4.2.2 Modelling: Calculations

Icône de l'outil pédagogique Author

Patrik Wallman

SEAMLESS-IF consists of four main models coupled in a model chain. The different models in the chain represent different geographical scales, from field to region to country and the EU, but also different scientific disciplines such as biophysical models and economic models.

Icône de l'outil pédagogique APES

APES (Agricultural Production and Externalities Simulator) is a tool to integrate analyses of impacts on a wide range of aspects of sustainability and multi-functionality by evaluating agricultural production and system externalities for most types of agricultural production systems.  APES uses three kinds of input data: 1) variables and parameters provided directly by the user (physical site,  soil parameters and daily weather data), 2) parameters which can be accessed by specific components i.e. biophysical parameters for different crops,  and 3) parameters provided via agro-management files (all the actions to be performed on the crop). APES calculates the yield of crops by use of physiologically based process descriptions such as root growth, water uptake, light interception etc.

Icône de l'outil pédagogique FSSIM

FSSIM (Farm System Simulator) is a bio-economic farm model that links a mathematical programming model formulation of farmers’ resource management decisions, to a data module that includes agronomic and economic information coming respectively from APES and statistical data bases (costs, labour, machine requirements). The data module aims to generate a set of agricultural activities and to quantify the input-output coefficients (both yields and environmental effects) of the farming system. In the data module, firstly a set of suitable production enterprises is generated, secondly these production enterprises are linked to production techniques that describe all the agronomic inputs to the farming system and lastly, for these combinations between production enterprises and production techniques input-output coefficients are derived. The set of agricultural activities and quantified input-output coefficients is then included in the FSSIM model. The FSSIM model tries to solve the mathematical programming model by maximizing a utility function subject to a limited number of explicit constraints.

Icône de l'outil pédagogique EXPAMOD

EXPAMOD (Extrapolation Model) is used for up-scaling the outcomes from FSSIM to the European scale, in the form of price-supply relationships. EXPAMOD estimates the differences in supply responses, and statistically propagates these responses to out of sample farm-region combinations. Changes in relative farm level profits are then used to assign new weights to the farm types covered by the analysis. The supply changes at the micro level and the revised weights for the farm types are then used to adjust supply in the market model SEAMCAP (see below), so that revised prices are obtained. These prices are then fed back in a last step to FSSIM.

Icône de l'outil pédagogique SEAMCAP

SEAMCAP, a version of the CAPRI (Common Agricultural Policy Regional Impact Analysis) model that has been adapted for SEAMLESS-IF, is a comparative static equilibrium model providing information on price-supply relationships, solved by iterating supply (from EXPAMOD) and market modules, and applied to the agricultural sector of the European Union. Simulation results cover areas cropped and herd sizes along with output and inputs coefficients and income indicators for each agricultural activity and each region; prices, supply and demand positions at country level; environmental indicators (gas emissions, N,P,K balances) at regional level; producer and consumer prices, supply and demand positions as well as bilateral trade flows with attached prices, transport costs and tariffs globally for each trade block; the costs of Common Agricultural Policy broken down to individual of policy instruments; a welfare analysis for all countries or country blocks in the system and many other interesting aspects of agriculture.

Icône de l'outil pédagogique PICA

A fifth model that does not include calculations per se is also attached to SEAMLESS-IF, which is PICA (Procedure for Institutional Compatibility Assessment). PICA is a systematic procedure to use information from ex-post case studies and indicator databases for making ex-ante predictions of the institutional feasibility of policies. PICA comprises four distinct steps: 1) Policy options are clustered according to the type of intervention (regulatory, economic, and advisory), the area of intervention (hierarchy/bureaucracy, market, and self-organized network), possibly involved property rights changes, and the attributes of the natural resource addressed. This classification allows identifying the generic structure of a policy option. 2) Each policy cluster is linked to specific sets of crucial institutional aspects (CIA) that may constrain or foster policy implementation. 3) Institutional indicators are used to evaluate the potential of a respective CIA. 4) Combination of the identified CIA and assessment of their relative explanatory power leads to statements about the probable effectiveness of a policy option. The mainly qualitative PICA outputs are arranged in thematic categories of institutional compatibility.

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