Tag Archives: Labor market trends

Let’s Celebrate the Productive U.S. Workforce

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

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

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

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

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

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

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

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

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

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

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

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

Labor Day 2019 Fast Facts

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

Working

Working or Looking for Work

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

Not Working

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

Job Openings

Pay and Benefits

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

Productivity

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

Safety and Health

Unionization

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

Work Stoppages

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

Education

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

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

What is “Benchmarking” of Bureau of Labor Statistics Employment Data?

BLS has released the “preliminary benchmark” information for the Current Employment Statistics (CES) survey, the source of monthly information on jobs.

You know what a bench is

Image of a park bench

and you know what a mark is,

Image of a checkmark

but what pray tell is a benchmark? And what does this preliminary benchmark tell us?

So as not to bury the lead, I’ll let you know that this year’s preliminary estimate of the benchmark revision is a bit bigger than it has been in the last few years. Our preliminary estimate indicates a downward adjustment to March 2019 total nonfarm employment of 501,000. Still, that estimated revision is only -0.3 percent of nonfarm employment. In most years our monthly employment survey has done a good job at estimating the total number of payroll jobs. More details on that below. This year our survey estimates are off more than we would like. Our goal is to provide estimates that are excellent and not just good or pretty good, and that’s why we benchmark the survey data each year.

What is benchmarking and why do we do it?

The CES is a monthly survey of approximately 142,000 businesses and government agencies composed of approximately 689,000 individual worksites. As with all sample-based surveys, CES estimates are subject to sampling error. This means that while we work hard to ensure those 689,000 worksites represent all 10 million worksites in the country, sometimes our sample may not perfectly reflect all worksites. So the monthly CES estimates aren’t exactly the same as if we had counted employment from all 10 million worksites each month. To fix this problem, we “benchmark” the CES data to an actual count of all employees, information that’s only available several months after the initial CES data are published.

In essence, we produce employment information really quickly from a sample of employers, then anchor that information to a complete count of employment once a year.

The primary source of the CES sample is the BLS Quarterly Census of Employment and Wages (QCEW) program, which collects employment and wage data from states’ unemployment insurance tax systems. This is also the main source of the complete count of employment used in the benchmark process. QCEW data are typically available about 5 months after the end of each quarter.

Each year, we re-anchor the sample-based employment estimates to these full population counts for March of the prior year. This process—which we call benchmarking—improves the accuracy of the CES data. That’s because the population counts are not subject to the sampling and modeling errors that may occur with the CES monthly estimates. Since the CES data are re-anchored to March of the last year, CES estimates are typically revised from April of the year prior up to the March benchmark. Then estimates from the benchmark forward to December are revised to reflect the new March employment level.

We will publish the final benchmark revision in February 2020 and will incorporate revisions to data from April 2018 to December 2019. (Thus, we’re not showing a 2019 number in graph and table below). On August 21, BLS released a first look at what this revision will be—what we call the “preliminary benchmark.” This preliminary benchmark gives us an idea of what the revised nonfarm employment estimates for March 2019 will be.

The size of the national benchmark revision is a measure of the accuracy of the CES estimates, and we take pride that these revisions are typically small.

Chart showing differences in nonfarm employment after benchmarking, 2009–18

For total employment nationwide, the absolute annual benchmark revision has averaged about 0.2 percent over the past decade, with a range from −0.7 percent to +0.3 percent.

The following table shows the total payroll employment estimated from the CES before and after the benchmark over the past 10 years. For example, pre-benchmark employment for 2018 was 147.4 million; post-benchmark employment was also 147.4 million.

Nonfarm employment estimates before and after benchmarking, March 2009–March 2018
Year Level before benchmark Level after benchmark Difference Percent difference
2009 132,077,000 131,175,000 -902,000 –0.7
2010 128,958,000 128,584,000 -374,000 –0.3
2011 129,899,000 130,061,000 162,000 0.1
2012 132,081,000 132,505,000 424,000 0.3
2013 134,570,000 134,917,000 347,000 0.3
2014 137,147,000 137,214,000 67,000 <0.05
2015 140,298,000 140,099,000 -199,000 –0.1
2016 142,895,000 142,814,000 -81,000 –0.1
2017 144,940,000 145,078,000 138,000 0.1
2018 147,384,000 147,368,000 -16,000 <-0.05

The 2019 preliminary benchmark revision is following the same pattern, with an estimated difference of -0.3 percent. We provide this first look at the benchmark revision to give data users a sense of what we are seeing in the data. The final benchmark may be a little different—could be higher, could be lower. But based on recent experience, we are confident the benchmark released next February will show only a moderate difference from what we’ve been publishing each month and will validate the accuracy of our monthly CES estimates.

Want to know more? See our Current Employment Statistics webpage, send us an email, or call (202) 691-6555.

New State Data on Labor Productivity and Job Openings and Labor Turnover

While international trade has become increasingly important to our economy over the past 60 years, U.S. households and businesses continue to rely primarily on local markets for most goods and services. The products we create come from all over our country. Workers, businesses, and policymakers care deeply about the economy in our own backyards. That’s why BLS recently began publishing new data on labor productivity by state and, separately, on job openings and labor turnover by state.

State labor productivity

Our measures of labor productivity for states are still experimental, meaning we’re still assessing them and considering ways to improve them. These measures cover the private nonfarm sector for all 50 states and the District of Columbia from 2007 to 2017. They show that labor productivity growth varies a lot from state to state. 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. In 2017, labor productivity grew fastest in Montana (2.0 percent), West Virginia (1.9 percent), California (1.8 percent), and Hawaii (1.7 percent). You can get the complete dataset from our state labor productivity page.

U.S. map showing productivity growth in the private nonfarm sector in each state from 2007 to 2017

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

We construct these state measures from data published by several BLS programs and by our colleagues at the Bureau of Economic Analysis. A recent Monthly Labor Review article, “BLS publishes experimental state-level labor productivity measures,” explains the data and the methods for putting them all together. The article also highlights how you might use these new state data. We’re happy to have your feedback on these new measures. Just send us an email.

State job openings and labor turnover

We also have new data on job openings, hiring, and separations by state. Data from the Job Openings and Labor Turnover Survey are widely used by economic policymakers and others who want to understand the job flows that lead to net changes in employment. We have these data back to December 2000 and update them every month for the nation and the four broad census regions. Now we have them for all states and the District of Columbia too. These state estimates are available from February 2001 through December 2018 for the total nonfarm sector.

Many of you have told us you want more geographic details about job openings and turnover. To make sense of data on job openings, for example, it helps to know where the jobs are. The survey sample size is designed to estimate job openings and turnover for major industries only at the national and regional levels. For several years we have researched ways to produce model-assisted estimates for states. As with the state productivity data, these estimates are experimental. We plan to update the state estimates each quarter while we assess your feedback on the models and the usefulness of the data. We encourage you to send us your comments.

But wait, there’s more! We’ve updated the BLS Local Data App!

In previous blog posts, we’ve told you about our mobile app for customers who want to know more about local labor markets. This app now includes employment and wage data for detailed industries and occupations. (It doesn’t yet have the new data on state productivity, job openings, and turnover.)

Interested in local data for a particular industry or occupation? The latest version allows you to quickly search or use the built-in industry and occupational lists. Want to know which industry employs the most workers in your area or which occupation pays the highest? The updated app allows you to sort the employment and wage data across groups of industries and occupations. You can still find data on unemployment rates and total employment. You also can find your state, metro area, or county by searching for a zip code or using your device’s current location.

These new data and features result from the continued partnership between BLS and the U.S. Department of Labor’s Office of the Chief Information Officer. Be on the lookout for more new features to be added in future releases.

Download the BLS Local Data app from the App Store or Google Play today!

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

Why This Counts: 10 Million U.S. Establishments for the First Time

In the third quarter of 2018, the number of establishments in the U.S. economy reached 10 million. This milestone is based on data from the Quarterly Census of Employment and Wages (QCEW), which uses administrative records to identify the number of establishments in our economy.

What is the QCEW?

The QCEW compiles quarterly reports of the Unemployment Insurance systems in each state, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. Every business with an employee, other than the owner, must register with the state where it has a business location. We call these locations establishments.

 Behind the number

Behind the 10 million establishments are some interesting facts about our labor market.

First, the U.S. labor market is dynamic

Roughly 200,000 establishments are new each quarter. That adds up to almost 800,000 new establishments each year. If we consider that we first hit the 9 million mark in third quarter 2007, you may wonder why we didn’t reach 10 million sooner.

Some establishments continue for long periods, while others close. In 2018, more than half of all private sector establishments were 10 years or older. And while the number of establishments grows in most years, during a recession fewer establishments open and more close. Openings and closings that mostly offset one another result in a pretty stable rate of change in the total number of establishments over time.

Line chart showing the number of establishments each quarter from 2001 to 2018

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

Second, most establishments are small

If we define small establishments as having fewer than 500 employees, 99.8 percent of all establishments in the U.S. economy are small. These employ 82.6 percent of workers and pay 73.5 percent of all wages, including bonuses.

Less than one-tenth of 1 percent of establishments have 1,000 employees or more, yet these establishment have an outsized impact. In first quarter 2018 they accounted for 11.0 percent of employment and 17.8 percent of total wages, far higher than their representation in our economy.

Chart showing the share of establishments, employment, and total wages by establishment size in the first quarter of 2018

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

Slicing the data a different way, we find that 62.5 percent of all establishments in first quarter 2018 had fewer than 5 employees. In fact, the five industries with the most establishments are all dominated by small establishments.

Services for the elderly and disabled is the industry with both the highest number of establishments and the highest number of small establishments. In first quarter 2018, it had 742,364 private establishments, and 97.1 percent of them had fewer than 5 employees. The industry office of physicians, except mental health ranks fifth in the U.S. economy in terms of the number of establishments, and 52.5 percent of them had fewer than 5 employees.

An interesting story about physicians’ offices

The real value of the QCEW data is in its fine level of detail. Drilling down, we find that in first quarter 2018 Los Angeles County had 10,360 establishments in offices of physicians, except mental health, ranking first in the U.S. economy.

However, the highest concentration of physicians’ offices is not in Los Angeles, but in Johnson County, Georgia. We use location quotients to measure the concentration of establishments in a geographic area. A location quotient greater than 1 means the industry has a greater concentration of establishments within the county than in the nation. With a location quotient of 5.0, Johnson County has five times the concentration of physicians’ offices than the nation.

Offices of physicians, except mental health, number of establishments and establishment location quotients in selected counties, first quarter 2018
County Number of Establishments Establishment location quotient
Johnson County, Georgia 14 5.0
Greenup County, Kentucky 40 3.2
Boyd County, Kentucky 103 3.1
Angelina County, Texas 107 2.8
Jefferson County, Texas 359 3.0
Los Angeles County, California 10,360 1.0

 

So, who uses the data?

The detail available in QCEW data is important to a range of users. In the private sector, commercial real estate brokers may use the data when deciding the best location for a new business. Small business owners may compare average weekly wages. Large corporations may use local data to develop geographic profiles and market studies.

In the public sector, local and regional economic development agencies use the data for planning and program development. Understanding the type and size of establishments can help them recruit and retain businesses and support workforce development investment. Disaster relief agencies use information on the size of establishments or the concentration in an area to determine risk and track recovery efforts. State governments and academic institutions use the data to study the health of regional economies.

Want to know more?

For this blog, we use private ownership data from first quarter 2018 to explore QCEW establishment size data. You can explore establishment size data using the QCEW Data Viewer.

For even more information, visit our QCEW page.

Number of establishments, 2001–18
Quarter Number of establishments
Q1 2001 7,925,541
Q2 2001 7,958,077
Q3 2001 8,008,006
Q4 2001 8,046,492
Q1 2002 8,042,613
Q2 2002 8,060,770
Q3 2002 8,124,227
Q4 2002 8,179,879
Q1 2003 8,188,261
Q2 2003 8,206,992
Q3 2003 8,239,152
Q4 2003 8,280,956
Q1 2004 8,298,175
Q2 2004 8,305,907
Q3 2004 8,389,106
Q4 2004 8,465,990
Q1 2005 8,478,533
Q2 2005 8,525,655
Q3 2005 8,613,899
Q4 2005 8,666,489
Q1 2006 8,690,719
Q2 2006 8,726,001
Q3 2006 8,816,751
Q4 2006 8,902,635
Q1 2007 8,862,947
Q2 2007 8,936,111
Q3 2007 9,014,197
Q4 2007 9,074,333
Q1 2008 9,028,884
Q2 2008 9,059,689
Q3 2008 9,108,151
Q4 2008 9,131,473
Q1 2009 8,967,310
Q2 2009 8,984,662
Q3 2009 9,020,598
Q4 2009 9,040,216
Q1 2010 8,925,889
Q2 2010 8,962,280
Q3 2010 9,014,193
Q4 2010 9,070,072
Q1 2011 8,989,800
Q2 2011 9,042,922
Q3 2011 9,104,661
Q4 2011 9,153,801
Q1 2012 9,006,016
Q2 2012 9,179,368
Q3 2012 9,128,346
Q4 2012 9,173,740
Q1 2013 9,107,736
Q2 2013 9,178,547
Q3 2013 9,241,547
Q4 2013 9,295,722
Q1 2014 9,288,442
Q2 2014 9,313,909
Q3 2014 9,380,061
Q4 2014 9,463,005
Q1 2015 9,414,823
Q2 2015 9,470,124
Q3 2015 9,561,224
Q4 2015 9,644,927
Q1 2016 9,601,391
Q2 2016 9,677,672
Q3 2016 9,758,568
Q4 2016 9,828,841
Q1 2017 9,718,391
Q2 2017 9,807,791
Q3 2017 9,871,253
Q4 2017 9,942,980
Q1 2018 9,910,520
Q2 2018 9,988,054
Q3 2018 10,065,152
Q4 2018 10,169,140
Percent of establishments, employment, and total wages by establishment size, first quarter 2018
Number of employees in establishment Percent of total establishments Percent of total employment Percent of total wages
1,000 or more 0.1% 11.0% 17.8%
500 to 999 0.1 6.4 8.7
Fewer than 500 99.8 82.6 73.5