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Modelling the Energy Transition – MET is a research program aimed at studying the energy transition in dynamic settings and under uncertainty by developing economic models with both a micro and macro approach. Within the program, different types of models are studied, with the aim of exploring how different methodological approaches can have different impacts and solutions while studying environmental and energy economics.

The activities of the MET program concern two specific areas:

  1. ABM – Agent Based Model and
  2. EEUMs – Environment, Energy, Uncertainty Models.

ABM – Agent Based Model for Energy Transition
The activities in this area aim to develop Agent Based Models on multiple sectors, with a special focus on energy sectors and their environmental impacts. Using Agent Based Models allows to grasp the heterogeneity of the economic agents at sectoral level, with the goal of providing new perspectives and insights to the economic research. The program intends to consolidate the development of the MATRIX (Multi-Agent model for Transition Risks) model by including a specific module for climate change, mitigation policies and environmental awareness of households and consumers (demand-side approach). The agents’ heterogeneity of the AB Model represents the building block of the economic processes’ dynamics and makes it possible to study at best the endogenous shocks of such processes.

EEUMs – Environment, Energy, Uncertainty Models
The activities in this area aim to deepen the issue of uncertainty within the framework of environmental and energy economics, with a focus on renewable resources, the use of new technologies and the role of information for the decarbonization process. To this end, models based on the representative agent, strategic models and macroeconomic models will be used for an analysis of the dynamics of the traditional and renewable energy markets. The analysis is also focused on the study of systemic and idiosyncratic shocks at economic and environmental level and on the role of information in energy market phenomena.