Periodic Reporting for period 1 - PATTERN (Providing operational economic appraisal methods and practices for informed decision-making in climate and environmental policies)
Reporting period: 2022-06-01 to 2023-11-30
PATTERN’s main objective is to improve practitioners’ capacity for decision-making on climate and biodiversity policies, by developing new economic appraisal methods oriented to reduce the gap between ex-ante and ex-post evaluations. This integrated economic appraisal approach is composed of innovative models and improved methods, all integrated into a global operational approach, developed with particular attention to social acceptance, environmental justice, climate damages, and considering unpriced value and high uncertainty. An Aggregation Model Tool (AMT) is used for the micro level ex-post evaluations of actual performances of selected policies. It will then allow for the REMES-EU CGE Model to recalibrate its ex-ante estimates with ex-post results. A set of complementary economic appraisal methods will feed the first layer of the AMT and complement the REMES-EU CGE Model, such as LCA, Choice experiment, and Q-methods providing cumulative probabilities of different key aspects pointed out by the tailored theory of change.
The work carried out has been oriented to bridging ex-post and ex-ante economic appraisals, in the domain of environment and climate policies. A collection of 102 EU-wide ex-post evaluations and ex-ante assessments were collected in an online repository. The State-of-the art of economic appraisal methods has been analyzed and conceptual guidelines have been provided to identify potential bridging techniques. A block of intertwined activities aimed at providing a social nuanced and qualitative complement to the economic and quantitative component of the project’s appraisal approach were developed. The whole process was inspired by a highly participatory approach in both: (i) the adoption of a Theory of Change approach to better define the expected outcome and impacts of the policy in the medium-long run and the causal mechanisms and (ii) the provision of policy-specific sets of indicators to assess the social dimensions of the expected outcome and impacts. Tools for ex-post evaluations were applied to five selected case studies. An open-source database was created to be used and updated along the project. Regionalized accounting data from national accounts, were collected and refined. Various methodological enhancements have been implemented for ex-post analyses of case studies, including: (i) REMES CGE model was adjusted to consider sea and land resources in Aquaculture and Agriculture cases, (ii) the development of impact assessments on productivity changes in the Aquaculture case, (iii) updates to the LC-IMPACT model to include climate change impacts on ecosystem quality and marine eutrophication, (iv) the use of a Real Option approach in the Agricultural case, (v) improvements to the Carbon Handprint model to focus on climate benefits from specific regional policies, particularly in the Traffic case study in Lappeenranta and (vi) a direct mapping between the models outputs and Social Impacts (SI). AMT has been developed in order to allow for future integration of all these different assessments at the micro-level, with the distal impacts through REMES CGE model. A detailed bridging procedure between different models is described and programed.
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.
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.