For release 10:00 a.m. (EDT), Thursday, March 19, 2015 USDL-15-0427 

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

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

COUNTY EMPLOYMENT AND WAGES

Third Quarter 2014 

From September 2013 to September 2014, employment increased in 306 of the 339 largest U.S. 

counties, the U.S. Bureau of Labor Statistics reported today. Weld, Colo., had the largest increase, with 

a gain of 8.8 percent over the year, compared with national job growth of 2.0 percent. Within Weld, the 

largest employment increase occurred in natural resources and mining, which gained 2,299 jobs over the 

year (22.1 percent). Atlantic, N.J., had the largest over-the-year decrease in employment among the 

largest counties in the U.S. with a loss of 4.0 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 2.9 percent over the year, growing to $949 in the third quarter 

of 2014. Olmsted, Minn., had the largest over-the-year increase in average weekly wages with a gain of 

11.1 percent. Within Olmsted, an average weekly wage gain of $238, or 19.7 percent, in education and 

health services made the largest contribution to the county’s increase in average weekly wages. Collier, 

Fla., experienced the largest decrease in average weekly wages with a loss of 3.9 percent over the year. 

Chart 1. Large counties ranked by percent increase in 

employment, September 2013-14 

(U.S. average = 2.0 percent) 

Chart 2. Large counties ranked by percent increase in 

average weekly wages, third quarter 2013-14 

(U.S. average = 2.9 percent) 

 

0

2

4

6

8

10

Weld,

Colo.

Benton,

Ark.

Midland,

Texas

Lee,

Fla.

Sarasota,

Fla.

Percent

0

2

4

6

8

10

12

Olmsted,

Minn.

San

Francisco,

Calif.

Santa Clara,

Calif.

San Mateo,

Calif.

Brazoria,

Texas

Percent
- 2 - 

 

Table A. Large counties ranked by September 2014 employment, September 2013-14 employment 

increase, and September 2013-14 percent increase in employment 

Employment in large counties 

 

September 2014 employment Increase in employment, Percent increase in employment, 

(thousands) September 2013-14 September 2013-14 

 (thousands) 

 

United States 137,724.1 United States 2,708.5 United States 2.0

 

Los Angeles, Calif. 4,184.4 Los Angeles, Calif. 87.6 Weld, Colo. 8.8

New York, N.Y. 2,494.4 Harris, Texas 79.2 Benton, Ark. 7.4

Cook, Ill. 2,481.9 New York, N.Y. 65.7 Midland, Texas 7.4

Harris, Texas 2,269.5 Dallas, Texas 53.1 Lee, Fla. 6.1

Maricopa, Ariz. 1,756.8 King, Wash. 41.5 Sarasota, Fla. 6.1

Dallas, Texas 1,558.5 Santa Clara, Calif. 41.4 Adams, Colo. 5.7

Orange, Calif. 1,475.0 Clark, Nev. 39.8 Kings, N.Y. 5.4

San Diego, Calif. 1,344.5 Maricopa, Ariz. 34.1 Williamson, Tenn. 5.4

King, Wash. 1,252.8 Orange, Calif. 32.6 San Francisco, Calif. 5.1

Miami-Dade, Fla. 1,047.0 San Francisco, Calif. 31.4 Fort Bend, Texas 5.1

 Montgomery, Texas 5.1

Large County Employment 

In September 2014, national employment was 137.7 million (as measured by the QCEW program). Over 

the year, employment increased 2.0 percent, or 2.7 million. The 339 U.S. counties with 75,000 or more 

jobs accounted for 71.8 percent of total U.S. employment and 76.9 percent of total wages. These 339 

counties had a net job growth of 2.0 million over the year, accounting for 74.1 percent of the overall 

U.S. employment increase. (See chart 3.) 

Weld, Colo., had the largest percentage increase in employment (8.8 percent) among the largest U.S. 

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

Harris, Texas; New York, N.Y.; Dallas, Texas; and King, Wash. These counties had a combined overthe-year employment gain of 327,100 jobs, which was 12.1 percent of the overall job increase for the 

U.S. (See table A.) 

Employment declined in 25 of the largest counties from September 2013 to September 2014. Atlantic, 

N.J., had the largest over-the-year percentage decrease in employment (-4.0 percent). Within Atlantic, 

leisure and hospitality had the largest decrease in employment, with a loss of 5,853 jobs (-12.0 percent). 

Passaic, N.J., had the second largest percentage decrease in employment, followed by McLean, Ill.; 

Peoria, Ill.; and Burlington, N.J. (See table 1.) 

 
- 3 - 

Table B. Large counties ranked by third quarter 2014 average weekly wages, third quarter 2013-14 

increase in average weekly wages, and third quarter 2013-14 percent increase in average weekly wages 

 

Average weekly wage in large counties 

 

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

third quarter 2014 wage, third quarter 2013-14 weekly wage, third 

 quarter 2013-14 

 

United States $949 United States $27 United States 2.9

 

Santa Clara, Calif. $2,012 Santa Clara, Calif. $138 Olmsted, Minn. 11.1

San Mateo, Calif. 1,824 San Francisco, Calif. 134 San Francisco, Calif. 8.6

New York, N.Y. 1,733 San Mateo, Calif. 121 Santa Clara, Calif. 7.4

San Francisco, Calif. 1,685 Olmsted, Minn. 108 San Mateo, Calif. 7.1

Washington, D.C. 1,631 Suffolk, Mass. 84 Brazoria, Texas 7.1

Arlington, Va. 1,545 Midland, Texas 80 Midland, Texas 6.8

Suffolk, Mass. 1,515 Washington, Ore. 71 Washington, Ore. 6.2

King, Wash. 1,452 Arlington, Va. 71 Howard, Md. 6.0

Fairfax, Va. 1,447 King, Wash. 71 Hamilton, Ohio 6.0

Fairfield, Conn. 1,400 Howard, Md. 67 Suffolk, Mass. 5.9

Large County Average Weekly Wages 

Average weekly wages for the nation increased to $949, a 2.9 percent increase, during the year ending in 

the third quarter of 2014. Among the 339 largest counties, 328 had over-the-year increases in average 

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

counties (11.1 percent). 

Of the 339 largest counties, 10 experienced over-the-year decreases in average weekly wages. Collier, 

Fla., had the largest percentage decrease in average weekly wages, with a loss of 3.9 percent. Within 

Collier, professional and business services had the largest impact on the county’s average weekly wage 

decrease. Within this industry, average weekly wages declined by $498 (-33.2 percent) over the year. 

Dane, Wis., had the second largest percentage decrease in average weekly wages, followed by 

Williamson, Texas; Hamilton, Ind.; and Shawnee, Kan. (See table 1.) 

Ten Largest U.S. Counties 

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

2014. Harris, Texas, had the largest gain (3.6 percent). Within Harris, trade, transportation, and utilities 

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

15,547 jobs, or 3.4 percent. Cook, Ill., had the smallest percentage increase in employment (1.2 percent) 

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

Average weekly wages increased over the year in all of the 10 largest U.S. counties. King, Wash., 

experienced the largest percentage gain in average weekly wages (5.1 percent). Within King, 

information had the largest impact on the county’s average weekly wage growth. Within this industry, 

average weekly wages increased by $437, or 9.3 percent, over the year. San Diego, Calif., had the 

smallest increase in average weekly wages (0.8 percent) among the 10 largest counties. 
- 4 - 

For More Information

The tables and charts included in this release contain data for the nation and for the 339 U.S. counties 

with annual average employment levels of 75,000 or more in 2013. September 2014 employment and 

2014 third 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 9.4 million employer reports cover 137.7 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 

third quarter of 2014 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 fourth quarter 2014 is scheduled to be released 

on Wednesday, June 17, 2015. 
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 2014 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 340 counties presented in 

this release were derived using 2013 preliminary annual averages of 

employment. For 2014 data, five counties have been added to the 

publication tables: Shelby, Ala.; Osceola, Fla.; Black Hawk, Iowa; 

Washington, Minn.; and Cleveland, Okla. These counties will be included in all 2014 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 9.4 million establishments in first quarter of 2014 

 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 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 9.2 million employer 

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

2013. 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 2013, UI and 

UCFE programs covered workers in 134.0 million jobs. The estimated 

128.7 million workers in these jobs (after adjustment for multiple jobholders) represented 95.8 percent of civilian wage and salary employment. Covered workers received $6.673 trillion in pay, representing 

93.7 percent of the wage and salary component of personal income 

and 39.8 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 2013 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. Beginning with the first quarter of 2008, adjusted data account 

for administrative changes caused by multi-unit employers who start 

reporting for each individual establishment rather than as a single entity. Beginning with the second quarter of 2011, adjusted data account 

for selected large administrative changes in employment and wages. 

Beginning with the third quarter of 2014, adjusted data account for 

state verified improvements in reporting of employment and wages. 

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 340 largest counties,

third quarter 2014

Employment Average weekly wage 2

County1

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-143

Ranking by

percent

change

Third

quarter

2014

Percent

change,

third quarter

2013-143

Ranking by

percent

change

United States4.............................. 9,419.7 137,724.1 2.0 - $949 2.9 -

Jefferson, AL................................ 17.8 339.0 0.4 282 956 3.7 55

Madison, AL................................. 9.1 183.2 1.0 228 1,036 4.0 40

Mobile, AL.................................... 9.6 165.7 1.0 228 820 1.6 274

Montgomery, AL........................... 6.3 128.1 0.5 276 810 1.8 257

Shelby, AL.................................... 5.1 80.1 2.7 96 868 2.0 231

Tuscaloosa, AL............................. 4.3 90.6 4.5 17 814 1.1 293

Anchorage Borough, AK............... 8.4 156.2 -0.2 318 1,066 3.2 91

Maricopa, AZ................................ 93.4 1,756.8 2.0 145 914 1.8 257

Pima, AZ....................................... 18.7 352.4 0.1 299 818 2.9 125

Benton, AR................................... 5.7 106.5 7.4 2 926 0.5 317

Pulaski, AR................................... 14.3 242.9 0.2 293 849 2.3 194

Washington, AR........................... 5.7 96.8 1.5 171 774 0.3 325

Alameda, CA................................ 57.5 706.5 3.2 65 1,247 4.2 31

Contra Costa, CA......................... 29.9 342.7 2.2 128 1,142 2.1 223

Fresno, CA................................... 31.1 365.4 1.0 228 747 3.2 91

Kern, CA....................................... 17.3 326.4 2.2 128 819 3.8 50

Los Angeles, CA........................... 442.4 4,184.4 2.1 137 1,036 3.1 103

Marin, CA..................................... 12.1 111.3 3.0 77 1,120 3.9 44

Monterey, CA............................... 12.9 197.1 4.0 34 797 1.0 300

Orange, CA.................................. 108.0 1,475.0 2.3 119 1,050 2.6 154

Placer, CA.................................... 11.4 143.7 3.8 42 937 2.9 125

Riverside, CA............................... 53.6 626.4 4.4 19 756 2.6 154

Sacramento, CA........................... 52.7 618.0 3.3 61 1,050 2.0 231

San Bernardino, CA..................... 51.4 658.1 4.1 29 793 2.7 140

San Diego, CA.............................. 100.8 1,344.5 2.3 119 1,030 0.8 306

San Francisco, CA....................... 57.6 648.6 5.1 9 1,685 8.6 2

San Joaquin, CA.......................... 16.7 224.0 3.6 51 799 1.4 286

San Luis Obispo, CA.................... 9.8 110.8 3.8 42 785 2.2 206

San Mateo, CA............................. 26.1 375.4 4.4 19 1,824 7.1 4

Santa Barbara, CA....................... 14.6 194.6 3.3 61 901 2.3 194

Santa Clara, CA........................... 66.2 986.6 4.4 19 2,012 7.4 3

Santa Cruz, CA............................ 9.2 100.8 2.1 137 837 2.6 154

Solano, CA................................... 10.3 128.3 2.1 137 958 4.1 38

Sonoma, CA................................. 18.9 195.1 3.5 54 896 1.9 244

Stanislaus, CA.............................. 14.4 177.6 2.5 107 801 1.9 244

Tulare, CA.................................... 9.2 151.6 2.8 86 667 3.6 61

Ventura, CA.................................. 24.9 310.7 1.2 199 945 2.1 223

Yolo, CA....................................... 6.1 101.2 0.8 248 972 4.5 23

Adams, CO................................... 9.4 185.4 5.7 6 924 2.8 129

Arapahoe, CO.............................. 19.7 307.9 2.8 86 1,096 2.7 140

Boulder, CO.................................. 13.7 170.1 2.8 86 1,129 3.0 117

Denver, CO.................................. 28.0 467.4 4.9 13 1,175 4.6 22

Douglas, CO................................. 10.3 107.9 3.7 48 1,037 0.4 323

El Paso, CO.................................. 17.2 250.4 1.8 153 859 2.3 194

Jefferson, CO............................... 18.2 223.8 3.2 65 951 3.0 117

Larimer, CO.................................. 10.6 143.7 3.8 42 859 3.4 74

Weld, CO...................................... 6.3 100.7 8.8 1 869 4.3 28

Fairfield, CT................................. 34.1 420.4 0.8 248 1,400 1.7 264

Hartford, CT.................................. 26.4 503.0 1.0 228 1,123 0.0 329

New Haven, CT............................ 23.1 361.2 0.7 263 987 2.0 231

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 340 largest counties,

third quarter 2014 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-143

Ranking by

percent

change

Third

quarter

2014

Percent

change,

third quarter

2013-143

Ranking by

percent

change

New London, CT.......................... 7.1 122.3 -0.6 330 $927 2.0 231

New Castle, DE............................ 18.3 278.7 2.3 119 1,074 1.9 244

Washington, DC........................... 36.3 732.9 1.5 171 1,631 3.8 50

Alachua, FL.................................. 6.7 121.5 2.5 107 790 3.4 74

Brevard, FL................................... 14.9 190.0 1.7 162 851 1.2 291

Broward, FL.................................. 66.5 739.9 2.8 86 869 2.2 206

Collier, FL..................................... 12.7 123.9 4.3 24 806 -3.9 339

Duval, FL..................................... 27.7 456.5 1.3 192 890 2.8 129

Escambia, FL............................... 8.2 124.9 2.1 137 733 3.2 91

Hillsborough, FL........................... 39.7 620.0 2.9 83 891 2.6 154

Lake, FL....................................... 7.7 86.2 2.8 86 656 2.5 165

Lee, FL......................................... 20.1 223.2 6.1 4 743 1.6 274

Leon, FL....................................... 8.4 142.2 2.8 86 771 1.7 264

Manatee, FL................................. 10.0 106.5 3.1 73 706 1.0 300

Marion, FL.................................... 8.1 94.9 3.2 65 644 1.1 293

Miami-Dade, FL............................ 94.3 1,047.0 3.0 77 891 2.2 206

Okaloosa, FL................................ 6.2 78.2 0.1 299 779 2.8 129

Orange, FL................................... 38.7 735.7 3.6 51 821 2.1 223

Osceola, FL.................................. 6.1 80.9 3.0 77 656 2.2 206

Palm Beach, FL............................ 52.6 538.4 3.9 36 903 1.9 244

Pasco, FL..................................... 10.3 105.7 4.2 26 650 2.7 140

Pinellas, FL................................... 31.7 397.8 2.1 137 826 2.5 165

Polk, FL........................................ 12.7 196.2 1.9 147 730 1.5 282

Sarasota, FL................................ 15.1 152.5 6.1 4 754 1.3 290

Seminole, FL................................ 14.2 169.0 4.1 29 777 1.8 257

Volusia, FL................................... 13.7 156.2 2.6 102 664 2.3 194

Bibb, GA....................................... 4.5 81.8 1.8 153 737 1.5 282

Chatham, GA................................ 8.2 141.8 4.4 19 800 1.7 264

Clayton, GA.................................. 4.3 113.0 2.4 113 892 1.9 244

Cobb, GA...................................... 22.6 325.4 3.8 42 988 2.7 140

De Kalb, GA................................. 18.8 283.6 3.4 57 947 0.9 304

Fulton, GA.................................... 44.4 772.1 3.5 54 1,236 3.2 91

Gwinnett, GA................................ 25.3 327.9 3.8 42 932 3.4 74

Muscogee, GA.............................. 4.8 94.4 0.5 276 744 2.1 223

Richmond, GA.............................. 4.7 102.5 3.0 77 800 1.5 282

Honolulu, HI.................................. 24.9 456.1 0.8 248 906 4.0 40

Ada, ID......................................... 14.1 210.3 1.1 212 831 2.1 223

Champaign, IL.............................. 4.5 90.0 1.3 192 850 1.7 264

Cook, IL........................................ 158.3 2,481.9 1.2 199 1,071 2.0 231

Du Page, IL.................................. 39.2 601.5 0.9 241 1,067 1.7 264

Kane, IL........................................ 14.1 206.8 0.7 263 831 3.4 74

Lake, IL........................................ 23.3 333.9 -0.4 323 1,180 2.4 183

McHenry, IL.................................. 9.1 97.3 1.7 162 782 3.0 117

McLean, IL.................................... 3.9 84.0 -1.2 336 892 0.3 325

Madison, IL................................... 6.2 98.1 2.4 113 771 1.6 274

Peoria, IL...................................... 4.8 100.0 -1.2 336 870 1.6 274

St. Clair, IL.................................... 5.7 92.1 -0.7 332 769 2.5 165

Sangamon, IL............................... 5.5 128.8 1.2 199 983 3.1 103

Will, IL.......................................... 16.4 218.0 1.2 199 835 2.6 154

Winnebago, IL.............................. 7.0 128.0 1.5 171 798 2.8 129

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 340 largest counties,

third quarter 2014 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-143

Ranking by

percent

change

Third

quarter

2014

Percent

change,

third quarter

2013-143

Ranking by

percent

change

Allen, IN........................................ 8.8 179.2 1.3 192 $775 2.0 231

Elkhart, IN..................................... 4.7 121.3 3.7 48 778 2.6 154

Hamilton, IN.................................. 8.8 127.7 4.1 29 891 -0.7 336

Lake, IN........................................ 10.2 187.3 -0.4 323 848 1.1 293

Marion, IN..................................... 23.4 580.5 0.9 241 947 0.2 327

St. Joseph, IN............................... 5.8 118.8 1.4 184 772 3.1 103

Tippecanoe, IN............................. 3.3 81.9 2.6 102 800 4.4 26

Vanderburgh, IN........................... 4.7 106.0 2.0 145 759 2.6 154

Black Hawk, IA.......................... 3.8 75.9 0.1 299 802 3.1 103

Johnson, IA.................................. 4.0 81.1 0.4 282 891 2.2 206

Linn, IA......................................... 6.5 128.6 0.5 276 915 3.5 66

Polk, IA........................................ 16.5 287.2 1.7 162 958 3.5 66

Scott, IA........................................ 5.5 90.4 1.1 212 764 1.1 293

Johnson, KS................................. 21.6 328.7 2.4 113 955 2.5 165

Sedgwick, KS............................... 12.4 245.5 1.2 199 825 1.4 286

Shawnee, KS................................ 4.8 97.7 1.5 171 769 -0.4 335

Wyandotte, KS............................. 3.3 88.3 4.1 29 914 3.9 44

Boone, KY................................... 4.2 78.7 3.3 61 803 0.5 317

Fayette, KY................................... 10.4 184.8 0.8 248 844 0.7 310

Jefferson, KY................................ 24.4 446.1 2.5 107 897 2.3 194

Caddo, LA.................................... 7.3 114.1 -0.4 323 788 3.7 55

Calcasieu, LA............................... 4.9 88.6 4.0 34 849 5.5 13

East Baton Rouge, LA.................. 14.6 271.7 2.3 119 889 1.0 300

Jefferson, LA................................ 13.5 191.4 0.5 276 855 2.2 206

Lafayette, LA................................ 9.2 142.1 1.1 212 949 4.4 26

Orleans, LA.................................. 11.6 186.4 3.2 65 931 2.4 183

St. Tammany, LA.......................... 7.6 83.1 2.3 119 816 3.3 81

Cumberland, ME.......................... 12.7 174.8 0.8 248 832 2.3 194

Anne Arundel, MD........................ 14.5 255.5 0.9 241 1,021 2.4 183

Baltimore, MD............................... 21.0 365.5 0.2 293 959 2.6 154

Frederick, MD............................... 6.3 96.1 0.8 248 905 4.0 40

Harford, MD.................................. 5.6 88.8 0.1 299 904 3.1 103

Howard, MD................................. 9.4 161.2 0.8 248 1,183 6.0 8

Montgomery, MD.......................... 32.5 455.9 0.4 282 1,243 2.2 206

Prince Georges, MD..................... 15.6 306.2 1.6 167 1,033 2.9 125

Baltimore City, MD....................... 13.7 337.3 2.2 128 1,123 2.7 140

Barnstable, MA............................. 9.2 98.9 1.4 184 782 2.2 206

Bristol, MA.................................... 16.5 220.5 1.7 162 839 0.8 306

Essex, MA.................................... 22.8 316.3 1.4 184 1,000 3.4 74

Hampden, MA.............................. 16.6 202.2 0.7 263 860 2.4 183

Middlesex, MA.............................. 51.4 857.9 1.8 153 1,382 1.7 264

Norfolk, MA................................... 24.0 337.6 1.4 184 1,079 2.5 165

Plymouth, MA............................... 14.5 185.4 1.8 153 880 2.3 194

Suffolk, MA................................... 25.6 621.9 2.1 137 1,515 5.9 10

Worcester, MA.............................. 22.6 331.4 2.3 119 949 0.7 310

Genesee, MI................................. 7.0 133.7 1.2 199 777 2.5 165

Ingham, MI................................... 6.1 150.5 -0.4 323 899 3.2 91

Kalamazoo, MI............................. 5.1 113.2 0.2 293 875 3.2 91

Kent, MI....................................... 13.9 363.8 2.7 96 837 3.3 81

Macomb, MI.................................. 17.2 307.6 1.0 228 942 2.4 183

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 340 largest counties,

third quarter 2014 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-143

Ranking by

percent

change

Third

quarter

2014

Percent

change,

third quarter

2013-143

Ranking by

percent

change

Oakland, MI.................................. 38.1 693.8 1.4 184 $1,028 2.2 206

Ottawa, MI.................................... 5.5 119.1 4.2 26 801 4.8 19

Saginaw, MI.................................. 4.0 83.9 -0.1 315 763 2.7 140

Washtenaw, MI............................. 8.0 198.9 0.9 241 1,028 3.6 61

Wayne, MI.................................... 30.4 694.5 0.8 248 1,027 2.9 125

Anoka, MN.................................... 6.9 118.2 1.9 147 937 3.8 50

Dakota, MN.................................. 9.6 181.5 1.3 192 919 3.6 61

Hennepin, MN.............................. 40.3 872.8 1.5 171 1,175 1.1 293

Olmsted, MN................................ 3.4 92.5 -0.3 322 1,077 11.1 1

Ramsey, MN................................. 13.3 326.1 0.3 290 1,057 2.7 140

St. Louis, MN................................ 5.3 97.6 0.5 276 827 4.2 31

Stearns, MN................................. 4.2 83.6 0.7 263 793 5.7 12

Washington, MN........................... 5.3 76.7 0.4 282 783 2.6 154

Harrison, MS................................ 4.5 82.9 -0.2 318 694 2.5 165

Hinds, MS..................................... 6.0 119.5 0.2 293 817 1.0 300

Boone, MO................................... 4.7 91.0 1.5 171 764 1.9 244

Clay, MO...................................... 5.2 95.0 4.1 29 838 0.4 323

Greene, MO.................................. 8.2 159.6 2.3 119 725 1.8 257

Jackson, MO................................ 19.9 349.2 0.0 307 961 1.7 264

St. Charles, MO............................ 8.6 133.6 1.4 184 763 4.8 19

St. Louis, MO................................ 34.1 582.5 1.1 212 993 3.7 55

St. Louis City, MO........................ 11.1 224.7 1.1 212 1,031 3.1 103

Yellowstone, MT........................... 6.3 79.5 1.2 199 807 3.9 44

Douglas, NE................................. 18.8 326.7 1.2 199 885 -0.1 330

Lancaster, NE............................... 10.2 164.4 1.2 199 769 2.5 165

Clark, NV..................................... 51.8 883.2 4.7 15 823 0.5 317

Washoe, NV................................. 13.9 196.6 2.7 96 854 0.6 315

Hillsborough, NH.......................... 12.2 195.0 1.8 153 1,014 2.7 140

Rockingham, NH.......................... 10.6 142.1 1.2 199 918 5.8 11

Atlantic, NJ................................... 6.6 131.2 -4.0 339 790 3.3 81

Bergen, NJ................................... 32.7 439.0 0.8 248 1,106 2.0 231

Burlington, NJ............................... 11.0 195.0 -1.1 335 969 0.5 317

Camden, NJ................................. 11.8 198.1 2.4 113 893 -0.1 330

Essex, NJ.................................... 20.3 327.9 -0.4 323 1,159 0.7 310

Gloucester, NJ.............................. 6.1 101.9 2.5 107 812 -0.1 330

Hudson, NJ................................... 14.1 238.0 0.4 282 1,275 1.9 244

Mercer, NJ.................................... 11.0 235.6 1.5 171 1,229 3.2 91

Middlesex, NJ.............................. 21.8 393.8 0.9 241 1,120 0.5 317

Monmouth, NJ.............................. 20.0 248.8 1.5 171 917 2.6 154

Morris, NJ..................................... 16.9 281.1 0.6 271 1,341 0.7 310

Ocean, NJ.................................... 12.6 158.9 1.5 171 749 1.6 274

Passaic, NJ.................................. 12.2 164.5 -2.2 338 926 3.5 66

Somerset, NJ............................... 10.0 180.8 2.2 128 1,372 2.2 206

Union, NJ..................................... 14.2 220.6 0.3 290 1,146 1.8 257

Bernalillo, NM............................... 18.2 315.5 1.1 212 826 2.2 206

Albany, NY................................... 10.3 226.7 1.6 167 1,008 3.5 66

Bronx, NY..................................... 17.7 254.0 3.1 73 901 0.9 304

Broome, NY.................................. 4.6 88.2 0.0 307 737 1.9 244

Dutchess, NY............................... 8.5 109.4 0.2 293 943 2.3 194

Erie, NY........................................ 24.6 461.2 0.6 271 836 2.8 129

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 340 largest counties,

third quarter 2014 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-143

Ranking by

percent

change

Third

quarter

2014

Percent

change,

third quarter

2013-143

Ranking by

percent

change

Kings, NY..................................... 57.5 569.3 5.4 7 $789 4.1 38

Monroe, NY.................................. 18.6 376.9 0.7 263 905 0.1 328

Nassau, NY.................................. 53.5 606.5 1.3 192 1,022 3.2 91

New York, NY............................... 127.7 2,494.4 2.7 96 1,733 3.8 50

Oneida, NY................................... 5.4 103.5 0.0 307 746 3.2 91

Onondaga, NY.............................. 13.1 242.9 0.0 307 856 1.9 244

Orange, NY.................................. 10.2 137.6 1.8 153 777 2.5 165

Queens, NY.................................. 50.0 558.8 3.9 36 884 2.8 129

Richmond, NY.............................. 9.6 98.9 1.0 228 805 0.6 315

Rockland, NY............................... 10.3 116.6 2.5 107 955 -0.1 330

Saratoga, NY................................ 5.8 81.2 0.4 282 844 3.6 61

Suffolk, NY................................... 52.1 640.3 0.8 248 1,031 3.1 103

Westchester, NY.......................... 36.6 413.6 1.2 199 1,196 3.1 103

Buncombe, NC............................. 8.2 120.2 1.9 147 731 2.5 165

Catawba, NC................................ 4.3 81.5 1.3 192 715 2.7 140

Cumberland, NC........................... 6.2 116.5 -0.8 334 748 1.1 293

Durham, NC................................. 7.6 188.7 1.5 171 1,219 2.4 183

Forsyth, NC.................................. 9.1 179.0 1.1 212 889 5.0 17

Guilford, NC.................................. 14.2 270.9 0.8 248 843 4.2 31

Mecklenburg, NC.......................... 33.8 612.5 4.2 26 1,071 1.7 264

New Hanover, NC........................ 7.4 104.1 3.2 65 750 1.1 293

Wake, NC..................................... 30.6 491.8 3.1 73 953 1.9 244

Cass, ND...................................... 6.7 116.3 4.4 19 897 4.3 28

Butler, OH..................................... 7.5 143.5 2.2 128 827 3.5 66

Cuyahoga, OH.............................. 35.5 707.9 0.1 299 974 1.8 257

Delaware, OH............................... 4.7 82.5 -0.7 332 921 2.7 140

Franklin, OH................................. 30.3 709.8 2.5 107 948 2.4 183

Hamilton, OH................................ 23.3 502.1 1.2 199 1,073 6.0 8

Lake, OH...................................... 6.3 94.8 0.8 248 786 3.8 50

Lorain, OH.................................... 6.1 97.0 1.3 192 767 1.7 264

Lucas, OH.................................... 10.0 205.2 0.0 307 827 4.2 31

Mahoning, OH.............................. 5.9 99.5 0.6 271 683 1.6 274

Montgomery, OH.......................... 12.0 247.4 1.9 147 814 1.4 286

Stark, OH..................................... 8.7 159.1 1.6 167 755 4.3 28

Summit, OH................................. 14.1 261.3 1.0 228 851 2.5 165

Warren, OH................................. 4.4 83.9 1.9 147 824 3.5 66

Cleveland, OK.............................. 5.3 80.2 1.1 212 709 2.2 206

Oklahoma, OK.............................. 26.5 445.2 1.4 184 949 4.5 23

Tulsa, OK..................................... 21.4 344.4 1.4 184 893 3.4 74

Clackamas, OR............................ 13.3 147.9 2.2 128 874 1.9 244

Jackson, OR................................ 6.8 81.7 1.6 167 740 4.2 31

Lane, OR...................................... 11.2 143.1 2.3 119 754 3.7 55

Marion, OR................................... 9.7 144.2 2.9 83 764 4.2 31

Multnomah, OR............................ 31.2 466.7 2.7 96 979 2.8 129

Washington, OR........................... 17.3 267.1 2.3 119 1,216 6.2 7

Allegheny, PA............................... 35.1 686.2 0.1 299 1,024 2.0 231

Berks, PA..................................... 8.9 167.6 1.5 171 852 3.0 117

Bucks, PA..................................... 19.6 252.1 1.2 199 892 2.5 165

Butler, PA..................................... 5.0 85.2 0.0 307 889 2.7 140

Chester, PA.................................. 15.1 240.9 0.9 241 1,160 1.8 257

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 340 largest counties,

third quarter 2014 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-143

Ranking by

percent

change

Third

quarter

2014

Percent

change,

third quarter

2013-143

Ranking by

percent

change

Cumberland, PA........................... 6.1 127.3 1.5 171 $867 1.9 244

Dauphin, PA................................ 7.3 176.8 0.6 271 939 2.7 140

Delaware, PA............................... 13.7 216.0 1.0 228 994 2.7 140

Erie, PA........................................ 7.2 125.2 0.1 299 755 2.0 231

Lackawanna, PA.......................... 5.8 97.9 0.7 263 735 3.2 91

Lancaster, PA............................... 12.9 227.4 2.2 128 790 3.0 117

Lehigh, PA.................................... 8.5 182.0 1.1 212 926 2.3 194

Luzerne, PA.................................. 7.5 141.7 1.1 212 751 2.3 194

Montgomery, PA........................... 27.2 473.0 0.8 248 1,133 2.4 183

Northampton, PA.......................... 6.6 106.1 0.7 263 824 1.4 286

Philadelphia, PA........................... 34.7 645.3 1.8 153 1,125 2.0 231

Washington, PA............................ 5.3 88.1 1.5 171 939 4.9 18

Westmoreland, PA....................... 9.3 133.9 0.8 248 767 3.1 103

York, PA....................................... 8.9 173.0 0.2 293 825 2.1 223

Providence, RI.............................. 17.3 280.5 1.8 153 937 1.6 274

Charleston, SC............................. 12.7 228.9 4.3 24 837 2.8 129

Greenville, SC.............................. 12.9 248.3 3.9 36 841 2.6 154

Horry, SC..................................... 8.0 118.3 3.3 61 580 2.7 140

Lexington, SC............................... 5.9 107.9 3.2 65 728 2.8 129

Richland, SC................................ 9.3 209.9 2.1 137 815 2.5 165

Spartanburg, SC........................... 5.9 124.1 2.9 83 795 3.9 44

York, SC....................................... 5.0 81.6 3.9 36 752 3.3 81

Minnehaha, SD............................. 6.8 121.9 2.8 86 824 3.3 81

Davidson, TN................................ 19.8 459.7 3.8 42 967 2.0 231

Hamilton, TN................................ 8.9 188.1 0.6 271 831 3.1 103

Knox, TN...................................... 11.3 227.6 2.7 96 815 2.3 194

Rutherford, TN.............................. 4.8 113.0 3.2 65 825 3.3 81

Shelby, TN.................................... 19.6 476.1 1.0 228 965 0.8 306

Williamson, TN............................. 7.2 109.5 5.4 7 1,047 2.8 129

Bell, TX......................................... 4.9 111.2 -0.1 315 798 3.5 66

Bexar, TX..................................... 37.1 796.4 2.6 102 854 3.3 81

Brazoria, TX................................. 5.2 99.4 2.6 102 966 7.1 4

Brazos, TX.................................... 4.2 96.2 1.1 212 734 3.2 91

Cameron, TX................................ 6.3 133.5 1.0 228 603 3.1 103

Collin, TX...................................... 21.3 346.4 3.2 65 1,097 2.0 231

Dallas, TX..................................... 71.4 1,558.5 3.5 54 1,141 2.5 165

Denton, TX.................................. 12.6 205.8 4.5 17 871 3.6 61

El Paso, TX.................................. 14.4 283.4 0.4 282 682 2.4 183

Fort Bend, TX............................... 11.2 164.4 5.1 9 956 0.7 310

Galveston, TX............................... 5.7 101.0 2.8 86 824 2.1 223

Gregg, TX..................................... 4.2 79.0 3.0 77 864 2.5 165

Harris, TX..................................... 108.7 2,269.5 3.6 51 1,238 4.0 40

Hidalgo, TX................................... 11.8 237.9 2.6 102 616 3.5 66

Jefferson, TX................................ 5.8 124.0 4.6 16 969 4.5 23

Lubbock, TX................................. 7.3 131.5 2.2 128 764 3.7 55

McLennan, TX.............................. 5.0 105.0 0.7 263 775 4.2 31

Midland, TX.................................. 5.4 93.1 7.4 2 1,256 6.8 6

Montgomery, TX........................... 10.0 159.5 5.1 9 954 5.5 13

Nueces, TX.................................. 8.1 164.1 3.4 57 860 5.5 13

Potter, TX..................................... 4.0 77.3 0.5 276 802 3.4 74

 See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 340 largest counties,

third quarter 2014 - Continued

Employment Average weekly wage 2

County1

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-143

Ranking by

percent

change

Third

quarter

2014

Percent

change,

third quarter

2013-143

Ranking by

percent

change

Smith, TX..................................... 5.9 96.9 1.7 162 $818 3.9 44

Tarrant, TX................................... 39.9 825.6 1.9 147 944 3.9 44

Travis, TX..................................... 35.3 658.1 3.9 36 1,074 3.7 55

Webb, TX..................................... 5.0 95.0 2.4 113 653 3.3 81

Williamson, TX............................. 9.0 144.5 2.4 113 923 -0.8 337

Davis, UT..................................... 7.8 115.9 3.9 36 762 3.0 117

Salt Lake, UT................................ 40.8 627.0 2.8 86 897 2.4 183

Utah, UT....................................... 13.9 198.8 4.8 14 747 -0.1 330

Weber, UT.................................... 5.6 95.3 1.8 153 721 1.7 264

Chittenden, VT............................. 6.4 100.7 1.1 212 916 2.1 223

Arlington, VA................................ 8.8 164.7 0.0 307 1,545 4.8 19

Chesterfield, VA........................... 8.1 123.2 0.9 241 825 2.2 206

Fairfax, VA.................................... 35.1 579.3 -0.4 323 1,447 1.2 291

Henrico, VA.................................. 10.5 178.7 1.1 212 922 2.2 206

Loudoun, VA................................ 10.6 147.9 1.0 228 1,105 1.9 244

Prince William, VA........................ 8.4 118.5 1.0 228 845 0.8 306

Alexandria City, VA...................... 6.2 94.9 -0.1 315 1,345 2.3 194

Chesapeake City, VA................... 5.7 96.0 0.0 307 743 2.2 206

Newport News City, VA................ 3.7 97.7 0.1 299 928 2.4 183

Norfolk City, VA........................... 5.5 134.6 -0.4 323 931 3.3 81

Richmond City, VA....................... 7.1 149.5 1.0 228 1,041 2.2 206

Virginia Beach City, VA................ 11.3 172.3 1.1 212 751 2.0 231

Benton, WA.................................. 5.7 82.7 3.4 57 930 1.5 282

Clark, WA..................................... 14.0 143.0 5.0 12 890 2.8 129

King, WA...................................... 84.3 1,252.8 3.4 57 1,452 5.1 16

Kitsap, WA.................................... 6.7 83.1 3.0 77 904 3.3 81

Pierce, WA................................... 21.7 282.3 2.8 86 870 3.0 117

Snohomish, WA............................ 20.2 269.9 2.2 128 1,019 0.5 317

Spokane, WA............................... 15.7 208.5 2.1 137 823 3.1 103

Thurston, WA............................... 7.9 104.3 3.7 48 877 1.6 274

Whatcom, WA.............................. 7.1 83.5 1.1 212 782 2.2 206

Yakima, WA................................. 8.1 119.2 3.1 73 658 3.1 103

Kanawha, WV............................... 5.9 103.9 -0.2 318 828 3.0 117

Brown, WI..................................... 6.4 149.6 -0.2 318 829 3.1 103

Dane, WI...................................... 14.1 314.7 1.1 212 900 -2.2 338

Milwaukee, WI.............................. 25.0 482.4 0.4 282 902 2.5 165

Outagamie, WI............................. 5.0 103.4 0.8 248 808 2.5 165

Waukesha, WI.............................. 12.3 232.1 0.3 290 929 2.5 165

Winnebago, WI............................. 3.5 89.7 -0.6 330 865 3.2 91

San Juan, PR............................... 11.4 249.3 -1.8 (5) 603 1.3 (5)

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

2 Average weekly wages were calculated using unrounded data.

3 Percent changes were computed from 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 339 U.S. counties comprise 71.8 percent of the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,

third quarter 2014

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-142

Third

quarter

2014

Percent

change,

third quarter

2013-142

United States3................................................................. 9,419.7 137,724.1 2.0 $949 2.9

 Private industry............................................................. 9,125.2 116,563.5 2.3 940 2.8

 Natural resources and mining.................................... 136.7 2,200.5 3.5 1,072 6.1

 Construction............................................................... 758.2 6,371.0 4.7 1,040 3.6

 Manufacturing............................................................ 339.4 12,226.3 1.3 1,153 2.7

 Trade, transportation, and utilities.............................. 1,918.4 26,099.3 2.0 802 2.8

 Information................................................................. 152.3 2,723.0 0.5 1,726 6.3

 Financial activities...................................................... 837.0 7,692.6 0.9 1,392 3.4

 Professional and business services........................... 1,685.8 19,249.6 2.9 1,202 2.3

 Education and health services................................... 1,489.1 20,622.5 1.8 882 2.1

 Leisure and hospitality............................................... 798.5 14,882.7 2.5 399 3.1

 Other services............................................................ 816.1 4,240.0 1.8 644 3.4

 Government.................................................................. 294.5 21,160.6 0.4 1,004 3.4

Los Angeles, CA.............................................................. 442.4 4,184.4 2.1 1,036 3.1

 Private industry............................................................. 436.6 3,647.8 2.2 1,000 2.7

 Natural resources and mining.................................... 0.5 9.5 -1.4 1,618 -8.9

 Construction............................................................... 13.5 121.9 2.5 1,062 0.0

 Manufacturing............................................................ 12.6 361.0 -2.0 1,136 1.6

 Trade, transportation, and utilities.............................. 54.0 788.2 2.3 857 3.4

 Information................................................................. 9.7 198.6 0.0 1,840 6.6

 Financial activities...................................................... 24.6 207.8 -0.4 1,624 7.7

 Professional and business services........................... 47.8 604.0 0.9 1,242 0.9

 Education and health services................................... 203.5 719.8 2.3 802 2.8

 Leisure and hospitality............................................... 30.8 468.3 4.5 578 5.1

 Other services............................................................ 28.1 148.2 3.8 688 2.7

 Government.................................................................. 5.8 536.7 1.9 1,288 5.5

New York, NY.................................................................. 127.7 2,494.4 2.7 1,733 3.8

 Private industry............................................................. 127.3 2,060.9 3.3 1,845 3.4

 Natural resources and mining.................................... 0.0 0.2 -3.2 3,140 48.3

 Construction............................................................... 2.2 35.6 4.4 1,716 2.6

 Manufacturing............................................................ 2.2 25.4 -0.7 1,196 6.4

 Trade, transportation, and utilities.............................. 20.7 261.4 1.4 1,265 4.7

 Information................................................................. 4.8 150.4 1.6 2,360 1.0

 Financial activities...................................................... 19.3 360.5 2.7 3,285 5.1

 Professional and business services........................... 26.9 523.6 3.6 2,074 3.2

 Education and health services................................... 9.7 320.6 3.7 1,265 0.9

 Leisure and hospitality............................................... 13.7 277.2 4.5 818 5.5

 Other services............................................................ 20.0 98.5 2.9 1,049 3.8

 Government.................................................................. 0.4 433.5 0.0 1,195 4.6

Cook, IL........................................................................... 158.3 2,481.9 1.2 1,071 2.0

 Private industry............................................................. 157.0 2,187.8 1.5 1,071 3.3

 Natural resources and mining.................................... 0.1 1.0 3.4 1,112 7.0

 Construction............................................................... 13.1 71.8 5.9 1,387 3.7

 Manufacturing............................................................ 6.7 185.4 -0.3 1,137 4.8

 Trade, transportation, and utilities.............................. 31.4 454.8 2.1 869 3.7

 Information................................................................. 2.9 54.4 1.2 1,627 3.0

 Financial activities...................................................... 16.2 184.2 -0.1 1,848 5.1

 Professional and business services........................... 33.7 455.4 2.0 1,345 2.9

 Education and health services................................... 16.6 421.7 0.8 919 1.5

 Leisure and hospitality............................................... 14.3 258.7 2.0 481 1.3

 Other services............................................................ 17.9 96.8 0.8 838 4.9

 Government.................................................................. 1.3 294.1 -0.6 1,075 -6.0

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

third quarter 2014 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-142

Third

quarter

2014

Percent

change,

third quarter

2013-142

Harris, TX........................................................................ 108.7 2,269.5 3.6 $1,238 4.0

 Private industry............................................................. 108.1 2,009.9 3.9 1,254 4.0

 Natural resources and mining.................................... 1.8 95.1 6.5 3,079 7.5

 Construction............................................................... 6.8 158.6 9.9 1,262 6.4

 Manufacturing............................................................ 4.7 198.0 3.6 1,491 4.9

 Trade, transportation, and utilities.............................. 24.6 468.6 3.4 1,103 3.7

 Information................................................................. 1.2 27.9 -2.4 1,373 4.4

 Financial activities...................................................... 11.1 119.1 1.8 1,490 0.7

 Professional and business services........................... 21.9 396.3 2.7 1,513 3.6

 Education and health services................................... 14.9 270.6 2.7 972 0.8

 Leisure and hospitality............................................... 9.1 211.1 5.5 419 3.7

 Other services............................................................ 11.7 63.7 3.7 755 5.4

 Government.................................................................. 0.6 259.6 1.6 1,112 4.3

Maricopa, AZ.................................................................... 93.4 1,756.8 2.0 914 1.8

 Private industry............................................................. 92.7 1,547.6 2.2 907 1.7

 Natural resources and mining.................................... 0.5 7.0 0.2 920 0.2

 Construction............................................................... 7.3 92.3 -1.4 935 -0.5

 Manufacturing............................................................ 3.2 114.0 0.7 1,313 3.0

 Trade, transportation, and utilities.............................. 20.0 347.8 2.1 832 0.8

 Information................................................................. 1.5 33.2 5.1 1,213 2.4

 Financial activities...................................................... 11.0 153.0 2.8 1,145 1.2

 Professional and business services........................... 21.8 295.4 1.5 996 3.8

 Education and health services................................... 10.7 261.8 2.6 935 2.2

 Leisure and hospitality............................................... 7.4 191.3 3.0 433 1.6

 Other services............................................................ 6.3 48.3 2.6 651 -0.9

 Government.................................................................. 0.7 209.2 0.3 972 1.9

Dallas, TX........................................................................ 71.4 1,558.5 3.5 1,141 2.5

 Private industry............................................................. 70.9 1,390.9 3.8 1,144 2.4

 Natural resources and mining.................................... 0.6 10.0 4.9 3,840 18.3

 Construction............................................................... 4.1 77.9 5.7 1,084 5.3

 Manufacturing............................................................ 2.7 107.1 -0.4 1,278 -1.4

 Trade, transportation, and utilities.............................. 15.4 312.5 4.2 1,030 2.3

 Information................................................................. 1.4 49.2 0.4 1,722 0.2

 Financial activities...................................................... 8.6 152.3 2.5 1,532 5.1

 Professional and business services........................... 16.0 313.4 5.7 1,290 1.7

 Education and health services................................... 8.8 182.2 3.5 1,027 0.8

 Leisure and hospitality............................................... 6.1 145.9 4.9 480 4.8

 Other services............................................................ 6.8 39.9 0.6 751 4.5

 Government.................................................................. 0.5 167.6 1.1 1,112 2.9

Orange, CA...................................................................... 108.0 1,475.0 2.3 1,050 2.6

 Private industry............................................................. 106.7 1,341.6 2.4 1,037 2.9

 Natural resources and mining.................................... 0.2 3.3 -0.8 822 16.8

 Construction............................................................... 6.5 83.4 4.8 1,174 4.4

 Manufacturing............................................................ 4.9 158.1 0.3 1,387 6.3

 Trade, transportation, and utilities.............................. 16.8 254.2 2.4 939 1.4

 Information................................................................. 1.3 23.5 -4.9 1,600 5.2

 Financial activities...................................................... 10.7 113.2 1.2 1,568 0.3

 Professional and business services........................... 20.7 276.1 2.2 1,205 4.4

 Education and health services................................... 27.2 185.7 2.5 879 1.2

 Leisure and hospitality............................................... 7.9 194.3 2.1 457 4.1

 Other services............................................................ 6.9 43.5 4.0 647 1.6

 Government.................................................................. 1.3 133.4 0.6 1,196 0.9

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

third quarter 2014 - Continued

Employment Average weekly wage 1

County by NAICS supersector

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-142

Third

quarter

2014

Percent

change,

third quarter

2013-142

San Diego, CA................................................................ 100.8 1,344.5 2.3 $1,030 0.8

 Private industry............................................................. 99.4 1,124.1 2.6 987 0.1

 Natural resources and mining.................................... 0.7 11.2 4.8 610 -3.6

 Construction............................................................... 6.4 64.7 4.6 1,069 1.9

 Manufacturing............................................................ 3.1 96.9 1.4 1,414 3.9

 Trade, transportation, and utilities.............................. 14.2 212.0 1.4 773 -0.4

 Information................................................................. 1.2 24.3 -1.2 1,751 0.7

 Financial activities...................................................... 9.4 69.8 -1.3 1,340 2.1

 Professional and business services........................... 18.2 227.7 1.7 1,417 -2.1

 Education and health services................................... 28.0 184.1 3.1 874 0.8

 Leisure and hospitality............................................... 7.7 178.4 3.3 457 3.9

 Other services............................................................ 7.3 49.6 5.8 570 1.4

 Government.................................................................. 1.4 220.5 0.5 1,262 4.5

King, WA......................................................................... 84.3 1,252.8 3.4 1,452 5.1

 Private industry............................................................. 83.7 1,094.8 3.7 1,479 5.3

 Natural resources and mining.................................... 0.4 2.8 2.5 1,221 1.6

 Construction............................................................... 6.0 60.5 9.5 1,213 4.3

 Manufacturing............................................................ 2.3 106.6 0.3 1,542 1.7

 Trade, transportation, and utilities.............................. 14.8 234.4 4.6 1,125 4.5

 Information................................................................. 2.0 87.1 4.4 5,134 9.3

 Financial activities...................................................... 6.5 65.9 1.2 1,490 3.3

 Professional and business services........................... 15.8 209.1 4.3 1,528 4.9

 Education and health services................................... 20.8 160.4 3.3 949 4.3

 Leisure and hospitality............................................... 6.8 127.1 3.3 510 2.2

 Other services............................................................ 8.4 41.0 3.2 794 2.5

 Government.................................................................. 0.5 158.0 1.3 1,262 3.0

Miami-Dade, FL............................................................... 94.3 1,047.0 3.0 891 2.2

 Private industry............................................................. 94.0 911.7 3.6 873 2.2

 Natural resources and mining.................................... 0.5 7.4 6.0 573 4.8

 Construction............................................................... 5.4 37.1 11.4 887 4.5

 Manufacturing............................................................ 2.7 37.3 1.9 850 4.7

 Trade, transportation, and utilities.............................. 27.4 269.0 3.1 806 1.6

 Information................................................................. 1.6 18.4 4.5 1,402 2.0

 Financial activities...................................................... 9.9 71.8 4.2 1,362 4.0

 Professional and business services........................... 19.8 141.3 4.2 1,055 3.5

 Education and health services................................... 10.1 163.4 2.2 913 0.6

 Leisure and hospitality............................................... 7.2 127.3 2.9 521 -0.4

 Other services............................................................ 8.2 37.3 3.2 576 2.7

 Government.................................................................. 0.3 135.3 -1.3 1,017 2.2

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 2013 annual average employment. Includes workers covered by Unemployment Insurance

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

third quarter 2014

Employment Average weekly wage 1

State

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-14

Third

quarter

2014

Percent

change,

third quarter

2013-14

United States2.......................................... 9,419.7 137,724.1 2.0 $949 2.9

Alabama.................................................... 118.3 1,871.2 1.3 815 2.5

Alaska........................................................ 22.4 344.7 -0.1 1,019 3.0

Arizona...................................................... 147.4 2,539.6 1.8 876 2.0

Arkansas................................................... 87.3 1,170.9 1.3 737 1.8

California................................................... 1,386.5 16,013.4 3.1 1,095 3.7

Colorado.................................................... 180.9 2,443.0 3.7 982 3.0

Connecticut............................................... 114.4 1,663.2 0.8 1,124 1.4

Delaware................................................... 30.1 426.1 1.9 961 2.2

District of Columbia................................... 36.3 732.9 0.8 1,631 4.5

Florida....................................................... 642.5 7,748.4 3.3 826 2.1

Georgia...................................................... 283.0 4,059.0 3.4 891 2.8

Hawaii........................................................ 39.0 625.1 0.9 870 3.9

Idaho......................................................... 55.4 658.4 2.1 721 2.6

Illinois........................................................ 416.0 5,807.4 1.2 982 2.5

Indiana....................................................... 158.6 2,924.7 1.4 799 1.9

Iowa........................................................... 100.2 1,528.8 1.1 800 3.6

Kansas...................................................... 86.0 1,363.1 1.2 794 2.3

Kentucky.................................................... 121.0 1,827.8 1.8 781 2.5

Louisiana................................................... 127.2 1,928.3 1.7 852 3.1

Maine......................................................... 49.4 604.5 0.3 754 2.6

Maryland.................................................... 164.9 2,574.5 1.1 1,042 3.1

Massachusetts.......................................... 232.1 3,386.7 1.8 1,164 3.0

Michigan.................................................... 236.5 4,141.0 1.7 896 2.4

Minnesota.................................................. 165.9 2,757.9 1.1 965 2.9

Mississippi................................................. 71.5 1,105.0 0.5 697 1.3

Missouri..................................................... 185.7 2,686.4 1.0 828 2.7

Montana.................................................... 44.3 449.5 0.7 732 3.7

Nebraska................................................... 72.1 950.0 1.1 779 1.8

Nevada...................................................... 76.2 1,215.8 4.0 840 0.5

New Hampshire......................................... 50.3 633.5 1.4 927 3.6

New Jersey............................................... 264.4 3,880.4 0.8 1,087 1.7

New Mexico............................................... 57.2 804.0 1.1 786 2.6

New York.................................................. 627.7 8,902.1 2.0 1,145 3.2

North Carolina........................................... 260.3 4,085.5 1.9 839 2.8

North Dakota............................................. 31.7 455.9 4.3 977 6.1

Ohio........................................................... 290.0 5,219.1 1.4 863 3.1

Oklahoma.................................................. 107.4 1,592.3 1.0 826 3.6

Oregon...................................................... 137.5 1,752.8 2.4 887 3.6

Pennsylvania............................................. 349.5 5,676.2 1.0 937 2.6

Rhode Island............................................. 35.9 471.8 1.4 895 1.8

South Carolina.......................................... 118.7 1,902.7 2.4 768 2.4

South Dakota............................................ 32.1 415.8 1.7 733 3.7

Tennessee................................................. 146.2 2,775.5 2.4 837 2.1

Texas......................................................... 623.1 11,433.6 3.1 988 3.8

Utah........................................................... 90.8 1,304.7 3.1 803 1.5

Vermont..................................................... 24.5 306.5 1.2 805 2.3

Virginia...................................................... 242.4 3,667.9 0.6 989 2.0

Washington............................................... 236.9 3,112.8 3.2 1,087 3.9

West Virginia............................................. 49.8 709.3 -0.2 778 3.5

Wisconsin.................................................. 166.2 2,783.1 1.1 808 1.9

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

third quarter 2014 - Continued

Employment Average weekly wage 1

State

Establishments,

third quarter

2014

(thousands)

September

2014

(thousands)

Percent

change,

September

2013-14

Third

quarter

2014

Percent

change,

third quarter

2013-14

Wyoming................................................... 25.6 291.3 1.7 $877 4.4

Puerto Rico............................................... 49.0 896.7 -1.5 505 0.8

Virgin Islands............................................ 3.4 37.5 -1.0 720 2.0

1 Average weekly wages were calculated using unrounded data.

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

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

Federal Employees (UCFE) programs.
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,

September 2013-14 (U.S. average = 2.0 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, third quarter 2013-14 (U.S. average = 2.9 percent)