Topic Archives: Consumer Spending

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

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

BLS Celebrates Read Across America Day

BLS celebrates the National Education Association’s Read Across America Day on March 2. Not by coincidence, it is also the birthday of the well-known author Dr. Seuss.

In the words of the famous author, “The more that you read, the more things you will know. The more that you learn, the more places you’ll go.”

BLS data show that reading is every bit as important as Dr. Seuss claimed. Only 2.5 percent of workers do not need to read or write on their job, according the Occupational Requirements Survey. However, the American Time Use Survey finds that only about 20 percent of people read for personal interest on an average day.

In honor of Dr. Seuss and Read Across America Day, how about taking some time to learn what else BLS data tell us about reading?

“Fill your house with stacks of books, in all the crannies and all the nooks.” –Dr. Seuss

Consumers spent $15,268,000,000 on reading in 2016, according to the Consumer Expenditure Surveys. On average, households (technically referred to as consumer units) spent $118 on reading. So, of the Whos down in Whoville, which Whos are reading?

  • Households in the West region spent an average of $171 on reading. Those in the Midwest averaged $121, while households in the Northeast and South regions averaged just under $100.
  • Married couples without children spent an average of $174 on reading for their household; those with children spent $123. The households of single parents with children under 18 spent an average of $41.
  • Generationally, when the reference person was a baby boomer (born between 1946 and 1964), the household spent an average of $130 on reading. That compares with an average of $64 spent by households of millennials (those born in 1981 or later).

The Consumer Price Index gives us information about changes in the prices of the goods and services we buy. For example, prices for eggs (white or brown, but not green) increased 11.6 percent in 2017, and prices for ham were up 2.7 percent.

  • Prices for recreational books decreased 3.2 percent in 2017 and were 7.7 percent lower than in 2007.
  • Costs for newspapers and magazines declined 1.1 percent in 2017, but were 37.5 percent higher than a decade ago.
  • Prices for educational books and supplies decreased 1.8 percent in 2017, but were 58.3 percent higher than in 2007.

“I can read in red. I can read in blue. I can read in pickle color too.” –Dr. Seuss

According to the American Time Use Survey, the share of women who spent time reading for personal interest was larger than the share of men. In addition, women were slightly more likely than men to spend time reading to and with children in the household (excluding education- and health-related reading).

  • Seventeen percent of men and 21.8 percent of women spent time reading for personal interest on an average day. On the days they read, men and women spent an average of around an hour and a half participating in this activity.
  • On an average day, 13.4 percent of fathers and 18.5 percent of mothers spent time reading to and with their young children. On days they engaged in this activity, it accounted for about a half an hour of time for both fathers and mothers.

“You’re never too old, too wacky, too wild, to pick up a book and read to a child.” –Dr. Seuss

Do you want to spend more time with Thing 1 and Thing 2? How about a fox in socks or a cat in a hat? Library workers get to do all of that!

Librarians, library technicians and clerical library assistants spend all day with books. Librarians earn the highest wages of the three and also require higher levels of education and work experience, according to the Occupational Employment Statistics and the Occupational Requirements Surveys.

  • Nearly 50 percent of librarian jobs required a bachelor’s degree, and another 42 percent required a master’s degree in 2017. High school diplomas were more common for library techs (42 percent) and clerical library assistants (80 percent).
  • The average annual wage for librarians in 2016 was $59,870. Library technicians averaged $34,780 and clerical library assistants, $27,450.
  • Lifting books is a big job. On a scale from sedentary to very heavy, a medium level of strength was required for about 57 percent of librarian jobs and 71 percent of clerical library assistant jobs.

“There’s no limit to how much you’ll know, depending how far beyond zebra you go.” –Dr. Seuss

So, how will you celebrate Read Across America Day—in a boat, with a goat, in the rain, on a train, in a box, with a fox, in a house, with a mouse? Don’t forget the green eggs and ham! And remember, “You can find magic wherever you look, sit back and relax, all you need is a book.” –Dr. Seuss

Do You Understand Your Local Economy?

The national unemployment rate may make the headline news every month, but many folks are most interested in understanding their own local economy.

BLS has a stat for that (really MANY statistics for that)! In fact, BLS data were highlighted in a webinar focusing on local data sponsored by the Association for Public Data Users, the American Statistical Association, and the Congressional Management Foundation.

Dr. Martin (Marty) Romitti, a Senior Fellow at the Center for Regional Economic Competitiveness, presented a webinar called “Understanding Your Congressional District’s Economy and Workforce Using Federal Statistical Data.” Though geared to Congressional staff, the information is applicable to anyone interested in knowing more about their local economy.

By using an extended example of the Napa, California, metropolitan area (where we immediately think, “Wine Country!”), Dr. Romitti finds some interesting information that may shatter some of your preconceived notions of that region.

He does this by answering 10 questions — 5 about “our people,” where he uses U.S. Census Bureau data and 5 about “our economy,” where he uses BLS data.

We are going to focus on the BLS portion (run time 31:12)* of the webinar. The five questions Dr. Romitti poses about our economy are:

  1. How healthy is my economy now?
  2. How many unemployed people live in my area?
  3. What are the largest employing industries?
  4. Which industries pay most to workers?
  5. What are our economic strengths?

Below are some steps and tips if you want to access the same information as Dr. Romitti on www.bls.gov. Note that he uses Internet Explorer; use a different browser and your screen will look different.

Dr. Romitti uses two BLS tools; we have included the path and links to pages as appropriate:

  • To answer Questions 1 and 2: Economy at a Glance -> California -> Napa (Dr. Romitti suggests clicking on the maps.)
    • Tips:
    • For context, suggest you compare your area data to your state numbers. Beware: Your state unemployment rate is seasonally adjusted, while your area data are not.
    • Also, for context, you may want to look at the data over time, such as the last 10 years. Just remember the “Great Recession” occurred starting in late 2007.
  • To answer Questions 3, 4, and 5: BLS Data Tools -> Employment -> Quarterly -> State and County Employment and Wages -> Tables

By following these instructions, you can uncover the same information as Dr. Romitti. We believe Dr. Romitti does a good job of explaining how to answer questions related to local economic data in under an hour!

But wait, there’s more! Let me offer two more resources in your quest for local data:

  1. Are you familiar with our Economic Summaries? These summaries present a sampling of economic information for the area covered, such as unemployment, employment, wages, prices, spending, and benefits. For example, take a look at San Francisco. If you are looking for something quick and easy, you might find what you need in one of these summaries.
  2. The Economic Summaries are produced by the BLS regional information offices. The BLS regional office staff stand ready to assist you with questions about your local economy.

*The taped webinar starts with a musical interlude and some brief introductions. The real action starts at the following run-time intervals:

Run Time                    Presentation Topic   

6:46                             Introduction by Dr. Romitti

11:30                           About our people (Census Bureau data)

31:12                           About our economy (BLS data) begins

52:36                           Regional Economic Accounts (Bureau of Economic Analysis data)

58:53                           Conclusion

60:00                           End

What Does the U.S. Bureau of Labor Statistics Tell Us about Football?

Football season is here. From pee-wee and youth sports, to high school and college rivalries, to professional matchups, it seems like there’s a game available almost every day of the week. You may wonder how football is related to economic statistics. Well, at BLS, we have a stat for that!

A recent Spotlight on Statistics by Bonnie Nichols, a research analyst at the National Endowment for the Arts, examines information from the BLS Consumer Expenditure Survey on what households spent on entertainment, including sporting events.

  • In 2015, American consumers spent an average of $652 for admission to entertainment events, including movies, performing arts, and sporting events. The average spent on sporting events was about $43.
  • Americans ages 35–44 spent an average of $957 per year and those ages 45–54 spent an average of $879 per year.

The Spotlight also provides information from the National Endowment for the Arts on the percentage of adults who attend sporting events—about 30 percent in 2012. Attendance varied by education level. Nearly twice the share of people with a bachelor’s degree or higher (43.4 percent) attended a sporting event as did people with a high school diploma or less education (22.5 percent).

Another source of information about America’s football behavior is the American Time Use Survey, which measures how Americans spend their day. In 2016, about 22 percent of Americans spent some time during the day in sports, exercise, and recreation activities. That could include playing a game of touch football on the back lawn at Thanksgiving or attending a game to cheer on your favorite team.

Percent of the population age 15 and older engaged in sports, exercise, and recreation on an average day, 2016 annual averages

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

More tidbits. The Consumer Price Index for October 2017 showed prices for admission to sporting events fell 1.7 percent over the year. Maybe it’s a good time to think about attending a game. On the other hand, the CPI also showed the price of beer bought away from home, such as at a stadium, rose 2.0 percent over the year.

I have to go get ready for the Thanksgiving Day games. Hope to see you on the gridiron.

Percent of the population age 15 and older engaged in sports, exercise, and recreation on an average day, 2016 annual averages
Age Percent

Total

21.7

15 to 24 years

28.9

25 to 34 years

21.6

35 to 44 years

20.2

45 to 54 years

19.1

55 to 64 years

22.0

65 years and older

18.8