THE ACCURACY OF THE ACCURACY OF PROPERTY PROPERTY

FORECASTING IN THE FORECASTING IN THE UKUK

GRAEME NEWELLUniversity of Western SydneyandPATRICK McALLISTERUniversity of Reading

June 2009

PROPERTY FORECASTINGPROPERTY FORECASTING

Importance Uncertainty Procedures

– quantitative - qualitative Role of judgement 2008 property environment

- UK@ -22.1% - Ireland @ -34.2%- Norway@ -4.7% - Sweden@ -3.3%

- Spain@ -2.9% - France @ -0.9%

PREVIOUS RESEARCHPREVIOUS RESEARCH

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

models

ACCURACY OF PROPERTY ACCURACY OF PROPERTY EXPERT FORECASTSEXPERT 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

ACCURACY ISSUESACCURACY ISSUES Uncertainty Disagreement Conservative forecasts; bias Inertia Group differences “Numbers” versus “turning points” Individual forecasters

- consistency - banding - persistence

PURPOSEPURPOSE Assess accuracy of UK property forecasts re:

2008 IPD Overall @ -22.1% IPD Office @ -22.4% IPD Retail @ - 22.6% IPD Industrial @ -21.2% Accuracy

- uncertainty - disagreement Behavioural issues

METHODOLOGYMETHODOLOGY 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

METHODOLOGYMETHODOLOGY Focus = 2008 total return forecasts Up to 36 months ahead 36M, 33M, …, 9M, 6M, 3M # 2006-08 participants: 24 – 37 # property advisors: 10 – 18 # fund managers: 9 – 16 # equity brokers: 3 – 5 Statistical analysis

- MAE - MAPE- range - Theil U1 statistic

Target = -22.1%Target = -22.1%

MEAN ABSOLUTE ERRORMEAN ABSOLUTE ERROR

    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 13.3 9.1 4.6

Office : 23.8 20.8 13.1 7.7 4.6

Retail : 22.3 19.9 14.4 9.5 6.0

Industrial : 21.9 19.3 13.4 9.0 5.8

MEAN ABSOLUTE PERCENTAGE MEAN ABSOLUTE PERCENTAGE ERRORERROR

    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%

THEIL U1 STATISTICTHEIL U1 STATISTIC

    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 0.14

FMs : 0.79 0.69 0.43 0.22 0.11

EBs : 0.79 0.66 0.44 0.28 0.12

Office : 0.82 0.72 0.43 0.22 0.11

Retail : 0.80 0.70 0.47 0.28 0.15

Industrial : 0.82 0.72 0.47 0.28 0.16

AVERAGE RANGEAVERAGE RANGE

    36M 24M 12M 6M 3M

All : 10.30 10.70 10.40 10.20 9.50

PAs : 7.10 7.40 7.50 7.10 5.60

FMs : 8.40 8.30 7.70 6.60 6.60

EBs : 5.70 7.00 7.30 6.80 9.50

““BEST” FORECASTER: MAEBEST” 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 0.60

““BEST” FORECASTER: MAPEBEST” 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% 2.70%

Theil   0.58 0.48 0.25 0.12 0.01

““BEST” FORECASTERBEST” FORECASTER

Groups:– PAs: 0% - FMs: 75% - EBs:25%

Individuals:– PAs: 25% - FMs: 58% - EBs:17%

““WORST” FORECASTER: MAEWORST” 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 : 25.8 23.1 16.3 10.5 7.7

EBs : 25.3 22.4 17.4 12.6 10.1

““WORST” FORECASTER: MAPEWORST” 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% 34.80%

EBs : 114.70% 101.30% 78.50% 57.00% 45.70%

Theil   0.91 0.86 0.67 0.47 0.30

““WORST” FORECASTERWORST” FORECASTER

Groups:– PAs: 42% - FMs: 0% - EBs:58%

Individuals:– PAs: 33% - FMs: 42% - EBs:25%

PROPERTY FORECASTING PROPERTY FORECASTING IMPLICATIONSIMPLICATIONS

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?