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on Resource Economics |
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Issue of 2017‒07‒30
two papers chosen by |
| By: | Ross McKitrick (Department of Economics, University of Guelph, Guelph ON Canada) |
| Abstract: | This paper makes two contributions to the economics of pollution policy. First, many studies have looked at the effects of emission taxes in the absence of regulations and vice versa, but the implications for optimal tax design when one is layered on top of the other have been ignored, even though the practice is commonly observed. I develop a model of multiple polluting sectors capable of providing a tractable characterization of this case. Second, numerical modeling has shown that tax interactions can yield a positive damage threshold below which any emission tax is welfare-reducing even if marginal damages are positive, but this has largely been ignored in both the theoretical and policy literatures. I show that a positive damage threshold occurs when the policy is not revenue-raising and/or the rest of the tax system is not optimized, but can also occur in a second-best context with optimal taxes and full revenue-recycling, a result not previously shown. Introducing a pollution tax when one firm is already subject to an emissions constraint yields a positive damage threshold that goes up, the more the regulation distorts the income tax base. Hence, under more general conditions than have previously been realized, pollution taxes are not guaranteed to raise welfare even when marginal damages are positive and revenues are fully recycled. |
| Keywords: | emissions taxes, tax interactions, second-best, carbon taxes |
| JEL: | H21 H23 Q54 Q58 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:gue:guelph:2017-05&r=res |
| By: | Kitessa, Rahel Jigi (Tilburg University, Center For Economic Research) |
| Abstract: | Standard economic theory suggests that agents make decision based on the outcomes. Subsequently, environmental valuation using contingent valuation method (CVM) assumes the agent’s valuation of a given environmental good is based on the (expected) results. However, Bulte et al. (2005) found that causes in addition to outcomes matter in valuation. I extended this notion to contribute to design of CVM that attenuate free riding, thus remove the downward bias of method. I used field experiment and tested if designing a scenario that reinforce responsibility in decision making (valuation), attenuates free riding. I do so by eliciting contributions to a reforestation program among farmers in an environmentally valuable area, the Bale eco-Region in Ethiopia, by including or omitting explicit information that one of the main forest related activities the respondents engage in, logging, is among the most important causes of local forest degradation. I find that explicitly stating that logging is one of the main causes of deforestation increases our respondents’ willingness to pay. More interestingly, I find that this “responsibility effect” is sufficiently strong to eliminate free rider behavior. When the information about the cause of deforestation is in place, the respondents’ willingness to pay for the reforestation project is not significantly different if they are informed of other forest protection projects, or not. |
| Keywords: | valuation of environment; incentive compatible valuation techniques; conservation; field experiment; forestry; public goods |
| JEL: | C93 D04 H41 O13 Q51 Q23 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:tiu:tiucen:3d1f1a62-d62a-44d3-8c8a-65bad2f0d7a8&r=res |