Automobile Industry Retail Price
Equivalent and Indirect Cost Multipliers
United States
Environmental Protection
Agency
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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 posi-
tions. 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.
SER&
United States
Environmental Protection
Agency
EPA-420-R-09-003
February 2009
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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, Ml 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, Ml 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, Ml 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, Ml 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 1C Multiplier Approaches 2-1
3 RPE Multiplier Estimation 3-1
3.1 Components of Indirect Costs 3-1
3.2 Company-Level 1C 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 1C Components and RPE Multiplier Values 3-5
3.3 Industry Average Indirect Costs andRPEs 3-8
4 1C 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 1C Multipliers 4-11
4.5 Summary 4-12
5 Conclusion 5-1
5.1 Applicability of the RPE and 1C Multipliers in Future Years 5-1
in
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References R-l
Appendix
A: Calculation of RPE Multipliers for Individual Manufacturers A-1
IV
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LIST OF FIGURES
Number Page
2-1. RPE Multiplier vs. 1C Multiplier Approach 2-2
4-1. Impacts of Technology Complexity on 1C Multiplier 4-3
4-2. Definition of Innovation Processes 4-3
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LIST OF TABLES
Number Page
ES-1. Industry Average and Individual Company RPE Multipliers: 2007 2
ES-2. 1C 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 RTFs 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 1C 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 1C Multiplier Calculations 4-13
A-l. 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-l 1
A-10. Ford Motor Company RPE Multiplier Calculations: 2007 A-12
A-l 1. 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
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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
vn
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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 (1C) 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 1C 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
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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
DaimlerChrysler3
Ford
GM
Honda
Hyundai
Nissan
Toyota
VW
Weighted Average
Annual Production (number of vehicles) (2007)
4,635,601
6,247,506
9,349,818
3,911,814
2,617,725
3,431,398
8,534,690
6,267,891
RPE Multiplier
1.47
1.45
1.45
1.47
1.42
1.49
1.48
1.43
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 1C 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 1C 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 1C 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
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Table ES-2.1C Multipliers by Technology Complexity and Time Frame
Time Frame
Short-term effects
Long-term effects
Technology Complexity
Low
1.05
1.02
Medium
1.20
1.05
High
1.45
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 1C multiplier specific to that technology.
ES-3
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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.
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This study develops a modified multiplier, referred to as an indirect cost (1C) multiplier,
which specifically evaluates the components of indirect costs that are likely to be affected by
vehicle modifications associated with environmental regulation.
1C Multiplier = (Incremental direct + indirect costs)/(incremental direct manufacturing costs)
A range of 1C 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 1C 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 1C 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
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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 (1C) 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 1C 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 1C 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.
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(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 1C multipliers. We estimated
that the value of the 1C 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 1C 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.
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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 1C 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 1C 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 Qi and buyers purchase that quantity at the price of
PI 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.
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The RPE multiplier approach assumes that the multiplier captures the full market impact
of the new cost. Sales continue at Qi, 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
P2
P3
PI
: With Regulation
S0: Without Regulation
Q3 Q2
Quantity
Figure 2-1. RPE Multiplier vs. 1C 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
Si, the price axis, and quantity Qi. The actual social cost is the area between lines So and Si, 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 1C 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 Qi 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
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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
?2, quantity Qs. 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 Cb, and the
price will not rise as much as ?2. 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 1C 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
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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 1C multiplier
approach, determines the distribution of regulatory burden between producers and consumers
consistent with economic theory.
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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
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.
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Table 3-1. RPE Multiplier Contributors in Vyas et al.'s Methodology
Cost Category
Manufacturing
Production overhead
Corporate overhead
Cost Contributor
Cost of manufacture
Warranty
R&D/engineering
Depreciation and amortization
Corporate overhead, retirement and
health care
Relative to Cost of
Manufacturing
1.00
0.10
0.13
0.11
0.14
Share of
MSRP (%)
50.0
5.0
6.5
5.5
7.0
Selling Transportation, marketing, dealer 0.47 23.5
support, and dealer discount
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
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dealer gross profits.8 The increased level of disaggregation allowed for more flexibility when
estimating the 1C 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 1C) 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
1 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.
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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%).
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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-of-
sales 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
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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.
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Table 3-3. Individual Manufacturer and Industry Average RPE Multipliers: 2007
Relative to Cost of Sales
RPE Multiplier Contributor
Vehicle Manufacturing
Cost of sales
Production Overhead
Warranty
R&D (product development)
Depreciation and amortization
Maintenance, repair, operations cost
Total production overhead
Corporate Overhead
General and administrative
Retirement
Health
Total corporate overhead
Selling
Transportation
Marketing
Dealers
Dealer new vehicle net profit
Dealer new vehicle selling cost
Total selling and dealer contributors
Sum of Indirect Costs
Net income
Other costs (not included as contributors)
RPE Multiplier
Industry
Average
1.00
0.03
0.05
0.07
0.03
0.18
0.07
<0.01
0.01
0.08
0.04
0.04
<0.01
0.06
0.14
0.40
0.06
0.04
1.46
Daimler
Chrysler
1.00
0.04
0.04
0.11
0.03
0.22
0.05
0.01
<0.01
0.06
0.04
0.02
<0.01
0.06
0.12
0.40
0.07
0.04
1.47
Ford
1.00
0.03
0.02
0.05
0.03
0.13
0.12
0.00
<0.01
0.13
0.04
0.04
<0.01
0.06
0.14
0.39
0.05
0.11
1.45
GM
1.00
0.03
0.06
0.06
0.03
0.17
0.07
0.01
0.01
0.08
0.04
0.05
<0.01
0.06
0.14
0.40
0.05
0.06
1.45
Honda
1.00
0.01
0.07
0.05
0.03
0.16
0.11
<0.01
0.01
0.14
0.04
0.03
<0.01
0.06
0.13
0.44
0.04
0.02
1.47
Hyundai
1.00
0.02
0.04
0.06
0.03
0.15
0.08
<0.01
0.01
0.09
0.04
0.05
<0.01
0.06
0.15
0.39
0.03
0.01
1.42
Nissan
1.00
0.03
0.06
0.09
0.03
0.21
0.03
<0.01
0.01
0.04
0.04
0.08
<0.01
0.06
0.18
0.43
0.06
0.01
1.49
Toyota
1.00
0.04
0.05
0.08
0.03
0.19
0.06
<0.01
0.01
0.07
0.04
0.03
<0.01
0.06
0.12
0.38
0.09
<0.01
1.48
vw
1.00
0.02
0.06
0.09
0.03
0.20
0.03
<0.01
0.01
0.04
0.10
0.02
<0.01
0.06
0.17
0.41
0.02
0.05
1.43
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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
Company
DaimlerChrysler
Ford
GM
Honda
Hyundai
Nissan
Toyota
VW
Weighted Average
Annual Production (number of
vehicles) (2007)
4,635,601
6,247,506
9,349,818
3,911,814
2,617,725
3,431,398
8,534,690
6,267,891
RPE Multiplier
1.47
1.45
1.45
1.47
1.42
1.49
1.48
1.43
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.
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SECTION 4
INDIRECT COST MULTIPLIER ESTIMATION
This section outlines calculations of 1C 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 1C 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 1C 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 1C 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).
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Table 4-1. Weighted Average 1C 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
Healthcare 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 1C 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.
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Technology
Complexity
[V
, >
\s
Innovation
Scope
Impact on
Operations
|\
, >
\/
Impact on
TnHirprt Cost
Contributors
Figure 4-1. Impacts of Technology Complexity on 1C 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
c
+- » 6Q
O ( <— <
1 "§
0 c
1> CH
O o
S s
^ °
S oo
00 C
^ ^
Reinforced Overturned
Incremental
Innovation
Architectural
Innovation
Modular
Innovation
Differential
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.
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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
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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 Innovation
Complexity Scope
One-Time R&D and
Retooling
Corporate and Dealer
Labor
Materials
Low
Incremental
innovation
Minimal
No additional
corporate labor needed
No labor training
needed. No impact on
corporate labor health
care, retirement,
corporate overhead
Purchase of new materials is
required
Medium
Modular
innovation
Some R&D efforts are
required
Architectural Some investment in new
innovation tools is required
Minimal additional
corporate labor needed
Labor training is
required. Minimal
impact on corporate
health care, retirement,
corporate overhead.
Purchase of new materials and
parts is required
High
Differential
innovation
Extensive R&D efforts
are required
Extensive investment in
new tools is required
Additional corporate
labor needed
Extensive labor
training is required.
Substantial impact on
corporate health care,
retirement, corporate
overhead
Purchase of new materials,
parts, and systems is required
11 Among the indirect cost contributors, retooling is captured in depreciation and amortization cost.
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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 1C 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:
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• 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 high-
complexity 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 CC>2 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.
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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 CC>2 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
R&D
Depreciation and
amortization
Maintenance, repair,
operations cost
Corporate Overhead
G&A
Retirement
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.
0.2
1.1
R&D is expected to increase with the complexity of the activity. For a low-
complexity 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 medium-
complexity activity, the additional R&D is expected to be slightly more than the
average level. For high-complexity, much more R&D is necessary.
0 0 1
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.
0 0 1
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.
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.
0 0 0.5
These values are expected to correspond to the values for G&A.
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Table 4-3. Short-Term Effects on Indirect Cost Contributors (continued)
Indirect Cost/Technology
Complexity
Low
Medium
High
Corporate Overhead
(continued)
Health care
Selling
Transportation
Marketing
Dealer new vehicle selling
cost
0 0
These values are expected to correspond to the values for G&A.
0
0
0.5
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.
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.
0.1
1
1.5
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 high-
complexity 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 high-
complexity technologies.
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Table 4-4. Long-Term Effects on Indirect Cost Contributors
Indirect Cost/Technology
Complexity
Low
Medium
High
Production Overhead
R&D
Depreciation and
amortization
Maintenance, repair,
operations cost
Corporate Overhead
G&A
Retirement
Health care
Selling
Transportation
Marketing
Dealer new vehicle selling
cost
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.
0
0
1
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.
0 0 1
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.
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.
0 0 0.5
These values are expected to correspond to the values for G&A.
0 0 0.5
These values are expected to correspond to the values for G&A.
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.
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.
0 0.3 1
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, low-
complexity activities are expected to have no additional costs, medium-
complexity activities are expected to have small additional costs, and high-
complexity activities will have an average value for dealer support.
4-10
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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 light-
duty 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 1C 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 1C 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 1C multipliers for
the different levels of complexity and time frames.
4-11
-------
4.5 Summary
1C 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 1C 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
-------
Table 4-5. Short- and long-Term 1C Multiplier Calculations
RPE
Multiplier
Approach
1C Multiplier Approach
Short -Term Effects
RPE and 1C Multiplier
Contributors
Manufacturing
Cost of sales
Production overhead
Warranty
R&D (product development)
Depreciation and amortization
Maintenance, repair, operations
cost
Total production overhead
Corporate Overhead
General and administrative
Retirement
Health
Total corporate overhead
Selling
Transportation
Marketing
Dealers
Dealer net profit
Dealer new vehicle selling cost
Total selling and dealer contributors
Sum of Indirect Costs
Net income
Other costs (not included in
contributing costs)
Total contribution to cost of sales
Weighted
Average
Industry
Indirect Cost
Contributors
to RPE
1.00
0.03
0.05
0.07
0.03
0.18
0.07
0.00
0.01
0.08
0.04
0.04
O.01
0.06
0.14
0.40
0.06
0.04
1.46
Low Technology
Complexity
Adjust- 1C
ment Multip-
Factor lier
1.00
1.20 0.04
0.20 0.01
0.00 0.00
0.00 0.00
0.04
0.00 0.00
0.00 0.00
0.00 0.00
0.00
0.00 0.00
0.00 0.00
0.10 0.01
0.01
0.05
1.05
Medium
Technology
Complexity
Adjust- 1C
ment Multip-
Factor lier
1.00
1.60 0.05
1.10 0.06
0.00 0.00
0.00 0.00
0.10
0.00 0.00
0.00 0.00
0.00 0.00
0.00
0.00 0.00
1.00 0.04
1.00 0.06
0.09
0.20
1.20
High Technology
Complexity
Adjust- 1C
ment Multip-
Factor lier
1.00
2.00 0.06
2.00 0.10
1.00 0.07
1.00 0.03
0.26
0.50 0.03
0.50 <0.01
0.50 <0.01
0.04
0.30 0.01
1.50 0.05
1.50 0.08
0.15
0.45
1.45
Long-Term Effects
Low Technology
Complexity
Adjust- 1C
ment Multip-
Factor lier
1.00
0.60 0.02
0.00 0.00
0.00 0.00
0.00 0.00
0.02
0.00 0.00
0.00 0.00
0.00 0.00
0.00
0.00 0.00
0.00 0.00
0.00 0.00
0.00
0.02
1.02
Medium
Technology
Complexity
Adjust- 1C
ment Multip-
Factor lier
1.00
0.80 0.02
0.00 0.00
0.00 0.00
0.00 0.00
0.02
0.00 0.00
0.00 0.00
1.00 0.01
0.01
0.00 0.00
0.00 0.00
0.30 0.02
0.02
0.05
1.05
High Technology
Complexity
Adjust- 1C
ment Multip-
Factor lier
1.00
1.00 0.03
0.30 0.02
1.00 0.07
1.00 0.03
0.14
0.50 0.03
0.50 <0.01
0.50 <0.01
0.04
0.30 0.01
0.00 0.00
1.00 0.06
0.07
0.26
1.26
-------
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 1C 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 1C 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 1C 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 1C 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 1C 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 1C 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
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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 1C 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://fmancialservices.house.gov/autostabilization.html.
5-2
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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 1C multiplier. A
change in the RPE multiplier will have a larger effect on the 1C 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 1C 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
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REFERENCES
DaimlerChrysler AG. 2005. DaimlerChrysler: Annual Report 2003. Available at:
http://www.daimler.com/dccom/0-5-660593-l-169901-l-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.daimlerchrysl er.com/Proj ects/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/executive-
orders/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/fm_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/fm_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.hyundai-
motor.com/download/Annual_Report_2005.pdf. Accessed on October 10, 2008.
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-------
Hyundai Motor Company. 2008. Annual Report 2007. Available at: http://csr.hyundai-
motor.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-ranking-
2007.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.nissan-
global.com/EN/IR/LIBRARY/AR/. Accessed on October 10, 2008.
Nissan Motor Company. 2008. Annual Report 2006-2007. Available at: http://www.nissan-
global.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.
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-------
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.
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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.I 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-l.
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-l). 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-l
-------
Table A-l. McKinsey's Automobile Industry Manufacturers' Cost Contributions to
MSRP
Cost Contributor Average Amount Per Vehicle ($)
Material cost (purchased parts)
Material cost (raw materials)
Manufacturing cost
Maintenance, repair, operations cost
Product development
Transportation
Sales & marketing
Depreciation and Interest
Warranty costs
General & administrative
Net profit
Wholesale price to dealer
Dealer gross
MSRP
10,030
1,770
2,400
2,000
1,600
500
1,200
1,150
600
500
750
22,500
1,600
24,100
Percent Share
41.6%
7.3%
10.0%
8.3%
6.6%
2.1%
5.0%
4.8%
2.5%
2.1%
3.1%
93.4%
6.6%
100.0%
Source: McKinsey & Company. 2003. Preface to the Auto Sector Cases.
Table A-2. Automobile Manufacturing Industry RPE
Data)
RPE Multiplier Contributor
Manufacturing
Manufacturing cost
Production Overhead
Warranty
R&D (product development)
Depreciation and amortization
Maintenance, repair, operations cost
Total production overhead
Corporate Overhead
Corporate overhead, retirement and health
Selling
Transportation, marketing, dealer support, dealer discount
Sum of Indirect Costs
Profit
RPE Multiplier
Multiplier (based
Relative to Cost of
Manufacturing
1.00
0.04
0.11
0.08
0.14
0.38
0.04
0.23
0.64
0.05
1.70
on McKinsey's
Share of RPE
Multiplier
0.59
0.03
0.07
0.05
0.08
0.22
0.02
0.14
0.38
0.03
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 1C 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 _
New vehicle sales
Dealer new vehicle selling cost _
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
0
w
A
B
C
D
E
Average Dealership Financial^ ($ Thousand)
New vehicle sales
New vehicle gross profit margin
New vehicle gross profit
New vehicle net profit
New vehicle selling cost
2003
19,359
0.044
848
147
701
2004
20,116
0.041
818
141
677
2005
19,469
0.039
768
44
724
2006
18,795
0.038
714
-25
739
2007
19,545
0.034
672
-41
713
Source /
Calculation
NADA
J.D. Power
A*B
NADA
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 1C 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
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' Cost of Sales
ON
R
0
w
A
B
C
D
E
F
G
H
Calculation of Dealer Profit
and Dealer Expense
Cost of sales 2007 ($ Billion)
Annual sales 2007 ($ Billion)
Dealer new vehicle gross margin
New vehicle sales ($ Billion)
New vehicle sales / Cost of sales
Line items for RPE multiplier
Dealer new vehicle net profit
Dealer new vehicle selling cost
Annual production 2007
Daimler
Chrysler1
$124.7
$190.3
3.9%
$197.7
1.59
0.004
0.06
4,635,601
Ford
$130.4
$154.0
3.9%
$160.0
1.23
0.003
0.04
6,247,506
GM
$143.0
$178.2
3.9%
$185.1
1.29
0.003
0.05
9,349,818
Honda
$65.4
$93.9
3.9%
$97.6
1.49
0.004
0.05
3,911,814
Hyundai
$53.5
$74.2
3.9%
$77.1
1.44
0.004
0.05
2,617,725
Nissan
$67.0
$88.7
3.9%
$92.2
1.38
0.004
0.05
3,431,398
Toyota
$150.2
$262.4
3.9%
$272.6
1.82
0.005
0.07
8,534,690
vw
$67.0
$149.2
3.9%
$155.0
2.31
0.006
0.08
6,267,891
Source/
Calculation
Annual
Reports
Annual
Reports
J.D. Power
(Table A-3)
B x (1 + C)
D/A
Weighted
Average
0.004
0.06
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 $4.4 billion in 2007, we used 0.05, the
McKinsey study estimate, to account for long-term profit. The share of retirement and health
care costs applicable to the RPE multiplier (see the discussion in Section 3.2.2) was calculated as
a ratio of selling, G&A, and other expenses to the sum of selling, administrative, and other
expenses and manufacturing labor cost. The remaining contributors to the RPE multiplier are
shown in Table A-6, which shows the result as 1.45 in 2007.
Table A-7 provides historical indirect cost contributors for GM. Here and in the
remainder of this appendix, historical indirect cost contributors were based on high-level cost
categories: selling, administrative, and other expenses; operating and other expenses; and
depreciation. Profit was also included as part of the calculation. Manufacturing costs are
presented in the companies' respective currency, and high-level cost contributors are presented
as a share of the cost of sales. The cost of sales numbers are not adjusted as in Table A-6, but
cited as they were stated in annual reports.
A-7
-------
Table A-6. General Motors RPE Multiplier Calculations: 2007
RPE Multiplier Contributor
Expense
($
Billions)
Relative to
Cost of Sales
Calculation and Source
Vehicle Manufacturing
Cost of sales
143.0
1.00
Calculated Manufacturing Cost + 70% x
(Retirement + 55% x Health Care) -
Maintenance, Repair, Operations Cost
Production Overhead
Warranty
R&D (product development)
Depreciation and amortization
Maintenance, repair, operations cost
Total production overhead
Corporate Overhead
General and administrative
Retirement
Health
Total corporate overhead
Selling
Transportation
Marketing
Dealers
Dealer new vehicle net profit
Dealer new vehicle selling cost
Total selling and dealer contributors
Sum of Indirect Costs
Net income
Other costs (not included as
contributors)
RPE Multiplier
4.7
8.1
8.3
4.0
25.0
9.4
0.9
0.7
11.0
5.0
6.5
8.2
7.9
27.6
7.6
8.8
0.03
0.06
0.06
0.03
0.17
0.07
0.01
0.01
0.08
0.04
0.05
O.OO
0.06
0.14
0.40
0.05
0.06
1.45
[p. 72, General Motors, 2007]
[p. 86, General Motors, 2007]
[p. 67, General Motors, 2007]
[p. 9, Sierra, 2007]
[p. 49, General Motors, 2007]
30% x ( Pension Expense (1.799) [p. 84,
General Motors, 2007] + Pension
Contributions (0.937) [p. 84, General
Motors, 2007])
30% x ( Payroll and Benefits (2.148) [p.
92, General Motors, 2007])
Based on McKinsey study
Advertising [p. 86, General Motors,
2007] + Dealer Advertising [p. 52,
General Motors, 2007]
RTI calculation
RTI calculation
Based on McKinsey study
Legacy Costs3 + Automotive Interest and
Other Income (0.961) [p. 50, General
Motors, 2007]
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
Selling, administrative, and other 0.09
expenses
Operating and other expenses 0.05
Depreciation 0.05
Profit -0.23
Other expenses (not included as 0.07
contributor)
Sum of main indirect cost contributors 0.96
(including profit)
2006
0.08
0.05
0.05
-0.01
0.07
1.17
2005
0.08
0.06
0.06
-0.07
0.08
1.13
2004
0.08
0.06
0.04
0.02
0.08
1.19
2003
0.08
0.06
0.04
0.03
0.07
1.21
2002
0.08
0.06
0.04
0.01
0.05
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
Vehicle Manufacturing
Cost of sales
Production Overhead
Warranty
R&D (product development)
Depreciation and amortization
Maintenance, repair, operations
cost
Expense
(€ Million)
124,668.1
5,267.7
5,331.0
13,614.0
3,490.7
Total production overhead
Corporate Overhead
General and administrative
Retirement
Health
Total corporate overhead
Selling
Transportation
Marketing
Dealers
Dealer new vehicle net profit
Dealer new vehicle selling cost
Total selling and dealer
contributors
Sum of Indirect Costs
Net income
Other costs (not included as
contributors)
6,292.6
922.8
185.6
7,401.0
4,389.7
2,563.0
7,158.2
6,873.9
20,984.8
3,227.0
4,699.3
RPE Multiplier
Relative to
Cost of Sales
1.00
0.04
0.04
0.11
0.03
0.22
0.05
0.01
Less than 0.01
0.06
0.04
0.02
<0.01
0.06
0.12
0.40
0.07
0.04
1.47
Calculation and Source
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]
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]
Based on McKinsey study
[p. 162, DaimlerChrysler, 2006]
RTI calculation
RTI calculation
[p. 214, DaimlerChrysler, 2006]
Interest Paid (4,193) [p. 214,
DaimlerChrysler, 2006] + 45% x Health
Care
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
Selling, administrative, and other expenses
Operating and other expenses
Depreciation
Profit
Other expenses (not included as contributor)
Sum of main indirect cost contributors
(including profit)
2006
0.19
0.05
0.11
0.03
0.01
1.38
2005
0.20
0.05
0.10
0.02
0.01
1.38
2004
0.21
0.05
0.10
0.02
0.01
1.37
2003
0.21
0.05
0.11
0.00
0.01
1.37
2002
0.05
0.04
0.12
0.04
0.01
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-l-169901-l-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-ll
-------
Table A-10. Ford Motor Company RPE Multiplier Calculations: 2007
RPE Multiplier Contributor
Expense
(S Billions)
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
130.4
3.3
2.9
6.8
3.7
1.00
0.03
0.02
0.05
0.03
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 -
Transportation
[p. 117,Ford,2007a]
[p. 63, Ford, 2007a] - Transportation
[p. 56, Ford, 2007b]
[p. 9, Sierra, 2007]
Total production overhead
16.6
0.13
Corporate Overhead
General and administrative
Retirement
Health
Total corporate overhead
Selling
Transportation
Marketing
Dealers
15.8
0.5
0.4
16.7
4.6
5.4
0.12
0.00
0.00
0.13
0.04
0.04
Selling, Administrative and Other Expenses (21.2)
[FS2, Ford, 2007] - Advertising (5.4) [p. 64, Ford,
2007a] - Transportation
30% x Pensions (1.128+0.885) [107, Ford, 2007a]
30% x 55% x Health Carea
Based on McKinsey study
Advertising (5.4) [p. 56, Ford, 2007b]
Dealer new vehicle net profit
Dealer new vehicle selling
cost
Total selling and dealer
contributors
Sum of Indirect Costs
Net income
7.5
7.2
24.7
6.9
0.01
0.06
0.14
0.39
0.05
RTI calculation
RTI calculation
Based on McKinsey
study
Other costs (not included as
contributors)
14.3
0.11
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]+
30% x 45% x Health Carea
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-l 1 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-ll. Ford Motor Company Main Indirect Cost Contributors (as a Share of Cost of
Sales)
Indirect Cost Contributor 2007
Selling, administrative, and other expenses 0.10
Operating and other expenses 0.01
Depreciation 0.05
Profit -0.02
Other expenses (not included as contributor) 0.06
Sum of main indirect cost contributors 1.13
(including profit)
2006
0.09
0.01
0.04
-0.13
0.06
1.01
2005
0.08
0.04
0.04
-0.03
0.06
1.13
2004
0.08
0.04
0.05
0.03
0.06
1.20
2003
0.08
0.04
0.07
0.00
0.08
1.19
2002
0.08
0.04
0.08
-0.01
0.10
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
RPE Multiplier Contributor
Expense
(¥ Billion)
Relative to
Cost of Sales
Calculation and Source
Vehicle Manufacturing
Cost of sales
7,609.8
1.00
Cost of Sales [p. 54, Honda, 2007] + 70% x
Pensions and Postretiremen! Benefits -
Maintenance, Repair, Operations Costs
Production Overhead
Warranty
R&D (product development)
Depreciation and amortization
Maintenance, repair,
operations cost
Total production overhead
Corporate Overhead
General and administrative
113.5
551.8
371.5
213.1
1,249.8
0.01
0.07
0.05
0.03
0.16
[p. 109, Honda, 2008]
[p. 2, Honda, 2008]
[p. 11 3, Honda, 2008]
[p. 9, Sierra, 2008]
Selling, General and Administrative
(1818.2)
[p. 72, Honda, 2008] - Transportation -
Marketing [p. 78, Honda, 2008] - Dealer
Retirement
Health
Total corporate overhead
Selling
Transportation
Marketing
Dealers
Dealer new vehicle net profit
Dealer new vehicle selling cost
Total selling and dealer
contributors
Sum of Indirect Costs
Net income
Other costs (not included as
contributors)
RPE Multiplier
883.7
10.6
220.9
1,115.2
267.9
247.0
436.9
419.6
1,371.5
268.6
114.6
0.12
Less than 0.01
0.01
0.15
0.04
0.03
<0.01
0.06
0.13
0.44
0.04
0.02
1.47
Support
30% x Retiree Health Care [p. 9, Sierra,
2007]
Based on McKinsey study
[p. 78, Honda, 2008]
RTI calculation
RTI calculation
Net Income [p. 72, Honda, 2008]
Interest + Other Expenses [p. 72, Honda,
200]
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
Selling, administrative, and other expenses 0.23
Operating and other expenses NA
Depreciation 0.05
Profit 0.08
Other expenses (not included as contributor) 0.02
Sum of main indirect cost contributors (including 1.35
profit)
2006
0.24
NA
0.04
0.09
0.01
1.36
2005
0.25
NA
0.04
0.08
0.01
1.37
2004
0.27
NA
0.04
0.08
0.00
1.39
2003
0.27
NA
0.04
0.08
0.02
1.41
2002
0.26
NA
0.04
0.07
0.02
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
Production Overhead
Warranty 975,825.0 0.02
R&D (product development) 2,193,479.0 0.04
Depreciation and
amortization
3,293,479.0 0.06
Maintenance, repair,
operations cost 2,786,433.0 0.03
Cost of Sales [p. 52, Hyundai, 2008] + 70% x
Payments of Severance Benefits - Research
and Development - Maintenance, Repair,
Operations Costs
[p. 109, Hyundai, 2008]
[p. 86, Hyundai, 2008]
Depreciation [p. 56, Hyundai, 2008] +
Amortization of intangibles [p. 56, Hyundai,
2008]
[p. 9, Sierra, 2007]
Total production overhead
Corporate Overhead
General and administrative
9,249,216.0
0.15
Retirement
Health
4,038,378.0
241,712.4
389,450.6
0.08
Less than 0.01
0.01
Selling and Administrative Expenses [p. 109,
Hyundai, 2008] - Export Related Expenses -
Sales Promotion - Sales Commission - Sales
Warranties - Freight and Warehousing - Rent
- Travel - Research - Depreciation -
Amortization
30% x Payment of Severance Benefits [p. 57,
Hyundai, 2008]
30% x Retiree Health Care [p. 9, Sierra, 2008]
Total corporate overhead
Selling
Transportation
Marketing
Dealers
Dealer new vehicle net
profit
Dealer new vehicle selling
cost
4,669,541.0 0.09
1,975,596.0 0.04
2,392,644.0 0.05
2,981,515.7 <0.01
2,863,122.9 0.06
Export Related Expenses + Freight and
Warehousing + Rent + Travel [all p. 109,
Hyundai, 2008]
Sales Promotion [p. 109, Hyundai, 2008]
RTI calculation
RTI calculation
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
Other costs (not included as
contributors) 430,631.0 0.01
[p. 69, Hyundai, 2008]
Interest Expense [p. 52, Hyundai, 2008]
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
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Hyundai Motor Company. 2008. Annual Report 2007. Available at: http://csr.hyundai-
motor.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
Selling, administrative, and other expenses
Operating and other expenses
Depreciation
Profit
Other expenses (not included as contributor)
Sum of main indirect cost contributors (including
profit)
2007
0.20
NA
0.05
0.03
NA
1.28
2006
0.23
NA
0.06
0.03
NA
1.32
2005
0.23
NA
0.05
0.05
NA
1.33
2004
0.29
NA
0.04
0.04
NA
1.37
NA = Not available
Sources: Hyundai Motor Company. 2006. Annual Report 2005. Available at: http://csr.hyundai-
motor.com/download/Annual_Report_2005.pdf. Accessed on October 10, 2008.
Hyundai Motor Company. 2008. Annual Report 2007. Available at: http://csr.hyundai-
motor.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
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Table A-16. Nissan Motor Company RPE Multiplier Calculations: 2007
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
7,789,660.3
1.00
222,390.0 0.03
464,839.0 0.06
705,380.0 0.09
218,110.5 0.03
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
1,610,719.5 0.21
267,054.0
0.03
Selling, General, and Administrative
Costs [p. 50, Nissan, 2008] -
Transportation - Marketing - Research
and Development
Retirement
Health
Total corporate overhead
Selling
Transportation
Marketing
Dealers
Dealer new vehicle net profit
Dealer new vehicle selling
cost
Total selling and dealer
contributors
Sum of Indirect Costs
Net income
Other costs (not included as
contributors)
RPE Multiplier
21,079.5
1,635.8
289,769.4
274,283.8
658,281.2
447,264.6
429,504.2
1,809,333.8
460,796.0
93,343.0
Less than 0.01
0.01
0.04
0.04
0.08
0.06
0.06
0.18
0.43
0.06
0.01
1.49
30% x Retirement Benefit Expenses
30% x Retiree Health Care [p. 9,
Sierra, 2007]
Based on McKinsey study
Based on McKinsey study
RTI calculation
RTI calculation
[p. 50, Nissan, 2008]
Other, net [p. 50, Nissan, 2008]
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
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Nissan Motor Company. 2008. Annual Report 2006-2007. Available at: http://www.nissan-
global.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
Selling, administrative, and other 0.21
expenses
Operating and other expenses 0.08
Depreciation 0.10
Profit 0.06
Other expenses (not included as 0.02
contributor)
Sum of main indirect cost contributors 1 .44
(including profit)
2006
0.22
0.06
0.09
0.07
0.02
1.44
2005
0.22
0.01
0.08
0.08
0.02
1.39
2004
0.24
0.09
0.09
0.10
0.02
1.51
2003
0.25
0.08
0.08
0.10
0.01
1.51
2002
0.26
0.01
0.08
0.08
0.03
1.43
Sources: Nissan Motor Company. 2006. Annual Report 2004-2005. Available at: http://www.nissan-
global.com/EN/IR/LIBRARY/AR/. Accessed on October 10, 2008.
Nissan Motor Company. 2008. Annual Report 2006-2007. Available at: http://www.nissan-
global.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
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Table A-18. Toyota Motor Company RPE Multiplier Calculations: 2007
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
17,463,582.6
616,133.0
890,700.0
1,382,594.0
488,980.3
1.00
0.04
0.05
0.08
0.03
Cost of Product Sold [p. 71, Toyota,
2007] - 50% x Research and
Development + 70% x Pensions
Warranties Paid Through the Year [p.
109, Toyota, 2007] + Provisions for
Warranties [p. 109, Toyota, 2007]
[p. 79, Toyota, 2007]
Depreciation [p. 94, Toyota, 2007]
[p. 9, Sierra, 2007]
Total production overhead
Corporate Overhead
General and administrative
3,378,407.3 0.19
969,568.1 0.06
Selling, General, and Administrative -
50% x Research and Development -
Advertising - Transportation
Retirement
Health
Total corporate overhead
Selling
Transportation
Marketing
Dealers
Dealer new vehicle net profit
Dealer new vehicle selling cost
Total selling and dealer
contributors
Sum of Indirect Costs
Net income
Other costs (not included as
contributors)
RPE Multiplier
83,765.7 Less than 0.01
130,976.9
1,184,310.7
614,914.9
451,182.0
1,002,719.3
962,902.4
3,031,718.5
1,644,032.0
49,326.0
0.01
0.07
0.04
0.03
0.06
0.06
0.12
0.38
0.09
0.00
1.48
30% x Pensions
30% x Retiree Health Care
2007]
Based on McKinsey study
Advertising [p. 97, Toyota,
RTI calculation
RTI calculation
[p. 96, Toyota, 2007]
[p. 9, Sierra,
2007]
Interest Expense [p. 94, Toyota, 2007]
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
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Table A-19. Toyota Motor Company Main Indirect Cost Contributors (as a Share of Cost
of Sales)
Indirect Cost Contributor 2007
Selling, administrative, and other 0.14
expenses
Operating and other expenses 0.05
Depreciation 0.08
Profit 0.09
Other expenses (not included as 0.00
contributor)
Sum of main indirect cost contributors 1.35
(including profit)
2006
0.14
0.04
0.07
0.08
0.00
1.33
2005
0.14
0.03
0.07
0.08
0.00
1.31
2004
0.13
0.03
0.07
0.09
0.00
1.32
2003
0.16
0.04
0.07
0.06
0.00
1.33
2002
0.16
0.04
0.07
0.05
NA
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
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Table A-20. Volkswagen Group RPE Multiplier Calculations: 2007
RPE Multiplier Contributor
Expense
(€ Million)
Relative to
Cost of Sales
Calculation and Source
Vehicle Manufacturing
Cost of sales
82,595.6
1.00
Cost of Sales [p. 135, VW, 2007] -
Warranty -R&D - MRO + 70% x
Pensions and Postretirement Benefits
Production Overhead
Warranty
R&D (product development)
Depreciation and amortization
Maintenance, repair, operations
cost
Total production overhead
Corporate Overhead
General and administrative
Retirement
Health
2,056.3
4,653.3
7,278.0
2,312.7
16,300.3
2,453.0
386.4
17.3
0.02
0.06
0.09
0.03
0.20
0.03
Less than 0.01
0.01
Based on McKinsey study
Based on McKinsey study
[p. 133, VW, 2007]
[p. 9, Sierra, 2007]
[p. 135, VW, 2007]
30% x Old-Age Pensions [p. 143
2007]
30% x Retiree Health Care [p. 9,
2007]
,VW,
Sierra,
Total corporate overhead
Selling
Transportation
Marketing
Dealers
Dealer new vehicle net profit
Dealer new vehicle selling cost
2,856.7
7,864.0
1,410.0
4,742.5
4,554.1
0.04
0.10
0.02
<0.01
0.06
Distribution Expenses - Marketing
Selling, general and administrative
expense - Administrative Expenses [p.
139, VW, 2007]
RTI calculation
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
Other costs (not included as
contributors) 3,799.0 0.05
RPE Multiplier 1.43
[p. 142, VW, 2007]
Financial Result [p. 142, VW, 2007]
Sources: Sierra Research, Inc. November 21, 2007.
Changes in Retail Price Equivalent (RPE)
"Study of Industry—Average Mark-Up Factors Used to Estimate
for Automotive Fuel Economy and Emissions Control Systems."
McKinsey & Company. 2003. Preface to the Auto Sector Cases.
A-23
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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
Selling, administrative, and other expenses 0.12
Operating and other expenses 0.05
Depreciation 0.08
Profit 0.05
Other expenses (not included as contributor) NA
Sum of main indirect cost contributors 1.29
(including profit)
2006
0.13
0.06
0.09
0.02
NA
1.29
2005
0.13
0.04
0.09
0.01
NA
1.28
2004
0.13
0.04
0.10
0.01
NA
1.27
2003
0.14
0.04
0.09
0.01
NA
1.29
2002
0.13
0.05
0.08
0.04
NA
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
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