WELFARE IMPACTS OF ALTERNATIVE BIOFUEL AND ENERGY … · addition, the Energy Policy Act of 2005...

WELFARE IMPACTS OF ALTERNATIVE BIOFUEL

AND ENERGY POLICIES

JINGBO CUI, HARVEY LAPAN, GIANCARLO MOSCHINI, AND JOSEPH COOPER

An open-economy equilibrium model is derived to investigate the effects of energy policy on the U.S.economy,with emphasis on corn-based ethanol.A second best policy of a fuel tax and ethanol subsidy isfound to approximate fairly closely the welfare gains associated with the first best policy of an optimalcarbon tax and tariffs on traded goods. The largest economic gains to the U.S. economy from theseenergy policies arise from their impact on U.S. terms of trade,particularly in the oil market. Conditionalon the current fuel tax, an optimal ethanol mandate is superior to an optimal ethanol subsidy.

Key words: biofuel policies, carbon tax, ethanol subsidy, gasoline tax, greenhouse gas emissions,mandates, renewable fuel standard, second best.

JEL Classification: Q2, H2, F1.

Two interrelated critical issues facing theUnited States and world economies are thedwindling supply of fossil fuels and the increas-ing emissions of carbon into the atmosphere.The U.S. dependence on imported oil hasincreased sharply in the past quarter century,with a number of significant economic andpolitical consequences. Oil imports worsen theU.S. balance of trade deficit and, together withgrowing energy consumption from develop-ing countries such as China, lead to higherprices. This dependence on oil imports weak-ens U.S. national security and entails significantmilitary and defense expenditures to ensurecontinued U.S. access to world oil supplies. Sep-arately, there is the concern over greenhousegas (GHG) emissions associated with fossil fuelenergy use. While some disagreement exists onthe potential implications of carbon buildup inthe atmosphere, it seems that major industri-alized countries are moving toward a regimein which these emissions will be regulated and(or) priced.

Jingbo Cui is a Ph.D. student, Harvey Lapan is a university pro-fessor, and GianCarlo Moschini is professor and Pioneer Chair inScience and Technology Policy, all with the Department of Eco-nomics, Iowa State University. Joseph Cooper is with the EconomicResearch Service, USDA. This study was partially supported bya cooperative research project with the Economic Research Ser-vice. The views expressed in this article are those of the authorsand may not be attributed to the Economic Research Service orthe USDA. The authors thank editor Erik Lichtenberg and thejournal’s reviewers for helpful comments.

Partly in response to such issues,governmentsupport for biofuels has led to rapid growthin U.S. ethanol production, which increasedfrom 1.65 billion gallons in 2000 to 10.76 billiongallons in 2009, making the United States thelargest world producer of ethanol. U.S. ethanolproduction currently benefits from a $0.45/gal-lon subsidy (technically an excise tax credit),anout-of-quota ad valorem import tariff of 2.5%,and a $0.54/gallon duty on ethanol imports. Inaddition, the Energy Policy Act of 2005 spec-ified a Renewable Fuel Standard (RFS1) that“mandated” specific targets for renewable fueluse, the level of which has been considerablyexpanded by the Energy Independence andSecurity Act of 2007 and its RFS2. Since then,the ethanol mandates under RFS2 have beenmore than met, and renewable fuel require-ments have risen from 12.95 billion gallons in2010 to 20.5 billion gallons in 2015 to 36 billiongallons in 2022. Of these requirements, up to15 billion gallons may come from ethanol,whilethe rest are meant to come from “advancedbiofuels,” such as cellulosic biofuel.

The purpose of this article is to providean economic analysis of the welfare impli-cations of U.S. policies that impact biofuelproduction. Facets of this topic have been thesubject of a few studies. de Gorter and Just(2009a) analyze the impact of a biofuel blendmandate on the fuel market. They find thatwhen tax credits are implemented along withthe blend mandate, tax credits subsidize fuel

Amer. J. Agr. Econ. 93(5): 1235–1256; doi: 10.1093/ajae/aar053Received June 10, 2011; published online October 2, 2011

© The Author (2011). Published by Oxford University Press on behalf of the Agricultural and Applied EconomicsAssociation. All rights reserved. For permissions, please e-mail: [email protected]

at Iowa State U

niversity on April 29, 2013

http://ajae.oxfordjournals.org/D

ownloaded from

http://ajae.oxfordjournals.org/

1236 October 2011 Amer. J. Agr. Econ.

consumption instead of biofuels. de Gorter andJust (2009b) also develop a framework to ana-lyze the interaction effects of a biofuel taxcredit and a price-contingent farm subsidy. Theannual rectangular deadweight costs—whicharise because they conclude that ethanol wouldnot be commercially viable without govern-ment intervention—dwarf in value the tra-ditional triangular deadweight costs of farmsubsidies. Elobeid and Tokgoz (2008) set upa multimarket international ethanol model toanalyze the influence of trade liberalizationand the removal of the federal tax credit in theUnited States on ethanol markets. They findthat the removal of current tariffs on importedethanol would lead to a 13.6% decrease inthe U.S. domestic ethanol price and a 3.7%increase of ethanol’s share in U.S. fuel con-sumption and that the removal of both taxcredit and tariffs would cause U.S. ethanolconsumption to fall by 2.1% and the price ofethanol to fall by 18.4%.

The foregoing studies do not account explic-itly for the impact of climate policies on GHGemissions associated with the fuel energy sec-tor. Khanna, Ando, and Taheripour (2008)examine the welfare impact of a carbon tax($25 per metric tonne of carbon [tC]) on fuelconsumption, when the purpose of the tax isto correct the pollution externality from car-bon emissions and to account for the otherexternal costs associated with congestions andaccidents. At the time of their study, they foundthat the fuel tax of $0.387/gallon and the then-current ethanol subsidy of $0.51/gallon reducescarbon emissions by 5% relative to the no-tax,laissez faire situation. Their second best policyof a $0.085/mile tax with a $1.70/gallon ethanolsubsidy could reduce gasoline consumption by16.8%, thereby reducing carbon emissions by16.5% (71.7 million tC).1

In assessing the effectiveness of ethanolin reducing GHG emissions, an issue thathas commanded considerable attention is thatof “indirect land use” effects: The diversionof feed corn to ethanol production in theUnited States increases aggregate demandfor agricultural output and might bring newmarginal land into production (Searchingeret al. 2008). To assess the global economicand land use impacts of biofuel mandates,

1 Some studies discuss emissions in terms of metric tons ofcarbon (tC), others in terms of metric tons of carbon dioxide(tCO2). One ton of carbon is equivalent to 3.67 tons of carbondioxide. Of course, when reductions are expressed in percentages,units will not matter.

Hertel, Tyner, and Birur (2010) use acomputable general equilibrium model builtupon the standard Global Trade AnalysisProject modeling framework. To jointly meetthe biofuel mandate policies of the UnitedStates (15 billion gallons of ethanol by 2015)and the EU (6.25% of total fuel as renewableby 2015), they find that coarse grains acreage inthe United States rises by 10%, oilseed acreagein the EU increases dramatically by 40%, crop-land areas in the United States increase by0.8%, and about one-third of these changesoccur because of the EU mandate policy. TheU.S. and EU mandate policies jointly reducethe forest and pastureland areas of the UnitedStates by 3.1% and 4.9%, respectively. Themost recent RFS2 pronouncement by the EPAaccounts for international indirect land usechanges (ILUCs) and makes several changesfor GHG emission reduction of ethanol fromall feedstocks (U.S. Environmental ProtectionAgency [EPA] 2010). Accounting for ILUCs,the EPA finds that corn ethanol still achieves a21% GHG reduction compared with gasoline.The EPA also finds, using its ILUC modifi-cation, that sugarcane ethanol qualifies as anadvanced biofuel because it achieves an aver-age 61% GHG reduction compared with base-line gasoline, which exceeds the 50% GHGreduction threshold for advanced biofuels

Lapan and Moschini (2009) note that mostexisting work does not explicitly accountfor the welfare consequences to the UnitedStates of policies supporting biofuel produc-tion (such as the externality of GHG emis-sions or the benefits to the United States thataccrue either from improved terms of tradeor from “improved national security” due todecreased reliance on oil imports). To considerfirst and second best policies within that nor-mative context, Lapan and Moschini build asimplified general equilibrium (multimarket)model of the United States and the rest-of-the-world economies that links the agriculturaland energy sectors to each other and to theworld markets; they model the process bywhich corn is converted into ethanol, accountfor by-products of this process, and allow forthe endogeneity of world oil and corn prices,as well as the (different) carbon emissions fromgasoline derived from oil and from blends withethanol. The analysis by Lapan and Moschini(2009) is theoretical in nature, aiming at pro-viding analytical insights and results. They findthat the first best policy would include a tax oncarbon emissions, an import tax on oil, and anexport tax on corn. If policy is constrained—for

at Iowa State U



ownloaded from


Cui et al. Welfare Impacts of Biofuel and Energy Policies 1237

example, by international obligations—theyfind that a fuel tax and an ethanol subsidy canbe welfare enhancing. They also find that anethanol mandate is likely to welfare-dominatean ethanol subsidy.

In this article we construct a tractable com-putational model that applies and extendsthe analytical setup of Lapan and Moschini(2009), and we use the model to provide quan-titative estimates of the welfare benefits ofalternative policies. The model specificationallows endogenous determination of equilib-rium quantities and prices for oil, corn, andethanol and is calibrated to represent a recentbenchmark data set for the year 2009, usingthe available econometric evidence on elas-ticity estimates. By varying some governmentpolicies, we explore how these policies affectequilibrium (domestic and world) prices ofcorn, oil, ethanol, and gasoline. Throughout theanalysis, we maintain the assumption that dueto a prohibitive tariff, there are no U.S. importsof ethanol. This approach is consistent witha number of other articles that have studiedthe impact of biofuel mandates (e.g., the the-oretical model of de Gorter and Just 2009a;de Gorter and Just 2009b; Khanna, Ando,and Taheripour 2008). Whereas some modelshave considered the possibility of U.S. ethanolimports (e.g., Elobeid and Tokgoz 2008), all ofthe foregoing studies have treated world oilprices as exogenous.As discussed in the conclu-sion, the welfare consequences of eliminatingthis (prohibitive) ethanol tariff would be sig-nificantly affected by the endogeneity of worldoil prices.

Using standard welfare measures, we com-pare the net welfare implications of alternativepolicies and show how different groups areaffected by them. In addition to characteriz-ing the first best policy, we consider a numberof second best interventions involving vari-ous combinations of ethanol mandates,ethanolsubsidies, and a fuel tax. Using the model,we calculate the optimal values for the pol-icy instruments (given the constraint on whichinstruments are used) and the associated wel-fare gains. We then explore the robustnessof our conclusions by varying the values ofvarious parameters.

Our results consistently show that the largesteconomic gains to the United States frompolicy intervention come from the impact ofpolicies on U.S. terms of trade, particularlyon the price of oil imports. We also find thatfirst best policy outcomes, which would requireoil import tariffs that are not consistent with

U.S. international obligations, can be closelyapproximated by second best tools such asfuel taxes. Furthermore, our results probablyunderestimate the gains that come from reduc-ing U.S. oil imports because the model does notaccount for any of the “national security” gainsthat could arise from reduced U.S. dependenceon imported oil.

The Model

We adapt and extend the model developed inLapan and Moschini (2009) to make it moresuitable for simulating the consequences ofalternative policies directed toward reducingU.S. GHG emissions and reducing U.S. relianceon oil imports. The extension recognizes thatwhen oil is refined, other products, in additionto gasoline, are produced (distillate fuel oil,jet fuel, etc.). We aggregate all the nongaso-line output into a single good called petroleumby-products. The model is a stylized econ-omy with three basic commodities:a numerairegood, corn (food) output, and oil. In addition,there is a processing sector that refines oil intogasoline and other petroleum by-products, andanother sector that converts corn into ethanol,which may then be blended with gasoline tocreate fuel used by households. Consumersare assumed to have quasi-linear preferences(which can then be aggregated into a repre-sentative consumer) with the following utilityfunction:

U = y + ϕ(Df ) + θ(Dc)

+ η(Dh) − σ(xg + λxe)(1)

where y represents consumption of thenumeraire, and Df , Dc, and Dh represent con-sumption of fuel, of food, and of petroleumby-products, respectively. The last term, σ(·),represents environmental damages from car-bon emissions due to aggregate combustion ofgasoline and ethanol. The parameter λ reflectsthe relative pollution emissions of ethanolcompared with gasoline (we will return to thisparameter later).

The basic elements of the model consist ofthe following:

1. U.S. demand for corn as food/feed, repre-sented by Dc(pc)

2. U.S. demand for fuel Df (pf )3. U.S. demand for petroleum by-products

Dh(ph)

at Iowa State U



ownloaded from



4. U.S. corn supply equation Sc(pc)5. U.S. oil supply equation So(po)

6. Foreign oil export supply curve So(pwo )

7. Foreign corn import demand curve Dc(pwc )

8. U.S. oil refining sector, which converts oilinto gasoline and petroleum by-products

9. U.S. ethanol production sector,which con-verts corn into ethanol and produces aby-product of dried distillers grains withsolubles (DDGS), which becomes part ofthe food/feed supply

Components 1–7 are self-explanatory. Inparticular, the (household) demand curves(1.–3.) come from utility maximization andthus are the inverse of the marginal utilityrelations ϕ′(Df ), θ ′(Dc), and η′(Dh), respec-tively, and pf , pc, ph are the prices facinghouseholds.2 The domestic supply relations(4. and 5.) come from competitive profit max-imization so that (assuming no externalitiesassociated with their production) they are theinverse of the marginal private (and social)costs; because we assume no taxes on domes-tic corn or oil producers, pc and po representboth supply and demand prices.3 Foreign rela-tions (6. and 7.) represent aggregate excessworld oil supply and world corn demand, anddistinguishing the world prices (pw

o , pwc ) from

domestic prices allows for the possibility of U.S.border policies (tariffs or quotas) that wouldcause U.S. prices to diverge from world prices.Note that if the United States were a smallcountry, world prices (pw

o , pwc ) would be exoge-

nous to U.S. economic conditions. However, inreality, the United States is a large economicagent in both markets, and our simulation willreflect that fact. Throughout the analysis, weassume that U.S. tariffs on ethanol imports areprohibitive, so the U.S. ethanol price is decou-pled from the world price. Finally, components8 and 9 require a bit more elaboration.

Oil Refining Sector

The refinement of oil yields gasoline xg andpetroleum by-products xh. We assume a fixedcoefficients production technology so that the

2 Since the marginal utility of the numeraire is one, the marginalrate of substitution between each of the three consumption goods(food, fuel, and petroleum by-products) and the numeraire is thesame as the marginal utility of that good.The price of the numeraireis (by definition) normalized to one, so pf , pc , and ph representrelative prices.

3 We do allow for taxes or subsidies on fuel and ethanol, whichis equivalent to taxes or subsidies on gasoline and ethanol.

process is represented as follows4:

xg = Min[βxo, zo](2.1)

xh = β2xg/β(2.2)

where xg is gallons of gasoline output, xh is gal-lons of the petroleum by-product, xo is barrelsof oil input (where domestically produced oiland imported oil are perfect substitutes), andzo is the amount of a composite input, whichaggregates all other inputs used in the oil refin-ing process. Thus, β is the number of gallonsof gasoline per barrel of crude oil, and β2 is thenumber of gallons of the petroleum by-productper barrel of oil. This technology and perfectcompetition imply the following relationshipamong input and output prices:

(3) βpg + β2ph = po + βωg

where ωg represents the unit cost of the com-posite input zo, including the rental price ofcapacity.

Ethanol Production Sector

We also assume a fixed coefficients productionprocess for ethanol production:

(4) xe = Min[αxc, ze]where xe is ethanol output and ze is the amountof other inputs used per unit of ethanol out-put. Because the energy content of ethanol ismuch lower than that of gasoline,and given ourworking assumption that consumers’ demandtake that into account (e.g., they ultimatelycare about the miles traveled with any givenamount of fuel, as discussed by de Gorter andJust 2010), it is important to keep track ofthis fact to handle the blending of ethanoland gasoline (into fuel) in a consistent fashion.Consequently, xe in equation (4) and in whatfollows is measured in what we term “gasoline-energy-equivalent gallons” (GEEGs).5 Fur-thermore, we wish to account for the valuablebioproducts of ethanol production by countingonly the “net” use of corn in the technological

4 Although in reality there is some substitutability among thevarious products produced from crude oil, it seems that this substi-tutability is limited and that the assumption of fixed proportions inoutput provides a reasonable approximation.

5 This measure is related to the more common notion of a“gasoline gallon equivalent,” which is defined as the amount ofalternative fuel it takes to equal the energy content of one gallon ofgasoline (essentially this represents the reciprocal of our measure).

at Iowa State U



ownloaded from



relation in equation (4). That is, if one bushelof corn used in ethanol production also yieldsδ1 units of DDGS, which, being a close cornsubstitute in feed use, we assume commandsa price of δ2pc, then the net amount of cornrequired to produce a gallons of ethanol is only(1 − δ1δ2). Hence, the production parameter αin equation (4) satisfies

(5) α = aγ

1 − δ1δ2

where a is the number of gallons of ethanol (innatural units) per bushel of corn; γ capturesthe lower energy content of ethanol (relativeto gasoline); δ1 represents the units of DDGSper bushel of corn used to produce ethanol;andδ2 represents the relative price of DDGS.

Given perfect competition in the ethanolsector, this implies the following price relationbetween the supply price of ethanol and theprice of corn6:

(6) pe = pc

α+ ωe

where ωe is the cost of all inputs other thancorn, including the rental cost of plant capacity,required to produce one unit of ethanol (mea-sured in GEEGs) and pe is the price of oneGEEG of ethanol.

Equilibrium

In order to simulate the model,we need to spec-ify the equilibrium conditions that must holdand the set of policy instruments that are con-sidered. For the purpose of our policy analysis,the policy instruments that we allow are borderpolicies, fuel taxes, and ethanol subsidies/taxes(or border policies, ethanol mandates, andethanol subsidies).7 We assume that there istrade in crude oil but no trade in the refinedproducts, which is a fair approximation of thestatus quo.8 Given all that, the equilibrium

6 If the United States imported ethanol,we would need to specifythe net world export supply of ethanol to close the model.

7 If we also allowed, for example, a tax/subsidy on corn produc-tion, we would have to distinguish between the supply and demandprices for corn.

8 Although imports account for over 50% of U.S. crudeoil consumption, over the period 2007–2009 net imports ofgasoline averaged about 1.7% of total consumption and nettrade of “refinery and blender finished petroleum product”averaged (in absolute value) under 3% of total consumption(calculated from the “Supply and Disposition Tables” of the U.S.

conditions are as follows9:

Sc(pc) = Dc(pc) + Dc(pwc ) + xe/α

(Corn Market Equilibrium)(7)

Df (pf ) = βSo(po) + So(pwo ) + xe

(Fuel Market Equilibrium)(8)

Dh(ph) = β2So(po) + So(pwo )

(Petroleum By-product

Equilibrium)(9)

βpg + β2ph = po + βωg

(Zero Profit Condition Oil Refining)(10)

pe = pc

α+ ωe (Zero Profit

Condition Ethanol Industry)(11)

po = pwo + τo

(Oil Import Arbitrage Relation)(12)

pwc = pc + τc

(Corn Export Arbitrage Relation)(13)

Note that equation (7) embeds the technolog-ical relationship xc = xe/α. In equations (12)and (13), τo and τc are the specific tariffsfor oil imports and corn exports, respectively(assumed to be nonprohibitive, so that tradestill occurs). To close the model, consider firstthe hypothetical case of laissez faire equilib-rium, in which τo = τc = 0 and there are noother active policy instruments that interferewith the competitive equilibrium. Then wemust also have pe = pg = pf , and subject to thisrestriction, equations (7)–(13) can be solvedfor the equilibrium prices (pc, pw

c , po, pwo , pf , ph)

and for the ethanol quantity xe. For scenariosin which there are active policy instruments, onthe other hand, model closure needs to be tai-lored to the specifics of the policy that applies(e.g., the case of fuel taxes and ethanol subsi-dies, or that of a binding ethanol “mandate”).

Equilibrium with Fuel Taxes and EthanolSubsidies

Let t be the consumption tax on fuel, per gal-lon, and b be the volumetric blending subsidy

Energy InformationAdministration,http://tonto.eia.doe.gov/dnav/pet/pet_sum_snd_d_nus_mbbl_m_cur.htm).

9 If there were world trade in ethanol, with perhaps some non-prohibitive import tariff, then an additional arbitrage conditionwould be needed to relate world and domestic ethanol prices.

at Iowa State U



ownloaded from

http://tonto.eia.doe.gov/dnav/pet/petprotect LY1extunderscore sumprotect LY1extunderscore sndprotect LY1extunderscore dprotect LY1extunderscore nusprotect LY1extunderscore mbblprotect LY1extunderscore mprotect LY1extunderscore cur.htm




per gallon of ethanol. Then, because gasolineand ethanol are modeled as perfect substitutesfor consumers once measured in GEEGs, andbecause one gallon of ethanol is equivalent toγ GEEGs, arbitrage relations imply10

(14) pg = pf − t

(15A) pe = pf + bγ

− tγ

= pg + b

where b ≡ (b − t(1 − γ ))/γ is the effective netsubsidy to ethanol, compared with gasoline,per GEEG.11 Thus, for the case of taxes andsubsidies, equations (7)–(15A) can be usedto calculate the equilibrium, given the policyparameters τo, τc, t, b.Equilibrium with Mandates

With a binding ethanol mandate (denoted byxM

e ),equations (7)–(13) still apply,but with xe =xM

e exogenously set. Note that in this case theamount of corn utilized by the ethanol industryis fixed at xM

e /α, and so, as equation (7) makesclear, the corn price is effectively determinedin the corn market. Furthermore, the pricesof fuel, gasoline, and ethanol will have to besuch that arbitrage possibilities are exhausted,i.e., blenders that combine ethanol and gaso-line earn zero profit. This zero profit condition,allowing for the existence of exogenous fueltaxes and ethanol subsidies, can be expressedas

(pf − t) · Df (pf ) = pg[Df (pf ) − xMe ]

+ (pe − b) · xMe .(15B)

Equation (15B) states that the price of fuel isa weighted average of the price of its compo-nents (ethanol, gasoline), where the amount ofethanol is exogenously determined. Thus, witha mandate, the equilibrium is calculated usingequations (7)–(13) and (15B). As shown byLapan and Moschini (2009), the impact of anethanol mandate is that of combining a fuel taxwith an ethanol subsidy in a revenue-neutralfashion.

10 The assumption of perfect substitutes seems valid up to at leasta 10% utilization rate for ethanol.

11 Note that equation (5) also accounts for the fact that the taxon fuel t is levied per volume unit. Because it takes 1/γ > 1 gallonsof ethanol to make one GEEG of fuel, the effective tax on ethanolis higher than that on gasoline.

Welfare

In defining welfare, we assume that all tax rev-enue is returned to domestic consumers andthat there are no externalities other than thosedue to carbon emissions. Domestic welfarecould be calculated using the indirect utilityfunction along with the profit function for thedomestic oil and corn industries and govern-ment tax revenue, or by using the direct utilityfunction along with the production costs fordomestic oil and corn and the net importsfrom world trade in oil and corn. Using thelatter approach, and consumer preferences inequation (1), we have

W = I − C(Qc) − (So) − ωexe

− ωgxg − [pwo So − pw

c Dc]+ [ϕ(xg + xe) + θ(Dc) + η(Dh)]− σ(xg + λxe).(16)

The term in curly brackets in equation (16)measures consumption of the numeraire good,y,while the term in square brackets on the thirdline measures consumer utility derived fromconsumption of fuel, corn, and petroleum by-products, and the last term measures the disu-tility due to pollution arising from energy con-sumption.12 Consumption of the numeraire inequation (16) is total income I (taken as exoge-nous and measured in numeraire units) less (a)C(Qc), the cost of aggregate corn output; (b) (So), the cost of domestic oil production; (c)ωexe + ωgxg, the cost of the other inputs usedin ethanol production and oil refining; and (d)

[pwo So − pw

c Dc], the value of net imports of oiland corn,which are paid for with the numerairegood. Note that the competitive equilibriumconditions C′(Qc) = pc and ′(So) = po yieldthe inverse supply curves, so specification ofthe supply curves for the two goods, used inequilibrium conditions (7) and (8), implies theform of the cost relations in equation (16).Similarly, specification of the demand rela-tions used in equations (7)–(9) imply the formsof the subutility functions in equation (16),so the only additional specification of func-tional forms needed for the welfare calcula-tions is that of the externality term, σ(..). Thus,

12 This formulation does not explicitly impute pollution to theuse of distillates. However, because gasoline and distillates arederived from a barrel of oil in fixed proportions in the model, thena tax on any one of them—properly adjusted—will have the sameeffect.

at Iowa State U



ownloaded from



for the simulation exercise, welfare compar-isons for different policy tools (τc, τo, t, b; xM

e )can be made by solving the relevant equilib-rium conditions, specifying σ(·) and then usingequation (16) to calculate welfare.

To understand how the optimal (or secondbest) policies are determined,take the total dif-ferential of equation (16) and rearrange terms(Lapan and Moschini, 2009) to yield

dW = (θ ′ − C′)dDc + (φ′ − λσ ′ − ωe

− (C′/α))dxe + ([φ′ + (β2/β)η′

− σ ′] − ωg − ( ′/β))dxg

+ ( ′ − [pwo + So(dpw

o /dSo)])× S′

odpwo + ([pw

c + Dc(dpwc /dDc)]

− C′)D′cdpw

c .(17)

The first three terms in equation (17) relateto domestic resource allocation decisions,whereas the last two relate to trade decisions,and for each term, optimality entails equat-ing marginal benefit to marginal cost. Thus,θ ′ is the value to consumers of additionalcorn consumption, C′ is the marginal cost ofcorn production,and hence optimality requiresthat marginal benefit equals marginal costθ ′ = C′. Similarly, the second term—relatingto ethanol production—says that the marginalvalue of fuel to consumers, less the pollu-tion cost, should be equated to the marginalcost of producing ethanol. A similar interpre-tation applies to the third term, where theterm in square brackets is the net social valueof another unit of refined gasoline and by-products, and [ωg + ( ′/β)] is the extractionand refining cost of producing that gallon. Theterms in the last three lines relate to trade deci-sions and are the only places where (world)prices appear explicitly; domestic prices affectdomestic welfare only insofar as they affectresource allocation,but changes in world pricesaffect domestic welfare directly. Thus, the lasttwo terms state that the marginal cost ofproducing oil domestically should equal themarginal cost of importing oil and that themarginal cost of producing corn domesticallyshould equal the marginal revenue derivedfrom corn exports.

In a market economy, rational consumersequate the marginal private value of a goodto the market price they face, and com-petitive profit-maximizing firms will equatethe marginal private cost to the prices they

face. Hence, the rationale for governmentintervention arises when there is some diver-gence between private and social costs orbenefits. In our model this divergence obvi-ously occurs when fuel is consumed, becauseof the externality generated by the combustionof that fuel. Furthermore, from the perspec-tive of the domestic economy, a divergencebetween private and (domestic) social costsalso occurs if the country’s trade decisionsaffect world prices. For example, for a compet-itive firm importing oil, the marginal privatecost of the import is its price pw

o , but fromthe perspective of the economy as a whole,if additional imports increase world price, themarginal cost of the import is higher than that,namely, pw

o + So(dpwo /dSo). Similarly, for corn

exports, the marginal value perceived by acompetitive corn exporter is pw

c , whereas themarginal revenue for the country as a wholeis pw

c + Dc(dpwc /dDc). Thus, as noted by Lapan

and Moschini (2009),the first best policy entailsoil import tariffs, corn export tariffs, and atax on carbon emissions.13 As for the latter,the “carbon tax” is fully equivalent, in thismodel, to a fuel tax (i.e., a tax on both gaso-line and ethanol) along with an ethanol subsidy(because of the assumed differential pollutionof ethanol, captured by the parameter λ).14

Specifically, it is shown that the “first best”policy instruments are15

t∗ = σ ′(·);b∗ = (1 − λ)σ ′(·)τ ∗

o = So(·)/S′o(·)

τ ∗c = Dc(·)/D′

c(·).

(18)

In our analysis, such a first best scenario pro-vides an important (and insightful) benchmarkfor other, perhaps more realistic, policy scenar-ios. Another useful benchmark is the laissezfaire scenario, i.e., the unfettered competitive

13 Article 1, Section 9 of the U.S. Constitution states:“No Tax orDuty shall be laid on Articles exported from any State,” so that thefirst best policy could not be supported through export tariffs oncorn. However, there are other constitutionally permissible policiesthat have the same economic consequences as export tariffs.

14 The first best net ethanol subsidy, b, reflects the differentialpollution rates between the two energy sources. The fact that thestatutory fuel tax is in gallon terms implies a higher effective taxon ethanol in GEEG units. Thus, even if ethanol caused the sameamount of pollution as gasoline, the first best would require apositive gross subsidy b to ethanol to offset the higher fuel tax.

15 To calculate the actual values of the instruments, the equilib-rium conditions described earlier must be used in conjunction withequation (18).

at Iowa State U



ownloaded from



equilibrium with t = b = τo = τc = 0. In fact, allwelfare calculations are reported as differencesrelative to the laissez faire, and comparisons ofeach policy scenario with the first best provideinformation as to the efficacy of the varioussecond best policies considered. Note that inall scenarios except the first best we restricttariffs to be zero (i.e., τo = τc = 0) so that, real-istically, they presume that the United Statesis in compliance with its obligations to theWorld Trade Organization.16 Once we imposethis restriction, we are operating in a “sec-ond best” environment and the (constrained)optimal values of these second best instru-ments depend on the feasible policy space. Asnoted, we assume the feasible policy instru-ments are fuel taxes and/or ethanol subsidies(or ethanol mandates and/or ethanol subsidiesor fuel taxes).17 Using these policy restrictionsand the behavioral conditions outlined earlier,equation (17) can be rewritten as

dW = (pf − pe − λσ ′)dxe

+ (pf − pg − σ ′)dxg

− Sodpo + Dcdpc.(17A)

Thus, when tariffs are not permitted, in deter-mining the welfare consequences of domesticpolicy instruments, one must consider theirimpact on the terms of trade as well as oncarbon emissions.As we shall see from the sim-ulations, under many plausible scenarios, it isthese “large country” effects that dominate thewelfare calculations. When there are no borderpolicies, it can be shown that equation (17A)reduces to18

dW =(

pf − pe − λσ ′ + Dc

αQ′(pc)

)dxe

+(

pf − pg − σ ′ − So

′(po)

)dxg.(17B)

16 Because an import tariff on a given good is equivalent to adomestic production subsidy and a domestic consumption tax ofthe same amount, banning import tariffs is equivalent to placinga restriction on domestic policies, which explains the second bestnature of these policy scenarios.

17 Thus, for example, we do not allow a tax on domestic cornproduction.

18 The paper by Lapan and Moschini (2009) contains the details,but the logic underlying equation (17B) is direct. If the governmentinduces increased ethanol use, this increases the price of corn:specifically, dpc/dxe = 1/αQ′. Similarly, increased gasoline use willdrive up the price of oil, harming the country by making importsmore expensive.

Here (po) ≡ β(So(po) + So(po)) is the supplyof unblended gasoline, and Q(pc) ≡ Sc(pc) −Dc(pc) − Dc(pc) is the residual supply of cornfor ethanol. When both fuel taxes and ethanolsubsidies can be used, the second best policiesare

tsb = σ ′ + So

′

bsb = (1 − λ)σ ′ + So

′ + Dc

αQ′

(19)

where the superscript sb denotes second best.The tax tsb can be thought of as the taxlevied on gasoline,which incorporates two pos-itive components because increased gasolineuse worsens the U.S. terms of trade for oiland increases pollution costs. The differencebetween the tax and subsidy optimal levels,bsb − tsb = Dc/αQ′ − λσ ′, represents the effec-tive overall subsidy (or tax) on ethanol;the pos-itive component reflects the fact that increasedethanol use benefits the United States byincreasing world corn prices, while the neg-ative component reflects the pollution costsassociated with ethanol use.

When the ethanol subsidy is the only choicevariable, the government cannot indepen-dently control gasoline and ethanol consump-tion. For this case it can be shown that theoptimal ethanol subsidy, as a function of theexogenous fuel tax, t0, is19

bsub = Dc

αQ′ − λσ ′ + ρ

(σ ′ + βSo

ψ ′

)

+ (1 − ρ)t0(20)

where

ρ = β′

β′ −D′f +β′(β2/β)2(D′

f /D′b)

∈ (0, 1).

Note that bsub = bsb + (1 − ρ)(t0 − tsb). Hence,when the fuel tax is not a choice variable andt0 < tsb, then the subsidy will generally be lowerthan the second best subsidy and this subsidywill be increasing in the exogenous tax rate.

19 This formula differs from the corresponding one of Lapanand Moschini (2009) because here we explicitly allow for the pres-ence of petroleum by-products, a feature that is important for thequantitative results of interest in this study. In the special casewhere β2 = 0 (i.e., no by-products), of course, the two conditionsare identical.

at Iowa State U



ownloaded from



When only the mandate is the choicevariable, it can be shown that the first-ordercondition for an optimal choice of the mandatereduces to20

dWdxe

=(

pf − pe − λσ ′ + Dc

αQ′

)

+(

pf − pg − σ ′ − So

′

)

×(

dxg

dxe

)man

= 0(21)

where the superscript man denotes the man-date scenario, and(

dxg

dxe

)man

=−

(1 +

( −D′f

α2Q′

)s + (1 − s)δ

(−D′f

xf

))1 + (−D′

f )(

1β′ + (β2/β)2

−D′b

)(1 − s) + sδD′

f

xf

where s ≡ xe/(xe + xg) ∈ (0, 1) denotes theshare of ethanol in total fuel, and δ ≡ (pe −pg − b) > 0. In the simulations that follow, weconsider each of the cases discussed above.

Calibration of the Model

The baseline model is calibrated to fit 2009data using linear supply and demand curves.In order to calibrate the model, we need tospecify the values of the exogenous param-eters and the value of the policy variablesin this baseline period. In addition, we alsoneed to specify the domestic and world importdemand functions for corn Dc(pc) and Dc(pw

c ),the domestic supply of corn Sc(pc), the domes-tic and world export supply functions foroil So(po) and So(pw

o ), the demand for fuelDf (pf ), and the demand for petroleum by-products Dh(ph). If these functions come froma two-parameter family of functions, as forthe linear functional forms that we will beusing, each demand or supply function can be“calibrated” using an estimate of the elasticity(of supply or demand) for that function and the

20 Again, the procedure for deriving this result is similar to thatin Lapan and Moschini (2009),but the specific result differs becauseof the presence, in our model, of petroleum by-products.

value of the relevant variables in the baselineperiod.

Table 1A gives the assumed baseline values,and sources, for the primitive parameters(e.g., elasticities) used in the calibration ofthe model, and table 1B gives the valueof some other calculated parameters, andtheir method of calculation, which are pro-vided to ease the interpretation of the model.Tables 2A and 2B give the primary sources(or methods of calculation) and the 2009value used for each baseline variable, includ-ing the policy variables. Some parameters aredrawn from a comprehensive survey of theliterature, while others are calculated fromtheir definitions in terms of more primitiveterms. In general, data for corn utilizationand price are gathered from the Feed GrainDatabase of the USDA (http://www.ers.usda.gov/Data/FeedGrains) and data for oil, gaso-line, and oil refinery by-products are obtainedfrom the U.S. Energy Information Adminis-tration (EIA;http://www.eia.doe.gov). Ethanolquantity data are from the Renewable FuelsAssociation (RFA; http://www.ethanolrfa.org),and ethanol prices are provided by theNebraska Energy Office (NEO; http://www.neo.ne.gov/statshtml/66.html). More specificinformation on sources of data used is providedin the tables that follow.

Prices in the Baseline

Because ethanol has a lower energy con-tent than gasoline, its quantity, price, fuel tax,and subsidy level used in the simulation areall converted to be expressed per GEEG.Currently, fuel consumption (blended gaso-line with ethanol) is subject to the federaltax of $0.184/gallon plus state taxes, whichare, on average, equal to $0.203/gallon. Hence,for gasoline, t0 = $0.39. However, because 1.0gallon of ethanol equals only 0.69 GEEG,the fuel tax on ethanol is t0/γ , that is,$0.565/GEEG. Ethanol production has a taxcredit of b0 = $0.45/gallon when blended withgasoline, which is equivalent to a net sub-sidy to ethanol of b0 = $0.475/GEEG. The U.S.ethanol price of $1.79/gallon is the 2009 aver-age rack price F.O.B. Omaha, Nebraska, andthis corresponds to a price of $2.59/GEEG.21

Prices of fuel and (unblended) gasoline arecalculated from arbitrage conditions, which

21 See http://www.neo.ne.gov/statshtml/66.html for the primarydata.

at Iowa State U



ownloaded from

http://www.ers.usda.gov/Data/FeedGrains

http://www.ers.usda.gov/Data/FeedGrains

http://www.eia.doe.gov

http://www.ethanolrfa.org

http://www.neo.ne.gov/statshtml/66.html





Table 1A. Primitive Parameters Used to Calibrate the Model

Parameter Symbol Value Source/explanation

Domestic supply elasticity of oil εo 0.20 de Gorter and Just (2009b)Foreign supply elasticity of oil εo 3.00 de Gorter and Just (2009b)Domestic supply elasticity of corn εc 0.30 Westhoff (priv. comm., 2010)Foreign demand elasticity of corn ηc −1.50 Food and Agricultural Policy Research

Institute (2004)Domestic demand elasticity of corn ηc −0.20 de Gorter and Just (2009b)Demand elasticity of fuel ηf −0.50 Toman, Griffin and Lempert (2008)Demand elasticity of petroleum

by-productsηh −0.50 Assumed equal to ηf

Ethanol produced by one bushel ofcorn (gallons/bushel)

a 2.8 Eidman (2007)

DDGS production coefficient δ1 0.303 δ1 = 17/56DDGS relative price to corn δ2 0.776 δ2 = (114.4 × 56)/(3.74 × 2205)

Gasoline production coefficient(gallon/barrel)

β 23.6 β = xg/xo

Ethanol heat content (BTUs/gallon) γe 76,000 National Renewable EnergyLaboratory (2008)

Gasoline heat content (BTUs/gallon) γg 110,000 National Renewable EnergyLaboratory (2008)

CO2 emissions rate of gasoline(kg/gallon)

CEg 11.29 Wang (2007)

CO2 emissions rate of ethanol(kg/GEEG)

CEe 8.42 Farrel et al. (2006)

Marginal emissions damage ($/tCO2) σ ′(·) 20 Stern (2007), National Highway TrafficSafety Administration (2009)

Table 1B. Calculated Parameters Used in the Model

Parameter Symbol Value Source/Explanation

Derived supply elasticity of ethanol εe 5.01 εe = (εscSc − ηcDc − ηcDc)αpe/Qcpc

Derived supply elasticity of gasoline εg 1.61 εg = (εoSo + εoSo)βpg/xopo

Portion value of DDGS returning to corn market δ1δ2 0.24 Calculated

Ethanol produced by one bushel of cornaccounting for DDGS value (GEEG/bushel)

α 2.53 α = aγ

1 − δ1δ2

Petroleum by-product production coefficient(GEEG/barrel)a

β2 21.1 β2 = 42 × 1.065 − β

Ethanol energy equivalent coefficient(GEEG/gallon)

γ 0.69 γ = γe/γg

Relative pollution efficiency λ 0.75 λ = CEe/CEg

Normalized marginal emissions damage ofgasoline ($/gallon)

σ ′(·) 0.226 σ ′(·) = σ ′(·)CEg/1000

Note: aA 42-U.S.-gallon barrel of crude oil provided around 6.5% average gains from processing crude oil in 2009 (see Refinery Yield Rate Table [EIA],http://tonto.eia.doe.gov/dnav/pet/pet_pnp_pct_dc_nus_pct_m.htm).

are assumed to hold in the status quo, thatis, pf = pe − b0 + t0 = $2.50/GEEG, and pg =pe − b0 = $2.11/GEEG.22 The crude oil price

22 This calculation method ensures the internal consistency ofour model. A question, perhaps, is how close this calculated value

of $61.00/barrel is the refiner’s compositeacquisition cost of crude oil, the weighted

is to 2009 observed data. From EIA data, the average retail price ofall grades and all formulations of gasoline in 2009 was $2.406/gallon,which is fairly close to the calculated fuel price. Also, from the samesource, the average wholesale (rack) price of gasoline in 2009 was$1.75/gallon, which is not too close to our computed gasoline price.

at Iowa State U



ownloaded from

http://tonto.eia.doe.gov/dnav/pet/petprotect LY1extunderscore pnpprotect LY1extunderscore pctprotect LY1extunderscore dcprotect LY1extunderscore nusprotect LY1extunderscore pctprotect LY1extunderscore m.htm



Table 2A. Value of Variables at the Calibrated Point (raw data for year 2009)

Variable Symbol Value Source/Explanation

Fuel tax ($/gallon) t0 0.39 Sum of federal tax 18.4 c/gal and weightedaverage of state tax 20.6 c/gal (EIA)a

Ethanol subsidy ($/gallon) b0 0.45 RFS2Oil price ($/barrel) po 61.0 Composite acquisition cost of crude oil

(EIA)b

Corn price ($/bushel) pc 3.74 Weighted average farm price of corn (FeedGrains Database, USDA)c

Ethanol price ($/gallon) pve 1.79 Ethanol average rack price in Omaha, NE

DDGS price ($/ton) pd 114.4 Wholesale price in Lawrenceburg, IN (FeedGrains Database, USDA)d

Domestic oil supply (billion barrels) So 1.93 Production plus adjustments and stockchanges (EIA)e

Foreign oil supply (billion barrels) So 3.29 Net import (EIA)Ethanol supply (billion gallons) xv

e 10.76 Domestic production (RFA)Fuel demand (billion gallons) Dv

f 134.4 Finished motor gasoline including ethanol(EIA)

Domestic corn supply (billionbushels)

Sc 13.15 Domestic production (Feed GrainsDatabase, USDA)f

Foreign corn import demand (billionbushels)

Dc 1.86 Net export (Feed Grains Database, USDA)

Notes: aThese tax values are taken from the EIA table “Federal and State Motor Fuels Tax,” http://www.eia.doe.gov/pub/oil_gas/petroleum/data_publications/petroleum_marketing_monthly/current/pdf/enote.pdf.bOil price comes from table “Refiner Acquisition Cost of Crude Oil” (EIA), http://tonto.eia.doe.gov/dnav/pet/pet_pri_rac2_dcu_nus_m.htm.cCorn price comes from table“Corn and Sorghum:Average Prices Received by Farmers”(Feed Grains Data,USDA). http://www.ers.usda.gov/Data/FeedGrains/Table.asp?t=09d DDGS price comes from table “By-product Feeds: Average Wholesale Price, Bulk, Specified Markets” (Feed Grains Data, USDA). http://www.ers.usda.gov/Data/FeedGrains/Table.asp?t=16eOil domestic/foreign supply and fuel/ethanol supply on volumetric basis come from table“Supply and Disposition”(EIA). http://tonto.eia.doe.gov/dnav/pet/pet_sum_snd_d_nus_mbbl_m_cur.htmf Corn supply and foreign demand come from table “Corn: Supply and Disappearance” (Feed Grains Data, USDA). http://www.ers.usda.gov/Data/FeedGrains/Table.asp?t=04

average of acquisition costs of domestic andimported oil. The corn price of $3.74/busheluses the averaged farm price. The USDAprice of the by-product in ethanol produc-tion, DDGS, is $114.40/t (metric ton), whichreflects the wholesale price in Lawrenceburg,Indiana. We used EIA data to calculate aweighted average retail price, excluding taxes,for petroleum by-products in the oil refiningprocess; this price index is denoted ph, andits 2009 value is $1.76/GEEG.23 The pricesof the “other” inputs used in gasoline andethanol production, wg and we, are derivedfrom the zero profit condition,wg = pg + β2ph/− po/β = $1.10/GEEG and we = pe − pc/α =$1.11/GEEG, respectively. The estimated pro-ductivity parameters α, β, and β2 are discussednext.

23 Because prices for all the by-products of the refining processwere not available, the price index we constructed uses the pricesof only aviation gasoline, kerosene-type jet fuel, kerosene, distillatefuel oil, and residual fuel oil. Together, these products account for70%, by weight, of all petroleum by-products in the oil refiningprocess.

Productivity Parameters

One bushel of corn produces approximately2.80 gallons of ethanol (Eidman 2007); thusα = 2.80. The production of ethanol generatesby-products that are useful as animal feed (andthus can replace corn in that use).The nature ofsuch by-products depends on whether ethanolis produced in a dry milling plant or in a wetmilling plant. Because dry milling plants aremuch more common,we construct the model asif all ethanol is produced in dry milling plants.24

According to the RFA, such a process gener-ates as a by-product about 17 lbs of DDGSper bushel of corn; given that there are 56 lbsin a bushel, then δ1 = 0.303. The DDGS pricerelative to the corn price is captured by theparameter δ2 = 0.776, calculated as describedin table 1A from the data discussed in theforegoing. Given the assumption of perfect

24 According to the RFA,more than 80% of corn used in ethanolproduction is processed via dry milling plants, with the remaining20% processed via wet milling plants.

at Iowa State U



ownloaded from

http://www.eia.doe.gov/pub/oilprotect LY1extunderscore gas/petroleum/dataprotect LY1extunderscore publications/petroleumprotect LY1extunderscore marketingprotect LY1extunderscore monthly/current/pdf/enote.pdf

http://www.eia.doe.gov/pub/oilprotect LY1extunderscore gas/petroleum/dataprotect LY1extunderscore publications/petroleumprotect LY1extunderscore marketingprotect LY1extunderscore monthly/current/pdf/enote.pdf

http://tonto.eia.doe.gov/dnav/pet/petprotect LY1extunderscore priprotect LY1extunderscore rac2protect LY1extunderscore dcuprotect LY1extunderscore nusprotect LY1extunderscore m.htm

http://www.ers.usda.gov/Data/FeedGrains/Table.asp?t=09










Table 2B. Variables at the Calibrated Point (calculated values)

Variable Symbol Value Source/Explanation

Net ethanol subsidy ($/GEEG) bo 0.477a bo = bo/γ − (1 − γ )to/γEthanol price ($/GEEG) pe 2.59a pe = pv

e/γ

Fuel price ($/GEEG) pf 2.50a pf = pe − bo + to

Gasoline price ($/GEEG) pg 2.11 pg = pe − bo

Price of inputs other than corn inethanol production ($/GEEG)

ωe 1.11 ωe = pe − pc/α

Price of inputs other than oil ingasoline production ($/GEEG)

ωg 1.10 ωg = pg + β2ph/β − po/β

Price of petroleum by-products($/GEEG)

ph 1.76 Weighted average retail price excludingtaxes (EIA)b

Quantity of petroleum by-products(billion GEEGs)

xh 110.3 xh = β2xo

Oil supply (billion barrels) xo 5.22 xo = So + SoCorn used in ethanol production

accounting for by-product value(billion bushels)

Qc 2.94 Qc = xe/α

Domestic corn demand as food/feeduses (billion bushels)

Dc 8.35 Dc = Sc − Dc − Qc

DDGS supply (billion bushels) xd 0.89 xd = δ1QcEthanol supply (billion GEEGs) xe 7.43a xe = γ xv

eGasoline supply(billion GEEGs) xg 123.6 xg = Dv

f − xve

Fuel demand (billion GEEGs) Df 131.0 Df = xg + xe

Note: aEthanol subsidy, quantity and price are expressed in GEEG units (see text).bPrice index includes resale prices to end users excluding taxes for aviation gasoline, kerosene-type jet fuel, kerosene, distillate fuel oil, and residual fuel oil,which come from table “Refiner Petroleum Product Prices by Sales Type” (EIA), http://tonto.eia.doe.gov/dnav/pet/pet_pri_refoth_dcu_nus_m.htm.

substitution between corn and DDGS in feeduse, each processed bushel of corn generates,as a by-product, the equivalent of δ1δ2 = 0.24bushels of corn.25 Hence, the ethanol pro-duction coefficient, accounting for by-productvalue, is α = 2.53 GEEG/bushel.

Quantities in the Baseline

For the baseline scenario, we use domes-tic production, including stock changes andother adjustments, to measure domestic sup-ply; net exports of corn to measure foreigndemand; and net imports of oil to measureforeign oil supply. In the status quo (for2009), there are 13.15 billion bushels of cornand 1.93 billion barrels of domestic oil pro-duced in the United States. The quantitiesof foreign corn demanded (U.S. exports) andoil supplied (U.S. imports) were 1.86 billionbushels and 3.29 billion barrels, respectively.Corn utilization consists of three main uses:domestic food/feed use (exclusive of ethanoluse), foreign demand (exports), and ethanol

25 EPA now assumes that 1 pound of distillers grains will replace1.196 pounds of total corn and soybean meal for various beef cattleand dairy cows in 2015. The displacement ratio remains at 1:1 forswine and poultry (Environmental Protection Agency 2010).

use. The U.S. ethanol production of 10.76billion gallons (RFA data) corresponds to7.43 billion GEEGs. Given the assumed fixed-proportion technology of ethanol production,the net amount of corn used in ethanol pro-duction is calculated to be Qc = xe/α = 2.94billion bushels. The corn food/feed use isthen obtained from market balance, whereDc = Sc − Dc − Qc = 8.35 billion bushels. EIAreports data for the finished motor gasolineproduct, including blended ethanol, of 134.4billion gallons, which measures total fuelconsumption in volumetric units. Subtractingethanol production (in volumetric units) fromthe figure for finished motor gasoline givesunblended gasoline’s contribution to total fuelconsumption, xg = 123.6 billion GEEGs. Finalfuel consumption, measured in GEEGs, isthe sum of gasoline and ethanol consumptionin the same units, xf = xg + xe = 131.0 billionGEEGs. The assumed fixed-proportions tech-nology in oil refining gives the calculated yieldof gallons of gasoline per barrel of crude oilas β = xg/xo = 23.6 GEEGs/barrel.26 Given β,the yield of petroleum by-products (in gallons)

26 Alternatively, one could recover the β parameter fromrefinery yields data reported by EIA, e.g., β = (42 gallon/barrel) ×

at Iowa State U



ownloaded from

http://tonto.eia.doe.gov/dnav/pet/petprotect LY1extunderscore priprotect LY1extunderscore refothprotect LY1extunderscore dcuprotect LY1extunderscore nusprotect LY1extunderscore m.htm.



from a barrel of crude oil is calculated to beβ2 = 21.1.27

Carbon Emissions

We use the carbon emission rate of gaso-line, measured as carbon dioxide (CO2), of11.29 kg/GEEG (Wang 2007). As for the netcarbon dioxide emissions of ethanol, in ourbaseline we apply the rate of 8.42 kg/GEEGof CO2 from the life-cycle perspective sug-gested by Farrel et al. (2006), which is close tothe emission rate of corn ethanol with feed-stock credits but without land use changesreported by Searchinger et al. (2008).28 Thesevalues, in turn, imply that the relative pollu-tion efficiency of ethanol to gasoline (i.e., theparameter λ) is around 0.75 in our benchmarkcase, a parameterization that is consistent withEPA (2010). There is, of course, considerableuncertainty (and controversy) about ethanol’sactual carbon dioxide emissions. For example,Searchinger et al. (2008) estimate that whenthey account for land use changes, the netcarbon emission of ethanol is 93% larger thanthat of gasoline.29 To capture the influence ofsuch uncertainty,the sensitivity analysis carriedout later will consider the range [0.5, 2] for theparameter λ.

Carbon Emissions Cost

There are many estimates regarding the socialcost of carbon dioxide emissions.Tol (2009) sur-veys 232 published estimates of the marginaldamage cost of carbon dioxide. The mean ofthese estimates is a marginal cost of carbonemissions of $105/tC, which is equivalent to$28.60/tCO2, with a standard deviation equiv-alent to $243/tC ($66/tCO2), where social costsare measured in 1995 dollars. The widely cited

(1 –Annual Average Process Gains) × (Finished Motor Gaso-line Yield). Note that this formula accounts for the fact that EIAmeasures gains as negative numbers. This procedure would yieldβ = 20.6 GEEG/barrel. The discrepancy of this value with the onewe use, as explained in the text, is likely due to the additives inblended gasoline.

27 As explained in table 1, there are 42 gallons per barrel of crudeoil, and because of a yield gain in the refining product, there areapproximately 44.7 gallons of refined product per barrel of oil. Sub-tracting the calculated value of 23.6 gallons of gasoline per barrelof crude oil provides the calculated value of β2.

28 The feedstock credits refer to the carbon benefit of devotingland to biofuels (Searchinger et al. 2008).

29 Hertel et al. (2010) provide a lower estimate of ILUCemissions, which is roughly one-fourth the value estimated bySearchinger et al. (2008). But their estimates still suggest the pol-lution inefficiency of ethanol relative to gasoline when accountingfor ILUC.

Stern Review (Stern 2007) has a higher esti-mate of approximately $80/tCO2, due to alower discount rate applied to future economicdamage from climate change. The NationalHighway Traffic Safety Administration (2009)calculates its proposed corporate average fueleconomy standard by relying on Tol’s (2008)survey, which includes 125 estimates of thesocial carbon cost published in peer-reviewedjournals through the year 2006. Tol (2008)reports a $71/tC mean value, and a $98/tCstandard deviation of these estimates of thesocial carbon cost (expressed in 1995 dol-lars). Adjusted to reflect increases of emissionsat now-higher atmospheric concentrations ofGHGs, and expressed in 2007 dollars, Tol’s(2008) mean value corresponds to $33/tCO2,and this is the mean value for the global cost ofcarbon used by the National Highway TrafficSafety Administration (2009). The EPA (2008)derives estimates of the social carbon costusing the subset of estimates in Tol’s (2008)survey and reports average global values of$40/tCO2 (for studies using a 3% discount rate)and $68/tCO2 (for studies using a 2% discountrate).

Because of the U.S.-centered welfare func-tion used here, the pollution externality costused in our modeling framework shouldarguably reflect local and global warmingcosts to the United States. In the baselinewe use a value of $20/tCO2, which essen-tially is the estimate provided by the SternReview, adjusted to reflect the U.S. share ofthe world economy.Whereas some might thinkthat the reference parameter of the SternReview is perhaps too high,30 others mightyet argue that it is the global damage dueto carbon emission that ought to be con-sidered. Also, as noted by a reviewer, otherexternality costs—associated with congestion,accidents, and noncarbon pollution—are notexplicitly taken into account.31 In the end,because of the uncertainty and controversysurrounding this parameter, one might wantto rely on sensitivity analysis to explore theimpact of alternative parametric assumptions.For the sensitivity analysis discussed later, wetake the global value of the Stern Review

30 Using a more conventional discount rate, Hope and Newbery(2008) find that the (global) carbon cost from the Stern report couldbe reduced to the range of $20–$25/tCO2.

31 Parry and Small (2005) take the lower and upper limit of pollu-tion damages to be $0.7/tC and $100/tC,respectively,and the centralvalue to be $25/tC (expressed in year 2000 dollars). They alsoaccount for external congestion costs of 3.5 c/mile and an externalaccident cost of 3 c/mile.

at Iowa State U



ownloaded from



estimate of $80/tCO2 as the upper bound ofthe range we consider, with a lower boundof $5/tCO2. Given the assumed linear costfunction of the emissions externality σ(·), themarginal effect σ ′(·) represents the normal-ized constant marginal emissions damage fromgasoline. Given our assumption of $20/tCO2for the cost of carbon dioxide pollution,σ ′(·) = $0.23/GEEG.

Elasticities

The elasticity values that we use are takenfrom the literature to reflect the consensuson the available econometric evidence. Forthe corn supply elasticity we rely on esti-mates by the Food and Agricultural PolicyResearch Institute (P. Westhoff, private com-munication,2010) and set εc = 0.3 in our bench-mark,32 with a range of [0.1, 0.5] used in thesensitivity analysis. The elasticity of domes-tic food/feed demand of ηc = −0.2 is fromde Gorter and Just (2009b), and we explorethe range [−0.5, −0.1] in the sensitivity anal-ysis. The estimates for the elasticity of foreigncorn import demand range from an inelastic(short-run) value of −0.30 used by Gardinerand Dixit (1986) to a considerably more elas-tic value reported by the country commoditylinked system of the Economics Research Ser-vice of the USDA, which, following a sustainedexogenous shock to the world price of cornonly, obtains an implied elasticity of net for-eign corn imports in the third year of −2.41.We use a benchmark value for this parameterof ηc = −1.5, which is consistent with a popu-lar modeling platform (Food andAgriculturalPolicy Research Institute 2004), and wecarry out a sensitivity analysis within therange of [−3, −1].

For the elasticities of domestic oil supply, wefollow de Gorter and Just (2009b) and assumeεo = 0.2, with the range [0.1, 0.5] explored inthe sensitivity analysis. This is a more inelas-tic assumption than that suggested by Toman,Griffin, and Lempert (2008), who provide arange of [0.2, 0.6] for the long-run domesticoil supply elasticity with a baseline value of0.4. For foreign export oil supply elasticity, weassume the baseline value of εo = 3, which issimilar to the 2.63 value used by de Gorterand Just (2009b), and analyze the range [1, 5]in the sensitivity analysis. The elasticity of fuel

32 Gardner (2007) uses a short-run elasticity of 0.23 and a long-run elasticity of 0.5; de Gorter and Just (2009b) use 0.2 as theelasticity of corn supply.

demand is assigned a benchmark value of ηf =−0.5, with the range [−0.9, −0.2], as suggestedbyToman,Griffin,and Lempert (2008),which isfairly similar to the value and range consideredby Parry and Small (2005). Not much explicitevidence exists on the elasticity of petroleumby-product demand, hence we adopt the samebaseline value and range as the elasticity offuel demand. As for elasticities of gasoline andethanol supply, the construction of our modeldoes not need these as primitive parameters,although the implied elasticities of the derivedethanol supply and gasoline supply are easilyderived for the purpose of comparison withother models.33

Results

Given the assumed parameters discussed inthe foregoing section, the remaining param-eters of the model are calibrated (i.e., thecoefficients of the postulated linear supplyand demand curves are computed) to replicateprice and quantity data of the baseline (or sta-tus quo) scenario for the calendar year 2009.We then consider a number of policy environ-ments;only in the first best situation are borderpolicies (import and export tariffs) allowed.These scenarios are as follows:34

1. Laissez faire, with no border or domestictaxes or subsidies

2. No ethanol policy: current fuel tax butwithout ethanol subsidy or mandates

3. Status quo, with the current fuel tax andethanol policy

4. The first best: use of border policies anddomestic policies

5. The second best: the fuel tax and ethanolsubsidy chosen optimally

6. Ethanol subsidy chosen optimally; fuel taxset at its current level

7. Ethanol mandate chosen optimally; fueltax set at its current level

For each scenario, we report in table 3Athe values of the policy instruments and the

33 Quantities are given by production technology, and prices arefound from long-run equilibrium conditions, as explained in thetext. Given these quantities and prices, the implied elasticities (inthe baseline case) of the derived ethanol supply and gasoline supplycan be calculated as per the formulae reported in table 1 to yieldεe = 5.01 and εg = 1.61, respectively.

34 Our analysis does not consider other farm policies, such asdeficiency payments. The policies we do consider may make theeconomic impact of these other policies essentially irrelevant.

at Iowa State U



ownloaded from



equilibrium value of the simulated variables.In table 3B, for the same sets of scenarios, wereport the welfare impacts (as changes fromthe fictitious laissez faire equilibrium), brokendown into their components so as to illus-trate the distributional effect, as well as theimpact of each scenario on the total carbonemission.35 The overall net welfare gains arecalculated in the usual manner, by summingthe (changes in) producer surpluses, consumersurpluses,government tax revenue and the pol-lution damages.36 Our results show that allthe policy scenarios improve upon the lais-sez faire equilibrium solution. The presence ofa market failure implies that optimally cho-sen policies must do so, of course, but it isperhaps a bit surprising that seemingly adhoc policies (like the status quo) also do so.In particular, the status quo equilibrium withad hoc levels of the ethanol subsidy and thefuel tax captures over one-half of the maxi-mum gain that can be achieved with first bestpolicies.37

Status Quo and Status Quo Ante Ethanol

The status quo values for prices and quantitiesreflect the actual (average) values of thosevariables for 2009. Compared with the sim-ulated laissez faire equilibrium, the fuel taxof $0.39/GEEG and the gross ethanol sub-sidy of $0.45/gallon lead to higher (retail) fuelprices, higher ethanol prices, and a modest3% decline in (world and domestic) oil pricesbut a significant 18% increase in corn prices.

35 The producer surpluses for ethanol producers and oil refin-ers are zero because of the assumed constant-returns-to-scaletechnology and competitive behavior in these sectors.

36 Because ethanol production for 2009 exceeds the mandatelevel, in calibrating the model we assume that the mandate doesnot bind, and that it is the fuel tax and ethanol subsidy policies thataffect equilibrium values.

37 We do not explicitly model the fact that energy is an input inthe production of corn and ethanol (the calculation of emissions,which uses the life-cycle approach, does account for the energycontent of this production). Because in this model resources haveto be diverted from production of other goods (the numeraire) toincrease corn and ethanol production, this omission would mat-ter if the energy intensity of corn and ethanol production differedsubstantially from that of the rest of the economy. The EIA esti-mates that energy use on farms is about 0.9% of total U.S. energyconsumption (Newell 2011), a fraction that is very close to the con-tribution of farm production to U.S. GDP (U.S. Bureau of Eco-nomic Analysis 2011). If corn and ethanol production were moreenergy intensive than other sectors in the economy, the resultingcorn and ethanol supply curves would depend upon energy pricesand be more inelastic, since increased corn production will raiseenergy prices, shifting the supply curve leftward. In this case, poli-cies promoting ethanol are likely to lead to even higher increasesin corn prices than in our model.

Consequently, the combined policy causesdomestic fuel consumption to fall somewhat,as a 6.9 billion gallon decline in gasoline con-sumption is only partly offset by an increaseof 4.73 billion gallons (3.26 billion GEEGs)in ethanol consumption. This (small) drop infuel consumption, and the substitution of someethanol for gasoline, leads to a 3% (or a 50.9million tCO2) decrease in carbon emissions; atthe baseline cost of $20/tCO2, this is equiva-lent to a $1 billion decrease in pollution costs.As table 3B shows, the principal beneficiariesof this status quo policy are the government(higher tax revenue) and corn producers, whileoil producers are hurt by the fuel tax and con-sumers are hurt by higher prices (but they ben-efit, however modestly, because of the reducedexternality incidence). Relative to laissez faire,there is a $6.7 billion increase in net welfare,which amounts to 58% of the maximum gainachievable by optimum policies. U.S. depen-dence on foreign oil also declines,as oil importsfall by about 8%.

The column “no ethanol policy” in tables 3Aand 3B looks at the scenario in which the cur-rent fuel tax of $0.39/GEEG continues to applybut there is no subsidy or other policy sup-porting ethanol production. When comparedwith the status quo scenario, this case pro-vides a useful characterization of the marginalimpact of current U.S. ethanol policies. Specif-ically, without such policies, the ethanol indus-try would be almost nonexistent (only 0.05billion gallons of production). The lack ofexplicit government support is not the onlyeffect working against ethanol production inthis scenario: The fuel tax, being levied pervolume of fuel, implicitly taxes ethanol at ahigher rate (because of the latter’s lower effi-ciency level in GEEG terms). The fuel price isalso higher with no ethanol policy than in thestatus quo, which illustrates an aspect of cur-rent policies discussed by de Gorter and Just(2009b): The ethanol subsidy has a consump-tion subsidy effect for final consumers. As forwelfare effects, the introduction of the currentethanol support policy is beneficial (the welfaremeasure of the status quo exceeds that of theno-ethanol-policy scenario by $6.2 billion). Butnote that the mechanism by which this happensis not by reducing pollution, which actually ishigher under the status quo than under the no-ethanol-policy scenario (by 19.2 million tCO2).Instead, ethanol policies are useful mostlybecause of their terms-of-trade effects. Com-parison of these two scenarios in table 3Balso illustrates that the big winners from the

at Iowa State U



ownloaded from



Table 3A. Market Effects of Alternative Policy Scenarios

Laissez No Ethanol Status First Optimal Tax Optimal OptimalFaire Policy Quo Best and Subsidy Subsidy Mandate

Fuel tax ($/gallon) 0.00 0.39 0.39 0.23 0.96 0.39 0.39Ethanol subsidy ($/gallon) 0.00 0.00 0.45 0.11 1.02 0.67 0.00Oil tariff ($/barrel) 0.00 0.00 0.00 17.53 0.00 0.00 0.00Corn tariff ($/bushel) 0.00 0.00 0.00 1.26 0.00 0.00 0.00Fuel price ($/GEEG) 2.36 2.64 2.50 2.75 2.74 2.44 2.47Gasoline price ($/GEEG) 2.36 2.25 2.11 2.52 1.78 2.05 1.98Ethanol price ($/gallon) 1.63 1.43 1.79 1.78 1.95 1.96 2.01U.S. Oil price ($/barrel) 62.8 62.0 61.0 75.7 58.7 60.5 60.1U.S. Corn price ($/bushel) 3.17 2.44 3.74 3.71 4.32 4.38 4.56Petroleum by-product price

($/GEEG)1.56 1.65 1.76 2.00 2.02 1.81 1.86

Gasoline quantity (billionGEEGs)

130.5 127.4 123.6 115.1 114.3 121.7 119.9

Ethanol quantity (billiongallons)

6.03 0.05 10.76 13.94 15.51 16.02 17.45

Corn production (billionbushels)

12.55 11.78 13.15 13.12 13.76 13.83 14.01

Corn demand (billionbushels)

8.61 8.93 8.35 8.37 8.10 8.07 7.99

Corn export (billion bushels) 2.29 2.83 1.86 0.94 1.43 1.38 1.25Oil domestic supply (billion

barrels)1.94 1.94 1.93 2.03 1.92 1.93 1.93

Oil import (billion barrels) 3.57 3.45 3.29 2.84 2.91 3.21 3.14

Note: Although we use GEEG units for ethanol price, subsidy and quantity in our simulation, as discussed in the text, for ease of interpretation the resultsreported here are converted into natural units.

Table 3B. Welfare Effects of Alternative Policies (changes relative to laissez faire)

No Ethanol Status First Optimal Tax Optimal OptimalPolicy Quo Best and Subsidy Subsidy Mandate

Social welfare ($ billion) 0.5 6.7 11.5 9.9 7.5 8.2Pollution effect ($ billion) 1.4 1.0 2.6 2.6 0.8 1.1Tax revenue ($ billion) 49.7 47.6 78.5 108.5 43.0 53.6P.S. Oil supply ($ billion) −1.5 −3.4 25.8 −7.9 −4.3 −5.2P.S. Corn supply ($ billion) −8.8 7.4 7.0 15.2 16.0 18.4C.S. Corn demand ($ billion) 6.4 −4.9 −4.6 −9.6 −10.1 −11.5C.S. Fuel demand ($ billion) −36.4 −18.7 −49.6 −48.3 −9.8 −14.3C.S. Petroleum by-product

($ billion)−10.2 −22.3 −48.1 −50.5 −28.2 −33.9

CO2 emission (million tCO2) −70.1 −50.9 −128.7 −128.7 −41.4 −54.2

Note: P.S. = producer surplus; C.S. = consumer surplus. Under laissez faire the pollution effect is $30.2 billion and the CO2 emission level is 1,509 million tons.

ethanol policy are corn producers and fuelconsumers.

The First Best Policies

In the baseline scenario,the marginal emissionsdamage is $20/tCO2 and thus the first bestpolicy entails a tax on carbon emissions of$20/tCO2, in addition to oil import and corn

export tariffs. This carbon tax is equivalent, inour model, to a gasoline tax of $0.23/GEEG.Since in the baseline model ethanol is assumedto pollute less than gasoline,and since the $0.23tax is assumed levied on gallons of fuel, thena gross subsidy to ethanol of $0.11/gallon isrequired to support the first best solution.Thus,the first best policies entail a $0.17/GEEG taxon ethanol, a $0.23/GEEG tax on gasoline,a $17.53/barrel import tariff on oil, and a

at Iowa State U



ownloaded from



$1.26/bushel export tariff on corn.38 These poli-cies would increase welfare by $11.5 billioncompared with the lassez faire scenario, and$4.8 billion relative to the status quo. Com-pared with the laissez faire scenario, the com-bined effect of these policies is to increase U.S.oil prices by about 21%, while world oil pricesfall by about 7%. Despite the corn export tar-iff, U.S. corn prices increase by 17% (worldcorn prices rise by 58%);because of the conver-sion of corn into ethanol, the negative impacton U.S. corn prices of the corn export tariff isoverwhelmed by the positive impact of higherdomestic oil prices. Overall fuel consumptionfalls significantly, and ethanol replaces somegasoline, so carbon emissions fall by 8.5%.U.S. dependence on foreign oil falls sharply,as imports fall by 20%, oil consumption falls,and domestic oil production rises. From a wel-fare perspective, domestic oil producers andcorn producers both gain and the governmentgains significant tax revenue, but consumerslose both because of higher oil (and fuel) pricesand because of higher corn prices.

Compared with current policies, the first bestpolicy leads to a significant reduction in oilimports, fuel consumption, and pollution anda significant increase in ethanol production.Corn prices fall as the negative impact of thelower ethanol subsidy and the corn export tar-iff more than offset the positive impact on cornprices because of the oil import tariff. Thus,while the implementation of first best policiesbrings a welfare gain of $4.8 billion comparedwith the status quo, there is a significant redis-tribution of income away from consumers andcorn producers to oil producers and the gov-ernment. About a third of the welfare gain isaccounted for by the decline in pollution costs.

Second Best Policies: Fuel Taxes and EthanolSubsidies

The second best fuel tax and ethanol subsidyare presented in tables 3A and 3B. Inter-estingly, we see that these policies performalmost as well as the first best policies in termsof the welfare gain and actually result in an

38 As noted by one of the Journal’s editors, the fact that the firstbest gasoline tax is actually smaller than the status quo (average)fuel tax of $0.39 needs to be interpreted with care. In the statusquo, of course, we do not have optimal oil import and corn exporttaxes. Furthermore, here we are focusing on only the carbon exter-nality rationale for fuel taxation, which in fact could be invoked toaddress other mileage-related external costs associated with fuelconsumption (Parry, Walls, and Harrington 2007).

equal reduction in carbon emissions. In addi-tion, oil imports are only 2.5% larger thanunder first best policies. The first best oil tar-iff of $17.53/barrel (at 23.6 gallons per bar-rel) amounts to a gasoline tax of $0.74/gallon;combined with the $0.23/gallon tax for pol-lution damages, this means that the first bestpolicies are similar to an overall fuel tax of$0.97, which is remarkably close to the sec-ond best tax of $0.96, as given in table 3A.39

We also see from the table that relative to thefirst best, the ethanol subsidy increases signif-icantly. Note that the second best policy canbe characterized as a tax on gasoline at therate of $0.96/gallon and a small net subsidyon ethanol of $0.09/GEEG (the second bestsubsidy of $1.02/gallon for ethanol more thanoffsets the fuel tax). Ethanol production in thisscenario reaches 15.5 billion gallons, slightlyabove the 2015 mandate level of 15 billiongallons. Relative to the first best, the domes-tic corn price increases 16%. Thus, the fueltax increase largely substitutes for the unavail-ability of the oil import tariff, and the ethanolsubsidy increase partially offsets the impact onthe world corn price of the unavailability ofthe corn export tariff.40 Compared with lais-sez faire, these policies reduce world oil pricesby 6.5% and increase world corn prices by36%. Relative to the first best, world oil pricesincrease by a very modest $0.53/barrel andworld corn prices fall by a more substantial$0.65/bushel.

Even though the second best policy captures86% of the gains achievable by the first bestpolicy mix (relative to laissez faire), the distri-butional effects differ. Compared with the firstbest policy mix, consumers lose more, largelybecause of higher domestic corn prices;domes-tic oil producers suffer significant losses as thedomestic price of oil falls; but corn produc-ers gain and government tax revenue increases.Overall, the policy largely redistributes incomefrom oil producers to the government. Perhapsthe principal surprise is how well this secondbest policy mix performs compared with thefirst best policy mix.

It should also be noted that the crucial differ-ence between this second best scenario and thefirst best scenario discussed earlier is that, here,

39 The reason the gasoline tax is not equivalent to an oil importtariff, despite the assumed Leontief technology for converting oilto gasoline, is because the gasoline tax is also levied on domesticproduction.

40 Of course, the fuel tax affects corn prices, and the ethanolsubsidy has a modest effect on oil prices.

at Iowa State U



ownloaded from



border policies (oil import and corn exporttariffs) are precluded. Having restricted thepolicy space to taxing fuel while supportingethanol production, which policy instrumentis used in the ethanol market does not mat-ter. More precisely, the second best policy mixcould be alternatively characterized as com-prising an ethanol mandate equal to the secondbest ethanol production (15.51 billion gallons)along with the appropriate fuel tax (which canbe shown to equal $0.86/gallon).

Optimal (Constrained) Ethanol Policy

The last two columns of tables 3A and 3Breport the results of two scenarios in whichethanol policy instruments are the only levers,with the fuel tax fixed at its current rate of$0.39/gallon. Specifically, in the scenario of thenext-to-last column, an ethanol subsidy is theonly discretionary policy instrument;and in thescenario of the last column, an ethanol man-date is the only instrument. For both cases itis seen that while there are significant welfaregains relative to the laissez faire equilibrium,the gains compared with the status quo are notlarge; thus, in terms of our second best policyinstruments, the fuel tax has a potentially largerimpact on welfare than does ethanol policy.

As shown in tables 3A, the optimal ethanolsubsidy is $0.67/gallon when the fuel tax isfixed at $0.39/GEEG, higher than the statusquo subsidy level but, as predicted by the the-ory, well below the second best subsidy levelthat applies when fuel taxes are also chosenoptimally. However, because here the fuel taxis held at $0.39/gallon fuel tax, the “net” sub-sidy to ethanol is actually $0.40/GEEG (asopposed to a net subsidy of only $0.09/GEEGin the second best scenario). Compared withthe second best scenario, ethanol productionincreases by 3.3% and slightly exceeds the 2015mandate level of 15 billion gallons. Comparedwith the second best, the lower fuel tax meansthat gasoline consumption also increases, soCO2 emissions are not only higher than in thesecond best, they are higher than in the statusquo situation (table 3B). Overall, then, giventhe fuel tax, the welfare benefits of adjustingthe subsidy away from its status quo value areminimal, and the environmental benefits areactually negative.

As shown in Lapan and Moschini (2009), anethanol mandate is equivalent to a revenue-neutral ethanol subsidy and fuel tax. Since thelast column combines this mandate with thestatus quo fuel tax and since this combined

effective fuel tax is lower than the second bestcombination of fuel tax and ethanol subsidy,the optimal mandate yields higher welfare thanthe optimal subsidy policy. Of course, by con-struction, the welfare level that is attained hereis lower than that associated with the optimalsecond best policy. Compared with the opti-mal subsidy policy, since raising the ethanolmandate simultaneously raises the effectivefuel tax, gasoline consumption is lower underthe mandate than under the subsidy whereasethanol production (and hence the price ofethanol) exceeds that under any other pol-icy.41 This ethanol consumption level exceedsthe RFS2 mandate requirement of 15 billiongallons per year of conventional biofuel (cornethanol) in 2015. The mandate also leads tohigher domestic corn prices than under anyof the other policies, and world corn pricesare higher only in the first best case when acorn export tariff is used. World oil prices arelower than under the status quo or the opti-mal ethanol subsidy, but higher than under thefirst or second best policies.42 Carbon emis-sions are lower than under the optimal ethanolsubsidy but higher than under the first or sec-ond best policies. These emissions decreaserelative to the status quo, even though totalfuel consumption increases slightly, because ofthe replacement of some gasoline by ethanol.Welfare, by definition, is higher than underthe status quo, and also higher than under theoptimal subsidy, but considerably lower thanunder first or second best policies.

Summary of Baseline Results

By definition, the inability to use the firstbest policies, including import and export tar-iffs, must result in lower welfare. Nevertheless,when we are free to choose the ethanol sub-sidy and fuel tax optimally, this second bestpolicy combination comes surprisingly closeto matching the first best policy in terms ofwelfare gains and carbon emission reductions.Naturally, the additional restriction to only onefree policy instrument—the ethanol subsidy orthe ethanol mandate—leads to further welfaredeclines. In either of these cases,since fuel taxes(or oil import tariffs) are not choice variables,

41 In the case in which the mandate is the only choice variable,raising it has the additional effect of reducing gasoline consump-tion and imports; under either first or second best policies, gasolineconsumption can be controlled through its own policy instrument.

42 World corn and oil prices are important because they reflectthe terms of trade for the United States and thus are one componentof the welfare impact of each policy.

at Iowa State U



ownloaded from



it is desirable to increase ethanol consumption(and price), with the larger increase comingunder the mandate because of the fact that rais-ing the mandate increases the effective tax onfuel. Because of this effective tax, the ethanolmandate yields higher welfare and higherethanol utilization than does the ethanol sub-sidy, and, as noted, the optimal mandate leadsto fulfillment of the RFS2 mandate on con-ventional biofuel in 2015, as do all of the con-strained policies we considered. Still, the clearlesson is that fuel taxes are a more powerfulinstrument for reducing carbon emissions andincreasing welfare than are ethanol policies.

Sensitivity Analysis

In order to investigate the robustness of ourconclusions, we varied the nine key param-eters one at a time, recalibrated the model(when necessary) to the status quo 2009 base-line,and then explored the welfare implicationsof alternative policies. The alternative valuesfor each of the parameters that we consideredare summarized in table 4. Needless to say, theoptimized value of the relevant policy instru-ments changed with the change in these basicparameters. There are several results that arecommon to all sensitivity analysis experiments(see the tables in the supplementary Appendixonline for more details):

• For all cases considered, the status quopolicies dominated laissez faire and in allcases, except when foreign oil export sup-ply is relatively inelastic, delivered at least44% of the maximal benefits achievablewith first best policies.

• The basic result that the fuel tax/ethanolsubsidy regime is a close substitute for firstbest policy holds for all cases.

• The optimal mandate policy dominatedthe optimal subsidy policy in all cases andresulted in the highest use of ethanol inall cases considered. Nevertheless, in mostcases it did not significantly outperformthe status quo in welfare terms, the oneexception being when foreign oil exportsupply was very inelastic.

• In all cases in which ethanol emitted lesspollution than gasoline (per GEEG), theoptimal mandate resulted in lower pol-lution than the optimal ethanol subsidy(even when carbon dioxide was priced at$5/tCO2). The mandate also resulted inlower pollution than laissez faire in allcases except when ethanol pollutes morethan gasoline (λ = 2.0).

• In all cases, though, the carbon emis-sions reductions achieved through eitherthe first best or the second best policyof fuel taxes and ethanol subsidies werevery close to each other and far exceededthose achieved under any other consid-ered policy. Not surprisingly, oil importswere always lowest under the first best,when oil tariffs were used, but the secondbest was a very close second in reducingU.S. dependence on foreign oil.

• The welfare gains achievable with the sec-ond best policy of fuel taxes and ethanolsubsidies was greater than 76% of themaximum gains achievable in all cases(the average of this fraction of the max-imum welfare gain, over all experimentsreported in the Appendix, is 86%).

• The case in which optimal policy deliveredsmall gains—and hence did not improvemuch on other policies such as the statusquo or the optimal mandate—was whenthe world oil export supply elasticity waslarge (εo = 5).This illustrates the dominat-ing role played by the oil market on thepotential gains from government policy.

• Varying the parameters of the model doesnot change one of our basic results: thecase for ethanol is not largely about pol-lution, but rather, it is about the pol-icy’s impact on the U.S. gains from trade(through its impact on the terms of trade).

As an additional sensitivity analysis exercisewe carried out a Monte Carlo simulationmeant to represent our uncertainty aboutthe model’s true parameters. Specifically, theparameters of the model were randomly drawn100,000 times, from a beta distribution con-sistent with the ranges reported in table 4,with the shape parameters of this distributioncalibrated with the so-called PERT (ProgramEvaluation and Review Technique) method-ology (Davis 2008)—see the Appendix formore details—and for each parameter vec-tor we calculated the optimal values of thepolicy instruments for the various scenariosanalyzed. One way to interpret the results ofthis Monte Carlo experiment is as a robust-ness check on the magnitude of the policytool parameters that we computed in our base-line. Within this perspective, some of our mainconclusions are re-emphasized by the MonteCarlo simulation. For example, for the secondbest scenario we find that the optimal fueltax and ethanol subsidy remain significantlyabove the status quo level. Specifically, taking

at Iowa State U



ownloaded from



Table 4. Parameters and Values Used in the Sensitivity Analysis

Parameter Symbol Baseline Range

Cost of CO2 emission ($/tCO2) σ ′(·) 20 [5, 80]Ethanol CO2 emission efficiency λ 0.75 [0.5, 2.0]Elasticity of fuel demand ηf −0.5 [−0.9, −0.2]Elasticity of petroleum by-product demand ηh −0.5 [−0.9, −0.2]Elasticity of foreign corn import demand ηc −1.5 [−3.0, −1.0]Elasticity of foreign oil export supply εo 3.0 [1.0, 5.0]Elasticity of domestic corn demand ηc −0.20 [−0.5, −0.1]Elasticity of domestic corn supply εc 0.30 [0.1, 0.5]Elasticity of domestic oil supply εo 0.20 [0.1, 0.5]

the 10% and 90% of the empirical distributionfrom the simulation, the fuel tax ranges from$0.75/gallon to $1.27/gallon and the ethanolsubsidy ranges from $0.86/gallon to $1.28/gal-lon. More details concerning this and otherscenarios are reported in table A10.

Conclusion

This article constructs a tractable compu-tational model, which applies and extendsthe analytical model of Lapan and Moschini(2009), to analyze the market and welfareimpacts of U.S. energy policies. Specifically,using this framework, we solve for the optimalvalues for policy instruments under alternativepolicy scenarios.We then calibrate the model tofit the baseline period of 2009, and use simula-tion to compare equilibrium quantities, prices,and net welfare under the alternative policysettings. Not surprisingly, the simulations sup-port the policy rankings in Lapan and Moschini(2009), and in particular the conclusion that anethanol mandate dominates an ethanol subsidypolicy.

There are several interesting findings. First,the second best instruments of a fuel tax andan ethanol subsidy come close to replicatingthe outcomes under the first best policy combi-nation of oil import tariffs, corn export tariffs,and a carbon tax. For our baseline model,the second best fuel tax of $0.96/GEEG andethanol subsidy of $1.02/gallon would increaseethanol consumption to 15.51 billion gallons, a44% increase compared with the current (sta-tus quo) situation, it would decrease gasolineconsumption by 7.5% and reduce emissions by5.3% compared with the status quo.

In addition, the ethanol mandate, whenused optimally in conjunction with the exist-ing fuel tax, would achieve the highest ethanolconsumption of approximately 17.5 billion

gallons, which exceeds the RFS2 mandate onconventional biofuels (15 billion gallons peryear by 2015). However, since the effective taxon fuel is lower than under either the first orsecond best policy, it would achieve a smallerreduction in carbon emissions and a smallerwelfare gain than would either of these poli-cies. Finally, because of the magnitude of U.S.oil imports, the greatest economic gain arisingfrom any policy intervention considered is dueto the terms of trade effects through the worldoil market. Because we have not included anyother putative gain from reducing oil imports(e.g., national security effects arising from areduced dependence on imports), we probablystill significantly underestimate the potentialgains associated with policies that reduce oilimports.

Finally, a few caveats. In our analysis wehave ignored the “blend wall” issue, whichmight make it difficult to increase ethanolconsumption beyond 10% of total fuel use.But of course the blend wall is also ignored byRFS2 and, in any event, such an issue might beaddressed as an increasing fleet of vehicles thatcan utilize E85 fuel becomes available, and/orby allowing newer standard vehicles to use E15fuel. We have also assumed, as is the norm, thatmarkets are competitive. If imperfect competi-tion were present in some of the markets, thiswould affect the model both through the speci-fication of equilibrium conditions and throughthe analysis of optimal policy. For example, ifthere were monopoly power exercised by aU.S. firm in the corn export market, then thiswould reduce the benefits derived from gov-ernment policies that restrict corn exports. Onthe other hand, if foreign oil exporters wereexercising monopoly power, this would meanhigher world prices than would otherwise pre-vail and thus could increase the desirability ofU.S. oil import policy or ethanol policies thatreduce the demand for oil.

at Iowa State U



ownloaded from



As for directions for future research, themodeling framework that we have presentedcould be extended to represent explicitly thepossibility of trade in ethanol. Such a tradeis currently prevented by prohibitive tariffs(as noted earlier, the 2.5% ad valorem importtariff is supplemented by a $0.54/gallon importduty), a condition that we have reflected inthe structure of our model. Looking forward,there are at least two reasons to be interestedin modeling ethanol border tariffs as activepolicy instruments. First, it is widely believedthat producing ethanol from sugarcane, asdone in Brazil, is more efficient than producingethanol from corn. Opening up ethanol tradewould provide the United States with analternative way to reduce the use of fossil fuelfor transportation. Second, reducing or elimi-nating import tariffs on ethanol might help theUnited States accomplish the ambitious RFS2mandates. At present it is clear that whereasthe 15-billion-gallon mandate for corn-basedethanol will be easily reached by the planned2015 year, the RFS2 overall target of 36 billiongallons by 2022 might be problematic becausethe feasibility of cellulosic ethanol and otheradvanced biofuels is lagging expectations.Because the EPA has certified sugarcaneethanol as an advanced biofuel, imports ofsugarcane ethanol (from Brazil, say) couldhelp satisfy the RFS2 mandate for noncel-lulosic advanced biofuel (and, perhaps moregenerally, for all nonconventional biofuel ifthe EPA were to allow noncellulosic advancedbiofuel to substitute for cellulosic ethanol).In such a context, of course, an importantquestion to be studied is how reductions oreliminations of this tariff would affect U.S.markets and U.S. welfare. This problem is nottrivial, because the benefits of this importedethanol could be at least partly offset by thefact that U.S. imports will drive up the worldprice of sugarcane ethanol and thus reduce itsuse in other countries as a substitute for oil.This, in turn, will increase foreign emissionsand world oil prices, both of which will haveadverse consequences for U.S. welfare. Thefull characterization of such ethanol tradeimpacts is left for future research.

References

Davis, R. 2008. Teaching Project Simulationin Excel Using PERT-Beta Distributions.INFORMS Transactions on Education8(3): 139–148.

de Gorter, H., and D. R. Just. 2009a. The Wel-fare Economics of a BiofuelTax Credit andthe Interaction Effects with Price Contin-gent Farm Subsidies. American Journal ofAgricultural Economics 91(2): 477–488.

———. 2009b.The Economics of a Blend Man-date for Biofuels. American Journal ofAgricultural Economics 91(3): 738–750.

———. 2010. The Social Costs and Benefitsof Biofuels: The Intersection of Environ-mental, Energy and Agricultural Policy.Applied Economic Perspectives and Policy32(1): 4–32.

Eidman, V. R. 2007. Economic Parametersfor Corn Ethanol and Biodiesel Produc-tion. Journal of Agricultural and AppliedEconomics 39(2): 345–356.

Elobeid, A., and S. Tokgoz. 2008. RemovingDistortions in the U.S. Ethanol Market:What Does It Imply for the United Statesand Brazil? American Journal of Agricul-ture Economics 90(4): 918–932.

Farrel, A. E., R. J. Plevin, B. T. Turner,A. D. Jones, M. O’ Hare, and D. M.Kammen. 2006. Ethanol Can Contributeto Energy and Environmental Goals. Sci-ence 311(5760): 506–508.

Food and Agricultural Policy ResearchInstitute. 2004. Documentation of theFAPRI Modeling System. FAPRI-UMCReport No. 12–04, December.

Gardiner, W. H., and P. M. Dixit. 1986. PriceElasticity of Export Demand Concepts andEstimates. Staff Report AGES 860408,ERS/USDA.

Gardner, B. 2007. Fuel Ethanol Subsidies andFarm Price Support. Journal of the Agri-cultural and Food Industrial Organization5(2), article 4.

Hertel, T. W., A. A. Golub, A. D. Jones,M. O’Hare, R. J. Plevin, and D. M.Kammen. 2010. Effects of US MaizeEthanol on Global Land Use and Green-house Gas Emissions; Estimating Market-Mediated Responses. BioScience 60(3):223–231.

Hertel,T.W.,W. E.Tyner,and D. K. Birur. 2010.The Global Impacts of Biofuel Mandates.Energy Journal 31(1): 75–100.

Hope, C., and D. Newbery. 2008. Calculatingthe Social Cost of Carbon. In Delivering aLow Carbon Electricity System: Technolo-gies, Economics and Policy, ed. M. Grubb,T. Jamasb, and M. G. Pollitt. Cambridge,UK: University Press.

Khanna, M., A. W. Ando, and F. Taheripour.2008. Welfare Effects and Unintended

at Iowa State U



ownloaded from



Consequences of Ethanol Subsidies.Review of Agricultural Economics 30(3):411–421.

Lapan, H., and G. Moschini. 2009. Biofuel Poli-cies and Welfare: Is the Stick of MandatesBetter than the Carrot of Subsidies? Work-ing Paper No. 09010, Iowa State UniversityDepartment of Economics.

National Highway Traffic Safety Administra-tion. 2009. Corporate Average Fuel Econ-omy for MY 2011 Passenger Cars and LightTrucks. Office of Regulatory Analysis andEvaluation, National Center for StatisticsandAnalysis,NHTSA,U.S. Department ofTransportation, March.

National Renewable Energy Laboratory. 2008.Ethanol Basics,Clean Cities Fact Sheet. U.S.Department of Energy, October.

Newell, R. G. 2011. Statement of the EnergyInformation Administration. U.S. Depart-ment of Energy before the Committee onAgriculture, Nutrition and Forestry, U.S.Senate, March 30.

Parry, I. W. H., and K. Small. 2005. DoesBritain or the United States Have theRight Gasoline Tax? American EconomicReview 95(4): 1276–1289.

Parry, I. W. H., M. Walls, and W. Harrington.2007. Automobile Externalities and Poli-cies. Journal of Economic Literature 45:373–399.

Searchinger, T. D., R. Heimlich,R. A. Houghton, F. Dong, A. Elobeid, J.Fabiosa, S. Tokgoz, D. Hayes, and T.-H. Yu.2008. Use of U.S. Croplands for BiofuelsIncreases Greenhouse Gases throughEmissions from Land-Use Change.Science 319(5867): 1238–1240.

Stern, N. H. 2007. The Economics of ClimateChange. The Stern Review. Cambridge,UK: University Press.

Tol, R. S. J. 2008. The Social Cost ofCarbon: Trends, Outliers and Catastro-phes, Economics. The Open-Access, Open-Assessment E-Journal 2(25): 1–24.

———. 2009.The Economic Effects of ClimateChange. Journal of Economic Perspectives23(2): 29–51.

Toman, M., J. Griffin, and R. J. Lempert. 2008.Impacts on U.S. Energy Expenditures andGreenhouse-Gas Emissions of IncreasingRenewable-Energy Use. RAND Corpora-tion. http://www.rand.org/pubs/technical_reports/TR384-1 (accessed August 26,2011).

U.S. Bureau of Economic Analysis. 2011.Survey of Current Business Online 91(5).http://www.bea.gov/scb/toc/0511cont.htm(accessed August 26, 2011).

USDA. 2007. An Analysis of the Effects ofan Expansion in Biofuel Demand on U.S.Agriculture. Economic Research Service,May.

U.S. Environmental Protection Agency. 2008.Technical Support Document on Benefitsof Reducing GHG Emissions. EPA-HQ-OAR-2008-318-0078, June.

———. 2010. EPA Finalizes New Regulationsfor the National Renewable Fuel StandardProgram for 2010 and Beyond. EPA-420-F-10-006, February.

Wang, M. 2007. The Greenhouse Gases,Regulated Emissions, and EnergyUse in Transportation (GREET)Model, version 1.7. Argonne NationalLaboratory.

at Iowa State U



ownloaded from

http://www.rand.org/pubs/technicalprotect LY1extunderscore reports/TR384-1

http://www.rand.org/pubs/technicalprotect LY1extunderscore reports/TR384-1

http://www.bea.gov/scb/toc/0511cont.htm

http://www.bea.gov/scb/toc/0511cont.htm


WELFARE IMPACTS OF ALTERNATIVE BIOFUEL AND ENERGY … · addition, the Energy Policy Act of 2005...

Documents

Transcript of WELFARE IMPACTS OF ALTERNATIVE BIOFUEL AND ENERGY … · addition, the Energy Policy Act of 2005...