Impact of Population Aging and Renewable Energy Consumption on Agricultural Green Total Factor Productivity in Rural China: Evidence from Panel VAR Approach

Abstract

China is moving toward the important goal of being a green and low-carbon country, and the current severity level of population aging is of particular concern to the government. Aging, renewable energy consumption, and technological progress are closely linked. In this research, a panel vector autoregressive (PVAR) model is employed to investigate the long-run equilibrium relationship between population aging, renewable energy consumption and agricultural green total factor productivity using panel data for 30 Chinese provinces (cities) from 2000 to 2019. The findings reveal that, in the long run, both population aging and renewable energy use have considerable positive impacts on agricultural green total factor productivity. In addition, in order to more intuitively understand the impact of population aging and renewable energy consumption on agricultural green total factor productivity, the analysis adopts the impulse response function and variance decomposition. The contributions of population aging and renewable energy consumption to agricultural green total factor productivity are 2.23% and 0.56%, respectively, when the lag period is chosen to be 15, which implies that population aging and renewable energy use will continuously contribute to agricultural green total factor productivity. The study results have significant theoretical implications for understanding China’s aging population structure and current renewable energy use. Given the above results, this study puts forward countermeasures and suggestions from four aspects: improving agricultural infrastructure, increasing agricultural technology investment, increasing the stock of agricultural human capital and strengthening international cooperation.

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

“…For example, Liu et al [39] investigated the determinants of agricultural TFP in China and found that the elderly population had a significant and positive impact on technical efficiency improvement. Similarly, Li et al [43] found that population aging impacted positively agricultural GTFP in China. From a micro perspective, a case study using microdata of the assembly plant of truck manufacturing by Börsch-Supan and Weiss [42] showed that the average age-productivity profile of workers increased until age 65.…”

“…However, from a positive research perspective, aging is seen to raise total factor productivity (TFP) because of investment in human capital and knowledge accumulation. Specifically, the ever-growing aging population promotes opportunities for an increase in human capital investment to reduce the dampening effect of aging on productivity, i.e., population aging promotes productive capacity [43]. Compared to younger workers, older workers usually have more experience in production and can make fuller use of their experience to increase productivity.…”

Spatial Distribution and Convergence of Agricultural Green Total Factor Productivity in China

“…The index could effectively avoid the possibility of no solution, meet the requirements of circularity, as well as allow technical regression. The global benchmark enveloped the whole current benchmark into a single set of global production possibilities, serving as a common reference set for each period [ 30 , 31 ]. The sets of production possibilities for current and global benchmarks were shown as follows: The current benchmark: The global benchmark: …”

“…Considering the homogeneity and accessibility of the data statistical caliber, the study compiled the relevant data from 31…”

How Does Agricultural Mechanization Service Affect Agricultural Green Transformation in China?

“…Existing studies have empirically tested that implementing crop insurance, carbon trading systems, and other agricultural environment protection policies can help increase AGTFP [ 18 , 19 , 34 ]. In addition, the use of new technologies is also a significant driving force for the sustained growth of AGTFP, including renewable energy consumption, the spread of Internet technologies, and the development of inclusive digital finance [ 35 , 36 , 37 ]. Some scholars have also studied the influencing factors that hinder the growth of AGTFP, including factor market distortion, resource mismatch, farmland pollution, agricultural disasters, and climate change [ 38 , 39 , 40 , 41 ].…”