Luận văn thạc sĩ 2015 ứng dụng mô hình hedonic xác định các nhân tố ảnh hưởng đến giá nhà ở trên địa bàn quận 11, TPHCM

P T NG GIA MIÊU HEDONIC 11, 2015 T NG GIA MIÊU HEDONIC Chuyên ngành: ) 60310105 10 tháng 1 1 2.1 2.1.1 2.1.2 2.2 2.2.1 2.2.2 10 2.2.3 11 2.2.4 11 2.2.5 13 2.2.6 16 2.3 n 17 2.3.1 17 2.3.2 19 2.3.3 20 2.4 Mơ hình Hedonic 23 2.4.1 23 2.4.2 25 2.4.3 30 34 3.1 34 3.2 34 3.2.1 34 3.2.2 35 3.3 36 3.3.1 36 3.3.2 37 3.4 42 3.5 42 3.6 42 43 4.1 Quy trình phân tích 43 4.2 44 4.2.1 44 4.2.2 49 4.3 50 4.3.1 50 4.3.2 -Watson 50 4.3.3 50 4.4 53 4.4.1 53 4.4.2 54 4.4.3 55 4.4.4 55 4.4.5 56 4.5 57 4.6 57 4.7 58 60 5.1 60 5.1.1 60 5.1.2 5.1.3 5.2 62 62 63 DAT HCM HM KC LG NHA TP VT Mơ hình Hedonic 2.1 147 quan sát 44 -Watson 50 52 4.2 54 4.5 57 Hình 3.1 34 Hình 3.2 36 Hình 4.1 phân tích 43 45 45 46 DAT 46 e n NHA 47 f LG 47 g ST 48 48 49 52 54 55 56 1 ) khác Theo phân có liên quan p , ác có n n trò nh qua các (Pagourtzi et al., 2003) n Adair, A.S., Greal, S., Smyth, A, Cooper, J & Ryley, T., 2000 House prices and accessibility: The testing of relationships within the Belfast urban area Housing Studies, voll A.T Court., 1939 House price index with Automotive Examples Automobile Manufacturers Association, pp 99 119 Benson, E.D., Hansen, J L., Schwartz, A.L & Smersh, G.T., 1998 Pricing residential amenities: The value of a view Journal of Real Estate Finance and Economics Bernardo P M, et al., August 2002 Hedonic price model and smell consequences of sewage treatment plants in Urban areas Economics of air pollution, no 234, pp 25 Bloomquist, G and Worley, L., 1981 Hedonic prices, demands for urban housing attributes and benefit estimates Jourmal of Real Estates Finance and Economics Brasington, Diane Hite, 2008 A mixed index approach to indentifying hedonic price models Regional Science and Urban Economics, vol.38, pp.271-284 Brown, James N and Harvey S.Rosen., 1982 On the Estimation of Structural Hedonic Price Models Econometrica 50, pp 765- 768 Case, B.J., Clapp, R., Dubin & M., Rodriguez, 2004 Modelling spatial and temporal house price patterns: a comparision of four model Journal of Real Estate Finance and Economics, vol 29, issue 2, pp 167-191 Colwell, P F & Dillmore, G., 1999 Who was first? An examination of an early hedonic study Land Economics Fan Meng, Ye Wang, Jing Li, 2013 An Approach to buil industry asset price index: Take Four Industries for examples Procedia Computer Science Gabriel Kayode Babawale, 2011 The impact of Neighbourhood Churches on House Prices Vol 4, pp 246 253 Genesee, D and C.J Mayer Equity and Time to Sale in the real Estate Market American Economic Review Goodman, Allen C., 1998 Andrew Court and The invention of Hedonic price analysis Journal of Urban Economics, vol.44, pp 291 298 Goodman, A and T Thibodeau Dwelling Age Heteroscedasticity in Repeat Sales House Price Equations Real Estates Economics Griliches, Z., ed., 1971 Price Indexes and Quality Changes: Studies in New Methods of Measurement Cambridge, Mass: Harvard U Press Hasan Selim, 2009 Determinants of house prices in Turkey: Hedonic regression versus artificial neural network Expert Systems with Applications, pp 2843 2852 James Follain, Gill-Chin Lim, Bertrand Renaud, 1980 The demand for housing in developing countries: The case of Korea Journal of Urban Economics James R Follain Jr., Stephen Malpezi, 1981 The flight to the suburbs: Insights gained from an analysis of central-city vs suburban housing cost Journal of Urban Economics Jud, G D and Seaks, T G, 1994 Sample selection bias in estimating housing sales Price Journal of Real Estate Research, no.9, pp 289 297 Kim, 2007 The impact of Social Norms in the Market Pricing of Private Property Right in VietNam North Versus South, vol 35, pp.2079 2095 Kim, S.,2005 Search Hedonic price and Housing Demand, Review of Economics and Statistics Knight, J R., 2002 Listing Price, Time on Market, and Ultimate Selling Price: Causes and Effects of Listing Price Changes Real Estate Economics Knight, J R, C F Sirmans and G Tumbull, List Price Signaling a Buyer Behavior in the Housing Market Journal of Real Estate Finance and Economics Kwang Sik Kim, Sung Joong Park, Young-Jun Kweon., 2005 Highway traffic noise effects on land price in an urban area Transportation Research Part D: Transportand Environment, vol 12, pp.275-280 Lancaster K J., 1966 A New Approach to Consumer Theory Journal of Political Economy, pp.132 157 M Dalton, G Finlayson, 2013 Hedonics, satiation and satiety, Satiation, satiety and Control of Food Intake, pp 221 237 Malpezzi, S., 2002 Hedonic Pricing Models: A Selective and Applied Review, in Housing Economics and Public Policy Essays in Honor of Duncan Maclennan Palmquist R., 1980 Estimating the demand for characteristics of housing The review of Economic and Statistics, vol.66, no.3, pp.304-404 Paul M Anglin., 2006 Value and liquidity under changing market conditions; Original Research Article Journal of Housing Economics, vol 15, pp.293-304 Raymond B Palmquist., 1979 Hedonic price and depreciation indexes foe residential housing: A comment Journal of Urban Economics Ridker, R.G., 1967 Economic Cost of Air Pollution: Studies and Measure Praeger, New York Ridker, Ronald G., and John A Henning, 1967 The Determinants of Residential Property Values with Special Reference to Air pollution The Review of Economic and Statistics, vol.49, no.2, pp 246 257 Rober Halvorsen, Henry O Pollakowski, 1981 Choice of functional form for hedonic price equations Journal of Urban Economics Rosen S., 1974 Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition Journal of Political Economics, pp 34 55 Simon Stevenson, 2004 New empirical evidence on heteroscedasticity in hedonic housing models Journal of Housing Economics Timothy J Dalton, 2004 A household hedonic model of rice traits: economic values from farmers in West Africa Agricultural Economics, Vol31, pp.149-159 Ustaoglu, E., 2003 Hedonic price analysis of office rent: A case study of office market in Ankara Middle East Technical University, Unpublished MSc Thesis Wang, K.O and Wolverton, 1999 Real Estate Valuation Theory Journal of Housing Economics Wayne R Archer, Dean H Gatzlaff, David C Ling, 1996 Measuring the Importance of Location in House Price Appreciation Journal of Urban Economics, vol.40, pp.334-353 Wayne R Archer, David C Ling, Gary A McGill, 1997 Demographic versus Option-Driven Mortgage Terminations Journal of Housing Economics THÔNG TIN CHUNG Khác Khác 2.1 khuôn viên: ) ) ) ký STT (2002) Selim S (2008) Selim H (2009) Gabriel K.B (2011) OgWang Wang (1999) (2001) Messe Wallace (2003) Stevenson (2004) pháp ANN STT 10 Kim Park (2005) 11 12 13 14 (2006) Kim (2007) Minh Correlations LnPrice Pearson Correlation LnPrice Pearson Correlation VT DAT NHA LG ST KC 147 698** 698** 764** 558** 712** -.186* -.234** 000 Sig (2-tailed) N VT 000 000 000 024 004 147 147 147 147 147 147 345** 245** 767** -.170* -.223** 000 003 000 040 007 147 147 147 147 147 612** 333** -.105 -.043 000 000 207 602 147 147 147 147 166* -.506** -.195* 045 000 018 Sig (2-tailed) 000 N 147 147 764** 345** Sig (2-tailed) 000 000 N 147 147 147 558** 245** 612** Sig (2-tailed) 000 003 000 N 147 147 147 147 147 147 147 712** 767** 333** 166* -.120 -.069 000 000 000 045 148 409 Pearson Correlation DAT Pearson Correlation NHA Pearson Correlation LG Sig (2-tailed) N Pearson Correlation ST Sig (2-tailed) N 147 147 147 147 147 147 147 -.186* -.170* -.105 -.506** -.120 269** 024 040 207 000 148 001 147 147 147 147 147 147 147 -.234** -.223** -.043 -.195* -.069 269** Sig (2-tailed) 004 007 602 018 409 001 N 147 147 147 147 147 147 Pearson Correlation KC ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) 147 Model Summary Model R R Square Std Error of the Square 935a Adjusted R Estimate 874 869 Durbin - Watson 24777 a Predictors: (Constant), VT, DAT, NHA, LG, KC, ST b 1.778 Dependent Variable: LnPrice ANOVAa Model Sum of Squares Regression Mean Square F 59.620 9.937 140 161.861 Sig .000b 061 68.214 Total 8.595 Residual df 146 a Dependent Variable: LnPrice b Predictors: (Constant), VT, DAT, NHA, LG, KC, ST Coefficientsa Model Unstandardized Standardized Coefficients t Sig Coefficients 95.0% Collinearity Statistics Confidence Interval for B B Std Beta Lower Bound Error (Constant) 21.918 248 VT 238 067 174 DAT 009 NHA Upper Tolerance VIF Bound 88.319 000 3.544 001 105 371 372 2.688 001 474 11.221 000 007 010 504 1.984 001 000 163 3.514 001 000 002 417 2.398 LG 026 003 391 8.141 000 020 033 389 2.570 KC -.134 033 -.132 -4.086 000 -.199 -.069 866 1.155 ST 109 070 058 1.551 123 -0.30 248 643 1.555 a Dependent Variable: LnPrice b Predictors: (Constant), VT, DAT, NHA, LG, KC, ST 21.427 22.408 Residuals Statisticsa Minimum Predicted Value Maximum Mean Std Deviation N 21.2107 24.4759 22.1261 63903 147 -1.432 3.677 000 1.000 147 030 170 050 020 147 Adjusted Predicted Value 21.2244 25.0282 22.1311 65686 147 Residual -.65451 68128 00000 24263 147 Std Residual -2.642 2.750 000 979 147 Stud Residual -3.429 2.817 -.009 1.020 147 -1.16942 71532 -.00502 26675 147 -3.570 2.891 -.009 1.030 147 Mahal Distance 1.085 67.962 5.959 7.520 147 Cook's Distance 000 1.503 017 124 147 Centered Leverage Value 007 465 041 052 147 Std Predicted Value Standard Error of Predicted Value Deleted Residual Stud Deleted Residual a Dependent Variable: LnPrice Descriptive Statistics Giá tr trung bình Price 133 10000000 19000000 45976691 33637278 00.00 000.00 72.9323 39.85765 22.0437 2.030 210 4.940 417 62303 378 210 -.173 417 LnPrice 133 20.72 23.67 DAT 133 11.30 145.30 49.2898 24.59135 1.604 210 2.921 417 NHA 133 17.50 457.00 111.1550 72.55650 1.484 210 3.435 417 LG 133 2.50 40.00 14.1286 9.72450 937 210 -.130 417 KC 133 6.20 8.80 7.5000 57787 -.056 210 -.657 417 VT 133 00 1.00 4361 49777 261 210 -1.962 417 ST 133 00 1.00 8797 32654 -2.361 210 3.629 417 Valid N (listwise) 133 Descriptive Statistics Mean LnPrice Std Deviation N 22.0437 62303 133 4361 49777 133 DAT 49.2898 24.59135 133 NHA 111.1550 72.55650 133 LG 14.1286 9.72450 133 ST 8797 32654 133 KC 7.5000 57787 133 VT Correlations LnPrice Pearson LnPrice Correlation VT DAT NHA LG ST KC 1.000 755 778 550 754 -.124 -.211 VT 755 1.000 473 356 794 -.141 -.171 DAT 778 473 1.000 653 419 -.049 -.050 NHA 550 356 653 1.000 217 -.516 -.139 LG 754 794 419 217 1.000 -.076 -.082 ST -.124 -.141 -.049 -.516 -.076 1.000 197 KC -.211 -.171 -.050 -.139 -.082 197 1.000 000 000 000 000 077 007 Sig (1- LnPrice tailed) VT 000 000 000 000 053 024 DAT 000 000 000 000 286 285 NHA 000 000 000 006 000 055 LG 000 000 000 006 192 173 ST 077 053 286 000 192 012 KC 007 024 285 055 173 012 LnPrice 133 133 133 133 133 133 133 VT 133 133 133 133 133 133 133 DAT 133 133 133 133 133 133 133 NHA 133 133 133 133 133 133 133 LG 133 133 133 133 133 133 133 ST 133 133 133 133 133 133 133 KC 133 133 133 133 133 133 133 N Variables Entered/Removeda Model Variables Entered Variables Removed KC, DAT, ST, LG, VT, NHAb Method Enter a Dependent Variable: LnPrice b All requested variables entered Model Summaryb Adjusted R Model R Square R Square 929a Std Error of the Estimate 863 857 Durbin-Watson 23575 1.515 a Predictors: (Constant), KC, DAT, ST, LG, VT, NHA b Dependent Variable: LnPrice ANOVAa Model Sum of Squares Regression df Mean Square F 44.236 7.373 7.003 126 51.238 132.653 000b 056 132 Residual Total Sig a Dependent Variable: LnPrice b Predictors: (Constant), KC, DAT, ST, LG, VT, NHA Coefficientsa 95.0% Unstandardized Standardized Confidence Collinearity Coefficients Coefficients Interval for B Statistics Std Model (Constant) B Error Lower Beta T Sig 76.987 000 Upper Tolera Bound Bound nce VIF 21.826 283 VT 213 072 170 2.939 004 070 356 324 3.087 DAT 012 001 463 8.744 000 009 014 386 2.588 NHA 001 000 098 1.701 091 000 002 324 3.091 LG 025 004 396 7.076 000 018 032 346 2.886 ST 051 083 027 613 541 -.114 216 568 1.762 KC -.127 037 -.118 -3.449 001 -.200 -.054 933 1.071 a Dependent Variable: LnPrice 21.265 22.387 Correlations LnPrice Pearson LnPrice Correlation VT DAT LG KC LnNha 1.000 755 778 754 -.211 523 VT 755 1.000 473 794 -.171 327 DAT 778 473 1.000 419 -.050 609 LG 754 794 419 1.000 -.082 193 KC -.211 -.171 -.050 -.082 1.000 -.141 523 327 609 193 -.141 1.000 000 000 000 007 000 VT 000 000 000 024 000 DAT 000 000 000 285 000 LG 000 000 000 173 013 KC 007 024 285 173 052 LnNha 000 000 000 013 052 LnPrice 133 133 133 133 133 133 VT 133 133 133 133 133 133 DAT 133 133 133 133 133 133 LG 133 133 133 133 133 133 KC 133 133 133 133 133 133 LnNha 133 133 133 133 133 133 LnNha Sig (1-tailed) N LnPrice Variables Entered/Removeda Model Variables Entered Variables Removed LnNha, KC, LG, DAT, VTb Method Enter a Dependent Variable: LnPrice b All requested variables entered Model Summaryb Std Error of the Model R R Square 930a Adjusted R Square 864 Estimate 859 Durbin-Watson 23409 1.455 a Predictors: (Constant), LnNha, KC, LG, DAT, VT b Dependent Variable: LnPrice ANOVAa Model Sum of Squares Regression df Mean Square F 44.279 127 161.612 000b 055 51.238 Total 8.856 6.959 Residual Sig 132 a Dependent Variable: LnPrice b Predictors: (Constant), LnNha, KC, LG, DAT, VT Coefficientsa Standar dized 95.0% Unstandardized Coefficie Confidence Collinearity Coefficients nts Interval for B Statistics Std Model (Constant) B Error 21.552 331 VT 212 072 DAT 012 LG KC Lower Beta LnNha T Sig Upper Bound Bound Tolerance VIF 65.075 000 20.897 22.207 170 2.964 004 071 354 326 3.066 001 475 10.526 000 010 014 525 1.905 025 004 394 7.153 000 018 032 352 2.843 -.122 036 -.114 -3.381 001 -.194 -.051 949 1.054 081 040 086 2.023 045 002 161 596 1.677 ... i nhà, s c, v trí ki u nhà bi n s quan tr ng nh t n giá nhà T i khu v giá nhà nơng thơn 26.26% Theo m t nghiên c u g t c a Gabriel K.B (2011), y u t ngo i tác nh n giá y ut kho ng cách t d n nhà. .. di n tích nhà, lo i nhà, h v trí ki u nhà nh ng bi n quan tr ng nh t có c ti p t c m r ng b i Selim.H (2009), v i hai lo pc c s d ng tro mô hình h i quy Hedonic ANN Các k t qu c a mơ hình h i... kho ng cách t u xe K t qu h i quy cho th y y u t ngo i tác nhà th tiêu c Nhà n giá m nhà phù h p v Càng xét c, ng xa nhà th c quan tr ng ch ng cu c s c tính c a ngơi nhà h t s c c n thi nh giá