Systems models to simulate structural change in agriculture

The article discusses the contribution of systems analysis and simulation to the analysis and projection of structural change in agriculture. It starts out with a discussion of general problems of agricultural change and emphasizes the need for appropriate models to control this process by means of policy instruments. Consequently the main part deals with some basic concepts of systems theory and simulation which appear to be useful in this context. Simulation is defined as a numerical method to describe the behaviour of a system under a finite number of randomly or independently selected environmental conditions. Compared to analytical tools it provides a greater flexibility with respect to model structure and component link. The specific concepts discussed in more detail refer to topics of considerable relevance in the process of agricultural change. These concepts are Stochastic simulation; explicit incorporation of delay functions; feedback and control mechanism for economic policy. Three aspects of ‘experimental design’ for projections under varying factor configurations are discussed: Policy projections to analyze factor response relationships (response surfaces); determination of optimal levels of policy instruments or control strategies for given goal structures; construction of social preference orderings for policy makers by means of experiments. Finally three empirical approaches to the simulation of structural change in agriculture with comprehensive systems models are discussed with respect to model structure and economic content.