The purpose of this paper is to examine the effect of biased technology on employment distribution and labor status in income distribution of China. It also testifies a threshold effect of the capital per labor and employment distribution on labor status from biased technology.
This paper presents a normalized supply-side system of three equations to measure the bias of technology in China. Linear and threshold regressions approaches are applied over cross-province panel data to investigate the influence which biased technology has on labor status under different capital per labor and employment distribution regimes.
This paper empirically shows that technology has been mostly capital-biased in China. The regression results indicate that capital-biased technology impairs labor income status and tend to modify employment distribution and labor income between industries. Furthermore, it reveals the threshold effect of capital per labor and employment distribution on the relationship between biased technology and labor status.
This paper extends the literature by explaining labor status from the perspective of biased technology and the effect of inter-industry employment distribution in China. It further explores the asymmetric effect of biased technology on labor productivity and income, which promotes inter-industry labor mobility and modifies employment distribution. This paper highlights the implications of this explanation for labor relations and human resource management.
The authors are grateful for research supports from the projects below: National Natural Science Foundation of China (No.71573088); Key Project of the National Social Science Foundation of China (No.17AZD009); The Research Project of the Social Science and Humanity on Young Fund of the Ministry of Education (No.17YJC790132).
Wang, L., Zhao, J., Sun, J. and Dong, Z. (2019), "The impact of biased technology on employment distribution and labor status in income distribution: Evidence from China", Chinese Management Studies, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/CMS-07-2018-0615Download as .RIS
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