Spatial–Temporal Evolution and Driving Factors of Agricultural Green Development in China: Evidence from Panel Quantile Approaches

Abstract

Agricultural green development has become essential for sustainable agriculture and the reduction of carbon dioxide emissions. This study evaluates the total index of agricultural green development by applying the entropy method; it then examines the spatial–temporal evolution of agricultural green development and finally uses the panel quantile model to examine the driving factors of agricultural green development in China. The results indicate that the level of agricultural green development is rising with time, and the differences among the regions have not changed, showing an increasing direction from west to east. The results from the panel quantile regression with nonadditive fixed effects show that the driving factors have different impacts on agricultural green development across quantiles. Industrial structure upgrading, rural informatization, and agricultural marketization have more significant effects in provinces with higher agricultural green development; agricultural finance and the per capita GDP have greater impacts in provinces at a moderate level of agricultural green development; and technology development, rural informatization, and the urbanization rate play a more important role in provinces at a lower level of agricultural green development. Thus, each province should devise policies according to its level of agricultural green development, which would be beneficial in improving the policies’ effectiveness.