国际经济与贸易学院知识库

党的二十大报告指出，要坚持发展实体经济，着力提高全要素生产率，实现经济的提质增效。制造业作为实体经济的基础，目前面临核心技术“卡脖子”、技术创新动力不足和劳动力成本优势丧失等多重压力，生产率增速持续放缓。如何寻找新的经济增长点并借此突破技术屏障成为我国亟待解决的问题。随着数字经济的蓬勃发展，以大数据和云计算等新一代数字技术为企业的生产经营模式带来深刻变革，在“十四五”规划和“数据要素×”行动等政策共同推动下，为制造业企业实现数字化转型升级提供坚实支撑。在此背景下，探究制造业企业如何通过数字化转型为全要素生产率赋能具有一定的现实意义。
本文首先归纳总结数字化转型的经济效应与全要素生产率的影响因素，以资源基础理论、信息不对称理论、技术创新理论为理论框架，分析制造业数字化转型对全要素生产率的影响机制。其次利用文本分析法形成制造业数字化转型指标体系，计算2007-2021年我国A股制造业上市企业数字化转型程度，并利用LP法计算同时期企业全要素生产率。在实证研究方面进行全样本回归分析并通过内生性检验与多重稳健性检验；同时考虑到企业规模、产权性质、行业要素密集程度的差异性进行分组回归；引入中介变量探究其作用效应，并利用调节效应模型检验外部环境因素对数字化转型影响全要素生产率过程的调节效应。
具体得到以下研究结论：第一，数字化转型显著提升全要素生产率，在选用除本企业外的行业数字化转型均值作为工具变量进行两阶段最小二乘回归的内生性检验，并利用更换变量测度方法、缩短样本区间、解释变量滞后处理这三种方法进行稳健性检验后，仍与基准回归结果保持一致。第二，分企业来看，数字化转型对大规模企业及国有企业促进作用较强；分行业来看，数字化转型对高科技行业有显著的促进作用。第三，制造业企业数字化转型可以通过激发技术创新和优化人力资本的方式间接促进全要素生产率的增长。第四，制造业企业所处行业竞争程度与所处地区数字经济综合发展水平可以正向调节数字化转型影响全要素生产率的过程。根据上述研究结果分别对政府与企业提供相关政策建议：政府应营造良好制度环境，健全数字基础设施，推动数字金融改革；制造业企业应结合自身发展状况选择相应的数字化发展战略从而加大数字化进程，构建数字化人才培养体系，强化科技创新能力。

The report of the Twentieth Party Congress (CPC) pointed out that we should insist on developing the real economy, strive to improve total factor productivity (TFP) and realize the quality and efficiency of the economy. The manufacturing industry, as the foundation of the real economy, is currently facing multiple pressures such as the "Stranglehold" of core technology, insufficient impetus for technological innovation, and the loss of labor cost advantage, and the growth rate of productivity has continued to slow down, so how to find a new point of economic growth and use it to break through the technological barriers has become an urgent problem in China. With the booming development of the digital economy, a new generation of digital technologies such as big data and cloud computing has brought about profound changes to the production and operation mode of enterprises and has provided solid support for the realization of digital transformation and upgrading of manufacturing enterprises under the joint promotion of the "14th Five-Year Plan" and policies such as the "Data Element x" action. Under the joint promotion of the "14th Five-Year Plan" and policies such as the "Data Element X" action, it provides solid support for manufacturing enterprises to realize digital transformation and upgrade. In this context, it is of practical significance to explore how manufacturing enterprises can be empowered by digital transformation for TFP.

In this paper, we first summarize the economic effects of digital transformation and the influencing factors of TFP and analyze the influence mechanism of digital transformation on TFP in the manufacturing industry with the theoretical framework of resource base theory, information asymmetry theory, and technology innovation theory. Secondly, the text analysis method is used to form the index system of digital transformation of the manufacturing industry, to calculate the degree of digital transformation of China's A-share listed manufacturing enterprises in 2007-2021, and to calculate the TFP of the enterprises in the same period by using the LP method. In terms of empirical research, we conduct full sample regression analysis and pass the endogeneity test and multiple robustness test; secondly, taking into account the differences in enterprise size, nature of property rights, and industry factor intensity, we conduct group regression; we introduce intermediary variables to explore their effects, and we use the moderating effect model to test the moderating effect of external environmental factors on the process of digital transformation affecting TFP.

Specifically, the following research conclusions are obtained: first, digital transformation significantly improves TFP, which is still consistent with the benchmark regression results after selecting the instrumental variables of the mean value of digital transformation of industries other than our own for two-stage least squares regression, replacing the variable measurement method, shortening the sample interval, and lagging the explanatory variables for endogeneity and robustness testing. Second, by enterprise, digital transformation has a stronger promotion effect on large-scale enterprises and state-owned enterprises; by industry, digital transformation has a significant promotion effect on high-tech industries. Third, the digital transformation of manufacturing enterprises can indirectly promote TFP growth by stimulating technological innovation and optimizing human capital. Fourth, the degree of competition in the industry in which manufacturing enterprises are located and the level of comprehensive development of digital economy in the region in which they are located can positively regulate the process of digital transformation affecting TFP.Based on the above findings, the government and enterprises are provided with relevant policy recommendations:the government should create a good institutional environment, improve the digital infrastructure, and promote digital financial reform; manufacturing enterprises should increase digitalization process, choose the corresponding digital development strategy by their development situation, build a digital talent training system, and strengthen the ability of scientific and technological innovation.