scholarly journals Impact Factors of Spatial Differentiation of Housing Prices in China's Cities

Author(s):  
Yang Wang ◽  
Lixia Jin ◽  
Hong'ou Zhang ◽  
Changjian Wang ◽  
Kangmin Wu
Author(s):  
Emil Drápela

Since the 1990s, there has been an increase in interregional differences in housing prices in Czechia. These differences largely depend on the size and economic strength of the municipality or regional centre, but there exist also differences between regions. The article uses the indicator of housing construction intensity (HCI) for the twenty-two-year period 1997-2018 per 1 km2, which is processed at the level of municipalities using spatial autocorrelation (Anselin Local Moran's I) and hotspot analysis (Getis-Ord Gi*), and presented in GIS. By comparing the results of both methods it was found that the interregional differences in the popularity of the Czech regions are significantly influenced by their distance to the main economic centres. On the contrary, the hypothesis that some regions with a worse environment, a higher share of the socially weak population and a low supply of above-average jobs will be the cause of the negative push effect has not been confirmed. In discussion, the current situation is compared with Richard Florida's concept of “New Urban Crisis”, to which arrival in Czechia it indirectly points to, although the initial conditions in Czechia are significantly different than in the US.


2019 ◽  
Vol 11 (9) ◽  
pp. 2627 ◽  
Author(s):  
Chunhui Liu ◽  
Weixuan Song

Launched in 1998, the market-oriented reform of urban housing has given urban housing the dual attributes of residence and investment, and led to the rapid growth of housing prices as well as the intensification of its spatial differentiation within cities. However, the spatial patterns of the differentiation and its mechanism as well as socio-spatial effects are rarely touched. This paper studies 3963 urban residential districts in central Nanjing and explores the socio-spatial differentiation pattern and process of the urban housing prices and its growth in Nanjing based on the sample data of housing transactions over 30 quarters during the period of 2009–2017. The paper concludes that, by splitting the research duration into phases of six quarters each, the average housing prices in Nanjing alternates between “rapid growth” and “relatively stable” phases. At the same time, this paper finds that the spatial heterogeneity of housing prices in the city has been enhanced constantly, and the price gap in different types of residential housing has been clearly widened. In combination with the price level, location characteristics and architectural attributes of residential districts, this paper has categorized housing in Nanjing into nine typical types in a comprehensive manner. Based on the differences in their spatial attributes such as location, comfort and scarcity etc., different types of residences exhibit different pricing and price-to-rent ratio growth models. Based on those findings, we discussed the mechanism of the socio-spatial differentiation of housing prices in Nanjing from the housing reform and strategies of urban renewal and expansion. Beyond that, we discussed the role of urban housing consumption in the process of (re)production of urban classes, and its negative effects on urban young people, rural immigrants and other disadvantaged families. At the end of the paper, the policy suggestion about the supply-side reform of the housing market to promote socio-spatial equity and sustainable development is also presented.


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Song Xu ◽  
Zhen Zhang

The multiscale geographic weighted regression (MGWR) model obtains different influence scales of various variables better than the classical geographic weighted regression (GWR) model. This paper studies the price characteristics of second-hand residential transactions in Binhu New District taking advantage of the hedonic price model and MGWR model and draws the following conclusions. (1) There are obvious spatial positive correlation and spatial heterogeneity in the price of second-hand housing in Binhu New District. (2) The number of bedrooms, area, age of the house, and the distance to the nearest school have small effect on the scale, so they have strong spatial heterogeneity. The decoration status and floor are global scale variables, and their spatial heterogeneity is weak. (3) The number of bedrooms, orientation, decoration status, floor, and building structure all positively affect house prices, while area, house age, the distance to the nearest subway station, and the distance to the nearest school negatively affect house prices. Among all factors, the distance to the nearest school is the most important factor affecting house prices, followed by the number of bedrooms and then followed by the distance to the nearest subway station and area, while the orientation, floor, building structure, and decoration conditions have less impact, and the house age has the weakest impact.


2015 ◽  
Vol 25 (9) ◽  
pp. 1122-1136 ◽  
Author(s):  
Yang Wang ◽  
Lingling Zhao ◽  
Leszek Sobkowiak ◽  
Xingliang Guan ◽  
Shaojian Wang

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Radosław Cellmer ◽  
Aneta Cichulska ◽  
Mirosław Bełej

The aim of this study is to identify the factors that significantly determine the regional spatial differentiation of housing prices as well as housing market activity in Poland. The present research makes the assumption that average housing prices and market activity (number of transactions) are regionally shaped by economic, social, infrastructural and environmental conditions which can be described as a set of diagnostic features ascribed to a given area, constituting a statistical unit. Furthermore, it is assumed that individual effects may appear, being tied to the idiosyncrasies and significance of the given area. The time horizon of the research is 2008-2018. Based on data sourced from the Central Statistical Office a panel data was prepared for each of 380 Polish districts (poviats). Next, parameters were estimated for a single-factor panel model, as well as a two-factor model in which the constant term is different for different time periods and different units. This resulted in a model encompassing both average price determinants, and individual effects which reflect certain regularities of their spatial distribution. Moreover, the research will result in a set of cartograms made with Geographic Information System tools, depicting the random effects resulting from estimates of panel models using the Nerlove and Swamy-Arora transformations.


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