地理研究 ›› 2019, Vol. 38 ›› Issue (1): 75-84.doi: 10.11821/dlyj020180443
收稿日期:
2018-09-10
修回日期:
2018-11-23
出版日期:
2019-01-20
发布日期:
2019-01-20
作者简介:
作者简介:孙斌栋(1970- ),男,河北阜平人,教授,博士生导师,主要从事城市地理与经济地理研究。E-mail:
基金资助:
Bindong SUN1,2,3(), Xiaoxi JIN1,2,3, Jie LIN1,2,3
Received:
2018-09-10
Revised:
2018-11-23
Online:
2019-01-20
Published:
2019-01-20
摘要:
为了落实国家新型城镇化规划提出的大中小城市协调发展战略,对1952-2014年中国城市规模分布指数进行演化分析,并在时间序列分析基础上探索了影响因素。结果表明,2000年以来,中国城市规模分布一改长期的分散化趋势,正走向集中化;人口规模增长、政策干预以及城市之间信息和交通成本的节约,都促使城市规模分布分散化;人均GDP长期以来促进了城市规模分布的集中,但近年来开始促进分散化;对外开放水平则主要促进分布的集中。未来应以全国适度均衡发展作为指导方针;远期以市场一体化,近期以共赢互利机制建设为抓手,促进城市群内大中小城市协调分工,优势互补;注意政策的稳定性和长期性,减少城市化格局的人为波动。
孙斌栋, 金晓溪, 林杰. 走向大中小城市协调发展的中国新型城镇化格局——1952年以来中国城市规模分布演化与影响因素[J]. 地理研究, 2019, 38(1): 75-84.
Bindong SUN, Xiaoxi JIN, Jie LIN. China's new pattern of urbanization toward coordinated development of large, medium and small cities: Evolution and determinants of city size distribution since 1949[J]. GEOGRAPHICAL RESEARCH, 2019, 38(1): 75-84.
表1
我国城市规模分布的影响因素:协整回归结果"
1952-2014年 | 1960-2014年 | 1978-2014年 | 1993-2014年 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
模型(1) | 模型(2) | 模型(3) | 模型(4) | 模型(5) | 模型(6) | 模型(7) | 模型(8) | ||||
GDP一次 | GDP一二次 | GDP一次 | GDP一二次 | GDP一次 | GDP一二次 | GDP一次 | GDP一二次 | ||||
POP | 0.0525*** | 0.1109*** | 0.1429*** | 0.1033** | 0.2971 | 0.1901 | -0.3095 | 2.0826** | |||
(0.018) | (0.038) | (0.045) | (0.043) | (0.195) | (0.339) | (0.588) | (0.736) | ||||
GDP | -0.0063 | -0.0862* | -0.0561*** | 0.1528** | -0.0302** | 0.0145 | 0.0355 | -0.6820*** | |||
(0.004) | (0.046) | (0.019) | (0.067) | (0.013) | (0.115) | (0.036) | (0.190) | ||||
GDP2 | 0.0054* | -0.0195*** | -0.0027 | 0.0386*** | |||||||
(0.003) | (0.006) | (0.007) | (0.010) | ||||||||
HD | 0.0079 | 0.0082 | -0.0044 | 0.0119 | -0.0112 | -0.0110 | -0.0008 | 0.0042 | |||
(0.009) | (0.008) | (0.012) | (0.012) | (0.014) | (0.014) | (0.007) | (0.005) | ||||
RD | -0.0246 | -0.0545 | -0.0439 | -0.0405 | 0.0224 | 0.0248 | 0.0176 | 0.1226** | |||
(0.030) | (0.034) | (0.037) | (0.034) | (0.064) | (0.065) | (0.047) | (0.041) | ||||
GOV | 0.0642 | 0.0751* | 0.0826* | 0.1046** | 0.0330 | 0.0458 | 0.6977*** | 0.2015 | |||
(0.042) | (0.042) | (0.047) | (0.043) | (0.094) | (0.101) | (0.208) | (0.188) | ||||
INDUSTRY | 0.0084 | 0.0140* | 0.0028 | 0.0061 | -0.0191 | -0.0056 | |||||
(0.008) | (0.007) | (0.014) | (0.017) | (0.039) | (0.026) | ||||||
TRADE | 0.0124 | -0.0267 | -0.0608** | -0.0639** | 0.0175 | -0.0242 | |||||
(0.025) | (0.026) | (0.029) | (0.030) | (0.019) | (0.016) | ||||||
URBAN | 0.4101** | 1.0468*** | 0.0905 | 0.2079 | -0.2214 | -2.1901*** | |||||
(0.171) | (0.250) | (0.241) | (0.388) | (0.578) | (0.640) | ||||||
TELEPHONE | 0.0018*** | 0.0017*** | 0.0003 | 0.0027* | |||||||
(0.000) | (0.000) | (0.002) | (0.001) | ||||||||
INCOME | 0.0014 | 0.0012 | -0.0185 | 0.0147 | |||||||
(0.008) | (0.008) | (0.011) | (0.011) | ||||||||
INTERNET | -0.0017 | -0.0000 | |||||||||
(0.002) | (0.001) | ||||||||||
C | 0.1348 | -0.8168 | -1.5333* | -1.4325* | -4.7171 | -2.7075 | 7.4594 | -38.6282** | |||
(0.362) | (0.6527) | (0.855) | (0.779) | (3.997) | (6.569) | (11.985) | (14.404) | ||||
样本量 | 63 | 63 | 55 | 55 | 37 | 37 | 22 | 22 | |||
R-squared | 0.310 | 0.3455 | 0.431 | 0.539 | 0.677 | 0.679 | 0.974 | 0.990 |
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