摘要
农村居民生活条件与农业现代化的问题是关系我国粮食安全与经济发展的两大重要问题,对两者耦合关系的研究,有重要意义,以山东省为研究区域,建立两者的评价指标体系,基于耦合协调度模型评估两者的耦合度与协调发展度,并利用灰色预测模型对两者2018-2022年的耦合协调度进行预测.结果显示:①2007-2017年农村居民生活条件持续走高,农业现代化水平缓慢增加;两者的耦合度一直处于拮抗状态;协调度从高度失调过渡为濒临失调.②预测结果显示,两者的综合指数均不断增大,但农村居民生活条件综合指数增长速度明显较快,导致二者耦合程度逐步下降,但协调度值在逐年增大.最后从农村公共服务的有效供给、系统反馈作用、统筹兼顾等方面提出了建议.
Rural residents living conditions and agricultural modernization are two important problems concerning food security and economic development in China,so it is of great significance to study the coupling relationship between the two.Taking Shandong province as the study area,we build an evaluation index system to assess the coupling degree and the coordinated development degree of the two based on the coupling coordination degree model,and we also predict the coupling coordination degree of the two from 2018 to 2022 by using grey prediction model.The results showed that:①the living coupling degree of the two has been in an antagonistic state;living conditions of rural residents continued to rise from 2007 to 2017,and the level of agricultural modernization increased slowly;degree of coordination transitioned from highly disordered to near disordered.②the prediction results show that the comprehensive index of the two is increasing,but the rural residents living conditions of the comprehensive index growth rate is significantly faster,resulting in a gradual decline in the degree of coupling between the two,but the degree of coordination increased year by year.Finally,some suggestions are put forward from the aspects of effective supply of rural public service,systematic feedback and overall consideration.
作者
吴姝璇
李贻学
姜长军
WU Shuxuan;LI Yixue;JIANG Changjun(College of Resources and Environmect,Shandong Agricultural University,Tai’an 271000,China)
出处
《湖北民族学院学报（自然科学版）》
CAS
2019年第2期234-240,共7页
Journal of Hubei Minzu University(Natural Science Edition)
关键词
农村居民生活条件
农业现代化
耦合协调度模型
灰色预测模型
山东省
rural residents living conditions
agricultural modernization
coupling coordination degree model
grey prediction model
Shandong province
