Countercyclical Capital Buffer - March 2019 - Background material for decision - Lietuvos bankas
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Countercyclical Capital Buffer Background material for decision March 2019
COUNTERCYCLICAL CAPITAL BUFFER ISSN 2424-371X (online)
Background material for decision
The publication was prepared by the Economics and Financial Stability Service of the Bank of Lithuania.
Unless otherwise indicated, the cut-off date for data used in the publication is 14 February 2019.
Periods indicated in charts include data for the respective year, quarter, etc.
Reproduction for educational and non-commercial purposes is permitted provided that the source is
acknowledged.
©Lietuvos bankas
Gedimino pr. 6, LT-01103 Vilnius, Lithuania
www.lb.lt
1DECISION BASIS FOR SETTING THE COUNTERCYCLICAL CAPITAL BUFFER RATE
On 26 March 2018, the Board of the Bank of Lithuania took a decision to leave the countercyclical capital
buffer (CCyB) rate unchanged at 1%, as set in June 2018. It will come into effect on 30 June 2019.
Such a decision was taken in view of the recent financial and economic trends, as well as core and additional
indicators for setting the CCyB rate. The credit and real estate (RE) market analysis points to no significant
imbalances in the financial system, yet the financial cycle in Lithuania is on an upswing. In periods of
moderate systemic risk, when credit and RE market activity is relatively high, the domestic economy is
expanding and corporate financial health is strong, the Bank of Lithuania seeks to ensure that banks
accumulate a 1% CCyB.
The portfolio of loans to the private non-financial sector has increased but remains stable. In 2018, its annual
growth rate stood at 6.0%, a year-on-year decrease of 0.2 percentage point. The slowdown was led by a
contraction in the corporate loan portfolio, reflecting amortisation of individual large-scale loans and the
reduced volume of micro-lending. The annual growth rate of the portfolio of loans to households, conversely,
has increased and reached 8.7% at the end of 2018. Lending continued to be driven by the improving
economic situation in the country as well as more positive business and household expectations. However,
after a long period, interest rates started to rise in 2018, while banks began gradually tightening lending
conditions. Nonetheless, the growth rate of the portfolio of loans to the private sector should not exceed the
projected nominal economic growth in 2019.
In Q4 2018, activity in the housing market remained at historic highs. According to the Centre of Registers, in
Q4 2018 4.5% more housing was assigned across Lithuania on a year-on-year basis, while the total number
of transactions in 2018 was 1.9% higher compared to the previous year. The annual growth rate of house
prices in Lithuania has slightly diminished and stood at 6.6% in Q3 2018. The annual growth rate of house
prices in Vilnius has increased by 0.3 percentage point to reach 3.5%, while in the remaining part of the
country it slowed down by 1.9 percentage points (to 9.1%).
With no significant imbalances, the level of cyclical systemic risk in the financial system remains average. The
1% CCyB rate set by the Bank of Lithuania is justified in terms of the current state of the domestic financial
system. The gap between the credit-to-GDP ratio and its long-term trend remains negative, the
loan-to-deposit ratio fluctuates around 100%, the current account balance is positive and house prices are not
overestimated in terms of income growth rates and other fundamental factors. Thus it might be stated that
the likelihood of a systemic crisis in Lithuania is low.
Resolution No 03-66 of the Board of the Bank of Lithuania of 26 March 2019 on the application of the countercyclical capital buffer.
The 0.5% CCyB rate came into effect on 31 December 2018, the 1% CCyB rate will come into effect on 30 June 2019.
2DEVELOPMENTS IN CREDIT AND REAL ESTATE MARKET
According to the Bank of Lithuania’s assessment, in Q4 2018 lending in Lithuania remained active,
yet its growth rate scaled down. This is also evidenced by the credit impulse, which was negative for
several consecutive months. In 2018, the portfolio of loans to the private non-financial sector increased by
6.0% (compared to 6.2% in 2017). The slowdown in the loan portfolio in Q4 2018 was primarily led by faster
loan repayments by major borrowers – manufacturing and trade enterprises – although this decline was
somewhat offset by increased lending to holding companies.1 The portfolio of loans to non-financial
corporations expanded by 3.2% in 2018, its weakest growth performance since the beginning of 2016.
Contrary to corporate lending, growth in the portfolio of loans to households has been robust for the last few
years, having reached 8.7% at the end of 2018.
Having fluctuated around 8% for the last several years, household lending gained momentum in
Q4 2018. Lending to households remains active. Such trends are underpinned by the more favourable
macroeconomic environment (i.e. rapidly increasing wages and diminishing unemployment), improving
household sentiment and interest rates that remain historically low (although gradually rising). In Q4 2018,
the annual growth rate of the housing loan portfolio has accelerated to reach 8.7% in December 2018
(a year-on-year increase of 0.7 percentage point). The net flow of new housing loans followed an upward
trajectory as well: in 2018 it amounted to €1.3 billion, an increase of 10.1% compared to 2017. At least for
now, such trends go hand in hand with fundamental factors: the ongoing tensions in the labour market
underpin the rise in employment rates and robust wage growth (9.5%2 over 2018). The improving financial
health of households is boosting consumer confidence. For the first time since March 2008, the consumer
confidence indicator turned positive in the second half of 2018. At the same time, an increasing share of
households acquired durable consumer goods (housing, cars); part of such purchases are usually financed
with borrowed funds. On the other hand, the number of factors that may prevent growth in the household
loan portfolio has risen as well. According to bank lending surveys, lending conditions are becoming somewhat
tighter, while interest rates for new housing loans increased in 2018.
Lending to non-financial corporations slumped in the last quarter of 2018. In 2018, the annual
growth rate of the portfolio of loans to non-financial corporations granted by monetary financial institutions
(MFIs) amounted to 3.2% (in 2017 – 4.9%), reaching its lowest point in the last three years. Such changes
were mainly driven by one-off factors – several large enterprises (e.g. manufacturing and trade enterprises,
holding companies) borrowed from banks or repaid previously granted loans. Lending to the smallest
enterprises (with up to 10 employees) declined, while the flow of micro-lending (loans for up to €0.25 million)
dropped by a third over the year. On the other hand, lending to small and medium-sized enterprises (with
10-249 employees) continued on an upward path and was the main contributor to the overall growth in the
portfolio of corporate loans. Despite the anticipated slowdown in Lithuania’s export growth3, demand for
corporate lending in 2019 should be fuelled by robust investment and increasing flows of EU funds.
It should be noted that demand for corporate lending has declined as some enterprises attracted
funds they lacked from abroad. Attracting funds from foreign holding companies or by issuing debt
securities abroad is becoming increasingly common. For instance, in 2005-2008 funds attracted from abroad
accounted for roughly a fifth of the total flow of financial liabilities of non-financial corporations, whereas in
2016-2018 the share of such funding increased to one-third.
In Q3 2018, the annual growth rate of house prices in Lithuania continued to moderate. However,
more recent RE market participant data suggests that the rise in apartment prices in major cities
gained momentum at the end of the year. According to the latest data of Statistics Lithuania, in Q3 2018
house prices in the country were up by 6.6% year on year (a quarter-on-quarter decrease of 0.8 percentage
1
The category of holding companies includes enterprises engaged in professional, scientific and technical activities (according to the statistical
classification of economic activities).
2
Bank of Lithuania projection for December 2018.
3
The slowdown in export growth in 2019 will be mainly led by the decline in re-exports.
3point from 7.4%). The ongoing robust rise in house prices was observed outside the country’s capital. In
Vilnius, house prices increased by 3.5%, in the remainder of the country – by 9.5%. According to the more
recent UAB Ober-Haus data on the apartment price index, at the end of 2018 growth in apartment prices in
Lithuania somewhat accelerated, compared to Q3 2018. In December 2018, apartment prices across Lithuania
were 3.9% higher on a year-on-year basis (the growth rate in Q3 stood at 3.2%). The most pronounced price
increases were recorded in smaller cities: the annual growth rate of apartment prices in Šiauliai and
Panevėžys stood at 8.9% and 11.6% respectively. The annual increase in apartment prices in Vilnius, Kaunas
and Klaipėda was 2.8%, 4.1% and 3.5% respectively.
Housing market activity in 2018 was the strongest since 2007 (in terms of number of residents –
since 2004). According to the Centre of Registers, in 2018, 45.1 thousand housing units were sold across the
country – a year-on-year increase of 1.9%. The number of such transactions reached 16.1 per thousand
residents (the highest number in 15 years). In Q4 2018, the number of apartment and house transactions in
the country reached 11.9 thousand, a year-on-year increase of 4.5%. Regarding housing market activity,
there are still significant regional differences: the rise in the number of transactions during the
abovementioned period was mainly driven by stronger housing market activity in Vilnius and Kaunas, where it
picked up by 9.4% and 9.5% respectively. Over the quarter, housing market activity in Klaipėda and the rest
of the country showed a moderate change (an increase of 3.6% and 1.2% respectively). Activity in Vilnius
primary apartment market remained relatively high in Q4 2018. According to UAB Eika, in the last three
months of 2018, the number of new-build apartments sold and reserved by RE developers grew by a fourth
(23.1%) year on year and almost by a tenth (8.3%) compared to the average number per quarter in
2016-2018.
The supply of new-build housing in Lithuania has not changed significantly over the quarter and
remained at historic highs. According to the data of Q3 2018, the annual number of apartments built in
Lithuania remained almost unchanged on a year-on-year basis (12.4 thousand). During the year, the housing
supply has increased the most in Kaunas and Vilnius regions (cities and their districts), while the number of
new-build apartments in the rest of the country has decreased by a fifth. The share of private houses built in
Lithuania remained higher compared to apartments in multi-apartment buildings, although the number of
apartments built during the reporting period grew more rapidly. On the other hand, the number of
construction permits issued in 2018 has significantly decreased (-8.0%). Although in Vilnius and Klaipėda
regions the number of construction permits issued rose by 7.4% and 4.4% respectively, it has dropped by
41.5% in Kaunas region.
Expectations regarding the rise in prices of new-build housing have strengthened, whereas no
significant changes in prices of old-construction apartments are expected to take place in 2019.
According to the Bank Lending Survey conducted by the Bank of Lithuania in Q4 2018, the majority of
respondents (63%) expected prices of new-build apartments to rise by up to 5% over the next 12 months.
With regard to old-construction apartments, the majority of banks (63%) expected them to remain
unchanged over the year. Compared to the Bank Lending Survey conducted in Q3 2018, the share of banks
anticipating a rise in prices of new-build apartments increased by 19 percentage points.
The negative credit-to-GDP gap slightly reduced in Q3 2018, while most indicators that are used to
assess the build-up of financial system imbalances did not signal excess risk. In Q3 2018, the overall
annual credit (including non-banking credit) growth stood at 10.2%, while nominal GDP expanded by 7.1%.4
However, the quarterly credit growth rate was lower compared to the quarterly GDP growth rate, leading to a
0.6 percentage point decline in the credit-to-GDP ratio in Q3 2018 (to 66.8%). At the same time, the negative
gap between the credit-to-GDP ratio and its long-term trend slightly increased and, subject to the method of
assessment, fluctuated between -9.6 and -2.8 percentage points at the end of Q3 2018. Other indicators also
suggest that there are no significant imbalances in the financial system and that the level of cyclical systemic
risk is sustainable. For instance, at the end of Q3 2018, the MFI loan-to-deposit ratio continued to fluctuate at
4
Expressed as the last four-quarter moving sum.
4100%, the current account balance improved over the quarter, while the gap between the
house price-to-income ratio and its long-term trend remained negative. Given that trends in RE and credit
markets in Q3 2018 remained largely unchanged, the CCyB rate was left at 1.0%.
5ANNEX 1. CREDIT AND HOUSING MARKET TRENDS
Chart 1. Annual growth of the portfolio of loans Chart 2. Flow of new loans to households
to non-financial corporations and households
(January 2010–December 2018) (January 2004–January 2019)
Percentages EUR millions
15 500
450
10
400
350
5
300
0 250
200
-5
150
100
-10
50
-15 0
2010 2011 2012 2013 2014 2015 2016 2017 2018 2005 2007 2009 2011 2013 2015 2017 2019
Non-financial corporations New loans for consumption and other purposes
Households New housing loans
Source: Bank of Lithuania. Source: Bank of Lithuania.
Chart 3. Flows of financial liabilities of non-financial Chart 4. Annual change in the portfolio of MFI
corporations (4-quarter moving sum) loans to non-financial corporations by economic
activity
(Q1 2005–Q3 2018) (2017-2018)
EUR billions EUR millions
12
Transportation and storage
Professional activities
8 Trade
Real estate activities
Administrative activities
4
Manufacturing
Accommodation and catering
0
Agriculture
Water supply
-4 Mining
Construction
Information and communication
-8
2005 2007 2009 2011 2013 2015 2017 Other activities
Energy supply
National economy: financial sector -327
National economy: other -100 0 100 200
Rest of the world 2018 2017
Source: Bank of Lithuania. Source: Bank of Lithuania.
6Chart 5. Flow of new corporate loans by loan size Chart 6. Share of consumers intending to take
(12-month moving sum) a certain action within the year
(January 2011–January 2019) (January 2004–January 2019)
EUR billions Percentages
5
25
4
20
3 15
2 10
1 5
0
2011 2012 2013 2014 2015 2016 2017 2018 2019 2004 2006 2008 2010 2012 2014 2016 2018
< €0.25 million Intend to buy a car
€0.25 million–€1 million Intend to buy/build a housing
Intend to upgrade a housing
> €1 million
Sources: Statistics Lithuania and Bank of Lithuania
Source: Bank of Lithuania. calculations.
Chart 7. Annual change in the number of housing Chart 8. Annual growth in house prices according
transactions and the house price index to different sources
(Q1 2010–Q4 2018) (Q1 2007–Q2 2018)
Percentages Percentages Percentages
50 25 50
40 20 40
30 15 30
20 10 20
10 5 10
0 0 0
-10 -5 -10
-20 -10 -20
-30 -15 -30
-40 -20 -40
2010 2011 2012 2013 2014 2015 2016 2017 2018 2007 2009 2011 2013 2015 2017
Housing tranactions Estimates range
HPI (right-hand scale) Median
Sources: Centre of Registers and Statistics Lithuania. Sources: Centre of Registers, Statistics Lithuania,
UAB Ober-Haus, Aruodas.lt.
7Chart 9. Number of new-build housing transactions Chart 10. Liquidity within Vilnius new-build
and completed housing units apartment market
(Q1 2008–Q3 2018) (Q1 2009–Q4 2018)
Housing, thousands Duration, months
9 35
8 30
7 25
6 20
15
5
10
4
5
3
0
2 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
1 Liquidity ratio of new-build apartments in Vilnius
0 2009-2018 average of the liquidity ratio of new-
2008 2010 2012 2014 2016 2018 build apartments in Vilnius
New-build housing transactions (4-quarter sum) Sources: UAB Eika and Bank of Lithuania calculations.
Completed housing units (4-quarter sum) Note: The liquidity ratio indicates how much time it would take
for developers to sell the apartments offered if demand remained
Sources: Centre of Registers and Statistics Lithuania. the same and no more apartments were built.
Chart 11. Gap between investment in housing and Chart 12. Completed housing units per year
other buildings (compared to GDP) and the long-term (4-quarter moving sum)
average
(Q1 2000–Q2 2018) (Q1 2001–Q2 2018)
Percentages Units
6 10,000
9,000
4 8,000
7,000
2 6,000
5,000
0 4,000
3,000
-2 2,000
1,000
-4 0
2000 2003 2006 2009 2012 2015 2018 2007 2009 2011 2013 2015 2017
Gap between the GDP share of investment in housing Number of housing units built in 1-2 apartment
and the long-term average buildings
Gap between the GDP share of investment in other Number of housing units built in multi-apartment
buildings and the long-term average buildings
Source: Statistics Lithuania.
Source: Statistics Lithuania.
8ANNEX 2. CREDIT AND HOUSING MARKET IMBALANCES
Chart A. Evaluation of credit market imbalances based Chart B. Core indicator I: Credit to the private
on core and additional indicators non-financial sector-to-GDP ratio gap
(calculated using the standardised Basel method)
(Q1 2019) (Q1 2001–Q3 2018)
Percentages Percentage points
Credit-to-GDP ratio gap 100 60
(Basel method)
80 45
Credit-to-GDP ratio gap 60 30
Current account deficit (forecast-augmented
method)
40 15
20 0
MFI loan-to-GDP ratio 0 -15
MFI loan-to-deposit
gap (forecast-
ratio
augmented method)
-20 -30
2001 2003 2005 2007 2009 2011 2013 2015 2017
House price-to-income
ratio gap (forecast- Crisis period
augmented method)
Credit-to-GDP gap (right-hand scale)
Large imbalances accrued
Emerging imbalances Credit-to-GDP ratio
Sustainable environment Long term trend of the credit-to-GDP ratio
Assessment in Q1 2018
Assessment in Q1 2019 Average ratio from Q4 1995
Sources: Statistics Lithuania and Bank of Lithuania calculations. Sources: Statistics Lithuania and Bank of Lithuania calculations.
Note: Axes are scaled according to the range of a particular Note: The long-term trend is computed using a one-sided
indicator: from its minimal value up to the maximal value. HP filter with a smoothing parameter of 400,000.
Chart C. Core indicator II: Credit to the private Chart D. Additional indicator I: MFI loan to the
non-financial sector-to-GDP ratio gap private non-financial sector-to-GDP ratio gap
(calculated using the forecast-augmented method) (calculated using the forecast-augmented method)
(Q1 2001–Q3 2018) (Q1 2001–Q4 2018)
Percentages Percentage points Percentages Percentage points
100 40 80 40
80 30 60 30
60 20 40 20
40 10 20 10
20 0 0 0
0 -10 -20 -10
2001 2003 2005 2007 2009 2011 2013 2015 2017 2001 2003 2005 2007 2009 2011 2013 2015 2017
Crisis period Crisis period
Credit-to-GDP ratio gap (right-hand scale) MFI loan-to-GDP ratio gap (right-hand scale)
Credit-to-GDP ratio MFI loan-to-GDP ratio
Long-term trend of the credit-to-GDP ratio Long-term trend of the MFI loan-to-GDP ratio
Average ratio from Q4 1995 Average ratio from Q4 1995
Sources: Statistics Lithuania and Bank of Lithuania calculations. Sources:Statistics Lithuania and Bank of Lithuania calculations.
Note: The long-term trend is computed by applying a one-sided Note: The long-term trend is computed by applying a one-sided
HP filter with a smoothing parameter of 400,000; before HP filter with a smoothing parameter of 400,000; before
applying the filter, the ratio is modelled for the next 5-year applying the filter, the ratio is modelled for the next 5-year
window using a 4-quarter weighted average. window using a 4-quarter weighted average.
9Chart E. Additional indicator II: House price-to-income Chart F. Additional indicator III: Ratio between MFI
ratio gap loans to the private sector and private sector
(calculated using the forecast-augmented method) deposits (adjusted for seasonal effects)
(Q1 2001–Q3 2018) (Q1 1999–Q3 2018)
2010 = 100 Index points Percentages
160 60 250
140 50
200
120 40
100 30 150
80 20
60 10 100
40 0
50
20 -10
0 -20 0
2001 2003 2005 2007 2009 2011 2013 2015 2017 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Crisis period
Crisis period
House price-to-income gap (right-hand scale)
MFI loan-to-deposit ratio
House price-to-income ratio Average ratio from Q4 1993 until the current period
Long-term trend (with forecast) Long-term average +/-2 standard deviations
Average ratio from Q4 1998
Source: Bank of Lithuania calculations.
Sources: Statistics Lithuania and Bank of Lithuania calculations.
Note: The ratio develops in a balanced way if it does not
Notes: 1) income – household wages and salaries; 2) the long-
deviate from its long-term average by more than two standard
term trend is estimated by applying a one-sided HP filter with a
deviations. Standard deviation is computed on the basis of data
smoothing parameter of 400,000; before applying the filter, the
covering the period of moderate changes in the ratio, excluding
ratio is modelled for the next 5-year window using a 4-quarter
data for Q2 2006-Q4 2011.
weighted average.
Chart G. Additional indicator IV: Ratio between Chart H. Contributions to Lithuania’s financial cycle
the current account balance (4-quarter moving sums) index
and GDP
(Q1 1997–Q3 2018) (Q1 2001–Q2 2018)
Percentages of GDP, 4-quarter moving sums P Index
6 0.8
3 0.7
0.6
0
0.5
-3
0.4
-6
0.3
-9
0.2
-12
0.1
-15 0.0
-18 -0.1
1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 2001 2003 2005 2007 2009 2011 2013 2015 2017
Current account balance New household loan-to-GDP ratio
Average from Q4 1995 until the current period New loan to non-financial corporations-to-GDP ratio
House price-to-income ratio
Sources: Statistics Lithuania and Bank of Lithuania calculations.
Other
Note: different colours indicate different levels of risk which have
Index average (Q1 2001-Q2 2018)
been set based on Reinhart S. M. and V. R. Reinhart (2008):
Financial cycle index
"Capital flow bonanzas: An encompassing of the past and present",
NBER working paper, 14321. Sources: Statistics Lithuania and Bank of Lithuania calculations.
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