Empirical Research On Determinants Of Interurban Residential Land Price Differences

Since reform and opening up, China's urban land-use system has undergone major changes, going through the "three-no" to the "three-one" change. With the continuous development of urban land markets, and the market value of land assets reflected rapidly, the land market has become an important force of allocating land resources. Meanwhile, under land price marketplace decision mechanism effect, the residential land price is displaying the huge difference among the cities. Generally speaking, the municipal residential land price is influenced by many factors, which form different comprehensive effects through different combination in a city's geographical area. In other words, the deciding factor of the housing land price is a comprehensive indicator system. Then, what kind of indicator system influences the residential land price, and which factors causes the interurban difference of housing land price, these questions are precisely which this research have paid close attention to.This article, profiting from the domestic and foreign scholar's related research results, and unifying the reality of our country land market, takes advantage of the principles of supply chain process management and constructs an indicator system of the factors which determine the interurban residential land price differences. Meanwhile, on the basis of supply and determine theory, this paper constructs municipal residential land price variance determining factor model, selects much related resources about the urban residential land market, economic, society and regional situation of 34 cities around the country in 2007, and conducts a empirical study by taking use of Ordinary Least Squares method and Stepwise method.The achievement made in this thesis mainly reflects in two aspects:Firstly, this thesis has made a systematic combing of the determinants which form the interurban residential land price difference and has conducted a set of index systems. Taking advantage of the principles of supply chain process management, this thesis has put land purchase, store, transition and consumption in a supply chain process. Through analyzing the behavior of related participators in this supply chain process, this thesis find that the interurban residential land price difference determinants distribute in two levels: one is the micro-market level, including land store, transition and consumption three stages; the other one is the macroeconomic environment which contains policy, economic, social and regional four aspects. Above this analysis, the determinants contribute to land resources, land supplier behavior constraints, land demand behavior as well as policy, economic, social and geographical situation.Secondly, on the basis of supply and determine theory, this paper builds a municipal residential land price variance determining factor model and makes a regression analysis. After regression analyzing, there are five variables determining the interurban residential land price difference, which contain the average gross domestic product, average paving path area, total freight traffic and passenger volume. In other words, consumer paying capacity, economic development condition and area position condition are the main reasons which contribute to the interurban housing land price difference.These conclusions have certain reference value for government regulating the residential land price, for the developer choosing a right city to invest and making a reasonable price decision, and also for the families choosing living cities.Currently, there is little domestic research on interurban housing land price differences. Under the condition that the residential land market is becoming mature, this thesis takes the year 2007 as the study target and makes a multiple regression analysis. However, owing to fewer samples and the samples scattering around the country, some variables can not be quantified and taken into consideration. Thus, the research results of this thesis still need to be examined. The future study could target at such aspects as variable choice, variable quantification and the reliability of sample data and make further optimization.