明星國中學區與到校距離對房地產價格影響 -以臺北市大安區為例

Impact of " Star " Middle School Districts and Lenghth of School Commute on Real Estate Price: A Study of Taipei’s Da-an District

簡素錦(Su-Ching Chien)

指導教授 ： 唐代彪

國立臺灣大學/社會科學院/國家發展研究所/碩士(2014年)

https://doi.org/10.6342/NTU.2014.00412

摘要

本研究採特徵價格法探討明星學區與到校距離對房地產價格之影響，以2011年第二季至2012年第三季「內政部地政司全球資訊網-房地產交易價格簡訊」公布之臺北市大安區成交資料共397 筆作為實證研究樣本。而明星學校的認定方式，係以臺北市政府教育局所每年所公布之國中新生入學「額滿學校」，並將「第一額滿學校」及「第二額滿學校」定義為明星學區，而「非額滿學校」則為非明星學區。另到校距離係以Google Map 量測法逐筆量測房地產成交資料之座落所在地與學校之直線距離、步行距離、步行時間、搭乘大眾交通工具距離、搭乘大眾交通工具時間、自行開車距離及自行開車時間。
本文變數之選取，分為「環境控制變數」及「自變數」兩部分，環境控制變數為街廓數、路寬、臨街關係、用途類別、構造種類、屋齡、移轉樓層、土地使用分區、移轉土地面積、移轉房屋面積及捷運站等11項，上述環境控制變數，本研究不再進行研究。另自變數選取採1.距離因素，包括 (1)「到校直線距離」、(2)「到校步行距離」、(3)「到校步行時間」；2.學區因素「明星學區」共計4項，本研究架構採二階層回歸，第一階層先分析「環境控制變數」，第二階層再將明星學區因素分別與距離因素的三項自變數加入分析，另依變項為房地產總價與單價。綜上，透過多元線性迴歸分析（Multiple Linear Regression Analysis ），歸納出明星學區到校距離對房地產價格的影響程度。
實證結果顯示，明星學區屬性在各模型的估計係數均與假設相左，亦即臺北市大安區之明星學區對於房價並無正面之加乘效果。透過分析，恐因本研究樣本為臺北市大安區，其生活機能、交通建設、地理位置、人文素質皆冠全國，亦即臺北市大安區本身就是一個大明星區，故自變數明星學區在臺北市大安區並不適用。
另針對到校距離不同對房地產價格之影響，就成交總價而言，本研究結果估計如下：1.到校直線距離每增加1公尺，不動產總價約減少2萬元；2.到校步行距離每增加步行1公尺，不動產總價約減少1.83萬元；3.到校步行時間每增加步行 1分鐘，不動產總價約減少120萬元。另再就成交單價而言，本研究結果估計如下：1.到校直線距離每增加1公尺不動產，每坪單價價約減少400元；2.到校步行距離每增加步行1公尺，不動產每坪單價價約減少300元；3.到校步行時間每增加步行 1分鐘，不動產每坪單價價約減少2萬元。

關鍵字

明星國中學區 ； 到校距離 ； Google Map ； 特徵價格法、房地產價格

並列摘要

This study is to discuss how the length between "Star Middle School" and house impact the real estate price. The empirical research samples are 397 transactions from 2011 Q2 to 2012 Q3 in Da-an District of Taipei City according to the real estate transaction database website of Department of Land Administration, the Ministry of the Interior. The "Star Junior High Schools" are defined as "First-full Schools" and "Second-full Schools" declared by Department of Education, Taipei City Government according to the junior high school freshman registration situation, and the "Non-star Schools" are defined as "Non-full schools". The "Distance" is defined as the straight distance, walking distance, walking time, distance by public transport, time by public transport, distance by driving, and time by driving between the real estates and the schools, measuring by Google Map.
The variables of this study are divided to "environmental control variables" and "independent variables" in two parts. The environmental control variables include the numbers of street blocks, widths of the lane, street relationships, usage categories, structure types, ages, floors, land zones, land areas, house areas, and the distances to MRT station. The environmental control variables are not further studied. The independent variables include three distance factors, which are straight distance, walking distance, and walking time, and "Star Junior High School Districts".
The research framework adopted two hierarchical regressions. The first is to analyze "environmental control variables". The second is to analyze the "Star Junior High School Districts" with three distance factors. The dependent variables are the total amount and the unit price of real estate. In summary, through the Multiple Linear Regression Analysis, the analysis summed up the price effect of the distance between Star School Districts and the real estates.
The empirical results show that the coefficients of the Star School District are different to the assumptions, which means the Star School Districts in Daan District of Taipei City have no positive price effect. The reason might be that the life functions, transportation construction, location, humanistic quality in Daan District are all the best in the country. It means the Daan District is a big Star School District, so the independent variables do not apply in Daan District.
To the total amounts, the effect of distance factors are estimated as follows: 1) the straight distance increases 1 meter, the total amount reduces about NT$20,000; 2) the walking distance increases 1 meter, the total amount reduces about NT$18,300; 3) the walking time increases 1 minute, the total amount reduces about NT$1.2 million. To the unit price, the effect of distance factors are estimated as follows: 1) the straight distance increases 1 meter, the price per ping reduces about NT$400; 2) the walking distance increases 1 meter, the price per ping reduces about NT$300; 3) the walking time increases 1 minute, the price per ping reduces about NT$20,000.

並列關鍵字

Star Middle School Districts ； Lenghth of School Commute ； Google Map ； Hedonic price method ； Housing Price

參考文獻

彭建文;蔡怡純,2012.12,"住宅負擔能力與住宅自有率之長期關係-追蹤資料共整

楊宗憲;蘇倖慧,2011.12,「迎毗設施與鄰避設施對住宅價格影響之研究」,《住宅

林祖嘉、馬毓駿（2007/12），「特徵方程式大量估價法在臺灣房地產市場之應用」，《住宅學報》，16（2），pp.1-22。

林左裕（2005）《房地產投資管理》，臺北：智勝文化事業有限公司。林素菁（2004）<臺北市國中小明星學區邊際願意支付之估計>，《住宅學報》13（1）：15-34。

李泳龍；黃宗誠；戴政安；李善將，2009/09。「醫學中心對鄰近住宅環境影響之研究」，『建築與規劃學報』。10卷2期,P75-93。