The climate in climate economics (original) (raw)

We develop a generic and transparent calibration strategy for climate models used in economics. The key idea is to choose the free model parameters to match the output of large-scale Earth System Models, which are run on pre-defined future emissions scenarios and collected in the Coupled Model Intercomparison Project (CMIP5). We propose to jointly use four different test cases that are considered pivotal in the climate science literature. Two of these tests are highly idealized to allow for the separate quantitative examination of the carbon cycle and the temperature response. Another two tests are closer to the scenarios that arise from economic models. They test the climate module as a whole, that is, they incorporate gradual changes in CO2 emissions, exogenous forcing, and ultimately the temperature response. To illustrate the applicability of our method, we re-calibrate the free parameters of the climate part of the seminal DICE-2016 model for three different CMIP5 model responses: the multi-model mean as well as two other CMIP5 models that exhibit extreme but still permissible equilibrium climate sensitivities. As an additional novelty, our calibrations of DICE-2016 allow for an arbitrary time step in the model explicitly. By applying our comprehensive suite of tests, we show that i) both the temperature equations and the carbon cycle in DICE-2016 are miscalibrated and that ii) by re-calibrating its coefficients, we can match all three CMIP5 targets we consider. Finally, we apply the economic model from DICE-2016 in combination with the newly calibrated climate model to compute the social cost of carbon and the optimal warming. We find that in our updated model, the social cost of carbon is very similar to DICE-2016. However, a significant difference is that the optimal long-run temperature lies almost one degree below that obtained by DICE-2016. This difference in climate behavior is reflected in the over-sensitivity of the social cost of carbon to the discount rate of the social planner. We also show that under the optimal mitigation scenario, the temperature predictions of DICE-2016 (in contrast to our proposed calibration) fall outside of the CMIP5 scenarios, suggesting that one might want to be skeptical about policy predictions derived from DICE-2016.

Sign up for access to the world's latest research.

checkGet notified about relevant papers

checkSave papers to use in your research

checkJoin the discussion with peers

checkTrack your impact