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Tag Archives: J.D. Power

Measuring Consumer Prices for New Vehicles More Accurately

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
MonthResearch indexOfficial index

Jan 2018

100.000100.000

Feb 2018

100.02699.871

Mar 2018

99.48199.817

Apr 2018

99.84299.370

May 2018

99.58399.560

Jun 2018

99.49999.705

Jul 2018

99.84199.681

Aug 2018

99.94299.424

Sep 2018

99.91799.129

Oct 2018

99.88699.043

Nov 2018

100.07299.204

Dec 2018

99.47199.409

Jan 2019

99.969100.043

Feb 2019

100.295100.157

Mar 2019

100.182100.539

Apr 2019

100.487100.574

May 2019

100.659100.452

Jun 2019

100.362100.287

Jul 2019

100.484100.027

Aug 2019

100.08999.633

Sep 2019

100.20399.224

Oct 2019

100.44399.136

Nov 2019

99.96599.138

Dec 2019

99.91299.472

Jan 2020

100.486100.175

Feb 2020

100.843100.549

Mar 2020

101.301100.087

Apr 2020

102.431100.008

May 2020

102.842100.154

Jun 2020

103.653100.076

Jul 2020

104.047100.549

Aug 2020

104.142100.284

Sep 2020

103.895100.249

Oct 2020

103.841100.653

Nov 2020

103.977100.726

Dec 2020

103.781101.425

Jan 2021

104.818101.620

Feb 2021

105.652101.714

Mar 2021

106.308101.582

Apr 2021

107.156101.971

May 2021

111.189103.502

Jun 2021

113.656105.341

Jul 2021

114.795106.944

Aug 2021

115.205107.930

Sep 2021

115.942109.013

Oct 2021

118.107110.566

Nov 2021

118.980111.915

Dec 2021

120.336113.373

Jan 2022

121.230114.005

Feb 2022

122.481114.308
Comparison of 12-month standard errors for the research index and official index for new vehicle prices
MonthResearch indexOfficial index

Jan 2019

0.110.61

Feb 2019

0.100.58

Mar 2019

0.110.42

Apr 2019

0.110.43

May 2019

0.130.43

Jun 2019

0.120.46

Jul 2019

0.140.43

Aug 2019

0.130.42

Sep 2019

0.140.42

Oct 2019

0.120.45

Nov 2019

0.160.46

Dec 2019

0.160.40

Jan 2020

0.150.41

Feb 2020

0.150.38

Mar 2020

0.140.33

Apr 2020

0.150.36

May 2020

0.130.40

Jun 2020

0.130.36

Jul 2020

0.150.48

Aug 2020

0.140.47

Sep 2020

0.130.60

Oct 2020

0.130.64

Nov 2020

0.120.65

Dec 2020

0.120.62

Jan 2021

0.130.62

Feb 2021

0.130.66

Mar 2021

0.120.67

Apr 2021

0.110.60

May 2021

0.120.59

Jun 2021

0.130.63

Jul 2021

0.130.61

Aug 2021

0.130.69

Sep 2021

0.130.74

Oct 2021

0.160.72

Nov 2021

0.150.55

Dec 2021

0.150.69

Jan 2022

0.140.67

Feb 2022

0.140.68

Improving How We Measure Prices for New Vehicles

We have a guest blogger for this edition of Commissioner’s Corner. Brendan Williams is an economist in the Office of Prices and Living Conditions at the U.S. Bureau of Labor Statistics.

For nearly as long as cars and trucks have been sold, the BLS Consumer Price Index (CPI) has tracked changes in the prices consumers pay for new vehicles. Our traditional method of determining the change in vehicle prices is to survey dealers and collect estimated prices for models with a specific set of features. For example, a Brand X 8-cylinder two-door sports coupe with a sunroof. We recently debuted a research index for new vehicles based on a large dataset of prices actually paid, which we call “transaction” prices. This is just one of many efforts currently underway in the CPI (and throughout BLS) to identify and introduce new sources of data into our statistical measures. As you are about to learn, a lot goes into introducing these new measures.

We purchased the new data for new vehicles from J.D. Power. The new dataset includes records of the prices paid during hundreds of thousands of transactions every month—far more than the roughly 2,000 vehicle prices in the CPI sample. The larger dataset provides more precise measures of price change.

But it’s not as simple as plugging the new data into the monthly CPI. We found that applying current CPI methods to the transaction data produced a biased index. So we had to make some changes. We combined an estimate of the long-run trend in new vehicle prices with a measure of high-frequency fluctuations in the market. The long-run trend is based on the year-over-year price change between a vehicle in the current month and the same vehicle in the prior model year 12 months ago; we get these values from the J.D. Power data. The high-frequency fluctuation is extracted from a monthly index based on current methods used in the CPI.

The research index includes all types of new vehicles—cars, SUVs, and trucks. And since the data reflect actual transactions, the shift in consumer preference from cars to other types of vehicles is reflected in the data. This differs from the currently published CPI, which has maintained a roughly equal weight between cars and trucks.

The new vehicles research index performs very similarly to the published index. From December 2007 to March 2020, the research index (untaxed) increased 8.2 percent, while the official new vehicles index (which is taxed) increased 7.7 percent. Looking under the hood, the research truck index is also similar to its published index. The difference in the car indexes is larger, with the official index showing a 5.2-percent increase, while the research index shows only a 1.5-percent increase.

Chart showing trends in research and official price indexes for new vehicles, 2007 to 2020

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

While the new vehicle indexes look similar, the research index has a much lower standard error, which means there is less variation in the data. The research index had a 12-month standard error of 0.11, compared to the 0.43 standard error in the new vehicles index.

This research index is just one of many ways BLS is innovating the CPI and all our measures. For more information on BLS efforts to use new sources of data in the CPI, see “Big Data in the U.S. Consumer Price Index: Experiences & Plans.” Details of the methods and other aspects of research are in, “A New Vehicles Transaction Price Index: Offsetting the Effects of Price Discrimination and Product Cycle Bias with a Year-Over-Year Index.”

We are asking for your feedback about whether to use this research index or the current index. We specifically want to know whether you think this proposal improves our methods and data sources. Please tell us what you think about the research new vehicles data by emailing cpixnv@bls.gov. You can send other CPI-related questions to cpi_info@bls.gov.

Research and official price indexes for new vehicles
MonthResearch index, trucks untaxedOfficial index, trucks untaxedResearch index, all vehicles untaxedOfficial index, all vehicles untaxedResearch index, cars untaxedOfficial index, cars untaxed

Dec 2007

100.0100.0100.0100.0100.0100.0

Jan 2008

99.9100.299.6100.199.2100.0

Feb 2008

100.199.999.899.799.599.7

Mar 2008

100.899.3100.299.399.699.5

Apr 2008

99.998.799.698.999.399.2

May 2008

99.698.199.698.599.699.1

Jun 2008

100.197.7100.898.4101.599.2

Jul 2008

98.797.1100.098.3101.499.6

Aug 2008

96.395.898.397.6100.799.3

Sep 2008

95.794.797.996.9100.599.0

Oct 2008

95.894.797.896.8100.398.9

Nov 2008

95.294.797.296.999.999.0

Dec 2008

94.094.795.996.898.598.9

Jan 2009

94.095.595.797.597.899.5

Feb 2009

95.296.796.498.298.199.7

Mar 2009

95.297.496.398.597.899.7

Apr 2009

96.697.897.498.798.699.8

May 2009

96.898.197.698.998.699.9

Jun 2009

97.098.697.499.397.9100.1

Jul 2009

96.698.996.699.696.9100.3

Aug 2009

96.997.797.098.197.498.7

Sep 2009

99.098.099.498.5100.199.0

Oct 2009

98.899.899.3100.4100.0101.1

Nov 2009

99.2100.799.5101.6100.0102.5

Dec 2009

99.3100.999.2101.699.3102.5

Jan 2010

99.3101.199.2101.599.3102.1

Feb 2010

99.8101.499.5101.699.4102.1

Mar 2010

100.4101.4100.2101.4100.2101.7

Apr 2010

100.9101.2100.7101.198.3101.3

May 2010

101.0100.8100.8100.8100.7101.1

Jun 2010

101.3100.6100.9100.6100.7101.0

Jul 2010

101.5100.5101.1100.598.2100.8

Aug 2010

101.7100.5101.2100.3100.6100.6

Sep 2010

101.7100.7100.9100.5100.0100.8

Oct 2010

102.3101.0101.2100.999.7101.1

Nov 2010

102.5101.5101.2101.199.4101.2

Dec 2010

102.3101.9100.8101.498.9101.3

Jan 2011

102.4102.4100.8101.798.7101.3

Feb 2011

102.7103.3101.1102.699.2102.4

Mar 2011

103.7103.8102.0103.199.9102.9

Apr 2011

104.3104.0103.0103.5101.4103.5

May 2011

104.7104.3103.8104.3102.7104.7

Jun 2011

104.6104.3103.8104.7103.1105.5

Jul 2011

104.4104.0103.7104.5103.1105.4

Aug 2011

104.3103.7103.6104.1103.2105.1

Sep 2011

104.1103.6103.5104.1103.4105.2

Oct 2011

104.2103.8103.5104.3103.1105.2

Nov 2011

104.3104.1103.4104.4102.6105.2

Dec 2011

104.4104.3103.5104.6102.5105.3

Jan 2012

105.0105.0103.9105.0102.7105.4

Feb 2012

105.1105.9104.0105.6102.8105.8

Mar 2012

105.4106.0104.5105.6103.5105.7

Apr 2012

105.7106.1104.8105.7103.8105.9

May 2012

105.2105.8104.4105.7103.5105.9

Jun 2012

105.4105.8104.5105.6103.5105.9

Jul 2012

105.1105.5104.1105.3103.1105.5

Aug 2012

105.0105.5104.1105.2103.1105.4

Sep 2012

105.2105.6104.3105.2103.3105.3

Oct 2012

105.3105.8104.5105.4103.7105.4

Nov 2012

105.6106.2104.6105.9103.4106.1

Dec 2012

105.7106.5104.5106.2103.0106.4

Jan 2013

105.7107.1104.6106.7103.1106.8

Feb 2013

106.3107.2105.1106.8103.5106.8

Mar 2013

106.4107.4105.2106.8103.6106.8

Apr 2013

106.7107.7105.5107.0103.8106.8

May 2013

106.8107.6105.5106.8103.8106.6

Jun 2013

106.4107.8105.1106.9103.3106.4

Jul 2013

106.4107.6105.0106.6103.2106.1

Aug 2013

106.4107.3105.0106.3103.2105.8

Sep 2013

106.3107.6104.9106.4102.9105.8

Oct 2013

106.5107.6105.1106.5103.2105.7

Nov 2013

106.7107.8105.1106.6103.0105.8

Dec 2013

106.4108.0104.6106.7102.0105.9

Jan 2014

106.5108.1104.6106.7101.8106.0

Feb 2014

107.1108.6105.2107.1102.3106.3

Mar 2014

107.3108.6105.3107.1102.4106.2

Apr 2014

107.8109.0105.7107.4102.6106.4

May 2014

108.1108.9105.8107.3102.4106.4

Jun 2014

107.9108.4105.5106.9101.8106.0

Jul 2014

108.2108.6105.7106.9101.9105.9

Aug 2014

108.6108.7105.9106.7101.7105.4

Sep 2014

108.4108.7105.6106.7101.3105.4

Oct 2014

108.7109.0105.9107.1101.5105.7

Nov 2014

108.5109.2105.5107.2100.8105.9

Dec 2014

108.3109.4105.1107.2100.0105.8

Jan 2015

109.0109.3105.8107.2100.9105.8

Feb 2015

109.2109.9106.0107.8101.0106.4

Mar 2015

109.4110.2106.2108.0101.1106.5

Apr 2015

109.8110.5106.6108.2101.6106.5

May 2015

109.7110.6106.4108.2101.3106.5

Jun 2015

109.9110.5106.5108.2101.3106.5

Jul 2015

109.7110.2106.2107.7100.9105.9

Aug 2015

110.0109.8106.3107.3100.5105.5

Sep 2015

110.5109.8106.7107.2100.6105.3

Oct 2015

110.5109.8106.6107.2100.4105.2

Nov 2015

110.6110.2106.5107.499.9105.2

Dec 2015

111.0110.1106.9107.4100.4105.3

Jan 2016

111.5110.6107.3107.9100.7105.8

Feb 2016

111.8111.2107.7108.5101.2106.4

Mar 2016

112.0111.4107.8108.5101.1106.2

Apr 2016

112.2111.2108.0108.2101.3105.8

May 2016

111.9111.0107.6108.0100.7105.6

Jun 2016

111.9110.8107.4107.7100.1105.2

Jul 2016

111.1110.7106.8107.7100.0105.0

Aug 2016

111.8110.3107.3107.499.8104.7

Sep 2016

111.5110.3106.9107.299.5104.6

Oct 2016

111.3110.6106.7107.599.1104.9

Nov 2016

110.9110.6106.4107.699.0105.0

Dec 2016

111.1110.9106.5107.898.8105.1

Jan 2017

112.0111.9107.4108.999.8106.3

Feb 2017

111.8111.9107.3109.0100.0106.5

Mar 2017

112.1111.7107.3108.799.5106.0

Apr 2017

112.1111.7107.3108.699.3105.9

May 2017

111.9111.6107.1108.399.2105.5

Jun 2017

112.0111.1107.1107.899.1104.9

Jul 2017

111.9110.4106.9107.098.4103.9

Aug 2017

111.8110.2106.6106.697.9103.4

Sep 2017

111.4109.8106.3106.197.6102.8

Oct 2017

111.5109.7106.5106.097.9102.7

Nov 2017

112.0109.9106.8106.497.4103.2

Dec 2017

111.4110.7106.3107.297.9104.0

Jan 2018

111.9111.0106.9107.698.7104.4

Feb 2018

111.8110.8106.9107.498.9104.2

Mar 2018

111.2110.8106.3107.498.3104.2

Apr 2018

111.4110.3106.7106.999.3103.7

May 2018

111.1110.5106.4107.198.8104.1

Jun 2018

110.9110.6106.3107.299.1104.2

Jul 2018

111.3110.5106.7107.299.4104.3

Aug 2018

111.4110.2106.8106.999.5104.0

Sep 2018

111.3109.8106.8106.699.8103.9

Oct 2018

111.2109.6106.8106.5100.0103.9

Nov 2018

111.5109.8107.0106.799.9104.1

Dec 2018

110.7110.0106.3106.999.6104.2

Jan 2019

111.3110.8106.8107.6100.0104.8

Feb 2019

111.7111.0107.2107.7100.2104.9

Mar 2019

111.6111.5107.1108.199.9105.2

Apr 2019

112.0111.5107.4108.2100.1105.2

May 2019

112.2111.3107.6108.0100.3105.2

Jun 2019

111.7111.0107.2107.9100.6105.2

Jul 2019

111.9110.7107.4107.6100.6104.9

Aug 2019

111.5110.3106.9107.2100.2104.6

Sep 2019

111.6109.9107.1106.7100.1104.1

Oct 2019

111.9109.8107.3106.6100.3104.1

Nov 2019

111.3109.9106.8106.6100.0104.1

Dec 2019

111.2110.4106.8107.099.8104.3

Jan 2020

111.8111.0107.4107.7100.4105.1

Feb 2020

112.2111.4107.7108.2101.0105.7

Mar 2020

112.7110.9108.2107.7101.5105.2