Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Climate Policy Under Uncertainty Location: B127 Session Chair: Louis Daumas, EIEE | |
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Ambiguity and model misspecification with potentially disruptive mitigation options 1: EIEE, Italy; 2: Politecnico di Milano, Italy This paper aims to explore the impact of ambiguity, ambiguity aversion, and model misspecification on mitigation dynamics when several mitigation options are considered. It develops a continuous-time endogenous-growth economic model allowing for ambiguity and model misspecification on (i) climate and investment dynamics and (ii) uncertainty around technological jumps for potentially disruptive decarbonisation technologies. The model further innovates by considering a relative degree of technology richness, by representing emission-free capital, carbon intensity reductions and negative-emission technologies. Given the high dimensionality of the model and the inherent difficulties encountered in optimal control in the presence of misspecification corrections, we solve the model using a recent deep learning method to solve complex high-dimensional partial differential equation, the Deep-Galerkin Method with Policy Iteration Algorithm (DGM-PIA) proposed by Al-Aradi et al. (2022). Our preliminary findings indicate that misspecification and ambiguity aversion can give rise to a wide variety of transition strategies, including lower reliance on uncertain technologies, like negative-emission mitigation options. | |