From: "Achanta, Chandana L." <Ch andana_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 summ arizing 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 25 th



## .

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 Establis h Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards”. They are for your

consideration and s ubject 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 paragrap h in the Preamble discussion of ICM as

well.

“One of the sensitivity analyses perfor med 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 discussi ng 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 gi ven 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 th e 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-vehicl e 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 st udy 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 co efficients of we ight reduction while maintaining footprint in the statistical analyses of hi storical data. As discussed above, presenting this scenario is possible because NHTSA was able to separate the effects of weight and footprin t 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 expe rt 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 chos e the adjust those coefficients. 9) Page. 6 states that mass reduction co uld be achieved through various means, including “reduced powertrain require ments.” 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 footpr int 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 st atistical approaches described in the document? For example, on page 26 it is noted that “using material substitution

and other current mass reduction methods c ould 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 comi ng years”. Surely, simulation and modeling efforts can likely help address such questions now. 12) Page 2 ¶2 line 13: It is noted an “unmodi fied 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 regressi on scenario. It would be useful to describe the scenario here, or note to see Section 3 a nd 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 experi ence 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 da ta 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 manuf acturers 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 pass enger cars the upper-estimate scenario is the actual regression result.

17) If Kahane’s 2010 report has not been p eer 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 st andards 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 econom y increases have occurr ed in the past, andthe 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 ve hicle 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 f ootprint-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 incr easing fuel economy and reducing CO 2 

### emissions, and the agencies have incorporated this expect ation into our modeling analysis supporting today’s final standards. NHTS A’s previous analyses examin ing the relationship between vehicle mass and fatalities found fatality in creases as vehicle we ight and size were reduced, but these previous analyses did not differentiate between we ight 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 inform ation about safety in the CA FE 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 di scussed 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 fr om 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 concer ning mass and size reduction in MYs 1991- 1999 vehicles, and evaluated a “worst-case scen ario” in which the safety effects of the

combined reductions of both mass and size for those vehicles were determined for the future passenger car an d light truck fleets. 1 

### In the NPRM analysis, mass and size could not be separated from one an other, resulting in what NHTSA recognized was a larger safety disbenefit than was likely unde r 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 si gnificantly 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, w ithin the limits of our current knowledge, the potential safety effects of future mass re duction 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 passenge r 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 re ductions 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 re sults of the peer review and any subs equent 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 conv ey a sense of bounding for potential safety

effects of reducing mass while hol ding footprint constant . The upper-estimate scenario reflects potential safety effects given the re port’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 co llisions 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 like through 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 signif icant increase if footprint is reduced.

4 We note that there may be some (currently non-qua ntifiable) 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 comput er 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 sect ional thicknesses of structural components to reduce mass while maintaining or improving the function of th e 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 rede signed with a lighter “unibody” construction. Comment [A8]: Please insert this important point.

Comment [A9]: You should make explicit thatany 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 bene ficial 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 th e 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 a nd 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 accu rately 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), ligh t 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 driver s 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 perc ent of baseline curb weight, depending on vehicle subclass, in response to recently-submitted manufacturer product plans as well as public statements indicating that these leve ls were possible and likely. 5-10 percent represented a maximum bound; EPA’s modeling, for example, included average vehicleweight 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 rede signs 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 ma nufacturers 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 fata lities 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 Kaha ne’s 2003 percentages to a baseline of

2007 fatalities were then mu ltiplied by 0.874 to account for changes that the agency believed would take place in passenger ca r 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 th e actual on-road safety experience of 1991-1999 vehicles. For those vehicles, heavier usually also mean t 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 a alter

a vehicle’s physical dimensions. This is because as footprint decreases, the corresponding fuel economy/GHG emi ssion 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 acco unted 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 re quire electronic stability control in all new vehicles by MY 2012, and the upgrade to Federal Motor Ve hicle Safety Standard No. 214 (Side Impact Protection, 49 CFR 571.214) will li kely result in all new ve hicles 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 ba se resulted in smaller absolute increases than those that were predicted in the 2003 report.

8 We note, however, that vehicle foot print 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 crus h 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. T hus, t he 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 standard s, 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 woul d be accomplished by strategies, such as material substitution, smart design, re duced powertrain requirements, and mass compounding, that have a lesser safety effect than the prevalent 19 80s strategy of simply making the vehicles smaller. The agencies noted that to the extent that future mass reductions could be achieved by these met hods—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 reduc tion could be evaluated, particularly in relation to the worst-case scenario presente d 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 th e low numbers of vehicles in the current onroad fleet that have utilized these technologies extensively. Further, to the extent that mass reductions were accomplished thro ugh 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 wh ile it thought materi al substitution and

other methods of mass reduction could consider ably 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 st andards discourage downsizing as a wa y of “balancing out” sales of larger/heavier vehicles, they do not discour age manufacturers from reducing crush space

manufacturer has confidentially indicated plans to re duce overhang as a way of reducing mass on some vehicles during the rulemaking time frame. Addition ally, 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 th at 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 explai n 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 th e weight reduction is achieved.

NHTSA also noted in the NPRM that several studies by Dynamic Research, Inc. (DRI) had been repeatedly cited to the agen cy in support of the pr oposition that reducing vehicle mass while maintaining track widt h 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 wei ght and size (in terms of wheelbase and track width) on safety, and presented results indi cating 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 FA RS 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 “muscl e” cars, which have particular ly 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 regr ession analysis of historical data is appropriate, and indeed has no overly-biasing effects.

The 2005 DRI studies also differed from th e 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 re ductions 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 rati ngs 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, NH TSA 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 th at mass reduction could be an important tool for achieving higher levels of fuel economy and reducing CO 2 

### 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 agenc ies receive on the safety analysis

and discussions in the NPRM?

Several dozen commenters a ddressed the safety issue. Claims/arguments made by c C omments 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 heavie r 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 r R easons that NHTSA and DRI may have reached different

conclusions:

 NHTSA’s study should distinguish be tween 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 wi th regard to future standards beyond MY 2016. The agencies are committed to analyz ing this issue thoroughly and holistically going forward, based on the best available scie nce, in order to further their closely related missions of safety, energy co nservation, 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 co nsiders 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 inaccu rate 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 ar e 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, beca use additional weight inheren tly makes a vehicle safer to its own occupants, citing the 2003 Kahane re port, while AISI argued that Desapriya had found that passenger car drivers and occupant s 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 NH TSA’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 Associat ion, 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 advan ced materials for lightweighting purposes and other engineering advances. The Aluminum Association stated that advanced vehicle design and construction techni ques using aluminum can impr ove 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 li kely be encouraged to build smaller and lighter vehicles in order to achieve complian ce, 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 progra ms 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 an alyses in the NPRM and final rule are

based in the next several mont hs 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 th e NPRM would not have enabled the agency to complete it and then conduct a new anal ysis 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 al uminum-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 vehi cles 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 relationship s 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 database s due to the presence of these vehicles, but any such changes are likely to be slow and ev olutionary, 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 flee t, driving population, and op erating environm ent 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 popula tion (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 coul d 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-achie ving 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 th e vehicle’s mass and adds new safety equipment to it, thus creating a variant (vehicle A 1 ), 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 A 1 might not be as safe as second variant (vehicle A 2 ) 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 appl y to CAD?

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

15 heavier light trucks could be reduced in we ight 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 safe ty would be different if they did. We emphasize that our estimates are based on th e 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 heavie r 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 be tter,” 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 tr ack, because “Crash avoidance can depend, amongst other factors, on the vehicle directio nal control and rollover characteristics.” DRI argued that, therefore, “These results in dicate that vehicle we ight 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 em pirical 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 pr esents a discussion of improved accident avoidance as vehicle mass is reduced in Chapte r 7.6 of its final RIA. The important point to emphasize is that it depends on the situat ion – it would oversimplify drastically to point to one situation in which extra mass he lps 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 pi ckups 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 cent er of gravity height

14 This is due to the beneficial e ffect 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, wh ile 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 hi gher collision-involvement rate s than heavier cars – even

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

issue. 15 

### Based on our analyses using nationally-c ollected 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, spee ding, 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 powerfu l 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). Correl ation 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 ar gued that NHTSA should acknowledge that other vehicle attributes may be as important, if not more importa nt, than vehicle weight or footprint in terms of occupant safety, su ch as unibody construction as compared to ladder-frame, lower bumpers, and less rigi d 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 in trusion 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 origin al views about compatib ility,” which thought

that mass and the mass ratio were the dominant factors. Since footprint-based standards will encourage the reduction of vehicle we ight 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 factor s 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 th an truck-based SUVs, there are no analyses that attribute the improved safety to mass alon e, 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 vehi cles without necessarily harming their own drivers and occupants. Moreover, in th e 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 g ood for elderly and child occupa nt 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

s S ignificant 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 attri bute-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 smal ler, 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 mi tigate safety risks, while others stated that there would still be safety risks even with footprint-based standards – CEI, for example, argued that mass reduc tion 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 sa fety (CEI, Congress of Racial Equal ity, Heritage Foundation, IIHS, Spurgeon, University of PA Environmental Law Project) or whether they believed that the co rrelation was less clear, for example because they believed that vehicle desi gn 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 crus h space and worsen vehicle handling.

U.S. Steel and AISI both co mmented 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 st udents 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 La w 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 passeng er 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-f ootprint 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 a nd 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 th e characteristics of passenger cars, and the light truck curve should be based on the charact eristics 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 vehi cle 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 potenti al 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 regu lations 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’ sugge stions and notes that the agency is continually striving to improve motor vehicle sa fety consistent with its mission. As noted above, improving safety in other areas affects the target population that the mass/footprint relationship co uld 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 th ey might otherwise be absent the final MYs

2012-2016 standards. It does consider the eff ect of known safety regulations as they are projected to affect th e 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 wi de range in casualty ri sk for vehicles with the same weight or footprint. Wenzel stated that for drivers, casualty risk does generally decrease as weight or footprint increases, es pecially for passenger cars, but the degree of variation in the data for vehicles (particularl y 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 eff ect 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 c ited, 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 ma ss 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 path s between the impacting object and the occupant compartment during the crash event. It is therefore difficult to predict

and assess structural interacti ons 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 re quire 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 re lative 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 cited 22 

### 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 respons e characteristics.” Mr. Wenzel implies the latter can “isolate the effect of specific design changes, such as weight reduction” and thus quantify the fleet-w ide effect of substantial vehicl e redesigns. Yet while Kebschull reports injury reductions to three significant digits, there is no va lidation that vehicle structures of the proposed weight and stiffness are even feasib le 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 vehicl es 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, “Estima tion of the Effects of Vehicle Size and Mass on CrashInjury Outcome Through Parameterized Probability Ma nifolds,” Society of Automotive Engineers (2003),

Document No. 2003-01-0905. Available at http://www.sae.or g/technical/papers/2003-01-0905 (last accessed Feb. 15, 2010).

22 Mr. Wenzel cites the report by Kebschull et al [2 004, 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 no t 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 lo ad-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. NHT SA 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 e xperience 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 wei ght 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 diff erent 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 we ight 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 eq ually to mass and footprint – that is, the effect of reducing mass alone is abou t 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 reduc ing weight without reducing size; while NHTSA did find a safety bene fit 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 diff erent 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 analys is 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

24door 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 shou ld include 2-door cars in its analysis.

Wenzel also commented that NHTSA should in clude 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 driv er 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 suffici ent 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 incl usion 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 passe nger cars due to mass reduction.

NHTSA and DRI may have reached diff erent conclusions due to different assumptions

DRI commented that the differences f ound 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 othe r control variables. DRI suggested that this may also affect the

results and cause or contribute to the diff erences in outcomes between NHTSA and DRI.

Agencies’ response:

NHTSA’s FRIA documents that NHTSA analy zed 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 regres sion 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 nu mber of control variab les 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 fa talities with a 100 pound reduction while maintaining track width and wh eelbase. 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 provi de 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 woul d 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 histori cal 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 hist orical 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 anal ysis. However, even the new analysis of LTVs produced some coefficients that NHTS A 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 su ch 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 whic h 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 stro ng, natural and historic al correlation of mass

and size – can lead to inaccurate statistical estimates of their effects. 25 

### NHTSA has performed new statistical analyses of its hi storical 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 Kaha ne 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 hazards 26 

### 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 re port attempt to account for the differences primarily by applying selected techniques fr om DRI’s analyses to NHTSA’s database.

The statistical analyses – logistic re gressions – 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 th ese effects might conceivably carry over to future mass reductions, there are two reasons that future safety effects of mass reduction could differ from projecti ons from historical data:

25 Greene, W. H. (1993). Econometric Analysis , Second Edition. New Yo rk: 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 infl ation 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 re lationships between curb weight and dependent variables by sp litting 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 rate s 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 anal yses 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 histor ical 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 re gression method of the 2003 Kahane report estimates an increase of 700-800 fatali ties 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 car s). 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 fi ndings 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 unbiased 28 

### . 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 depend ent 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 fa tality risk in MY 1991-1999 cars generally increased and rarely decreased for lighter rela tive to heavier cars of the same footprint

. They suggest that the historical, cross-s ectional trend wa s 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 pedestrian s) 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, exceed ing the 2.5 level where near multicollinearity begins to become a concern in logistic regression analyses.

28 Section 2.3 of the 2010 Kahane re port attempts to explain why the two-step method, when applied to NHTSA’s 2003 database, produces results a lot like DR I’s, but it does not claim that DRI obtained its results from its own database for exactly those reason s. 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.iih s.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, ht tp://www.iihs.org/research/hldi/fa ct_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 re port 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 an d 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 LTV s has a harmful effect (for the LTVs’ own occupants), as in cars. The regression met hod 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-f oot 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 ve hicles. 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 th e 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 ExpertOpinion UpperEstimate

Scenario 32 

### NHTSA ExpertOpinion 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 ef fects of a 100-pound mass reduction while maintaining footprint are an increase in fa talities 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 w ill 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 influen ced 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 in crease in the cars < 2,950 pounds and the societal fatality reduction attri buted 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 safe ty 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 describe d 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 manufact urer’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 w ithout 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 esti mate,” 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 be tter if it was undertaken with a thorough and extensive vehicle redesign to maximi ze 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 ne ver 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 ca n and do recognize that the f ootprint-based standards will significantly limit the likelihood of its occurre nce 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 CO 2 

### 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 a ccount better for the possibility that mass reduction will be accomplished entirely th rough 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 be neficial if mass reduction is carefully

undertaken in the future and if the mass re duction 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 begi n 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 studi es and independent research, to the extent possible, to help ensure the work is comple mentary 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 agen cy— 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 a ll 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 resp onse to the NPRM in developing plans for

future studies and rese arch 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 understa nd 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 analy ze 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 statisti cal 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 consultati on 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 a ffect 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 an d 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 stiffn ess and whether any trends identified impact occupant injury response in crashes. Vehi cle manufacturers may employ stiffer light weight materials to limit occupant compartment intrusion while controlling for mass that may expose the occupants to high er 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 sa fety of newer vehicle designs.

In addition, NHTSA and EPA, possibly in collaboration with DOE, may conduct a longer-term computer modeling-based design an d analysis study to help determine the maximum potential for mass reduction in th e MYs 2017-2021 timeframe, through direct material substitution and smart design while meeting safety regulat ions and guidelines, and maintaining vehicle size and functionality. This study may build upon prior research completed on vehicle mass reduction. Th is study would further explore the comprehensive vehicle effects, including dissimilar material joining technologies, manufacturer feasibility of both supplier a nd 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 privat e gains to consumers in three major areas: (1) reductions in spending on fuel, (2) time saved du e to less refueling, a nd (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 offere d 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 thos e conditions, if If

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) ti ed to improved fuel economy that reduce(s)

consumer welfare.

With respect to the latter, EPA believes the co sts of the technologies developed for this

rule take into account the cost needed to ensure that all vehicle qualitie s (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 ve hicle attributes that manufacturers elect to make

, may result in additional private impacts on to 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, theSummary of Interagency Working Comments on Draft Rule under EO 12866

2 private gains from the rule, together with th e 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

. ;

 Consumers t hey might lack information or a full appreciation of information even when it is presented

. ;

 Consumers t hey might be especially averse to the s hort-term losses associated with the higher prices of energy efficient products (the behavioral phenomenon of “loss aversion”)

.  ; E e ven if consumers have relevant knowledge, the benefits of energy

- efficient vehicles might not be sufficiently sa lient 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
,  I i n 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 charact eristics, 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 a pplies 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 corres ponding 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 disagrees has not reached a consensus about the reasons for its existence. due in part to

consumers ’ inability Several 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 ci ty and highway) available among all listed 2010 6-cylinder minivans is 18 to 20 miles per gallon. With a manual-tran smission 4-cylinder minivan, it is possible to get 24 mpg. See http://www.fueleconomy.gov, which is jointly maintain ed 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, av ailable 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 f actor is sufficiently salient to play the proper role in purchasing decisions. Formatted: Bulleted + Level: 1 + Aligned at:

0.5" + Indent at: 0.75"

Formatted: Indent: First line: 0"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, c C onsumers face difficulty in predicting the fuel savings that they are likely to get from a vehicle , for a nu mber 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 consum ers’ vehicle purchases, but modeling that role may still be is still in development , and there is no consensus that most consumers make fully

informed tradeoffs

. 9

Another subset of the literature Other studies, however, finds suggest 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/ga spaper_latest.pdf (Docke t EPA-HQ-OAR-2009-0472-0044)

. 10 For recent but unpublished evidence in this regard, s ee 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. Formatted: Font: 10 pt

Formatted: Font: Times New RomanSummary 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 addition Also 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 of argued 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 usin consumer use of g 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 visi ble, status-providing features of vehicles more than on relatively invi sible 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 thro ugh their purchase

decisions that make 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 to as a result the rule.

While acknowledging the diversity of perspectives, EPA continues to include the full fuel savings as a private private benefit s 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 place developing due to shifts in consumer demand for fuel economy. It is possible that some of these savings would have occurred in the absence of theSummary 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 as sumption 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 es timate the effects of the rule on net benefits in the market for

vehicles.

Consumer vehicle choice models estimate wh at 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 c onsumers’ purchase decisions and the effects of this rule on the benefits that consumers will ge t 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 cons umer 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 no t previously seen in markets, such as higher fuel economy and higher price with other character istics 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 cons umers’ vehicle purchase decisions. 11 It The review finds no consensus on the role of fuel economy in c onsumer purchase decisions. Of 22 studies, approximately equal numbers find that consumers undervalue, overvalue, or value approximately

11 Greene, David L. XX- to fill in laterSummary 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 not ed 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 succeed ed in maintaining these other attributes.

EPA will continue its efforts to review th e 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 cons umer 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 anal ysis 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 technologie s. 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 compen sating variation, a payment of money after a change that

would make a consumer as well off after the change as before it. A related c oncept, equivalent variation, estimates the income change that would be an a lternative 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 overestim ate of the loss to the consumer, becaus e the consumer has choices other than buying the same vehicle with a higher price; she could ch oose a different vehicle, or decide not to buy a new vehicle. The consumer would choose one of those options only if the alternative invo lves less loss than paying the higher price. Thus, the increase in price that the co nsumer 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 featur es 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 curren t levels of other vehicle attributes such as safety, utility, and performance. Third, widesp read 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 be of 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 the The majority of commenters on this issue suggested that potential losses in welfare from requiring higher fuel economy was were

un likely to be only a minor issue a significant concern because of the many possible

reasons imperfections in why the market for fuel economy does not function perfectly economy. But

, other comments suggested that potential un identified and unquantified consumer welfare losses could be large. This section identifies the potential issues and summarizes the key public

comments. Acknowledging the comments, t T he FRIA provides a sensitivity analysis showing

how various levels of unidentified consumer welf are 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 s several ome 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 resu lt from higher fuel economy – will be experiencedSummary of Interagency Working Comments on Draft Rule under EO 12866

9 exclusively by the initial purchasers and subse quent 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 ne w 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 th eir costs for complying with increased CAFE standards for those model years by increasing vehicle sales prices. As the table shows, theagency’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 proj ects 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 Savi ngs 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 $2,739Summary 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 questi on 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 illustra ted by the comparisons presented in Table IV.G.6-1? And why would manuf acturers voluntarily forego opportunities to increase the attractiveness, value, and comp etitive 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 standa rds 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 theore tical 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 re lated findings that consumers may underweight benefits and costs that are less salient or that will be realized only in the future. 15

Published literature Existing 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 uncerta produce an exaggerated sense of uncerta inty about the value of future fuel saving s, s sufficiently to make making consumers reluctant to purchas e ing a more fuel-efficient vehicle seem unattractive

, even when doing so is likely to be a sound economic

decision. As an illustration 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

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 a nd 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 th e 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 illu stration, 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 resultin g fuel savings when those are discounted at 7% over the vehicle’s expected lifetime. 20 Although the The wide variation in these estimates undoubtedly reflects methodological and measurem ent 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 La boratory, December 29, 2009; see Table 10, p. 37. ?? See also? David Greene and Jin-Tan Liu (1988). “A utomotive 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 fact reflect 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 th at 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 cap acity, 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 isolat e 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 the 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 , 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 obviously even 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 for there 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 vehi cles or sellers of used cars and light trucks have more complete knowledge of vehicles’ actual fuel economy levels, or of 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 th is 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 decisi ons 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 ma rket 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.f ueleconomy.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 consumer s’ apparent unwilli ngness 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 econ omy, 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 off er 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 t he 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 purch ase 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 welf are 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 Administrati on, 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 th e effect of differing assumptions about vehicle buyers’ time horizons fo r 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 evaluate d 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), thei r 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 excee ds 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

Lifetime 24 10 Years Average Loan

Term 25

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 fu ture 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 aff ect 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 Re serve 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

15estimates 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 ratesreflecting 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 di scount 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 e E ven 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 Re serve 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 Re serve 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 hi gher 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 comb ination 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 fo r passenger cars and $570 for light trucks. Some evidence also suggests directly that vehicle buye rs 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 ha ve 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 plausible Imaginable 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 offe ring the increased fuel economy levels this rule will require manufactur ers to produce. At the same time, they might

a lso 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 i the aggregate benefits and costs

of this rule t to differ significantly from NHTSA’s assessment of the aggregate benefits and costs

of this rule estimates . 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 manufactur ers 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 at tributes such as fuel economy, performance, passenger- and cargo-carrying capacity, and other sour ces 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 t echnologies that manufacturers could employ to increase the fuel efficiency of cars or light truc ks. Although NHTSA has revised its estimates of manufacturers’ costs for some technologies signifi cantly for use in this rulemaking, these revised estimates are still intended to represent costs that would allow manufacturers to maintain the performance, safety, carrying cap acity, 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 ove rall 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 res ponses 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 ot her possibilities outlined previously.

As the foregoing discussion suggests, t T he agency has been unable to resolve does 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 po ssibility, 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 reta il 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 bene fits 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 th at 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 externalit ies 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 ef fect; 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 tr ucks, which represent th e principal cost of requiring higher fuel economy. The net total be nefits (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 lin e 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 res ources 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. Re presenting the change in fuel tax revenues in effect as an economy-wide cost is necessary to of fset the portion of fuel savings included in line 1 that represents savings in fuel tax payments by consumers. This prevents the savi ngs 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 remains 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 reductions in consumer welfare that could result from buyers’ responses to changes in

vehicle attributes that manufact urers 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 previo usly 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 fr om higher fuel economy – will be experienced exclusively by the initial purchasers and subse quent 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 distingu ish 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 truc ks 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-14Summary 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 Measure Fleet

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 standard s 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 vehi cles 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 competitiv e 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 subs et 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 paradox explanation 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’ asse ssment 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 a nd 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 differen ces 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 fo r 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 evaluate d 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 disc ounted 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

Measure Vehicle

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 af fect private consumption decisions, as will be the case if manufacturers’ costs for complying with higher fu el 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 outla ys 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 standa rds established by this rule, again using MY 2016 passenger cars and light trucks as an ex ample. 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 (w hich 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

Measure Vehicle

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 comb ination 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 fo r passenger cars and $570 for light trucks. SomeSummary 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 plausible Imaginable 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 signif icantly from NHTSA’s assessment of the aggr4egate

benefits and costs of this rule. If consumers’ vi ews 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 wo uld 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 thei r 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 co sts of complying with stricter CAFE standards.

As indicated in its previous di scussion 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 t echnologies that manufacturers could employ to increase the fuel efficiency of cars or light truc ks. Although NHTSA has revised its estimates of manufacturers’ costs for some technologies signifi cantly 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. Wh ile 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 manufact urers 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 st ricter 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 w ith 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 fr om 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 theiruncertainty 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 $405Summary 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 illu stration, 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 resultin g 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 measurem ent differences among the studies surveyed, it probably also reflects the fact that the expect ed 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 th eir purchasing decisions. A related possibility is that because the effects of differing fuel economy levels are relatively modest when comparedto 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 li ght 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 w ould be ere willing to pay the increased prices necessary to provide it. Most obviou sly, 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 prod ucers’ profit incentive to supp ly 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 La boratory, December 29, 2009; see Table 10, p. 37. and Jin-Tan Liu (1988). “Automotive Fuel Economy Im provements 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 manuf acturers 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 ma nufacturers 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 underestimat e the premiums that shoppers in certain market segments are willing to pay for mo re fuel-efficient versions of the vehicle models thy currently offer to prospective buyers within those segmen ts. If this occurs, ma nufacturers may fail to supply levels of fuel efficiency as high as t hose buyers are willing to pay for, and the average fuel efficiency of their entire new vehicle fleet s 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 hi gher fuel economy significantly exceeds the costs of providing it may indeed be correct, yet the re sulting 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 the reach 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.f ueleconomy.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 l ack 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 ac knowledges 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 (re ported 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 fr om 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 increas ed 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 show s manufacturers’ technology outlays for meeting higher CAFE standards for passenger cars and light trucks, wh ich 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 reso urces 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. Re presenting the change in fuel tax revenues in effect as an economy-wide cost is necessary to of fset the portion of fuel savings included in line 1 that represents savings in fuel tax payments by consumers. This prevents the savi ngs 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

30 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 featur es 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 st em 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 e E xternal 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 co sts 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 Formatted: Indent: First line: 0.5"Summary of Interagency Working Comments on Draft Rule under EO 12866

31 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 possibilitie s 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 illustrate d 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 ve hicle 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 possibiliti es 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 cl aim here that they have an empirical basis, or that they are founded in any existing estimate s, theoretical or empirical, of actual offsets. While some empirical evidence suggests that consumer s 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 potentia l degree of consumer loss in welfare. As Table VIII-18 it 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, if If

these factors combine to offset even as much as 25% of the agency’s estimate of total private benefits (line 5), th e rule’s net private (line 6) and net total (line 15) benefits would be reduced, but are remain still s s ubstantially positive. If the private savings turn out to be 25% less th an 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 v alue of fuel savings offset as much as half of the rule’s estimated private benefits If 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 one

third of the original estimate significantly decline, but w ould 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 Formatted: Bulleted + Level: 1 + Aligned at:

0.5" + Indent at: 0.75"Summary of Interagency Working Comments on Draft Rule under EO 12866

32 w c ould decline to zero or even become decline rapidly and at a certain point become negative.Summary of Interagency Working Comments on Draft Rule under EO 12866

33 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 re emphasize 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 un likely. 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 stan dards 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:



### 8.1.2 1.1.1 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. Becau se 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 technol ogy 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 ch aracteristics – 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 ne eds) 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 character istics 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 su rplus 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.) Formatted: Bullets and NumberingSummary of Interagency Working Comments on Draft Rule under EO 12866

35 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 sec tion will give some background on these differences among the

models.

8.1.2.1 1.1.1.1 Methods

Consumer choice models (CCMs) of vehicle purc hases typically use a form of discrete choice modeling. Discrete choice models seek to explai n 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 va riant on discrete choice models estimates the

market share for each vehicle. Because the mark et share is, essentially, the probability that consumers will purchase a specific vehicle, these ap proaches 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 consum ers play a larger role than in nested logit. While nested logit can look at the effects of a ch ange 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 th e 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 Kleit vii and Austin and Dinan viii ) 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 we ll as Austin and Dinan used the elasticities from an internal GM

vehicle choice model.

8.1.2.2 1.1.1.2 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 mi ght 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 sour ces (estimated models), or using values taken from other studies (calibrated models). Formatted: Bullets and Numbering

Formatted: Bullets and NumberingSummary of Interagency Working Comments on Draft Rule under EO 12866

36 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 thei r 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 Administration xi and the New Vehicle Market Model developed by NERA Economic Consulting xii are examples of calibrated models.

8.1.2.3 1.1.1.3 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 distributi on of income in the population influencing choice; xvii others include varying numbers and kind s of vehicle and consumer attributes.

8.1.2.4 1.1.1.4 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 mul tiple new modeling issues into its framework. In addition, because the vehicle sector is a majo r 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 taxes xxiii and “feebates” xxiv (subsidizing fuel-efficient cars with revenue collected by taxing fuel-inefficient vehicles).

8.1.2.5 1.1.1.5 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 models xxv 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 toestimate 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 Formatted: Bullets and Numbering

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37 more fuel-efficient vehicle and consider the savings equivalent to a reduction in purchase price.

Turrentine and Kurani xxvi 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, us e 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 m odels 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

research xxxi 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 muchconsumers 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: wh ile 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 Greene xxxiii 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 attribut es, 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, Gramlich xxxiv 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 st udies that appear to be well conducted. As a result, further work needs to be conducted before it is possib le to identify one value that represents the role of fuel economy in consumer purchase decisions.

Some studies xxxv argue that automakers could increase profits by increasing fuel economy because the amount that consumers are willing to pay for increased fuel economy outweighs theSummary of Interagency Working Comments on Draft Rule under EO 12866

38 costs of that improvement. Other studies xxxvi 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 studies xxxvii notes that its baseline model implie s 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.

8.1.2.6 1.1.1.6 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 possi ble 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 estimat es 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 routinely to undervalue a wide range of investments in energy conservation. Some possible explanations for the paradox xxxix 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; Formatted: Bullets and NumberingSummary of Interagency Working Comments on Draft Rule under EO 12866

39  Fuel savings in the future are uncertain; in contrast uncertain, while

, at the time of purchase the increased costs of fuel-savin g 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 style s. s.

Both theoretical and empirical research sugges ts 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 t This conclusion is in line with related findings that consumers may underweight be nefits and costs that ar e 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 regarding about the degree to which these various explanations disentangle contribute to the Ee nergy Pp aradox, 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 a nd 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. Formatted: Indent: Left: 0.5", No bullets or numbering

Formatted: Space Before: 12 pt, After: 12 pt, No bullets or numberingSummary 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 misestimated underestimate 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

consumers savings 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.

8.1.2.7 1.1.1.7 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 imp acts, 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 deve loped, 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 outsid e 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 vehi cles are sold. The fact that consumers and Formatted: Bullets and NumberingSummary of Interagency Working Comments on Draft Rule under EO 12866

41 producers have additional options suggests that co mpliance 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 behavi or 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 cons umer 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 feat ures 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 pr ices that consumers face. Firms with market power usually pass along less than full cost increas es, in order not to reduce sales very much. As a result, for most vehicles the increased technolo gy 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 fu el 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 char acteristics, then a consumer has the choices of

44 A closely related concept, equivale nt 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 (com pensating variation) or the consumer’s utility after the change (equivalent variation). In practice, the differen ce 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) ch oosing 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 ve hicles 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 mode ls 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 attr ibutes. For these reasons, EPA believes that consumers will enjoy significant savings that subs tantially outweigh any lik ely consumer welfare

losses.. Nonetheless, EPA continues to consider these questions, and because ther e are potential advantages to using co nsumer vehicle choice m odels 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 ex amine 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 evalua te 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 informi ng the analysis for future rules. Formatted: Indent: First line: 0.5"Summary of Interagency Working Comments on Draft Rule under EO 12866

43 i Goldberg, Pinelopi Koujianou, “Product Differentiation a nd 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 Corporat e 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 Sanj ana 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, an d Jia Li, “Feebates, Rebates, and Gas-Guzzler Taxes: A Study of Incentives for Increase d Fuel Economy,” Energy Policy 33 (2005): 757-775 (Docket EPA-HQ-OAR-2009- 0472-0023).

iii McManus, Walter M., “Can Proactive Fuel Economy Strate gies 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 Ta xes: 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 C hoice 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 Ta xes: 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 Be nefit-Cost Analysis of 2011-2015 CAFE Standards,” 2008, available at http://www.heartland.org/policybot/results/23495/Evalua tion_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 Pa kes, “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 Ta xes: 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 Ta xes: 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://ec onweb.tamu.edu/gan/w11553.pdf , accessed 5/12/09 (Docket EPA-HQ-OAR-2009-0472-0034).

xvii NERA Economic Consulting, “Appendix B: New Vehi cle Market Model,” “Impacts of the California

Greenhouse Gas Emission Standards on Motor Vehicle Sale s,” comments submitted to the U.S. EnvironmentalProtection 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, “Aut omobile 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 a nd Vehicles Choice Model Documentation,” prepared by the Oak Ridge National Laboratory for the U.S. Depart ment 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 Produc ts: The Case of the Minivan,” Journal of Political Economy 110 (2002): 705-729 (Docket EP A-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 Choi ce 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 Ta xes: 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://ec onweb.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, “Veh icle 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 th e Air: The Costs and Consequences of Higher CAFE Standards and Increased Gasoline Taxes,” Journa l 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 Pa kes, “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/gaspap er_latest.pdf (accessed 6/16 /09) (Docket EPA-HQ-OAR2009-0472-0044); Li, Shanjun, Christopher Timmins, and R oger 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 Pr ices on the Demand for Sport Utility Vehicles.” Working Paper. Macalester College, http://www.macalester.edu/~wests/SarahWestMEA2007.pdf,

accessed 1/25/10.

xxxii Greene, David L., and Jin-Tan Liu, 1988. “Automotive Fuel Economy Improvements and Consumers’ Surplus,” Transportation Research Part A 22A (3): 203-218 (Docket EPA-HQ-OAR-2009-0472-0045).

xxxiii Greene, David L. (2010). “How Consumers Valu e Fuel Economy: A Literature Review.”

xxxiv Gramlich, Jacob, “Gas Prices and Endogenous Pr oduct Selection in the U.S. Automobile Industry,” http://www.econ.yale.edu/seminars/apmicro/am08/gramlic h-081216.pdf , accessed 5/11/09 (Docket EPA-HQ-OAR2009-0472-0046).Summary of Interagency Working Comments on Draft Rule under EO 12866

46 xxxv Gramlich, Jacob, “Gas Prices and Endogenous Pr oduct Selection in the U.S. Automobile Industry,” http://www.econ.yale.edu/seminars/apmicro/am08/gramlic h-081216.pdf , accessed 5/11/09 (Docket EPA-HQ-OAR2009-0472-0046); McManus, Walter, 2007. “The Impact of Attribute-Based Corporate Average Fuel Economy (CAFE) Standards: Preliminary Results.” Ann Arbor, MI : University of Michigan Transportation Research Institute, Report No. UMTRI-2007-31 (Docket EPA-HQ-OAR-2009-0472-0054).

xxxvi For instance, 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); 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); Klier, Thomas, and Joshua Linn, 2008. “New Vehi cle Characteristics and the Cost of the Corporate Average Fuel Economy Standard,” Federal Reserve Bank of Chicago WP 2008-13, at http://www.chicagofed.org/publications/workingpapers /wp2008_13.pdf (accessed 5/6/09) (Docket EPA-HQ-OAR2009-0472-0047); Jacobsen, Mark, 2008. “Evaluating U.S. Fuel Economy Standards in a Model with Producer and Household Heterogeneity,” working paper, at http: //econ.ucsd.edu/~m3jacobs/Jacobsen_CAFE.pdf (accessed 5/6/09) (Docket EPA-HQ-OAR-2009-0472-0048).

xxxvii 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).

xxxviii IEA. 2007. “Mind the Gap: Quantifying Principal-Agent Problems in Energy Efficiency

. ” Paris, France: International Energy Agency (Docket EPA-HQ-OAR-2009-047 2-0049); Jaffe, Adam B., Richard G. Newell, and Robert N. Stavins (2001). "Energy Efficient Technologies and Climate Change Policies: Issues and Evidence." In Climate Change Economics and Policy , Toman, Michael A., ed., Washington, D.C.: Resources for the Future. p.171-181 (Docket EPA-HQ-OAR-2009-0472-0050); Metcalf, Gilbert E., and Kevin A. Hassett (1999). "Measuring the Energy Savings From Home Improvement Inve stments: Evidence From Monthly Billing Data." The Review of

Economics and Statistics 81(3): 516-528 (Docket EPA-HQ-OAR-2009-0472-0051); Tietenberg, T. (2009). “Reflections – Energy Efficiency Policy: Pipe Dream or Pipeline to the Future?” Review of Environmental Economics and Policy. Vol.3, 2: 304-320 (Docket EPA-HQ-OAR-2009-0472-0052).

xxxix Helfand, Gloria, and Ann Wolverton (2009). “Evaluati ng the Consumer Response to Fuel Economy: A Review of the Literature.” U.S. Environmental Protection Agen cy, National Center for Environmental Economics Working Paper 2009-4, available at http://yosemite.epa.gov/ EE/epa/eed.nsf/WPNumber/2009-04?OpenDocument, accessed

1/25/10.

xl Welch, David. “CAFE: A Prize for Making Gas-Guzzlers?” Business Week April 16, 2009, http://www.businessweek.com/magazine/c ontent/09_17/b41280480 30307.htm?chan=magazine+channel_what's+ne xt , accessed 7/7/09 (Docket EPA-HQ-OAR-2009-0472-0053).

xli Berry, Steven, James Levinsohn, and Ariel Pakes (July 1995). “Automobile Prices in Market Equilibrium,” Econometrica 63(4): 841-940 (Docket EPA-HQ-OAR-2009-0472-0025).

xlii 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).

xliii Rex, Emma, and Henrikke Baumann (2007). “Beyond ecolabels: what green marketing can learn from conventional marketing.” Journal of Cleaner Production 15: 567-576.