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Tag Archives: Hours

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

Productivity Perspective of the 2020 COVID-19 Pandemic

Labor productivity, a key measure of the health of the U.S. economy, had been rising steadily but slowly throughout the 2010s—just over one percent per year on average. But what happens when the economy is thrown into a sudden decline by an unprecedented shock? COVID-19 landed in the United States in the early months of 2020, and it did not take long for its effects on productivity to hit hard and fast.

First, some background. Labor productivity is the ratio of real output to hours worked. Productivity increases when the output of goods and services increases faster than the amount of labor needed to produce the goods and provide the services. Productivity growth is often thought to show that businesses are becoming more efficient and profitable, but the path to positive productivity is not always desirable. Productivity may also increase when output falls but hours worked fall faster.

During 2020, two distinct paths yielded positive productivity growth. From the first quarter to the second quarter of 2020, hours worked decreased more than output. We can think of this path as businesses rapidly cutting hours and employment faster than output fell. Conversely, in the third quarter of 2020, the economy began to rebound, and the increase in demand for goods and services outpaced the rising labor hours, also resulting in positive labor productivity growth. (See chart 1).

When looking at the growth rates for output, hours worked, and productivity, we annualize the numbers, meaning these are the growth rates we would observe if the change in a quarter were to continue at that rate for an entire year. The data presented here are for the nonfarm business sector, covering about three-fourths of the U.S. economy, from the end of 2019 to the end of 2020. Although we report labor productivity measures quarterly, we incorporated higher frequency data to more accurately capture the rapid changes resulting from the COVID-19 pandemic.

Chart 1. Output, hours worked, and labor productivity, nonfarm business sector, fourth quarter 2019 to fourth quarter 2020

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

First Quarter 2020, Pandemic on the Horizon

Although the COVID-19 pandemic began during the first quarter of 2020, data from January and February were not significantly affected by the pandemic; business closures and job losses didn’t occur until the latter part of March. Since only one out of three months in the first quarter was affected, the decreases were modest compared to what was to come in the second quarter. Nevertheless, both output (-6.4 percent) and hours worked (-5.6 percent) declined in the first quarter, the first decreases since the second quarter of 2009. The declines in first quarter 2020 were an early sign of the drastic decreases we were about to see. While labor productivity declined only 0.8 percent at an annual rate in the first quarter, this was the first decline in labor productivity since the second quarter of 2017.

Second Quarter 2020, COVID-19 Rears Its Ugly Head

The second quarter of 2020 saw historically large decreases in both output and hours worked. Our measures of nonfarm business began in 1947, and the second quarter of 2020 had the largest declines ever recorded in both output (-36.8 percent) and hours worked (-43.2 percent). While the resulting labor productivity growth of 11.1 percent was the largest increase since the first quarter of 1971 (12.3 percent), the large increase in second quarter 2020 resulted from the devastation of the U.S. economy in terms of both employment and output.

How can productivity grow at near a record rate with such large declines in output and hours worked? Remember the different paths to positive labor productivity. Many consumers avoided stores, restaurants, and other public gatherings to reduce the risk of catching or spreading the virus that causes COVID-19. With shutdowns of nonessential businesses and limited contact and other restrictions for businesses still opened, businesses had to adapt quickly to reduce work hours while trying to preserve output. For example, many eating establishments focused on carryout and outdoor seating to limit their revenue loss. Additionally, online buying and home delivery became more widespread. The data from the second quarter show hours worked fell faster than output, resulting in productivity growth.

Third Quarter 2020, the Road to Recovery

By the third quarter of 2020, both output and hours worked began to climb again and in a big way. Many more businesses had shifted operations online or tried to bring workers back and resume normal operations. Following the historically large declines in the second quarter, we saw historically large increases in the third quarter in both output (44.1 percent) and hours worked (38.3 percent). With output recovering more quickly than hours worked, labor productivity grew by a robust 4.2 percent.

The automotive industry is one that highlights the jumpstart to recovery. In the second quarter, automotive production factories stopped almost entirely, resulting in output and hours worked plummeting. Once they started to reopen in the third quarter, both hours worked and output rebounded. While the third quarter outcome was positive, both output and hours worked still had not returned to their values before the pandemic, meaning much more work remained to fully recover. It is important to remember nonfarm employment at the end of the third quarter was still 10.7 million below the level at the start of the pandemic.

Fourth Quarter 2020, on the Right Track

The fourth quarter continued the large growth for both output (5.5 percent) and hours worked (10.1 percent). This quarter shows how negative productivity is not always a negative thing. In this case, hours worked outpaced output growth, leading to a productivity decline.

When we look over the past year, we see that we are digging out of the huge decline in the second quarter of 2020. The fourth quarter of 2020 was the second straight increase in both hours and output. In the fourth quarter of 2020, output was only 2.6 percent below the level a year earlier, and hours worked were 4.9 percent below. (See chart 2). After the labor productivity rollercoaster ride of 2020, the fourth quarter data suggest things may be on a path to normalcy.

Chart 2. Output and hours worked indexes, nonfarm business sector, fourth quarter 2019 to fourth quarter 2020

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

Pandemic in Perspective

So how does productivity in a pandemic compare with other major economic events like the Great Recession? From 2007 to 2009, both output and hours worked declined (see chart 3), as the U.S. economy endured a period known as the “Great Recession.” (To learn more, see “Below Trend: the U.S. productivity slowdown since the Great Recession.”) In 2020, both output and hours worked declined at the start of the pandemic. The wild changes from quarter to quarter during the rest of the year were unprecedented, even for an economic downturn. Over the past decade, the movements in output, hours, and productivity were usually small, making 2020 even more unusual.

The last time productivity growth was close to what it was in the second quarter of 2020 was in the second quarter of 2009. Labor productivity typically spikes at the start of an economic recovery because output rises faster than businesses can restore hours. In both the Great Recession and the 2020 pandemic, the magnitude of the changes in output and hours worked were larger than usual. In the Great Recession it took several quarters to see gains in hours worked, whereas 2020 saw a faster turnaround as businesses began to reopen and government restrictions eased in the third quarter. In fact, hours worked in the fourth quarter of 2020 grew faster than output, causing productivity to decline.

Chart 3. Output, hours, and  labor productivity indexes in the nonfarm business sector, 2007–20

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

BLS labor productivity data help us study efficiencies and the economic well-being of the country. Positive labor productivity isn’t always positive. The components that make up the labor productivity measure—output and hours worked—should not be examined alone but rather together to fully understand productivity’s effect on economic growth.

During unprecedented events like the COVID-19 pandemic, historical trends in productivity can provide important context into the economic environment. We at BLS, like many of you, will be very interested to see how the economy recovers and what that will mean for productivity and the economy.

Want to Learn More?

To dive into the data for yourself, check out the BLS webpages on labor productivity. Get the most recent news release to see the data firsthand! Check out Productivity 101 and our video “What is Productivity?” to learn more about the concepts of productivity.

If you have a specific question, you might find it answered in our Frequently Asked Questions. Or you can always contact our staff by email or call (202) 691-5606.

Chart 1. Output, hours worked, and labor productivity, nonfarm business sector, fourth quarter 2019 to fourth quarter 2020
QuarterOutputHours workedLabor productivity

Q4 2019

2.8%1.3%1.5%

Q1 2020

-6.4-5.6-0.8

Q2 2020

-36.8-43.211.1

Q3 2020

44.138.34.2

Q4 2020

5.510.1-4.2
Chart 2. Output and hours worked indexes, nonfarm business sector, fourth quarter 2019 to fourth quarter 2020
QuarterOutputHours worked

Q4 2019

100.000100.000

Q1 2020

98.36998.573

Q2 2020

87.69585.589

Q3 2020

96.08292.810

Q4 2020

97.36695.067
Chart 3. Output, hours, and labor productivity indexes in the nonfarm business sector, 2007–20
QuarterOutputHours workedLabor productivity

Q1 2007

100.000100.000100.000

Q2 2007

100.820100.442100.377

Q3 2007

101.464100.134101.329

Q4 2007

102.01599.802102.217

Q1 2008

100.88699.531101.361

Q2 2008

101.36398.944102.444

Q3 2008

100.50297.862102.698

Q4 2008

97.40995.434102.069

Q1 2009

95.79593.004103.002

Q2 2009

95.59290.900105.161

Q3 2009

95.93590.031106.559

Q4 2009

97.29689.843108.295

Q1 2010

97.75289.839108.808

Q2 2010

98.85190.689108.999

Q3 2010

99.94191.205109.579

Q4 2010

100.70891.521110.038

Q1 2011

100.16791.652109.291

Q2 2011

101.20292.496109.412

Q3 2011

101.20092.842109.001

Q4 2011

102.63893.537109.730

Q1 2012

103.84994.272110.158

Q2 2012

104.48394.492110.573

Q3 2012

104.72794.868110.392

Q4 2012

104.90595.356110.013

Q1 2013

105.96995.726110.700

Q2 2013

105.97696.095110.282

Q3 2013

107.03596.647110.748

Q4 2013

108.24296.967111.628

Q1 2014

107.72697.426110.573

Q2 2014

109.57298.110111.682

Q3 2014

111.31498.777112.692

Q4 2014

112.07099.904112.177

Q1 2015

113.326100.020113.302

Q2 2015

114.278100.471113.742

Q3 2015

114.683100.817113.753

Q4 2015

114.787101.306113.307

Q1 2016

115.503101.635113.645

Q2 2016

115.821102.017113.531

Q3 2016

116.522102.310113.891

Q4 2016

117.514102.419114.738

Q1 2017

118.213102.823114.966

Q2 2017

118.819103.599114.691

Q3 2017

119.944103.754115.605

Q4 2017

121.319104.488116.108

Q1 2018

122.600105.109116.642

Q2 2018

123.497105.680116.859

Q3 2018

124.208105.970117.211

Q4 2018

124.648106.228117.341

Q1 2019

125.823106.216118.459

Q2 2019

126.204106.032119.025

Q3 2019

127.104106.663119.165

Q4 2019

127.990107.000119.617

Q1 2020

125.902105.474119.369

Q2 2020

112.24191.580122.561

Q3 2020

122.97599.306123.833

Q4 2020

124.619101.722122.510

Why This Counts: Measuring Industry Productivity

At BLS, productivity is the economic statistic that describes the efficiency of production. The productivity statistics you hear about most often in the news are for the entire U.S. economy. But there’s more to the productivity story than just the overall numbers. The economy is made up of hundreds of industries, and each one works in a different way. Productivity data for each industry help us understand how specific types of production have changed over time. Let’s look at a few specific industries to see how labor productivity data can enhance our understanding of their unique production systems.

General Freight Trucking: Technological Innovations

Economic conditions in the general freight trucking industry closely mirror the health of the overall economy. During the 2007–09 recession, both output and hours worked fell dramatically in trucking. Because employment and spending were down nationwide, there was less demand for the transportation of all kinds of goods. After the recession ended, output and hours in trucking picked back up. Output reached prerecession levels by 2014, but in 2018 hours worked were still slightly below their 2007 level.

Dividing output by hours worked yields labor productivity. Because output in trucking has grown faster than hours during the recovery from the recession, labor productivity has increased. This helps us understand the nature of operations in general freight trucking. Innovative technologies such as communications systems, mapping software, and truck-based sensors and monitors known as “telematics” have improved transportation efficiency. These systems allow deliveries to be planned more efficiently with fewer delays, allowing more freight to be delivered without an equivalent increase in worker hours.

General freight trucking, average yearly percent change in output, hours worked, and productivity from 2007 to 2018

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

Travel Agencies: Digital Transformation

Another industry that has changed the way it operates is travel agencies. Since 2000, output has increased substantially, while hours fell from 2000 to 2010 and have increased only slightly since then. The major transformation for travel agencies has been the Internet. Online tools have allowed clients to make travel reservations with far less help from workers. This increase in efficiency is reflected in the industry’s labor productivity, which has more than tripled from 2000 to 2017.

Travel agencies, average yearly percent change in output, hours worked, and productivity from 2000 to 2017

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

Supermarkets: Incremental Change

Changes in other industries have been more subtle. Supermarkets are a particularly competitive industry, and firms employ a large number of workers to maintain high levels of customer service. Managing inventories, stocking shelves, checking out merchandise, and staffing specialty stations are all tasks that supermarkets continue to need. But even in supermarkets, productivity has been increasing since 2009, as output has grown faster than worker hours. To continue growing sales with lower costs, many firms in this industry have relied more on labor-saving technology, such as self-checkout machines. This technology increases efficiency by allowing supermarkets to process more transactions with less help from workers.

Supermarkets, average yearly percent change in output, hours worked, and productivity from 2009 to 2018

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

Cut and Sew Apparel Manufacturing: Establishment Turnover

Productivity declines also can show the changing nature of work. Cut and sew apparel manufacturing has seen much of its production move outside the United States. In 2018, U.S. apparel manufacturers produced less than 15 percent of the output they produced in 1997. Although worker hours also have declined, they have not dropped as much as output, leading to a decline in labor productivity. This indicates a shift over time in the nature of the average apparel manufacturer. While many large establishments moved overseas in search of cheaper labor, the remaining domestic apparel manufacturing establishments are on average smaller and more specialized, requiring more labor-intensive work.

Cut and sew apparel manufacturing, average yearly percent change in output, hours worked, and productivity from 1997 to 2018

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

To Learn More

BLS industry productivity data help us study the efficiencies of economic activities. Historical trends in productivity provide an important window into each industry’s working conditions, competitiveness, contribution to the economy, and potential for future growth. These data are used by investors, business leaders, jobseekers, researchers, and government decision makers. We have annual labor productivity measures for over 275 detailed industries.

To dive into the data for yourself, check out the BLS webpages on labor productivity. You also can see productivity data in a brand new way using our industry productivity viewer! Even more specialized industry data are on our webpages for hospitals, construction industries, elementary and secondary schools, and urban transit systems. We also have a recent article on productivity in grocery stores.

Average yearly percent change in output, hours worked, and productivity in selected industries
IndustryOutputHours workedProductivity

General freight trucking, 2007 to 2018

1.0%-0.1%1.2%

Travel agencies, 2000 to 2017

4.8-3.08.1

Supermarkets, 2009 to 2018

1.90.71.2

Cut and sew apparel manufacturing, 1997 to 2018

-9.4-7.5-2.1