REGIONAL DIFFERENCES, SPATIOTEMPORAL EVOLUTION, AND CONVERGENCE OF AGRICULTURAL GREEN DEVELOPMENT IN CHINA: A COMPARISON BASED ON TWO TYPES OF REGIONAL DIVISIONS

This study, aiming a comparative analysis of two types of regional divisions, employs multiple research methodologies, including the Dagum Gini coefficient, Kernel density estimation, Markov chains, and convergence analysis, to empirically examine regional differences, evolutionary trends, and convergence issues in China's agricultural green development. Findings indicate that within the sample period, the overall level of China's agricultural green development as measured by the Dagum Gini coefficient shows a slight upward trend amid fluctuations, with disparities between regions being the primary cause of the overall regional differences in agricultural green development levels; All sample regions demonstrate a rightward shift over time in the centers and variance of Kernel density curves, indicating continuous improvements in the level of agricultural green development; There is a high degree of mobility between states of agricultural green development levels, with relative positions of various types of regions within the distribution being quite unstable and highly variable; sigma-convergence is not evident, however, absolute beta-convergence and conditional beta-convergence are present; Comparative analysis of different regional divisions reveals that finer regional divisions provide more accurate estimation results, bringing the research findings closer to reality. Consequently, coarser regional divisions may introduce certain biases and potentially obscure some actual conditions.