SINGAPORE PROPERTY RESEARCH FORUM
Theme: Property Issues Close to Heart
Dynamics of Condominium
Market in Singapore
Dr. SING Tien Foo
Centre for Real Estate Studies (CRES)
Department of Real Estate
School of Design & Environment
National University of Singapore
Date:31 August 2002
Outlines of Presentation
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Introduction
Condominium Market in Singapore
Literature Review
Theoretical Framework
 Condominium Housing Market Structure
 Empirical Model Specification
Empirical Analysis & Data
 Data Source
 Empirical Results
Simulation Analysis
Conclusion
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Introduction
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Condominium housing is the largest private residential
property market in Singapore
It accounted for 38% of the total available private residential
stock (Figure 1)
Together with apartments, non-landed constituted 2/3 of the
accumulated stocks
By ownership status, 66% of the total 193,319 units of
completed private residential properties in Singapore (as at
2nd quarter 2001)
74.8% of the condominium & apartment units owned by
Singaporeans
Owning private residential properties is every Singaporean’s
dream
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Fig 1: Ownership of Completed Private
Residential Properties by Type
(As at end 2nd Quarter 2001)
5.05%
10.32%
18.65%
65.98%
Detached House
Terrace House
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Semi-Detached House
Apartment & Condominium
Historical Condominium Price Trends
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Divergence of prices and monthly income especially from 3Q94
to 2Q96
Quarterly compounded growth figures (3Q94 – 2Q96):
 URA condominium price index = 19.5% (Figure 2)
 Average all industries’ monthly earnings = $5.92%
Serious concern on the affordability of private residential
properties
A slew of deliberate anti-speculation measures imposed by
government on May 15, 1996 to stamp out speculative activities
Two key measures:
 Imposition of a 80% loan to value limit on mortgage
 Stepping up of supply via government’s land sale program –
to increase supply from 6,000 to 7,000-8,000 units per
annum
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Fig 2: Historical Condominium Price and Return Trends
25%
350
Rate of Change of Prices
URA Condominium Price Index
300
15%
250
10%
200
5%
150
0%
100
Condominium Price Index
Rate of Change of Prices (%)
20%
-5%
50
-10%
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2000 1Q
1999 1Q
1998 1Q
1997 1Q
1996 1Q
1995 1Q
1994 1Q
1993 1Q
1992 1Q
1991 1Q
1990 1Q
1989 1Q
1988 1Q
1987 1Q
1986 1Q
-15%
1985 1Q
Source: URA
0
Year-Qty
Land Sale Policy Instruments
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The land sale program in May 1996 and the slowing down in
demand caused by the recession in 2001 sent the market into
doldrums
18,205 uncompleted units with sale licenses remained unsold
as of the 2nd Quarter 2001
In the off-budget measures announced on 13 October 2001,
land sale program is used against to regulate the market
movement
The land sale has been deferred/halted to tighten the supply
and to shore up the sluggish property market
Market intervention via land sales and mortgage rationing have
been adopted from time to time to smoothen undesirable
market volatility
How effective and how long would the measures take to
influence the market movement? – An important policy question
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Property recovery depends on economic
recovery – Mr Mah
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“Off-Budget measures to stabilise the property
market will not have an immediate effect, but will
help boost confidence and help the real estate
industry ride out the downturn.”
“The measures will not on their own help the real
estate industry to recover. Ultimately, the recovery
of the real estate sector will depend on the
recovery of the economy as a whole.”
Mr Mah Bow Tan,
Minister for National Development
At the 42nd Annual Dinner of the REDAS
Reported in Business Times (by Kalpana Rashiwala)
10 November 2001
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Motivation of Study
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Motivation of study –
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To understand the market dynamics of the condominium markets
To examine economic & property market forces that drive price,
demand and supply of the condominium market
Earlier studies in Singapore – Ho and Tay (193), Ho and
Cuervo (1999) and Tu (2001)
Three main differences in this study
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It focuses on private condominium market
It empirically tests the effects of the May 1996 anti-speculation
measures / policies
It simulates the exogenous shocks of variables and analyses the
effects of changes in these variables on the market dynamics
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Condominium Market in Singapore
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Condominium housing concept was brought into Singapore in
1974
High-rise & high-density living with recreational facilities
1970s slow take-off due to unfamiliarity of the condominium
living & lack of knowledge of owner’s preference
The demand and popularity of condominiums rose in the
early 1980s
 Rapid economic growth
 Influx of multinational corporation & foreign talents
 Relaxation of the Central Provident Fund rule to allow
members to draw on the Approved Residential Property
Scheme (ARPS) to purchase private properties
The 1985 economic recession caused a market slump that
was beset by excessive supply and declining demand
Economic forces and their effects on the condominium
market
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Historical performance of Condominium
Market
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After hitting the trough in 1985, prices rebound in 2Q86 with a 2.09%
quarter-to-quarter growth
Prices peaked in 2Q1996 with an 11.70% jump in quarterly price
index (Figure 2)
Government introduced anti-speculation measures to cool the market
in May 1996
The first reversal of the upward trends occurred in 3Q96 and hit the
trough in 4Q98
Price declines aggravated by the 1997 financial crisis – ranged
between –7.15% and –10.08% in 1998
Supply surplus culminated in 4Q1997 – government’s stepping up of
land sale program
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From 5,870 units (95) to 10,472 units (96) and 16,471 units (97)
Stock were depleted rapidly between 3Q1997-4Q2000 due to pent-up
demand by public housing up-graders (Figure3)
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Fig 3: Historical Take-up and Commencement of
Condominium Housing
6000
Demand
Housing Start
Supply Shortfall
4000
3000
2000
1000
4Q00
2Q00
2Q99
4Q99
4Q98
4Q97
2Q98
2Q97
2Q96
4Q96
4Q95
4Q94
2Q95
2Q94
2Q93
4Q93
4Q92
4Q91
2Q92
2Q91
2Q90
4Q90
4Q89
4Q88
2Q89
0
2Q88
Number of Condominium units
5000
-1000
-2000
Qtr-Year
-3000
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Overseas Housing Market Literature
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Extensive housing studies in UK & North America
Earlier studies place significant emphasis on data coherency
and neglect theoretical underpinnings
Micro-foundation of empirical housing models
 Neo-classical equilibrium framework
 Davidson, Hendry, Srba and Yeo (1978) and Hendry (1984)
 In classical Hendry’s cubic excess demand model, existing
housing prices is a function of personal disposable income,
rental rate, interest rate, mortgage stock, tax rate and
number of families
 New housing (Dicks, 1990), Investment Demand (Hsieh,
1990)
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Different Housing Models
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Investment-based model – Marshallian’s marginal rate of
return concept
 Topel & Rosen (1998), Mortgomery (1996)
Incorporating Stock-flow process
 Wheaton and DiPasquale (1994)
User cost of capital concept
 Dougherty and Van Order (1982), Poterba (1984),
Credit rationing effects
 Breedon and Joyce (1992), Meen (1990, 1995, 1996)
Ad-hoc model - Smith (1969)
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Singapore’s Housing Literature
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User cost of capita model (Tu, 2001)
Single equation cointegration model (Ho Cuervo,
1999)
Two-stage least square model (Ho and Tay, 1993)
Price discovery between private and public housing
markets (Ong and Sing, 2002)
Inflation hedging characteristics of private residential
properties (Sing and Low, 2001; Chen and Sing, 2000)
No econometric modeling on condominium market
Effects of land supply and credit rationing policies on
condominium market dynamics are not examined
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Theoretical Framework
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Condominium housing market structure (Figure 4)
5 key players in the real estate markets
Government
 Management of macro-economic policy & regulatory role in
development planning & control
Firms
 Output performance translated into higher stock prices
 Increased in remuneration of staff & employment
Financial institutions
 Origination of mortgage loan –Households
 Changes in demographic patters and user costs of capital
 Consumption & investment demand of housign
Developers
 Construction starts and costs management
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Macro-Economic Shocks:
Condominium Housing Market Structure
Development
Financing
Government
Development Planning
& Controls /
Macro-Economic Policies
Space demand:
Housing demand:
Developers
Housing Supply:
Profits
Construction cost
Land cost
Cost of capital
Demographic changes
Wealth & Disposable Income
Appreciation of asset prices
Stock market investment
Housing stocks & expectations
Others
Construction
Households
Residential
Space Market
Business Expansion
Industrial Output Increases
Rising Stock Prices
Low Interest Rates
Others
Residential
Capital Market
Firms
Capital Asset
Investment & Holding:
Risk Premium&
Diversification
Optimal Portfolio
Mortgage
Financing/
Securitization
New Completion
Existing Supply
& Vacancy
Gross Domestic Products
Money Supply
Exchange Rate
Stock Market Volatility
Expected & Unexpected Inflation
Tax Rate/ Regime
Term Structure Changes
Foreign Reserve
Deposits
Financial
Institutions
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Interaction &
Market Equilibrium
Empirical Models Specification
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Empirical Model Specification (Table 1)
Equilibrium framework – Demand & Supply side factors
Three structural equations:
Demand model
HDt =  (GDP, HF, IR, CPI, STI, P)t-i
Supply Model
Supply, HCt =  (BMC, LRC, PLR, P, HS, HC)t-i
Price Model
Price, P* =  (GDP, HF, IR, CPI, STI, Pt-i, BMC, LRC, PLR, HS,
D96Q4)t
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D96Q4 is a time dummy variable that represents the
policy effects of the May 1996 measures (80% credit
limit and planned increase in supply)
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Key Model Variables
HD
GDP
HF
IR
STI
P
BMC
LRC
PLR
HS
= Demand function represented by incremental change in
occupied condominium housing stocks
= Supply function represented by the change in
commencement of new condominium housing stocks
= Gross Domestic Product
= Household Formation
= Interest Rate for Housing Loan
= Stock Exchange All Share Price Index
= Condominium Price Index
= Basic Material Costs
= Labour Costs
= Prime Lending Rate
= Stock of Completed Condominium
HCt-i
= Lagged period condominium housing Commencements
HC
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Empirical Analysis & Data
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Quarterly economic and condominium market data were
collected for a 12-year sample period from 1988 to 2000
(Table 2)
Five main public sources:
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URA, MAS, DOS, BCA, ROM
Data limitations
 No time-series data on mortgage stocks, historical tax
rate, rent variables, household disposable incomes
 Condominium stocks is I(2)
Data are I(1) stationary – conversion of the data into logdifferenced series
Empirical Results (Table 3)
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2SLS Multiple Regression Results
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See Table 3
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Summary of Empirical Results
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Price model
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Demand model
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Last quarter inflation rate, last two quarters stock market returns and
current housing stocks have positive effects no condominium price
changes
Negatively related to 2-quarter lagged housing stocks and contemporary
mortgage rate
D96Q4 is significant – the anti-speculation measures have dampening
effect on prices
Negatively related to 2-quarter lagged price change, 1-quarter lagged
stock price change, demand in two previous quarters and 1-quarter
household formation
GDP and inflation in the previous quarter have positive effects on demand
Supply model
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Negatively related to last quarter housing stock, prime lending rate, and
construction commencements two quarter ago
Also adversely affected by the last 2-quarter labor costs
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Simulation Analysis
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Assuming that coefficients for the price, supply and demand
model determinants remain unchanged
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Ex-post predicted demand and new supply of condominium
stocks are simulated
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Ex-post predicted surpluses and actual surpluses are shown
(Figure 5)
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Supply surplus is defined as the difference between new
condominium commencement & occupied housing stock
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Expected predicted surpluses (374 units) against expected
actual surpluses (historical) (633units)
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Predicted new supply 1,310 (predicted surpluses = 28.56%)
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Fig 5: Actual and Predicted Surpluses (Shortfalls) in
Condominium Stocks
6000
Predicted Surplus (Shortfall)
Actual Surplus (Shortfall)
5000
3000
2000
1000
0
19
88
19 4Q
89
19 3Q
90
19 2Q
91
19 1Q
91
19 4Q
92
19 3Q
93
19 2Q
94
19 1Q
94
19 4Q
95
19 3Q
96
19 2Q
97
19 1Q
97
19 4Q
98
19 3Q
99
20 2Q
00
20 1Q
00
4Q
Condominium Units
4000
-1000
-2000
-3000
Year Qtr
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Simulation Results
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Shocking the Exogenous Variables
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One standard deviation shocks on exogenous
variables in the demand and supply models
Monte-Carlo simulation analysis
42.10 % probability that historical oversupply
condition (surpluses) in the condominium market
would improve, i.e. will drop below the expected
surpluses of 374 units (Figure 6)
Market clearing condition is most sensitive to lagged
quarter condominium stock shocks
Other sensitive factors are 1-quarter lagged inflation
rate and GDP growth and prime lending rate
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Conclusion
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Land supply and mortgage rationing on loan quantum have been
effective as policy tools to regulate condominium demand and
supply in Singapore
There were significant corrections of prices in the 4Q96 and 1Q97
1% increase in mortgage rate will cause the current condominium
price to drop by 0.46%
1% increase in condominium housing stocks will dampen the
condominium price by 0.85% two quarter ahead
On demand, GDP growth and inflation rate are positive signals for
new demand
Demand is inversely affected by lagged quarter stock price and 2quarter house price and demand in the previous 2 quarters
For new condominium commencement, the last quarter housing
stocks, prime lending rate and new construction commencement
have adverse effects on supply
Thank you
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