公佈降雨淹水模擬地圖對淹水區與其鄰近地區住宅價格之影響

Impacts of the Announcement of the Rainfall-induced Flood Simulation Map on Flood Area and Neighborhood Housing Prices

李春長(Chung-Chang Lee) ； 俞錚(Zheng Yu) ； 梁志民(Chih-Min Liang)

《住宅學報》 29卷1期 (2020/06) Pp. 63-89

摘要

本研究探討公佈降雨淹水模擬圖對淹水區與其鄰近地區住宅價格之影響。我們使用實價登錄網站2014年10月到2017年7月的住宅價格資料和水利處公佈的降雨淹水模擬地圖，運用分量迴歸和空間分量迴歸，並結合差異中之差異法進行估計。在考慮空間自我相關的情況下，公佈降雨淹水模擬地圖後，位於淹水區內之住宅價格會下降約13.5%。進一步考慮公告效果對不同價位住宅的影響，公佈後且位於淹水區內，於低價位、中低價位、中價位、中高價位和高價位住宅價格分別會下降約17.0%、8.9%、11.6%、17.0%和19.3%。公佈後且位於淹水區之鄰近地區，於高價位住宅價格則會下降約5.4%。

關鍵字

差異中之差異法 ； 空間分量迴歸 ； 淹水地區 ； 淹水模擬地圖 ； 住宅價格

並列摘要

This study aims to examine the impact of releasing the rainfall-induced flood simulation map on housing prices in locations deemed to be flood areas and their neighboring areas. Quantile and spatial quantile regressions, as well as the difference-in-differences method, were utilized to analyze the data from a real housing price website that spanned the period from October 2014 to July 2017 and the rainfall-induced flood simulation map released by the Hydraulic Engineering Office. After taking into account spatial autocorrelation, the release of the rainfall-induced flood simulation map was found to have led to a decline of approximately 13.5% in the housing prices of locations in flood areas. A further examination of the announcement’s effects across different housing price ranges revealed that housing prices in the low, mid-low, mid, mid-high, and high price ranges of locations in flood areas fell by 17.0%, 8.9%, 11.6%, 17.0%, and 19.3%, respectively. The release of the rainfall-induced flood simulation map was found to have led to a decline of approximately 5.4% in the high price range of housing in locations neighboring flood areas.

並列關鍵字

difference-in-difference method ； spatial quantile regression ； flooded area ； the rainfall-induced flood simulation map ； housing prices

參考文獻

好房網2015 〈北市「淹水地圖」難推柯Ｐ憂影響房價〉(https://news.housefun.com.tw/news/article/196947108531.html)。HowFun News2015 “Rainfall-induced Flood Simulation Map in Taipei City Doesn’t Work Well, The Mayor Worries the Impacts of the House Prices,” (https://news.housefun.com.tw/news/article/196947108531.html).

李春長、梁志民與林豐文2017 〈捷運系統對鄰近住宅價格之影響—以差異中之差異法估計〉 《台灣土地研究》20(2)：31-58。Lcc, C. C., C. M. Liang & F. W. Lin2017 “The Impact of the Taipei Mass Rapid Transit System on Nearby Housing Prices: An Estimation Using the Difference-in-Difference Method,”Journal of Taiwan Land Research. 20(2): 31-58.

李春長、游淑滿與張維倫2012 〈公共設施、環境品質與不動產景氣對住宅價格影響之研究—兼論不動產景氣之調節效果〉 《住宅學報》21(1)：67-87。Lee, C. C., S. M. You & W. L. Chang2012 “The Influence of Public Facility, Environmental Quality, and Real Estate Business Cycle on the Housing Price-Real Estate Business Cycle as a Moderator,” Journal of Housing Studies. 21(1): 67-87.

洪鴻智2002 〈科技風險知覺與風險消費態度的決定：灰色訊息關聯分析之應用〉 《都市與計劃》29(4)：575-593。Hung, H. C. 2012 “The Determination of Technological Risk Perception and Risk Consumption: Using Grey Information Relation Approach,” Journal of City and Planning. 29(4): 575-593.

洪惠娟2016 《大眾捷運系統對鄰近住宅價格之影響—空間計量之應用》碩士論文，國立屏東大學。Hung, H. C. 2016 The Impact of Mass Rapid Transit System on Neighborhood Housing Prices: An Application of Spatial Econometrics, Master Thesis, National Pingtung University.