1

I. What are the Agencies’ Estimated Cost, Economic, and 

Other Impacts of the Final Program?

In this section, we present the costs and impacts of the final HD National 

Program. It is important to note that NHTSA’s final fuel consumption standards and 

EPA’s final GHG emissions standards will both be in effect, and each will lead to 

average fuel efficiency increases and GHG emission reductions. The two agencies’ final 

standards comprise the HD National Program.

The net benefits of the final HD National Program consist of the effects of the 

program on: 

 the vehicle program costs (costs of complying with the vehicle CO2 standards)

 fuel savings associated with reduced fuel usage resulting from the program

 reductions in greenhouse gas emissions, 

 the reductions in other (non-GHG) pollutants, 

 costs associated with increases in noise, congestion, and accidents resulting from 

increased vehicle use, 

 improvements in U.S. energy security impacts,

 benefits associated with increased vehicle use due to the “rebound” effect. 

We also present the cost-effectiveness of the standards, or the cost per ton of 

emissions reduced. Where possible, we identify the uncertain aspects of these economic 

impacts and attempt to quantify them when/if possible (e.g., sensitivity ranges associated 

with quantified and monetized GHG impacts; probabilistic uncertainty associated with 

non-GHG health benefits). For some impacts, however, there is a lack of adequate 

information to inform a probabilistic assessment of uncertainty. EPA continues to work 

toward developing a comprehensive strategy for characterizing the aggregate impact of 

uncertainty in key elements of its analyses and we will continue to work to refine these 

uncertainty analyses in the future as time and resources permit.

The program may have other effects that are not included here. The agencies 

sought comment on whether any costs or benefits were omitted from this analysis, so that 

they could be explicitly recognized in the final rules. In particular, as discussed in 

Section III and in Chapter 2 of the RIA, the technology cost estimates developed here 

take into account the costs to hold other vehicle attributes, such as size and performance, 

constant. In addition, the analysis assumes that the full technology costs are passed along 

to vehicle buyers. With these assumptions, because welfare losses are monetary 

estimates of how much buyers would have to be compensated to be made as well off as in 

the absence of the change,1the price increase measures the loss to the buyer.2 Assuming 

 

1 This approach describes the economic concept of compensating variation, a payment of money after a 

change that would make a consumer as well off after the change as before it. A related concept, equivalent 

variation, estimates the income change that would be an alternative to the change taking place. The 

difference between them is whether the consumer’s point of reference is her welfare before the change 

(compensating variation) or after the change (equivalent variation). In practice, these two measures are 

typically very close together. 
2

that the full technology cost gets passed along to the buyer as an increase in price, the 

technology cost thus measures the welfare loss to the buyer. Increasing fuel efficiency

would have to lead to other changes in the vehicles that buyers find undesirable for there 

to be additional losses not included in the technology costs. 

The agencies sought comments, including supporting data and quantitative 

analyses, of any additional impacts of the final standards on vehicle attributes and 

performance, and other potential aspects that could positively or negatively affect the 

welfare implications of this final rulemaking, not addressed in this analysis. 

The comments received by the agencies did not provide any clear insights into 

this question. Some comments noted the diversity of the trucking industry and expressed 

a request that the program continue the great variety of options for the industry, because 

of the variation in needs for different customers. Additional comments noted that the 

separate engine and vehicle programs support the maintenance of variety and current 

market structure. Though a few commenters raised concerns, no information was offered 

to indicate that choice will in fact be limited by the program, or that other vehicle 

attributes are adversely affected.

The total monetized benefits (excluding fuel savings) under the program are 

projected to be $4.3 to $11.1 billion in 2030, depending on the value used for the social 

cost of carbon. These benefits are summarized below in Table I-3. The costs of the 

program in 2030 are estimated to be approximately $2.6 billion for new engine and truck 

technology less $20.6 billion in savings realized by trucking operations through fewer 

fuel expenditures (calculated using pre-tax fuel prices). These costs are summarized 

below in Table I-1. The present value of the total monetized benefits (excluding fuel 

savings) under the program are expected to range from $48.7 billion to $180.1 billion 

with a 3% discount rate; with a 7% discount rate, the total monetized benefits are 

expected to range from $24.3 billion to $155.7 billion. These values, summarized in 

Table I-3, depend on the value used for the social cost of carbon. The present value of 

costs of the program for new engine and truck technology, in Table I-1, are expected to 

be $47.4 billion using a 3% discount rate, and $24.7 billion with a 7% discount rate, less 

fuel savings (calculated using pre-tax fuel prices) of $375.3 billion with a 3% discount 

rate, and $166.5 billion with a 7% discount rate. Total net present benefits (in Table I-4) 

are thus expected to range from $376.6 billion to $508 billion with a 3% discount rate, 

and $166.1 billion to $297.5 billion with a 7% discount rate.

The estimates developed here are measured against a baseline fuel efficiency

associated with MY 2010 vehicles. The agencies also considered an alternate baseline 

associated with AEO 2011 projections, which is further discussed in Section IX. All 

calculations presented in Section VIII use the constant 2010 vehicle baseline. The extent 

 

2

Indeed, it is likely to be an overestimate of the loss to the buyer, because the buyer has choices other than 

buying the same vehicle with a higher price; she could choose a different vehicle, or decide not to buy a 

new vehicle. The buyer would choose one of those options only if the alternative involves less loss than 

paying the higher price. Thus, the increase in price that the buyer faces would be the upper bound of loss 

of consumer welfare, unless there are other changes to the vehicle due to the fuel economy improvements 

that make the vehicle less desirable to buyers.
3

to which fuel efficiency improvements may have occurred in the absence of the rules 

affects the net benefits associated with the program. If trucks were to install technologies 

to achieve the fuel savings and reduced GHG emissions in the absence of this program, 

then both the costs and benefits of these fuel savings could be attributed to market forces, 

not the rules. As a baseline for estimates of the extent of fuel-saving technologies that 

might have been adopted in the absence of the program, the proposal used the level of 

these technologies in MY 2010 vehicles. We sought comment on whether the agencies 

should use an alternative baseline based on data provided by commenters to estimate the 

degree to which the technologies discussed in the proposal would have been adopted in 

the absence of these rules. No comments were received on this issue. One comment cites 

the EPA draft RIA as noting a historic 1% per year improvement in fuel efficiency, and 

argues that the rules are therefore not needed; the actual figure in the draft RIA, however, 

was a 0.09% per year improvement.

EPA has undertaken an analysis of the economy-wide impacts of the final heavyduty truck fuel efficiency and GHG standards as an exploratory exercise that EPA 

believes could provide additional insights into the potential impacts of the program.3 

These results were not a factor regarding the appropriateness of the final standards. It is 

important to note that the results of this modeling exercise are dependent on the 

assumptions associated with how manufacturers would make fuel efficiency 

improvements and how trucking operations would respond to increases in higher vehicle 

costs and improved vehicle fuel efficiency as a result of the final program. 

Further information on these and other aspects of the economic impacts of our 

rules are summarized in the following sections and are presented in more detail in the 

RIA for this final rulemaking.

A. Conceptual Framework for Evaluating Impacts

This regulation is motivated primarily by the goals of reducing emissions of 

greenhouse gases and promoting U.S. energy security by reducing consumption and 

imports of petroleum-based fuels. These motivations involve classic externalities, 

meaning that private decisions do not incorporate all of the costs associated with these 

problems; these costs are not borne completely by the households or businesses whose 

actions are responsible for them. In the absence of some mechanism to “internalize” 

these costs – that is, to transfer their burden to individuals or firms whose decisions 

impose them – individuals and firms will consume more petroleum-based fuels than is 

socially optimal. Externalities are a classic motivation for government intervention in 

markets. These externalities, as well as effects due to changes in emissions of other 

pollutants and other impacts, are discussed in Sections VIII.H – VIII.K. 

In some cases, these classic externalities are by themselves enough to justify the 

costs of imposing fuel efficiency standards. For some discount rates and some projected

social costs of carbon, however, the reductions in these external costs are less than the 

 

3

See Memorandum to Docket, “Economy-Wide Impacts of Proposed Heavy-Duty Truck Greenhouse Gas 

Emissions and Fuel Efficiency Standards”, October 8, 2010. Docket EPA-HQ-OAR-2010-0162.
4

costs of new fuel saving technologies needed to meet the standards. (See Tables 9-18 and 

9-19 in the RIA.) Nevertheless, this regulation reduces trucking companies’ fuel costs; 

according to our estimates, these savings in fuel costs are by themselves sufficient to pay

for the technologies over periods of time considerably shorter than vehicles’ expected 

lifetimes under the assumptions used for this analysis (e.g., AEO 2011 projected fuel 

prices). If these estimates are correct, then the entire value of the reductions in external 

costs represents additional net benefits of the program, beyond those resulting from the 

fact that the value of fuel savings exceeds the costs of technologies necessary to achieve 

them.

It is often asserted that there are cost-effective fuel-saving technologies that 

markets do not take advantage of. This is commonly known as the “energy gap” or 

“energy paradox.” Standard economic theory suggests that in normally functioning 

competitive markets, interactions between vehicle buyers and producers would lead 

producers to incorporate all cost-effective technology into the vehicles that they offer, 

without government intervention. Unlike in the light-duty vehicle market, the vast 

majority of vehicles in the medium- and heavy-duty truck market are purchased and 

operated by businesses with narrow profit margins, and for which fuel costs represent a 

substantial operating expense. 

Even in the presence of uncertainty and imperfect information – conditions that 

hold to some degree in every market – we generally expect firms to attempt to minimize

their costs in an effort to survive in a competitive marketplace, and therefore to make 

decisions that are in the best interest of the company and its owners and/or shareholders. 

In this case, the benefits of the rules would be due exclusively to reducing the economic 

costs of externalities resulting from fuel production and consumption. However, as 

discussed below in Section VIII.E, the agencies have estimated that the application of 

fuel-saving technologies in response to the final standards would, on average, yield 

private returns to truck owners of 140% to 420% (see Table VIII-21 below). The 

agencies have also estimated that the application of these technologies would be 

significantly lower in the absence of the final standards (i.e., under the “no action” 

regulatory alternative), meaning that truck buyers and operators ignore opportunities to 

make investments in higher fuel efficiency that appear to offer significant cost savings.

As discussed in the NPRM, there are several possible explanations in the 

economics literature for why trucking companies do not adopt technologies that would be 

expected to increase their profits: there could be a classic market failure in the trucking 

industry – market power, externalities, or asymmetric or incomplete (i.e., missing market)

information; there could be institutional or behavioral rigidities in the industry (union 

rules, standard operating procedures, statutory requirements, loss aversion, etc.), whereby 

participants collectively do not minimize costs; or the engineering estimates of fuel 

savings and costs for these technologies might overstate their benefits or understate their 

costs in real-world applications.

To try to understand why trucking companies have not adopted these seemingly 

cost-effective fuel-saving technologies, the agencies surveyed published literature about 

the energy paradox, and held discussions with numerous truck market participants. The 
5

proposal discussed five categories of possible explanations derived from these sources. 

Collectively, these five hypotheses may explain the apparent inconsistency between the 

engineering analysis, which finds a number of cost-effective methods of improving fuel 

efficiency, and the observation that many of these technologies are not widely adopted. 

These hypotheses include imperfect information in the original and resale 

markets, split incentives, uncertainty about future fuel prices, and adjustment and 

transactions costs. As the discussion indicated, some of these explanations suggest 

failures in the private market for fuel-saving technology in addition to the externalities 

caused by producing and consuming fuel that are the primary motivation for the rules. 

Other explanations suggest market-based behaviors that may imply additional costs of 

regulating truck fuel efficiency that are not accounted for in this analysis. As noted 

above, an additional explanation – adverse effects on other vehicle attributes -- did not 

elicit supporting information in the public comments. Anecdotal evidence from various 

segments of the trucking industry suggests that many of the hypotheses discussed here 

may play a role in explaining the puzzle of why truck purchasers appear to under-invest 

in fuel efficiency, although different explanations may apply to different segments, or 

even different companies. The published literature does not appear to include empirical 

analysis or data related to this question.

The agencies invited comment on these explanations, and on any data or 

information that could be used to investigate the role of any or all of these five 

hypotheses in explaining this energy paradox as it applies specifically to trucks. Some 

comments expressed dissatisfaction about the explanations presented; they argued that 

these arguments were not sufficient to explain the phenomenon. These comments argued 

that the truck owners and operators are better judges of the appropriate amount of fuel 

efficiency than are government agencies; they choose not to invest because of warranted 

skepticism about these technologies. The agencies also requested comment and 

information regarding any other hypotheses that could explain the appearance that costeffective fuel-saving technologies have not been widely incorporated into trucks. The 

following discussion summarizes the fuller discussion provided in the NPRM and 

includes discussion of the comments received.

(1) Information Issues in the Original Sale Markets

One potential hypothesis for why the trucking industry does not adopt what 

appear to be inexpensive fuel saving technologies is that there is inadequate or unreliable 

information available about the effectiveness of many fuel-saving technologies for new 

vehicles. If reliable information on the effectiveness of many new technologies is absent, 

truck buyers will understandably be reluctant to spend additional money to purchase 

vehicles equipped with unproven technologies. 

This lack of information can manifest itself in multiple ways. For instance, the 

problem may arise purely because collecting reliable information on technologies is 

costly (also see Section VIII.A.5 on transaction costs). Moreover, information has 

aspects of a public good, in that no single firm has the incentive to do the costly

experimentation to determine whether or not particular technologies are cost-effective, 
6

while all firms benefit from the knowledge that would be gained from that 

experimentation. Similarly, if multiple firms must conduct the same tests to get the same 

information, costs could be reduced by some form of coordination of information 

gathering.

While its effect on information is indirect, we expect the requirement for the use 

of new technologies included in this program will circumvent these information issues, 

resulting in their adoption, thus providing more readily available information about their 

benefits. The agencies appreciate, however, that the diversity of truck uses, driving 

situations, and driver behavior will lead to variation in the fuel savings that individual 

trucks or fleets experience from using specific technologies. 

One commenter noted that the SmartWay program targets semi-truck owners and 

thus should have the largest impact on that sector, rather than vocational or medium-duty

trucks. However, the gap between actual investment in fuel efficiency and the agencies’ 

estimates of optimal investment is largest for combination tractors. Some of the 

difference in magnitude is likely to be due to the higher vehicle miles traveled for semitrucks compared to medium-duty and vocational vehicles: more driving means more fuel 

savings. Additionally, not even a majority of semi-trucks are owned by participants in 

SmartWay; non-participants are unlikely to get all the benefits of participants. Other 

explanations, noted below, are also likely to play a role. This observation may also 

suggest some limitations of improved information provision as a means of addressing the 

“efficiency gap.”

(2) Information Issues in the Resale Market

In addition to issues in the new vehicle market, a second hypothesis for why 

trucking companies may not adopt what appear to be cost-effective technologies to save 

fuel is that the resale market may not adequately reward the addition of fuel-saving 

technology to vehicles to ensure their original purchase by new truck buyers. This 

inadequate payback for users beyond the original owner may contribute to the short 

payback period that new purchasers appear to expect.4 The agencies requested data and 

information on the extent to which costs of fuel saving equipment can be recovered in the 

resale truck market. No data were received. One reviewer disputed this theory on the 

basis that people are willing to pay more for better vehicles, new or used. It is not clear, 

however, whether buyers of used vehicles can tell which are the better vehicles.5

Some of this unwillingness to pay for fuel-saving technology may be due to the 

extension of the information problems in the new vehicle market into resale markets. 

Buyers in the resale market have no more reason to trust information on fuel-saving 

technologies than buyers in the original market. Because actual fuel efficiency of trucks 

on the road depends on many factors, including geography and driving styles or habits, 

 

4

See NAS 2010, Note Error! Bookmark not defined.Error! Bookmark not defined., at p. 188.

5 Akerlof, George A. “The Market for ‘Lemons’” Quality Uncertainty and the Market Mechanism,” 

Quarterly Journal of Economics 84(3) (1970): 488-500 points out that asymmetric information – the seller 

has better information than the buyer – can potentially lead to complete failure of a market, even when both 

buyers and sellers would benefit from trade.
7

even objective sources such as logs of truck performance for used vehicles may not 

provide reliable information about the fuel efficiency that potential purchasers of used 

trucks will experience.

A related possibility is that vehicles will be used for different purposes by their 

second owners than those for which they were originally designed, and the fuel-saving 

technology is therefore of less value. 

It is possible, though, that the fuel savings experienced by the secondary

purchasers may not match those experienced by their original owners if the optimal 

secondary new use of the vehicle does not earn as many benefits from the technologies. 

One commenter asks whether the fuel-saving technology is unvalued because it is 

unproven or overrated. In that case, the premium for fuel-saving technology in the 

secondary market should accurately reflect its value to potential buyers participating in 

that market, even if it is lower than its value in the original market, and the market has 

not failed. Because the information necessary to optimize use in the secondary market 

may not be readily available or reliable, however, buyers in the resale market may have 

less ability than purchasers of new vehicles to identify and gain the advantages of new 

fuel-saving technologies, and may thus be even less likely to pay a premium for them.

For these reasons, purchasers’ willingness to pay for fuel efficiency technologies 

may be even lower in the resale market than in the original equipment market. Even 

when fuel-saving technologies will provide benefits in the resale markets, purchasers of 

used vehicles may not be willing to compensate their original owners fully for their 

remaining value. As a result, the purchasers of original equipment may expect the resale 

market to provide inadequate appropriate compensation for the new technologies, even 

when those technologies would reduce costs for the new buyers. This information issue 

may partially explain what appears to be the very short payback periods required for new 

technologies in the new vehicle market.

(3) Split Incentives in the Medium- and Heavy-Duty Truck Industry

A third hypothesis explaining the energy paradox as applied to trucking involves 

split incentives. When markets work effectively, signals provided by transactions in one 

market are quickly transmitted to related markets and influence the decisions of buyers 

and sellers in those related markets. For instance, in a well-functioning market system, 

changes in the expected future price of fuel should be transmitted rapidly to those who 

purchase trucks, who will then reevaluate the amount of fuel-saving technology to 

purchase for new vehicles. If for some reason a truck purchaser will not be directly

responsible for future fuel costs, or the individual who will be responsible for fuel costs 

does not decide which truck characteristics to purchase, then those price signals may not 

be transmitted effectively, and incentives can be described as “split.” 

One place where such a split may occur is between the owners and operators of 

trucks. Because they are generally responsible for purchasing fuel, truck operators have 

strong incentives to economize on its use, and are thus likely to support the use of fuelsaving technology. However, the owners of trucks or trailers are often different from 
8

operators, and may be more concerned about their longevity or maintenance costs than 

about their fuel efficiency, when purchasing vehicles. As a result, capital investments by

truck owners may be channeled into equipment that improves vehicles’ durability or 

reduces their maintenance costs, rather than into fuel-saving technology. If operators can 

choose freely among the trucks they drive, competition among truck owners to employ

operators would encourage owners to invest in fuel-saving technology. However, if truck 

owners have more ability to choose among operators, then market signals for improved 

fuel savings that would normally be transmitted to truck owners may be muted. Truck 

fleets that rent their vehicles may provide an example: renters may observe the cost of 

renting the truck, but not its fuel efficiency; if so, then the purchasers will aim for 

vehicles with lower costs, to lower the cost of the rental. It might be possible to test this 

theory by comparing the fuel efficiency of trucks by owner-operators with those that are 

leased by operators. The agencies have not had the data to conduct such a test.

One commenter noted that there are always tradeoffs in an investment decision: a 

purchaser may prefer to invest in other vehicle attributes than fuel efficiency. In an 

efficient market, however, a purchaser should invest in fuel-saving technology as long as 

the increase in fuel-saving technology costs less than the expected fuel savings. This 

result should hold regardless of the level of investment in other attributes, unless there are 

constraints on a purchaser’s access to investment capital. The agencies believe that truck 

fleets do have an incentive to make investments in fuel efficiency, and that this 

assumption is reflected in the regulatory analysis. The agencies also believe, however, 

that sufficient evidence suggests that truck fleets are not availing themselves of all the 

opportunities for efficiency improvements.

In addition, the NAS report notes that split incentives can arise between tractor 

and trailer operators.6 Trailers affect the fuel efficiency of shipping, but trailer owners do 

not face strong incentives to coordinate with truck owners. EPA and NHTSA are not 

regulating trailers in this action.

By itself, information provision may be inadequate to address the potential 

underinvestment in fuel efficiency resulting from such split incentives. In this setting, 

regulation may contribute to fuel savings that otherwise may be difficult to achieve.

(4) Uncertainty About Future Cost Savings

Another hypothesis for the lack of adoption of seemingly fuel saving technologies 

may be uncertainty about future fuel prices or truck maintenance costs. When purchasers 

have less than perfect foresight about future operating expenses, they may implicitly

discount future savings in those costs due to uncertainty about potential returns from 

investments that reduce future costs. In contrast, the immediate costs of the fuel-saving 

or maintenance-reducing technologies are certain and immediate, and thus not subject to 

discounting. In this situation, both the expected return on capital investments in higher 

 

6

See NAS 2010, Note Error! Bookmark not defined.Error! Bookmark not defined., at p. 182.
9

fuel efficiency and potential variance about its expected rate may play a role in a firm’s 

calculation of its payback period on such investments.

In the context of energy efficiency investments for the home, Metcalf and 

Rosenthal (1995) and Metcalf and Hassett (1995) observe that households weigh known, 

up-front costs that are essentially irreversible against an unknown stream of future fuel 

savings.7 Notably, in this situation, requiring households to adopt technologies more 

quickly may make them worse off by imposing additional risk on them.

Greene et al (2009) also finds support for this explanation in the context of lightduty fuel economy decisions: a loss-averse consumer’s expected net present value of 

increasing the fuel economy of a passenger car can be very close to zero, even if a riskneutral expected value calculation shows that its buyer can expect significant net benefits 

from purchasing a more fuel-efficient car.

8

Supporting this hypothesis is a finding by

Dasgupta et. al (2007) that consumers are more likely to lease than buy a vehicle with 

higher maintenance costs because it provides them with the option to return it before 

those costs become too high.9 However, the agencies know of no studies that have 

estimated the impact of uncertainty on perceived future savings for medium- and heavyduty vehicles.

Purchasers’ uncertainty about future fuel prices implies that mandating 

improvements in fuel efficiency can reduce the expected utility associated with truck 

purchases. This is because adopting such regulation requires purchasers to assume a 

greater level of risk than they would in its absence, even if the future fuel savings 

predicted by a risk-neutral calculation actually materialize. One commenter expressed 

support for this argument. Thus the mere existence of uncertainty about future savings in 

fuel costs does not by itself assure that regulations requiring improved fuel efficiency will 

necessarily provide economic benefits for truck purchasers and operators. On the other 

hand, because risk aversion reduces expected returns for businesses, competitive 

pressures can reduce risk aversion: risk-neutral companies can make higher average 

profits over time. Thus, significant risk aversion is unlikely to survive competitive 

pressures.

(5) Adjustment and Transactions Costs

Another hypothesis is that transactions costs of changing to new technologies 

(how easily drivers will adapt to the changes, e.g.) may slow or prevent their adoption. 

Because of the diversity in the trucking industry, truck owners and fleets may like to see 

 

7 Metcalf, G., and D. Rosenthal (1995). “The ‘New’ View of Investment Decisions and Public Policy 

Analysis: An Application to Green Lights and Cold Refrigerators,” Journal of Policy Analysis and 

Management 14: 517–531. Hassett and Metcalf (1995). “Energy Tax Credits and Residential Conservation 

Investment: Evidence from Panel Data” Journal of Public Economics 57 (1995): 201-217. Metcalf, G., and 

K. Hassett (1999). “Measuring the Energy Savings from Home Improvement Investments: Evidence from 

Monthly Billing Data.” The Review of Economics and Statistics 81(3): 516-528.

8 Greene, D., J. German, and M. Delucchi (2009). “Fuel Economy: The Case for Market Failure” in 

Reducing Climate Impacts in the Transportation Sector, Sperling, D., and J. Cannon, eds. Springer Science.

9 Dasgupta, S., S. Siddarth, and J. Silva-Risso (2007). “To Lease or to Buy? A Structural Model of a 

Consumer’s Vehicle and Contract Choice Decisions.” Journal of Marketing Research 44: 490 – 502.
10

how a new technology works in the field, when applied to their specific operations, 

before they adopt it. One commenter expressed support for this argument. If a 

conservative approach to new technologies leads truck buyers to adopt new technologies 

slowly, then successful new technologies are likely to be adopted over time without 

market intervention, but with potentially significant delays in achieving fuel saving, 

environment, and energy security benefits.

In addition, there may be costs associated with training drivers to realize the 

potential fuel savings enabled by new technologies, or with accelerating fleet operators’ 

scheduled fleet turnover and replacement to hasten their acquisition of vehicles equipped 

with new fuel-saving technologies. Here, again, there may be no market failure; 

requiring the widespread use of these technologies may impose adjustment and 

transactions costs not included in this analysis. As in the discussion of the role of risk, 

these adjustment and transactions costs are typically immediate and undiscounted, while

their benefits are future and uncertain; risk or loss aversion may further discourage 

companies from adopting new technologies.

To the extent that there may be transactions costs associated with the new 

technologies, then regulation gives all new truck purchasers a level playing field, because 

it will require all of them to adjust on approximately the same time schedule. If 

experience with the new technologies serves to reduce uncertainty and risk, the industry 

as a whole may become more accepting of new technologies. This could increase 

demand for future new technologies and induce additional benefits in the legacy fleet 

through complementary efforts such as SmartWay.

(6) Additional Hypotheses

In the public comments, two additional ideas were raised for the lack of adoption 

of what appears to be cost-effective fuel-saving technology. The first suggestion is that 

tighter diesel emissions standards caused fuel efficiency for diesel trucks to decline in the 

past decade. Because engine manufacturers would have to invest heavily (both 

financially and with personnel) in emissions reduction technologies, they would not 

invest in fuel efficiency. The costs associated with the decline in fuel efficiency due to 

the emissions regulations were accounted for in that rulemaking. 

A second suggestion is that a truck may be a “positional good” – that is, a good 

whose value depends on how it compares to the goods owned by others. If trucks confer 

status on their owners or operators, and if that status depends on easily observable 

characteristics, then owners may invest disproportionately in status-granting 

characteristics rather than less visible characteristics, such as fuel efficiency. Because 

status depends on comparisons to others, an “arms race” may develop in which all parties 

spend additional money on visible characteristics but may not manage to make 

themselves better off. In this case, regulation may improve welfare: by increasing the 

requirements for non-positional fuel efficiency, regulation could reduce expenditures 

made purely for competition rather than actual increase in welfare. In a competitive 

business, cost reduction provides a major opportunity cost to investing in status rather 
11

than in fuel-saving technology; thus, this argument may play less of a role in the heavyduty market than in the consumer market for vehicles.

Both these hypotheses leave open the question, though, why additional 

investments were not made in fuel efficiency if they would provide rapid payback. Truck 

purchasers should, in principle, be willing to buy additional fuel-saving technology as 

long as it is cost-effective, regardless of other vehicle attributes. Limited access to 

capital, if it is a problem in this sector, might provide some reason for the “crowding out” 

of the purchase of fuel-saving technology. The agencies received no comments 

indicating that constrained access to capital might explain the efficiency gap in this 

market.

(7) Summary

On the one hand, commercial vehicle operators are under competitive pressure to 

reduce operating costs, and thus their purchasers would be expected to pursue and rapidly 

adopt cost-effective fuel-saving technologies. On the other hand, the short payback 

period required by buyers of new trucks is a symptom that suggests some combination of 

uncertainty about future cost savings, transactions costs, and imperfectly functioning 

markets. In addition, widespread use of tractor-trailer combinations introduces the 

possibility that owners of trailers may have weaker incentives than truck owners or 

operators to adopt fuel-saving technology for their trailers. The market for medium- and 

heavy-duty trucks may face these problems, both in the new vehicle market and in the 

resale market.

Provision of information about fuel-saving technologies through voluntary

programs such as SmartWay will assist in the adoption of new cost-saving technologies, 

but diffusion of new technologies can still be obstructed. Those who are willing to 

experiment with new technologies expect to find cost savings, but those may be difficult 

to prove. As noted above, because individual results of new technologies vary, new truck 

purchasers may find it difficult to identify or verify the effects of fuel-saving 

technologies. Those who are risk-averse are likely to avoid new technologies out of 

concerns over the possibility of inadequate returns on the investment, or with other 

adverse impacts. Competitive pressures in the freight transport industry can provide a 

strong incentive to reduce fuel consumption and improve environmental performance. 

However, not every driver or trucking fleet operating today has the requisite ability or 

interest to access the technical information, some of which is already provided by 

SmartWay, nor the resources necessary to evaluate this information within the context of 

his or her own freight operation.

It is unclear, as discussed above, whether some or many of the technologies 

would be adopted in the absence of the program. To the extent that they would have been 

adopted, the costs and the benefits attributed to those technologies may not in fact be due 

to the program and may therefore be overstated. Both baselines used project substantially

less adoption than the agencies consider to be cost-effective. The agencies will continue 

to explore reasons for this slow adoption of cost-effective technologies.
12

Note: Text deleted for convenience

B. Summary of Costs and Benefits 

In this section, the agencies present a summary of costs, benefits, and net benefits 

of the HD National program. 

Table I-1 shows the estimated annual monetized costs of the final program for the 

indicated calendar years. The table also shows the net present values of those costs for 

the calendar years 2012-2050 using both 3 percent and 7 percent discount rates.10

Table VIII-30 shows the estimated annual monetized fuel savings of the final 

program. The table also shows the net present values of those fuel savings for the same 

calendar years using both 3 percent and 7 percent discount rates. In this table, the 

aggregate value of fuel savings is calculated using pre-tax fuel prices since savings in fuel 

taxes do not represent a reduction in the value of economic resources utilized in 

producing and consuming fuel. Note that fuel savings shown here result from reductions 

in fleet-wide fuel use. Thus, they grow over time as an increasing fraction of the fleet 

meets the 2018 standards. 

Table I-1: Estimated Monetized Costs of the Final Program (Millions, 2009$ )

a

2020 2030 2040 2050 NPV, Years

2012-2050, 3% 

Discount Rate

NPV, Years

2012-2050, 7% 

Discount Rate

Technology

Costs

$2,000 $2,200 $2,700 $3,300 $47,400 $24,700

Note:

a Technology costs for separate truck segments can be found in Section VIII.B.1.

Table I-2: Estimated Fuel Savings of the Final Program (Millions, 2009$ )

a

2020 2030 2040 2050 NPV, Years

2012-2050, 3% 

Discount Rate

NPV, Years

2012-2050, 7% 

Discount Rate

Fuel 

Savings 

(pre-tax)

$9,600 $20,600 $28,000 $36,500 $375,300 $166,500

Note:

a

Fuel savings for separate truck segments can be found in Section VIII.B.1.

Table I-3 presents estimated annual monetized benefits for the indicated calendar 

years. The table also shows the net present values of those benefits for the calendar years 

 

10 For the estimation of the stream of costs and benefits, we assume that after implementation of the final 

MY 2014-2017 standards, the 2017 standards apply to each year out to 2050.
13

2012-2050 using both 3 percent and 7 percent discount rates. The table shows the 

benefits of reduced CO2 emissions—and consequently the annual quantified benefits (i.e., 

total benefits)—for each of four SCC values estimated by the interagency working group. 

As discussed in the RIA Section 9.3, there are some limitations to the SCC analysis, 

including the incomplete way in which the integrated assessment models capture 

catastrophic and non-catastrophic impacts, their incomplete treatment of adaptation and 

technological change, uncertainty in the extrapolation of damages to high temperatures, 

and assumptions regarding risk aversion. 

In addition, these monetized GHG benefits exclude the value of net reductions in 

non-CO2 GHG emissions (CH4, N2O, HFC) expected under this action. Although EPA 

has not monetized the benefits of reductions in non-CO2 GHGs, the value of these 

reductions should not be interpreted as zero. Rather, the net reductions in non-CO2

GHGs will contribute to this program’s climate benefits, as explained in Section VI.C. 

Table I-3: Monetized Benefits Associated with the Final Program (Millions, 2009$)

2020 2030 2040 2050 NPV, Years 

2012-2050, 

3% Discount 

Ratea

NPV, Years 

2012-2050, 

7% Discount 

Ratea

Reduced CO2 Emissions at each assumed SCC value b

5% (avg SCC) $300 $700 $1,200 $1,700 $9,000 $9,000

3% (avg SCC) $1,000 $2,500 $3,600 $4,800 $46,100 $46,100

2.5% (avg SCC) $1,600 $3,800 $5,400 $7,000 $78,000 $78,000

3% (95th 

percentile)

$3,100 $7,500 $11,100 $14,600 $140,400 $140,400

Energy Security 

Impacts (price 

shock)

$500 $1,100 $1,500 $1,700 $19,800 $8,800

Accidents, 

Congestion, Noise

-$200 -$400 -$600 -$600 -$7,900 -$3,700

Refueling Savings $100 $100 $200 $200 $2,500 $1,100

Non-GHG Impacts 

c,d

B $2,800 $2,800 $2,800 $25,300 $9,100

Non-CO2 GHG 

Impactse

n/a n/a n/a n/a n/a n/a

Total Annual Benefits at each assumed SCC value b

5% (avg SCC) $700 $4,300 $5,100 $5,800 $48,700 $24,300

3% (avg SCC) $1,400 $6,100 $7,500 $8,900 $85,800 $61,400

2.5% (avg SCC) $2,000 $7,400 $9,300 $11,100 $117,700 $93,300

3% (95th percentile) $3,500 $11,100 $15,000 $18,700 $180,100 $155,700

Notes:

a Net present value of reduced CO2 emissions is calculated differently than other benefits. The same 

discount rate used to discount the value of damages from future emissions (SCC at 5, 3, 2.5 percent) is used 

to calculate net present value of SCC for internal consistency. Refer to the SCC TSD for more detail. 
14

b

Section VIII.G notes that SCC increases over time. Corresponding to the years in this table, the SCC 

estimates range as follows: for Average SCC at 5%: $5-$16; for Average SCC at 3%: $22-$46; for 

Average SCC at 2.5%: $36-$66; and for 95th percentile SCC at 3%: $66-$139. See Section VIII.F.

c Note that “B” indicates unquantified criteria pollutant benefits in the year 2020. For the analysis of the 

final program, we only modeled the rule’s PM2.5- and ozone-related impacts in the calendar year 2030. For 

the purposes of estimating a stream of future-year criteria pollutant benefits, we assume that the benefits 

out to 2050 are equal to, and no less than, those modeled in 2030 as reflected by the stream of estimated 

future emission reductions. The NPV of criteria pollutant-related benefits should therefore be considered a 

conservative estimate of the potential benefits associated with the final program.

d Non-GHG-related health and welfare impacts (related to PM2.5 and ozone exposure) range between $1,300 

and $4,200 million in 2030, 2040, and 2050. $2,800 was chosen as the mid-point of this range for the 

purposes of estimating total benefits across all monetized categories.

e The monetized GHG benefits presented in this analysis exclude the value of changes in non-CO2 GHG 

emissions expected under this program (See RIA Chapter 5). Although EPA has not monetized changes in 

non-CO2 GHGs, the value of any increases or reductions should not be interpreted as zero. 

Table I-4 presents estimated annual net benefits for the indicated calendar years. 

The table also shows the net present values of those net benefits for the calendar years 

2012-2050 using both 3 percent and 7 percent discount rates. The table includes the 

benefits of reduced CO2 emissions (and consequently the annual net benefits) for each of 

four SCC values considered by EPA. 

Table I-4: Monetized Net Benefits Associated with the Final Program (Millions, 2009$)

2020 2030 2040 2050 NPV, 3%a NPV, 7%a

Total Technology

Costs

$2,000 $2,200 $2,700 $3,300 $47,400 $24,700

Total Fuel Savings $9,600 $20,600 $28,000 $36,500 $375,300 $166,500

Total Annual Benefits at each assumed SCC value b

5% (avg SCC) $700 $4,300 $5,100 $5,800 $48,700 $24,300

3% (avg SCC) $1,400 $6,100 $7,500 $8,900 $85,800 $61,400

2.5% (avg SCC) $2,000 $7,400 $9,300 $11,100 $117,700 $93,300

3% (95th 

percentile)

$3,500 $11,100 $15,000 $18,700 $180,100 $155,700

Monetized Net Benefits at each assumed SCC value c

5% (avg SCC) $8,300 $22,700 $30,400 $39,000 $376,600 $166,100

3% (avg SCC) $9,000 $24,500 $32,800 $42,100 $413,700 $203,200

2.5% (avg SCC) $9,600 $25,800 $34,600 $44,300 $445,600 $235,100

3% (95th 

percentile)

$11,100 $29,500 $40,300 $51,900 $508,000 $297,500

Notes: 

a Net present value of reduced CO2 emissions is calculated differently than other benefits. The same 

discount rate used to discount the value of damages from future emissions (SCC at 5, 3, 2.5 percent) is used 

to calculate net present value of SCC for internal consistency. Refer to the SCC TSD for more detail.

b

Section VIII.G notes that SCC increases over time. Corresponding to the years in this table, the SCC 

estimates range as follows: for Average SCC at 5%: $5-$16; for Average SCC at 3%: $22-$46; for 

Average SCC at 2.5%: $36-$66; and for 95th percentile SCC at 3%: $66-$139. Section VIII.G also 

presents these SCC estimates.

c Net Benefits equal Fuel Savings minus Technology Costs plus Benefits.
15

EPA also conducted a separate analysis of the total benefits over the model year 

lifetimes of the 2014 through 2018 model year trucks. In contrast to the calendar year 

analysis presented above in Table I-1 through Table I-4, the model year lifetime analysis 

below shows the impacts of the final program on vehicles produced during each of the 

model years 2014 through 2018 over the course of their expected lifetimes. The net 

societal benefits over the full lifetimes of vehicles produced during each of the five model 

years from 2014 through 2018 are shown in Table I-5 and Table I-6 at both 3 percent and 

7 percent discount rates, respectively. 

Table I-5: Monetized Fuel Savings, Technology Costs, Benefits, and Net Benefits Associated with the 

Lifetimes of 2014-2018 Model Year Trucks (Millions, 2009$; 3% Discount Rate)

2014

MY

2015

MY

2016

MY

2017

MY

2018

MY

Sum

Technology -$1,600 -$1,400 -$1,500 -$1,600 -$2,000 -$8,100

Fuel Savings (pre-tax) $9,300 $8,300 $8,100 $11,500 $12,900 $50,100

Energy Security 

Impacts (price shock)

$500 $400 $400 $600 $700 $2,700

Accidents, 

Congestion, Noise

-$300 -$300 -$300 -$300 -$300 -$1,500

Refueling Savings $60 $60 $60 $80 $100 $400

Non-CO2 GHG 

Impacts and NonGHG Impacts c,d

n/a n/a n/a n/a n/a n/a

Reduced CO2 Emissions at each assumed SCC value a, b

5% (avg SCC) $200 $200 $200 $300 $300 $1,200

3% (avg SCC) $1,100 $900 $900 $1,300 $1,500 $5,700

2.5% (avg SCC) $1,800 $1,600 $1,500 $2,100 $2,400 $9,400

3% (95th percentile) $3,300 $2,900 $2,800 $4,000 $4,500 $17,000

Monetized Net Benefits at each assumed SCC value a, b

5% (avg SCC) $8,200 $7,300 $7,000 $10,600 $11,700 $44,800

3% (avg SCC) $9,100 $8,000 $7,700 $11,600 $12,900 $49,300

2.5% (avg SCC) $9,800 $8,700 $8,300 $12,400 $13,800 $53,000

3% (95th percentile) $11,300 $10,000 $9,600 $14,300 $15,900 $60,600

Notes: 

a Net present value of reduced CO2 emissions is calculated differently than other benefits. The same 

discount rate used to discount the value of damages from future emissions (SCC at 5, 3, 2.5 percent) is used 

to calculate net present value of SCC for internal consistency. Refer to the SCC TSD for more detail. 

b

Section VIII.G notes that SCC increases over time. Corresponding to the years in this table, the SCC 

estimates range as follows: for Average SCC at 5%: $5-$16; for Average SCC at 3%: $22-$46; for 

Average SCC at 2.5%: $36-$66; and for 95th percentile SCC at 3%: $66-$139. Section VIII.G also 

presents these SCC estimates.

c The monetized GHG benefits presented in this analysis exclude the value of changes in non-CO2 GHG 

emissions expected under this action (see RIA Chapter 5). Although EPA has not monetized changes in 

non-CO2 GHGs, the value of any increases or reductions should not be interpreted as zero. 

d Due to analytical and resource limitations, MY non-GHG emissions (direct PM, VOCs, NO2 and SO2) 

were not estimated for this analysis.
16

Table I-6: Monetized Fuel Savings, Technology Costs, Benefits, and Net Benefits Associated with the 

Lifetimes of 2014-2018 Model Year Trucks (Millions, 2009$; 7% Discount Rate)

2014 

MY

2015 

MY

2016 

MY

2017 

MY

2018 

MY

Sum

Technology -$1,600 -$1,400 -$1,500 -$1,600 -$2,000 -$8,100

Fuel Savings (pre-tax) $6,900 $5,900 $5,600 $7,600 $8,300 $34,400

Energy Security Impacts 

(price shock)

$400 $300 $300 $400 $400 $1,800

Accidents, Congestion, 

Noise

-$200 -$200 -$200 -$200 -$200 -$1,000

Refueling Savings $50 $40 $40 $60 $60 $200

Non-CO2 GHG Impacts and 

Non-GHG Impacts c,d

n/a n/a n/a n/a n/a n/a

Reduced CO2 Emissions at each assumed SCC value a, b

5% (avg SCC) $200 $200 $200 $300 $300 $1,200

3% (avg SCC) $1,100 $900 $900 $1,300 $1,500 $5,700

2.5% (avg SCC) $1,800 $1,600 $1,500 $2,100 $2,400 $9,400

3% (95th percentile) $3,300 $2,900 $2,800 $4,000 $4,500 $17,000

Monetized Net Benefits at each assumed SCC value a, b

5% (avg SCC) $5,800 $4,800 $4,400 $6,600 $6,900 $28,500

3% (avg SCC) $6,700 $5,500 $5,100 $7,600 $8,100 $33,000

2.5% (avg SCC) $7,400 $6,200 $5,700 $8,400 $9,000 $36,700

3% (95th percentile) $8,900 $7,500 $7,000 $10,300 $11,100 $44,300

Notes: 

a Net present value of reduced CO2 emissions is calculated differently than other benefits. The same 

discount rate used to discount the value of damages from future emissions (SCC at 5, 3, 2.5 percent) is used 

to calculate net present value of SCC for internal consistency. Refer to the SCC TSD for more detail. 

b

Section VIII.G notes that SCC increases over time. Corresponding to the years in this table, the SCC 

estimates range as follows: for Average SCC at 5%: $5-$16; for Average SCC at 3%: $22-$46; for 

Average SCC at 2.5%: $36-$66; and for 95th percentile SCC at 3%: $66-$139. Section VIII.G also 

presents these SCC estimates.

c The monetized GHG benefits presented in this analysis exclude the value of changes in non-CO2 GHG 

emissions expected under this action (see RIA Chapter 5). Although EPA has not monetized changes in 

non-CO2 GHGs, the value of any increases or reductions should not be interpreted as zero. 

d Due to analytical and resource limitations, MY non-GHG emissions (direct PM, VOCs, NO2 and SO2) 

were not estimated for this analysis.

C. Employment Impacts

(1) Introduction

Although analysis of employment impacts is not part of a cost-benefit analysis 

(except to the extent that labor costs contribute to costs), employment impacts of federal 

rules are of particular concern in the current economic climate of sizeable unemployment. 

The recently issued Executive Order 13563, “Improving Regulation and Regulatory 

Review” (January 18, 2011), states, “Our regulatory system must protect public health, 

welfare, safety, and our environment while promoting economic growth, innovation, 
17

competitiveness, and job creation” (emphasis added). Although EPA and NHTSA did 

not undertake an employment analysis of the proposed rules, several commenters 

suggested that we undertake an employment analysis for the final rulemaking. Consistent 

with Executive order 13563, we have provided a discussion of the potential employment 

impacts of the Heavy-Duty National Program. 

Our general conclusion is that employment impacts in the regulated sector (truck 

and engine manufacturing) and the parts sectors are likely to be positive; effects on 

employment in the transport and shipping sectors are ambiguous; the fuel supplying 

sectors may face reduced employment; and there may be increased general employment 

due to reduction in costs that may be passed along to the transport industry and thus to 

the public. Because we did not include employment analysis in the NPRM and provide 

opportunity for public comment on the methods, we here present a qualitative discussion. 

Because the discussion is qualitative, we do not sum the net effects on employment in the 

economy. 

When the economy is at full employment, an environmental regulation is unlikely 

to have much impact on net overall U.S. employment; instead, labor would primarily be 

shifted from one sector to another. These shifts in employment impose an opportunity

cost on society, approximated by the wages of the employees, as regulation diverts 

workers from other activities in the economy.

11

 In this situation, any effects on net 

employment are likely to be transitory as workers change jobs. For example, some 

workers may need to be retrained or require time to search for new jobs, while shortages 

in some sectors or regions could bid up wages to attract workers.

12

It is also true that, if a regulation comes into effect during a period of high 

unemployment, a change in labor demand due to regulation may affect net overall U.S. 

employment because the labor market is not in equilibrium. Either negative or positive 

effects are possible. Schmalansee and Stavins13 point out that net positive employment 

effects are possible in the near term when the economy is at less than full employment 

due to the potential hiring of idle labor resources by the regulated sector to meet new 

requirements (e.g., to install new equipment) and new economic activity in sectors related 

to the regulated sector. In the longer run, the net effect on employment is more difficult to 

predict and will depend on the way in which the related industries respond to the 

regulatory requirements. As Schmalansee and Stavins note, it is possible that the 

magnitude of the effect on employment could vary over time, region, and sector, and 

positive effects on employment in some regions or sectors could be offset by negative 

effects in other regions or sectors. For this reason, they urge caution in reporting partial 

employment effects since it can “paint an inaccurate picture of net employment impacts if 

not placed in the broader economic context.” 

 

11 Schmalensee, Richard, and Robert N. Stavins. “A Guide to Economic and Policy Analysis of EPA’s 

Transport Rule.” White paper commissioned by Excelon Corporation, March 2011.

12 Although the employment level would not change substantially, there would be costs to the workers

associated with shifting from one activity to another. Jacobson, Louis S., Robert J. LaLonde, and Daniel G. 

Sullivan, “Earnings Losses of Displaced Workers.” American Economic Review 83(4) (1993): 685-709.

13 Ibid.
18

This rulemaking is expected to have a relatively small effect on net employment 

in the United States through the regulated sector – the truck and engine manufacturer 

industry – and several related sectors, specifically, industries that supply the truck and 

engine manufacturing industry (e.g., truck parts), the trucking industry itself, other 

industries involved in transporting goods (e.g., rail and shipping), the petroleum refining 

sector, and the retail sector. According to the U.S. Bureau of Labor Statistics, about 1.25 

million people were employed in the truck transportation industry and about 675,000 

people were employed in the motor vehicle parts industry between 2010 and 2011.14 

Although heavy-duty vehicles (HD) account for approximately 4% of the vehicles on the 

road, these vehicles consume more than 20% of on-road gasoline and diesel fuel use. As 

discussed in Chapter 5 of this RIA, this rulemaking is predicted to reduce the amount of 

fuel these vehicles use, and thus affect the petroleum refinery industry. The petroleum 

refinery industry employed about 65,000 people in the U.S. in 2009, the most recent year 

that employment estimates are available for this sector.15 As discussed in Chapter 5 of 

this RIA, this rulemaking is predicted to reduce the amount of fuel these vehicles use, and 

thus affect the petroleum refinery industry. The petroleum refinery industry employed 

about 65,000 people in the U.S. in 2009, the most recent year that employment estimates 

are available for this sector.16 Finally, since the net reduction in cost associated with 

these rules is expected to lead to lower transportation and shipping costs, in a competitive 

market a substantial portion of those cost savings will be passed along to consumers, who 

then will have additional discretionary income (how much of the cost is passed along to 

consumers depends on market structure and the relative price elasticities). 

Several commenters suggested that the HD vehicle rules would lead to an increase 

in employment in affected sectors by offering the potential for new employment 

opportunities in the design and production of new vehicle technologies. Also, these 

commenters suggested that since the U.S. manufacturers and suppliers are leaders in 

certain advanced truck technologies, this program has the potential to help them 

consolidate their leadership and thrive in a global market. In this context, several 

commenters referred to an assessment by the Union of Concerned Scientists (UCS) and 

CalStart of the economic and employment benefits of the improved efficiency in HD 

vehicles.17 The study predicts an increase of tens of thousands of jobs between 2020 and 

2030, as result of higher fuel efficiency for HD vehicles. These quantitative estimates 

were derived using a standard input-output model, though the estimates themselves have 

not yet been peer reviewed. Input-output (I/O) models do not account for opportunity

costs of labor – that is, all employment needs due to the regulatory change will be met by

unemployed workers. In addition, I/O models assume no changes in the average use of 

 

14 U.S. Bureau of Labor Statistics seasonally-adjusted Current Employment Statistics Survey for the Truck 

Transportation Industry (NAICS 484) and the Motor Vehicle Parts Manufacturing Industry (NAICS 3363).

16 U.S. Census Bureau, 2009 Annual Survey of Manufactures, Published December 3, 2010.

16 U.S. Census Bureau, 2009 Annual Survey of Manufactures, Published December 3, 2010.

17 Union of Concerned Scientists and CalStart, Delivering Jobs: The Economic Costs and Benefits of 

Improving Fuel Economy of Heavy Duty Vehicles, July, 2010. http://www.ucsusa.org/deliveringjobs.
19

labor per dollar of output in the affected sectors. For these and other reasons, these may

at best be considered an imprecise upper bound on actual employment impacts.18

Determining the direction of employment effects even in the regulated industry

may be difficult due to the presence of competing effects that lead to an ambiguous 

adjustment in employment as a result of environmental regulation. Morgenstern, Pizer 

and Shih19 identify three separate ways that employment levels may change in the 

regulated industry in response to a new (or more stringent) regulation. 

 Demand effect: higher production costs due to the regulation will lead to higher 

market prices; higher prices in turn reduce demand for the good, reducing the 

demand for labor to make that good. In the authors’ words, the ““extent of this effect 

depends on the cost increase passed on to consumers as well as the demand elasticity

of industry output”.

 Cost effect: As costs go up, plants add more capital and labor (holding other factors 

constant), with potentially positive effects on employment; in the authors’ words, as 

“production costs rise, more inputs, including labor, are used to produce the same 

amount of output”.

 Factor-shift effect: post-regulation production technologies may be more or less 

labor-intensive (i.e., more/less labor is required per dollar of output). In the authors’ 

words, “environmental activities may be more labor intensive than conventional 

production,” meaning that “the amount of labor per dollar of output will rise,” though 

it is also possible that “cleaner operations could involve automation and less 

employment, for example”.

The “demand effect” is expected to have a negative effect on employment, the “cost 

effect” to have a positive effect on employment, and the “factor-shift effect” has an 

ambiguous effect on employment. Without more information with respect to the 

magnitudes of these competing effects, it is not possible to predict the total effect 

environmental regulation will have on employment levels in a regulated sector

Morgenstern et al. estimated the effects on employment of spending on pollution 

abatement for four highly polluting/regulated industries (pulp and paper, plastics, steel, 

and petroleum refining). They conclude that increased abatement expenditures generally 

have not caused a significant change in employment in those sectors. More specifically, 

their results show that, on average across the industries studied, each additional $1 

million spent on pollution abatement results in a (statistically insignificant) net increase 

of 1.5 jobs. While the specific sectors Morgenstern et al. examined are different than the 

sectors considered here, the methodology that Morgenstern et al. developed is useful in 

this context.

 

18 Berck, Peter, and Sandra Hoffman. “Assessing the Employment Impacts of Environmental and Natural 

Resource Policy.” Environmental and Resource Economics 22 (2002): 133-156.

19 Morgenstern, Richard D., William A. Pizer, and Jhih-Shyang Shih. “Jobs Versus the Environment: An 

Industry-Level Perspective.” Journal of Environmental Economics and Management 43 (2002): 412-436.
20

(2) Overview of Affected Sectors

The above discussion focuses on employment changes in the regulated sector, but 

the regulated sector is not the only source of changes in employment. In these rules, the 

regulated sectors are truck and engine manufacturers; they are responsible for meeting the 

standards set in these rules. The effects of these rules are also likely to have impacts 

beyond the directly regulated sector. Some of the related sectors which these rules are 

also likely to impact include: motor vehicle parts producers, to the extent that the truck 

and engine industries purchase components rather than manufacture them in-house; 

shipping and transport, because many companies in this sector purchase trucks and their 

operating costs will be affected by both higher truck prices and fuel savings; oil refineries 

due to reduced demand for petroleum-based fuels; and the final retail market, which is 

where any net cost reductions due to fuel savings are ultimately expected to be 

experienced. We acknowledge that there may be impacts in other sectors that are not 

discussed here, but we have sought to include the sectors where we think the impacts are 

most direct. The following discussion describes the direction of impacts on employment 

in these industries. The effects of the HD rule on net U.S. employment depend, not only

on their relative magnitudes, but also on employment levels in the overall economy. As 

previously discussed, in a full-employment economy these sector-specific impacts will be 

mostly offset by employment changes elsewhere in the economy and would not be 

expected to result in a net change in jobs. However, in an economy with significant 

unemployment these changes may affect net employment in the U.S.

(a) Truck and Engine Manufacturers

The regulated sector consists of truck and engine manufacturers. Employment 

associated with manufacturing trucks and engines may be affected by the demand, cost, 

and factor-shift effects. 

Demand Effect

The demand effect depends on the effects of this rulemaking on HD vehicle sales. 

If vehicle sales increase, then more people will be required to assemble trucks and their 

components. If vehicle sales decrease, employment associated with these activities will 

decrease. The effects of this rulemaking on HD vehicle sales depend on the perceived 

desirability of the new vehicles. Unlike in Morgenstern et al.’s study, where the demand 

effect decreased employment, there are countervailing possibilities in the HD market due 

to the fuel savings resulting from this program. On one hand, this rulemaking will 

increase vehicle costs; by itself, this effect would reduce vehicle sales. On the other 

hand, this rulemaking will reduce the fuel costs of operating the vehicle; by itself, this 

effect would increase vehicle sales, especially if potential buyers have an expectation of 

higher fuel prices. The agencies have not made an estimate of the potential change in 

vehicle sales. However as discussed in Preamble Section VIII.E.5 the agencies have 

estimated an increase in vehicle miles traveled (i.e., VMT rebound) due to the reduced 

operating costs of trucks meeting these new standards. Since increased VMT is most 

likely to be met with more drivers and more trucks, our projection of VMT rebound is 

suggestive of an increase in vehicle sales and truck driver employment (recognizing that 
21

these increases may be partially offset by a decrease in manufacturing and sales for 

equipment of other modes of transportation such as rail cars or barges). 

As discussed above in Section VIII.A, the agencies find that the reduction in fuel 

costs associated with this rulemaking outweigh the increase in vehicle cost. This finding 

is puzzling: market forces should lead truck manufacturers and buyers to install all costeffective fuel-saving technology, but the agencies find that they have not. Section VIII.A 

discusses various hypotheses that have been suggested to explain this phenomenon. 

Some of the explanations suggest that vehicle manufacturers and buyers will benefit from 

the rulemaking, and vehicle sales will increase; others suggest that the opposite might 

occur. The agencies do not have strong evidence supporting one specific explanation 

over another. However, some in the heavy-duty industry indicate the potential for an 

increase in jobs. As stated by Tom Linebarger (President and Chief Operating Officer of 

Cummins) and Fred Krupp (President of the Environmental Defense Fund), "Finally, 

strong environmental standards play a crucial role in getting innovations to market that 

will create economic opportunity for American companies and jobs for American 

workers. . . . It helps that Cummins and other forward-thinking businesses view this as an 

opportunity to innovate and increase international market share."20

One commenter raised the issue of whether there could be a loss of recreation 

vehicle (RV) industry jobs due to a reduction in the sales of motor homes and towable 

RVs. As mentioned above, the effects of this rulemaking on HD vehicle sales depend on 

the desirability of the new vehicles. 

Cost Effect

The truck and engine manufacturing sector has great flexibility in how to respond 

to the requirement for reduced greenhouse gases and increasing fuel efficiency, with a 

broad suite of technologies being available to achieve the standards. These technologies 

are described in detail in Chapter 2 of this RIA. Among these technologies, a distinction 

can be made between technologies that can be “added on” to conventional trucks versus 

those that replace features of a conventional truck. “Added on” features require 

additional labor to install the technologies on trucks, thus clearly increasing labor demand 

(the “cost effect”). 

Factor-Shift Effect

For “replacement” technologies, the predicted impact on labor demand from 

regulation depends on the change in the amount of labor used to build and install one type 

of technology compared to another. In many cases, the new technologies are predicted to 

be more complex than the existing technologies and are therefore likely to require 

additional labor installation inputs. In other cases, the opposite may be true.

 

20 Tom Linebarger (President and Chief Operating Officer of Cummins) and Fred Krupp (President of the 

Environmental Defense Fund), "Clear rules can create better engines, clean air," Indianapolis Star, October 

28, 2010, p. 19; included as part of Cummins' comments on the rule, Docket Number EPA-HQ-OAR-2010-

0162-1765.1[1]
22

Most of the technologies that are expected to be used to meet these standards are 

replacement technologies. For example, almost all of the engine improvements involve 

replacement technologies that are not expected to significantly change the labor 

requirements. Similarly, regulations of the chassis on vocational vehicles will only

require the installation of a different type of tire, which is also not expected to have large 

labor intensity impacts. Therefore, the potential magnitude of the factor shift effect is 

expected to be relatively small, though slightly positive due to the additional labor needed 

to install more complex technologies. 

Summary for the Truck and Engine Manufacturing Sector

For the truck and engine manufacturing sector, the demand effect may result in 

either increased or decreased employment; the cost effect is expected to increase 

employment; and the factor-shift effect may have a slightly positive effect on 

employment in this sector. 

(b) Motor Vehicle Parts Manufacturing Sector

Some vehicle parts are made in-house and would be included directly in the 

regulated sector. Others are made by independent suppliers and are not directly 

regulated, but they will be affected by the rules as well. The parts manufacturing sector 

will be involved primarily in providing “add-on” parts, or components for replacement 

parts built internally. Because demand for these parts is expected to increase, 

employment effects in this sector are expected to be positive.

(c) Transport and Shipping Sectors

Although not directly regulated by these rules, employment effects in the 

transport and shipping sector are likely to result from these regulations. If the overall 

cost of shipping a ton of freight decreases because of increased fuel efficiency (taking 

into account the increase in upfront purchasing costs), in a perfectly competitive industry

these costs savings will be passed along to customers. With lower prices, demand for 

shipping would lead to an increase in demand for truck shipping services (consistent with 

the VMT rebound effect analysis) and therefore an increase in employment. In addition, 

if the relative cost of shipping freight via trucks becomes cheaper than shipping by other 

modes (e.g., rail or barge), then employment in the truck transport industry is likely to 

increase. To the extent that the trucking industry is more labor intensive than other 

modes, we would expect this effect to lead to an overall increase in employment in the 

transport and shipping sectors.21,22

 

21 American Transportation Research Institute, “An Analysis of the Operational Costs of Trucking: 2011 

Update.” See http://www.atrionline.org/research/results/Op_Costs_2011_Update_one_page_summary.pdf. 

22 Association of American Railroads, “All Inclusive Index and Rail Adjustment Factor.” June 3, 2011. See 

http://www.aar.org/~/media/aar/RailCostIndexes/AAR-RCAF-2011-Q3.ashx
23

(d) Fuel Suppliers

In addition to the effects on the trucking industry and related truck parts sector, 

these rules will result in reductions in fuel use that lower GHG emissions. Fuel saving, 

principally reductions in liquid fuels such as diesel and gasoline, will affect employment 

in the fuel suppliers industry sectors, principally the Petroleum Refinery sector.23 

Expected fuel consumption reductions by fuel type, and by heavy-duty vehicle 

type, can be found in Table VIII-7. These reductions reflect impacts from the new fuel 

efficiency and GHG standards and include increased consumption from the rebound 

effect. These fuel savings are monetized in Table VIII-8 by multiplying the reduced fuel 

consumption in each year by the corresponding estimated average fuel price in that year, 

using the Reference Case from the AEO 2011. In 2014, the pre-tax fuel savings is $1.2 

billion (2009$). While these figures represent a level of fuel savings for purchasers of 

fuel, it also represents a loss in value of output for the petroleum refinery industry. Since 

50 percent of the fuel would have been refined in the U.S., the loss in output to the U.S. 

Petroleum Refinery sector is $600 million (2009$), which will result in reduced sectoral 

employment.24 Because this sector is very capital-intensive, the employment effect is not 

expected to be large.

(e) Fuel Savings

As a result of this rulemaking, it is anticipated that trucking firms will experience 

fuel savings. Fuel savings lower the costs of transportation goods and services. In a 

competitive market, the fuel savings that initially accrue to trucking firms are likely to be 

passed along as lower transportation costs that, in turn, could result in lower prices for 

final goods and services. In either case, the savings will accrue to some segment of 

consumers: either owners of trucking firms or the general public. In both cases, the effect 

will be increased spending by consumers in other sectors of the economy, creating jobs in 

a diverse set of sectors, including retail and service industries. 

As mentioned above, the value of fuel savings from this rulemaking is projected 

to be $1.2 billion (2009$) in 2014, according to Table VIII-8. If all those savings are 

spent by consumers or trucking firm owners, the fuel savings will stimulate increased

employment in the economy through those expenditures. If the fuel savings accrue 

primarily to firm owners, they may either reinvest the money or take it as profit. 

Reinvesting the money in firm operations would increase employment directly. If they

take the money as profit, to the extent that these owners are wealthier than the general 

 

23 North American Industry Classification System (NAICS) Code 32411.

24 EPA and NHTSA estimate that approximately 50 percent of the reduction in fuel consumption resulting 

from adopting improved fuel GHG standards and fuel efficiency standards is likely to be reflected in 

reduced U.S. imports of refined fuel, while the remaining 50 percent is expected to be reflected in reduced 

domestic fuel refining. Of this latter figure, 90 percent is anticipated to reduce U.S. imports of crude 

petroleum for use as a refinery feedstock, while the remaining 10 percent is expected to reduce U.S. 

domestic production of crude petroleum. Because we do not expect to see a significant reduction in crude 

oil production in the U.S., we do not expect this rule to have a significant impact on the Oil and Gas 

Extraction industry sector in the U.S. (NAICS 211000). For more information, refer to Section VIII-I on 

the energy security impacts from the program.
24

public, they may spend less of the savings, and the resulting employment impacts would 

be smaller than if the savings went to the public.

(3) Summary

The net employment effects of this rulemaking are expected to be found 

throughout several key sectors: truck and engine manufacturers, the trucking industry, 

truck parts manufacturing, fuel production, and consumers. For the regulated sector, the

demand effect may result in either increased or decreased employment, depending on the 

net effect on HD vehicle sales. The cost effect is expected to increase employment in the 

regulated sector; and the factor-shift effect may have a slightly positive effect on 

employment, though we cannot definitively say this is the case without quantification. 

Increased expenditures by truck and engine manufacturers are expected to require 

increased labor to build parts, though this effect also depends on any changes in the labor 

intensity of production; increased complexity of technologies may imply increased labor 

inputs. It is possible, if access to capital markets is limited, that this rule might displace 

other HD sector investment, which would reduce employment associated with those 

activities. Lower prices for shipping are expected to lead to an increase in demand for 

truck shipping services and, therefore, an increase in employment, though this effect may

be offset somewhat by changes in employment in other shipping sectors. Reduced fuel 

production implies less employment in the fuel provision sectors. Finally, any net cost 

savings would be expected to be passed along to some segment of consumers: either the 

general public or the owners of trucking firms, who are expected then to increase 

employment through their expenditures. Given the job creation as a result of the $1.2B 

(2009$) in fuel savings in 2014 and the possible employment increases in the 

manufacturing and parts sectors, we find it highly unlikely that there would be significant 

net job losses related to this policy. Given the current level of unemployment, net 

positive employment effects are possible, especially in the near term, due to the potential 

hiring of idle labor resources by the regulated sector to plan for and meet new 

requirements. In the future, when full employment is expected to return, any changes in 

employment levels in the regulated sector due to this program are mostly expected to be 

offset by changes in employment in other sectors.