Essays on Environmental Governance and Climate Impact Uncertainty

Abstract

Chapter 1 studies the links between international trade agreements, environmental regulation, and welfare in the presence of politically influential firms. The motivation comes from the observation that after decades of gradual trade liberalization, import tariffs are already low in most sectors, with little room for further cuts. As a result, modern trade agreements increasingly focus on smoothing out other traderestricting regulatory differences across countries. Such deep trade integration is often highly controversial due to concerns of a regulatory race to the bottom. This chapter builds a theoretical two-country model to analyze the strategic interactions between producers, policymakers, and industry lobbies. The results formalize how private-sector interference can lead to welfare-reducing trade agreements, especially if the lobby groups in different countries coordinate their efforts. However, policymakers can use different trade agreement designs to dilute the private sector’s influence. Chapter 2 focuses on the international governance of solar geoengineering. If deployed in a globally coordinated regime, interventions with geoengineering could reduce adverse climate change impacts. In the absence of such a regime, however, strategic incentives of individual actors might result in detrimental outcomes. This chapter investigates different international governance structures using a game of farsighted coalition formation. In this setting, a country pondering whether to leave or join a coalition anticipates that its decision could spark another (dis)integration process among the other players. In contrast to the static models of international environmental agreements, this dynamic structure enables a more realistic picture of what coalitions are likely to form and remain stable. The model also provides a unified framework for comparing different institutional arrangements for geoengineering deployment, such as consensus-based and majority-vote coalitions. Chapter 3 develops a modelling framework for estimating the long-run economic impacts of tropical cyclones. The framework combines a numerical general equilibrium model of the economy with a probabilistic disaster modelling platform. Both components are global in their regional scope, which allows a consistent comparison across countries with different disaster risk profiles. The results highlight how the recovery after a single cyclone shock can take several decades, with the negative disaster impacts accumulating quickly for the frequently exposed regions. Assumptions regarding the drivers of economic growth and climate change’s impact on future cyclone damages affect the numerical results. However, they do not change the overall qualitative conclusions. Chapter 4 explores the applicability of learning-based model predictive control for solving stochastic economic decision problems. The high computational cost of sequential decision-making under uncertainty and the long planning horizons encountered in many economic applications severely restrict the usability of conventional dynamic programming techniques in high-dimensional settings. This chapter demonstrates that learning-based model predictive control provides a promising alternative approach as it can often deliver high-quality approximate solutions with a significantly smaller computational budget. In addition, stochastic model predictive control enables an intuitive formulation of cautious behaviours that complement the conventional risk-averse decision rules. An integrated climate-economy assessment model provides a challenging environment to evaluate the proposed method.