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 communities. 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.

Most existing studies empirically investigated the impact of rail transit on housing prices using the traditional hedonic price model, which is based on ordinary least squares (OLS). This method can estimate only the average implicit prices of housing characteristics and may ignore possible heterogeneous impacts of rail transit at different housing price levels. As a useful supplement to OLS regression, quantile regression can measure how implicit prices of explanatory variables vary across different price levels, thereby providing a comprehensive picture of the relationship between housing characteristics and prices. By using Hangzhou, China as an example, this study adopts the traditional hedonic price model and quantile regression model to investigate the capitalization effect of a new subway line on housing prices. Empirical results suggest the significant impacts of accessibility to subway stations. The average housing price within 2 km of the station is 2.1% to 6.1% higher than those outside. We also find that the impacts of the subway differ significantly across the distribution of housing prices, wherein the absolute value of estimated coefficients increased from 0.023 for the 15th quantile to 0.086 for the 95th quantile. The subway opening strengthens the capitalization effect of traffic accessibility. The absolute value of price elasticity increases from 0.044 to 0.053, and the range of influence is expanded from 1500 m to 2000 m.

Urban agglomerations (UAs) have become the urbanized “growth poles”, especially against the background of increasing population flow to cities. The spatial structure of UAs has been deemed the essential factor affecting regional function and sustainable development. Although there have been many meaningful studies on spatial structure changes in China, a systematically comparative work of UAs is still absent. Under this context, this paper examines the changing process of spatial structure in 20 Chinese UAs from monocentric to polycentric during the years 1992–2012 by using the night-time light data—an alternative to census data—and explores the major driving forces underlying the evolution. Our empirical results suggest that there is an obvious polycentric tendency of UAs, the spatial distribution pattern of which is not apparent. Panel regression models reveal that the economic level, the population size, the foreign direct investment (FDI), the human capital, and the transport infrastructure play significant positive roles in shaping the polycentric changing process, while the growth of the government expenditure does the opposite. Moreover, transport infrastructure and FDI are positively associated with polycentric spatial structure in mature UAs; on the contrary, they are negatively associated with it in the emerging UAs. Our study results have important policy implications for rapid Chinese urbanization—the policy whereby “China’s future urbanization development model is to limit the agglomeration of large cities while focusing on developing small and medium-sized cities” may be more efficient in mature UAs.

There are few studies on the externalities of shopping malls affecting the housing market. This study aims to discuss two issues: (1) What is the intensity of the impact of a shopping mall? (2) When does the external influence of a shopping mall begin to reveal itself? The West Intime Shopping Mall in Hangzhou offers a unique situation to research the questions. By dividing the study area into nine blocks, using hedonic price theory, and the price gradient approach with housing price data from 2011 to 2015, we found that in the space dimension, the mall exerted a significantly positive effect on the housing prices of nearby blocks. With the increase in distance from the mall, the positive effect decreased. There were more significantly positive effects in blocks far away from the city center. In the time dimension, the effects of West Intime did not reveal themselves until the mall had started to operate and gradually matured over time, implying that the mall did not have the obvious expected impact on housing prices before the mall had begun operating.

Rent-price ratio is a key indicator reflecting the health of the real estate market. However, this ratio varies in different periods and different areas of China. To understand the changes of the rent-price ratio, it is important to identify what factors impact it. With a simultaneous equation model and panel data from 30 cities in China during 2008–2013, this paper investigates the influential factors of housing price and housing rent, respectively, and then identifies the different influential factors of the rent-price ratio among various tiers of cities. Hausman test verifies that housing price and housing rent have an endogenous relationship. At 10% significance, eight and five exogenous variables exert significant impacts on housing price and housing rent, respectively. At the national level, price expectation has been observed to have the strongest impact on the rent-price ratio. At the city level, except gross domestic product (GDP) and price expectation, eight other factors have been observed to have different impacts on the rent-price ratio in different cities.

Land value appreciation in the urbanization process has triggered market speculation. The Land Bank System strengthens local governments’ ability to control land supply and distribution rights. Local governments are considered close stakeholders. Under the pressure of guaranteeing economic growth and promotion, local governments have increased their dependence on land finances. It is important for investors to understand the local governments’ behaviors, and draw up business strategies. This study aims to examine the influencing factors and formation mechanism of local government land hoarding. The research hypothesis was tested by collating provincial-level panel data of China from 2004 to 2015 and using dynamic panel data estimated by the Generalized Method of Moments (GMM). A significant positive correlation was found between residential land price and land hoarding area by local governments. Land speculation in the eastern region is also more pronounced than that in central and western regions. In addition, empirical studies have found a correlation between the degree of government intervention and local government land hoarding behavior. The higher the degree of government intervention, the less land sold through bid invitation, auction, and listing, which are linked to the corresponding hoarding land area.