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.

The analysis of the influence factors of China＇s real estate prices

The real estate market is an ilnportant part of China＇s socialist market economy. Real estate price xs not only a profound role on the level of consumption of the residents, but a profound role on the steady development of the banking sector-based financial sector. Real estate price have a significant impact not only on the development ofmacroeconomic stability, but on the safety of financial system. Chinese economy is currently on the period of transition from investment and export promotion of economic growth mode to a demand-led growth, it is an important role to China＇s economic growth for sustained and healthy development of real estate market.

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.

Empirical research on the relationship between real estate price fluctuation and foreign money inflow

In recent years, the real estate price has been raising with the volume of foreign money inflow increasing. The relationship between foreign money and real estate price becomes a focus. This paper studies the relationship with empirical methods. The co-integration test shows that there is a long equilibrium between real estate price rising and foreign money inflow. The analysis of ECM shows that foreign money inflow as to real estate price rising is less important than real estate price rising as to foreign money inflow. And Granger test also shows that foreign money inflow is not the cause of real estate price rising, on the contrary, real estate price rising causes foreign money flowing in.

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.

Energy Price Fluctuation and Real Estate Market Risk Prevention——Empirical Evidence at the Prefecture-Level City Level in China

The impact of energy price fl uctuation on the macro economy is a hot issue that is continuously concerned by the academic community,but few literature have paid attention to the impact of energy price fl uctuation on housing price and the financial risks that may arise.Based on the data of cities at and above the prefecture level in China,this paper empirically examines the impact of energy price fl uctuation on the price fl uctuation of the domestic real estate,and analyzes its infl uencing mechanism and transmission pathways.The results show that changes of energy price will significantly affect the fl uctuation of domestic real estate price,and it is more obvious in large cities and megacities.Energy price affect the demand for housing through changes of interest rate levels on the one hand,and the supply of the real estate market through the cost of housing construction on the other hand,which leads to housing price fl uctuation.After a series of robustness tests,the results are still valid.At the same time,the effect is asymmetric,that is,higher energy price increases the fl uctuation of house price,but the impact of falling energy price is not significant.Therefore,when preventing real estate market risks,energy price should be considered as a forward-looking indicator to focus on,and the regulation and control policies of the real estate market should be scientifically formulated.This paper not only provides a new perspective on the mechanism of housing price formation,but also enriches the research on the interconnection between energy and financial markets.

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.

Study on the House Market and Pricing——A Case Study of Nanjing's Building Groups

In this paper,some methods of economics and management were used.Based on analysis of the house market structure,the factors influencing the house price,the house pricing methods and strategies were proposed.Then a case in Nanjing was studied,and the results show:firstly,the house market is a monopolistic competitive market,and in some places it is even an oligopoly market;secondly,the cost-plus pricing method is reasonable and scientific,and the specificity is the base of pricing;thirdly,the average price of a building groups in Nanjing should be 8 906$/sq.m.Finally,aiming at the house pricing,some countermeasures and suggestions are put forward in this paper.

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.

Real Estate Evaluation in Germany

The real estate market is at risk to produce economic bubbles, which produce heavy financial losses while bursting. To flatten these bubbles, Germany tried since the 1960s a way of thorough analysis and high transparency of the real estate market as a public task. The experts from different professions in the local market effectively are included in a honorary form. The competition between the experts and also between the experts and the public institution is intentionally maintained.

房地产股价波动对高技术板块的溢出效应研究——基于DGC-t-MSV模型

过度的金融资产投资可能导致房地产股价泡沫,并且通过风险溢出渠道给高技术板块带来价格冲击。研究聚焦于房地产行业和高技术产业的股票价格指数,结合MODWT分解和DGC-t-MSV模型进行实证分析,结果表明:其一,“房地产-高技术”的股票价格动态相关,房地产行业价格波动的传导作用更加强烈,对高技术板块具有明显的溢出效应;其二,实施限制性政策后房地产行业的挤出效应降低,高技术及其分类产业的创新投入受到的限制逐渐减弱;其三,短、中期频繁交易是导致房地产溢价的主要原因,需要警惕高技术板块面临的溢出风险。积极引导高技术板块的价值投资,合理配置技术要素,能够有效促进高技术产业的高质量、高水平发展。

基于资产负债表衰退理论的中国房地产经济现状分析——以房地产和建筑业上市公司为例

当前我国房地产经济面临较为严峻的形势,多项指标呈负增长状态,陆续有房地产企业发生债务违约等风险事件,房地产行业的低迷已经开始拖累整体经济发展。由于房地产及与其密切相关的建筑业是国民经济的重要支柱,其对金融稳定和经济安全的影响极为重大。对当前我国房地产经济的现状进行科学分析和研判,并提出相应的政策建议就具有重大现实意义。本文基于资产负债表衰退理论,以中国内地房地产及建筑业上市公司2019-2022年数据为研究对象,对其资产价值及负债情况进行分析,从微观企业层面对当前房地产经济是否陷入资产负债表衰退做出判断,并提出下一步的政策建议。

人口老龄化对货币政策调控房地产价格效果的影响研究

文章基于1999—2022年中国宏观经济数据,通过构建时变参数向量自回归模型(TVP-VAR)分析货币政策对于房地产价格的调控效果。实证结果表明数量型货币政策与价格型货币政策在中长期对房地产价格调节均明显衰减,同时价格型货币政策的调节效果具有显著不确定性。利用2000—2021年中国省级面板数据构建系统广义矩估计模型(System-GMM)分析人口老龄化对货币政策调控房地产价格效果的影响。结果表明人口老龄化对于数量型货币政策调控房地产价格的效果产生负面影响,但对价格型货币政策在调控房地产价格方面的影响并不显著。在人口老龄化时代背景下,为中央银行改进货币政策,提高货币政策实施效果,以应对人口老龄化并促进房地产市场稳步发展提供参考,具有重要理论与现实意义。

新房价格底部特征分析及政策建议

判断房价的趋势和拐点,是房地产市场研究的重点和难点,需要找到关键的分析指标。主要发达国家房地产市场发展历程表明,房价收入比的低点通常是房价的低点,房贷利率连续大幅下调会促进房价企稳,租金回报率超过无风险利率时房价触底支撑增强,购房意愿度最低时往往也是房价筑底的时候。我国在2008—2009年和2014—2015年经历过两次房价下行,房价筑底时房价收入比、个人住房贷款利率、租金回报率与无风险利率的利差、购房者预期四个指标均表现出了与国际市场相似的特征。本轮始于2021年下半年的房地产市场下行,是时间最长、房价调整幅度最大的一次。用房价收入比等四个指标判断,当前新房价格已呈现明显的底部特征。建议重视解决房企资金紧张问题,优化住房供给结构,降低居民改善置换成本,促进房地产市场尽快回稳。

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。

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。

人口老龄化对金融稳定的影响

金融是国民经济的血脉,人口因素是影响金融稳定的关键因素,因此人口结构失衡会对宏观经济发展和金融市场稳定产生重要的影响。本文选取我国2013~2022年的宏观季度数据,实证检验人口老龄化与金融稳定的关系。结论表明:从省份层面来看,人口老龄化对金融稳定呈现负面影响,通过增加房地产价格波动和增加财政压力降低金融稳定性。在进一步研究中,本文从全国层面出发,研究发现人口老龄化对金融稳定同样存在负面影响。

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。