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Journal of Zhejiang University (Science Edition)  2023, Vol. 50 Issue (5): 619-627    DOI: 10.3785/j.issn.1008-9497.2023.05.013
Urban Science     
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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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 wordscounty economy      spatial-temporal evolution      patterns of difference      spatial econometric model      influencing factors     
Received: 10 October 2022      Published: 16 September 2023
CLC:  TU 982  
Corresponding Authors: Chunying ZHANG     E-mail: zhangchuying_zcy@163.com
Cite this article:

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.

URL:

https://www.zjujournals.com/sci/EN/Y2023/V50/I5/619


广西壮族自治区县域经济发展差异及影响因素分析

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 
Fig.1 Measurement of economic development differences in Guangxi counties
Fig.2 Theil index decomposition and contribution margin
Fig.3 Decomposition of the contribution of within-group differences
Fig.4 Line chart of county-wide Moran's I of GDP per capita
Fig.5 Local LISA aggregation map of county per capita GDP
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
Table 1 Meaning of explanatory variables, mode of representation and significance of selection
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
Table 2 LM test and its corresponding probability value
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
Table 3 Estimation results of the measurement model of factors affecting the level of economic development
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