Real Estate Modelling and Forecasting Hardcover 7 pot

... building in real estate 5 1.5 What do we model and forecast in real estate? 6 1.6 Model categorisation for real estate forecasting 8 1 .7 Why real estate forecasting? 9 1.8 Econometrics in real estate, ... techniques to real data and problems in real estate. 2 Real Estate Modelling and Forecasting 1.1 Motivation for this book The complexity of the re...

Ngày tải lên: 20/06/2014, 20:20

... 0.91 0.51 2 0. 57 0.29 0.60 0.12 0.81 0.14 30.25−0.05 0.32 −0.34 0 .73 −0.23 Sample period 1980–20 07 1981–20 07 1980–20 07 1981–20 07 1980–20 07 1981–20 07 Notes: RR is the level of real office rents; ... plausible; ● be consistent with underlying real estate theory, including satisfying any relevant parameter restrictions; 172 Real Estate Modelling and Forecasting is...

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... below. ˆ y = 6. 176 7 +49.458 inflation R 2 = 0. 47 ˆ y = 4.1 572 +0.5691 long-term government bond R 2 = 0. 27 ˆ y = 5.5034 + 0.4612 short-term interest rates R 2 = 0 .76 ˆ y = 7. 91 97 +−0.1 176 rent R 2 = ... Bera–Jarque test) and the form of the equation with the RESET test. Normality test: BJ = 33  0.15 2 6 + (3.42 − 3) 2 24  = 0. 37 222 Real Estate Modelling and Foreca...

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... Forecast Dec. 06 −0.02 27 −0.0100 −0.0400 −0.0100 Jan. 07 0. 071 8 0.0200 0.2000 0.0800 Feb. 07 −0.0355 −0.00 67 0.0100 −0.0 579 −0.0400 0.0 976 −0.0100 0.0 470 Mar. 07 −0.0359 0.0030 0. 070 0 0.0186 −0.1600 ... the non-stationarity: the random walk model with drift, y t = µ + y t−1 + u t (12.1) 376 Real Estate Modelling and Forecasting 30 25 20 15 10 5 0 –5 1 40 118 1 57 2...

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... line, y = α + βx (4.1) Real estate analysis: statistical tools 69 25 20 15 10 5 0 –5 –10 –15 47 931 139 185 231 277 323 369 415 461 5 07 558 599 645 691 73 7 78 3 829 875 921 9 67 1013 Figure 3.9 Sample ... variate can be scaled to have zero mean and unit variance by subtracting its mean and dividing by its standard deviation. 74 Real Estate Modelling and Forecasting...

Ngày tải lên: 21/06/2014, 00:20

... −0.06 76 ,044 90,481 6.2 22,030 101 20,662 100 1,9 47 791 .7 1Q 07 −0.01 76 ,033 90,485 6.2 22,130 100 20 ,76 2 100 1,952 75 2.9 2Q 07 0.01 76 ,043 90,4 27 6.2 22,230 100 20,863 101 1,9 57 713 .7 3Q 07 0.02 76 ,062 ... 20,840 118 19,445 174 1,909 476 .9 2Q04 −1.43 78 ,904 90,403 6.5 20,958 118 19,592 1 47 1,908 686.0 3Q04 −0. 97 78,138 90,459 6.4 21, 074 116 19 ,72 1 129 1,9 0...

Ngày tải lên: 21/06/2014, 00:20

... line, y = α + βx (4.1) Real estate analysis: statistical tools 69 25 20 15 10 5 0 –5 –10 –15 47 931 139 185 231 277 323 369 415 461 5 07 558 599 645 691 73 7 78 3 829 875 921 9 67 1013 Figure 3.9 Sample ... 2.6 19 97 5.3 7. 1 3.4 4 .7 1998 6.2 10.1 4.0 5.4 1999 10.4 9.5 4.9 5.6 2000 11.1 11 .7 5.3 5 .7 2001 11.3 5.4 5.8 7. 1 2002 4.0 5.6 6.2 7. 3 2003 2.6 5 .7 9.6 8.0 2004 −...

Ngày tải lên: 21/06/2014, 07:20

... 202 Real Estate Modelling and Forecasting Table 7. 3 Regression models for Frankfurt rents Model A (equation (7. 3)) Model B (equation (7. 4)) Coefficient t-ratio (p-value) ... of the RESET, heteroscedasticity and autocorrelation tests. Equally, a small number of large outliers could cause non-normality and 172 Real Estate Modelling and Forecasting is no relationship ....

Ngày tải lên: 21/06/2014, 07:20

... correction and we would divide by N rather than N − 1. Real estate analysis: statistical tools 69 25 20 15 10 5 0 –5 –10 –15 47 931 139 185 231 277 323 369 415 461 5 07 558 599 645 691 73 7 78 3 829 875 ... 2.0 −0 .7 2.0 1995 −0 .7 −2.0 0.8 2.1 1996 −2.5 7. 3 2.6 2.6 19 97 5.3 7. 1 3.4 4 .7 1998 6.2 10.1 4.0 5.4 1999 10.4 9.5 4.9 5.6 2000 11.1 11 .7 5.3 5 .7 2001 11.3 5.4 5...

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... modelled. 76 Real Estate Modelling and Forecasting ● There are bound to be random outside influences on y that, again, cannot be modelled. For example, natural disasters could affect real estate ... (yoy%) 20 15 10 5 −5 −10 −1 −2 −3 −15 −20 −25 1 979 1981 1983 1985 19 87 1989 1991 1993 1995 19 97 1999 2001 2003 2005 1 979 1981 1983 1985 19 87 1989 1991 1993 1995 19 97 1999...

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