Poverty and inequality implications of carbon pricing under the long-term climate target

Abstract

Many countries have taken stringent climate policies to minimize the risks by climate change. But these policies could burden households and the poor with the extra costs and threaten their wellbeing. However, the consequences of climate policies on poverty and welfare loss are seldom presented in stringent long-term climate change mitigation projections. Carbon pricing is a cost-effective approach; how it affects households varies among countries. This study investigated the distributional effects and poverty implications of carbon pricing in China during the transition towards carbon neutrality and the Paris Agreement’s long-term goals. We assessed multiple poverty and equity standards in future scenarios with a newly developed integrated assessment model. It was found that climate change mitigation efforts would not greatly hinder poverty alleviation in China, with the poverty headcount under the $3.2/cap/day-threshold being less than 0.3 million people in 2050 in most scenarios. A carbon tax became a regressive factor mainly due to price increases in food and energy goods. This indicates that the distributional effects on carbon pricing should be considered. For example, supplementary policies that compensate for price changes, such as subsidies and early mitigation actions, that lead to modest price increases in the long term are worthy of consideration as valid instruments for the just transition towards the 2 °C or even 1.5 °C pathway.

Carbon Pricing Drives Critical Transition to Green Growth

“…Shocks of −50% and +50% in fossil fuel prices are applied for two years, reverting to a baseline price thereafter. Lower-income and wealth groups are more affected by these shocks, with effects being more persistent for wealth than income and in line with recent empirical observations [65]. For higher income groups, real income reductions are offset by increases in capital income, explaining their quicker recovery.…”

Realizing the full potential of behavioural science for climate change mitigation

“…We thus agree with calls for a "heterogeneity revolution" in behavioral science 112 , for better considering and integrating contextual and structural factors in intervention design, and for broadening and diversifying studied populations 110 (even though Western populations bear disproportionate responsibility for GHG emissions 69 ). Examining heterogeneity in intervention effects is also critical for assessing the accessibility of interventions for economically disadvantaged or marginalized individuals 15 , such as access to subsidies or tax incentives, and addressing unintended distributional impacts of interventions 113,114 .…”

Who pays for higher carbon prices?

“…Hynes and O'Donoghue (2014 [24]) provide a broad review of the use of microsimulation models to inform environmental policy. The distributional implications of carbon taxes have been analysed by Casler and Rafiqui (1993[61]) and Mathur and Morris (2014 [62]) in the USA, Hamilton and Cameron (1994[63]) in Canada, Pearson and Smith (1991[49]), Symons et al (1994[64]) and Symons et al (2002[65]) in the United Kingdom, Cornwell and Creedy (1997 [66]) and Creedy and van de Ven (1997 [67]) in Australia, Callan et al (2009[46]) and O'Donoghue (1997 [68]) in Ireland, Bach et al (2002[69]) and Bork (2006[70]) in Germany, Kerkhof et al (2009[71]) in the Netherlands, Poltimäe and Võrk (2009[72]) in Estonia, Labandeira and Labeaga (1999 [73]), Labandeira et al (2009[74]) and Garcia-Muros et al (2017 [75]) in Spain, Bureau (2011[76]) and Berry (2019 [43]) in France, Vandyck and Van Regemorter (2014 [77]) in Belgium, Yusuf & Resosudarmo (2015 [78]) in Indonesia, and Rosas-Flores (2017 [79]) in Mexico.…”