房屋交易價格之鄰近效應分析-以台北市為例

Abstract

本研究主要探討台北市的房價是否受到鄰近效應的影響，採用政府最新公布的不動產實價登錄資料，以房屋交易點作為分析單位，利用傳統迴歸和空間分析方法找出影響房價的因素並欲證實有鄰近效應的存在。 經過資料探索可以發現影響房價的因素可以分成三大類，分別是房屋本身條件、地理環境特徵以及鄰近效應。其中本研究中將房屋本身條件以及地理環境特徵因子作為控制變數，主要探討鄰近效應變數對於房價的影響。 研究結果指出，由傳統迴歸分析有空間自相關的問題產生，因此利用空間迴歸分析解決空間聚集的問題，並由空間迴歸檢定得知有鄰近效應的存在。

The research is going to discuss about if the housing price is affected by neighborhood in Taipei city. To use the traditional and spatial analysis to look for the factors which affect housing price and also prove that there is the neighborhood effect. By exploring the data, we can find out that there are three kinds of factors that affect housing price. They are housing properties, geographical features and neighborhood effect respectively. By controlling the housing properties and geographical features factors to prove that housing price is affected by neighborhood effect factors. The result points out that there is the spatial autocorrelation when using traditional regression to analyze. We can use the spatial regression to eliminate the cluster also prove that there is the neighborhood effect.