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Tag Archives: Recession

A Labor Day Look at How American Workers Have Changed over 40 Years

Forty years ago, teenagers ages 16 to 19 made up 8 percent of all U.S. workers. By 2019, that share fell to just 3 percent. With fewer teenagers working, the face of American labor looks much different today than it did when the Bee Gees ruled the American pop charts.

Happy Labor Day! The U.S. workforce has been changing over many generations. It’s been changing with respect to the work people do. For example, an increasing share of workers is engaged in service or technology work, while a decreasing share is engaged in factory or farm work. My focus today, however, is on the people who do the work.

Here at BLS, we spend a great deal of time and effort measuring and reporting on employment. How many jobs are there this month? What kind of jobs? But as Labor Day approaches, I’d like to shift the focus away from employment and jobs and toward labor itself. Who are the people holding down the jobs that we count? What is the face of American labor? And how has labor’s profile changed—and yes, it has changed—over a generation or more?

So today I’m not going to say much about what jobs workers hold or what their jobs pay. Instead, I’ll focus on more personal characteristics of the people who hold the jobs—characteristics that are not a function of workers’ jobs, but that are intrinsic to the workers themselves. Is America’s employed population getting older or younger? Are African Americans, Hispanics and Latinos, Asians, and other groups making up an increasing share of employment? And so forth. Call it the “composition” of America’s employed population. To examine this, I’ll be using data from the Current Population Survey, or CPS, which is a large, monthly survey of many thousands of U.S. households.

BLS collects data directly from lots of employers, such as businesses and state and local governments. This data collection is behind our monthly news release about how many jobs were added or lost in the U.S. economy. It gives us a vital, current, and accurate picture of work in America—but not of workers.

To learn more about workers, rather than about just their jobs, we can’t ask their employers. We have to ask workers themselves. BLS partners with the U.S. Census Bureau each month to survey some 60,000 U.S. households about their work and other topics. We can learn at least three important things by surveying workers that we can’t learn by surveying employers. First, we can learn about things like self-employment, multiple jobholding, and “alternative” work arrangements, like so-called “gig” work. Second, we can learn about people who are not currently employed. In fact, BLS uses these data each month to measure how many are “unemployed,” roughly meaning they are actively looking for a job and available to start. Third, and most relevant here, we can learn about people’s personal characteristics—things like their age, race, and marital status, which their employers might not know or might find hard to detail in a BLS survey.

Let’s look at data from the CPS to explore how the personal characteristics of America’s employed population have shifted. I’ll share some of my own favorite nuggets of information, which I think you’ll find interesting. I’ll mostly compare 1979 with 2019—a 40-year span that roughly coincides with two peaks in U.S. employment and economic activity. The comparisons would look similar if we looked at 2020 or today, but I think the long-term trends are better understood “peak to peak” than in comparison to the more recent but very unusual COVID-19 economy. Along the way I’ll link to some BLS resources that go deeper into these topics. Let’s dive in!

Where have the teenagers gone? In 1979, 8 percent of U.S. workers were ages 16 to 19. By 2019, just 3 percent were. Over the same 40-year period, the share that were ages 16 to 24 fell from 23 percent to 12 percent. Two things happened. First, the age composition of the entire population shifted. In 1979, the tail end of the large, post-World War II “baby boom” generation was about 16 years old. The generation that came after this group was smaller, so its share of the workforce was smaller too. Second, young people’s “participation rate”—the share that were working or seeking work—declined. In fact, that rate peaked at 58 percent in 1979, then fell to 34 percent by 2011. This huge change coincided with increases in school enrollment and educational attainment. This example illustrates how two forces combine to reshape the face of American labor: the shifting composition of the working age population, and shifts in participation rates of different groups.

The American workforce has aged. Between 1979 and 2019, the fraction of the employed population that is 65 years old or older grew from 3 percent to 7 percent. The share that is 55 or older grew from 15 percent to 24 percent. Forces behind this trend include the aging of baby boomers (they are mostly 60 or older today), medical and other advances that have extended lives and health, and less physically strenuous jobs. The participation rate story is a little more complicated: As a group, today’s older women always were more likely to work for pay than their mothers or grandmothers were. Participation among older men, in contrast, first ebbed and then rebounded across these 40 years.

Percent of employed people by age, 1979–2019 annual averages

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

There are more working women. By 1979, women’s share of the employed population, at 42 percent, had already been growing for some time; it was up from just 28 percent in 1948. It kept growing for about 20 more years, before leveling off at around 47 percent by 2000 and remaining there through 2019.

What’s love got to do with it? Between 1979 and 2019, the trend in marital status was more pronounced than the trend in gender. The fraction of all workers who were unmarried grew from 36 percent to 48 percent. This trend was sharper among men (31 percent to 45 percent) than women (44 percent to 51 percent).

Percent of employed people by sex and marital status, 1979 and 2019 annual averages

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

Racial and ethnic diversity is changing too. The U.S. population has long been very diverse, shaped by colonization, slavery and emancipation, and migration. Over the last 40 years, workforce diversity has been shaped mostly by immigration and by differences in fertility among racial and ethnic groups. Between 1979 and 2019 the non-White fraction of all U.S. workers grew from 12 percent to 22 percent. The fraction who are Hispanic or Latino (who may be of any race) grew from 5 percent to 18 percent. A note of caution: the survey questions about race and ethnicity changed over the years, and this might skew the measurements a little, but not enough to change the story that non-Whites and Hispanics and Latinos represent a growing share of employed people. The latest survey questions provide lots of detail about diversity today.

Percent of employed people by race and Hispanic or Latino ethnicity, 1979 and 2019 annual averages

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

The more you survey, the more you know. Changes in the CPS and other surveys affect more than just our measures of labor diversity. Of course, we can’t measure everything all the time. Big household surveys can be expensive for taxpayers and burdensome for the thousands of households who answer the long questionnaires. Over time, we may change how we think about who we are and what we do, so survey questions must change as well. New survey questions can inform us better about where we are today, but they can make it harder to compare conditions over time. For example, beginning in 1992, the CPS questions about educational attainment were changed to emphasize degrees earned rather than years of school completed. We know that the fraction of U.S. workers age 25 or older who had a bachelor’s degree or higher grew from 27 percent in 1992 to 42 percent in 2019, but we don’t know for sure what percentage of the workforce was this educated in 1979.

The CPS has its roots in a tough time for American labor. The Great Depression of the 1930s brought mass unemployment to the United States. Back then, there was no sure way to measure the problem or track progress toward recovery. By the end of the 1930s, the U.S. launched the monthly household survey that today we call the CPS. The survey has gone through many changes, but it has measured unemployment each month since then. For economists like me, the history of the CPS is almost as interesting as the history of American labor. If you happen to be an economist or statistician yourself, BLS and the U.S. Census Bureau can tell you all you need to know about this great source of information. But not today – it’s Labor Day! Save the technical stuff for after the celebration.

Percent of employed people by age, 1979–2019 annual averages
YearAges 16–19Ages 20–24Ages 25–54Ages 55–64Age 65 and older

1979

8.2%14.5%62.6%11.7%3.0%

1980

7.814.263.411.73.0

1981

7.214.164.311.52.9

1982

6.613.865.311.52.9

1983

6.313.666.011.22.9

1984

6.113.566.810.92.7

1985

6.013.067.610.72.6

1986

5.912.668.410.42.7

1987

5.912.069.210.22.7

1988

5.911.569.89.92.8

1989

5.811.070.59.82.9

1990

5.511.370.99.42.8

1991

5.011.071.89.32.8

1992

4.810.972.39.32.8

1993

4.810.772.59.22.8

1994

5.010.472.59.13.0

1995

5.110.072.89.22.9

1996

5.19.673.19.32.9

1997

5.19.672.99.52.9

1998

5.49.672.59.82.8

1999

5.49.772.110.02.9

2000

5.39.771.810.23.1

2001

4.99.771.510.73.1

2002

4.69.870.911.53.2

2003

4.39.870.612.13.3

2004

4.29.970.012.43.5

2005

4.29.769.512.93.6

2006

4.39.669.013.43.7

2007

4.09.668.813.83.8

2008

3.89.468.414.34.1

2009

3.59.168.015.04.4

2010

3.19.167.715.64.5

2011

3.19.367.015.94.8

2012

3.19.466.116.35.1

2013

3.19.465.616.55.3

2014

3.19.565.316.75.4

2015

3.29.464.916.85.7

2016

3.39.364.716.95.9

2017

3.39.264.517.06.0

2018

3.39.064.417.16.2

2019

3.39.064.117.16.6

2020

3.28.564.517.26.6
Percent of employed people by sex and marital status, 1979 and 2019 annual averages
Marital status1979, total2019, total1979, men2019, men1979, women2019, women

Married, spouse present

63.6%52.3%69.0%55.0%56.1%49.1%

Never married

24.132.323.332.625.231.9

Widowed, divorced, and separated

12.315.57.712.318.719.0
Percent of employed people by race and Hispanic or Latino ethnicity, 1979 and 2019 annual averages
YearWhiteNot WhiteHispanic or Latino

1979

88.3%11.7%4.8%

2019

77.722.317.6

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

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

Let’s Celebrate the Productive U.S. Workforce

Earlier this month our nation celebrated Labor Day. We celebrate Labor Day for many good reasons, but one of the best is to appreciate, even for just one day, how amazingly productive our nation’s workforce is. As we shop online or in stores, we rarely stop to think about the skills and effort it takes to produce our goods and services. Let’s take a moment to celebrate that productivity and the progress we have seen in the last few years.

Indeed, productivity of labor is at the heart of the American economy. How much workers produce for each hour they labor and how efficiently they use resources determines the pace of economic growth and the volume of goods that supply everyone (workers included) with the products and services that shape our daily lives. Growing productivity means that our standard of living very likely is improving.

Our workers are very productive. On average, each U.S. worker produced goods and services worth $129,755 last year. That’s compared with the next largest world economies: Germany at $99,377; the United Kingdom at $93,226; Japan at $78,615; China at $32,553; and India at $19,555.

Despite our great reliance on rising productivity to attain the good things of life, academics and researchers still marvel at the mysteries that surround the subject. What drives productivity change? What are the key factors behind these international differences in output per worker?

For example, does the quality of labor alone determine the rate of productivity growth? It is certainly a component of what drives labor productivity, although some countries have high educational and training levels but low productivity per worker. Labor quality has been steadily rising in the United States, but we don’t know the impact on productivity as the baby boomers retire and are replaced.

What is the right mix of labor and technology needed for changing the productivity growth rate? How can we measure the value of the dignity of work, or the personal and social value that work yields? And, what is the role of technical knowledge and product design in determining the productivity of labor?

Then there’s the mysterious role of innovation. Economists think they know that invention and scientific breakthroughs can make massive changes to productivity. However, which innovations transform productivity, and have all the low-lying fruits of productivity enhancement already been harvested?

Despite our strong international showing, analysts who watch these data may be a tad bit concerned with the sluggishness in U.S. productivity growth over the past 10 years. Since 2011, the rate of growth in labor productivity has slowed to one-third of the pace shown between 2000 and 2008, despite acceleration in the past 2 years. Even when we broaden the concept of productivity to include the output attributable to the combination of labor and other productive factors (also known as multifactor productivity), the rate of growth is still one-third of the pace it was in the first decade of this century.

Even with a subsidence in the growth rate, it is worth noting that both labor input and output are on the rise. Since the start of the current business cycle expansion in 2009, the rate of growth in labor input has been five times what it was prior to the Great Recession during the previous expansion.

Output has also grown steadily, but at a slower rate than hours. Because labor productivity is the quotient of output divided by hours, productivity can slow even when both components are rising. The relationship between the relative growth of output and hours is one of the many features that makes productivity both challenging and fascinating to study.

The Bureau of Labor Statistics engages with an extensive network of researchers in and out of the academic community whose mission is, like ours, to better understand and measure the productivity of the U.S. labor force. Labor productivity is an amazing subject because it incorporates so many facets of the nation’s economy into one statistic. By peeling back layers and looking at the details behind the summary number, we can gain valuable insight on the hours and output of our nation’s workforce. We will continue to produce and provide context for these valuable statistics that help tell the story of America’s workers.

That said, we should never lose sight of the big picture. America’s workers lead the world in their capacity to create the goods and services that define our economy and improve our lives. And that, certainly, is something great to celebrate!

Labor Day 2019 Fast Facts

I have been Commissioner of Labor Statistics for 5 months now, and I continue to be amazed by the range and quality of data we publish about the U.S. labor market and the well-being of American workers. As we like to say at BLS, we really do have a stat for that! We won’t rest on what we have done, however. We continue to strive for more data and better data to help workers, jobseekers, students, businesses, and policymakers make informed decisions. Labor Day is a good time to reflect on where we are. This year is the 125th anniversary of celebrating Labor Day as a national holiday. Before you set out to enjoy the long holiday weekend, take a moment to look at some fast facts we’ve compiled on the current picture of our labor market.

Working

Working or Looking for Work

  • The civilian labor force participation rate—the share of the population working or looking for work—was 63.0 percent in July 2019. The rate had trended down from the 2000s through the early 2010s, but it has remained fairly steady since 2014.

Not Working

  • The unemployment rate was 3.7 percent in July. In April and May, the rate hit its lowest point, 3.6 percent, since 1969.
  • In July, there were 1.2 million long-term unemployed (those jobless for 27 weeks or more). This represented 19.2 percent of the unemployed, down from a peak of 45.5 percent in April 2010 but still above the 16-percent share in late 2006.
  • Among the major worker groups, the unemployment rate for teenagers was 12.8 percent in July 2019, while the rates were 3.4 percent for both adult women and adult men. The unemployment rate was 6.0 percent for Blacks or African Americans, 4.5 percent for Hispanics or Latinos, 2.8 percent for Asians, and 3.3 percent for Whites.

Job Openings

Pay and Benefits

  • Average weekly earnings rose by 2.6 percent from July 2018 to July 2019. After adjusting for inflation in consumer prices, real average weekly earnings were up 0.8 percent during this period.
  • Civilian compensation (wage and benefit) costs increased 2.7 percent in June 2019 from a year earlier. After adjusting for inflation, real compensation costs rose 1.1 percent over the year.
  • Paid leave benefits are available to most private industry workers. The access rates in March 2018 were 71 percent for sick leave, 77 percent for vacation, and 78 percent for holidays.
  • About 91 percent of civilian workers with access to paid holidays receive Labor Day as a paid holiday.
  • In March 2018, civilian workers with employer-provided medical plans paid 20 percent of the cost of medical care premiums for single coverage and 32 percent for family coverage.

Productivity

  • Labor productivity—output per hour worked—in the U.S. nonfarm business sector grew 1.8 percent from the second quarter of 2018 to the second quarter of 2019.
  • Some industries had much faster growth in 2018, including electronic shopping and mail-order houses (10.6 percent) and wireless telecommunications carriers (10.1 percent).
  • Multifactor productivity in the private nonfarm business sector rose 1.0 percent in 2018. That growth is 0.2 percentage point higher than the average annual rate of 0.8 percent from 1987 to 2018.

Safety and Health

Unionization

  • The union membership rate—the percent of wage and salary workers who were members of unions—was 10.5 percent in 2018, down by 0.2 percentage point from 2017. In 1983, the first year for which comparable union data are available, the union membership rate was 20.1 percent.

Work Stoppages

  • In the first 7 months of 2019, there have been 307,500 workers involved in major work stoppages that began this year. (Major work stoppages are strikes or lockouts that involve 1,000 or more workers and last one full shift or longer.) For all of 2018, there were 485,200 workers involved in major work stoppages, the largest number since 1986, when about 533,100 workers were involved.
  • There have been 15 work stoppages beginning in 2019. For all of 2018, 20 work stoppages began during the year.

Education

  • Occupations that typically require a bachelor’s degree for entry made up 22 percent of employment in 2018. This educational category includes registered nurses, teachers at the kindergarten through secondary levels, and many management, business and financial operations, computer, and engineering occupations.
  • For 18 of the 30 occupations projected to grow the fastest between 2016 and 2026, some postsecondary education is typically required for entry. Be sure to check out our updated employment projections, covering 2018 to 2028, that we will publish September 4!

From an American worker’s first job to retirement and everything in between, BLS has a stat for that! Want to learn more? Follow us on Twitter @BLS_gov.