### BIOFUEL TAXES, SUBSIDIES, AND MANDATES: IMPACTS ON US AND BRAZILIAN MARKETS

Bruce A. Babcock, Marcelo Moreira, and Yixing Peng

Staff Report 13-SR 108 May 22, 2013

Bruce Babcock holds the Cargill Chair in Energy Economics at Iowa State University. Marcelo Moreira is a staff economist at Agroicone in São Paulo, Brazil. Yixing Peng is a graduate research assistant, Department of Economics, Iowa State University.
Partial support for this work is based upon work supported by the National Science Foundation under Grant Number EPS-110 1284. Any opinions, fi ndings, and conclusion s or recommendations expressed in this material are those of the autho r and do not necessarily reflect the views of the National Science Foundation.
Funding for this project was also provided by t he Biobased Industry Center, and the USDA Policy Research Center at Iowa State University.
This publication is available online on the CARD website: www.card.iastate.edu . Permission is granted to reproduce this information with approp riate attribution to the author and the Center for Agricultural and Rural Development, Iowa State University, Ames, Iowa 50011-1070.
For questions or comments about the contents of this paper, please contact Bruce Babcock, 468H Heady Hall, Ec onomics ISU, Ames IA 50011-1070. babcock@iastate.edu

.

Iowa State University does not discriminate on the bas is of race, color, age, ethnicity, religion, national origin, pregnancy, sexual orientation, gender identity, genetic information, sex, marital status, disability, or status as a U.S. veteran. Inquiries can be directed to the Interim Assi stant Director of Equal Opportunity and Compliance, 3280 Beardshear Hall, (515) 294-7612.

### Contents I. Introduction .............................................................................................................. 1 II. The Model ................................................................................................................ 2 US Corn .................................................................................................................... 3 US Ethanol Demand ................................................................................................. 6 Brazilian Ethanol Demand ....................................................................................... 7 Brazilian Ethanol Supply ........................................................................................ 10 Brazilian Sugar Demand ........................................................................................ 12 US Biodiesel Supply and Demand ......................................................................... 13 Soybeans, Soybean Oil, and Soybean Meal ........................................................... 16 III. RIN Supply Curves ................................................................................................ 18 Biodiesel RIN Supply ............................................................................................. 19 Corn Ethanol RIN Supply ...................................................................................... 20 Sugarcane Ethanol RIN Supply .............................................................................. 22 Advanced RIN Supply from Biodiesel ................................................................... 23 IV. RIN Competition .................................................................................................... 24 V. Model Results ......................................................................................................... 28 Baseline Results ..................................................................................................... 30 Biodiesel Tax Credit Results .................................................................................. 32 Brazil Tax Reduction Results ................................................................................. 33 VI. Concluding Remarks .............................................................................................. 34 Appendix A. Results Conditional on US Corn Yields .................................................... 36 Appendix B. Results Conditional on US Gasoline Prices ............................................... 39 Appendix C. Results Conditional on Brazilian Production of TRS ................................ 42 Appendix D. Results Conditional on World Demand for Brazilian Sugar ..................... 44

### Executive Summary

Future prospects for biofuels in the Un ited States and Brazil depend on government policies, the prices of gasoline and feedstocks , and the ability of each country’s fleet of vehicles to use ethanol. Because trade barr iers between the two countries are low, the prospects for biofuels in each country are dependent on what goes on in the other. To help sort out the complex web of interrelate d markets and fuels requ ires a model of the markets in which the fuels are traded. In this paper we present an updated and expanded market model of biofuels in Brazil and the United States and use the model to help understand the economic impacts of the US biodi esel tax credit and a recent reduction in the tax on ethanol in Brazil. The model looks ahead to the 2013/14 corn ma rketing year in the United States that begins on September 1, 2013. Crop acreage is assumed known and fixed. For 500 different yield levels of US corn and soybeans, Brazilian soybean, sugarcane and recoverable sugar yields, Argentine soybean yields, gasoline prices and demand for Brazilian exports, the model solves for market -clearing prices and quantities of US corn ethanol and biodiesel, Brazilian sugarcane ethanol, and world prices of corn, soybeans, soybean oil and meal, and sugar. US biofuel mandates are a major driver of the market solutions. The competition between biodiesel and sugarcane ethanol to meet the US advanced mandate and the competition between sugarcane ethanol and co rn ethanol to meet the US conventional mandate as well as ethanol demand in Brazi l are what determine model solutions. The outcome of this competition is a set of equilibrium RIN (Renewable Identification Number) prices that reflect underlying biofuel supply and demand conditions. The model is calibrated to USDA’s Ma y 2013 WASDE projections and to Brazil’s latest CONAB projections. Both sets of proj ections indicate that corn and sugarcane supplies are likely to increase from recent leve ls, lowering the cost of producing ethanol. This lower cost helps to hold down conventiona l biofuel RIN prices, which still must be high enough to induce ethanol consumption beyond the 10 percent blend wall in the United States. In Brazil, more abundant s ugarcane supplies will result in increased ethanol production and consumption, but becau se the demand for ethanol in Brazil is price elastic, market prices will no t drop much from recent levels. The biodiesel tax credit increases the comp etitiveness of US biodiesel relative to sugarcane ethanol. Thus, biodiesel production w ill likely exceed levels needed to meet the biomass-based diesel mandate and will result in lower imports of sugarcane ethanol. The decline in Brazilian ethanol exports decreases Brazilian domestic demand for imported US corn ethanol so the extent of two-way trade in ethanol is reduced under the tax credit. However, demand for ethanol in Brazil is strong enough, and the cost of producing corn ethanol will likely be lo w enough, to induce strong exports of corn ethanol to Brazil even with the tax credit. Th e strong demand for ethanol in Brazil due to its large fleet of flex vehicles is further boosted by the reduction in one of Brazil’s ethanol taxes. Because of the availability of corn ethanol, much of the ethanol consumption increase in Brazil caused by the lo wer tax is met by increased imports of US corn ethanol.

### TAXES, SUBSIDIES, MANDATES, AND BIOFUELS: IMPACTS ON US AND BRAZILIAN MARKETS

I. Introduction

The future of biofuels in Brazil and the United States would seem to be bright. In Brazil, potential ethanol demand far out strips supply because the numb er of flex fuel vehicles has grown from about one million cars in 2005 to more than 18 million today. In the United States, demand growth is also set to ou tstrip available supplies because of rapidly growing mandates specified in the Renewabl e Fuels Standard (RFS). California’s low carbon fuel standard can also most readily be met by increasing the consumption of low
carbon biofuels over the next five years. Potential demand growth in bot h countries, however, will on ly result in additional supplies if the future outlook for biofuel prices is attractive enough to drive investment. In Brazil, ethanol production stalle d in recent years because of a lack of investment in new and existing sugarcan e fields and high world s ugar prices, which makes su gar more profitable to produce than ethanol. In the United States, most growth in mandated biofuel use is for
cellulosic and other advanced biofuels. Investment in cellulosic biofuel pl ants will not be able to generate enough prod uction to meet schedu led mandates, an d the most avai lable advanced biofuel is suga rcane ethanol from Brazil. A lthough it is certain th at available supplies of
cellulosic biofuels will not keep up with the US mandates, there is uncertainty about how the mandates will change to reflec t this reality. Adding to this policy uncertainty is the uncertainty about how US biof uel consumption can increase enough to meet even noncellulosic mandate incr eases because ethanol c onsumption will need to move significantly higher than levels that can be supported by 10 per cent blends. How the so-called E10 blend
wall will be breached or even it if will be br eached is not yet settle d. This uncertainty makes it difficult to justify the levels of investme nt needed today to meet tomorrow’s mandates. Adding to the uncertainty facing the demand for biofuels is uncertainty caused by other government policies. In Brazil, the go vernment has fixed th e wholesale price of gasoline below the gasoline import price. Because ethanol is a substitute for gasoline, this gasoline subsidy decreases domestic Brazilian demand for ethanol. The Brazilian government recently announced a reduction in a tax that is assessed on ethanol when it2 / Babcock, Moreira, and Peng

leaves the plant. This measur e was taken to counteract the gasoline subsidy. In the United States, a $1.00 per gallon biodiesel demand subs idy in the form of a blenders tax credit is set to expire on December 31, 2013. Because biodiesel and su garcane ethanol both qualify
as advanced biofuels under th e RFS, this subsidy reduces th e demand for sugarcane ethanol
and hence reduces the amount of ethanol that will be needed to meet RFS mandates. We write this paper to meet two objectives. The first is to provide insight into how
Brazil’s reduction in its tax on ethanol and the US biodiesel tax credit impact the markets for biofuels in both countries. The period that we examine is the upcoming US corn marketing year, which runs from Sept ember 1, 2013, to August 31, 2014. The second objective is to provide an intu itive explanation of how biof uels and the RFS affect the markets for corn, soybeans, and sugarcane through the market for Renewable Identification Numbers (RINs). This sec ond objective is met by explaining how the
economics of the RIN markets wo rk and providing the data th at is used to estimate and calibrate the key supply and demand drivers of these markets that underlie our empirical
simulation model. The basics of our model along with unde rlying data are provided in Section II. Section III shows how RIN supply curves are derived. Section IV explains how competition between biofuels to meet the mandates RINs works. Model results for the 2013/14 US marketing year are provided in Section V. Additionally, more detailed results are provided in appendices. Readers who do not mind their results coming from a “black box” model can just skip ahead to Section V and the appendices. Those who don’t trust
black box model results can find detailed e xplanations of the important modeling assumptions and data that drive the results in Sections II, III and IV.



### II. The Model

The basic model framework builds on the a pproach developed by Babcock, Barr, and Carriquiry (2010). The model solves for mark et-clearing prices and quantities of corn ethanol, sugarcane ethanol, corn, soybeans, soyb ean oil and meal, biodiesel, and raw sugar. Random exogenous variables are wholesale gasoline prices, US corn yields, soybean yields in the United States, Brazil, and Argentina, total recoverable sugar (TRS) production in Brazil, and sugar export demand facing Brazil. The model is a short-run model becauseBiofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 3

crop acreages are fixed. Model solutions are fo und for 500 sets of the stochastic exogenous
variables which are drawn from distributions th at reflect their degree of uncertainty over the 2013/14 US corn and soyb ean marketing. Thus, the aver age value of the 500 model solutions can be interpreted as expected prices and quantities. To put the model results into perspective it is important to understand the important supply and demand determinants and modeling approaches for eac h of the markets analyzed.

US Corn Corn supply in the 2013 marketing year equa ls beginning stocks plus the product of harvested acres and yield. Yield follows a be ta distribution with a mean of 160 bushels per acre and a standard devi ation of 14.5 bushels per acre. 1 Harvested acres are fixed at 89.5 million acres, which is what USDA pr ojects in its May, 2013 WASDE report . Beginning stocks are set at 759 million bushels . The cumulative distribution of US corn supply is shown in Figure 1. This chart shows the probability that beginning stocks plus production will be less than a given level. So for example, there is a 30 percent probability that supply will be less than 14 billion bushels. By contrast, supply in the 2012/13 marketing year was only 11.8 billion bushe ls. The probability that supply will be that low again is only 1.5 percent. 2
Non-ethanol corn demand consists of dema nds for feed, food, exports and storage. Demand curves for feed, food, and exports are assumed to be linear and calibrated to the corn prices and estimated us e levels contained in USDA’s May WASDE projections. The mid-point of the projected range for corn prices for 2013/14 is $4.70 per bushel. The
demand elasticities used to determine demand slopes and intercepts are -0.4 for feed demand, -0.065 for food demand, and -1.0 for export demand. Stock demand is specified
as a non-linear function to acc ount for stock-out conditions. 3 Non-ethanol corn demand is shown in Figure 2.

1 Trend yield for 2013 using 1980 to 2012 data is 157.25 bushels per acre. Using data from 1980 to 2010, trend yield is 163.21 bushels per acre, and using data from 1980 to 2011, trend yield is 161.65 bushels per acre. The 160 bushel per acre trend yield used here is a proxy for what trend yield would be if the weather variations were accounted for in estimating trend. 2 The probabilities of extreme high and low supply events are somewhat understated by Figure 1 because variability in planted and harveste d acreage is not accounted for. 3 The demand function for ending stocks is (1-betacdf(min(Pcorn,8)/8,2.24644,1.65025))*3000+600.4 / Babcock, Moreira, and Peng

Figure 1. Cumulative distribution of US corn supplies in 2013/14 marketing year

Figure 2. Non-ethanol corn demand in the United StatesBiofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 5


### Corn Ethanol Supply The amount of corn available to produce corn ethanol is simply co rn supply, which is fixed once harvest is in, mi nus non-ethanol corn demand gi ven by Figure 2. For a given corn supply, there is a unique combination of corn price an d corn quantity available to produce ethanol. The amount of ethanol producti on equals the av ailable corn for ethanol multiplied by 2.75, whic h is the number of gallons of ethanol that are assumed to be produced from each bu shel of corn. The price of et hanol is found by assuming a zero economic profit condition in the indust ry and solving for the ethanol price that is
needed to cover al l production costs. 4 Production costs are set at $0.50 per gallon plus the per-gallon cost of corn minus the value of distiller s grains, which is set at 90 percent of the price of corn. Increases in corn ethano l production increase the ethanol industry’s use of corn, whic h necessitates a higher corn price to free up enough corn from non-ethanol uses. A high er corn price increases the cost of producing ethanol which requires a higher ethanol price to co ver costs. Henc e the corn ethanol supply curve slopes up. Three ethanol supply curves are shown in Figure 3. Each supply curve corresponds to a different US corn yield. The effect of increasing corn production on ethanol supply can be measured in two ways. One way is to see how corn yield affects how much ethanol production will take place for a given pr ice of ethanol. For example, if the price of ethanol received by plants is $2.00 per gallon then the plants will produce only 5 billion gallons if corn yield is 130 bushels pe r acre, 9.9 billion gallons if corn yield is 150 bushels per acre, and 14.8 billi on gallons if corn yield is 170 bushels per acre. The second way of measuring the effect of corn production on ethanol supply is to see what price of ethanol is needed for a given level of produc tion. The corn ethanol mandate rises to 14.4 billion gallons in 2014. To produce this quantity of ethanol will requi re a plant-received ethanol price of $1.96 per gallon with the co rn yield of 170 bushels per acre, $2.45 per gallon with a corn yield of 150 bushels per acre and $2.97 per gallon if the corn yield is 130 bushels per acre.

4 The zero-economic profit condition is a reasonable assumption in an annual model given that the corn ethanol industry has excess capacity and that it has shown an ability to produce large volumes of ethanol at relatively low margins since 2008.6 / Babcock, Moreira, and Peng

Figure 3. US supply curves of corn ethanol in 2013/14 marketing years

US Ethanol Demand In the fall of 2012, the Environmental Protec tion Agency (EPA) analyzed the impact on corn prices if requests for a waiver of the conventional biofuel manda te were granted. In their analysis EPA used a short-run demand fo r ethanol that was provided to them by the US Department of Energy. This demand curv e is the curve in Figure 4 labeled “EPA demand curve.” The EPA demand curve is quite price insensitive at about 13.5 billion gallons, which is essentially where the E10 blend wall occurs. EPA also assumes that
little E85 would be sold even if ethanol were priced at a 60 percent discount to gasoline. Furthermore, the EPA demand curve assumed that blenders would pay more than a 50 percent premium for ethanol if ethanol quantity dropped below 10 billion gallons. The difficulty in estimating whether the EP A demand curve at low and high ethanol prices is reasonable is that there are no data to show what price discount would be required to induce owners of flex fuel vehicles in mo st parts of the country to fill up with
E85 for the first time. There are also no data that shows what th e quantity of ethanol demand would be if the price of ethanol ro se about parity with gasoline now that refineries have been configured to produce 84 octane blendstock that when blended with 10 percent ethanol results in 87 oc tane regular blended gasoline.Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 7

Figure 4. Demand curves for US ethanol

In this study we assume that consumers, refineries, and blen ders will be more responsive to price signals than EPA assumed in their waiver analysis . When the price of ethanol rises above gasoline, refineries w ill begin to have an incentive to use more gasoline and less ethanol. If the price of etha nol drops low enough rela tive to the price of gasoline, then owners of flex fuel vehicles (FFVs) will have an incentive to use E85 because the cost per mile traveled will be si gnificantly less than with E10. The amount of price responsiveness that is added at the two ends of EPA’s demand curve shown in Figure 4 is the demand curve used in this study.

Brazilian Ethanol Demand Brazilian fuel ethanol consumption consists of ethanol that is blended with gasoline to meet Brazilian blending requirements and pure ethanol that is used by owners of FFVs. The ethanol that is blended with gasoline is anhydrous (without water) ethanol. The pure ethanol that is consumed by FFVs and ethanol cars is hydrous et hanol that contains approximately five percent water. The modeling approach used here is to first specify the number of vehicles that will be driven in Brazil and the average consumption of fuel per8 / Babcock, Moreira, and Peng

vehicle. The average consumption per vehicle is made a function of the weighted average price of hydrous ethanol and blended gasoline. 5 Owners of FFVs choose whether to buy gasoline or E100 based on relativ e prices at the retail level. The model solves for the plant-received price of hydrous ethanol. The re tail price of hydrous ethanol is specified by a mark-up equation. The wholesale price of gasoline equals the we ighted average of the price of “neat” gasoline, which is known as gasoline A, and the wholesale price of anhydrous ethanol, which is a deterministic function of the plant -received price of hydrous ethanol. The retail price of blended ga soline, which is known as gasoline C, is specified by a different mark-up equation. 6 The two key components of Brazilian ethanol demand for this analysis is the FFV de mand for hydrous ethanol and the impact of Brazil’s regulation of the price of gasoline A. Since 2006, mostly reliable data on annua l hydrous ethanol consumption and the
number of cars in the Brazilian fleet have b een available. Because hydrous ethanol is only
consumed in FFVs or ethanol cars—that can only run on ethanol—the proportion of the miles traveled by the FFV fleet that is accounted for by hydrous ethanol can be calculated. The scatter plot of red points in Figure 5 s hows the relationship between this proportion and the retail price of hydrous ethanol relative to gasoline C from 2006 to 2012. Because we have not observed price ratios gr eater than 0.7 or less than 0.5, we rely on survey data published by EPE (2013) to de termine the response of FFV drivers to price ratios outside the range of data. The two data points we use to determine the relationship between fuel use a nd price are shown as triangles in Figure 5. The actual fuel use data show that when the average annual pr ice of hydrous ethanol is 70 percent of the price of gasoline then approximately 23 percen t of miles traveled in FFVs are fueled by hydrous ethanol. When the price drops to 50 per cent of the price of gasoline then owners of FFVs use hydrous ethanol for about 80 percent of their driving. Because the proportion of hydrous ethanol used cannot fall below zer o or rise above 100 percent, there are natural limits on the relationship between the price ratio and ethanol use. The portions of the solid line in Figure 5 that lie outside the fuel use data show the assumed relationship

5 The demand elasticity of vehicle miles traveled with respec t to the average price of fuel is assumed to be -0.04. 6 The hydrous and gasoline retail markup equation were specified as linear functions of wholesale prices of each fuel and estimated using monthly price data from January 2003 to Janu ary 2011. The estimated ethanol markup equation is Retail Price = 0.35082 + 1. 2086*Plant Price. The gasoline markup equation is Retail Price = 0.233 + 1.54*Wholesale Gasoline C Price.Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 9

Figure 5. Demand for hydrous ethanol by owners of FFVs in Brazil

where no data are available. If the price of ethanol rises a bove 115 percent of the price of gasoline, then it is assumed that hydrous ethanol consumption by FFVs falls to zero. Once the price of ethanol falls below 52 per cent of the price of gasoline, then the remaining FFV owners begin to fill use hydrous ethanol linearly until 100 percent of miles traveled is fueled by hydrous ethanol. Figure 6 shows the gasoline prices that are needed to understand the Brazilian ethanol market. Brazilian internal prices of gasoline are highly regulated. This regulation is made easier because the Federal government owns such a large share of Petrobras, the largest oil company in Brazil. The gasoline A price has not varied much from its current level of R$1.54 per liter sin ce 2010. The difference between th e gasoline A price and the Brazilian refinery price is tax. As world gaso line prices have increased over this time period, the Brazilian government has lowere d taxes on Brazilian ga soline to reduce the cost of having to import gasoline at a higher price than it is sold for domestically. By reducing the tax on gasoline while holdi ng it constant on ethanol, the Brazilian government has increasingly reduced the demand for ethanol. In an attempt to offset some of this reduced demand, Brazil’s gove rnment decided to reduce the tax on10 / Babcock, Moreira, and Peng

Figure 6. World and Brazilian gasoline prices

wholesale ethanol by 12 reais cen ts per liter (R $ 0.12 per liter). 7 The effect of the tax reduction is to lower the retail price of ethanol, thereby increasing the demand for ethanol, which will increase the price ethanol producers receive in Brazil. We assume
that this tax reduction is made available to both domestically produced ethanol and imported ethanol.

Brazilian Ethanol Supply Almost all Brazilian sugar refineries produ ce both ethanol and sugar. The amount of ethanol produced relative to sugar depends in part on which product generates more profits for the plant. Figure 7 plots the annua l price of ethanol (expr essed in R$ per liter) relative to the price of sugar (expressed in US$ pe r pound) against the proportion TRS used to produce ethanol. The e quation of the best fit line is sh own also. In general, as the price of ethanol increases rela tive to sugar, the greater is the proportion of TRS that is devoted to producing ethanol.

7 The order reducing the tax is Provisional Executive Order no 613, decree number 7.997/13 released on May 8, 2013.Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 11

Figure 7. Relationship between ethanol’s share of Brazilian total recoverable sugar and the relative price of ethanol

The quantity of TRS produced equals th e product of sugarcane harvested and the average TRS expressed as a percentage of the tonnage of total harvest. Sugarcane harvested equals the product of area harvested and sugarcane yield. To make the analysis
tractable we fix area harvested at 8.893 million ha in 2013/14 and 9.407 million ha for 2014/15. Sugarcane yield draws were multip lied by harvested area to obtain total sugarcane production in each year. The yield draws are assumed independent across the two years. The average production of sugarcan e in the two years is 654 million tons in 2013/14 and 710 million tons in 2014/15. The average yield for 2013/2014 of 73.5 tons per ha is taken from CONAB’s forecast in April of 2013. Mean yield was increased by 1.3 tons per ha for 2014/15 because of a decline in the average age of Brazilian sugarcane
fields due to increased investment in new a nd renewed fields. The st andard deviation of yields was estimated from a regression of suga rcane yields in the state of Sao Paulo from 1990 to 2012 on a trend term and the average age of the fields. The st andard deviation of the residuals from this regression was 1.40 tons per ha. Yields in 2013/14 are assumed12 / Babcock, Moreira, and Peng

beta distributed with a mean of 73.5, a sta ndard deviation of 1.4, a maximum of 77 and a
minimum of 70. Based on data from 1992/93 to 2011/12 TRS, expressed as a percentage of the tons of sugarcane harvested, averaged 13.8 percent in Brazil. The standard deviation of the percent TRS across these years is 0.33. Beta -distributed draws of TRS for 2013/14 and
2014/15 were obtained with a maximum value of 14.3 percent and a minimum value of 13.0 percent. These percent TRS draws were mu ltiplied by total sugarcane harvest draws in each year to obtain million tons of TRS. To fit the Brazilian crop year into the US marketing year, a weighted average of the Brazilian total TRS draws were made with weights of 0.44 and 0.56 being assigned to 2013/14 and 2014/15 respectively. The resulting distribution of TRS in million tons is shown in Figure 8.

Brazilian Sugar Demand Brazil is the world’s larges t producer of sugar and the largest sugar exporter. The decision about how much ethanol to produce will therefore impact the world sugar price because more ethanol means less sugar will be produced. As a first step to modeling

Figure 8. Distribution of Brazilian TR S for the 2013/14 US marketing yearBiofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 13

world sugar markets, here we specify a downward sloping demand curve for Brazilian sugar exports. The demand curve is a constant elasticity demand curve with a demand elasticity of -0.3. Demand is inel astic in the short run because world trade in sugar is thin and Brazil is by far the larges t exporter. Sugar demand is cal ibrated so that Brazilian exports will total 28 million tons at a worl d sugar price of $0.18 per pound, which was the average futures price for sugar in the 2013/14 US marketing year in the middle of May, 2013. Sugar supply in other major produ cing countries is hi ghly variable, and therefore so too is the expor t demand facing Brazilian sugar producers. To capture this variability the multiplicative constant in the export demand curve is varied by adding a
mean-zero normal deviate with a standard deviation of 1.2. The supply of sugar available for export e quals the total supply of Brazilian sugar not used to produce ethanol less domestic suga r demand. The Brazilian domestic sugar demand
curve is assumed deterministic and linear and equals 12 million tons at the $0.18 per pound price with a demand elasticity of -0.05. Sugar stock demand is a non-linear function of the world sugar price with stock out conditions ha ppening at 100,000 tons if the 2013/14 price hits 33 cents per pound. Maxi mum storage is thre e million tons and oc curs if the sugar price drops to eight cents pe r pound. The equilibri um world price is found where the quantity demanded of Brazilian sugar exports eq uals the available supply of exports.

US Biodiesel Supply and Demand The US biodiesel supply curve is perhaps the mo st uncertain aspect of this analysis. The supply curve shows the quantity of biodiesel produced for an y given biodiesel price. The biodiesel price must be sufficient to cover all variable costs of production and it must generate high enough returns for enough production capacity to be brought on line. The calculation of the price needed to cover incr emental variable cost of making biodiesel from soybean oil is straightforward to calculate using soybean oil prices and variable cost data; however, the returns needed to induce biodiesel plant owners to turn on their plants
is more difficult to determine as can be de monstrated in Figure 9. Plotted are monthly production and returns data since 2010. 8 The production figures have been multiplied by

8 Returns are calculated as the plant-received biodie sel price minus the cost of producing biodiesel from soybean oil. These returns are reported at http://www .card.iastate.edu/research/b io/tools/hist_bio_gm.aspx.14 / Babcock, Moreira, and Peng

Figure 9. Production and return data for biodiesel since 2010

12 to annualize them. Although there is clearly an overall positive relationship between returns and production, it is also clear that th e relationship is not c onstant across the three

years. 9 For example, in 2010, returns were low and so too was biodiesel production. But
in 2012 returns were also low for some mont hs but production was much higher than in 2010. In 2011 higher returns resulted in highe r production levels in nearly a linear fashion. But production levels in 2012 were n early as high with much lower returns. What seems to be going on with these da ta is that in 2010 low production levels indicate that many biodiesel pl ants were idled. To induce owne rs of the plants to begin production requires high enough returns to cove r switch-on costs of getting the plants operational. This is why margins of ov er $1.00 per gallon were needed to push production to about a billion gallons on an a nnualized basis. But once the plants were switched on in 2011, a billion gallons of annua lized production was produced in 2012 at much lower margins. So the key question for this study is whether sufficient plants are

9 Assuming that the demand for biodiesel is perfectly el astic, the data in Figure 9 trace out supply curves because the major shifter in supply is the price of feedstock which is accounted for in the calculation of margin.Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 15

operating to meet potential demand in the 2013/14 marketing year or whether margins need to be high enough to cover the costs of switching them on. Monthly biodiesel production through Ma rch of 2013 lags the amount needed to
meet 2013 biomass-based diesel mandates. Th is implies that currently-operating plants will need to ramp up production and/or addi tional production capacity will need to be brought on line. Either will require higher margins between April and September 1. Given that production increases in this time period, then the 2012 price quantity data would seem to be more applicable than the 2011 data for this study. But the 2012 data are not adequate to identify the relationship between margin and production because the potential demand for biodiesel in the 2013/14 marketing year exceeds the highest production levels yet ach ieved by the US biodiesel industry. The key question for this study is what level of return s is needed to induce the industry to produce 1.6 billion gallons or 2.0 billion gallons in 2013/14? The supply response curve shown in Figure 9 is the one used in th is study. It uses the 2012 data so that returns over variables costs need to be 43 cents per gallon to indu ce the industry to produ ce 1.28 billion gallons,
which is the 2013 biomass-based diesel mandate . If returns rise to $1.00 per gallon, then the industry is assumed to respond by produc ing 1.85 billion gallons. The responsiveness of the industry declines at greater producti on levels to reflect capacity constraints. Increases in biodiesel producti on will require increased am ounts of soybean oil. The quantity demanded of soybean oil to produce biodiesel is a signifi cant share of world soybean oil supplies so increased use of soyb ean oil to produce biodies el will increase the price of soybean oil. This price response is why the model includes the soybean sector in the analysis. Of course not all biodiesel is produced from soybean oil. But because soybean oil is the most widely availabl e feedstock approved by EPA for use as an advanced biofuel, we model all biodiesel produced in ex cess of 680 million gallons as coming from soybean oil. The first 680 million gallons of biodiesel is assumed to come
from other feedstocks that incl ude corn oil obtained from etha nol plant’s distillers grains, waste grease, inedible tall ow, lard, and poultry grease. 10

10 No accounting for the differences in renewable diesel and biodiesel is made in this report. All fuel used to meet the biomass-based diesel mandate is referred to and modeled as biodiesel.16 / Babcock, Moreira, and Peng

Biodiesel demand is assumed to be perfectly elastic at a disco unt to the wholesale price of diesel in the model. The discount is 8.65 percent plus 15 cents per gallon. The proportionate discount reflects the lo wer energy content of biodiesel. 11 The fixed discount reflects extra handling and transportation co sts of biodiesel re lative to diesel.

Soybeans, Soybean Oil, and Soybean Meal The key aspect of the soybean portion of th e model, with respect to biofuels production, is the impact of expanded biodiesel production on the price of soybean oil. In the model, the world supply of soybeans is fixed once the realization of soybean yields in the US, Brazil, and Argentina occur; a nd thus, so too is the world supply of soybean oil because all soybeans are crushed. Soybean oil to produce biodiesel is obtained by diverting soybean oil from other uses. The total supply of soybeans plus the elasticity of demand for soybean oil for other uses are the two key factors that de termine at what cost soybean oil can be bid away from other uses. Soybean oil and palm oil ar e the two most widely trad ed and produced vegetable oils. The large market share of soybean oil lo wers its demand elasticity. But the fact that other vegetable oils can substi tute for soybean oil increases its elasticity. A more elastic demand implies a smaller price impact on soybe an oil from expansion of US biodiesel production. The model’s relationship between th e use of soybean oil to produce biodiesel and the market price of soybean oil is s hown in Figure 10. For every 200 million gallons of biodiesel produced from soybean oil, the price of soybean oil increases by 3.2 cents per pound. Because it takes 7.6 pounds of soybean oil to produce a gallon of biodiesel, the cost of producing biodiesel in the mode l increases by about 24 cents per gallon for each 200 million gallons produced. The supply curve of biodiesel combines the required margin increase and the feedstock price increase. The model’s supply curve when soybean yields in the United States, Brazil, and Argentina are at their mean levels is shown in Figure 11. The elasticity of supply of biodiesel at 1.2 billi on gallons is approximately 2.0.

11 See http://www.biodiesel.org/docs/ffs-basics/e nergy-content-final-oct-2005.pdf?sfvrsn=6.Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 17

Figure 10. Model’s relationship between th e price of soybean oil and quantity of biodiesel produced from soybean oil

Figure 11. US biodiesel supply curv e at mean 2013/14 soybean yields18 / Babcock, Moreira, and Peng


### III. RIN Supply Curves
Three categories of RINs curre ntly trade. Conventional bi ofuel RINs are known as D6
RINs. D4 RINs are biomass-based diesel RINs. D5 RINs are generated by advanced
biofuels. A fourth RIN category will begin trading once cellulosic biofuel production begins in enough volume. These RINs are used to meet thre e mandates. D4 RINs can be
used to meet the biom ass-based diesel mandate , the advanced biofue ls mandate, and the
conventional biofuels mand ate. D5 RINs can meet th e advanced mandate and the
conventional mandate. D6 RINs can on ly meet the conven tional mandate.12 Because of this hierarchy, the price of D6 RINs cannot be greater than the price of D4 and D5 RINs. If it was, then the cost of meeting the conventional mandate could be lowered by using D5 or D6 RINs. Similarly, th e price of D5 RINs cannot be greater than price of D4 RINs. This means that D4 RINs will first be used to meet the biomass-based diesel mandate. They will then be in co mpetition with D5 RINs for the advanced mandate. D5 RINs will first be used to meet the advanced mandated before competing
with D4 RINs for the conventional mandate. Corn ethanol can only generate D6 RINs because current law does not allow biofuels made from corn starch to generate D5 RINs . Sugarcane ethanol is the major biofuel that can generate D5 RINs. A variety of feedstoc ks are being used to produce biodiesel and
meet the biomass-based diesel mandate. The competition for meeting the advanced and conventional manda tes takes place not on a price per gallon basi s but rather on a RIN price basi s. That is, mandates will be met at minimum cost by using the lowest -priced RINs. RIN pr ices are quoted on a dollar-per-gallon-of-ethanol basis because the RFS is expressed in ethanol equivalent gallons. Because biod iesel contains approximately 50 percent more energy per gallon than ethanol, each gallon of biodiesel generate s 1.5 RINs. To see how this competition is modeled, first consider Figure 12, which shows how th e biodiesel RIN supply curve is developed.

12 Throughout this paper the term “advanced mandate” refe rs to the portion of total advanced biofuels that is not met by RINS generated from biomass-based biodiesel.Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 19

Figure 12. Deriving the biodiesel RIN supply curve

Biodiesel RIN Supply The Figure 11 biodiese l supply curve along with the biod iesel demand curve are the drivers of the biodiesel RIN suppl y curve, as is shown in Figure 12. Recall th at a model assumption is that any quantity of biodiesel can be sold at a discounted diesel price so the demand curve in Figure 12 is fl at. In this example the demand curve co rresponds to a whol esale diesel price of $3.00 per gallon. The vertical differenc e between the biodiesel supply curve and the demand curve is the price- value gap that must be closed by the RIN price. As an example, in Figure 12 at the 2013 ma ndate level of 1280 million gallons, the plant pric e that is needed to cover the cost of prod ucing 1280 million gallon is $4.75 per gallon. The value of this quantity
of biodiesel in the market is $2.59 per gallon. Thus there is a pric e-value gap of $2.16 per gallon which will be covered by the pr ice of RINs genera ted by biodiesel. A RIN supply curve shows the RIN price that corresponds to any quantity of RINs that will be generated by biofuel plants. If biodiesel RINs were expressed in biodiesel equivalent gallons, then the biodiesel RIN supply curve would go through a price of $2.1 6 at a quantity of 1280. If an obligated party wanted to buy on e of these biodiesel-de nominated RINs instead of a gallon of biod iesel to meet their mandate, it woul d cost $2.16 per gallon. But RINs are20 / Babcock, Moreira, and Peng

expressed in ethanol equi valent gallons so that 1280 million gallons of biodiesel creates 1920 million RINs. Thus, the biodiesel RIN supply curve that corresponds to a $2.16 per gallon price-value gap goes through 192 0 million RINs, not 1280 milli on RINs. This is shown in Figure 12. Now suppose that an obligated pa rty wants to buy enough ethanol equivalent RINs to offset a $2.16 price-value gap of biod iesel. The obligated party must buy 1.5 ethanoldenominated RINs for each gallon of biodiesel that is being offset. Th e price of each of these RINs must be less than $2.16 , otherwise the obligated party would be better off buying and blending a gallon of biodiesel than buying RI Ns. The price of ethano l-equivalent RINs is simply $2.16 divided by 1.5 or $1.44 per RIN. Thus, the biodiesel RIN supply curve expressed in ethanol-eq uivalent gallons goes through a price of $1.44 and a quantity of 1920
million as shown in Figure 12. The $1.00 per gallon biodiesel tax credit is paid to blenders who buy a gallon of
biodiesel and blend it with di esel. The tax credit increases the value of biodiesel from $2.59 per gallon to $3.59 per gallon in our example. With reference to Figure 12, the impact of the tax credit is to shift the biodiesel demand curve up by $1.00. This reduces the price-value gap of biodiesel from $2.16 to $1.16 per gallon of biodiesel. The shift up
in the biodiesel demand curves shifts th e biodiesel RIN supply curve down by $0.667 per RIN at all quantities. Thus instead of a $1.44 RIN price at 1920 million RINS, the D4 RIN price would be $0.77 per RIN. The $1.00 tax credit does not reduce the D4 RIN price by a dollar because it takes 1.5 D4 RINs to offset the per-gall on price-value gap of biodiesel. If the D4 RIN pr ice fell by a full dollar to $0.44 per RIN instead of $0.77 per RIN, then the cost of offsetting the pric e-value gap of $1.16 per gallon of biodiesel though D4 RINs would only be $0.72. This is why the $1.00 tax credit per gallon of
biodiesel translates into a reduction in RIN price of $0.667 per RIN. Both RIN supply curves are shown in Figure 13.

Corn Ethanol RIN Supply The RIN supply curve of corn ethanol is deri ved similarly. At any quantity of ethanol, the RIN price is greater than zero if the ethanol price needed to cover production costs isBiofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 21

Figure 13. Biodiesel RIN supply curves with and without the $1.00 tax credit

greater than the market value of ethanol at that quantity. With a 2013 /14 yield equal to the trend yield of 160 bushel s per acre, the supply curve of ethanol shown in Figure 14 results.
The demand curve for ethanol in Figure 14 is derived at wholesale gasoline price of $2.70 per gallon. The RIN supp ly curve from corn ethanol is the ve rtical difference between the ethanol supply curve and the ethanol demand curve wh en the supply curve is above the demand curve. The price of RIN is zer o when the demand curve is abov e supply. Thus, RIN prices for
corn ethanol are zero until the mandate exceeds 13.3 billion gallons. 13 The price of RINs rises sharply after 13.3 billion gallons because of the E10 blend wall. As illu strated in Figure 14, RIN prices for conventional etha nol will have to exceed $0.85 if ethanol co nsumption is to be pushed past 14 billion ga llons with a corn yiel d of 160 and a ga soline price of $2.70, as in this example. 14

13 We can observe positive RIN prices even if the current difference between supply and demand is zero if traders expect RIN prices to rise in the future. This was the situation in the first part of the 2013 calendar year when RIN prices increased rapidly as the market became aware that RINs will be quite valuable in the future because of increased mandates. The ability to buy RINs today and bank them for use in the future is what can cause current RIN prices to be different th an the vertical distance between current supply and demand curves. How the use of banked RINs impacts the model results is discussed in Section IV. 14 The US ethanol industry likely cannot produce much more than 15.5 or 16 billion gallons of ethanol even with all plants running at capacity. The ethanol supp ly curve and the RIN supply curve in Figure 14 would22 / Babcock, Moreira, and Peng

Figure 14. Deriving the corn ethanol RIN supply curve

Sugarcane Ethanol RIN Supply The final RIN supply curve to derive is fo r sugarcane ethanol. The sugarcane ethanol supply curve that is needed to derive the RIN supply curve is the ethanol export supply curve from Brazil to the United States. Expor t supply equals total supply minus domestic demand minus export demand facing Brazil from other countries. Figure 15 shows the export supply curve when TRS production of 95 million tons, total non-fuel ethanol use of 1.5 billion liters, non-US ethanol exports are 750 million liters, and the cost of transporting ethanol to the US from a suga r refinery in Brazil is $0.38 per gallon. As shown it is quite an elastic (flat) export s upply curve because when the price of ethanol increases in Brazil, owners of flex vehicl es readily switch from ethanol to gasoline. Sugarcane ethanol qualifies as both a c onventional biofuel and as an advanced biofuel. Thus it can compete with corn etha nol in the market for D6 RINs and with
biodiesel for D5 RINs. In Fi gure 15, it is assumed that suga rcane ethanol generates D5 RINs that are used to meet the advanced mandate. Thus, the demand curve for imported

become increase vertically if this capacity limit were illustrated in Figure 14. Also, the physical limit on the US vehicle fleet to use ethanol does not exceed perhaps 16 to 17 billion gallons, a limit that would cause the demand curve to decrease vertically at this limit.Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 23

Figure 15. Advanced biofuel RIN supply curv e for sugarcane ethanol from Brazil

sugarcane ethanol is the portion of the US ethanol demand curv e that is in excess of the
corn ethanol mandate. For 2013/14 if we fix the corn ethanol mandate at 14.2 billion gallons, then the demand curve for sugar cane ethanol is as shown in Figure 15. 15

Advanced RIN Supply from Biodiesel There is one last step that is needed before showing how the model uses the RIN supply
curves to solve for market-c learing quantities and prices. Biomass-based diesel has its own mandate that can only be met by biodiesel or renewable diesel. This mandate is at 1280 million gallons for 2013. Thus, the first 128 0 million gallons of biodiesel produced will go to meet this mandate. Additional quantities of biodiesel can be produced to meet
either the advanced mandate or even the conventional mandate. This means that the competition for the other mandates begins for biod iesel where its mandate lets off, that is, at 1280 million gallons. Figure 16 shows the RIN supply curve of biodiesel for quantities

15 If California refineries have a higher willingness to pay for imported sugarcane ethanol to meet their obligations under California’s low carbon fuel standard (LCFS), then their demand curve would be the appropriate demand curve to use to derive RIN values for sugarcane ethanol. No consideration of the possibility of such a high er willingness to pay is made in this study.24 / Babcock, Moreira, and Peng

Figure 16. RIN supply from biodiesel in ex cess of the 1280 million gallon mandate

in excess of 1280 million gallons both with th e $1.00 blenders tax credit and without it. These RIN supply curves are dependent on th e assumed wholesale price of diesel and assumptions about soybean production. Altering either diesel prices or soybean supply will result in different supply curves.


### IV. RIN Competition
The hierarchy of competition between RINs means that D4 RINs will first meet the biomass-based diesel mandate, then compete to meet the advanced mandate, and then compete to meet the conventional mandate. D5 RINs will first meet the advanced mandate and then compete to meet the convent ional mandate. Thus, the price of D4 RINs can be found by looking at the biodiesel RIN supply curve in Figure 13. A 1280 million gallon biodiesel mandate is met with 1920 million D6 RINs. The price of these RINs in Figure 13 is $0.77 per gallon with the tax cr edit and $1.44 per gallon without it, when yields and gasoline prices ar e at their average levels.Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 25

Determining the price of D5 RINs needs to account for competition between sugarcane ethanol and biodiesel. Whichever fuel can generate lower-cost RINs will prevail in the competition. The cost or price of RINs is given by each fuel’s RIN supply curve. Figure 17 adds the sugarcane ethanol RIN supply curve from Figure 15 to the two biodiesel RIN supply curves from Figure 16. When biodiesel receives a tax credit, th e lowest-priced advanced RINs are from biodiesel. Until RIN prices rise to $1.37 in Figure 17, sugarcane ethanol cannot compete
with biodiesel for the advanced mandate with the tax credit. Biodiesel RINs reach $1.37 at a quantity of 634 million RINs. So if the advanced mandate is above 634 million gallons, some sugarcane ethanol will be im ported to meet the advanced mandate. The part of the mandate that exceeds 634 million gallons will be shared by sugarcane ethanol and biodiesel. If the mandate is greater th an 634 million gallons with the tax credit in place then the price of D5 RINs will equal the price of D4 RINs because biodiesel will be
used to meet both mandates. Without the tax credit, initia lly the low-cost source of advanced RINs is sugarcane ethanol. This is true until the price of s ugarcane ethanol RINs ri se above $1.44. This

Figure 17. Advanced RIN supply curves26 / Babcock, Moreira, and Peng

occurs at a quantity of 340 million RINs. If the advanced mandate is greater than 340 million gallons then sugarcane ethanol and bi odiesel will both meet the mandate and the price of D5 and D4 RINs will be equal. If the advanced mandate is lower than 340 million gallons and there is no biodiesel tax credit, then the price of D5 RINs will be less than the price of D4 RINs. Figure 18 shows how the exact mix of sugar cane ethanol and biodiesel is determined when biodiesel has the advantage of the ta x credit. The aggregate RIN supply curve to meet the advanced mandate is found by a dding the number of RINs from sugarcane
ethanol to the number of RINs from biodiesel at each RIN price. As discussed above, no sugarcane ethanol RINs will be supplied in Figure 18 until the price of RINs rises above $1.37. This means that the aggregate RIN suppl y curve equals the biodiesel RIN supply curve for RIN prices below $1.37. For higher prices, both biodiesel and sugarcane ethanol will provide addition RINs so the aggr egate supply curve is greater than either individual supply curve as shown.

Figure 18. Derivation of the aggregate RIN s upply curve and using it to determine equilibrium mix of biofuels to meet to a mandateBiofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 27

The exact mix of fuels that will be used to meet the advanced mandate is easily found. In Figure 18 the mandate is assumed to be 1000 million gallons of ethanol equivalent fuels. At this mandate the RIN pr ice that is needed to generate 1000 RINs is given by the aggregate RIN supply curve. In this example, it is $1.43 per RIN. At this price both sugarcane ethanol and biodiesel will be used to meet the mandate. Each individual fuel’s RIN supply curve is used to determine the amount of each fuel that will be used. At a $1.43 RIN price, 300 million gallons of sugarcane ethanol will be imported to meet the mandate, and biodiesel will be used to generate 700 million RINs. The quantity of biodiesel that will be produced to generate this number of RINs is 467 million gallons. Thus in this example, a total of 1,747 million gallons of biodiesel will be produced. The biomass-based diesel mandate will be met with 1280 million gallons and
the remainder will contribute towa rds meeting the advanced mandate. The same kind of competition can occur in meeting the co nventional ethanol mandate. It might be assumed that corn ethanol woul d meet the entire conven tional mandate but the sharp increase in RIN prices for corn ethanol for quantitie s of RIN in excess of 13.5 billion suggests that biodiesel RINs could compete wi th corn ethanol. Note that RIN prices for corn ethanol exceed $0.80 for qua ntities in excess of 14 billi on gallons and that biodiesel RIN prices with the tax cred it in Figure 18 are $1.43. Th is means that there is the possibility that biodiesel with the tax credit could compete with corn ethanol in the
conventional RIN market even after both the biomass-based diesel and advanced mandates are met. In this case, the price of D4 , D5, and D6 RINs would all be equal. 16 Most of the explanatory charts in this section and the prev ious section are applicable to just a single future. In reality we do not know what corn, soybean, or sugarcane yields are going to be and we do not know what gaso line prices are going to be. Each possible
outcome of these random variables will chan ge crop prices, the cost of producing biofuels, RIN prices and the equilibrium mix of biofuels that will meet the advanced mandate. To account for the wide range of po ssible future outcomes the model is solved
500 times for 500 sets of random variables. The distributions of the random variables
reflect the information that is available when the model was calibrated so that the average

16 Irwin and Good suggest that equality of RIN pri ces between corn ethanol, biodiesel, and sugarcane ethanol is likely due to the difficulty of increasing consumption of ethanol in th e United States because of the E10 blend wall.28 / Babcock, Moreira, and Peng

of the 500 model solutions can be interpreted as the expect ed outcome. But it is also
useful to examine the model outcomes for differe nt levels of the random variables. In the next section, average results across the 500 model solutions are presented. For those interested, results by quintiles are reported in the appendices in the form of charts. So, for example, equilibrium corn prices for the next marketing year are presented for the lowest 100 corn yields, the second lowest 100 corn yields, the 100 middle corn yields, the second-highest set of 100 corn yields and th e highest 100 corn yields. This allows the reader to see what happens to corn prices (and all other variables of interest) if the random variables are higher or lower than their average values. As discussed earlier, the purpose of this pape r is to provide insi ght into the impacts
of the biodiesel tax credit and Brazilian ethanol tax rates. But the model can just as easily be used to provide estimates of the impact other policies, such as alternative mandate levels. All that is needed is to specify how a particular policy affects the underlying supply and demand curves and then re-solve th e model. The next section presents model solutions for the two policies considered here. The section begins with a discussion of the mandate levels used in the analysis.



### V. Model Results
The RIN supply curves developed in the prev ious section show the importance of the level of the mandates on RIN price levels. Table 1 shows mandate levels for calendar years 2013 and 2014. The 2013 mandates are th e latest proposed mandates from EPA although some believe that the volumes could still be subject to change. The 2014
biomass-based diesel mandate has not been determined. Throughout this analysis we assume that it will stay at its 2013 level. Total advanced biofuel mandates are as they were written into law by Congress. Other ad vanced mandates are simply equal to total
advanced minus the biomass-based diesel ma ndates. The 2013/14 marketing year average is the weighted average of the calendar year 2013 and 2014 mandates with a one-third weight being given to 2013. Two key uncertain ties for this analysis regarding mandates are whether EPA is going to reduce the a dvanced mandate for 2014 and the number of banked conventional RINs that are going to be used in the 2013/14 marketing year.Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 29

Table 1. RFS Volumes 2013 2014 2013/14

(billion gallons) Total Renewable Fuel 16.55 18.15 17.62 Conventional Biofuel 13.8 14.4 14.20 Total Advanced Biofuel 2.75 3.75 3.42 Biomass-Based Diesel gallons of biodiesel 1.28 1.28 1.28 ethanol equivalent gallons 1.92 1.92 1.92 Other Advanced 0.83 1.83 1.50
Even though cellulosic biofue ls has a mandate, the lack of production has led EPA to waive nearly all of it. To date, however, EPA has kept the total volume of advanced biofuels constant. If EPA does this again in 2014, then the portion of the advanced mandate that can be made by sugarcane ethanol or bi odiesel in excess of the biomass-based diesel mandate increases significantly by one billion gallons. If instead EP A were to reduce the total advanced volume by the cellulosic volum e, then the other advanced portion would stay constant at 0.83 billion gallons, assuming that the bi omass-based diesel mandate stays constant. Whether the 2013/14 weighted average mandate used in this analysis is 1.5 billion gallons or 0.83 billion gallons is primarily impor tant for the amount of ethanol that will be mandated because, as shown in the previous section, high levels of ethanol assumption can only be consumed if the ethanol price is he avily discounted to consumers. These heavy discounts will be accomplished by high RIN prices. The model used here is a one-year annual m odel. Thus it cannot directly account for
how the incentive to bank or borrow RINs a ffects RIN prices. The RI N prices calculated by the model are simply the current year’s ve rtical distance between the supply curve for a biofuel and its demand curve. Thus, the mandates that are used in our model should
reflect the actual volumes of biofuels consum ed in the year. For biodiesel and sugarcane ethanol, the only divergence be tween the Table 1 mandates a nd the actual volumes that will be consumed will be if obligated parties decide to build their bank of advanced RINs by blending more of these biofuels than they are required to do because the current bank of advanced RINs is empty. Given the hi gh RIN prices that we see today and the uncertainty about the future of the RFS, it is unlikely that obligated parties will build their bank of these RINs, so it is safe to assume that the mandated volumes will be consumed.30 / Babcock, Moreira, and Peng

But the bank of ethanol RINs is not em pty. As of the beginning of 2013 there were approximately 2.4 billion banked conventional RINs available. Some portion of these
RINs will be used to meet the 2013 mandate if current trends continue. But given continued growth in the conventional mandate, it is likely that obligated parties will not want this bank to go to zero at the end of 2014. If we assume that the stock of banked
RINs will total one billion at the end of cal endar year 2014, and that banked RIN use will be constant for all months in 2013 and 2014, then 700 million banked RINs will be used for each 12 month period. This means that in the 2013/14 marketing year, the level of the conventional mandate that will be met by actual consumption of ethanol will be 13.5 billion gallons. Average results across the 500 model solutions are reported in Table 2 for the United
States and Table 3 for Brazil. The first colu mn of results are baseline results which assumes that the $1.00 per gallon US biodiesel tax credit is exte nded through the 2013/14 marketing year and that Brazil maintains its R$0.12 per liter reduction in the tax on hydrous ethanol. The second column of results a ssumes that the US biodiesel tax credit is not in place for the 2013/14 marketing year. Thus , subtracting the column 2 results from the column 1 results shows the impact of th e tax credit. The third column of results
assumes that the Brazilian ethanol tax reduction is not in place. Thus, the impacts of the tax reduction can be seen by subtracting the column 3 results from the column 1 results.

Baseline Results Before discussing the impacts of the two policies analyzed, it is useful to examine the
baseline results. In the Un ited States, the combination of an average yield of 160 bushels per acre, harv ested acreage of 89.5 million acres, and be ginning stoc ks of 759 million bushels implies total corn supplies of more than 15 billion bushels. This much corn combined with USDA’s corn demand proj ections implies much lower corn prices
and an abundance of corn to produce ethanol. Ethanol pro duction averages 15.9 billion gallons, well in excess of mandated consumption levels. The excess production is exported. In Table 1 the US ethanol supply price averages only $1.80 per gallon. With an average wholesale gasoline price of $2.69 per gallon th is means that US ethanol production costs will only be ab out 67 percent of the gasoline price. So even if ethanolBiofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 31

Table 2. Results for the United States

Baseline No Biodiesel Tax Credit No Brazil Tax Reduction Ethanol Quantities (billion gallons) a Production 15.9 16.2 15.1 Exports 2.36 2.66 1.34 Consumption 13.88 14.33 13.96 Imports 0.31 0.82 0.40 Ethanol Prices ($/gal) Demand Price 1.39 1.30 1.35 Supply Price ($/gal) 1.80 1.83 1.74 Biodiesel Production (million gallons) 1654 1,330 1616 Biodiesel Prices ($/gal) Demand Price 2.47 2.47 2.47 Supply Price 5.22 4.54 5.13 RIN Prices ($/gall on-ethanol-equiv.) Conventional (D6) 0.41 0.53 0.39 Advanced (D5) 1.16 1.28 1.11 Biodiesel (D4) 1.16 1.38 1.11 Corn Price ($/bu) 4.83 4.91 4.60 Soybean Complex Prices Soybean ($/bu) 10.55 10.31 10.52 Soybean oil ($/lb) 53.34 48.17 52.74 Soybean meal ($/ton) 284.98 297.15 286.40

a Production and consumption quantities are anhy drous-equivalent gallons of ethanol.

Table 3. Results for Brazil

Baseline No Biodiesel Tax Credit No Brazil Tax Reduction Ethanol Quantities (billion gallons) a Production 8.39 8.41 8.37 Fuel Consumption 9.88 9.70 8.81 Ethanol Prices ($/gal) b Plant Price ($/gal) 2.07 2.09 1.98 Retail Price ($/gal) 2.94 2.97 3.06 Share of TRS to Ethanol 0.564 0.565 0.563 Sugar Production (million tons) 39.56 39.52 39.71 Sugar Exports (million tons) 26.96 26.92 27.10 World Sugar Price ($/lb) 0.219 0.220 0.211

a Production and consumption quantities are h ydrous-equivalent gallons of ethanol. b Prices expressed in $US per gallon of hydrous ethanol. An exchange rate of 2 reais per dollar is used.32 / Babcock, Moreira, and Peng

is priced at its energy valu e (as it is in Brazil) there will be ample demand for US
ethanol at this co st of production. 17 With regards to biodiesel, production aver ages 30 percent over the biomass-based diesel mandate. This extra production is used to meet a large share of the advanced mandate, displacing imported sugarcane et hanol. Because both imported sugarcane
ethanol and biodiesel ar e used to meet the advanced mandate in almost all of the model outcomes, the average D4 RIN price is equal to the D5 RIN price.

Biodiesel Tax Credit Results The biodiesel tax credit increases the competitiveness of biodiesel relative to sugarcane ethanol, and imports of sugarcane ethanol to meet the US advanced mandate decline by an average of 510 million gallons. Because more Brazilian ethanol is consumed in Brazil, the tax credit reduces US ethanol exports to Brazil by an average of 300 million gallons; although, US exports to Brazil in the baseline case are projected to average more than they have ever been in the past at 2.36 billion gallons. Relatively low corn prices combined with continued high gasoline prices and an elastic expor t demand set the stage for the US to be a major ethanol exporter across all three scenarios. The drop in demand for US ethanol exports decreases US pr oduction a small amount (300 million gallons) and the price of corn drops by an average of 8 cents per bushel. The biodiesel tax credit reduces US consumption of ethanol so the US ethanol demand price is 9 cents per gallon higher under the tax credit. The drop in etha nol production due to adoption of the tax credit reduces the ethanol supply price by 3 cents per gallon so the conventional RIN price is reduced by 12 cents per gallon because of the biodiesel tax credit.
The tax credit increases biodies el production by an average of 324 milli on gallons. This increased production incr eases the soybean price by 24 cents per bushel, soybean oil prices by about 5 cents per pound, and re duces the soybea n meal price by $12 per ton. Because the
tax credit increases the biodies el demand price by $1.00 per gall on of biodiesel, the biomass based diesel RIN price is decreased because of the tax credit. The diffe rence in RIN price of

17 No capacity constraint was imposed on US ethanol production in the model. If the industry cannot produce in excess of 15.5 or 16 billion gallons, then average US exports will be cut and the price of corn will drop. This will create profits for the industry and an incentive to add capacity.Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 33

22 cents per gallon of etha nol equivalent is less than the full amount of the tax credit because the supply price of biodiesel is 68 cents high er due to higher feedstock costs and higher required margins needed to pr oduce that addi tional biodiesel. 18 A combination of biodiesel and sugarcane ethanol met the advanced mandate in 491
of the 500 model solutions. The ot her nine were met solely w ith biodiesel. Thus, the D5 and D6 average RIN prices ar approximat ely equal at $1.16 per gallon. Without the tax credit, 278 of the 500 model solutions had impor ted sugarcane ethanol meeting all of the advanced mandate. Thus, without the tax cr edit the average D4 RIN price is 10 cents higher than the average D5 RIN price. In Brazil, the biodiesel tax credit lowers the plant price of ethanol by two cents per gallon because of the drop in demand fo r Brazilian ethanol. From Table 2, ethanol exports to the United States drop by 510 million gallons as biodiesel takes a larger share of the advanced mandate. This drop in expor ts reduces the demand for U.S. imports. The net effect on ethanol consumption in Braz il is a decline of 180 million gallons. Because the price of ethanol is largely unchanged in Br azil, the impact of the biodiesel tax credit on sugar production, exports and world prices is small.

Brazil Tax Reduction Results The decision by Brazil to reduce the tax on etha nol is an attempt to offset the negative effects on ethanol demand from Brazil’s pol icy of holding down ga soline prices below world market levels. Thus, the effect of th e tax reduction is to increase the demand for ethanol. From Table 3, the average effect of the tax reduction (found by subtracting column 3 results from column 1 results) on Brazilian ethanol prices is to increase the plant price of ethanol by 9 cents (US) per ga llon. Part of the tax reduction is passed along to consumers in the form of lower retail prices, which decrease by 12 cents per gallon. This reduction in retail price increases ethanol consumption in Brazil by 1.07 billion gallons (about 14 percent). As shown in Table 2, a larg e portion of this increased consumption is accounted for by the large chan ge in imports from the United States, and

18 To see where the $1.00 tax credit goes, on a gallon of ethanol equivalent basis, $1.00 of biodiesel is $0.67 per gallon of ethanol. The 68 cents per gallon of biodiesel change in the biodiesel supply price is 45 cents per ethanol-equivalent gallon. The change in RIN price is 22 cents per gallon of ethanol. Thus, the sum is 67 cents per gallon.34 / Babcock, Moreira, and Peng

a smaller portion is accounted for by a drop in ethanol exports to the United States. This
shows how the tax reduction makes Brazil a more attractive place to se ll ethanol, whether it is produced in the United States or Brazil.
The tax reduction in Brazil increases US ethanol production by an average of 790 million gallons (5.2 percent). Be cause average US exports increa se by about this amount and US imports from Brazil decrease, less ethanol is consumed in the United States. This drop in consumption increases the ethanol demand price by 4 cents per gallon. However, because the
Brazilian tax reduct ion increases US ethanol productio n, the US supply price of ethanol increases by 6 cents per gallon because of higher co rn prices. Thus conv entional RIN prices increase by an average of 2 cents per gallon. Because the biod iesel tax credit is assumed to be in place in both the baseline set of results and in the results wi th no Brazil tax re duction, both biodiesel and sugarcane ethanol ar e used to meet the advanced mandate. Becaus e the price of
Brazilian ethanol increases due to the tax reduction, the cost of importing sugarcane ethanol
increases so the D5 a nd D6 RIN prices increa se by an average of 5 cents. Because the tax reduction increases the demand for biodiesel, th e average price of soybean oil increases by 0.6 cents per pound, the pr ice of soybean meal decreases $1.42 per ton, and th e price of soybeans increase by an aver age of 3 cents per bushel. The increased price of ethanol in Brazil be cause of the tax reduction causes Brazilian refineries to tilt slightly more towards et hanol and away from s ugar. Brazilian sugar production drops by an average of 150,000 tons, almost all of which comes out of the export market. Thus world sugar prices av erage 0.8 cents per pound higher (3.8 percent) with the tax reduction in place than without it.



### VI. Concluding Remarks

To understand biofuels markets in the Unite d States and Brazil requires understanding feedstock markets, government policies, and consumer demand for fuel. And, because
direct trade barriers in biofue ls are low, it is important to consider how changes to policies in one country affect biofuels in the other. R ecent biofuel policy changes in Brazil and the United States are analyzed with an objective of fostering greater understanding of the important factors that a ffect biofuel markets in the two countries. The re-introduction of the $1.00 pe r gallon biodiesel tax credit in the United States at theBiofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 35

end of 2012 increases the demand for biodies el and reduces the demand for imported sugarcane ethanol. Thus less sugarcane ethanol will be imported to meet the advanced
biofuel mandate in the United States. On May 8, 2013, Brazil decreased the tax on
ethanol. This reduction increases the dema nd for ethanol in Brazil, making it more attractive place to sell ethanol, whether it be domestically produced or imported. A stochastic simulation model provides esti mates of the market impacts of these two policy changes for the upcomi ng 2013/14 US corn marketing year that begins on September 1, 2013. The results demonstrate how ethanol trade links the US and Brazilian markets even though the total volume of trade between the two countries is low relative to total production and consump tion. The results also dem onstrate how US mandates link
ethanol and biodiesel markets because biodiesel is allowed to meet its own mandate, the mandate for other advanced biofuel, and even the conventional mandate. Sorting out the net effects of these policy changes across both countries and across fuels requires a detailed model of each key market. Because a model is only as good as the assumptions and data that underlie it, it is important to be transpar ent about the assumptions and the data used to parameterize the supply and demand curves th at make up the model. Because the model used in this analysis is upda ted often, interested readers who disagree with assumptions
used or who have better data are welcom e to share their in sights and data. Finally, as with all model-based projections of future price levels, one should take care when viewing the exact level of prices be ing projected. If one or more parts of the model calibration differs significantly from current market conditions, then the model projections may be quite diffe rent from current price levels as indicated by futures markets. Or if the set of prices and quantitie s to which the model is calibrated are flawed then so too will be the projected prices levels from the model. 19 Less sensitive to the
exact model calibration are the differences in price levels ac ross different policy
scenarios or across different levels of the exogenous stochastic va riables that include yields, gasoline price, and world de mand for Brazilian sugar exports.

19 For example, there are three aspects of the May WA SDE projections that some feel may be opne to question. Projected corn feed use seems high given the drop in the number of cattle on feed. Projected corn exports seem low given historic export levels and the level of projected corn production that is possible. And the projected soybean crush spread at more than $2.00 per bushel seems high.36 / Babcock, Moreira, and Peng


### Appendix A. Results Conditional on US Corn Yields

Figure A1. Impact of corn yield on corn price: Baseline policies.

Figure A2. Impact of corn yield on conv entional RIN price: Baseline policies 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00

138 152 161 170 178$perbushel

Corn Yield Quintile Mean (bushels per acre)

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70

138 152 161 170 178$perRIN

Corn Yield Quintile Mean (bushels per acre)Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 37

Figure A3. Impact of corn yield on et hanol net exports: Baseline policies

Figure A4. Impact of corn yield on US ethanol consumption: Baseline policies 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00

138 152 161 170 178billiongallons

Corn Yield Quintile Mean (bushels per acre)

10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0

138 152 161 170 178billiongallons

Corn Yield Quintile Mean (bushels per acre)38 / Babcock, Moreira, and Peng

Figure A5. Impact of corn yield on US ethanol supply and demand prices: Baseline policies

Figure A6. Impact of corn yield on ad vanced and biomass diesel RIN prices: Baseline policies 0.00 0.50 1.00 1.50 2.00 2.50

138 152 161 170 178$pergallon

Corn Yield Quintile Mean (bushels per acre) Supply Price Demand Price

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60

138 152 161 170 178$perRIN

Corn Yield Quintile Mean (bushels per acre)Biofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 39


### Appendix B. Results Conditional on US Gasoline Prices

Figure B1. Impact of gasoline price on conventional RIN price

Figure B2. Impact of gasoline price on biomass diesel RIN price 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90

2.15 2.45 2.67 2.91 3.34$pergallon

Gasoline Price Quintile Mean ($ per gallon) Baseline
No Biodiesel Tax Credit
No Brazil Tax Reduction

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80

2.15 2.45 2.67 2.91 3.34$pergallon

Gasoline Price Quintile Mean ($ per gallon) Baseline
No Biodiesel Tax Credit
No Brazil Tax Reduction40 / Babcock, Moreira, and Peng

Figure B3. Impact of gasoline price on advanced RIN price

Figure B4. Impact of gasoline price on biodiesel production 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80

2.15 2.45 2.67 2.91 3.34$pergallon

Gasoline Price Quintile Mean ($ per gallon) Baseline
No Biodiesel Tax Credit
No Brazil Tax Reduction

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800

2.15 2.45 2.67 2.91 3.34milliongallons

Gasoline Price Quintile Mean ($ per gallon) Baseline
No Biodiesel Tax Credit
No Brazil Tax ReductionBiofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 41

Figure B5. Impact of gasoline price on soybean oil prices 40 42 44 46 48 50 52 54 56

2.15 2.45 2.67 2.91 3.34centsperpound

Gasoline Price Quintile Mean ($ per gallon) Baseline
No Biodiesel Tax Credit
No Brazil Tax Reduction42 / Babcock, Moreira, and Peng


### Appendix C. Results Conditiona l on Brazilian Production of TRS

Figure C1. Impact of TRS production on world sugar price

Figure C2. Impact of TRS production on Brazilian sugar exports 0.00 0.05 0.10 0.15 0.20 0.25

98.3 96.5 95.2 93.9 92.1$perpound

TRS Quintile Mean (million tons) Baseline
No Biodiesel Tax Credit
No Brazil Tax Reduction

22.0 23.0 24.0 25.0 26.0 27.0 28.0

98.3 96.5 95.2 93.9 92.1milliontons

TRS Quintile Mean (million tons) Baseline
No Biodiesel Tax Credit
No Brazil Tax ReductionBiofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 43

Figure C3. Impact of TRS production on Brazilian ethanol production

Figure C4. Impact of TRS production on Brazilian ethanol price received by plants 7.40 7.60 7.80 8.00 8.20 8.40 8.60 8.80 9.00

98.3 96.5 95.2 93.9 92.1billiongallons

Sugar Export Demand Shock Quintile Mean (million tons) Baseline
No Biodiesel Tax Credit
No Brazil Tax Reduction

1.75 1.80 1.85 1.90 1.95 2.00 2.05 2.10 2.15

98.3 96.5 95.2 93.9 92.1$pergallon

TRS Quintile Mean (million tons) Baseline
No Biodiesel Tax Credit
No Brazil Tax Reduction44 / Babcock, Moreira, and Peng


### Appendix D. Results Conditional on World Demand for Brazilian Sugar

Figure D1. Impact of sugar export demand shock on world sugar price

Figure D2. Impact of sugar export de mand shock on Brazilian sugar exports 0.00 0.05 0.10 0.15 0.20 0.25 0.30

1.69 0.59 0.01

‐ 0.62

‐ 1.67$perpound

Sugar Export Demand Shock Quintile Mean (million tons) Baseline
No Biodiesel Tax Credit
No Brazil Tax Reduction

22.0 23.0 24.0 25.0 26.0 27.0 28.0 29.0 30.0

1.69 0.59 0.01

‐ 0.62

‐ 1.67milliontons

TRS Quintile Mean (million tons) Baseline
No Biodiesel Tax Credit
No Brazil Tax ReductionBiofuel Taxes, Subsidies, and Mandates: Impacts on US and Brazilian Markets / 45

Figure D3. Impact of sugar export demand shock on Brazilian ethanol production

Figure D4. Impact of sugar export demand shock on Brazilian ethanol price 7.60 7.80 8.00 8.20 8.40 8.60 8.80

1.69 0.59 0.01

‐ 0.62

‐ 1.67billiongallons

Sugar Export Demand Shock Quintile Mean (million tons) Baseline
No Biodiesel Tax Credit
No Brazil Tax Reduction

1.75 1.80 1.85 1.90 1.95 2.00 2.05 2.10 2.15

1.69 0.59 0.01

‐ 0.62

‐ 1.67$pergallon

Sugar Export Demand Shock Quintile Mean (million tons) Baseline
No Biodiesel Tax Credit
No Brazil Tax Reduction46 / Babcock, Moreira, and Peng

References
Babcock, B.A., K.J. Barr, and M. Carriquir y. 2010. “Costs and Benefits to Taxpayers, Consumers, and Producers from U.S. Etha nol Policies.” Staff Report, 10-SR 106, Center for Agricultural and Rural Development, July 2010.

CONAB. 2013. “Cana-de-Acúcar: Safra 2013/20 14 Primeiro Levantamento Abril/2013.
EPE. 2013. “Avaliacão do Comportament o Dos Usuários de Veículos Flex Fuel No Consumo de Combustíveis No Brasil.” Minist ério de Minas e Energia, Government of Brasil. March 2013.
Irwin, S., and D. Good. 2013. “Is Speculation Driving Up the Pr ice of RINs?” Available at http://farmdocdaily.illi nois.edu/2013/04/speculation- driving-up-price-rins.html