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应用生态学报 ›› 2022, Vol. 33 ›› Issue (2): 509-516.doi: 10.13287/j.1001-9332.202202.014

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浙江三大城市群绿色发展效率时空分异及影响机理

翁异静*, 汪夏彤, 陈思静   

  1. 浙江科技学院经济与管理学院, 杭州 310023
  • 收稿日期:2021-08-02 修回日期:2021-11-21 出版日期:2022-02-15 发布日期:2022-08-15
  • 通讯作者: *E-mail: wyj646@126.com
  • 作者简介:翁异静, 女, 1987年生, 副教授, 硕士生导师。 主要从事区域可持续发展研究。E-mail: wyj646@126.com
  • 基金资助:
    教育部人文社会科学研究规划基金项目(21YJA630095)和国家自然科学基金项目(71701185)资助。

Spatial-temporal differentiation and influencing mechanism of green development efficiency in three major urban agglomerations in Zhejiang Province, China.

WENG Yi-jing*, WANG Xia-tong, CHEN Si-jing   

  1. School of Economics and Management, Zhejiang University of Science and Technology, Hangzhou 310023, China
  • Received:2021-08-02 Revised:2021-11-21 Online:2022-02-15 Published:2022-08-15

摘要: 提升浙江三大城市群绿色发展效率是浙江加快建成美丽中国先行示范区的重要途径之一。以三大城市群包含的41个县(市)为依托,以2000—2019年县域面板数据为样本,将超效率SBM模型与窗口分析及测度效率相结合,运用空间计量分析方法研究效率的空间分布及区域差异,并借助面板固定效应模型探索效率的差异化影响机理。结果表明: 研究期间,三大城市群绿色发展效率整体呈波动式缓慢上升;效率值分布从北高南低的态势,逐渐转向各地区相对共同协调发展;三大城市群绿色发展效率存在显著空间集聚效应,但相近城市空间集聚处于波动状态;浙中城市群绿色发展效率最高,且群内发展最稳定,环杭州湾次之,且一直保持相对稳定,温(温州)台(台州)沿海城市群最低,但效率增幅最大。人口密度、第三产业增加值占GDP比重、人均工业增加值、地方财政支出、教育支出和人均实际利用外资的增加均能提高绿色发展效率,但工业用电量和全社会固定资产投资的增加会抑制绿色发展效率提升,其中,人均工业增加值、地方财政支出、教育支出和人均实际利用外资对各城市群的影响存在异质性。

关键词: 浙江三大城市群, 绿色发展效率, 时空格局, 区域差异

Abstract: Improving the green development efficiency of the three major urban agglomerations in Zhejiang is an important way to faster build the pilot demonstration area of beautiful China. Based on county panel data from 2000 to 2019 of 41 counties (cities) included in the three major urban agglomerations, we combined the super-efficiency SBM model with window analysis to evaluate the efficiency, and used spatial econometric analysis method to study the spatial distribution and the differences in regional difference. Furthermore, the fixed panel fixed effect model was used to explore the differential influencing mechanism. The results showed that green development efficiency of the three major urban agglomerations increased gradually with fluctuations during the study period. The distribution of efficiency values gradually shifted from a situation of ‘high in the north and low in the south' to a ‘relatively common and coordinated' development in the various regions. There was a significant spatial agglomeration effect in green development efficiency of the three major urban agglomerations, but it presented fluctuating phenomenon among cities which were at the similar level. The average green development efficiency of central Zhejiang urban agglomeration was the highest. The development within the three major urban agglomerations was relatively stable. The annulus Hangzhou Bay urban agglomeration came next, with stable development. The Wenzhou-Taizhou coastal urban agglomeration was the lowest, but the efficiency enhancement was the largest. The increases in population density, along with the proportion of added value of tertiary industry in GDP, per capita industrial added value, local fiscal expenditures, education expenditures and per capita actual use of foreign capital could improve the efficiency of green development. However, the increases in industrial electricity consumption and fixed asset investment in kennels would inhibit the improvement of green development efficiency. The impacts of per capita industrial added value, local fiscal expenditure, education expenditure and per capita actual use of foreign capital on urban agglomerations were heterogeneous among different cities.

Key words: three major urban agglomerations in Zhejiang, green development efficiency, time-space pattern, regional difference