Search results

The purpose of this paper is to re-examine the long-run relationship between radiative forcing (including emissions of carbon dioxide, sulphur oxides, methane and solar radiation) and temperatures from a structural time series modelling perspective. The authors assess whether forcing measures are cointegrated with global temperatures using the structural time series approach.

A Bayesian approach is used to obtain estimates that represent the uncertainty regarding this relationship. The estimated structural time series model enables alternative model specifications to be consistently compared by evaluating model performance.

The results confirm that cointegration between radiative forcing and temperatures is consistent with the data. However, the results find less support for cointegration between forcing and temperature data than found previously.

Given considerable debate within the literature relating to the “best” way to statistically model this relationship and explain results arising as well as model performance, there is uncertainty regarding our understanding of this relationship and resulting policy design and implementation. There is a need for further modelling and use of more data.

There is divergence of views as to how best to statistically capture, explain and model this relationship. Researchers should avoid being too strident in their claims about model performance and better appreciate the role of uncertainty.

The results of this study make a contribution to the literature by employing a theoretically motivated framework in which a number of plausible alternatives are considered in detail, as opposed to simply employing a standard cointegration framework.