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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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