Inter-factor/inter-fuel substitution, carbon intensity, and energy-related CO2 reduction: Empirical evidence from China

Carbon dioxide (CO2) reduction, which is the central issue in addressing global warming, depends on the extent that clean energy can substitute for CO2 emitting coal and non-energy factors can substitute for energy factor. The purposes of this paper are to empirically investigate inter-factor/inter-fuel substitution in China and to evaluate the determinants of China's energy-related carbon intensity as well as mitigation effects of carbon tax. Considering China's rapid increase in energy consumption and the slow adjustment in substitution, the two-stage estimation method and the dynamic error correction mechanism are employed in this study. The empirical results suggest substitutability among different types of energy sources as well as substitutability among energy, labor, and capital. The magnitude of cross-price elasticities indicates that the substitutions are inelastic, which limits the scope of the Chinese government to implement substitution strategy aiming at energy conservation and environmental management. China's carbon intensity declined during 1985–2012, most of which can be attributed to labor substitution and energy price increase. However, carbon-intensive technology being embodied in China's capital investment (energy consuming equipment) has contributed to the increase in carbon intensity. A carbon tax of RMB 50/tonne could reduce 332.9 million tonnes CO2 emissions on the basis of 2012. In addition, if ignoring the feedback between inter-factor/inter-fuel substitutions, CO2 mitigation potential would be underestimated. •Two-stage estimation method and dynamic error correction mechanism are employed.•This paper investigates the relative contributions of the main driving forces behind China's carbon intensity decrease.•This paper evaluates the mitigation effect of carbon tax based on inter-factor/inter-fuel substitution.•Ignoring the feedback between inter-factor/inter-fuel substitution would lead to downward bias of CO2 mitigation potential.