Search

Over the past two decades, China has actively pursued a green, low-carbon economy in response to climate change. Amidst rapid economic development, China's green total factor productivity—a key metric reflecting the nation's green development—has notably risen. As a developing country with a population exceeding 1.4 billion, agriculture plays a key role in China. China has persistently strived to comprehensively promote the scale and scope of agricultural mechanization, recognizing it as a crucial gauge to enhance agricultural productivity, thereby facilitating agricultural modernization and ensuring food security. However, can elevating the agricultural mechanization level improve China's green development within the agricultural sector? Specifically, how does agricultural mechanization (A M) affect agricultural green total factor productivity (A G T F P)? To address these questions, we assess the effects of agricultural mechanization on agricultural green total factor productivity and examine its channels using panel data from 30 provinces in China spanning from 2000 to 2021. Additionally, we investigate the heterogeneous effects under different levels of economic development, agricultural economic development, environmental regulation intensity, and agricultural technology. The results indicate that: First, the development of agricultural mechanization promotes the agricultural green total factor productivity. Second, channel analysis indicates that agricultural mechanization can bolster agricultural green total factor productivity through three channels: enhancing agricultural management level, improving agricultural factor efficiency, and fostering diversification of agricultural industrial structure. Third, heterogeneous analysis suggests that agricultural mechanization exerts a more pronounced impact on agricultural green total factor productivity in provinces characterized by lower levels of economic development, more backward agricultural economic development, higher environmental regulation intensity, and more advanced agricultural technology. This article is anticipated to furnish empirical evidence from China for developing nations seeking to foster agricultural green sustainable development through the widespread adoption of agricultural mechanization, thereby contributing significantly to global efforts to mitigate climate change. [ABSTRACT FROM AUTHOR]

As an effective risk guarantee mechanism, crop insurance can not only disperse agricultural operation risk, but also guide the agricultural green development. Based on Chinese provincial panel data from 2002 to 2015, this paper uses SBM-GML (Global-Malmquist-Luenberger) index model to measure agricultural green total factor productivity and systematically examines the impact of crop insurance on agricultural green total factor productivity as well as its mechanism. This study supplements the determinants of agricultural green total factor productivity. It is found that crop insurance has a significant positive impact on agricultural green total factor productivity. The promotion effect of crop insurance on agricultural green total factor productivity increases with the expanded use of agricultural green technologies such as precision sowing, deep fertilization, subsoiling and no-tillage. Moreover, our results show that the role of crop insurance in promoting agricultural green total factor productivity increases with the increase in operational scales. In addition, compared with food crops, the promotion effect is stronger for cash crops. Therefore, the Chinese government should continue to support the implementation of crop insurance policy. It is necessary to not only increase crop insurance subsidies, but also set up differentiated subsidy systems in different operational scales and planting structures to promote agricultural green development. • Crop insurance has a significant positive impact on AGTFP. • The promotion effect of crop insurance on AGTFP increases with the expanded use of agricultural green technologies. • The role of crop insurance in promoting AGTFP increases with the increase in operational scales. • Compared with food crops, the promotion of crop insurance on AGTFP is stronger for cash crops. [ABSTRACT FROM AUTHOR]

Agricultural sector is the basic industry supporting the construction and development of national economy. With the continuous deterioration of agricultural pollution, measuring and understanding agricultural total factor productivity (AGTFP) is the important premise to achieve agricultural green development and clean production. Regarding carbon emissions and agricultural non-point source pollution (ANSP) as undesired outputs, this paper applies a three-stage Data Envelopment Analysis (DEA) method combined with the Slack-Based Measure (SBM) model to eliminate the influences of environmental factors and random errors and explore the real AGTFP of 30 provinces in China from 2000 to 2017.On this basis, the spatial distribution and dynamic changes of AGTFP before and after adjustment are further discussed to seek the underlying reasons. The empirical results demonstrate that AGTFP is lower when carbon emissions and ANSP are both considered, and it decreases from east to west in StageⅠbut the Northeast region surpasses the East to achieve the highest productivity after removing the interferences. Moreover, China's AGTFP has been restricted by the external environment, and superior external environment disguises the poor management efficiency of Beijing and Shanghai. Therefore, some policy implications to balance agricultural environment and economic development are proposed. [Display omitted] • Non-point source pollution and CO 2 are integrated to measure agricultural green efficiency. • A three-stage SBM-DEA approach is employed to calculate the real agricultural green total factor productivity. • Different environmental factors have different effects on the slack of agricultural inputs. • China's agricultural green total factor productivity is restricted by the external environment. [ABSTRACT FROM AUTHOR]

China's economy is currently moving from a stage of high-speed growth to a stage of high-quality development. Agricultural green total factor productivity is of great significance for promoting the high-quality development of the economy. Based on the panel data of China's provincial agriculture, this paper uses the Super-SBM model to calculate China's agricultural green total factor productivity based on carbon emissions. On this basis, this paper uses the nuclear density estimation method to investigate its dynamic evolution trend and the panel data model to empirically study the influencing factors of China's agricultural green total factor productivity. The results show that China's agricultural carbon emissions show an inverted-"U" trend, but the overall growth rate shows a gradual declining trend. The main concentration areas are transferred from the eastern region to the central region, and agricultural fertilizer is the main source of such emissions. China's agricultural green total factor productivity overall shows a fluctuating growth trend, and the differences between provinces show an increasing trend. Agricultural factor endowments and regional characteristics affect China's agricultural green total factor productivity, and there are regional differences in these effects. An important way to improve China's agricultural green total factor productivity and promote the coordinated development of agricultural regions and the high-quality development of the economy is by promoting clean agricultural production, strengthening the research and development of agricultural science and technology, expanding the agricultural opening-up level, and promoting the deep integration of industrialization and agricultural modernization. Image 1 [ABSTRACT FROM AUTHOR]