Serial persistence in individual real estate returns in the UK
| Date | 01 May 2007 |
| Published date | 01 May 2007 |
| Pages | 241-273 |
| DOI | https://doi.org/10.1108/14635780710746911 |
| Author | Steven P. Devaney,Stephen L. Lee,Michael S. Young |
| Subject Matter | Property management & built environment |
Serial persistence in individual
real estate returns in the UK
Steven P. Devaney
Department of Real Estate and Planning,
University of Reading Business School, Reading, UK
Stephen L. Lee
Real Estate Finance and Investment Group, Faculty of Finance,
Cass Business School, City of London University, London, UK, and
Michael S. Young
San Rafael, California, USA
Abstract
Purpose – The purpose of this paper is to examine individual level property returns to see whether
there is evidence of persistence in performance, i.e. a greater than expected probability of well (badly)
performing properties continuing to perform well (badly) in subsequent periods.
Design/methodology/approach – The same methodology originally used in Young and Graff is
applied, making the results directly comparable with those for the US and Australian markets.
However, it uses a much larger database covering all UK commercial property data available in the
Investment Property Databank (IPD) for the years 1981 to 2002 – as many as 216,758 individual
property returns.
Findings – While the results of this study mimic the US and Australian results of greater persistence
in the extreme first and fourth quartiles, they also evidence persistence in the moderate second and
third quartiles, a notable departure from previous studies. Likewise patterns across property type,
location, time, and holding period are remarkably similar.
Research limitations/implications – The findings suggest that performance persistence is not a
feature unique to particular markets, but instead may characterize most advanced real estate
investment markets.
Originality/value – As well as extending previous research geographically, the paper explores
possible reasons for such persistence, consideration of which leads to the conjecture that behaviors in
the practice of institutional-grade commercial real estate investment management may themselves be
deeply rooted and persistent, and perhaps influenced for good or ill by agency effects.
Keywords Property, Realestate, Return on investment, Performance levels, Asset valuation,
United Kingdom
Paper type Research paper
Introduction
The persistence of property returns is a topic of particular interest to real estate fund
managers as it suggests that choosing those properties that will perform well in the
future is as simple as looking at those that performed well in the past. Consequently,
much effort has been expended to determine if such a rule exists in the real estate
The current issue and full text archive of this journal is available at
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The authors would like to thank the anonymous referees for their comments. The analysis was
undertaken whilst one of the authors was employed at IPD, and within its confidentiality
restrictions.
Serial persistence
241
Received July 2006
Accepted October 2006
Journal of Property Investment &
Finance
Vol. 25 No. 3, 2007
pp. 241-273
qEmerald Group Publishing Limited
1463-578X
DOI 10.1108/14635780710746911
market. Serial persistence in real estate returns has been examined in the direct
property markets in the USA (Young and Graff, 1996, 1997), Australia (Graff et al.,
1999) and the UK (Lee and Ward, 2001). Studies have also examined the serial
persistence of publicly-traded (REIT) real estate (Graff and Young, 1997). The
approach adopted for testing for persistence was much the same in each case. For each
time period, the total returns of each property or REIT was calculated and the
cross-sectional returns ranked into quartiles. If the performance of real estate returns
through time is independent, the use of quartile ranks implies that there is only a 25 per
cent probability of a property remaining in the same quartile return rank from one
period to the next. A significant departure from the 25 per cent theoretical probability
can therefore be considered an indicator of serial dependence in performance.
This paper extends prior studies in three ways. First, it applies to the UK the same
methodology as originally used in Young and Graff (1996), making the results directly
comparable with those in the US and Australian property markets. Second, this study
uses a much longer and larger database than in previous studies. The data cover
commercial property returns for individual properties in the Investment Property
Databank (IPD) for the years 1981 to 2002 – as many as 216,758 observations and
30,000 property time-series returns. This should, therefore, provide a strong statement
on the issue of persistence in individual real estate returns.
Third, this study debates a number of possible reasons why properties might
persist in their relative performance. This is an important issue, not only from the
perspective of investment strategy, but also in terms of the operation of the market. If
relative persistence is found to occur, then it may indicate institutional factors that
prevent the market from operating efficiently. Alternatively, it may demonstrate the
impact of behavioral influences or reveal locational forces that reinforce the success of
certain regions or urban areas. The paper also considers whether these reasons explain
differences between UK, US and Australian findings.
Previous studies
The analysis for the US direct institutional-grade real estate market (Young and Graff,
1996, 1997) used annual returns from the NCREIF database, over the period 1978 to
1994. The study was based on the return performance of 50 Metropolitan Statistical
Areas (MSA) that had at least one occurrence of two consecutive years of data, the total
number of MSAs ranging from eight in 1978 to 44 in 1991. The data was also
decomposed into five property types:
(1) office;
(2) retail;
(3) warehouse;
(4) R&D; and
(5) apartments.
The results for the five property types indicated that for the two extreme quartiles, the
highest and lowest ranks, serial persistence was demonstrated with almost complete
certainty from one year to the next. However, the persistence tended to fade beyo nd
this, except for Apartments where serial persistence was extended to runs of two and
three years. For the combined data, serial persistence was exhibited for one, two, three,
JPIF
25,3
242
four and five years, indicating that real estate returns exhibit persistence for some
considerable time. In contrast, little or no significant serial persistence was found for
the second and third quartiles, except for warehouses over one year and the combined
data for one- and two-years runs. In other words, persistence is exhibited at the
extremes of performance, the best and the worst properties, in any one year but not by
properties around the median.
Graff et al. (1999) applied the same approach to the Australian direct
institutional-grade property market using annual data over the period from 1985 to
1997 from the Property Council of Australia database. The data decomposed into three
property types:
(1) office;
(2) retail; and
(3) industrial.
The results of the analysis showed that serial persistence was exhibited by office and
retail property at the extreme quartiles (the first and fourth) and for the median quartiles
(second and third combined), but that Industrial properties exhibited serial
independence in all categories. In addition, there was a qualitative difference in the
office data between CBD and non-CBD properties. In particular, the Office data in the
CBD locations exhibited serial persistence in all quartiles, but no serial persistence was
found for the non-CBD data, while the combined data exhibited statistical si gnificance in
all quartiles. In other words, superior performance is generally followed by continued
superior performance and inferior performance by continued inferior performance.
Lee and Ward (2001) tested the persistence in performance of direct real estate
returns in the UK between 1981 and 1996 applying the same quartile ranking method
used in previous studies. However, the authors then used a Markov Chain approach
that allowed the estimation of several parameters of interest not readily available from
the binomial approach of Young and Graff (1996, 1997). The sample data consisted of
the total returns on properties in three types, retail, office, and industrial property, in
various local authority districts (essentially towns) in the UK, to give a total of 392
asset possibilities. The authors found that the observed persistence in per formance of
real estate returns in other countries was confirmed and appeared to be fairly stable
between 1981 and 1996. Second, the persistence did not appear to be driven by
volatility, and was robust across sectors, regions, and unaffected by size variations.
The authors also tested a number of trading strategies and concluded that real
estate investors would be better off, in terms of higher returns coupled with a lower
turnover rate, by purchasing properties identified as the best in one period and only
selling those that fall below the median in the next, rather than concentrating
investment in properties from the first quartile. Such a strategy outperformed a
random approach and one that assumed absolute persistence in returns, even after
transaction costs. The evidence suggested two important rules-of-thumb for property
fund managers who wish to maximize performance:
(1) avoid properties with below average performance; and
(2) invest in properties in the upper quartile of performance in one year as they
have a higher-than-average chance of achieving above average returns next
year.
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