Automobile Industry Retail Price 

Equivalent and Indirect Cost Multipliers 
Automobile Industry Retail Price 


Equivalent and Indirect Cost Multipliers


Assessment and Standards Division


Office of Transportation and Air Quality


U.S. Environmental Protection Agency


Prepared for EPA by 


RTI International 


and


Transportation Research Institute


University of Michigan


RTI Project Number 0211577.002.004


NOTICE 

This report has been peer-reviewed following the guidelines recommended 

by the EPA Science Policy Council’s Peer Review Handbook, 3rd Edition, 

June 2006. The peer review report for this report is available as a separate 

document, “Peer Review for the RTI Report, Passenger Vehicle Retail Price 

Equivalent Factors and Indirect Cost Multipliers” (EPA-420-R-09-004). This 

technical report does not necessarily represent final EPA decisions or positions. It is intended to present technical analysis of issues using data that are 

currently available. The purpose in the release of such reports is to facilitate 

the exchange of technical information and to inform the public of technical 

developments. 

EPA-420-R-09-003 

February 2009 
February 2009 

Automobile Industry Retail Price 

Equivalent and Indirect Cost 

Multipliers 

Report 

Prepared for 

Gloria Helfand 

U.S. Environmental Protection Agency 

Office of Transportation and Air Quality 

2000 Traverwood Drive 

Ann Arbor, MI 48105 

Prepared by 

Alex Rogozhin 

Michael Gallaher 

RTI International 

3040 Cornwallis Road 

Research Triangle Park, NC 27709 

Walter McManus 

Transportation Research Institute 

University of Michigan 

2901 Baxter Road 

Ann Arbor, MI 48109 

RTI Project Number 0211577.002.004 
_________________________________ 

RTI Project Number 

0211577.002.004 

Automobile Industry Retail Price 

Equivalent and Indirect Cost 

Multipliers 

Report 

February 2009 

Prepared for 

Gloria Helfand 

U.S. Environmental Protection Agency 

Office of Transportation and Air Quality 

2000 Traverwood Drive 

Ann Arbor, MI 48105 

Prepared by 

Alex Rogozhin 

Michael Gallaher 

RTI International 

3040 Cornwallis Road 

Research Triangle Park, NC 27709 

Walter McManus 

Transportation Research Institute 

University of Michigan 

2901 Baxter Road 

Ann Arbor, MI 48109 

RTI International is a trade name of Research Triangle Institute. 
CONTENTS

Section Page

 Executive Summary....................................................................................................ES-1 

1 Introduction................................................................................................................... 1-1 

2 Comparing RPE Multiplier and IC Multiplier Approaches.......................................... 2-1 

3 RPE Multiplier Estimation............................................................................................ 3-1 

3.1 Components of Indirect Costs.............................................................................. 3-1 

3.2 Company-Level IC Components and RPE Multipliers ....................................... 3-3 

3.2.1 Data Origin and Limitations .................................................................... 3-3 

3.2.2 Data Assumptions and Adjustments ........................................................ 3-3 

3.2.3 IC Components and RPE Multiplier Values............................................ 3-5 

3.3 Industry Average Indirect Costs and RPEs.......................................................... 3-8 

4 IC Multiplier Estimation............................................................................................... 4-1 

4.1 Technology Complexity and Innovation Scope................................................... 4-2 

4.2 Impacts of a New Technology on Automotive Manufacturers’ Operations........ 4-4 

4.3 Evaluating Indirect Cost Contributors ................................................................. 4-6 

4.3.1 Low Complexity: Low Rolling Resistance Tires..................................... 4-7 

4.3.2 Medium Complexity: Dual Clutch Transmissions .................................. 4-8 

4.3.3 High Complexity: Hybrid Electric Vehicle ........................................... 4-11 

4.4 Calculating IC Multipliers ................................................................................. 4-11 

4.5 Summary............................................................................................................ 4-12 

5 Conclusion .................................................................................................................... 5-1

5.1 Applicability of the RPE and IC Multipliers in Future Years ............................. 5-1 

iii 
References..............................................................................................................................R-1 

Appendix 

A: Calculation of RPE Multipliers for Individual Manufacturers ........................... A-1 

iv 
LIST OF FIGURES 

Number Page 

2-1. RPE Multiplier vs. IC Multiplier Approach .............................................................. 2-2

4-1. Impacts of Technology Complexity on IC Multiplier ............................................... 4-3

4-2. Definition of Innovation Processes............................................................................ 4-3

v 
LIST OF TABLES 

Number Page 

ES-1. Industry Average and Individual Company RPE Multipliers: 2007..............................2

ES-2. IC Multipliers by Technology Complexity and Time Frame ........................................3

3-1. RPE Multiplier Contributors in Vyas et al.’s Methodology ...................................... 3-2

3-2. RPE Multiplier Contributors in RTI’s Methodology................................................. 3-2

3-3. Individual Manufacturer and Industry Average RPE Multipliers: 2007 ................... 3-7

3-4. Weighted RPE Multiplier: 2007 ................................................................................ 3-8

4-1. Weighted Average IC Multiplier Contributors to RPE: 2007 ................................... 4-2

4-2. Impact on Operations................................................................................................. 4-5

4-3. Short-Term Effects on Indirect Cost Contributors..................................................... 4-8

4-4. Long-Term Effects on Indirect Cost Contributors................................................... 4-10

4-5. Short- and long-Term IC Multiplier Calculations ................................................... 4-13

A-1. McKinsey’s Automobile Industry Manufacturers’ Cost Contributions to 

MSRP........................................................................................................................ A-2

A-2. Automobile Manufacturing Industry RPE Multiplier (based on McKinsey’s 

Data).......................................................................................................................... A-2

A-3. Dealer Gross Profit Margin on New-Vehicle Sales.................................................. A-3

A-4. Average U.S. Dealership Net Profit and Selling Expenses on New Vehicle 

Sales as a Share of New Vehicle Sales, 2003–2007 ................................................. A-4

A-5. Dealer Net Profit and Selling Expenses on New Vehicle Sales as a Share of 

Manufacturers’ Cost of Sales.................................................................................... A-6

A-6. General Motors RPE Multiplier Calculations: 2007................................................. A-8

A-7. General Motors Main Indirect Cost Contributors (as a Share of Cost of Sales)....... A-9

A-8. DaimlerChrysler RPE Multiplier Calculations: 2006............................................. A-10

A-9. DaimlerChrysler Main Indirect Cost Contributors (as a Share of Cost of Sales)... A-11

A-10. Ford Motor Company RPE Multiplier Calculations: 2007..................................... A-12

A-11. Ford Motor Company Main Indirect Cost Contributors (as a Share of Cost of 

Sales)....................................................................................................................... A-14

A-12. Honda Motor Company RPE Multiplier Calculations: 2007.................................. A-15

A-13. Honda Motor Company Main Indirect Cost Contributors (as a Share of Cost 

of Sales) .................................................................................................................. A-16

A-14. Hyundai Motor Company RPE Multiplier Calculations: 2007............................... A-17

vi 
A-15. Hyundai Motor Company Main Indirect Cost Contributors (as a Share of Cost 

of Sales) .................................................................................................................. A-18

A-16. Nissan Motor Company RPE Multiplier Calculations: 2007 ................................. A-19

A-17. Nissan Motor Company Main Indirect Cost Contributors (as a Share of Cost 

of Sales) .................................................................................................................. A-20

A-18. Toyota Motor Company RPE Multiplier Calculations: 2007................................. A-21

A-19. Toyota Motor Company Main Indirect Cost Contributors (as a Share of Cost 

of Sales) .................................................................................................................. A-22

A-20. Volkswagen Group RPE Multiplier Calculations: 2007......................................... A-23

A-21. Volkswagen Historical Main Indirect Cost Contributors (as a share of Cost of 

Sales)....................................................................................................................... A-24

vii 
EXECUTIVE SUMMARY 

When developing environmental regulations, government agencies typically must 

estimate and consider the cost of the regulation to society. The cost of new regulations to 

producers, such as vehicle manufacturers, typically shows up in two broad categories: direct 

manufacturing costs and indirect costs. Direct manufacturing costs include manufacturing labor 

and direct material costs, which can be estimated via reverse engineering or other approaches. 

Indirect costs include research and development, corporate operations, dealer support, and 

marketing and are difficult to estimate because many indirect costs are difficult to allocate to 

specific production activities or are not affected by levels of production. 

Because of the difficulties of estimating indirect costs associated with new technologies, 

the automotive industry has often applied scaling factors to changes in estimated direct costs to 

capture changes in indirect costs and, hence, predict the full impact vehicle modifications will 

have on the final selling price. A commonly used scaling factor is the retail price equivalent 

(RPE) multiplier, which is historically based and compares direct manufacturing costs with all 

other factors that influence the final price of a vehicle. Regulatory agencies, including the U.S. 

Environmental Protection Agency (EPA), have used RPE multipliers to scale the direct 

manufacturing costs associated with a regulation when estimating the total social cost of the 

regulation. However, a problem in using RPE multipliers in regulatory analysis is that some of 

the indirect cost components of the RPE multiplier, such as fixed depreciation costs, health care 

costs for retired workers, or pensions, may not be affected by all vehicle modifications resulting 

from regulation. 

This report develops a modified multiplier, referred to as an indirect cost (IC) multiplier, 

which specifically evaluates the components of indirect costs that are likely to be affected by 

vehicle modifications associated with environmental regulation. A range of IC multipliers are 

developed that 1) account for differences in the technical complexity of required vehicle 

modifications and 2) adjust over time as new technologies become assimilated into the 

automotive production process. 

We started our analysis by developing an industry average RPE multiplier for the 

passenger car industry. Using the methodology described by Vyas, Santini, and Cuenca (2000) as 

a guideline, we identified contributing factors to an automobile manufacturer’s RPE multiplier. 

We used the data from annual reports of DaimlerChrysler, Ford, General Motors, Honda, 

Hyundai, Nissan, Toyota, and Volkswagen to calculate RPE multipliers for passenger car 

ES-1 
manufacturers. Individual manufacturers’ RPE multipliers are presented in Table ES-1 and range 

from 1.42 to 1.49. Weighting by 2007 worldwide sales provides an industry average RPE 

multiplier of 1.46. 

Table ES-1. Industry Average and Individual Company RPE Multipliers: 2007 

Company Annual Production (number of vehicles) (2007) RPE Multiplier 

DaimlerChryslera 4,635,601 1.47 

Ford 6,247,506 1.45 

GM 9,349,818 1.45 

Honda 3,911,814 1.47 

Hyundai 2,617,725 1.42 

Nissan 3,431,398 1.49 

Toyota 8,534,690 1.48 

VW 6,267,891 1.43 

Weighted Average 1.46 

a Only 2006 sales were available. Thus, 2006 sales and a 2006 RPE multiplier for DaimlerChrysler were used in 

calculating the industry average. 

Source: 2007 Company Annual Reports. 

We then assert that not all components of the RPE will be affected by future EPA 

environmental regulations and conclude that a series of adjusted IC multipliers should be 

developed and be available for a range of possible regulatory alternatives. We show that 

environmental regulatory actions would have different impacts on cost contributors depending 

on the complexity of the technology associated with compliance. We introduce three levels of 

technology complexity: low, medium, and high. We argue that low-complexity technologies 

would have a smaller impact on manufacturers’ operations than high-complexity technologies. 

We also argue that the magnitude of impacts would decline over time. Based on these findings, 

we constructed a series of IC multipliers, presented in Table ES-2, that more accurately reflect 

the change in manufacturers’ indirect costs associated with the change in direct manufacturing 

costs under different scenarios. We believe using these IC multipliers is a more appropriate 

method for EPA to estimate indirect costs associated with future regulatory actions compared to 

using a single RPE multiplier. 

ES-2 
Table ES-2. IC Multipliers by Technology Complexity and Time Frame 

 Technology Complexity 

Time Frame Low Medium High 

Short-term effects 1.05 1.20 1.45 

Long-term effects 1.02 1.05 1.26 

This approach to estimating the indirect costs of new technologies can be used in two 

ways. First, the values in Table ES-2 can be used directly once the level of complexity of a new 

technology is determined. Second, if there is more detailed information about the indirect costs 

associated with a new technology, the methodology developed in this study can be used to 

develop a unique IC multiplier specific to that technology. 

ES-3 
SECTION 1

INTRODUCTION 

In addition to the direct manufacturing costs incurred during the vehicle production 

process, a manufacturer incurs certain indirect costs. These costs may be related to production, 

such as research and development (R&D); corporate operations, such as salaries, pensions, and 

health care costs for corporate staff; or selling, such as transportation, dealer support, and 

marketing. Indirect costs are generally recovered by allocating a share of the costs to each unit of 

goods sold (Vyas, Santini, and Cuenca, 2000). Because indirect costs affect the retail price of a 

vehicle, markup factors that relate indirect costs to the changes in direct manufacturing costs 

have been developed and are often referred to as retail price equivalent (RPE) multipliers. Cost 

analysts have frequently used these multipliers to predict the impact vehicle modifications will 

have on the final selling price. Using these multipliers implicitly assumes that incremental 

changes in direct manufacturing costs have a common (percentage) change on all indirect cost 

components as well as profits. 

Conceptually, RPE multipliers provide, at an aggregate level, the relative shares of direct 

manufacturing costs and all other items that affect the business of auto manufacturing. The 

numerator of this ratio comprises indirect costs and profits. 

RPE = (Revenues)/(direct manufacturing costs), 

or, equivalently, 

RPE = (direct + indirect costs + profits)/(direct manufacturing costs) 

Regulatory agencies, including the U.S. Environmental Protection Agency (EPA), have 

used RPE multipliers to scale the incremental direct manufacturing costs associated with a 

regulation to estimate the total cost of the regulation. However, a problem in using RPE 

multipliers in regulatory analysis is that some of the indirect cost component of the RPE 

multiplier, such as fixed depreciation costs, retirees’ health care costs, or pensions, may not be 

affected by vehicle modifications resulting from regulation. In addition, RPEs assume that 

market prices will increase by the full cost plus constant profit of the new technology; in fact, 

other factors that influence price (especially consumer demand and preferences) will affect how 

much of those costs will be passed along into market price. 

1-1 
This study develops a modified multiplier, referred to as an indirect cost (IC) multiplier, 

which specifically evaluates the components of indirect costs that are likely to be affected by 

vehicle modifications associated with environmental regulation. 

IC Multiplier = (Incremental direct + indirect costs)/(incremental direct manufacturing costs) 

A range of IC multipliers are developed that 1) account for differences in the technical 

complexity of required vehicle modifications and 2) adjust over time as modifications become 

assimilated into the automotive supply chain. 

To calculate the IC multiplier, we began with the relative shares (%) for individual 

indirect cost categories developed through past RPE studies and updated them based on 

company-specific information obtained from recent annual reports. We then adjusted these 

indirect cost category shares to reflect differences in the technical complexity of automotive 

modifications that could result from different environmental regulations and to reflect how 

indirect cost impacts will change over time as new technologies are assimilated into the industry 

supply chain. 

The remainder of this section describes how indirect multipliers have been developed in 

the past and focuses on the applicability of individual indirect cost components when considering 

vehicle technology changes due to environmental regulations. This discussion is followed by an 

overview of the methodology we used to calculate the IC multiplier we recommend to be used to 

assess potential environmental regulations. 

1.1 Previous Indirect Cost Studies 

In past mobile source regulatory actions, EPA has sometimes used a multiplier of 1.26 to 

account for the indirect costs associated with the direct manufacturing cost impacts of a 

regulation. This factor was originally derived for light-duty highway or passenger vehicles in the 

late 1970s and then updated (including other vehicle types) in 1985 by Jack Faucett Associates 

under contract to EPA (Jack Faucett Associates, 1985). 

In 2000, researchers at the Argonne National Laboratory published a technical 

memorandum comparing three different estimates of RPE multipliers (Vyas, Santini, and 

Cuenca, 2000). In their study, Vyas et al. compared their own estimates (developed for passenger 

vehicles with an emphasis on electric vehicles) with those from Chrysler and Energy and 

Environmental Analysis and found that the three estimates, when put on a comparable basis, 

1-2 
were very similar. Vyas et al.’s analysis estimated RPE factors of 1.5 for outsourced components 

and 2.0 for products developed and manufactured internally at an automotive manufacturer. 

A more recent analysis commissioned by the automobile manufacturing industry and 

conducted by Sierra Research, Inc. (2007) suggested that the 1985 Faucett report contains “basic 

methodological errors that make it unreliable for use in a regulatory analysis.” The Sierra 

Research analysis concluded that an RPE factor for components manufactured internally at an 

automotive manufacturer should be about 2.0 to accurately account for indirect costs. 

1.2 Indirect Cost (IC) Multiplier Developed as Part of This Study 

Building on the analysis developed by Vyas et al., we developed a methodology to 

evaluate which indirect cost components will be affected by different potential regulatory 

actions. We distinguished between regulations requiring different levels of technical complexity. 

The underlying concept is that regulations requiring major changes in materials or manufacturing 

processes, or significant invention of new technology, will likely have a significant impact on 

indirect costs. In contrast, regulations requiring simple technology modifications may have 

negligible impacts on indirect costs. For this reason, implementing a single multiplier including 

all indirect costs across all technologies is not appropriate. 

Our analysis is presented in four sections. In Section 2, we discuss the relationship of 

multiplicative adjustment factors to a market model based on a supply and demand modeling 

approach. We also explain why we believe the IC multiplier approach is more appropriate than 

the RPE multiplier approach when calculating a change in indirect costs associated with a 

regulation. 

In Section 3, we present an overview of how we used Vyas et al.’s methodology to 

calculate RPE multipliers for individual manufacturers. We then calculated an average RPE 

multiplier for the automobile manufacturing industry using data from the annual reports of 

DaimlerChrysler, Ford, General Motors (GM), Honda, Hyundai, Nissan, Toyota, and 

Volkswagen1. 

In Section 4, we present the methodology we used to calculate IC multipliers customized 

for different types of regulations and present the application of the methodology for three 

potential technology categories. We then developed adjustment factors for each component of 

that multiplier for different complexities of technologies because not all components of the RPE 

will be affected by the introduction of new technologies. We also made adjustments for short-run 

1

 Calculations were based on the financial statements of manufacturers that covered worldwide automobile 

production (including passenger cars and light trucks). Manufacturers did not breakout financial results by 

production of passenger car vs. light truck vehicles, or worldwide vs. United States production. 

1-3 
(approximately the first 4 to 5 years of application of the new technology) and long-run (after 5 

years of use) effects to account for technology assimilation over time. The multipliers that result 

from this adjustment process are called indirect cost multipliers, or IC multipliers. We estimated 

that the value of the IC multipliers varies from 1.02 to 1.45 for technologies with different levels 

of technical complexity in the short and long runs. 

Section 5 summarizes our conclusions and provides a discussion of how IC multipliers 

might be affected by industry restructuring. Finally, in Appendix A we provide a detailed 

description of calculations and data sources of RPE multipliers for individual manufacturers. 

1-4 
SECTION 2

COMPARING RPE MULTIPLIER AND INDIRECT COST MULTIPLIER 

APPROACHES 

Executive Order 12866, “Regulatory Planning and Review,” issued in 1993, requires 

federal agencies to estimate the benefits and costs of significant regulatory actions. Circular A-4 

of the Office of Management and Budget and the EPA’s Guidelines for Preparing Economic 

Analyses stipulate use of a microeconomic framework to analyze the benefits and costs. This 

section discusses the relationship between the multipliers developed in this report and the 

microeconomic framework in which they will be used. 

In this section, we compare two approaches for estimating the total cost of a regulation. 

One approach is to use an RPE multiplier to account for indirect costs and estimate the price 

change. The second is to use an IC multiplier to estimate the shift in the supply curve and then 

use a market model to estimate the change in price and quantity (which will influence the total 

cost of a regulation). 

The RPE multiplier approach has been used as a method to estimate the change in 

indirect costs that are included in the total cost of a regulation. This approach has typically 

included using all indirect cost categories and profits to develop a multiplier that is then applied 

to the estimated direct manufacturing costs. The projected change in the retail price times the 

quantity affected is then used in the estimate of the full cost of the regulation. 

We believe the RPE multiplier approach has problems in two areas. First, as we discuss 

in the following sections of this report, regulations will most likely not affect all categories of 

indirect costs. The indirect costs affected will vary by the complexity of the technology and will 

change over time (short run versus long run). In Section 4, we develop a series of IC multipliers 

to capture these factors. 

Second, applying the RPE alone does not yield an accurate estimate of the change in 

price. Direct manufacturing costs and indirect costs resulting from a regulation reflect shifts in 

the total cost of production. In a market framework, this is represented by a shift in the supply 

function. Consider the following scenario presented in Figure 2-1. Initially the market is in 

equilibrium. Manufacturers produce quantity Q1 and buyers purchase that quantity at the price of 

P1 per vehicle (point A). Then a regulation is passed requiring manufacturers to implement a new 

technology. The added cost shifts the supply curve upward. The shift equals the per-unit cost of 

regulation, which includes both direct and indirect costs. 

2-1 
The RPE multiplier approach assumes that the multiplier captures the full market impact 

of the new cost. Sales continue at Q1, and the price will rise to P2 (point B). The RPE multiplier 

approach implies that demand is perfectly inelastic and there is a full pass-through of costs to 

consumers. 

Price 

S1: With Regulation 

D 

P2 

P3 

S0: Without Regulation 

P1 A 

B 

C 

Q3 Q2 Q1 Quantity 

Figure 2-1. RPE Multiplier vs. IC Multiplier Approach 

However, if the demand curve is less than perfectly inelastic (as shown in Figure 2-1), 

consumers will demand fewer vehicles as the price increases. A new equilibrium will be 

determined at the intersection of the supply and demand curves (point C). The new price will be 

P3 and the new output will be Q2. As a result, the final cost of the regulation (social cost) will be 

slightly less than the original cost estimate because of the decrease in quantity being produced. 

The original cost estimate, based on operation at point B, would be the area between lines S0 and 

S1, the price axis, and quantity Q1. The actual social cost is the area between lines S0 and S1, the 

price axis, and points A and C; it is smaller than the original cost estimate by triangle ABC. 

The market analysis represented in Figure 2-1 also highlights that profits should not be 

included in the IC multiplier. The RPE approach implicitly assumes disequilibrium in the 

market. Producer profits are calculated by assuming production at point B, even though 

consumers are not willing to pay P2 and buy Q1 vehicles. In reality, both price and quantity will 

change in response to the shift in costs. The impact on producer profits is determined by the 

slopes (elasticities) of the supply and demand curves. Producers and consumers typically share 

the burden of the compliance costs. Indeed, if profits were fully included in costs, then 

2-2 
producers would not be affected by regulations: their profits would be the same before and after 

the change. It is common, however, for a rule to affect profits; indeed, manufacturers often 

object to rules on this basis. 

In a long run model of a perfectly competitive industry, microeconomic theory predicts 

that full costs are passed along to consumers. The perfect competition model assumes that firms 

make zero economic profits (that is, profits including all opportunity costs) before the regulation; 

the increased costs associated with the regulation will make profits negative if they are not able 

to pass them along. This is similar to assuming that the supply curve is horizontal in the long run. 

As a result, firms will exit the industry, until quantity supplied equals quantity demanded at price 

P2, quantity Q3. In an imperfectly competitive industry, firms are predicted to have profits greater 

than zero. When imperfectly competitive firms face increased costs, they seek to mitigate losses 

in production by not passing along the full costs; the quantity will not fall as much as Q3, and the 

price will not rise as much as P2. Economists often, but not always, argue that the automotive 

industry is imperfectly competitive. 

Another factor that is difficult to predict in this setting is the effects of new technologies 

on consumer demand. Some changes may be invisible to consumers and will not affect their 

demand. Others, such as technologies that increase fuel economy with little other observable 

effect to the consumer, may increase demand. Finally, some technological changes may reduce 

demand, although automakers and regulators are not likely to pursue undesirable changes as long 

as more attractive alternatives exist. Any shifts in the demand curve due to new technologies 

should be included in regulatory impact analyses of new requirements. They should not, 

however, affect the estimate of indirect costs used to shift the supply curve. The RPE approach 

omits demand shifts as well as market adjustments due to the shifting supply curve. 

In conclusion, we believe that the RPE approach has problems because it 

 typically includes all categories of indirect costs, thus overstating the impact; 

 typically includes profits in the multiplier and thus cannot be used as a supply shift in 

a market analysis; 

 does not accurately project the change in market price or quantity or the total cost of 

the regulation, as a result of the first two bullets; and 

 does not provide a framework in which demand shifts can be analyzed. 

The IC multiplier is preferred because it models the appropriate shift in the supply curve 

(including direct manufacturing costs and relevant indirect costs) that then can be used in a 

2-3 
market analysis to determine a new equilibrium price and quantity, and hence the total cost of the 

regulation. A market analysis, pivoting on the new equilibrium generated from the IC multiplier 

approach, determines the distribution of regulatory burden between producers and consumers 

consistent with economic theory. 

2-4 
SECTION 3 

RPE MULTIPLIER ESTIMATION 

In this section, we identify and quantify the indirect cost components that constitute RPE 

multipliers for the automobile manufacturing industry. We present an overview of how Vyas et 

al.’s methodology was used to calculate RPE multipliers for individual manufacturers. We then 

calculate an average RPE multiplier for the automobile manufacturing industry using data from 

the annual reports of DaimlerChrysler, Ford, GM, Honda, Hyundai, Nissan, Toyota, and 

Volkswagen. 

3.1 Components of Indirect Costs 

We start our analysis by identifying components of indirect costs that EPA regulations 

could potentially affect. Table 3-1 presents the categories developed in Vyas et al.’s (2000) 

analysis2. The major categories among these are manufacturing costs,3 production overhead 

costs,4 corporate overhead costs,5 selling costs,6 and profit.7 Added together these categories 

contributed to an estimated RPE multiplier of 2.0 for internally sourced components. That value 

was estimated to be 1.5 for externally sourced components (Vyas, Santini, and Cuenca, 2000). 

Since Ford spun off parts supplier Visteon in 1997, and GM spun off parts supplier Delphi in 

1999, and since other manufacturers have independent parts suppliers (Denso for Toyota, Keihin 

for Honda, Bosch for Volkswagen, and Visteon for DaimlerChrysler, Nissan and Hyundai), we 

might expect the RPE multipliers for eight automobile manufacturers we estimate in this report 

to be close to 1.5 as a preliminary estimate. 

Using Vyas et al.’s methodology as a guideline, we partitioned the indirect cost 

components as shown in Table 3-2. The corporate overhead costs component was broken into 

general administrative, retirement, and health care. The selling costs component was broken into 

transportation and marketing. We also accounted for dealer costs of selling new vehicles, and 

2

 Vyas et al.’s report also presents the results of two studies performed by Chrysler and EEA, Inc. However, our 

study specifically utilized the methodology developed by Vyas et al. 3 Manufacturing costs refer to the total cost of making vehicles, consisting of direct production labor costs, direct 

materials costs, and other direct expenses. 4 Production overhead is defined as indirect costs that arise from manufacturing and producing vehicles (such as the 

warranty, R&D, and depreciation and amortization). 5 Corporate overhead costs refer to the costs of running a corporation, which include salaries of nonproduction 

workers, pensions, and health care expenses. 6 Selling costs include salaries of marketing staff, advertising cost, dealer advertising etc. 7 Profit (net profit) is defined as the difference between the total of all the manufacturers’ revenue and the total of all 

the manufacturers’ expenditures. 

3-1 
Table 3-1. RPE Multiplier Contributors in Vyas et al.’s Methodology 

Cost Category Cost Contributor 

Relative to Cost of 

Manufacturing 

Share of 

MSRP (%) 

Manufacturing Cost of manufacture 1.00 50.0 

Production overhead Warranty 0.10 5.0 

 R&D/engineering 0.13 6.5 

Depreciation and amortization 0.11 5.5 

Corporate overhead Corporate overhead, retirement and 

health care 

0.14 7.0 

Selling Transportation, marketing, dealer 

support, and dealer discount 

0.47 23.5 

Sum of costs 1.95 97.5 

Profit Profit 0.05 2.5 

Total contribution to MSRP 2.00 100.0 

Source: Vyas, A., D. Santini, and R. Cuenca. April 2000. “Comparison of Indirect Cost Multipliers for 

Manufacturing.” Center for Transportation Research, Energy Systems Division, Argonne National Laboratory. 

Table 3-2. RPE Multiplier Contributors in RTI’s Methodology 

Contributor 

Manufacturing 

Manufacturing cost 

Production Overhead 

Warranty 

R&D (product development) 

Depreciation and amortization 

Maintenance, repair, operations cost 

Corporate Overhead 

General and administrative (G&A) 

Retirement 

Health care 

Selling 

Transportation 

Marketing 

Dealer 

Dealer new vehicle net profit 

Dealer new vehicle selling expense 

Profit 

3-2 
dealer gross profits.8

 The increased level of disaggregation allowed for more flexibility when 

estimating the IC multipliers presented in Section 4. 

3.2 Company-Level Indirect Cost Components and RPE Multipliers 

Using automobile manufacturers’ annual reports, we developed values for each of the 

indirect cost categories for individual automobile manufacturers. The majority of the information 

was obtained from income statement tables in manufacturers’ annual reports. Appendix A 

presents detailed calculations of indirect cost components and RPE multipliers for individual 

manufacturers. Below we describe the limitations, assumptions, and adjustments for the data 

used in our analysis. 

3.2.1 Data Origin and Limitations 

The data for company-level RPE (and IC) multiplier analyses were gathered from 

publicly available annual reports. As a peer reviewer on this study, Glen Mercer, argues, 

although public availability is an advantage, these reports are accounting statements and may not 

relate directly to actual engineering costs. For example, depreciation is an accounting measure 

that might not correspond to actual wear and tear on the equipment. Additionally, annual reports 

might be biased toward corporate strategy rather than actual engineering realities. For example, a 

manufacturer might not raise the price of a vehicle by the full cost of a technology for marketing 

reasons. An alternative solution would be to request internal accounting information for various 

technology samples from each of the manufacturers, which would be slow, costly, and difficult. 

An argument can be made that some of these issues would wash out by averaging results across 

multiple manufacturers (Mercer, 2009). 

3.2.2 Data Assumptions and Adjustments 

In some instances, assumptions and adjustments were needed to make the cost data 

comparable across companies. Most of the manufacturers did not report direct manufacturing 

costs (cost of materials and labor used in manufacturing process). However, all manufacturers 

reported “cost of sales.” Investopedia, Forbes’s financial definitions Web site, defines cost of 

sales, which is often referred to as cost of goods sold (COGS), as “direct costs attributable to the 

production of the goods sold by a company, which includes the cost of the materials used in 

creating the good along with the direct labor costs used to produce the good.” Manufacturing 

cost excludes indirect expenses such as costs and sales force costs. However, Investopedia 

(2008) warns that the exact costs included in cost-of-sales calculations may differ from one 

8

 Another item we reported was “other expenses,,” which included interest expense, legacy costs and other 

miscellaneous expenses listed in annual reports as “other expenses.” This expense is NOT included in RPE 

multipliers, and was reported for completeness of the snapshot of manufacturers’ expenses. 

3-3 
business to another. Nevertheless, cost of sales was the best estimate of direct manufacturing 

costs reported by all companies. 

“Health care” and “retirement” costs provided in domestic manufacturers’ annual reports 

included expenditures for both manufacturing and corporate labor. The share of these costs 

related to manufacturing labor is a part of manufacturing expenses and, therefore, was added to 

the cost of manufacturing (i.e., to direct costs). The share related to corporate workers is a part of 

indirect costs and was added to the RPE multiplier. To determine how to attribute these shares, 

we looked at Ford’s and GM’s shares of manufacturing to production workers.9 This showed that 

approximately 70% of workers were involved in manufacturing, while 30% were corporate 

workers. Since the share of manufacturing to production workers was not evident from other 

manufacturers’ annual reports, a 70% to 30% share was used for all manufacturers. 

Health care and retirement costs could be attributed to “legacy” or “current” costs. 

Legacy costs apply to workers who have already retired. A change in direct manufacturing costs 

due to a new vehicle technology applied to comply with an environmental regulation would have 

no effect on these costs. In contrast, current costs cover existing employees. These costs might 

change if the number of corporate employees were to change as a result of regulation (note that 

any increase in manufacturing labor would result in higher health care and retirement costs for 

those workers but, for this analysis, those costs would be captured under direct manufacturing 

costs). Based on domestic manufacturers’ annual reports, we concluded that retirement costs 

included only current costs; therefore, all of these costs were included in the RPE multiplier. 

However, the reported health care costs appear to include both legacy and current costs. For 

example, for Ford Motor Company, the split was 45% legacy to 55% current. We used this share 

as a proxy for all domestic manufacturers and included only 55% of health care costs in the RPE 

multiplier calculations (as noted earlier, a regulatory change would have no effect on legacy 

costs). Since only a few foreign manufacturers reported actual health care costs, we applied a 

proxy of 0.03 of the cost of sales (30% of which were applicable as the corporate labor share) 

reported in the Sierra Research report (Sierra Research, 2007). It is worth noting that legacy 

costs are changing rapidly. For example, GM is gradually phasing out legacy costs. This and 

other forward-looking issues are discussed in Section 5. 

Manufacturers did not report maintenance, repair, and operations (MRO) costs. The 2003 

report from McKinsey was one source we identified for estimates of MRO costs (detailed 

9

 Ford Motor Company reported 64,000 hourly (73%) and 23,700 salaried workers (27%) (Ford, 2007, p. 12). 

General Motors reported expenditures for manufacturing labor of $27.9 billion (66%) and selling, general, 

administrative and other expenses of $14.4 billion (36%). 

3-4 
calculations of indirect cost contributors estimated using data from the McKinsey report are 

presented in Appendix B). However, McKinsey’s estimate of MRO (0.14) was not documented 

and likely included direct manufacturing costs (such as purchase of equipment, technician labor 

costs, etc.) that are covered in depreciation, amortization, and cost of sales in our methodology. 

The Sierra Research (2007) report estimated the historic value of MRO to the cost-ofsales ratio for Chrysler Company, which equaled 0.03. This value was used to reallocate costs to 

this category when a manufacturer did not provide estimates. In these cases, the value was 

subtracted from the cost of sales to redistribute existing costs instead of creating additional costs. 

Similarly, some manufacturers did not report health care costs. Since the McKinsey report did 

not provide an estimate of health care costs, we used the 0.03 estimate from the Sierra Research 

report to reallocate costs to health care. A detailed list of assumptions and sources for each 

manufacturer’s indirect cost contributors is presented in Appendix A. 

The only costs that were added (rather than redistributed from one of the indirect cost 

components) were dealer new vehicle net profit and dealer new vehicle selling expenses. These 

components are part of the final price of a vehicle but are not reported by automobile 

manufacturers. As discussed in Appendix Section A.2, we used the data from National 

Automotive Dealer Association (NADA) and estimated dealer new vehicle net profit to be 

0.004, and new vehicle selling expenses to be 0.06. 

3.2.3 Indirect Cost Components and RPE Multiplier Values 

Table 3-3 presents the values of indirect cost components and RPE multipliers for 

individual manufacturers in 2007. Production overhead (and its subcomponents) were the largest 

contributor to the RPE multiplier and stayed relatively consistent across all manufacturers, 

ranging from 13% to 22% of cost of sales. Selling and dealer contributing factors were the 

second largest contributors to the RPE multiplier, with values ranging from 0.12 to 0.18. 

Corporate overhead (primarily general and administrative cost) were a smaller contributor to 

indirect costs and had greater variance, ranging from 4% to 14% of cost of sales. Other expenses, 

which are not part of indirect costs but are reflected in RPE multipliers, also varied significantly 

across companies. 

Some corporations (e.g., Nissan and DaimlerChrysler) had lower corporate overhead 

costs but higher selling or production costs. The variance between companies can be explained 

by the differences in accounting definitions and practices. However, the sum of corporate 

overhead and selling costs tends to be comparable across the companies. Indirect production 

overhead costs tend to be inversely related to the sum of corporate and selling overhead. This 

3-5 
indicates that, although individual companies track and report indirect costs differently, 

aggregate indirect costs are similar. 

Toyota, Hyundai, and Ford had the lowest totals of indirect cost components, equaling 

38, 39 and 39 percent of cost of sales. Hyundai also had the lowest RPE multiplier at 1.42. Even 

though Toyota’s share of indirect costs with respect to cost of sales was lower than Hyundai’s, 

Toyota’s profit (0.09) surpassed Hyundai’s (0.03). Volkswagen had the second lowest RPE 

multiplier of 1.43. Among the American manufacturers, DaimlerChrysler had the highest RPE 

multiplier of 1.47, followed by GM and Ford with 1.45. 

To ensure that 2007 was not an outlier year, we looked at a 5-year historical analysis of 

indirect cost contributors for individual manufacturers. For all but one manufacturer 

(DaimlerChrysler), the sum of three major indirect cost contributing factors (selling, 

administrative, and other expenses; operating and other expenses; and depreciation) deviated in 

the range of 10 percentage points in the past 5 years (see Appendix A for a historical RPE 

analysis for individual manufacturers). Keeping in mind that averaging manufacturers’ costs 

would create an unbiased estimate, we concluded that 2007 RPE multipliers are unlikely to be 

underestimated. 

3-6 
Table 3-3. Individual Manufacturer and Industry Average RPE Multipliers: 2007 

Relative to Cost of Sales 

Industry Daimler 

RPE Multiplier Contributor Average Chrysler Ford GM Honda Hyundai Nissan Vehicle Manufacturing 

Cost of sales 1.00 1.00 1.00 1.00 1.00 1.00 1.00 

Production Overhead 

Warranty 0.03 0.04 0.03 0.03 0.01 0.02 0.03 R&D (product development) 0.05 0.04 0.02 0.06 0.07 0.04 0.06 Depreciation and amortization 0.07 0.11 0.05 0.06 0.05 0.06 0.09 Maintenance, repair, operations cost 0.03 0.03 0.03 0.03 0.03 0.03 0.03 Total production overhead 0.18 0.22 0.13 0.17 0.16 0.15 0.21 

Corporate Overhead 

General and administrative 0.07 0.05 0.12 0.07 0.11 0.08 0.03 Retirement < 0.01 0.01 0.00 0.01 < 0.01 < 0.01 < 0.01 Health 0.01 < 0.01 < 0.01 0.01 0.01 0.01 0.01 Total corporate overhead 0.08 0.06 0.13 0.08 0.14 0.09 0.04 

Selling 

Transportation 0.04 0.04 0.04 0.04 0.04 0.04 0.04 Marketing 0.04 0.02 0.04 0.05 0.03 0.05 0.08 

Dealers 

Dealer new vehicle net profit < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 Dealer new vehicle selling cost 0.06 0.06 0.06 0.06 0.06 0.06 0.06 Total selling and dealer contributors 0.14 0.12 0.14 0.14 0.13 0.15 0.18 

Sum of Indirect Costs 0.40 0.40 0.39 0.40 0.44 0.39 0.43 Net income 0.06 0.07 0.05 0.05 0.04 0.03 0.06 Other costs (not included as contributors) 0.04 0.04 0.11 0.06 0.02 0.01 0.01 RPE Multiplier 1.46 1.47 1.45 1.45 1.47 1.42 1.49 

3-7 
3.3 Industry Average Indirect Costs and RPEs 

To arrive at an RPE multiplier for the industry as a whole, we weighted each 

manufacturer’s RPE multiplier by their 200710 worldwide production. Table 3-4 presents 

individual company production alongside the RPE multipliers. The weighted average RPE 

multiplier for the automobile manufacturing industry equaled 1.46 in 2007. The 2007 production 

figures presented in Table 3-4 were also used in Table 3-3 to generate industry-weighted average 

individual cost components. 

Table 3-4. Weighted RPE Multiplier: 2007 

Annual Production (number of 

Company vehicles) (2007) RPE Multiplier 

DaimlerChrysler 4,635,601 1.47 

Ford 6,247,506 1.45 

GM 9,349,818 1.45 

Honda 3,911,814 1.47 

Hyundai 2,617,725 1.42 

Nissan 3,431,398 1.49 

Toyota 8,534,690 1.48 

VW 6,267,891 1.43 

Weighted Average 1.46 

Source: International Organization of Motor Vehicle Manufacturers (OICA). 2008. “World Motor Vehicle 

Production”. http://oica.net/wp-content/uploads/world-ranking-2007.pdf. 

10 DaimlerChrysler’s RPE multiplier was calculated for 2006 (the last year the company released an annual report); 

therefore, their RPE multiplier was weighted by 2006 revenue. 

3-8 
SECTION 4

INDIRECT COST MULTIPLIER ESTIMATION

This section outlines calculations of IC multipliers that reflect differences in technology 

complexity and changes in indirect costs over time as modifications to production are 

assimilated. The motivation is to model the diversity of potential cost impacts that may influence 

the design and production of automobiles under a wide range of potential future environmental 

regulations. 

In Section 3, we calculated an average RPE multiplier for the automobile manufacturing 

industry of approximately 1.46. This number includes markup for all indirect costs and profit. In 

this section, we focus solely on components of indirect costs that are likely to be impacted by 

future environmental regulations. We show that only a portion of the RPE multiplier should be 

used as a markup factor to account for the change in indirect costs from an environmental 

regulation. Because this factor reflects indirect costs only, it is referred to as an IC multiplier. 

Regulations that require implementing different levels of technology complexity are 

likely to impact indirect cost contributors with different magnitudes. Rather than assuming that a 

single multiplier is appropriate for all technologies, we consider the possibility that regulations 

with low technology complexity (such as simply replacing an existing technology) would have a 

lower IC multiplier than a regulation involving high technology complexity (such as requiring 

significant new integration efforts). In addition, the magnitude of impacts of different 

technologies is also likely to change over time as new technologies are assimilated: for instance, 

although such expenses as research are likely to be high in the short run, in the long run, the new 

technology may no longer require special research efforts. 

In this section, we describe the methodology used to calculate six automobile 

manufacturing industry IC multipliers, which capture technology differences associated with 

diverse EPA regulatory actions, as well as short- versus long-term impacts. Table 4-1 repeats the 

indirect cost contributors from Table 3-3, which are calculated as part of the industry average 

RPE multiplier. Table 4-1 excludes dealer and manufacturer profits for reasons discussed in 

Section 2. Our approach is to scale these values up or down depending on the complexity of the 

technology (which would be used by a manufacturer to meet new EPA regulations) and the time 

frame (short or long run). 

4-1 
Table 4-1. Weighted Average IC Multiplier Contributors to RPE: 2007 

Cost Contributor Light Car Industry Average 

Production Overhead 

Warranty 0.03 

R&D (product development) 0.05 

Depreciation and amortization 0.07 

Maintenance, repair, operations cost 0.03 

Total production overhead 0.18 

Corporate Overhead 

General and administrative 0.07 

Retirement 0.00 

Health care 0.01 

Total corporate overhead 0.08 

Selling 

Transportation 0.04 

Marketing 0.04 

Dealers 

Dealer new vehicle selling cost 0.06 

Total selling and dealer costs 0.14 

Sum of Indirect Costs 0.40 

Technology complexity is defined in our methodology by the scope of the innovation in 

the automaker’s products, product architectures, and processes induced by the technology. The 

more complex the technology associated with a regulation (low, medium, or high), the more 

indirect cost contributors that constitute the IC multiplier would be affected and to a greater 

degree. 

4.1 Technology Complexity and Innovation Scope 

Figure 4-1 provides a visual representation of the relationship between technology 

complexity and indirect costs. The flow of impacts from left to right in the figure starts with the 

technological complexity facing the automaker in meeting a new or revised EPA regulation. The 

broader the innovation scope, the greater the impact on the company’s operations (e.g., 

manufacturing or purchasing of materials). The nature of the impact on operations determines 

which indirect costs will change and by what amount. In the following sections, we clarify and 

describe each of the categories. 

4-2 
Technology 

Complexity 

Innovation 

Scope 

Impact on 

Operations 

Impact on 

Indirect Cost 

Contributors 

Figure 4-1. Impacts of Technology Complexity on IC Multiplier 

As mentioned above, technology complexity is defined by the innovation in the 

automaker’s products, product architectures, and processes induced by the technology. The 

framework to classify innovation was originally developed by Henderson and Clark (1990) and 

is based on the idea that successful product innovation requires two types of knowledge: 

knowledge about core design concepts of a product and knowledge about the architecture of the 

product or how components are integrated and linked together in a coherent whole. Following on 

Henderson and Clark, we identify four different innovation scopes, presented in Figure 4-2: 

incremental, modular, architectural, and differential. 

Core Concepts 

Linkages between Core Concepts and

Components 

Changed Unchanged 

Reinforced Overturned 

Incremental Modular 

Innovation Innovation 

Architectural Differential 

Innovation Innovation 

Figure 4-2. Definition of Innovation Processes 

Adapted from: Henderson, R.M., and K.B. Clark, 1990. “Architectural Innovation: The Reconfiguration of Existing 

Product Technologies and the Failure of Established Firms.” Administrative Science Quarterly 35(1):12. 

4-3 
Incremental innovation introduces only minor changes to an existing product, using an 

established design. The underlying core design concepts and the links between them remain the 

same. A low-complexity technology would fall within this scope. An example of such 

technology in the automotive industry is low rolling resistance tires because they simply replace 

existing tires and require no vehicle redesign or part-integration effort by the automaker. 

Modular innovation does not change the architecture of how the components interact 

with each other, but it changes the core concept of the technology. A medium-complexity 

technology would fall within this scope. 

Architectural innovation changes the way in which the product’s components are linked 

together without changing core design concepts. Again, a medium-complexity technology would 

fall within this scope. An example of such technology in the automotive industry is dual clutch 

transmission (DCT) because such transmissions simply replace an existing transmission but, 

unlike the case with low rolling resistance tires, would require some redesign and integration 

effort since the way that parts interact with each other would have to be changed. 

Differential innovation is based on different engineering and scientific principles; it 

establishes a new dominant design and, hence, a new set of core design concepts embodied in 

components that are linked together in a new architecture. A high-complexity technology falls 

within this scope. An example of such technology in the automotive industry is the hybrid 

electric vehicle because it represents an entirely new approach to propulsion relative to total 

reliance on an internal combustion engine. 

We classified these different kinds of innovation into different degrees of complexity of 

new technologies. Incremental innovation involves low complexity for new systems. Medium 

complexity is associated with either architectural innovation or modular innovation. Finally, 

differential innovation involves high complexity. Low, medium, and high complexities are the 

major categories that are used in the remainder of this section. 

4.2 Impacts of a New Technology on Automotive Manufacturers’ Operations 

Implementation of a new technology can affect company operations in several ways. An 

obvious impact would be on the direct costs of operation. Even something as simple as changing 

a bolt or screw would require a new part number in a parts database to ensure that the proper bolt 

is used in every appropriate instance. Such a change could also trigger requirement for validation 

and/or durability testing. For operations, we have considered three areas of indirect costs that are 

4-4 
likely to be affected by a change in a part or technology: R&D and retooling11 (through the 

change in R&D costs and production overhead), indirect labor costs (through increases in health 

care and retirement of corporate staff, corporate overhead, training of dealer mechanics to 

service new technologies, and dealer sales force to market new technologies), and indirect costs 

linked to materials used (due to warranty costs). 

Table 4-2 illustrates possible impacts on each of the three areas. A technology’s 

complexity determines to what degree that technology will impact company operations. The 

addition of a new low-complexity technology would likely require minimal investment in new 

tools and machinery (since existing tools can be used), and perhaps a minimal investment in 

R&D in order to validate the safety, compatibility and durability of the new component. No 

additional labor would be required, because current labor can be shifted easily to accommodate 

Table 4-2. Impact on Operations 

Technology 

Complexity 

Innovation 

Scope 

One-Time R&D and 

Retooling 

Corporate and Dealer 

Labor Materials 

Low Incremental Minimal No additional Purchase of new materials is 

innovation corporate labor needed required 

No labor training 

needed. No impact on 

corporate labor health 

care, retirement, 

corporate overhead 

Medium Modular Some R&D efforts are Minimal additional Purchase of new materials and 

innovation required corporate labor needed parts is required 

Architectural 

innovation 

Some investment in new 

tools is required 

Labor training is 

required. Minimal 

impact on corporate 

health care, retirement, 

corporate overhead. 

High Differential 

innovation 

Extensive R&D efforts 

are required 

Additional corporate 

labor needed 

Purchase of new materials, 

parts, and systems is required 

Extensive investment in Extensive labor 

new tools is required training is required. 

Substantial impact on 

corporate health care, 

retirement, corporate 

overhead 

11 Among the indirect cost contributors, retooling is captured in depreciation and amortization cost. 

4-5 
the implementation of such technology. The majority of the costs would be incurred to purchase 

new materials. 

In contrast, the addition of a new medium-complexity technology would likely require 

some R&D effort to redesign a core component or a product’s architecture such as replacing a 

larger 6-cylinder engine with a smaller turbo charged 4-cylinder engine. New machines and tools 

might need to be purchased to accommodate the production or assembly of redesigned parts. 

Minimal additional labor might be required, and some labor training may be necessary. 

Companies may need to purchase new materials and tooling to manufacture new designs. 

Finally, the addition of a new highly complex technology would likely require extensive 

R&D efforts and substantial investment in tools and machinery to design and build new core 

concepts and architecture. Additional labor would likely be needed, and extensive labor training 

would likely be required. Companies might need to purchase new materials, parts, tooling, and 

whole systems to support implementation of high-complexity technologies. 

4.3 Evaluating Indirect Cost Contributors 

As the above discussion argues, the indirect costs associated with new technologies are 

expected to differ based on the degree of complexity of the technology and the time frame 

involved. EPA’s National Vehicle and Fuel Emissions Laboratory assembled a team of engineers 

with experience working for auto manufacturers to provide adjustment factors for the 

contributions of indirect cost categories to the costs of new technologies. The team had among 

them 11 bachelor’s degrees in engineering and physics; 10 master’s degrees in engineering, 

atmospheric chemistry, and business; one Ph.D. in mechanical engineering; approximately 100 

years of experience working for auto and engine manufacturers and service companies; and 

expertise in a wide range of auto technologies, including (among others) engines, powertrains, 

onboard diagnostics, fuel economy, and emissions controls. The team met five times over a 

period of 3 weeks to discuss each indirect cost component and reach a consensus on the potential 

impact resulting from different regulatory scenarios. 

For low-, medium-, and high-complexity technologies, for both the short run and long 

run, the team of engineers reviewed the indirect costs required for new technologies. The 

baseline was the IC multiplier reported in Table 4-1. To provide context for the analysis, the 

team focused on three example technologies that are described in more detail in Sections 4.3.1, 

4.3.2, and 4.3.3: 

4-6 
 Low complexity: low rolling resistance tires 

 Medium complexity: dual clutch transmission 

 High complexity: hybrid electric vehicle 

For the low- and medium-complexity technologies, the team assumed that the development and 

manufacturing of these components is primarily purchased from suppliers. In contrast, the highcomplexity example assumes in-house development and manufacturing. Using these 

technologies, the team identified adjustment factors that capture the extent to which each indirect 

cost contributor would be affected by the new technology, both in the short run (approximately 

the first 4 to 5 years from putting the technology into use) and in the long run (after 5 years of 

use). The adjustment factors are presented Tables 4-3 (short run) and 4-4 (long run), along with 

the rationale for their magnitude. A value of 0 indicates that current expenditures on the 

component will not change as a result of the new technology. A value greater than 0 indicates 

that the new technology will add costs to that component. The additional costs of that 

component then are calculated as the additional cost of the technology multiplied by the indirect 

cost contributor for the given category multiplied by the adjustment factor. An adjustment factor 

of 1 indicates that the indirect cost contributor scales directly with the cost of the new 

technology. 

4.3.1 Low Complexity: Low Rolling Resistance Tires 

Low rolling resistance tires are designed to reduce the energy wasted as heat from the 

flexing of the tire during driving and by reducing the tires’ rolling resistance. The advances 

slightly change handling and braking but do not compromise the overall comfort of driving a 

vehicle (NRC, 2002). The Department of Energy recently estimated that, on average, this 

technology can reduce CO2 emissions by 3% for light-duty vehicles (DOE, 2008). 

Implementing this technology will require automobile manufacturers to purchase low 

rolling resistance tires. Implementing this technology does not require a change in core structure 

or redesign of architecture. The low rolling resistance tire is installed in place of a stock tire with 

a low degree of additional testing and development required. The development work may include 

some tuning and validation of stability control, ride and handling, and anti-lock brake systems; 

new vehicle coastdown tests; and recertification of fuel economy labels. This example assumes 

that there will not be significant modifications required in the chassis or suspension components. 

This technology is an example of a low-complexity technology. 

4-7 
4.3.2 Medium Complexity: Dual Clutch Transmissions 

DCTs were recently introduced into mass production (primarily by the Volkswagen-Audi 

group in Europe). This technology combines the high mechanical efficiency of a manual 

transmission with the shift control of an automatic transmission. The benefits of this technology 

are lower CO2 emissions and better fuel economy. Mechanically, DCT represents two 

transmission paths in parallel, each containing its own clutch. A change in gear is achieved by 

disengaging one clutch, while simultaneously engaging the other (Ricardo Inc., 2007). 

Table 4-3. Short-Term Effects on Indirect Cost Contributors 

Indirect Cost/Technology 

Complexity Low Medium High 

Production Overhead 

Warranty 1.2 1.6 2.0 

Warranty costs reflect the risk of failure and the cost of failure. In the short run, 

the expectation is that warranty costs will be higher for any new part or 

configuration, because of the manufacturers’ lack of market exposure of the item. 

Warranty, especially risk, is expected to be higher for higher levels of complexity. 

The low and medium complexity warranty costs are assumed to include some 

sharing of the costs between the manufacturer of the component and the vehicle 

manufacturer. 

R&D 0.2 1.1 2 

R&D is expected to increase with the complexity of the activity. For a lowcomplexity activity, the additional R&D associated with the incremental cost of 

the activity is expected to be less than the average R&D. For a mediumcomplexity activity, the additional R&D is expected to be slightly more than the 

average level. For high-complexity, much more R&D is necessary. 

Depreciation and 0 0 1 

amortization For low- and medium-complexity activities, no new technology is considered 

necessary at the vehicle manufacturer level; therefore, there is no increment for 

depreciation of new equipment. For high-complexity activities, the average level 

of new equipment is expected. 

Maintenance, repair, 0 0 1 

operations cost For low- and medium-complexity activities, there is no expected change in 

maintenance or other plant requirements because the new component or system 

replaces an existing one. For high-complexity activities, the average level of plant 

maintenance, repair, and operations is expected. 

Corporate Overhead 

G&A 0 0 0.5 

For low- and medium-complexity activities, there is no expected change in 

personnel in corporate offices. For high-complexity activities, a small increase in 

personnel, less than proportional to the increase in direct manufacturing cost, is 

expected. 

Retirement 0 0 0.5 

These values are expected to correspond to the values for G&A. 

4-8 
Table 4-3. Short-Term Effects on Indirect Cost Contributors (continued) 

Indirect Cost/Technology 

Complexity Low Medium High 

Corporate Overhead 

(continued) 

Health care 0 0 0.5 

These values are expected to correspond to the values for G&A. 

Selling 

Transportation 0 0 0.3 

This value represents the cost of transporting the new vehicle to the dealer. For 

low- and medium-complexity activities, there is not expected to be any increase in 

cost. For high-complexity activities, it is possible that additional costs may be 

associated with transporting the vehicle because of special requirements and 

increased value of the vehicle. 

Marketing 0 1 1.5 

The key factor that affects marketing is whether consumers notice the difference. 

For low-complexity activities, consumers are not expected to notice any change. 

For medium- and high-complexity activities, consumers are expected to need 

additional information, with a greater marketing effort for high-complexity 

activities than for medium. 

Dealer new vehicle selling 0.1 1 1.5 

cost Dealer new vehicle selling costs in part depend on the cost of the vehicle and in 

part depend on the amount of training for servicing the vehicles. These costs are 

expected to increase with the complexity of the vehicle. Low-complexity 

activities are expected to have very small additional costs, medium-complexity 

activities are expected to have an average weight for additional costs, and highcomplexity activities will have a weight greater than average. 

Table 4-4. Long-Term Effects on Indirect Cost Contributors 

Indirect Cost/Technology 

Complexity Low Medium High 

Production Overhead 

Warranty 0.6 0.8 1 

Warranty costs reflect the risk of failure and the cost of failure. In the long run, 

the expectation is that warranty costs will be directly proportional to direct costs 

of a product for high-complexity technologies, as manufacturers work to reduce 

the failure rate for all products. For low- and medium-complexity technologies, 

the risk and cost of failure are expected to fall more than those of highcomplexity technologies. 

4-9 
Table 4-4. Long-Term Effects on Indirect Cost Contributors 

Indirect Cost/Technology 

Complexity Low Medium High 

Production Overhead 

R&D 0 0 0.3 

Almost all R&D is expected to be done (by definition) in the short run. Any 

remaining R&D, except for high-complexity activities, is expected to be no 

different than the R&D that would have taken place in the absence of the 

regulatory action. In the case of a high-complexity activity, some additional R&D 

is expected even in the long run. 

Depreciation and 0 0 1 

amortization 

For low- and medium-complexity activities, no new technology is considered 

necessary; therefore, there is no increment for depreciation of new equipment. For 

high-complexity activities, the average level of new equipment is expected. 

Maintenance, repair, 0 0 1 

operations cost For low- and medium-complexity activities, there is no expected change in

maintenance or other plant requirements. For high-complexity activities, the 

average level of plant maintenance, repair, and operations is expected. 

Corporate Overhead 

G&A 0 0 0.5 

For low- and medium-complexity activities, there is no expected change in 

personnel in corporate offices. For high-complexity activities, a small increase in 

personnel is expected. 

Retirement 0 0 0.5 

These values are expected to correspond to the values for G&A. 

Health care 0 0 0.5 

These values are expected to correspond to the values for G&A. 

Selling 

Transportation 0 0 0.3 

This value represents the cost of transporting the new vehicle to the dealer. For 

low- and medium-complexity activities, there is not expected to be any increase in 

cost. For high-complexity activities, it is possible that additional costs may be 

associated with transporting the vehicle because of special requirements and 

increased value of the vehicle. 

Marketing 0 0 0 

In the long run, consumers are expected to have adapted to any changes, and no 

additional incremental increase in marketing is expected. 

Dealer new vehicle selling 0 0.3 1 

cost Dealer new vehicle selling cost in part depend on the cost of the vehicle and in 

part depend on the amount of training for servicing the vehicles. These costs are 

expected to increase with the complexity of the vehicle. In the long run, lowcomplexity activities are expected to have no additional costs, mediumcomplexity activities are expected to have small additional costs, and highcomplexity activities will have an average value for dealer support. 

4-10 
This example assumes that implementation of this technology in mass production 

requires the vehicle manufacturer to integrate the purchased transmission with the other vehicle 

systems, such as the engine. However, the core task of the transmission—to provide stepped gear 

ratios to maximize vehicle performance and efficiency—remains. This work is completed by the 

supplier, with the associated costs included in the direct cost. This technology is an example of a 

medium-complexity technology. 

4.3.3 High Complexity: Hybrid Electric Vehicle 

Hybrid electric vehicles are in various stages of development by almost all major lightduty car manufacturers. Among the popular hybrid cars being developed are “mild hybrids,” 

with regenerative breaking, integrated starter generator (ISG), launch assist, and minimal battery 

storage. There are two basic types of driveline structure found in hybrid vehicles. The most 

common, parallel hybrid, is where the engine drives the powertrain and a generator helps 

recharge the battery. A second type, a series hybrid, is where the engine does not drive the 

powertrain but always drives the motor/generator to move the vehicle and recharge the battery. 

Reductions in carbon dioxide emissions vary between 15% and 30% (Ricardo Inc., 2007). 

Production of a hybrid vehicle would require automobile manufacturers not only to 

redesign the car’s physical and electronic architecture to accommodate the additional electric 

drive components, but also redesign the core structure of the main driveline components, 

including the transmission, engine, and other elements of the propulsion system. This technology 

is an example of a high-complexity technology. 

4.4 Calculating IC Multipliers 

The adjustment factors in Tables 4-3 and 4-4 are then multiplied by the industry weighted 

average indirect cost contributors to RPE presented in Table 4-1. The adjusted indirect cost 

contributors are then summed to calculate IC multipliers. These calculations are presented in 

Table 4-5. Adjustment factors are in effect scaling up or down the magnitude of the impact of 

specific indirect cost categories based on technology complexity. The time frame adds another 

dimension to our study. In the short run, indirect costs are likely to be higher, depending on the 

complexity of the technology, because of such factors as increased R&D, training of workers and 

dealers. However, R&D, investment in tools and machinery, and training represent one-time 

fixed costs. Thus, we expect to see higher indirect costs initially and lower impacts in the long 

run as companies assimilate the new technologies. Table 4-5 presents the final IC multipliers for 

the different levels of complexity and time frames. 

4-11 
4.5 Summary 

IC multipliers are calculated to range from 1.05 to 1.45 in the short run and from 1.02 to 

1.26 in the long run. The differences between the short- and long-run IC multipliers are primarily 

due to R&D and warranty costs, which are projected to decrease over time. R&D expenditures 

also vary greatly over the level of technology complexity, as does the need for dealer support. 

To use the multipliers presented in Table 4-5, analysts can start by assessing the degree of 

complexity of the new technology under consideration. That identification process will lead to 

the short-run and long-run multipliers for the new technology. If an analyst has additional 

information about the role of indirect cost contributors for the new technology, that information 

can be used to develop different adjustment factors than those in Tables 4-3 and 4-4. This will 

then lead to the calculation of project-specific adjustment factors that can be substituted for those 

in Table 4-5. 

4-12 
4-13

Table 4-5. Short- and long-Term IC Multiplier Calculations 

RPE 

Multiplier 

Approach IC Multiplier Approach 

 Short -Term Effects Long-T

Low Technology 

Complexity 

Medium 

Technology 

Complexity 

High Technology 

Complexity 

Low Technology 

Complexity 

M

Tec

Com

RPE and IC Multiplier 

Contributors 

Weighted 

Average 

Industry 

Indirect Cost 

Contributors 

to RPE 

Adjustment 

Factor 

IC 

Multiplier 

Adjustment 

Factor 

IC 

Multiplier 

Adjustment 

Factor 

IC 

Multiplier 

Adjustment 

Factor 

IC 

Multiplier 

Adjus

ment 

Facto

Manufacturing 

Cost of sales 1.00 1.00 1.00 1.00 1.00 Production overhead Warranty 0.03 1.20 0.04 1.60 0.05 2.00 0.06 0.60 0.02 0.80 R&D (product development) 0.05 0.20 0.01 1.10 0.06 2.00 0.10 0.00 0.00 0.00 Depreciation and amortization 0.07 0.00 0.00 0.00 0.00 1.00 0.07 0.00 0.00 0.00 Maintenance, repair, operations 

cost 

0.03 0.00 0.00 0.00 0.00 1.00 0.03 0.00 0.00 0.00 

Total production overhead 0.18 0.04 0.10 0.26 0.02 

Corporate Overhead 

General and administrative 0.07 0.00 0.00 0.00 0.00 0.50 0.03 0.00 0.00 0.00 Retirement 0.00 0.00 0.00 0.00 0.00 0.50 <0.01 0.00 0.00 0.00 Health 0.01 0.00 0.00 0.00 0.00 0.50 <0.01 0.00 0.00 1.00 Total corporate overhead 0.08 0.00 0.00 0.04 0.00 

Selling 

Transportation 0.04 0.00 0.00 0.00 0.00 0.30 0.01 0.00 0.00 0.00 Marketing 0.04 0.00 0.00 1.00 0.04 1.50 0.05 0.00 0.00 0.00 

Dealers 

Dealer net profit <0.01 Dealer new vehicle selling cost 0.06 0.10 0.01 1.00 0.06 1.50 0.08 0.00 0.00 0.30 Total selling and dealer contributors 0.14 0.01 0.09 0.15 0.00 

Sum of Indirect Costs 0.40 0.05 0.20 0.45 0.02 

Net income 0.06 Other costs (not included in 

contributing costs) 

0.04 

Total contribution to cost of sales 1.46 1.05 1.20 1.45 1.02 
SECTION 5

CONCLUSION 

The RPE multiplier approach has been used as a method to estimate the change in 

indirect costs which are included in the total cost of a regulation. This approach has typically 

included using all indirect cost categories and profits to develop a multiplier that is then applied 

to the estimated direct manufacturing costs. Regulatory agencies, including EPA, have used RPE 

multipliers to scale the direct manufacturing costs associated with a regulation when estimating 

the total social cost of the regulation. However, a key problem in using RPE multipliers in 

regulatory analysis is that some of the indirect cost components of the RPE multiplier, such as 

fixed depreciation costs, health care costs for retired workers, or pensions, may not be affected 

by all vehicle modifications resulting from regulation. 

This report develops a modified multiplier, referred to as an IC multiplier, which 

specifically evaluates the components of indirect costs that are likely to be affected by vehicle 

modifications associated with environmental regulation. A range of IC multipliers are developed 

that 1) account for differences in the technical complexity of required vehicle modifications and 

2) adjust over time as new technologies become assimilated into the automotive supply chain. 

The IC multiplier is preferred because it models the appropriate shift in the supply curve 

(including direct manufacturing costs and relevant indirect costs) that then can be used in a 

market analysis to determine a new equilibrium price and quantity, and hence the total cost of the 

regulation. The new equilibrium generated from the IC multiplier approach and the market 

analysis determines the distribution of regulatory burden between producers and consumers 

consistent with economic theory. 

5.1 Applicability of the RPE and IC Multipliers in Future Years 

The results of this analysis suggest that each manufacturer’s RPE multiplier has been 

fairly consistent from 2002 to 2007 (2002 to 2006 for DaimlerChrysler). Further, the adjustments 

to develop the IC multipliers were based on engineering judgment of the effects of new 

technologies. While the technologies to which they will be applied might be very different in the 

future, there is unlikely to be a structural reason over time for the adjustment factors to change. 

These factors suggest that the multipliers developed here will continue to be appropriate in the 

future. 

On the other hand, the economic recession that began in 2008 had a strong effect on 

automobile sales and, especially for the United States automakers, the industry’s access to the 

5-1 
capital it needs to operate. As a result, the domestic manufacturers have stated that they intend to 

undergo significant restructuring in coming years to increase their productivity. This 

restructuring could affect the ratio of indirect costs to direct manufacturing costs that forms the 

basis for the RPE and IC multipliers. 

The domestic auto manufacturers have proposed plans to improve their financial 

viability. 12 All three companies are in the process of downsizing both their manufacturing and 

their white-collar workforce; they also are reducing their physical plants and changing their 

investment strategies. The magnitude of these changes may be sufficient to alter the RPE 

calculated here. Whether the multiplier for each manufacturer is likely to increase or decrease in 

response to the restructuring depends on the relative changes that will take place in the indirect 

and direct manufacturing cost categories. 

Direct manufacturing costs consist of direct production labor costs, direct materials costs, 

and other direct expenses. Direct materials costs and other direct expenses are not discussed in 

the restructuring plans. A change in materials costs could result from a major change in vehicle 

design. They might increase if vehicles use more expensive inputs; they might decrease because 

of using less expensive inputs or the increased emphasis on smaller vehicles that the plans imply. 

Direct labor costs are on a trajectory to decrease because of the new 2007 contract that each 

company negotiated with the United Auto Workers. Thus, it is likely but not certain that direct 

manufacturing costs will decrease because of restructuring. 

Indirect cost categories include production overhead (including warranty, R&D, 

depreciation and amortization, and MRO cost), corporate overhead (including general and 

administrative, retirement, and health care), and selling (including transportation, marketing, 

dealer support, discounts, and markup). The restructuring plans all imply major reductions in 

these categories. Each producer is closing plants and has reduced salaried labor costs. In 

addition, each plans to coordinate more across international divisions to achieve greater 

economies of scale in design and production. Warranty costs are expected to continue to 

decrease; health care and retirement costs are becoming more contained over time, and they are 

closing a number of dealerships. While the reports all discuss new technologies that the 

automakers plan to develop, it is not clear whether these R&D expenditures involve increases in 

that account. The plans all imply that the sum of these costs is likely to go down significantly. 

12 Robert Nardelli, “Chrysler’s Plan for Short-Term and Long-Term Viability,” United States House Committee on 

Financial Services, December 2, 2008; “Ford Motor Company Business Plan Submitted to the House Financial 

Services Committee,” December 2, 2008; General Motors Corporation, “Restructuring Plan for Long-Term 

Viability: Submitted to Senate Banking Committee & House of Representatives Financial Services Committee,” 

December 2, 2008; all found at http://financialservices.house.gov/autostabilization.html. 

5-2 
How the multiplier is affected by industry restructuring depends on whether the indirect 

costs go down more quickly or less quickly than the direct manufacturing costs. Much of the 

restructuring implies large reductions in indirect costs, through plant and dealership closures, 

reductions in salaried employees and warranty costs, and greater coordination across 

international divisions. These changes will reduce the RPE multiplier. The revised UAW 

contract, on the other hand, will reduce direct manufacturing costs and thus increase the RPE 

multiplier. The net effect of these changes on the RPE multiplier is difficult to predict. 

The foreign automakers do not appear to be under the same pressures to restructure that 

the U.S. automakers appear to face. Their RPE multipliers are not very different from the U.S. 

companies’ RPE multipliers. As Table 3-3 shows, Nissan has the highest RPE multiplier in 2007, 

while Hyundai had the lowest, with RPE multipliers for U.S. producers between them. If the 

U.S. restructuring leads them to have cost structures similar to those of foreign automakers, their 

RPE multipliers may not change greatly from the current values. 

For low- and medium-complexity changes, the adjustment factors are such that a change 

in the RPE multiplier is not likely to have very much effect on the relevant IC multiplier. A 

change in the RPE multiplier will have a larger effect on the IC multiplier for high-complexity 

technologies. 

In sum, while the RPE multiplier is likely to change because of domestic auto industry 

restructuring, the direction of the change cannot be predicted at this time. The fact that foreign 

automakers have similar RPE multipliers and do not appear to face the same restructuring 

pressures suggests that the RPE multipliers may not in fact change greatly. The adjustment 

factors developed in Section 4.3 are unlikely to need modification in the future. For these 

reasons, using the IC multipliers in Table 4-5 is likely to be reasonable. It may nevertheless be 

worthwhile to re-evaluate the RPE multipliers periodically to examine the effect of changes in 

industry structure. 

5-3 
REFERENCES 

DaimlerChrysler AG. 2005. DaimlerChrysler: Annual Report 2003. Available at: 

http://www.daimler.com/dccom/0-5-660593-1-169901-1-0-0-0-0-0-12591-7164-0-0-0-0-

0-0-0.html. Accessed on November 14, 2008. 

DaimlerChrysler AG. 2007. DaimlerChrysler: Annual Report 2006. Available at: 

http://www.daimlerchrysler.com/Projects/c2c/channel/documents/1003905_DCX_2006_ 

Annual_Report.pdf. Accessed on November 14, 2008. 

Department of Energy. 2008. Alternative and Advanced Vehicles: Low Rolling Resistance Tires. 

Available at: http://www.afdc.energy.gov/afdc/vehicles/fuel_economy_tires_light.html. 

Washington, DC: Department of Energy. 

Executive Order 12866. October 4, 1993. “Regulatory Planning and Review,” Federal Register 

vol. 58 no. 190. Available at: http://www.archives.gov/federal-register/executiveorders/pdf/12866.pdf. Accessed on February 17, 2009. 

Ford Motor Company. 2006. Ford Company: 2005 Annual Report. Available at: 

http://www.ford.com/microsites/annual-reports. Accessed on September 20, 2008. 

Ford Motor Company. 2007. Ford Company: 2007 Annual Report. Available at: 

http://www.ford.com/microsites/annual-reports. Accessed on September 20, 2008. 

Ford Motor Company. 2007a. 10-K Annual Report 2007. Available via EDGAR database from: 

http://sec.gov/edgar. Accessed on September 20, 2008. 

General Motors Corporation. 2005. 2005 Annual Report. Available at: 

http://www.gm.com/corporate/investor_information/docs/fin_data/gm05ar/index.html. 

Accessed on August 20, 2008. 

General Motors Corporation. 2007. 2007 Annual Report. Available at: 

http://www.gm.com/corporate/investor_information/docs/fin_data/gm07ar/index.html. 

Accessed on August 20, 2008. 

Henderson, R.M., and K.B. Clark, 1990. “Architectural Innovation: The Reconfiguration of 

Existing Product Technologies and the Failure of Established Firms.” Administrative 

Science Quarterly 35(1):12. 

Honda Motor Company. 2006. Annual Report 2005. Available at: 

http://world.honda.com/investors/annualreport/2005/. Accessed on September 20, 2008. 

Honda Motor Company. 2008. Annual Report 2008. Available at: 

http://world.honda.com/investors/annualreport/2008/. Accessed on September 20, 2008. 

Hyundai Motor Company. 2006. Annual Report 2005. Available at: http://csr.hyundaimotor.com/download/Annual_Report_2005.pdf. Accessed on October 10, 2008. 

R-1 
Hyundai Motor Company. 2008. Annual Report 2007. Available at: http://csr.hyundaimotor.com/download/Annual_Report_2007.pdf. Accessed on October 10, 2008. 

International Organization of Motor Vehicle Manufacturers (OICA). 2008. “World Motor 

Vehicle Production.” Available at: http://oica.net/wp-content/uploads/world-ranking2007.pdf. 

Investopedia. 2008. Cost of Goods Sold—COGS. Available at: http://www.investopedia.com/ 

terms/c/cogs.asp>. Forbes Corp. Accessed on October 12, 2008. 

Jack Faucett Associates. September 4, 1985. “Update of EPA’s Motor Vehicle Emission Control 

Equipment Retail Price Equivalent (RPE) Calculation Formula.” 

McKinsey & Company. October 2003. Preface to the Auto Sector Cases. In New Horizons: 

Multinational Company Investment in Developing Economies. San Francisco, CA. 

Mercer, Glen. 2009. Review of the Estimating Indirect Cost Multipliers for Individual Domestic 

and Foreign Automobile Manufacturers. Comments submitted under contract to EPA. 

National Automobile Dealers Association (NADA). 2008. 2007 NADA DATA Report. Available 

at: http://www.nada.org/Publications/NADADATA/2007/default.htm. Accessed on 

January 20, 2009. 

National Research Council. 2002. Technologies for Improving the Fuel Economy of Passenger 

Cars and Light-Duty Trucks. Available at: http://books.nap.edu/openbook.php? 

isbn=0309076013. Washington, DC: National Research Council. Accessed on December 

8, 2008. 

Nissan Motor Company. 2006. Annual Report 2004–2005. Available at: http://www.nissanglobal.com/EN/IR/LIBRARY/AR/. Accessed on October 10, 2008. 

Nissan Motor Company. 2008. Annual Report 2006–2007. Available at: http://www.nissanglobal.com/EN/IR/LIBRARY/AR/. Accessed on October 10, 2008. 

Office of Management and Budget. 2003. Circular A-4: Regulatory Analysis. Available at: 

http://www.whitehouse.gov/omb/circulars/a004/a-4.aspx. Accessed on February 17, 

2009. 

Ricardo, Inc. June 2008. “A Study of Potential Effectiveness of Carbon Dioxide Reducing 

Vehicle Technologies, Revised Final Report.” EPA420-R-08-004a. Available at 

http://www.epa.gov/oms/technology/420r08004a.pdf. Accessed on February 17, 2009. 

Sierra Research, Inc. November 21, 2007. “Study of Industry—Average Mark-Up Factors Used 

to Estimate Changes in Retail Price Equivalent (RPE) for Automotive Fuel Economy and 

Emissions Control Systems.” 

Toyota Motor Company. 2006. Annual Report 2006. Available at: 

http://www.toyota.co.jp/en/ir/library/annual/index.html. Accessed on October 10, 2008. 

R-2 
Toyota Motor Company. 2008. Annual Report 2008. Available at: 

http://www.toyota.co.jp/en/ir/library/annual/index.html. Accessed on October 10, 2008. 

Volkswagen Group AG. 2004. Annual Report 2003. Available at: 

http://www.vwfsag.de/fsag/ucus/vwfsag/en/investor_relations/annual_report/ 

archive_2003.htx. Accessed on October 10, 2008. 

Volkswagen Group AG. 2008. Annual Report 2007. Available at: 

http://www.volkswagenag.com/vwag/gb2007/content/en/annual_report_2007.html. 

Accessed on October 10, 2008. 

Vyas, A., D. Santini, and R. Cuenca. April 2000. “Comparison of Indirect Cost Multipliers for 

Manufacturing.” Center for Transportation Research, Energy Systems Division, Argonne 

National Laboratory. 

U.S. Environmental Protection Agency. 2000. Guidelines for Preparing Economic Analyses. 

EPA 240-R-00-003. Available at: 

http://yosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html. Accessed on February 

17, 2009. 

R-3 
APPENDIX A 

CALCULATION OF RPE MULTIPLIERS FOR INDIVIDUAL MANUFACTURERS 

This appendix describes calculations of RPE multipliers for the automobile 

manufacturing industry and for individual automobile manufacturers. The section is structured 

in the following manner: 

 Appendix A.1: Automobile Industry (McKinsey) 

 Appendix A.2: Dealer Cost and Profit Calculation 

 Appendix A.3: General Motors 

 Appendix A.4: DaimlerChrysler AG 

 Appendix A.5: Ford Motor Company 

 Appendix A.6: Honda Motor Company 

 Appendix A.7: Hyundai Motor Company 

 Appendix A.8: Nissan Motor Company 

 Appendix A.9: Toyota Motor Company 

 Appendix A.10: Volkswagen Group 

A.1 Automobile Industry (McKinsey) 

A white paper developed by McKinsey & Company (2003) described an analysis of 

costs (in dollars per vehicle) observed by original equipment manufacturers (OEMs) and their 

contribution to the manufacturer’s suggested retail price (MSRP). The analysis was based on 

data provided by Roland Berger Consultants, Deutsche Bank, and McKinsey. These costs are 

presented in Table A-1. 

Using cost categories and profit reported in the McKinsey study, we developed an RPE 

multiplier. In Table A-2, costs of materials (both raw and purchased parts) and manufacturing 

costs are combined to comprise the “cost of manufacturing” category (these costs are listed 

separately in Table A-1). G&A costs were counted as part of corporate overhead. 

Transportation costs and dealer discount were counted in selling costs. As Table A-2 indicates, 

the RPE multiplier was 1.70. 

A-1 
Table A-1. McKinsey’s Automobile Industry Manufacturers’ Cost Contributions to 

MSRP 

Cost Contributor Average Amount Per Vehicle ($) Percent Share 

Material cost (purchased parts) 10,030 41.6% 

Material cost (raw materials) 1,770 7.3% 

Manufacturing cost 2,400 10.0% 

Maintenance, repair, operations cost 2,000 8.3% 

Product development 1,600 6.6% 

Transportation 500 2.1% 

Sales & marketing 1,200 5.0% 

Depreciation and Interest 1,150 4.8% 

Warranty costs 600 2.5% 

General & administrative 500 2.1% 

Net profit 750 3.1% 

Wholesale price to dealer 22,500 93.4% 

Dealer gross 1,600 6.6% 

MSRP 24,100 100.0% 

Source: McKinsey & Company. 2003. Preface to the Auto Sector Cases. 

Table A-2. Automobile Manufacturing Industry RPE Multiplier (based on McKinsey’s 

Data) 

Relative to Cost of Share of RPE 

RPE Multiplier Contributor Manufacturing Multiplier 

Manufacturing 

Manufacturing cost 1.00 0.59 

Production Overhead 

Warranty 0.04 0.03 

R&D (product development) 0.11 0.07 

Depreciation and amortization 0.08 0.05 

Maintenance, repair, operations cost 0.14 0.08 

Total production overhead 0.38 0.22 

Corporate Overhead 

Corporate overhead, retirement and health 0.04 0.02 

Selling 

Transportation, marketing, dealer support, dealer discount 0.23 0.14 

Sum of Indirect Costs 0.64 0.38 

Profit 0.05 0.03 

RPE Multiplier 1.70 1.00 

A-2 
A.2 Dealer Cost and Profit Calculation 

This section describes a calculation of dealer net profit and new vehicle selling cost as 

a share of manufacturers’ cost of sales. Car dealerships in the United States primarily engage 

in three types activities: new vehicle sales, used vehicle sales, and service and parts sales. For 

automobile industry RPE and IC multipliers, we are only concerned with profit and cost of 

new vehicle sales, because only these profits and costs will affect new vehicle retail price. 

Sales of used cars are not directly related to manufacturers, and service and parts operations 

are covered under warranties and otherwise paid for by consumers and not by manufacturers. 

We find that the industry average dealer net profit margin on new vehicle sales as a 

share of manufacturers’ cost of sales was 0.004, and the industry average new vehicle selling 

costs as a share of manufacturers’ cost of sales was 0.06. We will describe calculation steps 

below. 

Table A-3 lists dealer gross profit margin on new vehicle sales, which were obtained 

from J.D. Power and Associates. 

Table A-3. Dealer Gross Profit Margin on New-Vehicle Sales 

Year Dealer Gross Profit Margin 

2003 0.044 

2004 0.041 

2005 0.039 

2006 0.038 

2007 0.034 

Average 0.039 

Source: Estimates of annual U.S. dealer gross profit margins on new vehicle sales based on Walter McManus’ direct 

communication with J.D. Power and Associates 

The National Automotive Dealer Association (NADA) books provide detailed 

information on sales and profits, including new vehicle sales, and new vehicle net profits 

(NADA, 2008). Using new vehicle sales (NADA, 2008) and dealer gross profit margin on new 

vehicle sales (from J.D. Power and Associates) we calculated gross profit (the difference 

between total sales and vehicle costs) on new vehicle sales (row C in Table A-4). We then 

obtained new vehicle selling costs (row E in Table A-4) by subtracting net profits on new 

vehicle sales (NADA, 2008) from gross profit on new vehicle sales. Finally, we calculated 

ratios of net profit and selling expenditures on new vehicle sales to new vehicle sales. To 

A-3 
normalize these ratios we performed this calculation by first averaging new vehicle sales, net 

profits, and selling expenses and calculating the ratios then. The values of these ratios were: 

Dealer new vehicle net profit =0.003 

New vehicle sales 

Dealer new vehicle selling cost =0.04 

New vehicle sales 

The low ratio of net profits on new vehicle sales to new vehicle sales makes sense. The 

surge in dealers' net profits from new vehicles in 2001-2005 is largely the result of the rapid 

deflation of new vehicle prices (through cash and interest rate incentives) by automakers. The 

automakers doubled consumer incentives each year from 2002 through 2004 (and a smaller 

increase in 2005). 

Table A-4. Average U.S. Dealership Net Profit and Selling Expenses on New Vehicle 

Sales, 2003–2007 

R Average Dealership Financials ($ Thousand) 

o 

w Source / 

2003 2004 2005 2006 2007 Calculation 

A New vehicle sales 19,359 20,116 19,469 18,795 19,545 NADA 

B New vehicle gross profit margin 0.044 0.041 0.039 0.038 0.034 J.D. Power 

C New vehicle gross profit 848 818 768 714 672 A * B 

D New vehicle net profit 147 141 44 -25 -41 NADA 

E New vehicle selling cost 701 677 724 739 713 C - D 

Source: NADA, 2008. 

We then calculate a share of dealer net profit and selling cost on new vehicle sales as a 

share of the automobile manufacturers’ cost of sales (this will allow us to include these costs 

as cost contributors to the RPE and IC multiplier calculations). We started with individual 

manufacturers’ annual sales (row B in Table A-5) and calculated new vehicle sales (row D in 

Table A-5) by adding average13 dealer gross profit (row C in Table A-5) from Table A-3. This 

new vehicle sales value is comparable to dealer new vehicle sales value from Table A-4. We 

then calculate the ratios of new vehicle sales to manufacturers’ cost of sales (row E in Table 

A-5). 

13 5-year arithmetic average was used to normalize the value of dealer gross profit margin 

A-4 
We then multiplied the ratios in row E in Table A-5 by the ratios in rows F and G in 

Table A-4 to arrive at dealer’s net profit and selling expense on new vehicles: 

Dealer new vehicle net profit New vehicle sales Dealer new vehicle net profit x = New vehicle sales Manufacturer's cost of sales Manufacturer's cost of sales 

Dealer new vehicle selling cost New vehicle sales Dealer new vehicle selling cost 

x = New vehicle sales Manufacturer's cost of sales Manufacturer's cost of sales 

Finally, we weighted these values by individual manufacturers’ annual production (row H in 

Table A-5) to arrive at industry averages. As Table A-5 shows, dealer new vehicle net profit as 

a share of cost of sales equaled 0.004, and new vehicle selling cost as a share of cost of sales 

equaled 0.06. Thus, the value of these cost contributors would be 0.004 and 0.06 respectively. 

A-5 
Table A-5. Dealer Net Profit and Selling Expenses on New Vehicle Sales as a Share of Manufacturers’ Co

A-6 

R 

o 

w 

Calculation of Dealer Profit 

and Dealer Expense 

Daimler 

Chrysler1 Ford GM Honda Hyundai Nissan Toyota 

A Cost of sales 2007 ($ Billion) 

$124.7 $130.4 $143.0 $65.4 $53.5 $67.0 $150.2 

B Annual sales 2007 ($ Billion) 

$190.3 $154.0 $178.2 $93.9 $74.2 $88.7 $262.4 

C Dealer new vehicle gross margin 

3.9% 3.9% 3.9% 3.9% 3.9% 3.9% 3.9% 

D New vehicle sales ($ Billion) $197.7 $160.0 $185.1 $97.6 $77.1 $92.2 $272.6 E New vehicle sales / Cost of sales 1.59 1.23 1.29 1.49 1.44 1.38 1.82 

Line items for RPE multiplier 

F Dealer new vehicle net profit 0.004 0.003 0.003 0.004 0.004 0.004 0.005 G Dealer new vehicle selling cost 0.06 0.04 0.05 0.05 0.05 0.05 0.07 H Annual production 2007 4,635,601 6,247,506 9,349,818 3,911,814 2,617,725 3,431,398 8,534,690 

1 2006 Sales and production data was used for Daimler Chrysler. 
A.3 General Motors Corporation 

Cost information presented in GM’s annual report did not always match cost contributors 

useful to our analysis. We performed several calculations to adjust costs presented in GM’s 

annual report so they can be applied to our methodology. GM’s annual report did not clearly 

state manufacturing labor costs and material costs. However, it did provide “material cost, freight 

and policy, warranty” and “manufacturing labor, pensions and postretirement benefits, 

engineering expense and marketing related costs” categories. Thus, manufacturing costs were 

calculated as follows: 

Manufacturing labor cost = Manufacturing labor, pensions and postretirement benefits, 

engineering expense and marketing related costs – Pensions – Postretirement Employee Benefits 

– Advertising – Dealer Advertising – R&D 

Material cost = Material cost, freight, warranty and policy – Warranty and policy – Freight 

(was not readily available, so we used 2.07% McKinsey Industry Average) 

Calculated Manufacturing Costs = Manufacturing labor costs + Material cost 

Since no information on the MRO cost category could be deduced from GM’s annual 

reports, we used 0.03 (see Table A-6) from the Sierra Research study as a proxy for reallocating 

MRO costs. Also, since GM experienced a loss of $4.4 billion in 2007, we used 0.05, the 

McKinsey study estimate, to account for long-term profit. The share of retirement and health 

care costs applicable to the RPE multiplier (see the discussion in Section 3.2.2) was calculated as 

a ratio of selling, G&A, and other expenses to the sum of selling, administrative, and other 

expenses and manufacturing labor cost. The remaining contributors to the RPE multiplier are 

shown in Table A-6, which shows the result as 1.45 in 2007. 

Table A-7 provides historical indirect cost contributors for GM. Here and in the 

remainder of this appendix, historical indirect cost contributors were based on high-level cost 

categories: selling, administrative, and other expenses; operating and other expenses; and 

depreciation. Profit was also included as part of the calculation. Manufacturing costs are 

presented in the companies’ respective currency, and high-level cost contributors are presented 

as a share of the cost of sales. The cost of sales numbers are not adjusted as in Table A-6, but 

cited as they were stated in annual reports. 

A-7 
Table A-6. General Motors RPE Multiplier Calculations: 2007 

Expense 

($ Relative to 

RPE Multiplier Contributor Billions) Cost of Sales Calculation and Source 

Vehicle Manufacturing 

Cost of sales Calculated Manufacturing Cost + 70% x 

(Retirement + 55% x Health Care) −

143.0 1.00 Maintenance, Repair, Operations Cost 

Production Overhead 

Warranty 4.7 0.03 [p. 72, General Motors, 2007] 

R&D (product development) 8.1 0.06 [p. 86, General Motors, 2007] 

Depreciation and amortization 8.3 0.06 [p. 67, General Motors, 2007] 

Maintenance, repair, operations cost 4.0 0.03 [p. 9, Sierra, 2007] 

Total production overhead 25.0 0.17 

Corporate Overhead 

General and administrative 9.4 0.07 [p. 49, General Motors, 2007] 

Retirement 30% x ( Pension Expense (1.799) [p. 84, 

General Motors, 2007] + Pension 

Contributions (0.937) [p. 84, General 

0.9 0.01 Motors, 2007]) 

Health 30% x ( Payroll and Benefits (2.148) [p. 

0.7 0.01 92, General Motors, 2007]) 

Total corporate overhead 11.0 0.08 

Selling 

Transportation 5.0 0.04 Based on McKinsey study 

Marketing Advertising [p. 86, General Motors, 

2007] + Dealer Advertising [p. 52, 

6.5 0.05 General Motors, 2007] 

Dealers 

Dealer new vehicle net profit 8.2 <0.00 RTI calculation 

Dealer new vehicle selling cost 7.9 0.06 RTI calculation 

Total selling and dealer contributors 27.6 0.14 

Sum of Indirect Costs 0.40 

Net income 7.6 0.05 Based on McKinsey study 

Other costs (not included as Legacy Costsa + Automotive Interest and 

contributors) Other Income (0.961) [p. 50, General 

8.8 0.06 Motors, 2007] 

RPE Multiplier 1.45 

a Legacy Costs = OPEB Expense (2.362) + VEBA Withdrawals (1.694) + OPEB Payments (3.751) [all p. 84, 

General Motors, 2007] 

Source: Sierra Research, Inc. November 21, 2007. “Study of Industry—Average Mark-Up Factors Used to 

Estimate Changes in Retail Price Equivalent (RPE) for Automotive Fuel Economy and Emissions 

Control Systems.”. 

McKinsey & Company. 2003. Preface to the Auto Sector Cases. 

General Motors Corporation. 2007. 2007 Annual Report. Available at: 

http://www.gm.com/corporate/investor_information/docs/fin_data/gm07ar/index.html. Accessed on 

August 20, 2008. 

A-8 
Table A-7. General Motors Main Indirect Cost Contributors (as a share of Cost of Sales) 

Indirect Cost Contributor 2007 2006 2005 2004 2003 2002 

Selling, administrative, and other 

expenses 

Operating and other expenses 

Depreciation 

Profit 

Other expenses (not included as 

contributor) 

0.09 

0.05 

0.05 

−0.23 

0.07 

0.08 

0.05 

0.05 

−0.01 

0.07 

0.08 

0.06 

0.06 

−0.07 

0.08 

0.08 

0.06 

0.04 

0.02 

0.08 

0.08 

0.06 

0.04 

0.03 

0.07 

0.08 

0.06 

0.04 

0.01 

0.05 

Sum of main indirect cost contributors 

(including profit) 

0.96 1.17 1.13 1.19 1.21 1.20 

Source: General Motors Corporation: Annual Report 2007, Annual Report 2005. 

Table A-7 illustrates that sum of the main indirect cost contributors had little variation 

between 2002 and 2004. It is worth noting that GM’s sum of main indirect cost contributors was 

0.96 in 2007 (see Table A-7). This value is much smaller than the RPE multiplier value of 1.45, 

which was calculated using our methodology (Table A-6). The discrepancy was caused by the 

use of some averages from other studies for missing values; these are cost contributors subtracted 

from the cost of sales in our methodology, but kept in the cost of sales in the sum of the main 

indirect cost contributors. Missing costs and overstated cost of sales (where missing costs are 

lumped together with our definition of cost of sales) force the sum of the main indirect cost 

contributors to be lower. 

We believe that our methodology is an improved method to account for costs. For 

example, in our methodology (Table A-6) we used a proxy of 0.05 for profit, while the same 

category in the historic calculation was -0.23. 

A.2 DaimlerChrysler AG 

In our analysis, we included DaimlerChrysler’s RPE multiplier, even though 

DaimlerChrysler AG was dissolved and Chrysler was sold to a private equity firm, Cerberus 

Capital Management, in 2007. This allows us to consider the cost structure from what was one of 

the world’s largest automotive firms based on publicly available information. The RPE 

multiplier calculations cover the entire DaimlerChrysler Corporation for 2006. Relevant RPE 

contributing factors gathered from DaimlerChrysler’s annual report are presented in Table A-8. 

A-9 
Table A-8. DaimlerChrysler RPE Multiplier Calculations: 2006 

RPE Multiplier Contributor 

Expense 

(€ Million) 

Relative to 

Cost of Sales Calculation and Source 

Vehicle Manufacturing 

Cost of sales 

Production Overhead 

Warranty 

R&D (product development) 

Depreciation and amortization 

Maintenance, repair, operations 

cost

124,668.1 

5,267.7 

5,331.0 

13,614.0 

 3,490.7 

1.00 

0.04 

0.04 

0.11 

0.03 

125,673 [p. 50, DaimlerChrysler, 2006] 

+ 70% x (Retirement + 55% x Health 

Care) − Maintenance, Repair, 

Operations Costs 

Based on McKinsey study 

[p. 214, DaimlerChrysler, 2006] 

[p. 205, DaimlerChrysler, 2006] 

[p. 9, Sierra, 2007] 

Total production overhead - 0.22 

Corporate Overhead 

General and administrative 

Retirement 

Health 

6,292.6 

922.8 

185.6 

0.05 

0.01 

Less than 0.01 

18,513 [p. 50, DaimlerChrysler, 2006] −

Marketing − Transportation − Warranty 

30% x Retirement (2247 + 829) [both p. 

184, DaimlerChrysler, 2006] 

30% x 55% x Health Care (832 + 293) 

[both p. 188, DaimlerChrysler, 2006] 

Total corporate overhead 

Selling 

Transportation 

Marketing 

Dealers 

Dealer new vehicle net profit 

Dealer new vehicle selling cost 

7,401.0 

4,389.7 

2,563.0 

7,158.2 

6,873.9 

0.06 

0.04 

0.02 

<0.01 

0.06 

Based on McKinsey study 

[p. 162, DaimlerChrysler, 2006] 

RTI calculation 

RTI calculation 

Total selling and dealer 

contributors 

Sum of Indirect Costs 

Net income 

Other costs (not included as 

contributors) 

20,984.8

3,227.0 

4,699.3 

 0.12 

0.40 

0.07 

0.04 

[p. 214, DaimlerChrysler, 2006] 

Interest Paid (4,193) [p. 214, 

DaimlerChrysler, 2006] + 45% x Health 

Care 

RPE Multiplier 1.47 

Source: Sierra Research, Inc. November 21, 2007. “Study of Industry—Average Mark-Up Factors Used to 

Estimate Changes in Retail Price Equivalent (RPE) for Automotive Fuel Economy and Emissions 

Control Systems.” 

McKinsey & Company. 2003. Preface to the Auto Sector Cases. 

As Table A-8 shows, DaimlerChrysler did not provide warranty or MRO expenditures. 

Values were added for these factors from the McKinsey and Sierra studies. Marketing, 

A-10 
transportation, and warranty costs were included in G&A expenditures and, thus, were 

subtracted. The estimated RPE multiplier for DaimlerChrysler was 1.47 in 2006. 

DaimlerChrysler’s sum of the main indirect cost contributors increased between 2002 and 

2003. This was mostly due to increasing selling, administrative, and other expenses, which 

increased from 0.05 to about 0.20 between those years. Other factors changed much less during 

this period. The sum of the main indirect cost contributors varied between 1.24 and 1.38 in the 

2002–2006 time period (Table A-9). 

Table A-9. DaimlerChrysler Main Indirect Cost Contributors (as a Share of Cost of Sales) 

Indirect Cost Contributor 2006 2005 2004 2003 2002 

Selling, administrative, and other expenses 

Operating and other expenses 

Depreciation 

Profit 

Other expenses (not included as contributor) 

0.19 

0.05 

0.11 

0.03 

0.01 

0.20 

0.05 

0.10 

0.02 

0.01 

0.21 

0.05 

0.10 

0.02 

0.01 

0.21 

0.05 

0.11 

0.00 

0.01 

0.05 

0.04 

0.12 

0.04 

0.01 

Sum of main indirect cost contributors 

(including profit) 1.38 1.38 1.37 1.37 1.24 

Sources: DaimlerChrysler AG. 2007. DaimlerChrysler: Annual Report 2006. Available at: 

http://www.daimlerchrysler.com/Projects/c2c/channel/documents/1003905_DCX_2006_Annual_Report.pd 

f. Accessed on November 14, 2008. 

DaimlerChrysler AG. 2005. DaimlerChrysler: Annual Report 2003. Available at: 

http://www.daimler.com/dccom/0-5-660593-1-169901-1-0-0-0-0-0-12591-7164-0-0-0-0-0-0-0.html. 

Accessed on November 14, 2008. 

A.3 Ford Motor Company 

Relevant RPE contributing factors gathered from Ford Motor Company’s annual report 

are presented in Table A-10. Ford included “freight, engineering, and research and development 

(R&D)” costs in their cost of sales (Ford Motor Company, 2008). We subtracted this line item 

($7.5 billion), together with the cost of employee separation (i.e., the recent buy-outs of 

employees, reported as $2.21 billion + $0.22 billion + $0.15 billion) and certain “electricity 

physical supply contracts” ($0.65 billion) and other factors (see Table A-10) from the cost of 

sales to arrive at an adjusted value for the cost of sales of $130.4 billion. Ford reported “selling, 

general, and other expenses” of $21.2 billion in their annual report. The report also indicated that 

marketing costs were included in “selling, general, and other expenses.” Marketing costs 

included advertising expenses and variable marketing expenses in the United States and were 

A-11 
Table A-10. Ford Motor Company RPE Multiplier Calculations: 2007 

Expense Relative to 

RPE Multiplier Contributor ($ Billions) Cost of Sales Calculation and Source 

Vehicle Manufacturing 

Cost of sales Cost of Sales [FS1, Ford, 2007b] − Cost of Employee 

Separation (1.036–0.817) [FS36, Ford, 2007b] −

Other Employee Separation Actions (2.435–0.225) 

[FS36, Ford, 2007b] − Certain Electricity Physical 

Supplies Contracts (0.154) [90, Ford, 2007a] − Hedge 

Accounting Designations (0.65) [p.101, Ford, 2007a] 

− Maintenance, Repair, Operations Cost - 

130.4 1.00 Transportation 

Production Overhead 

Warranty 3.3 0.03 [p. 117, Ford, 2007a]

R&D (product development) 2.9 0.02 [p. 63, Ford, 2007a] - Transportation 

Depreciation and amortization 6.8 0.05 [p. 56, Ford, 2007b]

Maintenance, repair, [p. 9, Sierra, 2007]

operations cost 3.7 0.03 

Total production overhead 16.6 0.13 

Corporate Overhead 

General and administrative Selling, Administrative and Other Expenses (21.2) 

[FS2, Ford, 2007] − Advertising (5.4) [p. 64, Ford, 

15.8 0.12 2007a] − Transportation 

Retirement 0.5 0.00 30% x Pensions (1.128+0.885) [107, Ford, 2007a] 

Health 0.4 0.00 30% x 55% x Health Care

a 

Total corporate overhead 16.7 0.13 

Selling 

Transportation 4.6 0.04 Based on McKinsey study

Marketing 5.4 0.04 Advertising (5.4) [p. 56, Ford, 2007b]

Dealers 

Dealer new vehicle net profit 7.5 <0.01 RTI calculation 

Dealer new vehicle selling RTI calculation 

cost 7.2 0.06 

Total selling and dealer 

contributors 24.7 0.14 

Sum of Indirect Costs 0.39 

Net income 6.9 0.05 Based on McKinsey study 

Other costs (not included as 

contributors) 

Goodwill Impairment (2.4) [p.54, Ford, 2007a] + 

Interest Expense (10.92) [p.54, Ford, 2007a] + 

Provision for Credit (0.688) [p.54, Ford, 2007a]+ 

14.3 0.11 30% x 45% x Health Care

a 

RPE Multiplier 1.45 

a

 Health care = Health care (2.2) [11, Ford, 2007a] + OPEB (0.414) [107, Ford, 2007a] + Benefits Paid (3,937)[108, 

Ford, 2007a] 

Sources: Sierra Research, Inc. November 21, 2007. “Study of Industry—Average Mark-Up Factors Used to Estimate 

Changes in Retail Price Equivalent (RPE) for Automotive Fuel Economy and Emissions Control Systems.” 

McKinsey & Company. 2003. Preface to the Auto Sector Cases. 

Ford Motor Company. 2007. Ford Company: 2007 Annual Report. Available at: http://www.ford.com/ 

microsites/annual-reports. Accessed on September 20, 2008. 

Ford Motor Company. 2007a. 10-K Annual Report 2007. Available via EDGAR database from: 

http://sec.gov/edgar. Accessed on September 20, 2008. 

A-12 
lumped in G&A costs. We subtracted marketing costs ($5.4 billion) from “selling, general, and 

other expenses” to arrive at an adjusted G&A of $15.8 billion. Ford did not report “maintenance, 

repair, and operations” costs; therefore, we used an industry average of 0.03 from the 2007 Sierra 

study as a proxy. Results of these calculations are outlined in Table A-10. 

As mentioned in Section 3.2.2 of this report, health care and retirement costs include 

expenditures for manufacturing and corporate workers. Ford’s annual report provided the 

number of hourly versus salaried workers it employed. In 2007, the number of hourly workers 

was 64,000, while the number of salaried workers was 23,700. We used these values as estimates 

for the number of manufacturing versus corporate workers. Thus, 73% of Ford’s retirement and 

health care costs were included in manufacturing costs, and 27% were used in the RPE multiplier 

calculation. 

Ford did not separate out transportation costs and dealer support or dealer discount costs, 

which were lumped into R&D and G&A costs, respectively. Lastly, Ford Motor Company 

reported a $2.7 billion loss in 2007, which is likely a result of the current economic conditions in 

the United States. In the long run, Ford’s profits are expected to be closer to the industry average. 

Because of this, we substituted the McKinsey study estimate of 0.05 for the net income loss 

reported by Ford. As a result, the value of the RPE multiplier for Ford Motor Company was 1.45 

in 2007. 

Table A-11 presents Ford’s sum of the main indirect cost contributors, which are much 

lower than the RPE value derived above for 2007. 

A.5 Honda Motor Company 

RPE calculations for Honda Motor Company are presented in Table A-12. Honda Motor 

Company’s annual report provided financials in Japanese yen. In 2007, the cost of sales equaled 

¥7,865 billion. Honda did not report MRO costs or health care cost; therefore, the Sierra study 

values of 0.03 and 0.03 (which was then multiplied by 30% to account for corporate labor only) 

were used as a proxy. As opposed to U.S. manufacturers, Honda’s historical profits were 

relatively comparable to that available for the 2007 RPE multiplier calculated using our 

methodology. The RPE multiplier for Honda Motor Company equaled 1.47 in 2007. 

Table A-13 presents Honda’s sum of the main indirect cost contributors, which are again 

lower than the RPE value derived above for 2007. 

A-13 
Table A-11. Ford Motor Company Main Indirect Cost Contributors (as a Share of Cost of 

Sales) 

Indirect Cost Contributor 2007 2006 2005 2004 2003 2002 

Selling, administrative, and other expenses 

Operating and other expenses 

Depreciation 

Profit 

Other expenses (not included as contributor) 

0.10 

0.01 

0.05 

−0.02 

0.06 

0.09 

0.01 

0.04 

−0.13 

0.06 

0.08 

0.04 

0.04 

−0.03 

0.06 

0.08 

0.04 

0.05 

0.03 

0.06 

0.08 

0.04 

0.07 

0.00 

0.08 

0.08 

0.04 

0.08 

−0.01 

0.10 

Sum of main indirect cost contributors 

(including profit) 

1.13 1.01 1.13 1.20 1.19 1.19 

Sources: Ford Motor Company. 2006. Ford Company: 2005 Annual Report. Available at: 

http://www.ford.com/microsites/annual-reports. Accessed on September 20, 2008. 

Ford Motor Company. 2008. Ford Company: 2007 Annual Report. Available at: 

http://www.ford.com/microsites/annual-reports. Accessed on September 20, 2008. 

A.6 Hyundai Motor Company 

Table A-14 presents relevant RPE cost contributors and the RPE multiplier for Hyundai 

Motor Company in 2007. Hyundai Motor Company’s financials were reported in Japanese yen. 

R&D expenses were included in the cost of sales, which we subtracted to arrive at an adjusted 

cost of sales of ¥53.27 billion. Hyundai did not report MRO cost, so we used the Sierra study 

value of 0.03 as a proxy. Health care cost was not reported, and because there was no industry 

estimate for this number, we used the Sierra study value of 0.03 as a proxy. Hyundai’s RPE 

multiplier value was calculated to be 1.42 for 2007. 

Hyundai’s annual reports were available dating back to 2004. Similar to Honda, 

Hyundai’s historical profits presented in Table A-15 were relatively comparable to that available 

for the 2007 RPE multiplier calculated using our methodology. 

A-14 
Table A-12. Honda Motor Company RPE Multiplier Calculations: 2007 

Expense Relative to 

RPE Multiplier Contributor (¥ Billion) Cost of Sales Calculation and Source 

Vehicle Manufacturing 

Cost of sales Cost of Sales [p. 54, Honda, 2007] + 70% x 

Pensions and Postretirement Benefits −

7,609.8 1.00 Maintenance, Repair, Operations Costs 

Production Overhead 

Warranty 113.5 0.01 [p. 109, Honda, 2008] 

R&D (product development) 551.8 0.07 [p. 2, Honda, 2008] 

Depreciation and amortization 371.5 0.05 [p. 113, Honda, 2008] 

Maintenance, repair, [p. 9, Sierra, 2008] 

operations cost 213.1 0.03 

Total production overhead 1,249.8 0.16 

Corporate Overhead 

General and administrative Selling, General and Administrative (1818.2) 

[p. 72, Honda, 2008] − Transportation −

Marketing [p. 78, Honda, 2008] – Dealer 

883.7 0.12 Support 

Retirement 10.6 Less than 0.01 

Health 30% x Retiree Health Care [p. 9, Sierra, 

220.9 0.01 2007] 

Total corporate overhead 1,115.2 0.15 

Selling 

Transportation 267.9 0.04 Based on McKinsey study 

Marketing 247.0 0.03 [p. 78, Honda, 2008] 

Dealers 

Dealer new vehicle net profit 436.9 <0.01 RTI calculation 

Dealer new vehicle selling cost 419.6 0.06 RTI calculation 

Total selling and dealer 

contributors 1,371.5 0.13 

Sum of Indirect Costs 0.44 

Net income 268.6 0.04 Net Income [p. 72, Honda, 2008] 

Other costs (not included as Interest + Other Expenses [p. 72, Honda, 

contributors) 114.6 0.02 200] 

RPE Multiplier 1.47 

Sources: Sierra Research, Inc. November 21, 2007. “Study of Industry—Average Mark-Up Factors Used to Estimate 

Changes in Retail Price Equivalent (RPE) for Automotive Fuel Economy and Emissions Control Systems.” 

McKinsey & Company. 2003. Preface to the Auto Sector Cases. 

Honda Motor Company. 2008. Annual Report 2008. Available at: 

http://world.honda.com/investors/annualreport/2008/. Accessed on September 20, 2008. 

A-15 
Table A-13. Honda Motor Company Main Indirect Cost Contributors (as a Share of Cost 

of Sales) 

Indirect Cost Contributor 2007 2006 2005 2004 2003 2002 

Selling, administrative, and other expenses 

Operating and other expenses 

Depreciation 

Profit 

Other expenses (not included as contributor) 

0.23 

NA 

0.05 

0.08 

0.02 

0.24 

NA 

0.04 

0.09 

0.01 

0.25 

NA 

0.04 

0.08 

0.01 

0.27 

NA 

0.04 

0.08 

0.00 

0.27 

NA 

0.04 

0.08 

0.02 

0.26 

NA 

0.04 

0.07 

0.02 

Sum of main indirect cost contributors (including 

profit) 

1.35 1.36 1.37 1.39 1.41 1.40 

NA = Not available 

Sources: Honda Motor Company: Annual Report 2006. 

Honda Motor Company. 2008. Annual Report 2008. Available at: 

http://world.honda.com/investors/annualreport/2008/. Accessed on September 20, 2008. 

A.7 Nissan Motor Company 

Relevant RPE contributing factors gathered from Nissan’s annual report are presented in 

Table A-16. Nissan Motor Company’s annual report provided expenses in Japanese yen and did 

not provide an estimate of MRO cost; therefore, the Sierra study value of 0.03 was used as a 

proxy (see Table A-16). Selling expenses (transportation, marketing, dealer support, and dealer 

discount) were reported as part of G&A expenses, so G&A was adjusted by that cost. Nissan also 

did not provide an estimate of health care cost, and since no industry average was available, this 

item was not included in Nissan’s RPE multiplier calculations. Nissan’s RPE multiplier value 

was calculated to be 1.49 in 2007. 

Nissan experienced little variation in its sum of main indirect cost contributors (see 

Table A-17). Between 2002 and 2007, the sum of main indirect cost contributors varied between 

1.39 and 1.51. 

A-16 
Table A-14. Hyundai Motor Company RPE Multiplier Calculations: 2007 

RPE Multiplier Contributor 

Expense 

(¥ Billion) 

Relative to 

Cost of Sales Calculation and Source 

Vehicle Manufacturing 

Cost of sales 

51,926,743.9 1.00 

Cost of Sales [p. 52, Hyundai, 2008] + 70% x 

Payments of Severance Benefits − Research 

and Development − Maintenance, Repair, 

Operations Costs 

Production Overhead 

Warranty 975,825.0 0.02 [p. 109, Hyundai, 2008] 

R&D (product development) 2,193,479.0 0.04 [p. 86, Hyundai, 2008] 

Depreciation and 

amortization 

3,293,479.0 0.06 

Depreciation [p. 56, Hyundai, 2008] + 

Amortization of intangibles [p. 56, Hyundai, 

2008] 

Maintenance, repair, 

operations cost 2,786,433.0 0.03 

[p. 9, Sierra, 2007] 

Total production overhead 9,249,216.0 0.15 

Corporate Overhead 

General and administrative Selling and Administrative Expenses [p. 109, 

Hyundai, 2008] − Export Related Expenses −

Sales Promotion − Sales Commission − Sales 

4,038,378.0 0.08 

Warranties − Freight and Warehousing − Rent 

− Travel − Research − Depreciation −

Amortization 

Retirement 

241,712.4 Less than 0.01 

30% x Payment of Severance Benefits [p. 57, 

Hyundai, 2008] 

Health 389,450.6 0.01 30% x Retiree Health Care [p. 9, Sierra, 2008] 

Total corporate overhead 4,669,541.0 0.09 

Selling 

Transportation Export Related Expenses + Freight and 

Warehousing + Rent + Travel [all p. 109, 

1,975,596.0 0.04 Hyundai, 2008] 

Marketing 2,392,644.0 0.05 Sales Promotion [p. 109, Hyundai, 2008] 

Dealers 

Dealer new vehicle net RTI calculation 

profit 2,981,515.7 <0.01 

Dealer new vehicle selling RTI calculation 

cost 2,863,122.9 0.06 

Total selling and dealer 

contributors 10,212,878.6 0.15 

Sum of Indirect Costs 0.39 

Net income 1,600,480.0 0.03 [p. 69, Hyundai, 2008] 

Other costs (not included as Interest Expense [p. 52, Hyundai, 2008] 

contributors) 430,631.0 0.01 

RPE Multiplier 1.42 

Sources: Sierra Research, Inc. November 21, 2007. “Study of Industry—Average Mark-Up Factors Used to Estimate 

Changes in Retail Price Equivalent (RPE) for Automotive Fuel Economy and Emissions Control Systems.” 

McKinsey & Company. 2003. Preface to the Auto Sector Cases. 

A-17 
Hyundai Motor Company. 2008. Annual Report 2007. Available at: http://csr.hyundaimotor.com/download/Annual_Report_2007.pdf. Accessed on October 10, 2008. 

Table A-15. Hyundai Motor Company Main Indirect Cost Contributors (as a Share of Cost 

of Sales) 

Indirect Cost Contributor 2007 2006 2005 2004 

Selling, administrative, and other expenses 

Operating and other expenses 

Depreciation 

Profit 

Other expenses (not included as contributor) 

0.20 

NA 

0.05 

0.03 

NA 

0.23 

NA 

0.06 

0.03 

NA 

0.23 

NA 

0.05 

0.05 

NA 

0.29 

NA 

0.04 

0.04 

NA 

Sum of main indirect cost contributors (including 

profit) 1.28 1.32 1.33 1.37 

NA = Not available 

Sources: Hyundai Motor Company. 2006. Annual Report 2005. Available at: http://csr.hyundaimotor.com/download/Annual_Report_2005.pdf. Accessed on October 10, 2008. 

Hyundai Motor Company. 2008. Annual Report 2007. Available at: http://csr.hyundaimotor.com/download/Annual_Report_2007.pdf. Accessed on October 10, 2008. 

A.8 Toyota Motor Company 

The RPE multiplier calculations for Toyota Motor Company are presented in Table A-18. 

Toyota Motor Company’s annual report provided expenses in Japanese yen. Toyota included 

their R&D expenses in cost of sales (which was called “cost of product sold” in its annual report) 

and G&A expenses. Because they did not report fractions that were charged to either of those 

costs, 50% of R&D costs were subtracted from the cost of sales and 50% from G&A expenses. 

Warranty costs included the actual costs paid throughout the year (¥336.5 billion) and the costs 

provisioned for warranties (¥290.0). Again, the Sierra study value of 0.03 was used as a proxy 

for MRO cost, since those costs were lumped into operations cost, which Toyota did not provide 

in its annual report. Research and development and advertising costs were reported as part of 

G&A expenses, and these costs were subtracted from G&A. Health care cost was not reported in 

Toyota’s annual report, so the Sierra study value of 0.03 was used as a proxy. The RPE 

multiplier for Toyota Motor Company was calculated to be 1.48 in 2007. 

Toyota experienced very little variation in the sum of the main indirect cost contributors: 

between 1.31 and 1.35 (see Table A-19). In this case, higher profits are associated with lower 

selling, administrative, and other expenses and higher manufacturing costs. 

A-18 
Table A-16. Nissan Motor Company RPE Multiplier Calculations: 2007 

RPE Multiplier Contributor 

Vehicle Manufacturing 

Cost of sales 

Production Overhead 

Warranty 

R&D (product development) 

Depreciation and 

amortization 

Maintenance, repair, 

operations cost 

Expense 

(¥ Million) 

7,789,660.3 

222,390.0 

464,839.0 

705,380.0 

218,110.5 

Relative to 

Cost of Sales 

1.00 

0.03 

0.06 

0.09 

0.03 

Calculation and Source 

Cost of Sales [p. 50, Hyundai, 2008] + 

70% x Retirement Benefit Expenses 

Accrual for warranty costs (current) [p. 

49, Nissan, 2008] + Accrual for 

warranty costs (long-term) [p. 49, 

Nissan, 2008] 

[p. 63, Nissan, 2008] 

[p. 58, Nissan, 2008] 

[p. 9, Sierra, 2008] 

Total production overhead 

Corporate Overhead 

General and administrative 

Retirement 

Health 

1,610,719.5 

267,054.0 

21,079.5 

1,635.8 

0.21 

0.03 

Less than 0.01 

0.01 

Selling, General, and Administrative 

Costs [p. 50, Nissan, 2008] −

Transportation – Marketing − Research 

and Development 

30% x Retirement Benefit Expenses 

30% x Retiree Health Care [p. 9, 

Sierra, 2007] 

Total corporate overhead 

Selling 

Transportation 

Marketing 

Dealers 

Dealer new vehicle net profit 

Dealer new vehicle selling 

cost 

289,769.4 

274,283.8 

658,281.2 

447,264.6 

429,504.2 

0.04 

0.04 

0.08 

0.06 

0.06 

Based on McKinsey study 

Based on McKinsey study 

RTI calculation 

RTI calculation 

Total selling and dealer 

contributors 

Sum of Indirect Costs 

Net income 

Other costs (not included as 

contributors) 

1,809,333.8 

460,796.0 

93,343.0

0.18 

0.43 

0.06 

 0.01 

[p. 50, Nissan, 2008] 

Other, net [p. 50, Nissan, 2008] 

RPE Multiplier 1.49 

Sources: Sierra Research, Inc. November 21, 2007. “Study of Industry—Average Mark-Up Factors Used to Estimate 

Changes in Retail Price Equivalent (RPE) for Automotive Fuel Economy and Emissions Control Systems.” 

McKinsey & Company. 2003. Preface to the Auto Sector Cases. 

A-19 
Nissan Motor Company. 2008. Annual Report 2006–2007. Available at: http://www.nissanglobal.com/EN/IR/LIBRARY/AR/. Accessed on October 10, 2008. 

Table A-17. Nissan Motor Company Main Indirect Cost Contributors (as a Share of Cost 

of Sales) 

Indirect Cost Contributor 2007 2006 2005 2004 2003 2002 

Selling, administrative, and other 

expenses 

Operating and other expenses 

Depreciation 

Profit 

Other expenses (not included as 

contributor) 

0.21 

0.08 

0.10 

0.06 

0.02 

0.22 

0.06 

0.09 

0.07 

0.02 

0.22 

0.01 

0.08 

0.08 

0.02 

0.24 

0.09 

0.09 

0.10 

0.02 

0.25 

0.08 

0.08 

0.10 

0.01 

0.26 

0.01 

0.08 

0.08 

0.03 

Sum of main indirect cost contributors 

(including profit) 

1.44 1.44 1.39 1.51 1.51 1.43 

Sources: Nissan Motor Company. 2006. Annual Report 2004–2005. Available at: http://www.nissanglobal.com/EN/IR/LIBRARY/AR/. Accessed on October 10, 2008. 

Nissan Motor Company. 2008. Annual Report 2006–2007. Available at: http://www.nissanglobal.com/EN/IR/LIBRARY/AR/. Accessed on October 10, 2008. 

A.9 Volkswagen Group 

Relevant RPE contributing factors gathered from Volkswagen’s annual report are 

presented in Table A-20. The Volkswagen Group reported its financial results in Euros. As 

opposed to other manufacturers, Volkswagen health care cost was relatively minor compared to 

the cost of sales and thus was substituted with the Sierra study value 0.03. The RPE multiplier 

for the Volkswagen Group was estimated to be 1.43 in 2007. 

Volkswagen experienced almost no variation in the sum of the main indirect cost 

contributors, which stayed around 1.28 (see Table A-21). Higher profits for the Volkswagen 

Group are associated with lower depreciation stated in their annual reports. 

A-20 
Table A-18. Toyota Motor Company RPE Multiplier Calculations: 2007 

Expense Relative to Cost 

RPE Multiplier Contributor (¥ Million) of Sales Calculation and Source 

Vehicle Manufacturing 

Cost of sales Cost of Product Sold [p. 71, Toyota, 

2007] − 50% x Research and 

17,463,582.6 1.00 Development + 70% x Pensions 

Production Overhead 

Warranty Warranties Paid Through the Year [p. 

109, Toyota, 2007] + Provisions for 

616,133.0 0.04 Warranties [p. 109, Toyota, 2007] 

R&D (product development) 890,700.0 0.05 [p. 79, Toyota, 2007] 

Depreciation and amortization 1,382,594.0 0.08 Depreciation [p. 94, Toyota, 2007] 

Maintenance, repair, operations [p. 9, Sierra, 2007] 

cost 488,980.3 0.03 

Total production overhead 3,378,407.3 0.19 

Corporate Overhead 

General and administrative Selling, General, and Administrative −

50% x Research and Development −

969,568.1 0.06 Advertising − Transportation 

Retirement 83,765.7 Less than 0.01 30% x Pensions 

Health 30% x Retiree Health Care [p. 9, Sierra, 

130,976.9 0.01 2007] 

Total corporate overhead 1,184,310.7 0.07 

Selling 

Transportation 614,914.9 0.04 Based on McKinsey study 

Marketing 451,182.0 0.03 Advertising [p. 97, Toyota, 2007] 

Dealers 

Dealer new vehicle net profit 1,002,719.3 0.06 RTI calculation 

Dealer new vehicle selling cost 962,902.4 0.06 RTI calculation 

Total selling and dealer 

contributors 3,031,718.5 0.12 

Sum of Indirect Costs 0.38 

Net income 1,644,032.0 0.09 [p. 96, Toyota, 2007] 

Other costs (not included as Interest Expense [p. 94, Toyota, 2007] 

contributors) 49,326.0 0.00 

RPE Multiplier 1.48 

Sources: Sierra Research, Inc. November 21, 2007. “Study of Industry—Average Mark-Up Factors Used to Estimate 

Changes in Retail Price Equivalent (RPE) for Automotive Fuel Economy and Emissions Control Systems.” 

McKinsey & Company. 2003. Preface to the Auto Sector Cases. 

Toyota Motor Company. 2008. Annual Report 2008. Available at: 

http://www.toyota.co.jp/en/ir/library/annual/index.html. Accessed on October 10, 2008. 

A-21 
Table A-19. Toyota Motor Company Main Indirect Cost Contributors (as a Share of Cost 

of Sales) 

Indirect Cost Contributor 2007 2006 2005 2004 2003 2002 

Selling, administrative, and other 

expenses 

Operating and other expenses 

Depreciation 

Profit 

Other expenses (not included as 

contributor) 

0.14 

0.05 

0.08 

0.09 

0.00 

0.14 

0.04 

0.07 

0.08 

0.00 

0.14 

0.03 

0.07 

0.08 

0.00 

0.13 

0.03 

0.07 

0.09 

0.00 

0.16 

0.04 

0.07 

0.06 

0.00 

0.16 

0.04 

0.07 

0.05 

NA 

Sum of main indirect cost contributors 

(including profit) 

1.35 1.33 1.31 1.32 1.33 1.33 

NA = Not available 

Sources: Toyota Motor Company. 2006. Annual Report 2006. Available at: 

http://www.toyota.co.jp/en/ir/library/annual/index.html. Accessed on October 10, 2008. 

Toyota Motor Company. 2008. Annual Report 2008. Available at: 

http://www.toyota.co.jp/en/ir/library/annual/index.html. Accessed on October 10, 2008. 

A-22 
Table A-20. Volkswagen Group RPE Multiplier Calculations: 2007 

Expense Relative to 

RPE Multiplier Contributor (€ Million) Cost of Sales Calculation and Source 

Vehicle Manufacturing 

Cost of sales Cost of Sales [p.135, VW, 2007] −

Warranty −R&D − MRO + 70% x 

82,595.6 1.00 Pensions and Postretirement Benefits 

Production Overhead 

Warranty 2,056.3 0.02 Based on McKinsey study 

R&D (product development) 4,653.3 0.06 Based on McKinsey study 

Depreciation and amortization 7,278.0 0.09 [p. 133, VW, 2007] 

Maintenance, repair, operations [p. 9, Sierra, 2007] 

cost 2,312.7 0.03 

Total production overhead 16,300.3 0.20 

Corporate Overhead 

General and administrative 2,453.0 0.03 [p. 135, VW, 2007] 

Retirement 30% x Old-Age Pensions [p. 143, VW, 

386.4 Less than 0.01 2007] 

Health 30% x Retiree Health Care [p. 9, Sierra, 

17.3 0.01 2007] 

Total corporate overhead 2,856.7 0.04 

Selling 

Transportation 7,864.0 0.10 Distribution Expenses − Marketing 

Marketing Selling, general and administrative 

expense − Administrative Expenses [p. 

1,410.0 0.02 139, VW, 2007] 

Dealers 

Dealer new vehicle net profit 4,742.5 <0.01 RTI calculation 

Dealer new vehicle selling cost 4,554.1 0.06 RTI calculation 

Total selling and dealer 

contributors 18,570.6 0.17 

Sum of Indirect Costs 0.41 

Net income 1,455.0 0.02 [p. 142, VW, 2007] 

Other costs (not included as Financial Result [p. 142, VW, 2007] 

contributors) 3,799.0 0.05 

RPE Multiplier 1.43 

Sources: Sierra Research, Inc. November 21, 2007. “Study of Industry—Average Mark-Up Factors Used to Estimate 

Changes in Retail Price Equivalent (RPE) for Automotive Fuel Economy and Emissions Control Systems.” 

McKinsey & Company. 2003. Preface to the Auto Sector Cases. 

A-23 
Volkswagen Group AG. 2008. Annual Report 2007. Available at: http://www.volkswagenag.com/vwag/ 

gb2007/content/en/annual_report_2007.html. Accessed on October 10, 2008. 

Table A-21. Volkswagen Historical Main Indirect Cost Contributors (as a share of Cost 

of Sales) 

Indirect Cost Contributor 2007 2006 2005 2004 2003 2002 

Selling, administrative, and other expenses 

Operating and other expenses 

Depreciation 

Profit 

Other expenses (not included as contributor) 

0.12 

0.05 

0.08 

0.05 

NA 

0.13 

0.06 

0.09 

0.02 

NA 

0.13 

0.04 

0.09 

0.01 

NA 

0.13 

0.04 

0.10 

0.01 

NA 

0.14 

0.04 

0.09 

0.01 

NA 

0.13 

0.05 

0.08 

0.04 

NA 

Sum of main indirect cost contributors 

(including profit) 

1.29 1.29 1.28 1.27 1.29 1.29 

NA = Not available 

Sources: Volkswagen Group AG. 2004. Annual Report 2003. Available at: 

http://www.vwfsag.de/fsag/ucus/vwfsag/en/investor_relations/annual_report/ archive_2003.htx. Accessed 

on October 10, 2008. 

Volkswagen Group AG. 2008. Annual Report 2007. Available at: 

http://www.volkswagenag.com/vwag/gb2007/content/en/annual_report_2007.html. Accessed on October 

10, 2008. 

A-24