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Metropolitan Area Employment and Unemployment (Monthly)

07/29/2020 | 10:25am EDT

For release 10:00 a.m. (ET) Wednesday, July 29, 2020

USDL-20-1464

Technical information:

Employment: sminfo@bls.gov • www.bls.gov/sae

Unemployment: lausinfo@bls.gov • www.bls.gov/lau

Media contact:

(202) 691-5902 • PressOffice@bls.gov

METROPOLITAN AREA EMPLOYMENT AND UNEMPLOYMENT - JUNE 2020

Unemployment rates were higher in June than a year earlier in 388 of the 389 metropolitan areas and lower in 1 area, the U.S. Bureau of Labor Statistics reported today. A total of 218 areas had jobless rates of less than 10.0 percent and 6 areas had rates of at least 20.0 percent. Nonfarm payroll employment decreased over the year in 307 metropolitan areas and was essentially unchanged in 82 areas. The national unemployment rate in June was 11.2 percent, not seasonally adjusted, up from 3.8 percent a year earlier.

This news release presents statistics from two monthly programs. The civilian labor force and unemployment data are based on the same concepts and definitions as those used for the national household survey estimates. These data pertain to individuals by where they reside. The employment data are from an establishment survey that measures nonfarm employment, hours, and earnings by industry. These data pertain to jobs on payrolls defined by where the establishments are located. For more information about the concepts and statistical methodologies used by these two programs, see the Technical Note.

Metropolitan Area Unemployment (Not Seasonally Adjusted)

Atlantic City-Hammonton, NJ, had the highest unemployment rate in June, 34.3 percent. Logan, UT-ID, and Idaho Falls, ID, had the lowest unemployment rates, 3.5 percent and 3.6 percent, respectively. A total of 267 areas had June jobless rates below the U.S. rate of 11.2 percent, 116 areas had rates above it, and 6 areas had rates equal to that of the nation. (See table 1 and map 1.)

The largest over-the-year unemployment rate increase occurred in Atlantic City-Hammonton, NJ (+29.9 percentage points). Rates rose over the year by at least 10.0 percentage points in an additional 31 areas. Owensboro, KY, was the only area with an unemployment rate decline relative to June 2019, however slight (-0.2 percentage point).

Of the 51 metropolitan areas with a 2010 Census population of 1 million or more, Los Angeles-LongBeach-Anaheim, CA, and Las Vegas-Henderson-Paradise, NV, had the highest unemployment rates in June, 18.1 percent and 18.0 percent, respectively. Salt Lake City, UT, had the lowest jobless rate among the large areas, 6.2 percent, followed by Louisville/Jefferson County, KY-IN, 6.4 percent. All 51 large areas had over-the-year unemployment rate increases, the largest of which were in Boston-Cambridge-

Nashua, MA-NH, and Los Angeles-LongBeach-Anaheim, CA (+14.0 percentage points each). The smallest rate increase occurred in Louisville/Jefferson County, KY-IN (+2.2 percentage points).

Metropolitan Division Unemployment (Not Seasonally Adjusted)

Eleven of the most populous metropolitan areas are made up of 38 metropolitan divisions, which are essentially separately identifiable employment centers. In June, Lawrence-MethuenTown-Salem, MA- NH, had the highest unemployment rate among the divisions, 23.4 percent. Silver Spring-Frederick- Rockville, MD, had the lowest division rate, 8.0 percent. (See table 2.)

In June, all 38 metropolitan divisions had over-the-year unemployment rate increases, the largest of which was in Lawrence-MethuenTown-Salem,MA-NH (+19.2 percentage points). The smallest rate increases occurred in Silver Spring-Frederick-Rockville, MD (+4.7 percentage points), and Dallas- Plano-Irving, TX (+4.8 points).

Metropolitan Area Nonfarm Employment (Not Seasonally Adjusted)

In June, 307 metropolitan areas had over-the-year decreases in nonfarm payroll employment and 82 were essentially unchanged. The largest over-the-year employment decreases occurred in New York- Newark-Jersey City, NY-NJ-PA(-1,549,100), Los Angeles-LongBeach-Anaheim, CA (-650,400), and Chicago-Naperville-Elgin,IL-IN-WI(-466,800). The largest over-the-year percentage losses in employment occurred in Atlantic City-Hammonton, NJ (-29.2 percent), Ocean City, NJ (-28.7 percent), and Kahului-Wailuku-Lahaina, HI (-26.5 percent). (See table 3 and map 2.)

Over the year, nonfarm employment declined in all of the 51 metropolitan areas with a 2010 Census population of 1 million or more. The largest over-the-year percentage decreases in employment in these large metropolitan areas occurred in New York-Newark-Jersey City, NY-NJ-PA(-15.4 percent), Boston-Cambridge-Nashua,MA-NH(-14.0 percent), and Las Vegas-Henderson-Paradise, NV (-13.8 percent).

Metropolitan Division Nonfarm Employment (Not Seasonally Adjusted)

In June, nonfarm payroll employment decreased in all of the 38 metropolitan divisions over the year. The largest over-the-year decrease in employment among the metropolitan divisions occurred in New York-JerseyCity-White Plains, NY-NJ(-1,148,300), followed by Los Angeles-LongBeach-Glendale, CA (-457,400), and Chicago-Naperville-Arlington Heights, IL (-366,300). (See table 4.)

The largest over-the-year percentage decreases in employment occurred in Haverhill-Newburyport- Amesbury Town, MA-NH(-16.9 percent), Lynn-Saugus-Marblehead, MA (-15.9 percent), and Lawrence-MethuenTown-Salem,MA-NH(-15.8 percent).

_____________

The State Employment and Unemployment news release for July is scheduled to be released on Friday, August 21, 2020, at 10:00 a.m. (ET). The Metropolitan Area Employment and Unemployment news release for July is scheduled to be released on Wednesday, September 2, 2020, at 10:00 a.m. (ET).

-2-

Coronavirus (COVID-19) Pandemic Impact on June 2020

Establishment and Household Survey Data

BLS has continued to review all estimation and methodological procedures for the establishment survey, which included the review of data, estimation processes, the application of the birth-death model, and seasonal adjustment. Business births and deaths cannot be adequately captured by the establishment survey as they occur. Therefore, the Current Employment Statistics (CES) program uses a model to account for the relatively stable net employment change generated by business births and deaths. Due to the impact of COVID-19, the relationship between business births and deaths is no longer stable. Typically, reports with zero employment are not included in estimation. For the May final and June preliminary estimates, CES included a portion of these reports in the estimates and made modifications to the birth-death model. In addition for both months, the establishment survey included a portion of the reports that returned to reporting positive employment from reporting zero employment. For more information, see www.bls.gov/web/empsit/cesbd.htm .

In the establishment survey, workers who are paid by their employer for all or any part of the pay period including the 12th of the month are counted as employed, even if they were not actually at their jobs. Workers who are temporarily or permanently absent from their jobs and are not being paid are not counted as employed, even if they are continuing to receive benefits. The length of the reference period does vary across the respondents in the establishment survey; one-third of businesses have a weekly pay period, slightly over 40 percent a bi-weekly, about 20 percent semi-monthly, and a small amount monthly.

For the June 2020 estimates of household employment and unemployment from the Local Area Unemployment Statistics (LAUS) program, BLS continued to implement level-shift outliers in the employment and/or unemployment inputs to the models, based on statistical evaluation of movements in each area's inputs. Both the Current Population Survey inputs, which serve as the primary inputs to the LAUS models, and the nonfarm payroll employment and unemployment insurance claims covariates were examined for outliers. The resulting implementation of level shifts preserved movements in the published estimates that the models otherwise would have discounted, without requiring changes to how the models create estimates at other points in the time series.

The "Frequently asked questions" document at www.bls.gov/cps/employment-situation-covid19-faq-june-2020.pdf extensively discusses the impact of a misclassification in the household survey on the national estimates for June 2020. Despite the considerable decline in its degree relative to prior months, this misclassification continued to be widespread geographically, with BLS analysis indicating that most states again were affected to at least some extent. However, according to usual practice, the data from the household survey are accepted as recorded. To maintain data integrity, no ad hoc actions are taken to reclassify survey responses. Hence, the household survey estimates of employed and unemployed people that serve as the primary inputs to the state models were affected to varying degrees by the misclassification, which in turn affected the official LAUS estimates for June 2020. Similar misclassifications had occurred in the household survey for March (see www.bls.gov/cps/employment- situation-covid19-faq-march-2020.pdf), April (see www.bls.gov/covid19/employment-situation-covid19-faq-april-2020.htm), and May (see www.bls.gov/covid19/employment-situation-covid19-faq-may-2020.htm).

-3-

Household data for substate areas are controlled to the employment and unemployment totals for their respective model-based areas. Hence, the preliminary June and revised May estimates for substate areas reflect the use of level-shift outliers, where implemented, in the inputs for their model-based control areas. The substate area estimates for both months also were impacted by misclassification in the household survey, in proportion to the impacts of the misclassifications on the data for their model- based control areas.

Household data for Puerto Rico are not modeled, but rather are derived from a monthly household survey similar to the Current Population Survey. Due to the effects of the pandemic and efforts to contain the virus, Puerto Rico had not been able to conduct its household survey for March or April 2020. Data collection resumed effective May 2020, and BLS resumed publication of data for Puerto Rico beginning with the State Employment and Unemployment news release for June 2020 on July 17, 2020. BLS is resuming publication of data for Puerto Rico's local areas beginning with this news release. The Puerto Rico Department of Labor reported a misclassification in its household survey for May and June similar in nature to the misclassification in the Current Population Survey, which affected the local area data proportionally.

-4-

Technical Note

This news release presents civilian labor force and unemployment data from the Local Area Unemployment Statistics (LAUS) program (tables 1 and 2) for 389 metropolitan statistical areas and metropolitan New England City and Town Areas (NECTAs), plus 7 areas in Puerto Rico. Estimates for 38 metropolitan and NECTA divisions also are presented. Nonfarm payroll employment estimates from the Current Employment Statistics (CES) program (tables 3 and 4) are provided for the same areas. State estimates were previously published in the news release State Employment and Unemployment, and are republished in this news release for ease of reference. The LAUS and CES programs are both federal-state cooperative endeavors.

Civilian labor force and unemployment-from the LAUS program

Definitions. The civilian labor force and unemployment data are based on the same concepts and definitions as those used for the official national estimates obtained from the Current Population Survey (CPS), a sample survey of households that is conducted for the Bureau of Labor Statistics (BLS) by the U.S. Census Bureau. The LAUS program measures employed persons and unemployed persons on a place-of-residence basis. The universe for each is the civilian noninstitutional population 16 years of age and older. Employed persons are those who did any work at all for pay or profit in the reference week (typically the week including the 12th of the month) or worked 15 hours or more without pay in a family business or farm, plus those not working who had a job from which they were temporarily absent, whether or not paid, for such reasons as labor-management dispute, illness, or vacation. Unemployed persons are those who were not employed during the reference week (based on the definition above), had actively looked for a job sometime in the 4-week period ending with the reference week, and were currently available for work; persons on layoff expecting recall need not be looking for work to be counted as unemployed. The civilian labor force is the sum of employed and unemployed persons. The unemployment rate is the number of unemployed as a percent of the civilian labor force.

Method of estimation. Estimates for states, the District of Columbia, the Los Angeles-LongBeach-Glendale metropolitan division, and New York City are produced using time-series models with real-time benchmarking to national CPS totals. Model-based estimates are also produced for the following areas and their respective balances: the Chicago- Naperville-Arlington Heights, IL Metropolitan Division; Cleveland-Elyria, OH Metropolitan Statistical Area; Detroit- Warren-Dearborn, MI Metropolitan Statistical Area; Miami- Miami Beach-Kendall, FL Metropolitan Division; and Seattle- Bellevue-Everett, WA Metropolitan Division. Modeling improves the statistical basis of the estimation for these areas and provides important tools for analysis, such as measures of errors and seasonally adjusted series. For all other substate

areas in this news release, estimates are prepared through indirect estimation procedures using a building-block approach. Estimates of employed persons, which are based largely on "place of work" estimates from the CES program, are adjusted to refer to place of residence as used in the CPS. Unemployment estimates are aggregates of persons previously employed in industries covered by state unemployment insurance (UI) laws and entrants to the labor force from the CPS. The substate estimates of employment and unemployment, which geographically exhaust the entire state, are adjusted proportionally to ensure that they add to the independently estimated model-based area totals. A detailed description of the estimation procedures is available from BLS upon request.

Annual revisions. Civilian labor force and unemployment data shown for the prior year reflect adjustments made at the beginning of each year, usually implemented with the issuance of January estimates. The adjusted model-based estimates typically reflect updated population data from the U.S. Census Bureau, any revisions in other input data sources, and model re-estimation. All substate estimates then are re-estimated using updated inputs and adjusted to add to the revised model-based totals. In early 2015, a new generation of time-series models was implemented, resulting in the replacement of data back to the series beginnings. At the same time, enhancements were made to the substate estimation methodology, and more timely inputs from the American Community Survey were incorporated.

Employment-from the CES program

Definitions. Employment data refer to persons on establishment payrolls who receive pay for any part of the pay period that includes the 12th of the month. Persons are counted at their place of work rather than at their place of residence; those appearing on more than one payroll are counted on each payroll. Industries are classified on the basis of their principal activity in accordance with the 2017 version of the North American Industry Classification System.

Method of estimation. CES State and Area employment data are produced using several estimation procedures. Where possible these data are produced using a "weighted link relative" estimation technique in which a ratio of current-month weighted employment to that of the previous-month weighted employment is computed from a sample of establishments reporting for both months. The estimates of employment for the current month are then obtained by multiplying these ratios by the previous month's employment estimates. The weighted link relative technique is utilized for data series where the sample size meets certain statistical criteria.

For some employment series, the sample of establishments is very small or highly variable. In these cases,

a model-based approach is used in estimation. These models use the direct sample estimates (described above), combined with forecasts of historical (benchmarked) data to decrease volatility in estimation. Two different models (Fay-Herriot Model and Small Domain Model) are used depending on the industry level being estimated. For more detailed information about each model, refer to the BLS Handbook of Methods.

Annual revisions. Employment estimates are adjusted annually to a complete count of jobs, called benchmarks, derived principally from tax reports that are submitted by employers who are covered under state unemployment insurance (UI) laws. The benchmark information is used to adjust the monthly estimates between the new benchmark and the preceding one and also to establish the level of employment for the new benchmark month. Thus, the benchmarking process establishes the level of employment, and the sample is used to measure the month-to-month changes in the level for the subsequent months.

Seasonal adjustment. Payroll employment data are seasonally adjusted for states, metropolitan areas, and metropolitan divisions at the total nonfarm level. For states, data are seasonally adjusted at the supersector level as well. Revisions to historical data for the most recent 5 years are made once a year, coincident with annual benchmark adjustments.

Payroll employment data are seasonally adjusted concurrently, using all available estimates, including those for the current month, to develop sample-based seasonal factors. Concurrent sample-based factors are created every month for the current month's preliminary estimate as well as the previous month's final estimate in order to incorporate real-time estimates.

Civilian labor force and unemployment estimates. Measures of sampling error are not available for metropolitan areas or metropolitan divisions. Model-basederror measures for states are available on the BLS website at www.bls.gov/lau/lastderr.htm. Measures of nonsampling error are not available for the areas contained in this news release. Information on recent data revisions for states and local areas is available online at www.bls.gov/lau/launews1.htm.

Employment estimates. Changes in metropolitan area nonfarm payroll employment are cited in the analysis of this news release only if they have been determined to be statistically significant at the 90-percent confidence level. Measures of sampling error for the total nonfarm employment series are available for metropolitan areas and metropolitan divisions at www.bls.gov/web/laus/790stderr.htm. Measures of sampling error for more detailed series at the area and division level are available upon request. Measures of sampling error for states at the supersector level and for the private service- providing, goods-producing, total private and total nonfarm levels are available on the BLS website at www.bls.gov/web/laus/790stderr.htm. Information on recent benchmark revisions is available online at www.bls.gov/web/laus/benchmark.pdf.

Area definitions

The substate area data published in this news release reflect the delineations issued by the U.S. Office of Management and Budget on April 10, 2018. Data reflect New England City and Town Area (NECTA) definitions, rather than county-based definitions, in the six New England States. A detailed list of the geographic definitions is available online at www.bls.gov/lau/lausmsa.htm.

Reliability of the estimates

The estimates presented in this news release are based on sample surveys, administrative data, and modeling and, thus, are subject to sampling and other types of errors. Sampling error is a measure of sampling variability-that is, variation that occurs by chance because a sample rather than the entire population is surveyed. Survey data also are subject to nonsampling errors, such as those which can be introduced into the data collection and processing operations. Estimates not directly derived from sample surveys are subject to additional errors resulting from the specific estimation processes used. The sums of individual items may not always equal the totals shown in the same tables because of rounding.

Use of error measures

Additional information

Estimates of unadjusted and seasonally adjusted civilian labor force and unemployment data for states and seven substate areas are available in the news release State Employment and Unemployment. Estimates of civilian labor force and unemployment for all states, metropolitan areas, counties, cities with a population of 25,000 or more, and other areas used in the administration of various federal economic assistance programs are available online at www.bls.gov/lau/. Employment data from the CES program are available on the BLS website at www.bls.gov/sae/.

Information in this news release will be made available to sensory impaired individuals upon request. Voice phone: (202) 691-5200; Federal Relay Service: (800) 877-8339.

LABOR FORCE DATA

NOT SEASONALLY ADJUSTED

Table 1. Civilian labor force and unemployment by state and metropolitan area

Civilian labor force

Unemployed

May

June

Number

Percent of labor force

State and area

2019

2020

2019

2020p

May

June

May

June

2019

2020

2019

2020p

2019

2020

2019

2020p

Alabama. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,232,314

2,235,610

2,246,030

2,204,545

55,339

204,935

73,570

176,036

2.5

9.2

3.3

8.0

Anniston-Oxford-Jacksonville. . . . . . . . . . .

46,092

45,149

46,355

44,212

1,363

5,220

1,784

4,147

3.0

11.6

3.8

9.4

Auburn-Opelika. . . . . . . . . . . . . . . . . . . . . . .

75,563

76,186

75,926

72,187

1,713

6,553

2,327

5,330

2.3

8.6

3.1

7.4

Birmingham-Hoover. . . . . . . . . . . . . . . . . . .

550,714

552,047

554,770

541,980

12,333

46,885

16,372

40,749

2.2

8.5

3.0

7.5

Daphne-Fairhope-Foley. . . . . . . . . . . . . . .

98,311

96,285

99,811

98,279

2,182

9,037

2,799

7,176

2.2

9.4

2.8

7.3

Decatur. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

72,232

69,500

72,755

69,193

1,571

5,282

2,147

4,401

2.2

7.6

3.0

6.4

Dothan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

63,836

62,324

64,481

62,391

1,636

4,845

2,146

4,403

2.6

7.8

3.3

7.1

Florence-Muscle Shoals. . . . . . . . . . . . . . .

66,144

65,011

66,072

64,208

1,897

6,545

2,556

5,056

2.9

10.1

3.9

7.9

Gadsden. . . . . . . . . . . . . . . . . . . . . . . . . . . .

42,724

41,743

42,958

40,996

1,171

5,053

1,595

3,952

2.7

12.1

3.7

9.6

Huntsville. . . . . . . . . . . . . . . . . . . . . . . . . . . .

228,208

225,244

228,912

222,645

4,835

16,567

6,548

14,205

2.1

7.4

2.9

6.4

Mobile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

187,604

190,718

189,001

187,724

5,796

23,140

7,554

21,591

3.1

12.1

4.0

11.5

Montgomery. . . . . . . . . . . . . . . . . . . . . . . . .

173,611

173,561

173,806

170,538

4,234

17,815

5,523

16,190

2.4

10.3

3.2

9.5

Tuscaloosa. . . . . . . . . . . . . . . . . . . . . . . . . .

117,726

120,602

117,757

114,818

2,883

13,038

3,902

10,432

2.4

10.8

3.3

9.1

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

348,619

334,106

355,191

350,583

21,029

41,953

22,261

43,062

6.0

12.6

6.3

12.3

Anchorage. . . . . . . . . . . . . . . . . . . . . . . . . . .

194,629

187,902

194,887

195,626

10,688

23,469

11,328

23,910

5.5

12.5

5.8

12.2

Fairbanks. . . . . . . . . . . . . . . . . . . . . . . . . . . .

44,943

43,026

44,424

43,854

2,378

4,415

2,420

4,580

5.3

10.3

5.4

10.4

Arizona. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,514,657

3,541,208

3,542,293

3,499,212

161,415

310,463

178,750

359,509

4.6

8.8

5.0

10.3

Flagstaff. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

76,964

70,186

78,032

70,333

3,874

8,238

4,594

9,338

5.0

11.7

5.9

13.3

Lake Havasu City-Kingman. . . . . . . . . . . .

87,815

88,464

88,783

85,201

4,793

12,077

5,233

10,882

5.5

13.7

5.9

12.8

Phoenix-Mesa-Scottsdale. . . . . . . . . . . . . .

2,468,113

2,499,631

2,490,205

2,471,241

98,991

207,061

109,300

240,696

4.0

8.3

4.4

9.7

Prescott. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

106,679

109,444

108,141

108,341

4,570

9,279

5,097

9,950

4.3

8.5

4.7

9.2

Sierra Vista-Douglas. . . . . . . . . . . . . . . . . .

50,168

51,250

50,239

50,587

2,748

3,680

3,039

4,449

5.5

7.2

6.0

8.8

Tucson. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

497,207

502,124

497,736

494,119

21,420

42,097

23,677

48,938

4.3

8.4

4.8

9.9

Yuma. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

96,746

92,032

96,187

92,592

16,631

16,733

18,137

20,191

17.2

18.2

18.9

21.8

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,363,674

1,349,503

1,376,830

1,329,793

45,702

127,087

52,458

109,561

3.4

9.4

3.8

8.2

Fayetteville-Springdale-Rogers. . . . . . . . .

279,152

277,485

280,387

273,583

6,717

19,885

7,694

17,424

2.4

7.2

2.7

6.4

Fort Smith. . . . . . . . . . . . . . . . . . . . . . . . . . .

119,110

119,688

120,421

115,429

4,016

13,713

4,690

8,522

3.4

11.5

3.9

7.4

Hot Springs. . . . . . . . . . . . . . . . . . . . . . . . . .

41,357

42,090

41,985

41,374

1,411

5,703

1,690

4,430

3.4

13.5

4.0

10.7

Jonesboro. . . . . . . . . . . . . . . . . . . . . . . . . . .

65,628

66,262

66,185

64,898

1,853

5,608

2,138

5,011

2.8

8.5

3.2

7.7

Little Rock-North Little Rock-Conway. . . .

358,949

354,363

362,917

349,070

10,789

36,235

12,176

30,991

3.0

10.2

3.4

8.9

Pine Bluff. . . . . . . . . . . . . . . . . . . . . . . . . . . .

34,899

34,637

35,190

34,233

1,807

3,476

2,019

3,246

5.2

10.0

5.7

9.5

California. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19,261,786

18,423,388

19,325,538

18,912,012

694,948

2,949,447

794,837

2,846,644

3.6

16.0

4.1

15.1

Bakersfield. . . . . . . . . . . . . . . . . . . . . . . . . . .

386,497

368,270

390,954

377,709

28,249

66,554

31,102

66,070

7.3

18.1

8.0

17.5

Chico. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

99,095

91,796

97,541

95,052

4,431

12,217

5,242

11,465

4.5

13.3

5.4

12.1

El Centro. . . . . . . . . . . . . . . . . . . . . . . . . . . .

70,532

71,751

71,901

73,995

11,698

19,864

13,142

20,191

16.6

27.7

18.3

27.3

Fresno. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

452,032

446,406

451,786

450,878

29,282

69,217

31,743

65,686

6.5

15.5

7.0

14.6

Hanford-Corcoran. . . . . . . . . . . . . . . . . . . . .

57,968

56,984

57,229

56,790

3,979

8,912

4,542

8,283

6.9

15.6

7.9

14.6

Los Angeles-LongBeach-Anaheim. . . . .

6,686,003

6,263,730

6,692,809

6,506,445

247,034

1,207,655

274,997

1,175,309

3.7

19.3

4.1

18.1

Madera. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

62,272

62,377

62,281

61,547

3,872

9,412

4,265

8,696

6.2

15.1

6.8

14.1

Merced. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

117,247

113,414

115,242

115,263

8,495

18,570

9,336

18,097

7.2

16.4

8.1

15.7

Modesto. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

242,732

232,106

242,761

235,818

13,606

37,616

15,409

35,421

5.6

16.2

6.3

15.0

Napa. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

74,257

72,137

75,059

74,216

1,730

10,461

2,067

9,240

2.3

14.5

2.8

12.5

Oxnard-ThousandOaks-Ventura. . . . . . .

422,230

405,527

421,387

411,859

12,732

55,428

15,163

51,984

3.0

13.7

3.6

12.6

Redding. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

73,885

71,000

74,445

72,761

2,984

9,211

3,402

8,398

4.0

13.0

4.6

11.5

Riverside-SanBernardino-Ontario. . . . . .

2,045,294

2,020,628

2,055,848

2,055,190

71,945

304,274

87,191

294,312

3.5

15.1

4.2

14.3

Sacramento--Roseville--Arden-Arcade. . .

1,090,489

1,068,326

1,096,850

1,085,291

34,625

146,424

40,851

139,317

3.2

13.7

3.7

12.8

Salinas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

229,342

200,202

231,689

204,625

11,086

33,169

11,019

29,556

4.8

16.6

4.8

14.4

San Diego-Carlsbad. . . . . . . . . . . . . . . . . .

1,576,186

1,549,978

1,582,682

1,580,385

44,141

235,733

52,870

219,248

2.8

15.2

3.3

13.9

San Francisco-Oakland-Hayward. . . . . . .

2,561,694

2,448,078

2,574,357

2,515,312

58,798

315,807

70,861

316,257

2.3

12.9

2.8

12.6

San Jose-Sunnyvale-Santa Clara. . . . . . .

1,074,494

1,042,646

1,081,065

1,071,314

24,105

118,219

29,140

115,178

2.2

11.3

2.7

10.8

San Luis Obispo-PasoRobles-Arroyo

Grande. . . . . . . . . . . . . . . . . . . . . . . . . . . .

141,818

130,428

142,111

131,852

3,450

16,789

4,239

15,193

2.4

12.9

3.0

11.5

Santa Cruz-Watsonville. . . . . . . . . . . . . . . .

142,122

130,694

144,904

132,624

5,732

19,033

6,112

17,307

4.0

14.6

4.2

13.0

Santa Maria-Santa Barbara. . . . . . . . . . . .

219,150

209,637

221,045

213,479

6,441

27,086

7,528

24,722

2.9

12.9

3.4

11.6

Santa Rosa. . . . . . . . . . . . . . . . . . . . . . . . . .

256,524

246,920

256,989

253,579

6,048

32,060

7,215

29,200

2.4

13.0

2.8

11.5

Stockton-Lodi. . . . . . . . . . . . . . . . . . . . . . . .

327,709

321,545

327,178

326,591

16,897

53,506

19,020

51,949

5.2

16.6

5.8

15.9

Vallejo-Fairfield. . . . . . . . . . . . . . . . . . . . . . .

208,198

199,928

209,064

202,366

6,888

28,756

8,063

27,670

3.3

14.4

3.9

13.7

Visalia-Porterville. . . . . . . . . . . . . . . . . . . . .

205,833

192,967

205,888

195,510

17,332

35,027

18,839

33,713

8.4

18.2

9.2

17.2

Yuba City. . . . . . . . . . . . . . . . . . . . . . . . . . . .

74,762

71,587

75,878

72,163

4,676

11,326

4,998

10,660

6.3

15.8

6.6

14.8

Colorado. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,119,482

3,055,723

3,162,311

3,189,798

80,659

306,981

92,508

340,422

2.6

10.0

2.9

10.7

Boulder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

197,793

195,128

195,857

199,071

4,175

16,125

5,160

18,831

2.1

8.3

2.6

9.5

Colorado Springs. . . . . . . . . . . . . . . . . . . . .

354,613

348,622

357,736

365,280

10,780

33,704

12,490

38,063

3.0

9.7

3.5

10.4

Denver-Aurora-Lakewood. . . . . . . . . . . . . .

1,664,907

1,640,291

1,690,123

1,713,692

41,279

171,888

47,514

189,200

2.5

10.5

2.8

11.0

Fort Collins. . . . . . . . . . . . . . . . . . . . . . . . . .

206,087

202,109

207,215

209,001

4,318

17,325

5,245

19,231

2.1

8.6

2.5

9.2

Grand Junction. . . . . . . . . . . . . . . . . . . . . . .

76,735

75,629

76,133

79,326

2,286

6,890

2,759

7,960

3.0

9.1

3.6

10.0

Greeley. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

169,182

164,569

168,997

169,810

3,799

14,191

4,713

17,072

2.2

8.6

2.8

10.1

Pueblo. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

76,192

74,046

76,305

77,572

2,880

6,747

3,255

8,352

3.8

9.1

4.3

10.8

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,905,616

1,777,738

1,925,633

1,887,870

67,905

167,737

74,192

188,487

3.6

9.4

3.9

10.0

Bridgeport-Stamford-Norwalk. . . . . . . . . . .

465,503

425,007

473,156

455,727

16,879

41,126

18,498

47,134

3.6

9.7

3.9

10.3

Danbury. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

106,690

98,867

108,232

106,074

3,147

8,711

3,501

9,541

2.9

8.8

3.2

9.0

Hartford-WestHartford-East Hartford. . . .

626,888

598,949

630,127

626,326

22,336

53,336

24,311

60,670

3.6

8.9

3.9

9.7

New Haven. . . . . . . . . . . . . . . . . . . . . . . . . .

327,625

308,045

329,978

328,367

11,383

26,166

12,541

29,990

3.5

8.5

3.8

9.1

See footnotes at end of table.

LABOR FORCE DATA

NOT SEASONALLY ADJUSTED

Table 1. Civilian labor force and unemployment by state and metropolitan area - Continued

Civilian labor force

Unemployed

May

June

Number

Percent of labor force

State and area

2019

2020

2019

2020p

May

June

May

June

2019

2020

2019

2020p

2019

2020

2019

2020p

Connecticut - Continued

Norwich-NewLondon-Westerly. . . . . . . . .

141,989

127,745

144,539

140,396

4,910

19,113

5,340

18,321

3.5

15.0

3.7

13.0

Waterbury. . . . . . . . . . . . . . . . . . . . . . . . . . .

111,320

103,274

112,484

109,849

4,892

10,732

5,215

12,434

4.4

10.4

4.6

11.3

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

484,877

471,396

490,751

491,813

16,258

73,086

19,899

62,574

3.4

15.5

4.1

12.7

Dover. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

78,676

79,530

79,134

82,123

2,934

13,382

3,745

11,559

3.7

16.8

4.7

14.1

Salisbury1. . . . . . . . . . . . . . . . . . . . . . . . . . .

194,722

184,235

204,404

195,431

7,386

27,377

8,566

20,700

3.8

14.9

4.2

10.6

District of Columbia. . . . . . . . . . . . . . . . . . . . .

408,260

386,742

412,636

397,766

21,301

32,680

24,062

35,673

5.2

8.5

5.8

9.0

Washington-Arlington-Alexandria. . . . . . .

3,452,965

3,358,412

3,489,162

3,437,663

103,578

299,108

115,882

288,117

3.0

8.9

3.3

8.4

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

10,297,648

9,651,892

10,318,834

9,789,069

310,611

1,304,072

344,231

1,045,481

3.0

13.5

3.3

10.7

Cape Coral-Fort Myers. . . . . . . . . . . . . . . .

345,234

327,399

344,466

333,525

10,504

42,587

11,891

32,564

3.0

13.0

3.5

9.8

Crestview-Fort Walton Beach-Destin. . . .

130,028

118,874

132,666

121,797

3,336

11,775

3,770

7,957

2.6

9.9

2.8

6.5

Deltona-DaytonaBeach-Ormond

Beach. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

301,334

284,512

301,711

288,978

10,311

38,103

11,386

28,141

3.4

13.4

3.8

9.7

Gainesville. . . . . . . . . . . . . . . . . . . . . . . . . . .

144,214

132,317

143,534

133,233

4,082

10,529

4,779

8,913

2.8

8.0

3.3

6.7

Homosassa Springs. . . . . . . . . . . . . . . . . . .

47,445

45,788

47,675

45,375

2,241

6,082

2,445

4,646

4.7

13.3

5.1

10.2

Jacksonville. . . . . . . . . . . . . . . . . . . . . . . . . .

779,073

732,457

787,160

748,074

23,447

75,823

26,777

59,589

3.0

10.4

3.4

8.0

Lakeland-Winter Haven. . . . . . . . . . . . . . . .

303,558

308,461

305,166

305,336

10,843

54,406

12,214

43,006

3.6

17.6

4.0

14.1

Miami-FortLauderdale-West Palm

Beach. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,147,395

2,876,540

3,144,322

2,940,463

87,247

384,706

93,941

333,308

2.8

13.4

3.0

11.3

Naples-Immokalee-Marco Island. . . . . . . .

179,247

165,796

175,950

167,339

5,080

20,467

5,867

16,214

2.8

12.3

3.3

9.7

North Port-Sarasota-Bradenton. . . . . . . . .

369,376

340,405

368,704

347,853

11,023

41,449

12,399

30,335

3.0

12.2

3.4

8.7

Ocala. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

137,269

132,803

137,956

133,949

5,136

14,185

5,736

11,392

3.7

10.7

4.2

8.5

Orlando-Kissimmee-Sanford. . . . . . . . . . .

1,355,270

1,304,400

1,364,425

1,302,852

39,214

274,723

43,960

215,052

2.9

21.1

3.2

16.5

Palm Bay-Melbourne-Titusville. . . . . . . . .

282,542

270,705

285,268

275,711

8,751

31,269

9,696

23,466

3.1

11.6

3.4

8.5

Panama City. . . . . . . . . . . . . . . . . . . . . . . . .

90,967

83,747

92,381

85,592

3,479

8,598

3,601

6,041

3.8

10.3

3.9

7.1

Pensacola-FerryPass-Brent. . . . . . . . . . .

228,632

210,410

229,761

214,928

6,740

21,225

7,758

15,962

2.9

10.1

3.4

7.4

Port St. Lucie. . . . . . . . . . . . . . . . . . . . . . . .

219,760

209,603

219,042

211,679

7,804

25,243

8,719

19,722

3.6

12.0

4.0

9.3

Punta Gorda. . . . . . . . . . . . . . . . . . . . . . . . .

71,663

67,918

71,458

68,617

2,556

8,475

2,775

6,476

3.6

12.5

3.9

9.4

Sebastian-Vero Beach. . . . . . . . . . . . . . . .

65,226

61,054

65,296

61,039

2,413

7,639

2,707

5,911

3.7

12.5

4.1

9.7

Sebring. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

36,326

34,651

36,110

34,805

1,590

3,584

1,768

3,204

4.4

10.3

4.9

9.2

Tallahassee. . . . . . . . . . . . . . . . . . . . . . . . . .

193,099

175,098

192,252

178,465

5,833

14,114

6,747

12,695

3.0

8.1

3.5

7.1

Tampa-St.Petersburg-Clearwater. . . . . .

1,546,072

1,465,931

1,554,392

1,486,272

47,885

178,392

52,744

136,374

3.1

12.2

3.4

9.2

The Villages. . . . . . . . . . . . . . . . . . . . . . . . .

32,657

30,844

32,753

31,242

1,489

3,670

1,637

3,046

4.6

11.9

5.0

9.7

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5,085,861

4,893,313

5,101,635

4,933,551

168,072

449,696

193,000

392,073

3.3

9.2

3.8

7.9

Albany. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

66,217

62,899

66,302

63,519

2,729

5,308

3,152

5,064

4.1

8.4

4.8

8.0

Athens-Clarke County. . . . . . . . . . . . . . . . .

98,265

94,990

97,409

94,246

3,068

7,609

3,695

6,260

3.1

8.0

3.8

6.6

Atlanta-SandySprings-Roswell. . . . . . . . .

3,071,436

2,944,868

3,088,537

2,990,486

97,732

291,709

111,677

257,668

3.2

9.9

3.6

8.6

Augusta-Richmond County. . . . . . . . . . . . .

267,303

259,513

268,204

259,836

9,296

22,661

10,685

18,595

3.5

8.7

4.0

7.2

Brunswick. . . . . . . . . . . . . . . . . . . . . . . . . . .

52,943

46,410

53,192

46,135

1,735

4,908

1,949

3,638

3.3

10.6

3.7

7.9

Columbus. . . . . . . . . . . . . . . . . . . . . . . . . . . .

123,567

116,215

123,369

117,280

4,703

11,270

5,450

10,158

3.8

9.7

4.4

8.7

Dalton. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

58,494

57,445

58,826

56,067

2,232

6,283

2,653

4,248

3.8

10.9

4.5

7.6

Gainesville. . . . . . . . . . . . . . . . . . . . . . . . . . .

101,369

96,713

101,625

96,260

2,752

7,380

3,199

5,642

2.7

7.6

3.1

5.9

Hinesville. . . . . . . . . . . . . . . . . . . . . . . . . . . .

34,233

33,195

33,879

33,478

1,294

2,403

1,449

2,166

3.8

7.2

4.3

6.5

Macon-Bibb County. . . . . . . . . . . . . . . . . . .

102,569

96,999

102,942

97,516

3,753

8,356

4,292

7,406

3.7

8.6

4.2

7.6

Rome. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

43,562

44,138

43,887

44,098

1,518

3,926

1,752

3,085

3.5

8.9

4.0

7.0

Savannah. . . . . . . . . . . . . . . . . . . . . . . . . . . .

188,911

180,170

189,824

181,956

5,779

19,393

6,656

15,708

3.1

10.8

3.5

8.6

Valdosta. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

63,416

60,959

63,309

61,740

2,051

4,621

2,481

3,936

3.2

7.6

3.9

6.4

Warner Robins. . . . . . . . . . . . . . . . . . . . . . .

86,152

80,538

86,516

80,679

2,876

5,521

3,310

5,007

3.3

6.9

3.8

6.2

Hawaii. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

660,719

624,626

665,587

615,118

17,075

146,131

22,078

88,774

2.6

23.4

3.3

14.4

Kahului-Wailuku-Lahaina. . . . . . . . . . . . . .

85,892

84,771

87,202

79,765

2,116

28,835

2,710

17,995

2.5

34.0

3.1

22.6

Urban Honolulu. . . . . . . . . . . . . . . . . . . . . . .

447,027

417,414

450,087

414,849

11,119

86,678

14,402

52,063

2.5

20.8

3.2

12.5

Idaho. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

879,900

883,170

891,130

902,551

22,733

76,117

23,779

48,142

2.6

8.6

2.7

5.3

Boise City. . . . . . . . . . . . . . . . . . . . . . . . . . .

374,019

380,505

378,088

388,774

9,259

35,159

10,106

22,071

2.5

9.2

2.7

5.7

Coeur d'Alene. . . . . . . . . . . . . . . . . . . . . . . .

80,622

79,535

81,852

79,955

2,348

8,919

2,379

5,470

2.9

11.2

2.9

6.8

Idaho Falls. . . . . . . . . . . . . . . . . . . . . . . . . . .

72,369

75,263

73,476

77,147

1,548

4,155

1,585

2,776

2.1

5.5

2.2

3.6

Lewiston. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

31,260

29,091

31,385

29,697

902

2,428

934

1,603

2.9

8.3

3.0

5.4

Pocatello. . . . . . . . . . . . . . . . . . . . . . . . . . . .

43,094

40,211

42,500

40,817

1,087

3,101

1,123

1,989

2.5

7.7

2.6

4.9

Twin Falls. . . . . . . . . . . . . . . . . . . . . . . . . . .

53,234

52,917

53,971

55,058

1,334

4,126

1,408

2,666

2.5

7.8

2.6

4.8

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6,416,363

6,283,576

6,517,399

6,559,573

222,493

931,965

267,575

958,349

3.5

14.8

4.1

14.6

Bloomington. . . . . . . . . . . . . . . . . . . . . . . . .

95,642

87,520

94,703

90,648

3,013

9,675

3,627

9,610

3.2

11.1

3.8

10.6

Carbondale-Marion. . . . . . . . . . . . . . . . . . .

59,666

58,026

58,579

59,023

2,025

8,839

2,378

7,277

3.4

15.2

4.1

12.3

Champaign-Urbana. . . . . . . . . . . . . . . . . . .

124,671

115,598

119,703

118,681

4,009

11,690

4,660

12,090

3.2

10.1

3.9

10.2

Chicago-Naperville-Elgin. . . . . . . . . . . . . . .

4,828,532

4,806,063

4,930,924

5,006,583

163,684

733,053

200,045

780,308

3.4

15.3

4.1

15.6

Danville. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33,026

31,983

33,223

33,504

1,396

4,496

1,584

4,105

4.2

14.1

4.8

12.3

Davenport-Moline-Rock Island1. . . . . . . . .

194,940

189,774

197,693

194,173

6,858

27,411

7,775

21,577

3.5

14.4

3.9

11.1

Decatur. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

49,294

44,732

49,456

48,053

2,118

6,702

2,565

6,943

4.3

15.0

5.2

14.4

Kankakee. . . . . . . . . . . . . . . . . . . . . . . . . . . .

55,598

53,484

56,391

56,900

2,225

7,238

2,481

6,833

4.0

13.5

4.4

12.0

Peoria. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

176,275

159,176

177,832

169,289

6,776

24,489

7,731

22,874

3.8

15.4

4.3

13.5

Rockford. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

165,285

160,488

167,898

165,995

8,355

31,244

9,164

26,518

5.1

19.5

5.5

16.0

Springfield. . . . . . . . . . . . . . . . . . . . . . . . . . .

107,826

101,000

109,454

107,092

3,547

13,221

4,179

12,609

3.3

13.1

3.8

11.8

Indiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,382,235

3,350,607

3,413,468

3,433,664

99,835

398,272

114,185

383,935

3.0

11.9

3.3

11.2

Bloomington. . . . . . . . . . . . . . . . . . . . . . . . .

80,392

79,973

76,121

79,744

2,456

6,352

2,886

7,191

3.1

7.9

3.8

9.0

Columbus. . . . . . . . . . . . . . . . . . . . . . . . . . . .

44,899

45,662

45,511

45,608

1,028

5,782

1,180

4,843

2.3

12.7

2.6

10.6

See footnotes at end of table.

LABOR FORCE DATA

NOT SEASONALLY ADJUSTED

Table 1. Civilian labor force and unemployment by state and metropolitan area - Continued

Civilian labor force

Unemployed

May

June

Number

Percent of labor force

State and area

2019

2020

2019

2020p

May

June

May

June

2019

2020

2019

2020p

2019

2020

2019

2020p

Indiana - Continued

Elkhart-Goshen. . . . . . . . . . . . . . . . . . . . . . .

113,356

108,353

115,752

110,293

3,090

12,799

3,583

11,996

2.7

11.8

3.1

10.9

Evansville. . . . . . . . . . . . . . . . . . . . . . . . . . . .

162,514

166,977

166,004

168,086

4,695

17,884

5,390

15,727

2.9

10.7

3.2

9.4

Fort Wayne. . . . . . . . . . . . . . . . . . . . . . . . . .

218,391

222,132

222,074

221,434

5,980

29,984

6,885

25,538

2.7

13.5

3.1

11.5

Indianapolis-Carmel-Anderson. . . . . . . . . .

1,068,726

1,048,267

1,083,451

1,095,064

29,520

107,349

33,673

115,631

2.8

10.2

3.1

10.6

Kokomo. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

36,160

41,547

36,204

39,549

1,213

9,322

1,365

6,638

3.4

22.4

3.8

16.8

Lafayette-West Lafayette. . . . . . . . . . . . . .

114,076

107,767

111,211

108,256

3,035

12,589

3,524

10,548

2.7

11.7

3.2

9.7

Michigan City-La Porte. . . . . . . . . . . . . . . .

48,002

49,631

48,878

51,798

1,757

7,448

1,996

8,088

3.7

15.0

4.1

15.6

Muncie. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

53,492

52,374

52,488

52,819

1,880

6,279

2,171

6,014

3.5

12.0

4.1

11.4

South Bend-Mishawaka. . . . . . . . . . . . . . .

161,273

156,202

161,917

161,385

5,376

21,462

6,294

21,528

3.3

13.7

3.9

13.3

Terre Haute. . . . . . . . . . . . . . . . . . . . . . . . . .

76,122

73,854

76,034

75,010

2,878

8,602

3,196

8,506

3.8

11.6

4.2

11.3

Iowa. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,726,212

1,688,213

1,750,382

1,651,843

41,050

167,567

48,303

130,982

2.4

9.9

2.8

7.9

Ames. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

59,824

54,696

56,480

53,948

1,007

3,879

1,379

3,273

1.7

7.1

2.4

6.1

Cedar Rapids. . . . . . . . . . . . . . . . . . . . . . . .

147,578

145,261

150,044

141,730

3,703

16,136

4,342

12,985

2.5

11.1

2.9

9.2

Des Moines-West Des Moines. . . . . . . . .

364,004

354,119

370,835

349,143

8,821

38,488

10,330

30,681

2.4

10.9

2.8

8.8

Dubuque. . . . . . . . . . . . . . . . . . . . . . . . . . . .

56,823

54,847

56,757

53,335

1,185

6,934

1,353

4,617

2.1

12.6

2.4

8.7

Iowa City. . . . . . . . . . . . . . . . . . . . . . . . . . . .

98,338

96,030

99,446

96,526

1,956

8,660

2,326

6,963

2.0

9.0

2.3

7.2

Sioux City. . . . . . . . . . . . . . . . . . . . . . . . . . .

92,739

92,335

94,570

91,161

2,246

8,016

2,736

6,716

2.4

8.7

2.9

7.4

Waterloo-Cedar Falls. . . . . . . . . . . . . . . . . .

90,627

89,973

90,789

87,013

2,292

9,961

2,631

7,217

2.5

11.1

2.9

8.3

Kansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,475,384

1,498,549

1,498,185

1,495,009

44,053

148,024

48,792

113,134

3.0

9.9

3.3

7.6

Lawrence. . . . . . . . . . . . . . . . . . . . . . . . . . . .

65,900

66,431

62,085

61,904

1,770

6,885

1,987

5,148

2.7

10.4

3.2

8.3

Manhattan. . . . . . . . . . . . . . . . . . . . . . . . . . .

48,122

45,811

44,736

42,398

1,256

3,412

1,357

3,092

2.6

7.4

3.0

7.3

Topeka. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

118,306

118,707

121,816

118,947

3,562

11,387

3,901

8,534

3.0

9.6

3.2

7.2

Wichita. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

313,521

329,145

317,999

321,711

10,050

46,370

11,109

34,723

3.2

14.1

3.5

10.8

Kentucky. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,074,273

2,037,060

2,099,909

1,950,426

86,279

217,891

101,143

94,543

4.2

10.7

4.8

4.8

Bowling Green. . . . . . . . . . . . . . . . . . . . . . .

84,770

79,220

85,136

74,625

3,221

9,477

3,960

3,772

3.8

12.0

4.7

5.1

Elizabethtown-Fort Knox. . . . . . . . . . . . . . .

67,577

67,712

68,761

64,259

2,748

8,306

3,247

3,222

4.1

12.3

4.7

5.0

Lexington-Fayette. . . . . . . . . . . . . . . . . . . . .

275,910

269,081

279,154

259,439

9,269

24,360

10,946

10,967

3.4

9.1

3.9

4.2

Louisville/Jefferson County. . . . . . . . . . . . .

672,675

646,313

682,869

646,247

25,026

76,274

28,782

41,244

3.7

11.8

4.2

6.4

Owensboro. . . . . . . . . . . . . . . . . . . . . . . . . .

55,829

54,251

56,338

53,575

2,164

5,593

2,499

2,227

3.9

10.3

4.4

4.2

Louisiana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,085,409

2,026,083

2,116,798

2,021,602

89,769

282,453

117,592

211,623

4.3

13.9

5.6

10.5

Alexandria. . . . . . . . . . . . . . . . . . . . . . . . . . .

62,679

61,141

64,011

60,888

2,868

6,024

3,756

4,608

4.6

9.9

5.9

7.6

Baton Rouge. . . . . . . . . . . . . . . . . . . . . . . . .

415,382

406,143

419,912

400,662

16,249

51,213

21,588

38,548

3.9

12.6

5.1

9.6

Hammond. . . . . . . . . . . . . . . . . . . . . . . . . . .

53,707

54,341

54,574

54,071

2,633

9,288

3,572

6,866

4.9

17.1

6.5

12.7

Houma-Thibodaux. . . . . . . . . . . . . . . . . . . .

87,968

85,401

88,995

85,254

3,668

9,916

4,686

7,521

4.2

11.6

5.3

8.8

Lafayette. . . . . . . . . . . . . . . . . . . . . . . . . . . .

211,142

206,718

214,706

209,165

9,114

25,730

11,678

19,269

4.3

12.4

5.4

9.2

Lake Charles. . . . . . . . . . . . . . . . . . . . . . . . .

110,653

105,509

112,499

103,360

3,986

14,809

5,221

10,314

3.6

14.0

4.6

10.0

Monroe. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

78,909

77,666

79,492

77,082

3,823

8,906

4,811

6,883

4.8

11.5

6.1

8.9

New Orleans-Metairie. . . . . . . . . . . . . . . . .

592,915

575,489

602,602

574,918

23,838

100,210

31,398

74,166

4.0

17.4

5.2

12.9

Shreveport-Bossier City. . . . . . . . . . . . . . .

184,936

180,783

188,535

182,229

8,520

24,034

11,125

17,986

4.6

13.3

5.9

9.9

Maine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

688,088

662,567

701,100

678,778

20,644

62,510

19,348

43,379

3.0

9.4

2.8

6.4

Bangor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

70,649

67,512

70,597

67,945

2,008

6,187

1,930

4,053

2.8

9.2

2.7

6.0

Lewiston-Auburn. . . . . . . . . . . . . . . . . . . . . .

55,447

54,290

55,821

54,244

1,600

5,046

1,562

3,617

2.9

9.3

2.8

6.7

Portland-South Portland. . . . . . . . . . . . . . .

207,483

195,826

211,982

201,134

4,984

20,309

4,874

13,528

2.4

10.4

2.3

6.7

Maryland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,244,597

3,106,005

3,285,538

3,229,628

111,054

302,371

126,624

267,300

3.4

9.7

3.9

8.3

Baltimore-Columbia-Towson. . . . . . . . . . .

1,517,116

1,441,783

1,536,254

1,501,034

53,100

139,344

60,333

119,959

3.5

9.7

3.9

8.0

California-Lexington Park. . . . . . . . . . . . . .

57,083

53,988

57,742

55,825

1,757

3,650

2,064

3,314

3.1

6.8

3.6

5.9

Cumberland. . . . . . . . . . . . . . . . . . . . . . . . . .

45,114

42,237

45,284

43,173

2,020

4,766

2,620

4,167

4.5

11.3

5.8

9.7

Hagerstown-Martinsburg. . . . . . . . . . . . . . .

132,550

127,397

134,893

130,509

4,674

13,320

5,332

10,991

3.5

10.5

4.0

8.4

Massachusetts. . . . . . . . . . . . . . . . . . . . . . . . .

3,790,731

3,525,512

3,851,461

3,713,361

109,174

582,796

120,601

648,604

2.9

16.5

3.1

17.5

Barnstable Town. . . . . . . . . . . . . . . . . . . . .

126,942

114,761

136,713

125,147

4,173

22,489

4,335

23,123

3.3

19.6

3.2

18.5

Boston-Cambridge-Nashua. . . . . . . . . . . .

2,809,844

2,615,118

2,852,718

2,743,087

74,261

422,746

82,005

462,978

2.6

16.2

2.9

16.9

Leominster-Gardner. . . . . . . . . . . . . . . . . . .

80,387

76,053

81,019

80,871

2,619

13,299

2,927

15,145

3.3

17.5

3.6

18.7

New Bedford. . . . . . . . . . . . . . . . . . . . . . . . .

85,665

84,158

86,843

86,971

3,533

18,016

3,941

18,251

4.1

21.4

4.5

21.0

Pittsfield. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

42,657

39,426

44,385

41,775

1,501

6,796

1,604

7,329

3.5

17.2

3.6

17.5

Springfield. . . . . . . . . . . . . . . . . . . . . . . . . . .

377,675

343,170

378,212

360,839

13,439

53,703

15,134

61,314

3.6

15.6

4.0

17.0

Worcester. . . . . . . . . . . . . . . . . . . . . . . . . . .

361,479

337,758

364,616

356,459

11,444

50,072

12,620

56,236

3.2

14.8

3.5

15.8

Michigan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4,923,525

4,765,123

4,971,319

4,993,785

184,604

991,814

212,011

743,803

3.7

20.8

4.3

14.9

Ann Arbor. . . . . . . . . . . . . . . . . . . . . . . . . . .

197,099

197,655

196,456

209,165

5,612

27,391

6,672

22,037

2.8

13.9

3.4

10.5

Battle Creek. . . . . . . . . . . . . . . . . . . . . . . . .

62,580

64,919

63,134

65,658

2,420

14,500

2,824

9,961

3.9

22.3

4.5

15.2

Bay City. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

50,110

50,609

50,736

51,642

2,134

10,092

2,473

7,060

4.3

19.9

4.9

13.7

Detroit-Warren-Dearborn. . . . . . . . . . . . . .

2,139,667

1,935,243

2,159,216

2,053,738

82,283

460,482

95,839

366,269

3.8

23.8

4.4

17.8

Flint. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

181,436

193,348

185,201

196,253

10,215

47,743

9,949

31,862

5.6

24.7

5.4

16.2

Grand Rapids-Wyoming. . . . . . . . . . . . . . .

583,537

584,403

589,196

613,794

16,206

99,867

19,094

73,168

2.8

17.1

3.2

11.9

Jackson. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

74,728

76,762

74,817

78,649

2,533

15,533

3,058

11,339

3.4

20.2

4.1

14.4

Kalamazoo-Portage. . . . . . . . . . . . . . . . . . .

168,589

169,692

169,797

178,704

5,663

26,330

6,535

21,029

3.4

15.5

3.8

11.8

Lansing-East Lansing. . . . . . . . . . . . . . . . .

252,387

246,998

246,625

255,254

7,738

41,134

9,231

28,716

3.1

16.7

3.7

11.2

Midland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

40,752

40,430

41,049

42,395

1,381

6,407

1,609

4,627

3.4

15.8

3.9

10.9

Monroe. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

76,340

77,904

76,171

78,375

3,091

16,673

3,039

10,353

4.0

21.4

4.0

13.2

Muskegon. . . . . . . . . . . . . . . . . . . . . . . . . . .

77,086

83,386

78,937

85,195

3,047

20,641

3,556

15,026

4.0

24.8

4.5

17.6

Niles-Benton Harbor. . . . . . . . . . . . . . . . . .

74,374

75,747

75,435

79,465

2,798

14,027

3,379

10,914

3.8

18.5

4.5

13.7

Saginaw. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

86,642

89,049

87,792

91,173

3,970

18,532

4,325

13,241

4.6

20.8

4.9

14.5

See footnotes at end of table.

LABOR FORCE DATA

NOT SEASONALLY ADJUSTED

Table 1. Civilian labor force and unemployment by state and metropolitan area - Continued

Civilian labor force

Unemployed

May

June

Number

Percent of labor force

State and area

2019

2020

2019

2020p

May

June

May

June

2019

2020

2019

2020p

2019

2020

2019

2020p

Minnesota. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,094,150

3,062,634

3,126,861

3,135,487

83,114

287,254

101,099

267,680

2.7

9.4

3.2

8.5

Duluth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

143,174

142,783

143,200

145,463

4,999

17,666

5,795

14,800

3.5

12.4

4.0

10.2

Mankato-North Mankato. . . . . . . . . . . . . . .

61,865

60,691

61,293

63,083

1,484

4,956

1,817

4,625

2.4

8.2

3.0

7.3

Minneapolis-St.Paul-Bloomington. . . . . .

2,012,906

2,003,350

2,037,819

2,048,839

51,769

201,616

63,618

188,123

2.6

10.1

3.1

9.2

Rochester. . . . . . . . . . . . . . . . . . . . . . . . . . .

124,441

126,743

125,968

128,861

2,926

11,808

3,620

10,347

2.4

9.3

2.9

8.0

St. Cloud. . . . . . . . . . . . . . . . . . . . . . . . . . . .

113,041

113,663

112,317

116,508

3,003

9,957

3,517

8,722

2.7

8.8

3.1

7.5

Mississippi. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,277,185

1,212,017

1,292,689

1,211,136

67,760

125,942

83,202

117,760

5.3

10.4

6.4

9.7

Gulfport-Biloxi-Pascagoula. . . . . . . . . . . . .

163,943

159,337

166,586

159,768

8,813

23,521

10,538

17,159

5.4

14.8

6.3

10.7

Hattiesburg. . . . . . . . . . . . . . . . . . . . . . . . . .

67,817

64,386

67,827

63,870

3,264

5,712

3,904

5,546

4.8

8.9

5.8

8.7

Jackson. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

267,911

254,335

270,897

254,042

12,727

25,563

15,600

23,562

4.8

10.1

5.8

9.3

Missouri. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,072,393

3,015,099

3,108,213

3,052,057

91,760

295,828

104,362

242,135

3.0

9.8

3.4

7.9

Cape Girardeau. . . . . . . . . . . . . . . . . . . . . .

48,399

45,031

48,795

45,088

1,401

4,049

1,681

3,223

2.9

9.0

3.4

7.1

Columbia. . . . . . . . . . . . . . . . . . . . . . . . . . . .

98,620

94,580

96,112

95,157

2,221

6,183

2,536

5,437

2.3

6.5

2.6

5.7

Jefferson City. . . . . . . . . . . . . . . . . . . . . . . .

74,753

73,487

75,277

73,616

1,812

4,381

2,170

4,109

2.4

6.0

2.9

5.6

Joplin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

83,996

83,502

84,416

84,109

2,468

7,466

2,777

6,037

2.9

8.9

3.3

7.2

Kansas City. . . . . . . . . . . . . . . . . . . . . . . . . .

1,128,980

1,121,107

1,152,837

1,133,613

33,634

121,298

37,689

88,096

3.0

10.8

3.3

7.8

St. Joseph. . . . . . . . . . . . . . . . . . . . . . . . . . .

62,872

61,030

64,060

62,193

1,723

4,043

2,027

3,564

2.7

6.6

3.2

5.7

St. Louis2. . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,465,940

1,427,683

1,490,157

1,456,573

43,458

160,797

50,765

141,076

3.0

11.3

3.4

9.7

Springfield. . . . . . . . . . . . . . . . . . . . . . . . . . .

234,519

229,502

235,326

234,579

6,114

18,794

6,617

17,161

2.6

8.2

2.8

7.3

Montana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

532,019

523,912

539,659

542,444

15,197

44,587

18,106

37,988

2.9

8.5

3.4

7.0

Billings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

87,611

85,581

88,323

89,595

2,288

6,741

2,988

5,963

2.6

7.9

3.4

6.7

Great Falls. . . . . . . . . . . . . . . . . . . . . . . . . . .

38,071

37,557

38,463

38,739

1,061

3,047

1,293

2,683

2.8

8.1

3.4

6.9

Missoula. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

64,193

64,615

64,333

66,814

1,646

6,008

1,907

4,900

2.6

9.3

3.0

7.3

Nebraska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,037,150

1,034,364

1,047,089

1,069,792

30,785

53,515

34,683

73,350

3.0

5.2

3.3

6.9

Grand Island. . . . . . . . . . . . . . . . . . . . . . . . .

44,221

44,050

44,721

44,571

1,319

3,288

1,486

3,396

3.0

7.5

3.3

7.6

Lincoln. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

185,818

186,682

184,484

191,306

5,197

9,656

5,892

13,326

2.8

5.2

3.2

7.0

Omaha-Council Bluffs. . . . . . . . . . . . . . . . .

494,733

489,874

499,939

504,687

14,737

31,372

16,414

40,744

3.0

6.4

3.3

8.1

Nevada. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,538,540

1,382,240

1,543,666

1,500,295

59,063

347,106

63,748

227,581

3.8

25.1

4.1

15.2

Carson City. . . . . . . . . . . . . . . . . . . . . . . . . .

26,393

22,729

26,575

25,080

1,013

3,462

1,058

2,099

3.8

15.2

4.0

8.4

Las Vegas-Henderson-Paradise. . . . . . . .

1,129,068

1,019,238

1,130,891

1,088,462

45,344

293,895

49,377

196,448

4.0

28.8

4.4

18.0

Reno. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

256,741

221,407

258,026

241,442

7,992

35,481

8,377

20,699

3.1

16.0

3.2

8.6

New Hampshire. . . . . . . . . . . . . . . . . . . . . . . .

768,801

730,536

781,077

754,781

18,515

111,950

19,442

88,100

2.4

15.3

2.5

11.7

Dover-Durham. . . . . . . . . . . . . . . . . . . . . . .

86,530

81,060

86,300

82,490

1,860

11,504

1,978

8,941

2.1

14.2

2.3

10.8

Manchester. . . . . . . . . . . . . . . . . . . . . . . . . .

123,310

119,812

123,274

123,944

2,829

18,872

2,979

14,995

2.3

15.8

2.4

12.1

Portsmouth. . . . . . . . . . . . . . . . . . . . . . . . . .

76,934

71,393

79,437

74,800

1,676

9,262

1,742

7,153

2.2

13.0

2.2

9.6

New Jersey. . . . . . . . . . . . . . . . . . . . . . . . . . . .

4,443,339

4,515,845

4,508,811

4,562,048

133,039

681,014

147,120

746,530

3.0

15.1

3.3

16.4

Atlantic City-Hammonton. . . . . . . . . . . . . .

118,905

123,110

122,278

129,318

4,981

40,061

5,413

44,322

4.2

32.5

4.4

34.3

Ocean City. . . . . . . . . . . . . . . . . . . . . . . . . . .

45,722

43,185

53,261

46,630

2,302

9,747

2,260

9,347

5.0

22.6

4.2

20.0

Trenton. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

200,414

203,684

203,279

201,061

5,307

21,521

6,058

24,212

2.6

10.6

3.0

12.0

Vineland-Bridgeton. . . . . . . . . . . . . . . . . . . .

66,272

67,865

65,373

66,401

2,858

10,253

3,118

11,115

4.3

15.1

4.8

16.7

New Mexico. . . . . . . . . . . . . . . . . . . . . . . . . . . .

944,675

898,698

958,214

927,685

42,160

78,436

52,893

83,390

4.5

8.7

5.5

9.0

Albuquerque. . . . . . . . . . . . . . . . . . . . . . . . .

432,023

407,727

438,294

421,656

18,287

37,184

23,151

37,678

4.2

9.1

5.3

8.9

Farmington. . . . . . . . . . . . . . . . . . . . . . . . . .

51,710

47,206

52,329

47,204

2,527

4,858

3,330

5,316

4.9

10.3

6.4

11.3

Las Cruces. . . . . . . . . . . . . . . . . . . . . . . . . .

97,165

90,239

96,906

91,937

5,172

7,684

6,217

8,094

5.3

8.5

6.4

8.8

Santa Fe. . . . . . . . . . . . . . . . . . . . . . . . . . . .

74,140

68,971

75,847

69,953

2,765

6,470

3,413

6,617

3.7

9.4

4.5

9.5

New York. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9,457,173

9,064,228

9,538,972

9,441,085

345,064

1,285,375

363,430

1,468,753

3.6

14.2

3.8

15.6

Albany-Schenectady-Troy. . . . . . . . . . . . . .

444,463

452,046

449,844

451,902

14,624

43,405

15,846

47,296

3.3

9.6

3.5

10.5

Binghamton. . . . . . . . . . . . . . . . . . . . . . . . . .

106,242

110,052

107,265

109,258

4,189

11,626

4,705

12,108

3.9

10.6

4.4

11.1

Buffalo-Cheektowaga-Niagara Falls. . . . .

536,693

544,382

541,610

548,878

20,451

76,972

21,969

75,200

3.8

14.1

4.1

13.7

Elmira. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

34,843

37,574

35,272

37,669

1,338

4,535

1,456

4,479

3.8

12.1

4.1

11.9

Glens Falls. . . . . . . . . . . . . . . . . . . . . . . . . .

58,034

58,629

60,965

58,714

2,152

6,490

2,197

6,330

3.7

11.1

3.6

10.8

Ithaca. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

49,179

49,538

47,722

49,184

1,602

3,883

1,811

4,369

3.3

7.8

3.8

8.9

Kingston. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

87,373

90,153

88,443

90,687

2,942

9,745

3,237

10,220

3.4

10.8

3.7

11.3

New York-Newark-Jersey City. . . . . . . . . .

9,872,404

9,484,546

9,961,096

9,887,401

333,212

1,453,211

353,469

1,680,176

3.4

15.3

3.5

17.0

Rochester. . . . . . . . . . . . . . . . . . . . . . . . . . .

516,558

511,969

522,374

517,372

19,028

56,213

20,409

58,697

3.7

11.0

3.9

11.3

Syracuse. . . . . . . . . . . . . . . . . . . . . . . . . . . .

303,407

304,623

307,251

303,446

11,404

36,006

12,277

36,031

3.8

11.8

4.0

11.9

Utica-Rome. . . . . . . . . . . . . . . . . . . . . . . . . .

128,219

129,487

130,145

129,999

4,984

14,359

5,698

13,991

3.9

11.1

4.4

10.8

Watertown-Fort Drum. . . . . . . . . . . . . . . . .

43,684

42,520

44,858

43,157

1,997

5,027

2,042

4,831

4.6

11.8

4.6

11.2

North Carolina. . . . . . . . . . . . . . . . . . . . . . . . . .

5,081,718

4,838,194

5,097,518

4,819,363

196,440

613,012

213,152

380,123

3.9

12.7

4.2

7.9

Asheville. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

237,789

226,555

239,348

226,555

7,598

35,359

8,232

20,227

3.2

15.6

3.4

8.9

Burlington. . . . . . . . . . . . . . . . . . . . . . . . . . . .

82,382

77,929

82,450

78,797

3,141

9,864

3,474

6,193

3.8

12.7

4.2

7.9

Charlotte-Concord-Gastonia. . . . . . . . . . . .

1,362,806

1,322,805

1,377,278

1,321,828

48,110

173,982

52,422

111,687

3.5

13.2

3.8

8.4

Durham-Chapel Hill. . . . . . . . . . . . . . . . . . .

305,664

283,215

304,896

284,207

10,670

29,895

11,600

19,906

3.5

10.6

3.8

7.0

Fayetteville. . . . . . . . . . . . . . . . . . . . . . . . . .

149,923

142,548

150,076

139,304

7,475

22,021

8,097

13,865

5.0

15.4

5.4

10.0

Goldsboro. . . . . . . . . . . . . . . . . . . . . . . . . . .

52,968

46,871

52,481

47,240

2,194

4,771

2,344

3,323

4.1

10.2

4.5

7.0

Greensboro-High Point. . . . . . . . . . . . . . . .

373,813

348,825

372,107

353,819

15,132

50,606

16,511

32,268

4.0

14.5

4.4

9.1

Greenville. . . . . . . . . . . . . . . . . . . . . . . . . . . .

91,057

84,899

89,437

83,923

3,905

8,849

4,395

6,111

4.3

10.4

4.9

7.3

Hickory-Lenoir-Morganton. . . . . . . . . . . . .

175,997

164,006

176,861

161,061

6,518

24,203

7,100

13,191

3.7

14.8

4.0

8.2

Jacksonville. . . . . . . . . . . . . . . . . . . . . . . . . .

65,820

63,114

65,496

61,724

3,024

7,380

3,251

4,524

4.6

11.7

5.0

7.3

New Bern. . . . . . . . . . . . . . . . . . . . . . . . . . . .

51,949

48,226

52,674

48,046

2,095

5,075

2,295

3,232

4.0

10.5

4.4

6.7

Raleigh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

729,398

676,504

733,697

682,842

25,203

77,528

27,311

49,162

3.5

11.5

3.7

7.2

Rocky Mount. . . . . . . . . . . . . . . . . . . . . . . . .

64,894

62,372

64,333

61,015

3,393

8,696

3,640

5,877

5.2

13.9

5.7

9.6

See footnotes at end of table.

LABOR FORCE DATA

NOT SEASONALLY ADJUSTED

Table 1. Civilian labor force and unemployment by state and metropolitan area - Continued

Civilian labor force

Unemployed

May

June

Number

Percent of labor force

State and area

2019

2020

2019

2020p

May

June

May

June

2019

2020

2019

2020p

2019

2020

2019

2020p

North Carolina - Continued

Wilmington. . . . . . . . . . . . . . . . . . . . . . . . . . .

154,656

142,828

155,317

144,154

5,608

19,065

6,057

10,748

3.6

13.3

3.9

7.5

Winston-Salem. . . . . . . . . . . . . . . . . . . . . . .

332,547

310,717

333,315

311,529

12,224

39,587

13,342

24,596

3.7

12.7

4.0

7.9

North Dakota. . . . . . . . . . . . . . . . . . . . . . . . . . .

404,896

403,856

412,677

408,023

8,303

34,993

10,907

25,569

2.1

8.7

2.6

6.3

Bismarck. . . . . . . . . . . . . . . . . . . . . . . . . . . .

67,418

66,936

68,843

68,565

1,447

5,189

1,851

3,501

2.1

7.8

2.7

5.1

Fargo. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

138,943

140,003

139,329

142,165

2,773

10,109

3,374

7,867

2.0

7.2

2.4

5.5

Grand Forks. . . . . . . . . . . . . . . . . . . . . . . . .

53,893

53,028

54,236

54,042

1,338

4,419

1,706

3,362

2.5

8.3

3.1

6.2

Ohio. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5,781,125

5,759,306

5,844,525

5,849,201

213,510

777,518

253,781

650,272

3.7

13.5

4.3

11.1

Akron. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

357,462

346,204

361,055

352,944

13,034

43,189

15,982

39,050

3.6

12.5

4.4

11.1

Canton-Massillon. . . . . . . . . . . . . . . . . . . . .

198,659

195,600

199,578

197,747

7,996

24,926

8,955

21,422

4.0

12.7

4.5

10.8

Cincinnati. . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,121,391

1,106,295

1,141,322

1,127,725

37,293

123,769

46,480

101,909

3.3

11.2

4.1

9.0

Cleveland-Elyria. . . . . . . . . . . . . . . . . . . . . .

1,035,875

1,044,537

1,052,016

1,061,026

39,603

180,517

47,648

148,175

3.8

17.3

4.5

14.0

Columbus. . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,090,198

1,080,949

1,102,941

1,095,382

34,456

118,631

42,223

108,433

3.2

11.0

3.8

9.9

Dayton. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

387,871

392,505

391,833

394,795

14,133

49,888

16,907

42,159

3.6

12.7

4.3

10.7

Lima. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

47,927

48,695

48,341

48,475

1,631

7,411

2,066

5,330

3.4

15.2

4.3

11.0

Mansfield. . . . . . . . . . . . . . . . . . . . . . . . . . . .

52,363

53,459

52,970

52,981

1,973

8,405

2,393

5,983

3.8

15.7

4.5

11.3

Springfield. . . . . . . . . . . . . . . . . . . . . . . . . . .

63,202

63,862

63,496

64,630

2,243

7,985

2,794

6,752

3.5

12.5

4.4

10.4

Toledo. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

307,201

310,647

304,702

304,839

15,046

54,129

13,392

37,492

4.9

17.4

4.4

12.3

Weirton-Steubenville1. . . . . . . . . . . . . . . . .

50,442

50,683

51,333

51,235

2,409

7,686

2,871

6,211

4.8

15.2

5.6

12.1

Youngstown-Warren-Boardman. . . . . . . .

238,905

232,716

241,561

235,134

12,316

36,153

14,073

31,290

5.2

15.5

5.8

13.3

Oklahoma. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,836,265

1,820,747

1,854,443

1,779,949

58,531

229,735

65,316

121,838

3.2

12.6

3.5

6.8

Enid. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

27,053

26,089

27,237

25,791

782

2,763

862

1,603

2.9

10.6

3.2

6.2

Lawton. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

50,818

51,093

51,509

49,349

1,768

8,033

1,982

3,484

3.5

15.7

3.8

7.1

Oklahoma City. . . . . . . . . . . . . . . . . . . . . . .

682,350

679,638

688,604

674,046

20,197

87,932

22,521

47,272

3.0

12.9

3.3

7.0

Tulsa. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

480,077

476,784

487,736

457,238

15,331

61,660

16,817

33,336

3.2

12.9

3.4

7.3

Oregon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,092,575

2,114,497

2,113,944

2,158,252

71,990

294,470

83,768

243,315

3.4

13.9

4.0

11.3

Albany. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

58,533

59,586

58,902

60,183

2,316

7,934

2,687

6,554

4.0

13.3

4.6

10.9

Bend-Redmond. . . . . . . . . . . . . . . . . . . . . . .

95,754

97,322

97,100

98,235

3,299

15,440

3,783

11,667

3.4

15.9

3.9

11.9

Corvallis. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

48,453

47,269

49,120

47,961

1,267

4,601

1,643

4,038

2.6

9.7

3.3

8.4

Eugene. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

180,388

184,312

181,181

188,592

6,720

26,275

7,915

21,268

3.7

14.3

4.4

11.3

Grants Pass. . . . . . . . . . . . . . . . . . . . . . . . .

35,781

35,997

36,143

36,351

1,618

4,837

1,834

4,061

4.5

13.4

5.1

11.2

Medford. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

102,918

104,319

103,596

106,335

4,170

14,970

4,815

12,278

4.1

14.4

4.6

11.5

Portland-Vancouver-Hillsboro. . . . . . . . . .

1,315,744

1,335,856

1,322,096

1,355,300

44,343

186,868

50,589

154,040

3.4

14.0

3.8

11.4

Salem. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

200,385

200,442

203,756

203,711

7,384

24,713

8,591

20,401

3.7

12.3

4.2

10.0

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . . . . .

6,447,401

6,494,406

6,514,786

6,383,465

258,627

859,499

287,947

835,196

4.0

13.2

4.4

13.1

Allentown-Bethlehem-Easton. . . . . . . . . . .

440,949

444,195

444,700

442,789

17,932

61,151

19,352

61,747

4.1

13.8

4.4

13.9

Altoona. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

59,231

60,832

60,402

58,262

2,261

8,010

2,820

6,869

3.8

13.2

4.7

11.8

Bloomsburg-Berwick. . . . . . . . . . . . . . . . . .

42,093

43,647

42,373

42,251

1,835

4,850

1,975

4,263

4.4

11.1

4.7

10.1

Chambersburg-Waynesboro. . . . . . . . . . .

77,185

78,606

78,317

76,891

2,677

8,894

2,997

8,710

3.5

11.3

3.8

11.3

East Stroudsburg. . . . . . . . . . . . . . . . . . . . .

82,569

83,000

83,661

82,481

4,114

15,156

4,449

14,746

5.0

18.3

5.3

17.9

Erie. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

127,955

127,309

129,310

124,627

5,264

17,747

6,025

17,929

4.1

13.9

4.7

14.4

Gettysburg. . . . . . . . . . . . . . . . . . . . . . . . . . .

55,202

57,611

55,868

55,404

1,636

6,548

1,907

5,725

3.0

11.4

3.4

10.3

Harrisburg-Carlisle. . . . . . . . . . . . . . . . . . . .

299,080

307,304

304,772

298,671

10,245

35,501

11,858

34,435

3.4

11.6

3.9

11.5

Johnstown. . . . . . . . . . . . . . . . . . . . . . . . . . .

57,872

56,913

58,485

55,095

2,676

7,611

3,419

7,092

4.6

13.4

5.8

12.9

Lancaster. . . . . . . . . . . . . . . . . . . . . . . . . . . .

283,772

292,827

288,734

290,201

9,026

33,525

10,432

32,489

3.2

11.4

3.6

11.2

Lebanon. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

72,444

75,104

73,742

72,399

2,530

8,643

2,920

8,512

3.5

11.5

4.0

11.8

Philadelphia-Camden-Wilmington. . . . . . .

3,101,906

3,124,509

3,125,601

3,119,025

117,240

428,342

128,623

437,877

3.8

13.7

4.1

14.0

Pittsburgh. . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,202,261

1,196,505

1,216,835

1,178,566

46,924

162,878

53,680

148,986

3.9

13.6

4.4

12.6

Reading. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

215,269

228,621

217,595

224,125

8,753

31,198

9,672

29,438

4.1

13.6

4.4

13.1

Scranton--Wilkes-Barre--Hazleton. . . . . . .

273,791

271,228

275,810

264,574

13,418

41,880

14,536

40,468

4.9

15.4

5.3

15.3

State College. . . . . . . . . . . . . . . . . . . . . . . .

80,537

80,592

76,322

74,549

2,637

6,544

2,752

6,261

3.3

8.1

3.6

8.4

Williamsport. . . . . . . . . . . . . . . . . . . . . . . . . .

56,285

52,741

56,896

52,880

2,440

6,774

2,628

6,446

4.3

12.8

4.6

12.2

York-Hanover. . . . . . . . . . . . . . . . . . . . . . . .

234,833

241,666

237,121

233,693

8,244

30,080

9,686

26,933

3.5

12.4

4.1

11.5

Rhode Island. . . . . . . . . . . . . . . . . . . . . . . . . . .

550,312

518,867

557,755

552,974

18,150

83,808

18,645

66,980

3.3

16.2

3.3

12.1

Providence-Warwick. . . . . . . . . . . . . . . . . .

685,457

650,024

693,435

689,375

22,806

108,686

23,768

93,158

3.3

16.7

3.4

13.5

South Carolina. . . . . . . . . . . . . . . . . . . . . . . . .

2,377,726

2,420,966

2,400,898

2,462,989

64,906

290,963

75,412

219,169

2.7

12.0

3.1

8.9

Charleston-North Charleston. . . . . . . . . . .

395,600

395,373

399,829

406,619

9,287

48,146

10,603

36,676

2.3

12.2

2.7

9.0

Columbia. . . . . . . . . . . . . . . . . . . . . . . . . . . .

402,295

410,299

404,598

412,816

10,513

38,296

12,295

32,043

2.6

9.3

3.0

7.8

Florence. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

97,831

100,415

98,716

103,187

2,885

9,583

3,391

8,351

2.9

9.5

3.4

8.1

Greenville-Anderson-Mauldin. . . . . . . . . . .

434,099

446,494

438,105

452,053

10,983

54,260

12,675

38,031

2.5

12.2

2.9

8.4

Hilton Head Island-Bluffton-Beaufort. . . .

91,119

91,434

92,852

95,721

2,370

10,062

2,758

7,102

2.6

11.0

3.0

7.4

Myrtle Beach-Conway-North Myrtle

Beach. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

206,220

202,655

212,728

209,826

7,616

35,276

8,411

22,346

3.7

17.4

4.0

10.6

Spartanburg. . . . . . . . . . . . . . . . . . . . . . . . . .

164,726

172,822

166,033

173,016

4,181

25,060

5,051

17,550

2.5

14.5

3.0

10.1

Sumter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

43,736

45,545

44,112

45,883

1,393

5,026

1,663

3,905

3.2

11.0

3.8

8.5

South Dakota. . . . . . . . . . . . . . . . . . . . . . . . . .

462,992

464,374

470,901

475,420

14,197

42,669

15,018

33,471

3.1

9.2

3.2

7.0

Rapid City. . . . . . . . . . . . . . . . . . . . . . . . . . .

74,934

74,666

77,299

76,983

2,479

8,115

2,551

6,318

3.3

10.9

3.3

8.2

Sioux Falls. . . . . . . . . . . . . . . . . . . . . . . . . . .

155,091

157,931

156,797

160,887

4,085

14,923

4,164

10,823

2.6

9.4

2.7

6.7

Tennessee. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,336,509

3,294,573

3,372,213

3,201,894

104,130

351,948

131,488

324,508

3.1

10.7

3.9

10.1

Chattanooga. . . . . . . . . . . . . . . . . . . . . . . . .

276,075

277,110

280,189

270,275

8,356

25,198

10,486

22,124

3.0

9.1

3.7

8.2

Clarksville. . . . . . . . . . . . . . . . . . . . . . . . . . .

117,061

119,017

117,764

113,678

4,721

12,514

5,759

9,942

4.0

10.5

4.9

8.7

Cleveland. . . . . . . . . . . . . . . . . . . . . . . . . . . .

58,681

58,580

59,810

59,065

1,926

5,457

2,506

5,005

3.3

9.3

4.2

8.5

Jackson. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65,093

61,773

66,091

61,866

2,099

6,122

2,681

5,764

3.2

9.9

4.1

9.3

See footnotes at end of table.

LABOR FORCE DATA

NOT SEASONALLY ADJUSTED

Table 1. Civilian labor force and unemployment by state and metropolitan area - Continued

Civilian labor force

Unemployed

May

June

Number

Percent of labor force

State and area

2019

2020

2019

2020p

May

June

May

June

2019

2020

2019

2020p

2019

2020

2019

2020p

Tennessee - Continued

Johnson City. . . . . . . . . . . . . . . . . . . . . . . . .

91,936

89,141

91,599

86,874

3,293

7,895

3,980

7,740

3.6

8.9

4.3

8.9

Kingsport-Bristol-Bristol. . . . . . . . . . . . . . . .

138,568

133,082

139,257

131,288

4,731

12,793

5,784

12,056

3.4

9.6

4.2

9.2

Knoxville. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

432,298

423,486

436,264

412,167

12,942

36,839

16,719

33,691

3.0

8.7

3.8

8.2

Memphis. . . . . . . . . . . . . . . . . . . . . . . . . . . .

644,084

623,761

651,549

620,350

25,134

66,493

31,456

73,822

3.9

10.7

4.8

11.9

Morristown. . . . . . . . . . . . . . . . . . . . . . . . . . .

53,311

53,202

53,423

51,352

1,865

5,991

2,317

4,847

3.5

11.3

4.3

9.4

Nashville-Davidson--Murfreesboro--

Franklin. . . . . . . . . . . . . . . . . . . . . . . . . . .

1,087,467

1,065,090

1,102,056

1,042,052

26,627

117,907

33,493

106,563

2.4

11.1

3.0

10.2

Texas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13,926,760

13,464,075

14,009,283

13,844,386

435,592

1,711,194

520,024

1,231,582

3.1

12.7

3.7

8.9

Abilene. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

78,140

73,746

78,274

76,595

2,075

6,555

2,553

4,940

2.7

8.9

3.3

6.4

Amarillo. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

132,061

121,586

131,854

125,555

2,928

10,368

3,661

7,596

2.2

8.5

2.8

6.0

Austin-Round Rock. . . . . . . . . . . . . . . . . . .

1,225,988

1,172,013

1,234,994

1,214,563

28,958

133,155

34,716

90,887

2.4

11.4

2.8

7.5

Beaumont-Port Arthur. . . . . . . . . . . . . . . . .

172,566

167,707

173,250

168,526

8,382

29,898

10,124

21,609

4.9

17.8

5.8

12.8

Brownsville-Harlingen. . . . . . . . . . . . . . . . .

165,540

159,995

167,285

163,479

8,044

25,581

9,663

18,354

4.9

16.0

5.8

11.2

College Station-Bryan. . . . . . . . . . . . . . . . .

134,677

129,166

130,319

131,338

3,329

11,225

4,153

8,585

2.5

8.7

3.2

6.5

Corpus Christi. . . . . . . . . . . . . . . . . . . . . . . .

205,863

194,298

206,451

201,378

7,874

28,466

9,325

20,299

3.8

14.7

4.5

10.1

Dallas-FortWorth-Arlington. . . . . . . . . . . .

3,926,375

3,829,800

3,960,641

3,957,398

115,327

469,577

136,815

331,426

2.9

12.3

3.5

8.4

El Paso. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

361,452

349,688

360,048

355,814

12,421

50,955

14,614

35,055

3.4

14.6

4.1

9.9

Houston-TheWoodlands-Sugar Land. . .

3,399,189

3,324,817

3,420,393

3,395,505

115,222

463,763

135,598

336,795

3.4

13.9

4.0

9.9

Killeen-Temple. . . . . . . . . . . . . . . . . . . . . . .

175,892

167,520

176,330

172,336

5,956

18,026

7,135

13,583

3.4

10.8

4.0

7.9

Laredo. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

118,482

113,431

118,663

115,398

4,016

15,991

4,730

11,612

3.4

14.1

4.0

10.1

Longview. . . . . . . . . . . . . . . . . . . . . . . . . . . .

98,949

92,284

98,958

94,915

3,206

11,225

3,762

8,663

3.2

12.2

3.8

9.1

Lubbock. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

162,906

152,316

163,106

157,302

3,973

14,321

5,321

10,777

2.4

9.4

3.3

6.9

McAllen-Edinburg-Mission. . . . . . . . . . . . .

349,154

350,895

351,385

353,115

18,882

61,587

22,911

45,060

5.4

17.6

6.5

12.8

Midland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

109,702

101,470

110,115

103,625

1,940

12,795

2,365

9,980

1.8

12.6

2.1

9.6

Odessa. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

87,802

84,968

87,649

85,961

1,954

14,017

2,397

11,139

2.2

16.5

2.7

13.0

San Angelo. . . . . . . . . . . . . . . . . . . . . . . . . .

54,929

50,052

55,148

52,338

1,490

5,366

1,804

4,096

2.7

10.7

3.3

7.8

San Antonio-New Braunfels. . . . . . . . . . . .

1,192,549

1,166,645

1,202,628

1,196,498

32,842

148,726

39,735

101,726

2.8

12.7

3.3

8.5

Sherman-Denison. . . . . . . . . . . . . . . . . . . .

63,849

61,027

64,188

63,050

1,754

5,874

2,062

4,277

2.7

9.6

3.2

6.8

Texarkana. . . . . . . . . . . . . . . . . . . . . . . . . . .

65,169

63,156

66,014

64,271

2,510

6,744

3,015

5,320

3.9

10.7

4.6

8.3

Tyler. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

106,825

103,773

107,044

106,382

3,163

11,744

3,795

8,482

3.0

11.3

3.5

8.0

Victoria. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45,861

42,786

45,954

44,116

1,398

5,475

1,646

3,985

3.0

12.8

3.6

9.0

Waco. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

125,126

120,620

126,235

124,773

3,630

11,756

4,608

8,815

2.9

9.7

3.7

7.1

Wichita Falls. . . . . . . . . . . . . . . . . . . . . . . . .

64,895

59,674

65,559

62,518

1,817

5,998

2,273

4,548

2.8

10.1

3.5

7.3

Utah. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,599,711

1,607,911

1,612,516

1,673,611

41,197

136,316

48,104

92,009

2.6

8.5

3.0

5.5

Logan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

72,152

68,388

70,907

72,241

1,522

3,301

1,800

2,506

2.1

4.8

2.5

3.5

Ogden-Clearfield. . . . . . . . . . . . . . . . . . . . .

332,658

339,080

335,168

353,178

8,415

27,038

9,889

17,239

2.5

8.0

3.0

4.9

Provo-Orem. . . . . . . . . . . . . . . . . . . . . . . . . .

308,763

309,059

310,895

327,314

7,434

19,142

8,797

13,985

2.4

6.2

2.8

4.3

St. George. . . . . . . . . . . . . . . . . . . . . . . . . . .

75,961

76,889

75,145

79,831

2,122

7,270

2,569

4,793

2.8

9.5

3.4

6.0

Salt Lake City. . . . . . . . . . . . . . . . . . . . . . . .

665,237

668,464

672,410

688,032

16,932

63,096

19,594

42,820

2.5

9.4

2.9

6.2

Vermont. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

341,657

342,245

346,954

345,764

7,493

43,468

8,577

32,395

2.2

12.7

2.5

9.4

Burlington-South Burlington. . . . . . . . . . . .

125,070

122,627

126,985

124,595

2,219

14,297

2,731

10,653

1.8

11.7

2.2

8.6

Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4,401,947

4,319,016

4,434,710

4,356,400

118,238

383,912

129,920

371,775

2.7

8.9

2.9

8.5

Blacksburg-Christiansburg-Radford. . . . .

91,859

83,602

89,081

83,878

2,657

7,382

2,954

6,392

2.9

8.8

3.3

7.6

Charlottesville. . . . . . . . . . . . . . . . . . . . . . . .

123,608

121,760

123,644

121,727

3,143

9,826

3,466

9,831

2.5

8.1

2.8

8.1

Harrisonburg. . . . . . . . . . . . . . . . . . . . . . . . .

65,914

64,205

66,483

64,015

1,872

5,657

2,059

5,020

2.8

8.8

3.1

7.8

Lynchburg. . . . . . . . . . . . . . . . . . . . . . . . . . .

123,287

118,214

123,657

120,995

3,911

9,717

4,440

9,563

3.2

8.2

3.6

7.9

Richmond. . . . . . . . . . . . . . . . . . . . . . . . . . . .

685,796

674,282

690,643

679,821

19,365

63,291

21,367

62,856

2.8

9.4

3.1

9.2

Roanoke. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

158,330

153,640

157,975

152,247

4,194

13,742

4,780

12,423

2.6

8.9

3.0

8.2

Staunton-Waynesboro. . . . . . . . . . . . . . . . .

60,634

61,731

60,950

62,364

1,520

4,628

1,651

4,366

2.5

7.5

2.7

7.0

Virginia Beach-Norfolk-Newport News. . .

859,269

851,043

866,525

857,800

25,563

85,492

27,796

82,516

3.0

10.0

3.2

9.6

Winchester. . . . . . . . . . . . . . . . . . . . . . . . . . .

73,641

71,501

74,444

71,096

1,900

5,635

2,133

4,989

2.6

7.9

2.9

7.0

Washington. . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,888,371

3,937,461

3,919,625

3,965,560

158,985

582,895

164,802

384,109

4.1

14.8

4.2

9.7

Bellingham. . . . . . . . . . . . . . . . . . . . . . . . . . .

114,936

119,856

115,468

115,432

5,403

18,658

5,880

12,156

4.7

15.6

5.1

10.5

Bremerton-Silverdale. . . . . . . . . . . . . . . . . .

127,404

133,933

127,845

129,106

5,751

17,667

6,152

10,759

4.5

13.2

4.8

8.3

Kennewick-Richland. . . . . . . . . . . . . . . . . .

146,921

150,588

152,203

155,722

7,443

18,452

7,647

14,159

5.1

12.3

5.0

9.1

Longview. . . . . . . . . . . . . . . . . . . . . . . . . . . .

47,572

49,775

47,638

47,729

2,890

7,688

2,966

4,777

6.1

15.4

6.2

10.0

Mount Vernon-Anacortes. . . . . . . . . . . . . .

62,744

64,393

63,521

62,710

3,281

10,646

3,463

7,081

5.2

16.5

5.5

11.3

Olympia-Tumwater. . . . . . . . . . . . . . . . . . . .

141,359

148,781

141,189

142,545

6,710

21,187

7,047

12,851

4.7

14.2

5.0

9.0

Seattle-Tacoma-Bellevue. . . . . . . . . . . . . .

2,161,440

2,164,320

2,163,471

2,223,411

69,343

330,228

72,654

216,571

3.2

15.3

3.4

9.7

Spokane-Spokane Valley. . . . . . . . . . . . . .

277,303

279,097

276,986

270,867

14,179

41,745

14,587

26,658

5.1

15.0

5.3

9.8

Walla Walla. . . . . . . . . . . . . . . . . . . . . . . . . .

31,661

32,152

32,364

31,870

1,437

3,435

1,587

2,098

4.5

10.7

4.9

6.6

Wenatchee. . . . . . . . . . . . . . . . . . . . . . . . . .

65,020

65,238

70,716

69,741

3,230

9,235

3,067

6,370

5.0

14.2

4.3

9.1

Yakima. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

130,493

135,473

140,204

143,023

8,856

18,845

8,176

14,420

6.8

13.9

5.8

10.1

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . .

794,398

781,397

806,744

775,692

35,373

97,854

39,694

80,734

4.5

12.5

4.9

10.4

Beckley. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

46,905

47,435

47,735

46,805

2,143

6,305

2,367

5,246

4.6

13.3

5.0

11.2

Charleston. . . . . . . . . . . . . . . . . . . . . . . . . . .

92,539

91,966

94,941

92,989

4,119

13,010

4,501

10,711

4.5

14.1

4.7

11.5

Huntington-Ashland. . . . . . . . . . . . . . . . . . .

145,749

149,110

147,578

148,349

6,714

18,881

7,958

13,728

4.6

12.7

5.4

9.3

Morgantown. . . . . . . . . . . . . . . . . . . . . . . . . .

70,043

69,318

68,595

68,463

2,516

6,898

2,914

6,297

3.6

10.0

4.2

9.2

Parkersburg-Vienna. . . . . . . . . . . . . . . . . . .

39,000

40,001

39,627

39,640

1,861

5,250

2,052

4,021

4.8

13.1

5.2

10.1

Wheeling. . . . . . . . . . . . . . . . . . . . . . . . . . . .

65,600

63,536

66,859

64,705

3,065

9,376

3,378

7,387

4.7

14.8

5.1

11.4

Wisconsin. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,085,969

3,088,644

3,150,680

3,100,848

94,828

366,905

117,562

270,982

3.1

11.9

3.7

8.7

Appleton. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

130,027

128,157

133,280

128,808

3,651

13,711

4,485

9,665

2.8

10.7

3.4

7.5

See footnotes at end of table.

LABOR FORCE DATA

NOT SEASONALLY ADJUSTED

Table 1. Civilian labor force and unemployment by state and metropolitan area - Continued

Civilian labor force

Unemployed

May

June

Number

Percent of labor force

State and area

2019

2020

2019

2020p

May

June

May

June

2019

2020

2019

2020p

2019

2020

2019

2020p

Wisconsin - Continued

Eau Claire. . . . . . . . . . . . . . . . . . . . . . . . . . .

92,171

89,141

91,934

89,857

2,715

9,663

3,348

7,456

2.9

10.8

3.6

8.3

Fond du Lac. . . . . . . . . . . . . . . . . . . . . . . . .

57,109

58,505

58,938

59,131

1,560

6,607

1,976

4,910

2.7

11.3

3.4

8.3

Green Bay. . . . . . . . . . . . . . . . . . . . . . . . . . .

172,773

173,539

176,162

173,140

5,199

20,929

6,375

14,837

3.0

12.1

3.6

8.6

Janesville-Beloit. . . . . . . . . . . . . . . . . . . . . .

84,832

84,030

86,443

84,589

2,951

11,633

3,594

8,217

3.5

13.8

4.2

9.7

La Crosse-Onalaska. . . . . . . . . . . . . . . . . .

76,830

74,951

76,422

75,483

2,105

7,778

2,664

5,612

2.7

10.4

3.5

7.4

Madison. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

382,348

370,284

391,595

373,563

9,814

35,900

12,019

27,498

2.6

9.7

3.1

7.4

Milwaukee-Waukesha-West Allis. . . . . . .

812,363

824,371

824,342

826,746

26,925

106,328

33,812

82,785

3.3

12.9

4.1

10.0

Oshkosh-Neenah. . . . . . . . . . . . . . . . . . . . .

91,139

90,840

92,133

91,026

2,646

9,881

3,268

7,016

2.9

10.9

3.5

7.7

Racine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

98,154

101,807

99,883

102,018

3,516

12,647

4,385

9,533

3.6

12.4

4.4

9.3

Sheboygan. . . . . . . . . . . . . . . . . . . . . . . . . .

62,176

62,640

63,844

63,297

1,630

7,933

2,061

5,028

2.6

12.7

3.2

7.9

Wausau. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

73,010

72,918

74,620

73,441

1,995

6,741

2,459

5,043

2.7

9.2

3.3

6.9

Wyoming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

290,120

292,873

297,410

301,336

9,616

25,426

10,840

22,832

3.3

8.7

3.6

7.6

Casper. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

38,975

39,607

39,460

40,001

1,427

4,585

1,600

4,382

3.7

11.6

4.1

11.0

Cheyenne. . . . . . . . . . . . . . . . . . . . . . . . . . .

48,095

49,664

48,383

50,385

1,541

3,934

1,748

3,333

3.2

7.9

3.6

6.6

Puerto Rico. . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,091,373

1,015,919

1,113,225

1,063,390

84,550

97,038

89,438

90,194

7.7

9.6

8.0

8.5

Aguadilla-Isabela. . . . . . . . . . . . . . . . . . . . .

86,800

78,566

87,896

82,162

8,851

8,660

9,422

7,821

10.2

11.0

10.7

9.5

Arecibo. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

52,955

49,723

53,747

52,290

5,034

5,078

5,146

4,586

9.5

10.2

9.6

8.8

Guayama. . . . . . . . . . . . . . . . . . . . . . . . . . . .

20,293

18,010

20,490

18,877

2,560

1,677

2,637

1,650

12.6

9.3

12.9

8.7

Mayaguez. . . . . . . . . . . . . . . . . . . . . . . . . . .

27,331

24,981

27,998

25,949

2,619

2,610

2,775

2,274

9.6

10.4

9.9

8.8

Ponce. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

93,125

85,294

94,817

88,676

10,369

8,563

10,420

7,682

11.1

10.0

11.0

8.7

San German. . . . . . . . . . . . . . . . . . . . . . . . .

34,481

31,718

35,242

33,105

3,516

3,455

3,794

2,999

10.2

10.9

10.8

9.1

San Juan-Carolina-Caguas. . . . . . . . . . . .

733,877

689,712

750,228

723,158

46,686

63,425

50,236

59,754

6.4

9.2

6.7

8.3

  • For operational reasons, these interstate areas are listed under the state that accounts for the larger share of the population, which is different from the state that contains the first principal city.
    2 The area boundary does not reflect the Office of Management and Budget delineation. p Preliminary

NOTE: Data refer to place of residence. Data for Puerto Rico are derived from a monthly household survey similar to the Current Population Survey. Area delineations are based on Office of Management and Budget Bulletin No. 18-03, dated April 10, 2018, and are available on the BLS website at https://www.bls.gov/lau/lausmsa.htm. Areas in the six New England states are Metropolitan New England City and Town Areas (NECTAs), while areas in other states are county-based. Some metropolitan areas lie in two or more states. They are listed under the state containing the first principal city, unless otherwise footnoted. Estimates for the latest month are subject to revision the following month.

LABOR FORCE DATA

NOT SEASONALLY ADJUSTED

Table 2. Civilian labor force and unemployment by state, selected metropolitan area, and metropolitan division1

Civilian labor force

Unemployed

May

June

Number

Percent of labor force

State, area, and division

2019

2020

2019

2020p

May

June

May

June

2019

2020

2019

2020p

2019

2020

2019

2020p

California. . . . . . . . . . . . . . . . . . . . . . . . . . . .

19,261,786

18,423,388

19,325,538

18,912,012

694,948

2,949,447

794,837

2,846,644

3.6

16.0

4.1

15.1

Los Angeles-LongBeach-Anaheim. . .

6,686,003

6,263,730

6,692,809

6,506,445

247,034

1,207,655

274,997

1,175,309

3.7

19.3

4.1

18.1

Anaheim-SantaAna-Irvine. . . . . . . . .

1,611,417

1,547,639

1,613,664

1,595,002

39,120

227,097

47,266

218,036

2.4

14.7

2.9

13.7

Los Angeles-Long

Beach-Glendale. . . . . . . . . . . . . . . .

5,074,586

4,716,091

5,079,145

4,911,443

207,914

980,558

227,731

957,273

4.1

20.8

4.5

19.5

San Francisco-Oakland-Hayward. . . . .

2,561,694

2,448,078

2,574,357

2,515,312

58,798

315,807

70,861

316,257

2.3

12.9

2.8

12.6

Oakland-Hayward-Berkeley. . . . . . . .

1,393,942

1,337,467

1,399,750

1,370,000

36,792

183,942

44,067

184,005

2.6

13.8

3.1

13.4

San Francisco-RedwoodCity-South

San Francisco. . . . . . . . . . . . . . . . .

1,029,427

982,948

1,035,359

1,012,263

19,277

118,441

23,442

118,914

1.9

12.0

2.3

11.7

San Rafael. . . . . . . . . . . . . . . . . . . . . .

138,325

127,663

139,248

133,049

2,729

13,424

3,352

13,338

2.0

10.5

2.4

10.0

District of Columbia. . . . . . . . . . . . . . . . . . .

408,260

386,742

412,636

397,766

21,301

32,680

24,062

35,673

5.2

8.5

5.8

9.0

Washington-Arlington-Alexandria2. . . .

3,452,965

3,358,412

3,489,162

3,437,663

103,578

299,108

115,882

288,117

3.0

8.9

3.3

8.4

Silver Spring-Frederick-Rockville3.. .

695,856

673,257

705,686

697,256

20,270

60,781

23,350

55,745

2.9

9.0

3.3

8.0

Washington-Arlington-Alexandria2.. .

2,757,109

2,685,155

2,783,476

2,740,407

83,308

238,327

92,532

232,372

3.0

8.9

3.3

8.5

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

10,297,648

9,651,892

10,318,834

9,789,069

310,611

1,304,072

344,231

1,045,481

3.0

13.5

3.3

10.7

Miami-FortLauderdale-West Palm

Beach. . . . . . . . . . . . . . . . . . . . . . . . . .

3,147,395

2,876,540

3,144,322

2,940,463

87,247

384,706

93,941

333,308

2.8

13.4

3.0

11.3

Fort Lauderdale-Pompano

Beach-Deerfield Beach. . . . . . . . .

1,038,920

979,822

1,042,537

992,435

30,934

148,708

33,791

117,120

3.0

15.2

3.2

11.8

Miami-MiamiBeach-Kendall. . . . . . .

1,374,809

1,220,976

1,369,579

1,269,957

33,538

146,069

34,494

145,655

2.4

12.0

2.5

11.5

West Palm Beach-Boca

Raton-Delray Beach. . . . . . . . . . . .

733,666

675,742

732,206

678,071

22,775

89,929

25,656

70,533

3.1

13.3

3.5

10.4

Illinois. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6,416,363

6,283,576

6,517,399

6,559,573

222,493

931,965

267,575

958,349

3.5

14.8

4.1

14.6

Chicago-Naperville-Elgin2. . . . . . . . . . .

4,828,532

4,806,063

4,930,924

5,006,583

163,684

733,053

200,045

780,308

3.4

15.3

4.1

15.6

Chicago-Naperville-Arlington

Heights. . . . . . . . . . . . . . . . . . . . . . .

3,694,475

3,715,509

3,778,783

3,870,973

123,584

577,485

154,332

633,901

3.3

15.5

4.1

16.4

Elgin. . . . . . . . . . . . . . . . . . . . . . . . . . . .

327,772

304,372

331,558

321,795

11,505

45,320

13,179

42,303

3.5

14.9

4.0

13.1

Gary3. . . . . . . . . . . . . . . . . . . . . . . . . . .

341,945

347,667

346,087

355,402

13,042

52,763

14,799

52,631

3.8

15.2

4.3

14.8

Lake County-Kenosha County2. . . .

464,340

438,515

474,496

458,413

15,553

57,485

17,735

51,473

3.3

13.1

3.7

11.2

Massachusetts. . . . . . . . . . . . . . . . . . . . . . .

3,790,731

3,525,512

3,851,461

3,713,361

109,174

582,796

120,601

648,604

2.9

16.5

3.1

17.5

Boston-Cambridge-Nashua2. . . . . . . . .

2,809,844

2,615,118

2,852,718

2,743,087

74,261

422,746

82,005

462,978

2.6

16.2

2.9

16.9

Boston-Cambridge-Newton. . . . . . . .

1,677,021

1,544,597

1,703,502

1,622,085

41,992

236,286

46,630

269,121

2.5

15.3

2.7

16.6

Brockton-Bridgewater-Easton. . . . . .

111,383

107,294

112,317

112,620

3,432

21,457

3,909

23,411

3.1

20.0

3.5

20.8

Framingham. . . . . . . . . . . . . . . . . . . . .

162,198

149,308

164,854

158,009

3,956

20,573

4,283

23,052

2.4

13.8

2.6

14.6

Haverhill-Newburyport-Amesbury

Town2. . . . . . . . . . . . . . . . . . . . . . . .

118,646

108,947

121,291

114,083

3,215

18,407

3,485

18,035

2.7

16.9

2.9

15.8

Lawrence-MethuenTown-Salem2. . .

98,986

97,168

100,438

102,413

3,794

21,904

4,237

23,968

3.8

22.5

4.2

23.4

Lowell-Billerica-Chelmsford2. . . . . . .

197,826

182,958

200,623

190,628

5,562

29,528

6,098

32,099

2.8

16.1

3.0

16.8

Lynn-Saugus-Marblehead. . . . . . . . .

86,588

83,456

87,807

88,613

2,537

16,932

2,796

19,306

2.9

20.3

3.2

21.8

Nashua2. . . . . . . . . . . . . . . . . . . . . . . .

176,482

168,650

179,349

174,330

4,538

26,088

4,781

20,464

2.6

15.5

2.7

11.7

Peabody-Salem-Beverly. . . . . . . . . . .

93,642

89,371

94,478

93,435

2,592

15,594

2,809

17,222

2.8

17.4

3.0

18.4

Taunton-Middleborough-Norton. . . .

87,072

83,369

88,059

86,871

2,643

15,977

2,977

16,300

3.0

19.2

3.4

18.8

Michigan. . . . . . . . . . . . . . . . . . . . . . . . . . . .

4,923,525

4,765,123

4,971,319

4,993,785

184,604

991,814

212,011

743,803

3.7

20.8

4.3

14.9

Detroit-Warren-Dearborn. . . . . . . . . . . .

2,139,667

1,935,243

2,159,216

2,053,738

82,283

460,482

95,839

366,269

3.8

23.8

4.4

17.8

Detroit-Dearborn-Livonia. . . . . . . . . .

797,188

737,185

804,409

779,293

36,524

195,615

42,322

160,937

4.6

26.5

5.3

20.7

Warren-Troy-Farmington Hills. . . . . .

1,342,478

1,198,058

1,354,808

1,274,445

45,758

264,866

53,517

205,333

3.4

22.1

4.0

16.1

New York. . . . . . . . . . . . . . . . . . . . . . . . . . .

9,457,173

9,064,228

9,538,972

9,441,085

345,064

1,285,375

363,430

1,468,753

3.6

14.2

3.8

15.6

New York-Newark-Jersey City2. . . . . .

9,872,404

9,484,546

9,961,096

9,887,401

333,212

1,453,211

353,469

1,680,176

3.4

15.3

3.5

17.0

Dutchess County-Putnam County. . .

194,460

193,073

195,887

194,184

6,414

20,375

6,977

22,110

3.3

10.6

3.6

11.4

Nassau County-Suffolk County. . . . .

1,478,984

1,461,147

1,504,901

1,493,083

47,214

179,032

50,916

192,996

3.2

12.3

3.4

12.9

Newark3. . . . . . . . . . . . . . . . . . . . . . . . .

1,223,115

1,231,356

1,239,114

1,243,394

37,700

175,601

41,763

193,897

3.1

14.3

3.4

15.6

New York-JerseyCity-White

Plains2. . . . . . . . . . . . . . . . . . . . . . . .

6,975,845

6,598,970

7,021,194

6,956,740

241,884

1,078,203

253,813

1,271,173

3.5

16.3

3.6

18.3

Pennsylvania. . . . . . . . . . . . . . . . . . . . . . . .

6,447,401

6,494,406

6,514,786

6,383,465

258,627

859,499

287,947

835,196

4.0

13.2

4.4

13.1

Philadelphia-Camden-Wilmington2. . . .

3,101,906

3,124,509

3,125,601

3,119,025

117,240

428,342

128,623

437,877

3.8

13.7

4.1

14.0

Camden3. . . . . . . . . . . . . . . . . . . . . . . .

627,184

647,702

632,427

649,474

19,395

91,413

21,517

98,367

3.1

14.1

3.4

15.1

Montgomery County-Bucks

County-Chester County. . . . . . . . .

1,081,755

1,062,720

1,096,775

1,048,314

35,821

123,221

38,310

121,740

3.3

11.6

3.5

11.6

Philadelphia. . . . . . . . . . . . . . . . . . . . .

1,011,828

1,045,878

1,015,771

1,039,802

48,946

162,299

53,083

171,396

4.8

15.5

5.2

16.5

Wilmington3. . . . . . . . . . . . . . . . . . . . .

381,139

368,209

380,628

381,435

13,078

51,409

15,713

46,374

3.4

14.0

4.1

12.2

Texas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13,926,760

13,464,075

14,009,283

13,844,386

435,592

1,711,194

520,024

1,231,582

3.1

12.7

3.7

8.9

Dallas-FortWorth-Arlington. . . . . . . . . .

3,926,375

3,829,800

3,960,641

3,957,398

115,327

469,577

136,815

331,426

2.9

12.3

3.5

8.4

Dallas-Plano-Irving. . . . . . . . . . . . . . .

2,643,980

2,585,170

2,669,214

2,669,803

78,161

313,049

92,125

221,370

3.0

12.1

3.5

8.3

Fort Worth-Arlington. . . . . . . . . . . . . .

1,282,395

1,244,630

1,291,427

1,287,595

37,166

156,528

44,690

110,056

2.9

12.6

3.5

8.5

Washington. . . . . . . . . . . . . . . . . . . . . . . . . .

3,888,371

3,937,461

3,919,625

3,965,560

158,985

582,895

164,802

384,109

4.1

14.8

4.2

9.7

Seattle-Tacoma-Bellevue. . . . . . . . . . . .

2,161,440

2,164,320

2,163,471

2,223,411

69,343

330,228

72,654

216,571

3.2

15.3

3.4

9.7

Seattle-Bellevue-Everett. . . . . . . . . . .

1,723,907

1,703,841

1,725,228

1,777,513

47,034

252,629

49,532

165,496

2.7

14.8

2.9

9.3

Tacoma-Lakewood. . . . . . . . . . . . . . .

437,533

460,479

438,243

445,898

22,309

77,599

23,122

51,075

5.1

16.9

5.3

11.5

  • These 11 areas contain all of the 38 metropolitan divisions.
  • Part of the area (or division) is in one or more adjacent states.
    3 All of the division is in one or more adjacent states. p Preliminary
    NOTE: Data refer to place of residence. Area delineations are based on Office of Management and Budget Bulletin No. 18-03, dated April 10, 2018, and are available on the BLS website at https://www.bls.gov/lau/lausmsa.htm. Areas in the six New England states are Metropolitan New England City and Town Areas (NECTAs), while areas in other states are county-based.Some metropolitan areas lie in two or more states. They are listed under the state containing the first principal city. Metropolitan divisions are listed under their metropolitan areas. Some divisions lie in more than one state, and some, like Camden, NJ, are totally outside the states under which their metropolitan areas are listed. For Washington-Arlington-Alexandria, DC-VA-MD-WV,the metropolitan area and division titles are identical. Estimates for the latest month are subject to revision the following month.

ESTABLISHMENT DATA

NOT SEASONALLY ADJUSTED

Table 3. Employees on nonfarm payrolls by state and metropolitan area, not seasonally adjusted

[In thousands]

May

June

Change from

State and area

June 2019 to June 2020p

2019

2020

2019

2020p

Number

Percent

Alabama. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,075.9

1,914.9

2,076.7

1,957.2

-119.5

-5.8

Anniston-Oxford-Jacksonville. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

47.4

42.0

47.4

43.3

-4.1

-8.6

Auburn-Opelika. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

66.3

63.3

66.3

61.1

-5.2

-7.8

Birmingham-Hoover. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

545.3

509.2

547.1

518.3

-28.8

-5.3

Daphne-Fairhope-Foley. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

81.8

73.7

83.1

79.7

-3.4

-4.1

Decatur. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

57.4

51.5

57.5

53.2

-4.3

-7.5

Dothan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

59.8

55.2

60.1

56.6

-3.5

-5.8

Florence-Muscle Shoals. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

57.6

52.1

57.2

54.1

-3.1

-5.4

Gadsden. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

37.7

33.1

37.6

34.1

-3.5

-9.3

Huntsville. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

245.1

227.9

244.6

233.2

-11.4

-4.7

Mobile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

186.5

170.8

186.5

173.3

-13.2

-7.1

Montgomery. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

178.7

163.5

178.3

166.1

-12.2

-6.8

Tuscaloosa. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

112.5

104.9

111.8

103.8

-8.0

-7.2

Alaska. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

334.5

292.4

349.3

308.3

-41.0

-11.7

Anchorage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

179.1

158.0

181.8

166.4

-15.4

-8.5

Fairbanks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

38.7

34.4

38.5

35.6

-2.9

-7.5

Arizona. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,919.6

2,755.4

2,869.8

2,775.1

-94.7

-3.3

Flagstaff. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

68.5

56.3

67.6

57.3

-10.3

-15.2

Lake Havasu City-Kingman. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

52.5

48.3

51.8

47.9

-3.9

-7.5

Phoenix-Mesa-Scottsdale. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,158.4

2,043.8

2,124.2

2,060.5

-63.7

-3.0

Prescott. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

66.0

63.9

65.2

64.6

-0.6

-0.9

Sierra Vista-Douglas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33.9

33.8

33.1

33.6

0.5

1.5

Tucson. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

389.7

368.9

379.4

368.8

-10.6

-2.8

Yuma. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

56.3

52.9

54.9

52.1

-2.8

-5.1

Arkansas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,284.0

1,192.4

1,272.4

1,210.9

-61.5

-4.8

Fayetteville-Springdale-Rogers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

263.9

251.3

261.0

253.8

-7.2

-2.8

Fort Smith. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

114.7

107.1

113.9

108.4

-5.5

-4.8

Hot Springs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

39.7

36.3

39.5

37.6

-1.9

-4.8

Jonesboro. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

60.0

57.7

59.6

57.8

-1.8

-3.0

Little Rock-North Little Rock-Conway. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

368.4

337.6

366.4

343.6

-22.8

-6.2

Pine Bluff. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33.0

31.3

32.5

31.6

-0.9

-2.8

California. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

17,415.3

15,136.4

17,453.9

15,701.8

-1,752.1

-10.0

Bakersfield. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

273.9

239.5

273.4

249.2

-24.2

-8.9

Chico. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

81.7

69.6

79.9

73.5

-6.4

-8.0

El Centro. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

53.4

48.0

53.7

50.4

-3.3

-6.1

Fresno. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

362.5

325.1

362.9

334.7

-28.2

-7.8

Hanford-Corcoran. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

41.4

37.4

40.9

38.2

-2.7

-6.6

Los Angeles-LongBeach-Anaheim. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6,229.7

5,366.8

6,235.8

5,585.4

-650.4

-10.4

Madera. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

39.3

36.2

39.7

36.0

-3.7

-9.3

Merced. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

71.2

62.3

69.7

64.3

-5.4

-7.7

Modesto. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

181.6

154.7

181.0

161.6

-19.4

-10.7

Napa. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

75.0

65.2

75.7

69.3

-6.4

-8.5

Oxnard-ThousandOaks-Ventura. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

313.1

270.7

312.4

280.6

-31.8

-10.2

Redding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

69.1

60.8

69.6

63.7

-5.9

-8.5

Riverside-SanBernardino-Ontario. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,537.3

1,351.4

1,538.6

1,392.7

-145.9

-9.5

Sacramento--Roseville--Arden-Arcade. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,018.6

898.7

1,023.3

926.7

-96.6

-9.4

Salinas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

147.4

119.7

147.2

127.1

-20.1

-13.7

San Diego-Carlsbad. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,504.8

1,301.7

1,509.3

1,355.7

-153.6

-10.2

San Francisco-Oakland-Hayward. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,476.9

2,128.3

2,489.4

2,204.5

-284.9

-11.4

San Jose-Sunnyvale-Santa Clara. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,145.2

1,017.8

1,152.0

1,058.8

-93.2

-8.1

San Luis Obispo-PasoRobles-Arroyo Grande. . . . . . . . . . . . . . . . . . . . . . . . . .

122.0

100.0

122.0

103.2

-18.8

-15.4

Santa Cruz-Watsonville. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

105.0

87.7

106.1

90.9

-15.2

-14.3

Santa Maria-Santa Barbara. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

189.0

161.1

189.9

167.7

-22.2

-11.7

Santa Rosa. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

208.3

181.0

208.8

190.1

-18.7

-9.0

Stockton-Lodi. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

245.9

218.6

245.3

225.6

-19.7

-8.0

Vallejo-Fairfield. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

144.0

123.5

144.7

126.2

-18.5

-12.8

Visalia-Porterville. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

129.1

114.7

128.8

119.4

-9.4

-7.3

Yuba City. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45.8

40.6

46.1

41.4

-4.7

-10.2

Colorado. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,774.3

2,539.0

2,798.4

2,620.5

-177.9

-6.4

See footnotes at end of table.

ESTABLISHMENT DATA

NOT SEASONALLY ADJUSTED

Table 3. Employees on nonfarm payrolls by state and metropolitan area, not seasonally adjusted - Continued

[In thousands]

May

June

Change from

State and area

June 2019 to June 2020p

2019

2020

2019

2020p

Number

Percent

Colorado - Continued

Boulder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

201.9

190.0

195.7

187.6

-8.1

-4.1

Colorado Springs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

300.3

278.4

300.9

287.7

-13.2

-4.4

Denver-Aurora-Lakewood. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,533.8

1,401.1

1,548.6

1,447.9

-100.7

-6.5

Fort Collins. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

175.4

162.6

175.0

166.3

-8.7

-5.0

Grand Junction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

66.0

61.7

64.7

63.6

-1.1

-1.7

Greeley. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

113.4

104.4

112.3

105.4

-6.9

-6.1

Pueblo. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

64.0

59.5

63.6

61.0

-2.6

-4.1

Connecticut. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,696.0

1,444.0

1,701.1

1,522.7

-178.4

-10.5

Bridgeport-Stamford-Norwalk. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

408.4

333.4

413.3

355.5

-57.8

-14.0

Danbury. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

78.3

66.3

78.6

71.4

-7.2

-9.2

Hartford-WestHartford-East Hartford. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

587.4

517.1

585.6

532.9

-52.7

-9.0

New Haven. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

289.9

252.5

289.0

267.2

-21.8

-7.5

Norwich-NewLondon-Westerly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

130.3

97.5

131.9

110.4

-21.5

-16.3

Waterbury. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

68.4

56.7

68.7

59.5

-9.2

-13.4

Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

468.3

398.8

470.3

421.0

-49.3

-10.5

Dover. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

71.0

63.1

70.6

65.9

-4.7

-6.7

Salisbury1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

168.0

140.1

176.3

154.1

-22.2

-12.6

District of Columbia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

793.4

727.6

798.9

740.3

-58.6

-7.3

Washington-Arlington-Alexandria. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,353.8

3,038.1

3,378.0

3,107.1

-270.9

-8.0

Florida. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8,950.3

8,123.5

8,838.6

8,311.5

-527.1

-6.0

Cape Coral-Fort Myers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

276.2

253.8

271.1

261.0

-10.1

-3.7

Crestview-Fort Walton Beach-Destin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

119.9

109.5

120.9

113.4

-7.5

-6.2

Deltona-DaytonaBeach-Ormond Beach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

206.6

191.9

203.1

197.7

-5.4

-2.7

Gainesville. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

146.2

136.6

143.0

135.9

-7.1

-5.0

Homosassa Springs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33.5

31.8

33.1

31.7

-1.4

-4.2

Jacksonville. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

721.5

676.9

717.0

690.0

-27.0

-3.8

Lakeland-Winter Haven. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

233.5

222.5

231.1

222.7

-8.4

-3.6

Miami-FortLauderdale-West Palm Beach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,719.7

2,427.8

2,684.0

2,486.6

-197.4

-7.4

Naples-Immokalee-Marco Island. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

155.0

140.4

150.6

142.8

-7.8

-5.2

North Port-Sarasota-Bradenton. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

314.6

283.7

309.4

293.7

-15.7

-5.1

Ocala. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

106.7

104.0

105.7

104.4

-1.3

-1.2

Orlando-Kissimmee-Sanford. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,326.7

1,114.0

1,314.5

1,144.7

-169.8

-12.9

Palm Bay-Melbourne-Titusville. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

231.3

218.5

230.0

223.9

-6.1

-2.7

Panama City. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

81.5

75.9

82.0

78.2

-3.8

-4.6

Pensacola-FerryPass-Brent. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

186.4

171.7

184.3

175.6

-8.7

-4.7

Port St. Lucie. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

156.2

148.4

152.8

150.3

-2.5

-1.6

Punta Gorda. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

49.9

46.7

49.2

47.3

-1.9

-3.9

Sebastian-Vero Beach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

54.5

50.2

53.6

50.2

-3.4

-6.3

Sebring. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

26.4

25.8

25.9

25.5

-0.4

-1.5

Tallahassee. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

186.0

172.2

181.4

171.7

-9.7

-5.3

Tampa-St.Petersburg-Clearwater. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,382.4

1,283.2

1,369.9

1,309.3

-60.6

-4.4

The Villages. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

32.0

31.3

31.4

31.5

0.1

0.3

Georgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4,613.5

4,229.8

4,609.4

4,370.9

-238.5

-5.2

Albany. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

62.9

58.1

62.9

59.4

-3.5

-5.6

Athens-Clarke County. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

96.8

90.6

95.5

91.7

-3.8

-4.0

Atlanta-SandySprings-Roswell. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2,843.4

2,600.3

2,845.4

2,688.1

-157.3

-5.5

Augusta-Richmond County. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

243.4

225.8

242.6

229.4

-13.2

-5.4

Brunswick. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45.2

36.9

45.4

38.0

-7.4

-16.3

Columbus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

123.5

110.7

122.4

114.0

-8.4

-6.9

Dalton. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

66.5

62.0

66.4

63.0

-3.4

-5.1

Gainesville. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

93.3

86.6

93.3

87.8

-5.5

-5.9

Hinesville. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

21.3

20.9

21.0

21.2

0.2

1.0

Macon-Bibb County. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

103.1

94.6

103.0

96.5

-6.5

-6.3

Rome. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

41.8

40.9

41.8

42.0

0.2

0.5

Savannah. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

187.9

168.4

187.8

175.0

-12.8

-6.8

Valdosta. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

56.4

52.9

56.2

54.6

-1.6

-2.8

Warner Robins. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

77.8

71.6

77.9

72.4

-5.5

-7.1