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LABOUR MOBILITY AND PLANT PERFORMANCE: ON THE (DIS)SIMILARITY BETWEEN LABOUR- AND CAPITAL-INTENSIVE SECTORS FOR KNOWLEDGE DIFFUSION AND PRODUCTIVITY

机译:劳动力流动性和工厂绩效:关于知识扩散和生产率的劳动密集型部门和资本密集型部门之间的(不相似)

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摘要

In this article we analyse differences between capital- and labour-intensive sectors with regard to the impact of workforce composition and labour mobility on plant performance. By the use of geo-referenced longitudinal employer-employee data on a micro level, we analyse labour flows between plants within and between labour market regions. The analysis is carried out using weighted least squares (WLS) regression analysis combined with additional variance analysis (ANOVA). The results show that there are differences between the sectors with regard to both in-house workforce composition and type of skill inflow. A high degree of related knowledge in the in-house workforce has a strong positive effect on plant performance in the labour-intensive sectors. The analysis of labour inflow indicates that knowledge in the capital-intensive sectors is localized - only intra-regional labour flows give rise to increased plant productivity. In the labour-intensive sectors, the geographic and cognitive dimensions complement one another; similar knowledge needs to be non-local in order to be beneficial to plant performance, and unrelated knowledge mainly contributes to plant productivity growth when it is local.
机译:在本文中,我们分析了劳动力密集型部门和劳动力密集型部门在劳动力构成和劳动力流动性对工厂绩效的影响方面的差异。通过在微观水平上使用地理参考的纵向雇主-雇员数据,我们分析了劳动力市场区域内和之间的工厂之间的劳动力流动。使用加权最小二乘(WLS)回归分析结合其他方差分析(ANOVA)进行分析。结果表明,就内部劳动力组成和技能流入类型而言,各部门之间存在差异。内部劳动力的高度相关知识对劳动密集型行业的工厂绩效产生了巨大的积极影响。对劳动力流入的分析表明,资本密集型行业的知识是本地化的,只有区域内部劳动力流动才能提高工厂的生产率。在劳动密集型部门中,地理和认知方面是相辅相成的。相似的知识必须是非本地的,才能对工厂的绩效有所帮助,而不相关的知识则在本地时主要有助于植物生产力的增长。

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