The effect of real estate speculation on the growth of economics in Lithuania
European countries with transition economies are suffering from unemployment and fluctuating prices, now being plagued by rampant real estate bubble. One of the major social and economic problems in recent years has been the sustained real estate price spiral. The excessively high real estate price...
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Інститут економіки промисловості НАН України
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irk-123456789-239952022-09-29T21:47:45Z The effect of real estate speculation on the growth of economics in Lithuania Simanaviсiene, Zaneta Sliupas, Rokas International and Regional Economics European countries with transition economies are suffering from unemployment and fluctuating prices, now being plagued by rampant real estate bubble. One of the major social and economic problems in recent years has been the sustained real estate price spiral. The excessively high real estate price means worsening affordability, mortgage payment defaults and impacts the economy’s growth. Present real estate boom is an archfiend wielding terrible power, capable of blowing out the flickering signs of a hopeful economic recovery. It is a common belief that the presence of bubbles in real estate price did impact on the economy and usually caused by speculative activities. Countries, wishing to reduce recession or prevent financial crisis, have to monitor and supervise the real estate market. This paper is designed to evaluate the contribution of speculative activities to real estate price hike. An empirical model is presented that allows for decomposition of house price appreciation into that driven by economic and demographic forces and that resulting from speculative demand. Lithuania is taken as an example of transition country due to its unique historical and financial situation. Main conclusion is that slowdown of accumulation in real estate market and slowed down growth in construction sector leads to real estate market recession as well as to economic slowdown. Key words: real estate speculation, real estate price bubble, real estate market crisis. Європейські країни з перехідними економіками страждають від безробіття та коливань цін на нерухоме майно. Однією з головних соціальних і економічних проблем останніми роками була спіраль цін нерухомого майна. Надмірно висока ціна на нерухоме майно передбачає погіршення купівельної спроможності та впливає на зростання економіки. Стаття присвячена оцінюванню внеску спекулятивних дій ціни нерухомого майна. Литва розглядається як приклад країни з перехідною економікою. Ключові слова: спекуляції нерухомим майном, міхур ціни нерухомого майна, криза ринку нерухомого майна. Европейские страны с экономиками перехода страдают от безработицы и колебаний цен на недвижимое имущество. Одной из главных социальных и экономических проблем в последние годы была спираль цен недвижимого имущества. Чрезмерно непомерная цена недвижимого имущества подразумевает ухудшение покупательной способности и воздействует на рост экономики. Статья посвящена оценке вклада спекулятивных действий цены недвижимого имущества. Литва рассматривается как пример страны с переходной экономикой. Ключевые слова: спекуляции недвижимым имуществом, пузырь цены недвижимого имущества, кризис рынка недвижимого имущества. 2010 Article The effect of real estate speculation on the growth of economics in Lithuania / Zaneta Simanaviсiene, Rokas Sliupas // Економічний вісник Донбасу. — 2010. — № 4(22). — С. 89-96. — Бібліогр.: 10 назв. — англ. 1817-3772 http://dspace.nbuv.gov.ua/handle/123456789/23995 [338.1:339.194](474.5) en Економічний вісник Донбасу Інститут економіки промисловості НАН України |
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International and Regional Economics International and Regional Economics |
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International and Regional Economics International and Regional Economics Simanaviсiene, Zaneta Sliupas, Rokas The effect of real estate speculation on the growth of economics in Lithuania Економічний вісник Донбасу |
| description |
European countries with transition economies are suffering from unemployment and fluctuating prices, now being plagued by rampant real estate bubble. One of the major social and economic problems in recent years has been the sustained real estate price spiral. The excessively high real estate price means worsening affordability, mortgage payment defaults and impacts the economy’s growth. Present real estate boom is an archfiend wielding terrible power, capable of blowing out the flickering signs of a hopeful economic recovery. It is a common belief that the presence of bubbles in real estate price did impact on the economy and usually caused by speculative activities. Countries, wishing to reduce recession or prevent financial crisis, have to monitor and supervise the real estate market. This paper is designed to evaluate the contribution of speculative activities to real estate price hike. An empirical model is presented that allows for decomposition of house price appreciation into that driven by economic and demographic forces and that resulting from speculative demand. Lithuania is taken as an example of transition country due to its unique historical and financial situation. Main conclusion is that slowdown of accumulation in real estate market and slowed down growth in construction sector leads to real estate market recession as well as to economic slowdown. Key words: real estate speculation, real estate price bubble, real estate market crisis. |
| format |
Article |
| author |
Simanaviсiene, Zaneta Sliupas, Rokas |
| author_facet |
Simanaviсiene, Zaneta Sliupas, Rokas |
| author_sort |
Simanaviсiene, Zaneta |
| title |
The effect of real estate speculation on the growth of economics in Lithuania |
| title_short |
The effect of real estate speculation on the growth of economics in Lithuania |
| title_full |
The effect of real estate speculation on the growth of economics in Lithuania |
| title_fullStr |
The effect of real estate speculation on the growth of economics in Lithuania |
| title_full_unstemmed |
The effect of real estate speculation on the growth of economics in Lithuania |
| title_sort |
effect of real estate speculation on the growth of economics in lithuania |
| publisher |
Інститут економіки промисловості НАН України |
| publishDate |
2010 |
| topic_facet |
International and Regional Economics |
| url |
http://dspace.nbuv.gov.ua/handle/123456789/23995 |
| citation_txt |
The effect of real estate speculation on the growth of economics in Lithuania / Zaneta Simanaviсiene, Rokas Sliupas // Економічний вісник Донбасу. — 2010. — № 4(22). — С. 89-96. — Бібліогр.: 10 назв. — англ. |
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Економічний вісник Донбасу |
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2025-07-03T03:28:10Z |
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| fulltext |
89
Економічний вісник Донбасу № 4 (22), 2010
Simanavič ienė Žaneta, Šliupas Rokas
Introduction
Real estate experts, reporters, politicians and even
ordinary people are wondering about the possible impact
of real estate bubble on the national economy and many
are concerned about the possibility of repeating Asian
experiences [1, с. 25]. It appears that such worries are
not well founded. It must be remembered that housing
situations were very different, but similarities exist with
respect to financial situation, i.e., the low interest rate
and abundance of liquid money.
Guttentag, Herring and Wachter have shown that
there is a built-in lender myopia that is intrinsic to certain
markets such as real estate, which may always be present
to some degree. Financial institutions can be unwittingly
caught into over-lending to real estate markets and feed
a severe boom and bust cycle. The reason is that lenders
underestimate their exposure to low-frequency shocks
when real estate prices have been climbing steadily for
sustained periods of time. The pattern of capital and rent
values during a property boom and bust suggests how
disaster myopia works. The cycle starts slowly with a
sustained phase of powerful lending accompanied by
widening asset price gains as we get close to the peak of
the boom. This peak is followed by a crash in values
over a much shorter period of time.
In immature markets, myopic or irrational pricing
may be dominant because reliable information about
aggregate market conditions is limited or missing. The
phenomenon of real estate market growth and recession
attracted the attention of different scholars and it is agreed
that more research is needed for the dynamic changes in
the market and their impact on the whole economy.
Novelty of the paper — the answer to the question
what peculiarities of real estate market and slowdown
may affect the economy of new open economy countries.
Scientific problem of the article is the lack of a
common opinion in the economics literature what threats
to the economy might cause real estate speculative bubble.
Purpose of the paper is to investigate how
speculative bubbles in real estate market effects economic
in countries with transition economy.
Object of the paper is the real estate market
speculative bubble.
Tasks raised in the article:
1. To present a theoretical view the speculation
features of real estate market.
2. To analyze related statistical data in Lithuania.
Research methods are logical and systemic
analysis of research literature based on the comparative
and generalization methods as well as statistical methods.
The speculative bubble’s meaning and features
in real estate market
Speculation is usually thought of as a demand-side
phenomenon, whether demand side events do result in a
bubble will depend on supply conditions and will determine
whether speculation will be observed and whether price
“bubbles” will form. Excessive and inappropriate
regulations «in-elasticize supply» and lead to rising real
estate prices. Higher prices that then drop increase defaults
and adversely affect the soundness of the financial system,
leading to credit crunches which then magnify the
downturn. Of course many things besides regulations
affect supply, notably natural constraints [2, c. 45].
According to the different main body [3, c. 176],
the speculative behavior in the real estate market can be
categorized into two kinds, one kind’s exponent is the
developers (Figure 1), who have information superiority
in the real estate merchant, they know that some real
estate price is higher than real value definitely, however,
they are sure that there will be more people buy it at
higher price, so, they purchase or hoarding and cornering
this kind real estate constantly to raise the real estate’s
price, and expect to sale them at the price peak. The
other kind uses consumer as exponent. Customer’s
demand can be divided in to the direct consume demand
and invest demand. In the real estate market, customers’
invest demand also can be categorized into long-term
rent demand, shot-term invest demand and the mixed
demand for acting as the occasion demands. The real
estate consumer’s short-term speculative demand and
part mixed demand also can induce the real estate bubble.
When they do decision-making of real estate
investment, this part consumers are at disadvantaged for
the asymmetrical information, they can only buy real estate
at high price or deceived by the falsehood flourish, which
give they the naive expectation that the flourish will went
on without day and then join into the troop of investing
in real estate, finally accelerate the bubble’s assemble.
So, speculative real estate bubble can be defined as
that, it is the bubble resulted from the speculative behavior
of the real estate developer and the consumer, who are
УДК [338.1:339.194](474.5)
Simanavič ienė Žaneta,
PhD (Economics), Prof., Kaunas University of Technology,
Šliupas Rokas,
Msc.,Vilnius Gediminas Technical University, Lithuania
THE EFFECT OF REAL ESTATE SPECULATION ON THE GROWTH OF ECONOMICS
IN LITHUANIA
90
Економічний вісник Донбасу № 4 (22), 2010
Simanavič ienė Žaneta, Šliupas Rokas
the two main body of real estate trade. Those speculative
behaviors which induce the speculative real estate bubble
have two obvious characters:
1. The invest main body’s intention is definite, that is
to gain the real estate business’s price difference, it has no
inner essential relation with the virtual economy increase.
2. The speculation main body’s behavior is short-
term and indefinitely after they get the real estate. Most
is changed hand in 1-2 years.
For the domestic real estate industry is such an
investment that returns good profits, and also because other
invest channel under the overseas exchange control is not
unobstructed, mass of overseas capital incurs into domestic
real estate market. Under the invest of foreign capital, the
domestic big and middle cities’ real estate price rises so rapidly
that it exceed the deserved value notably, and also beyond the
limit which common civilians can afford. This condition not
only brings huge press to those who really want to purchase
domicile, but also lead to great market risk.
Relationship of speculative real estate bubble
and economic growth rate stability in countries
with transition economy
Lithuania is taken as an example of transition country
due to its unique historical and financial situation. We
collected the house price data from the IMF IFS database,
Centre of Registers, Central Bank of Lithuania and, in
some cases, statistical office. The data begins between
1998 for and ends in 2008. The hypothesis here is that
by looking at the following dimensions it should be
possible to present a set of sufficient conditions for a
specific bubble episode:
1. The macroeconomic situation and
macroeconomic policies;
2. Structural changes in the economy;
3. The capital and credit market;
4. The beliefs, expectations and plans of the actors;
— Holding period
— Beliefs about the future development of the asset
price
— The rationality of the actors
5. The incentive of the individuals.
These factors combined would have drastically
increased the expectation for large windfall capital gains
from housing investment.
Firstly, the fall in interest rate would reduce the
financial burden of interest payment on the part of the
consumers, which would have led to the increase in the
demand for home mortgages. More households would
have purchased homes through mortgage financing,
which would also have pushed the demand for housing
and eventually raise the price of housing. In general a fall
in interest rate tends to make investors prefer real estate
to financial asset because the former yields relatively
higher rate of return than the latter. And also theoretically
if interest falls, the present value of the future income
streams increases. Asset value is computed simply by
dividing future income by interest rate. Therefore, if
interest rate falls, the real estate value goes up, other
things being equal, and again it stimulates speculative
housing demand and pushes housing price up [4, c. 28].
Another factor that might have caused the housing
price inflation is a record rise in both home mortgage and
personal lending. Personal borrowing became easy due to
low rate of interest. Besides those who borrowed money
were upper-middle class households and credit worthy.
Accordingly a large amount of liquid money has flown
into the housing market. Clearly credit availability helped
increase housing demand and thus, raise the housing price
as much. Furthermore, various financial and tax incentives
were provided for ordinary investors alike to invest money
into real estate. In particular home buyers were given
incentives to write off interest payments from income taxes.
Fig. 1. The classify of the speculative real estate bubble [3, c. 182]
Real estate developers
Real estate consumers
Land regretting
Loath to sell to drive the price
International capital drive the price
Consuming
Investing
Dwelling
Rent
Speculation
Mixed
Real estate
speculation
Speculative real
estate bubble
91
Економічний вісник Донбасу № 4 (22), 2010
Simanavič ienė Žaneta, Šliupas Rokas
These highly stimulative policy packages have clearly
resulted in housing price inflation.
Table 1 shows the basic annual data from 1998 to
2008. It is tempting, but not practical, to carry out a
regression analysis of the influence of these 17 factors
on real housing prices. As is evident from the table, we
have a richness of variables, a deficiency of observations,
and a potentially serious simultaneity bias problem as well.
According to the experts of National Development
Institute, home prices in Vilnius are just 30% lower than
prices in Berlin and Brussels. However, wage in Vilnius
is almost 8 times lower, the density of population is 5 —
6 times lower and population is decreasing if comparing
with these countries. All these analyzed indicators show
that the increase of home prices is unfounded; therefore
it is possible to state that it is one of the features which
indicate the price bubble in real estate market.
We found it expedient, instead, to group and analyze
the data using the key periods of the Lithuanian house
price cycle:
the initial period — 1998 to 2001;
the fundamental growth — 2001 to 2005;
the boom — 2005 to 2008.
The view that both the supply and demand for
housing interact to determine an equilibrium level for real
house prices should not be taken to imply that house
prices are necessarily stable. In many countries it is
frequently observed that house prices are significantly
more volatile than would be predicted by the variation in
the main determinants of supply and demand alone.
Moreover, the structure of housing finance, spatial effects
and tax treatment of owner occupancy may significantly
affect house price dynamics in the long term. The model
to be estimated is as follows:
phouse = f(Y+,r-,WE+,D+/-,e+,X-,C(PL,W,M)-)) (1)
On the demand side:
Y — household income;
r — the real rate on housing loans;
WE — financial wealth;
D — demographic and labour market factors;
e — the expected rate of return on housing;
X — and a vector of other demand shifters;
L — location;
A — age and state o f housing.
On the supply for housing side:
C — the real costs of construction;
PL — including the price of land;
W — wages of construction workers;
M — a material costs.
According to empirical literature [6, c. 41; 7,
c. 173], the model is based on both theories of excess
demand and cost push in real estate market. Assuming
that the housing market is in equilibrium, with demand
equal to supply at all times.
It also is assumed that, in the model, housing demand
has two components: «normal» demand and «speculative»
demand. Normal demand is assumed to depend on income
and yield rate of alternative investment. As income increases
and alternative investment yield falls, the normal consumer
would allocate increased income and the proceeds of the
sales of alternative investment to buy the house to live in.
The normal consumer is a risk averter and would buy the
house on the basis of such determinants as income increase
and alternative investment yield. On the other hand, the
speculative consumer is assumed to be a risk taker and
make up his or her decision to buy the house on the basis
of such high risk determinant as unknown increase in
housing price [8, c. 166].
These results provide support for the view that the
development of housing markets and housing finance
institutions has had a major impact on the dynamics of
house prices in Lithuania.
After analysis of long-term co-integrating
relationship between real house prices and the selected
explanatory variables we constructed polynomial function
of real estate prices:
phouse = 3.41(housing credit) + 1.80(labor force) +
0.91(population) + 0.27(real wage) + 0.25(GDP per
capita) — 0.02(real interest rates) — 0.07(unemployment)
— 0.12(stock market index) — 1.82 (2)
Table 1
Determinants of Lithuanian housing demand: 1998 to 2008
[5, c. 2]
REAL ESTATE
PRICES SUPPLY MACRO REAL
INTEREST TAX RATES CREDIT
(1) (2) (3) (4) (5) (6) (7) (8) (10) (11) (12) (13) (14) (15) (16)
PE
R
IO
D
Real
1-2
family
Real
multi
family
Real
Total
Urban
housing
supply
Total
housing
supply
Real
GDP Wages
Consumer
Prices
Producer
Prices Unemp
Money
market
rate
Fgn. cur.
money
market
rate
Bank credit
private
sector
Total
Credit
Credit/
GDP
'98-'01 3,0 42,5 12,2 1,4 1,4 9,6 7,3 3,1 14,7 6,1 -2,8 -1,5 17,4 23,4 2,2
'01-'05 56,2 71,0 57,7 2,3 1,9 39,8 19,5 3,0 19,4 -4,3 -1,4 -1,4 408,7 307,0 30,3
'05-'08 262,5 286,4 233,9 3,8 3,2 31,4 84,5 23,0 44,5 -2,5 2,0 0,3 721,7 528,6 41,8
92
Економічний вісник Донбасу № 4 (22), 2010
Simanavič ienė Žaneta, Šliupas Rokas
Credit measured by changes in the ratio of private
sector credit to GDP has a strongest positive relationship
to house prices. GDP per capita is highly significant and
has the expected positive sign in virtually all the
regressions, indicating that changes in income are strongly
positively related to changes in house prices. Real interest
rate coefficients in most cases have the expected negative
sign and are statistically significant, indicating that falling
interest rates are associated with rising real house prices.
The coefficient estimates for population, labor force
and unemployment for the Lithuania are all significant
and have the expected second biggest relationships. One
can notice that the size of the estimated coefficients for
the population is much higher in Vilnius than in other
biggest Lithuanian cities.
Real wages, used as a broad proxy for housing
quality, are positively correlated with real house prices.
To the extent that real wages, as an important component
of construction costs, adequately reflect improvements
in housing quality, these results support the view that
better housing quality had a stronger impact on real estate
prices in the Lithuania.
During the period of 38 quarters between the fourth
quarter of 1998 and the first quarter of 2008, the credit
measured by changes in the ratio of private sector credit to
GDP has a strongest positive relationship to house prices
except Vilnius district where population determinant has the
biggest impact to price inflation. During the measured period
a lot of people came to live in Vilnius from other districts.
Overly optimistic expectations about future house
price rises are not explicitly captured in the above
analysis, but inevitably played a role during the upturn,
while negative perceptions have exacerbated the
downturn. We showed house prices in Lithuania have
been driven by rapidly rising disposable incomes related
to steep GDP and wage growth, declining tax rates;
and a fall in after-ax interest rates during the first half
of the decade; favorable tax treatment of residential
property was also an important driver of house price
inflation. We made and hypothesis what there was a
speculative price bubble.
The share of an independent variable in influencing
dependent variable within a certain period of time can be
measured with the formula below:
∑∑
==
=
T
t
t
T
t
itii YXbW
11
ˆ/ (3)
Table 2
Long-term relationships dependent variables: change in Lithuanian biggest cities real estate prices
Lithuania Vilnius city
(new)
Vilnius city
(old) Kaunas city Klaipeda city Siauliai city Panevezys city
Credit for housing 3,41 2,33 3,10 3,63 4,18 4,47 3,47
Labour force market 1,80 0,70 1,01 1,85 2,71 2,15 -1,10
Population 0,91 2,29 2,80 0,80 -2,17 0,90 1,05
Real wage index 0,27 0,17 0,23 0,24 0,31 0,30 0,26
GDP (PPP) per capita 0,25 0,19 0,26 0,27 0,30 0,30 0,22
Real interest rates -0 ,02 0,01 0,00 -0,01 0,00 -0,04 -0,02
Unemployment rate -0 ,07 -0 ,02 -0,08 -0,06 -0,08 0,05 -0,03
OMX stock market
index -0 ,12 -0 ,09 -0,12 -0,17 -0,16 -0,24 -0,20
ECT -1 ,82 0,41 0,58 0,01 0,09 -0,53 0,12
No, obs, 45 45 45 45 45 45 45
R2 0,89 0,87 0,88 0,87 0,88 0,83 0,79
Table 3
Long-term relationships dependent variables: change in Lithuanian districts real estate prices
Lithuania Vilnius
district
Kaunas
district
Klaipeda
district
Siauliai
district
Panevezys
district
Credit for housing 3,41 4,26 5,54 5,73 3,72 2,92
Labor force market 1,80 1,13 2,39 2,89 1,36 -1,66
Population 0,91 6,70 1,46 2,30 -2,00 -0,79
Real wage index 0,27 0,30 0,35 0,39 0,25 0,22
GDP (PPP) per capita 0,25 0,26 0,33 0,38 0,17 0,12
Real interest rates -0,02 -0,01 -0,02 -0,02 -0,02 -0,01
Unemployment rate -0,07 -0,09 -0,06 -0,10 -0,01 -0,05
OMX stock market index -0,12 -0,22 -0,31 -0,27 -0,22 -0,18
ECT -1,82 -1,10 -1,22 -1,14 -0,07 0,29
No, obs, 45 45 45 45 45 45
R2 0,89 0,84 0,82 0,87 0,79 0,74
93
Економічний вісник Донбасу № 4 (22), 2010
Simanavič ienė Žaneta, Šliupas Rokas
Where:
Wi : share of Xi in the value of estimated Y at time t
b i : regression coefficient of Xi, a variable
influencing housing price inflation
Xit : Xi at time t
t : 1,2,…T
tŶ : estimated value of the housing price at time t
This method of estimating the impact of independent
variables has the advantage, compared to elasticities, β
coefficients and other measures, of making allowance
for the variation of independent variables themselves and
showing different impacts on the dependent variables in
different time periods.
Interestingly, the percentage share of speculative
demand in housing price spiral is very high. The share of
expected housing price which represents speculative
demand is much more powerful:
• Construction cost contributes significantly to
housing price hike accounting for 28% and speculation
62% for Lithuania, as a whole.
• In order to investigate more precisely the relative
weight of speculative demand variable, the share of the
speculative demand is divided by that of «normal»
demand.
• The ratio of speculative demand (expected housing
price) to normal demand (GDP and stock yield) for
Lithuania is 1.7.
• Biggest speculative demand were in Klaipeda and
Panevezys cities and lowest speculative demand — in
Vilnius new constructions dwellings.
• Construction cost contributes had the biggest
housing price hike Siauliai and Vilnius (new construction).
The share of expected housing price which
represents speculative demand is much more powerful
in Vilnius district, real estate supply seems to be at the
lowest scale. The lowest speculative impact on real estate
demand was measured in Siauliai district.
There are several ways of approaching estimating
bubbles. However, the followings are the most often used
model applied to real estate price — long-run equilibrium
price approach. This approach can be summarized:
ttt GDPPB ∆−∆= (4)
t
t
t
t B% share of
P
BB (%) =
∆
= (5)
Where Bt : amount of bubble at time t
Δ Bt : the rate of change in actual price
Δ GDPt : the rate of change in GDP
t : 1,2,…T
The indicators presented below are based on factors
discussed in the literature.
The estimates of housing price bubble according to
the fundamental market value are summarized in Table
6. In Lithuania, the bubble’s share in the price rose from
46% in the 1rd quarter of 2004, 68% in the 1th quarter
of 2007 to as much as 58% in the 1st quarter of 2008. In
Vilnius (lowest speculative share), on the other hand, the
bubble’s share rose from 29% in the 1rd quarter of 2005,
52% in the 2th quarter of 2006 to 32% in the 1st quater
of 2008. Finally, in Panevezys, it rose from -58% in the
1rd quarter of 2004, 82% in the 1th quarter of 2007 to
73% in the 1st quarter of 2008.
Finally, the estimates of the bubble are shown in
Table 6. The average ratio are 46% (Vilnius), 76% Kaunas,
Klaipeda), 68% (Siauliai, Panevezys). The list presented
below should however be seen more as an hypothesis
than as something rather final.
Impact of speculative bubble on countries whole
economies
Guttentag, Herring and Wachter have shown that
there is a built-in lender myopia that is intrinsic to certain
markets such as real estate, which may always be present
to some degree. Financial institutions can be unwittingly
Table 4
Degree of contribution to real estate price inflation in Lithuanian cities, (%)
Lithuania Vilnius
city (new)
Vilnius
city (old)
Kaunas
city
Klaipeda
city
Siauliai
city
Panevezys
city
I. Contribution of each variable 100
100 100 100 100 100 100
Real wages -14,8 -14,9 -18,0 -4,8 1,8 -9,5 19,8
Hypothec credit market 28,7 19,0 11,5 -7,2 -35,3 -14,4 -20,6
OMXV index 3,4 4,0 -6,3 -4,8 -10,2 -10,5 17,7
Expected housing price 62,8 31,9 80,0 68,0 84,2 63,1 73,5
Real construction cost 28,0 51,5 28,4 48,9 49,1 71,5 9,5
Real estate stock -8,1 8,5 4,5 -0,1 10,4 -0,2 0,1
II. Ratio of speculative demand to
normal demand 1,7 0,5 4,0 2,1 5,3 1,7 2,8
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Simanavič ienė Žaneta, Šliupas Rokas
caught into over-lending to real estate markets and feed
a severe boom and bust cycle. The reason is that lenders
underestimate their exposure to low-frequency shocks
when real estate prices have been climbing steadily for
sustained periods of time [9, c. 12]. The pattern of capital
and rent values during a property boom and bust suggests
how disaster myopia works itself into a long boom and
sharp bust cycle. The cycle starts slowly with a sustained
phase of powerful lending accompanied by widening asset
price gains as we get close to the peak of the boom. This
peak is followed by a crash in values over a much shorter
period of time ending with substantial losses for
developers, lenders and investors in the market before
the crash.
How does disaster myopia arise? A lender will decide
to allocate a significant share of its portfolio to an activity
like real estate according to three main criteria. The
expected return to this activity is higher compared with
other lending activities for a given cost of funds. The
default premium for that activity may also be considered
low. The portfolio is perceived as good for risk
diversification because the covariance of the real estate
portfolio performance with other activities is judged low.
Much has been written about the causes of the real
Table 5
Degree of contribution to real estate price inflation in Lithuanian districts, (%)
Lithuania Vilnius
district
Kaunas
district
Klaipeda
district
Siauliai
district
Panevezys
district
I. Contribution of each variable 100
100 100 100 100 100
Real wages -14,8 42,3 -29,0 -17,1 -13,9 -17,7
Hypothec credit market 28,7 -28,4 17,2 33,9 -2,6 10,1
OMXV index 3,4 -3,7 -11,0 -4,2 -14,7 -18,3
Expected housing price 62,8 56,6 46,9 43,0 30,2 45,1
Real construction cost 28,0 49,1 75,9 45,2 100,2 80,5
Real estate stock -8,1 -15,8 0,0 -0,6 0,8 0,3
II. Ratio of speculative demand to
normal demand 1,7 1,3 0,9 0,8 0,4 0,8
Table 6
Estimate of Bubble in the Variation of Housing Price by the Long-run Equilibrium Approach in main cities of Lithuania
Lithuania Vilnius
city (new)
Vilnius
city (old)
Kaunas
city
Klaipeda
city
Siauliai
city
Panevezys
city
2004K1 0,465 -0,108 0,289 0,357 0,664 -0,249 -0,587
2005K1
0,604 -0,287 0,517 0,601 0,689 0,648 0,663
2006K1
0,661 0,198 0,524 0,637 0,735 0,695 0,722
2007K1
0,680 0,291 0,470 0,682 0,748 0,788 0,822
2008K1
0,584 0,059 0,326 0,557 0,640 0,697 0,731
Table 7
Estimate of Bubble in the Variation of Housing Price by the Long-run Equilibrium Approach in main districts of
Lithuania
Lithuania Vilnius
district
Kaunas
district
Klaipeda
district
Siauliai
district
Panevezys
district
2004K1 0,465 -4,093 0,099 0,498 -3,555 1,930
2005K1
0,604 0,255 0,539 0,658 0,040 0,081
2006K1
0,661 0,488 0,644 0,725 0,581 0,490
2007K1
0,680 0,503 0,764 0,757 0,672 0,691
2008K1
0,584 0,466 0,720 0,757 0,650 0,701
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Економічний вісник Донбасу № 4 (22), 2010
Busting of speculative bubble
Sudden fall of housing price
Rapid increase in bank’s Non-
Performing Loans: NPL Housing bankruptcies
Sudden fall in consumption
Increase of jobless
Sudden decline of banks loans
Rapid decrease in production
Economic recession
Simanavič ienė Žaneta, Šliupas Rokas
estate crisis in general There appears to be a consensus
that the crisis was caused by a combination of structural
problems of the economies such as inadequate regulation
of the financial institutions and the intrinsic instability in
international flow of capital prone to panic rather than
mismanagement of monetary and fiscal policies.
Among the many explanations is the hypothesis
emphasizing the role of the boom and the bust of real
estate prices. For example, Krugman wrote, «..in all of
the afflicted countries there was a cycle in the asset
markets that preceded the currency crisis.. Asian story
is really about a bubble in and subsequent collapse of
asset values in general, with the currency crises more a
symptom than a cause of this underlying real malady.»[10,
c. 3] also points out that «Non-performing real estate
asset loans, overvalued real estate collateral and business
loans improperly defected into real estate investments
and contributing directly to banking failures are a familiar
story in quite a few countries.» He described the sequence
of causality in Thailand as «Real estate crisis=>banking
crisis=> currency crisis=> contraction» [10, c.4].
The mechanism of so-called asset deflation implied
by the above line of reasoning can be summarized by figure
2. Falling real estate prices lead to a reduction in consumption
through negative wealth effect, to an increase in non-
performing loans and hence a decrease in supply of new
credit by financial institutions, which results in a reduction
in investment by the firms. Investment decreases also
because the drop in real estate prices impairs the firms’
capacity to borrow. Contraction of consumption and
investment leads to a recession. And the vicious cycle begins.
Once bubble busts, the price of real estate goes down
dramatically and in particular, the value of mortgage collateral
falls to the extent that it becomes well below the amount of
loans outstanding. If the loan to value ratio is high, there is
no way to recover the loan and consequently, many financial
institutions would go bankrupt. The incidences of personal
bankruptcy would then be on the rise, leading to substantial
reduction of consumption and production as well, and
eventually to an increase in unemployment. Such a vicious
circle would continue for a long time and if so, the economy
would suffer from depression.
Conclusions
1. The current recession notwithstanding,
Lithuania’s real estate performance was unbalanced and
collapsed in 2008. The real estate boom-bust cycle was
driven by massive capital inflows under the currency
board, which fuelled credit and speculative real estate
boom. Other factors were rapid income growth,
increasingly negative real interest rates, and on the part
both Scandinavian lenders and Lithuanian borrowers an
overly optimistic assessment of the economic outlook.
2. A tightening of lending conditions led to steep
decline in construction and real estate related activities,
which has spread to other sectors. These domestic
factors were further exacerbated by the marked
deterioration of the external environment due to the onset
of the global economic and financial crisis, bringing
Lithuania into a deep recession.
3. However, the most significant finding is that the
speculative demand is far more important than normal
real estate demand. In fact, the contribution of speculative
demand to the determination of housing price is much
more important than that of normal housing demand. The
Fig. 2. Impact of housing price bubble in the national economy (Krugman, 1998)
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Економічний вісник Донбасу № 4 (22), 2010
Simanavič ienė Žaneta, Šliupas Rokas
surge of speculative housing demand since 2000 has been
largely attributable to the trend of declining interest rate,
rapidly increasing money supply. Second, contrary to
what many might have thought, the seriousness of housing
bubble in Lithuania less apparent than it was in Asia because
of differences in basic market conditions.
4. These findings have interesting policy
implications. First, the government should not repeat the
policy conducive to speculation including the allowance
of the sale of pre-sale contract. Second, the capital gains
tax is of course needed not only for government’s tax
receipts but also for better income distribution; but it is
not a suitable way of discouraging speculative activities.
The best way of fighting speculation and stabilizing
housing price is to minimize the excess demand through
the sustained increase of housing production on one hand
and well pre-planned land supply through better regional
development planning on the other.
References
1. Beka, J. (2007). Real Estate Prices, Credit
Growth and Implications for Monetary Policy. BIATEC,
25. 2. Girdzijauskas, S., & Streimikiene, D. (2009).
Application of Logistic Models for Stock Market Bubbles
Analysis. Journal of Business Economics and
Management, 10(1), 45-51. 3. Shiller, R., & Case, K.
(2003). Irrational Exuberance. 174-198. 4. Wheaton,
W. (1999). Real Estate «Cycles»: Some Fundamentals.
24-76. 5. Statistical Office of Lithuania (2010). http://
www.stat.gov.lt/lt/. 6. Girouard, N., Kennedy, M. &
André , C. (2006). Has the rise in debt made households
more vulnerable? OECD Economics Department Working
Papers(535), 33-70. 7. Grenadier, S.R. (1995). An
Equilibrium Analysis of Real Estate. 169-189.
8. Galinienė , B., Marč inskas, A., & Malevskienė ,
S. (2006). The cycles of real estate market in the Baltic
Countries. Technological and economic development of
economy(12), 161-167. 9. Hegerty, S.W. (2009). Is PPP
Sensitive to Time-Varying Trade Weights in Constructing
Real Effective Exchange Rates? Quarterly Review of
Economics and Finance(49), 10-15. 10. Krugman, P.
(1998). Bubble, boom, crash: theoretical notes on Asia’s
crisis, mimeo. http://web.mit.edu/krugman/www/.
Ž aneta Simanavičienė , Rokas Šliupas. The
effect of real estate speculation on the growth of
economics in Lithuania
European countries with transition economies are
suffering from unemployment and fluctuating prices, now
being plagued by rampant real estate bubble. One of the
major social and economic problems in recent years has
been the sustained real estate price spiral. The excessively
high real estate price means worsening affordability,
mortgage payment defaults and impacts the economy’s
growth. Present real estate boom is an archfiend wielding
terrible power, capable of blowing out the flickering signs
of a hopeful economic recovery. It is a common belief
that the presence of bubbles in real estate price did impact
on the economy and usually caused by speculative
activities. Countries, wishing to reduce recession or
prevent financial crisis, have to monitor and supervise
the real estate market.
This paper is designed to evaluate the contribution
of speculative activities to real estate price hike. An
empirical model is presented that allows for decomposition
of house price appreciation into that driven by economic
and demographic forces and that resulting from
speculative demand. Lithuania is taken as an example of
transition country due to its unique historical and financial
situation. Main conclusion is that slowdown of
accumulation in real estate market and slowed down
growth in construction sector leads to real estate market
recession as well as to economic slowdown.
Key words: real estate speculation, real estate price
bubble, real estate market crisis.
Симанавічене Ж., Шлюпас Р. Ефект спеку-
ляції нерухомістю на зростання економіки в Литві
Європейські країни з перехідними економіками
страждають від безробіття та коливань цін на нерухоме
майно. Однією з головних соціальних і економічних про-
блем останніми роками була спіраль цін нерухомого май-
на. Надмірно висока ціна на нерухоме майно передба-
чає погіршення купівельної спроможності та впливає на
зростання економіки. Стаття присвячена оцінюванню вне-
ску спекулятивних дій ціни нерухомого майна. Литва роз-
глядається як приклад країни з перехідною економікою.
Ключові слова: спекуляції нерухомим майном,
міхур ціни нерухомого майна, криза ринку нерухомо-
го майна.
Симанавичене Ж., Шлюпас Р. Эффект спеку-
ляции недвижимостью на рост экономики в Литве
Европейские страны с экономиками перехода
страдают от безработицы и колебаний цен на недви-
жимое имущество. Одной из главных социальных и
экономических проблем в последние годы была спи-
раль цен недвижимого имущества. Чрезмерно непо-
мерная цена недвижимого имущества подразумевает
ухудшение покупательной способности и воздействует
на рост экономики. Статья посвящена оценке вклада
спекулятивных действий цены недвижимого имуще-
ства. Литва рассматривается как пример страны с
переходной экономикой.
Ключевые слова: спекуляции недвижимым иму-
ществом, пузырь цены недвижимого имущества, кри-
зис рынка недвижимого имущества.
Received by the editors: 23.10.2010
and final form in 01.12.2010
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