Determination of Effective Policies for Ecological Agriculture Development with System Dynamics and Agent Based Models – Case Study in Slovenia

Abstract

Agricultural activity, beyond its primary function, can also shape the landscape, provide environmental benefits such as land conservation, sustainable management of renewable natural resources and preservation of biodiversity, and contribute to the socioeconomic viability of many rural areas (Majkovic et al., 2005). One way of emulating the prevailing EU policy reform trends is also to support and encourage organic farming, which is gaining in importance in Slovene agricultural production. Contemplated as a whole, any sound agricultural reform would entail not only necessary positive shifts in economic efficiency levels concerning the production and processing of food, but should specifically address some key socio-economic issues that are at the core of preserving and maintaining the ecological balances in the Slovene countryside; with biodiversity becoming an increasingly important agricultural policy concern (Ivancic et al., 2003). With respect to terms of multifunctionality, organic agriculture is the highest environmentally valuable agricultural system (Rozman et al., 2007a, 2007), and has strategic importance at national level that goes beyond the interests of agricultural sector. This alternative agricultural paradigm may provide the link between objectives of sustainable resource use and sustainable regional development. The consequences of policies are long term and irreversible. In this light the conceptual methodological approach for evaluation of development policies for organic farming must be developed. Organic agriculture represents a complex system at national level (Shi and Gill, 2005) and different modeling approaches have been described in the literature (farm level, regional level and national level). Also, technologic economic simulation at farm level and multicriteria decision analysis are often used for decision support at farm level (Rozman et al, 2005; Pažek et al, 2006). Boorsma (1990) distinguishes three approaches in modelling the behaviour of the farmer: econometric modelling (based on linear regression equations of a data set); mathematical programming and modelling decision processes based on decision rules. At the national and regional level we often encounter econometric models that can