Topic Archives: Beyond the Numbers

Why This Counts: Measuring Industry Productivity

At BLS, productivity is the economic statistic that describes the efficiency of production. The productivity statistics you hear about most often in the news are for the entire U.S. economy. But there’s more to the productivity story than just the overall numbers. The economy is made up of hundreds of industries, and each one works in a different way. Productivity data for each industry help us understand how specific types of production have changed over time. Let’s look at a few specific industries to see how labor productivity data can enhance our understanding of their unique production systems.

General Freight Trucking: Technological Innovations

Economic conditions in the general freight trucking industry closely mirror the health of the overall economy. During the 2007–09 recession, both output and hours worked fell dramatically in trucking. Because employment and spending were down nationwide, there was less demand for the transportation of all kinds of goods. After the recession ended, output and hours in trucking picked back up. Output reached prerecession levels by 2014, but in 2018 hours worked were still slightly below their 2007 level.

Dividing output by hours worked yields labor productivity. Because output in trucking has grown faster than hours during the recovery from the recession, labor productivity has increased. This helps us understand the nature of operations in general freight trucking. Innovative technologies such as communications systems, mapping software, and truck-based sensors and monitors known as “telematics” have improved transportation efficiency. These systems allow deliveries to be planned more efficiently with fewer delays, allowing more freight to be delivered without an equivalent increase in worker hours.

General freight trucking, average yearly percent change in output, hours worked, and productivity from 2007 to 2018

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

Travel Agencies: Digital Transformation

Another industry that has changed the way it operates is travel agencies. Since 2000, output has increased substantially, while hours fell from 2000 to 2010 and have increased only slightly since then. The major transformation for travel agencies has been the Internet. Online tools have allowed clients to make travel reservations with far less help from workers. This increase in efficiency is reflected in the industry’s labor productivity, which has more than tripled from 2000 to 2017.

Travel agencies, average yearly percent change in output, hours worked, and productivity from 2000 to 2017

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

Supermarkets: Incremental Change

Changes in other industries have been more subtle. Supermarkets are a particularly competitive industry, and firms employ a large number of workers to maintain high levels of customer service. Managing inventories, stocking shelves, checking out merchandise, and staffing specialty stations are all tasks that supermarkets continue to need. But even in supermarkets, productivity has been increasing since 2009, as output has grown faster than worker hours. To continue growing sales with lower costs, many firms in this industry have relied more on labor-saving technology, such as self-checkout machines. This technology increases efficiency by allowing supermarkets to process more transactions with less help from workers.

Supermarkets, average yearly percent change in output, hours worked, and productivity from 2009 to 2018

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

Cut and Sew Apparel Manufacturing: Establishment Turnover

Productivity declines also can show the changing nature of work. Cut and sew apparel manufacturing has seen much of its production move outside the United States. In 2018, U.S. apparel manufacturers produced less than 15 percent of the output they produced in 1997. Although worker hours also have declined, they have not dropped as much as output, leading to a decline in labor productivity. This indicates a shift over time in the nature of the average apparel manufacturer. While many large establishments moved overseas in search of cheaper labor, the remaining domestic apparel manufacturing establishments are on average smaller and more specialized, requiring more labor-intensive work.

Cut and sew apparel manufacturing, average yearly percent change in output, hours worked, and productivity from 1997 to 2018

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

To Learn More

BLS industry productivity data help us study the efficiencies of economic activities. Historical trends in productivity provide an important window into each industry’s working conditions, competitiveness, contribution to the economy, and potential for future growth. These data are used by investors, business leaders, jobseekers, researchers, and government decision makers. We have annual labor productivity measures for over 275 detailed industries.

To dive into the data for yourself, check out the BLS webpages on labor productivity. You also can see productivity data in a brand new way using our industry productivity viewer! Even more specialized industry data are on our webpages for hospitals, construction industries, elementary and secondary schools, and urban transit systems. We also have a recent article on productivity in grocery stores.

Average yearly percent change in output, hours worked, and productivity in selected industries
IndustryOutputHours workedProductivity

General freight trucking, 2007 to 2018

1.0%-0.1%1.2%

Travel agencies, 2000 to 2017

4.8-3.08.1

Supermarkets, 2009 to 2018

1.90.71.2

Cut and sew apparel manufacturing, 1997 to 2018

-9.4-7.5-2.1

Labor Day 2018 Fast Facts

About 92 percent of civilian workers with access to paid holidays receive Labor Day as a paid holiday. Before you set out for that long holiday weekend, take a moment to look at some fast facts we’ve compiled that show 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 62.9 percent in July. 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 3.9 percent in July. After 6 months at 4.1 percent, the rate has had offsetting movements in recent months. In May, the rate hit its lowest point, 3.8 percent, since April 2000.
  • In July, there were 1.4 million long-term unemployed (those jobless for 27 weeks or more). This represented 22.7 percent of the unemployed, down from a peak of 45.5 percent in April 2010 but still above the 16-percent share seen in late 2006.
  • Among the major worker groups, the unemployment rate for teenagers was 13.1 percent in July, while the rates were 3.4 percent for adult men and 3.7 percent for adult women. The unemployment rate was 6.6 percent for Blacks or African Americans, 4.5 percent for Hispanics or Latinos, 3.1 percent for Asians, and 3.4 percent for Whites.

Job Openings

Pay and Benefits

  • Average weekly earnings rose by 3.0 percent between July 2017 and July 2018; adjusted for inflation, real average weekly earnings are up 0.1 percent during this period.
  • Civilian compensation (wage and benefit) costs increased 2.8 percent between June 2017 and June 2018; adjusted for inflation, real compensation costs decreased 0.1 percent during this period.
  • 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.
  • In March 2018, civilian workers 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 1.1 percent in 2017, continuing the historically below-average pace seen since the Great Recession. Some industries had impressive growth, however, including wireless telecommunications carriers (11.1 percent) and electronics and appliance stores (9 percent).
  • Multifactor productivity growth in the private nonfarm business sector recovered in 2017, rising 0.9 percent after falling 0.6 percent in 2016. Labor input for multifactor productivity—measured using the combined effects of hours worked and labor composition—grew 2.0 percent in 2017, outpacing the long-term 1987–2017 growth for labor input by 0.5 percentage points.

Safety and Health

  • In 2017, 14.3 percent of all workers were exposed to hazardous contaminants. The use of personal protective equipment was required for 11.8 percent of workers.

Education

  • Occupations that typically require a bachelor’s degree for entry made up 21.5 percent of employment. 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.

Unionization

  • The union membership rate—the percent of wage and salary workers who were members of unions—was 10.7 percent in 2017, unchanged from 2016. In 1983, the first year for which comparable union data are available, the union membership rate was 20.1 percent.
  • Total employer compensation costs for union workers were $47.65 and for nonunion workers $32.87 per employee hour worked. The cost of benefits accounted for 40.4 percent of total compensation or $19.23 for union workers and 29.1 percent or $9.56 for nonunion workers.

Work Stoppages

  • In the first 7 months of 2018, there were 445,000 workers involved in work stoppages that began this year. This is the largest number of workers involved in stoppages since 2000, when 394,000 workers were involved. There have been 12 stoppages beginning this year, which surpassed the 7 recorded in all of 2017.

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.

Up and Down the Turnpike: The Power of State Estimates of Consumer Spending

You may know New Jersey for its Turnpike, its Parkway, and ribbons of highways crisscrossing the state, but new information shows that New Jersey households have fewer vehicles than the U.S. average. New Jersey households have an average of 1.4 vehicles, compared with an average of 1.8 vehicles nationwide.

This is just one of the tidbits we can glean from experimental state weights in the Consumer Expenditure Survey just released for New Jersey. Producing state estimates is part of our continuing plan to expand the use of data on consumer spending. The first available state weights are for New Jersey. We hope to release weights for more states in the coming months.

The survey is a nationwide household survey designed to find out how U.S. consumers spend their money. It is the only federal government survey that provides information on the full range of consumer spending, incomes, and demographic characteristics. One way BLS uses the consumer spending data is to create the market basket of goods and services tracked in the Consumer Price Index. Besides the spending information, the survey also collects the demographic characteristics of survey respondents. The new state weights allow us to examine what the typical New Jersey household looks like.

New Jersey looks similar to the United States as a whole, and even more similar to the New York metro area, which encompasses much of the northern part of New Jersey. One notable difference between New Jersey and other areas is the number of vehicles. Transportation in the Consumer Expenditure Survey includes vehicle purchases and gasoline and other car-related expenses. We would expect to see lower transportation spending in New Jersey compared with the nation because of fewer vehicles present in the state and other reasons.

A chart showing income and consumer spending levels in 2016 in New Jersey, the New York metro area, and the United States.

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

Now that we can produce statistically valid state estimates from the survey, we can answer all kinds of interesting questions. Many researchers look at different spending categories to examine public policies and to evaluate how certain decisions affect consumer behavior. Because we can now use the survey data to make estimates for certain states, researchers can explore these kinds of questions with more geographic detail. The chart below shows how New Jersey compares with the New York metro area and the nation in five of the broadest spending categories.

Average annual consumer spending in 2016 for selected categories in New Jersey, the New York metro area, and the United States.

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

Policymakers, researchers, and other data users have often asked for data about spending habits and income for states. Many times, household surveys just do not have enough sample to provide reliable estimates for all possible user needs. With our continuing improvements to the Consumer Expenditure Survey, we are learning which states provide enough responses for us to produce statistically valid state estimates. Once we create these weights for the states that can support them, data users will be able to explore a wider range of questions about consumer spending.

You can learn more from BLS economist Taylor Wilson’s article, “Consumer spending by state: BLS puts New Jersey to the test.”

Average annual income and selected expenditures, 2016
Measure New Jersey New York
Metropolitan
Statistical Area
United States
Income $89,927 $87,212 $74,069
Total expenditures 63,100 65,764 54,157
Transportation expenditures 7,295 6,828 8,755
Average consumer spending in selected categories, 2016
Geography Housing Food Transportation Healthcare Entertainment
New Jersey $23,617 $8,641 $7,295 $5,239 $2,097
New York Metropolitan Statistical Area 24,308 9,190 6,828 4,260 2,277
United States 17,774 7,203 8,755 4,373 2,497

Visualizing BLS Data to Improve Understanding

If a picture is worth a thousand words, what’s the value of a striking, cool chart or map of some BLS data? At the U.S. Bureau of Labor Statistics, we’re always thinking of better ways to help our users understand the information we produce. The global economy is complex, and the statistics to explain the economy can be complex too.

Data visualizations are one tool we use to present our data more clearly. What are data visualizations? They are any method of presenting numerical information visually—most commonly through charts and maps. Good data visualizations can improve understanding for all types of audiences, from students of all ages to experts with advanced degrees in economics, statistics, or other fields.

In recent years we’ve done more to include data visualizations in nearly all our publications. We have designed two of our publications to showcase data visualizations. One is The Economics Daily—or TED, as we call it. We publish a new edition of TED every business day, and we’ve done that since 1998. Each edition of TED typically includes a chart or map, sometimes two, with a few words to explain the data in the visualization.

Another publication geared toward data visualizations is Spotlight on Statistics. Spotlight tells a longer, more detailed story about a topic through a series of visualizations presented in a slideshow format. As with TED, Spotlight includes brief written analysis to explain more about the data.

Even our publications that feature mostly written analysis often include visualizations to tell a more complete story. Our flagship research journal, the Monthly Labor Review, has evolved a lot over its 100 years of publication to serve readers better; that evolution includes more and better data visualizations. Beyond the Numbers and BLS Reports often include visualizations as well.

We take pride in crafting our words carefully, but good data visualizations can complement the words. For example, during and after the Great Recession, the monthly Employment Situation news release has discussed the historically high levels of long-term unemployment. The number of long-term unemployed—those jobless 27 weeks or longer—has remained high years after the recession ended in June 2009. It’s one thing to read about long-term unemployment, but a good chart can tell the story even more clearly. long-term-unemployment

For an even broader perspective, we have a Spotlight on Statistics that examines long-term unemployment more fully.

Not only have we presented more data visualizations in recent years, but our visualizations also have gotten more sophisticated. A basic image can present information effectively. Take this simple map that shows the proportion of each state’s population age 16 or older that had a job in 2014. state-employment-population ratios

Now check out the interactive version of this map that we published in the March 9, 2015, edition of TED. When you hover over each state, more information pops up to show the state’s employment–population ratio in 2014 and how much it changed from 2013. When you hover over the items in the map legend, the states in each category light up more brightly to help you see the states with similar employment–population ratios. When you click on each state, you go to a webpage that provides even more information about the state’s labor market. Interactive features in our charts and maps give you the power to choose what information you want to see.

If you like the interactive features in our charts and maps, I think you’ll love the animation in some of our visualizations. Animation adds a time dimension to our data to let you see how measures change. For a great example of animation, see a TED we published last year that shows state unemployment rates before, during, and after the Great Recession.

The BLS website will feature even more data visualizations soon. Watch this space to learn more about them.

We share many of our data visualizations on Twitter, so follow us @BLS_gov. You also can sign up to receive email alerts for TED, Spotlight on Statistics, and our other publications.

And if you have created a great visualization of BLS data, please share it with us and the readers of this blog!

Seeking an expert to speak about the labor market and economy?

If you’ve ever visited the Bureau of Labor Statistics website or seen a news story about unemployment, inflation, wages, or some other economic topic, you know that BLS collects and publishes a huge volume of statistics to help inform businesses, workers, policymakers, households, and journalists about labor market and economic conditions in the United States. You also probably know that BLS has many publications that provide analytical insights about the mountains of statistics BLS produces. These publications include hundreds of news releases issued each year from the BLS national office and our regional offices. We also publish the Monthly Labor Review, Beyond the Numbers, our daily feature The Economics Daily, Spotlight on Statistics, and more.

Even if you are an experienced user of BLS data and publications, you may not know about another valuable service we provide: BLS can send an expert to speak at your conference, meeting, or classroom. If you are looking for a knowledgeable person to provide informative presentations about the U.S. labor market and economy, see our BLS Speakers page. Staff from our national office and our eight regional offices are happy to speak about such topics as the following examples:

  • How the government measures unemployment
  • Trends in labor force participation and long-term unemployment
  • How BLS calculates consumer, producer, and import and export prices
  • How many hours Americans work and how they spend their time outside of work
  • How local labor markets fared during and after the 2007–2009 recession
  • Trends in pay and benefits
  • Trends in workplace injuries, illnesses, and deaths
  • What labor productivity can tell us about the U.S. economy

Our experts can cover many other topics besides these and even customize topics to meet your needs.

I frequently speak at events myself. For example, in mid-July, I had the pleasure of participating in a lively conference at my alma mater, the University of Wisconsin-Madison. The topic of the conference, organized by the Institute for Research on Poverty, was “Building Human Capital and Economic Potential.” My talk described the ways in which BLS statistics inform us about the labor market, reviewed our resources for researchers, and told participants how they can help us.

It certainly was great to be back in Madison, and my BLS colleagues and I always enjoy the talks we give around the country. So if you need a speaker, we’re at your service!