Kathrin Happe

Agent-based Analysis of Agricultural Policies: an Illustration of the Agricultural Policy Simulator AgriPoliS, its Adaptation and Behavior

This paper combines agent-based modeling of structural change with agricultural policy analysis. Using the agent-based model AgriPoliS, we investigate the impact of a regime switch in agricultural policy on structural change under various framework conditions. Instead of first doing a sensitivity analysis to analyze the properties of our model and then examining the introduced policy in an isolated manner, we use a meta-modeling approach in combination with the statistical technique of Design of Experiments to systematically analyze the relationship between policy change and model assumptions regarding key determinants of structural change such as interest rates, managerial abilities, and technical change. As a result, we observe that the effects of policies are quite sensitive to the mentioned properties. We conclude that an isolated analysis of a policy regime switch would be of only minor value for policy advice given the ability of simulation models to examine various potential futures.

On the Dynamics of Structural Change in Agriculture Internalc Frictions, Policy Threats and Vertical Integration

The agricultural sector in Europe faces a number of important challenges, such as developments in biotechnology and biofuel, globalization, vertical integration and policy changes. The important questions are whether and how farms are able to adapt to these changes and what are the potential forces working against adaptation. This paper elaborates on internal frictions regarding structural change in agriculture, namely sunk costs, dependence on subsidies and the challenges of an increasing demand for vertical integration.

An agent-based approach to modeling impacts of agricultural policy on land use, biodiversity and ecosystem services

We present extensions to the agent-based agricultural policy simulator (AgriPoliS) model that make it possible to simulate the consequences of agricultural policy reform on farmers’ land use decisions and concomitant impacts on landscape mosaic, biodiversity and ecosystem services in a real agricultural region. An observed population of farms is modelled as a multi-agent system where individual farm-agent behaviour and their interactions—principally competition for land—are defined through an optimization framework with land use and landscape impacts resulting as emergent properties of the system. The model is calibrated to real data on the farms and the landscape to be studied. We illustrate the utility of the model by evaluating the potential impacts of three alternative frameworks for the European Union Common Agricultural Policy (CAP) on landscape values in two marginal agricultural regions. Mosaic value was found to be sensitive to the choice of policy scheme in one of the landscapes, whereas significant trade-offs were shown to occur in terms of species richness by habitat and species composition at the landscape scale in both regions. The relationship between food production and other ecosystem services was found to be multifaceted. Thus illustrating the difficulty of achieving landscape goals in a particular region with simple or general land management rules (such as the current rules attached to CAPs direct payments). Given the scarcity of funding for conservation, the level and conditions for allocating direct payments are, potentially, of great importance for preserving landscape values in marginal agricultural regions (subject to levels of other support).

Multifunctional farming, multifunctional landscapes and rural development

The Common European Agricultural Policy (CAP) is under transformation towards a Common Agricultural and Rural Policy of Europe (CARPE). During this transformation, substantial parts of the previously direct support for agricultural production (1st pillar measures) are now decoupled from production. Moreover, a share of direct payments is modulated to the rural development programme, which is the 2nd pillar of the CARPE (Table 1).

Agricultural management issues of implementing multifunctionality: commodity and non-commodity production in the approach of the MEA-Scope project

Management practises are actually designed CO-oriented. Following the societal demand for implementing multifunctional agriculture it is necessary to examine in how far the existing management practices are as well feasible to produce NCOs or in how far they are multifunctionally sound (jointly CO/NCO oriented). Multifunctional joint production has to be aware production, considering the specific “yield potentials” of COs and NCOs at a specific natural site. From the farm management perspective, we assume both, CO and NCO as markets existing.

The MEA-Scope Modelling Approach

The MEA-Scope project developed, and applied a modelling approach that allows for the ex ante assessment of sustainability impacts of new policies, technologies and market changes. Thereby, the agricultural production at farm level and its effect on social, economic and environmental assets under changing circumstances is examined. The MEA-Scope modelling approach simulates the development of regional agricultural production structures over time. Within the same analysis, the approach considers details of individual farms and soils. During the project duration, three pre-existing models were further completed and interlinked with each other. The modelling approach was applied at two different levels of detail in seven different European regions to examine the effects of five agricultural policy scenarios. The core models involved were AgriPoliS, MODAM and FASSET/Farm-N. In this chapter, the modelling approach, characteristics of the models involved and the policy scenarios are introduced while results as well as details on the different modelling applications can be found in subsequent chapters of this book.

Analysing Exemplary Policy Issues Using the MEA-Scope Framework

This contribution links the activity of farming in rural areas in response to policy changes to the achievement of economic, social, and environmental policy objectives. The focus here is on a model-based evaluation of policy impacts on the supply of multifunctional activities using an indicator framework. We apply the MEA-Scope modelling approach.

Validation of an Agent-Based, Spatio-Temporal Model for Farming in the River Gudenå Landscape. Results from the MEA-Scope Case Study in Denmark

A validation of the agent-based model AgriPoliS by back casting is presented. The agent-based model AgriPoliS is calibrated to a Danish agricultural catchment. The model was supplied with empirical data on the exact location of individual plots as well as farm characteristics of 2,383 individual farms covering the period 1998–2004. Validation was carried out comparing the results of the simulation to the empirical data. The comparison shows that the model simulates development on the most aggregated level (the number of farms in the catchment) relatively well. There are some variations to the degree of precisions on less aggregated levels of analysis. The overall conclusion is that the agent-based model approach utilized here was effective in regard to prediction.

Scaling from Farm to Landscape

This chapter presents upscaling methodologies, implemented in the MEA-Scope strategic research project. MEA-scope is based on a bottom-up approach, where farm information are collected for landscapes in Germany, Slovakia, Poland, France, Hungary, Italy and Denmark. This chapter is about the upscaling from farm to landscape level, and focuses on the modelling of Nitrogen surplus from agriculture as an indicator for water pollution. It is demonstrated in detail how farm information from the Danish landscape is upscaled for such landscape level analyses, using the EU Integrated Area Control System (IACS) and GIS. Subsequently, farm N-surpluses, upscaled for each of the other the landscapes, are also presented, and different upscaling pathways are reviewed. Based on the results, advantages in the bottom-up approaches applied are emphasized. It is concluded, that bottom-up methods for upscaling are needed to convey information from research to decision-makers, and that it is important to specifically address the scale issue within the cycle of strategic research, where an iterative interaction between researchers and decision-makers is carried out. MEA-Scope is an example of a project where such interactions have been practised.

Impacts of Three Direct Payment Options on Farm Structure, Economic Performance and Production Pattern: Results from the MEA-Scope Case Study in Italy

The Mugello area in the heart of Tuscany, Italy is a traditional region in which the existence of the characteristic cultural landscape is closely linked to quality beef and dairy production. This chapter uses the MEA-Scope modelling approach that is based on the micro-economic models AgriPoliS, MODAM and FASSET, to analyse how different EU policy options affect farm structure, farm profits, and agricultural production activities in Mugello. Simulated scenarios include an assumed continuation of the Agenda 2000 policy, an introduction of a decoupled single farm payment, and a scenario without direct payments.