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Skyrocketing housing prices in China's megacities have generated broad concerns. By integrating open data from Lianjia.com , Dianping.com , Mobike.com , and Baidu Map POI, we analyze spatial patterns of apartment prices and their association with local attributes in Shanghai. We find that Shanghai's residential market still has a monocentric structure because of the centralized distribution of public transport facilities and amenities. Hedonic models further confirm that structural attributes, accessibility, as well as public and private service amenities significantly shape the real estate market. These factors also are differentiated so as to form a pattern of concentric rings. In the inner-city and expanded inner-city areas, public service amenities such as parks, schools, hospitals, and banks, as well as private service amenities such as entertainment, shopping, and residential service facilities, boost housing prices. In the suburbs, better access to bike sharing, bus stops, and metro stations are the top preferences for apartment buyers. Our study also indicates that the Chinese government needs to make public and private services more accessible, not only spatially in urban peripheries and villages, but also institutionally to lower income families who cannot afford apartments in expensive neighborhoods. • The complexity of local factors of housing prices in Shanghai remains under-studied. • Shanghai's residential market is characterized by a monocentric structure. • Housing prices in Shanghai are heavily influenced by accessibility and amenity. • Public amenities such as metro stations, schools, and hospitals have an additional capitalization premium. • Better accessibility is the top preference for apartment buyers in the suburbs. • Residents in the inner-city area are willing to pay for better service amenities. [ABSTRACT FROM AUTHOR]

Negative amenities, such as air pollutions, have plagued many rapidly growing cities. However, researchers have not comprehensively examined their effects on housing values and on the local economy. These effects may be spatially auto-correlated with accessibility factors, differ in how they are dispersed over space and time, and have sizable localized effects. In this study, we use the assessed property value data and hedonic pricing models to examine consumers' underlying preferences for various amenities and accessibility factors in Salt Lake County, with a particular focus on air pollutions and forest coverage. Three models are used to address the problem of special and temporal heterogeneity. Results from ordinary least squares (OLS) regression show that single-family home values are affected not only by structural attributes, but also by urban amenities and accessibility factors such as air pollution, forest coverage, quality of public schools, and commuting cost. After controlling the covariates in spatial lag regression (SLR), we find that air pollutions and the lack of forest coverage have a significant and detrimental effect on housing values over time. Finally, results from geographically weighted regression (GWR) indicate that spatial heterogeneity is evident and that the forest coverage has more positive influences in the east side of Salt Lake County, while the negative effect of air pollutions is less pronounced on housing values in the southeast. However, air pollutions and forest cover matter irrespective of the method used. [ABSTRACT FROM AUTHOR]