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Tag Archives: Regions and states

BLS at the Olympics

When you find yourself in a 16-day marathon on the sofa shouting “U-S-A, U-S-A” at every swimmer, weightlifter, and beach volleyball player, you may not see the relationship to the U.S. Bureau of Labor Statistics. But as you sprint through the pages of our website or add your likes to Twitter, you’ll begin to see how BLS has a stat for that.

Olympic symbol with five interlocking rings and BLS emblem

Uneven bars

As we head into the gymnastics venue, we notice one of the women’s apparatus reminds us of how we measure productivity. We use two factors to compute labor productivity—output and hours worked. Over the past decade, the “bars” for output and hours worked aren’t quite parallel, but they are definitely uneven; output grew a little faster than hours, leading to rising productivity.  The COVID-19 pandemic resulted in sharp drops in both output and hours, leaving productivity to maintain its steady climb. BLS productivity staff stick the landing by providing a series of quarterly charts to let you vault into all the details.

Labor productivity (output per hour), output, and hours worked indexes, nonfarm business, 2012 to 2021

Editor’s note: Data for this chart are available in our interactive chart packages.

Decathlon

You may not have to run, jump, and throw, but the fastest growing occupations from our annual employment projections represent a diversity of skills. A decathlon has 10 events, but we have so much Olympic spirit we want to show you the 12 fastest growing occupations. Half of these jobs are in the healthcare field, while a couple involve alternative forms of energy. And, of course, BLS is pleased to see statisticians and data scientists and mathematical science occupations make the list. While the “World’s Greatest Athlete” is decided at the track and field venue, our Employment Projections staff goes the extra mile (1,500 meters, actually) to identify where the jobs will be in the future.

Fastest growing occupations, projected, 2019–29

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

Swimming 4×100 medley relay

At the natatorium, we are here to witness one of the premier events of the Olympic Games, the swimming 4×100 medley relay. Four price indexes will each take a lap to demonstrate how they work together to provide a complete inflation picture. In the leadoff position is the Import Price Index, which rose 11.2 percent from June 2020 to June 2021—with fuel prices being one of the largest drivers. After touching the wall first, imports made way for the Producer Price Index, which rose 7.3 percent for the year ending in June. Price increases for a variety of goods drove this gain. The third leg belonged to the Export Price Index, which rose 16.8 percent over the past year, the largest gain among the quartet. Agricultural products were among the largest contributors to the increase in export prices. In the anchor position was the Consumer Price Index, freestyling with a 5.4-percent increase over the year, leading BLS to the gold medal. Among the largest increases over the past year were consumer prices for gasoline and for used cars and trucks.

Percent change in BLS price indexes, June 2020 to June 2021

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

Greco-Roman wrestling

We bypassed the freestyle wrestling venue to watch Greco-Roman wrestling. The difference between freestyle and Greco-Roman wrestling is that freestyle wrestlers can use their legs for both defensive and offensive moves, but Greco-Roman forbids any holds below the waist. Our Survey of Occupational Injuries and Illnesses reports on the part of the body where workplace injuries occur, and, just like Greco-Roman, many of those occur above the waist.

Among workplace injuries that resulted in time away from work, nearly two out of three affected parts of the body above the waist, with the greatest number related to the upper extremities (shoulder, arm, hand, and wrist).

Number of workplace injuries and illnesses requiring days away from work, by part of body, 2019

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

Among the most prevalent injuries to the upper extremities were sprains, strains, punctures, cuts, and burns.

Beach volleyball

This popular sport takes place out on the sandy beaches, with two athletes on each side battling for the gold. Let’s look at some popular beach volleyball spots around the United States and pair them with the unemployment rates by state and metropolitan area. Florida serves up the lowest unemployment rate among the four states we have selected, at 5.7 percent (not seasonally adjusted) in June. Miami had an unemployment rate of 6.2 percent in June—the lowest among the metro areas chosen. Receiving the serve, Hawaii’s rate stood at a 7.9 percent. They bumped it to their teammate Illinois, which also had a rate of 7.9 percent. California reached a little higher, with a rate of 8.0 percent.

Unemployment rates in selected beach volleyball states and metropolitan areas, June 2021, not seasonally adjusted

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

BLS heads to Tokyo

Just as the United States exports its athletes to Japan for the Olympic Games, the two countries are regular trading partners. The BLS International Price Program provides a monthly look at inflation for U.S. imports and exports. Among the data available are price changes based on where the imports come from and where the exports go. And yes, this includes data for Japan. While we’ve seen increases in many inflation measures in recent months, the data show more modest increases in prices of U.S. imports from Japan. Not so for U.S. exports to Japan, which increased 15.8 percent from June 2020 to June 2021. No, this does not represent the price of exporting our athletes; it mostly relates to sharp increases in the price of agricultural exports.

Percent change in U.S. import and export prices, June 2020 to June 2021

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

Whether it’s weightlifting or dressage or the new sports climbing activities, BLS is cheering on the U.S. Olympians and Paralympians in Japan. At the same time, we’ll still be keeping to our data release schedule. Find out what’s available from BLS during August and September and be sure to follow BLS on Twitter.

Fastest growing occupations, projected, 2019–29
OccupationProjected percent change

Wind turbine service technicians

60.7%

Nurse practitioners

52.4

Solar photovoltaic installers

50.5

Occupational therapy assistants

34.6

Statisticians

34.6

Home health and personal care aides

33.7

Physical therapist assistants

32.6

Medical and health services managers

31.5

Physician assistants

31.3

Information security analysts

31.2

Data scientists and mathematical science occupations, all other

30.9

Derrick operators, oil and gas

30.5
Percent change in BLS price indexes, June 2020 to June 2021
Price indexPercent change

Import Price Index

11.2%

Producer Price Index

7.3

Export Price Index

16.8

Consumer Price Index

5.4
Number of workplace injuries and illnesses requiring days away from work, by part of body, 2019
Part of bodyNumber

Upper extremities (shoulder, arm, hand, wrist)

284,860

Lower extremities (knee, ankle, foot)

216,850

Trunk

187,130

Multiple body parts

82,650

Head

79,620

Body systems

15,150

Neck

11,600

All other body parts

10,360
Unemployment rates in selected beach volleyball states and metropolitan areas, June 2021, not seasonally adjusted
State or metropolitan areaRate

States

Florida

5.7%

Hawaii

7.9

Illinois

7.9

California

8.0

Metropolitan areas

Miami

6.2

Honolulu

7.1

Chicago

8.5

Los Angeles

9.5
Percent change in U.S. import and export prices, June 2020 to June 2021
Price indexAll countriesJapan

Import prices

11.2%1.8%

Export prices

16.815.8

New Measures of How Widespread Employment Changes Are across States and Metro Areas

BLS recently began publishing a new set of measures on employment changes in states and metropolitan areas. For decades we have published monthly estimates of employment, hours, and earnings for each state and metro area. Our new measure summarizes how widespread employment increases or decreases are across all states or metro areas. We call this measure a diffusion index.

What’s a diffusion index? Let me explain how we create the measure.

Let’s say we’re creating a diffusion index for the 50 states and the District of Columbia. We start by assigning each state and D.C. a value depending on whether its employment decreased, stayed the same, or increased over the period we’re looking at.

  • The assigned value is 0 if employment decreased.
  • The assigned value is 50 if employment stayed the same.
  • The assigned value is 100 if employment increased.

The diffusion index is the average of those 51 values. To create a diffusion index for metro areas, we assign values of 0, 50, or 100 for each of 388 metro areas and then average those values. We calculate diffusion indexes for employment changes over 1 month, 3 months, 6 months, and 12 months.

Now that we understand the simple arithmetic for calculating diffusion indexes, what do they mean? An index greater than 50 means more states or metro areas had increasing employment over the period. An index below 50 means more states or metro areas had decreasing employment. At the extremes, an index of 0 means employment fell in all states or metro areas; an index of 100 means employment rose in all of them. A diffusion index of 50 doesn’t necessarily mean 50 percent of the states or areas had increasing employment and the other 50 percent had decreasing employment. It just means the same number of states or areas had increases and decreases, with any of the other states or areas having no change.

The chart below shows 3-month diffusion indexes for all states and metro areas. You can see how all states and nearly all metro areas had job losses during the worst of the 2007–09 recession. We see it again more recently with the downturn associated with the COVID-19 pandemic.

3-month diffusion indexes for all states and all metropolitan areas, 2007–20

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

Diffusion indexes aren’t a new analytical tool. We publish other diffusion indexes using national employment data that summarize how employment change is dispersed across industries. The Federal Reserve Bank of Philadelphia publishes diffusion indexes using a variety of data. The new BLS diffusion indexes summarize how employment is changing across geographic areas to give us another perspective of the labor market.

Keep a look out for the new data. We update the indexes each month in our public database.

3-month diffusion indexes for all states and all metropolitan areas
MonthAll statesAll metropolitan areas

Jan 2007

96.177.7

Feb 2007

84.372.2

Mar 2007

84.372.6

Apr 2007

74.559.1

May 2007

86.365.3

Jun 2007

69.661.2

Jul 2007

78.467.7

Aug 2007

74.561.2

Sep 2007

56.951.3

Oct 2007

62.753.2

Nov 2007

79.459.1

Dec 2007

80.463.0

Jan 2008

81.465.3

Feb 2008

78.464.0

Mar 2008

52.050.6

Apr 2008

41.236.2

May 2008

25.529.8

Jun 2008

23.535.4

Jul 2008

16.733.9

Aug 2008

16.729.8

Sep 2008

15.723.6

Oct 2008

7.817.8

Nov 2008

7.811.9

Dec 2008

3.910.1

Jan 2009

2.04.3

Feb 2009

2.03.9

Mar 2009

0.04.1

Apr 2009

0.03.6

May 2009

2.04.9

Jun 2009

3.911.7

Jul 2009

8.814.6

Aug 2009

4.914.0

Sep 2009

5.920.0

Oct 2009

16.728.0

Nov 2009

21.638.5

Dec 2009

19.638.1

Jan 2010

26.538.8

Feb 2010

18.636.0

Mar 2010

70.656.3

Apr 2010

94.174.6

May 2010

100.086.6

Jun 2010

98.079.0

Jul 2010

85.364.3

Aug 2010

35.342.4

Sep 2010

39.244.7

Oct 2010

70.663.7

Nov 2010

74.564.8

Dec 2010

88.273.7

Jan 2011

62.757.0

Feb 2011

76.561.9

Mar 2011

87.367.9

Apr 2011

98.075.5

May 2011

90.267.0

Jun 2011

80.456.4

Jul 2011

83.366.8

Aug 2011

82.472.3

Sep 2011

98.081.8

Oct 2011

82.464.8

Nov 2011

96.166.8

Dec 2011

82.463.1

Jan 2012

88.276.7

Feb 2012

97.178.9

Mar 2012

98.083.1

Apr 2012

96.175.9

May 2012

94.170.0

Jun 2012

70.658.1

Jul 2012

74.557.0

Aug 2012

77.564.4

Sep 2012

86.367.5

Oct 2012

97.176.7

Nov 2012

93.175.4

Dec 2012

90.273.7

Jan 2013

88.270.2

Feb 2013

94.179.5

Mar 2013

99.075.9

Apr 2013

87.375.0

May 2013

82.468.7

Jun 2013

82.468.4

Jul 2013

81.470.6

Aug 2013

94.176.4

Sep 2013

92.277.8

Oct 2013

90.277.8

Nov 2013

94.174.7

Dec 2013

81.473.2

Jan 2014

88.268.7

Feb 2014

80.466.5

Mar 2014

86.373.6

Apr 2014

96.182.0

May 2014

98.083.4

Jun 2014

96.183.5

Jul 2014

96.174.2

Aug 2014

92.274.5

Sep 2014

90.277.2

Oct 2014

98.079.9

Nov 2014

96.179.8

Dec 2014

98.081.8

Jan 2015

93.180.0

Feb 2015

84.374.5

Mar 2015

64.762.5

Apr 2015

74.565.1

May 2015

84.377.1

Jun 2015

84.378.2

Jul 2015

92.284.1

Aug 2015

80.474.5

Sep 2015

86.374.1

Oct 2015

88.275.9

Nov 2015

88.274.6

Dec 2015

88.273.2

Jan 2016

75.571.1

Feb 2016

81.472.4

Mar 2016

78.469.5

Apr 2016

86.377.1

May 2016

72.567.3

Jun 2016

55.957.7

Jul 2016

84.371.3

Aug 2016

86.376.2

Sep 2016

94.185.1

Oct 2016

68.666.9

Nov 2016

82.473.6

Dec 2016

78.464.7

Jan 2017

84.370.0

Feb 2017

79.468.9

Mar 2017

98.076.5

Apr 2017

88.272.0

May 2017

78.468.4

Jun 2017

91.269.6

Jul 2017

80.471.6

Aug 2017

91.275.6

Sep 2017

76.560.8

Oct 2017

80.473.8

Nov 2017

84.370.7

Dec 2017

91.273.8

Jan 2018

90.274.2

Feb 2018

96.180.2

Mar 2018

96.180.9

Apr 2018

86.372.9

May 2018

82.473.6

Jun 2018

94.176.7

Jul 2018

91.281.3

Aug 2018

94.177.2

Sep 2018

82.468.4

Oct 2018

94.172.8

Nov 2018

92.272.3

Dec 2018

88.267.9

Jan 2019

89.279.4

Feb 2019

84.373.3

Mar 2019

82.474.9

Apr 2019

61.856.4

May 2019

64.758.5

Jun 2019

66.755.4

Jul 2019

74.560.8

Aug 2019

80.467.1

Sep 2019

79.466.4

Oct 2019

70.660.3

Nov 2019

68.663.7

Dec 2019

74.567.9

Jan 2020

87.375.9

Feb 2020

86.371.8

Mar 2020

5.929.0

Apr 2020

0.00.0

May 2020

0.00.3

Jun 2020[p]

0.00.6

[p] preliminary

New State and Metropolitan Area Data from the Job Openings and Labor Turnover Survey

Soon after I became Commissioner, the top-notch BLS staff shared with me their vision to expand the Job Openings and Labor Turnover Survey (JOLTS). The JOLTS program publishes data each month on the number and rate of job openings, hires, and separations (broken out by quits, layoffs and discharges, and other separations). These data are available at the national level and for the four large geographic regions—Northeast, Midwest, South, and West.

That left a major data gap on labor demand, hires, and separations for states and metropolitan areas. BLS provides data on labor supply for states and metro areas each month from the Local Area Unemployment Statistics program. We also provide data on employment change in states and metro areas each month from the Current Employment Statistics survey. Employment change is the net effect of hires and separations, but it doesn’t show the underlying flow of job creation and destruction. Having better, timelier state and metro JOLTS data would provide a quicker signal about whether labor demand is accelerating or weakening in local economies.

About 2 months after the staff briefed me, the JOLTS program published experimental state estimates for the first time on May 24, 2019. We have been updating those estimates on a quarterly basis since then. We use a statistical model to help us produce the most current state estimates. We then improve those estimates during an annual benchmark process by taking advantage of data available from the Quarterly Census of Employment and Wages. The JOLTS program is well on its way to moving these state estimates into its official, monthly data stream. Look for that to happen in the second half of 2021!

The President’s proposed budget for fiscal year 2021 includes three improvements to the JOLTS program.

  • Expand the sample to support direct sample-based estimates for each state.
  • Accelerate the review and publication of the estimates.
  • Add questions to provide more information about job openings, hires, and separations.

If funded, this proposal would allow BLS to improve the data quality available from the current JOLTS state estimates. It also would let us add very broad industry detail for each state and more industry detail at the national level.

The proposed larger sample size may also let us produce model-assisted JOLTS estimates for many metro areas. To demonstrate this potential, the JOLTS team produced a one-time set of research estimates for the 18 largest metropolitan statistical areas, those with 1.5 million or more employees. These research estimates show the potential for data that would be available regularly with a larger JOLTS sample. I encourage you to explore this exciting new research series and let us know what you think.

Number of unemployed per job opening in the United States and four large metropolitan areas, 2007–19

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

This is just one example of the excellent work I see at BLS every day. The BLS staff are consummate professionals who continue to do outstanding work even in the most trying of times. The entire BLS staff has been teleworking now for several months due to COVID-19, and every program continues to produce high quality data on schedule! Even in these extraordinary circumstances, BLS professionals continue to innovate and find ways to improve quality and develop new gold standard data products to help the policymakers, businesses, and the public make better-informed decisions.

Number of unemployed per job opening in the United States and four large metropolitan areas
DateNew York-Newark-Jersey City, NY-NJ-PADallas-Fort Worth-Arlington, TXChicago-Naperville-Elgin, IL-IN-WILos Angeles-Long Beach-Anaheim, CAUnited States

Jan 2007

1.81.41.81.61.6

Feb 2007

1.81.41.91.61.6

Mar 2007

1.71.31.81.61.6

Apr 2007

1.61.11.61.51.4

May 2007

1.51.01.51.51.4

Jun 2007

1.51.11.61.41.4

Jul 2007

1.61.21.81.51.5

Aug 2007

1.71.21.91.51.5

Sep 2007

1.71.21.81.71.5

Oct 2007

1.61.11.71.81.5

Nov 2007

1.61.21.81.91.5

Dec 2007

1.71.21.91.91.6

Jan 2008

1.91.32.02.11.7

Feb 2008

2.11.32.22.21.8

Mar 2008

2.21.32.42.21.9

Apr 2008

2.11.22.22.01.8

May 2008

2.01.22.22.11.8

Jun 2008

1.91.22.42.51.9

Jul 2008

2.21.43.03.02.2

Aug 2008

2.31.73.13.52.4

Sep 2008

2.41.83.13.62.5

Oct 2008

2.51.93.04.02.6

Nov 2008

2.82.13.44.62.9

Dec 2008

3.12.43.95.93.3

Jan 2009

3.62.94.86.74.0

Feb 2009

4.43.25.57.34.6

Mar 2009

5.03.56.47.45.1

Apr 2009

5.03.66.77.35.3

May 2009

5.14.06.87.15.4

Jun 2009

5.14.67.26.85.6

Jul 2009

5.25.37.77.46.0

Aug 2009

5.15.67.97.76.2

Sep 2009

5.45.88.08.06.1

Oct 2009

5.95.37.87.85.8

Nov 2009

6.75.68.68.25.9

Dec 2009

7.15.69.58.36.2

Jan 2010

7.06.310.88.36.2

Feb 2010

7.06.410.37.56.2

Mar 2010

7.05.98.87.15.9

Apr 2010

6.55.17.86.75.4

May 2010

5.94.86.66.54.9

Jun 2010

5.05.16.26.74.8

Jul 2010

4.85.26.07.14.9

Aug 2010

4.75.46.27.54.9

Sep 2010

4.94.76.17.54.7

Oct 2010

4.64.25.27.14.5

Nov 2010

4.84.05.07.14.5

Dec 2010

5.34.15.17.14.6

Jan 2011

6.04.35.57.15.0

Feb 2011

6.14.25.76.84.9

Mar 2011

5.54.05.36.34.6

Apr 2011

5.03.85.15.84.2

May 2011

4.63.64.65.84.1

Jun 2011

4.53.74.55.64.0

Jul 2011

4.63.84.65.94.1

Aug 2011

4.53.84.96.04.0

Sep 2011

4.43.44.65.83.8

Oct 2011

4.23.14.25.63.6

Nov 2011

4.03.04.25.33.6

Dec 2011

4.23.04.85.53.7

Jan 2012

4.63.05.25.93.7

Feb 2012

5.33.04.86.23.7

Mar 2012

5.12.84.25.73.5

Apr 2012

4.22.43.65.03.3

May 2012

3.92.13.44.83.1

Jun 2012

3.92.13.64.63.1

Jul 2012

4.22.33.95.33.3

Aug 2012

4.02.43.95.23.4

Sep 2012

3.82.43.55.53.2

Oct 2012

3.72.13.25.03.0

Nov 2012

3.92.03.44.83.0

Dec 2012

4.02.03.75.13.2

Jan 2013

4.22.24.35.43.4

Feb 2013

4.22.14.15.43.4

Mar 2013

4.02.03.94.93.2

Apr 2013

3.51.93.54.12.9

May 2013

3.21.93.53.82.7

Jun 2013

3.22.13.63.62.7

Jul 2013

3.42.33.83.82.9

Aug 2013

3.42.33.73.92.9

Sep 2013

3.42.13.64.02.8

Oct 2013

3.22.03.33.92.5

Nov 2013

3.22.03.24.12.5

Dec 2013

3.22.03.34.22.6

Jan 2014

3.42.03.54.22.7

Feb 2014

3.41.93.53.72.7

Mar 2014

3.21.93.33.32.6

Apr 2014

2.81.72.62.82.2

May 2014

2.51.62.12.82.0

Jun 2014

2.41.62.02.81.9

Jul 2014

2.61.62.13.12.0

Aug 2014

2.61.62.12.91.9

Sep 2014

2.51.62.02.91.9

Oct 2014

2.31.51.92.71.7

Nov 2014

2.41.51.92.91.8

Dec 2014

2.51.31.92.91.8

Jan 2015

2.61.32.02.91.9

Feb 2015

2.51.31.92.61.8

Mar 2015

2.41.31.82.41.7

Apr 2015

2.21.21.62.21.6

May 2015

2.01.11.52.21.5

Jun 2015

1.91.01.62.31.5

Jul 2015

1.91.01.62.31.5

Aug 2015

1.90.91.62.31.5

Sep 2015

1.80.91.52.31.4

Oct 2015

1.70.81.52.01.3

Nov 2015

1.60.81.52.01.3

Dec 2015

1.60.81.51.91.4

Jan 2016

1.70.91.61.91.4

Feb 2016

1.80.81.61.71.5

Mar 2016

1.70.81.61.61.4

Apr 2016

1.60.71.61.61.3

May 2016

1.40.71.41.61.2

Jun 2016

1.40.81.41.61.3

Jul 2016

1.40.91.41.81.3

Aug 2016

1.50.91.51.91.4

Sep 2016

1.40.91.51.91.3

Oct 2016

1.30.91.51.71.3

Nov 2016

1.30.91.41.71.3

Dec 2016

1.30.91.51.71.3

Jan 2017

1.41.01.71.81.4

Feb 2017

1.51.01.71.81.4

Mar 2017

1.51.01.51.81.4

Apr 2017

1.30.91.41.61.2

May 2017

1.30.91.21.51.1

Jun 2017

1.31.01.21.41.1

Jul 2017

1.31.11.21.51.1

Aug 2017

1.41.11.21.61.1

Sep 2017

1.41.01.11.51.1

Oct 2017

1.31.01.01.31.0

Nov 2017

1.21.01.01.31.0

Dec 2017

1.21.01.11.31.0

Jan 2018

1.21.11.31.31.1

Feb 2018

1.21.11.31.21.1

Mar 2018

1.21.11.21.21.1

Apr 2018

1.11.01.11.11.0

May 2018

1.01.00.91.00.9

Jun 2018

1.00.90.81.10.9

Jul 2018

1.00.80.81.10.9

Aug 2018

1.00.80.91.20.9

Sep 2018

0.90.80.91.20.8

Oct 2018

0.90.80.81.10.8

Nov 2018

0.80.80.81.20.8

Dec 2018

0.90.70.81.30.8

Jan 2019

1.00.80.91.40.9

Feb 2019

1.10.81.01.40.9

Mar 2019

1.10.80.91.40.9

Apr 2019

1.00.70.91.10.8

May 2019

0.80.70.81.00.8

Jun 2019

0.80.60.80.90.8

Jul 2019

0.80.70.81.00.8

Aug 2019

0.80.80.91.10.9

Sep 2019

0.80.80.91.20.8

Oct 2019

0.80.80.81.10.8

Nov 2019

0.80.80.71.00.8

Dec 2019

0.80.80.71.00.8

State Productivity: A BLS Production

We have a guest blogger for this edition of Commissioner’s Corner. Jennifer Price is an economist in the Office of Productivity and Technology at the U.S. Bureau of Labor Statistics. She enjoys watching theatrical performances when she’s not working.

I recently had the pleasure of attending a high school play. The cast was composed of a male and female lead and at least a dozen supporting actors. The program listed the performers and acknowledged many other students, parents, teachers, and administrators. They all played some important role to bring the play to life—lighting, sound, painting props, sewing costumes, creating promotional materials, selling tickets, working concessions. All of these pieces came together harmoniously to make the performance a success.

Setting the Stage: New Measures of State Productivity

We can view the health of the nation’s economy through the same lens. Our diversified economy is made up of lead performers and supporting roles in the form of industries. Some industries contribute more heavily to growth in output or productivity, playing the star role. Other industries are supporting characters, contributing to a smaller, but necessary, share of growth. Our productivity program recently published a webpage that examines how industries contribute to the nation’s private business output and productivity growth.

We also can examine these roles geographically. Until recently, BLS productivity measures were only produced at the national level. Last June, BLS published experimental measures of state labor productivity for the private nonfarm business sector. These measures, which cover the period from 2007 to 2017, will help us learn more about productivity growth in each state and how each state contributes to national productivity trends.

Measuring productivity for all states allows us to credit the role played by each state, not just the total performance of the national economy or region. Just as each person, no matter how small their role, was necessary for the success of the school play, each state contributes to how we evaluate national or regional productivity. When we examine the contribution of each state to total productivity trends, we find that, like actors, no two states perform identically. Similar individual growth rates may have different impacts on the productivity of the nation or region. By analyzing state productivity trends over the long term, we learn more about regional business cycles, regional income inequality, and the role of local regulations and taxes on growth.

From 2007 to 2017, labor productivity changes ranged from a gain of 3.1 percent per year in North Dakota to a loss of 0.7 percent per year in Louisiana.

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

We estimate each state’s annual contribution to national or regional productivity growth by multiplying the state’s productivity growth rate by its average share of total current dollar national or regional output. The economic size of each state influences its contribution to national and regional estimates. From 2007 to 2017, California was our lead performer, with the largest contribution to national productivity growth. The state’s productivity grew 1.7 percent per year on average, and its large economy means it contributed more than one-fifth of the 1.0-percent growth in national labor productivity.

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

Supporting actors included Texas and New York. Making a cameo appearance was North Dakota; despite having the largest productivity growth rate, it ranked 28th in terms of its contribution to national productivity growth. Stars in each region included Illinois (Midwest), New York (Northeast), Texas (South), and California (West). Understudies—those states with the largest growth rates—were North Dakota (Midwest), Pennsylvania (Northeast), and Oklahoma (South). Oregon and Washington shared this role out West.

Second Act

For now, our new measures cover the private nonfarm sector for all 50 states and the District of Columbia from 2007 to 2017. These measures include output per hour, output, hours, unit labor costs, hourly compensation, and real hourly compensation. Our measures of labor productivity for states are experimental, meaning we’re still assessing them and considering ways to improve them. In the second act, we will be looking into producing state-level measures for more detailed sectors and industries.

For an encore performance, check out our state labor productivity page. We’d love to hear your feedback! Email comments to productivity@bls.gov.

Annual percent change in labor productivity in the private nonfarm sector, 2007–17
StateAnnual percent change

North Dakota

3.1

California

1.7

Oregon

1.7

Washington

1.7

Colorado

1.6

Oklahoma

1.6

Maryland

1.5

Montana

1.5

Pennsylvania

1.5

Massachusetts

1.4

New Mexico

1.4

Vermont

1.4

Idaho

1.3

Kansas

1.3

Nebraska

1.1

New Hampshire

1.1

South Carolina

1.1

Tennessee

1.1

Texas

1.1

West Virginia

1.1

Alabama

1.0

Hawaii

1.0

Kentucky

1.0

Minnesota

1.0

New York

1.0

Rhode Island

1.0

South Dakota

1.0

Virginia

1.0

Georgia

0.9

Arkansas

0.8

Missouri

0.8

Ohio

0.8

Utah

0.8

Illinois

0.7

North Carolina

0.7

Delaware

0.6

Florida

0.6

Iowa

0.6

Indiana

0.5

Mississippi

0.5

New Jersey

0.5

Wisconsin

0.5

Alaska

0.4

Arizona

0.4

District of Columbia

0.4

Michigan

0.4

Maine

0.3

Nevada

0.3

Wyoming

0.1

Connecticut

-0.5

Louisiana

-0.7
States with the largest contributions to national labor productivity, average annual percent change, 2007–17
StateState contribution to U.S. labor productivity

California

0.22

Texas

0.10

New York

0.08

Pennsylvania

0.06

Washington

0.04

Massachusetts

0.04

Illinois

0.03

New Data on Employment and Wages in U.S. Establishments with Foreign Ownership

Did you know that U.S. establishments at least partially owned by foreign companies employed 5.5 million U.S. workers in 2012? That was 5.0 percent of U.S. private-sector employment. The U.S. Bureau of Labor Statistics recently partnered with the Bureau of Economic Analysis to produce new data on foreign direct investment in the United States. These two agencies created a new, richer dataset on employment, wages, and occupations in U.S. establishments that have at least one foreign owner.

So how do we define foreign direct investment anyway? In the simplest sense, it is when a U.S. establishment has an owner from another country with at least a 10-percent stake. We consider any establishment that does not meet this threshold as domestically owned. The new data are more detailed than any data previously available on foreign direct investment in the United States. This first set of data is for 2012, but the agencies plan to work together to produce more recent data soon.

Nearly two-thirds of jobs in establishments with foreign ownership had European ownership (3.5 million jobs). The United Kingdom accounted for 874,000 of these jobs. Asia accounted for 17 percent (936,000 jobs) of jobs in U.S. establishments with foreign ownership. Canada accounted for 12 percent (671,000 jobs). The remaining world regions together accounted for less than 8 percent.

Now let’s look at how employment in establishments with foreign ownership breaks down within the United States. The map below shows the percent of private employment in establishments with foreign ownership in each state. South Carolina had the largest share of private employment in establishments with foreign ownership, 8.0 percent. Other states with large shares include New Hampshire, Michigan, Connecticut, New Jersey, and Indiana.

Map showing  each state's percent of private employment in establishments with foreign ownership, 2012

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

Each state’s percent of employment in establishments with foreign ownership depends in part on the industry mix in the state. The chart below shows the percent of each industry’s employment in establishments with foreign ownership. In mining, quarrying, and oil and gas extraction, 14.7 percent of employment is in establishments with foreign ownership. A large share of employment in Alaska is in this industry. Alaska’s share of employment in establishments with foreign ownership, 5.7 percent, is above the national average. Alaska’s vast energy resources may play a role in its share of employment in establishments with foreign ownership.

About 13.2 percent of all employees in manufacturing work in establishments with foreign ownership. Michigan has a large share of employment in manufacturing, and also a large share of employment in establishments with foreign ownership.

Chart showing percent of private employment in establishments with foreign ownership, by industry, 2012

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

Now let’s turn from employment to wages. The map below shows how wages in establishments with foreign ownership compare with wages in domestically owned establishments across the country. We make this comparison by calculating the ratio of what workers make in average wages in establishments with foreign ownership compared to the average wage in domestically owned establishments. Wage ratios greater than one mean the average for establishments with foreign ownership is higher than for domestically owned establishments. The U.S. wage ratio in 2012 was 1.57, and every state had a wage ratio greater than one. The highest wage ratio was in New York, at 1.98. At the other end of the spectrum, Vermont had a wage ratio of 1.05.

Map showing each state's ratio of average wages in establishments with foreign ownership to domestically owned establishments, 2012

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

Does this mean every establishment with foreign ownership pays higher wages than domestically owned establishments? Let’s analyze wage ratios by industry. We see that the health care and social assistance industry had a wage ratio of 0.86 in 2012. All other major industry groups had wage ratios of 1.00 or higher. The finance and insurance industry had a wage ratio of 1.82.

Want to know more about these data? See our Spotlight on Statistics, “A look at employment and wages in U.S. establishments with foreign ownership.”

Chart showing ratio of average wages in establishments with foreign ownership to domestically owned establishments, by industry, 2012

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

BLS and the Bureau of Economic Analysis hope to continue this interagency collaboration. Our goal is to merge and analyze more recent data from both agencies. When agencies work together to produce new datasets with little increase in cost to the public, all data users benefit. Producing accurate, objective, relevant, timely, and accessible products is the BLS mission. This collaboration to produce new relevant data allows us to improve our service to the American people.

Percent of private employment in establishments with foreign ownership, 2012
StateEmployment share

National

5.0%

Alabama

5.4

Alaska

5.7

Arizona

3.9

Arkansas

4.5

California

4.2

Colorado

4.6

Connecticut

6.5

Delaware

6.0

District of Columbia

3.4

Florida

3.6

Georgia

5.5

Hawaii

6.0

Idaho

2.9

Illinois

5.1

Indiana

6.4

Iowa

4.0

Kansas

5.7

Kentucky

6.2

Louisiana

3.9

Maine

6.1

Maryland

4.7

Massachusetts

6.3

Michigan

6.6

Minnesota

4.0

Mississippi

3.4

Missouri

4.0

Montana

1.8

Nebraska

3.6

Nevada

3.8

New Hampshire

6.9

New Jersey

6.5

New Mexico

3.0

New York

5.8

North Carolina

6.2

North Dakota

3.8

Ohio

5.3

Oklahoma

3.6

Oregon

3.4

Pennsylvania

5.5

Rhode Island

6.1

South Carolina

8.0

South Dakota

2.1

Tennessee

5.5

Texas

5.3

Utah

4.0

Vermont

3.7

Virginia

5.1

Washington

4.0

West Virginia

4.8

Wisconsin

3.5

Wyoming

3.8
Percent of private employment in establishments with foreign ownership, by industry, 2012
IndustryEmployment share

Mining, quarrying, and oil and gas extraction

14.7%

Manufacturing

13.2

Management of companies and enterprises

9.6

Wholesale trade

9.0

Information

7.8

Finance and insurance

7.5

Utilities

7.3

Transportation and warehousing

6.3

Administrative and waste services

6.0

Professional, scientific, and technical services

5.5

Total private

5.0

Retail trade

4.7

Real estate and rental and leasing

2.2

Construction

1.8

Accommodation and food services

1.6

Other services (except public administration)

1.3

Agriculture, forestry, fishing, and hunting

1.0

Health care and social assistance

0.9

Arts, entertainment, and recreation

0.7

Educational services

0.6
Ratio of average wages in establishments with foreign ownership to domestically owned establishments, 2012
StateWage ratio

National

1.57

Alabama

1.44

Alaska

1.63

Arizona

1.28

Arkansas

1.43

California

1.49

Colorado

1.53

Connecticut

1.53

Delaware

1.78

District of Columbia

1.08

Florida

1.52

Georgia

1.36

Hawaii

1.06

Idaho

1.30

Illinois

1.61

Indiana

1.56

Iowa

1.48

Kansas

1.56

Kentucky

1.36

Louisiana

1.67

Maine

1.26

Maryland

1.28

Massachusetts

1.46

Michigan

1.84

Minnesota

1.50

Mississippi

1.63

Missouri

1.55

Montana

1.63

Nebraska

1.35

Nevada

1.47

New Hampshire

1.39

New Jersey

1.64

New Mexico

1.22

New York

1.98

North Carolina

1.47

North Dakota

1.55

Ohio

1.49

Oklahoma

1.40

Oregon

1.41

Pennsylvania

1.43

Rhode Island

1.31

South Carolina

1.43

South Dakota

1.45

Tennessee

1.42

Texas

1.80

Utah

1.45

Vermont

1.05

Virginia

1.23

Washington

1.40

West Virginia

1.33

Wisconsin

1.38

Wyoming

1.72
Ratio of average wages in establishments with foreign ownership to domestically owned establishments, by industry, 2012
IndustryWage ratio

Finance and insurance

1.82

Construction

1.62

Total private

1.57

Accommodation and food services

1.51

Real estate and rental and leasing

1.50

Arts, entertainment, and recreation

1.45

Other services (except public administration)

1.44

Agriculture, forestry, fishing, and hunting

1.40

Wholesale trade

1.39

Professional, scientific, and technical services

1.39

Mining, quarrying, and oil and gas extraction

1.28

Management of companies and enterprises

1.23

Retail trade

1.20

Educational services

1.19

Manufacturing

1.18

Utilities

1.15

Administrative and waste services

1.13

Information

1.05

Transportation and warehousing

1.00

Health care and social assistance

0.86