First-generation biofuels are relatively cheaper to produce than advanced biofuels (second-generation biofuels and beyond), but they still cost more than equivalent fossil fuels, and are also problematic from a sustainability perspective, as discussed in chapter “Environmental Issues in the Liquid Biofuels Industry”. Although advanced biofuels could address the latter issue, commercial production is yet to commence because of the higher start-up and operational costs associated with these production processes. This section will provide a comparison of the produc­tion costs of biofuels vis-a-vis fossil fuels.

The feedstock for first-generation biofuels, i. e. edible crops, accounts for nearly 55-70 % of the total production cost (IEA 2008). As a result, first-generation bio­fuels, in general, are unable to compete effectively with fossil fuels (UN 2008), particularly when government subsidies and other incentives are removed from the equation. Only sugarcane-based bioethanol produced in Brazil, which costs USD 0.25-0.35 per litre of gasoline equivalent[2] (lge), is competitive with gasoline at USD 0.34-0.42 per litre (i. e. USD 40-50 per barrel) (IEA 2007).[3] By way of con­trast, the cost of corn-based ethanol in the United States and sugar beet-based etha­nol in the EU vary between USD 0.60-0.80/lge (IEA 2007)—much higher than the then price of gasoline. Likewise, the cost of producing biodiesel from animal fat, vegetable oil, tallow fat and palm oil varies between USD 0.40-0.50, 0.60-0.80, 0.60-0.85 and 0.82-0.86/lde,[4] respectively (IEA 2007; RFA 2007), all higher than production costs of petroleum-based diesel. For some feedstocks, such as cooking oil, commercializable by-products could lower its effective cost (Demirbas 2009).

Second-generation biofuels are produced from the cellulosic content of inedible plants. While the cost of such feedstock is comparatively lower, it still represents around 36 % of the net production cost of the biofuel (USDA 2010). Processing — related expenses, including chemicals such as enzymes, are substantial. Although technological advances have significantly lowered the cost of cellulosic ethanol (Wyman 2008), the processing technique employed continues to be most signifi­cant determinant of the fuel’s net production costs. The IEA (2007) estimated the cost of second-generation bioethanol and biodiesel at approximately USD 1.00/lge (assuming feedstock price of USD 3.6/GJ) and USD 0.90/lde (assuming feedstock price of USD 3.6/GJ), with a potential reduction to USD 0.50/lge and 0.70-0.80, respectively, by 2017. Furthermore, the cost of setting up a second-generation biofuel refinery is potentially up to ten times that of establishing an equivalent first-generation production unit (Eisentraut 2010). While this additional outlay partially negates the advantage of using lower-cost feedstocks, larger plants may be able to capture economies of scale and achieve some cost savings (UN 2008). Nevertheless, high capital investments are a major concern, particularly for those plants being proposed in less developed countries (Eisentraut 2010).

Eisentraut (2010) theoretically deduced the cost of second-generation biofuels pro­duced in different countries by assuming capital costs to be 50 % of the total produc­tion costs, feedstock 35 %, operation and maintenance, energy supply for the plant, and other expenses between 1 and 4 % each. Table 3 summarizes these estimates.

Eisentraut (2010) also compared the probable production cost of second-generation biofuels if an oil price of USD 120/bbl is assumed. He concluded that bioethanol and biodiesel would cost USD 1.09 and 1.07, respectively, in the short term. In the long term, prices are projected to fall to USD 0.72 and 0.73, respectively, which would be lower than gasoline and rapeseed biodiesel, and also competitive with first-generation bioethanol. The above figures should be considered in tandem with the then price of fossil fuels. This, however, does not greatly change the cost efficiency of biofuels as the cost of biofuels continues to increase with the rise in price of feedstock and other inputs (OECD 2011). In addition, these costs are purely economic and do not include the various environmental costs typically included in life-cycle analyses (LCAs), as explored in chapter “A Comparison Between Ethanol and Biodiesel Production: The Brazilian and European Experiences”. Other costs associated with production, and that of first-generation biofuels in particular, relate to storage, especially given the seasonal nature of biofuel production (Moreira and Goldemberg 1999; Karp and Richter 2011).

The National Oil Agency carries out, since 2005, biodiesel auctions. At these auctions, the refineries buy biodiesel to mix it up with the oil-based diesel (ANP 2012). According to the source, the initial objective of such auctions was to gener­ate a market and hence stimulate the biodiesel production in a big enough quantity for the refineries and distributors to compose the mixture, according to the law. Based on the results of these auctions, we obtained the biodiesel production in cubic meters, per state, as shown on Table 1.

We can see on Table 1 that the beginning of the biodiesel production took place in 2005 and that only four states were producing (Minas Gerais, Para, Parana, and Piauf), showing a high concentration, despite the small quantity being pro­duced, when compared to 2011 and 2012. In 2012, the biodiesel was produced in 12 of the 25 Brazilian federal units, where the higher production of the states Rio Grande do Sul, Goias, Mato Grosso, and Sao Paulo, stands out, representing 78.50 % of the national production, showing that this market is highly concen­trated in these states.

Table 2 shows that the ethanol production has grown 45.74 % between 2005 and 2012 (from 15.924000 to 23,209000 m3 in 2012). This growth can be partially explained by the increase of demand where, the increase in the internal market has been due to the more favorable price of this fuel, when compared to gas, which forces the consumption of alcohol in biofuel cars (gas and ethanol), which have had more and more representativeness in the national freight of small urban vehi­cles, since, as shown on Fig. 4, in 2005, 7 % of the cars (1.4 million) were using biofuel, and are now 57 % of the national freight. Besides, the mixture level of ethanol in gas in the last decade has varied from 20 to 25 % (according to the gov­ernment decision), thus implying more pressure on ethanol’s demand.

Table 3 shows us that the production of ethanol has increased the concentration in the four most important states (Goias, Mato Grosso do Sul, Minas Gerais, and Sao Paulo) that represented 81 % of the national production of ethanol in 2012. Also, Sao Paulo produced 51 % of the national volume in 2012 (11,830 thousand m3); however, this high concentration has decreased, since in 2005, two-thirds of the national production was centralized in this state.

Table 3 shows that both indexes (HHI and Cr(4)) point to a high concentration of the biodiesel production in Goias, Mato Grosso, Rio Grande do Sul, and Sao Paulo, these four states accounted for 87.22 % of the total biodiesel production in

2008, remaining at a level close to 80 % in the following years. Notably, this result is influenced by the main raw material used: soybeans—Goias, Mato Grosso, and Rio Grande do Sul are the main producers. Sao Paulo, on the other hand, stands out due to the usage of beef fat and soybeans. In order to verify this high concen­tration is present, we initially identified the market participation of the 16 biggest companies producing biodiesel, as shown on Table 4.

We can see on Table 4 that for 2005, none of these companies produced biodiesel, whereas only in 2006 did Granol start its activities. In 2012, the 16 analyzed companies kept 80.19 % of market participation, thus indicating that this industry has characteristics of a Cr(16), because these companies keep at least 70 % of the Brazilian biodiesel production since 2007. Do also note that the majority of these companies are located in the south and central west, cor­roborating Picture 2. In order to confirm the installed capacity concentration, we calculated the HHI for the daily installed capacity per Brazilian region, as per Table 5.

Considering the increase in demand for ethanol, as well as the strategies of mergers and acquisitions among suppliers and distribution channels recently observed in Brazil, much has been discussed about the power of the market that may be taken by those agents who are involved in the product chain. Discussions on a possible cause for the increase of the product prices have risen interest on the existence of the market power by the ethanol producers, and/or by fuel distribution channels (Beiral 2011).

The analysis by companies (distilleries and/or sugar and ethanol plants) reveals a scattered environment, granted the great number of registered units. There are now 432 operational plants in Brazil, and 83 of these plants are located in the north-northeastern region and 349 are in the central-south region (MA 2012). Besides the great number of plants, this industry shows traits of a decentralized market, since in 2012 the five largest economic groups responded for 20 % of all the grinded cane in the country (UNICA 2010).

Despite the traits indicating a low concentration level in the ethanol industry in Brazil, it is impossible to calculate it, since the Instrugao Normativa No 52, of November 12, 2009, on the Diario Oficial da Uniao of November 13, 2009, does not allow the communication of all the necessary information, since according to the Article No. 5 “the information received from the legal entities will be classi­fied, and can only be communicated in an aggregated manner per state, region, or national total” (MA 2009).

Table 4 Market participation of the 16 largest biodiesel companies Company City Region 2005 (%) 2006 (%) 2007 (%) 2008 (%) 2009 (%) 2010 (%) 2011(%) 2012 (%) Adm Rondonopolis Central west 0.00 0.00 0.37 15.54 10.67 10.34 5.78 5.61 Biocamp Campo Verde Central west 0.00 0.00 0.00 1.07 1.73 2.08 2.05 2.49 Bsbios Passo Fundo South 0.00 0.00 3.58 7.91 7.02 5.63 4.82 4.91 Bsbios Marialva South 0.00 0.00 0.00 0.00 0.00 1.97 3.54 3.98 Camera Ijuf South 0.00 0.00 0.00 0.00 0.00 0.25 4.11 6.26 Caramuru Sao Simao Central west 0.00 0.00 11.43 9.80 7.62 6.70 5.46 5.54 Caramuru Ipameri Central west 0.00 0.00 0.00 0.00 0.00 1.96 3.78 4.59 Fiagril Fucas Rio Verde Central west 0.00 0.00 0.00 6.25 5.72 4.76 5.40 4.62 Granol Anapolis Central west 0.00 14.75 18.19 11.95 8.39 7.68 6.76 8.59 Grand Cachoeira do Sul South 0.00 0.00 0.00 7.71 7.54 6.92 7.91 4.72 JBS Colide Central west 0.00 0.00 0.31 6.26 5.43 5.22 3.83 2.44 Oleoplan Veranopolis South 0.00 0.00 2.08 8.66 11.13 8.54 9.15 8.70 Olfar Erechim South 0.00 0.00 0.00 0.00 0.00 2.28 4.59 5.05 Petrobras Candeias Northeast 0.00 0.00 0.00 0.87 2.54 2.86 4.19 5.75 Petrobras Montes Claro Southeast 0.00 0.00 0.00 0.00 2.50 3.06 2.80 2.95 V-Biodiesel Iraquara Northeast 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.98 Total 0.00 14.75 35.97 76.01 70.29 70.24 74.19 80.19 Source ANP (2013a)

The perspectives of the Brazilian and American governments are not the same, since according to the Section 1501 of the Energy Policy Act of 2005, the Federal Trade Commission must analyze the market concentration of the production of etha­nol, using the HHI to determine whether or not there is enough competition among the participants of this industry so as to avoid fixing prices and other anticompetition behaviors. According the US Federal Trade Commission (2012), the American etha­nol industry is not deconcentrated (HHI equals 244 in 2010, and 284 in 2011), thus suggesting that an attempt to exert market power by any agent is unlikely.

On the other hand, part of the ethanol marketing in Brazil is made via market­ing groups, the structure of the ethanol market is much more concentrated (Beiral 2011). Thus, point to a concentration of the ethanol market as a trend. For exam­ple, the purchase of the Esso by Cosan (the largest ethanol producer in Brazil); the purchase of the Ipiranga network by Ultra (the second largest distribution channel after the purchase of Texaco, only after BR Distribuidora), along with Petrobras and Braskem (Beiral 2011).

Considering the possible increase of concentration among the ethanol distributors, we sought to evaluate the market participation of the 18 largest distribution firms for ethanol in the country, from 2005 to 2012, as shown on Table 5. Table 5 shows that in 2012, 18 firms kept 80.57 % of the ethanol distribution market. Also, note that

only three companies (BR Distribuidora, Shell, and Ipiranga) held in 2012 55.66 % of this market, showing a high market concentration, increasing since 2005, since these companies held 35.32 % market share (a 57.58 % increase for this period).

On Table 6, we can see the higher installed capacity in central west region, with 42 % of all authorized capacity in Brazil, having 31 of those 64 companies authorized to produce biodiesel. When analyzing the usage of the authorized capacity of plants installed in each one of those five regions in Brazil, and considering a 365 day year, we can see that the south region has 62 % of usage, and that if we consider 264 work­ing days in a year, the south region holds 62 % of usage and that if we consider 264 working days in a year (22 days in a month and 12 months in a year), the south region points to the limit of its capacity, with 85 % usage of its capacity in 2011. On the other hand, the northeast region only has 32 % usage of its capacity, whereas the total num­ber of companies has used 63 % of its authorized capacity for producing biodiesel.

Table 7 shows that the largest capacity installed for cane grinding and sugar and ethanol production is in the southeast, with 89, 65, and 90 % of all the Brazilian productive capacity, respectively. By analyzing the use of the average installed capacity of plants, for each of the five Brazilian regions, we can see that the main productive constraint is grinding, where the central west, northeast, and southeast regions show an over 70 % usage. Note that the usage of the installed capacity of grinding in the southeastern region is 75 %, a concerning fact since two-thirds of the installed national capacity is in this region.

On Table 8, we can see that the industrial concentration level has significantly decreased since the National Biodiesel Production Program was implemented, where in the first years of this program (2005-2006), the market showed to be highly concentrated, significantly decreasing the companies power in the market, since in 2012, the four main companies (Granol in Anapolis; Oleoplan in Veranopolis; Petrobras in Candeias and Camera in Ijuf) represented around 30 % of the volume produced in the last three years (2010, 2011, and 2012). In order to verify the impact of this low industrial concentration, we analyzed the weighted average cost of the 16 main companies and compared it to the other companies in the same sector.

As it is commented, the negotiation process for biodiesel is performed accord­ing to auctions. In order to verify whether or not this low industrial concentration

Table 7 Daily installed capacity, usage of installed capacity per Brazilian region of Brazilian cane grinding, sugar and ethanol industry Daily installed capacity % in Brazil Annual plant usage (Considering 365 days) Region Cane grinding (thousand of tons) Sugar (thousand of tons) Ethanol (thousand of tons) Cane grinding Sugar Ethanol Cane grinding (%) Sugar (%) Ethanol (%) Central west 356.78 26.83 44,070,00 15 11 18 72 60 62 Northeast 205.50 40.90 22,511,00 9 16 9 79 49 46 North 26.84 1.18 6,559,00 1 0 3 44 38 28 Southeast 1,543.64 165.43 152,490,00 66 65 63 75 52 52 South 189.42 20.00 17,760,00 8 8 7 63 38 39 Source Conab (2013)

would interfere in the pricing at these auctions, we calculated the average cost per liter of the 16 main biodiesel producing companies in Brazil. The choice of these companies was due to the fact that they represent around 80 % of the national production. As a result, we observed that in 2011 (Auctions, 22, 23, and 24) these companies used a lower price than the other companies; however, in 2012, (Auctions, 25, 26, and 27) the situation was inverse: in two out the three auctions, these companies used a price lower than the others.

In order to verify whether or not the weighted average costs of these two cat­egories are statistically significant, we calculated the average difference t test (Table 9), where we accepted the null hypothesis of equal averages, thus indicating that such companies, despite the fluctuations, do not price in a differentiated man­ner in the long term. This result can be explained by the hypothesis that companies would not have significant gains, considering the sector’s low concentration that makes a significant price reduction impossible at auctions, thus indicating some homogeneity of prices practiced in the biodiesel industry in Brazil.

On the other hand, it is not possible to calculate the concentration level of the ethanol production in Brazil, considering the Instrugao Normativa Number 52 of the Ministry of Agriculture, prohibiting the communication of ethanol production per productive unit, only allowing its communication in an aggregated manner, per state, region, or national total. However, there is another type of strength in this system: the distribution channels. Thus, we sought to evaluate the evolution of industrial concentration of the ethanol distribution in Brazil, in the last 8 years, where we calculated the HHI and the Cr(4), as per Table 10.

Table 10 shows that the industrial concentration level has grown significantly, according to Bain and Qualls (1968) and Usdoj (1997), pointing to a situation where this market moved from a weak-concentration oligopoly, to a moderate concentration, especially after 2009. In order to verify the impact of this increase of industrial concentration on this industry’s profitability, we simulated the

contribution margin for the ethanol distribution channels, as suggested by Beiral (2011). Results are shown on Fig. 5.

Figure 5 shows that in 2005 and 2006, the ethanol distribution channels showed, for several months, a negative contribution margin, and it became positive as of January 2007. Note that as of now, the concentration level of the distribution industry has grown, showing a positive correlation among variables. In order to confirm this supposition, we calculated the Pearson’s product-moment correlation coefficient between these two variables, as shown on Table 11.

As it is shown on Table 11, the Pearson’s product-moment correlation coefficient between the distributors contribution margin, and the HHI, for this industry, was 0.433 (sig equals 0.320) pointing to a positive correlation, although it is relatively weak, between the variables, i. e., as one of the variables increases (industrial concentration level), the other one increases too (distribu­tors contribution margin), noting that this increase of concentration has made it easier for pricing, thus implying a profitability increase for this industry, in det­riment of society.

The environmental impacts of biofuel crops vary considerably. Among the first — generation feedstocks (e. g. sugar cane, sugar beet, maize, cassava, wheat, oil palm, rapeseed and soya bean), some absorb more CO2 than they release. But the wider environmental costs may still be greater than the benefits. For example, rapeseed offers relatively little benefit in terms of CO2 emissions and energy dependency when its impact on land and soil is taken into account (Russi 2008). Doubts have also been raised about staple food crops. Maize, in particular, has been regarded as not producing a worthwhile amount of energy when all the inputs are taken into con­sideration (IEA 2007). That said, it is one of the more efficient (others are wheat, sugar cane and sugar beet) biofuel crops in terms of reducing in CO2 emissions. On the contrary, the production of soya bean-based biodiesel releases substantial CO2, but has been pushed in the USA in recent years when other forms of oil-rich biomass are regarded as more environment friendly for biodiesel production (Pahl 2005).

Second-generation biofuel crops such as switchgrass, alfalfa, reed canary grass, Napier grass and Bermuda grass, which are mostly perennial, have fewer environmental impacts than first-generation crops. This is because the lower fertilizer input and less-intensive farming practices that these crops require help with respect to achieving greater reductions in GHG emissions (Karp and Richter 2011). In comparison with annual crops, perennial crops can have a positive effect on environmental quality and biodiversity (Sanderson and Adler 2008). In addition, as new technologies and processes for biomass production continue to mature and lead to the commercialization of second-generation biofuels, these biocrops are likely to revolutionize the biofuel industry (Ragauskas et al. 2006). Nevertheless, the environmental costs of biofuel feedstock are mostly viewed by biofuel proponents as either insignificant because of the limited economic and ecological value of existing vegetation and land uses, or worth bearing on account of the expected future benefits (MAPA 2006).

In Europe, most of the biofuel used in transportation is essentially sourced from biodiesel, which accounts for 78.2 % of the total energy content (10.9 mil­lion tons in 2011), as opposed to 21 % for bioethanol (2.9 million tons in 2011) (EurObserv’ER 2012).

Compared to USA and Brazil, and also to the European biodiesel sector, the EU fuel alcohol sector is rather small. Nowadays, the monthly production in USA is higher than the EU production per year. In 2008, a record in terms of imports in EU was registered. Total imports of bioethanol (fuel and non-fuel) are estimated to have reached 1.9 billion liters (increasing by 400 million compared to 2007), most of which (between 1.4 and 1.5 billion liters) came from Brazil (ePURE) (Shikida 2002; Ferreira Filho and Horridge 2009).

The EU is the world major player in biodiesel production with a share of 57 % of total world production in 2009. In the same year, biodiesel represented about 73 % of total biofuels produced in Europe (Biofuels-platform 2012).The European 2 Indirect land-use change (ILUC) can occur when land currently cropped for non-energy pro­duction is diverted for biofuel feedstock cultivation. The diverted crops must then be compen­sated for by converting other natural land, usually native systems (Ravindranath et al. 2009). Direct land-use change (dLUC) occurs when additional cropland is made available through the conversion of native ecosystems such as peatlands, forests, and grasslands, as well as by return­ing fallow or abandoned croplands into production. Particularly, when virgin land, such as rain­forest or peatland, is converted to agricultural land, the initial induced carbon losses can only be compensated after many decades of biofuels production (Ravindranath et al. 2009).

biodiesel industry consolidates its position at an international level despite a lower increase in its growth rate of production in 2010 when compared to previous years. For example, with a 9.5 million tons of biodiesel produced in 2010, EU bio­diesel production registered an increase of 5.5 % on the basis of the previous year. However, that stands below the increase in production of 17 % registered in 2009 and in the previous years (35 % in 2008). In 2011, the production decreased by 10 % when compared to 2010 (Fig. 5).

Currently, the production capacity of European biodiesel has reached approximately 22 million tons. The number of existing biodiesel facilities in July 2011 was 254 with a slight increase compared to 2009 due to the start of a few new production units (EBB 2011). This strong industrial basis is the result of considerable investments in biodiesel production planned before 2007. These investments are in reliance to the ambitious objectives for biofuels consumption given by EU authorities (EBB 2010). In 2011, Germany and France remained by far the leading biodiesel producing nations, while Spain confirmed its position of the third European biodiesel producer, ahead of Italy.

Within the EU, the first four largest biodiesel-producing member states that account for two-thirds of total production are Germany (33 % of total European pro­duction), followed by France (18 %), Spain (7 %), and Italy (5.6 %) (EBB 2013). Table 6 shows the biodiesel production and consumption of the countries of EU.

According to the European Biodiesel Board, in the first two-quarters of 2011, for the first time, the entire European production slightly decreased. Increased imports from third countries such as Argentina, Indonesia, and North America are mostly likely to have contributed to lessen European domestic production.

According to the EurObserv’ER (2012), biofuels consumption in transport con­tinued to increase in the UE at a slower pace though. It should stabilize at around 13.9 Mtoe in 2011 compared to 13.6 Mtoe of consumption in 2010. Thus, growth was only 2.7 % between 2010 and 2011, down from 13.9 % between 2009 and 2010, 24.6 % between 2008 and 2009, and 41.7 % between 2007 and 2008.

The biofuel market is very geographically concentrated, with a limited number of member states (Germany, France, Spain, Italy, UK, and Poland) representing over 78 % of EU-27 consumption.

The EU is the world’s largest biodiesel producer, consumer, and importer. The shift from tax incentives to mandates across Europe has been one of the key rea­sons for the growing amount of biodiesel imports. This shift can be attributed to a previous loss in fuel tax revenues for member states, causing a reduction of tax exemptions and compensation via mandates. Without tax exemptions, biodiesel was not price competitive against fossil diesel, even though the price of fossil

diesel increased. Under a mandate, fuel suppliers tend to opt for blending low-cost biofuels causing the increase of biodiesel imports (Ecofys 2011).

Imported biofuels in the EU come from a range of countries, with considerable changes in the list of countries from which the EU imported biofuels year by year, thus reflecting the impact that EU tariff preferences can have on such imports. This is demonstrated in Table 7 that depicts changes in EU biodiesel imports from 2008 to 2010 (European Commission, SEC 130 2011).

Looking at the trade volumes, in 2010, Argentina and Indonesia were the main exporters. The imports from USA and Canada reduced considerably regarding the previous years due to the application of the EU anti-dumping and countervailing duties for biodiesel.

The manner in which the economic stakeholders conduct their activities has increasingly distanced from the neoclassical conception, where the price system coordinates the markets. The new institutional economics (NIE) has for decades strived to demonstrate how the functioning of economics is influenced not only by economic and social institutions, but also by how the economic actors adapt to form governances or coordinate negotiations (Zylbersztajn 2005). In other words, formal and informal institutions strive to understand the processes in order to obtain efficiency in the business markets, including individual actions to coordi­nate business affairs in each market.

In the article “The nature of the firm,” Coase (1937), a researcher at NIE, pre­sents a firm as another area of resource allocation. Several works of Coase evi­dence the constant concern with the negotiations faced by a firm, pointing to specific interest on transaction costs (TCs) as a real barrier to market efficiency. Thus, if the company is a complex transaction unit, it is because the market and the overall business integration are not the only institutions that define economic efficiency, thus having to pay attention to the formal and informal agreements.

The ideas of Coase (1937) represented a step forward for economic studies, since until then the firm was known as a production function where inputs were transformed into end products. In the neoclassical view, the firm was an optimiz­ing entity, totally indifferent to its internal structure and its determining environ­ment, with the exception of prices.

According to the author, setting up the firm, represented by a set of agreements governing internal transactions, takes place because of the costs the actors to use in the price mechanism to organize production, given that this cost is related to discovering the relevance of the prices.

Thus, selecting the coordination mechanism to be used (firm or market) depends on the costs incurred, that is, the costs of discovering the prices prevailing in the mar­ket (information collection), the negotiation costs, setting up a contract, and the costs necessary to carry out inspections to ensure that the terms of the contract are met. The author designated these costs as TCs, thus explaining the existence of the firms.

The transaction concept is defined by Williamson (1993) as the transformation of an asset transferred across technologically separable interfaces. Zylbersztajn (1995) considers transactions as exchanges of property rights associated with goods or services.

“When people realize that what they want is more valuable than what they have (…)” (Barzel 1982, p. 27), transactions take place at any point of time and in any place.

However, as these transactions can take on a variety of forms, a completely sys­tematized framework is necessary to meet the objectives of such transactions. It is within this context that the institutions’ significance expands in order to enable coordinating the economic transactions, showing the limits of traditional analysis models and driving forward studies on transaction cost economics (TCE), the best known topic of NIE. Transactions, according to these approaches, will always be analyzed in a dual mode, which is the two agents under negotiation, the one that buys and the one that sells.

The theoretical framework of NIES deepens on the general concept of the firm, now as a set of agreements directing the internal transactions, rendering their anal­ysis more complex since it considers that the economic agents interact not only to reduce the production costs, as proclaimed by the orthodox economy, but also the costs related to the transactions.

According to Williamson (1975), TC can be defined as costs related to the mechanisms involved in the economic transaction, which are the negotiation costs, to obtain information, monitor performance along the chain, and ensure compli­ance with the agreements and also with recurring agreements. Thus, by includ­ing TC in the microeconomics analysis of the firm and of the markets, a series of costly procedures are considered before and after the negotiation, rendering a more complex nature to the business in terms of economic decisions. While the orthodox economic theory focuses on the process of determining the optimal allo­cation of resources by businessmen allegedly endowed with full rationality at deci­sion times, the objective of NIE is to identify the entrepreneurs’ best coordination method for their economic transactions in environments of uncertainty and, there­fore, the limiting forces for decision making (limited rationality). Thus, TCs are different from production costs as they depict how relationships are processed and not the technology used in a specific productive process. By breaking away from neoclassical economics, the individual preconized by NIE is not the same individ­ual as that of mainstream economy. “Homo economicus,” typified by a rational person with full information to maximize decision making for neoclassicism, is now defined by limited rationality and opportunism in an environment character­ized by uncertainty.

The concept of limited rationality was introduced as an important element of NIE by Williamson (1975) and preconized by Simon (1978). Richter (2001) and North (1990) refer to the individual’s cognitive limitations, who is not able to always be a maximizer despite wanting to be. Not much more can be added to this aspect since it is an unchallenged human condition. The mental shortcuts routinely used by economic agents for their market decisions are the first arguments for the problem of not achieving maximizing profits.

The theoretical framework of NIE discusses the role of institutions in two dif­ferent analytical levels: macroinstitutional and microinstitutional.

The part of NIE concerned with the relationship between institutions and eco­nomic development was the macroinstitutional type. From a macroanalytical point of view, the relationship of the institutional environment studied is composed of the economic, social, and political interactions and the individuals in a society. Thus, the importance of formal and informal rules and property rights is addressed by its contribution to the efficiency of the system.

As for the microanalytic type, focused on in this chapter, it addresses the under­standing of the rules governing specific transactions. Accordingly, TCE seeks to understand what factors drive up TCs and what mechanisms could be used to reduce them.

TCE enables to intensify the firm, now seen as a set of internal transactions governed by a set of contracts. This renders their analysis more complex, because the agents’ relationship is not only to reduce operating costs—as proclaimed by classical economics—but also to reduce TC—as suggested by NIE (Bonfim 2011).

TCE assumes that the question of economic organization is first of all a prob­lem of governance. Hence, it seeks to explain the different organizational forms that exist in the market and their contractual arrangements, highlighting the insti­tutional environment and its interaction with the organizations.

Williamson (1985), by proposing the firm as a governance structure of transac­tions, can determine if it will be a specific contract from a perfect market rela­tionship, if it will prefer a mixed form or if it will define the need for vertical integration, from the principles that minimize production costs (covered by neo­classical economics), added to the TC. For analytical purposes, the author pro­poses three basic governance forms, namely: [12]

Williamson (1991a, b) clarifies that hierarchy, market, and the hybrid form resulting from the combination of the former two are generic forms of economic organization. They are differentiated by their coordination and control mecha­nisms and their ability to respond to changes in the environment. Thus, the firm’s choice for governance structure—hierarchy, market, or intermediate form—will depend on the nature of the transactions. Williamson (1985) identifies three key attributes in transactions, determining the variation of TCs, namely frequency, uncertainty, and asset specificity.

Brazil has diverse sources of energy. Among the countries that produce fuel-based renewable energy, Brazil stands out in its ethanol production from sugarcane. This feedstock has shown the highest levels of technical and economic efficiency com­pared to other cultures used for ethanol production.

The Brazilian ethanol program began in 1975 with the National Ethanol Program, which was called “ProAlcool.” This program was created to encourage ethanol production to replace gasoline as the standard road transportation fuel. The program aimed to reduce oil imports, which compromised the trade balance, and reduce the country’s energy dependence (Moreira and Goldemberg 1999; Hira and Oliveira 2009).

In addition to these main goals, this program was intended to promote other advantageous consequences, such as: (1) a reduction in the economic disparities between Brazil’s highly industrialized southeast and less-industrialized northeast regions; (2) an increase in the national income from exploring the maximum potential of resources (particularly land and labor); and (3) stimulation of the national sector for capital goods, which would increase the demand for agricul­tural machinery and distillation equipment (Hira and Oliveira 2009).

The Brazilian Ethanol Program was a great success until 1990. This success was a result of several national and international factors that supported the devel­opment and implementation of ethanol fuel. In the domestic market, the Brazilian government subsidized agricultural production, financed up to 80 % of the con­struction of new refineries, reduced taxes on ethanol-fueled vehicles such as the excise tax (IPI), and subsidized ethanol at gas stations (setting the price of alcohol as 64.5 % of the gasoline price). In foreign markets, the rise in oil prices and the decline in sugar exports contributed to the increase in ethanol production.

After setting the structure from 1989 to 1990, ProAlcool suffered a major cri­sis. The rise of the international price of sugarcane increased Brazil’s exports of it and thereby compromised the supply of this feedstock for ethanol production, which exhibited a significant decrease. Thus, the Brazilian government was forced to import ethanol to meet the domestic demand created in the previous period (Puerto Rico et al. 2010).

Due to market fluctuations, the 1990s were marked by the deregulation of the sugarcane industry. The main decisions in this period included gradual cuts of subventions that were related to the price guarantees on exports, the elimination of production and trade controls by the government, and the official shutdown of ProAlcool (Hira and Oliveira 2009; Puerto Rico et al. 2010).

During this period, farmers and industries started being reorganized and new government agencies were created for the purpose of chain organization. After the crisis of 1990 and the reorganization of the sugarcane sector, a new boost for the sugar and ethanol industry came with the introduction of “flex-fuel” vehicles in March 2003, which led to the inclusion of new choices of fuel in gas stations. The government offered new incentives to the emerging market with tax benefits by offering the same advantages granted to ethanol vehicles (Kojima and Todd 2005). According to Goldemberg (2007), the rapid rise and success of this market hap­pened because of the maturity of the ethanol industry, the reduction of produc­tion costs (the learning curve), increasing economies of scale, and mastery of the manufacturing techniques for flexible-fuel vehicles.

Ethanol production is a promising market due to the growing global demand. There are different raw materials that may be used in this industry. Therefore, it is necessary to develop the ethanol industry to meet the domestic and foreign demand and promote the country’s development.

In addition to ethanol, another recent source of agro-energy in Brazil appeared: biodiesel. Law No. 11.097-05 established the mandatory introduction of biodiesel in the Brazilian energy matrix in the form of a mixture of 2 % biodiesel (B2) by volume with fossil-fueled diesel (Federal Law 2005). Based on this law, resolution No.6/2009/CNPE stated that B5 would become mandatory in 2013. However, the development of the biodiesel industry enabled enforcement of this resolution in January 1, 2010 (ANP 2010).

Currently, biodiesel is manufactured primarily from soybean oil, which is one of the most valued commodities in the international market. There are public policies for the encouragement of diversification of the feedstock to be used in biodiesel. A variety of options such as soybeans, canolas, peanuts, sunflowers, and cotton is present in the southeast, midwest, and south regions of Brazil. In addition, the north region is able to produce biodiesel from babassu palms and castor beans.

However, with the exception of soybeans, there are no structured and efficient sup­ply chains for these alternative crops, which limit the organized, stable, and cheap sup­plies that can be delivered to the biofuel industry. Regarding the public policies that foster the acquisition of diverse raw materials from companies producing biodiesel, the Ministry of Agrarian Development (MDA) created the so-called Social Fuel label. This label ensures that companies that buy raw materials primarily from family farm­ers obtain special conditions such as lower interest financing by the Brazilian National Bank for Economic and Social Development (BNDES) and other accredited financial institutions; in addition, these firms receive the benefit of tax rates as Pasep/COFINS with reductions of the differentiated coefficients (Garcez and Vianna 2009). It is intended by the government that this percentage shall increase to 10 % by 2014, as biodiesel production already has an installed industrial processing capacity.

Advances in the bioenergy production sector in Brazil have been achieved by developing the industry, and these advances are related to the learning curve that has occurred in this market. Among the improvements, we highlight the development and multiplication of new varieties of sugarcane with high levels of production, progress in the agricultural technology that is employed, cost reductions in the har­vest, the development of new equipment, and the management of agricultural waste. These factors and others have ensured the success of the Brazilian biofuel program.

Fuel mixes with ethanol content higher than 10 % might face constraints because of fuel market infrastructure with more flex-fuel vehicles being needed and distribution networks adjusted (Szulczyk et al. 2010). Based on data and projections made by the Energy Information Agency (EIA) in the 2009, Annual Energy Outlook (The U. S. Department of Energy 2009) future penetration costs of E85 are estimated. Calculations reflect the EIA projected increasing differ­ence between price of wholesale ethanol and gasoline as penetration increases (as discussed Beach et al. 2010). Table 3 presents estimation of market penetra­tion costs for ethanol. These costs are additional costs of infrastructure modi­fication, adding to feedstock costs, transportation costs, and processing costs incurred in refineries.

The oil crises in the 1970s awakened oil-importing countries to their dependency on oil-rich nations. Increasing energy demand, together with finite stock of fossil fuels, has resulted in rising oil prices over time. Since a good deal of global oil pro­duction occurs in politically unstable regions, thereby resulting in recurrent shocks, price spikes and general volatility, concerns about national security have escalated during an era of increasing energy demand (Council of Economic Advisers 2008). From an economic perspective, the pursuit of energy security can be related to a number of possible market failures, including the power of OPEC and the unequal distribution of oil wealth around the globe. This results in insufficient competi­tive conditions, which led to sub-optimal resource allocation (Tsui 2011). From a national perspective, the energy security argument ascribes benefits to reducing oil imports (Delucchi and Murphy 2008; Lapan and Moschini 2012). For example, the hidden cost of oil dependence for the United States is estimated to be about USD 3 per gallon of conventional liquid fuel (Copulos 2007). This cost includes incremen­tal military costs, supply disruption costs and direct economic costs.

Given that the existing mobile energy paradigm relies heavily on liquid fuels, this means, especially in the developed world, exchanging increasingly price-vol­atile hydrocarbon-based liquids fuels for a proportion of biofuels, the feedstock of which can be grown domestically, or at least sourced from comparatively sta­ble economies. An important issue is that biofuels are generally blended with hydrocarbon-based fuels. In effect, biofuels, especially land — and labour-intensive first-generation biofuels, cannot replace hydrocarbon-based liquid fuels on a one — for-one basis, yet they can extend remaining petroleum supplies and, at a general level, the infrastructure that uses them. But this means that liquid fuels in countries desirous of enhancing their energy security will not be able to divorce themselves completely from the global oil price. Hence, the use of biofuels merely improves energy security, but does not result in independence from fossil fuels.

It is necessary to understand the link between energy (i. e. oil and biofuels) and agricultural commodity markets to analyse how biofuels, especially first-genera­tion biofuels, could meet the stated national energy security objective when using feedstock optimized for food production, rather than for energy production. Given that agriculture is an energy-intensive sector, one can draw a direct linkage from oil prices to agricultural commodity prices. The emergence of biofuel markets has raised another linkage between oil prices, biofuel prices and the prices of feedstock crops (and the prices of agricultural commodities in the end).[5] Biofuels have a direct effect on the agricultural sector because they use biomass as an input that, together with agricultural commodities, is produced on a fixed area of agricultural land. The increase of agricultural commodity prices could be significant owing to price inelasticities of food demand and land supply. For example, markets for corn, wheat and rice in the United States, the world’s reserve supplier of grains, saw a drastic increase in related food prices (AgMRC 2009). Corn prices rose from USD 2.20 per bushel in 2006 to above USD 5.20 per bushel in 2007 and reached a high of USD 7.60 per bushel in the summer of 2008. A casual observation also suggests a direct link between these price rises and biofuel output.

However, the potential impact of the expansion of first-generation biofuel pro­duction on food crop prices remains controversial. Some argue that biofuel produc­tion has an adverse impact on food prices and poverty, especially in developing countries (Runge and Senauer 2007; Mitchell 2008). The World Bank has shown that up to 75 % of the increase in food prices could result from biofuel expansion (Mitchell 2008), while the IMF estimated that the increased demand for biofu­els accounted for 70 % of the increase in corn prices and 40 % of the increase in soybean prices (Lipsky 2008). Likewise, the FAO (2008) and the OECD (2009) have argued that biofuel expansion was a substantial factor in causing food price rises. Yet some, like Hassouneh et al. (2011), Mallory et al. (2012) and Du and McPhail (2012), have played this down. Indeed, according to the USDA, the bio­mass demand for biofuels has little impact on food commodity prices (i. e. biofuel production generating only 3 % of the 40 % rise in global food prices) (Reuters 2008). Similarly, the European Commission (2008) argues that the impact of bio­fuel on food crop prices is likely to be very small. Alexandratos (2008) found that increases in the demand for food in emerging countries, particularly China and India, together with weather issues, poor harvests, speculation and financial crises, are the dominant factors behind demand shocks. Yet he acknowledges that the addi­tion of biofuels results in food crop demand growing faster than in the past, which could prevent the current commodity prices trending back towards pre-surge levels.

According to the theoretical framework developed by Gardner (2007), de Gorter and Just (2008b, 2009a), together with empirical work by Ciaian and Kancs (2011), increased bioethanol production results in increasing corn prices, which in turn sub­stantially increases bioethanol prices. Yet an increase in bioethanol prices does increase the price of corn and of other crops because corn competes for land with other crops, while other crops are substitutes in consumption. Thus, the circular impact of high corn and bioethanol prices continues until the opportunity cost of corn for other uses is above the marginal benefit derived from converting corn to bioetha­nol when high-cost biofuel feedstocks are present. Above this point, bioethanol would cease to be produced unless there are substantial production subsidies. The ineffi­ciency of production subsidies owing to high taxpayers’ costs and the cost of interac­tion effects between existing policies (de Gorter and Just 2009a, 2010) implies that, with rising feedstock prices over time, no additional bioethanol would be produced in the longer term when subsidies are no longer enough to induce production. Indeed, a direct link between rising agricultural commodities prices and biofuel output raises concerns about the viability of biofuel production at a scale sufficient to replace a sig­nificant proportion of a nation’s use of petroleum. This is because biofuel production and costs are uncertain and vary with the feedstock available, together with price vola­tility. This is especially the case when feedstocks need to be imported.

U. S. Imported Crude Oil

Price

$/barrel

=== U. S. Diesel Fuel Price $/gallon

= =U. S. Gasoline Price $/gallon

——— Iowa Corn Price

$/bu

…….. Iowa Soybean Price

$/bu

— — .Iowa Ethanol Price $/gallon

The limitation of direct food-versus-fuel competition therefore favours the development of later-generation biofuels derived from non-edible biomass. Although these biofuels have addressed some of the problems associated with first-generation biofuels, the issues of competing land use and required land-use changes with regard to second-generation biofuels’ feedstock production are still relevant (Brennan and Owende 2010). Since food demand and land supply are price inelastic, the price increase of agricultural commodities owing to competi­tion with second-generation biofuels’ feedstock production may still be substan­tial. Figures 2 and 3 show the price trends of agricultural commodities and energy in the United States and at a global level, respectively. Prices of agricultural com­modities have been volatile and are rising over time. Although the surge in the sugar price during 2010-2011 stemmed from weather shocks and poor yields in the two largest sugarcane-producing nations (NREL 2013), i. e. Brazil and India, sugarcane-based bioethanol production was arguably another contributing factor (Alexandratos 2008). At a global level, the prices of palm oil and soybean are even more volatile. The explanation could be that both palm oil and soybean are not only used as feedstocks for biodiesel, but also are in demand for other purposes.

Furthermore, the trends of these agricultural prices are very much similar to those of energy prices, and crude oil prices in particular. The link between crude

Crude Oil, OK WTI Spot Price FOB (Dollars per Barrel)

oil prices and those of agricultural products works via the following: (a) the effects of crude oil prices on agricultural commodity production costs given agriculture’s heavy reliance on energy-intensive inputs (fertilizer, fuel and, in irrigated agri­culture, electricity) and (b) the macroeconomic effects of crude oil prices, e. g. on inflation, incomes, interest rates, exchange rates and foreign trade, all of which have impacts on the agricultural commodity demand-supply balance affecting the prices (Alexandratos 2008). The implication from Mitchell’s estimates (2008) is that the increased petroleum costs caused food prices to increase by 15-20 %. Thus, the use of pro-biofuel policies to improve national energy security becomes questionable. This is because a nation cannot entirely escape from oil price volatil­ity by moving to biofuels derived from edible crops because these remain linked to global oil prices. The difficulty of escaping from oil price volatility is exacer­bated with first-generation biofuels, but also might apply when a market is cre­ated for non-edible feedstocks, the production of which will also, in some cases, be affected by crude oil prices. Although later-generation biofuels could limit mar­ket distortions relating to the direct food-versus-biofuel competition, they may not escape volatility relating to fossil fuel prices. This would especially be the case for grass crops, but perhaps not for milling residue.

The objective of this research was of evaluating the concentration level of the bio­fuels industry market in Brazil from 2005 to 2012. Additionally, we calculated the concentration level for each Brazilian region, as well as the authorized productive capacity usage level and the impact of the industrial concentration in the average price and rentability of this industry.

For this research, we used the HHI and the CR to measure the evolution of industrial concentration level. The results point to a high concentration until 2006, when concentration of biodiesel industry started decreasing expressively, mak­ing the concentration in the industry atomistic, i. e., the industry has highly com­petitive features, considering the current concentration low level. These results reflect on the average price practiced by the 16 largest companies in the sector (that represent around 80 % of the volume produced in the country), and the other companies, where there was no statistically significant difference, where the aver­age prices practiced among both categories. This result can be explained by the hypothesis that companies would not have significant gains granted the sector’s low concentration, that prevents the significant reduction of auction prices, thus indicating some homogeneity of the prices practiced in the biodiesel industry in Brazil.

Besides the high competitiveness of this sector, it was possible to point out that most of the companies located in the south and central west regions, since these regions are known for their high soybean production, the main raw mate­rial used for biodiesel in Brazil. We also pointed out that the south region shows a high level of installed capacity usage level of its companies, pointing to a possible productive gap for this region, which represents 34 % of the national production.

On the other hand, we could see that the Brazilian ethanol industry concentra­tion is highly concentrated in the central-south region, where Sao Paulo (state) produces around 50 % of the Brazilian ethanol, considering that the concentration for ethanol distribution market has grown significantly in the last few years, which has implied better pricing opportunities and a better profitability for the sector, in detriment of consumers.

The conversion of biomass to biofuel varies substantially. First-generation bioethanol is produced through conventional fermentation of starch in the feedstock to convert it into glucose, which is then hydrolysed with the help of enzymes (Naik et al. 2010). The rest of the plant, as mentioned previously, is not employed in the production of bioethanol. It is therefore discarded, or used elsewhere, such as for fertilizer or as fuel in stationary energy provision. As a result, a substantial amount of the energy associated with cultivating, harvesting and processing is lost, with concomitant impacts on the environment, especially when carbon-based energy sources contrib­ute the bulk of the energy inputs, as they normally do so at present (Van der Laaka et al. 2007). A relatively high level of inefficiency and an arguably poor allocation of energy resources throughout the production process are therefore observable here.

First-generation biodiesel is produced from lipids, such as animal fats and vegetable oils, being reacted with an aliphatic alcohol, most often methanol or alcohol, in the presence of a homogeneous or heterogeneous catalyst (Naik et al. 2010). This process is generally referred to as transesterification. Some of the major drawbacks of this process include inefficient extraction of oil from seed, poisonous methanol run-off, high-reaction parameters and the complicated purifi­cation process that requires vast quantities of freshwater, which becomes contami­nated by small quantities of biodiesel. This necessitates water treatment to prevent these impurities entering ecosystems (Parida et al. 2011).

Some of the problems discussed above, however, may be addressed in the future through improvements in biotechnology. For example, genetic manipulation, together with biotechnological developments and improved horticultural practices, has the potential to greatly increase the amount of fermentable starches, sugars and oil found in crops destined for biofuel production (McLaren 2005; Davis et al. 2008). The use of sugar cane for biomass in Brazil has already shown itself as a leading light in first — generation bioethanol production, especially given that the fibre of the plant itself is used to produce the energy needed to produce the bioethanol (Larson 2008).

Second-generation biofuels are produced in a more sustainable way. There are two types of processes used to generate these fuels. The first, sometimes referred to as biochemical, uses enzymes to convert plant cellulose into bioethanol (Foyle et al. 2006; von Blottnitz and Curran 2007), with cellulosic or lignocellulosic (if the biomass contains lignin or woody material) bioethanol being the result. The second process, which is thermo-chemical in nature, is generally known as anhy­drous pyrolysis. This involves the chemical decomposition of biomass by heating it in an anaerobic environment, or without any reagents, so as to convert the plant material into liquid bio-oil or syngas. Liquid bio-oil cannot be used in conven­tional internal combustion engines, although it can be combusted to produce elec­tricity for stationary energy requirements (Chiaramonti and Tondi 2003). By way of contrast, fuels for conventional transport applications, including combustion in turbines, can be synthesized from synthesis gas (syngas) by subjecting them to heat treatment in the presence of air (Eggert et al. 2011). This is not a new pro­cess, having existed for decades, such as the gasification of fossil fuels to produce Fischer-Tropsch diesel, which, like Fischer-Tropsch gasoline, can also be cre­ated from second-generation biomass conversion (Larson 2008). In all these cases, high pressure and temperature requirements necessitate considerable energy inputs (Ragauskas et al. 2006).

It is obvious that a production process that uses all or almost all of the bio­mass is much more environmentally advantageous compared with first-generation processes. Furthermore, the choice of biomass for lignocellulosic bioethanol is much wider, which should allow a better matching of crop to local climatic con­ditions. For example, various types of hardy grasses requiring minimal care, and thus reduced energy inputs, can be used to produce the feedstock. Short rota­tion crops emerge as particularly useful for this purpose, including woody plants such as coppiced willow and poplar. Agricultural waste, such as sawdust, wood — chips or bagasse produced from sugar production, also looms as a clear possibil­ity for bioethanol production (Wright 2006). With anhydrous pyrolysis, any kind of organic waste material can be used. At present, second-generation production processes more or less only exist on a test or commercial demonstration scale, with almost all the commercial biofuel currently being used coming from first — generation processes (Eisentraut 2010). Stephen et al. (2011, p. 160) cite “large technological risk, large capital cost (driven by economies-of-scale), and the poor predicted economic performance of biorefineries” as the main barriers to their commercial uptake.

Overall, there is substantial debate about whether the production and applica­tions of fertilizers, pesticides and herbicides, together with energy inputs into the cultivation, harvesting, transport and production processes relating to the biomass and resultant biofuels themselves, in effect cancels out much of the energy derived from combusting biofuels for mobility-related purposes (Patzek et al. 2005). This is particularly so with regard to first-generation processes involving the waste of significant parts of edible food crops. Whatever the case, as Charles et al. (2007, p. 5743) concluded, “earlier biofuels have proved, at best, to be only marginally more environmentally sustainable and less polluting than fossil fuels, especially when one factors in resource requirements, in addition to production and refining costs”. Of course, improvement can clearly be expected as biomass cultivation and biofuel production methods are optimized over time.