Assessing green total factor productivity and spatial spillover effect in China’s maize industry for sustainable food production: a carbon emissions perspective

Abstract

Although Enhancing green total factor productivity (GTFP) within the agricultural sector is crucial for fostering sustainable development. In this paper, the GTFP of China’s maize industry is analyzed using the SBM-GML index method, considering data from the primary maize-producing provinces from 2004 to 2020. This analysis incorporates carbon emissions as undesirable outputs. The spatial Durbin model aids in investigating the factors influencing maize GTFP. Our findings reveal a positive trajectory for China’s maize GTFP over the designated period, featuring an average yearly increase of 0.8%. This ascension is primarily attributed to advancements in green maize technology. In the key cultivation regions of the Yellow and Huaihai areas, the Northern region, and the Southwest region, the average annual growth rates were 1.5%, 0.87%, and 0.09%, respectively. Among the direct influences, variables such as regional human capital, the extent of maize cultivation area, financial assistance towards agriculture, and the degree of agricultural mechanization considerably bolster the optimization of maize GTFP. Conversely, urbanization and the prevalence of natural disasters in the agricultural sector pose substantial challenges to enhancing maize GTFP. Furthermore, the spatial spillover effects reveal that natural agricultural disasters in a particular region inadvertently contribute to the improvement of maize GTFP in adjacent regions. Additionally, the regional human capital levels can significantly impede the progress of maize GTFP in neighboring regions. Therefore, to ensure food security, it is imperative to actively advocate for green development within the maize industry to Enhancing green total factor productivity (GTFP) in agriculture is crucial for agriculture to promote sustainable development. In this paper, using data from 2004-2020 from China’s main maize-producing provinces, the SBM-GML index method is used to measure China’s maize GTFP, and the spatial Durbin model is applied to examine the influencing factors and spatial spillover effects of China’s maize GTFP growth. The results of the study revealed a positive trajectory of Chinese maize GTFP over the specified period, with an average annual growth of 0.8%. This enhancement is mainly attributed to the progress of green maize technology. The average annual growth rates were 1.5%, 0.87%, and 0.09% in the major cultivation areas of the Yellow and Huaihai regions, the northern and southwestern regions, respectively. The analysis of influencing factors showed that among the direct influencing factors, variables such as regional human capital, extent of maize cultivation area, financial assistance to agriculture and degree of agricultural mechanisation contributed significantly to the optimization of maize GTFP. Conversely, urbanisation and the prevalence of natural disasters in the agricultural sector pose significant challenges to improving maize GTFP. Furthermore, spatial spillovers reveal that natural agricultural disasters in a given region unintentionally contribute to the improvement of maize GTFP in neighbouring regions. Furthermore, regional human capital levels can significantly hinder progress in maize GTFP in neighbouring regions. Therefore, in order to ensure food security, the greening of maize production must be actively promoted.