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中国区域经济增长俱乐部趋同及其演变分析——基于时空加权马尔科夫链的预测    

Regional Economic Growth Convergence Clubs and Their Evolution Analysis of All Prefecture: Level Cities in China on the Basis of Forecast With Spatial - temporal Weighted Markov Chain

文献类型:期刊文献

中文题名:中国区域经济增长俱乐部趋同及其演变分析——基于时空加权马尔科夫链的预测

英文题名:Regional Economic Growth Convergence Clubs and Their Evolution Analysis of All Prefecture: Level Cities in China on the Basis of Forecast With Spatial - temporal Weighted Markov Chain

作者:张伟丽[1]

第一作者:张伟丽

机构:[1]河南财经政法大学资源与环境学院

第一机构:河南财经政法大学资源与环境学院

年份:2015

卷号:0

期号:3

起止页码:108-114

中文期刊名:经济问题

外文期刊名:On Economic Problems

收录:CSTPCD;;国家哲学社会科学学术期刊数据库;北大核心:【北大核心2014】;CSSCI:【CSSCI2014_2016】;

基金:国家自然科学基金青年项目“时空耦合俱乐部趋同假说及中国案例的研究”(41101128);河南省政府决策研究招标项目(2014004);河南省高校科技创新人才支持计划项目(2013年);河南省高等学校青年骨干教师资助计划项目;河南财经政法大学青年学术创新骨干支持项目的阶段性成果

语种:中文

中文关键词:马尔科夫链;时空加权马尔科夫链;趋同俱乐部;演变

外文关键词:Markov chain ; spatial - temporal weighted Markov chain ; convergence club ; evolution

摘要:利用马尔科夫链、空间马尔科夫链及时空加权马尔科夫链等方法,分析了中国所有地级市经济增长的趋同俱乐部空间分布及其演变趋势,认为:(1)中国地级市经济增长存在低水平、中低水平、中高水平及高水平等四个趋同俱乐部。(2)低水平趋同俱乐部主要集中在我国中部的落后地区及西部边远地区,且多为少数民族聚集地。高水平趋同俱乐部主要集中在我国中西部资源型城市及沿海城市。(3)邻居越发达,越有利于趋同俱乐部的演变。(4)从极限分布来看,与低收入邻居相邻未来67.5%的可能仍然属于低收入类型,与高收入邻居相邻未来65.2%的可能属于高收入类型。最后,提出制定有梯度的区域适配型政策、提高基本公共服务水平、以企业间的合作为纽带及以新型中小城镇及城市群为增长极等政策建议。
By using Markov per analyses regional economic chain, growth spatial Markov chain and spatial -temporal weighted Markov chain this paconvergence clubs and their evolution of all prefecture -level cities in China. There are four convergence clubs such as low level, middle low level, middle high level and high level. The low convergence club mainly concentrates in the poor central China and the remote western and more for the ethnic enclaves. The high convergence club mainly concentrates in the resource type city of central and Western China and coastal cities. The neighbors are more prosperous that it is more conducive to the evolution of club convergence. From the limit distribution this paper concludes that cities with low income neighborhood tend to still belong to the low convergence club with 67.5 % probability. And cities with high income neighborhood tend to still belong to the high convergence club with 65.2% probability. Finally, according to the results this paper proposes some policy suggestions such as developing gradient cing the cooperation between enterprises and adaptation policies, raising the level of basic public services, enhan- nurturing new towns and city groups as growth poles.

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