组态视角下中国农业全要素水资源绿色生产率提升路径研究

ENHANCEMENT PATH OF CHINA’S AGRICULTURAL TOTAL FACTOR WATER GREEN PRODUCTIVITY FROM THE PERSPECTIVE OF CONFIGURATION

关键词:  农业水资源  绿色生产率  DSBM-GLPI模型  组态分析  提升路径

Key words:  agricultural water resources  green productivity  DSBM-GLPI model  configuration analysis  growth paths

摘要:

目的 测算中国农业全要素水资源绿色生产率，并揭示其提升的复杂组态路径，为推进农业水资源利用效率提升、实现农业绿色高质量发展提供决策参考。方法 文章基于2005—2021年中国30个省（市、区，不含港澳台和西藏）面板数据，采用基于松弛量的方向距离函数结合全局Luenberger生产率指数测算中国农业全要素水资源绿色生产率，并使用模糊集定性比较分析（fsQCA）方法探究其多元提升路径。结果 （1）2006—2021年中国农业全要素水资源绿色生产率累积增长3.60%，空间上构成“东高—中次—西低”的分布格局。（2）任何单一前因条件均不能单独成为高农业全要素水资源绿色生产率的必要驱动因素，存在技术与资源双元主导型、技术与经济双元主导型、技术与资源主导下经济驱动型以及技术与经济主导下政策支持型4类组态路径驱动农业全要素水资源绿色生产率提升。（3）产生高农业全要素水资源绿色生产率的组态路径具有明显的时序演变特征，并且条件变量间存在替代效应。结论 政府应推动农业全要素水资源绿色生产率全域协同增长，因地制宜制定农业全要素水资源绿色生产率增长战略，同时注重驱动因素之间的协同效应、替代效应。

Abstract:

The purpose of this study is to measure the agricultural total factor water green productivity in China, and reveal the complex configuration path of its improvement, so as to provide a decision-making reference for promoting the improvement of agricultural water resources utilization efficiency and realizing the green and high-quality development of agriculture. Based on the panel data of China's 31 provincial-level regions from 2005 to 2021, this research adopted a directional slacks-based measure combined with the global Luenberger productivity index model to measure the agricultural total factor water green productivity in China, and utilized the fuzzy-set qualitative comparative analysis (fsQCA) method to explore its multivariate enhancement paths. The results revealed that: (1) The cumulative growth of China's agricultural total factor water green productivity was 3.60% from 2006 to 2021, exhibiting a spatial composition of “highest in the east, second highest in the center, and lowest in the west” in space. (2) No single antecedent condition could be identified as the necessary driving factor for high agricultural total factor water green productivity, and the high agricultural total factor water green productivity primarily comprised four types of enhancement paths: technology and resource dual-driven, technology and economic dual-driven, technology and resource-led with economic support, and technology and economy-led with policy impetus. (3) The group paths that generated high agricultural total factor water green productivity displayed distinct time-series evolution characteristics, with four substitution effects observed among the conditional variables. Therefore, the government should promote synergistic growth in all regions of agricultural total factor water green productivity and develop agricultural total factor water green productivity growth strategies tailored to local conditions, while focusing on synergistic and substitution effects between drivers.