摘要
随着本轮房地产调控的深化,房地产价格正走入涨幅放缓甚至下行区间。2018年往后,我国房地产市场将面临诸多宏观风险。本文从供给、需求、房价泡沫水平三个方面,选取租金收入比、年化租售比、房价收入比、常住人口增速、老年人口占比、居民可支配收入增速、居民负债率以及土地财政依赖度和投资销售增速差9个维度的指标,对国内24个主要大中城市房地产风险水平进行评估分析。得出以下主要结论:一线城市的房地产风险要高于二线城市,一线城市接近房价下行拐点,二线城市房价涨速放缓;北京、上海人口下降将导致消费性需求减弱,投资性需求取决于限购条件;成都、重庆和长沙是目前房地产风险指数较低的城市,受到一线城市溢出效应以及人口往中心城市集中的影响,这些城市的潜在购房需求相对较大。
The deepening of this round of real estate regulation has curbed the skyrocketing trend in real estate price,and has even led the price entering into a downlink interval.Since 2018,our real estate market has been facing numerous macroeconomic risks.This article estimates real estate risk levels of 24 main large and medium-sized cities from three perspectives,including supply,demand,and real estate bubble.Based on this methodology,9 indicators are selected accordingly,namely rent-to-income ratio,annualized price-to-rent ratio,housing price-to-income ratio,permanent resident population growth rate,proportion of elderly population,residents’disposable income growth rate,residents’liability ratio,degree of dependence on land finance,and growth rate discrepancy between investment and sales.The estimation results convey several underlying messages:First tier cities have arrived at a turning point on the downward spiral,yet speed of housing price growth in second tier cities has been slowed down;the trend of demographic contraction in Beijing and Shanghai would be continuously weakening local consumption demand,while investment demand depends on future stringency of house purchase restrictions.Chengdu,Chongqin and Changsha are estimated to have lower real estate risk levels currently.As population has been gradually migrating from first tier cities,while these cities carry the characteristics of central cities,they would probably have the highest potential demand of house purchase in the future.
作者
林采宜
程丹
LIN Caiyi;CHENG Dan(Hua An Fund Management;Shanghai University of Finance and Economics)
出处
《新金融评论》
2018年第2期109-118,共10页
New Finance Review
关键词
房地产风险
房价泡沫水平
周期性拐点
人口结构变化
Real Estate Risks
Housing Bubble
Inflection Point in an Economic Cycle
Demographic Changes
