Agricultural Services: Another Way of Farmland Utilization and Its Effect on Agricultural Green Total Factor Productivity in China

Boosting agricultural green development: Does socialized service matter?

Agricultural socialized service is gradually emerging as a new stimulus for enhancing the agricultural production environment. However, their precise impact on improving the agricultural ecological environment and promoting the green development of agriculture remains incompletely understood. Therefore, leveraging panel data spanning from 2003 to 2020 across 31 provinces in China, this study utilizes the bidirectional fixed effect model, moderating effect model, and spatial Durbin model to systematically assess the influence of agricultural socialized services on agricultural green development and its spatial ramifications. The findings show that (I) agricultural socialized services significantly contribute to promoting agricultural green development, particularly in regions with lower aging demographics. (II) The application of the spatial Durbin model reveals that this promotional effect does not exhibit significant spatial spillover effect. (III) The role of agricultural socialized services in fostering agricultural green development can be significantly enhanced by advancements in land transfer, agricultural technological innovations, and the improvement of rural human capital. In conclusion, the study provides a set of policy recommendations that include government financial support, facilitating land transfer, improving rural education and technical training, and promoting green production technologies to effectively promote agricultural green development.

The role of agricultural machinery in improving green grain productivity in China: Towards trans-regional operation and low-carbon practices

Agricultural machinery is effective in improving food production and labor productivity, but it also raises environmental concerns. The impacts of agricultural machinery on the green total factor productivity (GTFP) of grain in China are still under debate in the scientific literature. This study proposed an integrated framework for confronting this issue. The findings suggest that both agricultural mechanization and the GTFP of grain demonstrate a consistent upward trend with moderate fluctuations between 2001 and 2019. By expanding the spatial pattern, there is a positive spatial correlation between them. In addition, we compared the results in three grain functional areas by using the spatial Durbin model (SDM). There were significantly positive spatial spillover effects in major grain-producing areas, which were attributed to the trans-regional operation of agricultural machinery and its carbon reduction effects on neighboring provinces. Notably, the direct effects in major grain-marketing areas and producing-marketing balance areas were significantly positive because agricultural machinery has played a critical role in filling the gap in local labor shortages in grain production. Accordingly, adaptive strategies including building the "Internet + agricultural machinery operation" platform, implementing the land consolidation suitable for machinery, and developing low-carbon agricultural machinery should be fully considered by Chinese policy-makers to promote mechanized agriculture and a low-carbon economy. The findings of this study can help us better understand the role of agricultural machinery in improving green grain productivity in China and thus have significance for the modern and green transformation of agricultural production systems.

How Does Agricultural Mechanization Service Affect Agricultural Green Transformation in China?

Agricultural mechanization service (AMS) is a critical path to achieving agricultural green transformation with smallholders as the mainstay of agricultural production. Based on the panel data of 30 Chinese provinces from 2011 to 2020, this paper measures the AGTFP using the Super-SBM model and examines the effects of different AMS supply agents on AGTFP and spatial spillover effects through the spatial Durbin model. The main conclusions are as follows: First, China's AGTFP showed a stable growth trend, with the mean value increasing from 0.1990 in 2011 to 0.5590 in 2020. Second, the specialization (SPO) and large-scale (LSO) of AMS supply organizations have significantly positive effect on the AGTFP of the local province. However, SPO has a significantly positive effect on the AGTFP of the neighboring provinces, while LSO has the opposite effect. Third, the specialization of AMS supply individuals (SPI) has significantly negative effect on the AGTFP of the local province. In contrast, the large-scale AMS supply individuals (LSI) has the opposite effect. Furthermore, the spatial spillover effects of both are insignificant. Fourth, the spatial spillover effect of AGTFP shows asymmetry among different regions and indicates that AMS resources flow from non-main grain production and economically developed regions to main grain production and less developed regions. These findings provide helpful policy references for constructing and improving the agricultural mechanization service system and realizing the agricultural green transformation in economies as the mainstay of agricultural production.

Spatial-temporal evolution and convergence analysis of agricultural green total factor productivity-evidence from the Yangtze River Delta Region of China

Measuring regional differences in agricultural green total factor productivity (AGTFP) provides a basis for policy guidance on agricultural green development in the Yangtze River Delta (YRD) region. By constructing a two-period Malmquist-Luenberger index under the carbon emission constraint, we measure the AGTFP of cities in the YRD region from 2001 to 2019. Furthermore, adopting the Moran index method and the hot spot analysis method, this paper analyzes the global spatial correlation and local spatial correlation of AGTFP in this region. Moreover, we investigate its spatial convergence. The results show that the AGTFP of 41 cities in the YRD region is on an increasing trend; the growth of AGTFP in the eastern cities is mainly driven by green technical efficiency, while this growth in the southern cities is mainly stimulated by green technical efficiency and green technological progress. We also find a significant spatial correlation between cities' AGTFP in the YRD region from 2001 to 2019, but with certain fluctuations, showing a U-shaped trend of "strong-weak-strong". In addition, absolute β convergence of the AGTFP exists in the YRD region, and this convergence speed is accelerated with the addition of spatial factors. This evidence provides support for implementing the regional integration development strategy and optimizing the regional agricultural spatial layout. Our findings offer implications for promoting the transfer of green agricultural technology to the southwest of the YRD region, strengthening the construction of agricultural economic belts and agricultural economic circles, and improving the efficiency of agricultural resource use.