1



## I. **What ar e the**  **Agencies ’**  **Estim ated 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 compl yi ng with the vehicle CO 2 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” effec t. 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 ass ociated 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 t o 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 permi t. The progr am may

have other effects that are not included here. The agencies sought comment on whether an y 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 anal ys is assumes that the full technology costs are passed al ong 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, 1 the 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 woul d 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 ty pically 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 und esirable for there to be additional losses not included in the technology costs. The agencies sought comments, including supporting data and quantitative anal ys es, of any

additional impacts of the final standards on vehicle attributes and performance, an d other potential aspects that could positively or negatively affect the welfare implications of this final rulemaking, not addressed in this anal ys is. 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 engi ne 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 p re - 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. Th e 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 a gencies also considered an alternate baseline associated with AEO 2011 projections, which is further discussed in S ection IX. All calculations presented in S ection V III 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 pri ce. 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

improve ments may

have occurred in the absence of the rules affects the net benefits associated with the program. I f 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 absen ce of these rules. No comments were received on this issue. One comment cites the EPA draft RIA as noting a historic 1% per ye ar improvement in fuel efficiency , and argues that the rules are therefore not needed; the actual figure in the draft RIA, howeve r, was a 0.09% per ye ar improvement. EPA has undertaken an analy sis of the econom y - wide impacts of the final heav y duty 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 m ake 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 impact s 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 greenhou se 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 completel y b y 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 th em

– 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. F or 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 Im pacts 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 T able s 9

- 18 and 9

- 1 9 in the RIA .) Nevertheless , th is regulation reduces trucking companies’ fuel costs; ac cording 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 analy sis (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.” S tandard economic theory suggests that in normall y functioning competitive markets, interactions between vehicle buyers and producers would lead producers to incorporate all co st
- effective technology into the vehicles that they offer, without government intervention. Unlike in the light

- dut y vehicle market, the vast majority of vehicles in the medium

- and heav y - duty truck market are purchased and operated b y businesses with nar row 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 reducin g 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, yi eld private returns to truck owners of 140% to 420% (see Table VIII

- 21 below). T he agencies have also estimated that the application of these technologies would be significantl y lower in the absence of the final standards ( i.e. , under the “no a ction” 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 asy mmetric 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.), whereb y participants collective ly

do not minimize costs; or the engineering estimates of fuel savings and costs fo r these technologies might overstate their benefits or understate their costs in real

- world application s . To try to understand why trucking companies have not adopted these seemingl y cost
- effective fuel

- saving technologies, the agencies surveyed published literature about the energy

paradox, and held discussions with numerous truck market participants. The5

proposal discussed five categories of possible explanations derived from these sources

. Collect ively , these five hy potheses may explain the apparent inconsistency between the engineering anal ys is, 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 h ypotheses 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 b y 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 anal ys is. As noted above, an additional explanation

– adverse effects on other vehicle attributes

-- did not elicit supporting information in the public comments. Anecdotal evidence from vari ous segments of the trucking industry suggests that many

of the hy potheses 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 anal ys is or data related to this question. The agencies invite d comment on these explanations, and on an y data or information that could be used to investigat e the role of any or all of these five hy potheses 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 exp lain 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 request ed comment and information regarding any other hy potheses that could explain the appearance that cost

effective fuel

- saving technologies have not been widely incorporated into trucks

. The following discussion summarizes the full er discussion provided in the NPRM and includes discussion of the comments received. **(1) Information Issues in the Original Sale Markets**  One potential h ypothesis for wh y the trucking industry does not adopt what appear to be inexpensive fuel saving technologie s 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 understandabl y be reluctant to spend additional money to purchase vehicles equipped with unproven technologies. This lack of information can manifest itself in multiple way s. For instance, the problem may

arise purely because collecting reliable information on technol ogies 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 b y some form of coordination of inf ormation 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 techn ologies. 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 a gencies’ 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 semi

trucks compared to medium

- duty and vocational vehicles: more driving means more fuel savings. Additionall y, not even a majority of semi

- trucks are owned b y participants in SmartWay ; non - participants are unlikel y to get all the benefits of participants. Other explanations, noted below, are also likely to play a role. This obse rvation 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 h ypothesis for why trucking compan ies 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 buye rs. This inadequate pay

b ack for users beyond the original owner may contribute to the short pay back 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 truc k 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 bu ye rs 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. Bu yers in the resale market have no more reason to trust information on fuel

- saving technologie s than bu yers 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! Bookm ark 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 asymmetri c 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 provid e 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 originall y 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 b y their original owners if the optimal secondary new use of the vehicle do es 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 accuratel y refl ect 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 readil y availabl e 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 techno logies would reduce costs for the new buyers. This information issue may partially explain what appears to be the very short pay back periods required for new technologies in the new vehicle market. **(3) Split**  **I ncentives**  **in the M edium**  **- and**  **H eavy**  **- D**  **uty T**  **ruck I**  **ndu stry**  A third hy

pothesis explaining the energy paradox as applied to trucking involves split incentives. When markets work effectivel y, signals provided b y transactions in one market are quickl y transmitted to related markets and influence the decisions of buyers and sellers in those related markets. For instance, in a well

- functioning market sy stem, changes in the expected future price of fuel should be transmitted rapidl y to those who purchase trucks, who will then reevaluate the amount of fuel

- saving te chnology 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 thos e price signals may not be transmitted effectivel y, 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 generall y responsible for purchasing fuel, truck operat ors have strong incentives to economize on its use, and are thus likely to support the use of fuel

saving technology . However, the owners of trucks or trailers are often different from8

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 freel y 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 fu el efficiency of trucks by

owner - operators with those that are leased b y operators. The agencies hav e not had the data to conduct such a test. One commenter noted that there are alway s 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 purch aser’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 anal ys is. 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 d ifficult to achieve. **(4) Uncertainty A**  **bout Future Cost Savings** Another h ypothesis for the lack of adoption of seemingl y fuel saving technologies may be uncertainty

about future fuel prices or truck maintenance costs . When purchasers have less than perfect for esight 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

- red

ucing 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! Bookm ark not defined.**  **Error! Bookm ark not defined.**  , at p. 182.9

fuel efficiency

and potential variance about its expected rate may play a role in a firm’s calc ulation of its pay

back 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 irreversib le against an unknown stream of future fuel savings. 7 Notably , in this situation, r equiring households to adopt technologies more quickly may make them worse off by

imposing additional risk on them

. Greene et al (2009) also find s support for this explanation in the context of light

duty fuel econom y 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 risk

neutral expected value calcu lation shows that its buyer can expect significant net benefits from purchasing a more fuel

- efficient car

. 8 Supporting this hy pothesis is a finding by Dasgupta et. al (2007) that consumers are more likely to lease than buy

a vehicle with higher maintenanc e 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 heav y duty vehicles

. Purc hasers’ 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 b y a risk

- neutral calculation actually materialize. One commenter expressed support for this argument. Thus the mere existence of uncertainty about future savings in fuel cost s 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 pr essures 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 h ypothesis is that transactions co sts of changing to new technologies (how easil y 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 Refrigerato rs, ” 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 delay s in achieving fuel saving, environment, and energy

securit y benefits. In addition, there may

be costs associated with training drivers to realize the potent ial 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; r equiring the widespread use of these technologies may impose adjustment and transactions costs not included in this analy sis. 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 ne w 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 th e 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 hav e to invest heavil y (both financiall y 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 r ulemaking. 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 easil y o bservable 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 expe nditures made purel y for competition rather than actual increase in welfare. In a competitive business, cost reduction provides a major opportunity cost to investing in status rather11

than in fuel

- saving technology ; thus, this argument may play less of a role in the heavy

duty market than in the consumer market for vehicles. Both these h ypotheses leave open the question, though, wh y additional investments were not made in fuel efficiency if they would provide rapid pay back. Truck purchasers should, in prin ciple, be willing to buy additional fuel

- saving technology as long as it is cost

- effective, regardless of other vehicle attributes. L imited access to capital, if it is a problem in this sector, might provide some reason for the “crowding out” of the purch ase 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 rapidl y adopt cost

- effective fuel

- saving technologies. On the other hand, the short pay back period required b y bu yers of new trucks is a s ymptom 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 o perators to adopt fuel

- saving technology f or their trailers. The market for medium

- and heav y - dut y 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 b e 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 likel y to avoid new technol ogies 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 f

or 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 ye ars. The table also shows the net present values of those costs for the calendar ye ars 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 resourc es 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 ,**  **200 9$**  **) a**  2020 2030 2040 2050 NPV, Y ears 2012

- 2050, 3% D iscount R ate NPV, Y ears

2012

- 2050, 7% D iscount R ate 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 ,**  **200 9$**  **) a**  2020 2030 2040 2050 NPV, Y ears 2012

- 2050, 3% D iscount R ate NPV, Y ears

2012

- 2050, 7% D iscount R ate Fuel Savings (pre

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

Note : a F uel 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 ye ars. The table also shows the net present values of those benefits for the calendar y ears

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 CO 2 emissions

— and consequently the annual quantified benefits (i.e., total benefits)

— for each of four SCC values estimated b y the interagency working group. As discussed in the RIA Section 9.3 , there are some limitations to the SCC analy sis, including the incomplete way in which the integrated assessment models capture catastrophic and non

- catastrophic impacts, their incomplete treatment of adaptation and technological change, unce rtaint y 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 - CO 2 GHG emissions (CH 4 , N 2 O, HFC) expected under this action. Although EPA has not monetized the benefits of reductions in non

- CO 2 GHGs, the value of these reductions should not be interpreted as zero. Rather, the net reductions in non

- CO 2 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** **(Million s,**  **200 9$)** 

2020 2030 2040 2050 NPV, Years 2012

- 2050, 3% Discount Rate a NPV, Years

2012

- 2050, 7% Discount Rate a Reduced CO 2 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 Securit y 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

- CO 2 GHG Impacts e 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% (95 th percentile) $3,500 $11,100 $15,000 $18,700 $180,100 $155,700 Notes: a Net present value of reduced CO 2 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 S CC 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 ; f or Average SCC at 2.5%: $36

- $66 ; and for 95 th 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 PM 2.5 - 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 emiss ion 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 PM 2.5 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 i n this analysis exclude the value of changes in non

- CO 2 GHG emissions expected under this program (S ee RIA Chapter 5). Although EPA has not monetized changes in non - CO 2 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 calenda r years 2012

- 2050 using both 3 percent and 7 percent discount rate s . The table includes the benefits of reduced CO 2 emissions (and consequently the annual net benefits) for each of four SCC values considered b y EPA. **Table I**  **- 4**  **: Monetized Net Benefits Associated with the**  **Final Program** **(Million s,**  **200 9$**  **)**

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 a ssumed 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 N et present value of reduced CO 2 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 S CC 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 anal ys is of the total benefits over the model year lifetimes of the 201 4 through 201 8 model year trucks . In contrast to the calendar ye ar anal ys is presented above in Table I

- 1 through Table I

- 4 , the model ye ar lifetime anal ys is 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 lifetime s . The net societal benefits over the full life times of vehicles produced during each of the five model ye ars from 201 4 through 201 8 are shown in Table I

- 5 and Table I

- 6 at both 3 percent and 7 percent discount rate s , respectivel y. **Table I**  **- 5**  **: Monetized Fuel Savings, Tec**  **hnology Costs, Benefits, and Net Benefits Associated with the** 

**Lifetimes of 2014 -**  **2018 Model Year Trucks (Millions ,**  **200 9$**  **; 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 Securit y 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

- CO 2 GHG Impacts and Non

GHG Impacts c,d n/a n/a n/a n/a n/a n/a
Reduced CO 2 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 N et present value of reduced CO 2 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 S CC 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

- $6 6; 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

- CO 2 GHG emissions expected under this action (see RIA Chapter 5) . Although EPA has not monetized changes in non - CO 2 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, NO 2 and SO 2 ) were not estimated fo r 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 ,**  **200 9$**  **; 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 Securit y 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

- CO 2 GHG Impacts and Non

- GHG Impacts c,d n/a n/a n/a n/a n/a n/a Reduced CO 2 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 N et present value of reduced CO 2 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 ; f or Average SCC at 2.5%: $36

- $66 ; and for 95 th 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

- CO 2 GHG emissions expected under this action (see RIA Chapter 5). Although EPA has not monetized changes in non - CO 2 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, NO 2 and SO 2 ) w ere not estimated for this analysis. 

### C. **Employment Impacts**  **(1) Introduction**  Although analy sis of employ ment impacts is not part of a cost

- benefit analy sis (except to the extent that labor costs contribute to costs), employ ment impacts of federal rules are of particular concern in the current economic climate of sizeable unemploy ment. The recentl y issued Executive Order 13563, “Improving Regulation and Regulatory Review” (January

18, 2011), states, “ Our regulatory s ys tem 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 anal ys is of the proposed rules, several commenters suggested that we undertake an employ ment analy sis for the final rulemaking. Consistent with Executive order 13563 , we have provided a discussion of the potential employ ment impacts of the Heavy

- Duty N ational Program

. Our general conclusion is that employ ment impacts in the regulated sector (truck and engine manufacturing) and the parts sectors are likely to be positive; effects on employ ment in the tr ansport and shipping sectors are ambiguous; the fu el supplying sectors may

face reduced employ

ment; and there may

be increased general employ ment due to reduction in costs that may be passed along to the transport industry and thus to the public . Because we did not include employ ment analy sis 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 employ ment in the econom y. When the econom y 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 employ ment 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 employ ment are likel y to be transitory as workers change jobs

. For example , some worke rs 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 unemp loy ment, a change in labor demand due to regulation may affect net overall U.S. employ ment because the labor market is not in equilibrium. Either negative or positive effects are possible. Schmalansee and Stavins 13 point out that net positive employ ment ef fects are possible in the near term when the economy is at less than full employ ment 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 emplo ym ent 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 employ ment 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 employ ment 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 c ost s 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 relativel y s mall effect on net employment in the United State s 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 675,00 0 people were emplo yed in the motor vehicle parts industry between 2010 and 2011. 14 Although heav y - dut y 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. A s 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 ye ar that employ

ment 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 ref inery industry employed about 65,000 people in the U.S. in 2009, the most recent ye ar that employ ment estimates are available for this sector. 16 Finall y, since the net reduction in cost associated with th e s e rule s is expected to lead to lower transportation and shipping costs, in a competitive market a substantial portion of those cost saving s 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 employ ment in affected sectors b y offering the potential for new employment opportunities in the design an d 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 employ ment benefits of the improved efficiency in HD vehicles. 17 The study

predicts an increa se 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 thems elves have not yet been peer reviewed. Input

- output (I/O) models do not account for opportunity costs of labor

– that is, all employ ment needs due to the regulatory change will be met by unemployed workers. In addition, I/O models assume no changes in th e 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 Im proving Fuel Economy of Heavy Duty Vehicles, July, 2010. http://**www.ucs usa.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 emplo ym ent impacts. 18 Determining the direction of employ ment effects even in the regulated industry may be difficult due to the presence of competing effects that lead to an ambiguous adjustment in employ

ment as a result of environmental regulation. Morgenstern, Pizer and Shih 19 identify

three separate way s that employment levels may ch ange 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 depen ds 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 employ ment; 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 i s 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 p ossible that “cleaner operations could involve automation and less employ ment, for example”. The “demand effect” is expected to have a negative effect on emplo ym ent, the “cost effect” to have a positive effect on employ ment, and the “factor

- shift effect” h as an ambiguous effect on employ ment. 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 employ ment levels in a regulated sector Morge nstern et al. estimated the effects on emplo yment 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 generall y have not caused a significant change in employ ment 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 tha n 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

- S hyang 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 discussi on focuses on employ ment changes in the regulated sector, but the regulated sector is not the only source of changes in emplo ym ent. In these rules, the regulated sectors are truck and engine manufacturers; they are responsible for meeting the standards se t in these rules. The effects of these rules are also likely to have impacts beyond the directl y 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 man y companies in this sector purchase trucks and their operating costs will be affected b y both higher truck prices and fuel savings; o il refineries due to reduced demand for petroleum

- based fuels; and the final retail market, which is where an y 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 employ ment in these industries. The effects of the HD rule on net U.S. employ me nt depend, not only on their relative magnitudes, but also on employment levels in the overall economy. As previously

discussed, in a full

- employ ment economy

these sector

- specific impacts will be mostly offset by employment changes elsewhere in the econom y and would not be expected to result in a net change in jobs. However, in an economy with significant unemploy ment these changes may

affect net employ

ment in the U.S. (a ) Truck and Engine Manufacturers The regulated sector consists of truck and engine manufa cturers. 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, employ ment 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 emplo yment, 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, especiall y if potential buyers have an expectati on 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 th e 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 emplo ym ent (recognizing that21

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 c osts associated with this rulemaking outweigh the increase in vehicle cost. This finding is puzzling: market forces should lead truck manufacturers and buye rs to install all cost

effective fuel

- saving technology , but the agencies find that they have not. Section VIII.A discusses various h ypotheses that have been suggested to explain this phenomenon. Some of the explanations suggest that vehicle manufacturers and buye rs 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 heav y - dut y i ndustry indicate the potential for an increase in jobs. As stated by Tom Linebarger (President and Chi ef Operatin g 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 j obs 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 an d 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 additi onal labor to install the technologies on trucks, thus clearl y increasing labor demand (the “cost effect”). Fa ctor
- Shift Effect For “replacement” technologies, the predicted impact on labor demand from regulation depends on the change in the amount of la bor used to build and install one ty pe of technology

compared to another. In man y cases, the new technologies are predicted to be more complex than the existing technologies and are therefore likel y to require additional labor installation inputs. Inother cases, the opposite may be true.

20 Tom Linebarger (President and Chief Operatin g Officer of Cummins ) and Fred Krupp (President of the Environme ntal 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 EP A

- HQ

- OAR

- 2010

- 0162

- 1765.1[1]22 M ost of the technologies that are expected to be used to meet these standards are replacement technologies . For example, alm ost all of the engine improvements involve replacement technologies that are not expected to significantl y change the labor requirements. Similarly , regulations of the chassis on vocational vehicles will only require the installation of a different ty pe o f 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 relativel y small, though slightl y 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 emplo y ment ; the cost effect is expected to increase employ ment; and the factor

- shift effect may have a slightly

positive effect on employ ment in this sector. (b ) Motor Vehicle Parts Manufacturing Sector Some vehicle parts are made in

- house and would be included direc tly in the regulated sector

. Others are made b y 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, employ ment effects in this sector are expected to be positive. (c) Transport and Shipping Sectors Although not directl y regulated by these rules, employ ment 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 c osts), in a perfectl y 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 anal ys is) and therefore an increase in employ ment. In addition, if the relative cost of shipping freight via trucks becomes cheaper than shipping b y other modes (e.g., rail or barge), then employ ment 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.atri

online.org/research/results/Op_Costs_2011_Update_one_page_summary.pd f

. 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.ashx23 (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 employ ment in the fuel suppliers industry sectors, princip all y the Petroleum Refinery sector. 23 Expected fuel consumption reductions b y fuel t yp e, and b y heav y - dut y vehicle ty pe, can be found in Table VIII

- 7. These reductions reflect impacts from the new fuel efficiency and GHG standards and include increased c onsumption 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 2 014, 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 employ ment. 24 Because this sector is very capital

- intensive, the employ ment effect is not expected to be larg e. (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 saving s that initially accrue to trucking firms are likel y 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 b y consumers in other sectors of the econom y, creating jobs in a diverse set of sectors, includin g 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 employ ment 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 employ ment 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 p ercent 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 2110 00). 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 employ ment impacts would be smaller than if the savings went to the public. **(3) Summary**  The net emplo ym ent effects of this rulemaking are expected to be found through out 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 employ ment, depending on the net effect on HD vehicle sales. The cost effect is expected to increase employ ment in the regulated sector; and the factor

- shift effect may have a slightl y positive ef fect on employ ment, though we cannot definitivel y say this is the case without quantification. In creased expenditures by truck and engine manufacturers are expected to require increased labor to build parts, though this effect also depends on an y changes in the labor intensity of production; increased complexity of technologies may

imply increased labor inputs. Itis possible, if access to capital markets is limited, that this rule might displace other HD sector investment, which would reduce employ ment a ssociated with those activities. Lo wer prices for shipping are expected to lead to an increase in demand for truck shipping services and, therefore, an increase in employ ment, though this effect may be offset somewhat b y changes in employment in other shipping sectors. Reduced fuel production implies less employ ment in the fuel provision sectors. Finall y, 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 employ ment through their expenditures

. Given the job creation as a result of the $1.2B (2009$) in fuel savings in 2014 and the possible employ ment increases in the manufacturing and parts sectors, we find it highl y unlikely that there would be significant net job losses related to this policy

. Given the current level of unemploy ment, net positive employ

ment effects are possible, especially in the near term, due to the potential hiring of idle labor resources b y the regulated sector to plan for and meet new requirements. In the future, when fu ll employ ment is expected to return , any changes in employ ment levels in the regulated sector due to this program are mostly expected to be offset b y changes in employ ment in other sectors.