The initial outcomes of PATTERN steer towards an innovative paradigm where nature is re-envisioned not merely as a passive component but as an essential participant in decision-making processes. Employing advanced theoretical frameworks, this effort has reinterpreted socio-economic systems as complex networks of interrelated behaviors. These interlinked models are key to improving our understanding of how representing human behavior alongside natural responses, can provide policymakers with better predictive insights.
Approaches to bridge ex-ante and ex-post policy evaluations are currently lacking in economic appraisals of environmental and climate policies. Therefore, the development of conceptual guidelines and potential techniques to link both types of assessments is a novelty in the domain of policy evaluation. The implementation of complexity methodology (Stakeholder Analysis, Theory of Change and Social Impact approach) allowed to produce two main innovations: (i) the identification of the expected impacts to be assessed was developed jointly to the understanding of the underlying causal mechanisms, that supported the refinement of evaluation questions, (ii) the identification of expected SI, resulted from a constructionist approach as it was based on the practitioners’ perspectives. We have prepared the existing models for being combined in a novelty way (for example integrating Q method and DCE, or using DCE results for the AMT), to join proximal to distal impacts in a coherent framework for an improved policy assessment. In a macroeconomic perspective, the development of a routine to collect regionalized accounting data from national accounts is a notable advancement. This level of granularity in data acquisition enables more precise economic modeling. The modification of the REMES CGE model to explicitly incorporate sea and land resources for the Aquaculture and Agriculture case studies allows for a more accurate assessment of the impact of policies on these sectors, surpassing traditional economic modeling methods. The updates to the LC-IMPACT model, including the addition of new impact categories and a detailed focus on climate change impacts on ecosystems, particularly at the level of large marine ecosystems, expand the horizons of environmental impact assessment. The introduction of a Real Option approach in analyzing PAMs in the Agricultural case study allows to make considerations about the flexibility in investment decisions, providing valuable insights into decision-making under uncertainty. Additionally, the precision in defining the scope of the Carbon Handprint model from a policy perspective, focusing on specific regional policies for climate benefits, is a forward-looking approach. Lastly, the algorithmic detailing of the bridging procedure between different models supports seamless data integration, facilitating a more holistic analysis of complex economic and environmental challenges.
