三亚市商品住房特征价格实证研究

发布时间：2018-06-07 03:05

本文选题：商品住房 + 住房价格　；参考：《华东理工大学》2017年硕士论文

【摘要】：商品住房因其异质性,每套商品住房的特征都是不相同的,如商品住房所在的区位、小区内环境、所在楼层、朝向、户型等都具有明显差异。使用特征价格模型对商品住房特征进行研究,是国内外学者的通行做法。国内运用特征价格模型进行相关研究始于20世纪90年代,主要集中在研究房地产的价格指数、特征价格模型的发展和房地产定价方面。由于实证研究需要收集大量的房屋交易数据,进入21世纪才开始有一、二线城市房地产的特征价格模型的实证研究,对三、四线城市的实证研究则较少,且这些实证研究中不仅数据量较少,而且基本都是使用房屋在中介市场的挂牌数据,不是新房销售时的实际数据。本文以三亚市商品住房为研究对象,在阐述特征价格模型理论的基础上,选取区位特征、建筑结构和邻里特征作为特征变量,构建了三亚商品住房特征价格模型。使用44个新建商品住房小区的4611套新建商品住房网签数据,通过检验和分析对比线性函数模型、对数函数模型和半对数函数模型三种函数模型,最终选择半对数函数形式来分析三亚市商品住房市场的特征价格。实证结果表明,影响三亚商品住房价格的特征变量有装修程度、容积率、物业管理、停车位、房屋所在楼层、房屋建筑面积、房屋类型和生活设施配套共8个变量。其中,除容积率对商品住房价格是反向影响外,其他7个变量对商品住房价格有正向影响。其中,影响程度从大到小依次为生活设施、装修程度、容积率、房屋类型、物业管理、停车位、所在楼层和面积。
[Abstract]:Because of its heterogeneity, the characteristics of each set of commodity housing are different, such as the location of the commodity housing, the environment in the community, the floor, the orientation, the household type and so on. It is a common practice for scholars at home and abroad to study the characteristics of commodity housing by using the feature price model. The research on the use of feature price model in China began in the 1990s, mainly focusing on the price index of real estate, the development of feature price model and the real estate pricing. Because the empirical research needs to collect a large amount of housing transaction data, in the 21st century, there began to be empirical research on the characteristic price model of real estate in the first and second tier cities, while the empirical research on the third and fourth tier cities is less. In these empirical studies, not only the amount of data is relatively small, but also the listing data of houses in the intermediary market, not the actual data when the new houses are sold. This paper takes the commodity housing in Sanya as the research object, on the basis of expounding the characteristic price model theory, selects the location characteristic, the building structure and the neighborhood characteristic as the characteristic variable, constructs the Sanya commodity housing characteristic price model. Using 4611 sets of new commodity housing net label data from 44 new commodity housing districts, three function models, namely linear function model, logarithmic function model and semi-logarithmic function model, are tested and analyzed. Finally, semi-logarithmic function is chosen to analyze the characteristic price of Sanya commodity housing market. The empirical results show that there are 8 variables affecting the housing price in Sanya, such as decoration degree, volume ratio, property management, parking space, housing floor, building area, housing type and living facilities. In addition to the negative impact of volume ratio on commodity housing prices, the other seven variables have a positive impact on commodity housing prices. Among them, the order of influence is living facilities, decoration degree, volume ratio, housing type, property management, parking space, floor and area.
【学位授予单位】：华东理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F299.23

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