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.
United States Department of Labor
