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浙江大学学报(理学版)  2023, Vol. 50 Issue (5): 619-627    DOI: 10.3785/j.issn.1008-9497.2023.05.013
城市科学     
广西壮族自治区县域经济发展差异及影响因素分析
孙昌盛1,2,胡欣琪2,张春英1,2(),吴优1,2
1.桂林理工大学 广西绿色建材与建筑工业化重点实验室,广西 桂林 541004
2.桂林理工大学 土木与建筑工程学院,广西 桂林 541004
Analysis on differences and influencing factors of economic development in counties of Guangxi Zhuang Autonomous Region
Changsheng SUN1,2,Xinqi HU2,Chunying ZHANG1,2(),You WU1,2
1.Guangxi Key Laboratory of Green Building Materials and Construction Industrialization,Guilin University of Technology,Guilin 541004,Guangxi Zhuang Autonomous Region,China
2.College of Civil Engineering and Architecture,Guilin University of Technology,Guilin 541004,Guangxi Zhuang Autonomous Region,China
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摘要:

经济发展不均衡是区域经济的常态,适度的区域经济差异有利于发挥地区比较优势。近年来,区域经济差异研究大多集中在中部沿海、长三角、珠三角等发达地区,对广西壮族自治区等欠发达地区的研究很少。以广西壮族自治区92个县域为基本研究单元,利用变异系数、泰尔指数和探索性空间数据分析,研究2005—2020年县域经济集聚差异的时空演变格局,并通过构建空间杜宾模型,探究差异的形成原因。结果表明:(1)县域经济的绝对差异逐渐增大,相对差异略有缩小,区域内差异一直大于区域间差异;(2)大部分县域经济发展处于孤立状态,低水平县域集聚分布,区域间的经济要素关联性较弱,整体呈低水平均衡状态;(3)城镇化水平、市场规模、公共财政支出、投资水平对县域经济差异具有促进作用,产业结构对县域经济差异具有负向作用。因此,广西壮族自治区需要继续坚持集聚式发展,促进区域经济共同发展。

关键词: 县域经济时空演变差异格局空间计量模型影响因素    
Abstract:

The unbalanced economic development is a normal state of regional economy, and moderate regional economic differences are conducive to exerting regional comparative advantages. In recent years, the research work on regional economic differences are mostly concentrated in the developed areas such as the central coastal areas, the Yangtze River Delta and the Pearl River Delta, and there are few research results concerning the underdeveloped areas such as Guangxi. Taking 92 counties in Guangxi Zhuang Autonomous Region as the basic research objects, this paper uses the coefficient of variation, theil index and exploratory spatial data analysis to study the spatial and temporal evolution pattern of county agglomeration differences in Guangxi from 2005 to 2020, and explores the causes of this difference by constructing the spatial Durbin model. The results show that: (1) the absolute difference of county economy in Guangxi increased in this period, while the relative difference decreased slightly, and the intra-regional difference was always greater than the inter-regional difference; (2) the economic development of most counties was in an isolated state, low-level counties are clustered, the correlation of economic factors among regions was weak, which presented globally is a low-level equilibrium state; (3) the urbanization level, market scale, fiscal expenditure and investment level promote the county economic differences, while the industrial structure had a negative effect on the economic differences. Therefore, Guangxi needs to persist in agglomeration development to promote the common development of regional economy.

Key words: county economy    spatial-temporal evolution    patterns of difference    spatial econometric model    influencing factors
收稿日期: 2022-10-10 出版日期: 2023-09-16
CLC:  TU 982  
基金资助: 国家自然科学基金资助项目(52268009);广西建筑新能源与节能重点实验室项目(桂科能22-J-21-29)
通讯作者: 张春英     E-mail: zhangchuying_zcy@163.com
作者简介: 孙昌盛(1979—),ORCID:https://orcid.org/0000-0003-3607-6392,男,硕士,副教授,主要从事城市空间结构与空间布局、城市空间发展战略研究.
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引用本文:

孙昌盛,胡欣琪,张春英,吴优. 广西壮族自治区县域经济发展差异及影响因素分析[J]. 浙江大学学报(理学版), 2023, 50(5): 619-627.

Changsheng SUN,Xinqi HU,Chunying ZHANG,You WU. Analysis on differences and influencing factors of economic development in counties of Guangxi Zhuang Autonomous Region. Journal of Zhejiang University (Science Edition), 2023, 50(5): 619-627.

链接本文:

https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2023.05.013        https://www.zjujournals.com/sci/CN/Y2023/V50/I5/619

图1  县域经济发展差异测度
图2  泰尔指数及差异贡献率
图3  区域内差异的贡献率分解
图4  县域人均GDP全域Moran's I折线图
图5  县域人均GDP局部LISA集聚图注 基于中国标准地图[审图号:GS(2022)1873]制作,底图无修改。
指标含义表征方式选取意义
K1城镇化水平城镇人口/常住人口城镇化是扩大区域内需的重要动力,与地区的经济发展呈正相关关系
K2市场规模

社会消费品零售总额/

常住人口

市场规模的扩大意味着对商品和要素的更大需求,将进一步带来更复杂的经济结构,因此市场规模与经济发展密不可分
K3产业结构

第三产业产值/

第二产业产值

合理的产业结构能够实现资源的优化配置,最大程度地发挥生产要素的作用,实现生产总量的增加,进而促进经济持续发展
K4公共财政支出

一般公共预算支出/

常住人口

公共财政支出是政府调控的重要手段,对地区经济发展具有重要意义
K5投资水平固定资产投资投资水平决定地区的生产能力和经济发展水平
表1  解释变量含义、表征方式及选取意义
检验统计量概率
LM lag6.1370.013
R-LM lag4.0620.044
LM err2.1110.146
R-LM err0.0360.146
残差Moran's I (0.091)-0.066
表2  LM检验及其相应概率
变量OLSSLMSEMSDM
K10.423*** (3.141)0.406*** (3.184)0.442*** (3.372)0.619*** (4.504)
K20.407*** (5.862)0.360*** (5.369)0.384*** (5.692)0.265*** (3.823)
K3-0.273*** (-6.255)-0.266*** (-6.469)-0.271*** (-6.447)-0.245*** (-6.029)
K40.158 (2.901)0.153*** (2.964)0.119** (2.243)0.159*** (2.871)
K50.122*** (2.954)0.102*** (2.590)0.108** (2.550)0.100** (2.257)
W_K1---0.500 (1.418)
W_K2----0.135 (-0.858)
W_K3---0.040 (0.436)
W_K4---0.472*** (0.436)
W_K5---0.150** (1.986)
ρλ-0.222*** (2.576)0.249** (1.942)0.116 (0.874)
R20.7650.7800.7730.804
lg likelihood-16.250-13.182-14.929-6.203
AIC44.499 440.364 141.857 636.406 7
表3  经济发展水平影响因素计量模型估计结果
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