Tallinn University of Technology Estonian real estate market – the day after housing boom Angelika...

Tallinn University of TechnologyTallinn University of Technology

Estonian real estate market – the day after housing boom

Angelika KallakmaaAngelika Kallakmaa

Ene KolbreEne Kolbre


According to the data of Global Property GuideAccording to the data of Global Property Guide

Estonia was 2006 the leader of the Estonia was 2006 the leader of the global house price boomglobal house price boom

Estonia was followed by Denmark, Estonia was followed by Denmark, Norway and IrelandNorway and Ireland


Housing price bustHousing price bust

Equity price busts occurred on average every 13 years, lasted for 2 1/2 years, and were associated with GDP losses of about 4 percent of GDP

Housing price busts were less frequent, but lasted nearly twice as long and were associated with output losses that were twice as large, reflecting greater effects on consumption and banking systems, which are typically heavily exposed to real estate

(IMF World Economic Outlook, April 2003, When Bubbles burst)


Economic indicators and forecastEconomic indicators and forecast

20062006 20072007 20082008 20092009 20102010 20112011

Real GDP Real GDP growth (%)growth (%)

10,410,4 6,36,3 -3,6-3,6 -12,3-12,3 0,20,2 4,74,7

Real private Real private consumption consumption growth (%)growth (%)

12,812,8 7,87,8 -4,0-4,0 -9,5-9,5 -1,7-1,7 4,74,7

Unemployment Unemployment rate (%)rate (%)

5,95,9 4,74,7 5,55,5 12,812,8 13,713,7 12,512,5

Real wage Real wage growth (%)growth (%)

11,611,6 11,611,6 3,33,3 -4,7-4,7 -3,2-3,2 3,73,7

Nominal credit Nominal credit growth (%)growth (%)

51,651,6 30,230,2 7,37,3 -7,5-7,5 -0,5-0,5 4,94,9


Average Monthly Gross Wages and

Salaries, EUR yearyear 1 Q1 Q 2Q2Q 3Q3Q 4Q4Q

20022002 393393 366366 406406 374374 416416

20032003 430430 405405 442442 411411 455455

20042004 466466 431431 474474 449449 492492

20052005 519519 475475 530530 498498 555555

20062006 604604 550550 609609 580580 653653

20072007 725725 660660 738738 697697 784784

20082008 819819 788788 850850 800800 838838

20092009 776776


Problem for householdsProblem for households

House or flat is mostly the largest House or flat is mostly the largest investment of investment of Estonian Estonian households households

Increasing house prices result in greater Increasing house prices result in greater housing wealth housing wealth and also maand also madde it e it possible to borrow more using housing possible to borrow more using housing wealth as collateral wealth as collateral


Stock of household loans and housing Stock of household loans and housing loans (loans (1997- 2008, 1997- 2008, EEK mEEK mln)ln)

0

20000

40000

60000

80000

100000

120000

140000

31.12.9

7

31.12.9

8

31.12

.99

31.12

.00

31.12.0

1

31.12.0

2

31.12.0

3

31.12

.04

31.12

.05

31.12

.06

31.12.0

7

31.12.0

8

mln

EE

K

household loans

housing loans


Interest rate on households housing loansInterest rate on households housing loans 1997-20081997-2008

Interest rate on households housing loans

0,00%

2,00%

4,00%

6,00%

8,00%

10,00%

12,00%

14,00%

31.12.97 31.12.99 31.12.01 31.12.03 31.12.05 31.12.07

EEK

DEM

EUR


• Total volume of housing loans has increased as a result of low interest rate and tight competition in banking sector

• Econometric model what was constructed 2007 by using 8 different economic indicators for describing their influence to price of 2-room apartment in Tallinn shows that only 2 of them – money supply and interests rate were significant indicators to price changes of housing market in Estonia (Kolbre, Kallakmaa 2007)


Credit Growth in Central and Eastern Europe:Trend, Cycle or Boom? 2006Gergely Kiss, Márton Nagy, Balázs Vonnák

• “The estimations show that large part of the credit growth in new member states can be explained by the catching-up process, and, in general, credit/GDP ratios are below the levels consistent with macroeconomic fundamentals

• However, in some countries credit growth is significantly faster than what would be justified along the equilibrium path

• The study finds that credit growth in Latvia and Estonia can be considered as potentially the most risky, beyond any plausible adjustment”


Loans granted by groups of customersLoans granted by groups of customers(1997-2008, EEK m)(1997-2008, EEK m)

0

20 000

40 000

60 000

80 000

100 000

120 000

140 000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

mln

EEK

commercial

households


Overdue loans and overdue housing loansOverdue loans and overdue housing loans (1997-2008 annual basis, 2009 monthly basis)(1997-2008 annual basis, 2009 monthly basis)

0,0

1 000,0

2 000,0

3 000,0

4 000,0

5 000,0

6 000,0

7 000,0

8 000,031

.12.

97

31.1

2.98

31.1

2.99

31.1

2.00

31.1

2.01

31.1

2.02

31.1

2.03

31.1

2.04

31.1

2.05

31.1

2.06

31.1

2.07

31.1

2.08

31.0

1.09

28.0

2.09

31.0

3.09

30.0

4.09

Mln

EE

K Overdue amount ofloans

Overdue amount ofhousing loans


Don't worry – left and right scales are Don't worry – left and right scales are different!different! (1997-2008 annual basis, 2009 monthly basis)(1997-2008 annual basis, 2009 monthly basis)

Housing loans and amount of the housing loans that are overdue

0

20 000

40 000

60 000

80 000

100 000

120 000

31.12

.97

31.12

.98

31.12

.99

31.12

.00

31.12

.01

31.12

.02

31.12

.03

31.12

.04

31.12

.05

31.12

.06

31.12

.07

31.12

.08

31.01

.09

28.02

.09

31.03

.09

30.04

.09

Ho

usi

ng

lo

ans

(mln

EE

K)

0

100

200

300

400

500

600

700

800

900

Ove

rdu

e h

ou

sing

lo

ans

(mln

E

EK

)

Amount of housing loans Amount of the housing loans that are overdue


Resent developmentsResent developments

• The volume of loans overdue by more than 60 days increased in April (making up 5.2% of the portfolio. In March the respective indicator was 4.5%)

• Nearly 75% of the loan portfolio quality deterioration in April derived from the corporate credit sector; households have so far been more successful in loan servicing

• Thus, loans overdue by more than 60 days accounted for 6.4% of the credit issued to enterprises and 3.9% of the credit to households


Access to credit and credit constraints (1)

• Unemployment rate is growing

• Wage increase has stopped

• No more unrealistic expectations

• Housing living cost are growing (thermal energy etc)


Access to credit and credit constraints (2)

• No more “customer-friendly” credit conditions

• Parent banks might have difficulties in raising external funds because of situation in global financial markets

This is supply-side constraints - less loan money for the Estonian market


Despite of global finance crisis Despite of global finance crisis Estonian Banking system is still stableEstonian Banking system is still stable

• The average capital adequacy of the banking sector stayed at the level of 22% in April 2009

• Banks have made remarkable provisions during this year to avoiding possible loan losses

• The capitalisation of banks continues to be sufficient to cope with the forecasted loan losses


The The acceleratedaccelerated price increase in housing sector price increase in housing sector and high demand was mostly driven by:and high demand was mostly driven by:

• High economic growth leading to an increase High economic growth leading to an increase in disposable incomein disposable income

• The rapid expansion of credit to the private The rapid expansion of credit to the private sectorsector

• A low ratio of living-space per capita and A low ratio of living-space per capita and deteriorating housing stockdeteriorating housing stock


Real estate purchase and sales transactions 1997-2008

Notarial real estate purcahse and sale transactions in Estonia during 1997-2008

0

10000

20000

30000

40000

50000

60000

70000

80000

1997 1999 2001 2003 2005 2007

year

va

lue number of transactions

value of transactions (EEK m)


Housing marketHousing market

• Prices of apartments started to rise rapidly in 2005 when the annual price rise was over 50%.

• The growth rate of transactions started to slow down in the middle of 2006.

• The price rise turned to decline in 2007 when the housing prices reached the maximum

• Average price fall since spring 2007 has been 40-45%• During 2008 prices of apartments in Tallinn dropped

30%


Average Purchase-Sale Prices per Square Metre of a 2-room Apartment and number of

transactions in Tallinn, EEK

EE

K/

sq

m

Average price

Number of transactions


Housing market todayHousing market today

• IIn 2004−2006 demand for housing was greater n 2004−2006 demand for housing was greater than supplythan supply

• SSince the beginning of 2007 supply started to ince the beginning of 2007 supply started to grow rapidly grow rapidly

• 20082008 supply has been greater than demandsupply has been greater than demand• Approximately 1700 vacant apartments areApproximately 1700 vacant apartments are in in

TallinnTallinn on the market today as a result of the on the market today as a result of the rapid growth of the volume of new rapid growth of the volume of new developmentsdevelopments


Tobin’s q of the Estonian and Tallinn apartment market

0,00

0,50

1,00

1,50

2,00

2,50

2000 2001 2002 2003 2004 2005 2006 2007 2008

Estonian apartment market Tallinn apartment market


Average Average grossgross monthly wages and average monthly wages and average price for a square metre of a two-room price for a square metre of a two-room apartment in Tallinn (EEK)apartment in Tallinn (EEK)

Average gross monthly wages and average price for a square metre of a two-room apartement in Tallinn (EEK)

0

5000

10000

15000

20000

25000

30000

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009Ikv

EEK

GrossWages andSalariesPrice per1m2


Number of square meters of a two-room apartment in Number of square meters of a two-room apartment in Tallinn obtainable for average gross monthly wagesTallinn obtainable for average gross monthly wages

Number of square meters of a two-room apartment in Tallinn obtainable for average gross monthly wages

0,0

0,2

0,4

0,6

0,8

1,0

1,2

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009Ikv


Housing affordabilityHousing affordability

• Households budgets are tightenHouseholds budgets are tighten

• Households living costs are raised (especially Households living costs are raised (especially thermal energythermal energy))

• There is one group of households who can't There is one group of households who can't afford to buy a new house or flatafford to buy a new house or flat

• And other group who might be have And other group who might be have difficulties to repay their home loansdifficulties to repay their home loans


ConclusionsConclusions (1) (1)

• In Tallinn or in its close vicinity no new major In Tallinn or in its close vicinity no new major projects are expected to be launched within the projects are expected to be launched within the next year or twonext year or two

• TThe bottom of the Estonian real estate market he bottom of the Estonian real estate market is approaching, although the shape of this is approaching, although the shape of this bottom is expected to be flat, which means a bottom is expected to be flat, which means a long vegetating in all economylong vegetating in all economy


ConclusionsConclusions (2) (2)

• Despite of global finance crisis Estonian Banking Despite of global finance crisis Estonian Banking system is still stablesystem is still stable

• Most of housing loans was taken in economic growth Most of housing loans was taken in economic growth conditions and full employment expectationsconditions and full employment expectations

• Households with repayment difficulties should sell Households with repayment difficulties should sell their property or change it for affordable variant their property or change it for affordable variant

• To build up the “building society” systemTo build up the “building society” system• The government should disclaim for the possibility to The government should disclaim for the possibility to

deduct the housing loan interest from taxable incomededuct the housing loan interest from taxable income


Thank you!Thank you!


AuthorsAuthors

• Angelika KallakmaaAngelika Kallakmaa

• School of Economics and Business Administration, School of Economics and Business Administration, Tallinn University of TechnologyTallinn University of Technology

• e-mail: e-mail: [email protected]@tallinnlv.ee

• Ene KolbreEne Kolbre

• School of Economics and Business Administration, School of Economics and Business Administration, Tallinn University of TechnologyTallinn University of Technology

• e-mail: e-mail: [email protected]@tseba.ttu.ee

mailto:[email protected]

mailto:[email protected]

Tallinn University of Technology Estonian real estate market – the day after housing boom Angelika...

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