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The automotive industry is an important part of the U.S. economy. During the recent economic expansion associated with the recovery from the COVID-19 pandemic, price increases for new cars and trucks contributed moderately to overall consumer inflation. In the previous expansion, which followed the global financial crisis of 2008 and lasted from 2009 to 2019, new-vehicle prices were largely subdued because of profit-margin compression at vehicle dealerships. However, the competitive dynamics and trends that developed during this earlier expansion set the stage for dealerships to subsequently increase profits from the sale of new vehicles, contributing largely to new-vehicle consumer inflation in the COVID-19 economic expansion.1 This latest development, analyzed in this article, reflects dealerships’ major role as an inventory intermediary in the vehicle supply chain.2
The U.S. Bureau of Labor Statistics (BLS) publishes several price indexes that track price changes for different goods and services in the automotive supply chain. The Consumer Price Index (CPI) for new cars and trucks (hereafter referred to as “CPI for new vehicles”) tracks prices paid by consumers for new vehicles. The Producer Price Index (PPI) for motor vehicles (hereafter referred to as “PPI for new vehicles”) tracks prices paid by wholesalers, dealerships, intermediaries, and other businesses to manufacturers of new motor vehicles. The Import Price Index (MPI) for automobile and light duty motor vehicle manufacturing (hereafter referred to as “MPI for new vehicles”) tracks prices for imported cars and trucks. Finally, the PPI for vehicle sales (hereafter referred to as “PPI for dealership markups”) tracks margins or markups,3 which are the retail selling prices received by dealerships for cars and trucks (regardless of whether the vehicles were manufactured in the United States or imported) less their acquisition prices.
A central theme of this analysis is that changes in retail markups drive the statistical and conceptual differences between changes in producer vehicle prices and changes in consumer vehicle prices.4 Table 1 shows the trends in the CPI for new vehicles, the PPI for new vehicles, and the PPI for dealership markups for the last three business cycles: December 2000 to September 2007 (peak to peak), September 2007 to December 2019 (peak to peak), and December 2019 to December 2022 (peak to December 2022). When the CPI for new vehicles and the PPI for new vehicles move similarly in magnitude and direction, the PPI for dealership markups is relatively stable; when they diverge, the PPI for dealership markups changes substantially.
Business cycle | Percent change for CPI for new vehicles | Percent change for PPI for new vehicles | Percent change for PPI for dealership markups | Difference between percent changes for CPI and PPI for new vehicles | Absolute difference between percent changes for CPI and PPI for new vehicles | Absolue value of percent change for PPI for dealership markups |
---|---|---|---|---|---|---|
December 2000 to September 2007 (peak to peak) | -6.0 | -8.8 | 2.6 | 2.8 | 2.8 | 2.6 |
September 2007 to December 2019 (peak to peak) | 8.4 | 22.4 | -32.9 | -14.0 | 14.0 | 32.9 |
December 2019 to December 2022 (peak to December 2022) | 20.7 | 7.9 | 144.7 | 12.8 | 12.8 | 144.7 |
Note: CPI = Consumer Price Index; PPI = Producer Price Index. Source: Author's calculations based on data from the U.S. Bureau of Labor Statistics. |
Covering the period from 2007 through 2022, charts 1 and 2 display scatterplots showing the absolute value of the year-ending annual percent change for the PPI for dealership markups (horizontal axis) and the absolute value of the difference between the year-ending annual percent changes for the CPI for new vehicles and the PPI for new vehicles (vertical axis). (Chart 1 includes the pandemic years, whereas chart 2 excludes them.) The PPI for dealership markups changes the most when the CPI for new vehicles and the PPI for new vehicles move in opposite directions, but it also fluctuates when the movements of those indexes differ substantially in magnitude. The comparatively larger magnitude of change in the PPI for dealership markups is due to the fact that, by definition, a markup is a marginal differential output of inputs that exist on much larger scales than the markup. These trends, which show how dealerships function as an intermediary materially affecting price transmission, are also corroborated by financial reporting data from the U.S. Securities and Exchange Commission (SEC).5
The competitive dynamics that evolved in the decades preceding the COVID-19 pandemic uniquely positioned dealerships to expand profits from new-vehicle sales during the recent economic expansion. During the 2007–19 business cycle, dealerships experienced substantial profit-margin compression on new-vehicle sales because they faced higher prices from manufacturers and did not fully push those higher prices onto consumers. Instead, dealerships weathered the margins squeeze by expanding their value proposition by selling more finance and insurance products that subsidized the sale of low-to-no-margin vehicles. Dealerships were caught in the margins squeeze for two reasons. First, the interdependencies and market-power dynamics between dealerships and manufacturers resulted in manufacturers pushing large amounts of inventory onto dealerships, with the latter being unable to negotiate on price. Second, after the Great Recession of 2007–09, consumers were very sensitive to high prices.6
The pandemic, along with the economic stimulus provided in response to it, created the perfect combination of exogenous shocks to invert the competitive dynamics of the preceding expansion. First, manufacturers encountered significant supply shortages and supply-chain bottlenecks, both due to the pandemic-related shutdowns adopted across the globe.7 Although this shock acutely affected manufacturers’ production, dealerships, which tend to have between 60 and 90 days of inventory on hand, initially had inventory volumes that did not require the purchase of additional vehicles from manufacturers.8 Moreover, during the initial phases of the pandemic, economic actors across the supply chain believed the recession would follow a typical path of sustained decreases in demand, so they cut output and scrambled to push inventories downstream to dealerships.9 Second, U.S. fiscal and monetary policy provided unprecedented stimulus in response to the pandemic, and this stimulus resulted in a large increase in personal savings.10 Third, the perceived economic cost of consuming services increased dramatically because of the consumer concern that services came with the increased cost of potentially contracting COVID-19. Consequently, consumers’ total budgets, boosted by stimulus, pivoted substantially toward physical goods, with the net result being a sharp increase in the consumption of those goods.11
The consumer spending changes and economic stimuluses associated with the pandemic merit special consideration because of their unprecedented scale and apparent impact on new-vehicle demand. The confluence of the three aforementioned factors allowed dealerships to substantially increase markups during the 2020–22 economic expansion, boosting their profits and sizably contributing to new-vehicle consumer inflation.
Graphical and statistical analyses of BLS price-index data for vehicles and dealership services indicate that, because of profit-margin increases at dealerships over the last 3 years, consumer prices for new vehicles outpaced manufacturer and import prices for new vehicles. Chart 3 shows that, from December 2019 to December 2022, the CPI for new vehicles grew by 20.7 percent, the PPI for new vehicles grew by 7.9 percent, the MPI for new vehicles increased by 6.4 percent, and the PPI for dealership markups increased by 144.7 percent. It should be noted that, during 2019, consumer, producer, and import prices for new vehicles remained largely unchanged, so the PPI for dealership markups was also relatively stable over the year. During 2020, consumer prices only slightly outpaced producer and import prices, so the PPI for dealership markups increased by only 31.9 percent in that year. However, the difference in trends for consumer, producer, and import prices accelerated sharply in 2021, resulting in the margins index increasing by 119.0 percent in 2021 alone. That year saw the largest ever absolute difference between the year-ending annual percent changes for the CPI for new vehicles and the PPI for new vehicles, as well as the largest ever year-ending annual increase (119.0 percent) for the PPI for dealership markups.
Besides showing the official PPI for dealership markups, chart 3 also presents an estimated markup index derived from a linear residual of the short-term price relatives (STRs) of the PPI for new vehicles and the CPI for new vehicles (long-term price relatives (LTRs) are constructed from STRs defined in equation set 1 in the appendix).12 Similarly to the PPI for dealership markups, the estimated markup index grew sharply from December 2019 to December 2022, rising by 255.1 percent. And similarly to the official price measures, the estimated markup index did not begin rapidly increasing until 2021. Under the assumption of an average markup of 5.0 percent in January 2019, the PPI for dealership markups would suggest that the markup would have peaked at 14.7 percent in June 2022, and under the same assumption, the estimated markup index would suggest that the markup would have peaked at 17.7 percent in September 2022. By December 2022, these estimated markups would have fallen to 11.9 and 16.6 percent, respectively. Both of these estimates are largely corroborated by SEC financial data, which show that average new-vehicle markups increased by 146.0 percent from the first quarter of 2019 to the third quarter of 2022, reaching 13.1 percent before falling to 10.9 percent in the fourth quarter of 2022.13
Combining the methodologies presented in two other Monthly Labor Review articles,14 one can use the PPI for new vehicles, the PPI for dealership markups, and the MPI for new vehicles to recreate the CPI for new vehicles. This can be accomplished through a weighted input price index (input price index including markups) that includes the services provided at a dealership, with margin percentages serving as weights.15 Conceptually, the equation for calculating this index (see equation set 2 in appendix) treats the PPI for new vehicles and the MPI for new vehicles as vehicle prices and the PPI for dealership markups as a markup, using actual (known) margin percentages as initial weights and estimated margin percentages as weights beyond the initial period.16
Chart 4 and table 2 show the correlations between the input price index including markups and the official CPI for new vehicles. The statistical and graphical correlations between the two series are strong, further demonstrating that profit-margin changes at dealerships explain the difference between the CPI for new vehicles and the PPI for new vehicles. The test statistics and graphical results exceed thresholds established in BLS-domain-hosted literature characterizing methods to recreate official BLS price measures.17 From December 2019 to December 2020, the CPI for new vehicles increased by 2.0 percent and the estimated input price index including markups increased by 2.5 percent, whereas the PPI for new vehicles increased by only 0.7 percent. Additionally, from December 2020 to December 2022, a period in which dealership markups increased dramatically, the CPI for new vehicles increased by 18.4 percent and the estimated input price index including markups increased by 17.3 percent, whereas the PPI for new vehicles increased by only 7.2 percent. The statistically univariate regression model between the STRs of the CPI for new vehicles and the STRs of the input price index including markups is the only model showing a statistically significant correlation at the 1-percent level of significance (p-value of 0.00) and a meaningfully high correlation coefficient of 0.57. All other models—those using only the PPI for new vehicles, only the MPI for new vehicles, only the PPI for dealership markups, or only the input price index without markups—have p-values greater than 0.01 and low correlation coefficients.
Independent variable | Correlation coefficient | p-value |
---|---|---|
PPI for new vehicles (STR) | 0.30 | 0.04 |
MPI for new vehicles (STR) | 0.17 | 0.24 |
PPI for dealership markups (STR) | 0.25 | 0.08 |
Input price index without markups (STR) | 0.31 | 0.04 |
Input price index including markups (STR) | 0.57 | 0.00 |
Note: CPI = Consumer Price Index; PPI = Producer Price Index; MPI = Import Price Index; STR = short-term price relative. Source: Author's calculations based on data from the U.S. Bureau of Labor Statistics. |
The strong graphical correlations between the official PPI for dealership markups and the estimated markup index, as well as between the CPI for new vehicles and the input price index including markups, further demonstrate that markup increases at dealerships drove the gaps among the CPI for new vehicles, the PPI for new vehicles, and the MPI for new vehicles. These gaps are crucial to understanding the drivers of new-vehicle consumer inflation during the COVID-19 pandemic, because they help isolate where in the supply chain inflation occurred—in this case, at dealerships. To further corroborate the trends apparent in BLS data, chart 5 and table 3 illustrate profit-margin changes at publicly traded dealerships from 2019 through 2022. Like BLS-derived estimates, SEC financial data for publicly traded dealerships show that markups grew from an average of 5.0 percent in 2019 to an average of 13.1 percent in 2022. This observation further demonstrates the impact of profit-margin growth on consumer vehicle prices and confirms the validity of the BLS-derived estimates presented earlier. Measuring profits as a percentage of the average vehicle price shows that the proportion of the consumer price represented by dealership markups grew from 4.8 percent in 2019 to 11.5 percent in 2022.18
Quarter | Industry total | AutoNation | Asbury Automotive Group | Group 1 Automotive | Lithia Motors | Sonic Automotive |
---|---|---|---|---|---|---|
Q1 2019 | 5.3 | 5.1 | 4.5 | 5.3 | 6.2 | 5.3 |
Q2 2019 | 4.9 | 4.7 | 4.1 | 4.7 | 5.9 | 4.9 |
Q3 2019 | 4.7 | 4.3 | 4.1 | 4.8 | 5.8 | 4.6 |
Q4 2019 | 5.2 | 4.8 | 4.5 | 5.3 | 6.1 | 5.2 |
Q1 2020 | 4.9 | 4.4 | 4.6 | 4.9 | 6.0 | 5.0 |
Q2 2020 | 6.0 | 5.6 | 5.3 | 6.4 | 7.2 | 5.3 |
Q3 2020 | 6.8 | 6.5 | 6.8 | 6.7 | 8.0 | 6.1 |
Q4 2020 | 7.0 | 6.9 | 7.3 | 7.0 | 7.5 | 6.5 |
Q1 2021 | 7.0 | 6.8 | 7.0 | 6.9 | 7.7 | 6.4 |
Q2 2021 | 10.2 | 10.3 | 10.0 | 9.8 | 11.1 | 8.8 |
Q3 2021 | 12.8 | 13.1 | 12.6 | 11.9 | 13.7 | 11.2 |
Q4 2021 | 14.5 | 14.6 | 14.7 | 13.2 | 15.6 | 13.2 |
Q1 2022 | 14.1 | 14.0 | 13.7 | 13.0 | 15.1 | 14.2 |
Q2 2022 | 13.8 | 13.7 | 13.4 | 12.8 | 14.4 | 14.3 |
Q3 2022 | 13.1 | 13.0 | 12.6 | 12.3 | 13.9 | 13.5 |
Q4 2022 | 11.9 | 12.0 | 12.0 | 11.1 | 12.5 | 11.7 |
Source: Author's calculations based on U.S. Securities and Exchange Commission data. |
Although pandemic-related supply-chain bottlenecks and semiconductor shortages significantly affected the quantity of vehicles produced by manufacturers—and also had an impact on producer prices for new vehicles—chart 3 shows that these disruptions had a stronger effect on consumer prices than on producer prices.19 From December 2019 through December of 2022, the compound annual rate of change for the PPI for new vehicles was 2.6 percent, which is only 0.9 percentage point higher than the average rate of 1.7 percent during the 2007–19 business cycle. Over the same 2019–22 period, the compound annual rate of change for the MPI for new vehicles was 2.1 percent, which is only 1.9 percentage points higher than the average rate of 0.2 percent during the 2007–19 business cycle. The increases in the PPI and MPI rates of change are overshadowed by the change in trend for the CPI for new vehicles. From December 2019 through December 2022, the CPI for new vehicles grew at a compound annual rate of 6.0 percent, which is 5.3 percentage points higher than the average rate of 0.7 percent during the 2007–19 business cycle. These stark differences further demonstrate that increases in dealership profit margins were a stronger driver of consumer price changes than were manufacturer price increases.
Trends in vehicle production, total sales, and vehicle inventories help explain the subdued price transmission from manufacturers to consumers, and from consumers to producers, in the automotive supply chain during the 2020–22 business cycle. Chart 6 shows that dealership inventories shrank substantially during the recent economic expansion. Shortly after stimulus checks were issued in two rounds in late 2020 and early 2021 (the first stimulus round occurred in April 2020), dealership sales surged in March and April of 2021, and monthly sales continued to remain above their pandemic lows during the remainder of 2021. However, chart 6 shows that dealerships did not substantially increase their orders of new vehicles from manufacturers, which led to shrinking inventories and subdued production. The drop in inventories and the increase in sales that occurred shortly after the second and third stimulus payments coincide with the rapid increase in consumer prices shown in charts 3 and 4.
Normally, dealerships maintain large vehicle inventories that are costly to manage and that can force dealers to offer competitive price cuts to consumers. However, given supply-chain disruptions and persistently high demand, dealership inventories shrank to all-time lows in 2021 and 2022, applying upward pressure on consumer prices.20 In January 2020, average inventories stood at 526,000 units, but by February 2022, that number had dropped to a record low of 65,000 units, a decline of 87.6 percent. In 2021, some dealerships averaged less than 2 weeks’ worth of inventory, down from a more typical 2 to 3 months of inventory before the pandemic. AutoNation, for example, averaged only 9 days’ worth of inventory in 2021, compared with an average of 52 days in 2019 and 60 days in 2018.21 Shrinking retail inventories are crucial to understanding the divergence between consumer and producer vehicle prices. Instead of relying on manufacturer supplies to meet consumer demand, dealerships drew down their existing inventories. As a result, backward demand transmission from consumer-demand increases was insufficient to generate demand increases for manufactures, and dealerships absorbed the existing demand through markup increases and inventory drawdowns.
During the pandemic downturn and the subsequent economic expansion, new-vehicle orders, unfilled orders, and factory output were highly volatile, contributing to the inventory drought at dealerships. Chart 6 shows that, from February 2020 through May 2020, new-vehicle orders to manufacturers collapsed as economic actors across the supply chain anticipated a large decrease in demand. Although new-vehicle orders quickly rose to prepandemic levels in June 2020, they failed to consistently remain above those levels after some initial spikes in the summer of 2020, despite surges in consumer demand. Additionally, because new-vehicle orders are a flow that cumulates into a stock of total orders, the 5 below-trend months from February to May 2020 had a cumulative impact on the stock of overall orders that the industry never overcame. Factories also shut down entirely in March 2020, with output falling 99.8 percent in a single month. Finally, when new-vehicle orders recovered, manufacturers failed to fill them because of global supply-chain disruptions. In 2020 and 2021, unfilled orders grew and manufacturing remained flat, causing further declines in dealer inventories.
Charts 7 and 8 show that automotive sales and automotive loans increased substantially during and immediately after the three rounds of stimulus payments in 2020 and 2021. The 1-month percent change for automotive sales jumped to an all-time high of 38.2 percent in April 2020, and this jump coincided with the initial COVID-19 stimulus. Additionally, the 1-month percent change for automotive loans reached an all-time high of 1.4 percent in April 2021, immediately after the stimulus of March 2021. The data strongly suggest that many consumers used their stimulus payments to support the purchase of vehicles. Personal savings and government expenditures all increased substantially during the months of the stimulus payments. These increases also coincided with increases in vehicle prices, decreases in vehicle inventories, and increases in vehicle sales (see charts 3 and 6).
Taken together, the trends in consumer prices, producer prices, dealership markups, automotive inventories, automotive production, and stimulus expenditures suggest that dealership profit-margin increases in response to stimulus-driven demand contributed substantially to new-vehicle consumer inflation in 2020 and 2021. Given the considerable evidence that profit-margin increases caused a divergence between the PPI for new vehicles and the CPI for new vehicles, the inflationary impact of those increases can be estimated simply as the difference between the two indexes. If the CPI for new vehicles had moved in lockstep with the PPI for new vehicles from 2019 to 2022 (meaning dealer margins were stable), it would have increased by 7.9 percent, which is 12.8 percentage points lower than the actual 20.7-percent increase (or 38.3 percent of the total change). SEC financial data show that the share of markups in a vehicle’s retail price increased by 140.9 percent during the pandemic, rising from an average of 4.9 percent in 2019 to an average of 11.5 percent in 2022. In total, profit-margin increases were responsible for 34.7 percent of dealerships’ total increase in revenues from new-vehicle sales. Using the implicit counterfactuals from BLS and SEC data, one can estimate that dealership markups, working through price transmission, contributed between 34.7 and 61.7 percent of total new-vehicle consumer inflation from 2019 through 2022. Given that new vehicles account for 4.3 percent of the overall CPI, the transmission of dealership markups to consumer prices contributed roughly 0.3 to 0.5 percentage point to the overall 15.6-percent increase in the CPI from December 2019 through December 2022.
In addition to raising new-vehicle prices, dealerships also substantially increased prices for other services. Chart 9 shows that these price increases coincided with the stimulus payments issued in late 2020 and early 2021. The dealership service index for “other receipts,” which mostly tracks the sale of financial, insurance, and extended warranty products, began increasing rapidly in March and April of 2021. Because products captured by the “other receipts” index are not affected by the supply chain, their price increases are entirely due to increased demand for dealership services. In February 2022, the “other receipts” index recorded a 12-month increase of 33.5 percent, an all-time high. The fact that prices for other dealership services and dealer markups increased at the same time further demonstrates that dealerships experienced an influx of customers in early 2021.
During the COVID-19 pandemic, dealership profit-margin increases drove new-vehicle consumer inflation and contributed modestly to overall consumer inflation. The implicit relationships between BLS consumer and producer price data illustrate these inflationary dynamics. By relying on their existing inventories to supply consumers with vehicles, dealerships shrank those inventories and gained more pricing power. The PPI for dealership markups is a moderator variable that bridges the gaps in the implicit relationships among the CPI, PPI, and MPI for physical goods. These relationships may work in other industries and could offer a predictive path to estimating lagged quarterly profits with the more timely BLS monthly price data.
This appendix presents two equation sets for calculating the STR of the estimated markup index (equation set 1) and the input price index including markups (equation set 2).
The STR of the estimated markup index is calculated as follows:
where and are the average vehicle transaction prices in, respectively, periods t – 1 and t – 2; and are the average vehicle wholesale prices in, respectively, periods t – 1 and t – 2; and and are the PPI STRs for new vehicles in, respectively, periods t and t – 1.
The values of and are calculated as follows:22
The initial average vehicle wholesale price in the base period of January 2019 is calculated as
where is 4.9 percent, and is 1.
The input price index including markups is calculated as follows:
where and are the PPIs for dealership markups in, respectively, periods T and T – t; and are the input price indexes without markups in, respectively, periods T and T – t; and and are the weights in, respectively, periods T and T – t.
The input price index excluding markups is calculated as follows:
where and are the PPIs for new vehicles in, respectively, periods T and T – t; and are the MPIs for new vehicles in, respectively, periods T and T – t; and and are the weights in, respectively, periods T and T – t.
The values of , , and are calculated as follows:
In the last equation, is the total dollar amount of domestically produced vehicles sold in the United States in period T, and is the total dollar amount of imported vehicles sold in the United States in period T.
Michael Havlin, "Automotive dealerships 2019–22: dealer markup increases drive new-vehicle consumer inflation," Monthly Labor Review, U.S. Bureau of Labor Statistics, April 2023, https://doi.org/10.21916/mlr.2023.7
1 Kevin M. Camp, Michael Havlin, and Sara Stanley, “Automotive dealerships 2007–19: profit-margin compression and product innovation,” Monthly Labor Review, October 2022, https://doi.org/10.21916/mlr.2022.26.
2 This article focuses on new-vehicle prices because supply-chain disruptions most proximally affected the manufacturing of new vehicles, rather than immediately causing shortages in the used-vehicle market. Used vehicles played an important role in the used-car shortage through their substitutability with new vehicles and merit attention in a separate analysis; however, the dynamics of the used-car market are quite distinct from those of the new-car market, and the used-car shortage is subordinate to the initial supply-chain shocks.
3 The U.S. Bureau of Labor Statistics (BLS) Producer Price Index (PPI) program publishes several margins indexes for dealer services, including an index for total vehicle sales, new-vehicle sales, and used-vehicle sales. This analysis uses the BLS index for total vehicle sales because corroborating evidence from corporate financial data (see chart 5) shows that this index was a much better estimator of new-vehicle margins during the pandemic.
4 This relationship is demonstrated in Camp, Havlin, and Stanley, “Automotive dealerships 2007–19.”
5 See ibid. Company-specific information is from the 10-K forms filed with the U.S. Securities and Exchange Commission (SEC), which are stored in the SEC EDGAR database (https://www.sec.gov/edgar/search/).
6 Camp, Havlin, and Stanley, “Automotive dealerships 2007–19.”
7 David Coffin, Dixie Downing, Jeff Horowitz, and Greg LaRocca, “The roadblocks of the COVID-19 pandemic in the U.S. automotive industry,” Working Paper ID-091 (U.S. International Trade Commission, June 2022), https://www.usitc.gov/publications/332/working_papers/final_the_roadblocks_of_the_covid-19_pandemic_in_the_automotive_industry.pdf.
8 Christian Zimmermann, “Clocking the sales of cars and homes,” The FRED Blog (Federal Reserve Bank of St. Louis, July 23, 2018), https://fredblog.stlouisfed.org/2018/07/clocking-the-sales-of-cars-and-homes/?utm_source=series_page&utm_medium=related_content&utm_term=related_resources&utm_campaign=fredblog.
9 Automotive manufacturers commonly seek to move excess inventories to dealerships because these inventories are costly to maintain.
10 “Personal saving” (FRED, Federal Reserve Bank of St. Louis, February 23, 2023), https://fred.stlouisfed.org/series/PSAVE.
11 Kristen Tauber and Willem Van Zandweghe, “Why has durable goods spending been so strong during the COVID-19 pandemic?” (Federal Reserve Bank of Cleveland, July 7, 2021), https://www.clevelandfed.org/publications/economic-commentary/2021/ec-202116-durable-goods-spending-during-covid19-pandemic.
12 The estimated markup index was generated by inflating the average consumer and producer vehicle prices in 2019 by the CPI for new vehicles and the PPI for new vehicles, subtracting those products from each other, and calculating a cumulative percent change from the derived margin. The dollar amounts in 2019 are algebraically and mathematically irrelevant to the results, so they simply serve to make the linear combination more intuitive for the reader. The determinative assumption in this recreation is the base-period margin, which is assumed to be 5.0 percent, pursuant to SEC data. Although the calculation of a proper input index should also include the import index, the latter was excluded because (1) the import prices of vehicles trended with producer prices, (2) vehicle imports had a small weight, and (3) the inclusion of the import index would have introduced complexity without changing the results.
13 These data are from the 10-K forms filed with the SEC, which are stored in the SEC EDGAR database (https://www.sec.gov/edgar/search/).
14 Michael Havlin, “From wholesalers to gas tanks: with gasoline, two plus two really does equal four,” Monthly Labor Review (forthcoming); and Jayson Pollock and Jonathan C. Weinhagen, “A new BLS satellite series of net inputs to industry price indexes: methodology and uses,” Monthly Labor Review, September 2020, https://doi.org/10.21916/mlr.2020.22.
15 Pollock and Weinhagen, “A new BLS satellite series of net inputs to industry price indexes.”
16 Here, margin percentages, rather than markups, should be used as weights because the weights reflect how a markup relates to its proportion of the final price.
17 Don A. Fast and Susan E. Fleck, “Unit values for import and export price indexes: a proof of concept,” in Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro, eds., Big data for twenty-first-century economic statistics (Chicago, IL: University of Chicago Press, 2022), pp. 275–295, https://www.bls.gov/mxp/data/unit-values-import-export-price-indexes.pdf; and Don Fast, Susan E. Fleck, and Dominic A. Smith, “Unit value indexes for exports—new developments using administrative trade data,” Journal of Official Statistics, Sciendo, vol. 38, no. 1, March 2022, pp. 83–106, https://doi.org/10.2478/jos-2022-0005.
18 Company-specific information is from the 10-K forms filed with the SEC, which are stored in the SEC EDGAR database (https://www.sec.gov/edgar/search/).
19 Coffin, Downing, Horowitz, and LaRocca, “The roadblocks of the COVID-19 pandemic in the U.S. automotive industry.”
20 See Hannah Lutz, “Auto dealers find inventory loans more costly,” Automotive News, April 8, 2019, https://www.autonews.com/nada/auto-dealers-find-inventory-loans-more-costly; and Ayelet Israeli, Fiona Scott-Morton, Jorge Silva-Risso, and Florian Zettelmeyer, “How market power affects dynamic pricing: evidence from inventory fluctuations at car dealerships,” Management Science, vol. 68, no. 2, February 2022, pp. 895–916, https://www.hbs.edu/faculty/Pages/item.aspx?num=59497.
21 AutoNation 2019 10-K form (annual report) retrieved from SEC EDGAR database (https://www.sec.gov/ix?doc=/Archives/edgar/data/0000350698/000035069820000042/an10k2019.htm).
22 The starting average vehicle transaction price and the starting average vehicle wholesale price are entirely irrelevant for the equation’s result. The determinative assumption is the initial percent difference between the average vehicle transaction price and the average vehicle wholesale price, and this difference is assumed to be 4.9 percent in the initial period (January 2019).