From: "Achanta, Chandana L." <Chandana_L._Achanta@omb.eop.gov> 

To: William Charmley/AA/USEPA/US@EPA, <james.tamm@dot.gov>, 

<Steve.Wood@dot.gov>, Robin Moran/AA/USEPA/US@EPA, <rebecca.yoon@dot.gov>, 

<Neil.Eisner@dot.gov>, Maureen Delaney/DC/USEPA/US@EPA, 

<Joanne.Petrie@dot.gov> 

Date: 03/24/2010 02:10 PM 

Subjec

t: 

Summary of Interagency working comments on draft rule under EO 12866 review 

  

Please find attached two documents summarizing interagency working comments 

received on the draft final rule under EO 12866 review. They are subject to further policy 

review. 

Please provide responses to these interagency comments by 12 noon tomorrow 

Thursday, March 25th. 

 

Thanks. 

[attachment "Summary of Interagency Working Comments of draft final rule under EO

128663.24.2010.pdf" deleted by Tad Wysor/AA/USEPA/US] [attachment "CONT Summary of

Interagency working comments of draft final rule under EO 12866 3.24.2010.pdf" deleted by

Tad Wysor/AA/USEPA/US]  
Summary of Interagency Working Comments on Draft Rule under EO 12866 

1 

Below is a summary of interagency comments received during EO 12866 review of the 

draft rule “Joint Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emission 

Standards and Corporate Average Fuel Economy Standards”. They are for your 

consideration and subject to further policy review. 

General Comments: 

 The TSD discussion of rebound effect does not clearly explain where the agencies 

got the 10% from. The studies cited use higher means and the range is from 6% to 

22% percent or higher. Is 10% a mean, a weighted average, or a point estimate 

from a particular study that you cited? Please explain the basis for using 10% as a 

point estimate. 

 NHTSA’s RIA has the following discussion about the ICM values on page 181. 

We recommend you include this paragraph in the Preamble discussion of ICM as 

well. 

“One of the sensitivity analyses performed by NHTSA for this final rule was to 

evaluate the effects of using the Retail Price Equivalent (RPE) 

multiplier employed in the MY 2011 CAFE final rule and in other NHTSA 

rulemakings, instead of using the Indirect Cost Multiplier (ICM) developed for 

this rulemaking. The RPE methodology multiplies variable costs by 1.5 to 

estimate consumer costs. The 1.5 multiplier is a general increase that is applied 

consistently to every technology and consists of fixed costs and profits for the 

manufacturer and automobile dealers. The indirect cost multiplier is estimated 

depending upon the complexity of the technology and in the aggregate for the 

technologies utilized in the model results in a multiplier in the 1.2 to 1.25 range 

and does not include profits. The sensitivity analysis indicates that using the 1.5 

RPE multiplier would result in noticeably higher costs compared to the final rule 

costs incorporating the ICM multiplier, although we note that even with those 

higher costs the 1.5 RPE analysis still resulted in significant net benefits for the 

rulemaking as a whole[1]. The agency plans to investigate this issue further for 

future rulemakings.” 

Safety Discussion in Preamble 

1) Please include a section explicitly discussing safety impacts of the flat spot below 

41 sq ft. Also, we recommend pointing out that the footprint-based curves were 

developed to discourage upsizing at the higher end of the distribution by 

flattening out the curve. But there could be adverse safety impacts from flattening 

out near the lower end of the curve. 

2) Please revise text to be more cognizant of the role that the size distribution of 

vehicles on the road plays. Safety of a given vehicle is not entirely independent of 

the overall distribution. 

 

[1] See Section X. below for the results of the sensitivity analyses. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

2 

3) Care should be taken to not overstate the historical relationship between safety 

and CAFÉ. Not all NAS panelists were in accord on this point. 

4) Safety should be more carefully defined. It gets used in multiple ways in the text 

and so it becomes difficult to understand if the text is referring to occupant safety 

for one or both cars as well as non-vehicle individuals that might be involved in a 

crash (pedestrians, cyclists, etc.). 

5) The Kahane study’s methodology could be more carefully described in the text. 

The text should also mention whether this study has been peer-reviewed. 

6) Please explain more in detail how the revised Kahane study addressed 

multicollinearity. The one-step technique nor the use of historical data address 

this issue. One part of the document seems to acknowledge this, but others do not 

and seem to assert the opposite. 

7) Please clarify that the discussion and study of safety does not account for the 

effect of CAFÉ on the proportion of cars vs. trucks on the road and the effect this 

may have on safety. 

8) around pg. 23 where NHTSA explains that it is now presenting three scenarios: 

“Instead, we present three scenarios: the first is an estimate based directly 

on the regression coefficients of weight reduction while maintaining 

footprint in the statistical analyses of historical data. As discussed above, 

presenting this scenario is possible because NHTSA was able to separate 

the effects of weight and footprint reduction in the new analysis. 

However, even the new analysis of LTVs produced some coefficients that 

NHTSA did not consider entirely plausible. NHTSA also presents an 

“upper estimate” in which those coefficients for the LTVs were adjusted 

based on additional analyses and expert opinion as a safety agency and a 

“lower estimate,” which estimates the effect if mass reduction is 

accomplished entirely by safety-conscious technologies such as material 

substitution.” 

There is a long discussion prior to this about the relative merits of the Kahane and 

DRA studies, but then in the end the coefficients that you use for their upper 

estimate is based on “additional analyses and expert opinion as a safety agency.” 

Please explain in detail how you chose the adjust those coefficients. 

9) Page. 6 states that mass reduction could be achieved through various means, 

including “reduced powertrain requirements.” So does this mean that 

performance is not actually held constant in analyzing impacts of this rule? 

10) Has EPA and NHTSA considered the potential for the footprint-based standard to 

encourage vehicle manufacturers to “upsize” (i.e., shift to manufacturing of 

larger-footprint vehicles to be subject to a less stringent standard) in response to 

the regulation? What would the potential fleetwide safety impacts be if there is 

some shift in vehicle footprint towards upsized vehicles? 

11) There are arguments in the document on how advanced materials may contribute 

to weight reductions without degrading performance standards. Are current 

simulation methods able to factor in material substitutions to better understand the 

maximum potential for mass reduction? If so, why not consider these 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

3 

predictions now in addition to the statistical approaches described in the 

document? For example, on page 26 it is noted that “using material substitution 

and other current mass reduction methods could avoid the historical trend in this 

area, but that remains to be studied as manufacturers introduce more of these 

vehicles into the on-road fleet in coming years”. Surely, simulation and modeling 

efforts can likely help address such questions now. 

12) Page 2 ¶2 line 13: It is noted an “unmodified regression scenario” is part of the 

new report. The later sections of this paragraph and the following paragraphs 

summarize the “upper-estimate scenario” and the “lower-estimate scenario” but 

do not mention the regression scenario. It would be useful to describe the 

scenario here, or note to see Section 3 and the table on page 28. The Table on 

page 28 refers to an “Actual Regression Result Scenario” rather than an 

“unmodified regression scenario”. We suggest the text on Page 2 match what is 

in the Table. 

13) Page 5 ¶ 1 line 8: It is noted changes are predicted to take place in passenger car 

and light truck safety and it’s not clear if these changes are those noted in 

Footnote 7 or are other changes expected. In addition, the multiplying factor 

suggests that 87.4% of the fleet will experience these changes by 2020. Is this the 

case? What is the basis for such a large change? 

14) Page 7 ¶ 1 last sentence: It is stated there were no overly-biasing effects noted in 

the regression analysis of historical data that included 2-door cars. Could an 

examination of the residuals lead to a different conclusion of no effects? 

15) Page 26 bottom¶: It is noted the CAFE standard lacks language that requires 

manufacturers to take a “safety-conscious approach to mass reduction”. What is 

the basis for not requiring manufacturers to be safety-conscious? 

16) Page 28 Table on percent fatality increase per 100-pound reduction: As 

regression results are presented, it would be helpful to present the correlation 

coefficients, particularly since for passenger cars the upper-estimate scenario is 

the actual regression result. 

17) If Kahane’s 2010 report has not been peer reviewed yet, we recommend that the 

agencies include the following caveat where it is first introduced: 

“Please note that this report has not been peer reviewed. Hence, the agencies are 

not relying on it for decision-making purposes at this point. The results of this 

study do not affect the stringency of the standards in this final rule. Since the 

study has not been peer reviewed, it also does not represent official agency 

position. NHTSA is planning a peer review of the analysis, and will ensure that 

concerns raised during this process will be addressed before relying on the report 

for future rulemakings.” 

*** 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

4 

G. What are the estimated safety effects of the final MYs 2012-2016 

CAFE and GHG standards? 

The primary goals of the final CAFE and GHG standards are to reduce fuel 

consumption and GHG emissions, but in addition to these intended effects, the agencies 

must consider the potential of the standards to affect vehicle safety, which the agencies 

have assessed in evaluating the appropriate levels at which to set the final standards. 

Safety trade-offs associated with fuel economy increases have occurred in the past, and 

the agencies must be mindful of the possibility of future ones. These past safety tradeoffs occurred because manufacturers chose, at the time, to build smaller and lighter 

vehicles – partly in response to CAFE standards - rather than adding more expensive 

fuel-saving technologies (and maintaining vehicle size and safety), and the smaller and 

lighter vehicles did not fare as well in crashes as larger and heavier vehicles. 

Historically, as shown in FARS data analyzed by NHTSA, the safest vehicles have been 

heavy and large, while the vehicles with the highest fatal-crash rates have been light and 

small, both because the crash rate is higher for small/light vehicles and because the 

fatality rate per crash is higher for small/light vehicle crashes. 

Changes in relative safety are related to shifts in the distribution of vehicles on the 

road. A policy that induces a widening in the size distribution of vehicles on the road, 

could result in negative impacts on safety, The primary mechanism in this rulemaking 

for mitigating the potential negative effects on safety is the application of footprint-based 

standards, which create a disincentive for manufacturers to produce smaller-footprint 

vehicles. Also, as recommended by the NAS, the footprint-based curves flatten out for 

larger-footprint vehicles to avoid giving an incentive to upsizing. 

Manufacturers have stated, however, that they will reduce vehicle weight as one 

of the cost-effective means of increasing fuel economy and reducing CO2 emissions, and 

the agencies have incorporated this expectation into our modeling analysis supporting 

today’s final standards. NHTSA’s previous analyses examining the relationship between 

vehicle mass and fatalities found fatality increases as vehicle weight and size were 

reduced, but these previous analyses did not differentiate between weight reductions and 

size (i.e., weight and footprint) reductions. 

The question of the effect of changes in vehicle mass on safety in the context of 

fuel economy is a complex question that poses serious analytic challenges and has been a 

contentious issue for many years, as discussed by a number of commenters to the NPRM. 

This contentiousness arises, at least in part, from the difficulty of isolating vehicle mass 

from other confounding factors (e.g., driver behavior, or vehicle factors such as engine 

size and wheelbase). In addition, several vehicle factors have been closely related 

historically, such as vehicle mass, wheelbase, and track width. The issue has been 

reviewed and analyzed in the literature for more than two decades. For the reader’s 

reference, much more information about safety in the CAFE context is available in 

Chapter IX of NHTSA’s FRIA. Chapter 7.6 of EPA’s final RIA also contained 

additional discussion on mass and safety. 

Comment [A1]: It is difficult to isolate the effects 

of CAFÉ from changes in fuel prices. 

Please add citation and time period. Is this from the 

NAS report for the 1970s? 

Not everyone on the NAS panel agreed that these 

trade-offs were caused by CAFÉ, another reason to 

add the word “partly.”

Comment [A2]: How is safety defined here? To 

the vehicle occupants? To other vehicle occupants? 

To pedestrians and cyclists? On net? Please be more 

specific. I find it hard to believe that heavier, larger 

vehicles are universally safer for everyone. 

Comment [A3]: There is a strange focus on only 

one end of the distribution, but my recollection is 

that the NAS talked about flattening the curve out to 

prevent upsizing as well.

Comment [A4]: Is there reason to believe or 

evidence indicating that it has changed? 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

5 

Over the past several years, as also discussed by a number of commenters to the 

NPRM, contention has arisen with regard to the applicability of analysis of historical 

crash data to future safety effects due to mass reduction. The agencies recognize that 

there are a host of factors that may make future mass reduction different than what is 

reflected in the historical data. For one, the footprint-based standards have been carefully 

developed by the agencies so that they do not encourage vehicle footprint reductions as a 

way of meeting the standards, but so that they do encourage application of fuel-saving 

technologies, including mass reduction. This in turn encourages manufacturers to find 

ways to separate mass reduction from footprint reduction, which will very likely result in 

a future relationship between mass and fatalities that is safer than the historical 

relationship. However, as manufacturers pursue these methods of mass reduction, the 

fleet moves further away from the historical trends, which the agencies recognize. 

NHTSA’s NPRM analysis of the safety effects of the proposed CAFE standards 

was based on NHTSA’s 2003 report concerning mass and size reduction in MYs 1991-

1999 vehicles, and evaluated a “worst-case scenario” in which the safety effects of the 

combined reductions of both mass and size for those vehicles were determined for the 

future passenger car and light truck fleets.1

 In the NPRM analysis, mass and size could 

not be separated from one another, resulting in what NHTSA recognized was a larger 

safety disbenefit than was likely under the MYs 2012-2016 footprint-based CAFE 

standards. NHTSA emphasized, however, that actual fatalities would likely be less than 

these “worst-case” estimates, and possibly significantly less, based on the various factors 

discussed in the NPRM that could reduce the estimates, such as careful mass reduction 

through material substitution, etc. 

For the final rule, as discussed in the NPRM and in recognition of the importance 

of conducting analysis that better reflects, within the limits of our current knowledge, the 

potential safety effects of future mass reduction in response to the final CAFE and GHG 

standards that is highly unlikely to involve concurrent reductions in footprint, NHTSA 

has revised its analysis in consultation with EPA. Perhaps the most important change has 

been that NHTSA agreed with commenters that it was both possible and appropriate to 

separate the effect of mass reductions from the effect of footprint reductions. NHTSA 

thus performed a new statistical analysis, hereafter referred to as the 2010 Kahane 

analysis, of the MYs 1991-99 vehicle database from its 2003 report (now including rather 

than excluding 2-door cars in the passenger car fleet), assessing relationships between 

fatality risk, mass, and footprint for both passenger cars and LTVs (light trucks and 

vans).2 As part of its results, the new report presents an “upper-estimate scenario,” a 

“lower-estimate scenario,” as well as an “unmodified regression scenario” representing 

potential safety effects of future mass reductions without corresponding vehicle size 

reductions, that assume, by virtue of being a cross-sectional analysis of historical data, 

 

1

 The analysis excluded 2-door cars. 

2

 “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 1991-1999 and Other 

Passenger Cars and LTVs,” Charles J. Kahane, NCSA, NHTSA, March 2010, available at Docket No. 

NHTSA-2009-0059-[item no.]. We note that this report has not yet been externally peer-reviewed, but that 

NHTSA had begun the process for peer review in accordance with OMB guidance by the time of 

publication of this final rule. The results of the peer review and any subsequent revisions to the report will 

be made available in a public docket and on NHTSA’s website as they are completed. 

Comment [A5]: What is the basis for this claim? 

Especially if we don’t know what effect of mass 

alone was in the past? NHTSA does not know what 

this historical relationship has been. 

Comment [A6]: Also does notapply to < 41 sq on 

flat part of the curve. 

Comment [A7]: Has this been peer-reviewed? 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

6 

that historical relationships between vehicle mass and fatalities are maintained. The 

“upper-estimate scenario” and “lower-estimate scenario” are based on NHTSA’s 

judgment as a vehicle safety agency, and are not meant to convey any more or less 

likelihood in the results, but more to convey a sense of bounding for potential safety 

effects of reducing mass while holding footprint constant. The upper-estimate scenario 

reflects potential safety effects given the report’s finding that that, using the one-step 

regression method of the 2003 Kahane report, the regression coefficients show that mass 

and footprint each accounted for about half the fatality increase associated with 

downsizing in a cross-sectional analysis of MYs 1991-1999 cars. A similar effect was 

found for lighter LTVs. Applying the same regression method to heavier LTVs, 

however, the coefficients indicated a significant societal fatality reduction when mass, 

but not footprint, is reduced in the heavier LTVs.3 Fatalities are reduced primarily 

because mass reduction in the heavier LTVs will reduce risk to occupants of the other 

cars and lighter LTVs involved in collisions with these heavier LTVs.4 Thus, even in the 

“upper-estimate scenario,” the potential fatality increases associated with mass reduction 

in the passenger cars would be to a large extent offset by the benefits of mass reduction in 

the heavier LTVs. 

The lower-estimate scenario, in turn, reflects NHTSA’s estimate of potential 

safety effects if future mass reduction is accomplished entirely by things likethrough

material substitution, smart design,5 and component integration, among other things, that 

can reduce mass without perceptibly changing a vehicle’s shape, functionality, or safety 

performance, maintaining structural strength without compromising other aspects of 

safety. If future mass reduction follows this path, it could limit the added risk close to 

only the effects of mass per se (the ability to transfer momentum to other vehicles or 

objects in a collision), resulting in estimated effects in passenger cars that are 

substantially smaller than in the upper-estimate scenario based directly on the regression 

results. The lower-estimate scenario also covers both passenger cars and LTVs. 

Overall, based on the new analyses, NHTSA estimated that fatality effects could 

be markedly less than those estimated in the “worst-case scenario” presented in the 

NPRM. The agencies believe that the overall effect of mass reduction in cars and LTVs 

 

3

 Conversely, the coefficients indicate a significant increase if footprint is reduced. 4

 We note that there may be some (currently non-quantifiable) welfare losses for purchasers of these 

heavier LTVs, the mass of which is reduced in response to these final standards. This is due to the fact that 

in certain crashes, as discussed below and in greater detail in Chapter IX of the NHTSA FRIA, more mass 

will always be helpful (although certainly in other crashes, the amount of mass reduction modeled by the 

agency will not be enough to have any significant effect on driver/occupant safety). However, we believe 

the effects of this will likely be minor. Consumer welfare impacts of the final rule are discussed in more 

detail in Chapter VIII of the NHTSA FRIA. 5 (is mass reduction necessary? I.e. can CAE be used to improve safety while reducing 

mass?)Manufacturers implement smart design through computer aided engineering (CAE) tools that can be 

used to better optimize load paths within structures by reducing stresses and bending moments applied to 

structures. This allows better optimization of the sectional thicknesses of structural components to reduce 

mass while maintaining or improving the function of the component. Smart designs also integrate separate 

parts in a manner that reduces mass by combining functions or the reduced use of separate fasteners. In 

addition, some “body on frame” vehicles are redesigned with a lighter “unibody” construction. 

 

Comment [A8]: Please insert this important 

point. 

Comment [A9]: You should make explicit that 

any observations about the effects of the footprintbased curves on safety are predicated on fuel 

economy standards not shifting the relative number 

of cars vs. trucks on the road. 

EIA’s AEO 2010 indicates that there is an 

expectation that 2012-2016 CAFÉ will result in 

fewer cars and more trucks on the road, however. 

There may be safety impacts associated with this 

shift that are not analyzed here. 

Comment [A10]: Why doesn’t logic of footnote 

#11 and #13 apply here too?
Summary of Interagency Working Comments on Draft Rule under EO 12866 

7 

may be close to zero, and may possibly be beneficial in terms of the fleet as a whole if 

mass reduction is carefully applied in the future (as with careful material substitution and 

other methods of mass reduction that can reduce mass without perceptibly changing a 

car’s shape, functionality, or safety performance, and maintain its structural strength 

without making it excessively rigid). This is especially important if the mass reduction in 

the heavier LTVs is greater (in absolute terms) than in passenger cars, as discussed 

further below and in the 2010 Kahane report. 

The following sections will address how the agencies addressed potential safety 

effects in the NPRM for the proposed standards, how commenters responded, and the 

work that NHTSA has done since the NPRM to revise its estimates of potential safety 

effects for the final rule. The final section discusses some of the agencies’ plans for the 

future with respect to potential analysis and studies to further enhance our understanding 

of this important and complex issue. 

1. What did the agencies say in the NPRM with regard to potential 

safety effects? 

In the NPRM preceding these final standards, NHTSA’s safety assessment 

derived from the agency’s belief that some of these vehicle factors, namely vehicle mass 

and footprint, could not be accurately separated. NHTSA relied on the 2003 study by Dr. 

Charles Kahane, which estimates the effect of 100-pound reductions in MYs 1991-1999 

heavy light trucks and vans (LTVs), light LTVs, heavy passenger cars, and light 

passenger cars.6

 The study compares the fatality rates of LTVs and cars to quantify 

differences between vehicle types, given drivers of the same age/gender, etc. In that 

analysis, the effect of “weight reduction” is not limited to the effect of mass per se, but 

includes all the factors, such as length, width, structural strength, safety features, and size 

of the occupant compartment, that were naturally or historically confounded with mass in 

MYs 1991-1999 vehicles. The rationale was that adding length, width, or strength to a 

vehicle historically also made it heavier. 

NHTSA utilized the relationships between mass and safety from Kahane (2003), 

expressed as percentage increases in fatalities per 100-pound mass reduction, and 

examined the mass effects assumed in the NPRM modeling analysis. While previous 

CAFE rulemakings had limited mass reduction as a “technology option” to vehicles over 

5,000 pounds GVWR, both NHTSA’s and EPA’s modeling analyses in the NPRM 

included mass reduction of up to 5-10 percent of baseline curb weight, depending on 

vehicle subclass, in response to recently-submitted manufacturer product plans as well as 

public statements indicating that these levels were possible and likely. 5-10 percent 

represented a maximum bound; EPA’s modeling, for example, included average vehicle 

weight reductions of 4 percent between MYs 2011 and 2016, although the average pervehicle mass reduction was greater in absolute terms for light trucks than for passenger 

cars. NHTSA’s assumptions for mass reduction were also limited by lead time such that 

 

6

 Kahane, Charles J., Ph.D., “Vehicle Weight, Fatality Risk and Crash Compatibility of Model Year 1991-

99 Passenger Cars and Light Trucks,” DOT HS 809 662, October 2003, Executive Summary. Available at

http://www.nhtsa.dot.gov/cars/rules/regrev/evaluate/809662.html (last accessed March 10, 2010). 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

8 

mass reductions of 1.5 percent were included for redesigns occurring prior to MY 2014, 

and mass reductions of 5-10 percent were only “achievable” in redesigns occurring in 

MY 2014 or later. NHTSA further assumed that mass reductions would be limited to 5 

percent for small vehicles (e.g., subcompact passenger cars), and that reductions of 10 

percent would only be applied to the larger vehicle types (e.g., large light trucks). 

Based on these assumptions of how manufacturers might comply with the 

standards, NHTSA examined the effects of the identifiable safety trends over the lifetime 

of the vehicles produced in each model year. The effects were estimated on a year-byyear basis, assuming that certain known safety trends would result in a reduction in the 

target population of fatalities from which the mass effects are derived.7

 Using this 

method, NHTSA found a 12.6 percent reduction in fatality levels between 2007 and 

2020. The estimates derived from applying Kahane’s 2003 percentages to a baseline of 

2007 fatalities were then multiplied by 0.874 to account for changes that the agency 

believed would take place in passenger car and light truck safety between the 2007 

baseline on-road fleet used for that particular analysis and year 2020. 

NHTSA and EPA both emphasized that the safety effect estimates in the NPRM 

needed to be understood in the context of the 2003 Kahane report, which is based upon a 

cross-sectional analysis of the actual on-road safety experience of 1991-1999 vehicles. 

For those vehicles, heavier usually also meant larger-footprint. Hence, the numbers in 

those analyses were used to predict the safety-related fatalities that could occur in the 

unlikely event that weight reduction for MYs 2012-2016 is accomplished entirely by 

reducing mass and reducing footprint. Any estimates derived from those analyses 

represented a “worst-case” estimate of safety effects, for several reasons. 

 First, manufacturers are far less likely to reduce mass by “downsizing” (making 

vehicles smaller overall) under the current attribute-based standards, because the 

standards are based on vehicle footprint. The selection of footprint as the attribute in 

setting CAFE and GHG standards helps to minimize reduce the incentive to reduce aalter 

a vehicle’s physical dimensions. This is because as footprint decreases, the 

corresponding fuel economy/GHG emission target becomes more stringent.8 Upsizing 

 

7

 NHTSA explained that there are several identifiable safety trends that are already in place or expected to 

occur in the foreseeable future and that were not accounted for in the study. For example, two important 

new safety standards that have already been issued and will be phasing in during the rulemaking time 

frame. Federal Motor Vehicle Safety Standard No. 126 (49 CFR 571.126) will require electronic stability 

control in all new vehicles by MY 2012, and the upgrade to Federal Motor Vehicle Safety Standard No. 

214 (Side Impact Protection, 49 CFR 571.214) will likely result in all new vehicles being equipped with 

head-curtain air bags by MY 2014.7

 Additionally, the agency stated that it anticipates continued 

improvements in driver (and passenger) behavior, such as higher safety belt use rates. All of these will 

tend to reduce the absolute number of fatalities resulting from mass reductions. Thus, while the percentage 

increases in Kahane (2003) was applied, the reduced base resulted in smaller absolute increases than those 

that were predicted in the 2003 report.

8

 We note, however, that vehicle footprint is not synonymous with vehicle size. Since the footprint is only 

that portion of the vehicle between the front and rear axles, footprint-based standards do not discourage 

downsizing the portions of a vehicle in front of the front axle and to the rear of the rear axle, or to other 

portions of the vehicle outside the wheels. The crush space provided by those portions of a vehicle can 

make important contributions to managing crash energy. NHTSA noted in the NPRM that at least one 

Comment [A11]: Please note that it is not 

applicable for <41. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

9 

also is discouraged through a flattening of the curve at larger footprints. Thus, the shape 

of the footprint curves themselves have also been designed to be approximately “footprint 

neutral” within the sloped portion of the functions – that is, to neither encourage 

manufacturers to increase the footprint of their fleets, nor to decrease it. For further 

discussion on these aspects of the standards, please see Section II.C above and Chapter 2 

of the joint TSD. However, as discussed in Sections III.H.1 and IV.G.6 below, the 

agencies acknowledge some uncertainty regarding how consumer purchases will change 

in response to the vehicles designed to meet the MYs 2012-2016 standards. This could 

potentially affect the mix of vehicles sold in the future, including the mass and footprint 

distribution. 

As a result, the agencies found it likely that a significant portion of the mass 

reduction in the MY 2012-2016 vehicles would be accomplished by strategies, such as 

material substitution, smart design, reduced powertrain requirements, and mass 

compounding, that have a lesser safety effect than the prevalent 1980s strategy of simply 

making the vehicles smaller. The agencies noted that to the extent that future mass 

reductions could be achieved by these methods—without any accompanying reduction in 

the size or structural strength of the vehicle—then the fatality increases associated with 

the mass reductions anticipated by the model as a result of the proposed standards could 

be significantly smaller than those in the worst-case scenario. 

However, even though the agencies recognized that these methods of mass 

reduction could be technologically feasible in the rulemaking time frame, and included 

them as such in our modeling analyses, the agencies diverged as to how potential safety 

effects accompanying such methods of mass reduction could be evaluated, particularly in 

relation to the worst-case scenario presented by NHTSA. NHTSA stated that it could not 

predict how much smaller those increases would be for any given mixture of mass 

reduction methods, since the data on the safety effects of mass reduction alone (without 

size reduction) was not available due to the low numbers of vehicles in the current onroad fleet that have utilized these technologies extensively. Further, to the extent that 

mass reductions were accomplished through use of light, high-strength materials, 

NHTSA emphasized that there would be significant additional costs that would need to 

be determined and accounted for than were reflected in the agency’s proposal. 

 Additionally, NHTSA emphasized that while it thought material substitution and 

other methods of mass reduction could considerably lessen the potential safety effects 

compared to the historical trend, NHTSA also stated that it did not believe the effects in 

passenger cars would be smaller than zero. EPA disagreed with this, and stated in the 

NPRM that the safety effects could very well be smaller than zero. Even though 

footprint-based standards discourage downsizing as a way of “balancing out” sales of 

larger/heavier vehicles, they do not discourage manufacturers from reducing crush space 

 manufacturer has confidentially indicated plans to reduce overhang as a way of reducing mass on some 

vehicles during the rulemaking time frame. Additionally, simply because footprint-based standards create 

no incentive to downsize vehicles, does not mean that manufacturers may not choose to do so if doing so 

makes it easier to meet the overall standard (as, for example, if the smaller vehicles are so much lighter that 

they exceed their targets by much greater amounts). 

Comment [A12]: This could go either way. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

10 

in overhang areas or from reducing structural support as a way of taking out mass.9

 

Moreover, NHTSA’s analysis had also found that lighter cars have a higher involvement 

rate in fatal crashes, even after controlling for the driver’s age, gender, urbanization, and 

region of the country. Being unable to explain this clear trend in the crash data, NHTSA 

stated that it must assume that mass reduction is likely to be associated with higher fatalcrash rates, no matter how the weight reduction is achieved.

NHTSA also noted in the NPRM that several studies by Dynamic Research, Inc. 

(DRI) had been repeatedly cited to the agency in support of the proposition that reducing 

vehicle mass while maintaining track width and wheelbase would lead to significant 

safety benefits. In its 2005 studies, one of which was published and peer-reviewed 

through the Society of Automotive Engineers as a technical paper, DRI attempted to 

assess the independent effects of vehicle weight and size (in terms of wheelbase and track 

width) on safety, and presented results indicating that reducing vehicle weight tends to 

reduce fatalities, but that reducing vehicle wheelbase and track width tends to increase 

fatalities. DRI’s analysis was based on FARS data for MYs 1985-1998 passenger cars 

and 1985-1997 light trucks, similar to the MYs 1991-1999 car and truck data used in the 

2003 Kahane report. However, DRI included 2-door passenger cars, while the 2003 

Kahane report excluded those vehicles out of concern that their inclusion could bias the 

results of the regression analysis, because a significant proportion of MYs 1991-1999 2-

door cars were sports and “muscle” cars, which have particularly high fatal crash rates for 

their relatively short wheelbases compared to the rest of the fleet. While in the NPRM 

NHTSA rejected the results of the DRI studies based in part on this concern, the agencies 

note that upon further consideration, NHTSA has agreed for this final rule that the 

inclusion of 2-door cars in regression analysis of historical data is appropriate, and indeed 

has no overly-biasing effects. 

The 2005 DRI studies also differed from the 2003 Kahane report in terms of their 

estimates of the effect of vehicle weight on rollover fatalities. The 2003 Kahane report 

analyzed a single variable, curb weight, as a surrogate for both vehicle size and weight, 

and found that curb weight reductions would increase rollover fatalities. The DRI study, 

in contrast, attempted to analyze curb weight, wheelbase, and track width separately, and 

found that curb weight reduction would decrease rollover fatalities, while wheelbase 

reduction and track width reduction would increase them. DRI suggested that heavier 

vehicles may have higher rollover fatalities for two reasons: first, because taller vehicles 

tend to be heavier, so the correlation between vehicle height and weight and vehicle 

center-of-gravity height may make heavier vehicles more rollover-prone; and second, 

because heavier vehicles may have been less rollover-crashworthy due to FMVSS No. 

216’s constant (as opposed to proportional) requirements for MYs 1995-1999 vehicles 

weighing more than 3,333 lbs unloaded. 

Overall, DRI’s 2005 studies found a reduction in fatalities for cars (580 in the first 

study, and 836 in the second study) and for trucks (219 in the first study, 682 in the 

second study) for a 100 pound reduction in curb weight without accompanying wheelbase 

 

9

 However, we recognize that FMVSS and NCAP ratings may limit the manufacturer’s ability to reduce 

crush space or structural support. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

11 

or track width reductions. In the NPRM, NHTSA disagreed with the results of the DRI 

studies, out of concern that DRI’s inclusion of 2-door cars in its analysis biased the 

results, and because NHTSA was unable to reproduce DRI’s results despite repeated 

attempts. NHTSA stated that it agreed intuitively with DRI’s conclusion that vehicle 

mass reductions without accompanying size reductions (as through substitution of a 

heavier material for a lighter one) would be less harmful than downsizing, but without 

supporting real-world data and unable to verify DRI’s results, NHTSA stated that it could 

not conclude that mass reductions would result in safety benefits. EPA, in contrast, 

believed that DRI’s results contained some merit, in particular because the study 

separated the effects of mass and size and EPA stated that applying them using the curb 

weight reductions in EPA’s modeling analysis would show an overall reduction of 

fatalities for the proposed standards. 

On balance, both agencies recognized that mass reduction could be an important 

tool for achieving higher levels of fuel economy and reducing CO2 emissions, and 

emphasized that NHTSA’s fatality estimates represented a worst-case scenario for the 

potential effects of the proposed standards, and that actual fatalities will be less than these 

estimates, possibly significantly less, based on the various factors discussed in the NPRM 

that could reduce the estimates. The agencies sought comment on the safety analysis and 

discussions presented in the NPRM. 

2. What public comments did the agencies receive on the safety analysis 

and discussions in the NPRM?

 Several dozen commenters addressed the safety issue. Claims/arguments made 

by cComments in response to the safety effects analysis and discussion in the NPRM 

tended to follow several general themes, as follows: 

 NHTSA’s safety effects estimates are inaccurate because they do not account for 

the fact that: 

o While NHTSA’s study only considers vehicles from MYs 1991-1999, 

more recently-built vehicles are safer than those, and future vehicles will 

be safer still; 

o Lighter vehicles are safer than heavier cars in terms of crash-avoidance, 

because they handle and brake better; 

o Fatalities are linked more to other factors than mass; 

o The structure of the standards reduces/contributes to potential safety 

effects from mass reduction; 

o NHTSA could mitigate additional safety effects from mass reduction, if 

there are any, by simply regulating safety more; 

o Casualty risks range widely for vehicles of the same weight or footprint, 

which skews regression analysis and makes computer simulation a better 

predictor of the safety effects of mass reduction; 

 DRI’s analysis shows that lighter vehicles will save lives, and NHTSA reaches 

the opposite conclusion without disproving DRI’s analysis; 

Comment [A13]: Since these are commenters’ 

views and not necessarily facts. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

12 

o Possible rReasons that NHTSA and DRI may have reached different 

conclusions: 

 NHTSA’s study should distinguish between reductions in size and 

reductions in weight like DRI’s; 

 NHTSA’s study should include two-door cars; 

 NHTSA’s study should have used different assumptions; 

 NHTSA’s study should include confidence intervals; 

 NHTSA should include a “best-case” estimate in its study; 

 NHTSA should not include a “worst-case” estimate in its study; 

The agencies recognize that the issue of the potential safety effects of mass 

reduction, which was one of the many factors considered in the balancing that led to the 

agencies’ conclusion as to appropriate stringency levels for the MYs 2012-2016 

standards, is of great interest to the public and could possibly be a more significant factor 

in regulators’ and manufacturers’ decisions with regard to future standards beyond MY 

2016. The agencies are committed to analyzing this issue thoroughly and holistically 

going forward, based on the best available science, in order to further their closely related 

missions of safety, energy conservation, and environmental protection. We respond to 

the issues and concerns claims raised by commenters in turn below. 

NHTSA’s estimates are inaccurate because NHTSA’s study only considers vehicles 

from MYs 1991-1999, but more recently-built vehicles are safer than those, and future 

vehicles will be safer still

 A number of commenters (CAS, Adcock, NACAA, NJ DEP, NY DEC, UCS, and 

Wenzel) argued that the 2003 Kahane report, on which the “worst-case scenario” in the 

NPRM was based, is outdated because it considers the relationship between vehicle 

weight and safety in MYs 1991-1999 passenger cars. These commenters generally stated 

that data from MYs 1991-1999 vehicles provide an inaccurate basis for assessing the 

relationship between vehicle weight and safety in current or future vehicles, because the 

fleets of vehicles now and in the future are increasingly different from that 1990s fleet 

(more crossovers, fewer trucks, lighter trucks, etc.), with different vehicle shapes and 

characteristics, different materials, and more safety features. Several of these 

commenters argued that NHTSA should conduct an updated analysis for the final rule 

using more recent data – Wenzel, for example, stated that an updated regression analysis 

that accounted for the recent introduction of crossover SUVs would likely find reduced 

casualty risk, similar to DRI’s previous finding using fatality data. CEI, in contrast, 

argued that the “safety trade-off” would not be eliminated by new technologies and 

attribute-based standards, because additional weight inherently makes a vehicle safer to 

its own occupants, citing the 2003 Kahane report, while AISI argued that Desapriya had 

found that passenger car drivers and occupants are two times more likely to be injured 

than drivers and occupants in larger pickup trucks and SUVs. 

 Several commenters (Adcock, CARB, Daimler, NESCAUM, NRDC, Public 

Citizen, UCS, Wenzel) suggested that NHTSA’s analysis was based on overly 

pessimistic assumptions about how manufacturers would choose to reduce mass in their 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

13 

vehicles, because manufacturers have a strong incentive in the market to build vehicles 

safely. Many of these commenters stated that several manufacturers have already 

committed publicly to fairly ambitious mass reduction goals in the mid-term, but several 

stated further that NHTSA should not assume that manufacturers will reduce the same 

amount of mass in all vehicles, because it is likely that they will concentrate mass 

reduction in the heaviest vehicles, which will improve compatibility and decrease 

aggressivity in the heaviest vehicles. Daimler emphasized that all vehicles will have to 

comply with the Federal Motor Vehicle Safety Standards, and will likely be designed to 

test well in NHTSA’s NCAP tests. 

Other commenters (Aluminum Association, CARB, CAS, ICCT, MEMA, NRDC, 

U.S. Steel) also emphasized the need for NHTSA to account for the safety benefits to be 

expected in the future from use of advanced materials for lightweighting purposes and 

other engineering advances. The Aluminum Association stated that advanced vehicle 

design and construction techniques using aluminum can improve energy management and 

minimize adverse safety effects of their use,10 but that NHTSA’s safety analysis could not 

account for those benefits if it were based on MYs 1991-1999 vehicles. CAS, ICCT, and 

U.S. Steel discussed similar benefits for more recent and future vehicles built with high 

strength steel (HSS), although U.S. Steel cautioned that given the stringency of the 

proposed standards, manufacturers would likely be encouraged to build smaller and 

lighter vehicles in order to achieve compliance, which fare worse in head-on collisions 

than larger, heavier vehicles. AISI, in contrast to U.S. Steel, stated that in its research 

with the Auto/Steel Partnership and in programs supported by DOE, it had found that the 

use of new Advanced HSS steel grades could enable mass of critical crash structures, 

such as front rails and bumper systems, to be reduced by 25 percent without degrading 

performance in standard NHTSA frontal or IIHS offset instrumented crash tests 

compared to their “heavier counterparts.” 

Agencies’ response:

NHTSA, in consultation with EPA and DOE, plans to begin updating the MYs 

1991-1999 database on which NHTSA’s safety analyses in the NPRM and final rule are 

based in the next several months in order to analyze the differences in safety effects 

against vehicles built in more recent model years. As this task will take at least a year to 

complete, beginning it immediately after the NPRM would not have enabled the agency 

to complete it and then conduct a new analysis during the period between the NPRM and 

the final rule. 

For purposes of this final rule, however, we believe that using the same MYs 

1991-1999 database as that used in the 2003 Kahane study provides a reasonable basis for 

 

10 The Aluminum Association (NHTSA-2009-0059-0067.3) stated that its research on vehicle safety 

compatibility between an SUV and a mid-sized car, done jointly with DRI, shows that reducing the weight 

of a heavier SUV by 20% (a realistic value for an aluminum-intensive vehicle) could reduce the combined 

injury rate for both vehicles by 28% in moderately severe crashes. The commenter stated that it would 

keep NHTSA apprised of its results as its research progressed. Based on the information presented, 

NHTSA believes that this research appears to agree with NHTSA’s latest analysis, which finds that a 

reduction in weight for the heaviest vehicles may improve overall fleet safety.
Summary of Interagency Working Comments on Draft Rule under EO 12866 

14 

attempting to estimate safety effects due to reductions in mass. While commenters often 

stated that updating the database would help to reveal the effect of recently-introduced 

lightweight vehicles with extensive material substitution, there have in fact not yet been a 

significant number of vehicles with substantial mass reduction/material substitution to 

analyze, and they must also show up in the crash databases for NHTSA to be able to add 

them to its analysis. Based on NHTSA’s research, specifically, on three statistical 

analyses over a 12-year period (1991-2003) covering a range of 22 model years (1978-

1999), NHTSA believes that the relationships between mass, size, and safety has only 

changed slowly over time, although we recognize that they may change somewhat more 

rapidly in the future.11 As the on-road fleet gains increasing numbers of vehicles with 

increasing amounts of different methods of mass reduction applied to them, we may 

begin to discern changes in the crash databases due to the presence of these vehicles, but 

any such changes are likely to be slow and evolutionary, particularly in the context of 

MYs 2000-2009 vehicles. The agencies do expect that further analysis of historical data 

files will continue to provide a robust and practicable basis for estimating the potential 

safety effects that might occur with future reductions in vehicle mass. However, we 

recognize that estimates derived from analysis of historical data, like estimates from any 

other type of analysis (including simulation-based analysis, which cannot feasibly cover 

all relevant scenarios), will be uncertain in terms of predicting actual future outcomes 

with respect to a vehicle fleet, driving population, and operating environment that does 

not yet exist. 

 

The agencies also recognize that more recent vehicles have more safety features 

than 1990s vehicles, which are likely to make them safer overall. To account for this, 

NHTSA did adjust the results of both its NPRM and final rule analysis to include known 

safety improvements, like ESC and increases in seat belt use, that have occurred since 

MYs 1991-1999.12 However, simply because newer vehicles have more safety 

countermeasures, does not mean that the weight/safety relationship necessarily changes. 

More likely, it would change the target population (the number of fatalities) to which one 

would apply the weight/safety relationship. Thus, we still believe that some mass 

reduction techniques for both passenger cars and light trucks can make them less safe, in 

certain crashes as discussed in NHTSA’s FRIA, than if mass had not been reduced.13

As for NHTSA’s assumptions about mass reduction, in its analysis, NHTSA 

generally assumed that lighter vehicles could be reduced in weight by 5 percent while 

 

11 NHTSA notes the CAS’ comments regarding changes in the vehicle fleets since the introduction of 

CAFE standards in the late 1970s, but believes they apply more to the differences between late 1970s 

through 1980s vehicles and 2010s vehicles than to the differences between 1990s and 2010s vehicles. 

NHTSA believes that the CAS comments regarding the phase-out of 1970s vehicles and their replacement 

with safer, better fuel-economy-achieving 1980s vehicles paint with rather too large a brush to be relevant 

to the main discussion of whether the 2003 Kahane report database can reasonably be used to estimate 

safety effects of mass reduction for the MYs 2012-2016 fleet. 

12 See NHTSA FRIA Chapter IX. 13 If one has a vehicle (vehicle A), and both reduces the vehicle’s mass and adds new safety equipment to it, 

thus creating a variant (vehicle A1), the variant might conceivably have a level of overall safety for its 

occupants is equal to that of the original vehicle (vehicle A). However, vehicle A1 might not be as safe as 

second variant (vehicle A2) of vehicle A, one that is produced by adding to vehicle A the same new safety 

equipment added to the first variant, but this time without any mass reduction. 

Comment [A14]: Does this apply to CAD?
Summary of Interagency Working Comments on Draft Rule under EO 12866 

15 

heavier light trucks could be reduced in weight by 10 percent. NHTSA recognizes that 

manufacturers might choose a different mass reduction scheme than this, and that its 

quantification of the estimated effect on safety would be different if they did. We 

emphasize that our estimates are based on the assumptions we have employed and are 

intended to help the agency consider the potential effect of the final standards on vehicle 

safety. Thus, based on the 2010 Kahane analysis, reductions in weight for the heavier 

light trucks would have positive overall safety effects,14 while mass reductions for 

passenger cars and smaller light trucks would have negative overall safety effects. 

NHTSA’s estimates are inaccurate because they do not account for the fact that 

lighter vehicles are safer than heavier cars in terms of crash-avoidance, 

because they handle and brake better 

ICCT stated that lighter vehicles are better able to avoid crashes because they 

“handle and brake slightly better,” arguing that size-based standards encourage lighterweight car-based SUVs with “significantly better handling and crash protection” than 

1996-1999 mid-size SUVs, which will reduce both fatalities and fuel consumption. ICCT 

stated that NHTSA did not include these safety benefits in its analysis. DRI also stated 

that its 2005 report found that crash avoidance improves with reduction in curb weight 

and/or with increases in wheelbase and track, because “Crash avoidance can depend, 

amongst other factors, on the vehicle directional control and rollover characteristics.” 

DRI argued that, therefore, “These results indicate that vehicle weight reduction tends to 

decrease fatalities, but vehicle wheelbase and track reduction tends to increase fatalities.” 

Agencies’ response:

In fact, NHTSA’s regression analysis of crash fatalities per million registration 

years measures the effects of crash avoidance, if there are any, as well as 

crashworthiness. Given that the historical empirical data for passenger cars show a trend 

of higher crash rates for lighter cars, it is unclear whether lighter cars have, in the net, 

superior crash avoidance, although the agencies recognize that they may have advantages 

in certain individual situations. EPA presents a discussion of improved accident 

avoidance as vehicle mass is reduced in Chapter 7.6 of its final RIA. The important point 

to emphasize is that it depends on the situation – it would oversimplify drastically to 

point to one situation in which extra mass helps or hurts and then extrapolate effects for 

crash avoidance across the board based on only that. 

For example, the relationship of vehicle mass to rollover and directional stability 

is more complex than commenters imply. For rollover, it is true that if heavy pickups 

were always more top-heavy than lighter pickups of the same footprint, their higher 

center of gravity could make them more rollover-prone, yet some mass can be placed so 

as to lower a vehicle’s center of gravity and make it less rollover-prone. For mass 

reduction to be beneficial in rollover crashes, then, it must take center of gravity height 

 

14 This is due to the beneficial effect on the occupants of vehicles struck by the downweighted larger 

vehicles. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

16 

into account along with other factors such as passenger compartment design and 

structure, suspension, the presence of various safety equipment, and so forth. 

Similarly, for directional stability, it is true that having more mass increases the 

“understeer gradient” of cars – i.e., it reinforces their tendency to proceed in a straight 

line and slows their response to steering input, which would be harmful where prompt 

steering response is essential, such as in a double-lane-change maneuver to avoid an 

obstacle. Yet more mass and a higher understeer gradient could help when it is better to 

remain on a straight path, such as on a straight road with icy patches where wheel slip 

might impair directional stability. Thus, while less vehicle mass can sometimes improve 

crash avoidance capability, there can also be situations when more vehicle mass can help 

in other kinds of crash avoidance. 

Further, NHTSA’s research suggests that additional vehicle mass may be even 

more helpful, as discussed in Chapter IX of NHTSA’s FRIA, when the average driver’s 

response to a vehicle’s maneuverability is taken into account. Lighter cars have 

historically (1976-2009) had higher collision-involvement rates than heavier cars – even 

in multi-vehicle crashes where directional and rollover stability is not particularly an 

issue.15 Based on our analyses using nationally-collected FARS and GES data, drivers of 

lighter cars are more likely to be the culpable party in a 2-vehicle collision, even after 

controlling for footprint, the driver’s age, gender, urbanization, and region of the country. 

Thus, based on this data, it appears that lighter cars may not be driven as well as 

heavier cars, although it is unknown why this is so. If poor drivers intrinsically chose 

light cars (self-selection), it might be evidenced by an increase in antisocial driving 

behavior (such as DWI, drug involvement, speeding, or driving without a license) as car 

weight decreases, after controlling for driver age and gender – in addition to the increases 

in merely culpable driver behavior (such as failure to yield the right of way). But 

analyses in NHTSA’s 2003 report did not show an increase in antisocial driver behavior 

in the lighter cars paralleling their increase in culpable involvements. 

NHTSA also hypothesizes that certain aspects of lightness and/or smallness in a 

car may give a driver a perception of greater maneuverability that ultimately results in 

driving with less of a “safety margin,” e.g., encouraging them to weave in traffic. That 

may appear paradoxical at first glance, as maneuverability is, in the abstract, a safety 

plus. Yet the situation is not unlike powerful engines that could theoretically enable a 

driver to escape some hazards, but in reality have long been associated with high crash 

and fatality rates.16

 

15 See, e.g., NHTSA (2000). Traffic Safety Facts 1999. Report No. DOT HS 809 100. Washington, DC: 

National Highway Traffic Safety Administration, p. 71; Najm, W.G., Sen, B., Smith, J.D., and Campbell, 

B.N. (2003). Analysis of Light Vehicle Crashes and Pre-Crash Scenarios Based on the 2000 General 

Estimates System, Report No. DOT HS 809 573. Washington, DC: National Highway Traffic Safety 

Administration, p. 48. 

16 Robertson, L.S. (1991), “How to Save Fuel and Reduce Injuries in Automobiles,” The Journal of 

Trauma, Vol. 31, pp. 107-109; Kahane, C.J. (1994). Correlation of NCAP Performance with Fatality Risk 

in Actual Head-On Collisions, NHTSA Technical Report No. DOT HS 808 061. Washington, DC: 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

17 

NHTSA’s estimates are inaccurate because fatalities are linked more to other 

factors than mass 

Tom Wenzel stated that the safety record of recent model year crossover SUVs 

indicates that weight reduction in this class of vehicles (small to mid-size SUVs) resulted 

in a reduction in fatality risk. Wenzel argued that NHTSA should acknowledge that other 

vehicle attributes may be as important, if not more important, than vehicle weight or 

footprint in terms of occupant safety, such as unibody construction as compared to 

ladder-frame, lower bumpers, and less rigid frontal structures, all of which make 

crossover SUVs more compatible with cars than truck-based SUVs. 

Marc Ross commented that fatalities are linked more strongly to intrusion than to 

mass, and stated that research by safety experts in Japan and Europe suggests the main 

cause of serious injuries and deaths is intrusion due to the failure of load-bearing 

elements to properly protect occupants in a severe crash. Ross argued that the results 

from this project have “overturned the original views about compatibility,” which thought 

that mass and the mass ratio were the dominant factors. Since footprint-based standards 

will encourage the reduction of vehicle weight through materials substitution while 

maintaining size, Ross stated, they will help to reduce intrusion and consequently 

fatalities, as the lower weight reduces crash forces while maintaining size preserves crush 

space. Ross argued that this factor was not considered by NHTSA in its discussion of 

safety. ICCT agreed with Ross’ comments on this issue. 

In previous comments on NHTSA rulemakings and in several studies, Wenzel and 

Ross have argued generally that vehicle design and “quality” is a much more important 

determinant of vehicle safety than mass. In comments on the NPRM, CARB, NRDC, 

Sierra Club, and UCS echoed this theme. 

ICCT commented as well that fatality rates in the EU are much lower than rates in 

the U.S., even though the vehicles in the EU fleet tend to be smaller and lighter than 

those in the U.S. fleet. Thus, ICCT argued, “This strongly supports the idea that vehicle 

and highway design are far more important factors than size or weight in vehicle safety.” 

ICCT added that “It also suggests that the rise in SUVs in the U.S. has not helped reduce 

fatalities.” CAS also commented that Germany’s vehicle fleet is both smaller and lighter 

than the American fleet, and has lower fatality rates. 

Agencies’ response:

NHTSA and EPA agree that there are many features that affect safety. While 

crossover SUVs have lower fatality rates than truck-based SUVs, there are no analyses 

that attribute the improved safety to mass alone, and not to other factors such as the lower 

center of gravity or the unibody construction of these vehicles. While a number of 

improvements in safety can be made, they do not negate the potential that another 100 

 National Highway Traffic Safety Administration, http://www-nrd.nhtsa.dot.gov/Pubs/808061.PDF, pp. 4-

7. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

18 

lbs. could make a passenger car or crossover vehicle safer for its occupants, because of 

the effects of mass per se as discussed in NHTSA’s FRIA, albeit similar mass reductions 

could make heavier LTVs safer to other vehicles without necessarily harming their own 

drivers and occupants. Moreover, in the 2004 response to docket comments, NHTSA 

explained that the significant relationship between mass and fatality risk persisted even 

after controlling for vehicle price or nameplate, suggesting that vehicle “quality” as cited 

by Wenzel and Ross is not necessarily more important than vehicle mass. 

As for reductions in intrusions due to material substitution, the agencies agree 

generally that the use of new and innovative materials may have the potential to reduce 

crash fatalities, but such vehicles have not been introduced in large numbers into the 

vehicle fleet. The agencies will continue to monitor the situation, but ultimately the 

effects of different methods of mass reduction on overall safety in the real world (not just 

in simulations) will need to be analyzed when vehicles with these types of mass reduction 

are on the road in sufficient quantities to provide statistically significant results. For 

example, a vehicle that is designed to be much stiffer to reduce intrusion is likely to have 

a more severe crash pulse and thus impose greater forces on the occupants during a crash, 

and might not necessarily be good for elderly and child occupant safety in certain types 

of crashes. Such trade-offs make it difficult to estimate overall results accurately without 

real world data. The agencies will continue to evaluate and analyze such real world data 

as it becomes available, and will keep the public informed as to our progress. 

ICCT’s comment illustrates the fact that different vehicle fleets in different 

countries can face different challenges. NHTSA does not believe that the fact that the EU 

vehicle fleet is generally lighter than the U.S. fleet is the exclusive reason, or even the 

primary factor, for the EU’s lower fatality rates. The data ICCT cites do not account for 

sSignificant differences between the US and EU such as exist in belt usage, drunk 

driving, rural/urban roads, driving culture, etc. 

The structure of the standards reduces/contributes to potential safety risks from 

mass reduction 

Since switching in 2006 to setting attribute-based light truck CAFE standards, 

NHTSA has emphasized that one of the benefits of a footprint-based standard is that it 

discourages manufacturers from building smaller, less safe vehicles to achieve CAFE 

compliance by “balancing out” their larger vehicles, and thus avoids a negative safety 

consequence of increasing CAFE stringency.17 Some commenters on the NPRM 

(Daimler, IIHS, NADA, NRDC, Sierra Club et al.) agreed that footprint-based standards 

would protect against downsizing and help to mitigate safety risks, while others stated 

that there would still be safety risks even with footprint-based standards – CEI, for 

example, argued that mass reduction inherently creates safety risks, while IIHS and 

 

17 We note that commenters were divided on whether they believed there was a clear correlation between 

vehicle size/weight and safety (CEI, Congress of Racial Equality, Heritage Foundation, IIHS, Spurgeon, 

University of PA Environmental Law Project) or whether they believed that the correlation was less clear, 

for example because they believed that vehicle design was more important than vehicle mass (CARB, 

Public Citizen). 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

19 

Porsche expressed concern about footprint-based standards encouraging manufacturers to 

manipulate wheelbase, which could reduce crush space and worsen vehicle handling. 

U.S. Steel and AISI both commented that the “aggressive schedule” for the proposed 

increases in stringency could encourage manufacturers to build smaller, lighter vehicles 

in order to comply. 

Some commenters also focused on the shape and stringency of the target curves 

and their potential effect on vehicle safety. IIHS agreed with the agencies’ tentative 

decision to cut off the target curves at the small-footprint end. Although the agencies’ 

did so in relation to concerns about the feasibility of attribute-based standards as applied 

to manufacturers emphasizing small vehicles, IIHS’s comments suggest IIHS is not 

concerned with the standards’ resultant neutrality with respect to incremental reductions 

in the size of the smallest vehicles. Regarding the safety effect of the curves requiring 

less stringent targets for larger vehicles, while IIHS stated that increasing footprint is 

good for safety, CAS, Wenzel, and the UCSB students stated that decreasing footprint 

may be better for safety in terms of risk to occupants of other vehicles. Daimler, Wenzel, 

and the University of PA Environmental Law Project commented generally that more 

similar passenger car and light truck targets at identical footprints (as Wenzel put it, a 

single target curve) would improve fleet compatibility and thus, safety, by encouraging 

manufacturers to build more passenger cars instead of light trucks. 

Agencies’ response:

 The agencies continue to believe that footprint-based standards help to mitigate 

potential safety risks from downsizing if the target curves maintain sufficient slope, 

because, based on NHTSA’s analysis, larger-footprint vehicles are safer than smallerfootprint vehicles.18 The structure of the footprint-based curves will also discourage the 

upsizing of vehicles. Nevertheless, we recognize that footprint-based standards are not a 

panacea – NHTSA’s analysis continues to show that there was a historical relationship 

between lower vehicle mass and increased safety risk in passenger cars even if footprint 

is maintained, and there are ways that manufacturers may increase footprint that either 

improve or reduce vehicle safety, as indicated by IIHS and Porsche. 

 With regard to whether the agencies should set separate curves or a single one, 

NHTSA also notes in Section II.C that EPCA requires NHTSA to establish standards 

separately for passenger cars and light trucks, and thus concludes that the standards for 

each fleet should be based on the characteristics of vehicles in each fleet. In other words, 

the passenger car curve should be based on the characteristics of passenger cars, and the 

light truck curve should be based on the characteristics of light trucks—thus to the extent 

that those characteristics are different, an artificially-forced convergence would not 

accurately reflect those differences. However, such convergence could be appropriate 

depending on future trends in the light vehicle market, specifically further reduction in 

the differences between passenger car and light truck characteristics. While that trend 

was more apparent when car-like 2WD SUVs were classified as light trucks, it seems 

 

18 See Chapter IX of NHTSA’s FRIA. 

Comment [A15]: What does this neutrality 

mean? 

Comment [A16]: IIHS comments are internally 

inconsistent and it is not clear that they necessarily 

supported or agreed with the specifc cutoff as you 

are claiming here. Is this discussion based on any 

other comments from IIHS apart from the official 

comment letter during the public comment period? 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

20 

likely to diminish for the model year vehicles subject to these rules as the truck fleet will 

be more purely “truck-like” than has been the case in recent years. 

NHTSA’s estimates are inaccurate because NHTSA could mitigate additional 

safety risks from mass reduction, if there are any, by simply regulating safety 

more 

 Since NHTSA began considering the potential safety risks from mass reduction in 

response to increased CAFE standards, some commenters have suggested that NHTSA 

could mitigate those safety risks, if any, by simply regulating more.19 In response to the 

safety analysis presented in the NPRM, several commenters stated that NHTSA should 

develop additional safety regulations to require vehicles to be designed more safely, 

whether to improve compatibility (Adcock, NY DEC, Public Citizen, UCS), to require 

seat belt use (CAS, UCS), to improve rollover and roof crush resistance (UCS), or to 

improve crashworthiness generally by strengthening NCAP and the star rating system 

(Adcock). Wenzel commented further that “Improvements in safety regulations will have 

a greater effect on occupant safety than FE standards that are structured to maintain, but 

may actually increase, vehicle size.” 

Agencies’ response:

 NHTSA appreciates the commenters’ suggestions and notes that the agency is 

continually striving to improve motor vehicle safety consistent with its mission. As noted 

above, improving safety in other areas affects the target population that the 

mass/footprint relationship could affect, but it does not necessarily change the 

relationship. 

 The 2010 Kahane analysis discussed in this final rule evaluates the relative safety 

risk when vehicles are made lighter than they might otherwise be absent the final MYs 

2012-2016 standards. It does consider the effect of known safety regulations as they are 

projected to affect the target population. 

 

Casualty risks range widely for vehicles of the same weight or footprint, which 

skews regression analysis and makes computer simulation a better predictor of 

the safety effects of mass reduction 

Wenzel commented that he had found, in his most recent work, after accounting 

for drivers and crash location, that there is a wide range in casualty risk for vehicles with 

the same weight or footprint. Wenzel stated that for drivers, casualty risk does generally 

decrease as weight or footprint increases, especially for passenger cars, but the degree of 

variation in the data for vehicles (particularly light trucks) at a given weight or footprint 

makes it difficult to say that a decrease in weight or footprint will necessarily result in 

increased casualty risk. In terms of risk imposed on the drivers of other vehicles, Wenzel 

stated that risk increases as light truck weight or footprint increases. 

 

19 See, e.g., MY 2011 CAFE final rule, 74 Fed. Reg. at 14403-05 (Mar. 30, 2009). 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

21 

Wenzel further stated that because a regression analysis can only consider the 

average trend in the relationship between vehicle weight/size and risk, it must “ignore” 

vehicles that do not follow that trend. Wenzel therefore recommended that the agency 

employ computer crash simulations for analyzing the effect of vehicle weight reduction 

on safety, because they can “pinpoint the effect of specific vehicle designs on safety,” 

and can model future vehicles which do not yet exist and are not bound to analyzing 

historical data. Wenzel cited, as an example, a DRI simulation study commissioned by 

the Aluminum Association (Kebschull 2004), which used a computer model to simulate 

the effect of changing SUV mass or footprint (without changing other attributes of the 

vehicle) on crash outcomes, and showed a 15 percent net decrease in injuries, while 

increasing wheelbase by 4.5 inches while maintaining weight showed a 26 percent net 

decrease in serious injuries. 

Agencies’ response: 

The agencies have reviewed Mr. Wenzel’s draft report for DOE to which he 

referred in his comments, but based on NHTSA’s work do not find such a wide range of 

safety risk for vehicles with the same weight, although we agree there is a range of risk 

for a given footprint. Wenzel found that for drivers, casualty risk does generally decrease 

as weight or footprint increases, especially for passenger cars, and that in terms of risk 

imposed on the drivers of other vehicles, risk increases as light truck weight or footprint 

increases, but concluded that the variation in the data precluded the possibility of drawing 

any conclusions. In the 2010 Kahane study presented in the FRIA, NHTSA undertook a 

similar analysis in which it correlated weight to fatality risk for vehicles of essentially the 

same footprint.20 The “decile analysis,” provided as a check on the trend/direction of 

NHTSA’s regression analysis, shows that fatality risk generally increases and rarely 

decreases for lighter relative to heavier cars of the same footprint. Thus, while Mr. 

Wenzel was reluctant to draw a conclusion, NHTSA believes that both our research and 

Mr. Wenzel’s appear to point to the same conclusion. We agree that there is a wide range 

in casualty risk among cars of the same footprint, but we find that that casualty risk is 

correlated with weight. The correlation shows that heavier cars have lower overall 

fatality rates than lighter cars of very similar footprint. 

The agencies agree that simulation can be beneficial in certain circumstances. 

NHTSA cautions, however, that it is difficult for a simulation analysis to capture the full 

range of variations in crash situations in the way that a statistical regression analysis 

does. Vehicle crash dynamics are complex, and small changes in initial crash conditions 

(such as impact angle or closing speed) can have large effects on injury outcome. This 

condition is a consequence of variations in the deformation mode of individual 

components (e.g., buckling, bending, crushing, material failure, etc.) and how those 

variations affect the creation and destruction of load paths between the impacting object 

and the occupant compartment during the crash event. It is therefore difficult to predict 

and assess structural interactions using computational methods when one does not have a 

detailed, as-built geometric and material model. Even when a complete model is 

available, prudent engineering assessments require extensive physical testing to verify 

 

20 Sections 2.4 and 3.3 of new report. 

Comment [A17]: I am confused by the 

discussion of safety risk inherent to a vehicle 

independent of what it runs into. In general, smaller 

cars have higher safety risks but this is also – in part 

– exacerbated by the existence of much larger 

vehicles on the road to crash into. The text could be 

better at acknowledging the role that the size 

distribution plays with regard to safety. It also could 

do better at parsing risks by vehicle occupant vs. 

occupants in the other vehicle, pedestrians, cyclists, 

etc. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

22 

crash behavior and safety. Despite all this, the agencies recognize that detailed crash 

simulations can be useful in estimating the relative structural effects of design changes 

over a limited range of crash conditions, and will continue to evaluate the appropriate use 

of this tool in the future. 

Simplified crash simulations can also be valuable tools, but only when employed 

as part of a comprehensive analytical program. They are especially valuable in 

evaluating the relative effect and associated confidence intervals of feasible design 

alternatives. For example, the method employed by Nusholtz et al.

21 could be used by a 

vehicle designer to estimate the benefit of incremental changes in mass or wheelbase as 

well as the tradeoffs that might be made between them once that designer has settled on a 

preliminary design. A key difference between the research by Nusholtz and the research 

by Kebschull that Mr. Wenzel cited22 is in their suggested applications. The former is 

useful in evaluating proposed alternatives early in the design process – Nusholtz 

specifically warns that the model provides only “general insights into the overall risk ... 

and cannot be used to obtain specific response characteristics.” Mr. Wenzel implies the 

latter can “isolate the effect of specific design changes, such as weight reduction” and 

thus quantify the fleet-wide effect of substantial vehicle redesigns. Yet while Kebschull 

reports injury reductions to three significant digits, there is no validation that vehicle 

structures of the proposed weight and stiffness are even feasible with current technology. 

Thus, while the agencies agree that computer simulations can be useful tools, we also 

recognize the value of statistical regression analysis for determining fleet-wide effects, 

because it inherently incorporates real-world factors in historical safety assessments.

DRI’s analysis shows that lighter vehicles will save lives, and NHTSA reaches the 

opposite conclusion without disproving DRI’s analysis

 The difference between NHTSA’s results and DRI’s results for the relationship 

between vehicle mass and vehicle safety has been at the crux of this issue for several 

years. While NHTSA offered some theories in the NPRM as to why DRI might have 

found a safety benefit for mass reduction, NHTSA’s work since then has enabled it to 

identify what we believe is the most likely reason for DRI’s findings. The potential near 

 

21 Nusholtz, G.S., G. Rabbiolo, and Y. Shi, “Estimation of the Effects of Vehicle Size and Mass on CrashInjury Outcome Through Parameterized Probability Manifolds,” Society of Automotive Engineers (2003), 

Document No. 2003-01-0905. Available at http://www.sae.org/technical/papers/2003-01-0905 (last 

accessed Feb. 15, 2010). 

22 Mr. Wenzel cites the report by Kebschull et al [2004, DRI-TR-04-04-02] as an example of what he 

regards as the effective use of computer crash simulation. NHTSA does not concur that this analysis 

represents a viable analytical method for evaluating the fleet-wide tradeoffs between vehicle mass and 

societal safety. The simulation method employed was not a full finite element representation of each major 

structural component in the vehicles in question. Instead, an Articulated Total Body (ATB) representation 

was constructed for each of two representative vehicles. In the ATB model, large structural subsystems 

were represented by a single ellipsoid. Consolidated load-deflection properties of these subsystems and the 

joints that tie them together were “calibrated” for an ATB vehicle model by requiring that it reproduce the 

acceleration pulse of a physical NHTSA crash test. NHTSA notes that vehicle simulation models that are 

calibrated to a single crash test configuration (e.g., a longitudinal NCAP test into a rigid wall) are often illequipped to analyze alternative crash scenarios (e.g., vehicle-to-vehicle crashes at arbitrary angles and 

lateral offsets).
Summary of Interagency Working Comments on Draft Rule under EO 12866 

23 

multicollinearity of the variables of curb weight, track width, and wheelbase creates some 

degree of risk that any regression models with those variables could inaccurately calibrate 

their effects. However, based on its own experience with statistical analysis, NHTSA 

believes that the specific two-step regression model used by DRI increases this risk, 

because it weakens relationships between curb weight and dependent variables by 

splitting the effect of curb weight across the two regression steps. 

 

 The comments below are in response to NHTSA’s theories in the NPRM about 

the source of the differences between NHTSA’s and DRI’s results. The majority of them 

are answered more fully in the 2010 Kahane report included in NHTSA’s FRIA, but we 

respond to them in this document as well for purposes of completeness. 

NHTSA and DRI may have reached different conclusions because NHTSA’s 

study does not distinguish between reductions in size and reductions in weight 

like DRI’s 

Several commenters (CARB, CBD, EDF, ICCT, NRDC, and UCS) stated that 

DRI had been able to separate the effect of size and weight in its analysis, and in so doing 

proved that there was a safety benefit to reducing weight without reducing size. The 

commenters suggested that if NHTSA properly distinguished between reductions in size 

and reductions in weight, it would find the same result as DRI. 

Agencies’ response:

 In the 2010 Kahane analysis presented in the FRIA, NHTSA did attempt to 

separate the effects of vehicle size and weight by performing regression analyses with 

footprint (or alternatively track width and wheelbase) and curb weight as separate 

independent variables. For passenger cars, NHTSA found that the regressions attribute 

the fatality increase due to downsizing about equally to mass and footprint – that is, the 

effect of reducing mass alone is about half the effect of reducing mass and reducing 

footprint. Unlike DRI’s results, NHTSA’s regressions for passenger cars and for lighter 

LTVs did not find a safety benefit to reducing weight without reducing size; while 

NHTSA did find a safety benefit for reducing weight in the heaviest LTVs, the 

magnitude of the benefit as compared to DRI’s was significantly smaller. NHTSA 

believes that these differences in results may be an artifact of DRI’s two-step regression 

model, as explained above. 

NHTSA and DRI may have reached different conclusions because NHTSA’s 

study does not include two-door cars like DRI’s 

One of NHTSA’s primary theories in the NPRM as to why NHTSA and DRI’s 

results differed related to DRI’s inclusion in its analysis of 2-door cars. NHTSA had 

excluded those vehicles from its analysis on the grounds that 2-door cars had a 

disproportionate crash rate (perhaps due to their inclusion of muscle and sports cars) 

which appeared likely to skew the regression. Several commenters argued that NHTSA 

should have included 2-door cars in its analysis. DRI and James Adcock stated that 2-
Summary of Interagency Working Comments on Draft Rule under EO 12866 

24 

door cars should not be excluded because they represent a significant portion of the lightduty fleet, while CARB and ICCT stated that because DRI found safety benefits whether 

2-door cars were included or not, NHTSA should include 2-door cars in its analysis. 

Wenzel also commented that NHTSA should include 2-door cars in subsequent analyses, 

stating that while his analysis of MY 2000-2004 crash data from 5 states indicates that, in 

general, 4-door cars tend to have lower fatality risk than 2-door cars, the risk is even 

lower when he accounts for driver age/gender and crash location. Wenzel suggested that 

the increased fatality risk in the 2-door car population seemed primarily attributable to 

the sports cars, and that that was not sufficient grounds to exclude all 2-door cars from 

NHTSA’s analysis. 

Agencies’ response: 

The agencies agree that 2-door cars can be included in the analysis, and NHTSA 

retracts previous statements that DRI’s inclusion of them was incorrect. In its 2010 

analysis, NHTSA finds that it makes little difference to the results whether 2-door cars 

are included, partially included, or excluded from the analysis. Thus, analyses of 2-door 

and 4-door cars combined, as well as other combinations, have been included in the 

analysis. That said, no combination of 2-door and 4-door cars resulted in NHTSA’s 

finding a safety benefit for passenger cars due to mass reduction. 

NHTSA and DRI may have reached different conclusions due to different 

assumptions

DRI commented that the differences found between its study and NHTSA’s may 

be due to the different assumptions about the linearity of the curb weight effect and 

control variable for driver age, vehicle age, road conditions, and other factors. NHTSA’s 

analysis was based on a two-piece linear model for curb weight with two different weight 

groups (less than 2,950 lbs., and greater than or equal to 2.950 lbs). The DRI analysis 

assumed a linear model for curb weight with a single weight group. Additionally, DRI 

stated that NHTSA’s use of eight control variables (rather than three control variables 

like DRI used) for driver age introduces additional degrees of freedom into the 

regressions, which it suggested may be correlated with the curb weight, wheelbase, and 

track width, and/or other control variables. DRI suggested that this may also affect the 

results and cause or contribute to the differences in outcomes between NHTSA and DRI. 

Agencies’ response: 

NHTSA’s FRIA documents that NHTSA analyzed its database using both a single 

parameter for weight (a linear model) and two parameters for weight (a two-piece linear 

model). In both cases, the logistic regression responded identically, allocating the same 

way between weight, wheelbase, track width, or footprint.23 Thus, NHTSA does not 

believe that the differences between its results and DRI’s results are due to whether the 

studies used a single weight group or two weight groups. 

 

23 Sections 2.2 and 2.3 of new report 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

25 

The FRIA also documents that NHTSA examined NHTSA’s use of eight control 

variables for driver age (ages 14-30, 30-50, 50-70, 70+ for males and females separately , 

versus DRI’s use of three control variables for age (FEMALE = 1 for females, 0 for 

males, YOUNGDRV = 35-AGE for drivers under 35, 0 for all others, OLDMAN = 

AGE-50 for males over 50, 0 for all others; OLDWOMAN = AGE-45 for females over 

45, 0 for all others) to see if that affected the results. NHTSA ran its analysis using the 

eight control variables and again using three control variables for age, and obtained 

similar results each time.24 Thus, NHTSA does not believe that the differences between 

its results and DRI’s results are due to the number of control variables used for driver 

age. 

NHTSA’s and DRI’s conclusions may be similar if confidence intervals are 

taken into account 

DRI commented that NHTSA has not reported confidence intervals, while DRI 

has reported them in its studies. Thus, DRI argued, it is not possible to determine 

whether the confidence intervals overlap and whether the differences between NHTSA’s 

and DRI’s analyses are statistically significant. 

Agencies’ response: 

NHTSA has included confidence intervals for the main results of the 2010 

Kahane analysis, as shown in Chapter IX of NHTSA’s FRIA. For passenger cars, the 

NHTSA results are a statistically significant increase in fatalities with a 100 pound 

reduction while maintaining track width and wheelbase (or footprint); the DRI results are 

a statistically significant decrease in fatalities with a 100 pound reduction while 

maintaining track width and wheelbase. The DRI results are thus outside the confidence 

bounds of the NHTSA results and do not overlap.

NHTSA should include a “best-case” estimate in its study 

Several commenters (Center for Auto Safety, NRDC, Public Citizen, Sierra Club 

et al., and Wenzel) urged NHTSA to include a “best-case” estimate in the final rule, 

showing scenarios in which lives were saved rather than lost. Public Citizen stated that 

there would be safety benefits to reducing the weight of the heaviest vehicles while 

leaving the weight of the lighter vehicles unchanged, and that increasing the number of 

smaller vehicles would provide safety benefits to pedestrians, bicyclists, and 

motorcyclists. Sierra Club et al. stated that new materials, smart design, and lighter, 

more advanced engines can all improve fuel economy while maintaining or increasing 

vehicle safety. Both Center for Auto Safety and Sierra Club argued that the agency 

should have presented a “best-case” scenario to balance out the “worst-case” scenario 

presented in the NPRM, especially if NHTSA itself believed that the worst-case scenario 

was not inevitable. NRDC requested that NHTSA present both a “best-case” and a “most 

likely” scenario. Wenzel simply stated that NHTSA did not present a “best-case” 

 

24 Id.

Comment [A18]: Why not age as a controlling 

variable? 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

26 

scenario, despite DRI’s finding in 2005 that fatalities would be reduced if track width 

was held constant. 

Agencies’ response:

NHTSA has included an “upper estimate” and a “lower estimate” in the new 2010 

Kahane analysis. The lower estimate assumes that mass reduction will be accomplished 

entirely by material substitution or other techniques that do not perceptibly change a 

vehicle’s shape, structural strength, or ride quality. The lower estimate examines specific 

crash modes and is meant to reflect the increase in fatalities for the specific crash modes 

in which a reduction in mass per se in the case vehicle would result in a reduction in 

safety: namely, collisions with larger vehicles not covered by the regulations (e.g., trucks 

with a GVWR over 10,000 lbs), collisions with partially-movable objects (e.g., some 

trees, poles, parked cars, etc.), and collisions of cars or light LTVs with heavier LTVs – 

as well as the specific crash modes where a reduction in mass per se in the case vehicle 

would benefit safety: namely, collisions of heavy LTVs with cars or lighter LTVs. 

NHTSA believes that this is the effect of mass per se, i.e., the effects of reduced mass 

will generally persist in these crashes regardless of how the mass is reduced. The lower 

estimate attempts to quantify that scenario, although any such estimate is hypothetical 

and subject to considerable uncertainty. NHTSA believes that a “most likely” scenario 

cannot be determined with any certainty, and would depend entirely upon agency 

assumptions about how manufacturers intend to reduce mass in their vehicles. While we 

can speculate upon the potential effects of different methods of mass reduction, we 

cannot predict with certainty what manufacturers will ultimately do. 

NHTSA should not include a “worst-case” estimate in its study 

NRDC, Public Citizen and Sierra Club et al. commented that NHTSA should 

remove the “worst-case scenario” estimate from the rulemaking, generally because it was 

based on an analysis that evaluated historical vehicles, and future vehicles would be 

sufficiently different to render the “worst-case scenario” inapplicable. 

Agencies’ response: 

NHTSA stated in the NPRM that the “worst-case scenario” addressed the effect of 

a kind of downsizing (i.e., mass reduction accompanied by footprint reduction) that was 

not likely to be a consequence of attribute-based CAFE standards, and that the agency 

would refine its analysis of such a scenario for the final rule. NHTSA has not used the 

“worst-case scenario” in the final rule. Instead, we present three scenarios: the first is an 

estimate based directly on the regression coefficients of weight reduction while 

maintaining footprint in the statistical analyses of historical data. As discussed above, 

presenting this scenario is possible because NHTSA was able to separate the effects of 

weight and footprint reduction in the new analysis. However, even the new analysis of 

LTVs produced some coefficients that NHTSA did not consider entirely plausible. 

NHTSA also presents an “upper estimate” in which those coefficients for the LTVs were 

adjusted based on additional analyses and expert opinion as a safety agency and a “lower 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

27 

estimate,” which estimates the effect if mass reduction is accomplished entirely by 

safety-conscious technologies such as material substitution. 

3. How has NHTSA refined its analysis for purposes of estimating the 

potential safety effects of this final rule? 

During the past months, NHTSA has extensively reviewed the literature on 

vehicle mass, size, and fatality risk. NHTSA now agrees with DRI and other commenters 

that it is essential to analyze the effect of mass independently from the effects of size 

parameters such as wheelbase, track width, or footprint – and that the NPRM’s “worstcase” scenario based on downsizing (in which weight, wheelbase, and track width could 

all be changed) is not useful for that purpose. The agency should instead provide 

estimates that better reflect the more likely effect of the regulation - estimating the effect 

of mass reduction that maintains footprint. 

Yet it is more difficult to analyze multiple, independent parameters than a single 

parameter (e.g., curb weight), because there is a potential concern that the near 

multicollinearity of the parameters – the strong, natural and historical correlation of mass 

and size – can lead to inaccurate statistical estimates of their effects.25 NHTSA has 

performed new statistical analyses of its historical database of passenger cars, light 

trucks, and vans (LTVs) from its 2003 report (now including also 2-door cars), assessing 

relationships between fatality risk, mass, and footprint. They are described in Sections 

2.2 (cars) and 3.2 (LTVs) of the 2010 Kahane report presented in Chapter IX of the 

FRIA. While the potential concerns associated with near multicollinearity are inherent in 

regression analyses with multiple size/mass parameters, NHTSA believes that the 

analysis approach in the 2010 Kahane report, namely a single-step regression analysis, 

generally minimizes reduces those hazards26 and models the trends in the historical data. 

The results differ substantially from DRI’s, based on a two-step regression analysis. 

Sections 2.3 and 2.4 of the 2010 Kahane report attempt to account for the differences 

primarily by applying selected techniques from DRI’s analyses to NHTSA’s database. 

The statistical analyses – logistic regressions – of trends in MYs 1991-1999 

vehicles generate one set of estimates of the possible effects of reducing mass by 100 

pounds while maintaining footprint. While these effects might conceivably carry over to 

future mass reductions, there are two reasons that future safety effects of mass reduction 

could differ from projections from historical data: 

 

25 Greene, W. H. (1993). Econometric Analysis, Second Edition. New York: Macmillan Publishing 

Company, pp. 266-268; Allison, P.D. (1999), Logistic Regression Using the SAS System. Cary, NC: SAS 

Institute Inc., pp. 48-51. The report shows variance inflation factor (VIF) scores in the 5-7 range for curb 

weight, wheelbase, and track width (or, alternatively, curb weight and footprint) in NHTSA’s database, 

exceeding the 2.5 level where near multicollinearity begins to become a concern in logistic regression 

analyses. 

26 NHTSA believes that the two-step regression is more hazardous because it weakens relationships 

between curb weight and dependent variables by splitting the effect of curb weight across the two 

regression steps, as discussed further below. 

Comment [A19]: This does not make sense to 

me. A logistic regression in and of itself does 

nothing to address multicollinearity. Unless you 

used a particular approach to reduce it, it is still 

present. Did you use an instrumental variable 

approach? Was there a way to separate out changes 

in mass and weight over time that was unavailable in 

a cross-section? This needs to be better explained, 

and if nothing additional was done to address it then 

the text should not asserted that it has been 

addressed. 

Comment [A20]: Given multicollinearity, the 

question is whether it actually does this. Can it 

isolate one from the other enough that the estimated 

parameter is actually measuring this and only this 

effect? 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

28 

 The statistical analyses are “cross-sectional” analyses that estimate the increase in 

fatality rates for vehicles weighing n-100 pounds relative to vehicles weighing n 

pounds, across the spectrum of vehicles on the road, from the lightest to the 

heaviest. They do not directly compare the fatality rates for a specific make and 

model before and after a 100–pound reduction from that model. Instead, they use 

the differences across makes and models as a surrogate for the effects of actual 

reductions within a specific model; those cross-sectional differences could include 

trends that are statistically, but not causally related to mass. 

 The manner in which mass changed across MY 1991-1999 vehicles might not be 

consistent with future mass reductions, due to the availability of newer materials 

and design methods. 

Therefore, Sections 2.5 and 3.4 of the 2010 Kahane report supplement those estimates 

with one or more scenarios in which some of the logistic regression coefficients are 

replaced by numbers based on additional analyses and NHTSA’s judgment of the likely 

effect of mass per se (the ability to transfer momentum to other vehicles or objects in a 

collision) and of what trends in the historical data could be avoided by current massreduction technologies such as materials substitution. The various scenarios may be 

viewed as a plausible range of point estimates for the effects of mass reduction while 

maintaining footprint, but they should not be construed as upper and lower bounds. 

Furthermore, being point estimates, they are themselves subject to uncertainties, such as, 

for example, the sampling errors associated with statistical analyses. 

 The principal findings and conclusions of the 2010 Kahane report are as follows: 

Passenger cars: This database with the one-step regression method of the 2003 Kahane 

report estimates an increase of 700-800 fatalities when curb weight is reduced by 100 

pounds and footprint is reduced by 0.65 square feet (the historic average footprint 

reduction per 100-pound mass reduction in cars). The regression attributes the fatality 

increase about equally to curb weight and to footprint. The results are approximately the 

same whether 2-door cars are fully included or partially included in the analysis or 

whether only 4-door cars are included (as in the 2003 report). Regressions by curb 

weight, track width and wheelbase produce findings quite similar to the regressions by 

curb weight and footprint, but the results with the single “size” variable, footprint, rather 

than the two variables, track width and wheelbase vary even less with the inclusion or 

exclusion of 2-door cars. 

In Section 2.3 of the new report, a two-step regression method that resembles 

(without exactly replicating) the approach by DRI, when applied to the same (NHTSA’s) 

crash and registration data, estimates a large benefit when mass is reduced, offset by even 

larger fatality increases when track width and wheelbase (or footprint) are reduced. 

NHTSA believes that the benefit estimated by this method is inaccurate, due to the 

potential concerns with the near multicollinearity of the parameters (curb weight, track 

Comment [A21]: A time-series does is still only 

measuring correlation, not causation.
Summary of Interagency Working Comments on Draft Rule under EO 12866 

29 

width, and wheelbase)27 even though the analysis is theoretically unbiased28. Almost any 

analysis incorporating those parameters has a possibility of inaccurate coefficients due to 

near multicollinearity; however, based on our own experience with other regression 

analyses of crash data, NHTSA believes a DRI-type two-step method augments the 

possibility of estimating inaccurate coefficients for curb weight, because it weakens 

relationships between curb weight and dependent variables by splitting the effect of curb 

weight across the two regression steps. 

In Section 2.4 of the new report, as a check on the results from the regression 

methods, NHTSA also performed what we refer to as “decile” analyses: simpler, tabular 

data analysis that compares fatality rates of cars of different mass but similar footprint. 

Decile analysis is not a precise tool because it does not control for confounding factors 

such as driver age/gender or the specific type of car, but it may be helpful in identifying 

the general directional trend in the data when footprint is held constant and curb weight 

varies. The decile analyses show that fatality risk in MY 1991-1999 cars generally 

increased and rarely decreased for lighter relative to heavier cars of the same footprint. 

They suggest that the historical, cross-sectional trend was generally in the lighter ↔ more 

fatalities direction and not in the opposite direction, as might be suggested by the 

regression coefficients from the method that resembles DRI’s approach. 

The regression coefficients from NHTSA’s one-step method suggest that mass 

and footprint each accounted for about half the fatality increase associated with 

downsizing in a cross-sectional analysis of 1991-1999 cars. They estimate the historical 

difference in societal fatality rates (i.e., including fatalities to occupants of all the vehicles 

involved in the collisions, plus any pedestrians) of cars of different curb weights but the 

same footprint. They may be considered an “upper-estimate scenario” of the effect of 

future mass reduction – if it were accomplished in a manner that resembled the historical 

cross-sectional trend – i.e., without any particular regard for safety (other than not to 

reduce footprint). 

However, NHTSA believes that future vehicle design is likely to take advantage 

of safety-conscious technologies such as materials substitution that can reduce mass 

without perceptibly changing a car’s shape or ride and maintain its structural strength. 

This could avoid much of the risk associated with lighter and smaller vehicles in the 

historical analyses, especially the historical trend toward higher crash-involvement rates 

for lighter and smaller vehicles.29 It could thereby shrink the added risk close to just the 

effects of mass per se (the ability to transfer momentum to other vehicles or objects in a 

 

27 As evidenced by VIF scores in the 5-7 range, exceeding the 2.5 level where near multicollinearity begins 

to become a concern in logistic regression analyses. 

28 Section 2.3 of the 2010 Kahane report attempts to explain why the two-step method, when applied to 

NHTSA’s 2003 database, produces results a lot like DRI’s, but it does not claim that DRI obtained its 

results from its own database for exactly those reasons. NHTSA did not analyze DRI’s database. The twostep method is “theoretically unbiased” in the sense that it seeks to estimate the same parameters as the 

one-step analysis. 

29 IIHS Advisory No. 5, July 1988, http://www.iihs.org/research/advisories/iihs_advisory_5.pdf; IIHS 

News Release, February 24, 1998, http://www.iihs.org/news/1998/iihs_news_022498.pdf; Auto Insurance 

Loss Facts, September 2009, http://www.iihs.org/research/hldi/fact_sheets/CollisionLoss_0909.pdf. 

Comment [A22]: Did you mean to have one 

direction sign from left to right? 

Comment [A23]: Please explain what you mean 

by this? 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

30 

collision). Section 2.5 of the 2010 Kahane report attempts to quantify a “lower-estimate 

scenario” for the potential effect of mass reduction achieved by safety-conscious 

technologies; the estimated effects are substantially smaller than in the upper-estimate 

scenario based directly on the regression results. 

We note, again, that the preceding paragraph is conditional. Nothing in the CAFE 

standard requires manufacturers to use material substitution or, more generally, take a 

safety-conscious approach to mass reduction and in fact the CAFÉ cost estimates do not 

estimate/assume such an approach.

30 Federal Motor Vehicle Safety Standards include 

performance tests that verify historical improvements in structural strength and 

crashworthiness, but few FMVSS provide test information that sheds light about how a 

vehicle rides or otherwise helps explain the trend toward higher crash-involvement rates 

for lighter and smaller vehicles. It is possible that using material substitution and other 

current mass reduction methods could avoid the historical trend in this area, but that 

remains to be studied as manufacturers introduce more of these vehicles into the on-road 

fleet in coming years. 

LTVs: The principal difference between LTVs and passenger cars is that mass reduction 

in the heavier LTVs is estimated to have significant societal benefits, in that it reduces the 

fatality risk for the occupants of cars and light LTVs that collide with the heavier LTVs. 

By contrast, footprint (size) reduction in LTVs has a harmful effect (for the LTVs’ own 

occupants), as in cars. The regression method of the 2003 Kahane report applied to the 

database of that report estimates a societal increase of 231 fatalities when curb weight is 

reduced by 100 pounds and footprint is reduced by 0.975 square feet (the historic average 

footprint reduction per 100-pound mass reduction in LTVs). But the regressions attribute 

an overall reduction of 266 fatalities to the 100-pound mass reduction and an increase of 

497 fatalities to the .975-square-foot footprint reduction. The regression results constitute 

one of the scenarios for the possible societal effects of future mass reduction in LTVs. 

However, NHTSA cautions that some of the regression coefficients, even by 

NHTSA’s preferred method, might not accurately model the historical trend in the data, 

possibly due to near multicollinearity of curb weight and footprint or because of the 

interaction of both of these variables with LTV type.31 Based on supplementary analyses 

and discussion in Sections 3.3 and 3.4, the new report defines an additional upperestimate scenario that NHTSA believes may more accurately reflect the historical trend in 

the data and a lower-estimate scenario that may come closer to the effects of mass per se. 

All three scenarios, however, attribute a societal fatality reduction to mass reduction in 

the heavier LTVs. 

 

30 Footprint-based standards do not specify how or where to remove mass while maintaining footprint, nor 

do they categorically forbid footprint reductions, even if they discourage them. 

31 For example, mid-size SUVs of the 1990s typically had high mass relative to their short wheelbase and 

footprint (and exceptionally high rates of fatal rollovers); minivans typically have low mass relative to their 

footprint (and low fatality rates); heavy-duty pickup trucks used extensively for work tend to have more 

mass, for the same footprint, as basic full-sized pickup trucks that are more often used for personal 

transportation. 

Comment [A24]: Please include this caveat. 

Comment [A25]: Please explain how this would 

happen? 

Comment [A26]: This is better than the section 

previously noted. Please modify previous text to 

more accurately reflect this point. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

31 

Overall effects of mass reduction while maintaining footprint in cars and LTVs: The 

immediate purpose of the new report’s analyses of relationships between fatality risk, 

mass, and footprint is to develop the four parameters that the Volpe model needs in order 

to predict the safety effects, if any, of the modeled mass reductions in MYs 2012-2016 

cars and LTVs over the lifetime of those vehicles. The four numbers are the overall 

percentage increases or decreases, per 100-pound mass reduction while holding footprint 

constant, in crash fatalities involving: (1) cars < 2,950 pounds (which was the median 

curb weight of cars in MY 1991-1999), (2) cars ≥ 2,950 pounds, (3) LTVs < 3,870 

pounds (which was the median curb weight of LTVs in those model years), and (4) LTVs 

≥ 3,870 pounds. Here are the percentage effects for each of the three alternative 

scenarios, again, the “upper-estimate scenario” and the “lower-estimate scenario” have 

been developed based on NHTSA’s expert opinion as a vehicle safety agency: 

Fatality Increase per 100-Pound Reduction (%) 

Actual Regression 

Result Scenario 

NHTSA Expert 

Opinion UpperEstimate 

Scenario32

NHTSA Expert 

Opinion LowerEstimate Scenario 

Cars < 2,950 

pounds 2.21 2.21 1.02

Cars > 2,950 

pounds 0.90 0.90 0.44

LTVs < 3,870 

pounds 0.17 0.55 0.41

LTVs > 3,870 

pounds -1.90 -0.62 -0.73

In all three scenarios, the estimated effects of a 100-pound mass reduction while 

maintaining footprint are an increase in fatalities in cars < 2,950 pounds, substantially 

smaller increases in cars ≥ 2,950 pounds and LTVs < 3,870 pounds, and a societal benefit 

for LTVs ≥ 3,870 pounds (because it reduces fatality risk to occupants of cars and lighter 

LTVs they collide with). These are the estimated effects of reducing each vehicle by 

exactly 100 pounds. However, the actual mass reduction will vary by make, model, and 

year. The aggregate effect on fatalities can only be estimated by attempting to forecast, 

as NHTSA has using inputs to the Volpe model, the mass reductions by make and model. 

It should be noted, however, that a 100-pound reduction would be 5 percent of the mass 

of a 2000-pound car but only 2 percent of a 5000-pound LTV. Thus, a forecast that mass 

will decrease by an equal or greater percentage in the heavier vehicles than in the lightest 

cars would be proportionately more influenced by the benefit for mass reduction in the 

heavy LTVs than by the fatality increases in the other groups; it is likely to result in an 

estimated net benefit under one or more of the scenarios. It should also be noted, again, 

that the three scenarios are point estimates and are subject to uncertainties, such as the 

sampling errors associated with the regression results. In the scenario based on actual 

 

32 For passenger cars, the upper-estimate scenario is the actual-regression-result scenario. 

Comment [A27]: Is this based on sales? 

Comment [A28]: Is the 0.73 more than a third of 

sales? 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

32 

regression results, the 1.96-sigma sampling errors in the above estimates are + 0.91 

percentage points for cars < 2,950 pounds and also for cars > 2,950 pounds, + 0.82 

percentage points for LTVs < 3,870 pounds, and + 1.18 percentage points for LTVs >

3,870 pounds. In other words, the fatality increase in the cars < 2,950 pounds and the 

societal fatality reduction attributed to mass reduction in the LTVs > 3,870 pounds are 

statistically significant. The sampling errors associated with the scenario based on actual 

regression results perhaps also indicate the general level of statistical noise in the other 

two scenarios. 

4. What are the estimated safety effects of this final rule? 

The table below shows the estimated safety effects of the modeled reduction in 

vehicle mass provided in the NPRM and in this final rule in order to meet the MYs 2012-

2016 standards, based on the analysis described briefly above and in much more detail in 

Chapter IX of the FRIA. These are combined results for passenger cars and light trucks. 

A positive number is an estimated increase in fatalities and a negative number (shown in 

parentheses) is an estimated reduction in fatalities over the lifetime of the model year 

vehicles compared to the MY 2011 baseline fleet. 

MY 

2012

MY 

2013

MY 

2014

MY 

2015

MY 

2016

NPRM “Worst Case” 34 54 194 313 493 

NHTSA Expert 

Opinion Final Rule 

Upper Estimate

9 14 26 24 22

NHTSA Expert 

Opinion Final Rule 

Lower Estimate

2 4 (17) (53) (80)

Actual Regression 

Result Scenario 0 2 (94) (206) (301) 

NHTSA emphasizes that the table above is based on the NHTSA’s assumptions 

about how manufacturers might choose to reduce the mass of their vehicles in response to 

the final rule, which are very similar to EPA’s assumptions. In general, as discussed 

above, the agencies assume that mass will be reduced by as much as 10 percent in the 

heaviest LTVs but only by as much as 5 percent in other vehicles and that substantial 

mass reductions will take place only in the year that models are redesigned. The actual 

mass reduction that is likely to occur in response to the standards will of course vary by 

make and model, depending on each manufacturer’s particular approach, with likely 

more opportunity for the largest LTVs that still use separate frame construction. 

The “upper estimate” presented above, as discussed in the FRIA, assumes only 

that manufacturers will reduce vehicle mass without reducing footprint. Thus, under such 

a scenario, safety effects could be somewhat adverse if, for example, manufacturers 

chose to reduce crush space associated with vehicle overhang as a way of reducing mass 

without changing footprint. The “lower estimate,” in turn, is based on the assumption 

Comment [A29]: Is this because more of weight 

reduction is in heavier trucks? Can you please 

provide a detailed explanation of how you got these 

numbers from the previous table? 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

33 

that manufacturers will reduce vehicle mass solely through methods like material 

substitution, which (under these assumptions) fully maintain not only footprint but also 

all structural integrity, and other aspects of vehicle safety. Under these scenarios, safety 

effects could be worse if mass reduction was not undertaken thoughtfully to maintain 

existing safety levels, but could also be better if it was undertaken with a thorough and 

extensive vehicle redesign to maximize both mass reduction and safety. 

 And finally, while NHTSA does not believe that the “worst-case” scenario 

presented in the NPRM is likely to occur during the MYs 2012-2016 timeframe, we 

cannot guarantee that manufacturers will never choose to reduce vehicle footprint, 

particularly if market forces lead to increased sales of small vehicles in response to sharp 

increases in the price of petroleum, though this situation would not be in direct response 

to the CAFE/GHG standards. Thus, we cannot completely reject the worst-case scenario 

for all vehicles, although we can and do recognize that the footprint-based standards will 

significantly limit the likelihood of its occurrence within the context of this rulemaking. 

In summary, the agencies recognize the balancing inherent in achieving higher 

levels of fuel economy and lower levels of CO2 emissions through reduction of vehicle 

mass. Based on the 2010 Kahane analysis that is able to separate the effects of mass 

reductions and footprint reductions, and to account better for the possibility that mass 

reduction will be accomplished entirely through methods that preserves structural 

strength and vehicle safety, the agencies now believe that the likely deleterious safety 

effects of the MYs 2012-2016 standards may be much lower than originally estimated. 

They may be close to zero, or possibly beneficial if mass reduction is carefully 

undertaken in the future and if the mass reduction in the heavier LTVs is greater (in 

absolute terms) than in passenger cars. In light of these findings, we believe that the 

balancing is reasonable. 

5. How do the agencies plan to address this issue going forward?

NHTSA and EPA believe that it is important for the agencies to conduct further 

study and research into the interaction of mass, size and safety to assist future 

rulemakings. The agencies intend to begin working collaboratively and to explore with 

DOE, CARB, and perhaps other stakeholders an interagency/ intergovernmental working 

group to evaluate all aspects of mass, size and safety. It would also be the goal of this 

team to coordinate government supported studies and independent research, to the extent 

possible, to help ensure the work is complementary to previous and ongoing research and 

to guide further research in this area. DOE’s EERE office has long funded extensive 

research into component advanced vehicle materials and vehicle mass reduction. Other 

agencies may have additional expertise that will be helpful in establishing a coordinated 

work plan. The agencies are interested in looking at the weight-safety relationship in a 

more holistic (complete vehicle) way, and thanks to this CAFE rulemaking NHTSA has 

begun to bring together parts of the agency— crashworthiness, and crash avoidance 

rulemaking offices and the agency’s Research & Development office—in an 

interdisciplinary way to better leverage the expertise of the agency. Extending this effort 

to other agencies will help to ensure that all aspects of the weight-safety relationship are 

Comment [A30]: Is there any implicit 

assumptions about center of mass?

Comment [A31]: Again, mention caveat that this 

assumes that the proportion of cars to trucks on the 

road does not change as a result of CAFÉ>

Comment [A32]: This seems overstated given 

the continued existence of multicollinearity. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

34 

considered completely and carefully with our future research. The agencies also intend to 

carefully consider comments received in response to the NPRM in developing plans for 

future studies and research and to solicit input from stakeholders. 

The agencies also plan to watch for safety effects as the U.S. light-duty vehicle 

fleet evolves in response both to the CAFE/GHG standards and to consumer preferences 

over the next several years. Additionally, as new and advanced materials and component 

smart designs are developed and commercialized, and as manufacturers implement them 

in more vehicles, it will be useful for the agencies to learn more about them and to try to 

track these vehicles in the fleet to understand the relationship between vehicle design and 

injury/fatality data. Specifically, the agencies intend to follow up with study and research 

of the following: 

First, NHTSA is in the process of contracting with an independent institution to 

review the statistical methods that NHTSA has used to analyze historical data related to 

mass, size and safety, and to provide recommendation on whether the existing methods or 

other methods should be used for future statistical analysis of historical data. This study 

is being initiated because, in response to the NPRM, NHTSA received a number of 

comments related to the methodology NHTSA used for the NPRM to determine the 

relationship between mass and safety, as discussed in detail above. 

Second, NHTSA and EPA, in consultation with DOE, intend to begin updating 

the MYs 1991-1999 database on which the safety analyses in the NPRM and final rule 

are based with newer vehicle data in the next several months. This task will take at least 

a year to complete. This study is being initiated in response to the NPRM comments 

related to the use of data from MYs 1991-1999 in the NHTSA analysis, as discussed in 

detail above. 

Third, in order to assess if the design of recent model year vehicles that 

incorporate various mass reduction methods affect the relationships among vehicle mass, 

size and safety, NHTSA and EPA intend to conduct collaborative statistical analysis, 

beginning in the next several months. The agencies intend to work with DOE to identify 

vehicles that are using material substitution and smart design. After these vehicles are 

identified, the agencies intend to assess if there are sufficient data for statistical analysis. 

If there are sufficient data, statistical analysis would be conducted to compare the 

relationship among mass, size and safety of these smart design vehicles to vehicles of 

similar size and mass with more traditional designs. This study is being initiated because, 

in response to the NPRM, NHTSA received comments related to the use of data from 

MYs 1991-1999 in the NHTSA analysis that did not include new designs that might 

change the relationship among mass, size and safety, as discussed in detail above. 

NHTSA may initiate a two-year study of the safety of the fleet through an 

analysis of the trends in structural stiffness and whether any trends identified impact 

occupant injury response in crashes. Vehicle manufacturers may employ stiffer light 

weight materials to limit occupant compartment intrusion while controlling for mass that 

may expose the occupants to higher accelerations resulting in a greater chance of injury 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

35 

in real-world crashes. This study would provide information that would increase the 

understanding of the effects on safety of newer vehicle designs. 

In addition, NHTSA and EPA, possibly in collaboration with DOE, may conduct 

a longer-term computer modeling-based design and analysis study to help determine the 

maximum potential for mass reduction in the MYs 2017-2021 timeframe, through direct 

material substitution and smart design while meeting safety regulations and guidelines, 

and maintaining vehicle size and functionality. This study may build upon prior research 

completed on vehicle mass reduction. This study would further explore the 

comprehensive vehicle effects, including dissimilar material joining technologies, 

manufacturer feasibility of both supplier and OEM, tooling costs, and crash simulation 

and perhaps eventual crash testing. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

1 

Below is a summary of interagency comments received during EO 12866 review of the draft rule 

“Joint Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emission Standards and 

Corporate Average Fuel Economy Standards”. They are for your consideration and subject to 

further policy review. 

*** 

EPA preamble section on consumer welfare – III.H.1: 

1. Conceptual Framework for Evaluating Consumer Impacts

For this rule, EPA projects significant private gains to consumers in three major areas: (1) 

reductions in spending on fuel, (2) time saved due to less refueling, and (3) welfare gains from 

additional driving that results from the rebound effect. In combination, these private savings, 

mostly from fuel savings, appear to outweigh by a large margin the costs of the program, even 

without accounting for externalities. 

Admittedly, these findings pose an economic conundrum. On the one hand, consumers 

are expected to gain significantly from the rules, as the increased cost of fuel efficient cars 

appears to be far smaller than the fuel savings. Yet these technologies are readily available; 

financially savvy consumers could have sought vehicles with improved fuel efficiency, and auto 

makers seeking those customers could have offered them. Assuming full information, perfect 

foresight, perfect competition, and financially rational consumers and producers, standard 

economic theory suggests that normal market operations would have provided the private net 

gains to consumers, and the only benefits of the rule would be due to external benefits. 

Assuming those conditions, ifIf our analysis projects that there are net private benefits that 

consumers have not realized in this perfectly functioning market, then increased fuel economy 

should be accompanied by a corresponding loss in consumer welfare. This calculation assumes 

that consumers accurately predict and act on all the benefits they will get from a new vehicle, 

and that producers market products providing those benefits. The existence of large private net 

benefits from this rule, then, suggests either that the assumptions noted above do not hold, or that 

EPA’s analysis has missed some factor(s) tied to improved fuel economy that reduce(s) 

consumer welfare. 

With respect to the latter, EPA believes the costs of the technologies developed for this 

rule take into account the cost needed to ensure that all vehicle qualities (including performance, 

reliability, and size) stay constant, except for fuel economy and vehicle price. As a result, there 

would need to be some other changed qualities that would reduce the benefits consumers receive 

from their vehicles. Changing circumstances (e.g., increased demand for horsepower in response 

to a drop in fuel prices), and any changes in vehicle attributes that manufacturers elect to make,

may result in additional private impacts onto vehicle buyers from requiring increased fuel 

economy. Most comments generally supported the cost estimates and the maintenance of vehicle 

quality, though two comments expressed concern over unspecified losses to vehicle quality. 

Even if there is some such unidentified loss (which, given existing evidence and modeling 

capabilities, is very difficult to quantify), EPA believes that under realistic assumptions, the 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

2 

private gains from the rule, together with the social gains (in the form of reduction of 

externalities), substantially outweigh the costs. 

The central conundrum has been referred to as the Energy Paradox in this setting (and in 

several others).1

 In short, the problem is that consumers appear not to purchase products that are 

in their economic self-interest. There are strong theoretical reasons why this might be so.

2

: 

 Consumers might be myopic and hence undervalue the long-term.;

 Consumersthey might lack information or a full appreciation of information even 

when it is presented.;

 Consumersthey might be especially averse to the short-term losses associated with the 

higher prices of energy efficient products (the behavioral phenomenon of “loss 

aversion”).

 ; Eeven if consumers have relevant knowledge, the benefits of energy- efficient 

vehicles might not be sufficiently salient to them at the time of purchase, and the lack 

of salience might lead consumers to neglect an attribute that it would be in their 

economic interest to consider.; or,

 Iin the case of vehicle fuel efficiency, and perhaps as a result of one or more of the 

foregoing factors, consumers may have relatively few choices to purchase vehicles 

with greater fuel economy once other characteristics, such as vehicle class, are 

chosen.3

 

A great deal of work in behavioral economics identifies and elaborates factors of this 

sort, which help account for the Energy Paradox.4 This point holds in the context of fuel savings 

(the main focus here), but it applies equally to the other private benefits, including reductions in 

refueling time and additional driving.5

 For example, it might well be questioned whether 

significant reductions in refueling time, and corresponding private savings, are fully internalized 

when consumers are making purchasing decisions.

Considerable research suggests that the Energy Paradox is real and significant but the 

literature disagreeshas not reached a consensus about the reasons for its existence. due in part to 

consumers’ inabilitySeveral researchers have found evidence suggesting that consumers do not 

give full or appropriate weight to fuel economy in purchasing decisions to value future fuel 

 

1 Jaffe, A. B., and Stavins, R. N. (1994). The Energy Paradox and the Diffusion of Conservation Technology. 

Resource and Energy Economics, 16(2), 91-122. Docket EPA-HQ-OAR-2009-0472-11415. 

2 For an overview, see id.

3

 For instance, the range of fuel economy (combined city and highway) available among all listed 2010 6-cylinder 

minivans is 18 to 20 miles per gallon. With a manual-transmission 4-cylinder minivan, it is possible to get 24 mpg. 

See http://www.fueleconomy.gov, which is jointly maintained by the U.S. Department of Energy and the EPA. For 

recent but unpublished evidence, see Hunt Alcott and Nathan Wozny, Gasoline Prices, Fuel Economy, and the 

Energy Paradox (2010, available at http://web.mit.edu/allcott/www/Allcott%20and%20Wozny%202010%20-

%20Gasoline%20Prices,%20Fuel%20Economy,%20and%20the%20Energy%20Paradox.pdf

4 Jaffe, A. B., and Stavins, R. N. (1994). The Energy Paradox and the Diffusion of Conservation Technology. 

Resource and Energy Economics, 16(2), 91-122. Docket EPA-HQ-OAR-2009-0472-11415. See also Alcott and 

Wozny, supra note.

5 For example, it might be maintained that, at the time of purchase, consumers take full account of the time spent 

refueling potentially saved by fuel-efficient cars, but it might also be questioned whether they have adequate 

information to do so, or whether that factor is sufficiently salient to play the proper role in purchasing decisions.

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0.5" + Indent at: 0.75"

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Summary of Interagency Working Comments on Draft Rule under EO 12866 

3 

savings appropriately. For example, Sanstad and Howarth (1994) argue that consumers optimize 

behavior without full information by resorting to imprecise but convenient rules of thumb. For a 

number of reasons, cConsumers face difficulty in predicting the fuel savings that they are likely 

to get from a vehicle, for a number of reasons. For instance, the calculation of fuel savings is 

complex, and consumers may not make it correctly.6 The attribute of fuel economy may be 

insufficiently salient, leading to a situation in which consumers pay less than $1 for an expected 

$1 benefit in terms of discounted gasoline costs.7 Larrick and Soll (2008) find evidence that 

consumers do not understand how to translate changes in miles-per-gallon into fuel savings (a 

concern that EPA is continuing to attempt to address).8

 In addition, future fuel price (a major 

component of fuel savings) is highly uncertain. Consumer fuel savings also vary across 

individuals, who travel different amounts and have different driving styles. Studies regularly 

show that fuel economy plays a role in consumers’ vehicle purchases, but modeling that role may 

still beis still in development, and there is no consensus that most consumers make fully 

informed tradeoffs.

9

 

Another subset of the literatureOther studies, however, findssuggest that a substantial 

portion of the Energy Paradox can be explained by rational behavior on the part of consumers. 

For instance, one set of studies finds that accounting for uncertainty in fuel savings over time due 

to unanticipated changes in fuel prices goes a long way toward explaining this paradox. In this 

case, consumers are hedging against the possibility that the upfront cost will not pay for itself in 

the event that gasoline prices are unexpectedly low.10

If there is a difference between fuel savings and consumers’ willingness to pay for fuel 

savings, the next question is, which is the appropriate measure of consumer benefit? Fuel 

 

6 Turrentine, T. and K. Kurani (2007). “Car Buyers and Fuel Economy?” Energy Policy 35: 1213-1223 (Docket 

EPA-HQ-OAR-2009-0472); Larrick, R. P., and J.B. Soll (2008). “The MPG illusion.” Science 320: 1593-1594 

(Docket EPA-HQ-OAR-2009-0472-0041).

7

 See Alcott and Wozny.

8 Sanstad, A., and R. Howarth (1994). “’Normal’ Markets, Market Imperfections, and Energy Efficiency.” Energy 

Policy 22(10): 811-818 (Docket EPA-HQ-OAR-2009-0472-11415); Larrick, R. P., and J.B. Soll (2008). “The MPG 

illusion.” Science 320: 1593-1594 (Docket EPA-HQ-OAR-2009-0472-0043). 9 Busse, Meghan R., Christopher R. Knittel, and Florian Zettelmeyer (2009). “Pain at the Pump: How Gasoline 

Prices Affect Automobile Purchasing in New and Used Markets,” Working paper (accessed 6/30/09), available at

http://www.econ.ucdavis.edu/faculty/knittel/papers/gaspaper_latest.pdf (Docket EPA-HQ-OAR-2009-0472-0044). 10 For recent but unpublished evidence in this regard, see Fan, Sallee, and West, “Do Consumers Recognize the 

Value of Fuel Economy? Evidence from Used Car Prices and Gasoline Price Fluctuations.” See also, Greene, D., J. 

German, and M. Delucchi (2009). “Fuel Economy: The Case for Market Failure” in Reducing Climate Impacts in 

the Transportation Sector, Sperling, D., and J. Cannon, eds. Springer Science; Dasgupta, S., S. Siddarth, and J. 

Silva-Risso (2007). “To Lease or to Buy? A Structural Model of a Consumer’s Vehicle and Contract Choice 

Decisions.” Journal of Marketing Research 44: 490 – 502; Metcalf, G., and D. Rosenthal (1995). "The ‘New’ View 

of Investment Decisions and Public Policy Analysis: An Application to Green Lights and Cold Refrigerators,’’ 

Journal of Policy Analysis and Management 14: 517–531. Metcalf and Hassett (1995). "Energy Tax Credits and 

Residential Conservation Investment: Evidence from Panel Data" Journal of Public Economics 57: 201-217. 

Metcalf, G., and K. Hassett (1999). "Measuring the Energy Savings from Home Improvement Investments: 

Evidence from Monthly Billing Data." The Review of Economics and Statistics 81(3): 516-528; van Soest D., Bulte 

E. (2000). “Does the Energy-Efficiency Paradox Exist? Technological Progress and Uncertainty.” Environmental 

and Resource Economics 18: 101–12.

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Summary of Interagency Working Comments on Draft Rule under EO 12866 

4 

savings measure the actual monetary value that consumers will receive after purchasing a 

vehicle; the willingness to pay for fuel economy measures the value that, before a purchase, 

consumers place on additional fuel economy. As noted, there are a number of reasons that 

consumers may incorrectly estimate the benefits that they get from improved fuel economy, 

including risk or loss aversion, and poor ability to estimate calculate savings. In additionAlso as 

noted, fuel economy may not be as salient as other vehicle characteristics when a consumer is 

considering vehicles. If these arguments are valid, then there will be significant gains to 

consumers of the government mandating additional fuel economy. 

EPA requested and received a number of comments discussing the role of the Energy 

Paradox in consumer vehicle purchase decisions. Ten commenters, primarily from a number of 

academic and non-governmental organizations, supported the existence ofargued that there is a 

gap between the fuel economy that consumers purchased and the cost-effective amount, due to a 

number of market and behavioral phenomena. These include consumers having inadequate 

information about future fuel savings relative to up-front costs; imperfect competition among 

auto manufacturers; lack of choice over fuel economy within classes; lack of salience of fuel 

economy relative to other vehicle features at the time of vehicle purchase; consumers 

usinconsumer use ofg heuristic decision-making processes or other rules of thumb, rather than 

analyzing fuel economy decisions; consumer risk and loss aversion leading to more attention to 

up-front costs than future fuel savings; and consumer emphasis on visible, status-providing 

features of vehicles more than on relatively invisible features such as fuel economy. The RIA, 

Chapter 8.1.2, includes further discussion of these phenomena. 

Because of the gap between the fuel economy consumers purchase and the cost-effective 

amount, those and additional commenters support using the full value of fuel savings as a benefit 

of the rule, because consumers will spend less money on fuel. A few asserted, in addition, that 

auto companies would benefit from offering vehicles with improved fuel economy. Automakers 

might underprovide fuel economy because they believe consumers would not buy it, or that it is 

not as salient as price when consumers are buying a vehicle. The commenters who supported the 

existence of the gap cite these phenomena as a basis for regulation of fuel economy. In contrast, 

two commenters (the United Auto Workers and one nonprofit research organization) argued that 

the market for fuel economy works efficiently; consumers reveal through their purchase 

decisions thatmake appropriate tradeoffs with respect to additional fuel economy is not important 

for them.economy. These commenters expressed concern that regulation to promote more fuel 

economy would limit consumers’ choices as well as the value of the vehicles to consumers. Yet 

other commenters (including some states) noted that the rule protects the existing variety and 

choice of vehicles in the market; for this reason, the value of vehicles to consumers should not 

suffer due toas a result the rule. 

While acknowledging the diversity of perspectives, EPA continues to include the full fuel 

savings as a privateprivate benefits of the rule. Improved fuel economy will significantly reduce 

consumer expenditures on fuel, thus benefiting consumers. However,It is true that limitations in 

modeling affect our ability to estimate how much of these savings would have occurred in the 

absence of the rule. For example, some of the technologies predicted to be adopted in response 

to the rule may already be taking placedeveloping due to shifts in consumer demand for fuel 

economy. It is possible that some of these savings would have occurred in the absence of the 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

5 

rule. If so, then some of the fuel savings, as well as some of the costs of the technology to 

achieve those savings, may be due to market forces, not to the rule itself. In the absence of 

robust means to identify the changes in fuel economy that would have occurred without the rule, 

we estimate the benefits and costs under the assumption that the rule will lead to more fuelefficient vehicles than would have occurred without the rule. As discussed below, limitations in 

modeling also affect our ability to estimate the effects of the rule on net benefits in the market for 

vehicles. 

Consumer vehicle choice models estimate what vehicles consumers buy based on vehicle 

and consumer characteristics. In principle, they such models could provide a means of 

understanding both the role of fuel economy in consumers’ purchase decisions and the effects of 

this rule on the benefits that consumers will get from vehicles. The NPRM included a discussion 

of the wide variation in the structure and results of these models. Models or model results have 

not frequently been systematically compared to each other. When they have, the results show 

large variation over, for instance, the value that consumers place on additional fuel economy. As 

a result, EPA found that further assessment needed to be done before adopting a consumer 

vehicle choice model. In the NPRM, EPA asked for comment on the state of the art of consumer 

vehicle choice modeling and whether it is sufficiently developed for use in regulatory analysis. 

The responses were varied. Of the six commenters on this issue, five supported EPA’s 

performing consumer vehicle choice modeling, but only in general terms; they did not provide 

recommendations for how to evaluate the quality of different models or identify a model 

appropriate for EPA’s purposes. One commenter argued that, if key differences across models 

were controlled, then different models would produce similar results, but there were no 

suggestions for what choices to make to control the key differences. One commenter specifically 

asked for estimates that quantify losses to consumer welfare. Two commenters mentioned the 

importance of taking into account any losses in vehicle attributes due to increasing fuel 

economy, but without specific guidance for how to do so. Some commenters, including some 

who supported the use of these models, highlighted some of the models’ potential limitations. 

Two commenters noted the challenges of modeling for vehicles that are not yet in the market. 

Most consumer vehicle choice models are based on existing vehicle fleets. Future vehicles will 

present combinations of vehicle characteristics not previously seen in markets, such as higher 

fuel economy and higher price with other characteristics constant; the existing models may not 

do well in predicting consumer responses to these changes. One comment suggested that the 

models might be sufficient for predicting changes in consumer purchase patterns, but not for 

calculating the welfare gains and losses to consumers of the changes. 

EPA has not used a consumer vehicle choice model for the final rule analysis, due to 

concerns we explained in the proposal (and discussed in Chapter 8.1 of the RIA), and because no 

new information became available to resolve those concerns. In fact, a recent review 

commissioned by EPA supports the finding of great variability, by looking at one key parameter: 

the role of fuel economy in consumers’ vehicle purchase decisions.11 It The review finds no 

consensus on the role of fuel economy in consumer purchase decisions. Of 22 studies, 

approximately equal numbers find that consumers undervalue, overvalue, or value approximately 

 

11 Greene, David L. XX- to fill in later 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

6 

correctly the fuel savings that they will receive from improved fuel economy. The variation in 

the value of fuel economy in these studies is so high that it appears to be inappropriate to identify 

one central estimate from the literature. Thus, estimating consumer response to higher vehicle 

fuel economy is still unsettled science. It is likely that this variation exists as well in measuring 

consumer response to changes in other vehicle characteristics, such as performance. Thus, there 

does not appear to be evidence at this time to develop robust estimates of consumer welfare 

effects of changes in vehicle attributes. As noted earlier, EPA’s and NHTSA’s cost estimates are 

based on maintaining these other vehicle attributes. Comments generally supported the finding 

that our cost and technology estimates succeeded in maintaining these other attributes. 

EPA will continue its efforts to review the literature, but, given the known difficulties, 

EPA has not conducted an analysis using these models for this program. These issues are 

discussed in detail in RIA Chapter 8.1.2. 

The next issue is the potential for loss in consumer welfare due to the rule. As mentioned 

above (and discussed more thoroughly in Section III.D of this preamble), the technology cost 

estimates developed here take into account the costs to hold other vehicle attributes, such as size 

and performance, constant. In addition, the analysis assumes that the full technology costs are 

passed along to consumers. With these assumptions, because welfare losses are monetary 

estimates of how much consumers would have to be compensated to be made as well off as in 

the absence of the change,12 the price increase measures the loss to the consumer.13 Assuming 

that the full technology cost gets passed along to the consumer as an increase in price, the 

technology cost thus measures the welfare loss to the consumer. Increasing fuel economy would 

have to lead to other changes in the vehicles that consumers find undesirable for there to be 

additional losses not included in the technology costs. 

At this time EPA has no available methods to estimate potential additional effects on 

consumers not included in the technology cost estimates, e.g., due to changes in vehicles that 

consumers find undesirable, shifts in consumer demand for other attributes, and uncertainties 

about the long term reliability of new technologies. Comments on the rule generally supported 

EPA’s analysis of the technology costs and the assumption that other vehicle characteristics were 

not adversely affected. Any consumer welfare loss cannot be quantified at this time. For reasons 

stated above, EPA believes that any such loss is likely far smaller than the private gains, 

including fuel savings and reduced refueling time.

 

12 This approach describes the economic concept of compensating variation, a payment of money after a change that 

would make a consumer as well off after the change as before it. A related concept, equivalent variation, estimates 

the income change that would be an alternative to the change taking place. The difference between them is whether 

the consumer’s point of reference is her welfare before the change (compensating variation) or after the change 

(equivalent variation). In practice, these two measures are typically very close together. 13 Indeed, it is likely to be an overestimate of the loss to the consumer, because the consumer has choices other than 

buying the same vehicle with a higher price; she could choose a different vehicle, or decide not to buy a new 

vehicle. The consumer would choose one of those options only if the alternative involves less loss than paying the 

higher price. Thus, the increase in price that the consumer faces would be the upper bound of loss of consumer 

welfare, unless there are other changes to the vehicle due to the fuel economy improvements that make the vehicle 

less desirable to consumers. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

7 

Chapter 8.1 of the RIA discusses in more depth the research on the Energy Paradox and 

the state of the art of consumer vehicle choice modeling. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

8 

NHTSA preamble section on consumer welfare – IV.G.6: 

6. Potential Unquantified Consumer Welfare Impacts of The Final Standards

 The underlying premise goal of the CAFE and GHG standards is to increase social 

welfare, in the broadest sense, and as shown in earlier sections, NHTSA projects that the MY 

2012-2016 CAFE standards will yield large positive net social benefits. In its net benefits 

analysis, NHTSA made every attempt to include all of the costs and benefits that could be 

identified and quantified. 

 It is important to highlight several features of the rulemaking analysis that NHTSA 

believes gives high confidence to its conclusion that there are large net social benefits from these 

standards. First, the agencies adopted footprint-based standards in large part so that the full 

range of vehicle choices in the marketplace could be maintained. Second, the agencies 

performed a very rigorous technological feasibility, cost, and leadtime analysis that showed that 

the standards could be met while maintaining current levels of other vehicle attributes such as 

safety, utility, and performance. Third, widespread automaker support for the standards, in 

conjunction with the future product plans that have been provided by automakers to the agencies,

and recent industry announcements on new product offerings, provides further indication that the 

standards can be met while retaining the full spectrum of vehicle choices. 

 

Notwithstanding these points, and its high degree of confidence that the benefits amply 

justify the costs, NHTSA recognizes the possibility that there may beof consumer welfare 

impacts that are not accounted for in its social welfare analysis. The agencies received public 

comments expressing diverging views on this issue. While theThe majority of commenters on 

this issue suggested that potential losses in welfare from requiring higher fuel economy waswere

un likely to be only a minor issuea significant concern because of the many possible 

reasonsimperfections in why the market for fuel economy does not function perfectlyeconomy. 

But, other comments suggested that potential unidentified and unquantified consumer welfare 

losses could be large. This section identifies the potential issues and summarizes the key public 

comments. Acknowledging the comments, tThe FRIA provides a sensitivity analysis showing 

how various levels of unidentified consumer welfare losses would affect the projected net social 

benefits from the CAFE standards established by this final rule. 

There are two viewpoints for evaluating the costs and benefits of the proposed increase in 

CAFE standards: the private perspective of vehicle buyers themselves on the higher fuel 

economy levels the proposed rule would require, and the economy-wide or “social” perspective 

on the costs and benefits of requiring higher fuel economy. It is important, in short, to distinguish

between costs and benefits that are “private” and costs and benefits that are “social.” The 

agency’s analysis of benefits and costs from requiring higher fuel efficiency, presented above, 

includes sseveralome categories of benefits (“social benefits”) that are not limited to automobile 

purchasers and that extend throughout the U.S. economy, such as reductions in the energy 

security costs associated with U.S. petroleum imports and in the economic damages expected to 

result from climate change. In contrast, other categories of benefits – principally the economic 

value of future fuel savings projected to result from higher fuel economy – will be experienced 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

9 

exclusively by the initial purchasers and subsequent owners of vehicle models whose fuel 

economy manufacturers elect to improve as part of their strategies for complying with higher 

CAFE standards (“private benefits”). 

Although the economy-wide or “social” benefits from requiring higher fuel economy 

represent an important share of the total economic benefits from raising CAFE standards, 

NHTSA estimates that benefits to vehicle buyers themselves will significantly exceed the costs of 

complying with the stricter fuel economy standards this rule establishes, as shown above. Since 

the agency also assumes that the costs of new technologies manufacturers will employ to 

improve fuel economy will ultimately be shifted to vehicle buyers in the form of higher purchase 

prices, NHTSA concludes that the benefits to vehicle buyers from requiring higher fuel 

efficiency will far outweigh the costs they will be required to pay to obtain it. However, this 

raises the question of why current purchasing patterns do not already result in higher average 

fuel economy, and why stricter fuel efficiency standards should be necessary to achieve that 

goal. 

 

As an illustration, Table IV.G.6-1 reports the agency’s estimates of the average lifetime 

values of fuel savings for MY 2012-2016 passenger cars and light trucks calculated using future 

retail fuel prices, which are those likely to be used by vehicle buyers to project the value of fuel 

savings they expect from higher fuel economy. The table compares NHTSA’s estimates of the 

average lifetime value of fuel savings for cars and light trucks to the price increases it projects to 

result as manufacturers attempt to recover their costs for complying with increased CAFE 

standards for those model years by increasing vehicle sales prices. As the table shows, the 

agency’s estimates of the present value of lifetime fuel savings (discounted using the OMBrecommended 3% rate) substantially outweigh projected vehicle price increases for both cars 

and light trucks in every model year, even under the assumption that all of manufacturers’ 

technology outlays are passed on to buyers in the form of higher selling prices for new cars and 

light trucks. By model year 2016, NHTSA projects that average lifetime fuel savings will 

exceed the average price increase by more than $2,000 for cars, and by more than $2,700 for 

light trucks. 

Table IV.G.6-1 

Value of Lifetime Fuel Savings vs. Vehicle Price Increases

 

Fleet Measure Model year 

2012 2013 2014 2015 2016 

Passenger 

Cars 

Value of Fuel Savings $759 $1,349 $1,914 $2,480 $2,932 

Average Price Increase $505 $573 $690 $799 $907

Difference $255 $897 $1,264 $1,680 $2,025 

 

Light 

Trucks 

Value of Fuel Savings $828 $1,634 $2,277 $2,887 $3,700 

Average Price Increase $322 $416 $621 $752 $961 

Difference $506 $1,218 $1,656 $2,135 $2,739 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

10 

The comparisons above raise the question of why current vehicle purchasing patterns do 

not already result in average fuel economy levels approaching those that this rule would require, 

and why stricter CAFE standards should be necessary to increase the fuel economy of new cars 

and light trucks. They also raise the question of why manufacturers do not elect to provide 

higher fuel economy even in the absence of increases in CAFE standards, since the comparisons 

in Table IV.G.6-1 suggest that doing so would reduce the effective price of purchasing many 

new vehicle models, and thus to increase sales of new vehicles. More specifically, why would 

potential buyers of new vehicles hesitate to make investments in higher fuel economy that would 

produce the substantial economic returns illustrated by the comparisons presented in Table 

IV.G.6-1? And why would manufacturers voluntarily forego opportunities to increase the 

attractiveness, value, and competitive positioning of their car and light truck models by 

improving their fuel economy? 

The majority of comments received on this topic answered this question by pointing out 

many reasons why the market for vehicle fuel economy does not appear to work perfectly, and 

accordingly, that properly designed CAFE standards would be expected to increase consumer 

welfare. Some of these imperfections might stem from standard market failures (such as an 

absence of adequate information on the part of consumers); some of them might involve findings

in behavioral economics (including, for example, a lack of sufficient consumer attention to longterm savings, or a lack of salience, to consumers at the time of purchase, of relevant benefits, 

including fuel and time savings). Both theoretical and empirical research suggests that many 

consumers do not make energy-efficient investments even when those investments would pay off 

in the relatively short-term.14 This research is in line with related findings that consumers may 

underweight benefits and costs that are less salient or that will be realized only in the future.15 

Published literatureExisting work also provides some support for the agency’s assertion 

conclusion that the benefits buyers will experience from higher fuel economy far outweigh the 

costs they will pay to acquire those benefits, by identifying plausible – if short-sighted – aspects 

of normal behavior that may make buyers reluctant to purchase vehicles whose higher fuel 

economy offers an attractive return. For example, consumers’ understandable aversion to the 

prospect of losses (“loss aversion”) from making investments that do not produce their expected 

returns may exaggerate their uncertaproduce an exaggerated sense of uncertainty about the value 

of future fuel savings,s sufficiently to make making consumers reluctant to purchaseing a more 

fuel-efficient vehicle seem unattractive, even when doing so is likely to be a sound economic 

decision. As an illustrationCompare the finding in, Greene et al. (2009), to the effect find that 

the expected net present value of increasing the fuel economy of a passenger car from 28 to 35 

 

14 Jaffe, A. B., and Stavins, R. N. (1994). The Energy Paradox and the Diffusion of Conservation Technology. 

Resource and Energy Economics, 16(2); see Hunt Alcott and Nathan Wozny, Gasoline Prices, Fuel Economy, and 

the Energy Paradox (2010, available at http://web.mit.edu/allcott/www/Allcott%20and%20Wozny%202010%20-

%20Gasoline%20Prices,%20Fuel%20Economy,%20and%20the%20Energy%20Paradox.pdf

15 Hossain, Janjim, and John Morgan (2009). “. . . Plus Shipping and Handling: Revenue (Non)Equivalence in Field 

Experiments on eBay,” Advances in Economic Analysis and Policy vol. 6; Barber, Brad, Terrence Odean, and Lu 

Zheng (2005). “Out of Sight, Out of Mind: The Effectsof Expenses on Mutual Fund Flows,” Journal of Business 

vol. 78, no. 6, pp. 2095-2020.
Summary of Interagency Working Comments on Draft Rule under EO 12866 

11 

miles per gallon falls from $405 when calculated using standard net present value calculations, to 

nearly zero when uncertainty regarding future cost savings is taken into account.16

The well-known finding that as gas prices rise, consumers show more willingness to pay 

for fuel-efficient vehicles is not in consistent with the possibility that many consumers 

undervalue gasoline costs and fuel economy at the time of purchase. In ordinary circumstances, 

such costs may be a relatively “shrouded” attribute in consumers’ decisions, in part because the 

savings are cumulative and extend over a significant period of time this claim fits well with 

recent findings to the effect that many consumers are willing to pay less than $1 upfront to obtain 

a $1 benefit reduction in discounted gasoline costs.17 

 

Some research suggests that the consumers’ apparent unwillingness to purchase more 

fuel efficient vehicles stems from their inability to value future fuel savings correctly. For 

example, Larrick and Soll (2008) find evidence that consumers do not understand how to 

translate changes in fuel economy, which is denominated in miles per gallon, into resulting 

changes in fuel consumption, measured in gallons per time period.18 Sanstad and Howarth 

(1994) argue that consumers resort to imprecise but convenient rules of thumb to compare 

vehicles that offer different fuel economy ratings, and that this behavior can cause many buyers 

to underestimate the value of fuel savings, particularly from significant increases in fuel 

economy.19 If the behavior identified in these studies is widespread, then the agency’s estimates 

suggesting that the benefits to vehicle owners from requiring higher fuel economy significantly 

exceeds the costs of providing it may indeed be correct. 

Another possible reconciliation of the agency’s claim that the average vehicle buyer will 

experience large fuel savings from the higher CAFE standards this rule establishes with the fact 

that the average fuel economy of vehicles currently purchased falls well short of the new 

standards is that the values consumers place on the future savings they expect to obtain from 

higher fuel economy vary widely. As an illustration, one recent review of consumers’ 

willingness to pay for improved fuel economy found estimates that varied from less than 1% to 

almost ten times the present value of the resulting fuel savings when those are discounted at 7% 

over the vehicle’s expected lifetime.20 Although theThe wide variation in these estimates 

undoubtedly reflects methodological and measurement differences among the studies surveyed. 

But, it may also reveal that the expected savings from purchasing a vehicle with higher fuel 

 

16 Greene, D., J. German, and M. Delucchi (2009). “Fuel Economy: The Case for Market Failure” in Reducing 

Climate Impacts in the Transportation Sector, Sperling, D., and J. Cannon, eds. Springer Science. Surprisingly, the 

authors find that uncertainty regarding the future price of gasoline appears to be less important than uncertainty 

surrounding the expected lifetimes of new vehicles. 

17 See Alcott and Wozny.

18 Larrick, R. P., and J.B. Soll (2008). “The MPG illusion.” Science 320: 1593-1594. 19 Sanstad, A., and R. Howarth (1994). “’Normal’ Markets, Market Imperfections, and Energy Efficiency.” Energy 

Policy 22(10): 811-818. 

20 Greene, David L., “How Consumers Value Fuel Economy: A Literature Review,” Draft report to U.S. 

Environmental Protection Agency, Oak Ridge National Laboratory, December 29, 2009; see Table 10, p. 37. 

?? See also? David Greene and Jin-Tan Liu (1988). “Automotive Fuel Economy Improvements and Consumers’ 

Surplus.” Transportation Research Part A 22A(3): 203-218. The study actually calculated the willingness to pay for 

reduced vehicle operating costs, of which vehicle fuel economy is a major component.
Summary of Interagency Working Comments on Draft Rule under EO 12866 

12 

economy vary widely among individuals, because they travel different amounts, have different 

driving styles, or have different expectations about future fuel prices. 

These differences may be reflected in the factreflect the possibility that many or most

buyers with high valuations of increased fuel economy already purchase vehicle models that 

offer it, while those with lower values of fuel economy emphasize other vehicle attributes in their 

purchasing decisions. A related possibility is that because the effects of differing fuel economy 

levels are relatively modest when compared to those provided by other, more prominent features 

of new vehicles – passenger and cargo-carrying capacity, performance, safety, etc. – it is simply 

not in many shoppers’ interest to spend the time and effort necessary to determine the economic 

value of higher fuel economy, attempt to isolate the component of a new vehicle’s selling price 

that is related to its fuel economy, and compare these two. (This possibility is consistent with the 

view that fuel economy is a relatively “shrouded” attribute.) In either case, although thethe

agency’s estimates of the average value of fuel savings that will result from requiring cars and 

light trucks to achieve higher fuel economy may be correct, but, they those savings may not be 

large enough to lead a sufficient number of buyers to push for vehicles with higher fuel economy 

to increase average fuel economy from its current levels. 

Defects in the market for cars and light trucks could also lead manufacturers to 

undersupply fuel economy, even in cases where many buyers were willing to pay the increased 

prices necessary to provide it. To be sure, the relevant market, taken as a whole, has a great deal 

of competition. But Most obviouslyeven in those circumstances, an absence of vigorous 

competition among producers of cars and light trucks may lead manufacturers to undersupply 

attributes that contribute to the overall quality of new vehicles, including fuel economy, because 

such “imperfect” competition reduces producers’ profit incentive to supply the level of fuel 

economy that buyers are willing to pay forthere may not such competition with respect to all 

vehicle attributes. Incomplete or “asymmetric” access to information on vehicle attributes such 

as fuel economy – whereby manufacturers of new vehicles or sellers of used cars and light trucks 

have more complete knowledge of vehicles’ actual fuel economy levels, or ofof the value of 

purchasing higher fuel economy, than do potential buyers – may also prevents sellers of new or 

used vehicles from capturing its full value. In this situation, the level of fuel efficiency provided 

in the markets for new or used vehicles might remain persistently lower than that demanded by 

potential buyers (at least if they are well-informed). 

It is also possible that deliberate decisions by manufacturers of cars and light trucks, 

rather than constraints on the combinations of fuel economy, carrying capacity, and performance 

that manufacturers can offer using current technologies, limit the range of fuel economy 

available to buyers within individual vehicle market segments, such as full-size automobiles, 

small SUVs, or minivans. As an illustration, once a potential buyer has decided to purchase a 

minivan, the range of fuel economy among current models extends only from 18 to 24 mpg.21 

Manufacturers might make such decisions if they underestimate the premiums that shoppers in 

certain market segments are willing to pay for more fuel-efficient versions of the vehicle models 

thy currently offer to prospective buyers within those segments. If this occurs, manufacturers 

 

21 This is the range of combined city and highway fuel economy levels from lowest (Toyota Siena 4WD) to highest 

(Mazda 5) available for model year 2010; http://www.fueleconomy.gov/feg/bestworstEPAtrucks.htm (last accessed 

February 15, 2010). 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

13 

may fail to supply levels of fuel efficiency as high as those buyers are willing to pay for, and the 

average fuel efficiency of their entire new vehicle fleets could remain below the levels that 

potential buyers demand and are willing to pay for. (Of course this possibility is most realistic if 

it is also assumed that buyers are imperfectly informed or if fuel economy savings are not 

sufficiently salient.)

Finally, some research suggests that the consumers’ apparent unwillingness to purchase 

more fuel efficient vehicles stems from their inability to value future fuel savings correctly. For 

example, Larrick and Soll (2008) find evidence that consumers do not understand how to 

translate changes in fuel economy, which is denominated in miles per gallon, into resulting 

changes in fuel consumption, measured in gallons per time period.22 Sanstad and Howarth 

(1994) argue that consumers resort to imprecise but convenient rules of thumb to compare 

vehicles that offer different fuel economy ratings, and that this behavior can cause many buyers 

to underestimate the value of fuel savings, particularly from significant increases in fuel 

economy.

23 If the behavior identified in these studies is indeed widespread, then the agency’s 

calculations suggesting that the benefits to vehicle owners from requiring higher fuel economy 

significantly exceeds the costs of providing it may indeed be correct, yet the resulting difference 

is still insufficient to motivate buyers to purchase a mix of car or light truck vehicle models 

whose average fuel economy approaches those required by this rule.

 

 However, other commenters suggested that, if one assumes a perfectly functioning 

market, there must be unidentified consumer welfare losses that would offset the private fuel 

savings that consumers are currently foregoing. 

One explanation for this apparent paradox is that NHTSA’s estimates of benefits and 

costs from requiring manufacturers to improve the fuel efficiency of their vehicle models do not 

match potential vehicle buyers’ assessment of the likely benefits and costs from requiring higher 

fuel efficiency. This could occur because the agency’s underlying assumptions about some of 

the factors that affect the value of fuel savings differ from those made by potential buyers, 

because NHTSA has used different estimates for some components of the benefits from saving 

fuel than do buyers, or because the agency has failed to account for some potential costs of 

achieving higher fuel economy. 

For example, buyers may not value increased fuel economy as highly as the agencies’ 

calculations suggest, because they have shorter time horizons than the full vehicle lifetimes 

assumed by NHTSA and EPA, or because, when buying vehicles, they discount future fuel 

future savings using higher rates than those prescribed by OMB for evaluating federal 

regulations. Potential buyers may also anticipate lower fuel prices in the future than those 

forecast by the Energy Information Administration, or may expect larger differences between 

vehicles’ rated and actual on-road mpg levels than the agencies estimate. 

 

22 Larrick, R. P., and J.B. Soll (2008). “The MPG illusion.” Science 320: 1593-1594. 23 Sanstad, A., and R. Howarth (1994). “’Normal’ Markets, Market Imperfections, and Energy Efficiency.” Energy 

Policy 22(10): 811-818. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

14 

To illustrate the first of these possibilities, Table IV.G.6-2 shows the effect of differing 

assumptions about vehicle buyers’ time horizons for assessing the value of future fuel savings. 

Specifically, the table compares the average value of fuel savings from purchasing a MY 2016 

car or light truck when fuel savings are evaluated over different time horizons to the estimated 

increase in its price. This table shows that as reported previously in Table IV.G.6-2, when fuel 

savings are evaluated over the entire expected lifetime of a MY 2016 car (approximately 14 

years) or light truck (about 16 years), their discounted present value (using the OMBrecommended 3% discount rate) lifetime fuel savings exceeds the estimated average price 

increase by more than $2,000 for cars and by more than $2,700 for light trucks. 

If buyers are instead assumed to consider fuel savings over a 10-year time horizon, 

however, the present value of fuel savings exceeds the projected price increase for a MY 2016 

car by about $1,300, and by somewhat more than $1,500 for a MY 2016 light truck. Finally, 

Table VI.G.6-2 shows that under the assumption that if buyers consider fuel savings only over 

the length of time for which they typically finance new car purchases (slightly more than 5 years 

during 2009), the value of fuel savings exceeds the estimated increase in the price of a MY 2016 

car by only about $350, and the corresponding difference is reduced to slightly more than $500 

for a MY 2016 light truck. 

Table IV.G.6-2 

Value of Fuel Savings vs. Vehicle Price Increases 

with Alternative Assumptions about Vehicle Buyer Time Horizons 

Vehicle Measure 

Value over Alternative Time Horizons 

Expected 

Lifetime24 10 Years Average Loan 

Term25

MY 2016 

Passenger 

Car 

Fuel Savings $2,932 $2,180 $1,254 

Price Increase $907 $907 $907 

Difference $2,025 $1,273 $347 

MY 2016 

Light Truck 

Fuel Savings $3,700 $2,508 $1,484 

Price Increase $961 $961 $961 

Difference $2,739 $1,547 $523 

Potential vehicle buyers may also discount future fuel future savings using higher rates 

than those typically used to evaluate federal regulations. OMB guidance prescribes that future 

benefits and costs of regulations that mainly affect private consumption decisions, as will be the 

case if manufacturers’ costs for complying with higher fuel economy standards are passed on to 

vehicle buyers, should be discounted using a consumption rate of time preference.26 OMB 

 

24 Expected lifetimes are approximately 14 years for cars and 16 years for light trucks. 

25 Average term on new vehicle loans made by auto finance companies during 2009 was 62 months; see Board of 

Governors of the Federal Reserve System, Federal Reserve Statistical Release G.19, Consumer Credit. Available at

http://www.federalreserve.gov/releases/g19/Current (last accessed March 1, 2010). 26 Office of Management and Budget, Circular A-4, “Regulatory Analysis,” September 17, 2003, 33. Available at

http://www.whitehouse.gov/omb/assets/regulatory_matters_pdf/a-4.pdf (last accessed March 1, 2009).
Summary of Interagency Working Comments on Draft Rule under EO 12866 

15 

estimates that savers currently discount future consumption at an average real or inflationadjusted rate of about 3 percent when they face little risk about its likely level, which makes it a 

reasonable estimate of the consumption rate of time preference. However, vehicle buyers may 

view the value of future fuel savings that results from purchasing a vehicle with higher fuel 

economy as risky or uncertain, or they may instead discount future consumption at rates 

reflecting their costs for financing the higher capital outlays required to purchase more fuelefficient models. In either case, they may discount future fuel savings at rates well above the 3% 

assumed in NHTSA’s evaluation in their purchase decisions. 

Table IV.G.6-3 shows the effect of higher discount rates on vehicle buyers’ evaluation of 

the fuel savings projected to result from the CAFE standards established by this rule, again using 

MY 2016 passenger cars and light trucks as an example. As Table IV.G.6-1 showed previously, 

average future fuel savings discounted at the OMB 3% consumer rate exceed the agency’s 

estimated price increases by more than $2,000 for MY 2016 passenger cars and by more than 

$2,700 for MY 2016 light trucks. If vehicle buyers instead discount future fuel savings at the 

average new-car loan rate during 2009 (6.7%), however, these differences decline to slightly 

more than $1,400 for cars and $1,900 for light trucks, as Table IV.G.6-3 illustrates. 

This is a particularly plausible alternative assumption, because buyers are likely to 

finance the increases in purchase prices resulting from compliance with higher CAFE standards 

as part of the process financing the vehicle purchase itself. Finally, as the table also shows, 

discounting future fuel savings using a consumer credit card rate (which averaged 13.4% during 

2009) reduces these differences to less than $800 for a MY 2016 passenger car and less than 

$1,100 for the typical MY 2016 light truck. Note, however, that eEven at these higher discount 

rates, the private net benefits from purchasing more fuel efficient vehicles remain large. 

Table IV.G.6-3 

Value of Fuel Savings vs. Vehicle Price Increases 

with Alternative Assumptions about Consumer Discount Rates

Vehicle Measure 

Value over Alternative Time Horizons 

OMB 

Consumer 

Rate (3%) 

New Car 

Loan Rate 

(6.7%)27

OMB 

Investment 

Rate (7%) 

Consumer 

Credit Card 

Rate 

(13.4%)28

MY 2016 

Passenger 

Car 

Fuel Savings $2,932 $2,336 $2,300 $1,669 

Price Increase $907 $907 $907 $907 

Difference $2,025 $1,429 $1,393 $762 

 

27 Average rate on 48-month new vehicle loans made by commercial banks during 2009 was 6.72%; see Board of 

Governors of the Federal Reserve System, Federal Reserve Statistical Release G.19, Consumer Credit. Available at

http://www.federalreserve.gov/releases/g19/Current (last accessed March 1, 2010). 28 Average rate on consumer credit card accounts at commercial banks during 2009 was 13.4%; see Board of 

Governors of the Federal Reserve System, Federal Reserve Statistical Release G.19, Consumer Credit. Available at

http://www.federalreserve.gov/releases/g19/Current (last accessed March 1, 2010). 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

16 

MY 2016 

Light Truck 

Fuel Savings $3,700 $2,884 $2,836 $2,030 

Price Increase $961 $961 $961 $961 

Difference $2,739 $1,923 $1,875 $1,069 

Combinations of a shorter time horizon and a higher discount rate could further reduce or 

even eliminate the difference between the value of fuel savings and the agency’s estimates of 

increases in vehicle prices. One plausible combination would be for buyers to discount fuel 

savings over the term of a new car loan, using the interest rate on that loan as a discount rate. 

Doing so would reduce the amount by which future fuel savings exceed the estimated increase in 

the prices of MY 2016 vehicles to about $340 for passenger cars and $570 for light trucks. Some 

evidence also suggests directly that vehicle buyers may employ combinations of higher discount 

rates and shorter time horizons for their purchase decisions; for example, consumers surveyed by 

Kubik (2006) reported that fuel savings would have to be adequate to pay back the additional 

purchase price of a more fuel-efficient vehicle in less than 3 years to persuade a typical buyer to 

purchase it. 29 As these comparisons and evidence illustrate, reasonable alternative assumptions 

about how consumers might evaluate the major benefit from requiring higher fuel economy can 

significantly affect the benefits they expect to receive when they decide to purchase a new 

vehicle. 

Many plausibleImaginable combinations of shorter time horizons, higher discount rates, 

and lower expectations about future fuel prices or annual vehicle use and fuel savings could 

make potential buyers hesitant or even unwilling to purchase vehicles offering the increased fuel 

economy levels this rule will require manufacturers to produce. At the same time, they might 

also cause vehicle buyers’ collective assessment of how the benefits from requiring higher fuel 

economy compare to the costs they will be required to pay for ithe aggregate benefits and costs 

of this rule t to differ significantly from NHTSA’s assessment of the aggregate benefits and costs 

of this ruleestimates. If consumers’ views about critical variables such as future fuel prices or 

the appropriate discount rate differ sufficiently from the assumptions used by the agency, some 

or perhaps many potential vehicle buyers might conclude that the value of fuel savings and other 

benefits they will experience from higher fuel economy are not sufficient to justify the increase 

in purchase prices they expect to pay. This would explain why their current choices among 

available models do not result in average fuel economy levels approaching those this rule would 

require. 

Another possibility is that achieving the fuel economy improvements required by stricter 

fuel economy standards might mean that manufacturers will forego planned future improvements 

in performance, carrying capacity, safety, or other features of their vehicle models that represent 

important sources of utility to vehicle owners. Although the specific economic values that 

vehicle buyers attach to individual vehicle attributes such as fuel economy, performance, 

passenger- and cargo-carrying capacity, and other sources of vehicles’ utility are difficult to infer 

from their purchasing decisions and vehicle prices, changes in vehicle attributes can significantly 

affect the overall utility that vehicles offer to potential buyers. Foregoing future improvements 

 

29 Kubik, M. (2006). Consumer Views on Transportation and Energy. Second Edition. Technical Report: National 

Renewable Energy Laboratory.
Summary of Interagency Working Comments on Draft Rule under EO 12866 

17 

in these or other highly-valued attributes could be viewed by potential buyers as an additional 

cost of improving fuel economy.

As indicated in its previous discussion of technology costs, NHTSA has approached this 

potential problem by developing cost estimates for fuel economy-improving technologies that 

include allowances for any additional manufacturing costs that would be necessary to maintain 

the reference fleet (or baseline) levels of performance, comfort, capacity, or safety of light-duty 

vehicle models to which those technologies are applied. In doing so, the agency followed the 

precedent established by the 2002 NAS Report on improving fuel economy, which estimated 

“constant performance and utility” costs for technologies that manufacturers could employ to 

increase the fuel efficiency of cars or light trucks. Although NHTSA has revised its estimates of 

manufacturers’ costs for some technologies significantly for use in this rulemaking, these revised 

estimates are still intended to represent costs that would allow manufacturers to maintain the 

performance, safety, carrying capacity, and utility of vehicle models while improving their fuel 

economy. The adoption of the footprint-based standards also addresses this concern. 

Finally, vehicle buyers may simply prefer the choices of vehicle models they now have 

available to the combinations of price, fuel economy, and other attributes that manufacturers are 

likely to offer when required to achieve higher overall fuel economy. If this is the case, their 

choices among models – and even some buyers’ decisions about whether to purchase a new 

vehicle – will respond accordingly, and their responses to these new choices will reduce their 

overall welfare. Some may buy models with combinations of price, fuel efficiency, and other 

attributes that they consider less desirable than those they would otherwise have purchased, 

while others may simply postpone buying a new vehicle. The use of the footprint-based 

standards, the level of stringency, and the lead time this rule allows manufacturers are all 

intended to ensure that this does not occur. Although the losses in buyers’ welfare associated 

with these responses cannot be large enough to offset the estimated value of fuel savings 

reported in the agencies’ analyses, they might reduce the benefits from requiring manufacturers 

to achieve higher fuel efficiency, particularly in combination with the other possibilities outlined 

previously. 

As the foregoing discussion suggests, tThe agency has been unable to resolvedoes not 

have a complete answer to the question of why the apparently large differences between its 

estimates of benefits from requiring higher fuel economy and the costs of supplying it do not 

result in higher average fuel economy for new cars and light trucks in the absence of this rule. 

One explanation is that NHTSA’s estimates are reasonable, and that for the reasons outlined 

above, the market for fuel economy is not operating efficiently. NHTSA believes that the 

existing literature gives support for the view that because of various market failures (including 

behavioral factors, such as emphasis on the short-term and a lack of salience), there are likely to 

be substantial private gains, on net, from the rule, but it will continue to investigate new 

empirical literature as it become available. NHTSA also acknowledges that this situation may 

mean that it has incorrectly not fully characterized the impact of the CAFE standards this rule 

establishes on consumers. To recognize this possibility, this section presents an alternative 

accounting of the benefits and costs of CAFE standards for MYs 2012-2016 passenger cars and 

light trucks and discusses its implications. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

18 

Table IV.G.6-4 displays the economic impacts of the rule from the perspective of 

potential buyers, and also reconciles the estimated net benefits of the rule as they are likely to be 

viewed by vehicle buyers with its net benefits to the economy as a whole. As the table shows, 

the total benefits to vehicle buyers (line 4) consist of the value of fuel savings at retail fuel prices 

(line 1), the economic value of vehicle occupants’ savings in refueling time (line 2), and the 

economic benefits from added rebound-effect driving (line 3). As the zero entries in line 5 of the 

table suggest, the agency’s estimate of the retail value of fuel savings reported in line 1 is 

assumed to be correct, and no losses in consumer welfare from changes in vehicle attributes 

(other than those from increases in vehicle prices) are assumed to occur. Thus there is no 

reduction in the total private benefits to vehicle owners, so that net private benefits to vehicle 

buyers (line 6) are equal to total private benefits (reported previously in line 4). 

As Table IV.G.6-4 also shows, the decline in fuel tax revenues (line 7) that results from 

reduced fuel purchases is in effect a social cost that offsets part of the benefits of fuel savings to 

vehicle buyers (line 1).30 Thus the sum of lines 1 and 7 is the savings in fuel production costs 

that was reported previously as the value of fuel savings at pre-tax prices in the agency’s usual 

accounting of benefits and costs. Lines 8 and 9 of Table IV.G.6-4 report the value of reductions 

in air pollution and climate-related externalities resulting from lower emissions during fuel 

production and consumption, while line 10 reports the savings in energy security externalities to 

the U.S. economy from reduced consumption and imports of crude petroleum and refined fuel. 

Line 12 reports the costs of increased congestion delays, accidents, and noise that result from 

additional driving due to the fuel economy rebound effect; net social benefits (line 13) is thus the 

sum of the change in fuel tax revenues, the reduction in environmental and energy security 

externalities, and increased costs from added driving. 

Line 14 of Table IV.G.6-4 shows manufacturers’ technology outlays for meeting higher 

CAFE standards for passenger cars and light trucks, which represent the principal cost of 

requiring higher fuel economy. The net total benefits (line 15 of the table) resulting from the 

rule consist of the sum of private (line 6) and external (line 13) benefits, minus technology costs 

(line 14); as expected, the figures reported in line 15 of the table are identical to those reported 

previously in the agency’s customary format. 

Table IV.G.6-4 highlights several important features of this rule’s economic impacts. 

First, comparing the rule’s net private (line 6) and external (line 13) benefits makes it clear that 

virtually all of the benefits from requiring higher fuel economy are experienced by vehicle 

buyers, with only a small share distributed throughout the remainder of the U.S. economy. In 

turn, the vast majority of private benefits stem from fuel savings. External benefits are small 

because the value of reductions in environmental and energy security externalities is almost 

exactly offset by the decline in fuel tax revenues and the increased costs associated with added 

vehicle use via the rebound effect of higher fuel economy. As a consequence, the net economic 

 

30 Strictly speaking, fuel taxes represent a transfer of resources from consumers of fuel to government agencies and 

not a use of economic resources. Reducing the volume of fuel purchases simply reduces the value of this transfer, 

and thus cannot produce a real economic cost or benefit. Representing the change in fuel tax revenues in effect as 

an economy-wide cost is necessary to offset the portion of fuel savings included in line 1 that represents savings in 

fuel tax payments by consumers. This prevents the savings in tax revenues from being counted as a benefit from the 

economy-wide perspective. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

19 

benefits of the rule mirror closely its benefits to private vehicle buyers and the technology costs 

for achieving higher fuel economy, again highlighting the importance of accounting for any other 

effects of the rule on the economic welfare of vehicle buyers. 

Table IV.G.6-4 

Private, Social, and Total Benefits and Costs of MY 2012-16 CAFE Standards: 

Passenger Cars plus Light Trucks 

Entry 

Model Year Total, 

2012-

2016 2012 2013 2014 2015 2016 

1. Value of Fuel Savings (at Retail Fuel Prices) $10.5 $22.9 $32.9 $42.5 $52.7 $161.6 

2. Savings in Refueling Time $0.7 $1.4 $1.9 $2.5 $3.0 $9.4 

3. Consumer Surplus from Added Driving $0.7 $1.5 $2.2 $2.8 $3.4 $10.5 

4. Total Private Benefits (=1+2+3) $11.9 $25.8 $37.0 $47.8 $59.0 $181.5 

5. Reduction in Private Benefits $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 

6. Net Private Benefits (=1+2) $11.9 $25.8 $37.0 $47.8 $59.0 $181.5 

7. Change in Fuel Tax Revenues -$1.3 -$2.7 -$3.8 -$4.8 -$5.9 -$18.5 

8. Reduced Health Damages from Criteria Emissions $0.5 $0.9 $1.3 $1.6 $2.0 $6.4 

9. Reduced Climate Damages from CO2 Emissions $0.9 $2.0 $2.9 $3.8 $4.8 $14.5 

10. Reduced Energy Security Externalities $0.5 $1.2 $1.6 $2.1 $2.5 $8.0 

11. Reduction in Externalities (=8+9+10) $1.9 $4.1 $5.9 $7.6 $9.3 $28.8 

12. Increased Costs of Congestion, etc. -$0.7 -$1.3 -$1.9 -$2.4 -$3.0 -$9.4 

13. Net Social Benefits (=7+11+12) $0.0 $0.1 $0.1 $0.3 $0.5 $1.0 

14. Technology Costs $5.9 $7.9 $10.5 $12.5 $14.9 $51.7 

15. Net Social Benefits (=6+12-14) $6.0 $17.9 $26.6 $35.5 $44.6 $130.7 

 As discussed in detail previously, NHTSA believes that the aggregate benefits of the rule 

amply justify the aggregate costs, but it remainsis possible that NHTSA has overestimated the 

value of fuel savings to buyers and subsequent owners of the cars and light trucks to which 

higher CAFE standards will apply. It is also possible that the agency has failed to identify and 

value reductions in consumer welfare that could result from buyers’ responses to changes in 

vehicle attributes that manufacturers make as part of their efforts to achieve higher fuel 

economy. To acknowledge these possibilities, NHTSA examines their potential impact on the 

rule’s benefits and costs, showing the rule’s economic impacts for MY 2012-16 passenger cars 

and light trucks under varying theoretical assumptions about the agency’s potential 

overestimation of private benefits from higher fuel economy and the value of potential changes 

in other vehicle attributes. See Chapter VIII of the FRIA. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

20 

NHTSA FRIA section on consumer welfare – Chapter VIII.H: 

H. Potential Impacts of the Final Standards on Consumer Welfare

There are two reasonable viewpoints for evaluating the costs and benefits of the increase in 

CAFE standards: the private perspective of vehicle buyers themselves on the higher fuel 

economy levels the final rule would require, and the economy-wide or “social” perspective on 

the costs and benefits of requiring higher fuel economy. The agency’s analysis of benefits from 

requiring higher fuel efficiency, presented previously in this Chapter, includes some categories 

that extend throughout the U.S. economy, such as reductions in the energy security costs 

associated with U.S. petroleum imports and in the economic damages expected to result from 

climate change. In contrast, other categories of benefits – principally the economic value of 

future fuel savings projected to result from higher fuel economy – will be experienced 

exclusively by the initial purchasers and subsequent owners of vehicle models whose fuel 

economy manufacturers elect to improve as part of their strategies for complying with higher 

CAFE standards. In short, it is important to distinguish between the “private” and “social” 

benefits and costs.

Although the economy-wide or “social” benefits from requiring higher fuel economy represent 

an important share of the total economic benefits from raising CAFE standards, NHTSA 

estimates that benefits to vehicle buyers themselves will significantly exceed the costs of 

complying with the stricter fuel economy standards this rule establishes, as Chapter X shows. 

Since the agency also assumes that the costs of new technologies manufacturers will employ to 

improve fuel economy will ultimately be shifted to vehicle buyers in the form of higher purchase 

prices, NHTSA concludes that the benefits to vehicle buyers from requiring higher fuel 

efficiency will far outweigh the costs they will be required to pay to obtain it. However, this 

raises the question of why current purchasing patterns do not result in higher average fuel 

economy, and why stricter fuel efficiency standards should be necessary to achieve that goal. 

As an illustration, Table VIII-14 reports the agency’s estimates of the average lifetime values of 

fuel savings for MY 2012-2016 passenger cars and light trucks calculated using future retail fuel 

prices, which are those likely to be used by vehicle buyers to project the value of fuel savings 

they expect from higher fuel economy. The table compares NHTSA’s estimates of the average 

lifetime value of fuel savings for cars and light trucks to the price increases it projects to result as 

manufacturers attempt to recover their costs for complying with increased CAFE standards for 

those model years by increasing vehicle sales prices. As the table shows, the agency’s estimates 

of the present value of lifetime fuel savings (discounted using the OMB-prescribed 3% rate) 

outweigh projected vehicle price increases for both cars and light trucks in every model year, 

even under the assumption that all of manufacturers’ technology outlays are passed on to buyers 

in the form of higher selling prices for new cars and light trucks. By model year 2016, NHTSA 

projects that average lifetime fuel savings will exceed the average price increase by more than 

$2,000 for cars, and by more than $2,700 for light trucks. 

Table VIII-14 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

21 

Value of Lifetime Fuel Savings vs. Average Technology Cost Increase/Vehicle

2012 2013 2014 2015 2016

Value of Fuel Savings $759 $1,469 $1,954 $2,480 $2,932

Average Price Increase $505 $573 $690 $799 $907

Difference $255 $897 $1,264 $1,680 $2,025

Value of Fuel Savings $828 $1,634 $2,277 $2,887 $3,700

Average Price Increase $322 $416 $621 $752 $961

Difference $506 $1,218 $1,656 $2,135 $2,739

Model Year Fleet Measure

Light Trucks

Passsenger 

Cars

 Assuming these comparisons are accurate, they raise the question of why current vehicle 

purchasing patterns do not result in average fuel economy levels approaching those that this rule 

would require, and why stricter CAFE standards should be necessary to increase the fuel 

economy of new cars and light trucks. They also raise the question of why manufacturers do not 

elect to provide higher fuel economy even in the absence of increases in CAFE standards, since 

the comparisons in Table VIII-14 suggest that doing so would reduce the effective price of 

purchasing many new vehicle models, and thus to increase sales of new vehicles. More 

specifically, why would potential buyers of new vehicles hesitate to make investments in higher 

fuel economy that would produce the substantial economic returns illustrated by the comparisons 

presented in Table VIII-14? And why would manufacturers voluntarily forego opportunities to 

increase the attractiveness, value, and competitive positioning of their car and light truck models 

by improving their fuel economy? 

One explanation for this apparent paradox involves imperfections in the relevant market. Some 

of these imperfections might stem from standard market failures (such as an absence of adequate 

information); some of them involve behavioral findings (including, for example, a lack of 

sufficient attention to long-term savings, or a lack of salience, at the time of purchase, of relevant 

benefits, including fuel and time savings). A subset of the theoretical and empirical research 

suggests that many consumers do not make energy-efficient investments even when those 

investments would pay off in the relatively short-term,31 in line with related findings that 

consumers may underweight benefits and costs that are less salient or that will be realized only in 

the future.32

Another One explanation for this apparent paradoxexplanation is that NHTSA’s estimates of 

benefits and costs from requiring manufacturers to improve the fuel efficiency of their vehicle 

models do not match potential vehicle buyers’ assessment of the likely benefits and costs from 

 

31 Jaffe, A. B., and Stavins, R. N. (1994). The Energy Paradox and the Diffusion of Conservation Technology. 

Resource and Energy Economics, 16(2); see Hunt Alcott and Nathan Wozny, Gasoline Prices, Fuel Economy, and 

the Energy Paradox (2010, available at http://web.mit.edu/allcott/www/Allcott%20and%20Wozny%202010%20-

%20Gasoline%20Prices,%20Fuel%20Economy,%20and%20the%20Energy%20Paradox.pdf

32 Hossain, Janjim, and John Morgan (2009). “. . . Plus Shipping and Handling: Revenue (Non)Equivalence in Field 

Experiments on eBay,” Advances in Economic Analysis and Policy vol. 6; Barber, Brad, Terrence Odean, and Lu 

Zheng (2005). “Out of Sight, Out of Mind: The Effectsof Expenses on Mutual Fund Flows,” Journal of Business 

vol. 78, no. 6, pp. 2095-2020.
Summary of Interagency Working Comments on Draft Rule under EO 12866 

22 

requiring higher fuel efficiency. This could occur because the agency’s underlying assumptions 

about some of the factors that affect the value of fuel savings differ from those made by potential 

buyers, because NHTSA has incorrectly estimated some components of the benefits from saving 

fuel, or because the agency has failed to account for some potential costs of achieving higher fuel 

economy. 

For example, buyers may not value increased fuel economy as highly as the agencies’ 

calculations suggest, because they have shorter time horizons than the full vehicle lifetimes 

assumed by NHTSA and EPA, or because they discount future fuel future savings using higher 

rates than those prescribed by OMB for evaluating federal regulations. Potential buyers may also 

anticipate lower fuel prices in the future than those forecast by the Energy Information 

Administration, or may expect larger differences between vehicles’ rated and actual on-road 

MPG levels than the agencies estimate. 

To illustrate the first of these possibilities, Table VIII-15 shows the effect of differing 

assumptions about vehicle buyers’ time horizons for assessing the value of future fuel savings. 

Specifically, the table compares the average value of fuel savings from purchasing a MY 2016 

car or light truck when fuel savings are evaluated over different time horizons to the estimated 

increase in its price. This table shows that as reported previously in Table VIII-15, when fuel 

savings are evaluated over the entire expected lifetime of a MY 2016 car (approximately 14 

years) or light truck (about 16 years), their discounted present value (using the OMB-prescribed 

3% discount rate) lifetime fuel savings exceeds the estimated average price increase by more 

than $2,000 for cars and by more than $2,700 for light trucks. 

If buyers are instead assumed to evaluate fuel savings over a 10-year time horizon, however, the 

present value of fuel savings exceeds the projected price increase for a MY 2016 car by about 

$1,300, and by somewhat more than $1,500 for a MY 2016 light truck. Finally, Table VIII-15 

shows that under the assumption that buyers value fuel savings only over the length of time for 

which they typically finance new car purchases (slightly more than 5 years during 2009), the 

value of fuel savings exceeds the estimated increase in the price of a MY 2016 car by only about 

$350, and the corresponding difference is reduced to slightly more than $500 for a MY 2016 

light truck. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

23 

Table VIII-15 

Value of Fuel Savings vs. Vehicle Price Increases 

with Alternative Assumptions about Vehicle Buyer Time Horizons 

Expected 

Lifetime (1) 10 Years Average Loan Term (2)

Fuel Savings $2,932 $2,180 $1,254

Price Increase $907 $907 $907

Difference $2,025 $1,273 $347

Fuel Savings $3,700 $2,508 $1,484

Price Increase $961 $961 $961

Difference $2,739 $1,547 $523

(1) Expected lifetimes are approximately 14 years for cars and 16 years for light trucks. 

(2) Average term on new-vehicle loans made by auto finance companies during 2009 

was 62 months; see Board of Governors of the Federal Reserve System, Federal Reserve 

Statistical Release G. 19, Consumer Credit, 

http://www.federalreserve.gov/releases/g19/Current/ last accessed March 1, 2010.

MY 2016 

Passenger 

Car

MY 2016 

Light Truck

Value over Alternative Time Horizons

Vehicle Measure

Potential vehicle buyers may also discount future fuel future savings using higher rates than 

those typically used to evaluate federal regulations. (For some consumers, these high discount 

rates might reflect rational behavior; for others, they might reflect an excessive focus on the 

short-term and a neglect of the future.). OMB guidance prescribes that future benefits and costs 

of regulations that mainly affect private consumption decisions, as will be the case if 

manufacturers’ costs for complying with higher fuel economy standards are passed on to vehicle 

buyers, should be discounted using a consumption rate of time preference.33 OMB estimates that 

savers currently discount future consumption at an average real or inflation-adjusted rate of 

about 3 percent when they face little risk about its likely level, which makes it a reasonable 

estimate of the consumption rate of time preference. However, vehicle buyers may view the 

value of future fuel savings that results from purchasing a vehicle with higher fuel economy as 

risky or uncertain, or they may instead discount future consumption at rates reflecting their costs 

for financing the higher capital outlays required to purchase more fuel-efficient models. In either 

case, they may discount future fuel savings at rates well above the 3% assumed in NHTSA’s 

evaluation.

Table VIII-16 shows the effect of higher discount rates on vehicle buyers’ evaluation of the fuel 

savings projected to result from the CAFE standards established by this rule, again using MY 

2016 passenger cars and light trucks as an example. As Table VIII-14 showed previously, 

average future fuel savings discounted at the OMB 3% consumer rate exceed the agency’s 

 

33 Office of Management and Budget, Circular A-4, “Regulatory Analysis,” September 17, 2003, 33. Available at

http://www.whitehouse.gov/omb/assets/regulatory_matters_pdf/a-4.pdf (last accessed March 1, 2009). 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

24 

estimated price increases by more than $2,000 for MY 2016 passenger cars and by more than 

$2,700 for MY 2016 light trucks. If vehicle buyers instead discount future fuel savings at the 

average new-car loan rate during 2009 (6.7%), however, these differences decline to slightly 

more than $1,400 for cars and $1,900 for light trucks, as Table VIII-16 illustrates. This is a 

particularly plausible alternative assumption, because buyers are likely to finance the increases in 

purchase prices resulting from compliance with higher CAFE standards as part of the process 

financing the vehicle purchase itself. Finally, as the table also shows, discounting future fuel 

savings using a consumer credit card rate (which averaged 13.4% during 2009) reduces these 

differences to less than $800 for a MY 2016 passenger car and less than $1,100 for the typical 

MY 2016 light truck. Thus even at relatively high discount rates, the higher fuel economy levels 

required by this final rule would generate significant net benefits to vehicle buyers. 

Table VIII-16 

Value of Fuel Savings vs. Vehicle Price Increases 

with Alternative Assumptions about Consumer Discount Rates

OMB 

Consumer 

Rate (3%)

New Car 

Loan Rate 

(6.7%; 1)

OMB 

Investment 

Rate (7%)

Consumer 

Credit Card 

Rate 

(13.4%; 2)

Fuel Savings $2,932 $2,336 $2,300 $1,669

Price Increase $907 $907 $907 $907

Difference $2,025 $1,429 $1,393 $762

Fuel Savings $3,700 $2,884 $2,836 $2,030

Price Increase $961 $961 $961 $961

Difference $2,739 $1,923 $1,875 $1,069

(1) Average rate on 48-month new-vehicle loans made by commercial banks during 2009 was 6.72%; 

see Board of Governors of the Federal Reserve System, Federal Reserve Statistical Release G. 19, 

Consumer Credit, http://www.federalreserve.gov/releases/g19/Current/ last accessed March 1, 2010.

(2) Average rate on consumer credit card accounts at commercial banks during 2009 was13.4%; see 

Board of Governors of the Federal Reserve System, Federal Reserve Statistical Release G. 19, 

Consumer Credit, http://www.federalreserve.gov/releases/g19/Current/ last accessed March 1, 2010.

Value at Alternative Discount Rates

Vehicle Measure

MY 2016 

Passenger 

Car

MY 2016 

Light Truck

Combinations of a shorter time horizon and a higher discount rate could further reduce or even 

eliminate the difference between the value of fuel savings and the agency’s estimates of 

increases in vehicle prices. One plausible combination would be for buyers to discount fuel 

savings over the term of a new car loan, using the interest rate on that loan as a discount rate. 

Doing so would reduce the amount by which future fuel savings exceed the estimated increase in 

the prices of MY 2016 vehicles to about $340 for passenger cars and $570 for light trucks. Some 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

25 

evidence suggests directly that vehicle buyers may employ combinations of higher discount rates 

and shorter time horizons than the agency assumes; for example, consumers surveyed by Kubik 

(2006) reported that fuel savings would have to be adequate to pay back the additional purchase 

price of a more fuel-efficient vehicle in less than 3 years to persuade a typical buyer to purchase 

it. 34 As these comparisons and evidence illustrate, reasonable alternative assumptions about how 

consumers might evaluate the major benefit from requiring higher fuel economy can 

significantly reduce its magnitude from the agency’s estimate. 

Many plausibleImaginable combinations of shorter time horizons, higher discount rates, and 

lower expectations about future fuel prices or annual vehicle use and fuel savings could make 

potential buyers hesitant or even unwilling to purchase vehicles offering the fuel economy levels 

this rule will require. At the same time, they would also cause vehicle buyers’ collective 

assessment of how the benefits from requiring higher fuel economy compare to the costs they 

will be required to pay for it to differ significantly from NHTSA’s assessment of the aggr4egate 

benefits and costs of this rule. If consumers’ views about critical variables such as future fuel 

prices or the appropriate discount rate differ sufficiently from the assumptions used by the 

agency, potential vehicle buyers might conclude that the value of fuel savings and other benefits 

they will experience from higher fuel economy are not sufficient to justify the increase in 

purchase prices they expect to pay. This would not only explain why their current choices 

among available models do not result in average fuel economy levels approaching those this rule 

would require, but, under what we believe to be unlikely assumptions, might also call into 

question NHTSA’s conclusion that the total – that is, private plus economy-wide – economic 

benefits from raising CAFE standards exceed the costs of complying with higher fuel economy 

requirements. 

Another possibility is that achieving the fuel economy improvements required by stricter fuel 

economy standards might require manufacturers to forego planned future improvements in 

performance, carrying capacity, safety, or other features of their vehicle models that represent 

important sources of utility to vehicle owners. In extreme cases, manufacturers might even find 

it necessary to change the levels of these attributes that some currently available models offer. 

Although the specific economic values that vehicle buyers attach to individual vehicle attributes 

such as fuel economy, performance, passenger- and cargo-carrying capacity, and other sources of 

vehicles’ utility are difficult to infer from their purchasing decisions and vehicle prices, changes 

in vehicle attributes can significantly affect the overall utility that vehicles offer to potential 

buyers. Compromises in these or other highly-valued attributes would be viewed by potential 

buyers as an additional cost of improving fuel economy that the agency has failed to 

acknowledge or include in its estimates of the costs of complying with stricter CAFE standards. 

As indicated in its previous discussion of technology costs, NHTSA has approached this 

potential problem by developing cost estimates for fuel economy-improving technologies that 

include allowances for any additional manufacturing costs that would be necessary to maintain 

the reference fleet (or baseline) levels of performance, comfort, capacity, or safety of light-duty 

vehicle models to which those technologies are applied. In doing so, the agency followed the 

 

34 Kubik, M. (2006). Consumer Views on Transportation and Energy. Second Edition. Technical Report: National 

Renewable Energy Laboratory.
Summary of Interagency Working Comments on Draft Rule under EO 12866 

26 

precedent established by the 2002 NAS Report on improving fuel economy, which estimated 

“constant performance and utility” costs for technologies that manufacturers could employ to 

increase the fuel efficiency of cars or light trucks. Although NHTSA has revised its estimates of 

manufacturers’ costs for some technologies significantly for use in this rulemaking, these revised 

estimates are still intended to represent costs that would allow manufacturers to maintain the 

performance, carrying capacity, and utility of vehicle models while improving their fuel 

economy. 

The agency readily acknowledges the difficulty of estimating technology costs that include 

adequate provision for the accompanying changes in vehicle design that are necessary to 

maintain performance, capacity, and utility. While NHTSA believe that its cost estimates for 

fuel economy-improving technologies are sufficient to prevent significant compromises in other 

attributes of the vehicle models to which manufacturers apply them, it is possible that these costs 

do not include adequate allowance for the necessary investments by manufacturers to maintain 

baseline levels of these critical vehicle attributes. If this is the case, the true economic costs of 

achieving higher fuel economy would include the opportunity costs to vehicle owners of any 

sacrifices in vehicles’ performance, carrying capacity, and utility that accompanied increases in 

their fuel economy. In that event, the agencies’ estimated technology costs would underestimate 

the true economic costs of complying with stricter fuel economy emission standards. 

Finally, vehicle buyers may simply prefer the choices of vehicle models they now have available 

to the combinations of price, fuel economy, and other attributes that manufacturers are likely to 

offer when required to achieve higher overall fuel economy. If this is the case, their choices 

among models – and even some buyers’ decisions about whether to purchase a new vehicle – 

will respond accordingly, and their responses to these new choices will reduce their overall 

welfare. Some may buy models with combinations of price, fuel efficiency, and other attributes 

that they consider less desirable than those they would otherwise have purchased, while others 

may simply postpone buying a new vehicle. It is also possible that manufacturers may 

discontinue some currently popular vehicle models or styles as part of their efforts to comply 

with requirements for higher fuel efficiency. Although the losses in buyers’ welfare associated 

with these responses cannot be large enough to offset the estimated value of fuel savings 

reported in the agencies’ analyses, they could significantly reduce the benefits from requiring 

manufacturers to achieve higher fuel efficiency, particularly in combination with the other 

possibilities outlined previously. 

An entirely different explanation for buyers’ reluctance to invest in higher fuel economy 

despite the large economic return it appears to promise is that the agency’s assertion that the 

benefits buyers will experience from higher fuel economy far outweigh the costs they will pay to 

acquire it is indeed correct, yet certain plausible – if short-sighted – aspects of normal behavior 

nevertheless make buyers reluctant to purchase vehicles whose higher fuel economy offers an 

attractive return. For example, consumers’ understandable aversion to the prospect of losses 

from making investments that do not produce their expected returns may exaggerate their 

uncertainty about the value of future fuel savings sufficiently to make purchasing a more fuelefficient vehicle seem unattractive even when doing so is likely to be a sound economic decision. 

Compare the finding in Greene et al. (2009), to the effect find that the expected net present value 

of increasing the fuel economy of a passenger car from 28 to 35 miles per gallon falls from $405 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

27 

when calculated using standard net present value calculations, to nearly zero when uncertainty 

regarding future cost savings is taken into account.35 

Another possible reconciliation of the agency’s claim that the average vehicle buyer will 

experience large fuel savings from the higher CAFE standards this rule establishes with the fact 

that the average fuel economy of vehicles currently purchased falls well short of the new 

standards is that the values consumers place on the future savings they expect to obtain from 

higher fuel economy vary widely. As an illustration, one recent review of consumers’ 

willingness to pay for improved fuel economy found estimates that varied from less than 1% to 

almost ten times the present value of the resulting fuel savings when those are discounted at 7% 

over the vehicle’s expected lifetime.36 Although the wide variation in these estimates partly 

undoubtedly reflects methodological and measurement differences among the studies surveyed, 

it probably also reflects the fact that the expected savings from purchasing a vehicle with higher 

fuel economy vary widely among individuals, because they travel different amounts, have 

different driving styles, or have different expectations about future fuel prices. 

This is likely to be reflected in the fact that buyers with high valuations of increased fuel 

economy already purchase vehicle models that offer it, while those with lower values of fuel 

economy emphasize other vehicle attributes in their purchasing decisions. A related possibility 

is that because the effects of differing fuel economy levels are relatively modest when compared 

to those provided by other, more prominent features of new vehicles – passenger and cargocarrying capacity, performance, safety, etc. – it is simply not in many shoppers’ interest to spend 

the time and effort necessary to determine the economic value of higher fuel economy, attempt to 

isolate the component of a new vehicle’s selling price that is related to its fuel economy, and 

compare these two. In either case, although the agency’s estimates of the average value of fuel 

savings that will result from requiring cars and light trucks to achieve higher fuel economy may 

be correct, they are not likely to be large enough to lead a sufficient number of buyers to 

purchase vehicles with higher fuel economy to increase average fuel economy from its current 

levels. 

Defects in the market for cars and light trucks could also lead manufacturers to undersupply fuel 

economy, even in cases where many (informed) buyers would beere willing to pay the increased 

prices necessary to provide it. Most obviously, an absence of vigorous competition among 

producers of cars and light trucks may lead manufacturers to undersupply attributes that 

contribute to the overall quality of new vehicles, including fuel economy, because such 

“imperfect” competition reduces producers’ profit incentive to supply the level of fuel economy 

 

35 Greene, D., J. German, and M. Delucchi (2009). “Fuel Economy: The Case for Market Failure” in Reducing 

Climate Impacts in the Transportation Sector, Sperling, D., and J. Cannon, eds. Springer Science. Surprisingly, the 

authors find that uncertainty regarding the future price of gasoline appears to be less important than uncertainty 

surrounding the expected lifetimes of new vehicles. 

36 Greene, David L., “How Consumers Value Fuel Economy: A Literature Review,” Draft report to U.S. 

Environmental Protection Agency, Oak Ridge National Laboratory, December 29, 2009; see Table 10, p. 37. 

and Jin-Tan Liu (1988). “Automotive Fuel Economy Improvements and Consumers’ Surplus.” Transportation 

Research Part A 22A(3): 203-218. The study actually calculated the willingness to pay for reduced vehicle operating 

costs, of which vehicle fuel economy is a major component.
Summary of Interagency Working Comments on Draft Rule under EO 12866 

28 

that buyers are willing to pay for. Incomplete or “asymmetric” access to information on vehicle 

attributes such as fuel economy – whereby manufacturers of new vehicles or sellers of used cars 

and light trucks have more complete knowledge of vehicles’ actual fuel economy levels, or of the 

value of purchasing higher fuel economy, than do potential buyers – may also prevents sellers of 

new or used vehicles from capturing its full value. In this situation, the level of fuel efficiency 

provided in the markets for new or used vehicles might remain persistently lower than that 

demanded by potential buyers. 

It is also possible that deliberate decisions by manufacturers of cars and light trucks, rather than 

constraints on the combinations of fuel economy, carrying capacity, and performance that 

manufacturers can offer using current technologies, limit the range of fuel economy available to 

buyers within individual vehicle market segments, such as full-size automobiles, small SUVs, or 

minivans. As an illustration, once a potential buyer has decided to purchase a minivan, the range 

of fuel economy among current models extends only from 18 to 24 MPG.37 Manufacturers 

might make such decisions if they underestimate the premiums that shoppers in certain market 

segments are willing to pay for more fuel-efficient versions of the vehicle models thy currently 

offer to prospective buyers within those segments. If this occurs, manufacturers may fail to 

supply levels of fuel efficiency as high as those buyers are willing to pay for, and the average 

fuel efficiency of their entire new vehicle fleets could remain below the levels that potential 

buyers demand and are willing to pay for. 

Finally, some research suggests that the consumers’ apparent unwillingness to purchase more 

fuel efficient vehicles stems from their inability to value future fuel savings correctly. For 

example, Larrick and Soll (2008) find evidence that consumers do not understand how to 

translate changes in fuel economy, which is denominated in miles per gallon, into resulting 

changes in fuel consumption, measured in gallons per time period.38 Sanstad and Howarth 

(1994) argue that consumers appear optimize behavior without full information by resorting to 

imprecise but convenient rules of thumb, which can cause many buyers to underestimate the 

value of fuel savings, particularly from significant increases in fuel economy.39 If the behavior 

identified in these studies is indeed widespread, then the agency’s calculations suggesting that 

the benefits to vehicle owners from requiring higher fuel economy significantly exceeds the costs 

of providing it may indeed be correct, yet the resulting difference is still insufficient to motivate 

buyers to purchase a mix of car or light truck vehicle models whose average fuel economy 

approaches those required by this rule. 

 

The agency has been unable to resolve thereach a conclusive answer to the question of why the 

apparently large differences between its estimates of benefits from requiring higher fuel 

economy and the costs of supplying it do not result in higher average fuel economy for new cars 

and light trucks. One explanation is that NHTSA’s estimates are reasonable, and the market for 

fuel economy is simply not operating efficiently. For reasons stated above, NHTSA believes that 

 

37 This is the range of combined city and highway fuel economy levels from lowest (Toyota Siena 4WD) to highest 

(Mazda 5) available for model year 2010; http://www.fueleconomy.gov/feg/bestworstEPAtrucks.htm (last accessed 

February 15, 2010). 

38 Larrick, R. P., and J.B. Soll (2008). “The MPG illusion.” Science 320: 1593-1594. 39 Sanstad, A., and R. Howarth (1994). “’Normal’ Markets, Market Imperfections, and Energy Efficiency.” Energy 

Policy 22(10): 811-818. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

29 

a number of imperfections in the relevant market (likely including the lack of salience of fuel 

economy benefits and an emphasis on the short-term) likely play a key role, thus justifying the 

conclusion that the private benefits are substantial. However, the agency acknowledges that this 

situation may also reflect the fact that some combination of overestimating the value of fuel 

savings and omitting potential reductions in the welfare of vehicle buyers means that it has 

incorrectly not fully characterized the impact of the CAFE standards this rule establishes on 

consumers. To recognize this possibility, and as part of a sensitivity analysis, this section 

presents an alternative accounting of the benefits and costs of CAFE standards for MY 2012-

2016 passenger cars and light trucks and discusses its implications. 

Table VIII-17 displays the economic impacts of the rule from the perspective of potential buyers, 

and also reconciles the estimated net benefits of the rule as they are likely to be viewed by 

vehicle buyers with its net benefits to the economy as a whole. As the table shows, the total 

benefits to vehicle buyers (line 4) consist of the value of fuel savings at retail fuel prices (line 1), 

the economic value of vehicle occupants’ savings in refueling time (line 2), and the economic 

benefits from added rebound-effect driving (line 3). As the zero entries in line 5 of the table 

suggest, the agency’s estimate of the retail value of fuel savings reported in line 1 is assumed to 

be correct, and no losses in consumer welfare from changes in vehicle attributes (other than those 

from increases in vehicle prices) are assumed to occur. Thus there is no reduction in the total 

private benefits to vehicle owners, so that net private benefits to vehicle buyers (line 6) are equal 

to total private benefits (reported previously in line 4). 

As Table VIII-17 also shows, the decline in fuel tax revenues (line 7) that results from reduced 

fuel purchases is in effect an external cost from the viewpoint of vehicle buyers, which offsets 

part of the benefits of fuel savings when those are viewed from the economy-wide or “social” 

perspective.40 Thus the sum of lines 1 and 7 is the savings in fuel production costs that was 

reported previously as the value of fuel savings at pre-tax prices in the agency’s usual accounting 

of benefits and costs (see Chapter X). Lines 8 and 9 of Table VIII-17 report the value of 

reductions in air pollution and climate-related externalities resulting from lower emissions during 

fuel production and consumption, while line 10 reports the savings in energy security 

externalities to the U.S. economy from reduced consumption and imports of crude petroleum and 

refined fuel. Line 12 reports the costs of increased congestion delays, accidents, and noise that 

result from additional driving due to the fuel economy rebound effect; net social benefits (line 

13) is thus the sum of the change in fuel tax revenues, the reduction in environmental and energy 

security externalities, and increased costs from added driving. 

Line 14 of Table VIII-17 shows manufacturers’ technology outlays for meeting higher CAFE 

standards for passenger cars and light trucks, which represent the principal cost of requiring 

higher fuel economy. The net total benefits (line 15 of the table) resulting from the rule consist 

of the sum of private (line 6) and social (line 13) benefits, minus technology costs (line 14); as 

 

40 Strictly speaking, fuel taxes represent a transfer of resources from consumers of fuel to government agencies and 

not a use of economic resources. Reducing the volume of fuel purchases simply reduces the value of this transfer, 

and thus cannot produce a real economic cost or benefit. Representing the change in fuel tax revenues in effect as 

an economy-wide cost is necessary to offset the portion of fuel savings included in line 1 that represents savings in 

fuel tax payments by consumers. This prevents the savings in tax revenues from being counted as a benefit from the 

economy-wide perspective. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

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expected, the figures reported in line 15 of the table are identical to those reported previously in 

the agency’s customary format (see Chapter X). 

Table VIII-17 highlights several important features of this rule’s economic impacts. First, 

comparing the rule’s net private (line 6) and external (line 13) benefits makes it clear that 

virtually all of the benefits from requiring higher fuel economy are experienced by vehicle 

buyers, with only a small share distributed throughout the remainder of the U.S. economy. In 

turn, the vast majority of private benefits stem from fuel savings, which highlights the 

importance of the many assumptions the agency uses to estimate and value future fuel savings 

resulting from higher fuel economy, as well as of the assumption that the rule has no adverse 

impacts on vehicle buyers. The aggregate eExternal benefits are small because the substantial

value of reductions in environmental and energy security externalities is almost exactly offset by 

the decline in fuel tax revenues and the increased costs associated with added vehicle use via the 

rebound effect of higher fuel economy. 

As a consequence, the net economic benefits of the rule mirror closely its benefits to 

private vehicle buyers and the technology costs for achieving higher fuel economy, again 

highlighting the importance of correctly valuing fuel savings from the perspective of those who 

experience them and accounting for any other effects of the rule on the economic welfare of 

vehicle buyers. 

Table VIII-17 

Private, Social, and Total Benefits and Costs of MY 2012-16 CAFE Standards: 

Passenger Cars plus Light Trucks 

2012 2013 2014 2015 2016

1 Value of Fuel Savings (at Retail Fuel Prices) $10.5 $22.9 $32.9 $42.5 $52.7 $161.6

2 Savings in Refueling Time $0.7 $1.4 $1.9 $2.5 $3.0 $9.4

3 Consumer Surplus from Added Driving $0.7 $1.5 $2.2 $2.8 $3.4 $10.5

4 Total Private Benefits (=1+2+3) $11.9 $25.8 $37.0 $47.8 $59.0 $181.5

5 Reduction in Private Benefits $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

6 Net Private Benefits (=1+2) $11.9 $25.8 $37.0 $47.8 $59.0 $181.5

7 Change in Fuel Tax Revenues -$1.3 -$2.7 -$3.8 -$4.8 -$5.9 -$18.5

8 Reduced Health Damages from Criteria Emissions $0.5 $0.9 $1.3 $1.6 $2.0 $6.4

9 Reduced Climate Damages from CO2 Emissions $0.9 $2.0 $2.9 $3.8 $4.8 $14.5

10 Reduced Energy Security Externalities $0.5 $1.2 $1.6 $2.1 $2.5 $8.0

11 Reduction in Externalities (=8+9+10) $1.9 $4.1 $5.9 $7.6 $9.3 $28.8

12 Increased Costs of Congestion, etc. -$0.7 -$1.3 -$1.9 -$2.4 -$3.0 -$9.4

13 Net Social Benefits (=7+11+12) $0.0 $0.1 $0.1 $0.3 $0.5 $1.0

14 Technology Costs $5.9 $7.9 $10.5 $12.5 $14.9 $51.7

15 Net Total Benefits (=6+12-14) $6.0 $17.9 $26.6 $35.5 $44.6 $130.7

Entry Model Year Total, 2012-

2016

As discussed in detail previously, it is possible that NHTSA has overestimated the value of fuel 

savings to buyers and subsequent owners of the cars and light trucks to which higher CAFE 

standards will apply. It is also possible that the agency has failed to identify and value 

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Summary of Interagency Working Comments on Draft Rule under EO 12866 

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reductions in consumer welfare that could result from buyers’ responses to higher vehicle prices 

or changes in vehicle attributes that manufacturers make as part of their efforts to achieve higher 

fuel economy. To acknowledge these possibilities and examine their potential impact on the 

rule’s benefits and costs, and in order to provide a sensitivity analysis, Table IV.G.6-5 shows the 

rule’s cumulative economic impacts for MY 2012-16 passenger cars and light trucks under 

varying assumptions about the agency’s potential overestimation of fuel savings and the value of 

potential changes in vehicle attributes such as performance, carrying capacity, or safety. 

Table VIII-18 accounts for both potential overestimation of the value of fuel savings to vehicle 

buyers and the possible omission of welfare losses from changes in other vehicle attributes in the 

entry labeled “Reduction in Private Benefits” (line 5). Although the examples reported 

previously in Tables VIII-15 and VIII-16 illustrated sources of possible overestimation of fuel 

savings using specific alternatives to the agency’s assumptions, NHTSA has been unable to 

determine exactly how buyers’ time horizons or discount rates might differ from those assumed 

in its analysis. Nor has NHTSA analyzed how vehicle buyers’ expectations about future fuel 

prices or differences between fuel economy ratings and actual on-road fuel economy might differ 

from those it employs to estimate the value of fuel savings. Finally, NHTSA has not attempted 

to project changes in vehicle attributes other than fuel economy, or to estimate the economic 

value of resulting losses in vehicle utility. 

Instead Table VIII-18 illustrates the effect of these possibilities using different assumptions 

about the fraction of total private benefits to vehicle buyers that might be offset by some 

combination of these factors. It is important to see that these assumptions are used merely for 

the sake of analysis and illustration; there is no claim here that they have an empirical basis, or 

that they are founded in any existing estimates, theoretical or empirical, of actual offsets. While 

some empirical evidence suggests that consumers are largely making rational decisions, other 

evidence suggests this is not the case. Since there is not agreement in the literature on this point, 

it is not possible to estimate the potential degree of consumer loss in welfare. As Table VIII-18it

shows, if there is no offset to private benefits, the rule’s total and net private and social benefits 

are exactly as shown in the last column of Table IV.G.6-4 above. Three findings are especially

noteworthy: 

 However, ifIf these factors combine to offset even as much as 25% of the agency’s 

estimate of total private benefits (line 5), the rule’s net private (line 6) and net total 

(line 15) benefits would be reduced, but areremain still ssubstantially positive. If the 

private savings turn out to be 25% less than projected, the benefits of the rule 

continue to justify the costs by a large measure.

 The table also shows that if losses in consumer welfare from changes in vehicle 

attributes or an overestimate of the value of fuel savings offset as much as half of the 

rule’s estimated private benefitsIf the offset is assumed to be as much as 50%,the its

net private benefits (line 6) would be reduced to slightly less than half of the agency’s 

original estimate, while its net total benefits (line 15) would decline to less than onethird of the original estimatesignificantly decline, but would remain positive, and the 

benefits would continue to justify the costs by a large measures.

 If. As the table also shows, if these the relevant factors combined to offset a 

sufficiently high fraction of the rule’s total private benefits,, its net total benefits 

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0.5" + Indent at: 0.75"
Summary of Interagency Working Comments on Draft Rule under EO 12866 

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wcould decline to zero or even becomedecline rapidly and at a certain point become

negative. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

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Table VIII-18 

Effect of Overestimation of Fuel Savings or Omission of Welfare Losses 

on Net Private and Total Benefits of MY 2012-2016 CAFE Standards 

None 25% 50% 75%

1 Value of Fuel Savings (at Retail Fuel Prices) $161.6 $161.6 $161.6 $161.6

2 Savings in Refueling Time $9.4 $9.4 $9.4 $9.4

3 Consumer Surplus from Added Driving $10.5 $10.5 $10.5 $10.5

4 Total Private Benefits (=1+2+3) $181.5 $181.5 $181.5 $181.5

5 Reduction in Private Benefits $0.0 -$45.4 -$90.7 -$136.1

6 Net Private Benefits (=1+2) $181.5 $136.1 $90.7 $45.4

7 Change in Fuel Tax Revenues -$18.5 -$18.5 -$18.5 -$18.5

8 Reduced Health Damages from Criteria Emissions $6.4 $6.4 $6.4 $6.4

9 Reduced Climate Damages from CO2 Emissions $14.5 $14.5 $14.5 $14.5

10 Reduced Energy Security Externalities $8.0 $8.0 $8.0 $8.0

11 Reduction in Externalities (=8+9+10) $28.8 $28.8 $28.8 $28.8

12 Increased Costs of Congestion, etc. -$9.4 -$9.4 -$9.4 -$9.4

13 Net Social Benefits (=7+11+12) $1.0 $1.0 $1.0 $1.0

14 Technology Costs $51.7 $51.7 $51.7 $51.7

15 Net Total Benefits (=6+12-14) $130.7 $85.3 $40.0 -$5.4

Fraction of Private Benefits Offset by 

Overestimation of Fuel Savings or Omission 

of Welfare Losses to Vehicle Buyers Entry

It is important to reemphasize that NHTSA views the alternative estimates of this rule’s 

economic impacts presented in Table VIII-18 as illustrative only, and for reasons elaborated 

above, that it views this last possibility as extremely unlikely. The agency has attempted to 

develop the most accurate estimates of the value of fuel savings that are possible, and the design 

of the CAFE standards (e.g., the footprint curves), the stringency of the standards, the lead time 

provided to manufacturers for complying with the new standards have all been tailored to ensure 

that desirable vehicle attributes other than fuel economy will not be compromised. NHTSA has 

also attempted to ensure that its estimates of technology costs include adequate provisions to 

prevent the degradation of performance, safety, or other valuable attributes as consequences of 

manufacturers’ efforts to comply with higher CAFE standards. 

A major lesson is that the benefits of the rule justify the costs even on the assumption that the 

private savings are significantly offset, however unlikely the agency believes that to be the case. 

Nevertheless, the agency feels believes that it is important to acknowledge uncertainty in its 

estimates of how buyers are likely to value fuel savings, as well as in its conclusion that no 

losses in the performance, utility, or safety of cars and light trucks subject to this rule will occur. 

As this analysis indicates, the implications of such uncertainty for the magnitude of economic 

benefits likely to result from the CAFE standards this rule establishes are significant. NHTSA is 

committed to developing improved methods to estimate the value of improvements in fuel 

economy, as well as the magnitude and economic consequences of accompanying changes in 

other vehicle attributes, as part of its future CAFE rulemaking activities. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

34 

EPA RIA section on consumer welfare – Chapter 8.1.2: 

8.1.21.1.1 Consumer Vehicle Choice Modeling 

In this section we describe some of the consumer vehicle choice models EPA has reviewed in the 

literature, and we describe the models’ results and limitations that we have identified. The 

evidence from consumer vehicle choice models indicates a huge range of estimates for 

consumers’ willingness to pay for additional fuel economy. Because consumer surplus estimates 

from consumer vehicle choice models depend critically on this value, we would consider any 

consumer surplus estimates of the effect of our rule from such models to be unreliable. In 

addition, the predictive ability of consumer vehicle choice models may be limited. While vehicle 

choice models are based on sales of existing vehicles, vehicle models are likely to change, both 

independently and in response to this proposed rule. The models may not predict well in 

response to these changes. Instead, we compare the value of the fuel savings associated with this 

rule with the increase in technology costs. Like NHTSA, EPA will continue its efforts to review 

the literature, but, given the known difficulties, neither NHTSA nor EPA has conducted an 

analysis using these models for this proposal. 

This rule will lead automakers to change characteristics – in particular, the fuel economy 

-- of the vehicles they produce. These changes will affect the cost of manufacturing the vehicle; 

as a result, the prices of the vehicles will also change. 

In response to these changes, the number and types of vehicles sold is likely to change. 

When consumers buy vehicles, they consider both their personal characteristics (such as age, 

family composition, income, and their vehicle needs) and the characteristics of vehicles (e.g., 

vehicle size, fuel economy, and price). In response to the changes in vehicle characteristics, 

consumers will reconsider their purchases. Increases in fuel economy are likely to be attractive 

to consumers, but increases in price, as well as some changes in other vehicle characteristics, 

may be deterrents to purchase. As a result, consumers may choose a different vehicle than they 

would have purchased in the absence of the rule. The changes in prices and vehicle 

characteristics are likely to influence consumers on multiple market scales: the total number of 

new vehicles sold; the mix of new vehicles sold; and the effects of the sales on the used vehicle 

market. 

Consumer vehicle choice modeling (CCM) is a method used to predict what vehicles 

consumers will purchase, based on vehicle characteristics and prices. In principle, it should 

produce more accurate estimates of compliance costs compared to models that hold fleet mix 

constant, since it predicts changes in the fleet mix that can affect compliance costs. It can also be 

used to measure changes in consumer surplus, the benefit that consumers perceive from a good 

over and above the purchase price. (Consumer surplus is the difference between what consumers 

would be willing to pay for a good, represented by the demand curve, and the amount they 

actually pay. For instance, if a consumer were willing to pay $30,000 for a new vehicle, but 

ended up paying $25,000, the $5000 difference is consumer surplus.) 

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A number of consumer vehicle choice models have been developed. They vary in the methods 

used, the data sources, the factors included in the models, the research questions they are 

designed to answer, and the results of the models related to the effects of fuel economy on 

consumer decisions. This section will give some background on these differences among the 

models. 

8.1.2.11.1.1.1 Methods 

Consumer choice models (CCMs) of vehicle purchases typically use a form of discrete choice 

modeling. Discrete choice models seek to explain discrete rather than continuous decisions. An 

example of a continuous decision is how many pounds of food a farm might grow: the pounds of 

food can take any numerical value. Discrete decisions can take only a limited set of values. The 

decision to purchase a vehicle, for instance, can only take two values, yes or no. Vehicle 

purchases are typically modeled as discrete choices, where the choice is whether to purchase a 

specified vehicle. The result of these models is a prediction of the probability that a consumer 

will purchase a specified vehicle. A minor variant on discrete choice models estimates the 

market share for each vehicle. Because the market share is, essentially, the probability that 

consumers will purchase a specific vehicle, these approaches are similar in process; they differ 

mostly in the kinds of data that they use. 

The primary methods used to model vehicle choices are nested logit and mixed logit. In a nested 

logit, the model is structured in layers. For instance, the first layer may be the choice of whether 

to buy a new or used vehicle. Given that the person chooses a new vehicle, the second layer may 

be whether to buy a car or a truck. Given that the person chooses a car, the third layer may be 

the choice among an economy, midsize, or luxury car. Examples of nested logit models include 

Goldberg,i

 Greene et al.,ii and McManus.iii

In a mixed logit, personal characteristics of consumers play a larger role than in nested logit. 

While nested logit can look at the effects of a change in average consumer characteristics, mixed 

logit allows consideration of the effects of the distribution of consumer characteristics. As a 

result, mixed logit can be used to examine the distributional effects on various socioeconomic 

groups, which nested logit is not designed to do. Examples of mixed logit models include Berry, 

Levinsohn, and Pakes,iv Bento et al.,v

 and Train and Winston.vi 

While discrete choice modeling appears to be the primary method for consumer choice 

modeling, others (such as Kleitvii and Austin and Dinanviii) have used a matrix of demand 

elasticities to estimate the effects of changes in cost. The discrete choice models can produce 

such elasticities. Kleit as well as Austin and Dinan used the elasticities from an internal GM 

vehicle choice model. 

8.1.2.21.1.1.2 Data Sources 

The predictions of vehicle purchases from CCMs are based on consumer and vehicle 

characteristics. The CCMs identify the effects of changing the characteristics on the purchase 

decisions. These effects are typically called the parameters or coefficients of the models. For 

instance, the model parameters might predict that an increase in a person’s income of 10% would 

increase the probability of her purchasing vehicle A by 5%, and decrease the probability of her 

purchasing vehicle B by 10%. 

The parameters in CCMs can be developed either from original data sources (estimated models), 

or using values taken from other studies (calibrated models). 

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Estimated models use datasets on consumer purchase patterns, consumer characteristics, and 

vehicle characteristics to develop their original sets of parameters. The datasets used in these 

studies sometimes come from surveys of individuals’ behaviors.ix Because they draw on the 

behavior of individuals, they provide what is sometimes called micro-level data. Other studies, 

that estimate market shares instead of discrete purchase decisions, use aggregated data that can 

cover long time periods.x

 

Calibrated models rely on existing studies for their parameters. Researchers may draw on results 

from a number of estimated models, or even from research other than CCM, to choose the 

parameters of the models. The Fuel Economy Regulatory Analysis Model developed for the 

Energy Information Administrationxi and the New Vehicle Market Model developed by NERA 

Economic Consultingxii are examples of calibrated models. 

8.1.2.31.1.1.3 Factors Included in the Models 

Consumer choice models vary in their complexity and levels of analysis. Some focus only on 

the new vehicle market;xiii others consider the choice between new vehicles and an outside good 

(possibly including a used vehicle);xiv others explicitly consider the relationship between the new 

and used vehicle markets.xv Some models include consideration of vehicle miles traveled,xvi

though most do not. 

The models vary in their inclusion of both consumer and vehicle information. One model 

includes only vehicle price and the distribution of income in the population influencing 

choice;xvii others include varying numbers and kinds of vehicle and consumer attributes. 

8.1.2.41.1.1.4 Research Questions for the Models 

Consumer choice models have been developed to analyze many different research and policy 

questions. In part, these models have been developed to advance the state of economic 

modeling. The work of Berry, Levinsohn, and Pakes,xviii for instance, is often cited outside the 

motor vehicle context for its incorporation of multiple new modeling issues into its framework. 

In addition, because the vehicle sector is a major part of the U.S. economy and a stakeholder in 

many public policy discussions, research questions cover a wide gamut. These topics have 

included the effects of voluntary export restraints on Japanese vehicles compared to tariffs and 

quotas,xix the market acceptability of alternative-fuel vehicles,xx the effects of introduction and 

exit of vehicles from markets,xxi causes of the decline in market shares of U.S. automakers,xxii

and the effects of gasoline taxesxxiii and “feebates”xxiv (subsidizing fuel-efficient cars with 

revenue collected by taxing fuel-inefficient vehicles). 

8.1.2.51.1.1.5 The Effect of Fuel Economy on Consumer Decisions 

Consumer vehicle choice models typically consider the effect of fuel economy on vehicle 

purchase decisions. It can appear in various forms. 

Some modelsxxv incorporate fuel economy through its effects on the cost of owning a vehicle. 

With assumptions on the number of miles traveled per year and the cost of fuel, it is possible to 

estimate the fuel savings (and perhaps other operating costs) associated with a more fuelefficient vehicle. Those savings are considered to reduce the cost of owning a vehicle: 

effectively, they reduce the purchase price. This approach relies on the assumption that, when 

purchasing vehicles, consumers can estimate the fuel savings that they expect to receive from a 

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Summary of Interagency Working Comments on Draft Rule under EO 12866 

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more fuel-efficient vehicle and consider the savings equivalent to a reduction in purchase price. 

Turrentine and Kuranixxvi question this assumption; they find, in fact, that consumers do not 

make this calculation when they purchase a vehicle. The question remains, then, how or whether 

consumers take fuel economy into account when they purchase their vehicles. 

Most estimated consumer choice models, instead of making assumptions about how consumers 

incorporate fuel economy into their decisions, use data on consumer behavior to identify that 

effect. In some models, the miles per gallon of vehicles is one of the vehicle characteristics 

included to explain purchase decisions. Other models use fuel consumption per mile, the inverse 

of miles per gallon, as a measure:xxvii since consumers pay for gallons of fuel, then this measure 

can assess fuel savings relatively directly.xxviii Yet other models multiply fuel consumption per 

mile by the cost of fuel to get the price of driving a mile,xxix or they divide fuel economy by fuel 

cost to get miles per dollar.xxx It is worth noting that these last two measures assume that 

consumers respond the same way to an increase in fuel economy as they do to a decrease in the 

price of fuel when each has the same effect on cost per mile driven. On the one hand, while this 

assumption does not rely on as complex a calculation as the present value of fuel savings that 

Turrentine and Kurani examined, it suggests a calculating consumer. On the other hand, it is 

also a way to recognize the role of fuel prices in consumers’ purchase of fuel economy: Recent 

researchxxxi presents results that higher fuel prices play a major role in that decision. 

Greene and Liu,xxxii in a paper published in 1988, reviewed 10 papers using consumer vehicle 

choice models and estimated for each one how much consumers would be willing to pay at time 

of purchase to reduce vehicle operating costs by $1 per year. They found that people were 

willing to pay between $0.74 and $25.97 for a $1 decrease in annual operating costs for a 

vehicle. This is clearly a very wide range: while the lowest estimate suggests that people are not 

willing to pay $1 once to get $1 per year reduced costs of operating their vehicles, the maximum 

suggests a willingness to pay 35 times as high. For comparison, the present value of saving $1 

per year for 15 years at a 3% discount rate is $11.94, while a 7% discount rate produces a present 

value of $8.78. While this study is quite old, it suggests that, at least as of that time, consumer 

vehicle choice models produced widely varying estimates of the value of reduced vehicle 

operating costs. 

A new review from David Greenexxxiii suggests continued lack of convergence on the value of 

increased fuel economy to consumers. Of 22 studies, willingness to pay for fuel economy as a 

percent of the expected value of fuel savings varied from highly positive to highly negative. 

Roughly equal numbers of estimates found that consumers overvalued fuel economy, 

undervalued fuel economy, or roughly valued fuel economy correctly relative to fuel savings. 

Part of the difficulty may be, as these papers note, that fuel economy may be correlated (either 

positively or negatively) with other vehicle attributes, such as size, power, or quality, not all of 

which may be included in the analyses; as a result, “fuel economy” may in fact represent several 

characteristics at the same time. Indeed, Gramlichxxxiv includes both fuel cost (dollars per mile) 

and miles per gallon in his analysis, with the argument that miles per gallon measures other 

undesirable quality attributes, while fuel cost picks up the consumer’s demand for improved fuel 

economy. Greene finds that, while some of the variation may be explainable due to issues in 

some of the studies, the variation shows up in studies that appear to be well conducted. As a 

result, further work needs to be conducted before it is possible to identify one value that 

represents the role of fuel economy in consumer purchase decisions. 

Some studiesxxxv argue that automakers could increase profits by increasing fuel economy 

because the amount that consumers are willing to pay for increased fuel economy outweighs the 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

38 

costs of that improvement. Other studiesxxxvi have found that increasing fuel economy standards 

imposes welfare losses on consumers and producers, because consumers should already be 

buying as much fuel economy as they want. In the course of reaching this result, though, at least 

one of these studiesxxxvii notes that its baseline model implies that consumers are willing to buy 

more fuel economy than producers have provided; they have to adjust their model to eliminate 

these “negative-cost” fuel economy improvements. 

The models do not appear to yield very consistent results on the role of fuel economy in 

consumer and producer decisions. 

8.1.2.61.1.1.6 Why Consumers May Not Buy, and Producers May Not Provide, Fuel 

Economy that Pays for Itself 

If consumers are willing to pay for fuel-saving technologies, why does the market not already 

take advantage of these low-cost technologies? Why aren’t consumers demanding these vehicle 

improvements, and manufacturers supplying them, when they appear to “pay for themselves” 

even in the absence of regulation? While existing research does not offer full answers, i t is 

important to attempt to explore these questions, because under certain assumptions, the purely 

private benefits of fuel economy (fuel savings, time savings, increases in driving time) are likely 

to be accompanied by private losses. If there is no such offset, or if it is small or insignificant, the 

reason lies in some kind of market failure. 

A detailed literature attempts to identify possible market failures that would justify the 

assumption that the degree of consumer welfare loss is relatively small. On the consumer side, 

this disconnect between net present value estimates of energy-conserving cost savings and what 

consumers actually spend on energy conservation is often referred to as the Energy Paradox,xxxviii

since consumers appear to routinelyto undervalue a wide range of investments in energy 

conservation. Some possible explanations for the paradoxxxxix include: 

 Consumers put little weight on benefits from fuel savings economy in the future and 

show high discount rates; 

 Consumers do not find the benefits from fuel economy to be sufficiently salient at the 

time of purchase, even if it would be in consumers’ economic interest to take account 

of those benefits;

 Consumers consider other attributes more important than fuel economy at the time of 

vehicle purchase, especially if fuel economy is a relatively “shrouded” attribute; 

 Consumers may not be able to find the vehicles they want with improved fuel 

economy; 

 Consumers have difficulty in calculating expected fuel savings; 

 Consumers may use imprecise rules of thumb when deciding how much fuel 

economy to purchase; 

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Summary of Interagency Working Comments on Draft Rule under EO 12866 

39 

 Fuel savings in the future are uncertain; in contrastuncertain, while, at the time of 

purchase the increased costs of fuel-saving technologies are certain and immediate; 

 Consumers may not be able to find the vehicles they want with improved fuel 

economy; 



 There is likely to be variation among consumers in the benefits they get from 

improved fuel economy, due to different miles driven and driving styles. s.

Both theoretical and empirical research suggests that, in the context of fuel economy and 

elsewhere, many consumers do not make energy-efficient investments even when those 

investments would pay off in the relatively short-term.41 While tThis conclusion is in line with 

related findings that consumers may underweight benefits and costs that are less salient or that 

will be realized only in the future,.42 At the same time, it is worth noting that not all of the above 

explanations imply a market failure. 43 For instance, accounting for uncertainty in future fuel 

savings is rational, and , and it would not be in the interest of the government to force consumers 

to take on more risk than private decisions justify. Additionally, for some consumers, high 

observed discount rates may reflect the illiquidity of investments in fuel economy or high

opportunity costs of such investments where consumers are carrying high-interest-rate debt. 

There is disagreement in the literature regardingabout the degree to which these various 

explanations disentangle contribute to the Eenergy Pparadox, and additional empirical 

investigation is still needed.

The producer side of this paradox is much less studied. Hypotheses for underprovision of fuel 

economy by producers, related to those involving consumers, include: 

 Producers put more effort into attributes that consumers have regularly sought in the 

past, such as size and power, rather than fuel (and time) savings with uncertain future 

returns; 

 In selecting a limited number of vehicle attributes among which consumers can 

choose, producers may aim to provide choices related to characteristics (such as 

numbers of doors or transmission types) that strongly influence what vehicle a 

consumer will buy, and fuel economy and time savings may not make that list; 

 

41 Jaffe, A. B., and Stavins, R. N. (1994). The Energy Paradox and the Diffusion of Conservation Technology. 

Resource and Energy Economics, 16(2); see Hunt Alcott and Nathan Wozny, Gasoline Prices, Fuel Economy, and 

the Energy Paradox (2010, available at http://web.mit.edu/allcott/www/Allcott%20and%20Wozny%202010%20-

%20Gasoline%20Prices,%20Fuel%20Economy,%20and%20the%20Energy%20Paradox.pdf

43 Hossain, Janjim, and John Morgan (2009). “. . . Plus Shipping and Handling: Revenue (Non)Equivalence in Field 

Experiments on eBay,” Advances in Economic Analysis and Policy vol. 6; Barber, Brad, Terrence Odean, and Lu 

Zheng (2005). “Out of Sight, Out of Mind: The Effectsof Expenses on Mutual Fund Flows,” Journal of Business 

vol. 78, no. 6, pp. 2095-2020.

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numbering

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 No bullets or numbering
Summary of Interagency Working Comments on Draft Rule under EO 12866 

40 

 While consumer preferences for fuel economy may change rapidly as fuel prices 

fluctuate, producers cannot change their design or production decisions as rapidly

and; as a result, vehicle designs may end up not satisfying consumer desires at a 

particular time; 

 Producers may have misestimatedunderestimate the value that consumers place on 

fuel economy. 

How consumers buy, and producers provide, fuel economy involves complex decisions on both 

sides of the market. Both sides of the market rely heavily in their calculations on the uncertain 

benefits of fuel savings. In addition, consumers trade off fuel economy with many other vehicle 

attributes, and producers do not provide the full range of attributes possible for 

consumerssavings from fuel economy improvements. From this perspective, it may not be a 

surprise that, at a given point in time, consumer preferences for fuel economy may not match up 

with producer provision of it. 

8.1.2.71.1.1.7 Assessment of the Literature 

Consumer vehicle choice modeling in principle can provide a great deal of useful information for 

regulatory analysis, helping to answer some of the central questions about relevant effects on 

consumer welfare. All models estimate changes in fleet mix of new vehicles; some also provide 

estimates of total new vehicle sales; and a few incorporate the used vehicle market, potentially to 

the decision on when a vehicle is scrapped. Being able to model these changes has several 

advantages. 

First, consumer vehicle choice modeling has the potential to describe more accurately the impact 

of a policy, by identifying market shifts. More accurate description of the market resulting from 

a policy can improve other estimates of policy impacts, such as the change in vehicle emissions 

or vehicle miles traveled. The predictive ability of models, though, is not proven. It is likely 

that, in coming years, new vehicles will be developed, and existing vehicles will be redesigned, 

perhaps to have improvements in both fuel economy and safety factors in combinations that 

consumers have not previously been offered. Welch,xl for instance, argues that auto producers 

are likely to increase the sizes of vehicles in response to the footprint-based fuel economy 

standard. Models based on the existing vehicle fleet may, however, not do well in predicting 

consumers’ choices among the new vehicles offered. One attempt to analyze the effect of the oil 

shock of 1973 on consumer vehicle choice found that, after two years, the particular model did 

not predict well due to changes in the vehicle fleet.xli Thus, consumer vehicle choice models, 

even if they did produce robust results in analyzing the short-term effects of policy changes, may 

miss changes associated with new and redesigned vehicles. 

The modeling may improve estimates of the compliance costs of a rule. Most current modeling 

is based on a fleet mix determined outside the model; neither vehicle manufacturers nor 

consumers respond directly to cost increases and other vehicle changes by a change in the fleet 

mix. With the use of consumer vehicle choice modeling, both consumers and producers have 

greater choices in response to these changes: they can either accept the new costs and vehicle 

characteristics, or they can change which vehicles are sold. The fact that consumers and 

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Summary of Interagency Working Comments on Draft Rule under EO 12866 

41 

producers have additional options suggests that compliance costs are likely to be lower through 

incorporation of a consumer choice model than through use of a technology-cost model alone. 

On the other hand, the effect may not be large: in the context of “feebates” (subsidizing fuelefficient cars with revenue collected by taxing fuel-inefficient vehicles), Greene et al. found that 

95% of the increase in fuel economy was due to addition of technology rather than changes in 

vehicles sold.xlii Consideration of consumer behavior in welfare estimates will improve 

regulatory analysis, but only to the extent that the predicted changes in consumer purchase 

patterns reflect actual changes. 

An additional complication associated with consumer choice modeling is accurate prediction of 

producers’ responses to the rule. Auto makers not only predict consumers’ preferences for 

vehicles; they also may seek to influence those preferences through marketing and advertising.xliii 

In addition, auto makers are commonly considered to have market power; they can influence the 

prices that consumers pay to increase their profits. As a result, the price increases that 

consumers face may reflect strategic factors that could make them higher or lower than the 

technology costs. Including these market features into consumer vehicle choice models is a 

complex undertaking. Not all consumer vehicle choice models include a producer model, and 

those that do may not include much detail, due to computational limits. Technology costs still 

represent an accurate measure of the opportunity cost of resources to society, but they may 

overestimate or underestimate the effect on the prices that consumers face. Firms with market 

power usually pass along less than full cost increases, in order not to reduce sales very much. As 

a result, for most vehicles the increased technology costs may not equal the price increases that 

consumers will see. 

An additional feature of consumer choice models, as noted above, is that they can be used to 

calculate consumer surplus impacts on vehicle purchase decisions. Consumer surplus is a 

standard measurement of consumer impacts in benefit-cost analysis. Consumer surplus 

calculations from these models estimate how much consumers appreciate the gains in fuel 

economy relative to the increased vehicle costs that they face, based on the assumption that 

consumers, at the time of vehicle purchase, have made the best decisions for themselves on the 

amount of fuel economy in the vehicles they purchase. These values, though, are based on the 

relationship between consumer willingness to pay for fuel economy and the costs of improved 

fuel economy. Because the estimates of consumer willingness to pay for fuel economy appear to 

be highly inconsistent, consumer surplus measures from any one model are unlikely to be 

reliable. 

Principles of welfare analysis can be useful for understanding the role of consumer vehicle 

choice models in benefit-cost analysis. Consumer welfare is commonly measured as the change 

in income that would leave the consumer as well off in the presence of the change (in this case, 

the increase in fuel economy and vehicle price) as in the absence of the change; this amount is 

known as compensating variation, since the consumer is compensated for the change.44 If the 

vehicle has not changed other than those two characteristics, then a consumer has the choices of 

 

44 A closely related concept, equivalent variation, measures the change in income that would be a perfect 

substitute for the increased fuel economy and vehicle cost. These measures differ based on whether the basis for 

evaluation is the consumer’s utility before the change (compensating variation) or the consumer’s utility after the 

change (equivalent variation). In practice, the difference between these two measures is typically very small for 

marketed goods. 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

42 

(i) paying the higher price for the vehicle, (ii) choosing to buy a different vehicle, or (iii) not 

buying a new vehicle. The only reason the consumer would decide to pay the higher price, (i), is 

if this option is preferable to the other two options. If the consumer cares nothing about the 

increased fuel economy but is given an amount of money equal to the price increase, she is at 

least as well off as before the price increase: she can still buy the original vehicle (which has 

improved fuel economy but is otherwise identical), or she can still choose options (ii) or (iii). 

Thus, the price increase due to the rule is an upper bound on the consumer’s welfare loss, if no 

other vehicle characteristics of interest to the consumer has changed. If the consumer actually 

appreciates the improved fuel economy, the welfare loss is even smaller. However, if the vehicle 

has changed due to the fuel economy increase in ways other than price and fuel economy, or if 

there are additional costs associated with these vehicles not included in the analysis, then there 

may be additional welfare impacts that are not included in the technology cost estimates. 

At this point, it is unclear whether two consumer vehicle choice models given the same scenario 

would produce similar results in either prediction of changes in the vehicles purchased or in 

estimates of consumer surplus effects. The estimates of consumer surplus from consumer 

vehicle choice models depend heavily on the value to consumers of improved fuel economy, a 

value for which estimates are highly varied. In addition, the predictive ability of consumer 

vehicle choice models may be limited as consumers face new vehicle choices that they 

previously did not have. If the results across models are not consistent or are highly sensitive to 

parameters or other features, then careful thought needs to be given to model selection and 

development. 

Given the current limitations in modeling the role of fuel economy in vehicle purchase 

decisions, and limitations in modeling market responses to the new regulations, in this 

rulemaking EPA compares the fuel (and other) savings that consumers will receive with the 

technology costs of the vehicles. The regulations have been carefully designed so that the full 

range of vehicle choices in the marketplace could be maintained; rigorous technological 

feasibility, cost, and lead-time analysis has showed that the standards could be met while 

maintaining current levels of other vehicle attributes. For these reasons, EPA believes that 

consumers will enjoy significant savings that substantially outweigh any likely consumer welfare 

losses.. Nonetheless, EPA continues to consider these questions, andbecause there are potential 

advantages to using consumer vehicle choice models if these difficulties can be addressed, EPA 

is continuing to explore options for including consumer and producer choice in modeling the 

impacts of fuel economy-related regulations. This effort includes further review of existing 

consumer vehicle choice models, and the estimates of consumers’ willingness to pay for 

increased fuel economy, and overall effects on consumer welfare. 

In addition, EPA is developing capacity to examine the factors that may affect the results 

of consumer vehicle choice models, and to explore their impact on analysis of regulatory 

scenarios. Under contract with EPA, Resources for the Future (RFF) is developing a model of 

the vehicle market that can be used to evaluate different policy designs and compare regulatory 

scenarios on the basis of changes in cost, changes in the prices paid by consumers, changes in 

consumer welfare, and changes in industry profits. It should help to shed light on whether it is 

more costly to rely solely on the application of technologies to vehicles to meet a given fuel 

standard than when consumer and producer behavior is taken into account. EPA plans to 

evaluate this work within the context of the overall literature on consumer vehicle choices, to 

determine its usefulness in informing the analysis for future rules. 

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Summary of Interagency Working Comments on Draft Rule under EO 12866 

43 

 

i

 Goldberg, Pinelopi Koujianou, “Product Differentiation and Oligopoly in International Markets: The Case of the 

U.S. Automobile Industry,” Econometrica 63(4) (July 1995): 891-951 (Docket EPA-HQ-OAR-2009-0472-0021); 

Goldberg, Pinelopi Koujianou, “The Effects of the Corporate Average Fuel Efficiency Standards in the US,” Journal 

of Industrial Economics 46(1) (March 1998): 1-33 (Docket EPA-HQ-OAR-2009-0472-0017). 

ii Greene, David L., K.G. Duleep, Doug Elliott, and Sanjana Ahmad, “A Fuel Economy Regulatory Analysis Model 

(FERAM) For the Energy Information Administration,” prepared by the Oak Ridge National Laboratory for the U.S. 

Department of Energy under contract No. DE-AC0500OR22725, 2005 (Docket EPA-HQ-OAR-2009-0472-0022); 

Greene, David L., Philip D. Patterson, Margaret Singh, and Jia Li, “Feebates, Rebates, and Gas-Guzzler Taxes: A 

Study of Incentives for Increased Fuel Economy,” Energy Policy 33 (2005): 757-775 (Docket EPA-HQ-OAR-2009-

0472-0023). 

iii McManus, Walter M., “Can Proactive Fuel Economy Strategies Help Automakers Mitigate Fuel-Price Risks?” 

University of Michigan Transportation Research Institute, September 14, 2006 (Docket EPA-HQ-OAR-2009-0472-

0024). 

iv Berry, Steven, James Levinsohn, and Ariel Pakes, “Automobile Prices in Market Equilibrium,” Econometrica

63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-2009-0472-0025); Berry, Steven, James Levinsohn, and Ariel 

Pakes, “Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car 

Market,” Journal of Political Economy 112(1) (2004): 68-105 (Docket EPA-HQ-OAR-2009-0472-0026). 

v

 Bento, Antonio M., Lawrence H. Goulder, Emeric Henry, Mark R. Jacobsen, and Roger H. von Haefen, 

“Distributional and Efficiency Impacts of Gasoline Taxes: An Econometrically Based Multi-Market Study,” 

American Economic Review 95(2) (May 2005): 282-287 (Docket EPA-HQ-OAR-2009-0472-0029). 

vi Train, Kenneth E., and Clifford Winston, “Vehicle Choice Behavior and the Declining Market Share of U.S. 

Automakers,” International Economic Review 48(4) (November 2007): 1469-1496 (Docket EPA-HQ-OAR-2009-

0472-0030). 

vii Kleit, Andrew N., “Impacts of Long-Range Increases in the Fuel Economy (CAFE) Standard,” Economic Inquiry

42(2) (April 2004): 279-294 (Docket EPA-HQ-OAR-2009-0472-0031). 

viii Austin, David, and Terry Dinan, “Clearing the Air: The Costs and Consequences of Higher CAFE Standards and 

Increased Gasoline Taxes,” Journal of Environmental Economics and Management 50 (2005): 562-582 (Docket 

EPA-HQ-OAR-2009-0472-0032). 

ix E.g., Bento, Antonio M., Lawrence H. Goulder, Emeric Henry, Mark R. Jacobsen, and Roger H. von Haefen, 

“Distributional and Efficiency Impacts of Gasoline Taxes: An Econometrically Based Multi-Market Study,” 

American Economic Review 95(2) (May 2005): 282-287 (Docket EPA-HQ-OAR-2009-0472-0029); Train, 

Kenneth E., and Clifford Winston, “Vehicle Choice Behavior and the Declining Market Share of U.S. Automakers,” 

International Economic Review 48(4) (November 2007): 1469-1496 (Docket EPA-HQ-OAR-2009-0472-0030). 

x

 E.g., Berry, Steven, James Levinsohn, and Ariel Pakes, “Automobile Prices in Market Equilibrium,” Econometrica

63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-2009-0472-0025). 

xi Greene, David L., K.G. Duleep, Doug Elliott, and Sanjana Ahmad, “A Fuel Economy Regulatory Analysis Model 

(FERAM) For the Energy Information Administration,” prepared by the Oak Ridge National Laboratory for the U.S. 

Department of Energy under contract No. DE-AC0500OR22725, 2005 (Docket EPA-HQ-OAR-2009-0472-0022). 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

44 

 xii NERA Economic Consulting, “Evaluation of NHTSA’s Benefit-Cost Analysis of 2011-2015 CAFE Standards,” 

2008, available at 

http://www.heartland.org/policybot/results/23495/Evaluation_of_NHTSAs_BenefitCost_Analysis_Of_20112015_C

AFE_Standards.html (Docket EPA-HQ-OAR-2009-0472-0033). 

xiii E.g., Train, Kenneth E., and Clifford Winston, “Vehicle Choice Behavior and the Declining Market Share of U.S. 

Automakers,” International Economic Review 48(4) (November 2007): 1469-1496 (Docket EPA-HQ-OAR-2009-

0472-0030). 

xiv E.g., Berry, Steven, James Levinsohn, and Ariel Pakes, “Automobile Prices in Market Equilibrium,” 

Econometrica 63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-2009-0472-0025). 

xv E.g., Bento, Antonio M., Lawrence H. Goulder, Emeric Henry, Mark R. Jacobsen, and Roger H. von Haefen, 

“Distributional and Efficiency Impacts of Gasoline Taxes: An Econometrically Based Multi-Market Study,” 

American Economic Review 95(2) (May 2005): 282-287 (Docket EPA-HQ-OAR-2009-0472-0029). 

xvi Bento, Antonio M., Lawrence H. Goulder, Emeric Henry, Mark R. Jacobsen, and Roger H. von Haefen, 

“Distributional and Efficiency Impacts of Gasoline Taxes: An Econometrically Based Multi-Market Study,” 

American Economic Review 95(2) (May 2005): 282-287 (Docket EPA-HQ-OAR-2009-0472-0029); Feng, Yi, Don 

Fullerton, and Li Gan, “Vehicle Choices, Miles Driven and Pollution Policies,” National Bureau of Economic 

Analysis Working Paper 11553, available at http://econweb.tamu.edu/gan/w11553.pdf , accessed 5/12/09 (Docket 

EPA-HQ-OAR-2009-0472-0034). 

xvii NERA Economic Consulting, “Appendix B: New Vehicle Market Model,” “Impacts of the California 

Greenhouse Gas Emission Standards on Motor Vehicle Sales,” comments submitted to the U.S. Environmental 

Protection Agency at Regulations.gov, document number EPA-HQ-OAR-2006-0173-9053.1 (Docket EPA-HQOAR-2009-0472-0035). 

xviii Berry, Steven, James Levinsohn, and Ariel Pakes, “Automobile Prices in Market Equilibrium,” Econometrica

63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-2009-0472-0025). 

xix Goldberg, Pinelopi Koujianou, “Product Differentiation and Oligopoly in International Markets: The Case of the 

U.S. Automobile Industry,” Econometrica 63(4) (July 1995): 891-951 (Docket EPA-HQ-OAR-2009-0472-0021). 

xx Brownstone, David, and Kenneth Train, “Forecasting New Product Penetration with Flexible Substitution 

Patterns,” Journal of Econometrics 89 (1999): 109-129 (Docket EPA-HQ-OAR-2009-0472-0036); Brownstone, 

David, David S. Bunch, and Kenneth Train, “Joint Mixed Logit Models of Stated and Revealed Preferences for 

Alternative-Fuel Vehicles,” Transportation Research Part B 34 (2000): 315-338 (Docket EPA-HQ-OAR-2009-

0472-00357); Greene David L., “TAFV Alternative Fuels and Vehicles Choice Model Documentation,” prepared by 

the Oak Ridge National Laboratory for the U.S. Department of Energy, July 2001 (Docket EPA-HQ-OAR-2009-

0472-0038); Greene, David L., K. G. Duleep, and Walter McManus, “Future Potential of Hybrid and Diesel 

Powertrains in the U.S. Light-Duty Vehicle Market,” prepared by the Oak Ridge National Laboratory for the U.S. 

Department of Energy, August 2004 (Docket EPA-HQ-OAR-2009-0472-0039). 

xxi Petrin, Amil, “Quantifying the Benefits of New Products: The Case of the Minivan,” Journal of Political 

Economy 110 (2002): 705-729 (Docket EPA-HQ-OAR-2009-0472-0040); Berry, Steven, James Levinsohn, and 

Ariel Pakes, “Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New 

Car Market,” Journal of Political Economy 112 (2004): 68-105 (Docket EPA-HQ-OAR-2009-0472-0026). 

xxii Train, Kenneth E., and Clifford Winston, “Vehicle Choice Behavior and the Declining Market Share of U.S. 

Automakers,” International Economic Review 48 (November 2007): 1469-1496 (Docket EPA-HQ-OAR-2009-

0472-0030). 
Summary of Interagency Working Comments on Draft Rule under EO 12866 

45 

 xxiii Bento, Antonio M., Lawrence H. Goulder, Emeric Henry, Mark R. Jacobsen, and Roger H. von Haefen, 

“Distributional and Efficiency Impacts of Gasoline Taxes: An Econometrically Based Multi-Market Study,” 

American Economic Review 95(2) (May 2005): 282-287 (Docket EPA-HQ-OAR-2009-0472-0029); Feng, Yi, Don 

Fullerton, and Li Gan, “Vehicle Choices, Miles Driven and Pollution Policies,” National Bureau of Economic 

Analysis Working Paper 11553, available at http://econweb.tamu.edu/gan/w11553.pdf , accessed 5/12/09 (Docket 

EPA-HQ-OAR-2009-0472-0034). 

xxiv Greene, David L., Philip D. Patterson, Margaret Singh, and Jia Li, “Feebates, Rebates, and Gas-Guzzler Taxes: 

A Study of Incentives for Increased Fuel Economy,” Energy Policy 33 (2005): 757-775 (Docket EPA-HQ-OAR2009-0472-0023); Feng, Yi, Don Fullerton, and Li Gan, “Vehicle Choices, Miles Driven and Pollution Policies,” 

National Bureau of Economic Analysis Working Paper 11553, available at 

http://econweb.tamu.edu/gan/w11553.pdf , accessed 5/12/09 (Docket EPA-HQ-OAR-2009-0472-0034); Greene, 

David L., “Feebates, Footprints and Highway Safety,” Transportation Research Part D (2009) (in press) (Docket 

EPA-HQ-OAR-2009-0472-0019). 

xxv E.g., Austin, David, and Terry Dinan, “Clearing the Air: The Costs and Consequences of Higher CAFE 

Standards and Increased Gasoline Taxes,” Journal of Environmental Economics and Management 50 (2005): 562-

582 (Docket EPA-HQ-OAR-2009-0472-0032). 

xxvi Turrentine, Thomas S., and Kenneth S. Kurani, “Car Buyers and Fuel Economy?” Energy Policy 35 (2007): 

1213-1223 (Docket EPA-HQ-OAR-2009-0472-0041). 

xxvii E.g., Espey, Molly, and Santosh Nair, 2005. “Automobile Fuel Economy: What Is It Worth?” Contemporary 

Economic Policy 23: 317-323 (Docket EPA-HQ-OAR-2009-0472-0042). 

xxviii Larrick, Richard P., and Jack B. Soll, 2008. “The MPG Illusion,” Science 320(5883): 1593-1594 (Docket 

EPA-HQ-OAR-2009-0472-0043). 

xxix E.g., Goldberg, Pinelopi Koujianou, “Product Differentiation and Oligopoly in International Markets: The Case 

of the U.S. Automobile Industry,” Econometrica 63(4) (July 1995): 891-951 (Docket EPA-HQ-OAR-2009-0472-

0021). 

xxx E.g., Berry, Steven, James Levinsohn, and Ariel Pakes, “Automobile Prices in Market Equilibrium,” 

Econometrica 63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-2009-0472-0025). 

xxxi Busse, Meghan, Christopher R. Knittel, and Florian Zettelmeyer, 2009. “Pain at the Pump: How Gasoline 

Prices Affect Automobile Purchasing in New and Used Markets,” working paper, 

http://www.econ.ucdavis.edu/faculty/knittel/papers/gaspaper_latest.pdf (accessed 6/16/09) (Docket EPA-HQ-OAR2009-0472-0044); Li, Shanjun, Christopher Timmins, and Roger H. von Haefen, 2009. “How Do Gasoline Prices 

Affect Fleet Fuel Economy?” American Economic Journal: Economic Policy 1(2): 113-137; Congressional Budget 

Office (2008). Effects of Gasoline Prices on Driving Behavior and Vehicle Markets. The Congress of the United 

States, Pub. No. 2883; West. Sarah (2007). “The Effect of Gasoline Prices on the Demand for Sport Utility 

Vehicles.” Working Paper. Macalester College, http://www.macalester.edu/~wests/SarahWestMEA2007.pdf, 

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