Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos 7 doc
Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_2 pot
... line,y = α + βx (4.1) Real estate analysis: statistical tools 692520151050–5–10–15 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 1013Figure 3.9Sample ... 2.619 97 5.3 7. 1 3.4 4 .7 1998 6.2 10.1 4.0 5.41999 10.4 9.5 4.9 5.62000 11.1 11 .7 5.3 5 .7 2001 11.3 5.4 5.8 7. 12002 4.0 5.6 6.2 7. 32003 2.6 5 .7 9.6 8.02004 −3 .7 2.1 9.9 9.52005 0.8 4 .7 10.4 ... vacancy or measures of demand) have confined empirical investigationsto standard regression models, which make lesser demands on the data 72 50 Real Estate Modelling and Forecasting Table 3.1 Summary...
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Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_3 doc
... it by ˆβ and adding ˆα will84 Real Estate Modelling and Forecasting 20(yoy %)ActualFitted(%)1510501 979 19811983198519 87 198919911993199519 97 19992001200320051 979 19811983198519 87 198919911993199519 97 1999200120032005−5−10−15−20(a) ... MacGregor and White, 2002). Employment in business and finance is a proxy for businessconditions among firms occupying office space and their demand for office88 Real Estate Modelling and Forecasting 4.8.2 ... chapters. 76 Real Estate Modelling and Forecasting ●There are bound to be random outside influences on y that, again, cannot bemodelled. For example, natural disasters could affect real estate...
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Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_4 ppt
... (1984–2006):ˆRRgt=− 17. 68 + 2.45EFBSgt+ 2 .71 GDPgt+ 0 .79 OFBSgt(5.48)(6.35) (3 .76 ) (1.92) (0. 87) where OFBSg is the annual percentage growth in OFBS,R2= 0 .76 , adj.R2= 0 .72 , URSS = 619.46, ... inparticular by means of the tests we discuss in the next chapter and theevaluation of forecast performance in later chapters. On the basis of the118 Real Estate Modelling and Forecasting ytxtFigure ... that in section5.9 – i.e. the true DGP is represented by yt= β1+ β2x2t+ β3x3t+ β4x4t+ ut(5.50)128 Real Estate Modelling and Forecasting 5.8.2 Determining the number of restrictions,...
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Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_6 potx
... 202 Real Estate Modelling and Forecasting Table 7. 3 Regression models for Frankfurt rentsModel 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 ... denoted by T1(even though it maycome second). The test statistic is given by test statistic =RSS −RSS1RSS1×T1− kT2(6.61)190 Real Estate Modelling and Forecasting of data at hand,...
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Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_7 doc
... below.ˆy = 6. 176 7 +49.458 inflation R2= 0. 47 ˆy = 4.1 572 +0.5691 long-term government bond R2= 0. 27 ˆy = 5.5034 + 0.4612 short-term interest rates R2= 0 .76 ˆy = 7. 91 97 +−0.1 176 rent R2= ... 0.44 0.80 0. 57 0.51 0 .72 DW 1.81 2.08 1.82 1.82 2.12 2.01RSS 1,383.86 992.91 209.81 1,460.02 904. 87 289.66Sample 1982–20 07 1982–94 1995–20 07 1981–20 07 1981–94 1995–20 07 T 26 13 13 27 14 13F -statistic ... 2.28.The212 Real Estate Modelling and Forecasting As a result, the equilibrium real rent varies through time with the real risk-free rate. The author also gives examples of the equilibrium rent:g∗1 970 =...
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Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_9 doc
... 3 97. 20 −12. 37 31.812004 −13.30 −16.06 2 .76 2 .76 7. 62 176 .89 2 57. 92 −12. 37 0.882005 −3.64 −9 .77 6.13 6.13 37. 58 13.25 95.45 −12. 37 76.212006 −4.24 4.21 −8.45 −8.45 71 .40 17. 98 17. 72 −12. 37 ... −18.01 −25.21 7. 20 7. 20 51.89 324.36 635 .72 −12. 37 31.812004 −13.30 −30. 07 16 .77 16 .77 281. 07 176 .89 903.91 −12. 37 0.862005 −3.64 −29.22 25.58 25.58 654.22 13.25 853.68 −12. 37 76.212006 −4.24 ... −12. 37 31.812004 −13.30 −13.81 0.51 0.51 0.26 176 .89 190.69 −12. 37 0.862005 −3.64 −12.46 8.82 8.82 77 . 87 13.25 155.35 −12. 37 76.212006 −4.24 −4.65 0.41 0.41 0. 17 17. 98 21.66 −12. 37 66.102007...
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Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_11 ppt
... 158 1582Q04 0.69 −1. 17 6.0 5 .7 1 17 294 124 1303Q04 0.96 0. 07 5 .7 4.8 202 293 148 1184Q04 0 .78 1. 17 5 .7 4.0 42 2 47 44 831Q05 0.23 2.02 5.1 3.6 186 185 62 902Q05 −0. 07 2.28 4.6 3.1 98 151 ... 0.03 27 0.2126 0.0000DIVY 0.5025 0.0000 0.6212 0.42 17 0.5654 0.4033SPREAD 0. 277 9 0.1328 0.0000 0.4 372 0.6563 0.00 07 UNEM 0.3410 0.3026 0.1151 0.0000 0. 075 8 0. 276 5UNINFL 0.30 57 0.5146 0.3420 0. 479 3 ... −2.19 80,0 47 90, 271 6.5 20,880 158 19,524 253 1.532Q04 −1. 17 79,111 90,403 5 .7 21,010 130 19,818 294 1.963Q04 0. 07 79,168 90,459 4.8 21,128 118 20,111 293 1.954Q04 1. 17 80,091 90, 477 4.0 21,212...
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Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos_12 pptx
... ForecastDec. 06 −0.02 27 −0.0100 −0.0400 −0.0100Jan. 07 0. 071 8 0.0200 0.2000 0.0800Feb. 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 ... 0.0800Feb. 07 −0.0355 −0.00 67 0.0100 −0.0 579 −0.0400 −0.0100 0.0 470 Mar. 07 −0.0359 0.0065 0. 070 0 0.0084 −0.1600 −0.0900 −0.0580Apr. 07 −0.00 57 −0.0030 −0.0500 −0.0128 0.1300 0. 170 0 −0.0348May. 07 −0.00 87 ... ofstationarity and unit root tests is known as confirmatory data analysis.364 Real Estate Modelling and Forecasting The forecast for SPYtfor August 20 07 – that is, the change betweenJuly 20 07 and August...
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Real Estate Modelling and Forecasting By Chris Brooks_1 doc
... real 20 07 prices1nominal real 1991 877 100.0 877 .0 86.0 10.2 1,0 87. 1 100.0 100.01992 72 0 101 .7 708.0 87. 5 8.2 877 .2 82.1 80 .7 1993 628 104.3 602.1 89 .7 7.0 74 6.3 71 .6 68 .7 1994 699 1 07. 3 651.4 ... Hamlets 2,5 37 3,851 4,536 5,631 5,051 4 ,75 2 4,5 57 3,890 5,143 4,2 37 Wandsworth 7, 389 8,6 47 7 ,79 3 9 ,75 7 7, 693 8,1 87 8,485 6,935 8,156 7, 072 Westminster 5,165 6,885 5,821 7, 118 6,516 6,024 6,4 17 5,014 ... 4,534 3 ,76 5 4,233 3,3 47 Islington 2,516 3,243 3,3 47 3,935 3, 075 3,4 07 3,365 2 ,77 6 2,941 2,900Kensington and Chelsea4 ,79 7 5,262 4, 576 5,558 4 ,70 7 4,195 4,514 3,4 97 4,043 3,426Lambeth 4,9 57 6,128...
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Real Estate Modelling and Forecasting By Chris Brooks_2 potx
... 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 4.3 Regression versus correlationAll ... line,y = α + βx (4.1) Real estate analysis: statistical tools 692520151050–5–10–15 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 1013Figure 3.9Sample ... −3 .7 −2.01993 5.8 −0.1 −2.5 −0.11994 3.4 2.0 −0 .7 2.01995 −0 .7 −2.0 0.8 2.11996 −2.5 7. 3 2.6 2.619 97 5.3 7. 1 3.4 4 .7 1998 6.2 10.1 4.0 5.41999 10.4 9.5 4.9 5.62000 11.1 11 .7 5.3 5 .7 2001...
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