Emissions trading systems and social equity: A CGE assessment for China.

Highlights • The impact of the ETS on social equity is assessed. • A dynamic CGE model with disaggregated labor and household sectors is developed. • Employment in China's coal industry will decline by 75% in 2030 in the ETS scenario. • ETS revenue will peak at 2278 billion yuan in 2042 in our scenario. • ETS revenue redistribution can reduce the Gini coefficient by 10% compared to BAU. Abstract Carbon dioxide emissions trading systems (ETS) are an important market-based mitigation strategy and have been applied in many regions. This study evaluates the potential for a national ETS in China. Using a dynamic computable general equilibrium (CGE) model with detailed representations of economic activity, emissions, and income distribution, we examine alternative mitigation policies from now until 2050. Based on statistical and survey data, we disaggregate the labor and household sectors and simulate the impacts of ETS policies on the incomes of different household groups. We find that ETS has the potential to reconcile China's goals for sustained, inclusive, and low-carbon economic growth. Results show some key findings. First, the number of unemployed people in energy-intensive industries such as coal and construction will continue to increase; by 2050, employment in the coal industry will decline by 75%. Second, if the scope of the carbon market extends to all industries in China, carbon market revenues will continue to increase, reaching a maximum of 2278 billion yuan ($336 billion) in 2042 to become the world's largest carbon market. Third, the distribution of benefits from the national ETS can help achieve greater social equity. By comparing different distribution policies, we find that the combination of targeted subsidies for unemployed coal workers and direct household subsidies based on proportional per capita will reduce the social income gap to the greatest extent compared with other scenarios. By 2050, this distribution policy will reduce the Gini coefficient in China by 10% compared to the Business as Usual (BAU) scenario. [ABSTRACT FROM AUTHOR]