Towards a distributionally painless carbon tax through revenue recycling

Carbon taxation is widely seen by economists as one of the top instruments for reducing greenhouse gas emissions and achieving ambitious decarbonization targets. Yet, despite its efficiency, it often faces public opposition, mainly driven by distributional concerns. A broad consensus in the literature holds that, in the absence of revenue recycling, carbon taxes tend to be regressive, disproportionately burdening low-income households. Consequently, a substantial body of research has focused on designing compensatory mechanisms,such as lump-sum rebates, tax shifts or targeted transfers, to restore progressivity and improve public acceptability.

While these approaches have provided important insights, they often conflate two distinct objectives: making carbon taxation more progressive on average, and reducing the heterogeneity and intensity of its adverse impacts across households. In practice, large disparities in energy consumption and bills persist even within standard socioeconomic groups (e.g. income deciles or geographic areas), meaning that the households most negatively affected by carbon pricing are not always those conventionally identified as vulnerable. In this paper, we therefore focus on the latter objective, namely reducing the “painfulness” of carbon taxation rather than progressivity per se. We argue that an effective compensation scheme should primarily protect households facing large increases in energy costs, smooth the distribution of impacts, avoid overcompensation of lightly affected households and preserve incentives to reduce carbon-intensive energy use. In this perspective, the change in the Energy Effort Rate (EER), that is the variation in the share of household income devoted to energy expenditures following a carbon price increase, emerges as a relevant indicator of household vulnerability.

We use the Prometheus microsimulation model, developed at the French General Commission for Sustainable Development, to analyze the distributional effects of alternative revenue-recycling schemes in France. Prometheus provides a fine-grained simulation of households’ energy bills for housing and transport, accounting for own- and cross-price elasticities, and is specifically designed to assess the impact of energy transition policies and compensatory measures. Using 2019 as the baseline year, we simulate a €10/tCO₂ increase in the carbon tax and compare three polar, budget-neutral redistribution scenarios, each leading to identical aggregate CO₂ emissions from household energy consumption: (i) a reduction in electricity taxation, in the context of France’s low-carbon electricity mix (ii) a uniform lump-sum rebate, and (iii) a progressive lump-sum rebate targeted at the bottom 50% of the income distribution. The microsimulation framework allows us to characterize the full distribution of changes in households’ EER under each scenario.

Our results highlight important trade-offs between progressivity and the smoothing of impacts from carbon taxation. While the targeted lump-sum rebate is the most progressive scheme by construction, it performs poorly in reducing the dispersion of changes in EER, leaving a non-negligible fraction of households exposed to substantial increases. The uniform rebate and the electricity tax shift exhibit comparable average redistributive profiles, but differ in their ability to smooth the impact of carbon taxation. Although the uniform rebate is slightly more progressive, the electricity tax shift consistently minimizes extreme variations in the EER and achieves the lowest overall dispersion according to several quantitative indicators.

Overall, our findings show that some revenue-recycling instruments, when carefully designed to account for context-specific energy and institutional conditions, can effectively smooth the burden of carbon taxation across households and thereby help improve public support for carbon pricing without compromising its environmental effectiveness.