The Spatial Dimension of House Prices

Authors

  • Yunlong Gong TU Delft, Faculty of Architecture and the Built Environment

DOI:

https://doi.org/10.7480/abe.2017.4.1747

Keywords:

Housing prices, Urban housing market,

Abstract

The economic reform in China, launched in the late 1970s, gradually promotes the free mobility of capital and labour between rural and urban areas, and between cities. The following housing market reform in the late 1990s thoroughly terminates the socialist allocation of housing and introduces market forces into the housing sector. Such institutional shifts have profound effects on the evolution of the Chinese interurban housing market. Yet, little is known about the spatial behaviour of house prices across cities in the post-reform era. How do the housing markets of different cities organise across space? What is the relationship between the house price dynamics of different cities? To answer these questions, this research performs economic and econometric analysis of the spatial dimension of the Chinese interurban housing market. In addition, this research also concerns the construction of a reliable house price index in the presence of spatial heterogeneity and dependence in the urban housing market of China. A reliable house price index is essential to the analysis of house price dynamic behaviour. However, owing to the data problem, this part is conducted based on the housing market of a Dutch city.

This research discovers the spatial regularities of house prices across Chinese prefecture cities in an economic common area and investigates the underlying formation process. It reveals an uneven distribution of house prices across cities, with those large and/or higher-tier cities and their neighbours having significantly higher house prices. Such an uneven pattern of house prices demonstrates the agglomeration spillovers in the interurban housing market. Two forms of spillovers are empirically examined. The first is the urban hierarchy distance effect, which is related to the position of a city in a hierarchical urban system. In general, the distance penalty of higher-tier urban centres is confirmed, that is, all else being equal, the further away a city is from the higher-tier city, the lower the house price. The second form of spillovers relates to a city’s position in a city network system, in which no hierarchical structure is imposed. In such a situation, the spillovers arise from the interaction with neighbouring cities and it is found that a city that has larger neighbours tends to have higher house prices. These two forms of spillovers are somewhat correlated with each other because a higher-tier city is always associated with a larger urban size.

It is argued that the spillovers in the interurban housing market work through two channels: the productivity and amenity channel. First, because of the economies of agglomeration, a location that has good access to large urban concentrations is likely to enjoy some productivity advantages and thus can bear higher house prices. Second, a location that is surrounded by large urban concentrations can easily get access to some unique amenities that need a large market potential to survive; households value such access and thus bid up the house price there. However, it seems that the role that the productivity channel plays is much more important than the role of the amenity channel.

In addition to the static distribution of house prices across space, this research also concerns the time series behaviour of house price dynamics across Chinese cities. Geography plays an important role in explaining the cross-city differences of house price dynamics. For the housing markets of major cities across the whole of China, the cluster analysis generally uncovers two relatively homogeneous groups, within which the house price growth series share a similar dynamic pattern. One cluster contains mainly the cities in the undeveloped central, western and northeast China, whereas the other is composed of the most important economic centres in eastern China. However, the spatial segregation of housing markets is more likely to occur in the most recent period. In the early period before 2010, the house price dynamics of cities are much more homogeneous.

The similarities and/or dissimilarities among house price dynamics of different cities indicate the complicated interrelationships between each of the markets. This research further examines various spatial interrelationships between the housing markets of an economic common area in south China. The spatial causal relationships between housing markets are first tested by the Granger causality test. The results reveal a complicated pattern, but it can be tentatively confirmed that house price changes in the developed eastern-central markets ‘cause’ the house price dynamics in the

less-developed western markets. Then a spatial-temporal model is built to depict the diffusion pattern of house prices between markets. In general, a shock given to the house price of a certain market gradually spreads to its neighbouring cities. However, the interurban housing market can hardly remain an equilibrium relationship in the long-run, that is, it tends to be divergent.

The last part of this research concerns the treatment of spatial effects in the hedonic house price model as well as its influence on the construction of hedonic imputation indexes, which measure the pure house price changes over time. It is argued that the value of a dwelling can be split into the value of the land and the value of the structure, and that the value of the location characteristics of a dwelling is capitalised into the price of the land. Thus, land prices can be expected to vary significantly across space. Indeed, the mixed geographically weighted regression framework adopted in this research, which allows the shadow price of structure to be constant across space and the implicit price of land to be property-based, is found to be superior to, in terms of model prediction, those models that restrict the spatial variation of land prices. Nevertheless, the Fisher imputation house price index based on the most sophisticated model is almost identical to those based on the simple specifications. The land and structure price indexes, on the other hand, are sensitive to the treatment of location in land prices.

This research underlines market forces in the operation of Chinese interurban housing markets in the post-reform era, and contributes to the understanding of spatial dimension of house prices, not only in China, but also in other market-oriented economies.

Author Biography

Yunlong Gong, TU Delft, Faculty of Architecture and the Built Environment

OTB Research for the Built Environment

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Published

2017-04-28

How to Cite

Gong, Y. (2017). The Spatial Dimension of House Prices. A+BE | Architecture and the Built Environment, 7(4), 1–186. https://doi.org/10.7480/abe.2017.4.1747