Examining the influence mechanism of artificial intelligence development on labor income share through numerical simulations

Cheng Qian, Chun Zhu, Duen-Huang Huang and Shangfeng Zhang

Technological Forecasting and Social Change, 2023, vol. 188, issue C

Abstract: Maintaining the stability of labor income share is a key foundation for optimizing the structure of income distribution. Based on Chinese macroeconomic data, this study constructs a dynamic general equilibrium model with production tasks and applies numerical simulation to investigate the impact of artificial intelligence (AI) development on labor income share. The results demonstrate that the influence direction of AI development on labor income share depends on the relative speed of machine replacement and new tasks. Mechanism analysis reveals that machine replacement makes the wage growth rate smaller than the labor productivity growth rate, causing a decline in labor income share; however, new tasks can offset this negative impact, and the faster the growth is, the more obvious this offsetting effect is. Further numerical simulation confirms the above. Our study extends the research on labor income share, providing a new approach for understanding the changing mechanism of labor income share in China.

Keywords: Artificial intelligence development; Task model; Labor income share; Dynamic general equilibrium model (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:188:y:2023:i:c:s0040162522008368

DOI: 10.1016/j.techfore.2022.122315

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