Department of Labor Logo United States Department of Labor
Dot gov

The .gov means it's official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Topic Archives: U.S. Statistical System

Has the Labor Market Recovered from the COVID-19 Pandemic?

I recently had the pleasure of speaking at the National Association for Business Economics Policy Conference, regarding labor market recovery. Today I’m sharing some highlights from that talk, updated to include the latest BLS data.

There continues to be widespread interest in how well U.S. labor markets are recovering from the massive job losses at the start of the COVID-19 pandemic. Not only does this interest involve counting the number of jobs, but it also includes shifts in labor skills and changes in compensation levels. Some parts of the labor market may emerge from a recession very differently from how they entered. This difference could be in skills required, compensation, changes in the workplace, or a worker’s use of capital. Thus, we always should consider the possibility that recovery in a labor market will differ from what we had before the economic shock. In other words, we should be ready to be surprised.

What does “labor market recovery” mean? According to the National Bureau of Economic Research, the pandemic-related recession lasted just 2 months in the first half of 2020. But we know resumption of work varied considerably over the past 2 years, with some industries maintaining or even expanding employment in the early months of the pandemic, while others continue a slower return to pre-pandemic work levels.

Let’s now step through some ways to understand labor market recovery. Many observers would define recovery as a return to the employment levels before the recession, or, in our case, before the economic collapse and slower economic activity as the pandemic continued. We measure this definition of recovery by the number of jobs below and above the February 2020 levels. Based on our most recent data releases, total nonfarm employment, as measured by the BLS Current Employment Statistics survey, has recovered 93 percent of the jobs lost in March and April 2020. This chart shows the change in employment since February 2020 for major industry groups. It’s easy to see industries with large gains and industries that have not yet recovered their previous employment level.

Change in jobs in each industry in March 2022 above or below the levels of February 2020

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

However, this straightforward definition of recovery does not account for the growth in the civilian population (16 years and older) over the past 2 years, which constitutes the base of employment and potential employment. The U.S. population age 16 and older grew by around 3.8 million between February 2020 and March 2022. Thus, we could define recovery as total jobs from February 2020 plus additional employment to account for population growth.

Of course, that does not account for one of the principal labor market characteristics of the past 2 years: The number of workers who left the labor force and never returned. Looking at data from the Current Population Survey, we learn that many of those people who are not in the labor force indicate that they want a job but are not looking. That number rose by nearly 5 million at the beginning of the pandemic but has declined significantly since then. In fact, it was still 741,000 higher in March 2022 than in February of 2020. And we still have nearly a million people who say they are not looking for work now because of the pandemic.

People not in labor force who say they want a job now, January 2006 to March 2022

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

In addition to these straightforward concepts of recovery, our colleagues at the Bureau of Economic Analysis report on our nation’s output of goods and services, called Gross Domestic Product (GDP). Nominal GDP was $4.5 trillion higher in the fourth quarter of 2021 than in the depths of the recession in the second quarter of 2020; after adjusting for inflation, real GDP was $2.5 trillion higher. Both nominal and real GDP were also higher in the fourth quarter of 2021 than in the quarters before the pandemic and recession. The recovery in output implies that the current labor force is enough to support more GDP than we had in the pre-pandemic economy.

Likewise, the BLS index of total private sector labor hours is 99.9 percent recovered from its February 2020 level.

Index of total weekly hours of all employees, private sector, May 2007 to March 2022

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

Still another way to think about labor market recovery is to measure the return of demand for labor. Labor demand is tricky because it is driven by so many factors in the product and service markets. That said, some recent evidence is instructive. In February 2022, the Job Openings and Labor Turnover Survey reported 11.3 million job openings, which is near a historical high. Hires stood at 6.7 million, and separations at 6.1 million. That’s a hires rate of 4.4 percent, little changed from the prior 12 months. In short, demand is high and rising, but hires remain relatively flat and at a normal level.

Job openings, hires, and separations rates, total nonfarm, January 2019 to February 2022

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

Finally, there’s the issue of labor force participation, the percentage of people age 16 and older who either are working or have looked for work in the past 4 weeks. The latest rate is 62.4 percent in March 2022, up from a low of 60.2 percent in April 2020. However, the rate stood at 63.4 percent in January and February of 2020.

For people ages 25 to 54, the March 2022 labor force participation rate for men was 88.7 percent, compared with 89.3 percent in January 2020. For women, the March 2022 rate was 76.5 percent, down from 76.9 percent in January 2020. Both rates, but particularly the rate for women, were buffeted by the waves of infections and the closing of schools and daycare facilities.

Labor force participation rates of people ages 25 to 54, January 2019 to March 2022

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

Let me conclude with a few observations. First, we see total work hours returning to their pre-pandemic level and GDP increasing. Labor force participation continues to lag its pre-pandemic rate. The recovery in output suggests the lagging labor force participation may result from demographic and other social factors, and not just economic conditions.

Change in jobs in each industry in March 2022 above or below the levels of February 2020
IndustryEmployment change

Professional and business services

723,000

Transportation and warehousing

607,500

Retail trade

278,300

Financial activities

41,000

Information

26,000

Construction

4,000

Utilities

-10,000

Mining and logging

-86,000

Wholesale trade

-103,900

Manufacturing

-128,000

Other services

-291,000

Education and health services

-456,000

Government

-710,000

Leisure and hospitality

-1,474,000
People not in labor force who say they want a job now
MonthWant a job now

Jan 2006

4,964,000

Feb 2006

4,901,000

Mar 2006

4,918,000

Apr 2006

4,719,000

May 2006

4,635,000

Jun 2006

4,726,000

Jul 2006

4,862,000

Aug 2006

4,951,000

Sep 2006

4,666,000

Oct 2006

4,868,000

Nov 2006

4,818,000

Dec 2006

4,390,000

Jan 2007

4,506,000

Feb 2007

4,706,000

Mar 2007

4,565,000

Apr 2007

4,794,000

May 2007

4,968,000

Jun 2007

4,857,000

Jul 2007

4,737,000

Aug 2007

4,827,000

Sep 2007

4,750,000

Oct 2007

4,352,000

Nov 2007

4,648,000

Dec 2007

4,657,000

Jan 2008

4,846,000

Feb 2008

4,739,000

Mar 2008

4,718,000

Apr 2008

4,733,000

May 2008

4,851,000

Jun 2008

4,929,000

Jul 2008

5,023,000

Aug 2008

4,922,000

Sep 2008

5,153,000

Oct 2008

5,094,000

Nov 2008

5,421,000

Dec 2008

5,431,000

Jan 2009

5,708,000

Feb 2009

5,617,000

Mar 2009

5,807,000

Apr 2009

5,927,000

May 2009

5,986,000

Jun 2009

5,908,000

Jul 2009

6,003,000

Aug 2009

5,649,000

Sep 2009

5,949,000

Oct 2009

6,002,000

Nov 2009

5,998,000

Dec 2009

6,186,000

Jan 2010

5,942,000

Feb 2010

6,098,000

Mar 2010

5,993,000

Apr 2010

5,913,000

May 2010

5,824,000

Jun 2010

5,909,000

Jul 2010

5,895,000

Aug 2010

6,037,000

Sep 2010

6,270,000

Oct 2010

6,289,000

Nov 2010

6,182,000

Dec 2010

6,431,000

Jan 2011

6,472,000

Feb 2011

6,390,000

Mar 2011

6,527,000

Apr 2011

6,537,000

May 2011

6,289,000

Jun 2011

6,519,000

Jul 2011

6,513,000

Aug 2011

6,463,000

Sep 2011

6,262,000

Oct 2011

6,384,000

Nov 2011

6,538,000

Dec 2011

6,323,000

Jan 2012

6,343,000

Feb 2012

6,335,000

Mar 2012

6,302,000

Apr 2012

6,426,000

May 2012

6,309,000

Jun 2012

6,564,000

Jul 2012

6,516,000

Aug 2012

7,011,000

Sep 2012

6,817,000

Oct 2012

6,551,000

Nov 2012

6,833,000

Dec 2012

6,728,000

Jan 2013

6,637,000

Feb 2013

6,772,000

Mar 2013

6,670,000

Apr 2013

6,428,000

May 2013

6,726,000

Jun 2013

6,614,000

Jul 2013

6,526,000

Aug 2013

6,284,000

Sep 2013

6,119,000

Oct 2013

6,024,000

Nov 2013

5,754,000

Dec 2013

6,126,000

Jan 2014

6,360,000

Feb 2014

6,011,000

Mar 2014

6,174,000

Apr 2014

6,207,000

May 2014

6,553,000

Jun 2014

6,207,000

Jul 2014

6,264,000

Aug 2014

6,376,000

Sep 2014

6,326,000

Oct 2014

6,431,000

Nov 2014

6,558,000

Dec 2014

6,406,000

Jan 2015

6,300,000

Feb 2015

6,503,000

Mar 2015

6,355,000

Apr 2015

6,221,000

May 2015

6,051,000

Jun 2015

6,130,000

Jul 2015

6,097,000

Aug 2015

5,890,000

Sep 2015

5,868,000

Oct 2015

5,997,000

Nov 2015

5,649,000

Dec 2015

5,909,000

Jan 2016

6,006,000

Feb 2016

5,927,000

Mar 2016

5,730,000

Apr 2016

5,812,000

May 2016

5,962,000

Jun 2016

5,590,000

Jul 2016

5,906,000

Aug 2016

5,752,000

Sep 2016

6,017,000

Oct 2016

5,948,000

Nov 2016

5,864,000

Dec 2016

5,668,000

Jan 2017

5,758,000

Feb 2017

5,653,000

Mar 2017

5,758,000

Apr 2017

5,708,000

May 2017

5,465,000

Jun 2017

5,277,000

Jul 2017

5,425,000

Aug 2017

5,734,000

Sep 2017

5,637,000

Oct 2017

5,293,000

Nov 2017

5,219,000

Dec 2017

5,275,000

Jan 2018

5,191,000

Feb 2018

5,169,000

Mar 2018

5,044,000

Apr 2018

5,163,000

May 2018

5,188,000

Jun 2018

5,204,000

Jul 2018

5,195,000

Aug 2018

5,413,000

Sep 2018

5,288,000

Oct 2018

5,408,000

Nov 2018

5,398,000

Dec 2018

5,320,000

Jan 2019

5,262,000

Feb 2019

5,216,000

Mar 2019

5,136,000

Apr 2019

5,107,000

May 2019

4,994,000

Jun 2019

5,272,000

Jul 2019

4,999,000

Aug 2019

5,212,000

Sep 2019

4,852,000

Oct 2019

4,778,000

Nov 2019

4,849,000

Dec 2019

4,839,000

Jan 2020

4,937,000

Feb 2020

4,996,000

Mar 2020

5,462,000

Apr 2020

9,921,000

May 2020

8,916,000

Jun 2020

8,182,000

Jul 2020

7,712,000

Aug 2020

7,070,000

Sep 2020

7,194,000

Oct 2020

6,685,000

Nov 2020

7,120,000

Dec 2020

7,277,000

Jan 2021

6,956,000

Feb 2021

6,923,000

Mar 2021

6,822,000

Apr 2021

6,628,000

May 2021

6,583,000

Jun 2021

6,422,000

Jul 2021

6,529,000

Aug 2021

5,701,000

Sep 2021

5,918,000

Oct 2021

5,935,000

Nov 2021

5,819,000

Dec 2021

5,713,000

Jan 2022

5,704,000

Feb 2022

5,355,000

Mar 2022

5,737,000
Index of total weekly hours of all employees, private sector, May 2007 to March 2022
MonthIndex

May 2007

100.0

Jun 2007

100.3

Jul 2007

100.1

Aug 2007

100.0

Sep 2007

100.0

Oct 2007

99.8

Nov 2007

100.1

Dec 2007

100.2

Jan 2008

100.2

Feb 2008

100.1

Mar 2008

100.3

Apr 2008

99.5

May 2008

99.6

Jun 2008

99.5

Jul 2008

99.0

Aug 2008

98.7

Sep 2008

98.1

Oct 2008

97.6

Nov 2008

96.7

Dec 2008

95.6

Jan 2009

95.1

Feb 2009

94.5

Mar 2009

93.3

Apr 2009

92.6

May 2009

92.4

Jun 2009

91.7

Jul 2009

91.8

Aug 2009

91.6

Sep 2009

91.7

Oct 2009

91.2

Nov 2009

91.5

Dec 2009

91.3

Jan 2010

91.9

Feb 2010

91.0

Mar 2010

91.6

Apr 2010

92.1

May 2010

92.2

Jun 2010

92.3

Jul 2010

92.3

Aug 2010

92.7

Sep 2010

93.1

Oct 2010

93.3

Nov 2010

93.1

Dec 2010

93.5

Jan 2011

93.2

Feb 2011

93.7

Mar 2011

93.9

Apr 2011

94.5

May 2011

94.3

Jun 2011

94.5

Jul 2011

94.9

Aug 2011

94.8

Sep 2011

95.3

Oct 2011

95.5

Nov 2011

95.6

Dec 2011

95.8

Jan 2012

96.4

Feb 2012

96.6

Mar 2012

96.6

Apr 2012

96.9

May 2012

96.7

Jun 2012

96.8

Jul 2012

96.9

Aug 2012

97.1

Sep 2012

97.2

Oct 2012

97.4

Nov 2012

97.5

Dec 2012

98.0

Jan 2013

97.9

Feb 2013

98.4

Mar 2013

98.6

Apr 2013

98.4

May 2013

98.9

Jun 2013

99.1

Jul 2013

98.9

Aug 2013

99.4

Sep 2013

99.3

Oct 2013

99.5

Nov 2013

100.0

Dec 2013

99.8

Jan 2014

99.9

Feb 2014

99.8

Mar 2014

100.6

Apr 2014

100.8

May 2014

101.1

Jun 2014

101.3

Jul 2014

101.5

Aug 2014

102.0

Sep 2014

101.9

Oct 2014

102.4

Nov 2014

102.6

Dec 2014

102.9

Jan 2015

102.7

Feb 2015

103.2

Mar 2015

103.0

Apr 2015

103.2

May 2015

103.5

Jun 2015

103.7

Jul 2015

103.9

Aug 2015

104.0

Sep 2015

104.1

Oct 2015

104.7

Nov 2015

104.6

Dec 2015

104.8

Jan 2016

105.2

Feb 2016

104.7

Mar 2016

104.9

Apr 2016

105.1

May 2016

105.1

Jun 2016

105.3

Jul 2016

105.6

Aug 2016

105.4

Sep 2016

105.9

Oct 2016

106.0

Nov 2016

106.2

Dec 2016

106.3

Jan 2017

106.5

Feb 2017

106.3

Mar 2017

106.5

Apr 2017

106.9

May 2017

107.1

Jun 2017

107.3

Jul 2017

107.4

Aug 2017

107.6

Sep 2017

107.4

Oct 2017

107.8

Nov 2017

108.2

Dec 2017

108.4

Jan 2018

108.2

Feb 2018

108.8

Mar 2018

109.0

Apr 2018

109.2

May 2018

109.4

Jun 2018

109.6

Jul 2018

109.6

Aug 2018

109.8

Sep 2018

109.9

Oct 2018

110.0

Nov 2018

109.8

Dec 2018

110.3

Jan 2019

110.5

Feb 2019

110.2

Mar 2019

110.7

Apr 2019

110.6

May 2019

110.6

Jun 2019

110.7

Jul 2019

110.9

Aug 2019

111.0

Sep 2019

111.0

Oct 2019

111.1

Nov 2019

111.0

Dec 2019

111.1

Jan 2020

111.4

Feb 2020

111.9

Mar 2020

109.7

Apr 2020

93.2

May 2020

97.3

Jun 2020

101.0

Jul 2020

102.1

Aug 2020

103.4

Sep 2020

104.6

Oct 2020

105.6

Nov 2020

105.6

Dec 2020

105.2

Jan 2021

106.5

Feb 2021

105.9

Mar 2021

107.4

Apr 2021

107.6

May 2021

107.9

Jun 2021

108.0

Jul 2021

108.6

Aug 2021

108.7

Sep 2021

109.4

Oct 2021

110.0

Nov 2021

110.5

Dec 2021

111.0

Jan 2022

110.8

Feb 2022

111.8

Mar 2022

111.8
Job openings, hires, and separations rates, total nonfarm, January 2019 to February 2022
MonthJob openings rateHires rateSeparations rate

Jan 2019

4.7%3.8%3.7%

Feb 2019

4.53.83.8

Mar 2019

4.63.83.7

Apr 2019

4.64.03.8

May 2019

4.63.83.7

Jun 2019

4.53.83.7

Jul 2019

4.53.93.9

Aug 2019

4.53.93.7

Sep 2019

4.53.93.8

Oct 2019

4.73.83.7

Nov 2019

4.43.93.7

Dec 2019

4.33.93.8

Jan 2020

4.53.93.8

Feb 2020

4.44.03.8

Mar 2020

3.83.510.8

Apr 2020

3.53.18.9

May 2020

3.96.13.6

Jun 2020

4.25.43.8

Jul 2020

4.54.53.7

Aug 2020

4.34.33.4

Sep 2020

4.44.23.6

Oct 2020

4.64.33.7

Nov 2020

4.64.14.0

Dec 2020

4.64.04.0

Jan 2021

4.84.03.6

Feb 2021

5.24.23.8

Mar 2021

5.54.33.8

Apr 2021

6.04.24.0

May 2021

6.24.23.8

Jun 2021

6.34.44.0

Jul 2021

6.94.54.0

Aug 2021

6.74.34.0

Sep 2021

6.84.44.1

Oct 2021

7.04.44.0

Nov 2021

6.84.54.2

Dec 2021

7.14.34.1

Jan 2022

7.04.34.0

Feb 2022

7.04.44.1
Labor force participation rates of people ages 25 to 54, January 2019 to March 2022
MonthTotalMenWomen

Jan 2019

82.5%89.3%75.8%

Feb 2019

82.589.475.8

Mar 2019

82.589.675.5

Apr 2019

82.389.275.5

May 2019

82.288.975.7

Jun 2019

82.288.875.9

Jul 2019

82.188.975.4

Aug 2019

82.689.076.3

Sep 2019

82.789.276.4

Oct 2019

82.889.176.7

Nov 2019

82.889.276.6

Dec 2019

82.989.176.8

Jan 2020

83.189.376.9

Feb 2020

83.089.276.9

Mar 2020

82.589.076.1

Apr 2020

79.986.473.5

May 2020

80.687.274.3

Jun 2020

81.587.875.3

Jul 2020

81.287.575.1

Aug 2020

81.487.974.9

Sep 2020

81.087.774.4

Oct 2020

81.287.874.8

Nov 2020

80.987.374.6

Dec 2020

81.087.474.7

Jan 2021

81.187.674.7

Feb 2021

81.287.674.9

Mar 2021

81.387.675.2

Apr 2021

81.487.975.1

May 2021

81.487.975.0

Jun 2021

81.788.175.4

Jul 2021

81.988.375.6

Aug 2021

81.888.375.4

Sep 2021

81.688.275.3

Oct 2021

81.788.175.4

Nov 2021

81.988.275.7

Dec 2021

81.988.075.9

Jan 2022

82.088.276.0

Feb 2022

82.288.875.8

Mar 2022

82.588.776.5

What’s Going on with the Large Revisions in Seasonally Adjusted Employment Estimates?

When BLS released The Employment Situation for January 2022 on February 4, we reported larger-than-normal revisions to the seasonally adjusted monthly nonfarm employment estimates from the Current Employment Statistics survey. Let’s take a closer look at the seasonal adjustment process and explain why the revisions were unusually large.

BLS seasonally adjusts data to account for recurring seasonal patterns in a time series. It allows our data users to analyze the underlying trends without the influence of seasonal movements. Seasonal movements might entail hiring extra retail trade workers around the December holidays. Seasonal movements also may entail workers leaving payrolls, such as school bus drivers when the schoolyear ends. These types of movements happen around the same time every year and affect about the same number of workers each year. Because the seasonal movements in nonfarm employment typically don’t change by much year to year, revisions to over-the-month changes from seasonal adjustment are typically small. However, data users may have a hard time seeing seasonal patterns when large events like strikes, hurricanes, or recessions occur. The unprecedented changes brought on by the COVID-19 pandemic make it even more difficult to determine the seasonal patterns.

Every year, during the employment benchmarking process, BLS staff takes a more comprehensive look back at the seasonal adjustment of time series to account for changes in seasonal patterns of nonfarm employment. Months in which large, irregular events occur are treated as outliers, which means that the abnormal change will not be treated as a new seasonal pattern. When we seasonally adjusted the data for 2020 after 2020 had ended, we treated several months individually as outliers. That works well for short-lived events, like strikes or a weather-related event. At that time, with very few observations after the start of the pandemic, that type of individual outlier detection was appropriate.

For example, the economy lost a massive number of jobs in March and April 2020 at the start of the pandemic. If we had not treated those months as outliers, or irregular events, the seasonal adjustment model would have expected massive employment losses as a new seasonal pattern for March and April 2021. That would not have been appropriate because those huge losses in March and April 2020 were not likely to recur. If the model had included the large March and April 2020 employment losses, when large job losses did not occur in March and April 2021, the model would have shown large job gains for those months on a seasonally adjusted basis. That would have distorted the underlying employment trend.

We now have more data observations after the start of the pandemic, and we benefit from the hindsight of our normal annual review of the data, which encompasses the last 5 years of data. We incorporated two additional outlier types that better isolated the initial losses in employment from the pandemic, while simultaneously accounting for new seasonal patterns that we have detected. One new type of outlier accounts for a temporary change in the level of the series. For example, drinking places that serve alcoholic beverages experienced a significant employment decline in April 2020 but have gained jobs since then, even if in fits and starts. In this case, we treated April 2020 as a temporary change outlier, which will adjust the months from April 2020 forward to account for both the large drop and subsequent recovery in employment this industry has experienced. This will better account for this temporary period of readjustment as employment levels recover towards what they were before the pandemic.

Employment in drinking places, alcoholic beverages, January 2020 to December 2021, seasonally adjusted

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

The other new type of outlier accounts for a permanent shift in the level of a series. An example of this is nursing care facilities, which continued to experience employment declines after April 2020. In this case, April 2020 was treated as a level shift outlier, which resulted in subsequent months being adjusted to better reflect the continued lower level of employment.

Employment in nursing care facilities, January 2020 to December 2021, seasonally adjusted

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

Incorporating these additional types of outliers stabilized the normal seasonal patterns and smoothed out the initial large swings in the seasonally adjusted data. These changes resulted in a more accurate payroll employment series and will allow users to better differentiate longer-term trends from seasonal movements.

These changes resulted in some large revisions to our monthly seasonally adjusted data for 2021, although the revisions partly offset each other. For example, total nonfarm employment in November and December 2021 combined is 709,000 higher than previously reported, while employment in June and July 2021 combined is 807,000 lower. The change for all of 2021 is just 217,000 higher than previously reported. Although these revisions are larger than usual, trends in the data emerge more clearly.

Want to really dig into the details of seasonal adjustment for the nonfarm employment data? See our specification files and technical documentation.

Employment in drinking places, alcoholic beverages, January 2020 to December 2021, seasonally adjusted
MonthPreviously publishedRevised

Jan 2020

417,200419,800

Feb 2020

423,700426,400

Mar 2020

381,800383,600

Apr 2020

85,60084,800

May 2020

145,400140,600

Jun 2020

233,800225,300

Jul 2020

238,700226,200

Aug 2020

250,800243,800

Sep 2020

266,200260,000

Oct 2020

289,700278,500

Nov 2020

280,900281,300

Dec 2020

243,000239,700

Jan 2021

248,300248,700

Feb 2021

282,200280,700

Mar 2021

303,900298,300

Apr 2021

311,700309,900

May 2021

318,300322,900

Jun 2021

322,000331,200

Jul 2021

329,700336,800

Aug 2021

329,500342,900

Sep 2021

343,900350,600

Oct 2021

345,500354,200

Nov 2021

347,900365,000

Dec 2021

344,500363,800
Employment in nursing care facilities, January 2020 to December 2021, seasonally adjusted
MonthPreviously publishedRevised

Jan 2020

1,586,5001,585,100

Feb 2020

1,585,7001,584,800

Mar 2020

1,581,6001,581,200

Apr 2020

1,534,3001,537,200

May 2020

1,502,6001,508,000

Jun 2020

1,487,3001,490,000

Jul 2020

1,469,7001,470,600

Aug 2020

1,459,2001,463,300

Sep 2020

1,456,6001,454,500

Oct 2020

1,451,5001,447,800

Nov 2020

1,439,0001,437,200

Dec 2020

1,433,4001,430,900

Jan 2021

1,415,0001,416,700

Feb 2021

1,404,2001,406,300

Mar 2021

1,400,5001,403,600

Apr 2021

1,382,2001,388,700

May 2021

1,375,0001,383,700

Jun 2021

1,371,1001,376,300

Jul 2021

1,371,0001,373,700

Aug 2021

1,365,3001,367,700

Sep 2021

1,349,8001,346,700

Oct 2021

1,359,1001,349,200

Nov 2021

1,350,9001,346,000

Dec 2021

1,345,7001,345,100

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

Answers to Some Recent Questions about BLS Data

I tell anyone who will listen that BLS staff love to talk about our data. We have LIVE people at the end of the phone line (or email request) who are happy to answer questions about BLS data and the methods behind those data. The COVID-19 pandemic has not stopped our ability to respond to public questions. Even in our telework posture, we pride ourselves on outstanding customer service. All BLS statistical programs have staff who answer public information requests. We also have a central information staff out of our national office and eight information offices scattered around the country. Yes, we get questions, and we are more than happy to provide answers.

Recently, we’ve received some general questions about our methods, which cover multiple BLS programs. Here are a few of those questions and our answers.

Why does BLS revise published estimates?

One of the hallmarks of BLS economic indicators is their prompt release. We provide a “first look” at a variety of economic conditions, including employment and unemployment, price change, wages, productivity, and more. To release these data in a timely manner, we follow very strict data collection and processing schedules. Data obtained after the collection deadline are not included in the initial release but can be incorporated later. We identify data subject to these revisions as preliminary. Revisions are a necessary part of the statistical estimation process to ensure accuracy.

The Producer Price Index (PPI) recently expanded the amount of revised data available to the public. PPI data are revised for 4 months following initial release, again to account for information received following the initial deadline, thus providing a clearer picture of price change. Until recently, revised data were only available in the fourth month. For example, July data originally published in August would be revised with the November release in December. The expanded data now available show monthly revisions for each of the 4 months following initial release. So, following the initial release of July data in August, revised data for July are available in September, October, and November, before we release final data in December. This change is in response to requests from data users for these interim values.

Other BLS programs release periodic revisions as updated data become available, providing a clearer view of the economy. For example, the Current Employment Statistics program has more information about the monthly revisions to payroll employment data. Details about the methods behind all BLS programs are available in the BLS Handbook of Methods.

Why is it important to respond to BLS surveys?

We carefully design our survey samples to represent the people and businesses in the United States. Without input from these sample members, BLS indicators would not accurately reflect the economic and social conditions in our country. We strive to make completing our surveys as easy as possible, and we often offer multiple ways to provide information. We design survey questions that are easy to understand and answer in a short period of time.

Nearly all of our surveys are voluntary, which means the people, households, and organizations selected can choose whether to participate. We are grateful that the great majority of them agree to participate. The information benefits all of us.

BLS maintains response rate information on our website and updates this information on a regular basis. This information can be very technical, which is why BLS staff stand ready to answer any questions you might have about response rates.

Check out this video to learn more about the importance of responding to BLS surveys.

What effect did the pandemic have on BLS survey participation?

With some careful planning, a lot of hard work, and a little bit of luck, BLS has been able to release all planned data products on schedule, despite the pandemic. We weathered both internal and external challenges. While many of our tasks had been successfully tested in remote environments, we had to change a few processes. Fortunately, those changed processes were successful, and some even spawned innovations we will continue. Externally, we were mindful that many businesses had limited operations or were closed, and many households were preoccupied with illness, childcare, and other responsibilities. Response rates did decline. Since the start of the pandemic, each BLS program has provided more information about survey response and methods. In some cases, response rates have recovered from their pandemic lows, but many are still below levels before the pandemic.

What steps has BLS introduced to combat weak survey response during the pandemic?

BLS takes many different approaches to data collection and works closely with our partners in the states and other statistical agencies to obtain high quality information from businesses and households. Traditionally, some data collection is done in person, where BLS builds a relationship with survey respondents and shows them the importance of response. BLS also offers many options designed to make ongoing response easy, including use of the internet, email, file transfer, and others. At the start of the pandemic, BLS suspended all in-person data collection. We were fortunate that many businesses, even many of those with limited operations during the pandemic, maintained electronic records they provided to BLS, allowing us to continue producing key economic data.

For our part, the pandemic provided an opportunity to accelerate our ongoing move away from paper and mail. We used phone and email to contact respondents and obtain their data. We also began to experiment with video data collection, a process that proved very successful and is now a vital part of our data collection toolkit. While we started slowly with video collection, and took particular care to ensure confidentiality, we quickly discovered huge benefits. BLS staff can use video communications systems to share their screen, demonstrate BLS confidentiality procedures, show data products, and more. In person, shuffling all these papers can be a little unwieldy. With a little practice and planning, video data collection has proved invaluable.

BLS also has explored ways of capturing information without burdening respondents at all. In some cases, we are able to use web scraping to obtain needed data. We are also exploring supplemental data sources, such as data aggregators and crowd sourcing websites. We have accelerated these explorations during the pandemic. We are learning a lot and obtaining more and more data through these alternative approaches, which can mitigate the effects of declining response rates on data quality. These efforts will ensure that BLS data products remain of high quality with enough detail for stakeholders, while lessening respondent burden.

We will return to some in-person data collection over time and will use those interactions to build ongoing relationships. But we also will continue to advance these innovations, such as video collection and web scraping, as options to make data collection more efficient in the future.

Spend Thanksgiving Day with BLS!

Thanksgiving is right around the corner. As we start to think about how we will celebrate, it might be hard to imagine the ties between BLS statistics and celebrating Thanksgiving. So, here’s a short tour of a typical Thanksgiving Day as seen through a few BLS statistics. Enjoy!

9:00 a.m. Put the turkey in the oven

All good chefs know the key to a successful Thanksgiving feast is to get the turkey in the oven bright and early. Whether you are roasting your turkey or firing up a deep fryer in the driveway, you will have to pay more for the fuel. The Consumer Price Index for household energy was pretty stable through 2019 and the first half of 2020 but then started a steady rise in September 2020.

Consumer Price Index for household energy, 2019–21

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

10:00 a.m. Watch the Macy’s Thanksgiving Day parade

The COVID-19 pandemic has caused ups and downs in the labor market, much like the impact of a windy day for the famous balloons in Macy’s Thanksgiving Day Parade. Keeping with the department store theme, employment in department stores plunged 25.3 percent in April 2020 but then rose 14.1 percent June 2020. These gyrations were more dramatic than the broader retail trade sector.

Monthly percent change in employment in retail trade and department stores, 2019–21

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

2:00 p.m. Scope out Black Friday deals

After watching the parade, it’s time to plan our Black Friday shopping! As consumers, we are always trying to get more for less. In the retail trade industry, it turns out they are doing just that. The industry has produced more output with steady or decreasing hours worked. The result is a corresponding increase in labor productivity. Now, only if we could prepare a bigger Thanksgiving feast in less time!

Indexes for labor productivity, hours worked, and output in retail trade, 2007–20

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

4:00 p.m. Play touch football

We need to make some room of the feast we are about to enjoy, so we assemble willing participants and play some touch football in the yard. The American Time Use Survey is the best source of information on how Americans spend their time each day. In this case, let’s compare how much time people spend playing sports versus how much time they spend watching sports on TV. We’ll look only at time spent in these activities on weekend days and holidays. The survey does not have details on what people watch on TV, but we can assume some time reported here is spent watching sports.

Average hours spent watching TV and playing sports, weekend days and holidays, 2019

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

We can see that Americans, on average, easily spend more time watching TV—3.36 hours—than playing sports—0.34 hours. But what is more interesting is that, on average, those who watch TV watch about 24 percent more than the overall population. However, those who play sports play, on average, nearly 6 times as many hours as the average for the population.

6:00 p.m. Thanksgiving feast

No matter what is on your dinner table this Thanksgiving, chances are it will cost more than previous years. All six major grocery store food groups in the Consumer Price Index for food at home continued to rise sharply in October 2021. Even if you decide to order out, it will set you back a bit more this year. Both full-service meals and limited services meals rose nearly 1 percent in October 2021.

Consumer Price Indexes for food at home and food away from home, 2018–21

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

7:00 p.m. Watch football

Now that we’ve finished our delicious feast, it’s a time-honored tradition to watch a bit of football on TV. If you are buying a new TV for this holiday, you can expect to pay a bit more. After years of steady declines, import prices for television and video receivers have reversed trend in 2021, much like a wide receiver changing direction to find an opening and catch a game-winning touchdown pass!

Import price index for television and video receivers, 2011–21

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

9:00 p.m. Say goodbye

It’s hard to say goodbye to your friends and family. In the United States, however, the Job Openings and Labor Turnover Survey is showing that workers are saying goodbye to their employers more often these days. The number of quits has been rising steadily since the shock of the pandemic affected layoffs and discharges in early 2020. (It’s only a coincidence that the layoffs line in the chart below looks like the outline of a pilgrim’s hat.)

Quits, layoffs and discharges, and other job separations, 2019–21

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

Now we’ve come to the end of our Thanksgiving feast of BLS data. Our hunger for the premier statistics on the U.S. labor force, prices, and productivity, has been satisfied, and we can rest easily knowing there’s a stat for that!

Consumer Price Index for household energy
MonthIndex

Jan 2019

100.000

Feb 2019

99.662

Mar 2019

100.046

Apr 2019

99.952

May 2019

99.679

Jun 2019

99.258

Jul 2019

99.415

Aug 2019

99.253

Sep 2019

99.033

Oct 2019

99.756

Nov 2019

99.890

Dec 2019

99.716

Jan 2020

99.666

Feb 2020

99.355

Mar 2020

98.812

Apr 2020

98.492

May 2020

98.278

Jun 2020

98.501

Jul 2020

98.542

Aug 2020

98.478

Sep 2020

99.590

Oct 2020

100.103

Nov 2020

101.043

Dec 2020

101.377

Jan 2021

101.299

Feb 2021

102.681

Mar 2021

103.436

Apr 2021

104.748

May 2021

105.512

Jun 2021

105.840

Jul 2021

106.664

Aug 2021

107.833

Sep 2021

109.273

Oct 2021

112.872
Monthly percent change in employment in retail trade and department stores
MonthRetail tradeDepartment stores

Jan 2019

-0.1%0.2%

Feb 2019

-0.2-1.4

Mar 2019

-0.1-0.6

Apr 2019

-0.1-0.9

May 2019

-0.1-0.5

Jun 2019

-0.1-0.7

Jul 2019

0.0-0.9

Aug 2019

-0.1-1.4

Sep 2019

0.10.3

Oct 2019

0.20.0

Nov 2019

-0.20.4

Dec 2019

0.3-0.4

Jan 2020

-0.1-2.7

Feb 2020

0.00.3

Mar 2020

-0.8-0.6

Apr 2020

-14.5-25.3

May 2020

3.16.7

Jun 2020

6.314.1

Jul 2020

1.74.3

Aug 2020

1.72.3

Sep 2020

0.2-0.8

Oct 2020

0.70.2

Nov 2020

0.00.7

Dec 2020

0.2-0.6

Jan 2021

0.1-0.3

Feb 2021

0.10.5

Mar 2021

0.30.1

Apr 2021

-0.10.2

May 2021

0.40.9

Jun 2021

0.61.3

Jul 2021

0.00.3

Aug 2021

0.1-0.5

Sep 2021

0.40.5

Oct 2021

0.2-0.2
Indexes for labor productivity, hours worked, and output in retail trade
YearLabor productivityHours workedOutput

2007

100.000100.000100.000

2008

97.76597.65895.475

2009

98.29492.03290.461

2010

100.69492.66793.310

2011

101.39794.68696.008

2012

103.65595.67399.170

2013

108.08095.212102.905

2014

109.91997.268106.916

2015

113.48698.821112.148

2016

118.52598.636116.908

2017

120.71999.896120.593

2018

124.39399.783124.123

2019

130.36098.139127.934

2020

140.39294.650132.880
Average hours spent watching TV and playing sports, weekend days and holidays, 2019
ActivityHours

Watching TV (average of population)

3.36

Watching TV (average of those who watched TV)

4.17

Playing sports (average of population)

0.34

Playing sports (average of those who played sports)

1.94
Consumer Price Indexes for food at home and food away from home
MonthFood at homeFood away from home

Jan 2018

100.000100.000

Feb 2018

99.793100.243

Mar 2018

99.780100.352

Apr 2018

100.026100.594

May 2018

99.779100.929

Jun 2018

99.865101.113

Jul 2018

100.127101.229

Aug 2018

100.198101.421

Sep 2018

100.252101.645

Oct 2018

100.046101.738

Nov 2018

100.259102.029

Dec 2018

100.554102.437

Jan 2019

100.683102.789

Feb 2019

101.014103.153

Mar 2019

101.163103.342

Apr 2019

100.716103.676

May 2019

100.913103.894

Jun 2019

100.718104.232

Jul 2019

100.716104.443

Aug 2019

100.654104.669

Sep 2019

100.902104.940

Oct 2019

101.124105.139

Nov 2019

101.324105.310

Dec 2019

101.331105.611

Jan 2020

101.440106.000

Feb 2020

101.851106.236

Mar 2020

102.220106.395

Apr 2020

104.775106.550

May 2020

105.718106.942

Jun 2020

106.309107.496

Jul 2020

105.343108.002

Aug 2020

105.322108.309

Sep 2020

105.051108.911

Oct 2020

105.177109.210

Nov 2020

105.012109.342

Dec 2020

105.335109.751

Jan 2021

105.203110.122

Feb 2021

105.474110.180

Mar 2021

105.587110.311

Apr 2021

106.047110.649

May 2021

106.423111.258

Jun 2021

107.309112.047

Jul 2021

108.031112.923

Aug 2021

108.431113.405

Sep 2021

109.779114.013

Oct 2021

110.841114.965
Import price index for television and video receivers
MonthIndex

Jan 2011

100.000

Feb 2011

100.173

Mar 2011

100.173

Apr 2011

99.136

May 2011

98.964

Jun 2011

97.409

Jul 2011

97.064

Aug 2011

96.373

Sep 2011

95.855

Oct 2011

94.991

Nov 2011

93.092

Dec 2011

94.128

Jan 2012

94.819

Feb 2012

94.473

Mar 2012

93.955

Apr 2012

92.573

May 2012

92.573

Jun 2012

92.401

Jul 2012

92.401

Aug 2012

92.573

Sep 2012

92.228

Oct 2012

92.573

Nov 2012

90.155

Dec 2012

90.155

Jan 2013

89.810

Feb 2013

89.637

Mar 2013

88.256

Apr 2013

88.083

May 2013

87.910

Jun 2013

87.910

Jul 2013

87.392

Aug 2013

87.219

Sep 2013

85.838

Oct 2013

85.492

Nov 2013

85.492

Dec 2013

85.492

Jan 2014

85.320

Feb 2014

85.320

Mar 2014

85.147

Apr 2014

84.801

May 2014

84.283

Jun 2014

84.111

Jul 2014

83.074

Aug 2014

82.902

Sep 2014

83.074

Oct 2014

81.865

Nov 2014

81.865

Dec 2014

81.347

Jan 2015

79.965

Feb 2015

79.965

Mar 2015

79.965

Apr 2015

79.965

May 2015

79.620

Jun 2015

79.620

Jul 2015

79.620

Aug 2015

79.620

Sep 2015

79.620

Oct 2015

79.447

Nov 2015

79.275

Dec 2015

78.929

Jan 2016

78.756

Feb 2016

77.547

Mar 2016

77.375

Apr 2016

77.029

May 2016

76.857

Jun 2016

77.029

Jul 2016

76.857

Aug 2016

76.684

Sep 2016

76.684

Oct 2016

76.684

Nov 2016

76.684

Dec 2016

76.684

Jan 2017

76.166

Feb 2017

76.166

Mar 2017

75.820

Apr 2017

75.993

May 2017

75.993

Jun 2017

75.993

Jul 2017

75.993

Aug 2017

75.993

Sep 2017

75.820

Oct 2017

75.475

Nov 2017

75.302

Dec 2017

75.130

Jan 2018

75.130

Feb 2018

75.302

Mar 2018

74.784

Apr 2018

74.439

May 2018

74.266

Jun 2018

73.575

Jul 2018

72.884

Aug 2018

72.884

Sep 2018

72.712

Oct 2018

72.539

Nov 2018

72.366

Dec 2018

72.021

Jan 2019

71.330

Feb 2019

70.812

Mar 2019

70.466

Apr 2019

70.466

May 2019

70.294

Jun 2019

69.948

Jul 2019

69.775

Aug 2019

69.603

Sep 2019

69.603

Oct 2019

69.430

Nov 2019

69.085

Dec 2019

68.912

Jan 2020

69.430

Feb 2020

68.048

Mar 2020

67.358

Apr 2020

66.839

May 2020

66.667

Jun 2020

66.667

Jul 2020

66.494

Aug 2020

66.494

Sep 2020

66.321

Oct 2020

66.667

Nov 2020

67.358

Dec 2020

68.048

Jan 2021

68.739

Feb 2021

68.739

Mar 2021

68.566

Apr 2021

69.775

May 2021

70.639

Jun 2021

70.812

Jul 2021

73.402

Aug 2021

73.402

Sep 2021

74.439

Oct 2021

74.784
Quits, layoffs and discharges, and other job separations
MonthQuitsLayoffs and dischargesOther separations

Jan 2019

3,521,0001,689,000301,000

Feb 2019

3,543,0001,769,000353,000

Mar 2019

3,524,0001,721,000331,000

Apr 2019

3,494,0001,954,000313,000

May 2019

3,487,0001,776,000307,000

Jun 2019

3,527,0001,771,000316,000

Jul 2019

3,627,0001,826,000344,000

Aug 2019

3,591,0001,825,000306,000

Sep 2019

3,449,0001,982,000345,000

Oct 2019

3,414,0001,793,000359,000

Nov 2019

3,482,0001,788,000374,000

Dec 2019

3,487,0001,952,000354,000

Jan 2020

3,568,0001,788,000358,000

Feb 2020

3,430,0001,953,000332,000

Mar 2020

2,902,00013,046,000360,000

Apr 2020

2,107,0009,307,000368,000

May 2020

2,206,0002,096,000316,000

Jun 2020

2,646,0002,204,000331,000

Jul 2020

3,182,0001,845,000365,000

Aug 2020

2,987,0001,573,000342,000

Sep 2020

3,307,0001,555,000373,000

Oct 2020

3,352,0001,728,000347,000

Nov 2020

3,296,0002,123,000325,000

Dec 2020

3,407,0001,823,000352,000

Jan 2021

3,306,0001,724,000294,000

Feb 2021

3,383,0001,723,000323,000

Mar 2021

3,568,0001,525,000343,000

Apr 2021

3,992,0001,450,000360,000

May 2021

3,630,0001,353,000347,000

Jun 2021

3,870,0001,354,000389,000

Jul 2021

4,028,0001,423,000341,000

Aug 2021

4,270,0001,385,000378,000

Sep 2021

4,434,0001,375,000410,000