1. THE ACCURACY OF PROPERTY FORECASTING IN THE UK
GRAEME NEWELL
University of Western Sydney
and
PATRICK McALLISTER
University of Reading
June 2009

2. PROPERTY FORECASTING Importance Uncertainty Procedures
quantitative - qualitative
Role of judgement
2008 property environment
% %
- -4.7% %
- -2.9% France @ -0.9%

3. PREVIOUS RESEARCH Forecasting rents, yields etc.
Econometric/structural modelling
Comparison of forecasting procedures
Simple forecasts versus econometric models

4. ACCURACY OF PROPERTY EXPERT FORECASTS
US: Ling (2005)
UK: McAllister, Newell and Matysiak(2008); Tsolacos (2006)
Australia: Newell and Karantonis (2003);
Newell and MacFarlane (2006)
Consensus and individual forecasts

5. ACCURACY ISSUES Uncertainty Disagreement Conservative forecasts; bias
Inertia
Group differences
“Numbers” versus “turning points”
Individual forecasters
- consistency banding
- persistence

6. PURPOSE Assess accuracy of UK property forecasts re: 2008
IPD %
IPD %
IPD %
IPD -21.2%
Accuracy
- uncertainty disagreement
Behavioural issues

7. METHODOLOGY Investment Property Forum
“Survey of Independent Forecasts”
1998 – 2009; quarterly; UK
Expert opinions : #= 18-37
- property advisors fund managers
- equity brokers
Capital returns, rental growth, total returns
Property sub-sectors
Forecasts generated to end of year
- up to 3 years ahead

8. METHODOLOGY Focus = 2008 total return forecasts Up to 36 months ahead
36M, 33M, …, 9M, 6M, 3M
# participants: 24 – 37
# property advisors: 10 – 18
# fund managers: 9 – 16
# equity brokers: 3 – 5
Statistical analysis
- MAE MAPE
- range - Theil U1 statistic

9. Target = -22.1%

10. MEAN ABSOLUTE ERROR 36M 24M 12M 6M 3M All : 22.4 19.7 13.3 8.4 5.3 PAs
36M
24M
12M 6M 3M
All :
22.4
19.7
13.3
8.4
5.3
PAs
22.8
20.1
13.5
8.7
5.5
FMs
21.7
19.1
12.8
7.5
4.3
EBs
22.5
18.7
9.1
4.6
Office
23.8
20.8
13.1
7.7
Retail
22.3
19.9
14.4
9.5
6.0
Industrial
21.9
19.3
13.4
9.0
5.8

11. MEAN ABSOLUTE PERCENTAGE ERROR
36M
24M
12M 6M 3M
All :
101.1%
89.1%
60.2%
38.0%
24.0%
PAs
103.0%
90.7%
61.2%
39.1%
24.9%
FMs
98.2%
86.5%
57.9%
33.9%
19.5%
EBs
101.9%
84.7%
60.3%
41.0%
20.8%
Office
106.2%
92.8%
58.4%
34.4%
20.5%
Retail
98.9%
88.2%
63.5%
42.0%
26.6%
Industrial
103.4%
91.0%
63.4%
42.2%
27.4%

12. THEIL U1 STATISTIC 36M 24M 12M 6M 3M All : 0.80 0.70 0.44 0.25 0.14
36M
24M
12M 6M 3M
All :
0.80
0.70
0.44
0.25
0.14
PAs
0.81
0.72
0.45
0.26
FMs
0.79
0.69
0.43
0.22
0.11
EBs
0.66
0.28
0.12
Office
0.82
Retail
0.47
0.15
Industrial
0.16

13. AVERAGE RANGE 36M 24M 12M 6M 3M All : 10.30 10.70 10.40 10.20 9.50 PAs
36M
24M
12M 6M 3M
All :
10.30
10.70
10.40
10.20
9.50
PAs
7.10
7.40
7.50
5.60
FMs
8.40
8.30
7.70
6.60
EBs
5.70
7.00
7.30
6.80

14. “BEST” FORECASTER: MAE
36M
24M
12M 6M 3M
All :
16.70
14.10
7.80
3.70
0.60
PAs
18.70
16.00
9.30
5.10
2.10
FMs
17.30
14.80
8.60
4.00
1.10
EBs
19.60
15.40
10.10
5.90

15. “BEST” FORECASTER: MAPE
36M
24M
12M 6M 3M
All :
75.50%
63.70%
35.40%
16.70%
2.70%
PAs
84.60%
72.60%
42.10%
23.10%
9.50%
FMs
78.30%
67.10%
38.70%
17.90%
5.00%
EBs
88.90%
69.60%
45.50%
26.50%
Theil
0.58
0.48
0.25
0.12
0.01

16. “BEST” FORECASTER Groups: Individuals: PAs: 0% - FMs: 75% - EBs:25%

17. “WORST” FORECASTER: MAE
36M
24M
12M 6M 3M
All :
27.0
24.8
18.3
13.9
10.1
PAs
25.8
23.6
17.0
12.7
7.7
FMs
23.1
16.3
10.5
EBs
25.3
22.4
17.4
12.6

18. “WORST” FORECASTER: MAPE
36M
24M
12M 6M 3M
All :
122.20%
112.00%
82.60%
62.90%
45.70%
PAs
116.90%
106.60%
76.90%
57.50%
34.80%
FMs
116.50%
104.60%
73.70%
47.50%
EBs
114.70%
101.30%
78.50%
57.00%
Theil
0.91
0.86
0.67
0.47
0.30

19. “WORST” FORECASTER Groups: Individuals: PAs: 42% - FMs: 0% - EBs:58%

20. PROPERTY FORECASTING IMPLICATIONS
Accuracy re: 2008 property forecasts
Uncertainty versus disagreement
Conservative bias
Improvements over time : 36M  3M
Critical times
Group differences
Sector differences
Other issues re: changes in forecasts
- impact of news expected returns (IPD monthly)
- anchoring
2009 property forecasts?