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

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

*Corresponding author for this work

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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.

Original languageEnglish
Pages (from-to)1250-1269
Number of pages20
JournalClimate Policy
Volume19
Issue number10
Early online date16 Sept 2019
DOIs
Publication statusPublished - 26 Nov 2019

Funding

This study was supported by the Natural Science Foundation of China [grant numbers 71373134], the Special Foundation to Build Universities of Tianjin, the Special Foundation to Build Universities of Tianjin [grant number C0291760], the China Scholarship Council [grant number 201806200003], the Tianjin Natural Science Foundation [grant number 18JCZDJC39900], and the Fundamental Research Funds for the Central Universities. We thank the anonymous referees for helpful and their constructive comments, which strengthened the current version of the article.

FundersFunder number
National Natural Science Foundation of China71373134
National Natural Science Foundation of China
China Scholarship Council201806200003
China Scholarship Council
Natural Science Foundation of Tianjin City18JCZDJC39900
Natural Science Foundation of Tianjin City
Fundamental Research Funds for the Central Universities
Special Foundation to Build Universities of TianjinC0291760
Special Foundation to Build Universities of Tianjin

    Keywords

    • Ageing
    • China
    • employment structure
    • number of households
    • per capita CO emissions
    • urban-rural population migration

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