A cointegration approach to understanding Singapore’s industrial space supply
| Pages | 96-115 |
| Date | 01 April 2002 |
| Published date | 01 April 2002 |
| DOI | https://doi.org/10.1108/14635780210420007 |
| Author | Yuen Leng Chow,Seow Eng Ong,Doreen Chze‐Lin Thang |
| Subject Matter | Property management & built environment |
JPIF
20,2
96
JournalofPropertyInvestment&
Finance,Vol.20No.2,2002,
pp.96-115.#MCBUPLimited,
1463-578X
DOI10.1108/14635780210420007
ReceivedJuly2001
Revisedandaccepted
November2001
ACADEMICPAPERS
Acointegrationapproachto
understandingSingapore's
industrialspacesupply
YuenLengChow,SeowEngOngand
DoreenChze-LinThang
DepartmentofRealEstate,NationalUniversityofSingapore,Singapore
KeywordsIndustrialproperty,Cointegration,Realestate,Modelling,Singapore
AbstractObservesthatthetimelyandsufficientprovisionofindustrialspacehelpstofacilitate
industrialactivitiesthatcontributetoeconomicgrowth.Anunderstandingoftheinteractions
betweentheeconomyandtherealestatemarketisusefultolocalpolicydecisionmakersand
developersinensuringthereadyavailabilityofindustrialspacewithoutincurringunnecessary
excessvacancy.Thisarticlehopestobuilduponexistingresearchbyapplyingcointegration
analysisanderror-correctionmodellingtoexaminethesupplydynamicsofSingapore'sindustrial
propertymarket.Thepresenceoflong-runequilibriumrelationshipsbetweenindustrialproperty
supply,economicandrealestatevariablesistestedusingcointegrationanalysis.Thepersistence
profileexaminestheeffectofsystem-wideshockstothecointegrationrelationstodetermine
whethertheyaretruecointegratingvectors.
1.Introduction
Thetimelyandsufficientprovisionofnecessaryinfrastructuretoindustrialists
isoneofthekeycomponentsinensuringcontinuedmanufacturinggrowth.Ina
realestatecontext,necessaryinfrastructureusuallyreferstotheprovisionof
utilitiestofactoriesandindustrialspacetocarryouttheproductionactivities.
Intheshort-term,businessandemploymentopportunitieswillbelostwhen
thereisinsufficientsupplyandhighdemandintheindustrialpropertymarket.
Conversely,whenthereisanover-supplyandlowdemandintheindustrial
propertymarket,thecapitalsunkintheindustrialpropertiescouldhavebeen
betterinvestedinothersectorsoftheeconomy.
Fromaninvestor'sviewpoint,investinginapropertydevelopmentprojectis
bothcapitalintensiveandrisky.Industrialprojectshaveaminimumproject
gestationperiodofapproximatelytwoyears[1].Manyfactorscanhappen
duringthisdevelopmentperiodthathaveaneffectonprojectprofitability.
Oftentheproject'sreturnoninvestmentisbasedonprojectedfuturevaluesof
variouseconomicandrealestatevariables.Changesintheeconomicclimate
caninfluencemarketsentiments,resultinginacorrespondingchangein
therentorpricetheprojectcommandsuponcompletion.Eventhough
pre-marketingtheuncompletedprojectmaycircumventthesefactors,the
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The authors would like to thank the two anonymous referees for their helpful comments. The
errors, if any, remain the responsibility of the authors.
Academic papers:
Industrial
space supply
97
developer still shoulders the possibility of foregoing the higher returns in a
more favourable market.
Therefore, understanding how the economy interacts with the real estate
market is useful when examining the supply of industrial space, whether from
an investor's viewpoint or macroeconomic viewpoint. This understanding
enables the astute investor to map appropriate strategies that maximise
profit and minimise risk for different investment scenarios, while the timely
and sufficient provision of industrial space facilitates economic growth as
industrialists' demand for manufacturing space is met.
While research in the industrial property market is limited, the research
methodologies used in existing literature are comprehensive. Various
econometric modelling methodologies like ordinary least squares (OLS) single-
equation modelling (Wheaton and Torto, 1990; Giussani and Tsolacos, 1994;
Tsolacos, 1995), simultaneous equations modelling (Koh, 1987; Thompson and
Tsolacos, 2000) and vector autoregression modelling (Kling and McCue, 1991)
have been applied to model the dynamics of the industrial property market.
This paper hopes to build upon existing research by applying cointegration
analysis and error-correction modelling to examine the supply dynamics of
Singapore's industrial property market. A data series' underlying long-run
information is often removed when the series is detrended or differenced.
By using non-stationary variables in modelling the long-run relationship,
cointegration analysis has the benefit of retaining this important statistical and
economic information.
This paper aims to determine whether long-run equilibrium relationships
exist between industrial building supply, economic and real estate variables. If
stable equilibrium relationships exist, error correction modelling can be applied
to identify the long-run relations and short-run dynamics adjustments.
Conclusions from this research would assist both local policy makers in their
assessment of providing industrial space and developers in making informed
decisions to reduce their downside risk in property development.
This paper is organized into six sections. Section 1 gives a brief background
to the research topic and states the aims of the paper. Section 2 is a literature
review of theoretical and empirical models of industrial building supply.
Section 3 discusses the research hypothesis and assumptions of the paper.
Section 4 gives a brief overview of the methodology adopted and builds the
empirical model with variables selected from literature reviews. Empirical
testing to the model is detailed in Section 5, along with discussions about the
results. Section 6 concludes and provides suggestions for further research.
2. Literature review
2.1 Theoretical models
Early research assumes a predominant owner-occupier market and that
development of new industrial properties is determined by a company's capital
investment behaviour. In recent years, there has been a shift in the theoretical
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