Responsive image
博碩士論文 etd-0622120-093005 詳細資訊
Title page for etd-0622120-093005
論文名稱
Title
地下管線資訊公佈後對周遭房價影響 : 以高雄市為例
The Impact of Pipeline Position Information Disclosure on Surrounding Housing Price – A Case Study of Kaohsiung City
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
79
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2020-07-10
繳交日期
Date of Submission
2020-07-22
關鍵字
Keywords
不動產產業、分量迴歸、差異中之差異法、地下石化管線、資訊揭露
differences in differences, real estate industry, information disclosure, underground petrochemical pipelines, quantile regression
統計
Statistics
本論文已被瀏覽 5795 次,被下載 0
The thesis/dissertation has been browsed 5795 times, has been downloaded 0 times.
中文摘要
市場總訴說著房屋買賣不外乎地點、地點還是地點,除了房屋格局外,房屋周遭更是影響了房屋的價值,而周遭環境也有好的與壞的事物影響著房屋,好的不論學區、公園、交通、生活採購,壞的則有垃圾場、焚化爐、公墓等,然而對於市場而言,這些顯而易見的鄰避設施估計容易,但那些難以估計的事物如空汙、土壤液化等則需仰賴資訊的揭露才能讓市場反映真實價格,本研究便針對不動產市場中,聚焦於不利估計的地下管線位置,來探討經政府公布後對周遭有管線的房屋有何影響。
過去的資訊揭露文獻皆以差異中之差異法以區分出在特定研究目標下,特定時點前後之影響,其中諸如土石流潛勢區、土壤液化潛勢區、噪音汙染地圖、鉛含量地圖等多使勇此方法來觀察效果。本研究除了沿用了過去文獻方法,使用差異中之差異法看出管線公布後對周遭房價之效果外,額外使用分量迴歸區分出不通分量的效果;此外,將額外探討不同距離下何種距離較為適合,以及管線經挑選後是否改變欲探討的效果。
筆者使用2012年至2017年高雄市所有不動產交易之資料,並運用差異中之差異法與分量迴歸模型進行分析。研究結果發現,一般最小平方法下個距離基準下圖資公布後且周遭有管線之係數皆呈現不顯著的狀況,而分量迴歸中以100公尺有管線為基準時,0.1分量出現顯著負向影響,下滑3.1%,其他距離區間與分量的關鍵變數,及住宅一定距離內是否有管線與交易是否於圖資公布後交互作用效果上,都出現正向影響,且多為顯著,並隨分量上升而效果越明顯。
對此本研究推測中高房價之交易受豪宅與商辦等因素因而不在乎管線因而呈現正相關,對此,本研究發現豪宅因素由於結果為不顯著,因此僅能證明豪宅對此研究目標較不在乎,無法證明因此出現正向效果,而商辦等非住宅則出現明顯負向影響,非住宅降幅達44.3%,除了變向證明非住宅並非正效果之因素之一外,其影響也比一般住宅更明顯。
Abstract
This study uses data from all real estate transactions in Kaohsiung city from 2012 to 2017, and uses differences in differences method(DID) to explore the effect of underground petrochemical pipelines on the surrounding housing prices after the pipelines information announcement. Moreover, we additionally uses quantile regression to distinguish the marginal effect in 10th,25th,50th,75th,90th quantile. In addition, we will discuss which distance is more suitable when computing distance between pipelines and transactions, and whether filtered pipelines might change the effect will also be discussed.
Our research results found that general least square method and the 10th quantile in quantile regression have a negative effect on the effect of the transaction is within 100 meters and transaction date is after the pipeline information released, of which only 10th quantile in quantile regression is significant. Moreover, other distance and quantile are mostly positively influence effect.
For this reason, this study speculates that mansion and non-residential housing are two factors which result in positively influence effect in higher quantile. Therefore, this study aims these two possible reasons, one is non-residential housing such as offices and store which people didn’t live there, the other is luxury house which might not care about pipeline risk. According to empirical results, the factors of luxury housing have not been significantly affected, while non-residential housing such as stores and offices still have strong and significant negative influence effect. Besides, regardless of pipeline filtering, empirical results show that there is not much difference in the effect of house prices, and there is no obvious better distance benchmark.
目次 Table of Contents
學位論文審定書 ...................................................... i
誌 謝 ............................................................ ii
摘 要 ........................................................... iii
Abstract ...................................................... iv
圖次 ............................................................... vi
表次 .............................................................. vii
1 緒論 ............................................................. 1
1.1 研究背景與動機 .............................................. 2
1.2 研究問題與流程 .............................................. 5
2 文獻回顧 ......................................................... 6
2.1 不動產估價方法之演變 ........................................ 6
2.2 房屋內部特徵之效果 .......................................... 7
2.3 房屋外部特徵之效果 .......................................... 8
2.4 資訊揭露對不動產市場之效果 .................................. 9
2.5 地下管線相關研究 ........................................... 12
3 研究方法 ........................................................ 13
3.1 資料來源 ................................................... 13
3.2 資料處理 ................................................... 19
3.3 分析工具 ................................................... 24
4 研究結果 ........................................................ 31
4.1 敘述統計與樣本概況 ......................................... 31
4.2 基本分析結果 ............................................... 35
4.3 進階分析結果 ............................................... 41
5 結論與建議 ...................................................... 48
5.1 研究結論 ................................................... 48
5.2 研究建議與未來方向 ......................................... 49
參考文獻 ........................................................... 51
1. 中文文獻 ..................................................... 51
2. 英文文獻 ..................................................... 51
3. 相關網站 ..................................................... 55
附錄 ............................................................... 56
參考文獻 References
1. 中文文獻
《臺灣學通訊》(2012). 12-13.
高雄港107年統計年報(2018). 21.
胥愛琦. (2009). 計量經濟學.
劉秀玲,張金鶚. (1993). 房地產品質、價格與消費者物價指數之探討. 國立政
治大學學報. 第67期. 369-400.
林秋瑾,楊宗憲,張金鶚. (1996). 住宅價格指數之研究—以台北市為例.住宅
學報
黃麟雅, 江穎慧, 張金鶚. (2016). 臺北市生活設施水準對住宅價格之影響
張怡文. 江穎慧, 張金鶚. (2008). 分量迴歸在大量估價模型之應用 -非典型
住宅估價之改進
郭紀子, 邊泰明. (2017). 物業管理隊集合住宅之影響
連婉淳, 邊泰明. (2002). 工業區不動產價格影響因素之研究
永槤瑢,董呈煌,李春長.(2016) 都市更新重建對鄰近房價之影響─空間計量之應

簡啓珉, 李春長. (2018). 高雄市環狀輕軌對鄰近地區住宅價格之影響:以差異
中之差異法結合分量迴歸模型之分析
許瑞盛,李春長. (2018). 高雄氣爆事件對鄰近房價的影響—以差異中之差異法
與分量迴歸模型之分析
董呈煌,李春長,陳俊麟,吳韻玲. (2016). SVR與OLS在住宅價格預測正確率的
比較
張維倫,游淑滿,李春長. (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

2. 英文文獻
Allen C.Goodman. (1988), An econometric model of housing price, permanent
income, tenure choice, and housing demand, Journal of Urban Economics
Volume 23, Issue 3, May 1988, Pages 327-353
Alex Coad, Rekha Rao. (2008), Innovation and firm growth in high-tech sectors: A
quantile regression approach. Research Policy, Volume 37, Issue 4, May 2008,
Pages 633-648
Akira Hibiki, Shunsuke Managi. (2010) Does the housing market respond to
information disclosure?: Effects of toxicity indices in Japan. Journal of
Environmental Management Volume 92, Issue 1, January 2011, Pages 165-171
Bae, H. The impact of the residential lead paint disclosure rule on house prices:
findings in the American Housing Survey. J Hous and the Built
Environ 31, 19–30 (2016). https://doi.org/10.1007/s10901-015-9441-x
Chica-Olmo, Jorge & Cano-Guervos, Rafael & Tamaris‐Turizo, Ivan. (2018).
Determination of buffer zone for negative externalities: Effect on housing prices. The Geographical Journal. 10.1111/geoj.12289.
Coady Wing, Kosali Simon, and Ricardo A. Bello-Gomez. (2018) Designing
Difference in Difference Studies: Best Practices for Public Health Policy
Research. Annual Review of Public Health, Volume 39, 2018, Wing, pp 453-
469
David R. Bowes and Keith R. Ihlanfeldt. (2001), Identifying the Impacts of Rail
Transit Stations on Residential Property Values. Journal of Urban
Economics Volume 50, Issue 1, July 2001, Pages 1-25.
Dennis B.Guignet, Adan L. Martinez-Cruz. (2018), The impacts of underground
petroleum releases on a homeowner's decision to sell: A difference-in-
differences approach. Regional Science and Urban Economics Volume 69, March 2018, Pages 11-24
D.M.Grether Peter Mieszkowski. (2005), Determinants of real estate values, Journal of
Urban Economics Volume 1, Issue 2, April 1974, Pages 127-145,
https://doi.org/10.1016/0094-1190(74)90013-8
Eric Eide, Mark H. Showalter. (1998), The effect of school quality on student
performance: A quantile regression approach. Economics Letters
Volume 58, Issue 3, 1 March 1998, Pages 345-350
Gatzlaff, D., McCullough, K., Medders, L. et al. The Impact of Hurricane
Mitigation Features and Inspection Information on House Prices. J Real
Estate Finan Econ 57, 566–591 (2018).
Great American Insurance Group. (2006) National Fire Protection Association
Classification of Flammable and Combusitble Liquids
Gong, C. M., Lizieri, C., & Bao, H. X. H. (2019). “Smarter information, smarter
consumers”? Insights into the housing market. Journal of Business
Research, 97, 51–64. doi:10.1016/j.jbusres.2018.12.036
Haojie Li, Daniel J. Graham, Arnab Majumdar. (2012), The effects of congestion
charging on road traffic casualties: A causal analysis using difference-in-
difference estimation. Accident Analysis & Prevention, Volume 49, November 2012, Pages 366-377
H. Spencer Banzhaf. (2019) Difference-in-Differences Hedonics. Georgia State
University, NBER, PERC
Hill, R. (2011), “Hedonic Price Indexes for Housing”, OECDStatistics Working Papers,
2011/01, OECD Publishing.
Jeffrey M. Wooldridge.2006“IntroductoryEconometrics–A Modern
Approach.”.
KA Kiel, KT McClain. (1995) House Prices during Siting Decision Stages: The Case
of an lncinerator from Rumor through Operation
Kyoungrae Jung, The impact of information disclosure on quality of care in HMO
markets, International Journal for Quality in Health Care, Volume 22, Issue 6, December 2010, Pages 461–468
Linda R. Stanley (1991). A Market Test of Consumer Responseto Information
Disclosure. JPP & M, Vol. 10 (2.) 202-218.
Lori S. Bennear, Sheila M. Olmstead(2008). The impacts of the “right to know”:
Information disclosure and the violation of drinking water standards. Journal of Environmental Economics and Management 56 (2008) 117– 130
Mark Dotzour, Everard Moorhead, and Daniel Winkler. (1998) The Impact of
Auctions on Residential Sales Prices in New Zealand. Journal of Real Estate
Research, 16(1), 57- 72.
National Fire Protection Association. (2011) 2011 Fall NFPA Revision Cycle
Nakagawa, Masayuki & Saito, Makoto & Yamaga, Hisaki (2007). Earthquake
Risks and Land Prices: Evidence from the Tokyo Metropolitan Area. Japanese Economic Review. 60. 10.1111/j.1468-5876.2008.00438.x.
Nicholas B. Irwin. (2020), Legacies of Lead: Estimating Home Buyer Response to
Potential Lead Exposure. Land Economics March 1, 2020 vol. 96 no. 2 171-187. doi: 10.3368/le.96.2.171
P Slovic. (1987) Perception of risk
Pedro S Martins, Pedro TPereira. (2004), Does education reduce wage inequality?
Quantile regression evidence from 16 countries. Labour Economics
Volume 11, Issue 3, June 2004, Pages 355-371
Pope, J. C. (2008) Do Seller Disclosures Affect Property Values? Buyer
Information and the Hedonic ModelLand Economics November 2008 84:551-572
Pope, J. C. (2008). Fear of crime and housing prices: Household reactions to
sex offender registries. Journal of Urban Economics, 64(3), 601–
614. doi:10.1016/j.jue.2008.07.001
Pope, J. C. (2008). Buyer Information and the Hedonic: The Impact of a Seller
Disclosure on the Implicit Price for Airport Noise. Journal of Urban Economics, Vol. 63, No. 2, pp. 498-516, 2008
Quan, D. C. (2002). Market Mechanism Choice and Real Estate Disposition: Search
vs. Auction. Real Estate Economics, 30(3), 365-384.
Roger Koenker; Gilbert Bassett, Jr. (1978) Regression Quantiles. Econometrica, 46(1),
33-50.
Sandra E. Black. (1999), Do Better Schools Matter? Parental Valuation of Elementary
Education. The Quarterly Journal of Economics, Volume 114, Issue 2, May
1999, Pages 577–599.
Sherwin Rosen. (1974), Hedonic Prices and Implicit Markets: Product
Differentiation in Pure Competition. Journal of Political
Economy, 1974, vol. 82, issue 1, 34-55.
Sirmans, S., Macpherson, D. and Zietz, E. (2005). The composition of hedonic
pricingmodels. Journal of real estate literature, 13(1), 1-44.
Sunak, Y. and Madlener, R. (2014). Local Impacts of Wind Farms on Property Values:
a Spatial Difference-in-Differences Analysis. FCN Working Paper.
Stuart, E.A., Huskamp, H.A., Duckworth, K. et al. Using propensity scores in
difference-in-differences models to estimate the effects of a policy change. Health Serv Outcomes Res Method 14, 166–182 (2014).
Tita, G.E., Petras, T.L. & Greenbaum, R.T. Crime and Residential Choice: A
Neighborhood Level Analysis of the Impact of Crime on Housing Prices. J Quant Criminol 22, 299 (2006). https://doi.org/10.1007/s10940-006-9013-z
Tu, C.C. and Eppli, M.J. (2001). An Empirical Examination of Traditional
NeighborhoodDevelopment. Real Estate Economics, 29(3), 485–501.
Votsis, A., & Perrels, A. (2015). Housing Prices and the Public Disclosure of
Flood Risk: A Difference-in-Differences Analysis in Finland. The Journal
of Real Estate Finance and Economics, 53(4), 450–471. doi:10.1007/s11146-015-9530-3
Yang Zhang, Hong Zhang & Michael J. Seiler (2015) Impact of Information Disclosure
on Prices, Volume, and Market Volatility: An Experimental Approach, Journal
of Behavioral Finance, 16:1, 12-19, DOI: 10.1080/15427560.2015.1000333
Youngre Noh. (2018) Does converting abandoned railways to greenways impact
neighboring housing prices?. Landscape and Urban Planning
Volume 183, March 2019, Pages 157-166.

3. 相關網站
內政部時價登錄服務網. Website:
https://lvr.land.moi.gov.tw/homePage.action
高雄市工業管線查詢系統. Website:
https://ops.kcg.gov.tw/khpipe/default_c.aspx
台灣工業用地供給與服務資訊網. Website:
https://idbpark.moeaidb.gov.tw/
2014年高雄氣爆事故. Website:
https://idbpark.moeaidb.gov.tw/Environ?AntiToken=xuEwXkLJKLXfqTWWL%2BRcZg7M%2BZZ%2BFJeT7q9mufGuQ64%3D&CityID=E&p=2
環境資訊中心. Website:
https://e-info.org.tw/node/28354
爆炸極限. Website:
https://zh.wikipedia.org/wiki/%E7%88%86%E7%82%B8%E6%A5%B5%E9%99%90#cite_note-21
Great-Circle Distance. Website:
https://en.wikipedia.org/wiki/Great-circle_distance
電子全文 Fulltext
本電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
論文使用權限 Thesis access permission:自定論文開放時間 user define
開放時間 Available:
校內 Campus:開放下載的時間 available 2025-07-22
校外 Off-campus:永不公開 not available

您的 IP(校外) 位址是 3.140.242.165
論文開放下載的時間是 校外不公開

Your IP address is 3.140.242.165
This thesis will be available to you on Indicate off-campus access is not available.

紙本論文 Printed copies
紙本論文的公開資訊在102學年度以後相對較為完整。如果需要查詢101學年度以前的紙本論文公開資訊,請聯繫圖資處紙本論文服務櫃台。如有不便之處敬請見諒。
開放時間 available 2025-07-22

QR Code