Abstract:Given the rapidly developing processes in the housing market of China, the significant regional difference in housing prices has become a serious issue that requires a further understanding of the underlying mechanisms. Most of the extant regression models are standard global modeling techniques that do not take spatial non-stationarity into consideration, thereby making them unable to reflect the spatial nature of the data and introducing significant bias into the prediction results. In this study, the geographically weighted regression model (GWR) was applied to examine the local association between housing price and its potential determinants, which were selected in view of the housing supply and demand in 338 cities across mainland China. Non-stationary relationships were obtained, and such observation could be summarized as follows: (1) the associations between land price and housing price are all significant and positive yet having different magnitudes; (2) the relationship between supplied amount of residential land and housing price is not statistically significant for 272 of the 338 cities, thereby indicating that the adjustment of supplied land has a slight effect on housing price for most cities; and (3) the significance, direction, and magnitude of the relationships between the other three factors (i.e., urbanization rate, average wage of urban employees, proportion of renters) and housing price vary across the 338 cities. Based on these findings, this paper discusses some key issues relating to the spatial variations, combined with local economic conditions and suggests housing regulation policies that could facilitate the sustainable development of the Chinese housing market.

Destinations formulate their tourism development strategies based on a number of factors, including tourism spillover effects. Using data from 98 administrative cities in Eastern China from 2004 to 2012 and spatial modelling techniques, this study examines the spillover effect of attractions, including natural, cultural and man-made attractions. The spillover effect refers to the impact attractions in the regions surrounding a specific destination have on tourist arrivals at that destination. The results show that, although the spatial substitution effect exists among the same type of attractions in adjacent regions, the size of this effect is too low to counteract the positive spillover effect of attractions. This study advances research on spillover phenomena in the tourism field and supports the strategy of interregional tourism collaboration centred on attractions.

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The issue of air quality in China has gotten great attention worldwide. This study makes the first effort to investigate the impact of air pollution on China's inbound tourism, using panel data at city level and the technique of corrected least square dummy variable (CLSDV). This study demonstrates how air pollution in China adversely impacts inbound tourism demand as well as the lagged effect of air pollution. Furthermore, this study reveals that for cities with different degrees of air pollution, the impact differs. Accordingly, we provide suggestions for governments and tourism firms on how to respond to the air pollution concern of international tourists.

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