Tag Archives: Survey redesign

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

Innovating for the Future

Erica L. Groshen was the 14th Commissioner of Labor Statistics. She served from January 2013 to January 2017. This is her final post for Commissioner’s Corner.

Image of former BLS Commissioner Erica L. Groshen

It didn’t take long after I became Commissioner of Labor Statistics in January 2013 for me to appreciate the skill, dedication, and innovation of the staff that works here. Whether they’re doing sampling, data collection, estimation, or dissemination; whether they’re the IT professionals or the statisticians or the HR staff; whether they’re the newest employees who are so tech-savvy or the more senior employees who hold a wealth of institutional knowledge. To a person they are phenomenal. I am honored to have had the pleasure of leading them — and letting them lead me — during the past 4 years.


I have had many opportunities to observe and encourage innovation during my tenure at the U.S. Bureau of Labor Statistics, from listening tours to senior staff conferences to regional office visits to discussions with a wide variety of stakeholders. From these efforts, we have identified several activities that will help us develop and implement the next generation of labor statistics. These days, we call these efforts a variety of names, such as “modernization” and “reengineering.” But, in truth, they just continue the impressive progress that has been the hallmark of BLS for the past 133 years.

In my final Commissioner’s Corner post, I want to tell you a little about some of our current reengineering efforts.

One of the things we do best at BLS is data collection, largely because we are always looking for ways to improve. Recent efforts include identifying alternative data sources, expanding electronic collection, and “scraping” information directly from the Internet. These efforts can expand the information we provide, lessen the burden we place on employers and households that provide data, and maybe even save some money to provide taxpayers the best value for their data dollar.

These efforts are not new. One source of alternative data we’ve used for many years comes from state unemployment insurance filings, which identify nearly every employer in the country. We tabulate these data but also use them as the source of our sample of employers for certain surveys and as a benchmark of detailed employment by industry. We also use information from private sources and from administrative sources, like vital statistics. Our latest efforts involve examining techniques to combine data across multiple sources, including mixing survey and nonsurvey data.

We want to give employers the opportunity to leverage the electronic data they already keep so it’s easier to respond to our surveys. These efforts include allowing employers to provide electronic information in multiple formats; identifying a single source of electronic data from employers, reducing the number of locations and number of requests made to multiple sites of the same organization; and working with employers to allow BLS to access their data directly from the Internet. We rely on good corporate citizens to supply the information that we use to produce important economic data. Making data collection easier is a win-win.

The innovation doesn’t stop at collection. We are using electronic text analysis systems extensively to streamline some of our data-processing activities. Much of the information we collect is in the form of text, such as a description of an industry or occupation, details about a workplace injury, or summaries of employee benefit plans. Transforming text into a classification system for tabulation and publication used to be a manual task. BLS has begun to transform this task through the use of machine-learning techniques, where computers learn by reviewing greater and greater amounts of information, resulting in accurate classification. As we expand our skills in this area and find more uses for these techniques, the benefits include accurate and consistent data and greater opportunities for our staff to use their brainpower to focus on new, unique, and unusual situations.

We are also modernizing our outputs, producing more with the information we have. For example, we have begun several matching projects, combining data from two or more sources to produce new information. One example is new information on nonprofit organizations. By linking our employment data with nonprofit status obtained from the Internal Revenue Service, we now have employment data separately for the for-profit and nonprofit sectors. And we took that effort one step further and produced compensation information for these sectors as well. Look for more output from these matching efforts in the future.

Finally, we’ve made great strides in how we present our information, including expanded graphics and video. And we are not stopping there. Each year we are expanding the number of data releases that include a companion graphics package. We are developing prototypes of a new generation of data releases, with more graphics and links to data series. And we have more videos to come.

My 4 years as Commissioner of Labor Statistics have flown by. I’m excited to see so many innovations begin, thrive, and foster additional innovations. I have no doubt that the culture of innovation at BLS will continue. As my term comes to an end, I know now more than ever that the skill, dedication, and creativity of the BLS staff will lead this agency to even greater advances in the years to come.

Why This Counts: Measuring “Gig” Work

With so much chatter about the emerging “gig” economy, you may wonder if BLS has a stat for that. While our regular measures of labor market activity probably reflect a lot of “gig” work, we can’t currently break this work out separately. To do that, we need to repeat a survey specially designed to measure contingent and alternative work arrangements. Fortunately, BLS has conducted such surveys in the past, and I am very happy to say that we will do it again in 2017.

If you follow our monthly and quarterly employment reports, you know we publish lots of information not just on the number of jobs gained or lost but on the characteristics of jobs and workers. What industries or occupations are growing or shrinking? What are the employment trends for states, counties, or metro areas? How many people work part time, either by choice or because they prefer a full-time job but can only find part-time work? How many people are self-employed? How many people have more than one job? These are just some of the questions we can answer regularly with our employment reports. Other questions are harder to answer.

Many people want to know about workers whose jobs are temporary or irregular or not expected to last. So what kinds of jobs are those? You may be familiar with services where drivers use their own cars to take people where they want to go. Customers who need a ride use a computer or mobile app to request a pickup. If a driver agrees to provide a ride, a third party electronically receives the payment from the rider and pays the driver. Other examples of workers we want to know more about are people who sign up online to perform tasks for pay when it is convenient for them.

While many of these short-term jobs are new, similar jobs have been around a long time in the U.S. economy: substitute teachers, truck drivers, freelance journalist, day laborers in agriculture or construction, on-call equipment movers, actors, and photographers. These jobs are often short term, and many people in these occupations now go online to match up with potential employers. Some people call jobs like these “gigs,” much like the Saturday night gigs your high school garage band played. At BLS we call these contingent or alternative employment arrangements. What do we mean by those terms? Contingent workers do not expect their jobs to last, or their jobs are temporary. Workers with alternative employment arrangements include independent contractors, on-call workers, or people who work through temporary help agencies or contract firms.

Not to brag about being ahead of the curve, but we first examined workers like these in a 1995 survey. We conducted similar surveys in 1997, 1999, 2001, and 2005. Sadly, we haven’t had funding to conduct the survey about contingent and alternative work arrangements since 2005. However, I am delighted the U.S. Department of Labor is funding a one-time update to the survey in May 2017.

BLS will conduct the survey on contingent and alternative employment as part of the May 2017 Current Population Survey. That’s the monthly survey from which we measure the unemployment rate and other important labor market indicators. The questions will identify workers with contingent or alternative work arrangements; measure workers’ satisfaction with their current arrangement; and measure earnings, health insurance coverage, and eligibility for employer-provided retirement plans. To be able to compare today’s economy with results from previous surveys, most of the questions will be the same as they were in earlier surveys. We also will explore whether we need to add questions to reflect changes in work arrangements since the 2005 survey.

To keep this information coming in the future, the 2017 President’s budget requests funds for BLS to permanently conduct one supplement to the Current Population Survey each year. If Congress approves this funding, we would ask the questions on contingent and alternative work arrangements every 2 years, with questions on other important topics in the alternating years.

We have a lot of work to get ready for the survey next year, but I’m very excited that all of us will soon have these measures again after so many years without them.

A History and Culture of Efficiency at BLS

We’re always looking for ways to improve our programs and surveys at BLS to provide what I call “gold standard” data. Good data help the American public make better decisions.

BLS has a strong history and culture of looking for ways to provide our data in the most timely, accurate, relevant, and cost-effective manner. I’m incredibly proud of what BLS has achieved through innovation and resourcefulness. Our focus on improving our programs and methods means we can produce better data and provide better service for you.

I am excited the President’s 2016 budget request contains several items to help us meet the needs of our data users. One innovative proposal is to improve the timeliness and detail of the Job Openings and Labor Turnover Survey. The new funding would allow us to release each month’s data much sooner, when we publish The Employment Situation. Data users then would be able to analyze net changes in jobs each month alongside information about job openings, hires, and separations for the same month. Having more information more quickly can give policymakers, employers, and workers an earlier warning about downturns or signal an improving economy.

The President’s 2016 budget also proposes funding to measure poverty more accurately. Other agencies use these measures to improve conditions for the poor. BLS would improve the Consumer Expenditure Survey to get more information about school breakfasts and lunches and programs that help pay for home heating and other household expenses. The improved data will help the U.S. Census Bureau develop alternative poverty measures.

At BLS, we work hard every day to improve efficiency. I want to highlight a few notable efficiencies we have made over the past few years.

  • In 2012 we began closing 36 Consumer Price Index data collection offices, allowing those data collectors to work from their homes using smart phones and tablets.
  • This year, we began applying a design change to the Consumer Expenditure Survey that will reduce the number of respondent interviews from five to four; we will use the savings from that change to support a small-scale redesign of the survey.
  • We have reduced mailing costs by redesigning survey mailings and increasing the use of our Internet Data Collection Facility.

Of course, saving money by improving efficiency cannot fund all the work we do, but it can make a big difference.

In sum, we are constantly working to improve the way we do business. We strive to make our work as efficient, relevant, timely, and cost-effective as possible, to deliver “gold standard” data to our customers.

Why This Counts: How BLS Data Support the Goals of the Americans with Disabilities Act

This July marks the 25th anniversary of the Americans with Disabilities Act (ADA). The ADA prohibits discrimination against people with disabilities. Its goal is to ensure that people with disabilities have equal opportunities in employment, government services, transportation, and other aspects of their lives. The law prohibits employment discrimination and requires employers to make reasonable accommodations for workers with disabilities.

Today I want to tell you about the role BLS data play in supporting the goals of the ADA—one of our nation’s proudest civil rights triumphs.

The renowned physicist Lord Kelvin wrote more than a century ago, “If you cannot measure it, you cannot improve it.” When the ADA became law, we had no reliable measure of the number of people with disabilities who were working or seeking work. To track our nation’s progress, we needed statistics.

In 1998, President Clinton signed Executive Order 13078 to reduce barriers to employment for people with disabilities. The order required BLS, the U.S. Census Bureau, and other agencies to “design and implement a statistically reliable and accurate method to measure the employment rate of adults with disabilities.” The order also required us to publish employment data on people with disabilities as often as possible. BLS joined with other federal agencies and academic researchers to develop a short set of survey questions to identify people with disabilities.

Extensive research and testing showed the challenges of counting the number of people with disabilities using only a few survey questions. The team persevered, however, and in June 2008, we added six new questions to the Current Population Survey (CPS) to identify people with disabilities. The CPS is the monthly survey of about 60,000 households that we use to measure the U.S. labor force and unemployment rate. Adding these questions allowed us for the first time to track the employment status of people with disabilities. You can learn more in our Frequently Asked Questions about the disability data we collect.

The charts below show a few of the facts we have learned about the labor force status of people with a disability.

In 2014, there were about 29 million people age 16 and older with a disability in the civilian population outside of institutions. (Institutions include skilled-nursing facilities, in-patient hospice facilities, psychiatric hospitals, and prisons.) That was 11.8 percent of the total. We call this the disability rate, the percentage of people in a group who have a disability. Older people are more likely than younger people to have a disability.


About 8 in 10 people with a disability were not in the labor force in 2014, compared with about 3 in 10 of those with no disability. Many of those with a disability are age 65 and older; older people are less likely to participate in the labor force than people in younger age groups.


The employment–population ratio—the number employed as a percentage of the population—for people with a disability is much lower than for those with no disability. This is the case across all major race and ethnicity groups.


The unemployment rate for people with a disability was 12.5 percent in 2014, about twice the rate of 5.9 percent for those with no disability. (The unemployed are people who did not have a job, were available for work, and were actively looking for a job in the 4 weeks preceding the survey.)


BLS publishes monthly data on people with a disability in Table A-6 of the Employment Situation news release. In addition, we have published an annual news release on the labor force characteristics of people with a disability since 2009.

Many dedicated economists, statisticians, and survey methodologists inside and outside the U.S. government conducted the research to develop questions about disability. Terry McMenamin was one of the key contributors in developing the first questions about people with a disability. Terry was also instrumental in developing, testing, and fielding questions in the May 2012 CPS that gathered even more data on people with a disability. Those questions asked about the labor market problems confronting people with a disability. Tragically, Terry passed away in an automobile accident last fall. Terry was passionate about his work in collecting high-quality labor market data on people with a disability. He was a valued member of the BLS family, and all who worked with him miss him greatly.

BLS is committed to providing essential economic information to support public and private decision making. As Commissioner, I am proud of the work by BLS and others not only in developing measures about disability, but also in supporting the ADA’s goal to promote fairness in labor practices for all Americans.