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on Resource Economics |
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Issue of 2019‒04‒01
three papers chosen by |
| By: | William Brock; Anastasios Xepapadeas |
| Abstract: | We study climate change policies using the novel pattern scaling approach of regional transient climate response, to develop a regional economy-climate model under conditions of deep uncertainty associated with: (i) temperature dynamics, (ii) regional climate change damages, and (iii) policy in the form of carbon taxes. We analyze cooperative and noncooperative outcomes. Under deep uncertainty, robust control policies are more conservative regarding emissions, the higher the aversion to ambiguity is, while damage uncertainty seems to produce more conservative behavior than climate dynamics uncertainty. As concerns about uncertainty increase, cooperative and noncooperative policies tend to move close together. Asymmetries in concerns about uncertainty tend to produce large deviations in regional emissions policy at the noncooperative solution. We calculate the cost of robustness in terms of welfare. If aversion to ambiguity is suciently high, optimal regulation might not be possible. The result is associated with the existence of regional hot spots and temperature spillovers across regions, a situation which emerges in the real world. In such cases, deep uncertainty about the impacts of climate change makes robust regulation infeasible. We show that, if resources are devoted to learning, which reduces uncertainty concerns, robust regulation is facilitated. |
| Keywords: | Regional temperature anomalies, Deep uncertainty, Cooperative solution solutions, Robust Open Loop Nash Equilibrium, Cost of Robustness, Learning |
| JEL: | Q54 Q58 D81 |
| Date: | 2019–03–23 |
| URL: | http://d.repec.org/n?u=RePEc:aue:wpaper:1903&r=all |
| By: | Kirill Borissov (European University at Saint Petersburg, Russia); Lucas Bretschger (ETH Zurich, Switzerland) |
| Abstract: | We derive the optimal contributions to global climate policy when countries differ with respect to income level and pollution intensity. Countries's growth rates are determined endogenously, and abatement effciency is improved by technical progress. We show that country heterogeneity has a crucial impact on optimal policy contributions: more developed countries have to make a larger effort while less developed countries are allowed to graduate under a less stringent environmental regime. The optimal allocation of pollution per- mits depends on international trade. In the absence of international permit trade, more developed countries should receive more permits than the less developed countries but permit prices are higher in the rich countries. With international permit trade, more developed countries receive less permits than the less developed. When global distribution of physical capital is uneven and the aggregate pollution ceiling is low, poor countries receive all the permits and incomes do not converge, even with free trade. |
| Keywords: | Climate policy, growth, abatement efficiency, policy convergence |
| JEL: | Q43 O47 Q56 O41 |
| Date: | 2018–10 |
| URL: | http://d.repec.org/n?u=RePEc:eth:wpswif:18/297&r=all |
| By: | Davide Cerruti (ETH Zurich, Switzerland); Claudio Daminato (ETH Zurich, Switzerland); Massimo Filippini (ETH Zurich, Switzerland) |
| Abstract: | Isolating the role of limited knowledge, psychological frictions and policy characteristics is key when evaluating a public program and designing future policies. This paper explores the role of awareness about the presence of fiscal programs in determining their impact on individual choices. Our identification strategy exploits quasi-experimental variation in the introduction of fiscal incentives aimed at promoting the purchase of energy efficient vehicles, and a direct measure of policy awareness at the individual level. We find an important impact of awareness on consumers’ vehicle choices, highlighting that limited awareness may represent a critical barrier to the effectiveness of public programs. |
| Keywords: | Policy awareness, Fiscal programs, Environmental taxation, Vehicle choices |
| JEL: | D12 D83 H23 H31 Q48 |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:eth:wpswif:19-316&r=all |