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THE ACCURACY OF PROPERTY FORECASTING IN THE UK

THE ACCURACY OF PROPERTY FORECASTING IN THE UK. GRAEME NEWELL University of Western Sydney and PATRICK McALLISTER University of Reading. June 2009. PROPERTY FORECASTING. Importance Uncertainty Procedures quantitative - qualitative Role of judgement 2008 property environment

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THE ACCURACY OF PROPERTY FORECASTING IN THE UK

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  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 - UK@ -22.1% - Ireland @ -34.2% - Norway@ -4.7% - Sweden@ -3.3% - Spain@ -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 Overall @ -22.1% • IPD Office @ -22.4% • IPD Retail @ - 22.6% • IPD Industrial @ -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 • # 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

  9. Target = -22.1%

  10. MEAN ABSOLUTE ERROR

  11. MEAN ABSOLUTE PERCENTAGE ERROR

  12. THEIL U1 STATISTIC

  13. AVERAGE RANGE

  14. “BEST” FORECASTER: MAE

  15. “BEST” FORECASTER: MAPE

  16. “BEST” FORECASTER • Groups: • PAs: 0% - FMs: 75% - EBs:25% • Individuals: • PAs: 25% - FMs: 58% - EBs:17%

  17. “WORST” FORECASTER: MAE

  18. “WORST” FORECASTER: MAPE

  19. “WORST” FORECASTER • Groups: • PAs: 42% - FMs: 0% - EBs:58% • Individuals: • PAs: 33% - FMs: 42% - EBs:25%

  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?

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