Topic Archives: Monthly Labor Review

100 years after World War I: What’s the Labor Market Status of Our Veterans in 2018?

As we commemorate the 100th anniversary of the end of World War I — at the 11th hour on the 11th day of the 11th month of 1918 — we also want to honor our current veterans.

In honor of Veterans Day, here are our most up-to-date statistics about veterans:

  • In October 2018, 19.1 million men and women were veterans, accounting for about 8 percent of the civilian noninstitutional population age 18 and over.
  • After reaching 9.9 percent in January 2011, the unemployment rate for veterans was 2.9 percent in October 2018. The peak unemployment rate for nonveterans was 10.4 percent in January 2010; their rate was 3.5 percent in October 2018.
  • The unemployment rate for Gulf War-era II veterans—those who served on active duty at any time since September 2001—reached 15.2 percent in January 2011. In October 2018, the unemployment rate for these veterans was 3.1 percent.
  • There were 269,000 unemployed veterans in the United States in October 2018. Eighteen percent of them were ages 18 to 34, 39 percent were ages 35 to 54, and 43 percent were 55 years and over.
  • In the third quarter of 2018, more veterans worked in government than any other industry; 21 percent of all employed veterans worked in federal, state, or local government. By comparison, 13 percent of employed nonveterans worked in government.
  • After government, veterans were most likely to work in manufacturing and in professional and businesses services (about 11 percent each).

Looking for more information on veterans? Check out our page devoted to veterans.

Now, let’s take a look at some data that may help veterans who are looking for work or considering a career change.

Thinking of moving?

In 2017, the unemployment rate for veterans varied across the country, ranging from 1.7 percent in Maine and Vermont to 7.3 percent in Rhode Island.

Map showing unemployment rates for veterans by state, 2017 annual averages

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

Considering different industries?

There were 7.0 million job openings in September 2018. Here’s how they break down by industry.

Chart showing job openings by industry in September 2018

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

Wondering about different jobs?

Thank you, veterans, for your service. As with our armed forces of the past, your service is the foundation of this great nation.

Want more information? Check out our website at www.bls.gov 24/7 or give our information office a call at (202) 691-5200. We also have regional information offices available to help you. BLS has the data YOU need to make wise decisions.

Unemployment rates for veterans by state, 2017 annual averages
State Unemployment rate
Total, 18 years and older 3.7%
Alabama 2.2
Alaska 5.3
Arizona 5.2
Arkansas 4.4
California 4.2
Colorado 3.7
Connecticut 3.4
Delaware 4.0
District of Columbia 6.3
Florida 2.9
Georgia 3.4
Hawaii 3.5
Idaho 3.4
Illinois 4.1
Indiana 2.4
Iowa 5.0
Kansas 2.5
Kentucky 2.0
Louisiana 3.0
Maine 1.7
Maryland 3.3
Massachusetts 2.4
Michigan 3.6
Minnesota 5.1
Mississippi 3.5
Missouri 3.1
Montana 4.4
Nebraska 4.5
Nevada 4.9
New Hampshire 3.3
New Jersey 4.0
New Mexico 3.3
New York 3.9
North Carolina 4.7
North Dakota 2.1
Ohio 3.5
Oklahoma 3.5
Oregon 4.3
Pennsylvania 5.0
Rhode Island 7.3
South Carolina 3.9
South Dakota 2.5
Tennessee 3.5
Texas 3.8
Utah 2.9
Vermont 1.7
Virginia 2.5
Washington 3.2
West Virginia 5.1
Wisconsin 3.3
Wyoming 4.6
Note: Veterans are men and women who served on active duty in the U.S. Armed Forces and were not on active duty at the time of the survey.
Job openings by industry in September 2018
Industry Job openings
Professional and business services 1,256,000
Health care and social assistance 1,223,000
Accommodation and food services 961,000
Retail trade 756,000
Manufacturing 484,000
State and local government, excluding education 317,000
Transportation, warehousing, and utilities 300,000
Construction 278,000
Finance and insurance 272,000
Other services 243,000
Wholesale trade 237,000
State and local government education 205,000
Information 117,000
Arts, entertainment, and recreation 87,000
Real estate and rental and leasing 84,000
Federal government 79,000
Educational services 76,000
Mining and logging 32,000

BLS Measures Electronically Mediated Work

Are you a ride-share driver using a mobile app (like Uber or Lyft) to find customers? Maybe you do household chores or yardwork for others by finding short-term jobs through a website (such as TaskRabbit or Handy) that arranges the payment for your work. Or perhaps you perform online tasks, like taking surveys or adding descriptive keywords to photos or documents through a platform (like Amazon Mechanical Turk or Clickworker). If so, you are an electronically mediated worker. That’s a term BLS uses to identify people who do short jobs or tasks they find through websites or mobile apps that connect them with customers and arrange payment for the tasks. Have you ever wondered how many people do this kind of work?

BLS decided to find out. In the May 2017 Contingent Worker Supplement to the Current Population Survey, we asked people four new questions designed to measure electronically mediated employment.

Measuring electronically mediated work is difficult

After studying respondents’ answers to the new questions and other information we collected about them, we realized the new questions didn’t work as intended. Most people who responded “yes” to the questions clearly had not found their work through a website or app. For example, a vice president of a major bank, a local police officer, and a surgeon at a large hospital all said they had done electronically mediated work on their main job. Many people seemed to think we were asking whether they used a computer or mobile app on their job. That could apply to many jobs that aren’t electronically mediated.

But it wasn’t all for naught. After extensive evaluation, we concluded we could use the other information in the survey about respondents’ jobs to identify and recode erroneous answers. That allowed us to produce meaningful estimates of electronically mediated employment.

So, who does electronically mediated work?

Based on our recoded data, we found that 1.6 million people did electronically mediated work in May 2017. These workers accounted for 1.0 percent of total employment. Compared with workers overall, electronically mediated workers were more likely to be ages 25 to 54 and less likely to be age 55 or older. Electronically mediated workers also were slightly more likely to be Black, and slightly less likely to be White, than workers in general. In addition, electronically mediated workers were more likely than workers overall to work part time (28 percent versus 18 percent).

Workers in the transportation and utilities industry were the most likely to have done electronically mediated work, with 5 percent of workers in this industry having done such work. Self-employed workers were more likely than wage and salary workers to do electronically mediated work (4 percent versus 1 percent).

What’s next?

We currently don’t have plans to collect information on electronically mediated work again. And even if we did, we wouldn’t want to use the same four questions. At the least, we would need to substantially revise the questions so they are easier for people to understand and answer correctly.

Taking a broader look, we are working with the Committee on National Statistics to learn more about what we should measure if we field the survey again. The committee is a federally supported independent organization whose mission is to improve the statistical methods and information on which public policies are based.

How can I get more information?

The data are available on our website, along with an article that details how we developed the questions, evaluated the responses, recoded erroneous answers, and analyzed the final estimates.

If you have a specific question, you might find it in our Frequently Asked Questions. Or you can contact our staff.

Why This Counts: Maximizing Our Data Using the Consumer Expenditure Survey

Almost all BLS statistical programs are based on information respondents voluntarily give us. We want to squeeze as much information as we can out of the data respondents generously provide. Limiting respondent burden while producing gold-standard data is central to our mission.

Let’s take a look at how one program, the Consumer Expenditure (CE) Survey, squeezes every last drop of information from the data to provide you, our customers, with more relevant information.

What is the Consumer Expenditure Survey?

The CE survey is a nationwide household survey that shows how U.S. consumers spend their money. It collects information from America’s families on their buying habits (expenditures), income, and household characteristics (age, sex, race, education, and so forth). For example, we publish what percentage of consumers bought bacon or ice cream and how much they spent on average.

A little back story: The first nationwide expenditure survey began in 1888. BLS was founded in 1884, so the CE Survey is one of our first surveys! It wasn’t until 1980 that we began publishing CE data each year, however. A 2010 article, The Consumer Expenditure Survey—30 Years as a Continuous Survey, provides more historical information.

How is the CE program doing more with what we have?

We’ll briefly look at four different areas, starting with the most recent improvements:

  • Limited state data
  • Higher-income data
  • Generational data
  • Estimating taxes

Limited State Data – Starting with New Jersey

  • Regarding geographical information, the CE survey is designed to produce national statistics. Enough sample data are available to produce estimates for census regions and for a few metropolitan areas.
  • Up to now, however, we did not produce state data. The CE program recently published state weights for New Jersey, which will allow for valid survey estimates at the state level for the first time.
  • State-level weights are available for states with a sample size that is large enough and meet other sampling conditions.
  • Right now, the state-level weighting is experimental. We provide state-level weights to data users to gauge interest and usefulness.

 Higher-Income Table

  • We evaluated the income ranges of the published tables and found that over time more and more households were earning more, and the top income range had not increased to keep pace. To provide greater detail, we divided the existing top income range of “$150,000 and over” into two new ranges: “$150,000 to $199,999” and “$200,000 and over.” We integrated these changes into the 2014 annual “Income before taxes” research table, allowing more robust analysis for our data users.
  • In addition, we added four new experimental cross-tabulated tables on income without the need for additional information from our respondents.

Generational Table

Grouping respondent information by age cohort can be helpful, since a person’s age can help to predict differences in buying attitudes and behaviors. The CE program has collected age data for years, but never grouped the data into generational cohorts before. A Pew Research Center report defines five generations for people born between these dates:

  • Millennial Generation: 1981 or later
  • Generation X: 1965 to 1980
  • Baby Boomers: 1946 to 1964
  • Silent Generation: 1928 to 1945
  • Greatest Generation: 1927 or earlier

The 2016 annual generational table shows our most recent age information for the “reference person” or the person identified as owning or renting the home included in the CE Survey. In 2016 we wrote a short article on Spending Habits by Generation, including a video, which used 2015 data. We’ve updated the chart using 2016 data:

A chart showing consumer spending patterns by generation in 2016.

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

Estimating Taxes

CE respondents used to provide federal and state income tax information as part of the survey. These questions were difficult for respondents to answer.

Starting in 2013, the CE program estimated federal and state tax information using the TaxSim model from the National Bureau of Economic Research and removed the tax questions from the survey. As a result, the quality and consistency of the data increased, and we have reduced respondent burden!

If you have any questions or want more information, our staff of experts is always around to help! Please feel free to contact us.

This is just one example of how we at BLS are always looking for ways to maximize our value while being ever mindful of the costs—and one of those important costs is the burden our data collection efforts place on our respondents. Maximizing our data means providing gold-standard data to the public while reducing the burden on our respondents—a true win-win!

Annual consumer spending by generation of reference person, 2016
Item Millennials, 1981 to now Generation X, 1965 to 1980 Baby Boomers, 1946 to 1964 Silent Generation, 1928 to 1945 Greatest Generation, 1927 or earlier
Food at home $3,370 $4,830 $4,224 $3,450 $2,023
Food away from home 2,946 4,040 3,100 2,042 1,095
Housing 16,959 22,669 18,917 14,417 17,858
Apparel and services 1,753 2,577 1,602 920 615
Transportation 8,426 10,545 9,762 5,952 3,142
Healthcare 2,473 4,492 5,492 6,197 5,263
Entertainment 2,311 3,613 3,144 2,114 1,223
All other spending 10,338 15,766 14,963 6,671 4,125

Why This Counts: Celebrating 100 years of Current Employment Statistics

You’re only as old as you feel, or so the saying goes. Here at BLS, we agree that age is only a state of mind. I’m proud to say the Current Employment Statistics (CES) survey—which some call the “payroll survey” or the “establishment survey”—is still going strong as it turns 100 years old this month. To celebrate, BLS is hosting a free public event with exciting guest speakers and topical booths staffed with economists ready to answer your questions. We will hold the 100 Years of CES Symposium on October 19, 2015, in Washington, DC. You need to register to attend. We hope to see you there.

Throughout its 100 years, many things about the CES have remained the same, while others bear no likeness to the survey’s origins. Instead of the monthly news releases and web updates we post rapidly today, the start of the modern CES program was one table called the “Number of employees and amount of earnings in identical establishments in certain industries during one week of October and November, 1915,” published in the January 1916 Monthly Labor Review. Interestingly enough, when the survey began, many analysts viewed the amount of earnings as more useful than a count of employees because they believed earnings were more closely tied to changes in production. Employers were more likely to reduce hours worked and therefore pay than lay people off. Today, the headline number on the monthly jobs report is the number of jobs added or lost each month.

One crucial feature that remains unchanged is the survey’s reliance on voluntary reports from US employers. So, I thank CES survey respondents for your cooperation then and now, because the survey could not succeed without you. The U.S. labor market is fueled by business of all sizes and industries. The experience of each employer tells an important story, so I encourage you to say “yes” when we call to ask for your participation.

The states have always played an especially important role in making, publishing, and explaining CES estimates. I thank our state partners for their continued support of the CES program.

I encourage all our readers to check the Monthly Labor Review regularly in the coming months because we will publish several articles that highlight the survey throughout the decades. As always, your source of the most up-to-date information about national and state and metro area employment, hours, and earnings estimates is www.bls.gov.

Have a question about the survey? Staff economists are available Monday through Friday from 8:30 a.m. to 4:30 p.m. Eastern time. For questions about national estimates, call (202) 691-6555 or send us an email. State and metro area economists are available at (202) 691-6559, and you also can email them.

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!