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Impact of industrial relatedness on manufacturing structural change: a panel data analysis for Chinese provinces

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  • Yanlin Sun
  • Yuanrong Lin

Abstract

A large body of literature has explored the determinants of manufacturing structural change, but little has highlighted industrial relatedness. This study probes the impact of technological and vertical relatedness on manufacturing structural rationalisation and advancement by constructing a panel data model with province and year fixed effects using data of 30 Chinese provinces from 2000 to 2019. The empirical results show that manufacturing structural change differs based on industrial relatedness. Specifically, at the national level, technological relatedness can promote both structural rationalisation and advancement within manufacturing. Vertical relatedness holds a negative effect on structural rationalisation and no significant effect on structural advancement. Besides, the effects of industrial relatedness exhibit regional heterogeneity. In coastal China, technological relatedness can still promote structural rationalisation and advancement. Vertical relatedness has no significant effect on structural rationalisation and a negative effect on structural advancement. In inland China, governmental supports help break the dependency of regional manufacturing structural change on industrial relatedness, and the establishment of development zones restrains structural rationalisation within manufacturing. This study offers insights for policymakers to adopt different approaches to support local manufacturing development, depending on the characteristics of regional manufacturing structural evolution.

Suggested Citation

  • Yanlin Sun & Yuanrong Lin, 2023. "Impact of industrial relatedness on manufacturing structural change: a panel data analysis for Chinese provinces," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 36(1), pages 2508-2526, March.
    • Handle: RePEc:taf:reroxx:v:36:y:2023:i:1:p:2508-2526
    DOI: 10.1080/1331677X.2022.2080732
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