26 June 2019

Evolution of Modeling of the Economics of Global Warming: Changes in the DICE Model, 1992-2017

Economic projections are the least precise parts of IAMs and deserve much greater study than has been the case up to now, especially careful studies of long-run economic growth.

Science

Many areas of the natural and social sciences involve complex systems that link together multiple physical or economic sectors. In this role, integrated assessment analysis and models play a key role. Integrated assessment models (IAMs) can be defined as approaches that integrate knowledge from two or more domains into a single framework. One of the major shortcomings of IAMs is that their structure makes it extremely difficult to use standard econometric techniques to assess their reliability—a feature that is shared with earth systems models and other large simulation models.

Impact

In the absence of statistical tests, the present study examines the extent and area of revisions of the DICE model from its earliest publication in 1992 to its latest version published in 2017 and 2018. This retrospective gives a flavor for changes in the underlying economic and earth sciences, data revisions, correction of mistakes, and the pure passage of time. Also, for those estimates that have included estimated errors in past studies, it is possible to compare the actual revisions with the estimated errors. The projections of most environmental variables (such as emissions, concentrations, and temperature change) have seen relatively small revisions (with the emphasis here on relatively). However, there have been massive changes in the projections of the economic variables, including those that were forecast in 1992 and have now been realized in 2017. The stability of the environmental variables largely reflects the fact that these processes were relatively well-understood by the early 1990s, and, therefore, modeling of these components within IAMs could be based on a solid scientific foundation.

Summary

Many areas of the natural and social sciences involve complex systems that link together multiple sectors. Integrated assessment models (IAMs) are approaches that integrate knowledge from two or more domains into a single framework, and these are particularly important for climate change. One of the earliest IAMs for climate change was the DICE/RICE family of models, first published in Nordhaus (Science 258:1315–1319, 1992a), with the latest version in Nordhaus (2017, 2018). A difficulty in assessing IAMs is the inability to use standard statistical tests because of the lack of a probabilistic structure. In the absence of statistical tests, the present study examines the extent of revisions of the DICE model over its quarter-century history. The study finds that the major revisions have come primarily from the economic aspects of the model, whereas the environmental changes have been much smaller. These results indicate that the economic projections are the least precise parts of IAMs and deserve much greater study than has been the case up to now, especially careful studies of long-run economic growth (to 2100 and beyond). Additionally, the approach developed here can serve as a useful template for IAMs to describe their salient characteristics and revisions for the broader community of analysts.

Contact
John Weyant
Stanford University