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我国高等教育投入效率时空演化研究

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聚焦于提升中国高等教育投入效能,推动高等教育强国建设,选取全国 31 个省份为研究对象,以高等院校的专任教师、固定资产和教育经费作为投入指标,按照"人才培养—科技成果—社会服务"的逻辑框架选取高等教育四类产出指标,从经济发展水平、政府支持力度和对外开放程度三个方面筛选环境变量,借助三阶段DEA模型对2017-2021 年中国高等教育投入效率进行深入分析.研究结果显示,在初始阶段中国高等教育投入效率整体较高,揭示出高等教育体系在资源配置及管理和技术方面已取得一定成效.通过进一步随机前沿(SFA)分析表明,地区生产总值和进出口总额占地区生产总值的比重增加与高等教育投入效率的提升呈正相关,而教育支出占一般公共预算支出比重的增加与高等教育投入效率的提升呈负相关.在剔除环境因素和随机扰动的影响后,综合效率均值有所下降,并呈现"东部领先、中部次之、西部滞后"的区域差异特征.
A Study of the Spatial and Temporal Evolution of China's Higher Education Input Efficiency
Focusing on improving the efficiency of China's higher education inputs and promoting the construction of a strong higher education country,31 provinces in China are selected as the research objects,the full-time teachers,fixed assets and education funds of higher education institutions are taken as the input indicators,four types of outputs of higher education are selected in accordance with the logical framework of"talent cultivation-scientific and technological achievements-social services",and environmental variables are screened from the level of economic development,the strength of government support and the degree of openness to the outside world,so as to conduct an in-depth analysis of China's higher education input efficiency in 2017-2021 with the help of the three-stage DEA model.The results of the study show that China's higher education input efficiency is overall high in the initial stage,revealing that the higher education system has achieved some success in resource allocation and management and technology.Further stochastic frontier(SFA)analysis shows that an increase in the proportion of regional GDP and total import and export to regional GDP is positively correlated with an increase in higher education input efficiency,while an increase in the proportion of education expenditure to general public budget expenditure is negatively correlated with an increase in higher education input efficiency.After removing the influence of environmental factors and random disturbances,the average value of comprehensive efficiency decreases,and shows the regional difference characteristic of"leading in the east,second in the center and lagging in the west".

higher educationinput efficiencythree-stage DEASFA regressionpure technical efficiency

张璐、赵宇蓉、雅玲

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内蒙古工业大学经济管理学院,内蒙古 呼和浩特 010051

高等教育 投入效率 三阶段DEA SFA回归 纯技术效率

2025

经济与管理评论
山东财经大学

经济与管理评论

北大核心
影响因子:0.745
ISSN:2095-3410
年,卷(期):2025.41(1)