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 language | English |
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Pages (from-to) | 1250-1269 |
Number of pages | 20 |
Journal | Climate Policy |
Volume | 19 |
Issue number | 10 |
Early online date | 16 Sept 2019 |
DOIs | |
Publication status | Published - 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.
Funders | Funder number |
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National Natural Science Foundation of China | 71373134 |
National Natural Science Foundation of China | |
China Scholarship Council | 201806200003 |
China Scholarship Council | |
Natural Science Foundation of Tianjin City | 18JCZDJC39900 |
Natural Science Foundation of Tianjin City | |
Fundamental Research Funds for the Central Universities | |
Special Foundation to Build Universities of Tianjin | C0291760 |
Special Foundation to Build Universities of Tianjin |
Keywords
- Ageing
- China
- employment structure
- number of households
- per capita CO emissions
- urban-rural population migration