Fondazione Eni Enrico Mattei (FEEM) and the Euro-Mediterranean Centre on Climate Change (CMCC) organise the International Workshop on "Numerical Climate Coalition Models: A Modelling Comparison Exercise"to be held on January 24th-25th, 2013 on the Island of San Giorgio Maggiore, Venice, Italy.

About the workshop

The workshop aims at discussing results from a comparison exercise using state-of-the art numerical climate coalition models.
Accordingly, the workshop will be structured along the following objectives:

  • Provide an overview of findings from the modeling comparison. In particular, which robust strategies can be identified in view of the current stalemate of international climate policy negotiations?
  • Enhance the understanding of existing coalition models. How do differences in model structure and calibration of key parameters such as mitigation costs and damages explain different outcomes?
  • Identify results that are robust or diverging across models. Are there outcomes e.g. regarding size, composition and welfare ranking of coalitions that are robust across models? Are there characteristic patterns of coalition formation and strategic choices of major players such as USA, China, and Europe?
  • Identify gaps in research. Which questions are particularly relevant given the current state of international climate policy negotiations? How may a climate coalition model comparison exercise move the community beyond the current state of literature?

    • Numerical models are used to explore climate coalition formation in an empirically based cost-benefit structure. Two topics where these numerical models give particularly valuable insights beyond those from their analytical counterparts are
    (i) the impact of asymmetry, i.e. the regional heterogeneity observed across the world, and (ii) quantitative estimates (of the order-of-magnitudes), in particular when trade-offs leave the net effects on, say, coalition stability or free-riding incentives ambiguous.
    For these questions, both the mechanics and the calibration of the models are of central importance, but the uncertainties are large. It is hence an asset of this comparison exercise to use multiple models: this will make uncertainty more transparent, help to identify robust results, and enable learning from the differences.

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    The workshop is upon invitation only.