摘要
文章基于我国2012—2019年的省级面板数据,运用DSBM方法测算了各省份制造业发展效率,并采用Tobit模型对制造业发展效率的影响因素及影响程度进行实证分析。结果显示,东部地区省份制造业发展效率领先于中西部地区省份,且稳中有进。地区之间制造业发展效率差异呈现扩大态势。进一步研究发现,科技研发投资和生产性服务业集聚度显著正向影响制造业发展效率,而制造业非国企数量占比、制造业法人数量占比与制造业行业政策占比阻碍制造业发展效率的提升。在控制了省份间经济发展水平差异后,新增固定资产投资显著正向影响制造业发展效率。因此,加大科技创新投入、发展生产性服务业、合理投资和科学推进组织管理变革是提高制造业发展效率的有效途径。
Based on the provincial statistical data of China from 2012 to 2019, this paper uses DSBM method to measure the development efficiency of manufacturing industry of each province, and then adopts Tobit model to conduct empirical analysis on the influencing factors and degree of the development efficiency of manufacturing industry. The results show that the manufacturing development efficiency of eastern provinces is ahead of that of central and western provinces, with steady progress, and that the gap of manufacturing development efficiency between regions is expanding. Further research findings are shown as below: Technology R&D investment and producer services agglomeration degree have a significant positive impact on the development efficiency of manufacturing industry, while the proportion of non-state-owned enterprises in manufacturing industry, the proportion of legal persons in manufacturing industry and the proportion of policies in manufacturing industry hinder the improvement of the development of manufacturing efficiency. After controlling differences between the provincial economic development levels, the new fixed asset investment has significantly positive influence on the development efficiency of manufacturing industry. Therefore, increasing scientific and technological innovation input, developing producer services, rationally investing and scientifically promoting the organizational management reform are effective ways to improve the development efficiency of manufacturing industry.
作者
张洪烈
刘宁
Zhang Honglie;Liu Ning(Department of International Cooperation and Exchange,Yunnan University of Unance and Economics,Kunming 650221,China;Business School,Yunnan University of Unance and Economics,Kunming 650221,China)
出处
《统计与决策》
CSSCI
北大核心
2021年第19期93-97,共5页
Statistics & Decision
基金
国家自然科学基金资助项目(71763028)
云南财经大学研究生创新基金项目(2021YUFEYC068)。