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The common agricultural policy (CAP) is going through a phase of significant restructuring. The original goals of the policy - already stated in 1957 - were primarily aimed at improving agricultural production and reducing consumer prices for agricultural products. The success of the CAP in achieving these goals led to a considerable increase in agricultural productivity within the EU. However, with this rapid development a number of negative external effects of agricultural production activities have also become apparent. The original CAP goals, then, no longer suffice when it comes to facing the problems encountered in present-day agriculture. Effects on social structure, on nature and landscape and on the environment have led to the identification of new policy goals to deal with these drawbacks. With the steadily increasing claim on the budget of the EU, the call for restructuring the CAP has become even more prominent.
The call for new objectives alone was not enough to facilitate the process of restructuring. Many of the actual proposals to change the CAP are restricted to relatively minor changes to the instruments used. Nobody is really willing to give up policies that have led to a healthy agricultural sector with reasonable incomes for the farmers, reasonably stable internal markets, a guaranteed food supply and reasonable consumer prices. Furthermoer, the questions whether these instruments were used to attain preferred policies and whether it was possible to achieve certain combinations of compatible policy goals were never addressed. However, recent history shows that much of the new intentions within the CAP have been frustrated as a result of ongoing growth in productivity.
In this study the proposition is put forward that the problem with restructuring the CAP concerns the CAP's relative ignorance of future possibilities. To overcome this lack of information the possibilities are investigated to set up a future study that brings to light a conceivable and feasible mix of policy goals. Methods from future studies research are critically surveyed so as to develop an adequate methodology for this purpose. It is concluded that an explorative approach based on the description of the properties of the agricultural production system combined with additional information about the external conditions of the system might indicate the technical feasibilities of this system. However, if the consequences of different policy goals for future developments in land-based agriculture are to be identified, the exploration should also incorporate the identification of these policy factors in the guise of an optimisation exercise. This combination of a technical exploration of feasibilities and a political optimisation of goals is denoted as a 'pragmatic' methodology to underline the observation that it is neither the technical possibilities that shape the future, nor the political aims, but a mixture of the two.
This methodology is then applied to the case of future land-use in the EU. The technical possibilities for land-based agriculture in the EU are quantified by combining agronomic information on the relation between plant properties and production potentials, information on soil properties and historical observations of the weather. First, a crop growth simulation model is used to assess the potential yield of various indicator crops. This simulation model uses information on crop characteristics, on quality of the soil and on properties of the climate as its inputs. Next, the potential yields of indicator crops are translated into cropping systems that comprise a certain rotation scheme, certain management decisions and a certain use of inputs. This translation requires information on possible farming systems and cultivation methods as additional inputs and is based on an expert judgement. Finally, the technical possibilities are confronted with political wishes regarding the performance of the agricultural system. Requirements for various policy goals related to land-use together with alternative cropping systems and a demand for agricultural produce are used to construct the linear programming model GOAL (General Optimal Allocation of Land-use).
With this model four contrasting scenarios of future land-use in the EU are developed, based on four different political philosophies: free trade and free market, regional development, nature and landscape conservation and environmental protection. To that end eight policy goals have been incorporated in the model: maximisation of yield per hectare, maximisation of total labour, minimisation of deviation from current regional distribution of labour, minimisation of total pesticide use, minimisation of pesticide use per hectare, minimisation of total N-fertiliser use, minimisation of N-fertiliser use per hectare, minimisation of total costs. In a stepwise procedure, the individual policy goals are optimised alternately to allow for a constant feedback of the results and thus constructing different future scenarios. In this procedure choices have to be made, so the scenarios will be normative by definition. The combined scenarios reflect certain preferences in policy goals and the consequences of these preferences for agricultural land-use in the EU. These results comprise the limits to the options available to the agricultural system.
The model calculations point to dramatic differences between the four scenarios. When it comes to land-use the highest value is some three times higher than the lowest. The difference is twofold as far as employment and use of nitrogen (total and per hectare) are concerned. Highest values for use of crop protection agents per hectare are 4 times the lowest, while the totals differ by a factor of 7.
All four scenarios lead to a considerable reduction in agricultural area. At present about 127 million hectares are used for land-based agriculture. In the nature and landscape scenario only 26 million hectares are needed. The other scenarios also lead to a sharp reduction in the area of land required, ranging from 42 million hectares in free trade and free market scenario to 76 million hectares in the regional development scenario. These results indicate that policies that aim to maintain the area of agricultural land at the current level will have to fight an increasingly fierce battle to withstand the overall trend. Similar conclusions can be drawn for the other policy goals.
The results of this study can be evaluated at three different levels. First, a comparison can be made between the stated demands for a method to explore future possibilities in agriculture and the method that has evolved in this study. The scenarios constructed with the aid of the GOAL model explore technical possibilities to attain a set of well-founded policy objectives. These possibilities are explored by investigating the technical limitations that restrict the potentials of the agricultural sector based on well-known quantitative data. The limitations form the 'hard facts' that are needed to convince policymakers. Although some of the assumptions can be brought under discussion, any adaptation would lead to a more pronounced result in terms of the scenarios. The combination of a technical assessment with a subjective optimisation has indeed given us scientifically underpinned description of limits to the growth of agricultural production and a politically retraceable optimisation of goals.
Second, the results of the exercise reveal that model calculations like these can act as a more or less unimpeachable authority that may discipline the discussion. The optimisations of relevant policy goals obtained with the GOAL model cannot be used to bridge a perceived gap between science and policy, but the outcomes can fulfil a functional role in the way in which the political issues are brought under discussion. If this is the ambition of scientific analysis in a policy context, it will be very difficult to trace the precise impact of any scientific finding in the policy debate. It can be illustrated, though, that there are numerous issues that may benefit from this type of information.
Thirdly, the question arises whether the methodology developed in this study may be transferred to other issues and policy domains. The basic assumption in the general approach is that it is the political process that is sovereign with respect to political choices and it is the scientific community that is sovereign with respect to analyses of order and regularity in nature (and society). This approach is truly pragmatic in the sense that it is fully understood that the analysis must provide policymakers with the best available information to facilitate an informed decision, while at the same time not forgetting that 'political efficiency' will ultimately be the decisive force. Both scientific facts and political goals thus retain their identity throughout the process of analysis, as appeared from our study of the future possibilities for land-based agriculture in the EU. It is in this very respect that the methodology developed in this study differs from other approaches. In other areas of research and policy, however, it may prove much more difficult to make this distinction between scientific analysis and political optimisation. It should be considered a challenging task for policy-oriented science then to develop a similar functional distinction by trial-and-error, thus opening up new possibilities. This requires, as a first step, that in all policy-oriented future studies facts that are prone to scientific analysis be systematically separated from more subjective assumptions and goals.
