Welfare impacts of alternative biofuel and energy policies

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1 Eonomis Working Papers ( ) Eonomis Welfare impats of alternative biofuel and energy poliies Jingbo Cui Iowa State University, Harvey E. Lapan Iowa State University, GianCarlo Moshini Iowa State University, Joseph Cooper Eonomi Researh Servie, U.S. Department of Agriulture, Follow this and additional works at: Part of the Eonomis Commons Reommended Citation Cui, Jingbo; Lapan, Harvey E.; Moshini, GianCarlo; and Cooper, Joseph, "Welfare impats of alternative biofuel and energy poliies" (2010). Eonomis Working Papers ( ) This Working Paper is brought to you for free and open aess by the Eonomis at Iowa State University Digital Repository. It has been aepted for inlusion in Eonomis Working Papers ( ) by an authorized administrator of Iowa State University Digital Repository. For more information, please ontat

2 Welfare impats of alternative biofuel and energy poliies Abstrat We employ an open eonomy general equilibrium model to investigate the effets of government energy poliy, with an emphasis on orn-based ethanol, on the U.S. eonomy. The model speifiation inorporates world and domesti markets, assumes pollution osts from fuel onsumption, and allows endogenous determination of equilibrium quantities and pries for oil, orn and ethanol. The model is alibrated to represent a reent benhmark data set for 2009 and is used to simulate the positive and normative effets of alternative poliies. We find that a seond best poliy of a fuel tax and ethanol subsidy approximates fairly losely the welfare gains assoiated with the first-best poliy of an optimal arbon tax and tariffs on traded goods. The largest eonomi gains to the U.S. eonomy from these energy poliies arise from the impat of the poliies on U.S. terms of trade, partiularly in the oil market. We also find that, onditional on the urrent fuel tax, an optimal ethanol mandate is superior to an optimal ethanol subsidy. In the benhmark ase, the optimal ethanol mandate is about 18 billion gallons. Keywords biofuel poliies, arbon tax, ethanol subsidy, gasoline tax, greenhouse gas emissions, mandates, renewable fuel standard, seond best, welfare Disiplines Eonomis This working paper is available at Iowa State University Digital Repository:

3 Welfare Impats of Alternative Biofuel and Energy Poliies Jingbo Cui, Harvey Lapan, GianCarlo Moshini, Joseph Cooper Working Paper No June 2010 IOWA STATE UNIVERSITY Department of Eonomis Ames, Iowa, Iowa State University does not disriminate on the basis of rae, olor, age, religion, national origin, sexual orientation, gender identity, sex, marital status, disability, or status as a U.S. veteran. Inquiries an be direted to the Diretor of Equal Opportunity and Diversity, 3680 Beardshear Hall, (515)

4 Welfare Impats of Alternative Biofuel and Energy Poliies Jingbo Cui, Harvey Lapan, GianCarlo Moshini and Joseph Cooper Abstrat We employ an open eonomy general equilibrium model to investigate the effets of government energy poliy, with an emphasis on orn-based ethanol, on the U.S. eonomy. The model speifiation inorporates world and domesti markets, assumes pollution osts from fuel onsumption, and allows endogenous determination of equilibrium quantities and pries for oil, orn and ethanol. The model is alibrated to represent a reent benhmark data set for 2009 and is used to simulate the positive and normative effets of alternative poliies. We find that a seond best poliy of a fuel tax and ethanol subsidy approximates fairly losely the welfare gains assoiated with the first-best poliy of an optimal arbon tax and tariffs on traded goods. The largest eonomi gains to the U.S. eonomy from these energy poliies arise from the impat of the poliies on U.S. terms of trade, partiularly in the oil market. We also find that, onditional on the urrent fuel tax, an optimal ethanol mandate is superior to an optimal ethanol subsidy. In the benhmark ase, the optimal ethanol mandate is about 18 billion gallons. Key Words: Biofuel poliies, arbon tax, ethanol subsidy, gasoline tax, greenhouse gas emissions, mandates, renewable fuel standard, seond best, welfare. JEL Classifiation: Q2, H2, F1 This version: June An earlier and provisional version of this paper was posted on AgEon Searh in April 2010 as part of the Seleted Papers requirements for the 2010 AAEA annual meeting. This version updates, orrets and extends that preliminary draft. Jingbo Cui is a Ph.D. student, Harvey Lapan is University Professor and GianCarlo Moshini is Professor and Chair, all with the Department of Eonomis, Iowa State University. Joseph Cooper is with the Eonomi Researh Servie, U.S. Department of Agriulture. This projet was partially supported by a ooperative researh projet with the Eonomi Researh Servie. The views expressed in this paper are those of the authors and may not be attributed to the Eonomi Researh Servie or the U.S. Department of Agriulture.

5 1. Introdution Two interrelated and ritial issues faing the U.S. and world eonomies are the dwindling supply of fossil fuels and the inreasing emissions of arbon into the atmosphere. The U.S. dependene on imported oil, in partiular, has inreased sharply in the past quarter entury, with a number of signifiant eonomi and politial onsequenes. Oil imports worsen the U.S. balane of trade defiit and, together with growing energy onsumption from developing ountries suh as China, lead to higher pries. Some argue that this dependene on oil imports weakens U.S. national seurity and entails signifiant military and defense expenditures to ensure ontinued U.S. aess to world oil supplies. Separately, there is the onern with greenhouse gas (GHG) emissions assoiated with fossil energy use. While some disagreement exists on the potential impliations of arbon buildup in the atmosphere, it seems that the major industrialized ountries are moving toward a regime in whih these emissions will be regulated and (or) pried. Partly in response to suh issues, government support for biofuels has led to rapid growth in U.S. ethanol prodution. U.S. fuel ethanol prodution has inreased from 1.65 billion gallons in 2000 to billion gallons in 2009, making the U.S. the largest world produer of ethanol. This dramati expansion of ethanol prodution owes muh to ritial support poliies implemented by the United States. Speifially, U.S. ethanol prodution urrently benefits from a $0.45/gallon subsidy (tehnially an exise tax redit), an out-of-quota ad valorem import tariff of 2.5% and a $0.54/gallon duty on ethanol imports. In addition, the Energy Poliy At of 2005 speified a renewable fuel standard that mandates speifi targets for renewable fuel use, the level of whih has been onsiderably expanded by the Renewable Fuel Standard (RFS2) of the Energy Independene and Seurity At of Sine then, the ethanol mandates under the RFS2 have been more than met, with ethanol prodution of billion gallons in 2009 exeeding the mandate level by 0.26 billion gallons. 1 Aording to the RFS2, the renewable fuel requirement rises from billion gallons in 2010 to 20.5 billion gallons in 2015, and to 36 billion gallons in 2022; of these latter amounts, up to 15 billion gallons may ome from ethanol, while the rest are meant to ome from advaned biofuels, suh as ellulosi biofuel. Given these ambitious targets and government poliy geared to implement them, it is important to have a lear understanding of the welfare impliations of poliies that impat biofuels prodution. This topi has been the subjet of a few studies that have eluidated some ritial eonomi effets. De Gorter and Just (2009a) analyze the impat of a biofuel blend 1 The ethanol prodution of 4.84 billion gallons in 2006 and 6.48 billion gallons in 2007 exeeded the previous RFS mandates of 4.0 billion gallons in 2006 and 4.7 billion gallons in Ethanol prodution of 9.23 billion gallons in 2008 also slightly surpassed the RFS2 mandate of 9.0 billion gallons. 1

6 mandate on the fuel market. They find that when tax redits are implemented along with the blend mandate, tax redits subsidize fuel onsumption instead of biofuels. De Gorter and Just (2009b) also develop a framework to analyze the interation effets of a biofuel tax redit and a prie-ontingent farm subsidy. The annual retangular deadweight osts whih arise beause they onlude that ethanol would not be ommerially viable without government intervention dwarf in value the traditional triangular deadweights osts of farm subsidies. Elobeid and Tokgoz (2008) set up a multimarket international ethanol model to analyze the influene of trade liberalization and the removal of the federal tax redit in the U.S. on ethanol markets. They find that the removal of urrent tariffs on imported ethanol will lead to a 13.6% derease in the U.S. domesti ethanol prie and a 3.7% inrease of ethanol s share in U.S. fuel onsumption. With the removal of both tax redits ($0.54/gallon at the time of that study) and tariffs, their study predits that U.S. ethanol onsumption will fall by 2.1% and the prie of ethanol will fall by 18.4%. The foregoing studies do not aount expliitly for the impat of limate poliies on GHG emissions assoiated with the fuel energy setor. Khanna, Ando and Taheripour (2008) examine the welfare impat of a arbon tax ($25/tC) on fuel onsumption, when the purpose of the tax is to orret the pollution externality from arbon emissions and to aount for the other external osts assoiated with ongestions and aidents. At the time of their study, they found that the fuel tax of $0.387/gallon and then-urrent ethanol subsidy of $0.51/gallon redues arbon emissions by 5% relative to the no-tax situation (lassez faire). 2 Their seond best poliy of a $0.085 mile tax with a $1.70/gallon ethanol subsidy ould redue gasoline onsumption by 16.8%, thereby reduing arbon emissions by 16.5% (71.7 million metri tons). In onsidering the effetiveness of ethanol in reduing GHG emissions, one issue that arises is that of indiret land use effets. It is argued that diverting feed orn to ethanol prodution in the United States might bring new marginal land into prodution elsewhere in order to satisfy the inreased demand for agriultural output (Searhinger et al. 2008), an indiret effet of biofuel mandates that ould be quite sizable. To assess the global eonomi and landuse impats of biofuel mandates, Hertel, Tyner and Birur (2008) use a omputable general equilibrium model (CGE), whih is built upon the standard Global Trade Analysis Projet (GTAP) modeling framework. To jointly meet the biofuel mandate poliies of the United States (15 billion gallons of ethanol used by 2015) and the EU (6.25% of total fuel as renewable fuel by 2 Some studies disuss emissions in terms of metri tons of arbon (tc), other in terms of metri tons of arbon dioxide (tco 2 ). One metri ton of arbon is equivalent to 3.67 metri tons of arbon dioxide (onversely, one metri ton of arbon dioxide is equivalent to 0.27 metri tons of arbon). Of ourse, when redutions are expressed in perentages, units will not matter. 2

7 2015), they find that oarse grains areage in the United States rises by 10%, oilseeds areage in the EU inreases dramatially, by 40%, ropland areas in the United States would inrease by 0.8%, and about one-third of these hanges our beause of the EU mandate poliy. The U.S. and EU mandate poliies jointly redue the forest and pasture land areas of the United States by 3.1% and 4.9%, respetively. However, the most reent RFS2 pronounement by the Environmental Protetion Ageny (EPA) has aounted for international indiret land use hanges (ILUC) and made several hanges for GHG emissions redution of ethanol from all feedstoks (EPA 2010). Aounting for ILUC, the EPA finds that orn ethanol still ahieves a 21% GHG redution ompared to gasoline. On the other hand, sugarane ethanol qualifies as an advaned biofuel aording to the overall result of the EPA s ILUC modifiation given that its alulated average of 61% GHG redution ompared to baseline gasoline exeeds the 50% GHG redution threshold for advaned biofuels. Sugarane ethanol even meets the 60% GHG redution standard for ellulosi ethanol. Lapan and Moshini (2009) note that most of the existing work does not expliitly aount for the welfare onsequenes to the U.S. of poliies supporting biofuel prodution (suh as the externality of GHG emission or the benefits to the U.S. that arue either from improved terms of trade or improved national seurity due to dereased reliane on oil imports). To onsider first- and seond-best poliies within that normative ontext, Lapan and Moshini (2009) build a simplified general equilibrium (multi-market) model of the United States and the rest-of-the-world eonomies that links the agriultural and energy setors to eah other and to the world markets. That paper models the proess by whih orn is onverted into ethanol, aounts for byproduts of this proess, and allows for the endogeneity of world oil and orn pries, as well as the (different) arbon emissions from gasoline derived from oil and that whih is blended with ethanol. The analysis presented is theoretial in nature, aiming at providing analytial insights and results. The authors find that, in their setting, the first best poliy would inlude a tax on arbon emissions, an import tax on oil, and an export tax on orn. If poliy is onstrained, for example by international obligations, they find that a fuel tax and an ethanol subsidy an be welfare enhaning. They also find that an ethanol mandate is likely to welfaredominate an ethanol subsidy. In this paper we onstrut a tratable omputational model that applies and extends the analytial setup of Lapan and Moshini (2009), and we use the model to provide quantitative estimates of the welfare benefits of alternative poliies. The model speifiation allows endogenous determination of equilibrium quantities and pries for oil, orn and ethanol and is 3

8 alibrated to represent a reent benhmark data set for the year 2009, using the available eonometri evidene on elastiity estimates. By varying government poliy, we explore how these poliies affet equilibrium (domesti and world) pries of orn, oil, ethanol and gasoline. Using standard welfare measures, we ompare the net welfare impliations of alternative poliies and show how different groups are affeted by the poliies. In addition to haraterizing the first best poliy, we onsider a number of seond best interventions involving various ombinations of ethanol mandates, ethanol subsidies and a fuel tax. Using the model, we alulate the optimal values for the poliy instruments (given the onstraint on whih instruments are used) and the assoiated welfare gains. We then explore the robustness of our onlusions by varying the values of various parameters. Our results onsistently show that the largest eonomi gains to the U.S. from poliy intervention ome from the impat of poliies on the U.S. terms of trade, partiularly on the prie of oil imports. We also find that first best poliy outomes, whih would require oil import tariffs that are not onsistent with U.S. international obligations, an be losely approximated by seond best tools suh as fuel taxes. Furthermore, our results probably underestimate the gains that ome from reduing U.S. oil imports beause the model does not aount for any of the national seurity gains that ould arise from redued U.S. dependene on imported oil. The rest of this paper is organized as follows. First, we review and extend the analytial model by Lapan and Moshini (2009). Next, we present the equilibrium onditions of the model so that, in onjuntion with the assumed parameter values, whih are also reported, our results an be readily repliated. This is followed by a definition of our welfare measure and a disussion of how (onstrained) optimal poliy an be determined. Finally, we report and disuss the results of our simulations, omparing the relative effiay of alternative poliies and investigating the sensitivity of these results to parametri values. 2. The Model We adapt and extend the model developed in Lapan and Moshini (2009) to make it more suitable for simulating the onsequenes of alternative poliies direted toward reduing U.S. emissions and reduing U.S. reliane on oil imports. The main extension is to reognize that when oil is refined, other produts, in addition to gasoline, are produed (e.g., distillate fuel oil, jet fuel, et.). We aggregate all the non-gasoline output into a single good alled petroleum byproduts. The model is a stylized eonomy with three basi ommodities: a numeraire good, orn (food) output and oil. In addition, there is a proessing setor that refines oil into gasoline and other petroleum byproduts, and another setor that onverts orn into ethanol, whih may 4

9 then be blended with gasoline to reate fuel used by households. Consumers are assumed to have quasi-linear preferenes (whih an then be aggregated into a representative onsumer) with utility funtion (1) U = y+ φ( Df ) + θ( D) + η( Dh) σ( xg + λxe) where y represents onsumption of the numeraire, and ( Df, D, D h) represent onsumption of fuel, of food, and of petroleum byproduts, respetively. The last term, σ ( ), represents environmental damages from arbon emissions due to aggregate ombustion of gasoline and ethanol. The parameter λ reflets the relative pollution emissions of ethanol as ompared to gasoline (we will return to this parameter later). The basi elements of the model onsist of the following: (I) U.S. demand for orn as food/feed, represented by D ( p ) (II) U.S. demand for fuel Df ( p f ) (III) U.S. demand for petroleum byproduts D ( p ) (IV) U.S. orn supply equation S ( p ) (V) U.S. oil supply equation S ( p ) (VI) Foreign oil export supply urve S w o( p o ) (VII) Foreign orn import demand urve D w ( p ) o o (VIII) U.S. oil refining setor, whih onverts oil into gasoline and petroleum byproduts (IX) U.S. ethanol prodution setor, whih onverts orn into ethanol, and produes a byprodut of dried distillers grains with solubles (DDGS), whih beomes part of the food/feed supply h h Components (I)-(VII) of the model are self-explanatory. In partiular, the (household) demand urves (I-III) ome from utility maximization, and thus are the inverse of the marginal utility relations φ ( D f ), θ ( D ), and η ( D h ), respetively, and pf, p, p h are the pries faing 5

10 households. 3 The domesti supply relations (IV and V) ome from ompetitive profit maximization so that (assuming no externalities assoiated with their prodution) they are the inverse of the marginal private (and soial) osts; beause we assume no taxes on domesti orn ( p, p ) or oil produers, represent both supply and demand pries. 4 The foreign relations (VI w o o and VII) represent aggregate exess world oil supply and world orn demand, and distinguishing w the world pries ( p, p ) from domesti pries allows for the possibility of U.S. border poliies (tariffs or quotas) that would ause U.S. pries to diverge from world pries. Note that if the United States were a small ountry, world pries ( p, p ) would be exogenous to U.S. eonomi onditions. However, in reality, the U.S. is a large eonomi agent in both markets and our simulation will reflet that fat. Finally, omponents (VIII) and (IX) of the model require a bit more elaboration. w o w 2.1. Oil Refining Setor The refinement of oil yields gasoline x g and petroleum byproduts x h. We assume a fixed oeffiients prodution tehnology so that the proess is represented as follows: 5 (2.1) xg = Min β xo, zo (2.2) xh = β2x g β where x g is gallons of gasoline output, x h is gallons of the petroleum byprodut, x o is barrels of oil input (where domestially produed oil and imported oil are perfet substitutes), and z o is the amount of a omposite input, whih aggregates all other inputs used in the oil refining proess. Thus, β is the number of gallons of gasoline per barrel of rude oil, and β 2 is the 3 Sine the marginal utility of the numeraire is one, the marginal rate of substitution between eah one of the three onsumption goods (food, fuel and petroleum byproduts) and the numeraire is the same as the marginal utility of that good. The prie of the numeraire is (by definition) normalized to one, so pf, p, p h represent relative pries. 4 We do allow for taxes or subsidies on fuel and ethanol, whih is equivalent to taxes or subsidies on gasoline and ethanol. 5 Although in reality there is some substitutability among the various produts produed from rude oil, it seems that this substitutability is limited and that the assumption of fixed proportions in output provides a reasonable approximation. 6

11 number of gallons of the petroleum byprodut per barrel of oil. This tehnology and perfet ompetition imply the following relationship among input and output pries: (3) β pg + β2ph = po + βωg where ω g represents the unit ost of the omposite input z o, inluding the rental prie of apaity Ethanol Prodution Setor We also assume a fixed oeffiients prodution proess for ethanol prodution: (4) xe = Min α x, ze where x e is ethanol output and z e the amount of other inputs used per unit of ethanol output. Beause the energy ontent of ethanol is muh lower than that of gasoline, and given our working assumption that onsumers demand take that into aount (e.g., they ultimately are about the miles traveled with any given amount of fuel, as disussed in de Gorter and Just 2010), it is important to keep trak of this fat to handle the blending of ethanol and gasoline (into fuel) in a onsistent fashion. Consequently, x e in equation (4) and in what follows is measured in what we term gasoline-energy-equivalent gallon (GEEG) units. 6 Furthermore, we wish to aount for the valuable bioproduts of ethanol prodution by ounting only the net use of orn in the tehnologial relation in (4). That is, if one bushel of orn used in ethanol prodution also yields δ 1 units of distillers dried grains with soluble (DDGS), whih, being a lose orn-substitute in feed use, we assume ommands a prie of δ 2p, then the net amount of orn required to produe a gallons of ethanol is only ( 1 δδ ) satisfies. Hene, the prodution parameter α in (4) 1 2 (5) aγ α = 1 δδ This measure is related to the more ommon notion of a gasoline gallon equivalent, whih is defined as the amount of alternative fuel it takes to equal the energy ontent of one gallon of gasoline (essentially this represents the reiproal of our measure). 7

12 where a is the number of gallons of ethanol (in natural units) per bushel of orn; γ aptures the lower energy ontent of ethanol (relative to gasoline); δ1 represents the units of DDGS per bushel of orn used to produe ethanol; and δ2 represents the relative prie of DDGS. Given perfet ompetition in the ethanol setor, this implies the following prie relation between the supply prie of ethanol and the prie of orn: p (6) pe = + ωe α where ω e is the ost of all inputs other than orn, inluding the rental ost of plant apaity, required to produe one unit of ethanol (measured in gasoline energy equivalent units) and p e is the prie of one GEEG of ethanol. 3. Equilibrium In order to simulate the model, we need to speify the equilibrium onditions that must hold and the set of poliy instruments that are onsidered. For the purpose of our poliy analysis, the poliy instruments that we allow are border poliies, fuel taxes and ethanol subsidies/taxes (or border poliies, ethanol mandates and ethanol subsidies). 7 We assume there is trade in rude oil but no trade in the refined produts, whih is a fair approximation of the status quo. 8 Given all that, the equilibrium onditions are as follows: w (7) ( ) ( ) ( ) e w (8) ( ) β { ( ) ( )} w (9) Dh( ph) β2 { So( po) So( po )} S p = D p + D p + x α (Corn Market Equilibrium) D p = S p + S p + x (Fuel Market Equilibrium) f f o o o o e = + (Petroleum Byprodut Equilibrium) 7 If we also allowed, for example, a tax/subsidy on orn prodution, we would have to distinguish between the supply and demand pries for orn. 8 Although imports aount for over 50% of U.S. rude oil onsumption, over the period net imports of gasoline averaged about 1.7% of total onsumption and net trade of Refinery and Blender Finished Petroleum Produt averaged (in absolute value) under 3% of total onsumption (alulated from the Supply and Disposition Tables of the U.S. Energy Information, 8

13 (10) β pg + β2ph = po + βωg (Zero Profit Condition Oil Refining) (11) p pe = + ωe α (Zero Profit Condition Ethanol Industry) (12) (13) w o o o p = p + τ (Oil Import Arbitrage Relation) w p = p + τ (Corn Export Arbitrage Relation) Note that equation (7) embeds the tehnologial relationship x = x α. In equations (12) and e (13), ( τ, τ ) are the oil-import-speifi and orn-export-speifi tariffs, respetively (assumed to o be non-prohibitive, so trade still ours). To lose the model, onsider first the hypothetial ase of laissez faire equilibrium, in whih τ = τ = 0 and there are no other ative poliy instruments o that interfere with the ompetitive equilibrium. Then we must also have pe = pg = pf, and subjet to this restrition, onditions (7)-(13) an be solved for the equilibrium pries w w o o f h ( p, p, p, p, p, p ) and for the ethanol quantity x e. For senarios in whih there are ative poliy instruments, on the other hand, model losure needs to be tailored to the speifis of the poliy that applies (e.g., the ase of fuel taxes and ethanol subsidies, or that of a binding ethanol mandate ) Equilibrium with Fuel Taxes and Ethanol Subsidies Let t be the onsumption tax on fuel, per gallon, and b be the volumetri blending subsidy per gallon of ethanol. Then, beause gasoline and ethanol are modeled as perfet substitutes for onsumers one measured in GEEG units, and beause one gallon of ethanol is equivalent to γ GEEGs, arbitrage relations imply 9, (14) pg = pf t b t (15A) pe = pf + pg b γ γ = + b b t γ γ is the effetive net subsidy to ethanol, as ompared to gasoline, per 0 where ( (1 )) 9 The assumption of perfet substitutes seems valid up to at least a 10% utilization rate for ethanol. 9

14 Thus, for the ase of taxes and subsidies, equations (7)-(13), (14) and (15A) an be GEEG unit. 10 { τ o, τ,, tb } used to alulate the equilibrium, given the poliy parameters Equilibrium with Mandates With a binding ethanol mandate (denoted by x e M e M x e ) equations (7)-(13) still apply, but with = x exogenously set. Note that in this ase the amount of orn utilized by the ethanol industry is fixed at M xe α, and so, as equation (7) makes lear, the orn prie is effetively determined in the orn market. Furthermore, the pries of fuel, gasoline and ethanol will have to be suh that arbitrage possibilities are exhausted, i.e., blenders that ombine ethanol and gasoline earn zero profit. This zero profit ondition, allowing for the existene of exogenous fuel taxes and ethanol subsidies, an be expressed as (15B) ( ) M ( ) pf t Df( pf) = pg D ( ) +. f pf xe p e b x e M Equation (15B) states that the prie of fuel is a weighted average of the prie of its omponents (ethanol, gasoline), where the amount of ethanol is exogenously determined. Thus, with a mandate, the equilibrium is alulated using equations (7)-(13) and (15B). As shown in Lapan and Moshini (2009), the impat of an ethanol mandate is that of ombining a fuel tax effet with an ethanol subsidy effet. 4. Welfare In defining welfare, we assume all tax revenue is returned to domesti onsumers and that there are no externalities other than those due to arbon emissions. Domesti welfare ould be alulated using the indiret utility funtion along with the profit funtion for the domesti oil and orn industries and government tax revenue, or by using the diret utility funtion along with the prodution osts for domesti oil and orn, and the net imports from world trade in oil and orn. Using the latter approah, and onsumer preferenes in equation (1), we have 10 Note that (15A) also aounts for the fat that the tax on fuel t is levied per volume unit. Beause it takes 1 γ > 1 gallons of ethanol to make one GEEG of fuel, the effetive tax on ethanol is higher than that on gasoline. 10

15 (16) w w { ( ) ( o) ωe e ω g g o o } W = I C Q Ω S x x p S p D ( xg xe) ( D) ( Dh) ( xg xe). + φ + + θ + η σ + λ The term in urly brakets in (16) measures onsumption of the numeraire good, y, while the term in square brakets on the seond line measures onsumer utility derived from onsumption of fuel, orn and petroleum byproduts, and the last term measures the disutility due to pollution arising from energy onsumption. Consumption of the numeraire in (16) is total inome I (taken as exogenous and measured in numeraire units) less (i) CQ ( ), the ost of aggregate orn output; (ii) ( ) S o Ω, the ost of domesti oil prodution; (iii) { ωexe ωgxg} +, the ost of the other w w inputs used in ethanol prodution and oil refining; and (iv) po So p D, the value of net imports of oil and orn, whih are paid for with the numeraire good. Note that the ompetitive equilibrium onditions C ( Q ) = p and ( S ) Ω = p yield the inverse supply urves, so o speifiation of the supply urves for the two goods, used in equilibrium onditions (7) and (8), implies the form of the ost relations in (16). Similarly, speifiation of the demand relations used in (7)-(9) imply the forms of the sub-utility funtions in (16), so the only additional speifiation of funtional forms needed for the welfare alulations is that of the externality term, σ (..). Thus, for the simulation exerise, welfare omparisons for different poliy tools (,,,; M o tbxe ) τ τ an be made by solving the equilibrium onditions from setion (3), speifying σ ( ) and then using (16) to alulate welfare. To understand how the optimal (or seond best) poliies are determined, take the total differential of (16) and rearrange terms to yield 11 o (17) ( ) w w w w w w ( ( ) ) ( ) po So dpo dso Sodpo p D dp dd C Ddp. ( θ ) ( φ λσ ω ( α )) φ ( β β ) η σ 2 ω ( β ) dw = C dd + C dx + + Ω dx e e g g ( ) + Ω The first three terms in (17) relate to domesti resoure alloation deisions, whereas the last two relate to trade deisions, and for eah term, optimality entails equating marginal benefit to marginal ost. Thus, θ is the value to onsumers of additional orn onsumption, C is the 11 See Lapan and Moshini (2009) for full details. 11

16 marginal ost of orn prodution, and hene optimality requires { θ C } =. Similarly, the seond term relating to ethanol prodution says that the marginal value of fuel to onsumers, less the pollution ost, should be equated to the marginal ost of produing ethanol. A similar interpretation applies to the third term, where the term in square brakets is the net soial value of another unit of refined gasoline and byproduts, and ω + ( Ω β) g is the extration and refining ost of produing that gallon. The two terms in the seond row relate to trade deisions and are the only plaes where (world) pries appear expliitly; domesti pries affet domesti welfare only insofar as they affet resoure alloation, but hanges in world pries affet domesti welfare diretly. Thus, the last two terms state that the marginal ost of produing oil domestially should equal the marginal ost of importing oil, and that the marginal ost of produing orn domestially should equal the marginal revenue derived from orn exports. In a market eonomy, rational onsumers equate the marginal private value of a good to the market prie they fae, and ompetitive profit-maximizing firms will equate the marginal private ost to the pries they fae. Hene, the rationale for government intervention arises when there is some divergene between private and soial osts or benefits. In our model this divergene obviously ours when fuel is onsumed, beause of the externality generated by the ombustion of that fuel. Furthermore, from the perspetive of the domesti eonomy, a divergene between private and (domesti) soial osts also ours if the ountry s trade deisions affet world pries. For example, for a ompetitive firm importing oil, the marginal w private ost of the import is its prie p o, but from the perspetive of the eonomy as a whole, if additional imports inrease world prie, the marginal ost of the import is higher than that, w w o o o o namely, p + S ( dp ds ). Similarly, for orn exports, the marginal value pereived by a ompetitive orn exporter is w w w p, whereas the marginal revenue for the ountry as a whole is p + D ( dp dd ). Thus, as shown in Lapan and Moshini (2009), the first best poliy entails oil import tariffs, orn export tariffs and a tax on arbon emissions. As for the latter, the arbon tax is fully equivalent, in this model, to a fuel tax (i.e., a tax on both gasoline and ethanol) along with an ethanol subsidy (beause of the assumed differential pollution of ethanol, aptured by the parameter λ ). 12 Speifially, it is shown that the first best poliy instruments are The first best net ethanol subsidy, b, reflets the differential pollution rates between the two energy soures. The fat that the statutory fuel tax is in gallon terms implies a higher effetive tax on ethanol in GEEG units. Thus, even if ethanol aused the same amount of pollution as gasoline, the first best would require a positive gross subsidy b to ethanol to offset the higher fuel tax. 12

17 (18) * t = σ ( ); * b = 1 λ σ ( ) ( ) * o o o * τ = S ( ) S ( ) τ = D ( ) D ( ). In our analysis, suh a first best senario provides an important (and insightful) benhmark for other, perhaps more realisti, poliy senarios. Another useful benhmark is the laissez faire senario, i.e., the unfettered ompetitive equilibrium with t = b= τ = τ = 0. In fat, all welfare alulations are reported as differenes relative to the laissez faire, and omparisons of eah poliy senario with the first best provide information as to the effiay of the various seond best poliies onsidered. Note that in all senarios exept the first best we restrit tariffs to be zero (i.e., τ = τ = 0 ) so that, realistially, they presume that the United States is in o ompliane with its WTO obligations. 14 One we impose this restrition, we are operating in a seond best environment and the (onstrained) optimal values of these seond best instruments depend on the feasible poliy spae. As noted, we assume the feasible poliy instruments are fuel taxes and/or ethanol subsidies (or ethanol mandates and/or ethanol subsidies or fuel taxes). 15 Using these poliy restritions and the behavioral onditions outlined earlier, (17) an be rewritten as o (17A) ( λσ ) ( σ ) dw = p p dx + p p dx S dp + D dp. f e e f g g o o Thus, when tariffs are not permitted, in determining the welfare onsequenes of domesti poliy instruments, one must onsider their impat on the terms of trade as well as on arbon emissions. As we shall see from the simulations, under many plausible senarios, it is these large ountry effets that dominate the welfare alulations. When there are no border poliies, it an 13 To alulate the atual values of the instruments, the equilibrium onditions desribed in Setion 3 must be used in onjuntion with (18). 14 Beause an import tariff on a given good is equivalent to a domesti prodution subsidy and a domesti onsumption tax of the same amount, banning import tariffs is equivalent to plaing a restrition on domesti poliies, whih explains the seond best nature of these poliy senarios. 15 Thus, for example, we do not allow a tax on domesti orn prodution. 13

18 be shown that (17A) redues to 16 (17B) D = λσ + S dw p + σ o f pe dxe p. α f pg dx ( ) g Q po Here ( po) β ( So( po) So( po) ) + is the supply of unblended gasoline, and ( ) { ( ) ( ) ( ) } Q p S p D p D p is the residual supply of orn for ethanol. When both fuel taxes and ethanol subsidies an be used, the seond best poliies are (19) sb S t = σ + o sb S = ( 1 λ) σ + o D b + αq where the supersript sb denotes seond best. The tax t sb an be thought of as the tax levied on gasoline, whih inorporates two positive omponents beause inreased gasoline use worsens the U.S. terms of trade for oil and inreases pollution osts. The differene between the tax and subsidy optimal levels, sb sb b t = D αq λσ, represents the effetive overall subsidy (or tax) on ethanol; the positive omponent reflets the fat that inreased ethanol use benefits the United States by inreasing world orn pries, while the negative omponent reflets the pollution osts assoiated with ethanol use. When the ethanol subsidy is the only hoie variable, the government annot independently ontrol gasoline and ethanol onsumption. For this ase it an be shown that the optimal ethanol subsidy, as a funtion of the exogenous fuel tax, 0 t, is The paper by Lapan and Moshini (2009) ontains the details, but the logi underlying (17B) is diret. If the government indues inreased ethanol use, this inreases the prie of orn: speifially, dp dx e = 1 α Q. Similarly, inreased gasoline use will drive up the prie of oil, harming the ountry by making imports more expensive. 17 This formula differs from the orresponding one in Lapan and Moshini (2009) beause here we expliitly allow for the presene of petroleum byproduts, a feature that is important for the quantitative results of interest in this study. In the speial ase where β 2 = 0 (i.e., no byproduts), of ourse, the two onditions are idential. 14

19 D βs αq ψ sub o (20) b = λσ + ρ σ + + ( 1 ρ ) t 0 where β ρ = ( 0,1 ). β D + β β β D D 2 ( 2 ) ( ) f f b. Hene, when the fuel tax is not a hoie variable and 0 Note that b sub = b sb + ( 1 ρ )( t t sb ) t 0 sb < t, then the subsidy will generally be lower than the seond best subsidy and this subsidy will be inreasing in the exogenous tax rate. When only the mandate is the hoie variable, it an be shown that the first-order ondition for an optimal hoie of the mandate redues to 18 (21) dw D So dxg = p f p e λσ + + p f p g σ = 0 dxe αq dx e man where the supersript man denotes the mandate senario, and ( D f ) D D ( s) f f man 1+ s+ 1 δ 2 dx x g α Q f = dx 2 e 1 ( β2 β ) sδ D f where s x ( x x ) ( 0,1) ( s) β D b e e + g denotes the share of ethanol in total fuel, and ( e g ) In the simulations that follow, we onsider eah of the ases disussed above. x f δ p p b > Calibration of the Model The baseline model is alibrated to fit 2009 data using linear supply and demand urves. In order to alibrate the model, we need to speify the values of the exogenous parameters and the value 18 Again, the proedure for deriving this result is similar to that in Lapan and Moshini (2009), but the speifi result differs beause of the presene, in our model, of petroleum byproduts. 15

20 of the poliy variables in this baseline period. In addition, we also need to speify the domesti and world import demand funtions for orn ( ) D p and ( w ) S ( p ), the domesti and world export supply funtions for oil ( ) demand for fuel f ( f ) D p, the domesti supply of orn S o p o and ( w ) o o D p and the demand for petroleum byproduts ( ) h h S p, the D p. If these funtions ome from a two-parameter family of funtions, as for the linear funtional forms that we will be using, eah demand or supply funtion an be alibrated using an estimate of the elastiity (of supply or demand) for that funtion and the value of the relevant variables in the baseline period. Table 1A gives the assumed baseline values, and soures, for the primitive parameters (e.g., elastiities) used in the alibration of the model, and Table 1B gives the value of some other alulated parameters, and their method of alulation, whih are provided to ease the interpretation of the model. Tables 2A and 2B give the primary soures (or methods of alulation) and the 2009 value used for eah baseline variable, inluding the poliy variables. Some parameters are drawn from a omprehensive survey of the literature, while others are alulated from their definitions in terms of more primitive terms. In general, data for orn utilization and prie are gathered from the Feed Grain Database of the U.S. Department of Agriulture (USDA) at and data for oil, gasoline and oil refinery byproduts are obtained from the U.S. Energy Information Administration (EIA) website at Ethanol quantity data are from the Renewable Fuels Assoiation (RFA) website and ethanol pries are provided by the Nebraska Energy Offie (NEO) website at More speifi information on soures of data used is provided in the tables that follow Pries in the Baseline Beause ethanol has a lower energy ontent than gasoline, its quantity, prie, fuel tax and subsidy level used in the simulation are all onverted to be expressed per GEEG. Currently, fuel onsumption (blended gasoline with ethanol) is subjet to the federal tax of $0.184/gallon plus state-level taxes, whih are, on average, equal to $0.203/gallon. Hene, for gasoline, t 0 = $0.39. However, beause one gallon of ethanol equals only.69 GEEG, the fuel tax on ethanol is t 0 γ, that is, $0.565/GEEG. Ethanol prodution has a tax redit of b 0 = $0.45/gallon when blended with gasoline, whih is equivalent to a net subsidy to ethanol of b 0 = $0.475/GEEG. The U.S. ethanol prie of $1.79/gallon is the 2009 average rak prie F.O.B. Omaha, Nebraska, and this 16

21 orresponds to a prie of $2.59/GEEG. 19 Pries of fuel and (unblended) gasoline are alulated from arbitrage onditions, whih are assumed to hold in the status quo, that is, p = p b t = $ /GEEG, and p = p b 0 = $ /GEEG. 20 The rude oil prie of f e g e $61.00/barrel is the refiner s omposite aquisition ost of rude oil, the weighted average of aquisition osts of domesti and imported oil. The orn prie of $3.74/bushel uses the averaged farm prie. The USDA prie of the byprodut in ethanol prodution, DDGS, is $114.40/t (metri ton), whih reflets the wholesale prie in Lawreneburg, IN. We used EIA data to alulate a weighted average retail prie, exluding taxes, for petroleum byproduts in the oil refining proess; this prie index is denoted, and its 2009 value is $1.76/GEEG. 21 The pries p h of the other inputs used in gasoline and ethanol prodution, and w e, are derived from the zero profit ondition, w g = p g + β2 p h β p o β = $ /GEEG and we = pe p α = $ 1.11 /GEEG, respetively. The estimated produtivity parameters α, β and β 2 are disussed next. w g 5.2. Produtivity Parameters One bushel of orn produes approximately 2.80 gallons of ethanol (Eidman 2007); thus a = The prodution of ethanol generates bioproduts that are useful as animal feed (and thus an replae orn in that use). The nature of suh bioproduts depends on whether ethanol is produed in a dry milling plant or in a wet milling plant. Beause dry milling plants are muh more ommon, we onstrut the model as if all ethanol is produed in dry milling plants. 22 Aording to industry soures (RFA), suh a proess generates as a byprodut about 17 lbs of DDGS per bushel of orn; given that there are 56 pounds in a bushel, then δ 1 = The 19 See for the primary data. 20 This alulation method is neessary for the internal onsisteny of our model. A question, perhaps, is how lose this alulated value is to 2009 observed data. From EIA data, the average retail prie of all grades and all formulations of gasoline in 2009 was $2.406/gallon, whih is fairly lose to the alulated fuel prie. Also, from the same soure, the average wholesale (rak) prie of gasoline in 2009 was $1.75/gallon, whih is not too lose to our omputed gasoline prie. 21 Beause pries for all the byproduts of the refining proess were not available, the prie index we onstruted only uses the pries of aviation gasoline, kerosene-type jet fuel, kerosene, distillate fuel oil, and residual fuel oil. Together, these produts aount for 70%, by weight, of all petroleum byproduts in the oil refining proess. 22 Aording to the RFA, more than 80% of orn used in ethanol prodution is proessed via dry milling plants, with the remaining 20% proessed via wet milling plants. 17

22 DDGS prie relative to the orn prie is aptured by the parameters δ 2 = 0.776, alulated as desribed in Table 1A from the data disussed in the foregoing. Given the assumption of perfet substitution between orn and DDGS in feed use, then eah proessed bushel of orn generates, as a byprodut, the equivalent of δδ 1 2 = bushels of orn. 23 oeffiient, aounting for byprodut value, is α = 2.53 GEEG/bushel. Hene, the ethanol prodution 5.3. Quantities in the Baseline For the baseline senario, we use domesti prodution inluding stok hanges and other adjustments to measure domesti supply, net exports of orn to measure foreign demand and net imports of oil to measure foreign oil supply. In the status quo (for 2009), there are billion bushels of orn and 1.93 billion barrels of domesti oil produed in the U.S. The quantities of foreign orn demanded (U.S. exports) and oil supplied (U.S. imports) were 1.86 billion bushels and 3.29 billion barrels, respetively. Corn utilization onsists of three main uses: domesti food/feed use (exlusive of ethanol use), foreign demand (exports) and ethanol use. The U.S. ethanol prodution of billion gallons (RFA data) orresponds to 7.43 billion GEEG. Given the assumed fixed-proportion tehnology of ethanol prodution, the net amount of orn used in ethanol prodution is alulated to be Q = x / α = billion bushels. The orn food/feed use is then obtained from market balane, where D = S D Q = billion e bushels. EIA reports data for the finished motor gasoline produt, inluding blended ethanol, of billion gallons, whih measures total fuel onsumption in volumetri units. Subtrating ethanol prodution (in volumetri units) from the figure for finished motor gasoline gives unblended gasoline s ontribution to total fuel onsumption, x g = billion GEEG units. Final fuel onsumption, measured in GEEG units is the sum of gasoline and ethanol f g e onsumption in the same units, x = x + x = billion GEEG units. The assumed fixedproportions tehnology in oil refining gives the alulated yield of gallons of gasoline per barrel of rude oil as β = x / x = 23.6 GEEG/barrel. 24 Given β, the yield of petroleum byproduts g o 23 EPA now assumes that 1 pound of distillers grains will replae pounds of total orn and soybean meal for various beef attle and dairy ows in The displaement ratio remains at 1:1 for swine and poultry (EPA 2010). 24 Alternatively, one ould reover the β parameter from refinery yields data reported by EIA, e.g., β = (42 gallon/barrel) (1 - Annual Average Proess Gains) (Finished Motor Gasoline Yield). Note that this formula aounts for the fat that EIA measures gains as negative numbers. This proedure would yield β = 20.6 GEEG/barrel. The disrepany of this value with 18

23 25 (in gallons) from a barrel of rude oil is alulated to be β 2 = Carbon Emissions The arbon emission rate of gasoline, measured as arbon dioxide (CO 2 ), is kg/geeg (Wang 2007). The estimated net arbon dioxide emissions rate of ethanol has a onsiderable range, whih depends on feedstok soures and the aounting for indiret land use hanges. We apply the rate of 8.42 kg/geeg of CO 2 from the life yle perspetive suggested by Farrel et al. (2006), whih is lose to the emission rate of orn ethanol without feedstok redits reported in Searhinger et al. (2008). There is, of ourse, onsiderable unertainty (and ontroversy) about ethanol s atual arbon dioxide emissions. For example, Searhinger et al. (2008) estimate the following speifi CO 2 rates: kg/geeg for orn ethanol with feedstok redits, and kg/geeg for orn ethanol without feedstok redits but aounting for land-use hanges. 26 These values, in turn, imply that the relative pollution effiieny of ethanol to gasoline (i.e., the parameter λ ) is around 0.75 in the benhmark ase, with a range of 0.52 to To apture the influene of suh unertainty on the optimal values of the poliy instruments, some sensitivity analysis on the impat of ethanol s emissions rate will be arried out Carbon Dioxide Emissions Cost There are extensive estimates regarding the soial ost of arbon dioxide emissions. Tol (2009) surveys 232 published estimates of the marginal damage ost of arbon dioxide. The mean of these estimates is a marginal ost of arbon emissions of $105/tC (metri ton arbon), whih is equivalent to $28.60/tCO 2, with a standard deviation equivalent to $243/tC ($66/tCO 2 ), where soial osts are measured in 1995 dollars. The widely ited Stern Review (Stern et al. 2006) has a higher estimate of approximately $80/tCO 2, due to a lower disount rate applied to future the one we use, as explained in the text, is likely due to the additives in blended gasoline. 25 As explained in Table 1, there are 42 gallons per barrel of rude oil, and beause of a yield gain in the refining produt, there are approximately 44.7 gallons of refined produt per barrel of oil. Subtrating the alulated value of 23.6 gallons of gasoline per barrel of rude oil provides the alulated value of β Note that, for ease of omparison, we have onverted their measures of arbon dioxide emissions rates from grams of CO 2 per megajoule of energy to kilograms per GEEG. The feedstok redits refer to the arbon benefit of devoting land to biofuels (Searhinger et al. 2008). 27 The value for λ of 0.75 orresponds losely to the reent EPA released value of 0.79 (EPA 2010). 19

24 eonomi damage from limate hange. Using a more onventional disount rate, Hope and Newbery (2008) find that the arbon ost from the Stern report ould be redued to the range of $20-$25/tCO 2. The National Highway Traffi Safety Administration (NHTSA) alulates their proposed orporate average fuel eonomy (CAFE) standard by relying on Tol s (2008) survey, whih inludes 125 estimates of the soial arbon ost published in peer-reviewed journals through the year 2006 (NHTSA 2009). Tol (2008) reports a $71/tC mean value, and a $98/tC standard deviation of these estimates of the soial arbon ost (expressed in 1995 dollars). Adjusted to reflet inreases of emissions at now-higher atmospheri onentrations of GHGs, and expressed in 2007 dollars, Tol s (2008) mean value orresponds to $33/tCO 2, with a standard deviation of about $47/tCO 2. NHTSA (2009) also employs a range of estimates for the value of reduing GHG emissions, whih onsists of a domesti value ($2/tCO 2 ) at the lower end, a global value ($33/tCO 2 ) equal to the mean value in Tol (2008), and a global value ($80/tCO 2 ) one standard deviation above the aforementioned mean value. The EPA (2008) derives estimates of the soial arbon ost using the subset of estimates in Tol s (2008) survey. They report an average value of $40/tCO 2 for studies using a 3% disount rate, and $68/tCO 2 for studies using a 2% disount rate. These values are also updated to reflet inreases in the marginal damage osts of emissions at growing atmospheri onentrations of CO 2 and expressed in 2006 dollars. The pollution externality ost used in our paper is meant to aount for loal and global warming osts. We use a value of $33/tCO 2, whih, as disussed, is onsistent with NHTSA (2009). For our sensitivity analysis we explore the impliations of different values for this ost, in the range of $2/tCO 2 $100/tCO 2. The lower end of this range is of some interest beause it orresponds to the NHTSA estimate of the impat of CO 2 pollution on the domesti eonomy only. Other externality osts assoiated with ongestion, aidents and non-arbon pollution are not expliitly taken into aount. 28 Given the assumed linear ost funtion of the emissions externality σ (), the marginal effet σ () represents the normalized onstant marginal emissions damage from gasoline. Given our assumption of $33/tCO 2 for the ost of arbon dioxide pollution, σ () = 37 ents/geeg. 28 Parry and Small (2005) take the lower and upper limit of pollution damages to be $0.7/tC and $100/tC respetively, and the entral value to be $25/tC. They also aount for external ongestion osts of 3.5 /mile, and an external aident ost of 3 /mile. 20

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