Property and the economic cycle: Building cycles revisited∗

Barras, Richard

doi:10.1080/09599919408724116

Cited by 107 publications

(110 citation statements)

References 8 publications

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“…Much of this research has appeared in the last 6 years. It has concentrated on valuation issues (Born and Pyhrr, 1994;Brown, 1994;Phyrr et al, 1996), conceptual modelling (Healy, 1991;Keogh, 1994;Roulac, 1996;Mueller, 1997a,b), specific feature modelling (Barras, 1994;Antwi and Henneberry, 1995;Grenadier, 1995), development of investment strategies (Antwi and Henneberry, 1995;Mueller, 1997a,b), the identification of boom and bust forces (Jones Lang Wootton, 1990;Barras, 1994), along with major empirical studies linking the economic, financial and real estate markets (Barras and Ferguson, 1985;Tsolacos, 1995a,b, 1997;Lizieri and Satchell, 1997). 3.…”

Section: Notesmentioning

confidence: 98%

The probability and timing of price reversals in the property market

Partington

Stevenson

2001

Manage Decis Econ

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In this paper, we develop models for estimating the time varying probability that there will be a price reversal in the property market. Knowledge of such price reversals may be helpful in forming property trading strategies, and providing confirming evidence of turning points in property cycles. Using an index from the UK property market, we obtain the time varying probabilities by estimating state transition rates. State transition rates are estimated for cases where the up-state (a run of positive price changes) switches to the down-state (price falls) and vice versa. We also estimate a model for absolute transitions, where we take no account of the direction of the state transition. The predictive power of our models is assessed using data from a holdout period. We find that the absolute transition model performs worse than separate state transition models for the up-state and the down-state. For these latter models, the more rapid the decline in the forecast probability of a run continuing beyond a certain time, the less likely it is that the run will actually continue. Further, the probability profiles provide a perfect rank ordering of the length of runs in the holdout period. This suggests that the probabilities could be used to predict whether a sequence of price rises or falls will be long- or short-lived. Copyright © 2001 John Wiley & Sons, Ltd.

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Section: Notesmentioning

confidence: 98%

The probability and timing of price reversals in the property market

Partington

Stevenson

2001

Manage Decis Econ

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“…The first commercial building cycle is 26 years long, running from the beginning of 1955 to the end of 1980, and the second was somewhat shorter, running from the end of 1980 to the beginning of 1996 ( Table 2). The two identi ed cycles contrast with the four short ones suggested by Barras (1994). He argues from orders data that the peaks are in 1964, 1972-3, 1981 and 1988-9, which ts in with his theory of a 9 to 10 of ce building cycle (Barras and Ferguson, 1987 a, b).…”

Section: Uk Commercial Property Investment 283mentioning

confidence: 78%

“…Barras, 1994;Antwi and Hennebery, 1995;Key et al, 1995). This paper adds to this literature by examining the nature of the post-war data on xed investment in commercial property -that is the volume new building and refurbishment of commercial premises -by offering our own limited model, and by considering feasible modelling strategies.…”

Section: Introductionmentioning

confidence: 92%

UK commercial property investment: time-series characteristics and modelling strategies

Ball¹,

Grilli²

1997

Journal of Property Research

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Modelling of UK commercial property development has been a growth industry in recent years. This paper examines the time series characteristics of the data on commercial output and considers the fruitfulness of modelling strategies with respect to it. The models estimated here make sense, and highlight the importance changes in national income, property values and construction costs in determining changes in commercial output. However, several technical and theoretical reasons suggest that they are likely to have poor forecasting ability. One reason is the data on commercial output have a low volatility, while the orders data are of poor accuracy and so are a bad substitute. Doubt is expressed over whether future econometric models can improve on this situation.

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“…It was hypothesised that ten years ex-post forecasting accuracy assessment period should be substantial to examine forecasting performance of each of the models. It was also anticipated that the ten year hold out period would contain two short 4-5 years property cycles driven by the classical business cycle (Barras, 1994;RICS, 1994;Ball et.al., 1998) and longer 9-10 years property cycle (Barras, 1994), as well as it would allow to assess the forecasting accuracy of each of the forecasting specification for short-and long-run horizons.…”

Section: In-and Out-of-sample Accuracy Measurementmentioning

confidence: 99%

Examination of property forecasting models - accuracy and its improvement through combination forecasting

Jadevicius¹,

Sloan²,

Brown³

2012

Proceedings of the 19th Annual European Real Estate Society Conference - Edinburgh, Scotland

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This paper investigates property forecasting accuracy and its improvement. The research suggests that despite increased sophistication of property market modelling and forecasting, there still remains a degree of inaccuracy between model outputs and actual property market performance. Subsequently, the paper presents the principle of combination forecasting as a medium helping to achieve greater predictive outcomes. The research implements combination forecasting principle. It then assesses whether combination forecasts from different forecasting techniques are better than single model outputs. It examines which of them -combination or single forecast -fits the UK property market better, and which of these options forecasts best.

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Property and the economic cycle: Building cycles revisited∗

Cited by 107 publications

References 8 publications

The probability and timing of price reversals in the property market

The probability and timing of price reversals in the property market

UK commercial property investment: time-series characteristics and modelling strategies

Examination of property forecasting models - accuracy and its improvement through combination forecasting

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