As climate change threats intensify, climate mitigation has become a central focus of government policy. This paper develops a multi-sector dynamic stochastic general equilibrium model of a closed economy to examine the effects of a regional emissions trading system. The economy features multiple energy input sectors that produce either brown or green energy, as well as a final output sector that produces aggregate goods. Both the input and output sectors require energy for production, but only brown energy generates emissions upon use. Emission permits are initially allocated across sectors and then traded in a competitive permit market. We show that the carbon price emerges as the shadow value of the emissions cap in the social planner's problem and, equivalently, as the equilibrium permit price in the decentralized market. We further incorporate a penalty term that captures the region's environmental contribution. The social preference is revised to include both pecuniary and non-pecuniary benefits of emissions reductions. Comparing outcomes in the penalized and unpenalized economies highlights the economic role of this penalty.

We develop a tractable continuous-time general equilibrium model to study the social value of insurance (SVI) under rare disaster risk. In the model, capital is subject to diffusion risk and Poisson-driven jump losses, a subset of which is insurable. The social planner chooses investment and insurance coverage to maximize welfare under recursive preferences. We define the social value of insurance via a utility-indifference measure that makes an uninsured economy welfare-equivalent to an insured economy. In the baseline calibration with known disaster parameters, access to insurance is equivalent to a 7.25% increase in the economy's capital stock. We further show that deep uncertainty about disasters substantially amplifies this value. Specifically, uncertainty harms the uninsured economy disproportionately more than the insured economy, because insurance stabilizes welfare across alternative disaster regimes.

The world we live in is undergoing rapid and unprecedented changes, fraught with multi-layered uncertainties. One of the driving forces behind this is climate change. Adaptation and mitigation are two commonly used approaches for combating climate change. We consider a regional integrated climate-economy (RICE) model in which climate damages are categorized into chronic and acute ones. Regions highly vulnerable to climate disasters often prioritize adaptation over mitigation, which reduces global efforts to combat climate change. We derive the optimal regional adaptation and mitigation expenditures under this RICE model. In doing so, we account for multi-layered uncertainties, which raise both adaptation and mitigation expenditures and increase the global social cost of carbon. Extensive numerical studies are conducted to illustrate our theoretical findings.