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Convergence across Chinese provinces: An analysis using Markov transition matrix

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  • Sakamoto, Hiroshi
  • Islam, Nazrul

Abstract

This paper adopts the distribution approach to study convergence across Chinese provinces. In particular, it uses the Markov transition matrix methodology to capture the dynamics embodied in the data and to produce corresponding ergodic distributions. The results indicate that distribution of per capita income across Chinese provinces has become bi-modal over the period of 1952-2003. However, a closer examination shows that the dynamics contained in the pre- and post-reform periods are different, producing very different types of ergodic distribution. While the ergodic distribution based on the pre-reform dynamics proves to be positively skewed, the one based on the post-reform period's dynamics proves to be negatively skewed. On balance, whether per capita income level of the Chinese provinces will converge soon still remains an open question.

Suggested Citation

  • Sakamoto, Hiroshi & Islam, Nazrul, 2008. "Convergence across Chinese provinces: An analysis using Markov transition matrix," China Economic Review, Elsevier, vol. 19(1), pages 66-79, March.
  • Handle: RePEc:eee:chieco:v:19:y:2008:i:1:p:66-79
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    References listed on IDEAS

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    Cited by:

    1. Jian-Xin Wu & Ling-Yun He, 2017. "The Distribution Dynamics of Carbon Dioxide Emissions Intensity across Chinese Provinces: A Weighted Approach," Sustainability, MDPI, Open Access Journal, vol. 9(1), pages 1-19, January.
    2. Herrerias, M.J. & Ordoñez, J., 2012. "New evidence on the role of regional clusters and convergence in China (1952–2008)," China Economic Review, Elsevier, pages 1120-1133.
    3. Herrerias, M.J. & Ordoñez, J., 2012. "New evidence on the role of regional clusters and convergence in China (1952–2008)," China Economic Review, Elsevier, pages 1120-1133.
    4. Jørn Rattsø & Hildegunn Stokke, 2014. "Regional Convergence of Income and Education: Investigation of Distribution Dynamics," Urban Studies, Urban Studies Journal Limited, pages 1672-1685.
    5. Nagayasu, Jun, 2009. "Regional Inflation in China," MPRA Paper 24722, University Library of Munich, Germany.
    6. Peng Bin, 2016. "Dynamic Development of Regional Disparity in Mainland China: An Experimental Study Based on a Multidimensional Index," Sustainability, MDPI, Open Access Journal, vol. 8(12), pages 1-28, December.
    7. Tsun Se Cheong & Yanrui Wu, 2012. "Regional Disparity, Transitional Dynamics and Convergence in China," Economics Discussion / Working Papers 12-23, The University of Western Australia, Department of Economics.
    8. Chen, Yu-Fu & Funke, Michael, 2009. "China's new Labour Contract Law: No harm to employment?," China Economic Review, Elsevier, pages 558-572.
    9. Hiroshi Sakamoto, 2013. "Prediction Of The Prefectural Economy In Japan Using A Stochastic Model," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 13-24, June.
    10. Hiroshi Sakamoto, 2012. "Future Prediction of the Prefectural Economy in Japan: Using a Stochastic Model," ERSA conference papers ersa12p139, European Regional Science Association.
    11. Cheong, Tsun Se & Wu, Yanrui, 2013. "Regional disparity, transitional dynamics and convergence in China," Journal of Asian Economics, Elsevier, pages 1-14.
    12. M. Herrerías, 2012. "Weighted convergence and regional growth in China: an alternative approach (1952–2008)," The Annals of Regional Science, Springer;Western Regional Science Association, pages 685-718.
    13. Sakamoto, Hiroshi, 2013. "Prediction of the Prefectural Economy in Japan Using a Stochastic Model," AGI Working Paper Series 2013-02, Asian Growth Research Institute.
    14. Bin, Peng, 2015. "Regional Disparity and Dynamic Development of China: a Multidimensional Index," MPRA Paper 61849, University Library of Munich, Germany.
    15. Funke, Michael & Yu, Hao, 2009. "Economic growth across Chinese provinces : insearch of innovation-driven gains," BOFIT Discussion Papers 10/2009, Bank of Finland, Institute for Economies in Transition.

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