## 6 Conclusions and Policy Implications  
Our main objective in this paper was to examine the impact of population aging on green total factor productivity (GTFP) in China. At the outset, we analyzed the spatiotemporal variations of the aging index of 30 Chinese provinces from 2002 to 2018. Next, we measured the GTFP score of each province during the sample period using the global Malmquist-Luenberger method, and thereafter discussed the spatiotemporal distribution. Lastly, we established a spatial Durbin model to quantify the direct and indirect spillover impact of population aging on GTFP. The main research findings are, first, that regional differences exist in the aging index among provinces in China. At the beginning of the 21 st century, the highest aging index was found mainly in the eastern region; however, the aging rate in the eastern provinces has slowed slightly in recent years, mainly due to the inflows of young people from other areas. Nevertheless, serious population aging gradually began to spread throughout the country over time. Accordingly, the aging problems in the central and western provinces have worsened. Notably, the northeastern region has long been characterized by a net outflow of population, with an average annual population outflow exceeding two million, thus exacerbating the aging problem in this region. In 2018, all 30 provinces entered the phase of moderate aging. A second finding shows regional differences in the change of GTFP. Specifically, 14 provinces witnessed continuous growth over time, and the growth rate in the central-eastern region is faster than in the west. The overall GTFP presents a U-shaped curve from 2002 to 2018 We expect the overall GTFP to continue to increase in the coming years; in other words, the high-quality sustainable development goal can be achieved. Third, although aging can decrease GTFP in a given province, the present research has verified that the positive spatial spillover effect of aging exists; that is to say, an increase in the aging index in neighboring provinces can positively affect GTFP in a province. The main reason is that high aging index regions provide fewer job opportunities to young people, which pushes them to migrate to economically developed neighboring provinces for work. As a result, the migration has caused GTFP losses in the aged provinces but has contributed to the GTFP growth in the neighboring provinces. The focus of our research is on the direct and indirect (spatial spillover) effects of aging on GTFP by means of SDM, rather than TFP ([PERSON] and [PERSON], 2017), agricultural TFP ([PERSON] et al., 2020), or productivity ([PERSON] et al., 2022). Besides, unlike the previous studies mentioned earlier, our study reveals that aging has the strong spatial spillover effect on the GTFP of neighboring regions. Hence, the joint effect of aging should be paid attention to when implementing relevant policies. Based on this study's main findings, policy implications can be given. The aging population in China will reach 400 million by 2035, when it will enter the phase of severe aging ([PERSON] et al., 2017). To face and cope with the challenge of rapid population aging, a series of policies is urgently needed. First, the government should actively promote the construction of an old-age security system through preferential policies or subsidies. The number of government-funded elderly care institutions should be increased to meet the rising demand for elderly care. Private capital should also be encouraged to invest in the elderly care industry through a series of preferential policies so that private capital-funded institutions can satisfy diversified aging care demand. Second, the central government should adjust appraisal and evaluation models for local governments, replacing the traditional \"GDP tournament\" with the novel \"GTFP score.\" Hence, a prerequisite for them is a deeper understanding of the importance of GTFP, which contributes to achieving the high-quality sustainable development goal.