Working Paper: CEPR ID: DP16065
Authors: Christian Traeger
Abstract: The paper analyzes optimal climate policy under uncertainty. It endows a recent quantitative analytic integrated assessment model (IAM) with long-run risk, adapting methods from the asset pricing literature to deal with endogenous climate risk. The model solves in closed-form for general degrees of risk aversion, stochastic climate feedbacks, and a stochastic damage-adaptation process. The model permits an exact solution of the infinite horizon stochastic fixed-point problem of a complex IAM. The approach facilitates new quantitative evidence for the role of uncertainty as well as analytic insights into the drivers and sensitivities of the optimal carbon tax facing an uncertain future.
Keywords: climate change; integrated assessment; uncertainty; risk aversion; social cost of carbon; damages; adaptation; long-run risk; endogenous risk; stochastic volatility
JEL Codes: Q54; H23; H43; E13; D80; D61
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Uncertainty over carbon flows (Q54) | Optimal tax level (H21) |
| Uncertainty about temperature feedbacks (D89) | Risk premium (G19) |
| Nonlinearity of greenhouse effect (Q54) | Uncertainty about temperature feedbacks (D89) |
| Increased uncertainty (D89) | Higher optimal carbon taxes (H21) |
| Time preference (D15) | SCC under uncertainty (D80) |
| Uncertainty in carbon flows, temperature dynamics, and damages (Q54) | Optimal carbon tax (H21) |
| Perceived severity of climate change (Q54) | Risk premium (G19) |
| Endogenous risk derived from perturbing climate system (Q54) | Optimal carbon tax (H21) |