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| Author: | Karp, L. Zhang, J. |
| Title: | Regulation with anticipated learning about environmental damages |
| Journal: | Journal of Environmental Economics and Management
2006 : MAY, VOL. 51:3, p. 259-279 |
| Index terms: | environmental damage global warming learning regulations taxation uncertainty |
| Language: | eng |
| Abstract: | A regulator anticipates learning about the relation between environmental stocks and economic damages. For a model with linear-quadratic abatement costs and environmental damages, and a general learning process, the authors show analytically that anticipated learning decreases the optimal level of abatement at a given information set. If learning causes the regulator to eventually decide that damages are higher than previously thought, learning eventually increases abatement. Learning also favours the use of taxes rather than quotas. Using a model that is caliberated to describe the problem of global warming, the authors show numerically that anticipated learning causes a significant reduction in first period abatement and a small increase in the preference for taxes rather than quotas. |
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