Ambiguity Reduction by Objective Model Selection, with an Application to the Costs of the EU 2030 Climate Targets

Energies

Richard S. J. Tol¹ 

[1] Department of Economics, University of Sussex, Jubilee Building, Falmer BN1 9SL, UK; E-Mail:

关键词: climate policy;    European Union;    carbon price;    forecast skill;    uncertainty;   

DOI  :  10.3390/en7116886

来源: mdpi

【 摘 要 】

I estimate the cost of meeting the EU 2030 targets for greenhouse gas emission reduction, using statistical emulators of ten alternative models. Assuming a first-best policy implementation, I find that total and marginal costs are modest. The statistical emulators allow me to compute the risk premiums, which are small, because the EU is rich and the policy impact is small. The ensemble of ten models allows me to compute the ambiguity premium, which is small for the same reason. I construct a counterfactual estimate of recent emissions without the climate policy and use that to test the predictive skill of the ten models. The models that show the lowest cost of emission reduction also have the lowest skill for Europe in recent times.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.