The Impact of Hot Money on Chinese Real Estate Price

Because of the expectation of RMB appreciation and the extremely high return rate of Chinese real estate market,more and more hot money rushed into China.As a result,the real estate price level is getting higher and higher,the bubble economy is getting worse,and the Chinese real estate is accumulating numerous risks.This study tried to find out the relation between the hot money and Chinese real estate price level with the help of empirical method.The study not only analyzed the impact of hot money on Chinese real estate price level and its harmful influence over the economy,but also proposed some suggestions to supervise the real estate market.

A Research on Government Regulations on High Price and High Vacancy in Real Estate: A Case Study of the Southern District of Qingdao City

Real estate plays a vital role in national economy and contributes a lot to social development. However, the rapid progress that has been made brings some problems, such as high price and high vacacy. This thesis takes Southern District of Qingdao City as an example to illustrate government regulation concerning real estate, and at the end some suggestions are provided.

Research on the Impact of Market Concern for Real Estate Policy on Housing Prices: Evidence from Internet Search and Hedonic Price Theory

To avoid the effects of systemic financial risks caused by extreme fluctuations in housing price,the Chinese government has been exploring the most effective policies for regulating the housing market.Measuring the effect of real estate regulation policies has been a challenge for present studies.This study innovatively employs big data technology to obtain Internet search data(ISD)and construct market concern index(MCI)of policy,and hedonic price theory to construct hedonic price index(HPI)based on building area,age,ring number,and other hedonic variables.Then,the impact of market concerns for restrictive policy,monetary policy,fiscal policy,security policy,and administrative supervision policy on housing prices is evaluated.Moreover,compared with the common housing price index,the hedonic price index considers the heterogeneity of houses and could better reflect the changes in housing prices caused by market supply and demand.The results indicate that(1)a long-term interaction relationship exists between housing prices and market concerns for policy(MCP);(2)market concerns for restrictive policy and administrative supervision policy effectively restrain rising housing prices while those for monetary and fiscal policy have the opposite effect.The results could serve as a useful reference for governments aiming to stabilize their real estate markets.

Virtualization of Real Estate Industry and Housing Bubbles --Empirical Evidence from China

In the last twenty years, China has experienced a rapid development in the real estate industry. The continuous rising house price causes many social and economic problems and draws a lot of attentions from academia, business world and government. Many researchers shed light on this problem from different angles, but till today, it hasn’t been fully resolved. In this paper, we try to examine the real estate bubble from a virtual economic perspective. We think that the virtual feature of real estate alters its economic role from a purely living and working place to a financing instrument. We use the newest monthly data of China real estate market from 2006 to 2018 and estimate the relationship between the housing bubble and real estate industry virtualization. We identify a significant positive association between house price index and the purchase price of land in real estate investment. This result suggests that virtual feature of real estate has deepen the bubble problem in the industry and its virtualization degree appears to be closely related to the virtual feature of land and its price proportion to real estate investment.

Study on the roles and acting mechanism of the real estate brokerage in China second-hand housing market

As China housing reform deepens, the second-hand housing transactions become more and more popular and real estate brokerages, as an intermediary of the transactions, become an undeniable important part of this market. This article mainly explores the roles and the acting mechanism of real estate brokerages in the second-hand housing market. The results show that the participation of real estate brokers in the second-hand housing market may have positive and negative influences. On one side, brokers ease the housing transaction process and benefits buyers and sellers by shortening the sale time on the market. On the other side, if brokers are the only participants in the housing transaction, acting as buyer and seller like some firms do, housing prices will increase and this negative effect will become even stronger as the participation of many more brokers increases. Therefore, the regulation and management of the industry is vital for the long and healthy development of the housing market in China.

The Impact of Property Tax on the Development of Real Estate Industry

In recent years,due to the rapid development of the real estate industry in China,land speculation has begun in addition to the significant growth in economy.However,this rapid development has led to an extreme rise in housing prices,largely owing to high property tax.This article analyzed the impact of property tax on the development of real estate industry and provided countermeasures.

Stock Market Turnover and China’s Real Estate Market Price: An Empirical Study Based on VAR

Our analysis used the monthly data of the average sales price of commodity houses and stock turnover in the Shenzhen Stock Exchange from January 2016 to December 2020. We selected this data to establish a Vector Autoregression(VAR) model using the Granger causality test to investigate the correlation between the stock market and the real estate market. We found that there is a significant positive correlation between the stock market and the real estate market. We also found that the real estate market price is the one-way Granger cause for the stock market turnover, and that changes in the real estate market price have a significant role in forecasting changes in stock market turnover. Therefore, the linkage between the two markets should be considered in macro regulations, and the impact on one of the markets should be considered when regulating the other.

Real estate appraisal system based on GIS and BP neural network

For the inefficiency and inaccuracy of appraisal method of traditional estate appraisal theory, the real estate appraisal system based on GIS and BP neural network was established. The structure of the system was designed which includes appraisal model, trade case, GIS database and query analysis module. With the help of the L-M algorithm in MATLAB software, BP neural network was improved and the trade cases were trained, then the BP neural network which has already been trained was tested. At the same time, the BP neural and GIS were put together to construct the hedonic price estimate model. The C# and ArcGIS9.3 were used to achieve the system in VS2008. City basic geographic data and real estate related information were used as the basic data in practice. The results show that the functions of querying, adding and editing the spatial data and attribute data are achieved and also the efficiency and accuracy of real estate are improved, so that the new method of real estate is provided by the system.

非对称信息视角下中国区域金融风险的影响机制

本文基于委托代理理论,构建非对称信息视角下中国区域金融风险影响机制的分析框架,并采用TVP-SV-VAR模型探究不同地区区域内金融风险影响机制的异质性。研究表明,非对称信息下金融系统委托代理行为致使商业银行存在信贷配给,资金倾斜助长了地方债扩张和房地产泡沫累积,一旦债务违约及泡沫破裂造成大量银行不良资产积聚,将引发区域金融风险。异质性研究发现,经济发达地区中房地产泡沫是区域金融风险形成的主导因素;经济次发达地区中地方政府过度举债是引致区域金融风险的主要冲击;而经济欠发达地区的区域金融风险是地方政府过度举债与房地产泡沫共同作用所致。国家金融监督管理总局应严控商业银行信贷资金流向,并对地方债扩张和房地产泡沫等区域金融风险影响因素实行“属性+对策”的差异化监管,构建风险治理的区域协作平台,提高区域金融风险的防范处置能力。

特征价格模型方法应用的研究进展与展望

特征价格模型方法是房地产市场价格评估、预测及影响因素分析研究中经典且常用的工具,通过梳理特征价格模型的理论基础,运用文献计量方法全面分析其研究现状。研究发现:1)新消费者理论和市场均衡理论是特征价格模型的理论基础;2)特征价格模型已成为应用经济学、人文地理学和城市规划等多学科领域使用的重要方法;3)特征价格模型包括普通多元回归模型、空间回归模型、多层次模型和机器学习等方法;4)特征价格模型的解释变量主要由结构特征、邻里特征和区位特征3大维度构成,其他环境特征也逐渐受到关注,但特征变量的测度方法不同可能导致研究结论的差异;5)未来的特征价格模型应用研究应从完善理论分析框架、选择合适的模型方法、准确测度特征变量内涵和提升研究结论的普适性等方面进行改进。

土地房地产税基基准价管理系统的设计与实现

为实现在土地房地产交易环节中实行计税基准价数字化、规范化管理的目标,针对土地房地产税基基准价管理中的问题,分析设计了土地房地产税基基准价管理系统主要功能、系统用例图、主要状态图等,并通过轻量级J2EE框架SSH来实现系统。系统主要包括系统管理、数据采集管理、数据运维管理、数据审核管理、应用查询系统等五大部分。该系统易于操作、使用、维护,满足用户的使用习惯,有效提高土地房地产交易环节中计税价格公正合理性,提高信息共享程度,具有较好的示范性及应用推广价值。

居民活动空间重塑视角下地铁与住宅价格的非线性关联

地铁重塑了居民的日常活动空间,拓展了他们接触各类资源的机会。然而,现有文献往往忽略地铁所带来的资源接触机会拓展对住宅价格的影响。文章以“15 min生活圈”概念为基础,以成都市为案例地,采用网络分析对居民的活动空间进行划定,将资源配置划分为邻里层面和跨区域层面,并构建极限梯度提升(XGBoost)模型,分析地铁可达性特征、邻里层面资源配置和跨区域层面资源配置对住宅价格的非线性影响。结果显示:1)最近地铁站接近中心性对住宅价格贡献率达14.26%,成为住宅价格的重要解释因素之一;2)邻里层面和跨区域层面资源配置的贡献率分别为34.60%和19.55%,表明邻里层面资源配置对住宅价格有较强的解释力度,但跨区域层面资源配置的影响也不容忽视;3)地铁可达性特征、邻里层面资源配置和跨区域层面资源配置与住宅价格存在复杂的非线性关系,且不同层面资源配置对住宅价格的影响呈现不同的趋势。

房地产企业资本结构对股价波动的传递效应分析——基于结构化GARCH模型

中国房地产企业资本结构长期处于高负债、高杠杆状态。在二十余年的房地产高速发展过程中,高杠杆风险长期被忽视,甚至被认为是房地产企业发展的固有模式。在结构化GARCH模型中引入资本结构因素,检验房地产企业资本结构对股价波动的传递与溢出效应。研究发现:中国房地产市场具有结构化特征,杠杆乘数与股价波动具有同步性;过高的负债水平并不会提升房地产企业的规模效应,反而会抑制股票收益率的增长。

基于麻雀搜索优化SVR模型的房地产价格研究

为解决传统经济指标作为房价影响因素的数据获取滞后性问题以及机器学习模型在预测房价时存在的参数选取不确定性问题,文中以网络搜索数据作为房价指数解释变量,采用麻雀搜索算法(Sparrow Search Algorithm,SSA)建立SSA-SVR(Support Vector Regression)模型对SVR的惩罚因子C和RBF(Radical Basic Function)核函数的参数g进行优化。将SSA-SVR模型与PSO(Particle Swarm Optimization)-SVR、GA(Genetic Algorithm)-SVR、WOA(Whale Optimization Algorithm)-SVR、GS(Grid Search)-SVR以及基准SVR进行对比,SSA-SVR的相关系数(0.99)、均方根误差(6.71)、平均绝对误差(5.24)、均方误差(45.13)以及平均绝对百分比误差(0.26%)均优于其他5种模型。结果表明,麻雀搜索算法优化的SVR模型在房价预测方面具有更好的全局寻优能力,可以提高模型的预测准确度和预测能力。

美联储加息冲击对中国房地产市场的溢出效应及其应对

利用2007—2022年季度数据构建BVAR模型,研究美联储加息对中国房地产市场的外溢效应,发现美联储加息将导致家庭债务、商品房销售额、房价和房地产投资下降,产生负向外溢效应。而后构建含有GHH效用函数、异质性家庭、信贷约束和房地产部门的小国开放经济DSGE模型,在加息冲击下,DSGE模型能够较好地拟合BVAR模型的特征事实。机制分析表明利息差渠道、国际资本流动渠道和利率渠道是其中主要的内在影响机制,信贷约束具有放大机制。反事实实验表明当美联储加息时,中国加息将使房地产市场进一步恶化;中国采取降息或放松信贷政策的逆向操作,在一定程度上能够对冲美联储加息的负面影响,但加剧了资本外流。中国在短期采取降息、在中长期采取加息和放松信贷相结合的政策组合,能够达到更好的政策调控效果。

货币政策、股票价格与房价波动

深入解析货币政策、股票价格与房价三者之间关系,有助于更好协调政策、经济增长与两类市场平稳发展。据此,本文基于价格超调理论,讨论了货币政策对股票市场价格和房地产市场价格的动态影响机制。理论研究表明,货币供应量的增加在直接抬高房价的同时,还会通过股票市场的超调效应间接影响房价。进一步应用随机波动时变参数向量自回归(TVP-SV-VAR)模型从时变角度测算了货币政策对两类资产价格影响的动态关系。研究发现:第一,短期内货币政策对股价较之房价有超调效应,长期看货币政策通过股票市场间接影响房价。第二,在经济扩张期、经济收缩期以及“新常态”时期三个代表性时点上,股价均对货币政策冲击产生超调现象,且会进一步向房价传导。第三,经济收缩期房价对货币政策的响应幅度要大于经济扩张期的响应幅度;经济“新常态”时期房价对货币政策的冲击响应小于经济“旧常态”时期。第四,股价作为中介效应通常是正向的,即股价对房价具有正向拉动作用。最后,引入传统中介效应检验方法,检验货币政策对房价传导过程的中介效应,结果显示货币政策确实存在以股价为中介向房价传导的作用机制。本文的研究结果为货币当局运用货币政策,协调经济增长和股票市场、房地产市场平稳发展提供了理论依据和实证参考。

水利基础设施投资信托基金(REITs)试点进展与推进思路

推进水利基础设施投资信托基金(REITs)试点是“两手发力”助力水利高质量发展的重要举措之一。试点采用的主要模式有大型水利基础设施的优质资产剥离和中小型水利基础设施的资产重组整合两种模式。试点相关政府部门、权益人以及专业机构各司其职,积极作为,协同推进试点工作。针对REITs融资效率偏低、水利项目较难满足发行条件、部分原始权益人不能或不愿参与试点等制约试点推进的因素,应建立健全工作协调、项目储备、监督管理“三项机制”,推进工程供水价格和水利工程管理“两项改革”,“两手发力”推进水利基础设施REITs试点。