Computable general equilibrium analysis of neutral carbon trading scheme and revenue recycling impacts on income distribution in China

The study investigates how revenue-neutral emissions trading schemes (ETS) in China—implemented via government subsidies or VAT reductions—affect macroeconomic performance, sectoral output, energy consumption, and income distribution while pursuing China’s peak carbon emissions target before 2030. Motivated by the expansion of China’s national ETS (electricity sector from 2021–2022 and eight energy-intensive sectors from 2023 onward), the research examines whether recycling carbon market revenues back to production sectors can mitigate the economic distortions of carbon pricing, accelerate carbon peaking, optimize the energy mix, and enhance social equity. The purpose is to provide evidence-based policy guidance on the design of neutral revenue recycling that balances environmental, economic, and distributional objectives.

The paper situates its contribution within CGE-based analyses of carbon pricing, revenue recycling, and distributional effects. Prior studies assess carbon taxes and ETS impacts on households and macroeconomy, examine revenue recycling designs (lump-sum, subsidies, tax cuts), and explore equity-efficiency trade-offs in various countries, including China. Works referenced include analyses of carbon peaking and neutrality pathways, ETS design and quota allocation effects, double-dividend hypotheses, and distributional impacts across income groups and regions. This study extends the literature by comparing neutral revenue recycling via government subsidies versus VAT reductions across sectoral recipients (ETS-covered, non-ETS, and all sectors) within China’s dynamic ETS expansion context and quantifying implications for GDP, government revenue, sectoral outputs, energy use, emissions peak timing, and the Gini coefficient.

• Model: A dynamic computable general equilibrium (CGE) model for China, simulating 2018–2035 with a BAU baseline and multiple ETS scenarios. The model incorporates carbon pricing via a national ETS and revenue recycling to production sectors via government subsidies or VAT reductions under revenue neutrality.
• Data and calibration: 2018 GDP used as base for real GDP. GDP growth rates for 2018–2020 taken from China’s National Bureau of Statistics. Labor force disaggregated into 20 types by urban/rural hukou, income level (five categories), and gender using CHIP2013 classifications. Employment sectors divided into 20 categories (international organizations excluded).
• ETS coverage: National ETS includes only electricity in 2021–2022; expands from 2023 to eight industries: power, aviation, steel, chemicals, building materials, petrochemicals, nonferrous metals, and paper.
• Emissions path and peaking: Scenario S1 (single ETS) follows a carbon intensity annual decline rate that increases by 0.05% yearly from 2021–2035, with an average annual decline of 4.5%, calibrated to peak emissions around 2029, consistent with literature on China peaking near 2030.
• Scenarios: BAU (no policies, 2018–2035); S1 (carbon ETS only); and six neutral revenue recycling scenarios that return ETS revenues to production sectors via subsidies (SUB) or VAT reductions (VAT), and target ETS-covered sectors, non-ETS sectors, or all sectors: • SUB-ETS: subsidies to ETS-covered sectors • SUB-NETS: subsidies to non-ETS sectors • SUB-ALL: subsidies to all sectors • VAT-ETS: VAT reduction for ETS-covered sectors • VAT-NETS: VAT reduction for non-ETS sectors • VAT-ALL: VAT reduction for all sectors
• Revenue neutrality: In all neutral scenarios, total carbon market revenue equals that in S1; only the distribution to sectors differs (subsidies vs VAT, and recipient sector group). Government receives all allowance-sale revenues in S1.
• Outcomes assessed: GDP and losses vs BAU; government revenue vs BAU; sectoral output changes (coal, oil, gas, and eight ETS-covered sectors) by 2035; total energy consumption levels and structure (coal share, non-fossil share); total carbon emissions paths and peak timing; income distribution via Gini coefficient.

• Carbon peaking and emissions: • Under S1 (ETS only), with average 4.5% annual carbon intensity decline, China’s emissions peak in 2029 at 10,923 Mt CO2. • Returning carbon revenues to ETS-covered sectors (via subsidies or VAT) maintains a 2029 peak; VAT reductions lower emissions more at the peak year. • Returning revenues to non-ETS or all sectors increases the peak level and delays the peak to 2030.
• Macroeconomy (GDP): • BAU real GDP: 132.51 trillion yuan (2025), 167.89 (2030), 204.75 (2035); growth rates 5.3%, 4.6%, 3.8% respectively. • ETS (S1) reduces GDP vs BAU; revenue recycling via subsidies or VAT mitigates the decline. • When revenues go to ETS-covered sectors: subsidies (SUB-ETS) yield smaller GDP loss than VAT (VAT-ETS). • When revenues go to non-ETS sectors: VAT (VAT-NETS) yields smaller GDP loss than subsidies (SUB-NETS).
• Government revenue (vs BAU): • S1 has the largest revenue increase since government keeps all allowance revenues: +2.68% (2025), +4.48% (2030), +7.01% (2035). • With revenue recycling, government revenue gains shrink relative to S1; VAT-based recycling generally leads to smaller declines than subsidies when targeted to ETS sectors. In 2035: SUB-ETS +1.40%; VAT-ETS +1.74%; SUB-NETS −1.84%; VAT-NETS −0.81%; SUB-ALL −1.27%; VAT-ALL −0.45%. • Returning revenues to ETS-covered sectors yields the least reduction relative to S1 (and still above BAU), reflecting stronger production and VAT bases in high-carbon sectors.
• Sectoral outputs by 2035 (vs BAU): • Coal declines under all scenarios, most under VAT-ETS (−24.26%); S1 −22.26%. • Oil increases, largest under VAT-ETS (+5.74%); S1 +1.66%. • Gas increases, up to +4.30% (VAT-ETS/VAT-NETS); S1 +0.34%. • Thermal power increases notably under VAT-ETS (+10.58%); SUB-ETS +8.84%; smaller gains or slight changes in other scenarios. • ETS-covered industrial sectors’ declines in S1 (e.g., steel −6.37%) are mitigated by subsidies/VAT; VAT often more effective in boosting certain sectors’ outputs than subsidies.
• Energy consumption: • BAU total energy rises from 4.770 to 6.69 billion tce (2018–2035). • All ETS and neutral ETS scenarios reduce total energy vs BAU; recycling to ETS-covered sectors achieves the largest reduction; to non-ETS sectors the smallest; all-industry recycling yields intermediate reductions. • Subsidies tend to induce larger overall energy use than VAT relief; VAT cuts incentivize efficiency and cleaner energy investment more strongly. • Energy mix shifts: under BAU, non-fossil share rises (13.96% in 2018 to 15.77% in 2035) and coal share falls (58.16% to 54.90%); ETS with recycling to ETS sectors further optimizes the mix (lower coal share, higher non-fossil share), with VAT more effective than subsidies.
• Income distribution (Gini coefficient): • BAU shows a rising Gini (widening gap). ETS-only (S1) reduces inequality due to government transfers funded by carbon revenues. • VAT-ETS is most effective for equity: Gini decreases by 1.86% in 2035 vs BAU. • VAT-NETS is least equitable: Gini increases by 1.17% in 2035 vs BAU. • Recycling to ETS-covered sectors (via either instrument) narrows inequality more than recycling to non-ETS or all sectors.

The analysis addresses whether revenue-neutral ETS designs can simultaneously advance China’s near-term carbon peaking goals while mitigating negative macroeconomic and distributional impacts. Results show that recycling carbon revenues to production sectors reduces GDP losses associated with ETS relative to no recycling, with instrument- and recipient-specific differences: subsidies are more growth-supportive when targeted to ETS sectors, whereas VAT reductions better support GDP when targeted to non-ETS sectors. From an environmental standpoint, directing revenues to ETS-covered sectors—particularly via VAT reductions—yields stronger emissions abatement at peak time, greater suppression of coal output, and improved energy mix cleanliness. Distributionally, VAT reductions targeted to ETS-covered sectors deliver the largest reductions in inequality, while VAT to non-ETS sectors may worsen inequality. These outcomes highlight the central role of targeted recycling in aligning incentives in high-emitting sectors, fostering shifts toward cleaner energy, and buffering vulnerable labor groups in energy-intensive industries. Policymakers can thus tailor recycling schemes to balance environmental ambition, economic efficiency, fiscal outcomes, and social equity, acknowledging inherent trade-offs (e.g., scenarios with the lowest emissions often entail larger GDP losses).

A dynamic CGE assessment indicates that China can reach peak emissions by 2029 under an ETS with an average annual carbon intensity decline of 4.5%. Revenue recycling to production sectors via subsidies or VAT reductions can achieve peaking before 2030 with smaller GDP losses than ETS alone. Recycling to ETS-covered sectors most effectively reduces emissions and optimizes the energy mix; VAT reductions outperform subsidies in lowering coal output and enhancing output in oil, gas, petrochemical, thermal power, and aviation. In contrast, recycling to non-ETS sectors yields higher energy use, delayed peaking (to 2030), and weaker fiscal and equity outcomes. Regarding equity, VAT relief to ETS-covered sectors most reduces inequality, while VAT relief to non-ETS sectors can increase it. Policy choices should reflect priorities: for stronger emission reduction, return revenues to ETS-covered sectors via tax cuts; for economic efficiency, return to non-ETS sectors via tax cuts; to balance emission reduction and efficiency, return to ETS-covered sectors via subsidies.