學術產出-學位論文

文章檢視/開啟

書目匯出

Google ScholarTM

政大圖書館

引文資訊

TAIR相關學術產出

題名 投資型購屋者機率預測模型之建立
The Probability predictive model of housing investors
作者 邱于修
Chiou,Yu Shiou
貢獻者 張金鶚
邱于修
Chiou,Yu Shiou
關鍵詞 投資型購屋者
自住型購屋者
二元羅吉特模型
機率界限
housing investor
owner-occupier
binary logit model
cutoff point
日期 2007
上傳時間 14-九月-2009 13:54:30 (UTC+8)
摘要 住宅為兼具消費及投資之雙重功能財貨,因此若從購屋動機劃分購屋族群,可以分為自住者及投資者,近年來受到國內房市呈現生氣蓬勃之景象及利率持續走低等總體經濟因素影響之下,出現越來越多以投資為主要目的之投資型購屋者,對於金融機構之購屋貸款業務來說,投資者之還款行為相較於自住者是比較不穩定的。故本文之研究目的即藉由探討自住者及投資者之購屋特徵異同,建立投資者之機率預測模型,預測某購屋者成為投資者之機率,提供一較為客觀之機率預測模型,供作金融機構放貸參考準則。接著進一步探討在不同機率界限(cutoff point)下之預測準確率,找出預測準確率最高之機率界限值,提高本模型之預測準確度;並探討金融機構在不同經營方針下之較適機率界限值。
     
本文使用台灣住宅需求動向季報之已購屋者問卷,建立二元羅吉特模型。研究結果顯示,區位在中心都市、高單價、小面積產品及大面積產品、預售屋及拍賣屋市場屬於投資型產品,而搜尋時間短、搜尋間數少、年齡較長、男性、無固定職業及家庭平均月收入較高者成為投資者之機率較高。接著,運用貝氏定理計算出預測準確率最高之機率界限值,結果當機率界限值為0.70時預測準確率最高,投資者達72.22%,自住者達80.07%。此外,並使用2007Q4的資料作樣本外驗證,投資者命中率為65.52%,自住者命中率為84.51%。最後,為提供金融機構運用,本文模擬兩種預測誤差在不同權重下對於金融機構所造成的損失,找出損失最少的機率界限值,結果皆是以0.70為最適機率界限值。
Housing is dual function goods, consumption and investment, so if we separate the home buyers by their motives, they can be defined as two groups, owner-occupiers and investors. Recently, because the housing market is vigorous inland and the rates are fairly low, there are more and more home buyers buying houses for investment. To financial institutions, their payment behaviors are more instable, compare to owner-occupiers. So this article is aim to build a probability predictive model of housing investors by discussing the different home buying characters between owner-occupiers and investors. Therefore we can provide financing institutions a more objective method evaluating if they should lend money to the home buyers. Then we discuss the predictive accuracy with different cutoff points, finding the cutoff point with highest predictive accuracy, therefore we can elevate the model"s predictive accuracy. Besides, we also discuss the most optimal cutoff point for financial institutions under different administration principles.<br>This article builds binary logit model by the data of “Housing Demand Survey in Taiwan”. Our results suggests that if the houses in downtown、high unit price、big and small acreage、presale and court auction housing market belong to investing houses. And short search duration、few search items、older、male、non-constant job、higher income are getting higher probability to be housing investors. Then, we use Bayesian Theorem to figure out the cutoff point with highest predictive accuracy, and Our results suggests that 0.70 cutoff point with highest predictive accuracy , at that time, investor predictive accuracy is 72.22%, owner-occupier is 80.07%. Besides, we also do the out-sample test by the 2007Q4 data, the investor"s hit-rate is65.52%, the owner-occupier"s hit-rate is 84.51%. At the end, in order to provide financial institution to use, we give two predictive deviation different weights, to find the smallest loss cutoff point, the result all suggest that 0.70 is the most optimal cutoff point.
參考文獻 參考文獻
1.王濟川、郭志剛,2004,『Logistic迴歸模型-方法及應用』二版,台北市:五南。
2.王國川,2004,『圖解SAS視窗在迴歸分析上的應用』初版,台北市:五南。
3.江百信、張金鶚,1995,「我國購屋貸款放款條件之研究」,『住宅學報』,3:1~20。
4.沈庭增,2007,「都市仙丹─台北市『小套房』之空間生產與消費」,國立臺灣大學工學院建築與城鄉研究所碩士論文。
5.李桐豪、呂美慧,2000,「在金融機構房貸客戶授信評量模式—以Logistic 迴歸分析」,台灣金融財務季刊,1(1):1-20。
6.李馨蘋,1997,「住宅抵押貸款違約風險之實證分析」,國立臺灣工業技術學院管理技術硏究所博士論文。
7.杜慶麟、張瑞芬,1998,「銀行授信決策應用神經網路之研究— 抵押貸款之實證研究」,『模糊系統學刊』, 4(1):31-44。
8.林左裕、劉長寬,2003,「應用Logit模型於銀行授信違約行為之研究」, 2003年中華民國住宅學會第十二屆年會。
9.林祖嘉、陳建良,2005,「租買選擇、貸款選擇、與世代組成:巢式Logit模型之應用」,『住宅學報』,14:1~20。
10.花敬群、張金鶚,1993,「房地產投機行為之研究」,『經社法制論叢』,11:327~359。
11.周美伶、張金鶚,2005,「購屋搜尋期間影響因素之研究」,『管理評論』,24(1):133~150。
12.施恩,1994,「房屋貸款還款速度之硏究」,國立台灣大學商學硏究所碩士論文。
13.張金鶚,2003,『房地產投資與市場分析理論與實務 上篇:房地產投資分析』初版,台北市:張金鶚出版:華泰總經銷。
14.張梅音、鍾陳佳,2002,「住宅法拍屋屋屬性與拍定價格關係之研究--以台中市12樓以下集合住宅為例」,『土地問題研究季刊』,1(2):12-20。
15.陳彥仲,1997,「住宅選擇之程序決策模式」,『住宅學報』,5:37-49。
16.陳彥仲、吳京玲,1998,「家戶住宅區位選擇與地方財政分配之實證研究」,『都市與計劃』,25(2):223-238。
17.陸劍清,2002,『投資心理學』初版,台北市:揚智文化。
18.黃文啟,2002,「以LOGIT模型硏究借款人特性與不動產抵押貸款提前償還之關係」,國立政治大學財務管理學系硏究所碩士論文。
19.劉展宏、張金鶚,2001,「購屋貸款提前清償行為之研究」,,『住宅學報』,10(1):29~49。
20.劉代洋、李馨蘋,1994,購屋貸款與家戶社經特色之實證研究-以台中都會區為例,『管理科學學報』,11(1):109-127。
21.賴麗華,1996,「住宅投資報酬率之硏究」,國立政治大學地政硏究所碩士論文。
22.Allison, P. D., 1999, “Logistic Regression Using the SAS System:Theory and Application〔M〕”Cary NC: SAS Institute Inc.
23.Alonso, W., 1964,”Location and Land Use: Toward a General Theory of Land Rent”, Cambridge, Massachusetts: Harvard University Press.
24.Chua, K. W., and Hung, C. T., 2001,”Developer’s Good Will as Significant influence on Apartment Unit Prices”, The Appraisal Journal, 69(1): 26-30.
25.Hsu, K. J., 1996,”A Model of Housing Consumption-Investment Behavior of Homeownership under Uncertainty”, Paper presented at the 35th WRSA Annual Meeting, Feb 26-28.
26.Jan, K. B., 1997,”Consumption and Investment Motives and the Portfolio Choices of Homeowners”, Journal of Real Estate Finance and Economics, 15(2): 159-180.
27.Lancaster, K.J., 1966,”A New Approach to Consumer Theory” Journal of Political Economy, 74:132-156.
28.Lin, C. C. and Lin, S. J., 1999,”An Estimation of Elasticities of Consumption Demand and Investment Demand for Owner-Occupied Housing in Taiwan:A Two- Period Model ”,International Real Estate Review, 2: 110-125.
29.Lin, T. C., 2004,”A Study on the Termination Behaviors of Residential Mortgages in Taiwan”, Journal of Agricultural Economics, 76:169-195.
30.Mendard, S., 1995, “Applied Logistic Regression Analysis.” Thousand Oaks, CA: Sage Publication.
31.McFadden, D., 1973,”Conditional Logit analysis and qualitative choice behavior”, in Frontiers in Economics, edited by P. Zaremka. New York: Academic Press.
32.McFadden, D., 1978,”Modeling the choice of residential location”, Transportation Research Record, 673(1): 72-77.
33.McFadden, D., and Manski, C. F., 1981,”Econometric models of probability choice and structural analysis of discrete data with choice”, in Economic Applications, edited by C. Manski and D. McFadden. MIT Press.
34.Neter, J., Kutner, M. H., Nachtsheim, C. J., Wasserman, W., 1999,”Applied Linear Statistical Models” Fourth Edition. Mcgraw-Hill, Inc., 1999.
35.Philips, R. A., Rosenblatt, E. and Vanderhoff, J. H., 1996,”The Probability of Fixed-Rate and Adjustable-Rate Mortgage Termination”, the Journal of Real Estate Finance and Economics, 13: 95-104.
36.Quigley, J. M. and Robert V. O., 1991,”Defaults on Mortgage Obligations and Capital Requirements for U.S. Savings Institutions-a policy perspective”, Journal of Public Economics, 44: 353-369.
37.Rosen, S., 1974,”Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition”, Journal of Political Economy, 82:34-55.
38.Sirmans, C. F. and J. D. Benjamin, 1990,”Pricing Fixed Rate Mortgage: Some Empirical Evidence”, The Journal of financial Services Research, 4: 191-202.
39.Swinburne, R., 2005,”Bayes’s Theorem.” Oxford University Press, New York.
40.Wayne A., David, C. L. and Gary, A. M., 1996, “The Effect of Income and Collateral Constraints on Residential Mortgage Termination”, Regional Science and Urban Economics, 26: 235-261.
41.Yang, H. C. , Lin, T. Y. and Chen, T. H., 2007, “A Study on the Default Determination of Residential Mortgages: The Application of Bayes’ Theorem on Classification Adequacy”, the 12th Asian Real Estate Society (AsRES) Annual Conference and the 2007 AREUEA International Conference, Macao.
描述 碩士
國立政治大學
地政研究所
95257018
96
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0095257018
資料類型 thesis
dc.contributor.advisor 張金鶚zh_TW
dc.contributor.author (作者) 邱于修zh_TW
dc.contributor.author (作者) Chiou,Yu Shiouen_US
dc.creator (作者) 邱于修zh_TW
dc.creator (作者) Chiou,Yu Shiouen_US
dc.date (日期) 2007en_US
dc.date.accessioned 14-九月-2009 13:54:30 (UTC+8)-
dc.date.available 14-九月-2009 13:54:30 (UTC+8)-
dc.date.issued (上傳時間) 14-九月-2009 13:54:30 (UTC+8)-
dc.identifier (其他 識別碼) G0095257018en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/32404-
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) 95257018zh_TW
dc.description (描述) 96zh_TW
dc.description.abstract (摘要) 住宅為兼具消費及投資之雙重功能財貨,因此若從購屋動機劃分購屋族群,可以分為自住者及投資者,近年來受到國內房市呈現生氣蓬勃之景象及利率持續走低等總體經濟因素影響之下,出現越來越多以投資為主要目的之投資型購屋者,對於金融機構之購屋貸款業務來說,投資者之還款行為相較於自住者是比較不穩定的。故本文之研究目的即藉由探討自住者及投資者之購屋特徵異同,建立投資者之機率預測模型,預測某購屋者成為投資者之機率,提供一較為客觀之機率預測模型,供作金融機構放貸參考準則。接著進一步探討在不同機率界限(cutoff point)下之預測準確率,找出預測準確率最高之機率界限值,提高本模型之預測準確度;並探討金融機構在不同經營方針下之較適機率界限值。
     
本文使用台灣住宅需求動向季報之已購屋者問卷,建立二元羅吉特模型。研究結果顯示,區位在中心都市、高單價、小面積產品及大面積產品、預售屋及拍賣屋市場屬於投資型產品,而搜尋時間短、搜尋間數少、年齡較長、男性、無固定職業及家庭平均月收入較高者成為投資者之機率較高。接著,運用貝氏定理計算出預測準確率最高之機率界限值,結果當機率界限值為0.70時預測準確率最高,投資者達72.22%,自住者達80.07%。此外,並使用2007Q4的資料作樣本外驗證,投資者命中率為65.52%,自住者命中率為84.51%。最後,為提供金融機構運用,本文模擬兩種預測誤差在不同權重下對於金融機構所造成的損失,找出損失最少的機率界限值,結果皆是以0.70為最適機率界限值。
zh_TW
dc.description.abstract (摘要) Housing is dual function goods, consumption and investment, so if we separate the home buyers by their motives, they can be defined as two groups, owner-occupiers and investors. Recently, because the housing market is vigorous inland and the rates are fairly low, there are more and more home buyers buying houses for investment. To financial institutions, their payment behaviors are more instable, compare to owner-occupiers. So this article is aim to build a probability predictive model of housing investors by discussing the different home buying characters between owner-occupiers and investors. Therefore we can provide financing institutions a more objective method evaluating if they should lend money to the home buyers. Then we discuss the predictive accuracy with different cutoff points, finding the cutoff point with highest predictive accuracy, therefore we can elevate the model"s predictive accuracy. Besides, we also discuss the most optimal cutoff point for financial institutions under different administration principles.<br>This article builds binary logit model by the data of “Housing Demand Survey in Taiwan”. Our results suggests that if the houses in downtown、high unit price、big and small acreage、presale and court auction housing market belong to investing houses. And short search duration、few search items、older、male、non-constant job、higher income are getting higher probability to be housing investors. Then, we use Bayesian Theorem to figure out the cutoff point with highest predictive accuracy, and Our results suggests that 0.70 cutoff point with highest predictive accuracy , at that time, investor predictive accuracy is 72.22%, owner-occupier is 80.07%. Besides, we also do the out-sample test by the 2007Q4 data, the investor"s hit-rate is65.52%, the owner-occupier"s hit-rate is 84.51%. At the end, in order to provide financial institution to use, we give two predictive deviation different weights, to find the smallest loss cutoff point, the result all suggest that 0.70 is the most optimal cutoff point.en_US
dc.description.tableofcontents 目錄
     第一章 緒論..............................1
      第一節 研究動機與問題 ...................1
      第二節 研究範圍與方法....................4
      第三節 研究架構與流程....................5
     第二章 相關理論與文獻回顧..................7
      第一節 購屋貸款提前清償與違約.............7
      第二節 住宅消費與投資行為................10
      第三節 二元羅吉特模型....................15
     第三章 資料說明與樣本分析..................17
      第一節 資料說明.........................17
      第二節 樣本基本資料分析..................18
     第四章 實證分析...........................21
      第一節 模型建立與變數選取.................21
      第二節 實證結果分析......................26
      第三節 機率界限值探討....................31
      第四節 金融機構於不同經營策略下的運用......35
      第五節 樣本外資料驗證....................37
     第五章 結論與建議.........................39
      第一節 結論.............................39
      第二節 後續研究建議......................41
     參考文獻..................................42
     附錄一 住宅需求動向調查(2006Q4已購屋者)........i
     附錄二 銀行住宅抵押貸款放貸人員訪談記錄整理....iii
     附錄三 主要銀行對房市投資客控管概況.............v
     附錄四 台灣地區都會區分類.....................vi
     附錄五 給兩種誤差不同權重(較高)所造成的總損失...vii
zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0095257018en_US
dc.subject (關鍵詞) 投資型購屋者zh_TW
dc.subject (關鍵詞) 自住型購屋者zh_TW
dc.subject (關鍵詞) 二元羅吉特模型zh_TW
dc.subject (關鍵詞) 機率界限zh_TW
dc.subject (關鍵詞) housing investoren_US
dc.subject (關鍵詞) owner-occupieren_US
dc.subject (關鍵詞) binary logit modelen_US
dc.subject (關鍵詞) cutoff pointen_US
dc.title (題名) 投資型購屋者機率預測模型之建立zh_TW
dc.title (題名) The Probability predictive model of housing investorsen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 參考文獻zh_TW
dc.relation.reference (參考文獻) 1.王濟川、郭志剛,2004,『Logistic迴歸模型-方法及應用』二版,台北市:五南。zh_TW
dc.relation.reference (參考文獻) 2.王國川,2004,『圖解SAS視窗在迴歸分析上的應用』初版,台北市:五南。zh_TW
dc.relation.reference (參考文獻) 3.江百信、張金鶚,1995,「我國購屋貸款放款條件之研究」,『住宅學報』,3:1~20。zh_TW
dc.relation.reference (參考文獻) 4.沈庭增,2007,「都市仙丹─台北市『小套房』之空間生產與消費」,國立臺灣大學工學院建築與城鄉研究所碩士論文。zh_TW
dc.relation.reference (參考文獻) 5.李桐豪、呂美慧,2000,「在金融機構房貸客戶授信評量模式—以Logistic 迴歸分析」,台灣金融財務季刊,1(1):1-20。zh_TW
dc.relation.reference (參考文獻) 6.李馨蘋,1997,「住宅抵押貸款違約風險之實證分析」,國立臺灣工業技術學院管理技術硏究所博士論文。zh_TW
dc.relation.reference (參考文獻) 7.杜慶麟、張瑞芬,1998,「銀行授信決策應用神經網路之研究— 抵押貸款之實證研究」,『模糊系統學刊』, 4(1):31-44。zh_TW
dc.relation.reference (參考文獻) 8.林左裕、劉長寬,2003,「應用Logit模型於銀行授信違約行為之研究」, 2003年中華民國住宅學會第十二屆年會。zh_TW
dc.relation.reference (參考文獻) 9.林祖嘉、陳建良,2005,「租買選擇、貸款選擇、與世代組成:巢式Logit模型之應用」,『住宅學報』,14:1~20。zh_TW
dc.relation.reference (參考文獻) 10.花敬群、張金鶚,1993,「房地產投機行為之研究」,『經社法制論叢』,11:327~359。zh_TW
dc.relation.reference (參考文獻) 11.周美伶、張金鶚,2005,「購屋搜尋期間影響因素之研究」,『管理評論』,24(1):133~150。zh_TW
dc.relation.reference (參考文獻) 12.施恩,1994,「房屋貸款還款速度之硏究」,國立台灣大學商學硏究所碩士論文。zh_TW
dc.relation.reference (參考文獻) 13.張金鶚,2003,『房地產投資與市場分析理論與實務 上篇:房地產投資分析』初版,台北市:張金鶚出版:華泰總經銷。zh_TW
dc.relation.reference (參考文獻) 14.張梅音、鍾陳佳,2002,「住宅法拍屋屋屬性與拍定價格關係之研究--以台中市12樓以下集合住宅為例」,『土地問題研究季刊』,1(2):12-20。zh_TW
dc.relation.reference (參考文獻) 15.陳彥仲,1997,「住宅選擇之程序決策模式」,『住宅學報』,5:37-49。zh_TW
dc.relation.reference (參考文獻) 16.陳彥仲、吳京玲,1998,「家戶住宅區位選擇與地方財政分配之實證研究」,『都市與計劃』,25(2):223-238。zh_TW
dc.relation.reference (參考文獻) 17.陸劍清,2002,『投資心理學』初版,台北市:揚智文化。zh_TW
dc.relation.reference (參考文獻) 18.黃文啟,2002,「以LOGIT模型硏究借款人特性與不動產抵押貸款提前償還之關係」,國立政治大學財務管理學系硏究所碩士論文。zh_TW
dc.relation.reference (參考文獻) 19.劉展宏、張金鶚,2001,「購屋貸款提前清償行為之研究」,,『住宅學報』,10(1):29~49。zh_TW
dc.relation.reference (參考文獻) 20.劉代洋、李馨蘋,1994,購屋貸款與家戶社經特色之實證研究-以台中都會區為例,『管理科學學報』,11(1):109-127。zh_TW
dc.relation.reference (參考文獻) 21.賴麗華,1996,「住宅投資報酬率之硏究」,國立政治大學地政硏究所碩士論文。zh_TW
dc.relation.reference (參考文獻) 22.Allison, P. D., 1999, “Logistic Regression Using the SAS System:Theory and Application〔M〕”Cary NC: SAS Institute Inc.zh_TW
dc.relation.reference (參考文獻) 23.Alonso, W., 1964,”Location and Land Use: Toward a General Theory of Land Rent”, Cambridge, Massachusetts: Harvard University Press.zh_TW
dc.relation.reference (參考文獻) 24.Chua, K. W., and Hung, C. T., 2001,”Developer’s Good Will as Significant influence on Apartment Unit Prices”, The Appraisal Journal, 69(1): 26-30.zh_TW
dc.relation.reference (參考文獻) 25.Hsu, K. J., 1996,”A Model of Housing Consumption-Investment Behavior of Homeownership under Uncertainty”, Paper presented at the 35th WRSA Annual Meeting, Feb 26-28.zh_TW
dc.relation.reference (參考文獻) 26.Jan, K. B., 1997,”Consumption and Investment Motives and the Portfolio Choices of Homeowners”, Journal of Real Estate Finance and Economics, 15(2): 159-180.zh_TW
dc.relation.reference (參考文獻) 27.Lancaster, K.J., 1966,”A New Approach to Consumer Theory” Journal of Political Economy, 74:132-156.zh_TW
dc.relation.reference (參考文獻) 28.Lin, C. C. and Lin, S. J., 1999,”An Estimation of Elasticities of Consumption Demand and Investment Demand for Owner-Occupied Housing in Taiwan:A Two- Period Model ”,International Real Estate Review, 2: 110-125.zh_TW
dc.relation.reference (參考文獻) 29.Lin, T. C., 2004,”A Study on the Termination Behaviors of Residential Mortgages in Taiwan”, Journal of Agricultural Economics, 76:169-195.zh_TW
dc.relation.reference (參考文獻) 30.Mendard, S., 1995, “Applied Logistic Regression Analysis.” Thousand Oaks, CA: Sage Publication.zh_TW
dc.relation.reference (參考文獻) 31.McFadden, D., 1973,”Conditional Logit analysis and qualitative choice behavior”, in Frontiers in Economics, edited by P. Zaremka. New York: Academic Press.zh_TW
dc.relation.reference (參考文獻) 32.McFadden, D., 1978,”Modeling the choice of residential location”, Transportation Research Record, 673(1): 72-77.zh_TW
dc.relation.reference (參考文獻) 33.McFadden, D., and Manski, C. F., 1981,”Econometric models of probability choice and structural analysis of discrete data with choice”, in Economic Applications, edited by C. Manski and D. McFadden. MIT Press.zh_TW
dc.relation.reference (參考文獻) 34.Neter, J., Kutner, M. H., Nachtsheim, C. J., Wasserman, W., 1999,”Applied Linear Statistical Models” Fourth Edition. Mcgraw-Hill, Inc., 1999.zh_TW
dc.relation.reference (參考文獻) 35.Philips, R. A., Rosenblatt, E. and Vanderhoff, J. H., 1996,”The Probability of Fixed-Rate and Adjustable-Rate Mortgage Termination”, the Journal of Real Estate Finance and Economics, 13: 95-104.zh_TW
dc.relation.reference (參考文獻) 36.Quigley, J. M. and Robert V. O., 1991,”Defaults on Mortgage Obligations and Capital Requirements for U.S. Savings Institutions-a policy perspective”, Journal of Public Economics, 44: 353-369.zh_TW
dc.relation.reference (參考文獻) 37.Rosen, S., 1974,”Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition”, Journal of Political Economy, 82:34-55.zh_TW
dc.relation.reference (參考文獻) 38.Sirmans, C. F. and J. D. Benjamin, 1990,”Pricing Fixed Rate Mortgage: Some Empirical Evidence”, The Journal of financial Services Research, 4: 191-202.zh_TW
dc.relation.reference (參考文獻) 39.Swinburne, R., 2005,”Bayes’s Theorem.” Oxford University Press, New York.zh_TW
dc.relation.reference (參考文獻) 40.Wayne A., David, C. L. and Gary, A. M., 1996, “The Effect of Income and Collateral Constraints on Residential Mortgage Termination”, Regional Science and Urban Economics, 26: 235-261.zh_TW
dc.relation.reference (參考文獻) 41.Yang, H. C. , Lin, T. Y. and Chen, T. H., 2007, “A Study on the Default Determination of Residential Mortgages: The Application of Bayes’ Theorem on Classification Adequacy”, the 12th Asian Real Estate Society (AsRES) Annual Conference and the 2007 AREUEA International Conference, Macao.zh_TW