Chris Brooks Real Estate Modelling and Forecasting 5 docx
Chris Brooks Real Estate Modelling and Forecasting_1 ppt
... hypothesis in favour of
170 Real Estate Modelling and Forecasting
25
20
15
10
(Regression residuals)
5
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
0
5
−10
− 15
Figure 6.10
Regression
residuals ... 158 Real Estate Modelling and Forecasting
autocorrelation, therefore, would be to use appropriately modified standard
error estimates.
While White’s correc...
Chris Brooks Real Estate Modelling and Forecasting_5 docx
... −4.02 4.02 16. 15 17.98 0. 05 −12.37 66.10
2007 3.48 2.00 1.48 1.48 2.18 12.11 4.02 −12.37 251 .22
Sum of column 5. 62 15. 55 77.80 54 4 .59 641.79 426.21
Forecast periods 5 5 5 5 5 5
Average of column ... 18.88 356 .39 17.98 53 4. 45 −12.37 66.10
2007 3.48 −17 .56 21.04 21.04 442 .55 12.11 308.24 −12.37 251 .22
Sum of column 89.46 89.46 1786.12 54 4 .59 3236.01 426.21
Forecast...
Chris Brooks Real Estate Modelling and Forecasting_6 pdf
... 1,017 .5
2Q 05 −0.40 76,896 90,499 6.3 21,410 110 20, 055 106 1,9 15 1,0 15. 5
3Q 05 −0.31 76, 656 90 ,56 4 6.3 21 ,51 7 107 20, 158 103 1,920 984.9
4Q 05 −0.26 76, 453 90,488 6.3 21,622 1 05 20,260 102 1,9 25 954 .5
1Q06 ... ahead
123 456 7 8
(a) LaSalle Investment Management rents series
VAR(1) −1.141 −2.844 −3.908 −4.729 5. 407 5. 912 −6. 158 −6 .58 6
VAR(2) −0.799 −1 .55 6 −2. 652...
Chris Brooks Real Estate Modelling and Forecasting_7 docx
... 247 1.47
1Q 05 2.02 81,7 05 90 ,56 3 3.6 21,302 90 20 ,54 3 1 85 0.81
2Q 05 2.28 83 ,56 8 90,499 3.1 21,366 64 20,694 151 0. 45
3Q 05 2.46 85, 6 25 90 ,56 4 2.7 21,4 15 49 20,832 138 0.32
4Q 05 2 .59 87,844 90,488 ... 100.0 51 .0
2 0.2 0.8 0.2 35. 1 0.2 12.3 0.4 1.4 1.6 2.9 97 .5 47 .5
3 3.8 2 .5 0.4 29.4 0.2 17.8 1.0 1 .5 2.3 3.0 92.3 45. 8
4 3.7 2.1 5. 3 22.3 1.4 18 .5 1.6 1...
Chris Brooks Real Estate Modelling and Forecasting_9 pptx
... RENT(qoq %)
1Q07 85. 5 156 .4 0.8 0.83
2Q07 87 .5 157 .2 0.8 2.34
3Q07 89.1 158 .2 1.0 1.83
4Q07 89.7 159 .2 −2. 95 1.0 0.67
1Q08 90.1 160.0 −2.98 0.8 0.440 0.49
2Q08 90.3 160.8 −3.34 0.8 0.1 15 0.13
3Q08 ... GDP growth.
408 Real Estate Modelling and Forecasting
Table 12.8 Johansen tests for cointegration between Asia, the United States and
Europe
λ
max
Critical 5% λ
trace
Cri...
Chris Brooks Real Estate Modelling and Forecasting_10 pdf
... 432 5
seasonal dummies 255 –7
seasonality 162, 2 45, 251 –7
securitised real estate 258 –9, 282, 344 5, 3 85
shocks 239, 352 –6, 361, 369–73, 378
sign predictions 288–9, 299, 301
significance level 59 –64, ... Press.
Brooks, C., Burke, S. P., and Persand, G. (2001) Benchmarks and the accuracy of
GARCH model estimation, International Journal of Forecasting 17(1), 45 56 .
441
428...
Real Estate Modelling and Forecasting Hardcover_15 docx
... 432 5
seasonal dummies 255 –7
seasonality 162, 2 45, 251 –7
securitised real estate 258 –9, 282, 344 5, 3 85
shocks 239, 352 –6, 361, 369–73, 378
sign predictions 288–9, 299, 301
significance level 59 –64, ... 311, 339, 352
explanatory 73, 75, 96, 109–12
irrelevant 130–2, 188, 242
macroeconomic 316, 357
omission of 129–30, 152 , 161, 219
ordering of 354 , 360
random 52 , 54 5, 89
sl...
Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_2 pot
... straight line,
y = α + βx (4.1)
Real estate analysis: statistical tools 69
25
20
15
10
5
0
5
–10
– 15
47 931 139 1 85 231 277 323 369 4 15 461 50 7 55 8 59 9 6 45 691 737 783 829 8 75 921 967 1013
Figure 3.9
Sample ... 2.6
1997 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
200...
Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_3 doc
... %)
Actual
Fitted
(%)
15
10
5
0
1979
1981
1983
19 85
1987
1989
1991
1993
19 95
1997
1999
2001
2003
20 05
1979
1981
1983
19 85
1987
1989
1991
1993
19 95
1997
1999
2001
2003
20 05
5
−10
− 15
−20
(a) Actual and fitted values for RR (b) Residuals
− 25
20
15
10
5
0
5
−10
− 15
−20
− 25
Figure 4.8
Actual and fitted
values and residuals
for ... by
ˆ
β and adding ˆα will
84...
Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_4 ppt
... following statistics were
obtained: R
2
= 0 .58 , adj. R
2
= 0 .55 , RRSS = 1,078.26.
Restricted equation:
ˆ
RRg
t
=−9 .54 + 3.25EFBSg
t
(5. 52)
(1.80) (5. 18)
R
2
= 0 .51 , adj. R
2
= 0.49, RRSS = 1,268.38. ... line
Example 5. 2 Measuring goodness of fit
We now estimate the R
2
for equation (4.28) applying formula (5. 27). RSS =
1214.20, TSS = 255 0 .59 .
R
2
= 1 −
RSS
TSS
= 1 −
1214.20
25...