Abstract

The United States and the European Union have been implementing sizeable biofuel support programmes since the beginning of the decade. Supporting the biofuel industry raises the price of the agricultural feedstock, and hence increases the farmer revenue and reduces the need for direct income support. Thus, for a given objective of agricultural income, the regulator is able to operate a partial substitution between agricultural decoupled payments and the support to the biofuel industry (subsidies or mandatory blending). We detail these effects and derive the biofuel and the environmental policies that maximise social welfare. We also show that for high levels of biofuel production, cross-compliance provisions are a more expensive way of enforcing the environmental policy than fining farmers.

1. Introduction

The recent impulse given to biofuel policies is likely to produce major side effects on highly regulated agricultural sectors, particularly in the European Union (EU) and in the United States (USA), where public regulation of the agricultural sector is prominent.1 Since the new biofuel policies trigger feedstock price increases, biofuel policies will have interactions with agriculture policies aiming at supporting farmers' income. Additionally, as most of the energy crop production might lead to more intensive agricultural practices, they will interact with environmental policies directed at agriculture as well.

As pointed out by several studies (see, for example, Elobeid et al., 2006; Schmidhuber, 2006; Tokgoz and Elobeid, 2006; Gohin, 2007), subsidising the biofuel industry raises the price of agricultural feedstock.2 These subsidies (and mandatory blending schemes) come in addition to the ‘traditional’ payments directed to agriculture. In the USA and in the EU, the support adds up to USD 4 billion per year (subsidies only). Even in Brazil (the most efficient producer in the world), the support is evaluated at USD 1 billion (Koplow, 2006; Kutas and Lindberg, 2007).3 In the EU, the development of biofuel production will allow the agricultural sector to benefit from a dual support: on the one hand, member states hand out decoupled payments to farmers (single-farm payments–SFPs) and on the other, they give large support to the biofuel industries whose production costs exceed the price at which they can sell their output. The increase in agricultural commodity prices raises the farmers' revenue and reduces the need for direct income support. Hence, for a given objective in terms of agricultural income, the regulator is able to operate a partial substitution between direct agricultural income support and subsidies to the biofuel industry. In that sense, biofuel subsidies and mandatory blending schemes could be considered a new element in the already wide range of instruments at the regulator's disposal to improve farmers' income. Owing to the importance of the Common Agricultural Policy (CAP) in the EU budget, the question of a partial substitution of biofuel subsidies for CAP payments could be on the EU political agenda very soon.4 In the USA, the ethanol programme might lead to a long-lasting price increase for maize, wheat and soybeans, which could temporarily stop the counter-cyclical and loan deficiency payments (Babcock, 2006).5 Of course, the competition for the same input with biofuel firms is harmful for the agro-food industry, which opposed policies favouring first-generation biofuels from the outset (see Unilever, 2006; Forbes, 2006; Confederation of the Food and Drink Industries of the EU, 2006). As early as 2006, Goldman Sachs (Financial Times, 2006) pointed to a possible decrease in agro-food firm profits owing to biofuel production. Hence, with rising revenues for farmers, decreasing profits for the agro-food industry and a reduced consumer surplus, the net effect on aggregate welfare is unclear.

We develop a model that disentangles these various effects in a framework related to the literature on the efficiency of agricultural programmes which considers the incidence of the opportunity cost of public funds in evaluating economic instruments aiming at supporting farmers' incomes (see, for example, Gardner, 1983; Alston and Hurd, 1990; Alston and James, 2002).

We show that even without any other motivation to support biofuel production (for example, to increase security of energy supply), the government may find it worthwhile to implement a biofuel programme to diminish the social cost of the farm support programme: indeed, it may be socially beneficial to implement such policies if the cost of public funds is high. This result might be one possible explanation as for why biofuel programmes have been in place in the EU and the USA for more than a decade.6 Three different biofuel-supporting schemes are considered in this article, namely subsidies, mandatory blending and subsidies in the framework of a dual energy market. We show that a mandatory blending scheme leads to a level of biofuel production higher than in the subsidy framework. When a dual energy market is considered, the quantity of biofuel produced may not necessarily be greater than in the two other frameworks: it depends on the distribution of the consumers' willingness to pay for biofuel and the level of the opportunity cost of public funds.

Considering the possibility of importing biofuels, the government may still take advantage of the substitution between the farm support programme and the biofuel support policies (subsidies or mandatory blending schemes). This effect leads to a higher domestic price of the agricultural commodity than the world price, relatively low import levels and the imported biofuels benefiting from a lower subsidy than biofuels produced from domestic input.

The effects of biofuels on environmental policies are double-edged. On the one hand, biofuels are presented as one of the main features of GHG mitigation policies in the transportation sector.7 On the other hand, sizeable production of energy crops will lead to increased local pollution, linked to the intensification in the use of fertilisers and pesticides notably, triggering concerns on rivers and ground water pollution as stressed by Marshall and Greenhalgh (2006) for the USA and Graveline (2006) for the EU. Farmers respond to the new market conditions by giving up environmental-friendly rotations and tillage in favour of agricultural practices that are more nitrogen-intensive.8 In addition, high levels of crop prices might push some farmers to opt out of the Conservation Reserve Program (CRP).9 More recently, a report from the National Academy of Science underlined the very negative consequences in the Mexico Gulf (eutrophication) linked to the increased production of corn (for ethanol) in the Midwest (National Research Council, 2008).

Hence, the environmental externalities may be positive for Greenhouse Gas (GHG) emissions (this externality is global by nature), but negative for agricultural production (local externalities). There is thus an essential contradiction between setting a prominent objective for biofuel production that will lead (through higher prices) to higher yields and to an intensification of agricultural production and adopting sound agricultural practices. The positive global environmental externalities of biofuels regarding GHG emissions ought to be weighed against the negative local externalities generated by the production of the agricultural raw material. We analyse the optimal trade-off between GHG mitigation and sound agricultural production practices. We show that because of the social cost of public funds, the optimal standard is stricter than the Pigouvian level. Indeed, by setting a stringent environmental standard, the regulator increases the marginal cost of production, hence the price of the agricultural feedstock, which reinforces the substitution effect between the biofuel policy and the farm support programme. Finally, we compare the monitoring policies associated with two types of monetary sanctions that the government can inflict in case of noncompliance, fines and cross-compliance provisions, and we show that for a high level of biofuels, cross-compliance provisions may prove less effective than fines.

Most of the literature that has investigated the links between agricultural policies and biofuel support schemes reaches conclusions pointing to the inefficiencies of these programmes (as in Gardner, 2007; Babcock, 2008; de Gorter and Just, 2009). In particular, Babcock (2008) finds that the US ethanol policy induces large welfare losses and results in transfers from taxpayers and non-ethanol corn users to corn and ethanol producers as well as blenders. Our results contradict this strand of literature due to premises that differ in three respects: (i) our model integrates a parity income programme that constrains the design of the agricultural policy, (ii) we take into account the opportunity cost of public funds and (iii) we compare biofuel support policies with decoupled agricultural policies, while most of this literature compares biofuel policies (subsidies) with coupled instruments (loan deficiency payments). Another original aspect of our work is that we consider the effect of biofuel policies on environmental policies directed to agriculture.

This paper is organised as follows. Section 2 introduces our model. The optimal production of biofuels and the optimal environmental standard are derived in a framework with a biofuel subsidy considering that biofuels and fossil fuels are perfect substitutes on the consumers' side. Section 3 deals with the mandatory blending policy. In Section 4, we relax the assumption of a perfect substitution between biofuels and fossil fuels and analyse the policy under a dual energy market. In Section 5, the model is extended to account for the possibility of biofuel imports. Lastly, Section 6 addresses the environmental consequences of increased agricultural production, notably pertaining to the enforcement of the environmental policies directed at agriculture.

2. Biofuel subsidy and the agricultural market

Consider an economy with an agricultural sector, a food sector and a biofuel sector. All agents in this economy are price-takers. Both the food and biofuel industries use the agricultural feedstock in order to produce their own outputs (food products and biofuels, respectively). The total quantity of the agricultural product is thus split between the food (xF) and biofuel (xE) sectors: X = xF + xE. The production of the representative firm in the food industry is given by yF = fF (xF), with fF > 0 and fF < 0. For the biofuel sector, we have yE =γ xE, where γ < 1 is the biorefinery yield.10 We assume in this section and in the following that biofuels and fossil fuels are perfect substitutes for consumers and thus they are indifferent between the two (or any mix of the two) as long as they are priced the same. We relax this assumption in Section 4, where we consider a dual energy market.

Denote by pF and pE the prices for the food and the energy products, respectively, and by pA the price of the agricultural raw material, paid by the food and biofuel firms. The energy price pE (the price at which biofuels are sold, which is the fossil fuel price corrected for the lower energy content of biofuels) is supposed to be unaffected by the emergence of biofuels. The agricultural price depends on the government policy but we assume that whatever the public policy implemented, it is always the case that
(1)
i.e. the production cost of biofuel is greater than sales revenue. Consequently, the production of bioenergy needs some type of governmental support. Our focus is on the two policy options that are the most favoured so far: subsidisation and mandatory blending. First consider that the government has decided to grant biofuel firms a per unit of energy crop subsidy formula which allows biofuel firms to break even.11 Assuming that the biofuel firm has no private information (the regulator knows the firm's technology and cost function), it extracts no profit abiding by the biofuel objective of the government, i.e. its profit verifies ΠE = 0 whatever yE. The demand for agricultural raw material coming from the food industry solves the programme of the representative firm given by
(2)
which leads to an optimal input demand xF satisfying
(3)
The supply of agricultural products is derived by solving the representative farmer's programme. We denote by C(X, e) the cost of producing quantity X, where e ∈ [0, eM] is an environmental index (e.g. the polluting emission level linked to the use of fertilisers, pesticides, the increased erosion, etc.) with CXe < 0.12 Hence, the more the farmer pollutes, the lower the marginal cost of production. Denote by ē the environmental standard in agriculture and assume that the farmer abides by the environmental regulation at no cost for the regulator.13 As the environmental standard is imposed on the farmer, the representative farmer programme is simply
(4)
and the first-order condition gives pA = CX (X, ē). Hence, using equation (3), the equilibrium condition on the input market can be written as:
(5)
for all xE ≥ 0, where pF (yF) corresponds to the inverse demand function of the food product, a decreasing function of the quantity of food on the market: pF (yF) < 0. Likewise, CX (X, ē) in equation (5) corresponds to the price of the agricultural input and is an increasing function of the quantity supplied by farmers. For a given environmental standard ē, equation (5) implicitly defines xF as a function of xE, thereby revealing the impacts on the agricultural and agro-food markets of the production objective assigned to the biofuel firm by the government. In particular, differentiating equation (5) gives (omitting arguments to simplify notation)
(6)
and
(7)
which indicate that increasing the biofuel objective reduces the agro-food demand of feedstock (and thus, the corresponding production) but increases the total demand of agricultural raw product. Consequently, the increase in the production of crops xE directed to the biofuel outlet more than offsets the decrease in the input demand of crops xF of the agro-food industry. The incidences on markets are thus an increase in both the agro-food and the crop prices.

2.1. Biofuel subsidy and the parity income programme

The objective of the regulator is to maximise the sum of the profits and surpluses of the different agents in the economy: with the biofuel firm profit equal to zero, it is comprised of the farmers and the food industry profits, the consumer surplus14
(8)
and the taxpayer surplus T. It also takes account of a guaranteed income formula for farmers. Hence, the taxpayer must finance the biofuel programme, on the one hand, and the direct payments to farmers, on the other. The total cost of subsidising the energy crops is given by formula, where the unit subsidy increases with the desired quantity of energy crops: we have formula. The parity income constraint leads to spending equal to formula, corresponding to the decoupled payments awarded to farmers. The total public spending is multiplied by 1 + λ in the Social Welfare Function (SWF), where λ is a positive parameter representing the social cost of public funds.15 We thus have (with the farmers' profits being expressed as formula:
(9)
where the last equality indicates that the taxpayer outlay increases with the production cost in agriculture and decreases with the value of the agricultural food production and the value of the biofuel production.
Using these definitions, it is possible to clarify the marginal effects on the different surpluses due to an increase in the biofuel objective, and notably what pertains to the transfers from the consumer and the food industry to the taxpayer. Marginally increasing the production of energy crops leads to a decrease in the total surplus on the agro-food market (the sum of the consumer's surplus and the profit of the agro-food firm). This loss is equal to the increase in the value of the agro-food input: we have
(10)
This, of course, comes from the fact that the aggregate quantity of agricultural feedstock rises as indicated by equation (7), which increases the price of crops. As for the taxpayer's outlay, a marginal increase in the production of energy crops leads to:
(11)
where the last term in the brackets corresponds to the increase in the value of the agro-food crops, hence the loss of surplus in the agro-food market. The effect revealed by equation (11) can be easily explained: by marginally increasing the biofuel objective, the government has to subsidise the biofuel firm for this supplementary unit (σE), which is detrimental for the taxpayer, but the resulting rise in the crop prices increases the farmers' total revenue, a gain equal to XdpA/dxE. However, this increase also impacts on the subsidy of bioenergy crops: xE dpA/dxE. The net benefit is thus equal to xF dpA/dxE, which is ‘extracted’ from the agro-food market. As
(12)
the variation in total public spending may be negative when the price elasticity of agricultural crop supply, formula, is low and xF/X, the share of food sector demand in the total demand for feedstock, is large. Adding up the variations of the surpluses above gives
(13)
The first term is the marginal social benefit of raising the biofuel objective, which is due to the increase in the agricultural price: the surplus extracted from the food market allows the government to diminish the fiscal deadweight loss of supporting the farmers' income. The second term corresponds to the marginal social cost of this increase: the taxpayer has to pay the biofuel subsidy to balance the revenue of the biofuel firm. Leaving aside environmental concerns, it is thus socially beneficial to implement a biofuel programme if the shadow cost of public funds is large, for the reason that transferring income from the food sector to farmers allows the government to reduce the social cost of the farm income support policy. More precisely, denoting by X0 the quantity of crops produced when there is no biofuel policy (crops are thus entirely produced for the agro-food sector) and by formula the corresponding price, it is beneficial to implement a biofuel subsidy programme if formula defined by:
(14)

In order to give a hint on the value of λs, consider rapeseed production in the EU-15. With a price elasticity of the agricultural crop supply equal to 0.28 (see FAPRI elasticity database, 2006), a biofuel production cost twice as high as its market value: formula and a 10 per cent decrease in the consumption of rapeseed by the food industry, i.e. formula, we obtain λs = 0.18, which is below the lower boundary of the range of λ given in the literature (0.2 to 0.6). Therefore, a strictly positive quantity of biodiesel ought to be produced in the EU-15 on purely redistributive grounds.

Of course, in addition to the redistributive aspects of biofuel policies, the governement also has to account for the environmental impacts of such programmes. The local damages caused by the agricultural production are summarised in an environmental damage function D(e), with D′ (e) > 0: the larger the farms' emissions, the greater the environmental damages. The environmental benefit stemming from the GHG mitigation effect of biofuels is denoted B(yE). In the absence of any constraint on the biofuel production level, the government's programme can thus be written as:
(15)
where the tax term in squared brackets corresponds to the public subsidies which comprise the biofuel subsidies (CXγpE)xE and the decoupled payments to farmers formula.

Solving programme (15) leads to the following result:

Proposition 1

 
If a biofuel subsidy programme is implemented (xE > 0), the biofuel subsidy satisfies
(16)
where α = 1/(1 + λ). The optimal environmental standard in agriculture satisfies
(17)

Proof: See Appendix A.

When a biofuel subsidy programme is beneficial, equation (16) defines the optimal subsidy as the weighted sum of two marginal benefits: GHG mitigation with weight α = 1/(1 + λ) and the increase in the value of agro-food crops with weight formula. With no fiscal distortion (λ = 0), we simply have σE = γB′ (yE), i.e. the Pigouvian rule that the optimal subsidy should equalise the marginal benefit of GHG mitigation. Of course, if γB′ (yE) is negative, the government must not subsidise the biofuel industry. With λ > 0, the optimal subsidy puts a lower weight on the GHG mitigation objective (α decreases with λ) and a larger weight on the increase in the value of agro-food feedstock. Hence, the larger the shadow cost of public funds, the less the GHG mitigation concern is the motive for the biofuel subsidy. Of course, if B′ (yE) is positive, it is beneficial to implement a biofuel subsidy programme even if the shadow cost of public funds is lower than threshold formula discussed above. But if B′ (yE) is negative, the government may still be willing to implement such a programme because of a large shadow cost of public funds (formula in that case).

Likewise, the right-hand side term of equation (17) is the weighted sum of two marginal losses of the agricultural environmental standard formula measures the marginal damage of the agricultural production and formula the decrease in the value of the agro-food feedstock due to a marginal increase in the environmental standard (see the appendix for the derivation of formula). Indeed, by increasing the environmental standard (i.e. by allowing farmers to pollute more), the government decreases the marginal cost of the agricultural input and thus the market value of crops. With no fiscal distortions, implying α = 1, we have the Pigouvian rule, which calls for an environmental standard that equalises the marginal decrease in the production cost with the marginal damage of agricultural practices. With fiscal distortions (λ > 0), the government puts a lower weight on the environmental motive (α < 1) and accounts for the price effect of the standard policy: by setting a stringent environmental standard, the regulator increases the marginal cost of production which reinforces the substitution effect between the biofuel subsidy policy and the farm support programme.

3. Mandatory blending

The main economic instruments to promote biofuels used to be subsidies. However, governments tend to rely more and more on a second type of instrument which does not harm public finances: mandatory blending. Under this policy, with a proportion yE/yM of biofuel in the energy mix (denoted yM), the consumer faces an energy price pM = pE + (pA – γ pE)xE / yM (assuming that the biofuel firm just breaks even) which is higher than the fossil fuel price pE. As the taxpayer only needs to finance the parity income policy, the regulator's programme is
(18)
where CS(yF, yM) denotes the consumer's surplus corresponding to a consumption bundle (yF, yM) of food products and energy blend. In this framework, the fiscal term (in squared brackets) boils down to the decoupled payments given to farmers, namely formula. As pM depends on xE (directly and indirectly through pA) a marginal increase in xE affects both the agro-food and the energy market. To illustrate, assume that the consumer's surplus takes the following separable form:
(19)
where DE(p) denotes the energy demand. Differentiating the last term, we obtain
(20)

Hence, in addition to the loss of surplus on the food market as identified above in the case of the subsidy policy, the consumer is affected by a loss of surplus on the energy market due to the impact on energy price of the blending policy. The marginal loss of surplus on this market is made up of two terms: one corresponding to the (implicit) biofuel subsidy and the other to the effect of the blending requirement on the agricultural price. Solving programme (18) leads to the following result:

Proposition 2

 
If a mandatory blending programme is implemented (xE > 0), the optimal level of energy crops, which satisfies
(21)
is greater than under a subsidy programme. The optimal environmental standard, satisfying
(22)

is more stringent than the environmental standard with the subsidy scheme.

Proof: See Appendix B.

The optimal biofuel production under a mandatory blending policy is greater than under a subsidy policy. There are two reasons explaining this result. First, the fiscal advantage of the blending policy not only affects the feedstock directed to the food sector, xF, but also the one directed to the biofuel production, hence the entire agricultural production X, as reflected by the last term of equation (21). Second, as the consumer surplus is affected by a unit weight in the SWF while the taxpayer surplus is weighted 1 + λ due to fiscal distortions, the implicit subsidy level given in equation (21) indicates that the blending policy does not balance the environmental benefit of the GHG mitigation with the fiscal advantage of a larger agricultural price as in equation (16). As a consequence, this implicit subsidy is larger than the GHG marginal benefit whatever λ > 0. For the environmental standard, as it affects the agricultural production cost and thus the decoupled payment directed at farmers and financed by the taxpayer, the rule given by equation (22) shows a weighted sum of two marginal benefits very close to equation (17), reflecting the fact that the increase in the agricultural cost due to the environmental standard raises the government outlay. However, as in equation (21), the last term of equation (17) indicates that the fiscal advantage of the rise in the agricultural price affects the entire production of feedstock, which explains that this standard is more stringent than under a subsidy policy.

4. Dual energy market

In this section, we relax the hypothesis of a perfect substitution between biofuels and fossil fuels and consider instead that consumers obtain a greater surplus from consuming biofuels rather than fossil fuels. This opens the possibility of a dual energy market where consumers are charged a different price depending on the type of fuel they choose. To simplify the analysis, we adopt a parsimonious specification of the consumer surplus by considering that the marginal surplus derived by any individual from the consumption of 1 litre of fossil fuel is constant, normalised to 1, while the surplus derived from the consumption of 1 litre of biofuel has value θ > 1, indicating that consumers are willing to spend a supplementary amount to obtain biofuel. With pB being the price of biofuel, the net surplus from consuming 1 litre of biofuel is θpB, while it is 1 − pE for 1 litre of fossil fuel. However, the consumers' willingness to pay for biofuel is influenced by several factors that affect individuals differently (environmental concerns such as awareness of GHG emissions due to fossil fuels and biofuels or local air pollution problems). To account for this variety of factors, we consider that θ takes its value over [1, θ¯] with cumulative distribution function F(θ) and density f(θ) = F′ (θ). The consumer who is indifferent between consuming biofuels or fossil fuel has a willingness to pay given by θ* = 1 + pBpE. With a fossil fuel price equal to pE, the total demand of energy is yM = DE (pE) but all consumers with θ > θ* prefer to buy biofuels, resulting in a splitting of the total demand of energy between fossil fuels and biofuels equal to yMF(θ*) and yM [1 − F(θ*)], respectively. Compared with equation (19), the total surplus derived by consumers from the food and the energy markets becomes:
where
Integrating by parts, the consumer surplus on the energy markets simplifies to:
where the last term corresponds to the increase in surplus due to biofuel consumption. The quantity of energy crops corresponding to the demand of biofuel charged at price pB is given by
(23)
While the consumers' valuation of biofuel is accounted for in this setting (whereas it was simply ignored in the previous sections), the corresponding optimal biofuel policy does not necessarily lead to a larger production of biofuels. Indeed, xE is greater than x*E, the biofuel production of the perfect substitutability case, if pB is not too large, hence if the willingness to pay of the indifferent consumer, θ*, is lower than threshold θE satisfying
(24)
Of course, if pB = pE, all consumers buy biofuels (we have θ* = 1) but the subsidy per unit of energy crop necessary for the biofuel firms to break even would be the same as in the pure substituability case, i.e. σE = pA − γpE. With a price p*B = pE + θE − 1 (hence, such that θ* = θE), the subsidy becomes sE = pA − γpB < σE and it is possible for the government to implement a policy that results in the same amount of biofuels, environmental quality and farmers revenues as in the perfect substituability case, but at a lower cost for taxpayers. Of course, this is not the optimal policy and it is possible for the government to increase the social welfare by either reducing the biofuel subsidy (hence reducing further the charge of the biofuel subsidy for the taxpayers) or increasing this subsidy (hence, reducing the charge of the parity income policy by increasing the quantity of biofuel consumption). More precisely, it is shown in the appendix that the government's tradeoff is reflected by the following expression:
(25)

In words, reducing the biofuel subsidy by EUR 1 (hence, increasing pB by EUR 1) allows to raise [1 − F(θE)]yM on the biofuel market, and thus the government is able to decrease the taxpayer charge by (1+λ)[1 − F(θE)]yM, leading to a social net gain given by the first term of equation (25). However, this price increase also leads a fringe of biofuels consumers, equal to f(θE), to switch to fossil fuels and thus it leads to a decrease in the biofuel production equal to f(θE)yM. The second term of equation (25) corresponds to the supplementary amount of tax needed to maintain the farmer revenue at the parity income level due to this marginal decrease in energy crops production. The result of these two counteracting effects depends on the distribution of the consumers' willingness to pay for biofuels and on the extent of the deadweight loss due to taxation, as stated formally in the following proposition:

Proposition 3

 
When biofuels and fossil fuels are imperfect substitutes, if a biofuel subsidy programme is implemented (xE* > 0), the optimal quantity of energy crops is larger than in the perfect substitution framework if
(26)
where θE is given by equation (24).

Proof: See Appendix C.

5. Imports of biofuels

The results of the previous section are limited to biofuels produced domestically. Buying biofuels on the world market could prove less expensive for society, even if governments must also account for the indirect benefits associated with a domestic biofuel support programme.16 To investigate this question, we assume that a quantity of biofuels zI bought at price pI is imported from a perfectly elastic world supply.17 The environmental GHG benefit linked to the use of the biofuel in replacement of fossil fuel is supposed to be identical whatever the biofuel origin, leading to total benefit B(yE + zI).18 We consider only a subsidy policy in this section and assume that biofuels and fossil fuels are perfect substitutes for consumers.

The subsidies awarded by the regulator to the biofuel sector are σE = pAγpE per unit of domestic feedstock and σI = pIpE for imported biofuels. The total biofuel subsidy is thus given by S = σExE + σIzI, which together with the decoupled payments given to farmers formula makes up the fiscal term in the SWF. The regulator's programme can be written as:
(27)

Denoting by formula and formula the optimal regulator choices, we have the following results:

Proposition 4

 

When the government can import the agricultural feedstock at pricepI

  • with no constraint on the biofuel production level, it is optimal to produce energy crops if λ is large. The optimal policy satisfies the following conditions
    (28)
    and
    (29)
    In particular, if the GHG marginal mitigation benefit is low, all the agricultural feedstock is produced domestically:formulaandformula.
  • and has to fulfil an exogenous biofuel production objectiveQ > γxE*, it is optimal to produce energy crops domestically at levelformula. The internal price of the agricultural feedstock verifiesγpA > pIleading to subsidiesγσE > σI.

    Proof: See Appendix D.

Condition (29) states that – in the absence of any constraint on the biofuel production – the optimal imported crop level equates the marginal social cost of subsidising the biofuel industry with the marginal environmental benefit of biofuel. If the marginal GHG mitigation benefit is large, it is optimal to import biofuels. Of course, if these benefits are low (or negative), the government does not allow imports: we have formula. Compared with equation (29), condition (28) entails the marginal social gain of the transfer of revenue from the food sector to the farmers, which eases the condition for a positive level of domestic biofuel crops. As equation (28) is similar to equation (16), if no biofuel objective is imposed to the regulator and GHG mitigation is low (or negative), a production of domestic energy crops will take place exactly as in the autarky framework, i.e. we have formula, formula and formula This result seems quite intuitive as the reason which had led to reach a ‘natural’ level of energy crops xE* essentially hinged upon the social benefit of transferring income from the agro-food industry and the consumer to the taxpayer, thus diminishing the distortions linked to taxation. The possibility of importing biofuels does not alter this rationale. However, when the regulator is faced with a biofuel objective, the situation changes with respect to the autarky framework. As the regulator goes beyond the ‘natural’ level of energy crops xE*, it trades off between two possibilities: producing domestically or importing. As long as the opportunity cost of blending domestic biofuels is smaller than the opportunity cost of blending imported biofuels, domestic production is preferred. Beyond this quantity level formula the remaining quantity to reach the constraint Q is imported.

6. Policy enforcement and cross-compliance

As stressed by Marshall and Greenhalgh (2006) for the USA and Graveline (2006) for the EU, in response to the increased demand of biofuel feedstock, farmers may be tempted to abandon environmental-friendly rotations and tillage. The alternatively adopted agricultural practices might well lead to water pollution problems due to a notable intensification in the use of fertilisers and pesticides as well as to increased soil erosion. In this section, we discuss the problem of enforcing environmental standards given the biofuel objectives of the governments. As noted by Bontems and Rotillon (2007), an efficient environmental policy is not a mere definition of the right level of tax or norm to abide by. To enforce a demanding policy, it is necessary for the State to control farms frequently, which is costly, and to be able to inflict sizeable penalties to have some effect on farmers' behaviour. The conventional rule which states that pollution should be reduced to the point where the marginal damage and the marginal cost of pollution reduction are equal does not apply if enforcing the rule is costly. The cost of pollution should be added up with the marginal cost of control. This ultimately reduces the level of environmental standards that must be imposed on farmers.19 Our focus is more particularly on the 2003 CAP reform, which imposed ‘cross-compliance’ provisions. This policy conditions the benefit from market support schemes to farmers abiding by environmental protection requirements. With the enactment of this policy, all farmers receiving direct payments must fulfil the requirements of 19 European legislative acts applying directly at the farm level in the domains of environment, public and animal health, pesticides and animal welfare. Farmers will face partial or total withdrawal of their SFP in case of non-compliance. As the SFP is a decreasing function of the farmers' revenue, the maximum fine in case of non-compliance is lower the larger the farmers' revenue. As the farmers' revenue increases with the biofuel production objective, it seems that this compliance policy may prove ineffective in the future given the high level of biofuel production forecast for 2020. We shall analyse this problem in a framework similar to Malik (1992), considering that inspecting farms is costly and that the government inflicts penalties that depend on the extent of the infringement. We analyse the two cases of an exogenous maximum penalty and a maximum penalty which corresponds to the farmer's decoupled payment, as is the case in the EU. We do not consider imports in this section.

Assume that whenever a farmer has chosen an emission level e that exceeds the standard formula, the agency is able to inflict a penalty that depends on the extent of the farmer's infringement, formula, and more precisely that the corresponding penalty is a fraction formula of a maximal penalty Ψ. The function f(·) is exogenously given (by an independent legislative body) and is assumed increasing and convex in the seriousness of the infringement, with f(0) = 0. The maximum penalty can either be a given amount formula (also determined by an independent legislative body), or the decoupled payment that the farmer should receive in case of compliance, i.e. formulaThe latter case corresponds to the current framework chosen by the EU to enforce environmental policies in agriculture. Let k be the intensity of control (the probability a farm is inspected), and μk the corresponding cost.

Facing this control policy, the representative farmer chooses his agricultural practices e in order to maximise his profits taking account of the expected penalty. His programme is given by
(30)
leading to an optimal level e* which satisfies:
(31)
i.e. the marginal cost of reducing pollution must be lower than (or equal to) the marginal expected penalty. We assume that there is no social benefit associated with the payment of fines, implying formula at the optimum of the government's programme: no fine is paid in equilibrium. Moreover, as inspecting farms is costly, this condition is binding at the optimum of the agency programme, i.e. we have:
(32)
The agency simultaneously chooses the optimal level of inspection, the environmental standard and the scope of the biofuel policy by maximising the following programme:

In this welfare function, the term in square brackets corresponds to public spending, which is made up of three components: the biofuel subsidies (CXγpE)xE, the decoupled payments to farmers formula and an additional term μk representing the cost of controlling farms.

Condition (32) gives some hint about the optimal compliance policy of the government. Indeed, assume that the government wants to fulfil a biofuel objective Q and to enforce a given environmental standard formula. Denote by formula the corresponding agricultural production implied by the equilibrium condition (5). Given these objectives, the best compliance policy corresponds to the one with the lowest intensity of control. These monitoring efforts, kf under the exogeneous maximal penalty policy and kcc under the cross-compliance policy, can be ranked using equation (32) as we have
(33)

Hence, cross-compliance may prove the most efficient policy if formula is low compared with the parity income formula and if agricultural production formula is low, while the government is more likely to choose an exogeneous maximal penalty policy for large biofuel objectives. Of course, for a given production level, the environnemental standard is different depending on the compliance policy. Denote by ecc (Q) the optimal environmental standard under the cross-compliance policy given biofuel objective Q. As ecc (Q) increases with Q, the farmer's profit formula also strictly increases with Q. Hence, for any biofuel production greater than formula, the government is able to implement the optimal environmental standard of the cross-compliance policy with an exogenous maximum penalty policy and thereby it can reduce its monitoring effort and thus the cost of the enforcement policy. Reciprocally, for production Q < Qs, cross-compliance proves to be the most efficient policy.

7. Conclusion

The main results of this paper can be summed up as follows. First, we have shown that biofuel programmes may allow the regulator to operate a partial substitution between decoupled payments and the support for biofuels. This substitution is detrimental to the food industry (and to consumers). However, when the social cost of public funding is high, the regulator should finance a biofuel programme because of its redistributive property. Of course, this result rests on the existence of sufficiently high distortions in the tax system. Positive environmental externalities of the substitution of biofuels for fossil fuels tend to push the optimal biofuel quantity a step further. Conversely, if these externalities are negative, the support is decreased. The conclusions drawn in the case of a biofuel programme financed through subsidies can also be made when biofuels are promoted thanks to a mandatory blending scheme. The optimal level of biofuels that ought to be produced is even higher in that case. When a dual energy market is implemented, the optimal production of energy crops is not necessarily greater than with the other policies: it depends on the distribution of the consumers' willingness to pay for biofuels and on the opportunity cost of public funds. Taking into account the possibility of imports, the optimal level of energy crops produced domestically is set at a level where the domestic price exceeds the world price for energy crops, thanks to the saving of public funds permitted by biofuels.

The emergence of biofuel policies marks a profound change in the path of agricultural policy reform, which has mainly consisted in decoupling the support awarded to farmers from production decisions. This evolution has begun with the 1992 reform and was further reinforced during the Agenda 2000, Mid-Term Reform in 2002 and the ‘Health-Check’ which was adopted at the end of 2008. Clearly, the decision to design large-scale biofuel programmes has contributed to sharp increases in agricultural commodity prices, and this new biofuel policy, although formally taking place outside the CAP, has deep consequences on the logic of its future evolution. It could be argued that biofuel support policies have implications that look like re-coupling. Moreover, the enforcement of stringent environmental policies in agriculture may be jeopardised by the high price levels triggered by biofuel programmes. The reforms of the CAP had led to the implementation of cross-compliance provisions, with the possibility for the regulator to fine the farmers in case of infringement, the penalty paid by the farmer being proportional to the decoupled payment. With a new framework of high commodity prices and decreased decoupled payments, the cross-compliance scheme would be put at risk.

Many extensions of our framework could be investigated. First, we have considered that the subsidies were fine-tuned. This assumption could be criticised, as there are informational asymmetries between the regulator and the biofuel firms. In the mandatory blending framework, such informational asymmetries are not relevant but informational rents could well be replaced by monopolistic rents for biofuel producers. For instance, the major biodiesel firm in France covers more than 75 per cent of the market. We have also assumed a perfectly competitive agro-food sector. Relaxing this assumption may well lead to very stringent conditions for a socially valuable subsidy substitution effect between the farm support and the biofuel programmes.

Acknowledgements

Financial support received by the ‘New Issues in Agricultural, Food and Bio-energy Trade (AGFOODTRADE)’ (Grant Agreement no. 212036) research project, funded by the European Commission, is gratefully acknowledged. The views expressed in this paper are the sole personal responsibility of the authors and do not reflect those of the Commission, which has not viewed, let alone approved the content of the paper. The paper does not reflect the views of the institutions of affiliation of the authors either.

1

The first US biofuel programme was initiated by the Energy Tax Act of 1978. Quantities have been increased significantly over the past few years, the latest target being 36 billion gallons (136 billion litres) of biofuels by 2022. In the EU, the Renewable Energy Directive voted in 2008 sets a 10 per cent mandatory target of ‘renewable fuels’ (i.e. biofuels but also green electricity and hydrogen) for 2020 (European Commission, 2008).

2

We curtail our analysis to the first generation of biofuels, which uses the same feedstock as the agro-food industry.

3

Fuel tax reduction has been the main economic instrument used to promote biofuels. Of course, this instrument can only be used to the extent that excise tax is levied on fossil fuels. This is the case for developed countries, but in some developing countries, fuels face only low taxes or are even subsidised.

4

In 2007, the CAP represented more than EUR 40 billion, i.e. 37 per cent of the EU budget (European Commission, 2007).

5

Likewise, Marshall and Greenhalgh (2006) calculate that a production of 15 billion gallons of corn ethanol would lead to savings for the federal government of USD 18.4 billion (versus a cost of approximately USD 7.5 billion in tax credit for ethanol as estimated with a USD 0.51 per gallon tax credit). See Banse et al. (2008) for an appraisal of the EU biofuel policy.

6

Of course, biofuel programmes have first and foremost been put forward for their alleged positive effects on energy security and for mitigating GHG emissions in the transport sector.

7

However, Searchinger et al. (2008) and Fargione et al. (2008) show that the carbon balance of biofuels would indeed be negative, owing to a ‘carbon debt’ incurred by biofuels when their production implies land-use changes leading to a carbon release (e.g. primary forest or peatland transformed into crop fields to produce biofuels). de Gorter and Tsur (2010) discuss the cost–benefit analyses linked to indirect land-use change.

8

Marshall and Greenhalgh (2006) also stress the fact that the increased rate of nutrient and soil loss is by far larger than the rate at which supplementary land is brought into production.

9

This programme has been set up mainly for soil conservation purposes. Contracts engage farmers to crop native grasses (no cash crop) in exchange for government payments for 10 to 15 years. Secchi and Babcock (2008) point out that owing to the high prices for corn, environmentally sensitive land will be cropped again and that very high spending levels would be necessary to maintain those lands within the CRP.

10

This yield is evaluated at 0.34 l/kg for biodiesel made from rapeseed and at 0.39 l/kg for corn ethanol (see Janulis, 2003 and Dias De Oliveira et al., 2005).

11

The aggregate economic support to biofuels is made up of very diverse economic measures: subsidies given by the State, accelerated depreciation, loans, loan guarantees, subsidies for buying flex-fuel cars, etc. (for more details, see Koplow, 2006). Considering that the subsidy is given to the biofuel firm is only for expositional clarity.

12

CXe stands for formula We also assume C(X,e) convex: we have formula.

13

This assumption will be relaxed in Section 6.

14

Recall that we consider that consumers value biofuels on an energy basis only. As the subsidy given by the regulator brings the price of biofuels down to the price of fossil fuels, these two products are perfect substitutes, i.e. the consumer is indifferent between consuming fossil fuels or biofuels. We relax this assumption in Section 4.

15

See Fullerton (1991) for a discussion on the value of λ.

16

A survey on biofuels trade is conducted in Energy Sector Management Program (2007). See also Elobeid and Tokgoz (2008) for an appraisal of the removal of US import duties on ethanol.

17

Note that the imports can take the form of energy crops (resulting in various biofuel prices since raw materials are imperfectly substituable), intermediate products or ready-to-blend biofuels. For our purposes, it is sufficient to consider that imports take the form of ready-to-use biofuels at world price pI.

18

More generally, the GHG benefit is given by B(yE, zI) with ∂ B/ ∂ yE ≠ ∂ B/ ∂ zI. Generalisation of our results in that case is straightforward.

19

Following Becker (1968), a large body of literature has been developed around the ‘economics of crime’, with a straightforward transposition to the enforcement problem in environmental policies. For a survey on enforcement models applied to environmental economics, see Cohen (1999) and Bontems and Rotillon (2002).

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Appendix A: Proof of Proposition 1

Denoting by β the Lagrange multiplier corresponding to the market equilibrium condition (5), the first-order conditions corresponding to the policy instruments xE and ē are given by
(A1)
and
(A2)
respectively, while the condition associated with xF is
(A3)
From equation (5), we have formula and formula. Rearranging terms of equation (A3) yields:
(A4)
Plugging into equation (A1) leads to
(A5)
Rearranging terms of equation (A5), using CXX dX/dxE = dpA/dxE and α = 1/(1 + λ) gives equation (16). For a given xE, totally differentiating CX (xE + xF, ē) = pA and equation (5) leads to
and
which gives
(A6)
Using equations (A3) and (A6), equation (A2) becomes
(A7)

Rearranging term gives equation (17).

Appendix B: Proof of Proposition 2

Denote by ℒMB the Lagrangian associated with programme (18) and β the multiplier corresponding to equation (5). The first-order conditions are
(B1)
(B2)
and
(B3)
Denoting by formula the optimal subsidy policy, we have, using equations (B1), (B2) and (A5):
hence formula. Similarly, using equations (B1), (B3), (A3) and (A2):
hence formula. Rearranging terms of equation (B1) yields:
Use of equations (5), (B1) and (B2) leads to the following condition:
(B4)

Rearranging terms and using formula gives equation (21). Similarly, equation (22) is derived from equation (B3) using (A6).

Appendix C: Proof of Proposition 3

Denoting by formula and μ the Lagrange multipliers corresponding to the market equilibrium condition (5), equation (23) and the definition of the energy crop subsidy sE = CXγ (θ* − 1 + pE), the Lagrangian of the welfare programme can be written as follows:
The first-order conditions corresponding to the policy instruments s, θ* and xE are given by:
(C1)
(C2)
(C3)
From equation (C1), we have:
(C4)
Equation (C2) gives the expression of the Lagrange multiplier η:
(C5)
First-order condition with respect to xF yields:
(C6)
or, rearranging using equation (C4),
(C7)
From equation (5), we have formula and formula. Rearranging terms of equation (C7) yields:
Plugging into equation (C3) leads to
(C8)
and, finally
(C9)
Denoting by θE the parameter such that formula, we have using equations (C9) and (A5):
Hence, the optimal quantity of energy crops is larger than in the perfect substitution framework if

Appendix D: Proof of Proposition 4

The government's programme leads to the following Lagrangian (neglecting the constants):
The first-order conditions w.r.t. xE, xF and formula are identical to equations (A1), (A3) and (A2) while we have
which gives equation (29). With a biofuel constraint, substituting formula for zI in programme (27) and maximising in xE and xF gives the following condition:
(D1)
which implicitly defines formula. Plugging formula into equation (A5) and using equation (A1) to substitute for the first term, we get:
which is negative if B′(Q) is low (or negative), implying that formula.

Author notes

Review coordinated by Thomas Heckelei