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Topic Archives: Labor Force Characteristics

BLS Now Publishing Monthly Data for Native Hawaiians and Other Pacific Islanders and People of Two or More Races

I am pleased to announce that BLS is now publishing monthly labor force estimates for Native Hawaiians and Other Pacific Islanders and people who are of Two or More Races. For several years we have published a small set of annual labor market estimates for these populations in our report on labor force characteristics by race and ethnicity. But we have not published monthly estimates of the unemployment rate, the employment–population ratio, the labor force participation rate, and other key metrics for Native Hawaiians and Other Pacific Islanders and people who are of Two or More Races. With the release of the Employment Situation report on September 2, 2022, we now have monthly data for both groups available back to January 2003.

The Native Hawaiian and Other Pacific Islander category is defined as people having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands. Pacific Islanders are diverse populations with different languages and cultures and include Polynesian, Micronesian, and Melanesian. Two or More Races is defined as people who identify as more than one race. Before 2003, people could identify only one race category as their main race in the Current Population Survey, the source of our data on unemployment and the labor force.

Unemployment

In February 2020, before the COVID-19 pandemic, the overall unemployment rate for the United States was 3.5 percent (seasonally adjusted). The rate was 2.7 percent (not seasonally adjusted) for Native Hawaiians and Other Pacific Islanders and 6.1 percent (not seasonally adjusted) for people who are of Two or More Races.

The jobless rate for Native Hawaiians and Other Pacific Islanders peaked at 14.6 percent in November 2020, about 9 months into the COVID-19 pandemic. This was double the seasonally adjusted rate of 6.7 percent for the total population. The unemployment rate for people who are of Two or More Races peaked at 19.3 percent in April 2020, early in the pandemic, compared with 14.7 percent for all groups.

The unemployment rate has declined for all groups since their peaks during the COVID-19 pandemic. By August 2022, the overall unemployment rate for the United States was 3.7 percent. The rate was 3.8 percent for Native Hawaiians and Other Pacific Islanders and 6.2 percent for people who are of Two or More Races.

Unemployment rates for Native Hawaiians and Other Pacific Islanders, Two or More Races, and the total population, January 2003 to August 2022

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

Employment

Before the COVID-19 pandemic, the employment–population ratio for the United States (the proportion of the population that is employed) was 61.2 percent (seasonally adjusted) in February 2020. The rate was 67.6 percent (not seasonally adjusted) for Native Hawaiians and Other Pacific Islanders and 63.7 percent (not seasonally adjusted) for people who are of Two or More Races.

The ratios for all groups declined sharply at the start of the COVID-19 pandemic and have not yet returned to their pre-pandemic levels. In August 2022, the employment–population ratio was 60.1 percent for the United States. The ratio was 65.7 percent for Native Hawaiians and Other Pacific Islanders and 61.3 percent for people who are of Two or More Races.

The employment–population ratio is generally higher for Native Hawaiians and Other Pacific Islanders than the U.S. average. The greater likelihood of employment among Native Hawaiians and Other Pacific Islanders reflects the fact that a larger share of this population is in the 25 to 54 age range than the overall population. People in this age range are more likely to be employed than people in younger and older age groups. By contrast, from 2003 to 2016, the employment–population ratio was generally lower for people who are of Two or More Races than the U.S. average. In recent years, the employment–population ratio for people who are of Two or More Races is little different than the national rate.

Employment–population ratios for Native Hawaiians and Other Pacific Islanders, Two or More Races, and the total population, January 2003 to August 2022

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

Monthly estimates give us timely measures to see how groups are faring in the labor market. However, one must exercise caution when analyzing and interpreting monthly data for small population groups. The measures for Native Hawaiians and Other Pacific Islanders and for people who are of Two or More Races tend to be volatile for two main reasons. First, the estimates are based on small sample sizes. We survey about 60,000 U.S. households every month. People who identify themselves as Native Hawaiians and Other Pacific Islanders make up about 0.5 percent of the total labor force. People who identify as having Two or More Races make up about 2.2 percent of the total labor force. Because of their small sample sizes, the month-to-month change in our key economic metrics must be pretty large to be statistically significant. On average, the unemployment rate for Native Hawaiians and Other Pacific Islanders must change by nearly 4 percentage points and the rate for people who are of Two or More Races must change by around 2 percentage points for the differences to be meaningful.

Second, these data are not seasonally adjusted. Seasonal adjustment is a statistical procedure used to remove the effects of seasonality from data so it is easier to see underlying trends. But not all data series can be seasonally adjusted; they must pass a battery of diagnostic tests to be fitted to a seasonal adjustment model. So far, we haven’t been able to do that for data for Native Hawaiians and Other Pacific Islanders and people who are of Two or More Races, but we’ll keep evaluating them as we get more data. Because these data aren’t seasonally adjusted, it can be challenging to compare one month to the following month.

We’re also publishing quarterly estimates for Native Hawaiians and Other Pacific Islanders and people who are of Two or More Races for the first time starting this month. Because these estimates are averages of three months of data, they are somewhat less volatile.

Unemployment rates for Native Hawaiians and Other Pacific Islanders, Two or More Races, and the total population, January 2003 to August 2022
MonthTotal (seasonally adjusted)Native Hawaiian or Other Pacific Islander (not seasonally adjusted)Two or more races (not seasonally adjusted)

Jan 2003

5.8%4.3%10.1%

Feb 2003

5.97.09.3

Mar 2003

5.96.58.8

Apr 2003

6.09.09.5

May 2003

6.17.79.3

Jun 2003

6.37.29.7

Jul 2003

6.26.89.0

Aug 2003

6.16.68.6

Sep 2003

6.18.69.4

Oct 2003

6.010.78.5

Nov 2003

5.810.39.1

Dec 2003

5.78.77.6

Jan 2004

5.77.48.8

Feb 2004

5.65.810.6

Mar 2004

5.84.28.6

Apr 2004

5.66.38.4

May 2004

5.63.78.8

Jun 2004

5.63.28.2

Jul 2004

5.55.28.0

Aug 2004

5.45.58.2

Sep 2004

5.47.89.2

Oct 2004

5.57.29.2

Nov 2004

5.46.57.5

Dec 2004

5.48.88.7

Jan 2005

5.33.39.0

Feb 2005

5.42.59.0

Mar 2005

5.24.29.2

Apr 2005

5.24.16.6

May 2005

5.15.87.7

Jun 2005

5.03.49.2

Jul 2005

5.05.48.1

Aug 2005

4.95.17.1

Sep 2005

5.05.67.6

Oct 2005

5.05.56.8

Nov 2005

5.04.38.7

Dec 2005

4.93.77.0

Jan 2006

4.77.67.0

Feb 2006

4.84.07.7

Mar 2006

4.75.47.8

Apr 2006

4.76.37.0

May 2006

4.67.56.0

Jun 2006

4.65.75.8

Jul 2006

4.74.46.6

Aug 2006

4.76.87.1

Sep 2006

4.54.96.6

Oct 2006

4.43.16.3

Nov 2006

4.55.16.1

Dec 2006

4.43.46.2

Jan 2007

4.64.07.8

Feb 2007

4.55.06.8

Mar 2007

4.47.38.5

Apr 2007

4.55.17.5

May 2007

4.45.56.4

Jun 2007

4.63.65.5

Jul 2007

4.76.06.9

Aug 2007

4.64.75.4

Sep 2007

4.76.47.2

Oct 2007

4.73.38.0

Nov 2007

4.74.67.4

Dec 2007

5.02.88.4

Jan 2008

5.04.48.6

Feb 2008

4.96.17.7

Mar 2008

5.14.29.6

Apr 2008

5.03.29.9

May 2008

5.44.19.7

Jun 2008

5.66.39.3

Jul 2008

5.86.18.6

Aug 2008

6.19.18.9

Sep 2008

6.19.410.5

Oct 2008

6.57.19.3

Nov 2008

6.87.311.0

Dec 2008

7.38.410.3

Jan 2009

7.87.412.7

Feb 2009

8.36.812.4

Mar 2009

8.713.414.7

Apr 2009

9.010.516.7

May 2009

9.48.914.7

Jun 2009

9.513.915.2

Jul 2009

9.514.611.4

Aug 2009

9.612.813.3

Sep 2009

9.814.413.5

Oct 2009

10.07.712.8

Nov 2009

9.910.112.5

Dec 2009

9.98.712.9

Jan 2010

9.810.914.4

Feb 2010

9.89.212.4

Mar 2010

9.911.314.4

Apr 2010

9.912.314.7

May 2010

9.610.614.9

Jun 2010

9.412.114.9

Jul 2010

9.412.914.9

Aug 2010

9.513.112.8

Sep 2010

9.510.512.9

Oct 2010

9.415.612.8

Nov 2010

9.815.112.2

Dec 2010

9.311.512.6

Jan 2011

9.111.913.1

Feb 2011

9.014.312.4

Mar 2011

9.013.014.7

Apr 2011

9.114.312.0

May 2011

9.09.512.1

Jun 2011

9.18.416.7

Jul 2011

9.06.715.3

Aug 2011

9.09.215.1

Sep 2011

9.09.213.8

Oct 2011

8.810.214.6

Nov 2011

8.69.711.2

Dec 2011

8.59.311.4

Jan 2012

8.39.313.6

Feb 2012

8.311.912.3

Mar 2012

8.210.412.2

Apr 2012

8.210.710.4

May 2012

8.214.711.2

Jun 2012

8.211.910.6

Jul 2012

8.211.512.8

Aug 2012

8.115.311.8

Sep 2012

7.811.810.8

Oct 2012

7.89.911.7

Nov 2012

7.79.713.6

Dec 2012

7.914.511.3

Jan 2013

8.09.512.1

Feb 2013

7.79.911.8

Mar 2013

7.511.811.6

Apr 2013

7.68.210.1

May 2013

7.58.510.2

Jun 2013

7.56.114.2

Jul 2013

7.310.011.3

Aug 2013

7.212.411.2

Sep 2013

7.210.39.7

Oct 2013

7.212.210.4

Nov 2013

6.912.19.5

Dec 2013

6.711.19.5

Jan 2014

6.69.611.2

Feb 2014

6.77.010.8

Mar 2014

6.74.79.9

Apr 2014

6.25.410.2

May 2014

6.34.19.6

Jun 2014

6.16.19.8

Jul 2014

6.27.311.8

Aug 2014

6.15.211.4

Sep 2014

5.95.710.8

Oct 2014

5.74.38.9

Nov 2014

5.87.09.2

Dec 2014

5.66.59.1

Jan 2015

5.77.911.0

Feb 2015

5.56.39.3

Mar 2015

5.42.510.1

Apr 2015

5.46.07.8

May 2015

5.65.69.6

Jun 2015

5.35.57.8

Jul 2015

5.24.18.8

Aug 2015

5.15.38.1

Sep 2015

5.09.18.0

Oct 2015

5.06.97.8

Nov 2015

5.14.56.9

Dec 2015

5.04.66.3

Jan 2016

4.82.08.6

Feb 2016

4.93.09.7

Mar 2016

5.04.29.4

Apr 2016

5.12.78.6

May 2016

4.83.36.9

Jun 2016

4.93.37.0

Jul 2016

4.85.88.0

Aug 2016

4.95.36.9

Sep 2016

5.07.87.3

Oct 2016

4.97.75.7

Nov 2016

4.73.85.7

Dec 2016

4.73.36.1

Jan 2017

4.72.77.4

Feb 2017

4.67.79.5

Mar 2017

4.42.86.6

Apr 2017

4.45.95.0

May 2017

4.43.47.7

Jun 2017

4.36.47.1

Jul 2017

4.311.66.8

Aug 2017

4.49.35.9

Sep 2017

4.37.36.2

Oct 2017

4.25.66.0

Nov 2017

4.25.66.0

Dec 2017

4.14.15.7

Jan 2018

4.04.75.6

Feb 2018

4.15.45.6

Mar 2018

4.09.06.4

Apr 2018

4.03.85.1

May 2018

3.84.56.0

Jun 2018

4.07.47.0

Jul 2018

3.82.96.9

Aug 2018

3.86.65.4

Sep 2018

3.75.65.3

Oct 2018

3.86.24.5

Nov 2018

3.84.44.6

Dec 2018

3.93.04.3

Jan 2019

4.02.35.5

Feb 2019

3.81.15.8

Mar 2019

3.84.16.3

Apr 2019

3.64.45.2

May 2019

3.62.74.9

Jun 2019

3.63.06.9

Jul 2019

3.72.16.1

Aug 2019

3.74.54.5

Sep 2019

3.54.74.9

Oct 2019

3.63.75.1

Nov 2019

3.63.04.9

Dec 2019

3.63.13.5

Jan 2020

3.52.66.3

Feb 2020

3.52.76.1

Mar 2020

4.43.07.3

Apr 2020

14.77.619.3

May 2020

13.210.517.7

Jun 2020

11.010.015.3

Jul 2020

10.211.814.6

Aug 2020

8.412.412.6

Sep 2020

7.914.511.2

Oct 2020

6.912.79.0

Nov 2020

6.714.69.3

Dec 2020

6.75.710.9

Jan 2021

6.410.010.1

Feb 2021

6.28.99.1

Mar 2021

6.07.19.0

Apr 2021

6.011.88.3

May 2021

5.85.68.1

Jun 2021

5.98.99.4

Jul 2021

5.47.29.3

Aug 2021

5.25.17.5

Sep 2021

4.75.98.0

Oct 2021

4.66.16.4

Nov 2021

4.22.77.7

Dec 2021

3.94.55.3

Jan 2022

4.05.26.4

Feb 2022

3.85.66.8

Mar 2022

3.62.96.2

Apr 2022

3.62.84.2

May 2022

3.64.14.4

Jun 2022

3.63.43.9

Jul 2022

3.54.55.6

Aug 2022

3.73.86.2
Employment–population ratios for Native Hawaiians and Other Pacific Islanders, Two or More Races, and the total population, January 2003 to August 2022
MonthTotal (seasonally adjusted)Native Hawaiian or Other Pacific Islander (not seasonally adjusted)Two or more races (not seasonally adjusted)

Jan 2003

62.5%66.5%59.8%

Feb 2003

62.563.059.4

Mar 2003

62.461.459.2

Apr 2003

62.459.859.8

May 2003

62.360.261.1

Jun 2003

62.362.162.8

Jul 2003

62.165.462.1

Aug 2003

62.162.862.0

Sep 2003

62.063.763.1

Oct 2003

62.164.963.7

Nov 2003

62.368.462.3

Dec 2003

62.265.761.7

Jan 2004

62.363.160.9

Feb 2004

62.365.858.1

Mar 2004

62.263.059.1

Apr 2004

62.363.460.4

May 2004

62.373.559.9

Jun 2004

62.469.961.9

Jul 2004

62.568.063.5

Aug 2004

62.465.463.1

Sep 2004

62.369.961.8

Oct 2004

62.369.062.4

Nov 2004

62.571.162.5

Dec 2004

62.468.760.8

Jan 2005

62.469.660.2

Feb 2005

62.469.560.5

Mar 2005

62.471.159.9

Apr 2005

62.771.261.6

May 2005

62.868.561.0

Jun 2005

62.769.462.1

Jul 2005

62.869.662.6

Aug 2005

62.967.763.0

Sep 2005

62.871.063.1

Oct 2005

62.867.462.9

Nov 2005

62.774.561.6

Dec 2005

62.872.260.5

Jan 2006

62.969.258.9

Feb 2006

63.070.459.1

Mar 2006

63.161.060.3

Apr 2006

63.063.460.3

May 2006

63.167.562.0

Jun 2006

63.170.664.9

Jul 2006

63.072.563.9

Aug 2006

63.170.162.1

Sep 2006

63.173.262.0

Oct 2006

63.373.961.8

Nov 2006

63.378.262.2

Dec 2006

63.475.160.4

Jan 2007

63.373.058.3

Feb 2007

63.369.461.0

Mar 2007

63.366.559.7

Apr 2007

63.066.759.5

May 2007

63.067.361.5

Jun 2007

63.066.063.1

Jul 2007

62.970.563.9

Aug 2007

62.768.963.5

Sep 2007

62.965.862.9

Oct 2007

62.773.061.9

Nov 2007

62.972.962.5

Dec 2007

62.773.060.9

Jan 2008

62.970.759.4

Feb 2008

62.864.159.2

Mar 2008

62.770.257.8

Apr 2008

62.771.659.1

May 2008

62.572.060.8

Jun 2008

62.465.560.3

Jul 2008

62.266.561.5

Aug 2008

62.065.861.4

Sep 2008

61.963.758.7

Oct 2008

61.767.558.6

Nov 2008

61.468.756.5

Dec 2008

61.068.758.6

Jan 2009

60.667.755.0

Feb 2009

60.365.756.2

Mar 2009

59.964.557.1

Apr 2009

59.863.855.4

May 2009

59.664.256.5

Jun 2009

59.460.256.9

Jul 2009

59.361.358.6

Aug 2009

59.159.557.5

Sep 2009

58.758.356.9

Oct 2009

58.560.657.0

Nov 2009

58.656.556.8

Dec 2009

58.359.956.1

Jan 2010

58.559.156.6

Feb 2010

58.563.857.2

Mar 2010

58.564.054.9

Apr 2010

58.761.255.1

May 2010

58.664.955.3

Jun 2010

58.563.057.2

Jul 2010

58.561.156.7

Aug 2010

58.659.356.6

Sep 2010

58.559.556.8

Oct 2010

58.354.256.9

Nov 2010

58.252.657.8

Dec 2010

58.358.456.6

Jan 2011

58.356.055.7

Feb 2011

58.457.957.0

Mar 2011

58.457.953.4

Apr 2011

58.460.354.3

May 2011

58.363.855.6

Jun 2011

58.265.255.0

Jul 2011

58.267.355.7

Aug 2011

58.364.154.5

Sep 2011

58.464.555.7

Oct 2011

58.460.554.9

Nov 2011

58.666.157.0

Dec 2011

58.663.255.3

Jan 2012

58.463.855.4

Feb 2012

58.566.856.9

Mar 2012

58.566.657.0

Apr 2012

58.464.060.1

May 2012

58.562.458.6

Jun 2012

58.664.458.7

Jul 2012

58.562.158.1

Aug 2012

58.459.658.5

Sep 2012

58.760.757.7

Oct 2012

58.863.558.4

Nov 2012

58.762.355.6

Dec 2012

58.760.055.3

Jan 2013

58.660.156.2

Feb 2013

58.660.956.0

Mar 2013

58.558.655.7

Apr 2013

58.665.555.1

May 2013

58.664.455.9

Jun 2013

58.664.155.6

Jul 2013

58.763.957.6

Aug 2013

58.763.359.3

Sep 2013

58.763.658.0

Oct 2013

58.363.056.2

Nov 2013

58.663.655.7

Dec 2013

58.764.155.2

Jan 2014

58.864.754.8

Feb 2014

58.762.155.7

Mar 2014

58.961.157.8

Apr 2014

58.960.057.4

May 2014

58.962.458.3

Jun 2014

59.062.459.7

Jul 2014

59.065.758.3

Aug 2014

59.064.256.8

Sep 2014

59.161.457.9

Oct 2014

59.366.958.1

Nov 2014

59.265.458.6

Dec 2014

59.366.857.8

Jan 2015

59.364.555.1

Feb 2015

59.263.056.9

Mar 2015

59.266.057.9

Apr 2015

59.364.259.0

May 2015

59.460.058.7

Jun 2015

59.461.459.6

Jul 2015

59.359.860.3

Aug 2015

59.458.660.3

Sep 2015

59.261.258.8

Oct 2015

59.364.760.5

Nov 2015

59.462.760.4

Dec 2015

59.669.260.7

Jan 2016

59.765.859.6

Feb 2016

59.866.257.4

Mar 2016

59.869.058.0

Apr 2016

59.763.858.7

May 2016

59.766.360.9

Jun 2016

59.766.361.7

Jul 2016

59.866.361.6

Aug 2016

59.862.260.7

Sep 2016

59.762.061.0

Oct 2016

59.766.760.5

Nov 2016

59.766.360.3

Dec 2016

59.767.861.6

Jan 2017

59.965.959.6

Feb 2017

60.058.761.0

Mar 2017

60.263.564.9

Apr 2017

60.258.764.1

May 2017

60.163.561.5

Jun 2017

60.164.363.2

Jul 2017

60.260.463.2

Aug 2017

60.161.761.9

Sep 2017

60.463.061.9

Oct 2017

60.165.463.2

Nov 2017

60.167.162.6

Dec 2017

60.163.861.8

Jan 2018

60.263.562.5

Feb 2018

60.463.762.2

Mar 2018

60.463.961.9

Apr 2018

60.464.762.6

May 2018

60.563.662.1

Jun 2018

60.461.763.9

Jul 2018

60.563.663.8

Aug 2018

60.363.963.0

Sep 2018

60.465.362.9

Oct 2018

60.564.663.6

Nov 2018

60.569.462.5

Dec 2018

60.672.064.2

Jan 2019

60.676.062.6

Feb 2019

60.871.162.9

Mar 2019

60.767.461.9

Apr 2019

60.668.462.4

May 2019

60.664.064.2

Jun 2019

60.764.164.4

Jul 2019

60.862.764.8

Aug 2019

60.860.465.2

Sep 2019

60.960.563.8

Oct 2019

60.966.963.3

Nov 2019

61.067.962.6

Dec 2019

61.068.564.5

Jan 2020

61.170.463.3

Feb 2020

61.267.663.7

Mar 2020

59.968.761.4

Apr 2020

51.365.650.4

May 2020

52.863.750.8

Jun 2020

54.763.253.7

Jul 2020

55.258.955.3

Aug 2020

56.555.954.4

Sep 2020

56.646.355.6

Oct 2020

57.450.757.4

Nov 2020

57.456.858.7

Dec 2020

57.464.659.3

Jan 2021

57.562.958.0

Feb 2021

57.662.558.7

Mar 2021

57.861.859.1

Apr 2021

57.960.159.9

May 2021

58.059.060.5

Jun 2021

58.060.161.5

Jul 2021

58.461.859.9

Aug 2021

58.566.559.0

Sep 2021

58.859.359.6

Oct 2021

58.961.459.6

Nov 2021

59.364.561.2

Dec 2021

59.566.763.0

Jan 2022

59.763.459.6

Feb 2022

59.962.260.2

Mar 2022

60.168.160.7

Apr 2022

60.064.363.4

May 2022

60.166.263.7

Jun 2022

59.961.864.5

Jul 2022

60.062.862.2

Aug 2022

60.165.761.3

Catching up on Recent BLS Activities

At BLS, we highly value feedback that can help us improve our economic statistics. Three groups regularly advise us on serving the needs of data users: the BLS Data Users Advisory Committee, the BLS Technical Advisory Committee, and the Federal Economic Statistics Advisory Committee.

I cannot overstate the value of these committees. They have given us truly wonderful ideas. If you want to join these meetings, they are open to the public. You can learn more about future meetings directly from the committee links provided above. I welcome and encourage you to attend.

As the Commissioner of BLS, my role at these meetings is to give an overview of all the new and exciting things happening at BLS. I want to share these updates directly with you, too.

Budgets for Fiscal Years 2022 and 2023

Let’s start with the budgets for fiscal years (FY) 2022 and 2023. For full information on the FY 2022 budget, please see the Department of Labor FY 2022 budget page, which has information on the budget for BLS and other agencies within the Department. You also can see the FY 2023 proposed budget, released on March 28, 2022.

In addition to funding our existing programs, the President’s FY 2023 proposed budget requests additional funds for several BLS initiatives.

We are requesting $14.5 million to continue developing a new National Longitudinal Survey of Youth cohort. We are developing plans for a new cohort called the National Longitudinal Survey of Youth 2026 (NLSY26). The NLSY26 will build upon our experience and analysis of two ongoing earlier cohorts:

  • NLSY79: A sample of 12,686 people who were born in the years 1957–64. The survey began in 1979, when sample members were ages 14–22. BLS has followed this cohort of late baby boomers for more than 40 years, recording their lives from their teens into their 50s and early 60s.
  • NLSY97: A sample of 8,984 people who were born in the years 1980–84. The survey began in 1997, when sample members were ages 12–17. BLS has followed this cohort for more than 20 years, and sample members are now in their mid-30s to early 40s.

As in previous National Longitudinal Surveys cohorts, BLS plans to ask NLSY26 cohort members a core set of questions on employment, training, education, income, assets, marital status, fertility, health, and occupational and geographic mobility. We also plan to administer cognitive and noncognitive assessments. We are considering other topics as we consult with stakeholders and subject matter experts in a range of fields.

The FY 2023 budget request for BLS also includes the following:

Expanding Our Data

Moving beyond the budget, one topic that’s getting a lot of attention lately is inflation. We’ve been measuring and reporting on inflation at BLS for over a century, and we are always looking for ways to improve our measurement. The National Academy of Sciences, Committee on National Statistics, recently completed a study that focuses on ways to improve the Consumer Price Index. The report provided 37 consensus recommendations on how BLS can adapt to the rapidly changing digital landscape to improve CPI methods. BLS staff are now reviewing the report and developing an action plan based on the committee’s recommendations. You can read my blog about the report and the full report itself.

BLS recently began publishing monthly and quarterly labor force measures for the American Indian and Alaska Native population on February 4, 2022. We have these data back to 2000. Previously, we published data for American Indians and Alaska Natives only annually. You can learn more about the new data in one of my February blog posts.

We now are evaluating whether we can begin publishing monthly and quarterly labor force data for the Native Hawaiian and Pacific Islander population and for detailed Asian groups. The populations of Native Hawaiians and Pacific Islanders and detailed Asian groups are relatively small, so we need to evaluate whether the Current Population Survey sample size is large enough to produce reliable monthly estimates for these groups. We currently publish annual data for Native Hawaiians and Pacific Islanders and detailed Asian groups in our report on Labor Force Characteristics by Race and Ethnicity.

Updates for Other Programs

I mentioned the National Longitudinal Surveys already, but the program is also doing other great work! In November 2021 we released data for the NLSY97 COVID-19 Supplement. We collected these data from February to May 2021. The survey asked questions about how the pandemic affected employment, health, and childcare. See our brief analysis of some of the COVID-19 data.

We’re also exploring how to measure the value of household production. BLS contracted with a vendor to consider how to use data from the American Time Use Survey on home production and impute the data to consumer units in the Consumer Expenditure Surveys. We expect to receive the recommendations by the end of the fiscal year.

Also in our Consumer Expenditure Surveys, we conducted an online survey test from November 2021 through January 2022 that will help us analyze alternative methods of collecting data. Response rates for most surveys have been declining for years. The COVID-19 pandemic also has made in-person interviewing less feasible. We are currently analyzing the results of the test to learn how we might reverse the trend of declining response rates and be ready for future events that might disrupt data collection.

Finally, we revamped the BLS Productivity program’s web space in April 2022. Information on labor productivity and total factor productivity is now available in a single cohesive and intuitive space. The new web space eliminates redundant material, improves consistency, and includes new material to fill information gaps. It truly enhances the customer experience!

I hope you find these updates useful and that they improve your experience with BLS data. We are always looking for opportunities to improve your experience with our gold standard economic statistics. Be on the lookout for more updates and improvements as we continuously adapt to meet your needs!

Employment Trends of Asians and Native Hawaiians and Other Pacific Islanders

May is Asian Pacific American Heritage Month, so let’s take a closer look at national employment statistics for Asians and for Native Hawaiians and Other Pacific Islanders. We’ll focus on how labor market conditions for these groups continue to recover from the effects of the COVID-19 pandemic.

BLS has been collecting data in the Current Population Survey on the labor market characteristics of people who identify their race as Asian or Native Hawaiian or Other Pacific Islander since 2003. Looking at historical data, the employment–population ratio—the percentage of the population that is employed—is generally higher for Asians and for Native Hawaiians or Other Pacific Islanders than the U.S. average. The ratio in 2019 was 62.3 percent for Asians and 66.2 percent for Native Hawaiians or Other Pacific Islanders, well above the national average of 60.8 percent. The ratios for all groups declined sharply in 2020 with the onset of the COVID-19 pandemic. Employment–population ratios had not yet fully recovered in 2021, but the ratios for Asians and Native Hawaiians or Other Pacific Islanders continued to be higher than the U.S. average. The greater likelihood of employment among Asians and Native Hawaiians or Other Pacific Islanders reflects the fact that larger shares of both groups are ages 25 to 54 than the overall population. People in this age range are more likely to be employed than people in younger and older age groups.

Employment–population ratios of the total population, Asians, and Native Hawaiians or Other Pacific Islanders, 2003–21 annual averages

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

The following chart shows how the labor market improved in 2021 compared to 2020 but remained below its 2019 pre-pandemic level. The employment–population ratio increased by 1.6 percentage points from 2020 to 2021 but remained 2.4 percentage points below its 2019 level. Similarly, this ratio increased by 3.3 percentage points for Asians and 1.4 percentage points for Native Hawaiians or Other Pacific Islanders in 2021. The ratio for Asians in 2021 was still 1.7 percentage points lower than in 2019, while the ratio for Native Hawaiians or Other Pacific Islanders was still 4.0 percentage points lower.

Employment–population ratios of the total population, Asians, and Native Hawaiians or Other Pacific Islanders, 2019–21 annual averages

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

The increase in the employment–population ratio between 2020 and 2021 varied for different groups within the Asian population. For example, this measure rose by 3.7 percentage points for Asian women and 2.9 percentage points for Asian men in 2021. The rise in the employment–population ratio was about twice as large for workers ages 16 to 24 (4.0 percentage points) and 25 to 54 (4.1 percentage points) than those age 55 and older (2.0 percentage points). Similarly, the increase in the percentage of foreign-born Asians (3.9 percentage points) who were employed was more than twice the increase for native-born Asians (1.8 percentage points). (Unfortunately, we can’t make these same comparisons for Native Hawaiians or Other Pacific Islanders because of their small sample size in the survey.)

Percentage point change in employment–population ratios for Asian groups, 2020 to 2021

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

Asian Americans trace their roots to many different distinct and culturally diverse peoples. We collect information on seven different Asian groups—Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, and Other Asian. As shown in the chart below, Asian Indians and Chinese are the largest groups of Asian Americans. Japanese, at 5 percent, represent the smallest share.

Percent distribution of the Asian population age 16 and older by detailed groups, 2021

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

Although the employment–population ratios for many of these groups increased in 2021, most remained below their 2019 pre-pandemic levels. After having the largest decline in their employment–population ratio from 2019 to 2020 (-9.2 percentage points), Vietnamese had the largest over-the-year gain in 2021 (7.1 percentage points) but remained 2.1 percentage points below the 2019 level. The employment–population ratio for Koreans in 2021, 5.9 percentage points below the 2019 level, had the largest decline over this 2-year period. The employment–population ratio of Asian Indians, however, had returned to the 2019 level in 2021.

Employment–population ratios of detailed Asian groups, 2019–21

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

This is just a sample of the information available on the labor force status of Asian Americans and Native Hawaiians and Other Pacific Islanders. Explore some of our other resources to expand your knowledge.

Employment–population ratios, 2003–21 annual averages
YearTotal populationAsianNative Hawaiian or Other Pacific Islander

2003

62.3%62.4%63.6%

2004

62.363.067.4

2005

62.763.470.2

2006

63.164.270.6

2007

63.064.369.4

2008

62.264.367.8

2009

59.361.261.8

2010

58.559.960.1

2011

58.460.062.2

2012

58.660.163.0

2013

58.661.262.9

2014

59.060.463.5

2015

59.360.462.8

2016

59.760.965.7

2017

60.161.562.9

2018

60.461.664.9

2019

60.862.366.2

2020

56.857.360.8

2021

58.460.662.2
Employment–population ratios, 2019–21 annual averages
YearTotal populationAsianNative Hawaiian or Other Pacific Islander

2019

60.8%62.3%66.2%

2020

56.857.360.8

2021

58.460.662.2
Percentage point change in employment–population ratios for Asian groups, 2020 to 2021
CharacteristicChange from 2020 to 202120202021

Total

3.357.360.6

Men

2.965.468.3

Women

3.750.253.9

Age

Ages 16 to 24

4.033.437.4

Ages 25 to 54

4.173.577.6

Age 55 and older

2.037.339.3

Country of birth

Foreign born

3.957.060.9

Native born

1.857.559.3
Percent distribution of the Asian population age 16 and older by detailed groups, 2021
Asian groupPercent distribution

Asian Indian

22.9%

Chinese

22.1

Other Asian

17.7

Filipino

14.9

Vietnamese

10.1

Korean

7.2

Japanese

5.0
Employment–population ratios of detailed Asian groups, 2019–21
Year201920202021

Asian Indian

66.6%63.2%66.6%

Filipino

63.955.860.6

Vietnamese

61.252.059.1

Other Asian

61.156.559.7

Chinese

60.456.659.7

Korean

60.355.654.4

Japanese

56.153.853.1

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Professional and business services

723,000

Transportation and warehousing

607,500

Retail trade

278,300

Financial activities

41,000

Information

26,000

Construction

4,000

Utilities

-10,000

Mining and logging

-86,000

Wholesale trade

-103,900

Manufacturing

-128,000

Other services

-291,000

Education and health services

-456,000

Government

-710,000

Leisure and hospitality

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

Jan 2006

4,964,000

Feb 2006

4,901,000

Mar 2006

4,918,000

Apr 2006

4,719,000

May 2006

4,635,000

Jun 2006

4,726,000

Jul 2006

4,862,000

Aug 2006

4,951,000

Sep 2006

4,666,000

Oct 2006

4,868,000

Nov 2006

4,818,000

Dec 2006

4,390,000

Jan 2007

4,506,000

Feb 2007

4,706,000

Mar 2007

4,565,000

Apr 2007

4,794,000

May 2007

4,968,000

Jun 2007

4,857,000

Jul 2007

4,737,000

Aug 2007

4,827,000

Sep 2007

4,750,000

Oct 2007

4,352,000

Nov 2007

4,648,000

Dec 2007

4,657,000

Jan 2008

4,846,000

Feb 2008

4,739,000

Mar 2008

4,718,000

Apr 2008

4,733,000

May 2008

4,851,000

Jun 2008

4,929,000

Jul 2008

5,023,000

Aug 2008

4,922,000

Sep 2008

5,153,000

Oct 2008

5,094,000

Nov 2008

5,421,000

Dec 2008

5,431,000

Jan 2009

5,708,000

Feb 2009

5,617,000

Mar 2009

5,807,000

Apr 2009

5,927,000

May 2009

5,986,000

Jun 2009

5,908,000

Jul 2009

6,003,000

Aug 2009

5,649,000

Sep 2009

5,949,000

Oct 2009

6,002,000

Nov 2009

5,998,000

Dec 2009

6,186,000

Jan 2010

5,942,000

Feb 2010

6,098,000

Mar 2010

5,993,000

Apr 2010

5,913,000

May 2010

5,824,000

Jun 2010

5,909,000

Jul 2010

5,895,000

Aug 2010

6,037,000

Sep 2010

6,270,000

Oct 2010

6,289,000

Nov 2010

6,182,000

Dec 2010

6,431,000

Jan 2011

6,472,000

Feb 2011

6,390,000

Mar 2011

6,527,000

Apr 2011

6,537,000

May 2011

6,289,000

Jun 2011

6,519,000

Jul 2011

6,513,000

Aug 2011

6,463,000

Sep 2011

6,262,000

Oct 2011

6,384,000

Nov 2011

6,538,000

Dec 2011

6,323,000

Jan 2012

6,343,000

Feb 2012

6,335,000

Mar 2012

6,302,000

Apr 2012

6,426,000

May 2012

6,309,000

Jun 2012

6,564,000

Jul 2012

6,516,000

Aug 2012

7,011,000

Sep 2012

6,817,000

Oct 2012

6,551,000

Nov 2012

6,833,000

Dec 2012

6,728,000

Jan 2013

6,637,000

Feb 2013

6,772,000

Mar 2013

6,670,000

Apr 2013

6,428,000

May 2013

6,726,000

Jun 2013

6,614,000

Jul 2013

6,526,000

Aug 2013

6,284,000

Sep 2013

6,119,000

Oct 2013

6,024,000

Nov 2013

5,754,000

Dec 2013

6,126,000

Jan 2014

6,360,000

Feb 2014

6,011,000

Mar 2014

6,174,000

Apr 2014

6,207,000

May 2014

6,553,000

Jun 2014

6,207,000

Jul 2014

6,264,000

Aug 2014

6,376,000

Sep 2014

6,326,000

Oct 2014

6,431,000

Nov 2014

6,558,000

Dec 2014

6,406,000

Jan 2015

6,300,000

Feb 2015

6,503,000

Mar 2015

6,355,000

Apr 2015

6,221,000

May 2015

6,051,000

Jun 2015

6,130,000

Jul 2015

6,097,000

Aug 2015

5,890,000

Sep 2015

5,868,000

Oct 2015

5,997,000

Nov 2015

5,649,000

Dec 2015

5,909,000

Jan 2016

6,006,000

Feb 2016

5,927,000

Mar 2016

5,730,000

Apr 2016

5,812,000

May 2016

5,962,000

Jun 2016

5,590,000

Jul 2016

5,906,000

Aug 2016

5,752,000

Sep 2016

6,017,000

Oct 2016

5,948,000

Nov 2016

5,864,000

Dec 2016

5,668,000

Jan 2017

5,758,000

Feb 2017

5,653,000

Mar 2017

5,758,000

Apr 2017

5,708,000

May 2017

5,465,000

Jun 2017

5,277,000

Jul 2017

5,425,000

Aug 2017

5,734,000

Sep 2017

5,637,000

Oct 2017

5,293,000

Nov 2017

5,219,000

Dec 2017

5,275,000

Jan 2018

5,191,000

Feb 2018

5,169,000

Mar 2018

5,044,000

Apr 2018

5,163,000

May 2018

5,188,000

Jun 2018

5,204,000

Jul 2018

5,195,000

Aug 2018

5,413,000

Sep 2018

5,288,000

Oct 2018

5,408,000

Nov 2018

5,398,000

Dec 2018

5,320,000

Jan 2019

5,262,000

Feb 2019

5,216,000

Mar 2019

5,136,000

Apr 2019

5,107,000

May 2019

4,994,000

Jun 2019

5,272,000

Jul 2019

4,999,000

Aug 2019

5,212,000

Sep 2019

4,852,000

Oct 2019

4,778,000

Nov 2019

4,849,000

Dec 2019

4,839,000

Jan 2020

4,937,000

Feb 2020

4,996,000

Mar 2020

5,462,000

Apr 2020

9,921,000

May 2020

8,916,000

Jun 2020

8,182,000

Jul 2020

7,712,000

Aug 2020

7,070,000

Sep 2020

7,194,000

Oct 2020

6,685,000

Nov 2020

7,120,000

Dec 2020

7,277,000

Jan 2021

6,956,000

Feb 2021

6,923,000

Mar 2021

6,822,000

Apr 2021

6,628,000

May 2021

6,583,000

Jun 2021

6,422,000

Jul 2021

6,529,000

Aug 2021

5,701,000

Sep 2021

5,918,000

Oct 2021

5,935,000

Nov 2021

5,819,000

Dec 2021

5,713,000

Jan 2022

5,704,000

Feb 2022

5,355,000

Mar 2022

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

May 2007

100.0

Jun 2007

100.3

Jul 2007

100.1

Aug 2007

100.0

Sep 2007

100.0

Oct 2007

99.8

Nov 2007

100.1

Dec 2007

100.2

Jan 2008

100.2

Feb 2008

100.1

Mar 2008

100.3

Apr 2008

99.5

May 2008

99.6

Jun 2008

99.5

Jul 2008

99.0

Aug 2008

98.7

Sep 2008

98.1

Oct 2008

97.6

Nov 2008

96.7

Dec 2008

95.6

Jan 2009

95.1

Feb 2009

94.5

Mar 2009

93.3

Apr 2009

92.6

May 2009

92.4

Jun 2009

91.7

Jul 2009

91.8

Aug 2009

91.6

Sep 2009

91.7

Oct 2009

91.2

Nov 2009

91.5

Dec 2009

91.3

Jan 2010

91.9

Feb 2010

91.0

Mar 2010

91.6

Apr 2010

92.1

May 2010

92.2

Jun 2010

92.3

Jul 2010

92.3

Aug 2010

92.7

Sep 2010

93.1

Oct 2010

93.3

Nov 2010

93.1

Dec 2010

93.5

Jan 2011

93.2

Feb 2011

93.7

Mar 2011

93.9

Apr 2011

94.5

May 2011

94.3

Jun 2011

94.5

Jul 2011

94.9

Aug 2011

94.8

Sep 2011

95.3

Oct 2011

95.5

Nov 2011

95.6

Dec 2011

95.8

Jan 2012

96.4

Feb 2012

96.6

Mar 2012

96.6

Apr 2012

96.9

May 2012

96.7

Jun 2012

96.8

Jul 2012

96.9

Aug 2012

97.1

Sep 2012

97.2

Oct 2012

97.4

Nov 2012

97.5

Dec 2012

98.0

Jan 2013

97.9

Feb 2013

98.4

Mar 2013

98.6

Apr 2013

98.4

May 2013

98.9

Jun 2013

99.1

Jul 2013

98.9

Aug 2013

99.4

Sep 2013

99.3

Oct 2013

99.5

Nov 2013

100.0

Dec 2013

99.8

Jan 2014

99.9

Feb 2014

99.8

Mar 2014

100.6

Apr 2014

100.8

May 2014

101.1

Jun 2014

101.3

Jul 2014

101.5

Aug 2014

102.0

Sep 2014

101.9

Oct 2014

102.4

Nov 2014

102.6

Dec 2014

102.9

Jan 2015

102.7

Feb 2015

103.2

Mar 2015

103.0

Apr 2015

103.2

May 2015

103.5

Jun 2015

103.7

Jul 2015

103.9

Aug 2015

104.0

Sep 2015

104.1

Oct 2015

104.7

Nov 2015

104.6

Dec 2015

104.8

Jan 2016

105.2

Feb 2016

104.7

Mar 2016

104.9

Apr 2016

105.1

May 2016

105.1

Jun 2016

105.3

Jul 2016

105.6

Aug 2016

105.4

Sep 2016

105.9

Oct 2016

106.0

Nov 2016

106.2

Dec 2016

106.3

Jan 2017

106.5

Feb 2017

106.3

Mar 2017

106.5

Apr 2017

106.9

May 2017

107.1

Jun 2017

107.3

Jul 2017

107.4

Aug 2017

107.6

Sep 2017

107.4

Oct 2017

107.8

Nov 2017

108.2

Dec 2017

108.4

Jan 2018

108.2

Feb 2018

108.8

Mar 2018

109.0

Apr 2018

109.2

May 2018

109.4

Jun 2018

109.6

Jul 2018

109.6

Aug 2018

109.8

Sep 2018

109.9

Oct 2018

110.0

Nov 2018

109.8

Dec 2018

110.3

Jan 2019

110.5

Feb 2019

110.2

Mar 2019

110.7

Apr 2019

110.6

May 2019

110.6

Jun 2019

110.7

Jul 2019

110.9

Aug 2019

111.0

Sep 2019

111.0

Oct 2019

111.1

Nov 2019

111.0

Dec 2019

111.1

Jan 2020

111.4

Feb 2020

111.9

Mar 2020

109.7

Apr 2020

93.2

May 2020

97.3

Jun 2020

101.0

Jul 2020

102.1

Aug 2020

103.4

Sep 2020

104.6

Oct 2020

105.6

Nov 2020

105.6

Dec 2020

105.2

Jan 2021

106.5

Feb 2021

105.9

Mar 2021

107.4

Apr 2021

107.6

May 2021

107.9

Jun 2021

108.0

Jul 2021

108.6

Aug 2021

108.7

Sep 2021

109.4

Oct 2021

110.0

Nov 2021

110.5

Dec 2021

111.0

Jan 2022

110.8

Feb 2022

111.8

Mar 2022

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

Jan 2019

4.7%3.8%3.7%

Feb 2019

4.53.83.8

Mar 2019

4.63.83.7

Apr 2019

4.64.03.8

May 2019

4.63.83.7

Jun 2019

4.53.83.7

Jul 2019

4.53.93.9

Aug 2019

4.53.93.7

Sep 2019

4.53.93.8

Oct 2019

4.73.83.7

Nov 2019

4.43.93.7

Dec 2019

4.33.93.8

Jan 2020

4.53.93.8

Feb 2020

4.44.03.8

Mar 2020

3.83.510.8

Apr 2020

3.53.18.9

May 2020

3.96.13.6

Jun 2020

4.25.43.8

Jul 2020

4.54.53.7

Aug 2020

4.34.33.4

Sep 2020

4.44.23.6

Oct 2020

4.64.33.7

Nov 2020

4.64.14.0

Dec 2020

4.64.04.0

Jan 2021

4.84.03.6

Feb 2021

5.24.23.8

Mar 2021

5.54.33.8

Apr 2021

6.04.24.0

May 2021

6.24.23.8

Jun 2021

6.34.44.0

Jul 2021

6.94.54.0

Aug 2021

6.74.34.0

Sep 2021

6.84.44.1

Oct 2021

7.04.44.0

Nov 2021

6.84.54.2

Dec 2021

7.14.34.1

Jan 2022

7.04.34.0

Feb 2022

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

Jan 2019

82.5%89.3%75.8%

Feb 2019

82.589.475.8

Mar 2019

82.589.675.5

Apr 2019

82.389.275.5

May 2019

82.288.975.7

Jun 2019

82.288.875.9

Jul 2019

82.188.975.4

Aug 2019

82.689.076.3

Sep 2019

82.789.276.4

Oct 2019

82.889.176.7

Nov 2019

82.889.276.6

Dec 2019

82.989.176.8

Jan 2020

83.189.376.9

Feb 2020

83.089.276.9

Mar 2020

82.589.076.1

Apr 2020

79.986.473.5

May 2020

80.687.274.3

Jun 2020

81.587.875.3

Jul 2020

81.287.575.1

Aug 2020

81.487.974.9

Sep 2020

81.087.774.4

Oct 2020

81.287.874.8

Nov 2020

80.987.374.6

Dec 2020

81.087.474.7

Jan 2021

81.187.674.7

Feb 2021

81.287.674.9

Mar 2021

81.387.675.2

Apr 2021

81.487.975.1

May 2021

81.487.975.0

Jun 2021

81.788.175.4

Jul 2021

81.988.375.6

Aug 2021

81.888.375.4

Sep 2021

81.688.275.3

Oct 2021

81.788.175.4

Nov 2021

81.988.275.7

Dec 2021

81.988.075.9

Jan 2022

82.088.276.0

Feb 2022

82.288.875.8

Mar 2022

82.588.776.5

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