We first reported in December 2019 on the expert panel convened by the National Academy of Sciences, Committee on National Statistics (CNSTAT), to study the U.S. Consumer Price Index (CPI). At the time, we were looking forward to the upcoming baseball season—and we didn’t know yet how different the 2020 season would be. Since then, CNSTAT assembled a panel of experts to tackle some of the biggest issues facing the CPI. The panel is chaired by Daniel Sichel, professor of economics at Wellesley College. Panel members include members of academia and experts at government agencies. Visit the CNSTAT website to review the panel members’ biographies and see the breadth of accomplishments and experiences on this team.
While the future of the baseball season that spring was uncertain, the CNSTAT panel on Improving Cost-of-Living Indexes and Consumer Inflation Statistics in the Digital Age forged ahead. The panel held a public meeting virtually on May 27, 2020, and invited BLS staff and luminaries from across the statistical community to clarify the study’s scope. The discussion centered on how we can harness new sources of data to improve CPI methods and produce accurate, timely, and relevant measures of consumer price change.
The baseball season finally got underway over the summer of 2020, and the CNSTAT panel continued its work. They held closed sessions to discuss the issues and to plan the gathering of information. The panel envisioned a series of public workshops designed to gather information from top experts in the field. Unlike the fate of the 2020 Major League All-Star Game, this gathering of experts would go on—as a series of virtual sessions rather than the typical one- or two-day event.
With the Washington Nationals out of playoff contention, everyone focused on the first workshop session held October 2, 2020. At this session, the panel discussed the challenges of measuring price change for different population groups. The CNSTAT panel added this topic to their scope of work in the May meeting. The panel heard from presenters in academia who use highly granular data and uncover measurement issues when combining information across households. The panel also heard from the United Kingdom’s Office for National Statistics and BLS about each agency’s efforts to improve price measurement for different population groups. Staff from the Bureau of Economic Analysis (BEA) also discussed potential uses for these indexes.
The next two workshop sessions (October 7, 2020 and October 30, 2020) centered on new data sources as an alternative to data from traditional surveys. The panel brought together experts from the Office for National Statistics, Statistics Canada, Statistics Belgium, and the Australian Bureau of Statistics. A benefit of a virtual meeting was the ability to convene people from so many countries without the cost of travel—although it was a challenge to coordinate a meeting over so many time zones. It is both reassuring and enlightening to hear that other countries face similar challenges and opportunities regarding new data sources. To give another perspective, the panel also convened experts from academia and the private sector to review research conducted outside of the statistical agencies. The panel heard about automated data collection efforts and methods to address quality change using new sources of data.
The final sessions (December 15, 2020 and March 31, 2021) tackled housing and medical care, arguably the most difficult areas to measure in the CPI market basket. Measuring the change in the cost of shelter for homeowners is a longstanding challenge. Since the late 1970s, BLS has used an approach called owner’s equivalent rent, which aims to isolate homeowners’ consumption of shelter services from their capital investment in a home. This method has been as hotly debated as baseball’s addition of the designated hitter around the same time. Presenters from BLS, BEA, Statistics Canada, and academia discussed potential improvements to owner’s equivalent rent and alternatives such as a user cost approach (how much it costs a homeowner to own their home).
Measuring price change for medical care services and health insurance is another longstanding challenge. While the panel’s scope is limited to health insurance, any changes to the BLS approach affect the larger scope of measuring price change for medical care services. The panel invited experts in health economics from government, academia, and nonprofits to discuss critical questions about quality change—such as medical care outcomes, utilization rates, and risk premiums.
With the All-Star public sessions now complete, the panel is weighing the information it has gathered. The panel originally planned to deliver its final report around the start of the 2021 baseball season, but the broader scope pushed back their timeline. We now expect the final report to coincide roughly with the beginning of the 2021 World Series. A truly global series of meetings produced a wealth of information for the panel to sift through. As they deliberate, we will enjoy the baseball season and report back on their recommendations in the fall.
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.
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.
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.
Editor’s note: Data for this chart are available in the table below.
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
Number of people not in the labor force who did not look for work because of the COVID-19 pandemic
We have a guest
blogger for this edition of Commissioner’s Corner. Jennifer Price is an
economist in the Office of Productivity and Technology at the U.S. Bureau of
Labor Statistics. She enjoys watching theatrical performances when she’s not
had the pleasure of attending a high school play. The cast was composed of a
male and female lead and at least a dozen supporting actors. The program listed the performers and acknowledged many
other students, parents, teachers, and administrators. They all played some important
role to bring the play to life—lighting, sound, painting props, sewing
costumes, creating promotional materials, selling tickets, working concessions.
All of these pieces came together harmoniously to make the performance a
Setting the Stage: New
Measures of State Productivity
We also can examine these roles geographically. Until recently, BLS productivity measures were only produced at the national level. Last June, BLS published experimental measures of state labor productivity for the private nonfarm business sector. These measures, which cover the period from 2007 to 2017, will help us learn more about productivity growth in each state and how each state contributes to national productivity trends.
productivity for all states allows us to credit the role played by each state,
not just the total performance of the national economy or region. Just as each
person, no matter how small their role, was necessary for the success of the
school play, each state contributes to how we evaluate national or regional productivity.
When we examine the contribution of each state to total productivity trends, we
find that, like actors, no two states perform identically. Similar individual
growth rates may have different impacts on the productivity of the nation or
region. By analyzing state productivity trends over the long term, we learn more
about regional business cycles, regional income inequality, and the role of local
regulations and taxes on growth.
to 2017, labor productivity changes ranged from a gain of 3.1 percent per year
in North Dakota to a loss of 0.7 percent per year in Louisiana.
Editor’s note: Data for this map are available in the table below.
We estimate each state’s annual contribution to national or regional productivity growth by multiplying the state’s productivity growth rate by its average share of total current dollar national or regional output. The economic size of each state influences its contribution to national and regional estimates. From 2007 to 2017, California was our lead performer, with the largest contribution to national productivity growth. The state’s productivity grew 1.7 percent per year on average, and its large economy means it contributed more than one-fifth of the 1.0-percent growth in national labor productivity.
Editor’s note: Data for this chart are available in the table below.
actors included Texas and New York. Making a cameo appearance was North Dakota;
despite having the largest productivity growth rate, it ranked 28th in terms of
its contribution to national productivity growth. Stars in each region included
Illinois (Midwest), New York (Northeast), Texas (South), and California (West).
Understudies—those states with the largest growth rates—were North Dakota (Midwest),
Pennsylvania (Northeast), and Oklahoma (South). Oregon and Washington shared
this role out West.
our new measures cover the private nonfarm sector for all 50 states and the
District of Columbia from 2007 to 2017. These measures include output per hour,
output, hours, unit labor costs, hourly compensation, and real hourly
compensation. Our measures of labor productivity for states are experimental,
meaning we’re still assessing them and considering ways to improve them. In the
second act, we will be looking into producing state-level measures for more detailed
sectors and industries.
We are in the “hot stove” months of the baseball year, when teams make trades and other decisions to improve their prospects for next season. Even the best teams, like the World Champion Washington Nationals, can’t rest on their laurels. In much the same way the Nationals continue to tinker with a good thing to make it better, we constantly work to improve our gold standard products, including the Consumer Price Index (CPI). There’s a lot going on with the CPI these days, and we’ll use this blog and other publications to share the latest information. You’ll read about how we reflect changes in consumer spending patterns, (including new goods), how we’re using other rich sources of data on prices and spending, how we’re accounting for changes in the quality of goods and services, and much more. So let’s get started.
The CPI is designed to measure the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. The CPI is used to determine annual cost-of-living allowances for Social Security beneficiaries. The CPI also is used to adjust the federal income tax system for inflation and as the yardstick for U.S. Treasury inflation-indexed bonds. These are just a few of the many uses of the CPI.
The CPI dates back to 1912, when the Washington baseball team was called the Senators and Walter Johnson ruled the mound. Throughout the history of the CPI, there has been debate about the concepts the CPI should measure and whether it might overstate or understate changes in consumer living costs. The CPI has undergone methodological changes both in response to these discussions and to reflect the changing economic environment. If we hadn’t made these changes, transportation, medical care, recreation, and other goods and services would still be combined into one “miscellaneous” category. Taking the long view, we can track major shifts in consumer inflation for more than a century.
In the 1960s, a committee commissioned by Congress recommended that BLS move the CPI closer toward a cost-of-living measure. We responded to those recommendations by creating the CPI for all urban consumers (CPI-U). The former index for urban wage earners was relabeled as the CPI-W. Today, the CPI-U represents the spending patterns of about 93 percent of the population, while the CPI-W represents the spending patterns of about 29 percent.
Here are a few more recent milestones in the
history of the CPI:
In 1988, following direction from Congress, BLS began calculating the CPI for Americans age 62 and older—called the CPI-E—as an experimental index.
In the early 1990s, Congress directed another study of the CPI, popularly referred to as the Boskin Commission. This commission estimated the CPI was overstating the rise in the cost of living and recommended changes in the way the CPI is designed and estimated.
In response, BLS sponsored a project in 2002 with the National Academy of Sciences, Committee on National Statistics (CNSTAT) to investigate conceptual, measurement, and other statistical issues in the development of cost-of-living indexes. At this point, we have adopted completely, partially, or experimentally almost all of the CNSTAT recommendations. This includes developing and publishing the Chained CPI, which broadly accounts for consumer substitution of goods and services.
we can’t stop researching and improving. Today, consumers buy goods and
services that weren’t even known a decade ago. And we buy things in many
different ways, including from the living room sofa. The growth of e-commerce
has created enormous opportunities, but also challenges, for measuring inflation. We continue to work on improvements in response to
these developments, and we will talk more about them in future blogs and other
publications. In addition, we recently sponsored another CNSTAT
panel to investigate three key methodological issues for the CPI:
How best to incorporate data on
How best to integrate other data sources
in the indexes for health insurance, owner-occupied housing, and durable goods?
How to lessen certain types of substitution
bias, such as when consumers purchase chicken when the price of steak increases?
(Our methods already do a good job accounting for shifts between more similar
items, such as between steak and ground beef.)
CNSTAT will convene an expert panel
and hold a workshop. Both the panel kickoff and the workshop will be open to
the public and will be announced in advance on the BLS website. The panel will
then spend about a year in internal discussions and preparing a written report
for our consideration.
We expect the
CNSTAT report in May of 2021—new ideas, to go with the start of a new baseball
season. I’ll be back to
blog about the results, so be sure to check back here.
Seeing that we are the U.S. Bureau of LABOR Statistics, we go the extra mile to attract the highest quality labor to accomplish our mission. This includes over 2,000 permanent staff scattered around the country. We also partner with state employees on several BLS programs, and we work with contractors and others to get the job done. Further, we look for opportunities to bring in specialized talent to help with some projects, such as the Civic Digital Fellows who joined us this past summer. Today I want to recognize the first-ever Science and Technology Policy Fellow to spend time at BLS — Samantha Tyner.
“AAAS Science & Technology Policy Fellowships (STPF) provide opportunities to outstanding scientists and engineers to learn first-hand about policymaking and contribute their knowledge and analytical skills in the policy realm. Fellows serve yearlong assignments in the federal government and represent a broad range of backgrounds, disciplines, and career stages. Each year, STPF adds to a growing corps over 3,000 strong of policy-savvy leaders working across academia, government, nonprofits, and industry to serve the nation and citizens around the world.”
This is the first year BLS has worked with AAAS to bring on a Science and Technology Fellow. We are so fortunate that Samantha (Sam) Tyner started in September and will be with us over the next year. Sam, one of about 200 fellows in the current class, earned her Ph.D. in statistics from Iowa State University and was most recently a postdoctoral researcher at the Center for Statistics and Applications in Forensic Evidence. She is working in the BLS Office of Survey Methods Research (OSMR), focusing on interactive data visualization, text mining, and effective communications to wider audiences.
find out a little bit about Sam and her fellowship. I asked her what drew her
to the federal government. She said she knew pretty early on in graduate school
that she didn’t want to go the traditional professor route. She also wasn’t
particularly interested in working in one of those internet giants, where the
statistics are interesting but the focus is on getting people to click more. She
wanted to find ways to use her statistical skills to solve real world problems,
and government seemed like a good place for that.
first impressions of BLS have been positive. “It’s like hanging out with a
bunch of professors, but the staff in OSMR is much more laid back.” One of her
current projects involves text mining of BLS mentions on Twitter — what are
people saying about us. We’ll use this research to learn how we can better
serve our customers.
Another project involves BLS data from the Quarterly Census of Employment and Wages. There is so much data each quarter, down to the county level. She is developing an R Shiny app that will graph these data and allow users to do quick searches. I got to see a quick demo — impressive work after only 2 months on the job.
is an expert in data visualization, so I asked her what she thinks of some of
the charts that BLS produces. I think she was a bit reluctant to criticize, but
the comment “you do have a lot of bar charts” was very telling. She describes
her goal as to “take a sad chart and make it better.” We certainly welcome her
guidance and look forward to producing fewer sad charts in the future.
Beyond all the work Sam is doing at BLS, she also provides posts on the AAAS blog, focusing on some practical aspects of her research. A recent blog taps into her expertise on data visualization. She writes about a problem that can sometimes occur when charts provide too much information. We hope we are not making this mistake with BLS charts.
glad that Samantha has gotten a good start to her Fellowship. We are planning
to take full advantage of her research and skills to improve BLS products. I
asked her what will make this year a success. Her response — a job offer. Maybe
at BLS, or at one of many government agencies where she can use her skills. She
will be an asset anywhere she goes.