摘要: |
由于国家政策和地理位置等方面原因,我国各省区的农村区域经济发展存在较大差异,严重影响了全面小康社会的建设步伐。文章以四川省21个地级农村区域经济差异为研究对象,通过文献分析和建立数学模型的研究方法,对四川省农村区域经济差异的显著性进行分析,结果表明:(1)四川省农村区域经济存在一定差异,其中经济发展较快的城市为成都市、绵阳市。(2)对四川省区域经济发展测算得出:2010~2014年期间,区域三内部差异的波动幅度较大,范围在0.14~0.01之间,说明经济发展潜力较大。区域二内部差异呈“降低—增高—降低”的趋势,经济发展潜力一般;区域一由于地理位置和气候资源等因素限制,经济发展较慢。该研究为四川省农村区域经济的均衡发展提供理论参考。 |
关键词: 农村区域经济 经济差异 均衡理论 差异显著性 主成分分析 |
DOI:10.7621/cjarrp.1005-9121.20160532 |
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ANALYSIS ON THE DIFFERENCE OF REGIONAL ECONOMY IN RURAL AREAS OF SICHUAN PROVINCE |
Chen Sitong1, Huang Xiaozhi2
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1.School of economics and information engineering,Southwestern University of Finance and Economics,Chengdu,Sichuang 611130,China;2.School of business administration,Xihua University,Chengdu,Sichuang 610039,China
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Abstract: |
Due to the national policy and geographical position,there are great differences in the economic development of rural areas,which seriously affect the pace of building a well-off society in an all-round way.Taking21 regional economic disparities of rural areas in Sichuan province as the research object,this paper analyzed the significance of rural regional economy differences of Sichuan Provincethrough the literature analysis and established mathematical model.The results showed that:(1)there was a certain difference in regional economic development in rural areas of Sichuan province.Chengdu andMianyang City had more rapid economic development.(2)Through the calculation of regional economic development in Sichuan Province,it showed that from 2010 to 2014,the regionalinternal differences fluctuated greatly,ranging from 0.01 to 0.14,indicating a greater economic development potential.The internal difference of the region showed a trend of decreasing-increasing-decreasing.The economic development in region was slow due to the geographical location and climate resources.The study can provide a theoretical reference for how to solve the problem of rural regional economic development in Sichuan province. |
Key words: rural regional economy economic difference equilibrium theory significant difference principal component analysis. |