摘要
为了研究成渝经济区固定资产投资效益的县域空间差异及分布规律,采用计量经济学中的协整检验和误差修正模型,利用Eviews 7.0、Geoda和ArcGIS 10.2软件,对成渝经济区145个县(区)2000—2016年的固定资产投资效益的空间差异进行了研究。研究发现:不同县(区)之间投资效益差异大,最高的县(区)和最低的县(区)差距达10倍以上;在空间上,县(区)固定资产投资效益存在明显的分异,整体上呈现东北、西南片区高,中间低的马鞍形分布;成都、重庆二市的主要城区投资效益最高,在整个经济区空间上形成双核心分布模式;接壤川西北高原地区的县(区)投资效益最差;成渝经济区2000—2016年的固定资产投资效益呈现正向空间相关性,高高集聚、低低集聚分布集中且明显。
To study the spatial difference and distribution regularity of investment efficiency in counties and districts of Chengdu-Chongqing Economic Zone,the co-integration test and error correction model in Econometrics and Eviews 7.0,Geoda and ArcGIS 10.2 software are employed to study the spatial difference of fixed assets investment efficiency in 145 counties and districts of Cheng-Yu Economic Zone from 2000 to 2016.The research shows that these counties and districts differ greatly in investment efficiency with a gap of over 10 times between the highest and the lowest.In spatial structure,the obvious difference of fixed assets investment efficiency is found in the saddle-shaped distribution of higher efficiency in the northeast and southwest area but lower efficiency in the middle area.The core areas of Chengdu and Chongqing have the highest fixed assets investment efficiency,forming a distribution pattern of dual cores.The counties and districts located near the northwest Sichuan plateau are the lowest in investment efficiency.The investment efficiency of fixed assets in Cheng-Yu Economic Zone from 2000 to 2016 shows a positive spatial correlation and a concentrated and obvious distribution pattern of high-high agglomeration and high-low agglomeration.
作者
余霞
王如渊
周敏
易鹏
邓静
YU Xia;WANG Ruyuan;ZHOU Min;YI Peng;DENG Jing(College of Land and Resources,China West Normal University,Nanchong Sichuan 637009,China;Yibin University,Yibin Sichuan 644000,China)
出处
《西华师范大学学报(自然科学版)》
2019年第3期310-315,共6页
Journal of China West Normal University(Natural Sciences)
基金
国家社会科学基金项目(11FJL016)
关键词
成渝经济区
固定资产投资
投资效益
地域差异
空间相关性分析
Cheng-Yu Economic Zone
fixed assets investment
investment efficiency
regional difference
spatial correlation analysis