Title

學校特徵與空間距離對周邊房價之影響分析-以台北市為例

Translated Titles

Analyzing the Effect of School Characteristics and Geographical Distance on Local Housing Price-The Case of Taipei City

DOI

10.6277/TER.2014.422.2

Authors

林忠樑(Chung-Liang Lin);林佳慧(Jia-Huey Lin)

Key Words

額滿學區 ; 特徵價格法 ; 傾向分數配對法 ; 房屋價格 ; full enrollment school district ; hedonic pricing method ; propensity score matching ; housing price

PublicationName

經濟論文叢刊

Volume or Term/Year and Month of Publication

42卷2期(2014 / 06 / 01)

Page #

215 - 271

Content Language

繁體中文

Chinese Abstract

本文主要在探討學校特徵與空間距離對周邊房價之影響,並進一步探討在不同空間距離下,學校特徵對房價之影響程度有何異同。根據2007年到2009年的內政部「房地產交易價格」與臺北市政府「不動產數位資料庫」之房屋交易資料,本文發現額滿學校學區對周邊房屋總價具有正向顯著的影響,房屋座落地點距離學校愈遠而其房屋交易價格愈高,但學校距離對交易房價之影響效果隨著距離學校愈遠而呈現遞減的現象;另外,我們發現捷運站的交通便利性為提升房價的重要因素。針對不同空間距離討論發現,學校特徵對房價之影響效果會隨著距離學校愈遠而呈現遞減的趨勢;而交通便利性對非額滿學區的房價提升有顯著的影響效果。為了降低文獻中的樣本選擇偏誤之可能性,本文應用傾向分數配對方法,以配對後的房屋樣本進行分析亦未出現相反的證據,位於額滿學區的房價是相對高於位於非額滿學區的房價。最後,在房屋座落在共同學區的交易資料當中,我們發現額滿學校與空間距離因素對房價之影響效果並不顯著,房屋本身的特徵為主要影響房價之決定因素。

English Abstract

This paper analyzes the effects of school characteristics and geographical distances on local housing prices, and further discusses these effects within different geographical areas. According to the housing price data from the years 2007 to 2009, merged together from the Department of Land Administration and Taipei Real-estate Database, we find that the housing price is higher if the house is located in a full enrollment school district and the magnitude of this effect is decreasing with geographical distance from the school. In addition, we also find that the distance from the house location to a Mass Rapid Transit (MRT) station plays an important role in increasing the local housing price. As for the analysis of the different geographical areas, the results also show that the magnitude of the effect of school characteristics on the housing price is decreasing with the distance from the house location to the school. We then find that the proximity to an MRT station raises the local housing price and the effect is only significant in the non-full enrollment school districts. Moreover, to reduce the sample selection bias, we use the Propensity Score Matching (PSM) method to analyze the impact of a full enrollment school district on the housing price by using the matching data and we do not find conflicting results. Finally, the empirical results suggest that the housing's own characteristics are the most important factors to affect the local housing price in multi-school districts.

Topic Category 社會科學 > 經濟學
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