ORNL/TM-2004/181 

Future Potential of Hybrid and Diesel 

Powertrains in the U.S. Light-Duty 

Vehicle Market 

August 2004 

David L. Greene 

Oak Ridge National Laboratory 

K. G. Duleep 

Energy & Environmental Analysis, Inc. 

Walter McManus 

J. D. Power and Associates
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FUTURE POTENTIAL OF HYBRID AND DIESEL POWERTRAINS IN 

THE U.S. LIGHT-DUTY VEHICLE MARKET 

David L. Greene 

Oak Ridge National Laboratory 

National Transportation Research Center 

2360 Cherahala Boulevard 

Knoxville, TN 37932 

K.G. Duleep 

Energy & Environmental Analysis, Inc. 

1655 North Fort Meyer Drive, Suite 600 

Arlington, VA 22209 

Walter McManus 

J.D. Power and Associates 

5435 Corp Drive, Suite 300 

Troy, MI 48098 

August 20, 2004 

Prepared by the 

OAK RIDGE NATIONAL LABORATORY 

P.O. BOX 2008 

Oak Ridge, Tennessee 37830 

managed by 

UT-Battelle, LLC 

for the 

U.S. DEPARTMENT OF ENERGY 

under contract No. DE-AC0500OR22725 

v 

TABLE OF CONTENTS 

Page 

LIST OF FIGURES .........................................................................................................................v 

LIST OF TABLES........................................................................................................................ vii 

ACKNOWLEDGMENTS ............................................................................................................. ix 

ABSTRACT .............................................................................................................................. xiii 

1. INTRODUCTION .....................................................................................................................1 

2. HYBRID AND DIESEL TECHNOLOGY STATUS AND PROSPECTS...............................3 

 2.1 DIESELS..............................................................................................................................3 

 2.2 HYBRIDS............................................................................................................................7 

3. RECENT MARKET ASSESSMENTS ...................................................................................13 

 3.1 DOE PROJECTIONS ........................................................................................................14 

4. METHODOLOGY AND DATA.............................................................................................17 

 4.1 SCENARIOS OF DIESEL AND HYBRID INTRODUCTIONS.....................................17 

 4.2 CONSUMER CHOICE MODEL ......................................................................................18 

 4.3 MARKET SEGMENTATION AND CHOICE MODEL STRUCTURE .........................20 

 4.4 CHOICE MODEL CALIBRATION .................................................................................22 

 4.5 PRICE SLOPES.................................................................................................................22 

5. RESULTS ................................................................................................................................31 

 5.1 THE LONG-RUN POTENTIAL MARKET SHARES OF DIESEL AND HYBRID 

 VEHICLES ........................................................................................................................31 

 5.2 2008 SCENARIOS ............................................................................................................39 

 5.3 2012 SCENARIOS ............................................................................................................41 

 5.4 IMPACTS ON FUEL ECONOMY ...................................................................................44 

 5.5 SENSITIVITY ANALYSIS ..............................................................................................48 

6. CONCLUSIONS......................................................................................................................55 

REFERENCES ..............................................................................................................................57 

APPENDIX A: CALCULATION OF CONFIGURATION AND CLASS CONSTANTS..........63 

APPENDIX B: ASSUMED PRODUCT INTRODUCTIONS......................................................67 

APPENDIX C: CHARACTERISTICS OF DIESEL AND HYBRID PRODUCT LINES 

 FOR WHICH THRE IS NO MODEL YEAR 2002 COUNTERPART ..................................77 

vii 

LIST OF FIGURES 

Figure Page 

1 The Public’s Impression of Diesel Fuel Availability in May, 2004 ..........................................4 

2 Diesel Vehicle Owners’ Views on Clean Diesel Vehicles ........................................................5 

3 Gasoline Vehicle Owners’ Views on Clean Diesel Vehicles ....................................................6 

4 Gasoline Vehicle Owners’ Views on Hybrid-Electric Vehicles................................................8 

5 Hybrid-Electric Vehicle Owners’ Views on Hybrid-Electric Vehicles.....................................8 

6 Intent to Purchase Diesel or Hybrid-Electric Vehicle..............................................................13 

7 Projections of Light-Duty Hybrid and Diesel Market Shares..................................................14 

8 Projected Diesel Market Shares in the United States...............................................................15 

9 Nested Multinomial Logit Model Structure and Approximate Price Elasticities....................20 

10 Power Functions Describing the Cost of Limited Fuel Availability........................................28 

11 Technology Market Shares by Vehicle Type >2012 Diesel Only Scenario ............................33 

12 Makes, Models, Configurations by Vehicle Type >2012 Diesel Only Scenario.....................33 

13 Technology Market Shares by Vehicle Type >2012 Full Hybrid Scenario.............................34 

14 Makes, Models, Configurations by Vehicle Type >2012 Full Hybrid Scenario .....................35 

15 Technology Market Shares by Vehicle Type >2012 Diesel & Full Hybrid Scenario .............36 

16 Makes, Models, Configurations by Vehicle Type >2012 Diesel & Full Hybrid Scenario......37 

17 Technology Market Shares by Vehicle Type >2012 Diesel & ISAD Hybrid Scenario ..........38 

18 Makes, Models, Configurations by Vehicle Type >2012 Diesel & ISAD Hybrid Scenario...38 

19 Diesel and Hybrid Vehicle Market Shares by Vehicle Type: 2008 Average Scenario ...........39 

20 Distribution of Hybrid Vehicle Sales by Degree of Hybridization, 2008 Average Scenario..40 

21 Diesel and Hybrid Market Shares by Vehicle Class, “Best Guess” Scenario .........................40 

22 Distribution of Hybrid Vehicle Sales by Degree of Hybridization, 2008 “Best Guess” 

 Scenario ................................................................................................................................41 

23 Hybrid and Diesel Market Shares by Vehicle Class, 2012 “Average” Scenario.....................41 

24 Distribution of Hybrid Technology Types in the 2012 “Best Guess” Scenario ......................42 

25 Comparison of Market Success in “Average” and “Best Guess” Scenarios ...........................43 

26 Distribution of Hybrid Vehicle Sales by Degree of Hybridization, 2012 

 “Average” Scenario .................................................................................................................43 

27 Distribution of Hybrid Vehicle Sales by Degree of Hybridization, 2012 “Best Guess” 

 Scenario ................................................................................................................................44 

28 New Light-Duty Vehicle Average Fuel Economy by Scenario...............................................45 

29 Sensitivity Analysis of Diesel Market Share, >2012 Diesel/Full Hybrid Scenario.................49 

30 Tornado Chart Showing Influence of Inputs on Diesel Market Share.....................................50 

31 Sensitivity Analysis of Hybrid Market Share, >2012 Diesel/Full Hybrid Scenario................51 

32 Tornado Chart Showing Influence of Inputs on Hybrid Market Share ...................................51 

33 Sensitivity Analysis of LDV Fuel Economy, >2012 Diesel/Full Hybrid Scenario.................52 

34 Tornado Chart Showing Influence of Inputs on LDV Fuel Economy.....................................53 

35 Comparison of Market Success in 2008 and 2012 under “Best Guess” Scenarios .................55 

ix 

LIST OF TABLES 

Table Page 

1 Estimated Additional Torque and Fuel Economy of Light-duty Diesel Vehicles.....................3 

2 Estimated Incremental Retail Price Equivalent for Diesel Vehicles .........................................6 

3 Estimated Additional Torque and Fuel Economy of Hybrid Vehicles......................................9 

4 Estimated Incremental Retail Price Equivalent of Hybrid Systems by Vehicle Type.............10 

5 Planned Introductions of Hybrid-Electric Vehicles in the U.S. Market ..................................11 

6 (Part 1) Definitions of Vehicle Classes....................................................................................21

6 (Part 2) California Energy Commission (CEC) Vehicle Classification System......................21 

7 Estimated Price Elasticities for Diesel and Hybrid Market Shares Based on a Survey 

 by J.D. Power and Associates..................................................................................................23 

8 Price Slopes, Elasticities, Prices and Market Shares for Market Segments.............................24 

9 Coefficients of the NMNL Vehicle Choice Model..................................................................26 

10 Numbers of Diesel and Hybrid Configurations Offered, by Scenario.....................................32 

11 Summary of Results of Diesel Hybrid Market Scenarios........................................................46 

12 Average Fuel Economy of Passenger Cars and Light Trucks .................................................47 

13 Assumptions for Sensitivity Analysis of Hybrid and Diesel Choice.......................................48 

 xi 

ACKNOWLEDGMENTS 

The authors thank the U.S. Departments of Energy and Transportation, and Natural Resources 

Canada for supporting this research. We also thank the representatives of those agencies who 

provided invaluable guidance and advice throughout the course of the project. 

Barry McNutt, Office of Petroleum and Transportation Fuels, Policy and International 

Affairs, U.S. Department of Energy 

Ed Wall, Office of Freedom Car and Vehicle Technology, U.S. Department of Energy 

Philip Patterson, Office of Energy Efficiency and Renewable Energy, U.S. Department of 

Energy 

Thomas White, Office of Petroleum and Transportation Fuels, Policy and International 

Affairs, U.S. Department of Energy 

John Maples, Energy Information Administration, U.S. Department of Energy 

Peter Feather, National Highway Traffic Safety Administration, U.S. Department of 

Transportation 

Kenneth Katz, National Highway Traffic Safety Administration, U.S. Department of 

Transportation 

Peter Reilly-Roe, Transportation Energy Use Division, Natural Resources Canada 

The authors thank these individuals and Steve Plotkin, Argonne National Laboratory for critical 

reviews of an earlier version of this report. 

The authors also thank the many individuals from private industry in the U.S., Japan and Europe 

who met with us and shared their knowledge and insights, especially the following. 

 Daimler Chrysler, Detroit, Michigan: 

Bernard Robertson, Senior Vice President, Engineering Technologies and Regulatory 

Affairs 

Philip Benjamin, Manager, Small Vehicle Product Team, Hybrid Vehicle Engineering 

Reginald Modlin, JD, Director, Environmental and Energy Planning 

Loren Beard, Senior Manager, Environmental and Energy Planning 

Lawrence Oswald, CEO, Global Electric Motorcars, LLC, Daimler Chrysler 

 U.S. Environmental Protection Agency, Ann Arbor, Michigan: 

Charles Gray, Director Advanced Technology Division, Office of Transportation and Air 

Quality 

Karl Hellman, Assistant Director, Advanced Technology Division, OTAQ 

Jeff Alson, Corporate Average Fuel Economy Policy Issues, OTAQ 

Robert Heavenrich, Fuel Economy Trends, OTAQ 

John White, Cooperative R&D Agreements, OTAQ 

 General Motors, Detroit Michigan: 

Hazem Ezzat, Director, Powertrain Engineering 

Shareef Ultari, Senior Research Engineer, Diesel Engine Research 

Peter Savagian, Chief Engineer, Traction and Thermal Systems 

 
 xii 

 Ford Motor Company, Detroit, Michigan: 

Graham Hoare, Director, Powertrain Research & Advanced Engineering 

Larry Brouwer, Chief Engineer, Advanced Powertrains 

William Stockhausen, Staff Technical Specialist, Strategic Powertrain Technologies, 

Powertrain Research & Advanced Engineering 

Robert Hammerle, Senior Staff Technical Specialist, Chemical Engineering Department 

Richard Baker, Corporate Technical Specialist, Combustion & Emissions Advanced 

Diesel Systems 

Richard Bell, Manager, Worldwide Recycling Planning, Vehicle Environmental 

Engineering 

Mike Tamor, Project Leader, Hybrid Electric Vehicle Design 

 Daimler-Chrysler, Stuttgart, Germany: 

Harald Braun, Manager, Passenger Car Development, Powertrain Electronics, Alternative 

Drives 

Gerhard Doll, Leader, V8 Diesel Engine Development 

Andreas Graf, Manager, Regulatory Affairs, Emissions and Fuel Consumption 

Gerhard Schweinle, Senior Manager, Regulatory Affairs and Government Liaison for 

Mercedes-Benz Passenger Cars 

Oliver Storz, Manager, Emission Certification and Government Liaison Worldwide 

(excluding USA) Large Passenger Cars and in Use 

Rudolph Thom, Director, Development MB-Passenger Cars Certification and Regulatory 

Affairs 

 FEV, Aachen, Germany: 

Peter Walzer, Executive Vice President 

Michael Krüger, Chief Engineer, Diesel Combustion Systems 

 Continental TEMIC, Landsberg, Germany: 

Frank Blome, Director, Profit Center ISAD 

Frank Kozlowski, Sales and Marketing, Profit Center ISAD 

Horst Kornemann, Director, Product Line Electronic Drives, ISAD 

Uwe Mohrstadt, Senior Manager, Sales and Marketing, ISAD 

 Bosch, Stuttgart, Germany: 

Stefan Becher, Group Leader, Development Engine Test Field, Commercial Vehicle 

Engines, Emission Legislation, Fuels 

Marcus Parche, Vice President, Marketing 

Thomas Wintrich, Head of Department, Advanced Engineering 

 Volkswagen, Wolfsburg, Germany 

Ekkehard Pott, Advanced Gasoline Engines 

Wolfgang Steiger, Director, Powertrain Group Research 

 Japan Automotive Research Institute, Tsukuba, Ibaraki, Japan: 

Kiyoyuki Minato, Senior Researcher 

Hirota Keiko, Researcher 
 xiii 

 Chuo University, Tokyo, Japan: 

Professor Tanishita, Department of Civil Engineering 

 Hitachi Automotive Systems, Hitachinaka, Japan 

Fumitoshi Emura, Manager of Sales 

Mr. Naiato, Senior Chief Engineer 

Tadashi Fujikado, General Manager, Marketing and Planning Department 

Tatsuo Horiba, Chief Researcher, Saitana Research Laboratory, Shin-Kobe Electric 

Machinery Co., Ltd. 

 Panasonic Electric Vehicle Energy, Nagoya, Japan 

Yuichi Fujii, Executive Vice President 

Osamu Takahashi, General Manager, Engineering Department 

Tadashi Fujikado, General Manager, Marketing and Planning Department 

 Toyota Motor Corporation, Nagoya, Japan 

Masatami Takimoto, Senior Managing Director, Powertrain Development Group and 

Fuel Cell Development Group 

 Toyota Motor Corporation, Toyotashi, Japan 

Kenichiro Takama, Project General Manager, R&D Management Division 

Toshiyuki Sekimore, General Manager, Electric and Hybrid Vehicle Engineering 

Division 

Takehisa Yaegashi, Senior General Manager, Powertrain Development Group 

Toshiro Yoshida, General Manager Powertrain Planning Department 

Takuku Masuoka, General Manager, Government and Regulatory Affairs Department, 

Engineering Administration Division 

Fumiaki Ohya, General Manager, Government and Regulatory Affairs Department, 

Engineering Administration Division 

 Honda Motor Company, Ltd., Tokyo, Japan 

Hikekazu Kanour, Chief Engineer, Advanced Product Planning Division 

Hiroo Shimada, Chief Engineer, Advanced Product Planning Division 

Kenji Nakano, Chief Engineer and Manager, Engineering Development H2 

Hiroshi Shuto, Chief Engineer, Regulatory Information Coordination Department 

Satoshi Fujitani, Chief Engineer, Regulatory Information Coordination Department 

John German, Environmental and Energy Analyses, Honda of America 

While all of the individuals mentioned above made significant contributions to the quality of this 

report, any errors or omissions it may contain are the sole responsibility of the authors.

xv 

ABSTRACT 

Diesel and hybrid technologies each have the potential to increase light-duty vehicle fuel 

economy by a third or more without loss of performance, yet these technologies have typically 

been excluded from technical assessments of fuel economy potential on the grounds that hybrids 

are too expensive and diesels cannot meet Tier 2 emissions standards. Recently, hybrid costs 

have come down and the few hybrid makes available are selling well. Diesels have made great 

strides in reducing particulate and nitrogen oxide emissions, and are likely though not certain to 

meet future standards. In light of these developments, this study takes a detailed look at the 

market potential of these two powertrain technologies and their possible impacts on light-duty 

vehicle fuel economy. A nested multinomial logit model of vehicle choice was calibrated to 

2002 model year sales of 930 makes, models and engine-transmission configurations. Based on 

an assessment of the status and outlook for the two technologies, market shares were predicted 

for 2008, 2012 and beyond, assuming no additional increase in fuel economy standards or other 

new policy initiatives. Current tax incentives for hybrids are assumed to be phased out by 2008. 

Given announced and likely introductions by 2008, hybrids could capture 4-7% and diesels 2-4% 

of the light-duty market. Based on our best guesses for further introductions, these shares could 

increase to 10-15% for hybrids and 4-7% for diesels by 2012. The resulting impacts on fleet 

average fuel economy would be about +2% in 2008 and +4% in 2012. If diesels and hybrids 

were widely available across vehicle classes, makes, and models, they could capture 40% or 

more of the light-duty vehicle market. 

1 

1. INTRODUCTION 

Direct-injection diesel engines and hybrid-electric power trains can significantly increase fuel 

economy without sacrificing attributes consumers value, but at a higher cost. At present, only a 

few makes and models offer these power train options and there is considerable uncertainty 

about their future in the U.S. light-duty vehicle market. This study assesses the future market 

potential of these technologies in competition with conventional gasoline power trains, and their 

potential impact on new light-duty vehicle fuel economy. Estimates are developed of the market 

potential for these technologies in competition with the conventional gasoline internal 

combustion engines that dominate the U.S. market today. 

Diesel and hybrid technologies each have the potential to increase any given light-duty vehicle’s 

fuel economy by a third or more without loss of performance, yet these technologies have 

typically been excluded from technical assessments of fuel economy potential on the grounds 

that hybrids are too expensive and diesels cannot meet Tier 2 emissions standards (NRC, 2002). 

However, hybrid vehicles are already present in the automotive marketplace and are selling well; 

sales increased 26% from 2002 to 2003 despite the availability of only three hybrid models 

(CNN, May 17, 2004). In Europe, sales of modern, direct-injection, high-pressure-injection 

diesel cars comprised 44% of 2003 passenger car sales (Schmidt, 2004). Yet only one 

manufacturer offers light-duty diesels in the United States today and captures about 0.2% of the 

market. Diesels have achieved significant reductions particulate and nitrogen oxide emissions in 

recent years and appear to be poised to meet Tier 2 emissions standards for at least bin 8 and 

very likely bin 5 (Duleep, 2004). 

Honda introduced the first hybrid vehicle into the U.S. market in 1999, the two-seater Honda 

Insight. Toyota followed with the Prius in 2000, a vehicle they had introduced into the Japanese 

market in 1997. Hybrid sales in the U.S. reached 38,000 units in 2002 (J.D. Power, 2003) and 

increased to 43,500 units in 2003 and from January to April 2004 23,000 hybrids were sold 

(Miller, 2004). Response to the redesigned model year 2004 Prius was especially strong: more 

than 12,000 purchase requests were made before the model was introduced in October 2003 

(Toyota, 2004). As a result, Toyota raised its production plan for the U.S. from 36,000 to 47,000 

units (Toyota, 2003). With demand for hybrids spurred on by higher fuel prices in 2004, 

manufacturers have been unable to keep pace with demand and waiting lists for hybrids have 

lengthened. 

The potential impact of hybrid technology on new light-duty vehicle fuel economy if all vehicles 

were converted to hybrids was assessed by Burke and Abeles (2004). They estimated that if all 

new light-duty vehicles were mild hybrids, fleet average fuel economy would increase to 38 

miles per gallon (mpg), at a cost increase of 7-9%. If all were full hybrids 42 mpg could be 

achieved for a price increase of 16-18%. Their study did not address the market acceptance of 

hybrid technology, however. 

In light of the fact that both technologies are present in the U.S. light-duty vehicle market today 

and are selling well, albeit with very limited product availability, it is no longer reasonable to 

assume that these technologies will play no role in determining future light-duty vehicle fuel 

economy. This study assesses the market potentials of hybrid and diesel technologies in the U.S. 

light-duty vehicle market, as well as their likely impacts on the fleet average fuel economy of 
2 

new light-duty vehicles. The impacts on fuel economy are based on estimated consumer demand 

for these technologies, with no subsidies or further increases in fuel economy standards. 

The estimated market potentials and fuel economy impacts assume no new policies to drive the 

market toward high fuel economy vehicles, such as higher CAFE standards or tax incentives for 

hybrid vehicles. Indeed, the existing federal tax incentives for hybrid vehicles are assumed to 

expire, as planned, before 2008. It is further assumed that manufacturers will neither lower nor 

raise the fuel economy of conventional gasoline vehicles as a result of the introduction of new 

diesel and hybrid products. No significant technological advances are assumed for any of the 

technologies except for those needed to control diesel NOX emissions to Tier 2, bin 5 levels. 

Economies of scale and learning-by-doing in the production of hybrid vehicles and emissions 

control systems for diesels are also assumed. Finally, the analysis is based on the mix of 

vehicles sold in the United States in model year 2002 and their attributes. No attempt has been 

made to project how consumers preferences or manufacturers offerings may change over the 

next 5-10 years, except for the introductions of new hybrid and diesel powertrains. 

The following section briefly reviews the status and prospects for the cost and performance of 

diesel and hybrid technologies. In Section 3, previous projections of hybrid and diesel market 

shares are reviewed. In Section 4, the data and methods used to assess future market potential 

are presented. Readers less interested in mathematical details may wish to skim this section. In 

Section 5, results are presented for eight scenarios to 2012 and beyond. 
3 

2. HYBRID AND DIESEL TECHNOLOGY STATUS AND PROSPECTS 

Although hybrid and diesel vehicles already have a limited presence in the North American lightduty vehicle market, they both face challenges to their future market success. Diesels must find 

a way to meet future Tier 2 emissions standards at the bin 5 level if they are to capture more than 

a niche market in the United States. Both hybrids and diesels face the challenge of consumer 

acceptance of their higher costs. In this section the status and outlook for these technologies are 

briefly reviewed, and our assumptions about future attributes are presented. The review draws 

heavily on in-depth reviews of the status of these technologies (Duleep, 2003; 2004). 

2.1 DIESELS 

Turbo-charged, direct-injection, high-pressure common rail, light-duty diesel engines are a well 

established technology that captured 44% of the European passenger car market in model year 

2003 (Schmidt’s, 2004). While higher motor fuel prices in Europe are clearly part of the 

explanation for the diesel’s success there, there is also no doubt that car buyers consider the 

modern diesel an acceptable alternative to the gasoline engine despite its higher price. Diesels 

have other advantages and disadvantages than simply fuel economy and cost that will affect their 

success in the North American market. Advantages such as greater driving range and higher 

torque may allow the diesel to capture a significant share of the North American market despite 

lower fuel costs. 

2.1.1 Diesel Advantages 

The diesel’s much higher compression ratio, lean burn operation and direct injection make it not 

only more energy efficient but give it more torque than a spark-ignition gasoline engine of the 

same displacement. In addition, diesel fuel contains about 10% more energy by volume than 

gasoline, a fact that further increases the diesel’s advantage in miles per gallon. Manufacturers 

are unlikely to try to downsize diesels to fully match the performance of a comparable gasoline 

engine vehicle. In our judgment, manufacturers will design diesel vehicles with not only higher 

fuel economy but also increased torque. Table 1 shows by calendar year the increases in fuel 

economy and torque we assume diesels will offer relative to a comparable gasoline vehicle. 

Tighter emissions standards account for the decrease in the diesel’s fuel economy benefit from 

2005 to 2008. Improved technology is assumed to restore most of the emissions penalty by 

2012. 

Table 1. Estimated Additional Torque and Fuel Economy 

of Light-Duty Diesel Vehicles 

 Torque MPG 

2005 25% 35% 

2008 25% 30% 

2012 25% 33% 

For a given make and model of vehicle, manufacturers are likely to offer the same size of fuel 

tank on gasoline and diesel versions. This implies that diesels will provide 30-35% greater 
4 

range, an added plus. In a 2002 survey by J.D. Power and Associates (McManus, 2003), 32% of 

respondents rated driving range as “extremely important” (8-10 on a scale of 1 to 10). Of those 

citing range as extremely important, 73% gave “have to refuel less frequently” as a key concern, 

while 44% cited “saves time.” This suggests that there is nuisance cost of refueling over and 

above the value of the time saved. Indeed, 27% said they simply “don’t like to refuel.” In the 

quantitative modeling presented below, only the value of time saved and not the avoided 

nuisance cost of refueling is considered, implying that we have most likely underestimated the 

value of greater range to consumers. 

2.1.2 Market Barriers 

Diesel fuel availability is a concern of many motorists. In a 2002 survey by J.D. Power and 

Associates (McManus, 2003), 46% cited limited diesel fuel availability as a concern for clean 

diesels. In a more recent survey (Caravan, 2004), only 35% of respondents said diesel fuel 

availability would be of no concern if they were considering buying a diesel vehicle (Figure 1). 

Another 20.8% considered it somewhat of a problem, but not a big deal, while another 8.2% 

viewed it as a problem, but not one that would prevent them from buying a diesel. On the other 

hand, only 27% said it was a serious enough problem that they either might not (7%) or would 

not (21%) buy a diesel because of it. In total, almost two thirds of respondents did not consider 

fuel availability a show stopper for diesels. 

Impression of Diesel Fuel Availability

Opinion Research Corporation, May 20,2004

34.7%

20.8%

8.2% 6.5%

20.6%

9.2%

0%

5%

10%

15%

20%

25%

30%

35%

40%

Not a problem,

available

everywhere

Somewhat of a

problem

Problem but

would still buy

Serious

problem might

not buy

Serious

problem would

not buy

Don't know

Relative Frequency

Figure 1. The Public’s Impression of Diesel Fuel Availability in May, 2004 

Owners of gasoline vehicles generally still believe that diesels are noisy, smelly and 

underpowered relative to gasoline vehicles. In the 2002 J.D. Power survey, 32% cited engine 

noise as a concern, and 27% cited exhaust odor. Thirty-one percent indicated lower performance 

was a concern. In large part, this is due to unfamiliarity with modern diesel technology. 

Compared with 1988 diesel technology, modern diesels have 100% more torque, 60% less noise, 

90% lower emissions and 30% less fuel consumption (Birch, 2003). Modern diesels are not 

noisier than gasoline engines, do not produce a diesel odor, and accelerate as well as comparable 
5 

gasoline vehicles. This suggests that many of the negative perceptions about diesels held by car 

buyers could be overcome with advertising and greater exposure to modern diesel vehicles. 

Two of the top three concerns emerging from the 2002 J.D. Power survey were the availability of 

service and repair locations, and the fact that the type of vehicle a car buyer wanted might not be 

available as a diesel. Both of these concerns would be addressed if more manufacturers offered 

diesels on more makes and models. Thus, a key question is whether diesels could significantly 

increase their market share even with the current level of fuel availability and limited product 

offerings, i.e., can the diesel solve its “chicken or egg” problem on its own? 

Surveys of owners of gasoline vehicles and diesel vehicles conducted by J.D. Power and 

Associates (McManus, 2004) reveal two key insights about the potential market for diesel 

vehicles. First, diesel vehicle owners have strongly positive perceptions of diesel vehicles, 

except for their higher price (Figure 2). Second, owners of gasoline vehicles have generally 

positive perceptions of diesel vehicles, but they are more negative than those of the owners of 

diesel vehicles (Figure 3). Diesel owners perceive their vehicles to be much more reliable, 

powerful, and fuel efficient than gasoline vehicles. They see them as cleaner and having about 

equal acceleration performance. More than half, however, consider the price of a diesel to be 

“worse.” More than half of gasoline vehicle owners believe diesels are more powerful and 

(surprisingly) cleaner; about three quarters consider them to be more fuel efficient. But they 

view diesels as about equally reliable, slower, and more expensive. Because the vast majority of 

gasoline owners are unfamiliar with diesels, it is likely that their perceptions would improve with 

greater exposure to diesels. These insights suggest that diesels are potentially a mass-market 

technology in the United States, provided that their price can be held at an acceptable level. 

Diesel Vehicle Owners: Clean Diesel v. Gasoline Vehicles

0% 20% 40% 60% 80% 100%

 Price of vehicle

 Emissions/pollution levels

 Fuel economy/efficiency

 Performance (acceleration)

 Power (torque)

 Reliability/dependability

Better Equal Worse

Figure 2. Diesel Vehicle Owners’ Views on Clean Diesel Vehicles 
6 

Gasoline Vehicle Owners: Clean Diesel v. Gasoline Vehicles

0% 20% 40% 60% 80% 100%

 Price of vehicle

 Emissions/pollution levels

 Fuel economy/efficiency

 Performance (acceleration)

 Power (torque)

 Reliability/dependability

Better Equal Worse

Figure 3. Gasoline Vehicle Owners’ Views on Clean Diesel Vehicles 

Undoubtedly the most significant downside of the diesel in the eyes of the consumer is its higher 

price. Diesels are more costly to manufacture chiefly because of their much higher pressure fuel 

injection systems and what we project will be far costlier emissions control systems. The 

estimates shown in Table 2 reflect the view that meeting Tier II bin 5 standards will add $550 to 

the retail price of a small diesel vehicles and $750 to the price of a larger one. The retail price 

equivalent (RPE) measures used throughout this report reflect a full mark-up over manufacturing 

costs, including all normal overheads and profits. The RPEs shown include the incremental costs 

of all necessary components, including all emissions control equipment. 

Table 2. Estimated Incremental Retail Price Equivalent for Diesel Vehicles 

 Small Vehicle 

(2.0-2.5L I4) 

Midsize Vehicle 

(3.0-3.5L V6) 

Large Vehicle 

(4.5-5.0L V6) 

2005 $1,750 $2,300 $2,500 

2008 $2,280 $2,925 $3,200 

2012 $2,300 $2,950 $3,250 

We assume that diesels will have no greater durability than spark-ignition gasoline engines. We 

also assume that diesels will continue to have limited fuel availability, which we put at 33% of 

refueling outlets through 2008 (Hadder, 2004). However, with a larger number of light-duty 

diesel vehicles on the road, it is reasonable to assume that fuel availability will increase. The 

sensitivity of future market shares to this assumption was tested, however. 
7 

2.2 HYBRIDS 

Hybrid vehicle designs can span a spectrum from 12-volt stop-start systems to over 300-volt 

systems with a substantial range of all-electric drive. In addition, for any given level of electric 

power capability, manufacturers may choose to emphasize fuel economy or performance. 

Discussions with manufacturers and review of their product plans indicate that the carmakers 

have divergent views about the desirability of the different design options and their potentials for 

market success (Duleep, 2003). On the one hand, this will lead to a broad array of designs tested 

in the marketplace. On the other hand, it will take more time to sort out the winners and losers. 

Details of our assessment can be found in EEA, Inc. (Duleep, 2004). 

It is assumed that all manufacturers face the same costs and can achieve the same technology 

performance. While it is clear that this is not the case today, it is our view that competition will 

drive the market in this direction in the future. The key assumptions about vehicle attributes 

used in this market analysis are given below. Assumed market introductions are listed in the 

appendix. 

Four types of hybrid systems are used in this assessment. They are listed below in order of 

increasing use of electric power, regenerative braking, energy storage capacity and benefit to fuel 

economy. 

1. Stop/Start (S/S): This hybrid system includes only the ability to shut off the engine when 

it would otherwise idle and to restart it instantly on demand. This provides no torque 

boost to aid acceleration, but offers a fuel economy advantage of 7.5% over the EPA test 

cycle. 

2. Integrated Starter Alternator with Damping (ISAD): This hybrid system will operate 

at 42 volts and will allow some power to be contributed by the electric drive system in 

addition to the stop/start capability. An increase in torque of 10% and 12.5% higher fuel 

economy are expected. 

3. Integrated Motor Assist (IMA): This 114 volt hybrid system is expected to be 

produced only by Honda through 2012. In comparison to the ISAD design it has a larger 

electric motor and greater battery power and energy storage and allows more electricity 

to be used for motive power. The system is expected to provide 15% higher torque and 

20% greater fuel economy on average. 

4. Full Hybrid (FH): These 300+ volt systems permit limited all-electric drive in addition 

to supplementing the power of the internal combustion engine. For cars, full hybrid 

systems should offer 20% more torque and 40% more miles per gallon; for light trucks 

increases of 15% in torque and 35% in fuel economy are expected. 

2.2.1 Hybrid Advantages 

Surveys show that consumers think of fuel economy (mentioned by 78%) and low pollution 

(54%) when they think of hybrid vehicles (McManus, 2003). Apparently because of early hybrid 

designs, they do not think of increased performance. Even owners of conventional gasoline 

vehicles see hybrids as exceptional when it comes to fuel economy and emissions (Figure 4), 

according to survey data developed by J.D. Power and Associates (McManus, 2004). But when 

it comes to acceleration performance and power, most gasoline vehicle owners believe hybrids 
8 

are inferior to gasoline vehicles. Gasoline vehicle owners also give hybrids low grades for 

reliability, and they believe they are much worse when it comes to price. 

Owners of hybrid vehicles have very different opinions about their vehicles (Figure 5). Not only 

do they consider them to be entirely superior when it comes to fuel economy and air pollution, 

but they perceive the hybrid’s performance and power to be just as good as that of a conventional 

gasoline vehicle and they give hybrids better marks for reliability. Even hybrid owners, 

however, see hybrids as more expensive. 

Gasoline Vehicle Owners: Hybrids v. Gasoline Vehicles

0% 20% 40% 60% 80% 100%

 Price of vehicle

 Emissions/pollution levels

 Fuel economy/efficiency

 Performance (acceleration)

 Power (torque)

 Reliability/dependability

Better Equal Worse

Figure 4. Gasoline Vehicle Owners’ Views on Hybrid-Electric Vehicles 

Hybrid Vehicle Owners: Hybrids v. Gasoline Vehicles

0% 20% 40% 60% 80% 100%

 Price of vehicle

 Emissions/pollution levels

 Fuel economy/efficiency

 Performance (acceleration)

 Power (torque)

 Reliability/dependability

Better Equal Worse

Figure 5. Hybrid-Electric Vehicle Owners’ Views on Hybrid-Electric Vehicles 
9 

Just as diesel owners had a more favorable impression of their vehicles than non-diesel owners, 

hybrid owners hold a better opinion of hybrids. On the one hand, there is almost certainly selfselection bias in these survey results. The more significant point, however, is that owners of 

these alternative power trains find them to be as good or better than gasoline vehicles in all 

respects except price. The fact that those who know these vehicles well are happy with them is 

important, since it implies that except for price there is no major market barrier to the success of 

either hybrids or diesels. Both technologies have mass-market potential. 

The combination of a conventional gasoline engine and an electric motor with high torque at low 

rpm permits exceptional launch and acceleration. Just as for diesels, it is likely that 

manufacturers will offer consumers both increased fuel economy and increased torque in future 

hybrid designs (Table 3). Stop/start systems will offer no increase in torque because they do not 

have the ability to use the starter/alternator for motive power. With other systems, torque will 

increase with the power of the electric motor. The full hybrid system is estimated to give only a 

15% torque increase and 35% fuel economy benefit when used on larger light trucks. 

 

Table 3. Estimated Additional Torque and 

Fuel Economy of Hybrid Vehicles

Hybrid 

System 

Change in 

Torque 

Change in 

MPG 

S/S 0% 7.5% 

ISAD 10% 12.5% 

IMA 15% 20% 

Full (cars and small trucks) 20% 40% 

Full (larger light trucks) 15% 35% 

Although a hybrid vehicle’s battery pack will take up additional space, we do not expect 

manufacturers to reduce the size of a hybrid’s fuel tank in comparison to a conventional gasoline 

vehicle. The Honda Civic hybrid’s fuel tank, for example, holds 13.2 gallons, exactly the same 

as conventional gasoline engine Civics. With fuel tanks of equivalent size, increased fuel 

economy will translate into increased range. 

Hybrids may have other advantages that we make no attempt to take into account. With smaller 

engines and all-electric drive at low speeds, hybrids are likely to be quieter than conventional 

gasoline vehicles. With two powerplants, hybrids could offer a kind of low-speed 4-wheel drive 

at little additional cost. Finally, with the ability to generate high-voltage electric power and 

considerable capability for storing electricity, hybrids can electrify many functions now 

performed mechanically or hydraulically, and can even provide electrical outlets for household 

appliances and tools. It seems likely that some combination of features will be found that will 

add value for customers. In the analyses presented below, however, we do not attempt to add 

extra value to hybrids to take account of this likelihood. 

Finally, hybrids are perceived to be environmentally friendly vehicles, and some car buyers are 

willing to pay something extra for a green vehicle. Fifty four percent of respondents to a J.D. 

Power and Associates survey who said they would consider buying a hybrid cited lower 

pollution as a reason (McManus, 2003). Nevertheless, we do not attempt to quantify the value of 

environmental friendliness in the quantitative analysis presented below. 
10 

2.2.2 Market Barriers 

Surveys of American consumers conducted by J.D. Power and Associates (McManus, 2003) 

indicate that insufficient power (34%), price (27%) and vehicle dependability (24%) are 

consumers’ top concerns about hybrid vehicles. Another 12% mentioned battery reliability as a 

concern. As a novel technology, it is understandable for consumers to be concerned about 

hybrids’ reliability. Very likely, only experience will fully overcome this barrier, though Toyota 

and Honda have made effective use of customer guarantees such as extended warrantees to allay 

the concerns of early purchasers. 

The incremental price of a hybrid system is undoubtedly the biggest barrier to its success. 

Hybrid costs have already begun to come down, and further reductions are expected. Toyota 

claims that the costs of batteries and motors were reduced by 30-35% from the first to the second 

generation Prius (Duleep, 2003). By 2012, we expect that costs will fall to $3,000-$4,000 for full 

hybrid designs, and from $600 to $640 for simple stop/start systems (Table 4). 

 

Table 4. Estimated Incremental Retail Price Equivalent 

of Hybrid Systems by Vehicle Type 

Hybrid 

System Small Cars 

Midsize & 

Large Cars Small Trucks Large Trucks 

Stop/Start $600 $640 $640 -- 

ISAD $1,250 $1,385 $1,450 $1,625 

IMA $1,620 $1,790 -- -- 

Full Hybrid $3,320 $3,920 $3,700 $4,100 

2.2.3 Manufacturers Near-Term Plans 

The six largest-selling manufacturers in the United States have announced planned introductions 

of sixteen additional hybrid vehicle configurations by 2008 (Table 5). This would bring the total 

number of hybrids in the market to nineteen. If these plans are realized hybrid options would be 

available not just as small to mid-size passenger cars, but in small and large SUVs and pick-ups, 

and in luxury as well as standard models. These announced introductions are the starting point 

for our “best guess” 2008 and 2012 scenarios described in Section 5, below and listed in detail in 

Appendix B. 
11 

Table 5. Planned Introductions of Hybrid-Electric Vehicles in the U.S. Market 

Model 

Nameplate 

(Division) 

Vehicle Name 

(Model) Manufacturer Market Segment Certainty 

Chevrolet Malibu Hybrid (BAS) Chevrolet Malibu General Motors Midsize-Entry Announced Chevrolet Silverado Hybrid (AHS II) Chevrolet Silverado General Motors Pickup-Fullsize Announced Chevrolet Silverado Hybrid (FAS) Chevrolet Silverado General Motors Pickup-Fullsize Announced 

Chevrolet Tahoe Hybrid (AHS II) Chevrolet Tahoe General Motors SUV-Fullsize Announced Dodge Ram Contractor Special Dodge Ram DaimlerChrysler Pickup-Fullsize Announced 

Ford Escape Hybrid Ford Escape Ford SUV-Entry Announced Ford Midsize Car Hybrid Ford Futura Ford Midsize-Premium Announced GMC Sierra Hybrid (AHS II) GMC Sierra General Motors Pickup-Fullsize Announced GMC Sierra Hybrid (FAS) GMC Sierra General Motors Pickup-Fullsize Announced GMC Yukon Hybrid (AHS II) GMC Yukon General Motors SUV-Fullsize Announced Honda Accord Hybrid Honda Accord Honda Midsize-Premium Announced Honda Civic Hybrid Honda Civic Honda Compact-Premium In Market Honda Insight Honda Insight Honda Compact-Premium In Market Lexus RX400h Lexus RX 400h Toyota SUV-Luxury Announced Mercury Mariner Hybrid Mercury Mariner Ford SUV-Entry Announced Nissan Altima Hybrid Nissan Altima Nissan Midsize-Premium Announced Saturn VUE Hybrid (BAS) Saturn VUE General Motors SUV-Entry Announced Toyota Highlander Hybrid Toyota Highlander Toyota SUV-Midsize Announced Toyota Prius Toyota Prius Toyota Midsize-Premium In Market 

Source: J.D. Power and Associates, Hybrid-Electric Vehicle Outlook, First Quarter, 2004, Troy, Michigan.

13 

3. RECENT MARKET ASSESSMENTS 

A recent survey by Opinion Research Corporation (Caravan, 2004) indicates substantial 

consumer interest in both diesel and hybrid technologies. In their 2004 survey, 8.6% of 

respondents indicated that they would definitely buy or were very likely to buy a diesel as their 

next vehicle (Figure 6). The respondents were evenly divided with 4.3% in each category. 

Almost seven percent indicated they would definitely buy a hybrid vehicle, with 8.3% indicating 

a hybrid purchase was very likely. The sum of the two most likely categories (“definitely” and 

“very likely”) suggests the following maximum near-term market potentials: 8.6% for diesels 

and 15.2% for hybrids. 

Intent to Purchase Diesel or Hybrid-Electric Vehicle

(Opinion Research Corportation, May 20, 2004)

4.3% 4.3%

13.7%

36.3%

38.5%

3.0%

6.9% 8.3%

27.4%

30.9%

20.4%

6.1%

0%

10%

20%

30%

40%

Definitley will

buy

Very likely to

buy

Likely to buy Not likely to

buy

Definitely

won't buy

Don't know

Relative Frequency

Diesel Hybrid electric

Figure 6. Intent to Purchase Diesel or Hybrid-Electric Vehicle (ORC, 2004) 

In 2004, J.D. Power and Associates (McManus, 2004) presented a new, less optimistic forecast 

of hybrid market share to 2013. From 0.6% of the market in 2004, hybrids were projected to 

grow to 2.5% of the market in 2008 and 3.2% in 2013, with a lower and upper bound of 2.1% to 

4.1%, respectively (Figure 7). 

Robert Bosch GmbH (Qualters, 2004) carried out a study of the diesel’s potential in the North 

American light-duty vehicle market. Key premises of the study were that emissions control 

strategies to achieve bin 8 would be available by 2007, bin 5 solutions by 2009, and that fuel 

availability would not hinder development of the diesel market. In addition, they assumed that 

total market volume would be approximately 17.5 million units, and that manufacturers’ market 

shares would remain relatively static. The Bosch assessment did not consider competition from 

alternative power trains, such as the hybrid. 

On the positive side, the Bosch study noted the enormous success of diesel engines in the larger 

(GVW class IIb) pick-up truck market, where they currently hold a 75% market share. In 2003, 

550,000 diesel pick-ups were sold in the North American market. Bosch’s opinion is that some 
14 

of the appeal of the diesel in this market segment must surely carry over, albeit to a lesser degree, 

into the lighter truck markets. They therefore conclude that the most likely path for diesel 

market penetration is to migrate downward from class IIb light trucks to large SUVs, lighter-duty 

pick-up trucks, standard and smaller sized SUVs, crossover vehicles and minivans and, finally, 

passenger cars. If such a strategy is pursued, they foresee the North American diesel market 

share expanding from about 5% today to nearly 15% by 2012. The Bosch study includes class 

IIb light trucks (>8,500 lbs. GVW) which are not included in this study. Excluding class IIb 

trucks, the Bosch projection for 2012 is 10% of the light-duty market as defined here (Figure 7). 

Approximately half of the new sales are expected to come in the light-duty pick-up market 

segment, and only a very small fraction would be attributable to passenger car diesel sales. 

Projections of Light-Duty (<8,500 lbs. GVW) 

Hybrid and Diesel Market Shares

JD Power 

2004/Hybrid

JD Power 

2004/Hybrid

Bosch/Diesel

Bosch/Diesel

JD Power/Diesel

Morgan 

Stanley/Hybrid

Morgan 

Stanley/Hybrid

JDP High

JDP Low

JD Power 

2004/Hybrid

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

2000 2005 2010 2015 2020

Figure 7. Projections of Light-Duty Hybrid and Diesel Market Shares 

(Passenger cars and class IIa light trucks, only) 

3.1 DOE PROJECTIONS 

Projections of future diesel vehicles sales have been made by the U.S. Department of Energy’s 

Office of Energy Efficiency and Renewable Energy (EERE) and by the Energy Information 

Administration (EIA, 2004; Patterson, 2004). The EIA’s projection foresees diesel sales 

reaching 585,000 units by 2005, increasing to 716,000 in 2010 and reaching 765,000 units in 

2015. Both the EIA’s and EERE’s projections nominally include class IIb light trucks (>8,500 

lbs. GVW). However, only the EIA forecast appears to have been calibrated to the current level 

of class IIb diesel sales. Current class IIb diesel sales amount to approximately 5% of total class 

1 and 2 light truck sales. Over 95% of the light-duty diesels are projected to be light trucks. The 
15 

EERE projection foresees only 179,000 light-duty diesels by 2010, followed by a rapid 

expansion to 2.1 million diesels in 2015 (Figure 8). Over 40% of the diesels in the EERE 2015 

forecast are passenger cars. 

Projected Diesel Market Shares in the U.S.: 

EERE and EIA (2004 Annual Energy Outlook)

0%

5%

10%

15%

20%

25%

30%

2000 2005 2010 2015 2020 2025

Percent of Light Vehicle Sales

EERE EIA

Figure 8. Projected Diesel Market Shares in the United States 

These studies reflect a considerable range of uncertainty but also substantial competitive market 

potential for diesels and hybrids over the next decade. In the sections that follow, we describe a 

methodology and data for estimating future market success, based on explicit assumptions about 

both the attributes of hybrid and diesel technologies and the values consumers attach to them. 

17 

4. METHODOLOGY AND DATA 

Evaluating the future market potentials of hybrid and diesel technologies requires: (1) estimating 

the extent to which manufacturers will offer products with diesel or hybrid options, and 

(2) predicting consumers’ response to those offerings. The key piece is consumer acceptance, 

since it is reasonable to assume that if enough consumers are willing to pay for diesels and 

hybrids, manufacturers will, eventually, produce them in a variety of shapes and sizes. In the 

near term, to 2008 and even to 2012, the number of diesel or hybrid offerings will be limited by 

several factors: 

(1) risk: uncertainty about the market’s response to these technologies will lead 

manufacturers to proceed with caution; 

(2) response time: redesigning vehicles to accommodate hybrid or diesel power trains 

takes time because engineering expertise is in limited supply and because accelerating 

the normal rate of retooling increases costs; and 

(3) technology status: the technological readiness of both technologies is evolving; for 

the diesel, there remains a question of how successfully it can reduce pollutant 

emissions; for the hybrid the question is how quickly and how far it can be moved 

down the learning curve and its costs reduced. 

Indeed, it is likely that almost all hybrid or diesel vehicles that will be available in 2008 have 

already been announced by manufacturers. 

4.1 SCENARIOS OF DIESEL AND HYBRID INTRODUCTIONS 

Our method for estimating the future market successes of diesels and hybrids consists of two 

steps. First, we specify a detailed scenario of diesel and hybrid product introductions. Second, 

we use a quantitative model of vehicle choice to predict the share of the new vehicle market 

those new products will capture. Scenarios are defined by, (1) time period (2008, 2012 and 

>2012), (2) technologies introduced (diesel, hybrid, type of hybrid), and (3) the makes-modelsengines-transmissions to which the technologies are applied. 

For 2008, our scenarios are based primarily on manufacturers’ product announcements, with a 

few additional models added based on our judgment. For 2012 we have augmented the 2008 

introductions with additional, likely product introductions, based on our judgment. The makes 

and models for which diesel and hybrid powertrains are assumed to be available in 2008 and 

2012 are listed in tables A.1 and A.2 in the appendix. The >2012 scenarios are intended to 

represent market tendencies driven by customer demand and largely unconstrained by make and 

model availability. 

If not every single vehicle configuration offers a diesel and a hybrid option, which configurations 

will offer them? This question is critically important to the calibration of the consumer choice 

model. Unfortunately, there is no obviously correct answer to this question, so we test two 

alternatives in the 2008 and 2012 analyses: (1) the announced or most likely (based on our 

judgment) configuration of each nameplate, and (2) an “average” configuration for each 

nameplate. A precise mathematical definition of an average configuration is provided in 
18 

Appendix A. We use the average configuration method as a lower bound estimate since it is 

reasonable to assume that manufacturers would tend to offer hybrids or diesels on the 

configurations that would sell best. 

In all, eight scenarios were analyzed: 

1. >2012 all configurations potentially have diesel available 

2. >2012 all configurations potentially have full hybrid available 

3. >2012 all configurations potentially have both full hybrid and diesel 

4. >2012 all configurations potentially have both ISAD hybrid and diesel 

5. 2008 best guess, best-judgment make/model/configuration 

6. 2008 product plans, average make/model/configuration 

7. 2012 best guess, best judgment make/model/configuration 

8. 2012 augmented product plan, average make/model/configuration 

Diesel and hybrid vehicles will have to sell well enough for manufacturers to achieve scale 

economies or the product lines will be canceled. Because drivetrains can be used on more than 

one nameplate, determining exactly how many diesel engines or hybrid drivetrains of a particular 

design a manufacturer may be selling is difficult and beyond the scope of this study. Instead we 

eliminate low-selling models with a simple rule of thumb: if the sum of diesel or hybrid sales for 

a given nameplate (make and model name) is less than a specified threshold, all configurations of 

that nameplate are deleted and sales shares are recomputed. The default assumption for the 2008 

scenarios is 5,000 units, for 2012 10,000 units must be sold and for >2012 the limit is raised to 

25,000 units. In addition, in the >2012 scenarios every configuration must sell more than 2,000 

units or it is deleted. 

Finally, a sensitivity analysis was carried out on scenario 3 (>2012 Full Hybrid & Diesel) to 

generate a distribution of outcomes and identify the most important factors determining the 

market success of diesels and hybrids. 

4.2 CONSUMER CHOICE MODEL 

The model of consumer choice must be able to predict the effects of introducing new products 

into the market as well as predicting the impacts of changes in vehicle attributes such as price, 

fuel economy, range and power. In addition, it must be possible to calibrate the model to the 

base year sales of the nearly 1,000 makes, models and configurations in the National Highway 

Traffic Safety Administration fuel economy database. Furthermore, it is desirable to recognize 

that there are different segments of the light-duty vehicle market and that consumer preferences 

and sensitivity to price may vary across these segments, affecting their propensity to accept 

diesel or hybrid vehicles. The Nested Multi-Nomial Logit (NMNL) random utility model can be 

used to carry out all of these tasks. 

Random utility models such as the NMNL assume that consumers’ vehicle choice decisions can 

be approximately represented as a problem of picking the vehicle which achieves the highest 

score on a ranking function. The simplest form of ranking, or utility function, is a weighted sum 

of relevant vehicle attributes such as price, performance, reliability, functionality, and so on. 

Recognizing that not every consumer attaches the same value to each attribute, and that there 
19 

may be unmeasured or unmeasurable yet relevant attributes, a random component that varies 

across individual consumers is added to the ranking function. Let uij be the ranking score for the 

i

th vehicle for the jth individual, let wl be the weight of the lth attribute, xil , and let εij be the jth

individual’s random component for the ith make and model. By convention, the weight for 

vehicle price, wP = 1, so that the units of wlxil are dollars. 

( )

1

∑=

= + +

K

l

ij i l il ij u b A w x ε

Equation 1 

In equation 1, Ai is a constant term reflecting the value, in dollars, of attributes of vehicle i not 

included in the set of measured attributes, xil. The parameter b is a critical parameter in that it 

determines the sensitivity of consumers’ choices to changes in the dollar values of alternatives. 

Because wp=1, the coefficient of price (or price slope) is b. 

Assuming that the random terms follow the type I extreme value distribution (a somewhat 

skewed bell shaped distribution similar to the normal distribution), then the probability that the 

i

th make and model will be chosen, given that the choice will be made from the kth vehicle class, 

is given by the multinomial logit (MNL) function. 

∑=

= L

l

bu

bu

i k

l

i

e

e

p

1

|

Equation 2 

Given a large enough population of car buyers, pi will also be the market share of the ith make 

and model. Sales for that carline can then be estimated by multiplying total light-duty vehicle 

sales by the predicted market share, Si = pi S. In equation 2, b is the coefficient of vehicle price 

and is also the inverse of the variance of the random utility term, ε. 

The NMNL model assumes that choices within a class of vehicles, e.g. choices among makes 

and models of small SUVs, follow the logit model of equation 2. Choices among vehicle classes 

follow a similar logit model, in which the utility function for a class is a probability-weighted 

average of the utility scores of the vehicles within the class. The expected utility of class k, Uk , 

is given by the following log sum. 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = ∑=

k

ik

n

i

u

k e

b

U

1

ln 1

Equation 3 

The probability that a consumer will choose a vehicle from class k is then given by the following 

logit function. 

∑=

+

+

= n

K

A BU

A BU

k

K K

k k

e

e

p

1
20 

Equation 4 

Here K is used to index summation over all vehicle classes and n is the number of vehicle 

classes. AK is a vehicle class-specific constant term analogous to the vehicle constant term Ai in 

equation 1. Likewise, B is a slope parameter that determines the sensitivity of choices among 

vehicle classes to changes in their expected value. The probability that vehicle i will be chosen 

from class k, which is equivalent to its expected market share, is given by the product of 

equations 2 and 4, the class and conditional vehicle choice probabilities pik = pi|k pk . 

4.3 MARKET SEGMENTATION AND CHOICE MODEL STRUCTURE 

The market structure assumed for this analysis is shown in Figure 9. Light-duty vehicles are 

divided into five classes (k = 1, 5): (1) standard passenger vehicles, (2) luxury vehicles, 

(3) sportscars, (4) pick-up trucks, and (5) standard vans. Standard passenger vehicles are further 

divided into passenger cars and passenger trucks. Passenger cars contain small, compact and 

midsize-large cars; passenger trucks comprise minivans, as well as small and large SUVs. 

Luxury vehicles are further divided into cars and trucks, sportscars are divided into luxury and 

standard segments, and pick-ups are split into small and large size classes (Table 6). 

Light-Duty Vehicles Sales -1 

-2 

 Sports Cars Luxury Vehicles 

-2 -3 

 Lux Sport Sportscar Lux Car Lux Trk 

 

 Passenger Vehicles 

 -3 

Passenger Cars Passenger Trucks Pick- ups 

-4 -4 -3 

 Small Comp Mid-Lg Small Van Small SUV Large SUV SM P-U Lg P-U Van 

 

 Make/Model/Configuration Choices -7 to -9

Figure 9. Nested Multinomial Logit Model Structure and 

Approximate Price Elasticities (shown in bold numbers) 

A useful feature of the NMNL model is the ability to group more similar vehicle types into 

“nests” within which demand will be more sensitive to price (elastic) than choices among the 

nests. The implication of Figure 9, for example, is that the choice among a small, compact and 

midsize-large car will be more price sensitive than the choice between a car and all sizes of 

passenger trucks. Choices among (1) standard van, (2) pick-up, (3) luxury vehicle, (4) passenger 

vehicle, and (5) 2-seater vehicle will be even less price sensitive, because these vehicle types 

serve very different functions. Within the lowest level nests, choice among makes and models of 

large SUVs, for example, will be most sensitive to small price changes. A price elasticity of -7, 

for example, implies that a 2% increase in price would produce a 14% reduction in market share. 
21 

Table 6 (Part 1). Definitions of Vehicle Classes 

Vehicle Class CEC Class

Number of 

Configurations Price 

 1. Minicompact & Subcompact 1,2 102 <$35,000 

 2. Compact 3 125 <$35,000 

 3. Midsize & Large 94 <$35,000 

 4. Small Van 9 36 <$35,000 

 5. Small SUV 11,13 162 <$35,000 

 6. Large SUV 12 13 <$35,000 

 7. Small Pick-up 7 64 <$35,000 

 8. Large Pick-up 8 56 <$35,000 

 9. Luxury Sedan 1-5 117 >$35,000 

10. Luxury Truck 7-16 43 >$35,000 

11. Standard Sportscar 6 37 <$35,000 

12. Luxury Sportscar 6 49 >$35,000 

13. Standard Van 10 32 <$35,000 

Table 6 (Part 2). California Energy Commission (CEC) Vehicle Classification System 

Passenger Cars 

CEC Classes 

 Passenger Volume 

(Cubic Feet) 

 1. Mini Under 82 

 2. Sub Compact 82—89 

 3. Compact 90—95 

 4. Mid Size 96—105 

 5. Large 106+ 

 6. Sports Under 89 

Trucks 

CEC Class 

Passenger & 

Cargo Volume 

(cu feet) 

Gross Vehicle 

Weight Rating 

(lbs) 

 7. Compact Pickup <4,500 

 8. Standard Pickup 4,500—8,500 

 9. Compact Van <=170 

10. Standard Van >170 

11. Compact Utility 120—170 

12. Standard Utility >170 

13. Mini Utility <120 

16. Truck Chassis Only 
22 

4.4 CHOICE MODEL CALIBRATION 

Calibration of the NMNL model to base year 2002 sales and vehicle attributes requires three 

steps. First, price slopes must be estimated for every nest and for every level of choice shown in 

Figure 1. The price slopes are critical parameters and are used in estimating coefficients for all 

the other attributes. Second, values per unit must be estimated for all variables included in the 

NMNL model. Attribute values are converted to NMNL model coefficients by multiplying 

values per unit by the purchase price coefficient. Third, intercept terms must be estimated to 

insure that the NMNL model exactly predicts the base year market shares of, (1) every make, 

model and configuration, and (2) every vehicle market segment shown in Figure 9. 

Price slopes not only determine the sensitivity of demand to purchase price but to all other 

variables included in the model. In the NMNL model, the price coefficients define the 

importance of unobserved attributes, factors left out of the formal model. If choice is highly 

price-sensitive, it implies that consumers perceive vehicles to be very similar except for the 

factors explicitly included in the model. If choice is relatively insensitive to price, it implies that 

most of the important factors on which consumers base their choices are not explicitly 

represented in the model. If choice is insensitive to price, the choice model will tend to give all 

vehicles an equal share of the market. In considering how sensitive choice may be to price, it is 

important to keep in mind that choices at the lowest level nests in Figure 1 are among similar 

vehicles, including diesel, hybrid or conventional gasoline versions of the same make and model. 

Thus, it is reasonable to assume a high degree of similarity with respect to attributes excluded 

from the model and, therefore, relatively high sensitivity to price. At the highest level, the 

choice among a sportscar, standard passenger vehicle, luxury vehicle, pick-up truck and standard 

van will be based primarily on factors not explicitly included in our NMNL model. Choices at 

this level should be much less sensitive to price. Indeed, the theory of NMNL models requires 

that price sensitivity uniformly decrease as one moves from the lowest level choices upward. 

This theoretical requirement is very useful in calibrating the model’s price slopes. 

Given the price and attribute coefficients, intercepts must be estimated for every make, model 

and configuration. This allows the expected utilities of classes to be computed. Given the class 

expected utilities and class price slopes, intercept terms can be calculated for each market 

segment. This calibration insures that the NMNL model exactly predicts each make, model and 

configuration share, and all the class shares for the base year. 

4.5 PRICE SLOPES 

Price slopes are computed using their relationship to price elasticity, vehicle price, and market 

share in the NMNL model. Let βk be the price elasticity for choices in vehicle class k, Pk the 

average price of a vehicle in the class, and let pk be the average market share for vehicle 

configurations in class k. Then the price slope for class k is given by equation 5. 

(1 ) k k

k

k P p

b − = β

Equation 5 
23 

The same relationship can be used to calculate price elasticities for choices among vehicle 

classes. 

McManus (2004) presents useful survey data on the potential sensitivity of diesel and hybrid 

market shares to their incremental prices. For each of the two alternative powerplants, a J.D. 

Power and Associates survey asked respondents how likely they would be to buy that powerplant 

if it cost a certain amount more than a comparable gasoline engine vehicle. Demand, in terms of 

market share, was set equal to the sum of those responding they would definitely or probably 

want to buy the powertrain in question. For the diesel, the cost increments were $1,500, $2,500, 

and $3,500 (2003 dollars). For the hybrid the cost increments were $3,000, $4,000 and $5,000. 

Table 7 shows the market shares and cost increments, and implied price elasticities based on the 

midpoint formula for computing arc elasticities. In both cases, the price elasticities for the initial 

price increment are just over -8, indicating highly elastic demand. In both cases price elasticities 

decrease with increasing price. 

Table 7. Estimated Price Elasticities for Diesel and Hybrid Market Shares 

Based on a Survey by J.D. Power and Associates 

Price Increase Market Share 

Relative Change 

in Price 

(Base = $25,026) 

Relative 

Change in 

Share 

Arc Elasticity 

Using Midpoint 

Formula 

Diesel 

$0 .75 - - - 

$1,500 .44 .0599 -0.514 -8.6 

$2,500 .34 .0400 -0.261 -6.5 

$3,500 .28 .0400 -0.182 -4.6 

Hybrid 

$0 .59 - - - 

$3,000 .21 .1199 -0.971 -8.1 

$4,000 .19 .0400 -0.057 -1.4 

$5,000 .18 .0400 -0.061 -1.5 

The inferences shown in Table 7 must be interpreted with caution because they are based on 

what consumers say they would do rather than what they actually did, and because of the 

crudeness of the estimation method. Nonetheless, the numbers are generally consistent with 

other price elasticity estimates from the economic literature. Greene (1986) analyzed the choice 

between gasoline and diesel engines for the same make and model in the U.S. market between 

1979 and 1983 and found a price elasticity of approximately -10 (Greene, 1994). For choices 

between makes and models, Irvine (1993) obtained price elasticities ranging from -4.6 to -17.0, 

with a mean of -10.4. Berry et al. (1995) analyzed choices among 2,217 carlines from 1971 to 

1990 and found that elasticities for 1990 model year cars ranged from -6.5 to -3.1, with price 

sensitivity generally decreasing with increasing price. In a similarly comprehensive analysis, 

Bordley (1994) found an average own price elasticity of -5 for choices among makes and 

models. Bordley also found a price elasticity of -2 for choices among broad market segments 

(e.g., subcompact, sports car, etc.). Finally, there is a general consensus that the price elasticity 

of demand for light-duty vehicles overall is close to -1 (Kleit, 1990; McCarthy, 1996; Bordley, 

1994). 
24 

Price slope coefficients are calculated from assumed price elasticities, base year vehicle prices 

and market shares, as shown in equation 5. The default price elasticities assumed at each level of 

the choice structure are shown in Figure 9. The resulting price slopes and the data used to 

compute them are provided in Table 8. 

Table 8. Price Slopes, Elasticities, Prices and Market Shares for Market Segments 

 2002 Market 

Make/Model 

 

Average Price Average Price 

 Share (%) Count Share Elasticity Price Slope 

All Vehicle Classes 20.00% -2 $25,026 -0.000100 

Passenger Vehicle 72.59% 50.00% -3 $22,769 -0.000207 

Passenger Car 43.35% 33.33% -4 $20,349 -0.000295 

Small Car 7.61% 102 0.98% -7 $17,226 -0.000410 

Midsize Car 14.53% 125 0.80% -7 $19,234 -0.000367 

Large Car 21.22% 94 1.06% -7 $22,233 -0.000318 

Passenger Truck 29.24% 33.33% -4 $26,357 -0.000228 

Minivan 7.01% 36 2.78% -7 $25,651 -0.000281 

Small SUV 20.40% 162 0.62% -7 $26,208 -0.000269 

Large SUV 1.83% 13 7.69% -7 $30,718 -0.000247 

Pick-up 15.31% 50.00% -3 $22,451 -0.000267 

Small Pick-up 5.19% 64 1.56% -7 $19,099 -0.000372 

Large Pick-up 10.12% 56 1.79% -9 $24,170 -0.000379 

Luxury 8.53% 50.00% -3 $47,429 -0.000127 

Luxury Sedan 3.95% 117 0.85% -7 $47,256 -0.000149 

Luxury Truck 4.59% 43 2.33% -7 $47,578 -0.000151 

Sportscar 2.88% 50.00% -2 $29,534 -0.000135 

Standard Sportscar 2.30% 37 2.70% -7 $23,393 -0.000308 

Luxury Sportscar 0.57% 49 2.04% -9 $54,159 -0.000170 

Van 

Standard Van 0.69% 32 3.13% -7 $23,726 -0.000305 

4.5.1 Estimating the Value of Attributes 

Attribute coefficients are calculated from the estimated value in dollars of one unit of an 

attribute. The slope coefficient for an attribute is its value per unit times the appropriate price 

slope. To the greatest extent possible, attribute values are derived from assumptions or taken 

from the existing economic literature. For example, it is possible to calculate the value of a 

change in fuel economy by calculating the present value of fuel savings. While this method 

requires making a number of arguable assumptions, it has the advantage of transparency. The 

behavior of the model is directly dependent on its coefficients which can be directly traced to 

specific assumptions about consumer behavior. Another virtue of this approach is that it makes 

it possible to test the sensitivity of model predictions to key assumptions such as the price of 

fuel, consumer discount rates, or the value of time spent refueling. 
25 

4.5.2 Fuel Economy 

The value of fuel economy is derived from assumptions about vehicle use, the consumer’s 

payback period and discount rate. EPA test fuel economy numbers are discounted to more 

accurately reflect real-world driving experience. For conventional gasoline vehicles, EPA 

composite MPG numbers are multiplied by 0.85. Although there is not yet definitive evidence, it 

appears that hybrid vehicle MPG should be discounted more severely (0.80) and diesel powered 

vehicles less (0.925). Since fuel costs are in units of dollars per mile, the attribute weight for 

fuel cost must be in units of present value miles, in other words miles driven over the consumers’ 

payback period, discounted to present value. The assumptions for these calculations are shown 

in Table 9. The annual miles by vehicle class for the first year of ownership are shown in the 

first column. Usage decreases with age and the rates of decline are given in the second column. 

It is assumed that consumers demand a simple 3-year payback, that is, they count the first three 

years of undiscounted fuel savings. 

Fuel economy determines the fuel cost per mile of travel, which equals the price of fuel, Pf , 

divided by fuel economy in miles per gallon, E. Thus, the value weight translates fuel cost per 

mile of travel into present value dollars (equivalent to dollars spent on purchase price). In effect, 

it answers the question, “How much is a change of $1 per mile in fuel costs worth at the time of 

purchase?” This depends on how many miles the vehicle will be driven over time, M(t) = Moe

-δt

, the buyer’s payback period, L, and discount rate, r.1

 The present value of fuel cost is given by 

the following equation, in which wf is the fuel cost per mile weight. 

∫ ∫

=

− −

=

− − = = =

L

t

f

t rt f

o

L

t

t rt f

o

f

f w

E

P

M e e dt

E

P

M e e dt

E

P

V

0 0

δ δ

 Equation 6 

Equation 6 reveals that the fuel cost per mile weight is in units of discounted or present value 

miles. Multiplying wf by the appropriate class-specific price slope yields the coefficient for fuel 

cost per mile. The reference assumptions are that consumers value fuel costs using a simple 3-

year payback period, i.e., L=3, r=0 (Table 9). This same assumption was one of two used in the 

National Academy of Sciences (NRC, 2002) assessment of U.S. fuel economy regulations, and is 

also roughly consistent with a recent nationwide random sample survey (Caravan, 2004) which 

indicated a 2.5 year payback period with an unspecified discount rate. Estimates based on a 

recent survey of California residents implied payback periods ranging from 2 to 10 years (Adler, 

et al., 2004). 

4.5.3 Range 

The value of increased range is the present value of time that need not be spent refueling. As 

noted above, it is likely that there is also a nuisance value associated with refueling events. 

However, in the absence of specific evidence about the nuisance cost of refueling and because 

we would prefer to undervalue rather than overvalue the attributes of diesel and hybrid vehicles 

in our analysis, the value of range is based solely on the value of time spent refueling without 

any additional nuisance value. 

 

1

 It may be more accurate to view the discount rate as a required rate of return on an investment in fuel economy. 
26 

Table 9. Coefficients of the NMNL Vehicle Choice Model 

FUEL ECONOMY SLOPES RANGE SLOPES FUEL AVAILAB

Annual 

Miles 

Rate of Use 

Decrease/yr 

Payback 

Horizon 

(yrs) 

Discount 

Rate 

Present 

Value 

Miles 

Fuel 

cost/mi 

Slopes 

Tank 

Size 

(gals) 

Minutes 

Per 

Refuel 

Value of Time 

(2002 $/hr) Slopes C Scale 

Exp

Small Car 15,502 4.6% 3 0.0% 42,534 -17.456 13.6 6.6 $17.91 -34.5427 -0.5 -0.3Midsize Car 15,502 4.6% 3 0.0% 42,534 -15.604 14.5 6.7 $20.00 -35.0513 -0.5 -0.3

Large Car 15,502 4.6% 3 0.0% 42,534 -13.536 17.4 7.1 $23.12 -36.9490 -0.5 -0.3

Minivan 17,239 4.3% 3 0.0% 47,569 -13.352 20.7 7.5 $26.67 -44.3941 -0.5 -0.3

Small SUV 17,955 5.7% 3 0.0% 48,262 -12.970 18.9 7.3 $27.25 -42.7935 -0.5 -0.3

Large SUV 17,955 5.7% 3 0.0% 48,262 -11.914 26.0 8.1 $31.94 -51.5016 -0.5 -0.3

Small Pick-up 19,151 5.8% 3 0.0% 51,381 -19.131 19.1 7.3 $19.86 -46.1849 -0.5 -0.3

Large Pick-up 19,151 5.8% 3 0.0% 51,381 -19.480 25.8 8.1 $25.13 -66.1052 -0.5 -0.3

Luxury Sedan 15,502 4.6% 3 0.0% 42,534 -6.355 19.2 7.3 $49.14 -60.6890 -0.5 -0.3

Luxury Truck 15,502 4.6% 3 0.0% 42,534 -6.407 26.1 8.1 $49.47 -68.5169 -0.5 -0.3

Standard Sportscar 15,502 4.6% 3 0.0% 42,534 -13.081 15.5 6.9 $24.32 -36.3521 -0.5 -0.3Luxury Sportscar 15,502 4.6% 3 0.0% 42,534 -7.216 17.5 7.1 $56.31 -76.7129 -0.5 -0.3

Standard Van 19,151 5.8% 3 0.0% 51,381 -15.648 32.5 8.9 $24.67 -57.2262 -0.5 -0.3
27 

Total lifetime refueling cost is equal to the miles driven per year divided by the effective vehicle 

range (which gives the total number of refueling events per year) multiplied by the time required 

to refuel (in hours), multiplied by the value of time (in $/hr), integrated over the consumers’ 

ownership horizon and discounted to present value. 

∫ ∫

=

− −

=

− − = = =

L

t

t rt R

o

L

t

t rt

R o R

w vHM e e dt

R

M e e dt

R

vH V

0 0

δ 1 δ

Equation 7 

Equation 7 reveals that range should appear as the inverse of range in the NMNL model. 

The reference assumptions are a three year time horizon, zero discount rate, $20 per hour, an 

average refueling time of 6 minutes, and an effective storage volume of 80% of the total fuel 

tank volume. It is not clear that consumers use the same method to value future time spent 

refueling as they use to value future fuel savings. However, in the absence of specific evidence, 

we choose to use consistent methods and assumptions. 

4.5.4 Torque/acceleration/power 

The value of acceleration or power-to-weight is very subjective and a wide range of estimates 

can be found in the literature. Greene (2001) used a value of $12.50 per horsepower (in 1990$, 

or about $16 in 2002 $), based on studies by Donndenlinger and Cooke (1997) and Greene and 

Liu (1988). This is equivalent to $375 (2002 $) per second reduction in 0-60 mph acceleration 

time. A recent study using stated preference survey data from California (Adler et al., 2004) 

found values over $1,000 per second. 

Although there is no exact relationship between torque and horsepower, for most vehicles the 

ratio is typically about 3/2. This would make the value per Nm about $10 in 2002. A value of 

$7 per 1 Nm of torque is assumed for all vehicles except luxury cars and trucks, for which a 

value of $15/Nm is used. For example, the willingness to pay for an increase in torque from 300 

to 400 Nm would be $700 to $1,500, roughly what consumers would pay for a 6- instead of a 4-, 

or an 8- instead of a 6-cylinder engine. 

The hybrid’s increase in torque is likely to be more pronounced when accelerating from a stop or 

when rpm is otherwise low, while the diesel’s torque will be most noticeable at mid-range engine 

speed. In the absence of information about the relative value of these two kinds of power, no 

attempt has been made here to resolve the issue of whether “off the line” acceleration is more 

valuable than passing acceleration (Santini, 2004). Both are assigned the same value. 

4.5.5 Fuel Availability 

The cost of limited fuel availability is assumed to be a power function of the fraction, x , of 

refueling outlets that offer the fuel in question. 

a VA = Cx

Equation 8 
28 

Greene (1998) found that either a power function or an exponential function fit survey data on 

the perceived cost of low fuel availability. Nicholas et al. (2004) used a power function to fit 

data on the extra travel time necessary to refuel on home to work trips in the Sacramento area as 

the number of service stations was reduced in a simulation modeling analysis. Greene (2001) 

assumed that the value (cost) of 5% availability in present, purchase price equivalent dollars was 

-$2,750, while the cost of 10% availability would be only about -$1,000. A power curve fitted to 

the Nicholas et al. (2004) simulation results and assuming a value of time of $20.00 per hour, 

results in costs of about -$2500 at just under 0.5% availability, decreasing to -$500 at about 10% 

availability (Figure 10). The associated coefficients are C =-0.546 and a = -0.345. For this 

analysis, coefficient values of C = -0.5 and a = -0.33 were used. These estimates of the cost of 

limited fuel availability are considered to be conservative because they do not include any 

estimate of the risk of running out of fuel or of waiting for a pump if queues form, and because 

the value of many new car buyers’ time is likely to be substantially higher than $20/hr. 

Cost of Limited Fuel Availability (Passenger Car)

-$8,000

-$7,000

-$6,000

-$5,000

-$4,000

-$3,000

-$2,000

-$1,000

$0

0% 10% 20% 30% 40% 50%

Fraction of Stations Offering Fuel

Present Value Dollars

After Nicholas, et al., 2004

Greene, 2001

Figure 10. Power Functions Describing the Cost of Limited Fuel Availability 

According to the Census Bureau, approximately 42,000 non-truck-stop stations offered diesel 

fuel in 1997 (Hadder, 2004, p. D-6) out of a total of 127,000 refueling outlets (33%). Because 

all truck-stops can be assumed to offer diesel fuel the number of diesel fuel outlets undoubtedly 

exceeds 42,000. On the other hand, The Census Bureau (2004, table 4.17) report 171,000 retail 

fueling outlets in 2002 based on a National Petroleum Survey. Despite considerable uncertainty 

in these numbers, we assume 33% as the baseline availability in 2008. 

4.5.6 High Quality Diesel Fuel 

Every potential diesel manufacturer interviewed for this study expressed a desire to see higher 

quality diesel fuel in the U.S. market. In this study, we do not consider the potential impact of 

high-quality diesel fuel availability on the market potential for diesel vehicles. However, we 

note that widely available high-quality diesel fuel could only increase the market potential of 

light-duty diesels. 
29 

Manufacturers were unanimous in requesting diesel fuel that would meet the World-wide Fuel 

Charter requirements for Category 4 Diesel Fuel. None thought that high quality diesel fuel 

would be essential for meeting Tier 2 emissions standards; the low-sulfur diesel coming to U.S. 

markets in 2006-7 would be adequate for that purpose. Rather, high-quality diesel fuel would 

allow manufacturers to deliver benefits to diesel car buyers in terms of quicker, easier ignition at 

low temperatures, faster, smoother warm-up, cleaner injectors and fuel system and reduced 

engine wear. 

Hadder (2004) has analyzed the likely fuel production, logistics and resulting consumer costs of 

high-quality diesel fuel significantly different from the ultra-low sulfur diesel fuel required to be 

in the market in 2010, and satisfying the World-wide Fuel Charter requirements. Depending on 

the volume of sales and market share, the distribution costs of high-quality diesel could add 0-5 

cents per gallon to its pump price. Hadder found that the added costs of refining high-quality 

diesel, principally distillate dearomatization and cetane improver, would add about 3 cents per 

gallon. Finally, because the energy content per gallon of high-quality diesel is likely to be 

slightly lower than that of ultra-low sulfur diesel, consumers would suffer another 2 cents per 

gallon cost increase due to reduced fuel economy. All told, consumers could be expected to pay 

6-10 cents per gallon more for high-quality diesel than for ultra-low sulfur diesel. This is, in 

general, less than the additional cost of premium gasoline versus unleaded regular. Premium 

gasoline, however, is often required to avoid engine knock. It is highly unlikely that 

manufacturers would require high-quality diesel fuel, though it might be recommended. Thus, 

high-quality diesel would be a customer option, purchased only when consumers felt it delivered 

more in benefits than it cost. In this respect, the availability of high-quality diesel could only 

increase the desirability of diesel vehicles. 

4.5.7 Extra Features of Hybrids or Diesels 

No attempt was made in this analysis to estimate the potential extra value that hybrids may be 

able to create due to the availability to generate and store high-voltage electricity or to impute 

extra value to diesels based on durability or other factors. 

4.5.8 Make, Model and Configuration Intercepts 

Configuration-specific intercepts ensure that the NMNL model exactly predicts base year market 

shares. The intercepts represent the value to the consumer of all vehicle attributes not explicitly 

included in this model (all attributes other than price, fuel economy, range, torque and fuel 

availability). The formulas for computing vehicle and class intercepts can be found in 

Appendix A. 

4.5.9 Minimum Sales Thresholds 

After introducing the diesel and hybrid vehicles and predicting their market shares, we then 

delete diesel or hybrid carlines that fail to achieve minimum sales thresholds. This is done by 

summing sales of diesel or hybrid configurations to the make and model level, and checking for 

adequate sales to achieve scale economies. Diesels or hybrids with sales less than the threshold 

value (5,000 in 2008; 10,000 in 2012; 25,000 for >2012) sold within a given nameplate are 

deleted. In addition, in the >2012 scenarios each configuration must sell at least 2,000 units. 

Market penetrations are then be re-estimated. 
 
31 

5. RESULTS 

Eight scenarios were developed, two each for 2008 and 2012, and four for beyond 2012 (>2012). 

For 2008, assumptions about the introductions of hybrid and diesel vehicles are based primarily 

on manufacturers’ announced product plans (a list of makes and models assumed to be 

introduced can be found in Appendix B). A “best guess” forecast is based on these 

announcements plus our own judgments about probable new introductions. In general, we 

believe that diesels and hybrids will most often be introduced on the better selling versions of 

makes and models. A lower forecast was also constructed based on the assumption that the 

diesel or hybrid configuration will be an average configuration of its make and model. The 

mathematics of this method are described in Appendix A. The 2012 scenario builds on the 

planned introductions of the 2008 scenario and extends them, again based on our judgment. The 

average 2012 scenario uses the same method of averaging configuration intercept terms as the 

2008 scenario. 

Two other factors are assumed to differ between 2008, 2012 and >2012. In 2008, the minimum 

sale for the hybrid or diesel versions of a nameplate is set at 5,000 units, reflecting a willingness 

of manufacturers to accept low volumes during the first few years. In 2012, the minimum 

production volume is raised to 10,000. For the >2012 scenarios, a minimum make and model 

sales volume of 25,000 units is assumed. In addition, in the >2012 scenarios a minimum sales 

limit of 2,000 units is enforced for each individual diesel or hybrid configuration. For 2008, 

diesel fuel is assumed to be available at 33% of retail outlets. In 2012 and >2012, assuming that 

more diesel vehicles are on the road, availability is increased to 50%. 

Because consumers value diversity of choice, the sales of diesel and hybrid vehicles are strongly 

dependent on the number of makes, models and configurations offered for sale (Table 10). 

However, economies of scale work against offering many makes and models; the more 

configurations offered, the fewer sold per configuration. The initial number of makes, models 

and configurations offering diesel and hybrid versions is strictly an assumption. The model, 

however, determines which makes and models will exceed the assumed sales thresholds (5,000 

for 2008, 10,000 for 2012 and 25,000/2,000 for >2012). This will depend not only on the 

attractiveness of diesel or hybrid vehicles, but on competition between them. For example, in the 

Diesel Only scenario, 257 diesel vehicles exceed the sales thresholds. When diesels must also 

compete with full hybrids in the Diesel/Full Hybrid scenario, the number of diesel vehicles that 

exceed the sales thresholds drops to 210. 

5.1 THE LONG-RUN POTENTIAL MARKET SHARES OF DIESEL AND HYBRID 

VEHICLES 

We begin by exploring the implications of consumers’ preferences, unconstrained by the 

availability of diesel and hybrid offerings. Four >2012 scenarios address the question, “How big 

could the diesel and hybrid markets become if hybrids and diesels were generally available 

throughout the light-duty vehicle market?” No particular date is attached to these scenarios 

because they are intended to represent the long-run tendencies of the marketplace. Assuming 

that customers’ preferences will eventually dictate manufacturers’ decisions, these scenarios 

should indicate the direction in which the market will move after the initial hurdles have been 
32 

overcome. How fast and how far the market will move will depend on a number of factors, 

including the rates of technological progress and learning, manufacturers’ willingness to take 

risks, future fuel prices, government policies towards fuel economy and greenhouse gas 

emissions, and the evolution of consumers’ preferences. 

Table 10. Numbers of Diesel and Hybrid Configurations Offered, by Scenario 

SCENARIO 

(921 Conventional Gasoline Configurations) 

No. of Diesel 

Configurations 

No. of Hybrid 

Configurations 

2008 Best Guess 38 54 

2008 Average Configuration 35 46 

2012 Best Guess 46 90 

2012 Average Configuration 46 72 

>2012 Diesel Only 257 0 

>2012 Hybrid Only 0 235 

>2012 Diesel/Full Hybrid 210 155 

>2012 Diesel/ISAD 176 228 

Rather than guessing which models manufacturers will choose to introduce, we initially assume 

that all models, body styles and engine-transmission combinations, (except sports cars for diesels 

and standard vans for both technologies) will be available in conventional gasoline, hybrid and 

diesel versions. However, if the total diesel or hybrid sales within a make and model do not sum 

to at least 25,000 units, all diesel or hybrid configurations for that make and model are canceled. 

In addition, if any individual configuration’s sales fall below 2,000 units, that configuration of 

the make and model is also deleted. No such minimum sales requirements are imposed on 

conventional gasoline vehicles, which should tend to bias our estimates against hybrids and 

diesels, to some degree. This will also produce a shift in the distribution of sales toward makes 

and models with successful diesel or hybrid options. 

Four >2012 scenarios have been created. Two introduce only diesels or only full hybrids to 

explore how each competes head-to-head against gasoline. A third assumes that both diesels and 

full hybrids are widely available, but no other types of hybrids are considered. A final scenario 

introduces diesels and only the milder ISAD-type hybrids, to determine whether a less expensive 

but lower fuel economy hybrid would be more or less successful than the full hybrid design. 

5.1.1 Diesels Only 

In head-to-head competition with gasoline, and under the availability assumptions described 

above, diesels succeed in capturing 31% of the light duty vehicle market. Were there no 

minimum sales volume constraints, diesels would have had a 38% market share. Diesels do 

better in the light truck market, as anticipated by the Bosch North American diesel market study. 

Diesel passenger truck sales amount to 1.9 million units, 960,000 diesel pick-ups are sold, and 

luxury trucks include 250,000 diesels (Figure 11). But 1.8 million diesel passenger cars are also 

sold, 1.1 million of which are large cars. The tendency to predict a greater diesel market share 

for trucks is underlined by the fact that more diesel passenger trucks are sold despite the fact that 

there are fewer configurations of passenger trucks (82) to choose from than passenger cars (95) 

(Figure 12). 
33 

In the light truck segment, diesel light-duty vehicles average 31.3 MPG in comparison to 24.3 for 

gasoline. The 31% diesel market share produces a 7.4% increase in new light-duty vehicle 

average fuel economy. 

Technology Market Shares by Vehicle Type

>2012 Diesel Only Scenario

0%

10%

20%

30%

40%

50%

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard

Van

Share of Light-Duty Market

Diesel

Gasoline

Figure 11. Technology Market Shares by Vehicle Type 

>2012 Diesel Only Scenario 

Makes, Models, Configurations by Vehicle Type

>2012 Diesel Only Scenario

0

50

100

150

200

250

300

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard Van

Number

Gasoline

Diesel

Figure 12. Makes, Models, Configurations by Vehicle Type 

>2012 Diesel Only Scenario 
34 

5.1.2 Full Hybrids Only 

Full hybrids take 26% of the market in direct competition with conventional gasoline engines, 

(this compares with 31% for diesels). The somewhat smaller market share for hybrids is a result 

of the diesel’s lower price (see Tables 2 and 4) and slightly greater torque (25% versus 15-20%). 

The hybrid’s greater fuel economy (35-40% versus 33%) and therefore greater range are not 

enough to make up for the diesel’s price and torque advantages. Thus, the diesel seems to offer 

customers value closer to its purchase price premium than the hybrid, but only a little closer. 

Hybrids do reasonably well across vehicle types, selling 1.5 million passenger cars, 1.6 million 

passenger trucks, 700,000 pick-ups and 270,000 luxury vehicles (mostly trucks) (Figure 13). 

Hybrids also have fewer passenger car than light truck configurations available (Figure 14). 

Technology Market Shares by Vehicle Type

>2012 Full Hybrid Scenario

0%

10%

20%

30%

40%

50%

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard

Van

Share of Light-Duty Market

Hybrid

Gasoline

Figure 13. Technology Market Shares by Vehicle Type 

>2012 Full Hybrid Scenario 
35 

Makes, Models, Configurations by Vehicle Type

>2012 Full Hybrid Scenario

0

50

100

150

200

250

300

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard

Van

Number

Gasoline

Hybrid

Figure 14. Makes, Models, Configurations by Vehicle Type 

>2012 Full Hybrid Scenario 

The 26% market share of full hybrids raises overall new light-duty vehicle fuel economy to 25.9 

from 24.3, a 6.7% increase. Although full hybrids are assumed to deliver 40% better fuel 

economy for any given passenger car or small light truck and 35% for any large light truck, on 

average the hybrid light-duty vehicle fleet has only 32% higher fuel economy. The reason for 

this is that hybrids tend to sell better on the less efficient vehicle configurations. Thus, a greater 

proportion of the less-efficient configuration hybrids meet the sales threshold. Whereas the 

average fuel economy of all gasoline vehicles is 24.3, the average fuel economy of the gasoline 

vehicles for which hybrid versions are available in the Full Hybrid scenario is 23.5. The addition 

of new makes and models for these somewhat lower mpg configurations causes a shift in sales in 

their favor, also increasing the market shares of the classes to which they belong. Such a shift 

towards vehicle configurations and classes where new options are introduced is an inherent 

feature of the NMNL model. The mathematics of the model guarantee that introducing new 

makes and models will produce such sales shifts. The extent of the shifts depends on the NMNL 

model structure, on its parameters, and on the number and characteristics of the new makes and 

models introduced. The effect is to reduce the fuel economy increase caused by introducing 

diesels and hybrids. Another feature of our methodology that also mitigates potential fuel 

economy gains is the fact that we do not apply the same sales thresholds to gasoline vehicles that 

we apply to diesel or hybrid vehicles. As a result, there is no culling of lower fuel economy 

gasoline vehicles in cases where introduction of diesels or hybrids may cause their sales to fall 

below the threshold level. These two aspects of our method should make our estimates of 

potential fuel economy increases conservative, all other things equal. 
36 

5.1.3 Diesels and Full Hybrids 

With equal assumptions about availability of makes and models to start with, diesels do slightly 

better than hybrids in a three-way competition with conventional gasoline vehicles. Together 

they capture 40% of the light-duty vehicle market, with diesels taking 23.8% to the hybrids’ 

16.5% (Figure 15). Both technologies appear to compete better in the light-truck market than in 

the passenger car market. The diesel’s greater success is consistent with the head-to-head results 

presented above. Not surprisingly, more diesel vehicle makes, models and configurations turn 

out to be available than hybrid versions (Figure 16). 

Technology Market Shares by Vehicle Type

>2012 Diesel & Full Hybrid Scenario

0%

10%

20%

30%

40%

50%

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard

Van

Share of Light-Duty Market

Diesel

Hybrid

Gasoline

Figure 15. Technology Market Shares by Vehicle Type 

>2012 Diesel & Full Hybrid Scenario 

The combined effect of both technologies is to raise overall light-duty vehicle fuel economy by 

almost 10% to 26.7 MPG. On average, hybrids get 31.3 MPG and diesels 31.0, in comparison to 

24.3 for gasoline vehicles. 
37 

Makes, Models, Configurations by Vehicle Type

>2012 Diesel & Full Hybrid Scenario

0

50

100

150

200

250

300

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard Van

Number

Gasoline

Hybrid

Diesel

Figure 16. Makes, Models, Configurations by Vehicle Type 

>2012 Diesel & Full Hybrid Scenario 

5.1.4 Diesels and ISAD Hybrids 

Mild, ISAD hybrids offer only a 12.5% increase in fuel economy versus a 35-40% increase for a 

full hybrid design. ISADs also increase torque only 10% in comparison to 15-20% for a full 

hybrid. On the other hand, the ISAD system is considerably less expensive, $1,385 versus $3,920 

for a midsize or large passenger car. The lower cost of the ISAD hybrid more than offsets its 

smaller benefits, with the result that ISAD hybrids capture a larger share of the market (27%) 

than diesels (19%) in a three-way competition with conventional gasoline vehicles. The 

assumption that consumers count only the first three years of fuel savings, rather than the full 

discounted present value of fuel savings over the life of a vehicle has a great deal to do with the 

preference seen here for less expensive but less fuel efficient vehicles. 

This is the first scenario in which more hybrid passenger cars are sold than hybrids or diesels in 

any other vehicle class (Figure 17). There are also more makes, models and configurations of 

hybrids than diesels in every vehicle class (Figure 18). But ISAD hybrids achieve only 26.8 

MPG in comparison to 24.3 MPG for conventional gasoline vehicles and 30.6 MPG for diesels. 

As a consequence, despite the greater combined market share of hybrids and diesels, overall 

light-duty vehicle MPG increases by only 7% to 26.0. 

The result that hybrid market share would be higher for milder hybrid technology than for full 

hybrid technology is consistent with Santini’s (2004) findings that mild hybrids and stop/start 

hybrids are more cost-effective than full hybrids. 
38 

Technology Market Shares by Vehicle Type

>2012 Diesel & ISAD Hybrid Scenario

0%

10%

20%

30%

40%

50%

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard

Van

Share of Light-Duty Market

Diesel

Hybrid

Gasoline

Figure 17. Technology Market Shares by Vehicle Type 

>2012 Diesel & ISAD Hybrid Scenario 

Makes, Models, Configurations by Vehicle Type

>2012 Diesel & ISAD Hybrid Scenario

0

50

100

150

200

250

300

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard Van

Number

Gasoline

Hybrid

Diesel

Figure 18. Makes, Models, Configurations by Vehicle Type 

>2012 Diesel & ISAD Hybrid Scenario 
39 

5.2 2008 SCENARIOS 

The two 2008 scenarios produce diesel market shares ranging from 2.4 % (0.4 million units) to 

3.9% (0.6 million units) of light-duty vehicle sales. The higher estimate is obtained under our 

“best guess” assumptions. The lower estimate is based on the assumption that the diesel will be 

similar to the average configuration for the make and model in question (i.e., an average 

intercept is used). Diesel sales are concentrated in the passenger truck, luxury truck, and pick-up 

truck market segments in 2008 (Figures 19 & 21). 

The predicted market shares for hybrid vehicles are larger, ranging from 4.6% (750,000 units) 

assuming average intercepts to 7.1% (1.1 million units) when the best-guess configurations are 

assumed. In large part, the greater success of hybrids can be attributed to the fact that more 

hybrid configurations are expected to be introduced (54 hybrids versus only 38 diesels in the 

best-guess scenario). Manufacturers are planning to move more cautiously into the diesel 

market, most likely due to uncertainties about the diesel’s ability to meet the Tier 2, bin 5 

emissions standard. Hybrids are more concentrated in the passenger vehicle segments (Figures 

19 & 21). 

In the 2008 average scenario, 450,000 passenger cars, 220,000 passenger trucks and 70,000 

luxury vehicles are hybrids. Only 16,000 hybrid pick-ups are sold and there are no hybrid 

sportscars or standard vans. In the “best-guess” scenario, 640,000 passenger cars are hybrids, as 

are 360,000 passenger trucks. Among hybrid technologies, full hybrids are the most prevalent, 

followed by stop-start and IMA, with ISAD capturing only a small share of the market (Figures 

20 & 22). 

Technology Market Shares by Vehicle Type

2008 Planned Introductions Average Scenario

0%

10%

20%

30%

40%

50%

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard

Van

Diesel

Hybrid

Gasoline

Figure 19. Diesel and Hybrid Vehicle Market Shares by Vehicle Type: 

2008 Average Scenario 
40 

Hybrid Vehicles by Degree of Hybridization: 

2008 "Planned Introductions Average Scenario"

(Total Hybrid Market Share = 4.6%)

Stop-Start, 1.6%

ISAD, 0.2%

IMA, 1.1%

Full Hybrid, 1.7%

Figure 20. Distribution of Hybrid Vehicle Sales by Degree of Hybridization, 

2008 Average Scenario

Technology Market Shares by Vehicle Type

2008 "Best Guess" Scenario

0%

10%

20%

30%

40%

50%

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard

Van

Diesel

Hybrid

Gasoline

Figure 21. Diesel and Hybrid Market Shares by Vehicle Class, “Best Guess” Scenario 
41 

Hybrid Vehicles by Degree of Hybridization: 

2008 "Best Guess" Scenario

(Total Hybrid Market Share = 7.1%)

Stop-Start, 2.5%

ISAD, 0.2%

IMA, 1.8%

Full Hybrid, 2.5%

Figure 22. Distribution of Hybrid Vehicle Sales by Degree of Hybridization, 

2008 “Best Guess” Scenario 

5.3 2012 SCENARIOS 

In the 2012 scenarios, diesel’s market share ranges from 4.1% (680,000 units) in the average 

scenario (Figure 23) to 7.2% (1.2 million units) in the “best guess” scenario (Figure 24). While 

light trucks still predominate, sales of diesel passenger trucks (small and large SUVs; no diesel 

minivans are assumed in the 2012 scenarios) outnumber diesel pick-ups. In both scenarios 

passenger cars are a small market for diesels (30,000 units in the “best guess” scenario; 50,000 in 

the “average” scenario). Diesels also make inroads in the luxury truck market with 170,000 to 

180,000 luxury diesel trucks sold in the average and best guess 2012 scenarios, respectively. 

Technology Market Shares by Vehicle Type

2012 Average Scenario

0%

10%

20%

30%

40%

50%

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard

Van

Diesel

Hybrid

Gasoline

Figure 23. Hybrid and Diesel Market Shares by Vehicle Class, 2012 “Average” Scenario 
42 

The 2012 hybrid share ranges from 10% (1.7 million units) for the average scenario to 15% (2.5 

million units) in the “best guess” scenario (Figure 25). Passenger cars are still the largest hybrid 

market (0.86 to 1.25 million units), followed by passenger trucks (0.56 to 0.92 million units), but 

hybrids also achieve some success among pick-ups (60,000 to 70,000) and luxury vehicles 

(190,000 to 220,000 units). 

In the 2012 “Average” scenario, full hybrids still capture more than half of the hybrid market, 

followed by the inexpensive stop-start system, IMA and then ISAD systems (Figure 26). In the 

“best guess” scenario, stop-start and IMA systems take a larger share of the hybrid market 

(Figure 27). While this produces greater overall hybrid sales, it also diminishes their relative 

impact on fuel economy. 

Technology Market Shares by Vehicle Type

2012 Best Guess Scenario

0%

10%

20%

30%

40%

50%

Passenger

Cars

Passenger

Trucks

Pick-ups Luxury

Vehicles

Sportcars Standard

Van

Diesel

Hybrid

Gasoline

Table 24. Distribution of Hybrid Technology Types in the 2012 “Best Guess” Scenario 
43 

Comparison of 2012 "Average" and "Best Guess" 

Market Share Estimates

77.8%

14.9%

7.2%

85.4%

10.2%

4.4%

0%

20%

40%

60%

80%

100%

Gasoline Hybrid Diesel

Best Guess

Average

Figure 25. Comparison of Market Success in “Average” and “Best Guess” Scenarios 

Hybrid Vehicles by Degree of Hybridization: 

2012 Average Scenario

(Total Hybrid Market Share = 10.2%)

Stop-Start, 2.2%

ISAD, 0.5%

IMA, 1.7%

Full Hybrid, 5.8%

Figure 26. Distribution of Hybrid Vehicle Sales by Degree of Hybridization, 

2012 “Average” Scenario 
44 

Hybrid Vehicles by Degree of Hybridization: 

2012 "Best Guess Scenario"

(Total Hybrid Market Share = 14.9%)

Stop-Start, 4.2%

ISAD, 0.7%

IMA, 2.9%

Full Hybrid, 7.1%

Figure 27. Distribution of Hybrid Vehicle Sales by Degree of Hybridization, 

2012 “Best Guess” Scenario 

The difference in combined diesel and hybrid sales between the 2012 “average” and “best guess” 

scenarios is an indication of the uncertainty of future market success, even given the specific 

makes and models assumed to be introduced: a combined 15% versus 22% of the market, 

respectively (Figure 25). This reflects the critical importance of the specific configurations on 

which manufacturers choose to offer these technologies. If diesels and hybrids are available on 

the more popular body styles and trim lines, they will fare better than if they are available only in 

a single, average style. This boosts sales and helps makes and models get over the 10,000 units 

sales threshold. In the “average configuration” scenario, only 72 configurations of hybrids are 

available (Table 10) whereas in the best guess scenario there are 90 different hybrid 

configurations. 

5.4 IMPACTS ON FUEL ECONOMY 

The potential impacts of diesel and hybrid technology on new passenger car and light truck fuel 

economy are estimated by comparing the actual fuel economy of model year 2002 light-duty 

vehicles to the fuel economy of the hypothetical new vehicle fleets of the 2008, 2012 and >2012 

scenarios. The scenario fleets contain all the conventional gasoline makes and models of the 

model year 2002 fleet, plus the assumed introductions of diesel and hybrid vehicles of the 

scenario in question. Whereas new diesel and hybrid vehicles must meet the minimum sales 

thresholds described in the previous section, all conventional gasoline makes and models are 

retained, regardless of their sales volumes. The total number of light-duty vehicles sold is 

assumed to remain constant but the sales distribution changes in response to the introductions of 

diesel and hybrid vehicles, as predicted by the NMNL model described in previous sections. 
45 

Because low-selling gasoline makes and models are not culled from the set of choices available 

to consumers, the NMNL will always predict some degree of shift in sales in favor of those 

vehicles introducing new hybrid and diesel configurations, simply because of the greater variety 

of choices they offer consumers. As will be seen below, this generally produces a modest shift 

in the sales distribution in favor of lower fuel economy vehicle configurations. In part, this is a 

product of our assumptions about which makes and models will offer diesels and hybrids. In 

part, it is a result of the fact that these technologies produce greater fuel savings on the lowest 

fuel economy vehicles and therefore sell best in those applications. 

Fuel economies are calculated as a sales-weighted harmonic mean of all make, model and 

configuration fuel economies. The fuel economies of gasoline vehicles are assumed to remain 

constant at the 2002 levels. Diesel and hybrid fuel economies are estimated by multiplying the 

model year 2002 fuel economy of the corresponding gasoline version of the vehicle by one plus 

the fractional improvements in fuel economy given in tables 1 and 3. In the few cases where 

there is no comparable gasoline vehicle, we have estimated the fuel economy of the new product. 

With the exception of the increase in torque we assume will be provided with diesel and hybrid 

vehicles, we assume no changes in the size, weight or performance of vehicles relative to model 

year 2002. We make no attempt to determine whether manufacturers would change the designs 

and fuel economies of gasoline vehicles as a result of increased sales of diesels and hybrids. 

The moderate market successes of diesel and hybrid technologies raise average fuel economy by 

1.5% to 2% in the 2008 scenario, 3% to 4% in the 2012 scenarios and up to 10% beyond 2012 

(Table 11). These scenarios assume no significant policy changes that would drive up fuel 

economy and no significant change in the price of motor fuel. In the 2008 and 2012 “best guess” 

scenarios, fuel economy increases from 24.3 MPG to 24.8 and 25.2, respectively (Figure 28). 

Fuel economy increases the most in the >2012 Diesel/Full Hybrid scenario, reaching 26.7 MPG. 

New Light-Duty Vehicle Fuel Economy by Scenario

24.3 24.6 24.8 24.9 25.2

26.7 26.0 26.1 25.9

0

5

10

15

20

25

30

2002 Data Base

2008 Average

2008 Best Guess

2012 Average

2012 Best Guess

Diesel and Full Hybrid

Diesel and ISAD Hybrid

Diesel only

Hybrid only

Miles per Gallon

Figure 28. New Light-Duty Vehicle Average Fuel Economy by Scenario 
46 

Table 11. Summary of Results of Diesel Hybrid Market Scenarios 

Scenario Shares (%) Sales (1,000s) Fuel Economy 

 Gasoline Hybrid Diesel Gasoline Hybrid Diesel Gasoline Hybrid Die

2002 Data Base 99.6% 0.1% 0.2% 24.3 58.4 43

2008 Average 93.0% 4.6% 2.4% 15,092 752 387 24.2 32.1 272008 Best Guess 89.1% 7.1% 3.9% 14,484 1,148 627 24.3 31.6 262012 Average 85.4% 10.2% 4.4% 14,041 1,675 722 24.2 31.5 262012 Best Guess 77.8% 14.9% 7.2% 12,791 2,457 1,189 24.2 31.8 26>2012 Diesel and Full Hybrid 59.7% 16.5% 23.8% 9,643 2,658 3,847 24.3 31.3 31>2012 Diesel and ISAD Hybrid 53.8% 27.0% 18.2% 8,692 4,362 3,094 24.3 26.8 30>2012 Diesel only 69.2% 0.0% 30.8% 11,180 0 4,969 24.3 -- 31>2012 Hybrid only 74.1% 25.9% 0.0% 11,959 4,189 0 24.3 32.0 -Total Vehicle Sales 16,148 
47 

In the 2008 and 2012 scenarios light truck fuel economy gains are somewhat greater than the 

increases for passenger cars. For example, in the 2012 “best guess” case, light truck MPG is 

6.3% higher than the 2002 base level of 21.0 MPG, while passenger car MPG increases by 3.2% 

over the 2002 base of 28.8 (Table 12). 

Table 12. Average Fuel Economy of Passenger Cars and Light Trucks 

 2008 

Best Guess 

2008 

Average 

2012 

Best Guess 

2012 

Average 

2002 

Base 

Passenger cars 29.4 29.2 29.7 29.4 28.8 

Light trucks 21.7 21.4 22.3 21.8 21.0 

All light-duty vehicles 24.9 24.7 25.2 24.9 24.3 

These fuel economy impacts may seem small at first. How could technologies offering 30% to 

40% better fuel economy and capturing 40% of the market raise MPG by only about 10%? Part 

of the answer is harmonic averaging. Consider two types of vehicles with initially equal fuel 

economy. The harmonic mean of a 0% increase (1.0) with a share of 0.6 and a 35% increase 

(1.35) with a share of 0.4 is only 11.6%, not 0.35 x 0.40 x 100% = 14%. 

1.116 11.6%

1.35

0.4

1.0

0.6

1 = ⇒

⎟

⎠

⎞ ⎜

⎝

⎛ +

Equation 9 

The difference between the value of 11.6% produced by this rough calculation and the model’s 

calculation of 9.5% is the result of sales mix shifts that mitigate against fuel economy increases. 

Hybrid and diesel technologies tend to sell better on vehicles with low fuel economy than on 

those with the highest fuel economy because the value of the fuel saved is greater relative to the 

cost of the technology. For example, in the Full Hybrid and Diesel scenario in which any vehicle 

could be a hybrid or diesel providing it meets minimum sales requirements, 25 of 37 hybrid 

passenger car models turn out to be large cars, and 113 of 155 total hybrid models are trucks. 

For diesels, 143 models are trucks out of a total of 210. The success of the new technologies in 

those market segments increases their overall market share. In addition to raising fuel economy, 

this causes an overall sales mix shift towards lower fuel economy vehicles, which mitigates the 

technologies’ fuel economy benefit. To some degree these sales shifts are an artifact of our 

methodology, as described above. 

Deleting diesel and hybrid makes and models selling under 25,000 units also has a significant 

effect on fuel economy. If all makes and models selling over 5,000 are included in the Full 

Hybrid and Diesel scenario, the average MPG of a hybrid increases from 31.3 (all <25,000 

excluded) to 32.3. Including diesel makes and models with sales in the interval 5,000-25,000 

raises the average MPG of a diesel car from 31.1 to 31.5. Overall, had the lower limit on sales 

volume been 5,000 instead of 25,000 in the >2012 diesel/full hybrid case, light-duty vehicle 

average MPG would have been 27.6, an increase of 14% instead of 9.5%. Diesels would capture 

28% of the market instead of 24%, and hybrids would claim a 23% market share instead of 16%. 

When the higher sales limits are imposed, small and midsize cars are the greatest losers. The 

number of small and midsize makes and models offered drops from 140 hybrids to only 12, and 
48 

from 161 diesels to only 34. In the following section the sensitivity of the model’s predictions to 

assumptions about scale economies is tested and measured.

5.5 SENSITIVITY ANALYSIS 

The sensitivity of the choice model’s predictions to eight key factors was tested using Monte 

Carlo simulation. In a Monte Carlo simulation inputs are treated as random variables rather than 

fixed parameters. Samples are drawn from the distributions of the random variables, the model 

is run, and the process is repeated (here 1,000 times), producing a distribution of output values 

rather than a single set of values. Given the resulting data base of outputs, one can measure the 

sensitivity of outputs of interest (e.g., diesel or hybrid market shares) to the input variables by 

means of regression analysis. 

The eight parameters are the incremental prices of (1) hybrid and (2) diesel vehicles, (3) the 

general sensitivity of vehicle choices to price, the prices of (4) gasoline and (5) diesel fuel (these 

are so highly correlated, about 0.95, that they should count as only one variable), (6) the overall 

sensitivity of vehicle choice to price diesel fuel availability, (7) the minimum nameplate, and 

(8) configuration sales volumes, for hybrids or diesels to be viable on a particular make and 

model. Table 13 lists the variables and describes the assumed probability distributions. Most of 

the distributions have the same or almost the same means as the >2012 scenarios described 

above. A notable exception is the minimum production volume, which has a mean of 15,000 

units. This will result in considerably greater hybrid and diesel sales and higher fuel economy 

than the other >2012 scenarios. 

Table 13. Assumptions for Sensitivity Analysis of Hybrid and Diesel Choice 

Input Variable Mean/Mode Distribution Minimum Maximum

Incremental Price of Hybrid Vehicle 1.0 

(relative) 

Triangular -50% +50% 

Incremental Price of Diesel Vehicle 1.0 

(relative) 

Triangular -50% +50% 

Price Sensitivity 1.0 

(relative) 

Triangular -50% +100% 

Price of 

 Gasoline / 

 Diesel Fuel 

$1.50 

$1.50 

Triangular $1.25 

$1.25 

$2.00 

$2.00 

Availability of Diesel Fuel 50% Triangular 20% 80% 

Minimum Nameplate Sales 15,000 Triangular 5,000 25,000 

Minimum Configuration Sales 1,500 Triangular 500 2,500 

Of the inputs chosen, all are factors exogenous to the consumer’s choice except price sensitivity. 

It would have been of interest to test the sensitivity of the model’s predictions to assumptions 

about the value of fuel savings, range, torque, etc., but these factors are interdependent with the 

price sensitivity of vehicle choice in ways that are too complex for the Monte Carlo simulation to 

handle easily. 
49 

The sensitivity analysis was carried out using the >2012, Diesel/Full Hybrid scenario. This 

scenario produced the greatest impact on fleet average fuel economy. Given the probability 

distributions shown in Table 13, the simulation produced a 90% confidence interval for diesel 

market share of 16% to 34%, with an expected value of 25% (Figure 29). This is higher than the 

original >2012 Diesel/Full Hybrid scenario partly because the mean minimum production 

threshold is lower, 15,000 versus 25,000 units. This allows a greater number of diesel and 

hybrid makes and models to be offered. 

Cumulative Probability Distribution of Diesel Market Share 

>2012 Diesel/Full Hybrid Scenario

Mean = 0.252

X <=0.34

95%

X <=0.16

5%

0

0.2

0.4

0.6

0.8

1

0.05 0.15 0.25 0.35 0.45

 Market Share (fraction)

 Probability Share < X

Figure 29. Sensitivity Analysis of Diesel Market Share, >2012 Diesel/Full Hybrid Scenario 

The tornado chart (Figure 30) shows which variables have the greatest influence on diesel’s 

market share. Not surprisingly, the incremental price of the diesel vehicle is the single most 

important factor, with a standardized regression coefficient (similar to a partial correlation) of 

-0.9: the higher the diesel’s price, the lower its market share. Next in importance are the prices 

of gasoline and diesel fuel: higher gasoline prices boost diesel sales, higher diesel prices lower 

sales. Gasoline and diesel prices are assumed to be highly correlated; a correlation coefficient of 

0.95, which is based on historical data, is used. Thus, the two prices will generally increase or 

decrease together. The tornado chart, however, shows the independent effects of these prices 

(i.e., the effect of an increase in the price of diesel fuel) assuming the price of gasoline stays 

constant. The positive effect of higher gasoline prices on diesel’s market share is greater than 

the negative effect of higher diesel prices, so the overall effect of an increase in petroleum prices 

would be to boost diesel market share. The price of hybrid vehicles is next in importance, 

followed by diesel fuel availability. Diesel and hybrid power trains compete to a limited degree, 

so that as the price of hybrids increases, sales of diesels increase somewhat. The greater the 

price elasticity of vehicle choice the smaller the diesel share will be. Since the price elasticity is 

an assumed parameter, it is comforting that its influence is not great despite varying 

-50%/+100% from its average value. The final two variables show that the higher the minimum 

production volume the lower diesel sales will be due to a reduction in diversity of choice. 
50 

 Regression Sensitivity for Diesel Market Share

-0.898

0.46

-0.32

0.319

-0.171

-0.165

-0.017

-1 -0.5 0 0.5 1

Price of Diesel Vehicle

Price of Gasoline

Price of Diesel

Price of Hybrid Vehicle

Price Elasticity

Minimum Nameplate Sales

Minimum Configuration Sales

Standardized Sensitivity Coefficients

Figure 30. Tornado Chart Showing Influence of Inputs on Diesel Market Share

Hybrid market shares have a similarly wide 90% confidence interval from 18% to 29%, with a 

mean of 19% (Figure 31). Again, the chief determinant of the hybrid’s market share is its own 

incremental price (Figure 32). The second most important determinant, however, is the assumed 

price elasticity of choice, indicating that the hybrid forecasts are much more sensitive to this 

assumption than those for diesels. The minimum production volume is about equally important 

for hybrids as for diesels. The fact that the predicted hybrid market share is more sensitive to the 

assumed price sensitivity suggests that the hybrid forecasts should be considered somewhat more 

uncertain than the diesel forecasts. The hybrid share will increase when diesel prices increase, 

but it may be a surprise that the hybrid share decreases when gasoline prices increase. This 

indicates that in the Diesel/Full Hybrid scenario, hybrids compete more directly with diesel 

vehicles than with conventional gasoline vehicles. In addition, because gasoline and diesel 

prices are highly correlated, in most cases they will rise together and the net effect will be an 

increase in hybrid’s market share. 
51 

Cumulative Probability Distribution of Hybrid Market Share

Mean = 0.188

X <=0.29

95%

X <=0.08

5%

0

0.2

0.4

0.6

0.8

1

0 0.1 0.2 0.3 0.4

 Market Share (fraction)

 Probability Share < X

Figure 31. Sensitivity Analysis of Hybrid Market Share, >2012 Diesel/Full Hybrid Scenario 

 Regression Sensitivity for Hybrid Market Share

0.223

-0.175

0.11

-0.067

-0.015

-0.486

-0.785

-1 -0.5 0 0.5 1

Price of Hybrid Vehicle

Price Elasticity

Price of Diesel Vehicle

Minimum Nameplate Sales

Price of Diesel

Price of Gasoline

Minimum Configuration Sales

Standardized Sensitivity Coefficients

Figure 32. Tornado Chart Showing Influence of Inputs on Hybrid Market Share 
52 

The average fuel economy of new light-duty vehicles has a confidence interval ranging from 

26.1 to 27.8 MPG, with a mean value of 27 (Figure 33). This is higher than the mean value of 

26.6 for the original >2012 Diesel/Full Hybrid scenario partly because the mean minimum 

production value of the sensitivity analysis is 15,000 rather than 25,000. 

Cumulative Probability Distribution for New Light-Duty 

Vehicle Fleet Average Fuel Economy

Mean = 26.97

X <=27.77

95%

X <=26.06

5%

0

0.2

0.4

0.6

0.8

1

25.0 25.9 26.8 27.6 28.5

 Miles per Gallon

Probability MPG < X

Figure 33. Sensitivity Analysis of LDV Fuel Economy, >2012 Diesel/Full Hybrid Scenario 

The most important determinants of the average MPG of new light-duty vehicles are the assumed 

price elasticities of vehicle choice and the incremental prices of hybrid and diesel vehicles 

(Figure 34). If consumers are much more sensitivity to price than assumed in this analysis, the 

MPG impacts of diesels and hybrids could be considerably lower. Next in importance are the 

incremental prices of diesels and hybrids, hardly a surprise. Also, if the range of choices 

available to consumers as influenced by the minimum nameplate sales requirement are much 

more limited, again the MPG impact will be reduced. Finally, an increase in the price of 

gasoline will tend to raise MPG as consumers shift to hybrids and to conventional gasoline 

vehicles with higher fuel economy. An increase in diesel price, the price of gasoline held 

constant, tends to discourage diesels sales which have a net negative impact on fleet average fuel 

economy. Greater diesel fuel availability has no significant impact. 
53 

 Regression Sensitivity for Light-Duty Vehicle MPG

0.21

-0.102

-0.025

-0.31

-0.423

-0.461

-0.643

-1 -0.5 0 0.5 1

Price Elasticity

Price of Hybrid Vehicle

Price of Diesel Vehicle

Minimum Nameplate Sales

Price of Gasoline

Price of Diesel

Minimum Configuration Sales

Standardized Sensitivity Coefficients

Figure 34. Tornado Chart Showing Influence of Inputs on LDV Fuel Economy 

55 

6. CONCLUSIONS 

This analysis indicates that if diesels and hybrids can achieve the technology goals we expect 

they will, they will have a future as mainstream drivetrain technologies for light-duty vehicles in 

the United States. Diesels must meet Tier 2 bin 5 emissions standards, an achievement that is 

almost but not quite within reach at the present. Hybrids must reduce costs to roughly half the 

cost increment of the first generation hybrids, a goal they are well on their way to reaching. If 

they can achieve these goals, diesels and hybrids should be able to capture 7-10% of the U.S. 

light-duty vehicle market by 2008, and 15-20% by 2012 (Figure 35). 

Comparison of 2012 and 2008 "Best Guess"

Market Share Estimates

77.8%

14.9%

7.2%

89.1%

7.1% 3.9%

0%

20%

40%

60%

80%

100%

Gasoline Hybrid Diesel

2012 2008

Figure 35. Comparison of Market Success in 2008 and 2012 under 

“Best Guess” Scenarios 

Because of their higher costs, the combined market share of diesels and hybrids is likely to be 

limited to half or less than half of all light-duty vehicles even in the long-run, unless policy and 

market conditions change significantly in their favor. Such changes are not unlikely, given 

continuing concerns about energy security and global climate change. The long-run impact of 

these technologies on fuel economy is likely to be about a 10% increase in the absence of 

additional policy initiatives to boost fuel economy or further technological advances. It is 

certainly possible, and indeed likely that increased sales of diesels and hybrids could raise new 

light duty vehicle fleet fuel economy by 1% to 3% by 2008, and by 3% to 5% by 2012, without 

new policies, assuming no reduction in the fuel economy of conventional gasoline vehicles. 

The market success of diesels and hybrids is highly dependent on manufacturers’ decisions to 

introduce a diverse array of makes and models in different vehicle classes. In 2008, when diesel 

and hybrid offerings are assumed to be very limited, diesels capture only 2-4% and hybrids only 

4-7% of the light-duty market. In >2012, when the number of diesel configurations is much 
56 

greater either can claim 15-30% of the market. Manufacturers face considerable risk in 

introducing diesel and hybrid vehicles due to their higher costs and the possibility that diesels 

may be unable to meet Tier 2, bin 5 standards. Thus, the timing of diesel and hybrid 

introductions and therefore their market success is uncertain, despite announced product plans. 
57 

REFERENCES 

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Duleep, K.G. 2003. “Analysis of Hybrid Technology,” presentation to the U.S. Department of 

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58 

Greene, D.L. 1994. Alternative Fuels and Vehicles Choice Model, ORNL/TM-12738, Center 

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Greene, D.L. and J.T. Liu. 1988. “Automotive Fuel Economy and Consumers’ Surplus,” 

Transportation Research A, vol. 22A, no. 3, pp. 203-218. 

Hadder, G.R. 2004. “High Quality Diesel Fuel Production, Logistics and Consumer Costs,” 

Engineering Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN, 

May. 

Irvine, F.O. 1993. “Demand Equations for Individual New Car Models Estimated Using 

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49, no. 3, pp. 764-782. 

J.D. Power and Associates. 2003. “Hybrid Electric Vehicle Sales Expected to Increase 

Dramatically over Next Decade,” news release, Westlake Village, CA, May 28. 

Kleit, A.N. 1990. “The Effect of Annual Changes in Automobile Fuel Economy Standards,” 

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McManus, W. 2004. “Hybrids and Clean Diesels: If you Build It, Will They Come?” J.D. 

Power and Associates, Detroit, Michigan. 

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Associates, Detroit, Michigan. 

Miller, J.B. 2004. “Higher Gas Prices May Fuel Hybrid Sales,” Norwich Bulletin, 

www.norwichbulletin.com/news/stories/20040609/localnews/603888.html , June 9, 2004. 

(NRC) National Research Council. 2002. Effectiveness and Impact of Corporate Average Fuel 

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Meeting of the Transportation Research Board, January 11-15, 2004, Washington, DC. 

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59 

Qualters, C. 2004. “Diesel Market Discussion,” private briefing, Bosch, GmbH, Farmington 

Hills, MI, February 5. 

Santini, D. 2004. “Customer Benefits and Attributes of Diesels and Hybrids: Market 

Competitors or Complements?” presentation slides dated April 14, 2004, Center for 

Transportation Research, Argonne National Laboratory, Argonne, IL. 

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England. 

Schmidt’s Auto Publications. 2003. “Diesels at 40% and Climbing,” AID Newsletter, no. 0302, 

Warwick, England, and on-line update, “Diesel Car Prospects to 2009,” May 17, 2003, 

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Toyota Motor Sales, U.S.A., Inc. 2004. “The 2004 Prius – A Wildly Successful Launch!” 

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Toyota Motor Sales, U.S.A., Inc. 2003. “Toyota Prius Hybrid Production Increased by 31 

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APPENDIX A 

CALCULATION OF CONFIGURATION AND CLASS CONSTANTS 

63 

APPENDIX A 

CALCULATION OF CONFIGURATION AND CLASS CONSTANTS 

Given the base year market shares for every configuration, the measured attributes of 

configurations, and the calculated attribute weights, an intercept term can be estimated for each 

configuration that causes the NMNL model predictions to exactly match base year sales. These 

intercept terms reflect the average value of all unmeasured attributes. The same can be done to 

insure that the NMNL model exactly predicts base year vehicle class shares. 

Let po be the base year sales share of an arbitrarily chosen reference configuration. The 

logarithm of the ratio of any configuration’s market share to the reference market share is equal 

to the difference in the utility indices of the two vehicles. 

U i o i o i

U

o

i U U A A U

e

e

p

p

o

i

= − = − + ∆ ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ =⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ ln ln

Equation A-1 

In equation A-2, ∆Ui is the difference of the measured utility indices of configuration i and the 

reference configuration. Solving for Ai , and summing over all configurations, i=1, n, and 

imposing the additional condition that ∑Ai = 0, gives an equation that can be solved for Ao . 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = ∑ ∆ − =

n

i o

i

o i

p

p U

n

A

1

ln 1

Equation A-2 

Inserting this value for Ao back into equation A-1 yields the equation for estimating all 

remaining Ai ‘s. 

i

o

i

i o U

p

p A A − ∆ ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = + ln

Equation A-3 

Estimation of vehicle class constants follows the same method; the difference of the expected 

class utilities are used in place of ∆Ui . 

CALCULATION OF AVERAGE CONSTANT TERMS 

The average configuration is intended to be a vehicle that is typical of (or the average of) all the 

configurations of a make and model with respect to all attributes not explicitly included in the 

vehicle choice model (i.e., other than price, fuel economy, range, fuel availability and torque). 
64 

The average nameplate constant was defined as follows. Let the average share for the i=1,ni

configurations of nameplate i be Si . 

i i

K

k

i i k ik

n

i

n

j

U

U

i

i and U A b x A Y

e

e

n

i

i

j

i

= ∑ = +∑ = +

∑= =

=

1 1

1

1 S

Equation A-4 

We wish to find an average constant term, A, such that if every configuration of nameplate i had 

a constant term equal to A, nameplate i would have exactly the same average share, Si . 

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎣

⎡

=

=

∑

∑

∑ ∑

=

=

+

= =

+

i

i

i

i i

i

i

i

i i

n

i

Y

n

i

A Y

n

i

A Y

n

i

A Y

e

e

A

e e e

1

1

1 1

ln

Equation A-5 

A is the average unobserved value of the configurations of nameplate i. It is not the constant 

term that would give a vehicle with the average observed characteristics of the configurations of 

nameplate i the average market share of those configurations. 
APPENDIX B 

ASSUMED PRODUCT INTRODUCTIONS 

67 

APPENDIX B 

ASSUMED PRODUCT INTRODUCTIONS 

Makes, Models, Configurations of Hybrid and Diesel Light-Duty Vehicles 

Assumed to Be Available in 2008 “Best Guess Scenario” 

2008 Hybrid Cars 

Manufacturer Division Name 

2002 

Sales 

2002 

Price 

Hybrid 

Type 

DCC Mer-Benz A-Class 24,000 $22,500 ISAD 

GMC Chevy Cavalier 210,244 $15,890 SS 

Honda Honda Civic FIT 20,000 $14,860 IMA 

Honda Honda Civic FIT 10,000 $13,860 IMA 

Toyota Toyota Echo 9,229 $11,780 SS 

Toyota Toyota Echo 23,266 $11,385 SS 

VWA VWA Jetta 47,846 $18,775 ISAD 

VWA VWA Jetta Wagon 5,605 $19,575 ISAD 

GMC Pontiac Grand Am 2,059 $18,465 SS 

GMC Pontiac Grand Am 67,168 $19,290 SS 

GMC Saturn L100/200 63,071 $19,065 SS 

GMC Saturn LW200 5,552 $20,130 SS 

GMC Saturn LW200 364 $19,270 SS 

Honda Acura Acura 3.2TL 60,860 $28,880 IMA 

Honda Honda Civic dx 4Dr 107,863 $14,060 IMA 

Toyota Lexus ES 300 70,517 $33,065 FULL 

Toyota Toyota Prius 22,737 $19,995 FULL 

FMC Ford Taurus 54,537 $22,445 FULL 

FMC Ford Taurus Wagon 9,942 $21,495 FULL 

FMC Mazda 626 35,363 $19,525 FULL 

FMC Mazda 626 12,787 $22,425 FULL 

FMC Mercury Sable 59,858 $20,020 FULL 

FMC Mercury Sable Wagon 4,201 $23,560 FULL 

GMC Chevy Malibu 144,946 $19,855 SS 

Honda Honda Accord 122,800 $25,300 IMA 

Nissan Nissan Altima 146,503 $18,849 FULL 

Toyota Toyota Camry 93,460 $23,700 FULL 

2008 Hybrid Trucks 

Manufacturer Division Name 

2002 

Sales 

2002 

Price 

Hybrid 

Type 

Honda Honda Odyssey 148,857 $26,750 IMA 

Toyota Toyota Sienna 85,417 $28,012 FULL 

FMC Ford Escape 4x2 67,376 $22,075 FULL 

GMC Chevrolet Blazer 2WD 1,394 $25,005 SS 

GMC Chevrolet Blazer 2WD 36,159 $26,005 SS 

GMC Chevrolet Blazer 4WD 437 $27,005 SS 

GMC Chevrolet Blazer 4WD 65,351 $28,005 SS 

GMC Saturn Vue AWD 1,052 $18,860 SS 

GMC Saturn Vue FWD 717 $17,265 SS 
68 

Manufacturer Division Name Sales Price 

Hybrid 

Type 

Honda Honda CR-V 29,053 $19,050 IMA 

Honda Honda CR-V 99,884 $20,250 IMA 

TKM Mazda Tribute 4x2 22,249 $21,485 FULL 

TKM Mazda Tribute 4x4 24,854 $22,685 FULL 

Toyota Toyota Highlander 2WD 42,567 $25,460 FULL 

Toyota Toyota Rav4 2WD 48,231 $17,575 FULL 

Toyota Toyota Rav4 4WD 39,291 $18,975 FULL 

GMC Chevrolet C1500 Tahoe 2WD 61,519 $33,409 FULL 

GMC GMC C1500 Yukon 2WD 7,193 $33,596 FULL 

GMC GMC K1500 Yukon 4WD 1,746 $34,996 FULL 

GMC Chevrolet C1500 Suburban 2WD 49,314 $36,143 FULL 

GMC Chevrolet K1500 Suburban 4WD 71,668 $38,209 FULL 

GMC Chevrolet K1500 Tahoe 4WD 5,017 $35,475 FULL 

GMC GMC C1500 Yukon XL 2WD 16,472 $36,501 FULL 

GMC GMC K1500 Yukon XL 4WD 22,731 $39,034 FULL 

2008 Diesel Cars 

Manufacturer Division Name 

2002 

Sales 

2002 

Price 

DCC Mer-Benz A-Class 24,000 $22,500 

VWA VWA Golf 3,255 $15,250 

VWA VWA Golf TDI 1,655 $17,420 

VWA VWA Golf TDI 6,025 $16,545 

VWA VWA Jetta 7,133 $18,950 

VWA VWA Jetta 11,326 $20,135 

VWA VWA Jetta 1,102 $24,700 

VWA VWA Jetta Wagon 340 $21,000 

VWA VWA New Beetle 4,766 $18,775 

VWA Audi Audi A4 1,174 $33,190 

VWA VWA Passat 8,167 $21,750 

VWA VWA Passat Wagon 8,379 $23,625 

VWA VWA Passat Wagon 695 $25,050 

BMW BMW 525i 12,579 $38,275 

DCC Mer-Benz C320 12,483 $38,135 

DCC Mer-Benz E 320 14,749 $48,450 

DCC Mer-Benz S 430 14,919 $71,850 

VWA Audi Audi A6 2,529 $36,400 

VWA Audi Audi A6 1,412 $50,650 

VWA Audi Audi A6 Avant 2,148 $39,350 

2008 Diesel Trucks 

Manufacturer Division Name 

2002 

Sales 

2002 

Price 

DCC Jeep Liberty 2WD 46,124 $22,994 

DCC Jeep Liberty 4WD 157,615 $24,479 

DCC Jeep Wrangler 25,831 $19,860 

Isuzu Isuzu Trooper 7,917 $29,405 

FMC Ford Expedition 4x2 32,851 $30,430 
69 

Manufacturer Division Name 

2002 

Sales 

2002 

Price 

FMC Ford Expedition 4x4 4,096 $33,300 

GMC Chevrolet C1500 Tahoe 2WD 14,214 $32,709 

GMC Chevrolet K1500 Tahoe 4WD 97,036 $27,857 

GMC GMC C1500 Yukon 2WD 16,240 $34,296 

GMC GMC K1500 Yukon 4WD 24,313 $34,996 

DCC Dodge Dakota 2WD 43,412 $19,625 

DCC Dodge Dakota 4WD 16,789 $22,835 

FMC Ford F150 4x2 108,687 $22,520 

FMC Ford F150 4x4 35,368 $25,935 

GMC Chevrolet C1500 Silverado 2WD 72,250 $24,184 

GMC Chevrolet K1500 Silverado 4WD 150,295 $27,134 

GMC GMC C1500 Sierra 2WD 22,782 $21,868 

GMC GMC K1500 Sierra 4WD 44,469 $26,435 

Nissan Nissan Titan 4x2 40,000 $24,000 

Nissan Nissan Titan 4x4 22,000 $26,500 

Toyota Toyota Toyota Tundra 2WD 42,344 $22,975 

DCC Mer-Benz ML 320 30,686 $37,595 

Toyota Toyota Land Cruiser Wagon 4 6,331 $52,595 

VWA Audi Allroad Quattro 4,463 $40,950 

Makes, Models, Configurations of Hybrid and Diesel Light-Duty Vehicles 

Assumed to be Available in 2012 “Best Guess” Scenario 

2012 Hybrid Cars and Trucks 

Manufacturer Division Name 

2002 

Sales 

2002 

Price 

Hybrid 

Type 

DCC Mer-Benz A-Class 24,000 $22,500 ISAD 

FMC Ford Escort 40,921 $15,015 SS 

GMC Chevy Cavalier 210,244 $15,890 SS 

Honda Acura RSX 16,507 $21,850 IMA 

Honda Honda Civic ex 540 $14,860 IMA 

Honda Honda Civic ex 960 $13,860 IMA 

Nissan Nissan New Model 12,000 $11,750 SS 

Nissan Nissan New Model 28,000 $12,650 SS 

Toyota Toyota Echo 9,229 $11,780 SS 

Toyota Toyota Echo 23,266 $11,385 SS 

VWA VWA Jetta 47,846 $18,775 ISAD 

VWA VWA Jetta Wagon 5,605 $19,575 ISAD 

BMW BMW 325i 30,738 $29,425 ISAD 

DCC Dodge Neon 103,205 $15,090 ISAD 

DCC Dodge Neon 16,048 $15,915 ISAD 

FMC Ford Focus 83,424 $16,050 SS 

FMC Ford Focus 95,367 $16,050 SS 

FMC Ford Focus Wagon 33,265 $17,565 SS 

FMC Volvo S60 20,570 $27,125 FULL 

GMC Pontiac Grand Am 2,059 $18,465 SS 

GMC Pontiac Grand Am 67,168 $19,290 SS 

GMC Saturn L100/200 63,071 $19,065 SS 

GMC Saturn LW200 5,552 $20,130 SS 

GMC Saturn LW200 364 $19,270 SS 

Honda Acura Acura 3.2TL 60,860 $28,880 IMA 
70 

Manufacturer Division Name Sales Price 

Hybrid 

Type 

Honda Honda Civic dx 4Dr 107,863 $14,060 IMA 

Suzuki Suzuki Aerio 7,529 $14,491 SS 

Suzuki Suzuki Aerio 1,652 $13,571 SS 

Suzuki Suzuki Aerio SX 1,229 $13,847 SS 

Suzuki Suzuki Aerio SX 3,256 $14,767 SS 

Toyota Lexus ES 300 70,517 $33,055 FULL 

Toyota Toyota Camry Solara 12,719 $22,485 FULL 

Toyota Toyota Prius 22,737 $19,995 FULL 

VWA Audi Audi A4 1,174 $33,190 ISAD 

DCC Chrysler 300 M 36,663 $28,415 FULL 

DCC Chrysler Concorde 14,548 $22,510 FULL 

DCC Dodge Intrepid 91,428 $20,520 FULL 

FMC Ford Taurus 54,537 $22,445 FULL 

FMC Ford Taurus Wagon 9,942 $21,495 FULL 

FMC Lincoln Lincoln LS 12,363 $33,220 FULL 

FMC Mazda 626 35,363 $19,525 FULL 

FMC Mazda 626 12,787 $22,425 FULL 

FMC Mercury Sable 59,858 $20,020 FULL 

FMC Mercury Sable Wagon 4,201 $23,560 FULL 

GMC Buick LaSabre 137,737 $24,495 FULL 

GMC Chevy Impala 118,204 $20,540 FULL 

GMC Chevy Malibu 144,946 $19,855 SS 

GMC Pontiac Bonneville 37,343 $28,890 FULL 

Honda Honda Accord 122,800 $25,300 IMA 

Hyundai Hyundai Sonata 49,666 $18,824 FULL 

Mitsubishi Mitsubishi Galant 80,656 $18,517 Y 

Nissan Nissan Altima 146,503 $18,849 FULL 

Nissan Nissan Maxima 79,206 $25,449 FULL 

Toyota Toyota Camry 93,460 $23,700 FULL 

VWA VWA Passat 8,167 $21,750 ISAD 

VWA VWA Passat 14,544 $25,325 ISAD 

VWA VWA Passat Wagon 8,379 $23,625 ISAD 

BMW BMW 525i 12,579 $38,275 ISAD 

DCC Mer-Benz C320 12,483 $38,135 FULL 

DCC Mer-Benz E 320 14,749 $48,450 FULL 

DCC Mer-Benz S 430 14,919 $71,850 FULL 

FMC Volvo S80 10,790 $38,450 FULL 

GMC Cadillac Seville 25,128 $44,039 FULL 

Toyota Lexus LS 430 27,162 $54,405 FULL 

VWA Audi Audi A6 2,529 $36,400 ISAD 

VWA Audi Audi A6 Avant 2,148 $39,350 ISAD 

DCC Chrysler Town & Country 2WD 69,325 $26,240 FULL 

DCC Dodge Grand Caravan 2WD 23,583 $24,950 FULL 

FMC Ford Windstar Van 18,364 $20,250 FULL 

FMC Ford Windstar Wagon 4,232 $28,625 FULL 

FMC Mercury Villager Wagon 142,042 $24,340 FULL 

Honda Honda Odyssey 148,857 $26,750 IMA 

Nissan Nissan Quest 21,099 $27,194 FULL 

Toyota Toyota Sienna 85,417 $28,012 FULL 

DCC Chrysler PT Cruiser 22,197 $17,990 SS 

DCC Chrysler PT Cruiser 147,362 $18,815 SS 

DCC Chrysler Pacifica 40,000 $28,845 FULL 

DCC Chrysler Pacifica 20,000 $32,300 FULL 

DCC Jeep Grand Cherokee 2WD 39,048 $25,425 FULL 

DCC Jeep Grand Cherokee 4WD 91,965 $27,395 FULL 

FMC Ford Escape 4x2 67,376 $22,075 FULL 
71 

Manufacturer Division Name 

2002 

Sales 

2002 

Price 

Hybrid 

Type 

GMC Chevrolet Blazer 2WD 1,394 $25,005 SS 

GMC Chevrolet Blazer 2WD 36,159 $26,005 SS 

GMC Chevrolet Blazer 4WD 437 $27,005 SS 

GMC Chevrolet Blazer 4WD 65,351 $28,005 SS 

GMC Chevrolet Trailblazer 2WD 87,430 $28,840 FULL 

GMC Chevrolet Trailblazer 4WD 165,819 $31,065 FULL 

GMC GMC Envoy 2WD 30,715 $31,935 FULL 

GMC GMC Envoy 4WD 77,935 $34,160 FULL 

GMC Saturn Vue AWD 1,052 $18,860 SS 

GMC Saturn Vue FWD 717 $17,265 SS 

Honda Honda Pilot 80,000 $29,470 IMA 

Honda Honda CR-V 29,053 $19,050 IMA 

Honda Honda CR-V 99,884 $20,250 IMA 

TKM Mazda Tribute 4x2 22,249 $21,485 FULL 

TKM Mazda Tribute 4x4 24,854 $22,685 FULL 

Toyota Toyota Highlander 2WD 42,567 $25,460 FULL 

Toyota Toyota Rav4 2WD 48,231 $17,575 FULL 

Toyota Toyota Rav4 4WD 39,291 $18,975 FULL 

GMC Chevrolet C1500 Tahoe 2WD 61,519 $33,409 FULL 

GMC GMC C1500 Yukon 2WD 7,193 $33,596 FULL 

GMC GMC K1500 Yukon 4WD 1,746 $34,996 FULL 

TKM Mazda Mazda B3000 4x2 7,231 $18,070 FULL 

FMC Ford EX SP Trac 4x2 40,864 $23,880 FULL 

FMC Ford EX SP Trac 4x4 30,725 $26,650 FULL 

GMC Chevrolet C1500 Silverado 2WD 85,182 $22,689 FULL 

GMC Chevrolet K1500 Silverado 4WD 35,847 $25,639 FULL 

GMC GMC C1500 Sierra 2WD 27,113 $21,068 FULL 

GMC GMC K1500 Sierra 4WD 9,917 $25,635 FULL 

BMW BMW X5 3.0 30,564 $41,225 FULL 

Honda Acura MDX 48,998 $37,300 IMA 

GMC Cadillac Escalade 2WD 10,692 $48,735 FULL 

GMC Cadillac Escalade AWD 43,311 $52,230 FULL 

GMC Chevrolet C1500Suburban 2WD 49,314 $36,143 FULL 

GMC Chevrolet K1500 Suburban 4WD 71,668 $38,209 FULL 

GMC Chevrolet K1500 Tahoe 4WD 5,017 $35,475 FULL 

GMC GMC C1500 Yukon XL 2WD 16,472 $36,501 FULL 

GMC GMC K1500 Yukon XL 4WD 22,731 $39,034 FULL 

2012 Diesel Cars and Trucks 

Manufacturer Division Name 

2002 

Sales 

2002 

Price 

DCC Mer-Benz A-Class 24,000 $22,500 

VWA VWA Golf 3,255 $15,250 

VWA VWA Golf TDI 1,655 $17,420 

VWA VWA Golf TDI 6,025 $16,545 

VWA VWA Jetta 7,133 $18,950 

VWA VWA Jetta 11,326 $20,135 

VWA VWA Jetta 1,102 $24,700 

VWA VWA Jetta Wagon 340 $21,000 

VWA VWA New Beetle 4,766 $18,775 

DCC Mer-Benz C240 33,611 $31,735 

VWA Audi Audi A4 1,174 $33,190 
72 

Manufacturer Division Name 

2002 

Sales 

2002 

Price 

VWA VWA Passat 8,167 $21,750 

VWA VWA Passat Wagon 8,379 $23,625 

VWA VWA Passat Wagon 695 $25,050 

BMW BMW 525i 12,579 $38,275 

BMW BMW 745i 10,575 $67,850 

DCC Mer-Benz C320 12,483 $38,135 

DCC Mer-Benz E 320 14,749 $48,450 

DCC Mer-Benz S 430 14,919 $71,850 

FMC Jaguar Jaguar S-Type 6 8,033 $43,675 

VWA Audi Audi A6 2,529 $36,400 

VWA Audi Audi A6 1,412 $50,650 

VWA Audi Audi A6 Avant 2,148 $39,350 

DCC Dodge Durango 2WD 16,800 $29,320 

DCC Dodge Durango 4WD 33,133 $31,440 

DCC Jeep Liberty 2WD 46,124 $22,994 

DCC Jeep Liberty 4WD 157,615 $24,479 

DCC Jeep Wrangler 25,831 $19,860 

FMC Ford Explorer 4x2 125,415 $29,190 

FMC Ford Explorer 4x4 217,575 $31,155 

FMC Mercury Mountaineer 4x2 7,070 $29,645 

FMC Mercury Mountaineer 4x4 27,422 $31,645 

Isuzu Isuzu Trooper 7,917 $29,405 

Nissan Nissan Pathfinder 2WD 15,861 $28,999 

Nissan Nissan Pathfinder 4WD 38,712 $32,499 

Nissan Nissan Xterra V6 2WD 40,628 $24,199 

Nissan Nissan Xterra V6 4WD 1,684 $26,449 

Nissan Nissan Xterra V6 4WD 34,714 $26,199 

FMC Ford Expedition 4x2 32,851 $30,430 

FMC Ford Expedition 4x4 4,096 $33,300 

GMC Chevrolet C1500 Tahoe 2WD 14,214 $32,709 

GMC Chevrolet K1500 Tahoe 4WD 97,036 $27,857 

GMC GMC C1500 Yukon 2WD 16,240 $34,296 

GMC GMC K1500 Yukon 4WD 24,313 $34,996 

DCC Dodge Dakota 2WD 43,412 $19,625 

DCC Dodge Dakota 4WD 16,789 $22,835 

DCC Dodge Ram 1500 2WD 114,196 $19,990 

DCC Dodge Ram 1500 4WD 55,866 $22,730 

FMC Ford F150 4x2 108,687 $22,520 

FMC Ford F150 4x4 35,368 $25,935 

GMC Chevrolet C1500 Silverado 2WD 72,250 $24,184 

GMC Chevrolet K1500 Silverado 4WD 150,295 27,134 

GMC GMC C1500 Sierra 2WD 22,782 $21,868 

GMC GMC K1500 Sierra 4WD 44,469 $26,435 

Nissan Nissan Titan 40,000 

Nissan Nissan Titan 22,000 

Toyota Toyota Toyota Tundra 2WD 42,344 $22,975 

BMW BMW X5 4.4 8,246 $50,420 

DCC Mer-Benz ML 320 30,686 $37,595 

FMC Lincoln Navigator 4x2 9,367 $44,590 

FMC Lincoln Navigator 4x4 8,517 $48,340 

FMC Rover Range Rover 4.6 3,927 $68,000 

GMC Chevrolet C1500 Suburban 2WD 49,314 $36,143 

GMC Chevrolet K1500 Suburban 4WD 71,668 $38,209 

GMC GMC K1500 Yukon XL 4WD 22,731 $39,034 

Mitsubishi Mitsubishi Montero 17,461 $35,897 

Nissan Infiniti Infiniti QX4 2WD 4,018 $35,150 
73 

Manufacturer Division Name 

2002 

Sales 

2002 

Price 

Nissan Infiniti Infiniti QX4 4WD 11,925 $36,550 

Nissan Nissan Armada 15,000 $36,450 

Nissan Nissan Armada 25,000 $39,250 

Toyota Toyota Land Cruiser Wagon 4 6,331 $52,595 

Toyota Toyota Sequoia 2WD 41,737 $39,405 

Toyota Toyota Sequoia 4WD 38,158 $42,752 

VWA Audi Allroad Quattro 4,463 $40,950 

FMC Ford E150 Van 20,688 $21,430 

APPENDIX C 

CHARACTERISTICS OF DIESEL AND HYBRID PRODUCT LINES FOR 

WHICH THERE IS NO MODEL YEAR 2002 COUNTERPART 

77 

Table C1. Characteristics of Diesel and Hybrid Product Lines for which there is No Model Year 200

 

Manufacturer Division Name Class Sales 

Price 

(2002$) 

Composite 

MPG 

Torque 

Nm 

Tank 

Size 

(gals.) 

Hybri

Type 

DCC Mer-Benz A-Class Mini & subcompact 24,000 $22,500 34.8 205.0 14.0 Nissan Nissan New Mini& subcompact 12,000 $11,750 37.8 175.0 13.2 Stop-staNissan Nissan New Mini & subcompact 28,000 $12,650 37.0 175.0 13.2 Stop-staDCC Chrysler Pacifica Small SUV 40,000 $28,845 340.0 20.0 Full DCC Chrysler Pacifica Small SUV 20,000 $32,300 340.0 20.0 Full Honda Honda Pilot Small SUV 80,000 $29,470 22.5 332.2 19.2 IMA Nissan Nissan Titan 4 x 2 Large Pickup 40,000 $24,000 18.4 500.0 24.0 Nissan Nissan Titan 4 x 4 Large Pickup 22,000 $26,500 18.0 500.0 24.0 Nissan Nissan Armada Luxury Truck 15,000 $36,450 18.4 500.0 24.0 Nissan Nissan Armada Luxury Truck 25,000 $39,250 18.0 500.0 24.0