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Convergence and Transitional Dynamics of China's Industrial Output: A County-Level Study Using a New Framework of Distribution Dynamics Analysis

Author

Listed:
  • Tsun Se Cheong

    (Business School, University of Western Australia)

  • Yanrui Wu

    (Business School, University of Western Australia)

Abstract

Many scholars have argued that the huge increase in regional inequality in China can be attributed greatly to the disparity in industrialization. This paper contributes to the literature by providing empirical evidence on the transitional dynamics of industrial output by employing a new framework of distribution dynamics analysis, namely the Mobility Probability Plot (MPP), and a database compiled at the county-level. The new framework can address several inadequacies of the traditional display tools in the distribution dynamics literature, while the database is made up of counties and county-level cities in 22 provinces in China. Stochastic kernel analyses are performed for the nation, the economic zones and the provinces individually so as to provide an in-depth understanding of the evolution and convergence of industrial output. This study fills the gap in the literature and provides information on mobility of the county-level units, which can greatly aid the policy making process.

Suggested Citation

  • Tsun Se Cheong & Yanrui Wu, 2014. "Convergence and Transitional Dynamics of China's Industrial Output: A County-Level Study Using a New Framework of Distribution Dynamics Analysis," Economics Discussion / Working Papers 14-21, The University of Western Australia, Department of Economics.
    • Handle: RePEc:uwa:wpaper:14-21
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    Cited by:

    1. Kounetas, Konstantinos & Stergiou, Eirini, 2019. "Examining eco-efficiency convergence of European Industries.The existence of technological spillovers within a metafrontier framework," MPRA Paper 94286, University Library of Munich, Germany.
    2. Jing Li & Tsun Se Cheong & Wenyang Huang & Wai Yan Shum, 2022. "Examining the Regional Disparity of Agricultural Development: A Distribution Dynamics Approach," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
    3. Tan, Xiujie & Sun, Qian & Wang, Meiji & Se Cheong, Tsun & Yan Shum, Wai & Huang, Jinpeng, 2022. "Assessing the effects of emissions trading systems on energy consumption and energy mix," Applied Energy, Elsevier, vol. 310(C).
    4. Wai Choi Lee & Jianfu Shen & Tsun Se Cheong & Michal Wojewodzki, 2021. "Detecting conflicts of interest in credit rating changes: a distribution dynamics approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.
    5. Lin, Boqiang & Shi, Fengyuan, 2024. "Coal price, economic growth and electricity consumption in China under the background of energy transition," Energy Policy, Elsevier, vol. 195(C).
    6. Lizhan Lv & Feng Dai, 2025. "How Agricultural Innovation Talents Influence County-Level Industrial Structure Upgrading: A Knowledge-Empowerment Perspective," Agriculture, MDPI, vol. 15(14), pages 1-39, July.
    7. Xiaoguang Liu & Jian Yu & Tsun se Cheong & Michal Wojewodzki, 2022. "Transitional Dynamics and Spatial Convergence of House-Price-to-Income Ratio in Urban China," Economics Bulletin, AccessEcon, vol. 42(2), pages 979-989.
    8. Tsun Se Cheong & Yanrui Wu & Jianxin Wu, 2016. "Evolution of carbon dioxide emissions in Chinese cities: trends and transitional dynamics," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 21(3), pages 357-377, July.
    9. Wu, Jian-Xin & He, Ling-Yun, 2017. "How do Chinese cities grow? A distribution dynamics approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 105-118.
    10. Chen, Haitao & Zhang, Bin & Wang, Zhaohua, 2022. "Hidden inequality in household electricity consumption: Measurement and determinants based on large-scale smart meter data," China Economic Review, Elsevier, vol. 71(C).
    11. Li, Qing & Vo, Long Hai & Wu, Yanrui, 2019. "Intangible capital distribution in China," Economic Systems, Elsevier, vol. 43(2), pages 1-1.
    12. Shi, Xunpeng & Yu, Jian & Cheong, Tsun Se, 2020. "Convergence and distribution dynamics of energy consumption among China's households," Energy Policy, Elsevier, vol. 142(C).
    13. Liu, Zhenhua & Chen, Shumin & Zhong, Hongyu & Ding, Zhihua, 2024. "Coal price shocks, investor sentiment, and stock market returns," Energy Economics, Elsevier, vol. 135(C).
    14. Wu, Jianxin & Wu, Yanrui & Guo, Xiumei & Cheong, Tsun Se, 2016. "Convergence of carbon dioxide emissions in Chinese cities: A continuous dynamic distribution approach," Energy Policy, Elsevier, vol. 91(C), pages 207-219.
    15. Ikenna Stephen Ezennia & Sebnem Onal Hoskara, 2019. "Methodological weaknesses in the measurement approaches and concept of housing affordability used in housing research: A qualitative study," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-27, August.
    16. Wu, Jianxin & Wu, Yanrui & Se Cheong, Tsun & Yu, Yanni, 2018. "Distribution dynamics of energy intensity in Chinese cities," Applied Energy, Elsevier, vol. 211(C), pages 875-889.
    17. Yu, Jian & Shi, Xunpeng & Cheong, Tsun Se, 2021. "Distribution dynamics of China's household consumption upgrading," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 193-203.
    18. Vo, Duc Hong & Vo, Long Hai & Ho, Chi Minh, 2022. "Regional convergence of nonrenewable energy consumption in Vietnam," Energy Policy, Elsevier, vol. 169(C).
    19. Xunpeng Shi & Tsun Se Cheong & Jian Yu & Xiaoguang Liu, 2021. "Quality of Life and Relative Household Energy Consumption in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(5), pages 127-147, September.
    20. Wang, Delu & Wan, Kaidi & Song, Xuefeng, 2020. "Understanding coal miners’ livelihood vulnerability to declining coal demand: Negative impact and coping strategies," Energy Policy, Elsevier, vol. 138(C).
    21. Xiaoguang Liu & Jian Yu & Tsun Se Cheong & Michal Wojewodzki, 2022. "The Future Evolution of Housing Price-to-Income Ratio in 171 Chinese Cities," Annals of Economics and Finance, Society for AEF, vol. 23(1), pages 159-196, May.

    More about this item

    JEL classification:

    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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