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題名 鄰避設施與迎毗設施對農地價格之影響 －以台南市為例
The Impact of NIMBY and YIMBY Facilities on Farmland Prices： A Case Study of Tainan City作者 陳品諺
Chen, Pin-Yan貢獻者 林子欽
Lin, Tzu-Chin
陳品諺
Chen, Pin-Yan關鍵詞 特徴價格法
空間迴歸模型
農地價格
鄰避設施
迎毗設施
Hedonic Price Method
Spatial Regression Model
Farmland Price
Not-In-My-Back-Yard
Yes-In-My-Back-Yard日期 2024 上傳時間 4-Sep-2024 14:28:31 (UTC+8) 摘要 農地價格受到多方因素的影響，極端的氣候變化、國際貿易影響、現代飲食習慣改變等等皆是原因，其中一部分原因即是受到周邊設施的外部性影響，如同房價會因為汙水處理廠、垃圾掩埋場而降低，農地價格也同樣會因周邊設施的設立而改變。本研究透過農地價格的改變，定義各種設施為鄰避設施或是迎毗設施，當價格因周邊設施而降低時即為鄰避設施，反之則稱為迎毗設施。另一方面，設施之影響在不同地區可能會產生不同的效果，因此本研究透過農地交易價格之高中低劃分出三個分區，藉以觀察設施在各個地區的不同影響，設施包含：一般道路、河川或水利設施、農業產銷設施、綠能設施、工廠、農舍、畜牧設施、養殖漁業設施、農路、休閒農場、農會、國道等共12種設施。 本研究透過實價登錄之農地交易資料，結合農地流通中心、政府資料開放平台之農地周邊設施資料，以特徵價格模型、空間迴歸模型分析設施外部性對於農地價格之影響。結果表明，一般道路等交通運輸設施除了農路在低價分區中作為鄰避設施以外，其他交通運輸設施皆具有正面之影響，與直覺相符，畜牧設施、漁業設施、也做為鄰避設施存在；農會、農舍、農業設施等等也做為迎毗設施存在，然而與直覺不符的是工廠與綠能設施，工廠對於周邊農地價格具有正面的影響，不論在何種分區皆是；綠能設施則在高價分區中有正面的影響，可見得目前政策對於工廠取締以及綠能政策與農地政策之間的權衡必須更加嚴謹並審慎衡量。
Farmland prices are influenced by a wide range of factors, including extreme climate events, international trade, and evolving dietary habits. One significant factor is the external impact of surrounding facilities. Just as property values may decline near sewage treatment plants or landfills, farmland prices can also fluctuate based on nearby developments. This study categorizes such facilities as either "NIMBY" (Not In My Back Yard) or "YIMBY" (Yes In My Back Yard) based on their influence on farmland prices. When prices decrease due to nearby facilities, these are classified as NIMBY, if prices increase, they are considered YIMBY facilities. Furthermore, the price impact of these facilities can vary across different regions. To capture these differences, this study divides farmland prices into three categories—high, medium, and low—and examines the effects of facilities in each area. This study covers 12 types of facilities, including transportation facilities, rivers or water resource facilities, agricultural production, green energy installations, factories, farmhouses, livestock facilities, aquaculture sites, farm road system, recreational farms, farmers’ association, and highways. This study uses actual transaction data from the Transaction Price Registration, combined with information on nearby facilities from the Taiwan Agriculture Land Information Service and government open data platforms. This study also employs Hedonic Price Method and Spatial Regression Model analysis to assess the externalities of facilities on farmland prices. The results indicate that most of transportation infrastructures, such as roads, has a positive impact on farmland prices, except for farm road system in low-price zones, which are defined as NIMBY facilities. Livestock and aquaculture facilities are also classified as NIMBY. In contrast, farmers’ association, farmhouses, and agricultural facilities are defined as YIMBY facilities. Unexpectedly, factories have a positive impact on farmland prices regardless of the regions, while green energy facilities show a positive effect only in high-price areas. These results suggest that current policies on factory regulation and the balance between green energy initiatives and farmland management require more careful evaluation and adjustment.參考文獻 一、中文參考文獻 丁秀吟，林子欽，吳文傑，2023，「從使用價值之差別課稅觀點分析農地合理使用」，『規劃學報』，41(1)：16-34 于宗先，2004，「公共設施與規模經濟」，『經濟前瞻』，(95)：24-26 王欽傳，2015，「外部性影響因子與屬性框架對鄰避設施民眾接受度之影響」，國立中山大學公共事務管理研究所碩士論文：高雄 丘昌泰，2004，「公共設施中鄰避情結的成因與因應：以民營電廠為例」，『政治學報』，37：37-110 李永展，1996，「鄰避設施對社區環境品質之影響－以台北市三個垃圾焚化廠為例」，『國立政治大學學報』，(72)2：263-297 李永展，1997，「鄰避症候群之解析」，『都市與計劃』，24(1)：69-79 李永展，林啓賢，1998，「鄰避型公共設施之環境態度與更新接受意願之研究－以台北市為例」，『都市與計劃』，25(2)：133-153 李泳龍，黃宗誠，戴政安，李善將，2009，「醫學中心對鄰近住宅環境影響之研究」，『臺灣經濟預測與政策』，10(2)：75-90 吳怡葶，胡吳岳，2011，「波爾多產區葡萄酒特徵價格之研究」，『農業經濟叢刊』，28(2)：135-172 林祖嘉，馬毓駿，2007，「特徵方程式大量估價法在台灣不動產市場之應用」，『住宅學報』，16(2)：1-22 徐鳳嬌，2020，「污染農地對農地價格影響之分析」，臺灣大學生物資源暨農業學院農業經濟學系碩士論文：台北 陳奉瑤，楊依蓁，2007，「個別估價與大量估價之準確性分析」，『住宅學報』，16(2)：67-84 陳晏筑，林雅亭，劉千菱，吳佳洟，張雅嵐，林左裕，2022，「鄰避設施對鄰近房價的影響－以臺北市為例」，『土地問題研究季刊』，21(4)：32-53 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 廖咸興，張芳玲，1997，「不動產評價模式特徵價格法與逼近調整法之比較」，『住宅學報』，5：17-35 賴韋廷，陳文雄，劉鋼，2014，「蓋設超高壓輸電線的外部成本－以台電「南投－彰林」線路為例」，『臺灣經濟預測與政策』，45(1)：1-39 二、外文參考文獻 Brian Lee, Hung-Hao Chang, Szu-Yung Wang, 2021, “Can environmental disamenities increase land values? A case study of manufacturing factories on farmland”, Journal of Cleaner Production, 279(10) Edward J. Fark, 1982, “The Nimby Syndrome”, Alternatives: Perspectives on Society, Technology and Environment, 10(2/3)：47-50. Haixiao Huang, Gay Y. Miller, Bruce J. Sherrick, Miguel I. Gómez, 2006, “Factors Influencing ILLINOIS Farmland Values”, American Journal of Agricultural Economics, 88(2)：458-470 Hung-Hao Chang, Tzu-Chin Lin, 2023, “Solar farm policy and farmland price – A land zoning perspective”, Journal of Environmental Management, 344(15) John C. Bergstrom, Richard C. Ready, 2009, “What Have We Learned from Over 20 Years of Farmland Amenity Valuation Research in North America?”, Review of Agricultural Economics, 31(1)：21-49. Jae Su Lee, Ming-Han Li, 2009,“The impact of detention basin design on residential property value: Case studies using GIS in the hedonic price modeling”, Landscape and Urban Planning, 89(1)：7-16 Janak Joshi, Mohammad Ali, Robert P. Berrens, 2017, “Valuing farm access to irrigation in Nepal: A hedonic pricing model”, Agricultural Water Management, 181(2)：35-46. Koebel C Theodore, Robert E. Lang, Karen A. Danielsen, 2004, “Community Acceptance of Affordable Housing”, National Association of Realtors Kwangyin Liu, Kuo-chen Lu, Kai-yuan Teng, 2016, “Taiwan’s Industrial Land Crisis”, CommonWealth Magazine, 1(611) Lee A. Craig, Raymond B. Palmquist, Thomas Weiss, 1998, “Transportation Improvements and Land Values in the Antebellum United States: A Hedonic Approach”, The Journal of Real Estate Finance and Economics,16：173-189 Lokesha M.N, Dr. Mahesha M, 2016, “Impact of Road Infrastructure on Agricultural Development and Rural Road Infrastructure development programmes in India”, International Journal of Humanities and Social Science Invention, 5(11)：1-7. Margot Hornblower, 1988, “Ethics: Not In My Backyard, You Don’t”, Time Malgorzata J. Rymsza-Pawlowska, 2018, “The Struggle to Preserve Cleveland Park”, Historical Society of Washington, D.C., 30(1)：3-17. Mei Wang, Xiang Li, Wen-yan He, Jin-xin Li, Yan-yuan Zhu, Yu-Liang Liao, Jin-yan Yang, Xiao-e Yang, 2019, “Distribution, health risk assessment, and anthropogenic sources of fluoride in farmland soils in phosphate industrial area, southwest China”, Science Direct, 249：423-433. Mei-Chun Lai, Pei-Ing Wu, Je-Liang Liou, Yi Chen, Hanhui Chen, 2019, “The impact of promoting renewable energy in Taiwan — How much hail is added to snow in farmland prices?”, Journal of Cleaner Production 241(20). Md. Shakhawat Hossain, Muhammad Arshad, Lu Qian, Harald Kächele, Imran Khan, Md Din Il Islam, M. Golam Mahboob, 2020, “Climate change impacts on farmland value in Bangladesh”, Ecological Indicators, 112 Olena Myrna, Martin Odening, Matthias Ritter, 2019, “The Influence of Wind Energy and Biogas on Farmland Prices”, Land, 8(1) Stuart Meck. Rebecca Retzlaff, and James Schwab, 2003, “Regional Approaches to Affordable Housing”, American Planning Association Thomas H Kean, Thomas Ludlow Ashley, 1991, “’Not In My Backyard’ Removing Barriers to Affordable Housing”, United States Department of Housing and Urban Development, pp. 1-44 World Bank (1997): ̳Rural Development: Vision to Action: A Sector Strategy‘, Washington DC: The World Bank. Xin Yang, Anlu Zhang, Fan Zhang, 2019, “Farmers’Heterogeneous Willingness to Pay for Farmland Non-Market Goods and Services on the Basis of a Mixed Logit Model—A Case Study of Wuhan, China”, Environmental Research and Public Health, 16(20). Yicong Luo, Brent M. Swallow, Wiktor L. Adamowicz, 2023, “Using WTP and WTA to value farmland preservation under ambiguous property rights and preference uncertainty”, Land Economics, 99(4) Zuzana Hloušková , Michaela Lekešová, Anna Prajerová, Tomáš Doucha, 2022, “Assessing the Economic Viability of Agricultural Holdings with the Inclusion of Opportunity Costs”, Sustainability, 14(2). 三、網頁參考文獻 內政部不動產交易實價查詢服務網，2012，https://lvr.land.moi.gov.tw/，取用日期：2024年3月5日 台南市政府地政局，2022，臺南市國土功能分區圖(草案)，https://w3fs.tainan.gov.tw/Download.ashx?u=LzAwMS9VcGxvYWQvMjA3L3JlbGZpbGUvMjI0ODYvNzkzODA4MS85MjEwYjA4ZS1iZjM4LTQyYmYtOWI2Yy1kZDZhYjJlYmE2MTgucGRm&n=6Ie65Y2X5biC5ZyL5Zyf5Yqf6IO95YiG5Y2A5YiG6aGe5ZyWKOiNieahiCkucGRm&icon=.pdf，取用日期：2024年6月12日。 政府資料開放平台，2013，https://data.gov.tw/，取用日期：2024年3月15日 農業部農地資料流通中心，https://talis.moa.gov.tw/ALDOC/，取用日期：2024年3月30日 描述 碩士
國立政治大學
地政學系
111257026資料來源 http://thesis.lib.nccu.edu.tw/record/#G0111257026 資料類型 thesis dc.contributor.advisor 林子欽 zh_TW dc.contributor.advisor Lin, Tzu-Chin en_US dc.contributor.author (Authors) 陳品諺 zh_TW dc.contributor.author (Authors) Chen, Pin-Yan en_US dc.creator (作者) 陳品諺 zh_TW dc.creator (作者) Chen, Pin-Yan en_US dc.date (日期) 2024 en_US dc.date.accessioned 4-Sep-2024 14:28:31 (UTC+8) - dc.date.available 4-Sep-2024 14:28:31 (UTC+8) - dc.date.issued (上傳時間) 4-Sep-2024 14:28:31 (UTC+8) - dc.identifier (Other Identifiers) G0111257026 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/153255 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 地政學系 zh_TW dc.description (描述) 111257026 zh_TW dc.description.abstract (摘要) 農地價格受到多方因素的影響，極端的氣候變化、國際貿易影響、現代飲食習慣改變等等皆是原因，其中一部分原因即是受到周邊設施的外部性影響，如同房價會因為汙水處理廠、垃圾掩埋場而降低，農地價格也同樣會因周邊設施的設立而改變。本研究透過農地價格的改變，定義各種設施為鄰避設施或是迎毗設施，當價格因周邊設施而降低時即為鄰避設施，反之則稱為迎毗設施。另一方面，設施之影響在不同地區可能會產生不同的效果，因此本研究透過農地交易價格之高中低劃分出三個分區，藉以觀察設施在各個地區的不同影響，設施包含：一般道路、河川或水利設施、農業產銷設施、綠能設施、工廠、農舍、畜牧設施、養殖漁業設施、農路、休閒農場、農會、國道等共12種設施。 本研究透過實價登錄之農地交易資料，結合農地流通中心、政府資料開放平台之農地周邊設施資料，以特徵價格模型、空間迴歸模型分析設施外部性對於農地價格之影響。結果表明，一般道路等交通運輸設施除了農路在低價分區中作為鄰避設施以外，其他交通運輸設施皆具有正面之影響，與直覺相符，畜牧設施、漁業設施、也做為鄰避設施存在；農會、農舍、農業設施等等也做為迎毗設施存在，然而與直覺不符的是工廠與綠能設施，工廠對於周邊農地價格具有正面的影響，不論在何種分區皆是；綠能設施則在高價分區中有正面的影響，可見得目前政策對於工廠取締以及綠能政策與農地政策之間的權衡必須更加嚴謹並審慎衡量。 zh_TW dc.description.abstract (摘要) Farmland prices are influenced by a wide range of factors, including extreme climate events, international trade, and evolving dietary habits. One significant factor is the external impact of surrounding facilities. Just as property values may decline near sewage treatment plants or landfills, farmland prices can also fluctuate based on nearby developments. This study categorizes such facilities as either "NIMBY" (Not In My Back Yard) or "YIMBY" (Yes In My Back Yard) based on their influence on farmland prices. When prices decrease due to nearby facilities, these are classified as NIMBY, if prices increase, they are considered YIMBY facilities. Furthermore, the price impact of these facilities can vary across different regions. To capture these differences, this study divides farmland prices into three categories—high, medium, and low—and examines the effects of facilities in each area. This study covers 12 types of facilities, including transportation facilities, rivers or water resource facilities, agricultural production, green energy installations, factories, farmhouses, livestock facilities, aquaculture sites, farm road system, recreational farms, farmers’ association, and highways. This study uses actual transaction data from the Transaction Price Registration, combined with information on nearby facilities from the Taiwan Agriculture Land Information Service and government open data platforms. This study also employs Hedonic Price Method and Spatial Regression Model analysis to assess the externalities of facilities on farmland prices. The results indicate that most of transportation infrastructures, such as roads, has a positive impact on farmland prices, except for farm road system in low-price zones, which are defined as NIMBY facilities. Livestock and aquaculture facilities are also classified as NIMBY. In contrast, farmers’ association, farmhouses, and agricultural facilities are defined as YIMBY facilities. Unexpectedly, factories have a positive impact on farmland prices regardless of the regions, while green energy facilities show a positive effect only in high-price areas. These results suggest that current policies on factory regulation and the balance between green energy initiatives and farmland management require more careful evaluation and adjustment. en_US dc.description.tableofcontents 第一章 緒論 1 第一節 研究動機與目的 1 第二節 研究範圍與方法 3 第三節 研究架構與流程 5 第二章 文獻回顧 9 第一節 鄰避效應與迎毗效應 9 第二節 農地價格之衡量方式 16 第三章 研究設計 21 第一節 模型建構 21 第二節 資料說明 29 第三節 變數選取 41 第四章 實證分析與結果 55 第一節 空間迴歸分析 55 第二節 小結 70 第五章 結論與建議 77 第一節 結論 77 第二節 建議 79 第三節 研究限制 80 參考文獻 83 附錄 89 zh_TW dc.format.extent 2147316 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0111257026 en_US dc.subject (關鍵詞) 特徴價格法 zh_TW dc.subject (關鍵詞) 空間迴歸模型 zh_TW dc.subject (關鍵詞) 農地價格 zh_TW dc.subject (關鍵詞) 鄰避設施 zh_TW dc.subject (關鍵詞) 迎毗設施 zh_TW dc.subject (關鍵詞) Hedonic Price Method en_US dc.subject (關鍵詞) Spatial Regression Model en_US dc.subject (關鍵詞) Farmland Price en_US dc.subject (關鍵詞) Not-In-My-Back-Yard en_US dc.subject (關鍵詞) Yes-In-My-Back-Yard en_US dc.title (題名) 鄰避設施與迎毗設施對農地價格之影響 －以台南市為例 zh_TW dc.title (題名) The Impact of NIMBY and YIMBY Facilities on Farmland Prices： A Case Study of Tainan City en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 一、中文參考文獻 丁秀吟，林子欽，吳文傑，2023，「從使用價值之差別課稅觀點分析農地合理使用」，『規劃學報』，41(1)：16-34 于宗先，2004，「公共設施與規模經濟」，『經濟前瞻』，(95)：24-26 王欽傳，2015，「外部性影響因子與屬性框架對鄰避設施民眾接受度之影響」，國立中山大學公共事務管理研究所碩士論文：高雄 丘昌泰，2004，「公共設施中鄰避情結的成因與因應：以民營電廠為例」，『政治學報』，37：37-110 李永展，1996，「鄰避設施對社區環境品質之影響－以台北市三個垃圾焚化廠為例」，『國立政治大學學報』，(72)2：263-297 李永展，1997，「鄰避症候群之解析」，『都市與計劃』，24(1)：69-79 李永展，林啓賢，1998，「鄰避型公共設施之環境態度與更新接受意願之研究－以台北市為例」，『都市與計劃』，25(2)：133-153 李泳龍，黃宗誠，戴政安，李善將，2009，「醫學中心對鄰近住宅環境影響之研究」，『臺灣經濟預測與政策』，10(2)：75-90 吳怡葶，胡吳岳，2011，「波爾多產區葡萄酒特徵價格之研究」，『農業經濟叢刊』，28(2)：135-172 林祖嘉，馬毓駿，2007，「特徵方程式大量估價法在台灣不動產市場之應用」，『住宅學報』，16(2)：1-22 徐鳳嬌，2020，「污染農地對農地價格影響之分析」，臺灣大學生物資源暨農業學院農業經濟學系碩士論文：台北 陳奉瑤，楊依蓁，2007，「個別估價與大量估價之準確性分析」，『住宅學報』，16(2)：67-84 陳晏筑，林雅亭，劉千菱，吳佳洟，張雅嵐，林左裕，2022，「鄰避設施對鄰近房價的影響－以臺北市為例」，『土地問題研究季刊』，21(4)：32-53 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 廖咸興，張芳玲，1997，「不動產評價模式特徵價格法與逼近調整法之比較」，『住宅學報』，5：17-35 賴韋廷，陳文雄，劉鋼，2014，「蓋設超高壓輸電線的外部成本－以台電「南投－彰林」線路為例」，『臺灣經濟預測與政策』，45(1)：1-39 二、外文參考文獻 Brian Lee, Hung-Hao Chang, Szu-Yung Wang, 2021, “Can environmental disamenities increase land values? 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