基于数智化背景下新质生产力赋能农业经济高质量发展的研究

Research on Empowering High-Quality Development of the Agricultural Economy through New Quality Productivity in the Context of Digital Intelligence

摘要: 在全面推进乡村振兴、加快建设农业强国的关键阶段，数智化背景下新质生产力培育成为推动农业经济高质量发展的核心抓手。本文以2020~2024年中国31个省级行政区面板数据为研究样本，运用熵权法构建包含数字技术、生产要素、经济高质量、绿色发展四大维度的综合评价指标体系，测度农业新质生产力发展水平，并结合双向固定效应面板回归、中介效应模型等方法，实证检验新质生产力赋能农业经济高质量发展的效应与作用机制。研究发现，2020~2024年我国农业新质生产力整体呈波动上升态势，数字技术维度增长最为显著，区域发展呈现非均衡特征；农业新质生产力对农业经济高质量发展具有显著正向赋能效应，农业生产要素升级是核心驱动因素，农村收入水平、农业产业规模在二者间发挥部分中介作用，经多维度稳健性检验后依然成立。本文还厘清了数智化应用广度的调节作用，丰富了数智化视角下新质生产力与农业经济高质量发展的相关理论研究，为依托新质生产力培育推动农业经济高质量发展、破解农业区域发展不均衡问题提供了实证参考与实践路径。

Abstract: At this critical juncture of comprehensively advancing rural revitalization and accelerating the development of an agricultural powerhouse, cultivating new-quality productive forces within the digital and intelligent context has become the core driver for promoting high-quality development in the agricultural economy. This study employs panel data from China’s 31 provincial-level administrative regions from 2020 to 2024. Utilizing the entropy weighting method, it constructs a comprehensive evaluation index system encompassing four dimensions: digital technology, production factors, high-quality economic development, and green development, to measure the development level of new-quality productive forces in agriculture. Combining methods such as two-way fixed-effects panel regression and mediation effect models, it empirically examines the effects and mechanisms through which new-quality productive forces empower high-quality agricultural economic development. The findings reveal that China’s new-quality agricultural productivity exhibited an overall fluctuating upward trend from 2020 to 2024, with the most significant growth occurring in the digital technology dimension. Regional development showed uneven characteristics. New-quality agricultural productivity exerts a significant positive enabling effect on high-quality agricultural economic development, with the upgrading of agricultural production factors serving as the core driving factor. Rural income levels and the scale of agricultural industries partially mediate this relationship, a finding that remains valid after multidimensional robustness tests. This study also clarifies the moderating role of digital and intelligent application breadth, enriching theoretical research on new-quality productivity and high-quality agricultural economic development from a digital-intelligence perspective. It provides empirical references and practical pathways for fostering high-quality agricultural economic development through new-quality productivity cultivation and addressing regional imbalances in agricultural development.