Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/260942 
Year of Publication: 
2020
Citation: 
[Journal:] Journal of Innovation & Knowledge (JIK) [ISSN:] 2444-569X [Volume:] 5 [Issue:] 4 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2020 [Pages:] 266-278
Publisher: 
Elsevier, Amsterdam
Abstract: 
We observe a growing empirical literature on the divergence between labor productivity and compensation on a global scale. Empirical evidence of the decoupling for the OECD and transitional economies support the hypothesis of divergence between productivity and pay after 1980s. In this paper, we offer evidence of the decoupling in China from 1952 to 2018. We use state-of-the art, robust econometric techniques based on long memory to identify the main determinants of persistence and divergence. From 1952 to 2018, we measure the decoupling average annual growth rate of 0.93% (using per hour worked data). Productivity-compensation per worker divergence follows the average annual growth rate of 1.52%. We provide evidence that the decoupling in China is caused by innovation-based shifts, globalization, a shift to knowledge growth management, "supercycles and boom-bust", "superstars", declining labor share and increasing wage inequality. Knowledge and innovation based technological advancement accounts for the labor productivity and compensation divergence in China. The results show a diverging trend between labor productivity and labor compensation caused by innovation and knowledge growth model. Study results offer robust proofs for the decoupling with a long memory pattern in China with innovation and knowledge leading to an increasing inequality in the long run. Policy makers and practitioners should address the issue promptly if do not want to face various growth headwinds in the future.
Subjects: 
ARFIMA
Bloomfield disturbances
China
Innovation
Knowledge
Labor productivity
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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