Dynamic Evolution and Configurational Heterogeneity of the Skill Wage Gap in China under Technological Transformation
Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v7i2.5166
Abstract
Against the backdrop of the accelerated penetration of artificial intelligence and robotics technologies, the impact of technological shocks on income distribution has become a core issue in development economics and labor economics. Based on four waves of data from the China Family Panel Studies (CFPS) from 2022 to 2025, this study constructs an individual-level indicator of the skill wage gap and adopts an occupational task automation exposure index as a proxy variable for technological shocks. It systematically examines the heterogeneous effects of automation technology diffusion on wage structures and their micro-level transmission mechanisms. The results show that technological shocks significantly widen the skill wage gap, and wage growth for occupational groups with high exposure to automation lags markedly behind that of low-exposure groups. The task substitution mechanism is the core channel underlying these effects, as workers with a higher share of standardized routine tasks face more pronounced downward wage pressure. Vocational education background and participation in on-the-job training can mitigate the negative effects of technological shocks, and improvements in skill adaptability reduce the risk of automation substitution.
Keywords
technological transformation; skill wage gap; task substitution mechanism; vocational education; CFPS data
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[2]Madan S, Yadav M. Decomposing skill based wage inequality in India: an application of Theil index[J]. The Indian Journal of Labour Economics, 2022, 65(4): 967-979.
[3]Das S, Chatterjee A. Impacts of ICT and digital finance on poverty and income inequality: A sub-national study from India[J]. Information Technology for Development, 2023, 29(2-3): 378-405.
[4]Cascio E U, Narayan A. Who needs a fracking education? The educational response to low-skill-biased technological change[J]. ILR Review, 2022, 75(1): 56-89.
[5]Challoumis C. Role of Public Policy in Enhancing Technological Advancement[J]. SSRN Electronic Journal, 2024.
[6]Kaputa V, Loučanová E, Tejerina-Gaite F A. Digital transformation in higher education institutions as a driver of social oriented innovations[M]//Social innovation in higher education: Landscape, practices, and opportunities. Cham: Springer International Publishing, 2022: 61-85.
[7]Bai Z, Wang X. Technological progress bias, wage income gap, and income equity[J]. Finance Research Letters, 2025, 81: 107471.
[8]Hu J, Tan C, Jiao Y, et al. The associational relationships between multidimensional digital literacy and wage income: evidence from urban–rural heterogeneity[J]. Scientific Reports, 2025, 15(1): 42830.
[9]Bozkus K. Organizational culture change and technology: Navigating the digital transformation[M]//Organizational culture-Cultural change and technology. IntechOpen, 2023.
[10]Shao Y, Chen Z. Can government subsidies promote the green technology innovation transformation? Evidence from Chinese listed companies[J]. Economic Analysis and Policy, 2022, 74: 716-727.
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