Developing agricultural socialized services is a crucial approach to drive small farmers onto the track of modern agricultural development. However, whether and how these services can promote the green transformation of agriculture still require systematic empirical evidence. This paper takes agricultural green total factor productivity (AGTFP) as the entry point, utilizes panel data from 31 provinces in China spanning from 2010 to 2024, and employs the SBM-GML model to measure AGTFP. Based on this, a two-way fixed effects model is used to examine the impact of agricultural socialized services on AGTFP. Furthermore, leveraging the multiplicative decomposition property of the global Malmquist-Luenberger index, the mechanism of action is identified from two channels: technological progress and improvement in technical efficiency. The research findings are as follows: Firstly, agricultural socialized services significantly promote the improvement of AGTFP. This conclusion remains valid after a series of robustness and endogeneity tests, including lagging explanatory variables, exclusion of municipalities, winsorization, and instrumental variable estimation. Secondly, channel tests indicate that agricultural socialized services primarily enhance AGTFP by promoting agricultural technological progress, while their effect on improving technical efficiency is not significant. Thirdly, the green productivity effect of agricultural socialized services exhibits significant heterogeneity, being notable in major grain-producing regions and central and western regions, but not in non-major grain-producing regions and eastern regions. This paper provides new empirical evidence for understanding the green development effect of agricultural socialized services from the perspective of GTFP decomposition. The research conclusions offer insights for guiding socialized service organizations to upgrade towards green technology integration services and implementing differentiated regional service supply policies.
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Li et al. (2026) studied this question.
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