长江流域资源与环境 >> 2024, Vol. 33 >> Issue (1): 27-39.doi: 10.11870/cjlyzyyhj202401003

• 区域可持续发展 • 上一篇    下一篇

贵州县域综合经济密度时空特征及影响因素研究

应奎,黄小丽,丁金宏*   

  1. (华东师范大学人口研究所,上海 200241)
  • 出版日期:2024-01-20 发布日期:2024-02-01

Economic Density in Guizhou Counties: Spatio-temporal Characteristics and Influencing Factors

YING Kui, HUANG Xiao-li, DING Jin-hong   

  1. (Institute of Population Research, East China Normal University,Shanghai 200241, China)
  • Online:2024-01-20 Published:2024-02-01

摘要:  经济均衡发展是区域经济高质量发展的重要内涵,这也是贵州等相对落后省份所面临的经济新常态发展要求。以2000、2010和2020年为基础,构建县域经济密度评价指标体系,运用熵权TOPSIS法、核密度估计法、空间自相关方法和空间面板模型,测算经济密度综合得分,探究其时空特征及影响因素。结果表明:(1)2000~2020年,贵州县域经济密度总体上随时间递增,核密度曲线以多峰为主,主峰随时间不断增高且宽度呈小幅收缩状态。(2)空间上,经济密度高值中心不断缩减,2000~2010年以正增长县域为主,2010~2020年以负增长县域为主;全局空间自相关中,经济密度空间聚集程度先增后减,局部空间自相关则以高-高和低-低方式聚集为主。(3)经济密度在空间上存在显著的内生交互作用,邻近县域的经济密度每提升1%,将促进本地经济密度提升0.2%。(4)影响因素方面,人才禀赋与医疗床位对经济密度呈正向作用,其他要素呈负向作用;直接效应的影响强度排序为:人才禀赋>降水#>人口老龄化#>民族结构#>植被覆盖度#>医疗床位(#表示负向影响),空间溢出效应贡献大小排序为:人才禀赋>人口老龄化#>降水#>民族结构#>医疗床位。因此,贵州应注重经济发展的区域均衡性,在继续吸引人才和改善社会福利条件下,补齐民族县域经济发展短板。

Abstract: Balanced economic development is an important connotation for measuring the high-quality development of regional economies, which is also a requirement for the development of the new normal in low economic development provinces such as Guizhou. This paper constructed the county economic density evaluation index system for 2000, 2010 and 2020. The entropy weight TOPSIS method, kernel density estimation method, spatial autocorrelation method and spatial panel model were applied to measure the comprehensive score of economic density. The spatio-temporal characteristics and influencing factors were also explored. The results showed that: (1) the economic density of Guizhou's counties generally increased over time. The nuclear density curve was dominated by multiple peaks, with the main peak increasing over time and a small contraction in width from 2000-2020. (2) Spatially, the centers of high economic density were shrinking, with positive growth counties dominating in 2000-2010 and negative growth counties dominating in 2010-2020; In the global spatial autocorrelation, the degree of spatial agglomeration of economic density increased and then decreased. The local spatial autocorrelation was dominated by the agglomeration of the high-high and the low-low modes. (3) There was a significant spatially endogenous interaction of economic density, where each 1% increase in economic density in the neighboring counties would promote a 0.2% increase in local economic density. (4) Regarding the affecting factors, talent endowment and medical beds had a positive effect on economic density, and other factors had a negative effect. The strength of the direct effect is ranked as follows: talent endowment > precipitation #> population aging #> ethnic structure #> vegetation cover #> medical beds (# indicates a negative effect). The size of spatial spillover effect contribution was ranked as follows: talent endowment > population aging #> precipitation #> ethnic structure #> medical beds. Therefore, Guizhou should focus on the regional balance of economic development, and make up for the shortcomings of economic development in ethnic counties while continuing to attract talents and improve social welfare conditions.

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