Sociospatial Differentiation in Urban China: Evidence from Shanghai's Real Estate Markets

2002 ◽  
Vol 34 (9) ◽  
pp. 1591-1615 ◽  
Author(s):  
Fulong Wu
Keyword(s):  
Real Estate ◽  
Urban Space ◽  
Spatial Data ◽  
Demographic Data ◽  
Housing Prices ◽  
Spatial Differentiation ◽  
Real Estate Market ◽  
Urban China ◽  
Commercial Development ◽  
Price Distribution

Market-oriented economic reform has led to an increase in social stratification in urban China. The reform of state-owned enterprises has meant that millions of workers have been ‘laid-off’, while the emergence of a private sector is creating thousands of ‘new rich’. Little is known about the spatial implications of the reform. The huge contrast between commercially developed housing estates and dilapidated inner-city areas is easily seen. However, there is a lack of systematic understanding of the extent to which urban space is differentiated in postreform China. The main obstacle to this understanding is the lack of small-area demographic data. Moreover, spatial data at a high resolution often remain confidential and hence underutilised. The author uses data from Shanghai's real estate market to examine the spatial differentiation of housing prices, so as to shed light on the transformation of urban space. The pattern identified by the analysis of price distribution and the contribution of the environment to property price is remarkably similar to the mental images of ‘upper end’ and ‘lower end’ that are commonly used in Shanghai dialect. Based on this research, three implications are suggested. First, the foremost impact of housing commodification is the revitalisation of the presocialist spatial division, because the socialist transformation of the built environment is never complete. Second, further sociospatial differentiation brought about by commercial development will be built upon the continuation of urban fabric. Third, privatisation of real estate itself becomes a source of sociospatial differentiation, because through the real estate market households are able to capitalise properties that were not distributed equally during the socialist period.

scholarly journals EPC Labels and Building Features: Spatial Implications over Housing Prices

2021 ◽  
Vol 13 (5) ◽  
pp. 2838
Author(s):  
Alice Barreca ◽  
Elena Fregonara ◽  
Diana Rolando
Keyword(s):  
Real Estate ◽  
Spatial Data ◽  
Housing Stock ◽  
Housing Prices ◽  
Energy Performance ◽  
Ordinary Least Squares ◽  
Real Estate Market ◽  
Hedonic Price ◽  
Spatial Error ◽  
The Impact

The influence of building or dwelling energy performance on the real estate market dynamics and pricing processes is deeply explored, due to the fact that energy efficiency improvement is one of the fundamental reasons for retrofitting the existing housing stock. Nevertheless, the joint effect produced by the building energy performance and the architectural, typological, and physical-technical attributes seems poorly studied. Thus, the aim of this work is to investigate the influence of both energy performance and diverse features on property prices, by performing spatial analyses on a sample of housing properties listed on Turin’s real estate market and on different sub-samples. In particular, Exploratory Spatial Data Analyses (ESDA) statistics, standard hedonic price models (Ordinary Least Squares—OLS) and Spatial Error Models (SEM) are firstly applied on the whole data sample, and then on three different sub-samples: two territorial clusters and a sub-sample representative of the most energy inefficient buildings constructed between 1946 and 1990. Results demonstrate that Energy Performance Certificate (EPC) labels are gaining power in influencing price variations, contrary to the empirical evidence that emerged in some previous studies. Furthermore, the presence of the spatial effects reveals that the impact of energy attributes changes in different sub-markets and thus has to be spatially analysed.

What drives housing prices, rent and new construction in China

2017 ◽  
Vol 10 (5) ◽  
pp. 662-686
Author(s):  
Dimitrios Staikos ◽  
Wenjun Xue
Keyword(s):  
Real Estate ◽  
Empirical Test ◽  
Housing Prices ◽  
Panel Cointegration ◽  
Real Estate Market ◽  
Estimation Methods ◽  
Content Type ◽  
New Construction ◽  
Using Data ◽  
First Time

Purpose With this paper, the authors aim to investigate the drivers behind three of the most important aspects of the Chinese real estate market, housing prices, housing rent and new construction. At the same time, the authors perform a comprehensive empirical test of the popular 4-quadrant model by Wheaton and DiPasquale. Design/methodology/approach In this paper, the authors utilize panel cointegration estimation methods and data from 35 Chinese metropolitan areas. Findings The results indicate that the 4-quadrant model is well suited to explain the determinants of housing prices. However, the same is not true regarding housing rent and new construction suggesting a more complex theoretical framework may be required for a well-rounded explanation of real estate markets. Originality/value It is the first time that panel data are used to estimate rent and new construction for China. Also, it is the first time a comprehensive test of the Wheaton and DiPasquale 4-quadrant model is performed using data from China.

scholarly journals Teoretyczne i metodyczne aspekty wyznaczania indeksów cen na rynku mieszkaniowym

2018 ◽  
Author(s):  
Radosław Trojanek
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Estate Market ◽  
Secondary Market ◽  
Property Right ◽  
Sources Of Information ◽  
Single Family ◽  
Starting Point ◽  
Price Indexes

In the book, an attempt was made to catalogue knowledge concerning the importance of research into the dynamics of housing prices for social and economic development. The analysis of the experience of countries with well-developed real estate markets in the aspect of building price indexes was carried out. Based on original databases of asking and transaction prices, price indexes were built, which were then subjected to numerous resistance tests. The aims of these research tasks were as follows: 1) to examine the quality of offers for sale as a source of information about changes in the real estate market, 2) to find out whether the repeat sales method can be used for building price indexes and to critically assess this method in terms of the stability of the obtained results, 3) to analyze hedonic methods and indicate the preferred one in terms of the ratio of the quality of results to how time-consuming and cost-intensive it is to build such indexes, 4) to establish the importance of methods and sources of information for building price indexes in different time horizons, 5) to identify how important it is for the fluctuation of price indexes if the cooperative property right to a flat is not taken into account. In order to perform the research tasks and accomplish the goals scopes of the work were defined. The subject followed the aim of the study and refers to prices in the secondary housing market, encompassing both the property right and cooperative property right to a flat or house. The broad scope concerns the discussion in the general part, being narrowed down to the secondary market of flats located in multi-family and single-family buildings. The time scope covers the years 2000-2015, which is connected to the range of empirical studies carried out. They focused both on actual transactions and on offers of flats for sale. On this basis, we built databases which served as the starting point for further analyses. The study involved transactions and offers in the area of Poznan.

scholarly journals Street Names through Sociological Lenses. Part II: Constructionism and Utilitarianism

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mihai Stelian Rusu
Keyword(s):  
Social Change ◽  
Real Estate ◽  
Urban Space ◽  
Social Constructionism ◽  
Place Branding ◽  
Real Estate Market ◽  
Previous Issue ◽  
The Real Estate ◽  
The Real Estate Market ◽  
The City

AbstractAs toponymic means of inscribing urban space, street names have been addressed mainly by human geographers, who have articulated the field of critical place-name studies. In this paper, I continue the endeavor started in the previous issue published in Social Change Review of reading street names through sociological lenses. Whereas in the first part of this two-part contribution the analysis was made from functionalist and conflictualist perspectives, this second and final part employs social constructionism and the utilitarian theoretical tradition in making sociological sense of street nomenclatures. First, conceiving of street names as forming discursively constructed linguistic landscapes, the paper shows how urban namescapes – the “city-text” – are written, erased, and rewritten to reflect the shifting political powers. Second, the paper examines the neoliberal processes of place branding and toponymic commodification by which street names are turned into sought-after urban commodities with transactional value on the real estate market. The paper concludes by inviting sociologists to join the conversation on street names, which should become an important topic of sociological reflection.

scholarly journals Did the COVID-19 Pandemic Crisis Affect Housing Prices Evenly in the U.S.?

2021 ◽  
Vol 13 (21) ◽  
pp. 12277
Author(s):  
Xinba Li ◽  
Chuanrong Zhang
Keyword(s):  
Real Estate ◽  
Spatial Patterns ◽  
Price Change ◽  
Housing Prices ◽  
Housing Price ◽  
Real Estate Market ◽  
Moran’S I ◽  
Moran's I ◽  
Price Changes ◽  
The U.S

While it is well-known that housing prices generally increased in the United States (U.S.) during the COVID-19 pandemic crisis, to the best of our knowledge, there has been no research conducted to understand the spatial patterns and heterogeneity of housing price changes in the U.S. real estate market during the crisis. There has been less attention on the consequences of this pandemic, in terms of the spatial distribution of housing price changes in the U.S. The objective of this study was to explore the spatial patterns and heterogeneous distribution of housing price change rates across different areas of the U.S. real estate market during the COVID-19 pandemic. We calculated the global Moran’s I, Anselin’s local Moran’s I, and Getis-Ord’s statistics of the housing price change rates in 2856 U.S. counties. The following two major findings were obtained: (1) The influence of the COVID-19 pandemic crisis on housing price change varied across space in the U.S. The patterns not only differed from metropolitan areas to rural areas, but also varied from one metropolitan area to another. (2) It seems that COVID-19 made Americans more cautious about buying property in densely populated urban downtowns that had higher levels of virus infection; therefore, it was found that during the COVID-19 pandemic year of 2020–2021, the housing price hot spots were typically located in more affordable suburbs, smaller cities, and areas away from high-cost, high-density urban downtowns. This study may be helpful for understanding the relationship between the COVID-19 pandemic and the real estate market, as well as human behaviors in response to the pandemic.

scholarly journals COVID-19 Infects Real Estate Markets: Short and Mid-Run Effects on Housing Prices in Campania Region (Italy)

2020 ◽  
Vol 9 (7) ◽  
pp. 114 ◽  
Author(s):  
Vincenzo Del Giudice ◽  
Pierfrancesco De Paola ◽  
Francesco Paolo Del Giudice
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Estate Market ◽  
Campania Region ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Short Run ◽  
Predator Model ◽  
Real Estate Prices

The COVID-19 (also called “SARS-CoV-2”) pandemic is causing a dramatic reduction in consumption, with a further drop in prices and a decrease in workers’ per capita income. To this will be added an increase in unemployment, which will further depress consumption. The real estate market, as for other productive and commercial sectors, in the short and mid-run, will not tend to move independently from the context of the aforementioned economic variables. The effect of pandemics or health emergencies on housing markets is an unexplored topic in international literature. For this reason, firstly, the few specific studies found are reported and, by analogy, studies on the effects of terrorism attacks and natural disasters on real estate prices are examined too. Subsequently, beginning from the real estate dynamics and economic indicators of the Campania region before the COVID-19 emergency, the current COVID-19 scenario is defined (focusing on unemployment, personal and household income, real estate judicial execution, real estate dynamics). Finally, a real estate pricing model is developed, evaluating the short and mid-run COVID-19 effects on housing prices. To predict possible changes in the mid-run of real estate judicial execution and real estate dynamics, the economic model of Lotka–Volterra (also known as the “prey–predator” model) was applied. Results of the model indicate a housing prices drop of 4.16% in the short-run and 6.49% in the mid-run (late 2020–early 2021).

scholarly journals Modeling the Real Estate Prices in Olsztyn under Instability Conditions

2012 ◽  
Vol 11 (1) ◽  
pp. 61-72 ◽  
Author(s):  
Mirosław Bełej ◽  
Sławomir Kulesza
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Intrinsic Property ◽  
Small Variation ◽  
Smooth Curve ◽  
Real Estate Market ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
The Stability

Abstract The paper deals with the description of the issues related to the dynamics of the real estate market in terms of sharp, unexpected changes in the housing prices which have been observed in the last decade in many European countries due to some macroeconomic circumstances. When such perturbations appear, the real estate market is said to be structurally unstable, since even a small variation in the control parameters might result in a large, structural change in the state of the whole system. The essential problem addressed in the paper is the need to define and discriminate between the intervals of stable and unstable real estate market development with special attention paid to the latter. The research aims at modeling hardly explored field of discontinuous changes in the real estate market in order to reveal the bifurcation edge. Assuming that the periods of sudden price changes reflect an intrinsic property of the real estate market, it is shown that the evolution path draws for most of the time a smooth curve onto the stability area of the equilibrium surface, and only briefly penetrates into the instability area to hop to another equilibrium state.

An Institutional Countermeasure to China's High Urban Housing Prices

2013 ◽  
Vol 448-453 ◽  
pp. 4075-4078
Author(s):  
Jin Zhang
Keyword(s):  
Civil Rights ◽  
Real Estate ◽  
Institutional Economics ◽  
Housing Prices ◽  
Urban Housing ◽  
Real Estate Market ◽  
System Level ◽  
The Real Estate ◽  
Economic Phenomenon ◽  
The Real Estate Market

The economic phenomenon of high urban housing prices in our country reflects asymmetry of rights and interests among government, real estate developers and buyers in essence, and behind this economic phenomenon imbedded financial crisis as well as political and social crisis. Regarding academic thought on the causes of high housing prices in the real estate market such as the theories of supply anddemand, cost, the system, and power imbalance between interest groups, this thesis proceeds institutional analysis, from the perspective of institutional economics, discusses the institutional causes of the persistent existence of four factors theories in the angle of vacancy of civil rights in the supply process of institution and rules, and puts forward policy suggestions of increasing effective supplies of institution in the system level.

scholarly journals Homeownership Rate and Other House Price Determinants Impacts on New House Prices in Colombia

2020 ◽  
pp. 35-50
Author(s):  
Hector Botello-Peñaloza
Keyword(s):  
Real Estate ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Real Estate Market ◽  
The Real Estate ◽  
Homeownership Rate ◽  
Colombian Government ◽  
Price Determinants ◽  
Price Instability

Homeownership remains a preferred form of tenancy in different parts of the world. The attractions of security, stability, investment potential and a sense of pride outweigh the fear of price instability. For this reason, the Colombian government has encouraged in recent years, various demand policies that have sought to promote the increase in the number of homeowners. However, these ideas could have a severe impact on prices in the real estate market. Therefore, this study seeks to examine the effect of homeownership rate on new house prices in an emerging country with low real estate ownership, credit restrictions and average per capita income. The study uses panel data model to examine the influence of housing tenancy and other variables on the variation of housing prices in Colombia. Data were obtained from various sources including the Central Bank of Colombia, Financial Superintendence of Colombia, and National Administrative Department of Statistics of Colombia. The results show that homeownership rates have a positive effect on the price of new homes, which supports the hypothesis of the research. The population growth of the cities is the factor that is most relevant when explaining the price variations.

scholarly journals Prediction of China’s Housing Price Based on a Novel Grey Seasonal Model

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Dayin Li ◽  
Lianyi Liu ◽  
Haitao Lv
Keyword(s):  
Real Estate ◽  
Prediction Models ◽  
Housing Prices ◽  
Market Price ◽  
Housing Price ◽  
Real Estate Market ◽  
Accurate Prediction ◽  
Price Changes ◽  
New Information ◽  
Seasonal Model

The fluctuation of real estate prices has an important impact on China's economic development. Accurate prediction of real estate market price changes has become the focus of scholars. The existing prediction methods not only have great limitations on the input variables but also have many deficiencies in the nonlinear prediction. In the process of real estate market price forecasting, the priority of data and the seasonal fluctuation of housing price are important influencing factors, which are not taken into account in the traditional model. In order to overcome these problems, a novel grey seasonal model is proposed to predict housing prices in China. The main method is to introduce seasonal factor decomposition into the new information priority grey prediction model. Two practical examples are used to test the performance of the new information priority grey seasonal model. The results show that compared with the existing prediction models, this method has better applicability and provides more accurate prediction results. Therefore, the proposed model can be a simple and effective tool for housing price prediction. At the same time, according to the prediction results, this paper analyzes the causes of housing price changes and puts forward targeted suggestions.

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