The population structural transition effect on rising per capita CO2 emissions: evidence from China

Junfeng Wang, Yaqing Wu, Yue Zhao, Shutong He, Zhanfeng Dong and Wenguang Bo

Climate Policy, 2019, vol. 19, issue 10, 1250-1269

Abstract: The per capita CO2 emissions (PCCE) of many developing countries like China have been rising faster than total CO2 emissions, and display spatial divergence. Such temporal growth and spatial divergence will have a significant influence on efforts to mitigate CO2 emissions. Given the research gap on the impact of the structural transition in population on PCCE, we constructed an econometric model using the dynamic panel method. The results reveal that the population structural transition has a significant nonlinear impact on PCCE, as the rate of population growth in China decelerates. Both demographic ageing and urban-rural migration have a stronger impact on PCCE than other factors. This effect, however, decreases beyond a certain threshold. An increase in the number of households due to urbanization and family downsizing has resulted in a positive effect on PCCE, without a threshold turning point. The research also finds that an increased share of the service sector in employment can reduce PCCE only if the sector employs more than 31.56% of the total employed population. Overall, these findings indicate that policymakers should pay attention to the prominence of the demographic structural transition for effective climate policy.Key policy insights Policymakers should address rising per capita carbon emissions (PCCE) and their spatial divergence in future climate policies, not just total CO2 emissions.The transitioning demographics of ageing and urbanization in China show a nonlinear, inverted U-shaped effect on PCCE instead of a continuously positive effect.Based on the nonlinear effect of employment structure on PCCE, policymakers should focus on the relationship between the structural transition of the economy and PCCE in future climate mitigation policies.

Date: 2019
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DOI: 10.1080/14693062.2019.1664381

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