Top PDF Impacts of European biofuel policies on global biofuel and agricultural markets

Impacts of European biofuel policies on global biofuel and agricultural markets

Impacts of European biofuel policies on global biofuel and agricultural markets

for their implementation and (2) by the type of instrument. Regarding (1) three policy areas can be distinguished. The first one is agricultural policy. Measures which are implemented here focus on the promotion of crops which are exclusively produced for energy purposes (energy crops). Agricultural policies are handled on European level within the framework of the CAP. The second policy area which has a significant influence on the production of bioenergies and biofuels is the regional or structural policy. Support measures which result from this area are also predominately handled on European level, covering mainly investment subsidies based on structural funds. The last and most important area is the energy policy. Important energy policy issues are still handled under national authority on European Member State level (Breuer and Becker, 2008). Here, many countries reorganise their biofuel support strategies in relative short time intervals or have not implemented such instruments so far but
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Global economic-biophysical assessment of midterm scenarios for agricultural markets-biofuel policies, dietary patterns, cropland expansion, and productivity growth

Global economic-biophysical assessment of midterm scenarios for agricultural markets-biofuel policies, dietary patterns, cropland expansion, and productivity growth

Land-use decisions are made at the local level. They are influenced both by local factors and by global drivers and trends. These will most likely change over time e.g. due to political shocks, market developments or climate change. Hence, their influence should be taken into account when analysing and projecting local land-use decisions. We provide a set of mid-term scenarios of global drivers (until 2030) for use in regional and local studies on agriculture and land-use. In a participatory process, four important drivers are identified by experts from globally distributed regional studies: biofuel policies, increase in preferences for meat and dairy products in Asia, cropland expansion into uncultivated areas, and changes in agricultural productivity growth. Their impact on possible future developments of global and regional agricultural markets are analysed with a modelling framework consisting of a global computable general equilibrium model and a crop growth model. The business as usual (BAU) scenario causes production and prices of crops to rise over time. It also leads to a conversion of pasture land to cropland. Under different scenarios, global price changes range between −42 and +4% in 2030 compared to the BAU. An abolishment of biofuel targets does not significantly improve food security while an increased agricultural productivity and cropland expansion have a stronger impact on changes in food production and prices.
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Will improved access to capital dampen the need for more agricultural land? A CGE analysis of agricultural capital markets and world wide biofuel policies  Factor Markets Working Paper No  48, May 2013

Will improved access to capital dampen the need for more agricultural land? A CGE analysis of agricultural capital markets and world-wide biofuel policies. Factor Markets Working Paper No. 48, May 2013

An IFPRI study, see Al-Riffai et al. (2010), commissioned by DG Trade of the EU- Commission applies a modified version of a global computable general equilibrium model MIRAGE. It assesses effect of DRE implementation and assumes binding target of 5.6% first generation biofuel used in transport in EU by 2020. According to the simulation results, the DRE causes a global increase of ethanol and biodiesel production by 7.6% and 5.1% compared to the reference scenario. Globally, the biofuel mandate leads to an increase in agricultural land use by 0.03% equivalent to 0.8 million hectares. The calculated emissions balance implied by the European mandate is positive and amounts 13 million tons CO2 equivalent. Sensitivity analysis carried out under different mandatory blending (from 4.65 to 8.6%) shows that saving GHG emission effect is decreasing when the level of the mandate increases since higher blending target results in more pressure on land and consequently use of less efficient land in the agricultural production.
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Consequences of EU Biofuel Policies on Agricultural Production and Land Use

Consequences of EU Biofuel Policies on Agricultural Production and Land Use

Consequences of EU Biofuels Policies To analyze the impact of enhanced use of biofuels as the consequence of the EU Biofuels Directive requires an analytical tool which considers not only the agricultural but also the energy markets. Within the last two years many existing models focus- ing on agriculture and food process- ing have been extended to represent the production and consumption of biofuels. All results show that a shift in demand for agricultural products as a consequence of increasing bio- fuel demand leads to substantially increased agricultural market prices and increased land use. However, whether this increase in production takes place within or outside the EU depends on the underlying assump- tions on the degree of openness of the EU. Therefore, two different baseline scenarios have been calculated up to 2020 which describe different visions of the future. This analysis is part of the EUruralis project (Wageningen UR and Netherlands Environmental Assessment Agency, 2007). A detailed description about the background, definition and set-up of the Eururalis scenarios can be found in (Westhoek, van den Berg et al. 2006) and the quantification of the scenarios are de- scribed in (Eickhout and Prins 2008). The scenarios have been calculated with the LEITAP model which is an extended GTAP model. The ‘Global Economy’ scenario depicts a world with fewer borders and regulation compared with today. Trade barriers are removed and there is an open flow of capital, people and goods, leading to a rapid economic growth, from which many (but not all) individuals and countries benefit.
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The Impact of Biofuel Policies on Crop Acreages in Germany and France

The Impact of Biofuel Policies on Crop Acreages in Germany and France

ply of the latter and raising their prices (Baffes and Haniotis, 2016). 2 However, the effect of biofuel policies on European crop acreages is not clear. For a causal link between biofuel policies and crop acreages to exist two issues are impor- tant. First, biofuel policies should have led to higher prices for crops that play an important role in biofuel production such as rapeseed. Second, if these crop prices rise relatively faster than prices of crops mainly used for food or feed, farmers should respond to these higher relative prices by expanding the areas planted with these crops. Although both issues seem straightforward and plausible, it turns out that find- ing empirical evidence for this is not so easy, particularly for the link between biofuel policies and prices. Available price data are limited and during the years of biofuel policies, crop prices have also been affected by other factors, obscuring the effect of biofuel policies. Moreover, prices of major global commodities such as wheat are strongly influenced by international markets.
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The Net Global Effects of Alternative U.S. Biofuel Mandates

The Net Global Effects of Alternative U.S. Biofuel Mandates

This report complements the Baker et al. (2011) analysis of the domestic effects of U.S. biofuel policies on GHG emissions and nitrogen use by accounting for the policies’ international spillover effects and net global consequences. For several reasons, ILUC effects from international sources could be particularly significant in the case of U.S. biofuel expansion policies. First, the United States is a leading producer of agricultural products and a major actor in international markets for oilseeds and cereals. In 2007, U.S. exports represented more than half of the total corn exports traded in international markets and 22% of wheat exports (FAO 2008). Moreover, the United States is the world’s leading soybean producer and exporter. Its exports amount to 40% of total soybeans exports, 10% of soybean cakes exports, and 9% of soybean oil exports (FAO 2008). Second, in the United States, as in most other member countries of the Organisation for Economic Co-operation and Development (OECD), cropland expansion is limited by previous expansion (most arable land is already in agricultural production), the costs of converting forestland to farmland, and the opportunity costs of com- peting urbanized and developed land uses. In addition, some significant restrictions have been set on land conversion and existing conservation programs could limit further expansion (such as the U.S. Conservation Reserve Program). By contrast, large natural areas in the southern hemisphere have no protection status or are left vulnerable because of the high costs of enforcing protection (Robalino and Herrera 2009). Many countries with large forests have become lead- ing agricultural exporters, increasing pressure on those forests and other natural resources. Relatively high agricultural prices increase the risk of deforestation and active agricultural trade has been identified as a powerful discriminator between countries with relatively high forest loss and those with relatively low forest loss (DeFries et al. 2010). Some other developing countries have become major food importers, raising the exposure of a portion of their population to international price developments. Given demographic pressure and economic integration, agricultural production throughout the world will probably become increasingly reactive to market signals.
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Impacts of the EU Biofuel Target on Agricultural Markets and Land Use - A Comparative Modelling Assessment

Impacts of the EU Biofuel Target on Agricultural Markets and Land Use - A Comparative Modelling Assessment

Land use changes Current and future support of biofuels could have important implications for global land use. In particular, it is likely to accelerate the expansion of land under crops particularly in Latin America and Asia. Although this may provide new income opportunities for poor rural populations, it carries the risk of significant and hardly reversible environmental damages. Recently, more attention has been paid to the effects of land use changes by distinguishing between direct land use changes (where land already used for agriculture is switched to produce biofuel feedstock) and indirect land use changes (where land that may or may not be currently used for agriculture is converted to produce non-biofuel crops in response to biofuel- driven displacement of commodity production in a different region, country or even continent) (see, for example, Kim et al., 2009). While direct land use changes are considered in various studies, indirect land use changes are more often ignored. In this report, in line with the terminology used in the Renewable Energy Directive (2009/28/EC, Recitals, para. 85), we use the term ‘indirect land use change’ to mean the net change in total area used to produce crops for all uses.
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US Baseline Briefing Book: Projections for agricultural and biofuel markets

US Baseline Briefing Book: Projections for agricultural and biofuel markets

International rice prices reached record levels in 2008, in response to tight global grain supplies and policies that limited exports from several major countries. Increased world rice production has resulted in lower prices in recent months, and may result in 2009/10 prices that are far below the 2008 peak.

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Biofuel Policies and the Green Paradox

Biofuel Policies and the Green Paradox

The purpose of this modeling exercise is to compare and contrast the extraction path for oil, the non-renewable resource, including time until exhaustion, for the global transport sector under different policies adopted to promote the use of biofuels. Consequences of revised emissions paths are used to evaluate any impacts on the accumulation of GHG in the atmosphere and temperature changes. The results are then used to conclude whether or not the green paradox, in weak or strict form, is withheld. In this chapter, reference scenarios for competitive and monopoly markets in the absence of biofuel policies are reviewed. The following chapter looks at how the adoption of different biofuel policies affects the results of these reference scenarios. The first section within this chapter describes and discusses a set of comprehensive assumptions used throughout the paper in order to create the reference scenarios. Results of the reference models under perfect competition and monopoly market structures are then presented. The sensitivity of the results to some of the key assumptions made in developing the models is addressed in Appendix A.
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Methodology to assess EU Biofuel Policies: The CAPRI Approach

Methodology to assess EU Biofuel Policies: The CAPRI Approach

39 5 Definition of the baseline scenario 5.1 Construction of the CAPRI baseline scenario In general the aim of the baseline is to create a point of comparison for counterfactual analysis. The baseline may be interpreted as a projection in time covering the most probable future development of the European agricultural sector under the status quo policy and including all future changes already foreseen in the current legislation. Conceptually, the baseline should capture the complex interrelations between technological, structural and preference changes for agricultural products worldwide in combination with changes in policies, population and non-agricultural markets. Given the complexity of these highly interrelated developments, baselines are in most cases not a straight outcome from a model but developed in conjunction of trend analysis, model runs and expert consultations. In this process, model parameters (such as elasticities) and exogenous assumptions (such as technological progress captured in yield growth) are adjusted in order to achieve plausible results (as foreseen by experts, e.g. European Commission projections). Therefore, the CAPRI projection tool (CAPTRD) is fed by trend forecasts using data from the COCO database as well as projections from different experts or modelling tools. The purpose of the trend estimates is, on the one hand, to compare expert forecasts with a purely technical prolongation of time series and on the other hand, to provide a safety net position in case no values from external projections are available. A more detailed description of the CAPRI projection tool can be found in Britz and Witzke (2012). The specific exogenous drivers and assumptions on policy changes underlying the baseline projection for 2020 are described in more detail below.
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The Impact of Domestic and Global Biofuel Mandates on the German Agricultural Sector

The Impact of Domestic and Global Biofuel Mandates on the German Agricultural Sector

Fuel ethanol and biodiesel are also included in the system. The ethanol sub-sector is a multi-market non-spatial world model. Linkages with feedstock crops, world sugar and gasoline markets are included. Consumption and production are expressed in detail for the US, Brazil, the EU-25, China and India. Trade equations are also linked to Japan and South Korea and the Rest of the World as an aggregate. Country production is distinguished by the type of inputs and processing technique used (i.e. corn from dry- milling with dried distillers grains in the US). First a world ethanol price is solved through a non-excess demand condition. Domestic prices are associated to the world price via exchange rates and various policy parameters. Biodiesel is described in a similar but less detailed manner. Competition for land occurs among crops grown within given geographical areas and depends on the revenue associated with agricultural prices and supply. Crops supply in turn is contingent on harvested surface multiplied by yield ratios. Fabiosa et al. (2008) employ FAPRI to estimate the land allocation effects of increased ethanol production. The simulation results show that in the US land for major crops and prasture is displaced in favour of energy crops while ethanol output expands. The reduced supply of coarse grains and consequent increase in prices has global effects on land allocation. Similar but considerably smaller impacts are caused by production expansion of Brazilian sugar-based ethanol. In June 2008 the University of Missouri
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Contributions of U.S. Crop Subsidies to Biofuel and Related Markets

Contributions of U.S. Crop Subsidies to Biofuel and Related Markets

0.6 billion gallons. Under the binding mandate, blenders are forced to blend more biofuel into the fuel supply, thus artificially increasing the demand for ethanol and feedstock inputs, which counteracts the agricultural subsidy reduction impacts discussed in the previous analysis. When the mandate and a 15% reduction in crop subsidies are implemented simultaneously, the impacts of the subsidy reduction are over- shadowed by the increased biofuel demand caused by the mandate. This point is imme- diately evident when comparing the 9.83% increase of corn production in the binding mandate case vs. the 0.66% decrease in the nonbinding case. Furthermore, the consumer price of corn increases by 3.89%, which is caused by the increased corn demand for eth- anol production. Both of these results support the claims that biofuel policies will provide much more support than the existing corn sub- sidy does (Gardner, 2003). Hochman, Sexton, and Zilberman (2008) also found that biofuel policies are economically feasible alternatives to deficiency payments because they sufficiently increase the demand for feedstock crops, raising the price above the target price. The binding mandate also increases the biodiesel demand, which augments oilseed production (3.56%).
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Assessing the Land Use Change Consequences of European Biofuel Policies

Assessing the Land Use Change Consequences of European Biofuel Policies

processing of biofuels. Adding the later, even with 2020 direct saving coefficients, the net emission saving fall to 19 grCO2eq/MJ over 20 years a mere 21 percent of fossil fuel emissions. Second, the question whether other policies should also be analyzed from a LUC perspective is also legitimate. Indeed, numerous policies (both agricultural and trade policies) have large land use consequences, and it is difficult to justify why only one policy (biofuels) has to go through the LUC analysis when GHG emissions remain a high priority in the overall EU policy. For instance, using the same methodological framework, it can be shown (Laborde 2010) that a large opening of the EU agricultural market in the Doha round may lead to larger land use emissions than the EU biofuel additional mandates. Even if the goals and global consequences of the two policies should not be compared, it remains true that overall consistency will require the same approach to be used to ensure that all EU policies will contribute to the general direction defined by the Member States and the European Commission. Additionally, policymakers who would like to introduce the LUC issue explicitly in the legislation have to consider this dilemma: “iLUC for all, iLUC for none” with potentially long-term consequences for impact assessment strategies. This argument may be used to discourage any LUC legislation in order to avoid opening Pandora’s Box. However, it should not be misinterpreted. Beyond the biofuel issue, the real challenge lies in knowing if low-carbon agriculture can be implemented in the coming decades with meaningful management of scarce land resources. Indeed, with increasing demographic pressures and potential climate change effects, the question of sustainable agriculture at the global level is critical. Cropland increases 20 times more in the baseline of our model by 2020 than it does as a consequence of the EU biofuel additional mandate. This does not mean that biofuels should get a free ride on the growing emissions trend. However, in order to make sense, any LUC legislation regarding biofuels should be consistent with a broader target and systematic approach.
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Land Use Change Greenhouse Gas Emissions of European Biofuel Policies Utilizing the Global Trade Analysis Project (GTAP) Model

Land Use Change Greenhouse Gas Emissions of European Biofuel Policies Utilizing the Global Trade Analysis Project (GTAP) Model

information on cropland pasture in the EU and Canada, but this could not be accomplished in time for this study. Another type of land not included in GTAP is temporary fallow. Temporary fallow could be due to agronomic practices or due to a lack of markets. Between 1992 and 2007, the European Union had programs that provided economic incentives to leave land fallow (set aside programs). Producers were paid to leave productive land fallow to try to manage the supply and support prices. There was also fallow land that was not part of the incentive programs. In 2004, there were 9.1 million ha of fallow land in the EU. The economic incentives for fallow land are no longer in place and some of this land has come back into production. There are no land use change emissions associated with this land, in fact there could be positive emission benefits as more carbon is added to the soils when fields are continually cropped than when they include a fallow period in the rotation.
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Will EU biofuel policies affect global agricultural markets

Will EU biofuel policies affect global agricultural markets

such effects is a computable general equilibrium (CGE) analysis (Sadoulet and de Janvry, 1995)'. In this article a general equilibrium approach is used, as energy demand and energy or climate change policies might become crucial determinants of agricultural markets. By using a global, multi-region, multi-sector model, this article seeks to increase the understanding of international trade aspects of biofuels and biofuel policies. In this first attempt, we focus on first generation biofuels only. In addition to the extensions directly related to modeling biofuels, some key characteristics of related markets have been included. A distinguishing feature of our method is the introduction of a land supply curve to include the process of land conversion and land abandonment endogenously (Meijl et al., 2006; Eickhout et al., forthcoming). In their overview article on land use and CGE models Hertel, Rose, and Tol (forthcoming) state: 'The beauty of this [the land supply curve presented by Meijl et al., 2006)] approach lies in the way they build up this supply curve. In particular they capitalize on detailed productivity information available from the IMAGE database.' Furthermore, agricultural labor and capital markets are segmented from factor markets in the rest of the economy.
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Abolishing biofuel policies: Possible impacts on agricultural price levels, price variability and global food security

Abolishing biofuel policies: Possible impacts on agricultural price levels, price variability and global food security

As pointed out by Burrell and Nii-Naate (2013) , the stochastic analysis is partial, in the sense that it does not cover all the sources of uncertainty. It only includes the past uncertainty in crop yields, macroeconomic indicators and crude oil price. The past develop- ment of yields is taken into account as from 1996. The yield crops treated stochastically include coarse grains (maize, barley, oats and other cereals), wheat (durum and soft wheat varieties), rice, oil- seeds (soybean, sunflower seed and rapeseed) and palm oil. In order to reflect the variability of grassland productivity, milk yield variability is also taken into account. The regions covered are North America (Canada. Mexico and US), South America (Argentina, Bra- zil, Paraguay and Uruguay), European Union (EU-15 and New Member States), Black Sea Region (Kazakhstan, Russian Federation and Ukraine), China, India, South East Asia (Indonesia, Malaysia and Thailand) and Oceania (Australia and New Zealand). It should be noted that not all the crops are treated as stochastically in every region. Appendix C provides a table summarising the crops for which uncertainty is included by region. For the macroeconomic and crude oil price uncertainty, the stochastic variables are Gross Domestic Product Index (GDPI), Gross Domestic Product Deflator (GDPD), Consumer Price Index (CPI), Exchange Rate with respect
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Welfare Impacts of Alternative Biofuel and Energy Policies

Welfare Impacts of Alternative Biofuel and Energy Policies

Lapan and Moschini (2009) note that most of the existing work does not explicitly account for the welfare consequences to the U.S. of policies supporting biofuel production (such as the externality of GHG emission or the benefits to the U.S. that accrue either from improved terms of trade or “improved national security” due to decreased reliance on oil imports). To consider first- and second-best policies within that normative context, Lapan and Moschini (2009) build a simplified general equilibrium (multi-market) model of the United States and the rest-of-the-world economies that links the agricultural and energy sectors to each other and to the world markets. That paper models the process by which corn is converted into ethanol, accounts for byproducts of this process, and allows for the endogeneity of world oil and corn prices, as well as the (different) carbon emissions from gasoline derived from oil and that which is blended with ethanol. The analysis presented is theoretical in nature, aiming at providing analytical insights and results. The authors find that, in their setting, the first best policy would include a tax on carbon emissions, an import tax on oil, and an export tax on corn. If policy is constrained, for example by international obligations, they find that a fuel tax and an ethanol subsidy can be welfare enhancing. They also find that an ethanol mandate is likely to welfare- dominate an ethanol subsidy.
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Welfare Impacts of Alternative Biofuel and Energy Policies

Welfare Impacts of Alternative Biofuel and Energy Policies

Lapan and Moschini (2009) note that most of the existing work does not explicitly account for the welfare consequences to the U.S. of policies supporting biofuel production (such as the externality of GHG emission or the benefits to the U.S. that accrue either from improved terms of trade or “improved national security” due to decreased reliance on oil imports). To consider first- and second-best policies within that normative context, Lapan and Moschini (2009) build a simplified general equilibrium (multi-market) model of the United States and the rest-of-the-world economies that links the agricultural and energy sectors to each other and to the world markets. That paper models the process by which corn is converted into ethanol, accounts for byproducts of this process, and allows for the endogeneity of world oil and corn prices, as well as the (different) carbon emissions from gasoline derived from oil and that which is blended with ethanol. The analysis presented is theoretical in nature, aiming at providing analytical insights and results. The authors find that, in their setting, the first best policy would include a tax on carbon emissions, an import tax on oil, and an export tax on corn. If policy is constrained, for example by international obligations, they find that a fuel tax and an ethanol subsidy can be welfare enhancing. They also find that an ethanol mandate is likely to welfare- dominate an ethanol subsidy.
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Modeling the global trade and environmental impacts of biofuel policies

Modeling the global trade and environmental impacts of biofuel policies

ABSTRACT There is rising skepticism about the potential positive environmental impacts of first generation biofuels. Growing biofuel crops could induce diversion of other crops dedicated to food and feed needs. The relocation of production could increase deforestation and bring significant new volumes of carbon into the atmosphere. In this paper, we develop a methodology for assessing the indirect land use change effects related to biofuel policies in a computable general equilibrium framework. We rely on the trade policy model MIRAGE and on the GTAP 7 database, both of which have been modified and improved to explicitly capture the role of different types of biofuel feedstock crops, energy demand and substitution, and carbon emissions. Land use changes are represented at the level of agroecological zones in a dynamic framework using land substitution with nesting of constant elasticity of transformation functions and a land supply module that takes into account the effects of economic land expansion. In this integrated global approach, we capture the environmental cost of different land conversions due to biofuels in the carbon budget, taking into account both direct and indirect carbon dioxide emissions related to land use change. We apply this methodology to look at the impacts of biofuel (ethanol) policies for transportation in the United States and in the European Union with and without ethanol trade liberalization. We find that emissions released because of ethanol programs significantly worsen the total carbon balance of biofuel policies. Ethanol trade liberalization benefits are ambiguous and depend highly on the parameters governing land use change, particularly in Brazil. We conclude by pointing out the critical aspects that have to be refined in order to improve our understanding of the environmental implications of biofuel development.
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Biofuel production in Vietnam : Greenhouse gas emissions and socioeconomic impacts

Biofuel production in Vietnam : Greenhouse gas emissions and socioeconomic impacts

Different from partial equilibrium model, general equilibrium models describe the entire economy as all economic agents are taken into account and behave according to the neo- classical microeconomic theory [54]. As biofuels are produced from agricultural sources for energetic purposes, the biofuel policies have not only impacts on agricultural and energy markets but also implications across the economy, e.g. production and consumption of other industries, trade balance, and households’ welfare. The general equilibrium models can address the impacts of biofuels policies due to the economy-wide characteristics and the linkage among production, consumption, and trade in the models [7,55,69]. The general equilibrium modeling applied to biofuels mainly has three approaches. First, in the implicit modeling approach, the biofuel sectors and biofuel commodity are not explicitly modelled, but modelled through the adjustments of data on biofuel crops, e.g. grain, sugar, and oilseeds instead [55,63,70]. Since modeling the biofuel crop inputs in this approach captures a part of production technology and because it is impossible to look into the government support and welfare implications, some authors have moved to the second approach of modeling biofuels as latent technologies with the requirement of data on inputs and cost structures of biofuels [55,71-73]. With the explicitly modeled biofuel production technologies, the representation of biofuels becomes more realistic with the processing stage and the consideration of the linkages between biofuel sectors and other sectors in the economy; however, there exists a shortcoming with the assumption of biofuel trade. The third approach of disaggregating biofuel sectors from the Social Accounting Matrix has been adopted with the availability of reliable data on biofuel sectors in recent studies, e.g. Taheripour et al. [74,75], Britz and Hertel [76], Hertel et al. [77], and Birur et al. [78]. Besides the equilibrium models, some authors have shifted the focus on time series econometrics with the availability of biofuel time-series data to investigate the price transmission and interactions among biofuel-related markets, e.g. Ciaian and Kancs [79, 80]; Kristoufek et al. [81,82], Zhang et al. [83,84], Serra et al. [85], and Serra and Zilberman [86].
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