their impacts on other system users, just as they do not fully value
the emissions impacts of their own driving. Congestion and noise costs
are ``external'' to the vehicle owners whose decisions about how much,
where, and when to drive more--or less--in response to changes in fuel
economy result in these costs. Therefore, unlike changes in the costs
incurred by drivers for fuel consumption or safety risks they willingly
assume, changes in congestion and noise costs are not offset by
corresponding changes in the travel benefits drivers experience.
    Congestion costs are limited to road users; however, since road
users include a significant fraction of the U.S. population, changes in
congestion costs are treated as part of the rule's economic impact on
the broader society instead of as a cost or benefit to private parties.
Costs resulting from road and highway noise are even more widely
dispersed, because they are borne partly by surrounding residents,
pedestrians, and other non-road users, and for this reason are also
considered as a cost to the society as a whole.
    To estimate the economic costs associated with changes in
congestion and noise caused by differences in miles driven, the agency
updated the underlying components of the cost estimates of per-mile
congestion and noise costs from increased automobile and light truck
use provided in FHWA's 1997 Highway Cost Allocation Study. The agencies
previously relied on this study in the 2010, 2011, and 2012 final
rules, and updating the individual underlying components for congestion

costs in this analysis improves currency and internal consistency with
the rest of the analysis. See TSD Chapter 6.2 for details on how the
agency calculated estimate the economic costs associated with changes
in congestion and noise caused by differences in miles driven. NHTSA
specifically seeks comment on the congestion costs employed in this
analysis, and whether and how to change them for the analysis for the
final rule.
(2) Fuel Tax Revenue
    As mentioned in III.G.1.b)(1), a portion of the fuel savings
experienced by consumers includes avoided fuel taxes. While fuel taxes
are treated as a transfer within the analysis and do not affect net
benefits, the agency provides an estimate here to show the potential
impact to state and local governments.
(b) Benefits
(1) Reduced Climate Damages
    Extracting and transporting crude petroleum, refining it to produce
transportation fuels, and distributing fuel generate additional
emissions of GHGs and criteria air pollutants beyond those from cars'
and light trucks' use of fuel. By reducing the volume of petroleum-
based fuel produced and consumed, adopting higher CAFE standards will
thus mitigate global climate-related economic damages caused by
accumulation of GHGs in the atmosphere, as well as the more immediate
and localized health damages caused by exposure to criteria pollutants.
Because they fall broadly on the U.S.--and global, in the case of
climate damages--population, reducing them represents an external
benefit from requiring higher fuel economy.
    NHTSA estimates the global social benefits of CO2,
CH4, and N2O emission reductions expected from
this proposed rule using the social cost of greenhouse gases (SC-GHG)
estimates presented in the Technical Support Document: Social Cost of
Carbon, Methane, and Nitrous Oxide Interim Estimates under Executive
Order 13990 (``February 2021 TSD''). These SC-GHG estimates are interim
values developed under Executive Order (E.O.) 13990 for use in benefit-
cost analyses until updated estimates of the impacts of climate change
can be developed based on the best available science and economics.
NHTSA uses the SC-GHG interim values to estimate the benefits of
decreased fuel consumption stemming from the proposal.
    The SC-GHG estimates used in our analysis were developed over many
years, using transparent process, peer-reviewed methodologies, the best
science available at the time of that process, and with input from the
public. Specifically, in 2009, an interagency working group (IWG) that
included the DOT and other executive branch agencies and offices was
established to ensure that agencies were using the best available
science and to promote consistency in the social cost of carbon dioxide
(SC-CO2) values used across agencies. The IWG published SC-
CO2 estimates in 2010. These estimates were updated in 2013
based on new versions of each IAM. In August 2016 the IWG published
estimates of the social cost of methane (SC-CH4) and nitrous
oxide (SC-N2O) using methodologies that are consistent with
the methodology underlying the SC-CO2 estimates. Executive
Order 13990 (issued on January 20, 2021) re-established the IWG and
directed it to publish interim SC-GHG values for CO2,
CH4, and N2O within thirty days. Furthermore, the
E.O. tasked the IWG with devising long-term recommendations to update
the methodologies used in calculating these SC-GHG values, based on
``the best available economics and science,'' and incorporating
principles of ``climate risk, environmental justice, and
intergenerational equity''.\347\ The E.O. also instructed the IWG to
take into account the recommendations from the NAS committee convened
on this topic, published in 2017.\348\ The February 2021 TSD provides a
complete discussion of the IWG's initial review conducted under E.O.
13990.
---------------------------------------------------------------------------

    \347\ Executive Order on Protecting Public Health and the
Environment and Restoring Science to Tackle the Climate Crisis.
(2021). Available at https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/20/executive-order-protecting-public-health-and-environment-and-restoring-science-to-tackle-climate-crisis/.
    \348\ National Academies of Science (NAS). (2017). Valuing
Climate Damage: Updating Estimation of the Social Cost of Carbon
Dioxide. Available at https://www.nap.edu/catalog/24651/valuing-climate-damages-updating-estimation-of-the-social-cost-of.
---------------------------------------------------------------------------

    NHTSA is using the IWG's interim values, published in February 2021
in a technical support document, for the CAFE analysis in this
NPRM.\349\ This approach is the same as that taken in DOT regulatory
analyses over 2009 through 2016. If the IWG issues new estimates before
the final rule, the agency will consider revising the estimates within
the CAFE Model time permitting. We request comment on this approach to
estimating social benefits of reducing GHG emissions in this rulemaking
in light of the ongoing interagency process.
---------------------------------------------------------------------------

    \349\ Interagency Working Group on Social Cost of Greenhouse
Gases, United States Government. (2021). Technical Support Document:
Social Cost of Carbon, Methane, and Nitrous Oxide Interim Estimates
under Executive Order 13990, available at https://www.whitehouse.gov/wp-content/uploads/2021/02/TechnicalSupportDocument_SocialCostofCarbonMethaneNitrousOxide.pdf?source=email.
---------------------------------------------------------------------------

    NHTSA notes that the primary analysis for this proposal estimates
benefits from reducing emissions of CO2 and other GHGs that
incorporate a 2.5% discount rate for distant future climate damages,
while discounting costs and non-climate related benefits using a 3%
rate. NHTSA also presents cost and benefits estimates in the primary
analysis that reflect a 3% discount rate for reductions in climate-
related damages while discounting costs and non-climate related
benefits at 7%. NHTSA believes this approach represents an appropriate
treatment of the intergenerational issues presented by emissions that
result in climate-related damages over a very-long time horizon, and is
within scope of the IWG's Technical Support Document: Social Cost of
Carbon, Methane, and Nitrous Oxide that recommends discounting future
climate damages at rates of 2.5%, 3%, and 5%.\350\
---------------------------------------------------------------------------

    \350\ Interagency Working Group on Social Cost of Greenhouse
Gases, United States Government, Technical Support Document: Social
Cost of Carbon, Methane, and Nitrous Oxide, Interim Estimates under
Executive Order 13990, February 2021.
---------------------------------------------------------------------------

    In addition, NHTSA emphasize the importance and value of
considering the benefits calculated using all four SC-GHG estimates for
each of three greenhouse gases. NHTSA includes the social costs of
CO2, CH4, and N2O calculated using the
four different estimates recommended in the February 2021 TSD (model
average at 2.5 percent, 3 percent, and 5 percent discount rates; 95th
percentile at 3 percent discount rate) in the PRIA.
    The February 2021 TSD does not specify how agencies should combine
its estimates of benefits from reducing GHG emissions that reflect
these alternative discount rates with the discount rates for nearer-
term benefits and costs prescribed in OMB Circular A-4. Instead, it
provides agencies with broad flexibility in implementing the February
2021 TSD. However, the February 2021 TSD does identify 2.5% as the
``average certainty-equivalent rate using the mean-reverting and random
walk approaches from Newell and Pizer (2003) starting at a discount
rate of 3 percent.'' \351\ As such, NHTSA believes using a 2.5%
discount rate for climate-related damages is consistent with the IWG
guidance.
---------------------------------------------------------------------------

    \351\ Ibid.
---------------------------------------------------------------------------

    This section provides further discussion of the discount rates that
NHTSA uses in its regulatory analysis

and presents results of a sensitivity analysis using a 3% discount rate
for reductions in climate-related damages. NHTSA welcomes public
comment on its selection of 2.5% for climate-related damages and will
consider other discount rates for the final rule.
    For a full discussion of the agency's quantification of GHGs, see
TSD Chapter 6.2.1 and the PRIA.
(a) Discount Rates Accounting for Intergenerational Impacts
    A standard function of regulatory analysis is to evaluate tradeoffs
between impacts that occur at different points in time. Many, if not
most, Federal regulations involve costly upfront investments that
generate future benefits in the form of reductions in health, safety,
or environmental damages. To evaluate these tradeoffs, the analysis
must account for the social rate of time preference--the broadly
observed social preference for benefits that occur sooner versus those
that occur further in the future.\352\ This is accomplished by
discounting impacts that occur further in the future more than impacts
that occur sooner.
---------------------------------------------------------------------------

    \352\ This preference is observed in many market transactions,
including by savers that expect a return on their investments in
stocks, bonds, and other equities; firms that expect positive rates
of return on major capital investments; and banks that demand
positive interest rates in lending markets.
---------------------------------------------------------------------------

    OMB Circular A-4 affirmed the appropriateness of accounting for the
social rate of time preference in regulatory analyses and prescribed
discount rates of 3% and 7% for doing so. The 3% discount rate was
chosen to represent the ``consumption rate of interest'' approach,
which discounts future costs and benefits to their present values using
the rate at which consumers appear to make tradeoffs between current
consumption and equal consumption opportunities deferred to the future.
OMB Circular A-4 reports a real rate of return on 10-year Treasury
notes of 3.1% between 1973 and its 2003 publication date and interprets
this as approximating the rate at which society is indifferent between
consumption today and in the future.
    The 7% rate reflects the opportunity cost of capital approach to
discounting, where the discount rate approximates the foregone return
on private investment if the regulation were to divert resources from
capital formation. OMB Circular A-4 cites pre-tax rates of return on
capital as part of its selection of the 7% rate.\353\ The IWG rejected
the use of the opportunity cost of capital approach to discounting
reductions in climate-related damages because ``consumption rate of
interest is the correct discounting concept to use when future damages
from elevated temperatures are estimated in consumption-equivalent
units as is done in the IAMs used to estimate the SC-GHG (National
Academies 2017).'' \354\
---------------------------------------------------------------------------

    \353\ OMB Circular A-4.
    \354\ Interagency Working Group on Social Cost of Greenhouse
Gases, United States Government, Technical Support Document: Social
Cost of Carbon, Methane, and Nitrous Oxide, Interim Estimates under
Executive Order 13990, February 2021.
---------------------------------------------------------------------------

    As the IWG states, ``GHG emissions are stock pollutants, where
damages are associated with what has accumulated in the atmosphere over
time, and they are long lived such that subsequent damages resulting
from emissions today occur over many decades or centuries depending on
the specific greenhouse gas under consideration.''\355\ OMB Circular A-
4 states that impacts occurring over such intergenerational time
horizons require special treatment:
---------------------------------------------------------------------------

    \355\ Ibid.

    Special ethical considerations arise when comparing benefits and
costs across generations. Although most people demonstrate time
preference in their own consumption behavior, it may not be
appropriate for society to demonstrate a similar preference when
deciding between the well-being of current and future generations.
Future citizens who are affected by such choices cannot take part in
making them, and today's society must act with some consideration of
their interest.\356\
---------------------------------------------------------------------------

    \356\ OMB Circular A-4.

    In addition to the ethical considerations, Circular A-4 also
identifies uncertainty in long-run interest rates as a potential
justification for using lower rates to discount intergenerational
impacts. As Circular A-4 states, ``Private market rates provide a
reliable reference for determining how society values time within a
generation, but for extremely long time periods no comparable private
rates exist.''\357\ The social costs of distant future climate
damages--and by implication, the value of reducing them by lowering
emissions of GHGs--are highly sensitive to the discount rate, and the
present value of reducing climate damages grows at an increasing rate
as the discount rate used in the analysis declines. This ``non-
linearity'' means that even if uncertainty about the exact value of the
long-run interest rate is equally distributed between values above and
below the 3% consumption rate of interest, the probability-weighted (or
``expected'') present value of a unit reduction in climate damages will
be higher than the value calculated using a 3% discount rate. The
effect of such uncertainty about the correct discount rate can thus be
accounted for by using a lower ``certainty-equivalent'' rate to
discount distant future damages.
---------------------------------------------------------------------------

    \357\ Ibid.
---------------------------------------------------------------------------

    The IWG identifies ``a plausible range of certainty-equivalent
constant consumption discount rates: 2.5, 3, and 5 percent per year.''
The IWG's justification for its selection of these rates is summarized
in this excerpt from its 2021 guidance:
    The 3 percent value was included as consistent with estimates
provided in OMB's Circular A-4 (OMB 2003) guidance for the consumption
rate of interest. . . .The upper value of 5 percent was included to
represent the possibility that climate-related damages are positively
correlated with market returns, which would imply a certainty
equivalent value higher than the consumption rate of interest. The low
value, 2.5 percent, was included to incorporate the concern that
interest rates are highly uncertain over time. It represents the
average certainty-equivalent rate using the mean-reverting and random
walk approaches from Newell and Pizer (2003) starting at a discount
rate of 3 percent. Using this approach, the certainty equivalent is
about 2.2 percent using the random walk model and 2.8 percent using the
mean reverting approach. Without giving preference to a particular
model, the average of the two rates is 2.5 percent. Additionally, a
rate below the consumption rate of interest would also be justified if
the return to investments in climate mitigation are negatively
correlated with the overall market rate of return. Use of this lower
value was also deemed responsive to certain judgments based on the
prescriptive or normative approach for selecting a discount rate and to
related ethical objections that have been raised about rates of 3
percent or higher.
    Because the certainty-equivalent discount rate will lie
progressively farther below the best estimate of the current rate as
the time horizon when future impacts occur is extended, the IWG's
recent guidance also suggest that it may be appropriate to use a
discount rate that declines over time to account for interest rate
uncertainty, as has been recommended by the National Academies and
EPA's Science Advisory Board.\358\ The IWG mentioned that it will
consider these recommendations and the relevant academic literature on
declining rates in developing its final

guidance on the social cost of greenhouse gases.
---------------------------------------------------------------------------

    \358\ Interagency Working Group on Social Cost of Greenhouse
Gases, United States Government, Technical Support Document: Social
Cost of Carbon, Methane, and Nitrous Oxide, Interim Estimates under
Executive Order 13990, February 2021.
---------------------------------------------------------------------------

    The IWG 2021 interim guidance also presented new evidence on the
consumption-based discount rate suggesting that a rate lower than 3%
may be appropriate. For example, the IWG replicated OMB Circular A-4's
original 2003 methodology for estimating the consumption rate using the
average return on 10-year Treasury notes over the last 30 years and
found a discount rate close to 2%. They also presented rates over a
longer time horizon, finding an average rate of 2.3% from 1962 to the
present. Finally, they summarized results from surveys of experts on
the topic and found a ``surprising degree of consensus'' for using a 2%
consumption rate of interest to discount future climate-related
impacts.\359\
---------------------------------------------------------------------------

    \359\ Ibid.
---------------------------------------------------------------------------

    NHTSA expects that the Interagency Working Group will continue to
develop its final guidance on the appropriate discount rates to use for
reductions in climate damages as NHTSA develops its final rule. If new
guidance is issued in time for NHTSA's final rule, NHTSA will
incorporate the IWG's updated guidance in the final regulatory
analysis.
(b) Discount Rates Used in This Proposal for Climate-Related Benefits
    As indicated above, NHTSA's primary analysis presents cost and
benefit estimates using a 2.5% discount rate for reductions in climate-
related damages and 3% for non-climate related impacts. NHTSA also
presents cost and benefits estimates using a 3% discount rate for
reductions in climate-related damages alongside estimates of non-
climate related impacts discounted at 7%. This latter pairing of a 3%
rate for discounting benefits from reducing climate-related damages
with a 7% discount rate for non-climate related impacts is consistent
with NHTSA's past practice.\360\ However, NHTSA's pairing of 2.5% for
climate-related damage reductions with 3% for non-climate related
impacts is novel in this proposal.
---------------------------------------------------------------------------

    \360\ See, e.g., the 2012 and 2020 final CAFE rules.
---------------------------------------------------------------------------

    As discussed above, the IWG's guidance indicates that uncertainty
in long-run interest rates suggests that a lower ``certainty-
equivalent'' discount rate is appropriate for intergenerational
impacts, and identifies 2.5%, 3%, and 5% as ``certainty-equivalent''
discount rates. NHTSA emphasizes the importance and value of
considering the benefits calculated using all four SC-GHG estimates for
each of three greenhouse gases. NHTSA includes the social costs of
CO2, CH4, and N2O calculated using the
four different estimates recommended in the February 2021 TSD (model
average at 2.5 percent, 3 percent, and 5 percent discount rates; 95th
percentile at 3 percent discount rate) in the PRIA. For presentation
purposes in this rule, NHTSA shows two primary estimates. NHTSA
believes that pairing OMB's 3% estimate of the consumption discount
rate for near-term costs and benefits with the IWG's lower certainty-
equivalent rate of 2.5% is consistent with current interim guidance in
the February 2021 TSD. NHTSA also believe that its pairing of the 3%
certainty-equivalent rate for climate-related benefits with OMB's 7%
discount rate is consistent with guidance from the February 2021 TSD
for GHGs and OMB Circular A-4 for other costs and benefits.
    In addition, NHTSA presents a sensitivity analysis where both
distant future and nearer-term GHG impacts are discounted using the 3%
rate combined with all other costs and benefits discounted at 3%.
[GRAPHIC] [TIFF OMITTED] TP03SE21.095

[GRAPHIC] [TIFF OMITTED] TP03SE21.096

NHTSA seeks comment on the above discussion.
(2) Reduced Health Damages
    The CAFE Model estimates monetized health effects associated with
emissions from three criteria pollutants: NOX,
SOx, and PM2.5. As discussed in Section III.F
above, although other criteria pollutants are currently regulated, only
impacts from these three pollutants are calculated since they are known
to be emitted regularly from mobile sources, have the most adverse
effects to human health, and there exist several papers from the EPA
estimating the benefits per ton of reducing these pollutants. Other
pollutants, especially those that are precursors to ozone, are more
difficult to model due to the complexity of their formation in the
atmosphere, and EPA does not calculate benefit-per-ton estimates for
these. The CAFE Model computes the monetized impacts associated with
health damages from each pollutant by multiplying monetized health
impact per ton values by the total tons of these pollutants, which are
emitted from both upstream and tailpipe sources. Chapter 5 of the TSD
accompanying this proposal includes a detailed description of the
emission factors that inform the CAFE Model's calculation of the total
tons of each pollutant associated with upstream and tailpipe emissions.
    These monetized health impacts per ton values are closely related
to the health incidence per ton values described above in Section III.F
and in detail in Chapter 5.4 of the TSD. We use the same EPA sources
that provided health incidence values to determine which monetized
health impacts per ton values to use as inputs in the CAFE Model. Like
the estimates associated with health incidences per ton of criteria
pollutant emissions, we used multiple EPA papers and conversations with
EPA staff to appropriately account for monetized damages for each
pollutant associated with the source sectors included in the CAFE
Model, based on which papers contained the most up-to-date data.\361\
The various emission source sectors included in the EPA papers do not
always correspond exactly to the emission source categories used in the
CAFE Model.\362\ In those cases, we mapped multiple EPA sectors to a
single CAFE source category and computed a weighted average of the
health impact per ton values.
---------------------------------------------------------------------------

    \361\ Environmental Protection Agency (EPA). 2018. Estimating
the Benefit per Ton of Reducing PM2.5 Precursors from 17
Sectors. https://www.epa.gov/sites/production/files/2018-02/documents/sourceapportionmentbpttsd_2018.pdf; Wolfe et al. 2019.
Monetized health benefits attributable to mobile source emissions
reductions across the United States in 2025. https://pubmed.ncbi.nlm.nih.gov/30296769/; Fann et al. 2018. Assessing Human
Health PM2.5 and Ozone Impacts from U.S. Oil and Natural
Gas Sector Emissions in 2025. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6718951/.
    \362\ The CAFE Model's emission source sectors follow a similar
structure to the inputs from GREET. See Chapter 5.2 of the TSD
accompanying this proposal for further information.
---------------------------------------------------------------------------

    The EPA uses the value of a statistical life (VSL) to estimate
premature mortality impacts, and a combination of willingness to pay
estimates and costs of treating the health impact for estimating the
morbidity impacts.\363\ EPA's 2018 technical support document,
``Estimating the Benefit per Ton of Reducing PM2.5
Precursors from 17 Sectors,'' \364\ (referred to here as the 2018 EPA
source apportionment TSD) contains a more detailed account of how
health incidences are monetized. It is important to note that the EPA
sources cited frequently refer to these monetized health impacts per
ton as ``benefits per ton,'' since they describe these estimates in
terms of emissions avoided. In the CAFE Model input structure, these
are generally referred to as monetized health impacts or damage costs
associated with pollutants emitted, not avoided, unless the context
states otherwise.
---------------------------------------------------------------------------

    \363\ Although EPA and DOT's VSL values differ, DOT staff
determined that using EPA's VSL was appropriate here, since it was
already included in these monetized health impact values, which were
best suited for the purposes of the CAFE Model.
    \364\ See Environmental Protection Agency (EPA). 2018.
Estimating the Benefit per Ton of Reducing PM2.5
Precursors from 17 Sectors. https://www.epa.gov/sites/production/files/2018-02/documents/sourceapportionmentbpttsd_2018.pdf.
---------------------------------------------------------------------------

    The CAFE Model health impacts inputs are based partially on the
structure the 2018 EPA source apportionment TSD, which reported
benefits per ton values for the years 2020, 2025, and 2030. For the
years in between the source years used in the input structure, the CAFE
Model applies values from the closest source year. For instance, the
model applies 2020 monetized health impact per ton values for calendar
years 2020-2022 and applies 2025 values for calendar years 2023-2027.
For some of the monetized health damage values, in order to match the
structure of other impacts costs, DOT staff developed proxies for 7%
discounted values for specific source sectors by using the ratio
between a comparable sector's 3% and 7% discounted values. In addition,
we used implicit price deflators from the Bureau of Economic Analysis
(BEA) to convert different monetized estimates to 2018 dollars, in
order to be consistent with the rest of the CAFE Model inputs.
    This process is described in more detail in Chapter 6.2.2 of the
TSD accompanying this proposal. In addition, the CAFE Model
documentation contains more details of the model's computation of
monetized health impacts. All resulting emissions damage costs for
criteria pollutants are located in the Criteria Emissions Cost
worksheet of the Parameters file.
(3) Reduction in Petroleum Market Externality
    By amending existing standards, the proposal would decrease
domestic consumption of gasoline, producing a correspondingly decrease
in the Nation's demand for crude petroleum, a commodity that is traded
actively in a worldwide market. Although the U.S. accounts for a
sufficient (albeit diminishing) share of global oil consumption that
the resulting decrease in global petroleum demand will exert some
downward pressure on worldwide prices.
    U.S. consumption and imports of petroleum products have three
potential effects on the domestic economy that are often referred to
collectively as ``energy security externalities,'' and increases in
their magnitude are sometimes cited as possible social costs of
increased U.S. demand for petroleum. First, any increase in global
petroleum prices that results from higher U.S. gasoline demand will
cause a transfer of revenue to oil producers worldwide from consumers
of petroleum, because consumers throughout the world are ultimately
subject to the higher global price that results. Although this transfer
is simply a shift of resources that produces no change in global
economic welfare, the financial drain it produces on the U.S. economy
is sometimes cited as an external cost of increased U.S. petroleum
consumption because consumers of petroleum products are unlikely to
consider it.
    As the U.S. approaches self-sufficiency in petroleum production
(the Nation became a net exporter of petroleum in 2020), this transfer
is increasingly from U.S. consumers of refined petroleum products to
U.S. petroleum producers, so it not only leaves welfare unaffected, but
even ceases to be a financial burden on the U.S. economy. In fact, as
the U.S. becomes a larger net petroleum exporter, any transfer from
global consumers to petroleum producers would become a financial
benefit to the U.S. economy. Nevertheless, uncertainty in the Nation's
long-term import-export balance makes it difficult to project precisely
how these effects might

change in response to increased consumption.
    Higher U.S. petroleum consumption can also increase domestic
consumers' exposure to oil price shocks and thus increase potential
costs to all U.S. petroleum users (including those outside the light
duty vehicle sector, whose consumption would be unaffected by this
proposed rule) from possible interruptions in the global supply of
petroleum or rapid increases in global oil prices. Because users of
petroleum products are unlikely to consider the effect of their
increased purchases on these risks, their economic value is often cited
as an external cost of increased U.S. consumption.
    Finally, some analysts argue that domestic demand for imported
petroleum may also influence U.S. military spending; because the
increased cost of military activities would not be reflected in the
price paid at the gas pump, this is often suggested to represent a
third category of external costs form increased U.S. petroleum
consumption. For example, NHTSA has received extensive comments to past
actions from the group Securing America's Energy Future on this topic.
    Each of these three factors would be expected to decrease--albeit
by a limited magnitude--as a consequence of decrease in U.S. petroleum
consumption resulting from the proposed standards. TSD Chapter 6.2.4
provides a comprehensive explanation of the agency's analysis of these
three impacts.
(4) Changes in Labor
    As vehicle prices rise, we expect consumers to purchase fewer
vehicles than they would have at lower prices. If manufacturers produce
fewer vehicles as a consequence of lower demand, manufacturers may need
less labor to produce their fleet and dealers may need less labor to
sell the vehicles. Conversely, as manufacturers add equipment to each
new vehicle, the industry will require labor resources to develop,
sell, and produce additional fuel-saving technologies.\365\ We also
account for the possibility that new standards could shift the relative
shares of passenger cars and light trucks in the overall fleet. Since
the production of different vehicles involves different amounts of
labor, this shift impacts the quantity of estimated labor.
---------------------------------------------------------------------------

    \365\ For the purposes of this analysis, DOT assumes a linear
relationship between labor and production volumes.
---------------------------------------------------------------------------

    The analysis considers the direct labor effects that the CAFE
standards have across the automotive sector. The facets include (1)
dealership labor related to new light-duty vehicle unit sales; (2)
assembly labor for vehicles, engines, and transmissions related to new
vehicle unit sales; and (3) labor related to mandated additional fuel
savings technologies, accounting for new vehicle unit sales. The labor
utilization analysis is intentionally narrow in its focus and does not
represent an attempt to quantify the overall labor or economic effects
of this rulemaking because adjacent employment factors and consumer
spending factors for other goods and services are uncertain and
difficult to predict. We do not consider how direct labor changes may
affect the macro economy and potentially change employment in adjacent
industries. For instance, we do not consider possible labor changes in
vehicle maintenance and repair, nor changes in labor at retail gas
stations. We also do not consider possible labor changes due to raw
material production, such as production of aluminum, steel, copper, and
lithium, nor does the agency consider possible labor impacts due to
changes in production of oil and gas, ethanol, and electricity.
    All labor effects are estimated and reported at a national level,
in person-years, assuming 2,000 hours of labor per person-year.\366\
These labor hours are not converted into monetized values because we
assume that the labor costs are included into a new vehicle's
purchasing price. The analysis estimates labor effects from the
forecasted CAFE Model technology costs and from review of automotive
labor for the MY 2020 fleet. The agency uses information about the
locations of vehicle assembly, engine assembly, and transmission
assembly, and the percent of U.S. content of vehicles collected from
American Automotive Labeling Act (AALA) submissions for each vehicle in
the reference fleet.\367\ The analysis assumes the portion of parts
that are made in the U.S. will remain constant for each vehicle as
manufacturers add fuel-savings technologies. This should not be
misconstrued as a prediction that the percentage of U.S.-made parts--
and by extension U.S. labor--will remain constant, but rather that the
agency does not have a clear basis to project where future productions
may shift. The analysis also uses data from the National Automotive
Dealers Association (NADA) annual report to derive dealership labor
estimates.
---------------------------------------------------------------------------

    \366\ The agencies recognize a few local production facilities
may contribute meaningfully to local economies, but the analysis
reports only on national effects.
    \367\ 49 CFR part 583.
---------------------------------------------------------------------------

    In sum, the analysis shows that the increased labor from production
of new technologies used to meet the preferred alternative will
outweigh any decreases attributable to the change in new vehicle sales.
For a full description of the process the agency uses to estimate labor
impacts, see TSD Chapter 6.2.5.
3. Costs and Benefits Not Quantified
    In addition to the costs and benefits described above, Table III-37
and Table III-38 each include two line-items without values. The first
is maintenance and repair costs. Many of the technologies manufacturers
apply to vehicles to meet CAFE standards are sophisticated and costly.
The technology costs capture only the initial or ``upfront'' costs to
incorporate this equipment into new vehicles; however, if the equipment
is costlier to maintain or repair--which is likely either because the
materials used to produce the equipment are more expensive or the
equipment is significantly more complex than less fuel efficient
alternatives and requires more time and labor--then consumers will also
experience increased costs throughout the lifetime of the vehicle to
keep it operational. The agency does not calculate the additional cost
of repair and maintenance currently because it lacks a basis for
estimating the incremental change attributable to the standards. The
agency seeks comment on methods for estimating these costs.
    The second item is the potential sacrifice in other vehicle
attributes. In addition to fuel economy, potential buyers of new cars
and light trucks value other features such as their seating and cargo-
carrying capacity, ride comfort, safety, and performance. Changing some
of these other features, however, can affect vehicles' fuel economy, so
manufacturers will carefully consider tradeoffs among them when
deciding how to comply with stricter CAFE standards. Currently the
analysis assumes that these vehicle attributes will not change as a
result of these rules,\368\ but in practice manufacturers may need to
make practical design changes to meet the standards. Even if
manufacturers are able to hold vehicles' other attributes at today's
levels while meeting higher fuel economy targets, manufacturers may
have to dedicate additional resources to comply with stricter CAFE
targets and forego improvements in other vehicle attributes. The
potential loss of other

vehicle attributes is an opportunity cost to consumers.
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    \368\ See TSD Chapter 2.4.5.
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    The agency has previously attempted to model the potential
sacrifice in other vehicle attributes in sensitivity analyses. In those
other rulemakings, the agency acknowledged that it is extremely
difficult to quantify the potential loss of other vehicle attributes.
To accurately do so requires extensive projections about which and how
much of other attributes will be sacrificed and a detailed accounting
of how much value consumers assigned to those attributes. The agency
modeled the loss in other vehicle attributes using published empirical
estimates of tradeoffs between higher fuel economy and improvements to
other attributes, together with estimates of the values buyers attach
to those attributes. The agency is unsure whether this is an
appropriate methodology since there is uncertainty about how much fuel
economy consumers are willing to pay for and how consumers value other
vehicle attributes. The agency seeks comment on alternative methods for
estimating the potential sacrifice in other vehicle attributes.

H. Simulating Safety Effects of Regulatory Alternatives

    The primary objective of CAFE standards is to achieve maximum
feasible fuel economy, thereby reducing fuel consumption. In setting
standards to achieve this intended effect, the potential of the
standards to affect vehicle safety is also considered. As a safety
agency, the agency has long considered the potential for adverse safety
consequences when establishing CAFE standards.
    This safety analysis includes the comprehensive measure of safety
impacts from three factors:
    1. Changes in Vehicle Mass. Similar to previous analyses, the
agency calculates the safety impact of changes in vehicle mass made to
reduce fuel consumption and comply with the standards. Statistical
analysis of historical crash data indicates reducing mass in heavier
vehicles generally improves safety, while reducing mass in lighter
vehicles generally reduces safety. The agency's crash simulation
modeling of vehicle design concepts for reducing mass revealed similar
effects. These observations align with the role of mass disparity in
crashes; when vehicles of different masses collide, the smaller vehicle
will experience a larger change in velocity (and, by extension, force)
which increases the risk to its occupants.
    2. Impacts of Vehicle Prices on Fleet Turnover. Vehicles have
become safer over time through a combination of new safety regulations
and voluntary safety improvements. The agency expects this trend to
continue as emerging technologies, such as advanced driver assistance
systems, are incorporated into new vehicles. Safety improvements will
likely continue regardless of changes to CAFE standards.
    As discussed in Section III.E.2, technologies added to comply with
fuel economy standards have an impact on vehicle prices, therefore
slowing the acquisition of newer vehicles and retirement of older ones.
The delay in fleet turnover caused by the effect of new vehicle prices
affect safety by slowing the penetration of new safety technologies
into the fleet.
    The standards also influence the composition of the light-duty
fleet. As the safety provided by light trucks, SUVs and passenger cars
responds differently to technology that manufacturers employ to meet
the standards--particularly mass reduction--fleets with different
compositions of body styles will have varying numbers of fatalities, so
changing the share of each type of light-duty vehicle in the projected
future fleet impacts safety outcomes.
    3. Increased driving because of better fuel economy. The ``rebound
effect'' predicts consumers will drive more when the cost of driving
declines. More stringent standards reduce vehicle operating costs, and
in response, some consumers may choose to drive more. Additional
driving increases exposure to risks associated with motor vehicle
travel, and this added exposure translates into higher fatalities and
injuries.
    The contributions of the three factors described above generate the
differences in safety outcomes among regulatory alternatives.\369\ The
agency's analysis makes extensive efforts to allocate the differences
in safety outcomes between the three factors. Fatalities expected
during future years under each alternative are projected by deriving a
fleet-wide fatality rate (fatalities per vehicle mile of travel) that
incorporates the effects of differences in each of the three factors
from baseline conditions and multiplying it by that alternative's
expected VMT. Fatalities are converted into a societal cost by
multiplying fatalities with the DOT-recommended value of a statistical
life (VSL) supplemented by economic impacts that are external to VSL
measurements. Traffic injuries and property damage are also modeled
directly using the same process and valued using costs that are
specific to each injury severity level.
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    \369\ The terms safety performance and safety outcome are
related but represent different concepts. When we use the term
safety performance, we are discussing the intrinsic safety of a
vehicle based on its design and features, while safety outcome is
used to describe whether a vehicle has been involved in an accident
and the severity of the accident. While safety performance
influences safety outcomes, other factors such as environmental and
behavioral characteristics also play a significant role.
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    All three factors influence predicted fatalities, but only two of
them--changes in vehicle mass and in the composition of the light-duty
fleet in response to changes in vehicle prices--impose increased risks
on drivers and passengers that are not compensated for by accompanying
benefits. In contrast, increased driving associated with the rebound
effect is a consumer choice that reveals the benefit of additional
travel. Consumers who choose to drive more have apparently concluded
that the utility of additional driving exceeds the additional costs for
doing so, including the crash risk that they perceive additional
driving involves. As discussed in Chapter 7 of the accompanying
Technical Support Document, the benefits of rebound driving are
accounted for by offsetting a portion of the added safety costs.
    The agency categorizes safety outcome through three measures of
light-duty vehicle safety: Fatalities to occupants occurring in
crashes, serious injuries sustained by occupants, and the number of
vehicles involved in crashes that cause property damage but no
injuries. Counts of fatalities to occupants of automobiles and light
trucks are obtained from the agency's Fatal Accident Reporting System
(FARS). Estimates of the number of serious injuries to drivers and
passengers of light-duty vehicles are tabulated from the agency's
General Estimates System (GES), an annual sampling of motor vehicle
crashes occurring throughout the U.S. Weights for different types of
crashes were used to expand the samples of each type to estimates of
the total number of crashes occurring during each year. Finally,
estimates of the number of automobiles and light trucks involved in
property damage-only (PDO) crashes each year were also developed using
GES. NHTSA seeks comment on the following discussion.
1. Mass Reduction Impacts
    Vehicle mass reduction can be one of the more cost-effective means
of improving fuel economy, particularly for makes and models not
already built with much high-strength steel or aluminum closures or
low-mass components. Manufacturers have stated that they will continue
to reduce vehicle

mass to meet more stringent standards, and therefore, this expectation
is incorporated into the modeling analysis supporting the standards.
Safety trade-offs associated with mass-reduction have occurred in the
past, particularly before CAFE standards were attribute-based; past
safety trade-offs may have occurred because manufacturers chose at the
time, in response to CAFE standards, to build smaller and lighter
vehicles. In cases where fuel economy improvements were achieved
through reductions in vehicle size and mass, the smaller, lighter
vehicles did not fare as well in crashes as larger, heavier vehicles,
on average. Although The agency now uses attribute-based standards, in
part to reduce or eliminate the incentive to downsize vehicles to
comply with CAFE standards, the agency must be mindful of the
possibility of related safety trade-offs.
    For this proposed rule, the agency employed the modeling technique
developed in the 2016 Puckett and Kindelberger report to analyze the
updated crash and exposure data by examining the cross sections of the
societal fatality rate per billion vehicle miles of travel (VMT) by
mass and footprint, while controlling for driver age, gender, and other
factors, in separate logistic regressions for five vehicle groups and
nine crash types.\370\ The agency utilized the relationships between
weight and safety from this analysis, expressed as percentage increases
in fatalities per 100-pound weight reduction (which is how mass
reduction is applied in the technology analysis; see Section III.D.4),
to examine the weight impacts applied in this CAFE analysis. The
effects of mass reduction on safety were estimated relative to
(incremental to) the regulatory baseline in the CAFE analysis, across
all vehicles for MY 2021 and beyond.
---------------------------------------------------------------------------

    \370\ Puckett, S.M. and Kindelberger, J.C. (2016, June).
Relationships between Fatality Risk, Mass, and Footprint in Model
Year 2003-2010 Passenger Cars and LTVs--Preliminary Report. (Docket
No. 2016-0068). Washington, DC: National Highway Traffic Safety
Administration.
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    In computing the impact of changes in mass on safety, the agency is
faced with competing challenges. Research has consistently shown that
mass reduction affects ``lighter'' and ``heavier'' vehicles differently
across crash types. The 2016 Puckett and Kindelberger report found mass
reduction concentrated among the heaviest vehicles is likely to have a
beneficial effect on overall societal fatalities, while mass reduction
concentrated among the lightest vehicles is likely to have a
detrimental effect on fatalities. This represents a relationship
between the dispersion of mass across vehicles in the fleet and
societal fatalities: Decreasing dispersion is associated with a
decrease in fatalities. Mass reduction in heavier vehicles is more
beneficial to the occupants of lighter vehicles than it is harmful to
the occupants of the heavier vehicles. Mass reduction in lighter
vehicles is more harmful to the occupants of lighter vehicles than it
is beneficial to the occupants of the heavier vehicles.
    To accurately capture the differing effect on lighter and heavier
vehicles, the agency splits vehicles into lighter and heavier vehicle
classifications in the analysis. However, this poses a challenge of
creating statistically meaningful results. There is limited relevant
crash data to use for the analysis. Each partition of the data reduces
the number of observations per vehicle classification and crash type,
and thus reduces the statistical robustness of the results. The
methodology employed by the agency was designed to balance these
competing forces as an optimal trade-off to accurately capture the
impact of mass-reduction across vehicle curb weights and crash types
while preserving the potential to identify robust estimates.
    Comments on the NPRM (83 FR 42986, August 24, 2018) for the 2020
CAFE rule included suggestions that the sample of LTVs in the analysis
should not include the medium- or heavy-duty (i.e., truck-based
vehicles with GVWR above 8,500 pounds) equivalents of light-duty
vehicles in the sample (e.g., Ford F-250 versus F-150, RAM 2500 versus
RAM 1500, Chevrolet Suburban 2500 versus Chevrolet Suburban 1500), or
Class 2b and 3 vehicles. For the proposal, NHTSA explored revising the
analysis consistent with such comments. The process involved two key
analytical steps: (1) Removing all case vehicles from the analysis
whose GVWR exceeded 8,500 pounds; and (2) re-classifying all crash
partners with GVWR above 8,500 pounds as heavy vehicles. The direct
effects of these changes are: (1) The range of curb weights in the LTV
sample is reduced, lowering the median curb weight from 5,014 pounds to
4,808 pounds; (2) the sample size of LTVs is reduced (the number of
case LTVs under this alternative specification is approximately 18
percent lower than in the central analysis); and (3) the relative
impact of crashes with LTVs on overall impacts on societal fatality
rates decreases, while the corresponding impact of crashes with heavy
vehicles increases.
    The results from the exploratory analysis of this alternative
approach are provided in Table III-41. The agency seeks comment on this
alternative approach; public comment will inform the decision whether
to incorporate the results into the CAFE Model. The primary functional
change offered by the alternative approach is that the sample of
vehicles classified as LTVs would be restricted to vehicles that would
be subject to CAFE regulations. At the statistical level, the concerns
raised in the agency's response to comment on the 2018 CAFE NPRM
remain. In particular, including Class 2b and 3 vehicles in the
analysis to determine the relationship of vehicle mass on safety has
the added benefit of improving correlation constraints. Notably, curb
weight increases faster than footprint for large light trucks and Class
2b and 3 pickup trucks and SUVs, in part because the widths of vehicles
are constrained more tightly (i.e., due to lane widths) than their curb
weights. Including data from Class 2b and 3 pick-up truck and SUV fatal
crashes provides data over a wider range of vehicle weights, which
improves the ability to estimate the mass-crash fatality relationship.
That is, by extending the footprint-curb weight-fatality data to
include Class 2b and 3 trucks that are functionally and structurally
similar to corresponding \1/2\-ton models that are subject to CAFE
regulation, the sample size and ranges of curb weights and footprint
are improved. Sample size is a challenge for estimating relationships
between curb weight and fatality risk for individual crash types in the
main analysis; dividing the sample further or removing observations
makes it increasingly difficult to identify meaningful estimates and
the relationships that are present in the data, as shown in the
sensitivity analysis below. For the proposal, the agency has determined
that the benefit of the additional data points outweighs the concern
that some of the vehicles used to determine the mass-safety
coefficients are not regulated by CAFE vehicles.
    The agency also explored three other alternative model
specifications that are presented in Table III-41. The first
alternative centers on aligning CUVs and minivans with the rest of the
sample, by splitting these vehicles into two weight classes. The key
factor restricting this change historically has been a low sample size
for these vehicles; the exploratory analysis examined whether the
current database (which, due to the range of CYs covered, contains a
smaller share of CUVs and

minivans than the current fleet) contains a sufficient sample size to
evaluate two weight classes for CUVs and minivans. A complicating
factor in this analysis is that minivans tend to have higher curb
weights than other CUVs, adding statistical burden in identifying
meaningful effects of mass on societal fatality rates after accounting
for body type in the weight class with the fewest minivans (i.e.,
lighter CUVs and minivans).
    The second alternative centers on aligning passenger cars with the
rest of the sample by including cars that are equipped with all-wheel
drive (AWD). In previous analyses, passenger cars with AWD were
excluded from the analysis because they represented a sufficiently low
share of the vehicle fleet that statistical relationships between AWD
status and societal fatality risk were highly prone to being conflated
with other factors associated with AWD status (e.g., location, luxury
vehicle status). However, the share of AWD passenger cars in the fleet
has grown. Approximately one-quarter of the passenger cars in the
database have AWD, compared to an approximately five-percent share in
the MY 2000-2007 database. Furthermore, all other vehicle types in the
analysis include AWD as an explanatory variable. Thus, the agency finds
the inclusion of a considerable portion of the real-world fleet (i.e.,
passenger cars with AWD) to be a meaningful consideration.
    The third alternative is a minor procedural question: Whether to
expand the CYs and MYs used to identify the distribution of fatalities
across crash types. The timing of the safety databases places the years
of the analysis used to establish the distribution of fatalities by
crash type firmly within the central years of the economic downturn of
the late 2000s and early 2010s. During these years, travel demand was
below long-term trends, resulting in fewer crashes. In turn, applying
the same window of CYs and MYs to the identification of the
distribution of fatalities across crash types results in notably fewer
crashes to incorporate into the analysis. The agency conducted
exploratory analysis on the question of whether to add CYs and MYs to
the range of crashes used to identify the distribution of fatalities
across crash types; this analysis was conducted in concert with the two
alternatives discussed directly above. Results incorporating these
three alternatives are presented in Table III-41.
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    Under the alternative specification excluding Class 2b and Class 3
truck-based vehicles as case vehicles, the median curb weight for LTVs
is 4,808 pounds, or 206 pounds lighter than in the central analysis.
When splitting CUVs and minivans into two weight classes, the median
curb weight for the vehicles is 3,955 pounds. Under this alternative
specification, where Class 2b and Class 3 truck-based crash partners
are shifted from truck-based LTVs to heavy-duty vehicles, the median
curb weight for LTV crash partners is 4,216 pounds, or 144 pounds
lighter than in the central analysis.
    Re-classifying Class 2b and Class 3 truck-based vehicles has a
strong effect on the point estimate for heavier LTVs. Critically,
removing the heaviest trucks as case vehicles yields a much smaller
point estimate (reduction in societal fatality rates of between 0.16%
and 0.17% per 100-pound mass reduction, versus 0.61% in the central
analysis). This result is consistent with a relationship where a key
share of the sensitivity of fatality risk is attributed to the mass of
the heaviest vehicles in the fleet (i.e., supporting the role of mass
dispersion in societal fatality rates). Importantly, the point estimate
for lighter LTVs is not meaningfully different from the corresponding
estimate in the central analysis (increase in societal fatality rates
of between 0.26% and 0.29% per 100-pound mass reduction, versus 0.3% in
the central analysis). Considered in concert, these results indicate
that the most effective reductions in societal fatality rates via mass
reduction in truck-based vehicles would arise not from lightweighting
the heaviest vehicles subject to CAFE

regulation, but rather from lightweighting similar, medium- and heavy-
duty vehicles.
    Including passenger cars with AWD in the analysis has little effect
on the point estimate for lighter passenger cars (increase in societal
fatality rates of approximately 1.1% per 100-pound mass reduction,
versus 1.2% in the central analysis). However, this revision has a
strong effect on the point estimate for heavier passenger cars
(increase in societal fatality rates of between 0.84% and 0.89% per
100-pound mass reduction, versus 0.42% in the central analysis). This
result supports a hypothesis that, after taking AWD status into
account, mass reduction in heavier passenger cars is a more important
driver of societal fatality rates than previously estimated. Although
this result could be spurious, estimated confidence bounds (presented
below) indicate that accounting for AWD status reduces uncertainty in
the point estimate. The agency seeks comment on the inclusion of
passenger cars with AWD when estimating the effects of mass reduction
on societal fatality rates.
    Splitting CUVs and minivans into two vehicle classes yields point
estimates that are consistent with the point estimate for the
consolidated CUV-minivan vehicle class (an average decrease in societal
fatality rates of approximately 0.16% to 0.18% per 100-pound mass
reduction across the two vehicle classes, versus a decrease of 0.25% in
the central analysis). However, sample sizes half as large in the two
vehicle classes relative to the consolidated vehicle class lead to very
large estimated confidence bounds, as shown below. Due to this
uncertainty, The agency does not feel that the current databases
contain a large enough sample of CUVs and minivans to split these
vehicles into two classes in the analysis; however, this issue will be
re-examined when the next iteration of the databases is complete.
    Extending the range of CYs and MYs used to establish the
distribution of fatalities across crash types has a negligible effect
on the point estimates. Based on the narrow ranges of results in Table
III-41, The agency finds evidence supporting a flexible approach in the
choice of CYs and MYs used in this manner. All else being equal,
extending the range helps to mitigate the potential for individual
crash types with large estimated effects to drive spurious effects on
overall estimates through unrepresentatively high estimated shares of
overall fatalities. As a hedge in this direction, the agency applied
the estimates from the alternative specification with two additional
CYs and MYs (i.e., the second column from the right in Table III-41)
when evaluating 95-percent confidence bounds for the alternative models
considered here. The agency seeks comment on this approach to
representing the distribution of fatalities across crash types.
    A more detailed description of the mass-safety analysis can be
found in Chapter 7 of the accompanying TSD.
2. Sales/Scrappage Impacts
    The sales and scrappage responses to higher vehicle prices
discussed in Section III.E.2 have important safety consequences and
influence safety through the same basic mechanism, fleet turnover. In
the case of the scrappage response, delaying fleet turnover keeps
drivers in older vehicles which tend to be less safe than newer
vehicles.\371\ Similarly, the sales response slows the rate at which
newer vehicles, and their associated safety improvements, enter the on-
road population. The sales response also influences the mix of vehicles
on the road--with more stringent CAFE standards leading to a higher
share of light trucks sold in the new vehicle market, assuming all else
is equal. This occurs because there is diminishing value to marginal
improvements in fuel economy (there are fewer gallons to be saved), and
as the difference in consumption between light trucks and passenger
cars diminishes, the other attributes of the trucks will likely lead to
increases in their market share--especially under lower gas prices.
Light trucks have higher rates of fatal crashes when interacting with
passenger cars and, as earlier discussed, different directional
responses to mass reduction technology based on the existing mass and
body style of the vehicle.
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    \371\ See Passenger Vehicle Occupant Injury Severity by Vehicle
Age and Model Year in Fatal Crashes, Traffic Safety Facts Research
Note, DOT-HS-812-528, National Highway Traffic Safety
Administration, April, 2018, and The Relationship Between Passenger
Vehicle Occupant Injury Outcomes and Vehicle Age or Model Year in
Police-Reported Crashes, Traffic Safety Facts Research Note, DOT-HS-
812-937, National Highway Traffic Safety Administration, March,
2020.
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    Any effects on fleet turnover (either from delayed vehicle
retirement or deferred sales of new vehicles) will affect the
distribution of both ages and model years present in the on-road fleet.
Because each of these vintages carries with it inherent rates of fatal
crashes, and newer vintages are generally safer than older ones,
changing that distribution will change the total number of on-road
fatalities under each regulatory alternative. Similarly, the dynamic
fleet share model captures the changes in the fleet's composition of
cars and trucks. As cars and trucks have different fatality rates,
differences in fleet composition across the alternatives will affect
fatalities.
    At the highest level, the agency calculates the impact of the sales
and scrappage effects by multiplying the VMT of a vehicle by the
fatality risk of that vehicle. For this analysis, calculating VMT is
rather simple: The agency uses the distribution of miles calculated in
TSD Chapter 4.3. The trickier aspect of the analysis is creating
fatality rate coefficients. The fatality risk measures the likelihood
that a vehicle will be involved in a fatal accident per mile driven.
The agency calculates the fatality risk of a vehicle based on the
vehicle's model year, age, and style, while controlling for factors
which are independent of the intrinsic nature of the vehicle, such as
behavioral characteristics. Using this same approach, the agency
designed separate models for fatalities, non-fatal injuries, and
property damaged vehicles.
    The fatality risk projections described above capture the
historical evolution of safety. Given that modern technologies are
proliferating faster than ever and offer greater safety benefits than
traditional safety improvements, the agency augmented the fatality risk
projections with knowledge about forthcoming safety improvements. The
agency applied detailed empirical estimates of the market uptake and
improving effectiveness of crash avoidance technologies to estimate
their effect on the fleet-wide fatality rate, including explicitly
incorporating both the direct effect of those technologies on the crash
involvement rates of new vehicles equipped with them, as well as the
``spillover'' effect of those technologies on improving the safety of
occupants of vehicles that are not equipped with these
technologies.\372\
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    \372\ These technologies included Forward Collision Warning
(FCW), Crash Imminent Braking (CIB), Dynamic Brake Support (DBS),
Pedestrian AEB (PAEB), Rear Automatic Braking, Semi-automatic
Headlamp Beam Switching, Lane Departure Warning (LDW), Lane Keep
Assist (LKA), and Blind Spot Detection (BSD). While Autonomous
vehicles offer the possibility of significantly reducing or
eventually even eliminating the effect of human error in crash
causation, a contributing factor in roughly 94% of all crashes,
there is insufficient information and certainty regarding autonomous
vehicles eventual impact to include them in this analysis.
---------------------------------------------------------------------------

    The agency's approach to measuring these impacts is to derive
effectiveness rates for these advanced crash-avoidance technologies
from safety technology literature. The agency then applies these
effectiveness rates to specific crash target populations for

which the crash avoidance technology is designed to mitigate and
adjusted to reflect the current pace of adoption of the technology,
including the public commitment by manufactures to install these
technologies. The products of these factors, combined across all 6
advanced technologies, produce a fatality rate reduction percentage
that is applied to the fatality rate trend model discussed above, which
projects both vehicle and non-vehicle safety trends. The combined model
produces a projection of impacts of changes in vehicle safety
technology as well as behavioral and infrastructural trends. A much
more detailed discussion of the methods and inputs used to make these
projections of safety impacts from advanced technologies is included in
Chapter 7 of the accompanying TSD.
3. Rebound Effect Impacts
    The additional VMT demanded due to the rebound effect is
accompanied by more exposure to risk, however, rebound miles are not
imposed on consumers by regulation. They are a freely chosen activity
resulting from reduced vehicle operational costs. As such, the agencies
believe a large portion of the safety risks associated with additional
driving are offset by the benefits drivers gain from added driving. The
level of risk internalized by drivers is uncertain. This analysis
assumes that consumers internalize 90 percent of this risk, which
mostly offsets the societal impact of any added fatalities from this
voluntary consumer choice. Additional discussion of internalized risk
is contained in TSD Chapter 7.4.
4. Value of Safety Impacts
    Fatalities, nonfatal injuries, and property damage crashes are
valued as a societal cost within the CAFE Model's cost and benefit
accounting. Their value is based on the comprehensive value of a
fatality, which includes lost quality of life and is quantified in the
value of a statistical life (VSL) as well as economic consequences such
as medical and emergency care, insurance administrative costs, legal
costs, and other economic impacts not captured in the VSL alone. These
values were derived from data in Blincoe et al. (2015), adjusted to
2018 dollars, and updated to reflect the official DOT guidance on the
value of a statistical life. Nonfatal injury costs, which differ by
severity, were weighted according to the relative incidence of injuries
across the Abbreviated Injury Scale (AIS). To determine this incidence,
the agency applied a KABCO \373\/maximum abbreviated injury scale
(MAIS) translator to GES KABCO based injury counts from 2010 through
2015. This produced the MAIS based injury profile. This profile was
used to weight nonfatal injury unit costs derived from Blincoe et al.,
adjusted to 2018 economics and updated to reflect the official DOT
guidance on the value of a statistical life. Property-damaged vehicle
costs were also taken from Blincoe et al. and adjusted to 2018
economics. VSL does not affect property damage. This gives societal
values of $10.8 million for each fatality, $132,000 for each nonfatal
injury, and $7,100 for each property damaged vehicle.
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    \373\ The ``KABCO'' injury scale also can be used for
establishing crash costs. This scale was developed by the National
Safety Council (NSC) and is frequently used by law enforcement for
classifying injuries: K--Fatal; A--Incapacitating injury; B--Non-
incapacitating injury; C--Possible injury; and O--No injury.
---------------------------------------------------------------------------

5. Impacts of the Proposal on Safety
    Table III-42 through Table III-44 summarize the safety impacts of
the proposed standards on safety broken down by factor. These impacts
are summarized over the lifetimes of model year 1981 through 2029
vehicles for all light passenger vehicles (including passenger cars and
light trucks). Economic impacts are shown separately under both 3% and
7% discount rates. Model years 1981 through 2029 were examined because
they represent the model years that might be affected by shifts in
fleet composition due to the impact of higher new vehicle prices on
sales of new vehicles and retention of older vehicles. Earlier years
will be affected by slower scrappage rates and we expect the impacts of
these standards will be fully realized in vehicle designs by MY 2029.
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    As seen in the tables, all three safety factors--changes in mass,
fleet turnover, and rebound--increase as the standards become more
stringent. As expected, rebound fatalities grow at a constant rate as
vehicles become more fuel efficient and are used more frequently. Mass
reduction has a relatively minimal impact on safety and diminishes as
stringency increases. This may point to either the fleet becoming more
homogeneous and hence less mass disparate in crashes. Alternatively,
the model may be capturing that there's little room for more mass
reductions in particular models. The slowing of fleet turnover due to
higher vehicle prices has the largest impact of the three factors and
accelerates with higher alternatives. Of course, if the agency's
assumptions overstate the rebound effect and/or slower fleet turnover,
fatalities, injuries and property damage would be lower, and vice
versa.
    PRIA Chapter 5.5 discusses the results of the analysis in more
detail and PRIA Chapter 5.6--Safety Impacts provides an overview of
sensitivity analyses performed to isolate the uncertainty parameters of
each of the three safety impacts.

IV. Regulatory Alternatives Considered in this NPRM

A. Basis for Alternatives Considered

    Agencies typically consider regulatory alternatives in proposals as
a way of evaluating the comparative effects of different potential ways
of accomplishing their desired goal. NEPA requires agencies to compare
the potential environmental impacts of their proposed actions to those
of a reasonable range of alternatives. Executive Orders 12866 and
13563, as well as OMB Circular A-4, also encourage agencies to evaluate
regulatory alternatives in their rulemaking analyses.
    Alternatives analysis begins with a ``no-action'' alternative,
typically described as what would occur in the absence of any
regulatory action. This proposal includes a no-action alternative,
described below, and three ``action alternatives.'' The proposed
standards may, in places, be referred to as the ``preferred
alternative,'' which is NEPA parlance, but NHTSA intends ``proposal''
and ``preferred alternative'' to be used interchangeably for purposes
of this rulemaking.
    Regulations regarding implementation of NEPA require agencies to
``rigorously explore and objectively evaluate all reasonable
alternatives, and for alternatives which were eliminated from detailed
study, briefly discuss the reasons for their having been eliminated.''
This does not amount to a requirement that agencies evaluate the widest
conceivable spectrum of alternatives. Rather, the range of alternatives
must be reasonable and consistent with the purpose and need of the
action.
    The different regulatory alternatives are defined in terms of
percent-increases in CAFE stringency from year to year. Readers should
recognize that those year-over-year changes in stringency are not
measured in terms of mile per gallon differences (as in, 1 percent more
stringent than 30 miles per gallon in one year equals 30.3 miles per
gallon in the following year), but rather in terms of shifts in the
footprint functions that form the basis for the actual CAFE standards
(as in, on a gallon per mile basis, the CAFE standards change by a
given percentage from one model year to the next). Under some
alternatives, the rate of change is the same from year to year, while
under others, it differs, and under some alternatives, the rate of
change is different for cars and for trucks. One action alternative is
more stringent than the proposal, while one is less stringent than the
proposal. The alternatives considered in this proposal represent a
reasonable range of possible final agency actions.

B. Regulatory Alternatives and Proposed CAFE Standards for MYs 2024-
2026

    The regulatory alternatives for this proposal are presented here as
the percent-increases-per-year that they represent. The sections that
follow will present the alternatives as the literal coefficients which
define standards curves increasing at the given percentage rates and
will also further explain the basis for the alternatives selected.

[GRAPHIC] [TIFF OMITTED] TP03SE21.101

    As for past rulemaking analyses, NHTSA has analyzed each of the
regulatory alternatives in a manner that estimates manufacturers'
potential application of technology in response to the corresponding
CAFE requirements and the estimated market demand for fuel economy,
considering estimated fuel prices, estimated product development
cadence, and the estimated availability, applicability, cost, and
effectiveness of fuel-saving technologies. The analysis sometimes shows
that specific manufacturers could increase CAFE levels beyond
requirements in ways estimated to ``pay buyers back'' very quickly
(i.e., within 30 months) for the corresponding additional costs to
purchase new vehicles through avoided fuel outlays. Consistent with the
analysis published with the 2020 final rule, this analysis shows that
if battery costs decline as projected while fuel prices increase as
projected, BEVs should become increasingly attractive on this basis,
such that the modeled application of BEVs (and some other technologies)
clearly outstrips regulatory requirements after the mid-2030s.
    The analysis accompanying the 2020 final rule presented such
results for CAFE standards as well as--separately--CO2
standards. New in this proposal, DOT has modified the CAFE Model to
account for the combined effect of both CAFE and CO2
standards, simulating technology application decisions each
manufacturer could possibly make when faced with both CAFE standards
and CO2 standards (and also estimated market demand for fuel
economy). This capacity was exercised for purposes of creating the
baseline against which alternatives were analyzed, but not for purposes
of modeling compliance with both agencies' proposals. Also, new for
this proposal, DOT has further modified the CAFE Model to account for
the ``Framework'' agreements California has reached with BMW, Ford,
Honda, Volkswagen, and Volvo, and for the ZEV mandate that California
and the ``Section 177'' states have adopted. The TSD elaborates on
these new model capabilities. Generally speaking, the model treats each
manufacturer as applying the following logic when making technology
decisions:
    1. What do I need to carry over from last year?
    2. What should I apply more widely in order to continue sharing
(of, e.g., engines) across different vehicle models?
    3. What new PHEVs or BEVs do I need to build in order to satisfy
the ZEV mandates?
    4. What further technology, if any, could I apply that would enable
buyers to recoup additional costs within 30 months after buying new
vehicles?
    5. What additional technology, if any, should I apply in order to
respond to CAFE and CO2 standards?
    All of the regulatory alternatives considered here include, for
passenger cars, the following coefficients defining the combination of
baseline Federal CO2 standards and the California Framework
agreement.
[GRAPHIC] [TIFF OMITTED] TP03SE21.102

    Coefficients a, b, c, d, e, and f define the current Federal
CO2 standards for passenger cars. Analogous to coefficients
defining CAFE standards, coefficients a and b specify minimum and
maximum passenger car CO2 targets in each model year.
Coefficients c and d specify the slope and intercept of the linear
portion of the CO2 target function,

and coefficients e and f bound the region within which CO2
targets are defined by this linear form. Coefficients g, h, i, and j
define the CO2 targets applicable to BMW, Ford, Honda,
Volkswagen, and Volvo, pursuant to the agreement these manufacturers
have reached with California. Beyond 2026, the MY 2026 Federal
standards apply to all manufacturers, including these five
manufacturers. The coefficients shown in Table IV-3 define the
corresponding CO2 standards for light trucks.
[GRAPHIC] [TIFF OMITTED] TP03SE21.103

    All of the regulatory alternatives considered here also include
NHTSA's estimates of ways each manufacturer could introduce new PHEVs
and BEVs in response to ZEV mandates. As discussed in greater detail
below, these estimates force the model to convert specific vehicle
model/configurations to either a BEV200, BEV300, or BEV400 at the
earliest estimated redesign. These ``ZEV Candidates'' define an
incremental response to ZEV mandates (i.e., beyond PHEV and BEV
production through MY 2020) comprise the following shares of
manufacturers' MY 2020 production for the U.S. market as shown in Table
IV-4.
[GRAPHIC] [TIFF OMITTED] TP03SE21.104

    For example, while Tesla obviously need not introduce additional
BEVs to comply with ZEV mandates, our analysis indicates Nissan could
need to increase BEV offerings modestly to do so, and Mazda and some
other manufacturers may need to do considerably more than Nissan to
introduce new BEV offerings.

    This representation of CO2 standards and ZEV mandates
applies equally to all regulatory alternatives, and NHTSA's analysis
applies the CAFE Model to examine each alternative treating each
manufacturer as responding jointly to the entire set of requirements.
This is distinct from model application of BEVs for compliance purposes
under the compliance simulations of the different action alternatives
which inform decision-makers regarding potential effects of the
standards.
    Chapter 1 of the TSD contains extensive discussion of the
development of the No-Action Alternative, and explains the reasons for
and effect of apparent ``over-compliance'' with the No-Action
Alternative, which reduces costs and benefits attributable to the
proposed CAFE standards and other action alternatives. NHTSA seeks
comment broadly on that discussion and whether and how to change its
approach to developing the No-Action Alternative for the final rule.
NHTSA also specifically seeks comment on whether and how to add to the
No-Action Alternative for the final rule an estimation of GHG standards
that California and the Section 177 states might separately enforce if
California's waiver of CAA preemption was re-established.
1. No-Action Alternative
    The No-Action Alternative (also sometimes referred to as
``Alternative 0'') applies the CAFE target curves set in 2020 for MYs
2024-2026, which raised stringency by 1.5 percent per year for both
passenger cars and light trucks.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.105

[GRAPHIC] [TIFF OMITTED] TP03SE21.106

    These equations are presented graphically in Figure IV-1 and Figure
IV-2, where the x-axis represents vehicle footprint and the y-axis
represents fuel economy, showing that in ``CAFE space,'' targets are
higher in fuel economy for smaller footprint vehicles and lower for
larger footprint vehicles.

[GRAPHIC] [TIFF OMITTED] TP03SE21.107

[GRAPHIC] [TIFF OMITTED] TP03SE21.108

    NHTSA must also set a minimum standard for domestically
manufactured passenger cars, which is often referred to as the
``MDPCS.'' Any time NHTSA establishes or changes a passenger car
standard for a model year, the MDPCS must also be evaluated or re-
evaluated and established accordingly, but for purposes of the No-
Action alternative, the MDPCS is as it was established in the 2020
final rule, as shown in Table IV-7.
[GRAPHIC] [TIFF OMITTED] TP03SE21.109

BILLING CODE 4910-59-C
    As the baseline against which the Action Alternatives are measured,
the No-Action Alternative also includes several other actions that
NHTSA believes will occur in the absence of further regulatory action.
First, NHTSA has included California's ZEV mandate as part of the No-
Action Alternative. NHTSA has already proposed to rescind the 2019
``SAFE I'' rule,\374\ and EPA has reopened consideration of whether to
grant California a waiver to consider its ZEV mandate,\375\ although
California does not currently possess a waiver of preemption under the
CAA and NHTSA regulations currently purport to preempt the California
ZEV program. Although neither of these actions has yet been finalized,
it is reasonably foreseeable that manufacturers selling vehicles in
California and in the Section 177 states could be required to comply
with the ZEV mandate during the timeframe of this rulemaking. Second,
NHTSA has included the agreements made between California and BMW,
Ford, Honda, VWA, and Volvo, because these agreements by their terms
are contracts,

even though they were entered into voluntarily.\376\ NHTSA did so by
including EPA's baseline (i.e., 2020) GHG standards in its analysis,
and introducing more stringent GHG target functions during MYs 2022-
2026, but treating only these five manufacturers as subject to these
more stringent target functions. Because a significant portion of the
market voluntarily adopted the California framework, presumably because
the manufacturers who joined believed it could be met, and because that
adoption is contractually binding once entered into, it is reasonable
to assume that it will occur as expected during the rulemaking
timeframe, and thus, reasonable to include in the No-Action
Alternative. As in past analyses, NHTSA's analysis further assumes
that, beyond any technology applied in response to CAFE standards, EPA
GHG standards, California/OEM agreements, and ZEV mandates applicable
in California and the Section 177 states, manufacturers could also make
any additional fuel economy improvements estimated to reduce owners'
estimated average fuel outlays during the first 30 months of vehicle
operation by more than the estimated increase in new vehicle price.
---------------------------------------------------------------------------

    \374\ 86 FR 25980 (May 12, 2021).
    \375\ 86 FR 22421 (Apr. 28, 2021).
    \376\ See https://ww2.arb.ca.gov/news/framework-agreements-clean-cars.
---------------------------------------------------------------------------

    NHTSA accomplished much of this through expansion of the CAFE Model
after the prior rulemaking. The previous version of the model had been
extended to apply to GHG standards as well as CAFE standards but had
not been published in a form that simulated simultaneous compliance
with both sets of standards. As discussed at greater length in the
current CAFE Model documentation, the updated version of the model
simulates all the following simultaneously:

1. Compliance with CAFE standards
2. Compliance with GHG standards applicable to all manufacturers
3. Compliance with alternative GHG standards applicable to a subset of
manufacturers
4. Compliance with ZEV mandates
5. Further fuel economy improvements applied if sufficiently cost-
effective for buyers

    Inclusion of these actions in the No-Action Alternative means that
they are necessarily included in each of the Action Alternatives. That
is, the impacts of all the alternatives evaluated in this proposal are
against the backdrop of these State and voluntary actions by
automakers. This is important to remember, because it means that
automakers will be taking actions to improve fuel economy even in the
absence of new CAFE standards, and that costs and benefits attributable
to those actions are therefore not attributable to possible future CAFE
standards.
2. Alternative 1
    Alternative 1 would increase CAFE stringency for MY 2024 by 9.14%
for passenger cars and 11.02% for light trucks and increase stringency
in MYs 2025 and 2026 by 3.26% per year for both passenger cars and
light trucks. NHTSA calculates that the stringency of Alternative 1 in
each of MYs 2024-2026 is equivalent to the average stringency of the
California framework agreement applied to all manufacturers in those
model years. NHTSA calculated the stringency values using a
spreadsheet, shown in TSD Chapter 1, assuming manufacturers would
achieve a one percent reduction in stringency each model year under the
California framework through the application of ZEV vehicle
multipliers. The spreadsheet applies a normalized stringency value of
100 percent in MY 2021 for both CO2 standards and CAFE
standards.
    Informed by these calculations, NHTSA defined Alternative 1 by
applying the CAFE equivalent stringency increases in MYs 2024-2026,
resulting in the coefficients listed in Table IV-8 and Table IV-9.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.110

[GRAPHIC] [TIFF OMITTED] TP03SE21.111

    These equations are represented graphically in Figure IV-4 and
Figure IV-4.
---------------------------------------------------------------------------

    \377\ For this and other action alternatives, readers may note
that the cutpoint for large trucks is further to the right than in
the 2020 final rule. The 2020 final rule (and its preceding NPRM)
did not contain an adjustment to the right cutpoint that had been
finalized in 2012. Because comments were not received to the NPRM,
the lack of adjustment was finalized. Considering the question again
for this proposal, NHTSA believes that moving the cutpoint to the
right for large trucks (consistent with the intent and requirements
in 2012) is reasonable, given the rate of increase in stringency for
this proposal.

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

[GRAPHIC] [TIFF OMITTED] TP03SE21.112

[GRAPHIC] [TIFF OMITTED] TP03SE21.113

    Under this alternative, the MDPCS is as shown in Table IV-10.
    [GRAPHIC] [TIFF OMITTED] TP03SE21.114

    NHTSA considered this alternative as a way to evaluate the effects
of industry-wide CAFE standards approximately harmonized with the
California framework agreement applied to signatory OEMs' production
for the U.S. market.\378\ The fact that five major manufacturers
voluntarily bound themselves to the framework levels, not just for MYs
2024-2026 but for MYs 2021-2026, is a relevant data point in terms of
their technological feasibility and economic practicability for the
fleet as a whole. NHTSA seeks comment on whether Alternative 1 (as
defined by the rate of increase and the curve coefficients)
appropriately captures its stated goal of approximating the fuel
savings that would occur under an industry-wide application of fuel
economy standards harmonized with the California framework, or whether
changes might be appropriate for the final rule. NHTSA asks that
commenters explain the specific technical basis for any requested
changes, as well as the basis for determining that the resultant CAFE
standards could meet EPCA's

requirement that NHTSA select the maximum feasible standard for each
fleet in each model year.
---------------------------------------------------------------------------

    \378\ CAFE standards defining this alternative reflect the fact
that EPCA does not provide a basis for CAFE standards to include
``multipliers'' applicable to PHEV and/or BEV production volumes, as
well as the fact that EPCA's treatment of BEV energy consumption is
different from the ``0 grams/mile'' treatment for purposes of
determining compliance with GHG emissions standards.
---------------------------------------------------------------------------

3. Alternative 2
    Alternative 2 would increase CAFE stringency at 8 percent per year,
which NHTSA calculates would result in total lifetime fuel savings from
vehicles produced during MYs 2021-2029 similar to total lifetime fuel
savings that would occur if the fuel economy standards harmonized with
California framework agreement had applied to all manufacturers during
MYs 2021-2026.
[GRAPHIC] [TIFF OMITTED] TP03SE21.115

[GRAPHIC] [TIFF OMITTED] TP03SE21.116

    Under this alternative, the MDPCS is as shown in Table IV-13.
    [GRAPHIC] [TIFF OMITTED] TP03SE21.117

    NHTSA considered this alternative as a way to evaluate the effects
of CAFE standards that sought to achieve the fuel savings that would be
achieved if fuel economy standards harmonized with the California
framework agreement had been applied to all vehicle manufacturers from
its beginning the time the framework was agreed. As for Alternative 1,
the fact that five major manufacturers voluntarily bound themselves to
these levels, not just for MYs 2024-2026 but for MYs 2021-2026, is a
relevant data point in terms of their technological feasibility and
economic practicability for the fleet as a whole.\379\ NHTSA seeks
comment on whether Alternative 2 (as defined by the rate of increase
and the curve coefficients) appropriately captures its stated goal of
representing the fuel savings achievement that would be achieved if
fuel economy standards harmonized with the California framework
agreement were applied to all companies at a national level over MYs
2021-2026, or whether changes might be appropriate for the final rule.
NHTSA asks that commenters explain the specific technical basis for any
requested changes, as well as the basis for determining that the
resultant CAFE standards could meet EPCA's requirement that NHTSA
select the maximum feasible standard for each fleet in each model year.
---------------------------------------------------------------------------

    \379\ Section VI discusses economic practicability in more
detail, including NHTSA's long-standing interpretation that economic
practicability need not mean that the standards are comfortably
achievable for every single manufacturer individually, as long as
they appear economically practicable for the fleet as a whole.
---------------------------------------------------------------------------

    As another possibility, NHTSA could modify Alternative 2 by
increasing the stringency of CAFE standards by 10 percent between model
years 2025 and 2026, rather than by 8 percent. Shown graphically, this
possibility would look as shown in Figure IV-5.

[GRAPHIC] [TIFF OMITTED] TP03SE21.118

    NHTSA seeks comment on this option as well as on Alternative 2.
4. Alternative 3
    Alternative 3 would increase CAFE stringency at 10 percent per
year, which NHTSA calculates would result in total lifetime fuel
savings from vehicles produced during MYs 2021-2029 similar to total
lifetime fuel savings that would have occurred if NHTSA had promulgated
final CAFE standards for MYs 2021-2025 at the augural levels announced
in 2012 and, in addition, if NHTSA had also promulgated MY 2026
standards that reflected a continuation of that average rate of
stringency increase (4.48% for passenger cars and 4.54% for light
trucks).
[GRAPHIC] [TIFF OMITTED] TP03SE21.119

[GRAPHIC] [TIFF OMITTED] TP03SE21.120

    These equations are represented graphically in Figure IV-6 and
Figure IV-7.
[GRAPHIC] [TIFF OMITTED] TP03SE21.121

[GRAPHIC] [TIFF OMITTED] TP03SE21.122

    Under this alternative, the MDPCS is as follows in Table IV-16.
    [GRAPHIC] [TIFF OMITTED] TP03SE21.123

BILLING CODE 4910-59-C
    NHTSA considered this alternative as a way to evaluate the effects
of CAFE standards that would return to a fuel consumption trajectory
exemplified by the standards announced in 2012. NHTSA seeks comment on
whether Alternative 3 (as defined by the rate of increase and the curve
coefficients) appropriately captures this goal, or whether changes
might be appropriate for the final rule. NHTSA asks that commenters
explain the specific technical basis for any requested changes, as well
as the basis for determining that the resultant CAFE standards could
meet EPCA's requirement that NHTSA select the maximum feasible standard
for each fleet in each model year. While NHTSA believes that this
alternative may be beyond maximum feasible based on the information
currently before us, as discussed in more detail in Section VI, all
alternatives remain under consideration for the final rule. Moreover,
because Alternative 3 produces significant social benefits, NHTSA seeks
comment on whether to adopt a more stringent increase from MY 2025 to
MY 2026, as described above, that would parallel the year over year
increase Alternative 3 analyzes.

V. Effects of the Regulatory Alternatives

A. Effects on Vehicle Manufacturers

    Each of the regulatory alternatives NHTSA has considered would
increase the stringency of both passenger car and light truck CAFE
standards in each of model years 2024-2026. To estimate the potential
impacts of each of these alternatives, NHTSA has, as for all recent
rulemakings, assumed that standards would continue unchanged after the
last model year (in this case, 2026) to be covered by newly issued
standards. It is possible that the size and composition of the fleet
(i.e., in terms of distribution across the range of vehicle footprints)
could change over time, affecting the average fuel economy requirements
under both the passenger car and light truck standards, and for the
overall fleet. If fleet changes differ from NHTSA's projections,
average requirements could, therefore, also differ from NHTSA's
projections. At this time, NHTSA estimates that, under each of the
regulatory alternatives, average fuel economy requirements could
increase as summarized in the following three tables.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.124

[GRAPHIC] [TIFF OMITTED] TP03SE21.125

[GRAPHIC] [TIFF OMITTED] TP03SE21.126

    Manufacturers do not always comply exactly with each CAFE standard
in each model year. To date, some manufacturers have tended to
regularly exceed one or both requirements. Many manufacturers make use
of EPCA's provisions allowing CAFE compliance credits to be applied
when a fleet's CAFE level falls short of the corresponding requirement
in a given model year. Some manufacturers have paid civil penalties
(i.e., fines) required under EPCA when a fleet falls short of a
standard in a given model year and the manufacturer cannot provide
compliance credits sufficient to address the compliance shortfall. As
discussed in the accompanying PRIA and TSD, NHTSA simulates
manufacturers' responses to each alternative given a wide range of
input estimates (e.g., technology cost and efficacy, fuel prices), and,
per EPCA, setting aside the potential that any manufacturer would
respond to CAFE standards in model years 2024-2026 by applying CAFE
compliance credits or introducing new models of alternative fuel
vehicles. Many of these inputs are subject to uncertainty and, in any
event, as in all CAFE rulemakings, NHTSA's analysis merely illustrates
one set of ways manufacturers could potentially respond to each
regulatory alternative. At this time, NHTSA estimates that
manufacturers' responses to standards defining each alternative could
lead average fuel economy levels to increase through model year 2029 as
summarized in the following three tables. Changes are shown to occur in
MY 2023 even though NHTSA is not explicitly

proposing to regulate that model year because NHTSA anticipates that
manufacturers could make changes as early as that model year to affect
future compliance positions (i.e., multi-year planning).
[GRAPHIC] [TIFF OMITTED] TP03SE21.127

[GRAPHIC] [TIFF OMITTED] TP03SE21.128

[GRAPHIC] [TIFF OMITTED] TP03SE21.129

    While these increases in average fuel economy account for estimated
changes in the composition of the fleet (i.e., the relative shares of
passenger cars and light trucks), they result almost wholly from the
projected application of fuel-saving technology. As mentioned above,
NHTSA's analysis merely illustrates one set of ways manufacturers could
potentially respond to each regulatory alternative. Manufacturers'
actual responses will almost assuredly differ from NHTSA's current
estimates.
    At this time, NHTSA estimates that manufacturers' application of
advanced gasoline engines (i.e., gasoline engines with cylinder
deactivation, turbocharging, high or variable compression ratios) could
increase through MY 2029 under the no-action alternative and through at
least MY 2024 under each of the action alternatives. However, NHTSA
also estimates that in MY 2024, reliance on advanced gasoline engines
could begin to decline under the more stringent action alternatives, as
manufacturers shift toward electrification.
[GRAPHIC] [TIFF OMITTED] TP03SE21.130

[GRAPHIC] [TIFF OMITTED] TP03SE21.131

[GRAPHIC] [TIFF OMITTED] TP03SE21.132

    The aforementioned estimated shift to electrification under the
more stringent regulatory alternatives is the most pronounced for
hybrid-electric vehicles (i.e., ``mild'' ISG HEVs and ``strong'' P2 and
Power-Split HEVs).
[GRAPHIC] [TIFF OMITTED] TP03SE21.133

[GRAPHIC] [TIFF OMITTED] TP03SE21.134

[GRAPHIC] [TIFF OMITTED] TP03SE21.135

    Under the more stringent action alternatives, NHTSA estimates that
manufacturers could increase production of plug-in hybrid electric
vehicles (PHEVs) well over current rates.
[GRAPHIC] [TIFF OMITTED] TP03SE21.136

[GRAPHIC] [TIFF OMITTED] TP03SE21.137

[GRAPHIC] [TIFF OMITTED] TP03SE21.138

    For this NPRM and accompanying PRIA, NHTSA's analysis excludes the
introduction of new alternative fuel vehicle (AFV) models during MY
2024-2026 as a response to CAFE standards.\380\ However, NHTSA's
analysis does consider the potential that manufacturers might respond
to CAFE standards by introducing new BEV models outside of MYs 2024-
2026, and NHTSA's analysis does account for the potential that ZEV
mandates could lead manufacturers to introduce new BEV models even
during MYs 2024-2026. Also accounting for shifts in fleet mix, NHTSA
projects increased production of BEVs through MY 2029.
---------------------------------------------------------------------------

    \380\ The SEIS does not make this analytical exclusion.

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

[GRAPHIC] [TIFF OMITTED] TP03SE21.139

[GRAPHIC] [TIFF OMITTED] TP03SE21.140

[GRAPHIC] [TIFF OMITTED] TP03SE21.141

    The PRIA provides a wider-ranging summary of NHTSA's estimates of
manufacturers' potential application of fuel-saving technologies
(including other types of technologies, such as advanced transmissions,
aerodynamic improvements, and reduced vehicle mass) in response to each
regulatory alternative. Appendices I and II of the accompanying PRIA
provide much more detailed and comprehensive results, and the
underlying CAFE Model output files provide all information, including
the specific combination of technologies estimated to be applied to
every specific vehicle model/configuration in each of model years 2020-
2050.\381\
---------------------------------------------------------------------------

    \381\ See Appendices I and II of the accompanying PRIA and the
CAFE Model output files.
---------------------------------------------------------------------------

    NHTSA's analysis shows manufacturers' regulatory costs for CAFE
standards, CO2 standards, and ZEV mandates increasing
through MY 2029, and (logically) increasing more under the more
stringent alternatives. Accounting for fuel-saving technologies
estimated to be added under each regulatory alternative (including air
conditioning improvements and other off-cycle technologies), and also
accounting for CAFE fines that NHTSA estimates some manufacturers could
elect to pay rather than achieving full compliance with CAFE standards
in some model years, NHTSA estimates that relative to the continued
application of MY 2020 technologies, manufacturers' cumulative costs
during MYs 2023-2029 could total $121b under the no-action alternative,
and $166b, $208b, and $251b under alternatives 1, 2, and 3,
respectively. The table below shows how these costs are estimated to
vary among manufacturers, accounting for differences in the quantities
of vehicles produced for sale in the U.S. Appendices I and II of the
accompanying PRIA present results separately for each manufacturer's
passenger car and light truck fleets in each model year under each
regulatory alternative, and the underlying CAFE Model output files also
show results specific to manufacturers' domestic and imported car
fleets.

[GRAPHIC] [TIFF OMITTED] TP03SE21.142

    As discussed in the TSD, these estimates reflect technology cost
inputs that, in turn, reflect a ``markup'' factor that includes
manufacturers' profits. In other words, if costs to manufacturers' are
reflected in vehicle price increases as in the past, NHTSA estimates
that the average costs to new vehicle purchasers could increase through
MY 2029 as summarized in Table V-20 through Table V-22.
[GRAPHIC] [TIFF OMITTED] TP03SE21.143

[GRAPHIC] [TIFF OMITTED] TP03SE21.144

[GRAPHIC] [TIFF OMITTED] TP03SE21.145

    Table V-23 shows how these costs could vary among manufacturers,
suggesting that disparities could decrease as the stringency of
standards increases.
[GRAPHIC] [TIFF OMITTED] TP03SE21.146

    NHTSA estimates that although projected fuel savings under the more
stringent regulatory alternatives could tend to increase new vehicles
sales, this tendency could be outweighed by the opposing response to
higher prices, such that new vehicle sales could decline slightly under
the more stringent alternatives. The magnitude of these fuel savings
and vehicle price increases depends on manufacturer compliance
decisions, especially technology application. In the event that
manufacturers select technologies with lower prices and/or higher fuel
economy improvements, vehicle sales effects could differ. For example,
in the case of the ``unconstrained'' SEIS results, manufacturer costs
across alternatives are lower.

[GRAPHIC] [TIFF OMITTED] TP03SE21.147

    The TSD discusses NHTSA's approach to estimating new vehicle sales,
including NHTSA's estimate that new vehicle sales could recover from
2020's aberrantly low levels.
    While these slight reductions in new vehicles sales tend to
slightly reduce projected automobile industry labor, NHTSA estimates
that the cost increases could reflect an underlying increase in
employment to produce additional fuel-saving technology, such that
automobile industry labor could about the same under each of the four
regulatory alternatives.

[GRAPHIC] [TIFF OMITTED] TP03SE21.148

    The accompanying TSD discusses NHTSA's approach to estimating
automobile industry employment, and the accompanying RIA (and its
Appendices I and II) and CAFE Model output files provide more detailed
results of NHTSA's analysis.

B. Effects on New Car and Truck Buyers

    As discussed above, NHTSA estimates that the average fuel economy
and purchase cost of new vehicles could increase between 2020 and 2029
and increase more quickly under each of the action alternatives than
under the baseline No-Action Alternative. On one hand, buyers could
realize the benefits of increase fuel economy: Spending less on fuel.
On the other, buyers could pay more for new vehicles, for some costs
tied directly to vehicle value (e.g., sales taxes and collision
insurance). Table V-24 reports sales-weighted MSRP values for the No-
Action Alternative and relative increases in MSRP for the three
regulatory alternatives.
[GRAPHIC] [TIFF OMITTED] TP03SE21.149

    Table V-25 through Table V-27 presents projected consumer costs and
benefits along with net benefits for model year 2029 and 2039 vehicles
under the proposed alternatives. Results are shown in 2018 dollars,
without discounting and with benefits and costs discounted at annual
rates of 3% and 7%. The TSD and PRIA accompanying this NPRM discuss
underlying methods, inputs, and results in greater detail, and more
detailed tables and underlying results are contained in the
accompanying CAFE Data Book and CAFE Model output files. For all of the
action alternatives, avoided outlays for fuel purchases account for
most of the projected benefits to consumers, and increases in the cost
to purchase new vehicles account for most of the projected costs.
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C. Effects on Society

    Table V-28 and Table V-29 describe the costs and benefits of
increasing CAFE standards in each alternative, as well as the party to
which they accrue. Manufacturers are directly regulated under the
program and incur additional production costs when they apply
technology to their vehicle offerings in order to improve their fuel
economy. In this analysis, we assume that those costs are fully passed
through to new car and truck buyers, in the form of higher prices.
Other assumptions are possible, but we do not currently have data to
support attempting to model cross-subsidization. We also assume that
any civil penalties--paid by manufacturers for failing to comply with
their CAFE standards--are passed through to new car and truck buyers
and are included in the sales price. However, those civil penalties are
paid to the U.S. Treasury, where they currently fund the general
business of Government. As such, they are a transfer from new vehicle
buyers to all U.S. citizens, who then benefit from the additional
Federal revenue. While they are calculated in the analysis, and do
influence consumer decisions in the marketplace, they do not contribute
to the calculation of net benefits (and are omitted from the tables
below).
    While incremental maintenance and repair costs would accrue to
buyers of new cars and trucks affected by more stringent CAFE
standards, we do not carry these costs in the analysis. They are
difficult to estimate for emerging

technologies but represent real costs (and benefits in the case of
alternative fuel vehicles that may require less frequent maintenance
events). They may be included in future analyses as data become
available to evaluate lifetime maintenance costs. This analysis assumes
that drivers of new vehicles internalize 90 percent of the risk
associated with increased exposure to crashes when they engage in
additional travel (as a consequence of the rebound effect).
    Private benefits are dominated by the value of fuel savings, which
accrue to new car and truck buyers at retail fuel prices (inclusive of
Federal and state taxes). In addition to saving money on fuel
purchases, new vehicle buyers also benefit from the increased mobility
that results from the lower cost of driving their vehicle (higher fuel
economy reduces the per-mile cost of travel) and fewer refueling
events. The additional travel occurs as drivers take advantage of lower
operating costs to increase mobility, and this generates benefits to
those drivers--equivalent to the cost of operating their vehicles to
travel those miles, the consumer surplus, and the offsetting benefit
that represents 90 percent of the additional safety risk from travel.
    In addition to private benefits and costs, there are purely
external benefits and costs that can be attributed to increases in CAFE
standards. These are benefits and costs that accrue to society more
generally, rather than to the specific individuals who purchase a new
vehicle that was produced under more stringent CAFE standards. Of the
external costs, the largest is the loss in fuel tax revenue that occurs
as a result of falling fuel consumption. While drivers of new vehicles
(purchased in years where CAFE stringency is increasing) save fuel
costs at retail prices, the rest of U.S. road users experience a
welfare loss, in two ways. First, the revenue generated by fuel taxes
helps to maintain roads and bridges, and improve infrastructure more
generally, and that loss in fuel tax revenue is a social cost. And
second, the additional driving that occurs as new vehicle buyers take
advantage of lower per-mile fuel costs is a benefit to those drivers,
but the congestion (and road noise) created by the additional travel
impose a social cost to all road users.
    Among the purely external benefits created when CAFE standards are
increased, the largest is the reduction in damages resulting from
greenhouse gas emissions. The estimates in Table V-28 assume a social
cost of GHG emissions based on a 2.5% discount rate, and those in Table
V-29 assume a social cost of GHG emissions based on a 3% discount rate.
The associated benefits related to reduced health damages from
conventional pollutants and the benefit of improved energy security are
both significantly smaller than the associated change in GHG damages
across alternatives. As the tables also illustrate, the overwhelming
majority of both costs and benefits are private costs and benefits that
accrue to buyers of new cars and trucks, rather than external welfare
changes that affect society more generally. This has been consistently
true in CAFE rulemakings.
    The choice of discount rate also affects the resulting benefits and
costs. As the tables show, net social benefits are positive for
Alternative 1 and 2 at a 3% discount rate, but only for Alternative 1
when applying a 7% discount rate to benefits and costs. Alternative 3
has negative net benefits under both discount rates. As mentioned
above, the benefits of the regulatory alternatives, but especially
Alternative 3, are concentrated in later years where a higher discount
rate has a greater contracting effect.
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    The following tables show the costs and benefits associated with
external effects to society. As seen in Table V-28 and Table V-29, the
external benefits are composed of reduced climate damages (Table V-30
and Table V-31), reduced health damages (Table V-32 and Table V-33),
and reduced petroleum market externalities (Table V-36). The external
costs to society include congestion and noise costs (Table V-34 and
Table V-35) and safety costs (Table V-37). We show the costs and
benefits by model year (1981-2029), in contrast to the tables above,
which present incremental and net costs and benefits over the lifetimes
of the entire fleet produced through 2029, beginning with model year
1981.

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    Table V-30 and Table V-31 present the total costs of GHGs in the
baseline scenario and the incremental costs relative to the baseline in
the other three alternatives. Negative incremental values indicate a
decrease in social costs of GHGs, while positive incremental values
indicate an increase in costs relative to the baseline for the given
model year. The GHG costs follow a similar pattern in all three
alternatives, decreasing across all model years, with the largest
reductions associated with 2025-2028 model years. The magnitude of
CO2 emissions is much higher than the magnitudes of
CH4 and N2O emissions, which is why the total
costs are so much larger for CO2.
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    The CAFE Model calculates health costs attributed to criteria
pollutant emissions of NOX, SOX, and
PM2.5, shown in Table V-32 and Table V-33. These costs are
directly related to the tons of each pollutant emitted from

various upstream and downstream sources, including on-road vehicles,
electricity generation, fuel refining, and fuel transportation and
distribution. See Chapter 4 of the SEIS and Chapter 5.4 of the TSD for
further information regarding the calculations used to estimate health
impacts, and more details about the types of health effects. The
following section of the preamble, V.D, discusses the changes in tons
of emissions themselves across rulemaking alternatives, while the
current section focuses on the changes in social costs associated with
those emissions.
    Criteria pollutant health costs (presented in Table V-32 and Table
V-35) increase slightly in earlier model years (1981-2023), but those
cost increases are offset by the decrease in health costs in later
model years. In Table V-32 and Table V-33, the costs in alternatives 1-
3 are shown in terms of percent of the baseline. For instance, the
total decrease in SOX costs in Alternative 2 is equivalent
to 0.2% of the total baseline SOX costs. The changes across
alternatives relative to the baseline are relatively minor, although
some impacts in later model years are more significant (e.g., 7.5%
decrease in PM2.5 in 2028, Alternative 3). Since the health
cost value per ton of emissions differs by pollutant, the pollutants
that incur the highest costs are not necessarily those with the largest
amount of emissions.
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    NHTSA estimates social costs of congestion and noise across
regulatory alternatives, throughout the lifetimes of model years 1981-
2029. Congestion and noise are functions of VMT and fleet mix, and the
differences between alternatives are due mainly to differences in VMT
(see Section V.D). Overall, congestion and noise costs increase
relative to the baseline across all alternatives, but viewed from a
model year perspective, the congestion and noise costs associated with
later model years are negative relative to the baseline. It is
important to note that the overall increases in congestion and noise
costs are relatively small when compared to the total congestion and
noise costs in the baseline (No-Action Alternative). For further
details regarding congestion and noise costs, see Chapter 6.2.3 of the
TSD and Chapter 6.5 of the PRIA.
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    The CAFE Model accounts for benefits of increased energy security
by computing changes in social costs of petroleum market externalities.
These social costs represent the risk to the U.S. economy incurred by
exposure to price shocks in the global petroleum market that are not
accounted for by oil prices and are a direct function of gallons of
fuel consumed. Chapter 6.2.4 of the accompanying TSD describes the
inputs involved in calculating these petroleum market externality
costs. Petroleum market externality costs decrease relative to the
baseline under all alternatives, regardless of the discount rate used.
This pattern occurs due to the decrease in gallons of fuel consumed
(see Section V.D) as the stringency of alternatives increases. Only the
earlier model year cohorts (1981-2023) contribute to slight increases
in petroleum market externality costs, but these are offset by the
decreases from later model years.
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    NHTSA estimates various monetized safety impacts across regulatory
alternatives, including costs of fatalities, non-fatal crash costs, and
property damage costs. Table V-37 presents these social costs across
alternatives and discount rates. Safety effects are discussed at length
in the PRIA accompanying this NPRM (see Chapter 5 of the PRIA).

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D. Physical and Environmental Effects

    NHTSA calculates estimates for the various physical and
environmental effects associated with the proposed standards. These
include quantities of fuel and electricity consumption, tons of
greenhouse gas (GHG) emissions and criteria pollutants, and health and
safety impacts.
    In terms of fuel and electricity usage, NHTSA estimates that the
proposal would save about 50 billion gallons of gasoline and increase
electricity consumption by about 275 TWh over the lives of vehicles
produced prior to MY 2030, relative to the baseline standards (i.e.,
the No-Action Alternative). From a calendar year perspective, NHTSA's
analysis also estimates total annual consumption of fuel by the entire
on-road fleet from calendar year 2020 through calendar year 2050. On
this basis, gasoline and electricity consumption by the U.S. light-duty
vehicle fleet evolves as shown in the following two graphs, each of
which shows projections for the No-Action Alternative (Alternative 0,
i.e., the baseline), Alternative 1, Alternative 2 (the proposal), and
Alternative 3.
BILLING CODE 4910-59-P
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    NHTSA estimates the greenhouse gas emissions (GHGs) attributable to
the light-duty on-road fleet, from both vehicles and upstream energy
sector processes (e.g., petroleum refining, fuel transportation and
distribution, electricity generation). Overall, NHTSA estimates that
the proposed rule would reduce greenhouse gases by about 465 million
metric tons of carbon dioxide (CO2), about 500 thousand
metric tons of methane (CH4), and about 12 thousand tons of
nitrous oxide (N2O). The following three graphs (Figure V-5,
Figure V-6, and Figure V-7) present NHTSA's estimate of how emissions
from these three GHGs could evolve over the years. Note that these
graphs include emissions from both vehicle and upstream processes. All
three GHG emissions follow similar trends in the years between 2020-
2050.

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    The figures presented here are not the only estimates NHTSA has
calculated regarding projected GHG emissions in future years. As
discussed in Section II, the accompanying SEIS uses an
``unconstrained'' analysis as opposed to the ``standard setting''
analysis presented in this NPRM and PRIA. For more information
regarding projected GHG emissions, as well as model-based estimates of
corresponding impacts on several measures of global climate change, see
the SEIS.
    NHTSA also estimates criteria pollutant emissions resulting from
vehicle and upstream processes attributable to the light-duty on-road
fleet. NHTSA includes estimates for all of the criteria pollutants for
which EPA has issued National Ambient Air Quality Standards. Under each
regulatory alternative, NHTSA projects a dramatic decline in annual
emissions of carbon monoxide (CO), volatile organic compounds (VOC),
nitrogen oxide (NOX), and fine particulate matter
(PM2.5) attributable to the light-duty on-road fleet between
2020 and 2050. As exemplified in Figure V-8, emissions in any given
year could be very nearly the same under each regulatory alternative.
    On the other hand, as discussed in the PRIA and SEIS accompanying
this NPRM, NHTSA projects that annual SO2 emissions
attributable to the light-duty on-road fleet could increase modestly
under the action alternatives, because, as discussed above, NHTSA
projects that each of the action alternatives could lead to greater use
of electricity (for PHEVs and BEVs). The adoption of actions--such as
actions prompted by President Biden's Executive order directing
agencies to develop a Federal Clean Electricity and Vehicle Procurement
Strategy--to reduce electricity generation emission rates beyond
projections underlying NHTSA's analysis (discussed in the TSD) could
dramatically reduce SO2 emissions under all regulatory
alternatives considered here.\382\
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    \382\ E.O. 14008, 86 FR 7619 (Feb. 1, 2021), https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/27/executive-order-on-tackling-the-climate-crisis-at-home-and-abroad/,
accessed June 17, 2021.

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    Health impacts quantified by the CAFE Model include various
instances of hospital visits due to respiratory problems, minor
restricted activity days, non-fatal heart attacks, acute bronchitis,
premature mortality, and other effects of criteria pollutant emissions
on health. Figure V-11 shows the differences in select health impacts
relative to the baseline, across alternatives 1-3. These changes are
split between calendar year decades, with the largest differences
between the baseline and alternatives occurring between 2041-2050. The
magnitude of the differences relates directly to the changes in tons of
criteria pollutants emitted. See Chapter 5.4 of the TSD for information
regarding how the CAFE Model calculates these health impacts.

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    Lastly, NHTSA also quantifies safety impacts in its analysis. These
include estimated counts of fatalities, non-fatal injuries, and
property damage crashes occurring over the lifetimes of the light-duty
on-road vehicles considered in the analysis. Chapter 5 in the PRIA
accompanying this NPRM contains an in-depth discussion on the effects
of the various alternatives on these safety measures, and TSD Chapter 7
contains information regarding the construction of the safety
estimates.

E. Sensitivity Analysis

    The analysis conducted to support this proposal consists of data,
estimates, and assumptions, all applied within an analytical framework,
the CAFE Model. Just like in all past CAFE rulemakings, NHTSA
recognizes that many analytical inputs are uncertain, and some inputs
are very uncertain. Of those uncertain inputs, some are likely to exert
considerable influence over specific types of estimated impacts, and
some are likely to do so for the bulk of the analysis. Yet making
assumptions in the face of that uncertainty is necessary, if we are
going to try to analyze meaningfully the effects of something that will
happen in the future--i.e., the regulatory alternatives being
considered, that represent different possible CAFE standards for MYs
2024-2026. To get a sense of the effect that these assumptions have on
the analytical findings, we conducted additional model runs with
alternative assumptions, which explored a range of potential inputs and
the sensitivity of estimated impacts to changes in model inputs.
Sensitivity cases in this analysis span assumptions related to
technology applicability and cost, economic conditions, consumer
preferences, externality values, and safety assumptions, among
others.\383\ A sensitivity analysis can identify two critical pieces of
information: How big an influence does each parameter exert on the
analysis, and how sensitive are the model results to that assumption?
---------------------------------------------------------------------------

    \383\ In contrast to an uncertainty analysis, where many
assumptions are varied simultaneously, the sensitivity analyses
included here vary a single assumption and provide information about
the influence of each individual factor, rather than suggesting that
an alternative assumption would have justified a different preferred
alternative.
---------------------------------------------------------------------------

    That said, influence is different from likelihood. NHTSA does not
mean to suggest that any one of the sensitivity cases presented here is
inherently more likely than the collection of assumptions that
represent the reference case in the figures and tables that follow. Nor
is this sensitivity analysis intended to suggest that only one of the
many assumptions made is likely to prove off-base with the passage of
time or new observations. It is more likely that, when assumptions are
eventually contradicted by future observation (e.g., deviations in
observed and predicted fuel prices are nearly a given), there will be
collections of assumptions, rather than individual parameters, that
simultaneously require updating. For this reason, we do not interpret
the sensitivity analysis as necessarily providing justification for
alternative regulatory scenarios to be preferred. Rather, the analysis
simply provides an indication of which assumptions are most critical,
and the extent to which future deviations from central analysis

assumptions could affect costs and benefits of this proposal.
    Table V-38 lists and briefly descries the cases that we examined in
the sensitivity analysis.
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    Complete results for the sensitivity cases are summarized in
Chapter 7 of the accompanying PRIA, and detailed model inputs and
outputs for curious readers are available on NHTSA's website.\384\ For
purposes of this preamble, Figure V-12 below illustrates the relative
change of the sensitivity effect of selected inputs on the costs and
benefits that we estimate for the proposal.