摘要
采用基于实数编码加速遗传算法的投影寻踪模型,对2014—2021年我国各城市的数据要素发展水平进行量化测度,并将其纳入新结构新生产函数实证检验其对我国经济增长的影响效应与机制。研究发现,数据要素作为新质生产力,显著推动了国内生产总值提升,且该效应受到宏观政策导向和区域经济结构的影响,凸显了政策制定者在优化数据资源管理和利用方面的作用。同时,数据要素发展水平的优化还促进了区域经济一体化和经济增长模式的非线性动态变化。研究结果表明:技术效率和劳动生产率提升,以及资本积累效应是数据要素推动经济增长的三条路径。上述结论为理解数据要素如何影响经济增长提供了新的视角,也为政策制定提供了实证基础,在数字经济时代,优化数据资源的开发和应用是推动经济持续增长的关键。为充分释放数据要素在新时代经济发展中的潜力,应加大对数据基础设施的投资,完善数据管理和应用的法律法规,促进数据的开放共享,并激发企业和研究机构的创新活力。这些政策建议不仅有助于优化数据资源的管理和利用,也为推动我国经济的高质量发展提供重要的理论依据和政策指导。
The authors employ a projection pursuit model based on a real-coded accelerated genetic algorithm to quantitatively measure the development level of data factors in various cities across China from 2014 to 2021.This measurement is then incorporated into a new structural production function to empirically test its impact effect and mechanisms on China's economic growth.It is found that data factors,as a new quality productive force,significantly promote the growth of gross domestic product(GDP),and this effect is influenced by macroeconomic policy orientation and regional economic structure,highlighting the role of policymakers in optimizing data resource management and utilization.Additionally,the optimization of the development level of data factors fosters regional economic integration and non-linear dynamic changes in economic growth models.The results indicate that the enhancement of technical efficiency and labor productivity,as well as the cumulative effect of capital,are the three pathways through which data factors drive economic growth.These conclusions provide a new perspective on understanding how data factors affect economic growth and offer an empirical foundation for policy formulation.In the digital economy era,optimizing the development and application of data resources is crucial for sustaining economic growth.To fully unleash the potential of data factors in the new era of economic development,investments in data infrastructure should be increased,legal regulations on data management and application should be improved,data openness and sharing should be promoted,and the innovative vitality of enterprises and research institutions should be stimulated.These policy recommendations not only help optimize the management and utilization of data resources but also provide important theoretical basis and policy guidance for promoting high-quality economic development in China.
作者
聂昀秋
马晓君
郑佳宁
NIE Yun-qiu;MA Xiao-jun;ZHENG Jia-ning(School of Statistics,Dongbei University of Finance and Economics,Dalian 116012,Liaoning,China)
出处
《中国流通经济》
北大核心
2024年第8期56-68,共13页
China Business and Market
基金
国家社会科学基金重大项目“数字赋能中国全球价值链攀升的路径与测度研究”(21&ZD148)
2023年全国统计科学研究重点项目“我国产业链供应链韧性的监测与提升:链条解构、动态测度与路径模拟”(2023LZ024)
2024年中国物流学会、中国物流与采购联合会面上研究课题“数字物流对供应链韧性和风险防控的平衡策略与实施路径研究”(2024CSLKT3-025)
辽宁省社会科学规划基金重大委托项目“辽宁省产业链供应链韧性和安全水平的监测与提升:链条解构、动态测度与路径模拟”(L23ZD053)。
