三亞市商品住房特征價格實證研究
本文選題:商品住房 + 住房價格; 參考:《華東理工大學(xué)》2017年碩士論文
【摘要】:商品住房因其異質(zhì)性,每套商品住房的特征都是不相同的,如商品住房所在的區(qū)位、小區(qū)內(nèi)環(huán)境、所在樓層、朝向、戶型等都具有明顯差異。使用特征價格模型對商品住房特征進(jìn)行研究,是國內(nèi)外學(xué)者的通行做法。國內(nèi)運(yùn)用特征價格模型進(jìn)行相關(guān)研究始于20世紀(jì)90年代,主要集中在研究房地產(chǎn)的價格指數(shù)、特征價格模型的發(fā)展和房地產(chǎn)定價方面。由于實證研究需要收集大量的房屋交易數(shù)據(jù),進(jìn)入21世紀(jì)才開始有一、二線城市房地產(chǎn)的特征價格模型的實證研究,對三、四線城市的實證研究則較少,且這些實證研究中不僅數(shù)據(jù)量較少,而且基本都是使用房屋在中介市場的掛牌數(shù)據(jù),不是新房銷售時的實際數(shù)據(jù)。本文以三亞市商品住房為研究對象,在闡述特征價格模型理論的基礎(chǔ)上,選取區(qū)位特征、建筑結(jié)構(gòu)和鄰里特征作為特征變量,構(gòu)建了三亞商品住房特征價格模型。使用44個新建商品住房小區(qū)的4611套新建商品住房網(wǎng)簽數(shù)據(jù),通過檢驗和分析對比線性函數(shù)模型、對數(shù)函數(shù)模型和半對數(shù)函數(shù)模型三種函數(shù)模型,最終選擇半對數(shù)函數(shù)形式來分析三亞市商品住房市場的特征價格。實證結(jié)果表明,影響三亞商品住房價格的特征變量有裝修程度、容積率、物業(yè)管理、停車位、房屋所在樓層、房屋建筑面積、房屋類型和生活設(shè)施配套共8個變量。其中,除容積率對商品住房價格是反向影響外,其他7個變量對商品住房價格有正向影響。其中,影響程度從大到小依次為生活設(shè)施、裝修程度、容積率、房屋類型、物業(yè)管理、停車位、所在樓層和面積。
[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.
【學(xué)位授予單位】:華東理工大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:F299.23
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