1. 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

2. 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

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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?

9. 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