Work Package 1: Assessing current modelling practices Thomas Schinko, Gabriel Bachner, Karl Steininger Wegener Center for Climate and Global Change, University of Graz April 24, 2015 WIFO, 1030 Wien ClimTrans2050

WP1 Guiding question: What kind of modeling framework is most suitable for assessing the long-term transformation processes needed to drastically reduce Austria’s GHG emissions?  meta-analysis of state-of-the-art GHG-energy-economic modeling approaches with respect to their ability and limitations to develop pathways for a low carbon society and economy

WP1 3 steps:  categorization of the different modeling approaches  focus on characteristics that are relevant for a model to be suitable for long term transition analyses  identify specific “prototypical” models  evaluate these different GHG-energy-economic modeling approaches in terms of their strengths and weaknesses to carry out low carbon transition analyses and discuss their advantages and disadvantages

Step 1 - categorization of the different modeling approaches  A general characteristic: a model always is a purposeful and simplified representation of aspects of reality (Starfield et al., 1990)  Purposeful: a model is developed in order to answer a specific research question  Simplification: purpose already paves the way for a simplified representation, but also “real world constraints” (limited time and financial resources)  Besides, there are many individual characteristics which differ substantially between modeling approaches  classify existing GHG-energy-economic modeling approaches and specific models to allow for an identification of the most appropriate approach  From literature and discussions of the project team, we identify the most important dimensions

Step 1 - categorization of the different modeling approaches 8 dimensions: 1.The purpose and intended use 2.The analytical approach and conceptual framework  Top-Down, Bottom-Up, Integrated Assessment/hybrid model 3.Model features and mechanisms; external assumptions 4.The time horizon 5.The underlying methodology  Optimization, Simulation, Econometric, Equilibrium etc.  estimation vs. calibration 6.The treatment of path dynamics (Static VS Dynamic) 7.Geographical and sectoral coverage 8.Data requirement

Step 1 - categorization of the different modeling approaches Identified approaches (defined by underlying methodology):  Econometric methods in energy modeling  Dynamic New Keynesian Input-Output Models  Neoclassical Economic Equilibrium Models  System Dynamics and Simulation Models  Backcasting Models  Optimization Models  Partial Equilibrium Models  Multi agent or Agent Based Models

Step 2 - identify specific “prototypical” models (Selection of) prototypical models:  DYNK (Dynamic New Keynesian Input-Output Model)  PRIMES (Partial equilibrium model)  POLES (Simulation/System Dynamics model)  GEM-E3 (Neoclassical Economic Equilibrium model [CGE])  MARKAL/TIMES (Optimization model)  GAINS (Integrated/Hybrid model)  to be continued

Step 3 – Evaluation of strengths and weaknesses (ongoing)  Important model features/mechanisms for long term low carbon transition analyses. E.g.:  Disruptive, Non-linear (endogenous) technological change  Technological detail  Energy cascade  Price and market mechanisms  Financing investments  (Macro-)economic feedbacks and rebound effects  Non-market mechanisms (e.g. non-market damages of CC)  Stocks and flows  Institutions  Behavioral mechanisms  Risk and uncertainty  International trade Any other?

Step 3 – Evaluation of strengths and weaknesses (ongoing) Next steps:  Evaluate prototypical models with respect to important model features and mechanisms  Give recommendations for WP5 (Research plan for an open source model)  What are crucial features an open source model should cover  Applicable existing modeling approaches  Building on strengths of existing models for sub-modules