摘要
以马克思的社会必要劳动时间和社会总资本的再生产理论为逻辑起点,分析了工业机器人的使用对劳动收入份额的影响,并利用2006—2017年中国省域面板数据进行了实证检验。研究结果表明,现阶段工业机器人使用规模与劳动收入份额显著负相关,伴随着工业机器人使用规模的扩张,我国劳动收入份额呈下降趋势。但从长期来看,当越过极值点后,工业机器人的使用将会促进劳动收入份额的提高。因此,短期内政策的关注点应是在推动工业机器人研发与应用的同时,如何提高劳动收入份额、构建合理的国民收入分配格局。对于劳动保护制度调节效应的分析结果表明,伴随着最低工资水平的上升和新《劳动合同法》的实施,工业机器人的使用对劳动收入份额的负向冲击会弱化,这意味着完善收入分配制度、强化劳动保护可以缓解工业机器人的使用对劳动收入份额的负向冲击。
Taking Marx's Socially necessary labour time and the reproduction theory of total social capital as the logical starting point,this paper analyzes the impact of the use of industrial robots on the share of labor income and conducts an empirical test using the provincial panel data of China from 2006 to 2017.The results show that:the usage scale of industry robots is significantly negatively correlated with the labor share.With the expansion of industry robots,the labor share would be declining.However,the usage of industry robots can promote technological innovation and the high-quality development of manufacturing industry.Moreover,in the long run,when the extreme point is crossed,the usage of industry robots can increase the labor share.Therefore,it is crucial to improve the labor share and build a reasonable national income distribution while promoting the application of industry robots in the short term.The analysis of the regulation effect shows that,with the rise of the minimum wage and the implementation of the new labor contract law since 2008,the negative impact of industry robots on the labor share will be weakened.This means improving the income distribution system and strengthening labor protection will help alleviate the adverse impact of industry robots usage on the national income distribution.
作者
孙慧文
王贺雨
Sun Huiwen;Wang Heyu
出处
《财经科学》
北大核心
2023年第7期64-76,共13页
Finance & Economics
基金
国家社会科学基金后期资助项目“基于要素错配的国民收入分配格局问题研究”(21FJLB016)
河南省高等学校哲学社会科学基础研究重大项目“中原城市群要素价格扭曲与产业结构升级的耦合发展问题研究”(2019-JCZD-011)的资助。
关键词
工业机器人
劳动收入份额
社会必要劳动时间
社会总资本再生产
劳动保护
Industry robots
Labor Income Share
Socially Necessary Labor Time
Reproduction of Total Social Capital
Labor Protection