Nonlinear associations and threshold effects between agricultural industrial development and carbon emissions: insights from China

Abstract

With the inevitability of global climate change, it has become increasingly important to understand the relationship between Agro-industrial Development (AID) and Agricultural Carbon Emissions (ACE) to promote the development of low carbon production in agriculture. Using a panel of datasets, as based on the "element-structure-function" framework of 30 Chinese provinces over the period from 2011-2021, the entropy weight method was used to calculate the level of AID in each province. With this approach, it was possible to assess correlations and mechanisms between AID and ACE. Here, with use of fixed-effect, regulatory and threshold models, we determined some of the critical factors contributing to the effects of AID and ACE. Our findings revealed: 1) AID displays an inverse U-shape relationship with ACE, as verified through endogeneity and robustness assessment, 2) A review of the mechanisms suggests that the crossing of the turning point of the inverted u-curve can be accelerated by the moderating effect of agricultural finance. and 3) As based on the threshold effect analysis, a two-tier effect of the digital economy, rural human capital and farmers' net income on AID, with facilitating effects on carbon emission reductions was obtained after the threshold crossing. The significance of this effect increases as a function of the post-threshold interval. Taken together, these findings demonstrate the long-standing interplay between AID and ACE. Thus, additional insights and empirical evidence that can inform the ongoing development of sustainable agricultural practices can be realized.