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Topic 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.

What Have You Been Looking for on the BLS Website?

In 2021, the BLS public website welcomed nearly 29 million users, who viewed just over 158 million pages. Wow, that’s a lot of data! It shows the extensive and growing interest in information about our economy. Let’s take a quick look back over the past year. What are the topics of interest? We see clear trends and a few surprises.

From its humble beginnings more than a quarter century ago, www.bls.gov has become the primary way we make the latest BLS data and analysis available to the public.

BLS website homepage, September 1995
First edition of the BLS website, 1995

Today, thousands of users get their first glimpse of the latest economic data through the website or through email alerts and tweets that link to the website. National economic news on employment, inflation, productivity, and other topics is first available on the website, with about 150 national releases each year. Not to be outdone, BLS regional office staff around the country last year posted nearly 1,000 regional and local news releases on the website.

And you came to check out those data—all 29 million of you.

Here’s a look at the five subject homepages that saw the greatest increase in page views from 2020 to 2021. You’ll note that all are timely topics.

  • The Business Response Survey to the Coronavirus Pandemic was a special data collection effort. Information from this survey was first available late in 2020, so the 166-percent increase in page views in 2021 is not surprising, especially given the great interest in all COVID-19 information. Results from a second round of this survey, with updated questions, will be available February 9, 2022.
  • Information from the Consumer Price Index also had more than a 100-percent increase in page views from 2020 to 2021, 106 percent increase to be exact. This is not a surprise, given the significant rise in prices recently.
  • Interest in inflation throughout the supply chain also led to a 60-percent increase in page views for Producer Price Indexes data.
  • BLS has been collecting data on Work Stoppages (strikes and lockouts) for many years, but interest in these data grew in 2021, perhaps because of several high-profile stoppages. There was a 25-percent increase in page views for these data.
  • Rounding out the top five was an 18-percent increase in page views for Job Openings and Labor Turnover Survey data. With record numbers of job openings and heightened interest in churn in the labor force, these data have garnered much attention recently. We also began publishing a news release on state data in 2021 to meet the growing need for geographic information on job openings and labor turnover.

Turning to analytical data, some of the most viewed pages were those focusing on fast growing industries, inflation at both the consumer and producer level, and the impact of COVID-19 on many aspects of the economy, such as unemployment and food prices. But viewers were also attracted to some unique topics:

  • The most read Commissioner’s Corner blog was about the 17-year cycle of cicadas, with a look at economic trends during past cicada invasions.
A cicada
A group of friends and family watching a football game on TV

We welcome our 29 million website visitors and encourage you to check back regularly. Your interests drive our commitment to provide timely research on relevant topics. There’s new content every business day, so you never know what new research may be right around the corner in 2022. It will all be at www.bls.gov. See you there!

BLS website homepage in 2022
BLS website homepage in 2022

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

Making Sense of Job Openings and Other Labor Market Measures

The current “supply” of labor gets a lot of attention. That concept refers to the number of people working or looking for work. Our monthly Employment Situation report is where policymakers and the general public learn how that supply has changed. BLS also examines the current “demand” for labor with monthly information on filled jobs and job openings. Readers find those estimate in the BLS Job Openings and Labor Turnover Survey (JOLTS). JOLTS defines job openings as all positions that are open, but not filled, on the last business day of the month. A job is “open” only if it meets all of these conditions:

  • A specific position exists and there is work available for that position.
  • The job could start within 30 days.
  • There is active recruiting for workers from outside the establishment.

There were 9.2 million job openings in May 2021, the same record-high level first reached in April. The May job opening rate also was the same as April’s record high; 6.0 percent of all currently available positions were unfilled. This rate is the number of job openings divided by the sum of current employment plus job openings. You can think of it as a measure of capacity or the rate of current unmet demand for labor.

Job openings rate, total nonfarm, December 2000 to May 2021

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

This spike in openings was sudden by historical standards. It came just one year after an equally sudden drop, which bottomed out in April 2020. In contrast, openings fell more gradually during the 2007–09 recession, then grew even more gradually during the subsequent recovery. The labor market movements during the COVID-19 pandemic have been far more abrupt than those in earlier business cycles.

An abundance of job openings usually signals a “tight” labor market; the demand for labor exceeds the supply at the offered wage. For workers, this may mean it is relatively easy to find a desirable job, assuming they possess the skills employers are seeking. In contrast, employers must compete to hire well-qualified workers.

High unemployment usually signals a “loose” labor market, in which many applicants compete for a limited number of openings; the supply of labor exceeds the demand. Unemployment—the number of workers who lack but seek jobs—stood at 9.5 million in June 2021. That was, down from its pandemic peak of 23 million in April 2020 but still well above its level of less than 6 million before the pandemic. Millions more have left the labor force during the pandemic, and many of them have not returned. These people are not counted as unemployed because they are not actively looking for work. However, we know that 6.4 million of those not in the labor force indicate they want a job now, and 1.6 million say they are not currently searching because of pandemic-related reasons. Some of these people might be willing to consider offers and might add more “looseness” to the labor market.

Comparing the number of job openings to the number of unemployed people provides one measure of the current job market. In May 2021, there was just one unemployed person per job opening—a ratio usually associated with a tight labor market.

Number of unemployed per job opening, December 2000 to May 2021

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

So, with openings at an all-time high, and unemployment still elevated, is the labor market tight or loose? The answer is complicated. It also can feel different depending on each worker’s and employer’s circumstances. The answer also differs when you look beyond the national data to uncover differing stories by industry or geography.

As the COVID-19 pandemic subsides and many restaurants and other businesses return to normal operations, some employers are finding it hard to hire enough workers quickly. Some economists are unsure whether recent, temporary increases in the availability and generosity of unemployment insurance have influenced some unemployed workers’ interest in taking jobs. At the same time, the lingering effects of the pandemic probably kept some potential workers from entering or reentering the labor force, especially those with school-aged children whose schools were still closed, and those lacking childcare options. These factors could also affect employers’ ability to hire.

We should also remember that not all job applicants come from the ranks of the unemployed. Many are changing jobs or entering (or reentering) the labor force. The recent abundance of job openings may be increasing workers’ likelihood to change jobs. Just as openings reached a new high in April 2021, so did quits, at 4.0 million. Unlike openings, however, quits edged down a bit in May.

Job openings, hires, and quit rates, total nonfarm, December 2000 to May 2021

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

Another factor could be mismatches between the open jobs and the jobseekers. In June 2021, about 15 percent of unemployed people were seeking part-time work. We don’t know how many of the openings were part-time. Since February of this year, the share of unemployed workers who were unemployed 27 weeks or longer has remained above 40 percent, a level last seen in 2012 and roughly twice the 2019 level. Historically, those unemployed longer are slower to connect with new jobs and more likely to stop looking. It is also possible that some workers’ job preferences changed, at least temporarily, as the pandemic changed the perceived risks and other characteristics of many jobs.

Finally, with many people on the sidelines of the labor market, and job openings at record high levels, employers may look to increase wages to entice potential employees back into the market. The BLS monthly measure of wage trends, average hourly earnings, has been heavily influenced by large employment shifts since the pandemic began. When employment dropped sharply in the spring of 2020, average wages increased, mainly because lower-paid workers were more likely to be out of work. Now that many businesses are reopening, some evidence of wage increases can be seen by focusing on the leisure and hospitality industry. From February 2020, just before the pandemic began, to June 2021, average hourly earnings for this industry rose 3.1 percent, after adjusting for inflation. Data from the Employment Cost Index, which are not influenced by employment shifts, show wages and salaries in the leisure and hospitality industry increasing 1.6 percent, after adjusting for inflation, for the year ending March 2021.

Percent change since February 2020 in real (inflation-adjusted) average hourly earnings

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

While some employers might find it hard to hire workers quickly, there is a lot of hiring going on. Consider the leisure and hospitality industry, which includes restaurants. In May, a whopping 9.0 percent of positions were open. But the hiring rate was even higher—9.3 percent, far above levels before the pandemic.

Job openings and hires rates, leisure and hospitality, December 2000 to May 2021

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

The labor market cannot be characterized with a single number. Over time, people change jobs, look for jobs, or leave the labor market entirely. These dynamics can be complicated, as they certainly were during the COVID-19 pandemic. This discussion covers just some of the many measures BLS reports to illuminate labor market conditions. For more analysis of JOLTS data, check out recent articles in the Monthly Labor Review and Beyond the Numbers.

Job openings rate, total nonfarm, December 2000 to May 2021
MonthRate

Dec 2000

3.7%

Jan 2001

3.8

Feb 2001

3.7

Mar 2001

3.5

Apr 2001

3.4

May 2001

3.2

Jun 2001

3.2

Jul 2001

3.3

Aug 2001

3.0

Sep 2001

3.0

Oct 2001

2.7

Nov 2001

2.8

Dec 2001

2.7

Jan 2002

2.7

Feb 2002

2.6

Mar 2002

2.7

Apr 2002

2.6

May 2002

2.6

Jun 2002

2.5

Jul 2002

2.5

Aug 2002

2.6

Sep 2002

2.5

Oct 2002

2.6

Nov 2002

2.6

Dec 2002

2.4

Jan 2003

2.6

Feb 2003

2.4

Mar 2003

2.3

Apr 2003

2.3

May 2003

2.5

Jun 2003

2.5

Jul 2003

2.2

Aug 2003

2.4

Sep 2003

2.3

Oct 2003

2.5

Nov 2003

2.5

Dec 2003

2.5

Jan 2004

2.6

Feb 2004

2.6

Mar 2004

2.6

Apr 2004

2.6

May 2004

2.7

Jun 2004

2.5

Jul 2004

2.8

Aug 2004

2.6

Sep 2004

2.8

Oct 2004

2.9

Nov 2004

2.6

Dec 2004

3.0

Jan 2005

2.8

Feb 2005

2.9

Mar 2005

2.9

Apr 2005

3.0

May 2005

2.8

Jun 2005

2.9

Jul 2005

3.1

Aug 2005

3.0

Sep 2005

3.1

Oct 2005

3.0

Nov 2005

3.1

Dec 2005

3.1

Jan 2006

3.1

Feb 2006

3.1

Mar 2006

3.4

Apr 2006

3.4

May 2006

3.2

Jun 2006

3.3

Jul 2006

3.1

Aug 2006

3.3

Sep 2006

3.3

Oct 2006

3.2

Nov 2006

3.3

Dec 2006

3.3

Jan 2007

3.3

Feb 2007

3.3

Mar 2007

3.5

Apr 2007

3.3

May 2007

3.3

Jun 2007

3.4

Jul 2007

3.2

Aug 2007

3.2

Sep 2007

3.3

Oct 2007

3.2

Nov 2007

3.3

Dec 2007

3.2

Jan 2008

3.2

Feb 2008

3.0

Mar 2008

3.0

Apr 2008

2.8

May 2008

3.0

Jun 2008

2.7

Jul 2008

2.7

Aug 2008

2.6

Sep 2008

2.3

Oct 2008

2.4

Nov 2008

2.3

Dec 2008

2.3

Jan 2009

2.0

Feb 2009

2.1

Mar 2009

1.9

Apr 2009

1.7

May 2009

1.9

Jun 2009

1.9

Jul 2009

1.7

Aug 2009

1.8

Sep 2009

1.9

Oct 2009

1.8

Nov 2009

1.9

Dec 2009

1.9

Jan 2010

2.1

Feb 2010

2.0

Mar 2010

2.0

Apr 2010

2.4

May 2010

2.2

Jun 2010

2.1

Jul 2010

2.3

Aug 2010

2.2

Sep 2010

2.2

Oct 2010

2.4

Nov 2010

2.4

Dec 2010

2.3

Jan 2011

2.3

Feb 2011

2.4

Mar 2011

2.4

Apr 2011

2.4

May 2011

2.4

Jun 2011

2.6

Jul 2011

2.7

Aug 2011

2.5

Sep 2011

2.8

Oct 2011

2.7

Nov 2011

2.6

Dec 2011

2.8

Jan 2012

2.8

Feb 2012

2.6

Mar 2012

2.9

Apr 2012

2.8

May 2012

2.8

Jun 2012

2.8

Jul 2012

2.7

Aug 2012

2.8

Sep 2012

2.8

Oct 2012

2.7

Nov 2012

2.8

Dec 2012

2.9

Jan 2013

2.8

Feb 2013

2.9

Mar 2013

2.9

Apr 2013

2.9

May 2013

3.0

Jun 2013

3.0

Jul 2013

2.8

Aug 2013

2.9

Sep 2013

2.9

Oct 2013

3.0

Nov 2013

2.9

Dec 2013

2.9

Jan 2014

2.9

Feb 2014

3.1

Mar 2014

3.1

Apr 2014

3.2

May 2014

3.3

Jun 2014

3.5

Jul 2014

3.4

Aug 2014

3.7

Sep 2014

3.4

Oct 2014

3.5

Nov 2014

3.3

Dec 2014

3.5

Jan 2015

3.7

Feb 2015

3.7

Mar 2015

3.6

Apr 2015

3.8

May 2015

3.8

Jun 2015

3.6

Jul 2015

4.1

Aug 2015

3.7

Sep 2015

3.7

Oct 2015

3.9

Nov 2015

3.8

Dec 2015

3.9

Jan 2016

4.0

Feb 2016

3.9

Mar 2016

4.1

Apr 2016

3.9

May 2016

3.9

Jun 2016

3.8

Jul 2016

4.0

Aug 2016

3.8

Sep 2016

3.9

Oct 2016

3.7

Nov 2016

4.0

Dec 2016

3.9

Jan 2017

3.7

Feb 2017

3.9

Mar 2017

3.8

Apr 2017

4.0

May 2017

3.8

Jun 2017

4.1

Jul 2017

4.1

Aug 2017

4.1

Sep 2017

4.1

Oct 2017

4.2

Nov 2017

4.1

Dec 2017

4.1

Jan 2018

4.3

Feb 2018

4.3

Mar 2018

4.4

Apr 2018

4.4

May 2018

4.5

Jun 2018

4.7

Jul 2018

4.6

Aug 2018

4.6

Sep 2018

4.7

Oct 2018

4.7

Nov 2018

4.8

Dec 2018

4.7

Jan 2019

4.7

Feb 2019

4.5

Mar 2019

4.7

Apr 2019

4.6

May 2019

4.6

Jun 2019

4.5

Jul 2019

4.5

Aug 2019

4.5

Sep 2019

4.5

Oct 2019

4.6

Nov 2019

4.4

Dec 2019

4.2

Jan 2020

4.5

Feb 2020

4.4

Mar 2020

3.7

Apr 2020

3.4

May 2020

3.9

Jun 2020

4.2

Jul 2020

4.6

Aug 2020

4.4

Sep 2020

4.5

Oct 2020

4.6

Nov 2020

4.5

Dec 2020

4.5

Jan 2021

4.7

Feb 2021

5.0

Mar 2021

5.4

Apr 2021

6.0

May 2021

6.0
Number of unemployed per job opening, December 2000 to May 2021
MonthRatio

Dec 2000

1.1

Jan 2001

1.2

Feb 2001

1.2

Mar 2001

1.3

Apr 2001

1.4

May 2001

1.4

Jun 2001

1.5

Jul 2001

1.5

Aug 2001

1.8

Sep 2001

1.8

Oct 2001

2.1

Nov 2001

2.1

Dec 2001

2.2

Jan 2002

2.2

Feb 2002

2.4

Mar 2002

2.3

Apr 2002

2.5

May 2002

2.4

Jun 2002

2.5

Jul 2002

2.5

Aug 2002

2.4

Sep 2002

2.5

Oct 2002

2.4

Nov 2002

2.4

Dec 2002

2.7

Jan 2003

2.5

Feb 2003

2.7

Mar 2003

2.8

Apr 2003

2.8

May 2003

2.7

Jun 2003

2.7

Jul 2003

3.0

Aug 2003

2.8

Sep 2003

2.9

Oct 2003

2.6

Nov 2003

2.6

Dec 2003

2.4

Jan 2004

2.4

Feb 2004

2.3

Mar 2004

2.4

Apr 2004

2.3

May 2004

2.2

Jun 2004

2.5

Jul 2004

2.1

Aug 2004

2.3

Sep 2004

2.1

Oct 2004

2.0

Nov 2004

2.3

Dec 2004

1.9

Jan 2005

2.0

Feb 2005

2.0

Mar 2005

1.9

Apr 2005

1.8

May 2005

2.0

Jun 2005

1.9

Jul 2005

1.7

Aug 2005

1.8

Sep 2005

1.7

Oct 2005

1.8

Nov 2005

1.8

Dec 2005

1.7

Jan 2006

1.6

Feb 2006

1.7

Mar 2006

1.5

Apr 2006

1.5

May 2006

1.6

Jun 2006

1.5

Jul 2006

1.6

Aug 2006

1.5

Sep 2006

1.4

Oct 2006

1.5

Nov 2006

1.5

Dec 2006

1.5

Jan 2007

1.5

Feb 2007

1.5

Mar 2007

1.4

Apr 2007

1.5

May 2007

1.5

Jun 2007

1.4

Jul 2007

1.6

Aug 2007

1.6

Sep 2007

1.5

Oct 2007

1.6

Nov 2007

1.6

Dec 2007

1.7

Jan 2008

1.7

Feb 2008

1.8

Mar 2008

1.9

Apr 2008

1.9

May 2008

2.0

Jun 2008

2.2

Jul 2008

2.4

Aug 2008

2.6

Sep 2008

2.9

Oct 2008

3.0

Nov 2008

3.3

Dec 2008

3.6

Jan 2009

4.4

Feb 2009

4.5

Mar 2009

5.3

Apr 2009

6.0

May 2009

5.7

Jun 2009

5.9

Jul 2009

6.5

Aug 2009

6.3

Sep 2009

6.0

Oct 2009

6.4

Nov 2009

6.1

Dec 2009

5.9

Jan 2010

5.3

Feb 2010

5.7

Mar 2010

5.7

Apr 2010

4.9

May 2010

5.0

Jun 2010

5.2

Jul 2010

4.7

Aug 2010

4.9

Sep 2010

5.0

Oct 2010

4.5

Nov 2010

4.7

Dec 2010

4.7

Jan 2011

4.5

Feb 2011

4.3

Mar 2011

4.2

Apr 2011

4.3

May 2011

4.4

Jun 2011

4.0

Jul 2011

3.8

Aug 2011

4.2

Sep 2011

3.7

Oct 2011

3.8

Nov 2011

3.7

Dec 2011

3.5

Jan 2012

3.3

Feb 2012

3.5

Mar 2012

3.2

Apr 2012

3.3

May 2012

3.3

Jun 2012

3.2

Jul 2012

3.4

Aug 2012

3.3

Sep 2012

3.1

Oct 2012

3.2

Nov 2012

3.1

Dec 2012

3.1

Jan 2013

3.2

Feb 2013

3.0

Mar 2013

2.9

Apr 2013

2.9

May 2013

2.8

Jun 2013

2.8

Jul 2013

2.9

Aug 2013

2.8

Sep 2013

2.7

Oct 2013

2.6

Nov 2013

2.6

Dec 2013

2.5

Jan 2014

2.5

Feb 2014

2.4

Mar 2014

2.4

Apr 2014

2.1

May 2014

2.1

Jun 2014

1.9

Jul 2014

2.0

Aug 2014

1.8

Sep 2014

1.9

Oct 2014

1.8

Nov 2014

1.9

Dec 2014

1.7

Jan 2015

1.7

Feb 2015

1.6

Mar 2015

1.6

Apr 2015

1.5

May 2015

1.6

Jun 2015

1.6

Jul 2015

1.3

Aug 2015

1.5

Sep 2015

1.4

Oct 2015

1.4

Nov 2015

1.4

Dec 2015

1.4

Jan 2016

1.3

Feb 2016

1.3

Mar 2016

1.3

Apr 2016

1.4

May 2016

1.3

Jun 2016

1.3

Jul 2016

1.3

Aug 2016

1.4

Sep 2016

1.4

Oct 2016

1.4

Nov 2016

1.3

Dec 2016

1.3

Jan 2017

1.3

Feb 2017

1.2

Mar 2017

1.2

Apr 2017

1.2

May 2017

1.2

Jun 2017

1.1

Jul 2017

1.1

Aug 2017

1.1

Sep 2017

1.1

Oct 2017

1.0

Nov 2017

1.1

Dec 2017

1.0

Jan 2018

1.0

Feb 2018

1.0

Mar 2018

1.0

Apr 2018

0.9

May 2018

0.9

Jun 2018

0.9

Jul 2018

0.9

Aug 2018

0.9

Sep 2018

0.8

Oct 2018

0.8

Nov 2018

0.8

Dec 2018

0.9

Jan 2019

0.9

Feb 2019

0.9

Mar 2019

0.8

Apr 2019

0.8

May 2019

0.8

Jun 2019

0.8

Jul 2019

0.8

Aug 2019

0.8

Sep 2019

0.8

Oct 2019

0.8

Nov 2019

0.9

Dec 2019

0.9

Jan 2020

0.8

Feb 2020

0.8

Mar 2020

1.2

Apr 2020

5.0

May 2020

3.9

Jun 2020

2.9

Jul 2020

2.4

Aug 2020

2.1

Sep 2020

1.9

Oct 2020

1.6

Nov 2020

1.6

Dec 2020

1.6

Jan 2021

1.4

Feb 2021

1.3

Mar 2021

1.2

Apr 2021

1.1

May 2021

1.0
Job openings, hires, and quit rates, total nonfarm, December 2000 to May 2021
MonthJob openings rateHires rateQuits rate

Dec 2000

3.7%4.1%2.2%

Jan 2001

3.84.32.4

Feb 2001

3.74.02.3

Mar 2001

3.54.22.3

Apr 2001

3.43.92.4

May 2001

3.24.12.3

Jun 2001

3.23.92.2

Jul 2001

3.34.02.2

Aug 2001

3.04.02.2

Sep 2001

3.03.82.1

Oct 2001

2.73.92.1

Nov 2001

2.83.72.0

Dec 2001

2.73.72.0

Jan 2002

2.73.72.2

Feb 2002

2.63.72.0

Mar 2002

2.73.61.9

Apr 2002

2.63.82.0

May 2002

2.63.71.9

Jun 2002

2.53.71.9

Jul 2002

2.53.82.0

Aug 2002

2.63.72.0

Sep 2002

2.53.71.9

Oct 2002

2.63.71.9

Nov 2002

2.63.71.8

Dec 2002

2.43.71.9

Jan 2003

2.63.91.9

Feb 2003

2.43.61.9

Mar 2003

2.33.41.8

Apr 2003

2.33.51.8

May 2003

2.53.61.8

Jun 2003

2.53.61.8

Jul 2003

2.23.61.7

Aug 2003

2.43.61.7

Sep 2003

2.33.71.8

Oct 2003

2.53.81.9

Nov 2003

2.53.71.8

Dec 2003

2.53.81.9

Jan 2004

2.63.71.8

Feb 2004

2.63.71.9

Mar 2004

2.64.02.0

Apr 2004

2.63.91.9

May 2004

2.73.81.8

Jun 2004

2.53.82.0

Jul 2004

2.83.72.0

Aug 2004

2.63.82.0

Sep 2004

2.83.81.9

Oct 2004

2.93.91.9

Nov 2004

2.63.92.1

Dec 2004

3.03.92.0

Jan 2005

2.83.92.1

Feb 2005

2.94.02.0

Mar 2005

2.94.02.1

Apr 2005

3.04.02.1

May 2005

2.83.92.1

Jun 2005

2.94.02.1

Jul 2005

3.14.02.0

Aug 2005

3.04.02.2

Sep 2005

3.14.12.3

Oct 2005

3.03.82.1

Nov 2005

3.14.02.1

Dec 2005

3.13.92.1

Jan 2006

3.13.92.2

Feb 2006

3.14.02.2

Mar 2006

3.44.12.2

Apr 2006

3.43.82.0

May 2006

3.24.02.2

Jun 2006

3.34.02.2

Jul 2006

3.14.12.2

Aug 2006

3.33.92.2

Sep 2006

3.33.92.1

Oct 2006

3.23.92.2

Nov 2006

3.34.02.2

Dec 2006

3.33.82.2

Jan 2007

3.33.92.1

Feb 2007

3.33.82.1

Mar 2007

3.54.02.2

Apr 2007

3.33.92.1

May 2007

3.34.02.2

Jun 2007

3.43.82.1

Jul 2007

3.23.82.1

Aug 2007

3.23.92.2

Sep 2007

3.33.91.9

Oct 2007

3.23.92.1

Nov 2007

3.33.72.0

Dec 2007

3.23.72.0

Jan 2008

3.23.72.1

Feb 2008

3.03.72.1

Mar 2008

3.03.61.9

Apr 2008

2.83.62.1

May 2008

3.03.41.9

Jun 2008

2.73.61.9

Jul 2008

2.73.41.8

Aug 2008

2.63.41.8

Sep 2008

2.33.31.8

Oct 2008

2.43.31.7

Nov 2008

2.33.01.6

Dec 2008

2.33.21.5

Jan 2009

2.03.11.5

Feb 2009

2.13.01.5

Mar 2009

1.92.91.4

Apr 2009

1.72.91.3

May 2009

1.92.91.3

Jun 2009

1.92.81.3

Jul 2009

1.73.01.3

Aug 2009

1.82.91.2

Sep 2009

1.93.01.2

Oct 2009

1.83.01.3

Nov 2009

1.93.11.4

Dec 2009

1.93.11.4

Jan 2010

2.13.01.3

Feb 2010

2.03.01.4

Mar 2010

2.03.31.4

Apr 2010

2.43.21.5

May 2010

2.23.41.4

Jun 2010

2.13.11.5

Jul 2010

2.33.21.4

Aug 2010

2.23.11.4

Sep 2010

2.23.11.5

Oct 2010

2.43.21.4

Nov 2010

2.43.21.4

Dec 2010

2.33.31.5

Jan 2011

2.33.11.4

Feb 2011

2.43.21.5

Mar 2011

2.43.41.5

Apr 2011

2.43.31.4

May 2011

2.43.21.5

Jun 2011

2.63.31.5

Jul 2011

2.73.21.5

Aug 2011

2.53.31.5

Sep 2011

2.83.31.5

Oct 2011

2.73.31.5

Nov 2011

2.63.31.5

Dec 2011

2.83.31.5

Jan 2012

2.83.31.5

Feb 2012

2.63.41.6

Mar 2012

2.93.41.6

Apr 2012

2.83.31.6

May 2012

2.83.41.6

Jun 2012

2.83.31.6

Jul 2012

2.73.21.5

Aug 2012

2.83.31.5

Sep 2012

2.83.21.4

Oct 2012

2.73.31.5

Nov 2012

2.83.31.5

Dec 2012

2.93.31.5

Jan 2013

2.83.31.7

Feb 2013

2.93.41.7

Mar 2013

2.93.21.6

Apr 2013

2.93.41.7

May 2013

3.03.41.6

Jun 2013

3.03.31.6

Jul 2013

2.83.31.7

Aug 2013

2.93.51.7

Sep 2013

2.93.51.7

Oct 2013

3.03.31.7

Nov 2013

2.93.41.7

Dec 2013

2.93.41.7

Jan 2014

2.93.41.7

Feb 2014

3.13.41.8

Mar 2014

3.13.51.8

Apr 2014

3.23.51.8

May 2014

3.33.51.8

Jun 2014

3.53.51.8

Jul 2014

3.43.61.9

Aug 2014

3.73.51.8

Sep 2014

3.43.72.0

Oct 2014

3.53.71.9

Nov 2014

3.33.61.9

Dec 2014

3.53.71.8

Jan 2015

3.73.62.0

Feb 2015

3.73.61.9

Mar 2015

3.63.62.0

Apr 2015

3.83.71.9

May 2015

3.83.61.9

Jun 2015

3.63.61.9

Jul 2015

4.13.61.9

Aug 2015

3.73.62.0

Sep 2015

3.73.72.0

Oct 2015

3.93.72.0

Nov 2015

3.83.82.0

Dec 2015

3.93.92.1

Jan 2016

4.03.62.0

Feb 2016

3.93.82.1

Mar 2016

4.13.72.0

Apr 2016

3.93.72.1

May 2016

3.93.62.1

Jun 2016

3.83.72.1

Jul 2016

4.03.82.1

Aug 2016

3.83.72.1

Sep 2016

3.93.72.1

Oct 2016

3.73.62.1

Nov 2016

4.03.72.1

Dec 2016

3.93.72.1

Jan 2017

3.73.82.2

Feb 2017

3.93.72.1

Mar 2017

3.83.72.2

Apr 2017

4.03.62.1

May 2017

3.83.72.1

Jun 2017

4.13.92.2

Jul 2017

4.13.82.1

Aug 2017

4.13.82.1

Sep 2017

4.13.72.2

Oct 2017

4.23.82.2

Nov 2017

4.13.72.1

Dec 2017

4.13.72.2

Jan 2018

4.33.72.1

Feb 2018

4.33.82.2

Mar 2018

4.43.82.2

Apr 2018

4.43.82.3

May 2018

4.53.92.3

Jun 2018

4.73.92.3

Jul 2018

4.63.82.3

Aug 2018

4.63.92.3

Sep 2018

4.73.82.3

Oct 2018

4.73.92.3

Nov 2018

4.83.92.3

Dec 2018

4.73.82.3

Jan 2019

4.73.82.3

Feb 2019

4.53.82.4

Mar 2019

4.73.82.3

Apr 2019

4.64.02.3

May 2019

4.63.82.3

Jun 2019

4.53.82.3

Jul 2019

4.54.02.4

Aug 2019

4.53.92.4

Sep 2019

4.53.92.3

Oct 2019

4.63.82.3

Nov 2019

4.43.82.3

Dec 2019

4.23.92.3

Jan 2020

4.53.92.3

Feb 2020

4.43.92.2

Mar 2020

3.73.41.9

Apr 2020

3.43.01.6

May 2020

3.96.21.7

Jun 2020

4.25.61.9

Jul 2020

4.64.52.3

Aug 2020

4.44.62.1

Sep 2020

4.54.22.3

Oct 2020

4.64.22.4

Nov 2020

4.54.22.3

Dec 2020

4.53.82.4

Jan 2021

4.73.82.3

Feb 2021

5.04.02.4

Mar 2021

5.44.22.5

Apr 2021

6.04.22.8

May 2021

6.04.12.5
Percent change since February 2020 in real (inflation-adjusted) average hourly earnings
MonthTotal privateLeisure and hospitality

Feb 2020

0.0%0.0%

Mar 2020

1.10.3

Apr 2020

6.57.7

May 2020

5.44.3

Jun 2020

3.51.4

Jul 2020

3.10.2

Aug 2020

3.10.6

Sep 2020

2.90.6

Oct 2020

2.80.6

Nov 2020

3.00.3

Dec 2020

3.80.5

Jan 2021

3.50.6

Feb 2021

3.41.1

Mar 2021

2.71.8

Apr 2021

2.62.5

May 2021

2.42.9

Jun 2021

1.83.1
Job openings and hires rates, leisure and hospitality, December 2000 to May 2021
MonthJob openings rateHires rate

Dec 2000

4.5%7.4%

Jan 2001

5.27.7

Feb 2001

4.87.3

Mar 2001

5.57.8

Apr 2001

4.68.3

May 2001

4.27.6

Jun 2001

3.67.2

Jul 2001

4.67.7

Aug 2001

4.37.2

Sep 2001

4.37.3

Oct 2001

3.06.9

Nov 2001

3.66.8

Dec 2001

3.56.8

Jan 2002

2.96.5

Feb 2002

3.36.9

Mar 2002

3.36.5

Apr 2002

3.16.9

May 2002

3.26.7

Jun 2002

2.86.6

Jul 2002

3.16.7

Aug 2002

3.26.9

Sep 2002

2.86.7

Oct 2002

3.16.5

Nov 2002

3.26.6

Dec 2002

3.06.8

Jan 2003

3.17.0

Feb 2003

2.96.6

Mar 2003

2.86.4

Apr 2003

3.06.5

May 2003

3.47.0

Jun 2003

3.46.7

Jul 2003

2.76.4

Aug 2003

3.16.7

Sep 2003

3.16.8

Oct 2003

3.66.9

Nov 2003

3.46.8

Dec 2003

3.57.1

Jan 2004

3.56.8

Feb 2004

3.66.9

Mar 2004

3.47.3

Apr 2004

3.27.1

May 2004

3.37.2

Jun 2004

3.67.0

Jul 2004

4.07.0

Aug 2004

3.67.0

Sep 2004

4.07.2

Oct 2004

3.76.9

Nov 2004

3.37.0

Dec 2004

3.66.8

Jan 2005

4.17.2

Feb 2005

4.06.9

Mar 2005

4.27.2

Apr 2005

4.77.0

May 2005

4.06.8

Jun 2005

4.37.3

Jul 2005

4.07.2

Aug 2005

3.87.3

Sep 2005

3.67.2

Oct 2005

3.86.8

Nov 2005

3.97.2

Dec 2005

4.47.1

Jan 2006

4.77.2

Feb 2006

4.47.4

Mar 2006

4.17.2

Apr 2006

4.97.1

May 2006

4.07.1

Jun 2006

4.07.2

Jul 2006

4.37.3

Aug 2006

4.26.8

Sep 2006

4.26.6

Oct 2006

4.37.1

Nov 2006

4.47.5

Dec 2006

4.27.0

Jan 2007

3.76.9

Feb 2007

4.06.9

Mar 2007

4.56.8

Apr 2007

4.07.2

May 2007

4.27.0

Jun 2007

4.57.2

Jul 2007

4.56.8

Aug 2007

4.57.0

Sep 2007

4.86.7

Oct 2007

4.36.9

Nov 2007

4.56.7

Dec 2007

4.16.6

Jan 2008

4.16.3

Feb 2008

3.96.8

Mar 2008

4.16.2

Apr 2008

3.96.3

May 2008

3.96.7

Jun 2008

3.45.9

Jul 2008

3.26.0

Aug 2008

3.16.2

Sep 2008

3.05.9

Oct 2008

3.05.8

Nov 2008

2.65.3

Dec 2008

2.65.6

Jan 2009

1.85.4

Feb 2009

2.45.2

Mar 2009

2.04.8

Apr 2009

2.04.7

May 2009

2.25.2

Jun 2009

2.14.8

Jul 2009

1.94.7

Aug 2009

1.55.0

Sep 2009

2.14.8

Oct 2009

2.04.7

Nov 2009

2.15.3

Dec 2009

2.05.0

Jan 2010

2.15.1

Feb 2010

2.04.7

Mar 2010

1.85.2

Apr 2010

2.15.2

May 2010

2.34.9

Jun 2010

2.54.9

Jul 2010

2.45.1

Aug 2010

2.74.9

Sep 2010

2.45.1

Oct 2010

3.15.0

Nov 2010

2.45.0

Dec 2010

2.65.1

Jan 2011

2.74.9

Feb 2011

2.95.1

Mar 2011

2.95.8

Apr 2011

2.45.1

May 2011

2.34.9

Jun 2011

3.05.5

Jul 2011

2.65.4

Aug 2011

2.85.4

Sep 2011

3.15.6

Oct 2011

3.15.5

Nov 2011

3.15.9

Dec 2011

3.25.5

Jan 2012

3.25.7

Feb 2012

2.75.7

Mar 2012

3.26.3

Apr 2012

3.45.5

May 2012

3.25.4

Jun 2012

3.45.3

Jul 2012

3.45.5

Aug 2012

3.05.8

Sep 2012

3.05.2

Oct 2012

3.45.5

Nov 2012

3.55.2

Dec 2012

3.35.8

Jan 2013

3.25.7

Feb 2013

3.65.6

Mar 2013

3.55.7

Apr 2013

3.36.1

May 2013

3.25.7

Jun 2013

3.35.7

Jul 2013

3.45.5

Aug 2013

3.55.4

Sep 2013

3.75.8

Oct 2013

3.65.6

Nov 2013

3.65.5

Dec 2013

3.95.5

Jan 2014

4.05.8

Feb 2014

3.75.9

Mar 2014

3.85.7

Apr 2014

4.35.9

May 2014

4.66.1

Jun 2014

4.46.2

Jul 2014

4.16.0

Aug 2014

4.65.8

Sep 2014

4.66.2

Oct 2014

4.36.0

Nov 2014

4.16.1

Dec 2014

4.56.3

Jan 2015

5.16.1

Feb 2015

4.86.2

Mar 2015

4.66.1

Apr 2015

4.66.3

May 2015

4.46.4

Jun 2015

4.26.1

Jul 2015

4.86.3

Aug 2015

4.46.7

Sep 2015

4.46.7

Oct 2015

4.96.6

Nov 2015

4.76.7

Dec 2015

4.66.8

Jan 2016

4.76.2

Feb 2016

4.76.8

Mar 2016

5.16.6

Apr 2016

4.76.5

May 2016

4.66.6

Jun 2016

4.86.7

Jul 2016

4.66.6

Aug 2016

4.96.6

Sep 2016

4.56.1

Oct 2016

4.66.2

Nov 2016

4.66.7

Dec 2016

4.56.4

Jan 2017

4.46.5

Feb 2017

5.36.4

Mar 2017

4.56.3

Apr 2017

5.06.4

May 2017

5.06.3

Jun 2017

5.06.5

Jul 2017

5.16.3

Aug 2017

5.26.2

Sep 2017

4.56.1

Oct 2017

4.86.5

Nov 2017

5.26.3

Dec 2017

5.26.1

Jan 2018

5.46.3

Feb 2018

5.46.5

Mar 2018

5.46.4

Apr 2018

5.66.5

May 2018

5.66.9

Jun 2018

6.16.4

Jul 2018

5.96.8

Aug 2018

5.86.5

Sep 2018

6.16.4

Oct 2018

5.86.7

Nov 2018

5.86.5

Dec 2018

6.26.3

Jan 2019

6.46.8

Feb 2019

5.76.6

Mar 2019

5.86.7

Apr 2019

5.87.1

May 2019

5.86.6

Jun 2019

5.47.0

Jul 2019

5.56.9

Aug 2019

5.46.9

Sep 2019

5.76.9

Oct 2019

5.66.6

Nov 2019

5.56.5

Dec 2019

5.26.8

Jan 2020

5.26.6

Feb 2020

5.36.5

Mar 2020

3.94.2

Apr 2020

3.84.9

May 2020

6.819.5

Jun 2020

7.017.5

Jul 2020

6.310.6

Aug 2020

6.08.1

Sep 2020

5.98.2

Oct 2020

6.18.5

Nov 2020

5.98.1

Dec 2020

5.45.8

Jan 2021

5.37.1

Feb 2021

6.58.8

Mar 2021

8.08.5

Apr 2021

9.19.5

May 2021

9.09.3

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.