北京邮电大学学报(社科版) ›› 2020, Vol. 22 ›› Issue (1): 77-86.doi: 10.19722/j.cnki.1008-7729.2019.0203

• 教育研究 • 上一篇    下一篇

义务教育财政支出效率评估与影响机制分析

  

  1. 武汉理工大学 经济学院,湖北 武汉430070
  • 收稿日期:2019-05-22 出版日期:2020-02-28

Efficiency Evaluation and Influencing Mechanism of Compulsory Education Fiscal Expenditure

  1. School of Economics, Wuhan University of Technology, Wuhan 430070, China
  • Received:2019-05-22 Online:2020-02-28

摘要: 基于我国目前教育财政支出机制,探究西部各省份义务教育财政支出效率及其影响因素。在此基础上,运用三阶段DEA(Data Envelopement Analysis)效率模型,采用西部各省份2007—2016年的义务教育财政支出相关数据,评估西部12个省份义务教育财政支出效率,同时探究环境因素对财政支出效率的影响机制。对西部各省份效率的分析表明:综合效率上,内蒙古和甘肃相对较高,受环境因素影响偏大;规模效率上,西藏相对较低,受环境因素影响最为明显;纯技术效率上,整体相差不大且处于较高水平,不受环境因素影响。进一步分析发现,环境因素中,城镇化比例、地方政府关注度及受教育年限对财政支出效率存在正向影响,而人均GDP、老年化人口及教育密度对财政支出效率存在负向影响。

关键词: 义务教育, 财政支出效率, 三阶段DEA模型, 环境因素

Abstract:  Based on Chinas current education fiscal expenditure mechanism, the efficiency of fiscal expenditure of compulsory education in the western provinces and its influencing factors are explored On this basis, the three-stage DEA efficiency model is used to evaluate the data from 2007 to 2016, and to evaluate the efficiency of their fiscal expenditure on compulsory education and explore the influencing mechanism made by different environmental factors The analysis shows that: Inner Mongolia and Gansu are relatively high in terms of overall efficiency, and are more affected by environmental factors; in terms of scale efficiency, Tibet is relatively low, and is most affected by environmental factors; with regard to technical efficiency, the overall difference is small and it is at a high level and not affected by environmental factors Further analysis finds that among the environmental factors, urbanization ratio, local government attention and years of education have a positive impact on the efficiency of fiscal expenditure, while per capita GDP, aging population and education density have a negative impact on the efficiency of fiscal expenditure

Key words: compulsory education, efficiency of fiscal expenditure, three-stage DEA model, environmental factors

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