1. . Dr. Fotis Mouzakis Dr. Papastamos Dimitrios Prof. Simon Stevenson

2. Purpose This study examines the rationality and momentum in forecasts for rental, capital value and total returns for the real estate investment market in the United Kingdom compiled by the IPF We adopt an innovative approach of a 3-dimensional panel data estimation, including momentum, macro-economic determinants and structural variation (fixed-effects) over: Individual forecasters (cross-section) Separate target years (cross-section) Horizon of re-issuing forecasts for the same target by each forecaster (time- series) The empirical model includes the effect (to forecast errors) of: Macro economic conditions including economic growth and investment risk Momentum in revising forecasts An approach which improves missing explanatory aspects of previous approaches and improves under-specification bias (omitted variable estimation bias)

3. Literature Review Tsolacos (2006) &McAllister et al. (2008) studies examined the accuracy of the IPF Consensus Forecasts for 1999-2004 period, thereby limited to broadly strong market conditions. Bond & Mitchell (2011) also consider the IPF data, although in a different context. Their analysis compares the forecasting accuracy of the IPF Consensus Forecast for total returns versus implied forecasts derived from total return swap contracts. The results, interestingly, show that for a one-year horizon, the derivatives based implied forecasts display greater accuracy than the consensus professional forecasts for total returns.

4. Data The data used in this study is provided by the Investment Property Forum (IPF) for the period 1999-2011. The total sample consists of 69 Property forecasters 22 property advisors, 26 fund managers and 21 equity brokers The forecasts provided are for growth rates/returns for the IPD ‘All Property’ Indices for Rental, Capital Value Growth and Total Returns up to 3-year ahead period in quarterly basis. The benchmark reference point is the return for the relevant annual index produced by the Investment Property Databank (IPD) who are the primary index provider in the commercial real-estate market in the United Kingdom. The macroeconomic variables that are used in this study are the gross domestic product (GDP) and the default spread (DS). All of these variables refer to the UK economy and was obtained from Datastream for the period 1999-2011.

5. Descriptive Statistics of Accuracy of the Consensus Figures

7. Rationality & Momentum of Property Forecasts We apply the Holden & Peel (1990) approach to consider the rationality (i.e. bias and efficiency) of property market related forecasts. The significance of the constant, τ, indicates biased forecasts. Model Specification:

8. Results of Bias & Momentum Formal tests of bias in the case of capital and total returns aren’t possible due to non-stationarity issues This is actually the result of extremely high momentum, with the coefficients relating to lagged forecast errors being in excess of 0.9, indeed some evidence of explosive forecast series (with  >1)

9. Behavioural Analysis of Property Forecasters We also run tests to see if forecasters are affected by general economic and property market conditions present at the time of forecast  We incorporate into the analysis GDP, Default Spread representing property market conditions

10. Behavioural Analysis of Forecasters – Rental Growth Target Year Fixed Effects – Rental growth Horizon fixed effects – Rental growth Excessively pessimistic during the strong years 1999-2004 Optimistic prior to down-turn 2005-2007 Too pessimistic in 2009 – overestimated down-turn Alternating direction of corrections when they re-issue the forecast Stronger corrections as forecasting horizon shortens Strong negative correction (more optimistic) in 3 and 6 quarter horizons Strong pessimistic (conservatism) final correction in last quarter

11. Behavioural Analysis of Forecasters – Capital Growth Target Year Fixed Effects – Rental growth Horizon fixed effects – Rental growth Similar pattern of correction over the historic years covered similar to rental growth They start from negative (conservative) bias in long horizons They reduce negative bias (optimistic corrections) as they re-issue forecasts At 5q horizon they switch to negative corrections (pessimistic corrections-with exception 2q) Strong final conservative correction in last quarter – a final attempt to reduce positive bias

12. Key Findings Forecasters tend to exhibit optimistic behaviour during periods of market underperformance and vice versa. This is consistent with the finding that they tend to exhibit greater forecast error when the property market is underperforming and vice-versa. The empirical findings show high levels of momentum in the forecasts, with highly persistent forecast errors. Forecasters tend to avoid ‘big numbers’ and display conservatism Property forecasters tend to update their previous forecast: Capital value: upwards in long horizons and downwards in short Rental growth: Increasingly as horizon falls, but with fluctuations The results also indicate that forecasters are affected by adverse conditions Capital value and rental growth: over-pessimistic during the strong years and most during the adjustment of 2009 Property forecasters tend to be affected by the general economic conditions at the time the forecasts are made, including Economic growth Risk premiums (default spread) The newly tested methodology (3d-panel) delivered statistically robust results and indications for the need to account simultaneously for time series and cross-section variations