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: Industries

Celebrating Women’s History Month with BLS Data

The U.S. Congress passed Public Law 100-9 on March 12, 1987, designating March as Women’s History Month. Beginning in 1995, each President has issued annual proclamations designating March as Women’s History Month.

Public Law 100-9 states in part:

“Whereas American women have played and continue to play a critical economic, cultural, and social role in every sphere of our Nation’s life by constituting a significant portion of the labor force working in and outside of the home;”

We at BLS have a lot to say about the critical role women have played in the economic health of our nation, especially their role in the labor market.

Let’s begin with the theme of this year’s Women’s History Month, “Providing healing and promoting hope.” This theme is especially relevant today as women serve on the front lines of the world’s battle against the COVID-19 pandemic. But women have been providing healing and promoting hope since time immemorial. BLS doesn’t have data going back that far, but we have interesting data on women employed in the health care and social assistance industry that highlight the critical importance of women in maintaining the health of our nation.

Women made up 77.6 percent of health care and social assistance employment

In 2021, 16.4 million women were employed in the health care and social assistance industry. This was 77.6 percent of the total 21.2 million workers in the industry. Looking at the component industries that make up health care and social assistance, women accounted for 75.0 percent of total employment in hospitals, 77.4 percent of total employment in health services, except hospitals, and 84.0 percent of total employment in social assistance. Social assistance includes child day care services, vocational rehabilitation services, and services for the elderly and disabled, among other industries.

Women employed in health care and social assistance, 2011 to 2021

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

Women providing care to household members

The excerpt from Public Law 100-9 I shared earlier mentioned activity both inside and outside the home. Data from the American Time Use Survey can shed light on the many ways women provide healing and promote hope, even when it is not directly related to their paid employment.

From May to December 2020, 84.5 percent of women engaged in household activities on a given day. Women who engaged in household activities spent an average of 2.77 hours per day on them as their primary activity.

Almost 25 percent of women also cared for and helped household members on a given day. These women averaged 2.41 hours per day caring for a household member as their primary activity.

Among women who were mothers, the time they spent caring for and helping household members varied depending on the age of the children and the employment status of the parent. Women of all marital and employment statuses averaged 2.1 hours per day caring for household members if their youngest child was under age 18 and 3.25 hours a day if their youngest child was under age 6. The averages were higher if women were not employed: 2.95 hours per day for women with children under age 18 and 3.88 hours for women with children under age 6.

Average hours per day mothers with children in the household spent caring for and helping household members, May to December 2020

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

The COVID-19 pandemic may have had several effects. Mothers of children under age 13 who were employed spent 7.3 hours per day during the pandemic in 2020 providing secondary childcare. Secondary childcare is when parents had at least one child under age 13 in their care while doing activities other than primary childcare. This was up by 1.5 hours per day from 2019. Employed fathers spent about 1 hour more per day providing secondary childcare in 2020 than in 2019.

Mothers and fathers of children under 13 who were not employed spent more time providing secondary childcare than those who were employed. Mothers who were not employed spent 8.7 hours per day providing secondary childcare, and fathers who were not employed spent 8.3 hours in 2020. Both figures are essentially unchanged from 2019.

Average hours per day spent providing secondary childcare, mothers and fathers of children under age 13, May to December, 2019 and 2020

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

This March, we are happy once again to celebrate the women who have made an impact both in the workforce and at home. Now more than ever, the world has come to count on women as healers and caregivers. On behalf of everyone at BLS, I am grateful for all the women who continue this crucial work. Not just this month, but every month.

Women employed in health care and social assistance, 2011 to 2021
YearTotal employedWomen employedPercent of total employed that are women

2011

18,902,00014,836,00078.5%

2012

19,405,00015,209,00078.4

2013

19,562,00015,343,00078.4

2014

19,577,00015,379,00078.6

2015

20,077,00015,752,00078.5

2016

20,589,00016,212,00078.7

2017

20,720,00016,271,00078.5

2018

21,133,00016,558,00078.4

2019

21,701,00016,959,00078.1

2020

20,736,00016,141,00077.8

2021

21,204,00016,446,00077.6
Average hours per day mothers with children in the household spent caring for and helping household members, May to December 2020
Employment statusYoungest child under age 18Youngest child under age 6

Total

2.103.25

Not employed

2.953.88

Employed

1.642.81

Employed full time

1.472.65

Employed part time

2.123.18
Average hours per day spent providing secondary childcare, mothers and fathers of children under age 13, May to December, 2019 and 2020
YearEmployed fathersEmployed mothersNot employed fathersNot employed mothers

2019

4.295.788.298.76

2020

5.247.258.328.66

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

Celebrating African American History Month

In honor of African American History Month, we’d like to highlight some employment statistics about Black or African American men and women.

Historically, the employment–population ratio for Black men has been considerably lower than the rate for men overall. For example, 60.0 percent of Black men were employed in January 2022, 5.1 percentage points lower than the employment–population ratio for men overall. By contrast, the employment–population ratios for Black women and for women overall have historically been much closer. In January 2022, the ratio for Black women was 55.7 percent, 1.1 percentage points higher than the ratio for women overall.

At the start of the COVID-19 pandemic, the employment–population ratio for Black men fell by 10.2 percentage points between February 2020 and April 2020 to 50.4 percent. This was the lowest in the history of the data, going back to 1972. Over the same period, the ratio for men overall fell by a slightly smaller amount—9.6 percentage points—to 57.2 percent. However, between April 2020 and January 2022, the ratio for Black men has risen by 9.6 percentage points, while the ratio for men overall has risen by a smaller amount, 7.9 percentage points.

Between February 2020 and April 2020, the employment–population ratio for Black women fell by 11.0 percentage points, a greater decline than the 10.1 percentage points for women overall. Since April 2020, the measure for Black women has risen less than that for women overall (8.3 percentage points versus 8.8 percentage points).

Employment–population ratios of Blacks or African Americans and the total population by sex, January 1972–January 2022, seasonally adjusted

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

The disparity in the recovery of the employment–population ratio between men and women may partially reflect the industries in which they are employed.

In 2021, 14.9 percent of employed Black men worked in transportation and utilities, a larger share than for men overall (8.7 percent). Within transportation and utilities, Black men were particularly likely to work in couriers and messengers and in warehousing and storage; these industries have fully recovered the jobs they lost between February 2020 and April 2020 and have continued to add jobs.

Percent distribution of employed Blacks or African Americans and the total workforce by selected  industry and sex, 2021 annual averages

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

In 2021, 40.1 percent of employed Black women worked in education and health services, a larger share than for women overall (36.0 percent). Employment in the education and health services industry is still 2.6 percent below its February 2020 level. Within this broad industry, Black women were especially likely to work in nursing and residential care facilities, where employment is 12.1 percent below its level before the pandemic.

We have more information about the labor force characteristics of Black men and women on our labor force demographics page.

This is just a sample of the information available on the labor force status of African Americans. Explore for yourself some of our other resources to expand your knowledge.

Employment–population ratios of Blacks or African Americans and the total population by sex, January 1972–January 2022, seasonally adjusted
MonthTotal menTotal womenBlack menBlack women

Jan 1972

74.6%40.8%65.1%43.1%

Feb 1972

74.640.865.742.9

Mar 1972

74.941.066.742.9

Apr 1972

74.940.967.143.0

May 1972

74.941.067.043.2

Jun 1972

75.140.968.542.9

Jul 1972

75.140.966.842.6

Aug 1972

75.341.067.242.4

Sep 1972

75.140.966.842.7

Oct 1972

75.040.966.642.3

Nov 1972

75.141.166.843.7

Dec 1972

75.441.367.243.9

Jan 1973

75.141.066.743.1

Feb 1973

75.441.667.843.8

Mar 1973

75.741.768.043.8

Apr 1973

75.541.967.543.5

May 1973

75.342.167.043.3

Jun 1973

75.642.367.143.1

Jul 1973

75.742.167.444.5

Aug 1973

75.442.167.444.4

Sep 1973

75.442.267.243.9

Oct 1973

75.742.468.044.4

Nov 1973

75.842.667.944.2

Dec 1973

75.842.568.344.0

Jan 1974

76.042.368.644.0

Feb 1974

75.842.667.643.9

Mar 1974

75.542.767.042.9

Apr 1974

75.142.766.643.7

May 1974

75.342.666.643.9

Jun 1974

75.042.765.743.8

Jul 1974

74.843.065.643.6

Aug 1974

74.742.865.243.9

Sep 1974

74.642.764.844.3

Oct 1974

74.442.665.343.5

Nov 1974

74.142.364.142.3

Dec 1974

73.442.163.042.0

Jan 1975

72.642.062.141.8

Feb 1975

72.241.761.441.4

Mar 1975

71.941.760.641.6

Apr 1975

71.641.859.741.4

May 1975

71.741.960.441.5

Jun 1975

71.341.960.142.0

Jul 1975

71.742.160.841.7

Aug 1975

71.842.260.741.4

Sep 1975

71.642.260.741.4

Oct 1975

71.542.360.241.6

Nov 1975

71.442.260.141.8

Dec 1975

71.442.459.742.1

Jan 1976

71.842.760.242.6

Feb 1976

71.942.860.142.6

Mar 1976

71.943.060.043.8

Apr 1976

72.243.160.943.4

May 1976

72.243.460.943.1

Jun 1976

71.843.359.942.8

Jul 1976

72.143.560.542.4

Aug 1976

72.343.361.142.5

Sep 1976

72.143.260.842.3

Oct 1976

72.143.260.642.2

Nov 1976

72.043.660.943.3

Dec 1976

72.043.661.242.7

Jan 1977

72.143.661.542.5

Feb 1977

72.243.861.842.5

Mar 1977

72.344.061.742.8

Apr 1977

72.644.262.343.1

May 1977

72.644.660.943.7

Jun 1977

72.844.462.043.3

Jul 1977

72.844.461.142.9

Aug 1977

72.944.660.843.5

Sep 1977

72.844.860.343.8

Oct 1977

73.244.860.643.5

Nov 1977

73.545.161.643.3

Dec 1977

73.645.362.645.0

Jan 1978

73.545.562.544.8

Feb 1978

73.445.762.845.4

Mar 1978

73.345.863.345.4

Apr 1978

73.646.263.245.6

May 1978

73.846.363.345.7

Jun 1978

74.146.563.546.1

Jul 1978

73.846.363.745.3

Aug 1978

73.946.462.646.6

Sep 1978

73.746.763.646.7

Oct 1978

73.847.063.846.5

Nov 1978

74.147.063.546.0

Dec 1978

73.947.163.546.0

Jan 1979

74.247.163.245.8

Feb 1979

74.347.363.145.8

Mar 1979

74.047.563.246.6

Apr 1979

73.947.162.945.9

May 1979

73.847.263.445.4

Jun 1979

74.047.263.845.8

Jul 1979

73.947.563.946.3

Aug 1979

73.747.364.245.3

Sep 1979

73.947.664.445.9

Oct 1979

73.547.763.746.4

Nov 1979

73.447.962.946.5

Dec 1979

73.548.062.646.6

Jan 1980

73.348.061.946.4

Feb 1980

73.447.961.646.3

Mar 1980

73.047.861.345.8

Apr 1980

72.347.760.945.6

May 1980

71.947.660.345.7

Jun 1980

71.547.559.845.4

Jul 1980

71.447.559.945.7

Aug 1980

71.447.559.746.0

Sep 1980

71.447.659.545.7

Oct 1980

71.647.660.045.4

Nov 1980

71.647.760.145.3

Dec 1980

71.747.659.945.2

Jan 1981

71.747.860.345.7

Feb 1981

71.648.059.845.2

Mar 1981

71.848.160.245.2

Apr 1981

72.148.360.346.3

May 1981

71.948.460.545.2

Jun 1981

71.148.158.445.1

Jul 1981

71.548.158.745.0

Aug 1981

71.448.158.244.3

Sep 1981

71.147.558.944.6

Oct 1981

70.847.958.445.0

Nov 1981

70.547.957.545.6

Dec 1981

70.047.657.544.9

Jan 1982

69.947.757.145.2

Feb 1982

69.947.757.244.5

Mar 1982

69.647.756.844.2

Apr 1982

69.547.656.643.7

May 1982

69.747.856.444.0

Jun 1982

68.947.855.544.2

Jul 1982

68.847.856.144.0

Aug 1982

68.847.856.044.3

Sep 1982

68.647.855.144.4

Oct 1982

68.447.555.044.0

Nov 1982

68.247.555.543.8

Dec 1982

68.047.554.644.1

Jan 1983

67.947.555.043.8

Feb 1983

67.847.555.344.5

Mar 1983

67.847.555.444.0

Apr 1983

68.047.655.243.8

May 1983

68.147.555.044.1

Jun 1983

69.047.756.143.7

Jul 1983

69.248.056.744.4

Aug 1983

69.248.456.244.3

Sep 1983

69.348.756.844.8

Oct 1983

69.448.557.143.9

Nov 1983

69.948.758.044.1

Dec 1983

69.948.858.044.1

Jan 1984

70.048.758.144.4

Feb 1984

70.349.059.445.7

Mar 1984

70.349.058.545.6

Apr 1984

70.449.357.846.1

May 1984

70.749.959.346.4

Jun 1984

71.249.758.847.3

Jul 1984

70.849.858.446.9

Aug 1984

70.749.559.547.4

Sep 1984

70.949.659.847.5

Oct 1984

70.949.660.247.3

Nov 1984

71.049.760.647.9

Dec 1984

71.049.960.048.0

Jan 1985

70.950.159.848.4

Feb 1985

70.850.359.647.5

Mar 1985

71.050.559.648.2

Apr 1985

71.050.459.748.5

May 1985

71.150.259.948.0

Jun 1985

70.650.160.148.6

Jul 1985

70.750.259.947.9

Aug 1985

70.950.260.947.8

Sep 1985

71.050.660.347.7

Oct 1985

71.050.759.948.1

Nov 1985

71.050.859.448.0

Dec 1985

71.050.960.148.6

Jan 1986

71.350.960.748.5

Feb 1986

70.950.860.548.5

Mar 1986

70.951.061.048.9

Apr 1986

70.951.060.949.2

May 1986

70.851.261.549.1

Jun 1986

70.951.561.048.9

Jul 1986

70.951.660.648.7

Aug 1986

70.951.759.448.2

Sep 1986

70.951.759.948.8

Oct 1986

70.951.860.349.2

Nov 1986

71.151.760.549.0

Dec 1986

71.251.761.248.7

Jan 1987

71.351.761.248.8

Feb 1987

71.351.961.549.4

Mar 1987

71.252.161.649.2

Apr 1987

71.352.361.649.5

May 1987

71.552.661.349.9

Jun 1987

71.352.561.750.2

Jul 1987

71.452.762.250.7

Aug 1987

71.652.962.951.3

Sep 1987

71.652.662.450.5

Oct 1987

71.752.862.651.5

Nov 1987

71.752.962.751.4

Dec 1987

71.853.162.551.5

Jan 1988

71.953.162.851.2

Feb 1988

72.053.162.150.9

Mar 1988

71.653.261.550.6

Apr 1988

72.253.262.950.1

May 1988

72.052.962.550.1

Jun 1988

72.153.362.550.1

Jul 1988

72.253.362.651.9

Aug 1988

72.253.563.351.4

Sep 1988

72.153.563.051.4

Oct 1988

72.053.863.151.8

Nov 1988

72.154.162.852.1

Dec 1988

72.054.162.952.4

Jan 1989

72.254.463.051.9

Feb 1989

72.454.262.852.0

Mar 1989

72.654.263.151.9

Apr 1989

72.554.262.051.8

May 1989

72.454.262.652.3

Jun 1989

72.854.163.351.6

Jul 1989

72.754.263.752.3

Aug 1989

72.654.463.052.0

Sep 1989

72.054.562.352.0

Oct 1989

72.454.362.451.7

Nov 1989

72.354.762.352.0

Dec 1989

72.354.462.251.9

Jan 1990

72.654.662.852.9

Feb 1990

72.654.563.152.9

Mar 1990

72.654.663.252.8

Apr 1990

72.354.563.252.5

May 1990

72.454.663.352.9

Jun 1990

72.254.463.152.1

Jul 1990

72.154.362.551.4

Aug 1990

71.954.462.451.2

Sep 1990

71.654.262.051.0

Oct 1990

71.654.262.051.2

Nov 1990

71.454.062.051.2

Dec 1990

71.353.961.850.9

Jan 1991

71.053.861.851.1

Feb 1991

70.753.861.750.8

Mar 1991

70.653.762.450.9

Apr 1991

70.754.161.551.1

May 1991

70.453.660.150.9

Jun 1991

70.453.761.150.6

Jul 1991

70.353.661.351.0

Aug 1991

70.253.560.950.3

Sep 1991

70.353.761.951.2

Oct 1991

70.153.761.149.6

Nov 1991

70.053.661.049.7

Dec 1991

69.753.560.750.3

Jan 1992

69.853.860.750.3

Feb 1992

69.653.759.850.3

Mar 1992

69.853.859.850.4

Apr 1992

70.053.959.750.3

May 1992

69.953.859.750.4

Jun 1992

69.953.760.151.0

Jul 1992

70.053.860.051.3

Aug 1992

70.053.860.351.9

Sep 1992

69.953.760.151.4

Oct 1992

69.753.659.650.8

Nov 1992

69.753.760.050.4

Dec 1992

69.853.759.250.6

Jan 1993

69.853.759.949.5

Feb 1993

69.953.760.750.8

Mar 1993

69.953.959.350.5

Apr 1993

69.853.858.850.3

May 1993

70.154.160.250.9

Jun 1993

70.154.159.850.5

Jul 1993

70.254.160.750.7

Aug 1993

70.354.361.151.1

Sep 1993

70.054.260.051.3

Oct 1993

70.054.359.951.6

Nov 1993

70.154.459.551.8

Dec 1993

70.154.659.752.1

Jan 1994

70.254.959.451.5

Feb 1994

70.155.159.851.8

Mar 1994

70.054.960.551.9

Apr 1994

70.155.160.652.2

May 1994

70.355.461.351.7

Jun 1994

70.255.160.852.8

Jul 1994

70.155.260.352.8

Aug 1994

70.555.360.152.7

Sep 1994

70.655.461.052.7

Oct 1994

70.855.561.652.5

Nov 1994

71.055.661.752.3

Dec 1994

71.355.562.652.0

Jan 1995

71.255.562.352.5

Feb 1995

71.355.663.153.4

Mar 1995

71.355.663.353.2

Apr 1995

71.155.762.653.3

May 1995

70.555.661.753.7

Jun 1995

70.855.361.752.9

Jul 1995

70.755.660.852.6

Aug 1995

70.655.760.552.8

Sep 1995

70.855.661.252.5

Oct 1995

70.755.861.454.0

Nov 1995

70.355.961.355.5

Dec 1995

70.455.660.554.6

Jan 1996

70.555.561.054.1

Feb 1996

70.755.760.853.8

Mar 1996

70.755.860.754.1

Apr 1996

70.755.960.754.1

May 1996

70.855.861.354.6

Jun 1996

71.055.960.754.4

Jul 1996

71.156.161.354.7

Aug 1996

71.156.262.254.4

Sep 1996

71.156.460.854.2

Oct 1996

71.356.461.154.8

Nov 1996

70.956.561.154.8

Dec 1996

71.156.461.154.7

Jan 1997

71.056.460.555.0

Feb 1997

71.056.360.754.9

Mar 1997

71.256.660.355.5

Apr 1997

71.356.760.655.4

May 1997

71.556.760.955.1

Jun 1997

71.356.860.954.8

Jul 1997

71.457.061.855.9

Aug 1997

71.457.063.556.5

Sep 1997

71.357.062.456.4

Oct 1997

71.457.062.155.6

Nov 1997

71.757.062.055.8

Dec 1997

71.457.261.156.4

Jan 1998

71.557.062.056.5

Feb 1998

71.557.061.857.0

Mar 1998

71.457.162.757.1

Apr 1998

71.857.063.156.5

May 1998

71.757.162.656.0

Jun 1998

71.657.063.757.1

Jul 1998

71.557.062.857.0

Aug 1998

71.457.162.857.3

Sep 1998

71.657.362.957.0

Oct 1998

71.657.163.857.8

Nov 1998

71.857.163.158.1

Dec 1998

71.757.463.158.5

Jan 1999

71.957.464.058.7

Feb 1999

71.757.362.958.0

Mar 1999

71.757.362.958.1

Apr 1999

71.657.362.758.7

May 1999

71.757.563.658.4

Jun 1999

71.657.463.258.6

Jul 1999

71.657.462.258.7

Aug 1999

71.557.563.258.6

Sep 1999

71.657.462.958.9

Oct 1999

71.557.663.058.7

Nov 1999

71.757.662.958.8

Dec 1999

71.857.663.358.3

Jan 2000

72.257.661.259.0

Feb 2000

72.257.561.558.9

Mar 2000

72.257.561.258.9

Apr 2000

72.158.064.559.0

May 2000

71.957.563.358.8

Jun 2000

72.057.563.258.5

Jul 2000

71.657.363.258.1

Aug 2000

71.957.162.958.2

Sep 2000

71.757.462.958.1

Oct 2000

71.657.463.358.5

Nov 2000

71.757.563.758.7

Dec 2000

71.757.663.358.7

Jan 2001

71.857.663.758.1

Feb 2001

71.657.563.258.5

Mar 2001

71.457.762.658.7

Apr 2001

71.357.262.258.6

May 2001

71.157.262.158.6

Jun 2001

70.957.061.658.6

Jul 2001

70.957.062.158.5

Aug 2001

70.456.661.557.5

Sep 2001

70.856.762.557.0

Oct 2001

70.356.661.256.7

Nov 2001

70.056.660.956.2

Dec 2001

70.056.361.856.1

Jan 2002

69.756.262.055.9

Feb 2002

69.956.661.955.9

Mar 2002

69.856.461.755.3

Apr 2002

69.856.261.855.6

May 2002

70.156.162.555.5

Jun 2002

69.856.260.755.6

Jul 2002

69.756.161.055.3

Aug 2002

69.756.360.955.7

Sep 2002

70.056.461.456.5

Oct 2002

69.756.361.256.1

Nov 2002

69.256.259.055.9

Dec 2002

69.156.259.156.2

Jan 2003

68.956.559.656.4

Feb 2003

69.256.260.255.5

Mar 2003

68.956.359.256.1

Apr 2003

69.056.359.556.1

May 2003

68.856.359.156.8

Jun 2003

68.756.459.455.6

Jul 2003

68.656.159.655.4

Aug 2003

68.656.059.355.6

Sep 2003

68.955.759.555.6

Oct 2003

68.955.959.254.8

Nov 2003

69.056.059.755.7

Dec 2003

69.255.760.054.3

Jan 2004

69.455.760.355.4

Feb 2004

69.156.059.455.7

Mar 2004

69.055.959.755.8

Apr 2004

69.056.058.956.0

May 2004

68.956.159.255.0

Jun 2004

69.256.059.454.7

Jul 2004

69.456.058.555.9

Aug 2004

69.356.059.055.8

Sep 2004

69.155.959.355.6

Oct 2004

69.255.959.555.5

Nov 2004

69.456.059.455.3

Dec 2004

69.256.158.955.4

Jan 2005

69.156.158.855.3

Feb 2005

69.256.058.655.0

Mar 2005

69.456.059.455.0

Apr 2005

69.656.260.255.2

May 2005

69.856.260.855.6

Jun 2005

69.856.160.955.8

Jul 2005

69.856.261.856.0

Aug 2005

69.956.461.255.9

Sep 2005

69.756.460.756.1

Oct 2005

69.756.460.757.0

Nov 2005

69.656.359.356.1

Dec 2005

69.756.360.055.9

Jan 2006

70.056.360.055.9

Feb 2006

70.056.460.756.4

Mar 2006

70.256.461.156.4

Apr 2006

70.056.460.956.0

May 2006

70.056.661.156.6

Jun 2006

70.056.760.356.2

Jul 2006

69.656.860.056.2

Aug 2006

69.956.860.357.1

Sep 2006

70.256.560.056.1

Oct 2006

70.256.860.657.2

Nov 2006

70.256.860.957.1

Dec 2006

70.456.961.657.2

Jan 2007

70.356.861.857.5

Feb 2007

70.156.861.257.2

Mar 2007

70.256.960.456.9

Apr 2007

70.056.360.656.7

May 2007

69.956.660.356.5

Jun 2007

69.856.759.956.7

Jul 2007

69.656.661.456.6

Aug 2007

69.456.561.756.3

Sep 2007

69.556.860.956.4

Oct 2007

69.356.559.856.3

Nov 2007

69.656.660.355.7

Dec 2007

69.456.559.856.1

Jan 2008

69.656.660.956.1

Feb 2008

69.556.560.856.3

Mar 2008

69.356.560.156.6

Apr 2008

69.256.660.256.8

May 2008

69.056.559.656.0

Jun 2008

68.856.459.755.9

Jul 2008

68.656.359.056.1

Aug 2008

68.356.159.955.6

Sep 2008

68.156.158.554.9

Oct 2008

67.856.157.855.1

Nov 2008

67.355.856.755.1

Dec 2008

66.755.656.455.3

Jan 2009

66.255.255.654.8

Feb 2009

65.755.254.953.8

Mar 2009

65.155.054.253.5

Apr 2009

65.054.953.853.4

May 2009

64.854.753.953.0

Jun 2009

64.654.553.553.2

Jul 2009

64.554.553.953.2

Aug 2009

64.254.353.252.6

Sep 2009

63.953.952.851.9

Oct 2009

63.753.752.851.3

Nov 2009

63.653.852.752.0

Dec 2009

63.353.552.751.3

Jan 2010

63.353.952.551.6

Feb 2010

63.453.852.551.8

Mar 2010

63.653.752.551.6

Apr 2010

64.053.753.351.5

May 2010

63.953.654.152.1

Jun 2010

63.853.652.852.2

Jul 2010

63.953.553.251.5

Aug 2010

63.953.553.451.3

Sep 2010

63.853.552.851.2

Oct 2010

63.653.353.451.5

Nov 2010

63.453.453.151.8

Dec 2010

63.653.353.251.8

Jan 2011

63.753.352.651.3

Feb 2011

63.853.252.751.2

Mar 2011

63.853.452.650.9

Apr 2011

63.753.352.550.4

May 2011

63.853.252.050.4

Jun 2011

63.753.052.650.0

Jul 2011

63.653.152.449.9

Aug 2011

63.953.152.550.6

Sep 2011

63.953.253.151.5

Oct 2011

63.953.353.551.7

Nov 2011

64.353.253.050.8

Dec 2011

64.453.154.450.6

Jan 2012

64.352.955.250.9

Feb 2012

64.353.154.052.2

Mar 2012

64.353.254.152.4

Apr 2012

64.353.053.852.6

May 2012

64.353.154.252.0

Jun 2012

64.453.254.352.1

Jul 2012

64.353.053.852.0

Aug 2012

64.153.153.752.2

Sep 2012

64.553.353.652.4

Oct 2012

64.753.354.052.9

Nov 2012

64.653.254.352.2

Dec 2012

64.653.254.051.7

Jan 2013

64.553.054.852.1

Feb 2013

64.553.055.251.6

Mar 2013

64.552.955.351.6

Apr 2013

64.453.254.452.4

May 2013

64.453.254.352.8

Jun 2013

64.553.253.952.0

Jul 2013

64.453.454.852.4

Aug 2013

64.353.554.052.1

Sep 2013

64.453.354.752.1

Oct 2013

64.052.954.451.5

Nov 2013

64.553.154.651.7

Dec 2013

64.553.254.452.1

Jan 2014

64.553.454.452.4

Feb 2014

64.353.654.253.3

Mar 2014

64.853.455.252.8

Apr 2014

64.653.555.452.7

May 2014

64.653.555.352.7

Jun 2014

64.953.556.153.0

Jul 2014

65.053.456.353.0

Aug 2014

65.053.456.352.1

Sep 2014

65.253.457.053.0

Oct 2014

65.353.756.953.1

Nov 2014

65.153.756.253.3

Dec 2014

65.353.656.753.4

Jan 2015

65.353.756.453.2

Feb 2015

65.353.656.753.3

Mar 2015

65.353.656.953.5

Apr 2015

65.553.658.554.2

May 2015

65.553.857.654.2

Jun 2015

65.353.857.154.8

Jul 2015

65.453.657.254.8

Aug 2015

65.453.857.254.8

Sep 2015

65.353.557.154.5

Oct 2015

65.353.757.254.9

Nov 2015

65.254.056.755.0

Dec 2015

65.554.157.955.1

Jan 2016

65.754.157.754.9

Feb 2016

65.954.158.254.5

Mar 2016

65.954.258.354.1

Apr 2016

65.854.058.253.8

May 2016

65.754.158.554.0

Jun 2016

65.953.958.554.1

Jul 2016

65.854.158.354.4

Aug 2016

65.954.158.555.6

Sep 2016

65.854.158.455.3

Oct 2016

65.754.158.055.3

Nov 2016

65.754.158.655.6

Dec 2016

65.754.158.755.7

Jan 2017

65.954.259.656.0

Feb 2017

65.954.459.055.9

Mar 2017

66.054.759.056.0

Apr 2017

66.254.659.855.9

May 2017

66.054.559.756.1

Jun 2017

66.154.659.855.9

Jul 2017

66.054.859.556.2

Aug 2017

66.054.658.955.9

Sep 2017

66.354.860.456.3

Oct 2017

66.054.558.956.2

Nov 2017

65.954.659.056.6

Dec 2017

66.154.559.456.8

Jan 2018

66.354.559.455.8

Feb 2018

66.654.761.456.3

Mar 2018

66.554.760.756.7

Apr 2018

66.554.760.356.0

May 2018

66.554.861.056.6

Jun 2018

66.354.959.757.2

Jul 2018

66.355.260.157.0

Aug 2018

66.154.860.456.1

Sep 2018

66.155.060.257.2

Oct 2018

66.255.160.257.1

Nov 2018

66.455.160.256.7

Dec 2018

66.255.259.656.4

Jan 2019

66.555.260.057.3

Feb 2019

66.555.360.056.7

Mar 2019

66.555.259.956.5

Apr 2019

66.455.260.356.8

May 2019

66.555.060.257.3

Jun 2019

66.655.160.056.7

Jul 2019

66.755.261.257.1

Aug 2019

66.655.460.757.1

Sep 2019

66.655.661.157.4

Oct 2019

66.555.760.957.3

Nov 2019

66.855.561.156.8

Dec 2019

66.755.761.057.9

Jan 2020

66.855.860.457.7

Feb 2020

66.855.960.658.4

Mar 2020

65.654.659.556.1

Apr 2020

57.245.850.447.4

May 2020

58.647.351.448.2

Jun 2020

60.249.551.949.9

Jul 2020

60.650.252.950.3

Aug 2020

62.051.354.151.0

Sep 2020

62.351.253.851.5

Oct 2020

63.052.155.052.5

Nov 2020

62.852.355.153.2

Dec 2020

62.952.255.552.6

Jan 2021

63.252.257.052.9

Feb 2021

63.252.556.452.5

Mar 2021

63.252.857.153.1

Apr 2021

63.452.857.353.6

May 2021

63.552.957.453.8

Jun 2021

63.552.958.353.9

Jul 2021

63.853.357.854.2

Aug 2021

64.153.457.754.8

Sep 2021

64.453.557.955.3

Oct 2021

64.653.658.454.5

Nov 2021

65.053.958.755.1

Dec 2021

65.154.358.255.0

Jan 2022

65.154.660.055.7
Percent distribution of employed Blacks or African Americans and the total workforce by selected industry and sex, 2021 annual averages
Selected industryTotal menTotal womenBlack menBlack women

Construction

12.4%1.7%7.2%0.7%

Manufacturing

12.96.011.25.3

Wholesale and retail trade

13.312.415.011.5

Transportation and utilities

8.73.214.95.3

Information

2.01.52.01.4

Financial activities

6.47.85.37.5

Professional and business services

13.711.411.58.9

Education and health services

11.036.013.640.1

Leisure and hospitality

7.79.08.37.8

Other services

4.35.24.13.9

Public administration

4.94.86.07.3

Note: Data do not sum to 100 percent because values are not shown for agriculture and related industries or for mining, quarrying, and oil and gas extraction.

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

Expanding BLS Data on Total Factor Productivity

Our data on multifactor productivity are getting a makeover. You’ll get the same great data but with a new name, “total factor productivity.” Why change the name if it’s the same data? To reach you! More web searches seek total factor productivity than multifactor productivity. That’s probably because most other countries, including our major trading partners, call it total factor productivity. We want to make it easier to find us and stop having to answer how multifactor productivity differs from total factor productivity. They’re the same thing!

Besides the name change, we will expand our annual release of trends in total factor productivity for manufacturing to include not only manufacturing, but all the major industries in the private sector. With this addition, total factor productivity measures for all private major industries of the economy will be available in our news release and the BLS database.

Back to Basics

For those new to productivity data, let’s back up a bit. What is productivity and why should we care about it?

Productivity is a measure of economic performance, often touted as the engine of a nation’s economic growth. Productivity compares the output of goods and services with the inputs used to produce them. The difference in growth rates between these two amounts—the unexplained portion—equals productivity growth. Productivity tells us how good we are at using the inputs to create the output.

Productivity growth is important because, in the long run, it accounts for a third of the growth in a nation’s output. This growth supports increased wages, profits, public sector revenue, and global competitiveness. There are two types of productivity measures produced by BLS, labor productivity and total factor productivity. They are similar, as you can see in the chart below, but they have key differences.

Labor and total factor productivity, annualized percent change, private nonfarm business, 2010–19

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

Much of the limelight goes to labor productivity, output per hour worked, which measures how many hours it takes to produce the goods and services in our economy. This measure is pretty simple to interpret and apply. If you used the same number of hours but produced more goods and services than last year, the economy became more efficient and labor productivity increased. Labor productivity increased because something besides worker hours (which we know stayed the same) contributed to the increased output. That something is productivity—the growth we didn’t account for in the calculation. With labor productivity, we only account for one input—hours worked. All the other inputs to production, like capital investment and materials, get lumped together into the unknown efficiency gains that can result from changes in technology or how work is organized.

This is where total factor productivity comes in. As the name suggests, total factor productivity measures more than just labor as an input to producing goods and services. It puts more “knowns” into the equation to help us pinpoint a more detailed story of why productivity is changing. For an industry, total factor productivity measures the output produced by a combined set of inputs: capital, labor, energy, materials, and purchased services. Total factor productivity tells us how much more output can be produced without increasing any of these inputs. The more efficiently an industry uses its inputs to create output, the faster total factor productivity will grow.

Total factor productivity gives us great insight into what drives economic growth. Is it the industries’ choice of capital investment? Better or more skilled labor? Or is it a change to the other factors of production, such as energy expenditures, materials consumed, or services purchased, or more efficient use of these inputs? The more detail with which we measure an industry, the more we can learn how these choices contribute to growth in this industry and ultimately our economy.

Let’s recap what we know:

Total factor productivity = output ÷ (combined inputs of capital, labor, energy, materials, and services)

And if we rearrange this equation and transform it to growth over time, we can see that increasing total factor productivity is a way to increase our nation’s output growth.

Output growth = total factor productivity growth + combined inputs growth

More is More

Previously, the annual release on Multifactor Productivity Trends in Manufacturing brought you information on the manufacturing sector and its 19 detailed industries. The manufacturing sector has often been a pioneer of technological development that drives productivity growth and is thus an important sector of the nation’s economy. You can see just how big of a role it has played in productivity growth in The Economics Daily.

And now we are providing a more complete picture. Not only will you get the first comprehensive look into what the COVID-19 pandemic in 2020 meant for labor, capital, and more, but we also will include all major industries and not just manufacturing. The chart below gives a taste of the expanded information that we will now include in the reimagined release with a new name. For example, we can see that in 2019, the information industry had strong output growth (third highest), stemming mostly from combined inputs growth and total factor productivity growth (those things that are harder to measure).

Percent change in total factor productivity, combined inputs, and output, by major private industry, 2019

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

Connecting Total Factor Productivity to Labor Productivity

We can use total factor productivity and combined inputs for more than just an explanation of output growth. These measures give us is a way to break down the growth of labor productivity. We are the Bureau of Labor Statistics after all, so using our data to understand the growth in efficiency of the nation’s workforce is important.

We can express labor productivity growth as the sum of the growth of six components:

  • Total factor productivity
  • Contribution of capital intensity
  • Contribution of labor composition (shifts in the age, education, and gender composition of the workforce)
  • Contribution of energy
  • Contribution of materials
  • Contribution of purchased services

The contribution of each input is the ratio of the services provided by that input to hours worked. When we look at the contribution of each input, we can measure the effect of increasing the use of that input on an industry’s labor productivity.

The chart below shows sources of labor productivity in 2019 for each industry. The information industry had the second largest increase in labor productivity, rising 5.9 percent. That increase was driven by an increase in capital of 2.8 percent and total factor productivity growth of 1.5 percent. Knowing what drives productivity helps businesses make better decisions and pass those efficiencies on to workers and customers.

Sources of labor productivity change (in percentage points) by major private industry, 2019

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

We will release new annual data for Total Factor Productivity in 2020 on November 18, 2021, at 10:00 a.m. Eastern Time. More detailed industry data are also available. For more information on productivity check, out our Productivity page. Want to help us improve our productivity data and publications? Please fill out our 10-minute survey by November 16, 2021.

Labor and total factor productivity, annualized percent change, private nonfarm business, 2010–19
YearLabor ProductivityTotal Factor Productivity

2010

3.4%2.7%

2011

-0.1-0.1

2012

0.80.7

2013

0.50.1

2014

0.80.6

2015

1.61.1

2016

0.4-0.4

2017

1.20.5

2018

1.50.9

2019

1.80.7
Percent change in total factor productivity, combined inputs, and output, by major private industry, 2019
IndustryOutputCombined inputsTotal Factor Productivity

Mining

6.7%2.0%4.6%

Management of companies

6.32.33.9

Information

5.74.21.5

Professional and technical services

3.72.21.5

Administrative and waste services

3.52.41.1

Real estate and rental and leasing

2.82.40.4

Accommodation and food services

2.82.10.7

Retail trade

2.30.51.7

Health care and social assistance

2.31.70.7

Transportation and warehousing

2.12.10.0

Arts, entertainment, and recreation

2.10.51.5

Finance and insurance

1.93.0-1.1

Agriculture, forestry, fishing, and hunting

0.50.8-0.3

Educational services

0.10.6-0.5

Construction

-0.70.7-1.4

Other services, except government

-0.8-2.21.3

Utilities

-1.1-4.63.6

Nondurable manufacturing

-1.60.3-1.9

Manufacturing

-1.70.3-2.0

Durable manufacturing

-1.80.1-1.9

Wholesale trade

-2.10.0-2.1
Sources of labor productivity change (in percentage points) by major private industry, 2019
IndustryServices intensityMaterials intensityEnergy intensityLabor compositionCapital intensityTotal Factor Productivity

Management of companies

1.9-0.10.00.50.03.9

Information

1.40.10.00.12.81.5

Mining

1.1-0.7-0.10.5-0.64.6

Arts, entertainment, and recreation

1.70.00.0-0.21.11.5

Administrative and waste services

1.80.30.00.30.31.1

Retail trade

1.70.0-0.10.00.51.7

Accommodation and food services

0.8-0.1-0.20.20.00.7

Finance and insurance

1.60.00.00.10.9-1.1

Professional and technical services

-0.1-0.20.0-0.10.31.5

Health care and social assistance

0.1-0.3-0.10.20.10.7

Real estate and rental and leasing

0.5-0.1-0.20.00.00.4

Utilities

-1.40.2-3.30.01.63.6

Other services, except government

-0.8-0.3-0.10.00.11.3

Agriculture, forestry, fishing, and hunting

0.00.4-0.30.1-0.3-0.3

Nondurable manufacturing

0.3-0.1-0.10.10.6-1.9

Manufacturing

0.00.1-0.20.00.5-2.0

Durable manufacturing

-0.20.1-0.10.00.4-1.9

Transportation and warehousing

-1.20.3-1.0-0.3-0.10.0

Wholesale trade

-1.00.0-0.10.10.7-2.1

Construction

-0.3-1.3-0.20.00.1-1.4

Educational services

-2.20.2-0.4-0.1-0.1-2.2