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Estimate the City Size Threshold of Industrial Agglomeration Model: Evidence From Chinese Prefecture Level Cities

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  • Yunjun Xiong
  • Weiyong Zou
  • Yaopei Wang

Abstract

Based on the externality theory, this paper estimates the city size threshold of specialized agglomeration and diversified agglomeration. We find that when the urban population is below 1.25 million, specialized agglomeration is more advantageous for improving urban labor productivity. When the urban population exceeds 0.9 million, diversified agglomeration is more advantageous for improving urban labor productivity. Moreover, Specialized agglomeration of small and medium-sized cities is more likely to play the role of Marshall-Arrow-Romer externality within the spillover radius of regional central cities. One important policy suggestion is that for areas with small administrative regions and small population, it is better to increase the level of specialized agglomeration through industrial transfer, and for areas with large administrative regions and large population, it is better to increase the level of diversified agglomeration through industrial introduction, so as to further improve the urban economic efficiency.

Suggested Citation

  • Yunjun Xiong & Weiyong Zou & Yaopei Wang, 2024. "Estimate the City Size Threshold of Industrial Agglomeration Model: Evidence From Chinese Prefecture Level Cities," International Regional Science Review, , vol. 47(2), pages 182-203, March.
  • Handle: RePEc:sae:inrsre:v:47:y:2024:i:2:p:182-203
    DOI: 10.1177/01600176231160489
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    References listed on IDEAS

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    1. N. N. Mikheeva, 2017. "Diversification of regional economic structure as growth strategy: Pros and cons," Regional Research of Russia, Springer, vol. 7(4), pages 303-310, October.
    2. Enrico Moretti, 2014. "Local Economic Development, Agglomeration Economies, and the Big Push: 100 Years of Evidence from the Tennessee Valley Authority," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(1), pages 275-331.
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