Tag Archives: CPI

The Griswold Family Vacation through the Lens of BLS Data

We have a guest blogger for this edition of Commissioner’s Corner. Joy Langston is a budget analyst at the U.S. Bureau of Labor Statistics. She enjoys watching classic movies when she’s not working.

As summer wraps up, let’s slow the transition into cooler weather to explore the dream American summer vacation of the Griswold family. America first met the Griswolds in the cult classic National Lampoon’s Vacation. We’ll relive their vacation through the lens of our gold-standard data. Clark Griswold, the easygoing and optimistic patriarch of the family, wants a fun vacation with his wife, Ellen, and adolescent son and daughter, Rusty and Audrey, before the kids grow up. For the past 15 years, Clark has worked as a food scientist creating “new and better food additives.” Data from the 2017 Employee Benefits Survey show that after 10 years of service, full-time workers like Clark receive on average 18 days of vacation, or almost 4 weeks.

Since he has the time, Clark decides to lead the family on a cross-country expedition from the Chicago suburbs to Walley World — “America’s Favorite Family Fun Park” in Southern California. Ellen agrees to the destination but wants to fly, as it will be less of a hassle. However, data from the Consumer Expenditure Surveys suggest driving may not be a bad idea. The average amount a household spent on vacations was $2,076 in 2017, with $684 for transportation costs, so flying from Chicago to Southern California was likely not in the Griswolds’ budget. To jumpstart this trip, Clark ordered the new “Antarctic Blue Super Sports Wagon with the Rally Fun Pack” from the local car dealership. He is scammed into buying the far less appealing, but now iconic, metallic pea, wood grained trimmed station wagon instead. Nevertheless, Clark is determined to make this the best family vacation ever.

Eventually, Ellen gives in to her husband’s enthusiasm and the Griswolds embark on their adventure, but not before stopping for their first tank of gas. You may remember that Clark struggled to find the gas tank, which was ridiculously located under the hood, by the engine, on the passenger’s side. The average household spent $109 in 2017 on gas for out-of-town trips and $1,797 for all uses. In July 2018, the national average price of gas was $2.93 per gallon, according to the Consumer Price Index. Although America has traded in station wagons for SUVs, neither are gas efficient and the Griswolds probably had to fuel up frequently on the 2,460-mile drive.

The family’s first misstep includes taking the wrong exit in St. Louis, Missouri, where they lose a couple of car parts while stopping to ask for directions in a questionable neighborhood. Despite this portrayal of St. Louis, the Occupational Employment Statistics data show this metro area had about 1.4 million jobs in 2017. About 16 percent of them were in office and administrative support occupations, with an average wage of $37,720 per year. Another 10 percent of jobs were in sales and related occupations, and 7 percent were in healthcare practitioners and technical occupations.

Driving through Kansas, they stop in Dodge City to experience life in the Wild West and order drinks in a saloon. According to the Current Employment Statistics survey, stops like these, including historical sites and other historical institutions, provide an average of 69,000 jobs from May to August nationwide.

The Griswolds make it to Coolidge, Kansas, where Ellen’s cousins live. The cousins pressure Clark and Ellen into dropping off cantankerous Aunt Edna — and her equally feisty dog — at her son’s home in Phoenix, Arizona. According to the American Time Use Survey Americans spend an average of 39 minutes a day — or about 237 hours a year — socializing and communicating in person. The survey also shows that Americans spend an average 4 minutes a day caring for and helping nonhousehold adults. The Griswold family gets a concentrated dose of this social activity by adding Aunt Edna to their road trip party.

For lunch, they stop off at rest stop to enjoy some homemade sandwiches. The average American household spent $56 in 2017 on food prepared for out-of-town trips, and $3,365 on food away from home (including fast food establishments and full service restaurants). The Griswolds’ enjoyment is cut short when they realize there is more to their soggy baloney cheese sandwiches than they bargained for. As it turns out, Aunt Edna’s spiteful dog used the picnic basket as a bathroom during the car ride. If you’re driving with a pet and want to avoid this mishap, Kansas has more than 4,600 restaurants and eating places to choose from, according to the Quarterly Census of Employment and Wages.

They spend the night in one of Colorado’s 98 campgrounds in three large, smelly tents. Despite their positive attitudes the next morning, the Griswolds meet with more misfortunes, including being pulled over by a state trooper, Ellen losing her bag with the credit cards, quarrels over their dwindling cash supply, and crashing in the Arizona desert while trying to find a shortcut to the Grand Canyon. After they are rescued and towed to a service station, Clark haggles with the local mechanic, who doubles as the local sheriff, and takes the rest of Clark’s cash. The average American household spent $954 on car maintenance and repairs in 2017, although costs usually are spread throughout the year and not on vacation misadventures.

By the time they drop off Aunt Edna in Phoenix, Ellen and the kids are begging Clark to buy plane tickets to go back home. However, Clark’s enthusiasm hasn’t waned, and he declares this road trip a pilgrimage.

When they finally arrive at Walley World, they discover it is closed for the next two weeks for repairs. Exasperated, Clark demands the security guard open the gates and let the family into the park. After a couple rollercoaster rides, the SWAT team and owner of the park, Roy Walley, arrive. As the police put handcuffs on Clark’s family, Clark begs Roy not to press charges. Clark persuades Roy not only to drop the charges but to allow the family to stay and enjoy all the rides! Americans do love their theme parks. There were nearly 1,000 theme parks in the United States in 2017, with 87 of them in California. These parks provided 185,000 jobs nationwide. This industry increased its labor productivity 13.7 percent in 2017, as theme parks reported higher output while hours worked by employees decreased.

Over the course of their trip, the Griswolds share a number of experiences, many of which either hit a little too close to home, or we hope to never experience for ourselves. After a long and tiresome trip, we hope Ellen finally has her way and Clark doesn’t force the Griswolds to spend another two weeks driving back to Chicago, which would deplete all his vacation days! This classic summer movie shows that BLS really does have a stat for that!

Why This Counts: What is the Producer Price Index and How Does It Impact Me?

The Producer Price Index (PPI) – sounds familiar, but what is it exactly? Didn’t it used to be called the Wholesale Price Index? It is related to the Consumer Price Index, but how? How does the PPI impact me?

Lots of questions! In this short primer we will provide brief answers and links for more information. Note, if you are an economist, this blog is NOT for you. It’s an introduction for everyone else!

Video: Introduction to the Producer Price Index

Before we go any further – what is an index? (You said this was a primer!)

An index is like a ruler. It is a way of measuring the change of just about anything. Producer price indexes measure the average change in prices for goods, services, or construction products sold as they leave the producer.

Here is an example of how an index works:

  • Suppose we created an index to track the price of a gallon of gasoline.
  • When we start tracking, gasoline costs $2.00 a gallon.
  • The starting index value is 100.0.
  • When gasoline rises to $2.50, our index goes to 125.0, which reflects a 25-percent increase in the price of gasoline.
  • If gasoline then drops to $2.25, the index goes to 112.5. The $0.25 decline in price reflects a 10-percent decrease in the price of gasoline from when the price was $2.50.

If you are a gasoline dealer, you might find a gasoline index useful. Instead of driving around every day to write down the prices of each competitor’s gasoline and averaging them together, the index can provide the data for you. (Question #5 in the PPI Frequently Asked Questions explains how to interpret an index.)

PPI is called a “family” of indexes. There are more than 10,000 indexes for individual products we release each month in over 500 industries. That is one big family!

OK, so PPI has lots of data – but what kind of data?

PPI produces three main types of price indexes: industry indexes, commodity indexes, and final demand-intermediate demand (FD-ID) indexes.

An industry refers to groups of companies that are related based on their primary business activities, such as the auto industry. The PPI measures the changes in prices received for the industry’s output sold outside the industry.

  • PPI publishes about 535 industry price indexes and another 500 indexes for groupings of industries.
  • By using the North American Industry Classification System (NAICS) index codes, data users can compare PPI industry-based information with other economic programs, including productivity, production, employment, wages, and earnings.

The commodity classification of the PPI organizes products by type of product, regardless of the industry of production. For example, the commodity index for steel wire uses pricing information from the industries for iron and steel mills and for steel wire drawing.

  • PPI publishes more than 3,700 commodity price indexes for goods and about 800 for services.
  • This classification system is unique to the PPI and does not match any other standard coding structure.

We also have more information on the differences between the industry and commodity classification systems.

The FD-ID classification of the PPI organizes groupings of commodities by the type of buyer. For example, the PPI for final demand measures price change in all goods, services, and construction products sold as personal consumption, capital investment, export, or to government. As a second example, the PPI for services for intermediate demand measures price change for services sold to business as inputs to production.

  • PPI publishes more than 300 FD-ID indexes.
  • This FD-ID classification system is unique to the PPI and does not match any other standard coding structure.

Now let’s go back to the beginning

  • 1902: Wholesale Price Index program begins, which makes it one of the oldest continuous set of federal statistics. The Wholesale Price Index captures the prices producers receive for their output. In contrast, the Consumer Price Index captures the prices consumers pay for their purchases.
  • 1978: BLS renames the program as the Producer Price Index to more accurately reflect that prices are collected from producers, rather than wholesalers.
  • PPI also shifts emphasis from a commodity index framework to a stage of processing index framework. This minimized the multiple counting that can occur when the price for a specific commodity and the inputs to produce that commodity are included in the same total index. For example, think of gasoline and crude petroleum both included in an all-commodities index.
  • 1985: PPI starts expanding its coverage of the economy to include services and nonresidential construction. As of January 2018, about 71 percent of services and 31 percent of construction are covered.
  • 2014: PPI introduces the Final Demand-Intermediate Demand system.
  • The “headline” number for PPI is called the PPI for Final Demand. It measures price changes for goods, services, and construction sold for personal consumption, capital investment, government purchases, and exports. We also produce a series of PPIs for Intermediate Demand, which measure price change for business purchases, excluding capital investment.
  • Let me give you an example: Within the PPI category for loan services, we have separate indexes for consumer loans and business loans. The commodity index for consumer loans is included in the final demand index and the commodity index for business loans is mostly in an intermediate demand index.
  • The Frequently Asked Question on the PPI for Final Demand provides even more information on this new way of measuring the PPI. The blog, Understanding What the PPI Measures, may also be helpful.
  • We also have an article that explains how the PPI for final demand compares with other government prices indexes, such as the CPI.

Why is the PPI important?

To me?

  • Inflation is the higher costs of goods and services. Low inflation may be good for the economy as it increases consumer spending while boosting corporate profits and stocks.
  • A change in producer prices may be a leading indicator of consumers paying more or less. Higher producer prices may mean consumers will pay more when they buy, whereas lower producer prices may mean consumers will pay less to retailers. For example, if the PPI gasoline index increases, you may see an increase soon at the pump!

To others (which may impact me!)?

  • Policymakers, such as the Federal Reserve, Congress, and federal agencies regularly watch the PPI when making fiscal and monetary policies, such as setting interest rates for consumers and businesses.
  • Business people use the PPI in deciding price strategies, as they measure price changes in inputs for their goods and services. For example, a company considering a price increase can use PPI data to compare the growth rate of their own prices with those in their industry.
  • Business people adjust purchase and sales contracts worth trillions of dollars by using the PPI family of indexes. These contracts typically specify dollar amounts to be paid at some point in the future. For example, a long-term contract for bread may be escalated for changes in wheat prices by applying the percent change in the PPI for wheat to the contracted price for bread.

Video: How the Producer Price Index is Used for Contract Adjustment

PPI is a voluntary survey completed by thousands of businesses nationwide every month. BLS carefully constructs survey samples to keep the number of contacts to a minimum, making every business, large and small, critical to the accuracy of the data. We thank you, our faithful respondents! Without you, BLS could not produce gold-standard PPI data.

Finally, check out the most recent monthly PPI release to get all the latest numbers. Head to the PPI Frequently Asked Questions to learn more. Or contact the PPI information folks at (202) 691-7705 or ppi-info@bls.gov.

Want to learn more about BLS price programs? See these blogs:

 

Reaching out to Stakeholders—and Steakholders—in Philadelphia

The U.S. Bureau of Labor Statistics has staff around the country who serve several critical roles:

  • Contacting employers and households to collect the vital economic information published by BLS
  • Working with partners in the states who also collect and review economic data
  • Analyzing and publishing regional, state, and local data and providing information to a wide variety of stakeholders

To expand the network of local stakeholders who are familiar with and use BLS data to help make good decisions, the BLS regional offices sponsor periodic Data User Conferences. The BLS office in Philadelphia recently held such an event, hosted by the Federal Reserve Bank of Philadelphia.

These Data User Conferences typically bring together experts from several broad topic areas. In Philadelphia, participants heard about trends in productivity measures; a mash-up of information on a single occupation—truck drivers—that shows the range of data available (pay and benefits, occupational requirements, and workplace safety); and an analysis of declines in labor force participation.

Typically, these events provide a mix of national and local data and try to include some timely local information. The Philadelphia conference included references to the recent Super Bowl victory by the Philadelphia Eagles and showed how to use the Consumer Price Index inflation calculator to compare buying power between 1960 (the last time the Eagles won the NFL Championship) and today.

We also tried to develop a cheesesteak index, a Philadelphia staple. Using data from the February 2018 Consumer Price Index, we can find the change in the price of cheesesteak ingredients over the past year.

Ingredient Change in Consumer Price Index, February 2017 to February 2018
White bread 2.5 percent decrease
Beef and veal 2.1 percent increase
Fresh vegetables 2.1 percent increase
Cheese and related products 0.8 percent decrease

Image of a Philadelphia cheesesteak

These data are for the nation as a whole and are available monthly. Consumer price data are also available for many metropolitan areas, including Philadelphia. These local data are typically available every other month and do not provide as much detail as the national data.

While the Data User Conferences focus on providing information, we also remind attendees the information is only available thanks to the voluntary cooperation of employers and households. The people who attend the conferences can help us produce gold standard data by cooperating with our data-collection efforts. In return we remind them we always have “live” economists available in their local BLS information office to answer questions by phone or email or help them find data quickly.

Although yet another Nor’easter storm was approaching, the recent Philadelphia Data User Conference included an enthusiastic audience who asked good questions and left with a greater understanding of BLS statistics. The next stop on the Data User Conference tour is Atlanta, later this year. Keep an eye on the BLS Southeast Regional Office webpage for more information.

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