What Drives Up Land Price in China?Evidence from Bidding Processes of Land Auctions in Beijing

The land price in big cities draws much attention and discussion for its skyrocketing appreciation.Most researches are from the macro perspective due to data restriction.This paper aims to investigate the critical factors in the price formation process of a land auction,using the listing auction micro bidding-level data in Beijing from 2013 to 2018.We construct a model for the relationship between quitting price and land,bidder's characteristics,housing market conditions and competitive intensity(including private and public signals),then we use OLS for identification.We find that competitive intensity increases the quitting price by causing competition and interaction between bidders.More importantly,we find evidence of cheating behavior in the land market.Results show that bidders have higher quitting prices when they are in a joint venture,and when a central SOE developer or a top 10 developer exist in the joint venture.We also find different behavior of developers in the short run and long run.Our research contributes to the literature of land auctions by analyzing the price formation process and developers'behavior.We also provide supporting evidence for the government to make adjustments of the auction system and identify the cheating developers.

UAV-based spatial pattern of three-dimensional green volume and its influencing factors in Lingang New City in Shanghai,China

Three-dimensional green volume(TDGV)reflects the quality and quantity of urban green space and its provision of ecosystem services;therefore,its spatial pattern and the underlying influential factors play important roles in urban planning and management.However,little is known about the factors contributing to the spatial pattern of TDGV.In this paper,TDGV and land use intensity(LUI)extracted from high spatial resolution(0.05 m)remotely sensed data acquired by an unmanned aerial vehicle(UAV),anthropogenic factors^(1))and natural factors^(2))were utilized to identify the spatial pattern of TDGV and the potential influencing factors in Lingang New City,a rapidly developed coastal town in Shanghai.The results showed that most of the TDGV was distributed in the western part of this new city and that its spatial variations were significantly axial.TDGV corresponded well with the chronologies of land formation,urban planning,and construction in the city.Generalized least squares(GLS)analysis of TDGV(grid cell size:100×100 m)and its influencing factors showed that the TDGV in this new city was significantly negatively correlated with both LUI and distance from roads and significantly positively correlated with land formation time and distance from water.Distance from buildings did not affect TDGV.Additionally,the degree of influence decreased in the following order:distance from water>land formation time>distance from roads>LUI.These results indicate that the spatial pattern of TDGV in this new town was mainly affected by natural factors(i.e.,the distance from water and land formation time)and that the artificial disturbances caused by rapid urbanization did not decrease the regional TDGV.The main factors shaping the spatial distribution of TDGV in this city were local natural factors.Our findings suggest that the improvement in local soil and water conditions should be emphasized in the construction of new cities in coastal areas to ensure the efficient provision of ecological services by urban green spaces.