There is general agreement among economists and climate policy practitioners that carbon pricing should play a central role among progressive policies used to tackle climate change effectively. However, in most jurisdictions that have adopted carbon pricing mechanisms (CPMs), the prevailing price levels are too low to accelerate decarbonization and drive down emissions. The gap between these prices and the prices aspired by the scientific community to hold climate change to levels tolerable for humanity produces the ‘carbon price gap.’ This gap can be largely attributed to numerous political economy constraints, but most pressingly, the regressive effects on low-income households and the blow to firms’ competitiveness. Indeed, the (re)distribution impact of stringent carbon pricing policies can be substantial and ignite opposition from firms and households unwilling to pay the relatively high cost of mitigating climate change.
My theoretical premise is that this political impasse can be ameliorated (or at least the effects mitigated) by utilizing the incentive structures of carbon pricing more effectively. This climate policy is unique in generating substantial revenue for states, that can then be employed to offset negative social reverberations, build long-lasting political coalitions behind stringent policies, and provide immediate social benefits. Good use of these mechanisms could change the challenging cost-benefit structure of pricing carbon, and modify public perception on fairness, environmental effectiveness and competitiveness — all of which could ultimately lead to higher political acceptability and thus more stringent policy implementation. Following this line of reasoning, varying price levels between countries might be explained by how governments use the revenue generated by carbon pricing to address distributional effects. Nevertheless, contextual differences (e.g., fossil fuel usage and income inequality) also matter because they require the prescription of disparate revenue recycling strategies to accommodate different social objectives. Thus, these two sets of factors will be analyzed in relationship to one another. My assumptions are tested through cross-case analysis of existing national-level CPMs, employing the method of fuzzy-set Qualitative Comparative Analysis (fsQCA).