检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:李鲁奇 叶滢 虞晓芬[3] 朱宇达 LI Luqi;YE Ying;YU Xiaofen;ZHU Yuda
机构地区:[1]浙江工业大学中国住房和房地产研究院 [2]浙江工业大学管理学院 [3]浙江工业大学中国住房和房地产研究院/管理学院 [4]杭州市房产市场综合管理服务中心
出 处:《价格理论与实践》2023年第8期105-109,209,共6页Price:Theory & Practice
基 金:杭州市住房租赁市场专项课题;浙江省科学技术厅一般软科学研究项目(2023C35055);国家自然科学基金项目(4230118371904175)。
摘 要:稳定城市房价,是确保房地产市场平稳发展、防范化解金融风险的重要手段。本文从住房板块尺度出发,以杭州市为例,测度板块间房价关联网络并分析其结构特征,随后借助指数随机图模型分析该网络形成的影响因素。研究表明:杭州各板块间房价波动的扩散存在不均衡性和时间滞后性;板块规模越大,其房价波动越容易影响其他板块,也越容易受其他板块影响;两板块在规模和房价整体水平上越相似,越容易产生房价关联;区县行政边界和距离的影响不明显。本文在空间尺度上细化了房价关联研究,有利于进一步理解城市内部房价波动扩散机理,并为因城施策稳定城市房价和预期提供一定借鉴。Stabilizing urban housing prices and preventing abnormal fluctuations in housing prices from spreading is significant to re-duce real estate market risks. Taking Hangzhou as an example, this paper measures the housing price correlation network between sectors and uses the exponential random graph model to reveal its formation mechanism. The research shows that the diffusion of housing price fluctuations among sectors is unbalanced and time-lagged;the larger the sector is, the more likely its housing price fluctuations will affect other sectors, and is also more easily affected by other sectors;The more similar the sectors are, the easier it is to generate house price corre-lation;the administrative boundaries and distances of districts and counties have no obvious influence on this. This paper offers a more mi-croscopic approach to understanding the diffusion mechanism of house price fluctuations within cities and the findings have policy implica-tions in stabilizing urban housing prices and expectations.
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:3.142.250.99