agnostic, achieving AERO20 improvements does assume the use of active
grille shutters, which is an off-cycle technology.
    Auto Innovators provided two comments on aerodynamic improvements.
Auto Innovators commented that it ``does not recommend considering
additional aerodynamic improvements (such as 25 percent aerodynamic
improvements, etc.). Some additional reductions in aerodynamic forces
may be possible if side view mirrors were no longer required by NHTSA
and FMVSSs.'' \474\
---------------------------------------------------------------------------

    \474\ Auto Innovators, Docket No. NHTSA-2021-0053-1492, at pp.
62, 135.
---------------------------------------------------------------------------

    We agree with Auto Innovators that we should not assume additional
aerodynamics technology adoption. We do not exceed 20 percent
aerodynamic improvement for all body styles and 15

percent improvement for the body styles discussed below.
    We also agree with Auto Innovators that side view mirrors cause
additional aerodynamic drag. Due to existing Federal motor vehicle
safety regulations, we currently do not consider aerodynamic
improvements from removing side view mirrors in the CAFE Model
analysis.\475\
---------------------------------------------------------------------------

    \475\ Federal motor vehicle safety standard (FMVSS) No. 111,
``Rear Visibility,'' currently requires that vehicles be equipped
with rearview mirrors to provide drivers with a view of objects that
are to their side or to their side and rear.
---------------------------------------------------------------------------

(b) Aerodynamics Analysis Fleet Assignments
    We use a relative performance approach to assign an initial level
of aerodynamic drag reduction technology to each vehicle. Each AERO
level represents a percent reduction in a vehicle's aerodynamic drag
coefficient (Cd) from a baseline value for its body style.
For a vehicle to achieve AERO5, the Cd must be at least 5
percent below the baseline for the body style; for AERO10, 10 percent
below the baseline, and so on. Baseline aerodynamic assignment is
therefore a three-step process: Each vehicle in the fleet is assigned a
body style, the average drag coefficient is calculated for each body
style, and the drag coefficient for each vehicle model is compared to
the average for the body style.
    We assign every vehicle in the fleet a body style; available body
styles included convertible, coupe, sedan, hatchback, wagon, SUV,
pickup, minivan, and van. These assignments do not necessarily match
the body styles that manufacturers use for marketing purposes. Instead,
we assign them based on analyst judgement, taking into account how a
vehicle's AERO and vehicle technology class assignments are affected.
Different body styles offer different utility and have varying levels
of baseline form drag. In addition, frontal area is a major factor in
aerodynamic forces, and the frontal area varies by vehicle. This
analysis considers both frontal area and body style as utility factors
affecting aerodynamic forces; therefore, the analysis assumes all
reduction in aerodynamic drag forces come from improvement in the drag
coefficient.
    We computed the average drag coefficients for each body style using
the MY 2015 drag coefficients published by manufacturers, which were
used as the baseline values in the analysis. We harmonize the Autonomie
simulation baselines with the analysis fleet assignment baselines to
the fullest extent possible.\476\
---------------------------------------------------------------------------

    \476\ See TSD Chapter 2.4.2 for a table of vehicle attributes
used to build the Autonomie baseline vehicle models. That table
includes a drag coefficient for each vehicle class.
---------------------------------------------------------------------------

    We source the drag coefficients for each vehicle in the analysis
fleet from manufacturer specification sheets, when possible. However,
manufacturers did not consistently publicly report drag coefficients
for MY 2020 vehicles. If we could not find a publicly reported drag
coefficient, analyst judgment was sometimes used to assign an AERO
level. If no level was manually assigned, we used the drag coefficient
obtained from manufacturers to build the MY 2016 fleet,\477\ if
available. The MY 2016 drag coefficient values may not accurately
reflect the current technology content of newer vehicles but are, in
many cases, the most recent data available.
---------------------------------------------------------------------------

    \477\ See 83 FR 42986 (Aug. 24, 2018). The MY 2016 fleet was
built to support the 2018 NPRM.
---------------------------------------------------------------------------

(c) Aerodynamics Adoption Features
    As already discussed, we use a relative performance approach to
assign current aerodynamic technology (AERO) level to a vehicle. For
some body styles with different utility, such as pickup trucks, SUVs
and minivans, frontal area can vary, and this can affect the overall
aerodynamic drag forces. In order to maintain vehicle utility and
functionality related to passenger space and cargo space, we assume all
technologies that improve aerodynamic drag forces do so by reducing
Cd while maintaining frontal area.
    Technology pathway logic for levels of aerodynamic improvement
consists of a linear progression, with each level superseding all
previous ones. Technology paths for AERO are illustrated in Figure III-
15.
    The model does not consider the highest AERO levels for certain
body styles. In these cases, this means that AERO20, and sometimes
AERO15, can neither be assigned in the baseline fleet nor adopted by
the model. For these body styles, there are no commercial examples of
drag coefficients that demonstrate the required AERO15 or AERO20
improvement over baseline levels. We also deemed the most advanced
levels of aerodynamic drag simulated as not technically practicable
given the form drag of the body style and costed technology, especially
given the need to maintain vehicle functionality and utility, such as
interior volume, cargo area, and ground clearance. In short, we
`skipped' AERO15 for minivan body styles, and `skipped' AERO20 for
convertible, minivan, pickup, and wagon body styles.
    We also do not allow application of AERO15 and AERO20 technology to
vehicles with more than 780 horsepower. There are two main types of
vehicles that informed this threshold: Performance internal combustion
engine (ICE) vehicles and high-power battery electric vehicles (BEVs).
In the case of the former, we recognize that manufacturers tune
aerodynamic features on these vehicles to provide desirable downforce
at high speeds and to provide sufficient cooling for the powertrain,
rather than reducing drag, resulting in middling drag coefficients
despite advanced aerodynamic features. Therefore, manufacturers may
have limited ability to improve aerodynamic drag coefficients for high
performance vehicles with internal combustion engines without reducing
horsepower. 1,655 units of sales volume in the baseline fleet include
limited application of aerodynamic technologies because of ICE vehicle
performance.\478\
---------------------------------------------------------------------------

    \478\ Market Data file.
---------------------------------------------------------------------------

    In the case of high-power battery electric vehicles, the 780-
horsepower threshold is set above the highest peak system horsepower
present on a BEV in the 2020 fleet. BEVs have different aerodynamic
behavior and considerations than ICE vehicles, allowing for features
such as flat underbodies that significantly reduce drag.\479\ BEVs are
therefore more likely to achieve higher AERO levels, so the horsepower
threshold is set high enough that it does not restrict AERO15 and
AERO20 application. Note that the CAFE Model does not force high levels
of AERO adoption; rather, higher AERO levels are usually adopted
organically by BEVs because significant drag reduction allows for
smaller batteries and, by extension, cost savings. BEVs represent
252,023 units of sales volume in the baseline fleet.\480\
---------------------------------------------------------------------------

    \479\ 2020 EPA Automotive Trends Report, at p. 227.
    \480\ Market Data file.

---------------------------------------------------------------------------

(d) Aerodynamics Effectiveness Modeling
    To determine aerodynamic effectiveness, the CAFE Model and
Autonomie use individually assigned road load technologies for each
vehicle to appropriately assign initial road load levels and
appropriately capture benefits of subsequent individual road load
improving technologies.
    The current analysis included four levels of aerodynamic
improvements, AERO5, AERO10, AERO15, and AERO20, representing 5, 10,
15, and 20 percent reduction in drag coefficient (Cd), respectively. We
assume that aerodynamic drag reduction can only come from reduction in
Cd and not from reduction of frontal area, to maintain vehicle
functionality and utility, such as passenger space, ingress/egress
ergonomics, and cargo space.
    The effectiveness values for the aerodynamic improvement levels
relative to AERO0, for all ten vehicle technology classes, are shown in
Figure III-16. Each of the effectiveness values shown is representative
of the improvements seen for upgrading only the listed aerodynamic
technology level for a given combination of other technologies. In
other words, the range of effectiveness values seen for each specific
technology (e.g., AERO 15) represents the addition of AERO15 technology
(relative to AERO0 level) for every technology combination that could
select the addition of AERO15. It must be emphasized that the change in
fuel consumption values between entire technology keys is used,\481\
and not the individual technology effectiveness values. Using the
change between whole technology keys captures the complementary or non-
complementary interactions among technologies. The box shows the inner
quartile range (IQR) of the effectiveness values and whiskers extend
out 1.5 x IQR. The dots outside the whiskers show effectiveness values
outside those thresholds.
---------------------------------------------------------------------------

    \481\ Technology key is the unique collection of technologies
that constitutes a specific vehicle, see TSD Chapter 2.4.7 for more
detail.
[GRAPHIC] [TIFF OMITTED] TR02MY22.094

(e) Aerodynamics Costs
    This analysis uses the AERO technology costs established in the
2020 final rule that are based on confidential business information
submitted by the automotive industry in advance of the 2018 NPRM,\483\
and on our assessment of manufacturing costs for specific aerodynamic
technologies.\484\ We received no additional comments from stakeholders
regarding the costs established in the 2018 NPRM, and

continued to use the established costs for the 2020 final rule and this
analysis.
---------------------------------------------------------------------------

    \482\ The data used to create this figure can be found in the
FE_1 Improvements file.
    \483\ See the PRIA accompanying the 2018 NPRM, Chapter
<IP_ADDRESS>.2.1.2, for a discussion of these cost estimates.
    \484\ See the FRIA accompanying the 2020 final rule, Chapter
VI.C.5.e.
---------------------------------------------------------------------------

    Table III-28 shows examples of costs for AERO technologies as
applied to the medium car and pickup truck vehicle classes in select
model years. The cost to achieve AERO5 is relatively low, as most of
the improvements can be made through body styling changes. The cost to
achieve AERO10 is higher than AERO5, due to the addition of several
passive aerodynamic technologies, and the cost to achieve AERO15 and
AERO20 is higher than AERO10 due to use of both passive and active
aerodynamic technologies. For a full list of all absolute aerodynamic
technology costs used in the analysis across all model years see the
Technologies file.
[GRAPHIC] [TIFF OMITTED] TR02MY22.095

Tire Rolling Resistance
    Tire rolling resistance is a road load force that arises primarily
from the energy dissipated by elastic deformation of a vehicle's tires
as they roll. Tire design characteristics (for example, materials,
construction, and tread design) have a strong influence on the amount
and type of deformation and the energy the tire dissipates. Designers
can select these characteristics to minimize rolling resistance.
However, these characteristics may also influence other performance
attributes, such as durability, wet and dry traction, handling, and
ride comfort.
    Lower rolling resistance tires have characteristics that reduce
frictional losses associated with the energy dissipated mainly in the
deformation of the tires under load, thereby improving fuel economy.
OEMs increasingly specify low rolling resistance tires in new vehicles,
and they are also increasingly available from aftermarket tire vendors.
They commonly include attributes such as higher inflation pressure,
material changes, tire construction optimized for lower hysteresis,
geometry changes (e.g., reduced aspect ratios), and reduced sidewall
and tread deflection. These changes are commonly accompanied by
additional changes to vehicle suspension tuning and/or suspension
design to mitigate any potential impact on other performance attributes
of the vehicle.
    We continue to assess the potential impact of tire rolling
resistance changes on vehicle safety. We have been following the
industry developments and trends in application of rolling resistance
technologies to light duty vehicles. As stated in the NAP special
report on Tires and Passenger Vehicle Fuel Economy,\485\ national crash
data does not provide data about tire structural failures specifically
related to tire rolling resistance, because the rolling resistance of a
tire at a crash scene cannot be determined. However, other metrics like
brake performance compliance test data are helpful to show trends like
that stopping distance has not changed in the last ten years,\486\
during which time many manufacturers have installed low rolling
resistance tires in their fleet--meaning that manufacturers were
successful in improving rolling resistance while maintaining stopping
distances through tire design, tire materials, and/or braking system
improvements. In addition, NHTSA has addressed other tire-related
issues through rulemaking,\487\ and continues to research tire problems
such as blowouts, flat tires, tire or wheel deficiency, tire or wheel
failure, and tire degradation.\488\ However, there are currently no
data connecting low rolling resistance tires to accident or fatality
rates.
---------------------------------------------------------------------------

    \485\ Tires and Passenger Vehicle Fuel Economy: Informing
Consumers, Improving Performance--Special Report 286 (2006),
available at https://www.nap.edu/read/11620/chapter/6.
    \486\ See, e.g., NHTSA Office of Vehicle Safety Compliance,
Compliance Database, https://one.nhtsa.gov/cars/problems/comply/index.cfm.
    \487\ 49 CFR 571.138, Tire pressure monitoring systems.
    \488\ Tire-Related Factors in the Pre-Crash Phase, DOT HS 811
617 (April 2012), available at https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811617.
---------------------------------------------------------------------------

    NHTSA conducted tire rolling resistance tests and wet grip index
tests on original equipment tires installed on new vehicles. The tests
showed that there is no degradation in wet grip index values (i.e., no
degradation in traction) for tires with improved rolling resistance
technology. With better tire design, tire compound formulations and
improved tread design, tire manufacturers have tools to balance
stopping distance and reduced rolling resistance. Tire manufacturers
can use ``higher performance materials in the tread compound, more
silica as reinforcing fillers and advanced tread design features'' to
mitigate issues related to stopping distance.\489\
---------------------------------------------------------------------------

    \489\ Jesse Snyder, A big fuel saver: Easy-rolling tires (but
watch braking) (July 21, 2008), https://www.autonews.com/article/20080721/OEM01/307219960/a-big-fuel-saver-easy-rolling-tires-but-watch-braking. Last visited December 3, 2019.
---------------------------------------------------------------------------

    U.S. Tire Manufacturers Association (USTMA) commented on NHTSA's
conclusion that the agency did not observe any unacceptable tradeoff
between tire rolling resistance and wet grip performance, which ``NHTSA
correctly recognized is due to advanced tire design, rubber compounding
and manufacturing technologies.'' However, USTMA cautioned that ``this
inverse relationship between rolling resistance and wet grip
performance still exists, and as the tire industry continues to enhance
rolling resistance performance, new and/or enhanced countermeasures
will also need to be developed to assure

no unacceptable impact to wet grip performance.'' \490\
---------------------------------------------------------------------------

    \490\ USTMA, Docket No. NHTSA-2021-0053-1612, at 2.
---------------------------------------------------------------------------

    The following sections discuss levels of tire rolling resistance
technology considered in the CAFE Model, how the technology was
assigned in the analysis fleet, adoption features specified to maintain
performance, effectiveness, and cost.
(a) Tire Rolling Resistance in the CAFE Model
    We continue to consider two levels of improvement for low rolling
resistance tires in the analysis: the first level of low rolling
resistance tires considered reduced rolling resistance 10 percent from
an industry-average baseline rolling resistance coefficient (RRC)
value, while the second level reduced rolling resistance 20 percent
from the baseline.\491\
---------------------------------------------------------------------------

    \491\ To achieve ROLL10, the tire rolling resistance must be at
least 10 percent better than baseline (.0081 or better). To achieve
ROLL20, the tire rolling resistance must be at least 20 percent
better than baseline (.0072 or better).
---------------------------------------------------------------------------

    We selected the industry-average RRC baseline of 0.009 based on a
CONTROLTEC study prepared for the California Air Resources Board,\492\
in addition to confidential business information submitted by
manufacturers prior to the 2018 NPRM analysis. The average RRC from the
CONTROLTEC study, which surveyed 1,358 vehicle models, was 0.009.\493\
CONTROLTEC also compared the findings of their survey with values
provided by Rubber Manufacturers Association (renamed USTMA-U.S. Tire
Manufacturers Association) for original equipment tires. The average
RRC from the data provided by RMA was 0.0092,\494\ compared to average
of 0.009 from CONTROLTEC.
---------------------------------------------------------------------------

    \492\ Technical Analysis of Vehicle Load Reduction by CONTROLTEC
for California Air Resources Board (April 29, 2015).
    \493\ The RRC values used in this study were a combination of
manufacturer information, estimates from coast down tests for some
vehicles, and application of tire RRC values across other vehicles
on the same platform.
    \494\ Technical Analysis of Vehicle Load Reduction by CONTROLTEC
for California Air Resources Board (April 29, 2015) at page 40.
---------------------------------------------------------------------------

    In past agency actions, commenters have argued that based on
available data on current vehicle models and the likely possibility
that there would be additional tire improvements over the next decade,
we should consider ROLL30 technology, or a 30 percent reduction of tire
rolling resistance over the baseline.\495\
---------------------------------------------------------------------------

    \495\ Wesley Dyer, Docket No. NHTSA-2018-0067-11985, at p. 49.
---------------------------------------------------------------------------

    As stated in the Joint TSD for the 2012 final rule for MY 2017-2025
and 2020 final rule, tire technologies that enable rolling resistance
improvements of 10 and 20 percent have been in existence for many
years.\496\ Achieving improvements of up to 20 percent involves
optimizing and integrating multiple technologies, with a primary
contributor being the adoption of a silica tread technology. Tire
suppliers have indicated that additional innovations are necessary to
achieve the next level of low rolling resistance technology on a
commercial basis, such as improvements in material to retain tire
pressure, and tread design to manage both stopping distance and wet
traction.\497\
---------------------------------------------------------------------------

    \496\ EPA-420-R-12-901, at p. 3-210.
    \497\ 2011 NAS Report, at p. 103.
---------------------------------------------------------------------------

    The agency believes that the tire industry is in the process of
moving automotive manufacturers towards higher levels of rolling
resistance technology in the vehicle fleet. Importantly, as shown
below, the MY 2020 baseline fleet does include a higher percentage of
vehicles with ROLL20 technology than the MY 2017 fleet. However, we
believe that at this time, the emerging tire technologies that would
achieve 30 percent improvement in rolling resistance, like changing
tire profile, stiffening tire walls, or adopting improved tires along
with active chassis control,\498\ among other technologies, will not be
available for widespread commercial adoption in the fleet during the
rulemaking timeframe. As a result, we continue to not to incorporate 30
percent reduction in rolling resistance technology.
---------------------------------------------------------------------------

    \498\ Mohammad Mehdi Davari, Rolling resistance and energy loss
in tyres (May 20, 2015), available at https://www.sveafordon.com/media/42060/SVEA-Presentation_Davari_public.pdf. Last visited
December 30, 2019.
---------------------------------------------------------------------------

    USTMA agreed with this assessment, and commented that ``its members
will continue to develop advanced rolling resistance technologies for
future adoption, since vehicle manufacturers continue to prioritize
rolling resistance as one of the more cost-effective ways to achieve
advancements in vehicle fuel economy.'' \499\ Auto Innovators, in their
comments to both NHTSA and EPA, also discouraged the addition of 30
percent tire rolling resistance, stating that ``performance neutrality
for cold weather traction, hot weather performance, wet weather
traction, load handling (for addition weight of batteries, for
instance), wear and durability, and noise, vibration, and harshness can
be challenging to achieve for 20 [percent] tire rolling resistance
reduction, and the technology pathway to ROLL30 for many vehicles
remains unclear.'' \500\
---------------------------------------------------------------------------

    \499\ USTMA, at 2.
    \500\ Auto Innovators, Docket No. NHTSA-2021-0053-1492, at 134.
---------------------------------------------------------------------------

    We will continue to monitor this issue and consider any additional
advancements in tire rolling resistance technology for future analyses.
(b) Tire Rolling Resistance Analysis Fleet Assignments
    Tire rolling resistance is not a part of tire manufacturers'
publicly released specifications and thus it is difficult to assign
this technology to the analysis fleet. Manufacturers also often offer
multiple wheel and tire packages for the same nameplates, further
increasing the complexity of this assignment. We employed an approach
consistent with previous rulemaking in assigning this technology. We
relied on previously submitted rolling resistance values that were
supplied by manufacturers in the process of building older fleets and
bolstered it with agency-sponsored tire rolling resistance testing by
Smithers.\501\
---------------------------------------------------------------------------

    \501\ See memo to Docket No. NHTSA-2021-0053, Evaluation of
Rolling Resistance and Wet Grip Performance of OEM Stock Tires
Obtained from NCAP Crash Tested Vehicles Phase One and Two. NHTSA
used tire rolling resistance coefficient values from this project to
assign baseline tire rolling resistance technology in the MY 2020
analysis fleet and is therefore providing the draft project
appendices for public review and comment.
---------------------------------------------------------------------------

    We carried over rolling resistance assignments for nameplates where
manufacturers had submitted data on the vehicles' rolling resistance
values, even if the vehicle was redesigned. If Smithers data was
available, we replaced any older or missing values with that updated
data. Those vehicles for which no information was available from either
previous manufacturer submission or Smithers data were assigned to
ROLL0. All vehicles under the same nameplate were assigned the same
rolling resistance technology level even if manufacturers do outfit
different trim levels with different wheels and tires.
    The MY 2020 analysis fleet includes the following breakdown of
rolling resistance technology: 44 percent at ROLL0, 20 percent at
ROLL10, and 36 percent at ROLL20, which shows that the majority of the
fleet has now adopted some form of improved rolling resistance
technology. The majority of the change from the MY 2017 analysis fleet
has been in implementing ROLL20 technology. There is likely more
proliferation of rolling resistance technology, but we would need
further information from manufacturers in order to account for it.
Accordingly, we made no changes to tire rolling

resistance assignments for this final rule.
(C) Tire Rolling Resistance Adoption Features
    Rolling resistance technology can be adopted with either a vehicle
refresh or redesign. In some cases, low rolling resistance tires can
affect traction, which may adversely impact acceleration, braking, and
handling characteristics for some high-performance vehicles. Similar to
past rulemakings, the agency recognizes that to maintain performance,
braking, and handling functionality, some high-performance vehicles
would not adopt low rolling resistance tire technology. For cars and
SUVs with more than 405 horsepower (hp), the agency restricted the
application of ROLL20. For cars and SUVs with more than 500 hp, the
agency restricted the application of any additional rolling resistance
technology (ROLL10 or ROLL20). The agency developed these cutoffs based
on a review of confidential business information and the distribution
of rolling resistance values in the fleet. We received no comments on
these adoption features and made no changes for this final rule
analysis.
(d) Tire Rolling Resistance Effectiveness Modeling
    As discussed above, the baseline rolling resistance value from
which rolling resistance improvements are measured is 0.009, based on a
thorough review of confidential business information submitted by
industry, and a review of other literature. To achieve ROLL10, the tire
rolling resistance must be at least 10 percent better than baseline
(.0081 or better). To achieve ROLL20, the tire rolling resistance must
be at least 20 percent better than baseline (.0072 or better).
    We determined effectiveness values for rolling resistance
technology adoption using Autonomie. Figure III-17 below shows the
range of effectiveness values used for adding tire rolling resistance
technology to a vehicle in this analysis. The graph shows the change in
fuel consumption values between entire technology keys,\502\ and not
the individual technology effectiveness values. Using the change
between whole technology keys captures the complementary or non-
complementary interactions among technologies. In the graph, the box
shows the interquartile range (IQR) of the effectiveness values and
whiskers extend out 1.5 x IQR. The dots outside of the whiskers show
values for effectiveness that are outside these bounds.
---------------------------------------------------------------------------

    \502\ Technology key is the unique collection of technologies
that constitutes a specific vehicle, see TSD Chapter 2.4.7 for more
information.
---------------------------------------------------------------------------

    The data points with the highest effectiveness values are almost
all exclusively BEV and FCV technology combinations for medium sized
nonperformance cars. The effectiveness for these vehicles, when the low
rolling resistance technology is applied, is amplified by a
complementary effect, where the lower rolling resistance reduces road
load and allows a smaller battery pack to be used (and still meet range
requirements). The smaller battery pack reduces the overall weight of
the vehicle, further reducing road load, and improving fuel efficiency.
This complimentary effect is experienced by all the vehicle technology
classes, but the strongest effect is on the midsized vehicle non-
performance classes and is only captured in the analysis through the
use of full vehicle simulations, demonstrating the full interactions of
the technologies.

[GRAPHIC] [TIFF OMITTED] TR02MY22.096

(e) Tire Rolling Resistance Costs
    For this final rule analysis, we continue to use the same DMC
values for ROLL technology that were used for the 2020 final rule,
which are based on NHTSA's MY 2011 CAFE final rule and the 2006 NAS/NRC
report.\503\ Table III-29 shows the different levels of tire rolling
resistance technology cost for all vehicle classes across select model
years, which shows how the learning rate for ROLL technologies impacts
the cost. For all ROLL absolute technology costs used in the analysis
across all model years see the Technologies file.
---------------------------------------------------------------------------

    \503\ ``Tires and Passenger Vehicle Fuel Economy,''
Transportation Research Board Special Report 286, National Research
Council of the National Academies, 2006, Docket No. EPA-HQ-OAR-2009-
0472-0146.
[GRAPHIC] [TIFF OMITTED] TR02MY22.097

7. Other Vehicle Technologies
    We included four other vehicle technologies in the analysis--
electric power steering (EPS), improved accessory devices (IACC), low
drag brakes (LDB), and secondary axle disconnect (SAX). The CAFE Model
applied the effectiveness values for each of these technologies
directly, with unique effectiveness values for each technology and for
each technology class, rather than using Autonomie effectiveness
estimates. We used this methodology in these four cases because the
effectiveness of these technologies varies little with combinations of
other technologies. Also, applying these technologies directly in the
CAFE Model significantly reduces the required runtime of Autonomie
simulations.
(a) Electric Power Steering
    Electric power steering reduces fuel consumption by reducing load
on the engine. Specifically, it reduces or

eliminates the parasitic losses associated with engine-driven power
steering pumps, which pump hydraulic fluid continuously through the
steering actuation system even when no steering input is present. By
selectively powering the electric assist only when steering input is
applied, the power consumption of the system is reduced in comparison
to the traditional ``always-on'' hydraulic steering system. Power
steering may be electrified on light duty vehicles with standard 12V
electrical systems and is also an enabler for vehicle electrification
because it provides power steering when the engine is off (or when no
combustion engine is present).
    Power steering systems can be electrified in two ways.
Manufacturers may choose to eliminate the hydraulic portion of the
steering system and provide electric-only power steering (EPS) driven
by an independent electric motor, or they may choose to move the
hydraulic pump from a belt-driven configuration to a stand-alone
electrically driven hydraulic pump. The latter system is commonly
referred to as electro-hydraulic power steering (EHPS). As stated in
past rulemakings, manufacturers have told us that full EPS systems are
being developed for all types of light-duty vehicles, as well as large
trucks.
    We described in past rulemakings that, like low drag brakes, EPS
can be difficult to observe and assign to the analysis fleet, however,
it is found more frequently in publicly available information than low
drag brakes. Based on comments received during the 2020 rulemaking, the
agency increased EPS application rate to nearly 90 percent for the 2020
final rule. The agency is maintaining this level of EPS fleet
penetration for this analysis, recognizing that some specialized,
unique vehicle types or configurations still implement hydraulically
actuated power steering systems for the baseline fleet model year.
    The effectiveness of both EPS and EHPS is derived from the
decoupling of the pump from the crankshaft and is considered to be
practically the same for both. Thus, a single effectiveness value is
used for both EPS and EHPS. As indicated in the Table III-30, the
effectiveness of EPS and EHPS varies based on the vehicle technology
class it is being applied to. This variance is a direct result of
vehicle size and the amount of energy required to turn the vehicle's
two front wheels about their vertical axis. More simply put, more
energy is required for vehicles that weigh more and, typically, have
larger tire contact patches.
[GRAPHIC] [TIFF OMITTED] TR02MY22.098

(b) Improved Accessories
    Engine accessories typically include the alternator, coolant pump,
cooling fan, and oil pump, and are traditionally mechanically driven
via belts, gears, or directly by other rotating engine components such
as camshafts or the crankshaft. These can be replaced with improved
accessories (IACC), which may include high efficiency alternators,
electrically driven (i.e., on-demand) coolant pumps, electric cooling
fans, variable geometry oil pumps, and a mild regeneration strategy.
Replacing lower-efficiency and/or mechanically driven components with
these improved accessories results in a reduction in fuel consumption,
as the improved accessories can conserve energy by being turned on/off
``on demand'' in some cases, driven at partial load as needed, or by
operating more efficiently.
    For example, electric coolant pumps and electric powertrain cooling
fans provide better control of engine cooling. Flow from an electric
coolant pump can be varied, and the cooling fan can be shut off during
engine warm-up or cold ambient temperature conditions, reducing warm-up
time, fuel enrichment requirements, and ultimately reducing parasitic
losses.
    IACC technology is difficult to observe and therefore there is
uncertainty in assigning it to the analysis fleet. As in the past, we
rely on industry-provided information and comments to assess the level
of IACC technology applied in the fleet. We believe there continues to
be opportunity for further implementation of IACC. The analysis has an
IACC fleet penetration of approximately eight percent compared to the
six percent value in the MY 2017 analysis fleet used for the 2020 final
rule analysis.
    The agency believes improved accessories may be incorporated in
coordination with powertrain related changes occurring at either a
vehicle refresh or vehicle redesign. This coordination with powertrain
changes enables related design and tooling changes to be implemented
and systems development, functionality and durability testing to be
conducted in a single product change program to efficiently manage
resources and costs.
    This analysis carries forward work on the effectiveness of IACC
systems conducted in the Draft TAR and EPA Proposed Determination that
is originally founded in the 2002 NAS Report \504\ and confidential
manufacturer data. This work involved gathering information by
monitoring press reports, holding meetings with suppliers and OEMs, and
attending industry technical conferences. The

resulting effectiveness estimates we use are shown in Table III-31. As
indicated in this table, the effectiveness values of IACC varies based
on the vehicle technology class it is being applied to. This variance,
like EPS, is a direct result of vehicle size as well as the amount of
energy generated by the alternator, the size of the coolant pump to the
cool the necessary systems, the size of the cooling fan required, among
other characteristics and it directed related to a vehicle size and
mass.
---------------------------------------------------------------------------

    \504\ National Research Council 2002. Effectiveness and Impact
of Corporate Average Fuel Economy (CAFE) Standards. Washington, DC:
The National Academies Press. https://doi.org/10.17226/10172.
[GRAPHIC] [TIFF OMITTED] TR02MY22.099

(c) Low Drag Brakes
    We have defined low drag brakes (LDB) as brakes that reduce the
sliding friction of disc brake pads on rotors when the brakes are not
engaged because the brake pads are pulled away from the rotating disc
either by mechanical or electric methods since 2009 for the MY 2011
CAFE rule.\505\ At that time, we estimated the effectiveness of LDB
technology to be a range from 0.5-1.0 percent, based on CBI data. We
applied a learning curve to the estimated cost for LDB, but noted that
the technology was considered high volume, mature, and stable.
Confidential manufacturer comments in response to the NPRM for MY 2011
(73 FR 24352, May 2, 2008) indicated that most passenger cars have
already adopted LDB technology, but ladder frame trucks have not.
---------------------------------------------------------------------------

    \505\ Final Regulatory Impact Analysis, Corporate Average Fuel
Economy for MY 2011 Passenger Cars and Light Trucks (March 2009), at
V-135.
---------------------------------------------------------------------------

    We and EPA used the same definition for LDB in the MY 2012-2016
joint rule, with an estimated effectiveness of up to 1 percent based on
CBI data.\506\ We only allowed LDB technology to be applied to large
car, minivan, medium and large truck, and SUV classes because the
agency determined the technology was already largely utilized in most
other subclasses. The 2011 NAS committee also utilized our definition
for LDB and added that most new vehicles have low-drag brakes.\507\ The
committee confirmed that the impact over conventional brakes may be
about a 1 percent reduction of fuel consumption.
---------------------------------------------------------------------------

    \506\ Final Regulatory Impact Analysis, Corporate Average Fuel
Economy for MY 2012-MY 2016 Passenger Cars and Light Trucks (March
2010), at 249.
    \507\ 2011 NAS Report, at 103-104.
---------------------------------------------------------------------------

    For the 2012 final rule for MY 2017-2025, however, we and EPA
updated the effectiveness estimate for LDB to 0.8 percent based on a
2011 Ricardo study and updated lumped-parameter model.\508\ The
agencies considered LDB technology to be off the learning curve (i.e.,
the DMC does not change year-over-year). The 2015 NAS Report continued
to use the agencies' definition for LDB and commented that the 0.8
percent effectiveness estimate is a reasonable estimate.\509\ The 2015
NAS committee did not opine on the application of LDB technology in the
fleet. The agencies used the same definition, cost, and effectiveness
estimates for LDB in the Draft TAR, but also noted the existence of
zero drag brake systems which use electrical actuators that allow brake
pads to move farther away from the rotor.\510\ However, the agencies
did not include zero drag brake technology in either compliance
simulation. EPA continued with this approach in its first 2017 Proposed
Determination that the standards through 2025 were appropriate.\511\
---------------------------------------------------------------------------

    \508\ Joint Technical Support Document: Final Rulemaking for
2017-2025 Light-Duty Vehicle Greenhouse Gas Emission Standards and
Corporate Average Fuel Economy Standards (August 2012), at 3-211.
    \509\ 2015 NAS Report, at 231.
    \510\ Draft TAR, at 5-207.
    \511\ EPA Proposed Determination TSD, at 2-422.
---------------------------------------------------------------------------

    In the 2020 final rule, the agencies applied LDB sparingly in the
MY 2017 analysis fleet using the same cost and effectiveness estimates
from the 2011 Ricardo study, with approximately less than 15 percent of
vehicles being assigned the technology. In addition, we noted the
existence of zero drag brakes in production for some BEVs, similar to
the summary in the Draft TAR, but did not opine on the existence of
zero drag brakes in the fleet. Some stakeholders commented to the 2020
rule that other vehicle technologies, including LDB, were actually
overapplied in the analysis fleet.
    For this analysis, we considered the conflicting statements that
LDB were both universally applied in new vehicles and that the new
vehicle fleet still had space to improve LDB technology. We determined
that LDB technology as previously defined going back to the MY 2011
rule (73 FR 24352, May 2, 2008) was universally applied in the MY 2020
fleet. However, we determined that zero drag brakes, the next level of
brake technology, was sparingly applied in the MY 2020 analysis fleet.
Currently, we do not believe that zero drag brake systems will be
available for wide scale application in the rulemaking timeframe and we
did not include it as a technology for this analysis. We sought comment
on the issue, including any data on the use

advanced LDB systems on current and forthcoming production vehicles,
but did not receive any comments. We will consider how to define a new
level of low drag brake technology that either encompasses the
definition of zero drag brakes or similar technology in future
rulemakings.
(d) Secondary Axle Disconnect
    AWD and 4WD vehicles provide improved traction by delivering torque
to the front and rear axles, rather than just one axle. When a second
axle is rotating, it tends to consume more energy because of additional
losses related to lubricant churning, seal friction, bearing friction,
and gear train inefficiencies.\512\ Some of these losses may be reduced
by providing a secondary axle disconnect function that disconnects one
of the axles when driving conditions do not call for torque to be
delivered to both.
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    \512\ Pilot Systems, ``AWD Component Analysis,'' Project Report,
performed for Transport Canada, Contract T8080-150132, May 31, 2016.
---------------------------------------------------------------------------

    The terms AWD and 4WD are often used interchangeably, although they
have also developed a colloquial distinction, and are two separate
systems. The term AWD has come to be associated with light-duty
passenger vehicles providing variable operation of one or both axles on
ordinary roads. The term 4WD is often associated with larger truck-
based vehicle platforms providing a locked driveline configuration and/
or a low range gearing meant primarily for off-road use.
    Many 4WD vehicles provide for a single-axle (or two-wheel) drive
mode that may be manually selected by the user. In this mode, a primary
axle (usually the rear axle) will be powered, while the other axle
(known as the secondary axle) is not. However, even though the
secondary axle and associated driveline components are not receiving
engine power, they are still connected to the non-driven wheels and
will rotate when the vehicle is in motion. This unnecessary rotation
consumes energy,\513\ and leads to increased fuel consumption that
could be avoided if the secondary axle components were completely
disconnected and not rotating.
---------------------------------------------------------------------------

    \513\ Any time a drivetrain component spins it consumes some
energy, primarily to overcome frictional forces.
---------------------------------------------------------------------------

    Light-duty AWD systems are often designed to divide variably torque
between the front and rear axles in normal driving to optimize traction
and handling in response to driving conditions. However, even when the
secondary axle is not necessary for enhanced traction or handling, in
traditional AWD systems it typically remains engaged with the driveline
and continues to generate losses that could be avoided if the axle was
instead disconnected. The SAX technology observed in the marketplace
disengages one axle (typically the rear axle) for 2WD operation but
detects changes in driving conditions and automatically engages AWD
mode when it is necessary. The operation in 2WD can result in reduced
fuel consumption. For example, Chrysler has estimated the secondary
axle disconnect feature in the Jeep Cherokee reduces friction and drag
attributable to the secondary axle by 80 percent when in disconnect
mode.\514\
---------------------------------------------------------------------------

    \514\ Brooke, L. ``Systems Engineering a new 4x4 benchmark'',
SAE Automotive Engineering, June 2, 2014.
---------------------------------------------------------------------------

    Observing SAX technology on actual vehicles is very difficult.
Manufacturers do not typically identify the technology on technical
specifications or other widely available information. We employed an
approach consistent with previous rulemaking in assigning this
technology. Specifically, we assigned SAX technology based on a
combination of publicly available information and previously submitted
confidential information. In the analysis fleet, 38 percent of the
vehicles that had AWD or 4WD are determined to have SAX technology. All
vehicles in the analysis fleet with FWD or RWD have SAX skipped since
SAX technology is a way to emulate FWD or RWD in AWD and 4WD vehicles,
respectively. We did not allow for the application of SAX technology to
FWD or RWD vehicles because they do not have a secondary driven axle to
disconnect.
    SAX technology can be adopted by any vehicle in the analysis fleet,
including those with a HEV or BEV powertrain,\515\ which was identified
as having AWD or 4WD. It does not supersede any technology or result in
any other technology being excluded for future implementation for that
vehicle. SAX technology can be applied during any refresh or redesign.
---------------------------------------------------------------------------

    \515\ The inefficiencies addressed on ICEs by SAX technology may
not be similar enough, or even present, in HEVs or BEVs.
---------------------------------------------------------------------------

    This analysis carries forward work on the effectiveness of SAX
systems conducted in the Draft TAR and EPA Proposed Determination.\516\
This work involved gathering information by monitoring press reports,
holding meetings with suppliers and OEMs, and attending industry
technical conferences. We did not simulate SAX effectiveness in the
Autonomie modeling because, similar to LDB, IACC, and EFR, the fuel
economy benefits from the technology are not fully captured on the two-
cycle test. The secondary axle disconnect effectiveness values, for the
most part, have been accepted as plausible based on the rulemaking
record and absence of contrary comments. As such, the agency has
prioritized its extensive Autonomie vehicle simulation work toward
other technologies that are emerging or considered more critical for
total system effectiveness. Table III-32 shows the resulting
effectiveness estimates we used in this analysis.
---------------------------------------------------------------------------

    \516\ Draft TAR, at 5-412; Proposed Determination TSD, at 2-422.

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[GRAPHIC] [TIFF OMITTED] TR02MY22.100

(e) Other Vehicle Technology Costs
    The cost estimates for EPS, IACC, SAX, and LDB \517\ rely on
previous work published as part of past rulemakings with learning
applied to those cost values which is founded in the 2002 NAS
Report.\518\ The cost values are the same values that were used for the
Draft TAR and 2020 final rule, updated to 2018 dollars. Table III-33
shows examples of costs for these technologies across select model
years. Note that these costs are the same for all vehicle technology
classes. For all absolute EPS, IACC, LDB, and SAX technology costs
across all model years, see the Technologies file.
---------------------------------------------------------------------------

    \517\ Note that because LDB technology is applied universally as
a baseline technology in the MY 2020 fleet, there is functionally
zero costs for this technology associated with this rulemaking.
    \518\ National Research Council 2002. Effectiveness and Impact
of Corporate Average Fuel Economy (CAFE) Standards. Washington, DC:
The National Academies Press. https://doi.org/10.17226/10172.
[GRAPHIC] [TIFF OMITTED] TR02MY22.101

8. Simulating Air Conditioning Efficiency and Off-Cycle Technologies
    Off-cycle and air conditioning (AC) efficiency technologies can
provide fuel economy benefits in real-world vehicle operation, but
those benefits cannot be fully captured by the traditional 2-cycle test
procedures used to measure fuel economy.\519\ Off-cycle technologies
include technologies like high efficiency alternators and high
efficiency exterior lighting.\520\ AC efficiency technologies are
technologies that reduce the operation of or the loads on the
compressor, which pressurizes AC refrigerant. The less the compressor
operates or the more efficiently it operates, the less parasitic load
the compressor places on the engine, resulting in better fuel
efficiency.
---------------------------------------------------------------------------

    \519\ See 49 U.S.C. 32904(c) (``The Administrator shall measure
fuel economy for each model and calculate average fuel economy for a
manufacturer under testing and calculation procedures prescribed by
the Administrator . . . . the Administrator shall use the same
procedures for passenger automobiles the Administrator used for
model year 1975 (weighted 55 percent urban cycle and 45 percent
highway cycle), or procedures that give comparable results.'').
    \520\ 40 CFR 86.1869-12(b)--Credit available for certain off-
cycle technologies.
---------------------------------------------------------------------------

    Vehicle manufacturers have the option to generate credits for off-
cycle technologies and improved AC systems under the EPA's CO2 program
and receive an FCIV equal to the value of the benefit not captured on
the 2-cycle test under NHTSA's CAFE program. The FCIV is not a
``credit'' in the NHTSA CAFE program,\521\ but the FCIVs increase the
reported fuel economy of a manufacturer's fleet, which is used to
determine compliance. EPA applies FCIVs during determination of a
fleet's final average fuel economy reported to NHTSA.\522\ In the CAFE
Model, we only calculate and apply FCIVs at a fleet level for a
manufacturer based on the volume of the manufacturer's fleet that
contain qualifying technologies.\523\
---------------------------------------------------------------------------

    \521\ Unlike, for example, the statutory overcompliance credits
prescribed in 49 U.S.C. 32903.
    \522\ 49 U.S.C. 32904(c)-(e). EPCA granted EPA authority to
establish fuel economy testing and calculation procedures. See
Section VII for more information.
    \523\ 40 CFR 600.510-12(c).
---------------------------------------------------------------------------

    There are three pathways that manufacturers can use to determine
the value of AC efficiency and off-cycle adjustments. First,
manufacturers can use a predetermined list or ``menu'' of g/mi values
that EPA established for specific off-cycle technologies.\524\ Second,
manufacturers can use 5-cycle testing to demonstrate off-cycle CO2
benefit; \525\ the additional tests allow emissions benefits to be
demonstrated over some elements of real-world driving not captured by
the 2-cycle compliance tests, including high speeds, rapid
accelerations, hot temperatures, and cold temperatures. Third,
manufacturers can seek EPA approval, through a notice and comment
process, to use an alternative methodology other than the menu or 5-
cycle methodology for determining the off-cycle technology improvement
values.\526\ For further discussion of the AC and off-cycle compliance
and application process, see Section VII.
---------------------------------------------------------------------------

    \524\ See 40 CFR 86.1869-12(b). The TSD for the 2012 final rule
for MYs 2017 and beyond provides technology examples and guidance
with respect to the potential pathways to achieve the desired
physical impact of a specific off-cycle technology from the menu and
provides the foundation for the analysis justifying the credits
provided by the menu. The expectation is that manufacturers will use
the information in the TSD to design and implement off-cycle
technologies that meet or exceed those expectations in order to
achieve the real-world benefits of off-cycle technologies from the
menu.
    \525\ See 40 CFR 86.1869-12(c). EPA proposed a correction for
the 5-cycle pathway in a separate technical amendments rulemaking.
See 83 FR 49344 (Oct. 1, 2019). EPA is not approving credits based
on the 5-cycle pathway pending the finalization of the technical
amendments rule.
    \526\ See 40 CFR 86.1869-12(d).
---------------------------------------------------------------------------

    We and EPA have been collecting data on the application of these
technologies since implementing the AC and off-cycle programs.\527\
\528\ Most manufacturers are applying AC efficiency and off-cycle
technologies; in MY 2020, 17 manufacturers employed AC efficiency
technologies and 20 manufacturers employed off-cycle technologies,
though the level of deployment varies by manufacturer.\529\
---------------------------------------------------------------------------

    \527\ See 77 FR 62832, 62839 (Oct. 15, 2012). EPA introduced AC
and off-cycle technology credits for the CO2 program in
the MYs 2012-2016 rule (75 FR 25324, May 7, 2010) and revised the
program in the MY 2017-2025 rule (77 FR 62624, Oct. 15, 2012) and
NHTSA adopted equivalent provisions for MYs 2017 and later in the MY
2017-2025 rule.
    \528\ Vehicle and Engine Certification. Compliance Information
for Light-Duty Gas (GHG) Standards. Compliance Information for
Light-Duty Greenhouse Gas (GHG) Standards [bond] Certification and
Compliance for Vehicles and Engines [bond] U.S. EPA. Last accessed
December 22, 2021.
    \529\ See 2021 EPA Automotive Trends Report, at 90 and 92.
---------------------------------------------------------------------------

    Manufacturers have only recently begun including detailed
information on off-cycle and AC efficiency technologies equipped on
vehicles in compliance reporting data. For this analysis, though, such
information was not sufficiently complete to support a detailed
representation of the application of off-cycle technology to specific
vehicle

model/configurations in the MY 2020 fleet. To account for the AC and
off-cycle technologies equipped on vehicles and the potential that
manufacturers will apply additional AC and off-cycle technologies in
the rulemaking timeframe, we specify CAFE Model inputs for AC
efficiency and off-cycle FCIVs in grams/mile for each manufacturer's
fleet in each model year. We estimate future potential AC efficiency
and off-cycle technology application in the CAFE analyses based on an
expectation that manufacturers already relying heavily on these
adjustments would continue do so, and that other manufacturers would,
over time, also approach the limits on adjustments allowed for such
improvements.
    The next sections discuss how the CAFE Model simulates the
effectiveness and cost for AC efficiency and off-cycle technology
adjustments.
(a) AC and Off-Cycle Effectiveness Modeling in the CAFE Model
    In this analysis, the CAFE Model applies AC and off-cycle
flexibilities to manufacturer's CAFE regulatory fleet performance in a
similar way to the regulation.\530\ As the CAFE Model simulates the
addition of technology to vehicles in a given model year fleet, the
model first applies conventional technologies to vehicles in an attempt
to meet a given standard, and then applies AC efficiency and off-cycle
FCIVs to each regulatory fleet. In other words, first the CAFE Model
applies conventional technologies to each manufacturers' vehicles in
each model year to assess the 2-cycle sales weighted harmonic average
CAFE rating. Then, the CAFE Model assesses the CAFE rating to use for a
manufacturer's compliance value after applying the AC efficiency and
off-cycle FCIVs designated in the Market Data file. The CAFE Model does
this on a year-by-year basis. The CAFE Model attempts to apply
technologies and FCIVs in a way that both minimizes cost and allows the
manufacturer to meet their standards without over or under complying.
---------------------------------------------------------------------------

    \530\ 49 CFR 531.6 and 49 CFR 533.6 Measurement and Calculation
procedures.
---------------------------------------------------------------------------

    To determine how manufacturers might adopt AC efficiency and off-
cycle technologies in the rulemaking timeframe, we use data from EPA's
2021 Trends Report for MY 2020 and CBI compliance material from
manufacturers.\531\ \532\ We use manufacturer's MY 2020 AC efficiency
and off-cycle FCIVs as a starting point, and then extrapolate values in
each model year until MY 2026, for light trucks to the proposed
regulatory cap, for each manufacturer's fleets by regulatory class.
---------------------------------------------------------------------------

    \531\ Vehicle and Engine Certification. Compliance Information
for Light-Duty Gas (GHG) Standards. Compliance Information for
Light-Duty Greenhouse Gas (GHG) Standards [verbar] Certification and
Compliance for Vehicles and Engines [verbar] U.S. EPA. Last accessed
May 24, 2021.
    \532\ 49 U.S.C. 32907.
---------------------------------------------------------------------------

    To determine the rate at which to extrapolate the addition of AC
and off-cycle technology adoption for each manufacturer, we use
historic AC and off-cycle technology applications, each manufacturer's
fleet composition (i.e., breakdown between passenger cars (PCs) and
light trucks (LTs)), availability of AC and off-cycle technologies that
manufacturers could still use, and CBI compliance data. Different
manufacturers show different levels of historical AC efficiency and
off-cycle technology adoption; therefore, different manufacturers hit
the proposed regulatory caps for AC efficiency technology for both
their PC and LT fleets, and different manufacturers hit caps for off-
cycle technologies in the LT regulatory class. We do not extrapolate
off-cycle technology adoption for PCs to the proposed regulatory cap
for a few reasons. First, past EPA Trends Reports showed that many
manufacturers did not adopt off-cycle technology to their passenger car
fleets. Next, manufacturers limited PC offerings in MY 2020 as compared
to historical trends. Last, available CBI compliance data indicated
that PCs adopt a lower level of menu item off-cycle technologies than
LTs. We accordingly limit the application of off-cycle FCIVs to 10 g/mi
for PCs but allow LTs to apply 15 g/mi of off-cycle FCIVs starting in
MY 2023 for the final rule analysis. This decision also aligns with
EPA's treatment of off-cycle adjustments in its final rule. The inputs
for AC efficiency technologies are set to 5 g/mi and 7.2 g/mi for PCs
and LTs, respectively. We allow AC efficiency technologies to reach the
regulatory caps by MY 2024, which is the first year of standards
assessed in this analysis.
    We apply FCIVs in this way because the AC and off-cycle
technologies are generally more cost-effective than other technologies.
The details of this assessment (and the calculation) are further
discussed in the CAFE Model Documentation.\533\ The AC efficiency and
off-cycle adjustment schedules used in this analysis are shown in TSD
Chapter 3.8 and in the Market Data file's Credits and Adjustments
worksheet. Like the NPRM, for this final rule analysis we did not allow
some manufacturers to reach the AC efficiency and off-cycle caps to
avoid over compliance in the rulemaking time frame. Table III-34 and
Table III-35 show the average FCIVs applied to the regulatory fleets
for the final rule analysis.
---------------------------------------------------------------------------

    \533\ CAFE Model Documentation, S5.
    [GRAPHIC] [TIFF OMITTED] TR02MY22.102

[GRAPHIC] [TIFF OMITTED] TR02MY22.103

    We received limited comments on how we model off-cycle and AC
efficiency for this rulemaking analysis. Auto Innovators stated that
``due to the static nature of the forecasts and input structure, the
NHTSA forecasts on the quantity of off-cycle credits do not vary by
scenario, and this creates material distortions in the model outputs.
For instance, the projected Central case adoption of off-cycle
technologies may contribute to over-compliance with some scenarios,
especially low stringency scenarios.'' \534\ On the other hand, UCS
stated that ``NHTSA has not acknowledge that its [CAFE Model] does not
consider increased adoption of off-cycle technology to yield any real-
world benefit . . . there is supportive evidence of their real-world
benefits, and at any rate NHTSA must state explicitly its rationale for
excluding these technologies from the benefits of the rule, as the
credits associated with these technologies represent a substantial
share of the credits accrued for compliance by manufacturers.'' UCS
also stated that ``NHTSA should correct the [CAFE Model] to ensure it
adjusts a vehicle's fuel economy to account for reductions in emissions
and fuel use from off-cycle technologies, which will yield a more
accurate accounting of the benefits from the CAFE program.'' \535\
---------------------------------------------------------------------------

    \534\ Auto Innovators, Docket No. NHTSA-2021-0053-0021 Appendix
VII, at 125-126.
    \535\ UCS, Docket No. NHTSA-2021-0053-1567, at 31.
---------------------------------------------------------------------------

    In response to comments from Auto Innovators, we agree that, in
theory, the way the CAFE Model is set up to apply off-cycle benefits
statically could create overcompliance for some manufacturers. However,
as discussed earlier and in TSD Chapter 3.8, we apply off-cycle and
other flexibilities differently for each manufacturer rather than apply
adjustments consistently to the cap for each manufacturer. For example,
if a manufacturer is on a trajectory to reach the off-cycle regulatory
cap, then we allow the model to reach that cap regardless of
alternatives. On the other hand, if a manufacturer has historically
lagged in the adoption of off-cycle technology, we use this historic
rate of application through the rulemaking time frame. As shown in
Table III-34 and Table III-35, on average, the fleet does not reach the
regulatory caps based on our extrapolation.
    We understand UCS's concern, that because the CAFE Model accounts
for off-cycle technology at the fleet level, the benefits do not
directly appear in the vehicle-level benefits analysis. Although
further refinement may be possible for future analyses, at this time
there are only limited vehicle-level data available. We agree that some
manufacturers have relied on these flexibilities more so than others,
but as indicated by the 2021 EPA Trends Report many are still lagging
in adopting these technologies.\536\ This is one reason why we declined
to apply off-cycle benefits up to the cap for each vehicle to have
those benefits automatically count in the benefits calculations. Based
on the ratio of benefits that manufacturers can expect from on-cycle
versus off-cycle technology, we believe that the small off-cycle
technology benefit that is not accounted for in the benefits
calculations does not make a material difference to the analysis.
---------------------------------------------------------------------------

    \536\ 2021 EPA Trends Report at 104-106.
---------------------------------------------------------------------------

    For the final rule analysis, we updated the baseline fleet off-
cycle data to reflect the 2021 EPA Trends Report, using the same
modeling methodology as the NPRM. We believe that this approach is
appropriate to capture the costs and benefits of off-cycle
technologies.
(b) AC and Off-Cycle Costs
    For this analysis, AC and off-cycle technologies are applied
independently of the decision trees using the extrapolated values shown
above, so it is necessary to account for the costs of those
technologies independently. Table III-36 shows the costs used for AC
and off-cycle FCIVs in this analysis. The costs are shown in dollars
per gram of CO2 per mile ($ per g/mile). The AC efficiency and off-
cycle technology costs are the same costs used in the EPA Proposed
Determination and described in the EPA Proposed Determination TSD.\537\
---------------------------------------------------------------------------

    \537\ EPA PD TSD. EPA-420-R-16-021. November 2016. At 2-423-2-
245. https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100Q3L4.pdf. Last
accessed May 24, 2021.
---------------------------------------------------------------------------

    To develop the off-cycle technology costs, we selected the second
generic 3 g/mile package estimated to cost $170 (in 2015$) to apply in
this analysis in $ per g/mile. We updated the costs used in the
Proposed Determination TSD from 2015$ to 2018$, adjusted the costs for
RPE, and applied a relatively flat learning rate.
    Similar to off-cycle technology costs, we used the cost estimates
from EPA Proposed Determination TSD for AC efficiency technologies that
relied on the 2012 rulemaking TSD.\538\ We updated these costs to 2018$
and adjusted for RPE for this analysis and applied the same mature
learning rate that we had applied for off-cycle technologies.
---------------------------------------------------------------------------

    \538\ Joint NHTSA and EPA 2012 TSD, see Section 5.1.

---------------------------------------------------------------------------

[GRAPHIC] [TIFF OMITTED] TR02MY22.104

    In the NPRM we sought comment on whether our costs were appropriate
or if other costs should be used. Overall, comments from UCS, Consumer
Reports, and ICCT stated that our costs for off-cycle technologies were
high.\539\ Consumer Reports indicated that they did not investigate the
NHTSA approach to AC and off-cycle adjustments and costs. However
Consumer Reports did find ``that under the EPA proposal the use of
similar costs for off-cycle technologies resulted in compliance costs
for those technologies that were more than three times the average
compliance costs of all the technology applied to achieve the Preferred
Alternative.'' \540\ ICCT stated that ``the agencies use an arbitrarily
and unrealistically high estimate of off-cycle credit cost in their
compliance modeling.'' \541\ UCS conducted an analysis of off-cycle
costs using the 2020 final rule's CAFE Model and data from the 2021 NAS
Report to show that the average costs could be different if the
agencies used different inputs.\542\ This approach is similar to the
one used by EPA in the final rule for MYs 2023-2026 in determining the
costs of off-cycle.
---------------------------------------------------------------------------

    \539\ Consumer Reports, Docket No. NHTSA-2021-0053-1576, at 22;
UCS, at 30; ICCT, Docket No. NHTSA-2021-0053-1581, at 8.
    \540\ Consumer Reports, at 22-23.
    \541\ ICCT, at 8.
    \542\ UCS, at 30.
---------------------------------------------------------------------------

    As we discussed in the NPRM and explained again above, the CAFE
Model was updated from the 2020 final rule model to better account for
costs of AC and Off-Cycle technologies.543 544 This update
fixed many of the issues highlighted by the commenters by baking in the
costs per vehicle of the off-cycle technology in the baseline vehicle
and excluding the costs from affecting the new vehicle model output
costs. The CAFE Model used by EPA in their rulemaking analysis for MYs
2023-2026 did not have this feature, and they were required to re-
evaluate the costs as described in the EPA Regulatory Impacts
Analysis.\545\
---------------------------------------------------------------------------

    \543\ 86 FR 49605 (Sept. 3, 2021).
    \544\ ``More accurate accounting for off-cycle incremental costs
relative to MY 2020 baseline fleet.''
    \545\ EPA Final Rule for MYs 2023-2026 RIA, Chapter <IP_ADDRESS>,
Off-Cycle Credit Cost and changes since the Proposed Rule, at p. 4-
6.
---------------------------------------------------------------------------

    Separately, none of these commenters provided alternative AC and
off-cycle technology costs in response to our request that commenters
provide any data or information on which any alternative costs are
based on. General statements that costs should be lower, without
specific data and analysis to support those statements, are not enough
to justify a change from the NPRM values. As one example, the 2021 NAS
Report observed an AC efficiency technology similar to one used by
Toyota, and they estimated the cost of that technology to be $170 in
2025.546 547 However, that was not enough information for us
to update our gram per mile cost for all technologies. We will continue
to research this issue for future analyses.
---------------------------------------------------------------------------

    \546\ 2021 NAS Report, at 68.
    \547\ EPA Decision Document. ``Off-Cycle Credits for Toyota
Motor North America.'' EPA-420-R-21-024. October 2021. https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1013CFF.pdf. (Accessed: March
15, 2022)
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E. Consumer Responses to Manufacturer Compliance Strategies

    The previous subsections in Section III have so far discussed how
manufacturers might respond to changes to the standards. While the
technology analysis is informative of the different compliance
strategies available to manufactures, the tangible costs and benefits
that accrue because of CAFE standards also depend on how consumers
respond to the decisions made by manufacturers. Many of the benefits
and costs resulting from changes to CAFE standards are private benefits
that accrue to the buyers of new cars and trucks produced in the model
years subject to this rulemaking. These benefits and costs largely flow
from the changes to vehicle purchases, ownership, and operating costs
that result from improved fuel economy, as well as from the costs of
the technology required to achieve those improvements. In addition,
buyers' and owners' decisions about the use of their vehicles can
impose costs or create benefits that fall on others, which the agency
refers to as ``external'' costs or benefits. The following subsections
describe how NHTSA's analyzes consumer responses to changing vehicles
and prices.
1. Assumptions About Macroeconomic Conditions and Consumer Behavior
    This final rule includes a comprehensive economic analysis of the
impacts of establishing more stringent CAFE standards, and most of the
effects it measures are influenced by future macroeconomic conditions
that are beyond the agency's influence. For example, domestic fuel
prices are mainly determined by global petroleum supply and demand as
well as refining costs, yet they determine how much technology
manufacturers will employ to improve the fuel economy of cars and light
trucks produced for the U.S. market, how much consumers are willing to
pay for new vehicles offering different levels of fuel economy, how
much new and used cars and light trucks will be driven, and the value
of each gallon saved through higher CAFE standards. Similarly,
projecting sales of new cars and light trucks produced during the model
years subject to the standards this final rule establishes requires
robust projections of demographic and macroeconomic variables that span
the entire timeframe of the analysis, including U.S. population, Gross
Domestic Product (GDP), consumer confidence about future economic
conditions, and disposable personal income.
    To ensure internal consistency within the agency's analysis,
projections of most of the economic variables used in our analysis are
obtained from the same source. The analysis presented here relies on
forecasts of fuel prices issued by the U.S. Energy Information
Administration (EIA), an agency within the DOE that collects, analyzes,
and disseminates independent and impartial energy data and forecasts to
promote sound policymaking, efficient markets, and public understanding
of energy and its interaction with the economy and the environment. EIA
uses its National Energy Model System (NEMS) to produce its Annual
Energy Outlook

(AEO), which includes forecasts of future U.S. macroeconomic growth and
fuel prices among many other energy-related variables. NHTSA's main
analysis uses forecasts of fuel prices, from the AEO 2021 Reference
Case. The agency also uses forecasts of the U.S. population, the number
of U.S. households, the Nation's Gross Domestic product (GDP),
disposable personal income, and consumer confidence to develop its
projections of new car and light truck sales as well as of total light-
duty vehicle travel. For the current analysis, NHTSA obtained forecasts
of these variables from the IHS Markit Global Insight October 2021
Macroeconomic Outlook base case, which represents the most likely
scenario from that organization's most current forecast. EIA also
relies on the IHS Markit Global Insight Macroeconomic Outlook to
develop the macroeconomic and energy price forecasts included as part
of its Annual Energy Outlook. However, the forecasts EIA presents in
its Annual Energy Outlook 2021 are based on the IHS Markit Global
Insight March 2021 Macroeconomic Outlook, rather than the more recent
October 2021 Outlook the agency relies on in this analysis. Because the
forecasts of population, GDP, disposable income, and other variables in
the March 2021 and October 2021 Macroeconomic Outlooks are very
similar, the forecasts the agency relies on in this analysis are
generally consistent with those reported in EIA's AEO 2021. TSD Chapter
4.1 includes a more complete discussion of the macroeconomic
assumptions made for the analysis.
    While these macroeconomic assumptions are some of the most critical
inputs to the analysis, they are also subject to the most uncertainty--
particularly over the lifetimes of the vehicles subject to this final
rule, which can extend as far as forty years into the future. The
agency also uses low and high economic growth and global oil price
forecasts issued by EIA as part of its Annual Energy Outlook as
alternative cases in its sensitivity analyses. The purpose of these
sensitivity analyses, which are discussed in greater detail in FRIA
Chapters 6 and 7, is not to posit a more credible future state of the
world than the central case, which the agency assumes represents the
most likely future state of the world. Instead, the sensitivity
analyses are intended to illustrate the degree to which important
future outcomes resulting from this final rule might change under
different assumptions about fuel prices, economic growth, and other
factors.
    The agency received several comments about the macroeconomic
assumptions used in the analysis. Auto Innovators correctly noted that
fuel prices will influence the adoption of advanced technologies and
the cost and benefits realized under the new standards, and commented
that EIA's projections may overestimate fuel prices. In support of its
claim, Auto Innovators notes that EIA's projections have historically
overestimated fuel prices and speculates that the current forecasts
could overestimate domestic demand if the ``EIA Central Case gasoline
forecast assumes fewer than 50 [percent] plug-in vehicles by 2030.''
\548\ In that event, Auto Innovators recommended that NHTSA instead
rely on the IHS Markit Global Insight forecast of fuel prices
throughout its main analysis, which as its comment showed falls
considerably below the AEO 2021 Reference Case forecast after about the
year 2030. Auto Innovators recognized that NHTSA does use the Global
Insight forecast it recommended for the purpose of sensitivity analysis
but encouraged the agency to feature it more prominently.
---------------------------------------------------------------------------

    \548\ Auto Innovators, Docket No. NHTSA-2021-0053-0021, at 58-
59. The AEO 2021 Reference Case forecasts that less than 2 percent
of new car and light truck sales during 2030 will be plug-in hybrid
models and including projected sales of conventional hybrid models
increases that figure to somewhat more than 6 percent.
---------------------------------------------------------------------------

    In contrast, Consumer Reports asserted that the AEO 2021
projections underestimated how quickly fuel prices would rebound from
the diminished demand caused by onset of COVID-19. Consumer Reports
suggested that the agency use the AEO 2020 reference case instead of
that from AEO 2021 to avoid the potential for fuel prices from calendar
year 2020 to unduly influence the rest of the analysis.\549\ As
discussed earlier, projections are inherently uncertain and actual
prices are likely to deviate from those forecast for any given future
year, and the accuracy of a multi-year forecast should not be judged by
its ability to predict the value realized in a single period. In any
case, the agency determined that the AEO 2021 projections of fuel
prices were more appropriate for this analysis, because they
incorporate the potential long-term impacts of the COVID-19 pandemic
and its effects on travel activity, gasoline demand, and future fuel
prices.\550\
---------------------------------------------------------------------------

    \549\ Consumer Reports, Comment Body, Docket No. NHTSA-2021-
0053-1576, at 23.
    \550\ EIA reports that actual retail gasoline prices during 2021
averaged $3.10 per gallon, considerably higher than the $2.36
average price projected for 2021 as part of AEO 2021. While part of
this discrepancy probably owes to an overly cautious view of how
rapidly global demand for petroleum products would return to its
pre-pandemic level, other unforeseen factors apparently contributed
as well. This is evidenced by the fact that actual gasoline prices
during 2021 were well above their levels during the pre-pandemic
years of 2018 and 2019, when they averaged $2.81 and $2.69 per
gallon.
---------------------------------------------------------------------------

    Commenters also raised concerns about the included electricity
price forecast. Auto Innovators, for example, proposed electricity rate
inputs are too low in the face of anticipated increases in renewable
electricity generation and may therefore overestimate benefits of the
regulatory action.\551\ The commenters pointed to research from the
National Renewable Energy Laboratory that suggests price increases are
possible and noted EPA's fuel price inputs increase to $0.133 per kWh
in 2040 (compared to $0.120 in the NHTSA's NPRM). Auto Innovators did
not suggest alternative price series and NHTSA is wary of varying fuel
prices without simultaneously varying assumptions about electricity
grid mix. Further, the CAFE Model is unable to simulate regional
differences in electricity generation and fuel prices and cannot
capture regional differences in electricity prices, which may arise
from heterogeneity in grid mix. The agency did include a sensitivity
case that varied projections about electricity supply and included a
case with high levels of renewable energy generation from EIA. These
results are included in FRIA Chapter 7.
---------------------------------------------------------------------------

    \551\ Auto Innovators, A1, at 85.
---------------------------------------------------------------------------

    Another key assumption that has important ramifications throughout
the agency's analysis is how much consumers are willing to pay for
improved fuel economy. If buyers fully value the savings in fuel costs
that result from driving (and potentially re-selling) vehicles with
higher fuel economy and manufacturers supply all improvements in fuel
economy that buyers demand, market-determined levels of fuel economy
would reflect both the cost of improving it and the private benefits
from doing so.\552\ In that case, regulations on fuel economy would
only be necessary to reflect environmental or other benefits other than
to buyers themselves. But if consumers instead undervalue future fuel
savings or are otherwise unable to purchase their optimal levels of
fuel economy due to market failures, they will underinvest in fuel
economy and manufacturers would spend too little on fuel-saving
technology (or deploy its energy-saving benefits to improve vehicles'
other

attributes). In that case, more stringent fuel economy standards could
lead manufacturers to adopt improvements in fuel economy that not only
reduce external costs from producing and consuming fuel to appropriate
levels but also improve consumer welfare.
---------------------------------------------------------------------------

    \552\ Besides fuel savings, the private benefits from increased
fuel economy may also include increased driving range, decreased
costs per mile driven, and refueling benefits such as the experience
of not having to stop as often to refuel.
---------------------------------------------------------------------------

    Increased fuel efficiency offers vehicle owners significant
potential savings; in fact, our analysis shows that the value of
prospective fuel savings exceeds manufacturers' technology costs to
comply with even the most stringent standards considered for this final
rule when both are discounted at a either a 3 percent or 7 percent
rate. It would seem reasonable to assume that well-informed vehicle
shoppers, if without time constraints or other barriers to rational
decision-making, will recognize the full value of fuel savings from
purchasing a model that offers higher fuel economy, since they would
enjoy an equivalent increase in their disposable income and the other
consumption opportunities it affords them. If consumers did value the
full amount of fuel savings, more fuel-efficient vehicles would
functionally be less costly for consumers to own when considering both
their initial purchase prices and subsequent operating costs, thus
making the models that manufacturers are likely to offer under stricter
alternatives more attractive than those available under the No-Action
Alternative.
    Recent econometric research is divided between studies concluding
that consumers value most or all of the potential savings in fuel costs
from driving higher-mpg vehicles, and those concluding that consumers
significantly undervalue expected fuel savings. Based on a detailed
analysis of changes in recent sale values of cars and light trucks in
response to variation in fuel prices, Busse et al. (2013) estimated
that buyers value 54 to 117 percent of fuel savings from purchasing
higher-mpg models, with the exact value depending on the discount rate
they apply to future savings; their estimates for new car buyers ranged
from 75 to 133 percent of future fuel savings, Using similar methods
and an extremely large sample of used vehicle sales, Allcott and Wozny
(2014) estimated a corresponding range of 55 to 76 percent depending on
their assumptions about buyers' discount rates and expectations for
future fuel prices, with a figure of 93 percent for buyers of the
newest (1-3 year old) cars in their sample. Again using similar
methods, Sallee et al. (2016) estimated that car and light truck buyers
are willing to pay from 60 percent to perhaps as much as 142 percent of
the value of future fuel savings to purchase models offering higher
fuel economy. Most recently, Leard and Zhou's (2021) analysis puts the
most likely value for this figure at slightly above half (54 percent),
and Gillingham et al. (2021) find that ``consumers systematically
undervalue fuel economy in vehicle purchases to a larger degree than
reported by much of the recent literature.'' 553 554
---------------------------------------------------------------------------

    \553\ Busse, M., C. Knittel, and F. Zettelmeyer. 2013. ``Are
Consumers Myopic? Evidence from New and Used Car Purchases.''
American Economic Review 103(1): 220-56; Allcott, H., and N. Wozny.
2014. ``Gasoline Prices, Fuel Economy, and the Energy Paradox.'' The
Review of Economics and Statistics 96(5): 779-95; Sallee, J., S.
West, and W. Fan. 2016. ``Do Consumers Recognize the Value of Fuel
Economy? Evidence from Used Car Prices and Gasoline Price
Fluctuations.'' Journal of Public Economics 135: 61-73; Leard, B.,
J. Linn, and Y. Zhou. 2021. ``How Much Do Consumers Value Fuel
Economy and Performance? Evidence from Technology Adoption.'' The
Review of Economics and Statistics: 1-45 (forthcoming); Gillingham,
K.T., S. Houde, and A. van Bentham, 2021. ``Consumer Myopia in
Vehicle Purchases: Evidence from a Natural Experiment.'' American
Economic Journal: Economic Policy 13(3): 207-238.
    \554\ Other research asks the more fundamental questions of
whether consumers are adequately informed about and attentive to
potential fuel savings from buying higher-mpg models when they shop
for new cars, and again arrives at mixed conclusions. This includes
Allcott, H. and C. Knittel, 2019. ``Are Consumers Poorly Informed
about Fuel Economy? Evidence from Two Experiments'', AEJ: Economic
Policy, 11(1): 1-37, and D. Duncan, A. Ku, A. Julian, S. Carley, S.
Siddiki, N. Zirogiannis and J. Graham, 2019. ``Most Consumers Don't
Buy Hybrids: Is Rational Choice a Sufficient Explanation?'', J. of
Benefit-Cost Analysis, 10(1): 1-38. The former analysis concludes
that consumers appear to be relatively well-informed about the value
of higher fuel economy when they shop for new vehicles, while the
latter concludes that some buyers appear inattentive to savings
available from buying higher-MPG hybrid versions of certain vehicle
models.
---------------------------------------------------------------------------

    More circumstantial evidence appears to show that consumers do not
fully value the expected lifetime fuel savings from purchasing higher-
mpg models. Although the average fuel economy of new vehicles reached
an all-time high of 25.7 MPG in MY 2020, this is still significantly
below the fuel economy of the fleet's most efficient vehicles that are
readily available for consumers to purchase.555 556
Manufacturers have repeatedly informed the agency that consumers value
only 2 to 3 years of the future fuel savings that higher-mpg cars and
light trucks offer when choosing among available models.
---------------------------------------------------------------------------

    \555\ See EPA 2020 Automotive Trends Report at 6 and 9,
available at https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1010U68.pdf. (Accessed: March 15, 2022)
    \556\ Of course, this could simply suggest that the future
savings in fuel costs those models offer--given potential buyers'
expectations about future fuel prices--do not justify manufacturers'
costs for providing them, since those are presumably reflected in
their higher purchase prices.
---------------------------------------------------------------------------

    The potential for car buyers to voluntarily forgo improvements in
fuel economy that appear to offer future savings exceeding their
initial costs is one example of what is often termed the ``energy-
efficiency gap.'' The appearance of a gap between the level of energy
efficiency that would minimize consumers' overall expenses and what
they actually purchase is typically based on engineering calculations
that compare the initial cost for providing higher energy efficiency to
the discounted present value of the resulting savings in future energy
costs. There has long been an active debate about why such a gap might
arise and whether it exists. Economic theory predicts that economically
rational individuals will purchase more energy-efficient products only
if the savings in future energy costs they offer promise to offset
their higher initial costs. On the other hand, various market failures,
including information asymmetries between consumers, dealerships, and
manufacturers; market power; first-mover disadvantages for both
consumers and manufacturers; split incentives between vehicle
purchasers and vehicle drivers; and other failures may prevent
consumers from purchasing the optimal level of fuel economy in an
unregulated market. Furthermore, behavioral economics has documented
numerous situations in which the decision-making of consumers differs
in important ways from the predictions of the model of the fully
optimizing consumer (e.g., Dellavigna, 2009).\557\
---------------------------------------------------------------------------

    \557\ Dellavigna, S., 2009. ``Psychology and economics: Evidence
from the field,'' Journal of Economic Literature, 47(2), 315-372.
Available at https://pubs.aeaweb.org/doi/pdfplus/10.1257/jel.47.2.315. (Accessed: Mar. 24, 2022).
---------------------------------------------------------------------------

    One explanation for such `undervaluation' of the savings from
purchasing higher-mpg models is myopia or present bias, where consumers
focus unduly on short-term costs while giving insufficient attention to
long-term benefits.\558\ This situation could arise because buyers are
unsure whether they will actually realize the fuel savings indicated by
test data posted on cars' fuel economy labels under the conditions
where they drive, what future fuel prices will be, how long they will
own a new vehicle, or whether they will drive it enough to realize the
promised savings. As a consequence, they may view choosing

to purchase a more fuel-efficient vehicle as a risky ``bet,'' and
experimental research has shown that when faced with a risky choice,
some consumers appear to weigh the potential loss from an adverse
outcome approximately twice as heavily as the potential gain from
``winning'' the bet, leading them to significantly undervalue that
choice relative to its probabilistic ``expected'' value (e.g., Kahneman
and Tversky, 1979; \559\ Kahneman, 2011).\560\ Viewed in the context of
a choice to pay more for a higher-mpg car, loss aversion has been shown
to have the potential to cause undervaluation of future fuel savings
like that reported by manufacturers (Greene, 2011; \561\ Greene et al.,
2013).\562\
---------------------------------------------------------------------------

    \558\ Gillingham et al., 2021, which is an AEJ: Economic Policy
paper, just published on consumer myopia in vehicle purchases; a
standard reference on present bias generally is O'Donoghue, Ted, and
Matthew Rabin. 2015. ``Present Bias: Lessons Learned and To Be
Learned.'' American Economic Review: Papers & Proceedings 105(5):
273-79. Available at https://pubs.aeaweb.org/doi/pdfplus/10.1257/aer.p20151085. (Accessed: Mar. 30, 2022).
    \559\ Kahneman, D. and A. Tversky, 1979. ``Prospect theory: An
analysis of decision making under risk,'' Econometrica, 47, 263-291.
    \560\ Kahneman, D., 2011. Thinking Fast and Slow. Farrar, Straus
and Giroux, New York.
    \561\ Greene, D.L., 2011. ``Uncertainty, Loss Aversion and
Markets for Energy Efficiency,'' Energy Economics, 33, 608-616.
    \562\ Greene, D.L., D.H. Evans, and J. Hiestand, 2013. ``Survey
evidence on the willingness of U.S. consumers to pay for automotive
fuel economy,'' Energy Policy, 61, 1539-1550. Application of
investment under uncertainty will yield similar results as costs may
be more certain and up front while the fuel savings or benefits of
the investment may be perceived as more uncertain and farther into
future, thereby reducing investments in fuel saving technologies.
---------------------------------------------------------------------------

    The ``behavioral'' model of consumer choice also holds that
consumers' decisions are affected by the context of choices and its
effect on how consumers ``frame'' decisions. From this perspective, it
is possible that consumers respond to changes in the fuel economy new
vehicles offer required by government regulations such as CAFE
standards differently than they respond to manufacturers voluntarily
offering buyers the option to purchase models featuring the same fuel
economy levels those regulations would require.\563\ The intuition
behind this possibility is that if a consumer is shopping for a new car
in an unregulated market and considering two models--one that offers
higher fuel economy but is more expensive and another that does not but
is cheaper--she may buy the less fuel efficient version even if
choosing the more expensive model could save money in the long run. If
instead the consumer faced the decision to buy a new car or keep an
older one, and all new car models were required to meet fuel economy
standards, she may view the decision differently and elect to purchase
a new model offering the same price and fuel economy that she
previously declined to purchase. Further, if fuel economy standards
increased gradually over a period of years, this would allow time for
consumers to consult other information sources and verify that
potential fuel savings are likely to prove real and of substantial
value.
---------------------------------------------------------------------------

    \563\ See NASEM (2021), Ch. 11.3.3, We explain this potential
differential response more thoroughly in TSD Chapter <IP_ADDRESS>.
---------------------------------------------------------------------------

    Another alternative explanation for consumers' reluctance to
purchase more costly models whose lower fuel costs would ultimately
repay their higher purchase prices is that consumers view those higher
prices in the context of tradeoffs they make among their purchasing
decisions. Households must choose how to spread their limited incomes
over many competing goods and services, including deciding how much to
spend on a new vehicle, or even whether to opt for another form of
transportation instead. While a consumer may correctly recognize the
cumulative long-term value of fuel savings, they may also prefer to
spend the extra cost of buying a car that offers those savings on other
items, whether other vehicle attributes--more interior space and
comfort, for example, or a more luxurious trim package--or on other
unrelated goods and services. Some of the same technologies that
manufacturers have available to increase fuel economy can also enable
increased vehicle size, power, or weight while maintaining fuel
economy.\564\ While increased fuel efficiency will free up disposable
income throughout the lifetime of the vehicle (and may ultimately
exceed the additional upfront costs to purchase a more expensive but
more fuel-efficient vehicle), the value of owning a different good
sooner may provide consumers with even more benefit.\565\
---------------------------------------------------------------------------

    \564\ Other technologies may simultaneously increase both fuel
economy and certain performance attributes.
    \565\ While households have budgets, both individual vehicle
purchasers and the purchasers of large fleets of vehicles may have
access to financing for vehicle purchases. Given sufficient
financing, a rational consumer could both purchase fuel economy
improvements that will pay for themselves over time as well as other
desired goods. Failure to do so would seem to indicate either a lack
of efficient access to financing or some market failure.
---------------------------------------------------------------------------

    NHTSA's NPRM included an extensive theoretical discussion of
consumer valuation of fuel economy, including a detailed theoretical
analysis of consumer choices between vehicle performance and fuel
economy when buyers are constrained by limited budgets and
manufacturers by fuel economy standards. That analysis showed that when
fuel economy standards are binding, consumers might prefer that
manufacturers employ newly available technologies that could be used to
improve performance or increase fuel economy to improve performance,
and that manufacturers would be likely to do so. NHTSA's analysis also
suggested that if fuel economy standards no longer constrained
consumers' choices, due either to shifting preferences for fuel economy
(for example, in response to changes in the price of gasoline) or to
changes in buyers' income levels, manufacturers would be likely to use
new technologies to improve both performance and fuel economy. NHTSA
then presented trends in new vehicle fuel economy and performance over
time and suggested that its theoretical analysis was consistent with
the historical record, which shows the fuel economy of the new vehicle
fleet increases when the price of gasoline increases.\566\ NHTSA
solicited comments on its theoretical analysis and the potential
implications for its FRIA, and also sought potential approaches for
valuing the tradeoff between performance and fuel economy when NHTSA's
standards constrain consumers to choose more fuel-efficient options.
---------------------------------------------------------------------------

    \566\ For additional details, see 86 FR 49723-31 (Sept. 3,
2021).
---------------------------------------------------------------------------

    NHTSA noted in the NPRM that the substantial literature on the
topic of consumer valuation of fuel economy is approximately evenly
divided between studies that suggest consumer undervalue fuel economy
and studies that support valuation at the full discounted present value
(no undervaluation). This potential undervaluation, frequently referred
to as the ``energy paradox'' or ``fuel efficiency gap,'' has prompted
an extensive exploration of potential behavioral explanations why
consumers might undervalue fuel economy. NHTSA explored the possibility
that the context and framing around consumer decisions may influence
consumer choices--and that consumers may value fuel-saving technology
differently when their choices are constrained to more fuel-efficient
options. NHTSA also discussed how the value consumers place on fuel
economy may change over time, and that they may come to value the
future stream of fuel savings more once they begin to experience those
savings when the rule is in place. NHTSA noted that if fuel economy
standards lead consumers to value fuel economy more once they
experience a savings, the new higher valuation of fuel economy may
offset some or all of the negative impact

on sales due to the higher prices of fuel-efficient vehicles.
    As explained in more detail in TSD Chapter <IP_ADDRESS>, the agency's
analyses of the extent to which manufacturers will voluntarily improve
fuel economy and of the response of new car and light truck sales to
higher sales prices assume that potential buyers of new cars and light
trucks value only the undiscounted savings in fuel costs they would
expect to realize over the first 30 months they own a newly purchased
vehicle. Depending on the discount rate buyers are assumed to apply,
this amounts to 25-30 percent of the expected savings in fuel costs
they (and any subsequent owners) would ultimately realize over the
vehicle's entire expected lifetime. However, NHTSA establishes CAFE
standards by comparing vehicles' lifetime savings in fuel costs and
other economic benefits from reducing fuel consumption to
manufacturers' costs to improve fuel economy, which leads the agency to
set standards that require much higher levels of fuel economy than it
assumes buyers are willing to pay for. Thus, the agency's analysis does
assume that new car shoppers are somewhat myopic--and that an ``energy
paradox'' exists in the case of fuel economy--but only at the time they
are consider purchasing a new car or light truck, and that they
ultimately value the lifetime fuel savings that purchasing a higher-mpg
model provides.\567\ The agency also assumes that manufacturers'
compliance costs will ultimately be borne by vehicle buyers in the form
of higher purchase prices for new cars and light trucks. This means
that the fraction of savings in future fuel costs buyers are assumed to
take into account at the time of purchase (again, 25-30 percent) when
choosing among models would offset only that same fraction of the
expected increase in new car and light truck prices.
---------------------------------------------------------------------------

    \567\ In addition to myopia, other market failures may also
cause consumers to undervalue fuel savings at the time of purchase
but still fully value the lifetime fuel savings they actually
experience, including information asymmetries, split incentives,
first-mover effects, and others. Moreover, it is appropriate in a
social cost-benefit analysis to fully value the resource savings
that will result from the purchase of vehicles with greater fuel
economy.
---------------------------------------------------------------------------

    NHTSA sought comment on the length of time that should be used for
this ``payback period'' assumption, and asked commenters to specify the
length of time they believed it should span, provide an explanation of
why that period is preferable to the agency's assumption, include
reference to any data or information on which an alternative payback
period is based, and discuss how changing this assumption would
interact with other elements in the analysis. In response, NHTSA
received a handful of comments on this apparent ``energy efficiency
gap'' and the agency's assumption about consumers' willingness to pay.
NADA and Auto Innovators agreed with the agency's assumption of a 30-
month payback period, while stressing the need to account for the
utility of other vehicle attributes that might be improved in the
absence of mandates to provide higher fuel economy.\568\ NADA commented
that consumers are not myopic, and any appearance that they are
actually reflects their wide range of preferences for other vehicle
attributes, which also explains their willingness to forgo some fuel
savings in favor of improvements to vehicles' other features. NADA
asserted that potential buyers of new cars and light trucks focus on
the total lifetime cost of vehicle ownership, and by doing so consider
the cost and value of purchasing models that offer higher levels of not
just fuel economy, but other desirable features as well. To support its
claim, NADA cited to data from the 2021 Strategic Vision New Vehicle
Efficiency Survey that found fuel economy ranked as the 12th most
important attribute to consumers. NADA argued that NHTSA needed to
examine ``actual sales and lease data or studies assessing how new
light-duty vehicle consumers value fuel economy technology when making
purchasing decisions,'' and implored the agency to account for the
``temporal shifting of consumer preferences.'' Auto Innovators
supported analyzing sensitivity cases with payback periods ranging from
1 to 4 years.\569\
---------------------------------------------------------------------------

    \568\ NADA, Docket No. NHTSA-2021-0053-1471, at 8-9.
    \569\ Auto Innovators, at 83-84.
---------------------------------------------------------------------------

    EDF commented that the agency should assume a longer repayment
period and cited as support a Consumer Reports study showing that 64
percent of consumers rank fuel economy as extremely or very important,
and view fuel economy as ``the number one attribute that has room for
improvement.'' \570\ NHTSA notes that the same Consumer Report study
also polled consumers about how quickly fuel savings would have to
offset higher vehicle purchase prices for them to be willing to pay for
increased fuel efficiency. Responses to this question showed that the
average consumer is willing to pay for only 2-3 years of fuel savings,
which aligns well with the agency's estimate of 30 months, and that
only 39 percent of consumers are willing to pay for fuel economy
improvements with a payback period longer than 3 years.\571\
---------------------------------------------------------------------------

    \570\ Environmental Defense Fund, Docket No. NHTSA-2021-0053-
1617, at 5.
    \571\ Consumer Reports, Consumer Attitudes Towards Fuel
Economy'' 2020 Survey Results (Feb. 2021), page 5, https://advocacy.consumerreports.org/wp-content/uploads/2021/02/National-Fuel-Economy-Survey-Report-Feb-2021-FINAL.pdf. (Accessed: March 15,
2022).
---------------------------------------------------------------------------

    CBD et al. commented that the agency is underestimating consumers'
willingness to pay by assuming that they require a 30-month payback
period, but did not explain why it believes this is the case or suggest
an alternative estimate.\572\
---------------------------------------------------------------------------

    \572\ Center for Biological Diversity, Chesapeake Bay
Foundation, Conservation Law Foundation, Earthjustice, Environmental
Law & Policy Center, Natural Resources Defense Council, Public
Citizen, Inc., Sierra Club, and Union of Concerned Scientists
(NHTSA-2021-0053-1572) (CBD et al.), Joint Summary Comments, Docket
No. NHTSA-2021-0053-1572, at 6.
---------------------------------------------------------------------------

    Institute for Policy Integrity at New York School of Law (IPI)
urged the agency consider using different payback assumptions at
different points throughout its analysis. Specifically, IPI commented
that NHTSA should use a lower willingness to pay under the baseline
scenario to determine how much manufacturers would voluntarily improve
fuel economy in the absence of stricter standards, but should assume a
higher willingness to pay when analyzing how the standards will affect
sales of new vehicles and the turnover of the used vehicle fleet.\573\
IPI endorsed the possibility the agency raised in its proposal that
CAFE regulations can ameliorate myopia among potential buyers or
information asymmetries between vehicle manufacturers and buyers, and
by doing so lead potential buyers to value a larger fraction of future
fuel savings from choosing a higher-mpg model. IPI also listed other
potential market failures that CAFE regulations could potentially
mitigate.\574\
---------------------------------------------------------------------------

    \573\ IPI, Docket No. NHTSA-2021-0053-1579-A1, at 16-17.
    \574\ See generally, id., at 9-14.
---------------------------------------------------------------------------

    Specifically, IPI suggested that the agency use a 1.7-year payback
period to identify the technologies manufacturers would adopt and to
estimate the resulting increase in fuel economy under the baseline, but
assume that actual buyers of new cars and light trucks would value fuel
savings over the first 7 years of their lifetimes when evaluating
whether to scrap a vehicle. scrappage rates. However, IPI did not offer
NHTSA a framework for implementing differing payback periods, or
explain whether the difference in payback periods was intended to
reflect manufacturers

underestimation of buyers' valuation of fuel economy and if so, why
manufacturers would do so only under the No-Action Alternative. Nor did
IPI specify how long after new standards were adopted would be required
for consumers to begin to value additional fuel economy, or why they
would revert to their original lower valuation once new standards took
effect and became the baseline for evaluating further increases. IPI
also commented that if the agency opted not to use differing payback
assumptions, then the agency should use a shorter payback period (1.7
years) throughout the analysis to avoid overestimating overcompliance
in the baseline,\575\ and suggested that the agency conduct expert
elicitation to derive a better estimate.\576\
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    \575\ Id.
    \576\ Id. at 15.
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    IPI also commented that NHTSA's theoretical analysis of constrained
consumer choice lacked an empirical test of its validity and that other
explanations for the historical pattern of increases in fuel economy
and changes to vehicles' other attributes may be more plausible than
that offered by the agency. IPI also argued that consumers' choices
involving higher-mpg models cannot be constrained by their budgets
because fuel savings compensate consumers for paying the higher upfront
costs (thus enabling buyers to finance those additional costs). IPI
argued further that failures in the market for auto financing that make
consumers unable to obtain favorable financing to purchase more fuel-
efficient vehicles may constrain consumers' choices more than any
budgetary limits. IPI continued that NHTSA's prior estimates of the
opportunity cost of other vehicle attributes lacked an empirical basis
and ignored potential countervailing effects such as reduced compliance
costs.
    In contrast, NADA commented that a consumer's willingness to
purchase fuel-economy technology must be viewed in the context of
losses in other vehicle attributes like power or safety, and argued
that consumers are not myopic. In support of its position, NADA cited
Leard et al.'s (2021) finding that consumers undervalue fuel economy
but place high values on performance and other attributes,\577\ as well
as Klier and Linn's (2016) finding that tighter vehicle standards
reduce horsepower and torque relative to their levels where standards
remain unchanged.\578\ Finally, IPI cited the conclusion of EPA's
Scientific Advisory Board that it found little ``useful consensus'' on
the subject of the opportunity cost of other vehicle attributes \579\
and Greene (2018), who found extensive variation in willingness-to-pay
estimates across the literature.
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    \577\ Leard, B., J. Linn, and Y. Zhou. 2021. ``How Much Do
Consumers Value Fuel Economy and Performance? Evidence from
Technology Adoption.'' The Review of Economics and Statistics: 1-45
(forthcoming). Adoption, The Review of Economics and Statistics 2021
(Leard, et al.).
    \578\ Klier, Thomas, and Joshua Linn. 2016. ``The Effect of
Vehicle Fuel Economy Standards on Technology Adoption.'' Journal of
Public Economics 133, pp. 41-63).
    \579\ EPA Sci. Advisory Bd., Consideration of the Scientific and
Technical Basis for the EPA's Proposed Rule Titled The Safer
Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-
2026 Passenger Cars and Light Trucks, at 2 (Feb. 27, 2020),
available at https://sab.epa.gov/ords/sab/f?p=100:18:6529621058907:::RP,18:P18_ID:2550 (``We concur with the
agencies that it is not yet feasible to quantify the impact on new
vehicle sales of additional vehicle characteristics (beyond fuel
economy) that are desired by consumers but restrained by federal
standards.''). David Greene et al., Consumer Willingness to Pay for
Vehicle Attributes: What Do We Know?, 118 TRANSP. RES. PART A: POL'Y
& PRAC. 258, 264, 273 (2018); see also id. at 274 (finding that,
even after trimming outliers, ``one standard deviation exceeds the
mean of the [willingness to pay] estimates for most of the
attributes'' and that ``the interquartile range also exceeds the
median'').
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    NHTSA agrees with IPI that the theoretical discussion of
constrained consumer choice under binding fuel economy standards has
not been tested empirically, and for this reason has not incorporated
an estimate of the opportunity cost of sacrifices in other vehicle
attributes in its FRIA. NHTSA notes that the alternative explanations
posited by IPI to explain the fuel efficiency gap also lack an
empirical basis--instead, both the agency's and IPI's explanations are
consistent with consumers' apparent willingness to forgo some fuel
savings in favor of improvements to vehicles' other features. However,
NHTSA notes that, because--as acknowledged later in its comment--IPI's
comment overlooks the theoretical possibility that automakers could at
some point run out of technologies that could improve performance such
that the use of a technology to improve fuel economy rather than
performance would necessarily mean a lack of availability of
performance enhancements. Even if all available technologies were
deployed to improve fuel economy rather than performance, and those
technologies fully paid for themselves with discounted future fuel
savings, then manufacturers would have no remaining technologies
available to meet buyers' demands for improved performance. However, no
such absolute technological constraint has been observed. Furthermore,
the agency notes that IPI's comment lacks any consideration of how much
households can afford to spend on vehicle loan payments, instead
assuming that households will assume as much debt as necessary to
purchase a vehicle with their preferred bundle of attributes. NADA
commented that most households already cannot afford to purchase new
vehicles, and noted that financing does not take into consideration
potential fuel savings but instead relies on a borrower's income,
finance amount, and credit worthiness.\580\
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    \580\ NADA, at 6-7. We note that EPA disagrees and has found
that some lenders give discounts for loans to purchase more fuel-
efficient vehicles. See EPA, Revised 2023 and Later Model Year
Light-Duty Vehicle GHG Emissions Standards: Regulatory Impact
Analysis at 8-27 and n.87 (2021).
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    NHTSA acknowledges that the opportunity cost of regulations on
other vehicle attributes is still an under-researched topic and relies
heavily on economic theory, and for this reason, we are excluding
estimates of this particular theoretical opportunity cost in its
primary analysis. NADA provided some literature that it believes may
assist the agency in developing an estimate of the opportunity cost of
other vehicle attributes in the future, but NHTSA agrees with the EPA's
Scientific Advisory board that there is little consensus on this issue.
For illustrative purposes, NHTSA has included a sensitivity analysis
estimating the theoretical opportunity cost of other vehicle attributes
in the FRIA, although as discussed elsewhere, NHTSA is not confident
that the assumptions used to generate this estimate are sound. NHTSA
notes that the sensitivity analysis of opportunity costs is a rough,
speculative proxy with multiple limitations that does not reflect many
other effects that may largely offset such opportunity costs. The
sensitivity estimate should be considered as an overestimate of the
potential effects, and is not sufficiently robust to include in the
main analysis. Opportunity cost from other vehicle attributes, to the
extent it exists, may be small. NHTSA notes that consideration of such
sensitivity analysis does not change NHTSA's conclusion that
Alternative 2.5 is the maximum feasible and most appropriate standard
under its statutory factors.
    NADA also comments that the agency's assumption that potential
buyers consider their expected future fuel savings over some assumed
``payback period'' when deciding whether to purchase models offering
higher fuel economy oversimplified buyer's choices, even if other
attributes

of models they are comparing are closely comparable.\581\ Specifically,
NADA argues that both the importance vehicle shoppers attach to higher
fuel economy and the time horizon over which they evaluate savings in
fuel costs from buying higher-MPG models vary in response to the
direction and speed of recent movements in fuel prices, and that
potential buyers appear to make the calculations the agency assumes
only when fuel prices are increasing rapidly. When fuel prices are more
stable, NADA argues that consumers appear to focus on vehicles' other
attributes, and at current fuel prices NADA asserts that buyers are
unlikely to demand more fuel-efficient cars and light trucks,
particularly as their preferences continue to evolve toward SUV and CUV
models.
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    \581\ NADA, at 9.
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    On these points, NADA does not offer specific recommendations about
how the agency could represent its interpretation of buyers' choice
process, and the agency's interpretation is that doing so would require
it to vary the assumed duration of buyers' payback period in response
to both the direction and pace of recent changes in fuel prices,
lengthening it when fuel prices are rising rapidly and shortening it
when prices are stable or declining. While the agency does not believe
that this approach is reasonable or practical, it has included
sensitivity cases in the accompanying FRIA that consider both shorter
and longer payback periods than the 2.5 years assumed in the central
analysis, and believes their results should shed useful light on the
potential effects of NADA's recommended approach.
    For several reasons, we decided to retain our 30-month payback
assumption for evaluating the alternatives we considered for the final
rule. First, there was no consensus among commenters about a more
appropriate payback period; approximately equal numbers of commenters
urged the agency to lengthen, maintain, and shorten the duration of its
assumed payback period. Second, none of the commenters who urged the
agency to change the duration of its assumed payback period provided
any additional evidence to support doing so, and thus NHTSA continues
to believe that the information on which the payback decision is based
is reasonable and appropriate. Finally, none provided plausible
explanations for why adopting fuel economy standards should change
vehicle buyers' time perspectives on future fuel savings, why their
longer-term perspectives would revert to their original shorter terms
once those standards took effect, or why repeat buyers' values would
once again adopt a longer-term perspective when valuing future fuel
savings when standards were once again raised.
    While we will continue to explore whether payback periods should
differ between the baseline and regulatory alternatives that would
establish higher standards, the agency still lacks a clear basis for
identifying whether, how much, or how quickly future changes in CAFE
standards could alter consumer perceptions of fuel economy and its
value. In addition, neither the agency nor commenters has identified a
satisfactory explanation for why once having adapted to the presence of
higher fuel economy standards by lengthening the time horizon over
which they value fuel savings, consumers would revert to their former
lower values once those new standards became the reference point for
evaluating further increases in required fuel economy. The agency will
also re-examine whether a 30-month payback period is appropriate to use
in analyzing future increases in standards, and will consider whether
an expert elicitation is appropriate.
2. Fleet Composition
    The composition of the on-road fleet--and how it changes in
response to CAFE standards--determines many of the costs and benefits
of the final standards. For example, how much fuel the light-duty fleet
consumes is dependent on the number of new vehicles sold, how many
older (and less efficient) vehicles are retired, and how much vehicles
are driven.
    Until recently, all previous CAFE rulemaking analyses used static
fleet forecasts that were based on a combination of manufacturer
compliance data, public data sources, and proprietary forecasts (or
product plans submitted by manufacturers). When simulating compliance
with regulatory alternatives, those analyses projected identical sales
and retirements across the alternatives, for each manufacturer down to
the make/model level--where the exact same number of each model variant
was assumed to be sold in a given model year under both the least
stringent alternative (typically the baseline) and the most stringent
alternative considered (intended to represent ``maximum technology''
scenarios in some cases). To the extent that an alternative matched the
assumptions made in the production of the proprietary forecast, using a
static fleet based upon those assumptions may have been warranted.
    However, a fleet forecast is unlikely to be representative of a
broad set of regulatory alternatives with significant variation in the
cost of new vehicles. Several commenters on previous regulatory actions
and peer reviewers of the CAFE Model encouraged consideration of the
potential impact of fuel efficiency standards on new vehicle prices and
sales, the changes to compliance strategies that those shifts could
necessitate, and the downstream impact on vehicle retirement rates. In
particular, the continued growth of the utility vehicle segment causes
changes within some manufacturers' fleets as sales volumes shift from
one region of the footprint curve to another, or as mass is added to
increase the ride height of a vehicle on a sedan platform to create a
crossover utility vehicle, which exists on the same place of the
footprint curve as the sedan upon which it might be based.
    The analysis now dynamically simulates changes in the vehicle
fleet's size, composition, and usage as manufacturers and consumers
respond to regulatory alternatives, fuel prices, and macroeconomic
conditions. The analysis of fleet composition comprises two forces, how
new vehicle sales--the flow of new vehicles into the registered
population--change in response to regulatory alternatives, and the
influence of economic and regulatory factors on vehicle retirement
(otherwise known as scrappage).
    While commenters raised specific objections to several of the
assumptions within the sales and scrappage modules--which are described
below--commenters generally were supportive of the agency's approach to
modeling fleet turnover. We did receive one comment from IPI suggesting
that we should consider returning to a static fleet model if we were
unable to correct what they perceived as modeling flaws. We disagree
with IPI's assessment, because it is widely acknowledged that CAFE
standards and other regulations on new vehicles can influence
consumers' decisions about both purchasing new vehicles and retiring
used ones, so to assume that the composition of the vehicle fleet is
unaffected by regulations would ignore these well documented impacts.
The agency feels that it is important to provide policymakers with the
most comprehensive and complete analysis of the regulations, which
includes understanding how CAFE standards will affect fleet turnover.
    Below are brief descriptions that of how the agency models sales
and scrappage. For a full explanation, refer to TSD Chapter 4.2.

(a) Sales
    For the purposes of regulatory evaluation, the relevant sales
metric is the difference in sales between alternatives rather than the
absolute number of sales in any of the alternatives. As such, the sales
response model currently contains three parts: A nominal forecast that
provides the level of sales in the baseline (based upon macroeconomic
inputs, exclusively), a price elasticity that creates sales differences
relative to that baseline in each year, and a fleet share model that
produces differences in the passenger car and light truck market share
in each alternative. The nominal forecast does not include price and is
merely a (continuous) function of several macroeconomic variables that
are provided to the model as inputs. The price elasticity is also
specified as an input. In the proposal, the agency assumed a price
elasticity of sales of -1.0 and sought comment on this assumption.
    Many commenters argued that NHTSA's unit elastic response
assumption of -1.0 is inaccurate. The California Attorney General et
al., IPI, ICCT, UCS, CBD et al., CARB and Dr. Kenneth Gillingham, all
commented that -1.0 is too large and unsupported by the evidence.\582\
CBD et al. and the California Attorney General noted that recent
literature suggests a much lower figure, with California's Attorney
General suggesting using the estimate from Leard (2021) of -0.34 and
the CBD et al. suggesting between -0.2 or -0.4 (or lower). IPI
suggested reducing the figure to at least -0.4, the figure used by EPA
in a recent sensitivity analysis. ICCT suggested that NHTSA use -0.5,
and further recommended that NHTSA consider using different elasticity
estimates for different vehicle classes.
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    \582\ California Attorney General et al., Docket No. NHTSA-2021-
0053-1499, Appendix A, at 32; IPI, A1, at 26-28; ICCT, Docket No.