On the Influence Factors of Second-hand House Prices in First-tier Cities——Empirical Analysis Based on Panel Data

With the arrival of the ＂housing stock＂ in first - tier cities, the second - handhousing^market will become the dominant property market. This ardcle aim to the first - tiercities of second - hand housing prices and new home price index for the empirical analysis, thedata related to the cointegration analysis found that the result of the first -tier cities real estatemarket in China, the new home price index is the significant factors influencing the second -hand house price indexi For Beijing, Shanghai second - hand housing and new home price in-dex time series johans test, found that there exists cointegration relationship between two varia-bles,the new city real estate market prices out of a line on the secondary market have clearguide. Therefore, the real estate market regulation aiming at the first -tier cities and the＂housing stock＂ should take the second - hand housing market as the main direction, startingwith the sale price and influencing factors of new houses. At the same time, in different cities,we should adhere to the city＇ s policies, reflect the policy differentiation, promote the reformof the real estate supply side, and promote the return of housing properties.

The Effects of Infrastructure Projects on House Prices and Rents:Evidence from the HS2 Extension Cancellation in the UK

This paper uses the HS2 extension cancellation in November 2021 as a quasi-experiment to study its impact on house prices and rents in Leeds.Using a DiD approach on repeat sales and monthly rents,I compare property values near the HS2 station and proposed construction site before and after the announcement.Results show a 3.6%decrease in house prices and a 3.9%decline in rents near the station,while properties near the construction site experienced a 2.4%increase in prices and a 2.1%rise in rents.This is the first paper to analyse the HS2 cancellation effect using panel data methods.

The Virtual Repeat Sale Model for the House Price Index for New Building in China

By using the characteristics of the new building in China, this article constructs the virtual repeat sale method to produce virtual repeat data which is similar to the repeat sale model on the house price index. Case-Shiller procedure and OFHEO method are used to calculate the house price index for new building in China. A discussion is given and furthering models are needed to take advantage of the virtual repeat sale data.

Identifying Spatial Heterogeneity in the Effects of High-Tech Firm Density on Housing Prices:Evidence from Guangdong-Hong Kong-Macao Greater Bay Area,China

Innovation capitalization is a new concept in innovation geography research.Extant research on a city scale has proven that innovation is an important factor affecting housing prices and verified that innovation has a capitalization effect.However,few studies investigate the spatial heterogeneity of innovation capitalization.Thus,case verification at the urban agglomeration scale is needed.Therefore,this study proposes a theoretical framework for the spatial heterogeneity of innovation capitalization at the urban agglomeration scale.Examining the Guangdong-Hong Kong-Macao Greater Bay Area(GHMGBA),China as a case study,the study investigated the spatial heterogeneity of the influence of high-tech firms,representing innovation,on housing prices.This work verified the spatial heterogeneity of innovation capitalization.The study constructed a data set influencing housing prices,comprising 11 factors in 5 categories(high-tech firms,convenience of living facilities,built environment,the natural environment,and the fundamentals of the districts)for 419 subdistricts in the GHMGBA.On the global scale,the study finds that high-tech firms have a significant and positive influence on housing prices,with the housing price increasing by 0.0156%when high-tech firm density increases by 1%.Furthermore,a semi-geographically weighted regression(SGWR)analysis shows that the influence of high-tech firms on housing prices has spatial heterogeneity.The areas where high-tech firms have a significant and positive influence on housing prices are mainly in the GuangzhouFoshan metropolitan area,western Shenzhen-Dongguan,north-central Zhongshan-Nansha district,and Guangzhou—all areas with densely distributed high-tech firms.These results confirm the spatial heterogeneity of innovation capitalization and the need for further discussion of its scale and spatial limitations.The study offers implications for relevant GHMGBA administrative authorities for spatially differentiated development strategies and housing policies that consider the role of innovation in successful urban development.

House Price, Consumption Power and Gap of Demographic Urbanization in China

This paper investigates the gap of demographic urbanization arising from the difference between rural residents who have migrated to cities and those who have acquired urban citizenship in the process of China's urbanization. The skyrocketing house prices and insufficient household consumption power are key factors to the widening gap, which had reached 18% in 2013. In order to explore this issue, by creating the basic model and the model with interaction term, this paper has analyzed the relationship among house prices, consumption power and gap of urbanization using the data of 31 provinces between 1999 and 2013 in China. Empirical result indicates that: there is a positive correlation between the house prices and the gap of China's demographic urbanization. However, such a correlation is restrained by these rural migrants who rent houses in cities. For an increase of house price by 1%, the gap of urbanization will widen by 1.05%. Although rising urban consumption power of rural residents has increased the ratio of migration, the lagged growth of consumption power has led to a widening gap of urbanization. Therefore, the only way to effectively reduce the gap of demographic urbanization is to increase the consumption power of migrant population and optimize consumption structure.

Inner-City Neighbourhood Changes Predicted from House Prices in Windsor, Ontario, since the Early- or Mid-1980s

Changes in prices of homes are hypothesized as correlated with the times of their sale and resale and the attributes of their dwelling unit and neighbourhood and those of neighbouring homes. They may also be correlated with the occurrences of events inside the neighbourhoods caused by the activities of individuals and organizations outside the neighbourhoods, such as whether the local economy is in a recession or has a high unemployment rate. Calibrated hybrid housing price models predict precipitous decreases in house prices of approximately 2900 sold and resold homes in two inner-city neighbourhoods in Windsor, Ontario, during those events since 1981 or 1986. Overall modest predicted percentage increases in houses’ prices during more than 30 years therefore subsumed periods of inner-city neighbourhood deterioration in dispersed locations of unimproved and disimproved homes. Compensatory predictions however are of increasing prices for minorities of homes with improvements to several attributes of the dwelling unit and neighbourhood.

Analysis of Factors Influencing Second-hand Housing Prices in Beijing based on Hierarchical Linear Model

In recent years,housing prices have attracted widespread attention,and the fluctuation of housing prices is due to a combination of many factors.In addition to the characteristics of the house itself,the price of a house is also affected by other factors,such as the community in which the house is located.This article used Beijing’s 2017 second-hand housing transaction data (based on second-hand housing transaction records on Lianjia.com),introduced a hierarchical linear model,and employed Stata software to analyze from different levels.It is intended to find the correlation between housing prices and different levels of characteristics,so to pin down the factors that affect prices of the second-hand housing.

Prediction of Nanjing Second-Hand Housing Price Index Based on Markov Chain Model

Current situation of the second-hand housing market Relatively speaking,we don’t pay much attention to the second-hand housing market.Therefore,this article has certain practical significance to predict the second-hand housing prices index.In 2005,China began to pursue the reform of the real estate tax and the second-hand housing transaction must pay personal tax.In 2006,the central bank increased mortgage interest rate,the state administration of taxation introduced the business tax policy

Slower House Price Growth

Home prices in Chinese cities grew at a slower pace in Febru ary and are expected to remain stable, according to the China Index Academy, a property research institution.

Relationship between Housing Price and Land Price Based on Grey Relational Analysis

In recent Years, China＇s real estate market has been rapid developed, and real estate has become a hot spot of consumption and investment. In some large and medium-sized cities there has been a rapid rise in housing prices. The rapid rise in housing prices has led to difficulties in the purchase of houses in some cities and towns, and this phenomenon has aroused the attention and con- cern of all walks of life. Housing is the basic human life needs. Housing problem is not only an economic problem, but also a social problem. The relationship between house price and land price and the effective control of housing prices have become the focus of government and scholars. Thus, grey relational analysis is used to ana- lyze the relationship between housing prices and land prices, and the grey relational coefficients are calculated.

A GIS-based Spatial Analysis of Housing Price and Road Density in Proximity to Urban Lakes in Wuhan City, China

As one of the essential urban open spaces, lakes usually contribute immensely to the quality of residents′ daily lives. Different from hedonic approach employed in existing researches on urban open spaces in China, this paper integrates housing price surface with road density to analyze the spatial characteristics in proximity to urban lakes in Wuhan City, China. With the expansion of Wuhan City, urban lakes became polluted, they shrunk or even disappeared, leading to unfavorable conditions for sustainable development of the city. To better understand the spatial relationship between the city and lakes, we classify the urban lakes in Wuhan central area into ′lakes in the urban center′ and ′lakes in urban fringe′. Based on housing price surface we explore the spatial characteristics in proximity to different lakes and differences between the lakes. We also use Geographic Information System(GIS) tool to calculate road density as a supplementary indicator to reflect the accessibility in proximity to urban lakes. The results indicate that relative independence exists between different towns, and the spatial characteristics are different depending on scales and locations. In most of cases, the road density is lower where closer to the lakeshore while the housing price exhibits an opposite pattern. We conclude that city governments and urban planners should give more considerations to these spatial differences, somewhere should be better planned and protected as an important waterfront and somewhere the control of unreasonable real estate development nearby should be strengthened.

Hedonic price analysis of urban housing:An empirical research on Hangzhou,China

The hedonic price model is widely applied to study the urban housing market because of the heterogeneity of housing products. Literature indicated that the hedonic price theory mainly includes two parts: Lancaster’s partiality theory and Rosen’s characteristic market equilibrium analysis. This paper chose 18 characteristics as independent variables and set up a linear hedonic price model for Hangzhou City. The model was tested with 2473 housing samples and field survey data of 290 housing commu-nities. This research found that 14 out of 18 characteristics had significant influence on housing price. They were classified into 5 groups according to their impact degree.

Impact of Accessibility on Housing Prices in Dalian City of China Based on a Geographically Weighted Regression Model

This paper studies the relationship between accessibility and housing prices in Dalian by using an improved geographically weighted regression model and house prices, traffic, remote sensing images, etc. Multi-source data improves the accuracy of the spatial differentiation that reflects the impact of traffic accessibility on house prices. The results are as follows: first, the average house price is 12 436 yuan(RMB)/m^2, and reveals a declining trend from coastal areas to inland areas. The exception was Guilin Street, which demonstrates a local peak of house prices that decreases from the center of the street to its periphery. Second, the accessibility value is 33 minutes on average, excluding northern and eastern fringe areas, which was over 50 minutes. Third, the significant spatial correlation coefficient between accessibility and house prices is 0.423, and the coefficient increases in the southeastern direction. The strongest impact of accessibility on house prices is in the southeastern coast, and can be seen in the Lehua, Yingke, and Hushan communities, while the weakest impact is in the northwestern fringe, and can be seen in the Yingchengzi, Xixiaomo, and Daheishi community areas.

Impact of Urban Public Service Facilities on Distribution Pattern of Housing Price

The impact of different public service facilities is obtained by investigating the infl uence of public service facilities on distribution pattern of housing price in 25 cities.According to the survey results,public education service facilities have the highest weight and the greatest impact,which also refl ects the root of“school district housing fever”from the side.Public sports service facilities have the lowest score when compared with other options.This is not because public sports service facilities are not important,but is determined by actual situation of social development and actual living standard of residents in China.From the improvement and enhancement of urban public service facilities,the construction of public service facilities should be convenient for people’s education,health,culture and entertainment.

LAND SUPPLY AND HOUSING PRICE:THE CASE IN HONG KONG

In this study we examine the relationship between land supply and housing price, percentage of land premium in the total government revenue and housing price, with reference to Hong Kong from 1981 to 1994. To do this we employ the Granger causality method to test the underlying hypothesis whether Hong Kong Government adopt high land-price policy. We use the first difference of data to ensure the stationarity in time series with the help of augmented Dick-Fuller unit root test. The results of the paper suggest no strong evidence to support the view that the land control of the government has caused soaringly rising housing prices. The findings also apparently implicate that the government has the revenue-maximizing behavior which is consistent with efficient allocation of resources.

Duration Dependence in Housing Price Market: A Metro Level Test in United States

Duration dependence affects the dynamics of multi sate time to event outcomes. In this paper we are testing if a contraction or an expansion state for the housing price is duration dependent on previous states lengths. This test has implications for explaining the dynamics and the predictability of the housing prices in subsequent spells of contraction/expansion. The test is carried on using a discrete time duration model. This research shows that federal fund rate has strong effect on duration of both expansion and contraction. The analysis is also showing that while for both contraction and expansion spells we observe duration dependence, the risk of exiting from either spell at the beginning of the spell is practically flat for the first five to six years in the expansion spells and between seven and eight years in the contraction spells. After these periods the risk of exiting an expansion spell is increasing but in a non-monotone way, while for the contraction spell the risk of exiting the state is increasing in a monotone way, making the contraction periods easier to predict than the expansion periods.

Heterogeneous Responses of Chinese Cities' Housing Prices to Monetary Policies

This works examine the responses of housing prices to the monetary policies in various Chinese cities. Thirty-five large and medium sized Chinese cities are classified into six clusters applying the minimum variance clustering method according to the calculated correlation coefficients between the housing price indices of every two cities.Time difference correlation analysis is then employed to quantify the relations between the housing price indices of the six clusters and the monetary policies.It is suggested that the housing prices of various cities evolved at different paces and their responses to the monetary policies are heterogeneous,and local economic features are more important than geographic distances in determining the housing price trends.

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.

Responses of Housing Price under Different Directions of Population Change:Evidence from China's Rust Belt

Population growth has been widely regarded as an important driver of surging housing prices of urban China,while it is unclear as yet whether population shrinkage has an impact on housing prices that is symmetrical with that of population growth.This study,taking 35 sample cites in Northeast China,the typical rust belt with intensifying population shrinkage,as examples,provides an empirical assessment of the roles of population growth and shrinkage in changing housing prices by analyzing panel data,as well as a variety of other factors in related to housing price,during the period of 1999–2018.Findings indicate that although gap in housing prices was widening between population growing cities and population shrinking cities,the past two decades witnessed an obvious rise in housing prices of those sample cities to varying degree.Changes in population size did not have a statistically significant impact on housing prices volatility of sample cities,because population reduction did not lead to a decline in housing demand correspondingly and an increasing housing demand aroused by population growth was usually followed by a quicker and larger housing supply.The rising housing prices in sample cities was mainly driven by factors like changes in land cost,investment in real estate,GDP per capita and household number.However,this does not mean that the impact of population shrinkage on housing prices could be ignored.As population shrinkage intensifies,avoiding the rapid decline of house prices should be the focus of real estate regulation in some population shrinking cities of Northeast China.Our findings contribute a new form of asymmetric responses of housing price to population growth and shrinkage,and offer policy implications for real estate regulation of population shrinking cities in China’s rust belt.

A Study on Spatial Distribution of Commercial Housing Prices in Xiangtan City

ArcGIS technology is used to study the spatial pattern of housing prices in Xiangtan City,and it is found that the spatial pattern of housing prices shows primary and secondary two-center rings. In Hedong Jianshe Road and near Hexi Jijianying,there are primary and secondary polar nuclei,respectively; the secondary housing price area is located near the east-west and south-north trunk road in the urban area; there are significant regional differences in housing price changes( fastest reduction of prices in the Hedong main center-southwest direction; slow reduction of prices in the main center-northwest,southeast direction; slowest reduction of prices in the main center-northeast direction). In Hexi sub-center,except slow reduction of prices in the Xiangjiang River direction,the prices decline rapidly in other directions. The housing prices exhibit an obvious overall decreasing trend from primary and secondary centers to the suburbs,but there are also exceptions. On this basis,this paper analyzes the driving factors for spatial pattern of housing prices in Xiangtan City,and finds that the spatial pattern of housing prices is mainly influenced by commercial centers,residential environmental conditions,traffic conditions,and urban land layout differences.