• Energy Research

Despite its significant role in mitigating climate change, technology was usually exogenously treated in evaluating climate policy, particularly emission trading scheme (ETS); such treatment cannot comprehensively reveal how ETS affects technological progress. To narrow this research gap, we attempt to endogenize ETS-induced technological change in this paper. A dynamic recursive Computable General Equilibrium (CGE) model is employed to quantify ETS-induced progress of clean technology (PCT) and efficiency improvement. The Chinese nationwide ETS is taken as a case study. The CGE model results show that PCT negatively affects anthropogenic emissions, while efficiency improvement decreases GDP loss or abatement cost. Simultaneously considering both technological progress increases emission abatement but slightly decreases GDP in the long term. The most interesting finding is that PCT moderates the relationship between efficiency improvement and emission abatement. Hence, PCT is crucial in emission abatement and economic growth under climate policy.

When evaluating climate policy, previous researchers tend to exaggerate positive employment benefits at aggregate level. Nevertheless, distributional employment at sectoral level is usually neglected, and consequently policy implementation may be impeded by the sectors with severe employment loss. Hence, distributional employment impacts of climate policy should be comprehensively studied. To achieve this target, in this paper, a Computable General Equilibrium (CGE) model is employed to simulate the Chinese nationwide Emission Trading Scheme (ETS). The CGE model results show that the ETS decreased total labor employment by approximately 3% in 2021, and then this negative impact will diminish to zero in 2024; the ETS will positively affect total labor employment in 2025-2030. The ETS increases labor employment in the electricity sectors and also agriculture, water, heat, and gas production sectors, as these sectors are complementary to the electricity sectors or do not have intensive use of electricity. In contrast, the ETS decreases labor employment in the sectors with intensive use of electricity, including the coal and petrol production, manufacturing, mining, construction, transport, and service sectors. Overall, a climate policy, which covers electricity generation only and is time-invariant, tends to have time-decreasing employment impacts. Because this policy increases labor employment in electricity generation from nonrenewable energy, it cannot help achieve low-carbon transition.

In the literature, very few studies have focused on how urbanisation will influence the policy effects of a climate policy even though urbanisation does have profound socioeconomic impacts. This paper has explored the interrelations among the urbanisation, carbon emissions, GDP, and energy consumption in China using the autoregressive distributed lag (ARDL) model. Then, the unit urbanisation impacts are inputted into the policy evaluation framework of the Computable General Equilibrium (CGE) model in 2015–2030. The results show that the urbanisation had a positive impact on the GDP but a negative impact on the carbon emissions in 1980–2014. These impacts were statistically significant, but its impact on the energy consumption was not statistically significant. In 2015–2030, the urbanisation will have negative impacts on the carbon emissions and intensity. It will decrease the GDP and the household welfare under the carbon tax. The urbanisation will increase the average social cost of carbon (ASCC). Hence, the urbanisation will reinforce the policy effects of the carbon tax on the emissions and welfare.

AbstractDespite the significant impacts of technology on the socioeconomic effects of climate policies, many previous researchers neglected the induced technical impacts and thus resulted in biased evaluations of climate policies. Hence, it is important that the induced technology should be endogenized in the policy evaluation framework. The purpose of this paper is the quantification of the technical impacts of the Chinese carbon tax using a Computable General Equilibrium (CGE) model. The technical impacts are denoted by the induced technological change (ITC), which is a function of the energy-use efficiency (EUE), energy-production efficiency (EPE), and nonenergy-production efficiency (ENE). The carbon tax will increase the energy cost share because of the internalisation of the abatement costs. This paper empirically shows that the carbon tax will decrease the energy cost share and production efficiency but increase the energy use and nonenergy production efficiency. Under the carbon tax, the ITC will decrease the energy use and production efficiency but increase the nonenergy production efficiency. The ITC will increase the RGDP, decrease the household welfare, and increase the average social cost of carbon (ASCC). This finding implies that the ITC of the carbon tax is biased towards the technical progress of nonenergy sectors; the emission abatement will become costlier under the ITC impacts. Although the quantification method of the technical impacts was from an existing published paper, the CGE analysis of the ITC impacts of the carbon tax in China is original in this paper.