Climate Change Through the Lens of Macroeconomic Modeling
这篇综述聚焦于结构综合评估模型的构建与求解，强调前沿自然科学与一般均衡理论的结合，并讨论深度学习等机器学习方法如何克服计算挑战、提升政策分析的准确性和相关性。
There is a rapidly advancing literature on the macroeconomics of climate change. This review focuses on developments in the construction and solution of structural integrated assessment models (IAMs), highlighting the marriage of state-of-the-art natural science with general equilibrium theory. We discuss challenges in solving dynamic stochastic IAMs with sharp nonlinearities, multiple regions, and multiple sources of risk. Key innovations in deep learning and other machine learning approaches overcome many computational challenges and enhance the accuracy and relevance of policy findings. We conclude with an overview of recent applications of IAMs and key policy insights.