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題名 天氣變化對房價的影響—以台灣各縣市為例
The Influence of Weather Changes on Housing Price-Evidence from Counties and Cities in Taiwan
作者 劉素芬
Liou, Su-Fen
貢獻者 黃智聰
Huang, Jr-Tsung
劉素芬
Liou, Su-Fen
關鍵詞 天氣
房價
空間計量經濟學
Weather
Housing Price
Spatial Econometrics
日期 2023
上傳時間 1-Sep-2023 14:45:04 (UTC+8)
摘要 人類生活與環境密不可分,環境與生活更是息息相關,居住環境受到人類與自然因素交互作用影響,時至今日面臨環境、社會以及經濟快速變遷下,房市發展因素日益複雜,近幾年的氣候環境變遷,世界各國紛紛提倡淨零碳排,間接影響生活消費習慣,而購屋亦為消費之一環,所需資金龐大,非屬一般性消費財,故民眾在購屋時會格外謹慎,除考量房屋本身條件、家庭結構或大環境等因素外,亦同時考慮周遭居住環境及品質。
台灣因海島氣候及其特殊地理位置,加以北迴歸線穿越,使島內各區天氣型態容有差異,無論是雨量、日照、溫度或濕度等主要天氣指標均顯有不同,如將該等指標按WHO就居住環境定義中有關舒適性(comfort)之理論基礎觀察,天氣指標之變化程度倘可歸屬於環境特質,將間接影響民眾生活及居住品質,故理論上對於房價有應有一定程度之影響。
本研究係選取2011年至2021年間天氣變化對房價的影響,透過Moran’s I檢定結果數據顯示,房價分布具有正向空間自我相關,存在空間聚集效應。並採取空間自我迴歸模型固定效果,經實證研究結果顯示平均溫度、每戶家庭可支配所得、老年人口比率、一般生育率及都市計畫已建闢公園比率與房價產生顯著的正向影響;而最高與最低氣溫差、雨量、前一年空屋率、刑案發生率、教育科學文化支出比率、每萬人口病床數及道路里程密度則對房價無顯著影響。
Human life and the environment are inextricably linked, and the environment is closely related to human life. The living environment is influenced by the interaction of both human and natural factors. In today`s rapidly changing environment, society, and economy, the development of the housing market is becoming increasingly complex. In recent years, with the climate and environmental changes, countries around the world have advocated for net zero carbon emissions, which has indirectly affected consumer habits and the purchase of homes is also part of consumption. Moreover, as it requires a huge amount of funding and is not considered a general consumer product, people are particularly cautious when buying a house. In addition to considering factors such as the condition of the house itself, family structure, or the overall environment, they also take into account the quality of the surrounding living environment.
Due to Taiwan`s island climate and unique geographical location, as well as the fact that it is crossed by the Tropic of Cancer, there are differences in the weather patterns in various regions of the island. The main weather indicators, such as rainfall, sunshine, temperature, and humidity, all show significant differences. If we observe these indicators based on the theoretical foundation of comfort in the WHO`s definition of living environment, the degree of variation in weather indicators can be attributed to environmental characteristics, indirectly affecting people`s lives and living quality. Therefore, in theory, it should have a certain degree of impact on housing prices.
This study selected the period from 2011 to 2021 to examine the impact of weather changes on housing prices. The data showed positive spatial autocorrelation and spatial clustering effects in the housing price distribution, as revealed by the Moran`s I test. A fixed-effects spatial autoregressive model was adopted, and the empirical results showed that average temperature, disposable income per household, proportion of elderly population, general fertility rate, and the ratio of urban park area already developed had a significant positive impact on housing prices. On the other hand, temperature difference between the highest and lowest points, rainfall, vacancy rate for the previous year, crime rate, ratio of education, science and cultural expenditure, hospital beds per 10,000 population, and road density had no significant impact on housing prices.
參考文獻 壹、中文部分
朱芳妮、陳明吉(2018),從行為經濟學看台灣不動產市場:羅伯特.席勒教授來台演講之省思與啟示。住宅學報,27(2),111-128。
吳森田(1994),所得、貨幣與房價-近二十年台北地區的觀察。住宅學報,2,49-65。
呂哲源、江穎慧、張金鶚(2019),土壤液化潛勢區公布對房價之影響。都市與計劃,46(1),33-59。
李泓見、張金鶚、花敬群(2006),台北都會區不同住宅類型價差之研究。臺灣土地研究,9(1),63-87。
李春長、游淑滿、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。
李春長、俞錚、梁志民(2020),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。住宅學報,29(1),63-89。
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林祖嘉、林素菁(1993),台灣地區環境品質與公共設施對房價與房租影響之分析。住宅學報,1,21-45。
林素菁(2004),台北市國中小明星學區邊際願意支付之估計。住宅學報13(1),15-34。
林忠樑、林佳慧(2014),學校特徵與空間距離對周邊房價之影響分析-以台北市為例。經濟論文叢刊,42(2),215-271。
花敬群(2001),自有率、空屋數量與住宅市場調整。住宅學報,10(2),127-137。
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胡海豐(2015),以條件評價法估算土地使用變更的外部性對房地產價格之影響程度與作用範圍。住宅學報,24(2),1-26。
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陳隆麒、李文雄(1998),臺灣地區房價、股價、利率互動關係之研究-聯立方程模型與向量自我迴歸模型之應用。中國財務學刊, 5(4),51-71。
國家災害防救科技中心(2017),臺灣氣候科學變遷報告2017-物理現象與機制。台北:國家災害防救科技中心。
彭建文(2000),台灣房地產景氣循環之研究-生產時間落差、宣告效果、總體經濟之影響。國立政治大學地政學系博士論文。
彭建文、蔡怡純(2017),人口結構變遷對房價影響分析。經濟論文叢刊,45(1),163-192。
彭建文(2005),自有住宅市場均衡空屋率分析-以台北縣市爲例。臺灣土地研究,8(1),1-21。
彭逸瑋(2013),綠建築對不動產價格之影響。國立政治大學地政研究所碩士論文。
黃元杰(2017),犯罪地圖政策公布對房價之探討-以台北市為例。國立臺灣大學生物資源暨農學院農業經濟學系碩士論文。
楊宗憲、蘇倖慧(2011),迎毗設施與鄰避設施對住宅價格影響之研究。住宅學報,20(2),61-80。
解鴻年、胡太山、邵澤恩(2000),鄰里公園對鄰近不動產影響之研究-以新竹市為例。建築規劃學報,1(3),258-271。
詹為巽、鄭可風、林俊成(2021),都市公園綠地對於房價之影響-以新北市八二三紀念公園為例。林業研究專訊,28(2),66-69。
劉志宏、 張卉婷(2015),房地產價格與生育行為之相關性研究:台灣實證資料之檢視。公共事務評論,15(2),21-43。
劉富容、游璿達、黃孝雲、劉正夫(2019),利用政府開放資料探討影響台北市房價之主要房屋特性及周邊設施影響因子, 數據分析,14 (5),1-26。
鄧志松、唐代彪、杜震華(2007)。中國大陸GIS空間資料庫的建置暨空間探索分析。臺北市:國立台灣大學社會科學院中國大陸研究中心。

貳、英文部分
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Bin, Okmyung, and Craig E. Landry (2013), “Changes in Implicit Flood Risk Premiums: Empirical Evidence from the Housing Market” Journal of Environmental Economics and Management, 65(3), 361-376.
Baldauf, Markus, Lorenzo Garlappi, Constantine Yannelis, and Jose Scheinkman(2020), “Does Climate Change Affect Real Estate Prices? Only If You Believe In It” The Review of Financial Studies, 33(3), 1256-1295.
Chiarazzo, Vincenza, Pierluigi Coppola, Luigi Dell’Olio, Angel Ibeas, and Michele Ottomanelli (2014), “The Effects of Environmental Quality on Residential Choice Location.” Procedia-Social and Behavioral Sciences, 162, 178-187.
Cao, Melanie, and Jason Wei (2005), “Stock Market Returns: A Note on Temperature Anomaly.” Journal of Banking & Finance, 29(6), 1559-1573.
Goodman, Allen C.(1978), “Hedonic Prices, Price Indices and Housing Markets.” Journal of Urban Economics, 5, 471-484.
Gourley, Patrick (2020), “Curb Appeal: How Temporary Weather Patterns Affect House Prices.” The Annals of Regional Science, 67, 107-129.
Hanink, Dean M., Robert G. Cromley, and Avraham Y. Ebenstein (2012), “Spatial Variation in the Determinants of House Prices and Apartment Rents in China.” The Journal of RealEstate Finance and Economics, 45(2), 347-363.
Hu, Maggie Rong, Adrian D. Lee (2020), “Outshine to Outbid: Weather-Induced Sentiment and the Housing Market.” Management science, 66 (3), 1440-1472.
Kim, Kwang Sik, Sung Joong Park, and Young-Jun Kweon (2007), “Highway Traffic Noise Effects on Land Price in an Urban Area.” Transportation Research Part D, 12, 275-280.
Linden, Leigh, and Jonah E. Rockoff (2008), “Estimates of the Impact of Crime Risk on Property Values from Megan`s Laws.” The American economic review, 98(3), 1103-1127.
Lavaine, Emmanuelle (2019), “Environmental Risk and Differentiated Housing Values: Evidence from the North of France. ”Journal of Housing Economics, 44, 74-87.
Levin, Andrew, Chien-Fu Lin, and Chia-Shang J. Chu (2002), “Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties.” Journal of Econometrics, 108, 1-24.
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Moran, P.A.P. (1950), “ Notes on Continuous Stochastic Phenomena.” Biometrika, 7, 17-23.
Scott, Wentland, Bennie Waller, and Raymond Brastow (2014), “Estimating the Effect of Crime Risk on Property Values and Time on Market: Evidence from Megan’s Law in Virginia.” Real Estate Economics, 42(1), 223-251.
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Zoppi, Corrado, Michele Argiolas, and Sabrina Lai (2015), “ Factors Influencing the Value of Houses: Estimates for the City of Cagliari, Italy.” Land Use Policy, 42,367-380.
Zhang, Lei (2016), “Flood Hazards Impact on Neighborhood House Prices:_A Spatial Quantile Regression Analysis.”Regional Science and Urban Economics, 60, 12-19.

參、網路資料
內政部不動產資訊平台,112年2月27日,取自網址:https://pip.moi.gov.tw/V3/Default.aspx。
經濟部水利署電子報,112年4月22日,取自網址:
https://epaper.wra.gov.tw/Article_Detail.aspx?s=6877&n=30177。
中華民國統計資訊網,112年1月15日,取自網址:
https://nstatdb.dgbas.gov.tw/dgbasall/webMain.aspx?k=defjsp。
交通部中央氣象局,111年12月2日,取自網址:
https://www.cwb.gov.tw/V8/C/。
描述 碩士
國立政治大學
行政管理碩士學程
110921007
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110921007
資料類型 thesis
dc.contributor.advisor 黃智聰zh_TW
dc.contributor.advisor Huang, Jr-Tsungen_US
dc.contributor.author (Authors) 劉素芬zh_TW
dc.contributor.author (Authors) Liou, Su-Fenen_US
dc.creator (作者) 劉素芬zh_TW
dc.creator (作者) Liou, Su-Fenen_US
dc.date (日期) 2023en_US
dc.date.accessioned 1-Sep-2023 14:45:04 (UTC+8)-
dc.date.available 1-Sep-2023 14:45:04 (UTC+8)-
dc.date.issued (上傳時間) 1-Sep-2023 14:45:04 (UTC+8)-
dc.identifier (Other Identifiers) G0110921007en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/146847-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 行政管理碩士學程zh_TW
dc.description (描述) 110921007zh_TW
dc.description.abstract (摘要) 人類生活與環境密不可分,環境與生活更是息息相關,居住環境受到人類與自然因素交互作用影響,時至今日面臨環境、社會以及經濟快速變遷下,房市發展因素日益複雜,近幾年的氣候環境變遷,世界各國紛紛提倡淨零碳排,間接影響生活消費習慣,而購屋亦為消費之一環,所需資金龐大,非屬一般性消費財,故民眾在購屋時會格外謹慎,除考量房屋本身條件、家庭結構或大環境等因素外,亦同時考慮周遭居住環境及品質。
台灣因海島氣候及其特殊地理位置,加以北迴歸線穿越,使島內各區天氣型態容有差異,無論是雨量、日照、溫度或濕度等主要天氣指標均顯有不同,如將該等指標按WHO就居住環境定義中有關舒適性(comfort)之理論基礎觀察,天氣指標之變化程度倘可歸屬於環境特質,將間接影響民眾生活及居住品質,故理論上對於房價有應有一定程度之影響。
本研究係選取2011年至2021年間天氣變化對房價的影響,透過Moran’s I檢定結果數據顯示,房價分布具有正向空間自我相關,存在空間聚集效應。並採取空間自我迴歸模型固定效果,經實證研究結果顯示平均溫度、每戶家庭可支配所得、老年人口比率、一般生育率及都市計畫已建闢公園比率與房價產生顯著的正向影響;而最高與最低氣溫差、雨量、前一年空屋率、刑案發生率、教育科學文化支出比率、每萬人口病床數及道路里程密度則對房價無顯著影響。
zh_TW
dc.description.abstract (摘要) Human life and the environment are inextricably linked, and the environment is closely related to human life. The living environment is influenced by the interaction of both human and natural factors. In today`s rapidly changing environment, society, and economy, the development of the housing market is becoming increasingly complex. In recent years, with the climate and environmental changes, countries around the world have advocated for net zero carbon emissions, which has indirectly affected consumer habits and the purchase of homes is also part of consumption. Moreover, as it requires a huge amount of funding and is not considered a general consumer product, people are particularly cautious when buying a house. In addition to considering factors such as the condition of the house itself, family structure, or the overall environment, they also take into account the quality of the surrounding living environment.
Due to Taiwan`s island climate and unique geographical location, as well as the fact that it is crossed by the Tropic of Cancer, there are differences in the weather patterns in various regions of the island. The main weather indicators, such as rainfall, sunshine, temperature, and humidity, all show significant differences. If we observe these indicators based on the theoretical foundation of comfort in the WHO`s definition of living environment, the degree of variation in weather indicators can be attributed to environmental characteristics, indirectly affecting people`s lives and living quality. Therefore, in theory, it should have a certain degree of impact on housing prices.
This study selected the period from 2011 to 2021 to examine the impact of weather changes on housing prices. The data showed positive spatial autocorrelation and spatial clustering effects in the housing price distribution, as revealed by the Moran`s I test. A fixed-effects spatial autoregressive model was adopted, and the empirical results showed that average temperature, disposable income per household, proportion of elderly population, general fertility rate, and the ratio of urban park area already developed had a significant positive impact on housing prices. On the other hand, temperature difference between the highest and lowest points, rainfall, vacancy rate for the previous year, crime rate, ratio of education, science and cultural expenditure, hospital beds per 10,000 population, and road density had no significant impact on housing prices.
en_US
dc.description.tableofcontents 第一章 緒論 1
第一節 研究背景及動機 1
第二節 研究目的 4
第三節 研究架構及流程 5
第二章 文獻回顧 8
第一節 居住環境對房價產生影響之相關文獻 9
第二節 其他影響房價因素之相關文獻 22
第三章 台灣房價與天氣現況分析 27
第一節 台灣房價現況 27
第二節 天氣變化現況 38
第四章 研究方法 48
第一節 空間相關性檢定 48
第二節 共線性檢定 51
第三節 空間計量模型設定 52
第四節 實證模型與變數設定 54
第五節 研究範圍與限制 62
第五章 實證結果與分析 63
第一節 檢定結果 63
第二節 實證模型估計之確立及分析結果 68
第六章 結論與建議 72
第一節 結論 72
第二節 建議 74
參考文獻 77
zh_TW
dc.format.extent 1717212 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110921007en_US
dc.subject (關鍵詞) 天氣zh_TW
dc.subject (關鍵詞) 房價zh_TW
dc.subject (關鍵詞) 空間計量經濟學zh_TW
dc.subject (關鍵詞) Weatheren_US
dc.subject (關鍵詞) Housing Priceen_US
dc.subject (關鍵詞) Spatial Econometricsen_US
dc.title (題名) 天氣變化對房價的影響—以台灣各縣市為例zh_TW
dc.title (題名) The Influence of Weather Changes on Housing Price-Evidence from Counties and Cities in Taiwanen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 壹、中文部分
朱芳妮、陳明吉(2018),從行為經濟學看台灣不動產市場:羅伯特.席勒教授來台演講之省思與啟示。住宅學報,27(2),111-128。
吳森田(1994),所得、貨幣與房價-近二十年台北地區的觀察。住宅學報,2,49-65。
呂哲源、江穎慧、張金鶚(2019),土壤液化潛勢區公布對房價之影響。都市與計劃,46(1),33-59。
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參、網路資料
內政部不動產資訊平台,112年2月27日,取自網址:https://pip.moi.gov.tw/V3/Default.aspx。
經濟部水利署電子報,112年4月22日,取自網址:
https://epaper.wra.gov.tw/Article_Detail.aspx?s=6877&n=30177。
中華民國統計資訊網,112年1月15日,取自網址:
https://nstatdb.dgbas.gov.tw/dgbasall/webMain.aspx?k=defjsp。
交通部中央氣象局,111年12月2日,取自網址:
https://www.cwb.gov.tw/V8/C/。
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