Singapore’s Property Market and the Macroeconomy

Presentation by: Tilak AbeysingheDepartment of Economics, NUS

Contributors: Choy Keen MengGu JiayingEnrico TanYong Yik WeiChong Soo Yuen

The Tools of the AnalysisThe Tools of the Analysis

Main Model:Main Model:ESU01 (62 equations)ESU01 (62 equations)By Tilak Abeysinghe and Choy Keen Meng By Tilak Abeysinghe and Choy Keen Meng (Book is out, (Book is out, ““The Singapore Economy: The Singapore Economy: An Econometric PerspectiveAn Econometric Perspective””, , RoutledgeRoutledge 2007)2007)

Objectives of the model:Objectives of the model:Understanding SingaporeUnderstanding Singapore’’s macroeconomic structures macroeconomic structurePolicy AnalysisPolicy AnalysisForecastingForecasting

The Tools of the AnalysisThe Tools of the Analysis

ESU MultiESU Multi--country model (12 equations)country model (12 equations)By Tilak AbeysingheBy Tilak Abeysinghe

NBER Working paper and other publicationsNBER Working paper and other publications

Objectives of the model:Objectives of the model:Transmission of shocks to GDP across bordersTransmission of shocks to GDP across bordersForecasting to generate FORGDPForecasting to generate FORGDPFirstFirst--cut forecasts on Singaporecut forecasts on Singapore’’s GDP growths GDP growth

The Tools of the AnalysisThe Tools of the Analysis

Housing market model Housing market model (Satellite model for ESU01)(Satellite model for ESU01)By Tilak Abeysinghe and Gu JiayingBy Tilak Abeysinghe and Gu Jiaying

6 equations:6 equations:Long run equilibrium priceLong run equilibrium priceShort run price adjustmentsShort run price adjustmentsHousing stock adjustment (identity)Housing stock adjustment (identity)New housing supply (residential investment)New housing supply (residential investment)Vacancy rateVacancy rateUser cost of housing (identity)User cost of housing (identity)

Plus some bridging equationsPlus some bridging equations

Projections on the Singapore Projections on the Singapore economyeconomy

Medium term projections (last chapter of the Medium term projections (last chapter of the book)book)

Under very plausible assumptions about external Under very plausible assumptions about external demand and assuming investment and labor inflows demand and assuming investment and labor inflows continue, continue, Singapore is likely to grow by 6Singapore is likely to grow by 6--7% over the next 7% over the next decade.decade.

Projections on the Singapore Projections on the Singapore economyeconomy

Short term forecasts (barring unexpected events)Short term forecasts (barring unexpected events)

2007Q4 is likely to register another healthy growth rate 2007Q4 is likely to register another healthy growth rate close to 9%.close to 9%.2008 growth may exceed 8%. Lower bound 6.5%2008 growth may exceed 8%. Lower bound 6.5%

Projections on the Singapore Projections on the Singapore economyeconomy

Why the optimism?Why the optimism?

The model picks up the increased intraThe model picks up the increased intra--regional trade regional trade effect, especially China (see next slide)effect, especially China (see next slide)

0.0-3.5-0.5-1.6-1.90.66.6-0.2-0.10.50.10.1ROECD

-0.20.0-2.73.90.0-0.90.3-0.30.00.00.00.1USA

-4.0-8.40.08.61.70.22.7-0.51.10.2-0.6-0.9Japan

4.3-2.9-0.60.0-6.7-0.32.90.40.60.61.00.8China

-3.4-7.7-0.311.30.0-0.50.7-0.10.10.00.0-0.4HK

-4.2-9.9-2.420.0-5.20.00.90.10.20.0-0.10.5Taiwan

-3.8-5.5-2.615.0-0.3-0.30.0-1.10.2-0.1-0.8-0.6S-Korea

-3.7-15.43.010.33.0-0.30.40.00.60.71.30.1Phil

-2.2-6.1-0.25.50.7-1.10.60.50.01.62.1-1.5Thai

-4.3-8.56.55.2-2.6-0.92.90.41.30.01.5-1.4Indo

-3.3-2.2-2.05.01.5-0.90.5-0.12.20.90.0-1.6Mal

-1.6-7.7-1.25.92.2-0.80.9-0.40.25.0-2.50.0Spore

RestOECDUSAJapChinaHK

Taiwan

S-KoreaPhilThaiIndoMalSpore

Percent Change in export shares between 2000 Percent Change in export shares between 2000 and 2006and 2006

SingaporeSingapore’’s Housing Markets Housing Market

Property Price Indices, HDB resale and private

0

20

40

60

80

100

120

140

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

HDBPrivate

Annual Rate of Change of Price (%)

-40-30-20-10

01020304050607080

1991 1993 1995 1997 1999 2001 2003 2005 2007

HDB

Private

Property Price and Rent Indices

30405060708090

100110120

1990 1992 1994 1996 1998 2000 2002 2004 2006

PPI

Rent

Vacancy Rate (%)

0

2

4

6

8

10

12

1988 1989 1991 1992 1994 1995 1997 1998 2000 2001 2003 2004 2006

Subsale Rate (%)

05

1015202530

1995 1996 1997 1998 2000 2001 2002 2003 2005 2006

Housing StockHousing Stock

0.30.31.7-0.1-0.010.30.8-1.4Growth

1001211112456233364879092651532078793304162727362006

998031108922229356879566651602072993277012766052005

TotalHDB+Exec5-room4-room1,2,3-

room

Rented or

VacantTotalPrivate

HDB and Other Govt

Housing Wealth InequalityHousing Wealth Inequality

50%50%Value (estimate)

20%80%Stock (units)

Private Share

Public Share

ModelModelAdaptation of the StockAdaptation of the Stock--Flow model Flow model

S

tS

etP

1( )t tE P−

P

1(1 )t t tH H Sδ −= − +

D

tP

D

S

Determination of LongDetermination of Long--run run Equilibrium Price Equilibrium Price

FF = total number of households (F to indicate family units)= total number of households (F to indicate family units)DD = proportionate demand (fraction of F who want to own a house)= proportionate demand (fraction of F who want to own a house)P*P* = long= long--run equilibrium pricerun equilibrium priceYYdd = per capita disposable income= per capita disposable incomeFWFW = per capita financial wealth, best proxy CPF balances= per capita financial wealth, best proxy CPF balancesUCUChh = user cost of housing= user cost of housingHH = housing stock (cumulative housing investment)= housing stock (cumulative housing investment)v*v* = natural vacancy rate (assumed to be constant)= natural vacancy rate (assumed to be constant)SS = new supply of property (residential investment in our case)= new supply of property (residential investment in our case)δδ = House depreciation rate (set at 3% per annum; en block sale ef= House depreciation rate (set at 3% per annum; en block sale effect?)fect?)

* *( , , , ) (1 )d ht t t t t t tF D P Y FW UC H v= −

1(1 )t t tH H Sδ −= − +

User cost of housing (demand side)User cost of housing (demand side)Mortgage payments or imputed rentsMortgage payments or imputed rentsManagement feesManagement feesOther maintenance costsOther maintenance costsProperty taxProperty taxExpected house price inflationExpected house price inflationOther shortOther short--term policy measuresterm policy measures

e.g. 1996 capital gain tax, loan ceiling 80% etc.e.g. 1996 capital gain tax, loan ceiling 80% etc.

Expected profits (supply side)Expected profits (supply side)Expected priceExpected priceLabor costLabor costLand priceLand priceBuilding material pricesBuilding material pricesDevelopment and other government charges Development and other government charges

1( )t tE P+

Assuming a logAssuming a log--linear relationship:linear relationship:

Solve for:Solve for:

Regular data series on Regular data series on FFt t , the number of households, are not available. , the number of households, are not available. Therefore, assumeTherefore, assume

FFtt = kPOP= kPOPt, t,

POP = POPR + POPF = resident POP + foreign POP 15POP = POPR + POPF = resident POP + foreign POP 15++

Proportionality doesnProportionality doesn’’t hold with respect to resident population; k seems to have t hold with respect to resident population; k seems to have increased over time due to the switch to nuclear families. But wincreased over time due to the switch to nuclear families. But with respect to ith respect to total population, k may be constant. total population, k may be constant.

Total population instead of resident population will capture theTotal population instead of resident population will capture the demand for demand for rental units too.rental units too.

*1 2 3 4

log log loglog log log log log

t t t

d ht t t t t

F D H constantD P Y FW UCβ β β β+ = +

= + + +

*2 3 4

1

1log [log log log log log ]d ht t t t t tP H F Y FW UCβ β β

β= − − − −

Previous formulation yieldsPrevious formulation yields

Estimating equation:Estimating equation:

Theoretically, Theoretically,

*2 3 4

1

1log [log( / ) log log log ]d ht t t t tP H POP Y FW UC constβ β β

β= − − − +

*0 1 2 3 4log log( / ) log log

( ) ( ) ( )( )

dt t t t tP H POP Y CPF t uα α α α α= + + + + +

− + −+

1 2 3 4.100 0α α α α+ + + =

The estimated longThe estimated long--run equilibrium price equation:run equilibrium price equation:

(this is a cointegrating regression)(this is a cointegrating regression)

Calibrated equation:Calibrated equation:

*log 2.8log( / ) 2.3log 1.6log 0.008dt t t tP constant H POP Y CPF t= − + + −

*log 2.8log( / ) 2.2log 1.6log 0.0025dt t t tP constant H POP Y CPF t= − + + −

In terms of annual percentage growth ratesIn terms of annual percentage growth rates

PP**growth = growth = --2.8(2.8(HHgrowthgrowth--POPPOPgrowth) growth) +2.2+2.2YYddgrowth+1.6growth+1.6CPFCPFgrowthgrowth--1.01.0

= = --2.82.8HHgrowth+2.2growth+2.2POPRPOPRgrowth+0.6growth+0.6POPFPOPFgrowthgrowth+2.2+2.2YYddgrowth+1.6growth+1.6CPFCPFgrowthgrowth--1.01.0

Demand growth = Demand growth = --0.40.4PP**growth+0.8growth+0.8YYddgrowth+0.6growth+0.6CPFCPFgrowthgrowth+0.8+0.8POPRPOPRgrowth+0.2growth+0.2POPFPOPFgrowthgrowth--0.40.4

A breakdown of Property Price Inflation RateA breakdown of Property Price Inflation Rate

7.0

Trend Property Price Inflation Rate since 1977

17.7Total

-1.0-1.0-Constant (User Cost of H)4.81.63.0CPF per capita8.12.23.7

Disposable income per capita

6.70.5612.0POP Foreign 15+4.02.241.8POP Resident-5.0-2.81.8H stock

Contribution toLong Run

Property Price Inflation (%)

(2)x(3)

Elasticity Estimates

(3)

Average annual growth (%)

2005Q1-2007Q2(2)

LongLong--run equilibrium property pricerun equilibrium property price

1975 1980 1985 1990 1995 2000 2005

2.0

2.5

3.0

3.5

4.0

4.5 Actual PPI (log scale)

Equilibrium PPI and its trend

Projected property price inflation based on:Projected property price inflation based on:Population growth = 2.6%Population growth = 2.6%Disposable income per capita growth = 4%Disposable income per capita growth = 4%CPF balances per capita growth = 4%CPF balances per capita growth = 4%Property supply (units) below (gross, not net of en block scrapsProperty supply (units) below (gross, not net of en block scraps))

(short run dynamics ignored)(short run dynamics ignored)

3.46.5275415167272010

3.26.5258688158462009

13.72.824284265792008

18.01.223626328992007

2333642006

House price inflation

Growth rate of

H stock

PrivateStock(Units)

PlannedSupply

(from ST)Year

ShortShort--run price adjustmentsrun price adjustmentsDependent variable = Property Price InflationDependent variable = Property Price InflationSample period 1995Q1 Sample period 1995Q1 –– 2007Q2, R2007Q2, R22 = 0.78= 0.78

ln tPPIΔ

0.240.001-3.62-0.06Error Correction Term ( )0.090.0571.960.18Subsale Rate ( )0.140.014-2.57-0.79Vacancy Rate ( vt )0.170.007-2.86-1.65User cost growth ( )0.060.1041.660.48CPF growth ( )0.260.0003.800.35Disposable income growth ( )0.550.0007.130.59

0.120.0242.350.06ConstantPartial R2t-probt-valueEstimate

1ln tPPIΔ −

ln dtYΔ

1ln tCPFΔ −

ln htCPIΔ

tSUBSRΔ*

1 1t tP P− −−

Impact of a 1% increase in PPI on the macroeconomy (from Impact of a 1% increase in PPI on the macroeconomy (from ESU01 model)ESU01 model)(% change from the baseline)(% change from the baseline)Note the drop in consumption expenditureNote the drop in consumption expenditure

-.05

.00

.05

.10

.15

.20

.25

0 4 8 12 16 20 24 28 32 36

GDPInvestment

Construction InvestmentConsumption

Quarters

% C

hang

e

Cumulative impact of a 1% increase in PPICumulative impact of a 1% increase in PPIGDP increases only by 0.13% over the baseline after 5 yearsGDP increases only by 0.13% over the baseline after 5 yearsObviously construction investment increase is the largest, 1.6%Obviously construction investment increase is the largest, 1.6%

-0.4

0.0

0.4

0.8

1.2

1.6

2.0

0 5 10 15 20 25 30 35

GDPConstruction Investment

InvestmentConsumption

Quarters

% C

hang

e

Price bubbles caused byPrice bubbles caused byDemandDemand--supply imbalancessupply imbalancesPanic buying and speculationPanic buying and speculation

Why price bubbles should be avoidedWhy price bubbles should be avoidedEffect on consumption expenditure. Loss of a Effect on consumption expenditure. Loss of a builtbuilt--inin--stabilizerstabilizerBubbles create persistent market disequilibrium Bubbles create persistent market disequilibrium due to the Cobbdue to the Cobb--Web phenomenon in the Web phenomenon in the property marketproperty marketIncome redistribution; who gets richer?Income redistribution; who gets richer?

Falling consumption share of disposable Falling consumption share of disposable income and property priceincome and property price

Lead Effect of Property price inflation on APC

0.4

0.5

0.5

0.6

0.6

0.7

0.7

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

APC

-60

-40

-20

0

20

40

60

80

100

120

Annu

al P

PI I

nfla

tion

APC

PPI

Optimal Property Price Inflation?Optimal Property Price Inflation?

This needs to be worked out.This needs to be worked out.Historical trend of 7% price appreciation per year Historical trend of 7% price appreciation per year seems more than sufficient. For this seems more than sufficient. For this --Assuming population growth =2.6%, disposable income per capita Assuming population growth =2.6%, disposable income per capita growth = 4%, CPF balances per capita growth = 4%:growth = 4%, CPF balances per capita growth = 4%:

Housing stock has to grow by 5% per year.Housing stock has to grow by 5% per year.Not easy given the land scarcityNot easy given the land scarcityNeed to manage the demand !Need to manage the demand !

Investment demand (local, foreign)Investment demand (local, foreign)Owner occupancy demandOwner occupancy demand

You can download the slides from the SCAPE You can download the slides from the SCAPE website:website:

NUS NUS Dept. of Economics Dept. of Economics SCAPE SCAPE ESU ESU ConferencesConferences

http://nt2.fas.nus.edu.sg/ecs/cent/ESU/conference.htmhttp://nt2.fas.nus.edu.sg/ecs/cent/ESU/conference.htm

Thank youThank you ☺☺