A cointegration approach to the price dynamics of private housing. A Singapore case study

Pages35-60
Published date01 March 1999
DOIhttps://doi.org/10.1108/14635789910252891
Date01 March 1999
AuthorDavid Ho Kim Hin,Javier Calero Cuervo
Subject MatterProperty management & built environment
Academic papers:
Price dynamics
of housing
35
ACADEMIC PAPERS
A cointegration approach to
the price dynamics of private
housing
A Singapore case study
David Ho Kim Hin
Pidemco Land Limited, Singapore and
Javier Calero Cuervo
School of Building and Real Estate, National University of Singapore,
Singapore
Keywords Cointegration, Housing (domestic property), Singapore
Abstract This paper looks into the dynamics of private housing prices in Singapore from the first
quarter of 1985 to the fourth quarter of 1995. Employing the cointegration analysis, the paper
shows that overall private housing price is cointegrated with real gross domestic product, prime
lending rate and private housing starts. An error-correction mechanism is also incorporated in the
estimation of changes in the overall private housing price to account for the short-run deviations
from the equilibrium relationship among these variables.
Introduction
This paper looks at the dynamics of private housing prices of Singapore and
investigates whether prices, on the whole, move in tandem with the economy as
inferred from the general equilibrium theory. Cointegration modelling (CM) will
be carried out to determine if there is a long-term equilibrium contempor aneous
relationship between private housing prices in Singapore and other relevant
macroeconomic and property-specific variables.
CM is concerned with cointegration analysis, one of the popular
developments in time series econometric modelling introduced by Engle and
Granger (1987). Cointegration refers to a linear combination of non-stationary
variables (Enders, 1995). A time series variable is non-stationary if its mean is
increasing over time. Many economic variables in their levels, such as gross
domestic product, housing prices and stock prices, are non-stationary variables.
Two variables are said to be cointegrated if these two non-stationary variables,
though stationary after differencing, can be linearly combined such that the
combination is stationary in levels (Sing, 1995). Thus, if two time series
variables are cointegrated, then their trends would adjust to an equilibrium
state, and error-correction models (ECM) could be identified to adjust for shor t-
run deviations (Ong, 1994). Equilibrium theory involving non-stationary
Journal of Property Investment &
Finance, Vol. 17 No. 1, 1999,
pp. 35-60. © MCBUniversity Press,
1463-578X
Received 11 March 1997
Revised 18 July 1998
The research register for this journal is available at
http://www2.mcb.co.uk/mcbrr/jpif.asp The current issue and full text archive of this journal is available at
http://www.emerald-library.com
JPIF
17,1
36
variables requires the existence of a combination of the variables that is
stationary (Enders, 1995).
The cointegration methodology applied in this study takes from the original
articles of Engle and Granger (1987), Johansen and Juselius (1990) and Johansen
(1995). A recent comprehensive treatment of the methodology is presented by
Greene (1997).
The paper’s main objective is to develop an explanation-based cointegration
model which would explain the price dynamics of the private housing price in
the short term using the vector error-correction mechanism (VECM). This
paper also seeks to test whether cointegration relationships exist between
private housing prices, real GDP, prime lending rate and private housing starts.
This paper is to be distinguished from earlier cointegration studies on the
private housing prices in Singapore by the use of the error-correction
mechanism using both the Engle-Granger and Johansen methodologies; and in
the development of the VECM model to make a short-term forecast of changes
in private housing price. The paper seeks to achieve the following objectives:
That private housing prices show a long-term contemporaneous
stationary relationship with key macroeconomic fundamentals reflected
in the following: prime lending rate (PLR), changes in gross domestic
product (GDP), and the number of private housing units commenced for
construction (PST).
That the contemporaneous convergence of these four variables exhibits
minimum systematic error due to the presence of an error-correction
mechanism.
Since the objective of this paper is to determine if a long-term contempor aneous
relationship exists among economic variables in the real estate market, a VECM
was seen as more relevant compared to using a “leading indicator” approach or
a “structural demand and supply” model.
The VECM developed in this paper enhances the cointegration modelling by
incorporating an essential er ror-correction mechanism to account for the sho rt-
term deviations, and their persistence, from the long-run equilibrium
relationship.
A “leading indicator” approach would have been more appropriate if the
objective of the study were to determine the cyclical patterns, duration and
magnitudes of real estate price, for the purpose of making a sho rt-term forecast
for example. Likewise, the “structural demand and supply” model would have
been more appropriate compared with the VECM if the objective of the study
were to establish causal relationships for structural analysis; to determine
elasticities and multipliers for policy analysis; and to make forecasts for
planning purposes.
This paper is organised into four major parts. The first part shows the
dynamics of private housing price using the real estate market framework. This
is followed by an explanation of the relationships of private housing and the
macroeconomy with specific reference to movements in gross domestic product,

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