【摘要】 传统要素促进制造业生产率提升的作用不断下降,在制造业高质量发展的要求下,数据要素能否成为驱动制造业生产率提升的新动能是中国进入数字经济时代后亟待回答的问题。本文采用双重机器学习检验了数据要素对制造业生产率的影响。研究发现,数据要素能够通过提高数据挖掘水平与提升资本和技术效率促进制造业生产率提升;数据要素对技术密集型制造业以及中国东部、南方地区制造业生产率提升更为明显,同时数据要素对制造业生产率影响的南北差距小于东西差距;时间趋势分析表明,进入大数据元年后数据要素对中国制造业生产率提升的作用日益显著。更多还原

【Abstract】 The role of traditional factors in promoting the improvement of manufacturing productivity is constantly declining.Under the requirements of high-quality development of manufacturing industry,whether data factors can become the new driving force for the improvement of manufacturing productivity is an urgent question to be answered after China enters the era of digital economy.Therefore,based on China ’s inter-provincial panel data from 2012 to 2019,this paper uses double machine learning to explore the impact of data factors on manufacturing productivity.It is found that data factors significantly promote the improvement of China ’s manufacturing productivity.In terms of influencing mechanism,data factors can promote the improvement of manufacturing productivity by improving data mining level,capital and technological efficiency.Heterogeneity analysis shows that data factors have more significant productivity improvement on technology-intensive manufacturing industries and manufacturing industries in eastern and southern regions of China,and the north-south gap of data factors on manufacturing productivity is smaller than the east-west gap.Time trend analysis indicates that,data factors have an increasingly significant role in improving the productivity of China ’s manufacturing industry after entering the first year of big data.更多还原