INTERMODAL AND MARKETING OF BRAZILIAN ETHANOL: AN APPLICATION OF A PARTIAL

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1 INTERMODAL AND MARKETING OF BRAZILIAN ETHANOL: AN APPLICATION OF A PARTIAL EQUILIBRIUM MODEL JAMILE DE CAMPOS COLETI¹, ANDREA LEDA RAMOS DE OLIVEEIRA² Institute of Economics, University of Campinas, Brazil¹ Faculty of Agricultural Engineering, University of Campinas, Brazil² Paper prepared for presentation at the 19 th ICABR Conference IMPACTS OF THE BIOECONOMY ON AGRICULTURAL SUSTAINABILITY, THE ENVIRONMENT AND HUMAN HEALTH Ravello (Italy): June 16-19, 2015 Copyright 2015 by author(s). All rights reserved. Readers may make verbatim copies of this document for noncommercial purposes by any means, provided that this copyright notice appears on all such copies.

2 ABSTRACT: The search for renewable energy sources have been increasing the global demand for ethanol. Brazil holds the position as the second largest ethanol s producer of the world, but the costs to transport this production are increasingly high. The main idea of this paper is to analyze the alternatives ethanol transportation in face of the logistics of the prevailing conditions in Brazil. Therefore, it is proposed a partial equilibrium model as a Mixed Complementarity Problem (PCM) applied to ethanol. It was evaluated three scenarios, the first is a baseline scenario with shipping routes on road modal and intermodal, the second estimated that the 15% reduction in the value of rail freight and the third is included new pipelines projects underway in the country. The scenario 3 presented the best marketing volumes with an increase of 0.20% compared to baseline, indicating that the road projects that prioritize intermodality, especially through the pipeline, implying reductions in the cost of transport and bestow an improvement in the efficiency the logistics system. Also noteworthy is that the cases of intermodal scenarios 2 and 3 reflected gains in competitiveness on the international market, because 100% of the routes to the external market are intermodal. Keywords: ethanol, spatial equilibrium, logistics. INTRODUCTION: Agribusiness expansion has been characterized by increasingly integrated production chains and by intensive use of capital in the various segments that comprise them. According to Oliveira (2011), agriculture is still characterized by its high share in the GDP, by maintaining trade surplus, as well as by contributing to control the inflation. According to data collected by the Centro de Estudos Avançados em Economia Aplicada (Center of Advanced Study in Applied Economics - CEPEA, 2015), agribusiness GDP represented a 23% share of overall GDP in 2013, and according to the Confederação de Agricultura e Pecuária do Brasil (Brazil Agriculture and Husbandry Condeferation - CNA, 2014), GDP variation between 2012 and 2013 was larger for agribusiness GDP (+3.56%) than for Brazilian GDP (+2.25%). Sugar-alcohol industry is one of the sectors that contribute for Brazilian agribusiness prominent position. Within a highly competitive environment caused by globalization, this production sector is overcoming barriers as from the creation

3 of Proálcool and going through 2009 economic crisis progressively increasing its production and insertion into the global market. Brazilian agro-industrial systems are highly developed, but despite the growth expected for the sector, new challenges arise, such as the domestic logistics system. According to Souza Filho (2014), logistics is responsible for the physical and information flow, from obtaining raw material to distribution of final product. Such activity is extremely relevant as various agricultural raw materials lose their quality if not harvest at the right time, transported under specific conditions and processed right after the harvest. Oliveira (2014) says the expression logistics blackout is pervading discussions concerning issues related to transportation, ports and storage in Brazil. Difficulties to transport agriculture and husbandry products are calling the attention of public and private sectors. Hence, logistics goes beyond mere goods handling function and assumes a strategic role in agribusiness. So, the purpose of this article is to analyze transportation alternatives for different ethanol routes in the face of current logistics conditions in Brazil, assessing the implications of transportation infrastructure restraints for enhancing ethanol competitiveness in the domestic and international markets. Then, we propose a partial equilibrium model in the form of a Mixed Complementarity Problem (PCM) applied to ethanol. The use of the model also aims to assess different scenarios related to ethanol handling logistics so as to guide new transport system projects capable of increasing the competitiveness of the sector. After the introduction, this paper will be arranged as follows: item one provides an overview of ethanol in Brazil; item two refers to ethanol transportation; item three describes the methodology used; item four presents the results achieved and an analysis of the scenarios proposed and, next, the final remarks. 1. ETHANOL IN BRAZIL Brazil is the world's second largest ethanol producer according to UNICA (2014) data. In 2012/2013 harvest, Brazil produced approximately 23 million m³, lagging behind only the United States that produced approximately 50 million m³ (RENEWABLE FUELS ASSOCIATION, 2014). Lemos et al. (2015) affirms that, in 2011/2012 harvest, approximately 16% of Brazilian plants have reached productivity levels greater than 6,500 liters/ha, classified as high productivity. Note that these plants are located in regions considered as agricultural frontier expansion areas, including the states of GO, MG, MS, MT, and SP. On the other

4 hand, 14% plants have shown productivity levels classified as very low, the justification being the fact that low productivity chiefly results from lack of investment in sugarcane farms and farming practices. Freitas and Kaneko (2011) say that the fact that ethanol is being used for carburant purposes both as gasoline additive and for directly fueling flex-fuel vehicles is being responsible for deep changes in Brazil fuel consumption dynamics. The increase of oil prices, the strong demand for clean and renewable sources of energy and the intense commercialization of flex-fuel cars have created a very favorable scenario for biofuel production. Ethanol has also environmental advantages, as its combustion generates less carbon dioxide than gasoline. Studies by the Ministry of Agriculture, Animal Husbandry and Food Supply (MAPA, 2010) estimates indicate that for harvest the country is expected to be producing billion liters of ethanol, which would represent a 146% increase over the volume produced in Another relevant factor to be discussed is the participation of foreign capital in the sector. In the last years, a pronounced process of mergers and acquisitions have affected sugar-alcohol industry companies. According to Moraes et al. (2013), these strategies have significantly changed the structure of this market, creating large domestic and international groups seeking out increase of efficacy and competitiveness through gains of scale, scope and synergies between companies creating the need for more efficient trading structures and investments in the development of new products and technologies. According to Nastari (2010), the participation of foreign groups in sugarcane milling in 2008 was 12.4%, went to 18.4% in 2009, and with the emergence of Raízen joint venture, the percentage reached 22.9%. The state of São Paulo is responsible for processing approximately 55% of the raw material produced in the country, and is the leading ethanol producing state. Following behind is the state of Goiás, responsible for processing (9%), Minas Gerais (8%), Paraná (6%), Mato Grosso do Sul (6%), and Mato Grosso (2%). In the Northeast region, the states have smaller share in sugarcane processing, the more representative states being Alagoas and Pernambuco, representing only 3% and 2%, respectively, of total raw material processed in the country. According to Petean et al. (2011), ethanol production, due to being an agro-industrial activity, receives direct impact from sugarcane planting and harvest timing effects, the months from December to March being the intercrop period and the remaining months the harvest periods. With respect to exports, Brazil holds the world leadership position. According to SECEX (2014) data, 3.09 million cubic meters of ethanol were exported along 2012, a volume 55.3% larger than in 2011, when approximately 1.96 million

5 cubic meters of ethanol were exported. Regarding Brazilian ethanol buyers, the United States are in fact the great Brazilian ethanol buyer, followed by South Korea and the Netherlands. According to Conab (2014) data, sugarcane productivity is being maintained at 72.4 kg/ha. The forecast of better weather conditions for the next harvest in relation to the past, as well as larger investment in maintenance of sugarcane farms, and expansion of field renovation promise a better performance. As to ethanol production, this is being kept at 23 billion liters in 2012/13 harvest. According to the latest CONAB (2014) survey, a production of 27.6 billion liters is expected for 2014/15 harvest, decline of approximately 1% from last harvest (2013/2014) 27.9 billion liters. The sector is growing under a positive perspective, supported by the growth of domestic market, global demand expansion and decrease of worldwide stocks that have made the prices more attractive to producers. 2. ETHANOL TRANSPORTATION Carvalho and Caixeta Fiho (2007) defend that an efficient logistics system is paramount for competitiveness of all economic sectors, as it intends to guide production processes, meeting the demand for products in terms of quality, timetable, technical assistance and innovation. In this case, the growing demand for ethanol requires high inversions of storage/tankage unit on strategic locations and a transportation structure compatible with growing production and consumption of this type of fuel. The expansion of sugarcane planted area could put a lot of strain on ethanol transportation system. Brazil is the world's leading ethanol producer and consumer, lagging behind only the United States, but the country's competitiveness power is restrained due to infrastructure and logistics issues that bring uncertainties as to supply guarantees. Currently, the country operates with the following transportation modes: road, railroad, waterway, pipeline, and air, and agricultural commodities are mostly transported by road. The road mode prevails in cargo transportation in Brazil, virtually reaching all areas of the national territory. It is responsible for over 60% of Brazilian transportation system. This mode is indicated for shorter distances, but this is not the case; due to its high availability, agricultural cargo ends up traveling long distances by road. The cost of road transportation is expressed by the term freight. Among ground modes, road transportation presents the highest cost, and still it is the most widely used.

6 The large amount of producing units and their proximity with distribution centers ease the prevalence of the road mode for ethanol transportation, which is more competitive in short routes and with low cargo volumes. In rare cases, there is drayage, short road segments up to transshipment terminals for other transportation modes. According to Milanez et al. (2010) plants are usually located on agricultural regions that have difficulty to access major transportation roadways and, due to the price of production, the investment in other transportation modes is not feasible. The possibility of door-to-door delivery is an advantage, where direct delivery from plants to fuel dealers takes place; in some cases, agreements for transportation directly from plant to fuel stations are possible. When it comes to the railroad mode, according to Ballou (2004), it has high sunk cost, despite the higher cargo transportation capacity generating economies of scale and for being slower, it is recommend for large amount of solid bulk cargo, larger travels and reasonable times. Table 1 indicates the progress of railroad usage for ethanol transporting, that increased in the last 3 years. Table 1. Progress of railroad ethanol transportation share for period (%) Railroad Fuels share in railroad transportation Ethanol share in fuel transportation Ethanol share in railroad transportation Source: ANTT (2015) Among the advantages from using railroads for ethanol transportation are: lower product cost increasing competitiveness in the foreign market; decrease of traffic congestion of trucks in port roadways, as well as environmental improvement through less release of carbon gas (JANOTTI et al., 2012). Regarding the waterway mode, for the transportation of sucro-energetic products from Brazil Central South, the single waterway that serves or is capable of serving the transportation of these products is Tietê-Paraná, and, due to the strong drought, it was rendered non-navigable along most of On the other hand, some alcohol ducts are being planned, so as to overcome the bottlenecks of fuel transportation market, such is the case of Logum project, a multimodal pipeline-railroad complex that will cover five states: São Paulo, Rio de Janeiro, Goiás, Minas Gerais, and Mato Grosso do Sul. For Milanez et. al (2010) new competitiveness gains can be achieved with the beginning of operation of the alcohol ducts.

7 Ethanol handling starts on one of the producing units. Next, ethanol is transferred for collection facilities for storage. Sometimes the product could be directly transferred for the distribution base. This transportation is mostly made by road. Oliveira (2015) states that after receipt at the collection facilities, ethanol is transported to distribution bases and, later on, transported from the bases to the domestic market or ports. Products destined for the domestic market (fuel stations or retail dealer) is usually delivered by road. Figure 1 shows ethanol transportation dynamics from plants/distilleries to final destination. According to ANP (2012) data, approximately 329 fuel distribution bases exist in Brazil. Production Distribution Trade PLANTS COLLECTION FACILITY EXPORT PORTS DISTRIBUTION FACILITIES FUEL STATIONS AUTOMOBILE CONSUMPTION Road Pipeline, Railroad or Waterway RETAILER INDUSTRIES AGRICULTURE CARRIERS Source: Adapted from Oliveira, Figure 1. Ethanol transportation dynamics The private sector, logistics segment main stakeholder, has been investing to improve the transportation network. One example is Odebrecht TransPort in partnership with Petrobras, Camargo Corrêa, Cosan Açúcar e Álcool, Copersucar, and Uniduto Logística that is developing a project for the construction of a multimodal logistics system comprised of a polyduct network of approximately 1,900 km integrated to Tietê-Paraná Waterway. The system intends to

8 allow the long distance storage of clear fuels, focused on ethanol a business estimated in R$ 6 billion. The system aims to integrate ducts and waterways to railroad, road and marine modes critical for the export process. This integration between different transportation modes will cover several key ethanol producing Brazilian states. Expected transportation capacity is 21 billion liters per year and transportation cost-cutting target is 20% (ODEBRECHT, 2011). This evidences the need for investments in the sector as an attempt to ensure competitiveness through the free market. Actually, the country operates with the following transportation modes: road, railroad, waterway, pipeline, and air, and agricultural commodities are mostly transported by road. Lício (1995) points out the need for making feasible and integrating multimodal transportation corridors (road, railroad, pipe, and waterway) as an instrument to leverage competitiveness of cargo transportation, linking production areas, consumer centers and international market. According to Caixeta Filho and Gameiro (2001), multimodality is extremely important for the development of nations when it comes to redistributing their internal transportation systems, so as to obtain a better position in the globalization process. Brazil has been making its way toward incorporating a multimodal transportation system so as obtain advantages such as cost reduction, shorter transit-time and decrease of cargo risks. 3. METHODOLOGY Samuelson (1952) was a pioneer in showing that it would be possible to solve spatial equilibrium problems between different markets through mathematical programming. He proposed the problem of two spatially separated markets in a non-normative economy on a mathematical maximization program. This problem was formulated with the purpose of maximizing under all excess demand curves minus the area of all excess supply curves, minus total transportation costs, resulting in a competitive spatial equilibrium solution, i.e., based on the resulting intersection areas of the curves of these three variables. Takayama and Judge (1971) used supply and demand functions to obtain spatial and atemporal dimensions for price, production, utilization factor and consumption determined by means of a quadratic programming chart. Based on Samuelson assumption, a suitable algorithm was developed to solve spatial equilibrium conditions involving commodities traded between different regions.

9 Alvim (2003), show that different theoretical approaches have been used to measure supply-demand interactions, with emphasis on general and partial equilibrium models. Oliveira (2011) defends that general equilibrium models require some information that sometimes is not available, therefore, simplifying assumptions have to be adopted compromising the results achieved. In partial equilibrium model, the direct impacts of any trade policy over a given market are analyzed. Due to being an agricultural commodity, its trade goes through origin and destination and is subject to elasticity effects, so partial or spatial equilibrium models are those that best suit this paper (BROWN and DRYNAN, 1986). Mattei (2007) says that spatial equilibrium models could be used to evaluate the effects of agricultural, commercial or weather policies in the agricultural or forest industries. In the case of sucro-energetic industry, Satolo and Caixeta Filho (2010) assess the impact of new plants and distilleries entering into operation during 2010/11 harvest over the distribution of hydrous ethanol in the Central West region. The writers used the spatial price equilibrium model to analyze the impact. The main finding of the research indicated that trade in the region should prioritize the destination for the state of São Paulo, a major player in the ethanol market. To forecast the impacts and effects of adopting new transporting policy for Brazilian ethanol trade, this paper developed a partial equilibrium model formulated as a Mixed Complementarity Problem (PCM) for ethanol transportation, proposed by Oliveira (2011). 3.1 DESCRIPTION OF MODEL DATA Initially, ethanol transportation routes to be analyzed were defined based on ethanol supply and demand data. The regions were selected according to their relevance for product commercial dynamics. This was possible by examining the behavior of the following variables along 2013: ethanol production, average output, planted area, exports, consumption and industrial capacity of sugar-alcohol plants. The definition of the regions included in the model was made through the relevance of their participation in the variables. The purpose was to characterize ethanol market dynamics in these regions, where, as believed, the highest potential for the sugar-alcohol industry is concentrated.

10 Central South region was selected due to its relevant share in the sector, as it is responsible for over 90% of ethanol production in Brazil. The states comprising the supply regions are: São Paulo, Goiás, and Mato Grosso do Su 1 l, where only the state of São Paulo is responsible for more than 50% of ethanol total production. Macroregion 1 represents the mesoregions of São José do Rio Preto and Ribeirão Preto. This region represents approximately 24% of all ethanol produced in Brazil. Mesoregions comprising Macroregion 2 are: Araraquara, Piracicaba and Campinas, that together produce approximately 13% of total ethanol. Macroregion is comprised of the following mesoregions: Araçatuba, Bauru, Presidente Prudente, Marília, Assis and Itapetininga, that combined are responsible for approximately 14% of total ethanol production in Brazil. The states of Goiás and Mato Grosso do Sul combined produce approximately 22% of total Brazilian ethanol (UNICA, 2015). Excess supply regions were defined based on the following criterion: if ethanol production exceeds the volume consumed, then this is an excess supply region, and the opposite is characterized as a excess demand region, therefore, although the state of Minas Gerais is the third largest producer, it consumes about 90% of its production, and its flow is not sufficient for being considered as an excess supply region. Northeast and South regions and the state of Rio de Janeiro are responsible for consuming great part of ethanol surplus produced in the Central South region, and, therefore, are considered as destination regions. Regarding the international demand, the following countries were selected: United States, South Korea and the Netherlands, as well as the Rest of the World. The United States is the world's leading ethanol producer and has the largest imports share of this market. South Korea and the Netherlands, according to export data, are the second and third largest importers of Brazilian ethanol, respectively (SECEX, 2014). The following variables comprise the model: production, consumption, domestic and international trading prices, freight of different transport modes, price elasticity of supply/demand. The base-year of the variables is The source of production data is the Brazilian Institute of Geography and Statistics (IBGE). The source of consumption and domestic and international trading prices data is the National Association for Oil, Natural Gas and Biofuels (ANP). Price elasticity of supply/demand were extracted from studies carried out by Beiral (2011), Boff (2009), Luchansky and Monks (2009). 1 Minas Gerais is not considered as excess supply region as it absorbs about 90% of its production.

11 The Scenario 1 is a base scenario where road and road-railroad routes fees are equal to currently charged fees. For Scenario 2 a 15% 2 decrease in railroad transportation freight was proposed, thus changing the transportation dynamics of the routes. Scenario 3 represents a future situation where the use of railroad mode, road-railroad and road-pipeline multimodality are compared, assuming that Logum Project works are already in operation. 3.2 PCM for Brazilian ethanol According to Oliveira (2011), PCM consists of a simultaneous equations system (that could be linear or nonlinear), that are described as inequalities, whose input are the supply and demand functions. The PCM proposed to analyze Brazilian ethanol market is presented next: Contents: i : ethanol supply regions (i=1,2,3,...5) j: ethanol domestic consumption regions (j=1, 2, 3) k: ethanol international demand regions (k=1, 2, 3) r: ethanol transportation routes (r=1, 2,..,18) Variables: : offer price : domestic consumption price : international demand price : quantity offered : domestic consumption : international demand consumption : volume transported Parameters: transportation cost 2 The 15% discount was adopted based on interviews with main players of the ethanol industry.

12 : shadow price in supply region i (for ethanol) : shadow price in consumption region j : shadow price in consumption region k Observing the equations below, we note that the symbol means that at least one of adjacent inequalities should be satisfied as a strict inequality. Equations (4) and (5) are thus described due to a complementarity formality to satisfy Karush-Kuhn-Tucker conditions. In this case, Scenario 2 proposes a discount in railroad freight fee. The tax ik and tax ij fees were already added due to zero profit condition presented in equations (6 and 7), where a new parameter is incorporated. In Bishop et al. (2001) the fee has implications only for flows destined for the international market, preventing zero profit condition. In the current proposal, this fee representing the transportation variation cost, so: (pi+tik).1+taxik pk i,k (6) (pi+tij).1+taxij pj i,j (7) The PCM developed for ethanol transportation in Brazil was processed through General Algebric Modeling System GAMS (BROOKE et al., 1995) computational program. One of the limitations of the model is the fact that it disregards the United States ethanol subsidies; as the proposal intends to analyze, above all, the domestic market flows, American subsidies were not included in the model. Note that Brazilian ethanol could be more competitive if American subsidies were not applied, therefore, future analysis could indicate the effect of subsidies over Brazilian ethanol.

13 4. RESULTS Table 2 shows ethanol trading flows destined for the domestic market per transportation route. Routes R1, R3, R4, R5, and R6 have an optimum transportation cost, and R1, R3, and R5 are direct road routes, whereas R4 and R6 are road-railroad transportation routes. According to the flow, Scenario 1 transportation destined for the domestic market was concentrated in the use of multimodality, where 46% of routes are transported through road mode, whereas 54% use multimodality. Table 2. Scenario 1: Ethanol trading flows destined for the domestic market per transportation route in thousands of m³. Origin** Destination Routes* R1 R3 R4 R5 R6 Macro 1 South Macro 1 Rio de Janeiro Macro 2 Rio de Janeiro Macro 3 South Goiás Northeast Goiás Rio de Janeiro Total *Even routes (R1, R3, and R5) are road routes and pair routes (R4 and R6) are multimodal routes. **Macro1:São José do Rio Preto and Ribeirão Preto Macro2: Araraquara, Piracicaba and Campinas Macro3: Presidente Prudente, Marília, Assis, Itapetininga, Araçatuba, Bauru Source: Research data (2015) Next, Table 3 shows the routes destined for the international market. Table 3. Scenario 1: Ethanol trading flows destined for the international market per transportation route in thousands of m³. Origin** Destination Macro 1 United States Macro 2 The Netherlands Routes* R8 R9 R11 R13 Macro 2 South Korea Macro 2 Rest of the Mato Grosso do Sul United States 1, World Total 2, *Even routes (R9, R11, and R13) are road routes, whereas the pair route (R8) is multimodal route **Macro1:São José do Rio Preto and Ribeirão Preto Macro2: Araraquara, Piracicaba and Campinas Macro3: Presidente Prudente, Marília, Assis, Itapetininga, Araçatuba, Bauru Source: Research data (2015)

14 We note that for transportation destined for the international market, SP 348 highway is an important access corridor for Santos port. In 2013, Bandeirantes Highway was considered the highway in the best state of repair by a survey conducted by the National Transportation Condeferation, and alongside Anchieta Highway and Mario Covas Belt Highway it comprises Brazil's largest road export corridor. The good state of repair of that roadway possibly makes its cost lower and more competitive than using the railroad. Regarding the volumes transported destined for the international market in Scenario 1, we note that only 22% use direct road mode, whereas 78% is more competitive using multimodality. In this scenario, most routes are transported using multimodality (64%), whereas direct road mode is responsible for 46% of Scenario 1 transported volume. Next you can find Scenario 2, where tax ik and tax ij fees were added representing a discount in the order of 15% in road freight amounts so as to analyze how much a discount would affect the choice for multimodality. Table 4 shows ethanol trading flows destined for the domestic market per transportation route. Table 4. Scenario 2: Ethanol trading flows destined for the domestic market per transportation route in thousands of m³. Origin** Destination Routes* R1 R4 R6 Macro 1 South Macro 2 South Macro 2 Rio de Janeiro Macro 3 South Goiás Northeast Goiás Rio de Janeiro Total , , *Even route (R1) is road route and pair routes (R4 and R6) are multimodal routes. **Macro1: São José do Rio Preto and Ribeirão Preto Macro2: Araraquara, Piracicaba and Campinas Macro3: Presidente Prudente, Marília, Assis, Itapetininga, Araçatuba, Bauru Source: Research data (2015) Regarding the volumes transported destined for the international market in Scenario 2, 23% are transported via direct road mode, whereas 77% is more competitive using multimodality. We note that in Scenario 2, regarding domestic market routes, for flows destined for the Northeast region the optimum transportation is still by road (100%) and is originated from the state of Goiás, but for routes destined for the South region and the state of Rio de Janeiro, the optimum result is an enhanced used of multimodal routes. In Table 5 next, Scenario 2 results for the international market will be shown.

15 Table 5. Scenario 2: Ethanol trading flows destined for the international market per transportation route in thousands of m³. Origin** Destination Routes* R8 R10 R12 R14 Macro 1 United States Macro 1 The Netherlands Macro 1 Rest of the World Macro 2 Korea Mato Grosso do Sul United States 1, Total 2, *Even routes are road routes and pair routes (R8, R10, R12, and R14) are multimodal routes. **Macro1: São José do Rio Preto and Ribeirão Preto Macro2: Araraquara, Piracicaba and Campinas Macro3: Presidente Prudente, Marília, Assis, Itapetininga, Araçatuba, Bauru Source: Research data (2015) Regarding routes destined for the international market, for all optimum routes the model has found the best transporting option is multimodality. Therefore, the following are competitive routes: R8, R10, R12, and R14. If we compare with Scenario 1, we observe a disproportion regarding the distribution of transport modes, as in Scenario 2 transportation destined for the external market was 100% concentrated in multimodality. In this scenario, only 13% of routes are transported via direct road, different from the previous one, where 36% used highways as main transportation mode. In Table 6 next, Scenario 3 results will be shown, where four transportation routes were added (R15, R16, R17, and R18) for the international market through pipeline. For road-railroad routes, the railroad freight prices used were equal to those currently charged, likewise Scenario 1. The purpose of this scenario is to examine the effect of implementing pipelines in multimodality. Table 6. Scenario 3: Ethanol trading flows destined for the domestic market per transportation route in thousands of m³. Origin** Destination Routes* R1 R3 R4 R5 R6 Macro 1 South Macro 1 Rio de Janeiro Macro 3 South Goiás Northeast Goiás Rio de Janeiro Total *Even routes (R1, R3, and R5) are road routes and pair routes (R4 and R6) are multimodal routes. **Macro1: São José do Rio Preto and Ribeirão Preto Macro2: Araraquara, Piracicaba and Campinas Macro3: Presidente Prudente, Marília, Assis, Itapetininga, Araçatuba, Bauru Source: Research data (2015)

16 Scenario 3 has shown five competitive routes for flows destined for the domestic market. Of these, three are by highways and two are multimodal, so, according to the volume transported, 50% of Scenario 3 routes destined for the domestic market use road mode, whereas 50% use multimodality. Scenario 3 domestic transportation is similar to Scenario 1 because the 15% discount on railroad freight fee was not applied as in Scenario 2. Therefore, we conclude that lacking these tax ik and tax ij fees, road mode is more competitive for ethanol transportation to the domestic market. In Table 7, Scenario 3 results regarding transportation for the international market are shown. As mentioned previously, 4 routes were added: R15, R16, R17, and R18, destined for the United States, the Netherlands, South Korea and Rest of the World, respectively, using road-duct multimodal option. Table 7. Scenario 3: Ethanol trading flows destined for the international market per transportation route in thousands of m³. Origin** Destination Routes* R8 R15 R16 R17 R18 Macro 1 South Korea Macro 2 United States Macro 2 The Netherlands Macro 2 South Korea Macro 2 Rest of the World Mato Grosso do Sul United States 1, Total 1, *Route R8 is road-railroad multimodal route, whereas R15, R16, R17, and R18 routes are road-pipeline multimodal routes. **Macro1:São José do Rio Preto and Ribeirão Preto Macro2: Araraquara, Piracicaba and Campinas Macro3: Presidente Prudente, Marília, Assis, Itapetininga, Araçatuba, Bauru Source: Research data (2015) Regarding the competitive routes identified in Scenario 3 for the international market, the first remark is that when the three options are on the table: road mode, road-railroad multimodality and road-pipeline multimodality, road mode is not competitive, thus, in Scenario 3 only multimodal routes for the international market are competitive. Scenario 3 result is similar to Scenario 2 result in the sense that competitive routes destined for the foreign market are 100% multimodal. Finally, Scenario 3 points out that, likewise Scenario 2, multimodal routes could be more competitive than road routes; in this scenario 71% of competitive routes are multimodal, whereas only 29% are road routes.

17 5. FINAL REMARKS The progress achieved by agribusiness in the last years are being followed by several sectors of the economy, but the current logistics configuration has been revealing several vulnerabilities regarding transportation and storage of agricultural cargo. Global demand for ethanol is increasing due to a wider search for renewable sources of fuel, hence, logistics should be adjusted so as to make possible to obtain competitive edge that reflects on the overall cost of the product. This research attempted to analyze transportation alternatives for different ethanol routes in the face of current logistics conditions in Brazil, assessing the implications of transportation infrastructure restraints for enhancing ethanol competitiveness in the domestic and international markets. Additionally, we analyzed ethanol transport alternatives so as to indicate which is the most efficient manner of transportation for given routes. A data survey of the ethanol market was carried out to understand the trading dynamics for this product. A review of the transportation methods was also performed so as to present the features and specifics of ground transportation modes. Agricultural cargo transportation is a very costly activity because the products have low added value, so the transportation cost has a large share in the total cost of the product, impacting its competitiveness. Brazil currently faces the risk of a logistics blackout, as previously mentioned, as well as challenges regarding storage and transportation capacity, that end up affecting product competitiveness. When it comes to ethanol, although Brazil is the world's second largest producer, logistics system shortages make the product lose competitiveness regarding major global players. In addition to the risk of logistics blackout, the sugar-alcohol industry, specially the ethanol sector, are going through a crisis in the last years. The drop in production of 2014/2015 harvest is already a reflex of the instabilities suffered by the sector, so the development of public policies is necessary so that the sector is able to recover in upcoming harvests. For Scenario 1, the results point out a higher use of multimodality (64%) when compared with the use of direct road transportation (36%) for ethanol handling, however, note that this is the base scenario, where fee amounts are those currently charged, without discounts. When a 15% discount is applied to railroad freight fees (Scenario 2), multimodality becomes more competitive than the use of direct road mode. Scenario 2 points out that adding tax ik and tax ij only 13% of ethanol routes are transported via road mode and 87% of routs point out multimodality as the most efficient option. Note that in Scenario 2 a

18 major change in the means of transportation occurs in routes destined for exports. In Scenario 1, approximately 78% of routes destined for the international market were transported using multimodality, but when the 15% discount on railroad fee is applied, 100% of routes destined for export are more efficient via multimodality, and transportation for Santos Port via direct road mode is less competitive. In Scenario 3, pipelines are added destined for the foreign market, and multimodal routes are also more competitive than the use of highways. The major difference observed in the three Scenarios between adopting multimodality or using only the road mode can be seen in the transportation destined for Santos Port, where in Scenario 2 100% of routes indicate that multimodality is more competitive for this destination. Regarding the domestic market, when the three scenarios are compared, we identify that 40% of routes are more competitive using direct road mode, whereas 60% are more competitive using multimodality. This indicates that multimodality is more competitive for domestic flows, so new investments in the multimodal infrastructure are needed to increase the use of multimodality in domestic consumption routes. An investment agenda is necessary, not only in transportation infrastructure, but also in the entire logistics chain, given the importance and weight of the logistics factor in the total price of agricultural cargo. New public policies that foster the use of multimodality as a means to obtain competitive edge must be adopted, so as to give access to multimodality to the main players of the industry. The research assumption that multimodality is more competitive is correct, as reducing the cost of railroad transportation and implementing a new pipeline system the transportation flows increase. 6. REFERENCES ALVIM, A. M. (2003). Os impactos dos novos acordos de livre comércio sobre o mercado de arroz no Brasil: um modelo de alocação espacial e temporal. Tese de Doutorado -Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil. ANP AGÊNCIA NACIONAL DO PETRÓLEO, GÁS NATURAL E BIOCOMBUSTÍVEIS. (2012). Anuário Estatístico Accessed on June 23, 2014, on: ANTT AGÊNCIA NACIONAL DE TRANSPORTES TERRESTRES. (2015). Idade média dos veículos Accessed on January 5, 2015, on: BALLOU, R. H. (2004). Gerenciamento da cadeia de suprimentos/logística empresarial. São Paulo: Atlas. BEIRAL, P. R. S. (2011). O mercado brasileiro de etanol: concentração e poder de mercado sob a ótica da nova organização industrial empírica. Dissertação de Mestrado Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo, Piracicaba, SP, Brasil.

19 'BISHOP, P.M.; NICHOLSON, C.F.; PRATT, J.E. (2001). Tariff-Rate Quotas: difficult to model or plain simple. Trade Working Papers, East Asian Bureau of Economic Research. BOFF, H. P., O mercado interno do etanol: Modelo e Estimação do Preço de Equilibrio. (2009) Seminários de pesquisa, 17032, IE/UFRJ, Rio de Janeiro, RJ, Brasil. BRAZIL. (2010). Ministério da Agricultura, Pecuária e Abastecimento. Companhia Nacional de Abastecimento. CONAB. Projeções do Agronegócio: Brasil a Brasília: Mapa/ACS. Accessed on December 12, 2014, on: (2014). Ministério do Desenvolvimento, Indústria e Comércio Exterior. Secretaria de Comércio Exterior - SECEX. Exportação NCM Brasileira. Accessed on May 6, 2014, on: < (2014). Ministério da Agricultura, Pecuária e Abastecimento. Companhia Nacional de Abastecimento. CONAB Séries Históricas de Área Plantada, Produtividade e Produção, Relativas às Safras 1976/77 a 2013/14 de Grãos, 2001 a 2014 de Café, 2005/06 a 2014/15 de Cana-de-Açúcar. Accessed on June 4, 2014, on: BROOKE, A.; KENDRICK, D.; MEERRAUS, A. (1995). GAMS: a user s guide. Release Redwood: The Scientific Press, 289 p. BROWN, C.G. & DRYNAN, R. G. (1986). Plant location analysis using discrete stochastic programming. The Australian Journal of Agricultural Economics, 30(1), CAIXETA-FILHO, J. V.; GAMEIRO, A. H. (2001). Transporte e Logística em Sistemas Agroindustriais. São Paulo, Brasil, Atlas. CARVALHO, L.B.; CAIXETA FILHO, J.V. (2007). Comportamento do mercado de preços de fretes rodoviários de açúcar para exportação no estado de São Paulo. Revista de Economia e Agronegócio. Vol. 5 no. 1, Jan-Mar. CEPEA. (2015). CENTRO DE ESTUDOS AVANÇADOS EM ECONOMIA APLICADA. Pib Agro USP/CNA. Accessed on January 2, 2015, on: <http://www.cepea.esalq.usp.br/pib/>. CONFEDERAÇÃO DA AGRICULTURA E PECUÁRIA DO BRASIL CNA. (2014). Balanço 2013/Perspectivas Accessed on January 3, 2015, on: FREITAS, L. C.; KANEKO, S. (2011). Ethanol Demand Under the Flex-Fuel Technology regime in Brazil. Energy Economics. n. 33, p IBGE. (2013). Instituto Brasileiro de Geografia e Estatística. Definições. Accessed on June 13, 2013, on: JANOTTI, P. R., RODRIGUES, I. C., RODRIGUES, A. M., REBELATO, M. G. (2012). A logística do açúcar e do etanol entre usinas paulistas e o Porto de Santos: um estudo comparativo entre agentes comerciais. Revista de Administração da UNIMEP, p LEMOS, P.; MESQUITA, F.; DAL-POZ, M. E.; SOUZA, L. G. A. (2015). Panorama e Desempenho Recente do Setor Sucroenergético: Condições para um Novo Ciclo? In: SALLES FILHO, S. (Org.). Futuros do Bioetanol: O Brasil na Liderança. Rio de Janeiro: Elsevier. p LÍCIO, A. (1995). Os eixos estruturadores e dos corredores de transportes. Revista de Política Agrícola, Brasília, v.9, n.4, p.3-4. LUCHANSKY, M. S.; MONKS, J. (2009). Supply and Demand Elasticities for the United States Ethanol Market. Energy Economics, v. 31, n. 3, p MATTEI, F. E. E. (2007). Modeling Linkages between Climate Policy and Land Use: An overview. Working Papers WP24. Italy.

20 MILANEZ, A. Y.; NYKO, D.; GARCIA, J. L. F.; XAVIER, C. E. O. (2010). Logística para o etanol: situação atual e desafios futuros. BNDES Setorial, Rio de Janeiro: BNDES, n. 31. MORAES, M. A. F. D.; ZAMBIANCO, W. M.; CINTRA, P. R. (2013). Consolidação do setor sucroalcooleiro: impactos na estrutura de mercado e participação de capital estrangeiro. In: DÖRR, A. C.; GUSE, J. C.; FREITAS, L. A. R. de. Agronegócios: Desafios e Oportunidades da Nova Economia. Curitiba: Appris, p NASTARI, P. A. (2010). A Internacionalização ganhou força em Revista Opiniões. Jan-Mar. Accessed on February 13, 2014, on: <http://www.revistaopinioes.com.br>. ODEBRECHT. (2011). Novas soluções para o transporte de etanol. Recuperado em 13 setembro, 2013, de:< OLIVEIRA, A. L. R. (2011). O sistema logístico e os impactos da segregação dos grãos diferenciados: desafios para o agronegócio brasileiro. Tese de Doutorado, Universidade Estadual de Campinas, Campinas, SP, Brasil. (2014). A logística no agronegócio: para além do apagão logístico. In: BUAINAIN, A. M.; ALVES, E.; SILVEIRA, J. M. F. J.; NAVARRO, Z. (Org.). O mundo rural no Brasil do século 21: a formação de um novo padrão agrário e agrícola. 1ed. Brasília: Embrapa, 2014, v. 1, Parte 2, cap. 6, p (2015). Logística de Etanol no Brasil. In: SALLES FILHO, Sergio (Org.). Futuros do Bioetanol: O Brasil na Liderança. Rio de Janeiro: Elsevier, p PETEAN, G. H.; NORILLER, R. M.; SANTOS, L. C.; CHAEBO, G.; SANCHES, F. T. (2011). Etanol Hidratado no estado de São Paulo: previsão de preços a partir do método de Holt-Winters. SIMPEP. RENEWABLE FUELS ASSOCIATION-RFA. (2014). Monthly U.S. Fuel Ethanol Production/Demand. Accessed on January 2, 2014, on: SAMUELSON, P.A. (1952). Spatial Price Equilibrium and Linear Program. American Economic Review, v.42, p SATOLO, L. F.; CAIXETA-FILHO, J. V. (2010). Impacto de novas usinas e destilarias na distribuição de etanol hidratado na região Centro-Oeste: uma aplicação do modelo de equilíbrio espacial de preços. In: 48º Congresso da Sociedade Brasileira de Economia, Administração e Sociologia Rural (SOBER), Campo Grande. SOUZA FILHO, H. (2014). Geração e distribuição de excedente em cadeias agroindustriais: implicações para a política agrícola. In: BUAINAIN, A. M.; ALVES, E.; SILVEIRA, J. M. F. J.; NAVARRO, Z. (Org.). O mundo rural no Brasil do século 21: a formação de um novo padrão agrário e agrícola. 1ed. Brasília: Embrapa. Parte 2, cap. 5, p TAKAYAMA, T.; JUDGE, G.G. (1971). Spatial and Temporal Price and Allocation Models. Amsterdam: North Holland Publishing Co. UNICA UNIÃO DA INDÚSTRIA DE CANA-DE-AÇÚCAR. (2014). Histórico de produção e moagem Accessed on January 23, 2015, on: UNICA UNIÃO DA INDÚSTRIA DE CANA-DE-AÇÚCAR. (2015). Exportação anual de etanol por local de embarque (mil litros). Recuperado em 4 janeiro, 2015, de:

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