Exploring the Direct and Spillover Effects of Aging on Green Total Factor Productivity in China: A Spatial Econometric Approach

Abstract

China is a rapidly aging nation. Therefore, it is a matter of urgency to address the challenges of aging in China and to coordinate the relationships between population aging, environmental issues, and socio-economic development. However, few empirical studies have thus far analyzed the impact of aging on green total factor productivity (GTFP) in China. Hence, this study employs a global Malmquist–Luenberger index method (GMLI) to calculate the GTFP scores of 30 Chinese provinces from 2002 to 2018. We apply spatiotemporal analysis methods to identify the variations of population aging and GTFP scores and then build a spatial econometric model to examine the impact of population aging on GTFP. Our study findings are as follows. (1) Whereas at the beginning of the 21st century, provinces with deep aging were mostly situated in the east, the population aging issue in China is now spreading across the entire country. (2) From a dynamic perspective, the overall GTFP growth rate in China during the sample period depicts a U-shaped structure with time. (3) Results of the spatial Durbin model show that the impact of population aging in a given region on GTFP is negative, but the spatial spillover effect of aging in neighboring regions on GTFP in a given region is positive, resulting in the loss of younger local labor forces in some provinces due to low birth rates and migration to neighboring regions. Finally, to cope with a growing aging population and to possibly eliminate the negative impacts of population aging on high-quality sustainable development, the government should promote the establishment of the old-age security system; increased investment in R & D and wide use of advanced technology should also be urgently encouraged.