大眾捷運交通系統對住宅區房地產價格的影響 ——以臺北市大眾捷運系統為例

The Effect of Mass Rapid Transit on Residential Area Property Value: Evidence from Taipei

黃龑(Yan Huang)

指導教授 ： 吳珮瑛

國立臺灣大學/生物資源暨農學院/農業經濟學研究所/碩士(2016年)

https://doi.org/10.6342/NTU201701245

摘要

大眾捷運交通系統不僅節省了捷運利用者的出行時間和經濟成本，而且也能夠減少道路交通的擁擠程度，極大方便居民出行。捷運的修建促進了社會經濟繁榮與發展，帶來了週邊顯著的房地產增值。過去的研究大多運用傳統特徵價格法分析大眾捷運交通系統對房地產價格的影響，由於房屋價格資料含有空間性和房價異質性，若檢定結果顯著，則應以空間迴歸模型取代最小平方法模型。另外，過去的研究缺乏在特徵價格法上建立充分的處理和分析。因此，為建立一個更準確的迴歸模型估計模式和流程，本文加入Box-Cox變數轉換選擇函數形式；模型中應用主成分分析，建立主成分迴歸，用主成分代替原始解釋變數，分析與特徵價格法應用的一致性；以及運用聚類分析，來進行市場細分，以確定合適的細分市場數目，依細分市場使用空間特徵價格法建立模型。
有鑒於此，本文使用了空間迴歸模型評估台北市大眾捷運交通系統對住宅區房地產價格的影響。從實證結果可知，整體而言，捷運對週邊房地產價值的影響範圍為0~1,500公尺，隨著距離的增加，對於房地產的增值效應逐漸減少。Box-Cox變數轉換驗證了對數線性模型函數形式在本文使用的有效性。主成分分析選擇兩個主成分，第一主成分代表房地產鄰里區位的影響因素；第二主成分代表房地產本身建築結構的影響因素。主成分迴歸模型為達到變數完全獨立不存在資訊交叉的優點，在模型的解釋能力上並沒有喪失太多。在本文中，應用主成分分析有效。聚類分析發現，臺北市房地產存在兩個細分市場，一群表示捷運沿線，在相同鄰里區位下，受房屋類型的影響房價顯著不同，這可能因為該地區不同房屋類型代表不同年代建成的建物類型或者建物類型的功能帶給居民的效用享受差別較大，表示該地區居民對不同房屋類型的偏好不同，也因此願意為不同類型的房屋願意支付顯著不同的房價；另一群表示捷運沿線，在相同鄰里區位下，不受房屋類型的影響，這可能因為該地區不同建屋類型帶給居民的功能效用比較一致，表示該地區居民對不同房屋類型的偏好基本相同，也因此只願意為不同類型的房屋願意支付差不多的的房價。整體市場使用特徵價格法結合空間落遲模型模型來進行估算的金額介於聚類分析中細分市場Cluster0估算金額和聚類分析中細分市場Cluster1估算金額之間；聚類分析中細分市場Cluster0估算金額相對高估，聚類分析中細分市場Cluster1估算金額相對低估。距離最近捷運站1,350公尺的房價總金額介於NT$20,208,307萬~ NT$21,443,887萬。若政府根據大眾捷運系統建設及周邊土地開發計劃申請與審查作業要點，將捷運周邊住宅區房地產創設回饋金額（距離最近捷運站1,350公尺），外部效益予以內部化為捷運建設經費，則可減輕政府財政補貼負擔。若課1個百分點的稅收，則可以得到NT$202,083萬~ NT$214,439萬的稅收收入用於支持捷運建設或相關都市公共建設。

關鍵字

特徵價格法 ； 空間回歸 ； Box-Cox轉換 ； 主成分分析 ； 聚類分析 ； 大眾捷運交通系統 ； 房地產價格

並列摘要

Mass Rapid Transit (MRT) helps commuters save time and cost and reduces traffic jams, benefiting citizens. Constructing MRT promotes social and economic prosperity and development and brings property appreciation in the regions nearby. Previous researchers mainly used hedonic price method (HPM) to analyze the impact of MRT to the housing price quantitatively. Due to the two features of housing price, spatial autocorrelation and spatial heterogeneity, using traditional HPM to estimate will lead to bias. In addition, previous studies put little emphasis on analyzing and choosing models. This study (1) uses Box-Cox to find and valid the best functional form of HPM; (2) applies principle component analysis (PCA) to establish regression and then tests the effectiveness of using PCA in modifying the HPM model; (3) uses cluster analysis to optimize the segmentation of the property market and builds HPM models accordingly. The purpose is to improve the accuracy of regression models and recommend a analysis pattern.
This study uses the spatial regression model to estimate the effect of MRT in Taipei on property values and conducts an empirical analysis on how to modify models. The results show that (1) generally, MRT brings property appreciation in the proximity ranging from 0 to 1500 meters. The further the region is, the less appreciation impact MRT brings;(2) Linear-log functional form is the best functional form; (3) Two principal components are selected in the regression. The First Principal Component represents he niche advantage of neighborhoods and the Second Principal Component represents the architectural structure. The impact of dummy variable is showcased in the First Principal Component. The Principal Component Analysis shows its strength on keeping variables independent and is still able to be used to explain the effect; (4) According to the results of cluster analysis, there are two market segments in Taipei. In the one segment, the housing price is significantly influenced by the property type, while in the other segment, the property type inserts little impact on the housing price.
(5) The property value estimated in the overall market through HPM is between the estimated value of the cluster 0 segment market and that of the cluster 1 segment market; On top of that, the value of the cluster 0 segment market is overestimated, while that of the cluster 1 segment market is underestimated. The total value of the property within 1,350 meters of MRT stations is between NT$ 202,083,070,000 to NT$ 214,438,880,000. If the government establishes a foundation by imposing tax on the surrounding residential real estate (within 1,350 meters of MRT stations), subsidies provided by the government to the MRT can be reduced significantly. By taxing 1 percent, NT$ 2,020,830,700 to NT$ 2,144,388,800 of tax revenue will be generated to support the construction and management of MRT or other infrastructure.

並列關鍵字

Hedonic Price Method ； Spatial Regression ； Box-Cox ； Principle Component Analysis, Cluster Analysis ； Mass Rapid Transit ； Property Value

參考文獻

洪得洋，1998。「捷運系統與道路寬度對房屋價格之影響」，國立政治大學碩士論文。

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