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For release 10:00 a.m. (EST), Tuesday, March 7, 2017 USDL-17-0297 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 2016 From September 2015 to September 2016, employment increased in 307 of the 344 largest U.S. counties, the U.S. Bureau of Labor Statistics reported today. York, S.C., had the largest percentage increase with a gain of 6.0 percent over the year, above the national job growth rate of 1.7 percent. Within York, the largest employment increase occurred in professional and business services, which gained 1,408 jobs over the year (15.0 percent). Midland, Texas, had the largest over-the-year percentage decrease in employment among the largest counties in the U.S., with a loss of 5.8 percent. Within Midland, trade, transportation, and utilities had the largest decrease in employment, with a loss of 1,504 jobs (-8.2 percent). County employment and wage data are from the Quarterly Census of Employment and Wages (QCEW) program, which provides the only detailed quarterly and annual universe count of establishments, employment, and wages at the county, metropolitan statistical area, state, and national levels by detailed industry. These data are published within 6 months following the end of each quarter. The U.S. average weekly wage increased 5.4 percent over the year, growing to $1,027 in the third quarter of 2016. Clark, Nev., had the largest over-the-year percentage increase in average weekly wages with a gain of 12.2 percent. Within Clark, an average weekly wage gain of $151 (24.0 percent) in leisure and hospitality made the largest contribution to the county’s increase in average weekly wages. Rockland, N.Y., experienced the largest percentage decrease in average weekly wages with a loss of 14.9 percent over the year. Within Rockland, manufacturing had the largest impact on the county’s average weekly wage decline with a decrease of $2,912 (-63.6 percent) over the year. Large County Employment In September 2016, national employment was 142.9 million (as measured by the QCEW program). Over the year, employment increased 1.7 percent, or 2.4 million. In September 2016, the 344 U.S. counties with 75,000 or more jobs accounted for 72.5 percent of total U.S. employment and 77.7 percent of total wages. These 344 counties had a net job growth of 2.0 million over the year, accounting for 80.5 percent of the overall U.S. employment increase. The 5 counties with the largest increases in employment levels had a combined over-the-year employment gain of 261,700 jobs, which was 10.7 percent of the overall job increase for the U.S. (See table A.) Employment declined in 33 of the largest counties from September 2015 to September 2016. Midland, Texas, had the largest over-the-year percentage decrease in employment (-5.8 percent), followed by Lafayette, La.; Gregg, Texas; Anchorage, Alaska; and Washington, Pa. (See table 1.) Table A. Large counties ranked by September 2016 employment, September 2015-16 employment increase, and September 2015-16 percent increase in employment -------------------------------------------------------------------------------------------------------- Employment in large counties -------------------------------------------------------------------------------------------------------- September 2016 employment | Increase in employment, | Percent increase in employment, (thousands) | September 2015-16 | September 2015-16 | (thousands) | -------------------------------------------------------------------------------------------------------- | | United States 142,940.5| United States 2,444.7| United States 1.7 -------------------------------------------------------------------------------------------------------- | | Los Angeles, Calif. 4,357.4| Los Angeles, Calif. 70.7| York, S.C. 6.0 Cook, Ill. 2,577.2| Maricopa, Ariz. 62.0| Williamson, Tenn. 5.8 New York, N.Y. 2,411.9| Dallas, Texas 49.6| Utah, Utah 5.3 Harris, Texas 2,262.3| King, Wash. 42.3| Collier, Fla. 5.1 Maricopa, Ariz. 1,885.6| New York, N.Y. 37.1| Washoe, Nev. 5.0 Dallas, Texas 1,662.8| Clark, Nev. 34.1| Placer, Calif. 4.9 Orange, Calif. 1,563.4| Orange, Calif. 32.3| Seminole, Fla. 4.8 San Diego, Calif. 1,415.6| Fulton, Ga. 31.7| Brevard, Fla. 4.7 King, Wash. 1,331.3| San Diego, Calif. 30.4| Volusia, Fla. 4.7 Miami-Dade, Fla. 1,107.4| Cook, Ill. 29.6| Thurston, Wash. 4.7 -------------------------------------------------------------------------------------------------------- Large County Average Weekly Wages Average weekly wages for the nation increased to $1,027, a 5.4 percent increase, during the year ending in the third quarter of 2016. Among the 344 largest counties, 339 had over-the-year increases in average weekly wages. Clark, Nev., had the largest percentage wage increase among the largest U.S. counties (12.2 percent). (See table B.) Of the 344 largest counties, 5 experienced over-the-year decreases in average weekly wages. Rockland, N.Y., had the largest percentage decrease in average weekly wages (-14.9 percent), followed by Lafayette, La.; Benton, Ark.; Lake, Ill.; and Midland, Texas. (See table 1.) Table B. Large counties ranked by third quarter 2016 average weekly wages, third quarter 2015-16 increase in average weekly wages, and third quarter 2015-16 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 2016 | wage, third quarter 2015-16 | weekly wage, third | | quarter 2015-16 -------------------------------------------------------------------------------------------------------- | | United States $1,027| United States $53| United States 5.4 -------------------------------------------------------------------------------------------------------- | | Santa Clara, Calif. $2,260| Santa Clara, Calif. $186| Clark, Nev. 12.2 San Mateo, Calif. 2,098| San Mateo, Calif. 172| Manatee, Fla. 10.7 San Francisco, Calif. 1,892| San Francisco, Calif. 150| Hillsborough, N.H. 10.4 New York, N.Y. 1,879| Middlesex, Mass. 139| Elkhart, Ind. 10.3 Washington, D.C. 1,728| King, Wash. 119| Boone, Ky. 10.3 Suffolk, Mass. 1,660| Alameda, Calif. 112| McLean, Ill. 10.2 Arlington, Va. 1,648| Hillsborough, N.H. 107| Dane, Wis. 10.1 King, Wash. 1,582| Clark, Nev. 103| Middlesex, Mass. 9.8 Middlesex, Mass. 1,555| Suffolk, Mass. 96| Washington, Ark. 9.5 Fairfax, Va. 1,546| Ramsey, Minn. 95| Alachua, Fla. 9.5 | Dane, Wis. 95| -------------------------------------------------------------------------------------------------------- Ten Largest U.S. Counties Among the 10 largest counties, 9 had over-the-year percentage increases in employment in September 2016. Maricopa, Ariz., had the largest gain (3.4 percent). Within Maricopa, professional and business services had the largest over-the-year employment level increase, with a gain of 12,662 jobs, or 4.0 percent. Harris, Texas, had the only percentage decrease in employment among the 10 largest counties (-0.9 percent). (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 (8.1 percent). Within King, trade, transportation, and utilities had the largest impact on the county’s average weekly wage growth. Within trade, transportation, and utilities, average weekly wages increased by $210, or 17.8 percent, over the year. Harris, Texas, had the smallest percentage gain in average weekly wages among the 10 largest counties (2.1 percent). For More Information The tables included in this release contain data for the nation and for the 344 U.S. counties with annual average employment levels of 75,000 or more in 2015. September 2016 employment and 2016 third quarter average weekly wages for all states are provided in table 3 of this release. The data are derived from reports submitted by employers who are subject to unemployment insurance (UI) laws. The 9.8 million employer reports cover 142.9 million full- and part-time workers. Data for the third quarter of 2016 will be available later at www.bls.gov/cew. Additional information about the quarterly employment and wages data is available in the Technical Note. More information about QCEW data may be obtained by calling (202) 691-6567. The most current news release on quarterly measures of gross job flows is available from QCEW Business Employment Dynamics at www.bls.gov/news.release/pdf/cewbd.pdf. Several BLS regional offices issue QCEW news releases targeted to local data users. Links to these releases are available at www.bls.gov/cew/cewregional.htm. _____________ The County Employment and Wages release for fourth quarter 2016 is scheduled to be released on Wednesday, June 7, 2017.
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 (NAICS). Data for 2016 are preliminary and subject to revision. For purposes of this release, large counties are defined as having employment levels of 75,000 or greater. In addition, data for San Juan, Puerto Rico, are provided, but not used in calculating U.S. averages, rankings, or in the analysis in the text. Each year, these large counties are selected on the basis of the preliminary annual average of employment for the previous year. The 345 counties presented in this release were derived using 2015 preliminary annual averages of employment. For 2016 data, four counties have been added to the publication tables: Merced, Calif.; Napa, Calif.; Bay, Fla.; and Merrimack, N.H. These counties will be included in all 2016 quarterly releases. Two counties, Black Hawk, Iowa, and Ector, Texas, which were published in the 2015 releases, will be excluded from this and future 2016 releases because their 2015 annual average employment levels were less than 75,000. The counties in table 2 are selected and sorted each year based on the annual average employment from the preceding year. 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. Summary of Major Differences between QCEW, BED, and CES Employment Measures ---------------------------------------------------------------------------------- | QCEW | BED | CES -----------|---------------------|----------------------|------------------------ Source |--Count of UI admini-|--Count of longitudi- |--Sample survey: | strative records | nally-linked UI ad- | 634,000 establish- | submitted by 9.7 | ministrative records| ments | million establish- | submitted by 7.7 | | ments in first | million private-sec-| | quarter of 2016 | tor employers | -----------|---------------------|----------------------|------------------------ Coverage |--UI and UCFE cover- |--UI coverage, exclud-|Nonfarm wage and sal- | age, including all | ing government, pri-| ary jobs: | employers subject | vate households, and|--UI coverage, exclud- | to state and fed- | establishments with | ing agriculture, pri- | eral UI laws | zero employment | vate households, and | | | self-employed workers | | |--Other employment, in- | | | cluding railroads, | | | religious organiza- | | | tions, and other non- | | | UI-covered jobs -----------|---------------------|----------------------|------------------------ Publication|--Quarterly |--Quarterly |--Monthly frequency | -Within 6 months | -7 months after the | -Usually first Friday | after the end of | end of each quarter| of following month | each quarter | | -----------|---------------------|----------------------|------------------------ Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam- file | and publishes each | quarter to longitu- | pling frame and to an- | new quarter of UI | dinal database and | nually realign sample- | data | directly summarizes | based estimates to pop- | | gross job gains and | ulation counts (bench- | | losses | marking) -----------|---------------------|----------------------|------------------------ Principal |--Provides a quarter-|--Provides quarterly |--Provides current month- products | ly and annual uni- | employer dynamics | ly estimates of employ- | verse count of es- | data on establish- | ment, hours, and earn- | tablishments, em- | ment openings, clos-| ings at the MSA, state, | ployment, and wages| ings, expansions, | and national level by | at the county, met-| and contractions at | industry | ropolitan statisti-| the national level | | cal area (MSA), | by NAICS supersec- | | state, and national| tors and by size of | | levels by detailed | firm, and at the | | industry | state private-sector| | | total level | | |--Future expansions | | | will include data | | | with greater indus- | | | try detail and data | | | at the county and | | | MSA level | -----------|---------------------|----------------------|------------------------ Principal |--Major uses include:|--Major uses include: |--Major uses include: uses | -Detailed locality | -Business cycle | -Principal national | data | analysis | economic indicator | -Periodic universe | -Analysis of employ-| -Official time series | counts for bench- | er dynamics under- | for employment change | marking sample | lying economic ex- | measures | survey estimates | pansions and con- | -Input into other ma- | -Sample frame for | tractions | jor economic indi- | BLS establishment | -Analysis of employ-| cators | surveys | ment expansion and | | | contraction by size| | | of firm | | | | -----------|---------------------|----------------------|------------------------ Program |--www.bls.gov/cew |--www.bls.gov/bdm |--www.bls.gov/ces Web sites | | | --------------------------------------------------------------------------------- Coverage Employment and wage data for workers covered by state UI laws are compiled from quarterly contribution reports submitted to the SWAs by employers. For federal civilian workers covered by the Unemployment Compensation for Federal Employees (UCFE) program, employment and wage data are compiled from quarterly reports submitted by four major federal payroll processing centers on behalf of all federal agencies, with the exception of a few agencies which still report directly to the individual SWA. In addition to the quarterly contribution reports, employers who operate multiple establishments within a state complete a questionnaire, called the "Multiple Worksite Report," which provides detailed information on the location and industry of each of their establishments. QCEW employment and wage data are derived from microdata summaries of 9.5 million employer reports of employment and wages submitted by states to the BLS in 2015. These reports are based on place of employment rather than place of residence. UI and UCFE coverage is broad and has been basically comparable from state to state since 1978, when the 1976 amendments to the Federal Unemployment Tax Act became effective, expanding coverage to include most state and local government employees. In 2015, UI and UCFE programs covered workers in 139.5 million jobs. The estimated 134.4 million workers in these jobs (after adjustment for multiple jobholders) represented 96.5 percent of civilian wage and salary employment. Covered workers received $7.385 trillion in pay, representing 94.0 percent of the wage and salary component of personal income and 40.9 percent of the gross domestic product. Major exclusions from UI coverage include self-employed workers, most agricultural workers on small farms, all members of the Armed Forces, elected officials in most states, most employees of railroads, some domestic workers, most student workers at schools, and employees of certain small nonprofit organizations. State and federal UI laws change periodically. These changes may have an impact on the employment and wages reported by employers covered under the UI program. Coverage changes may affect the over-the-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 part-time 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-the-year 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-the-year changes. Percent changes are calculated using an adjusted version of the final 2015 quarterly data as the base data. The adjusted prior-year levels used to calculate the over-the-year percent change in employment and wages are not published. These adjusted prior-year levels do not match the unadjusted data maintained on the BLS Web site. Over-the-year change calculations based on data from the Web site, or from data published in prior BLS news releases, may differ substantially from the over-the-year changes presented in this news release. The adjusted data used to calculate the over-the-year change measures presented in this release account for most of the administrative changes--those occurring when employers update the industry, location, and ownership information of their establishments. The most common adjustments for administrative change are the result of updated information about the county location of individual establishments. Included in these adjustments are administrative changes involving the classification of establishments that were previously reported in the unknown or statewide county or unknown industry categories. Adjusted data account for improvements in reporting employment and wages for individual and multi-unit establishments. To accomplish this, adjustments were implemented to account for: administrative changes caused by multi-unit employers who start reporting for each individual establishment rather than as a single entity (first quarter of 2008); selected large administrative changes in employment and wages (second quarter of 2011); and state verified improvements in reporting of employment and wages (third quarter of 2014). These adjustments allow QCEW to include county employment and wage growth rates in this news release that would otherwise not meet publication standards. The adjusted data used to calculate the over-the-year change measures presented in any County Employment and Wages news release are valid for comparisons between the starting and ending points (a 12-month period) used in that particular release. Comparisons may not be valid for any time period other than the one featured in a release even if the changes were calculated using adjusted data. County definitions are assigned according to Federal Information Processing Standards Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104-106. Areas shown as counties include those designated as independent cities in some jurisdictions and, in Alaska, those designated as census areas where counties have not been created. County data also are presented for the New England states for comparative purposes even though townships are the more common designation used in New England (and New Jersey). The regions referred to in this release are defined as census regions. Additional statistics and other information Employment and Wages Annual Averages Online features comprehensive information by detailed industry on establishments, employment, and wages for the nation and all states. The 2015 edition of this publication, which was published in September 2016, contains selected data produced by Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the first quarter 2016 version of this news release. Tables and additional content from the 2015 edition of Employment and Wages Annual Averages Online are now available at www.bls.gov/cew/cewbultn15.htm. The 2016 edition of Employment and Wages Annual Averages Online will be available in September 2017. News releases on quarterly measures of gross job flows also are available from BED at www.bls.gov/bdm, (202) 691-6467, or 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: (800) 877-8339.
Table 1. Covered establishments, employment, and wages in the 345 largest counties, third quarter 2016 Employment Average weekly wage(2) Establishments, County(1) third quarter Percent Ranking Percent Ranking 2016 September change, by Third change, by (thousands) 2016 September percent quarter third percent (thousands) 2015-16(3) change 2016 quarter change 2015-16(3) United States(4)......... 9,800.8 142,940.5 1.7 - $1,027 5.4 - Jefferson, AL............ 18.3 340.8 0.6 273 1,010 5.1 211 Madison, AL.............. 9.4 192.8 3.0 69 1,122 6.4 100 Mobile, AL............... 10.0 169.2 1.0 238 887 6.4 100 Montgomery, AL........... 6.4 131.6 2.0 142 858 4.9 226 Shelby, AL............... 5.7 84.3 0.7 265 970 6.7 79 Tuscaloosa, AL........... 4.5 92.9 0.3 297 824 1.7 334 Anchorage Borough, AK.... 8.3 153.3 -2.2 340 1,102 1.8 332 Maricopa, AZ............. 95.0 1,885.6 3.4 46 996 7.1 56 Pima, AZ................. 18.7 360.4 1.4 203 866 6.4 100 Benton, AR............... 6.1 116.5 3.3 51 934 -2.0 342 Pulaski, AR.............. 14.4 248.8 1.2 226 922 6.0 130 Washington, AR........... 5.9 104.4 2.9 74 862 9.5 9 Alameda, CA.............. 61.6 757.1 2.3 123 1,394 8.7 18 Butte, CA................ 8.3 82.7 2.9 74 780 7.3 47 Contra Costa, CA......... 31.7 362.2 3.0 69 1,245 6.3 108 Fresno, CA............... 33.9 385.0 1.9 153 807 4.5 254 Kern, CA................. 18.2 324.8 -0.3 316 861 4.6 247 Los Angeles, CA.......... 472.3 4,357.4 1.6 183 1,132 5.8 152 Marin, CA................ 12.5 114.6 2.0 142 1,243 6.0 130 Merced, CA............... 6.4 82.1 2.4 112 802 7.2 52 Monterey, CA............. 13.5 204.0 0.7 265 891 7.7 33 Napa, CA................. 5.8 77.7 -0.8 328 1,016 6.2 117 Orange, CA............... 116.1 1,563.4 2.1 131 1,153 6.8 68 Placer, CA............... 12.5 158.4 4.9 6 1,040 5.4 187 Riverside, CA............ 60.4 688.2 3.5 44 844 7.9 27 Sacramento, CA........... 55.9 640.4 2.7 87 1,117 5.0 215 San Bernardino, CA....... 56.4 706.2 2.6 96 881 7.8 30 San Diego, CA............ 107.6 1,415.6 2.2 125 1,130 4.9 226 San Francisco, CA........ 60.1 709.5 3.1 58 1,892 8.6 20 San Joaquin, CA.......... 17.4 244.1 1.8 164 875 5.0 215 San Luis Obispo, CA...... 10.3 115.2 2.1 131 861 4.7 242 San Mateo, CA............ 27.8 395.3 2.7 87 2,098 8.9 16 Santa Barbara, CA........ 15.3 199.1 1.0 238 999 6.8 68 Santa Clara, CA.......... 70.9 1,052.5 2.7 87 2,260 9.0 15 Santa Cruz, CA........... 9.5 107.0 2.9 74 936 5.3 198 Solano, CA............... 11.1 136.9 2.0 142 1,054 7.2 52 Sonoma, CA............... 19.7 206.0 2.1 131 993 6.3 108 Stanislaus, CA........... 15.0 189.4 3.3 51 887 5.8 152 Tulare, CA............... 10.1 163.0 1.6 183 744 8.1 24 Ventura, CA.............. 26.3 316.7 0.6 273 1,019 6.5 90 Yolo, CA................. 6.6 103.2 1.4 203 1,114 7.7 33 Adams, CO................ 10.5 201.2 3.4 46 1,016 6.8 68 Arapahoe, CO............. 21.5 322.6 1.8 164 1,200 7.1 56 Boulder, CO.............. 14.8 178.2 2.7 87 1,216 4.6 247 Denver, CO............... 31.0 500.9 3.1 58 1,248 4.5 254 Douglas, CO.............. 11.6 117.1 2.5 105 1,118 7.0 59 El Paso, CO.............. 18.7 267.9 3.2 54 934 6.5 90 Jefferson, CO............ 20.6 234.4 1.8 164 1,046 5.4 187 Larimer, CO.............. 11.6 156.4 4.3 14 938 5.4 187 Weld, CO................. 7.0 100.8 -0.3 316 912 5.6 168 Fairfield, CT............ 35.2 424.3 0.2 300 1,479 5.0 215 Hartford, CT............. 27.6 507.2 0.2 300 1,196 4.9 226 New Haven, CT............ 23.8 363.4 0.6 273 1,063 4.0 286 New London, CT........... 7.4 123.2 0.5 283 1,016 7.6 39 New Castle, DE........... 19.7 286.0 0.5 283 1,131 5.3 198 Washington, DC........... 39.2 759.2 1.7 177 1,728 3.8 292 Alachua, FL.............. 7.0 128.7 3.1 58 880 9.5 9 Bay, FL.................. 5.5 77.4 0.9 250 754 5.0 215 Brevard, FL.............. 15.3 203.2 4.7 8 932 7.0 59 Broward, FL.............. 68.0 781.2 2.5 105 951 5.8 152 Collier, FL.............. 13.5 135.8 5.1 4 869 6.8 68 Duval, FL................ 28.6 490.3 3.4 46 967 6.4 100 Escambia, FL............. 8.1 131.4 3.8 29 809 6.3 108 Hillsborough, FL......... 40.9 666.3 3.7 34 993 8.4 21 Lake, FL................. 7.9 93.9 4.2 16 715 5.9 139 Lee, FL.................. 21.3 247.6 4.5 12 806 5.4 187 Leon, FL................. 8.6 147.9 3.1 58 841 5.9 139 Manatee, FL.............. 10.4 116.1 2.7 87 816 10.7 2 Marion, FL............... 8.1 100.0 3.8 29 719 9.3 12 Miami-Dade, FL........... 96.5 1,107.4 2.6 96 983 6.0 130 Okaloosa, FL............. 6.3 82.2 2.9 74 855 4.8 233 Orange, FL............... 40.6 797.1 3.2 54 904 6.0 130 Osceola, FL.............. 6.6 89.1 3.8 29 707 5.5 177 Palm Beach, FL........... 54.8 579.8 3.6 40 973 5.0 215 Pasco, FL................ 10.6 114.2 4.1 18 717 6.2 117 Pinellas, FL............. 32.3 418.6 2.6 96 900 6.3 108 Polk, FL................. 12.9 210.0 3.2 54 783 5.7 160 Sarasota, FL............. 15.5 162.6 2.9 74 838 7.9 27 Seminole, FL............. 14.6 184.7 4.8 7 852 6.0 130 Volusia, FL.............. 13.9 169.2 4.7 8 727 4.3 269 Bibb, GA................. 4.5 81.7 1.8 164 790 4.1 279 Chatham, GA.............. 8.7 148.5 1.0 238 873 6.5 90 Clayton, GA.............. 4.5 120.9 3.9 26 981 7.6 39 Cobb, GA................. 23.9 345.6 2.4 112 1,095 9.4 11 DeKalb, GA............... 19.8 295.7 2.0 142 1,045 7.2 52 Fulton, GA............... 47.2 830.7 4.0 24 1,339 5.4 187 Gwinnett, GA............. 27.1 345.0 3.0 69 980 3.5 304 Hall, GA................. 4.7 83.1 2.6 96 861 4.9 226 Muscogee, GA............. 5.0 92.7 0.1 305 814 6.5 90 Richmond, GA............. 4.8 104.4 1.2 226 887 7.5 41 Honolulu, HI............. 25.6 472.9 2.1 131 997 6.9 63 Ada, ID.................. 14.9 229.3 4.2 16 905 7.2 52 Champaign, IL............ 4.3 90.4 -0.9 329 894 2.8 320 Cook, IL................. 152.8 2,577.2 1.2 226 1,159 4.5 254 DuPage, IL............... 37.9 610.8 0.4 292 1,156 3.7 296 Kane, IL................. 13.7 209.9 0.2 300 930 7.0 59 Lake, IL................. 22.2 334.9 -0.5 321 1,279 -0.9 341 McHenry, IL.............. 8.7 98.9 1.3 216 863 6.7 79 McLean, IL............... 3.8 83.5 -2.0 338 985 10.2 6 Madison, IL.............. 6.0 97.9 -1.4 335 807 2.0 329 Peoria, IL............... 4.6 100.8 -0.7 325 975 7.5 41 St. Clair, IL............ 5.5 93.2 -0.7 325 821 4.6 247 Sangamon, IL............. 5.2 129.9 -0.4 318 1,011 0.6 337 Will, IL................. 16.1 231.4 1.5 195 919 7.7 33 Winnebago, IL............ 6.6 127.3 -1.2 333 863 6.9 63 Allen, IN................ 8.8 185.3 1.0 238 834 4.8 233 Elkhart, IN.............. 4.7 128.5 3.1 58 869 10.3 4 Hamilton, IN............. 9.2 138.5 2.5 105 963 5.2 205 Lake, IN................. 10.3 190.0 1.0 238 877 4.2 275 Marion, IN............... 23.9 598.0 1.9 153 1,036 7.0 59 St. Joseph, IN........... 5.7 124.7 1.8 164 834 4.8 233 Tippecanoe, IN........... 3.4 83.8 1.4 203 870 4.8 233 Vanderburgh, IN.......... 4.8 108.3 1.6 183 822 5.0 215 Johnson, IA.............. 4.1 83.9 2.1 131 970 5.8 152 Linn, IA................. 6.7 130.5 0.6 273 1,000 7.8 30 Polk, IA................. 17.1 296.9 2.9 74 1,040 5.9 139 Scott, IA................ 5.6 91.0 -0.4 318 843 5.5 177 Johnson, KS.............. 23.5 338.6 1.3 216 1,029 6.3 108 Sedgwick, KS............. 12.8 248.5 0.6 273 884 6.5 90 Shawnee, KS.............. 5.2 98.5 1.7 177 839 7.3 47 Wyandotte, KS............ 3.6 92.3 2.5 105 1,006 6.7 79 Boone, KY................ 4.4 84.4 2.4 112 909 10.3 4 Fayette, KY.............. 10.9 194.3 2.2 125 917 4.7 242 Jefferson, KY............ 25.4 465.3 3.0 69 1,007 7.8 30 Caddo, LA................ 7.2 113.5 -1.1 332 813 2.0 329 Calcasieu, LA............ 5.2 94.2 1.2 226 920 4.7 242 East Baton Rouge, LA..... 15.3 273.5 1.9 153 955 4.5 254 Jefferson, LA............ 13.6 193.1 0.4 292 922 5.5 177 Lafayette, LA............ 9.4 129.2 -5.6 343 892 -3.4 343 Orleans, LA.............. 12.3 192.7 1.8 164 964 4.8 233 St. Tammany, LA.......... 8.0 88.4 1.1 235 852 1.1 336 Cumberland, ME........... 13.7 180.4 1.4 203 937 9.3 12 Anne Arundel, MD......... 15.0 269.1 1.9 153 1,083 3.8 292 Baltimore, MD............ 21.2 374.6 0.7 265 1,032 5.8 152 Frederick, MD............ 6.4 100.5 0.9 250 968 6.3 108 Harford, MD.............. 5.8 92.4 1.6 183 1,008 8.4 21 Howard, MD............... 10.0 169.1 1.6 183 1,259 6.6 87 Montgomery, MD........... 32.6 466.2 0.8 257 1,353 5.9 139 Prince George's, MD...... 15.9 317.9 2.1 131 1,112 5.0 215 Baltimore City, MD....... 13.6 338.7 0.9 250 1,209 3.9 289 Barnstable, MA........... 9.4 101.8 0.5 283 856 5.7 160 Bristol, MA.............. 17.3 224.7 1.2 226 916 3.9 289 Essex, MA................ 24.4 325.5 1.3 216 1,069 5.8 152 Hampden, MA.............. 17.8 209.6 1.7 177 932 5.7 160 Middlesex, MA............ 53.9 889.4 1.6 183 1,555 9.8 8 Norfolk, MA.............. 24.9 349.8 1.8 164 1,144 4.1 279 Plymouth, MA............. 15.5 191.6 1.7 177 944 3.7 296 Suffolk, MA.............. 28.3 665.9 3.6 40 1,660 6.1 125 Worcester, MA............ 24.4 342.6 2.0 142 1,018 5.2 205 Genesee, MI.............. 6.9 134.3 0.9 250 854 4.4 262 Ingham, MI............... 6.0 151.3 2.7 87 955 4.9 226 Kalamazoo, MI............ 5.0 117.8 2.4 112 943 5.2 205 Kent, MI................. 14.3 390.8 3.0 69 908 4.2 275 Macomb, MI............... 17.7 322.7 1.4 203 1,022 7.7 33 Oakland, MI.............. 39.3 727.5 2.4 112 1,124 5.9 139 Ottawa, MI............... 5.6 124.5 1.3 216 865 6.3 108 Saginaw, MI.............. 4.0 85.3 0.2 300 832 7.5 41 Washtenaw, MI............ 8.1 209.4 3.6 40 1,109 5.5 177 Wayne, MI................ 30.6 715.1 1.8 164 1,120 5.6 168 Anoka, MN................ 6.7 121.0 0.7 265 1,027 6.2 117 Dakota, MN............... 9.4 188.0 1.8 164 991 5.2 205 Hennepin, MN............. 39.9 912.2 2.4 112 1,277 6.2 117 Olmsted, MN.............. 3.3 96.2 1.2 226 1,151 3.7 296 Ramsey, MN............... 12.7 331.1 0.8 257 1,162 8.9 16 St. Louis, MN............ 5.1 98.2 0.1 305 874 4.9 226 Stearns, MN.............. 4.2 85.7 0.6 273 884 7.3 47 Washington, MN........... 5.2 82.3 1.5 195 870 6.5 90 Harrison, MS............. 4.5 85.5 1.9 153 713 2.1 327 Hinds, MS................ 5.9 120.7 0.3 297 873 5.6 168 Boone, MO................ 4.8 93.5 1.5 195 833 4.8 233 Clay, MO................. 5.5 104.8 4.3 14 899 5.3 198 Greene, MO............... 8.5 164.7 1.8 164 802 5.9 139 Jackson, MO.............. 20.9 365.9 2.8 83 1,024 3.2 312 St. Charles, MO.......... 9.0 145.7 2.7 87 822 6.1 125 St. Louis, MO............ 36.3 599.8 1.0 238 1,057 5.3 198 St. Louis City, MO....... 13.2 228.7 1.0 238 1,104 5.7 160 Yellowstone, MT.......... 6.4 82.2 0.8 257 879 3.9 289 Douglas, NE.............. 19.3 338.7 1.6 183 983 5.4 187 Lancaster, NE............ 10.3 170.0 1.4 203 845 6.0 130 Clark, NV................ 56.4 947.0 3.7 34 947 12.2 1 Washoe, NV............... 15.0 214.8 5.0 5 932 6.2 117 Hillsborough, NH......... 12.3 200.4 1.4 203 1,137 10.4 3 Merrimack, NH............ 5.1 77.2 1.9 153 954 7.3 47 Rockingham, NH........... 11.0 149.5 2.1 131 989 5.5 177 Atlantic, NJ............. 6.5 128.6 1.0 238 843 2.9 318 Bergen, NJ............... 32.8 446.6 0.5 283 1,180 3.8 292 Burlington, NJ........... 10.9 203.3 2.6 96 1,044 5.0 215 Camden, NJ............... 11.9 203.0 2.2 125 988 5.0 215 Essex, NJ................ 20.4 338.0 1.8 164 1,251 6.1 125 Gloucester, NJ........... 6.3 106.8 3.5 44 875 4.5 254 Hudson, NJ............... 14.7 255.6 3.7 34 1,355 5.9 139 Mercer, NJ............... 11.1 245.8 1.8 164 1,335 7.1 56 Middlesex, NJ............ 22.0 418.1 2.8 83 1,191 4.1 279 Monmouth, NJ............. 20.1 259.4 1.5 195 975 4.5 254 Morris, NJ............... 16.9 285.8 0.0 308 1,478 6.8 68 Ocean, NJ................ 13.0 165.9 1.6 183 814 6.3 108 Passaic, NJ.............. 12.3 166.4 1.3 216 996 5.8 152 Somerset, NJ............. 10.0 184.5 1.9 153 1,482 2.4 325 Union, NJ................ 14.2 220.0 1.3 216 1,234 4.1 279 Bernalillo, NM........... 18.3 327.2 2.0 142 890 5.6 168 Albany, NY............... 10.4 233.5 1.6 183 1,065 2.7 322 Bronx, NY................ 18.8 299.8 0.5 283 992 5.6 168 Broome, NY............... 4.6 87.4 0.9 250 808 7.4 44 Dutchess, NY............. 8.5 111.5 0.7 265 979 5.4 187 Erie, NY................. 24.9 471.3 0.9 250 907 6.0 130 Kings, NY................ 62.0 688.1 4.1 18 866 4.1 279 Monroe, NY............... 19.1 384.9 0.6 273 974 4.6 247 Nassau, NY............... 54.4 627.2 2.1 131 1,092 2.8 320 New York, NY............. 130.1 2,411.9 1.6 183 1,879 2.6 323 Oneida, NY............... 5.4 105.0 0.8 257 794 6.9 63 Onondaga, NY............. 13.1 246.1 0.7 265 938 2.5 324 Orange, NY............... 10.5 141.6 2.2 125 860 6.2 117 Queens, NY............... 52.8 651.9 1.9 153 974 4.4 262 Richmond, NY............. 9.9 115.3 2.6 96 918 4.6 247 Rockland, NY............. 10.8 122.9 2.1 131 987 -14.9 344 Saratoga, NY............. 6.0 84.8 0.5 283 925 7.4 44 Suffolk, NY.............. 53.2 659.4 0.8 257 1,126 6.7 79 Westchester, NY.......... 36.8 424.3 1.0 238 1,232 0.5 338 Buncombe, NC............. 9.0 128.5 3.7 34 788 3.7 296 Catawba, NC.............. 4.4 86.1 4.1 18 783 5.5 177 Cumberland, NC........... 6.2 118.8 0.7 265 813 6.7 79 Durham, NC............... 8.1 195.3 1.6 183 1,265 3.3 310 Forsyth, NC.............. 9.2 182.6 0.6 273 912 3.4 307 Guilford, NC............. 14.2 279.0 0.6 273 883 3.0 316 Mecklenburg, NC.......... 37.1 669.0 4.4 13 1,175 5.4 187 New Hanover, NC.......... 7.9 110.8 2.7 87 820 6.2 117 Wake, NC................. 33.5 532.8 3.9 26 1,045 6.0 130 Cass, ND................. 7.1 118.6 1.4 203 950 4.3 269 Butler, OH............... 7.6 151.6 2.5 105 905 6.5 90 Cuyahoga, OH............. 35.6 720.4 0.8 257 1,025 4.2 275 Delaware, OH............. 5.1 86.0 2.9 74 979 6.3 108 Franklin, OH............. 31.5 741.4 2.8 83 1,040 6.4 100 Hamilton, OH............. 23.7 513.2 1.5 195 1,095 4.3 269 Lake, OH................. 6.3 94.4 -0.5 321 834 4.8 233 Lorain, OH............... 6.2 97.2 0.9 250 811 4.5 254 Lucas, OH................ 10.1 210.1 1.0 238 901 6.9 63 Mahoning, OH............. 5.9 98.7 0.0 308 734 4.3 269 Montgomery, OH........... 11.9 253.6 1.3 216 883 5.6 168 Stark, OH................ 8.6 158.2 -0.1 312 770 4.2 275 Summit, OH............... 14.2 267.8 1.2 226 909 4.0 286 Warren, OH............... 4.8 91.2 1.5 195 948 6.9 63 Cleveland, OK............ 5.6 80.7 0.1 305 763 6.7 79 Oklahoma, OK............. 27.7 446.8 -1.4 335 967 3.4 307 Tulsa, OK................ 22.0 348.8 -0.6 324 934 3.5 304 Clackamas, OR............ 14.5 159.1 2.4 112 971 5.1 211 Jackson, OR.............. 7.2 87.3 2.6 96 798 4.7 242 Lane, OR................. 11.9 153.0 3.1 58 813 5.3 198 Marion, OR............... 10.4 153.8 2.3 123 836 6.1 125 Multnomah, OR............ 33.9 493.4 2.5 105 1,073 6.6 87 Washington, OR........... 18.9 283.8 3.1 58 1,327 3.2 312 Allegheny, PA............ 35.8 690.8 0.5 283 1,098 4.6 247 Berks, PA................ 9.0 171.8 0.4 292 947 9.2 14 Bucks, PA................ 20.0 261.4 2.0 142 960 5.5 177 Butler, PA............... 5.0 85.2 -0.1 312 947 3.0 316 Chester, PA.............. 15.5 250.2 1.7 177 1,228 1.8 332 Cumberland, PA........... 6.4 133.0 1.1 235 929 5.6 168 Dauphin, PA.............. 7.6 180.2 0.6 273 1,036 7.7 33 Delaware, PA............. 14.1 220.4 1.4 203 1,065 5.2 205 Erie, PA................. 7.0 124.0 -1.6 337 791 1.9 331 Lackawanna, PA........... 5.8 97.9 0.8 257 793 5.9 139 Lancaster, PA............ 13.4 236.4 2.4 112 862 5.6 168 Lehigh, PA............... 8.8 187.9 1.3 216 1,004 6.8 68 Luzerne, PA.............. 7.5 144.5 1.2 226 825 5.9 139 Montgomery, PA........... 27.6 485.3 1.4 203 1,234 6.4 100 Northampton, PA.......... 6.8 113.1 3.6 40 887 4.7 242 Philadelphia, PA......... 35.0 671.5 3.2 54 1,226 5.5 177 Washington, PA........... 5.5 85.8 -2.2 340 973 3.3 310 Westmoreland, PA......... 9.3 133.4 -1.0 331 827 4.9 226 York, PA................. 9.1 177.6 0.7 265 900 5.9 139 Providence, RI........... 17.6 285.6 0.5 283 1,046 8.7 18 Charleston, SC........... 14.6 243.7 3.7 34 916 4.4 262 Greenville, SC........... 13.6 262.2 1.9 153 898 4.3 269 Horry, SC................ 8.5 124.7 3.1 58 632 5.5 177 Lexington, SC............ 6.4 115.7 2.0 142 791 7.3 47 Richland, SC............. 9.9 219.0 2.0 142 885 6.0 130 Spartanburg, SC.......... 6.1 133.0 3.7 34 861 5.9 139 York, SC................. 5.3 89.8 6.0 1 830 8.2 23 Minnehaha, SD............ 7.1 125.0 1.5 195 907 6.8 68 Davidson, TN............. 21.5 479.1 4.6 11 1,058 2.3 326 Hamilton, TN............. 9.3 198.4 1.9 153 897 3.6 302 Knox, TN................. 11.9 237.4 2.1 131 887 6.2 117 Rutherford, TN........... 5.3 119.3 3.8 29 917 7.9 27 Shelby, TN............... 20.1 491.9 1.2 226 1,045 6.7 79 Williamson, TN........... 8.3 124.7 5.8 2 1,154 5.7 160 Bell, TX................. 5.3 116.3 0.0 308 868 5.7 160 Bexar, TX................ 39.9 846.6 2.4 112 914 4.6 247 Brazoria, TX............. 5.6 106.1 1.9 153 1,045 5.3 198 Brazos, TX............... 4.4 101.3 0.8 257 772 5.8 152 Cameron, TX.............. 6.5 138.4 2.2 125 636 4.3 269 Collin, TX............... 23.5 381.5 3.8 29 1,191 5.9 139 Dallas, TX............... 74.9 1,662.8 3.1 58 1,239 6.8 68 Denton, TX............... 14.1 228.8 3.4 46 954 6.8 68 El Paso, TX.............. 14.7 299.3 2.4 112 728 4.4 262 Fort Bend, TX............ 12.5 174.2 2.1 131 951 0.3 339 Galveston, TX............ 6.1 108.0 4.1 18 896 5.4 187 Gregg, TX................ 4.2 74.0 -3.4 342 858 1.2 335 Harris, TX............... 112.9 2,262.3 -0.9 329 1,267 2.1 327 Hidalgo, TX.............. 12.2 248.5 1.8 164 654 4.8 233 Jefferson, TX............ 5.8 122.3 -0.2 315 1,061 5.7 160 Lubbock, TX.............. 7.5 137.0 1.4 203 811 4.0 286 McLennan, TX............. 5.2 111.4 2.6 96 850 7.7 33 Midland, TX.............. 5.4 83.0 -5.8 344 1,176 -0.3 340 Montgomery, TX........... 10.8 168.4 1.0 238 1,007 4.1 279 Nueces, TX............... 8.3 161.6 -0.5 321 893 4.1 279 Potter, TX............... 4.0 78.9 0.0 308 831 3.1 315 Smith, TX................ 6.1 102.6 1.3 216 849 5.3 198 Tarrant, TX.............. 41.9 860.4 2.4 112 1,029 6.6 87 Travis, TX............... 39.0 710.0 2.9 74 1,174 5.1 211 Webb, TX................. 5.3 99.1 2.2 125 680 2.9 318 Williamson, TX........... 10.1 158.7 4.1 18 1,009 6.8 68 Davis, UT................ 8.2 123.2 4.1 18 831 5.7 160 Salt Lake, UT............ 43.6 676.2 3.9 26 993 6.5 90 Utah, UT................. 15.2 223.1 5.3 3 825 7.4 44 Weber, UT................ 5.9 103.0 2.9 74 784 5.9 139 Chittenden, VT........... 6.7 102.1 0.2 300 996 6.8 68 Arlington, VA............ 9.5 173.0 1.3 216 1,648 3.8 292 Chesterfield, VA......... 8.9 132.4 -0.1 312 877 5.4 187 Fairfax, VA.............. 37.6 598.1 1.7 177 1,546 5.6 168 Henrico, VA.............. 11.6 190.0 1.0 238 992 5.0 215 Loudoun, VA.............. 12.1 160.3 3.1 58 1,155 3.5 304 Prince William, VA....... 9.3 125.5 1.6 183 913 6.5 90 Alexandria City, VA...... 6.6 94.3 -0.7 325 1,447 5.0 215 Chesapeake City, VA...... 6.0 97.2 -0.4 318 812 6.4 100 Newport News City, VA.... 3.9 96.0 -2.1 339 995 3.6 302 Norfolk City, VA......... 5.9 140.9 0.3 297 1,030 3.4 307 Richmond City, VA........ 7.8 153.7 1.4 203 1,124 3.2 312 Virginia Beach City, VA.. 12.2 176.8 1.1 235 792 3.7 296 Benton, WA............... 5.7 86.9 2.5 105 1,042 8.1 24 Clark, WA................ 14.3 150.6 2.8 83 971 6.1 125 King, WA................. 85.7 1,331.3 3.3 51 1,582 8.1 24 Kitsap, WA............... 6.6 85.9 0.4 292 981 6.4 100 Pierce, WA............... 21.7 299.9 4.0 24 951 5.5 177 Snohomish, WA............ 20.6 284.9 2.0 142 1,108 5.4 187 Spokane, WA.............. 15.6 217.6 3.4 46 883 4.4 262 Thurston, WA............. 8.1 112.0 4.7 8 949 3.7 296 Whatcom, WA.............. 7.2 88.3 3.1 58 844 5.1 211 Yakima, WA............... 7.7 124.0 2.7 87 712 4.4 262 Kanawha, WV.............. 5.9 101.5 -1.3 334 890 6.5 90 Brown, WI................ 6.7 154.6 1.5 195 904 6.7 79 Dane, WI................. 15.0 330.7 2.6 96 1,032 10.1 7 Milwaukee, WI............ 25.6 487.0 0.5 283 970 4.5 254 Outagamie, WI............ 5.2 107.0 1.4 203 875 4.8 233 Waukesha, WI............. 12.8 239.0 0.4 292 1,006 5.2 205 Winnebago, WI............ 3.7 93.1 2.0 142 924 4.4 262 San Juan, PR............. 10.8 245.0 -1.4 (5) 634 2.8 (5) (1) Includes areas not officially designated as counties. See Technical Note. (2) Average weekly wages were calculated using unrounded data. (3) Percent changes were computed from employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. (4) Totals for the United States do not include data for Puerto Rico or the Virgin Islands. (5) This county was not included in the U.S. rankings. Note: Data are preliminary. Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. These 344 U.S. counties comprise 72.5 percent of the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties, third quarter 2016 Employment Average weekly wage(1) Establishments, third quarter County by NAICS supersector 2016 Percent Percent (thousands) September change, Third change, 2016 September quarter third (thousands) 2015-16(2) 2016 quarter 2015-16(2) United States(3) ............................ 9,800.8 142,940.5 1.7 $1,027 5.4 Private industry........................... 9,501.7 121,392.9 1.8 1,019 5.7 Natural resources and mining............. 137.6 1,963.4 -5.7 1,020 -0.8 Construction............................. 780.3 6,898.0 3.4 1,143 5.5 Manufacturing............................ 345.2 12,317.5 -0.6 1,242 6.2 Trade, transportation, and utilities..... 1,922.9 26,939.5 1.1 867 5.6 Information.............................. 157.8 2,792.9 1.0 1,927 8.4 Financial activities..................... 859.7 7,973.7 1.7 1,530 6.0 Professional and business services....... 1,766.7 20,200.9 2.2 1,308 5.3 Education and health services............ 1,590.0 21,741.6 2.8 958 6.0 Leisure and hospitality.................. 822.8 15,811.2 2.4 441 6.8 Other services........................... 835.9 4,390.8 1.7 705 6.0 Government................................. 299.1 21,547.5 1.2 1,077 4.6 Los Angeles, CA.............................. 472.3 4,357.4 1.6 1,132 5.8 Private industry........................... 466.1 3,793.2 1.7 1,096 6.4 Natural resources and mining............. 0.5 8.7 0.0 1,406 4.8 Construction............................. 13.9 134.1 3.9 1,192 5.5 Manufacturing............................ 12.4 353.8 -3.2 1,287 6.7 Trade, transportation, and utilities..... 53.7 811.3 0.5 936 7.6 Information.............................. 9.6 224.5 0.3 1,981 9.1 Financial activities..................... 25.3 217.1 0.4 1,789 4.5 Professional and business services....... 47.6 603.8 2.0 1,338 4.4 Education and health services............ 216.2 749.5 2.1 898 9.5 Leisure and hospitality.................. 32.1 508.7 2.8 633 6.7 Other services........................... 27.0 147.2 0.3 743 8.6 Government................................. 6.2 564.2 1.3 1,383 2.4 Cook, IL..................................... 152.8 2,577.2 1.2 1,159 4.5 Private industry........................... 151.5 2,279.3 1.2 1,166 4.9 Natural resources and mining............. 0.1 1.2 5.7 1,194 -1.6 Construction............................. 12.2 75.7 2.5 1,451 1.8 Manufacturing............................ 6.3 184.8 -1.3 1,250 7.3 Trade, transportation, and utilities..... 29.8 472.5 0.5 946 4.8 Information.............................. 2.7 52.6 -0.9 1,752 7.4 Financial activities..................... 15.1 193.0 0.9 2,013 4.9 Professional and business services....... 32.3 476.5 0.6 1,462 3.0 Education and health services............ 16.3 439.3 2.2 1,016 8.1 Leisure and hospitality.................. 14.1 282.9 3.6 547 7.5 Other services........................... 17.3 95.9 0.3 919 4.9 Government................................. 1.3 297.9 0.9 1,107 2.2 New York, NY................................. 130.1 2,411.9 1.6 1,879 2.6 Private industry........................... 129.2 2,148.9 1.7 1,946 2.7 Natural resources and mining............. 0.0 0.2 1.2 1,896 1.3 Construction............................. 2.2 41.2 3.6 1,876 4.7 Manufacturing............................ 2.1 26.5 -3.1 1,343 -0.3 Trade, transportation, and utilities..... 19.5 253.0 -2.3 1,352 5.9 Information.............................. 4.9 155.6 1.8 2,613 0.5 Financial activities..................... 19.2 368.6 0.2 3,373 2.6 Professional and business services....... 27.5 556.9 2.6 2,178 2.6 Education and health services............ 9.8 337.0 2.8 1,341 2.4 Leisure and hospitality.................. 13.7 293.6 1.8 896 5.5 Other services........................... 20.3 101.6 0.9 1,167 6.1 Government................................. 0.8 263.0 0.0 1,319 0.1 Harris, TX................................... 112.9 2,262.3 -0.9 1,267 2.1 Private industry........................... 112.3 1,990.6 -1.4 1,281 2.2 Natural resources and mining............. 1.8 73.7 -15.6 3,173 5.2 Construction............................. 7.2 160.8 -1.8 1,354 4.2 Manufacturing............................ 4.8 167.9 -9.5 1,576 6.5 Trade, transportation, and utilities..... 25.0 462.7 -1.2 1,137 5.1 Information.............................. 1.2 27.1 0.7 1,437 2.3 Financial activities..................... 11.7 123.8 1.9 1,591 2.3 Professional and business services....... 23.0 386.5 -2.3 1,569 1.9 Education and health services............ 15.6 291.7 3.7 1,041 3.1 Leisure and hospitality.................. 9.7 229.7 3.2 464 5.7 Other services........................... 11.7 65.5 0.1 797 0.6 Government................................. 0.6 271.7 2.6 1,166 1.7 Maricopa, AZ................................. 95.0 1,885.6 3.4 996 7.1 Private industry........................... 94.2 1,673.1 3.7 985 6.7 Natural resources and mining............. 0.4 7.5 0.9 936 1.4 Construction............................. 6.8 103.6 6.0 1,048 8.4 Manufacturing............................ 3.1 115.3 -0.8 1,405 7.6 Trade, transportation, and utilities..... 18.5 366.1 1.8 900 5.4 Information.............................. 1.5 34.0 0.5 1,498 21.2 Financial activities..................... 10.7 168.9 5.9 1,281 7.5 Professional and business services....... 20.6 325.4 4.0 1,055 5.3 Education and health services............ 10.6 285.1 3.6 1,011 6.9 Leisure and hospitality.................. 7.4 205.2 3.5 473 8.7 Other services........................... 6.0 49.8 1.1 715 7.2 Government................................. 0.7 212.6 1.5 1,086 9.6 Dallas, TX................................... 74.9 1,662.8 3.1 1,239 6.8 Private industry........................... 74.4 1,489.3 3.3 1,245 7.0 Natural resources and mining............. 0.6 8.6 -8.3 3,515 -0.2 Construction............................. 4.4 86.0 5.2 1,236 8.1 Manufacturing............................ 2.7 108.9 0.1 1,472 14.1 Trade, transportation, and utilities..... 16.0 338.5 3.2 1,149 9.0 Information.............................. 1.3 49.4 2.8 1,813 3.8 Financial activities..................... 9.2 159.3 3.7 1,659 5.9 Professional and business services....... 16.8 339.2 3.4 1,426 6.7 Education and health services............ 9.3 196.0 4.2 1,094 3.8 Leisure and hospitality.................. 6.6 160.4 3.9 509 7.4 Other services........................... 7.0 42.2 1.2 821 8.2 Government................................. 0.6 173.5 1.4 1,182 5.0 Orange, CA................................... 116.1 1,563.4 2.1 1,153 6.8 Private industry........................... 114.6 1,418.5 2.0 1,139 6.9 Natural resources and mining............. 0.2 2.9 -2.6 918 10.6 Construction............................. 6.7 97.2 3.5 1,317 7.5 Manufacturing............................ 4.9 155.9 -0.5 1,398 6.2 Trade, transportation, and utilities..... 16.9 255.8 -0.4 1,021 8.0 Information.............................. 1.3 25.6 2.5 1,922 12.7 Financial activities..................... 11.0 116.3 0.5 1,778 6.1 Professional and business services....... 20.5 295.3 2.3 1,364 5.7 Education and health services............ 30.1 200.2 2.8 977 8.8 Leisure and hospitality.................. 8.4 212.7 2.7 515 10.0 Other services........................... 6.9 45.9 2.5 723 8.4 Government................................. 1.5 144.9 3.1 1,301 4.8 San Diego, CA................................ 107.6 1,415.6 2.2 1,130 4.9 Private industry........................... 105.7 1,185.5 2.0 1,084 4.8 Natural resources and mining............. 0.7 9.5 -2.4 723 14.0 Construction............................. 6.7 76.6 5.4 1,213 8.4 Manufacturing............................ 3.2 107.0 -0.6 1,578 9.8 Trade, transportation, and utilities..... 14.2 217.4 -0.5 862 4.9 Information.............................. 1.2 23.3 -0.8 1,930 8.7 Financial activities..................... 9.7 72.1 2.2 1,438 7.1 Professional and business services....... 18.1 232.1 1.0 1,526 -0.3 Education and health services............ 29.7 192.9 2.5 978 8.7 Leisure and hospitality.................. 8.0 194.4 3.7 506 4.8 Other services........................... 7.4 51.3 0.7 632 8.8 Government................................. 1.9 230.1 3.1 1,378 5.1 King, WA..................................... 85.7 1,331.3 3.3 1,582 8.1 Private industry........................... 85.2 1,165.9 3.4 1,615 8.6 Natural resources and mining............. 0.4 3.2 4.0 1,208 3.0 Construction............................. 6.4 69.2 7.1 1,365 8.5 Manufacturing............................ 2.5 104.1 -3.7 1,615 3.1 Trade, transportation, and utilities..... 14.5 253.9 4.7 1,392 17.8 Information.............................. 2.2 98.1 8.1 4,960 3.1 Financial activities..................... 6.5 68.1 3.1 1,655 6.2 Professional and business services....... 17.2 220.9 2.1 1,668 8.3 Education and health services............ 19.4 166.9 4.6 1,051 8.5 Leisure and hospitality.................. 7.1 137.5 3.3 588 8.1 Other services........................... 9.0 43.9 2.7 907 11.4 Government................................. 0.5 165.4 2.1 1,348 3.9 Miami-Dade, FL............................... 96.5 1,107.4 2.6 983 6.0 Private industry........................... 96.2 969.7 2.7 957 5.3 Natural resources and mining............. 0.5 7.6 9.4 643 13.0 Construction............................. 6.2 44.3 9.6 969 4.1 Manufacturing............................ 2.9 40.4 2.0 977 14.1 Trade, transportation, and utilities..... 26.3 276.9 0.4 896 5.9 Information.............................. 1.5 17.8 0.6 1,781 22.1 Financial activities..................... 10.4 74.0 0.7 1,484 4.4 Professional and business services....... 21.2 154.8 3.7 1,114 3.2 Education and health services............ 10.3 174.3 3.2 979 2.1 Leisure and hospitality.................. 7.2 138.4 4.1 592 7.2 Other services........................... 8.2 39.8 2.7 628 6.1 Government................................. 0.3 137.8 1.9 1,172 10.9 (1) Average weekly wages were calculated using unrounded data. (2) Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note. (3) Totals for the United States do not include data for Puerto Rico or the Virgin Islands. Note: Data are preliminary. Counties selected are based on 2015 annual average employment. Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs.
Table 3. Covered establishments, employment, and wages by state, third quarter 2016 Employment Average weekly wage(1) Establishments, third quarter State 2016 Percent Percent (thousands) September change, Third change, 2016 September quarter third (thousands) 2015-16 2016 quarter 2015-16 United States(2)........... 9,800.8 142,940.5 1.7 $1,027 5.4 Alabama.................... 122.7 1,923.8 1.5 870 4.9 Alaska..................... 22.3 337.4 -2.6 1,055 1.2 Arizona.................... 154.6 2,695.5 3.1 950 6.9 Arkansas................... 89.1 1,205.4 1.0 794 5.2 California................. 1,493.8 16,871.1 2.4 1,210 6.7 Colorado................... 193.5 2,576.5 2.6 1,062 5.6 Connecticut................ 117.5 1,674.2 0.3 1,204 5.0 Delaware................... 31.7 440.7 0.8 1,022 5.6 District of Columbia....... 39.2 759.2 1.7 1,728 3.8 Florida.................... 664.8 8,320.2 3.7 905 6.2 Georgia.................... 302.2 4,290.4 2.9 969 5.9 Hawaii..................... 40.5 648.4 1.8 956 6.7 Idaho...................... 58.9 703.7 3.5 782 6.3 Illinois................... 405.1 5,933.6 0.6 1,062 4.4 Indiana.................... 162.2 3,025.9 1.8 866 5.9 Iowa....................... 101.6 1,548.6 0.8 873 6.2 Kansas..................... 90.6 1,377.2 0.5 857 5.9 Kentucky................... 123.6 1,880.2 1.5 857 6.5 Louisiana.................. 129.0 1,908.8 -0.9 883 2.9 Maine...................... 53.3 616.2 0.9 825 5.9 Maryland................... 168.7 2,648.1 1.4 1,124 5.3 Massachusetts.............. 246.1 3,522.9 2.0 1,277 6.8 Michigan................... 242.3 4,292.2 2.1 976 5.9 Minnesota.................. 162.7 2,849.5 1.6 1,053 6.4 Mississippi................ 73.7 1,126.9 0.7 739 4.7 Missouri................... 193.7 2,782.1 1.6 888 5.0 Montana.................... 46.2 464.5 1.5 792 4.3 Nebraska................... 73.2 973.9 0.9 857 5.5 Nevada..................... 82.6 1,300.7 3.8 949 10.1 New Hampshire.............. 52.0 655.0 1.8 1,027 7.9 New Jersey................. 267.7 4,000.0 1.8 1,173 5.0 New Mexico................. 58.4 811.5 0.2 830 4.0 New York................... 646.8 9,216.6 1.6 1,222 3.5 North Carolina............. 268.4 4,290.3 2.3 909 5.3 North Dakota............... 32.1 423.2 -3.4 964 0.7 Ohio....................... 293.9 5,347.3 1.1 924 5.4 Oklahoma................... 109.4 1,578.7 -1.3 854 3.5 Oregon..................... 148.4 1,866.5 2.6 970 5.2 Pennsylvania............... 356.6 5,776.7 1.0 1,013 5.4 Rhode Island............... 37.0 481.1 0.8 990 7.6 South Carolina............. 125.0 2,008.6 2.5 832 5.6 South Dakota............... 33.0 424.2 1.1 809 7.0 Tennessee.................. 154.0 2,918.8 2.5 912 5.4 Texas...................... 657.1 11,830.7 1.3 1,042 4.3 Utah....................... 96.8 1,407.4 3.8 881 6.3 Vermont.................... 25.1 309.9 0.5 880 6.2 Virginia................... 267.0 3,801.0 1.0 1,063 5.0 Washington................. 238.5 3,278.9 3.0 1,188 6.9 West Virginia.............. 50.6 691.5 -1.6 816 3.9 Wisconsin.................. 171.2 2,850.1 1.0 885 6.2 Wyoming.................... 26.3 274.8 -4.7 865 0.0 Puerto Rico................ 46.0 888.2 -0.4 524 2.3 Virgin Islands............. 3.4 37.4 1.4 778 5.9 (1) Average weekly wages were calculated using unrounded data. (2) Totals for the United States do not include data for Puerto Rico or the Virgin Islands. Note: Data are preliminary. Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs.