影響新北市永和區不動產價格因素分析-以法拍屋市場為例

An Analysis of the Factors Impact Real Estate Price In Younghe District,New Taipei City –The Market of Foreclosed Houses

張志弘(Jhih-Hong Jhang)

指導教授 ： 孫立群

國立臺灣大學/生物資源暨農學院/農業經濟學研究所/碩士(2011年)

https://doi.org/10.6342/NTU.2011.00445

摘要

隨著近年來永和地區的重大公共設施逐一完工、生活機能、交通設施越來越完善，永和地區的不動產價格近年來呈高成長幅度。本研究的主要內容為探究影響永和地區不動產成交價格之因素並建立分析永和地區不動產成交價格變動之迴歸模型。研究目的為建立準確度較高之區域價格預測模型，降低買賣雙方在交易時所面臨的不確定性，並藉由瞭解影響永和地區不動產價格之因素對分區建設規劃提出建議。
本研究以敘述統計以及特徵價格法建立分析的基礎，由實證的成果可知民國91年至99年的成交筆數排名前三的路段分別為中正路、中山路一段、竹林路；主要路段的平均成交單價前三名分別為環河東路、永貞路、安樂路。自身因素中達到5%顯著水準的變數有屋齡、所在樓層、總樓層、是否為公寓、建築型態、建築型態、總坪數、公共設施坪數、增建坪數、地坪等十項變數。其中，建築型態為影響每坪單價最為明顯的變數。鄰里環境因素達5%顯著水準的變數有距最近捷運設施距離、距最近變電所距離，每接近最近捷運設施一百公尺則每坪單價增加2.4%，每接近最近變電所一百公尺對每坪單價的影響為減少2.3%。法拍因素達5%顯著影響的變數為拍定標次與投標人次，法拍屋每增加一拍定標次，每坪成交單價下降7.57%，若投標人次每增加一人次則每坪成交單價上漲0.3%。總體因素達5%顯著影響的變數為景氣燈號分數，景氣對策信號每增加一分則每坪單價增加0.87%。

關鍵字

永和地區 ； 不動產成交價格 ； 迴歸模型 ； 特徵價格法

並列摘要

The housing price in Younghe district increases rapidly, because of the completion of important public facilities which make life better. The main contents of the research is to explore the factor impacting the housing price in Younghe district and establish the regression model to analyze the change of housing price in Younghe district. The objective is to establish high accuracy of the regional price forecasting model, in order to reduce the uncertainty in the transaction and make recommendations to zoning.
The research method bases on descriptive statistics and the hedonic price method. The empirical results show that the top three highest volumes are Zhongzheng road, Zhongshan Road, Section 1 and Zhulin road. The top three average transaction prices are Huanhe Eastern Road, Yongzhen Road and Anle Road.
The building factors reached 5% significance level are house age, floor, building height, architectural style, whether the top floor, the total number of floor, public Facilities, number of additional floor and land area. The construction type impacts unit price per ping most obviously. The environmental factors reached 5% significance level are distance from the nearest MRT facilities and distance from the nearest substation. Unit price increases of 2.4% per ping as every hundred meters close to the nearest MRT facilities. Unit price decreases of 2.3% per ping as every hundred meters close to the nearest substation. The foreclosed factors reached 5% significance level are auction frequency and the number of bidders. Unit price decreases of 7.57% per ping as the frequency of auction increase. Unit price increases of 0.3% per ping as the number of bidders increase. The Macroeconomic factors reached 5% significance level is economic signals. Unit price increases of 0.87% per ping as economic signals increase.

並列關鍵字

Younghe district ； housing price ； regression model ； hedonic price method

參考文獻

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