Labor Inputs and Productivity in Chinese Industries: 2000–2018

Abstract: Under the framework of growth accounting, this paper introduces four heterogeneity characteristics of labor, namely, educational level, age, gender and industry, constructs a cross classification matrix of employment, labor compensation and working hours, and calculates the labor input (volume) of the whole country and of 19 industries during 2000–2018. Then it decomposes the volume into quantity and quality parts to analyze the total amount of labor input and the performance of industry labor input. The results are as follows. First, during the research period, the annual growth rate of labor input was 2.5%, and 78.8% of that came from the growth of labor input quality. The growth of labor input was mainly resulted from the improvement of educational level and the optimization of industrial structure. Second, in 2018, the proportions of labor input of the primary, secondary and tertiary sectors were 13.76%, 31.06% and 55.18% respectively, and the transfer speed of labor input to the secondary and tertiary sectors was higher than that of the quantity structure; the labor input volume in the new economy and related industries in the tertiary sector has been greatly increased. Third, the index method-based labor productivity (ILP) of some producer service and consumer service industries was relatively low, and the growth of total industry output mainly attributed to the increase of labor input and the expansion of industrial scale. The improvement of labor input quality has become the key to the growth of labor input in China, and the improvement of educational level is the core power to improve the labor input quality.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Labor Inputs and Productivity in Chinese Industries: 2000–2018 ; volume:11 ; number:1 ; year:2022 ; pages:24-47 ; extent:24 ; China finance and economic review ; 11, Heft 1 (2022), 24-47 (gesamt 24)

Contributors, Places and Time

• Creator: Chen, Menggen ; Hou, Yuanyuan

Further information

• DOI: 10.1515/cfer-2022-0002
• URN: urn:nbn:de:101:1-2022083014041451373773
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:37 AM CEST