11:15 〜 11:30
[ACG46-03] Feedback-adjusted carbon prices
キーワード：経済モデル、フィードバック効果、非線形性、カーボンプライス
In economics literature, linear climate emulators are prevalent and frequently used for informing policy decisions, in spite of the fact that Earth's climate is characterized by numerous non-linearlities. For instance, the effectiveness of carbon sinks may diminish due to increasing human intervention into the carbon cycle. Furthermore, recent results of Earth System Models indicate that the deep ocean's capacity to absorb heat may decrease as temperatures continue to rise. While linearly approximating a non-linear system may be a reasonable modeling strategy, it is crucial to properly account for non-linear feedback effects when they significantly alter the policy implications derived from economic analyses.
In this paper, I develop a theoretical framework to evaluate, both qualitatively and quantitatively, how optimal climate policy should be adjusted if feedback effects in the climate system are incorporated. This framework encompasses a broad range of non-linear feedback effects, including but not limited to the carbon-cycle and thermal feedback mentioned above. Allowing for feedback effects, and thus dropping the assumption of linearity, could compromise the analytical tractability of otherwise manageable models. Nevertheless, I have derived a closed-form expression for the social cost of carbon (SCC), adjusted for these feedback effects. The feedback-adjusted SCC formula allows us to distinguish between linear and non-linear impacts on optimal carbon pricing, offering new analytical insights.
My findings indicate that feedback effects considerably increase the optimal carbon price, even before the physical manifestation of these effects. Although the current climate system may be well approximated by linear models, such models are likely to underestimate the carbon price. This is because the carbon pricing formula does not only consider current feedback, but also anticipate potential future feedbacks. Moreover, the non-linear model suggests that any delay in carbon mitigation today requires greater emission reductions in the future. In the presence of feedback effects, the marginal utility damage of carbon emissions is no longer constant, making the optimal carbon price responsive to the current climate state. This result sharply contrasts with the conventional wisdom in the literature, where the cost of inaction only materializes in the form of suppressed welfare.
Integrating climate non-linearities into an analytical model also permits a transparent examination of the role of technological changes. In models without non-linear channels, the production side of the economy, including technological changes, has limited impact on carbon pricing due to the constant marginal damage implied by the assumed linearity. While numerical models can incorporate both technological changes and non-linearities, they often lack general insights. Based on the feedback-equipped analytical model, I have derived an approximate closed-form expression for the optimal carbon price, properly adjusted for future technological changes. The derived SCC formula indicates that anticipated future decarbonization lowers today's carbon price, but the quantitative impact is likely to be modest.
In this paper, I develop a theoretical framework to evaluate, both qualitatively and quantitatively, how optimal climate policy should be adjusted if feedback effects in the climate system are incorporated. This framework encompasses a broad range of non-linear feedback effects, including but not limited to the carbon-cycle and thermal feedback mentioned above. Allowing for feedback effects, and thus dropping the assumption of linearity, could compromise the analytical tractability of otherwise manageable models. Nevertheless, I have derived a closed-form expression for the social cost of carbon (SCC), adjusted for these feedback effects. The feedback-adjusted SCC formula allows us to distinguish between linear and non-linear impacts on optimal carbon pricing, offering new analytical insights.
My findings indicate that feedback effects considerably increase the optimal carbon price, even before the physical manifestation of these effects. Although the current climate system may be well approximated by linear models, such models are likely to underestimate the carbon price. This is because the carbon pricing formula does not only consider current feedback, but also anticipate potential future feedbacks. Moreover, the non-linear model suggests that any delay in carbon mitigation today requires greater emission reductions in the future. In the presence of feedback effects, the marginal utility damage of carbon emissions is no longer constant, making the optimal carbon price responsive to the current climate state. This result sharply contrasts with the conventional wisdom in the literature, where the cost of inaction only materializes in the form of suppressed welfare.
Integrating climate non-linearities into an analytical model also permits a transparent examination of the role of technological changes. In models without non-linear channels, the production side of the economy, including technological changes, has limited impact on carbon pricing due to the constant marginal damage implied by the assumed linearity. While numerical models can incorporate both technological changes and non-linearities, they often lack general insights. Based on the feedback-equipped analytical model, I have derived an approximate closed-form expression for the optimal carbon price, properly adjusted for future technological changes. The derived SCC formula indicates that anticipated future decarbonization lowers today's carbon price, but the quantitative impact is likely to be modest.