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.

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.