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Topic Archives: Consumer Spending

How Timing and World Events Affect Price Statistics

Rising prices have certainly been in the news lately, and we have received a lot of questions about BLS price statistics. Some questions, however, are “evergreen.” Even in times of moderate price changes, BLS staff often hear that the Consumer Price Index (CPI) doesn’t reflect an individual’s experience. We address this concern and a wide range of other issues in our Questions and Answers about the CPI:

Q. Whose buying habits does the CPI reflect?

A. The CPI does not necessarily measure your own experience with price change. It is important to understand that BLS bases the market baskets and pricing procedures for the CPI-U and CPI-W populations on the experience of the relevant average household, not of any specific family or individual. For example, if you spend a larger-than-average share of your budget on medical expenses, and medical care costs are increasing more rapidly than the cost of other items in the CPI market basket, your personal rate of inflation may exceed the increase in the CPI. Conversely, if you heat your home with solar energy, and fuel prices are rising more rapidly than other items, you may experience less inflation than the general population does. A national average reflects millions of individual price experiences; it seldom mirrors a particular consumer’s experience.

Beyond the differences in individual spending habits, price statistics are affected by a variety of factors, including world events and the timing of price data collection. To explore these factors, we will look beyond the CPI to all BLS price indexes. We’ll focus on the price of oil and related items. Let’s start with a reminder of what is included in the BLS family of price indexes and look at how oil-related prices changed in March.

  • The Consumer Price Index measures the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services.
    • The CPI for gasoline (all types) rose 18.3 percent in March and 48.0 percent over the last 12 months.
    • The CPI for energy rose 11.0 percent in March and 32.0 percent over the last 12 months.
  • The Producer Price Index (PPI) measures the average change over time in the selling prices domestic producers receive for their output.
    • The PPI for crude petroleum rose 7.2 percent in March and 62.2 percent over the last 12 months.
    • The PPI for petroleum refineries rose 17.0 percent in March and 62.1 percent over the last 12 months.
    • The PPI for fuels and lubricants retailing rose 22.7 percent in March and 40.0 percent over the last 12 months.
  • The Import and Export Price Indexes show changes in prices of nonmilitary goods and services traded between the United States and the rest of the world.
    • The Import Price Index for crude petroleum rose 15.6 percent in March and 62.0 percent over the last 12 months.
    • The Export Price Index for crude petroleum rose 19.1 percent in March. (This is a new measure, and we haven’t yet tracked it over 12 months.)

National or international events, whether started by Mother Nature or human action, affect the prices businesses and consumers pay for goods and services. We’ve seen this in the past with weather disruptions, such as hurricanes along the Gulf Coast that shut down oil drilling and refining. Current prices may be influenced by the war in Ukraine, the embargo on Russian oil, and other events around the world.

We can see the influence of these events in price changes throughout the production and distribution of oil-related goods and services. BLS estimates the changes in the prices that domestic producers receive through the PPI; this includes petroleum-related industries such as drillers and refiners and the margins on gasoline station sales. Gasoline retailers make money on the margins of their sales—the difference between how much they pay for the fuel they buy from wholesalers and the prices they receive from consumers. Margins for gas stations typically decline when oil prices increase. To learn more, see “As crude oil plunges, retail gasoline margins spike, then retreat.”

Some domestic producers import oil rather than purchase it domestically, and the Import Price Index reflects changes in prices they pay. Some domestic producers also export petroleum-related products, which is captured in Export Price Indexes. Ultimately, consumers purchase gasoline, home heating oil, and other petroleum-based products, and often producers pass price changes on to consumers. Thus, an increase in oil prices can result in higher costs at the pump, more expensive airline fares, and price increases for goods transported by trucks. The CPI reflects these higher prices consumers may face.

The price of oil and related products can change rapidly, adding to the challenges of collecting and publishing timely price statistics. Ideally, BLS would collect prices throughout the month for all goods and services in all price indexes. While that is a long-term goal, it is not simple to implement. Currently, BLS identifies the official “pricing date” for each index, as follows:

  • We collect prices for the CPI throughout the month, with each outlet (such as a gas station) assigned one of three pricing periods, which roughly correspond to the first 10 days, second 10 days, and third 10 days of the month. Once established, prices are updated each month during the same pricing period.
  • We collect prices for most items in the PPI as of the Tuesday of the week containing the thirteenth day of the month. This is the case for the petroleum-related items. (Some items in the PPI have prices collected throughout the month.)
  • We obtain import price data for petroleum from the U.S. Department of Energy. We obtain export price data for petroleum from secondary source market prices. These data represent a weighted average of imported and exported oil throughout the month.

Let’s look at the price of oil over the past few months and how the BLS pricing dates might affect the price indexes.

Daily price per barrel of West Texas Intermediate Crude, January to March 2022

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

The chart shows the volatility of the oil prices, particularly in March. When the February CPI was released on March 10, West Texas Intermediate Crude Oil prices had already soared from $96 per barrel on the last day of February to over $123 two days before the CPI release. While consumers were feeling the pinch at the pump, this steep rise was not reflected in the February CPI data. Similarly, both the February and March PPI price dates (February 15 and March 15) missed the large run-up in oil prices in the first week of March. The Import Price Index, Export Price Index, and CPI did include the highest prices seen in early March, however.

BLS price indexes represent averages—average selections of goods and services, average weights, and typically average time periods. Over time, these indexes provide an accurate view of price change throughout the economy. But during periods of rapidly changing world events, and corresponding rapid changes in the price of individual commodities (and oil in particular), the index pricing periods may miss unusual highs and lows.

Daily price per barrel of West Texas Intermediate Crude, January to March 2022
DateDollars per barrel

Jan 3

$75.99

Jan 4

77.00

Jan 5

77.83

Jan 6

79.47

Jan 7

79.00

Jan 10

78.11

Jan 11

81.17

Jan 12

82.51

Jan 13

81.97

Jan 14

83.82

Jan 18

85.42

Jan 19

86.84

Jan 20

86.29

Jan 21

85.16

Jan 24

84.48

Jan 25

86.61

Jan 26

88.33

Jan 27

87.61

Jan 28

87.67

Jan 31

89.16

Feb 1

88.22

Feb 2

88.16

Feb 3

90.17

Feb 4

92.27

Feb 7

91.25

Feb 8

89.32

Feb 9

89.57

Feb 10

89.83

Feb 11

93.10

Feb 14

95.52

Feb 15

92.07

Feb 16

93.83

Feb 17

91.78

Feb 18

91.26

Feb 22

92.11

Feb 23

92.14

Feb 24

92.77

Feb 25

91.68

Feb 28

96.13

Mar 1

103.66

Mar 2

110.74

Mar 3

107.69

Mar 4

115.77

Mar 7

119.26

Mar 8

123.64

Mar 9

108.81

Mar 10

105.93

Mar 11

109.31

Mar 14

103.22

Mar 15

96.42

Mar 16

94.85

Mar 17

102.97

Mar 18

104.69

Mar 21

112.14

Mar 22

111.03

Mar 23

114.89

Mar 24

114.20

Mar 25

116.20

Mar 28

107.55

Mar 29

104.25

Mar 30

107.81

Mar 31

100.53

Spend Thanksgiving Day with BLS!

Thanksgiving is right around the corner. As we start to think about how we will celebrate, it might be hard to imagine the ties between BLS statistics and celebrating Thanksgiving. So, here’s a short tour of a typical Thanksgiving Day as seen through a few BLS statistics. Enjoy!

9:00 a.m. Put the turkey in the oven

All good chefs know the key to a successful Thanksgiving feast is to get the turkey in the oven bright and early. Whether you are roasting your turkey or firing up a deep fryer in the driveway, you will have to pay more for the fuel. The Consumer Price Index for household energy was pretty stable through 2019 and the first half of 2020 but then started a steady rise in September 2020.

Consumer Price Index for household energy, 2019–21

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

10:00 a.m. Watch the Macy’s Thanksgiving Day parade

The COVID-19 pandemic has caused ups and downs in the labor market, much like the impact of a windy day for the famous balloons in Macy’s Thanksgiving Day Parade. Keeping with the department store theme, employment in department stores plunged 25.3 percent in April 2020 but then rose 14.1 percent June 2020. These gyrations were more dramatic than the broader retail trade sector.

Monthly percent change in employment in retail trade and department stores, 2019–21

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

2:00 p.m. Scope out Black Friday deals

After watching the parade, it’s time to plan our Black Friday shopping! As consumers, we are always trying to get more for less. In the retail trade industry, it turns out they are doing just that. The industry has produced more output with steady or decreasing hours worked. The result is a corresponding increase in labor productivity. Now, only if we could prepare a bigger Thanksgiving feast in less time!

Indexes for labor productivity, hours worked, and output in retail trade, 2007–20

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

4:00 p.m. Play touch football

We need to make some room of the feast we are about to enjoy, so we assemble willing participants and play some touch football in the yard. The American Time Use Survey is the best source of information on how Americans spend their time each day. In this case, let’s compare how much time people spend playing sports versus how much time they spend watching sports on TV. We’ll look only at time spent in these activities on weekend days and holidays. The survey does not have details on what people watch on TV, but we can assume some time reported here is spent watching sports.

Average hours spent watching TV and playing sports, weekend days and holidays, 2019

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

We can see that Americans, on average, easily spend more time watching TV—3.36 hours—than playing sports—0.34 hours. But what is more interesting is that, on average, those who watch TV watch about 24 percent more than the overall population. However, those who play sports play, on average, nearly 6 times as many hours as the average for the population.

6:00 p.m. Thanksgiving feast

No matter what is on your dinner table this Thanksgiving, chances are it will cost more than previous years. All six major grocery store food groups in the Consumer Price Index for food at home continued to rise sharply in October 2021. Even if you decide to order out, it will set you back a bit more this year. Both full-service meals and limited services meals rose nearly 1 percent in October 2021.

Consumer Price Indexes for food at home and food away from home, 2018–21

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

7:00 p.m. Watch football

Now that we’ve finished our delicious feast, it’s a time-honored tradition to watch a bit of football on TV. If you are buying a new TV for this holiday, you can expect to pay a bit more. After years of steady declines, import prices for television and video receivers have reversed trend in 2021, much like a wide receiver changing direction to find an opening and catch a game-winning touchdown pass!

Import price index for television and video receivers, 2011–21

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

9:00 p.m. Say goodbye

It’s hard to say goodbye to your friends and family. In the United States, however, the Job Openings and Labor Turnover Survey is showing that workers are saying goodbye to their employers more often these days. The number of quits has been rising steadily since the shock of the pandemic affected layoffs and discharges in early 2020. (It’s only a coincidence that the layoffs line in the chart below looks like the outline of a pilgrim’s hat.)

Quits, layoffs and discharges, and other job separations, 2019–21

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

Now we’ve come to the end of our Thanksgiving feast of BLS data. Our hunger for the premier statistics on the U.S. labor force, prices, and productivity, has been satisfied, and we can rest easily knowing there’s a stat for that!

Consumer Price Index for household energy
MonthIndex

Jan 2019

100.000

Feb 2019

99.662

Mar 2019

100.046

Apr 2019

99.952

May 2019

99.679

Jun 2019

99.258

Jul 2019

99.415

Aug 2019

99.253

Sep 2019

99.033

Oct 2019

99.756

Nov 2019

99.890

Dec 2019

99.716

Jan 2020

99.666

Feb 2020

99.355

Mar 2020

98.812

Apr 2020

98.492

May 2020

98.278

Jun 2020

98.501

Jul 2020

98.542

Aug 2020

98.478

Sep 2020

99.590

Oct 2020

100.103

Nov 2020

101.043

Dec 2020

101.377

Jan 2021

101.299

Feb 2021

102.681

Mar 2021

103.436

Apr 2021

104.748

May 2021

105.512

Jun 2021

105.840

Jul 2021

106.664

Aug 2021

107.833

Sep 2021

109.273

Oct 2021

112.872
Monthly percent change in employment in retail trade and department stores
MonthRetail tradeDepartment stores

Jan 2019

-0.1%0.2%

Feb 2019

-0.2-1.4

Mar 2019

-0.1-0.6

Apr 2019

-0.1-0.9

May 2019

-0.1-0.5

Jun 2019

-0.1-0.7

Jul 2019

0.0-0.9

Aug 2019

-0.1-1.4

Sep 2019

0.10.3

Oct 2019

0.20.0

Nov 2019

-0.20.4

Dec 2019

0.3-0.4

Jan 2020

-0.1-2.7

Feb 2020

0.00.3

Mar 2020

-0.8-0.6

Apr 2020

-14.5-25.3

May 2020

3.16.7

Jun 2020

6.314.1

Jul 2020

1.74.3

Aug 2020

1.72.3

Sep 2020

0.2-0.8

Oct 2020

0.70.2

Nov 2020

0.00.7

Dec 2020

0.2-0.6

Jan 2021

0.1-0.3

Feb 2021

0.10.5

Mar 2021

0.30.1

Apr 2021

-0.10.2

May 2021

0.40.9

Jun 2021

0.61.3

Jul 2021

0.00.3

Aug 2021

0.1-0.5

Sep 2021

0.40.5

Oct 2021

0.2-0.2
Indexes for labor productivity, hours worked, and output in retail trade
YearLabor productivityHours workedOutput

2007

100.000100.000100.000

2008

97.76597.65895.475

2009

98.29492.03290.461

2010

100.69492.66793.310

2011

101.39794.68696.008

2012

103.65595.67399.170

2013

108.08095.212102.905

2014

109.91997.268106.916

2015

113.48698.821112.148

2016

118.52598.636116.908

2017

120.71999.896120.593

2018

124.39399.783124.123

2019

130.36098.139127.934

2020

140.39294.650132.880
Average hours spent watching TV and playing sports, weekend days and holidays, 2019
ActivityHours

Watching TV (average of population)

3.36

Watching TV (average of those who watched TV)

4.17

Playing sports (average of population)

0.34

Playing sports (average of those who played sports)

1.94
Consumer Price Indexes for food at home and food away from home
MonthFood at homeFood away from home

Jan 2018

100.000100.000

Feb 2018

99.793100.243

Mar 2018

99.780100.352

Apr 2018

100.026100.594

May 2018

99.779100.929

Jun 2018

99.865101.113

Jul 2018

100.127101.229

Aug 2018

100.198101.421

Sep 2018

100.252101.645

Oct 2018

100.046101.738

Nov 2018

100.259102.029

Dec 2018

100.554102.437

Jan 2019

100.683102.789

Feb 2019

101.014103.153

Mar 2019

101.163103.342

Apr 2019

100.716103.676

May 2019

100.913103.894

Jun 2019

100.718104.232

Jul 2019

100.716104.443

Aug 2019

100.654104.669

Sep 2019

100.902104.940

Oct 2019

101.124105.139

Nov 2019

101.324105.310

Dec 2019

101.331105.611

Jan 2020

101.440106.000

Feb 2020

101.851106.236

Mar 2020

102.220106.395

Apr 2020

104.775106.550

May 2020

105.718106.942

Jun 2020

106.309107.496

Jul 2020

105.343108.002

Aug 2020

105.322108.309

Sep 2020

105.051108.911

Oct 2020

105.177109.210

Nov 2020

105.012109.342

Dec 2020

105.335109.751

Jan 2021

105.203110.122

Feb 2021

105.474110.180

Mar 2021

105.587110.311

Apr 2021

106.047110.649

May 2021

106.423111.258

Jun 2021

107.309112.047

Jul 2021

108.031112.923

Aug 2021

108.431113.405

Sep 2021

109.779114.013

Oct 2021

110.841114.965
Import price index for television and video receivers
MonthIndex

Jan 2011

100.000

Feb 2011

100.173

Mar 2011

100.173

Apr 2011

99.136

May 2011

98.964

Jun 2011

97.409

Jul 2011

97.064

Aug 2011

96.373

Sep 2011

95.855

Oct 2011

94.991

Nov 2011

93.092

Dec 2011

94.128

Jan 2012

94.819

Feb 2012

94.473

Mar 2012

93.955

Apr 2012

92.573

May 2012

92.573

Jun 2012

92.401

Jul 2012

92.401

Aug 2012

92.573

Sep 2012

92.228

Oct 2012

92.573

Nov 2012

90.155

Dec 2012

90.155

Jan 2013

89.810

Feb 2013

89.637

Mar 2013

88.256

Apr 2013

88.083

May 2013

87.910

Jun 2013

87.910

Jul 2013

87.392

Aug 2013

87.219

Sep 2013

85.838

Oct 2013

85.492

Nov 2013

85.492

Dec 2013

85.492

Jan 2014

85.320

Feb 2014

85.320

Mar 2014

85.147

Apr 2014

84.801

May 2014

84.283

Jun 2014

84.111

Jul 2014

83.074

Aug 2014

82.902

Sep 2014

83.074

Oct 2014

81.865

Nov 2014

81.865

Dec 2014

81.347

Jan 2015

79.965

Feb 2015

79.965

Mar 2015

79.965

Apr 2015

79.965

May 2015

79.620

Jun 2015

79.620

Jul 2015

79.620

Aug 2015

79.620

Sep 2015

79.620

Oct 2015

79.447

Nov 2015

79.275

Dec 2015

78.929

Jan 2016

78.756

Feb 2016

77.547

Mar 2016

77.375

Apr 2016

77.029

May 2016

76.857

Jun 2016

77.029

Jul 2016

76.857

Aug 2016

76.684

Sep 2016

76.684

Oct 2016

76.684

Nov 2016

76.684

Dec 2016

76.684

Jan 2017

76.166

Feb 2017

76.166

Mar 2017

75.820

Apr 2017

75.993

May 2017

75.993

Jun 2017

75.993

Jul 2017

75.993

Aug 2017

75.993

Sep 2017

75.820

Oct 2017

75.475

Nov 2017

75.302

Dec 2017

75.130

Jan 2018

75.130

Feb 2018

75.302

Mar 2018

74.784

Apr 2018

74.439

May 2018

74.266

Jun 2018

73.575

Jul 2018

72.884

Aug 2018

72.884

Sep 2018

72.712

Oct 2018

72.539

Nov 2018

72.366

Dec 2018

72.021

Jan 2019

71.330

Feb 2019

70.812

Mar 2019

70.466

Apr 2019

70.466

May 2019

70.294

Jun 2019

69.948

Jul 2019

69.775

Aug 2019

69.603

Sep 2019

69.603

Oct 2019

69.430

Nov 2019

69.085

Dec 2019

68.912

Jan 2020

69.430

Feb 2020

68.048

Mar 2020

67.358

Apr 2020

66.839

May 2020

66.667

Jun 2020

66.667

Jul 2020

66.494

Aug 2020

66.494

Sep 2020

66.321

Oct 2020

66.667

Nov 2020

67.358

Dec 2020

68.048

Jan 2021

68.739

Feb 2021

68.739

Mar 2021

68.566

Apr 2021

69.775

May 2021

70.639

Jun 2021

70.812

Jul 2021

73.402

Aug 2021

73.402

Sep 2021

74.439

Oct 2021

74.784
Quits, layoffs and discharges, and other job separations
MonthQuitsLayoffs and dischargesOther separations

Jan 2019

3,521,0001,689,000301,000

Feb 2019

3,543,0001,769,000353,000

Mar 2019

3,524,0001,721,000331,000

Apr 2019

3,494,0001,954,000313,000

May 2019

3,487,0001,776,000307,000

Jun 2019

3,527,0001,771,000316,000

Jul 2019

3,627,0001,826,000344,000

Aug 2019

3,591,0001,825,000306,000

Sep 2019

3,449,0001,982,000345,000

Oct 2019

3,414,0001,793,000359,000

Nov 2019

3,482,0001,788,000374,000

Dec 2019

3,487,0001,952,000354,000

Jan 2020

3,568,0001,788,000358,000

Feb 2020

3,430,0001,953,000332,000

Mar 2020

2,902,00013,046,000360,000

Apr 2020

2,107,0009,307,000368,000

May 2020

2,206,0002,096,000316,000

Jun 2020

2,646,0002,204,000331,000

Jul 2020

3,182,0001,845,000365,000

Aug 2020

2,987,0001,573,000342,000

Sep 2020

3,307,0001,555,000373,000

Oct 2020

3,352,0001,728,000347,000

Nov 2020

3,296,0002,123,000325,000

Dec 2020

3,407,0001,823,000352,000

Jan 2021

3,306,0001,724,000294,000

Feb 2021

3,383,0001,723,000323,000

Mar 2021

3,568,0001,525,000343,000

Apr 2021

3,992,0001,450,000360,000

May 2021

3,630,0001,353,000347,000

Jun 2021

3,870,0001,354,000389,000

Jul 2021

4,028,0001,423,000341,000

Aug 2021

4,270,0001,385,000378,000

Sep 2021

4,434,0001,375,000410,000

BLS Data in More Than a Century of Pictures

BLS was established in 1884, and some of our programs date back nearly that far. We have more than a century of statistics on prices, employment, wages, productivity, and more. But even in those early days, we realized that pages full of numbers can be a little dull. We frequently use pictures to tell the stories behind those numbers and help readers see the important points more quickly. Let’s look at over a century of BLS price statistics, in five charts.

The first chart, which looks hand drawn, was originally presented as part of the Department of Labor’s exhibit at the Century of Progress International Exposition in Chicago in 1933, also known as the Chicago World’s Fair.

Poster for Century of Progress International Exposition in Chicago in 1933

The chart below depicts changes in the cost of living from 1913 to 1932, based on the BLS Consumer Price Index. Here we see market baskets (with legs) rising during World War I, then declining and holding steady during the roaring 1920s, and declining as the nation entered the Great Depression.

Chart showing changes in cost of living from 1913 to 1932, based on the Consumer Price Index

Source: What Are Labor Statistics For? A Series of Pictorial Charts, Bulletin of the United States Bureau of Labor Statistics, No. 599, published in 1933.

The next chart, again looking hand drawn – this time perhaps with a ruler – compares wholesale prices (what we now call the Producer Price Index) in the years leading up to the United States entering World War I and World War II. It comes from the first of two BLS bulletins on Wartime Prices. The increase in the wholesale price for all commodities was nearly twice as great in the earlier period, reflecting large differences in the price change for such commodities as fuel and chemicals.

Chart showing percent changes in wholesale prices for commodities in World War 1 and World War 2

Source: Wartime Prices, Bulletin of the United States Bureau of Labor Statistics, No. 749, published in 1944.

Now, let’s move forward about 20 years. BLS published a chart book in 1963 focusing on price changes over the prior decade. The chart book presented both consumer and wholesale prices for the nation, along with consumer price trends in the 12 largest U.S. cities. The chart shown here, perhaps produced on an early computer, tracks the change in prices for all consumer items, and separately for various categories. Prices for durable commodities, such as appliances and furniture, declined in the early part of the period and later rebounded, resulting in virtually no price change over the decade. In contrast, the price of services, such as shelter, transportation, and medical care, rose steadily throughout the period.

Chart showing changes in consumer prices, 1953 to 1962

Source: Prices: A Chartbook, 1953–62, Bulletin of the United States Bureau of Labor Statistics, No. 1351, published in 1963.

With advances in computer software, BLS expanded the use of charts to allow readers to visualize data trends. Such charts became prominent in the BLS flagship publication, the Monthly Labor Review. In an article from 1987, data from the BLS International Price Program track price changes for selected imports.

Chart showing changes in U.S. Import Price Indexes for machinery and transportation equipment and intermediate manufactures, 1982 to 1986

Source: “Import price declines in 1986 reflected reduced oil prices,” Monthly Labor Review, April 1987.

BLS ushered in the age of interactive charts in recent years, making chart packages available with most news releases. In the chart below, readers can track a decade of consumer price changes for all items, and then click on selected categories to compare trends. Want to compare price changes for food at home with food away from home? It’s just a couple of clicks away.

Chart showing 12-month changes in the Consumer Price Index, August 2001 to August 2021

Source: Charts related to the Consumer Price Index news release.

Our charts today are a lot more sophisticated than the hand-drawn charts of the early twentieth century. They may not have amusing cartoon characters like the CPI market basket with legs, but they have interactive features that let you dig into more details about the data or choose the data you want to see. We also have several publications that focus on the visual display of data. Check out The Economics Daily and Spotlight on Statistics!

It’s a Small Statistical World

BLS is one of several U.S. statistical agencies that follow consistent policies and share best practices. These agencies also frequently work with their statistical counterparts around the world to develop standards, share information, troubleshoot issues, and improve the quality of available data. At BLS, our Division of International Technical Cooperation coordinates these activities. The division helps to strengthen statistical development by organizing seminars, consultations, and meetings for international visitors with BLS staff. The division also provides BLS input on global statistical initiatives. Without missing a beat, most of these activities moved to virtual platforms during the COVID-19 pandemic. Despite some time-zone challenges, which often lead to early morning or late-night video meetings, BLS continues to play an active role on the world stage.

World map

Today I’m highlighting some recent international engagements, which have included our colleagues from Australia, Canada, France, Greece, Italy, Mexico, South Korea, and the United Kingdom. These events are often mutually beneficial, as they provide opportunities for BLS staff to learn more about the experiences of our international counterparts.

  • BLS staff met with a former Australian Bureau of Statistics official who was working with the U.K. Statistics Authority and the U.K. Office for National Statistics to research best practices in implementing international statistical standards. They discussed the international comparability of domestic industry and product classifications, data quality and publishing, and the independence of statistical organizations.
  • Staff from the Australian Bureau of Statistics are planning to revise their household expenditure survey. They turned to BLS experts, who shared their insights and experiences in improving our Consumer Expenditure Surveys.
  • Staff from the Statistical Division at the United Nations asked BLS to comment on issues surrounding the classification of business functions; household income, consumption, and wealth; and unpaid household service work. Input from staff in multiple offices will inform the BLS response to this request.
  • BLS staff, our counterparts in Canada and Mexico, and colleagues from across Europe and Asia discussed data ethics in a meeting organized by the Centre for Applied Data Ethics at the U.K. Statistics Authority. Country representatives summarized how their organizations assess ethical considerations when producing official statistics. The U.K. Statistics Authority identified the following ethical considerations as being especially important:
Public Good: The use of data has clear benefits for users and serves the public good.
Confidentiality, Data Security: The data subject's identity (whether person or organisation) is protected, information is kept confidential and secure, and the issue of consent is considered appropriately.
Methods and Quality: The risks and limits of new technologies are considered and there is sufficient human oversight so that methods employed are consistent with recognised standards of integrity and quality.
Legal Compliance: Data used and methods employed are consistent with legal requirements.
Public Views and Engagement: The views of the public are considered in light of the data used and the perceived benefits of the research.
Transparency: The access, use and sharing of data is transparent, and is communicated clearly and accessibly to the public.

From its founding, BLS has understood the importance of these issues. Our written policies and strategic plans reflect these principles. They also are reflected in the Foundations for Evidence-Based Policymaking Act and the newly formed Scientific Integrity Task Force, which includes BLS staff among its members.

And that’s just some of what we did this summer! BLS has a longstanding reputation for providing expert training and guidance and participating in international statistical forums. We also provide BLS data to the International Labour Organization and the Organisation for Economic Cooperation and Development, among others. These organizations often feature BLS statistics in their databases. Since its inception, BLS has provided technical assistance to our international counterparts, starting with our first Commissioner, Carroll Wright, who directed BLS staff to advise foreign governments establishing statistical agencies. Commissioner Wright was also a member of several international statistical associations, a tradition that continues today. Currently, BLS staff participate in many international expert groups, including the Voorburg Group on Service Statistics, the Wiesbaden Group on Business Registers, and the International Conference of Labor Statisticians. These groups provide BLS staff with opportunities to discuss topics of common interest, to propose and learn about innovative solutions to data measurement issues, and to influence discussions about important economic concepts.

BLS began providing technical assistance in earnest in the late 1940s as part of the U.S. government’s European Economic Recovery Program. BLS staff planned and conducted productivity studies and helped European governments establish their own economic statistics. Similar efforts continue today for our colleagues around the world, many of whom have participated in our international training programs. While we have temporarily halted in-person training programs because of the pandemic, our staff plan to provide more training modules virtually in response to the popularity of these programs. Over the last 10 years, BLS has provided training or other technical assistance to over 1,700 seminar participants and other visitors from 95 countries. More recently, the International Monetary Fund has asked BLS to provide training on Producer Price Indexes and Import and Export Price Indexes to our colleagues abroad.

I am incredibly grateful to all the subject matter experts throughout BLS who provide invaluable assistance with these activities and help maintain our excellent reputation in the international statistical community. We look forward to your continued support as BLS strengthens important international relationships, virtually for now, and hopefully in person soon.

The Latest on Improving the Accuracy of the Consumer Price Index

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.