Solving stochastic climate-economy models: A deep least-squares Monte Carlo approach
ETH Zurich（苏黎世联邦理工学院）；Vienna University of Economics and Business（维也纳经济与商业大学）；Macquarie University（麦考瑞大学）；Institute of Statistical Mathematics（统计数学研究所）；Norwegian University of Science and Technology（挪威科技大学）
Aleksandar Arandjelović, Pavel V. Shevchenko, Tomoko Matsui, Daisuke Murakami, Tor A. Myrvoll
Stochastic versions of recursive integrated climate-economy assessment models are essential for studying and quantifying policy decisions under uncertainty. However, as the number of state variables and stochastic shocks increases, solving these models via deterministic grid-based dynamic programming (e.g., value-function iteration / projection on a discretized grid over continuous state variables, typically coupled with discretized shocks) becomes computationally infeasible, and simulation-based methods are needed. The least-squares Monte Carlo (LSMC) method has become popular for solving optimal stochastic control problems in quantitative finance. In this paper, we extend the application of the LSMC method to stochastic climate-economy models. We exemplify this approach using a stochastic version of the DICE model with five key uncertainty sources highlighted in the literature. To address the complexity and high dimensionality of these models, we incorporate deep neural network approximations in place of standard regression techniques within the LSMC framework. Our results demonstrate that the deep LSMC method can be used to efficiently derive optimal policies for climate-economy models in the presence of uncertainty.
The role of money and the financial sector in energy-economy models used for assessing climate policy
Cambridge Econometrics Ltd（剑桥计量经济学有限公司）；Faculty of Science, Radboud University（拉德堡德大学理学院）；Cambridge Centre for Environment, Energy and Natural Resource Governance (C-EENRG), University of Cambridge（剑桥大学环境、能源和自然资源治理中心）
The Social Cost of Carbon with Economic and Climate Risks
Becker Friedman Institute at the University of Chicago（芝加哥大学贝克弗里德曼研究所）；Hoover Institution（胡佛研究所）；Department of Business Administration, University of Zurich（苏黎世大学工商管理系）
Equity Implications of Net-Zero Emissions: A Multi-Model Analysis of Energy Expenditures Across Income Classes Under Economy-Wide Deep Decarbonization Policies
Robustness to Model Uncertainties Drives More Rapid CO2 Emissions Reductions
Stanford University（斯坦福大学）；Princeton University（普林斯顿大学）；Environmental Protection Agency（美国环境保护署）；Dartmouth College（达特茅斯学院）；University of California Berkeley（加州大学伯克利分校）
