Explaining the macro‐economy and retail real estate sector dynamic interaction between prime and suburban retail real estate sectors

DOIhttps://doi.org/10.1108/14635781011024845
Date09 March 2010
Published date09 March 2010
Pages77-108
AuthorKim Hin David Ho,Faishal bin Ibrahim Muhammad
Subject MatterProperty management & built environment
Explaining the macro-economy
and retail real estate sector
dynamic interaction between
prime and suburban retail real
estate sectors
Kim Hin David Ho and Faishal bin Ibrahim Muhammad
Department of Real Estate, School of Design and Environment,
National University of Singapore, Singapore
Abstract
Purpose – From the perspective of the macro-economy and real estate sector interaction, this paper
aims to examine the maturing prime retail real estate sector versus the developing suburban retail real
estate sector.
Design/methodology/approach This paper adopts a highly specific dynamic computable
general equilibrium model under system dynamics programming to structure the resulting system
complexity within the context of Singapore.
Findings Ex post and ex ante model estimations find that the suburban retail real estate sector is on
the whole more susceptible to gross domestic product (GDP) growth policy that affects both GDP
expansion and retail rents in actual and expectation terms as well as returns.
Research limitations/implications – The DCGE model ex ante estimations for the planned
scenarios, under low or high GDP growth for the prime and suburban retail real estate sectors,
enhances understanding of structural factors and dynamic interaction in the maturation phase of the
prime retail real estate sector in Singapore.
Practical implications – In comparison, Singapore’s suburban retail real estate sector is found to
be in a developing phase.
Originality/value – There is limited local research on the underlying relationship between the
economy and the retail real estate sector, although Singapore’s retail sector and retail real estate sector
form an integral part of sustainable economic expansion.
Keywords Real estate, Singapore, National economy,Gross national product
Paper type Research paper
Introduction
Singapore’s economy remains one of Asia’s strongest performers, with retail real estate
generating the highest yield compared to other real estate sectors and constituting an
imperative economic sector (Liow, 2002). Retail rents have been relatively high at
between 6 and 9 per cent p.a., on a gross floor area basis and it does not include
transaction cost and the recovery rate for depreciation purposes. Thus, retail rents can
be even higher if the latter two are included and if rents are stipulated on a net floor
area basis. A key motivation of this paper is the limited local research on the
underlying relationship between the economy and the retail real estate sector, although
the retail sector and its associated retail real estate sector form an integral part of
sustainable economic expansion, In recent years, both the retail sector and the retail
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1463-578X.htm
Explaining the
macro-economy
77
Received June 2009
Accepted November 2009
Journal of Property Investment &
Finance
Vol. 28 No. 2, 2010
pp. 77-108
qEmerald Group Publishing Limited
1463-578X
DOI 10.1108/14635781011024845
real estate sector are becoming increasingly competitive, land use intensive and
regionally concentrated. In addition, the nature of retailing has changed significantly in
the last three decades, owing to growing affluence of the population, its greater
purchasing power and concerted physical planning made by the national planning
authority, the Urban Redevelopment Authority (URA). The URA has been highly
effective in “master planning” the development of enclosed shopping centres in the
prime central districts and suburban new towns. High-rise shopping centers, as
opposed to shop houses and strip shopping in the past, are now the predominant form
and shape of retail real estate to accommodate more retailers.
Another motivation is the limited local research that can distinguish the maturing
prime retail real estate sector and the developing suburban retail real estate sector,
from the perspective of the macro-economy and real estate sector interaction. Such
dynamic interaction can be structured to estimate ex post the changing
macro-economy and the retail real estate sector of interest. This paper therefore
adopts the dynamic computable general equilibrium (DCGE) model under system
dynamics programming to enable in-depth understanding of the non-linear interaction
complexity. The DCGE model itself falls under the broader class of the computable
general equilibrium (CGE) model, which in turn constitutes a class of economic models
that utilize actual economic data to estimate how an economy may react to changes in
policy, technology or other external factors. A CGE model consists of equations
describing model variables, and secondly, a very detailed database that is consistent
with the model equations. The equations are neo-classical in spirit, often assuming
cost-minimizing behavior by producers, average-cost pricing and household demand
based on optimizing behavior. The DCGE model seeks to explain aggregate economic
phenomena like economic growth, business cycles, effects of monetary and fiscal policy
on the basis of macroeconomic models that are consistent with microeconomic theory.
Policy makers would benefit from this paper. This is because the complexity of the
non-linear dynamicinteraction, pertainingto the changing macro-economy and theretail
real estate sector of interest within the Singapore context, enables policy makers to
estimate ex ante the impact of their actions on the prime and suburban retail real estate
sectors. Bakken (1993) highlights that some real estate developers realize that their
judgments arenot always consistent, that a bias in historicaldata may be inevitable, and
that there is a lack of adequate models to help decision makers understand the causes
behind unstable markets (e.g. commodity markets). He mentions that scarce attention
has been given to modeling decisions that may remedy poor real world learning. Thus,
real estate developers, retailers and retail management companies would also benefit
from this paper to enable them to better formulate their marketing strategies and
operations. The DCGE model is estimated, ex post and ex ante, with the help of the
system dynamics programing model – the “iThink” software program developed at the
Massachusetts Institute of Technology (MIT) (Roberts, 1978). Such a model not only
makes use of detailed historical data, but also structures the dynamic complexity of the
dynamic interaction involving thewider macro-economy and the retailreal estate sectors
holistically. Hence, two principal questions can be posed:
(1) Whether or not the dynamic and structura l relationships are rigorously
modeled and estimated among key macroeconomic factors and sector-specific
fundamentals of the prime and suburban retail real estate sectors, in the
sustainable and developed island-state economy of Singapore?
JPIF
28,2
78
(2) Whether or not the DCGE model under the system dynamics programing model
provides the cause-and-effect ex post model estimations and the corresponding
ex ante estimations via concentrating on micro market relationships involving
the prime and suburban retail real estate sectors and changing economic
growth in Singapore?
As a result, this paper is organized into several sections with the first section providing
the introduction. The next (second) section discusses the related literature inclusive of
the overall retail market in Singapore. The third section discusses the DCGE model
under system dynamics programming while the fourth section discusses the model
estimations. The fifth section discusses the results and findings while the sixth section
concludes the paper.
The related literature
There are many definitions of retailing but ultimately they share a common thought.
Lowry (1983) defines retailing as “an activity that includes all sales to the ultimate
consumer”. His concept of retail transactions is very comprehensive, and encompasses
anyone who sells a good or a service to the ultimate consumer for either personal or
family use as beingengaged in retailing. Newmenand Cullen (2002) define retailingas “a
set of activities thatmarkets products or services to final consumersfor their personal or
household use. Theretail sector on the whole has experienced a transition from peddlers
to palaces in most parts of the world, such as the USA (Lowry, 1983; Bartlett, 2003),
Russia (Robinson, 1997), Latin American city (Bromley, 1998), the UK (Jackson, 2001;
Ibrahim and McGoldrick, 2003), Poland (Werwicki, 1992) and Singapore (Ibrahim and
McGoldrick, 2003). Retailing activities are no longer conducted merely for the purposes
of satisfying basichuman physical wants, they also cater to a widerrange of wants. The
effects of retailing are reiterative and have directly and indirectly affected many people.
In Lowry’s (1983) words, “our retailing system provides us with an array of goods and
services that satisfies our material wants and improves our standard of living”.
Townsley (2002) further elaborates that retailing has enabled individuals to be able to
purchase and own items that they cannot produce. As manufacturers of products and
retail stores continue to earn profits from their business activities, they will need extra
help and hence create jobs for the local community. This affects the economy by
lowering unemployment and generating more purchases by individuals. In the UK, the
retail sector employs twice as many employees as the construction industry, four times
as many as the business services and seven times as many as agriculture, forestry and
fishing (William,1997). In the same study, using three casestudies, namely, the Fenland
District Council,the Metro Centre and Cross-Channel Shopping, William (1997) find that
the retail sector generates external income for an area, prevent leakage of income and
also acts as a growth pole and valuable place marketing tools.
Since retail sales account for some proportion of the economic activity in a country,
it implies the inherent relationship between the two; hence it is vital to understand the
macro-determinants of the retail industry. However, most retailing and shopping
related studies have concentrated on shopping behavior, which is concerned with the
consumer and his preferences (Ibrahim and McGoldrick, 2003). From the developer’s
perspective, an extensive literature can be found concerning the selection of the ideal
retail tenant mix (Gerbich, 1998), the determinants of shopping centre rents (Sirmans
and Guidry, 1993), the impact of anchor stores (Konishi and Sandfort, 2003) as well as
Explaining the
macro-economy
79

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