The nonlinear effect of population aging on carbon emission-Empirical analysis of ten selected provinces in China

Abstract

Existing related researches have focused on the linear relationship between population aging and carbon emissions, which easily lead to partial understanding of the effect of population aging on carbon emissions. In order to more comprehension of the effect of population aging on carbon emissions, this study explores the nonlinear relationship between population aging and carbon emission through empirical analysis of ten selected provinces in China from 2000 to 2016 using the panel threshold model. In the proposed panel threshold model, carbon emission is set as the explained variable, population aging is set as the core explanatory variable, the levels of population aging and trade openness are set as threshold variables, the levels of economic development, energy consumption structure, industrial structure, and technological innovation are set as the controlling variables, respectively. The results show that population aging has a threshold effect on curbing carbon emission. The levels of population aging and trade openness are two key factors that affect the relationship between population aging and carbon emission. Whether the level of popultion aging is lower or higher than the threshold value of 0.12937, the population aging has a negative coefficient on carbon emissions. Moreover, the higher the level of population aging, the greater the offsetting effect of population aging on carbon emission. When the level of trade openness is below the threshold value of 0.30990, the effect of population aging on carbon emission is negligible. When the level of trade openness is higher than the threshold value of 0.30990, the offesetting effect of population aging on carbon emission begins to appear. In other words, population aging has an offsetting effect on carbon emission when trade openness is in relatively high level, whereas the offsetting effect disappears when trade openness is lower than threshold value.