An Analysis of the Factors Impact Real Estate Price In Younghe District,New Taipei City –The Market of Foreclosed Houses
Date Issued
2011
Date
2011
Author(s)
Jhang, Jhih-Hong
Abstract
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.
Subjects
Younghe district
housing price
regression model
hedonic price method
SDGs
Type
thesis
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