Inflation, as Seen through the Bake Shop Window

June 2, 2022BLS Commissioner

At BLS, we are always looking for new ways to help readers understand the latest economic data. As measures of price change have garnered a heaping amount of financial coverage lately, the pastry chefs who publish our monthly inflation figures are experimenting with some new recipes to highlight current results. Our first attempt, straight out of the fryer: an inflation doughnut, in honor of National Doughnut Day.

We don’t mean to sugarcoat the impact of inflation on economic markets and household budgets, as high inflation can have disruptive and acrid consequences. Instead, we aim here to showcase the statistics in a window display that highlights the data in a fresh perspective. We start with an inflation doughnut, which is divided into sections to compare how many prices are increasing (inflation), decreasing (deflation), or remaining unchanged. You can display an inflation doughnut for just one month (think of it as just a doughnut hole) or over a longer time like a year or more (like a baker’s dozen). For this price change doughnut, we show all the ingredients to overall price change—the increases, the decreases, and the components with no change. Let’s look at an inflation doughnut example from the Consumer Price Index.

Consumer Price Index: Distribution of 12-month price changes for all goods and services, April 2022

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

But not everyone likes doughnuts, including my editors, who seem partial to crullers and other more linear pastries. Apparently, these circular graphics can be hard to understand. So, the charts below focus on the same data, but with a different look. Nonetheless, the doughnut references are too good to pass up.

As a reminder, BLS has three monthly price programs, each of which produces many different estimates. By tracking each of these programs, you can learn more about price transmission through the production process. (Hmm, that sounds like a topic for a future blog.) Here’s a brief reminder about the BLS price programs:

The Import/Export Price Indexes contain data on changes in prices of nonmilitary goods and services traded between the United States and the rest of the world. As the new kid on the block, import and export price indexes are like those new gourmet doughnuts, perhaps topped with bacon and maple syrup.
The Producer Price Index (PPI) measures the average change over time in the selling prices received by domestic producers for their output. As the oldest price index program, the PPI is the workhorse, your basic powdered doughnut. It’s been around for years but still hits the spot.
The Consumer Price Index (CPI) measures the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. The CPI is the doughnut on the top shelf that gets most of the attention, maybe with chocolate frosting and multi-colored sprinkles.

Now that your mouth is watering, let’s look at the data.

Starting with import and export price data, we can see that nearly half of import item prices were higher over the past year, with 48 percent of all imports prices exhibiting inflationary trends; for imports of consumer goods, 42 percent had higher prices. We see similar trends among exports.

Import Price Index: Distribution of 12-month price changes for all imports and import consumer goods, April 2022

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

With the PPI, we focus on the share of industries showing price changes. Data are available for three different sectors. In keeping with the doughnut theme, goods-producing industries represent the jelly filling, with 98 percent of these industries exhibiting inflation over the past year. In the center, or the cake, 86 percent of service-providing industries were inflationary. Finally, the strawberry glaze on the outside looks at construction industries, with all showing inflation.

Producer Price Index: Distribution of 12-month price changes for industry groups, April 2022

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

Finally, we look again at data for the CPI, but this time our doughnuts are flattened. Here we show the share of items in the market basket that experience rising or falling prices or no change. As a doughnut, the “core” CPI, that is, all items less food and energy, is somewhat vanilla, like Boston Cream filling. Over the past 12 months, about three-quarters of core items have shown price increases, 19 percent have shown price decreases, and a small percentage show no change. In contrast, the prices for food and energy pack more zest, like a chocolate glaze, showing considerable inflation—nearly 89 percent of items—with only a small amount of deflation. The food and energy inflation may be influenced by rising energy prices, perhaps related to an increase in late-night drives to the local bakery.

Consumer Price Index: Distribution of 12-month price changes for core and food and energy goods and services, April 2022

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

We hope our tour of the pastry shop has added some spice to your understanding of price change statistics. For more traditional graphics showing trends in BLS data, check out the Graphics for Economic News Releases page on our website. Next time, try the pumpkin spice.

Consumer Price Index: Distribution of 12-month price changes for all goods and services, April 2022
Index	Inflation	Deflation	No change
CPI for All Urban Consumers	78.0	16.5	5.5

Import Price Index: Distribution of 12-month price changes for all imports and import consumer goods, April 2022
Category	Inflation	Deflation	No change
All imports	47.7	13.7	38.6
Import consumer goods	42.0	12.8	45.3

Producer Price Index: Distribution of 12-month price changes for industry groups, April 2022
Industry group	Inflation	Deflation	No change
Goods-producing industries	98	1	1
Service-providing industries	86	5	9
Construction industries	100	0	0

Consumer Price Index: Distribution of 12-month price changes for core and food and energy goods and services, April 2022
Category	Inflation	Deflation	No change
Core	74.2	19.0	6.8
Food and energy	88.6	9.4	2.0

Topics: Consumer Spending | Inflation and Prices

Tags: Consumer Price Index, Consumer spending, CPI, Data visualization, Exports, Imports, Producer Price Index, Statistics awareness

Employment Trends of Asians and Native Hawaiians and Other Pacific Islanders

May 25, 2022BLS Commissioner

May is Asian Pacific American Heritage Month, so let’s take a closer look at national employment statistics for Asians and for Native Hawaiians and Other Pacific Islanders. We’ll focus on how labor market conditions for these groups continue to recover from the effects of the COVID-19 pandemic.

BLS has been collecting data in the Current Population Survey on the labor market characteristics of people who identify their race as Asian or Native Hawaiian or Other Pacific Islander since 2003. Looking at historical data, the employment–population ratio—the percentage of the population that is employed—is generally higher for Asians and for Native Hawaiians or Other Pacific Islanders than the U.S. average. The ratio in 2019 was 62.3 percent for Asians and 66.2 percent for Native Hawaiians or Other Pacific Islanders, well above the national average of 60.8 percent. The ratios for all groups declined sharply in 2020 with the onset of the COVID-19 pandemic. Employment–population ratios had not yet fully recovered in 2021, but the ratios for Asians and Native Hawaiians or Other Pacific Islanders continued to be higher than the U.S. average. The greater likelihood of employment among Asians and Native Hawaiians or Other Pacific Islanders reflects the fact that larger shares of both groups are ages 25 to 54 than the overall population. People in this age range are more likely to be employed than people in younger and older age groups.

Employment–population ratios of the total population, Asians, and Native Hawaiians or Other Pacific Islanders, 2003–21 annual averages

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

The following chart shows how the labor market improved in 2021 compared to 2020 but remained below its 2019 pre-pandemic level. The employment–population ratio increased by 1.6 percentage points from 2020 to 2021 but remained 2.4 percentage points below its 2019 level. Similarly, this ratio increased by 3.3 percentage points for Asians and 1.4 percentage points for Native Hawaiians or Other Pacific Islanders in 2021. The ratio for Asians in 2021 was still 1.7 percentage points lower than in 2019, while the ratio for Native Hawaiians or Other Pacific Islanders was still 4.0 percentage points lower.

Employment–population ratios of the total population, Asians, and Native Hawaiians or Other Pacific Islanders, 2019–21 annual averages

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

The increase in the employment–population ratio between 2020 and 2021 varied for different groups within the Asian population. For example, this measure rose by 3.7 percentage points for Asian women and 2.9 percentage points for Asian men in 2021. The rise in the employment–population ratio was about twice as large for workers ages 16 to 24 (4.0 percentage points) and 25 to 54 (4.1 percentage points) than those age 55 and older (2.0 percentage points). Similarly, the increase in the percentage of foreign-born Asians (3.9 percentage points) who were employed was more than twice the increase for native-born Asians (1.8 percentage points). (Unfortunately, we can’t make these same comparisons for Native Hawaiians or Other Pacific Islanders because of their small sample size in the survey.)

Percentage point change in employment–population ratios for Asian groups, 2020 to 2021

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

Asian Americans trace their roots to many different distinct and culturally diverse peoples. We collect information on seven different Asian groups—Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, and Other Asian. As shown in the chart below, Asian Indians and Chinese are the largest groups of Asian Americans. Japanese, at 5 percent, represent the smallest share.

Percent distribution of the Asian population age 16 and older by detailed groups, 2021

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

Although the employment–population ratios for many of these groups increased in 2021, most remained below their 2019 pre-pandemic levels. After having the largest decline in their employment–population ratio from 2019 to 2020 (-9.2 percentage points), Vietnamese had the largest over-the-year gain in 2021 (7.1 percentage points) but remained 2.1 percentage points below the 2019 level. The employment–population ratio for Koreans in 2021, 5.9 percentage points below the 2019 level, had the largest decline over this 2-year period. The employment–population ratio of Asian Indians, however, had returned to the 2019 level in 2021.

Employment–population ratios of detailed Asian groups, 2019–21

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

This is just a sample of the information available on the labor force status of Asian Americans and Native Hawaiians and Other Pacific Islanders. Explore some of our other resources to expand your knowledge.

Employment–population ratios, 2003–21 annual averages
Year	Total population	Asian	Native Hawaiian or Other Pacific Islander
2003	62.3%	62.4%	63.6%
2004	62.3	63.0	67.4
2005	62.7	63.4	70.2
2006	63.1	64.2	70.6
2007	63.0	64.3	69.4
2008	62.2	64.3	67.8
2009	59.3	61.2	61.8
2010	58.5	59.9	60.1
2011	58.4	60.0	62.2
2012	58.6	60.1	63.0
2013	58.6	61.2	62.9
2014	59.0	60.4	63.5
2015	59.3	60.4	62.8
2016	59.7	60.9	65.7
2017	60.1	61.5	62.9
2018	60.4	61.6	64.9
2019	60.8	62.3	66.2
2020	56.8	57.3	60.8
2021	58.4	60.6	62.2

Employment–population ratios, 2019–21 annual averages
Year	Total population	Asian	Native Hawaiian or Other Pacific Islander
2019	60.8%	62.3%	66.2%
2020	56.8	57.3	60.8
2021	58.4	60.6	62.2

Percentage point change in employment–population ratios for Asian groups, 2020 to 2021
Characteristic	Change from 2020 to 2021	2020	2021
Total	3.3	57.3	60.6
Men	2.9	65.4	68.3
Women	3.7	50.2	53.9
Age
Ages 16 to 24	4.0	33.4	37.4
Ages 25 to 54	4.1	73.5	77.6
Age 55 and older	2.0	37.3	39.3
Country of birth
Foreign born	3.9	57.0	60.9
Native born	1.8	57.5	59.3

Percent distribution of the Asian population age 16 and older by detailed groups, 2021
Asian group	Percent distribution
Asian Indian	22.9%
Chinese	22.1
Other Asian	17.7
Filipino	14.9
Vietnamese	10.1
Korean	7.2
Japanese	5.0

Employment–population ratios of detailed Asian groups, 2019–21
Year	2019	2020	2021
Asian Indian	66.6%	63.2%	66.6%
Filipino	63.9	55.8	60.6
Vietnamese	61.2	52.0	59.1
Other Asian	61.1	56.5	59.7
Chinese	60.4	56.6	59.7
Korean	60.3	55.6	54.4
Japanese	56.1	53.8	53.1

Topics: Employment | Labor Force Characteristics

Tags: Asian, Employment Situation, Labor market trends, Native Hawaiians and Other Pacific Islanders

A Blueprint for Modernizing the Consumer Price Index

May 24, 2022BLS Commissioner

At BLS, we never stop improving. We highly value any input from our data users, technical advisors, and other experts that helps us improve our high quality economic statistics. On May 3, 2022, we welcomed the latest evaluation of one of our statistical programs from the National Academy of Sciences, Committee on National Statistics (CNSTAT): Modernizing the Consumer Price Index for the 21st Century.

As we first reported in December 2019, CNSTAT convened an expert panel to study the Consumer Price Index (CPI). In our update in August 2021, we shared the panel membership and described the public meetings where the panel gathered information for its report. Now that the panel has completed its report, we share our plans to address their recommendations:

Adopt an alternative data strategy that significantly expands the use of new data sources and collection methods.
Improve the timeliness and quality of market basket weights in the CPI.
Continue research to enhance and inform the public’s understanding of consumer price change for shelter and medical care.
Calculate income-based CPIs and address methodology limitations.
Collaborate across the federal and international statistical system.

Use Alternative Data Sources

The chapter on modernizing elementary indexes focused on alternative data sources. Using data from sources beyond traditional surveys is a theme throughout the report. The recommendation to develop a household scanner data program would be a long-term strategy to address many challenges of calculating an accurate and timely CPI. BLS agrees with the panel to seek new data sources to improve every aspect of price index calculation: prices, expenditures (including the quantities purchased), quality adjustment, modeling, estimation, and imputation. Doing so will enable BLS to improve and expand the data we produce and provide users the data they need when they need it.

Even before the CNSTAT report, BLS has been busy building a pipeline of alternative data sources and improving our estimation methods for the CPI. Increasing the focus on alternative data should generate a steady flow of new data sources. This focus also will improve our ability to collect data through a variety of methods and give us new opportunities to address quality change. Consistent with our values to provide accessible information, we will keep you informed about new data sources and methods through the BLS website.

Improve Timeliness and Quality of Market Basket Weights

Beginning in January 2023, BLS plans to update market basket weights in the CPI annually, using 1 year of data. This change will immediately improve the timeliness of the market basket. BLS will continue our efforts to collect and process data more quickly to calculate the CPI using the most recent spending information.

BLS uses several data sources to adjust data collected in the Consumer Expenditure Surveys to calculate the CPI market basket weights. BLS will analyze the feasibility of using business data from the Bureau of Economic Analysis to adjust for categories consumers are reluctant to report, such as alcohol and tobacco. BLS plans to research alternative data sources to improve expenditure estimates when information from respondents is missing or aggregated.

BLS continues to believe collecting data directly from consumers is important to achieve our measurement objective. We are conducting research on a Household Cost Index, which requires household-level expenditure estimates to calculate household-specific indexes. As the panel notes, indexes for specific populations also require linking expenditures with information about households. Given current resources, we do not plan to expand our use of data from other sources in the next few years to supplement data collected in the Consumer Expenditure Surveys. In the future, BLS could pursue a household scanner data program to address the concerns the panel raises regarding the Consumer Expenditure Surveys.

Modernize Shelter

BLS is exploring alternative data sources to supplement rents collected in our housing survey and improve imputation of rental equivalence estimates for owner-occupied housing . We will continue to produce research indexes that meet user needs. BLS plans to publish research on a rent index focused on new tenants. Future research will target alternatives to rent data as a proxy for rental equivalence in predominantly owner-occupied areas and alternatives to the rental equivalence approach for high-end properties.

All BLS consumer indexes currently use a rental equivalence approach to target a cost-of-living measurement objective. Research indexes based on occupancy (renter and owner) will provide users with more insight. Some users need indexes for certain populations. As already mentioned, BLS will continue to research a Household Cost Index that uses a payments approach for owner-occupied housing. Some of these research indexes may ultimately be “promoted” to official status.

Modernize Medical Care

BLS uses an indirect method to price health insurance because directly pricing health insurance premiums is difficult. We have confirmed the retained earnings data incorporate rebates and will pursue further improvements to the indirect approach. We are pursuing implementation of claims data for physician’s and hospital outpatient services and will monitor hospital price transparency data as a possible data source in the future. Research comparing the indirect and direct methods is well underway and will be published initially as a research paper.

Calculate Supplemental Population Price Indexes

BLS continues research on producing price indexes by income groups. While BLS recognizes the limited benefit of reweighting the market basket to create indexes for particular population groups, we believe indexes for renters and owners will provide more insight into measuring price change for shelter. BLS will continue to seek cost-effective methods to study household behaviors and seek resources to collect household scanner data linked with demographics.

Collaborate with Other Statistical Organizations

Another theme throughout the report is communication and collaboration among statistical agencies. The panel recommended expanding collaboration, especially in research and data sharing. As the complexity of data sources and methods increases, BLS also needs to communicate with stakeholders to maintain transparency. Our practice is to announce on the BLS website in advance any changes to our data sources or methods. We will continue to share research index results to document the impact of these changes. BLS is looking into new ways of sharing data and improving transparency.

We value our partnerships with other agencies in the federal and international statistical community. In June 2022, we will share the CNSTAT recommendations with the Federal Economic Statistics Advisory Committee and discuss our plans. We will continue to seek out new opportunities to connect and collaborate with colleagues in the government, academic, and private sectors as we improve our statistics. We also will ensure our staff has the skills to innovate the modern methods of the future. In the last few years, BLS developed an in-house Data Science Training Program designed to bring awareness and improve the skills of BLS staff in key areas of data science. This annual program introduces a new cohort of BLS staff to these concepts, with plans to scale for larger cohorts in the future and include more specialized learning streams.

It is an exciting time to produce economic statistics. Their importance is paramount, and the opportunities have expanded to improve their accuracy, relevance, and timeliness. The CNSTAT’s latest report on the CPI is a valuable guide to help us keep improving and continue to produce gold standard data well into the future.

Tags: BLS products and services, Committee on National Statistics, Consumer Price Index, Consumer spending, CPI, Methodology, Owners' equivalent rent, Rent, Shelter, Statistics awareness

Measuring Changes in Shelter Prices in the Consumer Price Index

May 20, 2022BLS Commissioner

Shelter costs are the largest regular expense for most households. That makes them a topic of considerable interest to users of Consumer Price Index (CPI) data. The U.S. city average for shelter increased 5.1 percent from April 2021 to April 2022. Its two main components, owners’ equivalent rent of residences and rent of primary residence, each increased 4.8 over the year. (Lodging away from home is the other component of shelter, and lodging prices rose 19.7 percent from April 2021 to April 2022.)

Consumer Price Index for All Urban Consumers, all items and shelter, January 2012 to April 2022

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

Because of their large weight in the CPI market basket—nearly a third—the indexes for owners’ equivalent rent and rent can have a large impact on the overall inflation estimate. There is also a lot of misunderstanding about these shelter indexes, and so it is worth taking a few minutes to get a clear understanding of what they measure.

Owners’ equivalent rent is the larger of these two components, at nearly one quarter of the consumer market basket, or weight, in the CPI. It represents the implicit amount an owner of a housing unit would have to pay in rent to live in the unit, assuming it was leased instead of owned. The expenditure weight for owners’ equivalent rent in the CPI is based on a question in the Consumer Expenditure Survey. That question asks homeowners, “If someone were to rent your home today, how much do you think it would rent for monthly, unfurnished and without utilities?” The role of this question can be easily misunderstood by even sophisticated users of BLS data. That has contributed to a common misconception: the mistaken belief that the price observations used for owners’ equivalent rent in the CPI are also from homeowner estimates of their home’s rental value. In fact, the sample of prices used in the owners’ equivalent rent index comes from observations of rent collected in our monthly survey of housing prices, but with utilities and other similar charges removed.

Why don’t we just measure changes in home values in the CPI? It’s because a home isn’t just a consumption item for the owner. It is also an investment, often the largest investment many people will make in their lives. The concept in the CPI—and in the economic statistics programs of most other nations—is to treat owned housing as a capital or investment good, distinct from the shelter service it provides. We treat spending to buy and improve houses and other housing units as investment and not consumption in the CPI. Mortgage interest costs, property taxes, real estate fees, most maintenance, and all improvement costs are part of the cost of the capital good and are also not treated as consumption items. These nonconsumption costs of owned housing are out of scope for the CPI under the cost-of-living framework that guides the index.

Some people have noted that the CPI index for rent (which represents just over 7 percent of the weight of the CPI) is not rising as fast as some other measures, notably those published by firms in the real estate industry. One reason for this is that over 80 percent of rental units in the CPI sample each period have tenants who continue to rent the same unit. Landlords often raise rents when a unit is vacated by a prior tenant and a new tenant moves in. In some cases, the rent paid by tenants with multi-year leases increases periodically—and automatically, by the CPI itself—through an escalation clause in the lease agreement that cites the CPI for this purpose.

Because rents for existing tenants change in line with the terms of leases and rental agreements, and many leases are for 12 months, existing tenants typically do not face price change within the 12-month period of the lease. This is called a “sticky” price. Because of this, the process used to calculate the indexes for rent and owners’ equivalent rent differs from the process used to calculate the rest of the CPI. Most prices are collected either monthly or every 2 months, but rent prices are collected every 6 months. In effect, this means price increases for shelter can sometimes take longer to appear in the CPI than in some other data sources.

We are always working to improve the accuracy of the CPI, and that includes our shelter indexes. We asked for expert opinion from the National Academy of Sciences, Committee on National Statistics, on better ways to measure price change for these important items. The committee recently published their report, “Modernizing the Consumer Price Index for the 21st Century.” The report endorsed the use of owners’ equivalent rent in the CPI and recommended that, “BLS should continue using rental equivalence as the primary approach to estimating the price of housing services for owner-occupied units.”

I will say more about the report from the Committee on National Statistics soon. In the meantime, we will consider all the recommendations of this distinguished group as we plan future improvements to the CPI.

You can read more about shelter in our factsheet for rent and owners’ equivalent rent. We also have more technical details in the Handbook of Methods.

Consumer Price Index for All Urban Consumers, all items and shelter, January 2012 to April 2022
Month	All items	Shelter	Rent of primary residence	Owners’ equivalent rent of residences
Jan 2012	100.000	100.000	100.000	100.000
Feb 2012	100.440	100.205	100.182	100.102
Mar 2012	101.203	100.472	100.332	100.295
Apr 2012	101.509	100.638	100.469	100.465
May 2012	101.390	100.799	100.589	100.560
Jun 2012	101.241	100.999	100.657	100.660
Jul 2012	101.076	101.179	100.929	100.837
Aug 2012	101.639	101.350	101.150	101.097
Sep 2012	102.092	101.511	101.438	101.322
Oct 2012	102.052	101.737	101.937	101.538
Nov 2012	101.569	101.804	102.193	101.735
Dec 2012	101.295	101.922	102.477	101.880
Jan 2013	101.595	102.213	102.711	102.077
Feb 2013	102.427	102.481	102.926	102.249
Mar 2013	102.695	102.720	103.146	102.384
Apr 2013	102.588	102.848	103.209	102.542
May 2013	102.771	103.097	103.432	102.701
Jun 2013	103.017	103.340	103.566	102.888
Jul 2013	103.058	103.554	103.790	103.045
Aug 2013	103.182	103.779	104.187	103.355
Sep 2013	103.302	103.905	104.432	103.570
Oct 2013	103.036	104.053	104.752	103.839
Nov 2013	102.825	104.285	105.038	104.149
Dec 2013	102.816	104.509	105.422	104.415
Jan 2014	103.199	104.852	105.666	104.646
Feb 2014	103.581	105.113	105.828	104.815
Mar 2014	104.248	105.512	106.120	105.056
Apr 2014	104.591	105.696	106.358	105.227
May 2014	104.957	106.036	106.595	105.411
Jun 2014	105.152	106.252	106.832	105.604
Jul 2014	105.111	106.567	107.192	105.844
Aug 2014	104.935	106.787	107.502	106.124
Sep 2014	105.014	106.979	107.871	106.380
Oct 2014	104.751	107.224	108.254	106.667
Nov 2014	104.185	107.399	108.695	106.969
Dec 2014	103.594	107.543	108.987	107.140
Jan 2015	103.107	107.932	109.258	107.403
Feb 2015	103.555	108.247	109.575	107.632
Mar 2015	104.171	108.628	109.862	107.885
Apr 2015	104.383	108.871	110.044	108.142
May 2015	104.915	109.101	110.295	108.353
Jun 2015	105.282	109.454	110.600	108.720
Jul 2015	105.289	109.886	111.011	109.018
Aug 2015	105.140	110.096	111.390	109.325
Sep 2015	104.977	110.379	111.871	109.664
Oct 2015	104.929	110.648	112.306	109.963
Nov 2015	104.708	110.818	112.653	110.260
Dec 2015	104.350	111.000	112.995	110.509
Jan 2016	104.523	111.434	113.305	110.795
Feb 2016	104.609	111.802	113.605	111.031
Mar 2016	105.059	112.101	113.882	111.250
Apr 2016	105.557	112.353	114.148	111.546
May 2016	105.984	112.781	114.482	111.890
Jun 2016	106.332	113.231	114.818	112.249
Jul 2016	106.160	113.510	115.190	112.574
Aug 2016	106.258	113.834	115.599	112.942
Sep 2016	106.513	114.165	116.005	113.367
Oct 2016	106.646	114.543	116.563	113.751
Nov 2016	106.480	114.757	117.024	114.167
Dec 2016	106.515	115.016	117.469	114.458
Jan 2017	107.136	115.389	117.753	114.717
Feb 2017	107.473	115.736	118.042	114.947
Mar 2017	107.560	115.972	118.297	115.127
Apr 2017	107.879	116.233	118.533	115.321
May 2017	107.971	116.546	118.883	115.529
Jun 2017	108.069	116.916	119.246	115.874
Jul 2017	107.995	117.102	119.579	116.186
Aug 2017	108.318	117.589	120.086	116.629
Sep 2017	108.892	117.859	120.392	116.974
Oct 2017	108.823	118.253	120.871	117.386
Nov 2017	108.825	118.386	121.324	117.733
Dec 2017	108.761	118.701	121.803	118.092
Jan 2018	109.354	119.071	122.146	118.391
Feb 2018	109.850	119.356	122.336	118.563
Mar 2018	110.098	119.826	122.571	118.878
Apr 2018	110.536	120.167	122.913	119.194
May 2018	110.996	120.638	123.195	119.468
Jun 2018	111.172	120.877	123.516	119.779
Jul 2018	111.180	121.219	123.917	120.129
Aug 2018	111.242	121.574	124.421	120.514
Sep 2018	111.371	121.734	124.763	120.799
Oct 2018	111.568	122.001	125.188	121.205
Nov 2018	111.194	122.224	125.708	121.633
Dec 2018	110.839	122.500	126.037	121.899
Jan 2019	111.050	122.911	126.340	122.185
Feb 2019	111.520	123.376	126.633	122.505
Mar 2019	112.149	123.869	127.084	122.830
Apr 2019	112.743	124.313	127.536	123.190
May 2019	112.983	124.676	127.790	123.463
Jun 2019	113.005	125.113	128.300	123.861
Jul 2019	113.194	125.442	128.672	124.179
Aug 2019	113.188	125.656	129.073	124.542
Sep 2019	113.277	126.005	129.537	124.906
Oct 2019	113.536	126.081	129.865	125.222
Nov 2019	113.475	126.280	130.307	125.597
Dec 2019	113.372	126.476	130.683	125.894
Jan 2020	113.812	126.982	131.085	126.273
Feb 2020	114.123	127.454	131.392	126.523
Mar 2020	113.875	127.596	131.743	126.785
Apr 2020	113.114	127.559	131.982	126.973
May 2020	113.116	127.851	132.244	127.237
Jun 2020	113.735	128.067	132.431	127.379
Jul 2020	114.310	128.368	132.686	127.653
Aug 2020	114.671	128.532	132.878	127.889
Sep 2020	114.830	128.579	133.058	128.015
Oct 2020	114.878	128.640	133.332	128.347
Nov 2020	114.808	128.704	133.496	128.454
Dec 2020	114.916	128.809	133.658	128.625
Jan 2021	115.405	129.037	133.775	128.810
Feb 2021	116.036	129.321	133.963	129.090
Mar 2021	116.858	129.760	134.148	129.337
Apr 2021	117.819	130.245	134.361	129.564
May 2021	118.763	130.677	134.652	129.920
Jun 2021	119.867	131.372	134.969	130.363
Jul 2021	120.443	131.997	135.215	130.757
Aug 2021	120.692	132.182	135.697	131.151
Sep 2021	121.020	132.641	136.296	131.721
Oct 2021	122.025	133.121	136.932	132.368
Nov 2021	122.625	133.642	137.566	132.989
Dec 2021	123.002	134.131	138.111	133.505
Jan 2022	124.037	134.667	138.812	134.075
Feb 2022	125.170	135.454	139.545	134.649
Mar 2022	126.841	136.244	140.110	135.204
Apr 2022	127.549	136.941	140.835	135.764

Topics: Consumer Spending | Inflation and Prices | U.S. Statistical System

Tags: Consumer Price Index, Consumer spending, CPI, Methodology, Owners' equivalent rent, Rent, Shelter, Statistics awareness

Measuring Consumer Prices for New Vehicles More Accurately

May 9, 2022BLS Commissioner

In May 2020, we announced a new research index designed to improve the way we measure consumer price changes for new vehicles. Part of the Consumer Price Index (CPI) program, the research index uses transaction data on vehicle purchases. BLS obtains the data from J.D. Power. After carefully studying the data, we now plan to implement the new data source into the official CPI, effective with the April 2022 release, which we will publish on May 11, 2022. We also will update Measuring Price Change in the CPI: New vehicles factsheet at that time.

The research index departs from the traditional survey methods and data sources we have used in the CPI. The traditional methods sample vehicle dealers and the makes, models, and features of the vehicles they sell. That’s why we took a very deliberate approach before we incorporated the new data into the official CPI. We discuss details of our methods and research in “A New Vehicles Transaction Price Index: Offsetting the Effects of Price Discrimination and Product Cycle Bias with a Year-Over-Year Index.”

Leading up to March 2020, the movements of the research index for new vehicles were similar to the official index for new vehicles. Since March 2020, the indexes began to diverge, with the research index showing faster price increases that the official index did not reflect.

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

Since the COVID-19 pandemic began in March 2020, the economy experienced significant disruption. This is especially true of the automobile industry, which saw fluctuations in the supply chain, employment, and consumer demand. Combining these shifts in the economy with the changes in methods represented by the research index made it challenging to assess our results.

While the research index and the official new vehicles index maintained similar trends, the recent divergence between them provided an opportunity to assess the robustness of the two approaches.

We weighed several factors in deciding whether to incorporate the J.D Power data on new vehicle prices into the official CPI. The new data include records of the prices paid during hundreds of thousands of transactions each month. That dwarfs the roughly 500 prices collected using traditional CPI methods. The larger dataset allows us to estimate price changes more precisely. As a result, the research index has a much lower standard error than the official new vehicles index.

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

Because the research data reflect actual transactions, the shift in consumer preference from cars to other types of vehicles, such as trucks, is built into the data. This differs from the official index, which has maintained a roughly equal weight between cars and trucks.

In addition to the quantitative evaluations, BLS continued to ask for feedback on the research index through our website and by consulting with other statistical agencies. We received positive feedback and no major concerns, and we remain confident the research index is statistically sound. For these reasons, we have decided to incorporate the new data source and methods for new vehicles in the official CPI.

In some ways, the past 2 years have been an unprecedented time for statistical measurement, but in other ways business at BLS has continued as usual. When the COVID-19 pandemic began in March 2020, BLS ceased in-person data collection for the CPI and other programs. We collected more data online, by telephone, and through video. While the pandemic affected data collection, we continue to publish data on schedule. We also continue to assess our methods and seek ways to improve the quality of our data. Improving our methods for collecting price data for new vehicles is another step forward in innovating and improving the CPI.

Comparison of research index and official index for new vehicle prices
Month	Research index	Official index
Jan 2018	100.000	100.000
Feb 2018	100.026	99.871
Mar 2018	99.481	99.817
Apr 2018	99.842	99.370
May 2018	99.583	99.560
Jun 2018	99.499	99.705
Jul 2018	99.841	99.681
Aug 2018	99.942	99.424
Sep 2018	99.917	99.129
Oct 2018	99.886	99.043
Nov 2018	100.072	99.204
Dec 2018	99.471	99.409
Jan 2019	99.969	100.043
Feb 2019	100.295	100.157
Mar 2019	100.182	100.539
Apr 2019	100.487	100.574
May 2019	100.659	100.452
Jun 2019	100.362	100.287
Jul 2019	100.484	100.027
Aug 2019	100.089	99.633
Sep 2019	100.203	99.224
Oct 2019	100.443	99.136
Nov 2019	99.965	99.138
Dec 2019	99.912	99.472
Jan 2020	100.486	100.175
Feb 2020	100.843	100.549
Mar 2020	101.301	100.087
Apr 2020	102.431	100.008
May 2020	102.842	100.154
Jun 2020	103.653	100.076
Jul 2020	104.047	100.549
Aug 2020	104.142	100.284
Sep 2020	103.895	100.249
Oct 2020	103.841	100.653
Nov 2020	103.977	100.726
Dec 2020	103.781	101.425
Jan 2021	104.818	101.620
Feb 2021	105.652	101.714
Mar 2021	106.308	101.582
Apr 2021	107.156	101.971
May 2021	111.189	103.502
Jun 2021	113.656	105.341
Jul 2021	114.795	106.944
Aug 2021	115.205	107.930
Sep 2021	115.942	109.013
Oct 2021	118.107	110.566
Nov 2021	118.980	111.915
Dec 2021	120.336	113.373
Jan 2022	121.230	114.005
Feb 2022	122.481	114.308

Comparison of 12-month standard errors for the research index and official index for new vehicle prices
Month	Research index	Official index
Jan 2019	0.11	0.61
Feb 2019	0.10	0.58
Mar 2019	0.11	0.42
Apr 2019	0.11	0.43
May 2019	0.13	0.43
Jun 2019	0.12	0.46
Jul 2019	0.14	0.43
Aug 2019	0.13	0.42
Sep 2019	0.14	0.42
Oct 2019	0.12	0.45
Nov 2019	0.16	0.46
Dec 2019	0.16	0.40
Jan 2020	0.15	0.41
Feb 2020	0.15	0.38
Mar 2020	0.14	0.33
Apr 2020	0.15	0.36
May 2020	0.13	0.40
Jun 2020	0.13	0.36
Jul 2020	0.15	0.48
Aug 2020	0.14	0.47
Sep 2020	0.13	0.60
Oct 2020	0.13	0.64
Nov 2020	0.12	0.65
Dec 2020	0.12	0.62
Jan 2021	0.13	0.62
Feb 2021	0.13	0.66
Mar 2021	0.12	0.67
Apr 2021	0.11	0.60
May 2021	0.12	0.59
Jun 2021	0.13	0.63
Jul 2021	0.13	0.61
Aug 2021	0.13	0.69
Sep 2021	0.13	0.74
Oct 2021	0.16	0.72
Nov 2021	0.15	0.55
Dec 2021	0.15	0.69
Jan 2022	0.14	0.67
Feb 2022	0.14	0.68

Topics: Consumer Spending | Inflation and Prices | Survey Respondents | U.S. Statistical System

Tags: Cars, Consumer Price Index, COVID-19, CPI, J.D. Power, Methodology, Pandemic, Statistics awareness, Trucks, Vehicles