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題名 台北市房價泡沫知多少?-房價vs.租金與房價vs.所得
作者 鄧筱蓉
貢獻者 張金鶚
鄧筱蓉
關鍵詞 房價
租金
家戶恆常性所得
泡沫價格
狀態空間模型
housing price
rent
housing permanent income
bubble price
state-space model
日期 2007
上傳時間 18-Sep-2009 16:20:25 (UTC+8)
摘要 過去雖有文獻探討國內房地產市場泡沫化問題，卻僅從租金收益的單一角度衡量房價基值，對於自有住宅比例較高的台灣而言，家戶所得不僅代表購屋者的負擔能力，更是構成房價基值的重要因素。有鑑於此，本研究分別從租金收益及家戶所得兩者不同角度下，透過資產市場現值模型，分別建立房價基值模型分析泡沫化現象。此外，過去文獻僅從檢定價格波動穩定性與否或將殘差項視為泡沫來研究泡沫化問題，然泡沫為不可觀察之變數，故本文使用具有可估計不可觀察變數特質的狀態空間模型（STATE-SPACE MODEL），推估泡沫價格，分析在不同時期下泡沫的規模大小。
在實證方面，本研究使用台北市1973Q2至2008Q1共140筆住宅價格資料，發現由租金與所得所計算之房價泡沫規模略為一致。在1988~1990年房市泡沫化時期，所得推估之泡沫規模達到高峰，泡沫價格占市價約47%；而由租金面亦計算出泡沫價格占市價約54%的高比例。而在2008年房價持續上漲的情況下，兩者泡沫價格亦呈現相同上升之走勢，泡沫價格近市價38%，租金推估泡沫價格占市價27%；此結果表示出目前房市有泡沫化之跡象，現階段欲購屋自住者不宜進入市場，宜審慎等待時機。而本文認為房價所得比或是房價租金比皆是作為衡量台北市房地產市場泡沫化現象之重要指標，另外就總體因素分析而言，房價上漲率、貨幣供給額、貸款利率與大盤股價指數皆為影響泡沫之重要因素，且經由實證發現所得所推估之泡沫價格較具有市場代表性。
The past literatures about Taipei housing price bubble has only been measured the fundamental price by rent. However, the housing owner ratio is so high in Taiwan that housing income is not only regarded as affordability but also an important fundamental factor of housing price. According to the above, we focus on different fundamental models that define market fundamental price to analyses the bubble price from expected present value of both rent and permanent housing income. On the other hand, different from lots of literature testing the housing price volatility or residual to measure bubble prices, because housing bubble is an unobservable variable, we apply State-Space Model which is good for testing an invisible factor to estimate bubble in the housing markets of Taipei.

This paper tries to test whether there was a housing price bubble using Taipei housing price index ranged from 1973Q1 to 2008Q1. The findings indicate that there appeared bubble ratio from 1988 to 1990, 47% of the housing price based on housing income and 54 % of the housing price based on rent. In 2008 when housing price continually keeps rising, bubble price ratios are close to 38% and 27% respectively. Those results show that Taipei seems to have sign of a bubble in this moment and housing buyers should concern it with more caution. Secondly, both price-income ratio and price-rent ratio are good indicators to measure housing bubble prices. Beside, we find macro economic factors change, such as the growth rate of housing price, M2, mortgage rate, and stock price index, are important to influence the size of housing bubble. Thirdly, bubble price estimated by housing income has a better performance than rent.
參考文獻 1. 于宗先、王金利(1999)，『台灣泡沫經濟』台北：聯經。
2. 林祖嘉、林素菁(1995)，台灣地區住宅價格的泡沫現象，台灣經濟學會年會論文集，295-313。
3. 林祖嘉(2007)，房價、股價、與泡沫經濟：兩岸經驗之比較，房地產產業年鑑，689-703。
4. 林秋瑾(1996)，台灣區域性住宅價格模式之建立，政大地政學報，29-49。
5. 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，第二期，49-66。
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9. 張金鶚、高國峰、林秋瑾(2001)，台北市合理房價－需求面分析，住宅學報，第十卷，第一期，51-66。
10. 張金鶚、劉秀玲(1992)，房地產品質、價格與消費者物價指數之探討，政大地政學報，第67期。
11. 張金鶚、楊宗憲(1999)，台北成屋價格泡沫知多少？，中華民國住宅學會第9屆年會論文集，15-29。
12. 曾建穎、張金鶚、花敬群(2005)，不同空間、時間住宅租金與其房價關聯性之研究—台北地區之實證現象分析，住宅學報第十四卷第二期，27-49。
13. 張金鶚(2003)，『房地產投資與市場分析』，台北：華泰書局。
14. 陳眀吉(1990)，房地產價格變動因素之研究，台灣銀行季刊，220-244。
15. 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」，國立政治大學地政研究所博士論文。
16. 彭建文、花敬群(2001)，住宅租買選擇行為之探討-住宅服務品質差異之影響，台灣土地金融季刊，第38卷第4期，89-107。
17. 黃佩玲(1994)，住宅價格與總體經濟變數關係之研究，國立政治大學地政系碩士論文。
18. 薛立敏(1990)，台北市房價上漲決定因素之估計，當前金融情勢與物價問題研討會，1990年6月，中研院經濟所主辦。
19. Hamilton, J. D.著，劉明志譯(1999)，『時間序列分析』，北京：中國社會科學出版社。
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23. Bertus, M. and Stanhouse, B.(2001). Rational Speculative Bubbles in the Gold Futures Market: An Application of Dynamic Factor Analysis. The Journal of Futures Markets, 21(1), 79.
24. Black, A., Fraster, P., and Hoesli, M.(2006). House Prices, Fundamentals and Bubbles. Journal of Business Finance & Accounting, 33(9/10), 1535.
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27. Bjorklund, K., and Soderberg, B.(1999). Property Cycles, Speculative Bubbles and the Gross Income Multiplier. The Journal of Real Estate Research, 18(1), 151.
28. Bourassa, S. C., Hendershott, P. H., and Murphy, J.(2001). Further Evidence on the Existence of Housing Market Bubbles. Journal of Property Research, 18(1), 1.
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30. Capozza, D.R., P.H. Hendershott and C. Mack(2004). An Anatomy of Price Dynamics in Illiquid Markets: Analysis and Evidence from Local Housing Markets, Real Estate Economics,Vol. 32, 1–32.
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33. Campbell, J.Y., and Shiller, R.J.(1988). The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors. The Review of Financial Studies (1986-1998), 1(3), 195.
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36. Chan, H.L., Lee, S.K., and Woo, K.Y.(2001). Detecting Rational Bubbles in the Residential Housing Markets of Hong Kong. Economic Modelling, 18(1), 61.
37. Chen, M-C and Patel, K. (1998). House Price Dynamics and Granger Causality: An Analysis of Taipei New Dwelling Market. Journal of Asian Real Estate Society, 1(1), 101-126
38. Chen, M.C. and Patel, K.(2002). An Empirical Analysis of Determination of House Prices in the Taipei Area, Taiwan Economic Review, 30 (4): 563-595.
39. Commandeur, J.J.F., and Koopman, S.J. (2007). An Introduction to State Space Time Series Analysis. NewYork：OXFORD。
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41. Gilbert, P.D.(1993). State Space and ARMA Model：An Overview of the Equivalence
42. Farlow, A.(2004). UK House Prices: A Critical Assessment, Part One of a report prepared for the Credit Suisse First Boston Housing Market Conference in May 2003(London: Credit Suisse First Boston (CSFB), January,
43. Ferna´ndez-Kranz, D., and Hon, M.T.(2006). A Cross-Section Analysis of the Income Elasticity of Housing Demand in Spain: Is There a Real Estate Bubble? Journal of Real Estate Finance and Economics, 32(4), 449.
44. Flood, R.P., and Hodrick, R.J.(1986). Asset Price Volatility, Bubbles, and Process Switching. The Journal of Finance, 41(4), 831.
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46. Giussani, B. and Hadjimatheou, G.(1991). Modelling Regional House Price in United Kingdom, The Journal of the Regional Science Association International, 70(2), 201-19.
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50. Hendry, D.F.(1984). Econometric Modelling of House Prices in the UK, in Econometrics and Quantitative Economics, Hendry, D. F. and Wallis, K. F. (eds), Basil Blackwell, Oxford.
51. Hui, E.C.M., and Yue, S.(2006). Housing Price Bubbles in Hong Kong, Beijing and Shanghai: A Comparative Study. Journal of Real Estate Finance and Economics, 33(4), 299.
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54. Krainer, J.(2003). House Price Bubbles. FRBSF Economic Letter, 2003(6), 1.
55. Lau, E.E.L., Tan, G.K.R., and Rahman, S. (2005). Assessing Pre-Crisis Fundamentals In Selected Asian Stock Markets. The Singapore Economic Review, 50(2), 175.
56. Lin, C.C.(1993). "The Relationship Between Rents and Prices of Owner-Occupied Housing in Taiwan," Journal of Real Estate Finance and Economics, 6, 25-54,1993.
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描述 碩士
國立政治大學
地政研究所
95257001
96
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0095257001
資料類型 thesis
dc.contributor.advisor 張金鶚zh_TW
dc.contributor.author (Authors) 鄧筱蓉zh_TW
dc.creator (作者) 鄧筱蓉zh_TW
dc.date (日期) 2007en_US
dc.date.accessioned 18-Sep-2009 16:20:25 (UTC+8)-
dc.date.available 18-Sep-2009 16:20:25 (UTC+8)-
dc.date.issued (上傳時間) 18-Sep-2009 16:20:25 (UTC+8)-
dc.identifier (Other Identifiers) G0095257001en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/35900-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 地政研究所zh_TW
dc.description (描述) 95257001zh_TW
dc.description (描述) 96zh_TW
dc.description.abstract (摘要) 過去雖有文獻探討國內房地產市場泡沫化問題，卻僅從租金收益的單一角度衡量房價基值，對於自有住宅比例較高的台灣而言，家戶所得不僅代表購屋者的負擔能力，更是構成房價基值的重要因素。有鑑於此，本研究分別從租金收益及家戶所得兩者不同角度下，透過資產市場現值模型，分別建立房價基值模型分析泡沫化現象。此外，過去文獻僅從檢定價格波動穩定性與否或將殘差項視為泡沫來研究泡沫化問題，然泡沫為不可觀察之變數，故本文使用具有可估計不可觀察變數特質的狀態空間模型（STATE-SPACE MODEL），推估泡沫價格，分析在不同時期下泡沫的規模大小。
在實證方面，本研究使用台北市1973Q2至2008Q1共140筆住宅價格資料，發現由租金與所得所計算之房價泡沫規模略為一致。在1988~1990年房市泡沫化時期，所得推估之泡沫規模達到高峰，泡沫價格占市價約47%；而由租金面亦計算出泡沫價格占市價約54%的高比例。而在2008年房價持續上漲的情況下，兩者泡沫價格亦呈現相同上升之走勢，泡沫價格近市價38%，租金推估泡沫價格占市價27%；此結果表示出目前房市有泡沫化之跡象，現階段欲購屋自住者不宜進入市場，宜審慎等待時機。而本文認為房價所得比或是房價租金比皆是作為衡量台北市房地產市場泡沫化現象之重要指標，另外就總體因素分析而言，房價上漲率、貨幣供給額、貸款利率與大盤股價指數皆為影響泡沫之重要因素，且經由實證發現所得所推估之泡沫價格較具有市場代表性。		zh_TW
dc.description.abstract (摘要) The past literatures about Taipei housing price bubble has only been measured the fundamental price by rent. However, the housing owner ratio is so high in Taiwan that housing income is not only regarded as affordability but also an important fundamental factor of housing price. According to the above, we focus on different fundamental models that define market fundamental price to analyses the bubble price from expected present value of both rent and permanent housing income. On the other hand, different from lots of literature testing the housing price volatility or residual to measure bubble prices, because housing bubble is an unobservable variable, we apply State-Space Model which is good for testing an invisible factor to estimate bubble in the housing markets of Taipei.

This paper tries to test whether there was a housing price bubble using Taipei housing price index ranged from 1973Q1 to 2008Q1. The findings indicate that there appeared bubble ratio from 1988 to 1990, 47% of the housing price based on housing income and 54 % of the housing price based on rent. In 2008 when housing price continually keeps rising, bubble price ratios are close to 38% and 27% respectively. Those results show that Taipei seems to have sign of a bubble in this moment and housing buyers should concern it with more caution. Secondly, both price-income ratio and price-rent ratio are good indicators to measure housing bubble prices. Beside, we find macro economic factors change, such as the growth rate of housing price, M2, mortgage rate, and stock price index, are important to influence the size of housing bubble. Thirdly, bubble price estimated by housing income has a better performance than rent.		en_US
dc.description.tableofcontents 第一章 緒論.................................... 1
第一節 研究動機與問題...............................1
第二節 資料來源與研究範圍、限制.................. 4
第三節 研究方法、架構與流程...................... 6
第二章 相關理論與文獻回顧........................ 8
第一節 泡沫化之相關理論..........................8
第二節 影響房價泡沫化之因素探討.................. 11
第三節 基要價值之認定........................... 13
第四節 衡量泡沫之研究方法........................ 17
第三章 房價基值模型之建立與狀態空間模型之說明...... 20
第一節 基要價值理論模型......................... 20
第二節 狀態空間模型與卡門濾波法.................. 24
第三節 房價泡沫化之狀態空間模型建立............... 28
第四章 衡量房價泡沫化與影響泡沫因素之實證分析...... 29
第一節 資料說明與處理........................... 29
第二節 單根檢定結果............................. 30
第三節 泡沫實證分析............................. 32
第四節 影響泡沫因素分析......................... 38
第五章 結論與建議............................... 43
第一節　 結論.................................... 43
第二節 　建議與後續研究........................... 46
參考文獻 ........................................47		zh_TW
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dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0095257001en_US
dc.subject (關鍵詞) 房價zh_TW
dc.subject (關鍵詞) 租金zh_TW
dc.subject (關鍵詞) 家戶恆常性所得zh_TW
dc.subject (關鍵詞) 泡沫價格zh_TW
dc.subject (關鍵詞) 狀態空間模型zh_TW
dc.subject (關鍵詞) housing priceen_US
dc.subject (關鍵詞) renten_US
dc.subject (關鍵詞) housing permanent incomeen_US
dc.subject (關鍵詞) bubble priceen_US
dc.subject (關鍵詞) state-space modelen_US
dc.title (題名) 台北市房價泡沫知多少?-房價vs.租金與房價vs.所得zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 1. 于宗先、王金利(1999)，『台灣泡沫經濟』台北：聯經。zh_TW
dc.relation.reference (參考文獻) 2. 林祖嘉、林素菁(1995)，台灣地區住宅價格的泡沫現象，台灣經濟學會年會論文集，295-313。zh_TW
dc.relation.reference (參考文獻) 3. 林祖嘉(2007)，房價、股價、與泡沫經濟：兩岸經驗之比較，房地產產業年鑑，689-703。zh_TW
dc.relation.reference (參考文獻) 4. 林秋瑾(1996)，台灣區域性住宅價格模式之建立，政大地政學報，29-49。zh_TW
dc.relation.reference (參考文獻) 5. 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，第二期，49-66。zh_TW
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