Threshold Effects of Restraining Factors on China’s Provincial Ecological Footprint in the Process of Urbanization

Abstract

This study uses a panel threshold model to explore the nonlinear relationship between restraining factors and ecological footprint (EF) evolution from 2003 to 2015 in China. In addition, the heterogeneity of the environmental Kuznets curve (EKC) hypothesis is identified. The results show that the four regime-dependent variables, i.e., technology level, openness, industrial structure and energy efficiency, have significant single-threshold effects on the EF in China, and the negative correlations between these variables and EF are significantly enhanced when the threshold variable urbanization exceeds 86.20%, 68.71%, 86.20% and 47.51%, respectively. As the urbanization level increases, more factors begin to play a high restraining role on the EF. The single-threshold effects on the EKC are significant under the threshold variables of urbanization and industrial structure. Meanwhile, the significant inverted-U relationship trends emerge when the two variables exceed the thresholds of 86.2% and 69.1%, respectively. Based on an empirical study, to restrain the EF of China’s 30 provinces more effectively, the urbanization process should be accelerated, while energy efficiency, foreign capital investment, technology level and service sector proportion should be promoted according to the urbanization level. Compared to other studies, this study is more focused on EF restraining factors and it contributes to the identification of the heterogeneity of EF’s restraining factors and EKC hypothesis, which would be useful for the EF reduction policy in the case of China.

How do energy consumption, globalization, and income inequality affect environmental quality across growth regimes?

“…However, regardless of the regime, the results show that economic growth has a significant positive impact on the EF. This finding is consistent with Sirag et al ( 2017 ), Aydin et al ( 2019 ), and Wang et al ( 2022 ), but differs from Wu and Liu ( 2020 ), Simionescu ( 2021 ), and Wang et al ( 2023 ).…”

“…In contrast, Wu and Liu ( 2020 ) used urbanization, openness, industrial structure, and energy efficiency as the threshold variables instead of GDP to test the hypothesis for China’s provinces. It was determined that there are statistically significant threshold effects associated with both industrial structure and urbanization on the inverted U-shaped relationship between the EF and GDP.…”

Industrial structure, high-quality development of logistics industry and the economy

“…Moderate government intervention is conducive to promoting the operation of the economic market, and excessive government intervention, as well as government corruption and market segmentation, can have negative impacts [ 32 ]. Urbanization can solve environmental problems by concentrating population, stimulating innovation and increasing wealth to promote sustainable economic development [ 33 ]. The demographic dividend is particularly important for the high-quality economic development of a region.…”

Panel Data Analysis of Energy Conservation and Emission Reduction On High-Quality Development of Logistics Industry in Yangtze River Delta of China

“…China's rapid economic growth and industrial upgrading has led to significant changes in the structure of employment, which often requires more skilled workforce, particularly in hightech industries (Wang et al, 2020c). Urbanization can also contribute to ecologically sustainable development by concentrating population, stimulating innovation and increasing wealth to solve environmental problems (Wu and Liu, 2020). The demographic dividend is therefore particularly important for the economic growth of a region.…”