## July 2010



# Heavy Duty Truck Retail Price Equivalent and Indirect Cost

Multipliers

Draft Report

Prepared for

Chi Li Office of Transportation and Air Quality Assessment and Standard Division

2000 Traverwood Dr. Ann Arbor, MI 48105

Prepared by

Alex Rogozhin Michael Gallaher Anthony Lentz RTI International 3040 Cornwallis Road Research Triangle Park, NC 27709

Walter McManus Transportation Research Institute

University of Michigan 2901 Baxter Road Ann Arbor, MI 48109

RTI Project Number 0211577.003.002_________________________________ RTI International is a trade name of Research Trian gle Institute.



### RTI Project Number 0211577.003.002



# Heavy Duty Truck Retail Price Equivalent and Indirect Cost

Multipliers

Draft Report

Prepared for

Chi Li Office of Transportation and Air Quality Assessment and Standard Division

2000 Traverwood Dr. Ann Arbor, MI 48105

Prepared by

Alex Rogozhin Michael Gallaher Anthony Lentz RTI International 3040 Cornwallis Road Research Triangle Park, NC 27709

Walter McManus Transportation Research Institute

University of Michigan 2901 Baxter Road Ann Arbor, MI 48109

### iii CONTENTS

Section Page

1 Introduction ......................................

................................................... .......................... 1-1

2 Approaches to Estimate Indirect Costs Without Using Multipliers.............................. 2-1

3 RPE Multiplier ....................................

................................................... ....................... 3-1

3.1 Previously Published Studies on RPE Multiplier .... ............................................ 3-1

3.2 Description of Cost Contributors to RPE Multiplier ........................................... 3-1

3.3 Data Sources ......................................

................................................... ............... 3-2

3.4 Adjustments to RPE Multiplier Contributors ........ .............................................. 3-4

3.5 Engine vs. Truck Manufacturer Multipliers.......... ............................................... 3-8

3.6 Company-Level RPE Multipliers .....................

................................................... 3-8

3.7 Industry Average RPE Multipliers...................

................................................... . 3-9

4 IC Multiplier .....................................

................................................... ......................... 4-1

4.1 Technology Complexity and Impact on Operations .... ........................................ 4-2

4.2 Time Frame and Impact on Operations ............... ................................................ 4- 3

4.3 Adjustment Factors to Cost Contributors ........... ................................................. 4 -3

4.4 Industry Average IC Multipliers ...................

................................................... .... 4-7

4.5 IC Multipliers and Net Income .....................

................................................... .... 4-7

5 Example Technologies ..............................

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

5.1 Low Complexity: Single Wide Tires .................

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

5.2 Medium Complexity: Engine Turbo Compounding ....... ..................................... 5-1

5.3 High Complexity: Hybrid Electric Powertrains ...... ............................................. 5-2

### iv

6 RPE Multiplier Approach vs. Integrated IC Multiplie r and Market Model Approach ..........................................

................................................... .......................... 6-1

6.1 Market Model and RPE Multiplier ...................

................................................... 6-1

7 Summary and Conclusion ............................

................................................... .............. 7-1

8 References ........................................

................................................... .......................... 8-1

Appendix

A RPE Multiplier Calculations for Individual Manufa cturers ................................ A-1

LIST OF FIGURES

Number Page

6-1. RPE Multiplier vs. IC Multiplier Approach .........

................................................... ..... 6-2

LIST OF TABLES

Number Page

3-1. RPE Multipliers in Previous Studies................

................................................... .......... 3-2 3-2. RPE Multiplier Cost Contributors ..................

................................................... ........... 3-3 3-3. RPE Multipliers and Cost Contributors: 2008 .......

................................................... .... 3-5 3-4. Weighted RPE Multipliers: 2008 ....................

................................................... ........... 3-9 4-1. Weighted Average IC Multiplier Contributors to RPE: 2008 ...................................... 4-2 4-2. Short-term Adjustment Factors to Indirect Cost Cont ributors for Light Duty Vehicles: Consensus Approach.......................

................................................... ........... 4-4 4-3. Long-Run Adjustment Factors to Indirect Cost Contri butors for Light Duty Vehicles: Consensus Approach.......................

................................................... ........... 4-4 4-4. Short-Term Adjustment Factors to Indirect Cost Cont ributors for Light Duty Vehicles: Delphi-Based Method .....................

................................................... ........... 4-5 4-5. Long-Term Adjustment Factors to Indirect Cost Contr ibutors for Light Duty Vehicles: Delphi-Based Method .....................

................................................... ........... 4-5 4-6. Resultant Short-Term Adjustment Factors to Indirect Cost Contributors for Light Duty Vehicles ...............................

................................................... .................... 4-6

### v

4-7. Resultant Long-Term Adjustment Factors to Indirect Cost Contributors for Light Duty Vehicles ...............................

................................................... .................... 4-6 4-8. Short- and Long-Term IC Multiplier Calculations for Engine Manufacturers: 2008...............................................

................................................... ............................. 4-8 4-9. Short- and Long-Term IC Multiplier Calculations for Truck Manufacturers: 2008...............................................

................................................... ........................... 4-10 4-10. Long-Term Indirect Cost Multipliers with Net Income Included ............................... 4-12

### 1-1 SECTION 1
INTRODUCTION

In order to produce a unit of output, heavy duty tr uck manufacturers incur direct and
indirect costs. Direct costs include cost of materi als and labor costs. Indirect 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). Similarly to direct costs, indirect costs are generally recovered by allocating a share of the costs to each unit of goo d sold (Vyas, Santini, and Cuenca, 2000). Although it is possible to account for direct costs allocated to each unit of good sold, it is more challenging to account for indirect costs allocated to a unit of good sold. To make a cost analysis process more feasible, markup factors, which relate indirect costs to the changes in direct costs, have been developed. These factors are often referr ed to as retail price equivalent (RPE) multipliers.

Cost analysts and regulatory agencies (including th e U.S. Environmental Protection Agency [EPA]) have frequently used these multiplier s to predict the resultant impact on costs associated with heavy duty truck manufacturers’ res ponses to regulatory requirements. Clearly the best approach to determining the impact of chan ges in direct manufacturing costs on a manufacturer’s indirect costs would be to actually estimate the cost impact on each indirect cost element. However, doing this within the constraints of an agency’s time or budget is not always feasible, or the technical, financial, and accounti ng information to carry out such an analysis may simply be unavailable. Given this, EPA has continue d to use RPE multipliers for some of their regulatory cost analyses.

RPE multipliers provide, at an aggregate level, the relative shares of revenues 1 

### to direct manufacturing costs. The numerator of this ratio co mprises direct costs, indirect costs, and net
income:

RPE multiplier = (direct costs + indirect costs + net income)/(direct costs)

Using RPE multipliers implicitly assumes that incre mental changes in direct manufacturing costs produce common incremental chan ges in all indirect cost contributors as well as net income. A concern in using the RPE mult iplier in cost analysis for new technologies (which result from regulations requiring reductions in emissions) is that the indirect costs of

1 Revenue = Direct Costs + Indirect Costs + Net Inco me

### 1-2

vehicle modifications are not likely to be the same for different technologies. For example, less complex technologies could require fewer R&D effort s or less warranty coverage than more complex technologies. In addition, some simple tech nological adjustments may, for example, have no effect on the number of corporate personnel (Rogozhin et al., 2010).

To address this concern, modified multipliers have been developed. These multipliers are referred to as indirect cost multipliers (or IC mul tipliers). In contrast to RPE multipliers, IC multipliers assign unique incremental changes to ea ch indirect cost contributor.

IC multiplier = (direct cost + adjusted indirect c ost)/(direct cost)

The incremental change in indirect cost contributor s varies based on the complexity of the technology and the time frame under considerati on. Further, there is no reason to expect that the contributors would be the same for engine manuf acturers as for truck manufacturers. This report uses the methodology developed for “Automobi le Industry Retail Price Equivalent and Indirect Cost Multipliers Report” (the “LD RPE/IC s tudy”) (Rogozhin, Gallaher, and McManus, 2009). This report develops IC multipliers for the heavy duty truck manufacturing industry using financial data from, for reasons highlighted below, Hino, Cummins, PACCAR, Navistar, Daimler, and Volvo.

We derived two separate sets of IC multipliers: one for engine manufacturers (based on the data from Cummins and Hino) and another for hea vy duty truck manufacturers (based on the information from PACCAR, Navistar, Daimler, and Vol vo). Cummins’ market share for heavy duty truck engines in North America equaled 45% in 2008 (Cummins, 2009), and Hino is one of the largest suppliers of heavy duty truck engines i n Asia. The four heavy duty truck companies account for an 80% share of the heavy duty truck in dustry in North America (IBIS, 2010). Therefore, financial information from these compani es serves as a good representation of the U.S. heavy duty engine and truck industry as a whol e.

The remainder of the report is structured as follow s: Section 2 discusses published studies that have attempted to estimate indirect costs with out using cost multipliers. Section 3 describes the methodology, sources, and calculations of the R PE multiplier for the heavy duty engine and truck manufacturing industries. Section 4 describes the methodology and calculations of the IC multipliers for the same industries. Section 5 pres ents example technologies and the IC multipliers associated with them. Section 6 compare s the RPE multiplier approach with the integrated IC multipliers and market model approach . Section 7 presents a summary of the

### 1-3

findings and our conclusions, and Appendix A outlin es detailed calculations of the RPE multipliers for individual manufacturers.

### 2-1 SECTION 2
APPROACHES TO ESTIMATE INDIRECT COSTS WITHOUT USING MULTIPLIERS

This section describes studies that estimate indire ct costs in the process of estimating total production costs. These studies do not rely o n the use of multipliers but instead estimate indirect costs by adding overhead costs, distributi ng overhead costs in proportion to activities performed on a product during manufacturing, and ma thematical modeling.

There is a set of studies that developed a “bottom- up” approach to calculating indirect costs, which estimate overhead costs by summing all overhead costs (for example, Son [1991]). This method requires detailed information about res ources consumed to produce a product, including purchasing, processing, and maintenance c osts. EPA also used a similar approach for its regulatory analyses of rules on nonroad diesel and on locomotive and marine compression ignition engines. In those analyses, EPA calculated R&D and tooling components of indirect costs (e.g., EPA, 2004; EPA, 2008).

Activity-based costing (ABC), developed by Cooper a nd Kaplan (1988), is another
method to estimate indirect costs. This method dist ributes the overhead costs in proportion to the activities performed on a product to manufacture it . The method uses activity time estimates such as labor rates (direct labor costs or direct labor hour rates) or volume-based rates (machine hour, material cost, or units produced) as bases to calcu late overhead rates.

Mathematical modeling has also been used to calcula te indirect costs for an Asian electrical engineering company. Niazi et al. (2007) estimated indirect costs by modeling material
and time-related overhead costs.

When in-depth information and resources are availab le, one of these approaches might be appropriate. However, when faced with limited infor mation or time constraints, the multiplier approach provides an effective and efficient way to estimate indirect costs. In the next section, we present studies that estimated RPE multipliers i n the past and describe our methodology to estimate RPE and IC multipliers.

### 3-1 SECTION 3
RPE MULTIPLIER

The RPE multiplier is a ratio that relates direct c osts, indirect costs, and net income 1 

### to direct costs. When multiplied by the direct costs o f a new technology, this multiplier is intended to estimate the effects of the new technology on th e costs associated with heavy duty truck manufacturers’ responses to regulatory requirements . RPE multipliers are typically calculated from a heavy duty truck company’s financial stateme nts under the implicit assumption that all technologies in a company bear the same proportion of indirect costs. The RPE multiplier is
calculated as follows:

Cost Direct Income) Net Cost Indirect ( 1 Cost Direct Income)

Net Cost Indirect Cost (Direct Multiplier RPE + + = + +

=



### 3.1 Previously Published Studies on RPE Multiplier
The authors of this report were unable to find any studies that estimated RPE multipliers specifically for heavy duty truck manufacturers (th e 1985 Jack Faucett Associates report to EPA included multipliers for heavy duty engine manufact urers but none for heavy duty truck manufacturers). However, many of the cost contribut ors developed for light duty vehicles are applicable to heavy duty vehicles. Several studies estimated RPE multipliers for the light duty automobile manufacturing industry. These values are presented in Table 3-1 and range between 1.26 (a value developed for EPA in 1985) and 2.0 (t he value for outsourced parts estimated by researchers at Argonne National Laboratory). The ra nge of multiplier values should serve as an indicator that using one multiplier for all new tec hnologies should be considered an approximation in the absence of better information.

3.2 Description of Cost Contributors to RPE Multiplier
Table 3-2 presents the contributors that constitute the RPE multiplier. Components of the multiplier include manufacturing costs, production overhead costs, corporate overhead costs, manufacturer selling costs, and manufacturer net in come. In addition, we accounted for dealer costs of selling new vehicles and dealer net income from selling new vehicles. For each manufacturer, we gathered financial information usi ng annual and 10-K reports and systematically assigned it to the contributors list ed in Table 3-2.

1 Net income is the accounting term that is used for measuring accounting profit.

### 3-2

Table 3-1. RPE Multipliers in Previous Studies

Study Year Findings

Jack Faucett Associates, EPA 1985 1.26
Spinney et al. 1998 1.5
Vyas, Santini, and Cuenca, Argonne National Laborat ory 2000 2.0 for components developed internally 1.5 for outsourced components

National Research Council 2002 1.4
McKinsey & Company 2003 1.7

Sierra Research, Inc. for Alliance of Automobile Ma nufacturers 2007 2.0 at least
Rogozhin et al. 2009 1.46



### 3.3 Data Sources
We used publicly available sources so the results o f this study would be replicable and transparent. We gathered financial information for two heavy duty engine manufacturers (Cummins, Hino) and four heavy duty truck manufactu rers (PACCAR, Navistar, Daimler, and Volvo). Using several manufacturers instead of one provided more robustness to the results.

The majority of the information for the analysis wa s obtained from manufacturers’ annual reports and 10-K reports to the Securities and Exch ange Commission (SEC). The analysis was conducted using 2008 data for all manufacturers. Un fortunately, direct and indirect costs are not standard accounting terms. As a result, each manufa cturer presented the breakdown of costs in a unique fashion, while still following acceptable ac counting procedures. We tried to consolidate these costs in a systematic manner for each manufac turer to be able to average results for the industry.

Indirect costs associated with new technologies are expected to differ based on the degree of complexity of the technology and the time frame involved. Technology-specific adjustment factors used in our methodology were developed for the LD RPE/IC report. These factors were estimated using two different methods: consensus ap proach and Delphi-based method. These methods are briefly described in the remainder of t his section. The estimates for both of these approaches are re-presented in Section 4.3 for conv enience. We believe that these factors are appropriate to use for the heavy duty truck industr y given the similar structures of the light duty vehicle and heady duty truck industries (e.g., simi lar R&D challenges, similar employee benefits, similar competitive environment).

### 3-3

Table 3-2. RPE Multiplier Cost Contributors

Contributor Description
Manufacturing (Direct Cost)
Manufacturing cost Cost of materials and labor cost
Production Overhead (Indirect Cost)
Warranty Cost of providing product warranty
R&D (research and development) Cost of developing a nd engineering the product
Depreciation and amortization Cost related to depre ciation and amortization of manufacturing facilities and equipment
Maintenance, repair, operations cost Costs related to maintenance, repair, and operations of manufactu ring facilities and equipment
Corporate Overhead (Indirect Cost)

General and administrative (G&A) Costs related to s alaries of nonmanufacturing labor, operations of corporate office, etc.
Retirement Cost of pension for nonmanufacturing lab or

Health care Costs of health care for nonmanufacturi ng labor
Selling (Indirect Cost)
Transportation Costs related to transporting manufa ctured goods
Marketing Costs related to advertising of the manuf actured goods (manufacturer costs).
Dealer (Indirect Cost)

Dealer new vehicle net income Net income to dealers from sales of new vehicles
Dealer new vehicle selling expense Costs related to sales of the new vehicles by dealers (dealer costs ).

Net Income Net income to manufacturers



### Consensus Approach: EPA’s National Vehicle and Fuel Emissions Laboratory assembled a team of engineers with experience working for aut o manufacturers to provide adjustment factors for the RPE multiplier cost contributors. T he team had among them 11 bachelor’s degrees in engineering and physics; 10 master’s degrees in engineering, atmospheric chemistry, and business; and one Ph.D. in mechanical engineering.

Together the team had approximately 100 years of ex perience working for auto and engine manufacturers and service companies plus exp ertise in a wide range of auto technologies, including (among others) engines, powertrains, onbo ard diagnostics, fuel economy, and

### 3-4

emissions controls. The team met five times over a period of 3 weeks and developed consensus estimates for adjustment factors that capture the d ifferences in the impact of low-, medium-, and high-complexity technologies on each of the cost co ntributors to the RPE multiplier.

Delphi-Based Method: EPA also used a process based on the Delphi method and developed a set of adjustment factors based on the technologies not considered in the RPE/IC report (Helfand and Sherwood, 2009). These technolo gies were representative of the low-, medium-, and high-complexity technology definitions as described in the LD RPE/IC report. The Delphi-based method used a panel of automotive expe rts who provided individual, anonymous estimates of the adjustment factors. These experts then met three times to discuss both the process and the estimates of adjustment factors. Af ter each meeting, experts were given an opportunity to change their answers.

3.4 Adjustments to RPE Multiplier Contributors
The way that costs are reported in annual reports m ay differ from one business to another. Because of this, assumptions and adjustments were n ecessary to arrive at RPE multipliers that would be consistent across companies. For example, we used “cost of sales” reported in annual reports as an estimate of direct costs. Cost of sal es refers to direct costs attributable to the production of the goods sold by a company, which in cludes the cost of the materials used in creating the good along with the direct labor costs used to produce the good. However, the exact expenses included in cost of sales might differ fro m one manufacturer to another (Forbes, 2010). Nevertheless, cost of sales was the best estimate o f direct costs reported by all companies.

In some cases, information from secondary sources, such as Heavy Duty Truck Manufacturers Industry Report by Supplier Relations LLC (referred to as “SR LLC report,” 2009) and Census (2009), was used to fill in the g aps. For instance, Cummins, Hino, PACCAR, and Daimler did not report maintenance, repair, and operations costs; the factors of 0.01 (for engine manufacturers Cummins and Hino) and 0.02 (fo r heavy duty truck manufacturers PACCAR and Daimler) were calculated using Census da ta (based on the data for the Other Engine Equipment Manufacturing Industry [NAICS 3336 18] and Heavy Duty Truck Manufacturing Industry [NAICS 336120]). Section A.1 of the appendix to this report provides more details about these adjustments. The results o f the procedure are presented in Table 3-3.

We also used data from the SR LLC report and Census to construct an industry average RPE multiplier for comparison purposes. The average equaled 1.42, which is higher than the

### 3-5Table 3-3. RPE Multipliers and Cost Contributors: 2008Cost ContributorEngine Manufacturers Truck ManufacturersVehicle ManufacturingHeavy DutyTruckIndustry(Reports)EngineManufacturersIndustryAverageTruckManufacturersIndustryAverage Hino Cummins PACCARNavistar Daimler VolvoManufacturing cost 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00Production OverheadWarranty 0.03 0.02 0.04 0.01 0.02 0.03 0.02 0.04 0.04R&D (product development) 0.05 0.04 0.05 0.03 0.040.03 0.03 0.05 0.06Depreciation and amortization0.05 0.03 0.04 0.04 0.03 0.06 0.03 0.03 0.06Maintenance, repair,operations cost 0.02 0.01 0.02 0.01 0.01 0.02 0.030.02 0.01Total production overhead 0.14 0.08 0.14 0.10 0.080.13 0.12 0.13 0.17Corporate OverheadGeneral and administrative 0.12 0.11 0.07 0.09 0.120.03 0.12 0.03 0.12Retirement 0.01 0.01 0.01 0.01 0.01 0.01 0.03 0.010.01Health 0.01 0.01 0.01 0.02 0.01 0.001 0.02 0.01 0.004Total corporate overhead 0.15 0.13 0.09 0.12 0.14 0.04 0.16 0.05 0.13SellingTransportation 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00Marketing 0.01 0.01 0.01 0.00 0.01 0.01 0.00 0.01 0.01(continued)

### 3-6Table 3-3. RPE Multipliers and Cost Contributors: 2008 (continued)Cost ContributorEngine Manufacturers Truck ManufacturersVehicle ManufacturingHeavy DutyTruckIndustry(Reports)EngineManufacturersIndustryAverageTruckManufacturersIndustryAverage Hino Cummins PACCARNavistar Daimler VolvoDealersDealer new vehicle netincome < 0.01 — < 0.01 — — < 0.01 < 0.01 < 0.01 < 0.01Dealer new vehicle sellingexpense 0.06 — 0.06 — — 0.06 0.06 0.06 0.06Total selling and dealer costs 0.08 0.01 0.08 0.010.01 0.08 0.07 0.08 0.08Sum of Indirect Costs0.37 0.23 0.31 0.23 0.23 0.24 0.35 0.26 0.38Net Income 0.05 0.05 0.05 0.02 0.06 0.09 0.01 0.070.04Other costs (not included incontributing costs) 0.00 0.01 0.00 0.01 0.01 0.00 0.00 0.00 0.01RPE multiplier 1.42 1.28 1.36 1.25 1.29 1.33 1.36 1.34 1.43

### 3-7

average calculated based on manufacturers’ annual r eports (1.28 for engine manufacturers and 1.36 for truck manufacturers). The reason for this difference could be that SR LLC report defined heavy duty industry based on U.S. Census NA ICS 336120 (Heavy Duty Truck Manufacturing Industry), 2 

### while the RPE multiplier calculations in this repo rt are based on four heavy duty truck and two heavy duty engine manufact urers.

Health care and retirement costs provided in manufa cturers’ annual reports include expenditures for both manufacturing and corporate l abor. The share of these costs related to manufacturing labor is a part of manufacturing expe nses and, therefore, was added to the manufacturing cost (direct cost). The share related to corporate workers is a part of indirect costs
and was counted in the health care and retirement c ost contributors. To determine how to attribute these shares, we looked at the Census dat a (Supplier Relations LLC, 2009). It reported salaries and wages separately. Salaries are the cos t of corporate labor and accounted for 30% of total labor cost, and wages are the cost of manufac turing labor and accounted for 70% of total labor cost. Using this information, we assumed that approximately 70% of workers were involved in manufacturing, while 30% were involved in corporate operations for both heavy duty engine and truck manufacturers. This assumption is consistent with manufacturing/corporate labor division calculated for the LD RPE/IC multipl ier study (Rogozhin et al., 2009).

Cummins, PACCAR, Navistar, Daimler, and Volvo did n ot report transportation costs. Thus, the industry average of 0.004 (industry avera ge based on SR LLC report) was used as a proxy. PACCAR, Daimler, and Volvo did not report ma rketing costs. The heavy duty trucks industry engages in business-to-business marketing rather than business-to-consumer marketing. Our judgment is that business-to-business marketing costs are significantly lower than businessto-consumer marketing costs, possibly as low as 3 t o 5% of business-to-consumer marketing costs per unit. We defined business-to-business mar keting costs as 20% of the business-toconsumer marketing costs per unit from Rogozhin et al. (2009) as an upper bound.

The only costs that were added (rather than redistr ibuted from one of the cost items reported in manufacturers’ annual reports) were dea ler new vehicle net income and dealer new vehicle selling expenses. These expenses are acquir ed by heavy duty truck dealers and are part of the final price of a vehicle. Given the similar str uctures of light duty vehicle and heavy duty

2 NAICS 336120 includes manufacturers of heavy duty truck chassis and assemblers of complete heavy duty trucks, buses, heavy duty motor homes, and other special pu rpose heavy duty motor vehicles for highways. It al so includes manufacturers of heavy duty motor vehicles and car bodies.

### 3-8

truck dealers (similar employee benefits, similar c ompetitive environment, etc.) the value from the LD RPE/IC multiplier report (Rogozhin et al., 2 009) was used as a proxy. 3



### Appendix A presents detailed calculations of cost c ontributors for each of the six manufacturers and industry averages based on the se condary sources.

3.5 Engine vs. Truck Manufacturer Multipliers
We calculated two separate RPE multipliers: one for heavy duty engine manufacturers and another for heavy duty truck manufacturers. The reason for differentiating between engine
and truck manufacturers was the difference in their target markets. Although engine manufacturers sell product primarily to heavy duty truck manufacturers, heavy duty truck manufacturers sell product to end users. Because of this, dealer new vehicle selling expenses and dealer net income are not applicable to engine manu facturers. As a result, the indirect cost contributors are likely to be different for engine and truck manufacturers; hence, two RPE multipliers were developed.

3.6 Company-Level RPE Multipliers

Table 3-3 presents the values of cost contributors and RP E multipliers for individual manufacturers in 2008. Selling and dealer cost cont ributors were higher for heavy duty truck
manufacturers because of the inclusion of dealer co sts and net income. Other expenses, which are not part of indirect cost contributors, are ref lected in Table 3-3 for completeness; they did not
exceed 0.01 for all manufacturers.

To ensure that 2008 was not an outlier year, we loo ked at a 4-year historical analysis of
indirect cost contributors for individual manufactu rers. It would be costly to perform analysis similar to the one used for the year 2008 for every year, for every manufacturer. However, manufacturers’ readily provided three major indirec t cost contributing factors in their annual reports (selling, administrative, and other expense s; operating and other expenses; and depreciation). The sum of these factors varied with in 9 percentage points in the past 4 years (see Appendix A for a historical RPE analysis for indivi dual manufacturers). 4 

### Individual manufacturers’ RPE multipliers were averaged in the process of constructing an industry average RPE multiplier and, thus, diminished the effect of variability of cost contributors for individual

3 In the LD RPE/IC multiplier report, dealer new veh icle net income and new vehicle selling expenses we re constructed using National Automobile Dealers Assoc iation (NADA) data. Similar data were not available for heavy duty truck dealers.
4 If we were to exclude Daimler, which went through restructuring in 2007, the sum of three major cost contributors varied within 5 percentage points over the 4 years analyzed.

### 3-9

manufacturers in 2008. This led us to believe that 2008 RPE multipliers are unlikely to be
underestimated.

3.7 Industry Average RPE Multipliers
The industry average RPE multipliers were calculate d separately for heavy duty engine manufacturers and heavy duty truck manufacturers. T he industry averages were calculated by weighting company-level RPE multipliers by their 20 08 worldwide production. Table 3-4 presents company-level production alongside company -level RPE multipliers. In 2008, the industry average RPE multiplier for heavy duty engi ne manufacturers equaled 1.28, while the industry average RPE multiplier for heavy duty truc k manufacturers equaled 1.36. The 2008 production figures presented in Table 3-4 were also used in Table 3-3 to generate industryweighted average individual cost components.

Table 3-4. Weighted RPE Multipliers: 2008

Engine Manufacturer Annual Production (number of en gines/trucks) (2008) RPE Multiplier

Cummins 108,300 1.29

Hino 45,765 1.25
Weighted average 1.28

Truck manufacturer

PACCAR 125,900 1.33

Navistar 244,100 1.36

Daimler 472,000 1.34

Volvo 251,151 1.43
Weighted average 1.36

Sources: Cummins Inc. 2009. 2008 Annual Report on 1 0-K Form. Available at: http://phx.corporateir.net/phoenix.zhtml?c=112916&p=irol-reportsannual. Accessed on February 15, 2010. IHS Global Insight. September 30, 2009. HIS Global Insight Report: Volvo Trucks (Automotive). Waltham, MA: IHS Global Insight. IHS Global Insight. October 01, 2009. HIS Global In sight Report: PACCAR (Automotive). Waltham, MA: IHS Global Insight. IHS Global Insight. September 18, 2009. HIS Global Insight Report: Navistar (Automotive). Waltham, MA: IHS Global Insight. IHS Global Insight. September 14, 2009. HIS Global Insight Report: Daimler Trucks (Automotive). Waltha m, MA: IHS Global Insight. IHS Global Insight. September 18, 2009. HIS Global Insight Report: Volvo Trucks (Automotive). Waltham, MA: IHS Global Insight.

### 4-1 SECTION 4
IC MULTIPLIER

This section describes calculations of IC multiplie rs for engine and truck manufacturers. IC multipliers reflect differences in technology co mplexity and changes in indirect costs over time. The motivation is to model the diversity of p otential cost impacts under a wide range of potential future environmental regulations.

In Section 3, we calculated an average RPE multipli er for the heavy duty engine manufacturing industry of approximately 1.28 and fo r the heavy duty truck manufacturing industry of approximately 1.36. These numbers inclu de direct cost components, indirect cost components, and net income. In this section, we foc us solely on indirect cost components that are likely to be affected by future environmental regul ations. We show that only a portion of indirect cost contributors should be included in the markup factor. Because the resulting markup factors reflect changes in indirect costs relative to chang e in direct costs, they are referred to as IC multipliers.

Regulations that result in implementing different l evels of technology complexity are likely to affect the price of the unit of output wi th different magnitudes. Regulations that result in manufacturers implementing a technology with low co mplexity (such as simply replacing an existing technology with a better performing techno logy) would be associated with a lower IC multiplier. Regulations that result in manufacturer s implementing technology with high complexity (such as installing a technology that re quires significant integration efforts) would be associated with a higher IC multiplier. In addition , the magnitude of impacts of different technologies is also likely to change over time as new technologies are assimilated. For example, although R&D expenses are likely to be high in the short term, in the long term, R&D efforts become less important as technology matures.

In this section, we describe the methodology used t o calculate a set of IC multipliers for engine and truck manufacturers. Table 4-1 lists the indirect cost contributors from Table 3-3 that are applicable to IC multipliers. In this study we do not include net income among these cost contributors, mostly because net income results fro m the interaction of supply and demand. However, an argument can be made that net income sh ould be included in long-term multipliers,
and this is discussed further in Section 4.5.

Our approach is then to scale cost contributor valu es up or down depending on the complexity of the technology (low, medium, or high) and the time frame (short or long term).

### 4-2

Table 4-1. Weighted Average IC Multiplier Contribut ors to RPE: 2008

Cost Contributor Heavy Duty Engine Manufacturers Heavy Duty Truck Manufacturers

Production Overhead
Warranty 0.02 0.04
R&D (product development) 0.04 0.05
Depreciation and amortization 0.03 0.04
Maintenance, repair, operations cost 0.01 0.02
Total production overhead 0.08 0.14
Corporate Overhead

General and administrative 0.11 0.07

Retirement 0.01 0.01

Health care 0.01 0.01
Total corporate overhead 0.13 0.09
Selling
Transportation 0.01 0.00
Marketing 0.01 0.01

Dealers
Dealer new vehicle selling cost — 0.06
Total selling and dealer costs 0.01 0.08

Sum of Indirect Costs 0.23 0.31



### 4.1 Technology Complexity and Impact on Operations
We identify three levels of technology complexity: low, medium, and high. Technology complexity was based on work by Henderson and Clark (1990). 1



### Low-complexity technology introduces only minor changes to an existing produ ct, using an established design. The underlying core design c oncepts and the links between them remain the same. An example of such technology in the heav y duty truck industry is single wide tires, because they simply replace existing tires and requ ire no vehicle redesign or part-integration effort by the heavy duty truck manufacturer.

1 A more thorough discussion of the rationale of usi ng three technology levels and their impacts on ope rations can be found in Rogozhin et al. (2010).

### 4-3

Medium-complexity technology changes either the architecture of how the compone nts interact with each other or the core concept of the technology, but not both. An example of such technology in the heavy duty truck industry is engi ne turbo compounding. This technology would require some redesign and integration effort, since the parts’ interaction with each other would have to be changed.

High-complexity technology establishes a set of new core design concepts embod ied in components that are linked together in a new archit ecture. An example of such technology in the heavy duty truck industry is hybrid-electric powert rains because they represent an entirely new approach to propulsion relative to reliance on an i nternal combustion engine.

4.2 Time Frame and Impact on Operations
The time frame adds another dimension to this study . Many of the indirect costs are likely to be one-time or short-term activities, such as ed ucating dealers and upgrading mechanics’ equipment. These costs will not appear in the long- term IC multipliers. In addition, incremental R&D expenditures will occur over a short period of time, even though they may be amortized over 5 to 10 years (IRS, 2008). Thus, we expect to see higher indirect costs initially and lower impacts in the long term as companies assimilate th e new technologies.

4.3 Adjustment Factors to Cost Contributors
The reason for developing adjustment factors was th e fact that the cost contributors in
Table 4-1 would not all respond the same to new technolog ies. Warranty costs, for instance, would probably be higher per dollar of direct costs for more complex technologies, because there would be more opportunities for failure. There is, however, no public information to estimate how indirect costs vary with different technologies . Instead, we relied on expert judgment.

In two separate processes, a team of EPA engineers evaluated how new technologies of different complexities (low, medium, and high) woul d affect indirect cost contributors in the short and long terms for light duty vehicles. The f irst process was a consensus approach, and the second was based on the Delphi method (these approa ches are described in Section 3.2).

In both approaches, the team developed the adjustme nt factors with 0 and 1 as calibration units. An adjustment factor of 1 indica tes that implementing the technology had an effect equal to the average effect of that indirect cost contributor per dollar of direct cost. For instance, the warranty cost per dollar of a new tec hnology would equal the average warranty cost per dollar for the company. An adjustment factor of 0 indicated that implementing the technology did not affect that indirect cost contri butor. For example, a new technology might not affect corporate overhead.

### 4-4

Tables 4-2 and 4-3 present the adjustment factors from the consens us process for light duty vehicles. Table 4-2 presents adjustment factors for the short term, while Table 4-3 presents adjustment factors for the long term (for a detaile d discussion of the development of these factors, refer to Rogozhin et al. [2009]).

Table 4-2. Short-term Adjustment Factors to Indirec t Cost Contributors for Light Duty

Vehicles: Consensus Approach

Indirect Cost Low Medium High
Production Overhead Warranty 1.2 1.6 2.0
R&D 0.2 1.1 2.0 Depreciation and amortization 0 0 1.0 Maintenance, repair, operations 0 0 1.0 Corporate Overhead
General and administrative 0 0 0.5
Retirement 0 0 0.5
Health care 0 0 0.5 Selling Transportation 0 0 0.3 Marketing 0 1 1.5 Dealer new vehicle selling expense 0.1 1 1.5



### Table 4-3. Long-Run Adjustment Factors to Indirect Cost Contributors for Light Duty

Vehicles: Consensus Approach

Indirect Cost Low Medium High
Production Overhead Warranty 0.6 0.8 1
R&D 0 0 0.3 Depreciation and amortization 0 0 1 Maintenance, repair, operations 0 0 1 Corporate Overhead
General and administrative 0 0 0.5
Retirement 0 0 0.5
Health care 0 1 0.5 Selling Transportation 0 0 0.3 Marketing 0 0 0 Dealer new vehicle selling expense 0 0.3 1

### 4-5

Tables 4-4 and 4-5 present the adjustment factors from the Delphi- based method for light duty vehicles. Table 4-4 presents adjustment factors for the short term, while Table 4-5 presents adjustment factors for the long term. 2



### Table 4-4. Short-Term Adjustment Factors to Indirec t Cost Contributors for Light Duty

Vehicles: Delphi-Based Method

Indirect Cost Low Med High
Production Overhead Warranty 0.361 1.386 2.289
R&D 0.822 1.481 3.732 Depreciation and amortization 0.373 0.585 1.444 Maintenance, repair, operations 0.488 0.712 1.396 Corporate Overhead
General and administrative 0.339 0.579 1.057
Retirement 0.385 0.412 0.565
Health care 0.346 0.408 0.635 Selling Transportation 0.436 0.143 0.829 Marketing 0.215 0.821 1.511 Dealer new vehicle selling expense 0.250 0.626 1.296



### Table 4-5. Long-Term Adjustment Factors to Indirect Cost Contributors for Light Duty Vehicles: Delphi-Based Method

Indirect Cost Low Med High
Production Overhead Warranty 0.168 0.964 1.518
R&D 0.372 0.901 2.018 Depreciation and amortization 0.281 0.466 0.951 Maintenance, repair, operations 0.377 0.451 1.092 Corporate Overhead
General and administrative 0.286 0.425 0.671
Retirement 0.385 0.393 0.524
Health care 0.331 0.354 0.516 Selling Transportation 0.393 0.143 0.604 Marketing 0.207 0.569 0.829 Dealer new vehicle selling expense 0.229 0.426 0.694

2 For a detailed discussion of the development of th ese factors, refer to Helfand and Sherwood (2009).

### 4-6

To arrive at the final adjustment factors used in t his study, we averaged adjustment factors from two approaches for low- and medium-com plexity technologies and kept estimates from the two approaches for high-complexity technol ogies (thus creating two sets: High 1 [from the consensus approach] and High 2 [from the Delphi -based method]). 3 

### The resulting adjustment factors are presented in Table 4-6 (short term) and Table 4-7 (long term).

Table 4-6. Resultant Short-Term Adjustment Factors to Indirect Cost Contributors for

Light Duty Vehicles

Indirect Cost Low Med High 1 High 2 Production Overhead Warranty 0.78 1.49 2.00 2.29 R&D 0.51 1.29 2.00 3.73 Depreciation and amortization 0.19 0.29 1.00 1.44 Maintenance, repair, operations 0.24 0.36 1.00 1.40 Corporate Overhead General and administrative 0.17 0.29 0.50 1.06 Retirement 0.19 0.21 0.50 0.57 Health care 0.17 0.20 0.50 0.64 Selling Transportation 0.22 0.07 0.30 0.83 Marketing 0.11 0.91 1.50 1.51 Dealer new vehicle selling expense 0.18 0.81 1.50 1.30



### Table 4-7. Resultant Long-Term Adjustment Factors t o Indirect Cost Contributors for

Light Duty Vehicles

Indirect Cost Low Med High 1 High 2 Production Overhead Warranty 0.38 0.88 1.00 1.52 R&D 0.19 0.45 0.30 2.02 Depreciation and amortization 0.14 0.23 1.00 0.95 Maintenance, repair, operations 0.19 0.23 1.00 1.09 Corporate Overhead General and administrative 0.14 0.21 0.50 0.67 Retirement 0.19 0.20 0.50 0.52 Health care 0.17 0.68 0.50 0.52 Selling Transportation 0.20 0.07 0.30 0.60 Marketing 0.10 0.28 0.00 0.83 Dealer new vehicle selling expense 0.11 0.36 1.00 0.69

3 High 1 and High 2 are used because two processes y ielded substantially different results for high-com plexity technologies, and EPA believed these differences we re meaningful given the two technologies considered in the two different processes.

### 4-7

4.4 Industry Average IC Multipliers

Each contributor in Table 4-1 was then multiplied by an associated set of adj ustment factors presented in Tables 4-6 and 4-7. These calculations are presented in Tables 4-8 (engine manufacturers) and 4-9 (truck manufacturers). For example, the warrant y cost contributor for engine manufacturers in Table 3-3 is 0.02. This value was then multiplied by 0.78 , 1.49, 2.0, and 2.29 (from Table 4-2, for low, medium, High 1, and High 2 complexity technologies, respectively) to arrive at adjusted short-term indi rect contributors of 0.01, 0.02, 0.03, and 0.04 (see Table 4-3). Finally, adjusted indirect cost contributors were added for each complexity and time frame to calculate the IC multipliers.

4.5 IC Multipliers and Net Income
The goal for either the RPE multiplier or the IC mu ltiplier is to improve the estimate of the total costs of a new technology. In this contex t, the role of net income needs careful
consideration. Net income results from an interacti on of supply and demand curves for a product. The total effect on net income depends on the relat ive slopes of the supply and demand curves: although a reduction in quantity and an increase in cost hurt net income, a price increase can offset some or all of these effects (Rogozhin et al ., 2010).

However, an argument can be made that net income is not only the result of supply and demand interactions; businesses repay shareholders for the use of their capital investment. In this sense, net income is a cost of doing business: if a business cannot pay a return on its capital costs comparable to that in other industries, investors w ill move their money into other businesses, and the company will not be able to survive. Shareholde rs may be willing to accept losses in the short term in exchange for higher returns over time, but, in the long term, net income should be sufficient to keep shareholders investing in a comp any. According to this argument, net income should be included at least in the long-term multip liers (Rogozhin et al., 2010).

The IC multipliers presented in this report do not include net income. Since the ratio of
net income to indirect cost is estimated to be 0.05 (see Table 3-3), inclusion of net income in the long-term IC multipliers would increase these value s by 0.05. Table 4-10 presents long-term IC multipliers with net income included.

### 4-8Table 4-8. Short- and Long-Term IC Multiplier Calculations for Engine Manufacturers: 2008RPE and ICMultiplierContributorsRPEMultiplierApproachIC Multiplier ApproachWeightedAverageIndustryIndirectCostContributors toRPEShort-Term EffectsLong-Term EffectsLowComplexityTechnologyMediumComplexityTechnologyHighComplexityTechnology 1HighComplexityTechnology 2LowComplexityTechnologyMediumComplexityTechnologyHighComplexityTechnology 1HighComplexityTechnology 2AdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierManufacturingManufacturingCost1.00 1.00 1.00 1.00 1.001.00 1.001.001.00ProductionoverheadWarranty 0.02 0.78 0.01 1.49 0.02 2.00 0.03 2.290.040.38 0.01 0.88 0.011.00 0.021.52 0.02R&D (productdevelopment)0.04 0.51 0.02 1.29 0.05 2.00 0.07 3.73 0.130.19 0.01 0.45 0.020.30 0.012.02 0.07Depreciationandamortization0.03 0.19 0.01 0.29 0.01 1.00 0.03 1.44 0.040.14 <0.01 0.23 0.011.00 0.030.95 0.03Maintenance,repair,operationscost0.01 0.24 <0.01 0.36 0.01 1.00 0.01 1.40 0.020.19 <0.01 0.23 <0.011.00 0.011.09 0.01Totalproductionoverhead0.08 0.04 0.08 0.15 0.230.02 0.040.070.14CorporateOverheadGeneral andadministrative0.11 0.17 0.02 0.29 0.03 0.50 0.06 1.06 0.120.14 0.02 0.21 0.020.50 0.060.67 0.07Retirement 0.01 0.19 <0.01 0.21 <0.01 0.50 <0.010.57 <0.010.19 <0.01 0.20 <0.010.50 <0.010.52 <0.01Health 0.01 0.17 <0.01 0.20 <0.01 0.50 0.01 0.640.010.17 <0.01 0.68 0.010.50 0.010.52 0.01Total corporateoverhead0.13 0.02 0.04 0.07 0.130.02 0.030.070.09(continued)

### 4-9Table 4-8. Short- and Long-Term IC Multiplier Calculations for Engine Manufacturers: 2008 (continued)RPE and ICMultiplierContributorsRPEMultiplierApproachIC Multiplier ApproachWeightedAverageIndustryIndirectCostContributors toRPEShort-Term EffectsLong-Term EffectsLowComplexityTechnologyMediumComplexityTechnologyHighComplexityTechnology 1HighComplexityTechnology 2LowComplexityTechnologyMediumComplexityTechnologyHighComplexityTechnology 1HighComplexityTechnology 2AdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMulti-plierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierSellingTransportation 0.01 0.22 <0.01 0.07 <0.01 0.30 <0.01 0.83 <0.010.20 <0.01 0.07 <0.01 0.30 <0.010.60 <0.01Marketing 0.01 0.11 <0.01 0.91 0.01 1.50 0.01 1.51 0.010.10 <0.01 0.28 <0.01 0 00.83 0.01DealersDealer newvehicle netincome— — — — — — — — —— — — — — —— —ealer newvehicleselling cost— — — — — — — — —— — — — — —— —Total sellingand dealercontributors0.01 <0.01 0.01 0.01 0.02<0.01 <0.01 <0.010.01Sum of IndirectCosts0.23 0.06 0.13 0.23 0.380.04 0.08 0.140.24Net income 0.05 — — — — — — — —— — — — — —— —Other costs(notincluded incontributingcosts)0.01 — — — — — — — —— — — — — —— —RPE/ICMultiplier1.28 1.06 1.13 1.23 1.381.04 1.08 1.141.24

### 4-10Table 4-9. Short- and Long-Term IC Multiplier Calculations for Truck Manufacturers: 2008RPE and ICMultiplierContributorsRPEMultiplierApproachIC Multiplier ApproachWeightedAverageIndustryIndirectCostContributors toRPEShort-Term EffectsLong-Term EffectsLowComplexityTechnologyMediumComplexityTechnologyHighComplexityTechnology 1HighComplexityTechnology 2LowComplexityTechnologyMediumComplexityTechnologyHighComplexityTechnology 1HighComplexityTechnology 2AdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMulti-plierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierManufacturingManufacturingCost1.00 1.00 1.00 1.00 1.001.00 1.001.001.00ProductionoverheadWarranty 0.04 0.78 0.03 1.49 0.05 2.00 0.07 2.290.080.38 0.01 0.88 0.031.00 0.041.52 0.06R&D (productdevelopment)0.05 0.51 0.02 1.29 0.06 2.00 0.09 3.73 0.170.19 0.01 0.45 0.020.30 0.012.02 0.09Depreciationandamortization0.04 0.19 0.01 0.29 0.01 1.00 0.04 1.44 0.060.14 0.01 0.23 0.011.00 0.040.95 0.04Maintenance,repair,operationscost0.02 0.24 <0.01 0.36 0.01 1.00 0.02 1.40 0.020.19 0.00 0.23 0.001.00 0.021.09 0.02Totalproductionoverhead0.14 0.06 0.13 0.22 0.330.03 0.070.110.20CorporateOverheadGeneral andadministrative0.07 0.17 0.01 0.29 0.02 0.50 0.04 1.06 0.070.14 0.01 0.21 0.010.50 0.040.67 0.05Retirement 0.01 0.19 <0.01 0.21 0.00 0.50 0.01 0.57 0.010.19 0.00 0.20 0.000.50 0.010.52 0.01Health 0.01 0.17 <0.01 0.20 0.00 0.50 0.01 0.640.010.17 0.00 0.68 0.010.50 0.010.52 0.01Total corporateoverhead0.09 0.02 0.03 0.05 0.090.01 0.020.050.06(continued)

### 4-11Table 4-9. Short- and Long-Term IC Multiplier Calculations for Truck Manufacturers: 2008 (continued)RPE and ICMultiplierContributorsRPEMultiplierApproachIC Multiplier ApproachWeightedAverageIndustryIndirectCostContributors toRPEShort-Term EffectsLong-Term EffectsLowComplexityTechnologyMediumComplexityTechnologyHighComplexityTechnology 1HighComplexityTechnology 2LowComplexityTechnologyMediumComplexityTechnologyHighComplexityTechnology 1HighComplexityTechnology 2AdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMulti-plierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierAdjustmentFactorICMultiplierSellingTransportation 0.00 0.22 <0.01 0.07 <0.01 0.30 <0.01 0.83 <0.010.20 <0.01 0.07 <0.01 0.30 <0.010.60 <0.01Marketing 0.01 0.11 <0.01 0.91 0.01 1.50 0.01 1.51 0.010.10 <0.01 0.28 <0.01 0 00.83 0.01DealersDealer newvehicle netincome0.00Dealer newvehicleselling cost0.06 0.18 0.01 0.81 0.05 1.50 0.09 1.30 0.080.11 0.01 0.36 0.02 1.00 0.060.69 0.04Total sellingand dealercontributors0.08 0.01 0.06 0.10 0.090.01 0.02 0.060.05Sum of IndirectCosts0.31 0.09 0.21 0.37 0.520.05 0.11 0.220.31Net income 0.05 — — — — — — — —— — — — — —— —Other costs(notincluded incontributingcosts)0.00 — — — — — — — —— — — — — —— —RPE/ICMultiplier1.36 1.09 1.21 1.37 1.521.05 1.11 1.221.31

### 4-12

Table 4-10. Long-Term Indirect Cost Multipliers wit h Net Income Included

Time Frame Low Medium High 1 High 2
Engine manufacturers 1.09 1.13 1.19 1.29

Truck manufacturers 1.10 1.16 1.27 1.36

### 5-1 SECTION 5
EXAMPLE TECHNOLOGIES

This section provides examples of low-, medium-, an d high-complexity technologies. Single wide tires is used as an example of a low-co mplexity technology, engine turbo compounding as an example of a medium-complexity te chnology, and hybrid-electric powertrains as an example of a high-complexity tech nology.

5.1 Low Complexity: Single Wide Tires
Single wide tires are designed to improve fuel econ omy by reducing the tires’ rolling resistance and decreasing the mass of the tire and wheel assemblies. A 17-inch wide single tire replaces conventional dual tires on the drive and t railer axles. EPA estimated that, on average, this technology can reduce nitrogen oxides (NO x 

### ) emissions by 30% and improve fuel efficiency by 6% when traveling at highway speeds (EPA, 2005).

Implementing this technology will require truck man ufacturers to purchase single wide tires. Implementing this technology does not requir e a change in core structure or redesign of architecture. Single wide tires are installed in pl ace of stock tires with a low degree of additional testing and development required. This example assu mes that significant modifications will not be required in the chassis or suspension components . This technology is an example of a lowcomplexity technology. Short-term IC multipliers fo r this technology complexity equaled 1.06 for engine manufacturers and 1.09 for truck manufac turers. Long-term IC multipliers equaled 1.04 for engine manufacturers and 1.05 for truck ma nufacturers.

5.2 Medium Complexity: Engine Turbo Compounding
Engine turbo compounding adds a power turbine to th e exhaust system downstream from the turbocharger, which extracts additional energy from exhaust gases and supplies it to the engine’s crankshaft (Scania, 2010). Manufacturers c laim a 5% increase in fuel economy coupled with an increase in horsepower (Detroit Diesel Corp oration, 2010).

This example assumes that implementing this technol ogy in mass production requires vehicle manufacturers to integrate the technology w ith the other vehicle systems, such as the engine and exhaust system. However, the core tasks of the engine and exhaust system are not changed. This technology is an example of a medium- complexity technology. Short-term IC multipliers for this technology complexity equaled 1.13 for engine manufacturers and 1.21 for truck manufacturers. Long-term IC multipliers equal ed 1.08 for engine manufacturers and 1.11
for truck manufacturers.

### 5-2

5.3 High Complexity: Hybrid Electric Powertrains
Hybrid electric heavy duty vehicles are in various stages of development by almost all major heavy duty truck manufacturers. Hybrid vehicl es have two basic types of driveline structure. The most common, parallel hybrid, is whe re 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/ge nerator to move the vehicle and recharge the battery. Reductions in carbon dioxide emissions var y between 15% and 30% (Ricardo Inc., 2008).

Production of a hybrid vehicle would require truck manufacturers to not only redesign the physical and electronic architecture to accommodate the additional electric drive components, but also to redesign the core structure of the main driveline components, including the transmission, engine, and other elements of the pro pulsion system. This technology is an example of a high-complexity technology. Short-term IC multipliers for this technology complexity (High 1) equaled 1.23 for engine manufac turers and 1.37 for truck manufacturers. Long-term IC multipliers equaled 1.14 for engine ma nufacturers and 1.22 (High 1) and for truck
manufacturers.

High 2 technology complexity might be applicable fo r technologies currently in the research or development stage but not yet in the pr oduction phase. Plug-in hybrid was used as an example of such technology complexity in the LD RPE /IC study; it is not clear whether such technologies exist among heavy duty truck technolog ies. If they did exist, short-term multipliers that would be used equal 1.38 for engine manufactur ers and 1.52 for truck manufacturers. Longterm multipliers for High 2 technology complexity e qualed 1.24 for engine manufacturers and
1.31 for truck manufacturers.

### 6-1 SECTION 6
RPE MULTIPLIER APPROACH VS. INTEGRATED IC MULTIPLIE R AND MARKET
MODEL APPROACH

Executive Order 12866, “Regulatory Planning and Rev iew,” 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 EPA’s Guidelines for Preparing Economic Analyses stipulate use of a microeconomic framework to anal yze the benefits and costs. This section discusses the relationship between the RPE and IC multipliers developed in this report and the microeconomic framework in which they are u sed.

The RPE multiplier approach has been used as a meth od 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 net income 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.

The IC multipliers approach addresses two shortcomi ngs of the RPE multiplier approach. First, as we discuss in previous sections of this r eport, regulations will most likely not affect all categories of indirect costs. The indirect costs af fected will vary by the complexity of the technology and will change over time (short term ve rsus long term). In Section 4, we developed a series of IC multipliers to capture these factors . Second, applying the RPE alone does not account for market effects and hence does not yield an accurate estimate of the change in market price (and produces no estimate of the change in ma rket quantity). The IC multiplier approach identifies the appropriate shift in the supply curv e from which market effects (changes in price and quantity) can be analyzed.

6.1 Market Model and RPE Multiplier
Direct manufacturing costs and indirect costs resul ting 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 6-1. Initially the market is in equilibrium. Manufacturers produce quantity Q 1 

### and buyers purchase that quantity at the price of
P 1 

### 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.

### 6-2

Figure 6-1. RPE Multiplier vs. IC Multiplier Approa ch

The RPE multiplier approach assumes that the multip lier captures the full market impact of the new cost. Sales continue at Q 1 

### , and the price will rise to P 2 

### (point B). The RPE multiplier approach implies that demand is perfectly inelastic and there is a full pass-through of costs to

consumers.

However, if the demand curve is less than perfectly inelastic (as shown in Figure 6-1), consumers will demand fewer vehicles as the price i ncreases. A new equilibrium will be determined at the intersection of the supply and de mand curves (point C). The new price will be
P 3 

### and the new output will be Q 2 

### . As a result, the final cost of the regulation (so cial cost) will be slightly less than the original cost estimate becau se of the decrease in quantity being produced. The original cost estimate, based on the operation at point B, would be the area between lines S 0 

### and S 1 

### , the price axis, and quantity Q 1 

### . The actual social cost is the area between lines S 0 

### and S 1 

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

The market analysis represented in Figure 6-1 also suggests the reason not to include net income in the IC multiplier. The RPE approach impli citly assumes disequilibrium in the market. Manufacturer net income is calculated by assuming p roduction at point B, even though consumers are not willing to pay P 2 

### and buy Q 1 

### vehicles. In reality, both price and quantity will change in response to the shift in costs. The impac t on manufacturer net income is determined by the elasticities of the supply and demand curves. M anufacturers and consumers typically share

Price

Quantity S 1 : With Regulation

D
Q 2 P 2
P 3

Q 1 S 0 : Without Regulation

P 1 A B

C

Q 3

### 6-3

the burden of the compliance costs. Indeed, if net income were fully included in costs, then producers would not be affected by regulations: the ir net income would be the same before and after the change. It is common, however, for a rule to affect net income; indeed, manufacturers often object to rules on this basis.

In a long-term model of a perfectly competitive ind ustry, microeconomic theory predicts that full costs are passed along to consumers. The perfect competition model assumes that firms make zero economic profits (that is, net income inc luding 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 term. As a result, firms will exit the ind ustry, until quantity supplied equals quantity demanded at price P 2 

### , quantity Q 3 

### . In an imperfectly competitive industry, firms are predicted to have economic profits greater than zero. When imper fectly competitive firms face increased costs, they seek to mitigate losses in production b y not passing along the full costs; the quantity will not fall as much as Q 3 

### , and the price will not rise as much as P 2


### .
Another factor that is difficult to predict in this setting is the effects of new technologies on consumer demand. Some changes may be invisible t o 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. Finall y, some technological changes may reduce demand, although truck makers and regulators are no t likely to pursue undesirable changes as long as more attractive alternatives exist. Any shi fts in the demand curve due to new technologies should be included in regulatory impac t 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 adju stments due to the shifting supply curve.

The IC multiplier models the appropriate shift in t he supply curve (including direct manufacturing costs and relevant indirect costs) th at then can be used in a 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 ge nerated from the IC multiplier approach, determines the distribution of regulatory burden be tween producers and consumers consistent with economic theory.

### 7-1 SECTION 7
SUMMARY AND CONCLUSION

The RPE multiplier has historically been used to es timate the indirect costs that are
included in the total cost of vehicle modification. This approach has typically included all indirect cost categories and net income to develop a multiplier that is then applied to the estimated direct manufacturing costs. The weighted average RPE multiplier for engine manufacturers equaled 1.28 in 2008, while the weigh ted average RPE multiplier for truck manufacturers equaled 1.36 in 2008. However, a key problem in using RPE multipliers in cost analysis is that not all contributors to indirect c osts are affected in the same way by new technologies. Some changes may lead to higher indir ect costs, and some lower, depending of the complexity and timing of the new technologies being introduced.

This report calculates modified multipliers, referr ed to as IC multipliers. IC multipliers explicitly recognize that technologies differ in th eir indirect cost requirements. In an ideal world, the calculation of costs of new technologies would include indirect costs specific to the technology. When resources are not available to con duct such an in-depth analysis, multipliers can provide an approximation of those indirect cost s. Because those indirect costs are likely to vary both with the complexity of the technology and with the time frame, the IC multipliers calculated here are expected to provide superior es timates of the actual costs of a new technology compared to using RPE multipliers. We find that IC multipliers range from 1.06 to 1.38 in the short term and from 1.04 to 1.24 in the long term f or heavy duty engine manufacturers, and from
1.09 to 1.52 in the short term and from 1.05 to 1.3 1 in the long term for heavy duty truck
manufacturers.

### 8-1 SECTION 8
REFERENCES

Cooper, R., and R.S. Kaplan., 1988. “How Cost Accou nting Distorts Product Costs.” Management Accounting 69(10):20-7.

Cummins Inc. 2006. 2005 Annual Report on 10-K Form. Available at: http://phx.corporateir.net/phoenix.zhtml?c=112916&p=irol-reportsannual. Accessed on February 15, 2010.

Cummins Inc. 2009. 2008 Annual Report on 10-K Form. Available at: http://phx.corporateir.net/phoenix.zhtml?c=112916&p=irol-reportsannual. Accessed on February 15, 2010.

Daimler. 2006. Annual Report 2006. Available at: ht tp://www.daimler.com/investorrelations/reports-and-key-figures/annual-documents/ daimler-ag. Accessed February 7, 2010.

Daimler. 2008. Annual Report 2008. Available at: ht tp://www.daimler.com/investorrelations/reports-and-key-figures/annual-documents/ daimler-ag. Accessed February 7, 2010.

Detroit Diesel Corporation. 2010. Detroit Diesel: D D 15. Detroit, MI: Detroit Diesel Corporation. Available at: http://www.detroitdiesel .com /pdf/engines/2009-dd15- brochure.pdf. Accessed on March 30, 2010.

Forbes Inc. 2010. Investopedia. Cost of Goods Sold— COGS. Available at: http://www.investopedia.com/terms/c/cogs.asp>. Acce ssed on March 22, 2010.

Helfand, G., and T. Sherwood. 2009. “Memorandum: Do cumentation of the Development of Indirect Cost Multipliers for Three Automotive Tech nologies.” Washington, DC: Office of Transportation and Air Quality, U.S. Environment al Protection Agency.

Henderson, R.M., and K.B. Clark. 1990. “Architectur al Innovation: The Reconfiguration of Existing Product Technologies and the Failure of Es tablished Firms.” Administrative Science Quarterly 35(1):9-30.

Hino Motors, Ltd. and Consolidated Subsidiaries. 20 09a. Hino: Financial Results of the Fiscal Year Ended March 31, 2009.

Hino Motors, Ltd. and Consolidated Subsidiaries. 20 09b. Hino: Five-year Summary Ended March 31, 2009.

IBIS. January 2010, IBISWorld Industry Report 3361 2: Truck & Bus Manufacturing in the US. CA: IBIS.

IHS Global Insight. September 14, 2009. HIS Global Insight Report: Daimler Trucks (Automotive). Waltham, MA: IHS Global Insight.

### 8-2

IHS Global Insight. September 18, 2009. HIS Global Insight Report: Navistar (Automotive). Waltham, MA: IHS Global Insight.

IHS Global Insight. September 18, 2009. HIS Global Insight Report: Volvo Trucks (Automotive). Waltham, MA: IHS Global Insight.

IHS Global Insight. September 30, 2009. HIS Global Insight Report: Volvo Trucks (Automotive). Waltham, MA: IHS Global Insight.

IHS Global Insight. October 01, 2009. HIS Global In sight Report: PACCAR (Automotive). Waltham, MA: IHS Global Insight.

Jack Faucett Associates. September 4, 1985. Update of EPA’s Motor Vehicle Emission Control Equipment Retail Price Equivalent (RPE) Calculation Formula . Chevy Chase, MD: Jack Faucett Associates.

McKinsey & Company. October 2003. “Preface to the A uto Sector Cases.” In New Horizons: Multinational Company Investment in Developing Econ omies . San Francisco, CA: McKinsey & Company.

McManus, Walter. Personal communication on February 16, 2010.

National Research Council (NRC). 2002. Technologies for Improving the Fuel Economy of Passenger Cars and Light-Duty Trucks . Washington, DC: National Research Council. Available at: http://books.nap.edu/openbook.php?isb n =0309076013. Accessed on December 8, 2008.

Navistar. 2005. Annual Report 2005. Available at: h ttp://ir.navistar.com/sec.cfm. Accessed February 7, 2010.

Navistar. 2008. Annual Report 2008. Available at: h ttp://ir.navistar.com/sec.cfm. Accessed February 7, 2010.

Niazi, A., J. Dai, S. Balabani, and L. Seneviratne. 2007. “A New Overhead Estimation Methodology: A Case Study in an Electrical Engineer ing Company.” Proceedings of the Institution of Mechanical Engineers, Part B: Journa l of Engineering Manufacture 221(4):699-710.

PACCAR. 2006. PACCAR: Annual Report 2005. Available at: http://www.paccar.com/ investors/investor_resources_history.asp. Accessed on February 7, 2010.

PACCAR. 2009. PACCAR: Annual Report 2008. Available at: http://www.paccar.com/investors/investor_resources_ history.asp. Accessed on February 7, 2010.

### 8-3

Ricardo, Inc. June 2008. A Study of Potential Effectiveness of Carbon Dioxid e Reducing Vehicle Technologies, Revised Final Report . EPA420-R-08-004a. Washington, DC: Environmental Protection Agency. Available at: http://www.epa.gov/oms/technology/420r08004a.pdf. A ccessed on February 17, 2009.

Rogozhin, A., M. Gallaher, and W. McManus. February 2009. Automobile Industry Retail Price Equivalent and Indirect Cost Multipliers . EPA-420-R-09-003. Washington, DC: Environmental Protection Agency. Available at: http ://www. epa.gov/otaq/ldhwy/420r09003.pdf.

Rogozhin, A., M. Gallaher, G. Helfand, and W. McMan us. 2010. “Using Indirect Cost Multipliers to Estimate the Total Cost of Adding Ne w Technology in the Automobile Industry.” International Journal of Production Economics 124(2):360-368.

Scania Group. 2010. “Scania Turbocompound: Turbocom pounding Converts Excess Energy Into Power.” Available at: http://www.scania.com/product s-services/trucks/maincomponents/engines/engine-technology/turbocompound/ index.aspx. Accessed on March 30, 2010.

Sierra Research, Inc. November 21, 2007. Study of Industry—Average Mark-Up Factors Used to Estimate Changes in Retail Price Equivalent (RPE) f or Automotive Fuel Economy and Emissions Control Systems . Sacramento, CA: Sierra Research, Inc.

Son, Y.K. 1991. “A Cost Estimation Model for Advanc ed Manufacturing Systems.” International Journal of Production Research 29(3):441-52.

Spinney, B., B. Faigin, N. Bowie, and S. Kratzke. 1 998. Advanced Air Bag Systems Cost, Weight, and Lead Time Analysis. Summary Report . Contract No. DTNH22-96-0-12003. Washington, DC: Department of Transportation.

Supplier Relations US LLC. December 5, 2009. “Heavy Duty Truck Manufacturing Industry in the U.S. and its International Trade. NAICS 336120. ” Irvine, CA: Supplier Relations US LLC.

U.S. Department of Commerce, Bureau of Census (Cens us). 2009. American Factfinder: Sector 31: EC0731I1: Manufacturing: Industry Series: Detai led Statistics by Industry for the United States: 2007 . Washington, DC: Department of Commerce.

U.S. Census. 2010. American Factfinder: Sector 31: EC0731I1: Manufactu ring: Industry Series: Detailed Statistics by Industry for the United Stat es: 2007 . Washington, DC: Department of Commerce.

U.S. Environmental Protection Agency (EPA). 2004. Final Regulatory Analysis: Control of Emissions from Nonroad Diesel Engines . EPA420-R-04-007. Ann Arbor, MI: Environmental Protection Agency. Available at: http ://www.epa.gov/nonroaddiesel/2004fr/420r04007.pdf.

### 8-4

U.S. Environmental Protection Agency (EPA). 2005. “ Effect of Single Wide Tires and Trailer Aerodynamics on Fuel Economy and NO x 

### Emissions of Class 8 Line-Haul TractorTrailers.” Paper number 05CV-45. Available at: http ://epa.gov/smartway/documents/sae05cv045-110105.pdf. Accessed on March 30, 2010.

U.S. Environmental Protection Agency (EPA). 2008. Regulatory Impact Analysis: Control of Emissions of Air Pollution from Locomotive Engines and Marine Compression Ignition Engines Less than 30 Liters per Cylinder . EPA420-R-08-001a. Ann Arbor, MI: Environmental Protection Agency. Available at: http ://www.epa.gov/ otaq/regs/nonroad/420r08001a.pdf.

U.S. Internal Revenue Service (IRS). August 11, 200 8. “Amortization of R&D Expenditures.” Washington, DC: Internal Revenue Service. Available at: http://www.irs.gov/businesses/small/industries/arti cle/0,,id=97642,00.html. Accessed on August 20, 2009.

Volvo Group. 2006. Annual Report 2006. Available at : http://www.volvogroup.com/GROUP/ GLOBAL/EN-GB/INVESTORS/Pages/investor_relations.asp x. Accessed on February 7, 2010.

Volvo Group. 2008. Annual Report 2008. Available at : http://www.volvogroup.com/GROUP/ GLOBAL/EN-GB/INVESTORS/Pages/investor_relations.asp x. Accessed on February 7, 2010.

Vyas, A., D. Santini, and R. Cuenca. April 2000. Comparison of Indirect Cost Multipliers for Manufacturing. Argonne, IL: Center for Transportation Research, E nergy Systems Division, Argonne National Laboratory.

### A-1 APPENDIX A
CALCULATION OF RPE MULTIPLIERS FOR INDIVIDUAL MANUF ACTURERS

This appendix describes calculations of RPE multipl iers for the heavy duty truck manufacturing industry as a whole and for individua l heavy duty truck and engine manufacturers. The appendix is structured in the fo llowing manner:

 

### Appendix A.1: Heavy Duty Truck Industry (Supplier R elations LLC, Census)

 

### Appendix A.2: Cummins

 

### Appendix A.3: Hino

 

### Appendix A.4: PACCAR

 

### Appendix A.5: Navistar

 

### Appendix A.6: Daimler

 

### Appendix A.7: Volvo

A.1 Heavy Duty Truck Industry (Supplier Relations L LC, Census)
An industry report by Supplier Relations LLC (refer red to as “SR LLC report”) presents heavy duty truck industry income statements and bal ance sheets (2009). The industry report was based on data from the U.S. Census, McKinsey & Comp any, and industry associations. These costs are presented in Table A-1. In instances wher e cost contributors were unavailable from SR LLC report, we used Census data or pivoted off cost contributors from the LD RPE/IC study. We
describe these calculations below.

The manufacturing cost was calculated by adding cos t of materials and wages. One can notice that the total for manufacturing costs ($14, 652 million) is less than the sum of manufacturing costs for four manufacturers (PACCAR, Navistar, Daimler, and Volvo). Manufacturing costs for these four companies includ e their global operations, while manufacturing costs from the SR LLC report are main ly based on U.S. operations. We can, nevertheless, compare cost contributors derived usi ng the SR LLC report data with individual company contributors, because they represent ratios and not absolute quantities.

The SR LLC report did not report warranty and R&D c osts. We used the LD RPE/IC study’s cost contributors as a proxy. The SR LLC re port also did not report maintenance, repair, and operations (MRO) costs. We used the data from t he U.S. Census Other Engine Equipment

### A-2

Table A-1. Supplier Relations LLC, Census RPE Multi plier Calculations: 2008

RPE Multiplier Contributor Expense ($ Million) Relative to

Manufacturing Cost Calculation and Source Vehicle Manufacturing Manufacturing cost 14,652.0 1.00 Cost of materials (13,896) [p. 161, Supplier Relations LLC, 2009] + Wages (756) [p. 161, Supplier Relations LLC, 2009] Production Overhead Warranty 0.03 LD RPE/IC Study (only used to break out G&A) R&D (product development) 0.05 LD RPE/IC Study (o nly used to break out G&A) Depreciation and amortization 692.0 0.05 Depreciati on, depletion, and amortization of property, plant and equipment [p. 161, Supplier Relations LLC, 2009] Maintenance, repair, operations cost for engine manufacturers (truck manufactures in brackets) 232.8 0.02 U.S. Census

Total production overhead 0.14 Corporate Overhead General and administrative 3,118.1 0.12 Administrat ive, sales, and marketing costs (2,992) [p. 161, Supplier Relations LLC, 2009] − Marketing − Transportation -Salaries (330) [p. 161, Supplier Relations LLC, 2009] Retirement for engine manufacturers (truck manufacturers in brackets) 0.01 Fringe benefits (433) [p. 161, Supplier Relations LLC, 2009] Health for engine manufacturers (truck manufacturers in brackets) 0.01 Fringe benefits (433) [p. 161, Supplier Relations LLC, 2009] Total corporate overhead 0.15 Selling Transportation 58.0 0.004 Energy and fuel costs [p. 161, Supplier Relations LLC, 2009] Marketing 145.9 0.01 LD RPE/IC Study Marketing * 20 %, personal communication with Walter McManus
Dealers Dealer new vehicle net income 58.6 0.004 LD RPE/IC Study, personal communication with Walter McManus Dealer new vehicle selling cost 879.1 0.06 LD RPE/I C Study, personal communication with Walter McManus Total selling and dealer contributors 0.08
Sum of Indirect Costs 0.37 Net income 0.05 5-year average net income [p. 161 , Supplier Relations LLC, 2009] Other costs (not included as contributors) 0.00

RPE multiplier 1.42
Sources: Supplier Relations US LLC. December 5, 200 9. “Heavy Duty Truck Manufacturing Industry in the U.S.

and its International Trade. NAICS 336120.” Irvine, CA: Supplier Relations US LLC.
Personal communication with Walter McManus

### A-3

Manufacturing (NAICS 333618) and Heavy Duty Truck M anufacturing (NAICS 336120) industries to calculate cost contributors for heavy duty engine truck manufacturers, respectively. The resulting cost contributors equaled 0.01 for en gine manufacturers and 0.02 for truck manufacturers. These calculations are presented in Table A-2.

Table A-2. Calculation of Maintenance, Repair, and Operations Cost Contributors

Heavy Duty Engine Manufacturers (NAICS 333618) Heavy Duty Truck Manufacturers (NAICS 336120) Calculation Payroll $2,391,425 $1,335,228 A
Cost of materials $18,348,214 $15,025,846 B Manufacturing cost $20,739,639 $16,361,074 C = A + B Repair and maintenance $160,217 $53,442 D
Contract work $117,910 $206,492 E Maintenance, repair, operations cost $278,127 $259, 934 F = D + E Share of manufacturing cost 0.01 0.02 F/C

Source: U.S. Census. 2010. American Factfinder: Sec tor 31: EC0731I1: Manufacturing: Industry Series: D etailed Statistics by Industry for the United States: 2007. Washington DC: Department of Commerce.



### General and administrative (G&A) costs were calcula ted by subtracting salaries’ cost (costs of corporate labor) and marketing and transp ortation cost contributors from the administrative, sales, and marketing costs provided in the SR LLC report. The SR LLC report provided fringe benefits’ cost ($433 million, or 0. 0296 as a share of manufacturing costs [$14,652 million]) or a sum of health care and reti rement costs for manufacturing labor. The report did not provide a clear breakout for health care and retirement costs. We used a ratio of
health care to retirement costs from Cummins to cal culate proxies of these costs for engine
manufacturers and similar ratio from Navistar to ca lculate proxies of these costs for truck manufacturers. These calculations are presented in Table A-3.

Neither the SR LLC report nor the U.S. Census provi ded marketing costs; thus, we used a proxy from the LD RPE/IC report. However, we believ e that heavy duty vehicle manufacturers spend a lot less on marketing than light duty vehic le manufacturers. The heavy duty trucks industry engages in business-to-business marketing rather than business-to-consumer marketing. Our judgment is that business-to-business marketing costs are significantly lower than businessto-consumer marketing costs, possibly as low as 3 t o 5% of business-to-consumer marketing costs per unit. We defined business-to-business mar keting costs as 20% of the

### A-4

Table A-3. Calculation of Health Care and Retiremen t Cost Contributors

Cost Contributor Fringe Benefits Share of Manufacturing Cost (SP LLC) a Cost

Contributors (from Cummins) b Heavy Duty

Engine Manufacturers Cost

Contributors (from PACCAR) c Heavy Duty

Truck Manufacturers

Retirement 0.0296 0.01 0.01 0.03 0.02

Health care 0.01 0.02 0.02 0.01

Sources: a Supplier Relations US LLC. December 5, 2009. “Heav y Duty Truck Manufacturing Industry in the

U.S. and its International Trade. NAICS 336120.” Ir vine, CA: Supplier Relations US LLC.

b Table A-4; c Table A-10.



### business-to-consumer marketing costs per unit from Rogozhin et al. (2009) as an upper bound. Finally, because no data were available to calculat e dealer new vehicle net income nor dealer new vehicle selling cost contributors, we used the LD RPE/IC study contributors as a proxy. The LD RPE/IC study dealer new vehicle net income and d ealer new vehicle selling cost contributors
were based on National Association of Automobile De alers (NADA) data. For an exact calculation of these cost contributors, refer to Se ction A.2 of the LD RPE/IC study.

A.2 Cummins Inc. (Engine Manufacturer)
The general approach to estimate cost contributors to RPE multipliers is presented in Section 3. This appendix outlines calculations spec ific to each manufacturer. We performed several adjustments to numbers presented in the Cum mins annual report so they could be applied to our methodology. Calculations and citations for cost values (referencing pages where specific cost item is located) that we used in our analysis are outlined in Table A-4.

The Cummins annual report stated that manufacturing cost includes maintenance and repair costs (valued at $49 million). Therefore, we subtracted that cost from manufacturing cost.
We also added 70% of health care and retirement cos ts, because these costs are attributable to manufacturing labor (see Section 3.3 for justificat ion of this assumption).

The Cummins annual report did not clearly provide w arranty costs for 2008. Warranty costs were estimated by subtracting the balance of warranty provisions at the beginning of 2008 from the balance of warranty provisions at the end of 2008. Cummins also did not clearly state operations costs, which is a large share of the MRO contributor. Therefore, we used the industry average (calculated using Census data) as a proxy. Calculations of industry averages, which are based on the data from the industry report by SR LL C and Census, are presented in Section A.1 of this appendix. Cummins’ annual report also state d that transportation cost is a part of G&A costs; thus, the transportation cost contributor wa s subtracted from the G&A cost contributor.

### A-5

Table A-4. Cummins’ RPE Multiplier Calculations: 20 08

RPE Multiplier Contributor Expense ($ Million) Relative to

Cost of Sales Manufacturing Cost Calculation and Source Vehicle Manufacturing Manufacturing Cost 11,726.5 1.00 [p. 36, Cummins, 2 009] − Maintenance and repair (49)+70% *( Health care + retirement) Production Overhead Warranty

221.0 0.02 End of 2008 balance warranty provisions (962) − Beginning of 2008 Balance Warranty Provisions (749) [p. 104, Cummins, 2009] R&D (product development) 422.0 0.04 [p. 24, Cummin s, 2009] Depreciation and amortization 314.0 0.03 [p. 71, Cu mmins, 2009] Maintenance, repair, operations cost 152.9 0.01 Cen sus Total production overhead 1,109.9 0.08 Corporate Overhead General and administrative 1,404.9 0.12 [p. 27, Cum mins, 2009] − Transportation Retirement 62.4 0.01 0.3 * Retirement ((71) [p. 56, Cummins, 2009] + (102) [p. 58, Cummins, 2009] + 35 [p. 71, Cummins 2009]) Health 142.2 0.01 0.3*Health care [p. 87, Cummins, 2009] Total corporate overhead 1,609.5 0.14 Selling Transportation 45.1 0.004 Supplier Relations, LLC Marketing 120.0 0.01 Warranty and Marketing (341) [ p. 87, Cummins, 2009] − Warranty Cost Dealers Dealer new vehicle net income Dealer new vehicle selling cost Total selling and dealer contributors 165.1 0.01 Sum of Indirect Costs 0.23
Net income 755.0 0.06 [p. 27, Cummins, 2009] − Dealer Gross Other costs (not included as contributors) 70.0 0.01 [p. 27, Cummins, 2009] RPE multiplier 1.29

Sources: Supplier Relations LLC (2009); Census (201 0) (see references in Section A.1)

Cummins Inc. 2009. 2008 Annual Report on 10-K Form. Available at: http://phx.corporateir.net/phoenix.zhtml?c=112916&p=irol-reportsannual. Accessed on February 15, 2010.



### We made an assumption that corporate labor represen ts 30% of total labor (total labor comprised of corporate and manufacturing labor). Th us, 30% of retirement and health care cost
were attributed to retirement and health care cost contributors. Please refer to Section 3.3 for a

### A-6

detailed explanation of this assumption. The Cummin s annual report presented retirement costs by division; thus, retirement costs for the three d ivisions were added to calculate total retirement cost (see Table A-4).

Cummins did not provide transportation cost; thus, the industry average (based on the industry report and Census data) was used as a prox y. Finally, the Cummins annual report did not separate warranty and marketing costs but repor ted them as one figure. Therefore, we subtracted the warranty cost from the warranty and marketing cost to arrive at the marketing cost contributor. The remaining contributors to the RPE multiplier are shown in Table A-4. Based on these numbers, the RPE multiplier for Cummins was c alculated to be 1.29 in 2008.

Table A-5 provides a sum of the largest indirect co st contributors to RPE for Cummins from 2002 to 2007. Largest indirect cost contributo rs were readily available in manufacturers’ annual reports. Funds and timing of the project did not allow performing an extended analysis (similar to one done for year 2008) for historical data. The values of cost contributors are not adjusted as in Table A-4but cited as they were repo rted in annual reports. Table A-5 illustrates
that the sum of the main indirect cost contributors had little variation between 2004 and 2007.

Table A-5. Cummins’ Main Indirect Cost Contributors

Indirect Cost Contributor 2007 2006 2005 2004

Cost of sales 1.00 1.00 1.00 1.00 Selling, administrative, and other expenses 0.13 0 .12 0.13 0.15 Operating and other expenses 0.04 0.03 0.04 0.04 Depreciation < 0.01 < 0.01 < 0.01 < 0.01

Net income 0.03 0.03 0.03 0.04
Sum of main indirect cost contributors (including n et income) 1.26 1.26 1.28 1.29

Sources: Cummins Inc. 2006. 2005 Annual Report on 10-K Form. Available at: http://phx.corporateir.net/phoenix.zhtml?c=112916&p=irol-reportsannual. Accessed on February 15, 2010. Cummins Inc. 2009. 2008 Annual Report on 10-K Form. Available at: http://phx.corporateir.net/phoenix.zhtml?c=112916&p=irol-reportsannual. Accessed on February 15, 2010.



### A.2 Hino Motor Company (Engine Manufacturer)
Relevant RPE contributing factors gathered from Hin o’s annual report are presented in Table A-6. The RPE multiplier calculations are base d on 2008 data.

As Table A-6 shows, Hino’s manufacturing cost inclu des 70% of health care and retirement costs, an assumption covered in Section 3.3 of this report. With the exception of the

### A-7

Table A-6. Hino’s RPE Multiplier Calculations: 2008

RPE Multiplier Contributor Expense (¥ Millions) Relative to

Cost of Sales Calculation and Source Vehicle Manufacturing Manufacturing cost 1,137,120 1.00 [p. 1, Hino, 2009 b] + 70% (Retirement) Production Overhead Warranty 10,935 0.01 [p. 7, Hino, 2009a] R&D (product development) 39,547 0.03 [p. 1, Hino, 2009b] Depreciation and amortization 44,206 0.04 [p. 1, Hi no, 2009b] Maintenance, repair, operations cost 15,730 0.01 Ce nsus Total production overhead 110,418 0.10 Corporate Overhead General and administrative 99,066 0.09 General and Administrative (149,769) [p. 7, Hino, 2009a] − Retirement [p. 7, Hino, 2009a] − Transportation [p. 7, Hino, 2009a] − Advertising [p. 7, Hino, 2009a] − Health care Retirement 11,555 0.01 Supplier Relations, LLC Health 23,109 0.02 Supplier Relations, LLC Total corporate overhead 133,730 0.12 Selling Transportation 12,158 0.01 [p. 7, Hino, 2009a] Marketing 3,879 0.003 Advertising [p. 7, Hino, 2009 a] Dealers Dealer new vehicle net income Dealer new vehicle selling cost Total selling and dealer contributors 16,037 0.01 Sum of Indirect Costs 260,185 0.23 Net income 22,178 0.02 [p. 7, Hino, 2009a]

Other costs (not included as contributors) 10,602 0.01 Total nonoperating expenses [p. 7, Hino, 2009a] RPE multiplier 1,419,483 1.25

Sources: Supplier Relations LLC (2009); Census (201 0) (see references in Section A.1)

Hino Motors, Ltd. and Consolidated Subsidiaries, 20 09a. Hino: Financial Results of the Fiscal Year End ed March 31, 2009. Hino Motors, Ltd. and Consolidated Subsidiaries, 20 09b. Hino: Five-year Summary Ended March 31, 2009.



### MRO costs, values for production overhead were repo rted from Hino’s financial statements. Because Hino did not report MRO costs, an industry average (based on Census data) was used as a proxy. Hino’s G&A expense included re tirement, health care, transportation, and advertising. These costs have been subtracted from the G&A cost reported by Hino. Hino did not report health care and retirement costs, so we used an industry average as a proxy (based on data

### A-8

from SR LLC report; see Section A.1 for a detailed calculation). Hino’s remaining contributors to the RPE multiplier are shown in Table A-6. Based on these figures, Hino’s RPE for 2008 was
1.25.

Hino’s sum of the main indirect cost contributors r emained relatively flat from 2004 to
2007. The sum of the main indirect cost contributor s varied between 1.21 and 1.25 in the 2004 to 2007 time period (Table A-7).

Table A-7. Hino’s Main Indirect Cost Contributors

Indirect Cost Contributor 2007 2006 2005 2004

Cost of sales 1.00 1.00 1.00 1.00 Selling, administrative, and other expenses 0.13 0.13 0.13 0.14 Operating and other expenses NA NA NA NA Depreciation 0.03 0.03 0.03 0.03

Net income 0.02 0.03 0.02 0.04
Sum of main indirect cost contributors (including n et income) 1.22 1.23 1.21 1.25

Sources: Hino Motors, Ltd. and Consolidated Subsidi aries, 2009b. Hino: Five-year Summary Ended March 31, 2009.


### A.3 PACCAR (Heavy Duty Truck Manufacturer)
Relevant RPE contributing factors gathered from PAC CAR’s annual report are presented in Table A-8. PACCAR included “transportation expen se” in its cost of sales, representing approximately 0.4% of the cost of sales. We subtrac ted this line item, $46.5 million (see Table A-8), from the cost of sales to arrive at an adjust ed value for the manufacturing cost of $11.5 billion. PACCAR’s reported G&A cost included transp ortation ($46.5) and marketing costs ($115 million), which were subtracted from G&A to a rrive at an adjusted cost contributor of $308.7 million. Marketing costs were not reported b y PACCAR, so an industry average of 0.01 was used as a proxy. Also, PACCAR did not directly report transportation costs, which were assumed to be an industry average based on SR LLC d ata (see Section A.1 for these calculations).

PACCAR did not report MRO costs; therefore, we used an industry average of 0.02 (based on the Census data) as a proxy. Results of t hese calculations are presented in Table A-8.

### A-9

Table A-8. PACCAR RPE Multiplier Calculations: 2008

RPE Multiplier Contributor Expense ($ Million) Relative to

Cost of Sales Calculation and Source Vehicle Manufacturing Manufacturing cost 11,550 1.00 Cost of sales − tran sportation expense (0.4%) [Walter McManus, personal communication]
Production Overhead Warranty 304.6 0.03 [p. 40, PACCAR, 2008]

R&D (product development) 341.8 0.03 [p. 31, PACCAR, 2008]

Depreciation and amortization 649.4 0.06 [p. 49, PACCAR, 2008]

Maintenance, repair, operations
cost 186.5 0.02 Census

Total production overhead 1,482.3 0.13 Corporate Overhead
General and administrative 308.7 0.03 General & administrative (470.2) [p. 24, PACCAR, 2008] − Transportation (46.5) − Marketing (115.0)
Retirement 118.7 0.01 Benefits paid (48.8) [p. 42 of PACCAR Annual Report 2008] + Employer contributions (69.9) [p. 42 of PACCAR Annual Report 2008]
Health 12.0 0.001 Benefits paid (4.1) [p. 43, PACCAR, 2009] + Service cost (3.2) [p. 43, PACCAR, 2009] + Interest cost (4.7) [p. 43, PACCAR, 2009] Total corporate overhead 439.4 0.04 Selling Transportation 46.5 0.004 Supplier Relations, LLC Marketing 115.0 0.01 20% * [Marketing cost from LD Study] (Walter McManus, personal communication)

Dealers
Dealer new vehicle net income 46.2 0.004 Walter McManus, personal communication Dealer new vehicle selling cost 693.0 0.06 Walter McManus, personal communication Total selling and dealer contributors 900.7 0.08

Sum of Indirect Costs 1,921.7 0.24 Net income 1,017.9 0.09 [p. 1, PACCAR, 2008] Other costs (not included as contributors) 1.1 <0.001 [p. 34, PACCAR, 2008]

RPE multiplier 1.33
Sources: Supplier Relations LLC (2009); Census (20 10) (see references in Section A.1) PACCAR, 2008. PACCAR: Annual Report 2008. Available at: http://www.paccar.com/investors/ investor_resources_history.asp. Accessed on Februar y 7, 2010. Walter McManus, personal communication on February 16, 2010.

### A-10

As mentioned in Section 3.3 of this report, health care and retirement costs include expenditures for manufacturing and corporate worker s. PACCAR’s annual report provided figures for retirement costs in two categories: “be nefits paid” of $48.8 million and “employer contributions” of $69.9 million in 2008. These two costs were summed, totaling $118.7 million
for our retirement cost contributor. As with retire ment, PACCAR disaggregated 2008 health care costs into several categories: “benefits paid” of $ 4.1 million, “service cost” of $3.2 million, and “interest cost” of $4.7. These costs were summed to gether, bringing the health care cost contributor to a total of $12.0 million. The indust ry average values of 0.004 and 0.06 were used
for dealer new vehicle net income and dealer new ve hicle selling cost contributors. As a result, the value of the RPE multiplier for PACCAR was 1.33 in 2008.

Table A-9 presents PACCAR’s sum of the main indirec t cost contributors for years prior
to 2008. The sum of the main indirect cost contribu tors for earlier years was lower than the RPE multiplier value derived for 2008; however, the mai n cost contributors reported in Table A-9 range within 0.02 from cost contributors reported i n Table A-8.

Table A-9. PACCAR Main Indirect Cost Contributors

Indirect Cost Contributor 2007 2006 2005 2004

Cost of sales 1.00 1.00 1.00 1.00 Selling, administrative, and other expenses 0.04 0.04 0.04 0.04 Operating and other expenses NA NA NA NA Depreciation 0.04 0.03 0.03 0.03

Net income 0.10 0.11 0.10 0.10
Sum of main indirect cost contributors (including n et income) 1.21 1.20 1.18 1.19

Sources: PACCAR, 2006. PACCAR: Annual Report 2005. Available at: http://www.paccar.com/ investors/investor_resources_history.asp. Accessed on February 7, 2010. PACCAR, 2009. PACCAR: Annual Report 2008. Available at: http://www.paccar.com/ investors/investor_resources_history.asp. Accessed on February 7, 2010.



### A.4 Navistar (Heavy Duty Truck Manufacturer)
Table A-10 presents relevant RPE cost contributors and the RPE multiplier for Navistar in 2008. Navistar allocates a portion of “postretir ement benefit expense” in its cost of sales reporting. Thus, we subtracted this cost ($33 milli on) from the cost of sales to arrive at an adjusted manufacturing cost of $11,849 million. Nav istar also allocates a portion of

### A-11

Table A-10. Navistar RPE Multiplier Calculations: 2 008

RPE Multiplier Contributor Expense ($ Millions) Relative to

Cost of Sales Calculation and Source Vehicle Manufacturing Manufacturing cost 11,849.4 1.00 Cost of sales [p. 23, Navistar, 2008] − Truck postretirement benefit expense allocated to costs of products sold (22) [p. 42, Navistar, 2008] − Engine postretirement benefit expense allocated to costs of products sold (11) [p. 45, Navistar, 2008] Production Overhead Warranty 257.0 0.02 [p. 24, Navistar, 2008] R&D (product development) 384.0 0.03 [p. E-28, Navistar, 2008] Depreciation and amortization 393.0 0.03 [p. 72, Navistar, 2008] Maintenance, repair, operations cost 358.0 0.03 [p. E-28, Navistar, 2008] Total production overhead 1,392.0 0.12 Corporate Overhead General and administrative 1,389.8 0.12 [p. E-28, Navistar, 2008] − Postretirement benefits expense allocated to selling, general and administrative expenses (6) [p. 43, Navistar, 2008] − Transportation (47.2) [Supplier Relations, LLC] Retirement 355.0 0.03 [p. 116, Navistar, 2008] Health 209.0 0.02 [p. 116, Navistar, 2009] Total corporate overhead 1,953.8 0.16 Selling Transportation 47.2 0.004 Supplier Relations, LLC Marketing 24.0 0.00 [p. 83, Navistar, 2008] Dealers Dealer new vehicle net income 47.4 0.004 Walter McManus, personal communication

Dealer new vehicle selling
cost 711.0 0.06 Walter McManus, personal communication

Total selling and dealer contributors 829.6 0.07 [p. 25, Navistar, 2008]

Sum of Indirect Costs 4,175.4 0.35 Net income 134.0 0.01 [p. 23, Navistar, 2008] Other costs (not included as contributors) 14.0 0.001 [p. 26, Navistar, 2008]

RPE multiplier 1.36
Sources: Supplier Relations LLC (2009) (see referen ces in Section A.1) Navistar, 2008. Annual Report 2008. Available at: http://ir.navistar.com/sec.cfm. Accessed February 7

, 2010. Walter McManus, personal communication on February 16, 2010.

### A-12

“postretirement benefit expense” ($6 million) to G& A cost. Thus, we subtracted this expense from G&A. As with all the heavy duty truck manufact urers, we assumed the transportation cost ($47.2 million) was 0.4% of manufacturing costs (SR LLC). Based on the light duty vehicle study and personal communications with Walter McMan us (February 16, 2010), we imputed a dealer cost of $758 million. Navistar’s RPE multipl ier value was calculated to be 1.36 for 2008.

Navistar’s annual reports were available dating bac k to 2004. Similar to PACCAR,
Navistar’s sum of the main indirect cost contributo rs from 2004 to 2007 is lower than the RPE derived for 2008 (see Table A-11). However, the mai n cost contributors reported in Table A-9 range within 0.03 of cost contributors reported in Table A-8.

Table A-11. Navistar Main Indirect Cost Contributor s (as a Share of Cost of Sales)

Indirect Cost Contributor 2007 2006 2005 2004
Cost of sales 1.00 1.00 1.00 1.00 Selling, administrative, and other expenses 0.14 0. 11 0.10 0.11 Operating and other expenses < 0.01 < 0.01 < 0.01 < 0.01 Depreciation 0.04 0.03 0.03 0.03
Net income −0.01 0.03 0.01 −0.01 Sum of main indirect cost contributors (including n et income) 1.21 1.21 1.19 1.18

Sources: Navistar, 2005. Annual Report 2005. Availa ble at: http://ir.navistar.com/sec.cfm. Accessed Fe bruary 7, 2010. Navistar, 2008. Annual Report 2008. Available at: h ttp://ir.navistar.com/sec.cfm. Accessed February 7, 2010.



### A.6 Daimler (Heavy Duty Truck Manufacturer)
Relevant RPE contributing factors gathered from Dai mler’s annual report are presented in Table A-12. As with Volvo, Daimler has several o perating divisions, one of which is exclusive to the manufacturing of heavy duty diesel trucks. T he following reporting of cost contributors is
based on Daimler’s truck division. Daimler’s annual report did not provide an estimate of MRO cost; therefore, the industry average (based on Cen sus data) was used as a proxy (see Table A-12). In congruence with the other manufactu rers that did not directly report health care cost, we assumed manufacturing cost would reflect t he industry average of 70% of health care cost (see Table A-12). Warranty costs were reported as containing a portion of pension (€15 million) and health care costs (€3.2 million), and these two costs were subtracted to arrive at an adjusted warranty cost contributor of €953.7 millio n.

### A-13

Table A-12. Daimler (Truck) RPE Multiplier Calculat ions: 2008

RPE Multiplier Contributor Expense (€ Millions) Relative to

Cost of Sales Calculation and Source Vehicle Manufacturing Manufacturing cost 22,345.9 1.00 Cost of sales [p. 207, Daimler, 2008] + (70% * Health care)
Production Overhead Warranty 953.7 0.04 [p. 73, Daimler, 2008] (Warrant y, pensions, and Health care lumped together (18.2) − Pensions provisions (15.0))*Adjustment factor from Daimler Group to Daimler Trucks R&D (product development) 1,056.0 0.05 [p. 62, Daim ler, 2008] Depreciation and amortization 646.0 0.03 [p. 207, D aimler, 2008] Maintenance, repair, operations
cost 355.0 0.02 Census

Total production overhead 3,010.7 0.13 Corporate Overhead General and administrative 655.4 0.03 [p. 144, Daim ler, 2008] ( General & administrative for Daimler Group was reported as 4,124) − Health care − Transportation − Marketing Retirement 236.0 0.01 30% * [p. 53, Daimler, 2008] Health 261.8 0.01 Supplier Relations, LLC Total corporate overhead 1,153.2 0.05 Selling Transportation 87.7 0.004 Supplier Relations, LLC Marketing 222.6 0.01 20% * [Marketing cost from LD Study] (Walter McManus, personal communication)

Dealers
Dealer new vehicle net income 89.4 0.004 Walter McM anus, personal communication Dealer new vehicle selling cost 1,340.8 0.06 Walter McManus, personal communication Total selling and dealer contributors 1,740.4 0.08

Sum of Indirect Costs 5,904.2 0.26 Net income 1,607.0 0.07 [p. 207, Daimler, 2008] Other costs (not included as contributors) 0

RPE multiplier 1.34
Sources: Supplier Relations LLC (2009); Census (201 0) (see references in Section A.1) Daimler, 2008. Annual Report 2008. Available at: h ttp://www.daimler.com/investor-relations/reports-an dkey-figures/annual-documents/daimler-ag. Accessed F ebruary 7, 2010. Walter McManus, personal communication on February 16, 2010.

### A-14

Daimler (truck) did not directly report G&A expense s. Our methodology for determining G&A for Daimler (truck) was based on an imputed rat io of Daimler Group’s G&A expense to Daimler Group’s cost of sales (see Table A-12). G&A costs were reported to contain health care costs and transportation costs, both of which were subtracted from the imputed G&A cost to arrive at an adjusted G&A cost contributor for Daim ler’s truck division. Selling expenses (transportation, marketing, dealer support, and dea ler discount) were reported as an industry average based on information from SR LLC and person al communication with Walter McManus. Daimler also did not provide an estimate o f health care cost, so we calculated the health care cost contributor based on an industry a verage (SR LLC). Daimler’s (truck) RPE multiplier value was calculated to be 1.34 in 2008.

Daimler experienced mild variation in its sum of ma in indirect cost contributors (see Table A-13). Between 2005 and 2007, the sum of main indirect cost contributors varied between
1.33 and 1.42.

Table A-13. Daimler Main Indirect Cost Contributors

Indirect Cost Contributor 2007 2006 2005

Cost of sales 1.00 1.00 1.00 Selling, administrative, and other expenses 0.17 0. 17 0.17 Operating and other expenses < 0.01 0.01 0.00 Depreciation 0.11 0.16 0.16

Net income 0.05 0.05 —
Sum of main indirect cost contributors (including n et income) 1.37 1.42 1.33

Sources: Daimler, 2006. Annual Report 2006. Availab le at: http://www.daimler.com/investor-relations/re ports-and-keyfigures/annual-documents/daimler-ag. Accessed Febru ary 7, 2010. Daimler, 2008. Annual Report 2008. Available at: ht tp://www.daimler.com/investor-relations/reports-and -keyfigures/annual-documents/daimler-ag. Accessed Febru ary 7, 2010.


### A.7 Volvo (Heavy Duty Truck Manufacturer)
RPE calculations for Volvo’s truck division are pre sented in Table A-14. Volvo’s annual report segregated its financials among six operatin g divisions, one of which was the heavy duty diesel truck division. In 2008, Volvo’s (truck) man ufacturing cost equaled SEK 231,435. Volvo (truck) did not report transportation, marketing, o r dealer costs; therefore, imputed values from SR LLC and personal communications with Walter McMa nus were used as proxies. G&A costs were reported for Volvo (truck) and included transp ortation and marketing costs; these costs

### A-15

Table A-14. Volvo (Truck) RPE Multiplier Calculatio ns: 2008

RPE Multiplier Contributor Expense (SEK Millions) Relative to Cost

of Sales Calculation and Source Vehicle Manufacturing Manufacturing cost 231,435.5 1.00 [p. 75, Volvo, 2008]

Production Overhead Warranty 10,354.0 0.04 [p. 86, Volvo, 2008] R&D (product development) 14,348.0 0.06 [p. 75, Volvo, 2008] Depreciation and amortization 13,524.0 0.06 [p. 78, Volvo, 2008] Maintenance, repair, operations
cost 1,915.0 0.01 [p. 78, Volvo, 2009] Total production overhead 40,141.0 0.17 Corporate Overhead

General and administrative 28,518.4 0.12 Administrative expenses and selling expenses (31,763.9) [p. 75, Volvo, 2008] − Transportation (940.5) − Marketing (2,301.1) Retirement 1,365.0 0.01

Health 847.2 0.004 30% * [p. 106, Volvo, 2008]

Total corporate overhead 30,730.6 0.13 Selling Transportation 940.5 0.004 30% * [p. 106, Volvo, 2008]

Marketing 2,305.1 0.01 20% * [Marketing cost from LD Study] (Walter McManus, personal communication)
Dealers

Dealer new vehicle net income 925.7 0.004 Walter McManus, personal communication
Dealer new vehicle selling cost 13,886.1 0.06 Walter McManus, personal communication

Total selling and dealer contributors 18,057.4 0.08

Sum of Indirect Costs 0.38

Net income 10,016.0 0.04 [p. 93, Volvo, 2008]

Other costs (not included as contributors) 1,802.0 0.01 Dealer bonus [p.109, Volvo, 2008]

RPE multiplier 1.43

Sources: Supplier Relations LLC (2009); Census (201 0) (see references in Section A.1) Volvo Group, 2008. Annual Report 2008. Available a t: http://www.volvogroup.com/GROUP/GLOBAL/ENGB/INVESTORS/Pages/investor_relations.aspx. Accesse d February 7, 2010. Walter McManus, personal communication on February 16, 2010.

### A-16

were subtracted to determine G&A (see Table A-12). The RPE multiplier for Volvo (truck) equaled 1.43 in 2008.

Table A-15 presents Volvo’s sum of the main indirec t cost contributors, which are again
lower than the RPE value derived above for 2008.

Table A-15. Volvo Main Indirect Cost Contributors

Indirect Cost Contributor 2007 2006 2005 2004

Cost of sales 1.00 1.00 1.00 1.00 Selling, administrative, and other expenses 0.15 0.14 0.14 0.15 Operating and other expenses < 0.01 < 0.01 < 0.01 < 0.01 Depreciation 0.06 0.06 0.05 0.06

Net income 0.07 0.08 0.07 0.06
Sum of main indirect cost contributors (including n et income) 1.33 1.33 1.31 1.32

Sources: Volvo Group, 2006. Annual Report 2006. Ava ilable at: http://www.volvogroup.com/GROUP/ GLOBAL/EN-GB/INVESTORS/Pages/investor_relations.asp x. Accessed on February 7, 2010. Volvo Group, 2008. Annual Report 2008. Available at : http://www.volvogroup.com/GROUP/ GLOBAL/EN-GB/INVESTORS/Pages/investor_relations.asp x. Accessed on February 7, 2010.