Data Factors,Data Mining,and Productivity Improvement of Chinese Service Industry——Causal Inference from Double Machine Learning
China's economy has entered a development stage dominated by the service industry,but the momentum of traditional factors to improve the productivity of the service industry is insufficient.In the era of digital economy,the e-mergence of data factors provides new possibilities for further improving service industry productivity.Based on China's inter provincial panel data from 2012 to 2019,this paper uses the double machine learning method to explore the effects,internal mechanisms and heterogeneous effects of data factors on the improvement of service industry productivity.The re-sults show that data factors significantly promote the productivity improvement of China's service industry;The improve-ment of data mining ability significantly enhances the effects of data factors on the productivity improvement of the service industry;Data factors are more conducive to the improvement of productivity in the life service industry,and their impact on the improvement of productivity in the service industry in eastern and southern regions of China is more significant.
data factorsdata miningservice industry productivitydouble machine learning
NETL
NSTL
万方数据
