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Spatial Human Development Index in China: Measurement and Interpretation Based on Bayesian Estimation

Author

Listed:
  • Xiang Luo

    (College of Public Administration, Central China Normal University, Wuhan 430079, China)

  • Jingjing Qin

    (College of Public Administration, Central China Normal University, Wuhan 430079, China)

  • Qing Wan

    (School of Management, Wuhan Institute of Technology, Wuhan 430025, China)

  • Gui Jin

    (School of Economics and Management, China University of Geosciences, Wuhan 430078, China)

Abstract

The development of urban agglomerations dominated by the service industry is an important driving force for further sustainable economic growth of China. Spatial analysis marked by population density and regional integration is an essential perspective for studying the human development index (HDI) in China. Based on Bayesian estimation, this paper examines the influence of a spatial factor on HDI by using a spatial hierarchical factor model within the framework of Sen Capability Approach theory, overcoming the neglect of spatial factors and their equal weight in traditional measurement of HDI. On this basis, the HDI including the spatial factor was measured based on the panel data from 2000 to 2018. The results reveal that (1) provinces with high population densities and regional integration have higher rankings and low uncertainties of HDI, which can be attributed to the improvement of education weights; (2) HDI has a certain spatial spillover effect, and the spatial association increases year by year; (3) robust test by using nighttime lighting as an alternative indicator of GDP supports that the spatial correlation is positively related to HDI ranking. The policy recommendations of this paper are to remove the obstacles for cross-regional population mobility and adjust the direction and structure of public expenditure.

Suggested Citation

  • Xiang Luo & Jingjing Qin & Qing Wan & Gui Jin, 2023. "Spatial Human Development Index in China: Measurement and Interpretation Based on Bayesian Estimation," IJERPH, MDPI, vol. 20(1), pages 1-18, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:1:p:818-:d:1022406
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    1. Markus Eberhardt & Christian Helmers & Hubert Strauss, 2013. "Do Spillovers Matter When Estimating Private Returns to R&D?," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 436-448, May.
    2. Jaya Krishnakumar, 2018. "Trade-Offs in a Multidimensional Human Development Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 138(3), pages 991-1022, August.
    3. Niels Lind, 2019. "A Development of the Human Development Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(3), pages 409-423, December.
    4. Hendrik Wolff & Howard Chong & Maximilian Auffhammer, 2011. "Classification, Detection and Consequences of Data Error: Evidence from the Human Development Index," Economic Journal, Royal Economic Society, vol. 121(553), pages 843-870, June.
    5. Carmen Herrero & Ricardo Martínez & Antonio Villar, 2019. "Population Structure and the Human Development Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(2), pages 731-763, January.
    6. Wolfgang Keller, 2002. "Geographic Localization of International Technology Diffusion," American Economic Review, American Economic Association, vol. 92(1), pages 120-142, March.
    7. Conley, Timothy G & Ligon, Ethan, 2002. "Economic Distance and Cross-Country Spillovers," Journal of Economic Growth, Springer, vol. 7(2), pages 157-187, June.
    8. Kalimeris, Panos & Bithas, Kostas & Richardson, Clive & Nijkamp, Peter, 2020. "Hidden linkages between resources and economy: A “Beyond-GDP” approach using alternative welfare indicators," Ecological Economics, Elsevier, vol. 169(C).
    9. Wolfgang Keller, 2004. "International Technology Diffusion," Journal of Economic Literature, American Economic Association, vol. 42(3), pages 752-782, September.
    10. Cem Ertur & Wilfried Koch, 2011. "A contribution to the theory and empirics of Schumpeterian growth with worldwide interactions," Journal of Economic Growth, Springer, vol. 16(3), pages 215-255, September.
    11. Shiyin Chen & Qingxu Huang & Ziwen Liu & Shiting Meng & Dan Yin & Lei Zhu & Chunyang He, 2019. "Assessing the Regional Sustainability of the Beijing-Tianjin-Hebei Urban Agglomeration from 2000 to 2015 Using the Human Sustainable Development Index," Sustainability, MDPI, vol. 11(11), pages 1-17, June.
    12. Qiu, Qihua & Sung, Jaesang & Davis, Will & Tchernis, Rusty, 2018. "Using spatial factor analysis to measure human development," Journal of Development Economics, Elsevier, vol. 132(C), pages 130-149.
    13. Ratigan, Kerry, 2017. "Disaggregating the Developing Welfare State: Provincial Social Policy Regimes in China," World Development, Elsevier, vol. 98(C), pages 467-484.
    14. Amelia U. Santos‐Paulino & Alisa DiCaprio & Maria V. Sokolova, 2019. "The development trinity: How regional integration impacts growth, inequality and poverty," The World Economy, Wiley Blackwell, vol. 42(7), pages 1961-1993, July.
    15. Dejian Lai, 2003. "Principal Component Analysis on Human Development Indicators of China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 61(3), pages 319-330, March.
    16. Zhidan Shi & Xiao Tang, 2020. "Exploring the New Era: An Empirical Analysis of China’s Regional HDI Development," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(9), pages 1957-1970, July.
    17. Man Liang & Shuwen Niu & Zhen Li & Wenli Qiang, 2019. "International Comparison of Human Development Index Corrected by Greenness and Fairness Indicators and Policy Implications for China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(1), pages 1-24, February.
    18. Hogan J.W. & Tchernis R., 2004. "Bayesian Factor Analysis for Spatially Correlated Data, With Application to Summarizing Area-Level Material Deprivation From Census Data," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 314-324, January.
    19. Morse, Stephen, 2003. "For better or for worse, till the human development index do us part?," Ecological Economics, Elsevier, vol. 45(2), pages 281-296, June.
    20. Høyland, Bjørn & Moene, Karl & Willumsen, Fredrik, 2012. "The tyranny of international index rankings," Journal of Development Economics, Elsevier, vol. 97(1), pages 1-14.
    21. Chengjun Liu & Fuqiang Nie & Dong Ren, 2021. "Temporal and Spatial Evolution of China's Human Development Index and Its Determinants: An Extended Study Based on Five New Development Concepts," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(1), pages 247-282, August.
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