Predicting real estate rents: walking backwards into the future
| Date | 01 June 2000 |
| Published date | 01 June 2000 |
| Pages | 352-370 |
| DOI | https://doi.org/10.1108/14635780010339181 |
| Author | Russell Chaplin |
| Subject Matter | Property management & built environment |
JPIF
18,3
352
Journal of Property Investment &
Finance, Vol. 18 No. 3, 2000,
pp. 352-370. #MCB University
Press, 1463-578X
Received June 1999
Revised February 2000
ACADEMIC PAPERS
Predicting real estate rents:
walking backwards into the
future
Russell Chaplin
Property Market Analysis, Tower House, London, UK and Department
of Land Economy, University of Cambridge, Cambridge, UK
Keywords Modelling, Forecasting, Rent
Abstract Modelling, predicting and forecasting commercial rents are now seen as necessary
and explicit processes in real estate investment. Decisions on the prospects for specific
investments, the real estate portfolio and multi-asset portfolio are made as a result of these
processes and thus it is the accuracy of these models, predictions and forecasts in capturing future
movements in rents that are implicitly tested in the marketplace. Despite the amount of theoretical
and empirical research that has been conducted into modelling and predicting rents, it is unusual
to find research which explicitly considers the predictive accuracy of models on an ex ante basis.
This paper seeks to demonstrate the importance and possible value of such a procedure by
examining the predictability of commercial rents in the office, industrial and retail markets of
Great Britain over a real estate ``cycle''. The paper concludes that theory appears to be a better
indicator of the ``correct'' model structure than maximising historic fit. Often naõÈve competitors
are better predictors than the model selection strategy employed.
Preface
The ancient Greeks viewed the passage of time in a different way than we do
today. For an ancient Greek, standing at the present, the past disappeared in
front of him while the future was behind him ± analogous to ``walking
backwards into the future''.
Modern cultures prefer to view the future laid out in front of us and the past
behind us ± we walk forwards into the future. It is with our modern view of the
future that we approach the questions of modelling, predicting and forecasting
± although perhaps it would be more appropriate to approach these questions
through the eyes of an ancient Greek.
In this way we might have more realistic expectations of what we expect to
achieve from predicting the future.
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An earlier version of this paper was presented at the 6th annual European Real Estate Society
conference in Athens, Greece, June 1999.
The author would like to thank Anna Ahmad, a former M.Phil. student at the Department of
Land Economy, University of Cambridge, for her work on the Industrial portion of this paper.
He would also like to thank Hillier Parker (now CB Hillier Parker) for the provision of the rental
data. The comments of the two anonymous referees are gratefully acknowledged.
Academic
papers:
Predicting real
estate rents
353
1. Introduction
1.1 Background
Since the real estate crash of the late 1980s/early 1990s in the UK, the real estate
research community and practitioners have invested greater effort in
attempting to derive (predictive) models of various commercial real estate
performance indicators (Harris and Cundell, 1995). Published research has
concentrated largely on rental value prediction and mostly rents in the office
sector. This is a reflection of the volatility of that sector and the potential value
that can be added (and losses avoided) by accurately predicting the changes in
rents and hence onwards to total returns. The retail and industrial sectors have
generally attracted less attention.
Predictions for rents at the national level are normally made for five years
ahead (see Chaplin, 1998) that necessarily entails making predictions one year
ahead. Some earlier work (Chaplin, 1998, 1999) has demonstrated that the
predictive accuracy of models for office rents one year ahead can be, perhaps
surprisingly, poor.
The value of one year ahead predictions is threefold. First, such predictions
can indicate turning points in the series before they occur, thus giving investors
time to adjust their multi-asset or property portfolios accordingly. Therefore it
is important that the predictions are able to predict the correct direction of
change over the next year. Second, one year ahead predictions for rents are
likely to influence capital values greatest because of the discounting of rents
that takes place to present value. Third, predictions of rents one year ahead
usually feed into predictions for rents for subsequent years so any errors in this
first year may be compounded year upon year.
In this paper we take a look at the first of these two points (and by
implication, the third) by simulating the actions of an investor year by year
who attempts to predict commercial real estate rents just one year ahead. The
office, industrial and retail markets are analysed separately.
1.2 Aims and objectives
The paper aims to examine the predictability of commercial rents in the office,
industrial and retail sectors of Great Britain using an ex ante prediction
strategy based on selection of the best fitting model for use in predicting one
year ahead.
The objective of the paper is to compare this ex ante strategy with other
naive ex ante strategies and with the best predicting models to inform us of the
value of such a predictive strategy and to suggest possible alternative
approaches.
1.3 Structure
This paper is in a further four sections. Section two considers the variables that
have been used in the literature to explain office, industrial and retail sector
rents at the national level. Section three discusses the method used in the paper.
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