2013
DOI: 10.2139/ssrn.2338182
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Using the Tax System to Address Competition Issues with a Carbon Tax

Abstract: This paper considers how tax reductions financed by a carbon tax could be designed to mitigate the need for specific relief for firms in select energy-intensive, trade-exposed (EITE) sectors at the six-digit North American Industry Classification System level. Providing an output-based tax credit to EITE sectors or a broad based reduction in corporate income tax rates disproportionately benefits EITE sectors thereby potentially reducing pressure for other transitional relief. Payroll tax reductions, on the oth… Show more

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Cited by 3 publications
(2 citation statements)
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“…One solution may be to price carbon emissions at a level that is acceptable in a given country context, and to use carbon revenues to protect those negatively affected or generate other growth and development benefits . For instance, cash transfers can be used to correct distributional impacts of carbon taxes, and other taxes can be reduced to enhance the efficiency and fairness of the fiscal system …”
Section: Introductionmentioning
confidence: 99%
“…One solution may be to price carbon emissions at a level that is acceptable in a given country context, and to use carbon revenues to protect those negatively affected or generate other growth and development benefits . For instance, cash transfers can be used to correct distributional impacts of carbon taxes, and other taxes can be reduced to enhance the efficiency and fairness of the fiscal system …”
Section: Introductionmentioning
confidence: 99%
“…Besides tradable intensity‐based policy regulations, various policy designs contain incentives that are equivalent to those of emission pricing with OBR. Metcalf () suggests output‐based tax credits as a practicable design in cases of carbon taxation. For the case of emissions trading instead of carbon taxation, Böhringer and Lange () and Monjon and Quirion () analyze output‐based allocation (OBA) of free quotas.…”
Section: Introductionmentioning
confidence: 99%