Regional impact of aging population on carbon dioxide emissions in China: Evidence from panel threshold regression (PTR).

Carbon dioxide emission is a high-profile issue that can affect both the human economy and human existence, but few scholars have studied the relationship between these two. Therefore, this study constructs the panel threshold regression (PTR) based on the National Bureau of Statistics of China's panel data from 2002 to 2019 in 19 regions. One of the advantages of PTR is to leverage segmented functions, allowing for a more detailed analysis of the data. Besides, by introducing the idea of a threshold, PTR can effectively avoid structural changes in the data. The different between this study and other research is that this study divides 19 regions into two parts: Eastern China and Central China. Based on that, this study researches and compares the different influences of the aging population on carbon emissions in these two regions. The results show that although the Environment Kuznets Curve has been confirmed in both Eastern China and Central China, with the development of the economy, the carbon emissions will increase in Eastern China and decrease in Central China, respectively. In addition, the key factors affecting carbon emissions in Eastern China and Central China are trade dependence and urbanization rate separately. Hence, this study suggests that the regional governments in Eastern China may guide and encourage more international trading companies to move to Central China, and at the same time, the regional governments in Central China should issue more policies to attract these companies, such as: reducing land lease fees and building better transportation infrastructure. Apart from that, the governments in Central China should vigorously increase the rate of urbanization to reduce energy consumption and improve energy efficiency.

Regional impact of aging population on economic development in China: Evidence from panel threshold regression (PTR).

The aging population is a common problem faced by most countries in the world. This study uses 18 years (from 2002 to 2019) of panel data from 31 regions in China (excluding Hong Kong, Macao, and Taiwan Province), and establishes a panel threshold regression model to study the non-linear impact of the aging population on economic development. It is different from traditional research in that this paper divides 31 regions in China into three regions: Eastern, Central, and Western according to the classification standard of the National Bureau of Statistics of China and compares the different impacts of the aging population on economic development in the three regions. Although this study finds that the aging population promotes the economy of China's eastern, central, and western regions, different threshold variables have dramatically different influences. When the sum of export and import is the threshold variable, the impact of the aging population on the eastern and the central region of China is significantly larger than that of the western region of China. However, when the unemployment rate is the threshold variable, the impact of the aging population on the western region of China is dramatically higher than the other regions' impact. Thus, one of the contributions of this study is that if the local government wants to increase the positive impact of the aging population on the per capita GDP of China, the local governments of different regions should advocate more policies that align with their economic situation rather than always emulating policies from other regions.