机器人应用背景下行业间劳动力转移能提升全要素生产率吗?OA北大核心CHSSCD

Improving Total Factor Productivity(TFP)is an inevitable requirement for achieving high-quality economic development.This study,selecting panel data from 30 provinces in China from 2006 to 2019 and employing the Effective Structure Change Index to measure the efficiency-enhancing inter-industry labor transfer,investigates the impact of labor transfer on TFP growth and its mechanism of action.The research finds that the positive effect of effective structural change of labor transfer on the growth of TFP shows a pattern of first increasing and then decreasing.Heterogeneity analysis shows that compared with provinces with low levels of robot application,the promotion effect of the effective structural change index of labor transfer on the growth of TFP is stronger in provinces with high levels of robot application.Moreover,the increase in the index of effective structural change of labor has a positive impact on the TFP growth of conventional tasks and competitive industries,while having a reverse effect on unconventional tasks and monopolistic industries.To promote the efficient and orderly flow of labor elements,the study suggests that it is necessary to build a"Talent Pool"competent in different types of tasks,establish a collaborative innovation system between robot production,education,and research institutions to promote balanced and intelligent industrial development between regions,and improve anti-monopoly laws and regulations in the digital economy era to better take advantage of the important role of new-generation information technology in empowering the transformation and upgrading of competitive industries.