数据要素市场发展与生产率提升

Data Factor Market Development and Productivity Improvement

本文从中国制造业迫切需要实现全要素生产率持续提升这一现实出发,结合当前正在重点推进的要素市场化配置改革,着重关注了数据要素市场发展对制造业全要素生产率提升的影响。本文以大数据发展反映数据要素市场发展状况,结合2011—2020年A股上市公司数据,研究发现:大数据发展水平显著促进了制造业企业全要素生产率提升,该结论在控制内生性问题等一系列稳健性检验后仍成立。“十三五”期间的政策支持改善了大数据发展水平的作用效果,而沿海城市、省会城市和数据法治建设更完善的地区大数据发展水平的促进作用更明显,大数据发展水平对智能化程度较高企业的促进作用更大。进一步地,大数据发展水平对制造业企业全要素生产率提升的促进作用,主要是通过优化要素资源配置、降低交易成本、提高管理效率等机制实现的;而劳动力市场、资本市场与技术市场等要素细分市场发展,增强了大数据发展水平的作用效果。本文验证了大数据发展水平在制造业企业生产率提升中的重要作用,为数据要素市场发展与制造业高质量发展提供了有益的参考依据。

Based on the reality that China's manufacturing industry urgently needs to continuously improve productivity,and the ongoing factor market reform,this paper focuses on the impact of the big data development on the productivity growth of manufacturing enterprises(PCME).The development of the big data factor market is reflected by the development of big data,combined with the city-level and A-share listed company data from 2011 to 2020.It is found that the big data development(BDD)significantly promotes the productivity growth of manufacturing enterprises.The results can be justified after the control of endogenous problems and the robustness test of enterprise level data.The policy supported during the"13th Five-Year Plan"period has improved the effect of the big data development,while the promoting effect of the big data development is more obvious in coastal cities,provincial capitals and the city that has strict data rule of law,and the promoting effect of the big data development on enterprises with higher intelligence degree is greater.Moreover,the promotion effect of the big data development on the productivity growth of manufacturing enterprises is mainly through the mechanisms including optimizing the factor efficiency,reducing the transaction costs and improving management efficiency.In addition,the development of the labor market and capital market and technology market has enhanced the promotion effect of the big data development on the productivity growth of manufacturing enterprises.This paper shows the effect of the big data development on the productivity growth of manufacturing enterprises and provides a beneficial reference for the development of the big data factor market and the high-quality development of China's manufacturing industry.The above research findings provide significant policy insights for promoting the productivity growth of manufacturing enterprises and using the big data to promote factor market development.Firstly,the government policies for improving manufacturing productivity need to be combined with the development of big data.It is necessary to take the improvement of manufacturing total factor productivity as an important direction for the development of data factor markets.Particularly,inland cities and non-provincial capital cities should accelerate the development of data factor markets.The city shall formulate data element market development policies that conform to the regional institutional environment in combination with its own unique regional industrial base,resource conditions,market advantages and legal construction.For example,coastal cities such as Shanghai,Guangzhou and Shenzhen need to rely on their own talent and technological advantages to vigorously develop sophisticated businesses,such as data circulation trading and data technology research and development.Besides,the underdeveloped areas around the central economic zone need to develop traditional data services such as data labeling and cleaning based on the characteristics of human resources.Regional governments with poor data rule of law construction need to focus on improving data rights,especially in data opening Legislation and market supervision on data transaction and data security.Secondly,the policy that promote the development of the data factor market need to be coordinated with the measures that optimize the allocation of factor resources,reduce transaction costs,and improve management efficiency.Specifically,using the big data platform to improve the innovation and design ability of products,improving the level of resource utilization and enterprise management,and promoting the flattening and rationalization of the organizational structure.Thirdly,the government policy for the development of the data factor market need to be coordinated with the development of the labor,capital,technology and other factor markets.Especially we should attach more importance on these areas where the development of the labor market,capital market and technology and other factor markets is not perfect.The above work plays an important role in promoting the development of big data and real economy.