Predicting Long-run Economics of Climate Change

by Simon Bjerkholt

Predicting the future is always hard. According to a journal article written by Richard Rosen and Edeltraud Guenther predicting the net economic effects of climate change mitigation over long periods of time just might be impossible. Presently, the mode for predicting the effects of climate change mitigation on the world economy is to make predictions for the long term such as 2050 or 2100. The authors of this article argue that it would be much more effective to make plans for the short term and then adjust the plans as we learn more about the nature of the problem we are facing and the effectiveness of our attempts to stop it.

The current system of predicting climate change economics is broken for three main reasons. The first is that it is fundamentally impossible to predict the trajectory of the economy over many decades because it is so volatile and unpredictable. The inability to accurately predict the economy creates a roadblock to accurate representations of the economic viability and net cost of climate change mitigation. The second major reason is that the IAMs (integrated assessment models) used to predict the economic effects rely on many unfounded assumptions and leave out some key variables affecting the true cost of climate change mitigation. In particular, the net cost calculations leave out the positive benefits to the economy of reducing global carbon emissions. The third major issue is inconsistency. Different IAM models predicting the same scenario and same set of circumstances often yield very different results. This inconsistency only further strengthens the argument that long term modeling is completely ineffective.

In order to combat these issues, the authors suggest that we plan solutions for the short term only. This would allow us to actually begin taking action rather than spending so much time debating what our long term solutions must be.


Rosen, R., Guenther E., 2015. The economics of mitigating climate change: what can we know? Science Direct, Elsevier, 93-106.;



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