

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 2015 

From March 2014 to March 2015, employment increased in 323 of the 342 largest U.S. counties 

(counties with 75,000 or more jobs in 2014), the U.S. Bureau of Labor Statistics reported today. Utah, 

Utah, had the largest percentage increase, with a gain of 6.7 percent over the year, compared with 

national job growth of 2.1 percent. Within Utah, the largest employment increase occurred in trade, 

transportation, and utilities, which gained 2,962 jobs over the year (8.9 percent). Atlantic, N.J., had the 

largest over-the-year percentage decrease in employment among the largest counties in the U.S. with a 

loss of 4.3 percent. County employment and wage data are compiled under the Quarterly Census of 

Employment and Wages (QCEW) program, which produces detailed information on county employment 

and wages within 6 months after the end of each quarter. 

The U.S. average weekly wage increased 2.1 percent over the year, growing to $1,048 in the first

quarter of 2015. Olmsted, Minn., had the largest over-the-year percentage increase in average weekly 

wages with a gain of 11.7 percent. Within Olmsted, an average weekly wage gain of $243, or 18.6 

percent, in education and health services made the largest contribution to the county’s increase in 

average weekly wages. Snohomish, Wash., experienced the largest percentage decrease in average 

weekly wages with a loss of 4.8 percent over the year.

Chart 1. Large counties ranked by percent increase in 

employment, March 2014-15 

(U.S. average = 2.1 percent) 

Chart 2. Large counties ranked by percent increase in 

average weekly wages, first quarter 2014-15 

(U.S. average = 2.1 percent)

 

0

2

4

6

8

Utah,

Utah

Adams,

Colo.

Denton,

Texas

Montgomery,

Texas

Lee,

Fla.

Percent

0

2

4

6

8

10

12

Olmsted,

Minn.

Washington,

Pa.

Riverside,

Calif.

Lake,

Ill.

Orange,

Calif.

Percent
- 2 - 

 

Table A. Large counties ranked by March 2015 employment, March 2014-15 employment increase, and 

March 2014-15 percent increase in employment 

Employment in large counties

March 2015 employment Increase in employment, Percent increase in employment, 

(thousands) March 2014-15 March 2014-15

(thousands)

United States 137,412.4 United States 2,872.7 United States 2.1

Los Angeles, Calif. 4,204.3 Los Angeles, Calif. 86.4 Utah, Utah 6.7

Cook, Ill. 2,470.3 Harris, Texas 66.6 Adams, Colo. 5.8

New York, N.Y. 2,346.5 New York, N.Y. 60.5 Denton, Texas 5.8

Harris, Texas 2,288.8 Dallas, Texas 56.6 Montgomery, Texas 5.8

Maricopa, Ariz. 1,803.5 Maricopa, Ariz. 52.0 Lee, Fla. 5.7

Dallas, Texas 1,570.9 King, Wash. 42.5 Chatham, Ga. 5.3

Orange, Calif. 1,501.2 Santa Clara, Calif. 38.5 Calcasieu, La. 5.3

San Diego, Calif. 1,352.1 Clark, Nev. 37.0 Clay, Mo. 5.3

King, Wash. 1,254.9 Orange, Calif. 36.4 Weld, Colo. 5.2

Miami-Dade, Fla. 1,074.6 Cook, Ill. 36.1 Collier, Fla. 5.2

Williamson, Tenn. 5.2

Large County Employment 

In March 2015, national employment was 137.4 million (as measured by the QCEW program). Over the 

year, employment increased 2.1 percent, or 2.9 million. In March 2015, the 342 U.S. counties with 

75,000 or more jobs accounted for 72.3 percent of total U.S. employment and 78.6 percent of total 

wages. These 342 counties had a net job growth of 2.2 million over the year, accounting for 75.9 percent 

of the overall U.S. employment increase. (See chart 3.) 

Utah, Utah, had the largest percentage increase in employment (6.7 percent) among the largest U.S. 

counties. The five counties with the largest increases in employment levels were Los Angeles, Calif.; 

Harris, Texas; New York, N.Y.; Dallas, Texas; and Maricopa, Ariz. These counties had a combined 

over-the-year employment gain of 322,100 jobs, which was 11.2 percent of the overall job increase for 

the U.S. (See table A.)

Employment declined in 17 of the largest counties from March 2014 to March 2015. Atlantic, N.J., had 

the largest over-the-year percentage decrease in employment (-4.3 percent). Within Atlantic, leisure and 

hospitality had the largest decrease in employment, with a loss of 6,587 jobs (-15.9 percent). New 

London, Conn., had the second largest percentage decrease in employment, followed by Cumberland, 

N.C.; Broome, N.Y.; and Lafayette, La. (See table 1.) 
- 3 - 

Table B. Large counties ranked by first quarter 2015 average weekly wages, first quarter 2014-15

increase in average weekly wages, and first quarter 2014-15 percent increase in average weekly wages 

Average weekly wage in large counties

Average weekly wage, Increase in average weekly Percent increase in average 

first quarter 2015 wage, first quarter 2014-15 weekly wage, first

quarter 2014-15

United States $1,048 United States $22 United States 2.1

New York, N.Y. $2,847 Lake, Ill. $134 Olmsted, Minn. 11.7

Santa Clara, Calif. 2,203 Olmsted, Minn. 120 Washington, Pa. 10.7

Somerset, N.J. 2,080 Washington, Pa. 118 Riverside, Calif. 10.1

San Francisco, Calif. 2,070 San Francisco, Calif. 115 Lake, Ill. 9.2

San Mateo, Calif. 2,066 Morris, N.J. 112 Orange, Calif. 9.1

Fairfield, Conn. 1,938 Santa Clara, Calif. 111 Weld, Colo. 7.5

Suffolk, Mass. 1,909 Orange, Calif. 102 Bristol, Mass. 7.4

Washington, D.C. 1,764 Williamson, Tenn. 82 Jefferson, Ala. 7.1

Morris, N.J. 1,755 Riverside, Calif. 79 Williamson, Tenn. 6.9

Arlington, Va. 1,732 Middlesex, Mass. 77 Ottawa, Mich. 6.8

Morris, N.J. 6.8

Large County Average Weekly Wages 

Average weekly wages for the nation increased to $1,048, a 2.1 percent increase, during the year ending 

in the first quarter of 2015. Among the 342 largest counties, 297 had over-the-year increases in average 

weekly wages. (See chart 4.) Olmsted, Minn., had the largest percentage wage increase among the 

largest U.S. counties (11.7 percent). 

Of the 342 largest counties, 39 experienced over-the-year decreases in average weekly wages.

Snohomish, Wash., had the largest percentage decrease in average weekly wages, with a loss of 4.8 

percent. Within Snohomish, manufacturing had the largest impact on the county’s average weekly wage 

decrease. Within this industry, average weekly wages declined by $290 (-13.4 percent) over the year. 

Chester, Pa., had the second largest percentage decrease in average weekly wages, followed by 

Williamson, Texas; Saginaw, Mich.; and Palm Beach, Fla. (See table 1.) 

Ten Largest U.S. Counties 

All of the 10 largest counties had over-the-year percentage increases in employment in March 2015. 

Dallas, Texas, had the largest gain (3.7 percent). Within Dallas, professional and business services had 

the largest over-the-year employment level increase among all private industry groups with a gain of 

16,702 jobs, or 5.5 percent. Cook, Ill., had the smallest percentage increase in employment (1.5 percent) 

among the 10 largest counties. (See table 2.)

Average weekly wages increased over the year in 9 of the 10 largest U.S. counties. Orange, Calif., 

experienced the largest percentage gain in average weekly wages (9.1 percent). Within Orange, 

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

Within this industry, average weekly wages increased by $373, or 27.6 percent, over the year. New 
- 4 - 

York, N.Y., had the only decrease in average weekly wages (-1.3 percent) among the 10 largest 

counties. 

For More Information

The tables and charts included in this release contain data for the nation and for the 342 U.S. counties 

with annual average employment levels of 75,000 or more in 2014. March 2015 employment and 2015 

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

The employment and wage data by county are compiled under the QCEW program, also known as the 

ES-202 program. The data are derived from reports submitted by every employer subject to 

unemployment insurance (UI) laws. The 9.5 million employer reports cover 137.4 million full- and parttime workers. The QCEW program provides a quarterly and annual universe count of establishments, 

employment, and wages at the county, MSA, state, and national levels by detailed industry. Data for the 

first quarter of 2015 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 are issuing 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 2015 is scheduled to be released 

on Thursday, December 17, 2015. 

County Changes for the 2015 County Employment and Wages News Releases

Counties with annual average employment of 75,000 or more in 2014 are included in this release and 

will be included in future 2015 releases. Three counties have been added to the publication tables: 

Butte, Calif.; Hall, Ga.; and Ector, Texas. 
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 2015 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 343 counties presented in 

this release were derived using 2014 preliminary annual averages of 

employment. For 2015 data, three counties have been added to the 

publication tables: Butte, Calif.; Hall, Ga.; and Ector, Texas. These 

counties will be included in all 2015 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 9.5 million establishments in first quarter of 2015 

Count of longitudinally-linked UI administrative records submitted by 

7.5 million private-sector employers

Sample survey: 588,000 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

— 6 months after the end of each 

quarter

Quarterly

— 8 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 lossesUses UI file as a sampling frame and to 

annually realign sample-based estimates 

to population counts (benchmarking)

Principal

products

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

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 9.4 million employer 

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

2014. 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 2014, UI and 

UCFE programs covered workers in 136.6 million jobs. The estimated 

131.8 million workers in these jobs (after adjustment for multiple jobholders) represented 96.3 percent of civilian wage and salary employment. Covered workers received $7.017 trillion in pay, representing 

93.8 percent of the wage and salary component of personal income 

and 40.5 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 2014 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 2013 edition of this 

publication, which was published in September 2014, contains selected data produced by Business Employment Dynamics (BED) on 

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

2014 version of this news release. Tables and additional content from 

Employment and Wages Annual Averages 2013 are now available 

online at http://www.bls.gov/cew/cewbultn13.htm. The 2014 edition 

of Employment and Wages Annual Averages Online will be available 

in September 2015. 

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 343 largest counties,

first quarter 2015

Employment Average weekly wage 2

County1

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-153

Ranking by

percent

change

First

quarter

2015

Percent

change,

first quarter

2014-153

Ranking by

percent

change

United States4.............................. 9,531.3 137,412.4 2.1 - $1,048 2.1 -

Jefferson, AL................................ 17.6 335.5 0.3 309 1,066 7.1 8

Madison, AL................................. 9.1 183.8 1.9 165 1,052 0.2 292

Mobile, AL.................................... 9.6 166.9 1.1 243 834 1.8 162

Montgomery, AL........................... 6.3 128.0 0.6 290 801 1.5 195

Shelby, AL.................................... 5.4 82.3 2.4 135 991 2.5 108

Tuscaloosa, AL............................. 4.3 90.8 3.7 45 795 -0.5 314

Anchorage Borough, AK............... 8.3 151.6 0.7 282 1,105 3.0 67

Maricopa, AZ................................ 94.7 1,803.5 3.0 90 986 0.9 256

Pima, AZ....................................... 18.9 355.6 0.8 267 820 0.0 298

Benton, AR................................... 5.9 107.0 3.7 45 1,302 0.0 298

Pulaski, AR................................... 14.4 242.3 0.2 314 890 0.9 256

Washington, AR........................... 5.7 98.6 3.8 40 775 -0.4 310

Alameda, CA................................ 58.3 719.4 3.4 64 1,336 2.8 81

Butte, CA..................................... 7.9 76.9 2.8 103 726 5.4 17

Contra Costa, CA......................... 30.3 341.1 1.7 186 1,296 3.5 48

Fresno, CA................................... 31.6 355.1 2.9 97 771 2.1 133

Kern, CA....................................... 17.4 295.9 1.1 243 871 0.8 266

Los Angeles, CA........................... 448.7 4,204.3 2.1 155 1,120 2.6 96

Marin, CA..................................... 12.1 110.5 2.1 155 1,241 4.5 29

Monterey, CA............................... 13.0 168.3 3.0 90 850 1.8 162

Orange, CA.................................. 110.2 1,501.2 2.5 127 1,221 9.1 5

Placer, CA.................................... 11.7 145.6 3.6 52 990 4.0 38

Riverside, CA............................... 55.0 648.7 3.8 40 861 10.1 3

Sacramento, CA........................... 53.5 618.6 3.4 64 1,106 2.6 96

San Bernardino, CA..................... 52.8 675.7 4.0 31 811 2.0 142

San Diego, CA.............................. 102.6 1,352.1 2.5 127 1,130 0.2 292

San Francisco, CA....................... 58.3 660.1 4.6 15 2,070 5.9 15

San Joaquin, CA.......................... 16.9 224.7 4.1 29 818 2.4 114

San Luis Obispo, CA.................... 9.9 113.4 3.2 76 806 2.9 76

San Mateo, CA............................. 26.6 375.8 4.6 15 2,066 -0.2 307

Santa Barbara, CA....................... 14.7 192.4 1.3 223 936 3.0 67

Santa Clara, CA........................... 67.2 1,001.6 4.0 31 2,203 5.3 20

Santa Cruz, CA............................ 9.3 95.9 3.4 64 857 2.1 133

Solano, CA................................... 10.4 128.6 2.8 103 1,051 1.6 185

Sonoma, CA................................. 19.1 193.5 2.6 119 925 6.2 13

Stanislaus, CA.............................. 14.6 174.3 3.1 83 830 3.1 62

Tulare, CA.................................... 9.3 149.2 1.9 165 687 5.0 23

Ventura, CA.................................. 25.2 317.8 0.7 282 1,039 -1.8 337

Yolo, CA....................................... 6.3 94.2 3.5 58 1,015 0.2 292

Adams, CO................................... 9.8 188.3 5.8 2 930 1.8 162

Arapahoe, CO.............................. 20.4 310.2 3.2 76 1,256 0.6 279

Boulder, CO.................................. 14.0 170.9 2.9 97 1,196 3.0 67

Denver, CO.................................. 29.0 470.6 4.7 14 1,350 1.7 175

Douglas, CO................................. 10.8 109.1 3.9 37 1,205 5.0 23

El Paso, CO.................................. 17.7 250.5 2.6 119 892 1.8 162

Jefferson, CO............................... 18.7 223.5 3.2 76 1,020 2.6 96

Larimer, CO.................................. 11.0 143.0 4.0 31 906 5.3 20

Weld, CO...................................... 6.5 101.8 5.2 9 932 7.5 6

Fairfield, CT................................. 34.3 415.4 1.4 214 1,938 0.8 266

Hartford, CT.................................. 26.7 499.6 1.1 243 1,407 1.8 162

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,

first quarter 2015 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-153

Ranking by

percent

change

First

quarter

2015

Percent

change,

first quarter

2014-153

Ranking by

percent

change

New Haven, CT............................ 23.2 356.4 0.6 290 $1,032 0.4 286

New London, CT.......................... 7.1 118.1 -1.4 341 1,037 1.4 210

New Castle, DE............................ 18.7 280.6 3.0 90 1,272 -1.2 330

Washington, DC........................... 37.0 732.6 1.4 214 1,764 3.2 58

Alachua, FL.................................. 6.9 122.5 2.3 142 804 2.6 96

Brevard, FL................................... 15.2 194.7 2.5 127 856 0.9 256

Broward, FL.................................. 68.1 756.7 2.8 103 922 1.3 223

Collier, FL..................................... 13.1 140.2 5.2 9 828 0.4 286

Duval, FL..................................... 28.3 466.2 3.0 90 992 1.1 239

Escambia, FL............................... 8.2 124.8 1.9 165 771 4.3 34

Hillsborough, FL........................... 40.4 639.6 3.1 83 973 1.9 150

Lake, FL....................................... 7.9 89.7 4.4 19 649 1.4 210

Lee, FL......................................... 20.6 241.2 5.7 5 762 1.9 150

Leon, FL....................................... 8.5 142.8 1.5 210 774 0.7 274

Manatee, FL................................. 10.2 116.4 4.4 19 725 2.1 133

Marion, FL.................................... 8.3 96.9 3.7 45 664 1.2 235

Miami-Dade, FL............................ 96.4 1,074.6 3.3 73 982 3.4 54

Okaloosa, FL................................ 6.3 79.0 0.7 282 814 3.3 55

Orange, FL................................... 39.5 754.1 3.4 64 891 2.1 133

Osceola, FL.................................. 6.3 84.0 3.8 40 671 -1.5 334

Palm Beach, FL............................ 53.8 566.5 4.0 31 991 -2.0 338

Pasco, FL..................................... 10.6 108.6 4.6 15 658 1.4 210

Pinellas, FL................................... 32.1 407.1 3.1 83 865 2.5 108

Polk, FL........................................ 12.9 204.6 2.3 142 735 1.0 245

Sarasota, FL................................ 15.5 160.4 4.5 18 796 0.8 266

Seminole, FL................................ 14.5 170.7 3.3 73 826 2.5 108

Volusia, FL................................... 13.9 161.6 2.7 112 691 1.0 245

Bibb, GA....................................... 4.5 82.6 1.4 214 775 0.8 266

Chatham, GA................................ 8.3 143.5 5.3 6 852 1.5 195

Clayton, GA.................................. 4.4 115.9 4.0 31 976 1.7 175

Cobb, GA...................................... 22.9 330.1 2.4 135 1,137 3.2 58

DeKalb, GA................................. 19.1 286.9 1.9 165 1,066 0.4 286

Fulton, GA.................................... 45.3 781.8 4.2 26 1,506 0.7 274

Gwinnett, GA................................ 25.8 332.9 3.7 45 996 0.5 282

Hall, GA....................................... 4.5 78.0 4.0 31 824 2.7 88

Muscogee, GA.............................. 4.8 94.0 -0.1 326 823 2.6 96

Richmond, GA.............................. 4.7 105.0 3.0 90 825 3.1 62

Honolulu, HI.................................. 24.9 461.9 1.1 243 918 2.8 81

Ada, ID......................................... 13.9 212.7 2.1 155 873 2.0 142

Champaign, IL.............................. 4.5 88.5 0.6 290 852 2.3 119

Cook, IL........................................ 161.8 2,470.3 1.5 210 1,280 2.2 127

DuPage, IL................................. 39.6 592.4 0.8 267 1,202 1.3 223

Kane, IL........................................ 14.2 201.2 0.3 309 856 1.3 223

Lake, IL........................................ 23.5 320.7 0.4 306 1,585 9.2 4

McHenry, IL.................................. 9.1 93.0 -0.2 328 808 -0.4 310

McLean, IL.................................... 4.0 84.1 0.6 290 1,033 -1.1 327

Madison, IL................................... 6.3 96.0 0.8 267 803 1.0 245

Peoria, IL...................................... 4.9 99.2 -0.4 332 988 2.6 96

St. Clair, IL.................................... 5.8 92.1 1.1 243 766 0.7 274

Sangamon, IL............................... 5.5 126.8 0.4 306 1,001 0.5 282

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,

first quarter 2015 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-153

Ranking by

percent

change

First

quarter

2015

Percent

change,

first quarter

2014-153

Ranking by

percent

change

Will, IL.......................................... 16.7 214.7 1.0 254 $859 -0.7 318

Winnebago, IL.............................. 7.0 124.3 0.5 303 848 2.3 119

Allen, IN........................................ 8.8 177.9 2.2 150 841 1.1 239

Elkhart, IN..................................... 4.7 122.3 3.6 52 834 3.0 67

Hamilton, IN.................................. 8.9 128.0 3.9 37 1,027 0.9 256

Lake, IN........................................ 10.3 183.9 0.2 314 890 3.6 45

Marion, IN..................................... 23.5 575.0 1.9 165 1,071 0.8 266

St. Joseph, IN............................... 5.8 117.6 1.7 186 790 2.1 133

Tippecanoe, IN............................. 3.3 81.4 2.7 112 867 4.8 26

Vanderburgh, IN........................... 4.7 105.2 1.1 243 822 2.2 127

Black Hawk, IA............................ 3.8 74.1 -0.6 335 815 -1.5 334

Johnson, IA.................................. 4.0 81.0 0.8 267 897 2.7 88

Linn, IA......................................... 6.6 127.8 1.4 214 1,003 4.8 26

Polk, IA........................................ 16.5 281.9 0.8 267 1,073 2.7 88

Scott, IA........................................ 5.5 89.0 1.7 186 793 1.5 195

Johnson, KS................................. 21.9 329.2 2.8 103 1,087 1.6 185

Sedgwick, KS............................... 12.5 246.3 1.4 214 910 0.7 274

Shawnee, KS................................ 4.8 96.0 0.0 324 817 0.0 298

Wyandotte, KS............................. 3.3 87.6 2.6 119 969 3.2 58

Boone, KY................................... 4.2 79.1 3.0 90 833 1.3 223

Fayette, KY................................... 10.5 184.9 2.7 112 883 1.6 185

Jefferson, KY................................ 24.6 442.3 2.5 127 1,016 2.3 119

Caddo, LA.................................... 7.2 115.3 0.7 282 794 1.5 195

Calcasieu, LA............................... 4.9 91.6 5.3 6 858 0.2 292

East Baton Rouge, LA.................. 14.5 268.2 2.2 150 942 3.1 62

Jefferson, LA................................ 13.5 194.5 0.6 290 887 1.3 223

Lafayette, LA................................ 9.2 139.7 -0.9 338 952 -0.5 314

Orleans, LA.................................. 11.8 189.4 2.7 112 1,004 3.0 67

St. Tammany, LA.......................... 7.6 84.1 3.5 58 871 2.6 96

Cumberland, ME.......................... 12.9 169.6 1.1 243 924 1.3 223

Anne Arundel, MD........................ 14.5 253.2 1.1 243 1,077 1.8 162

Baltimore, MD............................... 21.2 367.1 0.9 260 999 1.5 195

Frederick, MD............................... 6.2 96.2 1.6 199 954 -0.7 318

Harford, MD.................................. 5.6 87.9 0.8 267 936 2.0 142

Howard, MD................................. 9.4 158.2 0.6 290 1,248 1.1 239

Montgomery, MD.......................... 32.6 454.0 0.9 260 1,407 2.9 76

Prince George's, MD.................... 15.8 302.5 1.0 254 1,040 3.3 55

Baltimore City, MD....................... 13.7 329.1 1.6 199 1,240 3.7 41

Barnstable, MA............................. 9.2 82.8 0.3 309 840 1.1 239

Bristol, MA.................................... 16.8 214.2 0.1 320 939 7.4 7

Essex, MA.................................... 23.2 311.5 1.5 210 1,057 1.0 245

Hampden, MA.............................. 16.9 199.2 1.2 234 921 -0.4 310

Middlesex, MA.............................. 52.4 857.2 2.4 135 1,627 5.0 23

Norfolk, MA................................... 24.4 332.6 0.9 260 1,170 1.5 195

Plymouth, MA............................... 14.9 180.2 0.9 260 904 1.5 195

Suffolk, MA................................... 26.6 626.0 2.2 150 1,909 2.8 81

Worcester, MA.............................. 23.3 329.4 1.9 165 986 0.8 266

Genesee, MI................................. 6.9 131.1 -0.2 328 822 4.2 37

Ingham, MI................................... 6.0 144.7 -0.2 328 943 1.8 162

Kalamazoo, MI............................. 5.1 113.2 1.2 234 954 2.9 76

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,

first quarter 2015 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-153

Ranking by

percent

change

First

quarter

2015

Percent

change,

first quarter

2014-153

Ranking by

percent

change

Kent, MI....................................... 13.9 364.3 3.1 83 $879 1.3 223

Macomb, MI.................................. 17.2 307.9 1.6 199 1,001 1.5 195

Oakland, MI.................................. 38.2 688.9 1.4 214 1,147 3.5 48

Ottawa, MI.................................... 5.5 115.2 2.8 103 835 6.8 10

Saginaw, MI.................................. 4.0 82.1 0.6 290 787 -2.4 339

Washtenaw, MI............................. 8.1 201.7 1.8 177 1,033 3.7 41

Wayne, MI.................................... 30.3 692.5 1.2 234 1,141 1.2 235

Anoka, MN.................................... 6.9 116.4 1.7 186 914 3.5 48

Dakota, MN.................................. 9.7 180.1 2.3 142 1,013 1.9 150

Hennepin, MN.............................. 40.6 868.0 2.2 150 1,385 4.4 31

Olmsted, MN................................ 3.4 91.4 0.5 303 1,148 11.7 1

Ramsey, MN................................. 13.3 321.1 1.3 223 1,259 5.4 17

St. Louis, MN................................ 5.3 95.6 1.6 199 830 2.3 119

Stearns, MN................................. 4.3 82.7 1.9 165 795 5.4 17

Washington, MN........................... 5.4 75.8 2.0 163 870 3.8 39

Harrison, MS................................ 4.4 82.1 0.3 309 723 2.3 119

Hinds, MS..................................... 5.9 119.8 1.0 254 844 1.0 245

Boone, MO................................... 4.8 90.1 1.6 199 771 3.1 62

Clay, MO...................................... 5.4 95.0 5.3 6 886 1.7 175

Greene, MO.................................. 8.4 159.3 1.8 177 750 1.8 162

Jackson, MO................................ 20.4 354.4 1.7 186 1,007 1.3 223

St. Charles, MO............................ 8.8 136.5 3.7 45 848 2.8 81

St. Louis, MO................................ 35.0 580.5 1.3 223 1,099 2.6 96

St. Louis City, MO........................ 11.9 221.2 1.8 177 1,175 0.8 266

Yellowstone, MT........................... 6.4 79.3 3.2 76 836 1.6 185

Douglas, NE................................. 18.4 326.6 1.3 223 960 2.7 88

Lancaster, NE............................... 9.9 163.4 1.6 199 797 2.6 96

Clark, NV..................................... 53.1 898.1 4.3 22 853 -0.4 310

Washoe, NV................................. 14.2 196.7 3.4 64 850 -0.7 318

Hillsborough, NH.......................... 12.1 194.0 1.7 186 1,070 -1.4 332

Rockingham, NH.......................... 10.6 138.3 1.9 165 983 3.7 41

Atlantic, NJ................................... 6.6 120.9 -4.3 342 831 2.6 96

Bergen, NJ................................... 32.8 435.1 1.0 254 1,226 -0.2 307

Burlington, NJ............................... 11.1 192.8 1.3 223 1,056 1.6 185

Camden, NJ................................. 11.9 197.5 2.5 127 946 1.0 245

Essex, NJ.................................... 20.4 334.2 0.6 290 1,359 1.4 210

Gloucester, NJ.............................. 6.2 100.7 2.3 142 849 1.0 245

Hudson, NJ................................... 14.3 242.2 3.5 58 1,548 -0.9 323

Mercer, NJ.................................... 11.0 234.9 2.6 119 1,521 3.5 48

Middlesex, NJ.............................. 22.0 393.6 0.4 306 1,334 2.5 108

Monmouth, NJ.............................. 20.0 244.0 1.3 223 992 -0.9 323

Morris, NJ..................................... 17.0 278.7 0.8 267 1,755 6.8 10

Ocean, NJ.................................... 12.8 152.5 1.7 186 790 1.2 235

Passaic, NJ.................................. 12.3 163.8 0.0 324 971 1.8 162

Somerset, NJ............................... 10.1 178.9 1.8 177 2,080 0.6 279

Union, NJ..................................... 14.3 218.1 1.0 254 1,327 4.4 31

Bernalillo, NM............................... 18.0 313.2 0.9 260 844 1.1 239

Albany, NY................................... 10.3 227.6 2.1 155 1,007 0.0 298

Bronx, NY..................................... 18.4 297.6 3.2 76 901 0.9 256

Broome, NY.................................. 4.6 85.8 -1.0 339 759 1.7 175

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,

first quarter 2015 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-153

Ranking by

percent

change

First

quarter

2015

Percent

change,

first quarter

2014-153

Ranking by

percent

change

Dutchess, NY............................... 8.4 108.5 0.9 260 $961 1.7 175

Erie, NY........................................ 24.5 453.3 0.6 290 885 1.3 223

Kings, NY..................................... 59.3 649.7 4.3 22 818 3.3 55

Monroe, NY.................................. 18.6 373.6 0.1 320 935 1.0 245

Nassau, NY.................................. 53.5 605.0 1.2 234 1,103 1.4 210

New York, NY............................... 129.0 2,346.5 2.6 119 2,847 -1.3 331

Oneida, NY................................... 5.4 101.8 0.6 290 763 1.6 185

Onondaga, NY.............................. 13.0 238.2 0.1 320 895 -1.5 334

Orange, NY.................................. 10.2 137.0 1.9 165 805 1.0 245

Queens, NY.................................. 50.9 621.3 3.5 58 936 1.4 210

Richmond, NY.............................. 9.7 111.3 2.1 155 825 0.9 256

Rockland, NY............................... 10.4 116.0 2.7 112 1,012 -1.4 332

Saratoga, NY................................ 5.9 80.6 2.5 127 882 1.5 195

Suffolk, NY................................... 52.0 624.0 0.7 282 1,048 2.4 114

Westchester, NY.......................... 36.5 411.8 1.6 199 1,419 -1.1 327

Buncombe, NC............................. 8.5 121.5 3.5 58 728 -0.1 304

Catawba, NC................................ 4.3 82.1 1.7 186 761 4.8 26

Cumberland, NC........................... 6.2 116.0 -1.3 340 741 1.4 210

Durham, NC................................. 7.8 189.3 2.8 103 1,369 2.2 127

Forsyth, NC.................................. 9.3 179.0 1.8 177 1,017 -0.8 322

Guilford, NC.................................. 14.2 273.0 2.4 135 901 1.6 185

Mecklenburg, NC.......................... 34.7 627.7 4.3 22 1,397 1.2 235

New Hanover, NC........................ 7.6 103.4 3.6 52 782 1.0 245

Wake, NC..................................... 31.4 500.0 3.7 45 1,039 1.5 195

Cass, ND...................................... 6.8 113.6 2.8 103 914 5.3 20

Butler, OH..................................... 7.5 141.6 1.4 214 909 3.6 45

Cuyahoga, OH.............................. 35.5 699.7 0.3 309 1,071 1.8 162

Delaware, OH............................... 4.8 81.2 0.2 314 1,107 -0.5 314

Franklin, OH................................. 30.3 703.4 2.5 127 1,045 1.9 150

Hamilton, OH................................ 23.1 495.3 1.3 223 1,122 0.6 279

Lake, OH...................................... 6.3 92.9 0.7 282 829 1.0 245

Lorain, OH.................................... 6.0 94.1 0.7 282 809 0.7 274

Lucas, OH.................................... 10.0 202.8 0.8 267 887 2.1 133

Mahoning, OH.............................. 5.8 96.4 0.7 282 698 2.2 127

Montgomery, OH.......................... 11.9 244.7 1.6 199 858 0.4 286

Stark, OH..................................... 8.6 155.4 0.8 267 759 1.3 223

Summit, OH................................. 14.1 259.4 1.2 234 938 1.5 195

Warren, OH................................. 4.6 83.9 2.0 163 873 1.7 175

Cleveland, OK.............................. 5.4 80.4 1.7 186 702 1.4 210

Oklahoma, OK.............................. 26.9 446.7 1.8 177 1,005 3.6 45

Tulsa, OK..................................... 21.7 347.5 2.3 142 980 0.9 256

Clackamas, OR............................ 13.8 147.8 2.7 112 914 3.5 48

Jackson, OR................................ 6.9 80.3 3.4 64 744 1.8 162

Lane, OR...................................... 11.5 144.0 2.5 127 760 2.6 96

Marion, OR................................... 9.9 140.8 4.2 26 770 2.1 133

Multnomah, OR............................ 31.8 472.3 3.4 64 1,026 1.5 195

Washington, OR........................... 17.9 270.5 3.6 52 1,278 6.0 14

Allegheny, PA............................... 35.5 675.6 0.1 320 1,200 6.3 12

Berks, PA..................................... 8.9 167.1 1.4 214 881 1.5 195

Bucks, PA..................................... 19.7 250.0 1.2 234 930 1.1 239

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,

first quarter 2015 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-153

Ranking by

percent

change

First

quarter

2015

Percent

change,

first quarter

2014-153

Ranking by

percent

change

Butler, PA..................................... 5.0 83.3 -0.6 335 $919 1.9 150

Chester, PA.................................. 15.2 240.1 0.6 290 1,363 -4.0 341

Cumberland, PA........................... 6.2 127.7 2.4 135 908 -0.5 314

Dauphin, PA................................ 7.4 173.7 0.6 290 1,036 0.0 298

Delaware, PA............................... 13.9 215.4 0.8 267 1,143 1.9 150

Erie, PA........................................ 7.2 122.6 1.0 254 770 1.4 210

Lackawanna, PA.......................... 5.8 95.8 -0.1 326 752 1.3 223

Lancaster, PA............................... 13.1 224.3 1.9 165 818 1.9 150

Lehigh, PA.................................... 8.5 178.7 1.1 243 1,006 2.9 76

Luzerne, PA.................................. 7.5 139.9 0.8 267 783 1.4 210

Montgomery, PA........................... 27.3 468.0 0.8 267 1,387 3.0 67

Northampton, PA.......................... 6.6 105.8 1.3 223 882 1.4 210

Philadelphia, PA........................... 35.0 646.1 1.6 199 1,214 2.4 114

Washington, PA............................ 5.4 86.3 1.5 210 1,219 10.7 2

Westmoreland, PA....................... 9.3 129.5 0.2 314 785 1.3 223

York, PA....................................... 9.0 171.5 0.8 267 854 1.4 210

Providence, RI.............................. 17.4 276.1 1.3 223 1,077 1.9 150

Charleston, SC............................. 13.2 230.2 3.1 83 880 1.5 195

Greenville, SC.............................. 13.2 252.2 2.8 103 858 0.5 282

Horry, SC..................................... 8.2 113.6 3.3 73 583 2.1 133

Lexington, SC............................... 6.2 110.4 3.4 64 748 3.2 58

Richland, SC................................ 9.6 210.8 1.1 243 862 1.4 210

Spartanburg, SC........................... 6.0 125.9 2.1 155 834 2.3 119

York, SC....................................... 5.2 83.6 3.1 83 800 3.0 67

Minnehaha, SD............................. 6.9 121.0 2.1 155 872 2.1 133

Davidson, TN................................ 20.5 444.7 2.9 97 1,085 2.6 96

Hamilton, TN................................ 9.1 189.2 2.3 142 880 2.0 142

Knox, TN...................................... 11.6 228.0 2.6 119 858 2.5 108

Rutherford, TN.............................. 5.0 113.6 2.6 119 861 3.0 67

Shelby, TN.................................... 20.0 477.2 1.3 223 1,009 -0.7 318

Williamson, TN............................. 7.6 111.2 5.2 9 1,262 6.9 9

Bell, TX......................................... 5.0 113.1 1.8 177 813 -0.9 323

Bexar, TX..................................... 37.7 810.1 3.2 76 937 2.4 114

Brazoria, TX................................. 5.3 102.3 4.3 22 1,073 4.4 31

Brazos, TX.................................... 4.2 99.1 4.2 26 736 3.1 62

Cameron, TX................................ 6.4 135.3 1.4 214 593 2.4 114

Collin, TX...................................... 21.8 357.2 4.1 29 1,244 1.9 150

Dallas, TX..................................... 72.0 1,570.9 3.7 45 1,303 1.7 175

Denton, TX.................................. 13.0 214.3 5.8 2 905 2.3 119

Ector, TX..................................... 3.9 76.1 2.3 142 1,067 -1.1 327

El Paso, TX.................................. 14.4 287.5 1.7 186 689 0.0 298

Fort Bend, TX............................... 11.5 167.4 5.0 12 1,028 0.1 297

Galveston, TX............................... 5.8 100.6 1.8 177 891 -0.9 323

Gregg, TX..................................... 4.2 78.0 1.1 243 875 0.3 290

Harris, TX..................................... 110.1 2,288.8 3.0 90 1,455 3.8 39

Hidalgo, TX................................... 11.9 245.2 2.8 103 607 1.7 175

Jefferson, TX................................ 5.8 123.6 2.9 97 1,077 5.9 15

Lubbock, TX................................. 7.3 132.7 2.2 150 760 1.6 185

McLennan, TX.............................. 5.0 104.6 0.2 314 797 3.0 67

Midland, TX.................................. 5.4 90.4 1.7 186 1,326 -0.2 307

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,

first quarter 2015 - Continued

Employment Average weekly wage 2

County1

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-153

Ranking by

percent

change

First

quarter

2015

Percent

change,

first quarter

2014-153

Ranking by

percent

change

Montgomery, TX........................... 10.3 164.5 5.8 2 $1,049 1.9 150

Nueces, TX.................................. 8.2 164.5 1.9 165 888 2.7 88

Potter, TX..................................... 3.9 78.4 1.2 234 794 2.8 81

Smith, TX..................................... 6.0 98.4 3.6 52 802 0.9 256

Tarrant, TX................................... 40.4 828.0 2.1 155 1,028 2.7 88

Travis, TX..................................... 36.3 676.0 3.8 40 1,153 3.7 41

Webb, TX..................................... 5.1 96.8 3.1 83 663 2.2 127

Williamson, TX............................. 9.3 147.9 2.9 97 1,091 -3.1 340

Davis, UT..................................... 7.7 115.1 3.9 37 785 0.8 266

Salt Lake, UT................................ 41.0 635.8 3.4 64 966 2.0 142

Utah, UT....................................... 14.1 202.0 6.7 1 786 1.9 150

Weber, UT.................................... 5.6 97.9 3.8 40 721 -0.1 304

Chittenden, VT............................. 6.5 99.3 1.6 199 942 0.5 282

Arlington, VA................................ 8.9 165.9 1.3 223 1,732 2.7 88

Chesterfield, VA........................... 8.1 125.4 1.8 177 863 1.8 162

Fairfax, VA.................................... 35.3 574.5 0.5 303 1,635 2.7 88

Henrico, VA.................................. 10.6 181.7 2.9 97 1,061 0.3 290

Loudoun, VA................................ 10.9 146.9 0.9 260 1,246 0.2 292

Prince William, VA........................ 8.5 121.2 1.7 186 862 -0.1 304

Alexandria City, VA...................... 6.3 94.5 1.2 234 1,395 1.5 195

Chesapeake City, VA................... 5.7 95.5 -0.8 337 765 0.9 256

Newport News City, VA................ 3.7 97.0 -0.4 332 1,032 4.3 34

Norfolk City, VA........................... 5.6 133.1 -0.4 332 979 1.6 185

Richmond City, VA....................... 7.1 147.4 0.6 290 1,206 4.5 29

Virginia Beach City, VA................ 11.3 169.4 1.7 186 780 1.7 175

Benton, WA.................................. 5.7 80.4 4.4 19 970 1.7 175

Clark, WA..................................... 14.0 142.5 4.8 13 898 1.8 162

King, WA...................................... 84.6 1,254.9 3.5 58 1,391 2.8 81

Kitsap, WA.................................... 6.7 82.6 2.3 142 907 2.3 119

Pierce, WA................................... 21.8 280.8 2.4 135 881 2.0 142

Snohomish, WA............................ 20.2 271.7 2.4 135 1,102 -4.8 342

Spokane, WA............................... 15.6 207.4 2.7 112 848 2.9 76

Thurston, WA............................... 7.9 105.1 3.2 76 881 2.0 142

Whatcom, WA.............................. 7.1 84.4 2.6 119 811 1.6 185

Yakima, WA................................. 7.9 102.9 3.6 52 658 0.9 256

Kanawha, WV............................... 6.0 102.5 -0.3 331 860 2.0 142

Brown, WI..................................... 6.5 148.0 0.8 267 900 2.5 108

Dane, WI...................................... 14.2 314.4 1.6 199 1,003 3.5 48

Milwaukee, WI.............................. 25.3 475.8 0.8 267 1,015 2.2 127

Outagamie, WI............................. 5.0 102.8 1.9 165 845 1.9 150

Waukesha, WI.............................. 12.2 229.5 1.2 234 1,034 4.3 34

Winnebago, WI............................. 3.5 88.7 0.2 314 954 2.8 81

San Juan, PR............................... 10.8 250.4 -2.1 (5) 631 1.6 (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 quarterly 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 342 U.S. counties comprise 72.3 percent of the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,

first quarter 2015

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-152

First

quarter

2015

Percent

change,

first quarter

2014-152

United States3................................................................. 9,531.3 137,412.4 2.1 $1,048 2.1

 Private industry............................................................. 9,232.7 115,901.4 2.5 1,056 2.0

 Natural resources and mining.................................... 137.8 1,933.8 0.2 1,278 2.8

 Construction............................................................... 760.9 6,016.1 4.9 1,016 1.7

 Manufacturing............................................................ 341.4 12,219.9 1.4 1,275 1.3

 Trade, transportation, and utilities.............................. 1,921.4 26,120.2 2.3 860 2.3

 Information................................................................. 150.6 2,717.9 0.7 1,959 2.5

 Financial activities...................................................... 843.0 7,723.3 1.7 2,161 2.0

 Professional and business services........................... 1,710.4 19,178.9 2.9 1,391 2.9

 Education and health services................................... 1,512.6 20,903.3 2.0 865 1.6

 Leisure and hospitality............................................... 802.9 14,546.2 2.7 400 3.4

 Other services............................................................ 823.3 4,237.2 1.6 657 2.5

 Government.................................................................. 298.6 21,511.0 0.4 1,006 2.3

Los Angeles, CA.............................................................. 448.7 4,204.3 2.1 1,120 2.6

 Private industry............................................................. 442.8 3,647.3 2.1 1,097 2.7

 Natural resources and mining.................................... 0.5 8.9 -7.4 1,717 26.3

 Construction............................................................... 13.2 121.6 3.7 1,080 1.8

 Manufacturing............................................................ 12.3 358.9 -1.5 1,258 3.5

 Trade, transportation, and utilities.............................. 52.8 791.1 2.2 896 2.3

 Information................................................................. 9.4 202.4 -0.2 2,186 4.3

 Financial activities...................................................... 24.4 209.1 -0.4 2,227 4.0

 Professional and business services........................... 46.8 590.4 1.9 1,381 2.8

 Education and health services................................... 206.1 718.8 1.4 805 2.7

 Leisure and hospitality............................................... 30.7 470.7 2.9 575 5.7

 Other services............................................................ 27.4 144.2 1.1 671 4.4

 Government.................................................................. 5.9 557.1 1.8 1,278 2.5

New York, NY.................................................................. 129.0 2,346.5 2.6 2,847 -1.3

 Private industry............................................................. 128.1 2,084.4 2.8 3,049 -1.5

 Natural resources and mining.................................... 0.0 0.1 -8.7 3,085 -22.0

 Construction............................................................... 2.2 35.0 4.9 1,795 5.5

 Manufacturing............................................................ 2.2 26.9 0.9 1,615 -10.0

 Trade, transportation, and utilities.............................. 20.5 256.8 1.1 1,352 1.3

 Information................................................................. 4.9 152.0 1.7 3,177 -0.8

 Financial activities...................................................... 19.2 361.9 1.6 8,932 -4.0

 Professional and business services........................... 27.1 532.3 3.7 2,667 4.1

 Education and health services................................... 9.8 332.7 3.0 1,215 1.2

 Leisure and hospitality............................................... 13.8 280.0 3.2 834 3.1

 Other services............................................................ 20.4 99.0 2.0 1,153 6.5

 Government.................................................................. 0.8 262.1 1.6 1,232 0.9

Cook, IL........................................................................... 161.8 2,470.3 1.5 1,280 2.2

 Private industry............................................................. 160.5 2,175.2 1.6 1,292 2.3

 Natural resources and mining.................................... 0.1 0.9 18.2 1,104 29.6

 Construction............................................................... 13.4 64.3 9.7 1,356 2.0

 Manufacturing............................................................ 6.7 186.3 -0.1 1,231 0.3

 Trade, transportation, and utilities.............................. 32.0 457.1 1.8 971 3.5

 Information................................................................. 2.8 54.0 2.5 2,076 2.6

 Financial activities...................................................... 16.3 183.9 0.1 3,492 6.7

 Professional and business services........................... 34.7 453.5 2.8 1,543 -0.4

 Education and health services................................... 16.9 427.3 0.4 891 1.0

 Leisure and hospitality............................................... 14.6 248.5 1.1 477 5.1

 Other services............................................................ 18.4 95.5 1.2 938 -3.9

 Government.................................................................. 1.3 295.2 0.7 1,192 1.0

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

first quarter 2015 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-152

First

quarter

2015

Percent

change,

first quarter

2014-152

Harris, TX........................................................................ 110.1 2,288.8 3.0 $1,455 3.8

 Private industry............................................................. 109.6 2,020.0 3.1 1,505 3.9

 Natural resources and mining.................................... 1.9 90.4 -1.1 4,460 7.1

 Construction............................................................... 7.0 161.2 6.9 1,333 1.4

 Manufacturing............................................................ 4.8 197.4 0.5 1,833 10.7

 Trade, transportation, and utilities.............................. 24.8 471.8 3.5 1,364 5.2

 Information................................................................. 1.1 27.3 -2.4 1,527 1.3

 Financial activities...................................................... 11.3 119.9 2.2 2,230 3.1

 Professional and business services........................... 22.2 392.5 2.2 1,741 1.8

 Education and health services................................... 15.0 276.1 4.6 966 0.9

 Leisure and hospitality............................................... 9.3 217.4 4.8 428 3.9

 Other services............................................................ 11.8 65.0 3.5 795 3.9

 Government.................................................................. 0.6 268.8 2.0 1,078 3.1

Maricopa, AZ.................................................................... 94.7 1,803.5 3.0 986 0.9

 Private industry............................................................. 94.0 1,591.6 3.2 995 0.7

 Natural resources and mining.................................... 0.5 8.6 3.1 1,179 1.1

 Construction............................................................... 7.3 94.4 2.6 965 -1.5

 Manufacturing............................................................ 3.2 114.0 -0.8 1,532 2.3

 Trade, transportation, and utilities.............................. 20.0 354.4 2.8 905 1.2

 Information................................................................. 1.6 34.1 4.0 1,405 -4.4

 Financial activities...................................................... 11.2 157.5 4.1 1,479 -2.2

 Professional and business services........................... 22.1 301.2 2.7 1,092 3.2

 Education and health services................................... 10.8 268.5 4.2 922 1.9

 Leisure and hospitality............................................... 7.5 204.3 2.9 451 2.5

 Other services............................................................ 6.4 49.7 4.9 658 -1.5

 Government.................................................................. 0.7 211.9 0.9 917 1.9

Dallas, TX........................................................................ 72.0 1,570.9 3.7 1,303 1.7

 Private industry............................................................. 71.5 1,401.7 4.0 1,328 1.6

 Natural resources and mining.................................... 0.6 9.6 2.4 4,845 7.2

 Construction............................................................... 4.1 78.0 4.7 1,099 0.1

 Manufacturing............................................................ 2.7 105.1 -0.2 1,687 5.4

 Trade, transportation, and utilities.............................. 15.6 318.4 5.1 1,094 0.6

 Information................................................................. 1.4 47.9 1.6 2,383 0.4

 Financial activities...................................................... 8.7 153.8 2.7 2,155 2.1

 Professional and business services........................... 16.2 319.3 5.5 1,448 3.4

 Education and health services................................... 8.9 182.8 3.5 1,032 -3.4

 Leisure and hospitality............................................... 6.2 145.9 4.8 500 4.4

 Other services............................................................ 6.8 40.4 1.9 787 1.7

 Government.................................................................. 0.5 169.2 1.4 1,094 2.3

Orange, CA...................................................................... 110.2 1,501.2 2.5 1,221 9.1

 Private industry............................................................. 108.8 1,352.3 2.5 1,209 10.1

 Natural resources and mining.................................... 0.2 3.3 -12.1 961 11.9

 Construction............................................................... 6.4 84.7 4.4 1,190 2.8

 Manufacturing............................................................ 4.8 154.7 0.1 1,423 3.0

 Trade, transportation, and utilities.............................. 16.5 250.7 1.5 1,043 7.2

 Information................................................................. 1.2 25.4 -0.8 1,921 6.5

 Financial activities...................................................... 10.7 114.4 2.8 1,953 5.9

 Professional and business services........................... 20.1 279.1 1.2 1,726 27.6

 Education and health services................................... 27.9 189.8 2.0 882 2.3

 Leisure and hospitality............................................... 8.0 196.1 3.0 460 5.5

 Other services............................................................ 6.8 43.2 2.1 657 3.8

 Government.................................................................. 1.4 148.9 2.2 1,336 1.8

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

first quarter 2015 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-152

First

quarter

2015

Percent

change,

first quarter

2014-152

San Diego, CA................................................................ 102.6 1,352.1 2.5 $1,130 0.2

 Private industry............................................................. 100.9 1,126.3 2.7 1,110 -0.2

 Natural resources and mining.................................... 0.7 9.3 1.4 624 1.1

 Construction............................................................... 6.3 65.8 5.8 1,092 2.5

 Manufacturing............................................................ 3.0 103.4 2.7 1,681 -6.1

 Trade, transportation, and utilities.............................. 14.0 212.5 1.2 864 -6.0

 Information................................................................. 1.1 23.1 -4.5 1,703 -4.8

 Financial activities...................................................... 9.4 69.1 0.8 1,633 4.4

 Professional and business services........................... 17.7 224.4 1.7 1,716 3.7

 Education and health services................................... 28.4 184.6 2.6 881 1.7

 Leisure and hospitality............................................... 7.7 177.0 2.9 449 5.2

 Other services............................................................ 7.3 48.2 1.3 572 4.4

 Government.................................................................. 1.7 225.9 1.0 1,230 1.7

King, WA......................................................................... 84.6 1,254.9 3.5 1,391 2.8

 Private industry............................................................. 84.1 1,091.4 3.8 1,412 2.8

 Natural resources and mining.................................... 0.4 2.5 9.3 1,440 -6.7

 Construction............................................................... 6.1 61.2 14.2 1,206 3.1

 Manufacturing............................................................ 2.3 106.6 0.6 1,792 -6.8

 Trade, transportation, and utilities.............................. 14.8 235.5 5.1 1,233 5.9

 Information................................................................. 2.0 85.3 2.2 3,025 7.8

 Financial activities...................................................... 6.5 65.1 1.1 2,017 5.1

 Professional and business services........................... 16.2 208.5 5.4 1,664 2.4

 Education and health services................................... 20.1 162.1 0.9 932 3.8

 Leisure and hospitality............................................... 6.9 122.8 3.0 491 4.0

 Other services............................................................ 8.7 41.8 2.8 817 2.6

 Government.................................................................. 0.5 163.5 1.9 1,248 1.8

Miami-Dade, FL............................................................... 96.4 1,074.6 3.3 982 3.4

 Private industry............................................................. 96.1 938.7 4.0 967 3.4

 Natural resources and mining.................................... 0.5 9.8 -1.4 512 6.4

 Construction............................................................... 5.6 38.3 9.9 913 1.7

 Manufacturing............................................................ 2.8 38.2 2.1 907 0.7

 Trade, transportation, and utilities.............................. 27.7 274.5 3.7 905 4.1

 Information................................................................. 1.5 17.8 -0.8 1,575 0.0

 Financial activities...................................................... 10.1 72.8 4.3 1,886 5.1

 Professional and business services........................... 20.2 145.6 5.4 1,148 3.0

 Education and health services................................... 10.1 165.6 2.3 934 3.3

 Leisure and hospitality............................................... 7.2 133.6 2.5 544 3.6

 Other services............................................................ 8.3 39.8 5.4 576 0.9

 Government.................................................................. 0.3 135.9 -0.9 1,084 3.2

1 Average weekly wages were calculated using unrounded data.

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

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

Note: Data are preliminary. Counties selected are based on 2014 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 2015

Employment Average weekly wage 1

State

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-15

First

quarter

2015

Percent

change,

first quarter

2014-15

United States2.......................................... 9,531.3 137,412.4 2.1 $1,048 2.1

Alabama.................................................... 118.4 1,873.5 1.3 844 2.2

Alaska........................................................ 22.2 322.2 1.0 1,051 2.6

Arizona...................................................... 150.1 2,605.6 2.5 926 1.0

Arkansas................................................... 88.2 1,166.6 1.3 790 0.8

California................................................... 1,408.9 16,029.5 3.0 1,207 3.7

Colorado.................................................... 183.9 2,458.0 3.7 1,071 2.4

Connecticut............................................... 114.9 1,640.5 0.8 1,382 1.5

Delaware................................................... 30.4 422.8 2.5 1,105 -0.5

District of Columbia................................... 37.0 732.6 1.4 1,764 3.2

Florida....................................................... 657.1 8,018.0 3.6 885 1.8

Georgia...................................................... 288.1 4,107.0 3.5 989 1.7

Hawaii........................................................ 39.4 633.7 1.3 881 2.8

Idaho......................................................... 55.0 650.3 3.1 736 2.2

Illinois........................................................ 422.9 5,724.6 1.2 1,130 2.4

Indiana....................................................... 159.4 2,894.8 1.8 857 1.4

Iowa........................................................... 100.4 1,504.3 1.3 848 2.9

Kansas...................................................... 86.4 1,357.1 1.0 851 1.4

Kentucky.................................................... 121.5 1,810.3 1.5 823 1.5

Louisiana................................................... 126.2 1,927.1 1.0 885 2.0

Maine......................................................... 50.1 571.4 0.9 793 0.9

Maryland.................................................... 165.9 2,540.8 1.2 1,113 2.5

Massachusetts.......................................... 237.3 3,338.6 1.7 1,341 3.2

Michigan.................................................... 237.2 4,079.5 1.8 969 1.9

Minnesota.................................................. 166.9 2,709.2 1.8 1,079 4.3

Mississippi................................................. 72.0 1,102.3 0.6 711 0.7

Missouri..................................................... 189.9 2,678.0 1.7 882 1.8

Montana.................................................... 45.3 441.0 2.7 750 2.6

Nebraska................................................... 70.8 943.1 1.4 818 2.5

Nevada...................................................... 77.8 1,227.7 3.7 865 -0.2

New Hampshire......................................... 50.1 623.5 1.5 982 1.2

New Jersey............................................... 266.6 3,834.6 1.4 1,288 1.9

New Mexico............................................... 56.6 798.7 1.4 805 1.5

New York.................................................. 631.3 8,865.0 1.9 1,463 0.2

North Carolina........................................... 264.8 4,099.4 2.5 930 1.9

North Dakota............................................. 31.9 436.0 1.6 984 4.2

Ohio........................................................... 290.4 5,144.5 1.4 922 1.4

Oklahoma.................................................. 108.5 1,592.7 1.3 869 2.0

Oregon...................................................... 141.5 1,748.7 3.5 919 2.9

Pennsylvania............................................. 351.8 5,606.9 0.9 1,031 2.4

Rhode Island............................................. 36.1 456.1 1.4 1,008 1.2

South Carolina.......................................... 122.2 1,919.1 2.5 801 1.8

South Dakota............................................ 32.1 406.5 1.5 763 3.0

Tennessee................................................. 150.6 2,772.7 2.1 886 1.4

Texas......................................................... 632.2 11,557.0 2.9 1,089 2.5

Utah........................................................... 91.3 1,318.8 3.7 845 1.7

Vermont..................................................... 24.6 303.9 0.9 824 2.0

Virginia...................................................... 246.1 3,649.3 1.1 1,068 1.7

Washington............................................... 237.6 3,064.4 3.2 1,087 1.8

West Virginia............................................. 49.9 692.4 -0.3 792 1.4

Wisconsin.................................................. 165.7 2,734.3 1.5 877 2.5

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

first quarter 2015 - Continued

Employment Average weekly wage 1

State

Establishments,

first quarter

2015

(thousands)

March

2015

(thousands)

Percent

change,

March

2014-15

First

quarter

2015

Percent

change,

first quarter

2014-15

Wyoming................................................... 25.9 277.8 0.8 $892 1.7

Puerto Rico............................................... 46.2 904.9 -1.1 524 1.0

Virgin Islands............................................ 3.4 38.5 0.0 738 -0.7

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.
Largest Counties

Higher than U.S. average

U.S. average or lower

Source: Bureau of Labor Statistics 

 

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

March 2014-15 (U.S. average = 2.1 percent)
Largest Counties

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 2014-15 (U.S. average = 2.1 percent)