金融科技、融资约束与全要素生产率——基于制造业上市公司的实证研究  

Fintech,Financing Constraints and Total Factor Productivity: An Empirical Study Based on Manufacturing Listed Companies

作　　者：王世文 张尹 祝演 Wang Shiwen;Zhang Yin;Zhu Yan

机构地区：[1]苏州科技大学商学院

出　　处：《宏观经济研究》2022年第8期55-64,74,共11页Macroeconomics

基　　金：国家自然科学项目“新产品开发前端客户隐性知识获取过程及机理研究”(71801169);苏州市软科学研究项目“创新金融服务模式完善科技型中小企业的成效与提升对策研究”的研究成果。

摘　　要：金融科技被认为是破解融资约束问题的有效手段,而融资约束又是制约企业全要素生产率的关键因素。因此本文以中国2016—2020年6985家A股制造业上市公司为样本,通过数据挖掘法构建区域金融科技指数,利用OP法和SA指数法分别计算全要素生产率、融资约束,对金融科技、融资约束与全要素生产率三者关系进行实证研究。结果表明:金融科技能够提高企业全要素生产率水平,这一结论在剔除直辖市的数据和进行随机样本抽取等稳健性检验后仍然成立;金融科技能够通过缓解企业面临的融资约束提升全要素生产率水平;相比于国有企业,金融科技对民营企业的正向影响更加显著;金融科技对全要素生产率的负向作用随着企业规模的增大而更加明显。Fintech is considered to be an effective means to solve the problem of financing constraints, which is the key factor restricting the total factor productivity of enterprises. Therefore, this paper takes 6985 A-share manufacturing listed companies in China from 2016 to 2020 as samples, constructs a regional fintech index through data mining, calculates total factor productivity and financing constraints by using OP method and SA index method, and makes an empirical study on the relationship of fintech, financing constraints and total factor productivity. The results show that fintech can improve the total factor productivity of enterprises, and this conclusion still holds after excluding the data of municipalities directly under the central government and conducting robustness tests such as random sample sampling;fintech can improve the total factor productivity by alleviating the financing constraints faced by enterprises;the positive effect of fintech on private enterprises is more significant than that of state-owned enterprises;the negative effect of fintech on total factor productivity becomes more pronounced with the increase of enterprise size.

关 键 词：金融科技 全要素生产率 融资约束 中介效应 

分 类 号：F832[经济管理—金融学] F425F406.7