Should Corporate Average Fuel Economy (CAFE) Standards Be Tightened?

Transcription

1 Should Corporate Average Fuel Economy (CAFE) Standards Be Tghtened? Ian W.H. Parry, Carolyn Fscher, and Wnston Harrngton December 2004 Dscusson Paper Resources for the Future 1616 P Street, NW Washngton, D.C Telephone: Fax: Internet: Resources for the Future. All rghts reserved. No porton of ths paper may be reproduced wthout permsson of the authors. Dscusson papers are research materals crculated by ther authors for purposes of nformaton and dscusson. They have not necessarly undergone formal peer revew or edtoral treatment.

2 Should Corporate Average Fuel Economy (CAFE) Standards Be Tghtened? Ian W.H. Parry, Carolyn Fscher, and Wnston Harrngton Abstract Ths paper develops analytcal models to estmate the welfare effects of hgher Corporate Average Fuel Economy (CAFE) standards on new passenger vehcles. The analyss ncorporates a broad range of fuel- and drvng-related externaltes, fuel taxes, dfferent assumptons concernng consumers valuaton of fuel savng technologes and ther alternatve value n enhancng other vehcle attrbutes, and endogenous vehcle fleet composton. To mplement the analyss, we develop estmates of CAFE s mpact on local polluton, natonwde congeston, and traffc accdents. We fnd that hgher fuel economy standards can produce anythng from moderate welfare gans, to very lttle or no effect, to substantal welfare losses, dependng on how consumers value fuel economy technologes and ther opportunty costs. Key Words: fuel economy standards, ol dependency, carbon emssons, rebound effect, gasolne tax JEL Classfcaton Numbers: R48, Q48, H23

3 Contents 1. Introducton Analytcal Models... 6 A. Assumptons n the Sngle-Vehcle Model... 6 B. Soluton to the Sngle-Vehcle Model Benchmark Parameter Values A. Basc Vehcle Data B. Cost of Improvng Fuel Economy C. Vehcle Demand and Mleage Elastctes D. Local Polluton Costs E. Global Polluton Costs F. Congeston Costs G. External Accdent Costs H. External Costs from Ol Dependency I. Government Parameters Results A. Sngle-Vehcle Model B. Mult-Vehcle Model Concluson References Appendx A: Analytcal Dervatons Tables and Fgures... 37

4 Should Corporate Average Fuel Economy (CAFE) Standards Be Tghtened? Ian W.H. Parry, Carolyn Fscher, and Wnston Harrngton 1. Introducton The Corporate Average Fuel Economy (CAFE) program requres automoble manufacturers to meet standards for the sales-weghted average fuel economy of ther passenger vehcle fleets; current standards are 27.5 mpg (mles per gallon) for cars and 20.7 mpg for lghtduty trucks (SUVs, mnvans, and pckups). 1 Recent attempts to sharply ncrease the standards have been blocked n Congress, though the Natonal Hghway Traffc Safety Admnstraton (NHTSA), whch has authorty to set lght-truck standards, has fnalzed an ncrease n that standard to 22.2 mpg by Model Year Proponents of tghter CAFE standards emphasze the benefts of reducng carbon emssons, partcularly after the U.S. wthdrawal from the 1997 Kyoto Protocol, and the economy s dependence on a volatle world ol market, made ncreasngly jttery by recent prce ncreases. The standards may also address a market falure assocated wth consumers undervaluaton of fuel economy, though ths s much dsputed (compare Gerard and Lave 2003 and Klet and Lutter 2004). Furthermore, there s concern that average fuel economy of the new passenger vehcle fleet has fallen sgnfcantly from ts peak n 1987, due to the rsng share Parry (parry@rff.org) and Harrngton are Senor Fellows and Fscher a Fellow at Resources for the Future. We are grateful to the Envronmental Protecton Agency and the Natonal Hghway Traffc Safety Admnstraton for fnancal support, to Jeff Alson, Paul Balserak, Paul Leby, and Keth Sargent for helpful comments and suggestons, and to Puja Jawahar and Kenneth Gllngham for research assstance. 1 Manufacturers must pay a penalty of $55 per vehcle for every 1 mpg that ther fleet average falls below the relevant standard; vehcles weghng more than 8,500 pounds (such as the Hummer H2 and Ford Excurson) are exempt.

5 of lght-duty trucks whch now account for just over half of new passenger vehcle sales (see Fgure 1). Gasolne accounts for 43% of U.S. ol consumpton and 20% of carbon emssons (EIA 2002, Tables 5.11 and 12.3). Broad ol and carbon taxes are therefore far more cost-effectve polces than CAFE, as they explot optons for reducng ol use and carbon emssons throughout the economy, rather than placng the entre burden on (new) passenger vehcles. Nonetheless, energy taxes are not beng debated by polcy stakeholders whle CAFE s; 2 understandng the socal welfare effects of tghtenng CAFE would enlghten ths debate. Ths paper develops and mplements an analytcal framework for assessng the socal welfare effects of tghtenng CAFE standards, a framework that takes nto account a number of mportant factors. Frst, the analyss ntegrates CAFE s mpact on a broad range of motor vehcle externaltes, ncludng carbon emssons and ol dependency, whch are proportonal to fuel use, as well as congeston and accdents, whch ncrease through the rebound effect, that s, the ncentve to drve more when fuel costs per mle fall. We also model CAFE s mpact on local ar polluton, whch s potentally affected by vehcle use, fleet composton, fugtve emssons from the petroleum ndustry, and the effects of fuel economy on the emsson profles of agng vehcles. Second, we ncorporate preexstng fuel taxes that work to rase fuel prces and nternalze fuel-related externaltes, consderng scenaros when revenues are earmarked for hghways and when they form part of general government revenue. Thrd, we consder scenaros meant to span the dverse range of opnons among experts about how consumers value fuel savng technologes, and the full economc costs of adoptng them, allowng for possble opportunty costs from forgong ther use n enhancng other vehcle attrbutes such as power, comfort, safety, and payload. Fourth, we consder mplcatons of changes n vehcle fleet composton when the net costs of mprovng fuel economy, and external costs, dffer across vehcle types. 2 For example, a recent hgh-profle report from a bpartsan commsson recommended hgher fuel economy standards (NCEP 2004). 2

6 We begn wth a sngle vehcle model, where welfare effects of fuel economy standards are explctly decomposed nto terms wth clear economc nterpretaton. The model s then extended to dstngush ten vehcle classes. Ths extenson allows us to consder dfferental standards for cars and lght trucks, nduced changes n the vehcle sales mx, and cost savngs from tradng of fuel economy credts across cars and lght-trucks. We develop new estmates of parameters requred to mplement the model where pror emprcal lterature s patchy. Emssons nspecton data s used to quantfy lfetme vehcle emsson rates and to assess the emssons/fuel economy relaton. Results from a computatonal transport network model are extrapolated to estmate margnal congeston costs for the naton as a whole. Crash data s used to estmate external accdent costs for the ten vehcle classes. Also, we account for some prevously unexamned subtletes n measurng fuel economy n absence of regulaton, vehcle demand elastctes, and the rebound effect. In prevous lterature, the usual approach has been to measure welfare effects of fuel economy regulatons by estmatng lfetme fuel savng benefts mnus added vehcle costs (e.g., Yee 1991, Greene 1991a, Thorpe 1997, Goldberg 1998, NRC 2002, Greene and Hopson 2003, CBO 2003). These studes yeld wdely dfferent results concernng not only the magntude but also the drecton of the welfare effect, dependng on whether they allow for market falure n fuel economy provson or rule t out by assumpton. There has been very lttle attempt to ntegrate externaltes nto welfare assessments of CAFE. The one excepton s Klet (2004); usng a dsaggregated, computatonal model of the auto market, he estmates that a long-run 3-mpg ncrease n the CAFE standard would reduce socal welfare by $0.78 per gallon of fuel savngs. Our analyss bulds on Klet (2004) n several respects. We develop detaled estmates of external effects and behavoral responses where pror emprcal lterature s sketchy. Our framework encompasses a broad spectrum of scenaros about consumers valuaton of fuel savng technologes and ther opportunty costs; Klet s analyss assumed no (nonexternalty) market falures. The analytcal framework explctly shows the contrbuton of underlyng parameters to welfare effects; the sngle vehcle model yelds welfare formulas that are easy to mplement and update n the lght of new evdence, and estmates from the smple model are approxmately consstent wth those from the mult-vehcle model. We also examne the role of 3

7 preexstng fuel taxes, the effect on accdents from changng fleet composton, and we consder a rch array of polcy scenaros and senstvty analyss. 3 We summarze the results as follows. Frst, we fnd essentally no dfference n the deteroraton of emssons per mle over vehcle lfetmes for cars wth dfferent fuel economyor for lght trucks wth dfferent fuel economy. Ths suggests conventonal polluton s (approxmately) ndependent of fuel economy wthn car and truck groups and vares only wth mleage. Overall, tghtenng CAFE slghtly ncreases polluton because emssons from added drvng domnate other behavoral responses; the contrbuton to overall welfare effects s small, however. Second, we estmate the margnal congeston cost, averaged across 348 U.S. ctes and rural areas, and across tme of day, at 6.5 cents per mle. External accdent costs per mle are estmated at 4.5 cents per mle for the average passenger vehcle; across the ten vehcle classes, there s lttle correlaton between estmated external accdent costs and fuel economy, 4 hence safety effects of changes n vehcle fleet composton contrbute very lttle to overall welfare effects. Thrd, we show that the reducton n fuel demand nduced by mproved fuel economy s tself welfare mprovng only f the margnal external costs of carbon emssons and ol dependency exceed the product of the exstng fuel tax and the margnal socal value of fuel tax revenues. When the socal value of an addtonal dollar of revenue s a dollar, whch could be a reasonable approxmaton even when revenues are earmarked for hghways, the reducton n gasolne demand (moderately) reduces welfare because the current (federal and state) fuel tax of 3 Another ssue that has been hotly debated s CAFE s mpact on hghway fatalty rates (e.g., Crandall and Graham 1989, Khazzoom 1997, Kahane 1997, van Auken and Zellner 2002, Noland 2004). Our analyss nstead quantfes the regulaton s effect on external accdent costs, whch s qute dfferent; external costs exclude own-drver fatalty rsk, and nclude nonfatal njures to other road users, traffc holdups, and a porton of property damage, medcal and emergency servce costs, and productvty losses (see below). 4 Ths fndng s consstent wth Mller et al. (1998) and Parry (2004), though the vehcle classes n those studes are far more aggregated. 4

8 $0.40 per gallon overcharges for fuel-related externaltes. Our benchmark values for margnal ol dependency and carbon externaltes are $0.20 and $0.12 per gallon respectvely. Fourth, relatve welfare losses from the rebound effect are sgnfcant (as n Klet 2004), though the ncrease n aggregate mleage s dmnshed to some extent by the reducton n vehcle sales, whch dffers dependng on how fuel economy technologes and ther costs are valued. Although the ncrease n mles drven s modest, t stll causes a substantal welfare cost because mleage-related external costs are large relatve to fuel-related external costs. Expressed on a pergallon equvalent bass at ntal on-road fuel economy, margnal external costs from congeston, accdents, and local polluton convert to $2.53 per gallon, or eght tmes combned carbon and ol dependency externaltes. Ffth, there s a wde range of possbltes for the welfare change from the mprovement n fuel economy tself. A number of engneerng studes suggest there are many emergng technologes for whch dscounted, lfetme fuel savngs would easly exceed costs of ncorporatng them n new vehcles (e.g., NRC 2002, Fgure 4.5). Many of these technologes may not be adopted f, as some evdence suggests, consumers care more about other vehcle attrbutes or f ther short tme horzons and hgh dscount rates cause them to undervalue fuel savngs substantally. In ths case, there s a potentally sgnfcant welfare gan from regulaton that nduces manufacturers to adopt such technologes. However, to the extent consumers perceve fuel savngs, vehcle manufacturers should ncorporate emergng technologes, thereby rasng baselne fuel economy and dmnshng the effectveness and welfare gans from hgher fuel economy mandates. If consumers correctly perceve fuel savngs but value technologes more when used to enhance other vehcle attrbutes (as n CBO 2003), there s a potentally large welfare loss from fuel economy regulatons that dvert technologes away from ther hghest valued use. Sxth, n the sngle vehcle model, when fuel savngs are correctly perceved a mandated ncrease of 4 mpg above current levels produces anythng from an annual net welfare loss of $8.89 bllon ($0.73 cents per gallon of dscounted fuel savng) to zero effect, dependng on whether technologes have hgh opportunty costs or not. In contrast, f consumers reckon three (rather than 14) years of fuel savngs, as many experts n the auto ndustry beleve, there s a net welfare gan of $2.96 to $3.95 bllon. 5

9 Seventh, welfare results from the mult-vehcle model are smlar to those from the sngle-vehcle model: the man dfference s that, n aggregate, added vehcle producton costs are hgher, because the same mpg ncrease s mandated for cars as a group and trucks even though, due to dfferental standards, the former have hgher margnal complance costs. Agan, whether a tghtenng of the truck standard alone ncreases welfare or not depends on how consumers value fuel savng technologes and ther opportunty costs. There are several caveats to our analyss, dscussed at the end of the paper: n partcular, margnal damages from carbon and ol dependency may change over tme, and we do not model possble effcency gans from nduced nnovaton n the presence of technology spllovers. Nonetheless, gven that tghtenng CAFE standards mght have lttle effect or produce large welfare losses, our own preference would be for alternatve polces whch appear to have a frmer effcency foundaton, such as broad-based ol and carbon taxes, hgher fuel taxes, pay-asyou-drve auto nsurance, subsdes for alternatve fuel vehcles, and subsdes for R&D nto carbon capture technologes. 5 The rest of the paper s organzed as follows. Secton 2 develops the sngle- and multvehcle analytcal models. Secton 3 provdes the parameter assessment. Secton 4 presents the man results and senstvty analyss. A fnal secton offers conclusons. 2. Analytcal Models A. Assumptons n the Sngle-Vehcle Model () Utlty and Drvng. We consder a one-perod model where the perod represents the average lfetme of a new passenger vehcle, currently 14 years (NRC 2002). At the start of the perod the representatve agent buys v dentcal vehcles, drves each of them for m mles, then scraps them at the end of the perod. 6 The agent has utlty functon: 5 See for example Parry and Small (2004), Parry (2005), Leby and Rubn (2001), Anderson and Newell (2004). 6 We treat v as a contnuous varable n the household optmzaton, as t represents the economy-wde vehcle stock. 6

10 (1a) U = u( D, T, Q, X ) A O Z M Z G (1b) D = D( v, m, H ) (1c) Q = qm, M = vm where u(.) s quas-concave n D, Q, and X and decreasng n T; all varables are present dscounted values per capta. D(.) denotes sub-utlty from vehcle mles traveled; t s ncreasng and concave n all arguments. 7 H s government spendng on hghways; more spendng may rase the beneft of drvng through access to a more extensve and better-mantaned road network. T s n-vehcle tme, and u T represents margnal dsutlty from reduced tme avalable for other actvtes. Q s sub-utlty from the qualty of vehcle travel and s ncluded to capture trade-offs between fuel economy and other vehcle attrbutes (e.g., power, comfort, safety, payload); t s equal to vehcle mles of travel (M) scaled by q, a vehcle qualty ndex. Q s defned relatve to a reference level (see below) and may be negatve. X s the quantty of a numerare consumpton good. A and O denote, respectvely, the socal costs of traffc accdents and external costs from the economy s dependence on a volatle world ol market (the nature of the externaltes are dscussed below). Z M s envronmental damages from local talppe emssons subject to emssons per mle regulatons. Even though abatement equpment may deterorate over tme, based on emprcal fndngs n Secton 3, we assume lfetme emssons are proportonal to vehcle mles and ndependent of fuel economy. Z G s the cost of emssons that are proportonal to fuel use. These nclude carbon emssons, whch are not subject to (federal) emssons per mle regulatons, and upstream local emssons leakages from the petroleum ndustry. A, Z G, O and Z M are expressed n utls. 7 Concavty n m ensures agents buy more than one vehcle; ths may represent ncreased rsk of breakdown for vehcles wth hgher mleage. 7

11 We defne: (2) G = gm, p = ~ p + t G G G g and G denote gallons of gasolne per mle (the nverse of fuel economy), and total gasolne consumpton, respectvely. p G s the consumer prce of gasolne equal to the pre-tax prce p~ G plus a specfc tax per gallon t G. The government mposes a maxmum allowable celng on fuel per mle, g, equvalent to a fuel economy standard. The welfare effects of ths mandated standard depend on how t reduces fuel per mle relatve to the free-market baselne; n practce the latter may declne n future wthout regulaton f emergng fuel savng technologes were to be adopted by the market. To ncorporate ths we defne two reference scenaros: the frst (denoted R1) represents currently observed fuel per mle nherted from a prevous perod; the second (denoted R2) represents the free-market baselne n the current perod after the possble adopton of emergng technologes. Thus: (3a) R2 R1 g < g R2 R1 g = g f emergng technologes would be adopted to rase fuel economy f not (3b) g = g f regulatons are bndng, R2 g < g R2 g = g f not We assume that any preexstng fuel economy standards (n the frst reference scenaro) are nonbndng, whch s a common modelng assumpton (e.g., Thorpe 1997, Goldberg 1998, Greene and Hopson 2003, CBO 2003). 8 To the extent that pror standards mght be bndng our analyss overstates the welfare effects of mandatng hgher standards (Klet 2004). 8 A possble justfcaton s that the car standard has been unaltered snce 1985 and untl a recent rulng the lght truck standard had been unaltered snce We also gnore the possblty that frms pay a fne nstead of meetng fuel economy requrements, as ths has not been the case for U.S. companes. See 8

12 We defne: (4) Γ = ρp G mg Γ s lfetme fuel costs as perceved by agents at the start of the perod. If ρ = 1 agents correctly percevng future fuel costs (as assumed n CBO 2003, Klet 2004, Thorpe 1997, and others); we refer to ths as the farsghted consumers case. If ρ < 1 agents undervalung fuel costs, for example they may have excessve dscount rates, consder fuel savngs over a shorter horzon than the vehcle lfetme, or t may not pay boundedly ratonal consumers to nform themselves about fuel costs f they care more about other vehcle attrbutes (e.g., Greene et al. 2004); we refer to ths as the myopc consumers case. () Externaltes. Travel tme s gven by: (5) T = πm ; π = π (M ) whereπ (.) > 0 and a bar denotes an economy-wde varable (expressed n per capta terms) perceved as exogenous by ndvdual agents. π s drvng tme per mle; t ncreases wth aggregate drvng as more congested roads slow drvng speeds. Agents do not take nto account the mpact of ther mleage on reducng speeds for other drvers. Accdent costs are: (6) A = a ( M ) a ( M ) INT + EXT where a, > 0. a INT s nternalzed accdent costs (e.g., own-njury rsks to drvers) and INT a EXT a EXT s external costs (e.g., pedestran njures, property damages not perceved on a per mle bass). Accdent costs depend on mleage; below we allow them to also vary wth fleet composton. Remanng external costs are: (7) Z G = Z G (G ) ; Z M = Z M (M ) ; O = O(G ) where Z G (.), Z M (.), O (.) > 0. 9

13 () Frms. We assume domestc, compettve frms produce gasolne, vehcles, and the numerare consumpton good wth labor under constant returns. We beleve these are reasonable smplfcatons for our purposes; Secton 5 brefly comments on alternatve assumptons. Manufacturers face the followng functons: 1 (8a) C C( g R 1 = g), C = α + β ( g R g) 1 (8b) q = q( g R g) where α and β are nonnegatve parameters. In (8a) C(.) s the added dollar producton cost per vehcle from reducng fuel per mle below the frst reference level through technology adopton (e.g., technologes to mprove engne effcency and transmsson or reduce vehcle drag and rollng resstance); margnal costs are assumed lnear. In (8b), we allow for the reducton n fuel per mle to lower qualty by dvertng technologes that would otherwse have been employed to enhance other vehcle attrbutes, q 0. 9 We denote the vehcle sales prce by p. Frms choces over fuel economy affect p and C (see below); however, entry/ext of frms ensure that n equlbrum (9) p p R 1 = + C where p R1 s the vehcle producton cost, and equlbrum sales prce, n the frst reference scenaro. (v) Government Budget Constrant. Ths s: (10) H + F = t G G 9 There s casual evdence that fuel savng technologes may have value n other uses. For example, emergng technologes dentfed as fuel savng technologes n NRC (1992), ncludng four valve per cylnder engnes and four- and fve-speed automatc transmssons, were wdely ntroduced over the last decade, yet new vehcle fleet fuel economy dd not mprove whle average horsepower ncreased sgnfcantly (CBO 2002, Table 2). Besdes these opportunty costs there may be other unobserved costs that are excluded from emprcal estmates of C, such as marketng, mantenance, consumer unfamlarty, and retranng of mechancs. However, ncorporatng them would have essentally the same effect of assumng a lower value for q. 10

14 where F s a lump-sum transfer to households. Ths equaton equates hghway and transfer spendng wth fuel tax revenues. We consder cases where changes n revenues mply ether changes n H or F. B. Soluton to the Sngle-Vehcle Model () Household Optmzaton. We solve the household optmzaton problem backwards n two steps (ths s necessary when agents msperceve lfetme fuel costs). Frst, for a gven number of vehcles v ~ purchased at the start of the perod, households choose mles per vehcle and the numerare good to maxmze utlty (1) subject to the budget constrant I + F pv~ = X + vp ~ mg and (5) (7), where I denotes (fxed) labor ncome. 10 Second, at the start of the perod they optmze over the number of vehcles and (planned) spendng on the numerare good, subject to the constrant I + F = X + v( p + Γ), (5) (7), and takng Γ as gven. G (11a) The optmzaton yelds: { u D / v + u π a }/ u = p G g + ω / m D m T INT X (11b) (11c) { u D / m + u π a } m / u = D p E v T p + Γ + ω INT X p E where ω( R1 R1 q q) = uq ( q q) m / u X s the utlty loss (n dollars) from reduced qualty per vehcle ( ω > 0 ). Equaton (11a) equates drvng benefts per mle, net of tme and nternal accdent costs, wth per mle costs of fuel and reduced travel qualty. Equaton (11b) smlarly equates drvng benefts per vehcle, net of tme and nternal accdent costs, wth effectve vehcle prce p E ; the latter ncludes the sales prce, perceved lfetme fuel costs, and qualty costs. 10 We assume agents correctly perceve fuel costs when choosng mleage, as ths s an ongong decson (unlke the vehcle purchase decson that requres forecastng over a 14-year perod). 11

15 To obtan demand functons we assume changes n π and a INT are neglgble (ths s reasonable as proportonate changes n M are small) and that m s unaffected by changes n vehcle qualty. 11 We also adopt constant-elastcty functonal forms: (12a) m m g g R1 R1 η m (12b) v p p R1 R E E v R1 p η v η m < 0 s the elastcty of mles drven per vehcle wth respect to fuel costs and η v < 0 s the elastcty of vehcle demand wth respect to the effectve prce. 12 () Frm Optmzaton. From (11b) frms face a sales prce p = p E Γ ω ; they take p E as gven as they are compettve, though ther choce of fuel economy alters how much consumers are wllng to pay for vehcles p, through alterng Γ and ω. Wth no fuel economy constrant frms choose g to maxmze profts per vehcle p ( C + p R1 ). Usng (4) and (8), ths yelds: (13) ρmpg R 2 R1 = C + ω q g = g { ρ mp ( α + ω q )}/ β G Equaton (13) states that fuel per mle s reduced untl the ncremental lfetme fuel savng benefts perceved by consumers, value of forgone vehcle qualty, ω q. ρ mpg, equals the added vehcle cost, C, plus the margnal Snce forgone qualty s unobservable, ω q s assumed constant, and we consder cases to span the range of possbltes for ts magntude. In a no opportunty costs scenaro (e.g., NRC 2002), we smply set ω q = 0. In an opportunty costs scenaro, we follow CBO (2003) and assume any falure to adopt emergng technologes for whch perceved fuel savng benefts exceed added vehcle costs, s explaned entrely by forgone qualty. 11 Thus, we gnore a possble counteractng effect on mleage due to the potental for fuel economy mprovements to reduce drvng qualty; the assumpton s made because emprcal evdence s unavalable to quantfy ths effect. 12 We defne changes n effectve prces relatve to the retal prce n order to apply elastctes from the emprcal lterature that are defned relatve to retal prces. 12

16 Thus, there are four possble equlbra n the second reference or baselne scenaro, llustrated n Fgure 2. Wth farsghted consumers, equlbrum s at pont A, wth opportunty costs, and pont B, wth no opportunty costs. Snce the perceved and actual (or socal) margnal benefts are the same, and equal to margnal cost, nclusve of any opportunty costs at these ponts, any mandated reducton n fuel per mle beyond these levels wll reduce effcency (leavng asde externaltes and fuel taxes). Wth myopc consumers, equlbrum s at pont C, wth opportunty costs, and pont D, wth no opportunty costs. In these cases, a mandated reducton n fuel per mle can ncrease effcency, because the socal margnal beneft ntally les above margnal costs (nclusve of any opportunty costs). Fnally, note that n the no opportunty cost cases, standards must be ncreased above a strctly postve threshold level before they become bndng and have any effect. () Welfare Effects. When regulaton s bndng ( g < R2 g ), the (monetzed) welfare effect (denoted W) from an ncremental reducton n g can be obtaned by dfferentatng the agent s ndrect utlty functon, accountng for changes n external costs, and n F or H to mantan government budget balance. The result can be expressed as the sum of the followng three components (see Appendx): gasolne reducton mleage 647 ncrease 48 fuel dw dg dm 6444 economy (15a) = (β tg EG ) E M dg dg dg + { mp G ( C + ω q )} v (15b) E ( Z + O ) / u ; = π ; G = G X E M { aext + Z M ut M }/ u X dg dm dm dm dv dpe (15c) = M + g > 0 ; = v + m < 0 dg dg dg dg dp dg E β = df dh u H 1 + dg dg u X tg E G s the external cost per gallon (n dollars) from carbon emssons, upstream local emssons, and ol dependency. E M s the external cost per mle from accdents, local talppe polluton, and congeston. 13 β s the socal value per dollar of tax revenue. If all margnal revenue s spent on 13 The margnal cost of congeston s the ncrease n travel tme per mle followng an ncremental ncrease n aggregate mleage π, tmes per capta mleage M, tmes the margnal dsutlty of n-vehcle tme, -u T. 13

17 transfer payments, df / dg = t G (from (10)) and β = 1. If t s all spent on hghways, dh / dg = t G and β = u / u H X ; n ths case β s greater/less than unty f the value of an extra $1 of hghway spendng s greater/less than $1. We assume E, E, and β are constant. 14 The frst component n (15a) s the nduced welfare change n the gasolne market. It equals the change n gasolne tmes the product of β and the gasolne tax, mnus the per gallon external cost. If β = 1, the reducton n gasolne ncreases/decreases welfare, dependng on whether the gasolne tax under- or over-charges for external costs of fuel use. Wth fuel tax revenues earmarked for hghways, the eroson of the fuel tax base nvolves hgher/lower effcency costs (gross of externaltes) f the socal value per $1 of margnal government spendng s greater/less than $1. Thus, the common percepton that fuel taxes are not dstortonary because they pay for hghways s only vald n our analyss f hghway spendng has no socal value. The second component n (15b) s a welfare loss equal to the ncrease n mleage, or rebound effect, tmes the external cost per mle from mleage-related externaltes. The ncrease n mleage equals the ncrease n mles per vehcle due to lower per mle costs, less a (partally) offsettng effect due to reduced vehcle demand as the effectve vehcle prce ncreases, as n (12a), (14) and (15c); note that the change n effectve prce wll vary wth the dfferent scenaros n Fgure The thrd welfare component s from the ncrease n fuel economy tself. It s the margnal socal beneft from fuel savngs, net of margnal vehcle costs, ncludng forgone qualty, tmes the number of vehcles. As can be seen n Fgure 2, there s a welfare loss wth farsghted consumers, but a potental welfare gan wth myopc consumers. G M 14 These are reasonable assumptons wth the possble excepton of margnal ol dependency costs, whch vary modestly wth reductons n ol use (Leby et al. 1997). 15 The effectve prce always ncreases because margnal costs, ncludng qualty costs, exceed perceved margnal benefts, for nonncremental reductons n fuel per mle beyond the free market baselne (see Fgure 2). In our smulatons below, the reducton n vehcle sales lowers the rebound effect by between 14 and 26% across dfferent scenaros. 14

18 Equaton (15a) s easly ntegrated to obtan welfare effects of nonncremental polcy changes, usng Equatons (8a), (12), assumptons about opportunty costs, and parameter values dscussed below. C. Mult-Vehcle Model We now assume the representatve agent drves = 1 N C cars and = N C +1 N T lght trucks; we mantan the assumpton of homogeneous frms, where each frm s engaged n producton of all vehcles. Intal prces, fuel economy, and the margnal cost of reducng fuel use per mle dffer across vehcles, as do accdent and polluton costs per mle, though not congeston costs. 16 Added vehcle producton cost and qualty take the same form as n (8). Vehcle demands are now gven by the constant elastcty formulas: (16) v = v T N R1 Π j= 1 R1 ηj pej pej 1 + R1,, j = 1 N T p j where η s an own-prce elastcty and η j (j ) a cross-prce elastcty. CAFE sets separate standards for the harmonc average mles per gallon across car and lght-truck fleets; ths s equvalent to mposng maxmum fuel per mle requrements, expressed as C g for cars and C N T g for trucks. When standards are bndng: C T (17) Σ ( g g ) v = 0, Σ ( g g ) v = 0 = 1 T N C = N + 1 Manufacturers choose fuel per mle for each vehcle, and vehcle sales, to maxmze profts T N Σ{ p = 1 ( C + p R1 )} v subject to (11c), (16) and (17), takng p E as gven. Ths yelds: (18a) C + ω q ρp m = G δ k, = 1 N C, k = C; = N C +1 N T, k = T R1 k (18b) p ( C + p ) = δ ( g g ), = 1 N C, k = C; = N C +1 N T, k = T k 16 FHWA (1997), Table V-23, puts the dfference n margnal congeston costs across cars and lght trucks at only 0.01 to 0.15 cents per mle; vehcles dffer n length, and therefore how much road space they take up, but these dfferences are small relatve to average on-road dstance between vehcles. 15

19 δ C and δ T are the shadow prces on the constrants for cars and trucks respectvely; pror to any mandated ncrease n fuel economy δ C, δ T = 0. Equaton (18a) states that wthn a vehcle class (cars or trucks) fuel economy s mproved n a vehcle untl the ncreased producton and qualty cost, net of perceved fuel savng benefts, s equated to the shadow prce of the fuel economy constrant for that class. (18b) states that, wthn a vehcle class, sales prces are above, equal to, or below producton costs, accordng to whether fuel per mle s above, equal to, or below the average for that class, when the standard s bndng. Thus, the standard effectvely taxes fuel neffcent vehcles and subsdzes fuel effcent ones. By alterng the relatve vehcle prces n ths way, the mult-vehcle model admts another channel for mprovng fleet average fuel economy that s absent from the sngle-vehcle model. External costs of fuel consumpton are dentcal for cars and trucks (though per mle costs dffer); thus, there s no effcency ratonale n our analyss for polces resultng n dfferent shadow prces on fuel economy for cars and trucks. 17 If fuel economy credts could be traded across cars and lght trucks ths would effectvely replace the separate standards wth a sngle standard and a sngle shadow prce; effcency would mprove n two respects. Frst, the margnal cost of mprovng fuel economy, ncludng qualty costs, and net of perceved fuel savngs, would be equated across all vehcles, rather than dfferng between cars and trucks; second, the penalty (subsdy) for a vehcle wth relatvely hgh (low) fuel per mle would be the same for cars and trucks. The mult-vehcle model s solved n a spreadsheet that selects values for the shadow prces, uses these to compute fuel economy and vehcle sales prces from (18), and then vehcle demands from (16), and then terates over the shadow prces untl constrants n (17) are met for gven fuel economy standards. Analogous to the decomposton n (15a), the welfare change from a nonmargnal polcy change s calculated by: 17 When CAFE standards were ntally ntroduced lght trucks were manly used for ndustral and agrcultural purposes and a lower standard for them was set to lmt the burden on commerce. Today however, today most lght trucks are used as passenger vehcles. 16

20 (19) W gasolne reducton R = ( βt E )( G 2 G G G ) mleage ncrease N T Σ E = 1 M ( M M R2 ) fuel economy N T + Σ = 1 R2 R2 R2 R1 { p [ g m g m ] [ C ( g ) C( g )] ω q ( g g )}( G v R2 + v ) / 2 3. Benchmark Parameter Values Here we dscuss benchmark parameter values; n a subsequent senstvty analyss we consder alternatve values for key parameters. A. Basc Vehcle Data Table 1 summarzes vehcle classfcatons, sales, ntal prces, fuel economy, and actual lfetme fuel costs for model year 2000; ths data s used to produce the frst reference scenaro. Followng Chapter 4 of NRC (2002), we dstngush four car classes (subcompact, compact, mdsze, and large) and sx lght truck classes (small SUV, md SUV, large SUV, small pckup, large pckup, and mnvan). Cars and lght trucks each account for about 50% of total passenger vehcle sales. Intal certfed fuel economy averages 27.4, 20.6 and 24.0 mpg across cars, lght trucks, and all vehcles, respectvely, or 3.65, 4.85 and 4.17 gallons per 100 mles. We assume on-road fuel economy s 85% of the certfed level. 18 Followng NRC (2002) we assume all vehcles are ntally drven 15,600 mles n the frst year, decreasng thereafter at 4.5% per year, over the 14-year lfe cycle. Intal dscounted 18 See NRC (2002), p. 66. Unlke certfed (.e. dynamometer-tested) fuel economy, on-road fuel economy vares wth traffc condtons, temperature, trp length, frequency of cold starts, drvng style, etc. Certfed fuel economy s from NRC (2002), Table 4.2 (adjusted for future safety and emssons standards). As n NRC (2002), we assume no deteroraton of fuel economy over vehcle lfetmes. Sales data was compled from Wards Automotve Handbook The prce for each vehcle class was obtaned from a sales-weghted average of prces of models wthn that class from To classfy vehcles accordng to the NRC subgroups we used a combnaton of the Wards descrptons and EPA classfcatons. Luxury vehcles, two-seaters, large vans, and some other specalty vehcles lke hybrds were excluded. 17

21 R1 R1 lfetme fuel costs for vehcle, m p g are therefore computed wth m R1 = 15,600 Σ 14 S j 1 j= 11/(1 + r +.045) G, where r S s a socal dscount rate. We assume r S = 0.05, a typcal value used n medum-term cost beneft analyss. 19 The retal gasolne prce, p G, s $1.50 per gallon. 20 A wdely cted econometrc analyss by Dreyfus and Vscus (1995) estmated that consumers dscount gasolne costs at between 11 and 17%, whch would mply ρ = 0.78 and 0.64 respectvely. 21 Many people n the auto ndustry beleve that new vehcle buyers only consder fuel costs over the frst three years, and ths s the assumpton bult nto the U.S. Energy Informaton s Natonal Energy Modelng System (Greene et al. 2004); ths would mply ρ =.33, whch we adopt for the myopc consumers case. B. Cost of Improvng Fuel Economy We calbrate the drect costs of mprovng fuel economy C to underlyng data n NRC (2002); 22 R1 ths yelds coeffcents shown n the last two columns of Table 1 (for g g n gallons per 100 mles). Margnal costs rse more rapdly for smaller vehcles wth hgher ntal fuel economy. The beneft from a gallon reducton n gasolne per 100 mles, evaluated at the 19 See for example 20 Ths s an average over the prevous decade. See 21 A possble explanaton for dscount rates exceedng market rates s that auto buyers are lqudty constraned; Ozazo et al. (2000) fnd some evdence for ths for younger and mddle ncome households. The above fndng s consstent wth evdence that consumer dscount rates for a wde spectrum of energy savng applances exceed market nterest rates (Frederck et al. 2002). 22 Ther data consst of costs and fuel savngs from a wde range of technologcal optons for each vehcle type, whch we order by the rato of average cost to the average percentage mprovement n fuel economy. Fttng regressons of the form n (8a) to ths data yelds our coeffcent estmates. The NRC estmates were obtaned from avalable evdence and conversatons wth manufacturers, and are broadly smlar to those n a number of other engneerng studes (see NRC 2002, fgures 4.5 and 4.6). Cost estmates are expressed as retal prce equvalents wth a 40% markup assumed for parts suppler, automaker, and dealer. Thus, costs may be overstated, snce some of the markup may reflect a transfer payment rather than a pure resource cost. 18

22 socal dscount rate and frst reference mleage, s $1,940 for each vehcle; ths greatly exceeds all the ntercepts of all the margnal cost curves. C. Vehcle Demand and Mleage Elastctes We smulate an nternal General Motors (GM) model of new vehcle sales to obtan a matrx of own and cross vehcle prce elastctes. 23 However the magntude of the ownprce elastctes are too large as they reflect people holdng on to used vehcles longer an effect that dsappears n the long run n addton to substtuton between vehcles and reduced overall vehcle demand; the own-prce elastctes are therefore adjusted as follows. Frst, we smulate a dynamc model of vehcle choce developed by Harrngton et al. (2003) to obtan long-run estmates of the own-prce elastctes for cars as a group, denoted ηˆ CC, and lght trucks as a group, denoted ηˆ TT ; results are ηˆ CC = 0.79 and ηˆ TT = Second, we express the own-prce elastcty for car computed from the GM model as η = Σ η x / x + η Σ η x / x ), where, j = 1 C. The frst component reflects j j j ( j j j substtuton effects among cars. The second component encompasses all other effects reduced overall vehcle demand, substtuton nto trucks, and people holdng on to vehcle longer; to remove the last effect we scale the second component by ˆ η CC / ~ ηcc, where ~ η CC s the own-prce elastcty for cars as a group from the GM model, equal to Truck elastctes are smlarly 23 The GM model estmates sales of specfc vehcle models, gven a set of prces for all ncluded models, for model year We aggregate these responses to estmate changes n demand for each new vehcle class, accordng to the percentage change n ts own prce and those of the other new vehcles. 24 The Harrngton et al. model ncorporates a nested logt structure of household ownershp over new and old cars and lght trucks where the demarcaton between new and old vehcles s 3.5 years. The nestng structure conssts of an upper level where the choce of how many vehcles to own s estmated and a lower level where vehcle class/vntage s estmated; vehcle mles traveled s then estmated condtonal on the number of vehcles owned. Behavoral response parameters are econometrcally estmated from the 1990 Natonal Personal Transportaton Survey (NPTS), and ntal condtons calbrated to match the observed 2001 vehcle fleet composton. The above elastctes were obtaned from ncreasng new car prces by 1% and runnng the model through 30 years and smlarly for lght trucks. 19

23 scaled usng ˆ η / ~ η CC CC, where ~ η TT = Results shown n Table 2: own-prce vehcle elastctes vary between 1.40 and For the sngle vehcle model we assume a vehcle demand elastcty η v of 0.36, based on the long run change n car and truck demand to a 1% ncrease n all vehcle prces that we estmated usng the Harrngton et al. (2003) model. 25 And we assume a mles per vehcle elastcty η m = D. Local Polluton Costs () Talppe emssons and fuel economy. Frst, we valdate our assumpton that local talppe emssons are ndependent of fuel economy wthn car and lght truck classes. If there were no deteroraton over tme of abatement equpment nstalled n new vehcles to satsfy a gven emssons per mle standard, mprovng a vehcle s fuel economy would have no effect on ts lfetme per mle emssons rate. However, because abatement equpment deterorates over tme, and vehcles wth lower fuel economy have greater engne-out emssons (.e. emssons nto the catalytc converter), t s concevable that talppe emssons wll be negatvely related to fuel economy n used vehcles. Indeed, Harrngton (1997) dentfed ths negatve relaton, by mappng remote sensng data on vehcle emssons n 1990 from the Arzona Inspecton and Mantenance (I/M) Program to EPA-certfed fuel economy data. However these results need to be revsted because current motor vehcles have more durable control equpment than the 1990 fleet, and even f the negatve relaton perssts t may have lost ts practcal sgnfcance gven the rapd declne n new vehcle emsson rates snce In contrast, aggregate vehcle demand falls by 1.2% followng a 1% ncrease n all vehcle prces n the GM model, whch s consstent wth other short-run estmates (e.g., McCarthy 1996, p. 543). 26 In recent tme seres the estmated elastcty of vehcle mles wth respect to fuel costs s around 0.1 n the short run, ncreasng to 0.2 or more over the long run; results from studes usng cross-sectonal survey data are more varable (see Greene et al and Small and van Dender 2004 for more dscusson). In the Washngton-START model descrbed below the mleage elastcty s These estmates understate the magntude of η m somewhat as they are net of the reducton n vehcle demand. 20

24 We repeated Harrngton s analyss of deteroraton rates usng data from the Arzona I/M program collected n 1995 and 2002 on car and truck emssons of volatle organc compounds (VOC), ntrogen oxdes (NO x ), and carbon monoxde (CO). 27 The 1995 dataset showed that emsson rates were stll sgnfcantly affected by fuel economy (though less so than n 1990); however we were unable to fnd much of an effect n the 2002 dataset. 28 As shown n Fgure 3, projected CO, hydrocarbon (HC) and NO x emssons per mle for cars wth certfed fuel economy of 20 and 30 mpg are vrtually ndstngushable over vehcle lfetmes; the same apples wthn trucks. 29 Thus t seems reasonable to assume lfetme emsson rates are equvalent for dfferent cars and for dfferent lght trucks. () Per mle talppe emsson damages. We obtaned average emssons per mle over car and truck lfetmes usng data n Fgure 3, and above assumptons about mles drven n each year of the vehcle lfe. We multply average emssons by (adjusted) damage estmates from Small and Kazm (1995), 0.19 cents per gram for VOC, 0.69 cents per gram for NO X, and zero for CO, 30 and aggregate over pollutants. The result s external damages of 1.1, 2.0, and 1.5 cents per mle for cars, lght trucks, and all vehcles respectvely. 27 Sample szes were 60,000 vehcles per month over a 12-month perod for 1995 and 35,000 per month for 2002 (the dfference beng due to new exempton rules for new vehcles). The test tself changed between these dates; however, we were able to transform 1995 test results nto 2002 test results usng a procedure developed by Serra Research (2003). 28 We used a Davdson-MacKnnon (1981) test to compare a smple model of emssons deteroraton based on mleage versus one based on fuel economy. The fuel economy model performed better n fve out of sx vehcle/polluton groups n In 2002 the superorty of the fuel economy model s lmted to car HC and CO; n other cases the mleage model does as well or better. Statstcal results are avalable from harrngton@rff.org. 29 The graphs n Fgure 3 were obtaned through regressng emssons on fuel economy for vehcles of a gven age, and readng off emssons from ths relaton at mpgs of 20 and See ther Table 5, baselne assumptons. Damages are domnated by mortalty effects; we scale estmates to be consstent wth the value of lfe for traffc fataltes assumed below. Small and Kazm s estmates are on the hgh sde as they apply to Los Angeles (rather than the naton as a whole), where the topography tends to trap pollutants and the clmate favors photochemcal reactons. 21

25 () Upstream emssons leakage. The most mportant pollutant emtted durng the actvtes of petroleum producton, refnng, transport and storage s VOCs. In 1999, petroleum ndustry VOC emssons amounted to 9.8 grams per gallon; 31 usng our damage estmate gves 1.9 cents per gallon. E. Global Polluton Costs Most economc assessments of the damages to future world agrculture, forestry, coastal actvtes, and so on, from carbon emssons put damages at well below $50 per ton of carbon (Tol et al. 2000, Pearce 2003). A few studes obtan much hgher values by attachng dfferng dstrbutonal weghts to rch and poor natons (the latter beng the most at rsk from clmate change) and assumng zero rates of tme preference (e.g., Tol 1999). The possblty of abrupt, nonlnear clmate change may also be understated n conventonal damage assessments (Schneder 2004). We follow NRC (2002) n adoptng a benchmark value of $50 per ton and consder other values later; snce a gallon of gasolne contans tons of carbon (NRC 2002) ths converts to 12 cents per gallon. F. Congeston Costs We are unaware of prevous estmates of natonwde margnal congeston cost (MCC). 32 To obtan an estmate we begn wth a model of the Washngton, DC, metropoltan area road 31 Calculated from EIA (2002) and EPA (1999), Appendx A-5. The emssons rate has fallen by 64% snce 1980 due, at least n part, to ncreased regulatory strngency. 32 Schrank and Lomax (2002) estmate average congeston costs per mle for 75 U.S. ctes. However, MCCs are hghly convex wth respect to traffc volumes under congested condtons, so t s dffcult to nfer MCC from average costs, even f we had estmates for all 348 ctes. Moreover, n dervng MCCs averaged across tme of day, we need to account for the weaker senstvty of peak-perod drvng to fuel costs than off-peak drvng; the former s domnated by commutng, and fuel costs are a smaller porton of combned tme and money costs of drvng. Furthermore, n computng MCC, account should be taken of varous re-allocatons of travel across peak and offpeak perods, and across roads wth dfferent degrees of congeston wthn a perod, as the pattern of drvng and congeston changes (Yang and Huang 1998); ths requres a network model. 22

26 network, Washngton-START. 33 Fuel economy s a parameter nput nto the model that affects per mle drvng costs. We ncrease ths parameter ncrementally and calculate the change n consumer welfare, after nettng out fuel savngs. Ths gves an estmate of net welfare change from added congeston and utlty of the addtonal trps taken by motorsts. Dvdng by extra aggregate mleage we obtan an MCC of 7.7 cents per mle. We extrapolate a natonwde MCC estmate as follows. We compute MCCs from the Washngton-START model wth the baselne populaton and travel demand scaled by between +20% and 40%, holdng the road capacty fxed; results are used to estmate a relaton between MCC and the mleage/pavement rato (R), where R s normalzed to unty for Washngton. We then nferred values for MCC for the 75 ctes for whch R can be obtaned from Schrank and Lomax (2002), usng our MCC/R relaton. These 75 ctes are then classfed nto four bns accordng to ther populaton and an average of MCCs for each bn s then obtaned: MCCs vary between 7.3 cents per mle for ctes wth over 3 mllon populaton to 2.2 cents per mle for ctes wth 100,000 to 500,000 populaton. We attrbute one of these four MCC values to the remanng 273 ctes usng populaton fgures from the Census Bureau. Fnally, we aggregate MCCs over all ctes usng the shares of total U.S. populaton wthn each cty class, and assumng MCC for areas outsde ctes s zero. The result s a natonwde MCC of 6.5 cents per mle. 34 G. External Accdent Costs We follow the methodology n Parry (2004) to estmate external accdent costs per mle for the ten vehcle types. 33 In the model, households have a nested logt utlty functon and optmze over trps, destnaton, mode, tme of day, and route. Forty travel zones are dsaggregated wth arterals and sde streets wthn each zone aggregated nto an n-bound, out-bound, and crcumferental lnk; freeway segments and brdges are also ncorporated. The dstrbuton of travel and the speed/traffc flow curves are taken from the Metropoltan Washngton Councl of Governments transportaton plannng model. Behavoral responses to travel costs at dfferent tmes of day are calbrated to estmates n the travel demand lterature. See Safrova et al. (2004) for more dscusson of the model. 34 Ths fgure s for the costs of recurrent congeston. Nonrecurrent congeston due to accdents s ncorporated below; congeston from roadworks and bad weather s excluded. 23