洪災對鄰近房價之影響-特徵價格模型實證分析

NCUIR > School of Management at National Central University > Graduate Institute of Industrial Economics > Electronic Thesis & Dissertation > Item 987654321/86231

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/86231

Title:	洪災對鄰近房價之影響-特徵價格模型實證分析
Authors:	吳欣諭;Wu, Sin-Yu
Contributors:	產業經濟研究所
Keywords:	洪水災害;房價;特徵價格法;地理資訊系統;分量迴歸;Flood disaster;Hedonic price method;QGIS;Quantile regression
Date:	2021-07-02
Issue Date:	2021-12-07 12:19:52 (UTC+8)
Publisher:	國立中央大學
Abstract:	本論文主要探討洪水災害是否對其鄰近地區之不動產價格造成影響，以及洪水災害是否對低價位與高價位的不動產價格有不同之影響。本研究將研究地區分為北部與南部地區兩大類，其中北部研究地區為台北市北投區、台北市大安區，新北市蘆洲區以及基隆河沿岸之部分區域；南部研究地區為台南市安南區、台南市北區、台南市仁德區以及高雄市楠梓區之部分區域。本研究之資料來源取自內政部不動產交易實價查詢服務網於104年1月1日至109年9月30日不動產買賣實價登錄資料，以及國家災害科技防救服務資料網提供之民國104年至108年歷史淹水災害位置，結合地理資訊系統(QGIS)以計算各區之淹水紀錄點個數並呈現不動產之位置以便於後續不動產與最近學校、公園、醫院及捷運站之最短距離測量。本研究使用半對數型態之特徵價格模型進行迴歸分析，探討房屋與鄰里特徵變數以及洪災虛擬變數對於不動產價格之影響，並進一步透過分量迴歸分析以探討洪災是否對低價位與高價位之不動產有不同影響，本研究所使用之對照組為淹水災害區外之鄰近地區房屋，實驗組為淹水災害區中之房屋。研究結果顯示，無論是北部或南部地區之房屋皆會受到淹水災害的影響，若房屋位於淹水災害範圍內，則房價會比災害區外的房價還低；而房屋與鄰里特徵變數之估計係數大多達10%顯著水準，並符合本研究之預期與房價為正向關係。在北部地區，淹水災害造成的負面影響於高價位之房屋中最明顯，估計房價會減少約9.08%；在南部地區，負面影響對於中、低、高價位之房屋上差異不大。;This study focuses on whether the flood disaster has an impact on the price of real estate in its neighboring areas, and whether the flood disaster has a differential effect between the lower and higher value of real estate. Our research divides the study area into two categories: the northern and southern areas in Taiwan. The northern area includes Beitou District, Da′an District of Taipei city, and Luzhou District of New Taipei city in addition to distinct areas along the Keelung River. The southern research area includes Annan District, North District, and Rende District of Tainan City, and Nanzi District of Kaohsiung City. The source of data is from the Department of Land Administration, M. O. I. Our study selected the housing transaction records from January 1, 2015 to September 30, 2020. In addition, NCDR provides the location of historical data of flooding disasters from 2015 to 2019. Furthermore, QGIS is used to calculate the number of flooding record points and check the location of real estate, so as to facilitate the follow-up measurement of the shortest distance between real estate and schools, parks, hospitals and MRT stations. This research uses semi logarithmic form of the hedonic price model to investigate the pricing effects of housing. We uses the OLS and quantile regression estimation method to analyze whether flood has different effects on low price and high price of real estate. We also adopt the similar difference-in-difference method which the control group is the houses outside the flood disaster area, and the experimental group is the houses located in the flood disaster area. The results show that the houses located in both the northern and the southern areas will be affected by flooding. If the house is located in the flood disaster area, the house price will be lower than those outside the disaster area. The estimated coefficients of all explanatory neighborhood characteristic variables are almost at the 10% significant level, which are consistent with the expectation of this study. In the northern region, the negative impact of flood disaster is most obvious among the higher value of houses. It is estimated that the housing price will be decreased by about 9.08%. In the southern region, the negative impact on the middle, low and high value of housing has little differences.
Appears in Collections:	[Graduate Institute of Industrial Economics] Electronic Thesis & Dissertation

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