数字经济赋能农业绿色全要素生产率——基于土地流转与数字普惠金融的双重路径研究

Digital Economy Empowering Agricultural Green Total Factor Productivity: A Dual-Path Study Based on Land Transfer and Digital Inclusive Finance

摘要

在我国“双碳”战略落地实施与数字经济深度发展的双重背景下，推动农业绿色低碳转型已成为实现中国农业实现高质量发展的核心任务。基于2011—2023年我国30个省份（不含西藏、港澳台地区）的省级面板数据，采用全局超效率SBM-GML模型测度各省份农业绿色全要素生产率，运用熵值法测算数字经济综合指数。构建双向固定效应模型，采用两阶段最小二乘法等多重手段分析双向因果导致的内生性问题。同时，运用中介效应模型，对土地流转和数字普惠金融作用路径进行分析。实证研究表明：1）数字经济对我国农业绿色全要素生产率具有显著的直接正向赋能效应。2）中介效应结果表明，数字经济依托大数据平台打破信息壁垒，促进了土地流转市场的透明化、规范化，进而通过规模化、集约化经营优化农地配置，从而提升农业绿色全要素生产率；同时，数字经济拓展了数字普惠金融的服务边界和覆盖广度，通过缓解小农户信贷配给和技术外溢约束，为绿色农业技术研发、引进与应用提供了资金保障。3）异质性检验结果显示，数字经济对农业绿色全要素生产率的促进作用在粮食主产区显著，但在非粮食主产区不显著；相较于黄河流域，长江流域农业发展受数字经济的绿色赋能效果更强。基于区域异质性特征，未来政策制定应当采取因地制宜的差异化协同策略：一方面，继续推进乡村数字基础设施全覆盖，搭建集产供销于一体的智慧农业数字化平台；另一方面，充分释放土地资源优化配置与数字普惠金融赋能农业的叠加效应，逐渐缩小城乡、区域农业数字鸿沟，促进全国农业绿色现代化协同均衡发展。

Abstract

Against the dual backdrop of the implementation of China's “dual carbon” strategy and development of digital economy, promoting the green and low-carbon transformation of agriculture has become the important task to realise high-quality development of China's agriculture. Based on provincial panel data of 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2011 to 2023, the global super-efficiency SBM-GML model is used to measure agricultural green total factor productivity in each province, and the entropy method is used to calculate the comprehensive index of digital economy. A two-way fixed effects model is constructed, and multiple methods such as two-stage least squares are used to address the endogeneity problem caused by two-way causality. Meanwhile, a mediation effect model is used to analyze the action paths of land transfer and digital inclusive finance. Empirical research shows that digital economy has a significant direct positive empowering effect on China's agricultural green total factor productivity. The mediation effect results indicate that digital economy, relying on big data platforms, breaks information barriers, promotes the transparency and standardization of the land transfer market, and thereby optimizes agricultural land allocation through large-scale and intensive management, thus enhancing agricultural green total factor productivity. At the same time, digital economy expands the service boundaries and coverage of digital inclusive finance, and by alleviating the credit rationing and technology spillover constraints of smallholder farmers, provides financial guarantee for the research and development, introduction, and application of green agricultural technologies. Heterogeneity test results show that the promoting effect of digital economy on agricultural green total factor productivity is significant in major grain-producing areas, but not significant in non-major grain-producing areas. Compared with the Yellow River Basin, agricultural development in the Yangtze River Basin is more strongly empowered by the digital economy's green effect. Based on regional heterogeneity characteristics, future policy formulation should adopt differentiated collaborative strategies tailored to local conditions. On the one hand, policymakers should continue to promote full coverage of rural digital infrastructure and build smart agricultural digital platforms that integrate production, supply, and marketing; on the other hand, they should fully leverage the synergistic effects of optimizing land resource allocation and empowering agriculture through digital inclusive finance, gradually narrow the urban-rural and regional agricultural digital divide, and promote the coordinated and balanced development of China's green agricultural modernization.

关键词

农业绿色全要素生产率 / 数字经济 / 土地流转 / 数字普惠金融 / 中介效应模型

Key words

agricultural green total factor productivity / digital economy / land transfer / digital inclusive finance / mediation effect model

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基金资助

国家自然科学基金面上项目(28932020039)