Conference Agenda

Integrated Assessment Models (IAMs) are essential tools for exploring climate change mitigation pathways, but they typically generate emission scenarios only until 2100. To address the growing need for longer-term scenarios beyond 2100, we developed an emulator of the IAM REMIND-MAgPIE. This emulator, emIAM, captures the behavior of the IAM by using marginal abatement cost (MAC) curves for three major greenhouse gases (GHGs), two sectors, and five carbon dioxide removal (CDR) techniques. We coupled emIAM with the reduced-complexity climate model ACC2 to generate a suite of internally consistent scenarios extending to 2300, targeting a range of temperature stabilization levels with varying overshoot profiles. These scenarios go beyond previously employed idealized approaches by incorporating the emulated dynamic response of the IAM and by explicitly characterizing CDR deployment pathways. Our scenarios serve as input to Earth System Models (ESMs) investigating the long-term consequences of climate change mitigation strategies, particularly the implications of CDR deployment and associated Earth system dynamics over centennial timescales. Furthermore, the modular design of the IAM emulator facilitates coupling with other reduced-complexity climate models, broadening its applicability for exploring climate-economic interactions.

We develop a global structural transformation integrated assessment model to study the interactions between the sectoral reallocation of economic activity, climate change and mitigation policies. The model integrates climate-economy interactions and sectoral heterogeneity in climate vulnerabilities and mitigation capabilities. We quantify distributional effects across regions and sectors due to damages from climate change and global coordination of mitigation efforts. We find that damages lead to regional variations in labor reallocation, with lower-income regions experiencing large shifts into the agriculture sector. Global coordination of mitigation efforts leads to a decrease in global CO2 emissions, welfare gains for developing regions, and a decrease in emission intensity in all regions. On the sectoral level, we observe a general shift towards services, where production is less emission intensive and substitution of energy sources easier. Sub-Saharan Africa experiences short-term growth in the manufacturing sector in order to increase the investments required to lower damages and sustain economic growth. The contribution of structural transformation in the reduction of emission intensity varies significantly between regions, and depending on if mitigation-related energy system investments are possible. Further results suggest that in low-income countries, increasing climate damages may trap labor in the agricultural sector, threatening to disrupt their development.

Many emerging economies tend to rely to an important extent on carbon-intensive sectors, generating exposure to the potential realization of transition risk. This paper quantifies the impact of such realization and the role of various policies and policy de-signs to potentially mitigate it. It does so with a two-country two-sector environmental dynamic stochastic general equilibrium model, where each ”country” represents a block of advanced or emerging economies, respectively. The model includes real-world features such as financial frictions and financial and trade linkages across blocks. With it, we simu-late climate policy in advanced economies, under the form of carbon taxes, including with carbon tariffs on top. This paper identifies and quantifies important vulnerabilities among emerging economies to the implementation of climate policy in advanced economies.

This paper operationalises Cost-Benefit-Risk Analysis (CBRA), an innovative framework that integrates well-known socioeconomic impacts into decision-making for global mitigation efforts by extending target based Cost-Risk Analysis (CRA). CBRA bridges trade-off-based approaches and target-driven methods while maintaining dynamic consistency within utility maximization, surpassing limitations of traditional Cost-Effectiveness Analysis. By updating the MIND model with the FaIR climate module and a new simplified uncertainty scheme focused on climate sensitivity, the paper enhances computational feasibility in policy optimization. Furthermore, it introduces a novel damage function derived from a forward-looking Computable General Equilibrium (CGE) model, emphasizing that direct calculation of global losses captures essential economic interactions overlooked in traditional methods. This approach highlights the transparency and specificity of CGE-derived damages, aligning them with the forward-looking nature of policy-optimizing Integrated Assessment Models. CBRA quantifies how much of the unknown risks in climate targets are addressed by these explicit damage functions, effectively mediating between target-based and trade-off-based perspectives.

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 \cite{al-aradi_extensions_2022}. Our preliminary findings indicate that misspecification and ambiguity aversion can give rise to a wide variety of transition strategies, including reductions in output growth and lower reliance on uncertain technologies, like negative-emission mitigation options