State of the Art Review: Agricultural Policy Assessment Models, Tools, and Indicators

Policy Impact Assessment (IA) in agriculture has evolved significantly, moving from broad evaluations to more granular analyses. The origin and scope of IA are driven by the need to understand the multifaceted consequences of agricultural policies, ranging from economic viability to environmental sustainability. The Common Agricultural Policy (CAP), with its various pillars and targeted measures, has been a primary catalyst for developing sophisticated IA methodologies. This section delves into the historical development of policy assessment, outlining the increasing demand for evidence-based policymaking and the expansion of assessment criteria to include a wider array of socio-economic and environmental factors. The growing complexity of agricultural systems and the interconnectedness of global markets necessitate IA approaches that can capture these dynamics effectively.

The AGRICORE project places a strong emphasis on farm-level Agent-Based Models (ABMs) as a core component for policy assessment. ABMs are computational models that simulate the actions and interactions of autonomous agents (in this case, farmers) within an environment. This approach allows for a highly disaggregated representation of farmer behavior, capturing heterogeneity in decision-making, adaptation strategies, and responses to policy interventions. The review underscores the increased reliance on farm-level data and models that can represent farmers' behavior in response to targeted policy measures, such as those within Pillar II of the Common Agricultural Policy. The development of these ABMs is crucial for understanding how micro-level decisions aggregate to macro-level outcomes and for evaluating the effectiveness of specific policy instruments at the farm gate.

Agricultural practices have significant environmental and climatic footprints, and policy assessment must rigorously evaluate these impacts. This section of the review focuses on models and indicators used to assess how agricultural policies affect biodiversity, water quality, soil health, greenhouse gas emissions, and climate change adaptation and mitigation. The document highlights the importance of considering environmental impacts at various scales, from the farm level to regional and global levels. It explores tools that can quantify the environmental consequences of different policy scenarios, including agri-environmental measures, land use changes, and the adoption of sustainable farming practices. The integration of climate change considerations, such as the use of IPCC scenarios and climate reanalysis data, is also a key focus.

The performance of the agricultural sector is intrinsically linked to the dynamics of its output and input markets. This module of the AGRICORE project focuses on analyzing how agricultural policies influence market prices, trade flows, supply chains, and the availability and cost of agricultural inputs (e.g., fertilizers, seeds, machinery). The review explores models that capture these market linkages, including partial equilibrium and general equilibrium models, as well as econometric and simulation approaches. Understanding these market dynamics is essential for assessing the economic impacts of policies, such as subsidies, price support mechanisms, and trade agreements, on farm profitability, consumer prices, and the competitiveness of the agricultural sector. The interplay between policy interventions and market forces is a critical area of investigation.

This state-of-the-art review has highlighted the complex landscape of agricultural policy assessment, emphasizing the need for integrated modeling approaches. The AGRICORE project's ambition to develop a farm-level Agent-Based Model (ABM) suite that incorporates modules for policy impact assessment, socio-economic and environmental factors, ecosystem services, and market dynamics represents a significant step forward. The review has identified key methodologies, tools, and indicators that will inform the development of these modules. The success of the AGRICORE suite will depend on prioritizing development avenues based on technical capabilities and effectively filling the identified gaps in current modeling efforts. By integrating these diverse aspects, the project aims to provide a powerful tool for evidence-based agricultural policymaking, fostering more sustainable and resilient agricultural systems.