| 中国区域经济增长的空间网络关联及收敛性检验 |
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| 引用本文： | 刘华军,贾文星.中国区域经济增长的空间网络关联及收敛性检验[J].地理科学,2019,39(5):726-733. |
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| 作者姓名： | 刘华军 贾文星 |
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| 作者单位： | 山东财经大学经济学院,山东济南,250014;山东财经大学经济学院,山东济南,250014 |
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| 基金项目： | 国家社会科学基金项目(16BJL033);山东省泰山学者青年专家计划资助(tsqn20171208) |
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| 摘 要： | 基于1992~2013年中国30个省份面板数据,利用引力模型和网络分析方法考察中国区域经济增长空间关联网络的结构特征,并基于空间网络权重,对中国区域经济增长进行收敛检验,研究发现：① 中国区域经济增长的空间关联网络呈现复杂化与全域性的发展趋势,但网络的整体紧密程度不够。② 山东、河南和江苏在空间关联网络中既扮演中心行动者的角色,又在网络中发挥着“中介”与“桥梁”的作用。③ 四大板块内部及之间存在普遍的关联关系,板块Ⅲ在四大板块中发挥核心带动作用。④ 中国区域经济增长存在全域性收敛现象,与基于传统空间权重的模型相比,空间网络权重下模型的收敛速度加快;资本积累是影响收敛的重要因素。此外,东部、中部和西部存在一定程度的俱乐部收敛趋势。
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| 关 键 词： | 区域经济增长 空间关联 网络分析 收敛检验 |
| 收稿时间： | 2018-05-15 |
| 修稿时间： | 2018-07-12 |
Spatial Network Correlation and Convergence Test of Regional Economic Growth in China |
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| Liu Huajun,Jia Wenxing.Spatial Network Correlation and Convergence Test of Regional Economic Growth in China[J].Scientia Geographica Sinica,2019,39(5):726-733. |
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| Authors: | Liu Huajun Jia Wenxing |
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| Institution: | School of Economics, Shandong University of Finance and Economics, Jinan 250014, Shandong, China |
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| Abstract: | Under the interaction of government regulation and market mechanism, the spatial correlation of regional economic growth in China has gradually evolved into a complex, multi-threaded network structure Based on the panel data of 30 provinces in China from 1992 to 2013, this article uses the gravitational model and the network analysis method to investigate the structural characteristics of the spatial association network of China's regional economic growth, and based on the weight of the space network to test the convergence of the regional economic growth in China. The research finds that: 1) The spatial correlation network of China's regional economic growth presents a complex and global development trend. The inter-provincial linkages show the coexistence of adjacent connections and jump connections. There are no independent development provinces, but the overall network is not tight enough; The connectivity and accessibility are strong, there are multiple overlapping spillover effects, and the stability of the network is strong; the network hierarchy has a significant downward trend, and the hierarchical structure of the spatial association network is not strict. 2) The degrees, proximity and intermediate centers of Shandong, Henan and Jiangsu are ranked in the top three, and they also have the most contacts with other provinces. They play the role of central actors in the spatial correlation network, and play the role of "intermediary" and "bridge" in the network. The provinces with the lowest degree of degree and near center degree are Jilin and Henan, and the phenomenon of mediation is 0 in many provinces. 3) The spatial correlation network of regional economic growth can be divided into four sections. There are general relationships within and between the four major sections. Among them, the impact of the spillover of the other sections of the sector II is the largest, and the relationship of the sector III to the other sections is the most. It plays a core role in the four sections. 4) The empirical results of convergence test show that there is a global convergence phenomenon in China's regional economic growth. Compared with the traditional spatial weight model, the convergence speed of the model is faster under the weight of the spatial network, reaching 0.07, and the spatial interaction between regions reduced the gap of them; the savings rate has a positive and significant impact on the economic growth rate, capital accumulation is still an important factor affecting convergence; in addition, there is a certain degree of club convergence in the eastern, central and western regions, the central region showed the strongest convergence trend, the convergence speed was as high as 0.101, and the convergence speed in the western region was the lowest, only 0.038. This reveals the important role of spatial network association in regional economic growth and has important theoretical significance for promoting regional coordinated development. |
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| Keywords: | regional economic growth spatial correlation network analysis convergence test |
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