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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/96252


    Title: 桃園捷運綠線對區域房價影響之研究;A Study on the Impact of the Taoyuan Metro Green Line on Regional Property Prices
    Authors: 李兆興;Lee, Chao-Hsing
    Contributors: 產業經濟研究所在職專班
    Keywords: 特徵價格法;半對數迴歸;地理資訊系統;Hedonic pricing method;semi-logarithmic regression;QGIS
    Date: 2024-12-31
    Issue Date: 2025-04-09 17:29:25 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 本研究採用價格特徵模型,針對桃園捷運綠線對區域房屋價格進行實證研究。研究範圍以2013年至2018年間桃園捷運綠線沿線三行政區域包含:桃園區、八德區與蘆竹區。樣本來源係根據內政部不動產交易實價登錄數據資料,經整理後導入至 QGIS 地理資訊系統中,將數據資料中房屋地址與地號依各房屋交易樣本進行空間定位,確認樣本數據盡在研究範圍內。並且納入桃園捷運綠線沿線 21個車站之地理資訊後,將桃園捷運綠線車站方圓500公尺範圍內定義為影響區並對其區域內房價進行研究。
    研究結果顯示,半對數模型對於房價有相當高解釋能力,而房屋特徵變數實證結果大致符合本研究預期。桃園捷運綠線在2016年政策核定後,相較於核定之前對沿線三個行政區 (桃園區、八德區、蘆竹區) 房屋單價提高0.9%,其值顯著。然而,在各行政區的分區實證結果中顯示,隨著房屋屬性不同、地區發展的前後時期與程度、主要開發區域位置與移轉、地區人口分佈與活動範圍,以及捷運站點設立位置等因素相互影響之下,對房屋特徵都會產生不同的隱含價格影響。
    ;This study aims to understand the correlation and impact of property prices and the approval of the Taoyuan Metro Green Line policy before and after 2016 on the real estate market. The research covers three districts along the Taoyuan Metro Green Line from 2012 to 2023, including Taoyuan District, Bade District, and Luzhu District. The sample data is sourced from the actual real estate transactions provided by the Ministry of the Interior. Using QGIS to locate the house address and land number in the data according to each property transaction sample, to confirm that the sample data is concentrated in the research scope. In addition, the geographic data information incorporates from the 21 stations along the Taoyuan Metro Green Line and groups the samples by a radius of 500 meters from the station center. Then, through semi-logarithmic regression and characteristic price model to analyze the changing relationship and impact between the approval of metro policy on the Green Line and the transaction price of property.
    The results show that the semi-log linear model has a high explanatory ability for property prices, the empirical results of property characteristic variables are generally in line with the expectations of this study. The after-approval Green Line policy in 2016 had a significant positive effect on the overall property prices in three districts (Taoyuan District, Bade District, and Luzhu District),which increased by 0.9%. However, due to the mutual influence of properties on residential samples, regional development period and degree, location and transfer of major development areas, regional population distribution and activity area, and the location of Metro stations, each region will have different effects on property prices.
    Appears in Collections:[Executive Master of Industrial Economics] Electronic Thesis & Dissertation

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