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For release 10:00 a.m. (ET), Wednesday, May 19, 2021 USDL-21-0906 Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew Media Contact: (202) 691-5902 * PressOffice@bls.gov COUNTY EMPLOYMENT AND WAGES – FOURTH QUARTER 2020 From December 2019 to December 2020, employment decreased in 352 of the 357 largest U.S. counties, the U.S. Bureau of Labor Statistics reported today. In December 2020, national employment (as measured by the QCEW program) decreased to 140.9 million, a 6.1-percent decrease over the year. Maui + Kalawao, HI, had the largest over-the-year decrease in employment with a loss of 22.8 percent. Employment data in this release are presented for December 2020, and average weekly wage data are presented for fourth quarter 2020. Employment was impacted by the COVID-19 pandemic and efforts to contain it. Among the 357 largest counties, 356 had over-the-year increases in average weekly wages. In the fourth quarter of 2020, average weekly wages for the nation increased to $1,339, a 13.0-percent increase over the year. San Francisco, CA, had the largest fourth quarter over-the-year wage gain at 44.3 percent. (See table 1.) Nationally, across most industries, increases in average weekly wages reflect substantial employment declines combined with wage increases. The lowest paying industry, leisure and hospitality, had the largest employment loss, which results in higher average weekly wages for the industry and the nation. Large County Employment in December 2020 Maui + Kalawao, HI, had the largest over-the-year percentage decrease in employment (-22.8 percent). Within Maui + Kalawao, the largest employment decrease occurred in leisure and hospitality, which lost 10,959 jobs over the year (-42.1 percent). Utah, UT, experienced the largest over-the-year percentage increase in employment with a gain of 3.8 percent. Within Utah, professional and business services had the largest employment increase with a gain of 3,769 jobs (+9.8 percent). Large County Average Weekly Wage in Fourth Quarter 2020 San Francisco, CA, had the largest over-the-year percentage increase in average weekly wages (+44.3 percent). Within San Francisco, an average weekly wage gain of $5,478 (+569.4 percent) in leisure and hospitality made the largest contribution to the county’s increase in average weekly wages. Ector, TX, had the only over-the-year percentage decrease in average weekly wages with a loss of 7.5 percent. Within Ector, natural resources and mining had the largest impact, with an average weekly wage decrease of $141 (-7.3 percent) over the year. Ten Largest Counties All of the 10 largest counties had over-the-year percentage decreases in employment. In December 2020, New York, NY, had the largest over-the-year employment percentage loss (-15.6 percent). Within New York, leisure and hospitality had the largest employment decrease with a loss of 172,534 jobs (-54.4 percent). (See table 2.) All of the 10 largest counties had over-the-year percentage increases in average weekly wages. In fourth quarter 2020, New York, NY, experienced the largest over-the-year percentage gain in average weekly wages (+20.9 percent). Within New York, professional and business services had the largest impact, with an average weekly wage increase of $619 (+21.0 percent) over the year. For More Information The tables included in this release contain data for the nation and for the 357 U.S. counties with annual average employment levels of 75,000 or more in 2019. December 2020 employment and fourth quarter 2020 average weekly wages for all states are provided in table 3 of this release. QCEW response rate tables are available at www.bls.gov/cew/response-rates/. The most current news release on quarterly measures of gross job flows is available from QCEW Business Employment Dynamics at www.bls.gov/news.release/pdf/cewbd.pdf. Several BLS regional offices issue QCEW news releases targeted to local data users. Links to these releases are available at www.bls.gov/cew/regional-resources.htm. QCEW data are available in the Census Business Builder suite of web tools assisting business owners and regional analysts in data-driven decision making at www.census.gov/data/data-tools/cbb.html. The QCEW news release schedule is available at www.bls.gov/cew/release-calendar.htm. ____________ The County Employment and Wages full data update for fourth quarter 2020 is scheduled to be released on Wednesday, June 2, 2021, at 10:00 a.m. (ET). The County Employment and Wages news release for first quarter 2021 is scheduled to be released on Wednesday, August 18, 2021, at 10:00 a.m. (ET). __________________________________________________________________________________________________________ QCEW Imputation Issue Caused by Pandemic-Related Challenges In the spring of 2020, BLS modified its imputation process for QCEW to be more responsive to current economic conditions. While continuing work to improve this process, BLS made an unintended data processing error. This error affected data for the second, third, and fourth quarters of 2020. BLS has analyzed this issue and has determined that the impact on QCEW employment was negligible at the statewide level. In smaller areas and industries, revisions may be larger than usual. Wage data were not affected. Following the usual QCEW practice, these data will be revised and corrected with the full data update on September 1, 2021. For more information on QCEW imputation methodology, see www.bls.gov/cew/additional-resources/imputation-methodology.htm. __________________________________________________________________________________________________________
Technical Note These data are the product of a federal-state cooperative program, the Quarterly Census of Employment and Wages program, also known as the ES-202 program. The data are derived from summaries of employment and total pay of workers covered by state and federal unemployment insurance (UI) legislation and provided by State Workforce Agencies (SWAs). The summaries are a result of the administration of state unemployment insurance programs that require most employers to pay quarterly taxes based on the employment and wages of workers covered by UI. QCEW data in this release are based on the 2017 North American Industry Classification System (NAICS). Data for 2020 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, PR, 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 358 counties presented in this release were derived using 2019 preliminary annual averages of employment. For 2020 data, three counties have been added to the publication tables: Baldwin, AL; Iredell, NC; and Gregg, TX. One county has been dropped from the publication tables: Bay, FL. These counties will be included or excluded, respectively, in all 2020 quarterly releases. 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: QCEW, Business Employment Dynamics (BED), and Current Employment Statistics (CES). Each of these measures makes use of the quarterly UI employment reports in producing data; however, each measure has a somewhat different universe coverage, estimation procedure, and publication product. Differences in coverage and estimation methods can result in somewhat different measures of employment change over time. It is important to understand program differences and the intended uses of the program products. (See table.) Additional information on each program can be obtained from the program Web sites shown in the table. 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- | 697,000 establish- | submitted by 10.4 | ministrative records| ments | million establish- | submitted by 8.3 | | ments in first | million private-sec-| | quarter of 2020 | 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, | | | including railroads, | | | religious organiza- | | | tions, and other non- | | | UI-covered jobs -----------|---------------------|----------------------|------------------------ Publication|--Quarterly |--Quarterly |--Monthly frequency | -Within 5 months | -7 months after the | -Usually the 3rd | after the end of | end of each quarter| Friday after the end | each quarter | | of the week including | | | the 12th of the month -----------|---------------------|----------------------|------------------------ Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sa- file | and publishes each | quarter to longitu- | mpling frame and to | new quarter of UI | dinal database and | annually realign sam- | data | directly summarizes | plebased estimates to | | gross job gains and | population counts | | losses | (benchmarking) -----------|---------------------|----------------------|------------------------ Principal |--Provides a quarter-|--Provides quarterly |--Provides current mon- products | ly and annual uni- | employer dynamics | thly estimates of emp- | verse count of es- | data on establish- | loyment, hours, and | tablishments, em- | ment openings, clos-| earnings at the MSA, | ployment, and wages| ings, expansions, | state, and national | at the county, MSA,| and contractions at | level by industry | state, and national| the national level | | levels by detailed | by NAICS supersec- | | industry | tors and by size of | | | firm, and at the | | | state private-sector| | | total level | | |--Future expansions | | | will include data | | | with greater indus- | | | try detail and data | | | at the county and | | | MSA level | -----------|---------------------|----------------------|------------------------ Principal |--Detailed locality |--Business cycle |--Principal federal uses | data | analysis | economic indicator | | | (PFEI) |--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 10.2 million employer reports of employment and wages submitted by states to the BLS in 2019. 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 2019, UI and UCFE programs covered workers in 148.1 million jobs. The estimated 142.5 million workers in these jobs (after adjustment for multiple jobholders) represented 97.1 percent of civilian wage and salary employment. Covered workers received $8.769 trillion in pay, representing 94.2 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 that reflect economic events or administrative changes. For example, economic change would come from a firm relocating into the county; administrative change would come from a company correcting its county designation. QCEW imputes employment and wages for nonrespondents. Records are imputed for two quarters of nonresponse. After two quarters of nonresponse, BLS drops the establishment from the universe. QCEW state staff attempt to contact large missing employers in the first quarter of nonresponse. Effective with the release of totals for the second quarter of 2020, imputation is based on the current trend of reported employment and wages. Nonrespondents are not included in totals if unemployment claims indicate that the worksite is not in operation. Imputation methodology is described in more detail at www.bls.gov/cew/additional-resources/imputation-methodology.htm. 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 2019 quarterly data as the base data. The adjusted prior-year levels used to calculate the over-the-year percent change in employment and wages are not published. These adjusted prior-year levels do not match the unadjusted data maintained on the BLS Web site. Over-the-year change calculations based on data from the Web site, or from data published in prior BLS news releases, may differ substantially from the over-the-year changes presented in this news release. The adjusted data used to calculate the over-the-year change measures presented in this release eliminate the effect of most of the administrative changes (those occurring when employers update the industry, location, and ownership information of their establishments). The most common adjustments for administrative change are the result of updated information about the county location of individual establishments. Included in these adjustments are administrative changes involving the classification of establishments that were previously reported in the unknown or statewide county or unknown industry categories. Adjusted data account for improvements in reporting employment and wages for individual and multi-unit establishments. To accomplish this, adjustments were implemented to account for: administrative changes caused by multi-unit employers who start reporting for each individual establishment rather than as a single entity (first quarter of 2008); selected large administrative changes in employment and wages (second quarter of 2011); and state verified improvements in reporting of employment and wages (third quarter of 2014). These adjustments allow QCEW to include county employment and wage growth rates in this news release that would otherwise not meet publication standards. The adjusted data used to calculate the over-the-year change measures presented in any County Employment and Wages news release are valid for comparisons between the starting and ending points (a 12-month period) used in that particular release. Comparisons may not be valid for any time period other than the one featured in a release even if the changes were calculated using adjusted data. County definitions are assigned according to Federal Information Processing Standards Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104-106. Areas shown as counties include those designated as independent cities in some jurisdictions and, in Alaska, those designated as census areas where counties have not been created. County data also are presented for the New England states for comparative purposes even though townships are the more common designation used in New England (and New Jersey). The regions referred to in this release are defined as census regions. Additional statistics and other information Employment and Wages Annual Averages Online features comprehensive information by detailed industry on establishments, employment, and wages for the nation and all states. The 2019 edition of this publication, which was published in September 2020, contains selected data produced by Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the first quarter 2020 version of this news release. Tables and additional content from the 2019 edition of Employment and Wages Annual Averages Online are now available at www.bls.gov/cew/publications/employment-and-wages-annual-averages/2019/home.htm. The 2020 edition of Employment and Wages Annual Averages Online will be available in September 2021. News releases on quarterly measures of gross job flows also are available from BED at www.bls.gov/bdm, (202) 691-6467, or data.bls.gov/cgi-bin/forms/bdm. Information in this release will be made available to sensory impaired individuals upon request. Voice phone: (202) 691-5200; TDD message referral phone number: (800) 877-8339.
Table 1. Covered establishments, employment, and wages in the 358 largest counties, fourth quarter 2020 Employment Average weekly wage(2) Establishments, County(1) fourth quarter Percent Ranking Percent Ranking 2020 December change, by Fourth change, by (thousands) 2020 December percent quarter fourth percent (thousands) 2019-20(3) change 2020 quarter change 2019-20(3) United States(4)......... 10,675.8 140,881.3 -6.1 - $1,339 13.0 - Baldwin, AL.............. 6.9 74.3 -1.7 23 876 11.9 199 Jefferson, AL............ 19.9 344.5 -3.9 78 1,260 10.4 272 Madison, AL.............. 10.5 208.0 -1.2 15 1,414 14.4 73 Mobile, AL............... 10.6 165.8 -5.0 127 1,119 12.1 189 Montgomery, AL........... 6.5 126.8 -3.6 68 1,106 11.4 227 Shelby, AL............... 6.1 83.0 -2.8 49 1,211 10.0 291 Tuscaloosa, AL........... 4.8 90.7 -8.2 269 1,036 10.4 272 Anchorage, AK............ 8.4 134.6 -8.1 266 1,332 11.1 242 Maricopa, AZ............. 113.1 2,069.7 -3.0 56 1,273 14.8 59 Pima, AZ................. 19.5 367.5 -4.8 120 1,106 13.9 94 Benton, AR............... 7.2 124.3 -1.5 18 1,232 10.5 266 Pulaski, AR.............. 14.6 242.4 -4.3 100 1,149 13.9 94 Washington, AR........... 6.5 109.3 -2.8 49 1,121 10.3 279 Alameda, CA.............. 67.3 729.1 -8.9 296 1,831 16.5 29 Butte, CA................ 8.4 75.1 -9.1 305 1,046 15.6 45 Contra Costa, CA......... 35.3 340.3 -9.1 305 1,609 13.9 94 Fresno, CA............... 38.9 376.4 -6.2 186 1,059 12.1 189 Kern, CA................. 22.5 319.2 -4.4 103 1,069 11.0 248 Los Angeles, CA.......... 528.3 4,105.3 -10.5 337 1,612 12.4 176 Marin, CA................ 12.9 104.3 -11.0 342 1,758 16.4 30 Merced, CA............... 7.1 75.7 -5.3 142 998 13.3 127 Monterey, CA............. 14.5 165.2 -8.8 294 1,100 9.9 295 Napa, CA................. 6.0 67.0 -12.7 347 1,331 11.8 205 Orange, CA............... 133.0 1,501.1 -9.6 320 1,513 16.6 27 Placer, CA............... 14.4 163.3 -6.4 198 1,382 17.3 19 Riverside, CA............ 72.7 739.8 -5.8 167 1,051 14.5 69 Sacramento, CA........... 64.3 653.3 -5.3 142 1,407 10.5 266 San Bernardino, CA....... 66.6 780.3 -3.8 74 1,115 14.7 64 San Diego, CA............ 120.1 1,369.8 -9.3 314 1,564 19.2 9 San Francisco, CA........ 62.2 665.6 -14.0 349 3,646 44.3 1 San Joaquin, CA.......... 19.2 256.5 -2.2 32 1,140 14.1 84 San Luis Obispo, CA...... 10.9 107.3 -9.3 314 1,202 14.3 76 San Mateo, CA............ 29.6 383.9 -9.2 310 3,435 31.0 2 Santa Barbara, CA........ 16.2 197.9 -6.9 221 1,239 10.5 266 Santa Clara, CA.......... 76.8 1,047.3 -8.2 269 3,690 30.6 3 Santa Cruz, CA........... 9.9 94.5 -8.2 269 1,241 0.2 356 Solano, CA............... 12.0 131.5 -8.5 284 1,347 12.7 161 Sonoma, CA............... 20.4 191.2 -10.1 330 1,378 15.0 52 Stanislaus, CA........... 16.7 183.4 -4.3 100 1,106 11.7 211 Tulare, CA............... 12.1 155.0 -4.2 97 963 13.2 130 Ventura, CA.............. 28.7 309.0 -7.7 252 1,329 14.7 64 Yolo, CA................. 7.4 102.7 -4.7 114 1,376 11.2 233 Adams, CO................ 12.2 226.6 -2.3 35 1,217 8.3 327 Arapahoe, CO............. 23.6 321.5 -4.6 107 1,530 13.2 130 Boulder, CO.............. 16.7 178.9 -6.3 191 1,669 17.5 15 Denver, CO............... 36.6 485.1 -9.8 326 1,683 15.3 47 Douglas, CO.............. 13.4 130.6 -2.4 37 1,512 0.8 355 El Paso, CO.............. 21.8 276.4 -4.0 83 1,186 13.5 112 Jefferson, CO............ 21.8 232.2 -5.3 142 1,376 12.8 153 Larimer, CO.............. 13.3 156.3 -6.2 186 1,230 12.8 153 Weld, CO................. 8.2 104.8 -8.7 290 1,106 5.8 347 Fairfield, CT............ 37.8 389.5 -7.6 247 2,031 15.7 42 Hartford, CT............. 30.0 485.3 -6.4 198 1,503 8.7 324 New Haven, CT............ 25.8 356.0 -5.5 151 1,316 11.0 248 New London, CT........... 7.9 110.2 -9.8 326 1,264 14.9 54 New Castle, DE........... 21.6 279.9 -6.3 191 1,389 11.0 248 Sussex, DE............... 7.8 79.6 -2.8 49 974 11.6 214 Washington, DC........... 43.8 712.9 -8.9 296 2,293 15.2 50 Alachua, FL.............. 7.6 130.4 -4.2 97 1,122 14.5 69 Brevard, FL.............. 17.2 219.7 -2.9 54 1,159 9.9 295 Broward, FL.............. 76.5 778.8 -7.6 247 1,247 13.6 110 Collier, FL.............. 16.0 149.9 -5.7 161 1,209 17.5 15 Duval, FL................ 32.0 524.3 -2.4 37 1,217 11.0 248 Escambia, FL............. 8.8 136.0 -3.4 62 1,027 12.2 187 Hillsborough, FL......... 48.6 701.4 -4.1 88 1,267 12.9 147 Lake, FL................. 9.3 102.8 -2.5 41 892 12.3 182 Lee, FL.................. 24.9 265.6 -4.6 107 1,038 11.0 248 Leon, FL................. 9.3 147.5 -4.4 103 1,061 12.8 153 Manatee, FL.............. 12.4 129.0 -4.8 120 1,039 16.7 26 Marion, FL............... 9.1 107.5 -3.1 59 918 14.3 76 Miami-Dade, FL........... 110.4 1,089.3 -8.3 275 1,295 14.0 89 Okaloosa, FL............. 6.9 85.4 -0.5 7 1,087 13.2 130 Orange, FL............... 48.5 778.4 -12.2 346 1,214 16.4 30 Osceola, FL.............. 8.3 92.4 -9.7 325 885 11.5 219 Palm Beach, FL........... 62.7 590.5 -6.6 207 1,321 14.5 69 Pasco, FL................ 12.3 123.2 -2.0 25 935 12.9 147 Pinellas, FL............. 36.3 429.6 -3.8 74 1,187 11.0 248 Polk, FL................. 15.2 238.1 -0.4 6 974 12.5 174 St. Johns, FL............ 8.7 81.1 -1.0 13 1,006 11.8 205 St. Lucie, FL............ 7.4 81.2 -1.5 18 929 9.2 315 Sarasota, FL............. 17.6 167.3 -4.7 114 1,085 11.7 211 Seminole, FL............. 16.5 196.7 -4.1 88 1,113 11.5 219 Volusia, FL.............. 15.6 169.0 -4.9 124 928 9.4 309 Bibb, GA................. 4.6 80.2 -4.8 120 980 10.5 266 Chatham, GA.............. 9.0 157.7 -5.0 127 1,043 9.0 319 Clayton, GA.............. 4.5 113.4 -10.1 330 1,169 6.9 341 Cobb, GA................. 24.6 365.4 -4.0 83 1,357 13.3 127 DeKalb, GA............... 20.0 291.9 -5.2 138 1,285 10.0 291 Forsyth, GA.............. 6.6 76.2 -2.9 54 1,135 8.3 327 Fulton, GA............... 49.7 858.5 -6.7 212 1,707 12.7 161 Gwinnett, GA............. 28.4 352.8 -4.7 114 1,204 10.2 282 Hall, GA................. 5.0 90.2 -2.0 25 1,157 12.5 174 Muscogee, GA............. 4.8 91.9 -4.7 114 967 10.9 255 Richmond, GA............. 4.8 102.2 -2.8 49 1,047 11.1 242 Honolulu, HI............. 28.1 404.4 -15.1 351 1,282 16.0 38 Maui + Kalawao, HI....... 7.0 63.5 -22.8 357 1,047 12.7 161 Ada, ID.................. 18.7 255.3 -0.6 9 1,263 14.4 73 Champaign, IL............ 4.2 88.4 -5.0 127 1,086 10.7 261 Cook, IL................. 140.7 2,377.0 -10.1 330 1,571 14.6 66 DuPage, IL............... 34.8 572.7 -7.8 256 1,456 11.9 199 Kane, IL................. 12.7 194.0 -9.1 305 1,166 13.3 127 Lake, IL................. 20.4 317.0 -7.3 241 1,637 12.7 161 McHenry, IL.............. 7.9 90.4 -7.1 230 1,024 10.9 255 McLean, IL............... 3.3 77.5 -6.0 174 1,175 18.4 11 Madison, IL.............. 5.4 101.0 -3.9 78 990 9.8 299 Peoria, IL............... 4.2 97.3 -6.8 218 1,333 14.5 69 St. Clair, IL............ 5.0 86.3 -7.6 247 1,032 14.8 59 Sangamon, IL............. 4.8 121.6 -5.9 170 1,204 7.5 333 Will, IL................. 15.4 241.8 -5.9 170 1,097 12.9 147 Winnebago, IL............ 5.9 115.2 -9.0 301 1,053 10.0 291 Allen, IN................ 9.3 186.2 -4.1 88 1,048 10.3 279 Elkhart, IN.............. 4.8 132.7 0.2 4 1,138 18.2 14 Hamilton, IN............. 10.2 143.1 -1.5 18 1,234 12.7 161 Lake, IN................. 10.6 180.8 -5.3 142 1,065 9.0 319 Marion, IN............... 25.2 575.5 -5.7 161 1,299 13.0 140 St. Joseph, IN........... 5.9 117.3 -6.7 212 1,051 13.1 138 Tippecanoe, IN........... 3.7 83.1 -5.1 134 1,068 8.1 330 Vanderburgh, IN.......... 4.9 105.5 -4.1 88 1,041 13.9 94 Johnson, IA.............. 4.5 79.3 -5.6 154 1,151 12.2 187 Linn, IA................. 7.2 124.3 -6.3 191 1,216 12.6 170 Polk, IA................. 18.5 293.0 -4.1 88 1,313 11.9 199 Scott, IA................ 5.8 85.3 -6.1 181 1,068 11.3 230 Johnson, KS.............. 24.6 345.9 -4.2 97 1,313 13.0 140 Sedgwick, KS............. 12.8 242.0 -7.6 247 1,098 13.7 105 Shawnee, KS.............. 5.1 94.0 -2.1 28 1,039 13.7 105 Wyandotte, KS............ 3.5 88.2 -4.5 106 1,167 2.8 353 Boone, KY................ 4.9 98.3 -2.1 28 1,066 10.9 255 Fayette, KY.............. 12.1 184.9 -7.4 243 1,163 13.7 105 Jefferson, KY............ 27.6 455.1 -5.4 148 1,256 9.1 317 Caddo, LA................ 7.5 104.9 -5.8 167 1,032 9.8 299 Calcasieu, LA............ 5.7 83.0 -16.4 353 1,186 12.1 189 East Baton Rouge, LA..... 17.3 251.5 -5.7 161 1,187 9.2 315 Jefferson, LA............ 14.9 180.6 -6.3 191 1,140 9.1 317 Lafayette, LA............ 10.6 125.3 -5.7 161 1,046 6.3 344 Orleans, LA.............. 14.6 169.4 -16.7 354 1,264 16.9 22 St. Tammany, LA.......... 9.3 89.2 -2.4 37 1,046 8.7 324 Cumberland, ME........... 14.6 177.9 -6.4 198 1,275 17.1 20 Anne Arundel, MD......... 15.5 258.0 -8.0 262 1,400 13.5 112 Baltimore, MD............ 21.1 356.3 -8.0 262 1,360 14.8 59 Frederick, MD............ 6.6 98.9 -6.7 212 1,207 13.8 100 Harford, MD.............. 5.9 92.1 -6.1 181 1,235 14.6 66 Howard, MD............... 10.1 160.5 -9.2 310 1,671 16.9 22 Montgomery, MD........... 33.0 444.1 -7.0 228 1,758 14.9 54 Prince George's, MD...... 16.3 298.1 -8.9 296 1,358 12.7 161 Baltimore City, MD....... 13.8 327.2 -6.8 218 1,593 11.2 233 Barnstable, MA........... 9.6 84.0 -8.1 266 1,189 14.0 89 Bristol, MA.............. 17.9 214.9 -7.5 244 1,211 14.1 84 Essex, MA................ 28.1 302.2 -8.2 269 1,400 14.4 73 Hampden, MA.............. 19.1 198.3 -7.9 257 1,141 13.9 94 Middlesex, MA............ 57.8 879.0 -7.7 252 2,043 18.4 11 Norfolk, MA.............. 25.8 323.2 -9.5 318 1,629 16.2 36 Plymouth, MA............. 16.6 182.5 -8.0 262 1,269 15.6 45 Suffolk, MA.............. 32.4 639.4 -10.4 336 2,558 19.9 7 Worcester, MA............ 26.9 332.8 -7.3 241 1,296 14.0 89 Genesee, MI.............. 7.2 124.1 -9.4 317 1,073 9.4 309 Ingham, MI............... 6.5 139.7 -9.8 326 1,252 10.6 264 Kalamazoo, MI............ 5.8 112.7 -8.6 288 1,190 13.8 100 Kent, MI................. 16.2 371.1 -10.7 339 1,194 16.4 30 Macomb, MI............... 18.9 306.0 -9.0 301 1,308 14.1 84 Oakland, MI.............. 42.5 682.0 -9.6 320 1,473 12.6 170 Ottawa, MI............... 6.3 120.0 -6.8 218 1,133 13.0 140 Saginaw, MI.............. 4.0 76.0 -10.8 340 1,076 13.9 94 Washtenaw, MI............ 9.2 203.3 -9.5 318 1,365 13.7 105 Wayne, MI................ 34.9 676.4 -9.2 310 1,391 9.9 295 Anoka, MN................ 8.0 119.4 -7.9 257 1,198 10.4 272 Dakota, MN............... 11.0 176.6 -8.2 269 1,291 9.6 304 Hennepin, MN............. 43.4 854.4 -9.6 320 1,618 13.4 120 Olmsted, MN.............. 3.9 96.3 -5.7 161 1,458 10.7 261 Ramsey, MN............... 14.4 306.1 -8.9 296 1,412 12.4 176 St. Louis, MN............ 5.5 87.7 -10.3 334 1,077 9.8 299 Stearns, MN.............. 4.4 80.2 -7.5 244 1,087 14.3 76 Washington, MN........... 6.3 83.7 -7.2 235 1,116 13.4 120 Harrison, MS............. 4.7 83.2 -4.4 103 863 9.4 309 Hinds, MS................ 5.7 115.2 -3.8 74 1,034 11.2 233 Boone, MO................ 5.1 93.5 -2.7 46 1,070 10.5 266 Clay, MO................. 6.1 105.5 -1.2 15 1,108 6.0 345 Greene, MO............... 9.9 168.1 -2.5 41 989 7.9 332 Jackson, MO.............. 23.8 356.9 -5.6 154 1,318 11.1 242 St. Charles, MO.......... 10.3 153.1 -2.7 46 1,030 11.1 242 St. Louis, MO............ 43.1 574.2 -7.1 230 1,391 13.5 112 St. Louis City, MO....... 15.9 212.7 -7.6 247 1,359 11.2 233 Yellowstone, MT.......... 6.9 81.7 -1.3 17 1,108 10.2 282 Douglas, NE.............. 19.1 332.8 -3.8 74 1,226 12.4 176 Lancaster, NE............ 10.1 166.0 -4.6 107 1,056 11.5 219 Clark, NV................ 56.7 899.1 -14.3 350 1,141 13.4 120 Washoe, NV............... 15.1 217.0 -6.0 174 1,218 14.8 59 Hillsborough, NH......... 12.6 196.4 -6.1 181 1,533 18.7 10 Merrimack, NH............ 5.3 73.8 -6.1 181 1,278 15.9 40 Rockingham, NH........... 11.5 145.4 -5.2 138 1,346 15.3 47 Atlantic, NJ............. 6.8 112.0 -12.9 348 1,115 14.2 81 Bergen, NJ............... 34.4 411.2 -9.6 320 1,533 13.2 130 Burlington, NJ........... 11.5 194.7 -5.0 127 1,379 16.6 27 Camden, NJ............... 12.6 192.7 -7.2 235 1,317 13.5 112 Essex, NJ................ 21.8 309.0 -11.8 345 1,598 14.1 84 Gloucester, NJ........... 6.7 112.3 -5.4 148 1,075 12.4 176 Hudson, NJ............... 16.6 253.0 -9.1 305 1,702 13.8 100 Mercer, NJ............... 11.7 253.1 -5.3 142 1,599 9.9 295 Middlesex, NJ............ 23.3 414.2 -5.2 138 1,475 12.0 195 Monmouth, NJ............. 20.9 248.9 -7.2 235 1,338 16.0 38 Morris, NJ............... 17.6 277.2 -7.7 252 1,986 17.4 17 Ocean, NJ................ 14.2 163.2 -4.9 124 1,058 12.6 170 Passaic, NJ.............. 13.1 153.8 -10.2 333 1,243 14.2 81 Somerset, NJ............. 10.6 178.8 -7.1 230 1,857 14.1 84 Union, NJ................ 15.3 215.7 -8.0 262 1,602 10.2 282 Bernalillo, NM........... 21.0 310.0 -8.5 284 1,129 15.0 52 Albany, NY............... 10.4 217.3 -7.9 257 1,359 12.7 161 Bronx, NY................ 19.5 307.4 -6.9 221 1,288 11.3 230 Broome, NY............... 4.3 78.5 -8.5 284 1,071 15.8 41 Dutchess, NY............. 8.5 105.8 -8.5 284 1,242 12.8 153 Erie, NY................. 24.8 425.8 -10.9 341 1,188 14.0 89 Kings, NY................ 67.1 760.2 -8.7 290 1,132 10.4 272 Monroe, NY............... 19.0 356.7 -9.6 320 1,186 13.2 130 Nassau, NY............... 54.7 584.6 -9.3 314 1,456 13.0 140 New York, NY............. 129.8 2,163.2 -15.6 352 3,036 20.9 6 Oneida, NY............... 5.3 97.3 -8.8 294 1,015 13.2 130 Onondaga, NY............. 12.7 230.0 -8.6 288 1,205 12.7 161 Orange, NY............... 10.9 139.0 -8.4 279 1,126 12.9 147 Queens, NY............... 54.5 651.3 -10.5 337 1,276 9.6 304 Richmond, NY............. 10.2 125.5 -6.4 198 1,221 11.5 219 Rockland, NY............. 11.3 122.9 -7.1 230 1,192 11.9 199 Saratoga, NY............. 6.1 83.9 -7.1 230 1,213 15.7 42 Suffolk, NY.............. 54.1 624.6 -7.2 235 1,454 13.4 120 Westchester, NY.......... 36.3 394.6 -10.3 334 1,681 10.2 282 Buncombe, NC............. 10.4 126.9 -6.7 212 1,024 11.3 230 Cabarrus, NC............. 5.3 77.7 -1.5 18 962 12.3 182 Catawba, NC.............. 4.6 86.2 -2.8 49 1,008 14.2 81 Cumberland, NC........... 6.6 116.8 -5.1 134 970 12.0 195 Durham, NC............... 9.2 216.0 -2.5 41 1,602 11.6 214 Forsyth, NC.............. 9.8 186.6 -4.0 83 1,131 8.1 330 Guilford, NC............. 15.2 279.3 -3.7 71 1,089 9.4 309 Iredell, NC.............. 5.8 77.2 -0.6 9 1,140 16.3 34 Mecklenburg, NC.......... 42.0 711.0 -2.7 46 1,453 10.2 282 New Hanover, NC.......... 9.1 115.8 -3.5 65 1,133 21.4 5 Pitt, NC................. 4.0 75.6 -3.7 71 1,016 11.2 233 Wake, NC................. 39.4 567.4 -2.1 28 1,321 10.4 272 Cass, ND................. 7.7 116.8 -4.0 83 1,182 11.5 219 Butler, OH............... 8.2 153.0 -4.6 107 1,120 13.8 100 Cuyahoga, OH............. 36.9 686.7 -6.9 221 1,319 10.4 272 Delaware, OH............. 6.0 86.6 -4.1 88 1,235 12.3 182 Franklin, OH............. 35.1 741.0 -5.2 138 1,288 14.6 66 Greene, OH............... 3.8 75.2 -3.5 65 1,265 9.4 309 Hamilton, OH............. 25.0 491.7 -6.5 205 1,387 11.8 205 Lake, OH................. 6.4 90.5 -6.9 221 1,034 10.1 289 Lorain, OH............... 6.4 92.5 -6.0 174 993 11.6 214 Lucas, OH................ 10.3 197.4 -6.7 212 1,117 10.6 264 Mahoning, OH............. 5.9 91.9 -6.6 207 906 10.9 255 Montgomery, OH........... 12.4 244.0 -5.6 154 1,112 12.8 153 Stark, OH................ 8.7 151.4 -5.1 134 987 13.2 130 Summit, OH............... 14.8 254.1 -6.0 174 1,132 12.1 189 Warren, OH............... 5.5 93.5 -4.6 107 1,210 17.0 21 Cleveland, OK............ 6.2 87.0 0.1 5 880 5.9 346 Oklahoma, OK............. 29.1 450.2 -4.3 100 1,160 9.5 307 Tulsa, OK................ 23.1 348.7 -5.6 154 1,087 7.2 337 Clackamas, OR............ 16.3 157.9 -8.4 279 1,260 13.4 120 Deschutes, OR............ 10.1 81.4 -6.0 174 1,130 16.9 22 Jackson, OR.............. 8.1 86.5 -6.3 191 1,009 12.7 161 Lane, OR................. 13.3 146.2 -8.4 279 1,054 14.8 59 Marion, OR............... 11.9 151.2 -5.6 154 1,100 11.8 205 Multnomah, OR............ 38.3 471.4 -11.0 342 1,440 15.3 47 Washington, OR........... 21.2 285.1 -6.7 212 1,641 16.4 30 Allegheny, PA............ 37.0 646.5 -8.3 275 1,393 11.2 233 Berks, PA................ 9.0 165.0 -6.4 198 1,148 12.9 147 Bucks, PA................ 20.7 250.0 -6.9 221 1,225 13.5 112 Butler, PA............... 5.2 82.6 -6.2 186 1,164 9.4 309 Chester, PA.............. 16.1 240.1 -6.2 186 1,617 14.0 89 Cumberland, PA........... 6.8 132.2 -5.0 127 1,157 11.8 205 Dauphin, PA.............. 7.7 176.3 -6.2 186 1,279 13.0 140 Delaware, PA............. 14.4 211.0 -8.9 296 1,358 14.9 54 Erie, PA................. 6.9 111.8 -9.0 301 970 12.9 147 Lackawanna, PA........... 5.6 90.5 -8.3 275 991 13.5 112 Lancaster, PA............ 14.0 235.0 -6.0 174 1,115 16.9 22 Lehigh, PA............... 8.9 186.0 -6.1 181 1,299 13.4 120 Luzerne, PA.............. 7.6 137.4 -7.7 252 1,007 12.8 153 Montgomery, PA........... 28.6 482.3 -6.6 207 1,627 17.4 17 Northampton, PA.......... 6.9 114.3 -6.4 198 1,094 13.6 110 Philadelphia, PA......... 35.5 633.9 -11.5 344 1,543 9.8 299 Washington, PA........... 5.6 79.6 -9.9 329 1,220 7.1 339 Westmoreland, PA......... 9.3 124.6 -7.5 244 1,028 10.3 279 York, PA................. 9.3 172.0 -6.0 174 1,115 11.2 233 Kent, RI................. 5.7 71.1 -9.1 305 1,144 14.3 76 Providence, RI........... 19.3 267.4 -9.0 301 1,299 14.9 54 Charleston, SC........... 18.2 247.4 -5.6 154 1,179 11.9 199 Greenville, SC........... 16.5 273.2 -2.5 41 1,099 10.1 289 Horry, SC................ 10.3 121.6 -6.4 198 808 11.9 199 Lexington, SC............ 7.5 121.5 -4.1 88 987 12.3 182 Richland, SC............. 11.2 216.1 -3.6 68 1,078 11.5 219 Spartanburg, SC.......... 7.0 147.5 -3.0 56 1,037 10.2 282 York, SC................. 7.1 100.8 -2.2 32 1,041 10.5 266 Minnehaha, SD............ 8.1 126.9 -2.0 25 1,207 18.3 13 Davidson, TN............. 26.4 486.4 -6.6 207 1,421 13.4 120 Hamilton, TN............. 10.9 204.5 -3.6 68 1,189 12.8 153 Knox, TN................. 13.7 237.3 -3.0 56 1,145 11.7 211 Rutherford, TN........... 6.5 136.7 0.5 3 1,084 8.8 322 Shelby, TN............... 22.0 488.3 -4.1 88 1,341 15.7 42 Williamson, TN........... 10.5 140.6 -2.1 28 1,509 9.7 303 Bell, TX................. 6.0 121.0 -2.2 32 1,070 7.5 333 Bexar, TX................ 44.1 847.0 -5.1 134 1,171 10.9 255 Brazoria, TX............. 6.4 110.6 -6.6 207 1,197 6.9 341 Brazos, TX............... 4.9 107.3 -3.5 65 932 9.6 304 Cameron, TX.............. 6.7 140.5 -2.3 35 760 8.3 327 Collin, TX............... 29.8 439.5 -3.2 60 1,496 12.1 189 Dallas, TX............... 81.7 1,704.6 -3.4 62 1,548 10.7 261 Denton, TX............... 17.5 267.7 -1.5 18 1,146 11.4 227 Ector, TX................ 4.3 66.2 -18.2 356 1,176 -7.5 357 El Paso, TX.............. 15.9 302.3 -5.5 151 892 12.3 182 Fort Bend, TX............ 15.8 197.2 -2.6 45 1,089 4.9 349 Galveston, TX............ 6.5 106.2 -5.3 142 1,118 8.9 321 Gregg, TX................ 4.3 70.4 -8.4 279 996 2.6 354 Harris, TX............... 121.5 2,220.9 -6.5 205 1,501 5.0 348 Hidalgo, TX.............. 13.0 260.8 -4.0 83 776 10.2 282 Jefferson, TX............ 5.9 112.7 -9.2 310 1,186 4.8 350 Lubbock, TX.............. 8.0 141.4 -1.9 24 980 7.2 337 McLennan, TX............. 5.6 114.1 -0.6 9 1,052 10.0 291 Midland, TX.............. 6.2 90.7 -16.8 355 1,594 3.4 351 Montgomery, TX........... 13.1 189.8 -4.7 114 1,229 7.5 333 Nueces, TX............... 8.4 151.4 -8.2 269 1,053 7.0 340 Potter, TX............... 4.0 75.8 -3.2 60 1,062 8.8 322 Smith, TX................ 6.5 104.3 -2.4 37 1,029 7.5 333 Tarrant, TX.............. 47.4 910.2 -3.9 78 1,262 10.8 260 Travis, TX............... 46.7 769.1 -3.4 62 1,632 15.2 50 Webb, TX................. 5.6 98.1 -6.9 221 829 10.4 272 Williamson, TX........... 13.0 186.1 -0.9 12 1,333 2.9 352 Davis, UT................ 9.7 136.5 2.3 2 1,086 11.6 214 Salt Lake, UT............ 53.6 726.7 -1.1 14 1,315 13.8 100 Utah, UT................. 19.6 266.1 3.8 1 1,153 16.3 34 Weber, UT................ 6.8 111.0 -0.5 7 967 11.4 227 Chittenden, VT........... 7.4 95.2 -8.3 275 1,293 13.7 105 Arlington, VA............ 9.4 171.6 -8.7 290 2,227 13.0 140 Chesterfield, VA......... 9.6 136.4 -3.9 78 1,093 13.0 140 Fairfax, VA.............. 37.6 599.9 -4.6 107 1,992 14.9 54 Henrico, VA.............. 12.0 183.6 -5.6 154 1,238 12.4 176 Loudoun, VA.............. 13.3 166.8 -6.9 221 1,571 16.2 36 Prince William, VA....... 9.8 128.3 -4.8 120 1,161 13.2 130 Alexandria City, VA...... 6.3 84.1 -7.2 235 1,832 11.2 233 Chesapeake City, VA...... 6.4 100.9 -3.9 78 1,018 13.5 112 Newport News City, VA.... 4.1 101.4 -4.1 88 1,228 11.1 242 Norfolk City, VA......... 6.2 133.4 -7.0 228 1,303 11.0 248 Richmond City, VA........ 8.2 146.5 -8.1 266 1,438 13.1 138 Virginia Beach City, VA.. 12.7 169.7 -5.4 148 1,030 12.8 153 Benton, WA............... 6.3 86.2 -5.9 170 1,259 11.8 205 Clark, WA................ 16.4 156.4 -5.9 170 1,276 13.5 112 King, WA................. 93.0 1,340.2 -7.9 257 2,176 19.7 8 Kitsap, WA............... 7.2 85.7 -7.9 257 1,346 22.7 4 Pierce, WA............... 24.4 303.8 -5.8 167 1,197 11.6 214 Snohomish, WA............ 22.7 269.9 -8.4 279 1,380 11.5 219 Spokane, WA.............. 17.5 217.5 -6.3 191 1,115 11.2 233 Thurston, WA............. 9.1 112.9 -5.5 151 1,194 11.1 242 Whatcom, WA.............. 7.7 83.9 -8.7 290 1,110 12.6 170 Yakima, WA............... 8.2 103.7 -4.6 107 924 8.7 324 Kanawha, WV.............. 5.6 90.8 -6.3 191 1,074 11.5 219 Brown, WI................ 7.4 152.5 -5.0 127 1,192 12.1 189 Dane, WI................. 16.8 330.5 -5.7 161 1,322 12.4 176 Milwaukee, WI............ 28.2 455.8 -7.2 235 1,258 12.0 195 Outagamie, WI............ 5.7 104.5 -4.9 124 1,118 9.5 307 Racine, WI............... 4.9 71.7 -4.7 114 1,172 14.3 76 Waukesha, WI............. 14.1 235.4 -5.0 127 1,314 12.0 195 Winnebago, WI............ 4.0 90.5 -3.7 71 1,163 6.6 343 San Juan, PR............. 10.9 234.0 -6.6 (5) 749 8.6 (5) (1) Includes areas not officially designated as counties. See Technical Note. (2) Average weekly wages were calculated using unrounded data. (3) Percent changes were computed from 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 357 U.S. counties comprise 73.1 percent of the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties, fourth quarter 2020 Employment Average weekly wage(1) Establishments, fourth quarter County by NAICS supersector 2020 Percent Percent (thousands) December change, Fourth change, 2020 December quarter fourth (thousands) 2019-20(2) 2020 quarter 2019-20(2) United States(3) ............................ 10,675.8 140,881.3 -6.1 $1,339 13.0 Private industry........................... 10,373.2 119,621.8 -6.4 1,352 13.8 Natural resources and mining............. 141.4 1,652.9 -8.5 1,219 0.7 Construction............................. 858.4 7,232.2 -2.9 1,463 7.1 Manufacturing............................ 361.7 12,154.0 -5.0 1,552 11.4 Trade, transportation, and utilities..... 1,965.7 27,910.4 -2.2 1,077 11.5 Information.............................. 206.7 2,700.8 -6.9 2,814 21.3 Financial activities..................... 960.0 8,241.1 -2.0 2,166 13.6 Professional and business services....... 2,024.8 20,783.9 -3.0 1,804 13.1 Education and health services............ 1,893.3 22,534.8 -4.3 1,181 12.4 Leisure and hospitality.................. 897.1 12,251.4 -24.9 567 8.4 Other services........................... 838.7 3,952.1 -12.4 911 12.7 Government................................. 302.6 21,259.5 -4.3 1,268 8.7 Los Angeles, CA.............................. 528.3 4,105.3 -10.5 1,612 12.4 Private industry........................... 521.9 3,555.2 -11.2 1,608 13.1 Natural resources and mining............. 0.6 6.1 7.6 1,236 6.4 Construction............................. 18.0 147.1 -2.4 1,568 6.3 Manufacturing............................ 12.6 309.6 -8.9 1,702 12.6 Trade, transportation, and utilities..... 60.8 822.0 -5.9 1,208 12.8 Information.............................. 14.6 186.3 -7.2 3,633 15.8 Financial activities..................... 32.1 211.2 -6.3 2,437 10.1 Professional and business services....... 60.8 598.1 -8.3 2,096 12.1 Education and health services............ 250.1 815.8 -3.6 1,120 11.8 Leisure and hospitality.................. 42.0 341.1 -38.5 1,413 16.4 Other services........................... 30.0 117.7 -23.4 993 17.5 Government................................. 6.4 550.1 -6.1 1,637 7.9 Cook, IL..................................... 140.7 2,377.0 -10.1 1,571 14.6 Private industry........................... 139.4 2,100.5 -10.5 1,585 14.8 Natural resources and mining............. 0.1 1.6 9.5 1,372 4.2 Construction............................. 11.3 68.9 -8.6 1,800 2.0 Manufacturing............................ 5.7 174.8 -5.9 1,527 6.0 Trade, transportation, and utilities..... 28.7 461.2 -5.5 1,171 8.5 Information.............................. 2.6 48.7 -8.3 2,536 19.3 Financial activities..................... 14.3 202.3 -2.3 2,911 13.4 Professional and business services....... 29.5 454.5 -6.6 2,087 15.0 Education and health services............ 16.3 438.6 -4.7 1,244 12.9 Leisure and hospitality.................. 14.0 164.1 -43.6 610 3.2 Other services........................... 16.3 85.4 -14.0 1,154 11.1 Government................................. 1.3 276.4 -6.2 1,469 13.8 New York, NY................................. 129.8 2,163.2 -15.6 3,036 20.9 Private industry........................... 128.4 1,935.8 -16.8 3,187 23.0 Natural resources and mining............. 0.0 0.2 2.4 2,796 11.9 Construction............................. 2.4 37.8 -11.8 2,480 5.5 Manufacturing............................ 1.8 15.2 -30.8 2,008 19.2 Trade, transportation, and utilities..... 18.0 204.1 -23.1 1,857 18.7 Information.............................. 5.9 183.0 -7.4 3,801 15.6 Financial activities..................... 19.5 376.8 -4.5 5,573 13.6 Professional and business services....... 29.3 537.9 -10.7 3,573 21.0 Education and health services............ 10.4 341.9 -7.7 1,724 11.2 Leisure and hospitality.................. 14.3 144.6 -54.4 1,405 19.0 Other services........................... 19.1 88.0 -19.8 1,544 15.6 Government................................. 1.5 227.4 -3.8 1,766 3.0 Harris, TX................................... 121.5 2,220.9 -6.5 1,501 5.0 Private industry........................... 120.9 1,938.2 -7.3 1,528 5.4 Natural resources and mining............. 1.5 52.7 -19.7 3,777 6.5 Construction............................. 8.0 149.3 -11.9 1,639 3.5 Manufacturing............................ 5.0 158.6 -11.3 1,792 4.3 Trade, transportation, and utilities..... 25.6 468.4 -3.4 1,293 5.3 Information.............................. 1.4 22.1 -16.2 1,825 14.2 Financial activities..................... 13.1 127.1 -3.3 2,111 7.8 Professional and business services....... 24.7 396.2 -5.2 1,929 3.1 Education and health services............ 17.4 299.2 -2.0 1,254 8.9 Leisure and hospitality.................. 10.9 201.5 -16.5 556 5.3 Other services........................... 11.8 61.0 -10.5 1,002 9.0 Government................................. 0.6 282.6 -1.0 1,316 3.2 Maricopa, AZ................................. 113.1 2,069.7 -3.0 1,273 14.8 Private industry........................... 112.4 1,859.1 -2.9 1,276 15.0 Natural resources and mining............. 0.5 7.5 -11.7 1,297 27.3 Construction............................. 8.9 133.0 -1.1 1,458 13.6 Manufacturing............................ 3.6 131.4 -1.0 1,730 9.9 Trade, transportation, and utilities..... 21.9 428.4 3.0 1,115 13.7 Information.............................. 2.6 35.6 -10.8 1,861 22.8 Financial activities..................... 15.1 196.4 0.6 1,742 17.7 Professional and business services....... 28.8 349.3 -3.0 1,381 12.6 Education and health services............ 14.2 336.2 -1.6 1,226 15.0 Leisure and hospitality.................. 9.4 190.3 -17.9 595 9.8 Other services........................... 7.3 50.7 -7.4 905 10.9 Government................................. 0.7 210.5 -4.0 1,244 13.0 Dallas, TX................................... 81.7 1,704.6 -3.4 1,548 10.7 Private industry........................... 81.2 1,526.5 -3.7 1,567 11.3 Natural resources and mining............. 0.5 7.7 -11.7 2,878 6.7 Construction............................. 5.1 89.3 -5.0 1,591 5.8 Manufacturing............................ 2.9 116.0 -2.8 1,703 12.1 Trade, transportation, and utilities..... 16.3 373.3 0.9 1,305 10.8 Information.............................. 1.5 44.0 -6.5 2,259 13.2 Financial activities..................... 10.2 161.9 0.8 2,193 11.0 Professional and business services....... 18.8 361.1 -2.2 1,894 8.9 Education and health services............ 10.2 200.6 -2.3 1,386 10.4 Leisure and hospitality.................. 7.4 133.6 -20.1 630 5.5 Other services........................... 7.3 37.6 -14.9 1,058 17.3 Government................................. 0.5 178.2 -0.3 1,387 5.8 Orange, CA................................... 133.0 1,501.1 -9.6 1,513 16.6 Private industry........................... 131.6 1,361.9 -10.0 1,519 17.3 Natural resources and mining............. 0.2 2.5 14.0 1,114 9.0 Construction............................. 8.1 100.6 -4.8 1,759 9.8 Manufacturing............................ 5.3 146.5 -8.2 1,925 19.3 Trade, transportation, and utilities..... 19.0 252.1 -5.2 1,242 11.4 Information.............................. 1.7 23.0 -10.0 2,579 22.6 Financial activities..................... 13.8 116.6 -2.6 2,626 17.1 Professional and business services....... 25.0 308.1 -5.8 1,758 15.3 Education and health services............ 40.2 223.9 -3.8 1,192 13.6 Leisure and hospitality.................. 10.1 148.9 -34.1 603 5.8 Other services........................... 8.1 39.6 -18.6 909 14.3 Government................................. 1.4 139.2 -6.0 1,461 10.0 San Diego, CA................................ 120.1 1,369.8 -9.3 1,564 19.2 Private industry........................... 118.2 1,144.1 -9.9 1,555 21.2 Natural resources and mining............. 0.7 8.8 -7.8 971 20.2 Construction............................. 8.3 81.7 -2.8 1,572 10.9 Manufacturing............................ 3.6 113.2 -5.1 1,938 11.7 Trade, transportation, and utilities..... 15.5 218.8 -5.4 1,107 16.3 Information.............................. 1.5 21.2 -10.6 2,769 28.1 Financial activities..................... 11.8 74.8 -3.9 2,115 20.7 Professional and business services....... 22.5 250.0 -2.4 2,444 23.2 Education and health services............ 36.3 207.9 -3.6 1,196 12.1 Leisure and hospitality.................. 9.3 128.7 -35.3 637 11.6 Other services........................... 8.5 39.0 -26.7 831 22.2 Government................................. 1.9 225.7 -6.5 1,610 10.0 King, WA..................................... 93.0 1,340.2 -7.9 2,176 19.7 Private industry........................... 92.4 1,176.1 -8.2 2,245 20.7 Natural resources and mining............. 0.4 3.0 -1.9 1,396 5.3 Construction............................. 7.1 73.7 -2.2 1,763 8.4 Manufacturing............................ 2.5 88.8 -15.6 2,002 13.7 Trade, transportation, and utilities..... 13.6 285.4 -0.5 2,316 20.4 Information.............................. 2.8 129.8 3.5 4,743 21.5 Financial activities..................... 7.3 68.1 -2.5 2,463 17.3 Professional and business services....... 19.8 231.7 -3.2 2,440 11.7 Education and health services............ 21.4 174.0 -4.9 1,279 9.5 Leisure and hospitality.................. 7.6 80.9 -43.8 726 7.9 Other services........................... 9.8 40.7 -16.1 1,155 16.4 Government................................. 0.6 164.1 -5.5 1,683 11.2 Miami-Dade, FL............................... 110.4 1,089.3 -8.3 1,295 14.0 Private industry........................... 110.1 952.6 -9.0 1,274 13.5 Natural resources and mining............. 0.5 9.1 -4.6 794 14.4 Construction............................. 7.6 50.4 -0.6 1,177 6.2 Manufacturing............................ 2.9 40.2 -4.8 1,135 7.9 Trade, transportation, and utilities..... 25.5 274.6 -9.3 1,127 12.6 Information.............................. 1.8 17.3 -12.3 1,986 23.4 Financial activities..................... 11.9 75.5 -2.8 1,968 8.8 Professional and business services....... 25.9 162.5 -3.7 1,701 10.7 Education and health services............ 13.7 181.9 -4.7 1,203 10.7 Leisure and hospitality.................. 8.1 105.8 -27.3 776 16.2 Other services........................... 8.5 34.2 -12.0 821 13.1 Government................................. 0.3 136.7 -3.3 1,444 17.2 (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 2019 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, fourth quarter 2020 Employment Average weekly wage(1) Establishments, fourth quarter State 2020 Percent Percent (thousands) December change, Fourth change, 2020 December quarter fourth (thousands) 2019-20 2020 quarter 2019-20 United States(2)........... 10,675.8 140,881.3 -6.1 $1,339 13.0 Alabama.................... 134.6 1,951.2 -2.9 1,096 11.4 Alaska..................... 23.1 290.1 -6.4 1,260 10.6 Arizona.................... 173.9 2,908.7 -3.3 1,214 14.6 Arkansas................... 94.6 1,194.8 -3.2 999 11.4 California................. 1,660.2 16,380.1 -8.3 1,724 18.5 Colorado................... 219.6 2,613.7 -5.7 1,378 12.3 Connecticut................ 126.8 1,578.4 -6.5 1,551 12.2 Delaware................... 35.1 432.9 -5.2 1,262 11.3 District of Columbia....... 43.8 713.0 -8.9 2,293 15.2 Florida.................... 765.4 8,642.8 -5.0 1,180 13.1 Georgia.................... 319.7 4,405.9 -4.0 1,208 10.9 Hawaii..................... 47.3 561.1 -16.1 1,219 16.0 Idaho...................... 71.8 763.5 0.8 1,034 12.8 Illinois................... 386.3 5,573.8 -7.8 1,378 13.0 Indiana.................... 173.1 2,985.1 -4.0 1,076 11.2 Iowa....................... 105.6 1,494.3 -4.3 1,099 11.6 Kansas..................... 89.9 1,346.9 -4.5 1,070 11.5 Kentucky................... 130.4 1,839.6 -4.8 1,057 10.8 Louisiana.................. 140.8 1,796.9 -7.0 1,078 8.6 Maine...................... 55.4 594.3 -4.3 1,092 14.5 Maryland................... 174.5 2,546.1 -6.7 1,445 13.6 Massachusetts.............. 266.7 3,365.8 -8.3 1,766 17.0 Michigan................... 265.3 3,998.2 -8.9 1,257 12.8 Minnesota.................. 186.4 2,684.1 -7.9 1,322 12.3 Mississippi................ 76.1 1,119.1 -2.4 901 10.4 Missouri................... 221.5 2,724.4 -4.3 1,127 11.6 Montana.................... 54.6 467.4 -1.4 1,035 12.7 Nebraska................... 72.5 962.7 -2.9 1,079 11.5 Nevada..................... 90.2 1,283.1 -10.7 1,178 14.4 New Hampshire.............. 57.1 637.3 -5.2 1,406 17.9 New Jersey................. 291.0 3,860.5 -7.2 1,517 13.9 New Mexico................. 64.8 767.1 -9.5 1,052 11.8 New York................... 662.4 8,693.4 -10.3 1,712 14.2 North Carolina............. 301.7 4,431.0 -2.7 1,152 11.2 North Dakota............... 32.6 394.4 -7.1 1,136 4.7 Ohio....................... 307.3 5,199.9 -5.1 1,161 12.0 Oklahoma................... 113.6 1,569.1 -4.4 1,013 7.3 Oregon..................... 167.3 1,824.3 -7.5 1,256 14.2 Pennsylvania............... 370.5 5,549.4 -7.4 1,287 12.6 Rhode Island............... 40.7 449.6 -8.3 1,259 14.7 South Carolina............. 149.2 2,074.4 -3.5 1,035 11.1 South Dakota............... 35.5 422.8 -1.9 1,048 14.4 Tennessee.................. 176.2 3,002.5 -2.7 1,172 11.7 Texas...................... 743.1 12,251.1 -4.3 1,294 9.0 Utah....................... 117.9 1,557.8 0.6 1,154 12.9 Vermont.................... 26.6 286.1 -8.9 1,133 14.7 Virginia................... 289.8 3,796.1 -4.7 1,360 13.0 Washington................. 259.7 3,219.7 -6.8 1,589 16.0 West Virginia.............. 51.9 654.1 -5.3 997 10.3 Wisconsin.................. 184.2 2,762.5 -4.8 1,140 11.7 Wyoming.................... 27.7 260.2 -5.3 1,061 4.6 Puerto Rico................ 46.0 873.8 -4.0 621 8.0 Virgin Islands............. 3.5 35.3 -11.5 1,057 -1.3 (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.