Stochastic scenarios for energy transition an applied general equilibrium approach

This dissertation studies how uncertainty affects technology choice and investment decision in the context of a transition towards low-carbon economies. We use multi-region dynamic applied general equilibrium models and stochastic programming. Chapter 1 deals with the uncertainty about post-2020 regional emission reduction targets. In Chapter 2, uncertainty is about the time the global economy will need to recover from the 2008 financial crisis. In Chapter 3, we propose an economic interpretation of the constraints that we imposed to limit the penetration of some technologies. In Chapter 4, we explain how the modeler‘s views of the about future structural changes are translated into benchmark scenarios and embedded in the calibration of the general equilibrium model. We also stress that these expectations affect counterfactual policy analysis. Chapter 5 illustrates this point by proposing analyzes of the impact of a carbon policy on the French economy, under alternative benchmarks scenarios that are contrasted in terms of energy efficiency gains and share of energy-intensive activities in the economy.(ECON 3) -- UCL, 201