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Topic Archives: Consumer Spending

Providing Context for Recent Increases in Gasoline Prices

If you’ve filled your car’s gas tank recently, you may have been surprised at how much more gas costs than it did just a few months ago or in early 2020 after the COVID-19 pandemic took hold. In recent months, gasoline prices have increased sharply and have pushed up overall consumer inflation. We documented the dramatic price declines for petroleum products that occurred in early 2020 in a recent Monthly Labor Review article. The article also documented the partial recovery in prices last summer.

Let’s now look at what has happened with oil and gas prices since we published that article. We’ll see that gasoline prices mostly just recovered from the steep declines experienced early in the pandemic.

The following chart shows the monthly percent change in the Consumer Price Index (CPI) for gasoline and for all items since October 2020.

Consumer Price Index for all items and for gasoline (all types), seasonally adjusted monthly percent changes, October 2020 to March 2021

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

After smaller increases in October and November, the CPI gasoline index rose much more rapidly in December and the first 3 months of 2021. Overall, in the 4 months from November to March, gasoline prices increased about 31 percent. Over the same 4 months, the CPI for all items increased 1.5 percent.

Meanwhile, the increase in gasoline prices as measured by the Producer Price Index (PPI) has been larger than the increase in consumer prices. In the last 4 months, the PPI gasoline index increased about 58 percent.

The following chart shows the change in the CPI and PPI gasoline indexes since January 2020.

Consumer Price Index and Producer Price Index for gasoline, seasonally adjusted, January 2020 to March 2021

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

Gasoline prices fell sharply at the start of the pandemic and then partially rebounded through the summer of 2020. The prices that gasoline producers received declined much more at the start of the pandemic than did the prices consumers paid. Producer prices also were slower to recover than consumer prices. The recent increase in gasoline prices continued the recovery from the sharp declines at the start of the pandemic. Through February 2021, consumer prices for gasoline were still down 2.8 percent from January 2020. Producer prices for gasoline had fully recovered the pandemic-related declines by February 2021 and were back to January 2020 levels. In March 2021, consumer and producer prices for gasoline rose sharply and were above their January 2020 levels.

The differences between consumer and producer gasoline prices can be partly explained by larger margins for fuel retailers. Gasoline retailers are often slower to pass increases or decreases in their purchase costs on to consumers because they are uncertain about future costs and because of competition in the retail gasoline market. The PPI for “automotive fuels and lubricants retailing” measures the margin for gasoline retailers. The chart below shows that this margin increased sharply in March and April 2020 when oil prices dropped. The margin then decreased over the summer months as oil prices increased. In March 2021, retail gasoline margins were still 16.6 percent above January 2020 levels, in seasonally unadjusted terms.

Producer Price Index for automotive fuels and lubricants retailing, January 2020 to March 2021

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

Gasoline prices tend to be volatile, and large moves, such as this winter’s, occur often. Consumer gasoline prices rose 24.7 percent in the first 3 months of 2021. Since 2001, the CPI gasoline index has had six increases that large or larger in 3 months. The most recent instance of a larger increase over 3 months was a 26.4-percent increase from May to August 2009.

Over the past 4 months, the sharp rise in gasoline prices has contributed to increasing overall prices as measured by the CPI for all items. In each of the last 4 months, half or more of the monthly increase in the all-items index was due to the increase in gasoline prices. This means that, if the price of gasoline had been unchanged in each of these months, the overall CPI would have increased by less than half of the 1.5-percent increase over this period.

One way to strip out the effects of gasoline prices on overall prices is to look at prices for all items less energy. The following chart shows the monthly change in the CPI for all item and the CPI for all items less energy.

Consumer Price Index, 1-month percent change, seasonally adjusted, January 2020 to March 2021

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

From July through December 2020, the indexes moved similarly each month. That means energy price changes were close to the price changes of other items. The two indexes have diverged in the last 3 months, however, with the index for all items less energy increasing much less than the index for all items.

Crude oil prices have a large effect on gasoline prices. The following chart shows the changes in the PPI for crude petroleum and in the Import Price Index for crude petroleum since January 2020. The PPI measures price changes for domestic producers of crude oil, while the Import Price Index tracks price changes for oil purchased from foreign producers.

Producer and import price indexes for crude petroleum, January 2020 to March 2021

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

Overall, producer prices and import prices for crude oil track closely together. Both declined sharply as the COVID-19 pandemic began and partly recovered through the early fall. From November 2020 to March 2021, both had large increases—60.3 percent for the PPI and 46.5 percent for import prices—and now exceed their January 2020 levels.

Market analysis by the Energy Information Administration identifies several contributors to recent oil and gas price increases. One is optimism over the economic recovery from the pandemic and expectations of increased energy demand as more people receive COVID-19 vaccinations. Another is the continued cooperation among members of the Organization of the Petroleum Exporting Countries and other oil-producing countries to limit crude oil production. Finally, in February, weather-related supply disruptions also contributed to price increases.

Although gasoline prices have increased sharply in recent months and have contributed to increases in overall consumer prices, gasoline prices are only just recovering January 2020 levels. Gasoline makes up only about 3 percent of the market basket for the CPI, and its share has been declining. Gasoline still is an important driver of changes in the overall index because of frequent large fluctuations in gas prices. Price changes in gasoline and crude oil can also affect the prices of other items because gas and oil are important for producing many goods and services.

Consumer Price Index for all items and for gasoline (all types), seasonally adjusted monthly percent changes
MonthGasoline, all typesAll items

Oct 2020

0.70.1

Nov 2020

0.50.2

Dec 2020

5.20.2

Jan 2021

7.40.3

Feb 2021

6.40.4

Mar 2021

9.10.6
Consumer Price Index and Producer Price Index for gasoline, seasonally adjusted
MonthCPI for gasolinePPI for gasoline

Jan 2020

100.000100.000

Feb 2020

95.76697.003

Mar 2020

86.60471.609

Apr 2020

69.95532.440

May 2020

66.51844.322

Jun 2020

73.41061.409

Jul 2020

76.92866.193

Aug 2020

78.57667.192

Sep 2020

79.89167.613

Oct 2020

80.48268.559

Nov 2020

80.86669.085

Dec 2020

85.06678.181

Jan 2021

91.36488.801

Feb 2021

97.221100.421

Mar 2021

106.070109.253
Producer Price Index for automotive fuels and lubricants retailing
MonthIndex

Jan 2020

100.000

Feb 2020

102.652

Mar 2020

127.281

Apr 2020

169.753

May 2020

154.292

Jun 2020

135.506

Jul 2020

128.449

Aug 2020

124.180

Sep 2020

127.506

Oct 2020

129.438

Nov 2020

127.416

Dec 2020

118.292

Jan 2021

121.798

Feb 2021

118.292

Mar 2021

116.629
Consumer Price Index, 1-month percent change, seasonally adjusted
MonthAll itemsAll items less energy

Jan 2020

0.20.2

Feb 2020

0.10.2

Mar 2020

-0.30.0

Apr 2020

-0.7-0.1

May 2020

-0.10.0

Jun 2020

0.50.3

Jul 2020

0.50.4

Aug 2020

0.40.3

Sep 2020

0.20.2

Oct 2020

0.10.1

Nov 2020

0.20.1

Dec 2020

0.20.1

Jan 2021

0.30.0

Feb 2021

0.40.1

Mar 2021

0.60.3
Producer and import price indexes for crude petroleum
MonthProducer Price Index for crude petroleumImport Price Index for crude petroleum

Jan 2020

100.000100.000

Feb 2020

85.69689.067

Mar 2020

56.58558.776

Apr 2020

28.98637.212

May 2020

39.38244.333

Jun 2020

59.42058.977

Jul 2020

63.01271.615

Aug 2020

65.78473.621

Sep 2020

63.70569.509

Oct 2020

64.77669.408

Nov 2020

67.29772.116

Dec 2020

79.89979.840

Jan 2021

89.47787.563

Feb 2021

97.16498.897

Mar 2021

107.876105.617

A Truckload of Transportation Statistics

BLS recently participated in the North American Transportation Statistics Interchange, better known as the NATS Interchange. (Not to be confused with the local baseball team, as the Washington Nationals are known. I look forward to the day when I’m back in the stands yelling “N-A-T-S, Nats, Nats, Nats — whoooo!” after each run scores. But I digress.)

Like many recent conferences, the NATS Interchange was held virtually and focused on the pandemic—how statistical agencies in the United States, Mexico, and Canada continued operations, produced new data, and are planning for the future. Our friends at the Bureau of Transportation Statistics, part of the U.S. Department of Transportation, led the U.S. effort and invited several other U.S. statistical agencies to share information. BLS was asked to participate in a short session on the transportation-related information we produce that may be useful in measuring the economic recovery. This turned into a great opportunity to focus on the BLS Industry at a Glance feature on our website, and to look further into what BLS has available related to transportation.

We classify workplaces by industry based on their principal product or activity. Industries are categorized using the North American Industry Classification System, or NAICS. BLS releases considerable data by NAICS classification, including employment, wages, workplace safety, and more. The BLS Industry at a Glance webpages bring these different statistics together for over 100 industries. Want to know everything BLS produces for the transportation and warehousing industry classification (NAICS codes 48–49)? It’s all there at Industry at a Glance. Want to dig deeper and look just at the air transportation industry (NAICS code 481)? We’ve got that, too. Of course, we may have less information available as you ask for more detailed classifications, but if we’ve got it, it’ll be there.

Let’s look at a couple of examples, starting with employment. In April 2020, BLS reported a loss of more than 20 million jobs in one month, based on data from the Current Employment Statistics program. The job losses were widespread, including a loss of 570,000 jobs in the transportation and warehousing industry from February to April. That’s a decline of 10 percent from the January 2020, level of 5.7 million workers in this industry. Through December, the sector had recovered about 84 percent of that job loss and still had a net loss of 90,000 jobs since January.

But looking at the overall sector hides some of the details. The job losses in early 2020 occurred in all components of transportation and warehousing except couriers and messengers. This industry recorded an increase of 210,000 employees from January to December 2020, likely due to the surge in online shopping and associated shipping and delivery. While initially losing jobs, employment in warehousing and storage was up 79,000 in December from the March level. All other sectors continue to have net losses. Of particular note is employment in air transportation, which showed inconsistent recovery for several months before recording new jobs losses in October.

Share of January 2020 employment in selected transportation industries through December 2020

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

Other details you can glean from the Industry at a Glance page for Transportation and Warehousing:

  • 16.1 percent of wage and salary workers in the transportation and warehousing industry were members of a union in 2019, and 17.6 percent were represented by a union.
  • The occupation with the most workers in this industry is heavy and tractor-trailer truck drivers, with nearly 1.1 million workers in 2019. The next largest occupation was school bus drivers, with about 284,000 workers.
  • 948 workers in this industry suffered a fatal work injury in 2019, up from 909 fatalities in 2018.

In preparing for the NATS interchange, BLS took a broader look at the world of transportation statistics. Turns out, if you look beyond the industry classification, you find even more information. For example, BLS programs on prices and spending look at what consumers spend on transportation, and the change in transportation prices over time. From the BLS Consumer Expenditure Surveys, we know the average “consumer unit” (our fancy name for households) spent an average of $10,742 on transportation in 2019, including vehicle purchases and maintenance and public transportation.

The pandemic revealed major disruptions in certain transportation activity, and those disruptions were evident in the BLS Consumer Price Index. The CPI as a whole declined by 0.8 percent in April, the largest one-month decline in more than a decade. Many of the declines were the result of stay-at-home orders and related shutdowns, as prices for gasoline, airfares, and other transportation-related items declined sharply. Of note was a sharp decline in the price of gasoline—down over 20 percent in April.

Percent change in consumer prices for transportation-related items, April and May 2020

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

To stretch the transportation concept just a little further, the BLS Census of Fatal Occupational Injuries records the “event or exposure” that results in each fatal work injury. Of the 5,333 fatal work injuries in 2019, nearly 40 percent were the result of a transportation incident. Such incidents may occur to workers in the transportation industry, such as truck drivers, but also to many other workers, including farmers, protective service officers, landscapers, and construction laborers. Transportation incidents are most often on a roadway but can also involve aircraft, rail, and water vehicles.

The NATS interchange asked BLS to consider what data might be helpful in tracking the recovery. Many of the transportation statistics discussed here, such as employment, consumer expenditures, and price changes, will likely provide a clue about returning to activity levels reached before the pandemic.

This exercise provided an opportunity to dig a little deeper into the transportation and warehousing industry and to expand the definition to explore related information. The BLS Industry at a Glance webpages offer that same opportunity to explore the current economic landscape of over 100 industries.

Share of January 2020 employment in selected transportation industries through December 2020
IndustryJanuaryAprilDecember

Transportation and warehousing

100.0%90.0%98.4%

Air transportation

100.085.176.9

Warehousing and storage

100.093.4107.9

Couriers and messengers

100.0100.2124.5
Percent change in consumer prices for transportation-related items, April and May 2020
ItemAprilMay

Gasoline (all types)

-20.6-3.5

Car and truck rental

-16.6-3.5

Airline fares

-15.2-4.9

Motor vehicle insurance

-7.2-8.9

Lodging away from home

-7.1-1.5

Innovations at BLS during the COVID-19 Pandemic

Our work at the Bureau of Labor Statistics is driven by the idea that good measurement leads to better decisions. Good measures of economic and social conditions help public policymakers and private businesses and households assess opportunities and areas for improvement. Measuring these conditions consistently over time helps people who use our data evaluate the impact of public and private decisions.

We also believe we must be completely transparent about the design of our surveys and programs and the methods we use to conduct them. It isn’t enough to publish statistics and expect people simply to trust their quality. We gain this trust by documenting the design and procedures for all our programs in our Handbook of Methods. Our website also explains our policies for ensuring data quality and protecting the confidentiality and privacy of the people and businesses who participate in our surveys and programs. Further, BLS works with the wider U.S. statistical community to ensure and enhance the quality of statistical information.

Good measures are essential in “normal” times, but the global COVID-19 pandemic has made these last few months anything but normal. I am so proud of the work of the career professionals at BLS and our fellow statistical agencies for continuing to produce vital economic statistics. Our entire BLS staff moved to full-time telework in mid-March and didn’t miss a beat. We continue to publish measures of labor market activity, working conditions, price changes, and productivity like BLS has done since its founding in 1884. See our dashboard of key economic indicators in the time of COVID-19.

Publishing these measures hasn’t been easy. The pandemic has raised new questions about how businesses, households, and consumers have changed their behavior. BLS also has had to innovate to find new ways of doing things during the pandemic.

Today I want to tell you about the new data we have been collecting to learn more about the effects of the pandemic. I also want to tell you about some of the ways the BLS staff has innovated to keep producing data that are accurate, objective, relevant, timely, and accessible.

New Data

How businesses have responded to the pandemic

We have collected new data on how U.S. businesses changed their operations and employment from the onset of the pandemic through September 2020. This information, combined with data collected in other BLS surveys, will aid in understanding how businesses responded during the pandemic. Other statistics we have collected and published during the pandemic show changes in employment, job openings and terminations, wages, employer-provided benefits, prices, and more. These new data provide more insights by asking employers directly what they experienced as a result of the pandemic and how they reacted. Data for the Business Response Survey to the Coronavirus Pandemic will be released in early December 2020.

Changes in telework, loss of jobs, and job search

The Current Population Survey is the large monthly survey of U.S. households from which we measure the unemployment rate and other important labor market indicators. We added questions to the survey to help gauge the effects of the pandemic on the labor market. These questions were added in May 2020 and will remain in the survey until further notice. One question asks whether people teleworked or worked from home because of the pandemic.

Percent of employed people who teleworked at some point in the previous 4 weeks because of the COVID-19 pandemic, May through October 2020

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

Other questions ask whether people were unable to work because their employers closed or lost business because of the pandemic; whether they were paid for that missed work; and whether the pandemic prevented them from searching for jobs.

Number of people not in the labor force who did not look for work because of the COVID-19  pandemic, May through October 2020

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

Changes in sick leave plans

We added several questions to the National Compensation Survey to understand the effects of the pandemic on sick leave plans. The questions asked whether private industry establishments changed their leave policies and whether employees used sick leave between March 1 and May 31, 2020.

Receiving and using stimulus payments during the pandemic

BLS is one of several federal agencies that developed questions for the rapid response Household Pulse Survey. The survey is a collaboration among the U.S. Census Bureau, BLS, the U.S. Department of Housing and Urban Development, the National Center for Education Statistics, the National Center for Health Statistics, and the U.S. Department of Agriculture’s Economic Research Service. BLS contributed questions on the receipt and use of Economic Impact Payments and on sources of income used to meet spending needs during the pandemic.

Our staff will continue to publish research on how the pandemic has affected the labor market and markets for goods and services. Check back regularly as we add to this library of research.

Innovations in Data Collection and Training

The COVID-19 pandemic has caused profound changes in the daily lives of Americans. BLS is no exception. As I mentioned earlier, all BLS staff moved to full-time telework in March. The pandemic hasn’t prevented us from continuing to publish high-quality data, but we have had to change some of our data-collection methods and estimation procedures. We will continue to explain those changes so you can understand how they affect the quality of our measures.

Our survey respondents are the heart of everything we do at BLS. Without their generous and voluntary cooperation, we would not be able to publish high-quality data for public and private decision making. Respondents have businesses and households to run, and a pandemic is a challenging time to ask for their help. The data-collection staffs at BLS, the U.S. Census Bureau, and our state partners form great relationships with survey respondents. We must continue to protect the health of data collectors while also training them in a rapidly changing environment. Let me highlight a few of the innovative changes we have made during the pandemic that focus on our relationships with respondents and how we train data collectors.

Using videoconferencing technology for data collection

Several of our surveys have started using videoconferencing tools to speak with respondents and collect data from them. Some of the surveys that now use this technology include the National Compensation Survey, the Occupational Requirements Survey, and the Producer Price Index. Many of our surveys previously relied on interviewers visiting businesses or households to collect data. We suspended all in-person data collection in March to protect the health of data collectors and respondents, so we had to find other ways to collect data. Many of our surveys also use telephone and internet to collect data, but those modes aren’t always ideal for every kind of data. We often need to develop personal relationships with respondents to gain their trust and cooperation and ensure high-quality data. Videoconferencing helps us accomplish what we often can’t do with phones or web survey forms.

The Occupational Requirements Survey is one that has begun using videoconferencing in data collection. The survey provides information about the physical demands; environmental conditions; education, training, and experience; and cognitive and mental requirements for jobs in the U.S. economy. Collecting data for this survey often requires visual aids, hand gestures, and other nonverbal information to understand job characteristics. It often helps to watch jobs as they are performed at a worksite, but that’s not an option during the pandemic. Videoconferencing is the next best alternative.

Many of our data collectors and respondents have mentioned how helpful videoconferencing is for developing a rapport and for sharing screens and other visual information. Videoconferencing also helps us reduce travel and lodging costs, so we likely will continue to rely on videoconferencing at least partly even after the pandemic.

Using videoconferencing technology for training and mentoring

Many of our surveys are complex and require considerable ongoing training for data collectors. For example, before the pandemic, our Consumer Price Index Commodities and Services (C&S) survey involved in-person training at our Washington, DC, headquarters. There were two classroom training courses: a 2-week introductory course and a 1-week advanced course. Each course was followed by on-the-job training held in our regional offices. Even before the pandemic, we were developing videoconference training. The pandemic caused us to accelerate these plans. We now provide C&S survey training through video collaboration tools. We also integrate on-the-job training throughout the classes.

Several other surveys have adopted a similar training approach as the Consumer Price Index. Our data-collection staffs also increasingly use videoconferencing for mentoring and to share ideas about how to make the data-collection experience better for data collectors and respondents.

A final note

Before I conclude, I want to share some sad news about one of the people who played an indispensable leadership role in developing the new survey questions and innovative data-collection and training methods. Jennifer Edgar, our Associate Commissioner for Survey Methods Research, died November 8 in a tragic fall in her home. She leaves behind her husband and two young children, her parents, and her sister. Moreover, she leaves hundreds of BLS colleagues and many more throughout the statistical community and beyond, who will grieve the loss of an exceptionally gifted friend and professional whose great promise was cut suddenly and tragically short. Jennifer was using her considerable energies to move BLS forward. Her passing is a huge blow to her family, loved ones, and the entire statistical community. We are working on ways to ensure Jennifer’s memory and passion is forever present at BLS.

Percent of employed people who teleworked at some point in the previous 4 weeks because of the COVID-19 pandemic
MonthPercent

May 2020

35.4%

Jun 2020

31.3

Jul 2020

26.4

Aug 2020

24.3

Sep 2020

22.7

Oct 2020

21.2
Number of people not in the labor force who did not look for work because of the COVID-19 pandemic
MonthNumber not in the labor force

May 2020

9,740,000

Jun 2020

7,043,000

Jul 2020

6,454,000

Aug 2020

5,200,000

Sep 2020

4,499,000

Oct 2020

3,563,000

Celebrating World Statistics Day 2020

At the Bureau of Labor Statistics, we always enjoy a good celebration. We just finished recognizing Hispanic Heritage Month. We are currently learning how best to protect our online lives during National Cybersecurity Awareness Month. We even track the number of paid holidays available to workers through the National Compensation Survey. Today I want to focus on a celebration that happens once every 5 years — World Statistics Day. While there may not be parades, special meals, or department store sales to honor this day, we at BLS and our colleagues worldwide take time out on October 20, 2020, to recognize the importance of providing accurate, timely, and objective statistics that form the cornerstone of good decisions.

United Nations logo for World Statistics Day 2020

World Statistics Day, organized under the guidance of the United Nations Statistical Commission, was first celebrated in October 2010. This year, the third such event, focuses on “connecting the world with data we can trust.” At BLS, the trustworthy nature of our data and processes has been a hallmark of our work since our founding in 1884. Our first Commissioner, Carroll Wright, described our work then as “conducting judicious investigations and the fearless publication of results.” That credo guides us to this day. As the only noncareer employee in the agency, I am surrounded by a dedicated staff of data experts  whose singular mission is to produce the highest-quality data, without regard to policy or politics. BLS and other statistical agencies throughout the federal government strictly follow Statistical Policy Directives that ensure we produce data that meet precise technical standards and make them available equally to all. For nearly 100 years, we have regularly updated our Handbook of Methods to provide details on data concepts, collection and processing methods, and limitations. Transparency remains a hallmark of our work.

The United States has a decentralized statistical system, with numerous agencies large and small spread throughout the federal government. Despite this decentralization, the agencies work together to improve statistical methods and follow centralized statistical guidance. This partnership was recently strengthened by the Foundations for Evidence-Based Policymaking Act of 2018, which reinforced how the statistical agencies protect the confidentiality of businesses and households that provide data. The Act also designated heads of statistical agencies, like myself, as Statistical Officials for their respective Departments. In my case, my BLS colleagues and I advise other Department of Labor agencies on statistical concepts and processes, while continuing to stay clear of policy discussions and decisions.

World Statistics Day is a global event, so this is a good time to share some examples where BLS participates in statistical activities around the world:

  • We have regular contact with colleagues at statistical organizations around the world. Just recently, I participated in a very long-distance video conference on improvements to the Consumer Price Index. For me, it was 6:00 a.m., and I made sure I had a mug of coffee handy; for my colleagues in Australia, it was 6:00 p.m., and I’m certain their mug had coffee as well.
  • We have a well-established training program for international visitors, focusing on our processes and methods. We hold training sessions at BLS headquarters (or at least we did before the pandemic), we send experts to other countries, and we are exploring virtual training. We are eager to share our expertise and long history.
  • We participate in international panels and study groups, such as those organized by the United Nations, the Organization for Economic Cooperation and Development, and others, with topics ranging from measuring the gig economy to use of social media.
  • We provide BLS data to international databases, highlighting employment, price, productivity and related information to compare with other countries.

And that’s just a taste of how BLS fits into the World of Statistics. As Commissioner, I’ve had the honor to represent the United States in conferences and meetings across the globe. The BLS staff and I also hold regular conversations with statistical officials worldwide. In a recent conversation with colleagues in the United Kingdom, we were eager to learn about each other’s changes in the ways we provide data and analyses to our customers. These interactions expand everyone’s knowledge and keep the worldwide statistical system moving forward.

To celebrate World Statistics Day, I asked some BLS cheerleaders if they would join me in a video message about the importance of quality statistical data. Here’s what they had to say:

In closing, let’s all raise a toast to World Statistics Day, the availability of high-quality and impartial data, and the dedicated staff worldwide who provide new information and analysis every day.

Happy World Statistics Day!

How Much Does a Cup of Coffee Cost? It’s Complicated

We have a guest blogger for this edition of Commissioner’s Corner. Rob Cage is the Assistant Commissioner for Consumer Prices and Price Indexes at the U.S. Bureau of Labor Statistics.

The pandemic has changed my morning routine. Before the outbreak of the COVID-19 pandemic and full-time telework at BLS, two things motivated me each morning.

Person holding mobile phone and ordering coffee on an app.

First, I was always on a mission to minimize my commute to work. I would do things each night so I wouldn’t waste time in the morning. Things like shaving, setting out clothes, and preparing the next day’s lunch. I timed my alarm to go off to allow just enough time to shower, suit up, grab that sandwich, and catch my commuter train as it rolled into the station.

The second thing I needed to start each work day was a strong, fresh, hot cup of joe—actually more like two or three cups. Not one of those fancy drinks with mocha, caramel, steamed milk, or anything like that. Ordinary drip-brewed, filtered coffee. Medium to dark roast and like Betty MacDonald, my coffee had to be “…so strong it snarled as it lurched out of the pot.” Then I add some cream (and by cream, I mean half-and-half), but no sugar. But by far the most important element of the drink: temperature. I like coffee precisely at a certain temperature. If it’s too hot, you taste nothing but a scalded tongue. If it’s too cold, you’re met with an overwhelming sense of disappointment. In that ideal temperate zone, you are jolted alive with a satisfying sip of silky cocoa and nutty fragranced bliss.

Through trial and error, I eventually unearthed a way to satisfy both of these morning habits efficiently: getting my coffee along the commute. Brewing the coffee at home took too much time, and I’d drink most of it on the train, arriving at my desk empty handed. Getting my first cup after I arrived was also uneconomical since I’d have to backtrack to get it. The simple solution? Find a place to get the coffee along the way, and preferably as close to my office as possible. This way, the temperature of the drink was in that sweet spot as I turned on my computer.

With four different coffee shops located along my route in Washington’s Union Station, one would think I could easily achieve this. But no, I’m foiled by impatience. According to a 2014 Journal of Consumer Behavior study, the time before ordering has the greatest influence on how customers perceive waiting times and service quality. A customer who has to wait 10 minutes in line before ordering will feel more dissatisfied than a customer waiting 10 minutes after ordering, even if the total wait time is the same. I couldn’t agree more. Queues at Union Station during the morning rush were just too long and unpredictable to meet my needs. I didn’t have the patience to wait behind customers pondering through a long order recital: Quad Grande nonfat extra hot caramel macchiato upside down, please. I needed my expeditiously stated, two-word order quickly. Luckily, the employee cafeteria in my building—conveniently located just off the lobby—had self-serve coffee. No competing commuters. No preorder queue. No postorder queue. Only a payment queue. I had found my routine: a 55-minute total commute, landing at my desk with strong, hot coffee in hand.

Then one day, I bumped into a coworker on the train. As we walked through Union Station and approached the maze of coffee shops with the insufferable queues, she stopped in front of one; took two steps to the left, scanned the drinks on top of a cart, found one with her name on it, picked it up, and met me back in stride. Amazed, I asked her how she pulled off this sensational stunt. She had placed her order on the coffee shop’s mobile app, of course. That was her routine. Curious but unconvinced, I asked her if she was concerned the coffee would be too cold by the time she picked it up. Through trial and error, she had figured out that if she placed her order on the app as the train rolled out of the L’Enfant Plaza stop, her drink would typically be hot and ready as she passed the cart. Could this be coffee-ordering nirvana? Guaranteed no-wait service, with guaranteed handoff at perfect temperature? Surely this improvement in the quality of the purchasing experience would cost more, which was my next question. And the astonishing answer: the coffee was the same price! I immediately downloaded the app, copied her process, and shaved three minutes off my morning routine. An equilibrium commute down to 52 minutes, about a 5-percent improvement!

Which brings me to how this tortured story relates to the business of BLS and specifically the measurement of the cost of living and consumer inflation. If the cost of my preferred cup of coffee was identical ($2.45 before sales tax) whether I stood in line to get it or not, then surely I would be better off by ordering on the app. Doing that resulted in a 5-percent time savings on my commute—an attribute of purchasing coffee that was critically important to me. In other words, the app-ordered coffee represented a higher-quality product, even though the price was the same. Using the federal minimum wage rate of $7.25\hour (or 12 cents a minute), an estimate of the time savings is 3 minutes x $0.12 = $0.36. One could say $0.36 is a reasonable estimate of the difference in quality. So what is the correct measure of price change between these two choices?

ApproachWalk-up purchaseApp purchasePrice changeNote

Ignore purchase time

$2.45 $2.45 0%No change in price

Add purchase time

$2.81 $2.45 -13%Deflation

Assume purchase time is built into market price, and adjust prices to reflect zero purchase time

$2.09 $2.45 17%Inflation

This is the million dollar question in consumer price index measurement, and the answer depends on how a unique consumer good—in this case a prepared cup of coffee—is defined. In the price index literature, the buzzword is homogeneity. To measure inflation accurately, goods that are homogenous must be identified and grouped together for proper treatment. This is at the core of getting the CPI right. Homogenous is defined as “of the same kind, alike; consisting of parts all of the same kind.” In CPI jargon, the component “parts” of a unique item in the sample are called “attributes.” So what are the attributes that define a cup of coffee? We could consider a list of attributes that most baristas might say are important, like size, bean variety, country of origin, blend, roast, freshness, or caffeine content; and a couple you already know that are important to me: temperature and queue time.

How many of these attributes do we explicitly control for in the CPI as obvious, overt, and separate variables used in scientifically selecting a sample of coffee drinks from quick service establishments, for use in calculating the index each month? You might be surprised by the answer: none! How, then, do we capture constant-quality price change for prepared coffee drinks accurately in the CPI?

We implicitly account for all of these characteristics one way or another. The CPI uses the matched-model approach to index measurement. We select a sample of 100,000+ unique, well-specified, strictly homogenous goods and services for the sample. Then we compare the price of each unique sampled item to the price of the exact same item in subsequent months. The key, of course, is defining and selecting the unique items. Generally speaking, sample selection has two major components: selection of the establishments (for example, a coffee shop) and then selection of a unique item (for example, 16-ounce dark roast drip coffee) at the selected establishments. Limited budget requires BLS to take a sample rather than a census of all goods and services consumers purchase. Thus, we group unique products into broadly homogeneous categories so the selected products can accurately reflect price change for unsampled items in those categories. We bundle prepared coffee from quick service establishments into the elementary category “limited service meals and snacks.” Comparatively, this is one of the more broadly defined components in the CPI basket. With a variety of different food and beverage items eligible for the sample, there are simply too many attributes to consider as separate selection steps to create the sample of unique items. Instead, we base the selection largely on the descriptions of different items listed on the menu. This is how we would distinguish an ordinary brewed coffee drink from other coffee drinks, such as a latte and cappuccino.

Any attribute expressly identified in the description of the menu item becomes a characteristic defining the unique item. For example, “12-ounce Cup of Organic Single Origin Light Roast Coffee” and “12-ounce Cup of Organic Classic Blend Medium Roast Coffee” may be two different menu items at a coffee shop. By rule, they are treated as distinct, unique, separate products for CPI sample selection. Then each month, CPI data collectors meticulously capture the price of the exact same product. If any of the characteristics change, that would trigger a quality review. Suppose medium roast was no longer available. A decision would have to be made to substitute the most comparable item to the originally selected item. Then a commodity analyst in the national office would have to decide if the new item was comparable to the old item. For example, is there a difference in quality between the light roast and the medium roast? Obviously, consumer taste and preferences are idiosyncratic, and the difference in quality of light roast and medium roast is a function of individual preference. But to the average consumer, perhaps not. In fact, prices tend not to vary by roast type. So in this situation, the analyst might judge medium and light to be comparable, and the price of the light will be matched to the previous price of the medium and used in the index. However, if a single-origin coffee was selected, a different outcome might result, especially if the price of the single-origin coffee was considerably different from a previously selected blend coffee, with all other characteristics being the same. Then a decision would need to be made as to how much of the difference was a quality difference (single origin versus blend), and how much was pure price change.

But what about the other factors that are not expressly identified in the description of the menu item, like temperature, freshness, and queue time? These are ostensibly identified, and held constant month after month, by the selection of the establishment. The outlet itself is associated with many attributes of product quality which are not observed. Over time, customers come to expect a certain level of service or product quality within each specific store, or at specific locations of chain stores. So, by controlling for the outlet, we are effectively able to hold constant these unobservable attributes.

Now that I am teleworking, my morning habits are out of equilibrium. My commute time is drastically shorter, reduced to the time it takes me to walk from my bedroom to the guest room, which has been hastily converted into a home office. My problem is the coffee. I haven’t figured out the roast, or the precise coffee-to-water ratio for the perfect strength; I don’t like spending time grinding whole bean, so I substitute ground coffee instead. My barista tells me that’s a quality decrease.

I’d say I am better off commute-timing wise but worse off coffee wise. A push. All in all, I can’t wait to return to on-premises work, mostly for that reliable cup of java.