Social Cost of Carbon: Revisit from a Systems Analysis Perspective

Abstract:

The Social Cost of Carbon (SCC) is estimated by integrated assessment models (IAM) and is widely used by government agencies to value climate impacts. While there is an ongoing scientific debate about the obtained numerical estimates and related uncertainties, relatively little attention has been paid so far to the SCC calculation method itself.

This work attempts to fill this gap and provides theoretical background and economic interpretation associated with the SCC calculation approach implemented in the open-source IAM DICE. The obtained results indicate that the presently employed calculation method provides only an approximate SCC value. While in some cases this approximation might work numerically pretty well, we present practical examples where it substantially (by the factor of two) deviates from the true value of the SCC. As indicated by the analytical results, the reason for this deviation is in the present calculation method, which is unable to catch the full complexity of linkages between the essential IAM's components - climate, economy, and associated human activities.

The implications of the obtained results are twofold. First, the SCC calculation method can be upgraded to avoid the bias introduced by the calculation methodology. This bias is not connected to any numerical uncertainties in the calibration of the IAM's parameters. Second, where such method upgrade seems to be problematic, a great attention needs to be paid to the obtained SCC estimates. The bias likely introduced into the assessment by employing an approximation needs to be taken into account and indicated within the total uncertainty range of the obtained SCC estimate. As IAMs reflect complex systems' inter-linkages, the associated calculation methods such as SCC should inherently preserve these inter-linkages in order to avoid bias in the resulting estimates.