Automation Exposure, Occupational Mobility, and Income Inequality in China

Miguel Niño Zarazúa and Wenjun Wang
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Miguel Niño Zarazúa: Department of Economics, SOAS University of London. Russell Square, London WC1H 0XG, UK; United Nations University World Institute for Development Economics Research (UNU-WIDER)
Wenjun Wang: Department of Economics, SOAS University of London. Russell Square, London WC1H 0XG, UK

No 276, Working Papers from Department of Economics, SOAS University of London, UK

Abstract: This paper examines how automation exposure is associated with income, occupational mobility, and inequality in China. Using nationally representative longitudinal data from the China Family Panel Studies for 2014--2022, we link individual occupations to a Routine Task Intensity (RTI) index and complement this task-based measure with a Bartik-style index of exposure to imported industrial robots. The results show that routine-task exposure is associated with lower individual income, with larger losses among older and more educated workers. Distributional estimates indicate that these losses are strongest among middle- and higher-income routine workers, providing evidence of income compression among exposed workers. Occupational-mobility results show that routine-intensive workers are more likely to move upward in occupational-status terms, although this does not necessarily imply economic upgrading because these workers often begin from relatively low positions in the occupational hierarchy. Intergenerational estimates suggest that RTI operates as a downward level shock to both occupational attainment and income, while family background continues to shape exposure through occupational sorting. By contrast, robot exposure is positively associated with income and occupational status in the baseline reduced-form specification, consistent with productivity and task-reinstatement effects in provinces more exposed to imported industrial robots and robot-intensive industrial upgrading. The findings show how automation interacts with institutional segmentation in emerging economies.

Keywords: Automation; Robots; Occupational Mobility; Inequality; China (search for similar items in EconPapers)
JEL-codes: D31 J24 J31 J62 O33 O53 (search for similar items in EconPapers)
Pages: 22,810 words
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