由於本研究資料限制關係,第二層次無法達到樣本數準則(24 個行政區小於 30 組),
建議後續研究者可遵從Kreft(1994)提出之樣本數(30⁄30)準則,將其研究第二層次提高至 30 組以上,而每組高於 30 人。Kreft 認為如此分析的結果才較具有類推性,也才可以適 用到不同的樣本預測上。
其次,我們租買選擇與命中率的研究,僅以台北市、新北市大台北地區為範圍,就 本研究實證結果之各自變數對租買選擇的影響與三種模型命中率等指標的優劣的判斷,
僅顯示該大台北地區的實證結果,非不同縣市或全國所一體適用。因為資料的來源與研 究目的與方法的不同,有可能會因時因地而顯示迥異的結果,後續研究者可針對不同縣 市或全國性的資料進一步作租買選擇相關的研究。
再者,有關未來研究建議方面,2014 年 7 月台灣各縣市實施新修訂之房屋稅課徵計 算方式,修訂後的稅率均較往年為高,如 3 戶以上的「囤屋稅」及台北市 7000 萬元、
新北市6000 萬元的豪宅課徵所謂「豪宅稅」(財政部賦稅署 http://www.dot.gov.tw,
2014-06-04)。又者,行 政 院 財 政 部 的 房 地 合 一 實 價 課 稅 方 案 , 已 於 2015.06.05 經 立 法 院 三 讀 通 過,2015.06.24 業 經 總 統 公 布,預期將於明年 2016 年付 諸 實 施 , 這 將 是 我 國 稅 制 改 革 上 的 重 要 政 策 (財政部賦稅署 http://www.dot.gov.tw , 2015.06.24)。這些稅改相對應的也皆加重家計部門擁房的成本,可考慮研究房屋租稅 及交易消費支出的增加對家戶部門租買選擇決策行為的影響。
61
參考文獻
一、中文文獻
1. 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》,1(1),pp.21-45。
2. 林祖嘉,1994,「臺灣地區住宅需求與租買選擇之聯合估計」,《國立政治大學學 報》,68(下),pp.183-200。
3. 林祖嘉、林素菁,1996,「住宅需求、住宅價格、與貸款成數」,《台灣經濟學會 年會論文集》,pp.203-220。
4. 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),pp.1-20。
5. 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),pp.1-22。
6. 林祖嘉、馬毓駿,2012,「貝氏多層次模型在台灣不動產市場估價之應用─以台北 市住宅建物為例」,《住宅學報》,21(1),pp.1-18。
7. 林秋瑾,1996,「穩健性住宅租金模式之探討—異常點之分析」,《住宅學報》,
4,pp.51-72。
8. 林素菁、林祖嘉,2001,「台灣地區住宅供給彈性之估計」,《住宅學報》,10(1),
pp.17-27。
9. 邱于修、周美伶、張金鶚,2013,「購屋者投資機率預測模型之探討」,《臺大管 理論叢》,23(2),pp.1-28。
10. 邱新雅、李春長、何宇明,2013,「個人條件、房屋屬性、私人借貸與租買選擇: 以 一般化階層線性模式分析」,國立屏東商業技術學院,不動產經營學系研究所碩士 論文。
11. 洪義雄、杜建衡,2009,「住宅抵押貸款信用風險之研究」,國立高雄應用科技大學,
金融資訊研究所碩士論文。
62
12. 邵凱揚,2012,「自備款來源對購屋負擔與購屋行為關係之研究」,玄奘大學,財 務金融學系研究所碩士論文。
13. 陳淑美、張金鶚、陳建良,2002,「家戶遷移與居住品質變化關係之研究─台北縣 市的實證分析」,《住宅學報》,13(1),pp.51-74。
14. 陳銘祥,2004,「一般優惠房貸公平性之影響分析」,國立政治大學,地政學系碩
士論文。
15. 陳俊麟,2013,「運用支撐向量機預測台北市住宅價格」,國立屏東商業技術學院,
不動產經營系(所)碩士論文。
16. 傅美生,1984,「台北都會區住宅權屬與住宅類型選擇之研究─Logit模型之應用」,
國立中興大學,都市計畫研究所碩士論文。
17. 黃佳盛,1997,「台中市民對鄰里公園植栽綠地滿意度之研究」,國立中興大學,園 藝學系。
18. 黃嘉興、謝永明、劉宗哲,2005,「房屋抵押貸款客戶違約預測模式之比較研究」,
《東吳經濟商學學報》,48,pp.103-126。
19. 謝文盛、林素菁,2000,「租稅效果對住宅租買選擇影響之分析」,《住宅學報》
9(1),pp.1-17。
20. 謝博明,2006,「台灣家庭所得與住宅消費之分配與變動:1980-2000」,《住宅學 報》,15(1),pp.59-78。
21. 薛立敏、陳綉里,1997,「台灣一九八0年代住宅自有率變化之探討」,《住宅學 報》,6,pp.27-48。
22. 薛立敏、陳琇里,1998,「住宅租擁選擇下家計消費支出之比較」,《住宅學報》
,7,pp.21-40。
23. 陳順宇,2005,四版,多變量分析,華泰文化。
24. 溫福星,2006,初版二刷,階層線性模式原理、方法與應用,雙葉書廊。
25. 內政部營建署,2015,「2014年第四季住宅需求動向調查」,12(4)。
63
26. 臺灣行政院主計處,2014,「2013年家庭收支調查報告」,《行政院主計總處2014年 年報》。
二、英文文獻
1. Agresti, A. (2002), “Categorical data analysis”, 2nd ed, New Jersey, Wiley-Interscience.
2. Andersen, H. S. (2011), “Motive for Tenure Choice during the Life Cycle: the Importance of Non-economic Factors and other Housing Preference”, Housing Theory and Society, 28(2), pp.183-207.
3. Barrios, V. E., Colom, M. C., and Moles, M. C. (2013), “Life Cycle and Housing Decisions:
A Comparison by Age Cohorts”, Applied Economics, 45(32), pp.4556-4568.
4. Bazyl, M. (2009), “Factors Influencing Tenure Choice in European Countries”, Social Science Research Network, SOEP paper No. 186.
5. Bonaiuto, M., Fornara, F., and Bonnes, M. (2003), “Indexes of Perceived Residential En-vironment Quality and Neighborhood Attachmentin Urban EnEn-vironments: A Confirmation Study on the City of Rome”, Landscape and Urban Planning, 65(1-2), pp.41-52.
6. Bonaiuto, M., Fornara, F., and Bonnes, M. (2006), “Perceived Residential Environmental Quality in Middle- and Low-extension Italian Cities”, European Review of Applied Psy-chology, 56(1), pp.23-34.
7. Bridge, H. S., Belcher, J. W., Lazarus, A. J., Sullivan, J. D., McNut, R. L., Bagenal, F., Scudder, J. D., Sittler, E. C., Siscoe, G. L., Vasyliunas, V, M., Goertz, C. K., and Yeates, C.
M. (1979), “Plasma observations near Jupiter: Initial results from Voyager” Science, 204(4396), pp. 987-991.
8. Bryk, A. S. and Raudenbush, S. W. (1988), “Toward a more appropriate conceptual-ization of research on school effects: A three-level hierarchical linear model”, American Journal of Education, 97(1), pp.65-108.
64
9. Brown, K. and Uyar, B. (2004), “A Hierarchical Linear Model Approach for Assessing the Effects of House and Neighborhood Characteristics on Housing Prices”, American Real Estate Society, 7(1), pp.15–24.
10. Can, A. (1990), “The Measurement of Neighborhood Dynamics in Urban House Prices”, Journal of Economic Geography, 66(3), pp.254-272.
11. Cannaday, R. E. and Sunderman, M. A. (1986), “Estimation of Depreciation for Sin-gle-family Appraisals”, Real Estate Economics, 14(2), pp.255-273.
12. Cardozo, R. N. (1965), “An Experimental Study of Consumer Effort, Expectation and Satisfaction”, Journal of Marketing Research, 2(3), 244-249.
13. Carter S. (2007), “Housing Tenure Choice and the Dual Income Household”, Deparment of Economics University of California, Irvine.
14. Chambers, M. S., Garriga, C., and Schlagenhauf, D. (2009), “The Loan Structure and Housing Tenure Decisions in an Equilibrium Model of Mortgage Choice”, Review of Economic Dyanmics, 12(3), pp.444-468.
15. Clark, W. A. V. and Onaka, J. L. (1985), “An Empirical Rest of a Joint Model of Residen-tial Mobility and Housing Choice”, Environment and Planning A, 17(7), pp.915-930.
16. Clark, W. A. V. and Dieleman, F.M. (1996), “Households and Housing: Choice and Out-comes in the Housing Market”, Center for Urban Policy Research.
17. Cochran, W. G. (1977), “Sampling Techniques (3rd edition)”, New York: Wiley.
18. Colom, M. C. and Moles, M. C. (2013), “Housing and Labor Decisions of Households”, Review of Economics of the Household, 11(1), pp.55-82.
19. DiPasquale D. (1996), “Urban Economics and Real Estate Markets”, Prentice Hall, Eng-lewood Cliffs, NJ.
20. Feng, Y. and Jones, K. (2015), “Comparing Methods: Using Multilevel Modelling and Artificial Neural Networks in the Prediction of House Prices based on property, location
65
and neighbourhood characteristics”, School of Geographical Sciences, University of
Bristol.
21. Floor, H., Kempen, R. V., and Vocht, A. D. (1996), “Leaving Randstad Holland: An Analysis of Housing Preferences with Decision Plan Nets”, Netherlands journal of hous-ing and the built environment, 11(3), pp.275-296.
22. Fotheringham, A. S., Brunsdon, C., and Charlton, M.E. (1998), “Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis”, Environment and Planning A, 30(11), pp. 1905-1927.
23. Francke, M. K. and Vos, G.A. (2004), “The Hierarchical Trend Model for Property Valu-ation and Local Price Indices”, Journal of Real Estate and Economics, 28(2-3), pp.
179-208.
24. Frew, J. and Jud, G. D. (2003), “Estimating the Value of Apartment Buildings”, Journal of Real Estate Research, 25(1), pp.77–86.
25. Gillingham, R. and Hagemann, R. (1983), “Cross-Sectional Estimation of a Simultaneous Model of Tenure Choice and Housing Service Demand”, Journal of Urban Economics, 14(1), pp.16-39.
26. Goodman, A. C. and Thibodeau, T.G. (1995), “Age-Rela House Price Equations”, Jour-nal of Housing Research, 6(1), pp.25-42
27. Gyoruko, J. (2001), “Access to Homeownership in the United States: The Impact of Changing Perspectives on Constraints to Tenure Choice”, Martin Bucksbaum Professor of Real Estate and Finance, The Wharton School, University of Pennsylvania.
28. Haurin, D. R., Parcel, T. L., and Haurin, R. J. (2002), “Does Homeownership Affect Child Outcomes?”, Real Estate Economics, 30(4), pp.635-666.
29. Heck, R. H. and Thomas, S. L. (2009), “An introduction to multilevel modeling tech-niques”, (2nd ed.), New York: Routledge.
66
30. Hendershott, P. H., Ong, R., Wood, G. A., and Flatau, P. (2009), “Marital History and Home Ownership: Evidence from Australia”, Journal of Housing Economics, 18(1), pp.13-24.
31. Henderson, J. V. and Ioannides, Y. M. (1983), “A Model of Housing Tenure Choice”, The American Economic Review, 73(1), pp.98-113.
32. Henley, A. (1998), “Residential Mobility, Housing Equity and the Labour market”, The Economic Journal, 108(447), pp.414-427.
33. Ho, M. H. C. (2006), “Determinants of Cross-border Tenure Choice Decision”, Habitat International, 30(1), pp.144-156.
34. Hofmann, D. A. and Gavin, M. B. (1998), “Centering Decisions in Hierarchical linear Models: Implications for Research in Organizations”, Journal of Management, 24(5), pp.623–641.
35. Huang, Y. and Clark, W. A. V. (2002), “Housing Tenure Choice in Transitional Urban China:A Multilevel Analysis”, Urban Studies, 39(1), pp.7–32.
36. Hsueh, L. M. and Chen, H. L. (1999), “An Analysis of Home Ownership Rate Changes in Taiwan in the 1980s”, Asian Economic Journal, 13(4), pp.367-388.
37. Ioannides, Y. M. and Zabel, J. E. (2003), “Neighborhood Effects and Housing Demand”, Journal of Applied Econometrics, 18(5), pp.563-584.
38. Ioannides, Y. M. and Zabel, J. E. (2008), “Interactions, Neighborhood Selection and Housing Demand”, Journal of Urban Economics, 63(1), pp.229-252.
39. James, H. (1997), “The Application of Artificial Intelligence to Mass Appraisal Systems”, Computer Assisted Mass Appraisal.
40. Kontrimas, V. and Verikas, A. (2011), “The Mass Appraisal of the Real Estate by Com-putational Intelligence”, Applied Soft Computing, 11(1), pp.443-448.
41. Kreft, I. G. G. and Leeuw, J. D. (1988), “Introduting Multilevel Modeling”, Sage Publi
67
cations Ltd.
42. Lang, B. J. and Hurst, E. H. (2013), “The Effect of Down Payment Assistance on Mort-gage Choice”, The Journal of Real Estate Finance and Economics, 49(3), pp.329-351.
43. Lee, C. C. (2009), “Hierarchical linear modeling to explore the influence of satisfaction with public facilities on housing prices”, International real estate review, 12(3), pp.252-272.
44. Lee, C. C. (2010), “The impact of facilities of leisure and sports on housing prices in Taiwan: An Application of Hierarchical Linear Modeling”, Journal of Real Estate Prac-tice and Education, 13(2), pp.159-175.
45. Lee, C. C., Lin, S.Z., You, S.M., and Shang, J.K. (2012), “A comparison of regular and franchise systems in the real estate brokerage in terms of operating efficiency: Applica-tion of the data envelopment analysis”, African Journal of Business Management, 6(25), pp.7431-7438.
46. Lercher, P. (2003), “Which Health Outcomes Should Be Measured in Health Related En-vironmental Quality Studies? ”, Landscape and Urban Planning , 65(1-2), pp.63-72.
47. Leung, Y., Mei, C.L., and Zhang, W.X. (2000), “Statistical Tests for Spatial Nonstationarity Based on the Geographically Weighted Regression Model”, Environment and Planning A, 32(1), pp.9-32.
48. Leung, Y., Mei, C.L., and Zhang, W.X. (2000), “Testing for Spatial Autocorrelation among the Residuals of the Geographically Weighted Regression”, Environment and Planning A, 32(5), pp.871-890.
49. Lewis, C. D. (1982), “Industrial and Business Forecasting Methods”, London:
Butterworths Scoentific.
50. Lin, C. C. S. (1993), “The Relationship between Rents and Prices of Owner-occupied Housing in Taiwan”, Journal of Real Estate Finance and Economics, 6(1), pp.25-54.
68
51. Lockword, L. J. and Rutherford, R.C. (1996), “Determinants of Industrial Property Val-ue”, Real Estate Economics, 24(2), pp.257-272.
52. Maas, C. J. M. and Hox, J. J. (2004), “Robustness Iissues in Multilevel Regression Anal-ysis”, Statistics Neerlandica, 58(2), pp.127-137
53. Maas, C. J. M. and Hox, J. J. (2004), “The Influence of Violations of Assumptions on Multilevel Parameters and Their Standard Errors”, Computational Statistics and Data Analysis, 46(3), pp.427-440.
54. Mathieu, J. E., Gilson, L. L., and Ruddy, T. M. (2006), “Empowerment and team effec-tiveness: an empirical test of an integrated model”, Journal of Applied Psychology, 91(1), pp.97-108.
55. McCluskey, W. J. and Borst, R.A. (1997), “An Evaluation of MRA, Comparable Sales Analysis and ANNs for the Mass Appraisal of Residential Properties in Northern Ireland”, Assessment Journal, 4(1), pp.47-55.
56. Mathieu, J. E. and Taylor, S. R. (2007), “A Framework for Testing MesoMediational Re-lationships in Organizational Behavior”, Journal of Organization Behavior, 28(2), pp.
141-172.
57. McGraw, K. O. and Wong, S. P. (1996), “Forming inferences about someintraclass cor-relation coefficients”, Psychological Methods, 1(1), pp.30-46.
58. Moriizumi, Y. and Naoi, M. (2011), “Unemployment Risk and the Timing of Homeown-ership in Japan”, Regional Science and Urban Economics, 41(3), pp.227-235.
59. Morrow-Jones, H. A. (1988), “The Housing Life-cycle and the Transitionfrom Renting to Owning a Home in the United States”, Environment and Planning A, 20(9), pp.1165-1184.
60. Mossman, D. (1994), “Assessing predictions of violence: Being accurate about accuracy”
Journal of Consulting and Clinical Psychology, 62(4), pp.783-792.
69
61. Muthen, B. O. and Satorra, A. (1995), “Complex Sample Data in Structural Equation Modeling”, Sociological Methodology, 25, pp. 267-316.
62. Nguyen, N. and A. Cripps. (2001), “Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks”, The Journal of Real Estate Re-search, 22(3), pp.313-336.
63. O’Connell, A. A. and McCoach, D. B. (2008), “Multilevel Modeling of Education Data, Charlotte”, Information Age Publishing, Inc.
64. Opoku, R. A. and Abdul-Muhmin, A. G. (2010), “Housing Preferences and Attribute Iimportance Among Low-income Consumers in Saudi Arabia”, Habitat International, 34(2), pp.219-227.
65. Pace, R. K., Barry, R., and Sirmans, C.F. (1998), “Spatial Statistics and Real Estate”, Journal of Real Estate Finance and Economics, 17(1), pp. 5-13.
66. Paulin, G. D. (1995), “A Comparison of Consumer Expenditure by Housing Tenure”, The Journal of Consumer Affairs, 29(1), pp. 164-198.
67. Poll, R. V. (1997), “The Perceived Quality of the Urban Residential Environment: A Multi-attribute Evaluation”, Ph.D. Dissertation, University of Groningen.
68. Praag, B. V. and Ferrer-i-Carbonell, A. (2004), “Happiness Quantified: A Satisfaction Calculus Approach”, New York: Oxford University Press.
69. Quinsey, V. L., Harris, G. T., Rice, M. E., and Cormier, C. A. (1998), “Violent offenders:
Appraising and managing risk. Washington”, American Psychological Association.
70. Raudenbush, S. W. and Bryk, A. S. (2002), “Hierarchical Linear Models: Applications and Data Analysis Methods”, SAGE Publications, Inc.
71. Rice, M. E. and Harris, G. T. (1995), “Violent recidivism: Assessing predictive validity”, Journal of Consulting and Clinical Psychology, 63(5), pp.737-748.
72. Rouwendal, J. and Nijkamp, P. (2007), “Homeownership and Labour Market Behaviour:
70
Interpreting the Evidence”, Environment and Planning A,42(2), 419 -433.
73. Sanchez, T. W. and Dawkins, C.J. (2001), “Distinguishing City and Suburban Movers:
Evidence from the American Housing Survey”, Housing Policy Debate, 12(3), pp.607-631.
74. Schuiz, R. and Werwatz, A. (2004), “A State Space Model for Berlin House Prices: Es-timation and Economic Interpretation”, Journal of Real Estate Finance and Economics, 28(1), pp.37-57.
75. Sing, T. F., Ho, D. K. H. and Tay, D. P. H. (2002), “A Fuzzy Discounted Cash Flow Analysis for Real Estate Investment”, Real Estate Valuation Theory, 8, pp.389-410.
76. Spalkova, D. and Spalek, J. (2012), “Factors of the Tenure Choice: the Case of the Czech Republic”, Masaryk University.
77. Snijders, T. A. B. and Bosker, R. (1999), “Multilevel analysis : An introduction to basic and advanced multilevel modeling”, Sage, London.
78. Subhan S. and Ahman E. (2012), “The Economic and Demographic Effects on Housing Tenure Choice in Pakistan”, American International Journal of Contemporary Research, 2(7), pp.15-24.
79. Summers, A. A. and Wolfe, B. L. (1977), “Do schools make a difference”, American Economic Review, 67(4), pp.639-652.
80. Tabachnick, B. G. and Fidell, L. S. (2007), “Using Multivariate Statistics”, Boston, Allyn and Bacon.
81. Tiwari P. (2000), “Housing Demand in Tokyo”, International Real Estate Review, 3(1), pp.65-92.
82. Uno, H., Cai, T., Pencina, M. J., Agostino, R. B., and Wei, L. J. (2011), “On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data”, Statistics in Medicine, 30(10), pp.1105-1117.
71
83. Vera-Toscano, E. and Ateca-Amestoy, V. (2008), “The Relevance of Social Interactions on Housing Satisfaction”, Social Indicators Research, 86(2), pp.257-274.
三、其他 網站
1、行政院主計處 http://www.dgbas.gov.tw/mp.asp?mp=1,2015 年。
2、內政部營建署 http://www.cpami.gov.tw/chinese/index.php,2015 年。
3、中華民國統計資訊網 http://ebas1.ebas.gov.tw/pxweb/Dialog/statfile9.asp,2015 年。
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附錄二、各變數租買次數及百分率統計表
TENU 購買(N=2500) 租賃(N=531) 第一層變數
類別變數 類別 購買次數 百分比 租賃次數 百分比
GENDER 男性 1983 79.3 403 75.9
女性 517 20.7 128 24.1
EDU 國中以下 630 25.2 136 25.6
高中職 709 28.4 162 30.5
專科 515 20.6 101 19.0
大學以上 646 25.8 132 24.9
LOANR 貸款成數大於 0.5 1354 54.2 0 0 貸款成數小於等於 0.5 1146 45.8 531 100 PMORTGAGE 無私人借貸 1790 71.6 531 100 私人借貸在 1 至 50 萬 604 24.2 0 0
私人借貸大於 50 萬以上 106 4.2 0 0
PRELOAN 無政府優惠貸款 1691 67.6 531 100
有政府優惠貸款 809 32.4 0 0
連續變數 租 0 買 1 最小值 最大值 平均數 標準差
PAGE 1 21 92 49.03 12.07
0 20 93 43.83 12.27
HAGE 1 1 94 22.35 11.85
0 1 94 23.85 12.28
PAREA 1 2 75 9.82 6.16
0 2 95 9.64 7.24
PROOM 1 0.07 8 1.07 0.53
0 0.07 5 1.05 0.56
FMSZ 1 1 16 4.12 1.67
0 1 13 3.69 1.75
第二層變數
變數 租 0 買 1 最小值 最大值 平均數 標準差
ENVI 1 3.17 4.89 3.66 0.28
0 3.31 4.89 3.65 0.31
LEIS 1 2.93 4.75 3.38 0.32
0 2.93 4.75 3.38 0.36
資料來源:本研究整理。
75
附錄三、各行政區 ENVI 與 LEIS 滿意度一覽表
附錄三、各行政區 ENVI 與 LEIS 滿意度一覽表