经济高质量发展背景下京津冀制造业创新效率及其影响因素
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F062

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河北省高等学校青年拔尖人才计划项目(编号:BJ2021106)


The Innovation Efficiency and Corresponding Influencing Factors of Manufacturing Industry in Beijing-tianjin-hebei Region Under the Background of High-quality Economic Development
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    摘要:

    制造业创新效率是衡量京津冀经济高质量发展的重要内容之一,文章利用DEA-BCC模型与Malmquist指数,实证分析了京津冀制造业2016—2019年的创新效率及其变化情况;随后利用面板Tobit模型考察了影响制造业创新效率的相关因素。研究表明:京津冀制造业创新效率主要表现为规模报酬递增,技术创新的全要素生产率(TFP)、技术效率(TE)、规模效率(SE)总体偏低、多数行业处于无效率状态;通过计算基尼系数发现,不同行业的创新效率存在明显差距,不平等现象突出,并呈现加剧趋势;进一步计算Malmquist指数发现,2016—2019年京津冀制造业的创新效率总体趋于上升;从行业细分来看,相对于低技术产业,高技术产业的效率优势更为明显,行业的技术水平对创新效率具有正向效应;最后,相关因素分析发现:政府补助、主营业务收入、市场化进程、外商直接投资与制造业创新效率正相关,可以促进效率的提升;而融资约束与创新效率负相关,对创新效率的影响具有一定的抑制作用。

    Abstract:

    Manufacturing innovation efficiency is one of the important dimensions of high-quality economic development in Beijing-Tianjin-Hebei region. In this sense, this paper, via DEA-BCC model and Malmquist index, analyzes the innovation efficiency and its variations of the manufacturing industry in Beijing-Tianjin-Hebei region, ranging from 2016 to 2019. Accordingly, the panel Tobit model is employed to analyze the factors influencing the innovation efficiency of manufacturing industry. The results show that the innovation efficiency of manufacturing industry in this region is mainly manifested by the increasing scale reward and the overall low levels in terms of technology innovation, such as the total factors productivity (TFP), technology efficiency (TE), and scale efficiency (SE). In this regard, most industries are in a state of very low efficiency. Through the calculation of Gini coefficient, it is also found that there is a significant gap in the innovation efficiency of different industries, and the inequality between industries has become prominent and increasingly serious. Further calculation of Malmquist index demonstrates that the overall innovation efficiency in question tends to rise from 2016 to 2019; From the perspective of industry segmentation, the efficiency advantage of high-tech industry is more remarkable than that of low-tech industry, accordingly, the technology level has a positive effect on innovation efficiency; Finally, via the panel Tobit model, we find that some factors are positively correlated with manufacturing innovation efficiency, namely, government subsidies, main business income, marketization process, and direct foreign investment, thereby promoting the efficiency. It is also noted that financing constraints are negatively correlated with innovation efficiency, thus inhibiting the improvement of innovation efficiency.

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王金波,肖凤华,李兴光.经济高质量发展背景下京津冀制造业创新效率及其影响因素[J].河北工程大学学报社会科学版,2022,39(3):21-30

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  • 收稿日期:2022-04-07
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  • 在线发布日期: 2022-11-03
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