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Prediction of High-Tech Talents Flow Impact on Labor Income Share: Based on DEA and Fractional Hausdorff Grey Model

机译:高科技人才流动对劳动力收入的影响:基于DEA和Fractional Hausdorff灰色模型

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The purpose of this paper is to analyze the impact of high-tech talents flow on labor income share and explore the influencing mechanism. It can be proved that high-tech talents flow affects labor income share by production function, with technological progress as a mediator variable. The labor income share is the dependent variable, and the gravity of high-tech talents as the independent variable is the index to measure the high-tech talents flow, constructing the panel data model with the Malmquist index of technological progress as a mediator variable. Furthermore, the Malmquist index of technological progress is decomposed into catching-up of technological progress index and leapfrogging of technological progress index, which, respectively, replaces the Malmquist index of technological progress as a mediator variable in the panel data model. Regression analysis shows that technological progress is a mediator variable for high-tech talents flow to reduce labor income share, and the impact mainly comes from leapfrogging of technological progress. However, although the mediating effect of catching-up technological progress index is not significant at the significance level of 10%, it is a mediator variable for high-tech labor mobility to increase income share at the significance level of 20%. Finally, this paper predicts the change in labor income share from 2018 to 2027 by the fractional Hausdorff grey model, and the results show that it is an increasing trend. However, the Gini coefficient whose change trend is opposite to the labor income share remains high in the past two years, indicating that there are other factors affecting the income gap, such as the urbanization rate and the transportation convenience. The innovation of this paper is mainly to reveal that the leapfrogging of technological progress is the major cause of the high-tech talents flow rising income inequality gap, while the catching-up of technological progress is the source of the former narrowing the latter. The fractional Hausdorff grey model predicts that the key determinants of income inequality gap are more than labor income share.
机译:本文的目的是分析高科技人才流动对劳动收入的影响,并探讨了影响机制。可以证明,高科技人才流量通过生产函数影响劳动力收入份额,作为调解员变量的技术进步。劳动力收入份额是受抚养变量,高科技人才的重力作为独立变量是测量高科技人才流量的指数,构建面板数据模型作为介质变量的技术进步的讽刺指标。此外,技术进步的Malmquist指标分解成追赶技术进步指数和技术进步指数的跨越,分别取代了面板数据模型中的调解员变量的技术进步的Malmquist指标。回归分析表明,技术进步是高科技人才流量的调解员变量,以降低劳动力收入份额,影响主要来自技术进步的跨越。然而,虽然追赶技术进步指数的调解效果在10%的意义水平的显着率不显着,但它是一种高科技劳动力流动的调解员变量,以增加收入份额,以20%的意义。最后,本文预测了2018年至2027年劳动收入份额的变化,由分数Hausdorff灰色模型,结果表明,这是一种越来越趋势。然而,过去两年的改变趋势与劳动收入份额相反的基尼系数仍然很高,表明还有影响收入差距的其他因素,如城市化率和交通便利。本文的创新主要是揭示技术进步的跨越性是高科技人才流量的主要原因,收入不平等差距,而技术进步的追赶是前者缩小后者的来源。分数Hausdorff灰色模型预测收入不平等差距的关键决定因素不仅仅是劳动力收入份额。

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