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Tag Archives: Unemployment

BLS Now Publishing Monthly Data for American Indians and Alaska Natives

I am pleased to announce that BLS is now publishing monthly labor force estimates for American Indians and Alaska Natives! For years we’ve published a small set of annual labor market estimates for American Indians and Alaska Natives in our yearly report on labor force characteristics by race and ethnicity. And we’ve also combined multiple years of data to do more in-depth analyses. But we haven’t published our key economic metrics—such as the unemployment rate, the employment–population ratio, and the labor force participation rate—on a monthly basis for American Indians and Alaska Natives. Monthly estimates give us timely measures to see how groups are faring in the labor market.

The jobless rate for American Indians and Alaska Natives peaked at 28.6 percent in April 2020 (not seasonally adjusted), early in the COVID-19 pandemic. This was nearly double the seasonally adjusted rate of 14.7 percent for the total population. The higher rate for American Indians and Alaska Natives reflects, in part, the extremely sharp increase at the start of the pandemic in the unemployment rate for service occupations. American Indians and Alaska Natives are considerably more likely to work in service occupations compared with the overall labor force. By contrast, the unemployment rate rose less sharply at the start of the pandemic for management, professional, and related occupations and other occupation groups in which American Indians and Alaska Natives are less represented. The unemployment rate for American Indians and Alaska Natives has declined since April 2020 and was 11.1 percent in January 2022, still much higher than the rate of 4.0 percent for the overall population.

Unemployment rates for American Indians and Alaska Natives and for the total population, January 2003 to January 2022

Editor’s note: Data for this chart are available in the table below.

In general, American Indians and Alaska Natives are less likely than the overall population to be employed. In April 2020, the employment–population ratio for American Indians and Alaska Natives declined to 42.4 percent, 8.9 percentage points below the ratio of 51.3 percent for the overall population. Since then, the ratio for American Indians and Alaska Natives has risen and stood at 52.7 percent in January 2022, 7.0 percentage points below the ratio of 59.7 percent for the population overall.

Employment–population ratios for American Indians and Alaska Natives and for the total population, January 2003 to January 2022

Editor’s note: Data for this chart are available in the table below.

The measures for American Indians and Alaska Natives tend to be fairly volatile for two main reasons. First, the estimates are based on a small sample size. We survey about 60,000 U.S. households every month, and respondents who identify as American Indians and Alaska Natives make up about 1 percent of the labor force. Because of that small sample size, the month-to-month change in the unemployment rate must be pretty large to be statistically significant—around 3 percentage points.

Second, these data are not seasonally adjusted. Seasonal adjustment is a statistical procedure used to remove the effects of seasonality from data so it’s easier to see underlying trends. But not all data series can be seasonally adjusted; they must pass a battery of diagnostic tests to be fitted to a seasonal adjustment model. So far, we haven’t been able to do that for data for American Indians and Alaska Natives, but we’ll keep evaluating them as we get more data. Because these data aren’t seasonally adjusted, it can be challenging to compare one month to the following month.

We’re also publishing quarterly estimates for American Indians and Alaska Natives for the first time starting this month. Because these estimates are averages of three months of data, they are somewhat less volatile.

Unemployment rates for American Indians and Alaska Natives and for the total population, January 2003 to January 2022
MonthTotalAmerican Indians and Alaska Natives

Jan 2003

5.8%10.0%

Feb 2003

5.914.2

Mar 2003

5.913.1

Apr 2003

6.010.8

May 2003

6.111.8

Jun 2003

6.39.7

Jul 2003

6.28.8

Aug 2003

6.17.9

Sep 2003

6.18.4

Oct 2003

6.09.5

Nov 2003

5.812.7

Dec 2003

5.78.2

Jan 2004

5.710.9

Feb 2004

5.612.2

Mar 2004

5.811.7

Apr 2004

5.69.6

May 2004

5.610.4

Jun 2004

5.68.2

Jul 2004

5.58.2

Aug 2004

5.49.3

Sep 2004

5.47.8

Oct 2004

5.58.0

Nov 2004

5.49.2

Dec 2004

5.410.2

Jan 2005

5.313.5

Feb 2005

5.411.3

Mar 2005

5.211.1

Apr 2005

5.210.6

May 2005

5.110.0

Jun 2005

5.08.3

Jul 2005

5.08.8

Aug 2005

4.99.0

Sep 2005

5.07.0

Oct 2005

5.07.6

Nov 2005

5.06.8

Dec 2005

4.98.0

Jan 2006

4.79.2

Feb 2006

4.89.1

Mar 2006

4.77.0

Apr 2006

4.77.5

May 2006

4.67.6

Jun 2006

4.68.3

Jul 2006

4.78.9

Aug 2006

4.77.7

Sep 2006

4.57.2

Oct 2006

4.47.0

Nov 2006

4.59.0

Dec 2006

4.46.5

Jan 2007

4.69.9

Feb 2007

4.510.9

Mar 2007

4.49.4

Apr 2007

4.55.8

May 2007

4.46.2

Jun 2007

4.67.2

Jul 2007

4.79.9

Aug 2007

4.69.9

Sep 2007

4.76.9

Oct 2007

4.77.7

Nov 2007

4.76.4

Dec 2007

5.07.8

Jan 2008

5.07.4

Feb 2008

4.910.6

Mar 2008

5.19.2

Apr 2008

5.010.4

May 2008

5.48.6

Jun 2008

5.611.3

Jul 2008

5.813.3

Aug 2008

6.112.3

Sep 2008

6.19.7

Oct 2008

6.58.0

Nov 2008

6.87.9

Dec 2008

7.310.3

Jan 2009

7.812.3

Feb 2009

8.313.1

Mar 2009

8.79.8

Apr 2009

9.08.7

May 2009

9.413.0

Jun 2009

9.513.7

Jul 2009

9.518.3

Aug 2009

9.615.1

Sep 2009

9.815.0

Oct 2009

10.013.9

Nov 2009

9.913.1

Dec 2009

9.914.9

Jan 2010

9.816.4

Feb 2010

9.814.4

Mar 2010

9.917.9

Apr 2010

9.912.7

May 2010

9.613.2

Jun 2010

9.414.3

Jul 2010

9.416.4

Aug 2010

9.517.8

Sep 2010

9.514.4

Oct 2010

9.415.4

Nov 2010

9.813.9

Dec 2010

9.314.8

Jan 2011

9.118.4

Feb 2011

9.014.8

Mar 2011

9.012.1

Apr 2011

9.110.2

May 2011

9.012.6

Jun 2011

9.115.3

Jul 2011

9.014.7

Aug 2011

9.014.4

Sep 2011

9.016.1

Oct 2011

8.815.4

Nov 2011

8.617.2

Dec 2011

8.513.7

Jan 2012

8.311.7

Feb 2012

8.314.2

Mar 2012

8.214.1

Apr 2012

8.212.8

May 2012

8.29.4

Jun 2012

8.212.2

Jul 2012

8.211.8

Aug 2012

8.111.9

Sep 2012

7.811.4

Oct 2012

7.811.8

Nov 2012

7.712.5

Dec 2012

7.913.4

Jan 2013

8.013.0

Feb 2013

7.710.5

Mar 2013

7.512.7

Apr 2013

7.610.9

May 2013

7.59.9

Jun 2013

7.512.8

Jul 2013

7.314.3

Aug 2013

7.213.8

Sep 2013

7.213.1

Oct 2013

7.213.9

Nov 2013

6.914.5

Dec 2013

6.713.5

Jan 2014

6.612.4

Feb 2014

6.712.6

Mar 2014

6.713.0

Apr 2014

6.211.0

May 2014

6.311.1

Jun 2014

6.110.8

Jul 2014

6.212.7

Aug 2014

6.111.0

Sep 2014

5.99.4

Oct 2014

5.712.3

Nov 2014

5.810.7

Dec 2014

5.69.1

Jan 2015

5.711.8

Feb 2015

5.511.2

Mar 2015

5.410.7

Apr 2015

5.49.5

May 2015

5.68.4

Jun 2015

5.310.8

Jul 2015

5.211.6

Aug 2015

5.19.4

Sep 2015

5.07.9

Oct 2015

5.08.5

Nov 2015

5.110.3

Dec 2015

5.08.8

Jan 2016

4.89.9

Feb 2016

4.99.3

Mar 2016

5.09.9

Apr 2016

5.18.0

May 2016

4.89.2

Jun 2016

4.99.5

Jul 2016

4.88.2

Aug 2016

4.99.7

Sep 2016

5.09.9

Oct 2016

4.96.6

Nov 2016

4.78.6

Dec 2016

4.78.2

Jan 2017

4.78.6

Feb 2017

4.67.4

Mar 2017

4.49.8

Apr 2017

4.48.3

May 2017

4.48.8

Jun 2017

4.39.1

Jul 2017

4.37.6

Aug 2017

4.47.4

Sep 2017

4.36.5

Oct 2017

4.26.8

Nov 2017

4.26.2

Dec 2017

4.17.8

Jan 2018

4.09.7

Feb 2018

4.17.9

Mar 2018

4.08.8

Apr 2018

4.07.5

May 2018

3.87.0

Jun 2018

4.06.5

Jul 2018

3.85.1

Aug 2018

3.84.3

Sep 2018

3.75.4

Oct 2018

3.86.1

Nov 2018

3.85.2

Dec 2018

3.96.3

Jan 2019

4.06.9

Feb 2019

3.86.4

Mar 2019

3.86.1

Apr 2019

3.66.1

May 2019

3.65.5

Jun 2019

3.66.7

Jul 2019

3.76.4

Aug 2019

3.74.9

Sep 2019

3.55.3

Oct 2019

3.66.0

Nov 2019

3.66.8

Dec 2019

3.65.7

Jan 2020

3.57.3

Feb 2020

3.57.5

Mar 2020

4.47.4

Apr 2020

14.728.6

May 2020

13.218.0

Jun 2020

11.013.1

Jul 2020

10.213.0

Aug 2020

8.410.3

Sep 2020

7.96.7

Oct 2020

6.910.8

Nov 2020

6.78.6

Dec 2020

6.710.0

Jan 2021

6.410.1

Feb 2021

6.212.1

Mar 2021

6.07.9

Apr 2021

6.09.2

May 2021

5.89.5

Jun 2021

5.97.7

Jul 2021

5.47.2

Aug 2021

5.28.5

Sep 2021

4.75.9

Oct 2021

4.65.7

Nov 2021

4.26.7

Dec 2021

3.97.9

Jan 2022

4.011.1

Note: Monthly data for American Indians and Alaska Natives are not seasonally adjusted. The total unemployment rate is seasonally adjusted.

Employment–population ratios for American Indians and Alaska Natives and for the total population, January 2003 to January 2022
MonthTotalAmerican Indians and Alaska Natives

Jan 2003

62.5%57.9%

Feb 2003

62.556.4

Mar 2003

62.457.8

Apr 2003

62.458.1

May 2003

62.358.9

Jun 2003

62.360.9

Jul 2003

62.159.9

Aug 2003

62.158.1

Sep 2003

62.055.1

Oct 2003

62.155.4

Nov 2003

62.354.7

Dec 2003

62.258.7

Jan 2004

62.356.0

Feb 2004

62.356.9

Mar 2004

62.257.0

Apr 2004

62.357.9

May 2004

62.359.2

Jun 2004

62.461.5

Jul 2004

62.562.4

Aug 2004

62.459.6

Sep 2004

62.355.2

Oct 2004

62.355.5

Nov 2004

62.554.9

Dec 2004

62.455.8

Jan 2005

62.453.6

Feb 2005

62.454.1

Mar 2005

62.456.3

Apr 2005

62.759.2

May 2005

62.856.7

Jun 2005

62.760.1

Jul 2005

62.860.1

Aug 2005

62.957.5

Sep 2005

62.859.4

Oct 2005

62.858.6

Nov 2005

62.757.7

Dec 2005

62.857.4

Jan 2006

62.955.6

Feb 2006

63.057.7

Mar 2006

63.157.1

Apr 2006

63.056.1

May 2006

63.158.5

Jun 2006

63.158.7

Jul 2006

63.058.7

Aug 2006

63.159.6

Sep 2006

63.158.8

Oct 2006

63.360.7

Nov 2006

63.357.3

Dec 2006

63.458.4

Jan 2007

63.354.5

Feb 2007

63.356.9

Mar 2007

63.359.7

Apr 2007

63.061.6

May 2007

63.060.2

Jun 2007

63.058.2

Jul 2007

62.956.9

Aug 2007

62.758.0

Sep 2007

62.959.1

Oct 2007

62.757.7

Nov 2007

62.957.6

Dec 2007

62.756.7

Jan 2008

62.956.9

Feb 2008

62.857.7

Mar 2008

62.759.3

Apr 2008

62.758.1

May 2008

62.556.8

Jun 2008

62.457.8

Jul 2008

62.254.3

Aug 2008

62.053.1

Sep 2008

61.957.5

Oct 2008

61.759.3

Nov 2008

61.459.2

Dec 2008

61.058.8

Jan 2009

60.656.5

Feb 2009

60.352.9

Mar 2009

59.954.4

Apr 2009

59.853.5

May 2009

59.650.6

Jun 2009

59.450.1

Jul 2009

59.347.5

Aug 2009

59.149.5

Sep 2009

58.749.6

Oct 2009

58.550.6

Nov 2009

58.649.1

Dec 2009

58.349.0

Jan 2010

58.548.3

Feb 2010

58.550.3

Mar 2010

58.550.6

Apr 2010

58.751.4

May 2010

58.650.2

Jun 2010

58.548.6

Jul 2010

58.546.3

Aug 2010

58.647.1

Sep 2010

58.548.2

Oct 2010

58.348.4

Nov 2010

58.248.8

Dec 2010

58.349.1

Jan 2011

58.350.6

Feb 2011

58.450.4

Mar 2011

58.453.6

Apr 2011

58.453.9

May 2011

58.351.2

Jun 2011

58.249.2

Jul 2011

58.249.9

Aug 2011

58.350.7

Sep 2011

58.449.6

Oct 2011

58.449.0

Nov 2011

58.648.5

Dec 2011

58.650.0

Jan 2012

58.450.8

Feb 2012

58.550.4

Mar 2012

58.551.2

Apr 2012

58.451.1

May 2012

58.553.4

Jun 2012

58.652.7

Jul 2012

58.553.3

Aug 2012

58.451.6

Sep 2012

58.753.4

Oct 2012

58.853.5

Nov 2012

58.752.0

Dec 2012

58.751.3

Jan 2013

58.648.4

Feb 2013

58.652.4

Mar 2013

58.552.1

Apr 2013

58.653.2

May 2013

58.654.0

Jun 2013

58.652.4

Jul 2013

58.751.3

Aug 2013

58.750.4

Sep 2013

58.752.4

Oct 2013

58.351.9

Nov 2013

58.651.3

Dec 2013

58.750.2

Jan 2014

58.849.9

Feb 2014

58.751.3

Mar 2014

58.952.4

Apr 2014

58.951.5

May 2014

58.954.3

Jun 2014

59.054.1

Jul 2014

59.054.2

Aug 2014

59.055.2

Sep 2014

59.154.9

Oct 2014

59.356.0

Nov 2014

59.255.1

Dec 2014

59.357.3

Jan 2015

59.356.0

Feb 2015

59.254.1

Mar 2015

59.255.0

Apr 2015

59.352.2

May 2015

59.453.4

Jun 2015

59.452.7

Jul 2015

59.354.1

Aug 2015

59.456.0

Sep 2015

59.257.6

Oct 2015

59.356.3

Nov 2015

59.453.3

Dec 2015

59.654.4

Jan 2016

59.753.6

Feb 2016

59.855.2

Mar 2016

59.855.1

Apr 2016

59.753.9

May 2016

59.754.0

Jun 2016

59.753.9

Jul 2016

59.854.7

Aug 2016

59.855.2

Sep 2016

59.758.4

Oct 2016

59.759.0

Nov 2016

59.758.0

Dec 2016

59.757.2

Jan 2017

59.954.9

Feb 2017

60.057.6

Mar 2017

60.254.7

Apr 2017

60.253.7

May 2017

60.153.7

Jun 2017

60.155.2

Jul 2017

60.257.1

Aug 2017

60.155.9

Sep 2017

60.457.3

Oct 2017

60.157.0

Nov 2017

60.154.9

Dec 2017

60.154.4

Jan 2018

60.251.9

Feb 2018

60.453.3

Mar 2018

60.454.6

Apr 2018

60.455.0

May 2018

60.556.4

Jun 2018

60.457.7

Jul 2018

60.558.5

Aug 2018

60.358.1

Sep 2018

60.456.1

Oct 2018

60.555.6

Nov 2018

60.555.4

Dec 2018

60.655.0

Jan 2019

60.654.2

Feb 2019

60.856.6

Mar 2019

60.757.7

Apr 2019

60.657.1

May 2019

60.656.9

Jun 2019

60.757.6

Jul 2019

60.858.0

Aug 2019

60.858.8

Sep 2019

60.957.0

Oct 2019

60.956.3

Nov 2019

61.058.3

Dec 2019

61.056.8

Jan 2020

61.155.9

Feb 2020

61.254.2

Mar 2020

59.954.3

Apr 2020

51.342.4

May 2020

52.848.4

Jun 2020

54.752.9

Jul 2020

55.252.5

Aug 2020

56.553.7

Sep 2020

56.655.8

Oct 2020

57.452.8

Nov 2020

57.453.3

Dec 2020

57.452.3

Jan 2021

57.551.3

Feb 2021

57.653.6

Mar 2021

57.855.2

Apr 2021

57.954.1

May 2021

58.056.5

Jun 2021

58.057.8

Jul 2021

58.458.0

Aug 2021

58.554.3

Sep 2021

58.856.7

Oct 2021

58.956.8

Nov 2021

59.356.6

Dec 2021

59.555.6

Jan 2022

59.752.7

Note: Monthly data for American Indians and Alaska Natives are not seasonally adjusted. The total employment–population ratio is seasonally adjusted.

BLS at the Olympics

When you find yourself in a 16-day marathon on the sofa shouting “U-S-A, U-S-A” at every swimmer, weightlifter, and beach volleyball player, you may not see the relationship to the U.S. Bureau of Labor Statistics. But as you sprint through the pages of our website or add your likes to Twitter, you’ll begin to see how BLS has a stat for that.

Olympic symbol with five interlocking rings and BLS emblem

Uneven bars

As we head into the gymnastics venue, we notice one of the women’s apparatus reminds us of how we measure productivity. We use two factors to compute labor productivity—output and hours worked. Over the past decade, the “bars” for output and hours worked aren’t quite parallel, but they are definitely uneven; output grew a little faster than hours, leading to rising productivity.  The COVID-19 pandemic resulted in sharp drops in both output and hours, leaving productivity to maintain its steady climb. BLS productivity staff stick the landing by providing a series of quarterly charts to let you vault into all the details.

Labor productivity (output per hour), output, and hours worked indexes, nonfarm business, 2012 to 2021

Editor’s note: Data for this chart are available in our interactive chart packages.

Decathlon

You may not have to run, jump, and throw, but the fastest growing occupations from our annual employment projections represent a diversity of skills. A decathlon has 10 events, but we have so much Olympic spirit we want to show you the 12 fastest growing occupations. Half of these jobs are in the healthcare field, while a couple involve alternative forms of energy. And, of course, BLS is pleased to see statisticians and data scientists and mathematical science occupations make the list. While the “World’s Greatest Athlete” is decided at the track and field venue, our Employment Projections staff goes the extra mile (1,500 meters, actually) to identify where the jobs will be in the future.

Fastest growing occupations, projected, 2019–29

Editor’s note: Data for this chart are available in the table below.

Swimming 4×100 medley relay

At the natatorium, we are here to witness one of the premier events of the Olympic Games, the swimming 4×100 medley relay. Four price indexes will each take a lap to demonstrate how they work together to provide a complete inflation picture. In the leadoff position is the Import Price Index, which rose 11.2 percent from June 2020 to June 2021—with fuel prices being one of the largest drivers. After touching the wall first, imports made way for the Producer Price Index, which rose 7.3 percent for the year ending in June. Price increases for a variety of goods drove this gain. The third leg belonged to the Export Price Index, which rose 16.8 percent over the past year, the largest gain among the quartet. Agricultural products were among the largest contributors to the increase in export prices. In the anchor position was the Consumer Price Index, freestyling with a 5.4-percent increase over the year, leading BLS to the gold medal. Among the largest increases over the past year were consumer prices for gasoline and for used cars and trucks.

Percent change in BLS price indexes, June 2020 to June 2021

Editor’s note: Data for this chart are available in the table below.

Greco-Roman wrestling

We bypassed the freestyle wrestling venue to watch Greco-Roman wrestling. The difference between freestyle and Greco-Roman wrestling is that freestyle wrestlers can use their legs for both defensive and offensive moves, but Greco-Roman forbids any holds below the waist. Our Survey of Occupational Injuries and Illnesses reports on the part of the body where workplace injuries occur, and, just like Greco-Roman, many of those occur above the waist.

Among workplace injuries that resulted in time away from work, nearly two out of three affected parts of the body above the waist, with the greatest number related to the upper extremities (shoulder, arm, hand, and wrist).

Number of workplace injuries and illnesses requiring days away from work, by part of body, 2019

Editor’s note: Data for this chart are available in the table below.

Among the most prevalent injuries to the upper extremities were sprains, strains, punctures, cuts, and burns.

Beach volleyball

This popular sport takes place out on the sandy beaches, with two athletes on each side battling for the gold. Let’s look at some popular beach volleyball spots around the United States and pair them with the unemployment rates by state and metropolitan area. Florida serves up the lowest unemployment rate among the four states we have selected, at 5.7 percent (not seasonally adjusted) in June. Miami had an unemployment rate of 6.2 percent in June—the lowest among the metro areas chosen. Receiving the serve, Hawaii’s rate stood at a 7.9 percent. They bumped it to their teammate Illinois, which also had a rate of 7.9 percent. California reached a little higher, with a rate of 8.0 percent.

Unemployment rates in selected beach volleyball states and metropolitan areas, June 2021, not seasonally adjusted

Editor’s note: Data for this chart are available in the table below.

BLS heads to Tokyo

Just as the United States exports its athletes to Japan for the Olympic Games, the two countries are regular trading partners. The BLS International Price Program provides a monthly look at inflation for U.S. imports and exports. Among the data available are price changes based on where the imports come from and where the exports go. And yes, this includes data for Japan. While we’ve seen increases in many inflation measures in recent months, the data show more modest increases in prices of U.S. imports from Japan. Not so for U.S. exports to Japan, which increased 15.8 percent from June 2020 to June 2021. No, this does not represent the price of exporting our athletes; it mostly relates to sharp increases in the price of agricultural exports.

Percent change in U.S. import and export prices, June 2020 to June 2021

Editor’s note: Data for this chart are available in the table below.

Whether it’s weightlifting or dressage or the new sports climbing activities, BLS is cheering on the U.S. Olympians and Paralympians in Japan. At the same time, we’ll still be keeping to our data release schedule. Find out what’s available from BLS during August and September and be sure to follow BLS on Twitter.

Fastest growing occupations, projected, 2019–29
OccupationProjected percent change

Wind turbine service technicians

60.7%

Nurse practitioners

52.4

Solar photovoltaic installers

50.5

Occupational therapy assistants

34.6

Statisticians

34.6

Home health and personal care aides

33.7

Physical therapist assistants

32.6

Medical and health services managers

31.5

Physician assistants

31.3

Information security analysts

31.2

Data scientists and mathematical science occupations, all other

30.9

Derrick operators, oil and gas

30.5
Percent change in BLS price indexes, June 2020 to June 2021
Price indexPercent change

Import Price Index

11.2%

Producer Price Index

7.3

Export Price Index

16.8

Consumer Price Index

5.4
Number of workplace injuries and illnesses requiring days away from work, by part of body, 2019
Part of bodyNumber

Upper extremities (shoulder, arm, hand, wrist)

284,860

Lower extremities (knee, ankle, foot)

216,850

Trunk

187,130

Multiple body parts

82,650

Head

79,620

Body systems

15,150

Neck

11,600

All other body parts

10,360
Unemployment rates in selected beach volleyball states and metropolitan areas, June 2021, not seasonally adjusted
State or metropolitan areaRate

States

Florida

5.7%

Hawaii

7.9

Illinois

7.9

California

8.0

Metropolitan areas

Miami

6.2

Honolulu

7.1

Chicago

8.5

Los Angeles

9.5
Percent change in U.S. import and export prices, June 2020 to June 2021
Price indexAll countriesJapan

Import prices

11.2%1.8%

Export prices

16.815.8

Improving Key Labor Market Estimates during the Pandemic and Beyond

If things were good enough yesterday, why would we change them today? Good enough is OK for folding laundry, cleaning the junk drawer, and raking leaves, but not for official statistics from BLS. We do our best to provide a timely look at the labor market and economy, but we often learn more after we publish those initial data. As a result, we sometimes revise our statistics. That’s mostly a good thing, but there is a fine line between the frequency of revisions and introducing noise and possibly confusion.

I recently wrote about the importance of maintaining and sometimes changing official historical records, using baseball as an example. Today I want to highlight two of our statistical programs: the Job Openings and Labor Turnover Survey (JOLTS) and the Local Area Unemployment Statistics (LAUS) data. We publish monthly statistics from these programs and revise them the following month as more information comes in. In addition to the monthly revisions, we incorporate more information once a year.

The COVID-19 pandemic continues to have a huge impact on our lives. Check out our summary of how the pandemic affected the labor market and economy in 2020. The magnitude of the labor market changes stress tested the JOLTS and LAUS programs. Based on what we observed in real time, and what we know now, we realized we needed to respond to this unusual economic environment. We change our estimating techniques infrequently, but even the best techniques need adjustments to respond to such significant shocks. These adjustments reflect our commitment to continuous improvement.

Changes in Job Openings and Labor Turnover Estimates

The economic conditions caused by the pandemic led us to make two changes to JOLTS procedures. First, we changed the way we handled unusual reports, which we call outliers. In normal times, these outliers may be businesses with unusually large numbers of job separations. This process mutes the outlier impact on the estimates because those outliers are unlikely to represent other businesses. At the start of the pandemic, however, very large increases in separations were followed by very large increases in hires in many businesses. During this period, we adjusted the JOLTS outlier-detection techniques to accept as normal those extreme changes. Under these circumstances, these “outlier” reports did in fact represent many other businesses.

Second, JOLTS uses data from the much larger Current Employment Statistics (CES) sample to adjust estimates of hires and separations to stay in sync with the monthly employment changes. This procedure assumes that, over the long term, the difference between JOLTS hires and separations is close to the CES employment change. This assumption, however, was not appropriate in late March 2020 as people, businesses, and governments tried to contain the spread of COVID-19. The two surveys have different reference periods. The CES reference period is the pay period that includes the 12th of the month, whereas JOLTS estimates of hires and separations cover the entire month. Hires and separations during the latter half of March 2020 were not included in the CES employment change for March but were included in the JOLTS estimates for the month. To accurately capture the timing of this unprecedented event, we stopped aligning the JOLTS estimates of hires and separations with the CES employment change from March through November 2020.

More changes to JOLTS estimates came with the publication of the January 2021 news release. As we do every year, we revised the past 5 years of historical JOLTS data using updated CES employment estimates. We also updated the seasonal adjustment factors and applied them over the past 5 years. In addition, because we stopped using the alignment procedure for most of 2020, the difference between CES and JOLTS estimates had become quite large by December. To preserve the true economic differences between CES and JOLTS but reduce the divergence by the end of 2020, we adjusted estimates of hires and separations for the months in which the alignment procedure was turned off. These adjustments ensure that we report the highest quality data as quickly as we can, while improving accuracy as we learn more information.

Changes in State Labor Force and Unemployment Estimates

We also made real-time changes during the pandemic to the models we use to produce state labor force and unemployment estimates. The primary inputs to the models are from the Current Population Survey (CPS), the source of the monthly national unemployment rate and other labor market measures. Because the CPS sample is not large enough to support state estimates on a monthly basis, we also use CES employment data and counts of continued claims for unemployment insurance to help inform the models. All of these model inputs experienced extreme movements, especially in the early part of the pandemic.

Starting with March 2020, we introduced two monthly adjustments we usually perform only once a year. These adjustments involved closer review and adjustment of outliers from all model inputs and level shifts. We discussed these changes in notes that appeared in the State Employment and Unemployment news releases for March 2020, April 2020, and May 2020.

These changes in 2020 provided a short-term solution for the state models. For the longer term, we respecified the relationships of the model inputs to provide more flexibility when unusual disruptions occur in the labor market. We explain these changes in our “Questions and Answers.”

We implemented the new estimation procedures for model-based areas in early 2021. They were reflected in the estimates published in the Regional and State Unemployment – 2020 Annual Averages news release. We replaced all previously published state data using the new procedures to ensure historically comparable estimates. The recent data revisions also reflect the best available inputs for model estimation. If you are interested in the details, you can read all about them at the LAUS Estimation Methodology page.

The speed with which the JOLTS and LAUS staff researched and implemented these improvements reflects the high quality of the BLS staff and their commitment to producing gold standard data. They make me proud to lead this great agency.

Looking Back on the 2020 U.S. Labor Market and Economy

I know many of us are glad to see 2020 in the rearview mirror and have higher hopes for 2021. The COVID-19 pandemic has caused so much suffering and hardship for people in the United States and around the world. During these challenging times, it remains important to have good, reliable, timely data. Good data are essential for the public health response to the pandemic and for tracking its economic and social effects, as well as the progress toward recovery. Let’s reflect back on some of the historic measures we saw in 2020.

Throughout the pandemic, the BLS staff and our colleagues across the statistical community have remained on the job to meet the growing needs for high-quality data. We are thankful we have been able to keep working; millions of other people haven’t been so fortunate. In part this is due to the way our work life at BLS changed in 2020. Nearly the entire staff has teleworked full time since March. That means we have needed to figure out new ways to collaborate with each other to continue producing essential data about the economy. That change in work life also meant that many staff members faced the challenges of new care arrangements for young children, schooling—often online—for older children, and keeping all their loved ones safe and healthy.

When the pandemic began in March 2020, many consumers began avoiding stores, restaurants, and other public gatherings to reduce the risk of catching or spreading the virus that causes COVID-19. Many businesses and other organizations reduced their operations or closed completely. At the recommendation of public health authorities, many governors and other public leaders issued stay-at-home orders. The economic impact of COVID-19 was breathtaking in its speed and severity.

National employment data. The nation experienced steady employment growth in recent years; BLS recorded average monthly increases in nonfarm employment between about 170,000 and 200,000 from 2016 to 2019. January and February 2020 brought continued job gains before the bottom dropped out in March (down 1.7 million jobs) and especially in April (down 20.7 million). These were the two largest declines in history, dating to 1939. These declines were then followed by the 4 largest increases in history: 2.8 million, 4.8 million, 1.7 million, and 1.5 million. You have to go back to 1983 to find the next highest increase, 1,118,000. Employment in December 2020 was nearly 10 million lower than in February.

Nonfarm payroll employment, January 1970–December 2020

Editor’s note: Data for this chart are available in the table below.

National unemployment data. The year started with some record-low unemployment rates. The 3.5-percent unemployment rate in both January and February 2020 tied for the lowest rate since December 1969 (also 3.5 percent). The unemployment rates for several demographic groups were at or near their record lows. For example, the unemployment rate for African Americans in February 2020, at 6.0 percent, was close to the all-time low of 5.2 percent in August 2019.

Then came the pandemic in March 2020. The unemployment rate that month rose 0.9 percentage point to 4.4 percent. In April, the unemployment rate increased by 10.4 percentage points to 14.8 percent, the highest rate and largest one-month increase in history (dating to January 1948). Nearly all demographic groups experienced record-high unemployment rates in April; for example, the rate for Hispanics was a record 18.9 percent, after a record low of 4.0 percent in September 2019. And for the first time since data became available for both groups in 1973, the unemployment rate for Hispanics in April 2020 exceeded the rate for African Americans.

Unemployment rates for selected groups, February, April, and December 2020

Editor’s note: Data for this chart are available in the table below.

State unemployment data. We see a similar pattern when looking at state unemployment rates, with record-setting lows early in 2020 followed by record-setting highs. In February, state unemployment rates ranged from a low of 2.2 percent in North Dakota to a high of 5.8 percent in Alaska, with 12 states at their historic lows that month. By April, rates had increased in all states, with 40 states and the District of Columbia setting new highs in that month, and another 7 states cresting in subsequent months. (The state data began in 1976.) State unemployment rates in April ranged from 8.3 percent in Connecticut to 30.1 percent in Nevada. Check out our animated map showing the rapid transformation of state unemployment rates.

Consumer price data. Beyond the job market, the pandemic had a big effect on other aspects of everyday life, including consumers’ buying habits. Toilet paper and wipes were disappearing from store shelves, while fewer people were commuting or traveling. Those trends were reflected in rapid changes in consumer prices.

One-month changes in the Consumer Price Index are typically 0.1 or 0.2 percent; the 0.8 percent decrease in April 2020, was the largest monthly decline since December 2008. The overall change included some large movements in both directions. For example, the price of gasoline declined 20.6 percent in April, the largest one-month decline since November 2008. In contrast, prices for food at home rose by 2.6 percent, the largest monthly increase since February 1974. Looking below the surface even further, several items experienced record one-month price changes, with some records going back over 50 years.

Percent change in consumer prices for selected items in April 2020, seasonally adjusted

Editor’s note: Data for this chart are available in the table below.

Labor Productivity data. The BLS quarterly measure of labor productivity in the nonfarm business sector compares output to hours worked. If output rises more than hours worked, productivity increases. The pandemic saw large declines in both output and hours starting in mid-March. There was a small decline in labor productivity in the first quarter of 2020, down 0.3 percent, as output declined (-6.4 percent) slightly more than hours worked (-6.1 percent). While we had not experienced declining productivity in nearly 3 years, small increases or decreases in the quarterly change are common. The second quarter saw labor productivity soar by 10.6 percent, the largest increase since 1971, when productivity increased 12.3 percent in the first quarter. The second quarter 2020 increase reflected a greater decline in hours worked (-42.9 percent) than in output (-36.8 percent).

Since its beginnings in 1884, BLS has built consistent data to allow comparisons across the decades. Maintaining this history allows data users to quickly learn “when was the last time.” We also have collected and published new data specifically about the COVID-19 pandemic. Still to come, BLS will release more 2020 data in the coming year. Those new results will add to the unique story of the extraordinary 2020 economy.

Nonfarm payroll employment, January 1970–December 2020
MonthEmployment levelOver-the-month change

Jan 1970

71,176,000-65,000

Feb 1970

71,305,000129,000

Mar 1970

71,451,000146,000

Apr 1970

71,348,000-103,000

May 1970

71,124,000-224,000

Jun 1970

71,029,000-95,000

Jul 1970

71,053,00024,000

Aug 1970

70,937,000-116,000

Sep 1970

70,944,0007,000

Oct 1970

70,521,000-423,000

Nov 1970

70,409,000-112,000

Dec 1970

70,792,000383,000

Jan 1971

70,865,00073,000

Feb 1971

70,807,000-58,000

Mar 1971

70,860,00053,000

Apr 1971

71,036,000176,000

May 1971

71,247,000211,000

Jun 1971

71,254,0007,000

Jul 1971

71,315,00061,000

Aug 1971

71,373,00058,000

Sep 1971

71,614,000241,000

Oct 1971

71,642,00028,000

Nov 1971

71,847,000205,000

Dec 1971

72,109,000262,000

Jan 1972

72,441,000332,000

Feb 1972

72,648,000207,000

Mar 1972

72,944,000296,000

Apr 1972

73,162,000218,000

May 1972

73,469,000307,000

Jun 1972

73,758,000289,000

Jul 1972

73,709,000-49,000

Aug 1972

74,141,000432,000

Sep 1972

74,264,000123,000

Oct 1972

74,674,000410,000

Nov 1972

74,973,000299,000

Dec 1972

75,268,000295,000

Jan 1973

75,617,000349,000

Feb 1973

76,014,000397,000

Mar 1973

76,284,000270,000

Apr 1973

76,455,000171,000

May 1973

76,648,000193,000

Jun 1973

76,887,000239,000

Jul 1973

76,913,00026,000

Aug 1973

77,168,000255,000

Sep 1973

77,276,000108,000

Oct 1973

77,607,000331,000

Nov 1973

77,920,000313,000

Dec 1973

78,031,000111,000

Jan 1974

78,100,00069,000

Feb 1974

78,254,000154,000

Mar 1974

78,296,00042,000

Apr 1974

78,382,00086,000

May 1974

78,549,000167,000

Jun 1974

78,604,00055,000

Jul 1974

78,636,00032,000

Aug 1974

78,619,000-17,000

Sep 1974

78,610,000-9,000

Oct 1974

78,630,00020,000

Nov 1974

78,265,000-365,000

Dec 1974

77,652,000-613,000

Jan 1975

77,293,000-359,000

Feb 1975

76,918,000-375,000

Mar 1975

76,648,000-270,000

Apr 1975

76,460,000-188,000

May 1975

76,624,000164,000

Jun 1975

76,521,000-103,000

Jul 1975

76,770,000249,000

Aug 1975

77,153,000383,000

Sep 1975

77,228,00075,000

Oct 1975

77,540,000312,000

Nov 1975

77,685,000145,000

Dec 1975

78,017,000332,000

Jan 1976

78,503,000486,000

Feb 1976

78,816,000313,000

Mar 1976

79,048,000232,000

Apr 1976

79,292,000244,000

May 1976

79,312,00020,000

Jun 1976

79,376,00064,000

Jul 1976

79,547,000171,000

Aug 1976

79,704,000157,000

Sep 1976

79,892,000188,000

Oct 1976

79,911,00019,000

Nov 1976

80,240,000329,000

Dec 1976

80,448,000208,000

Jan 1977

80,690,000242,000

Feb 1977

80,988,000298,000

Mar 1977

81,391,000403,000

Apr 1977

81,728,000337,000

May 1977

82,088,000360,000

Jun 1977

82,488,000400,000

Jul 1977

82,834,000346,000

Aug 1977

83,075,000241,000

Sep 1977

83,532,000457,000

Oct 1977

83,800,000268,000

Nov 1977

84,173,000373,000

Dec 1977

84,410,000237,000

Jan 1978

84,594,000184,000

Feb 1978

84,948,000354,000

Mar 1978

85,460,000512,000

Apr 1978

86,162,000702,000

May 1978

86,509,000347,000

Jun 1978

86,950,000441,000

Jul 1978

87,204,000254,000

Aug 1978

87,483,000279,000

Sep 1978

87,621,000138,000

Oct 1978

87,956,000335,000

Nov 1978

88,391,000435,000

Dec 1978

88,671,000280,000

Jan 1979

88,808,000137,000

Feb 1979

89,055,000247,000

Mar 1979

89,479,000424,000

Apr 1979

89,417,000-62,000

May 1979

89,789,000372,000

Jun 1979

90,108,000319,000

Jul 1979

90,217,000109,000

Aug 1979

90,300,00083,000

Sep 1979

90,327,00027,000

Oct 1979

90,481,000154,000

Nov 1979

90,573,00092,000

Dec 1979

90,672,00099,000

Jan 1980

90,800,000128,000

Feb 1980

90,883,00083,000

Mar 1980

90,994,000111,000

Apr 1980

90,849,000-145,000

May 1980

90,420,000-429,000

Jun 1980

90,101,000-319,000

Jul 1980

89,840,000-261,000

Aug 1980

90,099,000259,000

Sep 1980

90,213,000114,000

Oct 1980

90,490,000277,000

Nov 1980

90,747,000257,000

Dec 1980

90,943,000196,000

Jan 1981

91,033,00090,000

Feb 1981

91,105,00072,000

Mar 1981

91,210,000105,000

Apr 1981

91,283,00073,000

May 1981

91,296,00013,000

Jun 1981

91,490,000194,000

Jul 1981

91,601,000111,000

Aug 1981

91,565,000-36,000

Sep 1981

91,477,000-88,000

Oct 1981

91,380,000-97,000

Nov 1981

91,171,000-209,000

Dec 1981

90,895,000-276,000

Jan 1982

90,565,000-330,000

Feb 1982

90,563,000-2,000

Mar 1982

90,434,000-129,000

Apr 1982

90,150,000-284,000

May 1982

90,107,000-43,000

Jun 1982

89,865,000-242,000

Jul 1982

89,521,000-344,000

Aug 1982

89,363,000-158,000

Sep 1982

89,183,000-180,000

Oct 1982

88,907,000-276,000

Nov 1982

88,786,000-121,000

Dec 1982

88,771,000-15,000

Jan 1983

88,990,000219,000

Feb 1983

88,917,000-73,000

Mar 1983

89,090,000173,000

Apr 1983

89,364,000274,000

May 1983

89,644,000280,000

Jun 1983

90,021,000377,000

Jul 1983

90,437,000416,000

Aug 1983

90,129,000-308,000

Sep 1983

91,247,0001,118,000

Oct 1983

91,520,000273,000

Nov 1983

91,875,000355,000

Dec 1983

92,230,000355,000

Jan 1984

92,673,000443,000

Feb 1984

93,157,000484,000

Mar 1984

93,429,000272,000

Apr 1984

93,792,000363,000

May 1984

94,098,000306,000

Jun 1984

94,479,000381,000

Jul 1984

94,789,000310,000

Aug 1984

95,032,000243,000

Sep 1984

95,344,000312,000

Oct 1984

95,629,000285,000

Nov 1984

95,982,000353,000

Dec 1984

96,107,000125,000

Jan 1985

96,372,000265,000

Feb 1985

96,503,000131,000

Mar 1985

96,842,000339,000

Apr 1985

97,038,000196,000

May 1985

97,312,000274,000

Jun 1985

97,459,000147,000

Jul 1985

97,648,000189,000

Aug 1985

97,840,000192,000

Sep 1985

98,045,000205,000

Oct 1985

98,233,000188,000

Nov 1985

98,443,000210,000

Dec 1985

98,609,000166,000

Jan 1986

98,732,000123,000

Feb 1986

98,847,000115,000

Mar 1986

98,934,00087,000

Apr 1986

99,121,000187,000

May 1986

99,248,000127,000

Jun 1986

99,155,000-93,000

Jul 1986

99,473,000318,000

Aug 1986

99,588,000115,000

Sep 1986

99,934,000346,000

Oct 1986

100,121,000187,000

Nov 1986

100,308,000187,000

Dec 1986

100,509,000201,000

Jan 1987

100,678,000169,000

Feb 1987

100,919,000241,000

Mar 1987

101,164,000245,000

Apr 1987

101,499,000335,000

May 1987

101,728,000229,000

Jun 1987

101,900,000172,000

Jul 1987

102,247,000347,000

Aug 1987

102,420,000173,000

Sep 1987

102,647,000227,000

Oct 1987

103,138,000491,000

Nov 1987

103,372,000234,000

Dec 1987

103,661,000289,000

Jan 1988

103,753,00092,000

Feb 1988

104,214,000461,000

Mar 1988

104,489,000275,000

Apr 1988

104,732,000243,000

May 1988

104,962,000230,000

Jun 1988

105,326,000364,000

Jul 1988

105,550,000224,000

Aug 1988

105,674,000124,000

Sep 1988

106,013,000339,000

Oct 1988

106,276,000263,000

Nov 1988

106,617,000341,000

Dec 1988

106,898,000281,000

Jan 1989

107,161,000263,000

Feb 1989

107,427,000266,000

Mar 1989

107,621,000194,000

Apr 1989

107,791,000170,000

May 1989

107,913,000122,000

Jun 1989

108,027,000114,000

Jul 1989

108,069,00042,000

Aug 1989

108,120,00051,000

Sep 1989

108,369,000249,000

Oct 1989

108,476,000107,000

Nov 1989

108,752,000276,000

Dec 1989

108,836,00084,000

Jan 1990

109,199,000363,000

Feb 1990

109,435,000236,000

Mar 1990

109,644,000209,000

Apr 1990

109,686,00042,000

May 1990

109,839,000153,000

Jun 1990

109,856,00017,000

Jul 1990

109,824,000-32,000

Aug 1990

109,616,000-208,000

Sep 1990

109,518,000-98,000

Oct 1990

109,367,000-151,000

Nov 1990

109,214,000-153,000

Dec 1990

109,166,000-48,000

Jan 1991

109,055,000-111,000

Feb 1991

108,734,000-321,000

Mar 1991

108,574,000-160,000

Apr 1991

108,364,000-210,000

May 1991

108,249,000-115,000

Jun 1991

108,334,00085,000

Jul 1991

108,292,000-42,000

Aug 1991

108,310,00018,000

Sep 1991

108,336,00026,000

Oct 1991

108,357,00021,000

Nov 1991

108,296,000-61,000

Dec 1991

108,328,00032,000

Jan 1992

108,369,00041,000

Feb 1992

108,311,000-58,000

Mar 1992

108,365,00054,000

Apr 1992

108,519,000154,000

May 1992

108,649,000130,000

Jun 1992

108,715,00066,000

Jul 1992

108,793,00078,000

Aug 1992

108,925,000132,000

Sep 1992

108,959,00034,000

Oct 1992

109,139,000180,000

Nov 1992

109,272,000133,000

Dec 1992

109,495,000223,000

Jan 1993

109,794,000299,000

Feb 1993

110,044,000250,000

Mar 1993

109,994,000-50,000

Apr 1993

110,296,000302,000

May 1993

110,568,000272,000

Jun 1993

110,749,000181,000

Jul 1993

111,055,000306,000

Aug 1993

111,206,000151,000

Sep 1993

111,448,000242,000

Oct 1993

111,733,000285,000

Nov 1993

111,984,000251,000

Dec 1993

112,314,000330,000

Jan 1994

112,595,000281,000

Feb 1994

112,781,000186,000

Mar 1994

113,242,000461,000

Apr 1994

113,586,000344,000

May 1994

113,921,000335,000

Jun 1994

114,238,000317,000

Jul 1994

114,610,000372,000

Aug 1994

114,896,000286,000

Sep 1994

115,247,000351,000

Oct 1994

115,458,000211,000

Nov 1994

115,869,000411,000

Dec 1994

116,165,000296,000

Jan 1995

116,501,000336,000

Feb 1995

116,697,000196,000

Mar 1995

116,907,000210,000

Apr 1995

117,069,000162,000

May 1995

117,049,000-20,000

Jun 1995

117,286,000237,000

Jul 1995

117,380,00094,000

Aug 1995

117,634,000254,000

Sep 1995

117,875,000241,000

Oct 1995

118,031,000156,000

Nov 1995

118,175,000144,000

Dec 1995

118,320,000145,000

Jan 1996

118,316,000-4,000

Feb 1996

118,739,000423,000

Mar 1996

118,993,000254,000

Apr 1996

119,158,000165,000

May 1996

119,486,000328,000

Jun 1996

119,769,000283,000

Jul 1996

120,015,000246,000

Aug 1996

120,199,000184,000

Sep 1996

120,410,000211,000

Oct 1996

120,665,000255,000

Nov 1996

120,961,000296,000

Dec 1996

121,143,000182,000

Jan 1997

121,363,000220,000

Feb 1997

121,675,000312,000

Mar 1997

121,990,000315,000

Apr 1997

122,286,000296,000

May 1997

122,546,000260,000

Jun 1997

122,814,000268,000

Jul 1997

123,111,000297,000

Aug 1997

123,093,000-18,000

Sep 1997

123,585,000492,000

Oct 1997

123,929,000344,000

Nov 1997

124,235,000306,000

Dec 1997

124,549,000314,000

Jan 1998

124,812,000263,000

Feb 1998

125,016,000204,000

Mar 1998

125,164,000148,000

Apr 1998

125,442,000278,000

May 1998

125,844,000402,000

Jun 1998

126,076,000232,000

Jul 1998

126,205,000129,000

Aug 1998

126,544,000339,000

Sep 1998

126,752,000208,000

Oct 1998

126,954,000202,000

Nov 1998

127,231,000277,000

Dec 1998

127,596,000365,000

Jan 1999

127,702,000106,000

Feb 1999

128,120,000418,000

Mar 1999

128,227,000107,000

Apr 1999

128,597,000370,000

May 1999

128,808,000211,000

Jun 1999

129,089,000281,000

Jul 1999

129,414,000325,000

Aug 1999

129,569,000155,000

Sep 1999

129,772,000203,000

Oct 1999

130,177,000405,000

Nov 1999

130,466,000289,000

Dec 1999

130,772,000306,000

Jan 2000

131,005,000233,000

Feb 2000

131,124,000119,000

Mar 2000

131,596,000472,000

Apr 2000

131,888,000292,000

May 2000

132,105,000217,000

Jun 2000

132,061,000-44,000

Jul 2000

132,236,000175,000

Aug 2000

132,230,000-6,000

Sep 2000

132,353,000123,000

Oct 2000

132,351,000-2,000

Nov 2000

132,556,000205,000

Dec 2000

132,709,000153,000

Jan 2001

132,698,000-11,000

Feb 2001

132,789,00091,000

Mar 2001

132,747,000-42,000

Apr 2001

132,463,000-284,000

May 2001

132,410,000-53,000

Jun 2001

132,299,000-111,000

Jul 2001

132,177,000-122,000

Aug 2001

132,028,000-149,000

Sep 2001

131,771,000-257,000

Oct 2001

131,454,000-317,000

Nov 2001

131,142,000-312,000

Dec 2001

130,982,000-160,000

Jan 2002

130,852,000-130,000

Feb 2002

130,736,000-116,000

Mar 2002

130,717,000-19,000

Apr 2002

130,623,000-94,000

May 2002

130,634,00011,000

Jun 2002

130,684,00050,000

Jul 2002

130,590,000-94,000

Aug 2002

130,587,000-3,000

Sep 2002

130,501,000-86,000

Oct 2002

130,628,000127,000

Nov 2002

130,615,000-13,000

Dec 2002

130,472,000-143,000

Jan 2003

130,580,000108,000

Feb 2003

130,444,000-136,000

Mar 2003

130,232,000-212,000

Apr 2003

130,177,000-55,000

May 2003

130,196,00019,000

Jun 2003

130,194,000-2,000

Jul 2003

130,191,000-3,000

Aug 2003

130,149,000-42,000

Sep 2003

130,254,000105,000

Oct 2003

130,454,000200,000

Nov 2003

130,474,00020,000

Dec 2003

130,588,000114,000

Jan 2004

130,769,000181,000

Feb 2004

130,825,00056,000

Mar 2004

131,142,000317,000

Apr 2004

131,411,000269,000

May 2004

131,694,000283,000

Jun 2004

131,793,00099,000

Jul 2004

131,848,00055,000

Aug 2004

131,937,00089,000

Sep 2004

132,093,000156,000

Oct 2004

132,447,000354,000

Nov 2004

132,503,00056,000

Dec 2004

132,624,000121,000

Jan 2005

132,774,000150,000

Feb 2005

133,032,000258,000

Mar 2005

133,156,000124,000

Apr 2005

133,518,000362,000

May 2005

133,690,000172,000

Jun 2005

133,942,000252,000

Jul 2005

134,296,000354,000

Aug 2005

134,498,000202,000

Sep 2005

134,566,00068,000

Oct 2005

134,655,00089,000

Nov 2005

134,993,000338,000

Dec 2005

135,149,000156,000

Jan 2006

135,429,000280,000

Feb 2006

135,737,000308,000

Mar 2006

136,047,000310,000

Apr 2006

136,205,000158,000

May 2006

136,244,00039,000

Jun 2006

136,325,00081,000

Jul 2006

136,520,000195,000

Aug 2006

136,694,000174,000

Sep 2006

136,843,000149,000

Oct 2006

136,852,0009,000

Nov 2006

137,063,000211,000

Dec 2006

137,249,000186,000

Jan 2007

137,477,000228,000

Feb 2007

137,558,00081,000

Mar 2007

137,793,000235,000

Apr 2007

137,842,00049,000

May 2007

137,993,000151,000

Jun 2007

138,069,00076,000

Jul 2007

138,038,000-31,000

Aug 2007

138,015,000-23,000

Sep 2007

138,095,00080,000

Oct 2007

138,174,00079,000

Nov 2007

138,284,000110,000

Dec 2007

138,392,000108,000

Jan 2008

138,403,00011,000

Feb 2008

138,324,000-79,000

Mar 2008

138,275,000-49,000

Apr 2008

138,035,000-240,000

May 2008

137,858,000-177,000

Jun 2008

137,687,000-171,000

Jul 2008

137,491,000-196,000

Aug 2008

137,213,000-278,000

Sep 2008

136,753,000-460,000

Oct 2008

136,272,000-481,000

Nov 2008

135,545,000-727,000

Dec 2008

134,839,000-706,000

Jan 2009

134,055,000-784,000

Feb 2009

133,312,000-743,000

Mar 2009

132,512,000-800,000

Apr 2009

131,817,000-695,000

May 2009

131,475,000-342,000

Jun 2009

131,008,000-467,000

Jul 2009

130,668,000-340,000

Aug 2009

130,485,000-183,000

Sep 2009

130,244,000-241,000

Oct 2009

130,045,000-199,000

Nov 2009

130,057,00012,000

Dec 2009

129,788,000-269,000

Jan 2010

129,790,0002,000

Feb 2010

129,698,000-92,000

Mar 2010

129,879,000181,000

Apr 2010

130,110,000231,000

May 2010

130,650,000540,000

Jun 2010

130,511,000-139,000

Jul 2010

130,427,000-84,000

Aug 2010

130,422,000-5,000

Sep 2010

130,357,000-65,000

Oct 2010

130,625,000268,000

Nov 2010

130,750,000125,000

Dec 2010

130,822,00072,000

Jan 2011

130,841,00019,000

Feb 2011

131,053,000212,000

Mar 2011

131,288,000235,000

Apr 2011

131,602,000314,000

May 2011

131,703,000101,000

Jun 2011

131,939,000236,000

Jul 2011

131,999,00060,000

Aug 2011

132,125,000126,000

Sep 2011

132,358,000233,000

Oct 2011

132,562,000204,000

Nov 2011

132,694,000132,000

Dec 2011

132,896,000202,000

Jan 2012

133,250,000354,000

Feb 2012

133,512,000262,000

Mar 2012

133,752,000240,000

Apr 2012

133,834,00082,000

May 2012

133,934,000100,000

Jun 2012

134,007,00073,000

Jul 2012

134,159,000152,000

Aug 2012

134,331,000172,000

Sep 2012

134,518,000187,000

Oct 2012

134,677,000159,000

Nov 2012

134,833,000156,000

Dec 2012

135,072,000239,000

Jan 2013

135,263,000191,000

Feb 2013

135,541,000278,000

Mar 2013

135,680,000139,000

Apr 2013

135,871,000191,000

May 2013

136,093,000222,000

Jun 2013

136,274,000181,000

Jul 2013

136,386,000112,000

Aug 2013

136,628,000242,000

Sep 2013

136,815,000187,000

Oct 2013

137,040,000225,000

Nov 2013

137,304,000264,000

Dec 2013

137,373,00069,000

Jan 2014

137,548,000175,000

Feb 2014

137,714,000166,000

Mar 2014

137,968,000254,000

Apr 2014

138,293,000325,000

May 2014

138,511,000218,000

Jun 2014

138,837,000326,000

Jul 2014

139,069,000232,000

Aug 2014

139,257,000188,000

Sep 2014

139,566,000309,000

Oct 2014

139,818,000252,000

Nov 2014

140,109,000291,000

Dec 2014

140,377,000268,000

Jan 2015

140,568,000191,000

Feb 2015

140,839,000271,000

Mar 2015

140,910,00071,000

Apr 2015

141,194,000284,000

May 2015

141,525,000331,000

Jun 2015

141,699,000174,000

Jul 2015

142,001,000302,000

Aug 2015

142,126,000125,000

Sep 2015

142,281,000155,000

Oct 2015

142,587,000306,000

Nov 2015

142,824,000237,000

Dec 2015

143,097,000273,000

Jan 2016

143,205,000108,000

Feb 2016

143,417,000212,000

Mar 2016

143,654,000237,000

Apr 2016

143,851,000197,000

May 2016

143,892,00041,000

Jun 2016

144,150,000258,000

Jul 2016

144,521,000371,000

Aug 2016

144,664,000143,000

Sep 2016

144,953,000289,000

Oct 2016

145,071,000118,000

Nov 2016

145,201,000130,000

Dec 2016

145,415,000214,000

Jan 2017

145,612,000197,000

Feb 2017

145,795,000183,000

Mar 2017

145,934,000139,000

Apr 2017

146,154,000220,000

May 2017

146,295,000141,000

Jun 2017

146,506,000211,000

Jul 2017

146,734,000228,000

Aug 2017

146,924,000190,000

Sep 2017

146,966,00042,000

Oct 2017

147,215,000249,000

Nov 2017

147,411,000196,000

Dec 2017

147,590,000179,000

Jan 2018

147,671,00081,000

Feb 2018

148,049,000378,000

Mar 2018

148,244,000195,000

Apr 2018

148,397,000153,000

May 2018

148,667,000270,000

Jun 2018

148,881,000214,000

Jul 2018

149,030,000149,000

Aug 2018

149,259,000229,000

Sep 2018

149,364,000105,000

Oct 2018

149,576,000212,000

Nov 2018

149,668,00092,000

Dec 2018

149,908,000240,000

Jan 2019

150,145,000237,000

Feb 2019

150,095,000-50,000

Mar 2019

150,263,000168,000

Apr 2019

150,482,000219,000

May 2019

150,545,00063,000

Jun 2019

150,720,000175,000

Jul 2019

150,913,000193,000

Aug 2019

151,108,000195,000

Sep 2019

151,329,000221,000

Oct 2019

151,524,000195,000

Nov 2019

151,758,000234,000

Dec 2019

151,919,000161,000

Jan 2020

152,234,000315,000

Feb 2020

152,523,000289,000

Mar 2020

150,840,000-1,683,000

Apr 2020

130,161,000-20,679,000

May 2020

132,994,0002,833,000

Jun 2020

137,840,0004,846,000

Jul 2020

139,566,0001,726,000

Aug 2020

141,149,0001,583,000

Sep 2020

141,865,000716,000

Oct 2020

142,545,000680,000

Nov 2020

142,809,000264,000

Dec 2020

142,582,000-227,000
Unemployment rates for selected groups, February, April, and December 2020
Race and Hispanic or Latino ethnicityFebruary 2020April 2020December 2020

Total, 16 years and older

3.514.86.7

White

3.014.16.0

Black or African American

6.016.79.9

Asian

2.414.55.9

Hispanic or Latino

4.418.99.3
Percent change in consumer prices for selected items in April 2020, seasonally adjusted
Expenditure categoryPercent change

Car and truck rental (1998)

-16.6

Airline fares (1989)

-15.2

Hotel and motel lodging (1967)

-8.1

Women’s footwear (1978)

-5.2

Full service meals and snacks (1998)

-0.3

Carbonated drinks (1978)

4.5

Household paper products (1997)

4.5

Cookies (1978)

5.1

Chicken (2004)

5.8

Update on the Misclassification that Affected the Unemployment Rate

How hard can it be to figure out whether a person is employed or unemployed? Turns out, it can be hard. When BLS put out the employment and unemployment numbers for March, April, and May 2020, we also provided information about misclassification of some people. I want to spend some time to explain this issue, how it affected the data, and how we are addressing it.

In the monthly Current Population Survey of U.S. households, people age 16 and older are placed into one of three categories:

  • Employed — they worked at least one hour “for pay or profit” during the past week.
  • Unemployed — they did not work but actively looked for work during the past 4 weeks OR they were on temporary layoff and expect to return to work.
  • Not in the labor force — everyone else (including students, retirees, those who have given up their job search, and others).

Again, how hard can this be? It starts to get tricky when we talk to people who say they have a steady job but did not work any hours during the past week. In normal times, this might include people on vacation, home sick, or on jury duty. And we would continue to count them as employed. But during the COVID-19 pandemic, the collapse of labor markets created challenges the likes of which BLS has never encountered. People who reported zero hours of work offered such explanations as “I work at a sports arena and everything is postponed” or “the restaurant I work at is closed.” These people should be counted as unemployed on temporary layoff. As it turns out, a large number of people—we estimate about 4.9 million in May—were misclassified.

With the onset of the COVID-19 pandemic, the unemployment rate—at a 50-year low of 3.5 percent in February—rose sharply to 4.4 percent in March and to 14.7 percent in April, before easing to 13.3 percent in May. Despite the stark difference from February, we believe the unemployment rate likely was higher than reported in March, April, and May. As stated in our Employment Situation news releases for each of those months, some people in the Current Population Survey (also known as the CPS or household survey) were classified as employed but probably should have been classified as unemployed.

How did the misclassification happen?

We uncovered the misclassification because we saw a sharp rise in the number of people who were employed but were absent from their jobs for the entire reference week for “other reasons.” The misclassification hinges on how survey interviewers record answers to a question on why people who had a job were absent from work the previous week.

According to special pandemic-related interviewer instructions for this question, answers from people who said they were absent because of pandemic-related business closures should have been recorded as “on layoff (temporary or indefinite).” Instead, many of these answers were recorded as “other reasons.” Recording these answers as “on layoff (temporary or indefinite)” ensures that people are asked the follow-up questions needed to classify them as unemployed. It does not necessarily mean they would be classified as unemployed on temporary layoff, but I’ll get into that in a moment.

When interviewers record a response of “other reasons” to this question, they also add a few words describing that other reason. BLS reviewed these descriptions to better understand the large increase in the number of people absent from work for “other reasons.” Our analysis suggests this group of people included many who were on layoff because of the pandemic. They would have been classified as unemployed on temporary layoff had their answers been recorded correctly.

What are BLS and the Census Bureau doing to address the misclassification?

BLS and our partners at the U.S. Census Bureau take misclassification very seriously. We’re taking more steps to fix this problem. (The Census Bureau is responsible for collecting the household survey data, and BLS is responsible for analyzing and publishing the labor market data from the survey.) Both agencies are continuing to investigate why the misclassification occurred.

Before the March data collection, we anticipated some issues with certain questions in the survey because of the unprecedented nature of this national crisis. As a result, interviewers received special instructions on how to answer the temporarily absent question if a person said they had a job but did not work because of the pandemic. Nevertheless, we determined that not all of the responses to this question in March were coded according to the special instructions. Therefore, before the April data collection, all interviewers received an email that included instructions with more detailed examples, along with a reference table to help them code responses to this question. However, the misclassification was still evident in the April data. Before the May data collection, every field supervisor had a conference call with the interviewers they manage. In these conference calls, the supervisors reviewed the detailed instructions, provided examples to clarify the instructions, and answered interviewers’ questions.

Although we noticed some improvement for May, the misclassification persisted. Therefore, we have taken more steps to correct the problem. Before the June collection, the Census Bureau provided more training to review the guidance to the interviewers. The interviewers also received extra training aids. The electronic survey questionnaire also now has new special instructions that will be more accessible during survey interviews.

Why doesn’t BLS adjust the unemployment rate to account for the misclassification?

As I explained above, we know some workers classified as absent from work for “other reasons” are misclassified. People have asked why we just don’t reclassify these people from employed to unemployed. The answer is there is no easy correction we could have made. Changing a person’s labor force classification would involve more than changing the response to the question about why people were absent from their jobs.

Although we believe many responses to the question on why people were absent from their jobs appear to have been incorrectly recorded, we do not have enough information to reclassify each person’s labor force status. To begin with, we don’t know the exact information provided by the person responding to the survey. We know the brief descriptions included in the “other reasons” category often appear to go against the guidance provided to the survey interviewers. But we don’t have all of the information the respondent might have provided during the interview.

Also, we don’t know the answers to the questions respondents would have been asked if their answers to the question on the reason not at work had been coded differently. This is because people whose answers were recorded as absent from work for “other reasons” were not asked the follow-up questions needed to determine whether they should be classified as unemployed. Specifically, we don’t know whether they expected to be recalled to work and whether they could return to work if recalled. Therefore, shifting people’s answers from “other reasons” to “on layoff (temporary or indefinite)” would not have been enough to change their classification from employed to unemployed. We would have had to assume how they would have responded to the follow-up questions. Had we changed answers based on wrong assumptions, we would have introduced more error.

In addition, our usual practice is to accept data from the household survey as recorded. In the 80-year history of the household survey, we do not know of any actions taken on an ad hoc basis to change respondents’ answers to the labor force questions. Any ad hoc adjustment we could have made would have relied on assumptions instead of data. If BLS were to make ad hoc changes, it could also appear we were manipulating the data. That’s something we’ll never do.

How much did the misclassification affect the unemployment rate?

We don’t know the exact extent of this misclassification. To figure out what the unemployment rate might have been if there were no misclassification, we have to make some assumptions. These assumptions involve deciding (1) how many people in the “other reasons” category actually were misclassified, (2) how many people who were misclassified expected to be recalled, and (3) how many people who were misclassified were available to return to work.

In the material that accompanied our Employment Situation news releases for March, April, and May, we provided an estimate of the potential size of the misclassification and its impact on the unemployment rate. Here we assumed all of the increase in the number of employed people who were not at work for “other reasons,” when compared with the average for recent years, was due solely to misclassification. We also assumed all of these people expected to be recalled and were available to return to work.

For example, there were 5.4 million workers with a job but not at work who were included in the “other reasons” category in May 2020. That was about 4.9 million higher than the average for May 2016–19. If we assume this 4.9 million increase was entirely due to misclassification and all of these misclassified workers expected to be recalled and were available for work, the unemployment rate for May would have been 16.4 percent. (For more information about this, see items 12 and 13 in our note for May. We made similar calculations for March and April.)

These broad assumptions represent the upper bound of our estimate of misclassification. These assumptions result in the largest number of people being classified as unemployed and the largest increase in the unemployment rate. However, these assumptions probably overstate the size of the misclassification. It is unlikely that everyone who was misclassified expected to be recalled and was available to return to work. It is also unlikely that all of the increase in the number of employed people not at work for “other reasons” was due to misclassification. People may be correctly classified in the “other reasons” category. For example, someone who owns a business (and does not have another job) is classified as employed in the household survey. Business owners who are absent from work due to labor market downturns (or in this case, pandemic-related business closures) should be classified as employed but absent from work for “other reasons.”

Regardless of the assumptions we might make about misclassification, the trend in the unemployment rate over the period in question is the same; the rate increased in March and April and eased in May. BLS will continue to investigate the issue, attempting both to ensure that data are correctly recorded in future months and to provide more information about the effect of misclassification on the unemployment rate.