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題名 特徵價格法在住宅大量估價模型中的延伸—分量迴歸之應用
The Extension of Hedonic Price Theory in Housing Mass appraisal Models— The Application of Quantile Regression
作者 張怡文
Chang, Yi Wen
貢獻者 張金鶚
張怡文
Chang, Yi Wen
關鍵詞 不動產估價
大量估價
特徵價格法
分量迴歸
Real estate appraisal
Mass appraisal
Hedonic price theory
Quantile regression
日期 2006
上傳時間 19-Sep-2009 13:14:01 (UTC+8)
摘要 特徵價格模型是傳統常被使用於不動產大量估價的模型,由於模型將造成所有價位的不動產其特徵都具有同樣的邊際價格而無法解釋現實不動產特徵的各種可能狀況,故引發本研究利用分量迴歸建立大量估價模型之動機。研究利用台灣不動產成交行情公報的資料進行台北市大廈的實證分析,針對特徵價格法的延伸與估價準確度做檢視。嘗試應用分量迴歸建立大量估價模型,討論住宅特徵對於價格的邊際影響力於不同價位的住宅是否存在差異,並討論分量迴歸模型的估價精確度。研究採用交互驗證法與重複實驗30次討論模型的估計效果,並利用平均絕對百分比誤差(MAPE)以及命中率(Hit Rate)做為模型預測優劣程度的衡量標準,以討論分量迴歸模型是否可以較最小平方特徵價格模型有更為準確的估計表現。實證首先探討價格分量之下各住宅屬性對於價格的影響狀況,得到大部分住宅特徵對於價格的邊際影響力的確會因住宅價位的不同而有所差異。在估價準確度的部份,經測試得到利用分量迴歸建立大量估價模型的估價效果達研究的預期目標,且其估計表現優於最小平方特徵價格模型。<br>藉由分量迴歸模型,得到隨著住宅價位的增加,坪數與屋齡對於價格的影響力並非呈現一致的趨勢;坪數輪廓與屋齡輪廓出現轉折也為變數增加二次項變數的原因得到實證依據。重複實驗30次的整體表現,分量迴歸模型的MAPE較最小平方迴歸模型低了1.687%;誤差落在正負10%的Hit Rate較最小平方迴歸模型高了3.81%;誤差落在正負20%的Hit Rate較最小平方迴歸模型高了5.14%。30次的實證為分量迴歸模型的估價表現更優於最小平方迴歸模型得到較具說服力的結果。
Hedonic pricing models are traditionally used for real estate automated valuation models. Because the conditional mean calculated by OLS does not give a complete description of the relationship between dependent variable and independent variables, which leads to the motive of this study. This study inspects the extension of hedonic pricing models and appraisal accuracy, and we attempt to apply quantile regression to real estate automated valuation models and discuss the difference of the marginal contribution in each individual characteristic under different price level. Our study adopts cross validation and repeats empirical process for 30 times, and we use MAPE and hit rate to evaluate accuracy and argue if quantile regression models have better estimation. The empirical results show that the marginal contribution of housing area and age changes with price level; the turning points of area curve and age curve show empirical evidence for including square variables. The entirety performance of repeated experiments points out that the MAPE of quantile regression model is 1.687% lower than OLS model; as error ranged between 10% to -10%, the hit rate of quantile regression model is 3.81% higher than OLS model; as error ranged between 20% to -20%, the hit rate of quantile regression model is 5.14% higher than OLS model. The 30 times experiment of quantile regression models shows a much more persuasive result than OLS models.
參考文獻 1. 林祖嘉(1992),台灣地區房租與房價關係之研究,台灣銀行季刊,第43卷1 期,頁279-312。
2. 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,第1期,頁21- 45。
3. 張金鶚、林秋瑾、楊宗憲(1996),住宅價格指數之研究-以臺北市為例,住宅學報,第4期,頁1-30。
4. 財團法人台灣不動產資訊中心(2004),電腦大量估價技術之檢討與模式之建立案:電腦大量估價實證模式建構,中美經濟社會發展基金計畫編號79-1-356-3-k4002-03。
5. 廖仲仁、張金鶚(2006),不對稱的仲介服務價格效果:分量迴歸法之檢驗,都市與計劃,第3卷1 期,頁1-16。
6. 陳奉瑤、張欣民(2003),自動估價系統(AVM)到底算不算是估價?,土地問題研究季刊,第2卷2 期,頁72-77。
7. 陳建良、管中閔(2006),台灣工資函數與工資性別歧視的分量迴歸分析,經濟論文,第34卷4 期,頁435-468。
8. 曾眀遜(1992),不寧適設施對住宅價格影響之研究-以垃圾處理場為個案,中興大學都市計劃研究所碩士論文。
9. 楊依蓁(2006),個別估價與大量估價準確性之研究,國立政治大學地政學系碩士論文。
10. 楊宗憲、彭建文(2006),影響自動估價系統與不動產估價師關係之因素分析,全國不動產經營與管理實務學術研討會。
11. 管中閔、莊家彰(2005),台灣與美國股市價量關係的分量迴歸分析,中央研究院經濟研究所經濟論文,第33卷4 期,頁379-404。
12. 廖咸興、張芳玲(1997),不動產評價模式特價格法與逼近調整法之比較,住宅學報,第5卷1期,頁17-35。
13. Appraisal Foundation, (2003), Uniform Standards of Professional Appraisal Practice, Washington, D.C.: Appraisal Foundation.
14. Bourassa, S. C., Hoesli, M. and Peng V. S.,(2003), “Do housing submarkets really matter?”, Journal of Housing Economics, vol. 12, pp. 12-28.
15. Colwell, P. F. and Dillmore, G. , (1999), “Who Was First? An Examination of an Early Hedonic Study”, Land Economics, vol. 75, no.4, pp. 620-626.
16. Detweiler, J. H. and Radigan, R. E., (1999), “Computer Assisted Real Estate Appraisal: A Tool for the Practicing Appraiser”, The Appraisal Journal, vol. 67, no.3, pp. 280-286.
17. DiPasquale, D. and Wheaton, W. C. (1996), “Urban Economics and Real Estate Markets”, Englewood Cliffs, NJ: Prentice Hall.
18. Efron, B., (1982), “The Jacknife, the Bootstrap and Other Resampling Plans”, Philadelphia, PA: Society for Industrial and Applied Mathematics.
19. Fisher, A. W., (2002), Real Time Valuation, Journal of Property Investment and Finance, vol. 20, no. 3, pp.213-222.
20. Follain, J. R. and Malpezzi, S., (1980), “Dissecting Housing Value and Rent”, Washington, DC: The Urban Institute.
21. Goodman, A. C., (1998), “Andrew Court and the Invention of Hedonic Price Analysis”, Journal of Urban Economics, vol. 44, no.2, pp. 291-298.
22. IAAO, (2003), Standard on Automated Valuation Models, Chicago: IAAO.
23. Kinnard, W. N., (2001), “New Thinking in Appraisal Theory”, The Appraisal Journal, vol. 69, no.3, pp. 235-244.
24. Kirby, A., (1997), “Computer Assisted Mass Appraisal: The Queensland experience”, Computer Assisted Mass Appraisal: An International Review, pp. 198-209.
25. Koenker, R. and Bassett, G. W., (1978),“Regression Quantiles”, Econometrica, vol. 46, no.1, pp. 211-244.
26. Koenker, R. and Bassett, G. W., (1982), “Robust Tests for Heteroscedasticity Based on Regression Quantiles”, Journal of Derivatives, vol. 50, no.1, pp. 43-62.
27. Koenker, R. and Hallock, K. F., (2000), “Quantile Regression An Introduction”, University of Illinois at Urbana-Champaign.
28. Koenker, R. and Hallock, K. F., (2001),“Quantile Regression”, Journal of Economic Perspectives, vol. 15, no.4, pp. 143-156.
29. Kuan, C. M., (2003), “An Introduction To Quantile Regression”, Institute of Economics Academia Sinica.
30. Lancaster, K., (1965), “The Theory of Qualitative Linear Systems”, Econometrica, vol. 33, no.2, pp. 395-409.
31. Loans, D., (1990), “The Variance in Valuations”, Investment Property Databank, London.
32. Malpezzi, S., Ozanne L. and Thibodeau T., (1980), “Characteristic Prices of Housing in Fifty-Nine Metropolitan Areas”, Research Report, Washington, DC: The Urban Institute.
33. Malpezzi, S., (2003), “Hedonic Pricing Models: A Selective and Applied Review, in Housing Economics and Public Policy: Essays in Honor of Maclennan, D., Sullivan, T. O. and Gibbs, K. (Eds.), Blackwell.
34. Mark, G. and Goldberg, M. A., (1998), “Multiple Regression Analysis and Mass Assessment:A Review of the Issues”, The Appraisal Journal, Chicago, vol. 56, no.1, pp. 89-110.
35. Matysiak, G. and Wang, P., (1995), “Commercial Property Market Prices and Valuation: Analyzing the Correspondence”, Journal of Property Research, vol. 12, no.3, pp. 181-202.
36. McCluskey, W. J. and Adair, A. S. ,(1997),Computer Assisted Mass Appraisal: An International Review, Ashgate Publishing Limited, England.
37. Miller, N. G., (1982), “Residential Property Hedonic Pricing Models: A Review”, Research in Real Estate, vol. 2, no.1, pp. 31-56.
38. Nelson, J. P., (1978), “Residential Choice, Hedonic Prices, and the Demand for Urban Air Quality”, Journal of Urban Economics, vol. 5, pp. 357-369.
39. Pace, R. K. and Gilley, O. W., (1993), “Translating Prior Information Across Specifications to Improve Predictive Accuracy”, Journal of Business & Economic Statistics, vol. 11, no.3, pp. 301-309.
40. Reck, C., (2003), “Heterogeneity and Black-white Labor Market Differences: Quantile Regression with Censored Data 1979-2001”, UIUC:Dept of Economics.
41. Rosen, S., (1974), “Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition”, Journal of Political Economy, vol. 82, no.1, pp. 34-55.
42. Sirmans, G. S., Macpherson, D. A. and Zietz, E. N., (2005), “The Composition of Hedonic Pricing Models”, Journal of Real Estate Literature, vol. 13, no.1, pp. 3-44.
43. Söderberg, B., (2002), “A Note on the Hedonic Model Specification for Income Properties” , Research in Real Estate Monograph Series: Valuation Theory. Ed. K Wang & M L Wolverton, Kluwer, Boston.
描述 碩士
國立政治大學
地政研究所
94257024
95
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0094257024
資料類型 thesis
dc.contributor.advisor 張金鶚zh_TW
dc.contributor.author (Authors) 張怡文zh_TW
dc.contributor.author (Authors) Chang, Yi Wenen_US
dc.creator (作者) 張怡文zh_TW
dc.creator (作者) Chang, Yi Wenen_US
dc.date (日期) 2006en_US
dc.date.accessioned 19-Sep-2009 13:14:01 (UTC+8)-
dc.date.available 19-Sep-2009 13:14:01 (UTC+8)-
dc.date.issued (上傳時間) 19-Sep-2009 13:14:01 (UTC+8)-
dc.identifier (Other Identifiers) G0094257024en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/37346-
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) 94257024zh_TW
dc.description (描述) 95zh_TW
dc.description.abstract (摘要) 特徵價格模型是傳統常被使用於不動產大量估價的模型,由於模型將造成所有價位的不動產其特徵都具有同樣的邊際價格而無法解釋現實不動產特徵的各種可能狀況,故引發本研究利用分量迴歸建立大量估價模型之動機。研究利用台灣不動產成交行情公報的資料進行台北市大廈的實證分析,針對特徵價格法的延伸與估價準確度做檢視。嘗試應用分量迴歸建立大量估價模型,討論住宅特徵對於價格的邊際影響力於不同價位的住宅是否存在差異,並討論分量迴歸模型的估價精確度。研究採用交互驗證法與重複實驗30次討論模型的估計效果,並利用平均絕對百分比誤差(MAPE)以及命中率(Hit Rate)做為模型預測優劣程度的衡量標準,以討論分量迴歸模型是否可以較最小平方特徵價格模型有更為準確的估計表現。實證首先探討價格分量之下各住宅屬性對於價格的影響狀況,得到大部分住宅特徵對於價格的邊際影響力的確會因住宅價位的不同而有所差異。在估價準確度的部份,經測試得到利用分量迴歸建立大量估價模型的估價效果達研究的預期目標,且其估計表現優於最小平方特徵價格模型。<br>藉由分量迴歸模型,得到隨著住宅價位的增加,坪數與屋齡對於價格的影響力並非呈現一致的趨勢;坪數輪廓與屋齡輪廓出現轉折也為變數增加二次項變數的原因得到實證依據。重複實驗30次的整體表現,分量迴歸模型的MAPE較最小平方迴歸模型低了1.687%;誤差落在正負10%的Hit Rate較最小平方迴歸模型高了3.81%;誤差落在正負20%的Hit Rate較最小平方迴歸模型高了5.14%。30次的實證為分量迴歸模型的估價表現更優於最小平方迴歸模型得到較具說服力的結果。zh_TW
dc.description.abstract (摘要) Hedonic pricing models are traditionally used for real estate automated valuation models. Because the conditional mean calculated by OLS does not give a complete description of the relationship between dependent variable and independent variables, which leads to the motive of this study. This study inspects the extension of hedonic pricing models and appraisal accuracy, and we attempt to apply quantile regression to real estate automated valuation models and discuss the difference of the marginal contribution in each individual characteristic under different price level. Our study adopts cross validation and repeats empirical process for 30 times, and we use MAPE and hit rate to evaluate accuracy and argue if quantile regression models have better estimation. The empirical results show that the marginal contribution of housing area and age changes with price level; the turning points of area curve and age curve show empirical evidence for including square variables. The entirety performance of repeated experiments points out that the MAPE of quantile regression model is 1.687% lower than OLS model; as error ranged between 10% to -10%, the hit rate of quantile regression model is 3.81% higher than OLS model; as error ranged between 20% to -20%, the hit rate of quantile regression model is 5.14% higher than OLS model. The 30 times experiment of quantile regression models shows a much more persuasive result than OLS models.en_US
dc.description.tableofcontents 第一章 緒論
第一節 研究動機與研究目的…………………………………………1
第二節 研究問題與研究方法…………………………………………4
第三節 研究範圍與資料來源…………………………………………5
第四節 研究流程與架構………………………………………………6
第二章 相關理論與文獻回顧
第一節 大量估價之相關文獻…………………………………………8
第二節 特徵價格法之相關理論文獻…………………………………11
第三節 分量迴歸相關文獻……………………………………………15
第四節 研究設計………………………………………………………18
第三章 資料特性與模型建立
第一節 資料說明………………………………………………………22
第二節 研究範圍與資料敘述統計……………………………………23
第三節 實證模型設定…………………………………………………24
第四節 變數選取與描述………………………………………………25
第四章 實證結果與分析
第一節 分量迴歸模型之實證發現與分析……………………………29
第二節 模型估價精確度之實證與結果分析…………………………41
第五章 結論與建議
第一節 結論……………………………………………………………49
第二節 後續研究建議…………………………………………………51
參考文獻 ............................................52
附錄 ............................................55
zh_TW
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dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0094257024en_US
dc.subject (關鍵詞) 不動產估價zh_TW
dc.subject (關鍵詞) 大量估價zh_TW
dc.subject (關鍵詞) 特徵價格法zh_TW
dc.subject (關鍵詞) 分量迴歸zh_TW
dc.subject (關鍵詞) Real estate appraisalen_US
dc.subject (關鍵詞) Mass appraisalen_US
dc.subject (關鍵詞) Hedonic price theoryen_US
dc.subject (關鍵詞) Quantile regressionen_US
dc.title (題名) 特徵價格法在住宅大量估價模型中的延伸—分量迴歸之應用zh_TW
dc.title (題名) The Extension of Hedonic Price Theory in Housing Mass appraisal Models— The Application of Quantile Regressionen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 1. 林祖嘉(1992),台灣地區房租與房價關係之研究,台灣銀行季刊,第43卷1 期,頁279-312。zh_TW
dc.relation.reference (參考文獻) 2. 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,第1期,頁21- 45。zh_TW
dc.relation.reference (參考文獻) 3. 張金鶚、林秋瑾、楊宗憲(1996),住宅價格指數之研究-以臺北市為例,住宅學報,第4期,頁1-30。zh_TW
dc.relation.reference (參考文獻) 4. 財團法人台灣不動產資訊中心(2004),電腦大量估價技術之檢討與模式之建立案:電腦大量估價實證模式建構,中美經濟社會發展基金計畫編號79-1-356-3-k4002-03。zh_TW
dc.relation.reference (參考文獻) 5. 廖仲仁、張金鶚(2006),不對稱的仲介服務價格效果:分量迴歸法之檢驗,都市與計劃,第3卷1 期,頁1-16。zh_TW
dc.relation.reference (參考文獻) 6. 陳奉瑤、張欣民(2003),自動估價系統(AVM)到底算不算是估價?,土地問題研究季刊,第2卷2 期,頁72-77。zh_TW
dc.relation.reference (參考文獻) 7. 陳建良、管中閔(2006),台灣工資函數與工資性別歧視的分量迴歸分析,經濟論文,第34卷4 期,頁435-468。zh_TW
dc.relation.reference (參考文獻) 8. 曾眀遜(1992),不寧適設施對住宅價格影響之研究-以垃圾處理場為個案,中興大學都市計劃研究所碩士論文。zh_TW
dc.relation.reference (參考文獻) 9. 楊依蓁(2006),個別估價與大量估價準確性之研究,國立政治大學地政學系碩士論文。zh_TW
dc.relation.reference (參考文獻) 10. 楊宗憲、彭建文(2006),影響自動估價系統與不動產估價師關係之因素分析,全國不動產經營與管理實務學術研討會。zh_TW
dc.relation.reference (參考文獻) 11. 管中閔、莊家彰(2005),台灣與美國股市價量關係的分量迴歸分析,中央研究院經濟研究所經濟論文,第33卷4 期,頁379-404。zh_TW
dc.relation.reference (參考文獻) 12. 廖咸興、張芳玲(1997),不動產評價模式特價格法與逼近調整法之比較,住宅學報,第5卷1期,頁17-35。zh_TW
dc.relation.reference (參考文獻) 13. Appraisal Foundation, (2003), Uniform Standards of Professional Appraisal Practice, Washington, D.C.: Appraisal Foundation.zh_TW
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