Abstract
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.
Highlights
China’s carbon emissions are among the top in the world, so it has great pressure and potential to reduce carbon emissions
This paper introduces the Malmquist index of carbon emission reduction technological progress and uses the IDA (Index Decomposition Analysis) to decompose it into catching-up of technological progress index and the leapfrogging of technological progress index. is paper analyzes the influence of the high-tech labor flow on the labor income share with these two kinds of technological progress indexes as mediator variables and gives the possible path to increase the labor income share
CO2 data are from the “Energy” section in the “2006 IPCC Guidelines for National Greenhouse Gas Inventories” designated by the Intergovernmental Panel on Climate Change, which can be calculated using the final consumption of industrial energy data from the China Energy Statistical Yearbook. e Urb, education level (Edu), pension insurance (Pen), unemployment insurance (Unempl), and health insurance (Heal) data are all from the China Urban Statistical Yearbook. e data regarding highway and railway mileage are from the China Transportation Statistical Yearbook
Summary
China’s carbon emissions are among the top in the world, so it has great pressure and potential to reduce carbon emissions. The impact of the introduction of high-tech talents on the labor income share is uncertain on account of carbon emission reduction technological progress. The impact of high-tech talents flow on labor income share may be different due to different types of technological progress. E innovation of this paper is that the mediator variable of high-tech talents flow affecting labor income share is mainly the leapfrogging of technological progress rather than the catching-up of technological progress. The leapfrogging of technological progress is a mediator variable for high-tech talents flow to reduce labor income share at a significance level of 10%. The catching-up of technological progress is a mediator variable for high-tech talents flow to increase labor income share at a significance level of 20%.
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