世界地理研究 ›› 2025, Vol. 34 ›› Issue (7): 126-138.DOI: 10.3969/j.issn.1004-9479.2025.07.20230723
• 城市与创新 • 上一篇
收稿日期:
2023-10-25
修回日期:
2024-03-30
出版日期:
2025-07-15
发布日期:
2025-07-31
作者简介:
唐晓超(1995—),男,博士研究生,研究方向为区域经济与人口收缩,E-mail:1017918176@qq.com。
基金资助:
Received:
2023-10-25
Revised:
2024-03-30
Online:
2025-07-15
Published:
2025-07-31
摘要:
由中心城市虹吸效应所造成的集聚阴影现象是区域发展不平衡的重要方面与体现。城市群作为我国人口与经济要素集聚区域,一体化建设必然会对集聚阴影以及区域的协调发展产生重大影响。选取2010—2020年长江经济带三大城市群所处7省2市的656个区县级单位作为研究对象,基于地理断点回归方法,探究城市群一体化政策是否有利于缓解城市群内部集聚阴影的形成。结果发现:①2010—2020年,三大城市群区域人均GDP整体有所提高,内部经济发展差距呈缩小趋势,城市群一体化政策对缓解内部集聚阴影现象具有显著正向影响。②分区域来看,长三角城市群政策效果最为显著,长江中游和成渝城市群(经济圈)政策效果不显著。③机制研究发现,城市群内部可以通过中心地区工业产业向外围地区转移扩散有效缓解集聚阴影。尽管高铁的开通存在加剧地区集聚阴影的情况,但相较于城市群外部地区,在城市群内部对缓解集聚阴影仍发挥着积极作用。最后,根据研究结论提出要拓展政策效应的作用范围与深度、强化城市群产业协调及产业集群建设以及完善高铁网络实现区域要素自由流动。
唐晓超. 城市群一体化政策能否缓解集聚阴影?[J]. 世界地理研究, 2025, 34(7): 126-138.
Xiaochao TANG. Can urban agglomeration integration policies alleviate agglomeration shadow?[J]. World Regional Studies, 2025, 34(7): 126-138.
变量名 | 变量含义 | 样本数 | 平均值 | 标准差 | 最小值 | 最大值 |
---|---|---|---|---|---|---|
5 181 | 10.372 3 | 0.593 1 | 8.644 9 | 12.271 3 | ||
人均GDP占中心城市比重 | 5 181 | 0.304 6 | 0.216 0 | 0.046 0 | 1.892 5 | |
距城市群边界距离 | 5 181 | 44.638 6 | 26.561 1 | 3.419 9 | 98.974 2 | |
是否处于城市群内部 | 5 181 | 0.660 3 | 0.473 7 | 0 | 1 | |
第三产业占GDP比重 | 5 181 | 0.384 7 | 0.113 9 | 0.107 9 | 0.984 5 | |
人均财政支出 | 5 181 | 0.800 7 | 0.515 9 | 0.058 6 | 6.151 7 | |
5 180 | 9.442 5 | 0.676 4 | 7.189 2 | 12.285 9 | ||
在校小学生人数占常住人口比重 | 5 180 | 0.073 1 | 0.029 7 | 0.007 9 | 0.457 4 | |
每万人医院床位数 | 5 180 | 49.344 8 | 30.893 1 | 5.419 9 | 702.329 0 | |
夜间灯光指数 | 5 181 | 7.124 5 | 11.442 5 | 0.036 8 | 62.810 5 | |
工业集中率变化 | 6 560 | 0.002 5 | 0.085 9 | —1.190 0 | 1.505 8 |
表 1 主要变量的描述性统计
Tab.1 Descriptive statistics of main variables
变量名 | 变量含义 | 样本数 | 平均值 | 标准差 | 最小值 | 最大值 |
---|---|---|---|---|---|---|
5 181 | 10.372 3 | 0.593 1 | 8.644 9 | 12.271 3 | ||
人均GDP占中心城市比重 | 5 181 | 0.304 6 | 0.216 0 | 0.046 0 | 1.892 5 | |
距城市群边界距离 | 5 181 | 44.638 6 | 26.561 1 | 3.419 9 | 98.974 2 | |
是否处于城市群内部 | 5 181 | 0.660 3 | 0.473 7 | 0 | 1 | |
第三产业占GDP比重 | 5 181 | 0.384 7 | 0.113 9 | 0.107 9 | 0.984 5 | |
人均财政支出 | 5 181 | 0.800 7 | 0.515 9 | 0.058 6 | 6.151 7 | |
5 180 | 9.442 5 | 0.676 4 | 7.189 2 | 12.285 9 | ||
在校小学生人数占常住人口比重 | 5 180 | 0.073 1 | 0.029 7 | 0.007 9 | 0.457 4 | |
每万人医院床位数 | 5 180 | 49.344 8 | 30.893 1 | 5.419 9 | 702.329 0 | |
夜间灯光指数 | 5 181 | 7.124 5 | 11.442 5 | 0.036 8 | 62.810 5 | |
工业集中率变化 | 6 560 | 0.002 5 | 0.085 9 | —1.190 0 | 1.505 8 |
图 1 2010—2020年长江经济带三大城市群人均GDP变化格局
Fig.1 Change pattern of per capita GDP in the three major urban agglomerations of the Yangtze River Economic Belt,2010-2020
年份 | 长三角城市群内部差异 | 长江中游城市群内部差异 | 成渝城市群内部差异 | 区域内部差异 | 区域之间差异 | 内部差异贡献率 | 区域差异贡献率 | 三大城市群总体差异 |
---|---|---|---|---|---|---|---|---|
2010 | 0.124 3 | 0.192 8 | 0.131 2 | 0.141 0 | 0.075 3 | 65.19% | 34.81% | 0.216 4 |
2011 | 0.116 4 | 0.196 2 | 0.127 1 | 0.137 4 | 0.059 0 | 69.96% | 30.04% | 0.196 4 |
2012 | 0.111 3 | 0.185 5 | 0.124 2 | 0.131 7 | 0.054 5 | 70.72% | 29.28% | 0.186 2 |
2013 | 0.101 1 | 0.179 6 | 0.121 3 | 0.123 8 | 0.054 7 | 69.37% | 30.63% | 0.178 5 |
2014 | 0.097 7 | 0.177 8 | 0.117 0 | 0.121 0 | 0.051 4 | 70.21% | 29.79% | 0.172 4 |
2015 | 0.099 0 | 0.175 2 | 0.114 1 | 0.120 7 | 0.051 3 | 70.16% | 29.84% | 0.172 0 |
2016 | 0.099 3 | 0.167 7 | 0.109 4 | 0.118 1 | 0.052 3 | 69.33% | 30.67% | 0.170 4 |
2017 | 0.099 0 | 0.159 2 | 0.107 0 | 0.115 2 | 0.054 2 | 68.00% | 32.00% | 0.169 5 |
2018 | 0.096 4 | 0.164 6 | 0.108 1 | 0.115 3 | 0.051 5 | 69.13% | 30.87% | 0.166 8 |
2019 | 0.088 6 | 0.154 6 | 0.118 8 | 0.110 2 | 0.044 7 | 71.13% | 28.87% | 0.154 9 |
2020 | 0.072 4 | 0.140 3 | 0.089 5 | 0.091 6 | 0.038 6 | 70.38% | 29.62% | 0.130 2 |
表 2 三大城市群泰尔指数测算
Tab.2 Theil Index measurement of the three major urban agglomerations
年份 | 长三角城市群内部差异 | 长江中游城市群内部差异 | 成渝城市群内部差异 | 区域内部差异 | 区域之间差异 | 内部差异贡献率 | 区域差异贡献率 | 三大城市群总体差异 |
---|---|---|---|---|---|---|---|---|
2010 | 0.124 3 | 0.192 8 | 0.131 2 | 0.141 0 | 0.075 3 | 65.19% | 34.81% | 0.216 4 |
2011 | 0.116 4 | 0.196 2 | 0.127 1 | 0.137 4 | 0.059 0 | 69.96% | 30.04% | 0.196 4 |
2012 | 0.111 3 | 0.185 5 | 0.124 2 | 0.131 7 | 0.054 5 | 70.72% | 29.28% | 0.186 2 |
2013 | 0.101 1 | 0.179 6 | 0.121 3 | 0.123 8 | 0.054 7 | 69.37% | 30.63% | 0.178 5 |
2014 | 0.097 7 | 0.177 8 | 0.117 0 | 0.121 0 | 0.051 4 | 70.21% | 29.79% | 0.172 4 |
2015 | 0.099 0 | 0.175 2 | 0.114 1 | 0.120 7 | 0.051 3 | 70.16% | 29.84% | 0.172 0 |
2016 | 0.099 3 | 0.167 7 | 0.109 4 | 0.118 1 | 0.052 3 | 69.33% | 30.67% | 0.170 4 |
2017 | 0.099 0 | 0.159 2 | 0.107 0 | 0.115 2 | 0.054 2 | 68.00% | 32.00% | 0.169 5 |
2018 | 0.096 4 | 0.164 6 | 0.108 1 | 0.115 3 | 0.051 5 | 69.13% | 30.87% | 0.166 8 |
2019 | 0.088 6 | 0.154 6 | 0.118 8 | 0.110 2 | 0.044 7 | 71.13% | 28.87% | 0.154 9 |
2020 | 0.072 4 | 0.140 3 | 0.089 5 | 0.091 6 | 0.038 6 | 70.38% | 29.62% | 0.130 2 |
图 2 城市群两侧邻近区县人均GDP以及与人均GDP占中心城市比重的散点图
Fig. 2 Scatter diagram of per capita GDP of neighboring districts and districts on both sides of urban agglomerations and their proportion to the central city
参数 | (1) | (2) | (3) | (4) | (5) | (6) |
---|---|---|---|---|---|---|
2.220 5*** | 3.513 8*** | 0.287 7*** | ||||
(0.167 5) | (0.095 9) | (0.051 3) | ||||
0.027 4*** | 0.546 9*** | 0.460 7*** | ||||
(0.002 3) | (0.023 6) | (0.040 9) | ||||
核密度分布函数 | uniform | uniform | uniform | uniform | triangular | triangular |
控制变量 | NO | NO | YES | YES | YES | YES |
个体固定效应 | NO | NO | YES | YES | YES | YES |
时间固定效应 | NO | NO | YES | YES | YES | YES |
n | 518 1 | 518 1 | 518 1 | 518 1 | 518 1 | 518 1 |
表 3 地理断点基准回归
Tab.3 Baseline regression of geographic discontinuity
参数 | (1) | (2) | (3) | (4) | (5) | (6) |
---|---|---|---|---|---|---|
2.220 5*** | 3.513 8*** | 0.287 7*** | ||||
(0.167 5) | (0.095 9) | (0.051 3) | ||||
0.027 4*** | 0.546 9*** | 0.460 7*** | ||||
(0.002 3) | (0.023 6) | (0.040 9) | ||||
核密度分布函数 | uniform | uniform | uniform | uniform | triangular | triangular |
控制变量 | NO | NO | YES | YES | YES | YES |
个体固定效应 | NO | NO | YES | YES | YES | YES |
时间固定效应 | NO | NO | YES | YES | YES | YES |
n | 518 1 | 518 1 | 518 1 | 518 1 | 518 1 | 518 1 |
变量 | (1) | (2) | (3) | (4) | (5) |
---|---|---|---|---|---|
控制变量 | —0.011 3 | 0.524 1 | —0.002 2 | 0.037 6 | —0.762 4 |
(0.028 9) | (0.379 3) | (0.009 6) | (0.167 1) | (8.365 1) | |
n | 5 180 | 5 180 | 5 180 | 5 180 | 5 180 |
表 4 控制变量的连续性检验
Tab.4 Continuity test of control variables
变量 | (1) | (2) | (3) | (4) | (5) |
---|---|---|---|---|---|
控制变量 | —0.011 3 | 0.524 1 | —0.002 2 | 0.037 6 | —0.762 4 |
(0.028 9) | (0.379 3) | (0.009 6) | (0.167 1) | (8.365 1) | |
n | 5 180 | 5 180 | 5 180 | 5 180 | 5 180 |
变量 | (1) | (2) | (3) | (4) | (5) |
---|---|---|---|---|---|
52.505 0*** | |||||
(18.097 0) | |||||
3.418 5*** | 0.029 7 | —0.020 9 | 0.05030*** | ||
(0 .372 9) | (0.024 8) | (0.016 4) | (0.009 0) | ||
控制变量 | YES | YES | YES | YES | YES |
年份固定效应 | YES | YES | YES | YES | YES |
个体固定效应 | YES | YES | YES | YES | YES |
n | 5 180 | 4 234 | 5 180 | 5 180 | 5 180 |
表 5 稳健性检验 (Robustness test)
Tab.5
变量 | (1) | (2) | (3) | (4) | (5) |
---|---|---|---|---|---|
52.505 0*** | |||||
(18.097 0) | |||||
3.418 5*** | 0.029 7 | —0.020 9 | 0.05030*** | ||
(0 .372 9) | (0.024 8) | (0.016 4) | (0.009 0) | ||
控制变量 | YES | YES | YES | YES | YES |
年份固定效应 | YES | YES | YES | YES | YES |
个体固定效应 | YES | YES | YES | YES | YES |
n | 5 180 | 4 234 | 5 180 | 5 180 | 5 180 |
变量 | 长三角 | 长江中游 | 成渝双城 | |||
---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | |
0.092 7*** | 0.088 9*** | —1.797 0*** | ||||
(0.012 7) | (0.012 3) | (0.538 1) | ||||
0.015 0*** | —0.002 9 | —0.150 7*** | ||||
(0.002 3) | (0.004 9) | (0.009 9) | ||||
控制变量 | YES | YES | YES | YES | YES | YES |
年份固定效应 | YES | YES | YES | YES | YES | YES |
个体固定效应 | YES | YES | YES | YES | YES | YES |
n | 1 399 | 1 399 | 1 374 | 1 374 | 1 155 | 1 155 |
表 6 异质性分析
Tab.6 Heterogeneity analysis
变量 | 长三角 | 长江中游 | 成渝双城 | |||
---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | |
0.092 7*** | 0.088 9*** | —1.797 0*** | ||||
(0.012 7) | (0.012 3) | (0.538 1) | ||||
0.015 0*** | —0.002 9 | —0.150 7*** | ||||
(0.002 3) | (0.004 9) | (0.009 9) | ||||
控制变量 | YES | YES | YES | YES | YES | YES |
年份固定效应 | YES | YES | YES | YES | YES | YES |
个体固定效应 | YES | YES | YES | YES | YES | YES |
n | 1 399 | 1 399 | 1 374 | 1 374 | 1 155 | 1 155 |
变量 | |||||||
---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | |
—0.099 3** | |||||||
(0.039 2) | |||||||
1.613 7*** | 0.279 9*** | ||||||
(0.040 2) | (0.020 7) | ||||||
0.145 8*** | 0.093 9*** | 0.283 7*** | 0.118 6*** | ||||
(0.023 8) | (0.018 5) | (0.051 7) | (0.026 6) | ||||
0.125 7*** | 0.089 7*** | ||||||
(0.025 3) | (0.020 4) | ||||||
—0.066 9*** | —0.012 8** | ||||||
(0.016 3) | (0.005 3) | ||||||
0.083 9*** | 0.0169 0** | ||||||
(0.020 6) | (0.008 4) | ||||||
常数项 | 0.354 9** | 10.012 2*** | 0.287 7*** | 9.528 7*** | 0.112 1*** | 9.050 9*** | 0.312 0*** |
(0.150 1) | (0.004 7) | (0.002 1) | (0.028 7) | (0.014 8) | (0.206 6) | (0.100 8) | |
年份固定效应 | YES | YES | YES | YES | YES | YES | YES |
个体固定效应 | YES | YES | YES | YES | YES | YES | YES |
n | 6 560 | 4 710 | 4 710 | 4 710 | 4 710 | 5 180 | 5 180 |
表 7 机制分析
Tab.7 Analysis of mechanism
变量 | |||||||
---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | |
—0.099 3** | |||||||
(0.039 2) | |||||||
1.613 7*** | 0.279 9*** | ||||||
(0.040 2) | (0.020 7) | ||||||
0.145 8*** | 0.093 9*** | 0.283 7*** | 0.118 6*** | ||||
(0.023 8) | (0.018 5) | (0.051 7) | (0.026 6) | ||||
0.125 7*** | 0.089 7*** | ||||||
(0.025 3) | (0.020 4) | ||||||
—0.066 9*** | —0.012 8** | ||||||
(0.016 3) | (0.005 3) | ||||||
0.083 9*** | 0.0169 0** | ||||||
(0.020 6) | (0.008 4) | ||||||
常数项 | 0.354 9** | 10.012 2*** | 0.287 7*** | 9.528 7*** | 0.112 1*** | 9.050 9*** | 0.312 0*** |
(0.150 1) | (0.004 7) | (0.002 1) | (0.028 7) | (0.014 8) | (0.206 6) | (0.100 8) | |
年份固定效应 | YES | YES | YES | YES | YES | YES | YES |
个体固定效应 | YES | YES | YES | YES | YES | YES | YES |
n | 6 560 | 4 710 | 4 710 | 4 710 | 4 710 | 5 180 | 5 180 |
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