| Abstract |
The continuous deepening of aging has posed new challenges for global sustainable development. Measuring the impact of population aging on carbon emissions is crucial for the next stage of climate governance. However, the structural changes in social production and consumption make it difficult to evaluate the impact effects. Therefore, this study constructed a bidirectional fixed Space Durbin Model to explore the mediating pathway of aging's impact on carbon emissions. Furthermore, we have established high-precision prediction models to simulate the evolution trajectory of carbon emissions under multi-factor driving scenarios. The main findings are as follows: (1) The process of carbon emission reduction due to population aging has significant energy hindrance effect and industrial structure effect, while the process of carbon growth is constrained by the consumption enhancement effect, technology progress effect and labor participation effect. (2) The moderating effects of energy consumption and technological innovation on carbon emissions under the aging process are 10.74% and 10.24%, respectively, while the moderating effects of industrial structure and labor force participation are relatively weak. (3) The goodness of fit of the MNGM-ARIMA and MNGM-BPNN models is over 97%. Carbon emissions in the high aging regions show a decreasing trend in all scenarios except the energy consumptiondriven scenario, while in the medium and low aging regions decrease slowly only in the R&D- and labor supply-driven scenarios. This study advocates developing heterogeneous emission reduction measures based on the degree of aging, accelerating supply side upgrading, and increasing the proportion of green consumption. |
